[{"content":"","date":"29 March 2026","externalUrl":null,"permalink":"/","section":"","summary":"","title":"","type":"page"},{"content":"\rAvailable on Substack\n21 March is International Day against Racial Discrimination, so it’s perfectly on theme that we talk about race, albeit a little late. Race is something that appears simple at first but is actually quite complex. Most scientists agree that race is entirely social, but what does it mean to be a social construct? It also infringes on the common assumption that race has a genetic component. If genes determine your skin colour, shouldn’t it determine your race?\nHere’s the thing: two people from the same race don’t necessarily have more genes in common than people from different races. [1] Race is not shared genetically, it is shared culturally. While a black person can share a language, music and ceremonies with other black people, they can realistically have more in common genetically with a white person than another black person.\nThis strange scientific discovery was first discovered by American biologist Richard Lewontin in his paper The Apportionment of Human Diversity, [2] in which he studied genetic markers from seven distinct ‘races’ and noticed this palpable observation.\nHis work was later criticised (ineffectively) by A W F Edwards, thus birthing “Lewinton’s fallacy”, an argument heavily utilized by white supremacists [3] . During the 1970s, genetic technology was not as advanced as it is currently; it wasn’t possible at the time to sequence the entire human genome. It was much more prevalent to observe different phenotypes (like skin colour) and assume that stronger differences in phenotype equates to stronger differences in genes. Reality, however, is rarely as simple.\nWhile skin colour is readily observable, other genetic differences don’t appear easily to the human eye. For example, it is difficult to observe, from a cursory view, whether a person possesses genes that make them lactose intolerant. It could be assumed that a White man doesn’t, but such assumption should not be construed as truth. Lactose tolerant Black people exist, and so do White lactose intolerant people. You can observe what a person looks like, but someone’s exact genes are never guesswork.\nAn assumption could be made in which two people of different races are tolerant to lactose. However, it cannot be said with certainty that the genes governing their tolerance to lactose are exactly the same. Genes govern biochemical processes in the body which can become very complex. They could have mutations in completely different locations in the lactase gene, or a separate gene altogether that has a contribution in the pathway. [4] While genetic differences could cause differences in phenotype, genetic differences could also make similarities in phenotype.\nThis phenomenon is called convergent evolution, in which a population evolves to become phenotypically similar to another population simply because their environment calls for it. An East African population has independently evolved lactase persistence due to herding cattle [5] , a hundred miles away from the European population. Thus, alt-right claims about milk digestion being an exclusively European trait is dishonest. [6,7] While geographically separated, African and European ancestries evolved to have similar phenotypes (i.e. milk digestion) [8] and this is not an isolated case. Arabic ancestries also evolved separately to be lactose tolerant. [9]\nConvergent evolution does not always lead to similar gene sequences. Merely, the product of those genes are similar. Recall the complexity of biochemical processes: mutations in vastly different locations in the genome could lead to a few similarities in phenotype. [10] It is genetic convergence that refers to convergent evolution that does lead to similar genetic sequences. While lactose tolerance is not an example of genetic convergence, a vast majority of human traits do show genetic convergence. [11] For example, the genes for cholesterol appear to evolve similarly in all human populations around the globe. The strongest reason behind this is the adoption of farming, which acts as a selection pressure. [12]\nThe impact of farming to human genetics is huge: humans are evolving to become more similar. Even chimpanzees, which to our human eye look similar to each other, actually have more genetic diversity than humans. This was proven true in 2003; after the conclusion of the Human Genome Project (HGP). It found that 99.9% of the human genome is the same in all populations and that any differences per individual could be attributed to a mere 0.1% of the human genome. [13,14] This same study also affirmed Lewinton’ theory that there were more differences within a group than outside of it.\nA clinal population model\r#\rThe human species follows a clinal distribution of genes. [15]\nClinal or cline may appear to be an unfamiliar word in isolation, but can be understood as a gradient distribution. Gradients typically describe the shape of a graph and indicate whether the shape is an incline or a decline. An example of gradient distribution is skin colour, which is clinally distributed: the greater the UV light penetration, the greater the skin colour. While both Southeast Asian, South Asians and East Asians are categorically under the Asian umbrella of race in Western countries, they have many variations in skin color depending on the UV penetration of the region they originate. Hence, populations become a more accurate terminology to use in genetic studies, as opposed to race.\nGlobal skin colour distribution of native populations. The colours on the map are based on the 36-tone chromatic scale devised by Austrian anthropologist Felix von Luschan to assess the unexposed skin of human populations. The higher numbers represent darker skin colour. Original data compiled by Biasutti 1941s. doi:10.1371/journal.pone.0022103.g002\nAs time goes on, any organism with DNA will slowly accumulate mutations. Mutations are defined as random changes in the sequence of DNA. Mutations have a random chance of occurring, and paired with the knowledge that human genome exists in clinal variation, it could be safe to assume a probabilistic view. What is the possibility of two randomly sampled humans with no familial relation to have similar gene variants? Now, what about the possibility of two randomly sampled humans with no familial relation to have similar gene variants and be members of the same population?\nTo tackle this probabilistic problem, let us first define an allele. An allele is a gene variant, which we will denote as A.\nAn allele has a certain frequency within a population, which we define as p. p can also be defined as the probability of inheriting allele A. The probability of inheriting a different allele, or not inheriting this allele is 1-p, which we define as q. We will call this other allele a (lowercase). Let’s assume the value of p and q are both 0.5.\nLet’s put this all into a table for easier viewing. Remember, p and q remain constant as both are sampled from the same population.\n\\(p\\) 0.5 \\(q\\) 0.5 Since a person has two copies of genes, they have three possible genotypes: AA, Aa, aa.\nThe probabilities of each genotype is calculated below:\nAA \\(p^2\\) 0.25 Aa \\(2pq\\) 0.50 aa \\(q^2\\) 0.25 Hence, let’s calculate the probability that two random individuals from the same population have the same genotype.\nAA Aa aa AA 0.0625 0.125 0.0625 Aa 0.125 0.25 0.125 aa 0.0625 0.125 0.0625 Which adds up to 0.0625 + 0.25 + 0.0625 = 37.5%. There is a 37.5% chance two individuals from the same population share the same genotype, and a 62.5% chance two individuals do not share a genotype.\nOut-of-Africa Theory\r#\rWhen participating in a commercial DNA test, they will mention your ancestry as part of the results. This doesn’t mean they have a model human genome that represents a specific population. Rather, they identify alleles in your genome and attribute it to being alleles common to a specific population. The key word here is common: while alleles for blue eyes are common in Northern Europeans, it is not exclusive to it, and does not represent all Northern Europeans. Alleles can be common in certain populations but cannot represent those populations.\nAll ancestries descend from Africa. [16-18] It is hypothesized that the first humans came from Africa, and migrated to other parts of the globe, forming all varieties of populations. At least two major expansions of human populations occurred. [19] Not only is it a mistake to assume the premodern world had isolated civilisations that developed independently with genetic proof of migration; interbreeding between populations occurred during and after migration events. A Tibetan population could interbreed with the Han Chinese population, introducing new alleles into the gene pool. Once this allele is introduced, it spreads within the population, thus forming the clinal distribution.\nBy Saioa López, Lucy van Dorp and Garrett Hellenthal - López, S., van Dorp, L., \u0026amp; Hellenthal, G. (2015). Human Dispersal Out of Africa: A Lasting Debate. Evolutionary Bioinformatics Online, 11(Suppl 2), 57–68. http://doi.org/10.4137/EBO.S33489 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4844272/, CC BY 3.0\nOlder lineages tend to accumulate more mutations. As time advances into tens of thousand years, DNA makes more and more random changes to be passed down to offspring. The African lineage, being the eldest, will thus accumulate the most mutations compared to other lineages, and thus two people of African ancestry will have less in common than two people of European ancestry. In fact, it is entirely possible for a person of African ancestry to have more in common with a person of European ancestry than another person of African ancestry. This is because the European lineage descended from the African lineage, and thus is younger and has less time to accumulate mutations.\nRace as shared culture\r#\rRace does not work as a biological concept; it is a categorical social construct. It is the shared culture that makes race, not genetics. In fact, a study in the US reported that many self-reported racial identities do not match genetic ancestry. [20,21] The study found that there was a gradient of ancestral proportions within a race category, affected by the transatlantic slave trade, colonisation, and migration.\nHistorically, race was coined during European eras of exploration (now commonly referred to as colonisation) in which colonists identified different skin colours and speculated in differences of culture. In 1775, Blumenbach described 4 major races: Caucasian, Mongolian, Ethiopian and American. [22] Modern views have adapted Blumenbach’s classification into White, Asian, Black and Native/Indigenous.\nRace was a construct used to justify exploitation such as slavery. [23] Modern views such as critical race theory posits that race is a construct to justify racism and is facilitated by the legal system to maintain inequality. [24] While systemic racism is beyond the scope of this article, it remains justified to consider race as a social construct and not a biological one, and that any that state otherwise is ignoring a decade of genomic analysis and population studies.\nReferences\rDuello TM, Rivedal S, Wickland C, Weller A. Race and genetics versus “race” in genetics: A systematic review of the use of African ancestry in genetic studies. Evol Med Public Health. 2021 Jun 15;9(1):232–45. Lewontin RC. The Apportionment of Human Diversity. Evolutionary Biology. 1972;381–98. Edwards AWF. Human genetic diversity: Lewontin’s fallacy. BioEssays. 2003 Aug 1;25(8):798–801. Sackton TB, Clark N. Convergent evolution in the genomics era: new insights and directions. Philos Trans R Soc Lond B Biol Sci. 2019 Jun 3;374(1777):20190102. Swaminathan N. African Adaptation to Digesting Milk Is “Strongest Signal of Selection Ever” [Internet]. Scientific American. 2006 [cited 2026 Mar 30]. Available from: https://www.scientificamerican.com/article/african-adaptation-to-dig/ Moerking E. Milk Parties and Soyjaks: Understanding The Alt-Right’s Metapolitical Appropriation of Milk [Internet]. GNET. 2023 [cited 2026 Mar 30]. Available from: https://gnet-research.org/2023/09/27/milk-parties-and-soyjaks-understanding-the-alt-rights-metapolitical-appropriation-of-milk/ Gambert I, Linné T. How the alt-right uses milk to promote white supremacy [Internet]. 2018 [cited 2026 Mar 30]. Available from: https://theconversation.com/how-the-alt-right-uses-milk-to-promote-white-supremacy-94854 Tishkoff SA, Reed FA, Ranciaro A, Voight BF, Babbitt CC, Silverman JS, et al. Convergent adaptation of human lactase persistence in Africa and Europe. Nature genetics. 2006 Dec 10;39(1):31. Priehodová E, Abdelsawy A, Heyer E, Cerný V. Lactase persistence variants in Arabia and in the African Arabs. Human biology [Internet]. 2014 [cited 2026 Mar 30];86(1). Available from: https://pubmed.ncbi.nlm.nih.gov/25401983/ Fraser BA, Whiting JR. What can be learned by scanning the genome for molecular convergence in wild populations? Annals of the New York Academy of Sciences. 2019 Jun 26;1476(1):23. Wright SN, Yang J, Ideker T. Common and rare genetic variants show network convergence for a majority of human traits [Internet]. medRxiv : the preprint server for health sciences. 2025 [cited 2026 Mar 30]. Available from: https://pubmed.ncbi.nlm.nih.gov/40666368/ Le Page M. Human populations evolved in similar ways after we began farming [Internet]. New Scientist. 2026 [cited 2026 Mar 30]. Available from: https://www.newscientist.com/article/2518181-human-populations-evolved-in-similar-ways-after-we-began-farming/ Human Genome Project [Internet]. Genome.gov. [cited 2026 Mar 30]. Available from: https://www.genome.gov/about-genomics/educational-resources/fact-sheets/human-genome-project Collins FS, Fink L. The Human Genome Project. Alcohol Health and Research World. 1995;19(3):190. Going the distance: human population genetics in a clinal world. Trends in Genetics. 2007 Sep 1;23(9):432–9. Groucutt HS, Petraglia MD, Bailey G, Scerri EML, Parton A, Clark-Balzan L, et al. Rethinking the dispersal of Homo sapiens out of Africa. Evol Anthropol. 2015 Jul-Aug;24(4):149–64. Nei M. Genetic support for the out-of-Africa theory of human evolution. Proceedings of the National Academy of Sciences. 1995 Jul 18;92(15):6720–2. Mahapatra A, Mukherjee J. Human origin and migration deciphered from a novel genomic footprints of mitochondrial sequences [Internet]. bioRxiv. 2020 [cited 2026 Mar 30]. p. 848341. Available from: https://www.biorxiv.org/content/10.1101/848341v3.abstract Templeton A. Out of Africa again and again. Nature. 2002 Mar;416(6876):45–51. Mahase E. People’s racial and ethnic identities don’t reflect their genetic ancestry [Internet]. Live Science. 2025 [cited 2026 Mar 30]. Available from: https://www.livescience.com/health/genetics/peoples-racial-and-ethnic-identities-dont-reflect-their-genetic-ancestry Ortega RP. Race, ethnicity don’t match genetic ancestry, according to a large U.S. study [Internet]. [cited 2026 Mar 30]. Available from: https://www.science.org/content/article/race-ethnicity-don-t-match-genetic-ancestry-according-large-u-s-study 1752- BJF, Bendyshe T, Marx, K. F. H. (Karl Friedrich Heinrich), 1796-, (Pierre) 1794- FP, 1805- WR, d. HJ. The anthropological treatises of Johann Friedrich Blumenbach .. : Blumenbach, Johann Friedrich, 1752-1840 : Free Download, Borrow, and Streaming : [Internet]. Internet Archive. [cited 2026 Mar 30]. Available from: https://archive.org/details/anthropologicalt00blum Smedley A. Race in North America : origin and evolution of a worldview : Smedley, Audrey : Free Download, Borrow, and Streaming : [Internet]. Internet Archive. [cited 2026 Mar 30]. Available from: https://archive.org/details/raceinnorthameri00smed Website [Internet]. Available from: https://www.americanbar.org/groups/crsj/resources/human-rights/archive/lesson-critical-race-theory/ ","date":"29 March 2026","externalUrl":null,"permalink":"/articles/20260329/","section":"Articles","summary":"Race is a social construct, not a biological one, but why? I explore the biological reasonings behind abandoning the concept of race as biology.","title":"A genetics perspective on race","type":"articles"},{"content":"","date":"29 March 2026","externalUrl":null,"permalink":"/tags/anthropology/","section":"Tags","summary":"","title":"Anthropology","type":"tags"},{"content":"","date":"29 March 2026","externalUrl":null,"permalink":"/articles/","section":"Articles","summary":"","title":"Articles","type":"articles"},{"content":"","date":"29 March 2026","externalUrl":null,"permalink":"/tags/biology/","section":"Tags","summary":"","title":"Biology","type":"tags"},{"content":"","date":"29 March 2026","externalUrl":null,"permalink":"/tags/politics/","section":"Tags","summary":"","title":"Politics","type":"tags"},{"content":"","date":"29 March 2026","externalUrl":null,"permalink":"/tags/race/","section":"Tags","summary":"","title":"Race","type":"tags"},{"content":"","date":"29 March 2026","externalUrl":null,"permalink":"/tags/references-cited/","section":"Tags","summary":"","title":"References Cited","type":"tags"},{"content":"","date":"29 March 2026","externalUrl":null,"permalink":"/tags/science/","section":"Tags","summary":"","title":"Science","type":"tags"},{"content":"","date":"29 March 2026","externalUrl":null,"permalink":"/tags/","section":"Tags","summary":"","title":"Tags","type":"tags"},{"content":"","date":"28 March 2026","externalUrl":null,"permalink":"/tags/data/","section":"Tags","summary":"","title":"Data","type":"tags"},{"content":"","date":"28 March 2026","externalUrl":null,"permalink":"/tags/machine-learning/","section":"Tags","summary":"","title":"Machine Learning","type":"tags"},{"content":"","date":"28 March 2026","externalUrl":null,"permalink":"/tags/programming/","section":"Tags","summary":"","title":"Programming","type":"tags"},{"content":"TL;DR: The app works great.\nRecently, I obtained a dataset with 5110 rows containing health data of anonymised patients. This was a good opportunity to use this data to train some models to be able to predict stroke from health data. I happen to know some R and the caret package happens to be perfect for this.\nI\u0026rsquo;ll detail down below how I managed to train models and how these models can predict stroke. I\u0026rsquo;ve uploaded the files onto my Github and deployed the app using Shiny. It\u0026rsquo;s a bit wonky right now, but that\u0026rsquo;s the result of avoiding any AI use to write my code.\nHow it went\r#\rAs someone with no formal education in data science, computer science and the like, I taught myself how to code starting from HTML to code in internet forums in the early 2000s. I progressed since then, and learned R during university to process data. This was a challenge for me because I have never done machine learning before, and I wanted to particularly challenge myself with absolutely no AI use.\nLuckily, there were old StackOverflow posts from before the AI era and there were useful blog posts online that helped me. One of the most useful resources I found was a post from University of Virginia that taught me about multiple imputations. Originally, I thought of replacing missing values with averages, but I learned that there was a package called mice that could do calculations and impute missing data for me. It was amazing how many packages are out there and how useful they were.\nI really had to thank my friends who, despite them not understanding what I was doing, really tried to help me. I had friends with backgrounds in computer science who had zero experience in R reading .txt files I sent them to find errors. They also told me nobody uses R in 2026. I wonder if it\u0026rsquo;s true\u0026hellip;it\u0026rsquo;s difficult for me to abandon R (despite knowing Python) because R was the first programming language I learnt.\nI really value community so much, it upsets me people abandon good connections to speak with AI. Despite struggling, I really appreciate how much Bima and Kelvin tried helping me through Discord calls. It made me think about how people who rely completely to AI could have an entire learning journey without fostering any connections.\nNot relying on AI was a challenge that made me more serious about exploring for resources. I had to interpret some of the resources I found and practiced my literacy.\nHow I did it\r#\rSetup\r#\rLoad libraries: tidyverse to clean the data, caret for machine learning models, and mice for multiple imputation of missing values in the data. Note that some machine learning models will need additional package installs, but let\u0026rsquo;s proceed with these for now.\nlibrary(tidyverse)\r## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──\r## ✔ dplyr 1.1.4 ✔ readr 2.1.5\r## ✔ forcats 1.0.0 ✔ stringr 1.5.1\r## ✔ ggplot2 4.0.2 ✔ tibble 3.2.1\r## ✔ lubridate 1.9.4 ✔ tidyr 1.3.1\r## ✔ purrr 1.2.1 ## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──\r## ✖ dplyr::filter() masks stats::filter()\r## ✖ dplyr::lag() masks stats::lag()\r## ℹ Use the conflicted package (\u0026lt;http://conflicted.r-lib.org/\u0026gt;) to force all conflicts to become errors\rlibrary(mice)\r## ## Attaching package: 'mice'\r## ## The following object is masked from 'package:stats':\r## ## filter\r## ## The following objects are masked from 'package:base':\r## ## cbind, rbind\rlibrary(caret)\r## Loading required package: lattice\r## ## Attaching package: 'caret'\r## ## The following object is masked from 'package:purrr':\r## ## lift\rAfter downloading the data, it\u0026rsquo;s important to take a look at it to have a feel about it.\nfile = \u0026quot;D://R Files//healthcare-dataset-stroke-data.csv\u0026quot;\rdataset_raw = read.csv(file = file, na.strings=\u0026quot;N/A\u0026quot;)\rhead(dataset_raw)\r## id gender age hypertension heart_disease ever_married work_type\r## 1 9046 Male 67 0 1 Yes Private\r## 2 51676 Female 61 0 0 Yes Self-employed\r## 3 31112 Male 80 0 1 Yes Private\r## 4 60182 Female 49 0 0 Yes Private\r## 5 1665 Female 79 1 0 Yes Self-employed\r## 6 56669 Male 81 0 0 Yes Private\r## Residence_type avg_glucose_level bmi smoking_status stroke\r## 1 Urban 228.69 36.6 formerly smoked 1\r## 2 Rural 202.21 NA never smoked 1\r## 3 Rural 105.92 32.5 never smoked 1\r## 4 Urban 171.23 34.4 smokes 1\r## 5 Rural 174.12 24.0 never smoked 1\r## 6 Urban 186.21 29.0 formerly smoked 1\rsummary(dataset_raw)\r## id gender age hypertension ## Min. : 67 Length:5110 Min. : 0.08 Min. :0.00000 ## 1st Qu.:17741 Class :character 1st Qu.:25.00 1st Qu.:0.00000 ## Median :36932 Mode :character Median :45.00 Median :0.00000 ## Mean :36518 Mean :43.23 Mean :0.09746 ## 3rd Qu.:54682 3rd Qu.:61.00 3rd Qu.:0.00000 ## Max. :72940 Max. :82.00 Max. :1.00000 ## ## heart_disease ever_married work_type Residence_type ## Min. :0.00000 Length:5110 Length:5110 Length:5110 ## 1st Qu.:0.00000 Class :character Class :character Class :character ## Median :0.00000 Mode :character Mode :character Mode :character ## Mean :0.05401 ## 3rd Qu.:0.00000 ## Max. :1.00000 ## ## avg_glucose_level bmi smoking_status stroke ## Min. : 55.12 Min. :10.30 Length:5110 Min. :0.00000 ## 1st Qu.: 77.25 1st Qu.:23.50 Class :character 1st Qu.:0.00000 ## Median : 91.89 Median :28.10 Mode :character Median :0.00000 ## Mean :106.15 Mean :28.89 Mean :0.04873 ## 3rd Qu.:114.09 3rd Qu.:33.10 3rd Qu.:0.00000 ## Max. :271.74 Max. :97.60 Max. :1.00000 ## NA's :201\rCleaning and tidying up the data.\r#\rEnsure that the data has the correct data type.\ndataset \u0026lt;- transform(dataset_raw, bmi = as.numeric(bmi), hypertension = as.logical(hypertension), heart_disease = as.logical(heart_disease),\rgender = as.factor(gender),\rwork_type = as.factor(work_type),\rResidence_type = as.factor(Residence_type),\rever_married = as.factor(ever_married),\rstroke = as.factor(stroke),\rsmoking_status = as.factor(smoking_status)\r)\rdataset \u0026lt;- dataset %\u0026gt;%\rmutate(ever_married = if_else(ever_married == \u0026quot;Yes\u0026quot;, TRUE, if_else(ever_married==\u0026quot;No\u0026quot;, FALSE, FALSE)))\rLet\u0026rsquo;s check:\nsummary(dataset)\r## id gender age hypertension heart_disease ## Min. : 67 Female:2994 Min. : 0.08 Mode :logical Mode :logical ## 1st Qu.:17741 Male :2115 1st Qu.:25.00 FALSE:4612 FALSE:4834 ## Median :36932 Other : 1 Median :45.00 TRUE :498 TRUE :276 ## Mean :36518 Mean :43.23 ## 3rd Qu.:54682 3rd Qu.:61.00 ## Max. :72940 Max. :82.00 ## ## ever_married work_type Residence_type avg_glucose_level\r## Mode :logical children : 687 Rural:2514 Min. : 55.12 ## FALSE:1757 Govt_job : 657 Urban:2596 1st Qu.: 77.25 ## TRUE :3353 Never_worked : 22 Median : 91.89 ## Private :2925 Mean :106.15 ## Self-employed: 819 3rd Qu.:114.09 ## Max. :271.74 ## ## bmi smoking_status stroke ## Min. :10.30 formerly smoked: 885 0:4861 ## 1st Qu.:23.50 never smoked :1892 1: 249 ## Median :28.10 smokes : 789 ## Mean :28.89 Unknown :1544 ## 3rd Qu.:33.10 ## Max. :97.60 ## NA's :201\rhead(dataset)\r## id gender age hypertension heart_disease ever_married work_type\r## 1 9046 Male 67 FALSE TRUE TRUE Private\r## 2 51676 Female 61 FALSE FALSE TRUE Self-employed\r## 3 31112 Male 80 FALSE TRUE TRUE Private\r## 4 60182 Female 49 FALSE FALSE TRUE Private\r## 5 1665 Female 79 TRUE FALSE TRUE Self-employed\r## 6 56669 Male 81 FALSE FALSE TRUE Private\r## Residence_type avg_glucose_level bmi smoking_status stroke\r## 1 Urban 228.69 36.6 formerly smoked 1\r## 2 Rural 202.21 NA never smoked 1\r## 3 Rural 105.92 32.5 never smoked 1\r## 4 Urban 171.23 34.4 smokes 1\r## 5 Rural 174.12 24.0 never smoked 1\r## 6 Urban 186.21 29.0 formerly smoked 1\rnrow(dataset)\r## [1] 5110\rNow it\u0026rsquo;s time to check for missing values.\n(sum(is.na(dataset$bmi)) / nrow(dataset)) * 100\r## [1] 3.933464\r# 3% of the bmi data is missing.\rImpute missing values with MICE\r#\rThis is when mice package becomes useful. Create a mice object to define methods.\nset.seed(7)\rmice_1 \u0026lt;- mice(dataset, maxit=0) # Set maxit to zero first because we don't want to predict yet. We are only creating a mice object.\rpredM \u0026lt;- mice_1$predictorMatrix\rid shouldn\u0026rsquo;t be used to predict anything, so make sure to leave it out.\npredM[, c(\u0026quot;id\u0026quot;)] \u0026lt;- 0 meth \u0026lt;- mice_1$method\rCheck the methods. Only bmi has NA values and needs to be calculated.\nmeth\r## id gender age hypertension ## \u0026quot;\u0026quot; \u0026quot;\u0026quot; \u0026quot;\u0026quot; \u0026quot;\u0026quot; ## heart_disease ever_married work_type Residence_type ## \u0026quot;\u0026quot; \u0026quot;\u0026quot; \u0026quot;\u0026quot; \u0026quot;\u0026quot; ## avg_glucose_level bmi smoking_status stroke ## \u0026quot;\u0026quot; \u0026quot;pmm\u0026quot; \u0026quot;\u0026quot; \u0026quot;\u0026quot;\rRun mice to create dataset with 5 different possible values for the missing values.\nmice_results \u0026lt;- mice(dataset, maxit = 1, predictorMatrix = predM, method = meth, print = FALSE) Check the predicted values.\nhead(mice_results$imp$bmi) ## 1 2 3 4 5\r## 2 21.4 26.7 28.7 21.9 33.3\r## 9 27.3 19.4 24.2 28.6 32.2\r## 14 37.9 40.9 35.5 27.0 23.2\r## 20 26.7 27.8 22.1 20.5 27.0\r## 28 31.5 23.2 31.2 31.9 39.1\r## 30 45.2 32.8 37.3 29.1 28.6\rExtract the first set and use it to complete the data.\ndataset \u0026lt;- mice::complete(mice_results, 1)\rhead(dataset)\r## id gender age hypertension heart_disease ever_married work_type\r## 1 9046 Male 67 FALSE TRUE TRUE Private\r## 2 51676 Female 61 FALSE FALSE TRUE Self-employed\r## 3 31112 Male 80 FALSE TRUE TRUE Private\r## 4 60182 Female 49 FALSE FALSE TRUE Private\r## 5 1665 Female 79 TRUE FALSE TRUE Self-employed\r## 6 56669 Male 81 FALSE FALSE TRUE Private\r## Residence_type avg_glucose_level bmi smoking_status stroke\r## 1 Urban 228.69 36.6 formerly smoked 1\r## 2 Rural 202.21 21.4 never smoked 1\r## 3 Rural 105.92 32.5 never smoked 1\r## 4 Urban 171.23 34.4 smokes 1\r## 5 Rural 174.12 24.0 never smoked 1\r## 6 Urban 186.21 29.0 formerly smoked 1\rBuild prediction models\r#\rStarting from here, start using the caret package. Start by preparing a training and testing set.\ncontrol = trainControl(method=\u0026quot;cv\u0026quot;, number = 10)\rLet\u0026rsquo;s train using 6 different machine learning models.\nBoosted logistic regression Naive Bayesian K-nearest Neighbors Linear Support Vector Machine (SVM) Random forest (method=\u0026lsquo;ranger\u0026rsquo;) CART Each of these are can be plugged in the \u0026quot;model=\u0026quot; argument of the train() function. Some (i.e. ranger) prompt additional package installs, and simply say yes to all of them.\n# boosted logistic regression\rset.seed(7)\rfit.logreg \u0026lt;- train(stroke ~ gender + age + hypertension + ever_married + work_type + Residence_type + avg_glucose_level + bmi + smoking_status, data=dataset, method=\u0026quot;LogitBoost\u0026quot;, metric=\u0026quot;Accuracy\u0026quot;, trControl=control)\r# naive Bayes\rset.seed(7)\rfit.naivebayes \u0026lt;- train(stroke ~ gender + age + hypertension + ever_married + work_type + Residence_type + avg_glucose_level + bmi + smoking_status, data=dataset, method=\u0026quot;naive_bayes\u0026quot;, metric=\u0026quot;Accuracy\u0026quot;, trControl=control)\r# K-nearest neighbors set.seed(7)\rfit.knn \u0026lt;- train(stroke ~ gender + age + hypertension + ever_married + work_type + Residence_type + avg_glucose_level + bmi + smoking_status, data=dataset, method=\u0026quot;knn\u0026quot;, metric=\u0026quot;Accuracy\u0026quot;, trControl=control)\r# Linear support vector machine\rset.seed(7)\rfit.svm \u0026lt;- train(stroke ~ gender + age + hypertension + ever_married + work_type + Residence_type + avg_glucose_level + bmi + smoking_status, data=dataset, method=\u0026quot;svmLinear\u0026quot;, metric=\u0026quot;Accuracy\u0026quot;, trControl=control)\r# random forest\rset.seed(7)\rfit.rf \u0026lt;- train(stroke ~ gender + age + hypertension + ever_married + work_type + Residence_type + avg_glucose_level + bmi + smoking_status, data=dataset, method=\u0026quot;ranger\u0026quot;, metric=\u0026quot;Accuracy\u0026quot;, trControl=control)\r# CART\rset.seed(7)\rfit.cart \u0026lt;- train(stroke ~ gender + age + hypertension + ever_married + work_type + Residence_type + avg_glucose_level + bmi + smoking_status, data=dataset, method=\u0026quot;rpart\u0026quot;, metric=\u0026quot;Accuracy\u0026quot;, trControl=control)\rFrom all the models, check which is the most accurate.\nresults \u0026lt;- resamples(list(logreg=fit.logreg, cart=fit.cart, knn=fit.knn, svm=fit.svm, rf=fit.rf, naivebayes=fit.naivebayes))\rsummary(results)\r## ## Call:\r## summary.resamples(object = results)\r## ## Models: logreg, cart, knn, svm, rf, naivebayes ## Number of resamples: 10 ## ## Accuracy ## Min. 1st Qu. Median Mean 3rd Qu. Max. NA's\r## logreg 0.9432485 0.9476517 0.9510284 0.9491193 0.9510763 0.9511719 0\r## cart 0.9452055 0.9510763 0.9510763 0.9504896 0.9510763 0.9529412 0\r## knn 0.9412916 0.9471624 0.9510763 0.9489240 0.9511480 0.9530333 0\r## svm 0.9510763 0.9510763 0.9510763 0.9512724 0.9510763 0.9529412 0\r## rf 0.9510763 0.9510763 0.9510763 0.9512724 0.9510763 0.9529412 0\r## naivebayes 0.9510763 0.9510763 0.9510763 0.9512724 0.9510763 0.9529412 0\r## ## Kappa ## Min. 1st Qu. Median Mean 3rd Qu.\r## logreg -0.01368083 -0.006420385 -0.001888788 0.002818109 0.00000000\r## cart -0.01059472 0.000000000 0.000000000 0.024640625 0.05048551\r## knn -0.01657825 -0.007300869 0.000000000 0.009876670 0.00000000\r## svm 0.00000000 0.000000000 0.000000000 0.000000000 0.00000000\r## rf 0.00000000 0.000000000 0.000000000 0.000000000 0.00000000\r## naivebayes 0.00000000 0.000000000 0.000000000 0.000000000 0.00000000\r## Max. NA's\r## logreg 0.06731401 0\r## cart 0.12613722 0\r## knn 0.07343608 0\r## svm 0.00000000 0\r## rf 0.00000000 0\r## naivebayes 0.00000000 0\rLet\u0026rsquo;s test with a sample patient who is 81 years old and smokes.\npatient = tribble(~gender, ~age, ~hypertension, ~heart_disease, ~ever_married, ~work_type, ~Residence_type, ~avg_glucose_level, ~bmi, ~smoking_status, \u0026quot;Male\u0026quot;, 81, TRUE, TRUE, TRUE, \u0026quot;Private\u0026quot;, \u0026quot;Urban\u0026quot;, 300, 28.6, \u0026quot;smokes\u0026quot;)\rpredict(fit.rf, patient)\r## [1] 0\r## Levels: 0 1\rThe patient is unlikely to have stroke! What a surprise. Let\u0026rsquo;s try using a different model:\npredict(fit.logreg, patient)\r## [1] 1\r## Levels: 0 1\rThe logistic regression model says he might have stroke.\nPutting it all together as a web app\r#\rModels are trained and everything\u0026rsquo;s working well. However, how do we make this accessible for people who aren\u0026rsquo;t familliar with R? We cannot expect them to run predict() every single time.\nEnter shiny, a package that lets you turn R files in web apps.\nFirst, let\u0026rsquo;s save our models into an RDS file (this prevents us from retraining the models repeatedly)\nsaveRDS(fit.logreg, \u0026quot;logreg.rds\u0026quot;)\r# Do this for every model\rThen let\u0026rsquo;s create an App.R for shiny. This file will later be deployed on shinyapps.io.\nAfter saving each model into an RDS file, time to load them.\ncart_model \u0026lt;- readRDS(\u0026quot;./data//cart.rds\u0026quot;)\rknn_model \u0026lt;- readRDS(\u0026quot;./data//knn.rds\u0026quot;)\rlogreg_model \u0026lt;- readRDS(\u0026quot;./data//logreg.rds\u0026quot;)\rnaivebayes_model \u0026lt;- readRDS(\u0026quot;./data//naivebayes.rds\u0026quot;)\rrf_model \u0026lt;- readRDS(\u0026quot;./data//rf.rds\u0026quot;)\rsvm_model \u0026lt;- readRDS(\u0026quot;./data//svm.rds\u0026quot;)\rLibraries need to be loaded, and ensure that model-specific libraries are loaded as well.\nlibrary(shiny)\rlibrary(dplyr)\rlibrary(bslib)\rlibrary(caret)\rlibrary(kernlab)\rlibrary(ranger)\rlibrary(caTools)\rlibrary(naivebayes)\rDefine the UI. Let\u0026rsquo;s have a simple 2 column layout with input buttons on the left and the output on the right in the form of accordions that you can click to show hidden text.\nui \u0026lt;- page_fillable(\r\u0026quot;Stroke Prediction\u0026quot;,\rlayout_columns(\rcard(helpText(\u0026quot;Select below:\u0026quot;),\rselectInput(\r\u0026quot;gender\u0026quot;, label = \u0026quot;Gender:\u0026quot;,\rchoices = list(\u0026quot;Male\u0026quot;,\u0026quot;Female\u0026quot;,\u0026quot;Other\u0026quot;),multiple = FALSE),\rnumericInput(\r\u0026quot;age\u0026quot;,label=\u0026quot;Age:\u0026quot;,value=20),\rcheckboxInput(\u0026quot;hypertension\u0026quot;, \u0026quot;I have hypertension\u0026quot;, value = FALSE),\rcheckboxInput(\u0026quot;heart_disease\u0026quot;, \u0026quot;I have heart disease\u0026quot;, value = FALSE),\rcheckboxInput(\u0026quot;ever_married\u0026quot;, \u0026quot;I'm married/have been married\u0026quot;, value = FALSE),\rselectInput(\r\u0026quot;work_type\u0026quot;, label = \u0026quot;Type of employment: (Select children if you are below 18)\u0026quot;,\rchoices = list(\u0026quot;children\u0026quot;,\u0026quot;Govt_job\u0026quot;,\u0026quot;Never_worked\u0026quot;,\u0026quot;Private\u0026quot;,\u0026quot;Self-employed\u0026quot;), multiple=FALSE),\rselectInput(\r\u0026quot;Residence_type\u0026quot;, label = \u0026quot;Type of residence:\u0026quot;,\rchoices = list(\u0026quot;Rural\u0026quot;,\u0026quot;Urban\u0026quot;),multiple=FALSE),\rnumericInput(\r\u0026quot;avg_glucose_level\u0026quot;, label= \u0026quot;Average glucose level:\u0026quot;, value=106.1477),\r# Use mean as default.\rnumericInput(\r\u0026quot;bmi\u0026quot;, label=\u0026quot;BMI:\u0026quot;, value=28.92663),\r# Use mean as default\rselectInput(\r\u0026quot;smoking_status\u0026quot;, label=\u0026quot;Smoking status:\u0026quot;,\rchoices = list(\u0026quot;formerly smoked\u0026quot;,\u0026quot;never smoked\u0026quot;,\u0026quot;smokes\u0026quot;,\u0026quot;Unknown\u0026quot;)),),\rcard(\raccordion( accordion_panel( title = \u0026quot;Logistic Regression\u0026quot;, textOutput(\u0026quot;logreg\u0026quot;)\r), accordion_panel(\rtitle = \u0026quot;CART\u0026quot;,\rtextOutput(\u0026quot;cart\u0026quot;)\r), accordion_panel(\rtitle = \u0026quot;K-nearest Neighbors\u0026quot;,\rtextOutput(\u0026quot;knn\u0026quot;)\r), accordion_panel(\rtitle = \u0026quot;Naive Bayesian\u0026quot;,\rtextOutput(\u0026quot;naivebayes\u0026quot;) ),\raccordion_panel(\rtitle = \u0026quot;Random forest\u0026quot;,\rtextOutput(\u0026quot;rf\u0026quot;) ),\raccordion_panel(\rtitle = \u0026quot;Support vector machine (linear)\u0026quot;,\rtextOutput(\u0026quot;svm\u0026quot;) )\r),\r),\rcol_widths = c(3,9) ) )\rIt should look something like this:\nFunctions to rerun everytime someone modifies the input should be placed in server.\nserver \u0026lt;- function(input, output) {\rpatient_data \u0026lt;- reactive({\rdata.frame(\rgender = input$gender,\rage = input$age,\rhypertension = input$hypertension,\rheart_disease = input$heart_disease,\rever_married = input$ever_married, work_type = input$work_type,\rResidence_type = input$Residence_type,\ravg_glucose_level = input$avg_glucose_level,\rbmi = input$bmi,\rsmoking_status = input$smoking_status,\rstringsAsFactors = TRUE )\r})\rgenerate_prediction \u0026lt;- function(model, model_name) {\rrenderText({\rprediction \u0026lt;- predict(model, patient_data())\ris_high_risk \u0026lt;- if(is.factor(prediction)) prediction == \u0026quot;1\u0026quot; else prediction == 1\rif (is_high_risk) {\rpaste(\u0026quot;According to the\u0026quot;, model_name, \u0026quot;model, you have a high chance for stroke.\u0026quot;)\r} else {\rpaste(\u0026quot;According to the\u0026quot;, model_name, \u0026quot;model, you have a low chance for stroke.\u0026quot;)\r}\r})\r}\r# 3. Assigning the outputs\routput$logreg \u0026lt;- generate_prediction(logreg_model, \u0026quot;Logistic Regression\u0026quot;)\routput$cart \u0026lt;- generate_prediction(cart_model, \u0026quot;CART\u0026quot;)\routput$knn \u0026lt;- generate_prediction(knn_model, \u0026quot;K-nearest Neighbors\u0026quot;)\routput$naivebayes \u0026lt;- generate_prediction(naivebayes_model, \u0026quot;Naive Bayesian\u0026quot;)\routput$rf \u0026lt;- generate_prediction(rf_model, \u0026quot;Random Forest\u0026quot;)\routput$svm \u0026lt;- generate_prediction(svm_model, \u0026quot;SVM\u0026quot;)\r}\rFinally, let\u0026rsquo;s run the application\nshinyApp(ui = ui, server = server)\rAll done! Deploy it into shinyapps.io with the rsconnect package. You can see the final product here.\n","date":"28 March 2026","externalUrl":null,"permalink":"/articles/20260328/","section":"Articles","summary":"I reflect on my journey learning machine learning in R using a project in which I build a stroke prediction app.","title":"Teaching myself to code by building a stroke prediction app without AI","type":"articles"},{"content":"Available on Medium\nHerein lies, to date, the most controversial of my essays. While everything is political, this topic is one such that the politicisation of gender is one of the hottest topics of the 21st century. Gender is so incredibly politicised and at the same time, so incredibly personal to anyone speaking about it, which led it into realms of discourse reserved to confined conversations. Especially when the conversations start to veer from what is deemed “acceptable” to what is not; a contradiction in which an academic discourse could be limited by the society’s constraints of propriety, one of the taboos of the modern age.\nSomehow, gender as a discussion can define some political assumptions; for example, being a feminist will somehow place you as left-leaning, which, while true, since feminism is a political movement, it does show how much politicisation is occurring to the point that equal rights for women had to have a place on the political spectrum. This is not a treatise on how gender should be depoliticised. It is certainly clear that historical accounts would benefit from feminism as a political movement as opposed to not.\nFor example, without suffrages pioneering for women’s rights, it would not be possible for women to have the same worker’s rights as men. Conformity is political, and to protest for the right to be compensated fairly for work is deeply political, although this time it is a protest on discrimination based on gender. Gender is political because it enacts conformity to the common people; you must behave in a certain way to achieve a certain position in society, that is, you must be feminine to achieve the position of a woman in society. It is soft control masked with pretty colors and romanticism. Again, not a criticism towards femininity, but to comply with the enforced is a result of politics. Hence, you require a political movement to defy this conformity, this is where feminism was born as a movement.\nWestern soft power in gender performance\r#\rGlobalisation is defined as the process by which businesses or other organizations develop international influence or start operating on an international scale. Globalisation is best understood with examples: a song by Rihanna plays on the radio off the coast of Vietnam; pho noodles with chilli powder in western Wisconsin, or baguettes in Kedu, Indonesia. Globalisation is often lauded as a modern innovation. You can now experience the products of another country thousands of miles away in your home. But globalisation permeates in a lot more ways than not, and oftentimes, it is Western soft power that wins the race. Take myself, for example. I write in English in anticipation of a global audience, a western, modern language that has been adopted as an international language. Speaking English is no longer indicative of an English origin; you could be Argentinian and speak fluent English. I like to wear jeans and a T-shirt, and jeans weren’t popular as casual wear until James Dean wore it in a 1955 movie Rebel Without a Cause, a distinctly American actor in a distinctly American movie, and I believe you, dear reader, has put on a pair of jeans at least once in your lives. The concept of western exports being divorced from its “western-ness” normalises the western aspect as the default.\nGender performance does not escape from this fate; pink as an indication of femininity is a result of globalisation; the idea has permeated all countries to agree that specific, light, rosy color to be indicative of the female gender. But where did it all start? Theory says it started with Marmie Eisenhower, former First Lady of the United States from 1953 to 1961.\nAgain, a western country, despite pink being a prominent color in Mexico without much associations to femininity. Look at a United Nations meetup; most men wear suits, a male gender performance, using a garment with western origins. They signal their maleness with suits, and signal their conformity of using western formal wear. On rare occasions, you might see a middle eastern prince wearing a thawb, but this remains as an exception to the rule.\nIt is a permeable, obvious thing once noticed, but without proper observation, it becomes easy to accept things as is, to conform. You know what gender you are, and you would like to present as that gender. This leads to certain decisions being made in the morning, whether it is a conscious choice or an unconscious one. Your mind does not exist in isolation; your choices are influenced.\nWestern soft power ensures that the global view of gender follows the early 19th century conservative western ideal. The woman is the soft, nurturing head of the house, while the man is the productive and benevolent patriarch who provides and works. Non-western cultures could have a differing view; the Minangkabau ethnic group from western Indonesia, for example, posits that a matriarch spearheads the family and is the gender allowed to inherit land, while men are unable to inherit. Some cultures even do not subscribe to this binary view. The Bugis culture from south Sulawesi believes in the concept of five genders.\nThis conservative western ideal permeates into multiple cultures and erases the cultural presence of third genders or intersexuality. Even ancient Middle Eastern literature posits a presence of mukhannatun or feminine men, as an argument against Islamic values being entirely sexually dichotomous. Native American beliefs acknowledge the presence of two-spirit. Thailand was a country that was never colonised due to its strategic location and the strength of its former kingdom. Due to this, it became the first Southeast Asian country to legalise gay marriage and its long reputation for being a safe haven for transgender individuals is not an empty claim.\nWho stands to benefit?\r#\rHistorically, deeming the Western as the default has its roots in colonisation. Racial politics before modern times benefited colonising powers economically by considering the people they colonised as “other”, allowing them to cut down on labor costs. Equally, by considering women as “lesser” through false rationalisations such as “women can live off their husbands” or “women are less capable” to justify a gender wage gap. Policy can support this framework and is only overturned by modern feminist movements. Even when it was overturned, the reality is that it is not consistently applied.\nThe strict dichotomous gender binary of male/female outside a reproductive context benefits a capitalist worldview. In a typical heterosexual marriage dynamic, the man works, then the woman stays at home -- in order words, performs the shopping. The man provides and the woman consumes. It benefits the economy. The current feminist push for women to work equally benefits the economy, increasing the workforce. Colonisation and the economy are very intimately intertwined. The United Fruit Company, a now defunct multinational company originating in the US, was strongly involved in Honduran and South American politics, and history lessons in Southeast Asia will mention other western-origin companies abetting colonisation: the Dutch-origin Dutch East India Company operating until 1799 and English-origin East India Company operating until 1874.\nWhat role do people outside the dichotomy play? Opting out of conventional reproduction could harm the birth rate, ergo the economy, but you could equally say that the economy benefits from people outside the binary; especially in the modern era where every gender is expected to perform labor and consumption. In communal living situations where a “family unit” is not limited to only the father, mother and children, but includes aunts, uncles, and further relatives as participants in child-rearing, strict gender roles aren’t as necessary. You could technically be any gender and raise children, outside the reproductive part at the start. While different gender roles are imposed by the older family figures to socialise the young, both men and women can perform acts of nurture.\nDecolonisation as an active act?\r#\rIf strict gender ideals are a colonisation byproduct, rejecting it would be an act of decolonisation. To decolonise gender means to accept non-western ideals of gender and return to the roots of culture before Western influence. Strict, binary gender is argued to be non-traditional as opposed to traditional, and was introduced as a western soft power with roots in colonisation.\nHow can we move on with this information? Indeed, there is some difficulty in finding impactful acts towards uprooting centuries old thinking, especially when the system has embedded it worldwide, with limited cases of successful nationwide decolonisation that focuses on the specific aspect of gender. Besides, while the binary gender is a western soft power construct, traditionalism is not an entirely perfect solution. Female gender roles could suffer under traditionalism, and female genital mutilation is a traditional act. Decolonisation must be done with conscious efforts to balance the rights of everybody involved. While human rights itself might be a new concept that may not entirely be traditional, it is not a bad thing to accept the concept. Just so gender roles can play some benefit, it must be understood that we need to recognise how deeply colonisation has permeated modern society.\n","date":"21 March 2026","externalUrl":null,"permalink":"/articles/20260321/","section":"Articles","summary":"I discuss gender as a western soft power construct and how the framework of gender is dismantled with decolonisation.","title":"A conversation about the politicisation of gender","type":"articles"},{"content":"","date":"21 March 2026","externalUrl":null,"permalink":"/tags/gender/","section":"Tags","summary":"","title":"Gender","type":"tags"},{"content":"","date":"21 March 2026","externalUrl":null,"permalink":"/tags/sociology/","section":"Tags","summary":"","title":"Sociology","type":"tags"},{"content":"Available on Substack\nTrigger warning: discussions about suicide.\rNote: This is an informal discussion. While I mention several sources worthy to peruse, a lot of words written are my creative liberty and a method of exploration. I would rather my readers define by themselves what their emotions mean to themselves, but I do personally find some benefit in rationalising what I feel, and it may be useful to you too.\nHere’s a very common notion that may be of interest if your city regularly sees birds, specifically crows: you must be nice to crows. Crows will remember those who wronged them and those who didn’t. If you didn’t, you’ll receive gifts in coins, ephemera, or trinkets.\nThis behaviour is readily accepted as the norm, yet it is strangely bizarre. What drives these animals to do such things? If we apply the common-man’s knowledge of survival of the fittest, it makes little sense for them to conduct these things. Why expend resources to reward a creature who was previously beneficial? You could argue that it makes complete sense they would do so, a beneficial ally could prove to be beneficial again in the future, hence increasing the fitness of these birds. But to assume that a beneficial ally will remain beneficial requires an underlying notion; that is, the notion of trust.\nTrust is a little difficult to define. Dictionary-wise, it is the belief that something is safe and reliable. But where exactly did it come from? Are humans built with trust encoded in their DNAs, or is there no true “trust gene”? To delve into this, let’s take a look at a study from 1987, in which we look at a simpler organism.\nA case study on trust\r#\rThe study on stickleback fish enlightened a very basic form of mutual cooperation strategy, known as tit-for-tat. (1) You start with both parties cooperating. Then, whatever your opponent decides to do, you mirror. If your opponent continues to cooperate, you do so as well. If your opponent decides not to, you do not. Tit-for-tat is evidence for the evolutionary origins of cooperation.\nCrows operate on a different scale; they “assume” that there is continuity in benefit, ergo, trust, which elevates this interaction above tit-for-tat. There are elements present to affirm the presence of trust, which are (1) the memory of previous benefit and (2) the ability to predict future benefit, which requires a brain capable of identifying patterns. Could we, therefore, hypothesize that trust is a natural effect of the brain’s search for patterns? The hypothesis would fit well, and helps us understand trust as something more tangible. Instead of an abstract “a belief of goodness”, it is “an evolutionary by-product of pattern seeking, applied towards other sentient organisms”.\nTrust is debatably not genetic; it seems to be influenced by social and environmental factors more than genes. (2) You are not born with trust, you develop trust. This fits our hypothesis. Provided you have memory of benefit, and sufficient information to develop the pattern-based understanding that benefit will continue, you will develop trust.\nCrows and stickleback fishes are good model organisms, but let’s revisit humans. If you were to encounter a very distrustful person, you could reasonably assume they’ve had very bad experiences overall. You could extend this argument further, and say that trust is a biological response towards the environment they have had; similar to sweating on a hot sunny day, they are responding to stimuli reflexively.\nCompare these two situations: (the “I” in this case refers to an abstract narrator)\nI bought an ice cream, I tripped, the ice cream fell and I felt upset. I’ve been scammed by an ice cream seller, so I don’t think I’ll trust people more easily from now on. In both situations, the environment provided me with an “input” and an “output”. In the first situation, the cause is “ice cream on the ground”, and the result is “upset”. For the second situation, the input is “scammed by an ice cream seller” and the output is “more distrust”. The only difference between these is the complexity of the emotion. Being upset is temporary and mostly affects the current situation. Perhaps, because “I” was upset, “I” would cry a little, or perhaps buy another ice cream, or think of buying ice cream in cups from then on. The second situation is a little more complex. It could mean that all other decisions involving purchases in the future would be affected or it could mean that decisions relating to ice cream sellers only would be affected. However, the overall impact will be greater than that of being upset from dropping your ice cream. But if you take a step back, and look at the overall picture, they’re both responding to situations. Your response is not that different from that of a crow who has been treated terribly by an evil, devious human.\nWhile trust is a complex behavioural trait, we have divorced it from its poetic undertones to its most basal understanding. Trust is a response to multiple stimuli, compounded into one complex emotion. It could be argued that a lot of deep, emotional responses are this: responses to various stimuli that when compounded together can manifest as an emotion. We cannot say exactly that it is a cause-effect relationship and identify causation without statistical proof but we can, with a lot of hand-waving, somewhat identify a binary relation, in which the relation is “A makes you feel B”.\nAnger, for instance, occurs when a violation occurs, whether it is the safety of a certain individual or their boundaries which is used to define their sense of safety. You can observe territorial behaviour prevalent in many animals manifest in anger, because they feel like their physical boundaries, a territory they feel the safest in, is violated. This has evolutionary benefits. Assume that the anger from territorial behaviour is acted upon, and the borders of territory are maintained. Access to resources is retained and survival is guaranteed another day.\nEven more complex emotions can be broken down to evolutionary responses - grief is a response to losing a person close to you, and losing such a person means the individual loses an ally or a person capable of providing emotional comfort. Other individuals observe the behaviour of those undergoing grief, and the collective understanding is to prevent the death of another individual and prevent grief.\nA more concrete example is visible in depression: it appears that depressive symptoms can manifest when a person is ill. (3) Illness itself becomes the trigger that causes depression to occur. This is also beneficial evolutionary-wise, causing a person to self-isolate, preventing further infections to spread into the community, and to rest, which allows a person to gradually recover.\nGendered perspectives on emotion\r#\rWomen are from Venus, men are from Mars. Women are emotional, men are logical. Such is a pervasive thought. But it is an interesting thought; it assumes a strict dichotomy, not only between men and women, but between “emotional” and “logical”. Previously, we argued that trust is a by-product of responding to stimuli, and so is being upset. A stimulus resulting in a particular emotion simulates a binary relation of this-to-that.\nThis argument of a dichotomy falls flat once we dissect the origins of emotion as a logical response, moreso with an underlying complexity that fails to be factored in when defining what is logical and what is emotional. To begin with, you shouldn’t take statements like “men are logical” definitively. Men are certainly emotional, it comes with being an intelligent mammal. Emotion is a manifestation of social intelligence. It is the capacity to react and understand intent and implication.\nStatements that pit women and men through an emotional/logical lens are just symptomatic of a patriarchal system that affirms the myth of female hysteria. Hysteria, by itself, is uniquely diagnosed to women, as a method of oppression. Hysteria often manifests in great expressions of emotion, such as irritability and anxiety. This stigmatises female emotion as a disease and limits their movement. Additionally, the definition of emotion can be adjusted according to need. One of the top 5 movies in IMDb (as of 2026) is literally titled 12 Angry Men, yet men do not face the stereotypical view of being an emotional type. The common stereotype does typically exclude anger as an emotion, or otherwise consider it to be a masculine emotion.\nBut at its core, what is wrong with being emotional? Being emotional may mean being more perceptive to stimuli, and being unconsciously more receptive to patterns. There is nothing wrong with feeling. In fact, there should be no moral weight towards feeling. You could be feeling angry, but decide to calm yourself down with a cup of coffee or tea, or you could be angry and start slamming doors and banging tables. These are actions resulted by feelings, but while the motive that informs the action is there, the decision still lies on the person. This is where the moral weight lies. To stigmatise emotion is the lack of rationality that accompanies patriarchal behaviour. If we keep stigmatising emotion in a patriarchal environment, we affirm that men should have less of it, and this alienates genders from one another to detrimental effects.\nThe body plays a part\r#\rEmotions may fit into the realms of poetry and fantasy. Trying to define it in a logical sense may seem antithetical. But I would urge you to view coexistence of emotions and logic to be supporting each other instead of existing as a dichotomy.\nWhile complex behavioural traits are heavily influenced by social and environmental factors, there are genetic and hormonal factors playing a part in emotional responses. Variation in the CD38 genes cause an individual to be more prone to being stressed or anxious when faced with a problem related to relationships, whether it is platonic or romantic. (4) This means that some aspect of emotional response could be inherited from your parents as genes are inherited from parents.\nThe gene itself plays a part in the oxytocin signalling system, also known as the “love hormone”. While typically released in sex and childbirth, levels of this hormone have had influences in bonding, relationships, and community. It is a little difficult to define what the hormone does and how it affects how you act, but it appears it is not completely hands-off influencing people’s feelings and actions. For example, if you give a person a dose of oxytocin, they are more likely to be able to give you eye contact, and are also more likely to trust people. (5,6)\nRecall our definition of trust, coined before. Now we add a layer of complexity to it. Our pattern-seeking brain tends toward a more positive outlook in predicting goodness when loaded with oxytocin. Does this mean that our emotions are hard-coded in us, that we aren’t in control of ourselves? Well, maybe not to the point of losing control of ourselves. Of course, there is some physiological basis to why you feel what you feel. But what you feel isn’t who you are, it is what you do. Your decisions are based on who you are, and who you are is based on what you’ve been through. I believe in free will, that you can with your own power, break free from the inclinations of your birth.\nBeing overwhelmed and what comes out of it\r#\rWhen we talk about our emotions overwhelming us, sometimes it manifests into physical actions that may or may not be beneficial to us. When your environment, as a stimulus, continuously provides you with scenarios that trigger your distrust, you can become a mistrustful person. When your environment continues to give you stress, you could react to it with anger or depression. A recent discovery found that when infected with disease, ant larvae will signal other ants to kill it. (7) This absurdly drastic response can prove an evolutionary benefit. It prevents other ants from being infected with disease, and the larvae can die knowing it did its colony good.\nIn humans, this sort of suicidal behaviour has no benefit. No, not even Canada’s MAID. We have treatment for illness and there is no urgency to prevent spread of infection through dying. Anything “untreatable” will be treatable in the future. No suicidal behaviour in humans is beneficial. It is an overly extreme emotional reaction to the very understandable struggles of modern life.\nIt is truly a difficult time to live. It is the modern era and humans have had little time to adapt. Within a few millennia we have ditched the fletched arrows and started typing in plastic keyboards. The thrill of hunting a deer barely exists, now people stare at stock markets, waiting for the numbers to go up and down, just to emulate how it used to feel when your spear landed on a herbivore’s neck. Stimuli have changed too - you don’t fear being stalked by a light-footed jaguar, you fear your manager calling you for a layoff. The screen is blue while the sun is white. This isn’t enough time for your body to physiologically evolve with time. This makes things so different, and emotions change so much. Especially since new stressors like the job market and economic instability are lurking in the horizon.\nIt’s easy for your brain to trip up and feel like something is wrong, but it probably helps that we have things to help us rationalise. So far, we know that we are responding to the environment, and some things hard-coded into us will drive our response. It’s often hard to think clearly when you are extremely emotional (though you can argue that thinking clearly is thinking with emotion). But once you are stuck in a spiral, it really does help to take a step back and use what we know to figure out why we feel what we feel, and what we can do about it.\ngraph TD;\rA[I feel intensely sad/angry/impulsive and I don't know why] --\u003e B[I might have a psychological predisposition to feeling that way]\rA --\u003e C[There's a recent stressor that is really affecting me]\rA --\u003e D[I have a need that isn't being met]\rB --\u003e E[I need to be careful when taking care of myself]\rC --\u003e F[I need to do something about this stressor]\rD --\u003e G[I need to find ways to fulfill this need. Maybe a partial fulfillment is fine.]\rLet’s say you are feeling intensely sad. It’s possible that you are physiologically at a higher risk of being so; this means that you should take more care with yourself. Be kind to yourself, and give yourself things to focus on. If you feel sad about a recent death, you should be equally kind to yourself, and give yourself the space to heal. If you feel sad because you feel trapped, try to think of practical ways to get out of your situation.\nRemember that your body is responding, and that your emotions don’t define who you are. It is how you react, informed by your emotion, that defines who you are. If you are angry all the time and take your time to sit and knit quietly until your anger simmers, nobody will remember you as an angry person. You’ll simply be remembered as the person who knits.\nIt feels useful for me to rationalise how I feel and use the conventions of logic to stop from drowning in a certain emotion. If you look at it from a different perspective, we are just mammals trying our best after all.\nReferences\rMilinski M. TIT FOR TAT in sticklebacks and the evolution of cooperation. Nature. 1987;325(6103):433–5.\nWootton RE, Davis OSP, Mottershaw AL, Wang RAH, Haworth CMA. Exploring the genetic etiology of trust in adolescents: Combined twin and DNA analyses. Twin Res Hum Genet. 2016 Dec;19(6):638–46.\nDantzer R, O’Connor JC, Freund GG, Johnson RW, Kelley KW. From inflammation to sickness and depression: when the immune system subjugates the brain. Nat Rev Neurosci. 2008 Jan;9(1):46–56.\nProcyshyn TL, Leclerc Bédard LA, Crespi BJ, Bartz JA. CD38 genetic variation is associated with increased personal distress to an emotional stimulus. Sci Rep. 2024 Jan 31;14(1):2571.\nKosfeld M, Heinrichs M, Zak PJ, Fischbacher U, Fehr E. Oxytocin increases trust in humans. Nature. 2005 Jun 2;435(7042):673–6.\nTheodoridou A, Rowe AC, Penton-Voak IS, Rogers PJ. Oxytocin and social perception: oxytocin increases perceived facial trustworthiness and attractiveness. Horm Behav. 2009 Jun;56(1):128–32.\nDawson EH, Hoenigsberger M, Kampleitner N, Grasse AV, Lindorfer L, Robb J, et al. Altruistic disease signalling in ant colonies. Nat Commun. 2025 Dec 2;16(1):10511.\n","date":"12 January 2026","externalUrl":null,"permalink":"/articles/20260112/","section":"Articles","summary":"I describe emotion as a binary relation of stimuli and response and consider it as higher-order logic.","title":"An informal discussion about formalizing emotion","type":"articles"},{"content":"","date":"12 January 2026","externalUrl":null,"permalink":"/tags/logic/","section":"Tags","summary":"","title":"Logic","type":"tags"},{"content":"","date":"12 January 2026","externalUrl":null,"permalink":"/tags/mental-health/","section":"Tags","summary":"","title":"Mental Health","type":"tags"},{"content":"","date":"12 January 2026","externalUrl":null,"permalink":"/tags/self-help/","section":"Tags","summary":"","title":"Self Help","type":"tags"},{"content":"Available on Substack\nWho hasn’t heard of Jurassic Park? What started off as a novel, became a movie, and transformed into a franchise with amusement rides and a million dollar budget profiting off a fear of dinosaurs, a very strange, misplaced fear in the modern era in which dinosaurs have been extinct for more than a hundred thousand years and only remained in the state of bones. The original movie was a sci-fi horror in which the genetically engineered, synthetically created T-rex upends a touring car and velociraptors chase and kill men in a bloody, offscreen splatter. Dr Ellie Sattler, played by Laura Dern, cried to Hammond, “You never had control, that’s the illusion!”1 She played a paleobotanist, that is, a scientist who studies extinct plants, who came to Jurassic Park. She portrayed a sensitive yet resourceful dame in a Freudian trio with a heroic paleontologist and a cynical, logical mathematician.\nA scene from Jurassic Park, a classic movie in which scientists de-extinct dinosaurs. In the entire 127 minute runtime, dinosaurs only appeared onscreen for a total of 15 minutes. © Universal Studios\r#\rIt was clear that the movie wanted to warn people of the dangers of knowledge running unchecked. The mathematician warned Hammond, the park director, over and over about the dangers of trying to control nature, and Hammond soon realised he put everyone, including his grandchildren, in danger. The movie was released in 1993, when the notion of dinosaurs returning from extinction seemed like a fantasy. It is now 2025, thirty-two years since the release of Jurassic Park, and private biotechnology company Colossal Biosciences claimed they have revived the long-extinct dire wolf.2\nThe dire wolf existed in North America around 13,000 years ago, and was driven to extinction due to its prey being extinct and human-induced fires, which gradually decreased their population before dying off due to inbreeding.3,4 To allow dire wolves to return, Colossal Biosciences collected samples of DNA from fossils of dire wolves, studied it, and edited the genes of a gray wolf to make it indistinguishable (or so they say) from the DNA of dire wolves.5 If you’re wondering what DNA is, it’s a chemical substance that makes up the traits of every living thing, like hair in wolves and the apparatus to digest meat in carnivorous mammals. Genes are short sections of DNA that have specific instructions, for example, making sure that the hair in wolves is grey, instead of lighter coats in dire wolves.\nThe dire wolf case brings in mind scenes from Jurassic Park. It seems obvious to assume that these dire wolves could go wild and rip the throats of scientists like the raptors did in Jurassic Park. Hopefully, none of these gruesome scenes would ever occur, but it does make you think that something that was science fiction in 1993 could become true life in 2025. The subject of ethics became a debatable subject. Are extinct animals which never existed before, subject to conservation laws? Should the scientists be prosecuted, and if so, on what basis? Surely, fiction cannot be grounds to prosecute, and one could argue instead that prosecution would suffocate the progress of science. While science marches forward on ice skates, the law is crawling behind with one foot dragging on the pavement. Constitutions nearly a hundred years old never considered that the dead might again walk on Earth. Science is the study of progress ‒‒ it will evolve and move forward. Because of this, what should and what should not be done should be at the forefront.\nThe arrest of He Jiankui and the baby industry\r#\rOn the topic of prosecution, a shocking case occurred in 2019: a scientist was sentenced to three years in prison due to unethical scientific practices. While unethical practices have caused paper retractions before, the reason behind this imprisonment appeared to justify the occasion. His name was He Jiankui.6 The man claimed to have gene-edited humans for the very first time, changing what made humans into themselves, into a HIV-resistant version of them. This shocked the international scientist community. For the longest time, genetic engineering was restricted to plants and animals. Genetically modified (GMO) corn modified to be resistant to pesticides,7 bacteria designed to create insulin for diabetics,8 the genetically cloned Dolly the Lamb to test the limits of technology in 1996.9 Yet, He has done the unthinkable.\nWhile he claims that it is for a better cause, with the children he edited now resistant to HIV, the side effects are difficult to measure. What would occur to the lifespan of these children? If these children became sick, would the disease due to them obtaining a higher risk due to being gene-edited or would it just be a nasty coincidence? Human lives are greater of a risk. Nobody would protest to defend the rights of bacteria, but many would with a person. Why wouldn’t they? This is a person just like everybody else, who can think, talk and lead a life of their own. This person could grow up to become an esteemed Nobel Prize winner, have a spouse and three children. This person could also become a killer on death row at a penitentiary. Human life should not be so easily tampered.\nAs of the writing of this essay, He Jiankui has been released from prison, married10, and got a new job at a university11 and separated from his wife12. Surely he’s learned his lesson: whether to keep it on the down low this time or to just not touch humans ever again. But he has opened the floodgates of debate. Should his action be justified due to the babies (now children) being HIV-resistant? What limits what should or should not be edited out?\nHe Jiankui isn’t the only man out here manipulating babies. If you wanted a baby that is potentially smarter, instead of gene-editing children, you could purchase sperm from a sperm bank instead. Sperm is priced differently depending on the donor, and in the US, private companies such as Xytex could allow you to purchase sperm from non-anonymous donors. Those with doctorates are priced higher.13 Once you have made a sperm bank purchase, you could send it over to a fertility clinic which will do IVF for you.\nIn-vitro technology (IVF) refers to using laboratory techniques to fertilize an egg with sperm in a lab14. This egg can then be inserted into someone who could carry the baby to term. While the technology was originally developed to help those struggling with conception, the technology is now used to select for favorable traits. US laws do not prohibit selecting babies for non-medical reasons, which led to the industry boom of IVF in California. You could ask for tall, blue-eyed children if you wanted to.15\nThe baby of eugenicism is gestating. According to the The Sunday Times article, there is little demand to regulate a practice isolated to the upper-class of society, even though the industry sees clients from around the globe. Countries like the UK and Australia banned non-medical selection, but nothing stops them from purchasing a plane ticket and purchasing their “ideal” overseas.15 The reasoning behind why California, USA is the centerpoint for the fertility industry is politically grounded; Trump’s administration claims to be “pro-natalist” and as of 2025 Trump struck a deal to discount imported IVF drugs with Germany’s pharmaceutical company Merck.16\nTrump’s pro-natalist stance includes anti-abortion and has farmed criticism. Adriana Smith was thirty-one, pregnant, and died due to extensive blood clots in the brain. However, allowing her baby to die with her would be considered murder according to Georgia laws. Her body was kept on life support in order to keep alive the baby inside the brain-dead woman, and the baby was born prematurely through a C-section.17,18\nBoth of these cases lead to a question: Are we on a slippery slope? Babies born from eugenics would definitely widen the class gap that plagues current society, and to force a dead woman to give birth must be distressing for the family and friends of Adriana Smith. To treat a woman in that direction leads to discussions about the politicisation of the womb. Does a human right for a fetus to survive override the right for a dead woman to rest? The baby’s specific health status is currently unknown, but it appears that the unconventional birthing may have effects on healthy growth. Similarly, gene-editing babies or selective non-medical IVF may have effects that are yet to be experienced as of now, whether it be medical or societal.\nAdriana Smith’s case opens a discussion on the potential commercialisation of the womb; while her body was forced to carry a baby, some women have their wombs up for sale. Surrogacy is an age-old concept, and was even mentioned in the Code of Hammurabi (circa 1800 BC): a childless wife might give her husband a maid (who was no wife) to bear him children, who were reckoned hers.19 Note the use of the word maid. As Frantz Fanon said, “To speak a language is to take on a world, a culture.”20 Maids, while bearing the man’s children, do not have the full rights of the legal wife. She is simply a surrogate. This bellies the same argument to be made against modern surrogacy, in which the fertilised egg was instead inserted into the potential surrogate. It could be a means by which rich women exploit women who, through economic problems, are forced to become surrogates.21 The legal mother bears no physical risks with carrying, while the surrogate does. The legal mother does not concern herself with preeclampsia, gestational diabetes, and infections.22\nIntelligence in the 21st century\r#\rIt would be disingenuous to discuss the advancements of technology in the 21st century without touching upon artificial intelligence (AI). As of now, multiple artificial intelligence models are capable of passing the Turing Test.23 Intelligence of AI has developed to a point and is accessible enough that 700 million weekly users require AI assistance through ChatGPT24, leading to its parent company OpenAI has hit $500B in valuation.25\nIts intelligence comes with drawbacks. Due to the intense energy usage needed, the maintenance of supercomputers requires extensive resources and causes nasty byproducts. In the city of Memphis, a supercomputer called Colossus from xAI, owned by Elon Musk, has violated environmental laws by secretly importing 35 methane gas turbines. When the air quality of the city was tested, they found a 3% increase in the average concentrations of nitrogen dioxide after June 2024; clearly, one can extrapolate the date in which the data center became more active.26,27\nBut this is a paper about bioethics. What would that have to do with AI? Here enters organoid intelligence (OI), perfectly designed to solve some problems of AI. It is well known that the brain is extremely efficient and powerful. If you could grow some neurones in a Petri dish, why not program these brain cells to be able to run certain commands and self-learn just like AI?\nTable comparing a supercomputer with a human brain. This table is taken from https://www.frontiersin.org/journals/science/articles/10.3389/fsci.2023.1017235/full\r#\rThe brain could also address the issue of training data. Machine learning needs to be fed with a lot of data before it can develop the capacity to do a task, but humans learn their lessons quickly. For example, a same-different task would require 10 samples for a human to learn, but 107 samples wouldn’t be enough for machine learning.28–31 In Kenya, this has led to outsourcing and exploitation of workers. Workers with one to three month contracts had to annotate hundreds of violent and triggering content for machine learning for $1.16 per hour.32,33 With so much data required, it is also inevitable that copyrighted content would eventually be fed into AI, which led to lawsuits regarding intellectual property.34 With organoid intelligence, less energy and data is needed, and the likelihood of copyright infringements and exploitation could be lessened with the reduced data demand.\nAs much as the topic is exciting, it is still difficult to modify neuronal connections according to a scientist’s whim and still difficult to map the brain’s behaviour.28 This field requires a breakthrough similar to the discovery of CRISPR. Regardless, if you follow the track record of discovery in science, it is safe to assume it is in an achievable future.\nThe antagonist from “I Have No Mouth and I Must Scream”, a video game that adapted a short story from Harlan Ellison. While the antagonist, AM, is a supercomputer, how bizarre it is that it could continue to sustain itself with the typical energy demands of AI in a post-apocalyptic world. Perhaps it is an OI? © Cyberdreams\r#\rOrganoid intelligence seems to solve some problems AI has, but not all of them. It still won’t solve the problem of how it positions itself in society. Google engineer Blake Lemoine believed that Language Model for Dialogue Applications (LaMDA) is his sentient coworker.35. A community on Reddit is formed out of people who maintain romantic relationships with AI.36 When ChatGPT released an update to make the models less emotional, many in the community mourned the coldness of their digital lover.37 It appears that a basal component in some people cannot distinguish the consciousness of an AI. For others, they clearly understand AI is not conscious and have a strong pushback against fostering connections with AI. An AI companion, Friend, was launched with an advertising campaign on the New York City subway and had its posters defaced38,39.\nFuture goals in creation and consciousness\r#\rWhile data scientists have successfully built artificial intelligence and biologists ponder the possibilities of organoid intelligence, elsewhere, another form of creation is underway. The legend of the homunculi starts with the humble yeast. Yeast, generally known for its contributions in baking, is also finding a lot of use in research due to it being accessible and eukaryotic, thus making it closer to humans than bacteria40. From this, there was this general idea that with modern methods of synthesizing DNA, it was possible to create the entire genome (all the genes) of yeast, with the goal of making an entirely synthetic eukaryotic organism. This was the goal of the Sc2.0 consortium.41 While the goal of an entirely synthetic organism is yet to be realised, it was announced that a project to create human DNA from scratch, using similar techniques in creating synthetic yeast DNA, is starting in June 2025: The Synthetic Human Genome Project (SynHG).42,43\nScience has moved from simply manipulating to creating. It will be possible to create human DNA through chemical processes and if you take it a step further, you might even link those together using more processes, to create a genome. This genome would contain information about an entirely synthetic human. The DNA would tell how the hair would fall from the top of their head, whether it would curl or fall straight, how milk would be digested in their stomach, how their skin would react under the sun, whether it would tan or blush. All of this information of a person who was never born and exists without a true body. It isn’t fantasy, but an achievable goal. What if you inserted that genome into an empty egg cell? What would happen if the entirely synthetic DNA was allowed to develop into a fully functional human being?\nYou could potentially create something with sentient intelligence through organic computing, and you could also potentially create an entire homunculus using DNA from SynHG. What would limit humanity from creation? One could faithfully argue that humans playing God would call upon fire and brimstone. You could equally argue that if, assuming that if the SynHG project runs its course and someone does create a complete human genome from the results of the project, ensoulment never did occur, and no infringement upon the domain of God occurred. How does one objectively measure ensoulment? Religious and ethical concerns galore.\nWould Friend, the problematic AI companion strung around a person’s neck, be more acceptable if it wasn’t plastic? If AI companions aren’t conscious, would OI companions be considered conscious? It becomes a debate akin to the Ship of Theseus; never-ending and with a mixed bag of results. Even if it is conscious, would it be ethical to keep it around your neck and subject it to an endless cycle of service? Would an OI receive any rights? Of course, an OI would be a collection of cells, and the debate whether OI would have rights echoes similar sentiments to the abortion argument. When is it acceptable to consider a collection of cells alive, and when is it acceptable to consider that these may have rights?\nThese debates may seem far-fetched, but it could be our near future. After all, a million years ago it would be unthinkable to debate when human life started when embryo development wasn’t as strongly understood. A thousand years ago, it would have been unthinkable to debate whether cells could have rights, when cell theory wasn’t as strongly understood. The law struggles to catch up with current technology even now; how many regulations on artificial intelligence are enforced to ensure the rights of people are well-established? We have to prepare these debates for when technology keeps evolving faster than we could adjust.\nReferences\rJurassic Park (1993) - Quotes - IMDb [Internet]. [cited 2025 Oct 15]. Available from: https://www.imdb.com/title/tt0107290/quotes/ Kluger J. The Return of the Dire Wolf [Internet]. Time. 2025 [cited 2025 Oct 15]. Available from: https://time.com/7274542/colossal-dire-wolf/ Tankersley KB. Sheriden: A Clovis cave site in eastern North America. Geoarchaeology. 1997 Sep 1;12(6):713–24. Gregory L. Gedman, Kathleen Morrill Pirovich, Jonas Oppenheimer, Chaz Hyseni, Molly Cassatt-Johnstone, Nicolas Alexandre, William Troy, Chris Chao, Olivier Fedrigo, Savannah J. Hoyt, Patrick G.S. Grady, Sam Sacco, William Seligmann, Ayusman Dash, Mithil Chokshi, Laura Knecht, James B. Papizan, Tyler Miyawaki, Sven Bocklandt, James Kelher, Sara Ord, Audrey T. Lin, Brandon R. Peecook, Angela Perri, Mikkel-Holger S. Sinding, Greger Larson, Julie Meachen, Love Dalén, Bridgett vonHoldt, M Thomas P Gilbert, Christopher E. Mason, Rachel J. O’Neill, Elinor K. Karlsson, Brandi L. Cantarel, George R. R. Martin, George Church, Ben Lamm, Beth Shapiro. On the ancestry and evolution of the extinct dire wolf. bioXRiv [Internet]. 2025 Apr 11; Available from: https://doi.org/10.1101/2025.04.09.647074 Kluger J. The Science Behind the Return of the Dire Wolf [Internet]. Time. 2025 [cited 2025 Oct 15]. Available from: https://time.com/7275439/science-behind-dire-wolf-return/ Normile D. Chinese scientist who produced genetically altered babies sentenced to 3 years in jail [Internet]. [cited 2025 Oct 16]. Available from: https://www.science.org/content/article/chinese-scientist-who-produced-genetically-altered-babies-sentenced-3-years-jail Bt-Corn: What It Is and How It Works [Internet]. [cited 2025 Oct 16]. Available from: https://entomology.mgcafe.uky.edu/ef130 How did they make insulin from recombinant DNA? [Internet]. [cited 2025 Oct 16]. Available from: https://www.nlm.nih.gov/exhibition/fromdnatobeer/exhibition-interactive/recombinant-DNA/recombinant-dna-technology-alternative.html Loi P, Czernik M, Zacchini F, Iuso D, Scapolo PA, Ptak G. Sheep: The First Large Animal Model in Nuclear Transfer Research. Cellular Reprogramming. 2013 Oct;15(5):367. Chen C. Meet Cathy Tie, Bride of “China’s Frankenstein” [Internet]. MIT Technology Review. 2025 [cited 2025 Oct 16]. Available from: https://www.technologyreview.com/2025/05/23/1117373/cathy-tie-he-jiankui-china-crispr-x-twitter-feed/ L_. 武昌理工学院成立基因药物研究所 [Internet]. [cited 2025 Oct 16]. Available from: http://hb.people.com.cn/n2/2023/0909/c192237-40564107.html @CathyTie. Hello everyone, I wish to share that I have now relocated my base of operations to New York and, for a variety of both scientific and personal reasons, Jiankui and I will be pursuing separate paths. My professional and personal commitments are now rooted in North America, while Jiankui continues to contribute to the field of Chinese bioscience. I wish him every success in his endeavors. To support Jiankui in navigating this transition, I respectfully ask that he be given privacy and space, free from speculation or questioning, as he considers his next steps and seeks to return to laboratory science. This will be my only public statement on the matter. As for my own future, I remain committed to advancing the cause of science. In that spirit, I have made a modest gift to the scientists at Cold Spring Harbor Laboratory to support their groundbreaking work in molecular biology and their commitment to science in the service of humanity. I look forward to deepening my engagement with institutions that champion academic freedom and foster bold inquiry, wherever bright minds come together to ask the most fundamental questions. Cathy [Internet]. X (formerly Twitter). 2025 [cited 2025 Oct 16]. Available from: https://x.com/CathyTie/status/1948237638013530297 Barnett A. Blue-eyed, musical US physicist: sperm for sale, $500 a shot. The Guardian [Internet]. 2006 May 7 [cited 2025 Oct 17]; Available from: https://www.theguardian.com/uk/2006/may/07/freedomofinformation.politics Choe J, Shanks AL. In Vitro Fertilization. In: StatPearls [Internet]. StatPearls Publishing; 2023. Agnew M. Want a girl with blue eyes? Inside California’s VIP IVF industry [Internet]. The Sunday Times. 2024 [cited 2025 Oct 16]. Available from: https://www.thetimes.com/life-style/parenting/article/want-a-girl-with-blue-eyes-try-californias-fertility-clinics-zzfzhzgq9 Constantino AK. Trump announces efforts to expand access to IVF drugs [Internet]. CNBC. 2025 [cited 2025 Oct 17]. Available from: https://www.cnbc.com/2025/10/16/trump-announces-efforts-to-expand-access-to-ivf-drugs.html Jeff Amy, Associated Press, Geoff Mulvihill, Associated Press. Brain-dead woman must carry fetus to birth because of Georgia’s abortion ban, hospital tells family [Internet]. PBS News. 2025 [cited 2025 Oct 17]. Available from: https://www.pbs.org/newshour/nation/brain-dead-woman-must-carry-fetus-to-birth-because-of-georgias-abortion-ban-hospital-tells-family Burke M. Baby of brain-dead pregnant woman kept alive under abortion law has been delivered, family says [Internet]. NBC News. 2025 [cited 2025 Oct 17]. Available from: https://www.nbcnews.com/news/us-news/baby-brain-dead-pregnant-woman-kept-alive-abortion-law-delivered-famil-rcna213558 HAMMURABI�S CODE \u0026amp; BABYLONIAN LAW [Internet]. [cited 2025 Oct 17]. Available from: http://faculty.collin.edu/mbailey/hammurabi%27s%20code%20overview.htm Fanon F. A quote by Frantz Fanon [Internet]. [cited 2025 Oct 17]. Available from: https://www.goodreads.com/quotes/121169-to-speak-a-language-is-to-take-on-a-world Patel NH, Jadeja YD, Bhadarka HK, Patel MN, Patel NH, Sodagar NR. Insight into Different Aspects of Surrogacy Practices. Journal of Human Reproductive Sciences. 2018 Jul;11(3):212. Flickr F us on. What are some common complications of pregnancy? [Internet]. https://www.nichd.nih.gov/. [cited 2025 Oct 17]. Available from: https://www.nichd.nih.gov/health/topics/pregnancy/conditioninfo/complications Jones CR, Bergen BK. Large Language Models Pass the Turing Test [Internet]. 2025 [cited 2025 Oct 18]. Available from: http://arxiv.org/abs/2503.23674 Chatterji A, Cunningham T, Deming DJ, Hitzig Z, Ong C, Shan CY, et al. How People Use ChatGPT [Internet]. National Bureau of Economic Research; 2025 Sep [cited 2025 Oct 17]. Report No.: w34255. Available from: https://www.nber.org/system/files/working_papers/w34255/w34255.pdf Hu K. OpenAI hits $500 billion valuation after share sale to SoftBank, others, source says. 2025 Oct 2; Available from: https://www.reuters.com/technology/openai-hits-500-billion-valuation-after-share-sale-source-says-2025-10-02/ Kerr D. Elon Musk’s xAI accused of pollution over Memphis supercomputer. The Guardian [Internet]. 2025 Apr 25 [cited 2025 Oct 17]; Available from: https://www.theguardian.com/technology/2025/apr/24/elon-musk-xai-memphis Chow AR. “We Are the Last of the Forgotten:” Inside the Memphis Community Battling Elon Musk’s xAI. TIME [Internet]. 2025 Aug 13; Available from: https://time.com/7308925/elon-musk-memphis-ai-data-center/ Smirnova L, Caffo BS, Gracias DH, Huang Q, Morales Pantoja IE, Tang B, et al. Organoid intelligence (OI): the new frontier in biocomputing and intelligence-in-a-dish. Front Sci. 2023 Feb 28;1:1017235. Wu Z, Liu Z, Lin J, Lin Y, Han S. Lite Transformer with Long-Short Range Attention [Internet]. 2020 [cited 2025 Oct 19]. Available from: http://arxiv.org/abs/2004.11886 Kim J, Ricci M, Serre T. Not-So-CLEVR: learning same–different relations strains feedforward neural networks. Interface Focus [Internet]. 2018 Aug 6 [cited 2025 Oct 19]; Available from: https://royalsocietypublishing.org/doi/10.1098/rsfs.2018.0011 Fleuret F, Li T, Dubout C, Wampler EK, Yantis S, Geman D. Comparing machines and humans on a visual categorization test. Proceedings of the National Academy of Sciences of the United States of America [Internet]. 2011 Oct 25 [cited 2025 Oct 19];108(43). Available from: https://pubmed.ncbi.nlm.nih.gov/22006295/ Graham M, Cant C. Meet Mercy and Anita – the African workers driving the AI revolution, for just over a dollar an hour. The Guardian [Internet]. 2024 Jul 6 [cited 2025 Oct 17]; Available from: https://www.theguardian.com/technology/article/2024/jul/06/mercy-anita-african-workers-ai-artificial-intelligence-exploitation-feeding-machine Stahl L, Chasan A. Kenyan workers with AI jobs thought they had tickets to the future until the grim reality set in [Internet]. CBS News. 2024 [cited 2025 Oct 17]. Available from: https://www.cbsnews.com/news/ai-work-kenya-exploitation-60-minutes/ Brittain B. OpenAI copyright lawsuits from authors, New York Times consolidated in Manhattan. Reuters [Internet]. 2025 Apr 4; Available from: https://www.reuters.com/legal/litigation/openai-copyright-lawsuits-authors-new-york-times-consolidated-manhattan-2025-04-03/ De Cosmo L. Google Engineer Claims AI Chatbot Is Sentient: Why That Matters [Internet]. Scientific American. 2022 [cited 2025 Oct 20]. Available from: https://www.scientificamerican.com/article/google-engineer-claims-ai-chatbot-is-sentient-why-that-matters/ Pataranutaporn P, Karny S, Archiwaranguprok C, Albrecht C, Liu AR, Maes P. “My Boyfriend is AI”: A Computational Analysis of Human-AI Companionship in Reddit’s AI Community [Internet]. 2025 [cited 2025 Oct 17]. Available from: http://arxiv.org/abs/2509.11391 Anguiano D. AI lovers grieve loss of ChatGPT’s old model: “Like saying goodbye to someone I know.” The Guardian [Internet]. 2025 Aug 22 [cited 2025 Oct 17]; Available from: https://www.theguardian.com/technology/2025/aug/22/ai-chatgpt-new-model-grief Wong M. The Most Reviled Tech CEO in New York Confronts His Haters [Internet]. The Atlantic. 2025 [cited 2025 Oct 19]. Available from: https://www.theatlantic.com/technology/2025/10/friend-ai-companion-ads/684451/ Witte R. New Yorkers Are Defacing This AI Startup’s Million-Dollar Ad Campaign [Internet]. Futurism. 2025 [cited 2025 Oct 19]. Available from: https://futurism.com/artificial-intelligence/million-dollar-ai-campaign-defaced Botstein D, Fink GR. Yeast: An Experimental Organism for 21st Century Biology. Genetics. 2011 Nov;189(3):695. A spotlight on global collaboration in the Sc2.0 yeast consortium. Cell Genomics. 2023 Nov 8;3(11):100441. New project to pioneer the principles of human genome synthesis [Internet]. Wellcome. 2025 [cited 2025 Oct 18]. Available from: https://wellcome.org/insights/articles/new-project-pioneer-principles-human-genome-synthesis Ghosh P. Synthetic Human Genome Project gets go ahead. BBC News [Internet]. 2025 Jun 26 [cited 2025 Oct 18]; Available from: https://www.bbc.com/news/articles/c6256wpn97ro ","date":"21 October 2025","externalUrl":null,"permalink":"/articles/20251021/","section":"Articles","summary":"The future is now: this essay examines current and future developments in biology and why ethical considerations are an utmost concern.","title":"A case for a prioritisation of bioethics","type":"articles"},{"content":"","date":"21 October 2025","externalUrl":null,"permalink":"/tags/bioethics/","section":"Tags","summary":"","title":"Bioethics","type":"tags"},{"content":"","date":"13 October 2025","externalUrl":null,"permalink":"/tags/health/","section":"Tags","summary":"","title":"Health","type":"tags"},{"content":"Available on Substack\nA hidden pandemic has gripped the world. More than a billion people are sick. 1 It spreads with no agent nor pathogen. No vaccine nor cure exists for this pandemic and no single factor can determine the outcome of this disease. Some people deny having it. Some people will die from it. It is one of the leading causes of disability. 2\nIt sounds like zombie fiction, but this is the truth for mental illnesses. Anxiety and depression are the most common types with severe cases leading to suicide, one of the biggest killers of 20-35 year olds. Governments are criticised for their lack of action to mitigate this problem with median government spending at around 2% of their health budgets. 3 This is compensated with people-powered movements pushing for awareness and prevention. It seems unavoidable nowadays to scroll through social media without seeing a post about mental health awareness or something adjacent. But the reverse is also true; the prevalence of mental illnesses led to fetishizing tropes such as menhera girls, a Japanese subculture that sports self-injury scars with pride.\nRegardless, the image of mental health often evokes a gray picture of a young woman (women are more severely impacted by mental illness) with razor blades close at hand or a hand shoved down their throat. This is true with menhera girls. Other popular depictions are less obvious. An example is Hannah Baker, a highschooler who committed suicide in the problematic TV show 13 Reasons Why.\nFictional character Hannah Baker from 13 Reasons Why. The show was a major source of controversy due to Hannah’s very explicit suicide scene. The scene was edited after release. 4 © Netflix\r#\rYou might have heard this term: “mental illness is invisible”. Invisibility is an apt term. Self-harm scars can clearly indicate some issues converging towards mental illness. Its absence, however, does not eliminate the possibility that some mental illness does not exist. Hannah Baker wears long sleeves that conceal longitudinal scars, and the picture clearly shows a young woman and not much else. No cuts mar her face, and her face is remarkably flushed with no hints of paleness. There are no pustules or missing limbs. Removed from any context about the show, she looks remarkably and paradoxically healthy. Physically, that is.\nReality has its paradox. Mental health is an illness, yet it doesn’t have any clear, definable cause. You cannot test it with Koch’s postulates; it is impossible to accurately measure the depression and anxiety levels of a test organism. 5 Yet there are medicines ready to treat mental disorders. At the same time, some treatments are fickle and can vary in effectiveness from person to person. SSRIs, the most common antidepressant prescription, can both increase and decrease suicidal tendencies. 6 How come?\nYou can argue that mental illnesses are mental illnesses. They exist separately from physical illnesses and that usual methods designed to diagnose and treat mental illnesses don’t apply. You could take this argument one step further, say that the actual cure for mental illness is to “live well” and nobody who takes medicine ever needed them anyway. If it exists outside the realm of the physical, why should it follow its rules?\nBut to separate the mental and the physical requires a degree of faith. It assumes that feelings operate separately from the brain, a physical organ made of flesh. It assumes that feelings come from the soul, which is an entirely different theological debate. That explanation does not satisfy scientists so they conducted studies to try to find the pathophysiology (the biochemical or pathogenic cause) that underlie mental illnesses like autism, depression and anxiety.\nOne could argue that you could cure mental illness through living well and maintaining discipline. This claim could be true, but its implications must be evaluated. Are you still assuming it isn’t a “real illness” hence it could be easily “taken care of”? You must reframe your thinking if you assume being sated and happy immediately cures mental illness, but you must also reframe your thinking if being sated and happy doesn’t affect mental illness. Living well might include exercise, but exercise doesn’t improve mental health because it makes you happier, it improves your mental health because it affects your biochemical processes. 7 Eating well doesn’t just make you happier, it ensures you obtain the nutrients you need, and this is especially important in depression which is linked to vitamin deficiencies. 8\nA common theory that people have considered, aside from vitamin deficiencies, is that most mental illnesses are dysregulations of certain hormones in the body. If dopamine is the happy hormone, depressed people must be lacking it. The dopamine theory lacks some consistency with depression, 9 but irregular adrenaline seems to have an effect on people with PTSD. 10, 11 Anxiety seems to be related to cortisol; those with higher risks of anxiety shows similar patterns when their bodies are releasing cortisol. 12\nThis seems to be the working theory and is the basis of many medications nowadays, but the variance in the effects seem like our theory isn’t enough to cover the extremely broad subject of mental illnesses. What other factors are at play that make this theory work sometimes, but not always?\nYou’re not alone\r#\rIt may comfort a person with depression to tell them they aren’t alone. They aren’t alone in the context of other people experiencing depression, in the context that they still have people around them who care about them. It’s true, you are never alone. But not in that sense. You have trillions of living things dwelling inside your gut, numerous different species who call your insides their home. These could dwell there silently and not have any significance to you, but they could also help you digest foods that are difficult for you to digest. Or so you think.\nThe gut microbiota’s recent place in research is a realm of intrigue and adventure. Identical twins could have an identical set of DNA but vastly different species of gut microbiota. Whether you were born through a caesarean section or not will affect your gut microbiota. How long you sleep and when you sleep matters too. Most importantly, it is also affected by diet.\nThe gut microbiota might seem like a farfetched case compared to our previous discussions about mental disorders. But the gut plays a bigger role than you think. As bacteria, fungus and viruses go about their microscopic lives, they inadvertently release chemicals akin to sweat that naturally rests on human skin. These chemicals can communicate with the immune cells in the body. 13 In fact, it communicates with the human’s “second brain” which is the enteric nervous system, an entire nervous system located in the abdomen. 14\nWhile it makes sense that there is a nervous system dedicated for digestion, it starts to sound like fantasy that the gut microbiota could influence the nervous system and cause mental illnesses. Yet, this is a possibility worth exploring in science that does not yield empty results. Numerous studies have proven that the microbiota are linked to depression, anxiety, autism spectrum disorder (ASD), schizophrenia, bipolar disorder and ADHD. 15 People with depression have less Bacteroidetes in their gut while people with bipolar disorder seem to have four times less Clostridiaceae that ferments carbohydrates compared to people without bipolar disorder. There are more Actinobacteria in people with ADHD. 16\nTo some scientists, they can’t agree whether the microbiota caused the illness or the illness caused the microbiota. It may seem a more obvious conclusion that the latter makes more sense. Yet, in the case of ADHD, the microbiome seems to be capable of producing a component that allows for more production of dopamine. 17 Additionally, when you transfer the microbiota content of depression to a healthy organism, they start to exhibit depression-like symptoms.18 It seems that the obvious conclusion isn’t so obvious after all.\nSometimes you’re born with it\r#\rYou’ve heard of this on TV: “I got his DNA from his hair!” But what is DNA? A lot of people can’t answer beyond it being something unique that everyone has. Scientifically, DNA is a macromolecule. It is a small molecule that is large by chemistry standards. Meaning, you can’t see it with your naked eye, but it’s made up of millions of elements that is a mixed bag of carbon, nitrogen, hydrogen and oxygen. Every living part of your body has this, and what’s even more great is that it contains the instructions for your body to do the things it needs you to do. You have genes, short instructions, who will tell your body things like it should ensure your eye color is brown or another color.\nYou cannot change your genes; it is inherited to you from your parents. Genes seem to determine a lot of physical characteristics, but a lot of mental characteristics seem to have a link towards genes as well. This might seem deterministic. If my parents have given me the genes for introversion, does that mean I’m doomed to remain tragically a hermit? It sounds like genes remove any sort of individual agency. “My genes made me do it!” says a man in court during trial for murder. Luckily, there are more factors at play than just dealing with the genes you were dealt with. Genes could be silenced or overexpressed, depending on the situation and environment. Obviously, genes for growth wouldn’t be active throughout your entire life and at some point after puberty, your height will remain tragically the same.\nA lot of diseases have been attributed to genes. Diabetes, for example, has been attributed to hundreds of seemingly unrelated genes who, when malfunctioning, seems to increase the chances you develop type 2 diabetes. 19 If we want to treat mental illnesses the same, it appears that it is possible to attribute some genes to mental illnesses.\nYou may have heard this piece of interesting news: the man who discovered he was a psychopath 20. Psychopathy has long retained its reputation in media as evil, irredeemable villains beyond the understanding of guileless protagonists. In reality, psychopathy in a clinical context refers to “antisocial” behaviour from a lack of empathy to egocentric traits. While these traits might seem horrifying, these traits aren’t damning, as James H. Fallon, the neuroscientist who found he was a psychopath, leads an entirely normal life. That is, if normal includes starring in numerous documentaries and obtaining an acting role in Criminal Minds.\nJames H. Fallon, a neuroscientist who discovered his genetic disposition towards psychopathy. He proceeded to star in TV shows talking about his discovery. He has no criminal record. © IMDB\r#\rWhile Fallon admitted to some low empathy behaviour, he has no inclinations towards violence. He attributed this to a happy childhood and supportive environment, which destroyed any potential of genetic determinism taking hold of his life.\nRegardless, while genetics doesn’t always determine that you must definitely have mental disorders, it does change the odds of it. Autism, for example, is associated with 800 genes, and 50% of ASD individuals have one of these: another syndrome that may cause their autism, a single gene being mutated, or a problem with their chromosomes (that is, either a huge chunk of DNA is missing or a chunk of DNA keeps repeating itself through some error). 21 Meanwhile, ADHD has a very high heritability of 74%, meaning it has a 74% chance of being caused by the individual’s genetics. 22 Different types of depression can appear when genetics, environment, and the brain you were born with, encounters problems and the balance they maintain is disrupted. 23\nThe role of… immunity?\r#\rGenes often are given names that sound like code names. NCKAP1, for example, is a gene that helps regulate development of neurons. Apparently, a mutation, or a change, in NCKAP1 that affects its function, can cause autism-like symptoms to appear. 24 Yet, if you were to search NCKAP1 on the internet, a lot of it is about its role in cancer. What’s more, you might find something about the other function of the gene, which is to modulate, or control, some aspects of the immune system.\nA very controversial claim was made once, and would affect paranoid mothers forever everywhere: the claim that vaccines cause autism. The paper that first published this was retracted, partly due to the fear it nurtured towards vaccines, but mostly because the paper had a huge conflict of interest due to the writer receiving funding from parents who were in the midst of suing a pharmaceutical company. He intentionally selected children to manipulate the results of the study. 25\nVaccines work by inserting a very weakened version of a disease agent into a patient, whose body will recognise and allow the immune system to be trained to be able to prevent diseases when encountering truly dangerous diseases. At its core, the immune system’s entire schtick is to recognise and eliminate. Errors in the immune system could be something like it being too weak to fight off infections, or it being too strong that it starts fighting the body instead.\nWhile the paper is retracted, there still exists a link between the immune system and mental illnesses. Depression was linked to the body’s response to infection. 26, 27 Surely, it makes sense evolutionary-wise: first, your body is infected with disease; next, you develop depression with a higher chance of isolating your body from other human contact to prevent infecting other people and spreading the disease.\nBut what about other mental disorders like schizophrenia? Still, another immune dysfunction. A study replaced a schizophrenic patient’s bone marrow and the patient was cured from schizophrenia. The bone marrow is the maturation site of a lot of immune cells. This means that you could treat schizophrenia by treating the immune system. 28 Autism was also linked to a dysfunctional immune system, and studies proved this from taking blood and fluid from the spine. 29\nSo, what is the conclusion?\r#\rIs it the gut, the genes, the immune system, or the environment? In the end, it’s all of them. Depression, for example, is caused by all four. 30 Meaning, a lot of things had to go wrong for it to develop. This article doesn’t even cover how depression increases for people who have heart disease, 31 or how sex differences can cause different symptoms of ADHD to manifest and may or may not be due to sex-specific hormones. 32 The field of mental illnesses is rapidly developing, and to dismiss all mental illnesses to be anything below a systemic illness that involves the physical body is graciously uninformed. There is no separation between the mental and physical, all of that is a false dichotomy.\nReferences\rMental health [Internet]. [cited 2025 Oct 13]. Available from: https://www.who.int/news-room/fact-sheets/detail/mental-health-strengthening-our-response Lopez AD, Murray CC. The global burden of disease, 1990-2020. Nature medicine [Internet]. 1998 Nov [cited 2025 Oct 13];4(11). Available from: https://pubmed.ncbi.nlm.nih.gov/9809543/ Over a billion people living with mental health conditions – services require urgent scale-up [Internet]. [cited 2025 Oct 13]. Available from: https://www.who.int/news/item/02-09-2025-over-a-billion-people-living-with-mental-health-conditions-services-require-urgent-scale-up BBC News. 13 Reasons Why: Netflix removes suicide scene from season one. BBC News [Internet]. 2019 Jul 16 [cited 2025 Oct 13]; Available from: https://www.bbc.com/news/entertainment-arts-49001246 Berton O, Nestler EJ. New approaches to antidepressant drug discovery: beyond monoamines. Nature Reviews Neuroscience [Internet]. 2006 Feb [cited 2025 Oct 13];7(2):137–51. Available from: https://www.nature.com/articles/nrn1846 Reeves RR, Ladner ME. Antidepressant‐Induced Suicidality: An Update. CNS Neuroscience \u0026amp; Therapeutics [Internet]. 2010 Jun 11 [cited 2025 Oct 13];16(4):227. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC6493906/ Kandola A, Ashdown-Franks G, Hendrikse J, Sabiston CM, Stubbs B. Physical activity and depression: Towards understanding the antidepressant mechanisms of physical activity. Neuroscience and biobehavioral reviews [Internet]. 2019 Dec [cited 2025 Oct 13];107. Available from: https://pubmed.ncbi.nlm.nih.gov/31586447/ Zielińska M, Łuszczki E, Dereń K. Dietary Nutrient Deficiencies and Risk of Depression (Review Article 2018–2023). Nutrients [Internet]. 2023 May 23 [cited 2025 Oct 13];15(11):2433. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC10255717/ Delgado PL. Depression: the case for a monoamine deficiency. The Journal of clinical psychiatry [Internet]. 2000 [cited 2025 Oct 13];61 Suppl 6. Available from: https://pubmed.ncbi.nlm.nih.gov/10775018/ Gazarini L, Stern CA, Takahashi RN, Bertoglio LJ. Interactions of Noradrenergic, Glucocorticoid and Endocannabinoid Systems Intensify and Generalize Fear Memory Traces. Neuroscience [Internet]. 2022 Aug 10 [cited 2025 Oct 13];497. Available from: https://pubmed.ncbi.nlm.nih.gov/34560200/ Persike DS, Al-Kass SY. Challenges of post-traumatic stress disorder (PTSD) in Iraq: biochemical network and methodologies. A brief review. Hormone molecular biology and clinical investigation [Internet]. 2020 Nov 6 [cited 2025 Oct 13];41(4). Available from: https://pubmed.ncbi.nlm.nih.gov/33155990/ Fiksdal A, Hanlin L, Kuras Y, Gianferante D, Chen X, Thoma MV, et al. Associations between symptoms of depression and anxiety and cortisol responses to and recovery from acute stress. Psychoneuroendocrinology [Internet]. 2019 Apr [cited 2025 Oct 13];102. Available from: https://pubmed.ncbi.nlm.nih.gov/30513499/ Cryan JF, O’Riordan KJ, Cowan CSM, Sandhu KV, Bastiaanssen TFS, Boehme M, et al. The Microbiota-Gut-Brain Axis. Physiological reviews [Internet]. 2019 Oct 1 [cited 2025 Oct 13];99(4). Available from: https://pubmed.ncbi.nlm.nih.gov/31460832/ Young E. Gut instincts: The secrets of your second brain [Internet]. New Scientist. 2012 [cited 2025 Oct 13]. Available from: https://www.newscientist.com/article/mg21628951-900-gut-instincts-the-secrets-of-your-second-brain/ Katarzyna Socała, Urszula Doboszewska, Aleksandra Szopa, Anna Serefko, Marcin Włodarczyk, Anna Zielińska, Ewa Poleszak, Jakub Fichna, Piotr Wlaź. The role of microbiota-gut-brain axis in neuropsychiatric and neurological disorders. Pharmacological Research [Internet]. 2021 Oct 1 [cited 2025 Oct 13];172:105840. Available from: http://dx.doi.org/10.1016/j.phrs.2021.105840 Góralczyk-Bińkowska A, Szmajda-Krygier D, Kozłowska E. The Microbiota–Gut–Brain Axis in Psychiatric Disorders. International Journal of Molecular Sciences [Internet]. 2022 Sep 24 [cited 2025 Oct 13];23(19):11245. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC9570195/ Aarts E, Ederveen THA, Naaijen J, Zwiers MP, Boekhorst J, Timmerman HM, et al. Gut microbiome in ADHD and its relation to neural reward anticipation. PloS one [Internet]. 2017 Sep 1 [cited 2025 Oct 13];12(9). Available from: https://pubmed.ncbi.nlm.nih.gov/28863139/ Chang L, Wei Y, Hashimoto K. Brain-gut-microbiota axis in depression: A historical overview and future directions. Brain research bulletin [Internet]. 2022 May [cited 2025 Oct 13];182. Available from: https://pubmed.ncbi.nlm.nih.gov/35151796/ Shojima N, Yamauchi T. Progress in genetics of type 2 diabetes and diabetic complications. Journal of diabetes investigation [Internet]. 2023 Apr [cited 2025 Oct 13];14(4). Available from: https://pubmed.ncbi.nlm.nih.gov/36639962/ Fallon J. How I discovered I have the brain of a psychopath. The Guardian [Internet]. 2014 Jun 2 [cited 2025 Oct 13]; Available from: https://www.theguardian.com/commentisfree/2014/jun/03/how-i-discovered-i-have-the-brain-of-a-psychopath Genovese A, Butler MG. The Autism Spectrum: Behavioral, Psychiatric and Genetic Associations. Genes [Internet]. 2023 Mar 9 [cited 2025 Oct 13];14(3). Available from: https://pubmed.ncbi.nlm.nih.gov/36980949/ Faraone SV, Larsson H. Genetics of attention deficit hyperactivity disorder. Molecular Psychiatry [Internet]. 2018 Jun 11 [cited 2025 Oct 13];24(4):562. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC6477889/ Tassi E, Pigoni A, Turtulici N, Colombo F, Fortaner-Uyà L, Bianchi AM, et al. Gene–environment–brain topology reveals clinical subtypes of depression in UK Biobank. Scientific Reports [Internet]. 2025 Oct 10 [cited 2025 Oct 13];15(1):1–20. Available from: https://www.nature.com/articles/s41598-025-19624-0 Guo H, Zhang Q, Dai R, Yu B, Hoekzema K, Tan J, et al. NCKAP1 Disruptive Variants Lead to a Neurodevelopmental Disorder with Core Features of Autism. American Journal of Human Genetics [Internet]. 2020 Nov 5 [cited 2025 Oct 13];107(5):963. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC7674997/ Eggertson L. Lancet retracts 12-year-old article linking autism to MMR vaccines. CMAJ : Canadian Medical Association Journal [Internet]. 2010 Feb 4 [cited 2025 Oct 13];182(4):E199. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC2831678/ Yirmiya R. The inflammatory underpinning of depression: An historical perspective. Brain, behavior, and immunity [Internet]. 2024 Nov [cited 2025 Oct 13];122. Available from: https://pubmed.ncbi.nlm.nih.gov/39197544/ Dantzer R, O’Connor JC, Freund GG, Johnson RW, Kelley KW. From inflammation to sickness and depression: when the immune system subjugates the brain. Nature reviews Neuroscience [Internet]. 2008 Jan [cited 2025 Oct 13];9(1). Available from: https://pubmed.ncbi.nlm.nih.gov/18073775/ Jayakumar J, Ginjupalli M, Kalaivani BA, Rajarajan S, Jakkam SM. Schizophrenia and Bone Marrow Disorders: An Emerging Clinical Association. Cureus [Internet]. 2024 Dec 16 [cited 2025 Oct 13];16(12). Available from: https://pubmed.ncbi.nlm.nih.gov/39816323/ Robinson-Agramonte MLA, Noris GE, Fraga GJ, Vega HY, Antonucci N, Semprún-Hernández N, et al. Immune Dysregulation in Autism Spectrum Disorder: What Do We Know about It? International journal of molecular sciences [Internet]. 2022 Mar 11 [cited 2025 Oct 13];23(6). Available from: https://pubmed.ncbi.nlm.nih.gov/35328471/ Reyes-Martínez S, Segura-Real L, Gómez-García AP, Tesoro-Cruz E, Constantino-Jonapa LA, Amedei A, et al. Neuroinflammation, Microbiota-Gut-Brain Axis, and Depression: The Vicious Circle. Journal of integrative neuroscience [Internet]. 2023 May 8 [cited 2025 Oct 13];22(3). Available from: https://pubmed.ncbi.nlm.nih.gov/37258450/ Kozdağ G, Yaluğ İ, İnan N, Ertaş G, Selekler M, Kutlu H, et al. Major depressive disorder in chronic heart failure patients: Does silent cerebral infarction cause major depressive disorder in this patient population? Turk Kardiyoloji Dernegi arsivi : Turk Kardiyoloji Derneginin yayin organidir [Internet]. 2015 Sep [cited 2025 Oct 13];43(6). Available from: https://pubmed.ncbi.nlm.nih.gov/26363742/ Nussbaum NL. ADHD and female specific concerns: a review of the literature and clinical implications. Journal of attention disorders [Internet]. 2012 Feb [cited 2025 Oct 13];16(2). 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