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Facebook X (Twitter) WhatsApp LinkedIn Pinterest Copy link A primer on the Mutualism theory of general intelligence A new theory suggests intelligence develops through reciprocal interactions between abilities Introduction One of the most replicated findings in psychology is that if a sufficiently large and diverse battery of cognitive tests is administered to a representative sample of people, an all-positive correlation matrix will be produced. For a century, psychometricians have explained this occurrence by proposing the existence of g, a latent biological variable that links all abilities. G is statistically represented by the first factor derived from a correlation matrix using a method called factor analysis, which reduces the dimensionality of data into clusters of covariance between tests called factors. Early critics of g pointed out that nothing about the statistical g-factor required the existence of a real biological factor and that the overlap of uncorrelated mental processes sampled by subtests was sufficient. While the strength of correlations between subtests does generally correspond to intuitive beliefs about processes shared between them, this is not universally the case, and for this reason, sampling theory has never seen widespread acceptance. A new theory called mutualism has been proposed that explains the positive manifold without positing the existence of g. In mutualism the growth of abilities is coupled, meaning improvement in one domain causes growth in another, inducing correlations between abilities over time. The authors of the introductory paper demonstrated in a simulation that when growth in abilities is coupled the interaction between baseline ability, growth speed and limited developmental resources is sufficient to create a statistical general factor from abilities that are initially uncorrelated, offering a novel explanation for why abilities like vocabulary that are ‘inexpensive’ in terms of developmental resources explain the most variance in other abilities. Empirical evidence In the field of intelligence, mutualism has been tested twice among neurotypical children in the lab and once in a naturalistic setting with data from a gamified maths revision platform. Alongside these, a lone study exists comparing coupling in children with a language disorder and neurotypical children, however methodological issues related to attrition preclude it from discussion here. All studies used latent change score modelling (LCSM) to compare competing models of how intelligence develops over time. LCSM is a subset of structural equation modelling in which researchers compare the discrepancy between models of proposed causal connections between variables and their values in the real data using model fit indices. Three parameters resembling those used in the introductory paper’s simulations were used to represent causal connections between variables: the change score - wave #2 score minus wave #1 score of the same ability, the self-feedback parameter – the regression coefficient of baseline ability on the change score of the same ability and the coupling effect parameter – the regression coefficient of one ability at wave #1 on the change score of the other ability. The following models were compared: the g-factor model defined by the absence of coupling and growth driven by change in the g-factor, the investment model defined by coupling from matrix reasoning to vocabulary and the mutualism model defined by bidirectional coupling. Mutualism in the lab The first two lab studies investigated coupling between vocabulary and matrix reasoning in samples of 14-25 year olds and 6-8 year olds respectively. The mutualism model showed the best model fit in both studies albeit less decisively in the three wave younger sample, suggesting the stronger model fit of the first study may have been an artefact of regression to the mean. I think it’s problematic to interpret this as empirical support for mutualism due to issues that follow from only using two abilities. A g-factor extracted from two abilities may reflect specific non-g variance shared between tests as much as it does common variance caused by g. Adding to this ambiguity is the fact that the correlations between the change scores of the two tests after controlling for coupling and self-feedback effects were positive, reflecting the influence of an unmodelled third variable, be that g or unmeasured coupling. Another problematic feature of the studies comes from their model specification of the g-factor as being without coupling. This is despite the fact no latent change score modelling study of childhood development has ruled out that g may develop in a coupled or partially coupled manner. Studies using the methodology to study cognitive ageing have shown that some abilities are coupled whereas others are not suggesting that only sampling abilities that do show coupling may lead to a biassed comparison. Mutualism in the classroom Mutualism showed a marginally better fit than the investment model in explaining the development of counting, addition, multiplication and division over three years in a study featuring a sample of 12,000 Dutch 6-10 year olds using the revision platform Mathgarden. The change scores of each ability showed strong correlations after controlling for coupling and self-feedback effects. When considered in relation to the good model fit of the investment model, I believe this may reflect the standardised effect of the curriculum on the development of abilities independent of coupling and baseline ability. A finding with negative implications for mutualism from this study is the fact that the number of games played was not associated with any greater strength in coupling. This could reflect that coupling is a passive mechanism of development with little environmental input but it could equally reflect sorting of high ability students into a niche combined with self-feedback effects of their baseline ability impeding coupling. To observe the causal effect of effort on coupling after controlling for cognitive aging and the tendency of high ability people to train harder a randomised control trial of cognitive training is needed. Cognitive training Unfortunately, no cognitive training study has used latent change score modelling, meaning coupling must be inferred from the presence of far transfer (gains on untrained abilities), rather than directly estimated. COGITO’s youth sample resembled the first lab study to test mutualism in its age range and choice of fluid reasoning as a far transfer measure. Participants underwent 100 days of hour-long training sessions of working memory, processing speed and episodic memory. The authors found no near or far transfer gains for working memory and processing speed, possibly indicating developmental limits on their improvement. However, moderate effect sizes were found for fluid reasoning and episodic memory. The study’s results are lacklustre and developmentally bound but they offer an example of experimentally induced far transfer in a literature – in which it is a rarity – leaving open the possibility that the coupling effects observed in the lab studies were not mere passive effects of development. In contrast to COGITO which targeted young people at the tail end of their cognitive development, the Abecedarian Project started almost as soon as the subjects were born. Conceived of as a pre-school intervention to improve the educational outcomes of African Americans in North Carolina, the Abecedarian Project consisted of an experimental group that received regular guided educational play for infants aimed at building early language and a control condition which only received nutritional supplementation. At the entry of primary school, the experimental group showed a 7 point difference in IQ, which persisted in a diminished capacity at 4.4 IQ points by age 21. In contrast to previous early life interventions, in cognitive training studies and studies on the cognitive outcomes of adoption the gains were domain general rather than improvements on specific abilities. This provides causal evidence that if interventions are sufficiently early and target highly g-loaded abilities such as vocabulary they can induce cascades of domain-general improvement, a finding in line with the predictions of mutualism. It would be unfair to end this segment without mentioning perhaps the most standardised cognitive training regime there is: schooling. The causal effect of a year of schooling on IQ can be teased apart from the developmental effects of ageing by using a method called regression discontinuity analysis. In this method, the distance of a student’s birthday from the year cutoff for two year groups is used as a predictor variable alongside the school year in a multiple regression predicting IQ. A recent paper reanalysing data from a study using this method found that the subtest gains from a year of schooling showed a moderate negative correlation with their g loading. As mutualism states that g develops through coupling, this would lend credence to the view that coupling effects are passive mechanisms of g’s development rather than being inseparable from experience. Conclusion I believe that it’s more accurate to say there is evidence for coupling effects than it is to say there is evidence for mutualism. There is convergent evidence from a year of schooling effect, coupling effects not rising with the amount of maths games played and the COGITO intervention’s results that the environment has little causal role in coupling effects and their strength. Opposing evidence comes from the Abecedarian Project, however this is not an environmental stimulus to which most people will be exposed to. Therefore, more weight should be placed on the effects of a year of schooling because it is generalisable. To reconcile this conflicting evidence, future authors should seek to replicate the COGITO intervention in an early adolescent identical twin sample with co-twin controls. This would allow researchers to observe coupling effects while executive functions are still in development and give them a more concrete understanding of the self-feedback parameter grounded in developmental cascades of gene expression. A more readily available alternative would be to apply latent change score modelling to the Abecedarian Project dataset. I will end with a quote from a critic of mutualism, Gilles Gignac: I conclude with the suggestion that belief in the plausibility of the g factor (or mutualism) may be impacted significantly by individual differences in personality, attitudes, and worldviews, rather than rely strictly upon logical and/or empirical evidence. As the current evidence stands, this may be true, but with the availability of new developmental studies such as the Adolescent Brain Cognitive Development study and old ones like the Louisville twin study there’s less of an excuse than ever. Written by James Howarth Related article: Nature vs nurture in childhood intelligence REFERENCES Carroll, J. B. (1993). Human cognitive abilities: A Survey of Factor-Analytic Studies . Cambridge University Press Rindermann, H., Becker, D., & Coyle, T. R. (2020). Survey of expert opinion on intelligence: Intelligence research, experts’ background, controversial issues, and the media. Intelligence , 78 , 101406. https://doi.org/10.1016/j.intell.2019.101406 Spearman, C. (1904). “General intelligence,” objectively determined and measured. The American Journal of Psychology , 15 (2), 201. https://doi.org/10.2307/1412107 Thomson, G. H. (1916). A hierarchy without a general factor. British Journal of Psychology 1904-1920 , 8 (3), 271–281. https://doi.org/10.1111/j.2044-8295.1916.tb00133.x Jensen, A. R. (1998). The g factor: The science of mental ability. Praeger Publishers/Greenwood Publishing Group Van Der Maas, H. L. J., Dolan, C. V., Grasman, R. P. P. P., Wicherts, J. M., Huizenga, H. M., & Raijmakers, M. E. J. (2006). A dynamical model of general intelligence: The positive manifold of intelligence by mutualism. Psychological Review, 113 (4), 842–861. https://doi.org/10.1037/0033-295X.113.4.842 Johnson, W., Nijenhuis, J. T., & Bouchard, T. J. (2008). Still just 1 g: Consistent results from five test batteries. Intelligence , 36 (1), 81–95. https://doi.org/10.1016/j.intell.2007.06.001 Project Gallery

Facebook X (Twitter) WhatsApp LinkedIn Pinterest Copy link What does depression do to your brain? Also known as Major Depressive Disorder (MDD) This is Article 1 in a series on depression and the brain. Next article coming soon. -- I affect 3.8% of the population wide, With 280 million voices struggling inside. In women, my reach is 6%, And 5.7% of those over 60 feel me. Among new mothers, I reach 10%, With over 700,000 lost to my torment each year. What am I? Depression. The most prevalent psychiatric disorder that costs both money and lives. -- Also known as Major Depressive Disorder (MDD), depression is a heterogenous disease, which means the manifestation of the disorder is influenced by multiple genes. It is commonly known that consistent low mood, loss of interest in hobbies you used to enjoy, lethargy, feeling of hopelessness etc. are physical symptoms of depression. However, have you ever wondered what happens in the brain in a depression sufferer, from the neuroscience aspect? Structurally, research into the neuroscience of depression reveals significant structural abnormalities in the brains of affected individuals. Studies using structural magnetic resonance imaging (MRI) have shown that those with MDD show reductions in gray matter volume in regions responsible for emotion regulation. The limbic system of the brain is responsible for producing and regulating emotions. In depressed individuals, the hippocampus—a key component of the limbic system—shows reduced gray matter volume, which is linked to abnormalities in the associated white matter tracts. White matter consists of myelinated axons that facilitate communication between different brain regions, while grey matter contains the neuronal cell bodies responsible for processing information. The presence of abnormalities in white matter suggests a disconnection between regions within the limbic system, potentially impairing their ability to communicate effectively. This disconnection may contribute to the emotional dysregulation observed in depression, highlighting the intricate relationship between grey and white matter in the pathology of this disorder. Depression is a complex disorder that not only affects mood but changes the structure and function of the brain. By understanding the neurobiological changes—including reductions in grey matter and white matter disconnections—we can better grasp the pathogenesis of this condition. Continued research in the neuroscience behind depression is essential for developing more effective treatments. There is still much more to explore and understand in depression research; with each new discovery, we realise how much more there is to learn. Written by Chloe Kam Related article: Depression in children Project Gallery

Facebook X (Twitter) WhatsApp LinkedIn Pinterest Copy link Immune signals initiated by chromosomal instability lead to metastasis Non-cell-autonomous cancer progression from chromosomal instability Unravelling the intricate relationship between immune cells and cancer cells through STING pathway rewiring. Introduction Chromosomal instability ( CIN ) has long been recognised as a prominent feature of advanced cancers. However, recent research has shed light on the intricate connection between CIN and the STING (Stimulator of Interferon Genes) pathway. Researchers at Memorial Sloan Kettering Cancer Center (MSK) and Weill Cornell Medicine conducted this ground-breaking study, which has provided fascinating insights into the function of the immune system and its interactions with cancer cells. In this article, we will delve into the findings of this study and explore the implications for future cancer treatments. STING pathway The STING pathway plays a crucial role in the response to cellular stress and the innate immunity response to DNA damage and chromosomal instability. Chromosomal instability refers to the increased rate of chromosomal aberrations, such as mutations, rearrangements, and aneuploidy, within a cell population. This instability can lead to genomic alterations that contribute to the initiation and evolution of cancer. This pathway is activated when the presence of cytosolic DNA is detected, which can be indicative of cellular damage or infection, triggering a cascade of signalling events leading to the production of type I interferons and other inflammatory cytokines. Many recent studies have revealed an intriguing relationship between chromosomal instability and the STING pathway, including the STING pathway’s ability to be activated by the accumulation of micronuclei resulting from chromosomal instability in cancer cells. This activation can lead to the promotion of anti-tumour immunity and the suppression of tumourigenesis. The Promise and Limitations of STING Agonist Drugs STING-agonist drugs have shown great potential in preclinical studies, arousing optimism for their use in cancer therapy. However, clinical trials have yielded disappointing results, with low response rates observed in patients. Dr. Samuel Bakhoum, an assistant member at MSK, highlights the discrepancy between lab findings and clinical outcomes. Only a small fraction of patients demonstrated a partial response, leading researchers to question the underlying reasons for this disparity. The Sinister Cooperation: CIN and Immune Cells Chromosomal instability acts as a driver for cancer metastasis, enabling cancer cells to spread throughout the body. The STING pathway, specifically, is where Dr. Bakhoum's team discovered that the immune system has a significant impact on this process. The cooperation between cancer cells with CIN and immune cells is orchestrated by STING, resulting in a pro-metastatic tumour microenvironment. This finding provides a crucial understanding of why STING-agonist drugs have not been effective in clinical trials. Introducing Contact Tracing: Unravelling Cell-to-Cell Interactions Researchers utilised a newly developed tool called ContactTracing to examine cell-to-cell interactions and cellular responses within growing tumours. By analysing single-cell transcriptomic data, they gained valuable insights into the effects of CIN and STING activation. The tool's capabilities allowed them to identify patients who could still mount a robust response to STING activation, enabling the selection of better candidates for STING agonist therapy. STING Inhibition: A Potential Solution Interestingly, the study suggests that patients with high levels of CIN may actually benefit from STING inhibition rather than activation. Treatment of study mice with STING inhibitors successfully reduced metastasis in models of melanoma, breast, and colorectal cancer. These findings open up new possibilities for personalised medicine, where patients can be stratified based on their tumour's response. By identifying the subset of patients whose tumours can still mount a strong response to STING activation, doctors could select better candidates for STING agonists. This biomarker-based approach could help figure out which patients would benefit from turning on STING and which would benefit from turning it off. This could lead to more targeted and effective treatments for people with advanced cancer that is caused by chromosomal instability. Conclusion Based on the research findings, it can be concluded that chronic activation of the STING pathway, induced by CIN, promotes changes in cellular signalling that hinder anti-tumour immunity and facilitate cancer metastasis. This rewiring of downstream signalling ultimately renders STING-agonist drugs ineffective in advanced cancer patients. However, the study also suggests that STING inhibitors may benefit these patients by reducing chromosomal instability-driven metastasis. The research highlights the importance of identifying biomarkers to determine which patients would benefit from STING activation or inhibition. Overall, these findings provide valuable insights into the underlying mechanisms of cancer progression and offer potential opportunities for improved treatment strategies for patients with advanced cancer. The study shown in figure 1, analysed 39,234 single cells within the tumour microenvironment (TME), categorised by cell subtype assignment. It showed that tumour cell rates of CIN were genetically dialled-up or dialled-down. The study also showed CIN-dependent effects on differential abundance at the neighbourhood level, grouped by cell subtype and ranked by mean log2 (FC) within each cell subtype. Node opacity was scaled by the p-value. Written by Sara Maria Majernikova Reference: Li, J., Hubisz, M.J., Earlie, E.M. et al. Non-cell-autonomous cancer progression from chromosomal instability. Nature 620 , 1080–1088 (2023). https://doi.org/10.1038/s41586-023-06464-z Project Gallery

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Search Index All (250) Other Pages (231) Forum Posts (19) 250 items found Other Pages (231) The dopamine connection | Scientia News Facebook X (Twitter) WhatsApp LinkedIn Pinterest Copy link The dopamine connection How your gut influences your mood and behaviour Introduction to dopamine Dopamine is a neurotransmitter derived from an amino acid called phenylalanine, which must be obtained through the diet, through foods such as fish, meat, dairy and more. Dopamine is produced and released by dopaminergic neurons in the central nervous system and can be found in different brain regions. The neurotransmitter acts via two mechanisms: wiring transmission and volume transmission. In wiring transmission, dopamine is released to the synaptic cleft and acts on postsynaptic dopamine receptors. In volume transmission, extracellular dopamine arrives at neurons other than postsynaptic ones. Through methods such as diffusion, dopamine then reaches receptors in other neurons that are not in direct contact with the cell that has released the neurotransmitter. In both mechanisms, dopamine binds to the receptors, transmitting signals between neurons and affecting mood and behaviour. The link between dopamine and gut health Dopamine has been known to result in positive emotions, including pleasure, satisfaction and motivation, which can be influenced by gut health. Therefore, what you eat and other factors, including motivation, could impact your mood and behaviour. This was proven by a study (Hamamah et al., 2022), which looked at the bidirectional gut-brain connection. The study found that gut microbiota was important in maintaining the concentrations of dopamine via the gut-brain connection, also known as the gut microbiota-brain axis or vagal gut-to-brain axis. This is the communication pathway between the gut microbiota and the brain facilitated by the vagus nerve, and it is important in the neuronal reward pathway, which regulates motivational and emotional states. Activating the vagal gut-to-brain axis, which leads to dopamine release, suggests that modulating dopamine levels could be a potential treatment approach for dopamine-related disorders. Some examples of gut microbiota include Prevotella, Bacteroides, Lactobacillus, Bifidobacterium, Clostridium, Enterococcus, and Ruminococcus , and they can affect dopamine by modulating dopaminergic activity. These gut microbiota are able to produce neurotransmitters, including dopamine, and their functions and bioavailability in the central nervous system and periphery are influenced by the gut-brain axis. Gut dysbiosis is the disturbance of the healthy intestinal flora, and it can lead to dopamine-related disorders, including Parkinson's disease, ADHD, depression, anxiety, and autism. Gut microbes that produce butyrate, a short-chain fatty acid, positively impact dopamine and contribute to reducing symptoms and effects seen in neurodegenerative disorders. Dopamine as a treatment It is important to understand the link between dopamine and gut health, as this could provide information about new therapeutic targets and improve current methods that have been used to prevent and restore deficiencies in dopamine function in different disorders. Most cells in the immune system contain dopamine receptors, allowing processes such as antigen presentation, T-cell activation, and inflammation to be regulated. Further research into this could open up a new possibility for dopamine to be used as a medication to treat diseases by changing the activity of dopamine receptors. Therefore, dopamine is important in various physiological processes, both in the central nervous and immune systems. For example, studies have shown that schizophrenia can be treated with antipsychotic medications which target dopamine neurotransmission. In addition, schizophrenia has also been treated by targeting the dysregulation (decreasing the amount) of dopamine transmission. Studies have shown promising results regarding dopamine being used as a form of treatment. Nevertheless, further research is needed to understand the interactions between dopamine, motivation and gut health and explore how this knowledge can be used to create medications to treat conditions. Conclusion The bidirectional gut-brain connection shows the importance of gut microbiota in controlling dopamine levels. This connection influences mood and behaviour but also has the potential to lead to new and innovative dopamine-targeted treatments being developed (for conditions including dopamine-related disorders). For example, scientists could target and manipulate dopamine receptors in the immune system to regulate the above mentioned processes: antigen presentation, T-cell activation, and inflammation. While current research has shown some promising results, further investigations are needed to better comprehend the connection between gut health and dopamine levels. Nevertheless, through consistent studies, scientists can gain a deeper understanding of this mechanism to see how changes in gut microbiota could affect dopamine regulation and influence mood and behaviour. Written by Naoshin Haque Related articles: the gut microbiome / Crohn's disease Project Gallery How does moving houses impact your health and well-being? | Scientia News Facebook X (Twitter) WhatsApp LinkedIn Pinterest Copy link How does moving houses impact your health and well-being? Evaluating the advantages and disadvantages of gentrification in the context of health Introduction According to the World Health Organization (WHO), health is “a state of complete physical, mental and social well-being and not merely the absence of disease or infirmity". Another way to define health is an individual being in a condition of equilibrium within themselves and the surrounding environment, which includes their social interactions and other factors. Reflecting on historical views of health, ancient Indian and Chinese medicine and society in Ancient Greece thought of health as harmony between a person and their environment, which underlines the cohesion between the soul and body; this is similar to the WHO’s definition of health. Considering these ideas, one key determinant of health is gentrification (see Figure 1 ). It was first defined in 1964 by British sociologist Ruth Glass, who witnessed the dilapidated houses in the London Borough of Islington being taken over and renovated by middle-class proprietors. The broader consequences of gentrification include enhanced living conditions for the residents, differences in ownership prerequisites, increased prices of land and houses, and transformations in the social class structure. Also, these changes cause lower-income inhabitants to be pushed out or go to poorer neighbourhoods, and the conditions in these neighbourhoods, which can include racial separation, lead to inequities and discrepancies in health. For example, a systematic review discovered that elderly and Black residents were affected more by gentrification compared to younger and White citizens; this highlights the importance of support and interventions for specific populations during urban renewal. Given the knowledge provided above, this article will delve further into the advantages and disadvantages of gentrification in the context of health outcomes. Advantages of gentrification Gentrification does have its benefits. Firstly, it is positively linked with collective efficacy, which is about enhancing social cohesion within neighbourhoods and maintaining etiquette; this has health benefits for residents, like decreased rates of obesity, sexually transmitted diseases, and all-cause mortality. Another advantage of gentrification is the possibility of economic growth because as more affluent tenants move into specific neighbourhoods, they can bring companies, assets, and an increased demand for local goods and services, creating more jobs in the area for residents. Additionally, gentrification can be attributed to decreased crime rates in newly developed areas because the inflow of wealthier citizens often conveys a more substantial sense of community and investment in regional security standards. Therefore, this revitalised feeling of safety can make these neighbourhoods more appealing to existing and new inhabitants, which leads to further economic development. Moreover, reducing crime can improve health outcomes by reducing stress and anxiety levels among residents, for example. As a result, the community's general well-being can develop, leading to healthier lifestyle choices and more lively neighbourhoods. Furthermore, the longer a person lives in a gentrifying neighbourhood, the better their self-reported health, which does not differ by race or ethnicity, as observed in Los Angeles. Disadvantages of gentrification However, it is also essential to mention the drawbacks of gentrification, which are more numerous. In a qualitative study involving elderly participants, for example, one of them stated that, “The cost of living increases, but the money that people get by the end of the month is the same, this concerning those … even retired people, and people receiving the minimum wage, the minimum wage increases x every year, isn’t it? But it is not enough”. Elderly residents in Barcelona faced comparable challenges of residential displacement between 2011 and 2017 due to younger adults with higher incomes and those pursuing university education moving into the city. These cases spotlight how gentrification can raise the cost of living without an associated boost in earnings, making it problematic for people with lower incomes or vulnerable individuals to live in these areas. Likewise, a census from gentrified neighbourhoods in Pittsburgh showed that participants more typically conveyed negative health changes and reduced resources. Additionally, one study examined qualitative data from 14 cities in Europe and North America and commonly noticed that gentrification negatively affects the health of historically marginalised communities. These include threats to housing and monetary protection, socio-cultural expulsion, loss of services and conveniences, and raised chances of criminal behaviour and compromised public security. This can be equally observed during green gentrification, where longtime historically marginalised inhabitants feel excluded from green or natural spaces, and are less likely to use them compared to newer residents. To mitigate these negative impacts of gentrification, inclusive urban renewal guidelines should be drafted that consider vulnerable populations to boost health benefits through physical and social improvements. The first step would be to provide residents with enough information and establish trust between them and the local authorities because any inequality in providing social options dramatically affects people’s health-related behaviours. Intriguingly, gentrification has been shown to increase the opportunity for exposure to tick-borne pathogens by populations staying in place, displacement within urban areas, and suburban removal. This increases tick-borne disease risk, which poses a health hazard to impacted residents ( Figure 2 ). As for mental health, research has indicated that residing in gentrified areas is linked to greater levels of anxiety and depression in older adults and children. Additionally, one study found young people encountered spatial disconnection and affective exclusion due to gentrification and felt disoriented by the quickness of transition. Therefore, all of these problems associated with gentrification reveal that it can harm public health and well-being, aggravating disparities and creating feelings of isolation and aloneness in impacted communities. Conclusion Gentrification is a complicated and controversial approach that has noteworthy consequences for the health of neighbourhoods. Its advantages include enhanced infrastructure and boosted economic prospects, potentially leading to fairer access to healthcare services and improved health outcomes for residents. However, gentrification often leads to removal and the loss of affordable housing, which can harm the health of vulnerable populations. Therefore, it is vital for policymakers and stakeholders to carefully evaluate the likely health effects of gentrification and enforce alleviation strategies to safeguard the well-being of all citizens (see Table 1 ). Written by Sam Jarada Related article: A perspective on well-being REFERENCES WHO. Health and Well-Being. Who.int . 2015. Available from: https://www.who.int/data/gho/data/major-themes/health-and-well-being Sartorius N. The meanings of health and its promotion. Croatian Medical Journal. 2006;47(4):662–4. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2080455/ Krahn GL, Robinson A, Murray AJ, Havercamp SM, Havercamp S, Andridge R, et al. It’s time to Reconsider How We Define Health: Perspective from disability and chronic condition. Disability and Health Journal. 2021 Jun;14(4):101129. Available from: https://www.sciencedirect.com/science/article/pii/S1936657421000753 Svalastog AL, Donev D, Jahren Kristoffersen N, Gajović S. Concepts and Definitions of Health and health-related Values in the Knowledge Landscapes of the Digital Society. Croatian Medical Journal. 2017 Dec;58(6):431–5. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5778676/ Foryś I. Gentrification on the Example of Suburban Parts of the Szczecin Urban Agglomeration. remav. 2013 Sep 1;21(3):5–14. Uribe-Toril J, Ruiz-Real J, de Pablo Valenciano J. Gentrification as an Emerging Source of Environmental Research. Sustainability. 2018 Dec 19;10(12):4847. Schnake-Mahl AS, Jahn JL, Subramanian SV, Waters MC, Arcaya M. Gentrification, Neighborhood Change, and Population Health: a Systematic Review. Journal of Urban Health. 2020 Jan 14;97(1):1–25. Project Gallery The chemistry of an atomic bomb | Scientia News Facebook X (Twitter) WhatsApp LinkedIn Pinterest Copy link The chemistry of an atomic bomb Julius Oppenheimer Julius Robert Oppenheimer, often credited with leading the development of the atomic bomb, played a significant role in its creation in the early 1940s. However, it is essential to recognize the collaborative effort of many scientists, engineers, and researchers who contributed to the project. The history and chemistry of the atomic bomb are indeed fascinating, shedding light on the scientific advancements that made it possible. The destructive power of an atomic bomb stems from the rapid release of energy resulting from the splitting, or fission, of fissile atomic nuclei in its core. Isotopes such as uranium-235 and plutonium-239 are selected for their ability to undergo fission readily and sustain a self-sustaining chain reaction, leading to the release of an immense amount of energy. The critical mass of fissionable material required for detonation ensures that the neutrons produced during fission have a high probability of impacting other nuclei and initiating a chain reaction. To facilitate a controlled release of energy, neutron moderation plays a crucial role in the functioning of an atomic bomb. Neutrons emitted during fission have high velocities, making them less likely to be absorbed by other fissile material. However, by employing a moderator material such as heavy water (deuterium oxide) or graphite, these high-speed neutrons can be slowed down. Slowing down the neutrons increases the likelihood of their absorption by fissile material, enhancing the efficiency of the chain reaction and the release of energy. The sheer magnitude of the energy released by atomic bombs is staggering. For example, one kilogram (2.2 pounds) of uranium-235 can undergo complete fission, producing an amount of energy equivalent to that released by 17,000 tons (17 kilotons) of TNT. This tremendous release of energy underscores the immense destructive potential of atomic weapons. It is essential to note that the development of the atomic bomb represents a confluence of scientific knowledge and technological advancements, with nuclear chemistry serving as a foundational principle. The understanding of nuclear fission, the critical mass requirement, and the implosion design were key factors in the creation of the atomic bomb. Exploring the chemistry behind this devastating weapon not only provides insights into the destructive capabilities of atomic energy but also emphasises the responsibility that accompanies its use. In conclusion, while Oppenheimer's contributions to the development of the atomic bomb are significant, it is crucial to acknowledge the collective effort that led to its creation. The chemistry behind atomic bombs, from the selection of fissile isotopes to neutron moderation, plays a pivotal role in harnessing the destructive power of nuclear fission. Understanding the chemistry of atomic weapons highlights the remarkable scientific achievements and reinforces the need for responsible use of atomic energy. By Navnidhi Sharma Project Gallery View All Forum Posts (19) Quizzes #3 In Questions & Answers · 15 February 2023 Form of energy which is due to an object/ particle's motion? A. Kinetic energy B. Gravitational potential energy C. Potential energy D. Thermal energy 0 1 16 Quizzes #5 In Questions & Answers · 4 March 2023 0 1 22 Forum rules In General Discussion · 13 December 2022 We want everyone to get the most out of this community, so we ask that you please read and follow these guidelines: Respect each other Keep posts relevant to the forum topic No spamming 1 0 6 View All

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