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A Scientia News Biology collaboration Facebook X (Twitter) WhatsApp LinkedIn Pinterest Copy link Artificial intelligence: the good, the bad, and the future 20/03/25, 12:01 Last updated: Published: 13/12/23, 17:10 A Scientia News Biology collaboration Introduction Artificial intelligence (AI) shows great promise in education and research, providing flexibility, curriculum improvements, and knowledge gains for students. However, concerns remain about its impact on critical thinking and long-term learning. For researchers, AI accelerates data processing but may reduce originality and replace human roles. This article explores the debates around AI in academia, underscoring the need for guidelines to harness its potential while mitigating risks. Benefits of AI for students and researchers Students Within education, AI has created a buzz for its usefulness in aiding students to complete daily and complex tasks. Specifically, students have utilised this technology to enhance their decision making process, improve workflow and have a more personalised learning experience. A study by Krive et al. (2023) demonstrated this by having medical students take an elective module to learn about using AI to enhance their learning and understand its benefits in healthcare. Traditionally, medical studies have been inflexible, with difficulty integrating pre-clinical theory and clinical application. The module created by Krive et al. introduced a curriculum with assignments featuring online clinical simulations to apply preclinical theory to patient safety. Students scored a 97% average on knowledge exams and 89% on practical exams, showing AI's benefits for flexible, efficient learning. Thus, AI is able to assist in enhancing student learning experiences whilst saving time and providing flexibility. Additionally, we gathered testimonials from current STEM graduates and students to better understand the implications of AI. In Figure 1 , we can see that the students use AI to benefit their exam learning, get to grips with difficult topics, and summarise long texts to save time whilst exercising caution, knowing that AI has limitations. This shows that AI has the potential to become a personalised learning assistant to improve comprehension and retention and organise thoughts, all of which allow students to enhance skills through support as opposed to reliance on the software. Despite the mainstream uptake of AI, one student has chosen not to use AI in the worry of becoming less self-sufficient, and we will explore this dynamic in the next section. Researchers AI can be very useful for academic researchers, such as making the process of writing and editing papers based on new scientific discoveries less slow or even facilitating it altogether. As a result, society may have innovative ways to treat diseases and increase the current knowledge of different academic disciplines. Also, AI can be used for data analysis by interpreting a lot of information, and this not only saves time but a lot of money required to complete this process accurately. The statistics and graphical findings could be used to influence public policy or help different businesses achieve their objectives. Another quality of AI is that it can be tailored towards the researcher's needs in any field, from STEM to subject areas outside of it, indicating that AI’s utilities are endless. For academic fields requiring researchers to look at things in greater detail, like molecular biology or immunology, AI can help generate models to understand the molecules and cells involved in such mechanisms sufficiently. This can be through genome analysis and possibly next generation sequencing. Within education, researchers working as lecturers can utilise AI to deliver concepts and ideas to students and even make the marking process more robust. In turn, this can decrease the burnout educators experience in their daily working lives and may possibly help establish a work-life balance, as a way to feel more at ease over the long-term. Risks of AI for students and researchers Students With great power comes great responsibility, and with the advent of AI in school and learning, there is increasing concern on the quality of learners produced from schools, and if their attitude to learning and critical thinking skills are hindered or lacking. This matter has been echoed in results from a study conducted by Ahmad et al. (2023), which studied how AI affects laziness and distorts decision making in university students. The results showed using AI in education correlated with 68.9% of laziness and a 27.7% loss in decision making abilities in 285 students across Pakistani and Chinese institutes. This confirms some worries that a former testimonial shared with us in figure 1 and suggests that students may become more passive learners rather than develop key life skills. This may even lead to reluctance to learn new things and seeking out ‘the easy way’ rather than enjoy obtaining new facts. Researchers Although AI can be great for researchers, it carries its own disadvantages. For example, it could lead to reduced originality while writing, and this type of misconduct jeopardises the reputation of the people working in research. Also, the software is only as effective as the type of data they are specialised in, so specific AI could misinterpret the data. This has downstream consequences that can affect how research institutions are run, and beyond that, scientific inquiry is hindered. Therefore, if severely misused, AI can undermine the integrity of academic research, which could hinder the discovery of life-saving therapies. Furthermore, there is the potential for AI to replace researchers, suggesting that there may be fewer opportunities to employ aspiring scientists. When given insufficient information, AI can be biased, which can be detrimental; an article found that its use in a dermatology clinic can put certain patients at risk of skin cancer and suggested that it receives more diverse demographic data for AI to work effectively. Thus, it needs to be applicable in a strategic way to ensure it works as intended and does not cause harm. Conclusion Considering the uses of AI for students and researchers, it is advantageous to them by supporting any knowledge gaps, aiding in data analysis, boosting general productivity and can be used to engage with the public and much more. Its possibilities for enhancing industries such as education and drug development are endless for propagating societal progression. Nevertheless, the drawbacks of AI cannot be ignored, like the chance of it replacing people in jobs or that it is not completely accurate. Therefore, guidelines must be defined for its use as a tool to ensure a healthy relationship between AI and students and researchers. According to the European Network of Academic Integrity (ENAI), using AI for proofreading, spell checking, and as a thesaurus is admissible. However, it should not be listed as a co-author because, compared to people, it is not liable for any reported findings. As such, depending on how AI is used, it can be a tool to help society or be detrimental, so it is not inherently good or bad for students, researchers and society in general. Written by Sam Jarada and Irha Khalid Introduction, and 'Student' arguments by Irha Conclusion, and 'Researcher' arguments by Sam Related articles: Evolution of AI / AI in agriculture and rural farming / Can a human brain be uploaded to a computer? Project Gallery

Setting Neuropsychiatry In a Wider Medical Context Facebook X (Twitter) WhatsApp LinkedIn Pinterest Copy link Schizophrenia, Inflammation and Accelerated Aging: a Complex Medical Phenotype 20/02/25, 11:54 Last updated: Published: 24/05/23, 09:45 Setting Neuropsychiatry In a Wider Medical Context In novel research by Campeau et al. (2022), the proteomic analysis of 742 proteins from the blood plasma of 54 schizophrenic participants and 51 age-matched healthy volunteers. This investigation resulted in the validation of the previously-contentious link between premature aging and schizophrenia by testing for a wide variation of proteins involved in cognitive decline, aging-related comorbidities, and biomarkers of earlier-than-average mortality. The results from this research demonstrated that age-linked changes in protein abundance occur earlier on in life in people with schizophrenia. This data also helps to explain the heightened incidence rate of age-related disorders and early all-cause death in schizophrenic people too, with protein imbalances associated with both phenomena being present in all schizophrenic age strata over age 20. This research is the result of years of medical intrigue regarding the biomedical underpinnings of schizophrenia. The comorbidities and earlier death associated with schizophrenia were focal points of research for many years, but only now have valid explanations been posed to answer the question of the presence of such phenomena. The explanation for the greater incidence rate of early death in schizophrenia was described in this study as the increased volume of certain proteins. Specifically, these included biomarkers of heart disease (Cystatin-3, Vitronectin), blood clotting abnormalities (Fibrinogen-B) and an inflammatory marker (L-Plastin). These proteins were tested for due to their inclusion in a dataset of protein biomarkers of early all-cause mortality in healthy and mentally-ill people published by Ho et al. (2018) for the Journal of the American Heart Association. Furthermore, a protein linked to degenerative cognitive deficit with age, Cystatin C, was present in increased volume in schizophrenic participants both under and over the age of 40. This explains why antipsychotics have limited effectiveness in reducing the cognitive effects of schizophrenia. In this study, schizophrenics under 40 had similar plasma protein content as the healthy over-60 strata set, including both biomarkers of cognitive decline, age-related diseases and death. Schizophrenics under-40 showed the same likelihood for incidence of the latter phenomena compared to the healthy over-60 set. These results could demonstrate the necessity for use of medications often used to treat age-related cognitive decline and mortality-linked protein abundances to treat schizophrenia. One of these options include polyethylene glycol-Cp40, a C3 inhibitor used to treat nocturnal haemoglobinuria, which could be used to ameliorate the risk of developing age-related comorbidities in schizophrenic patients. This treatment may be effective in the reduction of C3 activation, which would reduce the opsonisation (tagging of detected foreign products in blood). When overexpressed, C3 can cause the opsonisation of healthy blood cells in a process called haemolysis, which can catalyse the reduction of blood volume implicated in cardiac events and other comorbidities. However, whether or not this treatment would benefit those with schizophrenia is yet to be proven. The potential of this research to catalyse new treatment options for schizophrenia cannot be understated. Since the publication of Kilbourne et al. in 2009, the impact of cardiac comorbidities in catalysing early death in schizophrenic patients has been accepted medical dogma. The discovery of exact protein targets to reduce the incidence rate of age-linked conditions and early death in schizophrenia will allow the condition to be treated more holistically, with greater observance to the fact that schizophrenia is not only a psychiatric illness, but also a neurocognitive disorder with affiliated comorbidities that have to be prevented adequately. Written by Aimee Wilson Related articles: Genetics of ageing and longevity / Ageing and immunity / Inflammation therapy Project Gallery

Discussing Peto's Paradox Facebook X (Twitter) WhatsApp LinkedIn Pinterest Copy link Why blue whales don't get cancer 14/07/25, 15:16 Last updated: Published: 16/10/23, 21:22 Discussing Peto's Paradox Introduction: What is Peto’s Paradox? Cancer is a disease that occurs when cells divide uncontrollably, owing to genetic and epigenetic factors . Theoretically, the more cells an organism possesses, the higher the probability should be for it to develop cancer. Imagine that you have one tiny organism – a mouse, and a huge organism – an elephant. Since an elephant has more cells than a mouse, it should have a higher chance of developing cancer, right? This is where things get mysterious. In reality, animals with 1,000 times more cells than humans are not more likely to develop cancer. Notably, blue whales, the largest mammals, hardly develop cancer. Why? In order to understand this phenomenon, we must dive deep into Peto’s Paradox. Peto’s paradox is the lack of correlation between body size and cancer risk. In other words, the number of cells you possess does not dictate how likely you are to develop cancer. Furthermore, research has shown body mass and life expectancy are unlikely to impact the risk of death from cancer . (see figure 1) Peto’s Paradox: Protective Mechanisms Mutations, otherwise known as changes or alterations in the deoxyribonucleic acid (DNA) sequence, play a role in cancer and ageing. Research scientists have analysed mutations in the intestines of several mammalian species , ranging from mice, monkeys, cats, dogs, humans, and giraffes, to tigers and lions. Their results reveal that these mutations mostly come from processes that occur inside the body, such as chemicals causing changes in DNA. These processes were similar in all the animals they studied, with slight differences. Interestingly, annually, animals with longer lifespans were found to have fewer mutations in their cells ( figure 2 ). These findings suggest that the rate of mutations is associated with how long an animal lives and might have something to do with why animals age. Furthermore, even though these animals have very different lifespans and sizes, the amount of mutations in their cells at the end of their lives was not significantly different – this is known as cancer burden. Since animals with a larger size or longer lifespan have a larger number of cells (and hence DNA) that could undergo mutation, and a longer time of exposure to mutations, how is it possible that they do not have a higher cancer burden? Evolution has led to the formation of mechanisms in organisms that suppress the development of cancerous cells . Animals possessing 1,000 times as many cells as humans do not display a higher susceptibility to cancer, indicating that natural mechanisms can suppress cancer roughly 1,000 times more efficiently than they operate in human cells . Does this mean larger animals have a more efficient protective mechanism against cancer? A tumour is an abnormal lump formed by cells that grow and multiply uncontrollably. A tumour suppressor gene acts like a bodyguard in your cells. They help prevent the uncontrollable division of cells that could form tumours. Previous analyses have shown that the addition of one or two tumour suppressor gene mutations would be sufficient to reduce the cancer risk of a whale to that of a human. However, evidence does not suggest that an increased number of tumour suppressor genes correlated with increasing body mass and longevity. Although a study by Caulin et al . identified biomarkers in large animals that may explain Peto’s paradox, more experiments need to be conducted to confirm the biological mechanisms involved. Just over a month ago, an investigation of existing evidence on such mechanisms revealed a list of factors that may contribute to Peto’s paradox. This includes replicative immortality, cell senescence, genome instability and mutations, proliferative signalling, growth suppression evasion and cell resistance to death. As far as we know, different strategies have been followed to prevent cancer in species with larger sizes or longer lifespans . However, more studies must be conducted in the future in order to truly explain Peto’s paradox. Peto’s Paradox: Other Theories There are several theories that attempt to explain Peto’s paradox. One of which explains that large organisms have a lower basal metabolic rate, leading to less reactive oxygen species. This means that cells in larger organisms incur less oxidative damage, causing a lower mutation rate and lower risk of developing cancer. Another popular theory is the formation of hypertumours . As cells divide uncontrollably in a tumour, “cheaters” could emerge. These “cheaters”, known as hypertumours, are cells which grow and feed on their original tumour, ultimately damaging or destroying the original tumour. In large organisms, tumours have more time to reach lethal size. Therefore, hypertumours have more time to evolve, thereby destroying the original tumours. Hence, in large organisms, cancer may be more common but is less lethal. Clinical Implications Curing cancer has posed significant challenges. Consequently, the focus on cancer treatment has shifted towards cancer prevention . Extensive research is currently underway to investigate the behaviour and response of cancer cells to the treatment process. This is done through a multifaceted approach; investigating the tumour microenvironment and diagnostic or prognostic biomarkers. Going forward, a deeper understanding of these fields enables the development of prognostic models as well as targeted treatment methods. One example of an exciting discovery is the revelation of TP53 . The discovery of this tumour suppressor gene indicates that it plays a role in making elephant cells more responsive to DNA damage and in triggering apoptosis by regulating the TP53 signaling pathway. These findings imply that having more copies of TP53 may have directly contributed to the evolution of extremely large body sizes in elephants, helping resolve Peto’s paradox . Particularly, there are 20 copies of the TP53 gene in elephants, but only one copy of the TP53 gene in humans (see figure 3 ). Through more robust studies and translational medicine, it would be fascinating to see how such discoveries could be applied into human medicine ( figure 4 ). Conclusion The complete mechanism of how evolution has enabled organisms that are larger in size and have longer lifespans than humans is still a mystery. There is a multitude of hypotheses that need to be extensively investigated with large-scale experiments. By unravelling the mysteries of Peto’s paradox, these studies could provide invaluable insights into cancer resistance and potentially transform cancer prevention strategies for humans. Written by Joecelyn Kirani Tan Related articles: Biochemistry of cancer / Orcinus orca (killer whale) / Canine friends and cancer Project Gallery

Why the fuss over a couple of km/s/Mpc? Facebook X (Twitter) WhatsApp LinkedIn Pinterest Copy link Hubble Tension 09/07/25, 14:20 Last updated: Published: 25/11/23, 11:10 Why the fuss over a couple of km/s/Mpc? You have probably heard that the universe is expanding, and perhaps even that this expansion is accelerating. A consequent observation of this is that distant objects such as galaxies appear to recede from Earth faster if they are further away. Here is a helpful analogy: imagine a loaf of raisin bread that is rising as it is baked. A pair of raisins on opposite sides of the loaf will move away from one another at a greater rate than a pair of raisins near the center. The more dough (universe) there is between a pair of raisins (galaxies), the faster they recede from one another. See Figure 1 . This phenomenon is encapsulated in Hubble’s Law, which relates specifically to the recessional velocity due to the expansion of space. Hubble’s Law is given by the equation v = H0 D . Where: v is the recessional velocity D is the distance to the receding object H0 is the Hubble constant It is worth noting that distant objects will often have velocities of their own due to gravitational forces - so-called ‘peculiar velocities’. In order to clarify the meaning of the title of this article, we must explore the unit in which the Hubble constant H0 is most often quoted: km/s/Mpc. This describes the speed (in kilometers per second) at which a distant object, such as a galaxy, is receding for every megaparsec of distance that galaxy is from Earth. Edwin Hubble is the name most often associated with this cosmological paradigm shift; however, physicists Alexander Friedmann and Georges Lemaître worked independently on the notion of an expanding universe, deriving similar results before Hubble verified them experimentally in 1929 at the Mount Wilson Observatory, California. What is the Hubble Tension? Hopefully the above discussion of units and raisin bread convinced you that the Hubble constant H0 is linked to the expansion rate of the universe. The larger H0 is, the faster galaxies are receding at a given distance, thus indicating a more quickly expanding universe. Therefore, cosmologists wish to accurately measure H0 in order to draw conclusions about the age and size of the universe. The Hubble Tension arises from the contradicting measurements of H0 obtained from different experiments. See Figure 2 of Edwin Hubble. CMB measurement One of these experiments uses the Cosmic Microwave Background (CMB), which can be thought of as an afterglow of light from near the time of the Big Bang. The wavelength of this light has expanded with the universe ever since the period of recombination - which I mentioned in my previous article on the DESI instrument. Our current best model of the universe, called ΛCDM, can describe how the universe evolved from a hot, dense state to the universe we see today, subject to a specifically balanced energy budget between ordinary matter, dark matter, and dark energy. From fitting this ΛCDM model to CMB data from missions such as ESA’s Planck Mission, one can derive a value for the expansion rate of the universe, i.e., a value for H0 . The Planck Mission measured temperature variations (anisotropies) across the CMB with unprecedented angular resolution and sensitivity. The most recent estimate for the Hubble constant using this method gave H0 = 67.4 ± 0.5 km/s/Mpc . Local Distance Ladder measurement Another technique to determine the value of H0 uses the distance-redshift relation. This is a wholly observational approach. It relies on the fact that the faster an object recedes from Earth, the more the light from that object is shifted towards longer wavelengths (redshifted). Hubble’s Law relates this recessional velocity to a distance; therefore, one can expect a similar relation between distance and redshift. A ‘ladder’ is invoked since astronomers wish to use objects that are visible from a vast range of distances; the rungs of the ladder represent greater and greater distances to the astronomical light source. Each rung of the ladder contains a different kind of ‘standard candle’, which are sources with reliable, well-constrained luminosities that translate to an accurate distance from Earth. I encourage you to look into these different types; some examples are Cepheid variables, Type Ia Supernovae, and RR Lyrae variables. When this method was employed using the Hubble Space Telescope and SH0ES (Supernova H0 for the Equation of State), a value of H0 = 73.04 ± 1.04 km/s/Mpc was obtained. The disagreement Clearly, these two values for the Hubble constant do not agree, nor do their uncertainty ranges overlap. Figure 3 shows some of the 21st-century measurements of H0 ; an excellent illustration of how the uncertainty has decreased for both methods, therefore making their disagreement more statistically significant. Many sources of scientific engagement with the public cite this disagreement as the ‘Crisis in Cosmology!’. In the author’s opinion, this is unnecessarily hyperbolic and plays on the human instinct to pick a side between two opposing viewpoints. In fact, new methods to measure H0 have been implemented using the tip of the Red-Giant branch (TRGB) as a standard candle, which demonstrate closer agreement with the value derived from the CMB. Some cosmologists believe that eventually this Hubble Tension will dissipate as our calibration of astronomical distances improves with the next generation of telescopes. Constraining the value of the Hubble constant is by no means low-hanging fruit for cosmologists, nor is the field in crisis. To see the progress we have made, one has to look back in time to 1929 when Edwin Hubble’s first estimate using a trend line and 46 galaxies gave H0 = 500 km/s/Mpc ! We must remain hopeful that the future holds a consistent approximation for the expansion rate and, with it, the age of our universe. Written by Joseph Brennan Project Gallery

Non-cell-autonomous cancer progression from chromosomal instability Facebook X (Twitter) WhatsApp LinkedIn Pinterest Copy link Immune signals initiated by chromosomal instability lead to metastasis 09/07/25, 14:23 Last updated: Published: 14/09/24, 21:17 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 Related articles: Cancer immunologist Polly Matzinger / The Hippo signalling pathway / Cancer metastasis / Arginine and tumour growth 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

The same condition after all? Facebook X (Twitter) WhatsApp LinkedIn Pinterest Copy link Hypermobile Ehlers-Danlos Syndrome and Hypermobility Spectrum Disorder 09/07/25, 14:21 Last updated: Published: 20/01/24, 11:38 The same condition after all? Practice and progress in rheumatology The relationship between hypermobile Ehlers-Danlos Syndrome (hEDS) and Hypermobility Spectrum Disorder (HSD) has been hotly debated in recent years, with research being published on a near-constant basis attempting to establish a valid symptomatological or causalogical difference between the two disorders. Now, a paper by Ritelli et al. (2022) threatens to end the savage cycle for all. Using RNA sequencing techniques and immunofluorescence, Ritelli et al. found identical gene expression and cellular characteristics in dermal biopsies from those with both conditions. Through immunofluorescence of biopsies from 20 women with hEDS, 16 women and 4 men with HSD and 40 controls, it was found that the shape and components of the extracellular matrix were greatly different in those with HSD/hEDS in comparison to those in the healthy control group. Abnormalities were discovered in the expression of cadherin-11, snail1, and αvβ3, α5β1 and α2β1 integrins. Integrins mediate the connections between the cell cytoskeleton and extracellular matrix to ensure they stay together, cell-to-cell adhesion is initiated by cadherin-11, and snail1 is localised close to the cyclin-dependent kinase inhibitor 2B (CDKN2B) gene. Snail1 can activate CDKN2B gene products when Snail1 is overexpressed to the point of reaching the general localisation of the CDKN2B domain. This demonstrates that there may be a similar causative link between the widespread inflammation and chronic pain in HSD/hEDS and rheumatoid arthritis. Li et al. (2021) proved that the polarisation of macrophages (white blood cells which destroy foreign products) was carefully controlled by the CDKN2B-AS1/ MIR497/TXNIP axis- the increased activation of which in rheumatoid arthritis catalyses the excessive polarisation of macrophages, which causes the macrophages to attack healthy cells. In rat studies published by Tan et al. (2022), it was found that rats with diabetes and induced sepsis experienced greater intestinal injury that control rats without any medical pathology who experienced induced sepsis. This was demonstrated to be due to interruptions in the miR-3061/Snail1 communication pathway. Research on this phenomenon in humans may elucidate the relevance of snail1 overproduction in hEDS/HSD sufferers to their complex gastrointestinal symptoms. If this pathway works similarly in human models of sepsis or localised GI infection, it may intimate that snail1 overproduction is responsible for the hyperpolarisation of macrophages in response to foreign product detection, which may cause immunological damage in the intestines. However, the relevance of this study to hEDS/HSD should be considered questionable until further human research into this avenue has been completed. The result of this research is that academia can potentially derive a genetic cause of the complex phenotypes demonstrated by sufferers of hEDS/HSD. This can be achieved by visualising the human genome, and testing genes like those above, or those implicated in modulating the activity of the genes above. Once garnered, this genetic evidence will elucidate whether or not hEDS and HSD are one disorder, or both variants of the same disorder with differing genetic causes. This, in turn, could lead to the development of medications or treatments based on genetic phenotype. Written by Aimee Wilson Related articles: Ehlers-Danlos syndrome / Types of movement Project Gallery

Rising temperatures can affect brain health Facebook X (Twitter) WhatsApp LinkedIn Pinterest Copy link The Brain-Climate Connection: The Hidden Impact of Rising Temperatures 19/06/25, 10:14 Last updated: Published: 24/05/23, 09:55 Rising temperatures can affect brain health Global warming is not only disrupting ecosystems, affecting the food we eat and the air we breathe, but it’s also impacting our neurological health. According to the 2022 Global Climate Report from NOAA National Centers for Environmental Information , 2022 was the sixth warmest year since 1880. To understand this better, let’s start with the basics. The brain is made up of billions of tiny cells called neurons that communicate with each other by generating electrochemical signals. Think of neurons as small batteries capable of producing electricity when triggered by electrically charged chemicals, called ions. When a neuron is at rest, so when it’s not transmitting an electrical signal, it maintains a negative charge inside compared to the outside. This difference in charge is created by the selective movement of ions across the neuron’s membrane through ion channels and pumps. The resting membrane potential of a neuron is typically around -70 millivolts (mV). When a neuron needs to send information, it generates electrical activity called action potential , which causes the electrical charge to become less negative and closer to zero. To trigger a full-sized action potential, the electrical charge needs to reach a threshold of approximately -55 mV. If the charge reaches this threshold, a full-sized action potential is triggered and the neuron will send a signal down to other neurons. However, if the electrical charge does not reach this threshold, the neuron will not send a signal at all. This is known as the “ALL OR NONE” principle. The action potential is a crucial part of the neuron’s communication process, as it allows the neuron to send signals quickly and efficiently to other neurons. But here’s the catch: temperature fluctuations can affect the ion channels that generate and propagate action potentials, which are critical for the neuron’s communication process. It turns out that an increase in temperature can influence the generation , speed , and duration of action potentials. But that’s not all! Hotter temperatures can trigger seizures in individuals with epilepsy or a history of seizures. One of the most concerning findings from scientific research is that climate change, among other factors, may contribute to an increase in seizure severity and frequency, as well as the development of cerebrovascular and neurodegenerative diseases, such as strokes or dementia . Triggering stress and sleep deprivation, heat waves can also exacerbate the symptoms of such pre-existing disorders. The good news is that we can take action to address the direct impact of climate change on our planet and health. Joining initiatives like Climatematch Academy (CMA) , a 2-week interactive online summer school, can help you learn more about climate science and become part of a global community that is working towards a more sustainable future. CMA is an all-volunteer organization run by dozens of science enthusiasts. It aims at introducing computational methods for climate science taking advantage of available open-source tools and datasets to make science accessible to students worldwide. This is your chance to learn cutting-edge techniques from climate science experts and make a difference in the world, ensuring a brighter future for ourselves and future generations. Written by Viviana Greco Related articles: The environmental impact of EVs / Emperor penguins / Impacts of global warming on NTDs Project Gallery

The science behind tooth decay Facebook X (Twitter) WhatsApp LinkedIn Pinterest Copy link How to prevent tooth decay 10/04/25, 10:52 Last updated: Published: 03/02/24, 11:24 The science behind tooth decay Dental caries, commonly referred to as tooth decay, manifests as a gradual process and progressive disease affecting the dental hard tissues, resulting in the breakdown of tooth structure and the potential for pain and infection within the oral cavity. Understanding the mechanisms behind tooth decay is crucial for adopting effective preventative measures, to stop or reverse the carious process and prevent cavity formation. Several factors contribute to dental caries, including bacteria, time, fermentable carbohydrates, and a susceptible tooth surface. In the absence of regular toothbrushing, a plaque biofilm is allowed to form on the tooth surface—a sticky, colourless film that serves as a breeding ground for bacteria such as Streptococcus mutans and Lactobacillus species. Once these bacterial species encounter fermentable carbohydrates and sugars from our diet, they begin to metabolise them, producing acids as a by-product. These acids contribute to an acidic environment in the mouth. When enamel, the outermost layer of tooth structure, is exposed to an acidic pH below 5.5, its mineral structure weakens, initiating the dissociation of hydroxyapatite crystals. Frequent acid attacks from dietary sugars result in a net mineral loss in teeth, leading to cavity formation, dental pain, and potential infections. The initial stage of decay involves the demineralisation of enamel. At this point, the damage can be reversible with good oral hygiene practices and through remineralising agents. Saliva has the capacity to remineralise initial carious lesions, and fluoride application through fluoridated toothpaste can also aid in reversing the initial stages of dental caries. However, if left untreated and allowed to progress, the decay can develop further into the tooth structure reaching the softer dentine beneath enamel. Dentin decay occurs more rapidly than enamel and can contribute to increased sensitivity and discomfort. As the decay advances, it may reach the dental pulp, which is the nerve of the tooth. Infection of the pulp can trigger severe pain and may necessitate root canal treatment in attempt to save the tooth. Persistent infections can lead to abscess formation—a pocket of pus causing swelling, pain, and systemic health issues, should the infection spread throughout the body. Tooth decay can be preventing through regular brushing with a fluoride toothpaste. The consistent disturbance to the plaque biofilm formation through brushing it away will not allow the caries process to continue, and hence prevent cavity formation. The fluoride aspect will help to strengthen the enamel and remineralise any mineral loss found in early lesions; this can stop and even reverse the carious process, thus preventing dental decay A healthy diet with limited consumption of sugary foods and drinks can significantly reduce the risk of tooth decay; with less sugars in the oral environment there is a lower rate of bacterial metabolisation to create the acids which contribute to the decay process. Regular dental check up appointments enable early detection and intervention of any initial lesions, preventing the progression of decay before reaching an irreversible status. Tooth decay is a preventable yet prevalent oral health issue. Instigated by the action of oral bacteria metabolising sugars in the mouth, our natural tooth structure can be destructed and decayed if the plaque biofilm is not controlled. By understanding the causes and progression of tooth decay, individuals can adopt proactive measures to maintain good oral hygiene, preserve enamel, and safeguard their smiles for a lifetime. Regular dental check-ups and a commitment to a healthy lifestyle play pivotal roles in preventing the onset and progression of tooth decay. Written by Isha Parmar Related article: Importance of calcium REFERENCE (Banerjee & Watson, 2015): Banerjee, A. and Watson, T.F. (2015) Pickard’s Guide to Minimally Invasive Operative Dentistry, King’s College London. Project Gallery

A rare neurological disease that is caused by a flaw in genetics Facebook X (Twitter) WhatsApp LinkedIn Pinterest Copy link Pseudo-Angelman Syndrome 12/09/25, 11:10 Last updated: Published: 07/09/24, 20:20 A rare neurological disease that is caused by a flaw in genetics This is article no. 8 in a series on Rare Diseases. Next article: Breaking down Tay-Sachs . Previous article: Apocrine carcinoma . An overview Name of the disease: Pseudo-Angelman Syndrome Other names the disease is known by: - 2q23.1 microdeletion syndrome - Del(2)(q23.1) - monosomy 2q23.1 Prevalence rate in the US: <1000 Average life expectancy: mid-50s – early 70s for severe to moderate intellectual disabilities Mortality rate: <10% in individuals with severe to moderate intellectual disabilities (this rate is more than double the general population) Pseudo-Angelman syndrome is a neurological disease, which is classified as Rare since it affects fewer than 1000 people in the US (as reported by the National Institute of Health). However, the information on this disease, like other rare diseases, is incomplete. This article aims to raise awareness of rare neurological diseases such as Pseudo-Angelman syndrome. Onset of symptoms: the symptoms of the disorder can appear early as a newborn and an infant Its symptoms include: - Seizures - Moderate-severe learning difficulties- mental retardation (MR)- and behaviour issues (the roles of the frontal and parietal lobes in the brain are planning and executing actions, as well as proprioception) - Speech and developmental delays (one of the functions the temporal lobe in the brain is responsible for is audio processing and speech) - Trouble sleeping - Repetitive movements of the fingers, wrists, etc. or motor stereotypy Hypotonia, slow weight gain, and shorter height may also be present in children affected by the disease. Symptoms help diagnose the diagnosis, but only genetic testing confirms it. The genetic mechanism of the disease Genetic cause of the disease: a microdeletion on 2q23.1 A chromosomal deletion occurs when a region of a chromosome is removed, resulting in the loss of genetic material within that specific segment. A microdeletion affects an even smaller part on the chromosome. Hence, in Pseudo-Angelman syndrome, the 2q23.1 microdeletion involves the loss of a small section of DNA on chromosome no. 2. More specifically, the DNA is lost from position 23.1 on chromosome 2. The exact role of chromosome 2 is not yet known (there is active research in this field), but chromosome 2 likely contains protein-coding genes. The chances are that key proteins that genes in chromosome 2 code for, are not made when there is a 2q23.1 microdeletion i.e. the microdeletion removes these crucial genes, and so cells cannot produce the proteins. Thus, giving rise to Pseudo-Angelman syndrome in the individual. Indeed, research has shown that usually the MBD5 gene is deleted in patients with the syndrome (in one study, all 15 patients had lost this gene from the removed region). The next prominent gene that is deleted is EPC2 , which is a gene that is thought to be involved in causing MR. Inheritance of the disease: mostly de novo A study by van Bon et. al (2009) depicted that 10 out of 11 patients were shown to have de novo inheritance of 2q23.1 microdeletion. Comparison to Angelman syndrome See Table 1 The syndrome is called Pseudo-Angelman, so where does the Angelman part of the name come from? (The disease is named after Dr. Harry Angelman, who had first described and reported the syndrome in 1965). Angelman syndrome (AS) is also a rare disease, however, it has a higher prevalence rate than Pseudo-Angelman. One possibility could be in the way these different conditions come about in the first place. Loss of function (rather than a deletion) of the UBE3A gene in chromosome 15 from the mother, gives rise to AS. It is an example of an imprinting disorder. (Two copies of each chromosome are normally inherited, but in genomic imprinting, only one copy of a particular chromosome is passed on i.e. either the copy from the mother is inherited, or from the father- not both. Deletion, loss of function etc. may cause the other copy to not be inherited. Imprinting disorders lead to developmental and growth problems in the affected individual). In contrast, Pseudo-Angelman syndrome is often de novo, and not inherited. It is not an imprinting disorder like Angelman’s, because Pseudo-Angelman is caused by a microdeletion in 2q23.1. However, AS presents severe physical, learning, and intellectual problems. The syndrome causes seizures and developmental delays. The similarity in patients with Pseudo-Angelman can be seen here; therefore, it may be why Pseudo-Angelman is named so. Table 1: a comparison of AS and Pseudo-Angelman syndrome Angelman syndrome (AS) Pseudo-Angelman Syndrome Prevalence rate 1 in 20,000- 12,000 <1000 in the US Symptoms in common severe physical, learning, and intellectual problems seizures and developmental delays severe physical, learning, and intellectual problems seizures and developmental delays Cause Loss of function of UBE3A gene Microdeletion (of MBD5 and ECP2 genes among others) Chromosome affected Chromosome 15 Chromosome 2 (2q23.1) Mode of inheritance Genomic imprinting; inherited in an autosomal dominant way in rare cases De novo Are there any treatments for Pseudo-Angelman syndrome? Cure available: none There is no one cure to help patients with the disease, but depending on symptoms, treatment may be offered accordingly. Current treatments based on symptoms: - Seizures--> anti-seizure medicines - Behaviour issues--> behaviour therapy - Speech and developmental delays--> speech therapy - Difficulty sleeping--> medicine, sleep training Potential future treatments or cures: targeted therapy in chromosome 2 Research is ongoing for a cure, and it is considering targeting particular genes of chromosome 2 in therapy- perhaps the MBD5 and ECP2 genes. The outlook for research into this disease Aside from discerning the exact roles and functions of the genes on chromosome 2, there is active research in targeted therapy for Pseudo-Angelman syndrome. Likely, once the rest of the roles of the genes on chromosome 2 are elucidated, efforts can be invested towards modifying or even inserting these genes (e.g. MBD5 and ECP2 ) back into the chromosome, which would lead to better protein expression. This could be a possible treatment for the rare neurological disease. Outside the molecular and genetic front, there should be increased awareness about this disease: this helps in reporting and diagnosing the syndrome, in addition to providing care and treatment to patients and their families. Summary In conclusion, Pseudo-Angelman Syndrome is a rare 2q23.1 microdeletion syndrome, which gets its name from the imprinting disorder AS. Pseudo-Angelman is characterised by seizures, moderate to severe learning difficulties, and developmental delays. Hence, making it a neurological disease as well. Treatments are available according to symptoms; but efforts are ongoing to ascertain the roles of other chromosome 2 genes, leading to potential targeted therapy. -- Patient organisations specifically for this disease: - Chromsome Disorder Outreach - Unique The information in this article does not substitute professional medical advice. For any concerns, please refer to your doctor or local genetic centre. -- Written by Manisha Halkhoree Related article: Childhood intelligence REFERENCES van Bon, B., Koolen, D., Brueton, L. et al. The 2q23.1 microdeletion syndrome: clinical and behavioural phenotype. Eur J Hum Genet 18, 163–170 (2010). https://doi.org/10.1038/ejhg.2009.152 Mayo Clinic, 2024. Angelman syndrome . Retrieved from Mayo Clinic: https://www.mayoclinic.org/diseases-conditions/angelman syndrome/diagnosis-treatment/drc-20355627#:~:text=Depending%20on%20your%20child's%20symptoms,sign%20language%20and%20picture%20communication. Medline Plus, 2024. Angelman syndrome . Retrieved from Medline Plus Gov: https://medlineplus.gov/genetics/condition/angelman-syndrome/#:~:text=Angelman%20syndrome%20affects%20an%20estimated%201%20in%2012%2C000%20to%2020%2C000%20people . National Institute of Health, 2024. 2q23.1 microdeletion syndrome . Retrieved from National Institute of Health: https://rarediseases.info.nih.gov/diseases/10998/2q231-microdeletion-syndrome Project Gallery

From the Big Bang to the current model Facebook X (Twitter) WhatsApp LinkedIn Pinterest Copy link Story of the atom 11/02/25, 12:23 Last updated: Published: 20/04/24, 11:16 From the Big Bang to the current model The Greek philosopher and physicist Democritus proposed the idea of an atom at around 440 B.C. The atom is first explained by him using a stone. When a stone is split in half, it becomes two separate stones. There would eventually come to be a portion of the stone that would be too small to be cut if it were to be cut continuously i.e., indivisible. Since then, many scientists have adopted, discarded, or published their own theories about the nature, structure, and size of atoms. However, the most widely accepted, and still the basic model used to study atoms is Rutherford’s model. Rutherford published his theory of the atom suggesting that it had an electron orbiting a positively charged nucleus. This model was created after a series of experiments which included shooting alpha particles at thin gold sheets. Most of the alpha particles flowed through with little disturbance, but a tiny fraction was scattered at extreme angles to their initial direction of motion. Rutherford calculated the estimated size of the gold atom's nucleus and discovered that it was at least 10,000 times smaller than the atom's total size, with a large portion of the atom made up of empty space. This theory paved the way to further the atomic models by various other scientists. (Figure 1) Researchers have discovered unidentified molecules in space which are believed to be the precursor of all chemistry in the universe. The earliest "atoms" in the cosmos were actually nuclei without any electrons. The universe was incredibly hot and dense in the earliest seconds following the Big Bang. The quarks and electrons that make up matter first appeared when the cosmos cooled, and the ideal conditions were met for them to do so. Protons and neutrons were created by quarks aggregating a few millionths of a second later. These protons and neutrons joined to form nuclei in a matter of minutes. (Figure 2) Things started to happen more slowly as the cosmos cooled and expanded. The first atoms were formed 380,000 years ago when electrons were locked into orbits around nuclei. These were mostly hydrogen and helium, which are still the elements that are found in the universe in the greatest quantities. Even now, the most basic nucleus, found in ordinary hydrogen, is only a single, unadorned proton. There were other configurations of protons and neutrons that also developed, but since the number of protons in an atom determines its identity, all these other conglomerations were essentially just variations of hydrogen, helium, and lithium traces. To say that this is an exciting time for astrochemistry is an understatement. Furthermore, the formation mechanism of amino acids and nucleobases is being demonstrated by laboratory simulations of interstellar environments. Now that we are finding answers to these known problems, even more are arising. Hopefully, a more thorough understanding of these chemical processes will enable us to make more precise deductions about the general history of the universe and astrophysics. Written by Navnidhi Sharma REFERENCES CERN (n.d.). The early universe. [online] CERN. Available at: https://home.cern/science/physics/earlyuniverse#:~:text=As%20the%20universe%20continued%20to . Compound Interest (2016). The History of the Atom – Theories and Models | Compound Interest. [online] Compound Interest. Available at: https://www.compoundchem.com/2016/10/13/atomicmodels/ . Fortenberry, R.C. (2020). The First Molecule in the Universe. Scientific American. [online] doi: https://doi.org/10.1038/scientificamerican0220-58 . Sharp, T. (2017). What is an Atom? [online] Live Science. Available at: https://www.livescience.com/37206-atom-definition.html . Project Gallery