AI can process data sets and identify patterns and biomarkers Facebook X (Twitter) WhatsApp LinkedIn Pinterest Copy link AI: the next step in diagnosis and treatment of genetic diseases 08/07/25, 17:19 Last updated: Published: 23/03/24, 17:59 AI can process data sets and identify patterns and biomarkers With the development of more intricate Artificial Intelligence (AI) software, which has rapidly grown from the chaotic chatbots to the more well-formed ChatGPT, it is easy to think we are seeing the rise of powerful artificial intelligence that could potentially replace us all. However, there is one problem. Originality does not exist for AI, at least not complete originality. At its most basic, an AI program is trained on a set of data, whether this be an entire search engine’s worth of data, as is the case for ChatGPT, or a few images and phrases gathered from the internet. Therefore, an AI does not know any more than what it can quote or infer from the provided data, which means that a piece of art, a picture of a family, or any short story AI is asked to produce is often a replica of techniques or a chaotic and terrifying mess of images it has been given to use. However, here also lies its strength. AI can take in thousands of images and data sets and notice minor changes and differences the average person could not. It is, therefore, not AI’s ability to create the unique, but instead its ability to recognise the mundane that we can utilise, even in diagnosing and treating genetic disorders. Diagnosis By analysing PET, MRI, fMRI and genetic data, AI can process enormous data sets and identify subtle patterns and biomarkers that often elude human observations, enabling earlier and more precise diagnosis. When looking at examples of the application of AI in the diagnosis of genetic disorders, a good reference is the so-far successful use of AI in diagnosing Huntington’s disease. Huntington’s disease diagnosis using AI Huntington’s disease symptoms present as patients experience involuntary movements and a decline in decision-making processes. Huntington's disease is a genetic disorder, meaning it is caused by a faulty gene, in this case, a fault in the Huntingtin gene (Htt). The Huntington’s disease mutation in Htt results from CAG trinucleotide repeats, a highly polymorphic expansion of Htt consisting of the CAG (cytosine, adenine, guanine) nucleotides (DNA building blocks). Whilst CAG repeats are common and often normal and unharmful, individuals with Huntington’s disease possess an abnormally high number of these CAG repeats (more than 36). When an individual has an abnormally high number of CAG repeats, their Htt proteins do not fold into their proper shape, causing them to bond with other proteins and become toxic to a cell, which ultimately causes cell death in crucial medium spiny neurons (MSN) in the basal ganglia. Basal ganglia are brain structures responsible for the fine-tuning of our motor processes, which they do by essentially allowing neurons to respond in a preferred direction (a target muscle) rather than a null direction using MSNs. So, it is clear how Huntington's disease symptoms occur; mutant Htt leads to cell death in MSNs, leading to the basal ganglia’s inability to control movement, which causes characteristic involuntary behaviours, among other symptoms. Because we identified these changes in Htt and loss of MSN in the basal ganglia, PET, MRI, and fMRI scans are often used in the diagnosis of Huntington’s disease, in addition to genetic and mobility tests. By collecting and extracting clinical and genetic data, certain AI algorithms can analyse the broad range of Huntington’s disease clinical manifestations, identify differences, including even minute changes in the basal ganglia that a doctor may not have, and make an earlier diagnosis. One branch of AI that has proved effective is machine learning. Machine learning models in diagnosis Machine learning uses data and algorithms to imitate the way humans learn. For Huntington's disease diagnosis, this involves the identification of biomarkers and patterns in medical images, gene studies and mobility tests, and detecting subtle changes between data sets, distinguishing Huntington’s disease patients from healthy controls. While machine learning in Huntington’s disease diagnosis comes in many forms, the decision tree model, where the AI uses a decision tree as illustrated in the Project Gallery, has proven very effective. A decision tree model looks at decisions and their possible consequences and breaks them into subsets branching downward, going from decision to effect. Recent research using AI in Huntington’s disease diagnosis has utilised this model to analyse gait dynamics data. This data looks at variation in stride length, how unsteady a person is while walking, and the degree to which one stride interval (the time between strides) differs from any previous and any subsequent strides. For an individual, it is widely accepted that if they have abnormal variations in stride (their walking speed is reduced, their stance is widened), then they are exhibiting symptoms of Huntington’s disease. Therefore, by using this gait data, and having the machine learning model come up with a mean value for stride variation for trial patients, it will be able to discern which patients have stride variation associated with Huntington’s disease (a higher variation in stride) and those that do not. Researchers found that using this method of diagnosis, they were able to accurately identify which gaits belonged to Huntington's disease patients, with an accuracy of up to 100%. Furthermore, researchers also found decision tree models useful when identifying whether a gene links with Huntington’s disease when comparing patients' genetic information with prefrontal cortex samples, with this method’s accuracy being 90.79%. With these results and even more models showing incredible promise, AI is already proving itself useful when it comes to identifying and diagnosing sufferers of genetic disorders, such as those with Huntington’s disease. But this leads us to ask, can AI even help in the treatment of those suffering from genetic disorders? Treatment- current studies in cystic fibrosis While AI models can be applied diagnostically for disorders such as Huntington's disease, they may also be relied upon in disease treatment. The use of AI in tailored treatment is the focus of current research, with one even looking at improving the lives of those suffering from cystic fibrosis. Around 10,800 people are recorded as having cystic fibrosis in the UK, and this debilitating disorder results in a buildup of thick mucus, leading to persistent infections and other organ complications. The most common cause of cystic fibrosis is a mutation in the gene coding for the protein CFTR, resulting from a deletion in its coding gene, causing improper folding in the protein CFTR, as we saw in Huntington’s disease. This misfolding leads to its retention in the wrong place in a cell, so it can no longer maintain a balance of salt and water on body surfaces. Because of the complex symptoms arising from this imbalance, this disease is very difficult to manage, but there is hope, and hope comes as SmartCare. SmartCare involved home monitoring and followed 150 people with cystic fibrosis for six months, having them monitor their lung function, pulse, oxygen saturation and general wellness and upload recorded data to an app. Subsequently, researchers at the University of Cambridge used machine learning to create a predictive algorithm that used this lung, pulse, and oxygen saturation data, identifying patterns that were associated with a decline in a patient's condition, and then predicted this decline much faster than the patient of their doctor could. On average, this model could predict a decline in patient condition 11 days earlier than when the patient would typically start antibiotics, allowing health providers to respond quicker and patients to feel less restricted by their health. This project was, in fact, so successful that the US CF Foundation is now supporting a clinical implementation study, called Breath, which began in 2019 and continues to this day. Although there is a long way to go, using AI, the future can seem brighter. In Huntington’s disease and cystic fibrosis, we can see its effectiveness in both disease diagnosis and treatment. With the usage of AI predicted to increase in the future, there is a great outlook for patients and an opportunity for greater quality of care. This ultimately could ease patient suffering and prevent patient deaths. All this positive research tells us AI is our friend (although science fiction would often persuade us otherwise), and it will guide us through the tricky diagnosis and treatment of our most challenging diseases, even those engrained in our DNA. Written by Faye Boswell Related articles: AI in drug discovery / Can a human brain be linked to a computer? / AI in medicinal chemistry Project Gallery

Characteristics, triggers and theoretical models of embarrassment Facebook X (Twitter) WhatsApp LinkedIn Pinterest Copy link Psychology of embarrassment: why do we get embarrassed? 05/06/25, 11:07 Last updated: Published: 06/09/24, 12:07 Characteristics, triggers and theoretical models of embarrassment The six basic emotions proposed by Ekman and recognised worldwide are sadness, happiness, fear, anger, surprise and disgust- Ekman (1999). Recently, the list of basic emotions has expanded to include self-conscious emotions, such as embarrassment, pride and shame, as all of those emotions show evidence for cross-cultural and cross-species production and perception. According to Miller (1995), embarrassment is the self-conscious feeling individuals get after realising they have done something stupid, silly or dishonourable. Embarrassment is a social emotion that emerges at around 18 months of age and the development of which is related to self-recognition. Characteristics of embarrassment in humans are gaze aversion, downward head movements, controlled smile and face touching. Embarrassment has been linked to the two main personality dimensions proposed by Eysenck (1983): extraversion/introversion and neuroticism/emotional stability. Kelly & Jones (1997) found that neuroticism is positively associated with embarrassment, suggesting that the individuals who score highly in neuroticism are more prone to experiencing embarrassment. The same researchers also concluded that embarrassment is negatively related to extraversion, implying that introverted individuals are more likely to feel embarrassed than extroverted individuals. The three triggers of embarrassment, according to Sabini, Siepmann & Meyerowitz (2000), are faux pas, sticky situations and centre of attention. Faux pas causes embarrassment when an individual creates a social mistake that forces them to think of others’ evaluation, like misspelling a word in a presentation and only realising when presenting it to a supervisor. Sticky situations lead to embarrassment when they threaten an individual's role, not their self-esteem, such as a leader being challenged publicly by their second in command. Centre of attention describes an anomaly when embarrassment is not a result of failure but of increased attention, for example being at your own birthday party. The faux pas trigger aligns with the social evaluation model of embarrassment, whilst sticky situations are in line with the dramaturgic model of embarrassment. There are four prominent theories of embarrassment: the dramaturgic model, the social evaluation model, the situational self-esteem model and the personal standards model. The dramaturgic model proposed by Silver, Sabini and Parrott (1987) says that embarrassment is the flustered uncertainty that follows a poor public performance and leaves the individual at a loss of what to do. This model suggests that anxiety and aversive arousal trigger embarrassment after realising a performance has gone wrong (see Figure 4 ). In this model, concern about what others think accompanies embarrassment but does not cause it. Miller (1996) suggests that whilst the dramaturgic model has substantial support, it is difficult for a dramaturgic dilemma to cause embarrassment without simultaneously creating unwanted social evaluations, highlighting a limitation of this model. The social evaluation model of embarrassment put forward by Edelmann (1987) suggests that embarrassed individuals fear failure to impress others and feeling at a loss of what to do is a result of embarrassment, not the cause (see Figure 5 ). This model assumes that individuals are concerned about others’ opinions. Miller (1996) supports this theory, saying that negative evaluation from others is crucial to embarrassment. The situational self-esteem model by Modigliani (1971) proposes that the root cause of embarrassment is the temporary loss of self-esteem that results from public failures based on one’s own opinions of self and performance in faulty situations (see Figure 6). Miller (1995) does not support this theory, arguing that self-esteem plays a secondary role in embarrassment and states that susceptibility to embarrassment depends more on the persistent concern about others’ evaluations of us. The personal standards model of embarrassment introduced by Babcock (1988) presents the view that embarrassment is caused by the individual realising they have failed the standards of behaviour that they have set for themselves, implying that the situation does not matter and that individuals can feel embarrassment when they are alone (see Figure 7 ). Miller (1992) disagrees with this theory, saying that guidelines for self are linked to impressions made on other people and that embarrassment can happen due to poor audience reaction, not letting yourself down. Therefore, there are many plausible theories behind embarrassment that have been linked to various causes like dispositional, situational and personality factors. Whilst it is unlikely that one theory can perfectly explain such a complex social emotion like embarrassment, the consensus among psychologists in the recent years has created the most support for a combination of the dramaturgic and the social evaluation models. I agree with the consensus and think that the different theories behind embarrassment may all apply to a given situation. For instance, forgetting someone’s name may lead to embarrassment due to being at a loss of what to say (the dramaturgic model), unwanted social judgements (the social evaluation model), the negative effects of this situation on the self-esteem (the situational self-esteem model) and the painful realisation of letting yourself down (the personal standards model). Thus, like many subjects in psychology, embarrassment is a multidimensional concept that can be looked at from many different angles. Written by Aleksandra Lib Related articles: Chemistry of emotions / Unmasking aggression / Inside out: chemistry of depression REFERENCES Babcock, M. K. (1988). Embarrassment: A window on the self. Journal for the Theory of Social Behaviour . Edelmann, R. J. (1987). The psychology of embarrassment . John Wiley & Sons. Ekman, P. (1999). Basic emotions. Handbook of cognition and emotion , 98 (45-60), 16. Eysenck, H. J. (1983). Psychophysiology and personality: Extraversion, neuroticism and psychoticism. In Individual differences and psychopathology (pp. 13-30). Academic Press. Kelly, K. M., & Jones, W. H. (1997). Assessment of dispositional embarrassability. Anxiety, Stress, and Coping, 10 (4), 307-333. Lewis, M., Sullivan, M. W., Stanger, C., & Weiss, M. (1989). Self development and self-conscious emotions. Child development , 146-156. Miller, R. S. (1992). The nature and severity of self-reported embarrassing circumstances. Personality and Social Psychology Bulletin , 18 (2), 190-198. Miller, R. S. (1995). On the nature of embarrassabllity: Shyness, social evaluation, and social skill. Journal of personality , 63 (2), 315-339. Miller, R. S. (1996). Embarrassment: Poise and peril in everyday life. Guilford Press. Modigliani, A. (1971). Embarrassment, facework, and eye contact: Testing a theory of embarrassment. Journal of Personality and social Psychology , 17 (1), 15. Sabini, J., Siepmann, M., Stein, J., & Meyerowitz, M. (2000). Who is embarrassed by what?. Cognition & Emotion , 14 (2), 213-240. Silver, M., Sabini, J., Parrott, W. G., & Silver, M. (1987). Embarrassment: A dramaturgic account. Journal for the Theory of Social Behaviour , 17 (1), 47-61. Tracy, J. L., Robins, R. W., & Tangney, J. P. (2007). The self-conscious emotions. New York: Guilford . Project Gallery

Symmetry in spectroscopy, reaction mechanisms and bonding Facebook X (Twitter) WhatsApp LinkedIn Pinterest Copy link The importance of symmetry in chemistry Last updated: 02/04/26, 18:25 Published: 08/01/26, 08:00 Symmetry in spectroscopy, reaction mechanisms and bonding Introduction Symmetry is everywhere- in snowflakes, flowers and even art. Chemistry is no different and the symmetrical properties of a molecule often dictate its behaviour. From interpreting spectra, to predicting reaction pathways and understanding bonding, symmetry shapes all chemical disciplines. 1. Symmetry in spectroscopy Firstly, understanding the symmetry of molecules is essential in a range of characterisation techniques. In 1 H NMR spectroscopy, the number of peaks seen in a spectrum correspond to the number of unique chemical environments. For example, dibenzylidene acetone has a plane of symmetry and a rotational axis (C 2 ) through the centre of the carbonyl. This explains why the spectrum only has 5 different proton environments. In IR spectroscopy, infrared radiation is absorbed by a molecule causing stretching and bending of bonds when they vibrate. The total number of vibrational modes can be predicted using: • 3N – 5 rule for linear molecules • 3N – 6 rule for non-linear molecules (where N = no. of atoms) However, only vibrations which cause a change in dipole moment are seen in IR spectra. This explains why CO 2 only shows 3 main absorption peaks, despite having 4 vibrational modes. 2. Symmetry in reaction mechanisms Considering the symmetry of molecules also helps chemists predict the stereochemical outcome of organic reactions. A common example is the E2 elimination of a halogenoalkane, where an alkene is formed via elimination of a halogen. For an E2 elimination to occur, the H and the leaving group must be 180 ° from each other, in an ‘anti-periplanar’ conformation. To predict which groups, have this relationship, Newman projections are used to easily assign and rotate bonds. A Newman projection is a perspective of a molecule, typically by imagining you are looking down a specific C-C bond. See Figure 3 . 3. Symmetry in bonding Lastly, considering the symmetry of a molecule is vital for understanding Molecular Orbital (MO) Theory. MO theory explains how covalent bonding occurs by considering the symmetry elements of the valence orbitals. For example, in H 2 , the two valence 1s orbitals are completely symmetric and therefore can overlap effectively to form a σ molecular orbital. However, in HF, the introduction of 2p orbitals means the shape and symmetry has changed. The 2p x and 2p y orbitals can no longer overlap with the 1s H orbital as their symmetries are incompatible. Using this information, a MO diagram can be constructed to show how the orbitals combine, explaining why H 2 has a single bond. In essence, symmetry determines which orbitals can ‘match up’ to form bonds. See Figure 4 . Conclusion Symmetry influences every aspect of chemistry and is frequently employed to rationalise observed molecular characteristics. While sometimes overlooked, considering the symmetry of a molecule underpins any chemistry undertaken across industry and academia. If you enjoyed this article, future articles could build on this topic by introducing Group Theory and showing how you can predict an entire vibrational spectrum, or the molecular geometry of a compound based entirely on its symmetry. Written by Antony Lee Related article: Diels-Alder reaction REFERENCES S. Civis, M. Ferus, A. Knizek, in The Chemistry of CO 2 and TiO 2 : From Breathing Minerals to Life on Mars, ed. S. Civis, M. Ferus, A. Knizek, Springer Nature, Switzerland, 1 st edn., 2019, vol. 1, ch. 1, pp. 1-7 A. Burrows, J. Holman, S. Lancatser, T. Overton, A. Parsons, G. Pilling, G. Price, in Chemistry 3 , Oxford University Press, Oxford, 3 rd edn., 2017, ch.4, pp. 172-219 Project Gallery

Manufacturing doubt is another strategy where facts are intentionally changed to promote an agenda. It is used in the tobacco industry and against the climate crisis. Meaning articles can maintain the façade of using scientific methods by referencing sources that are difficult to interpret whilst research supported by sound evidence is labelled and downplayed. Go back Facebook X (Twitter) WhatsApp LinkedIn Pinterest Copy link How fake science websites hijack our trust in experts to misinform and confuse Last updated: 13/06/26 Published: 29/12/22 In science, all research is peer-reviewed by experts. Now, fake science websites are mimicking these disciplines. These websites capitalise on our trust in experts. In some cases, these websites are paid to publish fake science. This is becoming more common. In a recent global survey, almost 50% of respondents said they see false or misleading information online daily. By understanding the methods these sites use, we can prevent their influence. In the age of AI, low-quality and 'spammy' content are being generated automatically. This is a much faster process than writing content manually, and it is not easy to spot textual AI content. The content is low-quality due to heavy misinformation (incorrect factual data), and hallucinations (un-grounded, unverified facts or claims). It is important to differentiate between factual and misleading information, as science often involves a lot of high-risk data e.g. in medicine, health. Hyperlinking is a technique used to convince website users. They reassure the user that the content is credible, but most people don’t have experience in analytical techniques and so these links aren’t questioned. Repetition is used to increase the visibility of fake science content but also saturate search engines. This content can be repeated and spread across different sites. Users of “lateral reading” get multiple websites that corroborate the fake science from the initial source. Many of these sites only choose articles that agree with their perspective and depend on the audience not taking time to follow up. Manufacturing doubt is another strategy where facts are intentionally changed to promote an agenda. It is used in the tobacco industry and against the climate crisis. Meaning articles can maintain the façade of using scientific methods by referencing sources that are difficult to interpret whilst research supported by sound evidence is labelled and downplayed. On fake science websites first, check the hyperlinked articles. These websites will use sites with repeated content from disreputable sites. Next, look at the number of reposts a website has. Legitimate science posts are on credible websites. Some websites investigate websites that feature fake science. Cross-checking and re-verifying the information produced on these websites will also aid in spotting 'fake' content. Ultimately, these websites thrive on users not having the time or skills to look deeper into the evidence, so doing so will help expose the fake websites. Written by Antonio Rodrigues Related articles: Digital disinformation / COVID-19 misconceptions

It’s been found that the species Dicrurus adsimilis (fork-tailed drongos) uses deception by flexible alarm mimicry to target and carry out food-theft attempts. The deceptive tactics of the fork-tailed drongo were studied which includes the use of false alarm calls and mimicked calls. Research was done on 64 wild drongos in the Kalahari Desert and it was found that the drongos spent more than a quarter of their time watching their target species which included southern pied babblers and meerkats Go back Facebook X (Twitter) WhatsApp LinkedIn Pinterest Copy link Deception by flexible alarm mimicry in an African bird Last updated: 03/10/26 Published: 28/12/22 It’s been found that the species Dicrurus adsimilis (fork-tailed drongos) uses deception by flexible alarm mimicry to target and carry out food-theft attempts. The deceptive tactics of the fork-tailed drongo were studied which includes the use of false alarm calls and mimicked calls. Research was done on 64 wild drongos in the Kalahari Desert and it was found that the drongos spent more than a quarter of their time watching their target species which included southern pied babblers and meerkats. The other species’ would listen to the alarm calls made by drongos and would rush to take cover as they would if it was an alarm call from their species. These alarm calls were beneficial to them as it increased the number of returns from foraging and reduced their vigilance. However, the drongos used this to their advantage and if the target species was to find a large item of food the drongos could produce a false alarm call to make the target species run to cover out of fear which allowed the observing drongo to steal the deserted food. In 42% of cases of false alarms the drongos used a mimicked cry and in another 27% it was a mixture of mimicked and drongo-specific. This could be because target species are more likely to respond to a mimicked alarm call. In the case of babblers, if they heard a mimicked alarm call they would take longer to carry on foraging than with a drongo-specific call. The results show that false alarm calls by drongos work to distract their target but the call should also be frequently changed and not overused for best results. Written by Areebah Khan Related article: Conserving the Californian condor SUMMARISED FROM Flower, T.P., Gribble, M. and Ridley, A.R. (2014) “Deception by flexible alarm mimicry in an African bird,” Science, 344(6183), pp. 513–516.

Health in Syria and Lebanon are hindered by inequities and inequalities stemming primarily from warfare Facebook X (Twitter) WhatsApp LinkedIn Pinterest Copy link Syria and Lebanon’s diverging yet connected struggles Last updated: 03/05/26, 18:23 Published: 19/06/25, 08:00 Health in Syria and Lebanon are hindered by inequities and inequalities stemming primarily from warfare This is article no. 4 in a series about global health injustices. Previous article: Yemen- a neglected humanitarian crisis . Next article: Injustices in conflicted Kashmir . Introduction Welcome to the fourth article of the Global Health Injustices Series. The previous article discussed Yemen, specifically how the health and well-being of the population are affected by the intricate geopolitics at play. In this article, I collaborated with Jana Antar , to discuss Syria and Lebanon. Although these countries border one another, they encounter distinct challenges. Similar to previous articles, the health and wellbeing of the Syrian and Lebanese people are hindered by the inequities and inequalities stemming primarily from warfare. Impact of war on healthcare: Syria's deliberate destruction Since the onset of the Syrian conflict in 2011, the country’s healthcare system has been systematically dismantled. Beyond the direct casualties of war, the destruction of hospitals, clinics, and medical supply chains has led to a secondary crisis, one where preventable deaths become inevitable. Between 2011 and 2020, Physicians for Human Rights documented nearly 600 attacks on healthcare facilities. Since 2 March 2026, 92 attacks on health care have been reported in Lebanon, resulting in 137 injuries and 53 deaths. The deliberate targeting of hospitals and medical personnel has rendered healthcare not just a casualty of war, but a weapon of war itself ( Figure 1 ). This destruction has had catastrophic consequences. Maternal and infant mortality rates have soared, vaccination coverage has plummeted, and chronic disease management has become nearly impossible. In the northwest of Syria, where displaced populations reside in makeshift camps, infectious diseases such as cholera and tuberculosis continue to spread due to poor sanitation and lack of medical oversight. The COVID-19 pandemic only exacerbated these challenges, whereby 46% of reported cases in Northwest Syria resulted in death due to the collapse of medical infrastructure. As of early 2025, only 57% of hospitals and 37% of primary healthcare centres in Syria remain fully functional. The remaining facilities operate under severe constraints due to damage from attacks and resource shortages. In 2024 alone, there were 77 attacks on healthcare facilities, further disrupting access to trauma care, maternal health, and treatment for chronic illnesses. Overcrowding in displacement camps and poor sanitation have also heightened the risk of outbreaks such as tuberculosis, making urgent intervention critical ( Figure 2 ). Impact of war on healthcare: Lebanon's fragile healthcare system Lebanon, a country once regarded as a regional medical hub, has borne the brunt of Syria’s refugee crisis. With an estimated 1.5 million Syrian refugees seeking shelter within its borders, the country has faced a 50% surge in demand for healthcare services. The healthcare system, already strained before the crisis, has since crumbled under the weight of economic collapse, political instability, and donor fatigue. The Lebanese economic crisis, which began in 2019, had devastating effects on healthcare delivery. The Lebanese pound has lost over 90% of its value, placing essential medical supplies out of reach for hospitals and individuals. Pharmacies frequently run out of life-saving medications, power outages disrupt critical care units, and the departure of healthcare professionals has left hospitals understaffed. The situation has worsened due to escalating hostilities, starting from the south of Lebanon and later expanding, displacing over 112,000 people as of February 2025. The violence has led to the closure of 130 primary health centres and seven hospitals, with 15 out of 153 hospitals either non-functional or operating at reduced capacity. In Nabatieh Governorate alone, 40% of hospital bed capacity has been lost. Attacks on health workers and facilities continued to mount between January and November 2024, when 137 attacks were reported, nearly half of which resulted in fatalities. These disruptions create a ripple effect, limiting immediate medical care and undermining public health initiatives such as vaccination programs and maternal health services. NGOs: the last line of defence In the face of government inaction, non-governmental organisations (NGOs) have become the backbone of healthcare provision in Syria and Lebanon. International and local NGOs have mobilised to provide vaccination campaigns, mental health support, and medical supplies to those in need. For example, WHO and UNICEF have facilitated vaccination drives, reaching 250,000 children under five years old, 30% of whom were displaced Syrians. However, while NGOs have played a crucial role in mitigating healthcare crises, their efforts remain primarily reactive rather than systemic and preventative, addressing immediate needs without long-term sustainability, and not adequately focusing on precautionary measures to avoid these undesirable situations. In fact, NGOs face mounting challenges. The overwhelming demand for services, lack of sustainable funding, and security threats have made it increasingly difficult for organisations to operate. Moreover, while NGOs are stretched in their deliverables, the humanitarian workers encounter frequent targeting, making their mission even more perilous. Conclusion: the role of the international community The crises in Syria and Lebanon are not isolated events; they are a reflection of global health injustices that demand international attention and intervention. Providing short-term aid is no longer enough, so long-term solutions must be prioritised to rebuild these destroyed healthcare systems. Moreover, de-escalating both crises would improve health outcomes for the vulnerable communities in Syria and Lebanon. The next article will focus on the population in conflicted Kashmir; addressing their injustices is crucial because of the profound impact and lack of coverage in mainstream discussions. Written by Jana Antar and Sam Jarada Related articles: Understanding health through different stances / Ethnic , and Socioeconomic health equalities REFERENCES A Decade of Destruction: Attacks on health care in Syria. The IRC. 2025. Available from: https://www.rescue.org/report/decade-destruction-attacks-health-care-syria-0 The Syrian Conflict: Eight Years of Devastation and Destruction of the Health System - PHR. PHR. 202. Available from: https://phr.org/our-work/resources/the-syrian-conflict-eight-years-of-devastation-and-destruction-of-the-health-system/ Ammar W, Kdouh O, Hammoud R, Hamadeh R, Harb H, Ammar Z, et al. Health system resilience: Lebanon and the Syrian refugee crisis. Journal of Global Health. 2016 Dec;6(2). Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC5234495/ Lebanon 2025 Indicators and Targets Lebanon Multi-year Strategy 2023 -2025. Available from: https://reporting.unhcr.org/sites/default/files/2025-01/Lebanon%20-%20Strategy%202023%20%E2%80%93%202025_0.pdf Lebanon | Humanitarian Action. Humanitarianaction.info . 2024. Available from: https://humanitarianaction.info/document/global-humanitarian-overview-2025/article/lebanon-1 WHO. WHO’s Health Emergency Appeal 2025 [Internet]. 2025. Available from: https://cdn.who.int/media/docs/default-source/documents/emergencies/2025-appeals/2025-hea-lebanon.pdf?sfvrsn=45f2a018_5&download=true Lebanon’s Pharmaceutical Sector: Challenges, Opportunities, and Strategic Solutions. LCPS. 2025. Available from: https://www.lcps lebanon.org/en/articles/details/4903/lebanon%E2%80%99s-pharmaceutical-sector-challenges-opportunities-and-strategic-solutions Sousa C, Akesson B, Badawi D. “Most importantly, I hope God keeps illness away from us”: The context and challenges surrounding access to health care for Syrian refugees in Lebanon. Global Public Health. 2020 Jun 12;1–10. Syrian refugee access to healthcare in Lebanon - Lebanon. ReliefWeb. 2020. Available from: https://reliefweb.int/report/lebanon/syrian-refugee-access-healthcare-lebanon World. Lebanon: a conflict particularly destructive to health care [Internet]. Who.int . World Health Organization: WHO; 2024. Available from: https://www.who.int/news/item/22-11-2024-lebanon--a-conflict-particularly-destructive-to-health-care Project Gallery

The most famous pericyclic reaction is the Diels–Alder cycloaddition Facebook X (Twitter) WhatsApp LinkedIn Pinterest Copy link Diels–Alder Reaction Last updated: 02/04/26, 18:27 Published: 02/04/26, 08:00 The most famous pericyclic reaction is the Diels–Alder cycloaddition Introduction How does a chemical reaction proceed? This is one of the most important questions in chemistry and still drives research today. Traditionally, reactions have been classed as either ionic or radical processes. But there is a third class: a pericyclic reaction. The pericyclics, named because of their concerted curly arrow mechanisms, are a class of reaction governed by orbital symmetry. Often triggered by heat or light, they are some of the ‘greenest’ reactions, frequently achieving 100% atom economy. Perhaps the most famous pericyclic reaction is the Diels–Alder cycloaddition. Awarded a Nobel Prize in 1950, this reaction has been used extensively in both industry and academia. This article will explore how the Diels–Alder reaction works, supported by examples of its use in total natural product syntheses. Diels-Alder reaction: orbital considerations The Diels–Alder reaction proceeds thermally, with a diene and a dienophile interacting with the correct orbital phases. To explain this, let’s consider the reaction of butadiene (diene) with ethene (dienophile) to form cyclohexene. In butadiene, there are four valence p orbitals, each of which can interact in phase (same colours touching) or out of phase (different colours overlapping), leading to the generation of four molecular orbitals. For ethene, two molecular orbitals are generated, as there are only two valence p orbitals. For all chemical reactions to proceed, the highest occupied molecular orbital (HOMO) and the lowest unoccupied molecular orbital (LUMO) of the reactants must overlap in phase. Considering the phases of the diene HOMO and the dienophile LUMO shows they can interact favourably. The curly arrows move cyclically to generate cyclohexene. Stereochemistry In terms of stereochemistry, the Diels–Alder reaction follows two rules which govern its reactivity. Firstly, the diene starting material must be s‑cis, meaning the double bonds must be cis to one another for the orbital overlap to be successful. Secondly, the Diels–Alder reaction always maintains any stereochemical information of the starting material. For example, reacting butadiene with dimethyl maleate always gives a cis product. Both isomers of the product will form, as this reaction is not stereoselective. Applications of the Diels–Alder Reaction The Diels–Alder reaction has a rich and diverse history in the synthesis of total natural products. In 1952, Woodward et al. were the first to incorporate a Diels–Alder reaction into a total synthesis of cholesterol. Woodward also used a Diels–Alder reaction in his famous synthesis of reserpine, a medicinal product used to treat high blood pressure. Another interesting example of the Diels–Alder reaction in a complex synthesis was Danishefsky’s synthesis of myrocin C, an antibiotic with anti‑tumour properties. The ingenuity of this synthesis is that the intermediary fragment was specifically designed to undergo an intramolecular Diels–Alder reaction. Conclusion In conclusion, the Diels–Alder reaction is a titan of synthetic chemistry. As the chemical industry continues to adopt more sustainable chemistry, the Diels–Alder reaction is still as relevant as it was almost 100 years ago. While this article has centred on the Diels–Alder reaction, the pericyclic reactions are far more extensive. There are further cycloadditions as well as electrocyclisations, sigmatropic rearrangements and group transfer reactions. These transformations show the elegance of synthetic chemistry and re‑emphasise the importance of symmetry in all chemical disciplines. Written by Antony Lee Related article: Symmetry in chemistry Project Gallery

Channel-blocking nanoparticles as a potential solution to plant diseases Facebook X (Twitter) WhatsApp LinkedIn Pinterest Copy link The secret to disarming plant pathogens revealed Last updated: 22/09/25, 11:14 Published: 27/03/25, 08:00 Channel-blocking nanoparticles as a potential solution to plant diseases Unravelling the role of bacterial proteins in plant diseases! Disarming plant diseases one protein at a time! Scientists may have found a means to neutralise them, saving farmers $220 billion in yearly crop losses. The impact of plant diseases on global food production Bacteria have long been known to wreak havoc on crops, threatening our food supply and causing substantial economic losses. For over two decades, biologist Sheng-Yang He and his dedicated team have been delving into the mysterious world of bacterial proteins, seeking to unravel their role in plant diseases that plague countless crops worldwide. Finally, a breakthrough has been achieved after years of tireless research and collaboration. In a groundbreaking study published in the esteemed journal Nature, he and his colleagues have uncovered the mechanisms by which these proteins induce disease in plants and devised a method to neutralise their harmful effects. Understanding the mechanism of harmful proteins Their investigation focused on a group of injected proteins called AvrE/DspE, responsible for causing diseases ranging from brown spots in beans to fire blight in fruit trees. Despite their significance, the exact workings of these proteins have long remained elusive. The researchers discovered that these proteins adopt a unique 3D structure resembling a tiny mushroom with a cylindrical stem through cutting-edge advancements in artificial intelligence and innovative experimental techniques. Intriguingly, this structure resembled a straw, leading the team to hypothesise that the proteins create channels in plant cells, enabling the bacteria to extract water from the host during infection. Further investigation into the 3D model of the fire blight protein revealed that its hollow inner core contains many proteins from the AvrE/DspE family. These proteins were found to suppress the plant's immune system and induce dark water-soaked spots on leaves, the telltale signs of infection. However, armed with this newfound knowledge, the researchers sought to develop a strategy to disarm these proteins and halt their destructive effects. They turned to poly(amidoamine) dendrimers (PAMAM), tiny spherical nanoparticles with precise diameters that can be tailored in the lab. By experimenting with different sizes, they identified a nanoparticle that effectively blocked the water channels formed by the bacterial proteins. Application of nanoparticles in blocking water channels In a remarkable series of experiments, the researchers treated frog eggs engineered to produce the water channel protein with these channel-blocking nanoparticles. The results were astounding—the eggs no longer swelled with water and remained unaffected. Similarly, infected Arabidopsis plants treated with the nanoparticles significantly reduced pathogen concentrations, effectively preventing disease development. This breakthrough discovery offers a glimmer of hope in the battle against plant diseases, which cause immense losses in global food production. Plants are responsible for 80% of the world's food supply, and protecting them from pathogens and pests is crucial for ensuring food security. The team's groundbreaking research on plant pathogens and their harmful proteins opens up new possibilities for combating various plant diseases. The implications of their findings extend far beyond a single crop or disease, offering novel approaches to address a wide range of plant diseases. By understanding the mechanism by which bacterial proteins, such as AvrE and DspE, cause diseases in plants, researchers can now explore strategies to disarm these proteins and prevent their harmful effects. The team discovered that these proteins act as water channels, allowing bacteria to invade plant cells and create a saturated environment that promotes their growth. This insight led to the development of channel-blocking nanoparticles, effectively preventing bacteria from infecting plants and causing disease symptoms. Using precise nanoparticles, such as PAMAM dendrimers, to block plant pathogens' water channels represents a promising avenue for crop protection. Figure 1: this figure shows that PAMAM are very branched polymers that are very small, have a low polydispersity index, and have a lot of active amine functional groups. They have multiple modifiable surface functionalities, facilitating the conjugation of ligands for cancer targeting, imaging, and therapy. PAMAM dendrimers also have solubilisation, high drug encapsulation, and passive targeting ability, contributing to their therapeutic success. Cancer researchers are excited about their potential as drug carriers and non-viral gene vectors, with a focus on diagnostic imaging applications. These nanoparticles can be tailored to specific diameters, allowing for targeted disruption of the bacterial proteins' channels. The nanoparticles effectively render the bacteria harmless by interfering with the proteins' ability to create a moist environment within plant cells. This innovative approach has shown success in combating diseases caused by pathogens like Pseudomonas syringae and Erwinia amylovora . Implications for global food production and food security The potential impact of this research on global food production is immense. Plant diseases result in significant crop losses, amounting to over 10% of global food production annually. This translates to a staggering $220 billion economic loss worldwide. Developing strategies to disarm harmful proteins and protect crops from diseases can mitigate these losses and enhance food security. Furthermore, the team's findings highlight the critical role of plant biology research in addressing global challenges. Plants provide 80% of our food, making their health and protection crucial for sustaining our growing population. By understanding how pathogens infect plants and developing innovative solutions, we can safeguard our food supply and reduce the economic impact of crop diseases. Experimental results and a promising outlook The researchers aim to further investigate the interaction between channel-blocking nanoparticles and bacterial proteins. By visualising the structures and mechanisms involved, they hope to refine their designs and develop even more effective strategies for crop protection. Additionally, artificial intelligence, such as the AlphaFold2 programme, has proven instrumental in predicting the 3D structures of complex proteins. Continued advancements in AI technology will undoubtedly contribute to further breakthroughs in understanding and combating plant diseases. By unravelling the mechanisms by which harmful proteins cause diseases in plants and developing innovative strategies to disarm them, we can protect global food production and enhance food security. The implications of this research extend beyond a single crop or disease, paving the way for novel approaches to combat a wide range of plant diseases and safeguard our agricultural systems. Conclusion The groundbreaking research conducted by biologist Sheng-Yang He and his team offer hope in the fight against plant diseases. By revealing the mechanisms by which harmful proteins cause diseases in plants and developing innovative strategies to disarm them, they have paved the way for novel approaches to combat various plant diseases. This enhances food security and protects global food production, reducing economic losses and ensuring a sustainable future. With continued advancements in artificial intelligence and the development of precise nanoparticles, the possibilities for further breakthroughs in understanding and combating plant diseases are endless. By safeguarding our agricultural systems, we can secure the health of our crops and, ultimately, the well-being of our growing population. The implications of this research extend far beyond agriculture, offering new avenues for addressing global challenges and paving the way for a brighter and more resilient future. Figure 2: this figure shows a working model for the molecular actions of AvrE-family effectors in plants. AvrE-family effectors are water- and solute-permeable channels that change the osmotic and water potential and make an apoplast that is rich in water and nutrients for bacteria to grow in plant tissues that are infected. They can also engage host proteins to modulate AvrE-family channel properties or optimise pathogenic outcomes. Written by Sara Maria Majernikova Related articles: Digital innovation in rural farming / Nanomedicine / Mechanisms of pathogen evasion / Nanocarriers REFERENCE Kinya Nomura, Felipe Andreazza, Jie Cheng, Ke Dong, Pei Zhou, Sheng Yang He. Bacterial pathogens deliver water- and solute-permeable channels to plant cells. Nature , 2023; DOI: 10.1038/s41586-023-06531-5 Project Gallery

Total solar eclipses Facebook X (Twitter) WhatsApp LinkedIn Pinterest Copy link Totality- Our Perfect Eclipse 14/07/25, 16:05 Last updated: Published: 24/05/23, 11:05 Total solar eclipses We are all familiar with the characteristic depiction of a solar eclipse, when the Moon passes directly between the Sun and the Earth. However, the significance of solar eclipses extends far beyond their aesthetic appeal. Major scientific discoveries, cultural practices, and even the behaviour of wild animals are derived from total solar eclipses that we have the privilege of experiencing (See image 1). A solar eclipse occurs when the Earth, Moon, and Sun all appear to lie on a straight line. They are collinear. Total solar eclipses occur when the Moon completely obscures the Sun's photosphere, enabling prominences and coronal filaments to be seen along the limb. This phenomenon is unique to the Earth, Sun, and Moon system and to understand why we must explore the mathematics underlying these ‘orbital gymnastics’. We wish to compare the ‘apparent’ size of the Sun and Moon, a quantity proportional to the ratio of their size and distance from Earth. The Moon has a radius of around 3,400 km, and is approximately 384,000 km from Earth. The Sun has a much larger radius of 1.4 million km, and is located at a distance of 150 million km. By dividing the Sun's radius by the Moon's radius and dividing the Earth-Sun distance by the Earth-Moon distance, we can determine that the Sun is 400 times larger than the Moon and 400 times further away. This unique relationship allows for total solar eclipses, where totality indicates **the complete blocking of sunlight from the Sun’s disk by the Moon. In partial eclipses, only part of the Sun is obscured. One might wonder why we don’t have total solar eclipses every month, and the reason is that the plane of the Moon’s orbit around Earth is tilted at 5 degrees relative to Earth’s orbital plane. This hugely decreases the likelihood of such perfect alignment. Of the hundreds of moons orbiting planets in our Solar System, only our Moon totally eclipses the Sun. For example, none of Jupiter’s 95 moons have the correct size and orbital separation that completely block out the Sun from any point on Jupiter’s surface! Surely this serendipitous interplay of Earth, Sun, and Moon cannot be a coincidence? (See image 2) It is at this point where divine intervention is typically invoked. There are a few problems with doing this. The Moon's eccentric orbit around Earth means that it will be closer during some total solar eclipses than others, resulting in annular eclipses when the Moon is furthest from Earth. Additionally, the Moon is receding from the Earth at a rate of 4 cm/year, which means that total solar eclipses will only be observable for another 250 million years. (See image 3) For those of you who wish to make the most of this brief window of opportunity, this website shows the dates and locations of upcoming total solar eclipses. Written by Joseph Brennan REFERENCE Guillermo Gonzalez, Wonderful eclipses, Astronomy & Geophysics , Volume 40, Issue 3, June 1999, Pages 3.18–3.20, https://doi.org/10.1093/astrog/40.3.3.18 Project Gallery

Peruse through the current treatment discoveries for one of the deadliest diseases in the world. Learn about the factors that cause tumour growth, metastatic processes and blastomas. Cancer Articles Peruse through the current treatment discoveries for one of the deadliest diseases in the world. Learn about the factors that cause tumour growth, metastatic processes and blastomas. You may also like: Biology, Medicine Arginine and tumour growth Another breakthrough in cancer research Unveiling the cancer magnet Stem cells in vertebral bones can act like cancer magnets for spinal tumour metastasis Brain metastasis in cognitive impairment Researchers used machine learning to investigate this Novel neuroblastoma driver Uncovering the role of IGF2BP1 in neuroblastoma and its potential as a therapeutic target Previous