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Book review Facebook X (Twitter) WhatsApp LinkedIn Pinterest Copy link 'The Emperor of All Maladies' by Siddhartha Mukherjee 08/03/25, 14:04 Last updated: Published: 28/11/24, 14:55 Book review Stretching nearly 4,000 years of history, Pulitzer Prize winner Siddhartha Mukherjee sets on a journey to document the biography of cancer in The Emperor of All Maladies. Drawing from a vast array of books, studies, interviews, and case studies, Mukherjee crafts a narrative that is as comprehensive as it is compelling. Driven by curiosity and a desire to understand the origins of cancer, Mukherjee sets the tone by reflecting on his experiences as an oncology trainee, drawing insightful parallels to contemporary perspectives on the fight against this relentless disease. Mukherjee also pays homage to Ancient Egyptian and Greek physicians for their early observations on cancer, from the work on Imhotep to Claudius Galen. He then introduces Sidney Farber, whose monumental contributions to modern chemotherapy are brought to life through Mukherjee's exceptional storytelling—tracing Farber's journey from his initial observations to his unprecedented success in treating children with leukaemia. As you progress through each chapter of this six-part book, your appreciation deepens for how far cancer treatments have advanced - and how much further they can go. Mukherjee’s unparalleled skill as a science communicator shines through, seamlessly weaving together groundbreaking scientific discoveries with the historical contexts in which they emerged contributing to an immersive reading experience. Siddhartha Mukherjee, The Emperor of All Maladies : In 2005, a man diagnosed with multiple myeloma asked me if he would be alive to watch his daughter graduate from high school in a few months. In 2009, bound to a wheelchair, he watched his daughter graduate from college. The wheelchair had nothing to do with his cancer. The man had fallen down while coaching his youngest son's baseball team. Mukherjee also makes an effort to highlight the critical role of raising awareness in shaping public health outcomes. ‘Jimmy’ was a cancer patient that represented children with cancer, his real name was Einar Gustafson, but his individual story was able to galvanise large-scale support. As the face of the ‘Jimmy Fund’, he was able to assist in raising $231,485.51 for the Dana-Farber Institute subsequently becoming the official charity for the Boston Red Sox. Mukherjee underscores how storytelling can serve as a catalyst for change, not just in raising money, but also in enacting larger societal and governmental shifts. In 1971, President Richard Nixon signed the National Cancer Act, the first of its kind where federal funding went directly into advancing cancer research. What struck me most was how Mukherjee connects this historical event to the broader need for advocacy, as science doesn’t just happen in the lab. It is a collective effort, driven by awareness, to push funding and influence policy. The ability to link individual stories to broader missions, as Mukherjee illustrates, continues to be one of the most effective strategies in keeping cancer research in the public eye. Mukherjee delves into the pivotal role of genetics in cancer research, tracing its evolution from the discovery of DNA's structure by Francis Crick, James Watson, and Rosalind Franklin to Robert Weinberg's ground-breaking work on how proto-oncogenes and tumour suppressors drive cancer progression. These discoveries ushered in a new era in cancer drug development. Mukherjee also emphasises the importance of collaboration and the rise of the internet, which gave birth to The Cancer Genome Atlas, a landmark program, that unites various research disciplines to diagnose, treat, and prevent cancer. In concluding the book, Mukherjee looks ahead to the future of cancer treatment, seamlessly connecting this discussion to his second book, The Gene . This book takes readers on a remarkable journey through the history of cancer, from the earliest recorded cases to groundbreaking discoveries in genetics. It weaves together compelling personal stories as well as pivotal moments in governmental policy. The storytelling is rich and immersive, drawing you in with its detail and depth. By the time you finish, you'll find yourself returning to its pages, eager to revisit the knowledge and insights it offers. Written by Saharla Wasarme Related book review: Intern Blues Project Gallery

The maths behind trading Facebook X (Twitter) WhatsApp LinkedIn Pinterest Copy link A comprehensive guide to the Relative Strength Index (RSI) 08/07/25, 14:37 Last updated: Published: 27/12/23, 11:02 The maths behind trading In this piece, we will delve into the essential concepts surrounding the Relative Strength Index (RSI). The RSI serves as a gauge for assessing the strength of price momentum and offers insights into whether a particular stock is in an overbought or oversold condition. Throughout this exploration, we will demystify the underlying calculations of RSI, explore its significance in evaluating market momentum, and unveil its practical applications for traders. From discerning opportune moments to buy or sell based on RSI values to identifying potential shifts in market trends, we will unravel the mathematical intricacies that underpin this critical trading indicator. Please note that none of the below content should be used as financial advice, but for educational purposes only. This article does not recommend that investors base their decisions on technical analysis alone. As indicated in the name, RSI measures the strength of a stock's momentum and can be used to show when a stock can be considered over- or under-bought, allowing us to make a more informed decision as to whether we should enter a position or hold off until a bit longer. It’s all very well and good to know that ‘you should buy when RSI is under 30 and sell when RSI is over 70' , but in this article, I will attempt to explain why this is the case and what RSI is really measuring. The calculations The relative strength index is an index of the relative strength of momentum in a market. This means that its values range from 0 to 100 and are simply a normalised relative strength. But what is the relative strength of momentum? Initial Average Gain = Sum of gains over the past 14 days / 14 Initial Average Loss = Sum of losses over the past 14 days / 14 Relative strength is the ratio of higher closes to lower closes. Over a fixed period of usually 14 days (but sometimes 21), we measure how much the price of the stock has increased in each trading day and find the mean average between them. We then repeat and do the same to find the average loss. The subsequent average gains and losses can then be calculated: Average Gain = [(Previous Avg. Gain * 13) + Current Day's Gain] / 14 Average Loss = [(Previous Avg. Loss * 13) + Current Day's Loss] / 14 With this, we can now calculate relative strength! Therefore, if our stock gained more than it lost in the past 14 days, then our RS value would be >1. On the other hand, if we lost more than we gained, then our RS value would be <1. Relative strength tells us whether buyers or sellers are in control of the price. If buyers were in control, then the average gain would be greater than the average loss, so the relative strength would be greater than 1. In a bearish market, if this begins to happen, we can say that there is an increase in buyers’ momentum; the momentum is strengthening. We can normalise relative strength into an index using the following equation: Relative Strength= Average Gain / Average Loss Traders then use the RSI in combination with other techniques to assess whether to buy or sell. When a market is ranging, which means that price is bouncing between support and resistance (has the same highs and lows for a period), we can use the RSI to see when we may be entering a trend. When the RSI is reaching 70, it is an indication that the price is being overbought, and in a ranging market, there is likely to be a correction and the price will fall so that the RSI stays at around 50. The opposite is likely to happen when the RSI dips to 30. Price action is deemed to be extreme, and a correction is likely. It should, however, be noted that this type of behaviour is only likely in assets presenting mean-reversion characteristics. In a trending market, RSI can be used to indicate a possible change in momentum. If prices are falling and the RSI reaches a low and then, a few days later, it reaches a higher low (therefore, the low is not as low as the first), it indicates a possible change in momentum; we say there is a bullish divergence. Divergences are rare when a stock is in a long-term trend but is nonetheless a powerful indicator. In conclusion, the relative strength index aims to describe changes in momentum in price action through analysing and comparing previous day's highs and lows. From this, a value is generated, and at the extremes, a change in momentum may take place. RSI is not supposed to be predictive but is very helpful in confirming trends indicated by other techniques. Written by George Chant Project Gallery

Unleashing the power of mRNA: revolutionising medicine with personalised vaccines Facebook X (Twitter) WhatsApp LinkedIn Pinterest Copy link The exciting potential of mRNA vaccines 11/07/25, 10:03 Last updated: Published: 03/12/24, 12:19 Unleashing the power of mRNA: revolutionising medicine with personalised vaccines Basic mRNA vaccine pharmacology Basic mRNA vaccine pharmacology involves the study of two types of RNA used as vaccines: non-replicating mRNA and self-amplifying RNA. Non-replicating mRNA-based vaccines encode the antigen of interest and contain untranslated regions (UTRs) at both ends. Self-amplifying RNAs, on the other hand, encode both the antigen and the viral replication machinery, allowing for intracellular RNA amplification and abundant protein expression. For successful protein production in mRNA therapeutics, the optimal translation of in vitro transcribed (IVT) mRNA is crucial. Factors such as the length of the poly(A) tail, codon usage, and sequence optimisation can influence translation efficiency and accuracy. Adding an optimal length of poly(A) to mRNA is necessary for efficient translation. This can be achieved by directly incorporating it from the encoding DNA template or by using poly(A) polymerase. Codon usage also plays a role in protein translation. Replacing rare codons with frequently used synonymous codons, which have abundant cognate tRNA in the cytosol, can enhance protein production from mRNA. However, the accuracy of this model has been subject to questioning. Optimally translated IVT mRNA encoding mRNA IVT mRNA plays a crucial role in mRNA vaccines as it is designed for optimal translation, ensuring efficient protein production. To achieve this, a 5ʹ cap structure is added, which is essential for efficient protein synthesis. Different versions of 5ʹ caps can be added during or after the transcription process. Furthermore, the poly(A) tail plays a significant regulatory role in mRNA translation and stability. Sequence optimisation is another critical factor that can enhance mRNA levels and protein expression. Increasing the G:C content has been shown to elevate steady-state mRNA levels in vitro and improve protein expression in vivo. Furthermore, modifying the codon composition or introducing modified nucleosides can positively influence protein expression. However, it is important to note that these sequence engineering techniques may impact mRNA secondary structure, translation kinetics, accuracy, protein folding, as well as the expression of alternative reading frames and cryptic T-cell epitopes. Sequence optimisation for protein translation Sequence optimisation plays a crucial role in the development of mRNA vaccines. It involves modifying the mRNA sequence to improve the efficiency of protein translation. By optimising the sequence, researchers can enhance the expression and stability of therapeutic mRNAs. However, the immunogenicity of exogenous mRNA is a concern, as it can trigger a response from various innate immune receptors. In some cases, encoding mRNA in the hypothalamus may even elicit a physiological response. Despite initial promising outcomes, the development of mRNA therapeutics has been hindered by concerns regarding mRNA instability, high innate immunogenicity, and inefficient in vivo delivery. As a result, DNA-based and protein-based therapeutic approaches have been preferred in the past. Modulation of immunogenicity Modulation of immunogenicity is a crucial aspect of mRNA vaccine development. Researchers aim to design mRNA vaccines that elicit a strong immune response while minimising adverse reactions. This involves careful selection of antigens and optimisation of the mRNA sequence to enhance immunogenicity. Self-replicating RNA vaccines and adjuvant strategies, such as TriMix, have shown increased immunogenicity and effectiveness. The immunostimulatory properties of mRNA can be further enhanced by including adjuvants. The size of the mRNA-carrier complex and the level of innate immune sensing in targeted cell types can influence the immunogenicity of mRNA vaccines. Advantages of mRNA vaccines mRNA vaccines offer several advantages over conventional vaccine approaches. First, they have high potency, meaning they can induce a strong immune response. Second, they have a capacity for rapid development, allowing for quick vaccine production in response to emerging infectious diseases or new strains. Third, mRNA vaccines have the potential for rapid, inexpensive, and scalable manufacturing, mainly due to the high yields of in vitro transcription reactions. Additionally, mRNA vaccines are minimal genetic vectors, avoiding anti-vector immunity, and can be administered repeatedly. However, recent technological innovations and research investments have made mRNA a promising therapeutic tool in vaccine development and protein replacement therapy. mRNA has several advantages over other vaccine platforms, including safety and efficacy. It is non-infectious and non-integrating, reducing the risk of infection and insertional mutagenesis. mRNA can be regulated in terms of in vivo half-life and immunogenicity through various modifications and delivery methods. Production of mRNA vaccines The production of mRNA vaccines involves in vitro transcription (IVT) of the optimised mRNA sequence. This process allows for the rapid and scalable manufacturing of mRNA vaccines. High yields of IVT mRNA can be obtained, making the production process cost-effective. Making mRNA more stable and highly translatable is achievable through modifications. Efficient in vivo delivery can be achieved by formulating mRNA into carrier molecules. The choice of carrier and the size of the mRNA-carrier complex can also modulate the cytokine profile induced by mRNA delivery. Current mRNA vaccine approaches (Figure 1) There are several current mRNA vaccine approaches being explored. These include the development of mRNA vaccines against infectious diseases and various types of cancer. mRNA vaccines have shown promising results in both animal models and humans. Cancer vaccines Cancer vaccines are a type of immunotherapy that aim to stimulate the body's immune system to recognise and destroy cancer cells. These vaccines work by introducing specific antigens, which are substances that can stimulate an immune response, into the body. The immune system then recognises these antigens as foreign and mounts an immune response against them, targeting and destroying cancer cells that express these antigens. There are different types of cancer vaccines, including personalised vaccines and predefined shared antigen vaccines. Personalised vaccines are tailored to each patient and are designed to target specific mutations or antigens present in their tumor. These vaccines are created by identifying tumor-specific antigens by sequencing the patient's tumor DNA and predicting which antigens are most likely to elicit an immune response. These antigens are then used to create a vaccine that is specific to that patient's tumor. On the other hand, predefined shared antigen vaccines are designed to target antigens that are commonly expressed in certain types of cancer. These vaccines can be used in multiple patients with the same type of cancer and are not personalised to each individual. The antigens used in these vaccines are selected based on their ability to induce an immune response and their potential to be recognised by T cells. Despite the promising potential of cancer vaccines, their clinical progress is limited, and skepticism surrounds their effectiveness. While there have been some examples of vaccines that have shown systemic regression of tumors and prolonged survival in small clinical trials, many trials have yielded marginal survival benefits. Challenges such as small trial sizes, resource-intensive approaches, and immune escape of heterogeneous tumors have hindered the field's progress. However, it is important to note that other immunotherapies, such as monoclonal antibodies and chimeric antigen receptor (CAR) T-cell therapies, have also faced challenges and setbacks before eventually achieving success. Therefore, cancer vaccines may also have the potential for eventual success, given their clear rationale and compelling preclinical data. To improve the efficacy of cancer vaccines, researchers are exploring various strategies. These include optimising antigen presentation and immune activation by using adjuvants or agonists of pattern-recognition receptors. Additionally, advancements in sequencing technologies and computational algorithms for epitope prediction allow for the identification of more specific tumor mutagens and the production of personalised neo-epitope vaccines. Neo-epitope vaccines are a type of personalised vaccine that target specific mutations or neo-epitopes present in a patient's tumor. These vaccines exploit the most specific tumor mutagens identified through computational methods and prioritise highly expressed neo-epitopes. They can be given with adjuvants to enhance their immunogenicity. Hence, cancer vaccines hold promise as a potential standard anti-cancer therapy. While their progress has been limited, a clear rationale and compelling preclinical data support their further development. Personalised vaccines targeting specific mutations or antigens present in a patient's tumor, as well as predefined shared antigen vaccines targeting commonly expressed antigens, are being explored. Future of mRNA vaccines mRNA vaccines have emerged as a promising alternative to traditional vaccine approaches due to their high potency, rapid development capabilities, and potential for low-cost manufacture and safe administration. Recent technological advancements have addressed the challenges of mRNA instability and inefficient in vivo delivery, leading to encouraging results in the development of mRNA vaccine platforms against infectious diseases and various types of cancer. Looking ahead, the future of mRNA vaccines holds great potential for further advancements and widespread therapeutic use. Efficient in vivo delivery of mRNA remains a critical area of focus for future development. Researchers are working on improving delivery systems to ensure targeted delivery to specific cells or tissues, thereby enhancing the effectiveness of mRNA vaccines. This includes the development of lipid nanoparticles, viral vectors, and other delivery mechanisms to optimize mRNA delivery and cellular uptake. The success of mRNA vaccines against infectious diseases and cancer has opened doors to exploring their potential in other areas of medicine. Future research may involve the development of mRNA vaccines for autoimmune disorders, allergies, and chronic diseases. The versatility of mRNA technology allows for the rapid adaptation of vaccine candidates to address various medical conditions. One exciting prospect for mRNA vaccines is their potential for personalised medicine. The ability to easily modify the genetic sequence of mRNA allows for the development of personalised vaccines tailored to an individual's specific genetic makeup or disease profile. This could revolutionise preventive medicine by enabling targeted immunisation strategies. Combining mRNA vaccines with other treatment modalities, such as immunotherapies or traditional therapies, could lead to synergistic effects and improved clinical outcomes. The unique properties of mRNA vaccines, such as their ability to induce potent immune responses and modulate the expression of specific proteins, make them attractive candidates for combination therapies. Continued advancements in manufacturing processes will be crucial for the widespread adoption of mRNA vaccines. Efforts are underway to optimise and scale up the production of mRNA vaccines, making them more accessible and cost-effective. This includes refining in vitro transcription reactions and implementing efficient quality control measures. The regulatory landscape surrounding mRNA vaccines will evolve as the field progresses. Regulatory agencies will need to establish guidelines and frameworks specific to mRNA vaccine development and approval. Ensuring safety, efficacy, and quality control will be essential to gain widespread acceptance and public trust in mRNA vaccines. Conclusion mRNA vaccines have shown great potential in revolutionising the field of medicine, particularly in the areas of personalised medicine and preventive medicine. The ability to easily modify the genetic sequence of mRNA allows for the development of personalised vaccines tailored to an individual's specific genetic makeup or disease profile. Furthermore, the unique properties of mRNA vaccines, such as their ability to induce potent immune responses and modulate the expression of specific proteins, make them attractive candidates for combination therapies. However, there are still challenges to overcome, such as ensuring safety, efficacy, quality control, addressing concerns regarding immunogenicity. Nonetheless, with continued advancements in manufacturing processes and regulatory guidelines, the future of mRNA vaccines holds great promise for further advancements and widespread therapeutic use. Efforts to improve in vivo delivery systems and explore the potential of mRNA vaccines in other areas of medicine, such as autoimmune disorders and chronic diseases, further contribute to the promising outlook for this technology. Written by Sara Maria Majernikova Related articles: Potential malaria vaccine / Bioinformatics in COVID vaccine production / Personalised medicine REFERENCES Lin, M.J., Svensson-Arvelund, J., Lubitz, G.S. et al. Cancer vaccines: the next immunotherapy frontier. Nat Cancer 3, 911–926 (2022). https://doi.org/10.1038/s43018-022-00418-6 Pardi, N., Hogan, M., Porter, F. et al. mRNA vaccines — a new era in vaccinology. Nat Rev Drug Discov 17 , 261–279 (2018). DOI: https://doi.org/10.1038/nrd.2017.243 Project Gallery

IT cells and their impact on public opinion Facebook X (Twitter) WhatsApp LinkedIn Pinterest Copy link The spread of digital disinformation 14/07/25, 15:04 Last updated: Published: 05/08/23, 10:06 IT cells and their impact on public opinion As of January 2023, the internet boasts a staggering 4.72 billion estimated social media accounts, with a 3% year-on-year growth of +137 million users and further expansion projected throughout the year. The average person now spends a substantial 6 hours and 58 minutes daily connected to online screens, underscoring the significant role the internet plays in our lives. Consequently, it comes as no surprise that governments worldwide have recognised its potential as a critical tool to advance their agendas, policies, and achievements. Through diverse digital channels, governments aim to reach a vast audience and change public perception, striving to build transparency, trust, and legitimacy while maintaining a powerful digital presence. However, this approach also raises concerns about bias, propaganda, and information manipulation, which can impact public perceptions in questionable ways. One such phenomenon that has emerged is the presence of IT cells, organised groups typically affiliated with political parties, organizations, or interest groups. These Information Technology cells dedicate themselves to managing and amplifying their respective organisations' online presence, predominantly on social media platforms and other digital avenues. During contentious political events or national issues, IT cells deploy coordinated messaging in support of government policies and leaders, inundating social media platforms. Unfortunately, dissenting voices and critics may face orchestrated attacks from these IT cells, aimed at discrediting and silencing them. While some IT cells may operate with genuine intentions, they have faced criticism for engaging in tactics that spread misinformation, disinformation, and targeted propaganda to sway public sentiment in favour of their affiliated organisations. In such instances, IT cells strategically amplify positive news and government achievements while downplaying or deflecting negative information. Social media influencers and online campaigns have become tools to project a positive image of the government and maintain public support. One striking example of how governments can exploit IT cells for their gain was evident in the infamous Cambridge Analytica scandal. In 2018, revelations exposed how the political consulting firm, Cambridge Analytica, acquired personal data from millions of Facebook users without consent. The firm then weaponised this data to construct highly targeted and manipulative political campaigns, including during the 2016 United States presidential election and the Brexit referendum. In India, the ruling BJP party has come under scrutiny for its orchestrated online campaigns through its social media cell. The cell allegedly intimidates individuals perceived as government critics and actively disseminates misogyny, Islamophobia, and animosity. According to Sadhavi Khosla, a BJP cyber-volunteer associated with the BJP IT Cell, the organisation promotes divisive content and employs trolling tactics against users critical of the BJP. Journalists and Indian film actors have also found themselves targeted by these campaigns. As technology continues to evolve, it is imperative to strike a balance between leveraging the internet for transparency and legitimacy while safeguarding against potential misuse that could erode trust in digital governance and public discourse. Monitoring and addressing the activities of IT cells can be a significant step towards ensuring responsible and ethical use of digital platforms in the political arena. Written by Jaspreet Mann Related articles: COVID-19 misconceptions / Fake science websites Project Gallery

And can we overcome them? Facebook X (Twitter) WhatsApp LinkedIn Pinterest Copy link The Challenges in Modern Day Chemistry 11/07/25, 09:56 Last updated: Published: 24/02/24, 22:09 And can we overcome them? Chemistry, heralded as the linchpin of the natural sciences, serves as the veritable bedrock of our comprehension of the world and concurrently takes on a pivotal role in resolving the multifaceted global challenges that confront humanity. In the context of the modern era, chemistry has undergone a prodigious transformation, with research luminaries persistently challenging the fringes of knowledge and technological application. However, this remarkable trajectory is shadowed by a constellation of intricately interwoven challenges that mandate innovative and often paradigm-shifting solutions. This article embarks on a comprehensive exploration of the salient and formidable challenges that presently beset the discipline of contemporary chemistry. Sustainability and the Imperative of Green Chemistry The paramount challenge confronting modern chemistry pertains to the burgeoning and compelling imperative of environmental sustainability. The chemical industry stands as a colossal contributor to ecological degradation and the inexorable depletion of vital resources. Consequently, an exigent necessity looms: the development of greener and environmentally benign chemical processes. Green chemistry, an avant-garde discipline, is at the vanguard of this transformation, placing paramount emphasis on the architectural design of processes and products that eschew the deployment of hazardous substrates. Researchers within this sphere are diligently exploring alternative, non-toxic materials and propounding energy-efficient methodologies, thereby diminishing the ecological footprint intrinsic to chemical procedures. Energy Storage and Conversion at the Frontier In an epoch marked by the surging clamour for renewable energy sources such as photovoltaic solar panels and wind turbines, the exigency of efficacious energy storage and conversion technologies attains unparalleled urgency. Chemistry assumes a seminal role in the realm of advanced batteries, fuel cells, and supercapacitors. However, extant challenges such as augmenting energy density, fortifying durability, and prudently attenuating production costs remain obstinate puzzles to unravel. In response, a phalanx of researchers is actively engaged in the relentless pursuit of novel materials and the innovative engineering of electrochemical processes to surmount these complexities. Drug Resistance as a Crescendoing Predicament The advent of antibiotic-resistant bacterial strains and the irksome conundrum of drug resistance across diverse therapeutic spectra constitute a formidable quandary within the precincts of medicinal chemistry. With pathogenic entities continually evolving, scientists face the Herculean task of continually conceiving novel antibiotics and antiviral agents. Moreover, the unfolding panorama of personalised medicine and the realm of targeted therapies necessitate groundbreaking paradigms in drug design and precision drug delivery systems. The tantalising confluence of circumventing drug resistance whilst simultaneously obviating deleterious side effects represents a quintessential challenge in the crucible of contemporary chemistry. Ethical Conundrums and the Regulatory Labyrinth As chemistry forges ahead on its unceasing march of progress, ethical and regulatory conundrums burgeon in complexity and profundity. Intellectual property rights, the ethical contours of responsible innovation, and the looming spectre of potential malevolent misuse of chemical knowledge demand perspicacious contemplation and meticulously crafted ethical architectures. Striking an intricate and nuanced equilibrium between the imperatives of scientific advancement and the obligations of prudent stewardship of chemical discoveries constellates an enduring challenge that impels the chemistry community to unfurl its ethical and regulatory sails with sagacity and acumen. In conclusion... Modern-day chemistry, ensconced in its dynamic and perpetually evolving tapestry, stands as the lodestar of innovation across myriad industries while confronting multifarious global challenges. However, it does so against the backdrop of its own set of formidable hurdles, ranging from the exigencies of environmental responsibility to the mysteries of drug resistance and the intricate tangle of ethical and regulatory dilemmas. The successful surmounting of these multifaceted challenges mandates interdisciplinary collaboration, imaginative innovation, and an unwavering commitment to the prudential and ethically-conscious stewardship of the profound knowledge and transformative potential that contemporary chemistry affords. As humanity continues its inexorable march towards an ever-expanding understanding of the chemical cosmos, addressing these challenges is the sine qua non for an enduringly sustainable and prosperous future. Written by Navnidhi Sharma Related article: Green Chemistry Project Gallery

Exploring the genetic roots of a neurological tragedy Facebook X (Twitter) WhatsApp LinkedIn Pinterest Copy link Breaking down Tay-Sachs 15/05/25, 10:43 Last updated: Published: 20/04/24, 11:29 Exploring the genetic roots of a neurological tragedy This is article no. 9 in a series on rare diseases. Next article: Ehlers-Danlos Syndrome . Previous article: Pseudo-Angelman Syndrome . Tay-Sachs disease is a heritable metabolic condition that affects the neurons in the brain. The disease is more common in infants and young children as well as people of Ashkenazi Jewish descent, although it can occur in any ethnicity. Symptoms of the disease most commonly manifest themselves in children around six months of age. However, it is possible to develop symptoms from five years old to the teenage years. There are three different forms of the disease, each appearing at different stages of life: infantile, juvenile, and adult. The adult form is much rarer and non-fatal but can still cause neuron dysfunction and psychosis. Early symptoms of the disease include mobility issues such as difficulty crawling, and as the disease progresses, the child may suffer from seizures, vision, and hearing loss. In the classic infantile form, the disease is fatal within the first few years of life or by three to five years old. In infants, infection and respiratory complications, such as pneumonia, are the most common cause of death. Being categorised as an autosomal recessive disease means that in order to display the phenotype, two copies of the mutated HEXA gene must be present in an individual. This HEXA gene is located on chromosome 15 and is responsible for producing enzymes that affect the nerve cells. The carrier frequency of Tay-Sachs is highly dependent on ethnic backgrounds, with carrier frequency being 1 in 30 for those of Ashkenazi Jewish descent and 1 in 300 for others. The chance of developing the disease early or late is predicated on the specific type of HEXA mutation that is inherited within the family. Meaning, if one child in a family possesses the infantile form, all other members of the family will also possess the infantile form (if they express the phenotype). When both parents are carriers of the Tay-Sachs gene mutation, there is a 25% chance with each pregnancy that the child will inherit two mutated copies of the HEXA gene and thus be affected by the disease. Also, there is a 50% chance the child will be a carrier like the parents and a 25% chance the child will inherit two normal copies of the gene and be unaffected. Furthermore, this particular type of gene mutation results in the disease being commonly labelled as a hexosaminidase A deficiency. The HEXA gene’s significance in the disease is further highlighted due to its ability to code for specific alpha subunits in the enzyme β-hexosaminidase A. This enzyme is involved in breaking down molecules that can be recycled in a cell through the use of lysosomes. This key cellular function helps a cell undergo apoptosis (programmed cell death) or help evade bacteria that can damage a cell. However, in individuals with this HEXA gene mutation, less of the enzyme β-hexosaminidase A is produced, which results in less degradation of GM2 ganglioside. GM2 ganglioside is a lipid involved in a host of processes such as membrane organisation, neuronal differentiation, and signal transduction. In addition, due to its lack of degradation, it accumulates inside the body. The rate at which the lipid accumulates inside the cell ultimately determines the form of Tay-Sachs an individual will possess. It is worth noting that this GM2 ganglioside pathology also includes other diseases, such as Sandhoff disease and the AB variant, which have similar disease prognoses. Furthermore, the disease specifically targets the brain as gangliosides are the main lipids that compose neuronal plasma membranes. Their expression is specific to brain regions, impacting key neurodevelopmental processes like neural tube formation and synaptogenesis. Furthermore, ganglioside synthesis is a highly regulated process facilitated by glycosyltransferases during transcription and post-transcription. They also modulate ion channels and receptor signalling, which are crucial for neurotransmission, memory, and learning. The exact mechanism of how this ganglioside accumulation due to HEXA malfunction leads to neuronal death remains unclear. Figure 1 illustrates the dysfunction of the alpha subunit in HEXA as it cannot break down GM2 gangliosides. This results in an accumulation of GM2 within the liposome, contrasting with its concentration in the external environment. This accumulation of GM2 causes lysosomal dysfunction and eventually cell damage, which leads to the symptoms commonly associated with Tay-Sachs. Mouse models have been created to understand this GM2 pathway in greater detail to develop treatments. However, this is quite limited as mice do not have the same pathway of breaking down GM2 as humans. Also, since the disease may be prevalent before birth, it is hard to establish the damage done to a baby inside the womb, making reversing this disease in infants very challenging. However, the later onset types of Tay-Sachs disease might respond to treatment. Implementing ganglioside synthesis inhibitors in combination with existing DNA and enzymatic screening programs holds promise for eventually managing and controlling this condition. Parents can undergo genetic screening to assess their risk of carrying the Tay-Sachs gene, which is done by doing a simple blood test that examines the DNA for mutations in the HEXA gene. Genetic screening is particularly important for couples who have a family history of Tay-Sachs disease or who belong to ethnic groups with a higher prevalence of the condition. Early detection through genetic screening allows couples to make informed reproductive decisions, such as pursuing in vitro fertilisation with preimplantation genetic testing or opting for prenatal testing during pregnancy to determine if the foetus has inherited the mutated gene. Utilising the acronym SHADES as a mnemonic to recognise potential signs of Tay-Sachs disease in their child can help parents get a prompt medical evaluation if any symptoms arise. SHADES: S tartle response H earing loss A ffecting vision D evelopmental delay E pileptic seizures S wallowing difficulties Written by Imron Shah REFERENCES Center, N. (2015). Tay-Sachs disease. Nih.gov . Available at: https://www.ncbi.nlm.nih.gov/books/NBK22250/ . Leal, A.F., Benincore-Flórez, E., Solano-Galarza, D., Garzón Jaramillo, R.G., Echeverri-Peña, O.Y., Suarez, D.A., Alméciga-Díaz, C.J. and Espejo-Mojica, A.J. (2020). GM2 Gangliosidoses: Clinical Features, Pathophysiological Aspects, and Current Therapies. International Journal of Molecular Sciences, 21(17), p.6213. doi: https://doi.org/10.3390/ijms21176213 . Ramani, P.K. and Parayil Sankaran, B. (2022). Tay-Sachs Disease. PubMed. Available at: https://www.ncbi.nlm.nih.gov/books/NBK564432/ . Project Gallery

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, 16:19 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

Transforming agriculture with computer science Facebook X (Twitter) WhatsApp LinkedIn Pinterest Copy link Digital innovation in rural farming 09/07/25, 14:04 Last updated: Published: 21/07/23, 09:58 Transforming agriculture with computer science With their rich agricultural heritage and significant contribution to the national economy, rural farming communities have always been at the forefront of agricultural innovation. Today, as the world undergoes rapid digital transformation, the integration of computer science has emerged as a game-changer in the agricultural sector. By harnessing the power of emerging technologies and data-driven approaches, farmers can enhance productivity, optimize resource allocation, and foster sustainable farming practices. This article delves into the role of computer science in revolutionising agriculture and farming practices in rural areas. From precision agriculture and data analytics to the utilisation of IoT, drones, and decision support tools, we explore how technology-driven solutions are shaping a new era of agriculture, promising increased efficiency, reduced environmental impact, and improved livelihoods for farmers. A recent report revealed that farmers in various regions, specifically rural and eastern regions such as Punjab, India have faced significant challenges, including crop failures, leading to distress and financial difficulties. It is important to address these issues and prevent the associated consequences. Digitalisation within the farming industry can play a vital role in mitigating these challenges and fostering resilience. So how exactly can rural farming benefit from digitalisation? Precision agriculture and data analytics: the implementation of precision agriculture techniques, supported by data analytics, can enable farmers to optimise resource utilisation, improve crop management, and mitigate agricultural risks. By analysing data related to weather patterns, soil conditions, and crop health, farmers can make informed decisions, enhance productivity, and reduce the incidence of crop failures. Market intelligence and price forecasting: computer science tools can facilitate better market intelligence and price forecasting, empowering farmers to make informed decisions about crop selection, timing of harvest, and market strategies. Access to real-time market data, coupled with predictive analytics, can help farmers negotiate fair prices and reduce financial vulnerability caused by market instability. Remote sensing and drone technology: utilising remote sensing and drone technology can enable efficient crop monitoring, early detection of diseases, and targeted interventions. High-resolution imagery and computer vision algorithms can identify crop stress, nutrient deficiencies, or pest outbreaks, allowing farmers to take timely action, reduce crop losses, and enhance yield. Decision support systems: the introduction of decision support systems can provide customised recommendations to farmers, incorporating data from multiple sources such as weather forecasts, market trends, and agronomic best practices. These systems can assist farmers in making well-informed decisions regarding crop selection, input usage, and resource allocation, ultimately improving their profitability, and reducing financial distress. The integration of computer science offers promising avenues for addressing the complex challenges faced by farmers in rural areas. By harnessing the power of data analytics, IoT, drones, and decision support tools, farmers can benefit from enhanced agricultural practices, improved market access, and financial stability. However, it is crucial to ensure the accessibility and affordability of these technologies, coupled with comprehensive support systems and policy reforms, to truly empower farmers and create sustainable change. Written by Jaspreet Mann Related articles: Revolutionising sustainable agriculture through AI / Plant diseases and nanoparticles Project Gallery

Natural substances and their treatment potential Facebook X (Twitter) WhatsApp LinkedIn Pinterest Copy link Using Natural Substances to Tackle Infectious Diseases 14/07/25, 15:11 Last updated: Published: 06/06/23, 17:06 Natural substances and their treatment potential Introduction There is increased concern of antimicrobial resistance, especially when referring to bacteria with superbugs such as Methicillin-resistant Staphylococcus aureus (MRSA) and Carbapenem-resistant Enterobacteriaceae (CRE) as they impact lives globally, mainly through fatalities. Given this predicament, It seems that humanity is losing as a result of this pressing issue. However, it is possible for healthcare professionals to utilise more natural products, which are chemicals made by plants, animals and even microorganisms. This includes resources such as wood and cotton aside from food like milk and cacao. In the context of medicinal treatments, an important justification for using more natural products is because although synthetic or partially synthetic drugs are effective for treating countless diseases, an article found that 8% of hospital admissions in the United States and approximately 100,000 fatalities per year were due to people experiencing unfortunate side effects from these drugs. This article explores three specific natural products, where each have similar and unique health properties that can be harnessed to tackle infectious diseases and its subsequent consequences when left sufficiently unaddressed (i.e. antimicrobial resistance). Honey One of the most famous natural products that has been referenced in various areas of research and has been a food and remedial source for thousands of years is honey. It has properties ranging from antibacterial to antioxidant, suggesting that when honey is applied clinically, they have the potential to stop pathogenic bacteria. For example, honey can protect the gastrointestinal system against Helicobacter pylori , which causes stomach ulcers. In disc diffusion assays, the inhibitive properties of honey were shown when honey samples were evaluated holistically as opposed to its individual ingredients. This implies that the macromolecules in honey (carbohydrates, proteins and lipids) work in unison with other biomolecules, illustrating that honey is a distinctive remedy for preventing bacterial growth. For tackling infectious diseases, particularly against wound infections among others, honey’s medicinal properties provide a lot of applications and because it is a natural product, honey would not present any drastic side effects to a patient upon its administration. Garlic Another natural product that can be effective against microorganisms is garlic because similar to honey, it has antimicrobial and antioxidative compounds. A study judged different garlic phenotypes originating from Greece and discovered that they were beneficial against Proteus mirabilis and Escherichia coli aside from inhibiting Candida albicans and C. kruzei . As for fresh garlic juice (FGJ), it increases the zone of inhibition in various pathogens at 10% and more along with it displaying minimum inhibitory concentrations (MICs) in the 4-16% range. Therefore, garlic in solid or liquid form does show potential as a natural antimicrobial agent, especially against pathogenic bacteria and fungi. With this in mind, it too has multiple applications like honey and should be further studied to best isolate the chemical compounds that could be involved in fighting infectious diseases. Turmeric Curcuma longa (also known as turmeric) is one other natural product with unique properties like garlic and honey, making it a suitable candidate against various microbes. One specific pigment that is part of the ginger family and found in turmeric is curcumin, which can tackle diverse microbes through numerous mechanisms illustrated below in Figure 2 . With this said, curcumin has drawbacks: it is highly hydrophobic, has low bioavailability and quickly breaks down. Although when paired with nanotechnology for delivery into the human body, its clinical applications can be advantageous and an additional observation about curcumin is that it can work collaboratively with other plant derived chemicals to stop antibiotic resistant bacteria. One specific bacterial strain that turmeric can attack is Clostridium difficile, a superbug that causes diarrhoea. A study had 27 strains to measure the MICs of turmeric constituents, particularly curcuminoids and curcumin. The results showed reduced C. difficile growth in the concentration range 4-32 μg/mL. Moreover, they had no negative impacts on the gut microbiome and curcumin had more efficacy in stopping C. difficile toxin production compared to fidaxomicin. Thus, turmeric is efficacious as a natural antimicrobial chemical and with further experimentation (same as honey and garlic), it can be harnessed to prevent infectious diseases besides their impact on human lives. Conclusion Considering the above examples of natural products in this article and others not mentioned, it is clear that they can be powerful in the battle against infectious diseases and the problems associated with them, mainly antimicrobial resistance. They are readily available to purchase in markets and shops at low cost, making them convenient. Moreover, populations in Eastern countries like China and India traditionally have used, and are still using these materials for curing pain and illness. In turn, manufacturing medicines from natural products on a larger scale has the prospect of preventing infectious diseases and even alleviating those that patients currently have. Written by Sam Jarada Related article: Mechanisms of pathogen evasion Project Gallery

Nanoparticles have unique properties Facebook X (Twitter) WhatsApp LinkedIn Pinterest Copy link Nanoparticles: the future of diabetes treatment? 17/07/25, 10:52 Last updated: Published: 06/05/24, 13:20 Nanoparticles have unique properties Diabetes mellitus is a chronic metabolic disorder affecting millions worldwide. Given its myriad challenges, there is a substantial demand for innovative therapeutic strategies in its treatment. The global diabetic population is expected to increase to 439 million by 2030, which will impose a significant burden on healthcare systems. Diabetes occurs when the body cannot produce enough insulin, a hormone crucial for regulating glucose levels in the blood. This deficiency leads to increased glucose levels, causing long-term damage to organs such as the eyes, kidneys, heart, and nervous system, due to defects in insulin function and secretion. Nanoparticles have unique properties making them versatile in their applications and are promising to help revolutionise the future of the treatment of diabetes. This article will explore the potential of this emerging technology in medicine and will address the complexities and issues that arise with the management of diabetes. Nanoparticles have distinct advantages: biocompatibility, bioavailability, targeting efficiency and minimal toxicity, making them ideal for antidiabetic treatment. The drug delivery is targeted, making the delivery precise and efficient, avoiding off-target effects. Modifying nanoparticle surfaces enhances therapeutic efficacy, enabling targeted delivery to specific tissues and cells, while reducing systemic side effects. Another currently researched key benefit is real-time glucose sensing and monitoring, which addresses a critical aspect in managing diabetes, as nanoparticle-based glucose sensors can detect glucose levels with high sensitivity and selectivity. This avoids the use of invasive blood sampling and allows for continuous monitoring of glucose levels. These can be functionalised and integrated into wearable devices, or implanted sensors, making it convenient and reliable to monitor and to be able to optimum insulin therapy. Moreover, nanoparticle-based approaches show potential in tissue regeneration, aiding insulin production restoration. For example, in particular, nanomedicine is a promising tool in theranostics of chronic kidney disease (CKD), where one radioactive drug can diagnose and a second delivers the therapy. The conventional procedure to assess renal fibrosis is by taking a kidney biopsy, which is then followed by a histopathological assessment. This method is risky, invasive, and subjective, and less than 0.01 % of kidney tissue is examined which results in diagnostic errors, limiting the accuracy of the current screening method. The standard use of pharmaceuticals has been promising but can cause hypoglycaemia, diuresis, and malnutrition because of the low caloric intake. Nanoparticles offer a new approach to both diagnosis and treatment and are an attractive candidate for managing CKD as they can carry drugs and enhance image contrast, controlling the rate and location of drug release. In the treatment of this multifaceted disease, nanoparticle delivery systems seem to be a promising and innovative therapeutic strategy, with the variety in the methods of delivery. The range of solutions that are currently being developed are promising, from enhancing the drug delivery to monitoring the glucose level, to direct tissue regeneration. There is immense potential for the advancement of nanomedicines, helping improve patient outcomes, the treatment efficacy, and allowing the alleviation of the burden and side effects of the disorder. With ongoing efforts and innovation, the future treatment of diabetes can be greatly helped with the use of nanoparticles, and these advancements will improve strategies for the management and future treatment of diabetes. Written by Saanchi Agarwal Related articles: Pre-diabetes / Can diabetes mellitus become an epidemic? / Nanomedicine / Nanoparticles on gut health / Nanogels / Nanocarriers REFERENCES Lemmerman LR, Das D, Higuita-Castro N, Mirmira RG, Gallego-Perez D. Nanomedicine-Based Strategies for Diabetes: Diagnostics, Monitoring, and Treatment. Trends Endocrinol Metab. 2020 Jun;31(6):448-458. doi: 10.1016/j.tem.2020.02.001. Epub 2020 Mar 4. PMID: 32396845; PMCID: PMC7987328. Dehghani P, Rad ME, Zarepour A, Sivakumar PM, Zarrabi A. An Insight into the Polymeric Nanoparticles Applications in Diabetes Diagnosis and Treatment. Mini Rev Med Chem. 2023;23(2):192-216. doi: 10.2174/1389557521666211116123002. PMID: 34784864. Luo XM, Yan C, Feng YM. Nanomedicine for the treatment of diabetes-associated cardiovascular diseases and fibrosis. Adv Drug Deliv Rev. 2021 May;172:234-248. doi: 10.1016/j.addr.2021.01.004. Epub 2021 Jan 5. PMID: 33417981. L. Tillman, T. A. Tabish, N. Kamaly, A. El-Briri F, C. Thiemermann, Z. I. Pranjol and M. M. Yaqoob, Review Advancements in nanomedicines for the detection and treatment of diabetic kidney disease, Biomaterials and Biosystems, 2022, 6, 100047. J. I. Cutler, E. Auyeung and C. A. Mirkin, Spherical nucleic acids, J Am Chem Soc, 2012, 134, 1376–1391. Veiseh, O., Tang, B., Whitehead, K. et al. Managing diabetes with nanomedicine: challenges and opportunities. Nat Rev Drug Discov 14, 45–57 (2015). https://doi.org/10.1038/nrd4477 Project Gallery