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OpenAI Unveils GPT-Rosalind to Speed Up Drug Discovery and Biological Research

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OpenAI has introduced a new artificial intelligence model aimed at transforming scientific work in biology and medicine, as the company expands its focus on healthcare innovation.

The model, called GPT-Rosalind, is designed to assist researchers in areas such as drug discovery, translational medicine and broader life sciences. It is named after Rosalind Franklin, whose work was key to understanding the structure of DNA.

According to OpenAI, the new system is built to handle complex scientific workflows, including analysing biological data, reviewing research literature and planning experiments. The company said the model performs particularly well in tasks that require reasoning across molecules, proteins, genes and disease-related processes.

Artificial intelligence is already playing a growing role in the pharmaceutical industry, helping scientists identify promising compounds more quickly and reduce the time needed to bring treatments from early research to clinical use. OpenAI said GPT-Rosalind aims to go further by helping researchers uncover patterns and connections that might otherwise go unnoticed.

“Advanced AI systems can help scientists move through complex workflows faster and explore more possibilities,” the company said in its announcement, adding that the tool is intended to improve both efficiency and the quality of scientific insights.

The model is also designed to integrate with scientific tools and databases, allowing it to support multi-step processes such as data analysis, sequence interpretation and experimental design. This capability is expected to make it useful for teams handling large volumes of biological information.

OpenAI is already working with several major organisations to apply the technology in real-world research settings. These include Moderna, Amgen, Allen Institute and Thermo Fisher Scientific.

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Stéphane Bancel said the model is already helping scientific teams process complex data and translate findings into experimental workflows. He noted that the technology could accelerate research and development efforts within the company.

The launch follows a broader push by OpenAI to deepen its involvement in life sciences. Earlier this month, the company announced a partnership with Novo Nordisk to support the development of new treatments using AI tools.

Sam Altman said artificial intelligence has the potential to reshape the healthcare sector by enabling faster innovation and improving patient outcomes. Pilot programmes using GPT-Rosalind are expected to roll out across research, manufacturing and commercial operations, with wider integration planned by the end of the year.

The release signals growing competition among technology firms to apply AI in scientific discovery, an area seen as one of the most promising frontiers for the technology.

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UK Children Growing Taller as Researchers Link Trend to Rising Obesity

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Children across United Kingdom are becoming taller on average, but researchers warn the trend may reflect worsening childhood obesity and widening social inequality rather than improvements in public health.

A study conducted by researchers from University of Oxford and University College London found that the average height of children in England, Scotland and Wales has steadily increased during the past two decades, with growth accelerating sharply during the COVID-19 pandemic.

The research, published in the Journal of Epidemiology & Community Health, examined height data among 11-year-old children and linked the increase to rising obesity rates, particularly in poorer communities.

According to the study, the average height of 11-year-old boys in England rose from 145 centimetres in the 2009-10 school year to 145.7 centimetres in 2019-20. During the pandemic period, the figure climbed more rapidly to 146.5 centimetres before easing slightly to 146.4 centimetres by 2023-24.

Girls showed a similar pattern. Average height increased from 145.8 centimetres in 2009-10 to 146.6 centimetres in 2019-20 before jumping to 148 centimetres during the pandemic and later settling at 147.5 centimetres.

Researchers said the increase was closely associated with rising childhood obesity, especially among children living in deprived areas.

The study pointed to pandemic lockdowns, school closures and reduced opportunities for exercise as major factors that contributed to unhealthy eating habits and lower physical activity among children.

In England’s poorest communities, the average height of 11-year-old boys increased by 1.7 centimetres between 2009 and 2024. During the same period, the proportion of overweight or obese children rose from 37.7 percent to 43.3 percent.

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The report also found that traditional differences in height between wealthier and poorer children are narrowing. Among girls, the gap temporarily reversed during the pandemic, with girls from the most deprived areas becoming slightly taller on average than those from wealthier neighbourhoods.

Researcher Andrew Moscrop said poorer communities are often exposed to greater numbers of unhealthy food outlets and have less access to healthier options.

The findings come as childhood obesity continues to rise across Europe. According to World Health Organization data, obesity rates among children aged five to 19 in the WHO European region doubled from 3.8 percent in 1990 to 8 percent in 2022.

Britain recorded one of the sharpest increases, rising from 4.5 percent to 11.3 percent over the same period. That made the UK the highest among Europe’s five largest economies, ahead of Spain, Italy and Germany. France recorded the lowest rate among the group.

Researchers said the findings highlight growing concerns about child nutrition, inequality and long-term health outcomes, warning that increased height linked to obesity should not be mistaken for improved childhood wellbeing.

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AI Model Surpasses Doctors in Key Medical Decision Tests, Study Finds

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A new study by researchers at Harvard Medical School and Beth Israel Deaconess Medical Center has found that advanced artificial intelligence systems can outperform human doctors in several medical reasoning tasks, including diagnosis and emergency care decisions.

The research compared physicians with large language models across a range of clinical scenarios. According to the findings, AI systems showed stronger performance in tasks such as identifying likely diagnoses, recommending treatment steps, and making decisions in emergency department settings where information is often limited.

Arjun Manrai, a co-senior author of the study, said the results demonstrate the rapid progress of AI in healthcare. He noted that the model surpassed both earlier systems and physician benchmarks in most tests. At the same time, he cautioned that better performance in controlled settings does not guarantee improved outcomes in real-world care.

The study evaluated OpenAI’s reasoning model, released in 2024, using a mix of published clinical cases and real-world emergency department data. Researchers presented the system with patient scenarios at different stages of care, from initial triage to later admission decisions. At each step, the AI was given only the information available at that point and asked to suggest diagnoses and next actions.

The results showed that the AI consistently outperformed doctors, especially in areas requiring structured reasoning and documentation. The largest gap appeared during the triage stage, when limited information makes decision-making more difficult. As additional data became available, both AI and physicians improved in accuracy, though the AI maintained an edge in many cases.

Peter Brodeur, a co-author of the study, said traditional testing methods such as multiple-choice questions are no longer sufficient to measure progress, as many AI models now achieve near-perfect scores. He added that newer evaluation approaches are needed to track further advances.

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Despite the promising results, researchers stressed that the use of AI in healthcare must be approached carefully. They warned that while a model may correctly identify a diagnosis, it could also recommend unnecessary tests or interventions that might carry risks for patients.

The study’s authors called for further trials in real clinical environments to better understand how AI tools perform in practice. They also highlighted the need for investment in infrastructure and clear frameworks to support the safe use of such technologies.

The findings come with some limitations, as the analysis focused on a specific version of the AI model, which has since been updated. Researchers said additional studies are needed to compare different systems and explore how doctors and AI can work together effectively in patient care.

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New Study Reveals How Coffee May Help Protect the Body From Ageing

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A new study has uncovered a key biological mechanism that may explain why coffee has long been linked to healthier ageing and a lower risk of chronic disease.

Researchers at Texas A&M College of Veterinary Medicine & Biomedical Sciences found that compounds in coffee interact with a protein in the body known as NR4A1, a receptor involved in regulating stress responses, inflammation and cellular repair. The findings shed new light on how coffee may help protect the body from age-related decline.

For years, studies have associated regular coffee consumption with a longer life and reduced risk of conditions such as heart disease, cancer and cognitive decline. Until now, however, the biological processes behind those benefits have remained largely unclear.

The research team identified NR4A1 as a critical target for several naturally occurring compounds in coffee, particularly polyphenols and other polyhydroxylated substances. These compounds bind to the receptor and appear to influence how it functions.

NR4A1 acts as what scientists call a nutrient sensor, responding to dietary compounds and helping the body adapt to stress and damage. It plays an important role in controlling inflammation, maintaining energy balance and promoting tissue repair — all essential processes in healthy ageing.

Stephen Safe, one of the study’s lead researchers, said the findings provide a clearer understanding of coffee’s protective effects. He explained that NR4A1 helps limit damage when tissues are under stress, and that its absence can worsen the effects of injury or disease.

Laboratory tests showed that coffee compounds reduced cellular damage and slowed the growth of cancer cells. When researchers removed NR4A1 from the cells, those benefits disappeared, strongly suggesting that the receptor is central to coffee’s protective action.

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The study also highlights that coffee’s health effects are likely driven by more than caffeine alone. Decaffeinated coffee has also been linked to improvements in learning and memory, indicating that other components, including polyphenols, may play a significant role.

Recent research has suggested that moderate consumption of caffeinated coffee may also reduce anxiety, improve attention and vigilance, and lower levels of inflammation.

Scientists caution that while the findings are promising, more research is needed to determine how significant the NR4A1 pathway is in humans and how it interacts with other biological systems.

Still, the discovery offers an important step toward understanding why coffee remains one of the most widely studied beverages in nutrition science. It also reinforces the idea that compounds found in everyday foods and drinks can play a meaningful role in supporting long-term health and resilience as people age.

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