The 1913 Nobel Prize in Physiology or Medicine was awarded to Charles Richet “in recognition of his work on anaphylaxis.”His research uncovered a paradoxical reaction in which the body’s defenses, instead of protecting it, could overreact with severe consequences. This discovery became a cornerstone of immunology and the study of allergic diseases.

In the late nineteenth and early twentieth centuries, medicine was advancing rapidly in understanding infections and immunity, but certain reactions remained mysterious. Doctors and researchers observed that both people and animals could suddenly develop difficulty breathing, collapse, or even fatal reactions after exposure to substances that had previously caused little harm. These responses were unpredictable and could not be explained by the existing understanding of how the immune system worked. Without understanding these reactions, treatments for toxins, vaccines, and other medical interventions carried significant risk, and there was no framework to prevent or manage severe allergic responses.

Early life

Charles Robert Richet was born on August 26, 1850, in Paris, France. He came from a medical family –his father, Alfred Richet, was a surgeon and professor. Besides immunology, he also studied subjects including physiology, psychology, and neuroscience. He studied medicine at the University of Paris, where he developed a fascination with physiology, toxins, and the body’s defensive mechanisms. Early in his career, Richet focused on understanding how animals responded to poisons and venoms, often observing that repeated exposure sometimes caused reactions far more severe than the first encounter.

These observations sparked his interest in systematically studying what he would later define as anaphylaxis. Richet spent years performing controlled experiments to uncover the principles behind these dangerous immune responses.

Richet’s major contribution

Richet’s breakthrough came in 1902 through experiments with marine toxins, in collaboration with French physiologist, Paul Portier. They exposed dogs to jellyfish and sea anemone venoms. While an initial dose often produced mild effects, subsequent exposures sometimes provoked violent reactions, including shock and death.

Richet documented these outcomes and recognised a distinct physiological phenomenon: anaphylaxis. He named it from the Greek “ana-” (opposite of) and “phylaxis” (protection), emphasising that the immune system could react in a harmful, rather than protective, way.

This discovery explained previously puzzling severe allergic reactions and became the first systematic description of hypersensitivity. Richet’s work showed that the immune system could overreact, providing the basis for understanding allergies, severe drug reactions, and other immune-mediated conditions. When Richet first described anaphylaxis in 1902, scientists largely believed the immune system only protected the body. His experiments revealed the opposite could also happen –the body’s own defenses could trigger sudden, deadly reactions after a second exposure to a substance.

Research contributions

Beyond describing anaphylaxis, Richet’s research laid the groundwork for safer medical practices. His findings informed the development of allergy testing, immunotherapy, and emergency interventions such as epinephrine treatment for life-threatening reactions. He also influenced the broader field of immunology, helping scientists understand that immune responses can be both protective and pathological.

Richet continued to study physiological reactions and toxins throughout his career, contributing to general knowledge of the nervous and circulatory systems. However, his work on anaphylaxis remained his best recognised achievement.

Impact on medicine

Charles Richet’s discovery fundamentally changed the understanding of the immune system. Today, anaphylaxis is recognised as a medical emergency, and protocols for its management directly reflect Richet’s insights. Treatments, preventive measures, and patient education in allergy care all trace back to his work.

His research also influenced the study of autoimmune diseases and other conditions in which the immune system causes harm. By revealing that the body’s defenses can sometimes overreact, Richet opened the door to safer therapies, vaccines, and clinical practices that anticipate and prevent harmful immune responses.

Charles Richet passed away on December 4, 1935, but his legacy endures. His experiments and documentation provided a framework for modern immunology, saving lives through a deeper understanding of allergic and hypersensitivity reactions.

Published – May 10, 2026 08:10 am IST

In cybersecurity, speed is everything. The faster a vulnerability is found and rectified, the safer the data is. For years, human expertise was needed to do this. Now, Artificial Intelligence can identify hidden vulnerabilities and write the code to patch them in hours, compressing a process that once took teams of experts days or weeks. But what happens when the same AI increases the risk?

The International Monetary Fund (IMF) has warned that while AI could strengthen cyber defence, it could also make cyberattacks faster, cheaper, and accessible even to non-experts. The risks are particularly serious for the financial sector, which relies heavily on shared digital infrastructure like software, cloud services, payment networks, and interconnected databases.

Also Read: Has Anthropic’s Mythos made the Cure worse than the disease?

In a new report, the IMF singled out Anthropic’s Claude Mythos Preview to show how quickly risks are rising. Mythos is a large language model developed with general-purpose reasoning, coding, and autonomous tasks.

This makes it great at identifying security vulnerabilities, but experts and the tech company itself are worried about its potential risks.

In April, Anthropic announced that Mythos would not be released publicly because of its ability to identify unknown flaws in IT systems, which could potentially be exploited by hackers. But on April 22, it confirmed it was investigating reports that unauthorised users had gained access to Mythos.

Mythos can find ‘zero-day’ or undiscovered vulnerabilities in real open-source codebases. It has also demonstrated capabilities to reverse-engineer exploits in closed-source software and turn N-day, or known but not yet widely patched, vulnerabilities into exploits. In short, Mythos can not only identify vulnerabilities that humans may have missed, but also generate ways to exploit them, potentially even for non-experts.

“The vulnerabilities it finds are often subtle or difficult to detect. Many of them are ten or twenty years old, with the oldest we have found so far being a now-patched 27-year-old bug in OpenBSD — an operating system known primarily for its security,” Anthropic said in a blog.

Also Read: Should the Mythos AI model raise cybersecurity alarms?

The company also revealed how quickly these capabilities emerged. Anthropic said its engineers were able to ask Mythos to find vulnerabilities and produce a complete, working exploit in just one night. “In other cases, we’ve had researchers develop scaffolds that allow Mythos Preview to turn vulnerabilities into exploits without any human intervention,” the company wrote.

Fears of cyberattacks

More worryingly, the company revealed that these capabilities were not intentionally trained into the system. The blog noted that Mythos was able to develop these capabilities “very quickly”, even though the AI was not trained specifically for them. “Rather, they emerged as a downstream consequence of general improvements in code, reasoning, and autonomy.”

The challenge is that AI is already deeply embedded within the financial system. Banks and financial institutions use AI for several banking activities, customer service, and risk management. AI-supported systems are increasingly being used to identify suspicious activity, detect vulnerabilities, and respond to cyber threats faster than traditional systems. Powerful systems like Mythos raise fears that cyberattacks could become more scalable, automated, and accessible. This threat is more real because many financial institutions still rely on interconnected legacy infrastructure that is difficult to patch or upgrade quickly, making the risks systemic.

The IMF has urged governments and regulators not to treat AI “as a purely technical or operational issue” and instead build resilience through supervision, coordination, and preparedness. Governments are beginning to respond. Regulators and financial authorities across the world are increasingly warning that AI could amplify cyber risks in critical sectors.

In India, after reports emerged that unauthorised users may have gained access to Mythos, Finance Minister Nirmala Sitharaman convened a meeting with Electronics and IT Minister Ashwini Vaishnaw, bankers, and other stakeholders to assess the risks posed by AI and its implications for financial data security.

Banks were advised to establish mechanisms for real-time threat intelligence sharing with other banks, the Indian Computer Emergency Response Team (CERT-In), and relevant agencies. Banks were also asked to report suspicious activity and cyber incidents more proactively. The government also set up a committee under C.S. Setty, chairman of State Bank of India, to assess the risks posed by Mythos and recommend safeguards.

Separately, the Reserve Bank of India introduced a framework in 2025 to promote the responsible and ethical adoption of AI in the financial sector.

Still, Mythos reveals a deeper problem in the system. The IMF points out that the risks are not limited to the financial sector alone. Sectors like energy, telecommunications, and public services are also vulnerable. Dependence on a small number of software platforms, cloud providers, and AI models could further increase the impact because many sectors rely on the same infrastructure.

Published – May 10, 2026 01:45 am IST

For decades, people using psychedelics have described a feeling where the line between ‘me’ and the world vanishes. While it is clear these drugs cause intense shifts in vision and thought, scientists have struggled to pin down exactly what the brain is doing.

A new multi-centric study published in Nature Medicine on April 6 has suggested the answer isn’t found in a single centre such as the thalamus or amygdala but that it arises from a total reorganisation of how different brain areas talk to one another.

To find a reliable pattern, researchers from Canada, the U.K., and the U.S. pooled 11 global datasets into a library of 500 fMRI scans — images that track changes in blood flow to show which parts of the brain are working. This included 267 people under the influence of LSD, psilocybin, DMT, mescaline or ayahuasca.

Previously, labs used software to clean data skewed by factors such as head moving during scanning, often producing contradictory results. To fix this, the team took the raw data and ran them through a single, common processing system to ensure they were comparing apples to apples for the first time.

Chain of command

The team had to figure out which brain changes were caused by the drugs and which were arbitrary differences between people or MRI machines. Instead of the usual statistical methods, the team used Bayesian modelling. It works like a fair judge who doesn’t simply declare guilty or innocent: it says exactly how confident it is and automatically prefers results based on hundreds of volunteers than those based on a handful. This let the researchers filter out the quirks and focus on the brain patterns that reliably appeared across every drug and lab.

University of Ottawa neuroscientist Sergio Perez-Rosal said “moving away from overconfident ‘yes’ or ‘no’ claims towards a more nuanced, uncertainty-aware conclusion represents a rare kind of epistemic humility” — meaning the scientific honesty to admit exactly what we don’t know, especially in the fledgling field of consciousness studies.

To understand the findings, it helps to see the brain as a building with a strict chain of command. In our normal, everyday state, the brain has a hierarchy. At the bottom are frontline workers, the brain regions that handle raw sensory input. At the top are the high-level managers — the parts of the brain responsible for abstract thought, memory, and our internal sense of self. Usually, these two groups don’t talk to each other directly. They are separated by layers of filters that keep our raw senses from overwhelming our complex thoughts.

‘Change how information flows’

The analysis found that psychedelics essentially collapse this ladder, instead increasing cross-talk, i.e. the thinking regions and the sensory regions begin exchanging information directly. And this collapses the neural boundary that usually defines ‘you’ as distinct from the world.

“What surprised us most is that psychedelics don’t just affect specific spots, they change how information flows across the entire brain,” Manesh Girn, a neuroscientist at the University of California San Francisco, and first author of the study, said. “The usual hierarchy between ‘high-level’ thought and ‘bottom-up’ perception starts to dissolve. Inner and outer experience begin to blur.”

While in a normal state, the brain operates like a city of segregated neighborhoods, where signals stay in their own lanes and travel only along established routes, psychedelics dissolve these boundaries. Dr. Girn said this is best described as a city where new, direct highways suddenly open up.

“This connects neighborhoods that usually you have to move through multiple smaller neighborhoods to get to,” he said. “Now, you can get from A to C without needing to go through B.”

Out of ruts

While the study offered the most robust map to date of the brain under psychedelics, Michiel van Elk, a cognitive psychologist at Leiden University said scientists must look closer at the tools used to draw it. He said psychedelics act on serotonin receptors, which naturally regulate the tension of blood vessels. Since fMRI tracks blood flow to guess where the brain is active, a drug that changes vessel tension could create a measurement artifact. Without using other techniques beyond fMRI, he argued, it remains unclear if these new highways are a reliable signature of neuronal firing or simply a side effect of how the drugs affect our blood.

Beyond the laboratory, in clinics, where psychedelics have been gaining traction as a therapeutic intervention, this study provides a vital biological clue for why these drugs might work as medicine. Akanksha Dadlani, a psychiatrist at Stanford University, said the flattened hierarchy found in the scans could explain how psychedelics “loosen the rigid patterns of thought” seen in depression.

“By temporarily breaking down the brain’s strict chain of command, the drugs may allow patients to step out of long-held mental ruts.”

‘Powerful tool’

However, Dr. Dadlani and Prof. Perez-Rosal both cautioned that a change in wiring is only a catalyst, not a magic bullet. The drug may physically open a door by rewiring the brain’s shortcuts. Prof. Perez-Rosal added that the actual healing will depend on how that experience is integrated into the patient’s life afterwards.

Matthew Wall, a neuroscientist and imaging expert at Imperial College London, said the real advance is that by unifying the most data to date, the study has established new baselines for how psychedelics trigger cross-talk. While the study used healthy volunteers, Dr. Wall said, “identifying this clear neural signature provides a solid foundation for understanding how psychedelic treatments may work in clinical practice.”

Ultimately, the study offers something more subtle than clinical promise: a rare glimpse into the mechanics of human awareness. For Dr. Girn, the work shows how psychedelics can be a “powerful perturbational tool” to break down the fundamental structures of experience, letting researchers understand how they are usually maintained.

Anirban Mukhopadhyay is a geneticist by training and science communicator from New Delhi.

Published – May 11, 2026 07:30 am IST

The story so far:

On May 4, Pixxel, a Bengaluru-based imaging satellite company, said that it would partner with the AI firm Sarvam to launch what is being described as India’s first ‘orbital data centre’ satellite, named Pathfinder. This is expected to be a 200 kg class satellite scheduled for orbit by the fourth quarter of 2026. It will carry datacentre-class GPUs (graphics processing units) alongside Pixxel’s hyperspectral imaging camera, the company’s bread-and-butter business.

What is an orbital data centre?

It is a constellation of satellites carrying the same kind of GPUs found in terrestrial data centres. It can train and run AI models in orbit rather than only relaying data to ground stations. Such a centre can do more demanding work than the low-power “edge” processors that conventional satellites use for tasks like signal compression. Edge computing on earth refers to the practice of running computation close to where data is generated rather than in a centralised cloud, and the same logic, applied in orbit, is what space-based compute promises to extend.

Pixxel’s Pathfinder is being built as a single-satellite demonstrator, designed to test whether ground-grade hardware can be made to function reliably in the harsh, hot environment of low Earth orbit. “It will start off as being one satellite, obviously, that we will try to launch before the end of this year,” Awais Ahmed, the company’s chief executive, told The Hindu.

Why are global firms suddenly interested?

Three factors have converged in the past two years, prompting large tech companies to strive towards making such centres real. Data centres are being constrained by limits on energy availability, land, water, and local regulation, all of which have been amplified by the demands of AI. In the right orbit, solar power is effectively continuous and offers free electricity, which proponents regard as the strongest argument for moving computation to space.

Earth observation satellites also generate detailed, heavy image files that are expensive to downlink; processing the data in orbit and beaming down only the conclusions has long been seen as a way to ease that bottleneck.

The third factor is competitive positioning. SpaceX CEO, Elon Musk said on X in 2025 that “simply scaling up Starlink V3 satellites, which have high-speed laser links, would work. SpaceX will be doing this.” He also argued that “Starship (the company’s most powerful rocket) could deliver 100GW/year to high Earth orbit within four to five years if we can solve the other parts of the equation.” Amazon founder Jeff Bezos’ Blue Origin, Microsoft’s Azure Space, and Lonestar Data Holdings have already begun pilot deployments. None of these efforts has yet produced a commercial-scale orbital data centre.

What are the challenges?

The GPU chips powered by electricity from solar panels become hot. Now space may be cold, and common sense may suggest it is a natural sink for the heat. However, space is also empty and its vacuum eliminates convection. This is the mechanism by which warm air on earth is normally carried away from terrestrial servers; in orbit, a hot GPU chip is effectively an oven unable to fan away its own waste energy, with no air to carry it off. The only solution to this is radiation, which requires that heat be pumped through ammonia-filled loops to deployable panels, where it can be radiated as infrared light into space. The history of crewed spaceflight is studded with reminders of how unforgiving this regime can be.

Radiation damage is the second problem and one that has shaped the design of every long-duration mission flown to date. ‘Bit flips’ — where bits and bytes of computers randomly change — and long-term semiconductor degradation are caused by cosmic rays, and radiation-hardened chips, which govern most space hardware, typically lag commercial GPUs by years. Power requires storage for eclipse periods, and maintenance is effectively impossible without robotic servicing, so redundancy must be designed in from the start.

What does the Pixxel–Sarvam partnership actually involve?

The Pathfinder satellite will be designed, built, launched, and operated by Pixxel. Sarvam, an Indian AI firm, will provide what it describes as the AI backbone, with full-stack language models being run on the satellite’s GPU layer for both training and inference. Pixxel’s hyperspectral camera will be carried on the same platform, giving the mission an immediate use case: imagery captured in orbit can be analysed in orbit, with only the conclusions transmitted to Earth. Mr. Ahmed declined to disclose costs, the number of GPUs, or the launch provider, saying the choice between ISRO and SpaceX would be determined by slot availability. However, the Pixxel team has several experts who have worked with the Indian Space Research Organisation and have experience in thermal management in space.

Can data crunching in space ever be cheaper than on ground?

Not yet, and not for some time, on the available evidence. Mr. Ahmed said that a single satellite carrying a given number of GPUs is more expensive than the same hardware on Earth. The argument for eventual parity is built on three assumptions: that constellations will be scaled to tens of thousands of satellites; that launch costs will be reduced sharply once SpaceX’s Starship is operational; and that the absence of cooling and grid-power expenses in orbit will eventually offset the higher capital outlay. Mr. Ahmed set the horizon at 5-10 years. “It would take about 100-500 satellites to replace a data centre in India and if someone were to pay for it, we could launch them even in 24 months,” he said. Independent assessments have been markedly more cautious than the timelines offered by Pixxel and its peers. Edge processing on satellites is judged viable in the near term by academic and agency reviews, but a wholesale replacement of terrestrial cloud is treated as a 10-to-30-year proposition.

Published – May 10, 2026 09:25 am IST

A bumblebee gathers nectar from a wildflower in Appleton, U.S., 2015.
| Photo Credit: AP