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Comment by Dr. Krishna Kumari Challa 52 minutes ago

To test whether that antibody fingerprint could reveal vaccine readiness, the researchers analyzed antibody responses to 185 antigens. These included SARS-CoV-2, the virus that causes COVID-19, other common viruses and bacteria, and targets associated with autoimmune diseases.

The study included 8,687 samples from 4,089 participants, spanning healthy volunteers and people with conditions or treatments linked to immune suppression, such as HIV, multiple myeloma, solid organ malignancy, autoimmune disease, inflammatory bowel disease and solid organ transplantation.

The researchers found that several immunosuppressed groups were more likely to have blunted responses to COVID-19 vaccination. But those categories were imperfect predictors. Some immunosuppressed participants mounted strong responses, while about 5% to 6% of healthy participants had weak responses.
The study found that higher levels of certain preexisting antibodies, including antibodies to common microbes such as Staphylococcus aureus, RSV and human respirovirus 3, were associated with stronger COVID-19 vaccine responses.

The researchers describe these as "sentinel" antibodies because they may indicate a person's baseline immune readiness. They are not necessarily fighting the vaccine target directly. Instead, they may reflect how responsive the antibody-producing arm of the immune system is likely to be.

The researchers then asked whether the full antibody fingerprint, not just a few individual markers, could help identify people likely to have weak vaccine responses. Their deep-learning model analyzed patterns across the antibody panel, combining many measurements into a broader immune profile.

The study highlights a key strength of AI in health research: its ability to find subtle, predictive patterns in millions of biological data points that might otherwise remain hidden. The approach suggests that vaccine readiness may be better understood by looking at the immune system as a whole, rather than focusing only on a single disease or a single antibody.

The work also highlights the value of newer technologies that can measure large numbers of antibody responses at once. Instead of asking whether someone has antibodies to one pathogen, the method can scan a wider immune landscape, capturing patterns formed by many previous encounters with viruses, bacteria and other immune targets.
Sentinel antibody profiling could help guide vaccine testing, vaccine development and clinical care for people at risk of weak immune responses.

The approach might eventually help doctors identify patients who need additional vaccine doses, closer follow-up or alternative protective measures. It could also help researchers better understand why some people respond well to vaccination while others do not.

Pre-vaccine sentinel antibodies predict blunted vaccine responses, Cell Press Blue (2026). DOI: 10.1016/j.cpblue.2026.100088. www.cell.com/cell-press-blue/f … 3051-3839(26)00086-1

Part 2

Comment by Dr. Krishna Kumari Challa 54 minutes ago

Why immune responses to vaccines vary from person to person

Vaccines protect most people from serious illness, but the strength of that protection can vary considerably from one person to another. A new study helps us understand why.
Before a vaccine ever enters the body, the immune system may already hold clues to how strongly it will respond. In blood samples from more than 4,000 people, researchers measured antibodies against 185 antigens—targets recognized by the immune system, including those from common viruses and bacteria as well as targets associated with autoimmune diseases.

They then used artificial intelligence to analyze patterns in samples collected before and after COVID-19 vaccination, identifying antibody signatures that helped distinguish strong vaccine responders from weak ones.

The research opens a possible path toward more personalized vaccination strategies.
What this study found is that certain biomarkers, when analyzed with AI, can predict who is likely to respond well to a vaccine, even before they receive it. This suggests that some people may be more immune-ready than others.
Usually, scientists evaluate vaccine response after the shot by measuring whether the immune system produces antibodies against the target. Here, the researchers asked a different question: Could patterns already present in the blood predict the response before vaccination?

Age, sex, genetics, prior illnesses and underlying health conditions have all been linked to how strongly people respond to vaccines. People with immune-compromising conditions are often at higher risk of weaker responses. But even within these groups, outcomes can differ sharply.

The new approach is one of the first to use a broad, pre-vaccine antibody "fingerprint" to assess immune readiness. Unlike some prediction methods that rely on genetic analyses, this strategy uses antibody patterns in blood, which may be easier to adapt for clinical use.
Part 1

Comment by Dr. Krishna Kumari Challa 59 minutes ago

Simple mouth rinse may help detect stomach and colorectal cancer signals
It's widely understood that the microbiome—especially microbes found in the mouth and the gut—can have a profound effect on health. In a study published in the journal Cell Host & Microbe on Aug. 20, researchers report that by analyzing the makeup of oral microbes, they may be able to detect signals associated with gastric (stomach) and colorectal cancer. These findings could lead to the development of new, less invasive screening tests for gastrointestinal cancers.
Many species of microbes associated with the mouth are also present in the gut and may flourish there. These observations made the researchers

wonder whether oral microbes reach and persist in the gastrointestinal tract differently in people with cancer.
To conduct the study, the researchers recruited 507 volunteers to donate both oral and fecal samples, using a highly standardized collection process. The cohort included 129 healthy individuals; 215 people with metabolic disorders such as metabolic syndrome, hypertension, hyperlipidemia and type 2 diabetes; 77 people with gastric cancer; and 86 people with colorectal cancer. For the volunteers with cancer, samples were collected before the start of any treatment.

The team used gene sequencing to create what they called a mouth-to-feces (MF) index, which measures the extent to which identical microbial sequence variants are found in oral and fecal samples from the same person. They then evaluated how well the MF index could distinguish cancer patients from healthy individuals. The analysis revealed distinct signatures in people with gastric or colorectal cancer.

The findings were more nuanced than a simple cancer-versus-healthy comparison. The MF index was significantly elevated in patients with gastric or colorectal cancer but not in people with metabolic disorders. After accounting for alcohol consumption, regular exercise and BMI, the association remained robust for both gastric and colorectal cancers.
The team also compared the signatures found in the cancer patients with results from fecal occult blood tests, a standard colorectal cancer screening tool that analyzes stool samples. They found higher sensitivity with the oral samples, which were collected by a simple mouth rinse.

"It was notable that cancer-related information could be recovered from oral samples alone," say the researchers. Although only a small fraction of oral bacterial variants were also detected in the gut, models built using only these oral features could distinguish patients with cancer from healthy individuals across several independent cohorts.
In the longer term, combining microbial patterns with genetics, lifestyle and clinical outcomes may help explain why oral microbes persist more readily in some people than in others and may improve individualized risk prediction.

Mouth-to-gut microbial transmission signatures enable robust, non-invasive diagnosis of gastrointestinal cancers, Cell Host & Microbe (2026). DOI: 10.1016/j.chom.2026.07.007. www.cell.com/cell-host-microbe … 1931-3128(26)00308-2

Comment by Dr. Krishna Kumari Challa 1 hour ago

Dark energy and quantum gravity may be deeply intertwined

For close to a century, physicists have pursued a way to unite gravity with quantum mechanics. Known as quantum gravity, this goal has remained frustratingly out of reach so far. Similarly elusive is the force of dark energy, which is believed to be driving the universe's accelerating expansion.
But through new research published in Physical Review D, physicists have proposed a new explanation suggesting that these two phenomena might not be separate at all. Instead, dark energy could be a natural side effect of quantum gravity, acting on the geometry of space itself.
Gravity and quantum mechanics shape the universe on vastly different scales: While quantum mechanics concerns the realm of subatomic particles, gravity shapes structures as large as galactic clusters and cosmic filaments.

Individually, both of these theories have been tested to extraordinary precision through decades of painstaking experiments. However, the extreme conditions where both should apply at once, such as inside a black hole, have remained far beyond what any experiment can reach.
In his study, physicists took a different approach: suggesting that we can't pin down both the size and expansion rate of the universe at the same time with perfect accuracy. This limitation is built into the fundamental uncertainty that governs the quantum world: When applied to the universe as a whole, it subtly changes the equations that describe how cosmic expansion should behave over time. This built-in uncertainty could then produce exactly the kind of accelerating expansion that cosmologists currently attribute to dark energy.

Depending on the exact mathematical details, this macroscopic imprint of quantum gravity could also replace the singularity at the instant of the Big Bang, which cosmologists have long struggled to explain. Rather than relying on a point of infinite density, their proposal suggests that the Big Bang followed a gentler rebound from a previously contracting universe.
If this idea is correct, it could provide a far cleaner explanation for the origins of dark energy. In contrast to many existing theories, this would mean that the phenomenon doesn't need to be explained by some hidden particle or exotic field waiting to be discovered: Instead, it is a property of space itself, hiding in plain sight in our observations of the universe.

Savvas M. Koushiappas, Cosmological uncertainty relation and late-universe acceleration, Physical Review D (2026). DOI: 10.1103/zgnd-h2xv. On arXiv: arxiv.org/abs/2604.27771

Comment by Dr. Krishna Kumari Challa 23 hours ago

A smarter antibody could skip the fetus
Researchers have engineered a possible way around the risk some antibody drugs pose in pregnancy. These drugs, used against cancer, autoimmune disease and migraines, are hard to use safely in pregnancy because they are actively carried to the fetus via a receptor called FcRn. But the process has a quirk: mouse models and human tissue showed that the receptor binds to both IgG antibodies — which are used in the majority of approved antibody therapies — and albumin, but only shuttles the antibody across the placenta. By fusing therapeutic antibodies to albumin, the team made drugs that reached the fetus far less and reduced adverse events in mice.

https://www.science.org/doi/10.1126/sciimmunol.aee5151?utm_source=L...

https://www.genengnews.com/topics/drug-discovery/albumin-fused-anti...

Comment by Dr. Krishna Kumari Challa 23 hours ago

Why does salmonella cause serious illness in some people but not others?
Salmonella usually remains in the gut, but some strains can survive within immune cells and spread to the bloodstream, potentially causing sepsis. Severe invasive disease depends on bacterial type and strain, infectious dose, age, immune status and underlying conditions. Hospitalization data may overrepresent severe cases and cannot alone establish unusual strain virulence.

original article.

Comment by Dr. Krishna Kumari Challa yesterday

A new transmissible cancer in bullhead catfish
Genomic analysis showed melanoma tumours in brown bullhead catfish are clonally related to each other rather than to their hosts, indicating a transmissible cancer, brown bullhead transmissible melanoma. Historical reports suggest similar lesions may be longstanding and widespread, but their relationship to this disease is unconfirmed.

transmissible cancer.

original article.

Comment by Dr. Krishna Kumari Challa yesterday

Is the laundry still damp, or just cold? Why your skin can't tell the difference

Humans lack dedicated wetness receptors; perceived wetness arises from integrated cold, friction, pressure, and contextual sensory signals. Cold dry laundry can mimic dampness because both activate cold receptors. Rubbing, squeezing, visual inspection, or warming fabric can improve discrimination.

original article.

Comment by Dr. Krishna Kumari Challa yesterday

Why do we get sleepy? How neurons control sleep drive

Why does staying awake inevitably make us sleepy? Researchers have identified neuronal populations in the brains of mice that become activated during prolonged wakefulness and are crucial for sleep drive. Their findings provide new insights into how the brain generates the need for sleep.
After a long day or a sleepless night, the urge to sleep becomes almost impossible to resist. This increasing sleep pressure, also known as sleep drive, ensures that prolonged wakefulness is followed by deeper and longer recovery sleep. As sleep is essential for survival, scientists have long been investigating how the brain keeps track of time spent awake and translates it into the need for sleep.
They now have identified specific neurons that are crucial for this balanced relationship between sleep and wakefulness. This is an important missing piece of the puzzle in understanding why we become sleepy.
To identify the brain regions involved, the researchers compared brain activation patterns in mice during normal sleep-wake cycles, sleep deprivation and recovery sleep. This highlighted specific brain areas that reflected time spent awake. Within one of these regions, they further identified two distinct neuronal populations that influence sleep drive: GABAergic and serotonergic neurons in the brainstem. The activation of both neuronal populations increased the longer the animals stayed awake and declined again after sleep onset.

The researchers next asked whether these neuronal populations merely reflect wakefulness or actively generate a compensatory response to sleep. When both populations were artificially activated, mice slept longer and more deeply, displaying a form of recovery sleep that normally follows prolonged wakefulness. In contrast, inhibiting these neurons strongly reduced sleep and allowed animals to maintain alert wakefulness.
These neurons do not simply signal that an animal has been awake. The experiments show that they are crucial to promote sleep, and that they may be key components of the neural circuitry that generates sleep drive. The findings therefore provide one of the clearest demonstrations to date that specific wake-active neurons increase the drive to sleep rather than merely responding to wakefulness.
Further experiments showed that long-term inhibition of the two neuronal populations substantially reduced the need for sleep, with mice sleeping approximately 70% less than usual. Unexpectedly, most of these animals did not exhibit some of the severe behavioural impairments that typically accompany sleep deprivation. In other words, these neurons appear to determine not only how much the animals sleep but also how strongly their need for sleep builds over time.
Understanding how the brain generates sleep drive would provide entirely new opportunities for sleep research.

William Joo et al, Wake-activated neuronal populations that regulate sleep drive., Nature (2026). DOI: 10.1038/s41586-026-10928-3

Comment by Dr. Krishna Kumari Challa yesterday

Link between whale calls and special relativity

For a more precise and consistent way to detect the presence of whales, oceanographers rarely rely on sight.
Sound from a fin whale can be heard from 100 kilometers (62 miles) away underwater with a single hydrophone. Because those calls travel so far, we can use them to pinpoint where an animal is by comparing when its sound reaches receivers spread across the seafloor.
But there's a catch: If they were trying to track a nearby whale using just standard physics, they'd probably place the animal in the wrong spot—off by hundreds of meters.

In a paper recently published in the journal Physical Review E, researchers offer a potential explanation for why this occurs: The humble whale call is, improbably, tangled up with the same speed limits Einstein deduced from the universe. Their findings could improve whale tracking for conservationists.
When a whale calls, the sound doesn't take a single path to each receiver. Some of the sound travels directly to a receiver, while some of it ricochets off the ocean surface first, arriving fashionably late.
That delay can put the two signals out of phase, causing them to interfere with one another and shifting when sound appears to arrive at a receiver.
The researchers stumbled onto this while refining a computer program meant to calculate the correct speed of sound for his whale-tracking equations. The results were surprising.

The first time, they got a number that was around 1,000 meters per second, well below the roughly 1,500 meters per second that sound normally travels in seawater. And then, further on, they got values that were sometimes 3,000 meters per second.

After examining the software for a few hours, they discovered that the behaviour wasn't a coding error, but a physical effect caused when a receiver picked up both the direct signal and its reflected echo when a whale was near the ocean's surface.
Physicists call this "temporal interference," the same phenomenon that causes TV broadcasts at your home antenna to fade out because two paths arrive out of phase or out of sync. The interference can also shift the peak of the energy earlier and break the speed limit.

What appears to speed up is not the signal carrying information but the position of the signal's strongest peak. That crucial distinction is the reason their finding aligns with Einstein's theory.

For more than a century, physicists have known that waves can sometimes appear to travel faster than light when their shape changes. But the information encoded in those waves still cannot travel faster than light—the central principle of Einstein's theory of special relativity.

John L. Spiesberger et al, Supersonic and superluminal energy and speed of information via temporal interference in a dispersionless environment, Physical Review E (2026). DOI: 10.1103/1mth-rs2j. On arXiv: arxiv.org/abs/2510.20060

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