Comment

Comment by Dr. Krishna Kumari Challa 10 hours ago

Ultra-processed foods tied to nearly fourfold asthma risk in children

Children who get more than 30% of their daily energy from ultra-processed foods (UPFs), such as soda drinks, packaged snacks, and sweetened breakfast cereals, have a nearly fourfold risk of developing asthma in their early school years.

The finding comes from a new study published in the journal Allergy that followed nearly 700  children for an average of 3.4 years as part of  a project.

Asthma is a common, long-term condition that affects breathing and often runs in families. While genetics are known to play a role, environment and lifestyle factors are also to blame. In this study, researchers wanted to know whether certain parts of our modern diet, specifically ultra-processed foods, were associated with the later development of asthma and other allergic diseases.
They followed 691 children who were 4 or 5 years old when the study started. Parents reported what their children ate by completing a detailed questionnaire, and the team categorized the foods using the NOVA system. This is a framework that classifies foods by processing levels rather than nutrient content.

Parents also updated the researchers each year on whether their children had been diagnosed with asthma or allergies. To ensure accuracy, the team took into account numerous factors that might skew the results, such as the child's weight and how much time they spent in front of screens.

Part 1

Comment by Dr. Krishna Kumari Challa 10 hours ago

How the brain switches between older and newer memories

As humans and other animals experience new things, their brains continuously update their memory of past events. These updates allow them to adapt to changing environments, all while preserving older memories that could still help them to make decisions in some situations.

Many past neuroscience studies have investigated the neural circuits involved in the encoding and retrieval of memories. However, the mechanisms via which it decides whether to retrieve older or newly updated memories remain poorly understood.

Researchers recently carried out a study involving mice that was aimed at better understanding how the brain switches between older and newer memories.

Their paper, published in Nature Neuroscience, delineates a specific neural pathway that appears to support the flexible switching between the retrieval of old and updated memories in mice, involving brain regions known as the medial septum (MS), the medial entorhinal cortex (MEC) and the CA1 segment in the hippocampus.

The researchers' earlier observations ultimately led them to hypothesize that individual events leave their own "memory traces" each time the brain updates memories. They also proposed that the brain can access previously formed engram cell ensembles (i.e., cells encoding specific memories) that remain unaltered during the updating process, but it predominantly retrieves memories encoded by newly formed engram cell ensembles.

To test their hypotheses, the researchers carried out a series of experiments involving adult male mice. The mice were trained to form specific associations between stimuli and rewards, which ultimately guided their behaviour.

The researchers then exposed the mice to new experiences that led them to update their original memory associations. Using neuroimaging techniques, they looked at what cells became active while the mice's brain was retrieving newer, updated memories.

Their approach was to investigate whether neurons are selectively activated during retrieval after memory updating, compared with a single learning episode as a non-memory-updating control.

The researchers  identified a neural pathway that appears to play a central role in the adaptive switching between older memories and newer, updated ones.

Mujun Kim et al, A septo–entorhinal GABAergic pathway that enables switching between episodic memories, Nature Neuroscience (2026). DOI: 10.1038/s41593-026-02280-6.

**

Comment by Dr. Krishna Kumari Challa 10 hours ago

The study has several limitations. Hospital records may miss less severe cases that were managed in primary care settings. The analysis was performed on 159 metabolites and 2,923 proteins from plasma samples alone, failing to capture specific molecular events that may occur in internal organs.

All data were collected at baseline, thereby preventing assessment of disease progression over time. Only the two omics layers were the focus of the study, and missing data have been imputed using methods that could introduce bias.

Feature importance could be misinterpreted due to correlations within the data. Since protein models proved so strong, the study focused on the best protein markers, without fully distinguishing which were common across diseases vs. disease-specific.

Despite limitations, the study carries important implications. Genomics and epigenomics enable greater predictive power than proteins and metabolites. Validating across populations enhances the robustness and fairness of a model. The combination of longitudinal data enables monitoring of disease progression, leading to timely interventions and personalized care processes.

Jiawen Du et al, Multi-omics integration predicts the incidence of 17 diseases in the UK Biobank, Nature Communications (2026). DOI: 10.1038/s41467-026-73017-z

Part 3

**

Comment by Dr. Krishna Kumari Challa 11 hours ago

Via this analysis, researchers identified key molecular markers such as the well-established prostate-specific antigen (PSA) in prostate cancer and new candidates such as PRG3 in skin cancer. Some of these proteins were stratified by medication use and also adjusted for socioeconomic status, demonstrating that omics data can correlate with individual risk factors, illuminate disease pathways, and potentially guide follow-up therapeutic targets.

The authors noted, "Our study not only develops better risk prediction models, but also provides insights into a wide range of disease risk factors."

The mixOmics tool was used to deal with data from extensive molecular datasets. Other deep learning methods, Cox regression, Elastic Net, Random Survival Forest, and MOGONET were also tested. Cox regression often overfitted; Random Forest models were slow; other approaches diluted the signal, but mixOmics was both accurate and fast.

Analysis of metabolites revealed only widespread lipid-related patterns and disease-specific structural changes associated with proteins. Collectively, these datasets revealed common biological pathways, metabolic processes, and signaling pathways involved in disease pathogenesis.

Proteins were the major predictors of combinations, confirming the strong individual predictive power of proteomics. It confirmed known protein-disease associations, such as PRG3 and skin cancer, and identified relationships between proteins and medications, demographics, and social factors.

Known drug-disease links, such as Bisoprolol and heart disease, were confirmed in some of the results, and others are promising leads for opportunities to repurpose drugs or identify new side effects that need further study.
Part 2

Comment by Dr. Krishna Kumari Challa 11 hours ago

Your blood may already know what illness comes next—long before symptoms appear, study finds

Predicting who will develop common diseases is key to prevention, detection, and early treatment. Traditionally, clinicians have estimated risk based on age, sex, laboratory results, and lifestyle factors. Although these classical indicators provide important information, they do not necessarily reflect the multifaceted biological mechanisms underlying disease development.

Researchers are now peering deeper into the hidden molecular world inside us. Multi-omics, an advanced biological analysis approach that integrates data from multiple "omes," such as genomics, transcriptomics, proteomics, and metabolomics, provides a comprehensive view of biological systems. It is like opening several windows at once. Each layer adds a clue, each clue adds a story.

Of the different types of omics technologies, proteomics (the study of proteins) and metabolomics (the study of metabolites) have been especially promising. Nevertheless, despite the advances achieved through large-scale approaches in these areas of research, studies integrating both remain scarce, and each new study is another step forward toward personalized medicine.

Publishing in Nature Communications, the researchers studied almost 24,000 people from the UK BIOBANK  to see if adding detailed molecular information, like proteins (proteomics) and small molecules (metabolomics), could help predict disease risk.

They found that using this additional data improved prediction accuracy across all 17 diseases they studied, including cancers, heart problems, diabetes, brain disorders, and lung diseases. This worked better than relying only on standard clinical measures.

Metabolomics provides inexpensive measures of circulating metabolites and can outperform traditional risk factors in predicting health. Proteomics is the quantification of proteins in blood and tissues to characterize disease biology that enhances risk prediction. Large-scale studies that combine both are rare.

Combined utilization of these complementary strategies may lead to improved disease prediction, allowing early diagnosis, precise prognosis, and ultimately personalized treatment approaches.

Given this gap, researchers performed a large-scale analysis of 159 metabolites and 2,923 proteins from nearly 24,000 individuals in the UK Biobank (a key resource for grand-scale studies bridging molecular data with disease). To determine the added predictive value of metabolomics and proteomics data (versus conventional clinical variables), researchers evaluated different prediction models across 17 diseases using these additional omics parameters.

They also matched important molecular attributes of the disease to demographic, clinical, and socioeconomic variables, illuminating underlying features across populations related to variability in disease etiology and risk.

The authors said, "Proteomics-only models generally outperformed metabolomics-only models for 16 of the 17 diseases, and integrating both omics added little prediction power over proteomics-only models."
Part 1

Comment by Dr. Krishna Kumari Challa on Wednesday

Bitter herbal extracts spur stomach acid in human gastric cells, study finds

Bitter herbal extracts, particularly those rich in polyphenols, stimulate proton secretion in human gastric cells via activation of bitter taste receptors TAS2R4, TAS2R5, and TAS2R39, promoting gastric acid production. Combinations of multiple extracts produced stronger effects than individual extracts, suggesting synergistic interactions among various plant compounds.
Bitter-tasting herbal extracts have traditionally been used to support digestion, yet the molecular basis of their effects has remained largely unclear.
Researchers now gained new insights into this mechanism. Using a cellular model, its researchers demonstrated that herbal extracts can stimulate proton secretion in human gastric cells as a key mechanism of gastric acid production, with combinations of extracts showing particularly strong effects. Extracts rich in polyphenols proved especially potent. The study further identified three human bitter taste receptor subtypes as key mediators of this response.
The researchers investigated a commercially available herbal preparation commonly used to alleviate digestive complaints. The formulation consists of extracts from nine plants and is characterized by a pronounced bitter taste. Based on this, the scientists hypothesized that the bitter compounds it contains, including polyphenols, not only activate bitter taste receptors in the mouth, but also stimulate gastric acid secretion through extraoral bitter taste receptors located in the stomach. Roughly 25 different human bitter taste receptor subtypes are known.
Their experiments revealed that several extracts, especially those from masterwort, juniper, sage, and yarrow, enhanced proton secretion in human gastric cells. In contrast, extracts from plants such as dandelion and gentian did not produce significant effects within the tested concentration range of up to 300 micrograms per milliliter.

The study also found that extracts with particularly high polyphenol levels exerted the strongest stimulatory effects. The researchers therefore propose that these phytochemicals may play an important role in promoting gastric acid secretion. Additional molecular biology analyses further indicated that the bitter taste receptors TAS2R4, TAS2R5, and TAS2R39 are involved in mediating the observed increase in proton secretion.
The combination containing all nine plant extracts produced the strongest stimulation of cellular proton secretion. In contrast, the mixture composed of the four most active individual extracts showed a considerably weaker effect, while the blend of the five least active extracts triggered only a slight increase in proton secretion."

According to the researcher, the findings indicate that cellular response emerges through the interaction of multiple compounds that enhance one another's effects.
Apart from polyphenols, other plant constituents are also likely to contribute to this synergistic effect.
The study therefore offers a potential molecular explanation for why bitter-tasting herbal preparations have long been regarded as digestive aids. By activating bitter taste receptors in the stomach, these compounds may directly stimulate gastric acid secretion and thereby support digestive processes. The results also indicate that complex herbal mixtures can, in some cases, be more effective than isolated extracts.

Phil Richter et al, A Digestive Herbal Mixture Preparation Stimulates Proton Secretion in Human Parietal Cells through Phenolic Compounds Targeting Bitter Taste Receptors, Molecular Nutrition & Food Research (2026). DOI: 10.1002/mnfr.70443

**

Comment by Dr. Krishna Kumari Challa on Wednesday

New study challenges the idea that testosterone drives risk-taking behavior
A meta-analysis of 52 studies with over 17,000 participants found no reliable association between testosterone levels and risk-taking behavior. The relationship between testosterone and risk-taking did not differ between men and women, and only weak links appeared in specific tasks such as lottery games. Risk-taking appears to result from a combination of biological, psychological, and social factors rather than testosterone alone.
A separate meta-analysis looking at sex differences found that testosterone's link to risk-taking behaviour is no stronger in men than in women.

Irene Sánchez Rodríguez et al, No relationship between testosterone and risk aversion: A meta-analytic review, Neuroscience & Biobehavioral Reviews (2026). DOI: 10.1016/j.neubiorev.2026.106575

Comment by Dr. Krishna Kumari Challa on Wednesday

In an ant colony, the queen isn't in charge. So who is?
Ant colonies function as self-organized systems without centralized leadership; the queen's primary role is reproduction, not governance. Complex colony behaviors, such as efficient transportation networks and intricate nest construction, emerge from simple individual rules, pheromone-based communication, and stigmergy. Collective problem-solving and coordination improve with group size in ants, contrasting with human group dynamics.

original article.

Comment by Dr. Krishna Kumari Challa on Wednesday

The fog is alive: Droplets host bacteria that clear toxins from our air

Fog droplets host active bacterial communities, notably methylobacteria, which grow and metabolize pollutants such as formaldehyde, converting it to carbon dioxide. These microbial processes contribute to air purification, indicating fog acts as a transient aquatic habitat with significant ecological and atmospheric implications. Fog water may require purification before use as a drinking source due to microbial presence.

Thi Thuong Thuong Cao et al, Growth and formaldehyde degradation of photoheterotrophic Methylobacterium within radiation fogs, mBio (2026). DOI: 10.1128/mbio.00463-26

Comment by Dr. Krishna Kumari Challa on Wednesday

Wine's leftovers could help wean chicken farms off antibiotics
Inclusion of 0.5% grape pomace in broiler chicken diets improved weight gain, feed efficiency, and gut health to levels comparable with antibiotic growth promoters, while reducing gut inflammation and harmful bacteria. Both raw and fermented grape pomace altered the gut microbiome favorably and increased butyrate production. Utilizing grape pomace as a feed additive could reduce reliance on antibiotics and repurpose a major agricultural byproduct.

Milan K. Sharma et al, Dietary grape pomace mitigates high-NSP-induced inflammation and production loss via microbiome-SCFA-immune mediated pathways, npj Biofilms and Microbiomes (2026). DOI: 10.1038/s41522-026-00996-8

• ‹ Previous
• 1
• 2
• 3
• 4
• …
• 1231
• Next ›
• Page