Lifeboat Foundation

The use of antidepressants during pregnancy significantly increased the risk of a child experiencing functional constipation—a common DGBI that may be painful—during their first year of life. “After adjusting for covariates, SSRI/SNRI exposure was associated with an over 3-fold increased risk for functional constipation,” the investigators wrote.

“We found that, at the age of one, 63% of children exposed to antidepressants during pregnancy experienced constipation, compared with 31% of children whose mothers did not take medication,” said study co-author Larissa Takser, MD, professor of pediatrics at the Université de Sherbrooke in Québec. “This finding suggests a potential connection between serotonin levels in utero and gut development, and opens new doors to examine SSRI properties not previously studied.”

The investigators’ collective findings point to a promising avenue of future studies: the gut epithelium as a new and potentially safer target for treating mood disorders, particularly for pregnant women. “Together, these data define a novel potential mechanism for gut-brain communication and identify intestinal epithelial 5-HT as a new and potentially safer therapeutic target for mood regulation,” the authors stated.

Quantum sensors, a cutting-edge technology capable of detecting subtle signals from the human body, could soon transform how diseases are diagnosed and monitored, according to a report from the Quantum Economic Development Consortium (QED-C).

The report outlines how quantum sensing tools — ranging from diamond-based detectors to optically pumped magnetometers — offer unprecedented sensitivity compared to traditional medical devices. These sensors could enable earlier diagnoses for diseases like Alzheimer’s, provide better imaging of fetal development, and even analyze the microbiome in real time.

“Improved sensors could impact diverse aspects of biomedicine,” the report states. “For example, quantum sensors offer the possibility of significantly more efficient and accurate medical diagnoses for patients, thanks to their increased sensitivity and novel options for form factor. These attributes could enable quantum sensors to collect vast amounts of data about patients and medical conditions, and thus facilitate drug and treatment development and earlier diagnosis of disease. The advantages of quantum sensors encourage new ideas about solutions, quantum use cases, and business models across the biomedical industry — from prenatal care to cancer detection and treatment.”

Artificial intelligence is no longer just a buzzword; it’s a transformative force reshaping industries, from healthcare to finance to retail. However, behind every successful AI system lies an often-overlooked truth: AI is only as good as the data that powers it.

Organizations eager to adopt AI frequently focus on algorithms and technologies while neglecting the critical foundation—data. Even the most advanced AI initiatives are doomed to fail without a robust data strategy. I’ll explore why a solid data strategy is the cornerstone of successful AI implementation and provide actionable steps to craft one.

Imagine building a skyscraper without solid ground beneath it. Data plays a similar foundational role for AI. It feeds machine learning models, drives predictions and shapes insights. However, as faulty materials weaken a structure, poor-quality data can derail an AI project.

A research team from the Chinese Academy of Sciences (CAS) and BGI Research has unveiled the complex mechanisms through which immunoglobulins impact the aging process, a discovery that could transform our understanding of aging.

This research, published in Cell on November 4, not only charts a high-precision map of aging across various organs but also reveals the dual-edged sword of immunoglobulins in systemic aging.

The quest for systemic biomarkers and key drivers of aging has been a long-standing puzzle in the field of gerontology. This study, a collaborative effort between Guanghui Liu’s team from the Institute of Zoology (IOZ) of CAS, Ying Gu’s team from BGI Research, Weiqi’s Zhang team from the Beijing Institute of Genomics of CAS, and Jing Qu’s team also from IOZ, has provided compelling answers.

Also known as Virgo A or NGC 4,486, M87 is the brightest object in the Virgo cluster of galaxies, the largest gravitationally bound type of structure in the universe. It came to fame in April 2019 after scientists from EHT released the first image of a black hole in its center.

Led by the EHT multi wavelength working group, a study published in Astronomy and Astrophysics presents the data from the second EHT observational campaign conducted in April 2018, involving over 25 terrestrial and orbital telescopes.

The authors report the first observation of a high-energy gamma-ray flare in over a decade from the supermassive black hole M87, based on nearly simultaneous spectra of the galaxy spanning the broadest wavelength range ever collected.

What are we missing?

Metabolic changes influence T cell identity and open avenues for interventions to sustain immune function.

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Psychological studies have shown that the way humans respond to others’ emotions is strongly influenced by their own past emotional experiences. When a similar emotional situation—such as a past stressful event—is observed in another person, we can react in two different ways. On one hand, it may generate empathy, enhancing the ability to understand others’ problems and increasing sensitivity to others altered emotions. On the other hand, it may induce self-distress resulting into an avoidance towards others.

The research group at IIT has demonstrated that a similar phenomenon also occurs in animals: recalling a negative experience strongly influences how an individual responds to another who is experiencing that same altered emotional state. More specifically, animals exhibit different reactions only if the negative event they experienced in the past is identical to the one they observe in others. This indicates that even animals can specifically recognize an emotional state and react accordingly even without directly seeing the triggering stimuli.

Continue reading “Self-experience of a negative event alters responses to others in similar states through prefrontal cortex CRF mechanisms” »

A new, more sustainable AI model recognizes visual scenes by mirroring brain processes, opening doors for applications in medical diagnostics, drug discovery and beyond.