Lifeboat Foundation: Safeguarding Humanity
Toggle light / dark theme

Blog

Category: biotech/medical – Page 269

Ancestry-Associated Performance Variability of Open-Source AI Models for EGFR Prediction in Lung Cancer

Open-source AI models for LungCancer EGFR mutation prediction showed high accuracy overall but reduced performance in Asian patients and pleural samples, indicating the need for broader validation.

Importance Artificial intelligence (AI) models are emerging as rapid, low-cost tools for predicting targetable genomic alterations directly from routine pathology slides. Although these approaches could accelerate treatment decisions in lung cancer, little is known about whether their performance is consistent across diverse patient populations and tissue contexts.

Objective To evaluate the performance and generalizability of 2 open-source AI pathology models for predicting EGFR mutation status in lung adenocarcinoma (LUAD) across independent cohorts and ancestral subgroups.

Design, Setting, and Participants This cohort study included patients with LUAD from 2 cohorts: Dana-Farber Cancer Institute (DFCI) from June 2013 to November 2023, and a European-based trial (TNM-I) from August 2016 to February 2022. All patients had paired next-generation sequencing data and hematoxylin-eosin–stained whole-slide images. In the DFCI cohort, genetic ancestry was inferred using germline genotype data. Data analyses were performed from July 2025 to September 2025.

Researchers uncover MraZ ‘donut’ deformation that triggers bacterial cell division

A research team led by UAB researcher David Reverter has discovered the molecular mechanism that describes in detail the process regulating cell division in bacteria, based on the binding of the MraZ protein to the dcw gene cluster. The research has been published in Nature Communications.

Cell division is a central process in all living organisms and requires the coordinated action of many proteins and other regulatory elements. In most bacteria, this process is encoded in a gene cluster called the dcw operon, which groups all the genes that produce the proteins necessary to carry out cell division and bacterial wall formation.

These sets of genes are activated by proteins that act as transcription factors: they bind to the promoter region of the gene, the DNA sequence that indicates the point to start transcription, just before the first codon (the basic unit of gene information) that codes for the beginning of the protein sequence. One of these transcription factors is MraZ, the first gene of the dcw operon in all bacteria. When activated, the necessary proteins (encoded within the genes of the operon) are produced so that the bacteria can divide. It is, therefore, the transcription factor that controls the activity of the operon responsible for cell division in most bacteria.

SREBP-1 upregulates SOAT1 to promote tumor growth by preventing lipotoxicity

Zhong et al. demonstrate that SREBP-1 and SOAT1 are co-upregulated in GBM and NSCLC, coupling cholesterol acquisition and storage. They reveal that SREBP-1 transcriptionally activates SOAT1, enabling cancer cells to sustain cholesterol homeostasis, and that targeting SOAT1 disrupts this balance, leading to ROS accumulation, mitochondrial dysfunction, and tumor cell death.

A drug to cure jet lag?

Adapting to eastward travel, such as west-to-east transmeridian flights, or to night-shift work requires advancing the internal clock, a process that normally takes longer and is physiologically harder than delaying it.

Existing methods, such as light therapy or melatonin, are heavily constrained by timing and often yield inconsistent results.

Mic-628’s consistent phase-advance effect, regardless of when it is administered, represents a new pharmacological strategy for resetting the circadian clock.

The researchers discovered that Mic-628 selectively induces the mammalian clock gene Per1.

Mic-628 works by binding to the repressor protein CRY1, promoting the formation of a CLOCK–BMAL1–CRY1–Mic-628 complex that activates Per1 transcription through a “dual E-box” DNA element.

As a result, both the central clock in the brain’s suprachiasmatic nucleus (SCN) and peripheral clocks in tissues such as the lungs were advanced—in tandem and independent of dosing time.

In a simulated jet lag mouse model (6-hour light-dark phase advance), a single oral dose of Mic-628 shortened re-entrainment time from seven days to four.

Continue reading “A drug to cure jet lag?” | >

Studies show 11 genetic variants affect gut microbiome

In two new studies on 28,000 individuals, researchers are able to show that genetic variants in 11 regions of the human genome have a clear influence on which bacteria are in the gut and what they do there. Only two genetic regions were previously known. Some of the new genetic variants can be linked to an increased risk of gluten intolerance, hemorrhoids and cardiovascular diseases.

The studies are published in the journal Nature Genetics.

The community of bacteria living in our gut, or gut microbiome, has become a hot research area in recent years because of its great significance for health and disease. However, the extent to which our genes determine which bacteria are present in the intestines has been unclear. Until now, it has only been possible to link a few genetic variants to the composition of the gut microbiome with certainty.

Brain mechanism behind ‘flashes of intuition’

Despite decades of research, the mechanisms behind fast flashes of insight that change how a person perceives their world, termed “one-shot learning,” have remained unknown. A mysterious type of one-shot learning is perceptual learning, in which seeing something once dramatically alters our ability to recognize it again.

Now a new study, the researchers address the moments when we first recognize a blurry object, a primal ability that enabled our ancestors to avoid threats.

Published in Nature Communications, the new work pinpoints for the first time the brain region called the high-level visual cortex (HLVC) as the place where “priors” — images seen in the past and stored — are accessed to enable one-shot perceptual learning.

“Our work revealed, not just where priors are stored, but also the brain computations involved,” said co-senior study author.

Importantly, past studies had shown that patients with schizophrenia and Parkinson’s disease have abnormal one-shot learning, such that previously stored priors overwhelm what a person is presently looking at to generate hallucinations.

“This study yielded a directly testable theory on how priors act up during hallucinations, and we are now investigating the related brain mechanisms in patients with neurological disorders to reveal what goes wrong,” added the author.

The research team is also looking into likely connections between the brain mechanisms behind visual perception and the better-known type of “aha moment” when we comprehend a new idea. ScienceMission sciencenewshighlights.

Continue reading “Brain mechanism behind ‘flashes of intuition’” | >

Discussing the implication of DNA methylation in human diseases

DNA methylation plays a critical role in gene expression regulation and has emerged as a robust biomarker of biological age. This modification will become heavier or site drift along with aging. Recently, it is termed epigenetic clocks—such as Horvath, Hannum, PhenoAge, and GrimAge—leverage specific methylation patterns to accurately predict age-related decline, disease risk, and mortality. These tools are now widely applied across diverse tissues, populations, and disease contexts. Beyond age-related loss of methylation control, accelerated DNA methylation age has been linked to environmental exposures, lifestyle factors, and chronic diseases, further reinforcing its value as a dynamic and clinically relevant marker of biological aging. DNA methylation is reshaping our understanding of aging and disease risk, with promising implications for preventive medicine and interventions aimed at promoting healthy longevity. However, it must be admitted that some challenges remain, including limited generalizability across populations, an unclear mechanism, and inconsistent longitudinal performance. In this review, we examine the biological foundations of DNA methylation, major advances in epigenetic clock development, and their expanding applications in aging research, disease prediction and health monitoring.

Aging is a complex, multifactorial process that affects nearly all biological systems. While chronological age simply measures the passage of time from birth, biological age reflects the functional state and health of an individual’s tissues and organs (Kiselev et al., 2025). This distinction is critical, as individuals of the same chronological age often exhibit markedly different biological conditions, disease risks, and mortality trajectories (Dugue et al., 2018). Therefore, biological age potentially serves as a more meaningful measure of aging-related decline and is increasingly used to assess overall health status, predict disease onset, and evaluate the effectiveness of interventions aimed at promoting healthy longevity (Dugue et al., 2018; Petkovich et al., 2017).

Among various biomarkers proposed to estimate biological age, epigenetic modifications—particularly DNA methylation—have emerged as one of the most reliable and informative (Dugue et al., 2018). In epigenetics, DNA methylation involves the addition of a methyl group to the 5′ position of cytosine residues, typically at CpG dinucleotides, which can regulate gene expression without altering the underlying DNA sequence. Moreover, DNA methylation can be accurately measured by sequencing at methylated sites with bisulfate treatment (Zhang et al., 2012). Age-related changes in DNA methylation pattern are not random; they occur at specific genomic locations. These methylated sites are picked and constitute come patterns, by which scientists can construct “epigenetic clocks” to precisely estimate a person’s biological age based on their DNA modification. As people grow older, their methylation profiles shift in predictable ways (Kiselev et al., 2025; Horvath, 2013; Horvath and Raj, 2018).

/* */