A mitochondrial transport protein promotes carnitine synthesis in mice when fat consumption is needed.
Learn more in a new SciencePerspective.
Angela M. Ramos-Lobo and Pierre Maechler Authors Info & Affiliations
Science.
Category: biotech/medical – Page 258
Two lipids that help switch on STING open doors in fight against autoimmune disorders and cancer
UT Southwestern Medical Center researchers have identified two lipids that work together with a quintessential protein known as stimulator of interferon genes (STING) to launch an immune response in the human body. Their findings, detailed in two papers published concurrently in Nature, could lead to new ways to manipulate the immune system to fight infections, cancer, autoimmune disorders, and neurodegenerative diseases.
“These studies reveal additional levels of regulation of the cGAS-STING pathway, underscoring the importance of controlling the activity of this pathway so the body can mount an effective immune response against infections while avoiding autoimmune reactions to self-tissues. Dysregulation of this pathway has been shown to cause a variety of autoimmune and inflammatory diseases,” said Zhijian “James” Chen, Ph.D., Professor of Molecular Biology and Director of the Center for Inflammation Research at UT Southwestern.
Dr. Chen, one of the world’s leading researchers on innate immunity, is a co-author on one study and senior author on the other. His discovery of cGAS, an enzyme that produces a molecule called cGAMP to activate STING, has been recognized with numerous top honors including the 2026 Japan Prize in Life Sciences, the 2024 Albert Lasker Basic Medical Research Award, and the 2019 Breakthrough Prize in Life Sciences.
Microplastic presence in dog and human testis and its potential association with sperm count and weights of testis and epididymis
The ubiquitous existence of microplastics and nanoplastics raises concerns about their potential impact on the human reproductive system. Limited data exists on microplastics within the human reproductive system and their potential consequences on sperm quality. Our objectives were to quantify and characterize the prevalence and composition of microplastics within both canine and human testes and investigate potential associations with the sperm count, and weights of testis and epididymis. Using advanced sensitive pyrolysis-gas chromatography/mass spectrometry, we quantified 12 types of microplastics within 47 canine and 23 human testes. Data on reproductive organ weights, and sperm count in dogs were collected.
Viewing Neural Networks Through a Statistical-Physics Lens
Statistical physics is shedding light on how network architecture and data structure shape the effectiveness of neural-network learning.
Machine-learning technologies have profoundly reshaped many technical fields, with sweeping applications in medical diagnosis, customer service, drug discovery, and beyond. Central to this transformation are neural networks (NNs), models that learn patterns from data by combining many simple computational units, or neurons, linked by weighted connections. Acting collectively, these neurons can process data to learn complex input–output relationships. Despite their practical success, the fundamental mechanisms by which NNs learn remain poorly understood at a theoretical level. Statistical physics offers a promising framework for exploring central questions in machine-learning theory, potentially clarifying how learning depends on the layout of the network—the NN architecture—and on statistics of the data—the data structure (Fig. 1).
Three recent papers in a special Physical Review E collection (See Collection: Statistical Physics Meets Machine Learning — Machine Learning Meets Statistical Physics) provide significant insights into these questions. Francesca Mignacco of City University of New York and Princeton University and Francesco Mori of the University of Oxford in the UK derived analytical results on the optimal fraction of neurons that should be active at a given time [1]. Abdulkadir Canatar and SueYeon Chung of the Flatiron Institute in New York and New York University investigated the influence of the precision with which a network is “trained” on the amount of data the NN can reliably decode [2]. Francesco Cagnetta at the International School for Advanced Studies in Italy and colleagues showed that NNs whose structure mirrors that of the data learn faster [3].
Why do microbes team up? A new model explains nutrient sharing in fluctuating environments
Depending on others for something you need may feel like a risky proposition—and perhaps a human one. It is actually a survival strategy found in the microbial world, and far more frequently than one might expect. Discovering why is key to understanding how microbes form stable communities across medical, industrial, and ecological settings.
A new study by bioengineering professor Sergei Maslov (CAIM co-leader), computational scientist Ashish George, and biology professor Tong Wang explores why interdependence can be such a winning move for microbial communities. Their work, published in Cell Systems, demonstrated that a mathematical model of how bacteria produce and share resources accurately predicted the outcome of experiments with living E. coli strains.
The researchers’ collaboration began during their time as colleagues at the Carl R. Woese Institute for Genomic Biology at the University of Illinois Urbana-Champaign. George continued the collaboration in his position at the Broad Institute; Wang, in his appointment at Purdue University. Maslov, who led the study, remains at Illinois and is an affiliate member of the National Institute for Theory and Mathematics in Biology.
The AI Tsunami is Here & Society Isn’t Ready | Dario Amodei x Nikhil Kamath | People by WTF
I sat down with Dario Amodei in Bangalore. He built Claude, but he started as a biologist looking for a tool to cure disease. Today, he’s at the helm of an AI revolution that he compares to a tsunami society is actively ignoring. We got into the heavy stuff: why Anthropic secretly withheld a working model before ChatGPT existed, whether AI is on the verge of consciousness, and if outsourcing our thinking is going to make humans measurably stupider. Dario makes the case that coding is a dying skill, critical thinking is our last real edge, and the absurd concentration of power in AI right now is a massive problem, even though he’s one of the people holding it.
00:00 Introduction.
06:13 Scaling laws explained simply.
13:27 Trust, humility, and corporate motives.
22:44 Using Claude personally, AI knowing you.
31:03 Rich people criticizing their own system.
37:05 India’s role and IT partnerships.
44:15 Will AI surpass humans at everything.
50:17 Career advice for young Indians.
56:38 Open source vs closed AI models.
1:02:40 Biotech as the next big bet.
#NikhilKamath Co-founder of Zerodha and Gruhas.
Host of ‘WTF is’ & ‘People By WTF’ Podcast.
Twitter: https://twitter.com/nikhilkamathcio/
Instagram: / nikhilkamathcio.
LinkedIn: https://www.linkedin.com/in/nikhilkam… / nikhilkamathcio #Darioamodei LinkedIN–
/ dario-amodei X — https://twitter.com/DarioAmodei Instagram —
/ dario.amodei Watch ‘WTF is’ Podcast on Spotify https://tinyurl.com/4nsm4ezn Watch ‘People by WTF’ Podcast on Spotify https://tinyurl.com/yme92c59 Watch ‘WTF Online’ on Spotify https://tinyurl.com/4tjua4th #WTFiswithnikhilkamath #PeopleByWTF #WTFOnline.
Facebook: / nikhilkamathcio.
#Darioamodei.
LinkedIN-/ dario-amodei.
X — https://twitter.com/DarioAmodei.
Instagram — / dario.amodei.
Watch ‘WTF is’ Podcast on Spotify.
https://tinyurl.com/4nsm4ezn.
Watch ‘People by WTF’ Podcast on Spotify.
Chemists thought phosphorus had shown all its cards—until it surprised them with a new move
A discovery by UCLA organic chemists may one day put catalytic converter thieves out of business. In new research, they’ve used abundant, inexpensive phosphorus as a catalyst in chemical reactions that usually require precious metals like platinum, one of the metals targeted in theft of the automotive components that convert chemicals in vehicle exhaust into less harmful forms.
This advance, however, will likely be more useful in the pharmaceutical industry and could one day help bring down the price of some drugs.
Common anti-seizure drug prevents Alzheimer’s plaques from forming
At the heart of the new discovery is amyloid precursor protein (APP), a protein that plays important roles in brain development and synaptic formation. Abnormal processing of APP can lead to the production of amyloid‑beta peptides, which play a central role in the development of Alzheimer’s disease. The scientists found that how APP is trafficked also controls whether a neuron forms amyloid-beta 42.
During the synaptic vesicle cycle — a fundamental process that underlies every thought, movement, memory or sensation — levetiracetam binds to a protein called SV2A. This interaction slows down a step in which neurons recycle synaptic vesicle components from the cell’s surface. By pausing this recycling process, the drug enables APP to remain on the cell’s surface longer, diverting it away from the pathway that produces toxic amyloid‑beta 42 proteins.
“In our 30s, 40s and 50s, our brains are generally able to steer proteins away from harmful pathways,” the author said. “As we age, that protective ability gradually weakens. This is not a statement of disease; this is just a part of aging. But in brains developing Alzheimer’s, too many neurons go astray, and that’s when you get amyloid-beta 42 production. And then it’s tau (or ‘tangles’), and then it’s dead cells, then dementia, then neuroinflammation — and then it’s too late.”
To effectively prevent Alzheimer’s symptoms, high-risk individuals would need to begin taking levetiracetam “very, very early,” the author said, possibly up to 20 years before the new FDA-approved Alzheimer’s disease test would even capture mildly elevated levels of amyloid-beta 42.
“You couldn’t take this when you already have dementia because the brain has already undergone a number of irreversible changes and a lot of cell death,” the author said.
Leveraging its status as an FDA-approved and widely used drug, the team mined existing human clinical data to investigate whether Alzheimer’s patients who took levetiracetam experienced slowed cognitive decline. They obtained clinical data from the National Alzheimer’s Coordinating Center and conducted a correlative analysis, finding that Alzheimer’s patients who took levetiracetam were associated with a significant delay from the diagnosis of cognitive decline to death compared to those taking lorazepam or no/other anti-epileptic drugs. ScienceMission sciencenewshighlights.