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Off-the-shelf kitchen chemistry could make Li–S batteries thinner

Demand is booming for batteries that are faster, thinner and cheaper. We want electric cars and bikes that travel further, devices that last longer, charge quicker and cost less. Today, lithium-ion batteries (LIBs) set the benchmark. But after decades of research, this technology is approaching its limits, and each new gain is harder to achieve.

Lithium–sulfur (Li–S) batteries are a promising next-generation technology. They store far more energy than LIBs by weight and are made from cheap, readily available materials.

But here’s the catch. Current Li–S batteries take up around 1.5 to 2.0 times more space than LIBs. In other words, their volumetric capacities are much lower. That’s a serious bottleneck because in many real-world applications, space matters more than weight. From portable electronics, electric vehicles to aerospace systems, every inch of space matters.

Cancer tumors may protect against Alzheimer’s by cleaning out protein clumps

Cancer and Alzheimer’s are two of the most common chronic diseases associated with aging. For years, doctors have known about a curious aspect of these two conditions: people who survive cancers are significantly less likely to develop Alzheimer’s. While this link has been observed in the data for some time, the biological reasons for it have remained a mystery. Now, a new study published in the journal Cell has discovered a possible explanation.

In the Alzheimer’s brain, abnormal levels of a naturally occurring protein called amyloid-beta clump together to form plaques. The plaques disrupt communication between brain cells, eventually leading to cognitive decline and memory loss. Current medicines struggle to remove these clumps, but this new research suggests that cancer might be sending in a biological cleanup crew.

To see whether and how cancer provides this protection, researchers at the Huazhong University of Science and Technology in China used advanced mouse models of Alzheimer’s disease. They transplanted three types of tumors (lung, colon and prostate cancer) into the mice and found that the amyloid plaques in their brains shrank significantly.

Metastatic Recurrence in Adolescent and Young Adult Cancer—Key Drivers of Early Mortality

Editorial: Metastatic recurrence nearly triples mortality risk in Breast Cancer among young adults and increases death risk in sarcoma and colorectal cancer—highlighting the need for earlier detection and novel treatments.

Survivors of adolescent and young adult cancer (aged 15 to 39 years at diagnosis) are a large and growing population at risk for early mortality, with death due to primary cancer recurrence/progression a large contributor to increased mortality among survivors.1-3 In JAMA Oncol ogy, using linked data between the California Cancer Registry, Kaiser Permanente Northern California, and the Department of Health Care Access and Information, Brunson and colleagues4 report on patterns of metastatic recurrence among adolescents and young adults with cancer and compare the risk of death between those with metastatic recurrence and those with metastatic disease at diagnosis. These data provide valuable insights into the burden of metastatic disease among adolescents and young adults with cancer and identify cancer types for which adolescents and young adults face high risk for metastatic recurrence and associated mortality. Findings largely parallel trends in metastatic recurrent disease incidence and mortality among populations with broader age ranges, with some notable exceptions.

In this analysis, Brunson and colleagues4 found that 9.2% of adolescents and young adults had metastatic disease at diagnosis and 9.5% had metastatic recurrence, with the incidence of metastatic recurrence differing by cancer type. These findings have important implications for prognosis, treatment planning, disease surveillance, and survivorship care. Despite a 5-year overall survival of 86% for cancer in adolescents and young adults, a critical unmet need remains for those who do not reach long-term survival.5 Future efforts should prioritize understanding biologic mechanisms driving metastasis, identifying novel therapeutic targets, improving monitoring of minimal residual disease, and addressing disparities in treatment access and adherence, particularly for cancers that present with metastatic disease or have a high risk for metastatic recurrence.

Notably, the 5-year cumulative incidence of metastatic recurrence was highest for adolescents and young adults with sarcoma and colorectal cancer, at 24.5% and 21.8%, respectively. Additionally, compared to having metastatic disease at diagnosis, metastatic recurrence was associated with approximately 1.5-fold increased risk for mortality among adolescents and young adults with sarcoma and colorectal cancer. Compared to other common cancer types for this age range that have seen improvements in 5-year survival across recent decades, improvements in sarcoma survival have been muted, particularly among older adolescents and young adults.5, 6 Findings from the current study demonstrate that, in addition to poor prognosis compared to other cancer types, adolescents and young adults with sarcoma face a high burden of metastatic disease at diagnosis and high incidence of metastatic recurrence associated with increased risk of mortality.

Elon Musk Holds Surprise Talk At The World Economic Forum In Davos

The musk blueprint: navigating the supersonic tsunami to hyperabundance when exponential curves multiply: understanding the triple acceleration.

On January 22, 2026, Elon Musk sat down with BlackRock CEO Larry Fink at the World Economic Forum in Davos and delivered what may be the most important articulation of humanity’s near-term trajectory since the invention of the internet.

Not because Musk said anything fundamentally new—his companies have been demonstrating this reality for years—but because he connected the dots in a way that makes the path to hyperabundance undeniable.

[Watch Elon Musk’s full WEF interview]

This is not visionary speculation.

This is engineering analysis from someone building the physical infrastructure of abundance in real-time.

Continue reading “Elon Musk Holds Surprise Talk At The World Economic Forum In Davos” | >

Biology-based brain model matches animals in learning, enables new discovery

A new computational model of the brain based closely on its biology and physiology not only learned a simple visual category learning task exactly as well as lab animals, but even enabled the discovery of counterintuitive activity by a group of neurons that researchers working with animals to perform the same task had not noticed in their data before, says a team of scientists at Dartmouth College, MIT, and the State University of New York at Stony Brook.

Notably, the model produced these achievements without ever being trained on any data from animal experiments. Instead, it was built from scratch to faithfully represent how neurons connect into circuits and then communicate electrically and chemically across broader brain regions to produce cognition and behavior. Then, when the research team asked the model to perform the same task that they had previously performed with the animals (looking at patterns of dots and deciding which of two broader categories they fit), it produced highly similar neural activity and behavioral results, acquiring the skill with almost exactly the same erratic progress.

“It’s just producing new simulated plots of brain activity that then only afterward are being compared to the lab animals. The fact that they match up as strikingly as they do is kind of shocking,” says Richard Granger, a professor of psychological and brain sciences at Dartmouth and senior author of a new study in Nature Communications that describes the model.

Neutrophil extracellular trapping network-associated biomarkers in liver fibrosis: machine learning and experimental validation

The diagnostic and therapeutic potential of neutrophil extracellular traps (NETs) in liver fibrosis (LF) has not been fully explored. We aim to screen and verify NETs-related liver fibrosis biomarkers through machine learning.

In order to obtain NETs-related differentially expressed genes (NETs-DEGs), differential analysis and WGCNA analysis were performed on the GEO dataset (GSE84044, GSE49541) and the NETs dataset. Enrichment analysis and protein interaction analysis were used to reveal the candidate genes and potential mechanisms of NETs-related liver fibrosis. Biomarkers were screened using SVM-RFE and Boruta machine learning algorithms, followed by immune infiltration analysis. A multi-stage model of fibrosis in mice was constructed, and neutrophil infiltration, NETs accumulation and NETs-related biomarkers were characterized by immunohistochemistry, immunofluorescence, flow cytometry and qPCR. Finally, the molecular regulatory network and potential drugs of biomarkers were predicted.

A total of 166 NETs-DEGs were identified. Through enrichment analysis, these genes were mainly enriched in chemokine signaling pathway and cytokine-cytokine receptor interaction pathway. Machine learning screened CCL2 as a NETs-related liver fibrosis biomarker, involved in ribosome-related processes, cell cycle regulation and allograft rejection pathways. Immune infiltration analysis showed that there were significant differences in 22 immune cell subtypes between fibrotic samples and healthy samples, including neutrophils mainly related to NETs production. The results of in vivo experiments showed that neutrophil infiltration, NETs accumulation and CCL2 level were up-regulated during fibrosis. A total of 5 miRNAs, 2 lncRNAs, 20 function-related genes and 6 potential drugs were identified based on CCL2.

Peripheral cancer attenuates amyloid pathology in Alzheimer’s disease via cystatin-c activation of TREM2

Now online! Peripheral cancer inhibits amyloid pathology and rescues cognition of Alzheimer’s disease through secretion of cystatin-c (Cyst-C), which binds amyloid oligomers and activates TREM2 in microglia and enables microglia to degrade pre-existing plaques.

Eco-Friendly Agrochemicals: Embracing Green Nanotechnology

In the pursuit of sustainable agricultural practices, researchers are increasingly turning to innovative approaches that blend technology and environmental consciousness. A recent study led by M.R. Salvadori, published in Discover Agriculture, delves into the promising world of green nanotechnology in agrochemicals. This research investigates how nanoscale materials can enhance the effectiveness of agrochemicals while minimizing their environmental footprint. The findings suggest that this novel approach may revolutionize crop protection and nutrient delivery systems.

Nanotechnology involves manipulating materials at the nanoscale, typically between 1 and 100 nanometers. At this scale, materials exhibit unique properties that differ significantly from their bulk counterparts. These properties can be harnessed to improve the delivery and efficacy of agrochemicals. For instance, nanosized fertilizers can increase the availability of nutrients to plants, enhancing growth and reducing waste. This targeted approach is essential in combating soil nutrient depletion and ensuring food security in an era of burgeoning global population.

Traditional agrochemicals often come with the burden of negative environmental impacts, including soil and water contamination. The introduction of green nanotechnology aims to address these concerns by developing more biodegradable and environmentally friendly agrochemicals. By using nanomaterials derived from natural sources, researchers hope to create a symbiotic relationship between agricultural practices and ecological health. This paradigm shift could pave the way for a new era of environmentally responsible farming.

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