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Congenital heart disease mutation linked to kidney damage

Biomedical engineers at Duke University have shown that a genetic mutation that causes congenital heart disease also contributes to kidney damage and developmental defects. Identifying this early cause of kidney damage could enable clinicians to diagnose and address kidney problems much sooner than current practices allow. The research was published on November 3 in the journal Nature Biomedical Engineering.

Congenital heart disease (CHD) is a common cause of death in childhood and affects 1 out of every 1,000 births. The disease occurs when the heart doesn’t form correctly before birth, causing leaky valves, defective vessels, or holes in the heart. While some cases of CHD can be remedied, children with life-threatening complications often require surgery or even a heart transplant. More than 25% of patients also end up developing problems with other organs, which severely compromise life expectancy.

“Research has shown that children diagnosed with CHD almost always have kidney problems by age 4,” said Samira Musah, the Alfred M. Hunt Faculty Scholar Assistant Professor of Biomedical Engineering and Assistant Professor of Medicine at Duke University, and the senior author of the study. “Given the shared developmental origin of the heart and kidney, I wondered if a genetic mutation tied to CHD also causes the observed in affected patients.”

Protein linked to cancer found to play key role in wound healing

When doctors detect elevated levels of SerpinB3 in a blood test, it can signal that something is seriously wrong, from hard-to-treat cancers to severe inflammatory conditions.

SerpinB3 is a that often reveals when the body’s barrier tissues, like the skin or lungs, are under serious stress from cancer or chronic illness.

But new research from Arizona State University shows that SerpinB3, long recognized as a disease marker, also has a natural role in the body: helping to heal wounds.

Silicon Valley data centers totalling nearly 100MW could ‘sit empty for years’ due to lack of power — huge installations are idle because Santa Clara can’t cope with surging electricity demands

Two major facilities built for AI-era workloads remain unpowered while the city races to expand its electricity supply.

Cybersecurity 2026: 6 Forecasts and a Blueprint for the Year Ahead

Thanks and stat safe! Chuck Brooks.

#cybersecurity #predictions2026 #AI #quantum #business #security


As we look toward 2026, the cybersecurity landscape is entering a pivotal phase of newfound technologies, evolving risks & threat actors, and shifting global dynamics.

Kakutani fixed-point theorem

In mathematical analysis, the Kakutani fixed-point theorem is a fixed-point theorem for set-valued functions. It provides sufficient conditions for a set-valued function defined on a convex, compact subset of a Euclidean space to have a fixed point, i.e. a point which is mapped to a set containing it. The Kakutani fixed point theorem is a generalization of the Brouwer fixed point theorem. The Brouwer fixed point theorem is a fundamental result in topology which proves the existence of fixed points for continuous functions defined on compact, convex subsets of Euclidean spaces. Kakutani’s theorem extends this to set-valued functions.

The Age of Sustainable Abundance Is Here!

Advancements in AI, robotics, and space exploration are driving us towards a future of sustainable abundance, enabled by innovations such as space-based solar power, humanoid robots, and scalable AI infrastructure. ## ## Questions to inspire discussion.

Terafabs and AI Chips.

🛠️ Q: What are Elon Musk’s plans for terafabs?

A: Musk plans to build terafabs with 10 lines, each producing 100k wafers/month, costing **$10–20 billion/line.

🔋 Q: What challenges do AI chips face for scaling?

A: Scaling AI faces bottlenecks in AI chips and energy, with Musk’s terafabs and solar power as key solutions.

Antibody therapy foils pancreatic cancer’s sugar-based disguise to reawaken immune system

Pancreatic cancer is notoriously hard to treat and often resists the most advanced immunotherapies. Northwestern Medicine scientists have uncovered a novel explanation for that resistance: Pancreatic tumors use a sugar-based disguise to hide from the immune system. The scientists also created an antibody therapy that blocks the sugar-mediated “don’t-attack” signal.

For the first time, the team identified how this sugar trick works and showed that blocking it with a monoclonal antibody reawakens immune cells to attack cancer cells in preclinical mouse models.

“It took our team about six years to uncover this novel mechanism, develop the right antibodies and test them,” said study senior author Mohamed Abdel-Mohsen, associate professor of medicine in the division of infectious diseases at Northwestern University Feinberg School of Medicine.

How plastics grip metals at the atomic scale: Molecular insights pave way for better transportation materials

What makes some plastics stick to metal without any glue? Osaka Metropolitan University scientists have peered into the invisible adhesive zone that forms between certain plastics and metals—one atom at a time—to uncover how chemistry and molecular structure determine whether such bonds bend or break.

Their insights clarify metal–plastic bonding mechanisms and offer guidelines for designing durable, lightweight, and more sustainable hybrid materials for use in transportation.

Combining the strength of metal with the lightness and flexibility of plastic, polymer–metal hybrid structures are emerging as key elements for building lighter, more fuel-efficient vehicles. The technology relies on bonding metals with plastics directly, without adhesives. The success of these hybrids, however, hinges on how well the two materials stick together.

New AI framework can uncover space physics equations in raw data

Artificial intelligence (AI) systems, particularly artificial neural networks, have proved to be highly promising tools for uncovering patterns in large amounts of data that would otherwise be difficult to detect. Over the past decade, AI tools have been applied in a wide range of settings and fields.

Among its many possible applications, AI systems could be used to discover physical relationships and symbolic expressions (i.e., ) describing these relationships.

To uncover these formulas, physicists currently need to extensively analyze , thus automating this process could be highly advantageous.

Triggering cell death in metastatic melanoma may pave the way for new cancer treatments

Metastatic melanoma cells that have spread to lymph nodes survive by relying on a protein called ferroptosis suppressor protein 1 (FSP1)—a surprising metabolic dependency that could open the door to a new class of cancer treatments, according to a new study led by Harvard T.H. Chan School of Public Health.

The researchers say the study, published in Nature, not only highlights the therapeutic potential of drugs that inhibit FSP1, but also offers new ways to understand cancer and its vulnerabilities.

Ferroptosis is a form of cell death driven by excessive lipid oxidation in cell membranes. When this occurs, the cell’s structural integrity collapses, leading to death. Cancer cells rely heavily on antioxidant proteins like FSP1 to prevent ferroptosis.

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