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Scratching that bug bite might feel good at first but science explains why it’s a bad idea

You’ve likely heard it since childhood: Don’t scratch that bug bite or rash, you’ll make it worse. But why would something that feels so good be bad?

A lot of things can cause itchiness, sometimes serious diseases. Whatever the cause, doctors have long warned that scratching too much can damage the skin. Now researchers better understand why even a mildly annoying itch could put you on an itch-and-scratch cycle if you give in.

How did they find out? In part by putting tiny “cones of shame” onto mice to uncover what happens on a cellular level when an itch gets scratched—or left alone.

When a pool or pond turns green with algae, don’t reach for chemicals—nature has better solutions

When the Lincoln Memorial Reflecting Pool turned green with algae just days after a US$15 million renovation, the U.S. government scrambled for chemicals and expensive technical solutions to fix the iconic landmark.

Trying to kill algae with chemicals is a common response when community ponds or other water features go green. But as a scientist who studies freshwater ecology, I can tell you there are better solutions that cost far less, last longer and carry less risk of harm to pets and wildlife.

Rather than battling against nature, these alternatives work with nature for long-term solutions.

Hospital AI tool predicts low blood sugar in patients up to 24 hours in advance

Cedars-Sinai Health Sciences University investigators developed an AI-based model that can identify hospitalized patients at risk of low blood sugar up to 24 hours before the condition occurs. The long short-term memory (LSTM) model, described in npj Digital Medicine, could help clinicians intervene earlier and prevent complications, including, in severe cases, seizures, coma and long-term heart arrhythmias.

The model addresses a longstanding challenge in hospital care. Low blood sugar, also called hypoglycemia, is a common and potentially life-threatening complication among hospitalized patients, including those receiving diabetes treatment, those who are fasting before procedures or those in critical care. However, there are no widely used tools for predicting which hospitalized patients may develop hypoglycemia.

“Today, most hospital care for hypoglycemia is reactive, and we respond after a patient’s blood sugar drops,” said Roma Gianchandani, MD, senior author of the study and vice chair of quality and innovation in the Department of Medicine and program director for diabetes.

AI can be an ally in rooting out ransomware threats

AI can be used to prevent cybersecurity threats linked to ransomware, says University of Cincinnati researcher Nelly Elsayed.

“We are in a hype era of AI,” says Elsayed, associate professor in the UC School of Information Technology. “Some people support it, others fear it, but in general people who design technology are trying to use it for good.”

Elsayed, founder and leader of the Applied Machine Learning and Intelligence Lab at UC, recently published research in the Journal of Information Security and Applications, arguing that generative AI may be an ally in strengthening ransomware defense.

The AI Future No One Wants to Talk About

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In today’s video I speculate about the future of artificial intelligence.

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Don’t forget about thrombosis in acute promyelocytic leukemia

Firstly, why examine the role of thromboembolic disease in APL when serious bleeding is essentially universal? Thromboembolic episodes are more common than may be appreciated in this setting. The 16% incidence of thromboembolic events observed by Rodriguez-Viega and co-workers is higher than the 12% found in patients with acute myeloid leukemia.5 Furthermore, the major cause of treatment failure in APL is early death and the development of clotting is associated with early death. Early death in APL occurs most frequently during the first 24–48 hours after presentation. Understandably, very few, if any, of such patients are enrolled on clinical trials. Enrollment on a trial would facilitate further insights into thromboembolic events and may pave the way for prevention and therapeutic intervention.

Secondly, why are patients with APL predisposed to develop thrombosis? After all, the disease is infamous for its life-threatening and potentially catastrophic bleeding. This prominent characteristic was recognized by Dr. Leif Hillstad, who is credited with the first description of APL as a distinct clinical entity in 1957.6 Acute promyelocytic leukemia cells are associated with the release of plasminogen activator inhibitor-1, tissue factor, and TNFα. These proteins, together with a decrease in thrombomodulin which functions as an anticoagulant by binding to thrombin, favor the balance towards thromboembolic events7 (Figure 1). Alternatively, with the generation of annexin II, plasminogen activators, and podoplanin, a transmembrane protein which interacts with cell lectin superfamily 2 (CLEC-2) on platelets to induce platelet aggregation and adhesion to lymphatic vessels,8 bleeding is much more commonly present. Furthermore, direct proteolysis of fibrinogen and von Willebrand factor contributes to bleeding. This compilation of processes explains why some patients with APL have bleeding while others have thromboembolic episodes and some have both depending on the balance of procoagulant and anticoagulant proteins. However, bleeding, usually clinically manifested by large ecchymoses on the trunk and extremities, is the major hallmark of the disease.

Finally, how can thromboembolic events in APL be prevented? The most important thing is to maintain a high level of suspicion. The report by Rodriguez-Veiga and co-workers reminds us to be vigilant for the possibility of thromboembolic events in patients with APL. The risk of thrombosis was 1.4% among low-risk patients (presenting WBC 40×109/L), 4.9% for intermediate-risk patients (WBC 10×109/L and platelet count 10×109/L). In contemporary practice, low-and intermediate-risk groups are combined since outcomes among these patients proved to be similar.

What really controls water chemistry in nanoscale spaces

Water is the most studied molecule on Earth, yet a surprisingly basic question has gone unanswered for decades: When water is squeezed into gaps just a few molecules wide—as happens inside nanoscale pores, membranes and biological channels—does it become more or less chemically reactive?

This matters because water’s most fundamental chemical property is its ability to split into two charged species, H₃O⁺ (the hydronium ion) and OH⁻ (the hydroxide ion). This reaction defines the pH, a measure of how acidic or alkaline (basic) a solution is, and underpins all of acid-base chemistry, from how enzymes work in your cells to how electrodes function in batteries.

Through this research, the scientists wanted to understand whether (and how) confining water to nanometer-scale spaces affects this behavior.

Advances in materials science are helping unlock secrets of nanomaterials

New instruments on the horizon promise the most precise tools yet to study and experiment on the smallest and most complex materials ever manufactured. In a paper published in the journal Nature Materials, University of Cincinnati assistant professor Hanxun Jin highlighted advances in ultrasensitive technology to measure and manipulate some of the tiniest nanomaterials used in manufacturing, aerospace, medicine and more.

And when Jin says tiny, he means really tiny. Semiconductor nanocrystals called quantum dots that are used in TV screens are so small they’re considered zero-dimensional. That makes the field of nanomaterials characterization a particularly exciting one, Jin said.

Defect detection automated in diamond, other advanced semiconductors

Materials scientists at Rice University have developed a new workflow methodology for measuring microscopic defects in diamond and other advanced semiconductor materials. By making it easier to spot flaws that can undermine performance, the approach could accelerate the development of more reliable electronic and quantum devices.

The research team developed a custom Python-based software tool to rapidly analyze data from high-resolution X-ray diffraction, a technique that uses X-rays to probe a material’s internal crystal structure. The software analyzes the resulting diffraction patterns, picks up on dislocations and irregularities in the atomic lattice, and calculates their density in a given material.

“Dislocations can disrupt how charge and heat move through the material, which impacts how efficient and reliable a device is and how easy it is to manufacture at scale,” said Xiang Zhang, assistant research professor of materials science and nanoengineering at Rice and a corresponding author on the study published in Advanced Materials.

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