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Category: bioengineering

Deep-learning algorithms enhance mutation detection in cancer and RNA sequencing

Researchers from the Faculty of Engineering at The University of Hong Kong (HKU) have developed two innovative deep-learning algorithms, ClairS-TO and Clair3-RNA, that significantly advance genetic mutation detection in cancer diagnostics and RNA-based genomic studies.

The pioneering research team, led by Professor Ruibang Luo from the School of Computing and Data Science, Faculty of Engineering, has unveiled two groundbreaking deep-learning algorithms—ClairS-TO and Clair3-RNA—set to revolutionize genetic analysis in both clinical and research settings.

Leveraging long-read sequencing technologies, these tools significantly improve the accuracy of detecting genetic mutations in complex samples, opening new horizons for precision medicine and genomic discovery. Both research articles have been published in Nature Communications.

A protein ‘tape recorder’ enables scientists to measure and decode cellular processes at scale and over time

Unraveling the mysteries of how biological organisms function begins with understanding the molecular interactions within and across large cell populations. A revolutionary new tool, developed at the University of Michigan, acts as a sort of tape recorder produced and maintained by the cell itself, enabling scientists to rewind back in time and view interactions on a large scale and over long periods of time.

Developed in the lab of Changyang Linghu, Ph.D., Assistant Professor of Cell and Developmental Biology and Biomedical Engineering and Principal Investigator in Michigan Neuroscience Institute, the so-called CytoTape is a flexible, thread-like intracellular protein fiber, designed with the help of AI to act as a tape recorder for large-scale measurement of cellular activities.

The research appears in the journal Nature.

Complement C5 Inhibitor Ameliorates a Case of Dysferlinopathy

Complement inhibition showed promising clinical improvement in this single case of dysferlinopathy.

Dysferlinopathy is a rare autosomal recessively inherited myopathy, presenting as several phenotypes, including a proximal weakness dominant limb-girdle muscular dystrophy R2 phenotype and a distal weakness dominant Miyoshi distal myopathy phenotype.1,2 Muscle weakness usually emerges in young adulthood, followed by a progressive motor decline over the first decade, which tends to be more rapid in individuals with earlier onset.3 Dysferlinopathy is caused by pathogenic variants of the DYSF gene that impair function of dysferlin, a protein that cooperates with others to repair membranes and restore skeletal muscle integrity after injury.4

To date, no effective treatment for dysferlinopathy has been clinically validated. Promising approaches, including exon skipping and gene editing targeting the DYSF gene, as well as myoblast transplantation, are still under investigation in preclinical models.5 Although dysferlinopathy often presents with inflammatory features on muscle pathology and is prone to misdiagnosis as myositis, it is characterized by the absence of focal MHC-I expression and complement C5b-9 deposition on nonnecrotic sarcolemma, which help distinguish it from other muscular dystrophies and inflammatory myopathies.6,7 Specially, complement C3 gene knockout in dysferlin-deficient mice has been demonstrated being able to reverse muscle pathology and improve motor function in the previous animal research.

Regenerating lost lymph nodes with bioengineered tissues

The rising incidence of cancer worldwide has led to an increasing number of surgeries that involve the removal of lymph nodes. Although these procedures play a major role in cancer staging and preventing the spread of malignancies, they sometimes come with severe long-term consequences.

Since lymph nodes do not naturally regenerate once removed, their absence can lead to a condition known as secondary lymphedema. It manifests as chronic swelling, discomfort, and reduced mobility in affected limbs or regions, severely affecting a patient’s quality of life.

A new atlas could help guide researchers studying neurological disease

Functioning brain cells need a functioning system for picking up the trash and sorting the recycling. But when the cellular sanitation machines responsible for those tasks, called lysosomes, break down or get overwhelmed, it can increase the risk of Alzheimer’s, Parkinson’s, and other neurological disorders.

“Lysosomal function is essential for brain health, and mutations in lysosomal genes are risk factors for neurodegenerative diseases,” said Monther Abu-Remaileh, a Wu Tsai Neuro affiliate and an assistant professor of chemical engineering in the Stanford School of Engineering and an assistant professor of genetics in the Stanford School of Medicine.

The trouble is, scientists aren’t sure exactly how lysosomes do their work, what’s going wrong with lysosomes that leads to neurodegeneration—or even in which cell types neurodegenerative disease begins. There might even be other lysosomal disorders yet to be discovered.

Biomimetic multimodal tactile sensing enables human-like robotic perception

Robots That Feel: A New Multimodal Touch System Closes the Gap with Human Perception.

In a major advance for robotic sensing, researchers have engineered a biomimetic tactile system that brings robots closer than ever to human-like touch. Unlike traditional tactile sensors that detect only force or pressure, this new platform integrates multiple sensing modalities into a single ultra-thin skin and combines it with large-scale AI for data interpretation.

At the heart of the system is SuperTac, a 1-millimeter-thick multimodal tactile layer inspired by the multispectral structure of pigeon vision. SuperTac compresses several physical sensing modalities — including multispectral optical imaging (from ultraviolet to mid-infrared), triboelectric contact sensing, and inertial measurements — into a compact, flexible skin. This enables simultaneous detection of force, contact position, texture, material, temperature, proximity and vibration with micrometer-level spatial precision. The sensor achieves better than 94% accuracy in classifying complex tactile features such as texture, material type, and slip dynamics.

However, the hardware alone isn’t enough: rich, multimodal tactile data need interpretation. To address this, the team developed DOVE, an 8.5-billion-parameter tactile language model that functions as a computational interpreter of touch. By learning patterns in the high-dimensional sensor outputs, DOVE provides semantic understanding of tactile interactions — a form of “touch reasoning” that goes beyond raw signal acquisition.

From a neurotech-inspired perspective, this work mirrors principles of biological somatosensation: multiple receptor types working in parallel, dense spatial encoding, and higher-order processing for perceptual meaning. Integrating rich physical sensing with model-based interpretation is akin to how the somatosensory cortex integrates mechanoreceptor inputs into coherent percepts of texture, shape and motion. Such hardware-software co-design — where advanced materials, optics, electronics and AI converge — offers a pathway toward embodied intelligence in machines that feel and interpret touch much like biological organisms do.

Biomimetic multimodal tactile sensing enables human-like robotic perception.

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APOE4 to APOE2 allelic switching in mice improves Alzheimer’s disease-related metabolic signatures, neuropathology and cognition

APOE allele switching improves Alzheimer’s in mice.

Type of apolipoprotein E (APOE) allele carried by individuals is a major risk factor in Alzheimer’s disease (AD). For example, compared to individuals carrying two copies of the APOE ε4 allele, ε2 homozygotes have an approximate 99% reduction in late-onset Alzheimer’s disease (AD) risk.

The authors in this study developed a knock-in mouse model that allows for an inducible ‘switch’ between risk and protective alleles (APOE4s2). These mice synthesize E4 at baseline and E2 after tamoxifen administration.

A whole-body allelic switch resulted in a metabolic profile resembling E2/E2 humans and drives AD-relevant alterations in the lipidome and single-cell transcriptome, particularly in astrocytes.

E4 to E2 switching improved cognition, decreased amyloid pathology, lowered gliosis and reduced plaque-associated apolipoprotein E.

Thus, APOE replacement may be a viable strategy for future gene editing approaches to simultaneously reduce multiple AD-associated pathologies. sciencenewshighlights ScienceMission https://sciencemission.com/APOE4-to-APOE2-allelic-switching

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New smart chip reduces consumption and computing time, advancing high-performance computing

A new chip aims to dramatically reduce energy consumption while accelerating the processing of large amounts of data.

A paper on this work appears in the journal Nature Electronics.

The chip was developed by a group of researchers from the Department of Electronics, Information and Bioengineering–DEIB at the Politecnico di Milano, led by Professor Daniele Ielmini, with researcher Piergiulio Mannocci as the first author.

How beige fat keeps blood pressure in check

In this report, researchers link thermogenic adipose tissue (brown/beige fat), best known for heat production, to blood-pressure control via direct fat–blood vessel communication. Using mouse models engineered to lose beige fat identity (via adipocyte-specific disruption of PRDM16), they observed elevated arterial pressure alongside perivascular remodeling, including fibrotic tissue accumulation and marked vascular hypersensitivity to the vasoconstrictor hormone angiotensin II. Mechanistically, loss of beige fat identity increased secretion of QSOX1 (quiescin sulfhydryl oxidase 1), which activated pro-fibrotic gene programs in vascular cells and promoted vessel stiffening; blocking this pathway (including genetic removal of QSOX1 in the model) restored healthier vascular signaling and function. The authors characterize this as a previously underappreciated, obesity-independent axis by which the “quality” (thermogenic vs white-like) of perivascular fat influences vascular stiffness and responsiveness to pressor signals, suggesting QSOX1 and related adipose-derived signals as potential precision targets for future antihypertensive therapies.

A mouse aorta with immunofluorescent tagging, emphasizing the close connection between vasculature and fat. (Credit: Cohen lab)

Obesity causes hypertension. Hypertension causes cardiovascular disease. And cardiovascular disease is the leading cause of death worldwide. While the link between fat and high blood pressure is clearly central to this deadly chain, its biological basis long remained unclear. What is it about fat that impacts vascular function and blood pressure control?

Now, a new study demonstrates how thermogenic beige fat—a type of adipose tissue, distinct from white fat, that helps the body burn energy—directly shapes blood pressure control. Building on clinical evidence that people with brown fat have lower odds of hypertension, the researchers created mouse models that cannot form beige fat (the thermogenic fat depot in mice that most closely resembles adult human brown fat) to watch what happens when this tissue is lost. They found that the loss of beige fat increases the sensitivity of blood vessels to one of the most important vasoconstricting hormones (angiotensin II)—and that blocking an enzyme involved in stiffening vessels and disrupting normal signaling can restore healthy vascular function in mice. These results, published in Science (opens in new window), reveal a previously unknown mechanism driving high blood pressure and point toward more precise therapies that target communication between fat and blood vessels.

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