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Category: biotech/medical – Page 80

In a recent study published in the journal Cell Reports, researchers used the machine learning (ML)-based Variational Animal Motion Embedding (VAME) segmentation platform to analyze behavior in Alzheimer’s disease (AD) mouse models and tested the effect of blocking fibrinogen-microglia interactions. They found that AD models showed age-dependent behavioral disruptions, including increased randomness and disrupted habituation, largely prevented by reducing neuroinflammation, with VAME outperforming traditional methods in sensitivity and specificity.

Background

Behavioral alterations, central to neurological disorders, are complex and challenging to measure accurately. Traditional task-based tests provide limited insight into disease-induced changes. However, advances in computer vision and ML tools, such as DeepLabCut, SLEAP, and VAME, now enable the segmentation of spontaneous mouse behavior into postural units (motifs) to uncover sequence and hierarchical structure, offering scalable, unbiased measures of brain dysfunction.

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The integration of quantum computing into personalized medicine holds great promise for revolutionizing disease diagnosis, treatment development, and patient outcomes. Quantum computers have the potential to process vast amounts of genetic data much faster than classical computers, enabling researchers to identify patterns and correlations that may not be apparent with current technology. This could lead to breakthroughs in understanding the genetic basis of complex diseases and developing targeted treatments.

Quantum computing also has the potential to revolutionize medical imaging by enabling the simulation of complex magnetic resonance imaging (MRI) and positron emission tomography (PET) scans. Quantum algorithms can efficiently process large-scale imaging data, enabling researchers to reconstruct high-resolution images that reveal subtle details about tissue structure and function. This has significant implications for disease diagnosis and treatment, where accurate imaging is critical for developing effective treatments.

The use of quantum computing in personalized medicine raises important ethical considerations, such as concerns about privacy and informed consent. The ability to rapidly analyze large amounts of genetic data also raises questions about how this information should be used and shared with patients. Regulatory frameworks will play a crucial role in shaping the development and deployment of quantum computing in personalized medicine, balancing the need to promote innovation with the need to protect patient safety and privacy.

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Results from a recent clinical trial led by physicians at Emory University and Grady Health System indicate that a twice-yearly injection of Lenacapavir offers a 96% reduced risk of HIV infection overall, significantly more effective than the daily oral PrEP.

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“In vivo measurement of basement membrane stiffness showed that ISCs reside in a more rigid microenvironment at the bottom of the crypt,” the article’s authors wrote. “Three-dimensional and two-dimensional organoid systems combined with bioengineered substrates and a stretching device revealed that PIEZO channels sense extracellular mechanical stimuli to modulate ISC function.”

The paper’s first author is Meryem Baghdadi, PhD, a former researcher at SickKids, and the paper’s senior authors are Tae-Hee Kim, PhD, a senior scientist at SickKids, and Danijela Vignjevic, PhD, a research director at Institut Curie. The study they led expanded on the work of one of the paper’s co-authors, Xi Huang, PhD, a senior scientist at SickKids.

In 2018, Huang found that PIEZO ion channels influence tumor stiffening in brain cancer. Inspired by this research, the collaborators in the current study set out to explore how stem cells in the intestines use PIEZO channels to stay healthy and function properly.

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“These sites act like Velcro with different colors – designed so that only strands with matching ‘colors’ (in fact, complementary DNA sequences) can connect,” said Dr. Luu.

This method allows researchers to construct customizable, highly specific architectures that can perform intricate tasks at the molecular level.

One of the most promising applications of this technology is its ability to create nanorobots capable of delivering drugs directly to targeted areas within the body.

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Evaluating the speed at which viruses spread and transmit across host populations is critical to mitigating disease outbreaks. A study published December 3 in PLOS Biology by Simon Dellicour at the University of Brussels (ULB), Belgium, and colleagues evaluate the performance of statistics measuring how viruses move across space and time in infected populations.

Genomic sequencing allows epidemiologists to examine the evolutionary history of pathogenic outbreaks and track the spatial movement of an outbreak. However, the sampling intensity of genomic sequences can potentially impact the accuracy of dispersal insights gained through these evolutionary approaches.

In order to assess the impact of the sampling size, researchers simulated the spread of several pathogens to evaluate three dispersal metrics estimated from the analysis of viral genomes: a lineage dispersal velocity (the speed at which lineages spread), a diffusion coefficient (how fast lineages invade space), and an isolation-by-distance signal (how genomic sequences of a population become less similar over geographic distance) metric.

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The Adaptive Immunity and Immunoregulation Section (AIIS) in the Laboratory of Allergic Diseases at #NIAID is seeking an exceptional candidate for a postdoctoral fellowship position.

The National Institute of Allergy and Infectious Diseases (NIAID), one of the largest institutes in the National Institutes of Health (NIH), and part of the Department of Health and Human Services (HHS), conducts and supports basic and applied research to better understand, treat, and ultimately prevent infectious, immunologic, and allergic diseases.

A postdoctoral fellowship position is available immediately in the Adaptive Immunity and Immunoregulation Section (AIIS) within the Laboratory of Allergic Diseases, NIAID. AIIS seeks highly motivated and collaborative candidates with a strong publication record who are capable of independent reasoning and excited about learning new technologies.

AIIS aims to define the cellular and molecular mechanisms controlling the balance between protective and pathogenic adaptive immune responses to allergens and pathogens. With a particular focus on memory T and B cells and T follicular helper (Tfh) cells, the lab utilizes state-of-the-art cellular and molecular approaches, including in vivo models of infection and allergy, multi-color flow cytometry, adoptive transfer experiments, cell fate tracking experiments, bone marrow chimeras, parabiosis surgery, imaging, conditional knockout and transgenic models, RNA-Seq, and single-cell technologies to characterize memory B-and T-cell responses in different models of food and respiratory allergens and infections.

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