bioRxiv

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Lectin Microarray-based Glycomics and Machine Learning Identify Shared Osteoarthritis Biomarkers in Humans, Dogs, and Horses

bioRxiv Jan 1, 2025
Post-traumatic osteoarthritis (PTOA) is a common sequela to joint injury in both humans and companion animal species such as horses and dogs. Despite the increasing prevalence of osteoarthritis (OA) in humans, investigation of glycosylation changes a...
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Organelle-Aware Representation Learning Enables Label-Free Detection of Mitochondrial Dysfunction in Live Human Neurons

bioRxiv Jan 1, 2025
Mitochondrial dysfunction is a convergent hallmark of neurodegenerative diseases and represents a promising biomarker for early diagnosis and therapy. However, current in vitro assays rely on fluorescence or electron microscopy, which are invasive, l...
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Universal super-resolution for subcellular fluorescence imaging

bioRxiv Jan 1, 2025
Super-resolution fluorescence microscopy has emerged as an essential instrument for investigating subcellular structures and monitoring intracellular physiology. Despite rapid advances driven by deep learning, most existing approaches are modality sp...
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A Non-Intrusive Computer Vision Framework for Real-Time Vital Sign Digitization and Adaptive Drug Infusion in Critical Care Environments

bioRxiv Jan 1, 2025
This work proposes a computer vision framework to automate the extraction of vital signs from bedside monitor systems and facilitate adaptive drug infusion in intensive care units (ICUs). This approach is intended to meet the requirement for less man...
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Extracellular space diffusion modelling identifies distinct functional advantages of archetypical glutamatergic and GABAergic synapse geometries

bioRxiv Jan 1, 2025
The brain extracellular space (ECS) is a convoluted compartment of nano- and microscale interconnected ducts. A key step in signaling between neural cells is diffusion of signaling molecules through the ECS, yet, signaling is generally considered sol...
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Non-invasive estrous cycle classification in mice using convolutional neural networks

bioRxiv Jan 1, 2025
Accurately identifying the estrous cycle phases in laboratory mice is essential for neurological research, reproductive studies, and breeding programs. Here, we introduce a non-invasive approach using Convolutional Neural Networks (CNNs) to classify ...
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Functional organization and natural scene responses across mouse visual cortical areas revealed with encoding manifolds

bioRxiv Jan 1, 2025
A challenge in sensory neuroscience is understanding how populations of neurons operate in concert to represent diverse stimuli. To meet this challenge, we have created “encoding manifolds” that reveal the overall responses of brain areas to diverse ...
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RNAtive to recognize native-like structure in a set of RNA 3D models

bioRxiv Jan 1, 2025
Most widely used methods for evaluating RNA 3D structure models require experimental reference structures, which restricts their use for novel RNAs. They also often overlook recurrent structural features shared across multiple predictions of the same...
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Global pattern of nitrogen metabolism in marine prokaryotes

bioRxiv Jan 1, 2025
The ocean nitrogen cycle is an ensemble of metabolic processes sustaining marine ecosystems and ocean productivity. However, the spatial distribution and environmental drivers of its major pathways, i.e., nitrogen fixation, denitrification, assimilat...
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A Machine Learning Model Optimized for Local Data Stratifies Patients for the Adoptive Cell Therapy with Tumor Infiltrating Lymphocytes in Bladder Tumors

bioRxiv Jan 1, 2025
Adoptive cell therapy with tumor-infiltrating lymphocytes (ACT-TILs) involves autologous TILs that are expanded ex vivo and then reinfused into the patient as a personalized form of therapy. For bladder cancer patients, there is a unique opportunity ...
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