Articles tagged with Biological Models
Comprehensive exploration of living organisms, biological systems, and life processes across all scales from molecules to ecosystems. Encompasses cutting-edge research in biology, genetics, molecular biology, ecology, biochemistry, microbiology, botany, zoology, evolutionary biology, genomics, and biotechnology. Investigates cellular mechanisms, organism development, genetic inheritance, biodiversity conservation, metabolic processes, protein synthesis, DNA sequencing, CRISPR gene editing, stem cell research, and the fundamental principles governing all forms of life on Earth.
Comprehensive medical research, clinical studies, and healthcare sciences focused on disease prevention, diagnosis, and treatment. Encompasses clinical medicine, public health, pharmacology, epidemiology, medical specialties, disease mechanisms, therapeutic interventions, healthcare innovation, precision medicine, telemedicine, medical devices, drug development, clinical trials, patient care, mental health, nutrition science, health policy, and the application of medical science to improve human health, wellbeing, and quality of life across diverse populations.
Comprehensive investigation of human society, behavior, relationships, and social structures through systematic research and analysis. Encompasses psychology, sociology, anthropology, economics, political science, linguistics, education, demography, communications, and social research methodologies. Examines human cognition, social interactions, cultural phenomena, economic systems, political institutions, language and communication, educational processes, population dynamics, and the complex social, cultural, economic, and political forces shaping human societies, communities, and civilizations throughout history and across the contemporary world.
Fundamental study of the non-living natural world, matter, energy, and physical phenomena governing the universe. Encompasses physics, chemistry, earth sciences, atmospheric sciences, oceanography, materials science, and the investigation of physical laws, chemical reactions, geological processes, climate systems, and planetary dynamics. Explores everything from subatomic particles and quantum mechanics to planetary systems and cosmic phenomena, including energy transformations, molecular interactions, elemental properties, weather patterns, tectonic activity, and the fundamental forces and principles underlying the physical nature of reality.
Practical application of scientific knowledge and engineering principles to solve real-world problems and develop innovative technologies. Encompasses all engineering disciplines, technology development, computer science, artificial intelligence, environmental sciences, agriculture, materials applications, energy systems, and industrial innovation. Bridges theoretical research with tangible solutions for infrastructure, manufacturing, computing, communications, transportation, construction, sustainable development, and emerging technologies that advance human capabilities, improve quality of life, and address societal challenges through scientific innovation and technological progress.
Study of the practice, culture, infrastructure, and social dimensions of science itself. Addresses how science is conducted, organized, communicated, and integrated into society. Encompasses research funding mechanisms, scientific publishing systems, peer review processes, academic ethics, science policy, research institutions, scientific collaboration networks, science education, career development, research programs, scientific methods, science communication, and the sociology of scientific discovery. Examines the human, institutional, and cultural aspects of scientific enterprise, knowledge production, and the translation of research into societal benefit.
Comprehensive study of the universe beyond Earth, encompassing celestial objects, cosmic phenomena, and space exploration. Includes astronomy, astrophysics, planetary science, cosmology, space physics, astrobiology, and space technology. Investigates stars, galaxies, planets, moons, asteroids, comets, black holes, nebulae, exoplanets, dark matter, dark energy, cosmic microwave background, stellar evolution, planetary formation, space weather, solar system dynamics, the search for extraterrestrial life, and humanity's efforts to explore, understand, and unlock the mysteries of the cosmos through observation, theory, and space missions.
Comprehensive examination of tools, techniques, methodologies, and approaches used across scientific disciplines to conduct research, collect data, and analyze results. Encompasses experimental procedures, analytical methods, measurement techniques, instrumentation, imaging technologies, spectroscopic methods, laboratory protocols, observational studies, statistical analysis, computational methods, data visualization, quality control, and methodological innovations. Addresses the practical techniques and theoretical frameworks enabling scientists to investigate phenomena, test hypotheses, gather evidence, ensure reproducibility, and generate reliable knowledge through systematic, rigorous investigation across all areas of scientific inquiry.
Study of abstract structures, patterns, quantities, relationships, and logical reasoning through pure and applied mathematical disciplines. Encompasses algebra, calculus, geometry, topology, number theory, analysis, discrete mathematics, mathematical logic, set theory, probability, statistics, and computational mathematics. Investigates mathematical structures, theorems, proofs, algorithms, functions, equations, and the rigorous logical frameworks underlying quantitative reasoning. Provides the foundational language and tools for all scientific fields, enabling precise description of natural phenomena, modeling of complex systems, and the development of technologies across physics, engineering, computer science, economics, and all quantitative sciences.
A study published in Science of The Total Environment found that e-cigarette exposure alters gut microbiota composition and affects neurobehavior in zebrafish. The researchers observed disruptions in the gut microbiome, with reduced microbial network stability and altered community composition, suggesting potential health risks.
Steatotic liver disease can be precisely assessed using three-dimensional ultrafast vascular ultrasound. The technology visualizes subtle microvascular changes, enabling real-time monitoring of disease progression and therapeutic response.
A machine-learning-based approach has been developed to map real-time tumor metabolism in brain cancer patients, helping doctors discover effective treatment strategies. The digital twin uses patient data to calculate metabolic flux, predicting which treatments are likely to work for individual cases of glioma.
The study created a critical framework for understanding the architecture of the genome and its association with gene function in cells. The 4DN Consortium integrated data from over a dozen techniques to compile an extensive catalogue of looping interactions between genes and regulatory elements.
A new computational model of the brain based on biology and physiology learned a simple visual category learning task as well as lab animals, discovering counterintuitive activity in neurons. The model produced naturalistic dynamics and learning without training data, enabling researchers to identify new insights into brain function an...
Early gastric cancer cells become self-sufficient by producing WNT7B, creating a self-sustaining loop and activating WNT signaling internally. This mechanism is triggered by MAPK signaling activation and has been validated in genetically engineered mouse models and human patient-derived organoids.
Researchers create powerful computational tools, sCCIgen and QuadST, to map how cells communicate in diseases like Alzheimer's and cancer. These tools provide a controlled environment to test methods for detecting cell communication, enabling the discovery of new mechanisms and therapies.
A new study found remarkable variation in how populations evolve in variable environments, with some cases benefiting from changes and others being hindered. The research has implications for understanding evolution and adapting to climate change, as well as informing AI and machine learning.
The new LimbNET platform enables direct simulation of complex biological growth processes, empowering researchers to test and compare hypotheses. The project aims to enhance collaboration, transparency, and knowledge building in the limb development community.
Recent genetic advancements have created a biodiversity library, offering untapped opportunities for solving global challenges. Researchers are exploring unconventional models, such as electric eels, octopi, and bacteria, to develop new therapeutics and tackle environmental issues.
A new AI model uses machine learning to predict drug toxicity in humans by identifying biological differences between cells, mice, and humans. The model improved predictive power over existing state-of-the-art models and demonstrated practicality in predicting market withdrawal due to toxicity.
Researchers at ETH Zurich have successfully produced muscle tissue using a new biofabrication system called G-FLight in microgravity. The process enables rapid production of viable muscle constructs with similar cell viability and muscle fibers as those printed under gravity.
Researchers from Ateneo de Manila University have identified key proteins produced by Helicobacter pylori that can trigger a strong immune response. By analyzing these proteins using immunoinformatics, the team has pinpointed potential vaccine targets to prevent stomach ulcers and cancer.
Scientists at RIKEN Center for Brain Science found that fruit flies use separate circuits to compute pleasant and unpleasant odors, challenging the idea that 'good' is the opposite of 'bad'. The discovery may contribute to a better understanding of human brain's flavor appreciation mechanisms.
Biomedical engineers at Duke University developed a platform combining automated wet lab techniques and AI to design nanoparticles for drug delivery. The TuNa-AI platform resulted in a 42.9% increase in successful nanoparticle formation compared to standard approaches.
A new model developed by University of Illinois researchers can accurately predict fluctuations in the relative abundance of tree species in a forest. The model uses genomic data and a one-time tree count to forecast changes in forest diversity, which is crucial for understanding how forests will change in the future.
A new open-source AI tool, ProRNA3D-single, has significantly increased accuracy in predicting and visualizing protein-RNA complex structures. This method can generate finely detailed images of molecules in 3D, enabling drug developers to design treatments by analyzing where viruses attach to human proteins.
Researchers developed a mathematical model that replicates the muscle movements of the esophagus during swallowing and reveals insights into esophageal motility disorders. The model includes signaling from the brain and nerves, as well as muscle contractions and relaxations, and can simulate various disorders.
The European consortium, funded by €4.5M, will recruit and train 15 PhD researchers to develop new models and methods for understanding complex biological systems. The network, coordinated by the University of Edinburgh, aims to create a framework grounded in physics that can be applied systematically.
Researchers from FAU and the Sensing Institute created a detailed computer model of the mouse brain's vasculature, simulating how brain blood vessels respond to hemodynamics and vasodynamics. The model shows that transitional vessels play a critical role in regulating flow and protecting the brain during increased activity.
Researchers at Penn State have simulated a new class of protein misfolding using atomic-scale models, revealing a type of entanglement that disrupts protein function and persists in cells. The findings support the existence of this long-lasting type of misfolding, which is thought to contribute to aging and disease.
Researchers have identified a hidden molecular mechanism involving two proteins that allows tumors to resist treatment. A new gelatin-based nanoparticle has been developed to shut down both proteins simultaneously, showing promising results in early studies with mice.
A new computational method combines 4D flow MRI, CFD, and data assimilation to estimate blood flow in brain aneurysms with greater accuracy and efficiency. The approach focuses on the aneurysm region, reducing computational cost while improving flow estimation.
Researchers at OIST introduce a mouse motion capture method using marker-based approach to track high-quality data on complex movements. The method avoids pitfalls associated with smaller animals, enabling detailed studies of neuroscientific and physiological foundations of mouse movement.
Researchers at Cold Spring Harbor Laboratory have developed a unified theory for gauge freedoms in models of biological sequences, which could revolutionize fields like plant breeding and drug development. The new approach provides efficient formulas for scientists to interpret research results with greater confidence.
Terrence Sejnowski has been elected to the Royal Society and the American Philosophical Society, a testament to his groundbreaking contributions to computational neuroscience. His pioneering work includes inventing the Boltzmann machine and NETtalk program, which revolutionized artificial neural networks and speech recognition.
Scientists at the University of Michigan have developed an improved model system to study embryo development, revealing insights into critical periods of formation. The new system allows for the prolonged culture of gastruloids, enabling researchers to visualize key processes such as mesoderm migration and gene expression.
The Mass Query Language (MassQL) tool empowers scientists to uncover previously unknown pollutants in massive chemical datasets. It has identified toxic compounds hidden in plain sight, including organophosphate esters and chemicals from breaking down over time.
The 4th Annual MPS World Summit brings together over 1,500 international experts to explore advancements in Microphysiological Systems (MPS) research. This event focuses on drug and chemical safety, disease modeling, and regulatory testing.
A new study reveals promising progress toward predicting how patients with major depressive disorder will respond to antidepressant medications. Brain connectivity patterns were found to significantly improve predictions of treatment response across two large, independent clinical trials.
Researchers at Texas Tech University Health Sciences Center have received a $1.94 million grant to study inhibitors that target peripheral neuropathic pain. The project aims to develop novel non-opioid and non-addicting therapies capable of effectively managing chronic pain.
Insilico Medicine's Pharma.AI Day 2025 will showcase the latest AI breakthroughs and updates, including precision target discovery engine PandaOmics and generative biologics platform Generative Biologics. The company aims to accelerate drug discovery and advance life sciences research with its proprietary platform.
The Vegetation Photosynthesis Model (VPM) 3.0 has been introduced, delivering a major leap in the accuracy of global gross primary production (GPP) estimates. The model enhances our understanding of terrestrial carbon dynamics and provides a powerful tool for climate change studies and ecosystem monitoring.
The researchers propose a novel defense algorithm, Wavelet-Based Adversarial Training (WBAD), to protect medical digital twins. The two-stage defense mechanism achieves 98% accuracy in breast cancer prediction, even under adversarial attacks, providing a comprehensive and effective defense against cyberattacks.
A novel approach combines large language models and quantum computing to predict Salmonella antimicrobial resistance. The SARPLLM algorithm outperforms other models in prediction accuracy.
A Lehigh University researcher is developing a new platform to enhance flu forecasting through a human judgment temporal forecast system, which aims to improve evidence-based public health decision making. The system will collect unbiased opinions and forecasts from public health experts and the general public.
Marine turtles' shells exhibit complex trade-offs between toughness, stiffness and flexibility to protect against predators while optimizing movement. The shell's design accommodates demands of both survival and efficient locomotion in aquatic habitats.
Researchers discovered that mammalian membranes have drastically different phospholipid abundances between their two leaflets, contradicting a major assumption of cell biology. The asymmetry is enabled by cholesterol's unique properties, which act as a buffer to redistribute between the leaflets and maintain robust barriers.
Researchers warn of misunderstandings in handling AI models, highlighting conditions for confidence in predictions. Explainability methods are crucial to understand algorithmic decisions, but interpreting results requires caution due to AI limitations.
Researchers have successfully reprogrammed part of the large intestine to function like the nutrient-absorbing small intestine, reversing malnutrition in a preclinical study. The technique, which deletes the colon gene SATB2, restored nutrient absorption and improved survival rates in mice with short bowel syndrome.
The conference gathered international researchers to discuss AI's role in drug discovery and development, including generative AI strategies for designing chemical compounds. The speakers emphasized the significance of personalized medicine, where therapies will be tailored to each patient's unique molecular profile.
Researchers developed a new viscoelastic model of enzymes, elucidating the intertwined effects of elastic forces and friction forces on enzyme function. This breakthrough allows proteins to be perceived as soft robots or programmable active matter, revolutionizing our understanding of enzymatic catalysis.
Researchers at Weill Cornell Medicine developed a new AI model that harnesses whole-slide tumor imaging data and gene expression analyses to predict how patients with muscle-invasive bladder cancer will respond to chemotherapy. The model outperforms previous models using a single data type, identifying key genes and tumor characteristi...
Researchers develop AI model to predict novel mutations in protein sequences, combining grammatical and semantic changes. The method uses all available information about the sequence and mutations to create a more accurate prediction model.
A study using NHANES data found that inflammation, rather than diet and exercise, has the strongest association with telomere shortening. Managing chronic inflammation may be key to preserving telomere length and promoting healthy aging.
A team of researchers from Osaka University has demonstrated that human tissue can be used to solve complex equations and process information, outperforming traditional computing methods. This breakthrough uses the concept of reservoir computing, where data is input into a complex 'reservoir' that encodes rich patterns.
A new study presents a proof-of-concept leptomeningeal neural organoid (LMNO) fusion model to study meninges-brain signaling. The co-culture system of neural organoids fused with fetal leptomeninges from mice demonstrates stability and interface characteristics.
A new model predicts how bacteria navigate obstacles to spread, informing strategies for curbing infections or designing better drug delivery. The model focuses on three surface states: uninterrupted movement, sliding along surfaces, and getting stuck in corners.
Researchers found that inhibiting the sonic hedgehog pathway restricts feather bud outgrowth and branching in chickens. Temporarily modified Shh expression resulted in proto-featherlike structures, highlighting the pathway's importance in feather development.
The Open Brain Institute launches a groundbreaking platform to simulate and study digital brains, empowering researchers to explore brain complexity and diseases. With its virtual neuroscience laboratories, the OBI enables global collaboration and access to cutting-edge virtual labs.
A study found that maternal depression can negatively influence children's executive function and lead to emotional overeating. Mothers with postpartum depression may model unhealthy coping mechanisms for their children, affecting their ability to regulate emotions and develop healthy eating habits.
A recent USF study found that strong ocean currents and wind pushed sargassum into the tropics, where it thrived in ideal growing conditions. Nutrients were supplied via vertical mixing, fueling massive blooms that end up on Caribbean beaches.
Developing heart cells use filopodia to probe and grab onto potential partners, seeking stability through energy equilibrium. The model predicts how cells match and rearrange, mirroring real embryo outcomes.
Researchers develop a 'colocatome' to study the interactions between cancer cells and their surrounding non-cancerous cells, revealing how these interactions impact tumor growth and treatment resistance. The study aims to provide insights into universal rules of tumor behavior and guide the design of more effective treatments.
A new brain-mapping technique identified memory-related brain cells vulnerable to protein buildup, a key factor in Alzheimer's disease. The study found that certain cell types in the hippocampus and cortex were more affected by tau buildup.
A comprehensive analysis of butterfly data in the US found that butterfly abundance fell by 22% between 2000 and 2020. The study, led by Eliza Grames at Binghamton University, examined data from over 12.6 million butterflies across the continental US.
The new AI model leverages hypergraphs to quickly and accurately identify therapeutic gene targets for diseases. HIT outperformed existing models in all tested metrics, demonstrating its accuracy in classifying therapeutic gene targets with great precision.
An international research team developed a user-friendly software method called Segment Anything for Microscopy, which can precisely segment images of tissues, cells, and similar structures. The new model improved performance for cell segmentation, enabling researchers to automate tasks that previously took weeks of manual effort.
Camille Bilodeau's project uses AI and molecular simulations to design peptide-covered surfaces for targeted applications, including new medicines, water desalination, and semiconductor manufacturing. Her research group aims to develop a rapid predictive tool to understand surface-water interactions of tethered peptides.
A deep learning model, CGMformer, leverages large-scale continuous glucose monitoring (CGM) data to extract individual glucose dynamics. The model captures a continuous picture of glucose fluctuations, identifying patterns that may indicate early metabolic dysfunction.