Sepsis

Fingerprint-Based Explainable Machine Learning for Predicting Blood–Brain Barrier Permeability

Predicting blood–brain barrier (BBB) permeability is essential for early central nervous system (CNS) drug discovery, yet reliable computational screening remains challenging. This study presents a gradient-boosted ensemble framework trained on precomputed molecular fingerprints to classify compounds as BBB-permeable (BBB+) or non-permeable (BBB−). The 2048-bit fingerprints encode substructural in...

Machine Learning-assisted Raman Spectral Analysis of Serotonin-responsive ssDNA-SWCNT Nanosensor for Improved Selectivity against Dopamine

Serotonin (5-hydroxytryptamine, 5-HT) plays critical roles in neuromodulation, yet current detection methods struggle for real-time sensing of 5HT with high sensitivity and selectivity. We previously developed nIRHT (near-infrared serotonin nanosensor), which consists of ssDNA-wrapped single walled carbon nanotube that sensitively detects 5-HT. However, nIRHT’s fluorescence response cannot discrim...

DANCE: An open-source analysis pipeline and low-cost hardware to quantify aggression and courtship in Drosophila

Quantifying animal behavior is pivotal for identifying the underlying neuronal and genetic mechanisms involved. Computational approaches have enabled ...

Adaptive transcriptional strategies underpin the host-specific virulence of the generalist oomycete Phytophthora capsici during early crown infection

Phytophthora capsici is a destructive, broad-host-range oomycete responsible for substantial losses in global agriculture. While most transcriptomic s...

Multiplex mapping of protein-protein interaction interfaces

We describe peptide mapping through Split Antibiotic Resistance Complementation (SpARC-map), a method to identify the probable interface between two i...

Coenzyme A depletion causes antibiotic tolerance in Pseudomonas aeruginosa

The widespread use of antibiotics promotes both resistance and tolerance. While resistance enables bacterial growth in the presence of drugs, toleranc...

Cholinergic-dependent dopamine signals in mouse dorsal striatum are regulated by frontal but not sensory cortices

Everyday decisions depend on linking sensory stimuli with actions and outcomes. The striatum supports these sensorimotor associations through dopamine...

Integrated analysis implicates novel insights of NMB into lactate metabolism and immune response prediction in primary glioblastoma

Glioblastoma (GBM), the most aggressive primary brain tumor in adults, exhibits profound treatment resistance and poor prognosis. Despite advances in ...

From sequence to signature: Machine learning uncovers multiscale feature landscapes that predict AMR across ESKAPE pathogens

Since the clinical introduction of antibiotics in the 1940s, antimicrobial resistance (AMR) has become an increasingly dire threat to global public he...

A corticostriatal learning mechanism linking excess striatal dopamine and auditory hallucinations

Auditory hallucinations are linked to elevated striatal dopamine, but their underlying computational mechanisms have been obscured by regional heterog...

Predicting pyrazinamide resistance in Mycobacterium tuberculosis using a graph convolutional network

Pyrazinamide is an important first-line antibiotic for treating tuberculosis and resistance is primarily caused by mutations in the pncA gene. Traditi...

A Non-Intrusive Computer Vision Framework for Real-Time Vital Sign Digitization and Adaptive Drug Infusion in Critical Care Environments

This work proposes a computer vision framework to automate the extraction of vital signs from bedside monitor systems and facilitate adaptive drug inf...

Hybrid Epidemic–Neuronal Dynamics: A SEIR–FitzHugh–Nagumo Model for Information Flow in Complex Neural Networks

Information transfer in neural systems is often modeled through diffusive or synaptic mechanisms that fail to capture the contagion-like propagation o...

SLOGEN: A Structure-based Lead Optimization Model Unifying Fragment Generation and Screening

Lead optimization plays an important role in preclinical drug discovery. While deep learning has accelerated this process, structure-based approaches ...

A hardwired neural circuit for temporal difference learning

The neurotransmitter dopamine plays a major role in learning by acting as a teaching signal to update the brain’s predictions about rewards. A leading...

Leveraging Deep Learning and MD Simulations to Decipher the Molecular Basis of Attenuated Activity in Glycocin F

The escalating crisis of multi-drug resistant bacteria demand a new generation of antibiotics. Glycocin F (GccF), a potent bacteriocin, is a promising...

Integrating theory and machine learning to reveal determinants of plasmid copy number

Plasmids are extrachromosomal mobile genetic elements whose copy numbers (PCNs) critically influence microbial evolution, antibiotic resistance and pa...

Leveraging Multimodal Large Language Models to Extract Mechanistic Insights from Biomedical Visuals: A Case Study on COVID-19 and Neurodegenerative Diseases

The COVID-19 pandemic has intensified concerns about its long-term neurological impact, with growing evidence linking SARS-CoV-2 infection to neurodeg...

Benchmarking Large Language Models for Pathogen–Disease Classification in Post-Acute Infection Syndromes

Post-Acute Infection Syndromes (PAIS) are medical conditions that persist following acute infections from pathogens such as SARS-CoV-2, Epstein-Barr v...

AI-driven discovery and optimization of antimicrobial peptides from extreme environments on global scale

The escalating crisis of global antimicrobial resistance (AMR) necessitates the discovery of novel antibiotics. Antimicrobial peptides (AMPs), particu...