MetaboLINK is a novel algorithm for unveiling cell-specific metabolic pathways in longitudinal datasets.

Introduction: In the rapidly advancing field of 'omics research, there is an increasing demand for sophisticated bioinformatic tools to enable efficient and consistent data analysis. As biological datasets, particularly metabolomics, become larger and more complex, innovative strategies are essential for deciphering the intricate molecular and cellular networks.

Methods: We introduce a pioneering analytical approach that combines Principal Component Analysis (PCA) with Graphical Lasso (GLASSO).

Extracellular domain of TREM2 possess two distinct ligand recognition sites: Insights from machine-learning guided docking and all-atoms molecular dynamics simulations.

The myeloid-specific triggering receptors expressed on myeloid cells 2 (TREM2) is a group of class I receptors expressed in brain microglia plays a decisive role in neurodegenerative diseases such as Alzheimer's disease (AD) and Nasu Hakola disease (NHD). The extracellular domain (ECD) of TREM2 interacts with a wide-range of ligands, yet the molecular mechanism underlying recognition of such ligands to this class I receptor remains underexplored. Herein, we undertook a systematic investigation for exploring the mode of ligand recognition in immunoglobulin-like ectodomain by employing both knowledge-based and machine-learning guided molecular docking approach followed by the state-of-the-art all atoms molecular dynamics (MD) simulations.

Sex and gender differentials in the prevalence of obesity and its association with multimorbidity among reproductive-aged individuals in India.

Introduction: The increase in the prevalence of obesity has become a common public health issue worldwide, with low- and middle-income countries (LMICs) like India witnessing an equal rise. It makes a considerable contribution to chronic diseases as it is a major risk factor for other chronic illnesses. Multimorbidity, or the presence of two or more chronic illnesses, is becoming more common in LMICs, resulting in poor health outcomes.

Long-Term Seizure Reduction Associated with Vagal Nerve Stimulation in Dravet Syndrome.

variants cause a range of epilepsy syndromes, including Dravet syndrome, leading to early cognitive and functional impairment. Despite advances in medical management, drug-resistant epilepsy remains common. Vagal nerve stimulation (VNS) has been suggested reducing seizure frequency in these patients but there is a lack of long-term follow-up, quantitative analysis that corrected for confounding factors such as antiseizure medications (ASMs) and the impact of VNS settings on response.

Adapting to evolving MRI data: A transfer learning approach for Alzheimer's disease prediction.

Integrating 3D magnetic resonance imaging (MRI) with machine learning has shown promising results in healthcare, especially in detecting Alzheimer's Disease (AD). However, changes in MRI technologies and acquisition protocols often yield limited data, leading to potential overfitting. This study explores Transfer Learning (TL) approaches to enhance AD diagnosis using a Baseline model consisting of a 3D-Convolutional Neural Network trained on 80 3T MRI scans.