Biology subjects

Low, M.

Publications and source records attributed to Low, M..

10 recordsLinked to original sources

bioRxiv2026

pHaseMD4AI: Phase-Space Dynamics Dataset with Chemical and pH Perturbations for Physically and Kinetically Consistent Biomolecular AI

Protein function emerges from dynamic conformational ensembles and transitions that are challenging to characterize experimentally and computationally. Recent advances in generative AI have created new opportunities for learning molecular thermodynamics, kinetics, and conformational evolution directly from simulation data, but progress is limited by the availability of large-scale datasets that combine rigorous sampling, complete phase-space information, and diverse physicochemical perturbations. Here, we present pHaseMD4AI, a molecular dynamics dataset that combines a globally equilibrated peptide branch with a protein-scale constant-pH molecular dynamics (CpHMD) branch spanning hundreds of soluble proteins. The peptide branch includes a complete set of canonical tripeptide and tetrapeptide systems together with post-translationally modified (PTM) and protonation-state datasets, providing synchronized atomic coordinates (R), velocities (V), forces (F), and Markov state model-based kinetic annotations. An accompanying web portal (https://isb.zju.edu.cn/md4ai/) enables users to browse, visualize, and download trajectories, annotations, and metadata. As an example application, we demonstrate a sequence-based model that can predict residue-level equilibrium dihedral distributions from sequence. pHaseMD4AI provides a resource for developing and benchmarking molecular machine learning methods while supporting broader studies of biomolecular dynamics under sequence, post-translational modification, and protonation-state perturbations.

bioinformatics↗

bioRxiv2026

Ligand Binding Kinetics, Thermodynamics, and Gating of Insect Odorant Receptor

Insect olfactory receptors (ORs) are unique ligand-gated ion channels specialized in detecting volatile molecules. The ancestral M. hrabei MhOR5 operates independently of the Orco co-receptor and exhibits broad ligand-binding capacity, yet the molecular underpinnings of its ligand specificity and gating dynamics have long remained unclear. To resolve this knowledge gap, we applied an integrated molecular dynamics enhanced sampling approach, combining collective variable machine learning, alchemical free energy calculations, and kinetic calculations, to dissect the ligand recognition and gating mechanisms of MhOR5 in complex with two key ligands: eugenol (EOL) and DEET. Our findings reveal striking differences in the binding modes of EOL and DEET, identify dual ligand binding/release pathways (solvent-facing and membrane-facing), and pinpoint two critical molecular determinants: W158 as a central gating residue regulating ligand dissociation, and a proline-disrupted S4 helix that modulates ligand specificity via water-mediated hydrogen bonding with DEET. Thermodynamic and kinetic calculations further demonstrate that DEET binds MhOR5 substantially more stably (-11.2 kcal/mol vs. -8.4 kcal/mol for EOL) and associates marginally faster, while EOL dissociates two to three orders of magnitude more rapidly. Collectively, these findings elucidate the atomic-level mechanisms of MhOR5's ligand recognition and gating, providing a foundational framework for understanding insect OR function.

biophysics↗

bioRxiv2024

The wide spectrum anti-inflammatory activity of andrographolide in comparison to NSAIDs: a promising therapeutic compound against the cytokine storm

The challenges of the COVID-19 pandemic have highlighted an increasing clinical demand for safe and effective treatment options against an overzealous immune defence response, also known as the "cytokine storm". Andrographolide is a naturally derived bioactive compound with promising anti-inflammatory activity in many clinical studies. However, its cytokine-inhibiting activity, in direct comparison to commonly used nonsteroidal anti-inflammatory drugs (NSAIDs), has not been extensively investigated in existing literature. The anti-inflammatory activities of andrographolide and common NSAIDs, such as diclofenac, aspirin, paracetamol and ibuprofen were measured on lipopolysaccharide (LPS) and interferon-{gamma} induced RAW264.7 cells. The levels of PGE2, nitric oxide (NO), TNF- & LPS-induced release of pro-inflammatory cytokines on differentiated human macrophage THP-1 cells were measured against increasing concentrations of andrographolide and aforementioned NSAIDs. The associated mechanistic pathway was examined on NF{kappa}B using flow cytometry on the human endothelial-leukocyte adhesion molecule (ELAM9) (E-selectin) transfected RAW264.7 cells with green fluorescent protein (GFP). Andrographolide exhibited broad and potent anti-inflammatory and cytokine-inhibiting activity in both cell lines by inhibiting the release of IL-6, TNF- and IFN-{gamma}, which are known to play a key role in the etiology of cytokine storm and the pathogenesis of inflammation. In comparison, the tested NSAIDs demonstrated weak or no activity against proinflammatory mediators except for PGE2, where the activity of andrographolide (IC50 = 8.8 {micro}M, 95% CI= 7.4 to 10.4 {micro}M) was comparable to that of paracetamol (IC50 = 7.73 {micro}M, 95% CI = 6.14 to 9.73 {micro}M). The anti-inflammatory action of andrographolide was associated with its potent downregulation of NF{kappa}B. The wide-spectrum anti-inflammatory activity of andrographolide demonstrates its therapeutic potential against cytokine storms as an alternative to NSAIDs.

pharmacology and toxicology↗

bioRxiv2023

Soil seed bank richness, abundance and density across spatial scales and global biomes

Soil seed banks are an important component of plant population and community dynamics, buffering temporal heterogeneity and allowing populations to recover following disturbance. At the same time, patterns in soil seed banks are likely to reflect scale-dependent patterns in above-ground vegetation, patterns that differ strongly across world regions. Here, we investigate components of diversity in the soil seed bank across global biomes and ecosystems. We found that patterns of species richness in the soil seed bank diverged from patterns of seed density, although there were high levels of uncertainty, especially at smaller spatial scales. Importantly, habitat degradation consistently led to lower richness, potentially limiting future ecosystem recovery. Among ecosystems, mediterranean and tropical regions had high species richness, but seed density m-2 in the soil was highest in wetlands and arable systems. Lower seed densities were found in both high-diversity tropical biomes that are characterised by short-lived seeds, and low-diversity boreal and tundra biomes with more stable established vegetation. Our findings of divergences between species richness and seed density across global biomes, and how they are impacted by habitat degradation, give valuable insights to the understanding of plant biodiversity worldwide.

ecology↗

bioRxiv2022

Mesenchymal Progenitors set the homeostatic inflammatory milieu via the TAK1-NFkB axis.

The ability of mesenchymal stromal cells to modulate inflammation is at the basis of the ongoing interest in their therapeutic potential. Yet, reliable success in clinical trials is limited, possibly due to a limited understanding of their impact on the inflammatory milieu in physiological conditions. Here we show that, at steady state, mesenchymal progenitors regulate the balance between type 1 and type 2 inflammatory milieus by acting on innate immune cells through the TAK1-NFkB pathway. Suppressing the constitutive activity of this pathway in MPs leads to skewing of the immune system toward systemic Type 2 inflammation (Th2). These changes have significant effects on diseases with an important inflammatory component, leading to a worsening of disease in a preclinical model of Th2-dependent Asthma, and a reduction of symptoms associated with Th1/Th17-dependent experimental autoimmune encephalitis.

cell biology↗

bioRxiv2021

Targeting fibrosis in the Duchenne Muscular Dystrophy mice model: an uphill battle

AimFibrosis is the most common complication from chronic diseases, and yet no therapy capable of mitigating its effects is available. Our goal is to unveil specific signallings regulating the fibrogenic process and to identify potential small molecule candidates that block fibrogenic differentiation of fibro/adipogenic progenitors. MethodWe performed a large-scale drug screen using muscle-resident fibro/adipogenic progenitors from a mouse model expressing EGFP under the Collagen1a1 promotor. We first confirmed that the EGFP was expressed in response to TGF{beta}1 stimulation in vitro. Then we treated cells with TGF{beta}1 alone or with drugs from two libraries of known compounds. The drugs ability to block the fibrogenic differentiation was quantified by imaging and flow cytometry. From a two-rounds screening, positive hits were tested in vivo in the mice model for the Duchenne muscular dystrophy (mdx mice). The histopathology of the muscles was assessed with picrosirius red (fibrosis) and laminin staining (myofiber size). Key findingsFrom the in vitro drug screening, we identified 21 drugs and tested 3 in vivo on the mdx mice. None of the three drugs significantly improved muscle histopathology. SignificanceThe in vitro drug screen identified various efficient compounds, none of them strongly inhibited fibrosis in skeletal muscle of mdx mice. To explain these observations, we hypothesize that in Duchenne Muscular Dystrophy, in which fibrosis is a secondary event due to chronic degeneration and inflammation, the drugs tested could have adverse effect on regeneration or inflammation, balancing off any positive effects and leading to the absence of significant results.

cell biology↗

bioRxiv2020

Applying Machine Learning to Increase Efficiency and Accuracy of Meta-Analytic Review

The rapidly burgeoning quantity and complexity of publications makes curating and synthesizing information for meta-analyses ever more challenging. Meta-analyses require manual review of abstracts for study inclusion, which is time consuming, and variation among reviewer interpretation of inclusion/exclusion criteria for selecting a paper to be included in a review can impact a studys outcome. To address these challenges in efficiency and accuracy, we propose and evaluate a machine learning approach to capture the definition of inclusion/exclusion criteria using a machine learning model to automate the selection process. We trained machine learning models on a manually reviewed dataset from a meta-analysis of resilience factors influencing psychopathology development. Then, the trained models were applied to an oncology dataset and evaluated for efficiency and accuracy against trained human reviewers. The results suggest that machine learning models can be used to automate the paper selection process and reduce the abstract review time while maintaining accuracy comparable to trained human reviewers. We propose a novel approach which uses model confidence to propose a subset of abstracts for manual review, thereby increasing the accuracy of the automated review while reducing the total number of abstracts requiring manual review. Furthermore, we delineate how leveraging these models more broadly may facilitate the sharing and synthesis of research expertise across disciplines.

neuroscience↗

bioRxiv2019

Population-scale prediabetic assessment using HbA1c from menstrual blood

CDC-recommended diabetes prevention programs aim to detect and reverse disease in the one-third of Americans with prediabetes, but high-compliance serial assessment of percent hemoglobin A1c (HbA1c) remains a barrier to delivering this vision at population scale. Venous phlebotomy is challenging for busy or resource-constrained patients.\n\nIn this paper, we introduce the first-ever quantitative diagnostic test based on menstrual fluid, which allows HbA1c quantification from self-collected mailed tampons.We demonstrate that menstrual HbA1c is comparable to venous HbA1c in the diagnosis of prediabetes with the standard threshold of 5.7. We also demonstrate accuracy, precision, stability, and interference testing. Finally, surveying subjects reveals strong preference for menstrual HbA1c in quarterly testing. These findings suggest that menstrual HbA1c can be a key tool in addressing prediabetes at population scale.

pathology↗

bioRxiv2019

Pathogenic potential of Hic1 expressing cardiac stromal progenitors

The cardiac stroma contains multipotent mesenchymal progenitors. However, lineage relationships within cardiac stromal cells are still poorly understood. Here, we identify heart-resident PDGFRa+ Sca-1+ cells as cardiac Fibro/Adipogenic Progenitors (cFAPs) and show that they respond to ischemic damage by generating fibrogenic cells. Pharmacological blockade of this differentiation step with an anti-fibrotic tyrosine kinase inhibitor decreases post-myocardial infarction (MI) remodeling and leads to improvements in heart function. In the undamaged heart, activation of cFAPs through lineage-specific deletion of the quiescence factor Hic1 reveals additional pathogenic potential, causing fibro-fatty infiltration of the myocardium and driving major pathological features of Arrhythmogenic Cardiomyopathy (AC). HighlightsO_LIA subpopulation of PDGFRa+, Sca-1+ cells, previously considered to be a sub-type of cardiac fibroblasts, are multipotent mesenchymal progenitors, C_LIO_LICardiac damage triggers the differentiation of PDGFRa+ Sca-1+ cells into Sca-1- cells expressing a fibrogenic transcriptional programme, C_LIO_LIBlockade of the cFAP-to-fibroblast transition by Nilotinib ameliorated cardiac dysfunction post-MI and modulated cardiac remodelling. C_LIO_LIStudies performed on a model of experimentally-induced AC confirmed that cFAPs are a source of both cardiac fibroblasts and adipocytes in vivo. C_LIO_LIConversely, in the undamaged heart, activation of cFAPs by means of lineage-specific deletion of transcription factor Hic1, resulted in fibro/fatty cardiac degeneration and pathological alterations reminiscent of AC. Collectively, our findings show that a proportion of what are commonly termed "fibroblasts" are actually multipotent mesenchymal progenitors that contribute to different forms of cardiac degeneration depending on the damage setting. C_LI

cell biology↗

bioRxiv2018

NKX2.1 is critical for melanocortin neuron identity, hypothalamic Pomc expression and body weight

Food intake is tightly regulated by a group of neurons present in the mediobasal hypothalamus which activate satiety by releasing Pomc-encoded melanocortins. Although the relevance of hypothalamic POMC neurons in the regulation of energy balance and body weight is well appreciated, little is known about the transcription factors that establish their cellular fate, terminal differentiation and phenotypic maintenance. Here, we report that the transcription factor Nkx2.1 activates hypothalamic Pomc expression from early development to adulthood by binding to conserved canonical NKX motifs present in the neuronal Pomc enhancers nPE1 and nPE2. Transgenic and mutant mouse studies showed that the NKX motifs present in nPE1 and nPE2 are essential for their transcriptional enhancer activity. Early inactivation of Nkx2.1 in the ventral hypothalamus prevented the onset of Pomc expression and selective Nkx2.1 ablation from POMC neurons impaired Pomc expression and increased body weight and adiposity. These results demonstrate that NKX2.1 is critical in the early establishment of arcuate melanocortin neurons and the regulation of Pomc expression and body weight in adulthood.

genetics↗