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12 recordsLinked to original sources

PubMed2025

An integrated multiscale air quality modelling framework for industrial park pollution: Linking local emissions to regional transport.

Capturing the spatiotemporal distribution of pollutants in industrial parks remains challenging for regional air quality models because of their coarse resolution (3 km), resulting in uncertainties in local emission quantification. To address this, we developed the Integrated Multiscale Air Quality Modelling System for Industry (IAQMS-Industry), coupling the regional Nested Air Quality Prediction Modelling System (NAQPMS) with a city-scale chemical transport model. This framework integrates point-source locations and Gaussian plume dispersion to simulate particulate matter with a diameter smaller than 2.5 micrometres (PM2.5) at 100 m resolution. Applied to the Beijing Yi Zhuang and Tangshan industrial parks and evaluated against observations. The coupled model achieved a normalized mean bias (NMB) ranging from 3.1 % to 6.2 %, improving upon NAQPMS (-16.9 % to -7.7 %). Spatial analysis revealed that coarse regional grids underestimated the PM2.5 concentrations at industrial sites by smoothing gradients, whereas IAQMS-Industry successfully resolved spatial patterns. Industrial point emissions accounted for 22.9 %-26.4 % of PM2.5 in the coupled model, which was significantly greater than the regional model estimates of 1.6 %-13.7 %. These findings indicate that regional models overestimate pollutant dispersion processes in industrial parks while underestimating local industrial impacts. By explicitly resolving point-source dynamics and linking them to regional transport, IAQMS-Industry provides a robust tool for designing targeted emission controls in industrial cities and balancing local air quality improvements with minimized regional pollution outflow. This study underscores the necessity of multiscale modelling for accurate source apportionment and informed environmental governance in industrial zones.

Air Pollution↗

PubMed2024

Identification of a putative novel polycyclic aromatic hydrocarbon-biodegrading gene cluster in a marine Roseobacteraceae bacterium Sagittula sp. MA-2.

UNLABELLED: The ability to biodegrade polycyclic aromatic hydrocarbons (PAHs) and the catabolic enzymes responsible for PAH biotransformation in marine bacteria belonging to the family Roseobacteraceae remain largely unexplored despite their wide distribution and highly diverse physiological traits. A bacterial isolate within Roseobacteraceae originating from coastal seawater, Sagittula sp. strain MA-2, that biotransformed phenanthrene and utilized it as a growth substrate was found to possess a putative PAH-degrading gene cluster on one of the eight circular plasmids in its genome. Subsequent comprehensive investigations utilizing bacterial genomes in public databases revealed that gene clusters potentially homologous to this newly found cluster are widely but heterogeneously distributed within Roseobacteraceae and a few non-Roseobacteraceae (Paracoccaceae and Rhizobiaceae) strains from saline environments. Catabolic functions of the enzymes encoded in strain MA-2 were predicted through the profiling of phenanthrene biotransformation products by liquid chromatography-electrospray ionization high-resolution mass spectrometry and substrate docking simulations using predicted three-dimensional structures of selected proteins, and phenanthrene biodegradation pathways were proposed. Strain MA-2 appeared to biodegrade phenanthrene via two separated, concurrent pathways, namely the salicylate and phthalate pathways. This study serves as the first investigation into the functional genes potentially responsible for PAH biodegradation conserved in Roseobacteraceae bacteria, expanding scientific understanding of the physiological repertoire evolved in this ubiquitous marine bacterial group. IMPORTANCE: The ocean is often characterized as the terminal destination for persistent polycyclic aromatic hydrocarbon (PAH) environmental pollutants; however, the ability to biodegrade PAHs and the corresponding enzymes conserved among marine bacteria are less understood compared to their terrestrial counterparts. A marine bacterial isolate, Sagittula sp. strain MA-2, belonging to the family Roseobacteraceae-a widely distributed and physiologically diverse marine bacterial group-was found to possess a functional gene cluster encoding enzymes potentially responsible for PAH biodegradation in its genome and exhibit the ability to biodegrade the three-ring PAH, phenanthrene. Intriguingly, gene clusters potentially homologous to this cluster were also distributed broadly across genomes from different Roseobacteraceae genera in public databases, which has not been previously investigated. The knowledge provided here expands our understanding of the physiology of Roseobacteraceae and may be applied to explore biotechnologically useful bacteria that contribute to the remediation of polluted marine environments or high-salinity wastewater.

Multigene Family↗

PubMed2026

Mechanism of Action of Hedyotis diffusa Extract in a Rat Model of Acute Lung Injury Based on Transcriptomic Analysis.

OBJECTIVE: This study established a rat model of lipopolysaccharide (LPS)-induced acute lung injury (ALI) to evaluate pathological damage, collagen deposition, inflammatory cytokine levels, and key gene/protein expression following Hedyotis diffusa water extract (HDWE) intervention. Combined with ultra-high-performance liquid chromatography-quadrupole Orbitrap high-resolution mass spectrometry (UHPLC-Q-Orbitrap HRMS), transcriptomic analysis, and molecular simulation, this study identified the bioactive components of HDWE, evaluated their potential interactions with ALI-related targets, and explored the multi-omics-based protective mechanisms of HDWE. METHODS: Thirty-six Sprague-Dawley (SD) rats were randomly divided into six groups: Control group, ALI group, DXMS group, HDWE-L group (100 mg/kg), HDWE-M group (200 mg/kg), and HDWE-H group (300 mg/kg). Hematoxylin and eosin (H&E) and Masson's trichrome staining were used to evaluate lung pathological changes and collagen deposition. Enzyme-linked immunosorbent assay (ELISA) was used to measure serum tumor necrosis factor-α TNF-α interleukin-1β IL-1β, erleukin-6 (IL-6), and interleukin-10 (IL-10) levels. Transcriptomic analysis identified differentially expressed genes (DEGs), followed by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), receiver operating characteristic (ROC), and immune infiltration analyses. Quantitative real-time polymerase chain reaction (qRT-PCR) detected the mRNA expression levels of SPHK1, RELA, and NFKBIA. Immunohistochemistry evaluated the expression of eight hub targets, including endothelin-1 (EDN1), sphingosine kinase 1 (SPHK1), intercellular adhesion molecule 1 (ICAM1), interleukin-17 (IL-17), prostaglandin-endoperoxide synthase 2 (PTGS2/COX-2), NF-κB p65 (encoded by RELA), WT1-associated protein (WTAP), and myeloperoxidase (MPO). UHPLC-Q-Orbitrap HRMS characterized HDWE constituents. Molecular docking analysis was performed between 22 compounds and eight hub targets, followed by 100 ns molecular dynamics simulations and molecular mechanics-Poisson-Boltzmann surface area (MM/PBSA) binding free energy calculations for five core targets. Compared with the control group, the ALI group showed increased levels of TNF-α (86%), IL-1β (107%), and IL-6 (66%), accompanied by a 43% reduction in IL-10 and a 300% increase in lung collagen deposition. All HDWE doses alleviated inflammatory responses, with medium-dose HDWE showing the most pronounced effects. Specifically, medium-dose HDWE increased IL-10 levels by 52% and reduced IL-6, TNF-α, and IL-1β levels by 18%, 22%, and 11%, respectively. Transcriptomic analysis identified 2512 DEGs between the control group and ALI groups, 832 exclusive DEGs between the ALI group and HDWE-M groups, and 876 overlapping DEGs enriched in TNF, IL-17, and NF-κB signaling pathways. The eight-hub-gene diagnostic model achieved an area under the curve (AUC) of 0.969. RELA, SPHK1, and four other hub genes showed positive correlations with Th1, Th17, and neutrophil infiltration. In the ALI group, SPHK1, RELA, and NFKBIA mRNA expression levels were 1.30-, 0.96-, and 0.71-fold of those in the control group, respectively. Compared with the ALI group, high-dose HDWE treatment and low-dose HDWE treatment reduced SPHK1 expression to 0.62- and 0.57-fold, respectively, and increased NFKBIA expression to 1.68- and 1.58-fold, respectively. High-dose HDWE treatment reduced RELA expression to 0.43-fold. The expression levels of inflammation-related proteins were increased in the ALI group and were reduced after HDWE treatment. Twenty-two HDWE components were identified, 16 of which met the docking criteria. Asperulosidic acid exhibited favorable predicted binding affinities with all eight targets, with calculated binding free energies of -14.74, -14.92, -17.58, -23.04, and -16.10 kcal/mol for MPO, IL-17, NF-κB p65, PTGS2/COX-2, and SPHK1, respectively. CONCLUSIONS: This study provides systematic in vivo pharmacodynamic and in silico component-target evidence regarding the protective effects of HDWE against LPS-induced ALI. HDWE treatment increased NFKBIA expression and reduced SPHK1, RELA, and multiple inflammatory protein levels, suggesting that HDWE may regulate the IL-17/NF-κB-associated inflammatory network, although direct causal relationships require further validation. Asperulosidic acid may represent a key bioactive component with broad target-binding potential. This study was limited by the use of an LPS-induced rat ALI model without gene knockout or target inhibitor validation; therefore, further functional experiments are required to confirm the proposed regulatory mechanisms.

Hedyotis diffusa↗

PubMed2025

Doblin: inferring dominant clonal lineages from high-resolution DNA barcoding time series.

MOTIVATION: The lineage dynamics and history of cells in a population reflect the interplay of evolutionary forces they experience, including mutation, drift, and selection. When the population is polyclonal, lineage dynamics also manifest the extent of clonal competition among co-existing mutational variants. If the population exists in a community of other species, the lineage dynamics could also reflect the population's ecological interaction with the rest of the community. Recent advances in high-resolution lineage tracking via DNA barcoding, coupled with next-generation sequencing of bacteria, yeast, and mammalian cells, allow for precise quantification of clonal dynamics in these organisms. RESULTS: In this work, we introduce Doblin, an R suite for identifying dominant barcode lineages based on high-resolution lineage tracking data. We first benchmarked Doblin's accuracy using lineage data from evolutionary simulations, showing that it recovers the clones' identity and relative fitness in the simulation. Next, we applied Doblin to analyze clonal dynamics in laboratory evolutions of Escherichia coli populations undergoing antibiotic treatment and in colonization experiments of the gut microbial community. Doblin's versatility allows it to be applied to lineage time-series data across different experimental setups. AVAILABILITY AND IMPLEMENTATION: Doblin is available on CRAN (https://CRAN.R-project.org/package=doblin) and Github (https://github.com/dagagf/doblin).

DNA Barcoding, Taxonomic↗

PubMed2025

Generating three-dimensional genome structures with a variational quantum algorithm.

Chromosome conformation capture experiments have revealed the underlying spatial interactions that govern three-dimensional (3D) genome organization and topology. Detecting 3D contacts between genomic loci considerably enhances our understanding of fundamental regulatory processes. Modeling 3D structures from experimental contact matrices can further contextualize the relationship between 3D genome organization and regulation. While classical algorithms have been successful in reconstructing genomic conformations, we investigate the prospect of quantum computation to aid in modeling the conformational space. In this context, we propose a novel variational quantum algorithm (VQA) to model the distribution of 3D genomic structures from experimental contact data. Through rigorous evaluations, we demonstrate the capability of our algorithm to sample ensembles of viable 3D conformations that agree well with experimental and simulated contact data. Furthermore, we extend our methodology to model the conformational space of a single cell or a population of cells. In the advent of sufficient quantum utility, the insights gained from this study can serve as a foundation for investigating high-resolution, large-scale ensembles of genomic conformations through generative VQAs.

Algorithms↗

PubMed2026

Reconstructing the early spatial spread of pandemic respiratory viruses in the United States.

Understanding the geographic spread of emerging respiratory viruses is critical for pandemic preparedness, yet the early spatiotemporal dynamics of the 2009 H1N1 pandemic influenza and severe acute respiratory syndrome coronavirus 2 in the United States remain unclear. While mobility and genomic data have revealed important aspects of pandemic spatial spread, several key questions remain: Did the two pandemics follow similar spatial transmission routes? How rapidly did they spread across the United States? What role did stochastic processes play in early spatial transmission? To address these questions, we integrated high-resolution disease data with a robust, data-efficient inference framework combining air travel, commuting flows, and pathogen superspreading potentials to reconstruct their spatial spread across US metropolitan areas. The two pandemics exhibited distinct transmission pathways across locations; however, both pandemics established local circulation in most metropolitan areas within weeks, driven by several shared transmission hubs. Early spatial spread was more strongly associated with air travel than with commuting, though stochastic dynamics introduced substantial uncertainty in transmission routes, creating challenges for timely detection and control. Simulations indicate that broad wastewater surveillance coverage beyond top transmission hubs coupled with effective infection control may slow initial spatial expansion. Our findings highlight the rapid, stochastic spread of pandemic respiratory pathogens and the difficulties of early outbreak containment.

Humans↗

PubMed2026

Dual solvent cavities and hydrogen-bond networks define the chromophore environment in a far-red/orange-sensing cyanobacteriochrome.

Cyanobacteriochromes (CBCRs) are bilin-binding photoreceptors that exhibit remarkable spectral diversity and mediate light-dependent signaling in cyanobacteria. Far-red/orange-sensing CBCRs (froCBCRs) have attracted interest because of their unusually red-shifted absorption properties, yet structural information for their illuminated states has been lacking. Here, we report the first high-resolution (1.8 Å) crystal structure of the orange-absorbing (Po) state of the froCBCR ToFrO from Tolypothrix sp. PCC 7910. The structure reveals a compact, cyclic bilin configuration and water-mediated hydrogen-bonding networks within two solvent-accessible cavities. Within the GAF domain, the D-ring remains nearly perpendicular to the planar A-to-C ring system through interactions involving a flexible loop region. Comparative analyses of cryogenic synchrotron and room-temperature X-ray free-electron laser (XFEL) structures, together with molecular dynamics (MD) simulations, revealed alternative Met636 conformations associated with dynamic water exchange through the solvent-accessible cavity. Site-directed mutagenesis of cavity-lining and water-interacting residues resulted in modest spectral shifts. By contrast, mutations of two Trp residues, participating in π-π stacking with the D-ring and likely imposing a steric constraint near the A-ring, resulted in substantial blue and red shifts in the dark and illuminated states, respectively. Together with the observed chromophore geometry, these findings indicate that the spectral properties of ToFrO are governed by chromophore conformation and its direct interaction with surrounding residues through hydrogen-bonding, electrostatic, and π-π interactions. These results further suggest that cavity-mediated solvent organization contributes to stabilizing the local structural environment surrounding the chromophore and adjacent protein backbone. Collectively, these findings elucidate the structural basis for photoconversion and spectral tuning in froCBCRs.

Cyanobacteria↗

PubMed2025

MOADE: a multimodal autoencoder for dissociating bulk multi-omics data.

In single cell biology, the complexity of tissues may hinder lineage cell mapping or tumor microenvironment decomposition, requiring digital dissociation of bulk tissues. Many deconvolution methods focus on transcriptomic assay, not easily applicable to other omics due to ambiguous cell markers and reference-to-target difference. Here, we present MOADE, a multimodal autoencoder pipeline linking multi-dimensional features to jointly predict personalized multi-omic profiles and cellular compositions, using pseudo-bulk data constructed by internal non-transcriptomic reference and external scRNA-seq data. MOADE is evaluated through rigorous simulation experiments and real multi-omic data from multiple tissue types, outperforming nine deconvolution pipelines with superior generalizability and fidelity.

Humans↗

PubMed1979

High-resolution phosphorus nuclear magnetic resonance spectra of yeast phenylalanine transfer ribonucleic acid. Melting curves and relaxation effects.

In a continuation of our studies on structural effects on the 31P chemical shifts of nucleic acids, we present 31P NMR spectra of yeast phenylalanine tRNA in the presence and absence of Mg2+. Superconducting field (146 MHz) and 32-MHz 31P NMR spectra reveal approximately 15 nonhelical diester signals spread over approximately 7 ppm besides the downfield terminal 3'-phosphate monoester. In the presence of 10 mM Mg2+, most scattered and main cluster signals do not shift between 22--66 degrees C, thus supporting our earlier hypothesis that 31P chemical shifts are sensitive to phosphate ester torsional and bond angles. At 70 degrees C, all of the signals merge into a single random coil conformation signal. Similar effects are observed in the absence of Mg2+ except that the transition melting temperature is approximately 20 degrees C lower. Measured spin-lattice and spin-spin relaxation times reveal another lower temperature transition besides the thermal denaturation process. A number of the scattered peaks are shifted (0.2--1.7 ppm) and broadened between 22 and 66 degrees C in the presence of Mg2+ as a result of this conformational transition between two intact tertiary structures. The loss of the scattered peaks in the absence of Mg2+ occurs in the temperature range expected for melting of a tertiary structure. An attempt to simulate the 31P spectra of tRNA Phe based upon the X-ray crystallographically determined phosphate ester torsional agles supports the suggestion that the large shifts in the scattered peaks are due to bond angle distortions in the tertiary structure.

Kinetics↗

PubMed2026

Bioactive peptides for meat quality and preservation: Integrating peptidomics and computational screening.

Bioactive peptides generated from meat proteins, fermented meat products, and slaughter by-products have attracted increasing attention as functional molecules for improving meat quality and preservation. In meat systems, peptides can be produced through endogenous postmortem proteolysis, microbial fermentation, gastrointestinal digestion, or controlled enzymatic hydrolysis of underutilized animal by-products. These peptides are closely associated with key meat science endpoints, including postmortem tenderization, oxidative stability, color retention, flavor development, microbial inhibition, and the valorization of processing by-products. However, although high-resolution peptidomics has greatly expanded the identification of meat-derived peptide sequences, their translation into practical meat applications remains limited by matrix interactions, processing stability, sensory constraints, safety concerns, and insufficient validation in real meat systems. This review synthesizes recent advances in meat-related peptidomics and computational screening, including sequence-based prediction, machine learning, molecular docking, molecular dynamics, stability assessment, and safety-oriented filtering. Particular attention is given to how these approaches can prioritize peptides with antioxidant, antimicrobial, flavor-modulating, and preservation-related functions under meat-specific technological constraints. By integrating peptide generation pathways, mass spectrometry-based identification, in silico prioritization, and meat quality endpoints, this review proposes a stage-gated framework for translating meat-derived bioactive peptides from discovery to application. Future research should strengthen matrix-specific validation, standardized peptidomic reporting, and safety assessment to support the use of bioactive peptides in meat quality improvement, clean-label preservation, and circular utilization of meat industry by-products.

Animals↗

PubMed2026

How advances in chromosome conformation capture (3C) methods are reshaping our understanding of gene regulation in hematopoiesis.

The three-dimensional organization of the DNA within the nucleus plays a key role in regulating gene expression. Over the past two decades, advances in chromosome conformation capture (3C) technologies, in tandem with other methods, have shown that the genome forms a complex structure at multiple scales. Early studies identified large-scale structures such as chromosome territories, compartments and topologically associating domains (TADs). As the resolution of 3C techniques has improved, it has become possible to identify contacts between regulatory elements in detail and more recently, it has become possible to define intricate structures within cis-regulatory elements. In this chapter, we review the development of 3C-based methodologies and discuss the strengths and limitations of the different approaches. We examine how these technologies have refined our understanding of genome organization and gene regulation. Recent high-resolution studies reveal that chromatin architecture extends beyond classical domain structures to include nanoscale organization. Integration of 3C data with super-resolution imaging and molecular dynamics simulations supports a model in which genome folding is governed by the biophysical properties of chromatin.

Animals↗

PubMed2026

An automated geometric modeling framework in GATE for the design and optimization of high-sensitivity converging-beam SPECT collimators.

Objective.The trade-off between detection sensitivity and spatial resolution is a fundamental challenge in designing organ-dedicated Single-photon emission computed tomography (SPECT) collimators. While converging-hole geometries offer a solution, their optimization is often hindered by the lack of flexible computational tools capable of modeling large-scale, non-parallel hole arrays. This study aims to develop an automated geometric modeling framework to facilitate the design and evaluation of complex converging- and diverging-hole collimators within standard Monte Carlo environments.Approach.We developed a specialized modeling framework by implementing custom C++ classes and a vector-based alignment algorithm within GATE. This platform enables automated, orientation-consistent construction of large-scale converging arrays not natively supported by standard implementations. A high-sensitivity pure cone-beam collimator (CBC) was designed using this framework. The evaluation used hot-rod, disc, and Jaszczak phantoms for physical characterization, while XCAT and dedicated brain models were employed for clinical tasks, including cardiac, brain perfusion, and DaTscan SPECT simulations.Main results.The CBC achieved a nearly fourfold sensitivity increase compared to a conventional low-energy high-resolution parallel-hole collimator at a 20 cm radius of rotation, while maintaining comparable spatial resolution. Despite a 52.3% field of view reduction, the CBC yielded a 2.2-fold noise reduction (CV: 11.7% vs 25.9%) and mitigated partial volume effects via geometric magnification. XCAT and brain phantom simulations confirmed enhanced anatomical definition and contrast recovery in cardiac, perfusion, and DaTscan tasks.Significance.This work provides an efficient computational tool for rapid design space exploration of advanced collimator geometries. The results demonstrate that the proposed CBC design offers a significant sensitivity advantage, making it highly suitable for high-performance, small-volume clinical applications such as brain and cardiac molecular imaging.

Tomography, Emission-Computed, Single-Photon↗