A5055014462- Gut microbiota and health
- Genomics and Phylogenetic Studies
- Physics of Superconductivity and Magnetism
- Advanced Condensed Matter Physics
- Microbial Community Ecology and Physiology
- Machine Learning in Bioinformatics
- High-pressure geophysics and materials
- Advanced Chemical Sensor Technologies
- Computational Drug Discovery Methods
- Protein Structure and Dynamics
- COVID-19 Clinical Research Studies
- Metabolomics and Mass Spectrometry Studies
- Single-cell and spatial transcriptomics
- Magnetic and transport properties of perovskites and related materials
- Traditional Chinese Medicine Analysis
- Bioinformatics and Genomic Networks
- Cell Image Analysis Techniques
- COVID-19 diagnosis using AI
- Biomedical Text Mining and Ontologies
- Traditional Chinese Medicine Studies
- Atomic and Subatomic Physics Research
- Mycobacterium research and diagnosis
- Rheumatoid Arthritis Research and Therapies
- Antibiotic Resistance in Bacteria
- Helicobacter pylori-related gastroenterology studies
Guizhou Provincial People's Hospital
2025
Huazhong University of Science and Technology
2019-2024
Ministry of Education
2021
University of Illinois Urbana-Champaign
1995-1996
University of Chicago
1993-1994
Rheumatoid arthritis (RA) is a progressive disease including four stages, where gut microbiome associated with pathogenesis. We aimed to investigate stage-specific roles of microbial dysbiosis and metabolic disorders in RA.
We analyze neutron experiments on $\mathrm{Y}{\mathrm{Ba}}_{2}{\mathrm{Cu}}_{3}{\mathrm{O}}_{6+x}$ at various stoichiometries in the superconducting state, within context of a bilayer theory that yields good agreement with normal state Cu NMR and data as function $\ensuremath{\omega}$, q, $T$. A $d$-wave exhibits peaks $\mathrm{q}=(\ensuremath{\pi}, \ensuremath{\pi}, \ensuremath{\pi})$ sharp maxima twice gap frequency. This behavior may have been observed experimentally. The counterpart for...
We show that it is possible to reconcile NMR and neutron-scattering experiments on both ${\mathrm{La}}_{2\ensuremath{-}x}{\mathrm{Sr}}_{x}\mathrm{Cu}{\mathrm{O}}_{4}$ $\mathrm{Y}{\mathrm{Ba}}_{2}{\mathrm{Cu}}_{3}{\mathrm{O}}_{6+x}$, by making use of the Millis-Monien-Pines mean-field phenomenological expression for dynamic spin-spin response function, re-examining standard Shastry-Mila-Rice hyperfine Hamiltonian experiments. The recent results Aeppli et al....
Regular high-intensity exercise can cause changes in athletes' gut microbiota, and the extent nature of these may be affected by patterns. However, it is still unclear to what different types athletes have distinct microbiome profiles whether we effectively monitor an athlete's inflammatory risk based on their microbiota. To address questions, conducted a multi-cohort study 543 fecal samples from three sports: aerobics (
Abstract Microbiome-based diagnosis of cancer is an increasingly important supplement for the genomics approach in diagnosis, yet current models microbiome-based face difficulties generality: not only could be adapted from one to another, but built based on microbes tissues blood. Therefore, a model suitable broad spectrum types urgently needed. Here we have introduced DeepMicroCancer, using artificial intelligence techniques types. Built random forest it has enabled superior performances...
<p>Antibiotic resistance genes (ARGs) have emerged in pathogens and are arousing worldwide concern, accurately identifying unknown ARGs is a formidable challenge studying the generation spread of antibiotic diverse environments. Current methods can identify known but limited utility for discovery novel ARGs, thus rendering profiling incomprehensive. Here, we developed ONN4ARG, an ontology-aware deep learning approach comprehensive ARG discovery. Systematic evaluation revealed that...
We report the emergence of a square-shaped skyrmion lattice in multi-orbital $f$-electron systems with easy-axis magnetic anisotropy on centrosymmetric square lattice. By performing mean-field calculations for an effective localized model consisting two Kramers doublets, we construct low-temperature phase diagram static external field. Consequently, find that number one appears intermediate-field region when crystal field splitting between doublets is small. Furthermore, identify another...
Early and accurate identification of patients at high risk metabolic dysfunction-associated steatotic liver disease (MASLD) is critical to prevent improve prognosis potentially. We aimed develop validate an explainable prediction model based on machine learning (ML) approaches for MASLD among the adult population. The national cross-sectional study collected data from National Health Nutrition Examination Survey 2017 2020, consisting 13,436 participants, who were randomly split into 70%...
We show that the anomalous temperature T dependences at low frequencies \ensuremath{\omega} observed in neutron measurements of structure factor S(q,\ensuremath{\omega}) are compatible with a ${\mathit{d}}_{\mathit{x}}^{2}$-${\mathit{y}}^{2}$ pairing state. further demonstrate convincing verification this anisotropic also requires observation q dependence which, low-T data, differs significantly from above ${\mathit{T}}_{\mathit{c}}$. In absence such evidence, establishing existence state...
Abstract The taxonomic structure of microbial community sample is highly habitat-specific, making source tracking possible, allowing identification the niches where samples originate. However, current methods face challenges when scaled up. Here, we introduce a deep learning method based on Ontology-aware Neural Network approach, ONN4MST, for large-scale tracking. ONN4MST outperformed other with near-optimal accuracy among 125,823 from 114 niches. also has broad spectrum applications....
Microbial community classification enables identification of putative type and source the microbial community, thus facilitating a better understanding how taxonomic functional structure were developed maintained. However, previous models required trade-off between speed accuracy, faced difficulties to be customized for variety contexts, especially less studied contexts. Here, we introduced EXPERT based on transfer learning that enabled model adaptable in multiple with both high efficiency...
Abstract The gut microbial communities are highly plastic throughout life, and the human show spatial-temporal dynamic patterns at different life stages. However, underlying association between time-related factors remains unclear. lack of context-awareness, insufficient data, existence batch effect three major issues, making trajection host based on problematic. Here, we used a novel computational approach (microDELTA, microbial-based deep trajectory) to track longitudinal communities’...
Large-scale campus resembles a small "semi-open community," harboring disturbances from the exchanges of people and vehicles, wherein stressors such as temperature population density differ among ground surfaces functional partitions. Therefore, it represents special ecological niche for study on microbial ecology in process urbanization. In this study, we investigated outdoor communities four campuses Wuhan, China. We obtained 284 samples 55 sampling sites over six seasons, well their...
Abstract The taxonomical structure of microbial community sample is highly habitat-specific, making it possible for source tracking niches where samples are originated. Current methods face challenges when the number and magnitudes more than current in use, under which circumstances they unable to accurately track a timely manner, rendering them difficult knowledge discovery from sub-million heterogeneous samples. Here, we introduce deep learning method based on Ontology-aware Neural Network...
Abstract General-purpose protein structure embedding can be used for many important biology tasks, such as design, drug design and binding affinity prediction. Recent researches have shown that attention-based encoder layers are more suitable to learn high-level features. Based on this key observation, we treat low-level representation learning separately, propose a two-level general-purpose neural network, called ContactLib-ATT. On the local level, simple yet meaningful hydrogen-bond is...
Abstract Microbial secondary metabolites are usually synthesized by colocalized genes termed biosynthetic gene clusters (BGCs). A large portion of BGCs remain undiscovered in microbial genomes and metagenomes, representing a pressing challenge unlocking the full potential natural product diversity. In this work, we propose BGC-Prophet, language model based on transformer encoder that captures distant location-dependent relationships among genes, allows accurately efficiently identifies known...
Abstract Microbial source tracking quantifies the potential origin of microbial communities, facilitates better understanding how taxonomic structure and community functions were formed maintained. However, previous methods involve a tradeoff between speed accuracy, have encountered difficulty in under many context-dependent settings. Here, we present EXPERT for context-aware tracking, which adopted Transfer Learning approach to profoundly elevate expand applicability enabling biologically...
Cohort-independent robust mortality prediction model in patients with COVID-19 infection is not yet established. To build up a reliable, interpretable strong foresight, we have performed an international, bi-institutional study from China (Wuhan cohort, collected January to March) and Germany (Würzburg March September). A Random Forest-based machine learning approach was applied 1,352 the Wuhan generating based on their clinical features. The results showed that five features at admission,...
With the rapid accumulation of microbiome data around world, numerous computational bioinformatics methods have been developed for pattern mining from such paramount data. Current methods, as gene and species mining, rely heavily on sequence comparison. Most these however, a clear trade-off, particularly, when it comes to big-data analytical efficiency accuracy. Microbiome entities are usually organized in ontology structures, that considered structures could offer advantages Here, we...