RDscan: Extracting RNA-disease relationship from literature Using pre-training model DOI Creative Commons
Yang Zhang, Yu Yang, Liping Ren

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: Feb. 9, 2024

Abstract With the rapid advancements in molecular biology and genomics, a multitude of connections between RNA diseases has been unveiled, making efficient accurate extraction RNA-disease relationships (RD relationships) from extensive biomedical literature crucial for advancing research this field. This study introduces RDscan, novel text mining method developed based on pre-training fine-tuning strategy, aimed at automatically extracting RD-related information vast corpus using pre-trained large language models. Initially, we constructed dedicated RD corpus, comprising 2,082 positive 2,000 negative statements, alongside an independent test dataset training evaluating RDscan. Subsequently, by Bioformer BioBERT models, RDscan demonstrated exceptional performance classification named entity recognition (NER) tasks. In 5-fold cross-validation, significantly outperformed traditional machine learning methods. summary, represents first tool specifically designed relationship extraction, is freely available https://github.com/ZhangCellab/RDScaning.

Language: Английский

A First Computational Frame for Recognizing Heparin-Binding Protein DOI Creative Commons
Wen Zhu, Shi-Shi Yuan, Jian Li

et al.

Diagnostics, Journal Year: 2023, Volume and Issue: 13(14), P. 2465 - 2465

Published: July 24, 2023

Heparin-binding protein (HBP) is a cationic antibacterial derived from multinuclear neutrophils and an important biomarker of infectious diseases. The correct identification HBP great significance to the study This work provides first recognition framework based on machine learning accurately identify HBP. By using four sequence descriptors, non-HBP samples were represented by discrete numbers. inputting these features into support vector (SVM) random forest (RF) algorithm comparing prediction performances methods training data independent test data, it found that SVM-based classifier has greatest potential model could produce auROC 0.981 ± 0.028 10-fold cross-validation overall accuracy 95.0% data. As for recognition, will provide some help diseases stimulate further research in related fields.

Language: Английский

Citations

71
Cm-siRPred: Predicting chemically modified siRNA efficiency based on multi-view learning strategy DOI
Tianyuan Liu, Junyang Huang, Hongmei Luo

et al.

International Journal of Biological Macromolecules, Journal Year: 2024, Volume and Issue: 264, P. 130638 - 130638

Published: March 7, 2024

Language: Английский

Citations

18
Applications of single‑cell omics and spatial transcriptomics technologies in gastric cancer (Review) DOI Open Access
Liping Ren,

Danni Huang,

Hongjiang Liu

et al.

Oncology Letters, Journal Year: 2024, Volume and Issue: 27(4)

Published: Feb. 14, 2024

Gastric cancer (GC) is a prominent contributor to global cancer‑related mortalities, and deeper understanding of its molecular characteristics tumor heterogeneity required. Single‑cell omics spatial transcriptomics (ST) technologies have revolutionized research by enabling the exploration cellular landscapes at single‑cell level. In present review, an overview advancements in ST their applications GC provided. Firstly, multiple methods are discussed, highlighting ability offer unique insights into gene expression, genetic alterations, epigenomic modifications, protein expression patterns location tissues. Furthermore, summary provided key findings from previous on used GC, which valuable diagnosis prognosis, microenvironment analysis, treatment response. summary, application has revealed levels holds promise for improving diagnostics, personalized treatments patient outcomes GC.

Language: Английский

Citations

11
ACVPred: Enhanced prediction of anti-coronavirus peptides by transfer learning combined with data augmentation DOI

Yi Xu,

Tianyuan Liu, Yu Yang

et al.

Future Generation Computer Systems, Journal Year: 2024, Volume and Issue: 160, P. 305 - 315

Published: June 7, 2024

Language: Английский

Citations

9
Role of oxidative stress in the concurrent development of osteoporosis and tendinopathy: Emerging challenges and prospects for treatment modalities DOI Creative Commons

Xianting Xia,

Zhengyuan Fang,

Yinhua Qian

et al.

Journal of Cellular and Molecular Medicine, Journal Year: 2024, Volume and Issue: 28(13)

Published: July 1, 2024

Both osteoporosis and tendinopathy are widely prevalent disorders, encountered in diverse medical contexts. Whilst each condition has distinct pathophysiological characteristics, they share several risk factors underlying causes. Notably, oxidative stress emerges as a crucial intersecting factor, playing pivotal role the onset progression of both diseases. This imbalance arises from dysregulation generating neutralising reactive oxygen species (ROS), leading to an abnormal environment. Elevated levels ROS can induce multiple cellular disruptions, such cytotoxicity, apoptosis activation reduced cell function, contributing tissue deterioration weakening structural integrity bones tendons. Antioxidants substances that prevent or slow down oxidation process, including Vitamin C, melatonin, resveratrol, anthocyanins so on, demonstrating potential treating these overlapping disorders. comprehensive review aims elucidate complex within interlinked pathways comorbid conditions. By integrating contemporary research empirical findings, our objective is outline new conceptual models innovative treatment strategies for effectively managing underscores importance further in-depth validate efficacy antioxidants traditional Chinese medicine plans, well explore targeted interventions focused on promising areas future advancements.

Language: Английский

Citations

8
Policy research on role of traditional medicine in emergency health system construction based on the PMC index model: evidence from China DOI Creative Commons
Yujing Zhang, Tian Xia, Chen Zhao

et al.

BMC Complementary Medicine and Therapies, Journal Year: 2025, Volume and Issue: 25(1)

Published: Jan. 8, 2025

Abstract Background The integration of traditional Chinese medicine (TCM) into emergency health systems in China serves as a model for global policy development and refining the inclusion emergencies. Methods This study investigated 13 public policies related to TCM released by central government from 2003–2023. A PMC(Policy Modeling Consistency) index was developed combining ROSTCM text mining analysis software. contents these documents were quantitatively assessed using 10 first- 40 s-level indicators. Results content results showed that current focus on treatment, State Administration Traditional Medicine is issuing authority main policies, most which are issued form notice. scoring two, five, three, three rated excellent, good, qualified, unqualified, respectively. indicates quality use response normally distributed generally although room further improvement exists; should follow principles science, reasonableness, operability, be updated timely manner with continuous governance period while focusing content, safeguards, role measures. Conclusion Effective backed state institutions vital. includes enforcing relevant laws regulations, establishing multidisciplinary medical teams, developing integrated strategies support clinical research maximize unique benefits medicine.

Language: Английский

Citations

1
TCM2COVID: A resource of anti‐COVID‐19 traditional Chinese medicine with effects and mechanisms DOI
Liping Ren, Yi Xu, Lin Ning

et al.

iMeta, Journal Year: 2022, Volume and Issue: 1(4)

Published: Aug. 5, 2022

In China, traditional Chinese medicine (TCM) has been widely used for coronavirus infectious disease 2019 (COVID-19) prevention, treatment, and recovery played a part in the battle against disease. A variety of TCM treatments have recommended different stages COVID-19. But, to best our knowledge, comprehensive database storing organizing anti-COVID is still lacking. Herein, we developed TCM2COVID, manually curated resource formulas, natural products (NPs), herbs. The current version TCM2COVID (1) documents over 280 formulas (including 300 herbs) with detailed clinical evidence therapeutic mechanism information; (2) records 80 NPs potential mechanisms; (3) launches useful web server querying, analyzing visualizing documented similar those supplied by user (formula similarity analysis). summary, TCM2COVD provides user-friendly practical platform documenting, browsing treatments, will help development elucidation mechanisms action new therapies support fight COVID-19 epidemic. freely available at http://zhangy-lab.cn/tcm2covid/.

Language: Английский

Citations

29
CFNCM: Collaborative filtering neighborhood-based model for predicting miRNA-disease associations DOI
Biffon Manyura Momanyi, Hasan Zulfiqar,

Bakanina Kissanga Grace-Mercure

et al.

Computers in Biology and Medicine, Journal Year: 2023, Volume and Issue: 163, P. 107165 - 107165

Published: June 9, 2023

Language: Английский

Citations

9
Research on Bitter Peptides in the Field of Bioinformatics: A Comprehensive Review DOI Open Access

Shanghua Liu,

Tianyu Shi,

Junwen Yu

et al.

International Journal of Molecular Sciences, Journal Year: 2024, Volume and Issue: 25(18), P. 9844 - 9844

Published: Sept. 12, 2024

Bitter peptides are small molecular produced by the hydrolysis of proteins under acidic, alkaline, or enzymatic conditions. These can enhance food flavor and offer various health benefits, with attributes such as antihypertensive, antidiabetic, antioxidant, antibacterial, immune-regulating properties. They show significant potential in development functional foods prevention treatment diseases. This review introduces diverse sources bitter discusses mechanisms bitterness generation their physiological functions taste system. Additionally, it emphasizes application bioinformatics peptide research, including establishment improvement databases, use quantitative structure–activity relationship (QSAR) models to predict thresholds, latest advancements classification prediction built using machine learning deep algorithms for identification. Future research directions include enhancing diversifying models, applying generative advance towards deepening discovering more practical applications.

Language: Английский

Citations

3
Microbial carbon oxidation in seawater below the hypoxic threshold DOI Creative Commons
Sarah Wolf,

Clare Jayawickrama,

Craig A. Carlson

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Jan. 22, 2025

Global oxygen minimum zones (OMZs) often reach hypoxia but seldom anoxia. Recently it was reported that Michaelis Menten constants (Km) of oxidative enzymes are orders magnitude higher than respiratory Km values, and in the Hypoxic Barrier Hypothesis proposed that, ecosystems experiencing falling oxygen, oxygenase enzyme activities become oxygen-limited long before respiration. We conducted a mesocosm experiment with phytoplankton bloom as an organic carbon source controlled dissolved (DO) concentrations dark to determine whether slows oxidation decline. Total utilization (TOU) hypoxic treatment (ca. 7.1 µM O2) 21.7% lower oxic 245.1 over first 43 days experiment. In addition, following restoration fully conditions treatment, TOU accelerated, demonstrating processes sensitive DO found large volumes ocean. Microbial amplicon-based community composition diverged between treatments, indicating specialized microbiome included Thioglobaceae (SUP05 Gammaproteobacteria), OM190 (Planctomycetota), ABY1 (Patescibacteria), SAR86 subclade D2472, thrived while genus Candidatus Actinomarina SAR11 alphaproteobacteria were sharply inhibited. Our findings support hypothesis kinetics might slow progression ocean deoxygenation oxygen-poor regions be factor evolution microbial taxa adapted environments.

Language: Английский

Citations

0