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Background: Chronic obstructive pulmonary disease (COPD) patients often show skeletal muscle dysfunction that has a prominent negative impact on prognosis. The study aims to further explore underlying mechanisms of skeletal muscle dysfunction as a characteristic systemic effect of COPD, potentially modifiable with preventive interventions (i.e. muscle training). The research analyzes network module associated pathways and evaluates the findings using independent measurements.
Methods: We characterized the transcriptionally active network modules of interacting proteins in the vastus lateralis of COPD patients (n = 15, FEV 46 ± 12% pred, age 68 ± 7 years) and healthy sedentary controls (n = 12, age 65 ± 9 years), at rest and after an 8-week endurance training program. Network modules were functionally evaluated using experimental data derived from the same study groups.
Results: At baseline, we identified four COPD specific network modules indicating abnormalities in creatinine metabolism, calcium homeostasis, oxidative stress and inflammatory responses, showing statistically significant associations with exercise capacity (VO peak, Watts peak, BODE index and blood lactate levels) (P < 0.05 each), but not with lung function (FEV). Training-induced network modules displayed marked differences between COPD and controls. Healthy subjects specific training adaptations were significantly associated with cell bioenergetics (P < 0.05) which, in turn, showed strong relationships with training-induced plasma metabolomic changes; whereas, effects of training in COPD were constrained to muscle remodeling.
Conclusion: In summary, altered muscle bioenergetics appears as the most striking finding, potentially driving other abnormal skeletal muscle responses. Trial registration The study was based on a retrospectively registered trial (May 2017), ClinicalTrials.gov identifier: NCT03169270.
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http://dx.doi.org/10.1186/s12967-018-1405-y | DOI Listing |
Plant Cell Environ
September 2025
National Engineering Laboratory for Resource Development of Endangered Crude Drugs in Northwest China, Key Laboratory of Medicinal Resources and Natural Pharmaceutical Chemistry of the Ministry of Education, College of Life Sciences, Shaanxi Normal University, Xi'an, China.
Drought stress dynamically reprograms specialised metabolism in medicinal plants. However, the transcriptional regulatory modules governing stress-adaptive metabolite synthesis remain poorly characterised. Here, we identified SbMYB8 as a drought-responsive transcription factor showing nuclear localisation and dose-dependent induction under drought in Scutellaria baicalensis.
View Article and Find Full Text PDFACS Sens
September 2025
Institute of Applied Mechanics, National Taiwan University, Taipei 106, Taiwan.
In recent AI-driven disease diagnosis, the success of models has depended mainly on extensive data sets and advanced algorithms. However, creating traditional data sets for rare or emerging diseases presents significant challenges. To address this issue, this study introduces a direct-self-attention Wasserstein generative adversarial network (DSAWGAN) designed to improve diagnostic capabilities in infectious diseases with limited data availability.
View Article and Find Full Text PDFKidney Blood Press Res
September 2025
Objective: Cisplatin-induced acute kidney injury (Cis-AKI) is a significant cause of renal damage, characterized by tubular injury, ferroptosis, and oxidative stress. While therapeutic options for Cis-AKI remain limited, identifying novel targets to prevent kidney injury is critical. This study focuses on GALNT14, a gene associated with ferroptosis, and its potential role in mitigating Cis-AKI.
View Article and Find Full Text PDFGenome Res
September 2025
College of Life Science, Sichuan Agricultural University, Ya'an, 625014, People's Republic of China;
Poultry egg production is shaped by the intertwined action of multiple physiological systems, greatly magnifying the complexity of its underlying genetic regulation. Although multitissue mapping of regulatory variants offers a powerful route to untangle this complexity, comprehensive data sets in ducks remain scarce. Meanwhile, the contributions of peripheral systems beyond neuroendocrine regulation on poultry egg production are still largely unexplored.
View Article and Find Full Text PDFMethods
September 2025
School of Computer and Information Engineering, Henan University, Kaifeng, Henan, China; Henan Key Laboratory of Big Data Analysis and Processing, Henan University, Kaifeng, Henan, China. Electronic address:
Genomic selection (GS) is a breeding technique that utilizes genomic markers to predict the genetic potential of crops and animals. This approach holds significant promise for accelerating the improvement of agronomic traits and addressing food security challenges. While traditional breeding methods based on statistical or machine learning techniques have been useful in predicting traits for some crops, they often fail to capture the complex interactions between genotypes and phenotypes.
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