Fibrotic microRNAs in the suppression of HSC activation and ECM deposition to facilitate the regression of hepatic fibrosis in zebrafish - Yu-Heng Lai; Mu-Kuang He; Chung-Tsui Huang; Han-Yu Tseng; Tzu-Ching Lin; Ting-Yu Yang; Semon Wu; Guor Mour Her (Journal of Molecular Medicine, 2026)
During liver injury, early pathological changes may go unnoticed, delaying the diagnosis until the disease has advanced to stages such as fibrosis, cirrhosis, or hepatocellular carcinoma. Hepatic fibrosis is a sign of long-term liver injury that leads toward permanent liver damage. It involves the buildup of too much extracellular matrix (ECM) and is activated by hepatic stellate cells (HSCs). The transforming growth factor-β1 (TGF-β1)/SMAD pathway is central to this process, which shows great potential for therapeutic strategies. Therefore, we investigated the therapeutic potential of microRNA (miRNA)-mediated regulation of fibrogenesis by using zebrafish models. A group of fibrosis-related miRNAs was identified and used to generate transgenic zebrafish lines. Fibrosis was induced via doxycycline (DOX)-controlled overexpression of TGF-β1a, and the antifibrotic efficacy of miRNAs was evaluated. Quantitative real-time PCR showed a marked downregulation of the target miRNAs, accompanied by decreased expression of fibrotic markers. Next, we confirmed that TGF-β1a, GREM1, and α-SMA protein levels were decreasing. Histological staining revealed improved liver structure and diminished collagen deposition. These findings indicate that through manipulating the miRNA expressions, we can effectively disrupt TGF-β-induced fibrogenesis, inactivate HSC, inhibit ECM remodeling, and attenuate liver fibrosis, and highlight the potential of miRNA-based therapeutic strategies for early intervention in liver disease. Key messages Establishment of an in vivo model for developing an inducible miRNA expression system in zebrafish. Predicting and evaluating targeted miRNAs that attenuate TGF-β-induced hepatic fibrosis. Elucidate the potential mechanism for fibrosis that may be a strategy for future therapies. Graphical Abstract MicroRNA-mediated modulation attenuates hepatic fibrosis by coordinately suppressing the TGF-β/SMAD signaling pathway, hepatic stellate cell activation, and extracellular matrix deposition. Protein-level validation confirms reduced phosphorylation of Smad2 and decreased expression of key fibrotic markers, including α-SMA, collagen I, and fibronectin. These findings highlight a multi-target regulatory mechanism through which miRNAs exert antifibrotic effects at the systems level.

Anaerobic Fe(II) bio-oxidation by Cyanidiophyceae to enhance As(III) removal: A novel and efficient biological material toward resilient remediation - Nhu Anh Thi Than; Liang Ching Hsu; Yu-Hsien Chen; Kamonchanok Huangmee; Chun-Chieh Wang; Heng Yi Teah; Yu-Min Tzou; Yen-Lin Cho; Yu-Ting Liu (Chemical Engineering Journal, 2025)

Prenatal exposure to air pollution and pediatric acute leukemia: A nationwide study - Hsin-Chien Yen; I-Chieh Chen; Wei-Szu Lin; Kuan-Chia Lin; Meng-Che Wu; Ching-Heng Lin (Science of The Total Environment, 2025)

Predicting ischemic stroke patients’ prognosis changes using machine learning in a nationwide stroke registry - Ching-Heng Lin; Yi-An Chen; Jiann-Shing Jeng; Yu Sun; Cheng-Yu Wei; Po-Yen Yeh; Wei-Lun Chang; Yang C. Fann; Kai-Cheng Hsu; Jiunn-Tay Lee (Medical & Biological Engineering & Computing, 2024)
Accurately predicting the prognosis of ischemic stroke patients after discharge is crucial for physicians to plan for long-term health care. Although previous studies have demonstrated that machine learning (ML) shows reasonably accurate stroke outcome predictions with limited datasets, to identify specific clinical features associated with prognosis changes after stroke that could aid physicians and patients in devising improved recovery care plans have been challenging. This study aimed to overcome these gaps by utilizing a large national stroke registry database to assess various prediction models that estimate how patients’ prognosis changes over time with associated clinical factors. To properly evaluate the best predictive approaches currently available and avoid prejudice, this study employed three different prognosis prediction models including a statistical logistic regression model, commonly used clinical-based scores, and a latest high-performance ML-based XGBoost model. The study revealed that the XGBoost model outperformed other two traditional models, achieving an AUROC of 0.929 in predicting the prognosis changes of stroke patients followed for 3 months. In addition, the XGBoost model maintained remarkably high precision even when using only selected 20 most relevant clinical features compared to full clinical datasets used in the study. These selected features closely correlated with significant changes in clinical outcomes for stroke patients and showed to be effective for predicting prognosis changes after discharge, allowing physicians to make optimal decisions regarding their patients’ recovery. Graphical Abstract

Thiol-functionalized black carbon as effective and economical materials for Cr(VI) removal: Simultaneous sorption and reduction - Kamonchanok Huangmee; Liang-Ching Hsu; Yu-Min Tzou; Yen-Lin Cho; Chih-Hao Liao; Heng Yi Teah; Yu-Ting Liu (Journal of Environmental Management, 2024)

Optimization and performance characteristics of diesel engine using green fuel blends with nanoparticles additives - Ching-Ming Lai; Dong Lin Loo; Yew Heng Teoh; Heoy Geok How; Thanh Danh Le; Huu Tho Nguyen; Ayman A. Ghfar; Farooq Sher (Fuel, 2023)

Evaluation of using comparative intradermal tuberculin test to diagnose bovine tuberculosis in dairy cattle in Taiwan - Heng-Ching Lin; Chishih Chu; Yaochi Su; Jyh-Mirn Lai (Tropical Animal Health and Production, 2022)

Spatial distribution of soil erosion and suspended sediment transport rate for Chou-Shui river basin - Chin-Ping Lin; Ching-Nuo Chen; Yu-Min Wang; Chih-Heng Tsai; Chang-Tai Tsai (Journal of Earth System Science, 2014)

Effect of the BDNF Val66Met Polymorphism on Regional Gray Matter Volumes and Cognitive Function in the Chinese Population - Mu-En Liu; Chu-Chung Huang; Mu-Hong Chen; Albert C. Yang; Pei-Chi Tu; Heng-Liang Yeh; Chen-Jee Hong; Jin-Fan Chen; Jen-Ping Hwang; Ching-Po Lin; Shih-Jen Tsai (NeuroMolecular Medicine, 2014)

Interleukin-1 beta C-511T polymorphism modulates functional connectivity of anterior midcingulate cortex in non-demented elderly Han males - Pei-Chi Tu; Tung-Ping Su; Chu-Chung Huang; Albert C. Yang; Heng-Liang Yeh; Chen-Jee Hong; Ying-Jay Liou; Mu-En Liu; Ching-Po Lin; Shih-Jen Tsai (Brain Structure and Function, 2014)

Pravastatin attenuates carboplatin-induced cardiotoxicity via inhibition of oxidative stress associated apoptosis - Ching-Feng Cheng; Shu-Hui Juan; Jin-Jer Chen; Ying-Chi Chao; His-Hsien Chen; Wei-Shiung Lian; Chun-Yi Lu; Chung-I Chang; Ted-H Chiu; Heng Lin (Apoptosis, 2008)

Inhibitory effect of resveratrol on angiotensin II-induced cardiomyocyte hypertrophy - Tzu-Hurng Cheng; Ju-Chi Liu; Heng Lin; Neng-Lang Shih; Yen-Ling Chen; Meng-Ting Huang; Paul Chan; Ching-Feng Cheng; Jin-Jer Chen (Naunyn-Schmiedeberg's Archives of Pharmacology, 2004)