Thermal dynamics of an intermittent subtropical stream controlled by surface water-groundwater interactions: evidence from distributed temperature sensing and heat-budget modeling - Yen-Wei Pan; Yu-Cheng Chen; Tsung-Yu Lee; Yung-Chia Chiu; Shao-Yu Hsu; Che-Ming Chen (Environmental Monitoring and Assessment, 2026)

Doxorubicin-Induced Cardiotoxicity in Breast Cancer: Mechanistic Pathways, Pharmacogenomic Modifiers, and Translational Strategies - Chi-Tong Kuok; Hao-Wei Lee; Chen-Yu Huang; Yu-Che Cheng; Shih-Chang Lin; Jiun-Wen Guo (Cardiovascular Toxicology, 2026)

Exosome Purification Strategy Influences the Regenerative Efficacy of Dental Pulp Stem Cell-Derived Exosomes in Bone Regeneration - Borae Lee; Chia-Yi Hung; Yu-Ting Chien; Chi-Che Hsieh; Wei-Hao Cheng; Ya-Hui Chan; Pin-Chuang Lai; Sheng-Wei Feng (Stem Cell Reviews and Reports, 2026)

Spatiotemporal dynamics of histone H3K27 demethylase during development - Yu-Chen Tsai; Yun-Chen Chung; Cheng-Chan Yang; Cheng-Hsien Lee; Che-Wei Liu; Shih-Ming Huang; Lan-Hsin Wang (Insect Biochemistry and Molecular Biology, 2025)

The significance of organophosphate flame retardants in patients with esophageal squamous cell carcinoma - Hung-I Lu; Wan-Ting Huang; Wen-Chin Lee; Fu-Jen Cheng; Chia-Te Kung; Chin-Chou Wang; Liang-Jen Wang; Yu-Che Ou; Shau-Hsuan Li (Environmental Geochemistry and Health, 2025)

Using Gaussian Mixture Model Clustering for the Automated Segmentation of Cerebral Arteriovenous Malformations in Magnetic Resonance Images - Ting-Yu Lin; Cheng‑Chia Lee; Yu-Wei Chen; Hsiu-Mei Wu; Ching-Jen Chen; Huai-Che Yang; Syu-Jyun Peng (Journal of Medical and Biological Engineering, 2025)

Performance of Convolutional Neural Network Models in Meningioma Segmentation in Magnetic Resonance Imaging: A Systematic Review and Meta-Analysis - Ting-Wei Wang; Jia-Sheng Hong; Wei-Kai Lee; Yi-Hui Lin; Huai-Che Yang; Cheng-Chia Lee; Hung-Chieh Chen; Hsiu-Mei Wu; Weir Chiang You; Yu-Te Wu (Neuroinformatics, 2024)
Background Meningioma, the most common primary brain tumor, presents significant challenges in MRI-based diagnosis and treatment planning due to its diverse manifestations. Convolutional Neural Networks (CNNs) have shown promise in improving the accuracy and efficiency of meningioma segmentation from MRI scans. This systematic review and meta-analysis assess the effectiveness of CNN models in segmenting meningioma using MRI. Methods Following the PRISMA guidelines, we searched PubMed, Embase, and Web of Science from their inception to December 20, 2023, to identify studies that used CNN models for meningioma segmentation in MRI. Methodological quality of the included studies was assessed using the CLAIM and QUADAS-2 tools. The primary variable was segmentation accuracy, which was evaluated using the Sørensen–Dice coefficient. Meta-analysis, subgroup analysis, and meta-regression were performed to investigate the effects of MRI sequence, CNN architecture, and training dataset size on model performance. Results Nine studies, comprising 4,828 patients, were included in the analysis. The pooled Dice score across all studies was 89% (95% CI: 87–90%). Internal validation studies yielded a pooled Dice score of 88% (95% CI: 85–91%), while external validation studies reported a pooled Dice score of 89% (95% CI: 88–90%). Models trained on multiple MRI sequences consistently outperformed those trained on single sequences. Meta-regression indicated that training dataset size did not significantly influence segmentation accuracy. Conclusion CNN models are highly effective for meningioma segmentation in MRI, particularly during the use of diverse datasets from multiple MRI sequences. This finding highlights the importance of data quality and imaging sequence selection in the development of CNN models. Standardization of MRI data acquisition and preprocessing may improve the performance of CNN models, thereby facilitating their clinical adoption for the optimal diagnosis and treatment of meningioma.

Revisit the classical Newmark displacement analysis for earthquake-induced wedge sliding of a rock slope - Che-Ming Yang; Jia-Jyun Dong; Chyi-Tyi Lee; Hui-Yun Cheng; Chang-Hsuan Hsu; Thi-Phuong Nguyen; Chun-Jung Lai; Wen-Jie Wu (Engineering Geology, 2024)

Detection of micro-plasma-induced exosomes secretion in a fibroblast-melanoma co-culture model - Han Lee; Jiunn-Der Liao; Tak-Wah Wong; Che-Wei Wu; Bo-Yao Huang; Shun-Cheng Wu; Pei-Lin Shao; Yu-Han Wei; Ming-Hsien Cheng (Analytica Chimica Acta, 2023)

Predicting survival after radiosurgery in patients with lung cancer brain metastases using deep learning of radiomics and EGFR status - Chien-Yi Liao; Cheng-Chia Lee; Huai-Che Yang; Ching-Jen Chen; Wen-Yuh Chung; Hsiu-Mei Wu; Wan-Yuo Guo; Ren-Shyan Liu; Chia-Feng Lu (Physical and Engineering Sciences in Medicine, 2023)

Analyzing landslide-induced debris flow and flow-bridge interaction by using a hybrid model of depth-averaged model and discrete element method - Wen-Jie Shiu; Ching-Fang Lee; Chia-Chi Chiu; Meng-Chia Weng; Che-Ming Yang; Wei-An Chao; Chun-Yuan Liu; Cheng-Han Lin; Wei-Kai Huang (Landslides, 2023)

Disclosing the mutual influence of photocatalytic fuel cell and photoelectro-Fenton process in the fabrication of a sustainable hybrid system for efficient Amaranth dye removal and simultaneous electricity production - Shen-Hui Thor; Li-Ngee Ho; Soon-An Ong; Che Zulzikrami Azner Abidin; Cheng-Yong Heah; Kea-Lee Yap (Environmental Science and Pollution Research, 2022)

Plasma Matrix Metalloproeteinase-9 Is Associated with Seizure and Angioarchitecture Changes in Brain Arteriovenous Malformations - Yo-Tsen Liu; Cheng-Chia Lee; Chun-Fu Lin; Hsiu-Mei Wu; Wan-Yuo Guo; Huai-Che Yang; Feng-Chi Chang; Kang-Du Liou; Chung-Jung Lin (Molecular Neurobiology, 2022)

Towards a rapid assessment of highway slope disasters by using multidisciplinary techniques - Meng-Chia Weng; Cheng-Han Lin; Wen-Jie Shiu; Wei-An Chao; Chia-Chi Chiu; Ching-Fang Lee; Wei-Kai Huang; Che-Ming Yang (Landslides, 2022)
Mega-earthquakes and extreme climate events accompanied by intrinsic fragile geology lead to numerous landslides along mountain highways in Taiwan, causing enormous life and economic losses. In this study, a system for rapid slope disaster information integration and assessment is proposed with the aim of providing information on landslide occurrence, failure mechanisms, and subsequent landslide-affected areas to the highway authority rapidly. The functionality of the proposed system is deployed into three units: (1) geohazard rapid report (GeoPORT I), (2) multidisciplinary geological survey report (GeoPORT II), and (3) site-specific landslide simulation report (GeoPORT III). After landslide occurrence, the seismology-based monitoring network rapidly provides the initial slope disaster information, including preliminary location, event magnitude, earthquake activity, and source dynamics, within an hour. Within 3 days of the landslide, a multidisciplinary geological survey is conducted to collect high-precision topographical, geological, and remote-sensing data to determine the possible failure mechanism. After integrating the aforementioned information, a full-scale three-dimensional landslide simulation based on the discrete element method is performed within 10 days to reveal the failure process and to identify the areas potentially affected by subsequent disasters through scenario modeling. Overall, the proposed system can promptly provide comprehensive and objective information to relevant authorities after the event occurrence for hazard assessment. The proposed system was validated using a landslide event in the Central Cross-Island Highway of Taiwan.

Downregulated Calcium-Binding Protein S100A16 and HSP27 in Placenta-Derived Multipotent Cells Induce Functional Astrocyte Differentiation - Yu-Che Cheng; Chi-Jung Huang; Wei-Chi Ku; Shu-Lin Guo; Lu-Tai Tien; Yih-Jing Lee; Chih-Cheng Chien (Stem Cell Reviews and Reports, 2022)
Little is known about genes that induce stem cells differentiation into astrocytes. We previously described that heat shock protein 27 (HSP27) downregulation is directly related to neural differentiation under chemical induction in placenta-derived multipotent stem cells (PDMCs). Using this neural differentiation cell model, we cross-compared transcriptomic and proteomic data and selected 26 candidate genes with the same expression trends in both omics analyses. Those genes were further compared with a transcriptomic database derived from Alzheimer’s disease (AD). Eighteen out of 26 candidates showed opposite expression trends between our data and the AD database. The mRNA and protein expression levels of those candidates showed downregulation of HSP27, S100 calcium-binding protein A16 (S100A16) and two other genes in our neural differentiation cell model. Silencing these four genes with various combinations showed that co-silencing HSP27 and S100A16 has stronger effects than other combinations for astrocyte differentiation. The induced astrocyte showed typical astrocytic star-shape and developed with ramified, stringy and filamentous processes as well as differentiated endfoot structures. Also, some of them connected with each other and formed continuous network. Immunofluorescence quantification of various neural markers indicated that HSP27 and S100A16 downregulation mainly drive PDMCs differentiation into astrocytes. Immunofluorescence and confocal microscopic images showed the classical star-like shape morphology and co-expression of crucial astrocyte markers in induced astrocytes, while electrophysiology and Ca 2+ influx examination further confirmed their functional characteristics. In conclusion, co-silencing of S100A16 and HSP27 without chemical induction leads to PDMCs differentiation into functional astrocytes. Graphical abstract

Intramyocardial injection of human adipose-derived stem cells ameliorates cognitive deficit by regulating oxidative stress–mediated hippocampal damage after myocardial infarction - Tsung-Ming LEE; Cheng-Che LEE; Horng-Jyh HARN; Tzyy-Wen Chiou; Ming-Hsi CHUANG; Chun-Hung CHEN; Chi-Hsuan CHUANG; Po-Cheng LIN; Shinn-Zong LIN (Journal of Molecular Medicine, 2021)
Cognitive impairment is a serious side effect of post-myocardial infarction (MI) course. We have recently demonstrated that human adipose-derived stem cells (hADSCs) ameliorated myocardial injury after MI by attenuating reactive oxygen species (ROS) levels. Here, we studied whether the beneficial effects of intramyocardial hADSC transplantation can extend to the brain and how they may attenuate cognitive dysfunction via modulating ROS after MI. After coronary ligation, male Wistar rats were randomized via an intramyocardial route to receive either vehicle, hADSC transplantation (1 × 10 6 cells), or the combination of hADSCs and 3-Morpholinosydnonimine (SIN-1, a peroxynitrite donor). Whether hADSCs migrated into the hippocampus was assessed by using human-specific primers in qPCR reactions. Passive avoidance test was used to assess cognitive performance. Postinfarction was associated with increased oxidative stress in the myocardium, circulation, and hippocampus. This was coupled with decreased numbers of dendritic spines as well as a significant downregulation of synaptic plasticity consisting of synaptophysin and PSD95. Step-through latency during passive avoidance test was impaired in vehicle-treated rats after MI. Intramyocardial hADSC injection exerted therapeutic benefits in improving cardiac function and cognitive impairment. None of hADSCs was detected in rat’s hippocampus at the 3rd day after intramyocardial injection. The beneficial effects of hADSCs on MI-induced histological and cognitive changes were abolished after adding SIN-1. MI-induced ROS attacked the hippocampus to induce neurodegeneration, resulting in cognitive deficit. The remotely intramyocardial administration of hADSCs has the capacity of improved synaptic neuroplasticity in the hippocampus mediated by ROS, not the cell engraftment, after MI. Key messages Human adipose-derived stem cells (hADSCs) ameliorated injury after myocardial infarction by attenuating reactive oxygen species (ROS) levels. Intramyocardial administration of hADSCs remotely exerted therapeutic benefits in improving cognitive impairment after myocardial infarction. The improved synaptic neuroplasticity in the hippocampus was mediated by hADSC-inhibiting ROS, not by the stem cell engraftment.

Detection of Vestibular Schwannoma on Triple-parametric Magnetic Resonance Images Using Convolutional Neural Networks - Tzu-Hsuan Huang; Wei-Kai Lee; Chih-Chun Wu; Cheng-Chia Lee; Chia-Feng Lu; Huai-Che Yang; Chun-Yi Lin; Wen-Yuh Chung; Po-Shan Wang; Yen-Ling Chen; Hsiu-Mei Wu; Wan-You Guo; et al. (Journal of Medical and Biological Engineering, 2021)
Purpose The first step in typical treatment of vestibular schwannoma (VS) is to localize the tumor region, which is time-consuming and subjective because it relies on repeatedly reviewing different parametric magnetic resonance (MR) images. A reliable, automatic VS detection method can streamline the process. Methods A convolutional neural network architecture, namely YOLO-v2 with a residual network as a backbone, was used to detect VS tumors from MR images. To heighten performance, T1-weighted–contrast-enhanced, T2-weighted, and T1-weighted images were combined into triple-channel images for feature learning. The triple-channel images were cropped into three sizes to serve as input images of YOLO-v2. The VS detection effectiveness levels were evaluated for two backbone residual networks that downsampled the inputs by 16 and 32. Results The results demonstrated the VS detection capability of YOLO-v2 with a residual network as a backbone model. The average precision was 0.7953 for a model with 416 × 416-pixel input images and 16 instances of downsampling, when both the thresholds of confidence score and intersection-over-union were set to 0.5. In addition, under an appropriate threshold of confidence score, a high average precision, namely 0.8171, was attained by using a model with 448 × 448-pixel input images and 16 instances of downsampling. Conclusion We demonstrated successful VS tumor detection by using a YOLO-v2 with a residual network as a backbone model on resized triple-parametric MR images. The results indicated the influence of image size, downsampling strategy, and confidence score threshold on VS tumor detection.

Cocaine Withdrawal Impairs mGluR5-Dependent Long-Term Depression in Nucleus Accumbens Shell Neurons of Both Direct and Indirect Pathways - Chiung-Chun Huang; Ying-Ching Liang; Cheng-Che Lee; Kuei-Sen Hsu (Molecular Neurobiology, 2015)

Chemical modification and anticancer effect of prenylated flavanones from Taiwanese propolis - Chia-Nan Chen; Che-Jen Hsiao; Shoei-Sheng Lee; Jih-Hwa Guh; Po-Cheng Chiang; Chih-Chiang Huang; Wei-Jan Huang (Natural Product Research, 2012)

Reactive oxygen species-mediated PKC and integrin signaling promotes tumor progression of human hepatoma HepG2 - Chi-Tan Hu; Jia-Ru Wu; Chuan-Chu Cheng; Sindy Wang; Hsiao-Ting Wang; Ming-Che Lee; Ling-Jung Wang; Siou-Mei Pan; Tsu-Yao Chang; Wen-Sheng Wu (Clinical & Experimental Metastasis, 2011)

Isolation and Characterization of Bacteria Capable of Degrading Phenol and Reducing Nitrate Under Low-Oxygen Conditions - Seung-Hun Baek; Kyoung-Ho Kim; Cheng-Ri Yin; Che Ok Jeon; Wan-Taek Im; Kwang-Kyu Kim; Sung-Taik Lee (Current Microbiology, 2003)

Increased expression of iNOS and c-fos via regulation of protein tyrosine phosphorylation and MEK1/ERK2 proteins in terminal bronchiole lesions in the lungs of rats exposed to cigarette smoke - Wen-Cheng Chang; Yuan-Chih Lee; Chuen-Lan Liu; Jeng-Dong Hsu; Hsue-Chun Wang; Chang-Che Chen; Chau-Jong Wang (Archives of Toxicology, 2001)

Comparison between `in vivo' and `in vitro' methods for evaluating tumor angiogenesis using cervical carcinoma as a model - Wen-Fang Cheng; Chien-Nan Lee; Chi-An Chen; Jan-Show Chu; Cheng-Che S. Kung; Chang-Yao Hsieh; Fon-Jou Hsieh (Angiogenesis, 1999)