1.The Growing Burden of Fall-Related Injuries among Older Adults: A Seven-Year Study from a Tertiary Medical Center in Taiwan
Yu-Chieh TSAI ; Shey-Ying CHEN ; Ya-Mei CHEN ; Edward Pei-Chuan HUANG ; Feng-Ping LU
Annals of Geriatric Medicine and Research 2026;30(1):70-76
Background:
As Taiwan’s population ages, falls among older adults have become a critical public health concern. However, limited data exist regarding temporal trends and injury patterns in fall-related emergency department (ED) visits. This study aimed to examine trends in fall-related ED visits and hospitalizations among older adults in Taiwan and to explore injury distributions by age group.
Methods:
We conducted a retrospective cohort study using data from the National Taiwan University Hospital between 2011 and 2017. Patients aged ≥65 years were compared with those aged 20–64 years. Fall-related visits were identified using chief complaints and the International Classification of Diseases 9th/10th revision (ICD-9/ICD-10) codes. Outcomes included hospitalization rates, length of stay, and 30-day mortality.
Results:
A total of 22,471 fall-related ED visits were analyzed. While visits among younger adults declined (annual growth rate, -1.34%), visits among older adults increased (2.37% annually), with the steepest rise in those aged ≥85 years. Hospitalization occurred in 27.1% of older adults, nearly double that of younger adults (14.4%). Older adults also had longer hospital stays and higher 30-day mortality rates, findings consistent even when restricted to lower limb fractures.
Conclusion
Fall-related ED visits and hospitalizations are rising disproportionately among Taiwan’s older population. Targeted prevention strategies and transitional care interventions are urgently needed to address the growing clinical and economic burden of falls in aging societies.
2.Predictive Factors Associated With Dysphagia in Patients With Traumatic Brain Injury
Shu-Mei YANG ; Ting-Ju LAI ; Ya-Chu HSU ; Yu-Lin LU ; Hsing-Yu CHEN ; Hsiao-Ting TSAI ; Sheng-Hao CHENG ; Ming-Yen HSIAO ; Meng-Ting LIN
Annals of Rehabilitation Medicine 2026;50(2):117-128
Objective:
To identify early clinical predictors associated with dysphagia and delayed swallowing recovery in patients with traumatic brain injury (TBI).
Methods:
In this retrospective study, we enrolled adult TBI patients admitted to the rehabilitation unit of a tertiary medical center between June 2019 and June 2023. Data on baseline characteristics, neurological status, imaging findings, and rehabilitation-related variables were collected. Swallowing function was assessed using two indicators: (1) nasogastric (NG) tube retention and (2) the Functional Oral Intake Scale (FOIS) scores at 1, 4, and 12 weeks post-injury. Regression analyses were conducted to identify predictors associated with dysphagia and swallowing recovery.
Results:
A total of 160 patients were included. At 1 week post-injury, longer intensive care unit (ICU) stay, poor initial sitting balance and use of sedative medication in ICU were associated with NG tube retention. At 4 weeks, lower initial Rancho Los Amigos Scale (RLAS) scores, immobility-related complications, longer hospitalization, and temporal lobe hematomas were associated with persistent NG tube dependence. By 12 weeks, older age, delayed ability to follow commands, and poor initial sitting balance remained associated with NG tube retention. FOIS outcomes were also associated with older age, delayed time to follow commands, impaired initial sitting balance, prolonged ICU stay, temporal lobe hematomas, lower initial RLAS scores, immobility-related complications, prolonged endotracheal tube placement and extended hospital stays.
Conclusion
Impaired cognitive status, poor physical function, immobility-related complications, and temporal lobe hematomas were key factors associated with dysphagia and delayed oral intake in individuals with TBI.
4.Parkinsonism in Cerebral Autosomal Dominant Arteriopathy With Subcortical Infarcts and Leukoencephalopathy: Clinical Features and Biomarkers
Chih-Hao CHEN ; Te-Wei WANG ; Yu-Wen CHENG ; Yung-Tsai CHU ; Mei-Fang CHENG ; Ya-Fang CHEN ; Chin-Hsien LIN ; Sung-Chun TANG
Journal of Stroke 2025;27(1):122-127
5.Predicting Clinically Significant Prostate Cancer Using Urine Metabolomics via Liquid Chromatography Mass Spectrometry
Chung-Hsin CHEN ; Hsiang-Po HUANG ; Kai-Hsiung CHANG ; Ming-Shyue LEE ; Cheng-Fan LEE ; Chih-Yu LIN ; Yuan Chi LIN ; William J. HUANG ; Chun-Hou LIAO ; Chih-Chin YU ; Shiu-Dong CHUNG ; Yao-Chou TSAI ; Chia-Chang WU ; Chen-Hsun HO ; Pei-Wen HSIAO ; Yeong-Shiau PU ;
The World Journal of Men's Health 2025;43(2):376-386
Purpose:
Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles.
Materials and Methods:
Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion.
Results:
The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column.
Conclusions
Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.
6.6-Gingerol Induced Apoptosis and Cell Cycle Arrest in Glioma Cells via MnSOD and ERK Phosphorylation Modulation
Sher-Wei LIM ; Wei-Chung CHEN ; Huey-Jiun KO ; Yu-Feng SU ; Chieh-Hsin WU ; Fu-Long HUANG ; Chien-Feng LI ; Cheng Yu TSAI
Biomolecules & Therapeutics 2025;33(1):129-142
6-gingerol, a bioactive compound from ginger, has demonstrated promising anticancer properties across various cancer models by inducing apoptosis and inhibiting cell proliferation and invasion. In this study, we explore its mechanisms against glioblastoma multiforme (GBM), a notably aggressive and treatment-resistant brain tumor. We found that 6-gingerol crosses the blood-brain barrier more effectively than curcumin, enhancing its potential as a therapeutic agent for brain tumors. Our experiments show that 6-gingerol reduces cell proliferation and triggers apoptosis in GBM cell lines by disrupting cellular energy homeostasis. This process involves an increase in mitochondrial reactive oxygen species (mtROS) and a decrease in mitochondrial membrane potential, primarily due to the downregulation of manganese superoxide dismutase (MnSOD). Additionally, 6-gingerol reduces ERK phosphorylation by inhibiting EGFR and RAF, leading to G1 phase cell cycle arrest. These findings indicate that 6-gingerol promotes cell death in GBM cells by modulating MnSOD and ROS levels and arresting the cell cycle through the ERFR-RAF-1/MEK/ ERK signaling pathway, highlighting its potential as a therapeutic agent for GBM and setting the stage for future clinical research.
7.6-Gingerol Induced Apoptosis and Cell Cycle Arrest in Glioma Cells via MnSOD and ERK Phosphorylation Modulation
Sher-Wei LIM ; Wei-Chung CHEN ; Huey-Jiun KO ; Yu-Feng SU ; Chieh-Hsin WU ; Fu-Long HUANG ; Chien-Feng LI ; Cheng Yu TSAI
Biomolecules & Therapeutics 2025;33(1):129-142
6-gingerol, a bioactive compound from ginger, has demonstrated promising anticancer properties across various cancer models by inducing apoptosis and inhibiting cell proliferation and invasion. In this study, we explore its mechanisms against glioblastoma multiforme (GBM), a notably aggressive and treatment-resistant brain tumor. We found that 6-gingerol crosses the blood-brain barrier more effectively than curcumin, enhancing its potential as a therapeutic agent for brain tumors. Our experiments show that 6-gingerol reduces cell proliferation and triggers apoptosis in GBM cell lines by disrupting cellular energy homeostasis. This process involves an increase in mitochondrial reactive oxygen species (mtROS) and a decrease in mitochondrial membrane potential, primarily due to the downregulation of manganese superoxide dismutase (MnSOD). Additionally, 6-gingerol reduces ERK phosphorylation by inhibiting EGFR and RAF, leading to G1 phase cell cycle arrest. These findings indicate that 6-gingerol promotes cell death in GBM cells by modulating MnSOD and ROS levels and arresting the cell cycle through the ERFR-RAF-1/MEK/ ERK signaling pathway, highlighting its potential as a therapeutic agent for GBM and setting the stage for future clinical research.
8.Predicting Clinically Significant Prostate Cancer Using Urine Metabolomics via Liquid Chromatography Mass Spectrometry
Chung-Hsin CHEN ; Hsiang-Po HUANG ; Kai-Hsiung CHANG ; Ming-Shyue LEE ; Cheng-Fan LEE ; Chih-Yu LIN ; Yuan Chi LIN ; William J. HUANG ; Chun-Hou LIAO ; Chih-Chin YU ; Shiu-Dong CHUNG ; Yao-Chou TSAI ; Chia-Chang WU ; Chen-Hsun HO ; Pei-Wen HSIAO ; Yeong-Shiau PU ;
The World Journal of Men's Health 2025;43(2):376-386
Purpose:
Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles.
Materials and Methods:
Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion.
Results:
The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column.
Conclusions
Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.
10.Parkinsonism in Cerebral Autosomal Dominant Arteriopathy With Subcortical Infarcts and Leukoencephalopathy: Clinical Features and Biomarkers
Chih-Hao CHEN ; Te-Wei WANG ; Yu-Wen CHENG ; Yung-Tsai CHU ; Mei-Fang CHENG ; Ya-Fang CHEN ; Chin-Hsien LIN ; Sung-Chun TANG
Journal of Stroke 2025;27(1):122-127

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