1.Survival impact of radiotherapy for patients with de novo metastatic rectal cancer
Harvey Yu-Li SU ; Yun-Hsuan LIN ; Ko-Chao LEE ; Yueh-Ming LIN ; Chun-Chieh HUANG ; Eng-Yen HUANG ; Tai-Jan CHIU ; Shih-Yu HUANG ; Chia-Che WU ; Chang-Ting LIN ; Ming-Chun KUO ; Kai-Lung TSAI
Annals of Coloproctology 2026;42(1):94-102
Purpose:
Metastatic rectal cancer (mRC) is a highly lethal and complex disease that demands a multidisciplinary treatment approach. However, the clinical effectiveness of radiotherapy (RT) for de novo mRC remains controversial and uncertain.
Methods:
This retrospective cohort study examined medical records from Kaohsiung Chang Gung Memorial Hospital for patients with histologically confirmed de novo mRC diagnosed between January 2015 and December 2020. All patients received standard systemic therapy and radical surgery when feasible. The primary outcome, overall survival (OS), was assessed using the Kaplan-Meier method. Multivariable analysis was performed using a Cox regression model.
Results:
Among 271 patients included in the analysis, 117 received RT and 154 did not. The median OS was significantly longer in the RT group compared with the non-RT group (27.8 months vs. 21.9 months; P=0.046). Multivariate analysis identified several independent predictors of OS: age ≥65 years (hazard ratio [HR], 1.69; 95% confidence interval [CI], 1.26–2.27; P=0.001), primary tumor resection (HR, 2.62; 95% CI, 1.90–3.61; P<0.001), M1b or M1c disease (HR, 1.97; 95% CI, 1.44–2.69; P<0.001), and receipt of RT (HR, 1.41; 95% CI, 1.02–1.94; P=0.036).
Conclusion
RT significantly improves OS in patients with mRC, underscoring its role in treatment strategies. These findings support its inclusion in therapeutic protocols and highlight the need for larger, multicenter trials to confirm and extend these results.
2.Licochalcone E Ameliorates Hepatic Steatosis in Obese Mice by Activating the Sirt1/AMPK Pathway and Reducing Hepatic Lipid Accumulation
Wen-Chung HUANG ; Shu-Ju WU ; Xuan-Min LIU ; Shu-Chen CHENG ; Po-Ting LIN ; Chun-Ling KUO ; Chian-Jiun LIOU
Biomolecules & Therapeutics 2026;34(3):676-688
Licochalcone E is a chalcone isolated from Glycyrrhiza uralensis and G. inflata Batal. This study explored the effect of licochalcone E on improving hepatic steatosis in obese mice and evaluated the role of licochalcone E in regulating lipid accumulation in hepatocytes. In vitro, oleic acid–induced hepatocytes were treated with licochalcone E to investigate its effect on lipid metabolic pathways. In animal experiments, male C57BL/6 mice were fed with a high-fat diet (HFD) and treated with licochalcone E by intraperitoneal injection for 12 weeks to assess its effects on biochemical indexes and hepatic steatosis. Furthermore, mice were fed a methionine/choline-deficient (MCD) diet and administered licochalcone E, followed by evaluation of liver fibrosis. Licochalcone E effectively reduced body weight, epididymal and inguinal fat weight, and adipocyte size in HFD-induced obese mice. Licochalcone E treatment of obese mice also reduced hepatic lipid accumulation and improved hepatocyte steatosis. Licochalcone E regulated the expression of lipogenesis- and lipolysis-related genes in the livers of obese mice and increased AMPK phosphorylation and Sirt1 expression in the liver. Licochalcone E also attenuated hepatic inflammation and oxidative stress in obese mice. Furthermore, treatment of MCD-induced mice with licochalcone E reduced the number of lipid vacuoles and the extent of fibrosis and inhibited liver inflammation. In FL83B hepatocytes, licochalcone E could regulate lipogenesis and lipolysis, and increase the phosphorylation of AMPK and ACC. These findings provide new insights into the role of licochalcone E in regulating lipid metabolism and preventing hepatic steatosis.
3.Harnessing Machine Learning for Personalized Care of Patients With Idiopathic Sudden Sensorineural Hearing Loss: A Multicenter Cohort Study
Yen-Ting GUO ; Ching-Ting TAN ; Chen-Chi WU ; Chun-Ying WANG ; Chein-Yu HUANG ; Tzu-Hsiang YANG ; Ting-Yi LEE ; Ting-Hua YANG ; Tien-Chen LIU ; Pey-Yu CHEN ; Pei-Hsuan LIN
Clinical and Experimental Otorhinolaryngology 2026;19(2):194-204
Objectives:
. Idiopathic sudden sensorineural hearing loss (ISSNHL) is a significant cause of hearing loss. Intratympanic steroid injection (ITSI) is commonly used as an initial or salvage treatment; however, the lack of a standardized treatment protocol has resulted in variability in clinical practice. In addition, no efficient prediction model currently exists to support personalized management. Therefore, this study aimed to develop tailored management strategies for ISSNHL using a machine-learning model.
Methods:
. This retrospective multicenter cohort study was conducted between January 2015 and December 2020, with data analysis performed between January 2021 and March 2024. Patients were selected based on the International Classification of Diseases, 10th Revision criteria for ISSNHL, along with relevant medication and procedure codes. Patients with pure-tone audiogram results not meeting ISSNHL criteria, better initial hearing in the affected ear, an identifiable etiology, no post-treatment audiogram, or delayed treatment (>6 weeks) were excluded. We included 770 patients diagnosed with ISSNHL who received ITSI. The primary outcome was the area under the receiver operating characteristic curve for prediction performance. Recovery status was determined using the last pure-tone audiogram. Modeling was conducted on the Quanta for Medical Care AI platform using five machine-learning algorithms and a nested cross-validation framework, in which feature selection and hyperparameter tuning were performed in the inner folds and model performance was evaluated in the outer folds.
Results:
. A random forest classifier outperformed the other models in predicting hearing outcomes, achieving an area under the receiver operating characteristic curve of 0.788. Time to ITSI was the most influential treatment-related factor, with ITSI administered within 10 days of hearing loss being associated with better outcomes. This model can be used to provide personalized prognostic estimates under different treatment protocols.
Conclusion
. The machine-learning-based prediction model facilitates personalized treatment strategies and timely treatment adjustments for ISSNHL, thereby optimizing the likelihood of complete recovery.
4.From index to insight: clinical perspectives on electroencephalographic spectrogram-guided anesthesia—a narrative review
Akira MUKAI ; Jen-Ting YANG ; Shao-Chun WU ; Tzu-Chun WANG ; Feng-Sheng LIN ; Chun-Yu WU
Korean Journal of Anesthesiology 2026;79(2):139-151
Processed electroencephalogram (EEG) indices, such as the Bispectral Index, have markedly influenced anesthesia practice as they translate brain activity into simple numerical indices. Nevertheless, as the manufacturing algorithms are not disclosed, the underlying neurophysiology remains obscured. Additionally, these indices are often affected by electromyographic contamination, pharmacological variability, and patient-specific EEG heterogeneity. In contrast, an EEG spectrogram, or density spectral array, preserves the frequency- and time-resolved structures of cortical oscillations. This information is presented in a form that is both physiologically meaningful and clinically interpretable. In this review, we trace the evolution of anesthesia from an index-based to a spectrogram-guided approach, and summarize the clinical rationale for adopting the latter. Key applications of this approach include the use of frontal alpha power as a biomarker of cortical stability and postoperative brain health, the identification of nociceptive arousal through alpha dropout and beta or delta arousal patterns, and individualized titration of multimodal or age-specific anesthetic management. Although current devices lack standardized quantitative alpha metrics and have limited sensitivity for low-frequency brain wave components, structured EEG education programs have proven to be effective in terms of fostering spectrogram literacy among anesthesiologists. By combining neurophysiological precision with bedside practicality, the EEG spectrogram represents a pivotal advance toward individualized, mechanism-based, and brain-protective anesthesia, transforming anesthetic monitoring from mere algorithmic abstraction to cortical insight.
5.Short-term and long-term outcomes of acute severe ulcerative colitis in Taiwan: a multicenter study with pre- and post-biologics comparison
Wei-Chen LIN ; Chun-Chi LIN ; Wen-Hung HSU ; Feng-Fan CHIANG ; Chen-Wang CHANG ; Tzu-Chi HSU ; Deng-Chyang WU ; Horng-Yuan WANG ; Jau-Min WONG ; Shu-Chen WEI
Intestinal Research 2026;24(1):117-128
Background/Aims:
Data from Asia regarding the short-term and long-term outcomes for acute severe ulcerative colitis (ASUC) are limited. We assessed the outcomes of ASUC, identified the risk factors for colectomy, and compared colectomy rates between the pre-biologics and post-biologics eras in Taiwan.
Methods:
The patients with an ASUC diagnosis between January 2013 and March 2022 at 5 tertiary medical centers were retrospectively analyzed.
Results:
In total, 98 patients were enrolled, with 68.4% diagnosed in the post-biologics era. In 78.6% of the ASUC patients initially received intravenous steroid therapy, for which the success rate was 74.1%. As for rescue therapy, 15 patients (93.8%) received biologics and 1 (6.3%) received cyclosporin. Biologics rescue therapy had a 93.3% success rate. One (1%) mortality due to septic shock occurred. The colectomy rate for index ASUC admission was 11.2%. Patients receiving colectomy were predominantly male (P= 0.012) and at older age (P= 0.016). Higher C-reactive protein (P= 0.035), lower albumin (P= 0.017), and hemoglobin (P= 0.023) levels were associated with colectomy risk. During a median follow-up of 24 months, 13 patients (15.1%) had recurrent ASUC and 23.1% of patients received colectomy. The accumulated colectomy rate at 3 years did not differ between the pre- and post-biologics eras (16.1% vs. 13.4%, P= 0.270).
Conclusions
This is the first Asian study on ASUC to compare colectomy rates between the prebiologics and post-biologics eras, revealing no significant difference. The recurrent ASUC had a higher colectomy rate than the index ASUC.
7.Effect of warm acupuncture on PINK1/Parkin pathway in the skeletal muscle of rats with chronic fatigue syndrome
Huayuan LI ; Chun LI ; Junwei LIU ; Ting WANG ; Long LI ; Yongli WU
Chinese Journal of Tissue Engineering Research 2025;29(8):1618-1625
BACKGROUND:It has been found that mitochondrial function is abnormal in patients with chronic fatigue syndrome,and the administration of coenzymes can improve the symptoms.Warm acupuncture is one of the most important treatments for this disease,but its mechanism of action is unclear. OBJECTIVE:To investigate the effects of warm acupuncture on the phosphatase and tensin inducible kinase 1(PINK1)/Parkin pathway in the skeletal muscle of rats with chronic fatigue syndrome. METHODS:After 3 days of adaptive feeding,32 male Sprague-Dawley rats were randomly divided into normal control,model,warm acupuncture,and coenzyme Q groups with 8 rats in each group.The chronic fatigue syndrome model was established by multiple factors,including swimming exhaustion,chronic immobilization and fasting.After successful modeling,the normal group and the model group were treated with the same fixation and gavage procedures,and the warm acupuncture group was treated with acupuncture at Guanyuan,Zhongwan and Zusanli(bilateral)points,once a day.After the needling was inserted,the moxa pillar was put on the needle handle and ignited,three sessions once.The coenzyme Q group was given 1 mL/kg coenzyme by gavage,once a day for 14 days.The body mass,exhaustive swimming time and food utilization rate during the treatment were recorded.After the treatment,the bilateral gastrocnemius muscles of rats in each group were collected.The pathological morphology of the gastrocnemius muscle was observed by hematoxylin-eosin staining,the mitochondrial morphology and autophagosome of the gastrocnemius muscle were observed by transmission electron microscope.The expression level of microtubule-associated protein light chain 3(LC3)Ⅱ protein in the skeletal muscle was detected by immunohistochemistry.Western blot was used to detect the expression of PINK1,Parkin,LC3 Ⅰ,and LC3 Ⅱ in the skeletal muscle. RESULTS AND CONCLUSION:Compared with the normal group,the gastrocnemius muscle nuclei of the model group were pyknotic,condensed,the number of cells was increased,the cells were arranged disorderly,and the fibers in the gastrocnemius muscle were tightly arranged in the model group.Compared with the model group,the intercellular space became smaller,the nuclei were reduced,and the cell arrangement was orderly in the warm acupuncture group and coenzyme Q group.Compared with the normal group,the skeletal muscle mitochondria in the model group were swollen,fused,and vacuolated seriously,the membrane was partially broken,the matrix was more dissolved,the cristae was broken and disappeared,and autophagy appeared.Compared with the model group,the number of mitochondria increased,the arrangement was relatively neat,mitochondrial vacuolization and rupture of cristae in the gastrocnemius muscle were improved,the membrane structure was relatively intact,and autophagy occurred.Compared with the normal group,the expression of PINK1 protein in the skeletal muscle of the model group was significantly increased(P<0.05),while the expression of Parkin,LC3 Ⅱ and LC3 Ⅱ/Ⅰ protein was slightly upregulated(P>0.05).Compared with the model group,the protein expressions of PINK1,Parkin,LC3 Ⅱ and LC3 Ⅱ/Ⅰ were significantly upregulated in the warm acupuncture and coenzyme Q groups(P<0.05),and the up-regulation was more significant in the warm acupuncture group.To conclude,warm acupuncture can play a role in the treatment of chronic fatigue syndrome by activating the PINK1/Parkin pathway,upregulating LC3 Ⅱ expression,forming mitochondrial autophagosomes,promoting the degradation of damaged mitochondria,and improving mitochondrial quality.
8.Alternative Polyadenylation in Mammalian
Yu ZHANG ; Hong-Xia CHI ; Wu-Ri-Tu YANG ; Yong-Chun ZUO ; Yong-Qiang XING
Progress in Biochemistry and Biophysics 2025;52(1):32-49
With the rapid development of sequencing technologies, the detection of alternative polyadenylation (APA) in mammals has become more precise. APA precisely regulates gene expression by altering the length and position of the poly(A) tail, and is involved in various biological processes such as disease occurrence and embryonic development. The research on APA in mammals mainly focuses on the following aspects:(1) identifying APA based on transcriptome data and elucidating their characteristics; (2) investigating the relationship between APA and gene expression regulation to reveal its important role in life regulation;(3) exploring the intrinsic connections between APA and disease occurrence, embryonic development, differentiation, and other life processes to provide new perspectives and methods for disease diagnosis and treatment, as well as uncovering embryonic development regulatory mechanisms. In this review, the classification, mechanisms and functions of APA were elaborated in detail and the methods for APA identifying and APA data resources based on various transcriptome data were systematically summarized. Moreover, we epitomized and provided an outlook on research on APA, emphasizing the role of sequencing technologies in driving studies on APA in mammals. In the future, with the further development of sequencing technology, the regulatory mechanisms of APA in mammals will become clearer.
9.Comparison of Logistic Regression and Machine Learning Approaches in Predicting Depressive Symptoms: A National-Based Study
Xing-Xuan DONG ; Jian-Hua LIU ; Tian-Yang ZHANG ; Chen-Wei PAN ; Chun-Hua ZHAO ; Yi-Bo WU ; Dan-Dan CHEN
Psychiatry Investigation 2025;22(3):267-278
Objective:
Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic.
Methods:
Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC).
Results:
LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models.
Conclusion
Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.
10.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.

Result Analysis
Print
Save
E-mail