1.A systematic review on the integrated application of evidence-based narrative education and undergraduate nursing teaching
Nannan BAI ; Meng LI ; Qian LIANG ; Chou YAO ; Yan WANG ; Ju HAN ; Chenyang HOU ; Nana XING
Chinese Medical Ethics 2026;39(2):229-237
ObjectiveTo systematically evaluate the application of narrative education in undergraduate nursing teaching, to understand the current application status of narrative education, and to provide a theoretical basis for the subsequent establishment of a sound narrative education system. MethodsA systematic search was conducted for studies published in Chinese and English databases on applying narrative education to undergraduate nursing teaching, with the search period ranging from database inception to February 23, 2025. Literature was screened, and relevant information was extracted. A rigorous quality evaluation was conducted on the included studies, and a descriptive analysis was performed on their content. ResultsA total of 20 papers were included, involving 3,180 research subjects, all of whom were undergraduate nursing students. The results of descriptive analysis showed that the teaching model of narrative education primarily encompassed reading narrative works, watching films and videos, performing narrative scenarios, and writing reflective journals. The course setting and content covered pre-teaching preparation and in-teaching implementation. The evaluation of teaching effectiveness included the evaluation of teachers’ teaching methods (student evaluation/self-evaluation) and the evaluation of students’ learning effectiveness (course grade evaluation/humanistic care scale/empathy scale assessment, and others). ConclusionNarrative education combines abstract concepts with concrete clinical situations, which not only enriches students’ learning experiences but also enhances their humanistic literacy. Meanwhile, it provides teachers with opportunities to develop their narrative teaching skills, which requires them to possess profound professional knowledge and employ narrative techniques to guide students in reflection and critical thinking, thereby improving teaching quality and learning outcomes. Future efforts should consistently deepen the connotation research of narrative education and build a systematic nursing education system.
2.Application Value of Scales for Symptom & Syndrome Evaluation in Spleen-Stomach Diseases Related New Drug Research and Development
Fengbin LIU ; Simeng YAO ; Ping WANG ; Liqun BIAN ; Zhengkun HOU ; Xudong TANG
Journal of Traditional Chinese Medicine 2026;67(5):504-509
Symptom and syndrome efficacy evaluation scales are indispensable tools for clinical efficacy assessment in traditional Chinese medicine (TCM), and hold significant value at all stages of new drug research development for spleen and stomach diseases. These scales can provide scientific basis for clinical positioning, efficacy evaluation, and expansion of indications of new drugs. By analyzing the current hotspots and difficulties in research, this study aims to explore the important significance of these scales in the development of new drugs for spleen and stomach diseases, summarize the domestic research progress, and conduct comparative analyses with international studies. Future development trends are also discussed in order to promote the application of symptom and syndrome efficacy evaluation scales in the development of new drugs for spleen and stomach diseases and to advance the moder-nization process of TCM.
3.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.
4.Predictive value of ultrasound-derived quantitative indicators of umbilical cord hypercoiling and hemodynamic parameters for adverse pregnancy outcomes.
Xiaotan TAN ; Qichang ZHOU ; Hongxia YUAN ; Da HOU ; Yunfang ZHU ; Ruji YAO
Journal of Central South University(Medical Sciences) 2025;50(7):1179-1187
OBJECTIVES:
The diagnostic value of ultrasonographic quantitative indicators of umbilical cord coiling, such as the umbilical coiling index (UCI) and pitch value, in identifying hypercoiling and predicting adverse pregnancy outcomes remains controversial. This study aims to evaluate the predictive value of UCI, pitch value, and the cerebroplacental ratio in pregnancies complicated by umbilical cord hypercoiling.
METHODS:
Pregnant women with densely coiled umbilical cords identified by routine obstetric ultrasound at Changsha Maternal and Child Health Hospital between November 2022 and November 2024 were enrolled. Complete clinical data, including UCI, pitch value, and cerebroplacental ratio (CPR), were collected. Pregnancy outcome scores were calculated, and newborns were categorized into the normal outcome group (n=177) and adverse outcome group (n=85), with the latter further subdivided into mild (n=51), moderate (n=19), and severe (n=15) subgroups. Differences in baseline data, UCI, pitch value, and incidence of CRP<1 were compared between groups and among subgroups. Correlations between UCI, pitch value, and adverse pregnancy outcomes were analyzed. Receiver operating characteristic (ROC) curve were used to assess the predictive performance of UCI, pitch value, CPR<1, and their combinations.
RESULTS:
Compared with the normal outcome group, the adverse outcome group had higher age, parity, parity, incidence of CPR<1, and UCI, while gestational age at delivery and pitch values were lower (all P<0.05). The incidence of obesity, gestational diabetes mellitus, and hypertensive disorders of pregnancy did not differ significantly between the 2 groups (all P>0.05). The normal outcome group showed lower UCI and higher pitch values than all 3 adverse outcome subgroups (all P<0.05), while differences among the 3 adverse subgroups were not significant (all P>0.05). UCI was positively correlated with adverse pregnancy outcomes (rs=0.350, P<0.05), whereas pitch value was negatively correlated (rs=-0.286, P<0.05). ROC curve analysis showed that the area under the curve (AUC) values for predicting adverse outcomes were 0.837 for UCI, 0.886 for pitch value, and 0.610 for CPR<1, with sensitivities of 77.6%, 82.4%, and 27.1% and specificities of 78.5%, 83.6%, and 94.9%, respectively. The combined UCI+CPR<1 and pitch value+CPR<1 models yielded AUCs of 0.841 and 0.886, with sensitivities of 78.8% and 81.2% and specificities of 78.5% and 84.2%, respectively. No significant differences were found between the AUCs of UCI and pitch value (P>0.05), but both outperformed CPR<1 alone (both P<0.001). The combined models showed no significant improvement over UCI or pitch value alone (both P>0.05), though both were superior to CPR<1 alone (both P<0.001).
CONCLUSIONS
Most umbilical cord hypercoiling cases had favorable outcomes, with UCI, pitch value, CPR<1 and their combinations demonstrating significant predictive value for adverse pregnancy outcomes.
Humans
;
Female
;
Pregnancy
;
Pregnancy Outcome
;
Adult
;
Ultrasonography, Prenatal/methods*
;
Umbilical Cord/diagnostic imaging*
;
Hemodynamics
;
Predictive Value of Tests
;
Infant, Newborn
;
ROC Curve
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.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.
7.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.
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.
9.Icariin improves busulfan- and cyclophosphamide-induced reproductive function damage in male mice.
Yao WU ; Shan-Shan SHI ; Hai-Yan LIU ; Hao HUANG ; Xing-Hua SHI ; Jing HOU
National Journal of Andrology 2025;31(1):25-33
OBJECTIVE:
To comprehensively evaluate the effect of icariin in alleviating reproductive function damage (RFD) in male mice via in vitro and in vivo experiments.
METHODS:
We isolated Leydig cells from 60 KM male mice in vitro, and examined the toxic effect of icariin on the Leydig cells using Cell Counting Kit-8 (CCK-8). We equally randomized the mice into six groups: normal control, RFD model control (made by intraperitoneal injection of busulfan at 10 mg/kg combined with cyclophosphamide (CP) at 120 mg/kg), positive control, and low-, medium- and high-dose icariin. After modeling, we treated the mice in the positive control group with Wuziyanzong Pills and those in the low-, medium- and high-dose icariin groups by intragastrical administration of icariin at 20, 40 and 80 mg/kg-1, respectively, for 30 successive days. Then we obtained the weight and visceral coefficients of the reproductive organs, calculated the sperm count, observed the pathological changes in the testis tissue by HE staining, measured the serum testosterone (T) level by ELISA, determined the indexes of testicular oxidative stress and nitric oxide (NO) signaling pathway by colorimetric assay, and detected the expression levels of the pro-apoptotic genes Fas and Bax by qRT-PCR.
RESULTS:
CCK-8 assay confirmed that icariin had no toxic effect on the isolated Leydig cells of the mice, and could effectively reduce busulfan- and CP-induced cytotoxicity and promote the secretion of serum T. Icariin at 80 mg/kg significantly increased the visceral coefficient of the testis and promoted spermatogenesis (P<0.05), but had little effect on the visceral coefficient of the epididymis in the RFD model mice. Testicular histomorphometric observation revealed significantly improved testis structure, intact boundary membrane of seminiferous tubules and increased numbers of various types of spermatogenic cells of the model mice after treated with icariin. Compared with the mice in the model control group, those treated with high-dose icariin showed a significantly reduced content of malondialdehyde (MDA) (by 35.3%, P<0.01), elevated total antioxidant capacity (TAOC) and superoxide dismutase (T-SOD) activity (P<0.05), and decreased NO content and nitric oxide synthase (NOS) activity in the testis tissue (P<0.01). In addition, icariin exhibited an evident inhibitory effect on the expressions of the pro-apoptotic genes Bax and Fas.
CONCLUSION
Icariin can ameliorate oxidative stress-induced damage to the testicular function and protect spermatogenesis of male mice by elevating TAOC, decreasing NOS activity, inhibiting the NO level in the testis, and suppressing busulfan- and CP-induced apoptosis of testicular cells.
Animals
;
Male
;
Cyclophosphamide/adverse effects*
;
Mice
;
Busulfan/adverse effects*
;
Flavonoids/pharmacology*
;
Leydig Cells/drug effects*
;
Oxidative Stress/drug effects*
;
Testis/drug effects*
;
Apoptosis/drug effects*
;
Testosterone/blood*
10.Traditional Chinese Exercise Improves Lung Function and Exercise Capacity in Patients with Preserved Ratio Impaired Spirometry.
Yan-Yi LIU ; Gai-Hua HOU ; Kun XIA ; Xiao-Yan YAO ; Yi WANG ; Guang-Xi LI
Chinese journal of integrative medicine 2025;31(12):1113-1118
OBJECTIVE:
To investigate the effect of traditional Chinese Five-body balance exercise on patients with preserved ratio impaired spirometry (PRISm).
METHODS:
Fifteen patients with PRISm and 15 patients diagnosed with chronic obstructive pulmonary disease (COPD) were recruited from the Outpatient Department of Guang'anmen Hospital and Beijing Niujie Health Service Center from April to December, 2023. Participants in both groups attended supervised Five-body balance exercise training twice a week for 12 weeks. Patients with COPD continued their regular medication regimen during the intervention period. The endpoints were mean changes in the 6-min walk test (6MWT), St. George's Respiratory Questionnaire (SGRQ) score, cardiopulmonary exercise testing (CPET), pulmonary function, and scores of COPD assessment test (CAT), modified British Medical Research Council, Self-Rating Anxiety Scale, and Self-Rating Depression Scale from baseline to 12 weeks. Adverse events were monitored throughout the study.
RESULTS:
The PRISm group showed a significant improvement from baseline to week 12 in 6MWT, SGRQ symptom score, and forced vital capacity (FVC) compared to the COPD group (P<0.05). No significant between-group changes were observed in other outcome measurements (P>0.05). In addition, compared with baseline, both groups exhibited improvements in 6MWT, SGRQ score, and CPET at week 12 (P<0.05). The PRISm group also showed a significant increase in forced expiratory volume in 1 s and FVC, as well as a significant decrease in CAT score at week 12 (P<0.05). No adverse events were reported.
CONCLUSION
Patients with PRISm may benefit from Five-body balance exercise training, which can improve the exercise capacity, health-related quality of life, and lung function. (Registration No. ChiCTR2200059290).
Humans
;
Spirometry
;
Male
;
Female
;
Pulmonary Disease, Chronic Obstructive/therapy*
;
Lung/physiopathology*
;
Middle Aged
;
Exercise Tolerance/physiology*
;
Exercise Therapy
;
Aged
;
Medicine, Chinese Traditional
;
Respiratory Function Tests
;
East Asian People

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