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.Research on Detection Method for Constituent Content of Fresh Tea Leaf Based on Residual Attention Convolutional Neural Network
Hai-Liang ZHANG ; Yan ZHOU ; Wei LUO ; Bai-Shao ZHAN ; Jing ZHANG ; Xue-Mei LIU
Chinese Journal of Analytical Chemistry 2025;53(5):842-851
The rapid and non-destructive detection of constituent content of fresh tea leaves shows an important reference value for quality identification of tea.Visible near infrared(Vis-NIR)spectroscopy has been used for qualitative and quantitative analysis of chemical components in plant samples with the advantages such as simple,rapid and non-destructive detection.In this study,residual attention convolutional neural network(RACNN)was used to predict the internal constituent content of fresh tea leaves.Firstly,the reflectance spectral data of the samples in the Vis-NIR band range and the constituent contents of gallic acid(GA),gallocatechin(GC),epigallocatechin(EGC),and epigallocatechin gallate(ECG)in fresh tea leaves were collected.Based on the preprocessing of the spectral data,the contents of the four components were predicted using a partial least squares regression(PLSR)model,and the optimal preprocessing was determined.Subsequently,the characteristic bands were extracted using the random forest(RF)algorithm.Finally,the performances of PLSR,convolutional neural network(CNN)and RACNN models were compared.The results showed that for GA,the RACNN model worked best with a validation set coefficient of determination(R2)of 0.946 and a root mean square error of the prediction set(RMSEP)of 1.173;for GC,the RACNN model works best with a validation set R2 of 0.928 and RMSEP of 6.081;for EGC,the RACNN model works best with a validation set R2 of 0.891 and a RMSEP of 15.197;for ECG,the RACNN model worked best with a validation set R2 of 0.878 and a RMSEP of 7.837.The RACNN model established by Vis-NIR spectroscopy combined with chemometrics could realize the accurate detection of the contents of components in fresh tea.
3.Evaluation of the performance of the artificial intelligence - enabled snail identification system for recognition of Oncomelania hupensis robertsoni and Tricula
Jihua ZHOU ; Shaowen BAI ; Liang SHI ; Jianfeng ZHANG ; Chunhong DU ; Jing SONG ; Zongya ZHANG ; Jiaqi YAN ; Andong WU ; Yi DONG ; Kun YANG
Chinese Journal of Schistosomiasis Control 2025;37(1):55-60
Objective To evaluate the performance of the artificial intelligence (AI)-enabled snail identification system for recognition of Oncomelania hupensis robertsoni and Tricula in schistosomiasis-endemic areas of Yunnan Province. Methods Fifty O. hupensis robertsoni and 50 Tricula samples were collected from Yongbei Township, Yongsheng County, Lijiang City, a schistosomiasis-endemic area in Yunnan Province in May 2024. A total of 100 snail sample images were captured with smartphones, including front-view images of 25 O. hupensis robertsoni and 25 Tricula samples (upward shell opening) and back-view images of 25 O. hupensis robertsoni and 25 Tricula samples (downward shell opening). Snail samples were identified as O. hupensis robertsoni or Tricula by schistosomiasis control experts with a deputy senior professional title and above according to image quality and morphological characteristics. A standard dataset for snail image classification was created, and served as a gold standard for recognition of snail samples. A total of 100 snail sample images were recognized with the AI-enabled intelligent snail identification system based on a WeChat mini program in smartphones. Schistosomiasis control professionals were randomly sampled from stations of schistosomisis prevention and control and centers for disease control and prevention in 18 schistosomiasis-endemic counties (districts, cities) of Yunnan Province, for artificial identification of 100 snail sample images. All professionals are assigned to two groups according the median years of snail survey experiences, and the effect of years of snail survey experiences on O. hupensis robertsoni sample image recognition was evaluated. A receiver operating characteristic (ROC) curve was plotted, and the sensitivity, specificity, accuracy, Youden’s index and the area under the curve (AUC) of the AI-enabled intelligent snail identification system and artificial identification were calculated for recognition of snail sample images. The snail sample image recognition results of AI-enabled intelligent snail identification system and artificial identification were compared with the gold standard, and the internal consistency of artificial identification results was evaluated with the Cronbach’s coefficient alpha. Results A total of 54 schistosomiasis control professionals were sampled for artificial identification of snail sample image recognition, with a response rate of 100% (54/54), and the accuracy, sensitivity, specificity, Youden’s index, and AUC of artificial identification were 90%, 86%, 94%, 0.80 and 0.90 for recognition of snail sample images, respectively. The overall Cronbach’s coefficient alpha of artificial identification was 0.768 for recognition of snail sample images, and the Cronbach’s coefficient alpha was 0.916 for recognition of O. hupensis robertsoni snail sample images and 0.925 for recognition of Tricula snail sample images. The overall accuracy of artificial identification was 90% for recognition of snail sample images, and there was no significant difference in the accuracy of artificial identification for recognition of O. hupensis robertsoni (86%) and Tricula snail sample images (94%) (χ2 = 1.778, P > 0.05). There was no significant difference in the accuracy of artificial identification for recognition of snail sample images with upward (88%) and downward shell openings (92%) (χ2 = 0.444, P > 0.05), and there was a significant difference in the accuracy of artificial identification for recognition of snail sample images between schistosomiasis control professionals with snail survey experiences of 6 years and less (75%) and more than 6 years (90%) (χ2 = 7.792, P < 0.05). The accuracy, sensitivity, specificity and AUC of the AI-enabled intelligent snail identification system were 88%, 100%, 76% and 0.88 for recognition of O. hupensis robertsoni snail sample images, and there was no significant difference in the accuracy of recognition of O. hupensis robertsoni snail sample images between the AI-enabled intelligent snail identification system and artificial identification (χ2 = 0.204, P > 0.05). In addition, there was no significant difference in the accuracy of artificial identification for recognition of snail sample images with upward (90%) and downward shell openings (86%) (χ2 = 0.379, P > 0.05), and there was a significant difference in the accuracy of artificial identification for recognition of snail sample images between schistosomiasis control professionals with snail survey experiences of 6 years and less and more than 6 years (χ2 = 5.604, Padjusted < 0.025). Conclusions The accuracy of recognition of snail sample images is comparable between the AI-enabled intelligent snail identification system and artificial identification by schistosomiasis control professionals, and the AI-enabled intelligent snail identification system is feasible for recognition of O. hupensis robertsoni and Tricula in Yunnan Province.
4.Prediction of PD-1 monoclonal antibody human pharmacokinetic characteristics based on PK in cynomolgus monkeys
Yanjun XU ; Zijun HAN ; Liang WANG ; Fang YANG ; Beilei LOU ; Shaoyu YAN ; Jiman ZHU ; Lihui BAI ; Yong GAO
Chinese Journal of Pharmacology and Toxicology 2025;39(2):109-117
OBJECTIVE To establish a population pharmacokinetic(PopPK)model to predict the PK characteristics of GLS-010 in humans.METHODS Fifty-eight cynomolgus monkeys were used,18 of which were randomly divided into three groups and received a single intravenous infusion of GLS-010 at doses of 2,6,and 18 mg·kg-1,respectively.The rest were randomly assigned to four groups and received multiple intravenous infusions of GLS-010 at doses of 0,5,25,and 100 mg·kg-1,respectively,once a week(quaque week,qw)for five consecutive weeks.Blood samples were collected before and after administration.The concentrations of GLS-010 in the monkey serum were measured using a validated enzyme-linked immunosorbent assay,while those of anti-drug antibodies(ADA)in the cynomolgus monkey serum were determined by ultra-sensitive electrochemiluminescence immunoassay.The PK data on GLS-010 in cynomolgus monkeys was obtained,and the drug-time curves were plotted.A PopPK model was constructed using non-compartmental analysis and evaluated by goodness-of-fit plots and visual predictive checks.The constructed PopPK model was used to predict the PK characteristics in humans,which were finally compared with actual Phase Ⅰ clinical study results for validation.RESULTS The predictive results of the PopPK model were highly consistent with the actual Phase Ⅰ clinical study results.The model was able to predict the human PK characteristics under various dosing regimens,including 1 mg·kg-1 quaque 2 weeks(q2w),4 mg·kg-1(q2w),240 mg(q2w),240 mg(q3w),and 10 mg·kg-1(q2w).The predicted maximum plasma concentrations(Cmax)were 24.8,99.1,85.0,85.0,and 247.8 mg·L-1,respectively,and the AUC0-336h was 4 902.0,20 060.0,17 147.7,22 145.7(AUC0-504h),and 50 817.6 mg·h·L-1,respectively.The safety risks for the corresponding dosing regimens were 47.3,11.6,13.5,10.5,and 4.6,respectively.The predicted receptor occupancy at steady state(ROss)at Cmax,average plasma concentration(Cavg),and minimum plasma concentration(Cmin)were 38.8%,72.7%,69.4%,64.1%and 87.2%,29.1%,63.8%,60.0%,49.8%and 82.1%,21.9%,55.5%,51.3%,36.3%and 76.7%,respectively.CONCLUSION The PopPK model can effectively predict the human PK characteristics under different dosing regimens with high consistency with actual Phase Ⅰ clinical study results,which can serve as an important reference for selection of safe and effective doses for first-in-human research.
5.Ultrasonography in Diagnosing Incarcerated Gravid Uterus
Tao YUAN ; Yan BAI ; Rong LIANG ; Yuying TANG ; Wenming JIANG
Chinese Journal of Medical Imaging 2025;33(8):867-871
Purpose To analyze the sonographic features of incarcerated gravid uterus and evaluate the diagnostic value of ultrasonography.Materials and Methods Clinical data of eight patients diagnosed with incarcerated gravid uterus at Sichuan Provincial Maternity and Child Health Care Hospital from January 2018 to December 2023 were retrospectively analyzed.Clinical manifestations,sonographic characteristics,management approaches and pregnancy outcomes were evaluated.Results Among the eight confirmed cases,seven presented with initial symptoms of dysuria and urinary retention,while one reported irregular lower abdominal pain.Ultrasonography consistently demonstrated:retroverted and retroflexed uterine position with the uterine body posterior to the cervix.Elongated cervix(range:4.0-8.6 cm)displaced anteriorly.Overdistended,elongated and superiorly displaced bladder in seven cases.Management included successful manual reduction via knee-chest position after catheterization in seven patients.One patient was managed conservatively with close monitoring and delivered by cesarean section at term.All eight patients achieved successful term deliveries with favorable maternal and neonatal outcomes.Conclusion Prenatal ultrasonography plays a crucial role in diagnosing and managing incarcerated gravid uterus.Early recognition of characteristic sonographic features facilitates prompt diagnosis and intervention,thereby mitigating risks of adverse pregnancy outcomes.
6.Machine learning model for prediction of bloodstream infections established based on routine test indexes and its predictive efficiency
Yan WANG ; Xin HE ; Yufang LIANG ; Gaixian WANG ; Ruifeng BAI ; Rui ZHOU
Chinese Journal of Nosocomiology 2025;35(10):1542-1548
OBJECTIVE To explore and evaluate the machine learning model for prediction of bacterial bloodstream infections established based on routine test data.METHODS By means of retrospective survey,a total of 5 421 pa-tients who were hospitalized in 3 medical institutions from Jan.2015 to Dec.2022 were recruited as the research subjects,1 914 of whom were assigned as the bloodstream infection group,and 3 507 were assigned as the non-bloodstream infection group.The baseline data including gender and age and the results of routine laboratory tests were collected from the enrolled patients.The 3 types of machine learning algorithms,logistic regression,support vector machine and random forest,were respectively used for the screening of the optimal prediction model;the contribution of feature variables to the predictive capability of the model was interpreted through SHAP.The fea-ture variables of the model were optimized by using recursive feature elimination method,and the predictive effi-ciency of the model was evaluated by the area under the curve(AUC)of receiver operating characteristic(ROC)curves.RESULTS Totally 26 variables involving age,gender and blood routine test indexes were included.The random forest was chosen as the optimal machine learning algorithm for the establishment of prediction model for bloodstream infections,and the accuracy of the model was 0.709,with the AUC 0.706.The result of SHAP ex-planation indicated that the age,hematokrit and erythrocyte volume distribution width-CV had remarkable effect on the model's making right decisions.17 variables of the prediction model showed more remarkable effect than 26 variable on distinguishing from the gram-positive bacteria bloodstream infections from the gram-negative bacteria bloodstream infections,with the AUC 0.715,the sensitivity 0.701,the specificity 0.632.CONCLUSIONS The prediction model that is established based on the blood routine test indexes by machine learning algorithm can pre-dict the bacterial bloodstream infection.Meanwhile,the feature selection strategy can further improve the predic-tive efficiency of the model on basis of lowering the dimensionality.
7.The application of surgical robots in head and neck tumors.
Xiaoming HUANG ; Qingqing HE ; Dan WANG ; Jiqi YAN ; Yu WANG ; Xuekui LIU ; Chuanming ZHENG ; Yan XU ; Yanxia BAI ; Chao LI ; Ronghao SUN ; Xudong WANG ; Mingliang XIANG ; Yan WANG ; Xiang LU ; Lei TAO ; Ming SONG ; Qinlong LIANG ; Xiaomeng ZHANG ; Yuan HU ; Renhui CHEN ; Zhaohui LIU ; Faya LIANG ; Ping HAN
Journal of Clinical Otorhinolaryngology Head and Neck Surgery 2025;39(11):1001-1008
8.Association of Body Mass Index with All-Cause Mortality and Cause-Specific Mortality in Rural China: 10-Year Follow-up of a Population-Based Multicenter Prospective Study.
Juan Juan HUANG ; Yuan Zhi DI ; Ling Yu SHEN ; Jian Guo LIANG ; Jiang DU ; Xue Fang CAO ; Wei Tao DUAN ; Ai Wei HE ; Jun LIANG ; Li Mei ZHU ; Zi Sen LIU ; Fang LIU ; Shu Min YANG ; Zu Hui XU ; Cheng CHEN ; Bin ZHANG ; Jiao Xia YAN ; Yan Chun LIANG ; Rong LIU ; Tao ZHU ; Hong Zhi LI ; Fei SHEN ; Bo Xuan FENG ; Yi Jun HE ; Zi Han LI ; Ya Qi ZHAO ; Tong Lei GUO ; Li Qiong BAI ; Wei LU ; Qi JIN ; Lei GAO ; He Nan XIN
Biomedical and Environmental Sciences 2025;38(10):1179-1193
OBJECTIVE:
This study aimed to explore the association between body mass index (BMI) and mortality based on the 10-year population-based multicenter prospective study.
METHODS:
A general population-based multicenter prospective study was conducted at four sites in rural China between 2013 and 2023. Multivariate Cox proportional hazards models and restricted cubic spline analyses were used to assess the association between BMI and mortality. Stratified analyses were performed based on the individual characteristics of the participants.
RESULTS:
Overall, 19,107 participants with a sum of 163,095 person-years were included and 1,910 participants died. The underweight (< 18.5 kg/m 2) presented an increase in all-cause mortality (adjusted hazards ratio [ aHR] = 2.00, 95% confidence interval [ CI]: 1.66-2.41), while overweight (≥ 24.0 to < 28.0 kg/m 2) and obesity (≥ 28.0 kg/m 2) presented a decrease with an aHR of 0.61 (95% CI: 0.52-0.73) and 0.51 (95% CI: 0.37-0.70), respectively. Overweight ( aHR = 0.76, 95% CI: 0.67-0.86) and mild obesity ( aHR = 0.72, 95% CI: 0.59-0.87) had a positive impact on mortality in people older than 60 years. All-cause mortality decreased rapidly until reaching a BMI of 25.7 kg/m 2 ( aHR = 0.95, 95% CI: 0.92-0.98) and increased slightly above that value, indicating a U-shaped association. The beneficial impact of being overweight on mortality was robust in most subgroups and sensitivity analyses.
CONCLUSION
This study provides additional evidence that overweight and mild obesity may be inversely related to the risk of death in individuals older than 60 years. Therefore, it is essential to consider age differences when formulating health and weight management strategies.
Humans
;
Body Mass Index
;
China/epidemiology*
;
Male
;
Female
;
Middle Aged
;
Prospective Studies
;
Rural Population/statistics & numerical data*
;
Aged
;
Follow-Up Studies
;
Adult
;
Mortality
;
Cause of Death
;
Obesity/mortality*
;
Overweight/mortality*
9.Non-invasive Modulation of Deep Brain Nuclei by Temporal Interference Stimulation.
Long LI ; Hao BAI ; Linyan WU ; Liang ZHENG ; Liang HUANG ; Yang LI ; Wenlong ZHANG ; Jue WANG ; Shunnan GE ; Yan QU ; Tian LIU
Neuroscience Bulletin 2025;41(5):853-865
Temporal interference (TI) is a form of stimulation that epitomizes an innovative and non-invasive approach for profound neuromodulation of the brain, a technique that has been validated in mice. Yet, the thin cranial bone structure of mice has a marginal influence on the effect of the TI technique and may not effectively showcase its effectiveness in larger animals. Based on this, we carried out TI stimulation experiments on rats. Following the TI intervention, analysis of electrophysiological data and immunofluorescence staining indicated the generation of a stimulation focus within the nucleus accumbens (depth, 8.5 mm) in rats. Our findings affirm the viability of the TI methodology in the presence of thick cranial bones, furnishing efficacious parameters for profound stimulation with TI administered under such conditions. This experiment not only sheds light on the intervention effects of TI deep in the brain but also furnishes robust evidence in support of its prospective clinical utility.
Animals
;
Deep Brain Stimulation/methods*
;
Nucleus Accumbens/physiology*
;
Male
;
Rats
;
Rats, Sprague-Dawley
;
Time Factors
10.Measurement of intervertebral disc height and analysis of strength after induced resorption of herniated nucleus pulpous
Liang BAI ; Su FU ; Xu YAN ; Chunlin ZHANG ; Ying LI
Chinese Journal of Tissue Engineering Research 2025;29(27):5785-5794
BACKGROUND:Induced resorption of herniated nucleus pulpous is a minimally invasive,non-invasive and innovative method for the treatment of cervical/lumbar intervertebral disc herniation.After induced resorption of herniated nucleus pulpous,the research about whether cervical/lumbar intervertebral disc can maintain the original biomechanical strength has not been reported.OBJECTIVE:To measure the height of adjacent vertebral centroid of cervical/lumbar intervertebral disc before and after induced resorption of herniated nucleus pulpous operation to analyze the changes of the biomechanical strength of the intervertebral disc after reclining and to provide a new basis for induced resorption of herniated nucleus pulpous treatment of cervical and lumbar intervertebral disc herniation.METHODS:A retrospective analysis was performed on 140 patients with cervical/lumbar intervertebral disc herniation who received induced resorption of herniated nucleus pulpous surgery in the First Affiliated Hospital of Zhengzhou University from January 2013 to January 2023.Related software was used to measure the height of adjacent vertebral centroid of cervical/lumbar intervertebral disc of patients at each follow-up time point before and after induced resorption of herniated nucleus pulpous surgery in Magnetic Resonance Imaging image data under Artificial Intelligence-assisted calibration.Unoperated T1/T2 and T12/L1 segments were taken respectively as controls.Those with preoperative height of adjacent vertebral centroid less than 8%of the corresponding T1/T2 or T12/L1 control segment were in the"height reduction group"(hereafter referred to as group A)and the rest were in the"height unchanged group"(hereafter referred to as group B).The difference of height of adjacent vertebral centroid before and after operation between the group A and the group B was statistically analyzed.Simultaneously,the correlation between the volume of cervical and lumbar herniated discs and the changes of height of adjacent vertebral centroid was analyzed according to the result measured by artificial intelligence.RESULTS AND CONCLUSION:(1)The study maintained a total of 140 patients,including 60 cases of cervical disc herniation and 80 cases of lumbar disc herniation.The postoperative follow-up period was 7 days to 12 months.(2)A total of 281 discs were measured in the cervical vertebra group,including 60 intervertebral discs in the control group.The mean value of height of adjacent vertebral centroid before and at the last postoperative follow-up was about 20.46 mm and 20.17 mm,respectively,with no statistical difference(P>0.05).There were 162 cervical discs in group A.The average height of adjacent vertebral centroid before and after operation was 16.65 mm and 15.92 mm,respectively,with no statistically significant difference(P>0.05).The mean cervical disc herniation volume before and after surgery was 510.28 mm3 and 364.76 mm3,respectively,which was not significantly correlated with height of adjacent vertebral centroid change(P>0.05).There were 64 discs in the group B,with average of 20.15 mm before operation and 19.09 mm at the last follow-up,and there was no significant difference(P>0.05).The mean volume of cervical disc herniation before and after surgery was 515.32 mm3 and 361.98 mm3,respectively,and there was no significant correlation with the change of height of adjacent vertebral centroid(P>0.05).(3)A total of 258 discs were measured in the lumbar spine group,of which 80 intervertebral discs in the control group,the average height of adjacent vertebral centroid was 33.03 mm before operation and 32.40 mm at the last follow-up,and there was no significant difference.There were 59 discs in the group A,and the average height of adjacent vertebral centroid before and after operation was 30.08 mm and 31.67 mm,respectively,with no statistically significant difference.The mean volume of lumbar disc herniation before and after operation was 690.51 mm3 and 496.58 mm3,respectively,and there was no significant correlation with the change of height of adjacent vertebral centroid(P>0.05).There were 119 discs in the group B,with an average height of adjacent vertebral centroid of 35.91 mm before surgery and 34.12 mm at the last follow-up.The mean volume of lumbar disc herniation before and after operation was 698.70 mm3 and 535.99 mm3,respectively,and there was no significant correlation with the change of height of adjacent vertebral centroid.(4)It is concluded that patients with cervical/lumbar intervertebral disc herniation can maintain the same intervertebral height level after induced resorption of herniated nucleus pulpous regardless of whether the intervertebral height has decreased before operation.It can be inferred that the resorption of the herniated disc does not affect its biomechanical strength.It suggests that induced resorption of herniated nucleus pulpous surgery should be performed before the intervertebral height of the degenerate segment has decreased.The induced resorption of herniated nucleus pulpous is more valuable to maintain the biomechanical strength of the resorptive disc.

Result Analysis
Print
Save
E-mail