Objective:To deeply explore the thematic needs and characteristics of learners regarding course elements based on the review texts of nursing massive open online courses (MOOC), providing a reference for achieving effective alignment between digital nursing education content and learner needs.Methods:Data were collected from the review texts of 112 nursing courses on the Chinese University MOOC platform using a web crawler script written with Python′s Requests library. The collection period spanned from the course launch dates to December 31, 2023. Sentiment analysis and high-frequency words analysis were conducted using Chinese text Nature language processing library, and core themes of learners′ positive and negative reviews were extracted using the latent dirichlet allocation.Results:A corpus of 18 184 nursing MOOC review texts was constructed, with positive sentiment reviews accounting for 89.30% (16 238/18 184) and negative sentiment reviews making up 10.70% (1 946/18 184). Word frequency analysis revealed that most nursing MOOC serve as carriers for blended online and offline teaching models, with students being the primary target audience, though social participants were also involved. The reviews effectively mirrored real-world clinical nursing scenarios. The need of learners was categorized into three major themes: content design and assessment, course resources and teaching strategies, and software applications and platform functionality.Conclusions:This study, leveraging text mining technology, thoroughly investigated the three thematic characteristics of nursing MOOC needs of online learners and proposed targeted optimization recommendations. Future research could incorporate other online teaching platforms and comprehensively construct a sentiment lexicon for nursing online course reviews using big data modeling and machine learning algorithms. These would enable a holistic analysis of the digital nursing education landscape, allowing for precise improvements to address existing shortcomings.

The small intestine is essential for digestion, nutrient absorption, immune regulation, and microbial balance. Its epithelial lining, containing specialized cells like Paneth cells and tuft cells, is crucial for maintaining intestinal homeostasis. Paneth cells produce antimicrobial peptides and growth factors that support microbial regulation and intestinal stem cells, while tuft cells act as chemosensors, detecting environmental changes and modulating immune responses. Along with immune cells such as intraepithelial lymphocytes, innate lymphoid cells, T cells, and macrophages, they form a strong defense system that protects the epithelial barrier. Disruptions in this balance contribute to chronic inflammation, microbial dysbiosis, and compromised barrier function-key features of inflammatory bowel disease, celiac disease, and metabolic syndromes. Furthermore, dysfunctions in the small intestine and immune cells are linked to systemic diseases like obesity, diabetes, and autoimmune disorders. Recent research highlights promising therapeutic strategies, including modulation of epithelial and immune cell functions, probiotics, and gene editing to restore gut health and address systemic effects. This review emphasizes the pivotal roles of small intestinal epithelia and immune cells in maintaining intestinal homeostasis, their involvement in disease development, and emerging treatments for intestinal and systemic disorders.
Humans ; Intestinal Mucosa/cytology* ; Intestine, Small/cytology* ; Animals ; Inflammatory Bowel Diseases/immunology* ; Celiac Disease/immunology* ; Paneth Cells/immunology*

Objective:To deeply explore the thematic needs and characteristics of learners regarding course elements based on the review texts of nursing massive open online courses (MOOC), providing a reference for achieving effective alignment between digital nursing education content and learner needs.Methods:Data were collected from the review texts of 112 nursing courses on the Chinese University MOOC platform using a web crawler script written with Python′s Requests library. The collection period spanned from the course launch dates to December 31, 2023. Sentiment analysis and high-frequency words analysis were conducted using Chinese text Nature language processing library, and core themes of learners′ positive and negative reviews were extracted using the latent dirichlet allocation.Results:A corpus of 18 184 nursing MOOC review texts was constructed, with positive sentiment reviews accounting for 89.30% (16 238/18 184) and negative sentiment reviews making up 10.70% (1 946/18 184). Word frequency analysis revealed that most nursing MOOC serve as carriers for blended online and offline teaching models, with students being the primary target audience, though social participants were also involved. The reviews effectively mirrored real-world clinical nursing scenarios. The need of learners was categorized into three major themes: content design and assessment, course resources and teaching strategies, and software applications and platform functionality.Conclusions:This study, leveraging text mining technology, thoroughly investigated the three thematic characteristics of nursing MOOC needs of online learners and proposed targeted optimization recommendations. Future research could incorporate other online teaching platforms and comprehensively construct a sentiment lexicon for nursing online course reviews using big data modeling and machine learning algorithms. These would enable a holistic analysis of the digital nursing education landscape, allowing for precise improvements to address existing shortcomings.

Objective To discuss the value of clinical radiomic nomogram(CRN)and deep convolutional neural network(DCNN)in distinguishing atypical pulmonary hamartoma(APH)from atypical lung adenocarcinoma(ALA).Methods A total of 307 patients were retrospectively recruited from two institutions.Patients in institu-tion 1 were randomly divided into the training(n=184:APH=97,ALA=87)and internal validation sets(n=79:APH=41,ALA=38)in a ratio of 7∶3,and patients in institution 2 were assigned as the external validation set(n=44:APH=23,ALA=21).A CRN model and a DCNN model were established,respectively,and the performances of two models were compared by delong test and receiver operating characteristic(ROC)curves.A human-machine competition was conducted to evaluate the value of AI in the Lung-RADS classification.Results The areas under the curve(AUCs)of DCNN model were higher than those of CRN model in the training,internal and external validation sets(0.983 vs 0.968,0.973 vs 0.953,and 0.942 vs 0.932,respectively),however,the differences were not statistically significant(p=0.23,0.31 and 0.34,respectively).With a radiologist-AI com-petition experiment,AI tended to downgrade more Lung-RADS categories in APH and affirm more Lung-RADS cat-egories in ALA than radiologists.Conclusion Both DCNN and CRN have higher value in distinguishing APH from ALA,with the former performing better.AI is superior to radiologists in evaluating the Lung-RADS classification of pulmonary nodules.

Objective To explore the value of combined prediction model based on clinical and CT radiomics features in discriminating atypical pulmonary hamartoma(APH)from atypical lung adenocarcinoma(ALA).Methods A total of 290 patients with APH and ALA confirmed by pathology were retrospectively selected.250 patients from the First Affiliated Hospital of Anhui Medical University were randomly assigned into a training set(APH=91,ALA=84)and an internal validation set(APH=39,ALA=36)at a ratio of 7∶3,and other 40 patients from the First Affiliated Hospital of USTC were assigned as an external validation set(APH=21,ALA=19).The independent model and multivariate logistic regression combined model were constructed using the selected clinical-CT features and radiomics features,respectively,and a nomogram was drawn.Receiver operating characteristic(ROC)curve and DeLong test were used to evaluate and compare the performances of the models.Results The area under the curve(AUC)of the combined model established by 3 clinical-CT features and 4 radiomics features in the training set was 0.980,which was higher than that of clinical-CT model(AUC=0.885,P＜0.001)and radiomics model(AUC=0.975,P=0.042).The AUC of the combined model in the internal and external validation sets(0.963 vs 0.917)were also higher than those of clinical-CT model(0.858 vs 0.774)and radiomics model(0.953 vs 0.897),respectively.Conclusion The combined prediction model based on clinical and CT radiomics features can improve the differential diagnosis ability of APH and ALA.

Flavonoid glycosides are the main active constituents of Epimedii Folium and its related plants. They can be divided into polyglycosides and low glycosides according to the number of glycosyl group. The polyglycosides of Epimedii Folium can be transformed into low glycosides after biotransformation ；pharmacological activities of low glycosides in anti-tumor ，tonifying kidney yang and anti-osteoporosis are stronger than those of polyglycosides. In this paper ， the research progress about biotransformation technology of flavonoid glycosides of Epimedii Folium was reviewed. It was found that the main biotransformation pathway of flavonoid glycosides of Epimedii Folium was to obtain low glycosides by removing glycosyl group ； related methods were mainly enzymatic hydrolysis and microbial transformation ，and also included plant cell transformation ，acid hydrolysis method and synthesis method.

To explore influence of exercise rehabilitation therapy on inflammatory factor levels and cardiac func‐tion in patients with chronic heart disease (CHD).Methods :A total of 92 CHF patients of our department from Jun 2016 to May 2018 were randomly and equally divided into routine treatment group and exercise rehabilitation group (received ex‐ercise rehabilitation training based on routine treatment group ) ,both groups were intervened for six months .Cardiac func‐tion ,6min walking distance (6MWD) ,levels of inflammatory factors ,quality of life (QOL) before and after treatment were observed and compared between two groups .Results :Compared with routine treatment group after six months ,there were significant reductions in left ventricular end diastolic volume [LVEDV ,(61.26 ± 8.03) ml vs.(55.77 ± 7.75) ml] , left ventricular end systolic volume [LVESV ,(54.89 ± 6.15) ml vs.(51.36 ± 4.99) ml] ,levels of CRP [(21.41 ± 4.14) ng／ml vs.(18.18 ± 4.22) ng／ml] ,TNF‐α [ (18.46 ± 4.69) ng／ml vs.(15.67 ± 3.37) ng／ml] ,IL‐6 [ (80.09 ± 14.47) ng／ml vs.(71.88 ± 16.16) ng／ml] ,score of Minnesota living with heart failure questionnaire [ (49.50 ± 6.91) scores vs. (46.74 ± 5.12) scores] ,and significant rise in LVEF [ (43.11 ± 4.59)% vs.(45.33 ± 5.58)%] and 6MWD [ (265.70 ± 12.37) m vs.(336.89 ± 11.23) m] in exercise rehabilitation group , P＜0.05 or ＜0.01. Conclusion :Exercise rehabilita‐tion therapy can significantly improve inflammatory factor levels ,cardiac function and QOL ,and reduce rehospitalization rate within six months in CHF patients .

Objective To understand the job well-being status of ICU nurses,and to explore the mediating role of psychological capital in job stress and job well-being.Methods ICU nurses'general data questionnaire,the Nurse Questionnaire Psychological Capital,Chinese Nurses' Work Stressor Scale and Work Well-Being Scale were used to investigate 224 ICU nurses in three grade a general hospitals.Results Total score of psychological capital for ICU nurses was(4.46±0.55)points,the total average working pressure was(2.14±0.37)points,the happiness score was(4.36±0.67)points.Psychological capital and job well-being were positively correlated(r=0.513,P＜0.01),job stress and job well-being was negatively correlated(r =-0.454,P＜ 0.05).The structural equation results showed that psychological capital played an intermediary role in the sense of ICU nurses job stress and job happiness.Conclusions Hospital nursing managers should pay more attention to the mental health of ICU nurses and lower their work stress,so as to improve the work well-being of ICU nurses and improve the quality of ICU nursing.

Objective To investigate the relationship between plasma docetaxel concentration and the efficacy as well as toxic and side effects in patients with breast cancer after chemotherapy.Methods Seventy -one patients with breast cancer who accepted AC sequential T chemotherapy regimen as first line treatment were selected from April 2015 to September 2015 in Hubei Provicial Tumor Hospital.The plasma concentration of docetaxel was detected by latex immunoturdidimetry after the docetaxel continuous infusion in each cycle.The three groups were assigned according to the concentration distribution of docetaxel:group A (plasma concentration docetaxel ≤ 2.0mg·h -1 · L -1 ),group B (2.1 -2.5mg·h -1 ·L -1 )and group C (≥2.6 mg·h -1 ·L -1 ).The relationship between the drug plasma concentration,therapeutic efficacy and adverse reactions in different docetaxel plasma concentration was analyzed retrospectively by Chi -square tests.Results The average plasma concentrations of docetaxel of the three groups were (1.55 ±0.36)mg·h -1 ·L -1 ,(2.28 ±0.13)mg·h -1 ·L -1 ,(2.87 ±0.38)mg· h -1 · L -1 respectively.The adverse reactions were enhanced with the increasing of docetaxel plasma concentration (χ2 =5.169, 4.463,3.630,P =0.023,0.035,0.047).The therapeutic efficacy of group C and group B was same(95.8%),which was higher than 87.0% of group A,but there was no statistically significant difference (χ2 =1.559,P =0.24). Conclusion Breast cancer patients whose plasma concentration of docetaxel is between 2.1 ~2.5mg·h -1 ·L -1 has a better prognosis,and its adverse reactions are controlled in a certain extent.

Objectives To investigate the relationship of sex difference with serum bisphenol-A (BP-A),adiponectin and metabolic syndrome (MetS)in elderly patients with isolated systolic hypertension(EISH).Methods A retrospective study of the clinical data was conducted in 540 subjects from the Cardiology and Geriatric Department in the Affiliated Hospital of Shanxi Medical University,Changzhi Municipal People,s Hospital and the Department of Cardiology of Shanxi Medical University,First Clinic Hospital from January 2010 to December 2013.Elderly patients with EISH were divided into male group(n=270)and female group(n=270).Meanwhile 560 older health persons were severed as controls,including 300 females and 260 males.The changes of BP-A and adiponectin (Ad) concentration were measured.The blood lipid,insulin resistance index (HOMA-IR),blood pressure,body mass index,heart rate variability and ultrasonic change of heart and blood vessel were tested regularly.Results The level of serum BP-A[(0.89±0.10)ng/L vs.(0.57±0.04)ng/L]and [(0.64±0.10)ng/L vs.(0.55 ± 0.08)ng/L] were higher in male EISH vs in male control,and in female EISH than in female control (F =23.76,23.86,all P ＜ 0.01),respectively.The levels of adiponectin were lower in male EISH vs control[(4.9±1.4)ng/L vs.(10.5±2.7)ng/L and in female EISH vs control(6.0±1.3) ng/L vs.(11.5±3.3)ng/L),F=13.10,16.20,all P＜0.01.Root mean sequare of the successive normal sinus RR interval difference(rMSSD)were lower in male/ female EISH than control groups(F=13.10、13.70,P ＜0.01).Serum BP-A level was positively correlated with the bocly mass index and systolic pressure (r =0.38,0.54,P ＜ 0.01),and was negatively correlated with serum Ad and rMSSD(r=-0.46,-0.42,P＜0.01).Conclusions Obvious gender difference in changes of serum BP-A exists in older patients with EISH.Network cytokines may take part in the pathophysiological process of the obesity related hypertension.