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.

POEMS syndrome is a rare condition associated with plasma cell disorders， and it often involves multiple systems and has diverse clinical manifestations. This article reports two cases of POEMS syndrome with hepatosplenomegaly as the initial manifestation. During the course of the disease， the patients presented with lower limb weakness， hepatosplenomegaly， lymph node enlargement， ascites， hypothyroidism， positive M protein， and skin hyperpigmentation， and ¹⁸F-FDG PET-CT imaging revealed bone lesions mainly characterized by osteolytic changes and plasma cell tumors. There was an increase in the serum level of vascular endothelial growth factor. The patients were finally diagnosed with POEMS syndrome， and the symptoms were relieved after immunomodulatory treatment.

Objective:To explore the predictive value of models based on clinical parameters, deep learning radiomics (DLR) from CT images, and traditional handcrafted radiomics (HCR) in assessing pathological complete response (pCR) after neoadjuvant radiotherapy combined with medical therapy in patients with esophageal cancer.Methods:A retrospective study was conducted on 130 patients with locally advanced esophageal cancer who underwent neoadjuvant radiotherapy combined with medical therapy followed by surgery at the First Affiliated Hospital of the University of Science and Technology of China from August 1, 2018, to August 31, 2024. Patients were randomly divided into a training set ( n=91) and a validation set ( n=39) at a ratio of 7:3. Logistic regression analysis was performed to identify clinical independent risk factors associated with pCR. DLR and HCR features were extracted from the tumor and the 5 mm peritumoral region on planning CT images. Features for modeling were selected using t-test, Mann-Whitney U test or Fisher exact probability method, least absolute shrinkage and selection operator (LASSO) regression to calculate the radiomics score (Rad-score). A nomogram was then constructed by integrating the clinical risk factors. The predictive performance of each model was evaluated using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, and decision curve analysis (DCA) to assess clinical benefits. Results:Multivariate logistic regression analysis identified body weight ( OR=1.101, 95% CI: 1.029-1.177, P=0.005) and lymph node positivity ( OR=0.100, 95% CI: 0.014-0.727, P=0.023) as independent predictors of pCR. The peritumoral DLR-HCR model showed superior predictive performance, with AUCs of 0.870 (95% CI: 0.799-0.942) in the training set and 0.866 (95% CI: 0.750-0.982) in the validation set. The combined model incorporating clinical parameters achieved the best performance, with AUCs of 0.903 (95% CI: 0.845-0.962) and 0.888 (95% CI: 0.782-0.994) in the training and validation sets, respectively. Conclusions:The combined model integrating peritumoral DLR-HCR features with clinical parameters provides excellent predictive value for pCR after neoadjuvant radiotherapy combined with medical therapy in esophageal cancer and offers valuable guidance for personalized treatment strategies.

Circular RNAs (circRNAs) are a type of endogenous noncoding RNAs with covalently looped structures. Compared with other noncoding RNAs, circRNAs have the characteristics of stable structures, high abundance and tissue-specific expression. Recent studies have demonstrated that circRNAs can act as sponges, decoys and scaffolds for microRNAs and proteins, and play an important role in skin tumors. This review summarizes recent advances in the functions and mechanisms of action of circRNAs in common skin tumors, in order to understand the way in which they affect skin tumors, and to assess the value of further research on them.

This study aims to explore protective effects of Lycium barbarum polysaccharides(LBP)on intestinal damage caused by lipopolysaccharide(LPS)-induced inflammatory bowel disease(IBD)in chicks.Network pharmacology was initially employed to determine the target proteins of wolfberry in the prevention and treatment of IBD.Following this,protein-protein interaction analy-sis,GO and KEGG pathway enrichment analysis,and molecular docking studies were conducted.Subsequently,an animal study was conducted:a total of 100 one-day-old male Hy-line brown lay-ing hens were randomly divided into five groups:a blank control group(CON),an LPS treatment group(LPS),a low-dose LBP group(LPS+LBP 0.25 g/L,L-LBP),a medium-dose LBP group(LPS+LBP 0.5 g/L,M-LBP),and a high-dose LBP group(LPS+LBP 1 g/L,H-LBP).Upon reac-hing 21 days old,duodenal,jejunal,ileal,and cecal tissues were collected to determine SOD and GSH-Px levels.Furthermore,the mRNA expression levels of TNF-α,AKT1,IL-6,IL-1β and TP53 in the intestinal tissues were measured using quantitative real-time PCR.The results demonstrated that network pharmacology identified 45 active ingredients in wolfberry that target 116 key protein sites,including TNF,AKT1 and IL6.The primary objectives focus on signaling pathways including AGE-RAGE,IL-17,TNF,HIF-1,and NF-κB.Molecular docking showed excellent ligand-receptor docking scores,with stable binding facilitated by hydrogen bonds and hydrophobic interactions.Compared to the LPS group,the 0.5 g/L LBP exhibited notably higher levels of SOD and T-AOC.In comparison with the LPS group,the medium and high-dose LBP experimental groups showed notably decreased the mRNA expressions of TNF-α,AKT1,IL-6,and IL-1β,while TP53 mRNA expression was significantly upregulated(P＜0.01).In summary,wolfberry exerts preventive and therapeutic effects on IBD through a multi-component,multi-target,and multi-pathway mecha-nism.

Objective: To investigate the expressions of GPR15 and FOXP3 in colorectal carcinoma(CRC) tissues and their clinical prognostic values. Methods : A total of 132 patients with CRC underwent radical surgery were collected. The control group selected the normal mucosal tissues more than 5 cm away from the edge of the cancer focus. Immunohistochemistry(Envision two-step method) was used to detect the expression levels of GPR15 and FOXP3 in CRC and adjacent tissues, and analyze their relationships with clinicopathological factors of colorectal cancer. Kaplan-Meier method was used to draw the survival curve to analyze the correlation between the expressions of GPR15 and FOXP3 and the survival prognosis of patients with CRC. The factors influencing prognosis of patients with colorectal cancer were analyzed by Cox regression. Results : The immunohistochemistry showed that the expression levels of GPR15 and FOXP3 in CRC were significantly higher than those in normal colorectal mucosal tissues(P<0.05). The expression of GPR15 in CRC tissues was correlated with location, nerve invasion and TNM stage; FOXP3 expression was correlated with sex(P<0.05).Both expressions were not significantly correlated with the clinicopathologic features of age, tumor size, differentiation degree, tissue type, depth of invasion, tumor budding, vascular invasion and lymph node metastasis. Correlation analysis showed that there was no significant correlation between GPR15 and FOXP3 expression(Kappa=-0.019,P>0.05). The survival prognosis of GPR15 positive group was significantly worse than that of negative group(log-rank: χ2=4.3,P=0.039);while the survival prognosis of FOXP3 positive group was significantly better than that of negative group(log-rank: χ2=7.3,P=0.007).Age ≤55 years, positive GPR15 and negative FOXP3 were independent risk factors for poor prognosis in patients with CRC(P<0.05). Conclusion The expression levels of GPR15 and FOXP3 in CRC are significantly higher than those in paracancer tissues, GPR15 and FOXP3 are expected to become new tumor markers for early screening, accurate treatment and prognosis assessment of CRC.

Objective To develop a machine learning model integrating preoperative chest CT radiomic features with clinical data for predicting 5-year postoperative recurrence risk in stage Ⅰ non-small cell lung cancer(NSCLC)patients undergoing surgical resection.Methods A total of 217 patients with pathologically confirmed stage Ⅰ NSCLC(selected from 778 initially screened cases based on our inclusion and exclusion criteria)treated in Army Medical Center of PLA between January 2014 and December 2019 were retrospectively enrolled,including 53 recurrence cases and 164 non-recurrence cases within 5-year follow-up.They were randomly divided into a training set(n=173)and a validation set(n=44)in a ratio of 8:2.Radiomic models were established based on extracted features from tumor-dominant regions of interest(ROI)on CT images,while clinical models were developed using demographic characteristics and preoperative laboratory examinations.A combined model was further constructed by integrating both feature sets,and model performance was compared to identify the optimal predictive model.Results This study screened the features from non-contrast CT images and ultimately selected 7 radiomic features for constructing radiomic model.Among 6 machine learning algorithms,the adaptive boosting(Adaboost)model demonstrated the best overall predictive performance,with an area under the curve(AUC)of 0.866(95%CI:0.808～0.923;accuracy:0.832,specificity:0.884)in the training set and of 0.806(95%CI:0.630～0.983;accuracy:0.795,specificity:0.971)in the validation set.Univariate and multivariate logistic regression analyses identified 4 clinical features for clinical model construction.The clinical model achieved an AUC value of 0.874(95%CI:0.821～0.928;accuracy:0.827,specificity:0.891)in the training set and 0.813(95%CI:0.677～0.948;accuracy:0.636,specificity:0.600)in the validation set.By integrating the 7 radiomic features and 4 clinical features using a feature-level fusion strategy,the combined model exhibited further improved predictive performance,with an AUC value of 0.953(95%CI:0.924～0.983;accuracy:0.884,specificity:0.860)and 0.852(95%CI:0.729～0.976;accuracy:0.682,specificity:0.629),respectively in the training set and the validation set.Conclusion The combined model integrating preoperative CT radiomic features with clinical risk factors may provide an evidence-based framework for evaluating 5-year postoperative recurrence risk in stage Ⅰ NSCLC patients.

Objective:To investigate the correlation between the neutrophil-to-lymphocyte ratio (NLR), monocyte-to-high-density lipoprotein cholesterol ratio (MHR), and cardiovascular calcification in patients on maintenance hemodialysis (MHD), and to evaluate their predictive value for cardiovascular calcification.Methods:This retrospective case-control analysis was conducted on the clinical data of 362 patients with chronic kidney disease who underwent regular hemodialysis for >3 months at the Hemodialysis Center of the Second People′s Hospital of Hefei from December 2018 to December 2023. Patients were divided into a cardiovascular calcification group (216 cases) and a cardiovascular non-calcification group (146 cases). The cardiovascular calcification group was further categorized according to different calcification sites, with 69 cases in the vascular calcification group, 79 in the valve calcification group, and 68 in the vascular and valve calcification group. Spearman correlation analysis was used to assess the correlation between cardiovascular calcification and various indicators. Risk factors for cardiovascular calcification in patients with MHD were analyzed using binary logistic regression analysis. The predictive value of the NLR and MHR for cardiovascular calcification was analyzed using the receiver operating characteristic (ROC) curve.Results:This study enrolled 362 cases, including 233 males and 129 females aged 29-89 years. Age, the NLR, and the MHR were positively correlated with cardiovascular calcification in patients on MHD ( r=0.338, 0.383, and 0.391, respectively, all P<0.05). In contrast, serum magnesium was negatively correlated with cardiovascular calcification ( r=-0.169, P<0.05). Age ( OR=1.063, 95% CI 1.036-1.092, P<0.001), male sex ( OR=2.017, 95% CI 1.104-3.685, P=0.023), neutrophil count ( OR=1.737, 95% CI 1.326-2.276, P<0.001), the NLR ( OR=1.722, 95% CI 1.310-2.263, P<0.001), and the MHR ( OR=1.352, 95% CI 1.153-1.586, P<0.001) were identified as independent risk factors for cardiovascular calcification in patients on MHD. Serum magnesium ( OR=0.034, 95% CI 0.001-0.797, P=0.036) was a protective factor. The combined area under the curve (AUC) of the NLR and MHR was the largest (AUC=0.804, 95% CI 0.759-0.850); the AUC for the NLR and MHR used alone was 0.725 (95% CI 0.672-0.779) and 0.730 (95% CI 0.677-0.783), respectively. Conclusions:The MHR, and the NLR are independent risk factors for cardiovascular calcification in patients with MHD. The combination of the MHR and NLR has a greater clinical predictive value for cardiovascular calcification.

Objective To conduct a retrospective analysis of the correlation among bedaquiline(BDQ)plasma concentrations,relevant clinical factors,and disease prognosis.Methods In this retrospective study,22 patients diagnosed with rifampicin-resistant tuberculosis(RR-TB),multidrug-resistant tuberculosis(MDR-TB),or pre-extensively drug-resistant tuberculosis(pre-XDR-TB)were enrolled.These patients were admitted to the tuberculosis ward of our hospital between February 2022 and October 2024.All patients were administered a treatment regimen containing BDQ.The cohort comprised 6 RR-TB patients(27.27%),12 MDR-TB patients(54.55%),and 4 pre-XDR-TB patients(18.18%).Peripheral blood samples were collected 2 hours after the oral administration of Bedaquiline.The plasma concentration of Bedaquiline was measured using liquid chromatography-tandem mass spectrometry(LC-MS/MS).Spearman correlation analysis was performed using R studio software with the ggplot2 and corrplot packages.The factors included the blood concentration of bedaquiline,electrocardiogram QTcF(QT interval corrected by the Fridericia method),liver and kidney function parameters,weight,age,body mass index,sex,blood uric acid level,serum creatinine level,and other relevant indicators.Results In 22 patients treated with BDQ,the plasma concentration reached a peak after 1.5 weeks of administration,and gradually stabilized after 2 weeks.The plasma concentration was approximately 1-3 μg/mL.After 24 weeks of withdrawal of bedaquiline,patients were continued to monitor their bedaquiline concentration and found that BDQ blood concentration in peripheral blood was approximate 1 μg/mL up to 36 weeks.The serum concentration of BDQ was not correlated with age,body weight,BMI,ALT,AST,GGT,TDiL,urea,uric acid and QT interval,but correlated with sputum negative transformation and serum creatinine.The correlation analysis between serum concentration of BDQ and acid-fast staining of sputum smear showed,the difference was significant(r=0.35,P<0.05).In addition,the correlation analysis between serum BDQ concentration and serum creatinine showed,the difference was significant(r=0.34,P<0.05).The results of multiple linear regression analysis showed that BDQ blood concentration was positively correlated with Scr level,and Scr was an independent factor affecting BDQ blood concentration.20 cases(90.9%,20/22)were cured,1 case died of Covid-19 virus infection,1 case was recurrence.Conclusions Regimens containing bedaquiline seem to exhibit relatively high safety profiles and good tolerability among patients with rifampicin-resistant,multidrug-resistant,or pre-extensively drug-resistant tuberculosis,typically yielding favorable treatment outcomes.The BDQ shows a positive correlation with serum creatinine(SCr).Consequently,close surveillance of BDQ levels and renal function remains of utmost importance throughout the treatment course.

Objective:To identify and validate secreted effector proteins of Chlamydia psittaci ( C. psittaci) through bioinformatic prediction and experimental verification, and to characterize their subcellular localization in host cells. Methods:Potential effector proteins were predicted using bioinformatics tools. Candidate effectors were fused to β-lactamase through the constructed expression vectors, and these vectors were transformed into C. psittaci. The secretion of these candidate effectors was evaluated by β-lactamase translocation assays. Eukaryotic expression vectors of confirmed effectors were transfected into host cells to determine their intracellular localization patterns. Results:Bioinformatic analysis identified 29 candidate effector proteins. Experimental validation confirmed the secretion of five effectors, with four exhibiting cytoplasmic localization and one displaying nuclear localization in host cells.Conclusion:This study characterizes five novel C. psittaci secreted effector proteins, providing critical insights for investigating the molecular pathogenesis of psittacosis.