ObjectiveBased on literature data mining， this study explores the modeling elements of diarrhea-predominant irritable bowel syndrome （IBS-D） animal models in China and abroad， providing references and suggestions for improving modeling methods and evaluation indicators. MethodsRelevant literature on IBS-D animal experiments from 2014 to 2024 was retrieved through computer searches in databases such as China National Knowledge Infrastructure （CNKI）， Wanfang Data， VIP， Chinese Medical Journals Full-text Database， and PubMed. Information on experimental animal species， gender， body weight， modeling methods， modeling periods， intervention controls， modeling standards， and detection indicators was organized. Microsoft Excel 2021 software was used to establish a database and perform statistical analysis to examine the characteristics of IBS-D animal models. ResultsA total of 398 articles that met the inclusion criteria were reviewed. The IBS-D animal models were predominantly established using SD rats， Wistar rats， and C57BL/6 mice. Male animals were more commonly used， with rats typically aged 6-8 weeks and mice aged 4-6 weeks. In terms of interventions， piverium bromide was the main Western medicine， Tongxieyaofang was the primary Chinese medicine， and electroacupuncture was the primary acupuncture method. Among the modeling methods， the multi-factor combined composite modeling approach was the most common. Modeling periods were mainly concentrated between 1-14 days and 15-30 days. The success criteria for modeling were mainly evaluated based on the animal's general condition， fecal appearance， visceral sensitivity， gastrointestinal motility， behavior， and pathology. Detection indicators included apparent indexes， pathological markers， biochemical indicators， oxidative stress， brain-gut peptides， neurotransmitters， inflammatory factors， immune function， intestinal permeability， autophagy， apoptosis， proteins related to relevant signaling pathways， intestinal microbiota and its metabolites， etc. ConclusionThere are various methods for establishing IBS-D animal models， but no unified and universally accepted method has been established. The operation of the same modeling methods and the evaluation standards of the models vary across studies. Based on the results of data mining， the authors suggest that the multi-factor combined composite modeling approach most closely reflects the pathophysiological processes of IBS-D， better simulating the complex clinical symptoms of IBS-D patients， such as abdominal pain and diarrhea， and has a high degree of clinical relevance. This method is relatively recommended. While animal models in general align with Western medicine standards， models incorporating traditional Chinese medicine （TCM） syndromes are relatively few. Therefore， one of the future directions for research is to establish IBS-D animal models that meet the combined clinical disease and syndrome requirements of both Western and Chinese medicine.

Inflammatory breast cancer(IBC)is a rare but highly aggressive subtype of breast cancer characterized by rapid clinical progression and poor prognosis.Although it accounts for only 2%-4%of all breast cancer cases,it is responsible for 8%-10%of breast cancer-related mortality.The etiology of IBC is multifactorial,involving genetic,hormonal,environmental,and socioeconomic factors.Pathologically,IBC is marked by the presence of dermal lymphatic tumor emboli,and molecular subtypes are predominantly HER2-positive and triple-negative,indicating high tumor invasiveness.Diagnosis relies on characteristic clinical manifestations and histopathological confirmation,while imaging techniques such as MRI and PET/CT play important roles in evaluating disease extent and metastasis.Given that IBC is often diagnosed at a locally advanced or metastatic stage,there is currently no specific treatment protocol.Instead,management generally follows the treatment paradigm of non-IBC,emphasizing systemic therapy within a multidisciplinary framework.HER2-positive IBC benefits from chemotherapy combined with dual-targeted anti-HER2 therapy;triple-negative IBC may respond to immune checkpoint inhibitors;and CDK4/6 inhibitors show potential efficacy in hormone receptor-positive subtypes.Despite advancements,the prognosis remains poor,with a high risk of early recurrence and distant metastasis.Prognostic factors include lymph node involvement,molecular subtype,and response to neoadjuvant therapy.As research into the tumor microenvironment and molecular mechanisms deepens,targeted and individualized therapies hold promise for improving outcomes.This review summarizes the epidemiology,pathology,diagnostic criteria,treatment strategies,and prognostic factors of IBC,aiming to inform clinical practice and future research.

OBJECTIVE: To identify the optimal machine learning algorithm for predicting post-stroke epilepsy (PSE) within one year following acute stroke, establish a nomogram model based on this algorithm, and perform external validation to achieve accurate prediction of secondary epilepsy. METHODS: A total of 870 acute stroke patients admitted to the emergency department of Xiang'an Hospital of Xiamen University from June 2019 to June 2023 were enrolled for model development (model group). An external validation cohort of 435 acute stroke patients admitted to the Fifth Hospital of Xiamen during the same period was used to validate the machine learning algorithms and nomogram model. Patients were classified into control and epilepsy groups based on the development of PSE within one year. Clinical and laboratory data, including baseline characteristics, stroke location, vascular status, complications, hematologic parameters, and National Institutes of Health Stroke Scale (NIHSS) score, were collected for analysis. Nine machine learning algorithms such as logistic regression, CN2 rule induction, K-nearest neighbors, adaptive boosting, random forest, gradient boosting, support vector machine, naive Bayes, and neural network were applied to evaluate predictive performance. The area under the curve (AUC) of receiver operator characteristic curve (ROC curve) was used to identify the optimal algorithm. Logistic regression was used to screen risk factors for PSE, and the top 10 predictors were selected to construct the nomogram model. The predictive performance of the model was evaluated using the ROC curve in both the model and validation groups. RESULTS: Among the 870 patients in the model group, 29 developed PSE within one year. Among the nine algorithms tested, logistic regression demonstrated the best performance and generalizability, with an AUC of 0.923. Univariate logistic regression identified several risk factors for PSE, including platelet count, white blood cell count, red blood cell count, glycated hemoglobin (HbA1c), C-reactive protein (CRP), triglycerides, high-density lipoprotein (HDL), aspartate aminotransferase (AST), alanine aminotransferase (ALT), activated partial thromboplastin time (APTT), thrombin time, D-dimer, fibrinogen, creatine kinase (CK), creatine kinase-MB (CK-MB), lactate dehydrogenase (LDH), serum sodium, lactic acid, anion gap, NIHSS score, brain herniation, periventricular stroke, and carotid artery plaque. Further multivariate logistic regression analysis showed that white blood cell count, HDL, fibrinogen, lactic acid and brain herniation were independent risk factors [odds ratio (OR) were 1.837, 198.039, 47.025, 11.559, 70.722, respectively, all P < 0.05]. In the external validation group, univariate logistic regression analysis showed that platelet count, white blood cell count, CRP, triacylglycerol, APTT, D-dimer, fibrinogen, CK, CK-MB, LDH, NIHSS score, and cerebral herniation were risk factors for PSE one year after acute stroke. Further multiple logistic regression analysis showed that APTT and cerebral herniation were independent predictors (OR were 0.587 and 116.193, respectively, both P < 0.05). The nomogram model, constructed using 10 key variables-brain herniation, periventricular stroke, carotid artery plaque, white blood cell count, triglycerides, thrombin time, D-dimer, serum sodium, lactic acid, and NIHSS score-achieved an AUC of 0.908 in the model group and 0.864 in the external validation group. CONCLUSIONS The logistic regression-based prediction model for epilepsy one year after acute stroke, developed using machine learning algorithms, showed optimal predictive performance. The nomogram model based on the logistic regression-derived predictors showed strong discriminative power and was successfully validated externally, suggesting favorable clinical applicability and generalizability.
Humans ; Machine Learning ; Stroke/complications* ; Nomograms ; Epilepsy/etiology* ; Algorithms ; Male ; Female ; Logistic Models ; Middle Aged ; Aged ; Risk Factors ; Bayes Theorem

Objective To systematic evaluate the impact of applying the clinical nursing pathway(CNP)on epidural anesthetic analgesia natural delivery.Methods The randomized controlled trial(RCT)and quasi-experimental researches on the application of CNP in epidural anesthetic analgesia natural delivery were retrieved from PubMed,Cochrane Library,Embase,Web of Science,China Knowledge Network database,Wanfang database,VIP and the Chinese Biomedical Literature Database.The retrieval time limit was from January 1,2014,to July 31,2024 with no language limitation.The meta analysis on the included studies was performed by applying RevMan5.4.1.Results A total of 5 RCTs and 2 quasi-experimental studies were in-cluded,involving 979 parturients with deliveries.The meta analysis showed that compared with the conven-tional nursing,CNP could shorten the duration of the first stage of labor(MD=—1.06,95％CI:—1.95——0.17,P=0.02)and the duration of the second stage of labor(MD=—0.12,95％CI:—0.21——0.03,P=0.006);decreased the rate of perineal lateral incision(RR=0.73,95％CI:0.65-0.83,P＜0.001)and inci-dence rate of postpartum urinary retention(RR=0.35,95％CI:0.20-0.63,P＜0.001);and shortened the time to lactation initiation(SMD=—1.52,95％CI:—2.38——0.66,P＜0.001).There was no influence on reducing postpartum 24 h hemorrhage amount(SMD=—0.51,95％CI:—1.23-0.21,P=0.16).The study subjects were divided into the primipara women subgroup and unclassified parturients subgroup.Compared with the conventional nursing group,compared with the conventional nursing,CNP had no impact on the dura-tion of the first stage of labor(MD=—0.32,95％CI:—0.61-0.98,P=0.63)and the duration of the second stage of labor(MD=—0.11,95％CI:—0.25-0.04,P=0.15)in the primipara women subgroup.CNP could reduce the postpartum 24 h hemorrhage volume in the unclassified parturients subgroup(SMD=—1.47,95％CI:—1.72——1.21,P＜0.001).Conclusion Application of CNP in parturients labor analgesia could reduce the perineal lateral incision rate and incidence rate of postpartum urinary retention and shorten the time to lac-tation initiation.Due to the heterogeneity among studies,the impact of CNP on the labor duration and the bleeding amount within postpartum 24 h still requires more high-quality studies to be conducted in the future for verification.

Objective:To construct univariate and multivariate relapse free survival (RFS) prediction models for breast cancer patients with diabetes mellitus type 2 (T2DM) and to compare and select the model with higher predictive performance.Methods:A total of 912 breast cancer patients treated at the First Affiliated Hospital of Dalian Medical University from January 2010 to December 2016 were included, of which 202 patients had T2DM and 710 patients did not. Kaplan-Meier survival curve was drawn based on whether patients had T2DM, and log-rank test was performed based on whether patients had T2DM. All patients were randomly divided into a training set ( n=640) and a validation set ( n=272) at a ratio of 7∶3. Univariate and multivariate Cox proportional risk regression models were used to analyze RFS in breast cancer patients with the survival package. The "rms" package was employed to construct univariate and multivariate RFS prediction models for breast cancer patients with T2DM. Clinical decision curves and calibration curves were used to validate the models. The receiver operator characteristic (ROC) curve was used to compare and analyze the prediction performance of the two models. Results:There were no statistically significant differences between the training set and the validation set patients in terms of age, T2DM, surgical approach, axillary management methods, T stage, N stage, molecular sub-type, estrogen receptor (ER) 1, ER2, progesterone receptor (PR) , ER and PR consistency, Ki67, human epidermal growth factor receptor 2 (HER2) (all P>0.05) . There was a statistically significant difference in histological grade ( χ2=7.59, P=0.022) . Survival analysis showed that the 5-year RFS rate was 83.7% in patients with T2DM and 92.3% in patients without T2DM ( χ2=16.61, P<0.001) . Univariate analysis revealed that age ( HR=1.04, 95% CI: 1.03-1.06, P<0.001) , T2DM ( HR=2.31, 95% CI: 1.49-3.55, P<0.001) , surgical approach ( HR=2.39, 95% CI: 1.20-4.77, P=0.013) , axillary management methods ( HR=2.62, 95% CI: 1.72-3.98, P<0.001) , T stage (T 2: HR=2.13, 95% CI: 1.36-3.31, P<0.001; T 3: HR=6.90, 95% CI: 3.35-14.22, P<0.001) , N stage (N 2: HR=3.87, 95% CI: 2.12-7.07, P<0.001; N 3: HR=8.61, 95% CI: 4.71-15.75, P<0.001) , molecular sub-type (Luminal B: HR=2.74, 95% CI: 1.17-6.36, P=0.019; HER2 +: HR=3.64, 95% CI: 1.38-9.58, P=0.009; TNBC: HR=4.40, 95% CI: 1.71-11.34, P=0.002) , ER1 (>10%: HR=0.57, 95% CI: 0.37-0.90, P=0.016) , ER2 ( HR=0.57, 95% CI: 0.37-0.89, P=0.015) , and PR ( HR=0.56, 95% CI: 0.37-0.86, P=0.008) were all factors influencing RFS in breast cancer patients. Multivariate analysis demonstrated that age ( HR=1.04, 95% CI: 1.02-1.06, P<0.001) , T2DM ( HR=1.82, 95% CI: 1.16-2.85, P=0.009) , T stage (T 2: HR=1.60, 95% CI: 1.01-2.54, P=0.046; T 3: HR=2.64, 95% CI: 1.22-5.72, P=0.014) , N stage (N 2: HR=3.72, 95% CI: 2.01-6.88, P<0.001; N 3: HR=5.34, 95% CI: 2.78-10.25, P<0.001) , and ER1 (>10%: HR=0.63, 95% CI: 0.39-0.99, P=0.046) were independent factors influencing RFS in breast cancer patients. Based on the 10 and 5 variables with P<0.05 in the univariate and multivariate analyses respectively, the nomograms of the univariate and multivariate prediction models were constructed to evaluate the influence of factors such as T2DM on the postoperative RFS of breast cancer patients. Clinical decision curves and calibration curves indicated that both models had high predictive value for RFS in breast cancer patients, and the predictive results were highly consistent with the actual observed results. ROC curve analysis showed that there was no statistically significant difference in the area under the curve (AUC) of the two models for predicting the RFS rates of breast cancer patients in the training set and validation set at 36, 60, and 84 months (all P>0.05) , indicating that the predictive efficacy of the two models was comparable. The multivariate model is more suitable for clinical application because it uses fewer variables. Conclusions:Breast cancer patients with T2DM have poorer prognosis. Age, T2DM, T stage, N stage, and ER1 are independent factors influencing postoperative RFS in breast cancer patients. The multi-factor prediction model of RFS in breast cancer patients based on T2DM is more suitable for clinical application due to its higher predictive efficacy and fewer variables.

Objective To explore the mediating effect of empowerment ability between type D personality and self-management behavior of patients with diabetes mellitus(DM).Methods A total of 738 patients with type 2 diabetes mellitus(T2DM)hospitalized in the Department of Endocrinology of three tertiary hospitals in Hainan Province from December 2022 to May 2023 were selected and divided into Type D personality(Type D,n=104)group and T2DM group(n=634).The general data,biochemical indexes,scores of negative emotion(NA),social inhibition(SI),empowerment ability,and scale of DM self-management activities(SDSCA)were compared between the two groups,and the correlation between type D personality,empowerment ability and self-management ability was analyzed.The mediating effect model was used to analyze the mediating effect of empowerment ability on the four self-management behaviors of patients with type D personality,and the chain mediating effect model was used to analyze the relationship between type D personality,empowerment ability,self-management behaviors and HbA1c.Results Compared with the T2DM group,HbA1c,proportion of rural residence,proportion of complications≥3,proportion of education level of junior high school or above,proportion of monthly income<3000 yuan,and NA and SI scores were significantly higher in the Type D group(P<0.05).The empowerment ability and scores of healthy diet,regular exercise,blood glucose monitoring and medication compliance were lower in the Type D group than in the T2DM group(P<0.05).Spearman correlation analysis showed that the empowerment ability score was positively correlated with the scores of healthy diet,regular exercise,blood glucose monitoring and medication compliance(P<0.05).NA and SI scores were negatively correlated with empowerment ability score,healthy diet,regular exercise,blood glucose monitoring and medication compliance(P<0.05).The results of model analysis with empowerment ability as the mediating variable showed that type D personality had direct,indirect and total effects on regular exercise,blood glucose monitoring,medication compliance and SDSCA total score(P<0.05),and indirect and total effects on regular diet score(P<0.05).The mediating effect of empowerment ability was significant(Bootstrap CI did not include 0).The chain mediating effect analysis showed that type D personality could indirectly affect HbA1c through empowerment ability,healthy diet(γ=0.389,95%CI 0.206～0.591),and medication compliance(γ=0.149,95%CI 0.040～0.265),and the effect proportion was 39.4%and 14.1%,respectively.Conclusions Type D personality can indirectly influence self-management behavior through the mediating effect of empowerment,and simultaneously affecting HbA1c through the chain effect of empowerment,diet,and medication behavior.

Objective To investigate the effect of miR-488-3p on renal tubular epithelial cell injury by regulating the cyclic guanosine monophosphate-adenosine monophosphate synthase(cGAS)-stimulator of interferon gene(STING)signaling pathway.Methods Human renal tubular epithelial HK-2 cells were divided into control,hypoxia-reoxygenation(HR),inhibition control,miR-488-3p inhibition,cGAS-STING pathway activator(RocA),and miR-488-3p inhibition+RocA groups.Quantitative real-time polymerase chain reaction was used to detect miR-488-3p expression in HK-2 cells.Cell viability was assessed using the CCK-8 assay.Enzyme-linked immunosorbent assay was used to measure the levels of interleukin(IL)-10,IL-1β,and tumor necrosis factor-α(TNF-α)in the culture supernatant of HK-2 cells.The DCFH-DA method was applied to detect the average fluorescence intensity of reactive oxygen species(ROS)in cells.Results Compared with the control group,the HR group showed increased miR-488-3p expression,IL-1β and TNF-α levels,average fluorescence intensity of ROS,malondialdehyde(MDA)levels,apoptosis rate,and protein expression of cleaved caspase-3,Bax,cGAS,and STING,whereas cell viability,IL-10 levels,and superoxide dismutase(SOD)activity were reduced in the HR group(P＜0.05).Com-pared with the HR and inhibition control groups,the miR-488-3p inhibition group exhibited decreased expression of miR-488-3p,IL-1β and TNF-α levels,average fluorescence intensity of ROS,MDA levels,apoptosis rate,and protein levels of cleaved caspase-3,Bax,cGAS,and STING,whereas cell viability,IL-10 levels,and SOD activity were increased(P＜0.05).Conclusion Downregulation of miR-488-3p expression mitigates HR-induced inflammation,oxidative stress,and apoptosis in HK-2 cells,thereby reducing cell damage.The under-lying mechanisms may be associated with an inhibition of the cGAS-STING signaling pathway.

Inflammatory breast cancer(IBC)is a rare but highly aggressive subtype of breast cancer characterized by rapid clinical progression and poor prognosis.Although it accounts for only 2%-4%of all breast cancer cases,it is responsible for 8%-10%of breast cancer-related mortality.The etiology of IBC is multifactorial,involving genetic,hormonal,environmental,and socioeconomic factors.Pathologically,IBC is marked by the presence of dermal lymphatic tumor emboli,and molecular subtypes are predominantly HER2-positive and triple-negative,indicating high tumor invasiveness.Diagnosis relies on characteristic clinical manifestations and histopathological confirmation,while imaging techniques such as MRI and PET/CT play important roles in evaluating disease extent and metastasis.Given that IBC is often diagnosed at a locally advanced or metastatic stage,there is currently no specific treatment protocol.Instead,management generally follows the treatment paradigm of non-IBC,emphasizing systemic therapy within a multidisciplinary framework.HER2-positive IBC benefits from chemotherapy combined with dual-targeted anti-HER2 therapy;triple-negative IBC may respond to immune checkpoint inhibitors;and CDK4/6 inhibitors show potential efficacy in hormone receptor-positive subtypes.Despite advancements,the prognosis remains poor,with a high risk of early recurrence and distant metastasis.Prognostic factors include lymph node involvement,molecular subtype,and response to neoadjuvant therapy.As research into the tumor microenvironment and molecular mechanisms deepens,targeted and individualized therapies hold promise for improving outcomes.This review summarizes the epidemiology,pathology,diagnostic criteria,treatment strategies,and prognostic factors of IBC,aiming to inform clinical practice and future research.

Objective:To investigate the correlations among diabetes-related distress, self-management behavior, empowerment, and glycated hemoglobin (HbA1c) levels in patients with type 2 diabetes mellitus (T2DM) .Methods:A convenience sampling method was used to recruit a total of 1 927 hospitalized patients with T2DM from the Endocrinology Departments of five tertiary general hospitals in Hainan, Jiangsu, and Henan Provinces between December 2022 and December 2023. General demographic and clinical data were collected. The Problem Areas in Diabetes 5 (PAID-5), the Summary of Diabetes Self Care Activities (SDSCA), and the Diabetes Empowerment Scale-Short Form (DES-SF) were used to evaluate patients' psychological distress, self-management behaviors, and empowerment levels. Pearson correlation analysis was performed to examine the relationships among diabetes-related distress, empowerment, self-management behaviors, and HbA1c levels.Results:Pearson correlation analysis showed that diabetes-related distress was negatively correlated with empowerment ( r=-0.119, P<0.001) and the total score of self-management behavior ( r=-0.106, P<0.001), and positively correlated with HbA1c levels ( r=0.103, P<0.001). Empowerment was positively correlated with self-management behavior ( r=0.538, P<0.001) and negatively correlated with HbA1c levels ( r=-0.170, P<0.001). Self-management behavior was negatively correlated with HbA1c levels ( r=-0.165, P<0.001) . Conclusions:Diabetes-related distress, empowerment, and self-management behavior are all associated with glycemic control. Future research and interventions should focus on enhancing patients' self-management abilities, strengthening empowerment, and providing psychological support in order to improve glycemic outcomes and offer a more comprehensive and effective management approach for patients with T2DM.

Objective To explore the mediating effect of empowerment ability between type D personality and self-management behavior of patients with diabetes mellitus(DM).Methods A total of 738 patients with type 2 diabetes mellitus(T2DM)hospitalized in the Department of Endocrinology of three tertiary hospitals in Hainan Province from December 2022 to May 2023 were selected and divided into Type D personality(Type D,n=104)group and T2DM group(n=634).The general data,biochemical indexes,scores of negative emotion(NA),social inhibition(SI),empowerment ability,and scale of DM self-management activities(SDSCA)were compared between the two groups,and the correlation between type D personality,empowerment ability and self-management ability was analyzed.The mediating effect model was used to analyze the mediating effect of empowerment ability on the four self-management behaviors of patients with type D personality,and the chain mediating effect model was used to analyze the relationship between type D personality,empowerment ability,self-management behaviors and HbA1c.Results Compared with the T2DM group,HbA1c,proportion of rural residence,proportion of complications≥3,proportion of education level of junior high school or above,proportion of monthly income<3000 yuan,and NA and SI scores were significantly higher in the Type D group(P<0.05).The empowerment ability and scores of healthy diet,regular exercise,blood glucose monitoring and medication compliance were lower in the Type D group than in the T2DM group(P<0.05).Spearman correlation analysis showed that the empowerment ability score was positively correlated with the scores of healthy diet,regular exercise,blood glucose monitoring and medication compliance(P<0.05).NA and SI scores were negatively correlated with empowerment ability score,healthy diet,regular exercise,blood glucose monitoring and medication compliance(P<0.05).The results of model analysis with empowerment ability as the mediating variable showed that type D personality had direct,indirect and total effects on regular exercise,blood glucose monitoring,medication compliance and SDSCA total score(P<0.05),and indirect and total effects on regular diet score(P<0.05).The mediating effect of empowerment ability was significant(Bootstrap CI did not include 0).The chain mediating effect analysis showed that type D personality could indirectly affect HbA1c through empowerment ability,healthy diet(γ=0.389,95%CI 0.206～0.591),and medication compliance(γ=0.149,95%CI 0.040～0.265),and the effect proportion was 39.4%and 14.1%,respectively.Conclusions Type D personality can indirectly influence self-management behavior through the mediating effect of empowerment,and simultaneously affecting HbA1c through the chain effect of empowerment,diet,and medication behavior.