Objective To investigate the role and regulatory mechanism of LINC00657 in the progression of cervical cancer. Methods Bioinformatics analysis predicted potential binding sites between LINC00657 and miR-30a-5p and between miR-30a-5p and Skp2. These sites were verified by using RNA immunoprecipitation and dual-luciferase reporter experiments. LINC00657, miR-30a-5p, and Skp2 mRNA expression levels in cervical cancer tissues and cell lines were assessed by utilizing RT-qPCR. Western blot analysis was employed to examine the protein levels of Skp2 in cells and subcutaneous xenograft tumor models in nude mice. Immunohistochemistry was applied to analyze Skp2 expression in animal tissues. The cellular processes of cervical cancer cell lines were evaluated through CCK-8, scratch, and Transwell assays. Results LINC00657 and Skp2 presented binding sites for miR-30a-5p. In cervical cancer, LINC00657 and Skp2 showed high expression levels (P<0.05), whereas miR-30a-5p displayed low expression (P<0.05). Functional experiments demonstrated that linc00657 upregulates Skp2 expression, a process that is dependent on its sequestration of miR-30a-5p. Conclusion LINC00657 promoted the malignant progression of cervical cancer by upregulating Skp2 expression through specifically sequestering miR-30a-5p, thereby relieving its inhibitory effect on the target gene Skp2.

Objective To analyze the significance of serum glucagon-like peptide-1(GLP-1)expression in patients with type 2 diabetes mellitus(T2DM)and its predictive value for diabetic retinopathy(DR).Methods A total of 160 T2DM patients admitted to our hospital from January 2020 to January 2022 were enrolled in this study and divided into DR group(n=68)and T2DM group(n=92)according to whether they had DR.Another 80 healthy physical examination subjects were selected as normal control(NC)group from our physical examination center during the same period.Serum GLP-1 levels were detected and compared among all the groups.Serum GLP-1 levels were compared among patients with different stages of DR.The correlation between serum GLP-1 and other indexes was evaluated by Pearson analysis.The influencing factors for DR were analyzed by Logistic regression analysis.The receiver operating characteristic(ROC)curve and the area under the curve(AUC)was generated,and the predictive efficacy of serum GLP-1 on DR was analyzed.Results Serum GLP-1 in NC,T2DM and DR groups decreased in turn(P<0.05).Serum GLP-1 in subgroups Ⅱ,Ⅲ,Ⅳ and Ⅴ decreased in turn(P<0.05).Pearson analysis showed that serum GLP-1 was negatively correlated with systolic blood pressure(SBP),diastolic blood pressure(DBP),2 h postprandial blood glucose(2 hPG),low density lipoprotein cholesterol(LDL-C),tumor necrosis factor-α(TNF-α)(r=-0.359,-0.314,-0.361,-0.308,-0.429,P<0.05),positively correlated with fasting C-peptide(FC-P)(r=0.382,P<0.05).Logistic regression analusis showed that DM duration,SBP,DBP,2 hPG,LDL-C,TNF-α and FC-P were the influencing factors for DR.The AUC of GLP-1 was 0.091 in predicting DR,and the sensitivity and specificity were 93.76%and 90.23%when the optimal cut-off value was 1.95 pmol/L.Conclusions Serum GLP-1 expression is low in T2DM patients,and serum GLP-1 is correlated with SBP,DBP,2 hPG,LDL-C,TNF-α and FC-P to a certain extent,which has high sensitivity and specificity in predicting the occurrence of DR.Abnormal low expression of serum GLP-1,metabolic disorders of blood glucose and lipids,hypertension,inflammation and other factors are involved in the progression of the disease,all of which are influencing factors for inducing DR,and should attract clinical attention.

Objective:To construct a network calculator based on interpretable machine learning models to predict the risk of prolonged length of stay in patients with acute ischemic stroke (AIS), and to provide a tool for the development of individualized intervention plans for patients.Methods:Adopting a retrospective analysis method. The 537 patients with AIS admitted to the Nanyang Central Hospital from July 2022 to July 2024 were selected. Length of stay exceeding the median length of stay was defined as length of stay prolongation. Length of stay prolongation risk profile variables were screened by Boruta algorithm. The 537 patients were randomly divided into a training set (322 cases) and a test set (215 cases) in a 3:2 ratio according to the random number table method to construct and train nine machine learning models and perform tenfold cross-validation. The best predictive performance model was assessed using receiver operating characteristic (ROC) curve analysis and calculating the area under the curve (AUC). The predictive accuracy and clinical utility of the model was assessed using calibration curve, clinical impact curve and decision curve analyses. Additional interpretation and visualisation of the machine learning model using Shapley additive explanations (SHAP) bar charts, summary, dependency and force diagrams. A network calculator for predicting the risk of length of stay prolongation in patients with AIS was constructed using the corresponding R package.Results:Among 537 AIS patients, there were 312 males and 225 females with an age of (58.40 ± 9.00) years old. The incidence of length of stay prolongation was 43.0% (231/537). Boruta algorithm screened 10 characteristic variables. The results of ROC curve analysis showed that the AUC of the extreme gradient boosting (XGBoost) model was at the highest among the 9 machine learning models in 10 random samples. In the training and test sets, the calibration curve and clinical impact curve analysis showed that the C-index was 0.815 and 0.816, respectively, indicating high consistency between the predicted results of the XGBoost model and the actual observations. Decision curve analysis showed that the net clinical benefit was>0 when the risk threshold was>0.18 and >0.22, respectively, indicating that the model had a high application value in actual clinical decision-making. The SHAP bar graph showed the order of importance as pneumonia, urinary tract infection, age, myoglobin, triacylglycerol, neuron-specific enolase (NSE), hemoglobin, total cholesterol, homocysteine (HCY), and National Institute of Health Stroke Scale (NIHSS) scores. SHAP summary charts visualised the contribution of the 10 characteristic variables, which showed a 'bipolar distribution' phenomenon. SHAP dependency plots showed the dependency between the observed values of the 10 variables and the SHAP values, with the trend being most significant for patients with pneumonia. SHAP seeks to provide a local interpretation for individual samples, making the XGBoost model more transparent and interpretable. A web-based calculator (https://nomogram1203.shinyapps.io/LOS_web/) based on the interpretable XGBoost model dynamically quantifies the risk of prolonged length of stay in patients with AIS.Conclusions:Pneumonia, urinary tract infection, age, myoglobin, hemoglobin, total cholesterol, NSE, HCY, triacylglycerol, and NIHSS can effect length of stay prolongation in AIS patients, and a network calculator constructed based on the interpretable XGBoost model dynamically predicts the risk of length of stay prolongation in patients with AIS, which can help to achieve an accurate risk assessment for individual patients.

Objective:To construct a mindfulness based cancer rehabilitation training program for patients with malignant hematologic diseases based on the Liverpool mindfulness model, providing practical guidance for improving their physical and mental symptoms.Methods:The system searched for relevant literature on the application of mindfulness intervention in patients with malignant hematological diseases retrieved from Cochrane Library, PubMed, CINAHL, PsycInfo, Chinese Biomedical Literature Database, and China National Knowledge Infrastructure. The search period was from January 1, 1982 to December 26, 2023. Using the Liverpool mindfulness model as the theoretical framework, based on the literature review, group meetings and semi-structured interviews, a preliminary draft of a mindfulness cancer rehabilitation training program for patients with malignant hematologic diseases was developed. After 2 rounds of Delphi expert consultation, the final version of the intervention plan was determined.Results:Among the 19 experts, there were 4 males and 15 females, aged 30-61 (47.11 ± 7.64) years old. The effective recovery rates of the two rounds of expert inquiry questionnaires were both 19/19, and the expert authority coefficients were both 0.88. The Kendall coordination coefficients for the two rounds of inquiry were 0.214 and 0.220, respectively ( χ2=77.37, 108.66, both P<0.01).A mindfulness based cancer rehabilitation training program for patients with malignant hematologic diseases was ultimately developed, including intervention subjects, intervention personnel, intervention sites and forms, intervention timing, intervention intensity, intervention process and training theme content. Conclusions:The mindfulness based cancer rehabilitation training program for patients with malignant hematologic diseases constructed based on the Liverpool mindfulness model is necessary, scientific, and clinically suitable, and can provide a basis for clinical psychological nursing practice for patients with malignant hematologic diseases.

Objective:To investigate the relationship between fibroblast growth factor receptor-2(FGFR2)gene polymorphisms and the risk of breast cancer and its protein expression in Han women from Heilongjiang,China.Meth-ods:Using the Snapshot technique for multiplex single nucleotide polymorphism genotyping,the polymorphisms rs3135718 and rs1219648 of FGFR2 were analyzed in 747 breast cancer patients and 716 healthy controls.Logistic re-gression was used to examine the association between these genotypes and breast cancer susceptibility.In a subset of 338 cases,immunohistochemistry was performed to assess FGFR2 protein expression,and chi-square tests was used to analyze the relationship between polymorphisms and protein expression.Results:The genotype frequencies of FGFR2 rs3135718 and rs1219648 showed significant differences between the breast cancer and control group.Logistic regression revealed that,for rs3135718,the CT,CC,and CT+CC genotypes were associated with increased breast cancer risk compared to the TT genotype(OR=1.280,95%CI:1.003-1.633;OR=1.500,95%CI:1.112-2.023;OR=1.341,95%CI:1.066-1.688).For rs1219648,the GA,GG,and GA+GG genotypes were significantly associated with higher breast cancer risk compared to the AA genotype(OR=1.352,95%CI:1.063-1.719;OR=1.826,95%CI:1.361-2.504;OR=1.475,95%CI:1.175-1.852).However,no significant association was found between FGFR2 rs3135718 and rs1219648 polymorphisms and FGFR2 protein expression(χ2=0.052,P=0.820;χ2=0.117,P=0.732).Conclusion:FGFR2 gene poly-morphisms rs3135718 and rs1219648 are significantly associated with breast cancer susceptibility in Han women from Heilongjiang,China,but these polymorphisms do not show a clear relationship with FGFR2 protein expression.

Parkinson's disease(PD)is one of the most common neurodegenerative disorders.Recent evidence implicates pyroptosis as one of the pathogenic mechanisms in central nervous system disorders,although its specific mechanisms remain unclear.In this study,SH-SY5Y cells were transfected with py-roptosis-related proteins GSDME full-length(GSDME-F)or GSDME-N terminal(GSDME-N)plasmids revealed that GSDME-N significantly reduced mitochondrial membrane potential(P＜0.0001).To inves-tigate the mechanism by which GSDME mediates mitochondrial dysfunction,Western blotting analysis demonstrated that transfection with GSDME-N plasmids significantly increased BAX expression and en-hanced its translocation to mitochondria in both HEK 293T and SH-SY5Y cells(P＜0.05).SH-SY5Y cells treated with varying concentrations of rotenone(ROT)exhibited GSDME cleavage,elevated BAX expression(P＜0.05),increased mitochondrial BAX aggregation(P＜0.05),and reduced mitochondrial membrane potential(P＜0.01),as confirmed by Western blotting and JC-1 staining.Concurrently,MTT assays assessing cell viability and lactate dehydrogenase(LDH)release assays indicated that ROT in-duced these processes prior to pyroptosis.Furthermore,in a ROT-induced mouse PD model,ROT trig-gered GSDME cleavage,enhanced BAX expression,caused dopaminergic neuronal damage,and induced motor deficits.In summary,this study demonstrates that GSDME-N exacerbates mitochondrial damage and increases cytotoxicity by upregulating BAX expression and facilitating its mitochondrial translocation.This study provides novel insights into the role of GSDME in PD pathogenesis and suggests potential avenues for therapeutic intervention.

Objective To explore the application value of CT-based radiomics in differentiating pneumonia-type mucinous adenocarcinoma(PTMA)from organizing pneumonia(OP).Methods A total of 52 PTMA patients and 102 OP patients were retrospectively included and randomly divided into training set(n=124)and test set(n=30)in an 8∶2 ratio.Eight PTMA patients and 22 OP patients from another hospital during the same period were included as external validation set(n=30).Clinical characteristics and CT signs of the patients were selected to construct the clinical model.Radiomics features were extracted and dimensionality reduction was performed through the least absolute shrinkage and selection operator(LASSO)algorithm.A radiomics model was constructed and the Radiomics score(Radscore)was calculated.The Radscore was combined with clinical factors to establish the combined model and a nomogram was illustrated.The models' fitting degree was analyzed by the calibration curve,while their efficacy was evaluated by the receiver operating characteristic(ROC)curve and decision curve analysis(DCA).Results The clinical model,established based on the border,cystic space and bronchial leafless tree sign,achieved area under the curve(AUC)of 0.850,0.782,and 0.759 in the training set,test set,and external validation set,respectively.Thirteen features were obtained to construct the radiomics model,with AUC of 0.925,0.865,and 0.830,respectively.The AUC of the combined model were 0.970,0.905,and 0.864,respectively,in which the calibration curve demonstrated good model fitting.DCA indicated that the combined model had the greatest clinical net benefit.Conclusion The combined model based on CT radiomics can effectively distinguish PTMA from OP.

Objective To analyze the significance of serum glucagon-like peptide-1(GLP-1)expression in patients with type 2 diabetes mellitus(T2DM)and its predictive value for diabetic retinopathy(DR).Methods A total of 160 T2DM patients admitted to our hospital from January 2020 to January 2022 were enrolled in this study and divided into DR group(n=68)and T2DM group(n=92)according to whether they had DR.Another 80 healthy physical examination subjects were selected as normal control(NC)group from our physical examination center during the same period.Serum GLP-1 levels were detected and compared among all the groups.Serum GLP-1 levels were compared among patients with different stages of DR.The correlation between serum GLP-1 and other indexes was evaluated by Pearson analysis.The influencing factors for DR were analyzed by Logistic regression analysis.The receiver operating characteristic(ROC)curve and the area under the curve(AUC)was generated,and the predictive efficacy of serum GLP-1 on DR was analyzed.Results Serum GLP-1 in NC,T2DM and DR groups decreased in turn(P<0.05).Serum GLP-1 in subgroups Ⅱ,Ⅲ,Ⅳ and Ⅴ decreased in turn(P<0.05).Pearson analysis showed that serum GLP-1 was negatively correlated with systolic blood pressure(SBP),diastolic blood pressure(DBP),2 h postprandial blood glucose(2 hPG),low density lipoprotein cholesterol(LDL-C),tumor necrosis factor-α(TNF-α)(r=-0.359,-0.314,-0.361,-0.308,-0.429,P<0.05),positively correlated with fasting C-peptide(FC-P)(r=0.382,P<0.05).Logistic regression analusis showed that DM duration,SBP,DBP,2 hPG,LDL-C,TNF-α and FC-P were the influencing factors for DR.The AUC of GLP-1 was 0.091 in predicting DR,and the sensitivity and specificity were 93.76%and 90.23%when the optimal cut-off value was 1.95 pmol/L.Conclusions Serum GLP-1 expression is low in T2DM patients,and serum GLP-1 is correlated with SBP,DBP,2 hPG,LDL-C,TNF-α and FC-P to a certain extent,which has high sensitivity and specificity in predicting the occurrence of DR.Abnormal low expression of serum GLP-1,metabolic disorders of blood glucose and lipids,hypertension,inflammation and other factors are involved in the progression of the disease,all of which are influencing factors for inducing DR,and should attract clinical attention.

Objective:To investigate the feasibility and value of nomogram based on base line clinical and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) characteristics for pretreatment predicting the depth of myometrial invasion and tumor grade of endometrioid endometrial carcinoma (EEC).Methods:Preoperative baseline clinical characteristics and DCE-MRI characteristics of 194 EEC patients were prospectively collected at Obstetrics and Gynecology Hospital, Fudan University from October 2020 to January 2022 and used as a training set. Univariate analysis was conducted to compare baseline clinical characteristics and DCE-MRI quantitative parameters [including tumor volume, and mean, median, and standard deviation of volume transfer constant (K trans), rate constant (K ep), extravascular extracellular volume fraction (V e), and initial area under the enhancement curve (iAUC)] between patients with deep myometrial invasion (DMI) and those with superficial myometrial invasion (SMI), as well as between high-grade and low-grade EEC. Multivariate logistics regression analysis was used to identify independent predictors for the construction of nomogram. An independent external testing set comprising 127 EEC patients was retrospectively collected from Zhongshan Hospital, Fudan University and Zhongshan Hospital, Fudan University (Xiamen Branch). The area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA) were used for evaluating the model′s predictive performance and clinical net benefit, respectively. Results:(1) The depth of myometrial invasion: univariate analysis showed that in the training set, the EEC patients with DMI differed significantly from those with SMI in clinical characteristics including higher proportion of postmenopausal state and overweight [body mass index (BMI)≥25 kg/m2], and abnormal levels of serum cancer antigen (CA) 125, CA 199, and human epididymis protein 4 (HE4), and in DCE-MRI quantitative parameters including tumor volume, and median, mean, and standard deviation of K trans, median of V e, as well as median, mean, and standard deviation of iAUC (all P<0.05). Multivariate analysis showed that the patient′s menstrual status, BMI, CA 199, tumor volume, and mean of iAUC were independent predictors of the depth of myometrial invasion, and constructed the nomogram (recorded as Nomogram_1), achieving an AUC of 0.861 (95% CI: 0.803-0.919) in the training set. In the independent external testing set, the AUC was 0.876 (95% CI: 0.815-0.938), with corresponding sensitivity of 82.0%, specificity of 80.7%, accuracy of 81.1%, positive predictive value (PPV) of 65.3%, and negative predictive value (NPV) of 91.0% for predicting DMI. (2) The EEC grade: univariate analysis showed that in the training set, high-grade EEC patients differed significantly from low-grade EEC in clinical characteristics including patient′s age, the proportion of postmenopausal state and overweight, and abnormal levels of serum CA 125, and in DCE-MRI quantitative parameters including tumor volume, median, mean, and standard deviation of K trans, median and mean of V e, as well as median, mean, and standard deviation of iAUC (all P<0.05). Multivariate analysis showed that the patient′s menstrual status, BMI, tumor volume, and median of V e emerged as independent predictors of EEC grade, and constructed the nomogram (recorded as Nomogram_2), achieving an AUC of 0.845 (95% CI: 0.786-0.893) in the training set. While in the external testing set, the AUC was 0.819 (95% CI: 0.744-0.894), with corresponding sensitivity of 72.4%, specificity of 72.4%, accuracy of 72.4%, PPV of 43.8%, and NPV of 89.9% for predicting high-grade EEC. (3) The DCA curves demonstrated that both Nomogram_1 and Nomogram_2 yielded obvious positive clinical net benefits across a wide range of threshold probabilities. Conclusion:The nomogram based on pretreatment clinical and DCE-MRI characteristics has the potential to noninvasive predict the depth of myometrial invasion and grade of EEC, providing valuable reference information for clinical management decision-making.

Objective:To compare pregnancy outcomes between patients undergoing combined hysteroscopy and hysterosalpingo-contrast sonography (HyCoSy) versus hysteroscopy alone prior to intrauterine insemination, and to evaluate the safety and clinical value of the combined procedure in the diagnosis and treatment of infertility.Methods:A retrospective analysis was conducted on clinical data from 385 patients who underwent hysteroscopy at Peking University Third Hospital between October 1, 2020 and September 30, 2022, and subsequently received their first cycle of artificial insemination with donor sperm (AID) within six months. Pregnancy outcomes were compared between the group receiving combined hysteroscopy with four-dimensional HyCoSy (hysteroscopy+4D-HyCoSy group) and the group receiving hysteroscopy alone (hysteroscopy group). Multivariate logistic regression was used to analyze factors influencing pregnancy outcomes after AID.Results:Among the 385 patients included, 79 achieved clinical pregnancy. The clinical pregnancy rate (24.9%, 53/213) and live birth rate (21.1%, 45/213) in the hysteroscopy+4D-HyCoSy group were significantly higher than those in the hysteroscopy group [15.1% (26/172) and 12.8% (22/172), respectively; all P<0.05]. There was no significant difference in tubal patency between the two groups ( P>0.05); however, the time interval from tubal patency assessment to intrauterine insemination was significantly longer in the hysteroscopy group compared to the hysteroscopy+4D-HyCoSy group (median: 4.0 vs 2.0 months; P<0.001). Multivariate analysis showed that double insemination significantly increased clinical pregnancy rate compared to single insemination ( OR=2.42, 95% CI: 1.02-5.72; P=0.044). An interval exceeding 6 months between tubal patency assessment and intrauterine insemination was identified as a risk factor for reduced clinical pregnancy ( OR=0.35, 95% CI: 0.14-0.92; P=0.047). Additionally, neither the time interval from hysteroscopy to intrauterine insemination nor hysteroscopic findings and pathological diagnoses had significant effects on clinical pregnancy rates (all P>0.05). Conclusions:The combination of hysteroscopy and HyCoSy provides a safe and efficient approach for fertility assessment in infertile patients and improves clinical pregnancy rate and live birth rate in intrauterine insemination cycles. Hysteroscopy is recommended for patients with suspected endometrial or intrauterine abnormalities. If no previous tubal patency assessment has been performed or the last assessment was more than six months prior, combined hysteroscopy and HyCoSy may be considered to enhance the likelihood of clinical pregnancy.