Purpose To investigate the expression of bone sialoprotein(BSP)in the tissues and cells of endome-trial cancer(EC)and its effects on the proliferation and invasion of EC cells.Methods The expression of BSP was assessed by immunohistochemistry in 235 EC tissues and 88 normal endometrial tissues,and its correlation with clinico-pathological features was analyzed.Western blot was used to compare BSP levels between human endometrial carcinoma cell line(HHUA)and normal human endumetial epithelial cells(HEEC).BSP was knocked down in HHUA cells via transient transfection,and the cells were divided into blank control group and BSP-knockdown group.The effects of BSP knockdown on cell cycle,proliferation,migration,invasion,and apoptosis were evaluated using PI staining,CCK-8,scratch,Transwell,and Annexin V-FITC assays,respectively.Protein levels of TGF-β signaling pathway compo-nents were analyzed by Western blot.Results BSP expression was significantly higher in EC tissues than in normal endometrium(P＜0.001)and correlated with lymph node metastasis and advanced FIGO stage(P＜0.05).BSP pro-tein level was also significantly elevated in HHUA cells(2.455 8±0.008 9)compared to HEECs(1.571 2±0.005 4)(P＜0.01).After knockdown,compared with the control group,the proliferation index(74.4±3.33),migration rate(0.48±0.03),and invasion ability(0.36±0.11)of the cells were increased,and the apoptosis rate(25.97％)of the cells was increased(P＜0.05).Furthermore,the expression levels of TGF-β signaling pathway downstream proteins TGF-β1(0.290 4±0.002 3)、TGF-β2(0.292 9±0.001 6)、Smad2(0.469 3±0.001 1)、Smad3(0.247 0±0.001 7)、pAKT(0.382 1±0.001 9)、ATK(0.119 6±0.001 6)and MEK1(0.258 9±0.000 3)in the BSP-knockdown group of EC cells decreased(P＜0.01).Conclusion BSP is highly expressed in endometrial cancer and promotes cancer cell proliferation,invasion,and metastasis by activating the TGF-β signaling pathway.

In recent years,protein and polypeptide drugs have developed rapidly and have been widely used to treat cancer,hepatitis,and other diseases.The activity of proteins and polypeptides is closely related to their structure.Protein structures can be divided into four levels:primary,secondary,tertiary,and quaternary structures.The primary structure determines the advanced structure and biological functions of proteins.To ensure drug safety,it is necessary to carry out structural characterization and quality control.The advanced structure is the basis for proteins to express their functions and activities,and changes in spatial structure can lead to alterations in functions.This article reviews the progress of research on the primary and advanced structure characterization of proteins and polypeptides,including techniques such as reversed-phase high-performance liquid chromatography,Edman degradation,mass spectrometry,and spectroscopy.It aims to provide a reference for the structural characterization and quality control of other protein and polypeptide drug products.

Objective:To examine the interaction between interpersonal issues and eating behavior problems among college freshmen, and to identify core psychological factors and potential pathways that drive eating behavior.Methods:In October 2019, a total of 5 073 college freshmen from a university in Shanghai were recruited as participants. Their general demographic data were collected, and they were evaluated using the eating disorder examination questionnaire 6.0 (EDE-Q 6.0) and inventory of interpersonal problems-32(IIP-32).Descriptive analyses were performed using SPSS 24.0 software.A regularized partial correlation network was constructed using the graphical least absolute shrinkage and selection operator (GLASSO) in R(v4.2.3) software. A Bayesian network analysis (BNA) was conducted to build a directed network, aiming to identify core driving factors and key psychological mechanisms.Results:Regularized partial correlation network identified shape concern as the most central node, with the highest strength centrality(1.32) and expected influence(1.20). It showed the highest bridge strength with dominance/control (0.22, 0.21), linking the interpersonal and eating behavior modules. Directed network analysis indicated that low self-confidence was the upstream node influencing social inhibition and cold/ distant relationships, indirectly affecting eating disorder.Within the eating module, shape concern and weight concern predicted eating preoccupation and dietary restraint, forming a pathway structure from eating cognition to behavior.The network demonstrated good stability (CS-coefficient=0.75).Conclusion:Shape concern is the core mechanism underlying eating problems in college freshmen. Low self-confidence contributes indirectly via interpersonal dysfunction. Dominance/control and shape concern bridge interpersonal and eating domains, providing key targets for early prevention and intervention.

Objective:To explore the association between albumin-corrected serum calcium (ACSC) levels and 30-day all-cause mortality in patients hospitalized for community-acquired bacterial pneumonia (CABP).Methods:A secondary analysis was conducted on 1 899 patients with CABP from a Norwegian cohort study. The relationship between baseline ACSC levels and 30-day mortality was assessed using multivariable logistic regression models, adjusted for potential confounders.Results:A significant positive correlation was found between ACSC levels and 30-day mortality risk after adjusting for confounding variables ( OR=1.95, 95% CI=1.48-2.58). When ACSC levels were categorized into tertiles (T1-T3), a trend analysis revealed that the T2 and T3 groups had significantly higher mortality risks compared to the lowest tertile (T1), with odds ratios ( OR) and 95% confidence intervals ( CI) of 1.52(95% CI: 0.97-2.38) and 2.21 (95% CI: 1.44-3.39), respectively ( P for trend <0.001). Subgroup analyses demonstrated no significant interactions across predefined subgroups (all P for interaction > 0.05). Conclusions:In patients with CABP and admission ACSC levels of ≥8.6 mg/dL, higher ACSC levels were positively associated with an increased risk of 30-day mortality. These findings highlight the potential prognostic value of ACSC levels in CABP patients.

Objective:s To investigate the risk factors for delayed encephalopathy after acute carbon monoxide poisoning (DEACMP) in patients with acute carbon monoxide poisoning (ACOP) and to develop predictive models based on machine learning algorithms.Methods:Patients with ACOP hospitalized at the First Affiliated Hospital of Zhengzhou University from August 2019 to October 2024 were included, with the occurrence of DEACMP as the outcome measure. The dataset was randomly divided into training and validation sets at a ratio of 7:3. Lasso regression was used to select features influencing the outcome in training sets. Nine machine learning models—including Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Support Vector Machine (SVM)—were constructed. Receiver operating characteristic (ROC) curves were plotted and the area under the curve (AUC) calculated for each model. Calibration curves were used to assess accuracy, and decision curve analysis (DCA) was applied to evaluate clinical utility. The SHapley Additive exPlanations (SHAP) method was employed to visualize and interpret the best-performing model.Results:A total of 264 ACOP patients were included, of whom 54 (20.5%) developed DEACMP. Lasso regression identified eight key feature variables. Based on these factors, predictive models were constructed, showing good AUC stability across the nine machine learning models in both training (0.92–0.99) and validation sets (0.85–0.91). The RF model performed best, with an AUC of 0.99 in the training set and 0.90 in the validation set; its calibration curve and DCA curve also demonstrated excellent performance. SHAP analysis of the RF model revealed the importance ranking of factors from highest to lowest as follows: Glasgow Coma Scale (GCS) score, duration of coma, age, history of coronary heart disease, CK-MB level, monocyte count, diastolic blood pressure (DBP), and drinking history.Conclusions:The RF model exhibited the highest predictive performance for DEACMP occurrence in ACOP patients. The influencing factors, ranked in order of importance from highest to lowest, are as follows: GCS score, duration of coma, age, history of coronary heart disease, CK-MB level, monocyte count, DBP, and drinking history.

OBJECTIVE: To explore the risk factors affecting the prognosis of patients with sepsis complicated with acute pulmonary embolism, and to construct and validate a nomogram predictive model for in-hospital mortality risk. METHODS: Based on the American Medical Information Mart for Intensive Care (MIMIC-III, MIMIC-IV) databases, the data were collected on patients with sepsis complicated with acute pulmonary embolism from 2001 to 2019, including baseline characteristics, and vital signs, disease scores, laboratory tests within 24 hours of admission to the intensive care unit (ICU), and interventions. In-hospital mortality was the outcome event. The total samples were divided into training and testing sets in a 7:3 ratio by random sampling. Univariate Cox regression analysis was used to verify the impact of all variables on the risk of in-hospital mortality, thereby screen potential influencing factors. Subsequently, a stepwise bi-directional regression method was applied to select factors one by one, leading to the construction of a nomogram prediction model. Collinearity testing was used to demonstrate the absence of strong multicollinearity among the influencing factors in the nomogram prediction model. The discrimination of the nomogram model, sequential organ failure assessment (SOFA), and simplified pulmonary embolism severity index (sPESI) was evaluated using C-index in the test set. Receiver operator characteristic curve (ROC curve) was drawn to evaluate the predictive value of various models for in-hospital mortality in patients with sepsis complicated with acute pulmonary embolism. RESULTS: A total of 562 patients with sepsis complicated with acute pulmonary embolism were included, including 393 in the training set and 169 in the testing set. Univariate Cox regression analysis showed that 30 factors associated with in-hospital mortality in patients with sepsis complicated with acute pulmonary embolism. Through stepwise bi-directional regression, 12 variables were ultimately selected, including gender, presence of malignant tumors, body temperature, red cell distribution width (RDW), blood urea nitrogen (BUN), serum potassium, prothrombin time (PT), 24-hour urine output, mechanical ventilation, vasoactive drugs, warfarin use, and sepsis-induced coagulopathy (SIC). Collinearity testing indicated no strong multicollinearity among the influencing factors [all variance inflation factor (VIF) > 10]. A nomogram model was constructed using the 12 variables mentioned above. The nomogram model predicted the C-index and its 95% confidence interval (95%CI) of in-hospital mortality in patients with sepsis complicated with acute pulmonary embolism better than SOFA score and sPESI [0.771 (0.725-0.816) vs. 0.579 (0.519-0.639), 0.608 (0.554-0.663)]. The ROC curve showed that the area under the curve (AUC) and its 95%CI of the nomogram model were higher than those of the SOFA score and sPESI [0.811 (0.766-0.857) vs. 0.630 (0.568-0.691), 0.623 (0.566-0.680)]. These findings were consistently replicated in the internal validation of the testing set. In both the training and testing sets, Delong's test showed that the AUC of the nomogram model was significantly higher than the SOFA score and sPESI (both P < 0.05). CONCLUSION The nomogram model demonstrated good predictive effectiveness for the risk of in-hospital mortality in patients with sepsis complicated with acute pulmonary embolism, enabling clinicians to predict mortality risk in advance and take timely interventions to reduce mortality.
Humans ; Pulmonary Embolism/mortality* ; Hospital Mortality ; Nomograms ; Sepsis/complications* ; Prognosis ; Risk Factors ; Intensive Care Units ; Male ; Female ; Middle Aged ; Aged

Objective:To investigate the effect of circulating plasma cell(CPC)on the prognosis of multiple myeloma(MM),and to es-tablish and validate a modified CPC-RISS staging system based on CPC and RISS.Methods:A retrospective analysis was performed for the clinical data of 639 treatment-na?ve patients with MM who were treated in Department of Hematology,Xijing Hospital,from January 2006 to June 2023.Peripheral blood smear was used to calculate the percentage of CPC in patients,and the impact of CPC and other related factors on the prognosis of MM patients was analyzed.A CPC-RISS staging system was established based on RISS stage and the percentage of CPC,and the differences in survival and prognosis were analyzed between patients with different stages.Results:Compared with the patients without CPC,detectable CPC was significantly associated with various high-risk factors for MM,and the MM patients with CPC had a lower complete remission rate and shorter overall survival time and progression-free survival time.The modified CPC-RISS staging system was used to classify the patients with MM into four stages,and there were significant differences in median survival time and progression-free survival time between the patients with different stages of MM.Conclusion:The MM pa-tients with the presence of CPC exhibit more aggressive features,worse response to treatment,and a reduction in long-term survival rate.The modified CPC-RISS staging system can effectively predict the prognosis of treatment-na?ve MM patients.

BACKGROUND: The incidence and mortality rates of lung cancer remain on the rise, creating an urgent need for screening among high-risk populations and early prevention. This study aims to explore the association and interaction between multidimensional lifestyle, socioeconomic status, and the incidence of lung cancer, and to provide scientific evidence for screening high-risk populations and preventing lung cancer. METHODS: Healthy lifestyle score was constructed using information on smoking, alcohol consumption, exercise, diet and sleep obtained through a questionnaire survey. Socioeconomic status was evaluated based on information on education, employment, and family income, and genetic testing data were used to assess the risk of genetic variation. A proportional hazards assumption test was conducted, and the Cox proportional hazards model was applied to analyze the associations between healthy lifestyle scores, socioeconomic status, and lung cancer, as well as the interactions among various factors, after adjusting for the risk of genetic variation, age, gender, diabetes, hypertension and the living environment score. RESULTS: A total of 245,538 samples that entered the cohort from March, 2006 to October, 2010 were included and followed up until December 31, 2022. The participants were divided into the case group (n=1472) and the control group (n=244,066). The analysis results showed that after adjusting for covariates, there was still an association between the healthy lifestyle score, socioeconomic status, and the incidence of lung cancer: compared with participants with a high healthy lifestyle score, the risk of lung cancer in participants with medium and low healthy lifestyle scores was significantly increased, with hazard ratios (HR) of 2.12 (95%CI: 1.86-2.41) and 3.36 (95%CI: 2.82-3.99) respectively; compared with participants with high socioeconomic status, the risk of lung cancer in participants with medium and low socioeconomic status was significantly increased, with HR of 1.29 (95%CI: 1.13-1.48) and 1.67 (95%CI: 1.46-1.90) respectively. Moreover, there were interactions between smoking status and socioeconomic status (Pfor interaction=0.05), as well as the other four lifestyle factors (Pfor interaction=0.02). CONCLUSIONS This study identified the association between multidimensional lifestyle factors and socioeconomic status with the incidence of lung cancer, as well as interactions between smoking and socioeconomic status and four other lifestyle factors, providing a scientific basis for screening and prevention in high-risk populations for lung cancer.
Humans ; Lung Neoplasms/epidemiology* ; Male ; Female ; Middle Aged ; Incidence ; Life Style ; Social Class ; Aged ; Adult ; Risk Factors

Objective:To describe the distribution characteristics of alcohol consumption in adult twins in the Chinese National Twin Registry (CNTR), and further explore the influence of genetic factors on alcohol consumption in adult twins.Methods:The subjects of the study were twins registered by CNTR in 11 project areas across China from 2010 to 2018. A total of 56 966 twins (28 483 pairs) aged 18 years and above who answered questions about drinking behavior were included, and the random effect model was used to describe the population and regional distribution characteristics of alcohol consumption. Intra-pair analysis was performed to calculate the concordance rate and heritability of their alcohol consumption.Results:The age of all subjects was (36.6±12.0) years, and current drinkers accounted for 16.6% (9 461/56 966) of all subjects. In men, those aged 50-59 years, those in northern China, those living in rural area, those with low education level and those with high BMI, the proportions of current drinkers were higher. After excluding 468 pairs of twins who had stopped alcohol use and 21 764 pairs of twins who had no drink or had small amount drink, an intra-pair analysis was conducted in 4 929 pairs of same-sex twins, and found that the concordance rate of alcohol consumption was 64.0% (2 059/3 215) in monozygotic twins, and 52.6% (902/1 714) in dizygotic twins, the difference was significant ( P<0.001), and the heritability of alcohol consumption was 24.1% (95% CI: 18.9%- 29.3%). The further stratified analysis found that in southern men, the heritability was highest in those aged 40-49 years (36.1%, 95% CI: 21.6%-50.7%), while in northern men, the heritability was highest in those aged 50-59 years (34.2%, 95% CI: 18.1%-50.3%). Conclusions:In adult twins in China, there were population and regional differences in the distribution of alcohol consumption behavior, and alcohol consumption was influenced by genetic factors, and gender, age and region had potential modifying effects.

Purpose To investigate the expression of bone sialoprotein(BSP)in the tissues and cells of endome-trial cancer(EC)and its effects on the proliferation and invasion of EC cells.Methods The expression of BSP was assessed by immunohistochemistry in 235 EC tissues and 88 normal endometrial tissues,and its correlation with clinico-pathological features was analyzed.Western blot was used to compare BSP levels between human endometrial carcinoma cell line(HHUA)and normal human endumetial epithelial cells(HEEC).BSP was knocked down in HHUA cells via transient transfection,and the cells were divided into blank control group and BSP-knockdown group.The effects of BSP knockdown on cell cycle,proliferation,migration,invasion,and apoptosis were evaluated using PI staining,CCK-8,scratch,Transwell,and Annexin V-FITC assays,respectively.Protein levels of TGF-β signaling pathway compo-nents were analyzed by Western blot.Results BSP expression was significantly higher in EC tissues than in normal endometrium(P＜0.001)and correlated with lymph node metastasis and advanced FIGO stage(P＜0.05).BSP pro-tein level was also significantly elevated in HHUA cells(2.455 8±0.008 9)compared to HEECs(1.571 2±0.005 4)(P＜0.01).After knockdown,compared with the control group,the proliferation index(74.4±3.33),migration rate(0.48±0.03),and invasion ability(0.36±0.11)of the cells were increased,and the apoptosis rate(25.97％)of the cells was increased(P＜0.05).Furthermore,the expression levels of TGF-β signaling pathway downstream proteins TGF-β1(0.290 4±0.002 3)、TGF-β2(0.292 9±0.001 6)、Smad2(0.469 3±0.001 1)、Smad3(0.247 0±0.001 7)、pAKT(0.382 1±0.001 9)、ATK(0.119 6±0.001 6)and MEK1(0.258 9±0.000 3)in the BSP-knockdown group of EC cells decreased(P＜0.01).Conclusion BSP is highly expressed in endometrial cancer and promotes cancer cell proliferation,invasion,and metastasis by activating the TGF-β signaling pathway.