Objective:To explore the value and related mechanism of preoperative serum sialic acid (SA) on evaluating microvascular invasion (MVI) in patients with intrahepatic cholangiocarcinoma (ICC).Methods:A total of 91 patients who underwent surgical resection and were pathologically diagnosed with ICC from December 2020 to September 2024 at the Oriental Hepatobiliary Surgery Hospital affiliated to the Naval Medical University were included in this retrospective analysis. The patients were divided into non-MVI (41 cases) and MVI groups (50 cases). The general data and laboratory examination indexes were collected and analyzed. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors for predicting MVI. The predictive value of serum indicators for MVI was evaluated by receiver operating characteristic curves. The correlation between MVI and SA was analyzed by point-biserial correlation. ICC cells stably overexpressing β-galactoside α2, 6-sialyltransferase 1 (ST6GAL1) were generated through lentiviral transfection. ST6GAL1 protein expression and mRNA expression were detected by Western blot and quantitative real-time polymerase chain reaction, respectively. Sambucus nigra (SNA) lectin fluorescence staining was used to detect α2, 6-sialylation levels on cells. Cell migration ability was assessed by wound healing and Transwell assays, and cell proliferation was evaluated by colony formation assays.Results:Compared with the non-MVI group, patients in the MVI group exhibited significantly higher levels of fibrinogen, aspartate aminotransferase, gamma-glutamyl transferase, alkaline phosphatase, SA and 5′-nucleotidase (5′-NT) (all P<0.05). Multivariate logistic regression analysis revealed that SA ( OR=1.01,95% CI 1.01-1.02, P=0.023) was the only independent predictor for MVI. The area under curve of SA in predicting MVI was 0.757 (95% CI 0.640-0.870), sensitivity 67.65%, specificity 77.78%. SA was positively correlated with MVI ( r=0.443, P<0.001). ICC cells overexpressing ST6GAL1 were featured with increased mean fluorescence intensity of SNA lectin, and increased level of α2, 6-sialylation on the cell surface (both P<0.05). The number of colonies formed by hypersialylated ICC cells was also increased ( P<0.05), and both the migration rate and the number of migrating cells were significantly higher ( P<0.05). Conclusions:Serum SA is an independent predictor for MVI in ICC patients. Hypersialylation in ICC cells is associated with higher malignancy.

Objective:To analyze differences in the expression of routine laboratory parameters and cerebrospinal fluid (CSF) examination indicators between patients with non-neurosyphilis (syphilis without nervous system involvement) and those with neurosyphilis, to screen for key predictive factors, and to construct a predictive model for neurosyphilis.Methods:A retrospective analysis was conducted on the clinical data from patients with syphilis at the Fifth People's Hospital of Suzhou from 2019 to 2024. Patients with neurosyphilis and non-neurosyphilis who were hospitalized from November 2019 to June 2022 were included in the model cohort, and those hospitalized from January 2024 to October 2024 were included in the validation cohort. The patients' basic information and laboratory test indicators (including routine blood tests, CSF biochemical analysis, and syphilitic antibody tests) were collected. Statistical analysis was performed using the GraphPad software. The receiver operating characteristic (ROC) curve and the binary logistic regression method were used to analyze the predictive performance of key indicators in patients from the model cohort with SPSS software, and a predictive model for neurosyphilis was constructed. The performance of the neurosyphilis predictive model for neurosyphilis was validated based on relevant indicators from the validation cohort.Results:The model cohort included 99 patients with non-neurosyphilis (including 49 males and 50 females), and they were aged between 19 and 85 years, with an average age of 47 years; 69 patients with neurosyphilis were also included in the model cohort, including 58 males and 11 females, and they were aged between 26 and 73 years, with an average age of 51 years. The neurosyphilis group showed a significant increase in the median levels of CSF adenosine deaminase (1 U/L) and microprotein (711 mg/L), white blood cell counts (0.009 × 10?/L), as well as in the proportion of positive Pandy tests (35/69, 50.7%) compared with the non-neurosyphilis group (0 U/L, 309 mg/L, 0.002 × 10?/L, 2 /99 [2.0%], respectively, all P < 0.001). Based on the ROC curve analysis, the CSF microprotein and white blood cell count had relatively high discriminative ability (area under the ROC curve [AUC] > 0.85), while adenosine deaminase and the Pandy test showed moderate discriminative ability (0.7 < AUC < 0.85). According to the above four indicators, the logistic regression analysis showed that CSF microprotein combined with CSF white blood cell counts could construct the best predictive model for neurosyphilis, with a prediction accuracy rate of 0.980, a sensitivity of 98.5%, and a specificity of 89.9%. The prediction formula was logit (p) = -9.926 + 0.015 × microprotein + 362.33 × CSF white blood cell count, with a cutoff value of ≥ -0.867. The validation cohort enrolled 72 patients with non-neurosyphilis and 51 with neurosyphilis, and there were significant differences in CSF microprotein levels and white blood cell counts between the two groups (both P < 0.001). In the validation cohort, the predictive model demonstrated an accuracy of 86.2%, with a sensitivity of 83.6% and a specificity of 91.1% for predicting neurosyphilis. Conclusion:The predictive model for neurosyphilis constructed by combining CSF microprotein and CSF white blood cell count may contribute to the early differential diagnosis of neurosyphilis.

Objective To explore the value of analysis on the incidence of healthcare-associated infection(HAI)based on disease diagnosis-related grouping(DRG),case mix index(CMI),and relative weight(RW).Methods All discharged cases,DRG and HAI status in a tertiary first-class general hospital from January 1 to December 31,2023 were analyzed retrospectively.Incidences of HAI in different departments were adjusted and compared by CMI.Incidences of HAI in different DRG groups were adjusted by RW.Results Among the 47 695 cases included in the analysis,757 were HAI cases,including 225 DRG groups.The department of critical care medicine had the highest incidence of HAI(11.98％).After CMI adjustment,departments with higher incidence of HAI were main-ly the department of respiratory and critical care medicine(3.96％),department of critical care medicine(3.04％),and department of neurology(2.85％),et al.DRG groups with the top five high incidence of HAI were AH11(tracheotomy and with ventilator support ≥96 hours or extracorporeal membrane oxygenation[ECMO],accompa-nied by major complications and comorbidity[MCC],50.00％),BC29(ventricular shunt and revision surgery,31.43％),BB21(craniotomy other than trauma,accompanied by MCC,27.56％),BB11(craniotomy of brain trauma,accompanied by MCC,26.32％),and GB1A(major surgery of esophagus,stomach,and duodenum,accompanied by major or moderate complications and comorbidity,16.00％).After RW adjustment,the DRG groups with the top five high incidence of HAI were ES21(respiratory system infection/inflammation,accompanied by MCC,5.89％),BR21(cerebral ischemic disease,accompanied by MCC,5.17％),FR11(heart failure,shock,accompanied by MCC,4.80％),BC29(4.57％)and AH11(3.57％).Conclusion Analyzing the incidence of HAI based on CMI and RW can help to identify key departments and disease groups for infection prevention and control,and provide reference for precise prevention and control of HAI in the new era.

Objective:To analyze differences in the expression of routine laboratory parameters and cerebrospinal fluid (CSF) examination indicators between patients with non-neurosyphilis (syphilis without nervous system involvement) and those with neurosyphilis, to screen for key predictive factors, and to construct a predictive model for neurosyphilis.Methods:A retrospective analysis was conducted on the clinical data from patients with syphilis at the Fifth People's Hospital of Suzhou from 2019 to 2024. Patients with neurosyphilis and non-neurosyphilis who were hospitalized from November 2019 to June 2022 were included in the model cohort, and those hospitalized from January 2024 to October 2024 were included in the validation cohort. The patients' basic information and laboratory test indicators (including routine blood tests, CSF biochemical analysis, and syphilitic antibody tests) were collected. Statistical analysis was performed using the GraphPad software. The receiver operating characteristic (ROC) curve and the binary logistic regression method were used to analyze the predictive performance of key indicators in patients from the model cohort with SPSS software, and a predictive model for neurosyphilis was constructed. The performance of the neurosyphilis predictive model for neurosyphilis was validated based on relevant indicators from the validation cohort.Results:The model cohort included 99 patients with non-neurosyphilis (including 49 males and 50 females), and they were aged between 19 and 85 years, with an average age of 47 years; 69 patients with neurosyphilis were also included in the model cohort, including 58 males and 11 females, and they were aged between 26 and 73 years, with an average age of 51 years. The neurosyphilis group showed a significant increase in the median levels of CSF adenosine deaminase (1 U/L) and microprotein (711 mg/L), white blood cell counts (0.009 × 10?/L), as well as in the proportion of positive Pandy tests (35/69, 50.7%) compared with the non-neurosyphilis group (0 U/L, 309 mg/L, 0.002 × 10?/L, 2 /99 [2.0%], respectively, all P < 0.001). Based on the ROC curve analysis, the CSF microprotein and white blood cell count had relatively high discriminative ability (area under the ROC curve [AUC] > 0.85), while adenosine deaminase and the Pandy test showed moderate discriminative ability (0.7 < AUC < 0.85). According to the above four indicators, the logistic regression analysis showed that CSF microprotein combined with CSF white blood cell counts could construct the best predictive model for neurosyphilis, with a prediction accuracy rate of 0.980, a sensitivity of 98.5%, and a specificity of 89.9%. The prediction formula was logit (p) = -9.926 + 0.015 × microprotein + 362.33 × CSF white blood cell count, with a cutoff value of ≥ -0.867. The validation cohort enrolled 72 patients with non-neurosyphilis and 51 with neurosyphilis, and there were significant differences in CSF microprotein levels and white blood cell counts between the two groups (both P < 0.001). In the validation cohort, the predictive model demonstrated an accuracy of 86.2%, with a sensitivity of 83.6% and a specificity of 91.1% for predicting neurosyphilis. Conclusion:The predictive model for neurosyphilis constructed by combining CSF microprotein and CSF white blood cell count may contribute to the early differential diagnosis of neurosyphilis.

Objective To explore the value of analysis on the incidence of healthcare-associated infection(HAI)based on disease diagnosis-related grouping(DRG),case mix index(CMI),and relative weight(RW).Methods All discharged cases,DRG and HAI status in a tertiary first-class general hospital from January 1 to December 31,2023 were analyzed retrospectively.Incidences of HAI in different departments were adjusted and compared by CMI.Incidences of HAI in different DRG groups were adjusted by RW.Results Among the 47 695 cases included in the analysis,757 were HAI cases,including 225 DRG groups.The department of critical care medicine had the highest incidence of HAI(11.98％).After CMI adjustment,departments with higher incidence of HAI were main-ly the department of respiratory and critical care medicine(3.96％),department of critical care medicine(3.04％),and department of neurology(2.85％),et al.DRG groups with the top five high incidence of HAI were AH11(tracheotomy and with ventilator support ≥96 hours or extracorporeal membrane oxygenation[ECMO],accompa-nied by major complications and comorbidity[MCC],50.00％),BC29(ventricular shunt and revision surgery,31.43％),BB21(craniotomy other than trauma,accompanied by MCC,27.56％),BB11(craniotomy of brain trauma,accompanied by MCC,26.32％),and GB1A(major surgery of esophagus,stomach,and duodenum,accompanied by major or moderate complications and comorbidity,16.00％).After RW adjustment,the DRG groups with the top five high incidence of HAI were ES21(respiratory system infection/inflammation,accompanied by MCC,5.89％),BR21(cerebral ischemic disease,accompanied by MCC,5.17％),FR11(heart failure,shock,accompanied by MCC,4.80％),BC29(4.57％)and AH11(3.57％).Conclusion Analyzing the incidence of HAI based on CMI and RW can help to identify key departments and disease groups for infection prevention and control,and provide reference for precise prevention and control of HAI in the new era.

Objective:To explore the value and related mechanism of preoperative serum sialic acid (SA) on evaluating microvascular invasion (MVI) in patients with intrahepatic cholangiocarcinoma (ICC).Methods:A total of 91 patients who underwent surgical resection and were pathologically diagnosed with ICC from December 2020 to September 2024 at the Oriental Hepatobiliary Surgery Hospital affiliated to the Naval Medical University were included in this retrospective analysis. The patients were divided into non-MVI (41 cases) and MVI groups (50 cases). The general data and laboratory examination indexes were collected and analyzed. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors for predicting MVI. The predictive value of serum indicators for MVI was evaluated by receiver operating characteristic curves. The correlation between MVI and SA was analyzed by point-biserial correlation. ICC cells stably overexpressing β-galactoside α2, 6-sialyltransferase 1 (ST6GAL1) were generated through lentiviral transfection. ST6GAL1 protein expression and mRNA expression were detected by Western blot and quantitative real-time polymerase chain reaction, respectively. Sambucus nigra (SNA) lectin fluorescence staining was used to detect α2, 6-sialylation levels on cells. Cell migration ability was assessed by wound healing and Transwell assays, and cell proliferation was evaluated by colony formation assays.Results:Compared with the non-MVI group, patients in the MVI group exhibited significantly higher levels of fibrinogen, aspartate aminotransferase, gamma-glutamyl transferase, alkaline phosphatase, SA and 5′-nucleotidase (5′-NT) (all P<0.05). Multivariate logistic regression analysis revealed that SA ( OR=1.01,95% CI 1.01-1.02, P=0.023) was the only independent predictor for MVI. The area under curve of SA in predicting MVI was 0.757 (95% CI 0.640-0.870), sensitivity 67.65%, specificity 77.78%. SA was positively correlated with MVI ( r=0.443, P<0.001). ICC cells overexpressing ST6GAL1 were featured with increased mean fluorescence intensity of SNA lectin, and increased level of α2, 6-sialylation on the cell surface (both P<0.05). The number of colonies formed by hypersialylated ICC cells was also increased ( P<0.05), and both the migration rate and the number of migrating cells were significantly higher ( P<0.05). Conclusions:Serum SA is an independent predictor for MVI in ICC patients. Hypersialylation in ICC cells is associated with higher malignancy.

Chronic skin diseases have complex pathogeneses and prolonged courses, and have long adverse impacts on the physical and mental health, as well as the normal life of patients. It is necessary to develop evidence-based strategies and measures for effective prevention and control of chronic skin diseases. However, related studies are limited in China. This article proposes a population medicine research plan for health promotion and equity, and disease prevention, diagnosis, control, treatment, and rehabilitation to establish a collaborative platform for strengthening research on the prevention and treatment of chronic skin diseases in China.

BACKGROUND: Breast cancer patients who are positive for hormone receptor typically exhibit a favorable prognosis. It is controversial whether chemotherapy is necessary for them after surgery. Our study aimed to establish a multigene model to predict the relapse of hormone receptor-positive early-stage Chinese breast cancer after surgery and direct individualized application of chemotherapy in breast cancer patients after surgery. METHODS: In this study, differentially expressed genes (DEGs) were identified between relapse and nonrelapse breast cancer groups based on RNA sequencing. Gene set enrichment analysis (GSEA) was performed to identify potential relapse-relevant pathways. CIBERSORT and Microenvironment Cell Populations-counter algorithms were used to analyze immune infiltration. The least absolute shrinkage and selection operator (LASSO) regression, log-rank tests, and multiple Cox regression were performed to identify prognostic signatures. A predictive model was developed and validated based on Kaplan-Meier analysis, receiver operating characteristic curve (ROC). RESULTS: A total of 234 out of 487 patients were enrolled in this study, and 1588 DEGs were identified between the relapse and nonrelapse groups. GSEA results showed that immune-related pathways were enriched in the nonrelapse group, whereas cell cycle- and metabolism-relevant pathways were enriched in the relapse group. A predictive model was developed using three genes ( CKMT1B , SMR3B , and OR11M1P ) generated from the LASSO regression. The model stratified breast cancer patients into high- and low-risk subgroups with significantly different prognostic statuses, and our model was independent of other clinical factors. Time-dependent ROC showed high predictive performance of the model. CONCLUSIONS A multigene model was established from RNA-sequencing data to direct risk classification and predict relapse of hormone receptor-positive breast cancer in Chinese patients. Utilization of the model could provide individualized evaluation of chemotherapy after surgery for breast cancer patients.
Humans ; Female ; Breast Neoplasms/genetics* ; East Asian People ; Neoplasm Recurrence, Local/genetics* ; Breast ; Algorithms ; Chronic Disease ; Prognosis ; Tumor Microenvironment

Objective:To assess the susceptibility of gonococcal clinical isolates to gentamicin in Guangxi region, China, and to analyze the correlation between the minimum inhibitory concentration (MIC) of gentamicin and MICs of 7 other antibiotics.Methods:From December 2020 to December 2021, 584 gonococcal clinical isolates were collected from 37 medical institutions in 14 prefecture-level cities in Guangxi region. The susceptibility of gonococcal clinical isolates to ceftriaxone, cefixime, azithromycin, spectinomycin, penicillin, tetracycline, ciprofloxacin and gentamicin was determined by using an agar dilution method. The MIC values of antibiotics were logarithmically transformed with base 2, and Spearman correlation analysis was carried out to evaluate the correlation between the MIC of gentamicin and MICs of the other 7 antibiotics.Results:The MIC of gentamicin ranged from 1 to 16 mg/L, and the MIC50 and MIC90 values were 4 and 8 mg/L, respectively; 361 strains (61.8%) were fully sensitive to gentamicin with the MIC ≤ 4 mg/L, 223 strains (38.2%) moderately sensitive with the MIC ranging from 8 to 16 mg/L, and no gentamicin-resistant strains were found. The number of strains resistant to azithromycin, penicillin, tetracycline and ciprofloxacin was 136 (23.3%), 415 (71.1%), 339 (58.0%) and 574 (98.3%) respectively, the number of lowly sensitive strains to ceftriaxone and cefixime was 17 (2.9%) and 6 (1.0%) respectively, and no spectinomycin-resistant strains were found. Spearman correlation analysis showed that the MIC of gentamicin was weakly correlated with the MICs of azithromycin, spectinomycin, penicillin, tetracycline, and ciprofloxacin (all P < 0.05), but was uncorrelated with the MICs of ceftriaxone and cefixime (both P > 0.05) . Conclusion:All gonococcal clinical isolates tested in this study showed a certain degree of susceptibility to gentamicin, and cross-resistance between gentamicin and other antibiotics was less likely to occur.

Monkeypox is a zoonotic viral disease caused by monkeypox virus infection. Monkeypox has become a public health emergency of international concern, since it first spread widely in many regions outside Africa in 2022. Accurate and effective detection methods are particularly important for the diagnosis and screening of monkeypox virus infection. This review summarizes laboratory testing techniques for monkeypox virus in recent years, and compares principles and detection performance of microscopy, culture, nucleic acid testing and immunological methods.