Objective To analyze the epidemiologic burden of colorectal cancer in Xishan District, Kunming City, Yunnan Province from 2018 to 2020. Methods Indicators of epidemiologic burden were calculated, including incidence rate, mortality rate, age-specific incidence/mortality rates, potential years of life lost (PYLL), and disability-adjusted life years (DALY) based on the National Disease Control and Prevention Center’s "Cancer Information Registration and Reporting System" and "Cause of Death Registration System". Results From 2018 to 2020, the ASR (China) for the incidence of colorectal cancer in Xishan District, Kunming City increased from 25.27/10⁵ to 26.29/10⁵, while the ASR (China) for mortality decreased from 17.11/10⁵ to 16.03/10⁵. The PYLL in 2018–2020 were 1399.63, 1376.78, and 1571.56 person-years, respectively, whereas the DALY in 2018–2020 were 1927.74, 1875.05, and 1945.17 person-years, respectively. The morbidity, mortality, PYLL, and DALY were generally higher in males than in females over 45 years of age. Conclusion Given the parallel trends of persistent incidence risk and steadily declining mortality for colorectal cancer in Xishan District, Kunming City, a three-tier prevention and control system centered on "lifestyle intervention–regular screening–positive case tracking" should be established, with a focus on covering high-risk populations, particularly males over 45 years of age.

Objective To analyze the virulence genes and antibiotics resistance of Escherichia coli(E.coli)isolates cause urinary tract infection(USI)in children,and further understand the epidemiological characteristics of E.coli isolates in children with USI.Methods Children with urinary system infection admitted to Quanzhou Maternity and Child Health Care Hospital&Children's Hospital from January to December 2021 were collected.E.coli was isolated from urine,and the drug sensitivity of the E.coli to 15 commonly used clinical antibiotics was detected by instruments.Among them,33 strains of E.coli that showed Extended-spectrum beta-lactamase(ESBL)production were increased,genomic DNA was extracted,and the whole genome sequence of the strains was analyzed by high-throughput sequencing technology.Results In the gene sequence analysis of 33 strains of E.coli,86 virulence genes were obtained,and the bacterial structural virulence genes accounted for the most(43/86),including capsular,fimbriae and cell-membrane system,followed by functional virulence genes and toxigenic genes,while fimH,fdeC and terC virulence genes had the highest detection rates.In the analysis of drug resistance,Cefazolin(96.97%)was the most resistant,and carbapenems were also found to be resistant.In addition,39 inactivation genes,18 target alteration genes and 51 e?ux system genes were obtained.The most information related to antibiotic e?ux(1 273/1 815),mainly RND and MFS superfamily e?ux pumps.There were 19～43 drug resistance genes in each E.coli genome.A variety of β-lactamase resistance genes were found,in which CTX-M/EC/TEM gene family dominated.Conclusion In the urine isolation of ESBL-producing E.coli in USI children,the β-lactamase should continue to be monitored.Virulence genes fimH,fdeC,terC and acrAB/emrAB/mdtABC-TolC e?ux pump gene detected higherratio,should be more attention.

BACKGROUND: Concurrent chemo-radiotherapy (CCRT) is the standard treatment for locally advanced cervical cancer (LACC), but there are still many patients who suffer tumor recurrence. However, valuable predictors of treatment outcomes remain limited. This study aimed to assess the value of the serum immune biomarkers to predict the prognosis. METHODS: We reviewed cervical cancer patients treated with CCRT between January 2014 and May 2018 at Peking Union Medical College Hospital. The systemic immune inflammation index (SII), systemic inflammation response index (SIRI), and lactate dehydrogenase (LDH) were calculated using blood samples. The relationship between immune markers and the treatment outcome was analyzed. The area under the receiver operating characteristic (ROC) curve was used to evaluate the predictive efficiency. The Cox proportional hazards model and log-rank were used to predict overall survival (OS) and disease-free survival (DFS). RESULTS: This study included 667 patients. Among them, 195 (29.2%) patients were defined as treatment failure, including 127 (19.0%) patients with pelvic failure, 94 (14.1%) distant failure, and 25 (3.7%) concurrent pelvic and distant failure. It revealed that the tumor stage, size, metastatic lymph nodes (MLNs), and serum immune biomarkers, such as SII, SIRI, and LDH, were significantly related to treatment outcomes. We demonstrated that the optimal cut-off of the SII, SIRI, and LDH were 970.4 × 10 9 /L, 1.3 × 10 9 /L, and 207.52 U/L, respectively. Importantly, this study presented that LDH level had the highest OR (OR = 4.2; 95% CI [2.3-10.8]). Furthermore, the OS and DFS for patients with pre-SII ≥970.5 × 10 9 /L were significantly worse than those with pre-SII <970.5 × 10 9 /L. Similarly, pre-SIRI ≥1.25 × 10 9 /L and pre-LDH ≥207.5 U/L were related to poor survival outcomes. CONCLUSIONS This study demonstrated that the baseline SII, SIRI, and LDH levels can be used to accurately and effectively predict the treatment outcomes after CCRT and long-term prognosis. Our results may offer additional prognostic information in clinical, which helps to detect the potential recurrent metastasis in time.
Humans ; Female ; Uterine Cervical Neoplasms/drug therapy* ; Middle Aged ; Adult ; Aged ; Chemoradiotherapy/methods* ; L-Lactate Dehydrogenase/blood* ; Treatment Outcome ; Disease-Free Survival ; Prognosis ; ROC Curve ; Biomarkers, Tumor/blood* ; Proportional Hazards Models

Objectives To identify key clinical factors influencing recurrence in osteosarcoma patients,to construct and validate a Nomogram-based recurrence risk prediction model,thereby providing a quantitative tool for clinical decision-making and recurrence prevention/control.Methods Clinical data of 469 osteosarcoma patients admitted to Yunnan Cancer Hospital between 2013～2022 were retrospectively collected.Statistical analysis was performed using R software(version 4.3.2).Potential influencing factors were initially screened via univariate analysis and LASSO regression analysis.Independent predictors of osteosarcoma recurrence were then identified using multivariate logistic regression analysis.Based on the identified independent factors,a Nomogram prediction model for recurrence risk was constructed.The area under the receiver operating characteristic curve(AUC)was used to evaluate the model's discriminative ability.Results Among the entire cohort,68 patients experienced recurrence,yielding a recurrence rate of 14.50%.Multivariate analysis identified the following as independent predictors of recurrence:Primary Tumor Location:Tibial lesions(P=0.009)were associated with a significantly lower recurrence risk compared to femoral lesions(OR=0.297),while lesions in"Other Bones"(P=0.008)carried a significantly higher risk(OR=3.294).Biopsy Method:Needle biopsy(P=0.033)was associated with a significantly lower recurrence risk compared to open biopsy(OR=0.461).Lung Metastasis Status:Patients with lung metastasis(P<0.001)had a significantly higher recurrence risk than those without(OR=11.873).Lymphocyte Count:A higher lymphocyte count(P=0.001)was a protective factor,associated with a lower recurrence risk(OR=0.450).The constructed Nomogram prediction model demonstrated excellent performance:Validation results showed an AUC=0.842(95%CI:0.806～0.875),indicating outstanding discriminative ability.Conclusions This study successfully constructed and validated a Nomogram prediction model for osteosarcoma recurrence risk integrating key clinical factors.The model demonstrates superior discriminative ability and can accurately and quantitatively assess the recurrence risk for individual patients.This tool thus provides critical reference for guiding clinical treatment decisions.

Lean six sigma (LSS) emphasizes patient demand-oriented, and continuously optimizing prolesses to achieve efficiency and standardization in medical services. Starting in 2021, a specialized children′s hospital (comprising one main campus and three branch campuses) introduced the LSS management method. Through define, measure, analyze, improve, and control, the hospital utilized tools such as questionnaire surveys, SIPOC models, and fishbone diagrams to identify pain points in the building of multi-campus child-friendly hospital and develop improvement measures.To address the main issues of insufficient cross-campus collaboration, significant disparities in service quality among different campuses, unclear functional positioning of each campus, and inadequate integration with social security mechanisms, the hospital implemented a " homogeneity-differentiation-coordination" management mode. The hospital implemented unified diagnosis and treatment standards and clinical pathways, carried out remote consultations and expert rotations, completed mutual recognition of examination and testing results, optimized child friendly labeling and child friendly environment, and built a " hospital-to-hospitals, hospital to medical schools, and hospital to community health centers" linkage platform, etc., to promote the standardization of diagnosis and treatment processes, clear functional positioning of the hospital area, and efficient resource allocation. Through practice, the outpatient appointment rate and patient satisfaction rate in the main hospital had increased from 86.72% and 98.64% in January December 2021 to 91.87% and 99.72% in January December 2024, respectively; The patient waiting time had been shortened from 26.54 minutes to 21.94 minutes, and the efficiency of medical treatment and service experience had been significantly improved. As of 2024, mutual recognition of 214 inspection and testing items had been achieved cross hospital campuses, forming a collaborative pattern of " main hospital leading, campuses support, and resource complementarity", and significantly improving the level of collaboration and child friendly connotation among multi-campus. This practice explored the integration path of multi-campus collaborative governance and child-friendly services, which could provide reference and inspiration for the similar hospitals.

Objective To analyze the virulence genes and antibiotics resistance of Escherichia coli(E.coli)isolates cause urinary tract infection(USI)in children,and further understand the epidemiological characteristics of E.coli isolates in children with USI.Methods Children with urinary system infection admitted to Quanzhou Maternity and Child Health Care Hospital&Children's Hospital from January to December 2021 were collected.E.coli was isolated from urine,and the drug sensitivity of the E.coli to 15 commonly used clinical antibiotics was detected by instruments.Among them,33 strains of E.coli that showed Extended-spectrum beta-lactamase(ESBL)production were increased,genomic DNA was extracted,and the whole genome sequence of the strains was analyzed by high-throughput sequencing technology.Results In the gene sequence analysis of 33 strains of E.coli,86 virulence genes were obtained,and the bacterial structural virulence genes accounted for the most(43/86),including capsular,fimbriae and cell-membrane system,followed by functional virulence genes and toxigenic genes,while fimH,fdeC and terC virulence genes had the highest detection rates.In the analysis of drug resistance,Cefazolin(96.97%)was the most resistant,and carbapenems were also found to be resistant.In addition,39 inactivation genes,18 target alteration genes and 51 e?ux system genes were obtained.The most information related to antibiotic e?ux(1 273/1 815),mainly RND and MFS superfamily e?ux pumps.There were 19～43 drug resistance genes in each E.coli genome.A variety of β-lactamase resistance genes were found,in which CTX-M/EC/TEM gene family dominated.Conclusion In the urine isolation of ESBL-producing E.coli in USI children,the β-lactamase should continue to be monitored.Virulence genes fimH,fdeC,terC and acrAB/emrAB/mdtABC-TolC e?ux pump gene detected higherratio,should be more attention.

Lean six sigma (LSS) emphasizes patient demand-oriented, and continuously optimizing prolesses to achieve efficiency and standardization in medical services. Starting in 2021, a specialized children′s hospital (comprising one main campus and three branch campuses) introduced the LSS management method. Through define, measure, analyze, improve, and control, the hospital utilized tools such as questionnaire surveys, SIPOC models, and fishbone diagrams to identify pain points in the building of multi-campus child-friendly hospital and develop improvement measures.To address the main issues of insufficient cross-campus collaboration, significant disparities in service quality among different campuses, unclear functional positioning of each campus, and inadequate integration with social security mechanisms, the hospital implemented a " homogeneity-differentiation-coordination" management mode. The hospital implemented unified diagnosis and treatment standards and clinical pathways, carried out remote consultations and expert rotations, completed mutual recognition of examination and testing results, optimized child friendly labeling and child friendly environment, and built a " hospital-to-hospitals, hospital to medical schools, and hospital to community health centers" linkage platform, etc., to promote the standardization of diagnosis and treatment processes, clear functional positioning of the hospital area, and efficient resource allocation. Through practice, the outpatient appointment rate and patient satisfaction rate in the main hospital had increased from 86.72% and 98.64% in January December 2021 to 91.87% and 99.72% in January December 2024, respectively; The patient waiting time had been shortened from 26.54 minutes to 21.94 minutes, and the efficiency of medical treatment and service experience had been significantly improved. As of 2024, mutual recognition of 214 inspection and testing items had been achieved cross hospital campuses, forming a collaborative pattern of " main hospital leading, campuses support, and resource complementarity", and significantly improving the level of collaboration and child friendly connotation among multi-campus. This practice explored the integration path of multi-campus collaborative governance and child-friendly services, which could provide reference and inspiration for the similar hospitals.

Purpose: To intelligently diagnose whether there is bladder outlet obstruction (BOO) in female with decent detrusor contraction ability by focusing on urodynamic study (UDS) data. Materials and Methods: We retrospectively reviewed the UDS data of female patients during urination. Eleven easily accessible urinary flow indicators were calculated according to the UDS data of each patient during voiding period. Eight diagnosis models based on back propagation neural network with different input feature combination were constructed by analyzing the correlations between indicators and lower urinary tract dysfunction labels. Subsequently, the stability of diagnostic models was evaluated by five-fold cross-validation based on training data, while the performance was compared on test dataset. Results: UDS data from 134 female patients with a median age of 51 years (range, 27–78 years) were selected for our study.Among them, 66 patients suffered BOO and the remaining were normal. Applying the 5-fold cross-validation method, the model with the best performance achieved an area under the receiver operating characteristic curve (AUC) value of 0.949±0.060 using 9 UDS input features. The accuracy, sensitivity, and specificity for BOO diagnosis model in the testing process are 94.4%, 100%, and 89.3%, respectively. Conclusions The 9 significant indicators in UDS were employed to construct a diagnostic model of female BOO based on machine learning algorithm, which performs preferable classification accuracy and stability.

Objective:To identify the phosphodiesterase (PDE) activity of the gene product encoded by LA_RS06960 of Leptospira interrogans ( L. interrogans), and analyze whether dinucleotides that can be degraded by PDE can activate macrophages to express innate immune factors. Methods:The LA_RS06960 gene in L. interrogans strain 56601 was amplified by PCR, and the prokaryotic expression system was constructed for the protein expression. The expressed rPDE was purified by Ni-NTA affinity chromatography. High performance liquid chromatography (HPLC) was used to measure the degration of c-di-AMP or 5′-pApA to AMP by rPDE. Real-time fluorescent quantitative RT-PCR (qRT-PCR) was used to detect the changes in the expression of target genes in Leptospira or THP-1 cells associated with innate immune factors during infection. qRT-PCR and ELISA were used to detect the changes in the expression and secretion level of the innate immune factors in macrophages treated with bacterial dinucleotide. Results:The prokaryotic expression system for LA_RS06960 gene of L. interrogans was constracted successfully, and the purified rPDE could degrate 5′-pApA and c-di-AMP into AMP in vitro. The mRNA level of leptospiral LA_RS06960 gene was significantly down-regulated, while IFN-β, TNF-α, IL-6 and IL-1β encoding genes of macrophages were significantly up-regulated during infection. The mRNA level or the secretion level of IFN-β and IL-6 of macrophages were increased after treated with the bacterial dinucleotide substrate of PDE. Conclusions:PDE encoded by LA_RS06960 gene has phosphodiesterase activity, and the bacterial dinucleotide substrate of the PDE could activate the innate immune response of macrophages.

Microglia, the innate immune cells of the retina, can actively monitor changes in the surrounding microenvironment.Photoreceptors, as the primary neurons of the retina, can convert light signals into electrical signals.Microglia play an important role in the function or survival of photoreceptors in various physiological and pathological conditions of the retina.During the development of the retina, microglia phagocytize cell debris and promote neurogenesis and synaptic plasticity.In a healthy retinal environment, microglia can maintain retinal homeostasis, maintain synaptic structure and function of neurons, and secrete neurotrophic factors.In the past, more attention has been paid to the damage of microglia in retinal diseases.In acute retinal injury and stress (retinal detachment, prion-induced damage, light-induced damage), the protective effect of microglial cells on photoreceptors is greater than damage.In retinal chronic inflammatory diseases such as retinitis pigmentosa, age-related macular degeneration and diabetic retinopathy, the immune microenvironment is imbalanced, microglia are over-activated, release a large number of inflammatory factors, phagocytize non-apoptotic photoreceptors, the damage is greater than protective effect.How to utilize the protective effect of microglia and inhibit their damage is of great significance for the treatment of retinal diseases, especially chronic inflammatory diseases.This article reviews the effects of microglia on photoreceptor cells under different retinal conditions.