Objective To describe the significance of the pretreatment inflammatory indicators in predicting the prognosis of patients with esophageal squamous cell carcinoma (ESCC) after undergoing radical radiotherapy. Methods The data of 246 ESCC patients who underwent radical radiotherapy were retrospectively collected. Receiver operating characteristic (ROC) curves were drawn to determine the optimal cutoff values for platelet-lymphocyte ratio (PLR), neutrophil-lymphocyte ratio (NLR), and systemic immune-inflammation index (SII). The Kaplan-Meier method was used for survival analysis. We conducted univariate and multivariate analyses by using the Cox proportional risk regression model. Software R (version 4.2.0) was used to create the nomogram of prognostic factors. Results The results of the ROC curve analysis showed that the optimal cutoff values of PLR, NLR, and SII were 146.06, 2.67, and 493.97, respectively. The overall response rates were 77.6% and 64.5% in the low and high NLR groups, respectively (P<0.05). The results of the Kaplan-Meier survival analysis revealed that the prognosis of patients in the low PLR, NLR, and SII group was better than that of patients in the high PLR, NLR, and SII group (all P<0.05). The results of the multivariate Cox regression analysis showed that gender, treatment modalities, T stage, and NLR were independent factors affecting the overall survival (OS). In addition, T stage and NLR were independent factors affecting the progression-free survival (PFS) (all P<0.05). The nomogram models of OS and PFS prediction were established based on multivariate analysis. The C-index values were 0.703 and 0.668. The calibration curves showed excellent consistency between the predicted and observed OS and PFS. Conclusion The pretreatment values of PLR, NLR, and SII are correlated with the prognosis of patients with ESCC who underwent radical radiotherapy. Moreover, NLR is an independent factor affecting the OS and PFS of ESCC patients. The NLR-based nomogram model has a good predictive ability.

Lipotoxicity is a pivotal factor that initiates and exacerbates liver injury and is involved in the development of metabolic-associated fatty liver disease (MAFLD). However, there are few reported lipotoxicity inhibitors. Here, we identified a natural anti-lipotoxicity candidate, HN-001, from the marine fungus Aspergillus sp. C1. HN-001 dose- and time- dependently reversed palmitic acid (PA)-induced hepatocyte death. This protection was associated with IRE-1α-mediated XBP-1 splicing inhibition, which resulted in suppression of XBP-1s nuclear translocation and transcriptional regulation. Knockdown of XBP-1s attenuated lipotoxicity, but no additional ameliorative effect of HN-001 on lipotoxicity was observed in XBP-1s knockdown hepatocytes. Notably, the ER stress and lipotoxicity amelioration was associated with PLA2. Both HN-001 and the PLA2 inhibitor MAFP inhibited PLA2 activity, reduced lysophosphatidylcholine (LPC) level, subsequently ameliorated lipotoxicity. In contrast, overexpression of PLA2 caused exacerbation of lipotoxicity and weakened the anti-lipotoxic effects of HN-001. Additionally, HN-001 treatment suppressed the downstream pro-apoptotic JNK pathway. In vivo, chronic administration of HN-001 (i.p.) in mice alleviated all manifestations of MAFLD, including hepatic steatosis, liver injury, inflammation, and fibrogenesis. These effects were correlated with PLA2/IRE-1α/XBP-1s axis and JNK signaling suppression. These data indicate that HN-001 has therapeutic potential for MAFLD because it suppresses lipotoxicity, and provide a natural structural basis for developing anti-MAFLD candidates.

Objective To analyze the combined effect of body mass index(BMI)and age with cancer occurrence among a hypertensive population in Minhang District,Shanghai.Methods Participants of this study were 212 394 hypertensive patients without cancer in Minhang District,Shanghai,registered in the electronic health information system from 2007 to 2015.Age and BMI were included as smoothing functions in the generalized additive Cox proportional risk model.The bivariate response model was constructed to visualize results using surface plots and to comprehensively analyze the association of BMI and age with the risk of cancer occurrence.Results A total of 22 141 participants developed cancer by Dec 31,2018.The association between age and the risk of cancer incidence showed an overall linear trend while the association between BMI and the risk of cancer incidence showed an overall"U"shape.BMI at about 26 kg/m2 showed the lowest risk of cancer incidence.The risk of cancer occurrence increased with increasing age in people with different BMIs.The associations between BMI and the risk of cancer incidence were different at different age groups:there was no significant association between BMI and the risk of cancer incidence in the young people(20-44 years).While in the middle-aged and older people aged over 45 years,BMI was associated with the risk of cancer incidence in a"U"shape.The lowest risk of cancer incidence was around the BMI of 26 kg/m2.Conclusion BMI among the population with hypertension should be controlled in a reasonable range,especially in the middle-aged and older population,to prevent cancer occurrence.

This article introduced the basic theory of quantile regression and its application in medical and public health research for methodological reference.We fit the quantile regression model to cross-sectional data from the National Health and Nutrition Examination Survey to estimate the association between sleep duration and depression levels at different quantiles of depression levels.The method showed that among people with low levels of depression,sleep duration was not significantly associated with depression level.While among people with higher levels of depression,the association of sleep duration with depression level became much more pronounced.The real data analysis shows that quantile regression can provide a comprehensive analysis of association between exposure and continuous outcome,and identify subgroups that are more sensitive to exposure,providing recommendations for targeted interventions.The method showed promising application value in medical and public health research.

This article introduced the basic theory of non-parametric regression and its application in medical and public health research for methodological reference.We conducted Cox proportional hazard models with restricted cubic splines using chronic disease management data from a Center for Disease Control and Prevention.We aimed to explore the separate and combined effects of mean fasting blood glucose level and glucose variability on all-cause mortality among individuals with type 2 diabetes.A non-linear association was observed between glucose variability and the risk of all-cause mortality.The association between glucose variability and all-cause mortality was stronger at higher mean fasting blood glucose levels compared to lower levels.The non-parametric regression methods comprehensively explored dose-response relationships between continuous exposure and outcome,revealing the combined effects of continuous exposures,which provided recommendations for targeted interventions.The method showed promising application value in medical and public health research.

Objective To develop the functions and optimize the automatic monitoring module for arrhythmias of the adverse drug event active surveillance and assessment system-Ⅱ,in order to continuously improve the performance,enhance the monitoring efficiency,and explore the ways to optimize the module.Methods Expand and optimize the functions of the module,increase the customized configuration,and determine the optimal setting conditions;compare the optimized test data with the results of the evaluation studies on the automatic monitoring of drug-induced arrhythmias in large samples of medicated population previously,and verify the optimization extent as well as the accuracy of the module.Results In the new module optimized according to the characteristics of the monitoring population,the function of"mandatory medical order keywords"was added,and it was determined that the inclusion of 6 electrocardiogram examination-related medical order keywords with a frequency of not less than 2 occurrences was the optimal configuration condition for the optimization of the module;combining the results of the previous automatic monitoring and evaluation researches,the system functions were verified and compared under the conditions of using the whole drugs and 2 kinds of single drug.While there was no loss of true positive cases,the number of cases with system alarms decreased by 30.75％,80.13％and 90.82％,respectively,compared with that before the optimization of the module,and the positive predictive value was significantly improved.Conclusion After the function expansion and optimization,the automatic monitoring module of drug-induced arrhythmias significantly reduces the labor cost of case evaluation and keeps the accuracy of monitoring results constant;the new module can better adapt to the demands of different automatic monitoring modes and operates stably,which is more generalizable and flexible,and provides a new way of considering for the research and development of automatic monitoring modules.

Temporomandibular joint (TMJ) diseases are common clinical conditions. The number of patients with TMJ diseases is large, and the etiology, epidemiology, disease spectrum, and treatment of the disease remain controversial and unknown. To understand and master the current situation of the occurrence, development and prevention of TMJ diseases, as well as to identify the patterns in etiology, incidence, drug sensitivity, and prognosis is crucial for alleviating patients′suffering.This will facilitate in-depth medical research, effective disease prevention measures, and the formulation of corresponding health policies. Cohort construction and research has an irreplaceable role in precise disease prevention and significant improvement in diagnosis and treatment levels. Large-scale cohort studies are needed to explore the relationship between potential risk factors and outcomes of TMJ diseases, and to observe disease prognoses through long-term follw-ups. The consensus aims to establish a standard conceptual frame work for a cohort study on patients with TMJ disease while providing ideas for cohort data standards to this condition. TMJ disease cohort data consists of both common data standards applicable to all specific disease cohorts as well as disease-specific data standards. Common data were available for each specific disease cohort. By integrating different cohort research resources, standard problems or study variables can be unified. Long-term follow-up can be performed using consistent definitions and criteria across different projects for better core data collection. It is hoped that this consensus will be facilitate the development cohort studies of TMJ diseases.

Objective Viral encephalitis is an infectious disease severely affecting human health.It is caused by a wide variety of viral pathogens,including herpes viruses,flaviviruses,enteroviruses,and other viruses.The laboratory diagnosis of viral encephalitis is a worldwide challenge.Recently,high-throughput sequencing technology has provided new tools for diagnosing central nervous system infections.Thus,In this study,we established a multipathogen detection platform for viral encephalitis based on amplicon sequencing. Methods We designed nine pairs of specific polymerase chain reaction(PCR)primers for the 12 viruses by reviewing the relevant literature.The detection ability of the primers was verified by software simulation and the detection of known positive samples.Amplicon sequencing was used to validate the samples,and consistency was compared with Sanger sequencing. Results The results showed that the target sequences of various pathogens were obtained at a coverage depth level greater than 20×,and the sequence lengths were consistent with the sizes of the predicted amplicons.The sequences were verified using the National Center for Biotechnology Information BLAST,and all results were consistent with the results of Sanger sequencing. Conclusion Amplicon-based high-throughput sequencing technology is feasible as a supplementary method for the pathogenic detection of viral encephalitis.It is also a useful tool for the high-volume screening of clinical samples.

Objective To develop an automatic urine volume detection and collection device to solve the problems of routine urine test.Methods An automatic urine volume detection and collection device was developed with the components of a main control system,a detection system,a prompting system and a grasping and moving system.The main control system consisted of two STM32 microcontrollers and a reset switch;the detection system was made up of a weighing module,an infrared module and indicator lights,which had its urine volume automatic detection algorithm developed based on the Keil5 platform;the prompting system realized voice broadcasting through the voice module fixed on the back panel of the box;the grasping and moving system was composed of a rail drive motor(86CM stepper motor),a photoelectric switch and a motorized gripper.Results The device developed tested urine samples with an accuracy of 99.44％,and could collect qualified samples automatically and quickly.Conclusion The device developed detects urine volume and collects samples automatically,and enhances the accuracy and efficiency of urine examination.[Chinese Medical Equipment Journal,2024,45(4):66-69]

Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in tertiary hospitals in major regions of China in 2022.Methods Clinical isolates from 58 hospitals in China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2022 Clinical &Laboratory Standards Institute(CLSI)breakpoints.Results A total of 318 013 clinical isolates were collected from January 1,2022 to December 31,2022,of which 29.5％were gram-positive and 70.5％were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species(excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi)was 28.3％,76.7％and 77.9％,respectively.Overall,94.0％of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 90.8％of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis showed significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 94.2％in the isolates from children and 95.7％in the isolates from adults.The resistance rate to carbapenems was lower than 13.1％in most Enterobacterales species except for Klebsiella,21.7％-23.1％of which were resistant to carbapenems.Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.1％to 13.3％.The prevalence of meropenem-resistant strains decreased from 23.5％in 2019 to 18.0％in 2022 in Pseudomonas aeruginosa,and decreased from 79.0％in 2019 to 72.5％in 2022 in Acinetobacter baumannii.Conclusions The resistance of clinical isolates to the commonly used antimicrobial agents is still increasing in tertiary hospitals.However,the prevalence of important carbapenem-resistant organisms such as carbapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a downward trend in recent years.This finding suggests that the strategy of combining antimicrobial resistance surveillance with multidisciplinary concerted action works well in curbing the spread of resistant bacteria.