Objective To explore the value of inflammatory load index(IBI)in the diagnosis and prognosis of gastric cancer patients.Methods Clinical data of patients who underwent gastric cancer surgery in the Department of General Surgery of the Second Hospital of Lanzhou University from January 2016 to December 2018 were retrospectively analyzed,and the patients were divided into the high IBI group and the low IBI group based on the optimal cut-off value of IBI.ROC curve was used to determine the optimal cut-off value of IBI,and the survival curve was constructed using the Kaplan-Meier method,and the differences between groups were examined using the Log-rank test.Cox regression analysis was performed to study the prognostic factors of gastric cancer patients.Results The best cut-off value for IBI diagnosis was 8.796,and the best cut-off value for prognosis was 28.75.IBI was related to the clinical case characteristics of gastric cancer patients,such as surgical access,the degree of differentiation,CK7,CK20,LMP-1,and Ki-67(P＜0.05).The results of univariate analysis showed that intraoperative bleeding,preoperative CEA,preoperative CA125,preoperative CA199,IBI,tumor diameter size,margins of incision,vascular invasion,nerve invasion,pT stage and pN stagewere the influencing factors on the prognosis of gastric cancer patients(P＜0.05).The results of multifactorial regression analysis showed that intraoperative bleeding,preoperative CEA,preoperative CA199,IBI,tumor diameter size,pT stage and pN stagewere independent risk factors affecting the prognosis of gastric cancer patients(P＜0.05).The median OS of patients in the high IBI group and low IBI group were 32.9 months and 74.8 months,respectively,with statistically significant differences(P＜0.001).Conclusion IBI is an independent risk factor for poor prognosis of patients with gastric cancer,and it has a good predictive value in diagnosis and prognosis.

Aim To infer novel therapeutic and phar-macological targets related to lung cancer treatment through multiomics approaches,so as to provide new directions for developing more personalized and effec-tive treatment strategies.Methods Genome-wide as-sociation study(GWAS)data analysis,pan-cancer,single-cell,transcriptomics,and protein-protein interac-tion analysis were employed in this study.Results We analyzed biomarkers and therapeutic targets associ-ated with lung cancer.The study identified key bio-markers closely related to lung cancer progression and explored the interrelationships between these biomark-ers and viral infections.According to KEGG pathway annotation,the number of genes related to metabolic processes increased significantly.In particular,metab-olites such as alanine and isoleucine emerged as pivotal factors in therapeutic interventions.The IgD+CD24+and IgD+CD24-B cell subsets were identified as cen-tral elements in immune evasion and treatment re-sponse.Concurrently,the Lachnospiraceae and Prevo-tella were shown to modulate host immune responses and the tumor microenvironment by regulating short-chain fatty acid levels,thereby opening novel avenues for cancer research.Conclusions Through mul-tiomics analysis combined with transcriptomics and pro-teomics analysis,we identify several potential therapeu-tic targets for lung cancer,providing key insights for developing novel treatment strategies.

Objective To explore the value of inflammatory load index(IBI)in the diagnosis and prognosis of gastric cancer patients.Methods Clinical data of patients who underwent gastric cancer surgery in the Department of General Surgery of the Second Hospital of Lanzhou University from January 2016 to December 2018 were retrospectively analyzed,and the patients were divided into the high IBI group and the low IBI group based on the optimal cut-off value of IBI.ROC curve was used to determine the optimal cut-off value of IBI,and the survival curve was constructed using the Kaplan-Meier method,and the differences between groups were examined using the Log-rank test.Cox regression analysis was performed to study the prognostic factors of gastric cancer patients.Results The best cut-off value for IBI diagnosis was 8.796,and the best cut-off value for prognosis was 28.75.IBI was related to the clinical case characteristics of gastric cancer patients,such as surgical access,the degree of differentiation,CK7,CK20,LMP-1,and Ki-67(P＜0.05).The results of univariate analysis showed that intraoperative bleeding,preoperative CEA,preoperative CA125,preoperative CA199,IBI,tumor diameter size,margins of incision,vascular invasion,nerve invasion,pT stage and pN stagewere the influencing factors on the prognosis of gastric cancer patients(P＜0.05).The results of multifactorial regression analysis showed that intraoperative bleeding,preoperative CEA,preoperative CA199,IBI,tumor diameter size,pT stage and pN stagewere independent risk factors affecting the prognosis of gastric cancer patients(P＜0.05).The median OS of patients in the high IBI group and low IBI group were 32.9 months and 74.8 months,respectively,with statistically significant differences(P＜0.001).Conclusion IBI is an independent risk factor for poor prognosis of patients with gastric cancer,and it has a good predictive value in diagnosis and prognosis.

BACKGROUND:Studies have shown that gut microbiota may affect the progression of rheumatoid arthritis.However,the causal relationship between the two is unknown.Mendelian randomization analysis of the two using published Genome Wide Association Study(GWAS)data can explore the causal relationship between gut microbiota and rheumatoid arthritis,helping to develop targeted microbial therapies and provide methods and strategies for the prevention and treatment of rheumatoid arthritis.OBJECTIVE:To explore the potential causal relationship between gut microbiota and rheumatoid arthritis using two-sample two-way Mendelian randomization method.METHODS:Gut microbiota GWAS data from the MiBio-Gen consortium and rheumatoid arthritis GWAS data from the IEU Open GWAS database(a large gene-phenotype association database developed at the MRC Integrative Epidemiology Unit(IEU)at the University of Bristol,UK)were used.Inverse variance weighting was used as the main analysis method,and MR-Egger regression method,weighted median method,weighted model and simple model method were used as supplements to study the causal relationship between gut microbiota and rheumatoid arthritis.Heterogeneity was assessed using Cochran's Q test,horizontal pleiotropy was assessed using MR-PRESSO and MR-Egger intercept tests,robustness of results was tested using leave-one method,and reverse Mendelian randomization analysis was used to assess the presence or absence of reverse causality.RESULTS AND CONCLUSION:(1)There was a causal relationship between five kinds of enteric bacteria and rheumatoid arthritis.Ruminococcus gauvreauii group(β=0.262,odds ratio[OR]=1.300,P=0.013)and Butyricimonas(β=0.001,OR=1.001,P=0.014)increased the risk of rheumatoid arthritis,while Anaerostipes(β=-0.225,OR=0.798,P=0.025),Lachnospiraceae-UCG010(β=-0.177,OR=0.838,P=0.026)and Oxalobacter(β=-0.171,OR=0.843,P=0.001)reduced the risk of rheumatoid arthritis.Sensitivity analyses showed no significant heterogeneity or horizontal pleiotropy(all P＞0.05),and leave-one-out testing confirmed the robustness of the results,while the addition of the remaining four methods other than the inverse variance weighting method further validated the reliability and stability of the results.(2)Reverse Mendelian randomization analysis did not find a causal association between rheumatoid arthritis and the five kinds of enteric bacteria identified by Mendelian randomization analysis.These findings indicate that Ruminococcus gauvreauii group and Butyricimonas may be the risk factors of rheumatoid arthritis,while Anaerostipes,Lachnospiraceae-UCG010 and Oxalobacter may be the protective factors of rheumatoid arthritis.Gut microbiota may play an important role in the pathogenesis of rheumatoid arthritis,and provide new biomarkers for the prevention and treatment of rheumatoid arthritis.In addition,for the field of biomedical research in China,we can learn from international experience and gradually establish and improve a multi-center large-scale genetic database,so as to deeply explore the relationship between gut microbiota and disease risk,and promote the development of precision medicine and personalized treatment in China.

Objective To propose a liver ultraound image classification model based on bimodal fusion and deep residual network to enhance the diagnosis accuracy of space-occupying lesions(SOLs)of liver.Methods Firstly,a liver ultrasound dataset containing 164 lesions from 100 patients was constructed,including the ultrasound and ultrasonography videos of the patients.Secondly,the parallel residual block was introduced to improve the ResNet-18 network,and the simple attention module and coordinate attention mechanism were used to extract the image features of ultrasound and echography videos,respectively.Finally,a bimodal fusion network was developed with the image features of ultrasound and sonography videos,which was combined with the improved ResNet-18 network to form an ultrasound image classification model.The ultrasound image classification model proposed underwent performance verification by ablation experiment,application evaluation,diagnosis efficacy evaluation,significance evaluation for assisting surgical operation and comparison with the existing classification models in terms of image classification ability.Results The ablation experiment results showed that the proposed model performed the best in classification speed and accuracy when compared with the existing classification models,with a floating-point operation speed of 5.328×109/s,an average accuracy of 0.941 and a calculation speed of 245.266 frames/s.The application evaluation results indicated when compared with the existing classification models the proposed model had the best convergence performance of the loss function curve and the lowest misdiagnosis rate of 7.03%.The diagnosis efficacy evaluation results proved the proposed model gained advantages over other models in diagnostic efficacy,with a sensitivity of 89.38%,a specificity of 94.12%,an accuracy of 90.85%,a positive predictive value of 97.12%and a negative predictive value of 80.00%.The significance evaluation for assisting surgical operation found when compared with the existing classification models the proposed model had the shortest end-to-end delay of 723 ms;laparoscopic hepatectomy assisted with the proposed model had the blood loss reduced by 109.832 mL when compared with the traditional laparoscopic procedure,with the difference being statistically significant(P<0.05).Conclusion The proposed model enhances the diagnosis efficiency and accuracy of ultrasond SOLs of liver,providing support for clinical diagnosis and surgical assistance.[Chinese Medical Equipment Journal,2025,46(10):9-16]

Three failures of YLY-020Y acidic oxidation potential water generator were introduced,and the causes and specific troubleshooting measures were explored.References were provided for engineers to treat similar failures.[Chinese Medical Equipment Journal,2025,46(10):118-120]

Objective: To evaluate the efficacy and safety of plasma exchange (PE) in thymoma-associated myasthenia gravis (MG), thereby to provide theoretical support for its application in the treatment of thymoma-associated MG. Methods: A total of 133 patients with thymoma-associated MG admitted from January 2018 to September 2024 were retrospectively analyzed. Patients were matched using propensity score to reduce selection bias, yielding 22 matched pairs for both PE group (n=22) and non-PE group (n=22). Patient characteristics including gender, age of disease onset, course of disease, history of thymoma resection, clinical absolute scores [clinical absolute scores (CAS) and clinical relative scores (CRS)], and synchronized immunotherapy regimen of the two groups were analyzed. The CAS scores before and after treatment were compared between the two groups, and the CRS was used to assess the treatment efficiency. Safety of the two treatment regimens were also compared. Continuous variables were compared using the t-test or ANOVA, while categorical data were compared by the chi-square test. Results: A total of 133 patients were included and divided into two groups according to whether they underwent plasma exchange treatment: the PE group (n=22) and the non-PE group (n=111). To exclude bias caused by large difference in the number of cases between the two groups, we performed propensity score matching. After matching, the number of cases in both groups was 22. There was no significant difference in baseline clinical characteristics between the two groups (P>0.05), including gender, age of onset, duration of disease course, history of thymectomy and baseline CAS score before treatment. Compared to the non-PE group, patients in the PE group showed more significant improvement in CAS score (5.09±1.95 vs 3.59±1.50, P<0.05) and a higher CRS score (75.00% vs 50.00%, P<0.001). Compared to the non-PE group, PE group had significantly longer ICU stay, longer hospital stay and higher hospitalization cost (P<0.05). There was no statistically significant difference in adverse events between the two groups during treatment (P>0.05). During long-term follow-up, both the PE and non-PE groups showed relatively low 1-, 3-, and 5-year recurrence rate, with no significant difference between the two groups (P>0.05). Conclusion: This study indicates that plasma exchange has clear value in the treatment of patients with thymoma-associated myasthenia gravis. It can not only significantly improve patients' muscle strength to alleviate motor dysfunction and enhance quality of life, but also does not significantly increase the incidence of adverse reactions. Therefore, it can be regarded as one of the preferred treatment options that achieve a "balance between efficacy and safety" for such patients, and provides an important basis for optimizing treatment strategies, improving prognosis, and promoting the application of subsequent treatment regimens.

OBJECTIVE: Exposure to polycyclic aromatic hydrocarbons (PAHs) or metal(loid)s individually has been associated with neural tube defects (NTDs). However, the impacts of PAH and metal(loid) co-exposure and potential interaction effects on NTD risk remain unclear. We conducted a case-control study in China among population with a high prevalence of NTDs to investigate the combined effects of PAH and metal(loid) exposures on the risk of NTD. METHODS: Cases included 80 women who gave birth to offspring with NTDs, whereas controls were 50 women who delivered infants with no congenital malformations. We analyzed the levels of placental PAHs using gas chromatography and mass spectrometry, PAH-DNA adducts with ³²P-post-labeling method, and metal(loid)s with an inductively coupled plasma mass spectrometer. Unconditional logistic regression was employed to estimate the associations between individual exposures and NTDs. Least absolute shrinkage and selection operator (LASSO) penalized regression models were used to select a subset of exposures, while additive interaction models were used to identify interaction effects. RESULTS: In the single-exposure models, we found that eight PAHs, PAH-DNA adducts, and 28 metal(loid)s were associated with NTDs. Pyrene, selenium, molybdenum, cadmium, uranium, and rubidium were selected through LASSO regression and were statistically associated with NTDs in the multiple-exposure models. Women with high levels of pyrene and molybdenum or pyrene and selenium exhibited significantly increased risk of having offspring with NTDs, indicating that these combinations may have synergistic effects on the risk of NTDs. CONCLUSION Our findings suggest that individual PAHs and metal(loid)s, as well as their interactions, may be associated with the risk of NTDs, which warrants further investigation.
Humans ; Neural Tube Defects/chemically induced* ; Polycyclic Aromatic Hydrocarbons/adverse effects* ; Female ; Case-Control Studies ; China/epidemiology* ; Adult ; Pregnancy ; Environmental Pollutants ; Maternal Exposure/adverse effects* ; Metals/toxicity* ; Young Adult ; Risk Factors

Objective To propose a liver ultraound image classification model based on bimodal fusion and deep residual network to enhance the diagnosis accuracy of space-occupying lesions(SOLs)of liver.Methods Firstly,a liver ultrasound dataset containing 164 lesions from 100 patients was constructed,including the ultrasound and ultrasonography videos of the patients.Secondly,the parallel residual block was introduced to improve the ResNet-18 network,and the simple attention module and coordinate attention mechanism were used to extract the image features of ultrasound and echography videos,respectively.Finally,a bimodal fusion network was developed with the image features of ultrasound and sonography videos,which was combined with the improved ResNet-18 network to form an ultrasound image classification model.The ultrasound image classification model proposed underwent performance verification by ablation experiment,application evaluation,diagnosis efficacy evaluation,significance evaluation for assisting surgical operation and comparison with the existing classification models in terms of image classification ability.Results The ablation experiment results showed that the proposed model performed the best in classification speed and accuracy when compared with the existing classification models,with a floating-point operation speed of 5.328×109/s,an average accuracy of 0.941 and a calculation speed of 245.266 frames/s.The application evaluation results indicated when compared with the existing classification models the proposed model had the best convergence performance of the loss function curve and the lowest misdiagnosis rate of 7.03%.The diagnosis efficacy evaluation results proved the proposed model gained advantages over other models in diagnostic efficacy,with a sensitivity of 89.38%,a specificity of 94.12%,an accuracy of 90.85%,a positive predictive value of 97.12%and a negative predictive value of 80.00%.The significance evaluation for assisting surgical operation found when compared with the existing classification models the proposed model had the shortest end-to-end delay of 723 ms;laparoscopic hepatectomy assisted with the proposed model had the blood loss reduced by 109.832 mL when compared with the traditional laparoscopic procedure,with the difference being statistically significant(P<0.05).Conclusion The proposed model enhances the diagnosis efficiency and accuracy of ultrasond SOLs of liver,providing support for clinical diagnosis and surgical assistance.[Chinese Medical Equipment Journal,2025,46(10):9-16]

Three failures of YLY-020Y acidic oxidation potential water generator were introduced,and the causes and specific troubleshooting measures were explored.References were provided for engineers to treat similar failures.[Chinese Medical Equipment Journal,2025,46(10):118-120]