Objective:To establish a mouse model of liver cancer resistant to PD-1 monoclonal antibody and analyze the changes in its metabolomics to explore the potential mechanism of drug resistance.Methods:BALB/c mice were randomly divided into control and treatment groups after being loaded with tumor,and a normal group was additionally set up.The normal and control groups were injected with saline,and the treatment group was injected with PD-1 monoclonal antibody,after which the mice in the treatment group were screened for drug resistant and response groups.Observed the drug-resistant situation,body mass,tumor growth and survival rate of mice in each group,calculate the spleen index.The pathological features of tumor tissues were observed by HE staining method.Serum metabolites were detected by non-targeted metabolomics.Finally,a bivariate Pearson correlation analysis was conducted between the differential serum metabolites and tumor size.Results:The tumor-bearing mouse model with PD-1 monoclonal antibody resistance was successfully established,and the drug resistance rate of the mice was 50％.Compared with the normal and response groups,mice in the resistant group showed an increase in body weight,a significant increase in tumor volume,a decrease in survival rate,and a significant increase in splenic index.There was less lymphocyte infiltration in the tumor tissue.Metabolomics analysis showed that the serum levels of glutamic acid and aspartic acid increased and malic acid decreased in the resistant mice compared with the response group,and these changes were closely related to the arginine biosynthesis pathway.Conclusions:The tumor-bearing mouse model with PD-1 monoclonal antibody resistance was successfully established.The changes in its peripheral serum metabolomics mainly involve arginine metabolism and the related changes of aspartate,malate and glutamate.

Objective:To explore the changes in the whole transcriptome gene expression profile affected by EPB41L4A-AS,and to reveal its potential mechanisms that influence the progression of AD.Methods:U251 cells with stable low expression of EPB41L4A-AS1 were constructed using shRNA technology.Transcriptome sequencing was performed to screen for transcripts regulated by EPB41L4A-AS1.KEGG pathway and GO analysis were used to explore the related signaling pathways and biological processes regulated by EPB41L4A-AS1.Immunofluorescence assay was used to investigate the effects of EPB41L4A-AS1 on the activity of glial cells with antibodies against GFAP.Results:Knocking down the expression of EPB41L4A-AS1 in U251 cells significantly influenced the levels of multiple transcripts,with 626 upregulated and 949 downregulated.Further analysis revealed that the downregulated transcripts are related to AD,activation and proliferation of glial cells,and formation of amyloid fibers,and close to multiple signaling pathways that are involved in the glial cells-mediated Aβ clearance.Cellular experiments have shown that EPB41L4A-AS1 regulated the synapses length and activity of glial cells.Conclusions:EPB41L4A-AS1 may influence the glial cells-mediated Aβ clearance through multiple signaling pathways.

Objective To evaluate the diagnostic performance of the minimum-cost-path-based CT angiography-derived fractional flow reserve(MCP-FFR)and the deep learning-driven CT angiography-derived fractional flow reserve(DeepCL-FFR),and to particularly explore the potential value of the DeepCL algorithm in improving diagnostic accuracy within the"gray zone."Methods A retrospective analysis was conducted on 151 coronary vessels from 109 patients with coronary artery disease,who were hospitalized at the General Hospital of the People's Liberation Army between January 2020 and June 2021.Pearson correlation and Bland-Altman plots were employed to assess the correlation and agreement of the two CT-FFR methods with invasive FFR.A CT-FFR range of 0.70-0.80 was defined as the diagnostic"gray zone."The accuracy,sensitivity,specificity,positive predictive value,and negative predictive value for detecting hemodynamic abnormalities were calculated and analyzed.The DeLong test was used to compare the areas under the receiver operating characteristic curves(AUC)between the two CT-FFR calculation methods.Results Both CT-FFR methods exhibited a positive correlation with invasive FFR(MCP-FFR:r=0.75,P＜0.001;DeepCL-FFR:r=0.86,P＜0.001)and showed good agreement(MCP-FFR:mean difference=0.010,P=0.351;DeepCL-FFR:mean difference=-0.003,P=0.772).Both DeepCL-FFR(AUC 0.97,95％CI 0.94-0.99)and MCP-FFR(AUC 0.92,95％CI 0.88-0.97)demonstrated favorable diagnostic performance for detecting hemodynamic abnormalities(P=0.122).In the"gray zone"for hemodynamic abnormality,the diagnostic accuracy of MCP-FFR was 68.8％,whereas DeepCL-FFR increased it to 89.7％.DeepCL-FFR also exhibited superior diagnostic performance(AUC 0.89,95％CI 0.73-0.99)within the"gray zone,"which was significantly higher than that of MCP-FFR(AUC 0.71,95％CI 0.54-0.87)(P＜0.001).Conclusions The deep learning-driven coronary centerline extraction algorithm,DeepCL,demonstrates superior diagnostic performance in CT-FFR for detecting hemodynamic abnormalities,particularly by significantly improving diagnostic accuracy in the"gray zone."

Objective This study aims to compare the clinical efficacy and complications associated with microwave ablation(MWA)and sublobectomyfor treating stage ⅠA non-small cell lung cancer(NSCLC).Methods Data from stage ⅠA1-ⅠA3 NSCLC patients treated at Yunnan Cancer Hospital between January 2021 and December 2022 were retrospectively collected.A total of 82 patients who underwent MWA and 82 patients who received sublobectomy were selected through propensity score matching.Periprocedural conditions,short-term efficacy,and complications were compared between the two groups.Progression-free survival(PFS)and Disease-free survival(DFS)were monitored and evaluated.The Kaplan-Meier method was employed to construct survival curves,and logistic regression was utilized to analyze the factors influencing complications.Results The MWA group exhibited shorter procedure times,less intraprocedural blood loss,less postprocedure pain,shorter hospitalization durations,and lower hospitalization costs compared to the sublobectomy group(P<0.001).All patients successfully underwent the procedures,with a complete ablation rate of 97.6%and a local control rate of 87.8%in the MWA group.The median follow-up duration was 26.5 months.Survival curve analysis indicated no statistically significant differences in PFS and DFS between the two groups.The primary complications observed were pneumothorax(24.4%,20/82)and moderate to severe pain(11.0%,9/82)in the MWA group,while the sublobectomy group experienced moderate to severe pain(41.5%,34/82)and pulmonary infection(12.2%,10/82).Single-factor analysis demonstrated six variables influenced the occurrence of MWA pneumothorax.Multi-factor logistic regression revealed that the shortest distance from the tumor to the pleura(P=0.021,OR=15.341,95%CI:1.699～24.367)and the number of punctures through the pleura(P=0.024,OR=0.068,95%CI:0.001～0.612)were identified as independent risk factors for pneumothorax.Conclusion MWA demonstrates good efficacy for treating stage ⅠA NSCLC due to minimal trauma,low cost,rapid recovery,few and mild complications.Additionally,MWA and sublobectomy exhibit comparable PFS and DFS,making MWA a safe and effective treatment method.Therefore,MWA is worthy of promotion in clini-cal practice.

Aim To study whether intravenous injec-tion of miR-129-3p mimetic(agomir)can resist bone loss caused by hind limb disuse,and to provide new i-deas for preventing bone loss in microgravity environ-ment.Methods Forty-eight C57BL/6J male mice were randomly divided into the control group(CON),tail suspension model group(TS),tail suspension+miR-129-3p agomir administration group(miRNA)and tail suspension+miR-129-3p negative sequence agomir control group(NC).The miRNA group was given 4 mg·kg-1 miR-129-3p agomir by intravenous injection into the medial canthus twice a week.The NC agomir group were consistent with those in the miR-129-3p agomir group,and the CON and TS groups were given only equal volumes of normal saline.After four weeks,all mice were sacrificed and samples were collected.Micro-CT scan of femur,three-point femur bending test,serum bone metabolism index detection,oxidative stress index detection and osteogenesis-related protein expression analysis in bone tissue were per-formed.Results After four weeks,the number of tra-becular bone in the TS group was significantly re-duced,and Tb.BMD,Tb.Th,Tb.N,Tb.BS/TV and Tb.BV/TV were significantly lower than those in the CON group(P＜0.01).While Tb.Sp TS group was significantly higher than the CON group(P＜0.05),the maximum load and flexural strength of the femur significantly decreased(P＜0.01),the content of ser-um bone formation index PINP was significantly lower than that of the CON group(P＜0.01),and the con-tent of bone resorption index CTX-I was significantly higher than that of the CON group(P＜0.01),the content of serum oxidative damage indexes 8-iso-PGF2α and 8-OHdG significantly increased(P＜0.01),and the expression of osteogenesis-related pro-teins in bone tissue markedly decreased(P＜0.01).However,the increase or decrease of all indexes in miRNA group was significantly lower than that in TS group.Conclusions miR-129-3p mimetic can signifi-cantly reduce bone loss caused by hind limb disuse.This experiment provides a new idea and method for preventing bone loss in microgravity environment.

Objective:To establish a mouse model of liver cancer resistant to PD-1 monoclonal antibody and analyze the changes in its metabolomics to explore the potential mechanism of drug resistance.Methods:BALB/c mice were randomly divided into control and treatment groups after being loaded with tumor,and a normal group was additionally set up.The normal and control groups were injected with saline,and the treatment group was injected with PD-1 monoclonal antibody,after which the mice in the treatment group were screened for drug resistant and response groups.Observed the drug-resistant situation,body mass,tumor growth and survival rate of mice in each group,calculate the spleen index.The pathological features of tumor tissues were observed by HE staining method.Serum metabolites were detected by non-targeted metabolomics.Finally,a bivariate Pearson correlation analysis was conducted between the differential serum metabolites and tumor size.Results:The tumor-bearing mouse model with PD-1 monoclonal antibody resistance was successfully established,and the drug resistance rate of the mice was 50％.Compared with the normal and response groups,mice in the resistant group showed an increase in body weight,a significant increase in tumor volume,a decrease in survival rate,and a significant increase in splenic index.There was less lymphocyte infiltration in the tumor tissue.Metabolomics analysis showed that the serum levels of glutamic acid and aspartic acid increased and malic acid decreased in the resistant mice compared with the response group,and these changes were closely related to the arginine biosynthesis pathway.Conclusions:The tumor-bearing mouse model with PD-1 monoclonal antibody resistance was successfully established.The changes in its peripheral serum metabolomics mainly involve arginine metabolism and the related changes of aspartate,malate and glutamate.

Objective:To explore the changes in the whole transcriptome gene expression profile affected by EPB41L4A-AS,and to reveal its potential mechanisms that influence the progression of AD.Methods:U251 cells with stable low expression of EPB41L4A-AS1 were constructed using shRNA technology.Transcriptome sequencing was performed to screen for transcripts regulated by EPB41L4A-AS1.KEGG pathway and GO analysis were used to explore the related signaling pathways and biological processes regulated by EPB41L4A-AS1.Immunofluorescence assay was used to investigate the effects of EPB41L4A-AS1 on the activity of glial cells with antibodies against GFAP.Results:Knocking down the expression of EPB41L4A-AS1 in U251 cells significantly influenced the levels of multiple transcripts,with 626 upregulated and 949 downregulated.Further analysis revealed that the downregulated transcripts are related to AD,activation and proliferation of glial cells,and formation of amyloid fibers,and close to multiple signaling pathways that are involved in the glial cells-mediated Aβ clearance.Cellular experiments have shown that EPB41L4A-AS1 regulated the synapses length and activity of glial cells.Conclusions:EPB41L4A-AS1 may influence the glial cells-mediated Aβ clearance through multiple signaling pathways.

Objective To evaluate the diagnostic performance of the minimum-cost-path-based CT angiography-derived fractional flow reserve(MCP-FFR)and the deep learning-driven CT angiography-derived fractional flow reserve(DeepCL-FFR),and to particularly explore the potential value of the DeepCL algorithm in improving diagnostic accuracy within the"gray zone."Methods A retrospective analysis was conducted on 151 coronary vessels from 109 patients with coronary artery disease,who were hospitalized at the General Hospital of the People's Liberation Army between January 2020 and June 2021.Pearson correlation and Bland-Altman plots were employed to assess the correlation and agreement of the two CT-FFR methods with invasive FFR.A CT-FFR range of 0.70-0.80 was defined as the diagnostic"gray zone."The accuracy,sensitivity,specificity,positive predictive value,and negative predictive value for detecting hemodynamic abnormalities were calculated and analyzed.The DeLong test was used to compare the areas under the receiver operating characteristic curves(AUC)between the two CT-FFR calculation methods.Results Both CT-FFR methods exhibited a positive correlation with invasive FFR(MCP-FFR:r=0.75,P＜0.001;DeepCL-FFR:r=0.86,P＜0.001)and showed good agreement(MCP-FFR:mean difference=0.010,P=0.351;DeepCL-FFR:mean difference=-0.003,P=0.772).Both DeepCL-FFR(AUC 0.97,95％CI 0.94-0.99)and MCP-FFR(AUC 0.92,95％CI 0.88-0.97)demonstrated favorable diagnostic performance for detecting hemodynamic abnormalities(P=0.122).In the"gray zone"for hemodynamic abnormality,the diagnostic accuracy of MCP-FFR was 68.8％,whereas DeepCL-FFR increased it to 89.7％.DeepCL-FFR also exhibited superior diagnostic performance(AUC 0.89,95％CI 0.73-0.99)within the"gray zone,"which was significantly higher than that of MCP-FFR(AUC 0.71,95％CI 0.54-0.87)(P＜0.001).Conclusions The deep learning-driven coronary centerline extraction algorithm,DeepCL,demonstrates superior diagnostic performance in CT-FFR for detecting hemodynamic abnormalities,particularly by significantly improving diagnostic accuracy in the"gray zone."

Objective To explore the feasibility and corresponding implementation methods of constructing a sample resource bank based on individual-level data of completed clinical trials and using it to construct external controls for drug/device clinical trials.Methods Taking the pre-marketing clinical trial of transcatheter active valve replacement(TAVR)for the treatment of aortic valve stenosis as an example,the individual-level databases of multiple trials were standardized to form a sample bank.The original data of any trial in the sample bank were selected as the experimental group,and the remaining samples were selected as the control group.The potential confounding was handled by using the propensity score matching and stratification methods to clarify the process of constructing external controls based on the sample bank of individual-level data of clinical trials.Results This study included individual-level data of single-group trials of 4 TAVR devices,with a total of 569 subjects(59.2%male).The number of subjects in Trials 1 to 4 was 120,120,163,and 166,respectively.Propensity score matching enabled the matching of 113,117,125,and 147 subjects with comparable or similar characteristics from individual-level data from other trials,respectively,demonstrating a high matching success rate.The PS score distribution plot after stratification showed that the proportions of subjects in the experimental and control groups in strata 1 to 5 in scheme 1 were 4/103,11/103,22/92,32/87,and 51/64,respectively.For all constructed external controlled trials,a certain number of control samples with similar baseline characteristics to the experimental groups were distributed within each propensity score stratum.The results of the simulation test also reflected the potential differences between different devices in the 12-month all-cause mortality rate.Conclusions The sample bank constructed with individual-level data from clinical trials,as a high-quality data source,can serve as a source of external control for single-arm trials in the same field,and as a useful supplement to the external control scenario of real-world evidence to support drug and device development.At the same time,targeted research on research methods and bias control measures in related fields is also needed.

Objective To design an intelligent airborne soldier physical training system based on human body composition analysis to solve the problems in diversity of training mode,targeted training plan and high incidence of military training-related injuries.Methods The intelligent airborne military physical training system was designed with B/S architecture and developed with Python language,which was composed of four functional modules for airborne soldier information acquisition,trainee physical fitness state assessment,physical fitness training program recommendation and airborne soldier physical fitness training program evaluation.The airborne soldier information acquisition module collected and analyzed the trainee physiological parameter information with a human body composition analyzer,clarified the parameter characteristics related to physical training with considerations on military physical training requirements and constructed a trainee physical fitness assessment parameter model;the trainee physical fitness state assessment module established an evaluation model based on machine learning to realize stage-by-stage physical fitness evaluation for airborne soldiers;the physical fitness training program recommendation module was constructed based on the physical training feature similarity algorithm and graph embedding theory to provide decision making assistance for program development of airborne military physical training;the airborne soldier physical fitness training program evaluation module compared the physical fitness and evaluation results before and after training by means of list and chart,and updated the training program based on the evaluation results by calling the physical training program recommendation module.Results The intelligent airborne soldier physical training system contributed to forming an individualized physical fitness training recommendation mechanism after trainee body evaluation,modifying training program based on comparison and feedback for stage-by-stage training evaluation,so as to decrease the incidence of military training-related injuries while increasing the training efficiency.Conclusion The system developed improves airborne soldier physical training in rationality and reliability,and provides references for intelligent military training of the PLA.[Chinese Medical Equipment Journal,2025,46(2):16-23]