Objective: To propose an improved method for constructing the internal quality control (IQC) framework for ELISA assays and validate its efficacy by statistically analyzing IQC data from nine blood center laboratories. Methods: 1) IQC data was collected from nine blood centers and analyzed using a domestic HBsAg ELISA detection kit as an example. 2) Differences between IQC values across batches within Blood Center 1 were assessed. 3) Statistical analyses were performed on batch usage, number of batches used, days of use, number of QC points, batch-specific means, and coefficients of variation (CV) across all nine centers. 4) Using the improved construction method for IQC framework, provisional and permanent frames were established for batches within Blood Center 1 and Blood Center 9, followed by outlier determination. Results: 1) Statistically significant differences were observed in IQC data between batches within Blood Center 1 (P<0.01). It is recommended that both the control material/reagents and the control chart framework be replaced simultaneously. 2) There were substantial differences among 9 blood centers regarding the control material/reagent lot numbers used, the number of QC runs per batch, and the QC values for identical lots. Therefore, individual laboratories should establish their own IQC chart frameworks. 3) The improved IQC framework construction method for ELISA assays is as follows: provisional frames are established via frame-shifting, using the pre-experimental mean and cumulative coefficient of variation (CV) from the preceding batch. For batches used >20 days with >20 QC points, permanent frames are constructed by aggregating in-control data accumulated over ≥20 days with ≥20 points to calculate cumulative mean and standard deviation. The provisional and permanent frames constructed by this method identified all 26 extreme outliers across Blood Centers 1 and 9 as out-of-control. Among the 218 general outliers, 10 were classified as normal by the provisional frames, while the remainder were designated as warnings or out-of-control. This method effectively monitors assay stability. Conclusion: Based on the statistical analysis of IQC practices across blood centers of varying scales, combined with the inherent characteristics of ELISA assays and the batch-to-batch instability of reagents/QC materials, it is recommended to reconstruct QC charts upon lot changes. The proposed method—utilizing frame-shifting for provisional frames and establishing permanent frames based on cumulative data—is applicable to blood center laboratories of differing sizes and effectively monitors the stability of the ELISA assay process.

ObjectiveTo investigate whether anti-programmed death-1 （PD-1） monoclonal antibody can enhance the efficacy and safety of argon-helium cryoablation combined with targeted therapy in patients with unresectable hepatocellular carcinoma （uHCC） aged 60 years or older. MethodsA retrospective analysis was performed for the clinical data of 124 patients with advanced uHCC aged 60 years or older who were treated at The Fifth Medical Center of Chinese PLA General Hospital from January 2013 to September 2024. After propensity score matching， 57 patients received cryoablation combined with targeted therapy （double combination group）， while 57 received cryoablation combined with targeted therapy and anti-PD-1 monoclonal antibody （triple combination group）. The indicators for efficacy assessment included objective response rate （ORR）， disease control rate （DCR）， progression-free survival （PFS）， overall survival （OS）， and the incidence rate of adverse events. The Mann-Whitney U test was used for comparison of continuous data between two groups， and the chi-square test or the Fisher’s exact test was used for comparison of categorical data between two groups. The Kaplan-Meier method was used to plot survival curves， and the Log-rank test was used for comparison between groups. A Cox proportional-hazards regression model analysis was used to investigate the influencing factors for survival prognosis. ResultsThe triple combination group had a significantly higher ORR than the double combination group （59.6% vs 29.8%， χ²=9.083， P=0.003）， while there was no significant difference in DCR between the two groups （87.7% vs 77.2%， χ²=1.516， P=0.218）， and compared with the double combination group， the triple combination group had significantly longer median PFS （9.1 months vs 4.8 months， χ²=7.813， P=0.005） and median OS （26.1 months vs 13.6 months， χ²=14.199， P<0.001）. The multivariate Cox proportional-hazards regression model analysis showed that triple combination treatment was an independent influencing factor for PFS （hazard ratio ［HR］=0.52， 95% confidence interval ［CI］： 0.35 — 0.78， P=0.001） and OS （HR=0.32， 95%CI： 0.20 — 0.51， P<0.001）. There was no significant difference in the incidence rate of adverse events between the two groups （P>0.05）. ConclusionTriple combination treatment with argon-helium cryoablation， targeted therapy， and anti-PD-1 monoclonal antibody can significantly improve survival benefits in uHCC patients aged 60 years or older， with a controllable safety profile.

OBJECTIVE To analyze the distribution and drug resistance of pathogenic bacteria in hospital-associat-ed infections for patients after renal transplantation,and to provide a reference for the rational selection of antibac-terial drugs for anti-infective treatment in such patients.METHODS Clinical data were collected from 89 hospital-ized patients who underwent renal transplantation and developed hospital-associated infection at Beidaihe Rehabili-tation and Recuperation Center(formerly known as 281 Hospital)from 2017 to 2021.The pathogenic bacteria de-tected in different types of hospital-associated infections and the drug resistance of the main pathogenic bacteria were analyzed.RESULTS A total of 89 pathogenic bacterial strains were isolated from the 89 patients with hospi-tal-associated infection,including 74 gram-negative bacterial strains(83.15％)and 15 gram-positive bacterial strains(16.85％).The predominant pathogenic bacterial strains were Klebsiella pneumoniae,Escherichia coli and Pseudomonas aeruginosa.Respiratory tract infection was the most common.E.coli showed severe drug re-sistance,with high drug resistance rates to various antibacterial drugs(complete drug resistance to piperacillin and ampicillin).K.pneumoniae was generally drug resistant to ampicillin.Enterobacter cloacae showed high sensitivi-ty to carbapenems,amikacin and enzyme inhibitor combinations.P.aeruginosa had low drug resistance rates to imipenem and meropenem.Staphylococcus aureus was completely drug resistant to antibacterial drugs such as penicillin,erythromycin and gentamicin,and no drug-resistant strains to vancomycin and linezolid were found.CONCLUSIONS The gram-negative bacteria are dominant among the bacteria isolated from the renal trans-planted patients with postoperative hospital-associated infections,with a high detection rate of E.coli and a severe drug resistance situation.Therefore,it is necessary to strengthen the monitoring of drug resistance in renal trans-plant recipients and make rational choices of antibacterial drugs.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Objective:To compare the clinical efficacy of O-arm navigation-assisted percutaneous vertebroplasty (PVP) versus C-arm-guided PVP in the treatment of postoperative recurrent vertebral fractures following Kümmell′s disease.Methods:A retrospective cohort study was conducted to analyze the clinical data of 48 patients with postoperative recurrent vertebral fractures following Kümmell′s disease who were admitted to Zhengzhou Orthopedic Hospital from January 2021 to September 2024, including 16 males and 32 females, aged 51-85 years [(69.8±6.6)years]. Among them, 21 patients had stage I Kümmell′s disease and 27 stage II. Fractured vertebrae involved T 8-T 10 in 4 patients, T 11-L 2 in 29, and L 3-L 5 in 15. Twenty-five patients underwent O-arm navigation-assisted PVP (O-arm-assisted group) and 23 underwent C-arm-guided PVP (C-arm-guided group). The two groups were compared in terms of the operative time, intraoperative blood loss, bone cement volume, and bone cement filling saturation rate in the injured vertebral body. The visual analogue scale (VAS) scores and Oswestry disability index (ODI) values were also compared before operation, at 1 day, 1 month, 6 months after operation, and at the last follow-up. The excellent-good rate based on the MacNab criteria at the last follow-up and incidence of postoperative complications were detected. Results:All the patients were followed up for 6-24 months [(13.3±3.5)months]. There were no significant differences in the operative time, operative blood loss or bone cement volume between the two groups ( P>0.05). The O-arm-assisted group demonstrated a bone cement filling saturation rate of 96% (24/25) in the fractured vertebrae, significantly higher than 65% (15/23) in the C-arm-guided group ( P<0.05). The VAS scores before operation, at 1 day, and 1 month after operation were (8.4±1.0)points, (1.9±0.7)points, and (1.8±0.6)points, respectively in the O-arm-assisted group, while they were (8.3±0.8)points, (2.0±0.6)points, and (1.9±0.5)points, respectively in the C-arm-guided group ( P>0.05). The ODI values before operation, at 1 day, and 1 month after operation were 76.6±8.2, 20.4±4.5, and 19.8±4.1, respectively in the O-arm-assisted group, and 74.9±9.1, 21.3±3.6, and 20.9±3.2, respectively in the O-arm-assisted group ( P>0.05). At 6 months after operation and at the last follow-up, the VAS scores were (1.4±0.5)points and (1.5±0.5)points in the O-arm-assisted group, with significant improvement compared to (1.8±0.4)points and (1.9±0.3)points in the C-arm-guided group ( P<0.01); the ODI values were 17.8±3.2 and 18.2±3.5 in the O-arm-assisted group, with significant improvement compared to 19.9±3.1 and 21.3±4.0 in the C-arm-guided group ( P<0.05). Both groups demonstrated significant improvements in VAS scores and ODI values at 1 day, 1 month, 6 months after operation, and at the last follow-up, compared to those preoperatively ( P<0.05), while no statistically significant differences were found in VAS scores or ODI values at any postoperative timepoints ( P>0.05). According to the MacNab criteria, the O-arm-assisted group had a 100% (25/25) excellent-good rate, compared to 74% (17/23) in the C-arm-guided group ( P<0.05). The complication rate was 4% (1/25) in the O-arm-assisted group, significantly lower than 35% (8/23) in the C-arm-guided group ( P<0.05). Conclusion:O-arm navigation-assisted PVP for postoperative recurrent vertebral fractures following Kümmell′s disease offers advantages in precise cement delivery with sufficient dispersion, enhanced pain relief, functional recovery, improved quality of life, and reduced complication rates when compared to C-arm navigation-assisted PVP.

Objective To discuss the potential mechanisms by which programmed cell death(PCD)might contribute to the pathogenesis of diabetic kidney disease(DKD).Methods Retrieve the datasets GSE30529 and GSE30122 from the Gene Expression Omnibus database and analyze them to obtain differentially expressed genes(DEGs)associated with DKD.Utilize the Gene Set Enrichment Analysis website,the ferroptosis database,and the autophagy database,along with relevant literature,to identify genes associated with apoptosis,necroptosis,pyroptosis,autophagy,and ferroptosis.Cross-reference these genes with the DKD DEGs to identify PCD-related genes that are differentially expressed in DKD.Perform Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analyses to explore the biological functions and potential pathways of the core genes.Conduct a protein-protein interaction network analysis to examine the interaction relationships of the target genes,and use the CytoHubba plugin in Cytoscape to screen for Hub genes.Results In the GSE30529 dataset,a total of 460 DEGs were identified,while the GSE30122 dataset yielded 992 DEGs.After merging and removing duplicates,932 DEGs were obtained.By intersecting these DEGs with PCD-related genes,61 apoptosis-related genes,7 necroptosis-related genes,39 pyroptosis-related genes,18 autophagy-related genes,and 16 ferroptosis-related genes associated with DKD were identified.The KEGG analysis results indicated that the DEGs related to apoptosis,necroptosis,pyroptosis,and autophagy in PCD were primarily enriched in pathways associated with diabetic complications,including the AGE-RAGE,IL-17,NF-κB,and TNF signaling pathways.In contrast,DEGs related to ferroptosis were mainly enriched in the fatty acid degradation pathway.GO enrichment analysis revealed that the biological processes of the differentially expressed PCD related genes in DKD were primarily involved in the regulation of signals such as NF-κB-inducing kinase/NF-κB,IL-1,and IL-17.Conclusions Differentially expressed PCD-related genes in DKD are mainly enriched in related signal pathways such as AGE-RAGE,IL-17,NF-κB and TNF,suggesting a critical role of PCD in the pathogenesis of DKD.

OBJECTIVE To analyze the distribution and drug resistance of pathogenic bacteria in hospital-associat-ed infections for patients after renal transplantation,and to provide a reference for the rational selection of antibac-terial drugs for anti-infective treatment in such patients.METHODS Clinical data were collected from 89 hospital-ized patients who underwent renal transplantation and developed hospital-associated infection at Beidaihe Rehabili-tation and Recuperation Center(formerly known as 281 Hospital)from 2017 to 2021.The pathogenic bacteria de-tected in different types of hospital-associated infections and the drug resistance of the main pathogenic bacteria were analyzed.RESULTS A total of 89 pathogenic bacterial strains were isolated from the 89 patients with hospi-tal-associated infection,including 74 gram-negative bacterial strains(83.15％)and 15 gram-positive bacterial strains(16.85％).The predominant pathogenic bacterial strains were Klebsiella pneumoniae,Escherichia coli and Pseudomonas aeruginosa.Respiratory tract infection was the most common.E.coli showed severe drug re-sistance,with high drug resistance rates to various antibacterial drugs(complete drug resistance to piperacillin and ampicillin).K.pneumoniae was generally drug resistant to ampicillin.Enterobacter cloacae showed high sensitivi-ty to carbapenems,amikacin and enzyme inhibitor combinations.P.aeruginosa had low drug resistance rates to imipenem and meropenem.Staphylococcus aureus was completely drug resistant to antibacterial drugs such as penicillin,erythromycin and gentamicin,and no drug-resistant strains to vancomycin and linezolid were found.CONCLUSIONS The gram-negative bacteria are dominant among the bacteria isolated from the renal trans-planted patients with postoperative hospital-associated infections,with a high detection rate of E.coli and a severe drug resistance situation.Therefore,it is necessary to strengthen the monitoring of drug resistance in renal trans-plant recipients and make rational choices of antibacterial drugs.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Objective To discuss the potential mechanisms by which programmed cell death(PCD)might contribute to the pathogenesis of diabetic kidney disease(DKD).Methods Retrieve the datasets GSE30529 and GSE30122 from the Gene Expression Omnibus database and analyze them to obtain differentially expressed genes(DEGs)associated with DKD.Utilize the Gene Set Enrichment Analysis website,the ferroptosis database,and the autophagy database,along with relevant literature,to identify genes associated with apoptosis,necroptosis,pyroptosis,autophagy,and ferroptosis.Cross-reference these genes with the DKD DEGs to identify PCD-related genes that are differentially expressed in DKD.Perform Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analyses to explore the biological functions and potential pathways of the core genes.Conduct a protein-protein interaction network analysis to examine the interaction relationships of the target genes,and use the CytoHubba plugin in Cytoscape to screen for Hub genes.Results In the GSE30529 dataset,a total of 460 DEGs were identified,while the GSE30122 dataset yielded 992 DEGs.After merging and removing duplicates,932 DEGs were obtained.By intersecting these DEGs with PCD-related genes,61 apoptosis-related genes,7 necroptosis-related genes,39 pyroptosis-related genes,18 autophagy-related genes,and 16 ferroptosis-related genes associated with DKD were identified.The KEGG analysis results indicated that the DEGs related to apoptosis,necroptosis,pyroptosis,and autophagy in PCD were primarily enriched in pathways associated with diabetic complications,including the AGE-RAGE,IL-17,NF-κB,and TNF signaling pathways.In contrast,DEGs related to ferroptosis were mainly enriched in the fatty acid degradation pathway.GO enrichment analysis revealed that the biological processes of the differentially expressed PCD related genes in DKD were primarily involved in the regulation of signals such as NF-κB-inducing kinase/NF-κB,IL-1,and IL-17.Conclusions Differentially expressed PCD-related genes in DKD are mainly enriched in related signal pathways such as AGE-RAGE,IL-17,NF-κB and TNF,suggesting a critical role of PCD in the pathogenesis of DKD.

Albendazole-glucan particles(ABZ-GPS)and abendazole(ABZ)were used to treat secondary alveolar echinococ-cosis in mice.The therapeutic effects of ABZ-GPS on alveolar echinococcosis in vivo were evaluated,and the feasibility of using glucan particles as anti-hydatid drug carriers was further verified.Mice with echinococcosis were randomly divided into an ABZ group,glucan nanoparticle(GP)group,ABZ-GPS group,and control group.After four courses of administration with a final concentration of 50 mg/mL,the therapeutic effects of ABZ-GPS were evaluated on the basis of imaging,histopathological changes,ultrastructure,and immunology.After ABZ-GPS and ABZ administration,clear liver lesion tissue necrosis and large numbers of infiltrating lymphocytes were observed.Significant differences in the average cyst wet weight(t=7.83,P＜0.05),were observed between the ABZ-GPS group and ABZ group.Imaging revealed that ABZ-GPs were targeted to liver tissue.Pa-thology and ultrastructure analyses demonstrated that the alveolar hydatid cells in the liver in the control group and GP group grew well,and the vesicles were large,filled with cystic fluid,and translucent or transparent;the cyst wall tension was high;no calcification was observed;the stratum corneum and germinal layer were clear;and more fertile capsules and different num-bers of protocephalospora were present in the liver.In the ABZ group,the capsular cavity collapsed,and showed partial necro-sis and lymphocyte infiltration.In the ABZ-GP group,the corneum and germinal layer of echinococcus vesicles were difficult to identify,and we observed bulbous necrosis,central calcification,fibrous tissue hyperplasia,inflammatory cell infiltration,coarser,shorter or absent microvilli of the germinal layer,nuclear shrinkage,dissolution or disappearance,clear expansion of cytoplasmic microtubules,and myelin-like or vacuole-like changes.Therefore,ABZ-GPs showed good targeting and killing ac-tivity in vivo in mice with secondary alveolar coccosis.