Objective To evaluate the application value of artificial intelligence (AI) in the quality control of mammographic images and explore its feasibility for improving image quality. Methods A retrospective analysis was conducted on 500 mammographic images from 125 female patients. These images were acquired in December 2024 at the Department of Radiology, Obstetrics and Gynecology Hospital of Tongji University by two junior technologists with qualification certificate for junior radiologic technologists and ≤ 2 months of independent operation. The reference standard was the evaluation by a panel of senior experts comprising one associate chief radiologist and two intermediate radiologic technologists with over 10 years of experience in mammography. The evaluation was based on nine criteria within an AI quality control system. The correlation and consistency (Kappa test) of the assessment outcomes were compared among the junior technologist group, the AI quality control group, and the panel group. Additionally, the differences in the proportions of high-, medium-, and low-quality images rated by the three groups were analyzed. After one month of AI assistance, 200 images from 50 additional patients acquired by the same two junior technologists in January 2025 were collected. The area under the receiver operating characteristic curve and 95% confidence interval (95%CI) were calculated for the assessment performance of the junior technologist group before and after AI assistance. Differences were compared using the DeLong test. Changes in the disqualification rates for the nine criteria were analyzed. Results In consistency analysis, the AI quality control group showed high consistency with the panel group across multiple key criteria, with Kappa values ranging from 0.41 to 1.00. In contrast, the consistency between the junior technologist group and the panel group was generally low, with Kappa values ranging from 0.13 to 0.49. In comparison of image quality classification, no significant differences were observed in image quality classification between the AI group and the panel group (P>0.05). However, the proportion of images rated as high quality by the junior technologist group was significantly higher, while the proportions rated as medium and low quality were significantly lower, compared to those rated by the panel group (P<0.05). After AI assistance, the area under the receiver operating characteristic curve for the assessment performance of junior technologist group increased significantly from 0.56 (95%CI: 0.51-0.61) to 0.91 (95%CI: 0.87-0.94) (P<0.001). The disqualification rates for skin folds, incomplete inclusion of the pectoralis major muscle, and nipple not in profile decreased significantly. Conclusion AI demonstrates assessment capability comparable to the panel group in mammographic quality control. AI effectively enhances the quality of images acquired by junior technologists through real-time, objective feedback.

Objective To evaluate the application value of artificial intelligence (AI) in the quality control of mammographic images and explore its feasibility for improving image quality. Methods A retrospective analysis was conducted on 500 mammographic images from 125 female patients. These images were acquired in December 2024 at the Department of Radiology, Obstetrics and Gynecology Hospital of Tongji University by two junior technologists with qualification certificate for junior radiologic technologists and ≤ 2 months of independent operation. The reference standard was the evaluation by a panel of senior experts comprising one associate chief radiologist and two intermediate radiologic technologists with over 10 years of experience in mammography. The evaluation was based on nine criteria within an AI quality control system. The correlation and consistency (Kappa test) of the assessment outcomes were compared among the junior technologist group, the AI quality control group, and the panel group. Additionally, the differences in the proportions of high-, medium-, and low-quality images rated by the three groups were analyzed. After one month of AI assistance, 200 images from 50 additional patients acquired by the same two junior technologists in January 2025 were collected. The area under the receiver operating characteristic curve and 95% confidence interval (95%CI) were calculated for the assessment performance of the junior technologist group before and after AI assistance. Differences were compared using the DeLong test. Changes in the disqualification rates for the nine criteria were analyzed. Results In consistency analysis, the AI quality control group showed high consistency with the panel group across multiple key criteria, with Kappa values ranging from 0.41 to 1.00. In contrast, the consistency between the junior technologist group and the panel group was generally low, with Kappa values ranging from 0.13 to 0.49. In comparison of image quality classification, no significant differences were observed in image quality classification between the AI group and the panel group (P>0.05). However, the proportion of images rated as high quality by the junior technologist group was significantly higher, while the proportions rated as medium and low quality were significantly lower, compared to those rated by the panel group (P<0.05). After AI assistance, the area under the receiver operating characteristic curve for the assessment performance of junior technologist group increased significantly from 0.56 (95%CI: 0.51-0.61) to 0.91 (95%CI: 0.87-0.94) (P<0.001). The disqualification rates for skin folds, incomplete inclusion of the pectoralis major muscle, and nipple not in profile decreased significantly. Conclusion AI demonstrates assessment capability comparable to the panel group in mammographic quality control. AI effectively enhances the quality of images acquired by junior technologists through real-time, objective feedback.

Objective To evaluate the application value of artificial intelligence (AI) in the quality control of mammographic images and explore its feasibility for improving image quality. Methods A retrospective analysis was conducted on 500 mammographic images from 125 female patients. These images were acquired in December 2024 at the Department of Radiology, Obstetrics and Gynecology Hospital of Tongji University by two junior technologists with qualification certificate for junior radiologic technologists and ≤ 2 months of independent operation. The reference standard was the evaluation by a panel of senior experts comprising one associate chief radiologist and two intermediate radiologic technologists with over 10 years of experience in mammography. The evaluation was based on nine criteria within an AI quality control system. The correlation and consistency (Kappa test) of the assessment outcomes were compared among the junior technologist group, the AI quality control group, and the panel group. Additionally, the differences in the proportions of high-, medium-, and low-quality images rated by the three groups were analyzed. After one month of AI assistance, 200 images from 50 additional patients acquired by the same two junior technologists in January 2025 were collected. The area under the receiver operating characteristic curve and 95% confidence interval (95%CI) were calculated for the assessment performance of the junior technologist group before and after AI assistance. Differences were compared using the DeLong test. Changes in the disqualification rates for the nine criteria were analyzed. Results In consistency analysis, the AI quality control group showed high consistency with the panel group across multiple key criteria, with Kappa values ranging from 0.41 to 1.00. In contrast, the consistency between the junior technologist group and the panel group was generally low, with Kappa values ranging from 0.13 to 0.49. In comparison of image quality classification, no significant differences were observed in image quality classification between the AI group and the panel group (P>0.05). However, the proportion of images rated as high quality by the junior technologist group was significantly higher, while the proportions rated as medium and low quality were significantly lower, compared to those rated by the panel group (P<0.05). After AI assistance, the area under the receiver operating characteristic curve for the assessment performance of junior technologist group increased significantly from 0.56 (95%CI: 0.51-0.61) to 0.91 (95%CI: 0.87-0.94) (P<0.001). The disqualification rates for skin folds, incomplete inclusion of the pectoralis major muscle, and nipple not in profile decreased significantly. Conclusion AI demonstrates assessment capability comparable to the panel group in mammographic quality control. AI effectively enhances the quality of images acquired by junior technologists through real-time, objective feedback.

Objective This study aimed to investigate the antimicrobial resistance profiles of bacterial strains isolated from pediatric intensive care units(PICU)in China for better antimicrobial therapy.Methods Clinical isolates were collected from 17 institutions,including tertiary care children's hospitals and pediatric department of tertiary general hospitals in China from January 1,2020 to December 31,2022.Antimicrobial susceptibility testing was carried out according to a unified protocol using Kirby-Bauer method or automated systems.Results were interpreted according to the breakpoints released by the Clinical and Laboratory Standards Institute(CLSI)in 2020.Results A total of 10 688 isolates were collected,including gram-positive organisms(39.2％)and gram-negative organisms(60.8％).The top three organisms were S.aureus(13.6％,1 453/10 688),A.baumannii(10.0％,1 067/10 688),and coagulase-negative Staphylococcus(9.9％,1 058/10 688).Multi-drug resistant organisms(MDROs)were very common in children.The prevalence of methicillin-resistant Staphylococcus aureus(MRSA),carbapenem-resistant Enterobacterales(CRE),carbapenem-resistant E.coli,carbapenem-resistant K.pneumoniae(CRKP),carbapenem-resistant A.baumannii(CRAB),and carbapenem-resistant P.aeruginosa(CRPA)was 41.1％,19.4％,8.8％,30.9％,67.4％,and 28.8％,respectively.Overall,more than 50％of Enterobacteriales isolates were resistant to cephalosporins,while nearly 25％of Enterobacteriales isolates were resistant to carbapenems.MDROs were highly resistant to commonly used antibiotics.More than 80％of CRE and CRAB strains were resistant to all beta-lactam antibiotics.CRE and CRAB showed low resistance rates to tigecycline and polymyxin.CRPA showed lower resistance rates to piperacillin,beta-lactamase inhibitor combinations than the resistance rates to third and fourth generation cephalosporins.All of the Staphylococcus and Enterococcus isolates were susceptible to vancomycin and tigecycline.None of PRSP strains isolated from meningitis and nonmeningitis samples were resistant to rifampicin,vancomycin,or linezolid.The prevalence of β-lactamase-negative ampicillin-resistant(BLNAR)strains was 43.3％in Haemophilus influenzae.Conclusions MDROs were prevalent in PICU.It is necessary to establish an effective multidisciplinary team(MDT)to control the antimicrobial resistance.

Objective To compare the effects of main artery clamping(MAC)and selective artery clamping(SAC)strategies on postoperative renal function in patients with chronic renal insufficiency undergoing robot-assisted partial nephrectomy.Methods A retrospective cohort study was conducted on 231 patients with preoperative chronic renal insufficiency[eGFR<90 mL/(min·1.73 m2)with renal injury markers or eGFR<60 mL/(min·1.73 m2)]who underwent robot-assisted partial nephrectomy in the Department of Urology of the First Affiliated Hospital of Army Medical University from February 2018 to February 2024.According to intraoperative renal artery clamping strategy,they were divided into a MAC group(n=129)and a SAC group(n=102).Preoperatively,individualized renal artery clamping strategies were developed using a machine learning-based multimodal holographic 3-D reconstruction technique.Serum creatinine(Scr)level was measured at 3 d and 3 months after surgery,and estimated glomerular filtration rate(eGFR)was calculated using the chronic kidney disease epidemiology collaboration equation(CKD-EPI)formula.Renal dynamic imaging with 99mTc-DTPA or 99mTc-MAG3 was used to assess the GFR of the affected kidney.Results At 3 d after surgery,the decrease in GFR of the affected kidney was significantly lower[(8.3±7.7)vs(16.0±10.2)mL/(min·1.73 m2),95%CI:-10.2～-5.2,P<0.001]in the SAC group than the MAC group.Scr increment analysis showed that the SAC group exhibited notably lower Scr increase[8.2(2.5,18.7)vs 15.5(5.8,28.3)μmol/L,95%CI:-12.3～-1.8,P=0.027],and milder eGFR decline[3.0(0.5,7.8)vs 7.5(2.0,14.3)mL/(min·1.73 m2),95%CI:-6.2～-0.8,P=0.015].And,in 3 months after surgery,the SAC group had lower Scr level[(89.2±23.1)vs(95.3±22.1)μmol/L,95%CI:-11.9～-0.3,P=0.042],and higher GFR of the affected kidney[(33.5±10.5)vs(26.1±10.9)mL/(min·1.73 m2),95%CI:4.6～10.2,P<0.001].Conclusion For patients with chronic renal insufficiency undergoing robot-assisted partial nephrectomy,SAC strategy is superior to MAC strategy in protecting postoperative renal function without increasing surgical risk.

Objective To investigate the effects of STIP1 homology and U-box containing protein 1(STUB1)on the ubiquitination of glutathione peroxidase 4(GPX4)and ferroptosis in colon cancer cells HCT116,as well as the impact on CD8+T cell-mediated killing of HCT116 cells.Methods HCT116 cells were divided into control group,empty plasmid transfection(pcDNA3.1-vector)group,STUB1 overexpression plasmid transfection(pcDNA3.1-STUB1)group,and co-transfection(pcDNA3.1-STUB1+pcDNA3.1-GPX4)group.Cell proliferation ability was assessed by CCK-8 assay.Clonogenic ability was determined by clone formation assay.Malondialdehyde(MDA)levels in cells were measured using an MDA kit.Intracellular ferrous ion(Fe2+)levels were detected with an Fe2+probe.Changes in mitochondrial membrane potential were detected using JC-1 dye.Protein expression levels of STUB1,solute carrier family 7 member 11(SLC7A11),and GPX4 were determined by western blot.The binding between STUB1 and GPX4 was assessed by co-immunoprecipitation.The effect of STUB1 on GPX4 protein ubiquitination was detected using a ubiquitin antibody.HCT116 cells transfected with different plasmids were co-cultured with human peripheral blood CD8+T cells,and the killing ability of CD8+T cells against HCT116 cells was measured using a lactate dehydrogenase(LDH)kit.Perforin,granzyme,and interferon-γ levels in the co-culture supernatant were determined by ELISA.Results Compared with the control group,the pcDNA3.1-STUB1 group showed decreased cell proliferation ability,mitochondrial membrane potential,and protein expression levels of SLC7A11 and GPX4,along with increased STUB1 protein expression,MDA,Fe2+levels,and GPX4 ubiquitination in HCT116 cells.Compared with the pcDNA3.1-STUB1 group,the pcDNA3.1-STUB1+pcDNA3.1-GPX4 group exhibited increased cell proliferation ability,mitochondrial membrane potential,and expression levels of SLC7A11 and GPX4,along with decreased MDA and Fe2+levels in HCT116 cells.After co-culture of HCT116 cells with CD8+T cells,the pcDNA3.1-STUB1 group showed significantly increased killing rate of CD8+T cells against HCT116 cells,as well as elevated levels of perforin,granzyme,and interferon-γ in the co-culture supernatant compared with the control group.Compared with the pcDNA3.1-STUB1 group,the pcDNA3.1-STUB1+pcDNA3.1-GPX4 group exhibited decreased killing rate of CD8+T cells against HCT116 cells and reduced levels of perforin,granzyme,and interferon-γ in the co-culture supernatant.Conclusion Overexpression of STUB1 promotes GPX4 ubiquitination in colon cancer cells HCT116,induces ferroptosis,and enhances the killing effect of CD8+T cells on HCT116 cells.

Objective To construct a prediction model for the risk of peripherally inserted central venous catheter(PICC)-related bloodstream infection(CRBSI)in preterm infants,and evaluate the effect of the model.Methods 1 295 preterm infants admitted to the neonatal intensive care unit(NICU)in a hospital and received PICC intrave-nous infusion from January 2019 to October 2023 were selected as the study subjects,including 1 080 preterm in-fants from January 2019 to December 2022 in the modeling set and 215 premature infants from January to October 2023 in the validation set.Risk factors of cases were analyzed based on 24 clinical characteristics,optimized charac-teristics was selected by LASSO regression,independent risk factors for CRBSI of preterm infants during PICC in-dwelling period were identified by multiple logistic regression analysis,and nomogram model was constructed with R software.Discrimination and fitting of the model were evaluated by the area under the curve(AUC)of the receiver operating characteristic(ROC)as well as Hosmer-Lemeshow test and calibration curve,and clinical practicality of the model was evaluated by decision curve analysis(DCA).Results Multivariate logistic analysis showed that birth weight ≥1 500 g,sterile protection during catheter maintenance,and sterile cloth wrapped joints were protective factors for CRBSI during PICC indwelling period in preterm infants(OR=0.172,0.187,0.063,respectively,all P＜0.05),while puncture frequency＞2 times,catheter indwelling period＞14 days,and use of tees were inde-pendent risk factors for CRBSI during PICC indwelling period in premature infants(OR=2.533,14.128,13.256,respectively,all P＜0.05).The AUC of ROC of the modeling set was 0.953(95％CI:0.936-0.969),and that of the validation set was 0.930(95％CI:0.885-0.974),indicating good discriminability of the model.The calibra-tion curve and Hosmer-Lemeshow goodness of fit test showed that the model had good accuracy and consistency,with high net profit value,indicating that the predictive value of the model was high and with good clinical practica-lity.The statistical test result in the rationality analysis of the model was P＜0.001.Conclusion The nomogram model based on the general clinical characteristics of preterm infants as well as the basic prevention and control measures of the catheter can provide a visual and simple evaluation tool for early identification of high risk factors for CRBSI in preterm infants.

Paraplegia caused by spinal cord injury is a serious neurological complication, for which surgery is currently the main treatment method. Due to different surgical approaches, patients are usually expected to maintain a passive prone position for a long time or switch between the supine and prone positions. Affected by multiple factors such as neurogenic sensory disorders, pathological changes in muscle tone and operative duration, the risk of intraoperative acquired pressure injury (IAPI) is significantly increased. Current clinical prevention strategies for IAPI in these patients predominantly focus on localized pressure relief during positioning, lacking systematic, standardized comprehensive prevention protocols or evidence-based guidelines. To address it, Department of Nursing, Orthopedics Branch, China International Exchange and Promotive Association for Medical and Health Care, Spinal Trauma Professional Committee, Orthopedics Branch, Chinese Medical Doctor Association, Nursing Group of Spine and Spinal Cord Professional Committee of Chinese Association of Rehabilitation Medicine organized experts in relevant fields to formulate Guideline for the prevention of intraoperative acquired pressure injury in paraplegic patients with spinal cord injury ( version 2025), based on evidence-based medical evidence and latest research results and clinical practice at home and abroad. Eleven recommendations were put forward from the aspects of preoperative risk assessment, intraoperative prevention strategies, postoperative handover and monitoring, and supportive mechanisms for IAPI prevention, aiming to standardize the prevention measures and management strategies of IAPI in paraplegic patients with spinal cord injury and accelerate the recovery of patients and improve the therapeutic effect.

Objective:To investigate the clinical efficacy of haploidentical high-dose in vitro non-T-cell-depleted peripheral blood hematopoietic stem cell transplantation (haplo-HDPSCT) in treating adult patients with Ph + acute lymphoblastic leukemia (Ph + ALL) . Method:This retrospective analysis was conducted on the clinical efficacy of 25 adult patients with Ph + ALL who underwent haplo-HDPSCT from July 2011 to June 2022 at our hospital. Results:This study included 25 patients with a median age of 27 (16-61) years, consisting of 12 males and 13 females. CR1 and ≥CR2 before transplantation were found in 23 and 2 cases, positive and negative minimal residual lesions were observed in 8 and 17 cases, and myeloablative conditioning and reduced-intensity conditioning were reported in 21 and 4 cases, respectively. Hematopoietic function was restored in all 25 patients after stem cell infusion. Of the 25 patients who underwent transplantation, 16 developed acute graft-versus-host disease (aGVHD). The cumulative incidence rates of Ⅱ-Ⅳ and Ⅲ-Ⅳ aGVHD were (40.4±11.3) % and (4.8±4.6) %, respectively. Four patients experienced relapse after transplantation, the cumulative relapse rates at 1 and 2 years after transplantation were (4.0±3.9) % and (14.5±7.9) %, respectively. The 2-year overall survival rate after transplantation was (81.3±8.5) % and the disease-free survival rate was (77.1±9.1) %.Conclusion:This study reveals that the unique haplo-HDPSCT protocol achieves good clinical efficacy in Ph + ALL treatment.

Objective:To evaluate the value of preoperative triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio in predicting postoperative delirium (POD) following internal fixation for lower limb fracture in geriatric patients.Methods:In this retrospective case-control study, the medical records of patients, aged ≥ 65 yr, with American Society of Anesthesiologists Physical Status classification Ⅱ or Ⅲ, who underwent internal fixation for lower limb fracture under general anesthesia or spinal-epidural anes-thesia at Hebei General Hospital from January 2023 to July 2024, with the postoperative length of hospital stay of at least 3 days, were collected. The baseline characteristics, preoperative length of hospital stay, parameters of the last preoperative laboratory tests, type of surgery, anesthesia method, duration of surgery and anesthesia, and intraoperative hypotension and fluid intake and output were collected, and the ratio of TG to HDL-C was calculated. Patients were stratified into POD group and non-POD group based on whether POD developed. The logistic regression was carried out to identify influencing factors for POD. The receiver operating characteristic (ROC) curve was plotted to evaluate the predictive accuracy of preoperative TG/HDL-C ratio in predicting POD.Results:A total of 234 patients were finally included, of whom 30 developed POD, with an incidence of 12.8%. The results of multivariate logistic regression indicated that the elevated preoperative TG/HDL-C ratio, increased WBC count and a history of cerebrovascular disease were independent risk factors for POD, and the increased albumin concentration was an independent protective factor for POD ( P<0.05). The area under the curve of preoperative TG/HDL-C ratio in predicting POD was 0.758, with a specificity of 0.809 and sensitivity of 0.633, and the optimal cut-off value was 3.285 ( P<0.001). Conclusions:Elevated preoperative TG/HDL-C ratio is an independent risk factor for POD and may have a certain predictive value for POD in geriatric patients undergoing internal fixation for lower limb fracture.