Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Background::In vitro fertilization (IVF) has emerged as a transformative solution for infertility. However, achieving favorable live-birth outcomes remains challenging. Current clinical IVF practices in IVF involve the collection of heterogeneous embryo data through diverse methods, including static images and temporal videos. However, traditional embryo selection methods, primarily reliant on visual inspection of morphology, exhibit variability and are contingent on the experience of practitioners. Therefore, an automated system that can evaluate heterogeneous embryo data to predict the final outcomes of live births is highly desirable. Methods::We employed artificial intelligence (AI) for embryo morphological grading, blastocyst embryo selection, aneuploidy prediction, and final live-birth outcome prediction. We developed and validated the AI models using multitask learning for embryo morphological assessment, including pronucleus type on day 1 and the number of blastomeres, asymmetry, and fragmentation of blastomeres on day 3, using 19,201 embryo photographs from 8271 patients. A neural network was trained on embryo and clinical metadata to identify good-quality embryos for implantation on day 3 or day 5, and predict live-birth outcomes. Additionally, a 3D convolutional neural network was trained on 418 time-lapse videos of preimplantation genetic testing (PGT)-based ploidy outcomes for the prediction of aneuploidy and consequent live-birth outcomes.Results::These two approaches enabled us to automatically assess the implantation potential. By combining embryo and maternal metrics in an ensemble AI model, we evaluated live-birth outcomes in a prospective cohort that achieved higher accuracy than experienced embryologists (46.1% vs. 30.7% on day 3, 55.0% vs. 40.7% on day 5). Our results demonstrate the potential for AI-based selection of embryos based on characteristics beyond the observational abilities of human clinicians (area under the curve: 0.769, 95% confidence interval: 0.709–0.820). These findings could potentially provide a noninvasive, high-throughput, and low-cost screening tool to facilitate embryo selection and achieve better outcomes. Conclusions::Our study underscores the AI model’s ability to provide interpretable evidence for clinicians in assisted reproduction, highlighting its potential as a noninvasive, efficient, and cost-effective tool for improved embryo selection and enhanced IVF outcomes. The convergence of cutting-edge technology and reproductive medicine has opened new avenues for addressing infertility challenges and optimizing IVF success rates.

Objective To explore clinical outcomes and bone resection of interlaminar fenestration decompression and u-nilateral biportal endoscopic(UBE)technique in treating lumbar disc herniation(LDH).Methods A retrospective study was performed on 105 patients with single-level LDH treated from December 2019 to December 2021.Fifty-four patients in UBE group,including 32 males and 22 females,aged from 18 to 50 years old with an average of(38.7±9.3)years old,were treated with UBE,29 patients withL4.5and 25 patients with L5S1.There were 51 patients in small fenestration group,including 27 males and 24 females,aged from 18 to 50 years old with an average of(39.9±10.0)years old,were treated with small fenestra-tion,25 patients with L4.5 and 26 patients with L5S1.Perioperative indexes,such as operation time,postoperative time of getting out of bed and hospital stay were observed and compared between two groups.Visual analogue scale(VAS)and Oswestry dis-ability index(ODI)were compared between two groups before operation and 1,3,6 and 12 months after operation,respective-ly;and modified MacNab evaluation criteria was used to evaluate clinical efficacy.Amount of bone resection and retention rate of inferior articular process laminoid complex were compared between two groups.Results All 105 patients were successfully completed operation.Both of two groups were followed up from 6 to 12 months with an average of(10.69±2.49)months.Oper-ation time,postoperative time of getting out of bed and hospital stay were(58.20±5.54)min,(2.40±0.57)dand(3.80±0.61)d in UBE group,and(62.90±7.14)min,(4.40±0.64)d and(4.40±0.64)d in small fenestrum group,respectively;and had sta-tistically difference between two groups(P＜0.05).Postoperative VAS of low back and leg pain and ODI in both groups were significantly lower than those before surgery(P＜0.05).VAS of lumbar pain in UBE group(1.37±0.49)score was lower than that of small fenestration group(2.45±0.64)score,and had statistically difference(t=9.745,P＜0.05).Postoperative ODI in UBE group at 1 and 3 months were(28.54±3.31)％and(22.87±3.23)％,respectively,which were lower than those in small fenestra group(36.31±9.08)％and(29.90±8.36)％,and the difference was statistically significant(P＜0.05).There were no significant difference in VAS and ODI between two groups at other time points(P＞0.05).According to the modified MacNab evaluation criteria at the latest follow-up,49 patients got excellent result,3 good,and 2 fair in UBE group.In small fenestration group,35 patients got excellent,12 good,and 4 fair.In UBE group,amount of bone resection on L4,5 segment was(0.45±0.08)cm3 and(0.31±0.08)cm3 on the segment of L5S1.In small fenestration group,amount of bone resection on L4.5 segment was(0.57±0.07)cm3 and(0.49±0.04)cm3 on the segment of L5S1,and amount of bone resection of lower articular process laminar complex on the same segment in UBE group was less than that in small fenestration group(P＜0.05).In UBE group,retention rate of laminoid complex on L4,5 segment was(0.73±0.04)and L5S1 segment was(0.83±0.03),whileL4,5segment was(0.68± 0.06)and L5S1 segment was(0.74±0.04)in small fenestration group,the lower articular process laminar complex retention rate in UBE group was higher than that in small fenestration group(P＜0.05).Conclusion Both unilateral double-channel endoscopy and small fenestration of laminae could achieve good clinical results in treating LDH,but UBE has advantages of less trauma,higher eficiency,faster postoperative recovery and less damage to bone structure.

Objective To analyze the risk factors of gastrointestinal bleeding in patients with type A aortic dissection(TAAD)after Sun's operation.Methods The clinical data of 87 patients who underwent TAAD Sun's operation in our hospital from March 2021 to June 2022 were retrospectively analyzed.They were divided into the bleeding group and the non-bleeding group according to whether there was gastrointestinal bleeding after operation.The clinical data of patients in the two groups was compared and analyzed.The binary Logistic regression analysis was used to analyze the risk factors of gastrointestinal bleeding.The clinical predictor of postoperative gastrointestinal bleeding was analyzed by receiver operating characteristic(ROC)curve.Results In this study,there were 40 cases of postoperative gastrointestinal bleeding(the bleeding group)and 47 cases of non-bleeding(the non-bleeding group).Compared with the non-bleeding group,the bleeding group had a shorter onset time,a higher proportion of patients with hypertension history,a higher preoperative creatinine abnormality rate,more intraoperative blood loss,longer postoperative mechanical ventilation time,higher postoperative infection rate,and higher poor prognosis rate,with statistically significant differences(P<0.05).There was no statistically significant difference in the gender,age,gastrointestinal diseases history,smoking history,preoperative platelets,preoperative international normalized ratio(INR),preoperative alanine aminotransferase(ALT),preoperative aspartate aminotransferase(AST),preoperative γ-glutamyl transpeptidase(GGT),preoperative dissection involving abdominal aorta,operation time,intraoperative cardiopulmonary bypass time,intraoperative circulatory arrest time,intraoperative aortic occlusion time or intraoperative blood transfusion rate.Logistic regression analysis showed that hypertension history(OR=2.468,95%CI:0.862 to 7.067,P=0.037),preoperative creatinine>105 μmol/L(OR=3.970,95%CI:1.352 to 11.659,P=0.011),long postoperative mechanical ventilation time(OR=1.015,95%CI:0.094 to 1.018,P=0.041)and postoperative infection(OR=3.435,95%CI:0.991 to 11.900,P=0.012)were the independent risk factors for postoperative gastrointestinal bleeding in TAAD patients.ROC curve showed that the postoperative mechanical ventilation time exceeding 64 hours were the clinical predictor of postoperative gastrointestinal bleeding in TAAD patients.Conclusion The prognosis of TAAD patients with postoperative gastrointestinal bleeding after Sun's operation is poor.Hypertension history,preoperative acute renal insufficiency,long postoperative mechanical ventilation time and postoperative infection are closely related to postoperative gastrointestinal bleeding in TAAD patients after operation,which should be paid more attention to,and corresponding evaluation,early identification and early intervention should be made to improve the prognosis of patients.

Objective To explore the value of artificial intelligence federated learning system based on chest X-ray films for pathogen diagnosis of community-acquired pneumonia(CAP)in children.Methods Totally 900 cases of CAP children from 2 hospitals were retrospectively enrolled,including bacterial,viral and mycoplasma CAP(each n=300),and chest posteroanterior X-ray films were collected.Meanwhile,chest posteroanterior X-ray films of 5856 children from the publicly available dataset GWCMCx were collected,including 4273 CAP images and 1583 healthy chest images.All above 6756 images were divided into training set(n=5359)and validation set(n=1397)at the ratio of 8∶2.Then a pathogen diagnosis model of children CAP was established based on attention mechanism.Binary and ternary diagnostic algorithms were designed,and federated deployment training was performed.The efficacy of this system for pathogen diagnosis of children CAP was analyzed and compared with DenseNet model.Results Based on all data,the accuracy of the obtained artificial intelligence federated learning system model for diagnosing children CAP was 97.00%,with the area under the curve(AUC)of 0.990.Based on hospital data,the AUC of this system using single imaging data and clinical-imaging data for pathogen diagnosis of children CAP was 0.858 and 0.836,respectively,both better than that of DenseNet model(0.740,both P＜0.05).Conclusion The artificial intelligence federated learning system based on chest X-ray films could be used for pathogen diagnosis of children CAP.

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.