ObjectiveTo investigate and analyze an outbreak of rotavirus infectious diarrhea in a prison in Chongqing Municipality, to provide a basis for adult rotavirus surveillance and prevention, and to explore the public health problems in special settings. MethodsA retrospective survey was conducted to collect and analyze data on individual cases with diarrheal disease on-site. The clinical characteristics, as well as the temporal, spatial and geographical distribution patterns of the epidemic were described. Multi-pathogen detection tests were conducted both on diarrhea cases and environmental samples, with viral genotyping performed on positive samples. A case-control analysis was performed to identify the causes of the outbreak, and an SEIR model was adopted to predict the outbreak trend and evaluate the effectiveness of interventions. ResultsA total of 65 cases were found among the inmates, with an attack rate of 2.03%. The predominant clinical manifestations included diarrhea (89.23%), watery stool (73.85%), and dehydration (18.46%). The epidemic curve indicated a “human-to-human” transmission pattern, with an average incubation period of 5‒6 days. The attack rates among chefs in the main canteen (80.00%, 8/10) and caterers (28.33%, 17/60) were significantly higher than those of other inmates （P<0.05）. Multi-pathogen polymerase chain reaction (PCR) testing detected positive for group A rotavirus, with the viral genotyping identified as G9P [8] strain. Factors such as unprotected "bare-handed" food distribution among cases with diarrhea (OR=9.512, 95%CI: 4.261‒21.234) and close contact with diarrhea cases (OR=3.656, 95%CI: 1.719‒7.778) were the possible cause of the outbreak. The SEIR model (r₀=5, α=0.3, β₁=0.08, β₂=0.04) was constructed using prison inmates as susceptible population, aiming at fitting the initial transmission trend of the outbreak, and the epidemic rate declined rapidly after intervention measures were implemented (r_t≈0). ConclusionThis rare rotavirus infection diarrhea outbreak among adults in confined settings suggests that the construction of public health prevention and control systems in prison may be overlooked. Cross infection during meal processing and distribution in the canteens of such settings is likely to be the cause of the outbreak. Given the potential neglect of public heath system construction in special settings, it is imperative to enhance the surveillance and monitoring of rotavirus and other intestinal multi-pathogens among adults, as well as the construction of public health prevention and control systems in these special settings.

This paper systematically summarizes the practical experience of the 2025 Dingri earthquake emergency medical rescue in Tibet. It analyzes the requirements for earthquake medical rescue under conditions of high-altitude hypoxia, low temperature, and low air pressure. The paper provides a detailed discussion on the strategic layout of earthquake medical rescue at the national level, local government level, and through social participation. It covers the construction of rescue organizational systems, technical systems, material support systems, and information systems. The importance of building rescue teams is emphasized. In high-altitude and cold conditions, rapid response, scientific decision-making, and multi-party collaboration are identified as key elements to enhance rescue efficiency. By optimizing rescue organizational structures, strengthening the development of new equipment, and promoting telemedicine technologies, the precision and effectiveness of medical rescue can be significantly improved, providing important references for future similar disaster rescues.

Objective To compare the effects of quadratus lumborum block at the lateral supra-arcuate ligament(QLB-LSAL)versus subcostal transversus abdominis plane block(STAPB)on perioperative analgesia and postoperative inflammation in patients undergoing laparoscopic radical resection of colorectal cancer.Methods In this prospective randomized study,we recruited 102 patients undergoing laparoscopic colorectal cancer surgery between October 2022 and October 2024 under general anesthesia and randomly assigned them to two groups:QLB-LSAL(Group Q,n=51)and STAPB(Group S,n=51).Mean arterial pressure(MAP)and heart rate(HR)were recorded before anesthesia induction(T0),before surgical incision(T1),start of surgery(T2),during pneumoperitoneum establishment(T3),during peritoneal lavage(T4),at the end of surgery(T5),and upon leaving the operating room(T6).Intraoperative remifentanil consumption,time to first patient-controlled analgesia demand,and frequency of effective compression and rescue analgesia were recorded.Visual Analog Scale(VAS)scores at rest and during coughing were assessed at 24,48,and 72 hours postoperatively.Interleukin-6(IL-6)and systemic immune-inflammatory index(SII)at 1 day preoperatively,1,and 3 days postoperatively were recorded.Postoperative recovery indicators and adverse events were also recorded.Results Group Q demonstrated significantly lower MAP and HR compared with Group S from T3 to T6(P<0.05).Group Q had significantly lower intraoperative remifentanil consumption,significantly longer time to first analgesic pump demand,fewer effective pump compres-sion,and lower frequency for rescue analgesia requests(all P<0.05).VAS scores at rest and during coughing in Group Q were significantly lower at 24 h and 48 h postoperatively(P<0.05).As compared with preoperative levels,both IL-6 and SII increased at 1 and 3 days postoperatively,but magnitude of increase in Group Q was smaller than in Group S(P<0.05).In comparison to Group S,Group Q demonstrated significantly earlier ambulation,shorter hospital stay,and fewer adverse events(P<0.05).Conclusion QLB-LSAL is superior to STAPB in enhancing perioperative analgesia,attenuating inflammatory response,and accelerating postoperative rehabilitation in patients undergoing laparoscopic colorectal cancer resection.

Objective:To explore the predictive value of models based on clinical parameters, deep learning radiomics (DLR) from CT images, and traditional handcrafted radiomics (HCR) in assessing pathological complete response (pCR) after neoadjuvant radiotherapy combined with medical therapy in patients with esophageal cancer.Methods:A retrospective study was conducted on 130 patients with locally advanced esophageal cancer who underwent neoadjuvant radiotherapy combined with medical therapy followed by surgery at the First Affiliated Hospital of the University of Science and Technology of China from August 1, 2018, to August 31, 2024. Patients were randomly divided into a training set ( n=91) and a validation set ( n=39) at a ratio of 7:3. Logistic regression analysis was performed to identify clinical independent risk factors associated with pCR. DLR and HCR features were extracted from the tumor and the 5 mm peritumoral region on planning CT images. Features for modeling were selected using t-test, Mann-Whitney U test or Fisher exact probability method, least absolute shrinkage and selection operator (LASSO) regression to calculate the radiomics score (Rad-score). A nomogram was then constructed by integrating the clinical risk factors. The predictive performance of each model was evaluated using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, and decision curve analysis (DCA) to assess clinical benefits. Results:Multivariate logistic regression analysis identified body weight ( OR=1.101, 95% CI: 1.029-1.177, P=0.005) and lymph node positivity ( OR=0.100, 95% CI: 0.014-0.727, P=0.023) as independent predictors of pCR. The peritumoral DLR-HCR model showed superior predictive performance, with AUCs of 0.870 (95% CI: 0.799-0.942) in the training set and 0.866 (95% CI: 0.750-0.982) in the validation set. The combined model incorporating clinical parameters achieved the best performance, with AUCs of 0.903 (95% CI: 0.845-0.962) and 0.888 (95% CI: 0.782-0.994) in the training and validation sets, respectively. Conclusions:The combined model integrating peritumoral DLR-HCR features with clinical parameters provides excellent predictive value for pCR after neoadjuvant radiotherapy combined with medical therapy in esophageal cancer and offers valuable guidance for personalized treatment strategies.

Objective To observe the value of pituitary radiomics and MRI features combined model for predicting growth hormone(GH)status in pediatric short stature.Methods Totally 300 children with short stature were enrolled as training set,while other 73 cases were taken as external validation set.Based on growth hormone stimulation test,the children were divided into GH deficiency(GHD)group(n=228)and non-GHD group(n=145).The training set included 196 cases in GHD subgroup and 104 cases in non-GHD subgroup,while the validation set included 32 cases in GHD subgroup and 41 cases in non-GHD subgroup.Radiomics features of pituitary were extracted from T1WI.The key features were selected using least absolute shrinkage and selection operator(LASSO)regression,and machine learning models were subsequently constructed using support vector machine(SVM),logistic regression(LR),naive Bayes(NB)and K-nearest neighbor(KNN),respectively.Then combined models were constructed combining with MRI features,and the efficacy of each model was evaluated.Results The area under the curve(AUC)of SVM,LR,NB,and KNN radiomics model for predicting GH status in pediatric short stature was 0.860,0.831,0.838 and 0.901 in training set,0.788,0.829,0.823 and 0.770 in validation set,while of the relative combined SVM,LR,NB and KNN model was 0.924,0.903,0.859 and 0.920 in training set,and 0.827,0.881,0.836 and 0.718 in validation set.LRcombined model had the best overall performance,with sensitivity of 84.94％,specificity of 80.56％and accuracy of 83.61％in training set,and 80.95％,72.22％and 80.00％in validation set,respectively.Conclusion Pituitary radiomics and MRI features combined model could effectively predict GH status in pediatric short stature.

Purpose To investigate the independent risk factors for early recurrence of solitary hepatocellular carcinoma after radiofrequency ablation based on gadoxetic acid disodium(Gd-EOB-DTPA)-enhanced MRI combined with clinical features.Materials and Methods Clinical and imaging data of hepatocellular carcinoma patients who underwent radiofrequency ablation at the First Affiliated Hospital of Henan University of Chinese Medicine from January 2019 to June 2022 were retrospectively collected.All patients underwent preoperative Gd-EOB-DTPA-enhanced MRI and were followed up for up to two years post-surgery.Univariate and multivariate Cox proportional hazards regression were performed to identify independent risk factors for recurrence after radiofrequency ablation.Results A total of 58 patients were finally included,including early recurrence group(n=22)and non-early recurrence group(n=36).Multivariate Cox regression analysis revealed that preoperative alpha-fetoprotein(AFP)levels(HR=1.103,95%CI 1.008-1.206,P=0.033),arterial-phase irregular margin enhancement(HR=4.647,95%CI 1.527-14.110,P=0.007),peritumoral arterial-phase enhancement(HR=11.575,95%CI 3.575-37.478,P=0.001)and peritumoral hepatobiliary phase hypointensity(HR=5.058,95%CI 1.129-22.668,P=0.034)were independent risk factors for early recurrence.The area under the curve for AFP combined with arterial-phase irregular margin enhancement,peritumoral arterial-phase enhancement and peritumoral hepatobiliary phase hypointensity were 0.896,0.842 and 0.860,with accuracy rates of 81.0%,84.5%and 82.8%,respectively.Conclusion Preoperative serum AFP levels,arterial-phase irregular margin enhancement,peritumoral arterial-phase enhancement and peritumoral hepatobiliary phase hypointensity are independent risk factors for early recurrence after radiofrequency ablation in hepatocellular carcinoma patients.The combination of AFP and any of these MRI features significantly improves predictive efficacy.

Purpose To investigate the independent risk factors for early recurrence of solitary hepatocellular carcinoma after radiofrequency ablation based on gadoxetic acid disodium(Gd-EOB-DTPA)-enhanced MRI combined with clinical features.Materials and Methods Clinical and imaging data of hepatocellular carcinoma patients who underwent radiofrequency ablation at the First Affiliated Hospital of Henan University of Chinese Medicine from January 2019 to June 2022 were retrospectively collected.All patients underwent preoperative Gd-EOB-DTPA-enhanced MRI and were followed up for up to two years post-surgery.Univariate and multivariate Cox proportional hazards regression were performed to identify independent risk factors for recurrence after radiofrequency ablation.Results A total of 58 patients were finally included,including early recurrence group(n=22)and non-early recurrence group(n=36).Multivariate Cox regression analysis revealed that preoperative alpha-fetoprotein(AFP)levels(HR=1.103,95%CI 1.008-1.206,P=0.033),arterial-phase irregular margin enhancement(HR=4.647,95%CI 1.527-14.110,P=0.007),peritumoral arterial-phase enhancement(HR=11.575,95%CI 3.575-37.478,P=0.001)and peritumoral hepatobiliary phase hypointensity(HR=5.058,95%CI 1.129-22.668,P=0.034)were independent risk factors for early recurrence.The area under the curve for AFP combined with arterial-phase irregular margin enhancement,peritumoral arterial-phase enhancement and peritumoral hepatobiliary phase hypointensity were 0.896,0.842 and 0.860,with accuracy rates of 81.0%,84.5%and 82.8%,respectively.Conclusion Preoperative serum AFP levels,arterial-phase irregular margin enhancement,peritumoral arterial-phase enhancement and peritumoral hepatobiliary phase hypointensity are independent risk factors for early recurrence after radiofrequency ablation in hepatocellular carcinoma patients.The combination of AFP and any of these MRI features significantly improves predictive efficacy.

Objective To compare the effects of quadratus lumborum block at the lateral supra-arcuate ligament(QLB-LSAL)versus subcostal transversus abdominis plane block(STAPB)on perioperative analgesia and postoperative inflammation in patients undergoing laparoscopic radical resection of colorectal cancer.Methods In this prospective randomized study,we recruited 102 patients undergoing laparoscopic colorectal cancer surgery between October 2022 and October 2024 under general anesthesia and randomly assigned them to two groups:QLB-LSAL(Group Q,n=51)and STAPB(Group S,n=51).Mean arterial pressure(MAP)and heart rate(HR)were recorded before anesthesia induction(T0),before surgical incision(T1),start of surgery(T2),during pneumoperitoneum establishment(T3),during peritoneal lavage(T4),at the end of surgery(T5),and upon leaving the operating room(T6).Intraoperative remifentanil consumption,time to first patient-controlled analgesia demand,and frequency of effective compression and rescue analgesia were recorded.Visual Analog Scale(VAS)scores at rest and during coughing were assessed at 24,48,and 72 hours postoperatively.Interleukin-6(IL-6)and systemic immune-inflammatory index(SII)at 1 day preoperatively,1,and 3 days postoperatively were recorded.Postoperative recovery indicators and adverse events were also recorded.Results Group Q demonstrated significantly lower MAP and HR compared with Group S from T3 to T6(P<0.05).Group Q had significantly lower intraoperative remifentanil consumption,significantly longer time to first analgesic pump demand,fewer effective pump compres-sion,and lower frequency for rescue analgesia requests(all P<0.05).VAS scores at rest and during coughing in Group Q were significantly lower at 24 h and 48 h postoperatively(P<0.05).As compared with preoperative levels,both IL-6 and SII increased at 1 and 3 days postoperatively,but magnitude of increase in Group Q was smaller than in Group S(P<0.05).In comparison to Group S,Group Q demonstrated significantly earlier ambulation,shorter hospital stay,and fewer adverse events(P<0.05).Conclusion QLB-LSAL is superior to STAPB in enhancing perioperative analgesia,attenuating inflammatory response,and accelerating postoperative rehabilitation in patients undergoing laparoscopic colorectal cancer resection.

Objective To observe the value of pituitary radiomics and MRI features combined model for predicting growth hormone(GH)status in pediatric short stature.Methods Totally 300 children with short stature were enrolled as training set,while other 73 cases were taken as external validation set.Based on growth hormone stimulation test,the children were divided into GH deficiency(GHD)group(n=228)and non-GHD group(n=145).The training set included 196 cases in GHD subgroup and 104 cases in non-GHD subgroup,while the validation set included 32 cases in GHD subgroup and 41 cases in non-GHD subgroup.Radiomics features of pituitary were extracted from T1WI.The key features were selected using least absolute shrinkage and selection operator(LASSO)regression,and machine learning models were subsequently constructed using support vector machine(SVM),logistic regression(LR),naive Bayes(NB)and K-nearest neighbor(KNN),respectively.Then combined models were constructed combining with MRI features,and the efficacy of each model was evaluated.Results The area under the curve(AUC)of SVM,LR,NB,and KNN radiomics model for predicting GH status in pediatric short stature was 0.860,0.831,0.838 and 0.901 in training set,0.788,0.829,0.823 and 0.770 in validation set,while of the relative combined SVM,LR,NB and KNN model was 0.924,0.903,0.859 and 0.920 in training set,and 0.827,0.881,0.836 and 0.718 in validation set.LRcombined model had the best overall performance,with sensitivity of 84.94％,specificity of 80.56％and accuracy of 83.61％in training set,and 80.95％,72.22％and 80.00％in validation set,respectively.Conclusion Pituitary radiomics and MRI features combined model could effectively predict GH status in pediatric short stature.

Objective:To explore the predictive value of models based on clinical parameters, deep learning radiomics (DLR) from CT images, and traditional handcrafted radiomics (HCR) in assessing pathological complete response (pCR) after neoadjuvant radiotherapy combined with medical therapy in patients with esophageal cancer.Methods:A retrospective study was conducted on 130 patients with locally advanced esophageal cancer who underwent neoadjuvant radiotherapy combined with medical therapy followed by surgery at the First Affiliated Hospital of the University of Science and Technology of China from August 1, 2018, to August 31, 2024. Patients were randomly divided into a training set ( n=91) and a validation set ( n=39) at a ratio of 7:3. Logistic regression analysis was performed to identify clinical independent risk factors associated with pCR. DLR and HCR features were extracted from the tumor and the 5 mm peritumoral region on planning CT images. Features for modeling were selected using t-test, Mann-Whitney U test or Fisher exact probability method, least absolute shrinkage and selection operator (LASSO) regression to calculate the radiomics score (Rad-score). A nomogram was then constructed by integrating the clinical risk factors. The predictive performance of each model was evaluated using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, and decision curve analysis (DCA) to assess clinical benefits. Results:Multivariate logistic regression analysis identified body weight ( OR=1.101, 95% CI: 1.029-1.177, P=0.005) and lymph node positivity ( OR=0.100, 95% CI: 0.014-0.727, P=0.023) as independent predictors of pCR. The peritumoral DLR-HCR model showed superior predictive performance, with AUCs of 0.870 (95% CI: 0.799-0.942) in the training set and 0.866 (95% CI: 0.750-0.982) in the validation set. The combined model incorporating clinical parameters achieved the best performance, with AUCs of 0.903 (95% CI: 0.845-0.962) and 0.888 (95% CI: 0.782-0.994) in the training and validation sets, respectively. Conclusions:The combined model integrating peritumoral DLR-HCR features with clinical parameters provides excellent predictive value for pCR after neoadjuvant radiotherapy combined with medical therapy in esophageal cancer and offers valuable guidance for personalized treatment strategies.