The welfare and ethics of laboratory animals are the ethical principles and behavioral norms that need to be followed in conducting animal-based scientific research, breeding and managing laboratory animals, and supervising and regulating such activities. The level of protection of laboratory animal welfare and ethics is closely related to the development of science and technology, which has become a widely recognized international consensus. At present, Guangdong Province is accelerating the construction of a high-level science and technology innovation province and the Guangdong-Hong Kong-Macao Greater Bay Area International Science and Technology Innovation Center. Guangdong Province should rely on its advanced governance capacity in the field of laboratory animal science and technology ethics to promote the high-quality development of its laboratory animal science and technology sector. Based on the management laws, regulations, and institutional mechanisms of laboratory animals in China, this paper explores the optimization of the laboratory animal science and technology ethics governance system, which includes the institutional guarantees, responsibility systems, ethical review and supervision mechanisms, and education and outreach. Through methods such as literature research, questionnaire surveys, and interview investigations, an empirical study of the laboratory animal science and technology ethics governance system in Guangdong Province has been conducted. Analysis of literature and research results shows that Guangdong Province has basically established a laboratory animal management system, collaboration mechanism, supervision mechanism, and education and training system that meet the current requirements of the laboratory animal science and technology ethics governance system in China. However, there are still problems such as an incomplete laboratory animal science and technology ethics supervision mechanism, an underdeveloped operation mechanism of review institutions, insufficient attention paid by laboratory animal units to the ethical review of animal experiments, inconsistent ethical review standards, and a lack of professional ethical education and training for ethics review personnel. Therefore, optimization measures such as improving the laboratory animal science and technology ethics review system, strengthening supervision and inspection, further strengthening the accountability of responsible entities, formulating review norms, and enhancing hierarchical and classified education and training are proposed, to provide a theoretical basis for promoting the normalized and long-term governance of laboratory animal science and technology ethics in Guangdong Province.

Objective To investigate the mid- to long-term follow-up results of ascending aorta (AAO)-descending thoracic aorta (DTA) bypass grafting via median sternotomy incision for the treatment of complex aortic arch coarctation. Methods A retrospective analysis was conducted on the clinical data of patients with complex aortic arch coarctation who underwent AAO-DTA bypass grafting via median sternotomy incision at the First Hospital of Tsinghua University from August 2004 to May 2017. Results A total of 7 patients were enrolled, including 4 males and 3 females, aged (13.3±4.6) years, and weighted (40.2±12.2) kg. Six (85.7%) patients had concomitant upper limb hypertension. Four patients were aortic arch coarctation combined with intracardiac malformations, two were post-operative restenosis, and 1 was post-operative restenosis combined with intracardiac malformation. All patients underwent surgery under cardiopulmonary bypass. There were no perioperative deaths or major complications. The pre-operative upper-lower limb pressure difference was (39.3±19.2) mm Hg, which decreased to (2.9±2.7) mm Hg post-operatively (P<0.01). The follow-up period was (14.9±5.9) years. There were no long-term deaths or artificial graft-related complications. Except for one patient who still had mild hypertension, the blood pressure of the remaining patients returned to normal. Conclusion AAO-DTA bypass grafting via median sternotomy incision for the treatment of complex aortic arch coarctation can effectively reduce upper limb blood pressure and the upper-lower limb arterial pressure difference, has fewer complications, and demonstrates satisfactory mid- to long-term efficacy.

[Purpose]To analyze the results of upper gastrointestinal cancer screening in rural areas of Lhasa from 2015 to 2019.[Methods]Upper gastrointestinal cancer screening program was conducted among residents aged 40～69 years old from 3 rural project sites in Lhasa selected by cluster sampling method from 2015 to 2019.The detected malignant tumors and precancerous le-sions were treated and confirmed by pathological examination.The detection rate of esophagus and stomach cancer were calculated by region,sex and age and compared by x2 test.[Results]A total of 1 399 people underwent gastroscopy,among whom 1 288 completed pathological biopsy(92.07％).Three cases of esophageal cancer were detected with a detection rate of 0.21％(3/1 399),all of which were advanced squamous cell carcinoma.Eight cases of gastric cancer were detected with a detection rate of 0.57％(8/1 399),and 2 cases were early gastric cancer.The detection rate of low-grade and high-grade epithelial neoplasia of gastric mucosa was 0.64％(9/1 399)and 0.21％(3/1 399),respectively.There was no significant difference in the detection rate among different regions,sexes and age groups(all P＞0.05).[Conclusion]The detection rate of upper gastrointesti-nal cancer in screening population in Lhasa is lower than the national average level.Men and the elderly are important target populations for upper gastrointestinal cancer screening,and increasing participation rates is necessary for more effective screening outcomes.

Objective To construct a nomogram model for prolonged length of stay in patients with acute cerebral infarction(ACI)based on total cerebral small vessel disease(CSVD)burden scores,and validate its effectiveness.Methods A total of 462 ACI patients admitted to the Department of Neurology of South Taihu Hospital Affiliated To Huzhou College from January 2021 to December 2023 were selected as the study subjects.According to the ratio of 7:3,patients were divided into training group of 323 cases and validation group of 139 cases.Lasso-Logistic regression was used to analyze the risk factors for prolonged length of stay in ACI patients,construct a nomogram model and validate the model using validation data.Receiver operating characteristic(ROC)curve were used to evaluate the predictive performance of the model.Results Based on the training group data,Lasso regression screened four non-zero coefficient indicators,including baseline National Institutes of Health stroke scale(NIHSS)score,age-adjusted Charlson comorbidity index(aCCI)score,neutrophil to lymphocyte ratio(NLR)and total CSVD burden score.Multivariate Logistic regression analysis showed that baseline NIHSS score,aCCI score,NLR and total CSVD burden score were independent risk factors for prolonged length of stay in ACI patients(P＜0.05).Based on the above four indicators,a nomogram model was constructed.The results showed that the ROC curve area of the model predicted prolonged length of stay between training group and validation group were 0.812(95％CI:0.756-0.868)and 0.820(95％CI:0.730-0.909).Conclusion The nomogram model for prolonged length of stay in ACI patients based on total CSVD burden score has good predictive performance and can be used as a screening tool for evaluating the prolonged length of stay in ACI patients.

Objective To meet the clinical need for dynamic monitoring on lactate metabolism in septic shock pa-tients,a time-series prediction model based on a long short-term memory(LSTM)network was developed to predict 24-hour lactate clearance rate at admission.Methods A multi-stage retrospective cohort design was adopted to en-roll septic shock patients admitted to the department of critical care medicine of a hospital from January 2018 to Sep-tember 2024.By conducting univariate analysis and LASSO combined feature screening,predictive factors were extracted from multidimensional clinical data.An end-to-end LSTM framework(two-layer 64/32 units,dropout rate=0.3)was constructed.A sliding window strategy(six-hour step size)was adopted for dynamic prediction and compared with traditional logistic model in terms of three dimensions:calibration(Brier score),discrimination(area under the curve[AUC]of time-dependent receiver operating characteristic[ROC]),and clinical practicality(deci-sion curve analysis).Consistency between model prediction result and actual lactate clearance rate was analyzed,and the accuracy of prediction was evaluated.Results A total of 112 septic shock patients were enrolled in the analysis,including 65 males and 47 females,with an average age of(67.35±7.28)years.65 patients were assigned in the lactate good clearance rate group(lactate good clearance rate≥10％)and 47 in the lactate poor clearance rate group(lactate good clearance rate＜10％);78 patients were in the training set and 34 in the validation set.Time-depen-dent AUC analysis revealed that the predictive performance of the LSTM model in the time windows of 6,12,and 24 hours were 0.89(0.85-0.93),0.91(0.88-0.95),and 0.92(0.89-0.96),respectively,superior to the logistic regression model(ΔAUC=0.085,P＜0.01).The core predictive factors included APACHE Ⅱ score(OR=1.38),lactate level at admission(OR=1.65),vasoactive drug dosage(OR=1.42),and 6-hour fluid resuscitation dosage(OR=1.35).The Pearson correlation coefficient between the predicted value of the model and the actual 24-hour lactate clearance rate was 0.83(P＜0.001),with an average absolute error of 8.2％.Decision curve analysis confirmed that when the threshold probability was 15％-60％,the LSTM model could increase clinical net benefits by 27.3％.The validation of each subgroup showed that the model maintained the optimal predictive performance(AUC=0.87)in the lung infection subgroup(n=16).Conclusion The LSTM-based dynamic prediction model for predicting 24-hour lactate clearance rate through integrating early admission indicators demonstrates excellent pre-dictive performance and clinical application value,which can provide important reference for individualized treatment decisions in septic shock patients.

Pain modulation encompasses a complex neurobiological process, in which the lateral habenula (LHb) plays a crucial role in integrating, regulating and modulating pain signals. It is also involved in pain-related memory functions associated with perception, transmission and regulation of pain. Furthermore, the LHb collaborates with structures such as the spinal dorsal horn, forebrain, and amygdala to form an essential neural circuit that contributes to sensitization, development of tolerance, and adaptation processes related to pain. However, there remains limited understanding regarding the specific roles and interactions among different neuron subtypes within the LHb concerning pain regulation. Additionally, further investigation is warranted to explore functional changes and plasticity within both the LHb and its associated neural circuits in chronic pain models. Future research endeavors should utilize advanced neuroimaging techniques alongside optogenetics and gene editing technologies to elucidate intricate neural circuits, cellular architecture, and molecular mechanisms governing LHb function in pain regulation. In conclusion, this paper aims to comprehensively review existing literature on the involvement of the LHb and its neural circuits in modulating pain, thereby enhancing our understanding of their neurobiological mechanisms while providing novel targets for precise therapeutic strategies aimed at alleviating pain.

Pain modulation encompasses a complex neurobiological process, in which the lateral habenula (LHb) plays a crucial role in integrating, regulating and modulating pain signals. It is also involved in pain-related memory functions associated with perception, transmission and regulation of pain. Furthermore, the LHb collaborates with structures such as the spinal dorsal horn, forebrain, and amygdala to form an essential neural circuit that contributes to sensitization, development of tolerance, and adaptation processes related to pain. However, there remains limited understanding regarding the specific roles and interactions among different neuron subtypes within the LHb concerning pain regulation. Additionally, further investigation is warranted to explore functional changes and plasticity within both the LHb and its associated neural circuits in chronic pain models. Future research endeavors should utilize advanced neuroimaging techniques alongside optogenetics and gene editing technologies to elucidate intricate neural circuits, cellular architecture, and molecular mechanisms governing LHb function in pain regulation. In conclusion, this paper aims to comprehensively review existing literature on the involvement of the LHb and its neural circuits in modulating pain, thereby enhancing our understanding of their neurobiological mechanisms while providing novel targets for precise therapeutic strategies aimed at alleviating pain.

Objective To construct a nomogram model for prolonged length of stay in patients with acute cerebral infarction(ACI)based on total cerebral small vessel disease(CSVD)burden scores,and validate its effectiveness.Methods A total of 462 ACI patients admitted to the Department of Neurology of South Taihu Hospital Affiliated To Huzhou College from January 2021 to December 2023 were selected as the study subjects.According to the ratio of 7:3,patients were divided into training group of 323 cases and validation group of 139 cases.Lasso-Logistic regression was used to analyze the risk factors for prolonged length of stay in ACI patients,construct a nomogram model and validate the model using validation data.Receiver operating characteristic(ROC)curve were used to evaluate the predictive performance of the model.Results Based on the training group data,Lasso regression screened four non-zero coefficient indicators,including baseline National Institutes of Health stroke scale(NIHSS)score,age-adjusted Charlson comorbidity index(aCCI)score,neutrophil to lymphocyte ratio(NLR)and total CSVD burden score.Multivariate Logistic regression analysis showed that baseline NIHSS score,aCCI score,NLR and total CSVD burden score were independent risk factors for prolonged length of stay in ACI patients(P＜0.05).Based on the above four indicators,a nomogram model was constructed.The results showed that the ROC curve area of the model predicted prolonged length of stay between training group and validation group were 0.812(95％CI:0.756-0.868)and 0.820(95％CI:0.730-0.909).Conclusion The nomogram model for prolonged length of stay in ACI patients based on total CSVD burden score has good predictive performance and can be used as a screening tool for evaluating the prolonged length of stay in ACI patients.

Objective To meet the clinical need for dynamic monitoring on lactate metabolism in septic shock pa-tients,a time-series prediction model based on a long short-term memory(LSTM)network was developed to predict 24-hour lactate clearance rate at admission.Methods A multi-stage retrospective cohort design was adopted to en-roll septic shock patients admitted to the department of critical care medicine of a hospital from January 2018 to Sep-tember 2024.By conducting univariate analysis and LASSO combined feature screening,predictive factors were extracted from multidimensional clinical data.An end-to-end LSTM framework(two-layer 64/32 units,dropout rate=0.3)was constructed.A sliding window strategy(six-hour step size)was adopted for dynamic prediction and compared with traditional logistic model in terms of three dimensions:calibration(Brier score),discrimination(area under the curve[AUC]of time-dependent receiver operating characteristic[ROC]),and clinical practicality(deci-sion curve analysis).Consistency between model prediction result and actual lactate clearance rate was analyzed,and the accuracy of prediction was evaluated.Results A total of 112 septic shock patients were enrolled in the analysis,including 65 males and 47 females,with an average age of(67.35±7.28)years.65 patients were assigned in the lactate good clearance rate group(lactate good clearance rate≥10％)and 47 in the lactate poor clearance rate group(lactate good clearance rate＜10％);78 patients were in the training set and 34 in the validation set.Time-depen-dent AUC analysis revealed that the predictive performance of the LSTM model in the time windows of 6,12,and 24 hours were 0.89(0.85-0.93),0.91(0.88-0.95),and 0.92(0.89-0.96),respectively,superior to the logistic regression model(ΔAUC=0.085,P＜0.01).The core predictive factors included APACHE Ⅱ score(OR=1.38),lactate level at admission(OR=1.65),vasoactive drug dosage(OR=1.42),and 6-hour fluid resuscitation dosage(OR=1.35).The Pearson correlation coefficient between the predicted value of the model and the actual 24-hour lactate clearance rate was 0.83(P＜0.001),with an average absolute error of 8.2％.Decision curve analysis confirmed that when the threshold probability was 15％-60％,the LSTM model could increase clinical net benefits by 27.3％.The validation of each subgroup showed that the model maintained the optimal predictive performance(AUC=0.87)in the lung infection subgroup(n=16).Conclusion The LSTM-based dynamic prediction model for predicting 24-hour lactate clearance rate through integrating early admission indicators demonstrates excellent pre-dictive performance and clinical application value,which can provide important reference for individualized treatment decisions in septic shock patients.

[Purpose]To analyze the results of upper gastrointestinal cancer screening in rural areas of Lhasa from 2015 to 2019.[Methods]Upper gastrointestinal cancer screening program was conducted among residents aged 40～69 years old from 3 rural project sites in Lhasa selected by cluster sampling method from 2015 to 2019.The detected malignant tumors and precancerous le-sions were treated and confirmed by pathological examination.The detection rate of esophagus and stomach cancer were calculated by region,sex and age and compared by x2 test.[Results]A total of 1 399 people underwent gastroscopy,among whom 1 288 completed pathological biopsy(92.07％).Three cases of esophageal cancer were detected with a detection rate of 0.21％(3/1 399),all of which were advanced squamous cell carcinoma.Eight cases of gastric cancer were detected with a detection rate of 0.57％(8/1 399),and 2 cases were early gastric cancer.The detection rate of low-grade and high-grade epithelial neoplasia of gastric mucosa was 0.64％(9/1 399)and 0.21％(3/1 399),respectively.There was no significant difference in the detection rate among different regions,sexes and age groups(all P＞0.05).[Conclusion]The detection rate of upper gastrointesti-nal cancer in screening population in Lhasa is lower than the national average level.Men and the elderly are important target populations for upper gastrointestinal cancer screening,and increasing participation rates is necessary for more effective screening outcomes.