Objective To introduce the modeling method of pendulum-like modified rat abdominal heart heterotopic transplantation model and evaluate the quality of the model. Methods An operator without transplantation experience performed 15 consecutive models, recorded the time of each step, changes in body weight and modified Stanford scores, and calculated the surgical success rate, postoperative 1-week survival rate and technical success rate. Ultrasound examinations was performed in 1 week postoperatively. Results The times for donor heart acquisition, donor heart processing, recipient preparation and transplantation anastomosis were (14.3±1.4) min, (3.5±0.6) min, (13.6±2.1) min and (38.3±5.2) min respectively. The surgical success rate was 87% (13/15), and the survival rate 1 week after operative was 100% (13/13). The improved Stanford score indicated a technical success rate of 92% (12/13), and the postoperative 1-week ultrasound examination showed that grafts with Stanford scores ≥3 had detectable pulsation and blood flow signals. Conclusions The pendulum-like modified rat abdominal heart heterotopic transplantation improved model further optimizes the operational steps with a high success rate and stable quality, may be chosen as a modeling option for basic research in heart transplantation in the future.

Lung transplantation is currently the only recognized effective treatment for end-stage lung disease and has improved the quality of life for patients. However, lung transplantation still faces many challenges, including rejection, infection, post-transplant acute kidney injury, post-transplant diabetes mellitus, ischemia-reperfusion injury and donor shortage, etc. Chinese lung transplantation scholars made a series of important progress in the field of clinical research in 2024, focusing on the study and solution of the above problems, and providing new ideas for lung transplantation surgery. This article systematically reviews the clinical research and technological innovation in the field of lung transplantation in 2024, summarizes the achievements of clinical research in the field of lung transplantation in China in 2024, and aims to providing new directions and strategies for future research.

Lung transplantation is the optimal treatment for end-stage lung diseases and can significantly improve prognosis of the patients. However, postoperative complications such as infection, rejection, ischemia-reperfusion injury, and other challenges (like shortage of donor lungs) , limit the practical application of lung transplantation in clinical practice. Chinese research teams have been making continuous efforts and have achieved breakthroughs in basic research on lung transplantation by integrating emerging technologies and cutting-edge achievements from interdisciplinary fields, which has strongly propelled the development of this field. This article will comprehensively review the academic progress made by Chinese research teams in the field of lung transplantation in 2024, with a focus on the achievements of Chinese teams in basic research on lung transplantation. It aims to provide innovative ideas and strategies for key issues in the basic field of lung transplantation and to help China's lung transplantation cause reach a higher level.

Gastric cancer is one of the major causes of cancer-related deaths worldwide, and infection with Helicobacter pylori and EBV, smoking and a salt-heavy diet have been shown to be risk factors for the development of gastric cancer. Currently, numerous research has demonstrated that differences in the structure of the gastric flora can be exploited to distinguish the different stages of gastric mucosal lesions and to predict the progression of gastric cancer. Therefore, a new biomarker is presented for the diagnosis of gastric cancer based on the structural differences of the gastric flora. Gastric flora has also potential in the treatment of gastric cancer. The application of non-H. pylori flora to modulate immune cells may increase the sensitivity of tumour cells for chemotherapy, improve the efficacy of immune checkpoint inhibitors and significantly prolong the survival of patients. This review of advances in the application of gastric flora in the diagnosis and treatment of gastric cancer is aimed at providing a reference and basis for future research in this field.

Gastric cancer is one of the major causes of cancer-related deaths worldwide, and infection with Helicobacter pylori and EBV, smoking and a salt-heavy diet have been shown to be risk factors for the development of gastric cancer. Currently, numerous research has demonstrated that differences in the structure of the gastric flora can be exploited to distinguish the different stages of gastric mucosal lesions and to predict the progression of gastric cancer. Therefore, a new biomarker is presented for the diagnosis of gastric cancer based on the structural differences of the gastric flora. Gastric flora has also potential in the treatment of gastric cancer. The application of non-H. pylori flora to modulate immune cells may increase the sensitivity of tumour cells for chemotherapy, improve the efficacy of immune checkpoint inhibitors and significantly prolong the survival of patients. This review of advances in the application of gastric flora in the diagnosis and treatment of gastric cancer is aimed at providing a reference and basis for future research in this field.

Gastric ulcer is a common digestive system disease,and the long-term use of non-steroidal anti-inflammatory drugs(NSAIDs)is the second most important cause.NSAID-induced gastric ulcer animal models are key experimental tools for studying the pathogenesis,corresponding treatment method,and effective mechanisms of NSAID-induced gastrointestinal injury.However,there are currently a lack of reviews on NSAID-induced gastric ulcer animal models.This review summarizes and compares the relevant literature on animal research into indomethacin-and aspirin-induced gastric ulcers in the past 10 years,including the selection of experimental animals,drug solvents,and specific modeling method.The limitations of current models,such as the cumbersome modeling method,incomplete modeling details,inadequate models for clinical use,and lack of comparative drug research,are discussed.Feasible solutions are proposed with the aim of providing an effective reference for research in this field.

A 13-year and 6-month-old girl attended the Hunan Children's Hospital due to delayed menarche. The laboratory test results indicated increased follicle-stimulating hormone and luteinizing hormone, decreased anti-Mullerian hormone, and pelvic ultrasound showed a cord-like uterus and absence of bilateral ovaries. Her 11-year and 5-month-old younger sister had the same laboratory and imaging findings, and both girls were diagnosed with primary ovarian insufficiency. Whole exome sequencing and Sanger sequencing confirmed that the proband and her sister carried heterozygous variants of HROB gene c.718C>T (p.Arg240*) and c.1351C>T (p.Arg451*), which were inherited from their parents respectively and consistent with autosomal recessive inheritance. Oral estradiol valerate at an initial dose of 0.125 mg/d was given to the proband, and the secondary sexual characteristics began to develop after 6 months.
Humans ; Female ; Child ; Infant ; Primary Ovarian Insufficiency/genetics* ; Luteinizing Hormone ; Estradiol

Objective:To evaluate the potential effects of serum lipid levels, appendicular skeletal muscle mass index (ASMI) and body mass index (BMI), together with its dynamic changes, on tumor progression in renal clear cell carcinoma patients, so as to inform body weight management.Methods:This prospective cohort study included a total of 100 patients with high-risk clear cell renal cell carcinoma. Serum lipid levels were detected, ASMI and BMI were measured using bioelectrical impedance analysis and the dynamic changes of BMI were tracked. The effects of BMI, ASMI and serum lipid levels on tumor progression within 2 years were explored.Results:Patients with normal BMI and low ASMI had 5.248 (95% CI: 1.946 to 14.153, P = 0.001) times higher risk of tumor progression than those who were overweight or obese. For every 0.1-unit increase in pre-operative HDL-C, the risk of tumor progression decreased by 0.771 (95% CI: 0.631 to 0.942, P = 0.011) times. Patients who experienced more than 5% decrease in BMI compared with baseline had 5.165 (95% CI: 1.735 to 15.370, P = 0.003) times the progression risk of patients whose BMI changed within ±5% from baseline. Conclusions:The advantage of obese clear cell carcinoma patients over normal-weight patients in tumor progression-free survival may be influenced by ASMI, pre-onset involuntary weight loss and lipid levels. Therefore, patient weight management should not merely focus on absolute BMI but tailor to individual characteristics, including cancer stage, body composition and metabolic status.

ObjectiveTo explore the mechanism of cucurbitacin B （CuB） in inhibiting cell proliferation and glycolysis. MethodCell counting kit-8 （CCK-8） was applied to investigate the effect of different concentrations of CuB （0， 40， 80， 120， 160， 200， 400， and 800 nmol·L^-1） on the proliferation of HuCCT1 cells. The effect of different concentrations of CuB （50， 100， and 200 nmol·L^-1） on the colony formation ability of HuCCT1 cells was detected by plate cloning assay. The effect of different concentrations of CuB （50， 100， 200 nmol·L^-1） on the HuCCT1 cell cycle was analyzed by flow cytometry. Visible spectrophotometry was employed to detect the activity of key glycolytic enzymes hexokinase （HK） and pyruvate kinase （PK）） and changes in glucose consumption， lactate production， and adenosine triphosphate （ATP） production in HuCCT1 cells after administration of different concentrations of CuB （50， 100， 200 nmol·L^-1）. Western blotting was used to assay the effect of CuB on the expression of cell cycle-related proteins， proliferation-related proteins， key glycolytic proteins， and Akt/mammalian target of rapamycin （mTOR） pathway-related proteins. ResultAs compared with the blank group， CuB at dose of 160-800 nmol·L^-1 after 24 h administration and CuB at dose of 80-800 nmol·L^-1 after 48 h administration inhibited the proliferation of HuCCT1 cells in a time- and dose-dependent manner （P<0.05， P<0.01）， and the median inhibitory concentration was 200 nmol·L^-1 48 h after administration. CuB can restrain the colony formation ability of HuCCT1 cells in a dose-dependent manner （P<0.01）， and block HuCCT1 cell cycle in G₂ phase （P<0.05， P<0.01）. CuB （100 and 200 nmol·L^-1） can suppress the activities of HK and PK and reduce cell glucose consumption and production of lactate and ATP （P<0.05， P<0.01）. Western blot results showed that CuB （100 and 200 nmol·L^-1） can inhibit the protein levels of cycle-related protein Cyclin B₁， proliferating cell nuclear antigen （PCNA）， HK1， HK2， PKM1， PKM2， phosphorylated Akt （p-Akt）， phosphorylated mTOR （p-mTOR）， and phosphorylated ribosomal protein S6 （p-RPS6） （P<0.05， P<0.01）. ConclusionCuB can inhibit aerobic glycolysis in HuCCT1 cells via the Akt/mTOR pathway， thereby affecting cell proliferation.

Early distinction of bipolar disorder (BD) from major depressive disorder (MDD) is difficult since no tools are available to estimate the risk of BD. In this study, we aimed to develop and validate a model of oxidative stress injury for predicting BD. Data were collected from 1252 BD and 1359 MDD patients, including 64 MDD patients identified as converting to BD from 2009 through 2018. 30 variables from a randomly-selected subsample of 1827 (70%) patients were used to develop the model, including age, sex, oxidative stress markers (uric acid, bilirubin, albumin, and prealbumin), sex hormones, cytokines, thyroid and liver function, and glycolipid metabolism. Univariate analyses and the Least Absolute Shrinkage and Selection Operator were applied for data dimension reduction and variable selection. Multivariable logistic regression was used to construct a model for predicting bipolar disorder by oxidative stress biomarkers (BIOS) on a nomogram. Internal validation was assessed in the remaining 784 patients (30%), and independent external validation was done with data from 3797 matched patients from five other hospitals in China. 10 predictors, mainly oxidative stress markers, were shown on the nomogram. The BIOS model showed good discrimination in the training sample, with an AUC of 75.1% (95% CI: 72.9%-77.3%), sensitivity of 0.66, and specificity of 0.73. The discrimination was good both in internal validation (AUC 72.1%, 68.6%-75.6%) and external validation (AUC 65.7%, 63.9%-67.5%). In this study, we developed a nomogram centered on oxidative stress injury, which could help in the individualized prediction of BD. For better real-world practice, a set of measurements, especially on oxidative stress markers, should be emphasized using big data in psychiatry.
Biomarkers/metabolism* ; Bipolar Disorder/metabolism* ; Depressive Disorder, Major/diagnosis* ; Early Diagnosis ; Humans ; Oxidative Stress