Human carboxylesterase 2A (hCES2A) plays pivotal roles in prodrug activation and hydrolytic metabolism of ester-bearing chemicals. Targeted inhibition of intestinal hCES2A represents a feasible strategy to mitigate irinotecan-triggered gut toxicity (ITGT), but the orally active, selective, and efficacious hCES2A inhibitors are rarely reported. Here, a novel drug-like hCES2A inhibitor was developed via three rounds of structure-based drug design (SBDD) and structural optimization. Initially, donepezil was identified as a moderate hCES2A inhibitor from 2000 US Food and Drug Administration (FDA)-approved drugs. Following two rounds of SBDD and structural optimization, a donepezil derivative (B7) was identified as a strong reversible hCES2A inhibitor. Subsequently, nine B7 carbamates were rationally designed, synthesized and biologically assayed. Among all synthesized carbamates, C3 showed the most potent time-dependent inhibition on hCES2A (IC₅₀ = 0.56 nmol/L), excellent specificity and favorable drug-like properties. C3 could covalently modify the catalytic serine of hCES2A with high selectivity, while this agent also showed favorable safety profiles, high intestinal exposure, and impressive effects for ameliorating ITGT in both human intestinal organoids and tumor-bearing mice. Collectively, this study showcases a rational strategy for developing drug-like and serine-targeting covalent inhibitors against target serine hydrolase(s), while C3 emerges as a promising orally active drug candidate for ameliorating ITGT.

Apoptotic bodies (ApoBDs) therapy is a novel and promising cell-free therapeutic strategy. However, the therapeutic mechanism and application of stem cells derived ApoBDs in tissue regeneration have not yet received adequate attention and research evidence. This review summarized the physiological and pathological effects, formation, release, enrichment and purification process of ApoBDs in detail. Furthermore, this review introduced the possible mechanism researches of stem cell-derived ApoBDs regulating regeneration of different organs and tissues, evaluated the possible strategies for their applications as drug delivery carrier, and prospected the development of the engineered modified ApoBDs in regenerative medicine.

Apoptotic bodies (ApoBDs) therapy is a novel and promising cell-free therapeutic strategy. However, the therapeutic mechanism and application of stem cells derived ApoBDs in tissue regeneration have not yet received adequate attention and research evidence. This review summarized the physiological and pathological effects, formation, release, enrichment and purification process of ApoBDs in detail. Furthermore, this review introduced the possible mechanism researches of stem cell-derived ApoBDs regulating regeneration of different organs and tissues, evaluated the possible strategies for their applications as drug delivery carrier, and prospected the development of the engineered modified ApoBDs in regenerative medicine.

Objective:To design an electronic nose that can detect and identify urinary volatile organic compounds (VOCs) as marker gases for bladder cancer.Methods:Isopropyl alcohol, ethylbenzene, acetic acid, and ammonia were selected as target gases, and 8 metal oxide gas sensors were used to construct sensor arrays for testing and collecting experimental data, and different characteristics were normalized. Recursive feature elimination (RFE) was used to select the best feature subset, and principal component analysis (PCA) and linear discriminant analysis (LDA) were further introduced to reduce the data dimension and facilitate visual analysis. In addition, three machine learning algorithms, including support vector machine (SVM), random forest (RF), and K-nearest neighbor (KNN), were combined to train and verify the model.Results:When the feature number was 12, the accuracy of the model classification had the best performance. The feature subset consisted of 5 differences, 5 sensitivities, and 2 integrals, and the data was reduced to 12 dimensions. Only PCA couldn’t distinguish the four gases. The LDA classification performance was significantly better than that of PCA, except that isopropyl alcohol and acetic acid had a small overlap area. LDA could distinguish ethylbenzene and ammonia from isopropyl alcohol and acetic acid; the sample points were gathered, which means the clustering performance was also better. The prediction accuracy of SVM, RF, and KNN was 0.85, 0.56, and 0.79, respectively. After model verification, the classification accuracy of PCA+SVM, LDA+RF, and LDA+KNN was 0.97, 0.94, and 0.97, respectively.Conclusions:An electronic nose was designed to detect and identify urinary VOCs marker gases for bladder cancer.

Objective:To automatically classify hypertensive heart disease (HHD) and hypertrophic cardiomyopathy (HCM) based on mul-titask learning algorithm using native T1 mapping images.Methods:A total of 203 patients admitted to Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University from January 2017 to December 2021 were enrolled, including 53 patients with HHD, 121 patients with HCM, and 29 patients with normal control (NC). Native T1 mapping images of all enrolled patients were acquired using MRI and processed by a multi-task learning algorithm. The classification performance of each model was validated using ten-fold crossover, confusion matrix, and receiver operator characteristic (ROC) curves. The Resnet 50 model based on the original images was established as a control.Results:The ten-fold crossover validation results showed that the MTL-1 024, MTL-64, and MTL-all models showed better performance in terms of area under the curve (AUC), accuracy, sensitivity, and specificity compared to the Resnet 50 model. In the classification task, the MTL-64 model showed the best performance in terms of AUC (0.942 1), while the MTL-all model reached the highest value in terms of accuracy (0.852 2). In the segmentation task, the MTL-64 model achieved the best results with the Dice coefficient (0.879 7). The confusion matrix plot showed that the MTL model outperforms the Resnet 50 model based on the original image in terms of overall performance. The ROC graphs of all MTL models were significantly higher than the original image input Resnet 50 model.Conclusions:Multi-task learning-based native T1 mapping images are effective for automatic classification of HHD and HCM.

Diabetes and its complications pose a serious threat to human life and health. It has become a public health problem of wide concern worldwide. Currently, diabetes is mainly treated with insulin injection in clinic. However, manual insulin injection still has many shortcomings. In recent years, with the deepening of research, it has been found that an automated insulin delivery system (AID), which combines a continuous glucose monitoring device with an insulin pump, can significantly improve the effectiveness of diabetes treatment and reduce the incidence of complications in patients. This paper firstly introduces the composition of the AID system and its working principle, and then details the development history and current status of the related technologies from the aspects of continuous glucose monitoring technology, insulin pumps and the development of closed-loop control algorithms, etc. Finally, this paper looks forward to the application prospect and future development of AID system in the field of diabetes treatment, providing theoretical reference for further research.
Humans ; Insulin Infusion Systems ; Insulin/administration & dosage* ; Blood Glucose Self-Monitoring/instrumentation* ; Diabetes Mellitus/drug therapy* ; Algorithms ; Hypoglycemic Agents/administration & dosage* ; Blood Glucose/analysis* ; Pancreas, Artificial ; Automation

Objective:To retrospectively identify the risk factors for postoperative nausea and vomiting (PONV)in the obese patients undergoing laparoscopic sleeve gastrectomy(LSG).Methods:The medical records from the obese patients who underwent elective laparoscopic sleeve gastrectomy from January 2018 to July 2022 were retrospectively collected. PONV was defined according to the use of remedial antiemetics in the nursing record sheet, and the patients were divided into PONV group and non-PONV group according to the occurrence of PONV that required treatment. The logistic regression analysis was used to identify the risk factors for PONV after LSG.Results:A total of 1 264 obese patients were included in this study, and there were 263 patients in PONV group, and the incidence of PONV was 20.81%. According to the results of multifactorial logistic regression analysis, female( OR=1.533, 95% CI 1.007-2.334, P=0.046), higher level of serum alanine aminotransferase concentrations ( OR=1.006, 95% CI 1.002-1.009, P=0.001), higher level of C-reactive protein ( OR=1.013, 95% CI 1.005-1.022, P=0.001), general anesthesia combined with nerve block (general anesthesia combined with TAPB: OR=2.737, 95% CI 1.817-4.121, P<0.001; general anesthesia combined with other nerve block: OR=1.899, 95% CI 1.249-2.889, P=0.003) and intraoperative use of sufentanil ( OR=2.114, 95% CI 1.308-3.415, P=0.002) were independent risk factors for PONV( P<0.05). However, the higher level of serum follicle-stimulating hormone concentrations ( OR=0.941, 95% CI 0.895-0.988, P=0.015), intraoperative use of dexmedetomidine ( OR=0.640, 95% CI 0.417-0.982, P=0.041), and administration of prophylactic antiemetic medication (antiemetic drugs during operation OR=0.669, 95% CI 0.469-0.955, P=0.027; antiemetic drugs after operation OR=0.303, 95% CI 0.182-0.503, P<0.001; antiemetic drugs during and after operation OR=0.215, 95% CI 0.107-0.434, P<0.001) were protective factors for PONV. Conclusions:Female, higher levels of serum alanine aminotransferase and C-reactive protein, general anesthesia combined with nerve block and intraoperative use of sufentanil are independent risk factors for PONV, while higher levels of follicle-stimulating hormone, intraoperative use of dexmedetomidine and administration of prophylactic antiemetic medication are protective factors for PONV among obese patients undergoing LSG.

Objective: To investigate craniofacial differences in individuals with hypodontia and explore the relationship between craniofacial features and the number of congenitally missing teeth. Methods: A cross-sectional study was conducted among 261 Chinese patients (males, 124; females, 137; age, 7–24 years), divided into four groups (without hypodontia: no teeth missing, mild: one or two missing teeth, moderate: three to five missing teeth, severe: six or more missing teeth) according to the number of congenitally missing teeth. Differences in cephalometric measurements among the groups were analyzed. Further, multivariate linear regression and smooth curve fitting were performed to evaluate the relationship between the number of congenitally missing teeth and the cephalometric measurements. Results: In patients with hypodontia, SNA, NA-AP, FH-NA, ANB, Wits, ANS-Me/N-Me, GoGn-SN, UL-EP, and LL-EP significantly decreased, while Pog-NB, AB-NP, N-ANS, and S-Go/N-Me significantly increased. In multivariate linear regression analysis, SNB, Pog-NB, and S-Go/N-Me were positively related to the number of congenitally missing teeth. In contrast, NA-AP, FH-NA, ANB, Wits, N-Me, ANS-Me, ANS-Me/N-Me, GoGn-SN, SGn-FH (Y-axis), UL-EP, and LL-EP were negatively related, with absolute values of regression coefficients ranging from 0.147 to 0.357. Further, NA-AP, Pog-NB, S-Go/N-Me, and GoGn-SN showed the same tendency in both sexes, whereas UL-EP and LL-EP were different. Conclusions Compared with controls, patients with hypodontia tend toward a Class III skeletal relationship, reduced lower anterior face height, flatter mandibular plane, and more retrusive lips. The number of congenitally missing teeth had a greater effect on certain characteristics of craniofacial morphology in males than in females.

The latest epidemiological data suggests that the situation of adult diabetes in China is severe, and metabolic diseases have become significant chronic illnesses that have a serious impact on public health and social development. After more than six years of practice, the National Metabolic Management Center(MMC) has developed distinctive approaches to manage metabolic patients and has achieved a series of positive outcomes, continuously advancing the standardized diagnosis and treatment model. In order to further improve the efficiency, based on the first edition, the second edition guideline was composed by incorporating experience of the past six years in conjunction with the latest international and domestic guidelines.

With the further increase of the global cancer burden, various cancers are increasingly challenging human health status and quality of life. Thus, early screening of cancer is crucial. Urinary volatile organic compounds (VOCs) detection techniques have the advantages of easy access to samples, high acceptance of patients, non-invasive, and so on, which have been favored and concerned by researchers. In this paper, existing techniques and methods for cancer diagnosis based on urine VOCs were described, relevant studies on the use of urine VOCs for cancer diagnosis were reviewed, and the barriers and future perspectives of the technique were discussed. This paper can be a reference for researchers working in the direction of urinary VOCs detection, a multidisciplinary field that spans medicine and materials science.