Accurate prediction of drug-induced adverse drug reactions (ADRs) is crucial for drug safety evaluation, as it directly impacts public health and safety. While various models have shown promising results in predicting ADRs, their accuracy still needs improvement. Additionally, many existing models often lack interpretability when linking molecular structures to specific ADRs and frequently rely on manually selected molecular fingerprints, which can introduce bias. To address these challenges, we propose ToxBERT, an efficient transformer encoder model that leverages attention and masking mechanisms for simplified molecular input line entry system (SMILES) representations. Our results demonstrate that ToxBERT achieved area under the receiver operating characteristic curve (AUROC) scores of 0.839, 0.759, and 0.664 for predicting drug-induced QT prolongation (DIQT), rhabdomyolysis, and liver injury, respectively, outperforming previous studies. Furthermore, ToxBERT can identify drug substructures that are closely associated with specific ADRs. These findings indicate that ToxBERT is not only a valuable tool for understanding the mechanisms underlying specific drug-induced ADRs but also for mitigating potential ADRs in the drug discovery pipeline.

L-citrulline is a nonprotein amino acid that plays an important role in human health and has great market demand. Although microbial cell factories have been widely used for biosynthesis, there are still challenges such as genetic instability and low efficiency in the biosynthesis of L-citrulline. In this study, an efficient, plasmid-free, non-inducible L-citrulline-producing strain of Escherichia coli BL21(DE3) was engineered by combined strategies. Firstly, a chassis strain capable of synthesizing L-citrulline was constructed by block of L-citrulline degradation and removal of feedback inhibition, with the L-citrulline titer of 0.43 g/L. Secondly, a push-pull-restrain strategy was employed to enhance the L-citrulline biosynthesis, which realized the L-citrulline titer of 6.0 g/L. Thirdly, the NADPH synthesis and L-citrulline transport were strengthened to promote the synthesis efficiency, which achieved the L-citrulline titer of 11.6 g/L. Finally, fed-batch fermentation was performed with the engineered strain in a 3 L fermenter, in which the L-citrulline titer reached 44.9 g/L. This study lays the foundation for the industrial production of L-citrulline and provides insights for the modification of other amino acid metabolic networks.
Citrulline/biosynthesis* ; Escherichia coli/genetics* ; Metabolic Engineering/methods* ; Fermentation ; NADP/biosynthesis*

The gut microbiota is a complex ecosystem composed of many bacteria and their metabolites.It plays an irreplaceable role in human digestion,nutrient absorption,energy supply,fat metabolism,im-mune regulation,and many other aspects.Exploring the structure and function of the gut microbiota,as well as their key genes and metabolites,will enable the early diagnosis and auxiliary diagnosis of disea-ses,new treatment methods,better effects of drug treatments,and better guidance in the use of antibiot-ics.The identification of gut microbiota plays an important role in clinical diagnosis and treatment,as well as in drug research and development.Therefore,it is necessary to conduct a comprehensive review of this rapidly evolving topic.Traditional identification methods cannot comprehensively capture the di-versity of gut microbiota.Currently,with the rapid development of molecular biology,the classification and identification methods for gut microbiota have evolved from the initial phenotypic and chemical identi-fication to identification at the molecular level.This review integrates the main methods of gut microbiota identification and evaluates their application.We pay special attention to the research progress on molec-ular biological methods and focus on the application of high-throughput sequencing technology in the iden-tification of gut microbiota.This revolutionary method for intestinal flora identification heralds a new chapter in our understanding of the microbial world.

Mulberry (Morus alba L.) leaf is a well-established traditional Chinese botanical and culinary resource. It has found widespread application in the management of diabetes. The bioactive constituents of mulberry leaf, specifically mulberry leaf flavonoids (MLFs), exhibit pronounced potential in the amelioration of type 2 diabetes (T2D). This potential is attributed to their ability to safeguard pancreatic β cells, enhance insulin resistance, and inhibit α-glucosidase activity. Our antecedent research findings underscore the substantial therapeutic efficacy of MLFs in treating T2D. However, the precise mechanistic underpinnings of MLF's anti-T2D effects remain the subject of inquiry. Activation of brown/beige adipocytes is a novel and promising strategy for T2D treatment. In the present study, our primary objective was to elucidate the impact of MLFs on adipose tissue browning in db/db mice and 3T3-L1 cells and elucidate its underlying mechanism. The results manifested that MLFs reduced body weight and food intake, alleviated hepatic steatosis, improved insulin sensitivity, and increased lipolysis and thermogenesis in db/db mice. Moreover, MLFs activated brown adipose tissue (BAT) and induced the browning of inguinal white adipose tissue (IWAT) and 3T3-L1 adipocytes by increasing the expressions of brown adipocyte marker genes and proteins such as uncoupling protein 1 (UCP1) and beige adipocyte marker genes such as transmembrane protein 26 (Tmem26), thereby promoting mitochondrial biogenesis. Mechanistically, MLFs facilitated the activation of BAT and the induction of WAT browning to ameliorate T2D primarily through the activation of AMP-activated protein kinase (AMPK)/sirtuin 1 (SIRT1)/peroxisome proliferator-activated receptor-gamma coactivator 1α (PGC-1α) signaling pathway. These findings highlight the unique capacity of MLF to counteract T2D by enhancing BAT activation and inducing browning of IWAT, thereby ameliorating glucose and lipid metabolism disorders. As such, MLFs emerge as a prospective and innovative browning agent for the treatment of T2D.
Mice ; Animals ; Adipose Tissue, Brown ; Sirtuin 1/pharmacology* ; Diabetes Mellitus, Type 2/metabolism* ; AMP-Activated Protein Kinases/metabolism* ; Morus/metabolism* ; Flavonoids/metabolism* ; Prospective Studies ; Signal Transduction ; Adipose Tissue, White ; Plant Leaves ; Uncoupling Protein 1/metabolism* ; Peroxisome Proliferator-Activated Receptor Gamma Coactivator 1-alpha/metabolism*

OBJECTIVE: To predict the learning curve of tooth preparation for all ceramic crowns of maxillary central incisors on phantom head simulators for graduate students participating in standardized dental resident training based on the modified Wright learning curve model, then to analyze and applicate the learning curve. METHODS: Twelve graduate students participating in standardized dental resident training were selected to prepare the resin maxillary central incisors on phantom head simulators for all ceramic crowns 4 times. The results of preparation were evaluated by 3 prosthetic experts with at least 10 years' experience focusing on the reduction, contour, taper, shoulder, finish line, margin placement, adjacent tooth injury, and preparation time for tooth preparation. The learning rate of tooth preparation was calculated by scores of tooth preparation of 4 times. The learning curve of tooth preparation was predicted based on the modified Wright learning curve model. According to the criteria of standardized training skill examinations for dental residents in Beijing, 80 was taken as the qualified standard score. The minimum training times for tooth preparation to satisfy the qualified standard score (80) was calculated, to analyze the characteristics of learning curve and evaluate the effectiveness of tooth preparation. RESULTS: The scores of 4 tooth preparation were 64.03±7.80, 71.40±6.13, 74.33±5.96, and 75.98±4.52, respectively. The learning rate was (106±4)%, which showed the learning curve an upward trend. There were no significant differences between the qualified standard score and the predicted scores of tooth preparation from the 5^th preparation to the 13^th preparation (P > 0.05). The predicted score of the 14^th preparation was higher than the qualified standard score (P < 0.05). CONCLUSION The trend of the learning curve of tooth preparation for all ceramic crowns of maxillary central incisors on phantom head simulators for graduate students participating in standardized dental resident training is upward, which predicts the minimum training times higher than the qualified standard score is 14 times.
Humans ; Tooth Preparation, Prosthodontic/methods* ; Incisor ; Learning Curve ; Crowns ; Tooth Preparation ; Ceramics ; Dental Porcelain ; Dental Prosthesis Design

Objective:To evaluate the predictive value of age-adjusted Charlson comorbidity index (ACCI) for in-hospital mortality and 1-year mortality in patients with acute type A aortic dissection (ATAAD).Methods:This was a retrospective cohort study, and the clinical data of ATAAD patients admitted to Wuhan Union Hospital from January 1, 1999 to December 31, 2018 were collected for analysis. All the patients were confirmed by computed tomography angiography or magnetic resonance imaging of the aorta and the onset time was less than 14 days. Patients who survived at discharge were followed up to obtain 1-year survival information. The ACCI score was calculated for patients based on their comorbidities and age at admission, and they were divided into three groups of 0, 1 and ≥2 according to the ACCI score. The in-hospital mortality and 1-year mortality of the three groups were compared. Logistic regression analysis was applied to determine the independent predictors for in-hospital mortality and 1-year mortality.Results:Among 1 133 ATAAD patients, 383, 357 and 393 patients had ACCI score of 0, 1, and ≥2, respectively. The in-hospital mortality and 1-year mortality of patients with ACCI score ≥2 were significantly higher than those of patients with ACCI score of 0 (25.4% vs. 17.0%, 30.0% vs. 19.6%, both P<0.05). Multivariate Logistic regression analysis showed that ACCI score ≥2 was an independent risk factor for in-hospital mortality ( OR=1.670, 95% CI: 1.176-2.370, P=0.004) and 1-year mortality ( OR=1.762, 95% CI: 1.264-2.456, P<0.001). Age (per 10-year increase) and cerebrovascular diseases were independent risk factors for in-hospital mortality and 1-year mortality, while diabetes mellitus was a protective factor for in-hospital mortality. Conclusions:ACCI can predict the in-hospital mortality and 1-year mortality of ATAAD patients, and patients with ACCI score ≥2 have a poorer prognosis.

Animal survival necessitates adaptive behaviors in volatile environmental contexts. Virtual reality (VR) technology is instrumental to study the neural mechanisms underlying behaviors modulated by environmental context by simulating the real world with maximized control of contextual elements. Yet current VR tools for rodents have limited flexibility and performance (e.g., frame rate) for context-dependent cognitive research. Here, we describe a high-performance VR platform with which to study contextual behaviors immersed in editable virtual contexts. This platform was assembled from modular hardware and custom-written software with flexibility and upgradability. Using this platform, we trained mice to perform context-dependent cognitive tasks with rules ranging from discrimination to delayed-sample-to-match while recording from thousands of hippocampal place cells. By precise manipulations of context elements, we found that the context recognition was intact with partial context elements, but impaired by exchanges of context elements. Collectively, our work establishes a configurable VR platform with which to investigate context-dependent cognition with large-scale neural recording.
Animals ; Mice ; Rodentia ; Virtual Reality ; Cognition ; Recognition, Psychology

Humans ; Esophageal Squamous Cell Carcinoma ; Esophageal Neoplasms/pathology* ; Carcinoma, Squamous Cell ; Microbiota

OBJECTIVE: To systematically evaluate the efficacy of Shengmai San in patients with cardiotoxicity of anthracyclines. METHODS: Randomized controlled trials (RCTs) were identified by searching China National Knowledge Infrastructure (CNKI), Wanfang Database, Chinese Biomedical Literature Database (CBM), PubMed, Cochrane Library, and Embase Databases from the inceptions until December 2020. The Cochrane Handbook was used to evaluate the risk of bias in the included studies. Data analysis was conducted using RevMan 5.3 software. RESULTS: Totally 19 RCTs with 2,331 participants were included in this review. Results showed that in improving arrhythmia (13 RCTs, n=1,877, RR=0.37, 95%CI 0.25 to 0.52, P<0.00001), the treatment group was superior to the control group. In terms of reducing left ventricular end-diastolic diameter (LVEDD, 2 RCTs, n=128, MD=-0.79, 95%CI -0.93 to -0.65, P<0.00001) and left ventricular end systolic diameter (LVESD, 2 RCTs, n=128, MD=-0.58, 95%CI -0.82 to -0.35, P<0.00001), the treatment group was also better than the control group. In reducing myocardial enzymes such as creatine kinase (CK) [(3 RCTs, n=256, SMD=-0.80, 95%CI -1.16 to -0.44, P<0.0001), (2 RCTs, n=126, SMD=-0.62, 95%CI -0.98 to -0.26, P=0.0007)], the treatment group was superior to the control group. CONCLUSION Shengmai San has a positive effect on the treatment of cardiotoxicity from anthracyclines. However, in the future, it is still necessary to conduct high-quality RCTs to verify its efficacy.
Anthracyclines/adverse effects* ; Cardiotoxicity/etiology* ; Drug Combinations ; Drugs, Chinese Herbal/adverse effects* ; Humans