Tethered peptide activation mechanism of the adhesion GPCRs ADGRG2 and ADGRG4.

Adhesion G protein-coupled receptors (aGPCRs) constitute an evolutionarily ancient family of receptors that often undergo autoproteolysis to produce α and ß subunits1-3. A tethered agonism mediated by the 'Stachel sequence' of the ß subunit has been proposed to have central roles in aGPCR activation4-6. Here we present three cryo-electron microscopy structures of aGPCRs coupled to the Gs heterotrimer. Two of these aGPCRs are activated by tethered Stachel sequences-the ADGRG2-ß-Gs complex and the ADGRG4-ß-Gs complex (in which ß indicates the ß subunit of the aGPCR)-and the other is the full-length ADGRG2 in complex with the exogenous ADGRG2 Stachel-sequence-derived peptide agonist IP15 (ADGRG2(FL)-IP15-Gs). The Stachel sequences of both ADGRG2-ß and ADGRG4-ß assume a U shape and insert deeply into the seven-transmembrane bundles. Constituting the FXφφφXφ motif (in which φ represents a hydrophobic residue), five residues of ADGRG2-ß or ADGRG4-ß extend like fingers to mediate binding to the seven-transmembrane domain and activation of the receptor. The structure of the ADGRG2(FL)-IP15-Gs complex reveals the structural basis for the improved binding affinity of IP15 compared with VPM-p15 and indicates that rational design of peptidic agonists could be achieved by exploiting aGPCR-ß structures. By converting the 'finger residues' to acidic residues, we develop a method to generate peptidic antagonists towards several aGPCRs. Collectively, our study provides structural and biochemical insights into the tethered activation mechanism of aGPCRs.

Membrane protein isolation and structure determination in cell-derived membrane vesicles.

Integral membrane protein structure determination traditionally requires extraction from cell membranes using detergents or polymers. Here, we describe the isolation and structure determination of proteins in membrane vesicles derived directly from cells. Structures of the ion channel Slo1 from total cell membranes and from cell plasma membranes were determined at 3.8 Å and 2.7 Å resolution, respectively. The plasma membrane environment stabilizes Slo1, revealing an alteration of global helical packing, polar lipid, and cholesterol interactions that stabilize previously unresolved regions of the channel and an additional ion binding site in the Ca2+ regulatory domain. The two methods presented enable structural analysis of both internal and plasma membrane proteins without disrupting weakly interacting proteins, lipids, and cofactors that are essential to biological function.

Correlation between structure and function in phosphatidylinositol lipid-dependent Kir2.2 gating.

SignificancePhosphatidylinositol 4,5-bisphosphate (PI(4,5)P2) levels regulate cell membrane voltage by gluing two halves of a K+ channel together and opening the pore. PI(4)P competes with this process. Because both of these lipids are relatively abundant in the plasma membrane and are directly interconvertible through the action of specific enzymes, they may function together to regulate channel activity.

Establishing an Ion-Sieving Separator by Depositing Oxygen-Deficient SiOx Layer for Stabilized Zinc Metal Anode.

Stable plating/stripping of Zn metal anode remains a great challenge owing to uncontrollable dendrite growth and side reactions. Ion-sieving separators is a unique and promising solution, that possess Zn2+ permeability and promote Zn2+ transport, can effectively alleviate the abovementioned problems. Ion-sieving on glass fiber separator by deposition of oxygen-deficient SiOx layer via active screen plasma technology is achieved. While having chemical composition similar to the glass fiber, the SiOx nanoparticles contain oxygen-rich vacancies that promoted dissociation of the adsorbed water and generation of the hydroxyl groups. The negatively-charged hydroxylated SiOx layer can repel SO4 2- and attract Zn2+, which can alleviate the side reactions. The strong interplay between hydroxyl groups and Zn2+ can boost Zn affinity and yield fast Zn2+ transport. Consequently, the SiOx-deposited GF separator enabled dendrite-free Zn deposition morphology, which displays lower overpotential of 18 mV and longer cycling life over 2000 h for Zn symmetric cell. Such a separator can also be easily scaled up to prepare the high-performance large-area (4 × 6 cm2) pouch Zn-based devices, showing remarkable flexibility and practicality.

Screening for functional circular RNAs using the CRISPR-Cas13 system.

Circular RNAs (circRNAs) produced from back-spliced exons are widely expressed, but individual circRNA functions remain poorly understood owing to the lack of adequate methods for distinguishing circRNAs from cognate messenger RNAs with overlapping exons. Here, we report that CRISPR-RfxCas13d can effectively discriminate circRNAs from mRNAs by using guide RNAs targeting sequences spanning back-splicing junction (BSJ) sites featured in RNA circles. Using a lentiviral library that targets sequences across BSJ sites of highly expressed human circRNAs, we show that a group of circRNAs are important for cell growth mostly in a cell-type-specific manner and that a common oncogenic circRNA, circFAM120A, promotes cell proliferation by preventing the mRNA for family with sequence similarity 120A (FAM120A) from binding the translation inhibitor IGF2BP2. Further application of RfxCas13d-BSJ-gRNA screening has uncovered circMan1a2, which has regulatory potential in mouse embryo preimplantation development. Together, these results establish CRISPR-RfxCas13d as a useful tool for the discovery and functional study of circRNAs at both individual and large-scale levels.

Multistep validation of a post-ERCP pancreatitis prediction system integrating multimodal data: a multicenter study.

BACKGROUND AND AIMS: The impact of various categories of information on the prediction of post-ERCP pancreatitis (PEP) remains uncertain. We comprehensively investigated the risk factors associated with PEP by constructing and validating a model incorporating multimodal data through multiple steps. METHODS: Cases (n = 1916) of ERCP were retrospectively collected from multiple centers for model construction. Through literature research, 49 electronic health record (EHR) features and 1 image feature related to PEP were identified. The EHR features were categorized into baseline, diagnosis, technique, and prevention strategies, covering pre-ERCP, intra-ERCP, and peri-ERCP phases. We first incrementally constructed models 1 to 4 incorporating these 4 feature categories and then added the image feature into models 1 to 4 and developed models 5 to 8. All models underwent testing and comparison using both internal and external test sets. Once the optimal model was selected, we conducted comparisons among multiple machine learning algorithms. RESULTS: Compared with model 2 that incorporated baseline and diagnosis features, adding technique and prevention strategies (model 4) greatly improved the sensitivity (63.89% vs 83.33%, P < .05) and specificity (75.00% vs 85.92%, P < .001). A similar tendency was observed in the internal and external tests. In model 4, the top 3 features ranked by weight were previous pancreatitis, nonsteroidal anti-inflammatory drug use, and difficult cannulation. The image-based feature has the highest weight in models 5 to 8. Finally, model 8 used a random forest algorithm and showed the best performance. CONCLUSIONS: We first developed a multimodal prediction model for identifying PEP with a clinical-acceptable performance. The image and technique features are crucial for PEP prediction.

A newly developed deep learning-based system for automatic detection and classification of small bowel lesions during double-balloon enteroscopy examination.

BACKGROUND: Double-balloon enteroscopy (DBE) is a standard method for diagnosing and treating small bowel disease. However, DBE may yield false-negative results due to oversight or inexperience. We aim to develop a computer-aided diagnostic (CAD) system for the automatic detection and classification of small bowel abnormalities in DBE. DESIGN AND METHODS: A total of 5201 images were collected from Renmin Hospital of Wuhan University to construct a detection model for localizing lesions during DBE, and 3021 images were collected to construct a classification model for classifying lesions into four classes, protruding lesion, diverticulum, erosion & ulcer and angioectasia. The performance of the two models was evaluated using 1318 normal images and 915 abnormal images and 65 videos from independent patients and then compared with that of 8 endoscopists. The standard answer was the expert consensus. RESULTS: For the image test set, the detection model achieved a sensitivity of 92% (843/915) and an area under the curve (AUC) of 0.947, and the classification model achieved an accuracy of 86%. For the video test set, the accuracy of the system was significantly better than that of the endoscopists (85% vs. 77 ± 6%, p < 0.01). For the video test set, the proposed system was superior to novices and comparable to experts. CONCLUSIONS: We established a real-time CAD system for detecting and classifying small bowel lesions in DBE with favourable performance. ENDOANGEL-DBE has the potential to help endoscopists, especially novices, in clinical practice and may reduce the miss rate of small bowel lesions.

Epidemiological characteristics of human rabies cases reported by sites in China from 2006 to 2022.

BACKGROUND: Rabies is an incessant public health threat in China. The Ministry of Health implemented the Central Payment for Rabies Prevention and Control Project to assist with rabies prevention and control in a few representative provinces in 2006. METHODS: Data on human rabies cases reported by the National Infectious Disease Reporting Information Management System and national surveillance sites from 2006 to 2022 were collected, and statistical and multivariate analyses were then used to assess the effectiveness of current prevention and control efforts. RESULTS: During 2006-2022, a total of 2025 human rabies cases were collected by the national surveillance sites, with incidence rates far above the national average, but the incidence rate was consistent with the national trend. Human rabies cases demonstrated a dual peak distribution in terms of exposure and onset dates, with the peak exposure dates falling mostly in the spring and summer and the peak onset dates occurring mostly in the summer and autumn. Three danger categories are shown by the geographical distribution: high, medium and low. Dogs had a high infection rate (86.93%), with own domesticated dogs accounting for the majority of infections. The rates of post-exposure prophylaxis are not constant. The median incubation period was 71 days. CONCLUSIONS: Various measures and policies implemented by the government have played a key role in reducing the incidence of rabies. To effectively prevent and control the resurgence of epidemics and halt the spread of the virus among host animals, it is imperative to prioritize and implement a robust dog management system, accelerate research and development of animal vaccines and improve the level of post-exposure prophylaxis.

The effect of incorporating domain knowledge with deep learning in identifying benign and malignant gastric whitish lesions: A retrospective study.

BACKGROUND AND AIM: Early whitish gastric neoplasms can be easily misdiagnosed; differential diagnosis of gastric whitish lesions remains a challenge. We aim to build a deep learning (DL) model to diagnose whitish gastric neoplasms and explore the effect of adding domain knowledge in model construction. METHODS: We collected 4558 images from two institutions to train and test models. We first developed two sole DL models (1 and 2) using supervised and semi-supervised algorithms. Then we selected diagnosis-related features through literature research and developed feature-extraction models to determine features including boundary, surface, roundness, depression, and location. Then predictions of the five feature-extraction models and sole DL model were combined and inputted into seven machine-learning (ML) based fitting-diagnosis models. The optimal model was selected as ENDOANGEL-WD (whitish-diagnosis) and compared with endoscopists. RESULTS: Sole DL 2 had higher sensitivity (83.12% vs 68.67%, Bonferroni adjusted P = 0.024) than sole DL 1. Adding domain knowledge, the decision tree performed best among the seven ML models, achieving higher specificity than DL 1 (84.38% vs 72.27%, Bonferroni adjusted P < 0.05) and higher accuracy than DL 2 (80.47%, Bonferroni adjusted P < 0.001) and was selected as ENDOANGEL-WD. ENDOANGEL-WD showed better accuracy compared with 10 endoscopists (75.70%, P < 0.001). CONCLUSIONS: We developed a novel system ENDOANGEL-WD combining domain knowledge and traditional DL to detect gastric whitish neoplasms. Adding domain knowledge improved the performance of traditional DL, which provided a novel solution for establishing diagnostic models for other rare diseases potentially.

Discovery of Sesquiterpene Lactones with Cytotoxicity from the Herb of Youngia japonica.

In the process of searching for anti-breast cancer agents, five sesquiterpene lactones (1-5), including two previously undescribed ones, yjaponica B-C (1-2), were isolated from the herb of Youngia japonica. Their structures were elucidated by spectroscopic data analyses and Marfey's method. Cytotoxic activities of all compounds against A549, U87, and 4T1 cell lines were tested using the CCK8 assay. The result showed that compound 3 possessed the highest cytotoxic activity against 4T1 cells with an IC50 value of 10.60 µM. Furthermore, compound 3 distinctly induced apoptosis, inhibited immigration, and blocked the cell cycle of 4T1 cells. In addition, compound 3 induced the production of reactive oxygen species. Further anticancer mechanism studies showed that compound 3 significantly upregulated expression of the cleaved caspase 3 and PARP, whereas it downregulated the expression of Bcl-2, cyclin D1, cyclin A2, CDK4, and CDK2. Taken together, our results demonstrate that compound 3 has a high potential of being used as a leading compound for the discovery of new anti-breast cancer agent.