Cryo-EM Structure of the Human Cannabinoid Receptor CB2-Gi Signaling Complex.

Drugs selectively targeting CB2 hold promise for treating neurodegenerative disorders, inflammation, and pain while avoiding psychotropic side effects mediated by CB1. The mechanisms underlying CB2 activation and signaling are poorly understood but critical for drug design. Here we report the cryo-EM structure of the human CB2-Gi signaling complex bound to the agonist WIN 55,212-2. The 3D structure reveals the binding mode of WIN 55,212-2 and structural determinants for distinguishing CB2 agonists from antagonists, which are supported by a pair of rationally designed agonist and antagonist. Further structural analyses with computational docking results uncover the differences between CB2 and CB1 in receptor activation, ligand recognition, and Gi coupling. These findings are expected to facilitate rational structure-based discovery of drugs targeting the cannabinoid system.

Differential performance of RoseTTAFold in antibody modeling.

Antibodies are essential to life, and knowing their structures can facilitate the understanding of antibody-antigen recognition mechanisms. Precise antibody structure prediction has been a core challenge for a prolonged period, especially the accuracy of H3 loop prediction. Despite recent progress, existing methods cannot achieve atomic accuracy, especially when the homologous structures required for these methods are not available. Recently, RoseTTAFold, a deep learning-based algorithm, has shown remarkable breakthroughs in predicting the 3D structures of proteins. To assess the antibody modeling ability of RoseTTAFold, we first retrieved the sequences of 30 antibodies as the test set and used RoseTTAFold to model their 3D structures. We then compared the models constructed by RoseTTAFold with those of SWISS-MODEL in a different way, in which we stratified Global Model Quality Estimate (GMQE) into three different ranges. The results indicated that RoseTTAFold could achieve results similar to SWISS-MODEL in modeling most CDR loops, especially the templates with a GMQE score under 0.8. In addition, we also compared the structures modeled by RoseTTAFold, SWISS-MODEL and ABodyBuilder. In brief, RoseTTAFold could accurately predict 3D structures of antibodies, but its accuracy was not as good as the other two methods. However, RoseTTAFold exhibited better accuracy for modeling H3 loop than ABodyBuilder and was comparable to SWISS-MODEL. Finally, we discussed the limitations and potential improvements of the current RoseTTAFold, which may help to further the accuracy of RoseTTAFold's antibody modeling.

Faecalibacterium prausnitzii as a potential Antiatherosclerotic microbe.

BACKGROUND: The gut microbiota plays a crucial role in coronary artery disease (CAD) development, but limited attention has been given to the role of the microbiota in preventing this disease. This study aimed to identify key biomarkers using metagenomics and untargeted metabolomics and verify their associations with atherosclerosis. METHODS: A total of 371 participants, including individuals with various CAD types and CAD-free controls, were enrolled. Subsequently, significant markers were identified in the stool samples through gut metagenomic sequencing and untargeted metabolomics. In vivo and in vitro experiments were performed to investigate the mechanisms underlying the association between these markers and atherosclerosis. RESULTS: Faecal omics sequencing revealed that individuals with a substantial presence of Faecalibacterium prausnitzii had the lowest incidence of CAD across diverse CAD groups and control subjects. A random forest model confirmed the significant relationship between F. prausnitzii and CAD incidence. Notably, F. prausnitzii emerged as a robust, independent CAD predictor. Furthermore, our findings indicated the potential of the gut microbiota and gut metabolites to predict CAD occurrence and progression, potentially impacting amino acid and vitamin metabolism. F. prausnitzii mitigated inflammation and exhibited an antiatherosclerotic effect on ApoE-/- mice after gavage. This effect was attributed to reduced intestinal LPS synthesis and reinforced mechanical and mucosal barriers, leading to decreased plasma LPS levels and an antiatherosclerotic outcome. CONCLUSIONS: Sequencing of the samples revealed a previously unknown link between specific gut microbiota and atherosclerosis. Treatment with F. prausnitzii may help prevent CAD by inhibiting atherosclerosis.

Identification of a novel signature based on M6a modification regulators related LncRNA for stratification of the prognosis of prostate cancer.

Prostate cancer emerges as a life-threatening disease that affects approximately 1.3 million patients of male population globally. Various studies established lncRNAs as a critical role in prostate cancer progression by regulating multiple epigenetic pathways. Therefore, it is imperative to disclose the involvement of lncRNAs in prostate cancer and their usability as prognostic markers for the disease. The model was constructed using Cox and LASSO analysis. The accuracy of model was evaluated using various cohorts. Furthermore, the study assessed the correlative relationship of the model with tumor immunity, immunotherapy, SNV mutation, and drug sensitivity, among other factors. We developed an accurate and stable prognostic model for prostate cancer patients by screening out 11 m6A regulators related lncRNAs and integrating pathological features and age through a nomogram model. The model had satisfactory accuracy and stability in stratification of clinical outcomes of prostate cancer patients, as demonstrated by AUC values (higher than 0.7) at 3, 5, and 7 years in both internal and external cohorts. Moreover, we performed PCA analysis to confirm m6A-related lncRNAs as the best modeling strategy. We developed a prognosis predicting model based on 11 selected m6A modification related lncRNA, which displayed satisfactory potency in multiple cohorts.

MCCS, a novel characterization method for protein-ligand complex.

Delineating the fingerprint or feature vector of a receptor/protein will facilitate the structural and biological studies, as well as the rational design and development of drugs with high affinities and selectivity. However, protein is complicated by its different functional regions that can bind to some of its protein partner(s), substrate(s), orthosteric ligand(s) or allosteric modulator(s) where cogent methods like molecular fingerprints do not work well. We here elaborate a scoring-function-based computing protocol Molecular Complex Characterizing System to help characterize the binding feature of protein-ligand complexes. Based on the reported receptor-ligand interactions, we first quantitate the energy contribution of each individual residue which may be an alternative of MD-based energy decomposition. We then construct a vector for the energy contribution to represent the pattern of the ligand recognition at a receptor and qualitatively analyze the matching level with other receptors. Finally, the energy contribution vector is explored for extensive use in similarity and clustering. The present work provides a new approach to cluster proteins, a perspective counterpart for determining the protein characteristics in the binding, and an advanced screening technique where molecular docking is applicable.

Virus-CKB: an integrated bioinformatics platform and analysis resource for COVID-19 research.

Given the scale and rapid spread of the coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), there is an urgent need for medicines that can help before vaccines are available. In this study, we present a viral-associated disease-specific chemogenomics knowledgebase (Virus-CKB) and apply our computational systems pharmacology-target mapping to rapidly predict the FDA-approved drugs which can quickly progress into clinical trials to meet the urgent demand of the COVID-19 outbreak. Virus-CKB reuses the underlying platform of our DAKB-GPCRs but adds new features like multiple-compound support, multi-cavity protein support and customizable symbol display. Our one-stop computing platform describes the chemical molecules, genes and proteins involved in viral-associated diseases regulation. To date, Virus-CKB archived 65 antiviral drugs in the market, 107 viral-related targets with 189 available 3D crystal or cryo-EM structures and 2698 chemical agents reported for these target proteins. Moreover, Virus-CKB is implemented with web applications for the prediction of the relevant protein targets and analysis and visualization of the outputs, including HTDocking, TargetHunter, BBB predictor, NGL Viewer, Spider Plot, etc. The Virus-CKB server is accessible at https://www.cbligand.org/g/virus-ckb.

IsAb: a computational protocol for antibody design.

The design of therapeutic antibodies has attracted a large amount of attention over the years. Antibodies are widely used to treat many diseases due to their high efficiency and low risk of adverse events. However, the experimental methods of antibody design are time-consuming and expensive. Although computational antibody design techniques have had significant advances in the past years, there are still some challenges that need to be solved, such as the flexibility of antigen structure, the lack of antibody structural data and the absence of standard antibody design protocol. In the present work, we elaborated on an in silico antibody design protocol for users to easily perform computer-aided antibody design. First, the Rosetta web server will be applied to generate the 3D structure of query antibodies if there is no structural information available. Then, two-step docking will be used to identify the binding pose of an antibody-antigen complex when the binding information is unknown. ClusPro is the first method to be used to conduct the global docking, and SnugDock is applied for the local docking. Sequentially, based on the predicted binding poses, in silico alanine scanning will be used to predict the potential hotspots (or key residues). Finally, computational affinity maturation protocol will be used to modify the structure of antibodies to theoretically increase their affinity and stability, which will be further validated by the bioassays in the future. As a proof of concept, we redesigned antibody D44.1 and compared it with previously reported data in order to validate IsAb protocol. To further illustrate our proposed protocol, we used cemiplimab antibody, a PD-1 checkpoint inhibitor, as an example to showcase a step-by-step tutorial.

MCCS: a novel recognition pattern-based method for fast track discovery of anti-SARS-CoV-2 drugs.

Given the scale and rapid spread of the coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, or 2019-nCoV), there is an urgent need to identify therapeutics that are effective against COVID-19 before vaccines are available. Since the current rate of SARS-CoV-2 knowledge acquisition via traditional research methods is not sufficient to match the rapid spread of the virus, novel strategies of drug discovery for SARS-CoV-2 infection are required. Structure-based virtual screening for example relies primarily on docking scores and does not take the importance of key residues into consideration, which may lead to a significantly higher incidence rate of false-positive results. Our novel in silico approach, which overcomes these limitations, can be utilized to quickly evaluate FDA-approved drugs for repurposing and combination, as well as designing new chemical agents with therapeutic potential for COVID-19. As a result, anti-HIV or antiviral drugs (lopinavir, tenofovir disoproxil, fosamprenavir and ganciclovir), antiflu drugs (peramivir and zanamivir) and an anti-HCV drug (sofosbuvir) are predicted to bind to 3CLPro in SARS-CoV-2 with therapeutic potential for COVID-19 infection by our new protocol. In addition, we also propose three antidiabetic drugs (acarbose, glyburide and tolazamide) for the potential treatment of COVID-19. Finally, we apply our new virus chemogenomics knowledgebase platform with the integrated machine-learning computing algorithms to identify the potential drug combinations (e.g. remdesivir+chloroquine), which are congruent with ongoing clinical trials. In addition, another 10 compounds from CAS COVID-19 antiviral candidate compounds dataset are also suggested by Molecular Complex Characterizing System with potential treatment for COVID-19. Our work provides a novel strategy for the repurposing and combinations of drugs in the market and for prediction of chemical candidates with anti-COVID-19 potential.

Mutated CYP17A1 promotes atherosclerosis and early-onset coronary artery disease.

BACKGROUND: Coronary artery disease (CAD) is a multi-factor complex trait and is heritable, especially in early-onset families. However, the genetic factors affecting the susceptibility of early-onset CAD are not fully characterized. METHODS: In the present study, we identified a rare nonsense variant in the CYP17A1 gene from a Chinese Han family with CAD. To validate the effect of this variation on atherosclerosis and early-onset coronary artery disease, we conducted studies on population, cells, and mice. RESULTS: The mutation precisely congregated with the clinical syndrome in all the affected family members and was absent in unaffected family members and unrelated controls. Similar to the human phenotype, the CYP17A1-deficient mice present the phenotype of metabolic syndrome with hypertension, increased serum glucose concentration, and presentation of central obesity and fatty liver. Furthermore, CYP17A1 knockout mice or CYP17A1 + ApoE double knockout mice developed more atherosclerotic lesions than wild type (WT) with high fat diary. In cell models, CYP17A1 was found to be involved in glucose metabolism by increasing glucose intake and utilization, through activating IGF1/mTOR/HIF1-α signaling way, which was consistent in CYP17A1 knockout mice with impaired glucose tolerance and insulin resistance. CONCLUSIONS: Through our study of cells, mice and humans, we identified CYP17A1 as a key protein participating in the pathophysiology of the atherosclerotic process and the possible mechanism of CYP17A1 C987X mutation induced atherosclerosis and early-onset CAD involving glucose homeostasis regulation was revealed. Video Abstract.

PI3K/AKT pathway promotes keloid fibroblasts proliferation by enhancing glycolysis under hypoxia.

Our previous study demonstrated altered glucose metabolism and enhanced phosphorylation of the PI3K/AKT pathway in keloid fibroblasts (KFb) under hypoxic conditions. However, whether the PI3K/AKT pathway influences KFb cell function by regulating glucose metabolism under hypoxic conditions remains unclear. Here, we show that when PI3K/AKT pathway was inactivated with LY294002, the protein expression of glycolytic enzymes decreased, while the amount of mitochondria and mitochondrial membrane potential increased. The key parameters of extracellular acidification rate markedly diminished, and those of oxygen consumption rate significantly increased after inhibition of the PI3K/AKT pathway. When the PI3K/AKT pathway was suppressed, the levels of reactive oxygen species (ROS) and mitochondrial ROS (mitoROS) were significantly increased. Meanwhile, cell proliferation, migration and invasion were inhibited, and apoptosis was increased when the PI3K/AKT pathway was blocked. Additionally, cell proliferation was compromised when KFb were treated with both SC79 (an activator of the PI3K/AKT pathway) and 2-deoxy-d-glucose (an inhibitor of glycolysis), compared with the SC79 group. Moreover, a positive feedback mechanism was demonstrated between the PI3K/AKT pathway and hypoxia-inducible factor-1α (HIF-1α). Our data collectively demonstrated that the PI3K/AKT pathway promotes proliferation and inhibits apoptosis in KFb under hypoxia by regulating glycolysis, indicating that the PI3K/AKT signalling pathway could be a therapeutic target for keloids.

Combination regimens containing daratumumab for initial diagnosed acquired thrombotic thrombocytopenic purpura.

Thrombotic thrombocytopenic purpura (TTP) is a rare and life-threatening thrombotic microangiopathy characterized by microangiopathic hemolytic anemia, severe thrombocytopenia, and organ ischemia associated with disseminated microvascular platelet-rich thrombus. Before the introduction of plasma therapy, acute TTP was almost universally fatal, which improved survival from < 10 to 80-90%. However, patients who survived an acute attack were at high risk for recurrence and long-term morbidity. It was reported that daratumumab can eradicate persistent ADAMTS13-inhibiting autoantibodies and restore ADAMTS13 activity in two patients with relapsed immune-mediated TTP without associated adverse drug reactions. Here we report a case series of patients with initial diagnosed acquired TTP treated with combination regimens containing daratumumab. All the patients achieved clinical response after the initial treatment. Three patients achieved clinical remission, one patient relapsed and one patient suffered an exacerbation during follow-up. The two patients were retreated with glucocorticoids, plasma exchange combined with daratumumab, and clinical remission was achieved again. Combination of daratumumab in the treatment of initial diagnosed acquired thrombotic thrombocytopenic purpura can rapidly restore ADAMST13 activity and turn negative for ADAMST13 inhibitors, resulting in long-term remission in patients.

Age and outcomes following personalized antiplatelet therapy in chronic coronary syndrome patients: a post hoc analysis of the randomized PATH-PCI trial.

It is particularly important to establish more effective and safer antiplatelet treatment strategies according to age. The present subanalysis of the PATH-PCI trial was to determine the safety and efficacy of any dual-antiplatelet therapy (DAPT) strategy in different age groups. We randomized 2285 chronic coronary syndrome (CCS) patients undergoing percutaneous coronary intervention (PCI) into a standard group or a personalized group from December 2016 to February 2018. The personalized group received personalized antiplatelet therapy (PAT) based on a novel platelet function test (PFT). The standard group received standard antiplatelet therapy (SAT). Then, all patients were divided according to age (under the age of 65 years and aged 65 years or over) to investigate the association and interaction of age on clinical outcomes at 180 days. In the patients under the age of 65 years, the incidence of NACEs was decreased in the personalized group compared to the standard group (5.1% vs. 8.8%, HR: 0.603, 95% CI: 0.409-0.888, P = .010). The rates of MACCEs (3.3% vs. 7.7%, HR: 0.450, 95% CI: 0.285-0.712, P = .001), MACEs (2.2% vs. 5.4%, HR: 0.423, 95% CI: 0.243-0.738, P = .002) also decreased. We did not find a significant difference in bleeding between the groups. In the patients aged 65 years or over, no difference in the primary endpoint was found (4.9% vs. 4.2%, P = .702), and comparable rates of survival were observed with the two strategies (all Ps > 0.05). The present study shows that PAT according to PFT was comparable to SAT at the 180-day follow-up for both ischemic and bleeding endpoints in CCS patients aged 65 years or over who underwent PCI. In patients under the age of 65 years, PAT can reduce ischemic events but does not increase bleeding, and it is an effective and safe treatment strategy. It may be necessary for young CCS patients after PCI to undergo PAT early after PCI.

What is the context? The PATH-PCI trial reported that personalized antiplatelet therapy (PAT) based on a novel platelet function test (PFT) can greatly reduce the incidence of ischemic events.Antiplatelet strategies may have very different effects on clinical outcomes in patients in China who are undergoing PCI at different ages.What is new? PL-12 is a new point-of-care platelet function analyzer that is used to test the platelet maximum aggregation rate (MAR).We explored the efficacy and safety of different antiplatelet strategies in chronic coronary syndrome (CCS) patients in different age groups.What is the impact? PAT according to PFT was comparable to standard antiplatelet therapy (SAT) at the 180-day follow-up for both ischemic and bleeding endpoints in CCS patients aged 65 years or over who underwent PCI.In patients under the age of 65 years, PAT can reduce ischemic events but not increase bleeding.PAT may be an effective and safe treatment strategy in CCS patients under the age of 65 years who underwent PCI.Abbreviation: PCI: percutaneous coronary intervention; CCS: chronic coronary syndrome; DAPT: dual antiplatelet therapy; PAT: personalized antiplatelet therapy; SAT: standard antiplatelet therapy; PFT: platelet function test; NACEs: net adverse clinical events; MACCEs: major adverse cardiac and cerebrovascular events; MACEs: major adverse cardiovascular events.

Epidemic trends of dyslipidemia in young adults: a real-world study including more than 20,000 samples.

BACKGROUND: There is an urgent need to learn more about the epidemiological features of dyslipidemia in youth to address the high burden of cardiovascular disease. METHODS: This experiment was an observational, cross-sectional study. The samples were collected from 22,379 college students at Xinjiang Medical University. RESULT: The overall prevalence of dyslipidemia was 13.17%, which was significantly higher in men (23%) than in women (7.2%), p < 0.01. Similarly, the prevalence rate of obesity in men (11.4%) was significantly higher than that in women (3.4%). The composition of blood lipids, such as triglyceride (TG), total cholesterol (TC), and low density lipoprotein cholesterol (LDL-C), began to increase gradually from the age of 22 and showed a sharp increase after the age of 30; however, a reverse trend was present in high density lipoprotein cholesterol (HDL-C). In terms of the proportion of dyslipidemia in both men and women, low HDL-C accounted for the largest proportion (74%), followed by elevated TGs (14.5%). The overall distribution of rates of dyslipidemia and excess weight showed a U-shaped trend with increasing age, with the lowest rates seen in the 20-24 age group. CONCLUSION: Our study sheds light on the epidemiological features of dyslipidemia in young adults and enriches the limited data available on dyslipidemia, providing a reference for the close monitoring and control of risk factors to reduce the occurrence and progression of atherosclerotic cardiovascular disease events.

Effects of Percutaneous Coronary Intervention and Coronary Artery Bypass Grafting on Clinical Outcomes in Patients with Reduced Ejection Fraction Heart Failure and Coronary Heart Disease: A Meta-Analysis.

OBJECTIVE: To clarify the effects of percutaneous coronary intervention (PCI) and coronary artery bypass grafting (CABG) on the clinical outcomes of patients with coronary heart disease (CHD) complicated with reduced ejection fraction heart failure (HFrEF) through meta-analysis. METHODS: Three major literature databases - PubMed, Web of Science, and Cochrane - were searched by search terms and the literature retrieval time was publications dating from January 2007 to December 2021. To search for observational studies and randomized controlled trials (RCT) comparing the efficacy of PCI and CABG in patients with CHD and HFrEF, the abstract or full text of the literature was read and the final included literature was determined, according to inclusion and exclusion criteria. The quality of the included literature was evaluated using the Ottawa scale and data extraction was further completed. Data analysis was made using RevMan5.4 and R4.1 software; relevant forest plots and funnel plots were made, according to the extracted data. Egger's test was used to evaluate whether the data had publication bias. Outcomes were the major adverse cardiovascular events (MACE). RESULTS: A total of 10 studies were included and 11,032 subjects were included, made up of 5,521 cases of PCI and 5,511 cases of CABG. The results showed no significant difference between the two groups in cardiac mortality (CM) (RR=1.13, 95% CI 0.98-1.30, P = 0.10) and in overall all-cause mortality (ACM) (RR=1.12, 95% CI 0.92-1.37, P = 0.25). In the subgroup analysis of ACM, in the subgroups with left ventricular ejection fraction (LVEF) less than 35% and exceeding 35% and less than 50% (RR=1.12, 95% CI 0.92-1.37, P = 0.25) between the two groups, there was no statistical difference. However, among other MACE, compared with the PCI group, the CABG group had a lower risk of MACE (RR=1.58, 95%CI 1.49-1.70, P < 0.00001), myocardial infarction (MI) (RR=1.99, 95% CI 1.02-3.88, P = 0.04), heart failure (HF) (RR=1.29, 95% CI 1.17-1.43, P < 0.00001) and revascularization (RR=2.74, 95% CI 1.93-3.90, P < 0.00001). Finally in the CABG group, the risk of stroke or transient ischemic attack (TIA) was higher (RR=0.71, 95% CI 0.58-0.86, P = 0.0006) than the PCI group. CONCLUSIONS: The mortality rates of PCI and CABG were similar in patients with CHD complicated with HFrEF. Compared with PCI, CABG had a lower incidence of MACE, MI, HF, and revascularization, and a higher incidence of stroke or TIA.

Multi-Lane Differential Variable Speed Limit Control via Deep Neural Networks Optimized by an Adaptive Evolutionary Strategy.

In advanced transportation-management systems, variable speed limits are a crucial application. Deep reinforcement learning methods have been shown to have superior performance in many applications, as they are an effective approach to learning environment dynamics for decision-making and control. However, they face two significant difficulties in traffic-control applications: reward engineering with delayed reward and brittle convergence properties with gradient descent. To address these challenges, evolutionary strategies are well suited as a class of black-box optimization techniques inspired by natural evolution. Additionally, the traditional deep reinforcement learning framework struggles to handle the delayed reward setting. This paper proposes a novel approach using covariance matrix adaptation evolution strategy (CMA-ES), a gradient-free global optimization method, to handle the task of multi-lane differential variable speed limit control. The proposed method uses a deep-learning-based method to dynamically learn optimal and distinct speed limits among lanes. The parameters of the neural network are sampled using a multivariate normal distribution, and the dependencies between the variables are represented by a covariance matrix that is optimized dynamically by CMA-ES based on the freeway's throughput. The proposed approach is tested on a freeway with simulated recurrent bottlenecks, and the experimental results show that it outperforms deep reinforcement learning-based approaches, traditional evolutionary search methods, and the no-control scenario. Our proposed method demonstrates a 23% improvement in average travel time and an average of a 4% improvement in CO, HC, and NOx emission.Furthermore, the proposed method produces explainable speed limits and has desirable generalization power.

[Evaluation of the lower urinary tract function using voiding spot assay in mice].

The objective of present study was to develop a simple and reliable voiding spot assay (VSA) system to evaluate the lower urinary tract function of mice, and to establish it as a standardized protocol. Ultraviolet (UV) light was used to screen out the filter paper without autofluorescence and with optimal urine diffusion properties. Next, the appropriate wavelength of UV was determined based on the quality of the photographic image of urine spots on the filter paper. To confirm that the urine stain area on the filter paper was correlated with the amount of urine, a volume-area standard curve was constructed. The utility of this VSA system was validated using female wild-type C57BL/6J mice aged 12-13 weeks, and the data generated under identical procedural settings were compared among laboratories. Furthermore, this VSA system was employed to analyze the changes in voiding patterns in mice with urinary tract infections or transportation stress. No. 4 filter paper with a thickness of 0.7 mm was identified as the most suitable material for VSA, exhibiting no autofluorescence and facilitating optimal urine diffusion. The filter paper retained its integrity during the assay, and there was a linear correlation between urine volume and stained area under 365 nm UV light. Utilizing this VSA system, we determined that female wild-type C57BL/6J mice produced approximately 695.8 µL total urine and 5.5 primary voiding spots (PVS) with an average size of 126.4 µL/spot within 4-h period. Over 84% of PVS volumes ranged from 20 to 200 µL. Notably, PVS volumes of mice were similar across different laboratories. Mice with urinary tract infections or transportation stress exhibited significant changes in VSA parameters, including increased voiding frequency, PVS number, and decreased PVS volume. Therefore, this VSA system can be used to evaluate the urinary function of normal mice, as well as those with urinary tract infection or transportation stress.

Discovery of a pyrano[2,3-b]pyridine derivative YX-2102 as a cannabinoid receptor 2 agonist for alleviating lung fibrosis.

BACKGROUND: Pharmacological modulation of cannabinoid 2 receptor (CB2R) is a promising therapeutic strategy for pulmonary fibrosis (PF). Thus, to develop CB2R selective ligands with new chemical space has attracted much research interests. This work aims to discover a novel CB2R agonist from an in-house library, and to evaluate its therapeutic effects on PF model, as well as to disclose the pharmacological mechanism. METHODS: Virtual screening was used to identify the candidate ligand for CB2R from a newly established in-house library. Both in vivo experiments on PF rat model and in vitro experiments on cells were performed to investigate the therapeutic effects of the lead compound and underlying mechanism. RESULTS: A "natural product-like" pyrano[2,3-b]pyridine derivative, YX-2102 was identified that bound to CB2R with high affinity. Intraperitoneal YX-2102 injections significantly ameliorated lung injury, inflammation and fibrosis in a rat model of PF induced by bleomycin (BLM). On one hand, YX-2102 inhibited inflammatory response at least partially through modulating macrophages polarization thereby exerting protective effects. Whereas, on the other hand, YX-2102 significantly upregulated CB2R expression in alveolar epithelial cells in vivo. Its pretreatment inhibited lung alveolar epithelial-to-mesenchymal transition (EMT) in vitro and PF model induced by transforming growth factor beta-1 (TGF-ß1) via a CB2 receptor-dependent pathway. Further studies suggested that the Nrf2-Smad7 pathway might be involved in. CONCLUSION: These findings suggest that CB2R is a potential target for PF treatment and YX-2102 is a promising CB2R agonist with new chemical space.

Molecular mechanisms of voiding dysfunction in a novel mouse model of acute urinary retention.

Acute urinary retention (AUR) is a common urological emergency and affects a significant patient population. The inability to eliminate urine may lead to permanent damage to the bladder's structure and functioning. However, we know little about the underlying molecular sequelae to the urine retention. To closely mirror the potential high pressures that patients with AUR could experience, we catheterized anesthetized female mice via the urethra and filled the bladder by pumping saline (25 µL/min) into the bladder lumen to 50 cm or 80 cm water pressure. A water column with designated height (50 or 80 cm) was then adjusted to maintain constant pressure in the bladder lumen for 30 minutes. Functional and morphological evaluations were performed from 0 to 24 hours after AUR treatment. Mice exhibited incontinence and overactivity with diminished voiding pressure. Significant injury was confirmed which revealed bladders with disrupted urothelial barrier, edematous lamina propria, and distorted muscle bundles. Bladder smooth muscle (BSM) from pressure-treated mice have significantly diminished contraction force, suggesting that bladder voiding dysfunction can be attributed to impaired BSM contractility. Indeed, dysregulation of acetylcholine and purinergic signaling pathways were demonstrated, indicating that reduced efficacy of these pathways contributes to impaired BSM contractility. Finally, altered expression of ß1-integrin and extracellular matrix mediated mechanotransduction pathways were detected, suggesting a profound remodeling process. These data demonstrated an easy to perform, quantifiable, and reproducible AUR mouse model, which mimics well the characteristics of human AUR patients, and our data generate new insights into the molecular mechanisms that occur following AUR.

Molecular pathways underlying tissue injuries in the bladder with ketamine cystitis.

Ketamine cystitis (KC) is a chronic bladder inflammation leading to urinary urgency, frequency, and pain. The pathogenesis of KC is complicated and involves multiple tissue injuries in the bladder. Recent studies indicated that urothelium disruption, lamina propria fibrosis and inflammation, microvascular injury, neuropathological alterations, and bladder smooth muscle (BSM) abnormalities all contribute to the pathogenesis of KC. Ketamine has been shown to induce these tissue injuries by regulating different signaling pathways. Ketamine can stimulate antiproliferative factor, adenosine triphosphate, and oxidative stress to disrupt urothelium. Lamina propria fibrosis and inflammation are associated with the activation of cyclooxygenase-2, nitric oxide synthase, immunoglobulin E, and transforming growth factor ß1. Ketamine contributes to microvascular injury via the N-methyl-D aspartic receptor (NMDAR), and multiple inflammatory and angiogenic factors such as tumor necrosis factor α and vascular endothelial growth factor. For BSM abnormalities, ketamine can depress the protein kinase B, extracellular signal-regulated kinase, Cav1.2, and muscarinic receptor signaling. Elevated purinergic signaling also plays a role in BSM abnormalities. In addition, ketamine affects neuropathological alterations in the bladder by regulating NMDAR- and brain-derived neurotrophic factor-dependent signaling. Inflammatory cells also contribute to neuropathological changes via the secretion of chemical mediators. Clarifying the role and function of these signaling underlying tissue injuries in the bladder with KC can contribute to a better understanding of the pathophysiology of this disease and to the design of effective treatments for KC.

In Silico Prediction and Validation of CB2 Allosteric Binding Sites to Aid the Design of Allosteric Modulators.

Although the 3D structures of active and inactive cannabinoid receptors type 2 (CB2) are available, neither the X-ray crystal nor the cryo-EM structure of CB2-orthosteric ligand-modulator has been resolved, prohibiting the drug discovery and development of CB2 allosteric modulators (AMs). In the present work, we mainly focused on investigating the potential allosteric binding site(s) of CB2. We applied different algorithms or tools to predict the potential allosteric binding sites of CB2 with the existing agonists. Seven potential allosteric sites can be observed for either CB2-CP55940 or CB2-WIN 55,212-2 complex, among which sites B, C, G and K are supported by the reported 3D structures of Class A GPCRs coupled with AMs. Applying our novel algorithm toolset-MCCS, we docked three known AMs of CB2 including Ec2la (C-2), trans-ß-caryophyllene (TBC) and cannabidiol (CBD) to each site for further comparisons and quantified the potential binding residues in each allosteric binding site. Sequentially, we selected the most promising binding pose of C-2 in five allosteric sites to conduct the molecular dynamics (MD) simulations. Based on the results of docking studies and MD simulations, we suggest that site H is the most promising allosteric binding site. We plan to conduct bio-assay validations in the future.