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.

AI-based IsAb2.0 for antibody design.

Therapeutic antibody design has garnered widespread attention, highlighting its interdisciplinary importance. Advancements in technology emphasize the critical role of designing nanobodies and humanized antibodies in antibody engineering. However, current experimental methods are costly and time-consuming. Computational approaches, while progressing, faced limitations due to insufficient structural data and the absence of a standardized protocol. To tackle these challenges, our lab previously developed IsAb1.0, an in silico antibody design protocol. Yet, IsAb1.0 lacked accuracy, had a complex procedure, and required extensive antibody bioinformation. Moreover, it overlooked nanobody and humanized antibody design, hindering therapeutic antibody development. Building upon IsAb1.0, we enhanced our design protocol with artificial intelligence methods to create IsAb2.0. IsAb2.0 utilized AlphaFold-Multimer (2.3/3.0) for accurate modeling and complex construction without templates and employed the precise FlexddG method for in silico antibody optimization. Validated through optimization of a humanized nanobody J3 (HuJ3) targeting HIV-1 gp120, IsAb2.0 predicted five mutations that can improve HuJ3-gp120 binding affinity. These predictions were confirmed by commercial software and validated through binding and neutralization assays. IsAb2.0 streamlined antibody design, offering insights into future techniques to accelerate immunotherapy development.

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.

Serum 5'-Nucleotidase as a Novel Predictor of Adverse Clinical Outcomes after Percutaneous Coronary Intervention in Patients with Coronary Artery Disease.

Background: The correlation between 5 ' -Nucleotidase ( 5 ' -NT) and the clinical outcomes in coronary artery disease (CAD) patients following percutaneous coronary intervention (PCI) is not clear. This study aims to clarify this relationship. Methods: The PRACTICE study enrolled 15,250 patients between December 2016 and October 2021. After filtering out those without 5 ' -NT data, a total of 6555 patients were analyzed with a median follow-up of 24 months. Based on the receiver operating characteristic (ROC) curve analysis, a 5 ' -NT level of 5.57 U/L was selected as the optimal cutoff value. All research samples were divided into high-value ( ≥ 5.57 U/L, n = 2346) and low-value groups ( < 5.57 U/L, n = 4209). Key clinical outcomes included all-cause death (ACD), cardiovascular death (CD), major adverse cardiovascular events (MACE), and major adverse cardiovascular and cerebrovascular events (MACCE). After separating patients into high and low value groups, multivariate Cox regression analysis was used to correct for potential confounding variables. Finally, risk ratios and their 95% confidence intervals (CIs) were calculated. Results: During the follow-up period, 129 instances of ACD were recorded-49 cases (1.2%) in the low-value group and 80 cases (3.4%) in the high-value group. Similarly, 102 CDs occurred, including 42 low-value group cases (1.0%) and 60 high-value group cases (2.6%). A total of 363 MACE occurred, including 198 low-value group cases (4.7%) and 165 high-value group cases (7%). A total of 397 cases of MACCE occurred, including 227 low-value group cases (5.4%) and 170 high-value group cases (7.2%). As serum 5 ' -NT increased, the incidence of ACD, CD, MACE and MACCE increased. After multivariate Cox regression, high 5 ' -NT levels were linked with a 1.63-fold increase in ACD risk (hazard ratio [HR] = 2.630, 95% CI: [1.770-3.908], p < 0.001) when compared to low 5 ' -NT patients. Similarly, the risk of CD, MACE, and MACCE increased by 1.298-fold (HR = 2.298, 95% CI: [1.477-3.573], p < 0.001), 41% (HR = 1.410, 95% CI: [1.124-1.768], p = 0.003) and 30.5% (HR = 1.305, 95% CI: [1.049-1.623], p = 0.017), respectively. Conclusions: high serum 5 ' -NT levels were independently correlated with adverse clinical outcomes in CAD patients following PCI, affirming its potential as a prognostic indicator.

Association between the C-Reactive Protein-Albumin-Lymphocyte (CALLY) Index and Adverse Clinical Outcomes in CAD Patients after PCI: Findings of a Real-World Study.

Background: The C-reactive protein-albumin-lymphocyte (CALLY) index is a novel inflammatory biomarker, and its association with the prognosis of coronary artery disease (CAD) after percutaneous coronary intervention (PCI) has not previously been studied. Therefore, this study aimed to investigate the effect of using the CALLY index on adverse outcomes in CAD patients undergoing PCI. Methods: From December 2016 to October 2021, we consecutively enrolled 15,250 CAD patients and performed follow-ups for primary endpoints consisting of all-cause mortality (ACM) and cardiac mortality (CM). The CALLY index was computed using the following formula: (albumin × lymphocyte)/(C-reactive protein (CRP) × 10 4 ). The average duration of the follow-up was 24 months. Results: A total of 3799 CAD patients who had undergone PCI were ultimately enrolled in the present study. The patients were divided into four groups according to the CALLY index quartiles: Q1 ( ≤ 0.69, n = 950), Q2 (0.69-2.44, n = 950), Q3 (2.44-9.52, n = 950), and Q4 ( > 9.52, n = 949). The low-Q1 group had a significantly higher prevalence of ACM (p < 0.001), CM (p < 0.001), major adverse cardiac events (MACEs) (p = 0.002), and major adverse cardiac and cerebrovascular events (MACCEs) (p = 0.002). Kaplan-Meier analysis revealed that a low CALLY index was significantly linked with adverse outcomes. After univariate and multivariate Cox regression analysis, the risk of ACM, CM, MACEs, and MACCEs decreased by 73.7% (adjust hazard risk [HR] = 0.263, 95% CI: 0.147-0.468, p < 0.001), 70.6% (adjust HR = 0.294, 95% CI: 0.150-0.579, p < 0. 001), 37.4% (adjust HR = 0.626, 95% CI: 0.422-0.929, p = 0.010), and 41.5% (adjust HR = 0.585, 95% CI: 0.401-0.856, p = 0.006), respectively, in the Q4 quartiles compared with the Q1 quartiles. Conclusions: This study revealed that a decreased CALLY index was associated with worse prognoses for CAD patients after PCI. The categorization of patients with a decreased CALLY index could provide valuable evidence for the risk stratification of adverse outcomes in CAD patients after PCI. Clinical Trial Registration: The details are available at http://www.chictr.org.cn (Identifier: NCT05174143).

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.

The U -shape relationship between free fatty acid level and adverse outcomes in coronary artery disease patients with hypertension: evidence from a large prospective cohort study.

BACKGROUND: Evidence is scarce on the effect of free fatty acid (FFA) level in the prognosis of coronary artery disease (CAD) patients with hypertension. This study. METHODS: A large prospective cohort study with a follow-up period of average 2 years was conducted at Xinjiang Medical University Affiliated First Hospital from December 2016 to October 2021. A total of 10,395 CAD participants were divided into groups based on FFA concentration and hypertension status, and then primary outcome mortality and secondary endpoint ischemic events were assessed in the different groups. RESULTS: A total of 222 all-cause mortality (ACMs), 164 cardiac mortality (CMs), 718 major adverse cardiovascular events (MACEs) and 803 major adverse cardiovascular and cerebrovascular events (MACCEs) were recorded during follow-up period. A nonlinear relationship between FFA and adverse outcomes was observed only in CAD patients with hypertension. Namely, a "U -shape" relationship between FFA levels and long-term outcomes was found in CAD patients with hypertension. Lower FFA level (< 310 µmol/L), or higher FFA level (≥ 580 µmol/L) at baseline is independent risk factors for adverse outcomes. After adjustment for confounders, excess FFA increases mortality (ACM, HR = 1.957, 95%CI(1.240-3.087), P = 0.004; CM, HR = 2.704, 95%CI(1.495-4.890, P = 0.001) and MACE (HR = 1.411, 95%CI(1.077-1.848), P = 0.012), MACCE (HR = 1.299, 95%CI (1.013-1.666), P = 0.040) prevalence. Low levels of FFA at baseline can also increase the incidence of MACE (HR = 1.567,95%CI (1.187-2.069), P = 0.002) and MACCE (HR = 1.387, 95%CI (1.070-1.798), P = 0.013). CONCLUSIONS: Baseline FFA concentrations significantly associated with long-term mortality and ischemic events could be a better and novel risk biomarker for prognosis prediction in CAD patients with hypertension. TRIAL REGISTRATION: The details of the design were registered on https://www.chictr.org.cn/ (Identifier NCT05174143).

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.

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.

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.

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.

Cystatin C to Left Ventricular Ejection Fraction Ratio as a Novel Predictor of Adverse Outcomes in Patients with Coronary Artery Disease: A Prospective Cohort Study.

Background: While both cystatin C and left ventricular ejection fraction (LVEF) revealed established prognostic efficacy in coronary artery disease (CAD), the relationship between cystatin C/left ventricular ejection fraction ratio (CLR) and adverse clinical outcomes among patients with CAD following percutaneous coronary intervention (PCI) remains obscure, to date. Therefore, we sought to assess the predictive efficacy of CLR among CAD patients who underwent PCI in current study. Methods: A total of 14,733 participants, including 8622 patients with acute coronary syndrome (ACS) and 6111 patients with stable coronary artery disease (SCAD), were enrolled from a prospective cohort of 15,250 CAD patients who underwent PCI and were admitted to the First Affiliated Hospital of Xinjiang Medical University from 2016 to 2021. The primary outcome of this study was mortality, including all-cause mortality (ACM) and cardiac mortality (CM). The secondary outcomes were major adverse cardiovascular events (MACEs), major adverse cardiac and cerebrovascular events (MACCEs) and nonfatal myocardial infarction (NFMI). For CLR, the optimal cut-off value was determined by utilizing receiver operating characteristic curve analysis (ROC). Subsequently, patients were assigned into two groups: a high-CLR group (CLR ≥ 0.019, n = 3877) and a low-CLR group (CLR < 0.019, n = 10,856), based on optimal cut-off value of 0.019. Lastly, the incidence of outcomes between the two groups was compared. Results: The high-CLR group had a higher incidence of ACM (8.8% vs. 0.9%), CM (6.7% vs. 0.6%), MACEs (12.7% vs. 5.9%), MACCEs (13.3% vs. 6.7%), and NFMIs (3.3% vs. 0.9%). After adjusting for confounders, multivariate Cox regression analyses revealed that patients with high-CLR had an 8.163-fold increased risk of ACM (HR = 10.643, 95% CI: 5.525~20.501, p < 0.001), a 10.643-fold increased risk of CM (HR = 10.643, 95% CI: 5.525~20.501, p < 0.001), a 2.352-fold increased risk of MACE (HR = 2.352, 95% CI: 1.754~3.154, p < 0.001), a 2.137-fold increased risk of MACCEs (HR = 2.137, 95% CI: 1.611~2.834, p < 0.001), and a 1.580-fold increased risk of NFMI (HR = 1.580, 95% CI: 1.273~1.960, p < 0.001) compared to patients with low-CLR. Conclusions: The current study indicated that a high CLR is a novel and powerful predictor of adverse long-term outcomes in CAD patients who underwent PCI, and that, it is a better predictor for patients wtih SCAD and ACS. Clinical Trial Registration: NCT05174143, http://Clinicaltrials.gov.

Predictive Value of the Modified GRACE Scoring System for All-Cause Mortality in Patients with Acute Myocardial Infarction.

Background: To establish a modified Global Registry of Acute Coronary Events (GRACE) scoring system with an improved predictive performance compared with the traditional GRACE scoring system. Methods: We identified 5512 patients who were hospitalized with a definite diagnosis of acute myocardial infarction (AMI) from January 1, 2015, to December 31, 2020, at the Heart Center of the First Affiliated Hospital of Xinjiang Medical University through the hospital's electronic medical record system. A total of 4561 patients were enrolled after the inclusion and exclusion criteria were applied. The mean follow-up was 51.8 ± 23.4 months. The patients were divided into dead and alive groups by endpoint events. The differences between the two groups were compared using the two-sample t test and chi-square test. Adjusted traditional risk factors as well as LogBNP (B-type natriuretic peptide precursor, BNP) and the modified GRACE scoring system were included in a multifactorial COX regression model. The predictive performance of the traditional and modified GRACE scoring systems was compared by (Receiver Operating Characteristic) ROC curves. Results: Significant differences in age, heart rate, creatinine, uric acid, LogBNP, traditional GRACE score, and modified GRACE score were found between the dead and alive groups by the two-sample t test. Comparison of the two groups by the chi-square test revealed that the dead group had a higher incidence of males; higher cardiac function class; a previous history of hypertension, diabetes, coronary artery disease (CAD), or cerebrovascular disease; a history of smoking; the need for intra-aortic balloon pump (IABP) support; and more patients taking aspirin, clopidogrel, ticagrelor, and ß -blockers. The results were analyzed by a multifactorial COX regression model, and after adjusting for confounders, age, cardiac function class, history of CAD, use of aspirin and ß -blockers, and the modified GRACE scoring system were found to be associated with all-cause mortality (ACM) in patients with AMI. The ROC curve was used to compare the predictive performance of the conventional GRACE scoring system with that of the modified GRACE scoring system, and it was found that the modified GRACE scoring system (Area Under Curve (AUC) = 0.809, p < 0.001, 95% (Confidence Interval) CI (0.789-0.829)) was significantly better than the traditional GRACE scoring system (AUC = 0.786, p < 0.001, 95% CI (0.764-0.808)), the comparison between the two scores was statistically significant (p < 0.001). The change in the C statistic after 10-fold crossover internal validation of the modified GRACE score was not significant, and the integrated discrimination improvement (IDI) between the old and new models was calculated with IDI = 0.019 > 0, suggesting that the modified GRACE score has a positive improvement on the traditional GRACE score. Conclusions: The modified GRACE scoring system, established by combining B-type natriuretic peptide precursor (BNP) and the traditional GRACE scoring system, was independently associated with ACM in patients with AMI, with a larger AUC and higher predictive value than the traditional GRACE scoring system. Clinical Trial Registration: NCT02737956.

Serum Globulin to Albumin Ratio as a Novel Predictor of Adverse Clinical Outcomes in Coronary Artery Disease Patients Who Underwent PCI.

Background: Coronary heart disease is one of the main causes of Mortality. Many biological indicators have been used to predict the prognosis of patients with coronary heart disease. The ratio of serum globulin to albumin (GAR) has been used to predict the prognosis of patients with various cancers. It has been proven that GAR is related to the prognosis of patients with stroke. However, GAR's role in cardiovascular disease remains unclear. Our purpose was to investigate the predictive value of GAR on clinical outcomes in post-percutaneous coronary intervention (PCI) patients with coronary artery disease (CAD). Methods: From Dec. 2016 to Oct. 2021, a total of 14,994 patients undergoing PCI patients admitted to the First Affiliated Hospital of Xinjiang Medical University were divided into high GAR group (GAR ≥ 0.76, n = 4087) and low GAR group (GAR < 0.76, n = 10,907). The incidence of adverse outcomes including all-cause mortality (ACM), cardiovascular mortality (CM), major adverse cardiovascular events (MACE) and major adverse cardiovascular and cerebrovascular events (MACCE) was compared between the two groups. Multivariate Cox regression was used to adjust for the effects of confounding factors, while hazard ratios (HRs) and 95% confidence intervals (95% CI) were calculated. Median follow-up time was 24 months. Results: Compared with the low GAR group, the high GAR group had significantly higher incidence of ACM (6.5% vs. 1.7%, p < 0.001); CM (4.9% vs. 1.2%, p < 0.001), MACE (10.5% vs. 6.7%, p < 0.001), and MACCE (11.3% vs. 7.5%, p < 0.001). Cox regression analysis showed the patients in the high GAR group had a 1.62-fold increased risk for ACM (HR = 2.622, 95% CI: 2.130-3.228, p < 0.01), a 1.782-fold increased risk for CM (HR = 2.782, 95% CI: 2.180-3.550, p < 0.01). There was a 37.2% increased risk for MACE (HR = 1.372, 95% CI: 1.204-1.564, p < 0.01), and 32.4% increased risk for MACCE (HR = 1.324, 95% CI: 1.169-1.500, p < 0.01), compared to the patients in the low GAR group. Conclusions: The present study suggested that post-PCI CAD patients with higher GAR presented significantly increased mortality and adverse events GAR level at admission may 296 be considered as part of risk stratification when PCI is possible in patients with coronary heart disease. Clinical Trial Registration: The detailed information of the PRACTICE study has been registered on http://Clinicaltrials.gov (Identifier: NCT05174143).

Predictive Value of the Fibrinogen to Gamma-Glutamine Transferase Ratio in the Long-Term Outcome in Patients with Coronary Heart Disease: A Retrospective Cohort Study.

Background: The ratio of fibrinogen to γ -glutamine transferase (FGR) was used to predict long-term prognosis in patients with coronary heart disease (CHD). Methods: A total of 5638 patients with CHD who were hospitalized from January 2008 to December 2016 were retrospectively enrolled in the study. The mean follow-up time was 35.9 ± 22.5 months. The follow-up endpoints were major cardiac and cerebrovascular adverse events (MACCE). The optimal FGR cut-off value was determined and divided into high- and low-FGR groups according to the receiver operating characteristic (ROC) curve. Statistical methods were used to compare the differences between the two groups and their prognoses to determine whether FGR can predict prognosis in patients with CHD. The traditional predictors were incorporated into the logistic regression model to observe the correlation between these indicators and all-cause mortality (ACM) events. We compared the prediction performance of FGR and traditional predictors on the occurrence of ACM events by ROC curves. Results: The optimal cut-off value was determined via a ROC analysis (FGR = 1.22, p = 0.002), and subjects were classified into high and low FGR groups. The follow-up found that the incidence of MACCE in the high FGR group was higher than that in the low FGR group. The COX multivariate regression model showed that high FGR was independently correlated with the occurrence of MACCE. In addition, the Kaplan-Meier survival curve showed that the risk of events was significantly increased in the group with high FGR. With increases in the FGR ratio, the risk of MACCE was increased. The ROC curve revealed that the risk of ACM was statistically different between the FGR and the traditional risk factor model (p = 0.002), (Fibrinogen (p = 0.008), γ -glutamine transferase (GGT) (p = 0.004), and N-terminal pro brain natriuretic peptide (NT-ProBNP) (p = 0.024)). The comparison between other different models were not statistically significant (p > 0.05). The area under the FGR model curve was larger than that of the traditional risk factors, fibrinogen, GGT and NT-ProBNP models. Conclusions: High FGR can increase the risk of MACCE in patients with CHD; additionally, it can be used as a new biomarker for long-term prognosis in CHD patients. Clinical Trial Registration: All details of this study are registered on the website (http://www.chictr.org.cn), registration number: ChiCTR-ORC-16010153.

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.