Association of sodium-glucose cotransporter 2 inhibitors with risk of major adverse cardiovascular events in type 2 diabetes patients with acute coronary syndrome: a propensity score­matched analysis.

BACKGROUND: This study aimed to investigate the association of sodium-glucose cotransporter 2 inhibitors (SGLT2i) use with cardiovascular (CV) clinical outcomes in type 2 diabetes (T2D) patients with acute coronary syndrome (ACS). METHODS: Data of T2D patients hospitalized for ACS at Civil Aviation General Hospital from January 2019 to December 2022 were collected. Based on SGLT2i use or not, patients were stratified as SGLT2i group and SGLT2i-free group. A 1:1 nearest-neighbor propensity score-matched (PSM) was performed to adjust for the confounding factors and facilitate the robust comparisons between groups. The first occurrence of major adverse cardiovascular events (MACE) with 1 year follow-up, which consisted of CV death, all cause death, non-fatal myocardial infarction or stroke, coronary revascularization or heart failure readmission, was assessed. Kaplan-Meier analysis and Cox regressions were conducted to evaluate the prognostic significance of SGLT2i use. Subgroup analyses were performed to assess the interaction between subgroups and SGLT2i use. RESULTS: A total of 925 patients were included, and the SGLT2i use increased from 9.9% in 2019 to 43.8% in 2022. 226 pairs were finally matched using the PSM model. During 1 year follow-up period, a total of 110 patients experienced MACE in the matched cohort, with a rate of 24.3%. Survival analyses showed cumulative incidence of MACE, CV death, and heart failure readmission in the SGLT2i group were significantly lower than the SGLT2i-free group. Additionally, the adjusted Cox analyses demonstrated that SGLT2i was associated with a 34.1% lower risk of MACE (HR 0.659, 95% CI 0.487-0.892, P = 0.007), which was primarily driven by a decrease in the risk of CV death by 12.0% (HR 0.880, 95% CI 0.7830.990, P = 0.033), and heart failure readmission by 45.5% (HR 0.545, 95% CI 0.332-0.893, P = 0.016). This MACE preventive benefit was consistent across different subgroups (P interaction > 0.05 for all comparisons). CONCLUSIONS: In T2D patients with ACS, there was a clear increasing trend in SGLT2i use. SGLT2i was associated with a significantly lower risk of MACE, driven by the decrease in the risk of CV death, and heart failure readmission. Our study confirmed real-world use and efficacy of SGLT2i in a general T2D population with ACS.

AnGong NiuHuang (AGNH) pill attenuated traumatic brain injury through regulating NF-κB/Nlrp3 axis and glycerophospholipid metabolism.

BACKGROUND: Traumatic brain injury (TBI), especially neuroinflammation after TBI persists for a long time and causes significant neurodegenerative pathologies and neuropsychiatric problems. PURPOSE: In this study, the neuroprotective effect of AnGong NiuHuang (AGNH) on TBI was investigated and the mechanism was revealed by integrating multiple omics. METHODS: The rats with TBI were administrated with AGNH for 5 consecutive days and the effect was evaluated by using modified neurologic severity score (mNSS), brain edema, H&E staining, Nissl staining and TUNEL staining. The mechanism was revealed by using RNA sequencing (RNA-seq) and metabolomic analysis. The inflammatory factors, apoptosis-related proteins and identified vital targets were validated by enzyme-linked immunosorbent assay, western blotting and immunofluorescence staining. RESULTS: Administration of AGNH decreased mNSS, brain edema, brain structure damage, but increased Nissl body density in the rats with TBI. Additionally, AGNH reduced IL-1ß, IL-17A, TNF-α, MMP9, MCP-1, IL-6, Bax and TUNEL staining,but elevated Bcl2 level. Integrating transcriptomic analysis and metabolomic analysis identified vital targets and critical metabolic pathways. Importantly, AGNH treatment reduced the expression of TLR4, MYD88, NLRP3, BTK, IL-18 and Caspase 1 as well as glycerophospholipid metabolism-related protein AGPAT2 and PLA2G2D, and decreased the nuclear translocation of NF-κB p65 in the brain of TBI rats. Additionally, AGNH increased phosphatidylcholine (PC), phosphatidylglycerol (PG), phosphatidylserine (PS), phosphatidylethanolamine (PE), but decreased 1-acyl-sn-glycero-3-phosphocholine (LysoPC) in the metabolic pathway of glycerophospholipid metabolism. CONCLUSION: Taken together, AGNH inhibited NF-κB/NLRP3 axis to suppress neuroinflammation, cell apoptosis and pyroptosis, and improved metabolic pathways of glycerophospholipid metabolism after TBI.

Traditional Chinese medicine Pien-Tze-Huang ameliorates LPS-induced sepsis through bile acid-mediated activation of TGR5-STAT3-A20 signalling.

Pien Tze Huang (PZH), a class I nationally protected traditional Chinese medicine (TCM), has been used to treat liver diseases such as hepatitis; however, the effect of PZH on the progression of sepsis is unknown. Here, we reported that PZH attenuated lipopolysaccharide (LPS)-induced sepsis in mice and reduced LPS-induced production of proinflammatory cytokines in macrophages by inhibiting the activation of mitogen-activated protein kinase (MAPK) and nuclear factor-kappa B (NF-κB) signalling. Mechanistically, PZH stimulated signal transducer and activator of transcription 3 (STAT3) phosphorylation to induce the expression of A20, which could inhibit the activation of NF-κB and MAPK signalling. Knockdown of the bile acid (BA) receptor G protein-coupled bile acid receptor 1 (TGR5) in macrophages abolished the effects of PZH on STAT3 phosphorylation and A20 induction, as well as the LPS-induced inflammatory response, suggesting that BAs in PZH may mediate its anti-inflammatory effects by activating TGR5. Consistently, deprivation of BAs in PZH by cholestyramine resin reduced the effects of PZH on the expression of phosphorylated-STAT3 and A20, the activation of NF-κB and MAPK signalling, and the production of proinflammatory cytokines, whereas the addition of BAs to cholestyramine resin-treated PZH partially restored the inhibitory effects on the production of proinflammatory cytokines. Overall, our study identifies BAs as the effective components in PZH that activate TGR5-STAT3-A20 signalling to ameliorate LPS-induced sepsis.

Xinshubao tablet rescues cognitive dysfunction in a mouse model of vascular dementia: Involvement of neurogenesis and neuroinflammation.

Vascular dementia (VaD) represents a severe cognitive dysfunction syndrome closed linked to cardiovascular function. In the present study, we assessed the potential of Xinshubao tablet (XSB), a traditional Chinese prescription widely used for cardiovascular diseases, to mitigate neuropathological damage in a mouse model of VaD and elucidated the underlying mechanisms. Our findings revealed that oral administration of XSB rescued the cardiac dysfunction resulting from bilateral common carotid artery stenosis (BCAS), improved the cerebral blood flow (CBF) and cognitive function, reduced white matter injury, inhibited excessive microglial and astrocytic activation, stimulated hippocampal neurogenesis, and reduced neural apoptosis in the brains of BCAS mice. Mechanistically, RNA-seq analysis indicated that XSB treatment was significantly associated with neuroinflammation, vasculature development, and synaptic transmission, which were further confirmed by q-PCR assays. Western blot results revealed that XSB treatment hindered the nuclear translocation of nuclear factor-κB (NF-κB), thereby suppressing the NF-κB signaling pathway. These results collectively demonstrated that XSB could ameliorate cognitive dysfunction caused by BCAS through regulating CBF, reducing white matter lesions, suppressing glial activation, promoting neurogenesis, and mitigating neuroinflammation. Notably, the NF-κB signaling pathway emerged as a pivotal player in this mechanism.

Acute exacerbation prediction of COPD based on Auto-metric graph neural network with inspiratory and expiratory chest CT images.

Chronic obstructive pulmonary disease (COPD) is a widely prevalent disease with significant mortality and disability rates and has become the third leading cause of death globally. Patients with acute exacerbation of COPD (AECOPD) often substantially suffer deterioration and death. Therefore, COPD patients deserve special consideration regarding treatment in this fragile population for pre-clinical health management. Based on the above, this paper proposes an AECOPD prediction model based on the Auto-Metric Graph Neural Network (AMGNN) using inspiratory and expiratory chest low-dose CT images. This study was approved by the ethics committee in the First Affiliated Hospital of Guangzhou Medical University. Subsequently, 202 COPD patients with inspiratory and expiratory chest CT Images and their annual number of AECOPD were collected after the exclusion. First, the inspiratory and expiratory lung parenchyma images of the 202 COPD patients are extracted using a trained ResU-Net. Then, inspiratory and expiratory lung Radiomics and CNN features are extracted from the 202 inspiratory and expiratory lung parenchyma images by Pyradiomics and pre-trained Med3D (a heterogeneous 3D network), respectively. Last, Radiomics and CNN features are combined and then further selected by the Lasso algorithm and generalized linear model for determining node features and risk factors of AMGNN, and then the AECOPD prediction model is established. Compared to related models, the proposed model performs best, achieving an accuracy of 0.944, precision of 0.950, F1-score of 0.944, ad area under the curve of 0.965. Therefore, it is concluded that our model may become an effective tool for AECOPD prediction.

Transcriptomics and Metabolomics Unveil the Neuroprotection Mechanism of AnGong NiuHuang (AGNH) Pill Against Ischaemic Stroke Injury.

As a famous prescription in China, AnGong NiuHuang (AGNH) pill exerts good neuroprotection for ischaemic stroke (IS), but its mechanism is still unclear. In this study, the neuroprotection of AGNH was evaluated in the rat IS model which were established with the surgery of middle cerebral artery occlusion (MCAO), and the potential mechanism was elucidated by transcriptomic analysis and metabolomic analysis. AGNH treatment obviously decreased the infarct volume and Zea-Longa 5-point neurological deficit scores, improved the survival percentage of rats, regional cerebral blood flow (rCBF), and rat activity distance and activity time. Transcriptomics showed that AGNH exerted its anti-inflammatory effects by affecting the regulatory network including Tyrobp, Syk, Tlr2, Myd88 and Ccl2 as the core. Integrating transcriptomics and metabolomics identified 8 key metabolites regulated by AGNH, including L-histidine, L-serine, L-alanine, fumaric acid, malic acid, and N-(L-arginino) succinate, 1-pyrroline-4-hydroxy-2-carboxylate and 1-methylhistamine in the rats with IS. Additionally, AGNH obviously reduced Tyrobp, Syk, Tlr2, Myd88 and Ccl2 at both the mRNA and protein levels, decreased IL-1ß, KC-GRO, IL-13, TNF-α, cleaved caspase 3 and p65 nucleus translocation, but increased IκBα expression. Network pharmacology analysis showed that quercetin, beta-sitosterol, baicalein, naringenin, acacetin, berberine and palmatine may play an important role in protecting against IS. Taken together, this study reveals that AGNH reduced neuroinflammation and protected against IS by inhibiting Tyrobp/Syk and Tlr2/Myd88, as well as NF-κB signalling pathway and regulating multiple metabolites.

Population Pharmacokinetics and Exposure-Response Relationship of Zimberelimab in Chinese Patients with Advanced Tumors.

This study aimed to establish a population pharmacokinetic (PopPK) model using data from 2 clinical trials of zimberelimab, evaluate the pharmacokinetics (PKs) of zimberelimab, explore the feasibility of 360 mg once every 3 weeks (Q3W) and 480 mg once every 4 weeks (Q4W) as alternative dosage regimens, and analyze the exposure-response relationship of the efficacy and safety of zimberelimab for advanced tumors. The PKs of zimberelimab were described using the 2-compartment model with time-dependent nonlinear elimination. The prediction-corrected visual predictive check was used to evaluate the model's predictive value on blood drug concentrations. In total, 2165 PK observations from 321 participants were included. The PopPK model demonstrated a high level of concordance between the observed data and the predicted values, indicative of a robust fit to the PK data of zimberelimab. The PK variables were similar for the 240 mg once every 2 weeks, 360 mg Q3W, and 480 mg Q4W regimens. No covariates significantly affecting the PK variables in the final model were found. The exposure variables of zimberelimab have no obvious correlations with efficacy and safety, and 360 mg Q3W and 480 mg Q4W are worthy of further study. This study establishes a PopPK model and analyzes the exposure-response relationship of zimberelimab, which helps to explore the potential for alternative dosing regimens and offers a foundation for optimizing therapeutic strategies for advanced cancer patients through simulation-based methods.

Immunomodulatory Function of Pien Tze Huang in T Cell-Mediated Anti-tumor Activity against B16-F10, MC38 and Hep1-6 Tumor Models.

OBJECTIVE: To investigate the anti-tumor effects of Pien Tze Huang (PZH) in mouse models of B16-F10 melanoma, MC38 colorectal cancer, Hep1-6 hepatocellular carcinoma and chemically induced hepatocellular carcinoma model. METHODS: Various tumor models, including B16-F10, MC38 and Hep1-6 tumor hypodermic inoculation models, B16-F10 and Hep1-6 pulmonary metastasis models, Hep1-6 orthotopic implantation model, and chemically induced hepatocellular carcinoma model, were utilized to evaluate the anti-tumor function of PZH. Tumor growth was assessed by measuring tumor size and weight of solid tumors isolated from C57BL/6 mice. For cell proliferation and death of tumor cells in vitro, as well as T cell activation markers, cytokine production and immune checkpoints analysis, single-cell suspensions were prepared from mouse spleen, lymph nodes, and tumors after PZH treatment. RESULTS: PZH demonstrated significant therapeutic efficacy in inhibiting tumor growth (P<0.01). Treatment with PZH resulted in a reduction in tumor size in subcutaneous MC38 colon adenocarcinoma and B16-F10 melanoma models, and decreased pulmonary metastasis of B16-F10 melanoma and Hep1-6 hepatoma (P<0.01). However, in vitro experiments showed that PZH only had slight impact on the cell proliferation and survival of tumor cells (P>0.05). Nevertheless, PZH exhibited a remarkable ability to enhance T cell activation and the production of interferon gamma, tumor necrosis factor alpha, and interleukin 2 in CD4+ T cells in vitro (P<0.01 or P<0.05). Importantly, PZH substantially inhibited T cell exhaustion and boosted cytokine production by tumor-infiltrating CD8+ T cells (P<0.01 or P<0.05). CONCLUSION: This study has confirmed a novel immunomodulatory function of PZH in T cell-mediated anti-tumor immunity, indicating that PZH holds promise as a potential therapeutic agent for cancer treatment.

COPD stage detection: leveraging the auto-metric graph neural network with inspiratory and expiratory chest CT images.

Chronic obstructive pulmonary disease (COPD) is a common lung disease that can lead to restricted airflow and respiratory problems, causing a significant health, economic, and social burden. Detecting the COPD stage can provide a timely warning for prompt intervention in COPD patients. However, existing methods based on inspiratory (IN) and expiratory (EX) chest CT images are not sufficiently accurate and efficient in COPD stage detection. The lung region images are autonomously segmented from IN and EX chest CT images to extract the 1 , 781 × 2 lung radiomics and 13 , 824 × 2 3D CNN features. Furthermore, a strategy for concatenating and selecting features was employed in COPD stage detection based on radiomics and 3D CNN features. Finally, we combine all the radiomics, 3D CNN features, and factor risks (age, gender, and smoking history) to detect the COPD stage based on the Auto-Metric Graph Neural Network (AMGNN). The AMGNN with radiomics and 3D CNN features achieves the best performance at 89.7 % of accuracy, 90.9 % of precision, 89.5 % of F1-score, and 95.8 % of AUC compared to six classic machine learning (ML) classifiers. Our proposed approach demonstrates high accuracy in detecting the stage of COPD using both IN and EX chest CT images. This method can potentially establish an efficient diagnostic tool for patients with COPD. Additionally, we have identified radiomics and 3D CNN as more appropriate biomarkers than Parametric Response Mapping (PRM). Moreover, our findings indicate that expiration yields better results than inspiration in detecting the stage of COPD.