Elevated low-density lipoprotein cholesterol (LDL-C) is directly associated with cardiovascular disease, with the risk level determined by the magnitude and duration of exposure. In routine practice, there are limited data on the expected LDL-C lowering with bempedoic acid (BA) alone or in combination with ezetimibe (BA + EZE).

Patients initiating BA or BA + EZE were identified in the Veradigm Network EHR linked to claims (index). LDL-C levels were evaluated at baseline, 3, 6, and 12 months. To further examine BA and BA + EZE efficacy, patients were stratified by background statin use (12 months pre-index) and by continuous index therapy use (no therapy gap >45 days).

Of the 900 BA and 615 BA + EZE patients identified, median baseline LDL-C was 137 mg/dL and 127 mg/dL, respectively. By 3 months, BA (21%) and BA + EZE (33%, p < 0.0001 for both) were associated with significant reductions in median LDL-C levels. At baseline, only 6.3% of BA and 8.5% of BA + EZE patients had LDL-C <70 mg/dL; by 3 months, this increased to 16.8% and 33.3%. Over 12 months, 18.0% and 27.5% of patients had LDL-C <70 mg/dL. When stratified, the median reductions by 3 months highlighted use of BA and BA + EZE in patients without background statin use (BA: 24.2%; BA + EZE: 36.7%) and with continuous use (BA: 26.1%; BA + EZE: 40.2%).

Patients initiating BA and BA + EZE experienced early and sustained LDL-C improvements. The greatest reductions were in patients with continuous use and patients with no evidence of prior statin use, underscoring the importance of long-term adherence and treating patients not on statin therapy.

Observational studies show metformin use associated with lower cancer risk, although experimental evidence is inconsistent. To provide genetic validation for repositioning of metformin in cancer prevention, we assessed genetically proxied effects of putative metformin targets on cancer outcomes using a drug-target Mendelian randomization (MR) design.

We identified genetic proxies of 11 metformin targets (PRKAA1, PRKAA2, PRKAB1, PRKAB2, PRKAG1, PRKAG2, PRKAG3, ETFDH, GPD1, SLC47A1 and ACACB) based on their associations with tissue-specific gene expression, overall/sex-specific HbA1c and type 2 diabetes. We then evaluated genetically proxied effects of these targets on five major cancers using MR. We also employed a conventional MR design to assess the relationship of HbA1c with cancer using the inverse variance method, with sensitivity analyses. Associations were corrected for multiple comparisons using false discovery rates.

We identified two genetic proxies of putative metformin targets (PRKAG1 and GPD1) as valid instrumental variables (F statistics > 10). PRKAG1 was associated with a reduced risk of colorectal cancer (OR: 0.74 per mmol/mol reduction in overall HbA1c, 95% CI: 0.63-0.87; p = 0.001), with consistent findings in sex-specific analysis. This effect was unlikely mediated by HbA1c reduction, as indicated by conventional MR analyses (OR: 1.01 per mmol/mol, 95% CI: 0.99-1.02). No significant association was observed for GPD1 (OR: 1.00, 95% CI: 0.74-1.36; p = 0.98).

Metformin may prevent colorectal cancer via the AMPKγ1 (PRKAG1) target based on genetic evidence, supporting the evaluation of metformin use in colorectal cancer prevention using randomised controlled trials.

Systemic sclerosis-associated interstitial lung disease (SSc-ILD) is a major cause of morbidity and mortality in systemic sclerosis patients. High-resolution computed tomography (HRCT) plays a crucial role in SSc-ILD diagnosis and management. In this study, we aimed to develop and evaluate a deep learning-based automated segmentation model for quantifying SSc-ILD lesions in HRCT images and assess its clinical relevance.

We developed a convolutional neural network model to segment normal lung, established fibrosis (EF), and ground-glass opacity (GGO) in HRCT scans from 40 SSc-ILD patients. The model was trained and evaluated using 8-fold cross-validation. Segmentation performance was assessed using the Dice score coefficient (DSC). Correlations between predicted lesion volumes and pulmonary function test (PFT) metrics were analyzed using Spearman's ρ.

Our model achieved a total lesion (EF+GGO) DSC of 78%. Class-wise segmentation performance was lower for EF (DSC: 70%) compared to GGO (DSC: 73%). Predicted lesion volumes showed significant negative correlations with forced expiratory volume in one second (FEV1) (ρ=-0.64, p<0.001) and FEV1/forced vital capacity (ρ=-0.73, p<0.001). We also created the SICCS dataset, a public dataset of SSc-ILD HRCT images with expert-annotated segmentation labels.

Deep learning-based automated segmentation can help quantify SSc-ILD lesions in HRCT images and provide clinically relevant information. The model's performance is comparable to previous studies, and the predicted lesion volumes correlate significantly with PFT metrics. This approach shows promise for aiding in SSc-ILD diagnosis, monitoring, and clinical decision-making, although further validation with larger datasets is needed.

Endothelial dysfunction induced by inflammation and oxidative stress represents a critical pathological mechanism in cardiovascular and cerebrovascular diseases, including sepsis and atherosclerosis. Although crebanine has been reported to possess anti-inflammatory and analgesic properties, its effects on inflammation and oxidative stress in endothelial cells remain unknown. In this study, we assessed cell viability, apoptosis, and migration using the Cell Counting Kit-8 (CCK-8), flow cytometry, and a wound healing assay, respectively. The levels of reactive oxygen species (ROS) and the expression of inflammatory and oxidative stress markers were determined by qRT-PCR, enzyme-linked immunosorbent assay (ELISA), and Western blotting analysis. Our results demonstrated that crebanine alleviated lipopolysaccharide (LPS)-induced apoptosis and dysfunction in human umbilical vein endothelial cells (HUVECs). Crebanine treatment inhibited the production of pro-inflammatory cytokines (TNF-α, IL-6, IL-1β), ROS, and malondialdehyde (MDA), while it enhanced the activity of the antioxidant enzyme superoxide dismutase (SOD). Mechanistically, crebanine suppressed LPS-induced activation of the NF-κB signaling pathway in HUVECs. Furthermore, the improvement effect of crebanine on the inflammation and dysfunction in LPS-treated HUVECs was reversed by diprovocim, an NF-κB activator. These findings suggest that crebanine ameliorates LPS-induced inflammation and oxidative stress in HUVECs by inhibiting the NF-κB signaling pathway, indicating its potential therapeutic value for treating vascular endothelial dysfunction-related diseases.

Drawing on a large, nationally representative population of older American adults (n = 3610), the study shows that individuals with more than eight missing teeth have a 6%-10% higher likelihood of cardiovascular disease compared with those with fewer tooth losses. Poorer diet quality emerged as a key pathway linking tooth loss and cardiovascular outcomes.

To develop and validate a clinically actionable prediction model for postoperative pulmonary complications (PPCs) in cardiac surgery patients, focusing on modifiable preoperative risk factors amenable to targeted optimization.

In this prospective observational cohort study, 492 adults undergoing open-chest cardiac surgery between August 15, 2023 and December 31, 2023 were analyzed. Prespecified predictors included gas exchange variables, pulmonary function, inspiratory muscle strength, and physical performance. Univariable and multivariable logistic regression analyses were used to develop the prediction model. Discrimination was assessed by the area under the receiver operating characteristic curve (AUC).

A total of 90 patients (14.1%) developed PPCs after surgery. Five independent predictors were identified: elevated arterial PaCO2 (odds ratio [OR] 1.12, 95% confidence interval [CI] 1.00-1.26), oxygen desaturation (SpO2<93%) (OR 12.47, 95% CI 3.51-48.13), reduced gait speed (OR 0.17, 95% CI 0.04-0.71), lower FEV1/FVC ratio (OR 0.96, 95% CI 0.92-1.00), and diminished inspiratory muscle strength (MIP % predicted) (OR 0.96, 95% CI 0.92-0.99). The model demonstrated good discriminative ability with an AUC of 0.86 (95% CI 0.80-0.93) in the training cohort and 0.87 (95% CI 0.74-0.93) in the validation cohort.

This parsimonious model achieved high predictive accuracy using five modifiable physiological variables. By targeting abnormalities in gas exchange, pulmonary mechanics, muscle strength, and functional reserve, the model offers a practical tool to guide individualized prehabilitation strategies for reducing PPC risk in cardiac surgery patients.

Background/Objectives: The gut microbiota is increasingly recognized as a key determinant of human health, playing a vital role in metabolism, immunity, and disease susceptibility. Dysbiosis, or microbial imbalance, is associated with gastrointestinal disorders such as irritable bowel syndrome (IBS), inflammatory bowel disease (IBD), and Clostridioides difficile infection (CDI), as well as extraintestinal conditions, including obesity, cardiovascular disease, and neuropsychiatric disorders. This review aims to provide an updated overview of emerging therapeutic strategies to modulate the gut microbiota to restore eubiosis and improve health outcomes. Methods: A narrative review of recent literature was conducted, focusing on preclinical and clinical studies investigating microbiota-targeted therapies. The review primarily covers innovative interventional approaches, including fecal microbiota transplantation (FMT), bacterial consortium transplantation (BCT), bacteriophage therapy and outer membrane vesicles (OMVs). Results: Evidence supports the role of probiotics, prebiotics, and synbiotics in remodeling microbial communities and improving host health, although their effects may be strain- and context-dependent. FMT has demonstrated high efficacy in the treatment of recurrent Clostridium difficile infections and is being studied for IBD, IBS and extraintestinal diseases, following the recent Food and Drug Administration approval of the first commercial FMT products. BCT offers a standardized alternative to donor-derived material, with early clinical successes such as FDA-approved SER-109. Phage therapy and OMVs represent promising frontiers, offering targeted microbial modulation and interactions with the immune system, although clinical data remain limited. Conclusions: Emerging gut microbiota modulation strategies offer new perspectives for precision medicine and could transform the prevention and treatment of many diseases, but further studies are needed to ensure their safety, standardization, and clinical application.

Inflammation is strongly related to the development of multiple chronic diseases, such as cardiovascular and autoimmune diseases, and is considered a crucial target for new therapeutic approaches, since it significantly impacts public health, contributes to high mortality rates, and decreases the quality of life. Conventional anti-inflammatory approaches are commonly used, but they present multiple limitations, such as undesirable side effects and low target-specificity. Medicinal plants and their bioactive phytochemical compounds have been studied in recent years and are considered promising alternatives to classical therapies. They are widely recognized for their capacity to modulate inflammatory pathways, regulate inflammatory responses, and consequently reduce inflammation and related symptoms. Although they are considered a good therapeutic alternative, their application in the human body is limited by certain characteristics, such as low solubility, which leads to rapid metabolism and excretion by the organism, significantly reducing bioavailability; for these reasons, the use of medicinal plants remains a biopharmaceutical challenge. Nanotechnology represents a promising tool in this context, since it can improve several characteristics of these compounds. By incorporating plant-derived compounds in nanosystems, considerable advantages, including sustained release, protection from degradation, an increase in the specificity to target tissues, and consequent reduction in toxicity, can be achieved. Thus, nanosystems promote more favorable therapeutic outcomes. This work aims to compile scientific evidence supporting the use of medicinal plants and their bioactive phytochemical compounds, incorporated in nanosystems, in inflammatory disorders. This review enlarges knowledge by integrating both in vitro and in vivo studies involving multiple medicinal plants and bioactive phytochemical compounds, describing their mechanisms of action and the nanosystems employed for drug delivery. In the future, the need for deeper mechanistic studies, the development of targeted and stimuli-responsive systems, and advancement toward clinically translatable, sustainable, and cost-effective plant-based nanotherapies is required.

Cardiovascular disease (CVD) is increasingly recognized as a significant comorbidity in people living with HIV (PWH), contributing to increased morbidity and mortality. Epidemiological studies indicate that PWH have a 1.2-2-fold higher risk of myocardial infarction (MI) and other CVD events compared to HIV-negative individuals. While the mechanisms underlying HIV-associated CVD are not fully understood, they are likely to include a combination of cardiovascular-related adverse effects of HIV medications, vascular dysfunction caused by HIV-induced monocyte activation, and cytokine secretion, in addition to existing comorbidities and lifestyle choices. This comprehensive review examines the complex relationship between HIV infection and CVD, highlighting key pathophysiological mechanisms such as chronic immune activation, inflammation, endothelial dysfunction, and the role of antiretroviral therapy (ART) in promoting cardiovascular risk. Alongside conventional risk factors such as smoking, hypertension, and dyslipidemia, HIV-specific elements, especially metabolic abnormalities associated with ART, significantly contribute to the development of CVD. Prevention strategies are crucial, focusing on the early identification and management of cardiovascular risk factors as well as optimizing ART regimens to minimize adverse metabolic effects. Clinical guidelines now recommend routine cardiovascular risk assessment in PWH, emphasizing aggressive management tailored to their unique health profiles. However, challenges exist in fully understanding the cardiovascular outcomes in this population. Future research directions include exploring the role of inflammation-modulating therapies and refining sustainable prevention strategies to mitigate the growing burden of CVD in PWH.

The natural polypeptide drug hirudin, a direct thrombin inhibitor, exhibits potent anticoagulant, anti-myocardial fibrotic, and anti-inflammatory effects in the treatment of cardiovascular diseases (CVD), but its clinical application remains limited by its low bioavailability, insufficient targeting capability, and bleeding risk. In recent years, the development of nanotechnology has enabled peptide drug delivery systems to demonstrate substantial promise in medical practice. Significant progress has been made in overcoming limitations and enhancing therapeutic efficacy against CVD through the use of Hirudin-based drug delivery systems by addressing drug stability in vivo, improving targeting ability, and ultimately achieving responsive release. This paper systematically reviews the mechanisms of action, clinical applications, and novel delivery strategies of the peptide drug hirudin in the treatment of CVD, with a particular focus on recent advances in hirudin-based drug delivery systems, and it also looks forward to future research directions for hirudin delivery systems, including the development of scalable intelligent carriers, the construction of real-time feedback systems, and the establishment of standardized in vitro and in vivo evaluation systems, aiming to present novel strategies for safe and efficient treatment of CVD.