Pathogen reduction treatment (PRT) of platelet concentrates (PC) is one of the most recent advances in improving blood safety and lowering the risk of transfusion-transmitted diseases. The characteristics of PR-treated PC differ slightly from those of untreated PC and may affect transfusion outcomes. We established how effective PRT methods, (INTERCEPT^TM Blood System) PC are when transfused to cardiac surgery patients.

 This study examined the influence of PRT using amotosalen and UVA light in a population of cardiac surgery patients. We analysed bleeding and platelet drop following cardiopulmonary bypass (CPB) surgery. We selected 73 patients after considering the medical exclusion criteria: 46 patients transfused with untreated platelet concentrate versus 27 patients transfused with PRT-treated platelet concentrate.

Data analysis concerns the readout after the first platelet concentrate transfusion. The decrease in patient platelet count between pre-operative and H0 [Intensive Care Unit (ICU) admission], and pre-operative and H6 post-surgery did not differ significantly with or without PRT. The volume of postoperative bleeding after CPB surgery did not differ significantly regardless of whether the patient was transfused with PRT-PC or untreated PC. No difference was documented between the groups in terms of postoperative pulmonary infection rate. Regardless of the use of platelet PRT, among the factors associated with bleeding, only Fg level was independently and significantly associated. A 1 mg/L increase in fibrinogen (pre-operative) is associated with a 159 mL decrease in bleeding 24 hours post-surgery.

In postoperative cardiac surgery, the use of platelets treated with amotosalen/UVA for pathogen reduction does not appear to affect transfusion effectiveness and postoperative bleeding.

We aimed to assess the association of depression severity with the incidence and progression of cardiometabolic multimorbidity (CMM) in middle-aged and older Chinese adults.

We analyzed data from 12,059 participants in the China Health and Retirement Longitudinal Study (CHARLS). Depression severity was categorized as none, mild-moderate, or severe using CES-D-10 scores. CMM was defined as the coexistence of two or more of type 2 diabetes, heart disease, or stroke. Cox proportional hazards models estimated the association of depression severity with first cardiometabolic disease (FCMD) and CMM. Multi-state models examined transitions from health to FCMD, CMM, and death.

Over 7 years of follow-up, 2080 participants developed FCMD and 305 developed CMM. Compared to no depression, mild-moderate (HR: 1.22, 95%CI: 1.11-1.34) and severe depression (HR: 1.46, 95%CI: 1.24-1.73) were associated with increased risk of FCMD; only severe depression was associated with CMM (HR: 2.08, 95%CI: 1.42-3.04). Multi-state models showed both mild-moderate (HR: 1.19, 95%CI: 1.09-1.31) and severe depression (HR: 1.42, 95%CI: 1.20-1.67) increased the risk of transitioning from health to FCMD, and from health to death (HR: 1.35, 95%CI: 1.17-1.55 and HR: 1.76, 95%CI: 1.40-2.21, respectively). Severe depression also increased the risk of transition from FCMD to CMM (HR: 1.55, 95%CI: 1.05-2.27). Results were robust in subgroup and sensitivity analyses.

Depression, particularly severe depression, was significantly associated with increased risks of incident cardiometabolic diseases, progression to multimorbidity, and mortality in middle-aged and older Chinese adults. Targeted interventions for depression may help delay CMM development.

Restrictive cardiomyopathy (RCM) is a severe cardiac disorder characterized by impaired ventricular filling and diastolic dysfunction, with mutations in sarcomeric proteins representing major causative factors. Mutations of TNNI3 gene (e.g., p.R192H) constitute major genetic causes of RCM, particularly affecting pediatric patients and being associated with poor prognosis. Here, we demonstrate that adenine base editor (ABE) can effectively correct RCM-causing mutation and alleviate RCM in a murine model. We develop a murine model harboring the Tnni3^R193H mutation that recapitulates the hallmark features of human RCM. Importantly, targeted delivery of ABE via adeno-associated virus (AAV) can achieve efficient and precise correction of the Tnni3^R193H mutation in adult RCM mice, leading to significant improvement of cardiac functions. Our findings establish base editing as a therapeutic strategy for RCM and highlight its broader potential for treating genetic cardiomyopathies in clinical settings.

Cardiovascular diseases and cancer represent leading global causes of mortality, sharing common risk factors. However, the specific impact of cancer on atherosclerotic plaque burden and coronary lesion complexity in acute coronary syndrome (ACS) remains understudied. We aim to compare coronary atherosclerotic burden as assessed by coronary angiography in cancer patients with ACS to those without cancer, including ACS and chronic disease.

This was a multicenter, ambispective observational study conducted between September 2016 and December 2022, involving detailed analysis of clinical records and invasive coronary angiograms. Patients were classified into three cohorts: (1) individuals presenting with acute coronary syndrome (ACS) and a prior history of cancer (ACSC), (2) ACS patients without any history of malignancy (ACSNC), and (3) patients with stable chronic coronary artery disease (CCAD). To reduce confounding, propensity score matching was applied to balance baseline characteristics between the ACSC and ACSNC groups. Comparative assessments focused on the presence of plaque rupture, angiographic complexity, and overall coronary atherosclerotic burden across the three cohorts.

618 patients were included, comprising 206 individuals each in the ACSC, ACSNC, and CCAD groups. A total of 3752 coronary lesions were analyzed. The most common types of cancer were prostate, hematological, and colorectal cancer. Patients with acute presentation had more eccentric and ulcerated lesions, involving bifurcations, and resulted in worse SYNTAX and Leaman scores when compared to chronic coronary artery disease (p values < 0.01 for all). Post-matching, 234 ACSC and ACSNC patients were compared, revealing higher anatomical complexity in ACSC, evidenced by elevated SYNTAX scores (p = 0.02), B2/C lesions (p < 0.01), and plaque rupture (p = 0.03). ACSC also showed a higher prevalence of plaque rupture in the proximal segments of the vessels (p < 0.01).

Among patients with acute coronary syndrome undergoing invasive coronary angiography, those with a history of cancer more frequently exhibited plaque rupture and greater anatomical complexity compared to non-cancer counterparts.

ClinicalTrials.gov Identifier: NCT04222608.

This national cross-sectional survey study aimed to investigate the prevalence and clustering of co-occurring diseases in persons with multiple sclerosis (MS) in Denmark. The study also examined the associations between socio-demographic and MS-specific characteristics and multimorbidity clusters.

The survey, conducted by the Danish MS Society, was carried out among 3,114 persons with MS (PwMS). The survey included information on 27 diseases, socio-demographic factors, and MS-specific factors. Weighted principal component analysis and K-means cluster analysis were used to identify multimorbidity clusters. Multinomial regression analyses were conducted to explore the associations between cluster membership and background variables.

Seventy-five percent of the respondents reported having one or more diseases in addition to MS. The most common coexisting diseases were hypertension (25.1%), hyperlipidemia (18.4%), allergy (18.2%), slipped disc/other spine disorders (17.9%), and osteoarthritis (17.9%). Five multimorbidity clusters were identified: "None-to-low multimorbidity", "Gastrointestinal, Musculoskeletal", "Cardiovascular, Diabetes", "Asthma, Allergy", and "Mental Illness". The clusters differed in terms of socio-demographic and MS-specific factors.

Understanding the patterns and clusters of multimorbidity, along with their links to socio-demographic and MS-specific characteristics, can help guide healthcare providers in assessing the healthcare needs of PwMS and in developing preventive strategies.

Propionyl L-carnitine (PPLC), a short -chain fatty acid derivative of carnitine, has been reported to produce beneficial effects in various cardiovascular diseases such as maladaptive cardiac hypertrophy, heart failure, ischemic heart disease, different types of cardiomyopathies and peripheral artery disease. Although all these cardiovascular diseases have diverse epidemiology and pathophysiology, both clinical and preclinical studies have indicated the role of oxidative stress, Ca2+-handling defects and metabolic abnormalities in their development and progression. In heart failure due to myocardial infarction, treatment with PPLC attenuated the inhibition of Na+-K+ ATPase and Na+-Ca2+ exchange activities. PPLC therapy of animals with diabetic cardiomyopathy improved Ca2+- handling abnormalities in cardiomyocytes by affecting the entry of Ca2+ through sarcolemma and regulating the sarcoplasmic reticular Ca2+- pump activities. The improvement of cardiac function recovery by PPLC treatment in ischemia- reperfused hearts was associated with its ability to antagonize the deleterious effects of palmitoyl L-carnitine on Ca2+-handling proteins. Treatment of peripheral artery disease with PPLC increased blood flow by affecting the vascular endothelium and smooth muscle functions in lower limbs. These observations support the view that PPLC improves cardiovascular function in diseased conditions by promoting mitochondrial metabolism, reducing oxidative stress and preventing Ca2+- handling abnormalities.

Sodium-glucose cotransporter 2 inhibitors demonstrate significant cardiovascular benefits in the management of heart failure; however, adverse effects such as urinary tract infection require careful clinical vigilance. This report describes a case of an 80-year-old female patient with heart failure who developed a urinary tract infection and subsequent septic shock following the initiation of dapagliflozin. The patient had been receiving long-term heart failure therapy, with dapagliflozin added 2 months prior to presentation. She presented with fever and developed hypotension (73/40 mmHg) within 30 min of hospital admission, leading to a diagnosis of septic shock. Management included antimicrobial therapy, vasopressor support, and fluid resuscitation, resulting in hemodynamic stabilization and resolution of the infection. The patient was discharged following clinical improvement. This case underscores the critical importance of vigilant monitoring, proactive patient education, and individualized risk-benefit assessment when prescribing sodium-glucose cotransporter 2 inhibitors to older patients with heart failure who are at high risk. It also provides valuable insights for the development of risk-mitigation strategies.

Venous thromboembolism (VTE) comprises provoked and unprovoked forms; accurate classification informs anticoagulation duration and recurrence risk but is limited by clinical phenotyping. We analysed the GSE48000 whole-blood transcriptomes to identify differentially expressed genes (DEGs) between provoked and unprovoked VTE. DEGs underwent GO and KEGG enrichment. Random forest ranked features, and an artificial neural network (ANN) built on the top 30 genes was trained and evaluated discrimination using stratified 10-fold cross-validation with receiver operating characteristic (ROC) analysis. A 30-gene signature cleanly separated the two subtypes. Most genes showed lower expression in unprovoked VTE, with a notable upregulation of GDF2, LGALS2, and LOC100130229. Enrichment analyses highlighted immune regulation and vesicle-transport pathways. The ANN achieved an AUC of 0.799 in this dataset. Transcriptomic profiling coupled with machine learning distinguished provoked from unprovoked VTE with excellent discrimination, supporting the feasibility of artificial intelligence (AI)-based molecular diagnostics for classification and risk assessment. Prospective validation in larger, independent cohorts is warranted.

Recent studies have highlighted the close relationship between gut microbiota and the cardiovascular system; however, the precise mechanisms and modes of their interaction remain incompletely understood. Among the various factors involved, bacterial extracellular vesicles (EVs) are often overlooked, despite their potential roles in multiple pathological processes. To investigate the role of bacterial EVs in shaping the inflammatory microenvironment following myocardial ischemia-reperfusion injury, we colonized the intestines of Rosa26.tdTomato reporter mice with Escherichia coli (E. coli) expressing Cre recombinase. Using FACS-beads and immunofluorescence techniques, we found that myocardial ischemia-reperfusion injury in mice significantly enhanced the invasion of gut-derived bacterial EVs. Meanwhile, in patients with ST-segment elevation myocardial infarction, we also confirmed the invasion of bacterial EVs via the FACS-bead method, and there was a significant correlation between extracellular vesicles in peripheral blood and LPS, suggesting that these EVs can be key carriers for LPS translocation. In this pathological process, invading E. coli EVs exacerbate the mobilization and infiltration of systemic and local inflammatory cells, thereby aggravating myocardial damage and impairing cardiac function. Notably, glucagon-like peptide-2 can effectively alleviate inflammatory responses and myocardial injury by inhibiting the translocation of E. coli-derived EVs. In conclusion, our study is the first to confirm the impact of gut-derived EVs on myocardial ischemia-reperfusion injury, revealing that E. coli EVs can amplify inflammatory responses. These findings provide new insights into the gut-heart axis and offer a theoretical basis for the therapeutic potential of glucagon-like peptide-2 in cardiovascular diseases.

Clinical trials are an important part of evidence generation in medicine but remain burdened by escalating costs, inefficiencies and manual processes. Artificial intelligence (AI) has emerged as a promising approach to address these limitations by improving efficiency across the trial lifecycle.

In this review, we examine emerging applications of AI across the clinical trial lifecycle. We highlight key examples demonstrating feasibility and potential impact.

AI-based approaches show promise in optimizing trial design, improving recruitment, streamlining conduct and enhancing data interpretation. Despite the potential of AI in trials, challenges persist, including data quality, regulatory and privacy concerns, as well as infrastructure issues. Ethical use will require strong governance frameworks emphasizing transparency and human oversight. The success of these technologies will depend on their continuous validation and monitoring of these technologies.

With appropriate validation, monitoring and governance, AI could enable a more efficient, cost-saving and effective clinical trial landscape that accelerates discovery.