Heart failure (HF), a major global health challenge with high morbidity and mortality, lacks effective biomarkers and non-invasive tools for early diagnosis and therapy evaluation. Endogenous carbon monoxide (CO), a key biological signaling molecule, is closely linked to cardiovascular diseases such as HF when dysregulated. Integrating near-infrared (NIR) fluorescence (FL) imaging with photoacoustic (PA) imaging offers a powerful approach, as the 2D FL data can validate and supplement the 3D PA information for a more holistic disease assessment. Herein, we developed CS-CO, an activatable dual-mode NIR probe for the selective monitoring of CO fluctuations in HF. Density functional theory (DFT) calculations validated the design, elucidating the signal turn-on mechanism upon CO binding. The metal-free CS-CO probe selectively detects CO, resulting in activated NIR absorption (710 nm) and emission (742 nm). Consequently, its excellent NIR PA and FL performance allowed for visualizing both exogenous and endogenous CO in cells, and for 2D FL and 3D PA imaging in mice. Crucially, using this dual-mode imaging approach, CS-CO successfully revealed dynamic CO level changes during both HF progression and drug-induced reversal for the first time. This study provides a pioneering strategy for early HF diagnosis and drug efficacy evaluation, with significant potential clinical impact.

Infections following cardiac surgery are common and associated with increased complications and spending. While 1 in 5 beneficiaries experience a postoperative infection within 180 days, rates vary by 40% in absolute terms across hospitals. Efforts to reduce healthcare expenditures would benefit from associating interhospital variability in infection rates with Medicare spending.

A total of 6439 coronary artery bypass grafting and/or surgical aortic valve replacement procedures between 2017 and 2022 across 33 hospitals in Michigan were evaluated using a clinical and administrative dataset. The primary outcome was overall and component inflation-adjusted spending within 180 days after surgery. Spending was compared across risk-adjusted terciles of hospital infection rates and phase of care.

The mean age (SD) of the cohort was 71.2 (7.7) years, with 29.1% female patients and 4.8% black patients. The mean adjusted infection rates across the low versus high terciles were 13.2% (2.3%) and 26.7% (6.5%) (P < .0001). Beneficiaries at low versus high infection tercile hospitals had more chronic lung disease, were more likely to undergo combined procedures and experienced longer cardiopulmonary bypass times. Overall mean (SD) spending was $72,956 ($39,875). Spending was 6.0% ($4306) lower on average at low infection rate versus high infection rate hospitals. The postindex hospitalization phase of care accounted for 19.3% of total 180-day spending but varied across hospital terciles (low, 15.9%; high, 24.5%). Infections increased 180-day spending on average by $37,207 ($102,351 vs $65,144).

Spending following cardiac surgery varies across hospital risk-adjusted infection rate terciles. Infection prevention interventions could enhance cardiac surgical value.

In this study, we applied a selective sigma-1 receptor agonist, SA4503, to an extracorporeal cardiopulmonary resuscitation rat model and investigated its cerebral protective effects and potential mechanisms.

Eighteen male adult Sprague-Dawley rats were randomly allocated to 3 groups after anesthesia and identical preparation work, with 6 rats per group. The 2 intervention groups underwent asphyxiation-induced cardiac arrest and were rescued with and without SA4503. The SHAM group did not undergo cardiac arrest or rescue but received the same critical care as the intervention groups until the experiments ended. The end point was 1 hour after the return of spontaneous circulation or death. Hemodynamic and blood gas indicators were measured during surgery. Cerebral injury was evaluated histopathologically. Cerebrospinal fluid samples were collected by microdialysis. Rat hippocampal tissues from the intervention groups were used for whole-transcriptome sequencing.

Compared with extracorporeal cardiopulmonary resuscitation (ECPR) group, the ECPR + SA4503 group showed alleviated neuronal destruction of the CA1 region, which is illustrated by the pathologic pictures and the statistical result. In addition, the levels of excitatory amino acids of the ECPR + SA4503 group were lower than that of the ECPR group. In total, 74 differentially expressed genes were detected by RNA sequencing, most of which were related to inflammation, apoptosis, and oxidative stress. The phosphoinositide 3-kinase-AKT signaling pathway was selected by Kyoto Encyclopedia of Genes and Genomes pathway analysis, which may contribute to the cerebral protection of ECPR + SA4503, and was verified via western blotting. Finally, a lncRNA-miRNA-mRNA interactive ceRNA network was established to elucidate the mutual regulation among these three different kinds of RNAs.

Our findings indicate that the sigma-1 receptor agonist SA4503 mitigates brain injury in an extracorporeal cardiopulmonary resuscitation rat model.

Federally qualified health centers (FQHCs) use core quality measures to guide care and secure funding. One core measure is "Ischemic Vascular Disease (IVD): Use of Aspirin or Another Antiplatelet." A pilot program at an FQHC utilized the clinical pharmacy team to improve appropriate aspirin prescribing. Clinical pharmacy technicians identified eligible patients through a best practice advisory (BPA) in the electronic health record and contacted individuals with IVD not prescribed aspirin to schedule a clinical pharmacist appointment. Pharmacists then conducted medication reconciliations and ordered aspirin when indicated. This study evaluated the impact of incorporating pharmacy technicians into the clinical pharmacy workflow on the IVD quality measure.

This retrospective chart review compared aspirin prescriptions ordered from June to November 2023 between patients contacted by pharmacy technicians and those who were not. Demographics, outreach attempts, aspirin orders, and diagnosis codes were collected. Descriptive statistics and Fisher's exact test were used for analysis.

Pharmacy technicians attempted to contact 65 eligible patients, with 49 successfully reached. Aspirin was prescribed for 3.1% of control patients vs 30.6% in patients successfully contacted by the pharmacy team (P < .001). Resolved BPAs increased to 53.8% in the intervention group.

A clinical pharmacy team significantly increased aspirin therapy among eligible patients with IVD, demonstrating the value of pharmacy team involvement on quality metrics. Future research should explore expanded integration of clinical pharmacy team services to enhance patient care.

Cardiovascular imaging is integral to modern clinical trials of new pharmaceuticals or devices, enabling refined eligibility, mechanistic insight, and sensitive assessment of treatment response and safety. Potential heterogeneity in data acquisition, analysis, and reporting may affect reproducibility and interpretability across multicentre settings. Rigorous standardization and fit-for-purpose validation of imaging endpoints can improve statistical efficiency, reduce trial duration and cost, and strengthen generated evidence. This Scientific Statement outlines a reference framework for the implementation of cardiovascular imaging in clinical trials. We provide considerations on use of imaging parameters as eligibility criteria in clinical trials, for efficacy signals evaluation, and for assessment of safety. We define principles for clinical, analytical, and operational validation of imaging endpoints, and discuss concepts of minimal clinically important change and minimal detectable change. Additionally, we discuss feasibility considerations for use of cardiovascular imaging endpoints in multicentre clinical trials where differences in equipment and local experience may exist. We delineate standards for harmonization, centralized analysis, and quality control in clinical trials, as well as challenges and opportunities of the integration of artificial intelligence within core-lab workflows. Lastly, we identify gaps in knowledge, challenge of preclinical-clinical translatability and highlight training needs and innovation priorities.

BackgroundMild cognitive impairment is a prodromal stage of dementia, and early identification is crucial for prognosis.ObjectiveThis study aims to create and validate a machine learning model for diagnosing mild cognitive impairment (MCI) using eye movement and gait analysis data.MethodsTo facilitate model training and internal validation, a cohort of 235 patients was recruited from the Memory Clinic at Xi'an NO.3 Hospital between August 2024 and November 2025. In addition, data from 71 patients were randomly selected to form an independent test set. Feature selection was conducted using the Least Absolute Shrinkage and Selection Operator (LASSO) and multivariable logistic regression. Subsequently, various machine learning classifiers were compared. Model performance was assessed using metrics such as the area under the receiver operating characteristic curve (AUC) and decision curve analysis. To evaluate model interpretability, SHapley Additive exPlanations (SHAP) were employed.ResultsThe study involved 235 participants, divided into mild cognitive impairment (MCI) (n = 130) and healthy control (HC) (n = 105) groups. The final prediction model used four features: gait speed during a dual-task test, ground reaction force in a single-task test, antisaccade task accuracy, and noise rate in a saccade-to-pursuit task. The Gaussian Naive Bayes (GNB) classifier showed excellent performance with an AUC of 0.952 (95% CI: 0.923-0.981) in the validation group and 0.944 (95% CI: 0.912-0.967) in the test set.ConclusionsThe GNB model, combining eye movement and gait parameters, enables early MCI detection with high accuracy and practical clinical use.

The kynurenine (KYN) pathway (KP) is a central hub in tryptophan (Trp) metabolism, orchestrating immune regulation, neural signaling, and systemic energy homeostasis. Although KP dysregulation has been linked to multiple diseases, a unifying framework explaining how localized metabolic perturbations propagate across organs -a "Domino Effect"- is lacking. This review provides a comprehensive synthesis of KP's dual, context-dependent roles in immunity, neurodegeneration, cardiovascular disease, and gastrointestinal disorders. We critically evaluate the mechanistic basis of KYN as a master regulator via the aryl hydrocarbon receptor (AhR) and NAD⁺ biosynthesis, resolving controversies surrounding its pro-versus anti-inflammatory and pro-versus antitumorigenic functions. Key findings reveal that KP metabolites determine disease outcomes: KYNA/QA balance in the brain, inflammatory vascular remodeling in the heart, and host-microbiome crosstalk in the gut. We further assess therapeutic targeting of KP enzymes (IDO1, TDO2, KMO) and AhR, acknowledging both promising preclinical data and clinical translation challenges. Finally, we propose that future strategies must move beyond conventional enzyme inhibition to include upstream regulatory mechanisms. This review proposes a "Domino Effect" framework to provide new avenues for biomarker discovery, precision medicine, and structure-based drug design targeting the KP.

The composite indicator (TyG-CVAI), constructed by combining the triglyceride-glucose index and the Chinese visceral adiposity index, can quantify the combined pathogenic effects of insulin resistance and visceral obesity. However, an in-depth exploration of the long-term longitudinal evolution trajectories, cumulative exposure burden of TyG-CVAI, and its nonlinear association with the risk of cardiovascular disease (CVD) subtypes is still lacking. This study aims to prospectively evaluate the dynamic evolution pattern of TyG-CVAI and its predictive value for incident CVD, stroke, and heart disease.

Based on the Kailuan prospective cohort, this study included 32,841 participants without CVD prior to the 2012 baseline. Using data from four repeated measurements between 2006 and 2012, the longitudinal evolution trajectories of TyG-CVAI were identified through the K-means clustering algorithm, and its cumulative exposure burden (cumTyG-CVAI) was calculated. Multivariable Cox proportional hazards regression models were utilized to evaluate its association with incident CVD and its subtypes after 2012, and its dose-response relationship and predictive accuracy were assessed using restricted cubic splines (RCS) and receiver operating characteristic (ROC) curves.

During a median follow-up of 6.9 years, a total of 3,212 incident CVD events were recorded. Longitudinal analysis identified three distinct evolutionary trajectories: low, moderate, and high. After fully adjusting for confounding factors, compared with the low trajectory group, the high trajectory group faced the highest risk of incident total CVD (HR 1.837, 95% CI 1.588-2.126), stroke (HR 1.919, 95% CI 1.672-2.203), and heart disease (HR 2.260, 95% CI 1.827-2.796). For each standard deviation (SD) increase in cumulative TyG-CVAI, the risks of the aforementioned outcomes significantly increased by 29.2%-34.1%, respectively. RCS analysis showed that TyG-CVAI was positively and linearly correlated with the risk of stroke, while exhibiting a significant nonlinear threshold effect with the risks of total CVD (cumulative inflection point: 4683.98) and heart disease (cumulative inflection point: 4828.73). ROC analysis confirmed that the cumulative TyG-CVAI (AUC: 0.624-0.655) provided incremental improvements in predictive performance compared with single baseline measurements and traditional single or composite metabolic indices (all P < 0.05).

The dynamic elevation of TyG-CVAI and its long-term cumulative burden are independent predictors of incident CVD, stroke, and heart disease. Compared to single baseline assessments and traditional static indicators, cumulative TyG-CVAI demonstrates improved risk stratification value for cardiovascular risk, highlighting the clinical utility of integrating longitudinal metabolic monitoring into routine cardiovascular screening. Furthermore, this index shows a nonlinear threshold effect with heart disease and a linear correlation with stroke, highlighting the clinical value of integrating longitudinal metabolic monitoring into routine cardiovascular stratification to achieve precise prevention.

Iatrogenic pulmonary vein obstruction (PVO) is a rare but serious complication that may occur following transcatheter correction of sinus venosus atrial septal defect (SVASD) with partial anomalous pulmonary venous connection (PAPVC) using covered stents. This procedure has gained increasing acceptance in recent years. The optimal management strategy, particularly the role of conservative therapy, remains poorly defined. A 42-year-old man with a 1.5 × 1.0 cm superior vena cava (SVC)-type SVASD, PAPVC, and severe pulmonary arterial hypertension (PAH) underwent transcatheter repair after six months of targeted vasodilator therapy. Under fluoroscopic and transesophageal echocardiographic (TEE) guidance, a 57 mm long Optimus-CVS PTFE-covered XXL stent (AndraTec, Germany) was deployed, internally telescoped with a 45 mm long bare-metal CP stent (NuMED, USA) for cranial anchoring. Intra-procedural TEE showed correct stent position and unobstructed pulmonary venous flow. However, 24 h later, the patient developed acute hypoxemia. Computed tomography angiography revealed complete occlusion of the anterior segment of the right upper pulmonary vein with associated thrombosis. Because the patient remained hemodynamically stable, conservative management was initiated with corticosteroids, diuretics, and therapeutic anticoagulation (apixaban plus aspirin). Within five days, oxygen saturation normalized to 90% on room air, and chest imaging confirmed resolution of pulmonary infiltrates. Follow-up at six months showed a stable stent position and no residual obstruction.

PVO following transcatheter SVASD repair may not be diagnosed immediately after stent deployment, as it can present with delayed onset due to progressive thrombosis formation. Normal intra-procedural imaging does not exclude subsequent PVO, and vigilant post-procedural monitoring is essential. In carefully selected, hemodynamically stable patients, conservative management with corticosteroids, anticoagulation, and diuretics can lead to complete clinical and radiographic recovery, restoring pulmonary venous drainage and potentially avoiding reintervention or surgery.