Serum potassium levels are regulated by renal function; however, the extent to which the association with mortality is affected by renal function remains unknown. We aimed to explore the association of admission serum potassium levels with mortality in patients with coronary artery disease (CAD), stratified by renal function. Renal function was categorized into normal (≥ 90 mL/min/1.73 m2), mildly decreased (60–89 mL/min/1.73 m2), and impaired (< 60 mL/min/1.73 m2) according to estimated glomerular filtration rate (eGFR). The outcome was all-cause mortality within 3 years after hospitalization. 7739 patients from a prospective multicenter registry were included. All-cause mortality occurred in 366 patients (4.7

Objective.Rapid stratification of acute chest pain patients with non-ischemic electrocardiograms (ECGs) remains challenging. We developed and externally validated an interpretable cardiodynamicsgram (CDG)- major adverse cardiovascular events (MACE) Score to predict 30 d MACE.Approach.We proposed a three-step framework: (1) ECG dynamic analysis: using deterministic learning to model the ST-T repolarization process and derive CDG features that capture subtle repolarization abnormalities. We defined the temporal heterogeneity index and spatial heterogeneity index as quantitative CDG. (2) Ensemble model: training an XGBoost classifier on eight pre-specified variables with five-fold cross-validation. Patient-level splits were used; only the first emergency department ECG per patient entered the model. (3) Score derivation: transforming the ensemble into a sparse, globally interpretable score via SHAP-based variable contributions. To mitigate the demographic influence, age and gender were included as explicit covariates, and the study results were prespecified to be reported stratified by age and gender in both cohorts.Main results.Calibration and decision-analytic utility were assessed. Two independent cohorts (n= 2836) were included. In Cohort-1 (n= 2196; 23.27% MACE), the ensemble model achieved AUC 0.8441. Adding CDG dynamics to clinical variables improved discrimination compared with a clinical-only model (AUC 0.7963-0.8221). The derived CDG-MACE Score maintained discrimination (internal AUC 0.8221) and generalized well to Cohort-2 (n= 640; 11.09% MACE; external AUC 0.8219). Using prespecified cutoffs from the training set (low ⩽ 9.52; high > 26.83), the internal low-risk group had negative predictive value (NPV) 99.22% and MACE 0.78%, while the external low-risk group achieved NPV 100%. Ablation analyses confirmed that CDG dynamics contributed independent signals beyond demographics.Significance.The CDG-MACE Score combines dynamic ECG modeling with a SHAP-linearized scoring system to achieve discrimination with global interpretability, enabling safe exclusion of low-risk patients without typical ischemic ECG changes. External validation suggests robustness and clinical utility; additional multicenter prospective studies and fairness monitoring are warranted.

The conceptual landscape of cell death has evolved beyond the traditional dichotomy of apoptosis and necrosis to encompass diverse regulated pathways including necroptosis, autophagy, ferroptosis, and pyroptosis. Necroptosis, a caspase-independent inflammatory form of programmed cell death, has emerged as a critical driver of the pathogenesis of cardiovascular disorders, neurodegenerative diseases, and cancer. Concurrently, our understanding of mitochondrial biology has undergone a paradigm shift: mitochondria are no longer viewed merely as bioenergetic powerhouses, but as dynamic signalling hubs that orchestrate metabolic reprogramming, cellular homeostasis, and ultimate cell fate decisions. In this regard, a growing body of evidence suggests that mitochondrial dysfunction is a central rheostat that enables necroptotic execution. This review delineates the mechanistic interplay between necroptosis and mitochondrial dysfunction and systematically analyzes the key molecular mediators and pathological pathways through which mitochondrial dysregulation drives necroptotic activation. Furthermore, this review identifies actionable therapeutic targets and translational strategies for modulating necroptosis in related diseases.

Aim In-hospital cardiac arrest (IHCA) is a catastrophic complication in patients with non-ST-segment elevation myocardial infarction (NSTEMI), who are more likely to be underrecognized and undertreated than patients with ST-segment elevation myocardial infarction. However, the epidemiology, characteristics, and factors influencing IHCA in NSTEMI patients remain poorly defined. Methods This was a retrospective cohort study based on data from the nationwide Improving Care for Cardiovascular Disease in China-Acute Coronary Syndrome (CCC-ACS) project in China. Patients diagnosed with NSTEMI between November 2014 and December 2020 were included and stratified by IHCA occurrence. IHCA incidence among NSTEMI patients and in-hospital mortality of IHCA patients were calculated. Cox proportional hazards models were applied to identify risk and protective factors for IHCA in patients with NSTEMI. Results Among 32,094 NSTEMI patients (29.45% female; mean age, 65.25 years), 397 (1.24%) developed IHCA. IHCA incidence decreased from 2.06% in 2014 to 0.89% in 2020, but in-hospital mortality remained high (65.74%). IHCA occurred most frequently on the day of admission (25.59%; median, 4 [1-7] days). Risk factors for IHCA included prior out-of-hospital cardiac arrest, ≥100-fold elevated TnT/TnI levels, age ≥75 years, Killip class IV, systolic blood pressure < 90 mmHg, and heart rate > 100 bpm at admission, history of heart failure, renal failure, ischemic stroke, and the latest glucose level >10 mmol/L. Coronary angiography before IHCA was the strongest protective factor. Conclusions IHCA remains a fatal complication of NSTEMI, often occurring early after admission. Recognition of high-risk features, timely initiation of coronary angiography, and implementation of guideline-directed therapies may reduce IHCA occurrence.

Background Myocardial fibrosis (MF) is a common pathological manifestation of end-stage cardiovascular diseases such as hypertension. Hypertension increases cardiac afterload and induces fibrotic myocardial remodeling, ultimately progressing to heart failure. DDR1 (discoidin domain receptor 1), a collagen-activated receptor, plays a pivotal role in multiorgan fibrosis progression. However, its specific mechanistic role in hypertension-induced MF remains to be investigated.Methods A pressure overload-induced MF model was established in male spontaneously hypertensive rats, and cardiac fibroblasts were stimulated with angiotensin II to induce a fibrotic phenotype. Cardiac function and fibrosis were assessed through echocardiography combined with histological/cellular staining. Western blotting, quantitative reverse transcription polymerase chain reaction, immunoprecipitation, and ubiquitination assays were used to investigate molecular mechanisms.Results Results demonstrated upregulated DDR1 expression in both activated cardiac fibroblasts and fibrotic hearts of spontaneously hypertensive rats. DDR1 inhibition improved cardiac structure and function in spontaneously hypertensive rats, while reducing the fibrotic phenotype of cardiac fibroblasts and attenuating MF progression. Mechanistically, DDR1 enhances direct interaction with SP1 (specificity protein 1), suppressing its ubiquitination and degradation. SP1 binds to the ROCK1 (rho-associated protein kinase 1) gene promoter to strengthen transcriptional regulation, thereby upregulating ROCK1 and downstream profibrotic signaling pathways.Conclusions In summary, this study demonstrates that DDR1 is a pivotal driver of MF progression, establishing both a theoretical foundation and an experimental basis for DDR1-targeted therapy in MF.

Objective: Coronary slow flow (CSF), present in 1-7% of coronary angiograms, occurs in patients with angiographically normal epicardial arteries and is associated with acute coronary syndrome, representing an unmet need in coronary microvascular dysfunction (CMD) management. This study proposes an anatomy-guided spatiotemporal dynamical fusion (AG-STDF) framework for CSF screening. Methods: AG-STDF integrates anatomical electrophysiological territory mapping with 12-lead electrocardiogram (ECG) dynamics. ECG signals are decomposed into coronary territories-left anterior descending (LAD), left circumflex (LCX), and right coronary artery (RCA)—and static morphology is fused with intrinsic dynamics (derived from dynamic modeling) using joint recurrence quantification and multi-scale decomposition. Results: AG-STDF achieves an AUROC of 0.9467 $\pm$ 0.0272 for CSF detection. At the vessel level, where therapeutic decisions are made per 2024 European Society of Cardiology guidelines, AG-STDF predicts corrected thrombolysis in myocardial infarction frame counts (CTFC) with an $\text{R}^{\text{2}}$ = 0.5951 $\pm$ 0.0666 (AUROC: 0.8428). Notably, AG-STDF performs steadily in right-dominant coronary patients, with favorable results in LAD ($\text{R}^{\text{2}}$ = 0.6753) and mild fluctuations in LCX ($\text{R}^{\text{2}}$ = 0.5673) and RCA ($\text{R}^{\text{2}}$ = 0.5296) due to anatomical variations and competitive perfusion. Anatomical constraints and spatiotemporal fusion improve AUROC by 3.5% (p $< $ 0.01) and 9.47% (p $< $ 0.05). When equipped with an Intel Core i5-10500 and NVIDIA GTX 1660S, AG-STDF processes a 10-second ECG segment in 19.37 s. Conclusion: AG-STDF allows accurate, non-invasive CSF detection and vessel-level assessment in right-dominant populations. Significance: It serves as a cost-effective CMD screening tool that may reduce invasive testing and support early diagnosis.

Exhaled breath (EB) harbors rich molecular information, providing important insights into multiple metabolism processes of the living body. Thus, EB analysis is believed to be a promising diagnostic method for fast and non-invasive disease detection in the future. In this work, we developed a cost-effective "nano-filter" integrated with ambient ionization mass spectrometry (AIMS) for the direct detection of EB aldehyde metabolites. The "nano-filter" features p-selenophenylhydrazide-functionalized silver nanoparticles (HSe-Ag NPs) immobilized on fiber paper, selectively capturing EB aldehydes while filtering interferents. Upon application of high voltage to induce cleavage of Ag-Se bonds, the Se-tagged aldehyde derivatives (Se-aldehydes) are liberated for AIMS detection. We demonstrated the high performance of this "nano-filter" AIMS strategy by analysing 152 clinical EB samples, including 91 healthy individuals and 61 lung cancer (LCa, non-small cell lung cancer) patients. Over 88 aldehydes were detected, most reported for the first time. Based on a machine learning (ML) model, the strategy achieved 95.8% accuracy in identifying LCa using these EB aldehydes. We believe that this novel nano-filter AIMS strategy, combined with the ML technique, can provide a robust and effective tool for high-throughput LCa screening for clinical diagnosis and biomedical research.

BACKGROUND:Acute kidney injury (AKI) is a critical complication in ST-segment elevation myocardial infarction (STEMI) patients who undergo percutaneous coronary intervention (PCI). The effect of high preoperative estimated glomerular filtration rate (eGFR; ≥ 105 mL/min/1.73 m2) on AKI and long-term adverse outcomes remains poorly understood. METHODS:In this multicentre, prospective cohort study we enrolled 4536 STEMI consecutive patients who underwent emergency PCI in China. Logistic regression was used to assess the association between preoperative eGFR and AKI, and Cox regression was used to evaluate the effect of preoperative eGFR and AKI on 2-year adverse outcomes. RESULTS:Among 4536 patients, 820 (18.1%) had high eGFR, 1806 (39.8%) normal eGFR (90-105 mL/min/1.73 m2), 1547 (34.1%) mild reduction of eGFR (60-90 mL/min/1.73 m2), and 363 (8.0%) had low eGFR (< 60 mL/min/1.73 m2). Mean age was 62 years; 23.2% were female. Low and high eGFR levels were independently associated with increased AKI risk (adjusted odds ratio, 1.818 [95% confidence interval (CI), 1.268-2.608] and 2.143 [95% CI, 1.517-3.025]). Two-year major adverse cardiovascular events incidence increased progressively with declining eGFR: 4.0% (high), 5.5% (normal), 11.3% (mild), and 22.3% (low). Among patients with normal-to-high eGFR, those with AKI had higher risks of major adverse cardiovascular events (hazard ratio, 2.418 [95% CI, 1.579-3.704]) and all-cause mortality (hazard ratio, 2.380 [95% CI, 1.407-4.025]). CONCLUSIONS:This study confirmed a U-shaped relationship between preoperative eGFR and AKI, highlighting that high eGFR is an under-recognized risk factor for AKI and long-term adverse outcomes in STEMI patients. These findings underscore the need for enhanced clinical vigilance and tailored management strategies for PCI patients with high preoperative eGFR. CLINICAL TRIAL REGISTRATION:NCT03510832.

Coronary artery disease (CAD) remains the leading cause of morbidity and mortality globally, placing a substantial burden on individuals and healthcare systems. While magnetocardiography (MCG) has emerged as a promising noninvasive modality for detecting CAD, its adoption is hindered by limited datasets and a lack of standardized interpretive criteria. In this study, we enrolled 624 individuals (205 healthy controls and 419 CAD patients) using a self-developed 36-channel spin-exchange relaxation-free MCG device. Manual expert analysis of time-line magnetocardiograms yielded 20 visually interpretable diagnostic indexes, which were extracted per channel across the 36 channels recorded per subject. Predictive models were constructed using these features via six machine learning algorithms: Random Forest, Support Vector Machine, Multilayer Perceptron, LightGBM, GBDT, and Naive Bayes. All models were developed using stratified 10-fold cross-validation on the internal dataset from Qilu Hospital. The final performance of the models was further evaluated on independent test cohorts collected from 3 additional medical centers.Across the four medical centers, LightGBM, GBDT, and Random Forest consistently demonstrated the most robust diagnostic performance, achieving AUC values of up to 0.9647 in the training set and up to 1.000 in external validation, while Naive Bayes exhibited the lowest overall efficacy (AUC 0.7124-0.8318) and Support Vector Machine and Multilayer Perceptron showed notable inter-center variability.These findings not only establish a robust framework for decoding MCG in CAD but also validate that MCG waveform morphological indicators analogous to those used in electrocardiography are equally applicable for CAD diagnosis. They further confirm that morphological analysis combined with machine learning enables accurate, noninvasive CAD detection, boosting MCG’s clinical translation potential.

AIM:This study aimed to evaluate whether the COVID-19 pandemic affected out-of-hospital cardiac arrest (OHCA) care and outcomes across multiple regions in China, despite the country's strict containment measures. METHODS:Data from the BASeline Investigation of Out-of-hospital Cardiac Arrest (BASIC-OHCA) Utstein Registry between 2019 and 2020 were analyzed. OHCA cases from 18 Emergency Medical Services (EMS) agencies were included. The primary outcome was survival to hospital discharge or 30 days, while secondary outcomes included return of spontaneous circulation (ROSC), and favorable neurologic outcome (Cerebral Performance Category [CPC] score 1-2). Three periods were compared: pre-COVID-19, outbreak, and regular prevention and control. Multilevel logistic regression adjusted for Utstein variables and center-level clustering was used. RESULTS:A total of 16,595 patients received CPR (pre-COVID-19 n = 3890; outbreak n = 5939; regular prevention and control n = 6766). Survival to hospital discharge or 30 days did not differ significantly across periods. ROSC was lower during the outbreak (5.3% vs. 3.6%, AOR 0.80, P = 0.045) and regular prevention and control periods (5.3% vs. 3.5%, AOR 0.80, P = 0.045). Bystander CPR and dispatcher-assisted CPR were significantly less frequent during the regular prevention and control period. EMS response time was longer in the regular prevention and control period (median 12 min vs. 11 min; AOR 1.25, P = 0.006). CONCLUSION:The COVID-19 pandemic impacted the EMS system in China, reducing bystander CPR, dispatcher-assisted CPR, and ROSC, and increasing EMS response times. However, survival and neurological outcomes did not deteriorate significantly.

Heart failure (HF) persists as the primary cause of death among patients recovering from acute myocardial infarction (AMI). Protein ubiquitination has been implicated as a key modulator of HF pathogenesis, yet the role of ubiquitination in the Aldh2 rs671 mutant - the most common single-nucleotide variant in human populations - remains poorly understood. We discovered TRIM21 as a previously unrecognized E3 ubiquitin ligase for the ALDH2 rs671 mutant and elucidated its mechanistic involvement in HF progression. Using Aldh2 BM chimeric mice to model AMI, we observed that WT mice transplanted with Aldh2 rs671 donor BM developed severe myocardial fibrosis and markedly reduced cardiac systolic function 2 weeks after infarction compared with controls. This phenotype arose from defective macrophage efferocytosis caused by myeloid-specific Aldh2 rs671 mutation. Through high-resolution mass spectrometry proteomics, we identified TRIM21 as the E3 ligase targeting ALDH2. TRIM21 catalyzed K48-linked ubiquitination at ALDH2 lysine 73. Macrophage-specific Trim21 knockdown via AAV-shTrim21 reversed both the exacerbated cardiac fibrosis and systolic dysfunction by restoring macrophage efferocytosis. These findings delineate the upstream E3 ubiquitin ligase and the ubiquitination site of ALDH2, revealing a potential therapeutic target for HF.

BACKGROUND AND AIMS:Prognostic stratification in older adults with coronary artery disease (CAD) remains challenging, and existing clinical risk scores have limitations in this population. We aimed to identify and validate a novel plasma metabolomic signature for 3-year all-cause mortality and assess its incremental value over established clinical risk factors. METHODS AND RESULTS:We performed a secondary analysis of data from two temporally distinct, prospectively collected cohorts from the Emory Cardiovascular Biobank (training: n = 269; validation: n = 190). The primary endpoint was 3-year all-cause mortality. A stability-based LASSO algorithm with permutation testing was used to select a robust prognostic signature from 1150 harmonized metabolomic features. The performance of a pre-specified Cox proportional hazards model was assessed for discrimination and calibration in the independent validation cohort. Net Reclassification Improvement (NRI) and Integrated Discrimination Improvement (IDI) were calculated to quantify added prognostic value over a clinical risk model. A robust 11-metabolite signature was identified. In the independent validation cohort, the pre-specified Cox model demonstrated strong discrimination for 3-year mortality (time-dependent AUC: 0.716; 95% CI: 0.630-0.802) and good calibration. Compared to a model with established clinical risk factors alone, the addition of the 11-metabolite signature resulted in a significant improvement in risk reclassification (NRI: 0.322, 95% CI: 0.190-0.447; IDI: 0.199, 95% CI: 0.127-0.283; both p < 0.001). CONCLUSION:A validated 11-metabolite signature improves long-term mortality risk stratification in older adults with CAD beyond established clinical measures, providing a basis for a new blood-based prognostic tool.

Magnetocardiography (MCG) provides non-contact, radiation-free recordings of cardiac magnetic activity, but its clinical translation has been hindered by the lack of standardized and interpretable visual criteria. Here we propose an interpretable visual computing framework that converts one-dimensional MCG timeline maps (TLMs) into a standardized visual lexicon for coronary artery stenosis diagnosis. Inspired by the visual logic of electrocardiographic ischemia interpretation, we defined nine quantifiable TLM indices capturing amplitude, direction, and waveform-ratio abnormalities across a 36-channel MCG array. We evaluated this framework in 4,438 individuals, including 2,673 patients with angiographically confirmed obstructive coronary artery disease and 1,765 ECG-negative reference participants. Data from one hospital campus were used for model development and internal validation, while two independent cohorts were used for external validation. Vessel-specific random forest models integrating TLM indices and spatial channel information achieved robust diagnostic performance for LAD, LCX, RCA, and LM stenosis, with particularly strong performance in ECG-negative individuals. Visual–anatomical interpretation and SHAP analyses showed that the model relied on spatially localized waveform abnormalities consistent with coronary perfusion territories. These findings establish a reproducible visual lexicon for MCG-TLM interpretation and demonstrate its potential as an interpretable adjunctive tool for non-invasive coronary risk stratification.

Cardiac arrest occurs rapidly, requires high timeliness in treatment, and has a poor prognosis. Cardiopulmonary resuscitation (CPR) is a key intervention to save the lives of patients with cardiac arrest. In recent years, CPR has made significant progress with the update of evidence-based research and technological development. The evolution of specific recommendations in international guidelines reflects the changes in the certainty of and understanding about emerging evidence. To unravel the logical progression of cognitive development in the CPR field, this review systematically clarifies the evidence base and evolutionary history of recommendations for core components of adult CPR, including the chain of survival, interruptions in compressions, high-quality CPR, early defibrillation, dispatcher-assisted CPR, extracorporeal CPR, and temperature control. Moreover, it identifies knowledge gaps and proposes potential development directions to provide systemic insights and strategic thinking in CPR for providers, researchers, and healthcare administrators.

Background: The influence of P2RY12 polymorphisms and expression on the ischemia-bleeding balance in patients with ST-segment elevation myocardial infarction (STEMI) remains poorly defined. Objectives: To evaluate the associations of P2RY12 with major adverse cardiovascular events (MACE) and bleeding risk in STEMI patients treated with ticagrelor. Methods: This prospective cohort study enrolled patients with STEMI who underwent percutaneous coronary intervention and received ticagrelor therapy between 2018 and 2020. The main outcomes were MACEs and bleeding events within 2 years. A Cox model was used to examine the effects of P2RY12 polymorphisms on both events. Additionally, the P2RY12 expression scores were constructed to further evaluate the association between its expression levels and both events. Results: A total of 1828 STEMI patients were included, with 194 MACE (10.61%) and 237 bleeding events (12.96%) recorded. Compared with the rs10755105 C/C, the MACE hazard ratios (HRs) (95% CI) of T/C and T/T carriers were 0.57 (0.42-0.79) and 0.67 (0.45-1.00), respectively, while for bleeding, they were 1.35 (0.99-1.85) and 1.53 (1.06-2.20), respectively. P2RY12 expression scores showed a U-shaped relationship with MACE risk and an inverse U-shaped association with bleeding (P-nonlinear < .05). Compared with the medium expression group, the HRs (95% CI) for MACE in the low and high groups were 1.84 (1.28-2.66) and 1.40 (0.83-2.34), respectively, and for bleeding were 0.77 (0.58-1.01) and 0.53 (0.33-0.85), respectively. Conclusion: Both rs10755105 and the P2RY12 expression score show opposing effects on ischemic and bleeding risks. The identified non-linear relationships provide novel insights for refined risk stratification in STEMI.

Regulator of calcineurin 1 (RCAN1) is an RNA-binding protein with diverse functions, the regulatory mechanisms underlying mitochondrial function in ischemic neuronal injury remain only partially understood. This study identified significantly elevated plasma RCAN1.1 levels in acute ischemic stroke (AIS) patients and demonstrated that mitochondrial translocation of RCAN1.1L ‌within the ischemic penumbra‌ aggravates cerebral infarction ‌by promoting pathological mitochondrial fission and neuronal apoptosis‌. Mechanistically, in AIS cell and mouse models, multi-omics screening identified activating transcription factor 2 (ATF2) mRNA as a critical downstream target of RCAN1.1L. RCAN1.1L binds to the 2915-2935 nucleotide in the 3’-untranslated region (UTR) of ATF2 mRNA, stabilizing its expression and promoting the accumulation of mitochondrial ATF2 (mtATF2) protein. MtATF2, in turn, binds to and upregulates mitochondrial fission 1 (FIS1) protein, thereby enhancing mitochondrial fission and driving intrinsic apoptosis. Notably, the RNA aptamer R1SR13 competitively binds to RCAN1.1L protein with ATF2 mRNA, exerting neuroprotective effects by disrupting the RCAN1.1L-mtATF2-FIS1 axis. These findings identify RCAN1.1L as an upstream regulator of ATF2 mRNA stability-mediated mitochondrial fission and apoptosis in ischemic penumbra neurons and highlight R1SR13 as a promising therapeutic candidate for preserving neuronal mitochondrial integrity.

AIM:To evaluate admission pulse pressure (PP) as an independent predictor of 12-month mortality in acute coronary syndrome (ACS) patients undergoing percutaneous coronary intervention (PCI), and to explore its joint effect with left ventricular ejection fraction (LVEF). METHODS:This observational study analyzed 2213 consecutive ACS patients from the BIPass study who underwent PCI. Patients were stratified by LVEF (>50% vs. ≤50%) and PP levels (≤ 40 mmHg, 40 < PP ≤ 60 mmHg, 60 < PP ≤ 80 mmHg, and > 80 mmHg). Primary endpoint was cardiac death, secondary endpoint was 12-month all-cause death. Restricted cubic spline (RCS) and Cox models assessed PP-mortality associations after adjusting for confounders; PP-LVEF interaction was visualized via heatmap and 3D surface plot. RESULTS:During follow-up, 37 all-cause deaths (1.67%) and 22 cardiac deaths (0.99%) were recorded. RCS confirmed a U-shaped PP-12-month mortality association (lowest risk: 41-60 mmHg). Multivariable analysis showed low PP (≤ 40 mmHg; adjusted HR = 18.21, 95% CI:1.65-201.01, P = 0.018) and high PP (> 80 mmHg; adjusted HR = 18.91, 95% CI:2.05-174.93, P = 0.010) independently predicted cardiac death. In LVEF ≤50% patients, extreme PP elevated cardiac death (P = 0.004) and all-cause death (P = 0.044); in LVEF >50% patients, only high PP increased outcomes (cardiac death: P = 0.034; all-cause death: P = 0.028), with low PP showing no significance. CONCLUSIONS:Admission PP has a U-shaped association with 12-month mortality in post-PCI ACS patients. Reduced LVEF amplifies extreme PP's adverse effects. Integrated PP-LVEF assessment enhances risk stratification and guides personalized management.

Background: The burden of early-onset cardiovascular disease (CVD) is increasing, but how intersecting social determinants shape this risk in US young adults is unclear. We quantified intersectional inequities in early-onset CVD prevalence and examined their temporal changes following the COVID-19 pandemic in US. Methods: In this retrospective serial cross-sectional study of 1,030,504 US adults aged 18-44 (BRFSS 2015-2024), we employed Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA). Individuals were nested within 240 strata defined by sex, race/ethnicity, education, income, and insurance. The variance partition coefficient (VPC) and median odds ratio (MOR) quantified disparities. Models were stratified into pre- and post-pandemic periods. Findings: The weighted prevalence of early-onset CVD was 2.1%. The variance components model revealed substantial between-stratum heterogeneity (VPC, 23.5%; MOR, 2.60). Predicted CVD probabilities ranged over 400-fold across strata (0.04%-15.91%), with the highest risk found in uninsured, low-income, low-education Asian males. Additive main effects explained only 44.6% of this inequality (PCV). Of 235 strata, 99 (42.1%) exhibited significant intersectional effects (58 penalties, 41 protections), with Asian adults featuring prominently at both risk extremes. From the pre- to post-pandemic period, intersectional inequities widened substantially, with the MOR increasing from 3.43 to 4.19 (a 22.2% relative increase). Interpretation: Young US adults face vast, widening, and largely non-additive intersectional inequities in early-onset CVD. Risk is exceptionally concentrated in multiply-marginalized strata, and the post-pandemic exacerbation of these disparities demands a paradigm shift from individual risk management to structurally competent, equity-focused preventive strategies.

Despite numerous therapeutic strategies targeting specific programmed cell death pathways, effectively eliminating malignant colorectal cancer (CRC) remains a significant challenge. Disulfidptosis, a newly identified form of cell death, is characterized by rapid NADPH depletion and abnormal disulfide bond formation in cytoskeletal proteins in cells with high SLC7A11 expression under glucose starvation. Given the aberrant expression of SLC7A11 and the hypermetabolic phenotype of CRC cells, targeting the disulfidptosis pathway offers a promising therapeutic approach for CRC treatment. Here, we developed a binuclear ruthenium complex, RuSSRu, bridged by a disulfide bond, to effectively induce the disulfidptosis pathway in CRC cells. Under two-photon excitation, RuSSRu generates reactive oxygen species (ROS), leading to lysosomal damage and initiating cellular escape mechanisms. Crucially, this process triggers a cascade of metabolic disruptions, including an accumulation of disulfide bonds and ROS-induced NADPH depletion, ultimately resulting in cytoskeletal collapse and disulfidptosis. The synergistic interaction between disulfidptosis and lysosomal damage-induced apoptosis amplified tumor cell death, unveiling a novel mechanism and a versatile therapeutic strategy platform for CRC management.

In recent years, venovenous extracorporeal membrane oxygenation (VV-ECMO) has emerged as a critical intervention in the management of adult respiratory failure, with its clinical application expanding at a rapid pace annually. For critically ill patients receiving VV-ECMO support, achieving and maintaining a balance between oxygen supply and oxygen consumption is of paramount importance. Oxygen supply primarily relies on cardiac output and arterial oxygen content; notably, in patients under VV-ECMO support, arterial oxygen content is closely linked to the parameter configurations of both VV-ECMO and mechanical ventilators. Therefore, based on national and industrial needs, this document has been formulated by integrating the latest advancements and practical experience in this field from both domestic and international sources. Its core objectives are to standardize the adjustment of oxygen supply during the combined use of mechanical ventilators and VV-ECMO, provide unambiguous guidance for healthcare professionals, and ultimately enhance the success rate in the treatment of severe respiratory conditions.