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Background: The identification of efficient predictors for short-term mortality among patients with myocardial infarction (MI) in coronary care units (CCU) remains a challenge. This study seeks to investigate the potential of machine learning (ML) to improve risk prediction and develop a predictive model specifically tailored for 30-day mortality in critical MI patients., Method: This study focused on MI patients extracted from the Medical Information Mart for Intensive Care-IV database. The patient cohort was randomly stratified into derivation ( n  = 1,389, 70%) and validation ( n  = 595, 30%) groups. Independent risk factors were identified through eXtreme Gradient Boosting (XGBoost) and random decision forest (RDF) methodologies. Subsequently, multivariate logistic regression analysis was employed to construct predictive models. The discrimination, calibration and clinical utility were assessed utilizing metrics such as receiver operating characteristic (ROC) curve, calibration plot and decision curve analysis (DCA)., Result: A total of 1,984 patients were identified (mean [SD] age, 69.4 [13.0] years; 659 [33.2%] female). The predictive performance of the XGBoost and RDF-based models demonstrated similar efficacy. Subsequently, a 30-day mortality prediction algorithm was developed using the same selected variables, and a regression model was visually represented through a nomogram. In the validation group, the nomogram (Area Under the Curve [AUC]: 0.835, 95% Confidence Interval [CI]: [0.774-0.897]) exhibited superior discriminative capability for 30-day mortality compared to the Sequential Organ Failure Assessment (SOFA) score [AUC: 0.735, 95% CI: (0.662-0.809)]. The nomogram (Accuracy: 0.914) and the SOFA score (Accuracy: 0.913) demonstrated satisfactory calibration. DCA indicated that the nomogram outperformed the SOFA score, providing a net benefit in predicting mortality., Conclusion: The ML-based predictive model demonstrated significant efficacy in forecasting 30-day mortality among MI patients admitted to the CCU. The prognostic factors identified were age, blood urea nitrogen, heart rate, pulse oximetry-derived oxygen saturation, bicarbonate, and metoprolol use. This model serves as a valuable decision-making tool for clinicians., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2024 Lin, Pan, Yang, Yang, Wang, Zou, Wang, Xiu, Yu, Lu, Zhao and Lu.)

Inflammation, extracellular matrix metabolic dysfunction, and oxidative stress are key pathogenic characteristics of intervertebral disk degeneration (IVDD), a major pathogenic cause of low back pain. Esculetin possesses anti-injury, anti-inflammation, and antinociceptive properties. This study aimed to explore its role in IVDD. In this research, esculetin exhibited little cytotoxicity to human nucleus pulposus cells (NPCs). Moreover, esculetin increased cell viability under IL-1β stimulation but attenuated IL-1β-induced cell apoptosis and caspase-3 activity. Furthermore, IL-1β-evoked increases in intracellular reactive oxygen species and malondialdehyde (MDA) levels, and decreases in superoxide dismutase (SOD) activity were reversed after esculetin treatment, indicating the antioxidative stress efficacy of esculetin. Esculetin alleviated the inhibitory effects of IL-1β on the transcription and protein expression of anabolic biomarkers (collagen II and aggrecan), accompanied by decreases in expression and release of catabolic biomarkers MMP-3 and MMP-13 from NPCs. Moreover, IL-1β exposure enhanced the expression levels of the inflammatory mediator nitric oxide and inflammatory cytokine IL-6 and TNF-α, which were overturned after esculetin treatment. Additionally, esculetin activated the nuclear factor-erythroid 2-related factor 2 (Nrf2)/heme oxygenase 1 (HO-1) to inhibit the activation of nuclear factor κB (NF-κB) signaling in NPCs. Importantly, suppression of Nrf2 signaling reversed the protective efficacy of esculetin against IL-1β-mediated oxidative injury, matrix metabolism disruption, and inflammatory response in NPCs. Together, esculetin may alleviate IL-1β-induced dysfunction in NPCs by regulating the Nrf2/HO-1/NF-kb signaling, indicating its potential as a promising therapeutic agent against IVDD., Competing Interests: The authors declare no competing financial interest., (© 2023 The Authors. Published by American Chemical Society.)