Atherosclerotic plaque vulnerability quantification system for clinical and biological interpretability

AI hybrid survival assessment for advanced heart failure patients with renal dysfunction

Renal dysfunction (RD) often characterizes the worse course of patients with advanced heart failure (AHF). Many prognosis assessments are hindered by researcher biases, redundant predictors, and lack of clinical applicability. In this study, we enroll 1736 AHF/RD patients, including data from Henan Province Clinical Research Center for Cardiovascular Diseases (which encompasses 11 hospital subcenters), and Beth Israel Deaconess Medical Center. We developed an AI hybrid modeling framework, assembling 12 learners with different feature selection paradigms to expand modeling schemes. The optimized strategy is identified from 132 potential schemes to establish an explainable survival assessment system: AIHFLevel. The conditional inference survival tree determines a probability threshold for prognostic stratification. The evaluation confirmed the system's robustness in discrimination, calibration, generalization, and clinical implications. AIHFLevel outperforms existing models, clinical features, and biomarkers. We also launch an open and user-friendly website www.hf-ai-survival.com , empowering healthcare professionals with enhanced tools for continuous risk monitoring and precise risk profiling.

Molecular subtypes of ischemic heart disease based on circadian rhythm

Coronary atherosclerotic heart disease (CAD) is among the most prevalent chronic diseases globally. Circadian rhythm disruption (CRD) is closely associated with the progression of various diseases. However, the precise role of CRD in the development of CAD remains to be elucidated. The Circadian rhythm disruption score (CRDscore) was employed to quantitatively assess the level of CRD in CAD samples. Our investigation revealed a significant association between high CRDscore and adverse prognosis in CAD patients, along with a substantial correlation with CAD progression. Remarkably distinct CRDscore distributions were also identified among various subtypes. In summary, we have pioneered the revelation of the relationship between CRD and CAD at the single-cell level and established reliable markers for the development, treatment, and prognosis of CAD. A deeper understanding of these mechanisms may offer new possibilities for incorporating "the therapy of coronary heart disease based circadian rhythm" into personalized medical treatment regimens.

The cytoplasmic sensor, the AIM2 inflammasome: A precise therapeutic target in vascular and metabolic diseases

Cardio-cerebrovascular diseases encompass pathological changes in the heart, brain and vascular system, which pose a great threat to health and well-being worldwide. Moreover, metabolic diseases contribute to and exacerbate the impact of vascular diseases. Inflammation is a complex process that protects against noxious stimuli but is also dysregulated in numerous so-called inflammatory diseases, one of which is atherosclerosis. Inflammation involves multiple organ systems and a complex cascade of molecular and cellular events. Numerous studies have shown that inflammation plays a vital role in cardio-cerebrovascular diseases and metabolic diseases. The absent in melanoma 2 (AIM2) inflammasome detects and is subsequently activated by double-stranded DNA in damaged cells and pathogens. With the assistance of the mature effector molecule caspase-1, the AIM2 inflammasome performs crucial biological functions that underpin its involvement in cardio-cerebrovascular diseases and related metabolic diseases: The production of interleukin-1 beta (IL-1β), interleukin-18 (IL-18) and N-terminal pore-forming Gasdermin D fragment (GSDMD-N) mediates a series of inflammatory responses and programmed cell death (pyroptosis and PANoptosis). Currently, several agents have been reported to inhibit the activity of the AIM2 inflammasome and have the potential to be evaluated for use in clinical settings. In this review, we systemically elucidate the assembly, biological functions, regulation and mechanisms of the AIM2 inflammasome in cardio-cerebrovascular diseases and related metabolic diseases and outline the inhibitory agents of the AIM2 inflammasome as potential therapeutic drugs.

An assessment system for clinical and biological interpretability in ulcerative colitis

Ulcerative colitis (UC) is a serious inflammatory bowel disease (IBD) with high morbidity and mortality worldwide. As the traditional diagnostic techniques have various limitations in the practice and diagnosis of early ulcerative colitis, it is necessary to develop new diagnostic models from molecular biology to supplement the existing methods. In this study, we developed a machine learning-based synthesis to construct an artificial intelligence diagnostic model for ulcerative colitis, and the correctness of the model is verified using an external independent dataset. According to the significantly expressed genes related to the occurrence of UC in the model, an unsupervised quantitative ulcerative colitis related score (UCRScore) based on principal coordinate analysis was established. The UCRScore is not only highly generalizable across UC bulk cohorts at different stages, but also highly generalizable across single-cell datasets, with the same effect in terms of cell numbers, activation pathways and mechanisms. As an important role of screening genes in disease occurrence, based on connectivity map analysis, 5 potential targeting molecular compounds were identified, which can be used as an additional supplement to the therapeutic of UC. Overall, this study provides a potential tool for differential diagnosis and assessment of bio-pathological changes in UC at the macroscopic level, providing an opportunity to optimize the diagnosis and treatment of UC.