Background: Exercise training has been extensively studied in heart failure (HF) and psychological disorders, which has been shown to worsen each other. However, our understanding of how exercise simultaneously protect heart and brain of HF patients is still in its infancy. The purpose of this study was to take advantage of big data techniques to explore hotspots and frontiers of mechanisms that protect the heart and brain simultaneously through exercise training.Methods: We studied the scientific publications on related research between January 1, 2003 to December 31, 2020 from the WoS Core Collection. Research hotspots were assessed through open-source software, CiteSpace, Pajek, and VOSviewer. Big data analysis and visualization were carried out using R, Cytoscape and Origin.Results: From 2003 to 2020, the study on HF, depression, and exercise simultaneously was the lowest of all research sequences (two-way ANOVAs, p < 0.0001). Its linear regression coefficient r was 0.7641. The result of hotspot analysis of related keyword-driven research showed that inflammation and stress (including oxidative stress) were the common mechanisms. Through the further analyses, we noted that inflammation, stress, oxidative stress, apoptosis, reactive oxygen species, cell death, and the mechanisms related to mitochondrial biogenesis/homeostasis, could be regarded as the primary mechanism targets to study the simultaneous intervention of exercise on the heart and brain of HF patients with depression.Conclusions: Our findings demonstrate the potential mechanism targets by which exercise interferes with both the heart and brain for HF patients with depression. We hope that they can boost the attention of other researchers and clinicians, and open up new avenues for designing more novel potential drugs to block heart-brain axis vicious circle.

International scientific collaborations have always been regarded as critical actions to address global pandemics, however, there was an obvious uncertainty between international collaboration and the COVID-19 control. We aim to combine digital data-based strategies to produce meaningful and advanced insights into the imbalance between COVID-19 and international collaboration, as well as reveal possible influencing factors, and ultimately enhance global collaboration. We conducted three retrospective cohort studies using respectively COVID-19 data from WHO, a complete dataset of scientific publications on coronavirus-related research from WoS, and daily data from Google Trends (GT). The results of geovisualization and spatiotemporal analysis revealed that the global COVID19 pandemic still remains serious. The global issue of imbalance between international collaborations and pandemic does exit, and the nations with good pandemic control had their own characteristics in above-mentioned correlation. Digital epidemiology provides, at least in part, evidence-based assessment and scientific advice to understand the imbalance between international collaborations and COVID-19. Our investigation demonstrates that transdisciplinary conversation through digital data-based strategies can help us fully understand the complex factors influencing the effectiveness of international scientific collaboration, thus facilitating the global response to COVID-19.

As a self-initiating, self-sustaining, and low-cost treatment for patients with heart failure, how voluntary exercise plays its roles in interfering with the pathophysiologic pathways associated with HFpEF is still largely unknown. The results of this study indicate that long-term voluntary exercise can effectively antagonize acute and chronic dual-energy stress and avoid diastolic function limitation caused by pathological ventricular remodeling.

Background: Traditional CHA₂DS₂-VASc scoring has well-recognized limitations in thromboembolic risk assessment for atrial fibrillation (AF), particularly in low-score patients who nevertheless thrombose, high-score event-free individuals, cancer patients, and post-ablation cohorts. The left atrial appendage (LAA) is the source of 98% of thrombi in non-valvular AF and exhibits marked inter-individual morphological and hemodynamic variability that traditional scores completely ignore. Aims: This narrative review critically evaluates current evidence on LAA morphology, hemodynamics, computational fluid dynamics/fluid-structure interaction (CFD/FSI) studies, and digital twin technology, and proposes a mechanism-driven, individualized risk assessment framework for AF-related thromboembolism. Methods: A literature search was conducted in PubMed/MEDLINE and Web of Science (1990–May 2026) using combinations of keywords related to LAA morphology, hemodynamics, AF, and thromboembolism. Priority was given to landmark original studies, high-quality observational studies with multivariable adjustment, meta-analyses, and contemporary CFD/digital twin studies. A narrative synthesis was adopted owing to heterogeneity in study designs and outcomes. Results: LAA morphological subtypes are associated with long-term stroke risk, with chicken-wing being protective (OR 0.21, 95% CI 0.05–0.91) and cauliflower carrying the highest risk (OR 8.02, 95% CI 0.92–27.86). However, risk is highly context-dependent, with chicken-wing unexpectedly increasing peri-ablation thromboembolic risk (OR 7.2, 95% CI 1.35–38.33) and windsock morphology independently predicting post-ablation AF recurrence (OR 2.72, 95% CI 1.21–6.12). Importantly, traditional morphological classification does not correlate directly with blood stasis ( p = 0.365), whereas quantitative geometric parameters such as trabecular number, normalized stroke volume, and ostial area are far more sensitive predictors (R² = 74%). Digital twins integrating multimodal clinical, morphological, and hemodynamic data identify a high-risk phenogroup with a 70% thrombus history rate. Conclusion: Based on these findings, we propose a practical two-tier assessment framework combining basic morphological classification with multimodal refined evaluation (digital twin) for intermediate-/high-risk or clinically challenging cases. This framework represents a paradigm shift from static clinical scores toward mechanism-driven, individualized risk management. Prospective validation of this approach is now warranted.

Purpose Given the large number of patients with primary advanced ovarian serous cystadenocarcinoma (OSC) undergoing lymphadenectomy, it is necessary to explore the intrinsic significance of this procedure to improve the quality of precision medicine. Methods SEER database, epidemiological analysis, continuous landmark analysis, principal component analysis, COX regression and matrix analysis were performed to explore the weight changes of treatment, long-term effects, specific risk factors, and the significance of lymph node examination, positive lymph node count and ratio (LNR) for patients. Results Of the total 8673 patients who underwent debulking surgery, approximately 46.5% underwent additional lymphadenectomy. Through PCA, we found that FIGO/M staging, residual tumor volume/size, T/N staging, age and grade were extremely important risk factors for patients. Furthermore, Cox regression analysis showed that N, histology, residual tumor volume, systemic/surgery sequence, laterality, and marital status influenced the prognostic impact of lymphadenectomy compared with self-control. The LOESS fitting curve showed that when the number of examinations > 40, the beneficial effect of lymph nodes examination on survival time began to diminish in the survivor group, while showed a downward trend in the death cases. Additionally, LNR was found to be significantly associated with survival time and vital status, while lymph node examination was only significantly associated with survival time. Finally, residual foci size was found to be significantly associated with LNR and lymph node examination, but not with positive lymph nodes. Conclusions A detailed assessment of lymphadenectomy may have implications for clinical gynecologic practices and precision medicine.