Cancer screening in hospitalized ischemic stroke patients: a multicenter study focused on multiparametric analysis to improve management of occult cancers.

Background/aims: The reciprocal promotion of cancer and stroke occurs due to changes in shared risk factors, such as metabolic pathways and molecular targets, creating a "vicious cycle." Cancer plays a direct or indirect role in the pathogenesis of ischemic stroke (IS), along with the reactive medical approach used in the treatment and clinical management of IS patients, resulting in clinical challenges associated with occult cancer in these patients. The lack of reliable and simple tools hinders the effectiveness of the predictive, preventive, and personalized medicine (PPPM/3PM) approach. Therefore, we conducted a multicenter study that focused on multiparametric analysis to facilitate early diagnosis of occult cancer and personalized treatment for stroke associated with cancer. Methods: Admission routine clinical examination indicators of IS patients were retrospectively collated from the electronic medical records. The training dataset comprised 136 IS patients with concurrent cancer, matched at a 1:1 ratio with a control group. The risk of occult cancer in IS patients was assessed through logistic regression and five alternative machine-learning models. Subsequently, select the model with the highest predictive efficacy to create a nomogram, which is a quantitative tool for predicting diagnosis in clinical practice. Internal validation employed a ten-fold cross-validation, while external validation involved 239 IS patients from six centers. Validation encompassed receiver operating characteristic (ROC) curves, calibration curves, decision curve analysis (DCA), and comparison with models from prior research. Results: The ultimate prediction model was based on logistic regression and incorporated the following variables: regions of ischemic lesions, multiple vascular territories, hypertension, D-dimer, fibrinogen (FIB), and hemoglobin (Hb). The area under the ROC curve (AUC) for the nomogram was 0.871 in the training dataset and 0.834 in the external test dataset. Both calibration curves and DCA underscored the nomogram's strong performance. Conclusions: The nomogram enables early occult cancer diagnosis in hospitalized IS patients and helps to accurately identify the cause of IS, while the promotion of IS stratification makes personalized treatment feasible. The online nomogram based on routine clinical examination indicators of IS patients offered a cost-effective platform for secondary care in the framework of PPPM. Supplementary Information: The online version contains supplementary material available at 10.1007/s13167-024-00354-8.

miRNA-211-5p inhibition enhances the protective effect of hucMSC-derived exosome in Aß1-40 -induced SH-SY5Y cells by increasing NEP expression.

Exosomes derived from human umbilical cord mesenchymal stem cells (hucMSCs) could alleviate Alzheimer's disease (AD) defects. Additionally, engineered exosomes are more effective in treating diseases. In this study, we established an in vitro model of AD by treating SH-SY5Y cells with Aß1-40 . We observed that incubation with hucMSC-derived exosomes effectively protected SH-S5Y5 cells from Aß1-40 -induced damage. Since NEP plays a central role in suppressing AD development, we screened NEP-targeting miRNAs that are differentially expressed in control and AD patients. We identified miR-211-5p as a potent repressor of NEP expression. Exosomes purified from hucMSCs overexpressing miR-211-5p inhibitor exhibited significantly greater efficiency than control exosomes in mitigating the injury caused by Aß1-40 treatment. However, this enhanced protective effect was nullified by the knockdown of NEP. These observations demonstrate that inhibition of miR-211-5p has the potential to improve the efficacy of hucMSC-derived exosomes in AD treatment by increasing NEP expression.

Adoption of Magnetic Resonance Image Features under Segmentation Algorithm in Effect Evaluation of Ginkgo Diterpenoid Lactone Glucamine Injection in Treatment of Cerebral Infarction.

Magnetic resonance imaging (MRI) image segmentation based on a segmentation algorithm was performed to assess neurological function in patients with acute cerebral infarction, to investigate the efficacy evaluation of Ginkgo diterpene lactones meglumine injection (GDLI) in the treatment of cerebral infarction and the efficiency of MRI image segmentation algorithm. First, the results of the fast semisupervised segmentation algorithm (algorithm group) and traditional processing (control group) were compared and analyzed. The recall rate, accuracy, recognition accuracy, and segmentation time of the two groups were compared. The control group was given conventional treatment, while the algorithm group was given GDLI based on conventional treatment. Finally, the difference in serum vascular endothelial growth factor (VEGF), hypoxia-inducible factor-la (HIF-la), angiotensin (Ang)-1, Ang-2, and interleukin (IL)-6 protein concentration was analyzed after treatment. The algorithm evaluation results showed that the accuracy and recall rate of MRI images recognized by the algorithm group fluctuate at 90%. In the control group, the accuracy and recall rate of MRI image results fluctuated at 80%, and the data were statistically different (p < 0.05). The clinical index test results showed that the serum VEGF content of the test group was higher than that of the control group, and the data was statistically different (p < 0.05). In addition, the cerebral blood flow (CBF) and cerebral blood volume (CBV) of the lesion side of the algorithm group were greatly higher than those of the control group on the 30th day, and the differences were significant (p < 0.05). There was little difference between the method presented in this study and the manual delineation by a physician. Compared with traditional manual segmentation, this method greatly reduced the time required for the segmentation of lesions. The diagnostic specificity, sensitivity, and accuracy of the images segmented by the fast semisupervised algorithm were higher than those of the conventional method, and the diagnostic accuracy of acute cerebral infarction was high. In addition, it was sensitive and accurate to detect acute cerebral infarction, which provided a reliable reference for early diagnosis and condition judgment of patients.

Gut microbial metabolite TMAO portends prognosis in acute ischemic stroke.

BACKGROUND: Over the recent years, the role of trimethylamine N-oxide (TMAO) as a gut-derived metabolite mediating cardiovascular disease pathogenesis has been under particularly intense scrutiny. The aim was to explore whether TMAO levels were associated with clinical severity or functional outcome in Chinese patients with ischemic stroke. METHODS: This is a single-center, prospective cohort study from Xiamen, China. We examined the relationship between fasting TMAO and 2 of its nutrient precursors, choline and betaine, vs. 3-month functional outcome and mortality in 351 first-ever patients with acute ischemic stroke. RESULTS: The median value of the plasma level of TMAO was 6.1 µM (IQR, 3.7-9.9 µM), which was higher than in those control cases (4.0; 2.4-5.9 µM). Patients with a poor outcome and nonsurvivors had significantly increased TMAO levels on admission (P < 0.001). Following adjustments for traditional risk factors, increased TMAO concentrations remained predictive of both poor outcome and mortality risks in stroke patients [e.g., quartiles 4 vs 1, odd ratio 5.65 (95% CI, 2.87-13.45), P < 0.001; and 5.84 (95% CI, 3.05-16.12), P < 0.001, respectively]. In multivariate analysis, TMAO was an independent predictor of functional outcome and mortality and improved the prognostic accuracy of the NIHSS to predict functional outcome (combined areas under the curve, 0.82; 95% CI 0.77-0.89, P = 0.003) and mortality (combined areas under the curve, 0.85; 95% CI: 0.80-0.90, P = 0.002). CONCLUSIONS: Fasting plasma concentrations of gut microbial TMAO are higher in patients with ischemic stroke and portend higher poor functional outcome events and mortality.