UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: The online version contains supplementary material available at 10.1007/s13167-024-00354-8.

UNASSIGNED: Intravenous leiomyomatosis (IVL) is a rare endocrine-associated tumor with unique characteristics of intravascular invasion. This study aimed to identify reliable biomarkers to supervise the development or recurrence of IVL in the context of predictive, preventive, and personalized medicine (PPPM/3PM).
UNASSIGNED: A total of 60 cases were recruited to detect differentially expressed proteins (DEPs) in serum samples from IVL patients. These cases included those with recurrent IVL, non-recurrent IVL, uterine myoma, and healthy individuals without uterine myoma, with 15 cases in each category. Then, weighted gene co-expression network analysis (WGCNA), lasso-penalized Cox regression analysis (Lasso), trend clustering, and a generalized linear regression model (GLM) were utilized to screen the hub proteins involved in IVL progression.
UNASSIGNED: First, 93 differentially expressed proteins (DEPs) were determined from 2582 recognizable proteins, with 54 proteins augmented in the IVL group, and the remaining proteins declined. These proteins were enriched in the modulation of the immune environment, mainly by activating the function of B cells. After the integrated analyses mentioned above, a model based on four proteins (A0A5C2FUE5, A0A5C2GPQ1, A0A5C2GNC7, and A0A5C2GBR3) was developed to efficiently determine the potential of IVL lesions to progress. Among these featured proteins, our results demonstrated that the risk factor A0A5C2FUE5 was associated with IVL progression (OR = 2.64). Conversely, A0A5C2GPQ1, A0A5C2GNC7, and A0A5C2GBR3 might act in a protective manner and prevent disease development (OR = 0.32, 0.60, 0.53, respectively), which was further supported by the multi-class receiver operator characteristic curve analysis.
UNASSIGNED: Four hub proteins were eventually identified based on the integrated bioinformatics analyses. This study potentiates the promising application of these novel biomarkers to predict the prognosis or progression of IVL by a 3PM approach.
UNASSIGNED: The online version contains supplementary material available at 10.1007/s13167-023-00338-0.

UNASSIGNED: Whether cardiovascular health (CVH) metrics impact longevity with and without cardiovascular diseases (CVDs) has not been well established. This study aimed to investigate the association between CVH metrics and life expectancy in participants free of CVD events. We hypothesized that ideal CVH status was associated with increased life expectancy and assessed the effect of CVH status as a prevention target of longevity in the framework of predictive, preventive, and personalized medicine (PPPM/3PM).
UNASSIGNED: A total of 92,795 participants in the Kailuan study were examined and thereafter followed up until 2020. We considered three transitions (from non-CVD events to incident CVD events, from non-CVD events to mortality, and from CVD events to mortality). The multistate lifetable method was applied to estimate the life expectancy.
UNASSIGNED: During a median follow-up of 13 years, 12,541 (13.51%) deaths occurred. Compared with poor CVH, ideal CVH attenuated the risk of incident CVD events and mortality without CVD events by approximately 58% and 27%, respectively. Women with ideal CVH at age 35 had a 5.00 (3.23-6.77) year longer life expectancy free of CVD events than did women with poor CVH metrics. Among men, ideal CVH was associated with a 6.74 (5.55-7.93) year longer life expectancy free of CVD events.
UNASSIGNED: An ideal CVH status is associated with a lower risk of premature mortality and a longer life expectancy, either in the general population or in CVD patients, which are cost-effective ways for personalized medicine of potential CVD patients. Our findings suggest that the promotion of a higher CVH score or ideal CVH status would result in reduced burdens of CVD events and extended disease-free life expectancy, which offered an accurate prediction for primary care following the concept of PPPM/3PM.
UNASSIGNED: The online version contains supplementary material available at 10.1007/s13167-023-00322-8.

UNASSIGNED: Ginseng, a traditional herbal medicine, has been used for thousands of years to treat various diseases including metabolic syndrome (MS). However, the underlying mechanism(s) of such beneficial actions of ginseng against MS is poorly understood. Emerging evidence indicates a close association of the host gut microbiota with MS. The present study was conducted to examine, whether the beneficial effects of Korean red ginseng (KRG) against MS could be influenced by gut microbial population and whether gut microbial profile could be considered a valuable biomarker for targeted treatment strategy for MS in compliance with the predictive, preventive, and personalized medicine (PPPM / 3PM).
UNASSIGNED: This clinical study was a randomized, double-blind, placebo-controlled trial evaluating the effects of KRG treatment for 8 weeks on patients with MS. The anthropometric parameters, vital signs, metabolic biomarkers, and gut microbial composition through 16S rRNA gene sequencing were assessed at the baseline and endpoint. The impact of KRG was also evaluated after categorizing the subjects into responders and non-responders, as well as enterotypes 1 and 2 based on their gut microbial profile at the baseline.
UNASSIGNED: Fifty out of 60 subjects who meet the MS criteria completed the trial without showing adverse reactions. The KRG treatment caused a significant decrease in systolic blood pressure (SBP). Microbial analysis revealed a decrease in Firmicutes, Proteobacteria, and an increase in Bacteroidetes in response to KRG. In patient stratification analysis, the responders showing marked improvement in the serum levels of lipid metabolic biomarkers TC and LDL due to the KRG treatment exhibited higher population of both the family Lachnospiraceae and order Clostridiales compared to the non-responders. The homeostasis model assessment-insulin resistance (HOMA-IR) and insulin level were decreased in enterotype 1 (Bacteroides-abundant group) and increased in enterotype 2 (prevotella-abundant group) following the KRG treatment.
UNASSIGNED: In this study, the effects of KRG on the glucose metabolism in MS patients were influenced by the relative abundances of gut microbial population and differed according to the individual enterotype. Therefore, the analysis of enterotype categories is considered to be helpful in predicting the effectiveness of KRG on glucose homeostasis of MS patients individually. This will further help to decide on the appropriate treatment strategy for MS, in compliance with the perspective of PPPM.