Quality of Life Research - The COVID-19 pandemic might add to the stressors experienced by people living with rheumatic diseases. This study aimed to examine rheumatic patients’ functional... 相似文献
Intratumor heterogeneity is a main cause of the dismal prognosis of glioblastoma (GBM). Yet, there remains a lack of a uniform assessment of the degree of heterogeneity. With a multiscale approach, we addressed the hypothesis that intratumor heterogeneity exists on different levels comprising traditional regional analyses, but also innovative methods including computer-assisted analysis of tumor morphology combined with epigenomic data. With this aim, 157 biopsies of 37 patients with therapy-naive IDH-wildtype GBM were analyzed regarding the intratumor variance of protein expression of glial marker GFAP, microglia marker Iba1 and proliferation marker Mib1. Hematoxylin and eosin stained slides were evaluated for tumor vascularization. For the estimation of pixel intensity and nuclear profiling, automated analysis was used. Additionally, DNA methylation profiling was conducted separately for the single biopsies. Scoring systems were established to integrate several parameters into one score for the four examined modalities of heterogeneity (regional, cellular, pixel-level and epigenomic). As a result, we could show that heterogeneity was detected in all four modalities. Furthermore, for the regional, cellular and epigenomic level, we confirmed the results of earlier studies stating that a higher degree of heterogeneity is associated with poorer overall survival. To integrate all modalities into one score, we designed a predictor of longer survival, which showed a highly significant separation regarding the OS. In conclusion, multiscale intratumor heterogeneity exists in glioblastoma and its degree has an impact on overall survival. In future studies, the implementation of a broadly feasible heterogeneity index should be considered. 相似文献
In clinical and epidemiological studies, there is a growing interest in studying the heterogeneity among patients based on longitudinal characteristics to identify subtypes of the study population. Compared to clustering a single longitudinal marker, simultaneously clustering multiple longitudinal markers allow additional information to be incorporated into the clustering process, which reveals co-existing longitudinal patterns and generates deeper biological insight. In the current study, we propose a Bayesian consensus clustering (BCC) model for multivariate longitudinal data. Instead of arriving at a single overall clustering, the proposed model allows each marker to follow marker-specific local clustering and these local clusterings are aggregated to find a global (consensus) clustering. To estimate the posterior distribution of model parameters, a Gibbs sampling algorithm is proposed. We apply our proposed model to the primary biliary cirrhosis study to identify patient subtypes that may be associated with their prognosis. We also perform simulation studies to compare the clustering performance between the proposed model and existing models under several scenarios. The results demonstrate that the proposed BCC model serves as a useful tool for clustering multivariate longitudinal data. 相似文献
The exercise pressor reflex is a feedback mechanism engaged upon stimulation of mechano- and metabosensitive skeletal muscle afferents. Activation of these afferents elicits a reflex increase in heart rate, blood pressure, and ventilation in an intensity-dependent manner. Consequently, the exercise pressor reflex has been postulated to be one of the principal mediators of the cardiorespiratory responses to exercise. In this updated review, we will discuss classical and recent advancements in our understating of the exercise pressor reflex function in both human and animal models. Particular attention will be paid to the afferent mechanisms and pathways involved during its activation, its effects on different target organs, its potential role in the abnormal cardiovascular response to exercise in diseased states, and the impact of age and biological sex on these responses. Finally, we will highlight some unanswered questions in the literature that may inspire future investigations in the field.
The coronavirus disease 2019 (COVID-19) pandemic has rapidly created widespread impacts on global health and the economy. Data suggest that women are less susceptible to severe illness. However, sex-disaggregated data are incomplete, leaving room for misinterpretation, and focusing only on biologic sex underestimates the gendered impact of the pandemic on women. This narrative review summarizes what is known about gender disparities during the COVID-19 pandemic and the economic, domestic, and health burdens along with overlapping vulnerabilities related to the pandemic. In addition, this review outlines recommended strategies that advocacy groups, community leaders, and policymakers should implement to mitigate the widening gender disparities related to COVID-19. 相似文献