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IntroductionThe alterations of gut microbiota have been associated with multiple diseases. However, the relationship between gut microbiota and adverse outcomes of hyperlipidemic stroke patients remains unclear. Here we determined the gut microbial signature to predict the poor outcome of acute ischemic stroke (AIS) with hyperlipidemia (POAH).MethodsFecal samples from hyperlipidemic stroke patients were collected, which further analyzed by 16s rRNA gene sequencing. The diversity, community composition and differential gut microbiota were evaluated. The adverse outcomes were determined by modified Rankin Scale (mRS) scores at 3 months after admission. The diagnostic performance of microbial characteristics in predicting adverse outcomes was assessed by receiver operating characteristic (ROC) curves.ResultsOur results showed that the composition and structure of gut microbiota between POAH patients and good outcome of AIS with hyperlipidemia (GOAH) patients were different. The characteristic gut microbiota of POAH patients was that the relative abundance of Enterococcaceae and Enterococcus were increased, while the relative abundance of Lachnospiraceae, Faecalibacterium, Rothia and Butyricicoccus were decreased. Moreover, the characteristic gut microbiota were correlated with many clinical parameters, such as National Institutes of Health Stroke Scale (NIHSS) score, mean arterial pressure, and history of cerebrovascular disease. Moreover, the ROC models based on the characteristic microbiota or the combination of characteristic microbiota with independent risk factors could distinguish POAH patients and GOAH patients (area under curve is 0.694 and 0.971 respectively).ConclusionsThese findings revealed the microbial characteristics of POAH, which highlighted the predictive capability of characteristic microbiota in POAH patients.

The scoping review aims to explore the use of virtual reality(VR) technology in breast cancer(BC) survivors.

For most patients with breast cancer (BC) decisions are complex in different ways, and there are a variety of influences to consider. Shared Decision Making (SDM) helps meet these needs and promotes informed value-based decision-making.

The review was conducted following the PRISMA-ScR for scoping reviews guidelines, employing a six-step process: formulating the research question, identifying and selecting relevant studies, study selection, data graphing, synthesizing the results and translating the results.

We recently developed stretchable electronic devices using several types of one-dimensional (1D) nanostructures such as silicon nanowires (SiNWs), AgNWs, and carbon nanotubes (CNTs). Several advantages of 1D nanostructures for such applications include: (i) the 1D nanostructures possess excellent electric and mechanical properties, such as high mobility and large fracture strength; (ii) they can be tailored into different buckling shapes, either individually or collectively. For example, individual SiNW were found to buckle into coiled shape, which exhibited superior stretchability (e.g., over 100% strain); CNTs and AgNWs buckled collectively either out-of-plane or in-plane. In this discussion, we will discuss several device applications based on the 1D nanostructures, including strain sensors, pressure sensors, tactile sensors, antennas, and wearable electrodes for bioelectric measurements.

The microstructural evolution and formation mechanism of nanograins in Ti-2Al-2.5Zr α -titanium alloys and Ti-10V-2Fe-3Al metastable β -titanium alloys subjected to multi-impact process at ambient temperature were investigated using optical microscopy, X-ray diffraction and transmission electron microscopy. The results show that deformation twinning, dislocation activities and shear banding successively dominate plastic deformation in Ti-2Al-2.5Zr alloy. In contrast, deformation-induced martensitic phase transformation becomes prevalent in Ti-10V-2Fe-3Al alloy. Martensitic subdivision, shear banding and reverse martensitic transformation contribute to grain refinement. Moreover, nanograins are finally achieved in both titanium alloys at a strain of 1.2, but grain refining efficiency is more significant in Ti-10V-2Fe-3Al alloy. The accelerated grain refinement could be attributed to the assistance of martensitic phase transformation.