Difference between arterial and venous peak optical density after thrombectomy is associated with functional outcomes.

Background: The density of contrast medium in digital subtraction angiography (DSA) have been used to evaluate the cerebral circulation function. Our aim was to study the effect of difference in arteriovenous peak optical density (POD) after thrombectomy on functional outcomes.

Methods: Consecutive patients with acute ischemic stroke due to large vessel occlusion who underwent thrombectomy were reviewed.

Prognosis and Prediction of Asymptomatic Intracranial Hemorrhage After Endovascular Thrombectomy: A Multi-Center Study.

Purpose: The impact of asymptomatic intracranial hemorrhage (aICH) on functional outcomes after endovascular thrombectomy (EVT) remains unclear, and tools for forecasting this complication are lacking. We aim to evaluate the clinical relevance of aICH and establish a prediction model.

Methods: Data of patients who received EVT for acute anterior-circulation large vessel occlusion in 3 comprehensive hospitals were retrospectively analyzed.

[Research on Oil Sands Spectral Characteristics and Oil Content by Remote Sensing Estimation].

Visible and near infrared spectroscopy is a proven technology to be widely used in identification and exploration of hydrocarbon energy sources with high spectral resolution for detail diagnostic absorption characteristics of hydrocarbon groups. The most prominent regions for hydrocarbon absorption bands are 1,740-1,780, 2,300-2,340 and 2,340-2,360 nm by the reflectance of oil sands samples. These spectral ranges are dominated by various C-H overlapping overtones and combination bands.

A partition-based approach to identify gene-environment interactions in genome wide association studies.

It is believed that almost all common diseases are the consequence of complex interactions between genetic markers and environmental factors. However, few such interactions have been documented to date. Conventional statistical methods for detecting gene and environmental interactions are often based on the linear regression model, which assumes a linear interaction effect.

A robust model-free approach for rare variants association studies incorporating gene-gene and gene-environmental interactions.

Recently more and more evidence suggest that rare variants with much lower minor allele frequencies play significant roles in disease etiology. Advances in next-generation sequencing technologies will lead to many more rare variants association studies. Several statistical methods have been proposed to assess the effect of rare variants by aggregating information from multiple loci across a genetic region and testing the association between the phenotype and aggregated genotype.

Identifying rare disease variants in the Genetic Analysis Workshop 17 simulated data: a comparison of several statistical approaches.

Genome-wide association studies have been successful at identifying common disease variants associated with complex diseases, but the common variants identified have small effect sizes and account for only a small fraction of the estimated heritability for common diseases. Theoretical and empirical studies suggest that rare variants, which are much less frequent in populations and are poorly captured by single-nucleotide polymorphism chips, could play a significant role in complex diseases. Several new statistical methods have been developed for the analysis of rare variants, for example, the combined multivariate and collapsing method, the weighted-sum method and a replication-based method.