Blood groups and protein polymorphisms in five goat breeds (Capra hircus)

Data on allele frequencies at six red cell blood group systems and three blood protein polymorphic loci in five goat breeds are reported. Two blood proteins, albumin and carbonic anhy-drase, were not found to be polymorphic. The B blood group system of goats, like its homologue in cattle and sheep, is highly complex. At least 44 B phenogroups (haplotypes) have been distinguished in this study. Based on the variation in allele frequencies between breeds, genetic distances were calculated. The distances estimated by four different methods were in close agreement with data from the history and geographic origins of the breeds examined.     

High content image analysis for human H4 neuroglioma cells exposed to CuO nanoparticles

Background  

High content screening (HCS)-based image analysis is becoming an important and widely used research tool. Capitalizing this technology, ample cellular information can be extracted from the high content cellular images. In this study, an automated, reliable and quantitative cellular image analysis system developed in house has been employed to quantify the toxic responses of human H4 neuroglioma cells exposed to metal oxide nanoparticles. This system has been proved to be an essential tool in our study.     

Microbial Transport, Survival, and Succession in a Sequence of Buried Sediments

Abstract Two chronosequences of unsaturated, buried loess sediments, ranging in age from <10,000 years to >1 million years, were investigated to reconstruct patterns of microbial ecological succession that have occurred since sediment burial. The relative importance of microbial transport and survival to succession was inferred from sediment ages, porewater ages, patterns of abundance (measured by direct counts, counts of culturable cells, and total phospholipid fatty acids), activities (measured by radiotracer and enzyme assays), and community composition (measured by phospholipid fatty acid patterns and Biolog substrate usage). Core samples were collected at two sites 40 km apart in the Palouse region of eastern Washington State, near the towns of Washtucna and Winona. The Washtucna site was flooded multiple times during the Pleistocene by glacial outburst floods; the Winona site elevation is above flood stage. Sediments at the Washtucna site were collected from near surface to 14.9 m depth, where the sediment age was approximately 250 ka and the porewater age was 3700 years; sample intervals at the Winona site ranged from near surface to 38 m (sediment age: approximately 1 Ma; porewater age: 1200 years). Microbial abundance and activities declined with depth at both sites; however, even the deepest, oldest sediments showed evidence of viable microorganisms. Same-age sediments had equal quantities of microorganisms, but different community types. Differences in community makeup between the two sites can be attributed to differences in groundwater recharge and paleoflooding. Estimates of the microbial community age can be constrained by porewater and sediment ages. In the shallower sediments (<9 m at Washtucna, <12 m at Winona), the microbial communities are likely similar in age to the groundwater; thus, microbial succession has been influenced by recent transport of microorganisms from the surface. In the deeper sediments, the populations may be considerably older than the porewater ages, since microbial transport is severely restricted in unsaturated sediments. This is particularly true at the Winona site, which was never flooded.     

3D cell nuclei segmentation based on gradient flow tracking

Background  

Reliable segmentation of cell nuclei from three dimensional (3D) microscopic images is an important task in many biological studies. We present a novel, fully automated method for the segmentation of cell nuclei from 3D microscopic images. It was designed specifically to segment nuclei in images where the nuclei are closely juxtaposed or touching each other. The segmentation approach has three stages: 1) a gradient diffusion procedure, 2) gradient flow tracking and grouping, and 3) local adaptive thresholding.     

Context based mixture model for cell phase identification in automated fluorescence microscopy

Background  

Automated identification of cell cycle phases of individual live cells in a large population captured via automated fluorescence microscopy technique is important for cancer drug discovery and cell cycle studies. Time-lapse fluorescence microscopy images provide an important method to study the cell cycle process under different conditions of perturbation. Existing methods are limited in dealing with such time-lapse data sets while manual analysis is not feasible. This paper presents statistical data analysis and statistical pattern recognition to perform this task.     

Bioluminescence imaging reveals inhibition of tumor cell proliferation by Alzheimer's amyloid β protein

Background  

Cancer and Alzheimer's disease (AD) are two seemingly distinct diseases and rarely occur simultaneously in patients. To explore molecular determinants differentiating pathogenic routes towards AD or cancer, we investigate the role of amyloid β protein (Aβ) on multiple tumor cell lines that are stably expressing luciferase (human glioblastoma U87; human breast adenocarcinoma MDA-MB231; and mouse melanoma B16F).