Mercury concentrations in muscle tissue from sportfish in Lake Mead, Nevada

Lake Mead is the largest reservoir by volume in the United States and provides fishing opportunities for numerous anglers. Considerable attention has been given to the bioaccumulation of methylmercury in fish tissues, however, no formal study utilizing approved USEPA methodology has been conducted to quantify the amount of mercury present in fish tissue from Lake Mead. The purpose of this study is to determine the concentrations of mercury present in the most commonly consumed fish from Lake Mead and to identify if any of the 4 major basins contain fish with elevated concentrations of mercury. Largemouth bass (n=49), striped bass (n=94), and channel catfish (n=78) were collected from selected sites in Boulder Basin, Overton Arm, Virgin Basin, and Gregg Basin of Lake Mead by gill netting or electrofishing. Muscle tissue was homogenized, digested, and analyzed for mercury in accordance with USEPA Method 245.6 which must be used to construct human health based fish consumption advisories. Mean mercury concentrations were (x ±SD) 0.089±0.065 ppm, 0.154±0.127 ppm, and 0.098±0.080 ppm in largemouth bass, striped bass, and channel catfish, respectively. An analysis of covariance (ANCOVA) indicated a significant difference between mercury concentrations among the three species (F 2,208 = 22.448, p\u3c 0.001). Contrasts revealed that each species differed significantly from each other (p\u3c0.050). There was a significant overall difference in mean mercury concentration between fish from the four major basins of Lake Mead (F3,208 = 20.541, p\u3c0.001). The mean mercury concentration in Boulder Basin was significantly lower than that of Gregg Basin (p\u3c0.001), Virgin Basin (p\u3c0.001), and Overton Arm (p\u3c0.001). Out of 221 samples analyzed, 2 samples (both striped bass) were found to have mean mercury concentrations above the Environmental Protection Agency\u27s action level of 0.5 ppm. There were no samples found containing concentrations above the Food and Drug Administration\u27s maximum allowable mercury concentration in fish and food products (1.0 ppm)

Oculomotor function in frontotemporal lobar degeneration, related disorders and Alzheimer's disease

Frontotemporal lobar degeneration (FTLD) often overlaps clinically with corticobasal syndrome (CBS) and progressive supranuclear palsy (PSP), both of which have prominent eye movement abnormalities. To investigate the ability of oculomotor performance to differentiate between FTLD, Alzheimer's disease, CBS and PSP, saccades and smooth pursuit were measured in three FTLD subtypes, including 24 individuals with frontotemporal dementia (FTD), 19 with semantic dementia (SD) and six with progressive non-fluent aphasia (PA), as compared to 28 individuals with Alzheimer's disease, 15 with CBS, 10 with PSP and 27 control subjects. Different combinations of oculomotor abnormalities were identified in all clinical syndromes except for SD, which had oculomotor performance that was indistinguishable from age-matched controls. Only PSP patients displayed abnormalities in saccade velocity, whereas abnormalities in saccade gain were observed in PSP > CBS > Alzheimer's disease subjects. All patient groups except those with SD were impaired on the anti-saccade task, however only the FTLD subjects and not Alzheimer's disease, CBS or PSP groups, were able to spontaneously self-correct anti-saccade errors as well as controls. Receiver operating characteristic statistics demonstrated that oculomotor findings were superior to neuropsychological tests in differentiating PSP from other disorders, and comparable to neuropsychological tests in differentiating the other patient groups. These data suggest that oculomotor assessment may aid in the diagnosis of FTLD and related disorders

Estimation of efficiency of the use of financial resources on enterprises

Стаття присвячена дослідженню теоретичних та практичних питань аналітичного забезпечення управління використанням фінансових ресурсів підприємств. Запропоновані комплексні показники оцінки даного процесуThe article is devoted to research of theoretical and practical questions of the analytical providing of management the use of financial resources of enterprises. The complex indexes of estimation of this process are offere

Sixty Years of Modern Human Origins in the American Anthropological Association

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65197/1/aa.2003.105.1.89.pd

MicroRNA Expression and Regulation in Human Ovarian Carcinoma Cells by Luteinizing Hormone

MicroRNAs have been widely-studied with regard to their aberrant expression and high correlation with tumorigenesis and progression in various solid tumors. With the major goal of assessing gonadotropin (luteinizing hormone, LH) contributions to LH receptor (LHR)-positive ovarian cancer cells, we have conducted a genome-wide transcriptomic analysis on human epithelial ovarian cancer cells to identify the microRNA-associated cellular response to LH-mediated activation of LHR.Human ovarian cancer cells (SKOV3) were chosen as negative control (LHR-) and stably transfected to express functional LHR (LHR+), followed by incubation with LH (0-20 h). At different times of LH-mediated activation of LHR the cancer cells were analyzed by a high-density Ovarian Cancer Disease-Specific-Array (DSA, ALMAC™), which profiled ∼ 100,000 transcripts with ∼ 400 non-coding microRNAs.In total, 65 microRNAs were identified to exhibit differential expression in either LHR expressing SKOV3 cells or LH-treated cells, a few of which have been found in the genomic fragile regions that are associated with abnormal deletion or amplification in cancer, such as miR-21, miR-101-1, miR-210 and miR-301a. By incorporating the dramatic expression changes observed in mRNAs, strong microRNA/mRNA regulatory pairs were predicted through statistical analyses coupled with collective computational prediction. The role of each microRNA was then determined through a functional analysis based on the highly-confident microRNA/mRNA pairs.The overall impact on the transcriptome-level expression indicates that LH may regulate apoptosis and cell growth of LHR+ SKOV3 cells, particularly by reducing cancer cell proliferation, with some microRNAs involved in regulatory roles

The next generation of training for arabidopsis researchers: Bioinformatics and Quantitative Biology

It has been more than 50 years since Arabidopsis (Arabidopsis thaliana) was first introduced as a model organism to understand basic processes in plant biology. A well-organized scientific community has used this small reference plant species to make numerous fundamental plant biology discoveries (Provart et al., 2016). Due to an extremely well-annotated genome and advances in high-throughput sequencing, our understanding of this organism and other plant species has become even more intricate and complex. Computational resources, including CyVerse,3 Araport,4 The Arabidopsis Information Resource (TAIR),5 and BAR,6 have further facilitated novel findings with just the click of a mouse. As we move toward understanding biological systems, Arabidopsis researchers will need to use more quantitative and computational approaches to extract novel biological findings from these data. Here, we discuss guidelines, skill sets, and core competencies that should be considered when developing curricula or training undergraduate or graduate students, postdoctoral researchers, and faculty. A selected case study provides more specificity as to the concrete issues plant biologists face and how best to address such challenges

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment