Studying Health Outcomes in Farmworker Populations Exposed to Pesticides

A major goal of studying farmworkers is to better understand how their work environment, including exposure to pesticides, affects their health. Although a number of health conditions have been associated with pesticide exposure, clear linkages have yet to be made between exposure and health effects except in cases of acute pesticide exposure. In this article, we review the most common health end points that have been studied and describe the epidemiologic challenges encountered in studying these health effects of pesticides among farmworkers, including the difficulties in accessing the population and challenges associated with obtaining health end point data. The assessment of neurobehavioral health effects serves as one of the most common and best examples of an approach used to study health outcomes in farmworkers and other populations exposed to pesticides. We review the current limitations in neurobehavioral assessment and strategies to improve these analytical methods. Emerging techniques to improve our assessment of health effects associated with pesticide exposure are reviewed. These techniques, which in most cases have not been applied to farmworker populations, hold promise in our ability to study and understand the relationship between pesticide exposure and a variety of health effects in this population

Tunnel vision, false memories, and intrusive memories following exposure to the Trier Social Stress Test

Most research examining the impact of stress on learning and memory has exposed participants to a stressor and measured how it affects learning and memory for unrelated material (e.g., list of words). Such work has been helpful, but it has not been the most translational to the human condition. When considering phenomena such as intrusive memories in post-traumatic stress disorder (PTSD) or an eyewitness\u27s memory for a crime, it is most useful to know what an individual remembers about the stress experience itself, not unrelated information. In prior work, investigators used a modified version of the Trier Social Stress Test (TSST) to quantify participant memory for the stressor. We aimed to replicate this work by examining participant memory for the TSST and extend on it by quantifying false and intrusive memories that result from TSST exposure. Forty-six undergraduate students from Ohio Northern University were exposed to the TSST or the friendly-TSST (f-TSST). The TSST required participants to deliver a ten-minute speech in front of two lab panel members as part of a mock job interview; the f-TSST required participants to casually converse with the panel members about their interests and hobbies. In both conditions, the panel members interacted with (central) or did not interact with (peripheral) several objects sitting on a desk in front of them. Participants’ anxiety levels were assessed before and after the TSST or f-TSST, and saliva samples were collected to assay for cortisol. The next day, participants’ memory for the objects that were present on Day 1 was assessed with recall and recognition tests. We also quantified participants’ intrusive memories for each task by having them complete an intrusive memory questionnaire on Days 2, 4, 6, and 8. Participants exposed to the TSST exhibited greater recall of central objects than participants exposed to the f-TSST. There were no differences observed for the recall of peripheral objects or for recognition memory. Interestingly, TSST exposure increased false recall in males, but reduced it in females. Females exposed to the TSST also showed greater evidence of intrusive memories than males exposed to the TSST. Consistent with prior work, these findings show that stress enhances memory for the central details of a stressful experience. They also extend on prior work by showing that stressful experiences sex-dependently impact the manifestation of false and intrusive memories. This is the first study of which we are aware to quantify intrusive memory formation with the TSST; the modified TSST paradigm may be useful in understanding differential susceptibility to intrusive memory formation and the development of PTSD

Serial selection for invasiveness increases expression of miR-143/miR-145 in glioblastoma cell lines

<p>Abstract</p> <p>Background</p> <p>Glioblastoma multiforme (GBM) is the most common primary central nervous system malignancy and its unique invasiveness renders it difficult to treat. This invasive phenotype, like other cellular processes, may be controlled in part by microRNAs - a class of small non-coding RNAs that act by altering the expression of targeted messenger RNAs. In this report, we demonstrate a straightforward method for creating invasive subpopulations of glioblastoma cells (IM3 cells). To understand the correlation between the expression of miRNAs and the invasion, we fully profiled 1263 miRNAs on six different cell lines and two miRNAs, miR-143 and miR-145, were selected for validation of their biological properties contributing to invasion. Further, we investigated an ensemble effect of both miR-143 and miR-145 in promoting invasion.</p> <p>Methods</p> <p>By repeated serial invasion through Matrigel^®-coated membranes, we isolated highly invasive subpopulations of glioma cell lines. Phenotypic characterization of these cells included <it>in vitro </it>assays for proliferation, attachment, and invasion. Micro-RNA expression was compared using miRCURY arrays (Exiqon). In situ hybridization allowed visualization of the regional expression of miR-143 and miR-145 in tumor samples, and antisense probes were used investigate <it>in vitro </it>phenotypic changes seen with knockdown in their expression.</p> <p>Results</p> <p>The phenotype we created in these selected cells proved stable over multiple passages, and their microRNA expression profiles were measurably different. We found that two specific microRNAs expressed from the same genetic locus, miR-143 and miR-145, were over-expressed in our invasive subpopulations. Further, we also found that combinatorial treatment of these cells with both antisense-miRNAs (antimiR-143 and -145) will abrogated their invasion without decreasing cell attachment or proliferation.</p> <p>Conclusions</p> <p>To best of our knowledge, these data demonstrate for the first time that miR-143 and miR-145 regulate the invasion of glioblastoma and that miR-143 and -145 could be potential therapeutic target for anti-invasion therapies of glioblastoma patients.</p

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

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

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

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

The NANOGrav 15-year Data Set: Bayesian Limits on Gravitational Waves from Individual Supermassive Black Hole Binaries

Evidence for a low-frequency stochastic gravitational wave background has recently been reported based on analyses of pulsar timing array data. The most likely source of such a background is a population of supermassive black hole binaries, the loudest of which may be individually detected in these datasets. Here we present the search for individual supermassive black hole binaries in the NANOGrav 15-year dataset. We introduce several new techniques, which enhance the efficiency and modeling accuracy of the analysis. The search uncovered weak evidence for two candidate signals, one with a gravitational-wave frequency of $\sim$4 nHz, and another at $\sim$170 nHz. The significance of the low-frequency candidate was greatly diminished when Hellings-Downs correlations were included in the background model. The high-frequency candidate was discounted due to the lack of a plausible host galaxy, the unlikely astrophysical prior odds of finding such a source, and since most of its support comes from a single pulsar with a commensurate binary period. Finding no compelling evidence for signals from individual binary systems, we place upper limits on the strain amplitude of gravitational waves emitted by such systems.Comment: 23 pages, 13 figures, 2 tables. Accepted for publication in Astrophysical Journal Letters as part of Focus on NANOGrav's 15-year Data Set and the Gravitational Wave Background. For questions or comments, please email [email protected]

Comprehensive and Integrated Genomic Characterization of Adult Soft Tissue Sarcomas

Sarcomas are a broad family of mesenchymal malignancies exhibiting remarkable histologic diversity. We describe the multi-platform molecular landscape of 206 adult soft tissue sarcomas representing 6 major types. Along with novel insights into the biology of individual sarcoma types, we report three overarching findings: (1) unlike most epithelial malignancies, these sarcomas (excepting synovial sarcoma) are characterized predominantly by copy-number changes, with low mutational loads and only a few genes (, , ) highly recurrently mutated across sarcoma types; (2) within sarcoma types, genomic and regulomic diversity of driver pathways defines molecular subtypes associated with patient outcome; and (3) the immune microenvironment, inferred from DNA methylation and mRNA profiles, associates with outcome and may inform clinical trials of immune checkpoint inhibitors. Overall, this large-scale analysis reveals previously unappreciated sarcoma-type-specific changes in copy number, methylation, RNA, and protein, providing insights into refining sarcoma therapy and relationships to other cancer types

The NANOGrav 15-year Data Set: Search for Anisotropy in the Gravitational-Wave Background

The North American Nanohertz Observatory for Gravitational Waves (NANOGrav) has reported evidence for the presence of an isotropic nanohertz gravitational wave background (GWB) in its 15 yr dataset. However, if the GWB is produced by a population of inspiraling supermassive black hole binary (SMBHB) systems, then the background is predicted to be anisotropic, depending on the distribution of these systems in the local Universe and the statistical properties of the SMBHB population. In this work, we search for anisotropy in the GWB using multiple methods and bases to describe the distribution of the GWB power on the sky. We do not find significant evidence of anisotropy, and place a Bayesian $95\%$ upper limit on the level of broadband anisotropy such that $(C_{l>0} / C_{l=0}) < 20\%$. We also derive conservative estimates on the anisotropy expected from a random distribution of SMBHB systems using astrophysical simulations conditioned on the isotropic GWB inferred in the 15-yr dataset, and show that this dataset has sufficient sensitivity to probe a large fraction of the predicted level of anisotropy. We end by highlighting the opportunities and challenges in searching for anisotropy in pulsar timing array data.Comment: 19 pages, 11 figures; submitted to Astrophysical Journal Letters as part of Focus on NANOGrav's 15-year Data Set and the Gravitational Wave Background. For questions or comments, please email [email protected]