Atypical miRNA expression in temporal cortex associated with dysregulation of immune, cell cycle, and other pathways in autism spectrum disorders.

BackgroundAutism spectrum disorders (ASDs) likely involve dysregulation of multiple genes related to brain function and development. Abnormalities in individual regulatory small non-coding RNA (sncRNA), including microRNA (miRNA), could have profound effects upon multiple functional pathways. We assessed whether a brain region associated with core social impairments in ASD, the superior temporal sulcus (STS), would evidence greater transcriptional dysregulation of sncRNA than adjacent, yet functionally distinct, primary auditory cortex (PAC).MethodsWe measured sncRNA expression levels in 34 samples of postmortem brain from STS and PAC to find differentially expressed sncRNA in ASD compared with control cases. For differentially expressed miRNA, we further analyzed their predicted mRNA targets and carried out functional over-representation analysis of KEGG pathways to examine their functional significance and to compare our findings to reported alterations in ASD gene expression.ResultsTwo mature miRNAs (miR-4753-5p and miR-1) were differentially expressed in ASD relative to control in STS and four (miR-664-3p, miR-4709-3p, miR-4742-3p, and miR-297) in PAC. In both regions, miRNA were functionally related to various nervous system, cell cycle, and canonical signaling pathways, including PI3K-Akt signaling, previously implicated in ASD. Immune pathways were only disrupted in STS. snoRNA and pre-miRNA were also differentially expressed in ASD brain.ConclusionsAlterations in sncRNA may underlie dysregulation of molecular pathways implicated in autism. sncRNA transcriptional abnormalities in ASD were apparent in STS and in PAC, a brain region not directly associated with core behavioral impairments. Disruption of miRNA in immune pathways, frequently implicated in ASD, was unique to STS

Adjunct & Faculty Survey: Perceptions of Quality & Rigor

Seeking comprehensive feedback about adjunct faculty experiences at Fort Hays State University, the authors created an anonymous survey tool to inquire about full-time and adjunct faculty perceptions of a broad range of factors affecting adjuncts and the classes they teach. Results include valuable information about adjunct satisfaction, compensation, recruitment, orientation, and support, as well as perceptions of course and program quality. Findings suggest significant differences in perceptions of academic rigor and expectations of student clock-hours. Results were shared with the Adjunct Faculty Advisory Committee and will be used to make various recommendations to the Provost and Academic Council. Additional research is needed, to clarify factors which affect adjunct and full-time faculty perceptions

Adjunct & Faculty Survey: Perceptions of Quality & Rigor

Seeking comprehensive feedback about adjunct faculty experiences at Fort Hays State University, the authors created an anonymous survey tool to inquire about full-time and adjunct faculty perceptions of a broad range of factors affecting adjuncts and the classes they teach. Results include valuable information about adjunct satisfaction, compensation, recruitment, orientation, and support, as well as perceptions of course and program quality. Findings suggest significant differences in perceptions of academic rigor and expectations of student clock-hours. Results were shared with the Adjunct Faculty Advisory Committee and will be used to make various recommendations to the Provost and Academic Council. Additional research is needed, to clarify factors which affect adjunct and full-time faculty perceptions

A Template Analysis of Intimate Partner Violence Survivors’ Experiences of Animal Maltreatment: Implications for Safety Planning and Intervention

This study explores the intersection of intimate partner violence (IPV) and animal cruelty in an ethnically diverse sample of 103 pet-owning IPV survivors recruited from community-based domestic violence programs. Template analysis revealed five themes: (a) Animal Maltreatment by Partner as a Tactic of Coercive Power and Control, (b) Animal Maltreatment by Partner as Discipline or Punishment of Pet, (c) Animal Maltreatment by Children, (d) Emotional and Psychological Impact of Animal Maltreatment Exposure, and (e) Pets as an Obstacle to Effective Safety Planning. Results demonstrate the potential impact of animal maltreatment exposure on women and child IPV survivors’ health and safety

Rostrolateral Prefrontal Cortex and Individual Differences in Uncertainty-Driven Exploration

SummaryHow do individuals decide to act based on a rewarding status quo versus an unexplored choice that might yield a better outcome? Recent evidence suggests that individuals may strategically explore as a function of the relative uncertainty about the expected value of options. However, the neural mechanisms supporting uncertainty-driven exploration remain underspecified. The present fMRI study scanned a reinforcement learning task in which participants stop a rotating clock hand in order to win points. Reward schedules were such that expected value could increase, decrease, or remain constant with respect to time. We fit several mathematical models to subject behavior to generate trial-by-trial estimates of exploration as a function of relative uncertainty. These estimates were used to analyze our fMRI data. Results indicate that rostrolateral prefrontal cortex tracks trial-by-trial changes in relative uncertainty, and this pattern distinguished individuals who rely on relative uncertainty for their exploratory decisions versus those who do not.Video Abstrac

A pathway-driven predictive model of tramadol pharmacogenetics

Predicting metabolizer phenotype (MP) is typically performed using data from a single gene. Cytochrome p450 family 2 subfamily D polypeptide 6 (CYP2D6) is considered the primary gene for predicting MP in reference to approximately 30% of marketed drugs and endogenous toxins. CYP2D6 predictions have proven clinically effective but also have well-documented inaccuracies due to relatively high genotype-phenotype discordance in certain populations. Herein, a pathway-driven predictive model employs genetic data from uridine diphosphate glucuronosyltransferase, family 1, polypeptide B7 (UGT2B7), adenosine triphosphate (ATP)-binding cassette, subfamily B, number 1 (ABCB1), opioid receptor mu 1 (OPRM1), and catechol-O-methyltransferase (COMT) to predict the tramadol to primary metabolite ratio (T:M1) and the resulting toxicologically inferred MP (t-MP). These data were then combined with CYP2D6 data to evaluate performance of a fully combinatorial model relative to CYP2D6 alone. These data identify UGT2B7 as a potentially significant explanatory marker for T:M1 variability in a population of tramadol-exposed individuals of Finnish ancestry. Supervised machine learning and feature selection were used to demonstrate that a set of 16 loci from 5 genes can predict t-MP with over 90% accuracy, depending on t-MP category and algorithm, which was significantly greater than predictions made by CYP2D6 alone.Peer reviewe

Use of Annual Phosphorus Loss Estimator (APLE) Model to Evaluate a Phosphorus Index

The Phosphorus (P) Index was developed to provide a relative ranking of agricultural fields according to their potential for P loss to surface water. Recent efforts have focused on updating and evaluating P Indices against measured or modeled P loss data to ensure agreement in magnitude and direction. Following a recently published method, we modified the Maryland P Site Index (MD-PSI) from a multiplicative to a component index structure and evaluated the MD-PSI outputs against P loss data estimated by the Annual P Loss Estimator (APLE) model, a validated, field-scale, annual P loss model. We created a theoretical dataset of fields to represent Maryland conditions and scenarios and created an empirical dataset of soil samples and management characteristics from across the state. Through the evaluation process, we modified a number of variables within the MD-PSI and calculated weighting coefficients for each P loss component. We have demonstrated that our methods can be used to modify a P Index and increase correlation between P Index output and modeled P loss data. The methods presented here can be easily applied in other states where there is motivation to update an existing P Index

Downregulation of miR-342 is associated with tamoxifen resistant breast tumors

<p>Abstract</p> <p>Background</p> <p>Tumor resistance to the selective estrogen receptor modulator tamoxifen remains a serious clinical problem especially in patients with tumors that also overexpress HER2. We have recently demonstrated that the clinically important isoform of HER2, HERΔ16, promotes therapeutically refractory breast cancer including resistance to endocrine therapy. Likewise additional breast tumor cell models of tamoxifen resistance have been developed that do not involve HER2 overexpression. However, a unifying molecular mechanism of tamoxifen resistance has remained elusive.</p> <p>Results</p> <p>Here we analyzed multiple cell models of tamoxifen resistance derived from MCF-7 cells to examine the influence of microRNAs (miRNAs) on tamoxifen resistance. We compared miRNA expression profiles of tamoxifen sensitive MCF-7 cells and tamoxifen resistant MCF-7/HER2Δ16 cells. We observed significant and dramatic downregulation of miR-342 in the MCF-7/HER2Δ16 cell line as well as the HER2 negative but tamoxifen resistant MCF-7 variants TAMR1 and LCC2. Restoring miR-342 expression in the MCF-7/HER2Δ16 and TAMR1 cell lines sensitized these cells to tamoxifen-induced apoptosis with a dramatic reduction in cell growth. Expression of miR-342 was also reduced in a panel of tamoxifen refractory human breast tumors, underscoring the potential clinical importance of miR-342 downregulation. Towards the goal of identifying direct and indirect targets of miR-342 we restored miR-342 expression in MCF-7/HER2Δ16 cells and analyzed changes in global gene expression by microarray. The impact of miR-342 on gene expression in MCF-7/HER2Δ16 cells was not limited to miR-342 <it>in silica </it>predicted targets. Ingenuity Pathways Analysis of the dataset revealed a significant influence of miR-342 on multiple tumor cell cycle regulators.</p> <p>Conclusions</p> <p>Our findings suggest that miR-342 regulates tamoxifen response in breast tumor cell lines and our clinical data indicates a trend towards reduced miR-342 expression and tamoxifen resistance. In addition, our results suggest that miR-342 regulates expression of genes involved in tamoxifen mediated tumor cell apoptosis and cell cycle progression. Restoring miR-342 expression may represent a novel therapeutic approach to sensitizing and suppressing the growth of tamoxifen refractory breast tumors.</p