Exploring the associations between sexual violence history and reasons for seeking care at college health centers

Approximately 20-25% of females and 5-7% of males report experiencing sexual contact involving force or incapacitation on college campuses. While this is a major public health concern that impacts a student’s mental, physical, and behavioral health, most unwanted sexual experiences go unreported. With 43-48% of students utilizing college health centers, campus health providers have the opportunity to intersect with victims of sexual violence (SV) and help to connect them to appropriate resources. The purpose of the current study was to (1) describe the reasons for care-seeking among students at college health or counseling centers (CHCCs) and (2) examine associations between reasons for care-seeking at CHCCs and SV status. Data used in this study comes from the College Health Study, which used a 2-arm cluster randomized controlled trial design with a sample of 2292 students from 28 colleges across Pennsylvania and West Virginia. This study found that a large proportion of care-seeking students (55.7%) have experienced sexual violence. Results show that students with a history of sexual violence victimization are more likely to visit college health centers for counseling and reproductive and sexual health care than non-victim students. Therefore, providers need to be prepared to recognize signs and respond to disclosure and colleges need to work toward a standard of policy and practice on SV knowledge and skills for anyone that comes in contact with college students

A Computational Algebra Approach to the Reverse Engineering of Gene Regulatory Networks

This paper proposes a new method to reverse engineer gene regulatory networks from experimental data. The modeling framework used is time-discrete deterministic dynamical systems, with a finite set of states for each of the variables. The simplest examples of such models are Boolean networks, in which variables have only two possible states. The use of a larger number of possible states allows a finer discretization of experimental data and more than one possible mode of action for the variables, depending on threshold values. Furthermore, with a suitable choice of state set, one can employ powerful tools from computational algebra, that underlie the reverse-engineering algorithm, avoiding costly enumeration strategies. To perform well, the algorithm requires wildtype together with perturbation time courses. This makes it suitable for small to meso-scale networks rather than networks on a genome-wide scale. The complexity of the algorithm is quadratic in the number of variables and cubic in the number of time points. The algorithm is validated on a recently published Boolean network model of segment polarity development in Drosophila melanogaster.Comment: 28 pages, 5 EPS figures, uses elsart.cl

Rethinking scientists’ ongoing participation in “feeding the world”

Agricultural science necessarily involves a commitment to some form of humanitarian and environmental ethics. For the past century, agricultural science has been based on a productivist ethic of maximizing agricultural production in pursuit or support of food security. Recognition of the ethical and political disposition of contemporary agricultural science can help scientists reorient their work to better address the urgent problems of the upcoming century: environmental degradation, climate change, and social inequality. A commitment to solving these problems is well within the scope of modern agricultural science. Supporting and furthering multidimensional food systems should replace productivism as an explicit goal of agricultural development and scientific innovation

Time lagged information theoretic approaches to the reverse engineering of gene regulatory networks

Background: A number of models and algorithms have been proposed in the past for gene regulatory network (GRN) inference; however, none of them address the effects of the size of time-series microarray expression data in terms of the number of time-points. In this paper, we study this problem by analyzing the behaviour of three algorithms based on information theory and dynamic Bayesian network (DBN) models. These algorithms were implemented on different sizes of data generated by synthetic networks. Experiments show that the inference accuracy of these algorithms reaches a saturation point after a specific data size brought about by a saturation in the pair-wise mutual information (MI) metric; hence there is a theoretical limit on the inference accuracy of information theory based schemes that depends on the number of time points of micro-array data used to infer GRNs. This illustrates the fact that MI might not be the best metric to use for GRN inference algorithms. To circumvent the limitations of the MI metric, we introduce a new method of computing time lags between any pair of genes and present the pair-wise time lagged Mutual Information (TLMI) and time lagged Conditional Mutual Information (TLCMI) metrics. Next we use these new metrics to propose novel GRN inference schemes which provides higher inference accuracy based on the precision and recall parameters. Results: It was observed that beyond a certain number of time-points (i.e., a specific size) of micro-array data, the performance of the algorithms measured in terms of the recall-to-precision ratio saturated due to the saturation in the calculated pair-wise MI metric with increasing data size. The proposed algorithms were compared to existing approaches on four different biological networks. The resulting networks were evaluated based on the benchmark precision and recall metrics and the results favour our approach. Conclusions: To alleviate the effects of data size on information theory based GRN inference algorithms, novel time lag based information theoretic approaches to infer gene regulatory networks have been proposed. The results show that the time lags of regulatory effects between any pair of genes play an important role in GRN inference schemes

Mystique et messianisme dans la pensée "hispano-portugaise" du XVIIIe siècle : Mordejay Gutyerez (? - Bayonne 1754) ("Recreo del Alma. Amplificación de el verso desde Beresit asta salida de hijos de Ysrael de Egipto" (Bordeaux 1698-Bayonne 1722). Edition, Introduction et notes)

Mon travail vise à dévoiler l univers mental d un homme issu du marranisme aux temps de l Ancien Régime finissant. Mordejay Gutyerez appartient à une population qui en 1550 obtient le permis légal pour résider au Sud Ouest de la France à tire de marchands portugais nouveaux Chrétiens. Gutyerez s efface derrière ses écrits qui attestent sa formation kabbaliste. On conserve deux manuscrits olographes rédigés en espagnol, datés en 1722-1723, ils composent les versants éthiques, prophétiques et messianiques de son système de pensée. La kabbale extatique professée par Gutyerez est bâtie sur les théories de la prophétie et l union mystique aboulafienne. On l appelle la mystique du langage ou les chemins des noms de Dieu, un modèle qui n est pas usité par la kabbale espagnole, attirée par le symbolisme théurgique. Mon auteur élabore ses livres puisant des traditions bibliques, rabbiniques, mystiques, philosophiques, dans un creuset des théories compatibles aux pratiques unitives professées par l Ecole aboulafienne. Pour lui, ses expériences découlent de l intellect, seul capable d atteindre l Intelligence Suprême. Cette supra-connaissance des réalités supérieures parviennent au mystique par révélation dans un état extatique, au sommet de sa devekut.My paper aims to reconstruct the mental universe of a mystic, a descendant of the Marranos, who lived during the last years of the Ancien Régime. My work focuses on Bayonne (where he lived) and his time. He died in 1754. Mordejay Gutyerez s thoughts are revealed in his writings, which testify to his Kabbalistic training. Two of his holograph manuscripts, written in Spanish and dated 1721 and 1723, have been preserved. These manuscripts constitute the ethical, prophetic and messianic aspects of his doctrine. The model o ecstatic Kabbalah in which he takes his first steps is based on Abraham Aboulafia s prophetic and mystical union theories ; this model, called language mysticism r the path of the names of Go, did not arouse the interest of the Spanish Kabbalah, attracted by the theurgic imagery. His books draw on the biblical, rabbinical, mystical and philosophical tradition, in a melting pot of therories adapted to the unitive practices of the prophetic school.PARIS-EPHE-Sciences religieuses (751052336) / SudocSudocFranceF

Rethinking scientists’ ongoing participation in “feeding the world”

Agricultural science necessarily involves a commitment to some form of humanitarian and environmental ethics. For the past century, agricultural science has been based on a productivist ethic of maximizing agricultural production in pursuit or support of food security. Recognition of the ethical and political disposition of contemporary agricultural science can help scientists reorient their work to better address the urgent problems of the upcoming century: environmental degradation, climate change, and social inequality. A commitment to solving these problems is well within the scope of modern agricultural science. Supporting and furthering multidimensional food systems should replace productivism as an explicit goal of agricultural development and scientific innovation

Farm resilience during the COVID-19 pandemic: The case of California direct market farmers

ContextThe COVID-19 pandemic caused significant shocks to U.S. food systems at multiple scales. While disturbances to long-distance supply chains received substantial attention in national media, local supply chains experienced mixed impacts. As broad closures of schools, restaurants, and other businesses sourcing from local farmers removed key marketing channels for many direct market farmers, consumer interest in Community Supported Agriculture (CSA), farmers markets, and on-farm and online direct farm sales increased.ObjectiveIn this paper, we examine the resilience and vulnerability of farmers during the March 2020 through December 2020 period of the COVID-19 pandemic. We focus on California farmers and ranchers engaged in direct market sales.MethodsThrough a widely disseminated survey, we collected responses from 364 farmers and used these data to answer the following questions about direct market farmers in California: 1) What were direct market farmers' experiences of the pandemic from March 2020 through December 2020? 2) Which factors (e.g., relationships, institutions, market channels) did farmers report enhanced their resilience during the pandemic? 3) Which individual and operational factors were significantly associated with resilience during the pandemic? And finally, 4) how do the farmer-reported factors compare to the statistically significant factors associated with resilience? We created three dependent variables-ability to respond to the pandemic, concern about pandemic impacts, and change in profitability-to operationalize several aspects of resilience and examine their association with individual and operational characteristics through a series of ordered logistic regression models.Results and conclusionsAcross both the quantitative models and the farmer reported factors, we found that farmers who increased their use of online sales and marketing during the first year of the pandemic, had larger-scale farms, and had more on-farm crop and livestock diversity were more resilient to the shocks of the pandemic. We also found that greater use of non-direct-to-consumer market channels was associated with less resilience. The characteristics of the farming operations played a relatively larger role in predicting resilience compared to the individual characteristics of the farmers surveyed.SignificanceThis study gives a detailed picture of how California direct market farmers fared during the pandemic and the characteristics associated with greater resilience. As short and long-term disruptions become increasingly common in agriculture, policies and programs can leverage support to direct market farmers, particularly direct-to-consumer farmers, as a strategy to strengthen farmer resilience

Integration of biological networks and gene expression data using Cytoscape

Cytoscape is a free software package for visualizing, modeling and analyzing molecular and genetic interaction networks. This protocol explains how to use Cytoscape to analyze the results of mRNA expression profiling, and other functional genomics and proteomics experiments, in the context of an interaction network obtained for genes of interest. Five major steps are described: (i) obtaining a gene or protein network, (ii) displaying the network using layout algorithms, (iii) integrating with gene expression and other functional attributes, (iv) identifying putative complexes and functional modules and (v) identifying enriched Gene Ontology annotations in the network. These steps provide a broad sample of the types of analyses performed by Cytoscape