La estructura en las redes personales

La mayoría de los estudios de redes personales (egocéntricas) describen las redes utilizando medidas que no son estructurales, recurriendo en su lugar a análisis de base-atributiva que resumen las relaciones de los encuestados con los miembros de la red. Los investigadores que han utilizado medidas estructurales lo han hecho con redes de menos de 10 miembros, que representan el núcleo de la red. Aunque se ha aprendido mucho centrándose en el análisis atributivo de los datos de redes personales, la aplicación de los análisis estructurales que tradicionalmente se han aplicado con datos de redes completas (sociocéntricas) puede resultar provechoso. La utilidad de este enfoque resulta evidente cuando la muestra elicitada de miembros de la red es relativamente grande. Cuarenta seis encuestados hicieron una lista libre de 60 miembros de la red y evaluaron la fuerza del lazo entre 1.770 pares de miembros. Los indicadores basados en grafos de de cohesión y subgrupos revelaron la variabilidad de la estructura de las redes personales. El análisis de clusters no jerárquicos generó subgrupos que fueron verificados a continuación por los encuestados como significativos. Posteriores análisis de la correlación entre los tipos de subgrupos y el solapamiento entre subgrupos demuestra cómo el análisis de cada red puede resumirse entre sujetos. Se presentan cuatro estudios de caso para ilustrar la riqueza de los datos y el valor de contrastar los resultados de la matriz individual con la norma definida por los 45 sujetos.Most personal (egocentric) network studies describe networks using measures that are not structural, opting instead for attribute-based analyses that summarize the relationships of the respondent to network members. Those researchers that used structural measures have done so on networks of less than 10 members who represent the network core. Although much has been learned by focusing on attribute-based analyses of personal network data, the application of structural analyses that are traditionally used on whole (sociocentric) network data may prove fruitful. The utility of this approach becomes apparent when the sample of network members elicited is relatively large. Forty-six respondents free-listed 60 network members and evaluated tie strength between all 1,770 unique pairs of members. Graph-based measures of cohesion and subgroups revealed variability in the personal network structure. Nonhierarchical clustering generated subgroups that were subsequently verified by respondents as meaningful. Further analysis of the correlation between subgroup types and overlap between subgroups demonstrates how the analysis of each network can be summarized across subjects. Four case studies are presented to illustrate the richness of the data and the value of contrasting individual matrix results to the norm as defined by all 45 subjects

Developmental Cis-Regulatory Analysis of the Cyclin D Gene in the Sea Urchin Strongylocentrotus purpuratus

Proper execution of animal development requires that it be integrated with cell division. In part, this is made possible due to cell cycle regulatory genes becoming dependent upon developmental signaling pathways that regulate their transcription. Cyclin D genes are important bridges linking the regulation of the cell cycle to development because these genes regulate the cell cycle, growth and differentiation in response to intercellular signaling. In this dissertation, a cis-regulatory analysis of a cyclin D gene, Sp-CycD, in the sea urchin, Strongylocentrotus purpuratus, is presented. While the promoters of vertebrate cyclin D genes have been analyzed, the cis-regulatory sequences across an entire cyclin D locus that regulate its expression pattern have not. From conducting the cis-regulatory analysis of Sp-CycD, regulatory regions located within six defined regions were identified. Two of these regions were found upstream of the start of transcription, but the remaining regions were found within introns. Regarding their activity patterns, two intronic regions were most strongly active at the time of induction of Sp-CycD expression, implying they contributed to this induction. The activity patterns of other regions indicated that each could have distinct roles, including controlling and maintaining Sp-CycD expression as it becomes spatially restricted during and after gastrulation. The sequences of the regulatory regions were analyzed. In three regions subregions containing the cis-regulatory modules responsible for activity were found, and in two other regions, sequences that lacked activating regulatory activity were found, allowing the identities of active regulatory sequences to be inferred. The sequences of each region were further analyzed for bearing significantly represented potential binding sites for transcription factors expressed in developmental lineages of the embryo where Sp-CycD is expressed. The transcription factors included those that act downstream of Wnt-beta catenin and Delta-Notch signaling pathways that induce the development of the endoderm and mesoderm; and those expressed within the Gene Regulatory Networks that contribute to the development of these lineages. From this, testable linkages between these binding sites and transcription factors that could regulate the expression of Sp-CycD as development progresses were identified, providing the foundation for future work

Why Local Party Leaders Don't Support Nominating Centrists

Would giving party leaders more influence in primary elections in the United States decrease elite polarization? Some scholars have argued that political party leaders tend to support centrist candidates in the hopes of winning general elections. In contrast, the authors argue that many local party leaders - especially Republicans - may not believe that centrists perform better in elections and therefore may not support nominating them. They test this argument using data from an original survey of 1,118 county-level party leaders. In experiments, they find that local party leaders most prefer nominating candidates who are similar to typical co-partisans, not centrists. Moreover, given the choice between a more centrist and more extreme candidate, they strongly prefer extremists: Democrats do so by about 2 to 1 and Republicans by 10 to 1. Likewise, in open-ended questions, Democratic Party leaders are twice as likely to say they look for extreme candidates relative to centrists; Republican Party leaders are five times as likely. Potentially driving these partisan differences, Republican leaders are especially likely to believe that extremists can win general elections and overestimate the electorate's conservatism by double digits

Fusion approach for remotely sensed mapping of agriculture (FARMA):A scalable open source method for land cover monitoring using data fusion

The increasing availability of very-high resolution (VHR; &lt;2 m) imagery has the potential to enable agricultural monitoring at increased resolution and cadence, particularly when used in combination with widely available moderate-resolution imagery. However, scaling limitations exist at the regional level due to big data volumes and processing constraints. Here, we demonstrate the Fusion Approach for Remotely Sensed Mapping of Agriculture (FARMA), using a suite of open source software capable of efficiently characterizing time-series field-scale statistics across large geographical areas at VHR resolution. We provide distinct implementation examples in Vietnam and Senegal to demonstrate the approach using WorldView VHR optical, Sentinel-1 Synthetic Aperture Radar, and Sentinel-2 and Sentinel-3 optical imagery. This distributed software is open source and entirely scalable, enabling large area mapping even with modest computing power. FARMA provides the ability to extract and monitor sub-hectare fields with multisensor raster signals, which previously could only be achieved at scale with large computational resources. Implementing FARMA could enhance predictive yield models by delineating boundaries and tracking productivity of smallholder fields, enabling more precise food security observations in low and lower-middle income countries.</p

Comparando dos métodos de estimación del tamaño de las redes personales

En este artículo comparamos dos métodos para la estimación del tamaño de las redes personales utilizando una muestra representativa de Estados Unidos a nivel nacional. Ambos métodos se basan en la habilidad de las personas encuestadas para estimar el número de personas que conocen en subpoblaciones específicas de EE.UU. (ej.: diabéticos, nativo-americanos) y gente en categorías específicas de relación (ej.: familia inmediata, compañeros de trabajo). Los resultados muestran una remarcable similitud entre el tamaño medio de la red obtenido por ambos métodos (aproximadamente 291). Se obtuvieron resultados similares con una muestra nacional distinta. La tentativa de corroboración de nuestras estimaciones mediante una reproducción exacta de la encuesta entre un segmento de población propenso a tener redes más amplias (el clero), dio como resultado un tamaño medio de la red superior. Una investigación extensiva sobre la existencia de efectos de respuesta mostró algunas preferencias por usar ciertos números a la hora de realizar estimaciones, pero nada que afectase de forma significativa a la estimación de tamaño de la red más allá del 6 por ciento. Nuestra conclusión es que ambos métodos utilizados para la estimación del tamaño de las redes personales proporcionan resultados válidos y fiables del tamaño de la red real, pero quedan algunas cuestiones pendientes sobre la exactitud.In this paper we compare two methods for estimating the size of personal networks using a nationally representative sample of the United States. Both methods rely on the ability of respondents to estimate the number of people they know in specific subpopulations of the U.S. (e.g., diabetics, Native Americans) and people in particular relation categories (e.g., immediate family, coworkers). The results demonstrate a remarkable similarity between the average network size generated by both methods (approximately 291). Similar results were obtained with a separate national sample. An attempt to corroborate our estimates by replicati among a population we suspect has large networks (clergy), yielded a larger average network size. Extensive investigation into the existence of response effects showed some preference for using certain numbers when making estimates, but nothing that would significantly affect the estimate of network size beyond about 6 percent. We conclude that both methods for estimating personal network size yield valid and reliable proxies for actual network size, but questions about accuracy remain

Longitudinal analysis of personal networks : the case of Argentinean migrants in Spain

Premi a l'excel·lència investigadora. 2010This paper discusses and illustrates various approaches for the longitudinal analysis of personal networks (multilevel analysis, regression analysis, and SIENA). We combined the different types of analyses in a study of the changing personal networks of immigrants. Data were obtained from 25 Argentineans in Spain, who were interviewed twice in a two-year interval. Qualitative interviews were used to estimate the amount of measurement error and to isolate important predictors. Quantitative analyses showed that the persistence of ties was explained by tie strength, network density, and alters' country of origin and residence. Furthermore, transitivity appeared to be an important tendency, both for acquiring new contacts and for the relationships among alters. At the network level, immigrants' networks were remarkably stable in composition and structure despite the high turnover. Clustered graphs have been used to illustrate the results. The results are discussed in light of adaptation to the host society

Substance Abuse Treatment Stage and Personal Networks of Women in Substance Abuse Treatment

This study examines the relationship among 4 treatment stages (i.e., engagement, persuasion, active treatment, relapse prevention) and the composition, social support, and structural characteristics of personal networks. The study sample includes 242 women diagnosed with substance dependence who were interviewed within their first month of intensive outpatient treatment. Using EgoNet software, the women reported on their 25 alter personal networks and the characteristics of each alter. With one exception, few differences were found in the network compositions at different stages of substance abuse treatment. The exception was the network composition of women in the active treatment stage, which included more network members from treatment programs or 12-Step meetings. Although neither the type nor amount of social support differed across treatment stages, reciprocity differed between women in active treatment and those in the engagement stage. Networks of women in active treatment were less connected, as indicated by a higher number of components, whereas networks of women in the persuasion stage had a higher degree of centralization, as indicated by networks dominated by people with the most ties. Overall, we find social network structural variables to relate to the stage of treatment, whereas network composition, type of social support, and sociodemographic variables (with a few exceptions) do not relate to treatment stage. Results suggest that social context, particularly how social contacts are arranged around clients, should be incorporated into treatment programs, regardless of demographic background

Intrathecal long-term gene expression by self-complementary adeno-associated virus type 1 suitable for chronic pain studies in rats

BACKGROUND: Intrathecal (IT) gene transfer is an attractive approach for targeting spinal mechanisms of nociception but the duration of gene expression achieved by reported methods is short (up to two weeks) impairing their utility in the chronic pain setting. The overall goal of this study was to develop IT gene transfer yielding true long-term transgene expression defined as ≥ 3 mo following a single vector administration. We defined "IT" administration as atraumatic injection into the lumbar cerebrospinal fluid (CSF) modeling a lumbar puncture. Our studies focused on recombinant adeno-associated virus (rAAV), one of the most promising vector types for clinical use. RESULTS: Conventional single stranded rAAV2 vectors performed poorly after IT delivery in rats. Pseudotyping of rAAV with capsids of serotypes 1, 3, and 5 was tested alone or in combination with a modification of the inverted terminal repeat. The former alters vector tropism and the latter allows packaging of self-complementary rAAV (sc-rAAV) vectors. Combining both types of modification led to the identification of sc-rAAV2/l as a vector that performed superiorly in the IT space. IT delivery of 3 × 10e9 sc-rAAV2/l particles per animal led to stable expression of enhanced green fluorescent protein (EGFP) for ≥ 3 mo detectable by Western blotting, quantitative PCR, and in a blinded study by confocal microscopy. Expression was strongest in the cauda equina and the lower sections of the spinal cord and only minimal in the forebrain. Microscopic examination of the SC fixed in situ with intact nerve roots and meninges revealed strong EGFP fluorescence in the nerve roots. CONCLUSION: sc-rAAVl mediates stable IT transgene expression for ≥ 3 mo. Our findings support the underlying hypothesis that IT target cells for gene transfer lack the machinery for efficient conversion of the single-stranded rAAV genome into double-stranded DNA and favor uptake of serotype 1 vectors over 2. Experiments presented here will provide a rational basis for utilizing IT rAAV gene transfer in basic and translational studies on chronic pain

A MAGIC population-based genome-wide association study reveals functional association of GhRBB1_A07 gene with superior fiber quality in cotton

Title: Quantile-quantile (Q-Q) Plot of six fiber traits generated from GWAS analysis following mixed linear model (MLM) using GAPIT software. A) Fiber elongation (ELO), B) Micronaire (MIC), C) Short fiber content (SFC), D) Fiber strength (STR), E) Upper half mean fiber length (UHM), and F) Uniformity index (UI). Description of data: Q-Q plots of six fiber traits generated from GWAS analysis following MLM are included in this figure. The X and Y axis have the expected and observed negative logarithm 10 of p value, respectively generated during GWAS analysis. (DOCX 207 kb