A Qualitative Descriptive Study of Teacher and Administrator Perceptions of Professional Learning Communities in a Texas School District With a Predominance of Hispanic Staff and Students

The purpose of conducting this qualitative descriptive study on professional learning communities in a South Texas public school district was to see if they are meaningful and structured to support the improvement of student success in the classroom as well as providing the support and steps outlined in an effective professional learning community. The study focused on the skill level implemented by the teachers, administrators, and other members of the committee to communicate, access the personal skills to collaborate with peers, and utilize the data for student achievement. This study sought to gain and understand the perceptions of department heads, administrators, and educators of how professional learning communities’ elements, characteristics, and three big ideas that guide a team when collaborating in a large district. Qualitative data were from 12 staff members of a large district in South Texas comprised of Hispanic administrators, Hispanic department heads, and Hispanic core subject coordinators. Open-ended interviews composed of 19 questions assemble the data. The findings of this study confirmed the perceptions in which participants felt supported and prepared for how professional learning communities supported the improvement of student success in the classroom. It also indicated where they felt a lack of support during how professional learning communities, improvement, and discussion is needed to achieve a desirable outcome. The results of this study balance other past research on the importance of how professional learning communities improve students’ scores and success. Keywords: professional learning community, collaboration, continuous improvement, student achievement, student learnin

Shared heritability and functional enrichment across six solid cancers

Correction: Nature Communications 10 (2019): art. 4386 DOI: 10.1038/s41467-019-12095-8Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (r(g) = 0.57, p = 4.6 x 10(-8)), breast and ovarian cancer (r(g) = 0.24, p = 7 x 10(-5)), breast and lung cancer (r(g) = 0.18, p = 1.5 x 10(-6)) and breast and colorectal cancer (r(g) = 0.15, p = 1.1 x 10(-4)). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis.Peer reviewe

Shared heritability and functional enrichment across six solid cancers

Abstract Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (rg = 0.57, p = 4.6 × 10−8), breast and ovarian cancer (rg = 0.24, p = 7 × 10−5), breast and lung cancer (rg = 0.18, p =1.5 × 10−6) and breast and colorectal cancer (rg = 0.15, p = 1.1 × 10−4). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis