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The third most abundant foraging ant, Nylanderia bourbonica (Forel), was more abundant in mineral soil fields than in shallow and deep organic soil fields. Results suggest that D. saccharalis population levels in Florida sugarcane are extremely low under current production conditions regardless of soil type. In addition, the observation of C. flavipes, S. invicta, and six other ant species suggest that biological control contributes to these low D. saccharalis population levels. © The Author(s) 2020. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.OBJECTIVE The purpose of this study was to evaluate relationships between multiple mild traumatic brain injuries (mTBIs) and objective and subjective clinical outcomes in a sample of combat-exposed Veterans, adjusting for psychiatric distress and combat exposure. METHOD In this cross-sectional study, 73 combat-exposed Iraq/Afghanistan Veterans were divided into three groups based on mTBI history 0 mTBIs (n = 31), 1-2 mTBIs (n = 21), and 3+ mTBIs (n = 21). Veterans with mTBI were assessed, on average, 7.78 years following their most recent mTBI. Participants underwent neuropsychological testing and completed self-report measures assessing neurobehavioral, sleep, and pain symptoms. RESULTS MANCOVAs adjusting for psychiatric distress and combat exposure showed no group differences on objective measures of attention/working memory, executive functioning, memory, and processing speed (all p’s > .05; ηp2 = .00-.06). In contrast, there were significant group differences on neurobehavioral symptoms (p’s =  less then  .001-.036; ηp2 = .09-.43), sleep difficulties (p = .037; ηp2 = .09), and pain symptoms (p  less then  .001; ηp2 = .21). Pairwise comparisons generally showed that the 3+ mTBI group self-reported the most severe symptoms, followed by comparable symptom reporting between the 0 and 1-2 mTBI groups. CONCLUSIONS History of multiple, remote mTBIs is associated with elevated subjective symptoms but not objective neuropsychological functioning in combat-exposed Veterans. These results advance understanding of the long-term consequences of repetitive mTBI in this population and suggest that Veterans with 3+ mTBIs may especially benefit from tailored treatments aimed at ameliorating specific neurobehavioral, sleep, and pain symptoms. Published by Oxford University Press 2020.Acute lymphoblastic leukemia (ALL) is one of the most common hematological malignancies in children. Recent studies suggest the involvement of multiple microRNAs in the tumorigenesis of various leukemias. However, until now, no comprehensive database exists for miRNAs and their cognate target genes involved specifically in ALL. Therefore, we developed ‘LeukmiR’ a dynamic database comprising in silico predicted microRNAs, and experimentally validated miRNAs along with the target genes they regulate in mouse and human. LeukmiR is a user-friendly platform with search strings for ALL-associated microRNAs, their sequences, description of target genes, their location on the chromosomes and the corresponding deregulated signaling pathways. this website For the user query, different search modules exist where either quick search can be carried out using any fuzzy term or by providing exact terms in specific modules. All entries for both human and mouse genomes can be retrieved through multiple options such as miRNA ID, their accession number, sequence, target genes, Ensemble-ID or Entrez-ID. User can also access miRNA mRNA interaction networks in different signaling pathways, the genomic location of the targeted regions such as 3’UTR, 5’UTR and exons with their gene ontology and disease ontology information in both human and mouse systems. Herein, we also report 51 novel microRNAs which are not described earlier for ALL. Thus, LeukmiR database will be a valuable source of information for researchers to understand and investigate miRNAs and their targets with diagnostic and therapeutic potential in ALL. Database URL http//tdb.ccmb.res.in/LeukmiR/. © The Author(s) 2020. Published by Oxford University Press.The identification and accurate quantitation of protein abundance has been a major objective of proteomics research. Abundance studies have the potential to provide users with data that can be used to gain a deeper understanding of protein function and regulation and can also help identify cellular pathways and modules that operate under various environmental stress conditions. One of the central missions of the Saccharomyces Genome Database (SGD; https//www.yeastgenome.org) is to work with researchers to identify and incorporate datasets of interest to the wider scientific community, thereby enabling hypothesis-driven research. A large number of studies have detailed efforts to generate proteome-wide abundance data, but deeper analyses of these data have been hampered by the inability to compare results between studies. Recently, a unified protein abundance dataset was generated through the evaluation of more than 20 abundance datasets, which were normalized and converted to common measurement units, in this case molecules per cell. We have incorporated these normalized protein abundance data and associated metadata into the SGD database, as well as the SGD YeastMine data warehouse, resulting in the addition of 56 487 values for untreated cells grown in either rich or defined media and 28 335 values for cells treated with environmental stressors. Abundance data for protein-coding genes are displayed in a sortable, filterable table on Protein pages, available through Locus Summary pages. A median abundance value was incorporated, and a median absolute deviation was calculated for each protein-coding gene and incorporated into SGD. These values are displayed in the Protein section of the Locus Summary page. The inclusion of these data has enhanced the quality and quantity of protein experimental information presented at SGD and provides opportunities for researchers to access and utilize the data to further their research. © The Author(s) 2020. Published by Oxford University Press.