Domainâ specific impairment in cognitive control among remitted youth with a history of major depression

AimImpairment in neuropsychological functioning is common in major depressive disorder (MDD), but it is not clear to what degree these deficits are related to risk (e.g. trait), scar, burden or state effects of MDD. The objective of this study was to use neuropsychological measures, with factor scores in verbal fluency, processing speed, attention, setâ shifting and cognitive control in a unique population of young, remitted, unmedicated, early course individuals with a history of MDD in hopes of identifying putative trait markers of MDD.MethodsYouth aged 18â 23 in remission from MDD (rMDD; n = 62) and healthy controls (HC; n = 43) were assessed with neuropsychological tests at two time points. These were from four domains of executive functioning, consistent with previous literature as impaired in MDD: verbal fluency and processing speed, conceptual reasoning and setâ shifting, processing speed with interference resolution, and cognitive control.ResultsrMDD youth performed comparably to HCs on verbal fluency and processing speed, processing speed with interference resolution, and conceptual reasoning and setâ shifting, reliably over time. Individuals with rMDD demonstrated relative decrements in cognitive control at Time 1, with greater stability than HC participants.ConclusionMDD may be characterized by regulatory difficulties that do not pertain specifically to active mood state or fluctuations in symptoms. Deficient cognitive control may represent a trait vulnerability or early course scar of MDD that may prove a viable target for secondary prevention or early remediation.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138407/1/eip12253_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/138407/2/eip12253.pd

Outcomes and risk score for distal pancreatectomy with celiac axis resection (DP-CAR) : an international multicenter analysis

Background: Distal pancreatectomy with celiac axis resection (DP-CAR) is a treatment option for selected patients with pancreatic cancer involving the celiac axis. A recent multicenter European study reported a 90-day mortality rate of 16%, highlighting the importance of patient selection. The authors constructed a risk score to predict 90-day mortality and assessed oncologic outcomes. Methods: This multicenter retrospective cohort study investigated patients undergoing DP-CAR at 20 European centers from 12 countries (model design 2000-2016) and three very-high-volume international centers in the United States and Japan (model validation 2004-2017). The area under receiver operator curve (AUC) and calibration plots were used for validation of the 90-day mortality risk model. Secondary outcomes included resection margin status, adjuvant therapy, and survival. Results: For 191 DP-CAR patients, the 90-day mortality rate was 5.5% (95 confidence interval [CI], 2.2-11%) at 5 high-volume (1 DP-CAR/year) and 18% (95 CI, 9-30%) at 18 low-volume DP-CAR centers (P=0.015). A risk score with age, sex, body mass index (BMI), American Society of Anesthesiologists (ASA) score, multivisceral resection, open versus minimally invasive surgery, and low- versus high-volume center performed well in both the design and validation cohorts (AUC, 0.79 vs 0.74; P=0.642). For 174 patients with pancreatic ductal adenocarcinoma, the R0 resection rate was 60%, neoadjuvant and adjuvant therapies were applied for respectively 69% and 67% of the patients, and the median overall survival period was 19months (95 CI, 15-25months). Conclusions: When performed for selected patients at high-volume centers, DP-CAR is associated with acceptable 90-day mortality and overall survival. The authors propose a 90-day mortality risk score to improve patient selection and outcomes, with DP-CAR volume as the dominant predictor

CLO: The cell line ontology

Abstract Background Cell lines have been widely used in biomedical research. The community-based Cell Line Ontology (CLO) is a member of the OBO Foundry library that covers the domain of cell lines. Since its publication two years ago, significant updates have been made, including new groups joining the CLO consortium, new cell line cells, upper level alignment with the Cell Ontology (CL) and the Ontology for Biomedical Investigation, and logical extensions. Construction and content Collaboration among the CLO, CL, and OBI has established consensus definitions of cell line-specific terms such as ‘cell line’, ‘cell line cell’, ‘cell line culturing’, and ‘mortal’ vs. ‘immortal cell line cell’. A cell line is a genetically stable cultured cell population that contains individual cell line cells. The hierarchical structure of the CLO is built based on the hierarchy of the in vivo cell types defined in CL and tissue types (from which cell line cells are derived) defined in the UBERON cross-species anatomy ontology. The new hierarchical structure makes it easier to browse, query, and perform automated classification. We have recently added classes representing more than 2,000 cell line cells from the RIKEN BRC Cell Bank to CLO. Overall, the CLO now contains ~38,000 classes of specific cell line cells derived from over 200 in vivo cell types from various organisms. Utility and discussion The CLO has been applied to different biomedical research studies. Example case studies include annotation and analysis of EBI ArrayExpress data, bioassays, and host-vaccine/pathogen interaction. CLO’s utility goes beyond a catalogue of cell line types. The alignment of the CLO with related ontologies combined with the use of ontological reasoners will support sophisticated inferencing to advance translational informatics development.http://deepblue.lib.umich.edu/bitstream/2027.42/109554/1/13326_2013_Article_185.pd

Connectivity: insights from the U.S. Long Term Ecological Research Network

Ecosystems across the United States are changing in complex and surprising ways. Ongoing demand for critical ecosystem services requires an understanding of the populations and communities in these ecosystems in the future. This paper represents a synthesis effort of the U.S. National Science Foundation-funded Long-Term Ecological Research (LTER) network addressing the core research area of “populations and communities.” The objective of this effort was to show the importance of long-term data collection and experiments for addressing the hardest questions in scientific ecology that have significant implications for environmental policy and management. Each LTER site developed at least one compelling case study about what their site could look like in 50–100 yr as human and environmental drivers influencing specific ecosystems change. As the case studies were prepared, five themes emerged, and the studies were grouped into papers in this LTER Futures Special Feature addressing state change, connectivity, resilience, time lags, and cascading effects. This paper addresses the “connectivity” theme and has examples from the Phoenix (urban), Niwot Ridge (alpine tundra), McMurdo Dry Valleys (polar desert), Plum Island (coastal), Santa Barbara Coastal (coastal), and Jornada (arid grassland and shrubland) sites. Connectivity has multiple dimensions, ranging from multi-scalar interactions in space to complex interactions over time that govern the transport of materials and the distribution and movement of organisms. The case studies presented here range widely, showing how land-use legacies interact with climate to alter the structure and function of arid ecosystems and flows of resources and organisms in Antarctic polar desert, alpine, urban, and coastal marine ecosystems. Long-term ecological research demonstrates that connectivity can, in some circumstances, sustain valuable ecosystem functions, such as the persistence of foundation species and their associated biodiversity or, it can be an agent of state change, as when it increases wind and water erosion. Increased connectivity due to warming can also lead to species range expansions or contractions and the introduction of undesirable species. Continued long-term studies are essential for addressing the complexities of connectivity. The diversity of ecosystems within the LTER network is a strong platform for these studies

Fatigue in patients with chronic disease:results from the population-based Lifelines Cohort Study

(1) To evaluate the prevalence of severe and chronic fatigue in subjects with and without chronic disease; (2) to assess to which extent multi-morbidity contributes to severe and chronic fatigue; and (3) to identify predisposing and associated factors for severe and chronic fatigue and whether these are disease-specific, trans-diagnostic, or generic. The Dutch Lifelines cohort was used, including 78,363 subjects with (n = 31,039, 53 ± 12 years, 33% male) and without (n = 47,324, 48 ± 12 years, 46% male) ≥ 1 of 23 chronic diseases. Fatigue was assessed with the Checklist Individual Strength-Fatigue. Compared to participants without a chronic disease, a higher proportion of participants with ≥ 1 chronic disease were severely (23% versus 15%, p < 0.001) and chronically (17% versus 10%, p < 0.001) fatigued. The odds of having severe fatigue (OR [95% CI]) increased from 1.6 [1.5–1.7] with one chronic disease to 5.5 [4.5–6.7] with four chronic diseases; for chronic fatigue from 1.5 [1.5–1.6] to 4.9 [3.9–6.1]. Multiple trans-diagnostic predisposing and associated factors of fatigue were found, explaining 26% of variance in fatigue in chronic disease. Severe and chronic fatigue are highly prevalent in chronic diseases. Multi-morbidity increases the odds of having severe and chronic fatigue. Several trans-diagnostic factors were associated with fatigue, providing a rationale for a trans-diagnostic approach

A Single Acidic Residue Can Guide Binding Site Selection but Does Not Govern QacR Cationic-Drug Affinity

Structures of the multidrug-binding repressor protein QacR with monovalent and bivalent cationic drugs revealed that the carboxylate side-chains of E90 and E120 were proximal to the positively charged nitrogens of the ligands ethidium, malachite green and rhodamine 6G, and therefore may contribute to drug neutralization and binding affinity. Here, we report structural, biochemical and in vivo effects of substituting these glutamate residues. Unexpectedly, substitutions had little impact on ligand affinity or in vivo induction capabilities. Structures of QacR(E90Q) and QacR(E120Q) with ethidium or malachite green took similar global conformations that differed significantly from all previously described QacR-drug complexes but still prohibited binding to cognate DNA. Strikingly, the QacR(E90Q)-rhodamine 6G complex revealed two mutually exclusive rhodamine 6G binding sites. Despite multiple structural changes, all drug binding was essentially isoenergetic. Thus, these data strongly suggest that rather than contributing significantly to ligand binding affinity, the role of acidic residues lining the QacR multidrug-binding pocket is primarily to attract and guide cationic drugs to the “best available” positions within the pocket that elicit QacR induction

Automated Coding of Job Descriptions From a General Population Study: Overview of Existing Tools, Their Application and Comparison

OBJECTIVES: Automatic job coding tools were developed to reduce the laborious task of manually assigning job codes based on free-text job descriptions in census and survey data sources, including large occupational health studies. The objective of this study is to provide a case study of comparative performance of job coding and JEM (Job-Exposure Matrix)-assigned exposures agreement using existing coding tools. METHODS: We compared three automatic job coding tools [AUTONOC, CASCOT (Computer-Assisted Structured Coding Tool), and LabourR], which were selected based on availability, coding of English free-text into coding systems closely related to the 1988 version of the International Standard Classification of Occupations (ISCO-88), and capability to perform batch coding. We used manually coded job histories from the AsiaLymph case-control study that were translated into English prior to auto-coding to assess their performance. We applied two general population JEMs to assess agreement at exposure level. Percent agreement and PABAK (Prevalence-Adjusted Bias-Adjusted Kappa) were used to compare the agreement of results from manual coders and automatic coding tools. RESULTS: The coding per cent agreement among the three tools ranged from 17.7 to 26.0% for exact matches at the most detailed 4-digit ISCO-88 level. The agreement was better at a more general level of job coding (e.g. 43.8-58.1% in 1-digit ISCO-88), and in exposure assignments (median values of PABAK coefficient ranging 0.69-0.78 across 12 JEM-assigned exposures). Based on our testing data, CASCOT was found to outperform others in terms of better agreement in both job coding (26% 4-digit agreement) and exposure assignment (median kappa 0.61). CONCLUSIONS: In this study, we observed that agreement on job coding was generally low for the three tools but noted a higher degree of agreement in assigned exposures. The results indicate the need for study-specific evaluations prior to their automatic use in general population studies, as well as improvements in the evaluated automatic coding tools