Knightduke8128

Widespread cortical thickness reductions were observed in pre-APM patients. Post-APM patients showed more reductions in cortical thickness, even in the frontotemporal regions without baseline reductions. Covariance analysis revealed strong cortico-cortical covariance and higher network integration in responders than in NRs. For the NRs, some of the prefrontal and temporal nodes were not covariant between the top-n regions with cortical thickness reduction. Antipsychotic effects are not restricted to a single brain region but rather exhibit a network-level covariance pattern. Neuroimaging connectomics highlights the positive effects of antipsychotics on the reconfiguration of brain architecture, suggesting that abnormalities in regional morphology may be compensated by increasing interregional covariance when symptoms are controlled by antipsychotics.

This study examined bidirectional associations between mother- and father-reported medical responsibility and medical skill mastery in youth with spina bifida (SB).

Participants were 140 youth with SB and their parents who participated in three waves of a longitudinal study across four years (ages 8-15 years at Time 1). buy AZD9291 Mother- and father-report of both medical responsibility and medical skill mastery were used, and age and estimated intelligence quotient were included as covariates, in cross-lagged models.

The cross-lagged model provided evidence for significant bidirectional associations between mother-reported medical responsibility and skill mastery across time (root mean square error of approximation=0.09, comparative fix index=0.97). These paths showed that higher levels of child responsibility predicted an increase in skill mastery and that higher levels of mastery predicted an increase in child responsibility across time. Moreover, based on mother-report, sharing of responsibility had stronger effects on increases in skill mastery (Time 1 to Time 2 β=.25, Time 2 to Time 3 β=.27) than skill mastery had on increases in child responsibility (Time 1 to Time 2 β=.08, Time 2 to Time 3 β=.07). The only significant cross-lagged path for father-report was from Time 1 skill mastery to Time 2 responsibility (β=.34).

Mothers perceive a bidirectional relationship between responsibility and skill mastery across time, whereas fathers appear to mainly consider how skills might affect a subsequent increase in responsibility sharing. Thus, it is important to consider both parents' perspectives when working to increase medical autonomy in youth with SB.

Mothers perceive a bidirectional relationship between responsibility and skill mastery across time, whereas fathers appear to mainly consider how skills might affect a subsequent increase in responsibility sharing. Thus, it is important to consider both parents' perspectives when working to increase medical autonomy in youth with SB.

Identifying predictors of electronic nicotine product (ENP) cessation can inform ENP cessation interventions. High rates of co-occurring ENP and cigarette (dual) use and transitions between these products underscore the importance of considering cigarette smoking status when assessing and addressing ENP cessation.

We analyzed waves 3 (W3) and 4 (W4) of the Population Assessment of Tobacco and Health (PATH) study to identify (i) W3 socio-demographics, tobacco and ENP use characteristics, and psychosocial correlates of W3 cigarette smoking status (non-smoker, former and current) among W3 adult ENP users, and (ii) W3 predictors of W4 combined ENP and cigarette smoking abstinence relative to use of one or both products.

At W3, 65.6% of ENP users concurrently smoked cigarettes. Adjusted multinomial regression results indicated that different W3 socio-demographics, tobacco and ENP use characteristics and psychosocial correlates were significantly associated with distinct W3 cigarette use profiles. At W4, 9.9%oking status when designing ENP cessation interventions and defining intervention outcomes.

This analysis contributes to advancing the nascent literature on predictors of electronic nicotine product (ENP) cessation, which can guide the development of ENP cessation interventions by indicating which populations, psychosocial and environmental constructs and co-occurring behaviors interventions should target. This research also highlights the importance of considering cigarette smoking status when designing ENP cessation interventions and defining intervention outcomes.Genetic variants and de novo mutations in regulatory regions of the genome are typically discovered by whole-genome sequencing (WGS), however WGS is expensive and most WGS reads come from non-regulatory regions. The Assay for Transposase-Accessible Chromatin (ATAC-seq) generates reads from regulatory sequences and could potentially be used as a low-cost 'capture' method for regulatory variant discovery, but its use for this purpose has not been systematically evaluated. Here we apply seven variant callers to bulk and single-cell ATAC-seq data and evaluate their ability to identify single nucleotide variants (SNVs) and insertions/deletions (indels). In addition, we develop an ensemble classifier, VarCA, which combines features from individual variant callers to predict variants. The Genome Analysis Toolkit (GATK) is the best-performing individual caller with precision/recall on a bulk ATAC test dataset of 0.92/0.97 for SNVs and 0.87/0.82 for indels within ATAC-seq peak regions with at least 10 reads. On bulk ATAC-seq reads, VarCA achieves superior performance with precision/recall of 0.99/0.95 for SNVs and 0.93/0.80 for indels. On single-cell ATAC-seq reads, VarCA attains precision/recall of 0.98/0.94 for SNVs and 0.82/0.82 for indels. In summary, ATAC-seq reads can be used to accurately discover non-coding regulatory variants in the absence of whole-genome sequencing data and our ensemble method, VarCA, has the best overall performance.Time-series gene expression profiles are the primary source of information on complicated biological processes; however, capturing dynamic regulatory events from such data is challenging. Herein, we present a novel analytic tool, time-series miner (TSMiner), that can construct time-specific regulatory networks from time-series expression profiles using two groups of genes (i) genes encoding transcription factors (TFs) that are activated or repressed at a specific time and (ii) genes associated with biological pathways showing significant mutual interactions with these TFs. Compared with existing methods, TSMiner demonstrated superior sensitivity and accuracy. Additionally, the application of TSMiner to a time-course RNA-seq dataset associated with mouse liver regeneration (LR) identified 389 transcriptional activators and 49 transcriptional repressors that were either activated or repressed across the LR process. TSMiner also predicted 109 and 47 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways significantly interacting with the transcriptional activators and repressors, respectively. These findings revealed the temporal dynamics of multiple critical LR-related biological processes, including cell proliferation, metabolism and the immune response. The series of evaluations and experiments demonstrated that TSMiner provides highly reliable predictions and increases the understanding of rapidly accumulating time-series omics data.There is a pressing need today to mechanistically interpret sets of genomic variants associated with diseases. Here we present a tool called 'VarSAn' that uses a network analysis algorithm to identify pathways relevant to a given set of variants. VarSAn analyzes a configurable network whose nodes represent variants, genes and pathways, using a Random Walk with Restarts algorithm to rank pathways for relevance to the given variants, and reports P-values for pathway relevance. It treats non-coding and coding variants differently, properly accounts for the number of pathways impacted by each variant and identifies relevant pathways even if many variants do not directly impact genes of the pathway. We use VarSAn to identify pathways relevant to variants related to cancer and several other diseases, as well as drug response variation. We find VarSAn's pathway ranking to be complementary to the standard approach of enrichment tests on genes related to the query set. We adopt a novel benchmarking strategy to quantify its advantage over this baseline approach. Finally, we use VarSAn to discover key pathways, including the VEGFA-VEGFR2 pathway, related to de novo variants in patients of Hypoplastic Left Heart Syndrome, a rare and severe congenital heart defect.

Acute lung injury (ALI) is a pulmonary manifestation of an acute systemic inflammatory response, which is associated with high morbidity and mortality. Accordingly, from the perspective of treating ALI, it is important to identify effective agents and elucidate the underlying modulatory mechanisms. β-Caryophyllene (BCP) is a naturally occurring bicyclic sesquiterpene that has anti-cancer and anti-inflammatory activities. However, the effects of BCP on ALI have yet to be ascertained.

ALI was induced intratracheally, injected with 5 mg/kg LPS and treated with BCP. The bone marrow-derived macrophages (BMDMs) were obtained and cultured then challenged with 100 ng/ml LPS for 4 h, with or without BCP pre-treatment for 30 min.

BCP significantly ameliorates LPS-induced mouse ALI, which is related to an alleviation of neutrophil infiltration and reduction in cytokine production. In vitro, BCP was found to reduce the expression of interleukin-6, interleukin-1β and tumour necrosis factor-α, and suppresses the MAPK signalling pathway in BMDMs, which is associated with the inhibition of TAK1 phosphorylation and an enhancement of MKP-1 expression.

Our data indicate that BCP protects against inflammatory responses and is a potential therapeutic agent for the treatment of LPS-induced acute lung injury.

Our data indicate that BCP protects against inflammatory responses and is a potential therapeutic agent for the treatment of LPS-induced acute lung injury.

The nicotine metabolite ratio and nicotine equivalents are measures of metabolism rate and intake. Genome-wide prediction of these nicotine biomarkers in multiethnic samples will enable tobacco-related biomarker, behavioral, and exposure research in studies without measured biomarkers.

We screened genetic variants genome-wide using marginal scans and applied statistical learning algorithms on top-ranked genetic variants, age, ethnicity and sex, and, in additional modeling, cigarettes per day (CPD), (in additional modeling) to build prediction models for the urinary nicotine metabolite ratio (uNMR) and creatinine-standardized total nicotine equivalents (TNE) in 2239 current cigarette smokers in five ethnic groups. We predicted these nicotine biomarkers using model ensembles and evaluated external validity using dependence measures in 1864 treatment-seeking smokers in two ethnic groups.

The genomic regions with the most selected and included variants for measured biomarkers were chr19q13.2 (uNMR, without dictors of physical dependence and nicotine exposure. Predicted nicotine biomarkers may facilitate tobacco-related disease and treatment research in samples with genomic data and limited nicotine metabolite or tobacco exposure data.