Appendix A. Details of multivariate regression procedures.

Details of multivariate regression procedures

Most important gray and adjacent white matter regions discriminating between heavy smokers and controls.

<p>W_i, weight of each cluster centroid <i>i</i>.</p

Regions that showed a significant structural difference between heavy smokers and controls from the VBM analysis: smaller volume in the bilateral cerebellum tosil (A); larger adjacent white matter volume in the anterior cingulate cortex (ACC) and the midcingulate cortex (MCC)/posterior cingulate cortex (PCC) (B), as well as the bilateral putamen (C).

<p>For display purpose, images were thresholded at P<0.001, uncorrected.</p

Discrimination map for grey (A) and white matter (B) classification.

<p>Red indicates higher values in the smokers than non-smokers, while blue indicates higher values for the non-smoker group than the smoker group. These regions were identified by setting the threshold to the top 30% of the weight vector scores. The x-coordinate for each sagittal slice and y-coordinate for each coronal slice in the standard Talairach space are given in millimetres.</p

DataSheet1_Prognostic significance and immune landscape of a fatty acid metabolism-related gene signature in colon adenocarcinoma.docx

Background: Fatty acid metabolism (FAM), as a hallmark of caner, plays important roles in tumor initiation and carcinogenesis. However, the significance of fatty acid metabolism-related genes in colon adenocarcinoma (COAD) are largely unknown.Methods: RNA sequencing data and clinical information were downloaded from the Cancer Genome Atlas (TCGA) cohort. Univariate and multivariate Cox regression analyses were utilized to construct a fatty acid metabolism-related gene signature. Kaplan-Meier survival and receiver operating characteristic (ROC) analyses were used to verify the performance of this signature. GEO datasets were applied to validate the signature. Maftools package was utilized to analyze the mutation profiles of this signature. Correlation between the risk signature and stemness scores was compared by RNA stemness score (RNAss). Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene set variation analysis (GSVA) were performed to explore the potential functions and signaling pathways. Immune landscape of the signature was explored by analyzing different immune cells infiltration, immune functions and microsatellite instability. A nomogram was constructed by combining the risk signature and multiple clinical factors. Expression levels and prognostic values of the risk genes were revealed in the cancer genome atlas and GEO databases. Moreover, the expression the risk genes were measured in cell lines using real time quantitative PCR (qRT-PCR).Results: Eight fatty acid metabolism-related genes (CD36, ENO3, MORC2, PTGR1, SUCLG2, ELOVL3, ELOVL6 and CPT2) were used to construct a risk signature. This signature demonstrated better prognostic value than other clinicopathological parameters, with AUC value was 0.734 according to the cancer genome atlas database. There was negative correlation between the riskscore and RNA stemness score. The patients in the high-risk group demonstrated higher infiltration of M0 macrophages, and less infiltration of activated CD4 memory T cells and Eosinophils. There were more MSI patients in the high-risk group than those in the low-risk group (38% vs. 30%). The risk scores of patients in the MSI group were slightly higher than those in the microsatellite stability group. Gene ontology, kyoto encyclopedia of genes and genomes and gene set variation analysis enrichment analyses showed that several metabolism-related functions and signaling pathways were enriched. A nomogram showed good predictive capability of the signature. Moreover, qRT-PCR revealed upregulated expression of ENO3, MORC2, SUCLG2 and ELOVL6, and downregulated expression of CPT2 in all examined colon adenocarcinoma cell lines.Conclusion: This study provided novel insights into a fatty acid metabolism-related signature in the prognosis an immune landscape of colon adenocarcinoma patients.</p

Trace plots of two independent MCMC chains.

<p>The two chains for selected parameters from fitting <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0065697#pone.0065697.e030" target="_blank">Equations 3</a>–<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0065697#pone.0065697.e031" target="_blank"></a><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0065697#pone.0065697.e032" target="_blank"></a><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0065697#pone.0065697.e042" target="_blank"></a><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0065697#pone.0065697.e043" target="_blank"></a><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0065697#pone.0065697.e076" target="_blank"></a><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0065697#pone.0065697.e107" target="_blank">9</a> (assuming ) are shown in red and blue, both thinned by 100 iterations. (a) Intercept . (b) Regression coefficient of the (centered) interaction . (c) Random effect . (d) Latent health . (e) Standard deviation . (f) Fixed effect . Trace plots for all other model parameters show similar patterns that suggest convergence after a burn-in of merely 1,000.</p

Table_2_Associations between two conceptualizations of materialism and subjective wellbeing in China: A meta-analysis of studies from 1998 to 2022.XLSX

This meta-analysis examines the relationship between materialism (materialistic values and extrinsic aspirations) and subjective wellbeing in the Chinese population. Fifty-six relevant studies covering the period from 1998 to 2022 were included in the meta-analysis. Fifty-eight independent effect sizes from a total of 52,368 participants were obtained to calculate the mean effect sizes. Materialistic values correlated with significantly lower subjective wellbeing (r = −0.205), while the mean effect size for extrinsic aspirations was found to be not significant (r = −0.048). The effect sizes varied across different types of wellbeing outcomes (materialistic values: rs = −0.095 to −0.202; extrinsic aspirations: rs = 0.066 to −0.125). The associations were also moderated by certain demographic factors (age and gender), methodological factors (study design and scoring method), publication features (type of publication and publication year), and economic indicators (economic growth and wealth inequality). We discuss our limitations and the implications for future research.</p

Metrics based on the definition of AMBI, used to construct LHFIs for the Richibucto estuary.

<p>Metrics based on the definition of AMBI, used to construct LHFIs for the Richibucto estuary.</p

Selected summary statistics of posterior draws.

<p>Selected summary statistics of posterior draws.</p

Distance downstream (km) for Richibucto sites.

<p>Distance downstream (km) for Richibucto sites.</p