Image_1_The Early Predictive Value of Circulating Monocytes and Eosinophils in Coronary DES Restenosis.TIF

BackgroundMonocytes and eosinophils are involved in intracoronary inflammatory responses, aggravating coronary artery plaque instability and in-stent restenosis (ISR).AimsTo investigate an early prediction of ISR in patients undergoing stenting by circulating monocytes and eosinophils.MethodsThe single-center data of patients undergoing successful drug-eluting stents (DES) implantation from January 1, 2017 to April 30, 2020 were retrospectively analyzed. Of the 4,392 patients assessed, 140 patients with restenosis and 141 patients without restenosis were enrolled. A scheduled postoperative follow-up was proceeded in four sessions: 0–3 months, 3–6 months, 6–12 months, and >12 months. The hematological and biochemical measurement was collected. The angiographic review was completed within two postoperative years.ResultsSignificant associations of monocyte count and percentage with ISR were evident [odds ratio (OR): 1.44, 95% CI: 1.23–1.68, P 9/L and 7.4%, respectively, and those of eosinophil count and percentage were 0.20 × 109/L and 2.5%, respectively.ConclusionThis study, with a long-term follow-up, first provides evidence that the elevated monocytes at three postoperative months and baseline eosinophils may be strong early predictors of ISR after drug-eluting stent implantation. Persistent elevation of monocytes may also be a signal of ISR after percutaneous coronary intervention (PCI).</p

Between-group differences in regional nodal efficiency.

<p>A, histogram of mean nodal efficiency showed an evident shift towards overall decrease in patients with ESRD compared to HCs. B, statistical analysis revealed that the global decrease was driven by numerous regions that predominantly located in lateral and medial prefrontal cortex, motor cortex, posterior parietal cortex, lateral temporal lobe and occipital regions. C, empirical frequency distributions of 221 randomly selected ROIs (10,000 times) in each of the four modules in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0121085#pone.0121085.g002" target="_blank">Fig. 2A</a>. ESRD, end-stage renal disease; HC, healthy control; ROIs, regions of interest; DMN, default mode network; ECN, executive control network; SMN, sensorimotor network; VN, visual network.</p

Between-group differences in gray matter volume.

<p>Multiple cortical and subcortical regions were identified to show gray matter atrophy in ESRD patients compared to HCs. Of note, no significant correlations were observed between nodal efficiency decreases and GM gray matter atrophy in the patients (P > 0.05, False Discovery Rate corrected). GM, gray matter; ESRD, end-stage renal disease.</p

Partial correlation coefficients between network metrics and biochemical parameters.

<p>The partial correlations were computed with age, gender and summary measures of head motion as the confounding covariates. Values in bold indicate significant correlations (<i>P</i>< 0.05). No significant correlations were observed for dialysis duration, kalium level, creatinine level and urea level.</p><p><i>E</i>_<i>loc</i>, local efficiency.</p><p>DMN, default mode network.</p><p>ECN, executive control network.</p><p>SMN, sensorimotor network.</p><p>VN, visual network.</p><p>Partial correlation coefficients between network metrics and biochemical parameters.</p

Decreased nodal efficiency in the patients when the global signals were removed (A) or when one patient with the lowest hemoglobin value was excluded (B).

<p>Decreased nodal efficiency in the patients when the global signals were removed (A) or when one patient with the lowest hemoglobin value was excluded (B).</p

Between-group differences in whole-brain topology.

<p>Error bars denote standard deviations. ESRD, end-stage renal disease; HC, healthy control; <i>E</i>_<i>loc</i>, local efficiency; <i>E</i>_<i>glob</i>, global efficiency; <i>Ẽ</i>_<i>loc</i>, normalized local efficiency; <i>Ẽ</i>_<i>glob</i>, normalized global efficiency.</p

Relationship between network measures and biochemical parameters.

<p>Significant correlations were observed for both global network organization and regional nodal efficiency with biochemical parameters in ESRD patients. SMA, supplemental motor area; SFGmed, medial superior frontal gyrus; R, right; ESRD, end-stage renal disease; HC, healthy control.</p

PCC-based functional connectivity.

<p>PCC-based functional connectivity.</p

Table S4.xlsx from A new insight into the evolution and functional divergence of <i>FRK</i> genes in <i>Pyrus bretschneideri</i>

In plants, plant fructokinases (FRKs) are considered to be the main gateway of fructose metabolism as they can phosphorylate fructose to fructose-6-phosphate. Chinese white pears are one of the popular fruits in the world market; sugar content is an important factor affecting the quality of the fruit. We identified 49 FRKs from four Rosaceae species; 20 of these sequences were from Chinese white pear. Subsequently, phylogenic relationship, gene structure and micro-collinearity were analysed. Phylogenetic and exon–intron analysis classified these FRKs into 10 subfamilies, and was aimed further to reveal the variation of the gene structure and the evolutionary relationship of this gene family. Remarkably, gene expression patterns in different tissues or different development stages of the pear fruit suggested functional redundancy for PbFRKs derived from segmental duplication or genome-wide duplication and sub-functionalization for some of them. Additionally, PbFRK11, PbFRK13 and PbFRK16 were found to play important roles in regulating the sugar content in the fruit. Overall, this study provided important insights into the evolution of the FRK gene family in four Rosaceae species, and highlighted its roles in both pear tissues and fruits. Results presented here provide the appropriate candidate of PbFRKs that might contribute to fructose efflux in the pear fruit

Between-group differences in module-level topology.

<p>Each functional module exhibited altered network organization in patients with ESRD compared to HCs in extremely similar patterns to those observed for the whole-brain networks (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0121085#pone.0121085.g001" target="_blank">Fig. 1</a>). Error bars denote standard deviations. ESRD, end-stage renal disease; HC, healthy control; <i>E</i>_<i>loc</i>, local efficiency; <i>E</i>_<i>glob</i>, global efficiency; <i>Ẽ</i>_<i>loc</i>, normalized local efficiency; <i>Ẽ</i>_<i>glob</i>, normalized global efficiency; DMN, default mode network; ECN, executive control network; SMN, sensorimotor network; VN, visual network.</p