PD-1 deficiency protects experimental colitis via alteration of gut microbiota

Programmed cell death-1 (PD-1) is a coinhibitory molecule and plays a pivotal role in immune regulation. Here, we demonstrate a role for PD-1 in pathogenesis of inflammatory bowel disease (IBD). Wild-type (WT) mice had severe wasting disease during experimentally induced colitis, while mice deficient for PD-1 (PD-1(-/-)) did not develop colon inflammation. Interestingly, PD-1(-/-) mice cohoused with WT mice became susceptible to colitis, suggesting that resistance of PD-1(-/-) mice to colitis is dependent on their gut microbiota. 16S rRNA gene-pyrosequencing analysis showed that PD-1(-/-) mice had altered composition of gut microbiota with significant reduction in Rikenellaceae family. These altered colon bacteria of PD-1(-/-) mice induced less amount of inflammatory mediators from colon epithelial cells, including interleukin (IL)-6, and inflammatory chemokines. Taken together, our study indicates that PD-1 expression is involved in the resistance to experimental colitis through altered bacterial communities of colon.112Ysciescopuskc

Reciprocal Relationship Between Depression and Internet Gaming Disorder in Children: A 12-month Follow-Up of the iCURE Study Using Cross-Lagged Path Analysis

Objectives: Previous studies have reported an association between Internet gaming disorder (IGD) and depression, but the directionality of the relationship remains unclear. Therefore, we examined the reciprocal relationship between level of depressive symptoms and IGD among children in a longitudinal study. Methods: Research panels for this study consisted of 366 elementary-school students in the iCURE study. All participants were current Internet users, so they could be considered an at-risk population for IGD. Self-reported severity of IGD features and level of depression were assessed by the Internet Game Use-Elicited Symptom Screen and Children’s Depression Inventory, respectively. Follow-up assessment was completed after 12 months. We fitted cross-lagged structural equation models to investigate the association between the two variables at two time points contemporaneously. Results: The cross-lagged analysis revealed that level of depression at baseline significantly predicted severity of IGD features at the 12-month follow-up (β = 0.15, p = .003). Severity of IGD features at baseline also significantly predicted level of depression at the 12-month follow-up (β = 0.11, p = .018), controlling for possible confounding factors. Conclusions: The cross-lagged path analysis indicates a reciprocal relationship between severity of IGD features and level of depressive symptoms. Understanding the reciprocal relationship between depressive symptoms and severity of IGD features can assist in interventions to prevent both conditions. These findings provide theoretical support for prevention and remediation plans for IGD and depressive symptoms among children

Outcomes of Revision Surgery Following Instrumented Posterolateral Fusion in Degenerative Lumbar Spinal Stenosis: A Comparative Analysis between Pseudarthrosis and Adjacent Segment Disease

Study DesignRetrospective study.PurposeWe examined the clinical and radiological outcomes of patients who received revision surgery for pseudarthrosis or adjacent segment disease (ASD) following decompression and instrumented posterolateral fusion (PLF).Overview of LiteratureAt present, information regarding the outcomes of revision surgery for complications such as pseudarthrosis and ASD following instrumented PLF is limited.MethodsThis study examined 60 patients who received PLF for degenerative lumbar spinal stenosis and subsequently developed pseudarthrosis or ASD leading to revision surgery. Subjects were divided into a group of 21 patients who received revision surgery for pseudarthrosis (Group P) and a group of 39 patients who received revision surgery for ASD (Group A). Clinical outcomes were evaluated using the visual analogue scales for back pain (VAS-BP) and leg pain (VAS-LP), the Korean Oswestry disability index (K-ODI), and each patient's subjective satisfaction. Radiological outcomes were evaluated from the extent of bone union, and complications in the two groups were compared.ResultsVAS-LP at final follow-up was not statistically different between the two groups (p =0.353), although VAS-BP and K-ODI at final follow-up were significantly worse in Group P than in Group A (all p <0.05), and only 52% of the patients in Group P felt that their overall well-being had improved following revision surgery. Fusion rates after the first revision surgery were 71% (15/21) in Group P and 95% (37/39) in Group A (p =0.018). The rate of reoperation was significantly higher in Group P (29%) than in Group A (5%) (p =0.021) due to complications.ConclusionsClinical and radiological outcomes were worse in patients who had received revision surgery for pseudarthrosis than in those who had revision surgery for ASD. Elderly patients should be carefully advised of the risks and benefits before planning revision surgery for pseudarthrosis

Growth direction determination of a single RuO2 nanowire by polarized Raman spectroscopy

The dependence of band intensities in the Raman spectrum of individual single-crystal ruthenium dioxide (RuO2) nanowires on the angle between the plane of polarization of the exciting (and collected) light and the long axis of the nanowire, is shown to be a simple, complementary technique to high resolution transmission electron microscopy (HRTEM) for determining nanowire growth direction. We show that excellent agreement exists between what is observed and what is predicted for the polarization angle dependence of the intensities of the nanowires' E-g (525 cm(-1)) and the B-2g (714 cm(-1)) Raman bands, only by assuming that the nanowires grow along the (001) crystallographic direction, as confirmed by HRTEM.open9

Depression and suicide risk prediction models using blood-derived multi-omics data

More than 300 million people worldwide experience depression; annually, ~800,000 people die by suicide. Unfortunately, conventional interview-based diagnosis is insufficient to accurately predict a psychiatric status. We developed machine learning models to predict depression and suicide risk using blood methylome and transcriptome data from 56 suicide attempters (SAs), 39 patients with major depressive disorder (MDD), and 87 healthy controls. Our random forest classifiers showed accuracies of 92.6% in distinguishing SAs from MDD patients, 87.3% in distinguishing MDD patients from controls, and 86.7% in distinguishing SAs from controls. We also developed regression models for predicting psychiatric scales with R2 values of 0.961 and 0.943 for Hamilton Rating Scale for Depression???17 and Scale for Suicide Ideation, respectively. Multi-omics data were used to construct psychiatric status prediction models for improved mental health treatment