Barnessexton0721

Autoantibodies are a hallmark of both autoimmune disease and cancer, but they also occur in healthy individuals. Here, we perform a meta-analysis of nine datasets and focus on the common autoantibodies shared by healthy individuals. We report 77 common autoantibodies based on the protein microarray data obtained from probing 182 healthy individual sera on 7,653 human proteins and an additional 90 healthy individual sera on 1,666 human proteins. There is no gender bias; however, the number of autoantibodies increase with age, plateauing around adolescence. We use a bioinformatics pipeline to determine possible molecular-mimicry peptides that can contribute to the elicitation of these common autoantibodies. There is enrichment of intrinsic properties of proteins like hydrophilicity, basicity, aromaticity, and flexibility for common autoantigens. Subcellular localization and tissue-expression analysis reveal that several common autoantigens are sequestered from the circulating autoantibodies.Generalization of visual aversion is a critical function of the brain that supports survival, but the underlying neurobiological mechanisms are unclear. We establish a rapid generalization procedure for inducing visual aversion by dynamic stripe images. By using fiber photometry, apoptosis, chemogenetic and optogenetic techniques, and behavioral tests, we find that decreased cholinergic neurons' activity in the medial septum (MS) leads to generalization loss of visual aversion. Strikingly, we identify a projection from MS cholinergic neurons to the medial habenula (MHb) and find that inhibition of the MS→MHb cholinergic circuit disrupts aversion-generalization formation while its continuous activation disrupts subsequent extinction. Further studies show that MS→MHb cholinergic projections modulate the generalization of visual aversion possibly via M1 muscarinic acetylcholine receptors (mAChRs) of downstream neurons coreleasing glutamate and acetylcholine. These findings reveal that the MS→MHb cholinergic circuit is a critical node in aversion-generalization formation and extinction and potentially provides insight into the pathogenesis of affective disorders.Adaptive behavior critically depends on the detection of behaviorally relevant stimuli. The anterior insular cortex (aIC) has long been proposed as a key player in the representation and integration of sensory stimuli, and implicated in a wide variety of cognitive and emotional functions. However, to date, little is known about the contribution of aIC interneurons to sensory processing. By using a combination of whole-brain connectivity tracing, imaging of neural calcium dynamics, and optogenetic modulation in freely moving mice across different experimental paradigms, such as fear conditioning and social preference, we describe here a role for aIC vasoactive intestinal polypeptide-expressing (VIP+) interneurons in mediating adaptive behaviors. Our findings enlighten the contribution of aIC VIP+ interneurons to sensory processing, showing that they are anatomically connected to a wide range of sensory-related brain areas and critically respond to behaviorally relevant stimuli independent of task and modality.

Research suggests that circRNAs play important roles in non-small cell lung cancer (NSCLC). The function of hsa_circ_0068252 in NSCLC, especially in cisplatin (DDP) resistance and the mechanisms, was explored in this study.

NSCLC patient samples and two NSCLC cell lines along with corresponding DDP-resistant cell lines were used. Expression levels of circ_0068252 were detected. SiRNA for circ_0068252 and inhibitor for miRNA were used in all functional analyses. A co-culture system of NSCLC cells with CD8+ T cells was used. The cellular location of circ_0068252 was detected and its target miRNA was predicted and verified. Finally, the mechanism responsible for circ_0068252 function on PD-L1 was analyzed using luciferase reporter assay in the two DDP-resistant cell lines, as well as in the co-culture system. The cytotoxicity of T cells was detected by lactate dehydrogenase assay.

Our findings revealed that a high level of circ_0068252 was correlated with poor prognosis of NSCLC and DDP resistance. Knockdown of circ_0068252 could promote the sensitivity of DDP-resistant NSCLC cells to DDP. Moreover, knockdown of circ_0068252 could regulate the immune microenvironment which was mediated via CD8+ T cells. Finally, circ_0068252 could up-regulate PD-L1 expression by adsorbing miR-1304-5p.

The circ_0068252/miR-1304-5p/PD-L1 signal axis participates in the regulation of DDP resistance and immune escape of NSCLC cells. Our results suggest that circ_0068252 may be a potential diagnostic marker and therapeutic target for DDP-resistant NSCLC.

The circ_0068252/miR-1304-5p/PD-L1 signal axis participates in the regulation of DDP resistance and immune escape of NSCLC cells. Our results suggest that circ_0068252 may be a potential diagnostic marker and therapeutic target for DDP-resistant NSCLC.With the advances in high-throughput biotechnologies, high-dimensional multi-layer omics data become increasingly available. They can provide both confirmatory and complementary information to disease risk and thus have offered unprecedented opportunities for risk prediction studies. However, the high-dimensionality and complex inter/intra-relationships among multi-omics data have brought tremendous analytical challenges. Here we present a computationally efficient penalized linear mixed model with generalized method of moments estimator (MpLMMGMM) for the prediction analysis on multi-omics data. Our method extends the widely used linear mixed model proposed for genomic risk predictions to model multi-omics data, where kernel functions are used to capture various types of predictive effects from different layers of omics data and penalty terms are introduced to reduce the impact of noise. Compared with existing penalized linear mixed models, the proposed method adopts the generalized method of moments estimator and it is much more computationally efficient. Through extensive simulation studies and the analysis of positron emission tomography imaging outcomes, we have demonstrated that MpLMMGMM can simultaneously consider a large number of variables and efficiently select those that are predictive from the corresponding omics layers. It can capture both linear and nonlinear predictive effects and achieves better prediction performance than competing methods.

HBI-8000 (tucidinostat) is a novel, oral histone deacetylase inhibitor that selectivity inhibits Class I (histone deacetylase 1, 2, 3) and Class II (histone deacetylase 10) with direct anti-tumor activity through various mechanisms of action, including epigenetic reprogramming and immunomodulation. It has been approved in China for the treatment of relapsed or refractory peripheral T-cell lymphoma.

This multicenter, prospective phase I dose-escalation trial evaluating the safety of twice weekly HBI-8000 was conducted in Japan. Eligible patients had non-Hodgkin's lymphoma and no available standard therapy. The primary endpoint was maximum tolerated dose; secondary endpoints included anti-tumor activity, safety and pharmacokinetics.

Fourteen patients were enrolled in the study. Twelve patients were assessed for dose-limiting toxicity six patients in the 30mg BIW cohort had no dose-limiting toxicitys; two of six patients in the 40mg BIW cohort had asymptomatic dose-limiting toxicitys. Treatment was well toults are encouraging.

It is not known whether modern stroke unit care reduces the impact of stroke complications, such as stroke-associated pneumonia (SAP), on clinical outcomes. We investigated the relationship between SAP and clinical outcomes, adjusting for the confounding effects of stroke care processes and their timing.

The Sentinel Stroke National Audit Programme provided patient data for all confirmed strokes between April 2013 and December 2018. SAP was defined as new antibiotic initiation for suspected pneumonia within the first 7 days from stroke admission. We compared outcomes after SAP versus non-SAP in appropriate multilevel mixed models. Each model was adjusted for patient and clinical characteristics, as well as markers of stroke care and their timing within the first 72 h. The appropriate effect estimates and corresponding 95% confidence intervals (CIs) were reported.

Of 201,778 patients, SAP was present in 14.2%. After adjustment for timing of acute stroke care processes and clinical characteristics, adverse outcomes remained for SAP versus non-SAP patients. In these adjusted analyses, patients with SAP maintained an increased risk of longer length of in-hospital stay (IRR of 1.27; 95% CI 1.25, 1.30), increased odds of worse functional outcome at discharge (OR of 2.9; 95% CI 2.9, 3.0), and increased risk of in-hospital mortality (HR of 1.78; 95% CI 1.74, 1.82).

We show for the first time that SAP remains associated with worse clinical outcomes, even after adjusting for processes of acute stroke care and their timing. These findings highlight the importance of continued research efforts aimed at preventing SAP.

We show for the first time that SAP remains associated with worse clinical outcomes, even after adjusting for processes of acute stroke care and their timing. These findings highlight the importance of continued research efforts aimed at preventing SAP.

The utility of endoscopic ultrasonography (EUS) in predicting tumor depth among superficial nonampullary duodenal epithelial tumors (SNADETs) is unclear. The aim was to compare EUS with conventional endoscopy (CE) for the evaluation of tumor invasion of SNADETs.

A retrospective analysis was performed on consecutive 174 lesions/169 patients with duodenal dysplasia or adenocarcinoma with invasion up to submucosa who underwent both CE and EUS before endoscopic (n = 133) or surgical (n = 41) treatment. Endoscopic staging by CE was performed based on the characteristic endoscopic criteria of submucosal invasion (irregular surface, submucosal tumor [SMT]-like marginal elevation, and fusion of converging folds). The diagnostic performance of each test was compared with the final histology.

The sensitivity and accuracy of estimating the depth were higher for CE compared to that of EUS (99.4% vs. 89.4%, p < 0.01 and 97.7% vs. 87.9%, p < 0.01, respectively). Univariate analysis of endoscopic factors revealed that tumor diameter, red color, SMT-like appearance, and hypoechogenicity were factors related to advanced histology. Multivariate analysis revealed that the presence of SMT-like appearance based on CE was an independent factor to predict submucosal invasion (p = 0.025). Gross morphology of the combined type was associated to incorrect diagnosis of EUS (p = 0.007). Among 3 cases in which EUS overestimated the tumor depth, carcinoma extension in submucosal Brunner's gland or nontumorous submucosal cystic dilation was observed.

EUS may not be necessary, and CE may be sufficient for determining the optimal therapeutic strategy for SNADETs.

EUS may not be necessary, and CE may be sufficient for determining the optimal therapeutic strategy for SNADETs.Internal validation is the most popular evaluation strategy used for drug-target predictive models. The simple random shuffling in the cross-validation, however, is not always ideal to handle large, diverse and copious datasets as it could potentially introduce bias. Hence, these predictive models cannot be comprehensively evaluated to provide insight into their general performance on a variety of use-cases (e.g. permutations of different levels of connectiveness and categories in drug and target space, as well as validations based on different data sources). In this work, we introduce a benchmark, BETA, that aims to address this gap by (i) providing an extensive multipartite network consisting of 0.97 million biomedical concepts and 8.5 million associations, in addition to 62 million drug-drug and protein-protein similarities and (ii) presenting evaluation strategies that reflect seven cases (i.e. general, screening with different connectivity, target and drug screening based on categories, searching for specific drugs and targets and drug repurposing for specific diseases), a total of seven Tests (consisting of 344 Tasks in total) across multiple sampling and validation strategies.