Learning Motion Predictors for Smart Wheelchair using Autoregressive Sparse Gaussian Process

Constructing a smart wheelchair on a commercially available powered wheelchair (PWC) platform avoids a host of seating, mechanical design and reliability issues but requires methods of predicting and controlling the motion of a device never intended for robotics. Analog joystick inputs are subject to black-box transformations which may produce intuitive and adaptable motion control for human operators, but complicate robotic control approaches; furthermore, installation of standard axle mounted odometers on a commercial PWC is difficult. In this work, we present an integrated hardware and software system for predicting the motion of a commercial PWC platform that does not require any physical or electronic modification of the chair beyond plugging into an industry standard auxiliary input port. This system uses an RGB-D camera and an Arduino interface board to capture motion data, including visual odometry and joystick signals, via ROS communication. Future motion is predicted using an autoregressive sparse Gaussian process model. We evaluate the proposed system on real-world short-term path prediction experiments. Experimental results demonstrate the system's efficacy when compared to a baseline neural network model.Comment: The paper has been accepted to the International Conference on Robotics and Automation (ICRA2018

Justification and reporting of subgroup analyses were lacking or inadequate in randomized controlled trials

Objectives: The aim of the article was to assess the appropriateness and rationales of subgroup analyses planned in protocols of randomized controlled trials and reported in subsequent corresponding trial publications. Study Design and Setting: We searched PubMed to identify trial protocols published in journals during 2006–2017. From a total of 3,774 initially identified records, we included a random sample of 479 protocols and identified 280 trial publications corresponding to the included protocols. Results: Subgroup analyses were specified in 19% of the protocols and reported in 21% of the trial publications. Of the 94 protocols with planned subgroup analyses, 32% mentioned testing for interaction, and only three considered statistical power. Subgroup analyses were not prespecified in 56% of the 59 trial publications with subgroup analyses. Subgroup analyses were stated as prespecified in nine trial publications, without support evidence from the corresponding protocols. Subgroup analyses were often reported insufficiently for assessing the consistency of subgroup effects across studies. Justifications for subgroup analyses were provided in only four trial protocols and seven trial publications. Conclusion: Inappropriate specification and reporting of subgroup analyses remain problematic in protocols and reports of randomized controlled trials. Justifications or rationales for subgroup analyses were only rarely provided in trial protocols and reports

Influenza vaccination rates among healthcare workers: a systematic review and meta-analysis investigating influencing factors

IntroductionHealthcare workers risk of exposure to the influenza virus in their work, is a high-risk group for flu infections. Thus WHO recommends prioritizing flu vaccination for them–an approach adopted by >40 countries and/or regions worldwide.MethodsCross-sectional studies on influenza vaccination rates among healthcare workers were collected from PubMed, EMBASE, CNKI, and CBM databases from inception to February 26, 2023. Influenza vaccination rates and relevant data for multiple logistic regression analysis, such as odds ratios (OR) and 95% confidence intervals (CI), were extracted.ResultsA total of 92 studies comprising 125 vaccination data points from 26 countries were included in the analysis. The meta-analysis revealed that the overall vaccination rate among healthcare workers was 41.7%. Further analysis indicated that the vaccination rate was 46.9% or 35.6% in low income or high income countries. Vaccination rates in the Americas, the Middle East, Oceania, Europe, Asia, and Africa were 67.1, 51.3, 48.7, 42.5, 28.5, and 6.5%, respectively. Influencing factors were age, length of service, education, department, occupation, awareness of the risk of influenza, and/or vaccines.ConclusionThe global influenza vaccination rate among healthcare workers is low, and comprehensive measures are needed to promote influenza vaccination among this population.Systematic review registrationwww.inplysy.com, identifier: 202350051

Neurotrophic Signaling Factors in Brain Ischemia/Reperfusion Rats: Differential Modulation Pattern between Single-Time and Multiple Electroacupuncture Stimulation

Electroacupuncture (EA) treatment has been widely used for stroke-like disorders in traditional Chinese medicine. However, the underlying mechanisms remain unclear. Our previous studies showed that single-time EA stimulation at “Baihui” (GV 20) and “Shuigou” (GV 26) after the onset of ischemia can protect the brain against ischemic injury in rats with middle cerebral artery occlusion (MCAO). Here, we further investigated the differential effects between multiple EA and single-time EA stimulation on ischemic injury. In the present study, we found that both single-time EA and multiple EA stimulation significantly reduced MCAO-induced ischemic infarction, while only multiple EA attenuated sensorimotor dysfunctions. Also, with PCR array screening and ingenuity gene analysis, we revealed that multiple EA and single-time EA stimulation could differentially induce expression changes in neurotrophic signaling related genes. Meanwhile, with western blotting, we demonstrated that the level of glia maturation factor β (GMFβ) increased in the early stage (day 1) of reperfusion, and this upregulation was suppressed only by single-time EA stimulation. These findings suggest that the short-term effect of single-time EA stimulation differs from the cumulative effect of multiple EA, which possibly depends on their differential modulation on neurotrophic signaling molecules expression

The role of IL-36 and 37 in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) has garnered considerable attention due to its morbidity and mortality. Although the precise mechanisms underlying HCC tumorigenesis remain to be elucidated, evidence suggests that host immunity plays a pivotal role in its development. IL-36 and IL-37 are important immunoregulatory cytokines classified as pro-inflammatory and anti-inflammatory respectively. In the context of HCC, the downregulation of intrahepatic IL-36 is inversely correlated with cirrhosis, but positively correlated with 5-year survival rates, suggesting that IL-36 offers protection during HCC development. However, IL-36 may lose its hepatoprotective effects as the disease progresses to HCC in the context of dysregulated immunity in cirrhotic patients. Substantially increased circulating IL-36 in HCC patients is likely a systemic response to HCC stimulation, but is insufficient to suppress progression towards HCC. Intrahepatic IL-37 is suppressed in HCC patients, consistent with the inverse correlation between intrahepatic IL-37 and the level of AFP in HCC patients, suggesting IL-37 exerts hepatoprotection. There is no significant difference in IL-37 among differentiations of HCC or with respect to clinical BCLC stages or cirrhosis status in HCC patients. However, IL-37 protection is demonstrated in an IL-37 transfected HCC animal model, showing significantly reduced tumour size. IL-36/37 may inhibit HCC by enhancing M1 tumour-associated macrophages while not affecting M2 macrophages. The interplay between IL-36 (pro-inflammatory) and IL-37 (anti-inflammatory) is emerging as a crucial factor in host protection against the development of HCC. Further research is needed to investigate the complex mechanisms involved and the therapeutic potential of targeting these cytokines in HCC management

Comprehensive Pan-Genomic Characterization of Adrenocortical Carcinoma

SummaryWe describe a comprehensive genomic characterization of adrenocortical carcinoma (ACC). Using this dataset, we expand the catalogue of known ACC driver genes to include PRKAR1A, RPL22, TERF2, CCNE1, and NF1. Genome wide DNA copy-number analysis revealed frequent occurrence of massive DNA loss followed by whole-genome doubling (WGD), which was associated with aggressive clinical course, suggesting WGD is a hallmark of disease progression. Corroborating this hypothesis were increased TERT expression, decreased telomere length, and activation of cell-cycle programs. Integrated subtype analysis identified three ACC subtypes with distinct clinical outcome and molecular alterations which could be captured by a 68-CpG probe DNA-methylation signature, proposing a strategy for clinical stratification of patients based on molecular markers

Genetic effects on gene expression across human tissues

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of diseas

High-coverage whole-genome analysis of 1220 cancers reveals hundreds of genes deregulated by rearrangement-mediated cis-regulatory alterations.

The impact of somatic structural variants (SVs) on gene expression in cancer is largely unknown. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole-genome sequencing data and RNA sequencing from a common set of 1220 cancer cases, we report hundreds of genes for which the presence within 100 kb of an SV breakpoint associates with altered expression. For the majority of these genes, expression increases rather than decreases with corresponding breakpoint events. Up-regulated cancer-associated genes impacted by this phenomenon include TERT, MDM2, CDK4, ERBB2, CD274, PDCD1LG2, and IGF2. TERT-associated breakpoints involve ~3% of cases, most frequently in liver biliary, melanoma, sarcoma, stomach, and kidney cancers. SVs associated with up-regulation of PD1 and PDL1 genes involve ~1% of non-amplified cases. For many genes, SVs are significantly associated with increased numbers or greater proximity of enhancer regulatory elements near the gene. DNA methylation near the promoter is often increased with nearby SV breakpoint, which may involve inactivation of repressor elements

The Somatic Genomic Landscape of Chromophobe Renal Cell Carcinoma

We describe the landscape of somatic genomic alterations of 66 chromophobe renal cell carcinomas (ChRCCs) based on multidimensional and comprehensive characterization, including mitochondrial DNA (mtDNA) and whole genome sequencing. The result is consistent that ChRCC originates from the distal nephron compared to other kidney cancers with more proximal origins. Combined mtDNA and gene expression analysis implicates changes in mitochondrial function as a component of the disease biology, while suggesting alternative roles for mtDNA mutations in cancers relying on oxidative phosphorylation. Genomic rearrangements lead to recurrent structural breakpoints within TERT promoter region, which correlates with highly elevated TERT expression and manifestation of kataegis, representing a mechanism of TERT up-regulation in cancer distinct from previously-observed amplifications and point mutations

Genetic effects on gene expression across human tissues

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of disease