The satellite compass is one of new variants of satellite navigational devices. Is it still treated with caution on International Convention for the Safety of Life at Sea (SOLAS) vessels, but has become popular on the fishing vessels and pleasure crafts. The standard data obtained by such devices suggest accuracy of satellite compasses at a level of about 1 degree, so it seems to be as accurate as gyro or the magnetic equivalent. A changeability of heading errors, especially its frequency spectrum, is analyzed and presented in the paper. The results of comparison of an onboard standard gyrocompass, a fiber-optic gyrocompass (FOG) and a satellite compass in real shipping circumstances have been discussed based on the available literature and previous research. The similar comportment of these compasses are confirmed, however, in real circumstances it is difficult to separate heading oscillations produced by the ships yaw (or helmsman abilities) from the oscillations of the compass. Analysis of the heading oscillations has been performed based on the measurements of the heading indications of stationary compass devices and the devices mounted on the vehicles moving on the straight line (straight part of a road and tram line) to separate the impact of the vessel steering system. Results of heading changeability in the frequency domain are presented based on the Fourier transform theory.

With the advance of sequencing technology, an increasing number of populations have been sequenced to study the histories of worldwide populations, including their divergence, admixtures, migration, and effective sizes. The variants detected in sequencing studies are largely rare and mostly population specific. Population-specific variants are often recent mutations and are informative for revealing substructures and admixtures in populations; however, computational methods and tools to analyze them are still lacking. In this work, we propose using reference populations and single nucleotide polymorphisms (SNPs) specific to the reference populations. Ancestral information, the best linear unbiased estimator (BLUE) of the ancestral proportion, is proposed, which can be used to infer ancestral proportions in recently admixed target populations and measure the extent to which reference populations serve as good proxies for the admixing sources. Based on the same panel of SNPs, the ancestral information is comparable across samples from different studies and is not affected by genetic outliers, related samples, or the sample sizes of the admixed target populations. In addition, ancestral spectrum is useful for detecting genetic outliers or exploring co-ancestry between study samples and the reference populations. The methods are implemented in a program, Ancestral Spectrum Analyzer (ASA), and are applied in analyzing high-coverage sequencing data from the 1000 Genomes Project and the Human Genome Diversity Project (HGDP). In the analyses of American populations from the 1000 Genomes Project, we demonstrate that recent admixtures can be dissected from ancient admixtures by comparing ancestral spectra with and without indigenous Americans being included in the reference populations.

Analysis of the related risks of disease provides a scientific basis for disease prevention and treatment, hospital management, and policy formulation by the changes in disease spectrum of patients in hospital. Retrospective analysis was made to the first diagnosis, age, gender, daily average cost of hospitalized patients, and other factors in the First Affiliated Hospital of Nanjing Medical University during 2006-2013. The top 4 cases were as follows: cardiovascular disease, malignant tumors, lung infections, and noninsulin dependent diabetes mellitus. By the age of disease analysis, we found a younger age trend of cardiovascular disease, and the age of onset of cancer or diabetes was somewhat postponed. The average daily cost of hospitalization and the average daily cost of the main noncommunicable diseases were both on the rise. Noncommunicable diseases occupy an increasingly important position in the constitution of the disease, and they caused an increasing medical burden. People should pay attention to health from the aspects of lifestyle changing. Hospitals should focus on building the appropriate discipline. On the other hand, an integrated government response is required to tackle key risks. Multiple interventions are needed to lower the burden of these diseases and to improve national health.

Autism spectrum disorder (ASD) is not a single disease but a set of disorders. To find clues of ASD pathogenesis in transcriptomic data, we performed an integrated transcriptomic analysis of ASD. After screening based on several standards in Gene Expression Omnibus (GEO) database, we obtained 11 series of transcriptomic data of different human tissues of ASD patients and healthy controls. Multidimensional scaling analysis revealed that datasets from the same tissue had bigger similarity than from different tissues. Functional enrichment analysis demonstrated that differential expressed genes were significantly enriched in inflammation/immune response, mitochondrion-related function and oxidative phosphorylation. Interestingly, genes enriched in inflammation/immune response were up-regulated in the brain tissues and down-regulated in the blood. In addition, drug prediction provided several compounds which might reverse gene expression profiles of ASD patients. And we also replicated the methods and criteria of transcriptomic analysis with datasets of ASD animal models and healthy controls, the results from animal models consolidated the results of transcriptomic analysis of ASD human tissues. In general, the results of our study may provide researchers a new sight of understanding the etiology of ASD and clinicians the possibilities of developing medical therapies.

To compare the reported accuracy and sensitivity of the various modalities used to diagnose autism spectrum disorders (ASD) in efforts to help focus further biomarker research on the most promising methods for early diagnosis.

Cre/Lox technology is a powerful tool in the mouse genetics tool-box as it enables tissue-specific and inducible mutagenesis of specific gene loci. Correct interpretation of phenotypes depends upon knowledge of the Cre expression pattern in the chosen mouse driver line to ensure that appropriate cell types are targeted. For studies of the brain and neurological disease a pan-neuronal promoter that reliably drives efficient neuron-specific transgene expression would be valuable. Here we compare a widely used "pan-neuronal" mouse Cre driver line, Syn1-cre, with a little-known alternative, Snap25-IRES2-cre. Our results show that the Syn1-cre line broadly expresses in the brain but is indetectable in more than half of all neurons and weakly active in testes. In contrast the Snap25-IRES2-cre line expressed Cre in a high proportion of neurons (~85%) and was indetectable in all non-brain tissues that were analysed, including testes. Our findings suggest that for many purposes Snap25-IRES2-cre is superior to Syn1-cre as a potential pan-neuronal cre driver.

Evidence of executive dysfunction in autism spectrum disorders (ASD) across development remains mixed and establishing its role is critical for guiding diagnosis and intervention. The primary objectives of this meta-analysis is to analyse executive function (EF) performance in ASD, the fractionation across EF subdomains, the clinical utility of EF measures and the influence of multiple moderators (for example, age, gender, diagnosis, measure characteristics). The Embase, Medline and PsychINFO databases were searched to identify peer-reviewed studies published since the inclusion of Autism in DSM-III (1980) up to end of June 2016 that compared EF in ASD with neurotypical controls. A random-effects model was used and moderators were tested using subgroup analysis. The primary outcome measure was Hedges' g effect size for EF and moderator factors. Clinical sensitivity was determined by the overlap percentage statistic (OL%). Results were reported according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. A total of 235 studies comprising 14 081 participants were included (N, ASD=6816, Control=7265). A moderate overall effect size for reduced EF (Hedges' g=0.48, 95% confidence interval (CI) 0.43-0.53) was found with similar effect sizes across each domain. The majority of moderator comparisons were not significant although the overall effect of executive dysfunction has gradually reduced since the introduction of ASD. Only a small number of EF measures achieved clinical sensitivity. This study confirms a broad executive dysfunction in ASD that is relatively stable across development. The fractionation of executive dysfunction into individual subdomains was not supported, nor was diagnostic sensitivity. Development of feasible EF measures focussing on clinical sensitivity for diagnosis and treatment studies should be a priority.

Mutations in RHO are the most common cause of autosomal dominant retinitis pigmentosa. However, the pathogenicity of many RHO variants is questionable. This study was designed to investigate the genotype-phenotype correlation for RHO variants. These RHO variants were collected from the in-house exome sequencing data of 7092 probands suffering from different types of eye conditions. The variants were classified using bioinformatics tools, family segregation, and clinical phenotypes. The RHO variants were assessed using multiple online tools and a genotype-phenotype analysis based on the data collected from of ours, gnomAD, and published literature. Totally, 52 heterozygous variants of RHO were detected in the 7092 probands. Of these 52, 17 were potentially pathogenic, were present in 35 families, and comprised 15 missense variants, one inframe deletion and one nonsense variant. All the 15 missense variants were predicted to be damaging by five different online tools. The analysis of the clinical data of the patients from the 35 families revealed certain common features, of an early damage to both the rods and the cones, relatively preserved visual acuity in adulthood, and mid-peripheral tapetoretinal degeneration with pigmentation or RPE atrophy. Our data, the data from gnomAD, and the systematic review of the 246 previously reported variants suggest that approximately two-thirds of the rare missense variants and most of the truncated variants involving upstream of K296 are likely benign. This study provides a brief summary of the characteristics of the pathogenic RHO variants. It emphasizes that the systematic evaluation of these variants at the individual-gene level is crucial in the current era of clinical genetic testing even for a well-known gene such as RHO.

The gold standard for clinical assessment of Autism Spectrum Disorders (ASD) relies on assessing behavior via semi-structured play-based interviews and parent interviews. Although these methods show good sensitivity and specificity in diagnosing ASD cases, behavioral assessments alone may hinder the identification of asymptomatic at-risk group. Resting-state functional magnetic resonance imaging (rs-fMRI) could be an appropriate approach to produce objective neural markers to supplement behavioral assessments due to its non-invasive and task-free nature. Previous neuroimaging studies reported inconsistent resting-state abnormalities in ASD, which may be explained by small sample sizes and phenotypic heterogeneity in ASD subjects, and/or the use of different analytical methods across studies. The current study aims to investigate the local resting-state abnormalities of ASD regardless of subject age, IQ, gender, disease severity and methodological differences, using activation likelihood estimation (ALE). MEDLINE/PubMed databases were searched for whole-brain rs-fMRI studies on ASD published until Feb 2018. Eight experiments involving 424 subjects were included in the ALE meta-analysis. We demonstrate two ASD-related resting-state findings: local underconnectivity in the dorsal posterior cingulate cortex (PCC) and in the right medial paracentral lobule. This study contributes to uncovering a consistent pattern of resting-state local abnormalities that may serve as potential neurobiological markers for ASD.

Autism is a complex genetic disorder where both de-novo and inherited genetics factors play a role. Next generation sequencing approaches have been extensively used to identify rare variants associated with autism. To date, all such studies were focused on nuclear genome; thereby leaving the role of mitochondrial DNA (mtDNA) variation in autism unexplored. Recently, analytical tools have been developed to evaluate mtDNA in whole-exome data. We have analyzed the mtDNA sequence derived from whole-exome sequencing in 10 multiplex families. In one of the families we have identified two variants of interest in MT-ND5 gene that were previously determined to impair mitochondrial function. In addition in a second family we have identified two VOIs; mtDNA variant in MT-ATP6 and nuclear DNA variant in NDUFS4, where both VOIs are within mitochondrial Respiratory Chain Complex. Our findings provide further support for the role of mitochondria in ASD and confirm that whole-exome sequencing allows for analysis of mtDNA, which sets a stage for further comprehensive genetic investigations of the role of mitochondria in autism. Autism Res 2017, 10: 1338-1343. © 2017 International Society for Autism Research, Wiley Periodicals, Inc.

Thyroid dyshormonogenesis (DH) is a genetically heterogeneous inherited disorder caused by thyroid hormone synthesis abnormalities. This study aims at comprehensively characterizing the mutation spectrum in Chinese patients with DH.

Biological motion, namely the movement of others, conveys information that allows the identification of affective states and intentions. This makes it an important avenue of research in autism spectrum disorder where social functioning is one of the main areas of difficulty. We aimed to create a quantitative summary of previous findings and investigate potential factors, which could explain the variable results found in the literature investigating biological motion perception in autism.

We conducted a meta-analysis to summarize the evidence from epidemiological studies of the association between asthma and autism spectrum disorder (ASD).

A rapidly increasing flow of genomic data requires the development of efficient methods for obtaining its compact representation. Feature extraction facilitates classification, clustering and model analysis for testing and refining biological hypotheses. "Shotgun" metagenome is an analytically challenging type of genomic data - containing sequences of all genes from the totality of a complex microbial community. Recently, researchers started to analyze metagenomes using reference-free methods based on the analysis of oligonucleotides (k-mers) frequency spectrum previously applied to isolated genomes. However, little is known about their correlation with the existing approaches for metagenomic feature extraction, as well as the limits of applicability. Here we evaluated a metagenomic pairwise dissimilarity measure based on short k-mer spectrum using the example of human gut microbiota, a biomedically significant object of study.

In daily contexts, fabrics embodied in garments are in contact with human body all the time. Since fabric material properties-such as softness or fineness-can be easily sensed by human fingertips, fabric materials can be roughly identified by fingertip sliding. Identification by simply touching and sliding is convenient and fast, although the room for error is always very large. In this study, a highly discernible fabric humanoid identification method with a fingertip structure inspired tactile sensor is designed to investigate the fabric material properties by characterizing the power spectrum integral of vibration signal basing on fast Fourier transform integral S(FFT), which is generated from a steel ball probe rubbing against a fabric surface at an increasing sliding velocity and normal load, respectively. kv and kw are defined as the slope values to identify the fabric surface roughness and hardness. A sample of 21 pieces of fabric categorized by yarn weight, weave pattern, and material were tested by this method. It was proved that the proposed humanoid sensing method has more efficient compared with fingertip sliding while it is also much more accurate for fabric material identification. Our study would be discussed in light of textile design and has a great number of potential applications in humanoid tactile perception technology.

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by early-onset social-communication challenges, restricted and repetitive behaviors, or unusual sensory-motor behaviors. A lack of specific biomarkers hinders the early diagnosis and treatment of this disease in many children. This study analyzes and validates potential urinary biomarkers using mass spectrometry proteomics. Global proteomics profiles of urine from 19 ASD patients and 19 healthy control subjects were compared to identify significantly changed proteins. These proteins were validated with targeted proteomics using parallel reaction monitoring (PRM) in an independent validation set consisting of samples from 40 ASD patients and 38 healthy controls. A total of 34 significantly changed proteins were found in the discovery set, among which seven proteins were identified as potential biomarkers for ASD through PRM assays in the validation set. Of these seven proteins, immunoglobulin kappa variable 4-1, immunoglobulin kappa variable 3-20, and immunoglobulin lambda variable 1-51 were up-regulated, while ATP synthase F1 subunit alpha, 10 kDa heat shock protein, apolipoprotein C-III, and arylsulfatase F were down-regulated. Six of these seven proteins support previous findings that ASD is accompanied by altered immune response and lipid metabolism, as well as mitochondrial dysfunction. This study lays the groundwork for additional research using biomarkers to clinically diagnose ASD. The proteomics and PRM raw data of this study have been deposited under the accession number IPX0002592000 at iProX. SIGNIFICANCE: This study identified 34 proteins in urine of ASD patients that were significantly changed from the urinary proteins of healthy subjects using LC-MS/MS-based proteomics in a discovery set. Seven of these proteins were validated by PRM analysis in an independent validation set. This report represents the first description of combined label-free quantitative proteomics and PRM analysis of targeted proteins for discovery of ASD urinary biomarkers. The results will be helpful for early diagnosis and can provide additional insight into the molecular mechanisms of ASD.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social communication and social interaction and restricted, repetitive patterns of behavior, interests, or activities. Given the lack of specific pharmacological therapy for ASD and the clinical heterogeneity of the disorder, current biomarker research efforts are geared mainly toward identifying markers for determining ASD risk or for assisting with a diagnosis. A wide range of putative biological markers for ASD is currently being investigated. Proteomic analyses indicate that the levels of many proteins in plasma/serum are altered in ASD, suggesting that a panel of proteins may provide a blood biomarker for ASD. Serum samples from 76 boys with ASD and 78 typically developing (TD) boys, 18 months-8 years of age, were analyzed to identify possible early biological markers for ASD. Proteomic analysis of serum was performed using SomaLogic's SOMAScanTM assay 1.3K platform. A total of 1,125 proteins were analyzed. There were 86 downregulated proteins and 52 upregulated proteins in ASD (FDR < 0.05). Combining three different algorithms, we found a panel of 9 proteins that identified ASD with an area under the curve (AUC) = 0.8599±0.0640, with specificity and sensitivity of 0.8217±0.1178 and 0.835±0.1176, respectively. All 9 proteins were significantly different in ASD compared with TD boys, and were significantly correlated with ASD severity as measured by ADOS total scores. Using machine learning methods, a panel of serum proteins was identified that may be useful as a blood biomarker for ASD in boys. Further verification of the protein biomarker panel with independent test sets is warranted.

Visual perception in individuals with autism spectrum disorder (ASD) is often debated in terms of enhanced local and impaired global perception. Deficits in global motion perception seem to support this characterization, although the evidence is inconsistent. We conducted a large meta-analysis on global motion, combining 48 articles on biological and coherent motion. Results provide evidence for a small global motion processing deficit in individuals with ASD compared to controls in both biological and coherent motion. This deficit appears to be present independent of the paradigm, task, dependent variable, age or IQ of the groups. Results indicate that individuals with ASD are less sensitive to these types of global motion, although the difference in neural mechanisms underlying this behavioral difference remains unclear.

One of the most conspicuous features of neurodegenerative diseases (NDs) is the occurrence of dramatic conformation change of individual proteins. We performed a mutational spectrum analysis of disease-causing missense mutations in seven types of NDs at nucleotide and amino acid levels, and compared the results with those of non-NDs. The main findings included: (i) The higher mutation ratio of G:C→T:A transversion to G:C→A:T transition was observed in NDs than in non-NDs, interpreting the excessive guanine-specific oxidative DNA damage in NDs; (ii) glycine and proline had highest mutability in NDs than in non-NDs, which favor the protein conformation change in NDs; (iii) surprisingly low mutation frequency of arginine was observed in NDs. These findings help to understand how mutations may cause NDs.

Epithelial-mesenchymal plasticity plays a critical role in many solid tumor types as a mediator of metastatic dissemination and treatment resistance. In addition, there is also a growing appreciation that the epithelial/mesenchymal status of a tumor plays a role in immune evasion and immune suppression. A deeper understanding of the immunological features of different tumor types has been facilitated by the availability of large gene expression datasets and the development of methods to deconvolute bulk RNA-Seq data. These resources have generated powerful new ways of characterizing tumors, including classification of immune subtypes based on differential expression of immunological genes. In the present work, we combine scoring algorithms to quantify epithelial-mesenchymal plasticity with immune subtype analysis to understand the relationship between epithelial plasticity and immune subtype across cancers. We find heterogeneity of epithelial-mesenchymal transition (EMT) status both within and between cancer types, with greater heterogeneity in the expression of EMT-related factors than of MET-related factors. We also find that specific immune subtypes have associated EMT scores and differential expression of immune checkpoint markers.