115 research outputs found

    Integrating External Controls by Regression Calibration for Genome-Wide Association Study

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    Genome-wide association studies (GWAS) have successfully revealed many disease-associated genetic variants. For a case-control study, the adequate power of an association test can be achieved with a large sample size, although genotyping large samples is expensive. A cost-effective strategy to boost power is to integrate external control samples with publicly available genotyped data. However, the naive integration of external controls may inflate the type I error rates if ignoring the systematic differences (batch effect) between studies, such as the differences in sequencing platforms, genotype-calling procedures, population stratification, and so forth. To account for the batch effect, we propose an approach by integrating External Controls into the Association Test by Regression Calibration (iECAT-RC) in case-control association studies. Extensive simulation studies show that iECAT-RC not only can control type I error rates but also can boost statistical power in all models. We also apply iECAT-RC to the UK Biobank data for M72 Fibroblastic disorders by considering genotype calling as the batch effect. Four SNPs associated with fibroblastic disorders have been detected by iECAT-RC and the other two comparison methods, iECAT-Score and Internal. However, our method has a higher probability of identifying these significant SNPs in the scenario of an unbalanced case-control association study

    A Review of Deep Learning Methods for Photoplethysmography Data

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    Photoplethysmography (PPG) is a highly promising device due to its advantages in portability, user-friendly operation, and non-invasive capabilities to measure a wide range of physiological information. Recent advancements in deep learning have demonstrated remarkable outcomes by leveraging PPG signals for tasks related to personal health management and other multifaceted applications. In this review, we systematically reviewed papers that applied deep learning models to process PPG data between January 1st of 2017 and July 31st of 2023 from Google Scholar, PubMed and Dimensions. Each paper is analyzed from three key perspectives: tasks, models, and data. We finally extracted 193 papers where different deep learning frameworks were used to process PPG signals. Based on the tasks addressed in these papers, we categorized them into two major groups: medical-related, and non-medical-related. The medical-related tasks were further divided into seven subgroups, including blood pressure analysis, cardiovascular monitoring and diagnosis, sleep health, mental health, respiratory monitoring and analysis, blood glucose analysis, as well as others. The non-medical-related tasks were divided into four subgroups, which encompass signal processing, biometric identification, electrocardiogram reconstruction, and human activity recognition. In conclusion, significant progress has been made in the field of using deep learning methods to process PPG data recently. This allows for a more thorough exploration and utilization of the information contained in PPG signals. However, challenges remain, such as limited quantity and quality of publicly available databases, a lack of effective validation in real-world scenarios, and concerns about the interpretability, scalability, and complexity of deep learning models. Moreover, there are still emerging research areas that require further investigation

    Children’s Non-symbolic and Symbolic Numerical Representations and Their Associations With Mathematical Ability

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    Most empirical evidence supports the view that non-symbolic and symbolic representations are foundations for advanced mathematical ability. However, the detailed development trajectories of these two types of representations in childhood are not very clear, nor are the different effects of non-symbolic and symbolic representations on the development of mathematical ability. We assessed 253 4- to 8-year-old children’s non-symbolic and symbolic numerical representations, mapping skills, and mathematical ability, aiming to investigate the developmental trajectories and associations between these skills. Our results showed non-symbolic numerical representation emerged earlier than the symbolic one. Four-year-olds were capable of non-symbolic comparisons but not symbolic comparisons; five-year-olds performed better at non-symbolic comparisons than symbolic comparisons. This performance difference disappeared at age 6. Children at age 6 or older were able to map between symbolic and non-symbolic quantities. However, as children learn more about the symbolic representation system, their advantage in non-symbolic representation disappeared. Path analyses revealed that a direct effect of children’s symbolic numerical skills on their math performance, and an indirect effect of non-symbolic numerical skills on math performance via symbolic skills. These results suggest that symbolic numerical skills are a predominant factor affecting math performance in early childhood. However, the influences of symbolic and non-symbolic numerical skills on mathematical performance both declines with age

    Palaeosedimentary Environment and Formation Mechanism of High-Quality Xujiahe Source Rocks, Sichuan Basin, South China

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    AbstractTriassic Xujiahe source rocks, the main gas source of shallow tight gas, are the most typical continental coal-bearing source rocks in the Sichuan Basin, South China. However, the organic matter enrichment section cannot be identified easily, leading to limited progress in the exploration of coal-bearing tight gas. This paper reveals the main controlling factors of the organic matter enrichment, reconstructs the evolution process of the Xujiahe palaeosedimentary environment, proposes a dynamic enrichment mechanism of the organic matter, and determines the organic matter enrichment section of the high-quality coal-bearing source rocks by geochemical characteristics of the source rocks, major elements, and trace elements. The results show that the Xujiahe sedimentary environment can be divided into a fluctuating stage of transitional sedimentation, stable stage of transitional sedimentation, fluctuating stage of continental sedimentation, and stable stage of continental sedimentation. The Xujiahe source rocks were featured with high-quality coal-bearing source rocks with high total organic carbon and maturity and good parent material in the stable stage of transitional sedimentation and fluctuating stage of continental sedimentation, in which the water was connected with the Palaeo-Tethys Ocean with abundant terrestrial organisms. The water was shallow in the fluctuating stage of transitional sedimentation with a low sedimentation rate, leading to poor organic matter enrichment. The Palaeo-Tethys Ocean withdrew westward from the Yangtze plate in the late period of the fluctuating stage of continental sedimentation, leading to the absence of algae and dinosteranes and a decrease in biological productivity in the stable stage of continental sedimentation. Therefore, high terrestrial inputs and biological productivity and high sedimentation rate were conducive to the organic matter preservation in the coal-bearing source rocks

    Metagenomic surveillance and comparative genomic analysis of Chlamydia psittaci in patients with pneumonia

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    Chlamydia psittaci, a strictly intracellular bacterium, is an underestimated etiologic agent leading to infections in a broad range of animals and mild illness or pneumonia in humans. In this study, the metagenomes of bronchoalveolar lavage fluids from the patients with pneumonia were sequenced and highly abundant C. psittaci was found. The target-enriched metagenomic reads were recruited to reconstruct draft genomes with more than 99% completeness. Two C. psittaci strains from novel sequence types were detected and these were closely related to the animal-borne isolates derived from the lineages of ST43 and ST28, indicating the zoonotic transmissions of C. psittaci would benefit its prevalence worldwide. Comparative genomic analysis combined with public isolate genomes revealed that the pan-genome of C. psittaci possessed a more stable gene repertoire than those of other extracellular bacteria, with ~90% of the genes per genome being conserved core genes. Furthermore, the evidence for significantly positive selection was identified in 20 virulence-associated gene products, particularly bacterial membrane-embedded proteins and type three secretion machines, which may play important roles in the pathogen-host interactions. This survey uncovered novel strains of C. psittaci causing pneumonia and the evolutionary analysis characterized prominent gene candidates involved in bacterial adaptation to immune pressures. The metagenomic approach is of significance to the surveillance of difficult-to-culture intracellular pathogens and the research into molecular epidemiology and evolutionary biology of C. psittaci

    Diversities of disability caused by lung cancer in the 66 Belt and Road initiative countries: a secondary analysis from the Global Burden of Disease Study 2019

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    ObjectivesDue to the increase in life expectancy and the aging of the global population, the “Belt and Road” (“B&R”) countries are faced with varying degrees of lung cancer threat. The purpose of this study is to analyze the differences in the burden and trend of lung cancer disability in the “B&R” countries from 1990 to 2019 so as to provide an analytical strategic basis to build a healthy “B&R”.MethodsData were derived from the Global Burden of Disease 2019 (GBD 2019). Incidence, mortality, prevalence, the years lived with disability (YLDs), and disability-adjusted life years (DALYs) of lung cancer and those attributable to different risk factors were measured from 1990 to 2019. Trends of disease burden were estimated by using the average annual percent change (AAPC), and the 95% uncertainty interval (UI) was reported.ResultsChina, India, and the Russian Federation were the three countries with the highest burden of lung cancer in 2019. From 1990 to 2019, the AAPC of incidence, prevalence, mortality, and DALYs generally showed a downward trend in Central Asia (except Georgia) and Eastern Europe, while in China, South Asia (except Bangladesh), most countries in North Africa, and the Middle East, the trend was mainly upward. The AAPC of age-standardized incidence was 1.33% (1.15%–1.50%); the AAPC of prevalence, mortality, and DALYs from lung cancer in China increased by 24% (2.10%–2.38%), 0.94% (0.74%–1.14%), and 0.42% (0.25%–0.59%), respectively. A downward trend of the AAPC values of age-standardized YLD rate in men was shown in the vast majority of “B&R” countries, but for women, most countries had an upward trend. For adults aged 75 years or older, the age-standardized YLD rate showed an increasing trend in most of the “B&R” countries. Except for the DALY rate of lung cancer attributable to metabolic risks, a downward trend of the DALY rate attributable to all risk factors, behavioral risks, and environmental/occupational risks was shown in the vast majority of “B&R” countries.ConclusionThe burden of lung cancer in “B&R” countries varied significantly between regions, genders, and risk factors. Strengthening health cooperation among the “B&R” countries will help to jointly build a community with a shared future for mankind

    Environment-driven variability in absolute band edge positions and work functions of reduced ceria

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    The absolute band edge positions and work function (Φ) are the key electronic properties of metal oxides that determine their performance in electronic devices and photocatalysis. However, experimental measurements of these properties often show notable variations, and the mechanisms underlying these discrepancies remain inadequately understood. In this work, we focus on ceria (CeO2), a material renowned for its outstanding oxygen storage capacity, and combine theoretical and experimental techniques to demonstrate environmental modifications of its ionization potential (IP) and Φ. Under O-deficient conditions, reduced ceria exhibits a decreased IP and Φ with significant sensitivity to defect distributions. In contrast, the IP and Φ are elevated in O-rich conditions due to the formation of surface peroxide species. Surface adsorbates and impurities can further augment these variabilities under realistic conditions. We rationalize the shifts in energy levels by separating the individual contributions from bulk and surface factors, using hybrid quantum mechanical/molecular mechanical (QM/MM) embedded-cluster and periodic density functional theory (DFT) calculations supported by interatomic-potential-based electrostatic analyses. Our results highlight the critical role of on-site electrostatic potentials in determining the absolute energy levels in metal oxides, implying a dynamic evolution of band edges under catalytic conditions

    DNA methylation on N6-adenine in mammalian embryonic stem cells

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    It has been widely accepted that 5-methylcytosine is the only form of DNA methylation in mammalian genomes. Here we identify N6-methyladenine as another form of DNA modification in mouse embryonic stem cells. Alkbh1 encodes a demethylase for N6-methyladenine. An increase of N6-methyladenine levels in Alkbh1-deficient cells leads to transcriptional silencing. N6-methyladenine deposition is inversely correlated with the evolutionary age of LINE-1 transposons; its deposition is strongly enriched at young (6 million years old) L1 elements. The deposition of N6-methyladenine correlates with epigenetic silencing of such LINE-1 transposons, together with their neighbouring enhancers and genes, thereby resisting the gene activation signals during embryonic stem cell differentiation. As young full-length LINE-1 transposons are strongly enriched on the X chromosome, genes located on the X chromosome are also silenced. Thus, N6-methyladenine developed a new role in epigenetic silencing in mammalian evolution distinct from its role in gene activation in other organisms. Our results demonstrate that N6-methyladenine constitutes a crucial component of the epigenetic regulation repertoire in mammalian genomes
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