美国区域卫生信息化及有效使用电子健康档案的启示

通过介绍美国区域卫生信息化发展、有效使用EHR计划、区域卫生信息化组织等，探讨推进区域卫生信息化和电子健康档案应用过程中的问题和挑战，包括公共医学术语和技术标准、电子健康档案及区域卫生信息化潜在经济效益、电子健康档案应用保障机制、区域卫生信息化水平评价及区域卫生信息化组织可持续运营等，以提供借鉴。     

The Future of Medical Diagnostics: Large Digitized Databases

The electronic health record mandate within the American Recovery and Reinvestment Act of 2009 will have a far-reaching affect on medicine. In this article, we provide an in-depth analysis of how this mandate is expected to stimulate the production of large-scale, digitized databases of patient information. There is evidence to suggest that millions of patients and the National Institutes of Health will fully support the mining of such databases to better understand the process of diagnosing patients. This data mining likely will reaffirm and quantify known risk factors for many diagnoses. This quantification may be leveraged to further develop computer-aided diagnostic tools that weigh risk factors and provide decision support for health care providers. We expect that creation of these databases will stimulate the development of computer-aided diagnostic support tools that will become an integral part of modern medicine.     

Plant Derived Antiviral Products for Potential Treatment of COVID-19: A Review

COVID-19 caused by SARS-CoV-2 is declared global pandemic. The virus owing high resemblance with SARS-CoV and MERS-CoV has been placed in family of beta-coronavirus. However, transmission and infectivity rate of COVID-19 is quite higher as compared to other members of family. Effective management strategy with potential drug availability will break the virus transmission chain subsequently reduce the pressure on the healthcare system. Extensive research trials are underway to develop novel efficient therapeutics against SARS-CoV-2. In this review, we have discussed the origin and family of coronavirus, structure, genome and pathogenesis of virus SARS-CoV-2 inside human host cell; comparison among SARS, MERS, SARS-CoV-2 and common flu; effective management practices; treatment with immunity boosters; available medication with ongoing clinical trials. We suggest medicinal plants could serve as potential candidates for drug development against COVID-19 infection.     

Long-term effects of birth weight and breastfeeding duration on inflammation in early adulthood

Chronic inflammation is a potentially important physiological mechanism linking early life environments and health in adulthood. Elevated concentrations of C-reactive protein (CRP)—a key biomarker of inflammation—predict increased cardiovascular and metabolic disease risk in adulthood, but the developmental factors that shape the regulation of inflammation are not known. We investigated birth weight and breastfeeding duration in infancy as predictors of CRP in young adulthood in a large representative cohort study (n = 6951). Birth weight was significantly associated with CRP in young adulthood, with a negative association for birth weights 2.8 kg and higher. Compared with individuals not breastfed, CRP concentrations were 20.1%, 26.7%, 29.6% and 29.8% lower among individuals breastfed for less than three months, three to six months, 6–12 months and greater than 12 months, respectively. In sibling comparison models, higher birth weight was associated with lower CRP for birth weights above 2.5 kg, and breastfeeding greater than or equal to three months was significantly associated with lower CRP. Efforts to promote breastfeeding and improve birth outcomes may have clinically relevant effects on reducing chronic inflammation and lowering risk for cardiovascular and metabolic diseases in adulthood.     

Estimating divergence times from DNA sequences

The patterns of genetic variation within and among individuals and populations can be used to make inferences about the evolutionary forces that generated those patterns. Numerous population genetic approaches have been developed in order to infer evolutionary history. Here, we present the “Two-Two (TT)” and the “Two-Two-outgroup (TTo)” methods; two closely related approaches for estimating divergence time based in coalescent theory. They rely on sequence data from two haploid genomes (or a single diploid individual) from each of two populations. Under a simple population-divergence model, we derive the probabilities of the possible sample configurations. These probabilities form a set of equations that can be solved to obtain estimates of the model parameters, including population split times, directly from the sequence data. This transparent and computationally efficient approach to infer population divergence time makes it possible to estimate time scaled in generations (assuming a mutation rate), and not as a compound parameter of genetic drift. Using simulations under a range of demographic scenarios, we show that the method is relatively robust to migration and that the TTo method can alleviate biases that can appear from drastic ancestral population size changes. We illustrate the utility of the approaches with some examples, including estimating split times for pairs of human populations as well as providing further evidence for the complex relationship among Neandertals and Denisovans and their ancestors.     

Pulling the covers in electronic health records for an association study with self-reported sleep behaviors

ABSTRACT

The electronic health record (EHR) contains rich histories of clinical care, but has not traditionally been mined for information related to sleep habits. Here, we performed a retrospective EHR study based on a cohort of 3,652 individuals with self-reported sleep behaviors documented from visits to the sleep clinic. These individuals were obese (mean body mass index 33.6 kg/m²) and had a high prevalence of sleep apnea (60.5%), however we found sleep behaviors largely concordant with prior prospective cohort studies. In our cohort, average wake time was 1 hour later and average sleep duration was 40 minutes longer on weekends than on weekdays (p < 10^?12). Sleep duration varied considerably as a function of age and tended to be longer in females and in whites. Additionally, through phenome-wide association analyses, we found an association of long weekend sleep with depression, and an unexpectedly large number of associations of long weekday sleep with mental health and neurological disorders (q < 0.05). We then sought to replicate previously published genetic associations with morning/evening preference on a subset of our cohort with extant genotyping data (n = 555). While those findings did not replicate in our cohort, a polymorphism (rs3754214) in high linkage disequilibrium with a previously published polymorphism near TARS2 was associated with long sleep duration (p < 0.01). Collectively, our results highlight the potential of the EHR for uncovering the correlates of human sleep in real-world populations.     

长江流域棉花综合群体品系的遗传多样性分析

以15个长江流域棉花杂交种为基础材料,花粉混合互交构建了综合群体,从中选育出29个棉花株系。通过田间试验对12个主要性状进行考察,衍生株系间霜前花率的变异最大,子棉产量及构成因素次之,纤维品质性状的变异最小。主成分分析表明,纤维品质、产量及构成因素、霜前花率、衣分和株高等前5个主成分,对变异方差的贡献率分别为24.312%、19.662%、13.287%、10.812%、9.085%。基于SSR的分子标记差异,绝大多数衍生株系聚在一类,遗传差异较小,明显区别于黄河流域棉花品种。     

A Graphical Chain Model Derived from a Model Selection Strategy for the Sociologists Graduates Study

This paper objects to the arising problems when fitting graphical chain models to multidimensional data sets like the one at our disposal: the so-called graduates study. These models seem adequate, because the analysis of dependencies and associations among the variables of interest requires a multivariate statistical device that is rich enough to capture not only direct, but also indirect associations. Since even for a moderate number of variables the graphical chain model space is vast appropriate strategies for fitting graphical chain models are needed. Here, a data-driven selection strategy is discussed in detail.     

The State of Research on Human–Animal Relations: Implications for Human Health

ABSTRACT

Since the late 1970s, scientific evidence has accumulated showing that pet ownership can have positive effects on people’s physical and mental wellbeing. This paper reviews the current state of affairs regarding the relationship between companion animals and human health, focusing on both the physical and psychological health outcomes related to human–animal interactions. Although designed to set the general scene on the link between animals and human wellbeing, research specific to older adults is highlighted where relevant. A particular emphasis is placed on disorders prevalent in modern-day society, notably cardiovascular disease and depression. The possible mechanisms by which companion animals might be able to enhance human wellbeing and quality of life are discussed, focusing on routes including, amongst others, the provision of companionship, social lubrication, and improvements to physical fitness. The role of the social bonding hormone, oxytocin, in facilitating attachment to our pets and the implications for human health is also discussed. Inconsistencies in the literature and methodological limitations are highlighted throughout. It is concluded that future human–animal interaction experiments should aim to account for the confounding variables that are inherent in studies of this nature.     

The modeling and health risk assessment of PM2.5 from Tema Oil Refinery

Fine particulate matters (PM_2.5) are known to pose serious health problems compared to other air pollutants. The current study employed air dispersion modeling system (AERMOD) to simulate the concentration of PM_2.5 from Tema Oil Refinery (TOR) and to assess the non-cancer risk and mortalities of the exposed population. In addition, the effects of local climatic factors on the distribution and concentration of PM_2.5 within the three main seasons (Major Raining Season (MRS), Low Raining Season (LRS) and Dry Season (DS)) were investigated. The AERMOD results showed that both 24-h (38.8 µg m^?3) and annual (12.6 µg m^?3) PM_2.5 concentration levels were in exceedance of the international limits. However, a decreasing trend in seasonal PM_2.5 concentrations was observed. Health risk assessment (HRA), indicated by hazard index (HI), revealed that the amount of Al₂O₃ present in the PM_2.5 caused a significant non-carcinogenic health risk to the exposed population (both adults and children) within the Metropolis (HI = 2.4 for adults and HI = 1.5 for children). Additionally, cardiopulmonary disease related mortalities due to PM_2.5 exposure (181 deaths for adults and 24 deaths for children) were found high compared to deaths caused by lung cancer (137 deaths for adults and 16 deaths for children).     

A robust approach for electronic health record–based case-control studies with contaminated case pools

We consider analyses of case-control studies assembled from electronic health records (EHRs) where the pool of cases is contaminated by patients who are ineligible for the study. These ineligible patients, referred to as “false cases,” should be excluded from the analyses if known. However, the true outcome status of a patient in the case pool is unknown except in a subset whose size may be arbitrarily small compared to the entire pool. To effectively remove the influence of the false cases on estimating odds ratio parameters defined by a working association model of the logistic form, we propose a general strategy to adaptively impute the unknown case status without requiring a correct phenotyping model to help discern the true and false case statuses. Our method estimates the target parameters as the solution to a set of unbiased estimating equations constructed using all available data. It outperforms existing methods by achieving robustness to mismodeling the relationship between the outcome status and covariates of interest, as well as improved estimation efficiency. We further show that our estimator is root-n-consistent and asymptotically normal. Through extensive simulation studies and analysis of real EHR data, we demonstrate that our method has desirable robustness to possible misspecification of both the association and phenotyping models, along with statistical efficiency superior to the competitors.     

Molecular Dynamics Simulations to Investigate the Structural Stability and Aggregation Behavior of the GGVVIA Oligomers Derived from Amyloid β Peptide

Abstract

Several neurodegenerative diseases, such as Alzheimer's, Parkinson's, and Huntington's dis-eases, are associated with amyloid fibrils formed by different polypeptides. Recently, the atomic structure of the amyloid-forming peptide GGVVIA from the C-terminal hydrophobic segment of amyloid-β (Aβ) peptide has been determined and revealed a dry, tightly self-com-plementing structure between two β-sheets, termed as “steric zipper”. In this study, several all-atom molecular dynamics simulations with explicit water were conducted to investigate the structural stability and aggregation behavior of the GGVVIA oligomers with various sizes. The results of our single-layer models suggested that the structural stability of the GGVVIA oligomers increases remarkably with increasing the numbers of β-strands. We fur-ther identified that SH2-ST2 may act as a stable seed in prompting amyloid fibril formations. Our results also demonstrated that hydrophobic interaction is the principle driving force to stabilize and associate the GGVVIA oligomers between β-strands; while the hydrophobic steric zipper formed via the side chains of V3, V4, and I5 plays a critical role in holding the two neighboring β-sheets together. Single glycine substitution at V3, V4, and I5 directly disrupted the hydrophobic steric zipper between these two β-sheets, resulting in the destabili-zation of the oligomers. Our simulation results provided detailed insights into understanding the aggregation behavior of the GGVVIA oligomers in the atomic level. It may also be help-ful for designing new inhibitors able to prevent the fibril formation of Aβ peptide.     

Toxic Effects of Iron for Cultured Mesencephalic Dopaminergic Neurons Derived from Rat Embryonic Brains

Iron, a transition metal possibly involved in the pathogenesis of Parkinson's disease, was tested for its toxic effects toward cultures of dissociated rat mesencephalic cells. When cultures were switched for 24 h to serum-free conditions, the effective concentrations of ferrous iron (Fe2+) producing a loss of 50% of dopaminergic neurons, as quantified by tyrosine hydroxylase (TH) immunocytochemistry, TH mRNA in situ hybridization, and measurement of TH activity, were on the order of 200 microM. High-affinity dopamine (DA) uptake, which reflects integrity and function of dopaminergic nerve terminals, was impaired at significantly lower concentrations (EC50 = 67 microM). Toxic effects were not restricted to dopaminergic neurons inasmuch as trypan blue dye exclusion index and gamma-aminobutyric acid uptake, two parameters used to assess survival of other types of cells present in these cultures, were also affected. Protection against iron cytotoxicity was afforded by desferrioxamine and apotransferrin, two ferric iron-chelating agents. Normal supplementation of the culture medium by serum proteins during treatment was also effective, presumably via nonspecific sequestration. Potential interactions with DA were also investigated. Fe2+ at subtoxic concentrations and desferrioxamine in the absence of exogenous iron added to the cultures failed to potentiate or reduce DA cytotoxicity for mesencephalic cells, respectively. Transferrin, the glycoprotein responsible for intracellular delivery of iron, was ineffective in initiating selective cytotoxic effects toward dopaminergic neurons preloaded with DA. Altogether, these results suggest (a) that ferrous iron is a potent neurotoxin for dopaminergic neurons as well as for other cell types in dissociated mesencephalic cultures, acting likely via autoxidation into its ferric form, and (b) that the presence of intra- and extracellular DA is not required for the observed toxic effects.     

Reconstructing the dynamics of ancient human populations from radiocarbon dates: 10 000 years of population growth in Australia

Measuring trends in the size of prehistoric populations is fundamental to our understanding of the demography of ancient people and their responses to environmental change. Archaeologists commonly use the temporal distribution of radiocarbon dates to reconstruct population trends, but this can give a false picture of population growth because of the loss of evidence from older sites. We demonstrate a method for quantifying this bias, and we use it to test for population growth through the Holocene of Australia. We used model simulations to show how turnover of site occupation across an archaeological landscape, interacting with erasure of evidence at abandoned sites, can create an increase in apparent site occupation towards the present when occupation density is actually constant. By estimating the probabilities of abandonment and erasure from archaeological data, we then used the model to show that this effect does not account for the observed increase in occupation through the Holocene in Australia. This is best explained by population growth, which was low for the first part of the Holocene but accelerated about 5000 years ago. Our results provide new evidence for the dynamism of non-agricultural populations through the Holocene.     

肠道菌群与代谢性综合征的关系及其运动干预效果的研究进展

人体肠道是一个复杂的微生态系统,栖息着数量、种类繁多的微生物,其中数目最庞大的微生物为肠道菌群,肠道微生物群落被认为是人体中的第二个基因组.诸多研究表明它们影响着机体许多功能,与代谢性疾病的发生有重要联系.运动干预能极大地改善肠道菌群和促进宿主的健康.通过查阅最近几年肠道菌群与代谢性综合征的资料,探索肠道菌群与代谢性综...