The impact of seasonally on caloric requirements of human populations

Human Ecology ◽  
1988 ◽  
Vol 16 (3) ◽  
pp. 343-346 ◽  
Author(s):  
William R. Leonard
Keyword(s):  
Human Populations ◽  
The Impact ◽  
Caloric Requirements

Systematic benchmark of ancient DNA read mapping

2021 ◽  
Author(s):  
Adrien Oliva ◽  
Raymond Tobler ◽  
Alan Cooper ◽  
Bastien Llamas ◽  
Yassine Souilmi
Keyword(s):  
Ancient Dna ◽  
Dna Sequences ◽  
Population Genetic ◽  
Reference Genome ◽  
Population Data ◽  
Human Populations ◽  
Current Standard ◽  
Read Mapping ◽  
Reference Bias ◽  
The Impact

Abstract The current standard practice for assembling individual genomes involves mapping millions of short DNA sequences (also known as DNA ‘reads’) against a pre-constructed reference genome. Mapping vast amounts of short reads in a timely manner is a computationally challenging task that inevitably produces artefacts, including biases against alleles not found in the reference genome. This reference bias and other mapping artefacts are expected to be exacerbated in ancient DNA (aDNA) studies, which rely on the analysis of low quantities of damaged and very short DNA fragments (~30–80 bp). Nevertheless, the current gold-standard mapping strategies for aDNA studies have effectively remained unchanged for nearly a decade, during which time new software has emerged. In this study, we used simulated aDNA reads from three different human populations to benchmark the performance of 30 distinct mapping strategies implemented across four different read mapping software—BWA-aln, BWA-mem, NovoAlign and Bowtie2—and quantified the impact of reference bias in downstream population genetic analyses. We show that specific NovoAlign, BWA-aln and BWA-mem parameterizations achieve high mapping precision with low levels of reference bias, particularly after filtering out reads with low mapping qualities. However, unbiased NovoAlign results required the use of an IUPAC reference genome. While relevant only to aDNA projects where reference population data are available, the benefit of using an IUPAC reference demonstrates the value of incorporating population genetic information into the aDNA mapping process, echoing recent results based on graph genome representations.

scholarly journals Impact of Influenza A Virus Shutoff Proteins on Host Immune Responses

Vaccines ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 629
Author(s):  
Megan M. Dunagan ◽  
Kala Hardy ◽  
Toru Takimoto
Keyword(s):  
Immune Response ◽  
Immune Responses ◽  
Influenza A Virus ◽  
Influenza A ◽  
Human Populations ◽  
Lymphocyte Migration ◽  
Host Immune Responses ◽  
Mhc Molecules ◽  
The Impact

Influenza A virus (IAV) is a significant human pathogen that causes seasonal epidemics. Although various types of vaccines are available, IAVs still circulate among human populations, possibly due to their ability to circumvent host immune responses. IAV expresses two host shutoff proteins, PA-X and NS1, which antagonize the host innate immune response. By transcriptomic analysis, we previously showed that PA-X is a major contributor for general shutoff, while shutoff active NS1 specifically inhibits the expression of host cytokines, MHC molecules, and genes involved in innate immunity in cultured human cells. So far, the impact of these shutoff proteins in the acquired immune response in vivo has not been determined in detail. In this study, we analyzed the effects of PA-X and NS1 shutoff activities on immune response using recombinant influenza A/California/04/2009 viruses containing mutations affecting the expression of shutoff active PA-X and NS1 in a mouse model. Our data indicate that the virus without shutoff activities induced the strongest T and B cell responses. Both PA-X and NS1 reduced host immune responses, but shutoff active NS1 most effectively suppressed lymphocyte migration to the lungs, antibody production, and the generation of IAV specific CD4+ and CD8+ T cells. NS1 also prevented the generation of protective immunity against a heterologous virus challenge. These data indicate that shutoff active NS1 plays a major role in suppressing host immune responses against IAV infection.

scholarly journals Characteristics of marine shipping emissions at berth: profiles for particulate matter and volatile organic compounds

2018 ◽  
Vol 18 (13) ◽  
pp. 9527-9545 ◽  
Author(s):  
Qian Xiao ◽  
Mei Li ◽  
Huan Liu ◽  
Mingliang Fu ◽  
Fanyuan Deng ◽  
...  
Keyword(s):  
Volatile Organic Compounds ◽  
Organic Compounds ◽  
Mass Spectrometer ◽  
Elemental Carbon ◽  
Atmospheric Stability ◽  
Diesel Oil ◽  
Human Populations ◽  
Volatile Organic ◽  
Before And After ◽  
The Impact

Abstract. Emissions from ships at berth play an important role regarding the exposure of high density human populations to atmospheric pollutants in port areas; however, these emissions are not well understood. In this study, volatile organic compounds (VOCs) and particle emissions from 20 container ships at berth were sampled and analyzed during the “fuel switch” period at Jingtang Port in Hebei Province, China. VOCs and particles were analyzed using a gas chromatography-mass spectrometer (GC-MS) and a single particle aerosol mass spectrometer (SPAMS), respectively. VOC analysis showed that alkanes and aromatics, especially benzene, toluene and heavier compounds e.g., n-heptane, n-octane and n-nonane, dominated the total identified species. Secondary organic aerosol (SOA) yields and ozone (O3) forming potential were 0.017 ± 0.007 g SOA g−1 VOCs and 2.63 ± 0.37 g O3 g−1 VOCs, respectively. Both positive and negative ion mass spectra from individual ships were derived and the intensity of specific ions were quantified. Results showed that elemental carbon (35.74 %), elemental carbon–organic carbon mixtures (33.95 %) and Na-rich particles (21.12 %) were major classes, comprising 90.7 % of the particles observed. Particles from ship auxiliary engines were in the 0.2 to 2.5 µm size range, with a peak occurring at around 0.4 µm. The issue of using vanadium (V) as tracer element was examined, and it was found that V was not a proper tracer of ship emissions when using low sulfur content diesel oil. The average percentage of sulfate particles observed in shipping emissions before and after switching to marine diesel oil remained unchanged at 24 %. Under certain wind conditions, when berths were upwind of emission sources, the ratios before and after 1 January were 35 and 27 % respectively. The impact of atmospheric stability was discussed based on PM2.5 and primary pollutant (carbon monoxide) concentration. With a background of frequent haze episodes and complex mechanisms of particulate accumulation and secondary formation, the impact of atmospheric stability is believed to have been weak on the sulfate contribution from shipping emissions. The results from this study provide robust support for port area air quality assessment and source apportionment.

scholarly journals Interconnections Accelerate Collapse in a Socio-Ecological Metapopulation

2019 ◽  
Vol 11 (7) ◽  
pp. 1852 ◽  
Author(s):  
Zachary Dockstader ◽  
Chris Bauch ◽  
Madhur Anand
Keyword(s):  
Theoretical Models ◽  
Ecological Sustainability ◽  
Human Populations ◽  
Metapopulation Model ◽  
Single Population ◽  
Metapopulation Structure ◽  
Model Dynamics ◽  
Simplifying Assumptions ◽  
Over Exploitation ◽  
The Impact

Over-exploitation of natural resources can have profound effects on both ecosystems and their resident human populations. Simple theoretical models of the dynamics of a population of human harvesters and the abundance of a natural resource being harvested have been studied previously, but relatively few models consider the effect of metapopulation structure (i.e., a population distributed across discrete patches). Here we analyze a socio-ecological metapopulation model based on an existing single-population model used to study persistence and collapse in human populations. Resources grow logistically on each patch. Each population harvests resources on its own patch to support population growth, but can also harvest resources from other patches when their own patch resources become scarce. We show that when populations are allowed to harvest resources from other patches, the peak population size is higher, but subsequent population collapse is significantly accelerated and across a broader parameter regime. As the number of patches in the metapopulation increases, collapse is more sudden, more severe, and occurs sooner. These effects persist under scenarios of asymmetry and inequality between patches. Our model makes simplifying assumptions in order to facilitate insight and understanding of model dynamics. However, the robustness of the model prediction suggests that more sophisticated models should be developed to ascertain the impact of metapopulation structure on socio-ecological sustainability.

scholarly journals The impact of mass drug administration expansion to low onchocerciasis prevalence settings in case of connected villages

2021 ◽  
Vol 15 (5) ◽  
pp. e0009011
Author(s):  
Anneke S. de Vos ◽  
Wilma A. Stolk ◽  
Luc E. Coffeng ◽  
Sake J. de Vlas
Keyword(s):  
Intermediate Host ◽  
Drug Administration ◽  
Mass Drug Administration ◽  
Human Populations ◽  
Individual Based Model ◽  
Low Prevalence ◽  
The Impact ◽  
Local Transmission

Background The existence of locations with low but stable onchocerciasis prevalence is not well understood. An often suggested yet poorly investigated explanation is that the infection spills over from neighbouring locations with higher infection densities. Methodology We adapted the stochastic individual based model ONCHOSIM to enable the simulation of multiple villages, with separate blackfly (intermediate host) and human populations, which are connected through the regular movement of the villagers and/or the flies. With this model we explore the impact of the type, direction and degree of connectedness, and of the impact of localized or full-area mass drug administration (MDA) over a range of connected village settings. Principal findings In settings with annual fly biting rates (ABR) below the threshold needed for stable local transmission, persistence of onchocerciasis prevalence can well be explained by regular human traffic and/or fly movement from locations with higher ABR. Elimination of onchocerciasis will then theoretically be reached by only implementing MDA in the higher prevalence area, although lingering infection in the low prevalence location can trigger resurgence of transmission in the total region when MDA is stopped too soon. Expanding MDA implementation to the lower ABR location can therefore shorten the duration of MDA needed. For example, when prevalence spill-over is due to human traffic, and both locations have about equal populations, then the MDA duration can be shortened by up to three years. If the lower ABR location has twice as many inhabitants, the reduction can even be up to six years, but if spill-over is due to fly movement, the expected reduction is less than a year. Conclusions/Significance Although MDA implementation might not always be necessary in locations with stable low onchocerciasis prevalence, in many circumstances it is recommended to accelerate achieving elimination in the wider area.

scholarly journals Efficient phasing and imputation of low-coverage sequencing data using large reference panels

2020 ◽  
Author(s):  
S. Rubinacci ◽  
D.M. Ribeiro ◽  
R. Hofmeister ◽  
O. Delaneau
Keyword(s):  
Paradigm Shift ◽  
Rare Variants ◽  
Association Studies ◽  
Cost Effective ◽  
Human Populations ◽  
Sequencing Data ◽  
Snp Arrays ◽  
Genomic Studies ◽  
Low Coverage ◽  
The Impact

AbstractLow-coverage whole genome sequencing followed by imputation has been proposed as a cost-effective genotyping approach for disease and population genetics studies. However, its competitiveness against SNP arrays is undermined as current imputation methods are computationally expensive and unable to leverage large reference panels.Here, we describe a method, GLIMPSE, for phasing and imputation of low-coverage sequencing datasets from modern reference panels. We demonstrate its remarkable performance across different coverages and human populations. It achieves imputation of a full genome for less than $1, outperforming existing methods by orders of magnitude, with an increased accuracy of more than 20% at rare variants. We also show that 1x coverage enables effective association studies and is better suited than dense SNP arrays to access the impact of rare variations. Overall, this study demonstrates the promising potential of low-coverage imputation and suggests a paradigm shift in the design of future genomic studies.

Gene variants of the renin–angiotensin system and hypertension: from a trough of disillusionment to a welcome phase of enlightenment?

2010 ◽  
Vol 118 (8) ◽  
pp. 487-506 ◽  
Author(s):  
Gavin R. Norton ◽  
Richard Brooksbank ◽  
Angela J. Woodiwiss
Keyword(s):  
Association Studies ◽  
Large Population ◽  
Renin Angiotensin System ◽  
Human Populations ◽  
Incomplete Penetrance ◽  
Gene Variants ◽  
Angiotensin System ◽  
Renin Angiotensin ◽  
Ras Genes ◽  
The Impact

There is substantial evidence to suggest that BP (blood pressure) is an inherited trait. The introduction of gene technologies in the late 1980s generated a sharp phase of over-inflated prospects for polygenic traits such as hypertension. Not unexpectedly, the identification of the responsible loci in human populations has nevertheless proved to be a considerable challenge. Common variants of the RAS (renin–angiotensin system) genes, including of ACE (angiotensin-converting enzyme) and AGT (angiotensinogen) were some of the first shown to be associated with BP. Presently, ACE and AGT are the only gene variants with functional relevance, where linkage studies showing relationships with hypertension have been reproduced in some studies and where large population-based and prospective studies have demonstrated these genes to be predictors of hypertension or BP. Nevertheless, a lack of reproducibility in other linkage and association studies has generated scepticism that only a concerted effort to attempt to explain will rectify. Without these explanations, it is unlikely that this knowledge will translate into the clinical arena. In the present review, we show that many of the previous concerns in the field have been addressed, but we also argue that a considerable amount of careful thought is still required to achieve enlightenment with respect to the role of RAS genes in hypertension. We discuss whether the previously identified problems of poor study design have been completely addressed with regards to the impact of ACE and AGT genes on BP. In the context of RAS genes, we also question whether the significance of ‘incomplete penetrance’ through associated environmental, phenotypic or physiological effects has been duly accounted for; whether appropriate consideration has been given to epistatic interactions between genes; and whether future RAS gene studies should consider variation across the gene by evaluating ‘haplotypes’.

Survival analyses

2021 ◽  
pp. 229-244
Author(s):  
Sarah Cubaynes ◽  
Simon Galas ◽  
Myriam Richaud ◽  
Ana Sanz Aguilar ◽  
Roger Pradel ◽  
...  
Keyword(s):  
Survival Data ◽  
Complex Life Cycle ◽  
Mortality Data ◽  
Human Populations ◽  
Imperfect Detection ◽  
Survival Analyses ◽  
Kaplan Meier ◽  
Animal Populations ◽  
Free Ranging ◽  
The Impact

Survival analyses are a key tool for demographers, ecologists, and evolutionary biologists. This chapter presents the most common methods and illustrates their use for species across the Tree of Life. It discusses the challenges associated with various types of survival data, how to model species with a complex life cycle, and includes the impact of environmental factors and individual heterogeneity. It covers the analysis of ‘known-fate’ data collected in lab conditions, using the Kaplan–Meier estimator and Cox’s proportional hazard regression analysis. Alternatively, survival data collected on free-ranging populations usually involve individuals missing at certain monitoring occasions and unknown time at death. The chapter provides an overview of capture–mark–recapture (CMR) models, from single-state to multi-state and multi-event models, and their use in animal and plant demography to estimate demographic parameters while correcting for imperfect detection of individuals. It discusses various inference frameworks available to implement CMR models using a frequentist or Bayesian approach. Only humans are an exception among free-ranging populations, with the existence of several consequent databases with perfect knowledge of age and cause of death for all individuals. The chapter presents an overview of the most common models used to describe mortality patterns over age and time using human mortality data. Throughout, focus is placed on eight case studies, which involve lab organisms, free-ranging animal populations, plant populations, and human populations. Each example includes data and codes, together with step-by-step guidance to run the survival analysis.

scholarly journals Long-lasting consequences of war on disability

2019 ◽  
Vol 56 (6) ◽  
pp. 860-875 ◽  
Author(s):  
Michael Palmer ◽  
Cuong Viet Nguyen ◽  
Sophie Mitra ◽  
Daniel Mont ◽  
Nora Ellen Groce
Keyword(s):  
United States Air Force ◽  
Relative Increase ◽  
Human Populations ◽  
Us Military ◽  
Disability Rate ◽  
Disability Status ◽  
Vietnamese Population ◽  
Nutritional Environment ◽  
The Impact

This article investigates the impact of exposure to United States air force bombing during 1965–75 on the disability status of individuals in Vietnam in 2009. Using a combination of national census and US military data and an instrumental variable strategy which exploits the distance to the former North–South border as a quasi-experiment, the article finds a positive and significant impact of bombing exposure on district level disability rates 40 years after the war. The overall effect of bombing on the long-term disability rate among the Vietnamese population is highest among heavily bombed districts. Districts in the top bombing quintile experience a 25% relative increase in the rate of disability attributable to bombing compared with districts in the lowest bombing quintile. Effects are highest on the prevalence of severe disability and among cohorts before the war’s end. A smaller, yet significant, effect is found among cohorts born after the war. The article finds further evidence of indirect channels through which bombing may have impacted on long-term disability including adverse effects on nutritional environment and human capital attainment. These findings add to the evidence from Vietnam and indicate that wars inflict costs on the health of human populations that last longer than those relating to economic growth and welfare.

Integration of Multiple Regression Model in an Epidemiological Decision Support System

2019 ◽  
Vol 18 (06) ◽  
pp. 1755-1783
Author(s):  
Fatima-Zohra Younsi ◽  
Ahmed Bounnekar ◽  
Djamila Hamdadou ◽  
Omar Boussaid
Keyword(s):  
Regression Analysis ◽  
Multiple Regression ◽  
Health Care Services ◽  
Network Effects ◽  
Social Contact ◽  
Public Health Care ◽  
Human Populations ◽  
Influenza Epidemic ◽  
Mortality And Morbidity ◽  
The Impact

Prevention and control of influenza epidemics are major challenges for public health care services. Early identification of flu outbreak is an important step towards implementing effective disease interventions for reducing mortality and morbidity in human populations. Indeed, health officials need a real geo-making tool for monitoring and prediction. The aim of the current study is to discuss a novel spatiotemporal tool for monitoring and predicting the phenomenon of the seasonal influenza epidemic spread in the human population using multiple regression analysis. The suggested tool is mainly based on three sub-systems. It allows generating simulation data by the use of a simulation system, integrating data sources in a data warehouse (DW) system and performing a specific online analysis Spatial On-Line Analytical Processing (SOLAP). Our proposal enables also to illustrate evolution of disease through visualizations in time and space. It can examine social network effects to better understand the topological structure of social contact and the impact of its properties. A regression analysis is performed on the influenza epidemic to examine the main factors influencing flu incidence number and therefore to predict and track influenza epidemic.

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