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1.
Nat Commun ; 11(1): 5071, 2020 10 08.
Artigo em Inglês | MEDLINE | ID: mdl-33033235

RESUMO

Identifying species that are both geographically restricted and functionally distinct, i.e. supporting rare traits and functions, is of prime importance given their risk of extinction and their potential contribution to ecosystem functioning. We use global species distributions and functional traits for birds and mammals to identify the ecologically rare species, understand their characteristics, and identify hotspots. We find that ecologically rare species are disproportionately represented in IUCN threatened categories, insufficiently covered by protected areas, and for some of them sensitive to current and future threats. While they are more abundant overall in countries with a low human development index, some countries with high human development index are also hotspots of ecological rarity, suggesting transboundary responsibility for their conservation. Altogether, these results state that more conservation emphasis should be given to ecological rarity given future environmental conditions and the need to sustain multiple ecosystem processes in the long-term.


Assuntos
Aves/fisiologia , Conservação dos Recursos Naturais , Ecossistema , Internacionalidade , Mamíferos/fisiologia , Animais , Geografia , Humanos , Camada de Gelo , Filogenia , Análise de Componente Principal , Especificidade da Espécie
2.
Nat Commun ; 11(1): 5085, 2020 10 08.
Artigo em Inglês | MEDLINE | ID: mdl-33033250

RESUMO

Tibetan wheat is grown under environmental constraints at high-altitude conditions, but its underlying adaptation mechanism remains unknown. Here, we present a draft genome sequence of a Tibetan semi-wild wheat (Triticum aestivum ssp. tibetanum Shao) accession Zang1817 and re-sequence 245 wheat accessions, including world-wide wheat landraces, cultivars as well as Tibetan landraces. We demonstrate that high-altitude environments can trigger extensive reshaping of wheat genomes, and also uncover that Tibetan wheat accessions accumulate high-altitude adapted haplotypes of related genes in response to harsh environmental constraints. Moreover, we find that Tibetan semi-wild wheat is a feral form of Tibetan landrace, and identify two associated loci, including a 0.8-Mb deletion region containing Brt1/2 homologs and a genomic region with TaQ-5A gene, responsible for rachis brittleness during the de-domestication episode. Our study provides confident evidence to support the hypothesis that Tibetan semi-wild wheat is de-domesticated from local landraces, in response to high-altitude extremes.


Assuntos
Adaptação Fisiológica , Altitude , Triticum/fisiologia , Adaptação Fisiológica/genética , Domesticação , Ecótipo , Genoma de Planta , Geografia , Metagenômica , Fenótipo , Análise de Componente Principal , Tibet , Triticum/genética
3.
Nat Commun ; 11(1): 4943, 2020 10 02.
Artigo em Inglês | MEDLINE | ID: mdl-33009384

RESUMO

Despite their high vulnerability, insular ecosystems have been largely ignored in climate change assessments, and when they are investigated, studies tend to focus on exposure to threats instead of vulnerability. The present study examines climate change vulnerability of islands, focusing on endemic mammals and by 2050 (RCPs 6.0 and 8.5), using trait-based and quantitative-vulnerability frameworks that take into account exposure, sensitivity, and adaptive capacity. Our results suggest that all islands and archipelagos show a certain level of vulnerability to future climate change, that is typically more important in Pacific Ocean ones. Among the drivers of vulnerability to climate change, exposure was rarely the main one and did not explain the pattern of vulnerability. In addition, endemic mammals with long generation lengths and high dietary specializations are predicted to be the most vulnerable to climate change. Our findings highlight the importance of exploring islands vulnerability to identify the highest climate change impacts and to avoid the extinction of unique biodiversity.


Assuntos
Mudança Climática , Ilhas , Mamíferos/fisiologia , Animais , Dieta , Análise de Componente Principal , Especificidade da Espécie
4.
Nat Commun ; 11(1): 4954, 2020 10 02.
Artigo em Inglês | MEDLINE | ID: mdl-33009396

RESUMO

Genetic variation is of crucial importance for crop improvement. Landraces are valuable sources of diversity, but for quantitative traits efficient strategies for their targeted utilization are lacking. Here, we map haplotype-trait associations at high resolution in ~1000 doubled-haploid lines derived from three maize landraces to make their native diversity for early development traits accessible for elite germplasm improvement. A comparative genomic analysis of the discovered haplotypes in the landrace-derived lines and a panel of 65 breeding lines, both genotyped with 600k SNPs, points to untapped beneficial variation for target traits in the landraces. The superior phenotypic performance of lines carrying favorable landrace haplotypes as compared to breeding lines with alternative haplotypes confirms these findings. Stability of haplotype effects across populations and environments as well as their limited effects on undesired traits indicate that our strategy has high potential for harnessing beneficial haplotype variation for quantitative traits from genetic resources.


Assuntos
Haplótipos/genética , Característica Quantitativa Herdável , Zea mays/genética , Biblioteca Gênica , Variação Genética , Genoma de Planta , Estudo de Associação Genômica Ampla , Haploidia , Melhoramento Vegetal , Análise de Componente Principal , Zea mays/crescimento & desenvolvimento
5.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 213-216, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33017967

RESUMO

For the extraction of underlying sources of brain activity, time structure-based techniques for applying Independent Component Analysis (ICA) have been demonstrably more robust than state-of-the-art statistical-based methods, such as FastICA. Since the early application of conventional ICA on electroencephalogram (EEG) recordings, Space-Time ICA (ST-ICA) has emerged as more capable approach for extracting complex underlying activity, but not without the 'curse of dimensionality'. The challenges in the future development of ST-ICA will require a focus on the optimisation of the mixing matrix, and on component clustering techniques. This paper proposes a new optimisation approach for the mixing matrix, which makes ST-ICA more tractable, when using a time structure-based ICA technique, LSDIAG. Such techniques rely on constructing a multi-layer covariance matrix, Cxk of the original dataset to generate the inverse of the mixing matrix; Csk = WCxkWT. This means a simple truncation of the mixing matrix is not appropriate. To overcome this, we propose a deflationary approach to optimise a much smaller mixing matrix - based on the absolute values of the diagonals of the co-variance matrix, Csk, to represent the underlying sources. The preliminary results of the new technique applied to different channels of EEG recorded using the standard 10-20 system - including the full selection of all channels - are very promising.Clinical Relevance-The potential of this deflationary approach for Space-Time ICA, seeks to allow clinicians to identify underlying sources in the brain - that both spatially and spectrally overlap - to be identified, whilst making the 'dimensionality' challenges more tractable. In the long run, applications of this technique could enhance certain brain-computer interface paradigms.


Assuntos
Algoritmos , Eletroencefalografia , Encéfalo , Análise de Componente Principal , Análise Espaço-Temporal
6.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 236-239, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33017972

RESUMO

Researchers have been using signal processing based methods to assess speech from Parkinson's disease (PD) patients and identify the contrasting features in comparison to speech from healthy controls (HC). The methodologies follow conventional approach of segmenting speech over a fixed window (≈25ms to 30ms) followed by feature extraction and classification. The proposed methodology uses MFCCs extracted from pitch synchronous and fixed window (25ms) based speech segments for classification using fine Gaussian support vector machines (SVM). Three word utterances with three different vowel sounds are used for this analysis. Clustering experiments are aimed at identifying two clusters and class labels (PD/HC) are assigned based on number of participants from the respective class in the cluster. The features are divided into 9 groups based on the vowel content to evaluate the effect of different vowel sounds. Principal component analysis (PCA) is used for dimensionality reduction along with a 10-fold cross-validation. From the results, we observed that pitch synchronous segmentation yields better classification performance compared to fixed window based segmentation. The results of this analysis support our hypothesis that pitch synchronous segmentation is better suited for PD classification using connected speech.Clinical Relevance- The automatic speech analysis framework used in this analysis establishes the greater efficiency of pitch synchronous segmentation over the traditional methods.


Assuntos
Doença de Parkinson , Máquina de Vetores de Suporte , Algoritmos , Humanos , Análise de Componente Principal , Fala
7.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 1108-1111, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018180

RESUMO

Reconstructing the perceived faces from brain signals has become a promising work recently. However, the reconstruction accuracies rely on a large number of brain signals collected for training a stable reconstruction model, which is really time consuming, and greatly limits its application. In our current study, we develop a new framework that can efficiently perform high-quality face reconstruction with only a small number of brain signals as training samples. The framework consists of three mathematical models: principle component analysis (PCA), linear regression (LR) and conditional generative adversarial network (cGAN). We conducted a functional Magnetic Resonance Imaging (fMRI) experiment in which two subjects' brain signals were collected to test the efficiency of our proposed method. Results show that we can achieve state-of-the-art reconstruction performance from brain signals with a very limited number of fMRI training samples.


Assuntos
Encéfalo , Imagem por Ressonância Magnética , Encéfalo/diagnóstico por imagem , Modelos Lineares , Análise de Componente Principal
8.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 1853-1858, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018361

RESUMO

The increasing prevalence and adaptability of 3D optical scan (3DO) technology has invoked many recent studies which use 3DO scanning as a convenient and inexpensive means for predicting body composition and health risks. The Shape Up studies seek a device-agnostic solution for body composition estimation based on principal component analysis (PCA). This paper reports a progress made on Shape Up's previous work which served as a criterion analysis for PCA-based body composition and health risk prediction. This study presents proof-of-concept for a novel automated landmark detection step that allows for a fully automated PCA-based approach to body composition estimation that facilitates a practical device-agnostic PCA-based solution to body composition estimation from 3DO scans. Our results show that replacing expensive and time-consuming manual point placement with the proposed automated landmarks will not diminish the quality of body composition estimates allowing for a more practical pipeline that can be used in real-world settings.


Assuntos
Composição Corporal , Análise de Componente Principal , Cintilografia
9.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 3497-3500, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018757

RESUMO

The unknown composition of residual muscles surrounding the stump of an amputee makes optimal electrode placement challenging. This often causes the experimental set-up and calibration of upper-limb prostheses to be time consuming. In this work, we propose the use of existing dimensionality reduction techniques, typically used for muscle synergy analysis, to provide meaningful real-time functional information of the residual muscles during the calibration period. Two variations of principal component analysis (PCA) were applied to electromyography (EMG) data collected during a myoelectric task. Candid covariance-free incremental PCA (CCIPCA) detected task-specific muscle synergies with high accuracy using minimal amounts of data. Our findings offer a real-time solution towards optimizing calibration periods.


Assuntos
Amputados , Membros Artificiais , Eletromiografia , Humanos , Músculo Esquelético , Análise de Componente Principal
10.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 3755-3758, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018818

RESUMO

Despite recent advancements in the field of pattern recognition-based myoelectric control, the collection of a high quality training set remains a challenge limiting its adoption. This paper proposes a framework for a possible solution by augmenting short training protocols with subject-specific synthetic electromyography (EMG) data generated using a deep generative network, known as SinGAN. The aim of this work is to produce high quality synthetic data that could improve classification accuracy when combined with a limited training protocol. SinGAN was used to generate 1000 synthetic windows of EMG data from a single window of six different motions, and results were evaluated qualitatively, quantitatively, and in a classification task. Qualitative assessment of synthetic data was conducted via visual inspection of principal component analysis projections of real and synthetic feature space. Quantitative assessment of synthetic data revealed 11 of 32 synthetic features had similar location and scale to real features (using univariate two-sample Lepage tests); whereas multivariate distributions were found to be statistically different (p <0.05). Finally, the addition of these synthetic data to a brief training set of real data significantly improved classification accuracy in a cross-validation testing scheme by 5.4% (p <0.001).


Assuntos
Eletromiografia , Detecção de Sinal Psicológico , Estudos de Viabilidade , Movimento (Física) , Análise de Componente Principal
11.
Medicine (Baltimore) ; 99(33): e21556, 2020 Aug 14.
Artigo em Inglês | MEDLINE | ID: mdl-32872004

RESUMO

Moxa floss is the primary material used in moxibustion, an important traditional Chinese medicine therapy that uses ignited moxa floss to apply heat to the body for disease treatment. Till date, there is no available data regarding quality control of different grades of moxa floss. The objectives of this study were to explore the probative value of the electronic nose (e-nose) in differentiating different quality grades of commercial moxa floss sold in China, and to investigate if data mining techniques could be used to optimize the sensor array while retaining classification accuracy of the samples. The e-nose with 12 metal oxide semiconductor type sensors was used to analyze the odor profiles of 15 commercial moxa floss samples of different quality grades. Feature selection algorithms using principal component analysis (PCA) and BestFirst (BC) coupled with correlation-based feature subset selection (CfsSubsetEval) method were used to obtain the most efficient feature subsets. Results for the BC feature selection method identified 3 optimized sensors (S2, S6, and S11), suggesting that aromatic compounds relate more to the identification of the samples. Radial basis function (RBF), multilayer perceptron (MLP), and random forests (RF) performed well in discriminating the samples, retaining prediction accuracies above 85%, which achieved cost-effectiveness and operational simplicity, while retaining prediction accuracy. The e-nose could be a rapid and nondestructive method for objective preliminary classification of quality grades of moxa floss and may be used for future studies related to moxa products safety and quality.


Assuntos
Medicamentos de Ervas Chinesas/classificação , Nariz Eletrônico , Moxibustão , Fumaça/análise , Algoritmos , China , Mineração de Dados , Humanos , Análise de Componente Principal
12.
PLoS One ; 15(9): e0237160, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32881879

RESUMO

Pareiorhaphis hystrix is a widely distributed species, occurring in the upper and middle Uruguay River and in the Taquari River basin, Patos Lagoon system, southern Brazil. Morphological variation has been detected throughout the distribution of P. hystrix, and this work seeks to test the conspecific nature of populations in several occurrence areas. Specimens from six areas in the Uruguay River basin and three in the Taquari River basin were compared. Variance analysis (ANOVA) was performed for the meristic data, and Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) were conducted for morphometric data. Molecular analyses used coI, cytb, 12S and 16S mitochondrial genes, examining nucleotide diversity, haplotype diversity, genetic distance, and delimitation of possible multiple species through the Generalized Mixed Yule Coalescent (GMYC) method. Phylogenetic relationships of studied populations were also investigated through Bayesian inference. While PCA indicated a tendency of overlap between areas, ANOVA and LDA detected a subtle differentiation between populations from the two hydrographic basins. Yet, both latter analyses recovered the population from Pelotas River, a tributary to Uruguay River, as more similar to populations from Taquari River, which is congruent to morphological observations of anterior abdominal plates. The molecular data indicated a nucleotide diversity lower than the haplotypic diversity, suggestive of recent expansion. The concatenated haplotype network points to slight differentiation between areas, with each locality presenting unique and non-shared haplotypes, although with few mutational steps in general. The species delimitation by coalescence analysis suggested the presence of a variable number of OTUs depending on the inclusion or exclusion of an outgroup. In general, the morphological data suggest a subtle variation by river basin, while the genetic data indicates a weak population structuration by hydrographic areas, especially the Chapecó and Passo Fundo rivers. However, there is still not enough differentiation between the specimens to suggest multiple species. The iterative analyses indicate that Pareiorhaphis hystrix is composed of a single, although variable, species.


Assuntos
Peixes-Gato/anatomia & histologia , Peixes-Gato/classificação , Animais , Teorema de Bayes , Brasil , Peixes-Gato/genética , Análise Discriminante , Feminino , Genes Mitocondriais , Geografia , Haplótipos/genética , Masculino , Fenótipo , Filogenia , Pigmentação , Análise de Componente Principal , Rios , Especificidade da Espécie
13.
Bull Environ Contam Toxicol ; 105(4): 613-619, 2020 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-32964273

RESUMO

The distribution, composition, sources, and potential ecological risks of polycyclic aromatic hydrocarbons (PAHs) in the sediments of the Lanzhou Reach of the Yellow River, China were investigated. The total concentration of the 18 individual PAHs (∑18PAHs) in the sediments ranged from 638 to 1620 ng/g, with a mean value of 901 ng/g. The pollution level of PAHs in the sediments was low to moderate. Spatially, the distribution of PAHs in the sediments showed an increasing trend along the direction of water flow. ∑18PAHs predominantly consisted of low molecular weight PAHs. The principal component analysis and isomer ratios of PAHs suggested the mixed sources of petroleum and those from the combustion of petroleum, coal, and biomass. The results showed that the PAHs in the sediments of the Lanzhou Reach of the Yellow River have a low ecological risk. However, the BaP equivalent exposure values suggested a potential cancer risk.


Assuntos
Monitoramento Ambiental , Hidrocarbonetos Policíclicos Aromáticos/análise , Poluentes Químicos da Água/análise , Biomassa , China , Carvão Mineral/análise , Sedimentos Geológicos/análise , Petróleo/análise , Análise de Componente Principal , Medição de Risco , Rios
14.
PLoS One ; 15(9): e0239961, 2020.
Artigo em Inglês | MEDLINE | ID: covidwho-810226

RESUMO

OBJECTIVE: COVID-19 pandemic led to major life changes. We assessed the psychological impact of COVID-19 on dental academics globally and on changes in their behaviors. METHODS: We invited dental academics to complete a cross-sectional, online survey from March to May 2020. The survey was based on the Theory of Planned Behavior (TPB). The survey collected data on participants' stress levels (using the Impact of Event Scale), attitude (fears, and worries because of COVID-19 extracted by Principal Component Analysis (PCA), perceived control (resulting from training on public health emergencies), norms (country-level COVID-19 fatality rate), and personal and professional backgrounds. We used multilevel regression models to assess the association between the study outcome variables (frequent handwashing and avoidance of crowded places) and explanatory variables (stress, attitude, perceived control and norms). RESULTS: 1862 academics from 28 countries participated in the survey (response rate = 11.3%). Of those, 53.4% were female, 32.9% were <46 years old and 9.9% had severe stress. PCA extracted three main factors: fear of infection, worries because of professional responsibilities, and worries because of restricted mobility. These factors had significant dose-dependent association with stress and were significantly associated with more frequent handwashing by dental academics (B = 0.56, 0.33, and 0.34) and avoiding crowded places (B = 0.55, 0.30, and 0.28). Low country fatality rates were significantly associated with more handwashing (B = -2.82) and avoiding crowded places (B = -6.61). Training on public health emergencies was not significantly associated with behavior change (B = -0.01 and -0.11). CONCLUSIONS: COVID-19 had a considerable psychological impact on dental academics. There was a direct, dose-dependent association between change in behaviors and worries but no association between these changes and training on public health emergencies. More change in behaviors was associated with lower country COVID-19 fatality rates. Fears and stresses were associated with greater adoption of preventive measures against the pandemic.


Assuntos
Infecções por Coronavirus/psicologia , Docentes de Odontologia/psicologia , Comportamentos Relacionados com a Saúde , Pneumonia Viral/psicologia , Teoria Psicológica , Adulto , Idoso , Betacoronavirus , Infecções por Coronavirus/prevenção & controle , Estudos Transversais , Feminino , Desinfecção das Mãos , Humanos , Masculino , Pessoa de Meia-Idade , Estresse Ocupacional/epidemiologia , Pandemias/prevenção & controle , Pneumonia Viral/prevenção & controle , Análise de Componente Principal , Inquéritos e Questionários
15.
Nat Commun ; 11(1): 4661, 2020 09 16.
Artigo em Inglês | MEDLINE | ID: mdl-32938925

RESUMO

The recent years have seen a growing number of studies investigating evolutionary questions using ancient DNA. To address these questions, one of the most frequently-used method is principal component analysis (PCA). When PCA is applied to temporal samples, the sample dates are, however, ignored during analysis, leading to imperfect representations of samples in PC plots. Here, we present a factor analysis (FA) method in which individual scores are corrected for the effect of allele frequency drift over time. We obtained exact solutions for the estimates of corrected factors, and we provided a fast algorithm for their computation. Using computer simulations and ancient European samples, we compared geometric representations obtained from FA with PCA and with ancestry estimation programs. In admixture analyses, FA estimates agreed with tree-based statistics, and they were more accurate than those obtained from PCA projections and from ancestry estimation programs. A great advantage of FA over existing approaches is to improve descriptive analyses of ancient DNA samples without requiring inclusion of outgroup or present-day samples.


Assuntos
DNA Antigo/análise , Análise Fatorial , Genoma Humano , Metagenômica/estatística & dados numéricos , Algoritmos , Inglaterra , Europa (Continente) , Frequência do Gene , Deriva Genética , Genética Populacional/estatística & dados numéricos , Humanos , Modelos Genéticos , Análise de Componente Principal
16.
PLoS One ; 15(9): e0239961, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32991611

RESUMO

OBJECTIVE: COVID-19 pandemic led to major life changes. We assessed the psychological impact of COVID-19 on dental academics globally and on changes in their behaviors. METHODS: We invited dental academics to complete a cross-sectional, online survey from March to May 2020. The survey was based on the Theory of Planned Behavior (TPB). The survey collected data on participants' stress levels (using the Impact of Event Scale), attitude (fears, and worries because of COVID-19 extracted by Principal Component Analysis (PCA), perceived control (resulting from training on public health emergencies), norms (country-level COVID-19 fatality rate), and personal and professional backgrounds. We used multilevel regression models to assess the association between the study outcome variables (frequent handwashing and avoidance of crowded places) and explanatory variables (stress, attitude, perceived control and norms). RESULTS: 1862 academics from 28 countries participated in the survey (response rate = 11.3%). Of those, 53.4% were female, 32.9% were <46 years old and 9.9% had severe stress. PCA extracted three main factors: fear of infection, worries because of professional responsibilities, and worries because of restricted mobility. These factors had significant dose-dependent association with stress and were significantly associated with more frequent handwashing by dental academics (B = 0.56, 0.33, and 0.34) and avoiding crowded places (B = 0.55, 0.30, and 0.28). Low country fatality rates were significantly associated with more handwashing (B = -2.82) and avoiding crowded places (B = -6.61). Training on public health emergencies was not significantly associated with behavior change (B = -0.01 and -0.11). CONCLUSIONS: COVID-19 had a considerable psychological impact on dental academics. There was a direct, dose-dependent association between change in behaviors and worries but no association between these changes and training on public health emergencies. More change in behaviors was associated with lower country COVID-19 fatality rates. Fears and stresses were associated with greater adoption of preventive measures against the pandemic.


Assuntos
Infecções por Coronavirus/psicologia , Docentes de Odontologia/psicologia , Comportamentos Relacionados com a Saúde , Pneumonia Viral/psicologia , Teoria Psicológica , Adulto , Idoso , Betacoronavirus , Infecções por Coronavirus/prevenção & controle , Estudos Transversais , Feminino , Desinfecção das Mãos , Humanos , Masculino , Pessoa de Meia-Idade , Estresse Ocupacional/epidemiologia , Pandemias/prevenção & controle , Pneumonia Viral/prevenção & controle , Análise de Componente Principal , Inquéritos e Questionários
17.
Environ Monit Assess ; 192(9): 573, 2020 Aug 09.
Artigo em Inglês | MEDLINE | ID: mdl-32772266

RESUMO

Among statistical tools for the study of atmospheric pollutants, trajectory regression analysis (TRA), cluster analysis (CA), and principal component analysis (PCA) can be highlighted. Therefore, this article presents a systematic review of such techniques based on (i) air mass influences on particulate matter (PM) and (ii) the study of the relationship between PM and meteorological variables. This article aims to review studies that use TRA and to review studies that adopt CA and/or PCA to identify the associations and relationship between meteorological variables and atmospheric pollutants. Papers published between 2006 and 2018 and indexed by five of the main scientific databases were considered (ScienceDirect, Web of Science, PubMed, SciELO, and Scopus databases). PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) recommendations supported this systematic review. From the resulting most relevant papers, eight studies analyzed the influence of air mass trajectories on PM using TRA and twenty-one studies searched for the relationship between meteorological variables and PM using CA and/or PCA. A combination of TRA and time series models was identified as the possibility of future works. Besides, studies that simultaneously combine the three techniques to identify both the influence of air masses on PM and its relationship with meteorological variables are a possibility of future papers, because it can lead to a better comprehension of such a phenomenon.


Assuntos
Poluentes Atmosféricos/análise , Meteorologia , Monitoramento Ambiental , Material Particulado/análise , Análise de Componente Principal
18.
Artigo em Inglês | MEDLINE | ID: mdl-32785046

RESUMO

The Health Opportunity Index (HOI) is a multivariate tool that can be more efficiently used to identify and understand the interplay of complex social determinants of health (SDH) at the census tract level that influences the ability to achieve optimal health. The derivation of the HOI utilizes the data-reduction technique of principal component analysis to determine the impact of SDH on optimal health at lower census geographies. In the midst of persistent health disparities and the present COVID-19 pandemic, we demonstrate the potential utility of using 13-input variables to derive a composite metric of health (HOI) score as a means to assist in the identification of the most vulnerable communities during the current pandemic. Using GIS mapping technology, health opportunity indices were layered by counties in Ohio to highlight differences by census tract. Collectively we demonstrate that our HOI framework, principal component analysis and convergence analysis methodology coalesce to provide results supporting the utility of this framework in the three largest counties in Ohio: Franklin (Columbus), Cuyahoga (Cleveland), and Hamilton (Cincinnati). The results in this study identified census tracts that were also synonymous with communities that were at risk for disparate COVID-19 related health outcomes. In this regard, convergence analyses facilitated identification of census tracts where different disparate health outcomes co-exist at the worst levels. Our results suggest that effective use of the HOI composite score and subcomponent scores to identify specific SDH can guide mitigation/intervention practices, thus creating the potential for better targeting of mitigation and intervention strategies for vulnerable communities, such as during the current pandemic.


Assuntos
Infecções por Coronavirus/epidemiologia , Pneumonia Viral/epidemiologia , Determinantes Sociais da Saúde/estatística & dados numéricos , Betacoronavirus , Censos , Mapeamento Geográfico , Humanos , Ohio/epidemiologia , Pandemias , Análise de Componente Principal , Fatores Socioeconômicos
19.
Ecotoxicol Environ Saf ; 202: 110953, 2020 Oct 01.
Artigo em Inglês | MEDLINE | ID: mdl-32800227

RESUMO

Heavy metal acclimated bacteria are profoundly the preferred choice for bioremediation studies. Bacteria get acclimated to toxic concentrations of heavy metals by induction of specific enzymes and genetic selection favoring new metabolic abilities leading to activation of one or several of resistance mechanisms creating bacterial populations with differences in resistance profile and/or level. Therefore, to use in bioremediation processes, it is important to discriminate acclimated bacterial populations and choose a more resistant strain. In this study, we discriminated heavy metal acclimated bacteria by using Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) spectroscopy and multivariate analysis methods namely Hierarchical Cluster Analysis (HCA), Principal Component Analysis (PCA) and Soft Independent Modeling of Class Analogy (SIMCA). Two acclimation methods, acute and gradual, were used which cause differences in molecular changes resulting in bacterial populations with different molecular and resistance profiles. Brevundimonas sp., Gordonia sp., and Microbacterium oxydans were exposed to the toxic concentrations of Cd (30 µg/ml) or Pb (90 µg/ml) by using broth medium as a growth media. Our results revealed that PCA and HCA clearly discriminated the acute-acclimated, gradual-acclimated, and control bacteria from each other in protein, carbohydrate, and whole spectral regions. Furthermore, we classified acclimated (acute and gradual) and control bacteria more accurately by using SIMCA with 99.9% confidence. This study demonstrated that heavy metal acclimated and control group bacteria can be discriminated by using chemometric analysis of FTIR spectra in a powerful, cost-effective, and handy way. In addition to the determination of the most appropriate acclimation procedure, this approach can be used in the detection of the most resistant bacterial strains to be used in bioremediation studies.


Assuntos
Aclimatação/efeitos dos fármacos , Actinobacteria/efeitos dos fármacos , Caulobacteraceae/efeitos dos fármacos , Farmacorresistência Bacteriana/efeitos dos fármacos , Metais Pesados/toxicidade , Actinobacteria/crescimento & desenvolvimento , Biodegradação Ambiental , Caulobacteraceae/crescimento & desenvolvimento , Análise por Conglomerados , Meios de Cultura , Análise Multivariada , Análise de Componente Principal , Espectroscopia de Infravermelho com Transformada de Fourier
20.
BMC Bioinformatics ; 21(1): 360, 2020 Aug 17.
Artigo em Inglês | MEDLINE | ID: mdl-32807073

RESUMO

BACKGROUND: Discovering single nucleotide polymorphisms (SNPs) from agriculture crop genome sequences has been a widely used strategy for developing genetic markers for several applications including marker-assisted breeding, population diversity studies for eco-geographical adaption, genotyping crop germplasm collections, and others. Accurately detecting SNPs from large polyploid crop genomes such as wheat is crucial and challenging. A few variant calling methods have been previously developed but they show a low concordance between their variant calls. A gold standard of variant sets generated from one human individual sample was established for variant calling tool evaluations, however hitherto no gold standard of crop variant set is available for wheat use. The intent of this study was to evaluate seven SNP variant calling tools (FreeBayes, GATK, Platypus, Samtools/mpileup, SNVer, VarScan, VarDict) with the two most popular mapping tools (BWA-mem and Bowtie2) on wheat whole exome capture (WEC) re-sequencing data from allohexaploid wheat. RESULTS: We found the BWA-mem mapping tool had both a higher mapping rate and a higher accuracy rate than Bowtie2. With the same mapping quality (MQ) cutoff, BWA-mem detected more variant bases in mapping reads than Bowtie2. The reads preprocessed with quality trimming or duplicate removal did not significantly affect the final mapping performance in terms of mapped reads. Based on the concordance and receiver operating characteristic (ROC), the Samtools/mpileup variant calling tool with BWA-mem mapping of raw sequence reads outperformed other tests followed by FreeBayes and GATK in terms of specificity and sensitivity. VarDict and VarScan were the poorest performing variant calling tools with the wheat WEC sequence data. CONCLUSION: The BWA-mem and Samtools/mpileup pipeline, with no need to preprocess the raw read data before mapping onto the reference genome, was ascertained the optimum for SNP calling for the complex wheat genome re-sequencing. These results also provide useful guidelines for reliable variant identification from deep sequencing of other large polyploid crop genomes.


Assuntos
Genoma de Planta , Triticum/genética , Sequenciamento Completo do Genoma/métodos , Área Sob a Curva , Humanos , Polimorfismo de Nucleotídeo Único , Poliploidia , Análise de Componente Principal , Curva ROC , Software
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