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1.
BMC Bioinformatics ; 23(1): 36, 2022 Jan 12.
Artigo em Inglês | MEDLINE | ID: mdl-35021985

RESUMO

BACKGROUND: The number of studies using single-cell RNA sequencing (scRNA-seq) is constantly growing. This powerful technique provides a sampling of the whole transcriptome of a cell. However, sparsity of the data can be a major hurdle when studying the distribution of the expression of a specific gene or the correlation between the expressions of two genes. RESULTS: We show that the main technical noise associated with these scRNA-seq experiments is due to the sampling, i.e., Poisson noise. We present a new tool named baredSC, for Bayesian Approach to Retrieve Expression Distribution of Single-Cell data, which infers the intrinsic expression distribution in scRNA-seq data using a Gaussian mixture model. baredSC can be used to obtain the distribution in one dimension for individual genes and in two dimensions for pairs of genes, in particular to estimate the correlation in the two genes' expressions. We apply baredSC to simulated scRNA-seq data and show that the algorithm is able to uncover the expression distribution used to simulate the data, even in multi-modal cases with very sparse data. We also apply baredSC to two real biological data sets. First, we use it to measure the anti-correlation between Hoxd13 and Hoxa11, two genes with known genetic interaction in embryonic limb. Then, we study the expression of Pitx1 in embryonic hindlimb, for which a trimodal distribution has been identified through flow cytometry. While other methods to analyze scRNA-seq are too sensitive to sampling noise, baredSC reveals this trimodal distribution. CONCLUSION: baredSC is a powerful tool which aims at retrieving the expression distribution of few genes of interest from scRNA-seq data.


Assuntos
Análise de Célula Única , Transcriptoma , Algoritmos , Animais , Teorema de Bayes , Perfilação da Expressão Gênica , Distribuição Normal , Análise de Sequência de RNA
2.
Environ Int ; 158: 106986, 2022 01.
Artigo em Inglês | MEDLINE | ID: mdl-34991248

RESUMO

BACKGROUND/AIMS: Early life exposures to marine contaminants can adversely impact child health but modes of action are unclear. Human milk contains extracellular vesicles (EVs) that can transport biologically relevant cargo from mother to infant, including microRNAs (miRNAs), and may partly mediate the effects of pollutants on child health. However, the role of marine pollutants on miRNA expression in milk EVs is unexplored. METHODS: We isolated EV RNA from 333 milk samples collected between 2 and 74 days postpartum from a Faroese birth cohort born 1997-2000 and sequenced 2083 miRNAs using a targeted library preparation method. We quantified five perfluoroalkyl substances (PFAS), pesticide metabolite p,p'-dichlorodiphenyldichloroethylene (DDE), and the sum of three major polychlorinated biphenyls (ΣPCBs) in maternal serum at 34 weeks of gestation and maternal hair total mercury (Hg) at birth. We used negative binomial regressions to estimate associations between individual pollutants and 418 reliably expressed EV-miRNAs adjusted for potential confounders. We performed sparse principal components (PCs) analysis to derive the first four components of the EV-miRNA data and examined associations between pollutants and PCs using Bayesian kernel machine regression (BKMR). RESULTS: We observed no associations between pollutants and individual EV-miRNA expression after controlling the false discovery rate at 0.1. However, BKMR suggested that Hg was positively associated with PC1 and negatively associated with PC3, while ΣPCBs was negatively associated with PC3, and two PFAS were associated with PC4. Exploration of PC loadings followed by pathway analyses suggested that miRNAs in PC1 (miR-200b-3p, miR-664a-3p, miR-6738-5p, miR-429, miR-1236-5p, miR-4464, and miR-30b-5p) may be related to Hg neurotoxicity, while remaining PCs require further research. CONCLUSIONS: Our findings suggest that groups of milk EV-miRNAs may better serve as environmental biomarkers than individual miRNAs. Future studies are needed to elucidate the role of milk EV-miRNAs in child health following prenatal exposures.


Assuntos
Poluentes Ambientais , Vesículas Extracelulares , MicroRNAs , Teorema de Bayes , Criança , Poluentes Ambientais/toxicidade , Feminino , Humanos , Recém-Nascido , MicroRNAs/genética , Leite Humano , Mães , Gravidez
3.
Environ Int ; 158: 107015, 2022 01.
Artigo em Inglês | MEDLINE | ID: mdl-34991269

RESUMO

BACKGROUND: Characteristics of the urban environment may contain upstream drivers of obesity. However, research is lacking that considers the combination of environmental factors simultaneously. OBJECTIVES: We aimed to explore what environmental factors of the urban exposome are related to body mass index (BMI), and evaluated the consistency of findings across multiple statistical approaches. METHODS: A cross-sectional analysis was conducted using baseline data from 14,829 participants of the Occupational and Environmental Health Cohort study. BMI was obtained from self-reported height and weight. Geocoded exposures linked to individual home addresses (using 6-digit postcode) of 86 environmental factors were estimated, including air pollution, traffic noise, green-space, built environmental and neighborhood socio-demographic characteristics. Exposure-obesity associations were identified using the following approaches: sparse group Partial Least Squares, Bayesian Model Averaging, penalized regression using the Minimax Concave Penalty, Generalized Additive Model-based boosting Random Forest, Extreme Gradient Boosting, and Multiple Linear Regression, as the most conventional approach. The models were adjusted for individual socio-demographic variables. Environmental factors were ranked according to variable importance scores attributed by each approach and median ranks were calculated across these scores to identify the most consistent associations. RESULTS: The most consistent environmental factors associated with BMI were the average neighborhood value of the homes, oxidative potential of particulate matter air pollution (OP), healthy food outlets in the neighborhood (5 km buffer), low-income neighborhoods, and one-person households in the neighborhood. Higher BMI levels were observed in low-income neighborhoods, with lower average house values, lower share of one-person households and smaller amount of healthy food retailers. Higher BMI levels were observed in low-income neighborhoods, with lower average house values, lower share of one-person households, smaller amounts of healthy food retailers and higher OP levels. Across the approaches, we observed consistent patterns of results based on model's capacity to incorporate linear or nonlinear associations. DISCUSSION: The pluralistic analysis on environmental obesogens strengthens the existing evidence on the role of neighborhood socioeconomic position, urbanicity and air pollution.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Expossoma , Poluentes Atmosféricos/análise , Poluição do Ar/análise , Teorema de Bayes , Estudos de Coortes , Estudos Transversais , Exposição Ambiental/análise , Humanos , Aprendizado de Máquina , Características de Residência
4.
Sensors (Basel) ; 22(1)2022 Jan 02.
Artigo em Inglês | MEDLINE | ID: mdl-35009870

RESUMO

Oxyhemoglobin saturation by pulse oximetry (SpO2) has always played an important role in the diagnosis of symptoms. Considering that the traditional SpO2 measurement has a certain error due to the number of wavelengths and the algorithm and the wider application of machine learning and spectrum combination, we propose to use 12-wavelength spectral absorption measurement to improve the accuracy of SpO2 measurement. To investigate the multiple spectral regions for deep learning for SpO2 measurement, three datasets for training and verification were built, which were constructed over the spectra of first region, second region, and full region and their sub-regions, respectively. For each region under the procedures of optimization of our model, a thorough of investigation of hyperparameters is proceeded. Additionally, data augmentation is preformed to expand dataset with added noise randomly, increasing the diversity of data and improving the generalization of the neural network. After that, the established dataset is input to a one dimensional convolution neural network (1D-CNN) to obtain a measurement model of SpO2. In order to enhance the model accuracy, GridSearchCV and Bayesian optimization are applied to optimize the hyperparameters. The optimal accuracies of proposed model optimized by GridSearchCV and Bayesian Optimization is 89.3% and 99.4%, respectively, and trained with the dataset at the spectral region of six wavelengths including 650 nm, 680 nm, 730 nm, 760 nm, 810 nm, 860 nm. The total relative error of the best model is only 0.46%, optimized by Bayesian optimization. Although the spectral measurement with more features can improve the resolution ability of the neural network, the results reveal that the training with the dataset of the shorter six wavelength is redundant. This analysis shows that it is very important to construct an effective 1D-CNN model area for spectral measurement using the appropriate spectral ranges and number of wavelengths. It shows that our proposed 1D-CNN model gives a new and feasible approach to measure SpO2 based on multi-wavelength.


Assuntos
Aprendizado Profundo , Teorema de Bayes , Aprendizado de Máquina , Redes Neurais de Computação , Oximetria
5.
BMC Infect Dis ; 22(1): 14, 2022 Jan 04.
Artigo em Inglês | MEDLINE | ID: mdl-34983395

RESUMO

BACKGROUND: Salmonella is a major cause of zoonotic illness around the world, arising from direct or indirect contact with a range of animal reservoirs. In the Australian state of New South Wales (NSW), salmonellosis is believed to be primarily foodborne, but the relative contribution of animal reservoirs is unknown. METHODS: The analysis included 4543 serotyped isolates from animal reservoirs and 30,073 serotyped isolates from domestically acquired human cases in NSW between January 2008 and August 2019. We used a Bayesian source attribution methodology to estimate the proportion of foodborne Salmonella infections attributable to broiler chickens, layer chickens, ruminants, pigs, and an unknown or unsampled source. Additional analyses included covariates for four time periods and five levels of rurality. RESULTS: A single serotype, S. Typhimurium, accounted for 65-75% of included cases during 2008-2014 but < 50% during 2017-2019. Attribution to layer chickens was highest during 2008-2010 (48.7%, 95% CrI 24.2-70.3%) but halved by 2017-2019 (23.1%, 95% CrI 5.7-38.9%) and was lower in the rural and remote populations than in the majority urban population. The proportion of cases attributed to the unsampled source was 11.3% (95% CrI 1.2%-22.1%) overall, but higher in rural and remote populations. The proportion of cases attributed to pork increased from approximately 20% in 2009-2016 to approximately 40% in 2017-2019, coinciding with a rise in cases due to Salmonella ser. 4,5,12:i:-. CONCLUSION: Layer chickens were likely the primary reservoir of domestically acquired Salmonella infections in NSW circa 2010, but attribution to the source declined contemporaneously with increased vaccination of layer flocks and tighter food safety regulations for the handling of eggs.


Assuntos
Galinhas , Infecções por Salmonella , Animais , Austrália , Teorema de Bayes , Microbiologia de Alimentos , Geografia , New South Wales/epidemiologia , Infecções por Salmonella/epidemiologia , Suínos
6.
Anal Chim Acta ; 1189: 339223, 2022 Jan 02.
Artigo em Inglês | MEDLINE | ID: mdl-34815054

RESUMO

The rapid detection of the pathogenic bacteria in patient samples is crucial to expedient patient care. The proposed approach reports the development of a novel lab-on-a-chip device for the rapid detection of P. aeruginosa based on immunomagnetic separation, optical scattering, and machine learning. The immunomagnetic particles with a diameter of 5 µm were synthesized for isolating P. aeruginosa from the test sample. A microfluidic chip was fabricated, and three optical fibers were embedded for connecting a laser light and two photodetectors. The laser light was pointed towards the channel to pass light through the sample. A pair of photodetectors via optical fibers were arranged symmetrically at 45° to the channel. The photodetectors acquired scattered light from the flowing sample and converted the light to an electrical signal. The sample containing immunomagnetic beads linked with bacteria was injected into the microfluidic chip. The optimized conditions for performing the experiments were characterized for real-time detection of P. aeruginosa. The data acquisition system recorded the real-time light scattering from the test sample. After removing noise from the output waveform, five different time-domain statistical features were extracted from each waveform: standard mean, standard variance, skewness, kurtosis, and coefficient of variation. The pathogens classification was performed by training the discrimination model using extracted features based on machine learning algorithms. The support vector machines (SVM) with a sigmoid function kernel showed superior classification performance with 97.9% accuracy among other classifiers, including k-nearest neighbors (KNN), logistic regression (LR), and naïve Bayes (NB). The method can detect P. aeruginosa specifically and quantitatively with a limit of detection of 102 CFU/mL. The device can classify P. aeruginosa within 10 min with a total assay time of 25 min. The device was used to test its ability to detect pathogen from the serum and sputum specimens spiked with 105 CFU/mL concentration of P. aeruginosa. The results indicate that light scattering combined with machine learning can be used to detect P. aeruginosa. The proposed technique is anticipated to be helpful as a rapid device for diagnosing P. aeruginosa related infections.


Assuntos
Dispositivos Lab-On-A-Chip , Pseudomonas aeruginosa , Teorema de Bayes , Humanos , Separação Imunomagnética , Aprendizado de Máquina , Máquina de Vetores de Suporte
7.
J Environ Manage ; 302(Pt B): 114080, 2022 Jan 15.
Artigo em Inglês | MEDLINE | ID: mdl-34773781

RESUMO

The present study investigates the environmental benefits of phasing-in autonomous ships in global maritime transportation along major dry bulk and tanker routes using Bayesian probabilistic forecasting algorithm. The focus is on the simulations and calibrations on the navigational behavior of autonomous ships at both port and high-sea, as well as the potential emission abatement of atmospheric pollutants compared to the conventional fleet along the sailing routes. We use historical data on major international tanker and dry bulk trade routes to characterize the ship movements and trends in ship emission. Different scenarios are evaluated with a combination of autonomous ship phase-in rates (25, 75, 100%) and cleaner fuel choices in Years 2030 and 2050 (from the baseline Year, 2020). The results show that the magnitude of the emission reduction generally increases with a higher level of autonomous ships in the fleet as expected, and the magnitude ranges from small increments to major reductions of 37-64% along the different routes. Overall, we hope that our findings can contribute towards the realization of environmental benefits with the adoption of autonomous shipping along the major shipping routes in the future.


Assuntos
Poluentes Atmosféricos , Poluentes Ambientais , Poluentes Atmosféricos/análise , Teorema de Bayes , Navios , Transportes , Emissões de Veículos/análise
8.
J Environ Manage ; 302(Pt B): 114089, 2022 Jan 15.
Artigo em Inglês | MEDLINE | ID: mdl-34775337

RESUMO

Maintaining ecosystem services (ESs) and reducing ecosystem degradation are important goals for achieving sustainable development. However, under the influence of various anthropogenic factors, the total ecosystem service value (ESV) of China continues to decline, and the detailed processes involved in this decline are unclear. In this paper, a new long-term annual land cover dataset (the Climate Change Initiative Land Cover or CCI-LC dataset) with a spatial resolution of 300 m was employed to estimate the ESV of China, and Bayesian spatiotemporal hierarchy models were built to examine the detailed patterns and anthropogenic driving factors. From 1992 to 2018, the total ESV of China fluctuated and decreased from 3265.3 to 3253.29 billion US$ at an average rate of 0.55 billion US$ per year. Furthermore, the model revealed the spatiotemporal variations in the ESV pattern, and simultaneously detected the influences of 9 variables related to economic factors, population, infrastructure, energy, agriculture and ecological restoration, providing a convenient and effective method for ESV spatiotemporal analysis. The results enrich our understanding of the detailed spatiotemporal variation and anthropogenic driving factors underlying the declining ESV in China. These findings have substantial guiding implications for adjusting ecological regulation policies.


Assuntos
Conservação dos Recursos Naturais , Ecossistema , Teorema de Bayes , China
9.
Environ Res ; 203: 111810, 2022 01.
Artigo em Inglês | MEDLINE | ID: mdl-34343550

RESUMO

With a recent surge of the new severe acute respiratory syndrome-coronavirus 2 (SARS-Cov-2, COVID-19) in South Korea, this study attempts to investigate the effects of environmental conditions such as air pollutants (PM2.5) and meteorological covariate (Temperature) on COVID-19 transmission in Seoul. To account for unobserved heterogeneity in the daily confirmed cases of COVID-19 across 25 contiguous districts within Seoul, we adopt a full Bayesian hierarchical approach for the generalized linear mixed models. A formal statistical analysis suggests that there exists a positive correlation between a 7-day lagged effect of PM2.5 concentration and the number of confirmed COVID-19 cases, which implies an elevated risk of the infectious disease. Conversely, temperature has shown a negative correlation with the number of COVID-19 cases, leading to reduction in relative risks. In addition, we clarify that the random fluctuation in the relative risks of COVID-19 mainly originates from temporal aspects, whereas no significant evidence of variability in relative risks is observed in terms of spatial alignment of the 25 districts. Nevertheless, this study provides empirical evidence using model-based formal assessments regarding COVID-19 infection risks in 25 districts of Seoul from a different perspective.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , COVID-19 , Poluentes Atmosféricos/efeitos adversos , Poluentes Atmosféricos/análise , Poluição do Ar/análise , Teorema de Bayes , Humanos , Material Particulado/análise , República da Coreia/epidemiologia , SARS-CoV-2 , Seul/epidemiologia , Temperatura
10.
Sci Total Environ ; 806(Pt 3): 150515, 2022 Feb 01.
Artigo em Inglês | MEDLINE | ID: mdl-34627116

RESUMO

BACKGROUND: Numerous studies have estimated adverse effects of short-term exposure to ambient air pollution on public health. Few have focused on sex-differences, and results have been inconsistent. The purpose of this study was three-fold: to identify sex-differences in air pollution-related health outcomes; to examine sex-differences by cause and season; and to examine time trends in sex-differences. METHODS: Daily data were collected on circulatory- and respiratory-related mortality (for 29 years) and cause-specific hospitalization (for 17 years) with hourly concentrations of ozone (O3), nitrogen dioxide (NO2), and fine particulate matter (PM2.5). For hospitalization, more specific causes were examined: ischemic heart disease (IHD), other heart disease (OHD), cerebrovascular disease (CEV), chronic lower respiratory diseases (CLRD), and Influenza/Pneumonia (InfPn). Generalized Poisson models were applied to 24 Canadian cities, and the city-specific estimates were combined for nationwide estimates for each sex using Bayesian hierarchical models. Finally, sex-differences were tested statistically based on their interval estimates, considering the correlation between sex-specific national estimates. RESULTS: Sex-differences were more frequently observed for hospitalization than mortality, respiratory than circulatory health outcomes, and warm than cold season. For hospitalization, males were at higher risk (M > F) for warm season (OHD and InfPn from O3; IHD from NO2; and InfPn from PM2.5), but F > M for cold season (CEV from O3 and OHD from NO2). For mortality, we found F > M only for circulatory diseases from ozone during the warm season. Among the above-mentioned sex-differences, three cases showed consistent time trends over the years: while M > F for OHD from O3 and IHD from NO2, F > M for OHD from NO2. CONCLUSIONS: We found that sex-differences in effect of ambient air pollution varied over health outcome, cause, season and time. In particular, the consistent trends (either F > M or M > F) across 17 years provide stronger evidence of sex-differences in hospitalizations, and warrant investigation in other populations.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Pneumonia , Poluentes Atmosféricos/análise , Poluentes Atmosféricos/toxicidade , Poluição do Ar/efeitos adversos , Poluição do Ar/análise , Teorema de Bayes , Canadá , Exposição Ambiental/análise , Feminino , Hospitalização , Humanos , Masculino , Material Particulado/análise , Material Particulado/toxicidade , Fatores de Tempo
11.
J Interpers Violence ; 37(1-2): NP25-NP47, 2022 01.
Artigo em Inglês | MEDLINE | ID: mdl-34911373

RESUMO

Research Questions: Rape prevention practice and policy have roots in data from 1985. This study uses 2015 national data to project recent prevalence, assesses whether rates now differ from those of 30 years ago, and disaggregates 2015 prevalence into rape of alcohol incapacitated victims, rapes combining both alcohol and physical tactics, and violent rape. Methods: Cross-sectional analyses were conducted comparing two national samples. The first was collected in 1984-85 (Koss, Gidycz, & Wisniewski, 1987); the second was collected 30 years later in 2014-2015. Both surveys used in-person administration and measurement by the most current version at the time of the Sexual Experiences Survey (SES). Prevalence rates were compared using Bayesian binomial tests. Results: In 2015, 33.4% (1 in 3) of women reported experiencing rape or attempted rape and 12.7% of men reported perpetration (1 in 8). Using Jeffreys' label for effect size of the Bayes binomial (1961), both results are "decisively" greater than expected given the 1985 benchmarks of 27.9% for victimization and 7.7% for perpetration. Victimization when incapacitated characterized approximately 75% of incidents in 2015 up from 50% in 1985. Cautions apply as cross-sectional data does not establish causality and the recent data set involved the revised SES. Conclusions: Across 30 years, neither containment nor reduction of rape was demonstrated and the increasingly prominent association with alcohol was apparent. Among the men who disclosed raping, 9 of 10 incidents were alcohol-involved. Prevention focus might profitably be directed to constraining alcohol environments and policies that facilitate rape of incapacitated persons and on misconduct responses that are proportional to the harm caused to rape victims, thereby raising the perceived risks of perpetration.


Assuntos
Vítimas de Crime , Estupro , Delitos Sexuais , Teorema de Bayes , Estudos Transversais , Feminino , Humanos , Masculino , Estudantes , Universidades
12.
Eur Radiol ; 32(1): 602-612, 2022 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-34117912

RESUMO

OBJECTIVES: In breast cancer screening, two readers separately examine each woman's mammograms for signs of cancer. We examined whether preventing the two readers from seeing each other's decisions (blinding) affects behaviour and outcomes. METHODS: This cohort study used data from the CO-OPS breast-screening trial (1,119,191 women from 43 screening centres in England) where all discrepant readings were arbitrated. Multilevel models were fitted using Markov chain Monte Carlo to measure whether reader 2 conformed to the decisions of reader 1 when they were not blinded, and the effect of blinding on overall rates of recall for further tests and cancer detection. Differences in positive predictive value (PPV) were assessed using Pearson's chi-squared test. RESULTS: When reader 1 recalls, the probability of reader 2 also recalling was higher when not blinded than when blinded, suggesting readers may be influenced by the other's decision. Overall, women were less likely to be recalled when reader 2 was blinded (OR 0.923; 95% credible interval 0.864, 0.986), with no clear pattern in cancer detection rate (OR 1.029; 95% credible interval 0.970, 1.089; Bayesian p value 0.832). PPV was 22.1% for blinded versus 20.6% for not blinded (p < 0.001). CONCLUSIONS: Our results suggest that when not blinded, reader 2 is influenced by reader 1's decisions to recall (alliterative bias) which would result in bypassing arbitration and negate some of the benefits of double-reading. We found a relationship between blinding the second reader and slightly higher PPV of breast cancer screening, although this analysis may be confounded by other centre characteristics. KEY POINTS: • In Europe, it is recommended that breast screening mammograms are analysed by two readers but there is little evidence on the effect of 'blinding' the readers so they cannot see each other's decisions. • We found evidence that when the second reader is not blinded, they are more likely to agree with a recall decision from the first reader and less likely to make an independent judgement (alliterative error). This may reduce overall accuracy through bypassing arbitration. • This observational study suggests an association between blinding the second reader and higher positive predictive value of screening, but this may be confounded by centre characteristics.


Assuntos
Neoplasias da Mama , Detecção Precoce de Câncer , Teorema de Bayes , Neoplasias da Mama/diagnóstico por imagem , Estudos de Coortes , Feminino , Humanos , Mamografia , Programas de Rastreamento , Variações Dependentes do Observador
13.
Sci Total Environ ; 806(Pt 3): 151273, 2022 Feb 01.
Artigo em Inglês | MEDLINE | ID: mdl-34718001

RESUMO

BACKGROUND: During 2014 to 2019, the SaniPath Exposure Assessment Tool, a standardized set of methods to evaluate risk of exposure to fecal contamination in the urban environment through multiple exposure pathways, was deployed in 45 neighborhoods in ten cities, including Accra and Kumasi, Ghana; Vellore, India; Maputo, Mozambique; Siem Reap, Cambodia; Atlanta, United States; Dhaka, Bangladesh; Lusaka, Zambia; Kampala, Uganda; Dakar, Senegal. OBJECTIVE: Assess and compare risk of exposure to fecal contamination via multiple pathways in ten cities. METHODS: In total, 4053 environmental samples, 4586 household surveys, 128 community surveys, and 124 school surveys were collected. E. coli concentrations were measured in environmental samples as an indicator of fecal contamination magnitude. Bayesian methods were used to estimate the distributions of fecal contamination concentration and contact frequency. Exposure to fecal contamination was estimated by the Monte Carlo method. The contamination levels of ten environmental compartments, frequency of contact with those compartments for adults and children, and estimated exposure to fecal contamination through any of the surveyed environmental pathways were compared across cities and neighborhoods. RESULTS: Distribution of fecal contamination in the environment and human contact behavior varied by city. Universally, food pathways were the most common dominant route of exposure to fecal contamination across cities in low-income and lower-middle-income countries. Risks of fecal exposure via water pathways, such as open drains, flood water, and municipal drinking water, were site-specific and often limited to smaller geographic areas (i.e., neighborhoods) instead of larger areas (i.e., cities). CONCLUSIONS: Knowledge of the relative contribution to fecal exposure from multiple pathways, and the environmental contamination level and frequency of contact for those "dominant pathways" could provide guidance for Water, Sanitation, and Hygiene (WASH) programming and investments and enable local governments and municipalities to improve intervention strategies to reduce the risk of exposure to fecal contamination.


Assuntos
Países em Desenvolvimento , Escherichia coli , Bangladesh , Teorema de Bayes , Criança , Cidades , Monitoramento Ambiental , Fezes , Humanos , Saneamento , Senegal , Uganda , Estados Unidos , Zâmbia
14.
Chemosphere ; 287(Pt 3): 132358, 2022 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-34583294

RESUMO

Previous studies suggested immunotoxicity of perfluoroalkyl substances (PFASs), but contradictory findings were reported for the associations of PFASs with allergies. The current study aimed to investigate the association of serum PFASs with incident chronic spontaneous urticaria (CSU) in adults. A nested case-control study within a longitudinal cohort of 7051 government employees in China was conducted. Participants with urticaria at the baseline were excluded. During the first follow-up, 70 incident CSU cases were included, and 70 matched healthy controls were randomly selected. In serum samples collected at the baseline, eight PFASs were determined using the UHPLC-MS/MS approach. The median serum concentrations of perfluorobutanoic acid (PFBA) and perfluoroheptanoic acid (PFHpA) were significantly higher in participants with incident CSU. The area under the receiver operating characteristic curve was 0.714 (95% CI: 0.60-0.83) based on the joint prediction by PFBA and PFHpA. The Bayesian kernel machine regression showed a nonlinear positive overall effect of the mixture of PFASs, and identified significant single effects of PFBA and PFHpA. Serum interleukin-4 was significantly higher in the case group at baseline, and was positively associated with PFHpA (r = 0.24). Causal mediation analysis indicated interleukin-4 as a partial mediator (14.8%) in the association of PFHpA with CSU. In conclusion, serum PFASs are associated with an increased risk of incident CSU, and PFBA and PFHpA might be the effective compounds.


Assuntos
Ácidos Alcanossulfônicos , Urticária Crônica , Fluorcarbonetos , Adulto , Teorema de Bayes , Estudos de Casos e Controles , Fluorcarbonetos/toxicidade , Humanos , Espectrometria de Massas em Tandem
15.
Chemosphere ; 287(Pt 4): 132402, 2022 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-34597642

RESUMO

Most previous studies have indicated inconsistent relationships between rice cadmium (Cd) and the soil properties of paddy fields at a regional scale under the adverse effects of confounding factors and spatial heterogeneity. In order to reduce these effects, this study integrates Geodetector, a stepwise regression model, and a hierarchical Bayesian method (collectively called GDSH). The GDSH framework is validated in a large typical rice production area in southeastern China. According to the results, significant stratified heterogeneity of the bioaccumulation factor is observed among different subregions and pH strata (q = 0.23, p < 0.01). Additionally, the soil-rice relationships and dominant factors vary by the subregions, and the available soil Cd and pH are found to be the dominant factors in 64% and 50% of subregions, respectively. In the entire region, when the pH < 6, the dominant factors are organic matter and available Cd, and when pH ≥ 6 they are organic matter, pH, and available Cd. Furthermore, these factors presented different sensitivity to the spatial heterogeneity. The results indicate that, at the subregional level, the GDSH framework can reduce the confounding effects and accurately identify the dominant factors of rice Cd. At the regional level, this model can evaluate the sensitivity of the dominant factors to spatial heterogeneity in a large area. This study provides a new scheme for the complete utilization of regional field survey data, which is conducive to formulating precise pollution control strategies.


Assuntos
Oryza , Poluentes do Solo , Teorema de Bayes , Cádmio/análise , Solo , Poluentes do Solo/análise
16.
J Environ Manage ; 301: 113576, 2022 Jan 01.
Artigo em Inglês | MEDLINE | ID: mdl-34597946

RESUMO

The approach of applying stressor load limits or thresholds to aid estuarine management is being explored in many global case studies. However, there is growing concern regarding the influence of multiple stressors and their cumulative effects on the functioning of estuarine ecosystems due to the considerable uncertainty around stressor interactions. Recognising that empirical data limitations hinder parameterisation of detailed models of estuarine ecosystem responses to multiple stressors (suspended sediment, sediment mud and metal content, and nitrogen inputs), an expert driven Bayesian network (BN) was developed and validated. Overall, trends in estuarine condition predicted by the BN model were well supported by field observations, including results that were markedly higher than random (71-84% concordance), providing confidence in the overall model dynamics. The general BN framework was then applied to a case study estuary to demonstrate the model's utility for informing management decisions. Results indicated that reductions in suspended sediment loading were likely to result in improvements in estuarine condition, which was further improved by reductions in sediment mud and metal content, with an increased likelihood of high abundance of ecological communities relative to baseline conditions. Notably, reductions in suspended sediment were also associated with an increased probability of high nuisance macroalgae and phytoplankton if nutrient loading was not also reduced (associated with increased water column light penetration). Our results highlight that if stressor limit setting is to be implemented, limits must incorporate ecosystem responses to cumulative stressors, consider the present and desired future condition of the estuary of interest, and account for the likelihood of unexpected ecological outcomes regardless of whether the experts (or empirical data) suggest a threshold has or has not been triggered.


Assuntos
Ecossistema , Estuários , Teorema de Bayes , Nitrogênio , Fitoplâncton
17.
J Environ Manage ; 301: 113817, 2022 Jan 01.
Artigo em Inglês | MEDLINE | ID: mdl-34607136

RESUMO

Assessing trade-offs among ecosystem services (ESs) that are provided by forests is necessary to support decision-making and to minimize negative effects of timber harvesting. In this study, we examined how spatial data, forest operational rules, ESs, and probabilistic statistics can be combined into a practical tool for trade-off analysis that could guide decision-making towards sustainable forestry. Our main goal was to analyze trade-offs among the wood provisioning ES and other forest ESs at the landscape level using a Bayesian belief network (BBN). We used LiDAR data to derive four ES layers as inputs to a spatial BBN: (i) wood provisioning; (ii) erosion regulating; (iii) climate regulating; and (iv) habitat supporting. We quantified operational constraints with four forest operational rules (FOR) that were defined in terms of: (i) potential harvest block size; (ii) distance between a small potential harvest block and a larger harvest block; (iii) gross merchantable volume (GMV); and (iv) distance to an existing resource road. Maps of the most probable trade-off classes between the wood provisioning ES and other ESs enabled us to identify areas where timber harvesting should be avoided or where timber harvesting should have a very low negative effect on other ESs. Even with our most restrictive management scenario, the total GMV that could be harvested met the annual allowable cut (AAC) volume required to meet sustainable forestry objectives. Through our study, we demonstrated that high-resolution spatial data could be used to quantify trade-offs among wood provisioning ES and other forest-related ESs and to simulate small changes in ES indicators within the BBN. We also demonstrated the potential to evaluate management scenarios to reduce trade-offs by considering FOR as inputs to the BBN. Maps of the most probable trade-off classes among two or three ESs under operational constraints provide key information to guide forest management decision-making towards sustainable forestry.


Assuntos
Ecossistema , Agricultura Florestal , Teorema de Bayes , Conservação dos Recursos Naturais , Florestas
18.
Environ Pollut ; 292(Pt A): 118247, 2022 Jan 01.
Artigo em Inglês | MEDLINE | ID: mdl-34624398

RESUMO

Dyslipidemia may be a potential mechanism linking air pollution to adverse cardiovascular outcomes and this may differ among obese and normal-weight populations. However, the joint effect of multiple air pollutants on lipid profiles and the role of each pollutant are still unclear. This panel study aims to investigate and compare the overall associations of major air pollutants with lipid parameters in obese and normal-weight adults, and assess the relative importance of each pollutant for lipid parameters. Forty-four obese and 53 normal-weight young adults were recruited from December 2017 to June 2018 in Beijing, China. Their fasting blood was collected and serum lipid levels were measured in three visits. Six major air pollutants were included in this study, which were PM2.5, PM10, NO2, SO2, O3 and CO. Bayesian kernel machine regression (BKMR) was implemented to estimate the joint effect of the six air pollutants on various lipid parameters. We found that decreased high-density lipoprotein cholesterol (HDL-C) in the obese group and increased low-density lipoprotein cholesterol (LDL-C) and non-HDL-C in the normal-weight group were associated with the exposure to the mixture of six air pollutants above. Significant increases in total cholesterol (TC)/HDL-C and non-HDL-C/HDL-C were observed in both groups, and the effect was stronger in obese group. Of the six air pollutants above, O3 had the largest posterior inclusion probability in above lipid indices, ranging from 0.75 to 1.00. In the obese group, approximately linear exposure-response relationships were observed over the whole range of logarithmic O3-8 h max concentration, while in the normal-weight group, these relationships existed when the logarithmic concentration exceeded about 2.8. Therefore, lipid profiles of obese adults may be more sensitive to air pollution and this study highlights the importance of strengthening emissions control efforts for O3 in the future.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Ozônio , Poluentes Atmosféricos/análise , Poluição do Ar/análise , Teorema de Bayes , China , Humanos , Lipídeos , Obesidade , Ozônio/análise , Material Particulado/análise , Adulto Jovem
19.
Acta Trop ; 225: 106181, 2022 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-34678259

RESUMO

INTRODUCTION: Cutaneous Leishmaniasis (CL) is a significant public health concern worldwide. Iran is among the most CL-affected countries, being one of the six most endemic countries in the world. This study aimed to provide a spatio-temporal visualisation of CL cases in an endemic urban area in north-eastern Iran identifying high-risk and low-risk areas during the period 2016-2019. METHODS: This ecological study was conducted in the city of Mashhad, north-eastern Iran. All cases (n=2425) were diagnosed based on clinical findings and parasitological tests. The patient data were aggregated at the census tract level (the highest resolution available). CL incidence rates were subjected to Empirical Bayesian smoothing across the census tracts followed by spatial autocorrelation analysis to identify clusters and outliers. Spatial scan statistic was used to explore the purely temporal, purely spatial and spatio-temporal trend of the disease. In all instances, the null hypothesis of no clusters was rejected at p ≤0.05. RESULTS: The overall crude incidence rate decreased from 34.6 per 100,000 individuals in 2016 to 19.9 per 100,000 in 2019. Cluster analysis identified high-risk areas in south-western Mashhad and low-risk areas in the north-eastern areas. Purely time scan statistics identified March to July as the time period with highest risk for CL occurrence. One most likely purely high-risk spatial cluster and six secondary purely high-risk spatial clusters were identified. Further, two spatio-temporal high-risk clusters, one in the north of the city from April to August and a second in the south-western part from March to September were observed. CONCLUSIONS: Significant spatial, temporal and spatio-temporal patterns of CL distribution were observed in the study area, which should be considered when designing tailored interventions, such as effective resource allocation models, informed control plans and implementation of efficient surveillance systems. Furthermore, this study generated new hypotheses to test potential relationships between socio-economic and environmental risk factors and incidence of CL in high-risk areas.


Assuntos
Leishmaniose Cutânea , Teorema de Bayes , Análise por Conglomerados , Humanos , Incidência , Irã (Geográfico)/epidemiologia , Leishmaniose Cutânea/epidemiologia , Análise Espaço-Temporal
20.
Crit Care Clin ; 38(1): 51-67, 2022 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-34794631

RESUMO

Clinical reasoning is prone to errors in judgment. Error is comprised of 2 components-bias and noise; each has an equally important role in the promulgation of error. Biases or systematic errors in reasoning are the product of misconceptions of probability and statistics. Biases arise because clinicians frequently rely on mental shortcuts or heuristics to make judgments. The most frequently used heuristics are representativeness, availability, and anchoring/adjustment which lead to the common biases of base rate neglect, misconceptions of regression, insensitivities to sample size, and fallacies of conjunctive, and disjunctive events. Bayesian reasoning is the framework within which posterior probabilities of events is identified. Familiarity with these mathematical concepts will likely enhance clinical reasoning. Noise is defined as inter or intraobserver variability in judgment that should be identical. Guidelines in medicine are a technique to reduce noise.


Assuntos
Heurística , Julgamento , Teorema de Bayes , Humanos , Unidades de Terapia Intensiva
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