scholarly journals Satellite-Based Estimation of Daily Ground-Level PM2.5 Concentrations over Urban Agglomeration of Chengdu Plain

Atmosphere ◽  
2019 ◽  
Vol 10 (5) ◽  
pp. 245 ◽  
Author(s):  
Weihong Han ◽  
Ling Tong
Keyword(s):  
Prediction Error ◽  
Ground Level ◽  
Public Health Research ◽  
Urban Agglomeration ◽  
Pollution Monitoring ◽  
Estimation Accuracy ◽  
Linear Mixed Effect Model ◽  
Mountain Areas ◽  
Mixed Effect ◽  
Chengdu Plain

Monitoring particulate matter with aerodynamic diameters of less than 2.5 μm (PM2.5) is of great importance to assess its adverse effects on human health, especially densely populated regions. In this paper, an improved linear mixed effect model (LMEM) was developed. The model introduced meteorological variable, column water vapor (CWV), which has as the same resolution as satellite-derived aerosol optical thickness (AOT), to enhance PM2.5 estimation accuracy by considering spatiotemporal consistency of CWV and AOT. The model was implemented to urban agglomeration of Chengdu Plain during 2015. The results show that model accuracy has been improved significantly compared to linear regression model (R2 = 0.49), with R2 of 0.81 and root mean squared prediction error (RMSPE) of 15.47 μg/m3, mean prediction error (MPE) of 11.09 μg/m3, and effectively revealed the characteristics of spatiotemporal variations PM2.5 level across the study area: The PM2.5 level is higher in the central and southern areas with dense population, while it is lower in the northwest and southwest mountain areas; and the PM2.5 level is higher during autumn and winter, while it is lower during spring and summer. The product data in this paper are valuable for local government pollution monitoring, public health research, and urban air quality control.

scholarly journals Estimation of High-Resolution Daily Ground-Level PM2.5 Concentration in Beijing 2013–2017 Using 1 km MAIAC AOT Data

2018 ◽  
Vol 8 (12) ◽  
pp. 2624 ◽  
Author(s):  
Weihong Han ◽  
Ling Tong ◽  
Yunping Chen ◽  
Runkui Li ◽  
Beizhan Yan ◽  
...  
Keyword(s):  
Human Health ◽  
Urban Areas ◽  
Prolonged Exposure ◽  
Atmospheric Correction ◽  
Ground Level ◽  
Linear Mixed Effect Model ◽  
Urban Landscapes ◽  
Spatiotemporal Variations ◽  
Spatiotemporal Resolution ◽  
Mixed Effect

High-spatiotemporal-resolution PM2.5 data are critical to assessing the impacts of prolonged exposure to PM2.5 on human health, especially for urban areas. Satellite-derived aerosol optical thickness (AOT) is highly correlated to ground-level PM2.5, providing an effective way to reveal spatiotemporal variations of PM2.5 across urban landscapes. In this paper, Multi-Angle Implementation of Atmospheric Correction (MAIAC) AOT and ground-based PM2.5 measurements were fused to estimate daily ground-level PM2.5 concentrations in Beijing for 2013–2017 at 1 km resolution through a linear mixed effect model (LMEM). The results showed a good agreement between the estimated and measured PM2.5 and effectively revealed the characteristics of its spatiotemporal variations across Beijing: (1) the PM2.5 level is higher in the central and southern areas, while it is lower in the northern and northwestern areas; (2) the PM2.5 level is higher in autumn and winter, while it is lower in spring and summer. Moreover, annual PM2.5 concentrations decreased by 24.03% for the whole of Beijing and 31.46% for the downtown area from 2013 to 2017. The PM2.5 data products we generated can be used to assess the long-term impacts of PM2.5 on human health and support relevant government policy decision-making, and the methodology can be applied to other heavily polluted urban areas.

scholarly journals MegaLMM: Mega-scale linear mixed models for genomic predictions with thousands of traits

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Daniel E. Runcie ◽  
Jiayi Qu ◽  
Hao Cheng ◽  
Lorin Crawford
Keyword(s):  
Genomic Prediction ◽  
Large Scale ◽  
Mixed Model ◽  
Human Genetics ◽  
Linear Mixed Effect Model ◽  
Mixed Effect ◽  
Statistical Framework ◽  
Effect Model ◽  
Plant Data ◽  
Genetic Value

AbstractLarge-scale phenotype data can enhance the power of genomic prediction in plant and animal breeding, as well as human genetics. However, the statistical foundation of multi-trait genomic prediction is based on the multivariate linear mixed effect model, a tool notorious for its fragility when applied to more than a handful of traits. We present , a statistical framework and associated software package for mixed model analyses of a virtually unlimited number of traits. Using three examples with real plant data, we show that can leverage thousands of traits at once to significantly improve genetic value prediction accuracy.

scholarly journals Sept8/SEPTIN8 involvement in cellular structure and kidney damage is identified by genetic mapping and a novel human tubule hypoxic model

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Gregory R. Keele ◽  
Jeremy W. Prokop ◽  
Hong He ◽  
Katie Holl ◽  
John Littrell ◽  
...  
Keyword(s):  
Complex Traits ◽  
Genetic Model ◽  
Association Studies ◽  
Model Systems ◽  
Linear Mixed Effect Model ◽  
Genome Wide Association Studies ◽  
Tubulointerstitial Injury ◽  
Heritable Variation ◽  
Mixed Effect

AbstractChronic kidney disease (CKD), which can ultimately progress to kidney failure, is influenced by genetics and the environment. Genes identified in human genome wide association studies (GWAS) explain only a small proportion of the heritable variation and lack functional validation, indicating the need for additional model systems. Outbred heterogeneous stock (HS) rats have been used for genetic fine-mapping of complex traits, but have not previously been used for CKD traits. We performed GWAS for urinary protein excretion (UPE) and CKD related serum biochemistries in 245 male HS rats. Quantitative trait loci (QTL) were identified using a linear mixed effect model that tested for association with imputed genotypes. Candidate genes were identified using bioinformatics tools and targeted RNAseq followed by testing in a novel in vitro model of human tubule, hypoxia-induced damage. We identified two QTL for UPE and five for serum biochemistries. Protein modeling identified a missense variant within Septin 8 (Sept8) as a candidate for UPE. Sept8/SEPTIN8 expression increased in HS rats with elevated UPE and tubulointerstitial injury and in the in vitro hypoxia model. SEPTIN8 is detected within proximal tubule cells in human kidney samples and localizes with acetyl-alpha tubulin in the culture system. After hypoxia, SEPTIN8 staining becomes diffuse and appears to relocalize with actin. These data suggest a role of SEPTIN8 in cellular organization and structure in response to environmental stress. This study demonstrates that integration of a rat genetic model with an environmentally induced tubule damage system identifies Sept8/SEPTIN8 and informs novel aspects of the complex gene by environmental interactions contributing to CKD risk.

scholarly journals Limited not lazy: a quasi-experimental secondary analysis of evidence quality evaluations by those who hold implausible beliefs

2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Kristy A. Martire ◽  
Bethany Growns ◽  
Agnes S. Bali ◽  
Bronte Montgomery-Farrer ◽  
Stephanie Summersby ◽  
...  
Keyword(s):  
Secondary Analysis ◽  
Past Research ◽  
Linear Mixed Effect Model ◽  
High Quality ◽  
Mixed Effect ◽  
High Quality Evidence ◽  
Effect Model ◽  
Evidence Quality ◽  
Quasi Experimental ◽  
Quality Evidence

AbstractPast research suggests that an uncritical or ‘lazy’ style of evaluating evidence may play a role in the development and maintenance of implausible beliefs. We examine this possibility by using a quasi-experimental design to compare how low- and high-quality evidence is evaluated by those who do and do not endorse implausible claims. Seven studies conducted during 2019–2020 provided the data for this analysis (N = 746). Each of the seven primary studies presented participants with high- and/or low-quality evidence and measured implausible claim endorsement and evaluations of evidence persuasiveness (via credibility, value, and/or weight). A linear mixed-effect model was used to predict persuasiveness from the interaction between implausible claim endorsement and evidence quality. Our results showed that endorsers were significantly more persuaded by the evidence than non-endorsers, but both groups were significantly more persuaded by high-quality than low-quality evidence. The interaction between endorsement and evidence quality was not significant. These results suggest that the formation and maintenance of implausible beliefs by endorsers may result from less critical evidence evaluations rather than a failure to analyse. This is consistent with a limited rather than a lazy approach and suggests that interventions to develop analytical skill may be useful for minimising the effects of implausible claims.

scholarly journals Associations between the Bovine Myostatin Gene and Milk Fatty Acid Composition in New Zealand Holstein-Friesian × Jersey-Cross Cows

Animals ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. 1447
Author(s):  
Ishaku L. Haruna ◽  
Yunhai Li ◽  
Ugonna J. Ekegbu ◽  
Hamed Amirpour-Najafabadi ◽  
Huitong Zhou ◽  
...  
Keyword(s):  
Fatty Acid ◽  
New Zealand ◽  
Nucleotide Sequence ◽  
Milk Fat ◽  
Linear Mixed Effect Model ◽  
Polymorphism Analysis ◽  
Mixed Effect ◽  
Myostatin Gene ◽  
Holstein Friesian ◽  
Nucleotide Sequence Variation

The myostatin gene (MSTN), which encodes the protein myostatin, is pleiotropic, and its expression has been associated with both increased and decreased adipogenesis and increased skeletal muscle mass in animals. In this study, the polymerase chain reaction, coupled with single strand conformation polymorphism analysis, was utilized to reveal nucleotide sequence variation in bovine MSTN in 410 New Zealand (NZ) Holstein-Friesian × Jersey (HF × J)-cross cows. These cows ranged from 3 to 9 years of age and over the time studied, produced an average 22.53 ± 2.18 L of milk per day, with an average milk fat content of 4.94 ± 0.17% and average milk protein content of 4.03 ± 0.10%. Analysis of a 406-bp amplicon from the intron 1 region, revealed five nucleotide sequence variants (A–E) that contained seven nucleotide substitutions. Using general linear mixed-effect model analyses the AD genotype was associated with reduced C10:0, C12:0, and C12:1 levels when compared to levels in cows with the AA genotype. These associations in NZ HF × J cross cows are novel, and they suggest that this variation in bovine MSTN could be explored for increasing the amount of milk unsaturated fatty acid and decreasing the amount of saturated fatty acid.

scholarly journals Dynamic Regional Brain Atrophy Rates in the First Year After Ischemic Stroke

Stroke ◽  
2020 ◽  
Vol 51 (9) ◽  
Author(s):  
Amy Brodtmann ◽  
Mohamed Salah Khlif ◽  
Natalia Egorova ◽  
Michele Veldsman ◽  
Laura J. Bird ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Cortical Thickness ◽  
Brain Atrophy ◽  
Brain Volume ◽  
Linear Mixed Effect Model ◽  
First Year ◽  
Intracranial Volume ◽  
Mixed Effect ◽  
Time Points ◽  
Regional Brain

Background and Purpose: Brain atrophy can be regarded as an end-organ effect of cumulative cardiovascular risk factors. Accelerated brain atrophy is described following ischemic stroke, but it is not known whether atrophy rates vary over the poststroke period. Examining rates of brain atrophy allows the identification of potential therapeutic windows for interventions to prevent poststroke brain atrophy. Methods: We charted total and regional brain volume and cortical thickness trajectories, comparing atrophy rates over 2 time periods in the first year after ischemic stroke: within 3 months (early period) and between 3 and 12 months (later period). Patients with first-ever or recurrent ischemic stroke were recruited from 3 Melbourne hospitals at 1 of 2 poststroke time points: within 6 weeks (baseline) or 3 months. Whole-brain 3T magnetic resonance imaging was performed at 3 time points: baseline, 3 months, and 12 months. Eighty-six stroke participants completed testing at baseline; 125 at 3 months (76 baseline follow-up plus 49 delayed recruitment); and 113 participants at 12 months. Their data were compared with 40 healthy control participants with identical testing. We examined 5 brain measures: hippocampal volume, thalamic volume, total brain and hemispheric brain volume, and cortical thickness. We tested whether brain atrophy rates differed between time points and groups. A linear mixed-effect model was used to compare brain structural changes, including age, sex, years of education, a composite cerebrovascular risk factor score, and total intracranial volume as covariates. Results: Atrophy rates were greater in stroke than control participants. Ipsilesional hemispheric, hippocampal, and thalamic atrophy rates were 2 to 4 times greater in the early versus later period. Conclusions: Regional atrophy rates vary over the first year after stroke. Rapid brain volume loss in the first 3 months after stroke may represent a potential window for intervention. Registration: URL: https://www.clinicaltrials.gov . Unique identifier: NCT02205424.

Variation in Cervical Length over Time during a Single Transvaginal Ultrasound Examination

2018 ◽  
Vol 36 (08) ◽  
pp. 781-784
Author(s):  
Katherine A. Connolly ◽  
Luciana Vieira ◽  
Elizabeth M. Yoselevsky ◽  
Stephanie Pan ◽  
Joanne L. Stone
Keyword(s):  
Correlation Coefficient ◽  
Intraclass Correlation Coefficient ◽  
Ultrasound Examination ◽  
Transvaginal Ultrasound ◽  
Intraclass Correlation ◽  
Cervical Length ◽  
Linear Mixed Effect Model ◽  
Mixed Effect ◽  
Time Points ◽  
Significant Difference

Objective To quantify the degree of change in cervical length (CL) over a 3-minute transvaginal ultrasound. Study Design We conducted a prospective observational study of nulliparous patients who underwent routine transvaginal CL screening at the time of their second-trimester ultrasound. We recorded CL at four time points (0, 1, 2, 3 minutes) and compared these values to determine the minute-to-minute change within a single patient. Results A total of 771 patients were included. The mean gestational age was 20.8 weeks (±0.84). We used a linear mixed effect model to assess if each minute during the ultrasound is associated with a change in CL. The intraclass correlation coefficient between minute 0 to minute 3 was 0.82 (95% confidence interval: 0.80, 0.84). This indicates that there is a relatively high within-patient correlation in CL during their ultrasound. Additionally, we stratified patients based on their starting CL; the intraclass correlation coefficient remained high for all groups. We additionally compared CL at each minute. Although there is a statistically significant difference between several time points, the actual difference is small and not clinically meaningful. Conclusion The variation in CL over a 3-minute transvaginal ultrasound examination is not clinically significant. It may be reasonable to conduct this examination over a shorter period.

scholarly journals On a Unifying ‘Reverse’ Regression for Robust Association Studies and Allele Frequency Estimation with Related Individuals

2018 ◽  
Author(s):  
Lin Zhang ◽  
Lei Sun
Keyword(s):  
Allele Frequency ◽  
Frequency Estimation ◽  
Association Studies ◽  
Genetic Association Studies ◽  
Linear Mixed Effect Model ◽  
Supporting Evidence ◽  
Mixed Effect ◽  
Allele Frequency Estimation ◽  
Reverse Regression ◽  
Related Individuals

AbstractFor genetic association studies with related individuals, standard linear mixed-effect model is the most popular approach. The model treats a complex trait (phenotype) as the response variable while a genetic variant (genotype) as a covariate. An alternative approach is to reverse the roles of phenotype and genotype. This class of tests includes quasi-likelihood based score tests. In this work, after reviewing these existing methods, we propose a general, unifying ‘reverse’ regression framework. We then show that the proposed method can also explicitly adjust for potential departure from Hardy–Weinberg equilibrium. Lastly, we demonstrate the additional flexibility of the proposed model on allele frequency estimation, as well as its connection with earlier work of best linear unbiased allele-frequency estimator. We conclude the paper with supporting evidence from simulation and application studies.

scholarly journals Changes in serum TG levels during pregnancy and their association with postpartum hypertriglyceridemia: a population-based prospective cohort study

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Yandi Zhu ◽  
Haiyan Zhu ◽  
Qinyu Dang ◽  
Qian Yang ◽  
Dongxu Huang ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Pregnant Women ◽  
Blood Lipid ◽  
Roc Curves ◽  
Population Based ◽  
Linear Mixed Effect Model ◽  
Mixed Effect ◽  
Adverse Pregnancy ◽  
Stratified Analysis ◽  
Over Time

Abstract Background Blood lipid increases during gestation are considered a physiological adaption, and decrease after delivery. However, some adverse pregnancy outcomes are thought to be related to gestational lipid levels. Therefore, it is necessary to have a reference range for lipid changes during gestation. The present study aims to describe triglyceride (TG) changes during pregnancy and 42 days postpartum and to find cut-off points for TG levels during the first, second, and third trimesters. Methods A total of 908 pregnant women were followed from recruitment to 42 days postpartum, and their serum lipids were collected at gestational weeks 6–8, 16, 24, and 36 and 42 days postpartum. The major outcome was postpartum hypertriglyceridemia. The association between gestational and postpartum TG levels was analysed by stepwise multiple linear regression. A two-stage approach including a linear mixed-effect model and linear or logistic regression was conducted to explore the contribution of the changes in TG over time in pregnancy to postpartum hypertriglyceridemia. Logistic regression was constructed to examine the association between gestational TG levels and postpartum hypertriglyceridemia. Cut-off points were calculated by receiver operating characteristic (ROC) curves. Results There was a tendency for serum TG to increase with gestational age and decrease at 42 days postpartum. Prepregnancy overweight, obesity, and GDM intensified this elevation. Higher TG levels at gestational weeks 6–8, 16, 24, and 36 were positively associated with a higher risk of postpartum hypertriglyceridemia [OR 4.962, 95 % CI (3.007–8.189); OR 2.076, 95 % CI (1.303–3.309); OR 1.563, 95 % CI (1.092–2.236); and OR 1.534, 95 % CI (1.208–1.946), respectively]. The trend of the change in TG over time was positively associated with the TG level and risk of postpartum hypertriglyceridemia [OR 11.660, 95 % CI (6.018–22.591)]. Based on ROC curves, the cut-off points of serum TG levels were 1.93, 2.35, and 3.08 mmol/L at gestational weeks 16, 24, and 36, respectively. Stratified analysis of prepregnancy body mass index (pre-BMI) and GDM showed that higher gestational TG was a risk factor for postpartum hypertriglyceridemia in women with normal pre-BMI and without GDM. Conclusions Gestational TG and its elevation were risk and predictive factors of postpartum hypertriglyceridemia, especially in pregnant women with normal pre-BMI or without GDM.

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