scholarly journals Evaluation of the growth traits of Toxicodendron vernicifluum progeny based on their genetic groups assigned using new microsatellite markers

2014 ◽  
Vol 63 (1-6) ◽  
pp. 267-274 ◽  
Author(s):  
Yuichiro Hiraoka ◽  
S. Hanaoka ◽  
A. Watanabe ◽  
T. Kawahara ◽  
M. Tabata
Keyword(s):  
Microsatellite Markers ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Growth Traits ◽  
Low Cost ◽  
Tree Height ◽  
Population Based ◽  
Likelihood Method ◽  
Sib Families ◽  
Toxicodendron Vernicifluum

Abstract Toxicodendron vernicifluum (Stokes) F. A. Barkley is a tree species cultivated in Japan for production of Japanese lacquer. To facilitate the low-cost improvement of T. vernicifluum, we developed microsatellite markers for DNA fingerprinting and family and lineage reconstruction. Nine useful microsatellites were developed, with 3 to 23 alleles per locus and an expected heterozygosity of 0.162-0.838 based on a commercially planted population that included 783 offspring. Six clusters were detected in this population based on the Bayesian clustering method, and 93 half-sib families were identified using parentage and sibship assignment analysis based on a maximum likelihood method. Many members (40-96%) of large (≥10) half-sib families included specific clusters, and members from different families included the same clusters. The cluster effect for tree height was more significant than the half-sib family effect using a linear mixed model, although these effects were not significant for other traits (diameter at breast height and number of forked trunks). Based on the findings from pedigree reconstruction, backward selection for tree height seems possible. We discuss the direction of research for improving T. vernicifluum using our proposed approach.

scholarly journals Estimates of the Time From Seroconversion to Antiretroviral Therapy Initiation Among People Newly Diagnosed With Human Immunodeficiency Virus From 2006 to 2015, New York City

2019 ◽  
Vol 71 (8) ◽  
pp. e308-e315
Author(s):  
McKaylee M Robertson ◽  
Sarah L Braunstein ◽  
Donald R Hoover ◽  
Sheng Li ◽  
Denis Nash
Keyword(s):  
Human Immunodeficiency Virus ◽  
Antiretroviral Therapy ◽  
Hiv Testing ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Population Based ◽  
Cd4 Count ◽  
Hiv Diagnosis ◽  
Art Initiation ◽  
Immunodeficiency Virus

Abstract Background We estimated the time from human immunodeficiency virus (HIV) seroconversion to antiretroviral therapy (ART) initiation during an era of expanding HIV testing and treatment efforts. Methods Applying CD4 depletion parameters from seroconverter cohort data to our population-based sample, we related the square root of the first pretreatment CD4 count to time of seroconversion through a linear mixed model and estimated the time from seroconversion. Results Among 28 162 people diagnosed with HIV during 2006–2015, 89% initiated ART by June 2017. The median CD4 count at diagnosis increased from 326 (interquartile range [IQR], 132–504) cells/µL to 390 (IQR, 216–571) cells/µL from 2006 to 2015. The median time from estimated seroconversion to ART initiation decreased by 42% from 6.4 (IQR, 3.3–11.4) years in 2006 to 3.7 (IQR, 0.5–8.3) years in 2015. The time from estimated seroconversion to diagnosis decreased by 28%, from a median of 4.6 (IQR, 0.5–10.5) years to 3.3 (IQR, 0–8.1) years from 2006 to 2015, and the time from diagnosis to ART initiation reduced by 60%, from a median of 0.5 (IQR, 0.2–2.1) years to 0.2 (IQR, 0.1–0.3) years from 2006 to 2015. Conclusions The estimated time from seroconversion to ART initiation was reduced in tandem with expanded HIV testing and treatment efforts. While the time from diagnosis to ART initiation decreased to 0.2 years, the time from seroconversion to diagnosis was 3.3 years among people diagnosed in 2015, highlighting the need for more effective strategies for earlier HIV diagnosis.

A threshold linear mixed model for identification of treatment-sensitive subsets in a clinical trial based on longitudinal outcomes and a continuous covariate

2020 ◽  
Vol 29 (10) ◽  
pp. 2919-2931
Author(s):  
Xinyi Ge ◽  
Yingwei Peng ◽  
Dongsheng Tu
Keyword(s):  
Clinical Trial ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Likelihood Function ◽  
Specific Treatment ◽  
Likelihood Method ◽  
Simulation Studies ◽  
Longitudinal Outcomes ◽  
Continuous Covariate

Identification of a subset of patients who may be sensitive to a specific treatment is an important problem in clinical trials. In this paper, we consider the case where the treatment effect is measured by longitudinal outcomes, such as quality of life scores assessed over the duration of a clinical trial, and the subset is determined by a continuous baseline covariate, such as age and expression level of a biomarker. A threshold linear mixed model is introduced, and a smoothing maximum likelihood method is proposed to obtain the estimation of the parameters in the model. Broyden-Fletcher-Goldfarb-Shanno algorithm is employed to maximize the proposed smoothing likelihood function. The proposed procedure is evaluated through simulation studies and application to the analysis of data from a randomized clinical trial on patients with advanced colorectal cancer.

Stressful life events and leukocyte telomere attrition in adulthood: a prospective population-based cohort study

2015 ◽  
Vol 45 (14) ◽  
pp. 2975-2984 ◽  
Author(s):  
S. L. van Ockenburg ◽  
E. H. Bos ◽  
P. de Jonge ◽  
P. van der Harst ◽  
R. O. B. Gans ◽  
...  
Keyword(s):  
Life Events ◽  
Mixed Model ◽  
Stressful Life Events ◽  
Linear Mixed Model ◽  
Smoking Status ◽  
Population Based ◽  
Adverse Life Events ◽  
Cross Sectional ◽  
Telomere Attrition ◽  
Multivariable Regression

Background.Telomere attrition might be one of the mechanisms through which psychosocial stress leads to somatic disease. To date it is unknown if exposure to adverse life events in adulthood is associated with telomere shortening prospectively. In the current study we investigated whether life events are associated with shortening of telomere length (TL).Method.Participants were 1094 adults (mean age 53.1, range 33–79 years) from the PREVEND cohort. Data were collected at baseline (T1) and at two follow-up visits after 4 years (T2) and 6 years (T3). Life events were assessed with an adjusted version of the List of Threatening Events (LTE). TL was measured by monochrome multiplex quantitative PCR at T1, T2, and T3. A linear mixed model was used to assess the effect of recent life events on TL prospectively. Multivariable regression analyses were performed to assess whether the lifetime life events score or the score of life events experienced before the age of 12 predicted TL cross-sectionally. All final models were adjusted for age, sex, body mass index, presence of chronic diseases, frequency of sports, smoking status, and level of education.Results.Recent life events significantly predicted telomere attrition prospectively (B = −0.031, p = 0.007). We were not able to demonstrate a significant cross-sectional relationship between the lifetime LTE score and TL. Nor did we find exposure to adverse life events before the age of 12 to be associated with TL in adulthood.Conclusions.Exposure to recent adverse life events in adulthood is associated with telomere attrition prospectively.

scholarly journals A generalized linear mixed model for understanding determinant factors of student's interest in pursuing bachelor's degree at Universitas Syiah Kuala

2021 ◽  
Vol 21 (2) ◽  
pp. 72-80
Author(s):  
ASEP RUSYANA ◽  
KHAIRIL ANWAR NOTODIPUTRO ◽  
BAGUS SARTONO
Keyword(s):  
High Schools ◽  
Normal Distribution ◽  
Random Effects ◽  
Fixed Effects ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Generalized Linear Mixed Model ◽  
Likelihood Method ◽  
Response Variable ◽  
Banda Aceh

Generalized Linear Mixed Model (GLMM) is a framework that has a response variable, fixed effects, and random effects. The response variable comes from an exponential family, whereas random effects have a normal distribution. Estimating parameters can be calculated using the maximum likelihood method using the Laplace approach or the Gauss-Hermite Quadrature (GHQ) approach. The purpose of this study was to identify factors that trigger student's interest to continue studying at Universitas Syiah Kuala (USK) using both techniques.  The GLMM is suitable for the data because the variable response has a Bernoulli distribution, and the random effects are assumed to be having a normal distribution. Also, the model helps identify the relationship between the dependent variable and the predictors. This study utilizes data from six high schools in Banda Aceh city drawn using a two-stage sampling technique. Stage 1, we randomly chose six out of sixteen public senior high schools in Banda Aceh. Stage 2, we selected students from each school from four different major classes. The GLMM model includes one binary response variable, five numerical fixed-effects, and two random effects. The response variable is the interest of high school students to continue study at USK (yes or no). The five fixed effects in the model including scores of collaboration (C), Action (A), Emotion (E), Purposes (P), and Hope (H).  Finally, the random effects are schools (S) and majors (M). In this study, both Laplace and GHQ techniques produce identical results. The predictors that can explain student interest are A, E, and H. These predictors have a positive effect. The random effects of schools and majors are not significantly different from zero. The model with three significant predictors is better than the complete predictor model.

scholarly journals Multivariate linear mixed model enhanced the power of identifying genome-wide association to poplar tree heights in a randomized complete block design

2021 ◽  
Author(s):  
Yuhua Chen ◽  
Hainan Wu ◽  
Wenguo Yang ◽  
Wei Zhao ◽  
Chunfa Tong
Keyword(s):  
Mixed Model ◽  
Linear Mixed Model ◽  
Block Design ◽  
Tree Height ◽  
Genome Wide Association ◽  
Hybrid Population ◽  
Time Points ◽  
Genome Wide ◽  
Randomized Complete Block Design ◽  
Traditional Breeding

Abstract With the advances in high-throughput sequencing technologies, it is not difficult to extract tens of thousands of single nucleotide polymorphisms (SNPs) across many individuals in a fast and cheap way, making it possible to perform genome-wide association studies (GWAS) of quantitative traits in outbred forest trees. It is very valuable to apply traditional breeding experiments in GWAS for identifying genome variants associated to ecologically and economically important traits in Populus. Here, we reported a GWAS of tree height measured at multiple time points from a randomized complete block design (RCBD), which was established with clones from an F1 hybrid population of Populus deltoides and Populus simonii. A total of 22,670 SNPs across 172 clones in the RCBD were obtained with restriction site-associated DNA sequencing (RADseq) technology. The multivariate mixed linear model was applied by incorporating the pedigree relationship matrix of individuals to test the association of each SNP to the tree heights over 8 time points. Consequently, 41 SNPs were identified significantly associated to the tree height under the p-value threshold determined by Bonferroni correction at the significant level of 0.01. These SNPs were distributed on all but 2 chromosomes (Chr02 and Chr18) and explained the phenotypic variance ranged from 0.26% to 2.64%, amounting to 63.68% in total. Comparison with previous mapping studies for poplar height as well as the candidate genes of these detected SNPs were also investigated. We therefore demonstrated that the application of multivariate linear mixed model to the longitudinal phenotypic data from the traditional breeding experimental design facilitated to identify far more genome-wide variants for tree height in poplar. The significant SNPs identified in this study would enhance understanding of molecular mechanism for growth traits and would accelerate marker-assisted breeding programs in Populus.

scholarly journals Genetic Analysis of Yield and Quality Traits in Switchgrass Based on Population Crosses

Agronomy ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 2220
Author(s):  
Serge Edmé ◽  
Rob Mitchell
Keyword(s):  
Genetic Variation ◽  
Combining Ability ◽  
Dry Matter ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Ethanol Yield ◽  
Lignin Content ◽  
Block Design ◽  
Likelihood Method ◽  
Single Pair

Obtaining greater genetic gains, particularly for biomass yield, requires a good understanding of the gene action governing the inheritance of traits with economic importance in switchgrass (Panicum virgatum L.). Individual genotypes from three different accessions were crossed in single-pair matings with reciprocals to assess the relative importance of additive to nonadditive genetic variation and the potential of using inter-ecotypic crosses to improve dry matter yield (DMY), in vitro dry matter digestibility (IVDMD), lignin content (ADL and KL), and ethanol yield (ETOH). Crosses and four reference populations were planted in a randomized complete block design with eight replications of single family-rows plots, with five-plants each and 1 m spacings. A linear mixed model was applied as per the restricted maximum likelihood method, integrated with a pedigree tracing back to the original founders of these parental populations, and augmented with the designation of four genetic groups. Variation due to SCA (specific combining ability) was predominant for all traits, contributing from 20% to 57% of the total phenotypic variation and with Baker’s ratios (GCA/SCA) varying from 0.003 to 0.67. Heritability values calculated at the fullsib-family mean level were moderate to very high. Variation due to GCA (general combining ability) was detected with a lesser significance for DMY and ETOH. A reciprocal GCA effect was present in the form of maternal inheritance for DMY, suggesting the use of the highest biomass-yielding parent as female in inter-ecotypic breeding. Selecting and deploying fullsib families, deploying clonal hybrids, and adopting an introgression breeding approach are all possibilities available to switchgrass breeders to exploit the complementary genes from this germplasm and capitalize on the non-additive genetic variation present in these crosses.

scholarly journals Usage Continuance in Software-as-a-Service

2020 ◽  
Author(s):  
Elias Baumann ◽  
Jana Kern ◽  
Stefan Lessmann
Keyword(s):  
Longitudinal Study ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Low Cost ◽  
Software As A Service ◽  
Client Characteristics ◽  
Study Approach ◽  
Using Data ◽  
Positive Effect ◽  
Over Time

Abstract Software-as-a-service applications are experiencing immense growth as their comparatively low cost makes them an important alternative to traditional software. Following the initial adoption phase, vendors are now concerned with the continued usage of their software. To analyze the influence of different measures to improve continued usage over time, a longitudinal study approach using data from a SaaS vendor was implemented. Employing a linear mixed model, the study finds several measures to have a positive effect on a software’s usage penetration. In addition to these activation measures performed by the SaaS vendor, software as well as client characteristics were also examined, but did not display significant estimates. The findings emphasize the need for proactive activation initiatives to raise usage penetration. More generally, the study contributes novel insights into the scarcely researched field of influencing factors on SaaS usage continuance.

scholarly journals Sedative use and incident cognitive decline among persons aged 75 years and older: a population-based longitudinal study

2011 ◽  
Vol 24 (1) ◽  
pp. 48-54 ◽  
Author(s):  
Franciska Desplenter ◽  
Piia Lavikainen ◽  
Sirpa Hartikainen ◽  
Raimo Sulkava ◽  
J. Simon Bell
Keyword(s):  
Cognitive Decline ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Adverse Drug Events ◽  
The Elderly ◽  
Sociodemographic Factors ◽  
Population Based ◽  
Gender Education ◽  
Sedative Drugs ◽  
State Examination

ABSTRACTBackground: Acute exposure to sedative drugs may induce memory impairment, but there is mixed evidence that long-term sedative use may result in incident cognitive decline. The objective of this study was to investigate the use of sedative drugs and incident cognitive decline in a population-based sample of persons aged 75 years and older.Methods: The study sample comprised 781 participants in the Geriatric Multidisciplinary Strategy for the Good Care of the Elderly (GeMS) study in Kuopio, Finland. Data on health status, drug use, and sociodemographic factors were elicited during annual nurse interviews from 2004 to 2007. A linear mixed model was used to compare change in Mini-Mental State Examination (MMSE) scores (2005–2007) among users of sedative drugs in 2004 and 2005 (n = 139) to non-users of sedative drugs from 2004 to 2007 (n = 310). The model was adjusted for covariates including age, gender, education, depressive symptoms and antipsychotic use.Results: Unadjusted mean MMSE scores were 27.50 in 2005, 26.58 in 2006, and 25.95 in 2007 among users of sedative drugs. Unadjusted mean MMSE scores were 28.05 in 2005, 27.61 in 2006, and 27.09 in 2007 among non-users of sedative drugs. Adjusted mean MMSE scores were 0.31 points lower in 2005, 0.62 points lower in 2006, and 0.93 lower in 2007 among users compared to non-users of sedative drugs (P = 0.051).Conclusions: Sedatives were not associated with statistically significant cognitive decline. However, clinicians should maintain a judicious approach to prescribing sedative drugs given the risk of adverse drug events.

scholarly journals Sporthorse performance testing in eventing by own and progeny performance

2012 ◽  
pp. 49-56
Author(s):  
Anita Mezei ◽  
János Posta ◽  
Sándor Mihók
Keyword(s):  
Random Effects ◽  
Fixed Effects ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Performance Testing ◽  
Population Based ◽  
Descriptive Statistics ◽  
European Countries ◽  
Breeding Values ◽  
Progeny Performance

The aim of the study was to evaluate the Hungarian Sporthorse population based on eventing competition performance. The database contained the results of 792 horses and 449 riders between 2000 and 2006. The eventing results were gathered from Hungary and other European countries. Blom transformed ranks were used to evaluate the sport performance.Three models were fitted to the Blom scores. Evaluating all the competition categories at the same time weighted Blom scores were used according to the difficulty of the category. The linear mixed model included fixed effects for age, sex, breeder, owner, location, year; and random effects for animal and rider. Horses from the database were judged by their own performance, and stallions were investigated by performance of their progenies on the basis of descriptive statistics of Blom scores and weighted Blom scores. Breeding values of eventing performance were predicted. To improve the reliability of breeding values, more progenies should beused in eventing competitions. 

scholarly journals Smoke Patterns around Prescribed Fires in Australian Eucalypt Forests, as Measured by Low-Cost Particulate Monitors

Atmosphere ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1389
Author(s):  
Owen Francis Price ◽  
Hugh Forehead
Keyword(s):  
Air Quality ◽  
Statistical Model ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Low Cost ◽  
Weather Conditions ◽  
Fire Size ◽  
Prescribed Burns ◽  
Eastern Australia ◽  
Generalised Linear Mixed Model

Prescribed burns produce smoke pollution, but little is known about the spatial and temporal pattern because smoke plumes are usually small and poorly captured by State air-quality networks. Here, we sampled smoke around 18 forested prescribed burns in the Sydney region of eastern Australia using up to 11 Nova SDS011 particulate sensors and developed a Generalised Linear Mixed Model to predict hourly PM2.5 concentrations as a function of distance, fire size and weather conditions. During the day of the burn, PM2.5 tended to show hourly exceedances (indicating poor air quality) up to ~2 km from the fire but only in the downwind direction. In the evening, this zone expanded to up to 5 km and included upwind areas. PM2.5 concentrations were higher in still, cool weather and with an unstable atmosphere. PM2.5 concentrations were also higher in larger fires. The statistical model confirmed these results, identifying the effects of distance, period of the day, wind angle, fire size, temperature and C-Haines (atmospheric instability). The model correctly identified 78% of hourly exceedance and 72% of non-exceedance values in retained test data. Applying the statistical model predicts that prescribed burns of 1000 ha can be expected to cause air quality exceedances over an area of ~3500 ha. Cool weather that reduces the risk of fire escape, has the highest potential for polluting nearby communities, and fires that burn into the night are particularly bad.

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