Linear models for joint association and linkage QTL mapping

Background

Populational linkage disequilibrium and within-family linkage are commonly used for QTL mapping and marker assisted selection. The combination of both results in more robust and accurate locations of the QTL, but models proposed so far have been either single marker, complex in practice or well fit to a particular family structure.

Results

We herein present linear model theory to come up with additive effects of the QTL alleles in any member of a general pedigree, conditional to observed markers and pedigree, accounting for possible linkage disequilibrium among QTLs and markers. The model is based on association analysis in the founders; further, the additive effect of the QTLs transmitted to the descendants is a weighted (by the probabilities of transmission) average of the substitution effects of founders'' haplotypes. The model allows for non-complete linkage disequilibrium QTL-markers in the founders. Two submodels are presented: a simple and easy to implement Haley-Knott type regression for half-sib families, and a general mixed (variance component) model for general pedigrees. The model can use information from all markers. The performance of the regression method is compared by simulation with a more complex IBD method by Meuwissen and Goddard. Numerical examples are provided.

Conclusion

The linear model theory provides a useful framework for QTL mapping with dense marker maps. Results show similar accuracies but a bias of the IBD method towards the center of the region. Computations for the linear regression model are extremely simple, in contrast with IBD methods. Extensions of the model to genomic selection and multi-QTL mapping are straightforward.     

A simple model for estimating Ni availability and leaf Ni accumulation for the Ni-hyperaccumulator Leptoplax emarginata

Aims

The aim of the present study was to predict kinetics of both Ni concentration in soil solution and leaf Ni mass for the Ni-hyperaccumulator Leptoplax emarginata cultivated on a fertilized and Ni-contaminated sandy topsoil.

Methods

The 0-D (independent of space) one-site rate-limited desorption model proposed by Ingwersen et al. (J Environ Qual 35:2055–2065, 2006) was modified. The plant sink term of the model was approximated by the biophysical equation which assumes that the leaf nickel mass is equal to the triple product of the Intact Plant Transpiration Stream Concentration Factor for Ni IPTSCF_Ni (xylem:solution Ni concentration ratio), Ni concentration in solution and the volume of transpired water. The model input variables were the constant mean IPTSCF_Ni value, determined from independent leaf Ni accumulation kinetics, and the exponential law fitting the transpiration rate kinetics. Using the best calibration, the model was validated and a sensitivity analysis was carried out thereafter. Models were formulated as sets of ordinary differential equation systems which were solved using the fourth-order Runge–Kutta method.

Results

The best model calibration was the joint parameter optimization: the two parameters of the Freundlich Ni adsorption isotherm and of the Ni desorption rate coefficient are obtained using the kinetics of Ni concentrations in the soil solutions for the reference unplanted Ni-contaminated topsoils. The model was validated reasonably well for both Ni concentration in soil solution and leaf Ni mass.

Conclusions

The joint parameter optimization of the two parameters of the Freundlich nickel sorption isotherm and of the Ni desorption rate was successful whereas the Freundlich batch Ni sorption isotherm dramatically overestimated Ni sorption. This joint approach is therefore recommended for any plant metal uptake model. The 0-D one-site rate-limited desorption model linked to a biophysical coupled Ni and water uptake model reasonably validated the kinetics of both Ni concentration in solution and leaf Ni mass. This promising simplified model for predicting both metal concentration in solution and leaf metal mass for metal needs further validations in culture chambers and further improvements in order to use it in the field as a one-dimensional model, taking into account soil moisture dynamics.     

Timing of Antimicrobial Therapy after Identification of Ventilator-Associated Condition Is Not Associated with Mortality in Patients with Ventilator-Associated Pneumonia: A Cohort Study

Purpose

Delays in antimicrobial therapy increase mortality in ventilator-associated pneumonia (VAP). The more objective ventilator-associated complications (VAC) are increasingly used for quality reporting. It is unknown if delays in antimicrobial administration, after patients meet VAC criteria, leads to worse outcomes.

Materials and Methods

Cohort of 81 episodes of antimicrobial treatment for VAP. We compared mortality, superinfections and treatment failures conditional on the timing of identification of VAC.

Results

60% of patients with VAC had an identifiable episode at least 48 before the initiation of antimicrobials. Antimicrobial administration after the identification of VAC was not associated with intensive care unit (ICU) mortality (OR 0.71, 95% CI 0.11–4.48, p = 0.701) compared to immediate antimicrobial administration. Similarly, the risk of treatment failure or superinfection was not affected by the timing of administration of antimicrobials in VAC (HR 0.95, 95% CI 0.42–2.19, p = 0.914).

Conclusions

We observed no signal of harm associated with the timing to initiate antimicrobials after the identification of a VAC. The identification of VAC should not lead clinicians to start antimicrobials before a diagnosis of VAP can be established.     

A novel microfluidic wound model for testing antimicrobial agents against Staphylococcus pseudintermedius biofilms

Background

Current methods for testing treatments for veterinary surgical site infections can successfully emulate elements of a chronic wound, but these are time consuming and costly, requiring specialized laboratory equipment and considerable space to house study animals. Microfluidic devices however, can be coated with collagen and maintained at basal body temperature, providing a more cost-effective and space-saving model of a chronic wound. Our study assesses the applicability of a new microfluidic model by testing the activity of DispersinB against biofilms of methicillin-resistant Staphylococcus pseudintermedius (MRSP); DispersinB has been shown to prevent biofilm growth of Staphylococcus epidermidis, another prominent wound colonizer.

Results

We successfully developed a microfluidic model to examine the effects of antimicrobial therapy on biofilms formed by organisms associated with wound infections in companion animals (e.g. MRSP). Although, we were unable to recapitulate previous findings that DispersinB-Gentamycin is highly effective against Staphylococcal biofilms using this model, we were able to confirm its effect in a microtitre plate. Differences in the experimental conditions likely account for this result (e.g. strains tested, flow conditions, treatment time, etc.). In the microtitre plate assay, DispersinB inhibited biofilm growth after a 24 hour period; there was an inverse relationship between the concentration of DispersinB-Gentamycin and the amount of biofilm remaining following treatment. Collagen-coated microtitre plates showed a similar result, but this did not correlate as well; collagen, the most abundant protein in the body may help to retain the biomass of treated biofilms.

Conclusions

Our model may be useful in examining the effect of treatment on wound infections, although we acknowledge that in this model the test organisms may be more recalcitrant to antimicrobials than in other published systems. We contend that this may in fact better represent the conditions in vivo, where organisms associated with chronic wound infections are highly resistant to antimicrobials.     

NIKEI: A New Inexpensive and Non-Invasive Scoring System to Exclude Advanced Fibrosis in Patients with NAFLD

Aims

To develop, validate and compare a non-invasive fibrosis scoring system for non-alcoholic fatty liver disease (NAFLD) derived from routinely obtained clinical and biochemical parameters.

Methods

267 consecutive patients with biopsy proven fatty liver or non-alcoholic steatohepatitis were randomly assigned to the estimation (2/3) or validation (1/3) group to develop a model for the prediction of advanced fibrosis. Univariate statistics were performed to compare patients with and without advanced fibrosis, and following a multivariate logistic regression analysis a new scoring system was constructed. This non-invasive Koeln-Essen-index (NIKEI) was validated and compared to the FIB-4 index by calculating the area under the receiver operating characteristic curve (AUC). We evaluated a stepwise combination of both scoring systems for the precise prediction of advanced fibrosis. To set in contrast, we additionally tested the diagnostic accuracy of the AST/ALT ratio, BARD score and the NAFLD fibrosis score in our cohort.

Results

Age, AST, AST/ALT ratio, and total bilirubin were identified as significant predictors of advanced fibrosis and used to construct the NIKEI with an AUC of 0.968 [0.937; 0.998] compared to 0.929 [0.869; 0.989] for the FIB-4 index. The absence of advanced fibrosis could be confirmed with excellent accuracy (99–100%). The positive predictive value of the FIB-4 index was higher (100% vs. 60%), however, the false negative rate was also high (33%). With a stepwise combination of both indices 82%–84% of biopsies would have been avoidable without a single misclassification. The AUROC for AST/ALT ratio, the NAFLD fibrosis score, and the BARD score were 0.81 (95% CI, 0.72–0.90), 0.96 (95% CI 0.92–0.99), and 0.67 (95% CI 0.55–0.78), respectively.

Conclusion

The NIKEI can reliably exclude advanced fibrosis in subjects with NAFLD. In combination with the FIB-4 index misclassification with inadequate clinical management can be avoided while the need for liver biopsies can be reduced.     

Drosophila melanogaster as a Model Host for the Burkholderia cepacia Complex

Background

Colonization with bacterial species from the Burkholderia cepacia complex (Bcc) is associated with fast health decline among individuals with cystic fibrosis. In order to investigate the virulence of the Bcc, several alternative infection models have been developed. To this end, the fruit fly is increasingly used as surrogate host, and its validity to enhance our understanding of host-pathogen relationships has been demonstrated with a variety of microorganisms. Moreover, its relevance as a suitable alternative to mammalian hosts has been confirmed with vertebrate organisms.

Methodology/Principal Findings

The aim of this study was to establish Drosophila melanogaster as a surrogate host for species from the Bcc. While the feeding method proved unsuccessful at killing the flies, the pricking technique did generate mortality within the populations. Results obtained with the fruit fly model are comparable with results obtained using mammalian infection models. Furthermore, validity of the Drosophila infection model was confirmed with B. cenocepacia K56-2 mutants known to be less virulent in murine hosts or in other alternative models. Competitive index (CI) analyses were also performed using the fruit fly as host. Results of CI experiments agree with those obtained with mammalian models.

Conclusions/Significance

We conclude that Drosophila is a useful alternative infection model for Bcc and that fly pricking assays and competition indices are two complementary methods for virulence testing. Moreover, CI results indicate that this method is more sensitive than mortality tests.     

Biodegradable thermosensitive hydrogel for SAHA and DDP delivery: therapeutic effects on oral squamous cell carcinoma xenografts

Background

OSCC is one of the most common malignancies and numerous clinical agents currently applied in combinative chemotherapy. Here we reported a novel therapeutic strategy, SAHA and DDP-loaded PECE (SAHA-DDP/PECE), can improve the therapeutic effects of intratumorally chemotherapy on OSCC cell xenografts.

Objective/Purpose

The objective of this study was to evaluate the therapeutic efficacy of the SAHA-DDP/PECE in situ controlled drug delivery system on OSCC cell xenografts.

Methods

A biodegradable and thermosensitive hydrogel was successfully developed to load SAHA and DDP. Tumor-beared mice were intratumorally administered with SAHA-DDP/PECE at 50 mg/kg (SAHA) +2 mg/kg (DDP) in 100 ul PECE hydrogel every two weeks, SAHA-DDP at 50 mg/kg(SAHA) +2 mg/kg(DDP) in NS, 2 mg/kg DDP solution, 50 mg/kg SAHA solution, equal volume of PECE hydrogel, or equal volume of NS on the same schedule, respectively. The antineoplastic actions of SAHA and DDP alone and in combination were evaluated using the determination of tumor volume, immunohistochemistry, western blot, and TUNEL analysis.

Results

The hydrogel system was a free-flowing sol at 10°C, become gel at body temperature, and could sustain more than 14 days in situ. SAHA-DDP/PECE was subsequently injected into tumor OSCC tumor-beared mice. The results demonstrated that such a strategy as this allows the carrier system to show a sustained release of SAHA and DDP in vivo, and could improved therapeutic effects compared with a simple additive therapeutic effect of SAHA and DDP on mouse model.

Conclusions

Our research indicated that the novel SAHA-DDP/PECE system based on biodegradable PECE copolymer enhanced the therapeutic effects and could diminished the side effects of SAHA/DDP. The present work might be of great importance to the further exploration of the potential application of SAHA/DDP-hydrogel controlled drug release system in the treatment of OSCC.     

Analysis of Combination Drug Therapy to Develop Regimens with Shortened Duration of Treatment for Tuberculosis

Rationale

Tuberculosis remains a worldwide problem, particularly with the advent of multi-drug resistance. Shortening therapy duration for Mycobacterium tuberculosis is a major goal, requiring generation of optimal kill rate and resistance-suppression. Combination therapy is required to attain the goal of shorter therapy.

Objectives

Our objective was to identify a method for identifying optimal combination chemotherapy. We developed a mathematical model for attaining this end. This is accomplished by identifying drug effect interaction (synergy, additivity, antagonism) for susceptible organisms and subpopulations resistant to each drug in the combination.

Methods

We studied the combination of linezolid plus rifampin in our hollow fiber infection model. We generated a fully parametric drug effect interaction mathematical model. The results were subjected to Monte Carlo simulation to extend the findings to a population of patients by accounting for between-patient variability in drug pharmacokinetics.

Results

All monotherapy allowed emergence of resistance over the first two weeks of the experiment. In combination, the interaction was additive for each population (susceptible and resistant). For a 600 mg/600 mg daily regimen of linezolid plus rifampin, we demonstrated that >50% of simulated subjects had eradicated the susceptible population by day 27 with the remaining organisms resistant to one or the other drug. Only 4% of patients had complete organism eradication by experiment end.

Discussion

These data strongly suggest that in order to achieve the goal of shortening therapy, the original regimen may need to be changed at one month to a regimen of two completely new agents with resistance mechanisms independent of the initial regimen. This hypothesis which arose from the analysis is immediately testable in a clinical trial.     

A GWAS assessment of the contribution of genomic imprinting to the variation of body mass index in mice

Background

Genomic imprinting is an epigenetic mechanism that can lead to differential gene expression depending on the parent-of-origin of a received allele. While most studies on imprinting address its underlying molecular mechanisms or attempt at discovering genomic regions that might be subject to imprinting, few have focused on the amount of phenotypic variation contributed by such epigenetic process. In this report, we give a brief review of a one-locus imprinting model in a quantitative genetics framework, and provide a decomposition of the genetic variance according to this model. Analytical deductions from the proposed imprinting model indicated a non-negligible contribution of imprinting to genetic variation of complex traits. Also, we performed a whole-genome scan analysis on mouse body mass index (BMI) aiming at revealing potential consequences when existing imprinting effects are ignored in genetic analysis.

Results

10,021 SNP markers were used to perform a whole-genome single marker regression on mouse BMI using an additive and an imprinting model. Markers significant for imprinting indicated that BMI is subject to imprinting. Marked variance changed from 1.218 ×10⁻⁴ to 1.842 ×10⁻⁴ when imprinting was considered in the analysis, implying that one third of marked variance would be lost if existing imprinting effects were not accounted for. When both marker and pedigree information were used, estimated heritability increased from 0.176 to 0.195 when imprinting was considered.

Conclusions

When a complex trait is subject to imprinting, using an additive model that ignores this phenomenon may result in an underestimate of additive variability, potentially leading to wrong inferences about the underlying genetic architecture of that trait. This could be a possible factor explaining part of the missing heritability commonly observed in genome-wide association studies (GWAS).     

Development and Validation of an Osteoporosis Self-Assessment Tool for Taiwan (OSTAi) Postmenopausal Women-A Sub-Study of the Taiwan OsteoPorosis Survey (TOPS)

Background

To develop an OSTAi tool and compare this with the National Osteoporosis Foundation recommendations in 2013 (NOF 2013) for bone mineral density (BMD) testing among Taiwan postmenopausal women.

Methods

Taiwan Osteoporosis Association (TOA) conducted a nationwide BMD survey by a bus installed with a dual energy X-ray absorptiometry (DXA) between 2008 and 2011. All of the participants completed questionnaire, which included demographics and risk factors of osteoporotic fracture in FRAX tool. We used the database to analyze potential risk factors for osteoporosis and followed the model by Koh et al. to develop a risk index via multiple variable regression analysis and item reduction. We used the index values to set up a simple algorithm (namely OSTAi) to identify those who need BMD measurement. Receiver operating characteristic (ROC) curve and the area under the curve (AUC) was used to compare the sensitivity/specificity analysis of this model with that of recommendations by NOF 2013.

Results

A total of 12,175 Taiwan postmenopausal women enrolled in this survey. The index value was derived by age and body weight of the participants according to weighted odds of each risk factor and the selected cutoff value was set at “-1”. There are 6393 (52.5%) participants whose index value is below “-1” and whose risk of osteoporosis was 57.5% (3674/6393). The AUC for OSTAi and NOF 2013 were 0.739 (95% confidence interval (CI), 0.728–0.749, P<0.001) and 0.618 (95% CI, 0.606–0.630, P<0.001), respectively. The sensitivity and specificity of OSTAi, at the selected cutoff value of -1, and NOF 2013 to identify osteoporosis were 73.1%, 62.0% and 78.3%, 45.7%, respectively.

Conclusions

As OSTA for Asian populations, OSTAi is an useful tool to identify Taiwan postmenopausal women with osteoporosis, In comparison with NOF 2013, OSTAi may be an easier and better tool for referral to BMD measurement by DXA in this area.     

Prognostic Value of TNF-Related Apoptosis Inducing Ligand (TRAIL) in Acute Coronary Syndrome Patients

Background

Apoptosis plays an important role in the development of heart failure. The aim of the prospectively designed study was to assess whether the concentration of apoptotic markers apoptosis-stimulating fragment (Fas, CD95/APO-1) and tumor necrosis factor-related apoptosis inducing ligand (TRAIL) can predict prognosis in patients with acute coronary syndromes.

Methods

The concentrations of soluble Fas and TRAIL were determined in 295 patients with acute coronary syndromes. The status of all patients was evaluated at 6 months. The primary goal was a composite end-point of death and hospitalization for heart failure. The secondary end-points were re-MI, death alone and stroke alone.

Results

During the median follow-up of 6 months, 26 patients experienced the composite end-point. Using multivariate logistic regression, the concentration of TRAIL was the strongest significant and independent predictor of composite end-point (OR 0.11 (95% CI 0.03–0.45), p = 0.002). Low concentration was associated with poor prognosis of patients. Other significant predictors of composite end-point were serum creatinine (OR 7.7 (95% CI 1.1–54.5, p = 0.041) and complete revascularization (OR 0.19 (95% CI 0.05–0.78, p = 0.02). Independent significant predictors of death in the multivariate analysis were the concentration of TRAIL (OR 0.053 (95% CI 0.004–0.744), p = 0.029), older age (OR 1.20 (95% CI 1.02–1.41, p = 0.026) and serum creatinine (OR 15.1 (95% CI 1.56–145.2), p = 0.0193). Re-MI or stroke could not be predicted by any combination of obtained parameters.

Conclusions

Low concentrations of soluble TRAIL represent a strong predictor of a poor prognosis in patients with acute coronary syndrome. The predictive value of TRAIL concentration is independent of age, ejection fraction, index peak troponin level, concentration of BNP or serum creatinine.     

Enhanced anticancer activity of gemcitabine in combination with noscapine via antiangiogenic and apoptotic pathway against non-small cell lung cancer

Background

The aim of this investigation was to evaluate the anticancer activity of Noscapine (Nos) and Gemcitabine (Gem) combination (NGC) against non-small cell lung cancer (NSCLC) and to elucidate the underlying mechanism of action.

Methods

Isobolographic method was used to calculate combination index values from cytotoxicity data. In vitro antiangiogenic and apoptotic activity of Nos, Gem and NGC was evaluated. For in vivo studies, female athymic Nu/nu mice were xenografted with H460 tumors and the efficacy of Nos, Gem, or NGC was determined. Protein expressions by immunohistochemical staining were evaluated in harvested tumor tissues.

Results

The CI values (<0.59) were suggestive of synergistic behavior between Nos and Gem. NGC treatment showed significantly inhibited tube formation and increased percentage of apoptotic cells. NGC, Gem and Nos treatment reduced tumor volume by 82.9±4.5 percent, 39.4±5.8 percent and 34.2±5.7 percent respectively. Specifically, NGC treatment decreased expression cell survival proteins; VEGF, CD31 staining and microvessel density and enhanced DNA fragmentation and cleaved caspase 3 levels compared to single agent treated and control groups.

Conclusion

Nos potentiated the anticancer activity of Gem in an additive to synergistic manner against lung cancer via antiangiogenic and apoptotic pathways. These findings suggest potential benefit for use of NGC chemotherapy for treatment of lung cancer.     

Observational study on the impact of initiating tiotropium alone versus tiotropium with fluticasone propionate/salmeterol combination therapy on outcomes and costs in chronic obstructive pulmonary disease

Background

This retrospective cohort study compared the risks of exacerbations and COPD-related healthcare costs between patients with chronic obstructive pulmonary disease (COPD) initiating tiotropium (TIO) alone and patients initiating triple therapy with fluticasone-salmeterol combination (FSC) added to TIO.

Methods

Managed-care enrollees who had an index event of ≥ 1 pharmacy claim for TIO during the study period (January 1, 2003-April 30, 2008) and met other eligibility criteria were categorized into one of two cohorts depending on their medication use. Patients in the TIO+FSC cohort had combination therapy with TIO and FSC, defined as having an FSC claim on the same date as the TIO claim. Patients in the TIO cohort had no such FSC use. The risks of COPD exacerbations and healthcare costs were compared between cohorts during 1 year of follow-up.

Results

The sample comprised 3333 patients (n = 852 TIO+FSC cohort, n = 2481 TIO cohort). Triple therapy with FSC added to TIO compared with TIO monotherapy was associated with significant reductions in the adjusted risks of moderate exacerbation (hazard ratio 0.772; 95% confidence interval [CI] 0.641, 0.930) and any exacerbation (hazard ratio 0.763; 95% CI 0.646, 0.949) and a nonsignificant reduction in COPD-related adjusted monthly medical costs.

Conclusions

Triple therapy with FSC added to TIO compared with TIO monotherapy was associated with significant reductions in the adjusted risks of moderate exacerbation and any exacerbation over a follow-up period of up to 1 year. These improvements were gained with triple therapy at roughly equal cost of that of TIO alone.     

Gene Expression Profile for Predicting Survival in Advanced-Stage Serous Ovarian Cancer Across Two Independent Datasets

Background

Advanced-stage ovarian cancer patients are generally treated with platinum/taxane-based chemotherapy after primary debulking surgery. However, there is a wide range of outcomes for individual patients. Therefore, the clinicopathological factors alone are insufficient for predicting prognosis. Our aim is to identify a progression-free survival (PFS)-related molecular profile for predicting survival of patients with advanced-stage serous ovarian cancer.

Methodology/Principal Findings

Advanced-stage serous ovarian cancer tissues from 110 Japanese patients who underwent primary surgery and platinum/taxane-based chemotherapy were profiled using oligonucleotide microarrays. We selected 88 PFS-related genes by a univariate Cox model (p<0.01) and generated the prognostic index based on 88 PFS-related genes after adjustment of regression coefficients of the respective genes by ridge regression Cox model using 10-fold cross-validation. The prognostic index was independently associated with PFS time compared to other clinical factors in multivariate analysis [hazard ratio (HR), 3.72; 95% confidence interval (CI), 2.66–5.43; p<0.0001]. In an external dataset, multivariate analysis revealed that this prognostic index was significantly correlated with PFS time (HR, 1.54; 95% CI, 1.20–1.98; p = 0.0008). Furthermore, the correlation between the prognostic index and overall survival time was confirmed in the two independent external datasets (log rank test, p = 0.0010 and 0.0008).

Conclusions/Significance

The prognostic ability of our index based on the 88-gene expression profile in ridge regression Cox hazard model was shown to be independent of other clinical factors in predicting cancer prognosis across two distinct datasets. Further study will be necessary to improve predictive accuracy of the prognostic index toward clinical application for evaluation of the risk of recurrence in patients with advanced-stage serous ovarian cancer.     

A comparison of methods to calculate a total merit index using stochastic simulation

Background

Modern dairy cattle breeding goals include several production and more and more functional traits. Estimated breeding values (EBV) that are combined in the total merit index usually come from single-trait models or from multivariate models for groups of traits. In most cases, a multivariate animal model based on phenotypic data for all traits is not feasible and approximate methods based on selection index theory are applied to derive the total merit index. Therefore, the objective of this study was to compare a full multitrait animal model with two approximate multitrait models and a selection index approach based on simulated data.

Methods

Three production and two functional traits were simulated to mimic the national Austrian Brown Swiss population. The reference method for derivation of the total merit index was a multitrait evaluation based on all phenotypic data. Two of the approximate methods were variations of an approximate multitrait model that used either yield deviations or de-regressed breeding values. The final method was an adaptation of the selection index method that is used in routine evaluations in Austria and Germany. Three scenarios with respect to residual covariances were set up: residual covariances were equal to zero, or half of or equal to the genetic covariances.

Results

Results of both approximate multitrait models were very close to those of the reference method, with rank correlations of 1. Both methods were nearly unbiased. Rank correlations for the selection index method showed good results when residual covariances were zero but correlations with the reference method decreased when residual covariances were large. Furthermore, EBV were biased when residual covariances were high.

Conclusions

We applied an approximate multitrait two-step procedure to yield deviations and de-regressed breeding values, which led to nearly unbiased results. De-regressed breeding values gave even slightly better results. Our results confirmed that ignoring residual covariances when a selection index approach is applied leads to remarkable bias. This could be relevant in terms of selection accuracy. Our findings suggest that the approximate multitrait approach applied to de-regressed breeding values can be used in routine genetic evaluation.     

Genomic selection of purebred animals for crossbred performance in the presence of dominant gene action

Background

Genomic selection is an appealing method to select purebreds for crossbred performance. In the case of crossbred records, single nucleotide polymorphism (SNP) effects can be estimated using an additive model or a breed-specific allele model. In most studies, additive gene action is assumed. However, dominance is the likely genetic basis of heterosis. Advantages of incorporating dominance in genomic selection were investigated in a two-way crossbreeding program for a trait with different magnitudes of dominance. Training was carried out only once in the simulation.

Results

When the dominance variance and heterosis were large and overdominance was present, a dominance model including both additive and dominance SNP effects gave substantially greater cumulative response to selection than the additive model. Extra response was the result of an increase in heterosis but at a cost of reduced purebred performance. When the dominance variance and heterosis were realistic but with overdominance, the advantage of the dominance model decreased but was still significant. When overdominance was absent, the dominance model was slightly favored over the additive model, but the difference in response between the models increased as the number of quantitative trait loci increased. This reveals the importance of exploiting dominance even in the absence of overdominance. When there was no dominance, response to selection for the dominance model was as high as for the additive model, indicating robustness of the dominance model. The breed-specific allele model was inferior to the dominance model in all cases and to the additive model except when the dominance variance and heterosis were large and with overdominance. However, the advantage of the dominance model over the breed-specific allele model may decrease as differences in linkage disequilibrium between the breeds increase. Retraining is expected to reduce the advantage of the dominance model over the alternatives, because in general, the advantage becomes important only after five or six generations post-training.

Conclusion

Under dominance and without retraining, genomic selection based on the dominance model is superior to the additive model and the breed-specific allele model to maximize crossbred performance through purebred selection.     

Influence of the exclusion distance among trees on gap fraction and foliage clumping index of forest plantations

Key message

A hypergeometric model is proposed explicitly instead of two previous stochastic models (the Poisson model and Neyman-A model) to describe the topological relationship of trees and the influence of the exclusion distance on gap fraction and clumping index of forest plantation canopies.

Abstract

Gap fraction (GF) and clumping index (CI) play key roles in plant light interception, and therefore they have strong impacts on plant growth and canopy radiative transfer processes. Trees are usually assumed to be randomly distributed in natural forests in many previous studies. However, few studies have shown how trees are distributed in forest plantations and how these distribution patterns affect GF and CI in these forests. In this paper, a simple and general distance factor defined as relative allowable shortest distance between centers of two adjacent crowns divided by the mean diameter of the crowns (RASD) is proposed to describe quantitatively the degree of mutual exclusion among trees in forest plantations of various tree distribution patterns. A hypergeometric model is proposed instead of two previous stochastic tree distribution models (the Poisson model and Neyman-A model) to describe the topological relationship of trees and the influences of the exclusion distance on the GF and CI of the forest plantation canopies. The results show that: (1) the hypergeometric model is more suitable than the Poisson model and Neyman-A model for describing the topological relationship of trees in forest plantations; (2) the exclusion distance has strong impacts on GF and CI: there are significant differences between the results of the hypergeometric model and the Poisson model. Larger RASD causes lower GF and larger CI. The simulations are verified by field measurements in four forest plantation stands. Similarly, impacts of RASD on GF and CI are also found for other two crown shapes (prolate and oblate ellipsoids).

     

Antiresorptive Agents Increase the Effects of Exercise on Preventing Postmenopausal Bone Loss in Women: A Meta-Analysis

Background and Objectives

It remains unknown whether the combination of antiresorptive agents and exercise would generate additive effects on bone mineral density (BMD) in postmenopausal women, though their separate roles in preventing bone loss have been well established. This meta-analysis aimed to evaluate the combined impact of antiresorptive treatment and exercise on the lumbar spine and femoral neck BMD in postmenopausal women compared with an exercise-only intervention.

Methods

A systematic literature search of PubMed, EMBASE, SportDiscus and ProQuest up to Jun 2014 was conducted to identify the influence of antiresorptive agents and exercise on BMD in postmenopausal women. The study quality of the included trials was evaluated. The effect sizes were estimated by calculating the standardized mean difference (SMD). Subgroup analyses were conducted by pharmacological regimens and exercise categories.

Results

Nine studies with a total of 1,248 postmenopausal women met the inclusion criteria. The heterogeneity between the studies was evident at the spine (I² = 78.7%) and hip (I² = 41.7%) measurements; random-effects models were used in the data analysis. The pooled effect sizes associated with the combined interventions of antiresorptive agents and exercise were significant at the lumbar spine BMD (SMD = 0.511, 95% CI = 0.118-0.904, p = 0.011). Combining hormone replacement therapy (HRT) and exercise training generated greater beneficial effects on lumbar spine (SMD = 0.729, 95% CI = 0.186-1.273, p = 0.009) and femoral neck BMD (SMD = 0.220, 95% CI = 0.0110-429, p = 0.039) than the exercise-only intervention. Impact exercise was sensitive to antiresorptive agents in preventing postmenopausal bone loss both at the spine (SMD = 1.252, 95%CI = 0.465-2.039, p = 0.002) and hips (SMD = 0.414, 95%CI = 0.106-0.723, p = 0.008).

Conclusions

Our findings indicate that antiresorptive agents significantly increase the impact of exercise on the prevention of bone loss in postmenopausal women, which implies that the combination of antiresorptive agents and exercise may generate additive effects.     

A Genetic Variant in the Promoter Region of miR-106b-25 Cluster Predict Clinical Outcome of HBV-Related Hepatocellular Carcinoma in Chinese

Background

MiR-106b-25 cluster, hosted in intron 13 of MCM7, may play integral roles in diverse processes including immune response, tumorigenesis and progression. A single nucleotide polymorphism (SNP), rs999885, is located in the promoter region of MCM7. Our previous study showed that the A to G base change of rs999885 may provide an increased risk for HCC in HBV persistent carriers by altering the expression of the miR-106b-25 cluster. However, it is unknown whether rs999885 is associated with prognosis of intermediate or advanced HBV-related hepatocellular carcinoma (HCC) patients.

Methods

The SNP, rs999885, was genotyped by using the TaqMan allelic discrimination Assay in 414 intermediate or advanced HCC patients. Log-rank test and Cox proportional hazard models were used for survival analysis.

Results

The variant genotypes of rs999885 were associated with a significantly decreased risk of death for intermediate or advanced HCC [additive model: adjusted hazard ratio (HR)  = 0.76,95% confidence intervals (CI)  = 0.59–0.97]. Further stepwise regression analysis suggested that rs999885 was an independently protective factor for the prognosis of HCC in the final model (additive model: adjusted HR  = 0.72, 95% CI  = 0.56–0.91, P = 0.007).

Conclusions

These findings indicate that the A to G base change of rs999885 may provide a protective effect on the prognosis of intermediate or advanced HCC in Chinese.