Bayes Factor Value Research Articles

Comparação das distribuições Normal, Logística, Laplace e t de Student para o erro experimental na descrição bayesiana do acúmulo de matéria seca de Allium sativum

ABSTRACT: This study assessed distributions associated with Bayesian nonlinear modeling error in the description of total plant dry matteraccumulation (TDMA) of Allium sativumas a function of days after planting (DAP). According to the DIC criterion, Logistic and Gompertzmodels that use student’s t distribution error exhibited the highest DIC with logistic error distribution. In general, the difference of DIC in all the scenarios was not more than 5.The Bayes factor (BF) criterion showed no difference in the Logistic and Gompertzmodel fit when four distributions are used for the errors, where BF values do not exceed 2. Posterior distributions and the usual estimators of Logistic and Gompertz model parameters were similar even forvaried error distribution. In summary, there was no difference in the use of 4 distributions associated with the modeling error of garlic plant growth by the Bayes factor, whereby the results showed that alternating between error distributions significantly changes the number of Markov Chain Monte Carlo (MCMC) iterations.

Associations Among Wound-Related Factors Including Biofilm, Wound-Related Symptoms and Systemic Inflammation in Older Adults with Chronic Venous Leg Ulcers.

Objective: The purposes of this observational prospective study were to (1) characterize the wound-related factors (wound area, the presence of biofilm, and total bacteria), wound-related symptoms (fatigue, pain, exudate, itching, and edema or swelling), and systemic inflammation (level of serum C-reactive protein [CRP]), and (2) explore associations between wound-related factors, wound-related symptoms, and systemic inflammation in older individuals with chronic venous leg ulcers (CVLUs) over 8 weeks of wound treatment. Approach: A total of 117 participants who received standardized care (weekly sharp debridement) for chronic venous ulcer were enrolled. We collected clinical data every 2 weeks during the 8 weeks of the study period or until the wound was healed (if healed before 8 weeks). Associations among variables were estimated using a Bayesian approach applied to general linear mixed models. Results: Based on Bayes factor (BF) value, there was extremely strong evidence for the association of biofilm with mean total bacteria (BF >1,000). There was moderate evidence of a direct association between biofilm presence and levels of CRP (BF 4.3) and moderate evidence of direct associations between biofilm and wound-related symptoms, pain and exudate (BF 5.12, 8.49, respectively). Innovation: Wound-related symptoms and the level of systemic CRP were associated with biofilm among patients who were receiving weekly sharp debridement. Symptom severity associated with CVLUs requires assessment and management of wound-related factors and levels of inflammation in addition to symptom assessment. Conclusion: This study is the first to examine associations among biofilm, as wound-related factors, systemic inflammation, wound-related symptoms, and wound healing in clinical settings. Symptom severity, level of systemic CRP, and wound-related factors should be considered as well as assessment of biofilm in CVLU in older individuals with CVLU.

Abstract 3124: Identification of sub-clonal loss of heterozygosity (LOH) in glioblastomas analyzed with spatial transcriptomics

Abstract We propose a method to leverage spatial transcriptomics and bioinformatic analysis to identify sub-clonal loss of heterozygosity that could otherwise be missed by standard bulk sequencing in glioblastoma tumors. Glioblastomas are highly invasive and aggressive brain tumors with a low five-year survival rate of less than 10%. Current treatment strategies are not sufficient for long term disease outcome, and innovative approaches to analyze glioblastoma are imperative for future improved options. Many factors contribute to difficulty of treatment, though one critical consideration is the diffuse nature and known intratumoral heterogeneity of this cancer. It is important to determine LOH heterogeneity, as this genomic alteration is associated with copy number variation and specific classifications of gliomas. Loss of heterozygosity is an irreversible deletion of DNA that is a common alteration in cancer. Application of spatial transcriptomics can increase our understanding of genomic complexity across a tissue, and unsupervised graph clustering can computationally separate spatial regions with similar gene expression patterns. Our method investigates spatial clusters individually at known heterozygous SNP sites to identify evidence for LOH with Bayesian inference and a hidden Markov model. Our analysis centers on the balance of reference (A) and non-reference (B) spatial transcriptomics read counts at SNPs of interest. B allele frequency is the number of reads aligned to the alternative allele divided by the total number of reads counted at the SNP. At a normal two-copy state at a heterozygous site, B allele frequency is ideally 50 percent. LOH can be identified as this value deviates toward 0 or 100, and copy number alterations impact this frequency. Our method utilizes Bayes factor values, or likelihood ratios between two models, using allele counts to provide support for either LOH or a heterozygous event. For our analysis, spatial transcriptomics BAMs are processed with a graph clustering algorithm and split into cluster-specific BAMs. We calculate allele count coverage for each cluster at pre-selected heterozygous SNP positions identified through germline exome sequencing. Bayes factor values are then calculated at each SNP, resulting in evidence for LOH or a heterozygous event. Chromosomal regions are segmented by a hidden Markov approach. Cumulative metrics for each segment are evaluated to determine a “state” label of heterozygous, LOH, or undefined. We tested our method on three WHO grade 4 IDH wild-type EGFRvIII positive fresh frozen glioblastoma tissue samples. Sub-clonal heterogeneity was identified in two samples and confirmed by bulk exome sequencing, bulk RNA sequencing, and analysis of initial clinical reports. Citation Format: Michelle G. Webb, Frances Chow, Carmel McCullough, Bohan Zhang, Kyle Hurth, John Carpten, Gabriel Zada, David W. Craig. Identification of sub-clonal loss of heterozygosity (LOH) in glioblastomas analyzed with spatial transcriptomics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3124.

Detection of the Copy Number Variants of Genes in Patients with Familial Cardiac Diseases by Massively Parallel Sequencing.

The implication of copy number variations in familial heart disease is known, although in-depth knowledge is lacking; hence, more studies are needed to further our understanding. Massively parallel sequencing, thanks to its recent surge in use, is emerging as a valid tool for the detection of this type of variant, through the use of appropriate software. We conducted a study with 182 patients diagnosed with mendelian cardiovascular diseases who underwent sequencing using a cardiac gene panel and then a specific calling process for copy number variations (CNVs) with ExomeDepth software, which provides us with a Bayes factor (BF), a score of the probability that a CNV detected is true. After a rigorous CNV prioritization process, we confirmed the variants obtained by MLPA or SNP-based array, finding three real CNVs in five individuals in the MYH11, FBN1 and PDMI7 genes. The confirmed CNVs present in all cases BF values >60, thus establishing a threshold to consider real CNVs in the calling process carried out by ExomeDepth on our gene panel.

Bayesian Testing of Granger Causality in Functional Time Series

We develop a multivariate functional autoregressive model (MFAR), which captures the cross-correlation among multiple functional time series and thus improves forecast accuracy. We estimate the parameters under the Bayesian dynamic linear models (DLM) framework. In order to test for Granger causality from one FAR series to another we employ Bayes Factor. Motivated by the broad application of functional data in finance, we investigate the causality between the yield curves of USA and UK. Bayes factor values shows that no causal relation exists among the interest rates of these two countries. Furthermore, we illustrate a climatology example, suggesting that the meteorological factors Granger cause pollutant daily levels in Delhi. The Github repository https://www.Bayesian-Testing-Of-Granger-Causality-In-Functional-Time-Series contains the detailed study of simulation and real data applications.

Genome-Wide Interaction Study of Late-Onset Asthma With Seven Environmental Factors Using a Structured Linear Mixed Model in Europeans.

Asthma is among the most common chronic diseases worldwide, creating a substantial healthcare burden. In late-onset asthma, there are wide global differences in asthma prevalence and low genetic heritability. It has been suggested as evidence for genetic susceptibility to asthma triggered by exposure to multiple environmental factors. Very few genome-wide interaction studies have identified gene-environment (G×E) interaction loci for asthma in adults. We evaluated genetic loci for late-onset asthma showing G×E interactions with multiple environmental factors, including alcohol intake, body mass index, insomnia, physical activity, mental status, sedentary behavior, and socioeconomic status. In gene-by-single environment interactions, we found no genome-wide significant single-nucleotide polymorphisms. However, in the gene-by-multi-environment interaction study, we identified three novel and genome-wide significant single-nucleotide polymorphisms: rs117996675, rs345749, and rs17704680. Bayes factor analysis suggested that for rs117996675 and rs17704680, body mass index is the most relevant environmental factor; for rs345749, insomnia and alcohol intake frequency are the most relevant factors in the G×E interactions of late-onset asthma. Functional annotations implicate the role of these three novel loci in regulating the immune system. In addition, the annotation for rs117996675 supports the body mass index as the most relevant environmental factor, as evidenced by the Bayes factor value. Our findings help to understand the role of the immune system in asthma and the role of environmental factors in late-onset asthma through G×E interactions. Ultimately, the enhanced understanding of asthma would contribute to better precision treatment depending on personal genetic and environmental information.

Identification of genetic loci affecting body mass index through interaction with multiple environmental factors using structured linear mixed model

Multiple environmental factors could interact with a single genetic factor to affect disease phenotypes. We used Struct-LMM to identify genetic variants that interacted with environmental factors related to body mass index (BMI) using data from the Korea Association Resource. The following factors were investigated: alcohol consumption, education, physical activity metabolic equivalent of task (PAMET), income, total calorie intake, protein intake, carbohydrate intake, and smoking status. Initial analysis identified 7 potential single nucleotide polymorphisms (SNPs) that interacted with the environmental factors (P value < 5.00 × 10−6). Of the 8 environmental factors, PAMET score was excluded for further analysis since it had an average Bayes Factor (BF) value < 1 (BF = 0.88). Interaction analysis using 7 environmental factors identified 11 SNPs (P value < 5.00 × 10−6). Of these, rs2391331 had the most significant interaction (P value = 7.27 × 10−9) and was located within the intron of EFNB2 (Chr 13). In addition, the gene-based genome-wide association study verified EFNB2 gene significantly interacting with 7 environmental factors (P value = 5.03 × 10−10). BF analysis indicated that most environmental factors, except carbohydrate intake, contributed to the interaction of rs2391331 on BMI. Although the replication of the results in other cohorts is warranted, these findings proved the usefulness of Struct-LMM to identify the gene–environment interaction affecting disease.

Phylogeographic analysis of H5N1 highly pathogenic avian influenza virus isolated in Cambodia from 2018 to 2019.

Since 2004, several outbreaks of highly pathogenic avian influenza (HPAI) have been reported in Cambodia. Until 2013, all H5N1 viruses identified in Cambodia belonged to clade 1 and its subclades. H5N1 HPAI viruses belonging to clade 2.3.2.1c have been dominant since the beginning of 2014, with various genotypes (KH1-KH5) reported. Here, we isolated nine H5N1 HPAI viruses from domestic poultry farms and slaughterhouses in Cambodia during 2018-2019 and performed phylogenetic analysis of whole genome sequences. All isolates were classified as H5 clade 2.3.2.1c viruses and all harbored multi-basic amino acid sequences (PQRERRRKR/GLF) at the haemagglutinin (HA) cleavage site. Phylogenetic analysis revealed that the H5N1 isolates in this study belonged to the KH2 genotype, the dominant genotype in Cambodia in 2015. Phylogenetic analysis of the HA gene showed that the isolates were divided into two groups (A and B). The results of Bayesian discrete phylogeography analysis revealed that the viral migration pathways from Vietnam to Cambodia (Bayes factor value: 734,039.01; posterior probability: 1.00) and from Cambodia to Vietnam (Bayes factor value: 26,199.95; posterior probability: 1.00) were supported by high statistical values. These well-supported viral migrations between Vietnam and Cambodia demonstrate that viral transmission continued in both directions. Several factors may have contributed to this, including the free-grazing duck system and movement of poultry-related products. Thus, the results emphasize the need for an enhanced international surveillance program to better understand transboundary infection and evolution of H5N1 HPAI viruses, along with implementation of more stringent international trade controls on poultry and poultry products.

The Use of the Bayes Factor for Identification of Culex pipiens and C. torrentium (Diptera: Culicidae) Based on Morphometric Wing Characters

The probabilistic approach was applied to morphometric identification of Culex pipiens pipiens / torrentium mosquito females collected in the Sablino caves (Leningrad Province of Russia). The distances between landmarks of the radial wing veins r(2+3) and r3 were measured, and the frequency distribution of the r(2+3) / r3 wing vein index was analyzed. The obtained distribution had two maxima coinciding with the distribution maxima obtained earlier by other authors for the German populations of Culex pipiens pipiens and C. torrentium. Most specimens in the sample from the Sablino caves grouped at the maximum of the Culex pipiens normal distribution. We propose to use the Bayes factor (BF) to select those mosquito females which most likely belong to C. p. pipiens. In the sample studied, the BF value was greater than 10 for 72.5% of the specimens, which was interpreted as strong or very strong evidence in favor of C. p. pipiens. For 16.5% of individuals the BF value was greater than 0.1 and smaller than 10, providing moderate or weak evidence in favor of one of the two species. Overall, 11% of the females had BF values smaller than 0.1, this being strong or very strong evidence in favor of C. torrentium. To increase the reliability of C. p. pipiens selection, the specimens with the highest BF values should be chosen.

Bayesian Methods in the Field of Rehabilitation.

Bayesian techniques, as an alternative method of statistical analysis in rehabilitation studies, have some advantages such as handling small sample sizes, allowing incorporation of previous experience of the researchers or clinicians, being suitable for different kinds of studies, and managing highly complex models. These characteristics are important in rehabilitation research. In the present article, the Bayesian approach is displayed through three examples in previously analyzed data with traditional or frequentist methods. The studies used as examples have small sample sizes and show that the Bayesian procedures enhance the statistical information of the results. The Bayesian credibility interval includes the true value of the corresponding parameter diminishing uncertainty about the treatment effect. In addition, the Bayes factor value quantifies the evidence provided by the data in favor of the alternative hypothesis as opposed to the null hypothesis. Bayesian inference could be an interesting and adaptable alternative statistical method for physical medicine and rehabilitation applications.

Early and late cortical reactivity to passively viewed emotional faces in pediatric bipolar disorder

BackgroundWe studied emotional information processing in youth with pediatric bipolar disorder (pBD) using the late positive potential (LPP), assessing automatic allocation of attentional resources to emotionally salient stimuli, and the occipital P1, assessing early sensory processing. MethodsParticipants were 20 youth with pBD and 26 healthy controls (HC). Participants passively viewed faces with a fearful, neutral or happy expressions. Group differences were tested with general linear models. P1 was included to examine modulating effects on LPP. We calculated Bayes factor (BF) values to express strength of evidence for choosing one hypothesis over another. ResultsA significant emotion by group interaction for LPP amplitude was associated with a larger amplitude for happy faces for pBD than HC (F[1,40] = 6.04, p = .018); this was not modulated by P1 amplitude or latency. P1 amplitude did not differ between groups, although P1 peaked earlier for HC (F[1,40] = 5.45, p = .025). BF for LPP was 2.93, suggesting moderate evidence favoring H1. BF for P1 latency of 14.58 suggests strong evidence favoring H1. LimitationsInclusion of children and adolescents prohibited careful control for neurodevelopmental effects. ConclusionsLarger LPP amplitude for happy faces without change in P1 suggests enhanced automatic allocation of attentional resources to positive information in pBD. Delayed P1 latency in pBD suggests slower early processing of emotional information.

Bioelectrical impedance analysis in patients with Alzheimer's disease

We studied emotional information processing in youth with pediatric bipolar disorder (pBD) using the late positive potential (LPP), assessing automatic allocation of attentional resources to emotionally salient stimuli, and the occipital P1, assessing early sensory processing.Participants were 20 youth with pBD and 26 healthy controls (HC). Participants passively viewed faces with a fearful, neutral or happy expressions. Group differences were tested with general linear models. P1 was included to examine modulating effects on LPP. We calculated Bayes factor (BF) values to express strength of evidence for choosing one hypothesis over another.A significant emotion by group interaction for LPP amplitude was associated with a larger amplitude for happy faces for pBD than HC (F[1,40] = 6.04, p = .018); this was not modulated by P1 amplitude or latency. P1 amplitude did not differ between groups, although P1 peaked earlier for HC (F[1,40] = 5.45, p = .025). BF for LPP was 2.93, suggesting moderate evidence favoring H1. BF for P1 latency of 14.58 suggests strong evidence favoring H1.Inclusion of children and adolescents prohibited careful control for neurodevelopmental effects.Larger LPP amplitude for happy faces without change in P1 suggests enhanced automatic allocation of attentional resources to positive information in pBD. Delayed P1 latency in pBD suggests slower early processing of emotional information.

Taxonomy ofCladonia angustilobaand related species

AbstractThe lichen speciesCladonia angustilobais characterized by a well-developed primary thallus and narrow squamules which show deep incisions, and the presence of usnic and fumarprotocetraric acids. Morphologically it is similar toC. foliaceaandC. convoluta, from which it can be distiguished by the squamule size and morphology. Since similar characters were used to distinguishC. foliaceafromC. convolutawhich do not represent different lineages, it is necessary to examine the taxonomic status ofC. angustilobaby means of DNA sequences. In this study, the species delimitation within theC. foliaceacomplex was studied by sequencing three loci, ITS rDNA,cox1andRPB2. The data were analyzed by means of phylogenetic and species delimitation methods (GMYC, PTP, ABGD and BPP). Our results show that none of the three species is monophyletic. Most of the species delimitation methods did not support the current species as evolutionary lineages. Only some of the BPP analyses supportedC. angustilobaas a species distinct fromC. foliaceaandC. convoluta. However, the hypothesis that considers theC. foliaceacomplex as constituted by a unique species obtained the best Bayes Factor value. Therefore,C. angustilobaandC. convolutaare synonymized withC. foliacea.A new, thoroughly checked synonymy with typifications of the wholeC. foliaceacomplex is presented. An updated survey of the world distribution data is compiled.

Decision qualities of Bayes factor and p value-based hypothesis testing.

The purpose of this article is to investigate the decision qualities of the Bayes factor (BF) method compared with the p value-based null hypothesis significance testing (NHST). The performance of the 2 methods is assessed in terms of the false- and true-positive rates, as well as the false-discovery rates and the posterior probabilities of the null hypothesis for 2 different models: an independent-samples t test and an analysis of variance (ANOVA) model with 2 random factors. Our simulation study results showed the following: (a) The common BF > 3 criterion is more conservative than the NHST α = .05 criterion, and it corresponds better with the α = .01 criterion. (b) An increasing sample size has a different effect on the false-positive rate and the false-discovery rate, depending on whether the BF or NHST approach is used. (c) When effect sizes are randomly sampled from the prior, power curves tend to be flat compared with when effect sizes are prespecified. (d) The larger the scale factor (or the wider the prior), the more conservative the inferential decision is. (e) The false-positive and true-positive rates of the BF method are very sensitive to the scale factor when the effect size is small. (f) While the posterior probabilities of the null hypothesis ideally follow from the BF value, they can be surprisingly high using NHST. In general, these findings were consistent independent of which of the 2 different models was used. (PsycINFO Database Record

Parâmetros e ganhos genéticos em características de crescimento de bovinos Tabapuã da Bahia

RESUMO Compararam-se dois modelos (com ou sem o efeito materno) na estimativa de parâmetros genéticos por meio do fator de Bayes (FB) e do critério de informação da deviance (DIC). Adicionalmente, avaliaram-se as tendências genéticas, maternas e fenotípicas em características de crescimento de bovinos da raça Tabapuã do estado da Bahia. O modelo que incluiu o efeito materno proporcionou menores valores de FB (167629,2; 117341,2 e 124804,8) e DIC (174550,0; 120242,7 e 128037,2) para pesos aos 205 (P205), 365 (P365) e 550 (P550) dias de idade, respectivamente. As estimativas médias, a posteriori, das herdabilidades diretas e maternas foram 0,33; 0,43 e 0,44 e 0,15; 0,14 e 0,16 para as três características, respectivamente. As tendências genéticas para o efeito direto foram de 0,4415 e 0,3613kg/ano para P205 e P365 e representam incrementos de apenas 0,25 e 0,15% nas médias das características ao ano. As tendências genéticas maternas para as três características demonstraram perdas e indicam ausência de seleção de matrizes para boa habilidade materna. Apesar de existir variabilidade genética suficiente para justificar ganhos genéticos via seleção, estes e os ganhos fenotípicos foram pequenos, sugerindo necessidade de melhorias genéticas e ambientais.

Detection of quantitative trait loci for maternal traits using high-density genotypes of Blonde d'Aquitaine beef cattle.

BackgroundThe genetic determinism of the calving and suckling performance of beef cows is little known whereas these maternal traits are of major economic importance in beef cattle production systems. This paper aims to identify QTL regions and candidate genes that affect maternal performance traits in the Blonde d’Aquitaine breed. Three calving performance traits were studied: the maternal effect on calving score from field data, the calving score and pelvic opening recorded in station for primiparous cows. Three other traits related to suckling performance were also analysed: the maternal effect on weaning weight from field data, milk yield and the udder swelling score recorded in station for primiparous cows. A total of 2,505 animals were genotyped from various chip densities and imputed in high density chips for 706,791 SNP. The number of genotyped animals with phenotypes ranged from 1,151 to 2,284, depending on the trait considered.ResultsQTL detections were performed using a Bayes C approach. Evidence for a QTL was based on Bayes Factor values. Putative candidate genes were proposed for the QTL with major evidence for one of the six traits and for the QTL shared by at least two of the three traits underlying either calving or suckling performance. Nine candidate genes were proposed for calving performance among the nine highlighted QTL regions. The neuroregulin gene on chromosome 27 was notably identified as a very likely candidate gene for maternal calving performance. As for suckling abilities, seven candidate genes were identified among the 15 highlighted QTL. In particular, the Group-Specific Component gene on chromosome 6, which encodes vitamin D binding protein, is likely to have a major effect on maternal weaning weight in the Blonde d’Aquitaine breed. This gene had already been linked to milk production and clinical mastitis in dairy cattle.ConclusionIn the near future, these QTL findings and the preliminary proposals of candidate genes which act on the maternal performance of beef cows should help to identify putative causal mutations based on sequence data from different cattle breeds.Electronic supplementary materialThe online version of this article (doi:10.1186/s12863-016-0397-y) contains supplementary material, which is available to authorized users.

Spatio-Temporal History of HIV-1 CRF35_AD in Afghanistan and Iran.

HIV-1 Circulating Recombinant Form 35_AD (CRF35_AD) has an important position in the epidemiological profile of Afghanistan and Iran. Despite the presence of this clade in Afghanistan and Iran for over a decade, our understanding of its origin and dissemination patterns is limited. In this study, we performed a Bayesian phylogeographic analysis to reconstruct the spatio-temporal dispersion pattern of this clade using eligible CRF35_AD gag and pol sequences available in the Los Alamos HIV database (432 sequences available from Iran, 16 sequences available from Afghanistan, and a single CRF35_AD-like pol sequence available from USA). Bayesian Markov Chain Monte Carlo algorithm was implemented in BEAST v1.8.1. Between-country dispersion rates were tested with Bayesian stochastic search variable selection method and were considered significant where Bayes factor values were greater than three. The findings suggested that CRF35_AD sequences were genetically similar to parental sequences from Kenya and Uganda, and to a set of subtype A1 sequences available from Afghan refugees living in Pakistan. Our results also showed that across all phylogenies, Afghan and Iranian CRF35_AD sequences formed a monophyletic cluster (posterior clade credibility> 0.7). The divergence date of this cluster was estimated to be between 1990 and 1992. Within this cluster, a bidirectional dispersion of the virus was observed across Afghanistan and Iran. We could not clearly identify if Afghanistan or Iran first established or received this epidemic, as the root location of this cluster could not be robustly estimated. Three CRF35_AD sequences from Afghan refugees living in Pakistan nested among Afghan and Iranian CRF35_AD branches. However, the CRF35_AD-like sequence available from USA diverged independently from Kenyan subtype A1 sequences, suggesting it not to be a true CRF35_AD lineage. Potential factors contributing to viral exchange between Afghanistan and Iran could be injection drug networks and mass migration of Afghan refugees and labours to Iran, which calls for extensive preventive efforts.

Chronic widespread pain after motor vehicle collision typically occurs through immediate development and nonrecovery: results of an emergency department-based cohort study.

Motor vehicle collision (MVC) can trigger chronic widespread pain (CWP) development in vulnerable individuals. Whether such CWP typically develops through the evolution of pain from regional to widespread or through the early development of widespread pain with nonrecovery is currently unknown. We evaluated the trajectory of CWP development (American College of Rheumatology criteria) among 948 European-American individuals who presented to the emergency department (ED) for care in the early aftermath of MVC. Pain extent was assessed in the ED and 6 weeks, 6 months, and 1 year after MVC on 100%, 91%, 89%, and 91% of participants, respectively. Individuals who reported prior CWP at the time of ED evaluation (n = 53) were excluded. Trajectory modeling identified a 2-group solution as optimal, with the Bayes Factor value (138) indicating strong model selection. Linear solution plots supported a nonrecovery model. Although the number of body regions with pain in the non-CWP group steadily declined, the number of body regions with pain in the CWP trajectory group (192/895, 22%) remained relatively constant over time. These data support the hypothesis that individuals who develop CWP after MVC develop widespread pain in the early aftermath of MVC, which does not remit.

Association mapping of oil content and fatty acid components in soybean

Soybean is a globally important oil crop, and the flavour, stability and nutritional value of soybean oil is dependent on the relative proportions of five primary fatty acids. In this study, association mapping was performed to identify molecular markers associated with QTL regions related to oil traits in soybean. Oil and fatty acid contents were measured in soybean accessions grown under field conditions for 2 years. Based on polymorphisms at 142 SSR loci, 94 soybean accessions were divided into two clusters corresponding to accessions from Asian and American gene pools. Linkage disequilibrium (LD) among the SSR loci suggested a structure across the soybean genome (LD decay) of approximately 12 cM. Pairwise kinship estimates among the accessions showed low values. A mixed linear model (MLM) adjusted using false discovery rate (FDR) and minimum Bayes factor (BFmin) values identified 110 strongly associated marker-traits. Oleic acid content had the highest number of associated SSR loci (33), followed by linoleic acid (26), palmitic acid (24), oil (16) and linolenic acid (14). Specific alleles at eight loci yielded high performing soybeans with respect to fatty acid content, and these are presented in a crossing matrix. Analysis of SSR loci and oil traits confirmed previous findings, and many new markers were also identified that may be useful for quickly improving oil traits in soybean.

Identifying Emerging Customer Requirements in an Early Design Stage by Applying Bayes Factor-Based Sequential Analysis

Rapid changes of new technologies, market dynamics, and swift fluctuation of customer tastes acerbate the needs for companies to identifying the emerging customer requirements and incorporate them in the conceptual design stage. Discovering emerging customer needs has great potential to create new product opportunities for the success of business. However, identifying customers' requirements in an early design stage has not been well addressed in the traditional design methodology. Because emerging needs are usually not obvious at the budding stage, the related observations are rare in dataset. Traditional methods fall short of providing enough support of eliciting the below-the-radar needs. This paper reports a new approach to identify emerging customer needs in the growing popular online interactive environment with customer participation. The Bayes factor, a methodology to quantify the occurrence possibility of a certain event, is used to calculate the likelihood that current offering cannot meet the customer's requirements whenever a new specification is incorporated. With the sequential input from customers, a series of the Bayes factor value can then be calculated as the weight of evidence that emerging customer needs appear. We show that the decreased value will be the potentially emerging needs which cannot be satisfied by the current product family. Numerical and analytical results are derived to demonstrate the viability and effectiveness of the proposed approach.