Genomic regions, candidate genes, and pleiotropic variants associated with physiological and anatomical indicators of heat stress response in lactating sows.

BACKGROUND: Heat stress (HS) poses significant threats to the sustainability of livestock production. Genetically improving heat tolerance could enhance animal welfare and minimize production losses during HS events. Measuring phenotypic indicators of HS response and understanding their genetic background are crucial steps to optimize breeding schemes for improved climatic resilience. The identification of genomic regions and candidate genes influencing the traits of interest, including variants with pleiotropic effects, enables the refinement of genotyping panels used to perform genomic prediction of breeding values and contributes to unraveling the biological mechanisms influencing heat stress response. Therefore, the main objectives of this study were to identify genomic regions, candidate genes, and potential pleiotropic variants significantly associated with indicators of HS response in lactating sows using imputed whole-genome sequence (WGS) data. Phenotypic records for 18 traits and genomic information from 1,645 lactating sows were available for the study. The genotypes from the PorcineSNP50K panel containing 50,703 single nucleotide polymorphisms (SNPs) were imputed to WGS and after quality control, 1,622 animals and 7,065,922 SNPs were included in the analyses. RESULTS: A total of 1,388 unique SNPs located on sixteen chromosomes were found to be associated with 11 traits. Twenty gene ontology terms and 11 biological pathways were shown to be associated with variability in ear skin temperature, shoulder skin temperature, rump skin temperature, tail skin temperature, respiration rate, panting score, vaginal temperature automatically measured every 10 min, vaginal temperature measured at 0800 h, hair density score, body condition score, and ear area. Seven, five, six, two, seven, 15, and 14 genes with potential pleiotropic effects were identified for indicators of skin temperature, vaginal temperature, animal temperature, respiration rate, thermoregulatory traits, anatomical traits, and all traits, respectively. CONCLUSIONS: Physiological and anatomical indicators of HS response in lactating sows are heritable but highly polygenic. The candidate genes found are associated with important gene ontology terms and biological pathways related to heat shock protein activities, immune response, and cellular oxidative stress. Many of the candidate genes with pleiotropic effects are involved in catalytic activities to reduce cell damage from oxidative stress and cellular mechanisms related to immune response.

Trends in mortality risk of patients with congenital heart disease during the COVID-19 pandemic.

BACKGROUND: Cardiovascular conditions are considered risk factors for poor outcomes associated with COVID-19. However, the effect of the COVID-19 pandemic on the mortality of patients with congenital heart disease (CHD) is unclear. Our study aims to examine the trends in mortality risk of CHD patients during the COVID-19 pandemic. METHODS: This is a retrospective cohort study from the Pediatric Cardiac Care Consortium, a US-based registry of interventions for CHD. We included patients having US residence and direct identifiers; death events were captured by matching with the National Death Index. The observation window (2017-2022) was divided into pre-COVID-19 and COVID-19 era defined around the national onset of COVID-19 disease in 2020. Stratified Cox model was used to assess all-cause mortality between the pre- and the COVID-19 era. RESULTS: Among 45,130 patients with CHD (median age in 2017: 23.3 years, IQR: 19.0-28.4), 503 deaths occurred during the pandemic with 44 deaths (8.7%) attributed to COVID-19 (COVID-19 mortality rate of 0.09%). The overall risk of death for patients with all types of CHD during the pandemic was significantly higher compared to the pre-COVID-19 era (aHR 1.28, 95%CI: 1.08-1.53), with a differential trend towards increased risk in patients with two-ventricle (aHR 1.44, 95% CI: 1.19-1.76) vs unchanged risk for those with single ventricle CHD (aHR = 0.83, 95% CI: 0.57-1.21). Adjusted subgroup analysis revealed a higher risk of death during the pandemic for CHD patients with male and chromosomal abnormalities. The excess deaths during the pandemic were attributed to COVID-19 itself rather than CHD or cardiovascular conditions. CONCLUSION: In this large CHD cohort study, there was a higher risk of death among CHD patients with male and chromosomal abnormalities. A differential trend towards higher risk for those with two vs. unchanged risk for single ventricle CHD was presented. The excess mortality was attributed to the COVID-19 itself and not to conditions potentially related to deferral of care. These results justify targeted protective measures towards the CHD population and may provide guidance for public health and medical care response in future epidemics.

Association of patient-level characteristics with long-term outcomes after Fontan palliation: Rationale, design, and baseline characteristics of the Pediatric Cardiac Care Consortium Fontan cohort study.

BACKGROUND: The Fontan operation is used to palliate single ventricle congenital heart defects (CHD) but poses significant morbidity and mortality risks. We present the design, planned analyses, and rationale for a long-term Fontan cohort study aiming to examine the association of patient characteristics at the time of Fontan with post-Fontan morbidity and mortality. METHODS AND RESULTS: We used the Pediatric Cardiac Care Consortium (PCCC), a US-based, multicenter registry of pediatric cardiac surgeries to identify patients who underwent the Fontan procedure for single ventricle CHD between 1 and 21 years of age. The primary outcomes are in-hospital Fontan failure (death or takedown) and post-discharge mortality through 2022. A total of 1461 (males 62.1%) patients met eligibility criteria and were included in the analytical cohort. The median age at Fontan evaluation was 3.1 years (IQR: 2.4-4.3). While 95 patients experienced in-hospital Fontan failure (78 deaths and 17 Fontan takedown), 1366 (93.5%) survived to discharge with Fontan physiology and formed the long-term analysis cohort. Over a median follow-up of 21.2 years (IQR: 18.4-24.5) 184 post-discharge deaths occurred. Thirty-year post Fontan survival was 75.0% (95% CI: 72.3%-77.8%) for all Fontan types with higher rates for current techniques such as lateral tunnel and extracardiac conduit 77.1% (95% CI: 73.5-80.8). CONCLUSION: The PCCC Fontan study aims to identify predictors for post-Fontan morbidity and mortality, enabling risk- stratification and informing surveillance practices. Additionally, the study may guide therapeutic interventions aiming to optimize hemodynamics and enhance Fontan longevity for individual patients.

Genetic parameters for novel climatic resilience indicators derived from automatically-recorded vaginal temperature in lactating sows under heat stress conditions.

BACKGROUND: Longitudinal records of automatically-recorded vaginal temperature (TV) could be a key source of data for deriving novel indicators of climatic resilience (CR) for breeding more resilient pigs, especially during lactation when sows are at an increased risk of suffering from heat stress (HS). Therefore, we derived 15 CR indicators based on the variability in TV in lactating sows and estimated their genetic parameters. We also investigated their genetic relationship with sows' key reproductive traits. RESULTS: The heritability estimates of the CR traits ranged from 0.000 ± 0.000 for slope for decreased rate of TV (SlopeDe) to 0.291 ± 0.047 for sum of TV values below the HS threshold (HSUB). Moderate to high genetic correlations (from 0.508 ± 0.056 to 0.998 ± 0.137) and Spearman rank correlations (from 0.431 to 1.000) between genomic estimated breeding values (GEBV) were observed for five CR indicators, i.e. HS duration (HSD), the normalized median multiplied by normalized variance (Nor_medvar), the highest TV value of each measurement day for each individual (MaxTv), and the sum of the TV values above (HSUA) and below (HSUB) the HS threshold. These five CR indicators were lowly to moderately genetically correlated with shoulder skin surface temperature (from 0.139 ± 0.008 to 0.478 ± 0.048) and respiration rate (from 0.079 ± 0.011 to 0.502 ± 0.098). The genetic correlations between these five selected CR indicators and sow reproductive performance traits ranged from - 0.733 to - 0.175 for total number of piglets born alive, from - 0.733 to - 0.175 for total number of piglets born, and from - 0.434 to - 0.169 for number of pigs weaned. The individuals with the highest GEBV (most climate-sensitive) had higher mean skin surface temperature, respiration rate (RR), panting score (PS), and hair density, but had lower mean body condition scores compared to those with the lowest GEBV (most climate-resilient). CONCLUSIONS: Most of the CR indicators evaluated are heritable with substantial additive genetic variance. Five of them, i.e. HSD, MaxTv, HSUA, HSUB, and Nor_medvar share similar underlying genetic mechanisms. In addition, individuals with higher CR indicators are more likely to exhibit better HS-related physiological responses, higher body condition scores, and improved reproductive performance under hot conditions. These findings highlight the potential benefits of genetically selecting more heat-tolerant individuals based on CR indicators.

Genomic predictions and GWAS for heat tolerance in pigs based on reaction norm models with performance records and data from public weather stations considering alternative temperature thresholds.

Genetic improvement of livestock productivity has resulted in greater production of metabolic heat and potentially greater susceptibility to heat stress. Various studies have demonstrated that there is genetic variability for heat tolerance and genetic selection for more heat tolerant individuals is possible. The rate of genetic progress tends to be greater when genomic information is incorporated into the analyses as more accurate breeding values can be obtained for young individuals. Therefore, this study aimed (1) to evaluate the predictive ability of genomic breeding values for heat tolerance based on routinely recorded traits, and (2) to investigate the genetic background of heat tolerance based on single-step genome-wide association studies for economically important traits related to body composition, growth and reproduction in Large White pigs. Pedigree information was available for 265,943 animals and genotypes for 8686 animals. The studied traits included ultrasound backfat thickness (BFT), ultrasound muscle depth (MDP), piglet weaning weight (WW), off-test weight (OTW), interval between farrowing (IBF), total number of piglets born (TNB), number of piglets born alive (NBA), number of piglets born dead (NBD), number of piglets weaned (WN) and weaning-to-estrus interval (IWE). The number of phenotypic records ranged from 6059 (WN) to 172,984 (TNB). Single-step genomic reaction norm predictions were used to calculate the genomic estimated breeding values for each individual. Predictions of breeding values for the validation population individuals were compared between datasets containing phenotypic records measured in the whole range of temperatures (WR) and datasets containing only phenotypic records measured when the weather station temperature was above 10°C (10C) or 15°C (15C), to evaluate the usefulness of these datasets that may better reflect the within-barn temperature. The use of homogeneous or heterogeneous residual variance was found to be trait-dependent, where homogeneous variance presented the best fit for MDP, BFT, OTW, TNB, NBA, WN and IBF, while the other traits (WW and IWE) had better fit with heterogeneous variance. The average prediction accuracy, dispersion and bias values considering all traits for WR were 0.36 ± 0.05, -0.07 ± 0.13 and 0.76 ± 0.10, respectively; for 10C were 0.39 ± 0.02, -0.05 ± 0.07 and 0.81 ± 0.05, respectively; and for 15C were 0.32 ± 0.05, -0.05 ± 0.11 and 0.84 ± 0.10, respectively. Based on the studied traits, using phenotypic records collected when the outside temperature (from public weather stations) was above 10°C provided better predictions for most of the traits. Forty-three and 62 candidate genomic regions were associated with the intercept (overall performance level) and slope term (specific biological mechanisms related to environmental sensitivity), respectively. Our results contribute to improve genomic predictions using existing datasets and better understand the genetic background of heat tolerance in pigs. Furthermore, the genomic regions and candidate genes identified will contribute to future genomic studies and breeding applications.

I s pelvic support osteotomy (PSO) suitable for ordinary high-riding hip dysplasia?

PURPOSE: Pelvic support osteotomy (PSO) is regarded to provide pelvic stability and improve abductor function to delay or even avoid total hip arthroplasty (THA) in young patients with high-riding hip dysplasia. However, some of these patients eventually have to undergo THA. Because of the double-angulation deformity of the femur after PSO, subsequent THA is challenging. This study aimed to analyze whether PSO surgery is suitable for high-riding hip dysplasia and summarize orthopaedic strategy during THA for patients with previous PSO. METHODS: This case-control study included eight cases of THA for high-riding hip dysplasia patients with previous PSO (study group) and 24 cases of high-riding hip dysplasia patients without any hip surgical therapy (control group) by a 1:3 match (from May 2018 to January 2022). We compared demographics and joint function before and after THA between two groups and recorded all patients' preoperative imaging data, surgical procedures, postoperative imaging data, and complications. The surgical techniques for patients with previous PSO were highlighted. RESULTS: There was no statistical difference between the two groups in demographic (p > 0.05). The study group had worse hip Harris score (HHS), range of motion (ROM), visual analogue scale (VAS), and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) (p < 0.05) compared with the control group before THA. All patients had concurrent THA and osteotomy at the proximal femur, but the study group experienced longer operation time (p = 0.047) with more blood loss (p = 0.027) and higher complication rate compared with the control group (p = 0.009). At the last follow-up, the study group's HHS, ROM, VAS, and WOMAC were still worse than those in the control group. CONCLUSIONS: PSO did not improve the joint function of high-riding hip dysplasia patients but brought challenges to subsequent THA and affected the surgical outcomes. In short, we suggested that PSO is unsuitable for routine high-riding hip dysplasia patients.

Covariate adjustment in continuous biomarker assessment.

Continuous biomarkers are common for disease screening and diagnosis. To reach a dichotomous clinical decision, a threshold would be imposed to distinguish subjects with disease from nondiseased individuals. Among various performance metrics, specificity at a controlled sensitivity level (or vice versa) is often desirable because it directly targets the clinical utility of the intended clinical test. Meanwhile, covariates, such as age, race, as well as sample collection conditions, could impact the biomarker distribution and may also confound the association between biomarker and disease status. Therefore, covariate adjustment is important in such biomarker evaluation. Most existing covariate adjustment methods do not specifically target the desired sensitivity/specificity level, but rather do so for the entire biomarker distribution. As such, they might be more prone to model misspecification. In this paper, we suggest a parsimonious quantile regression model for the diseased population, only locally at the controlled sensitivity level, and assess specificity with covariate-specific control of the sensitivity. Variance estimates are obtained from a sample-based approach and bootstrap. Furthermore, our proposed local model extends readily to a global one for covariate adjustment for the receiver operating characteristic (ROC) curve over the sensitivity continuum. We demonstrate computational efficiency of this proposed method and restore the inherent monotonicity in the estimated covariate-adjusted ROC curve. The asymptotic properties of the proposed estimators are established. Simulation studies show favorable performance of the proposal. Finally, we illustrate our method in biomarker evaluation for aggressive prostate cancer.

Covariate-specific evaluation of continuous biomarker.

Diagnostic tests usually need to operate at a high sensitivity or specificity level in practice. Accordingly, specificity at the controlled sensitivity, or vice versa, is a clinically sensible performance metric for evaluating continuous biomarkers. Meanwhile, the performance of a biomarker may vary across sub-populations as defined by covariates, and covariate-specific evaluation can be informative. In this article, we develop a novel modeling and estimation method for covariate-specific specificity at a controlled sensitivity level. Unlike existing methods which typically adopt elaborate models of covariate effects over the entire biomarker distribution, our approach models covariate effects locally at a specific sensitivity level of interest. We also extend our proposed model to handle the whole continuum of sensitivities via dynamic regression and derive covariate-specific ROC curves. We provide the variance estimation through bootstrapping. The asymptotic properties are established. We conduct extensive simulation studies to evaluate the performance of our proposed methods in comparison with existing methods, and further illustrate the applications in two clinical studies for aggressive prostate cancer.

Genetic parameters for automatically-measured vaginal temperature, respiration efficiency, and other thermotolerance indicators measured on lactating sows under heat stress conditions.

BACKGROUND: Genetic selection based on direct indicators of heat stress could capture additional mechanisms that are involved in heat stress response and enable more accurate selection for more heat-tolerant individuals. Therefore, the main objectives of this study were to estimate genetic parameters for various heat stress indicators in a commercial population of Landrace × Large White lactating sows measured under heat stress conditions. The main indicators evaluated were: skin surface temperatures (SST), automatically-recorded vaginal temperature (TV), respiration rate (RR), panting score (PS), body condition score (BCS), hair density (HD), body size (BS), ear size, and respiration efficiency (Reff). RESULTS: Traits based on TV presented moderate heritability estimates, ranging from 0.15 ± 0.02 to 0.29 ± 0.05. Low heritability estimates were found for SST traits (from 0.04 ± 0.01 to 0.06 ± 0.01), RR (0.06 ± 0.01), PS (0.05 0.01), and Reff (0.03 ± 0.01). Moderate to high heritability values were estimated for BCS (0.29 ± 0.04 for caliper measurements and 0.25 ± 0.04 for visual assessments), HD (0.25 ± 0.05), BS (0.33 ± 0.05), ear area (EA; 0.40 ± 0.09), and ear length (EL; 0.32 ± 0.07). High genetic correlations were estimated among SST traits (> 0.78) and among TV traits (> 0.75). Similarly, high genetic correlations were also estimated for RR with PS (0.87 ± 0.02), with BCS measures (0.92 ± 0.04), and with ear measures (0.95 ± 0.03). Low to moderate positive genetic correlations were estimated between SST and TV (from 0.25 ± 0.04 to 0.76 ± 0.07). Low genetic correlations were estimated between TV and BCS (from - 0.01 ± 0.08 to 0.06 ± 0.07). Respiration efficiency was estimated to be positively and moderately correlated with RR (0.36 ± 0.04), PS (0.56 ± 0.03), and BCS (0.56 ± 0.05 for caliper measurements and 0.50 ± 0.05 for the visual assessments). All other trait combinations were lowly genetically correlated. CONCLUSIONS: A comprehensive landscape of heritabilities and genetic correlations for various thermotolerance indicators in lactating sows were estimated. All traits evaluated are under genetic control and heritable, with different magnitudes, indicating that genetic progress is possible for all of them. The genetic correlation estimates provide evidence for the complex relationships between these traits and confirm the importance of a sub-index of thermotolerance traits to improve heat tolerance in pigs.

Longitudinal genomic analyses of automatically-recorded vaginal temperature in lactating sows under heat stress conditions based on random regression models.

BACKGROUND: Automatic and continuous recording of vaginal temperature (TV) using wearable sensors causes minimal disruptions to animal behavior and can generate data that enable the evaluation of temporal body temperature variation under heat stress (HS) conditions. However, the genetic basis of TV in lactating sows from a longitudinal perspective is still unknown. The objectives of this study were to define statistical models and estimate genetic parameters for TV in lactating sows using random regression models, and identify genomic regions and candidate genes associated with HS indicators derived from automatically-recorded TV. RESULTS: Heritability estimates for TV ranged from 0.14 to 0.20 over time (throughout the day and measurement period) and from 0.09 to 0.18 along environmental gradients (EG, - 3.5 to 2.2, which correspond to dew point values from 14.87 to 28.19 ËšC). Repeatability estimates of TV over time and along EG ranged from 0.57 to 0.66 and from 0.54 to 0.77, respectively. TV measured from 12h00 to 16h00 had moderately high estimates of heritability (0.20) and repeatability (0.64), indicating that this period might be the most suitable for recording TV for genetic selection purposes. Significant genotype-by-environment interactions (GxE) were observed and the moderately high estimates of genetic correlations between pairs of extreme EG indicate potential re-ranking of selection candidates across EG. Two important genomic regions on chromosomes 10 (59.370-59.998 Mb) and16 (21.548-21.966 Mb) were identified. These regions harbor the genes CDC123, CAMK1d, SEC61A2, and NUDT5 that are associated with immunity, protein transport, and energy metabolism. Across the four time-periods, respectively 12, 13, 16, and 10 associated genomic regions across 14 chromosomes were identified for TV. For the three EG classes, respectively 18, 15, and 14 associated genomic windows were identified for TV, respectively. Each time-period and EG class had uniquely enriched genes with identified specific biological functions, including regulation of the nervous system, metabolism and hormone production. CONCLUSIONS: TV is a heritable trait with substantial additive genetic variation and represents a promising indicator trait to select pigs for improved heat tolerance. Moderate GxE for TV exist, indicating potential re-ranking of selection candidates across EG. TV is a highly polygenic trait regulated by a complex interplay of physiological, cellular and behavioral mechanisms.

Interval estimation for operating characteristic of continuous biomarkers with controlled sensitivity or specificity.

The receiver operating characteristic (ROC) curve provides a comprehensive performance assessment of a continuous biomarker over the full threshold spectrum. Nevertheless, a medical test often dictates to operate at a certain high level of sensitivity or specificity. A diagnostic accuracy metric directly targeting the clinical utility is specificity at the controlled sensitivity level, or vice versa. While the empirical point estimation is readily adopted in practice, the nonparametric interval estimation is challenged by the fact that the variance involves density functions due to estimated threshold. In addition, even with a fixed threshold, many standard confidence intervals including the Wald interval for binomial proportion could have erratic behaviors. In this article, we are motivated by the superior performance of the score interval for binomial proportion and propose a novel extension for the biomarker problem. Meanwhile, we develop exact bootstrap and establish consistency of the bootstrap variance estimator. Both single-biomarker evaluation and two-biomarker comparison are investigated. Extensive simulation studies were conducted, demonstrating competitive performance of our proposals. An illustration with aggressive prostate cancer diagnosis is provided.

Gamma models for estimating the odds ratio for a skewed biomarker measured in pools and subject to errors.

Measuring a biomarker in pooled samples from multiple cases or controls can lead to cost-effective estimation of a covariate-adjusted odds ratio, particularly for expensive assays. But pooled measurements may be affected by assay-related measurement error (ME) and/or pooling-related processing error (PE), which can induce bias if ignored. Building on recently developed methods for a normal biomarker subject to additive errors, we present two related estimators for a right-skewed biomarker subject to multiplicative errors: one based on logistic regression and the other based on a Gamma discriminant function model. Applied to a reproductive health dataset with a right-skewed cytokine measured in pools of size 1 and 2, both methods suggest no association with spontaneous abortion. The fitted models indicate little ME but fairly severe PE, the latter of which is much too large to ignore. Simulations mimicking these data with a non-unity odds ratio confirm validity of the estimators and illustrate how PE can detract from pooling-related gains in statistical efficiency. These methods address a key issue associated with the homogeneous pools study design and should facilitate valid odds ratio estimation at a lower cost in a wide range of scenarios.

Impact of Prostate Health Index Results for Prediction of Biopsy Grade Reclassification During Active Surveillance.

PURPOSE: We assessed whether Prostate Health Index results improve prediction of grade reclassification for men on active surveillance. METHODS AND MATERIALS: We identified men in Canary Prostate Active Surveillance Study with Grade Group 1 cancer. Outcome was grade reclassification to Grade Group 2+ cancer. We considered decision rules to maximize specificity with sensitivity set at 95%. We derived rules based on clinical data (R1) vs clinical data+Prostate Health Index (R3). We considered an "or"-logic rule combining clinical score and Prostate Health Index (R4), and a "2-step" rule using clinical data followed by risk stratification based on Prostate Health Index (R2). Rules were applied to a validation set, where values of R2-R4 vs R1 for specificity and sensitivity were evaluated. RESULTS: We included 1,532 biopsies (n = 610 discovery; n = 922 validation) among 1,142 men. Grade reclassification was seen in 27% of biopsies (23% discovery, 29% validation). Among the discovery set, at 95% sensitivity, R2 yielded highest specificity at 27% vs 17% for R1. In the validation set, R3 had best performance vs R1 with Δsensitivity = -4% and Δspecificity = +6%. There was slight improvement for R3 vs R1 for confirmatory biopsy (AUC 0.745 vs R1 0.724, ΔAUC 0.021, 95% CI 0.002-0.041) but not for subsequent biopsies (ΔAUC -0.012, 95% CI -0.031-0.006). R3 did not have better discrimination vs R1 among the biopsy cohort overall (ΔAUC 0.007, 95% CI -0.007-0.020). CONCLUSIONS: Among active surveillance patients, using Prostate Health Index with clinical data modestly improved prediction of grade reclassification on confirmatory biopsy and did not improve prediction on subsequent biopsies.

Exploring the role of gut microbiota in host feeding behavior among breeds in swine.

BACKGROUND: The interplay between the gut microbiota and feeding behavior has consequences for host metabolism and health. The present study aimed to explore gut microbiota overall influence on feeding behavior traits and to identify specific microbes associated with the traits in three commercial swine breeds at three growth stages. Feeding behavior measures were obtained from 651 pigs of three breeds (Duroc, Landrace, and Large White) from an average 73 to 163 days of age. Seven feeding behavior traits covered the information of feed intake, feeder occupation time, feeding rate, and the number of visits to the feeder. Rectal swabs were collected from each pig at 73 ± 3, 123 ± 4, and 158 ± 4 days of age. DNA was extracted and subjected to 16 S rRNA gene sequencing. RESULTS: Differences in feeding behavior traits among breeds during each period were found. The proportion of phenotypic variances of feeding behavior explained by the gut microbial composition was small to moderate (ranged from 0.09 to 0.31). A total of 21, 10, and 35 amplicon sequence variants were found to be significantly (q-value < 0.05) associated with feeding behavior traits for Duroc, Landrace, and Large White across the three sampling time points. The identified amplicon sequence variants were annotated to five phyla, with Firmicutes being the most abundant. Those amplicon sequence variants were assigned to 28 genera, mainly including Christensenellaceae_R-7_group, Ruminococcaceae_UCG-004, Dorea, Ruminococcaceae_UCG-014, and Marvinbryantia. CONCLUSIONS: This study demonstrated the importance of the gut microbial composition in interacting with the host feeding behavior and identified multiple archaea and bacteria associated with feeding behavior measures in pigs from either Duroc, Landrace, or Large White breeds at three growth stages. Our study provides insight into the interaction between gut microbiota and feeding behavior and highlights the genetic background and age effects in swine microbial studies.

LINEAR BIOMARKER COMBINATION FOR CONSTRAINED CLASSIFICATION.

Multiple biomarkers are often combined to improve disease diagnosis. The uniformly optimal combination, i.e., with respect to all reasonable performance metrics, unfortunately requires excessive distributional modeling, to which the estimation can be sensitive. An alternative strategy is rather to pursue local optimality with respect to a specific performance metric. Nevertheless, existing methods may not target clinical utility of the intended medical test, which usually needs to operate above a certain sensitivity or specificity level, or do not have their statistical properties well studied and understood. In this article, we develop and investigate a linear combination method to maximize the clinical utility empirically for such a constrained classification. The combination coefficient is shown to have cube root asymptotics. The convergence rate and limiting distribution of the predictive performance are subsequently established, exhibiting robustness of the method in comparison with others. An algorithm with sound statistical justification is devised for efficient and high-quality computation. Simulations corroborate the theoretical results, and demonstrate good statistical and computational performance. Illustration with a clinical study on aggressive prostate cancer detection is provided.

Further host-genomic characterization of total antibody response to PRRSV vaccination and its relationship with reproductive performance in commercial sows: genome-wide haplotype and zygosity analyses.

BACKGROUND: The possibility of using antibody response (S/P ratio) to PRRSV vaccination measured in crossbred commercial gilts as a genetic indicator for reproductive performance in vaccinated crossbred sows has motivated further studies of the genomic basis of this trait. In this study, we investigated the association of haplotypes and runs of homozygosity (ROH) and heterozygosity (ROHet) with S/P ratio and their impact on reproductive performance. RESULTS: There was no association (P-value ≥ 0.18) of S/P ratio with the percentage of ROH or ROHet, or with the percentage of heterozygosity across the whole genome or in the major histocompatibility complex (MHC) region. However, specific ROH and ROHet regions were significantly associated (P-value ≤ 0.01) with S/P ratio on chromosomes 1, 4, 5, 7, 10, 11, 13, and 17 but not (P-value ≥ 0.10) with reproductive performance. With the haplotype-based genome-wide association study (GWAS), additional genomic regions associated with S/P ratio were identified on chromosomes 4, 7, and 9. These regions harbor immune-related genes, such as SLA-DOB, TAP2, TAPBP, TMIGD3, and ADORA. Four haplotypes at the identified region on chromosome 7 were also associated with multiple reproductive traits. A haplotype significantly associated with S/P ratio that is located in the MHC region may be in stronger linkage disequilibrium (LD) with the quantitative trait loci (QTL) than the previously identified single nucleotide polymorphism (SNP) (H3GA0020505) given the larger estimate of genetic variance explained by the haplotype than by the SNP. CONCLUSIONS: Specific ROH and ROHet regions were significantly associated with S/P ratio. The haplotype-based GWAS identified novel QTL for S/P ratio on chromosomes 4, 7, and 9 and confirmed the presence of at least one QTL in the MHC region. The chromosome 7 region was also associated with reproductive performance. These results narrow the search for causal genes in this region and suggest SLA-DOB and TAP2 as potential candidate genes associated with S/P ratio on chromosome 7. These results provide additional opportunities for marker-assisted selection and genomic selection for S/P ratio as genetic indicator for litter size in commercial pig populations.

Evidence for recombination variability in purebred swine populations.

This study aimed to investigate interpopulation variation due to sex, breed and age, and the intrapopulation variation in the form of genetic variance for recombination in swine. Genome-wide recombination rate and recombination occurrences (RO) were traits studied in Landrace (LR) and Large White (LW) male and female populations. Differences were found for sex, breed, sex-breed interaction, and age effects for genome-wide recombination rate and RO at one or more chromosomes. Dams were found to have a higher genome-wide recombination rate and RO at all chromosomes than sires. LW animals had higher genome-wide recombination rate and RO at seven chromosomes but lower at two chromosomes than LR individuals. The sex-breed interaction effect did not show any pattern not already observable by sex. Recombination increased with increasing parity in females, while in males no effect of age was observed. We estimated heritabilities and repeatabilities for both investigated traits and obtained the genetic correlation between male and female genome-wide recombination rate within each of the two breeds studied. Estimates of heritability and repeatability were low (h2  = 0.01-0.26; r = 0.18-0.42) for both traits in all populations. Genetic correlations were high and positive, with estimates of 0.98 and 0.94 for the LR and LW breeds, respectively. We performed a GWAS for genome-wide recombination rate independently in the four sex/breed populations. The results of the GWAS were inconsistent across the four populations with different significant genomic regions identified. The results of this study provide evidence of variability for recombination in purebred swine populations.

A varying-coefficient model for gap times between recurrent events.

Recurrent events often arise in follow-up studies where a subject may experience multiple occurrences of the same type of event. Most regression models for recurrent events consider the time scale measured from the study origin and assume constant effects of covariates. In many applications, however, gap times between recurrent events are of natural interest and moreover the effects may actually vary over time. In this article, we propose a marginal varying-coefficient model for gap times between recurrent events that allows for the intra-individual correlation between events. Estimation and inference procedures are developed for the varying coefficients. Consistency and weak convergence of the proposed estimator are established. Monte Carlo simulation studies demonstrate that the proposed method works well with practical sample sizes. The proposed method is illustrated with an analysis of bladder tumor clinical data.

[18F]Fluciclovine Positron Emission Tomography/Computerized Tomography for Preoperative Staging in Patients with Intermediate to High Risk Primary Prostate Cancer.

PURPOSE: Accurate preoperative staging of prostate cancer is essential for treatment planning. Conventional imaging is limited in detection of metastases. Our primary aim was to determine if [18F]fluciclovine positron emission tomography/computerized tomography is an early indicator of subclinical metastasis among patients with high risk prostate cancer. MATERIALS AND METHODS: A total of 68 patients with unfavorable intermediate to very high risk prostate cancer without systemic disease on conventional imaging were recruited before robotic radical prostatectomy with extended pelvic lymph node dissection. Diagnostic performance of [18F]fluciclovine positron emission tomography/computerized tomography and conventional imaging for detection of metastatic disease, and correlation of positivity to node and metastatic deposit size were determined. RESULTS: Overall 57 of 68 patients completed the protocol, of whom 31 had nodal metastasis on histology. [18F]Fluciclovine positron emission tomography/computerized tomography sensitivity and specificity in detecting nodal metastasis was 55.3% and 84.8% per patient, and 54.8% and 96.4% per region (right and left pelvis, presacral and nonregional), respectively. Compared with conventional imaging [18F]Fluciclovine positron emission tomography/computerized tomography had significantly higher sensitivity on patient based (55.3% vs 33.3%, p <0.01) and region based (54.8% vs 19.4%, p <0.01) analysis, detecting metastasis in 7 more patients and 22 more regions, with similar high specificity. Four additional patients had distant disease or other cancer detected on [18F] fluciclovine positron emission tomography/computerized tomography which precluded surgery. Detection of metastasis was related to size of metastatic deposits within lymph nodes and overall metastatic burden. CONCLUSIONS: [18F]Fluciclovine positron emission tomography/computerized tomography detects occult metastases not identified on conventional imaging and may help guide treatment decisions and lymph node dissection due to high specificity for metastatic disease.

Helicity Enhanced Torsion Sensor Based on Liquid Filled Twisted Photonic Crystal Fibers.

A highly sensitive torsion sensor can be constructed by combining a twisted photonic crystal fiber with a liquid-filled waveguide in its air-hole cladding. The torsion sensitivity of this type of sensor is determined directly by the phase-matching conditions between the fiber core mode and the liquid waveguide mode, which can be improved by tuning the helicity (denoted by the initial twist rate, α0) of the twisted photonic crystal fiber. The enhancement mechanism of α0 on the sensitivity of the proposed torsion sensor is investigated theoretically, followed by experimental verifications, and a torsion sensitivity as high as 446 nm∙mm∙rad-1 can be obtained by tailoring these parameters. Experimental results show that the torsion sensitivity increases with α0 decreasing from 3.142 to 3.925 rad/mm, which are in consistence with that of the numerical predictions. The demonstrated torsion sensor is expected to contribute to the development of highly sensitive torsion-related photonic crystal fiber devices.