Accuracy of Genome-Enabled Prediction in a Dairy Cattle Population using Different Cross-Validation Layouts

The impact of extent of genetic relatedness on accuracy of genome-enabled predictions was assessed using a dairy cattle population and alternative cross-validation (CV) strategies were compared. The CV layouts consisted of training and testing sets obtained from either random allocation of individuals (RAN) or from a kernel-based clustering of individuals using the additive relationship matrix, to obtain two subsets that were as unrelated as possible (UNREL), as well as a layout based on stratification by generation (GEN). The UNREL layout decreased the average genetic relationships between training and testing animals but produced similar accuracies to the RAN design, which were about 15% higher than in the GEN setting. Results indicate that the CV structure can have an important effect on the accuracy of whole-genome predictions. However, the connection between average genetic relationships across training and testing sets and the estimated predictive ability is not straightforward, and may depend also on the kind of relatedness that exists between the two subsets and on the heritability of the trait. For high heritability traits, close relatives such as parents and full-sibs make the greatest contributions to accuracy, which can be compensated by half-sibs or grandsires in the case of lack of close relatives. However, for the low heritability traits the inclusion of close relatives is crucial and including more relatives of various types in the training set tends to lead to greater accuracy. In practice, CV designs should resemble the intended use of the predictive models, e.g., within or between family predictions, or within or across generation predictions, such that estimation of predictive ability is consistent with the actual application to be considered

Diagnosing pregnancy status using infrared spectra and milk composition in dairy cows

Data on Holstein (16,890), Brown Swiss (31,441), Simmental (25,845), and Alpine Grey (12,535) cows reared in northeastern Italy were used to assess the ability of milk components (fat, protein, casein, and lactose) and Fourier transform infrared (FTIR) spectral data to diagnose pregnancy. Pregnancy status was defined as whether a pregnancy was confirmed by a subsequent calving and no other subsequent inseminations within 90 d of the breeding of specific interest. Milk samples were analyzed for components and FTIR full-spectrum data using a MilkoScan FT+ 6000 (Foss Electric, Hiller\uf8d, Denmark). The spectrum covered 1,060 wavenumbers (wn) from 5,010 to 925 cm 121. Pregnancy status was predicted using generalized linear models with fat, protein, lactose, casein, and individual FTIR spectral bands or wavelengths as predictors. We also fitted a generalized linear model as a simultaneous function of all wavelengths (1,060 wn) with a Bayesian variable selection model using the BGLR R-package (https://r-forge.r-project.org/projects/bglr/). Prediction accuracy was determined using the area under a receiver operating characteristic curve based on a 10-fold cross-validation (CV-AUC) assessment based on sensitivities and specificities of phenotypic predictions. Overall, the best prediction accuracies were obtained for the model that included the complete FTIR spectral data. We observed similar patterns across breeds with small differences in prediction accuracy. The highest CV-AUC value was obtained for Alpine Grey cows (CV-AUC = 0.645), whereas Brown Swiss and Simmental cows had similar performance (CV-AUC = 0.630 and 0.628, respectively), followed by Holsteins (CV-AUC = 0.607). For single-wavelength analyses, important peaks were detected at wn 2,973 to 2,872 cm 121 where Fat-B (C-H stretch) is usually filtered, wn 1,773 cm 121 where Fat-A (C=O stretch) is filtered, wn 1,546 cm 121 where protein is filtered, wn 1,468 cm 121 associated with urea and fat, wn 1,399 and 1,245 cm 121 associated with acetone, and wn 1,025 to 1,013 cm 121 where lactose is filtered. In conclusion, this research provides new insight into alternative strategies for pregnancy screening of dairy cows

A local and territorial approach to the operation of the culture economy in medium and small cities: case study of the Spanish cities of Merida and Cuenca

The chief objective of this research is to analyze the weight that several factors linked to territory and/or urban society (such as proximity, heritage, image, or infrastructures) exert in the development and operation of cultural clusters in small and medium-sized cities. To this end, a local territorial approach combining quantitative and qualitative methods has been undertaken and applied to the Spanish cities of Merida and Cuenca. The results from this case study show that many parameters observed in the international bibliography that form part of the idiosyncrasy of medium and small cities (''closeness'', possibility of face-to-face contact, quality of life, low production costs) are considered by selected interviewees as essential to understanding the operation of their organizations and the urban cultural economic cluster as a whole. In general, these parameters appear in the international bibliography as contributing to the development of the cultural economy, but their importance in medium and small cities had been tested only rarely

Changes in milk characteristics and fatty acid profile during the estrous cycle in dairy cows

The relationship of the estrous cycle to milk composition and milk physical properties was assessed on Holstein (n = 10,696), Brown Swiss (n = 20,501), Simmental (n = 17,837), and Alpine Grey (n = 8,595) cows reared in northeastern Italy. The first insemination after calving for each cow was chosen to be the day of estrus and insemination. Test days surrounding the insemination date (from 10 d before to 10 d after the day of the estrus) were selected and categorized in phases relative to estrus as diestrus high-progesterone, proestrus, estrus, metestrus, and diestrus increasing-progesterone phases. Milk components and physical properties were predicted on the basis of Fourier-transform infrared spectra of milk samples and were analyzed using a linear mixed model, which included the random effects of herd, the fixed classification effects of year-month, parity number, breed, estrous cycle phase, day nested within the estrous cycle phase, conception, partial regressions on linear and quadratic effects of days in milk nested within parity number, as well as the interactions between conception outcome with estrous cycle phase and breed with estrous cycle phase. Milk composition, particularly fat, protein, and lactose, showed clear differences among the estrous cycle phases. Fat increased by 0.14% from diestrus high-progesterone to estrous phase, whereas protein concomitantly decreased by 0.03%. Lactose appeared to remain relatively constant over diestrus high-progesterone, rising 1 d before the day of estrus followed by a gradual reduction over the subsequent phases. Specific fatty acids were also affected across the estrous cycle phases: C14:0 and C16:0 decreased ( 120.34 and 120.48%) from proestrus to estrus with a concomitant increase in C18:0 and C18:1 cis-9 (0.40 and 0.73%). More general categories of fatty acids showed a similar behavior; that is, unsaturated fatty acids, monounsaturated fatty acids, polyunsaturated fatty acids, trans fatty acids, and long-chain fatty acids increased, whereas the saturated fatty acids, mediumchain fatty acids, and short-chain fatty acids decreased during the estrous phase. Finally, urea, somatic cell score, freezing point, pH, and homogenization index were also affected indicating variation associated with the hormonal and behavioral changes of cows in standing estrus. Hence, the variation in milk profiles of cows showing estrus should potentially be taken into account for precision dairy farming management

Beyond Missing Heritability: Prediction of Complex Traits

Despite rapid advances in genomic technology, our ability to account for phenotypic variation using genetic information remains limited for many traits. This has unfortunately resulted in limited application of genetic data towards preventive and personalized medicine, one of the primary impetuses of genome-wide association studies. Recently, a large proportion of the “missing heritability” for human height was statistically explained by modeling thousands of single nucleotide polymorphisms concurrently. However, it is currently unclear how gains in explained genetic variance will translate to the prediction of yet-to-be observed phenotypes. Using data from the Framingham Heart Study, we explore the genomic prediction of human height in training and validation samples while varying the statistical approach used, the number of SNPs included in the model, the validation scheme, and the number of subjects used to train the model. In our training datasets, we are able to explain a large proportion of the variation in height (h2 up to 0.83, R2 up to 0.96). However, the proportion of variance accounted for in validation samples is much smaller (ranging from 0.15 to 0.36 depending on the degree of familial information used in the training dataset). While such R2 values vastly exceed what has been previously reported using a reduced number of pre-selected markers (<0.10), given the heritability of the trait (∼0.80), substantial room for improvement remains

Distributed Power Control with Received Power Constraints for Time-Area-Spectrum Licenses

peer reviewe

Harmine and Piperlongumine Revert TRIB2-Mediated Drug Resistance.

Therapy resistance is responsible for most relapses in patients with cancer and is the major challenge to improving the clinical outcome. The pseudokinase Tribbles homologue 2 (TRIB2) has been characterized as an important driver of resistance to several anti-cancer drugs, including the dual ATP-competitive PI3K and mTOR inhibitor dactolisib (BEZ235). TRIB2 promotes AKT activity, leading to the inactivation of FOXO transcription factors, which are known to mediate the cell response to antitumor drugs. To characterize the downstream events of TRIB2 activity, we analyzed the gene expression profiles of isogenic cell lines with different TRIB2 statuses by RNA sequencing. Using a connectivity map-based computational approach, we identified drug-induced gene-expression profiles that invert the TRIB2-associated expression profile. In particular, the natural alkaloids harmine and piperlongumine not only produced inverse gene expression profiles but also synergistically increased BEZ235-induced cell toxicity. Importantly, both agents promote FOXO nuclear translocation without interfering with the nuclear export machinery and induce the transcription of FOXO target genes. Our results highlight the great potential of this approach for drug repurposing and suggest that harmine and piperlongumine or similar compounds might be useful in the clinic to overcome TRIB2-mediated therapy resistance in cancer patients.This work was supported by the FUNDAÇÃO PARA A CIÊNCIA E TECNOLOGIA (FCT) Research Center Grant UID/BIM/04773/2013, Centre for Biomedical Research (CBMR), and by the Spanish Ministry of Science, Innovation and Universities through Grant RTI2018-094629-B-I00 to WL. B.I.F. was supported by FCT-SFRH/BPD/100434/2014 and the Marie Curie Individual Fellowship project TRIBBLES (#748585). This work was also supported by two LPCC-NRS/Terry Fox grants (2016/2017; 2017/2018). S. Machado is the recipient of a ProRegeM grant PD/BD/114258/2016. I. Duarte was supported by a scholarship from FCT Grant PTDC/BEX-BID/5410/2014S

Association of myostatin, a cytokine released by muscle, with inflammation in rheumatoid arthritis

Instituto Mexicano del Seguro Social, Fondo de Investigacion en Salud, FIS/IMSS/PROT/MD16/1565Supplemental Digital Content is available in the text Myostatin is a cytokine produced and released by myocytes that might have an outstanding role not only in muscle wasting during cachexia but also in inflammation. Herein we explore the association between myostatin levels and inflammatory parameters in rheumatoid arthritis (RA). One hundred twenty-seven women without rheumatic diseases and 84 women with a diagnosis of RA were assessed in a cross-sectional study. Outcomes reflecting the activity of the arthritis including Disease Activity Score (DAS28-ESR) and impairment in functioning by the Health Assessment Questionnaire-Disability Index were assessed in RA. We obtained Skeletal muscle mass index (SMI), fat-free mass index (FFMI), and fat mass index using dual-energy x-ray absorptiometry. Serum myostatin was determined by enzyme-linked immunosorbent assay. Myostatin levels were correlated with disease activity and parameters of muscle mass. The SMI was lower and concentration of myostatin was higher in RA patients than in controls (P = .008 and P < .001, respectively). Myostatin significantly positively correlated with C-reactive protein (rho = 0.48, P < .001), erythrocyte sedimentation rate (rho = 0.28, P = .009), and DAS28-ESR (rho = 0.22, P = .04), and negatively correlated with SMI (rho = −0.29, P = .008), (FFMI) (rho = −0.24, P = .027). In the multivariate logistic regression analysis, levels of myostatin remained associated with disease activity in RA (P = .027). In our study, myostatin was associated with disease activity in RA patients, suggesting a mechanistic link between myostatin, muscle wasting and inflammation in RA

Restricción alimenticia en ovinos: Respuesta endocrino metabólica dependiente de las reservas corporales

las respuestas metabólicas a los cambios en el estado corporal podrían depender de la historia metabólica reciente (nivel de alimentación, efecto dinámico) o más antigua (reservas corporales, efecto estático), concepto denominado "memoria metabólica". El objetivo de este trabajo fue estudiar la respuesta endocrino-metabólica a una restricción alimenticia en ovejas con diferente condición corporal (CC) al inicio del experimento. Durante la estación reproductiva, 36 ovejas Rasa Aragonesa fueron separadas en 2 grupos con diferente CC: CC > 2,75 (moderadamente alta, A, 2,9 ± 0,04) y CC < 2,25 (moderadamente baja, B, 2,1 ± 0,04). Durante 20 días, ambos grupos recibieron una dieta para cubrir los requerimientos de mantenimiento de energía y proteína, tras lo cual se asignaron al azar a dos tratamientos nutricionales: 1,5 (control, C) o 0,5 (subnutrición, S) veces los requerimientos de mantenimiento diario, estableciéndose cuatro grupos: altas control (AC, n = 9), altas subnutridas (AS, n = 10), bajas control (BC, n = 9) y bajas subnutridas (BS, n = 8). Se determinó el peso vivo (PV) y los niveles plasmáticos de glucosa, ácidos grasos no esterificados (AGNE), 3-hidroxibutirato (BHB), insulina, leptina y factor de crecimiento similar a la insulina tipo 1 (IGF-I). Los grupos BS y AS perdieron peso, el grupo BC lo ganó y las ovejas AC lo mantuvieron. La concentración plasmática de glucosa fue mayor y los AGNE menor en las ovejas controles. Las ovejas de alta CC presentaron mayores concentraciones de insulina y de IGF-I, y la leptina tendió a ser mayor en estos animales. A su vez, la insulina fue mayor en los animales controles, mientras que las otras hormonas no fueron afectadas por el tratamiento. Los perfiles de glucosa, BHB, insulina e IGF-I estuvieron afectados por la CC inicial y el tratamiento nutricional, como así lo demuestra la interacción significativa entre estos factores y días. Se evidenció un aumento en el momento del celo de las concentraciones de los metabolitos (glucosa y BHB) y de las hormonas metabólicas (insulina e IGF-I). En conclusión, en este estudio se encontró que los perfiles de glucosa, BHB, insulina e IGF-I varían de forma diferente frente a una restricción alimenticia en función del grado de reservas corporales de las ovejas en el momento de iniciarse la restricción alimenticia.Fil: Fernandez Foren, A.. Universidad de la República; UruguayFil: Abecia, José Alfonso. Universidad de Zaragoza; EspañaFil: Vazquez, Maria Isabel. Universidad Nacional de Río Cuarto. Facultad de Agronomía y Veterinaria; Argentina. Universidad Nacional de Rio Cuarto. Facultad de Agronomia y Veterinaria. Instituto de Ciencias Veterinarias. - Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - Cordoba. Instituto de Ciencias Veterinarias.; ArgentinaFil: Forcada Miranda, Fernando. Universidad de Zaragoza; EspañaFil: Sartore, I.. Universidad de la República; UruguayFil: Carriquiry, M.. Universidad de la República; UruguayFil: Meikle, Ana. Universidad de la República; UruguayFil: Sosa Misuraca, Cecilia. Universidad de Zaragoza; Españ