The list of standard abbreviations for JDS is available at adsa.org/jds-abbreviations-24. Nonstandard abbreviations are available in the Notes.
Estimating feed efficiency (FE) in dairy sheep is ...challenging due to the high cost of systems that measure individual feed intake. Identifying proxies that can serve as effective predictors of FE could make it possible to introduce FE into breeding programs. Here, 39 Assaf ewes in first lactation were evaluated regarding their FE by 2 metrics, residual feed intake (RFI) and feed conversion ratio (FCR). The ewes were classified into high, medium and low groups for each metric. Milk samples of the 39 ewes were subjected to untargeted metabolomics analysis. The complete milk metabolomic signature was used to discriminate the FE groups using partial least squares discriminant analysis. A total of 41 and 26 features were selected as the most relevant features for the discrimination of RFI and FCR groups, respectively. The predictive ability when utilizing the complete milk metabolomic signature and the reduced data sets were investigated using 4 machine learning (ML) algorithms and a multivariate regression method. The orthogonal partial least squares algorithm outperformed other ML algorithms for FCR prediction in the scenarios using the complete milk metabolite signature (R2 = 0.62 ± 0.06) and the 26 selected features (R2 = 0.62 ± 0.15). Regarding RFI predictions, the scenarios using the 41 selected features outperformed the scenario with the complete milk metabolite signature, where the multilayer feedforward artificial neural network (R2 = 0.18 ± 0.14) and extreme gradient boosting (R2 = 0.17 ± 0.15) outperformed other algorithms. The functionality of the selected metabolites implied that the metabolism of glucose, galactose, fructose, sphingolipids, amino acids, insulin, and thyroid hormones was at play. Compared with the use of traditional methods, practical applications of these biomarkers might simplify and reduce costs in selecting feed-efficient ewes.
The present study aimed to ascertain how different strategies for leveraging genomic information enhance the accuracy of estimated breeding values for milk and cheese-making traits and to evaluate ...the implementation of a low-density (LowD) SNP chip designed explicitly for that aim. Thus, milk samples from a total of 2,020 dairy ewes from 2 breeds (1,039 Spanish Assaf and 981 Churra) were collected and analyzed to determine 3 milk production and composition traits and 2 traits related to milk coagulation properties and cheese yield. The 2 studied populations were genotyped with a customized 50K Affymetrix SNP chip (Affymetrix Inc.) containing 55,627 SNP markers. The prediction accuracies were obtained using different multitrait methodologies, such as the BLUP model based on pedigree information, the genomic BLUP (GBLUP), and the BLUP at the SNP level (SNP-BLUP), which are based on genotypic data, and the single-step GBLUP (ssGBLUP), which combines both sources of information. All of these methods were analyzed by cross-validation, comparing predictions of the whole population with the test population sets. Additionally, we describe the design of a LowD SNP chip (3K) and its prediction accuracies through the different methods mentioned previously. Furthermore, the results obtained using the LowD SNP chip were compared with those based on the 50K SNP chip data sets. Finally, we conclude that implementing genomic selection through the ssGBLUP model in the current breeding programs would increase the accuracy of the estimated breeding values compared with the BLUP methodology in the Assaf (from 0.19 to 0.39) and Churra (from 0.27 to 0.44) dairy sheep populations. The LowD SNP chip is cost-effective and has proven to be an accurate tool for estimating genomic breeding values for milk and cheese-making traits, microsatellite imputation, and parentage verification. The results presented here suggest that the routine use of this LowD SNP chip could potentially increase the genetic gains of the breeding selection programs of the 2 Spanish dairy sheep breeds considered here.
Nuclear utilities are increasingly facing challenges meeting evolving regulatory requirements of probabilistic structural assessments with existing tools. Probabilistic methodologies are widely used ...as part of reactor safety analyses, including piping component structural integrity and fitness-for-service assessments. Probabilistic structural integrity assessments for nuclear piping components are typically conducted using special-purpose codes that may only provide limited probabilistic capabilities, may not be used with high-fidelity simulation software, or may not be used on high-performance computing clusters for large simulation campaigns. In the Canadian nuclear industry, probabilistic assessments for fuel channels are constrained by the large population of fuel channels in the case of in-core analyses. Meanwhile, for components such as steam generators, assessments are constrained by interfacing capabilities of the complex simulation codes that would be needed to represent the relevant physical phenomena. A generic and scalable probabilistic framework is needed to enable utilities to conduct large-scale probabilistic structural assessments with representative simulation codes.
The present study proposes a novel and scalable framework for developing Monte Carlo analysis workflows to assess the structural integrity of nuclear plant piping components. The methodology is demonstrated for two relevant scenarios: a vibration-induced cracking assessment of a steam generator and a CANDU11CANDU is a registered trademark of Atomic Energy of Canada Limited. pressure-tube fitness-for-service assessment. The study shows that the proposed methodology provides a convenient means for assessing uncertainty propagation, confidence intervals, and output parameter distributions for probabilistic structural integrity cases.
•A scalable method is proposed for probabilistic structural integrity assessments.•The method is demonstrated on steam generator tube and CANDU pressure tube simulation workflows.•The method is appropriate both for reduced order models and high fidelity simulation codes (e.g. finite element analysis).
As the prepubertal stage is a crucial point for the proper development of the mammary gland and milk production, this study aims to evaluate how protein restriction at this stage can affect ...methylation marks in milk somatic cells. Here, 28 Assaf ewes were subjected to 42.3% nutritional protein restriction (14 animals, NPR) or fed standard diets (14 animals, C) during the prepubertal stage. During the second lactation, the milk somatic cells of these ewes were sampled, and the extracted DNA was subjected to whole-genome bisulfite sequencing. A total of 1154 differentially methylated regions (DMRs) were identified between the NPR and C groups. Indeed, the results of functional enrichment analyses of the genes harboring these DMRs suggested their relevant effects on the development of the mammary gland and lipid metabolism in sheep. The additional analysis of the correlations of the mean methylation levels within these DMRs with fat, protein, and dry extract percentages in the milk and milk somatic cell counts suggested associations between several DMRs and milk production traits. However, there were no phenotypic differences in these traits between the NPR and C groups. In light of the above, the results obtained in the current study might suggest potential candidate genes for the regulation of milk production traits in the sheep mammary gland. Further studies focusing on elucidating the genetic mechanisms affected by the identified DMRs may help to better understand the biological mechanisms modified in the mammary gland of dairy sheep as a response to nutritional challenges and their potential effects on milk production.
To evaluate whether oligoclonal bands (OB) add information to MRI in predicting both a second attack and development of disability in patients with clinically isolated syndromes (CIS).
From 1995 to ...2006, 572 patients with CIS were included in a prospective study. Patients underwent brain MRI and determination of OB within 3 months of first attack. The number and location of lesions and presence of OB were studied. We analyzed time to second attack and to Expanded Disability Status Scale 3.0 according to number of Barkhof criteria (BC) and the presence or absence of OB.
We studied 415 (73%) patients with CIS with both baseline MRI and determination of OB. Patients were followed for a mean of 50 months (SD 31). Compared to the reference group with 0 BC at baseline MRI, patients with one to two BC showed a hazard ratio (HR) for conversion to CDMS of 3.8 (2.0 to 7.2) and patients with three to four BC of 8.9 (4.8 to 16.4). Of the total cohort, OB were positive in 61% of the patients. However, broken down by MRI group, OB were positive in 31% of those with no BC; 69% of those with one to two BC; and 85% of those with three or four BC. The presence of OB increased the risk of a second relapse (HR 1.7; 1.1 to -2.7) independently of baseline MRI but did not modify the development of disability.
Presence of oligoclonal bands doubles the risk for having a second attack, independently of MRI, but does not seem to influence the development of disability.
•Feed efficiency (FE) biomarkers were identified in the milk transcriptome of ewes.•We evaluate the effects of using different FE indices over the milk transcriptome.•Gene expression shows potential ...for predicting sheep FE with machine learning.•The impact of sustainability strategies on the sheep dairy industry was assessed.•Prepubertal protein restriction lacks impact on FE in Assaf ewes at first lactation.
In recent years, rising prices for high-quality protein-based feeds have significantly increased nutrition costs. Consequently, investigating strategies to reduce these expenses and improve feed efficiency (FE) have become increasingly important for the dairy sheep industry. This research investigates the impact of nutritional protein restriction (NPR) during prepuberty and FE on the milk transcriptome of dairy Assaf ewes (sampled during the first lactation). To this end, we first compared transcriptomic differences between NPR and control ewes. Subsequently, we evaluated gene expression differences between ewes with divergent FE, using feed conversion ratio (FCR), residual feed intake (RFI), and consensus classifications of high− and low-FE animals for both indices. Lastly, we assess milk gene expression as a predictor of FE phenotype using random forest. No effect was found for the prepubertal NPR on milk performance or FE. Moreover, at the milk transcriptome level, only one gene, HBB, was differentially expressed between the NPR (n = 14) and the control group (n = 14). Further, the transcriptomic analysis between divergent FE sheep revealed 114 differentially expressed genes (DEGs) for RFI index (high-FERFI = 10 vs low-FERFI = 10), 244 for FCR (high-FEFCR = 10 vs low-FEFCR = 10), and 1 016 DEGs between divergent consensus ewes for both indices (high-FEconsensus = 8 vs low-FEconsensus = 8). These results underscore the critical role of selected FE indices for RNA-Seq analyses, revealing that consensus divergent animals for both indices maximise differences in transcriptomic responses. Genes overexpressed in high-FEconsensus ewes were associated with milk production and mammary gland development, while low-FEconsensus genes were linked to higher metabolic expenditure for tissue organisation and repair. The best prediction accuracy for FE phenotype using random forest was obtained for a set of 44 genes consistently differentially expressed across lactations, with Spearman correlations of 0.37 and 0.22 for FCR and RFI, respectively. These findings provide insights into potential sustainability strategies for dairy sheep, highlighting the utility of transcriptomic markers as FE proxies.
This study aimed to perform a GWAS to identify genomic regions associated with milk and cheese-making traits in Assaf and Churra dairy sheep breeds; second, it aimed to identify possible positional ...and functional candidate genes and their interactions through post-GWAS studies. For 2,020 dairy ewes from 2 breeds (1,039 Spanish Assaf and 981 Churra), milk samples were collected and analyzed to determine 6 milk production and composition traits and 6 traits related to milk coagulation properties and cheese yield. The genetic profiles of the ewes were obtained using a genotyping chip array that included 50,934 SNP markers. For both milk and cheese-making traits, separate single-breed GWAS were performed using GCTA software. The set of positional candidate genes identified via GWAS was subjected to guilt-by-association-based prioritization analysis with ToppGene software. Totals of 84 and 139 chromosome-wise significant associations for the 6 milk traits and the 6 cheese-making traits were identified in this study. No significant SNPs were found in common between the 2 studied breeds, possibly due to their genetic heterogeneity of the phenotypes under study. Additionally, 63 and 176 positional candidate genes were located in the genomic intervals defined as confidence regions in relation to the significant SNPs identified for the analyzed traits for Assaf and Churra breeds. After the functional prioritization analysis, 71 genes were identified as promising positional and functional candidate genes and proposed as targets of future research to identify putative causative variants in relation to the traits under examination. In addition, this multitrait study allowed us to identify variants that have a pleiotropic effect on both milk production and cheese-related traits. The incorporation of variants among the proposed functional and positional candidate genes into genomic selection strategies represent an interesting approach for achieving rapid genetic gains, specifically for those traits difficult to measure, such as cheese-making traits.
The global production of sheep milk is growing, and the main industrial use of sheep milk is cheese making. The Spanish Churra sheep breed is one of the most important native dairy breeds in Spain. ...The present study aimed to estimate genetic parameters for a wide range of traits influencing the cheese-making ability of Churra sheep milk. Using a total of 1,049 Churra ewes, we studied the following cheese-making traits: 4 traits related to milk coagulation properties (rennet coagulation time, curd-firming time, and curd firmness at 30 and 60 min after addition of rennet), 2 traits related to cheese yield (individual laboratory cheese yield and individual laboratory dried curd yield), and 3 traits measuring curd firmness over time (maximum curd firmness, time to attain maximum curd firmness, and syneresis). In addition, a list of milk traits, including the native pH of the milk and several milk production and composition traits (milk yield; the fat, protein, and dried extract percentages; and the somatic cell count), were also analyzed for the studied animals. After discarding the noncoagulating samples (only 3.7%), data of 1,010 ewes were analyzed with multiple-trait animal models by using the restricted maximum likelihood method to estimate (co)variance components, heritabilities, and genetic correlations. In general, the heritability estimates were low to moderate, ranging from 0.08 (for the individual laboratory dried curd yield trait) to 0.42 (for the fat percentage trait). High genetic correlations were found within pairs of related traits (i.e., 0.93 between fat and dried extract percentages, −0.93 between the log of the curd-firming time and curd firmness at 30 min, 0.70 between individual laboratory cheese yield and individual laboratory dried curd yield, and −0.94 between time to attain maximum curd firmness and syneresis). Considering all the information provided here, we suggest that in addition to the current consideration of the protein percentage trait for improving cheese yield traits, the inclusion of the pH of milk as a measured trait in the Churra dairy breeding program would represent an efficient strategy for improving the cheese-making ability of milk from this breed.
To determine the relation between baseline MRI and both conversion to multiple sclerosis (MS) and development of disability in a cohort of patients with clinically isolated syndromes (CIS).
From 1995 ...to 1998, 175 consecutive patients with CIS underwent brain MRI within 3 months of their first attack and again 12 months and 5 years later. We studied the number and location of lesions at baseline and development of new T2 lesions. We also analyzed conversion to MS and development of disability (Expanded Disability Status Scale EDSS > or = 3.0).
We included 156 patients with CIS followed for a median of 7 years. Compared to the reference group with 0 Barkhof criteria at baseline MRI, patients with one or two Barkhof criteria showed an adjusted hazard ratio (HR) of 6.1 (2.2 to 16.6) and patients with three to four Barkhof criteria of 17.0 (6.7 to 43) for conversion to MS and differentiated patients with low, medium, and high conversion risk. EDSS at year 5 correlated with baseline number of Barkhof criteria (r = 0.46, p < 0.0001). When categorizing by number of baseline lesions, similar results were seen. Patients with a baseline MRI with three to four Barkhof criteria had an adjusted HR of 3.9 (1.1 to 13.6) for reaching EDSS > or = 3.0. Only 10% of the latter had disability at year 5, but 40% reached this at 8 years.
Baseline MRI determines the risk for converting to clinically definite multiple sclerosis and correlates with disability at 5 years. The proportion of patients developing disability is low during the first 5 years but rapidly increases shortly after.
Patients presenting sequelae of poliomyelitis may present new symptoms, known as post-polio syndrome (PPS).
To identify the clinical and functional profile and epidemiological characteristics of ...patients presenting PPS.
We performed a retrospective study of 400 patients with poliomyelitis attended at the Institut Guttmann outpatient clinic, of whom 310 were diagnosed with PPS. We describe patients’ epidemiological, clinical, and electromyographic variables and analyse the relationships between age of poliomyelitis onset and severity of the disease, and between sex, age of PPS onset, and the frequency of symptoms.
PPS was more frequent in women (57.7%). The mean age at symptom onset was 52.4 years, and was earlier in women. Age at primary infection > 2 years was not related to greater poliomyelitis severity.
The frequency of symptoms was: pain in 85% of patients, loss of strength in 40%, fatigue in 65.5%, tiredness in 57.8%, cold intolerance in 20.2%, dysphagia in 11.7%, cognitive complaints in 9%, and depressive symptoms in 31.5%. Fatigue, tiredness, depression, and cognitive complaints were significantly more frequent in women.
Fifty-nine percent of patients presented electromyographic findings suggestive of PPS.
While the symptoms observed in our sample are similar to those reported in the literature, the frequencies observed are not. We believe that patients’ clinical profile may be very diverse, giving more weight to such objective parameters as worsening of symptoms or appearance of weakness; analysis of biomarkers may bring us closer to an accurate diagnosis.
Las personas con secuelas de poliomielitis pueden presentar nuevos síntomas que constituirían el síndrome pospolio (SPP).
ObjetivoIdentificar el perfil clínico y funcional, y las características epidemiológicas de personas que padecen SPP.
Estudio retrospectivo de 400 pacientes afectados de poliomielitis visitados en consulta externa del Institut Guttmann, de los cuales a 310 se les diagnosticó SPP. Se describieron variables epidemiológicas, clínicas y electromiográficas. Se analizó la relación entre edad de adquisición de la polio y gravedad de la misma, así como entre el sexo y la edad de aparición del SPP y la frecuencia de síntomas.
Se observó mayor frecuencia de SPP en mujeres (57,7%). La edad media de inicio de la clínica fue 52,4 años, más precoz en mujeres. Edad de primoinfección mayor de 2 años no se relacionó con mayor gravedad de la polio.
La frecuencia de síntomas fue: dolor 85%, pérdida de fuerza 40%, fatiga 65,5%, cansancio 57,8%, intolerancia al frío 20,2%, disfagia 11,7%, quejas cognitivas 9%, síntomas depresivos 31,5%. La fatiga, el cansancio, la depresión y las quejas cognitivas fueron significativamente más frecuentes en mujeres.
El 59% de los pacientes presentaban hallazgos electromiográficos sugestivos de SPP.
El tipo de sintomatología que presentaba nuestra muestra es similar a la publicada, no así en la frecuencia de la misma. Creemos que el perfil clínico de los pacientes podría ser muy diverso, y dar mayor peso a parámetros objetivos como el empeoramiento o la aparición de debilidad y el estudio de biomarcadores podría acercarnos más a un diagnóstico preciso.
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