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To optimize breeding objectives of Fleckvieh and Brown Swiss cattle, economic values were re-estimated using updated prices, costs, and population parameters. Subsequently, the expected selection responses for the total merit index (TMI) were calculated using previous and newly derived economic values. The responses were compared for alternative scenarios that consider breeders' preferences. A dairy herd with milk production, bull fattening, and rearing of replacement stock was modeled. The economic value of a trait was derived by calculating the difference in herd profit before and after genetic improvement. Economic values for each trait were derived while keeping all other traits constant. The traits considered were dairy, beef, and fitness traits, the latter including direct health traits. The calculation of the TMI and the expected selection responses was done using selection index methodology with estimated breeding values instead of phenotypic deviations. For the scenario representing the situation up to 2016, all traits included in the TMI were considered with their respective economic values before the update. Selection response was also calculated for newly derived economic values and some alternative scenarios, including the new trait vitality index (subindex comprising stillbirth and rearing losses). For Fleckvieh, the relative economic value for the trait groups milk, beef, and fitness were 38, 16, and 46%, respectively, up to 2016, and 39, 13, and 48%, respectively, for the newly derived economic values. Approximately the same selection response may be expected for the milk trait group, whereas the new weightings resulted in a substantially decreased response in beef traits. Within the fitness block, all traits, with the exception of fertility, showed a positive selection response. For Brown Swiss, the relative economic values for the main trait groups milk, beef, and fitness were 48, 5, and 47% before 2016, respectively, whereas for the newly derived scenario they were 40, 14, and 39%. For both Brown Swiss and Fleckvieh, the fertility complex was expected to further deteriorate, whereas all other expected selection responses for fitness traits were positive. Several additional and alternative scenarios were calculated as a basis for discussion with breeders. A decision was made to implement TMI with relative economic values for milk, beef, and fitness with 38, 18, and 44% for Fleckvieh and 50, 5, and 45% for Brown Swiss, respectively. In both breeds, no positive expected selection response was predicted for fertility, although this trait complex received a markedly higher weight than that derived economically. An even higher weight for fertility could not be agreed on due to the effect on selection response of other traits. Hence, breeders decided to direct more attention toward the preselection of bulls with regard to fertility.
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http://dx.doi.org/10.3168/jds.2016-11095 | DOI Listing |
Pharmacoecon Open
September 2025
Department of Pharmacy, The Second Affiliated Hospital of Army Medical University, No.83 Xinqiao Central Street, Shapingba District, Chongqing, 400037, China.
Objective: Two vaccines against herpes zoster (HZ) are currently authorized for use in China: the adjuvanted recombinant zoster vaccine (RZV) and live-attenuated Zoster Vaccine Live (ZVL). The significant disparities in prices and efficacy between the two vaccines necessitate an evaluation of their relative value in order to make an informed choice. This study aimed to evaluate the comparative cost effectiveness of RZV, ZVL, and no vaccination for older adults at different ages from the societal perspective.
View Article and Find Full Text PDFJ Neurooncol
September 2025
Department of Neurosurgery, Johns Hopkins School of Medicine, Baltimore, MD, USA.
Background And Objectives: Explore whether community social capital measures (system of resources available to individuals through community engagement) are related to surgical outcomes among intracranial tumor patients.
Methods: Adults who underwent resection at a single medical center for intracranial tumor was identified and their zip codes were matched to three variables derived from the Social Capital Atlas: economic connectedness, volunteering rate, and civic organizations. The economic connectedness score quantifies the degree to which low-income and high-income community members are friends with each other, the volunteering rate is defined as the proportion of a given community engaged in community organizations and the civic organization score is defined as the number of local civic organizations within a given community.
Theor Appl Genet
September 2025
Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany.
The German Federal Ex Situ Genebank for Agricultural and Horticultural Crops (IPK) harbours over 3000 pea plant genetic resources (PGRs), backed up by corresponding information across 16 key agronomic and economical traits. The unbalanced structure and inconsistent format of this historical data has precluded effective leverage of genebank accessions, despite the opportunities contained in its genetic diversity. Therefore, a three-step statistical approach founded in linear mixed models was implemented to enable a rigorous and targeted data curation.
View Article and Find Full Text PDFJ Am Coll Radiol
August 2025
Vice-Chair for Clinical Research, John Westgate Hope Endowed Chair for Faculty Development, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania; Assistant Professor of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsyl
Objective: To determine the number of pediatric radiologists in the United States using professional imaging claims of children between 2016 and 2023 in a private payor claims database.
Methods: From 2016 to 2023, using private payer claims data (Inovalon Insights, LLC), all claim lines for radiology professional services billed by radiologists were identified. Each claim was assigned a work relative value unit (wRVU) in accordance with the CMS valuation for the claim year.
Radiology
September 2025
Department of Biomedical Informatics, Harvard Medical School, 10 Shattuck St, Boston, MA 02115.
Despite the rapid growth of Food and Drug Administration-cleared artificial intelligence (AI)- and machine learning-enabled medical devices for use in radiology, current tools remain limited in scope, often focusing on narrow tasks and lacking the ability to comprehensively assist radiologists. These narrow AI solutions face limitations in financial sustainability, operational efficiency, and clinical utility, hindering widespread adoption and constraining their long-term value in radiology practice. Recent advances in generative and multimodal AI have expanded the scope of image interpretation, prompting discussions on the development of generalist medical AI.
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