7 research outputs found

    Tiludronate and clodronate do not affect bone structure or remodeling kinetics over a 60 day randomized trial

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    Background Tiludronate and clodronate are FDA-approved bisphosphonate drug therapies for navicular disease in horses. Although clinical studies have determined their ability to reduce lameness associated with skeletal disorders in horses, data regarding the effect on bone structure and remodeling is lacking. Additionally, due to off-label use of these drugs in young performance horses, effects on bone in young horses need to be investigated. Therefore, the purpose of this randomized, experimental pilot study was to determine the effect of tiludronate and clodronate on normal bone cells, structure and remodeling after 60 days in clinically normal, young horses. Additionally, the effect of clodronate on bone healing 60 days after an induced defect was investigated. Results All horses tolerated surgery well, with no post-surgery lameness and all acquired biopsies being adequate for analyses. Overall, tiludronate and clodronate did not significantly alter any bone structure or remodeling parameters, as evaluated by microCT and dynamic histomorphometry. Tiludronate did not extensively impact bone formation or resorption parameters as evaluated by static histomorphometry. Similarly, clodronate did not affect bone formation or resorption after 60 days. Sixty days post-defect, healing was minimally affected by clodronate. Conclusions Tiludronate and clodronate do not appear to significantly impact bone tissue on a structural or cellular level using standard dose and administration schedules

    MusMorph, a database of standardized mouse morphology data for morphometric meta-analyses

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    Complex morphological traits are the product of many genes with transient or lasting developmental effects that interact in anatomical context. Mouse models are a key resource for disentangling such effects, because they offer myriad tools for manipulating the genome in a controlled environment. Unfortunately, phenotypic data are often obtained using laboratory-specific protocols, resulting in self-contained datasets that are difficult to relate to one another for larger scale analyses. To enable meta-analyses of morphological variation, particularly in the craniofacial complex and brain, we created MusMorph, a database of standardized mouse morphology data spanning numerous genotypes and developmental stages, including E10.5, E11.5, E14.5, E15.5, E18.5, and adulthood. To standardize data collection, we implemented an atlas-based phenotyping pipeline that combines techniques from image registration, deep learning, and morphometrics. Alongside stage-specific atlases, we provide aligned micro-computed tomography images, dense anatomical landmarks, and segmentations (if available) for each specimen (N = 10,056). Our workflow is open-source to encourage transparency and reproducible data collection. The MusMorph data and scripts are available on FaceBase (www.facebase.org, https://doi.org/10.25550/3-HXMC) and GitHub (https://github.com/jaydevine/MusMorph)

    MusMorph, a database of standardized mouse morphology data for morphometric meta-analyses.

    Get PDF
    Complex morphological traits are the product of many genes with transient or lasting developmental effects that interact in anatomical context. Mouse models are a key resource for disentangling such effects, because they offer myriad tools for manipulating the genome in a controlled environment. Unfortunately, phenotypic data are often obtained using laboratory-specific protocols, resulting in self-contained datasets that are difficult to relate to one another for larger scale analyses. To enable meta-analyses of morphological variation, particularly in the craniofacial complex and brain, we created MusMorph, a database of standardized mouse morphology data spanning numerous genotypes and developmental stages, including E10.5, E11.5, E14.5, E15.5, E18.5, and adulthood. To standardize data collection, we implemented an atlas-based phenotyping pipeline that combines techniques from image registration, deep learning, and morphometrics. Alongside stage-specific atlases, we provide aligned micro-computed tomography images, dense anatomical landmarks, and segmentations (if available) for each specimen (N = 10,056). Our workflow is open-source to encourage transparency and reproducible data collection. The MusMorph data and scripts are available on FaceBase ( www.facebase.org , https://doi.org/10.25550/3-HXMC ) and GitHub ( https://github.com/jaydevine/MusMorph )
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