No abstract

Neoplastic diseases are typically diagnosed by biopsy and histopathological evaluation. The pathology report is key in determining prognosis, therapeutic decisions, and overall case management and therefore requires diagnostic accuracy, completeness, and clarity. Successful management relies on collaboration between clinical veterinarians, oncologists, and pathologists. To date there has been no standardized approach or guideline for the submission, trimming, margin evaluation, or reporting of neoplastic biopsy specimens in veterinary medicine. To address this issue, a committee consisting of veterinary pathologists and oncologists was established under the auspices of the American College of Veterinary Pathologists Oncology Committee. These consensus guidelines were subsequently reviewed and endorsed by a large international group of veterinary pathologists. These recommended guidelines are not mandated but rather exist to help clinicians and veterinary pathologists optimally handle neoplastic biopsy samples. Many of these guidelines represent the collective experience of the committee members and consensus group when assessing neoplastic lesions from veterinary patients but have not met the rigors of definitive scientific study and investigation. These questions of technique, analysis, and evaluation should be put through formal scrutiny in rigorous clinical studies in the near future so that more definitive guidelines can be derived.

There is an increasing need for more accurate prognostic and predictive markers in veterinary oncology because of an increasing number of treatment options, the increased financial costs associated with treatment, and the emotional stress experienced by owners in association with the disease and its treatment. Numerous studies have evaluated potential prognostic and predictive markers for veterinary neoplastic diseases, but there are no established guidelines or standards for the conduct and reporting of prognostic studies in veterinary medicine. This lack of standardization has made the evaluation and comparison of studies difficult. Most important, translating these results to clinical applications is problematic. To address this issue, the American College of Veterinary Pathologists' Oncology Committee organized an initiative to establish guidelines for the conduct and reporting of prognostic studies in veterinary oncology. The goal of this initiative is to increase the quality and standardization of veterinary prognostic studies to facilitate independent evaluation, validation, comparison, and implementation of study results. This article represents a consensus statement on the conduct and reporting of prognostic studies in veterinary oncology from veterinary pathologists and oncologists from around the world. These guidelines should be considered a recommendation based on the current state of knowledge in the field, and they will need to be continually reevaluated and revised as the field of veterinary oncology continues to progress. As mentioned, these guidelines were developed through an initiative of the American College of Veterinary Pathologists' Oncology Committee, and they have been reviewed and endorsed by the World Small Animal Veterinary Association.

Abstract-We designed, fabricated, and characterized metamaterial-based RF-microelectromechanical system (RF-MEMS) strain sensors that incorporate multiple split ring resonators (SRRs) in a compact nested architecture to measure strain telemetrically. We also showed biocompatibility of these strain sensors in an animal model. With these devices, our bioimplantable wireless metamaterial sensors are intended, to enable clinicians, to quantitatively evaluate the progression of long-bone fracture healing by monitoring the strain on the implantable fracture fixation hardware in real time. In operation, the transmission spectrum of the metamaterial sensor attached to the implantable fixture is changed when an external load is applied to the fixture, and from this change, the strain is recorded remotely. By employing telemetric characterizations, we reduced the operating frequency and enhanced the sensitivity of our novel nested SRR architecture compared to the conventional SRR structure. The nested SRR structure exhibited a higher sensitivity of 1.09 kHz/kgf operating at lower frequency compared to the classical SRR that demonstrated a sensitivity of 0.72 kHz/kgf. Using soft tissue medium, we achieved the best sensitivity level of 4.00 kHz/kgf with our nested SRR sensor. Ultimately, the laboratory characterization and in vivo biocompatibility studies support further development and characterization of a fracture healing system based on implantable nested SRR.

BackgroundOsteosarcoma (OSA) spontaneously arises in the appendicular skeleton of large breed dogs and shares many physiological and molecular biological characteristics with human OSA. The standard treatment for OSA in both species is amputation or limb-sparing surgery, followed by chemotherapy. Unfortunately, OSA is an aggressive cancer with a high metastatic rate. Characterization of OSA with regard to its metastatic potential and chemotherapeutic resistance will improve both prognostic capabilities and treatment modalities.MethodsWe analyzed archived primary OSA tissue from dogs treated with limb amputation followed by doxorubicin or platinum-based drug chemotherapy. Samples were selected from two groups: dogs with disease free intervals (DFI) of less than 100 days (n = 8) and greater than 300 days (n = 7). Gene expression was assessed with Affymetrix Canine 2.0 microarrays and analyzed with a two-tailed t-test. A subset of genes was confirmed using qRT-PCR and used in classification analysis to predict prognosis. Systems-based gene ontology analysis was conducted on genes selected using a standard J5 metric. The genes identified using this approach were converted to their human homologues and assigned to functional pathways using the GeneGo MetaCore platform.ResultsPotential biomarkers were identified using gene expression microarray analysis and 11 differentially expressed (p < 0.05) genes were validated with qRT-PCR (n = 10/group). Statistical classification models using the qRT-PCR profiles predicted patient outcomes with 100% accuracy in the training set and up to 90% accuracy upon stratified cross validation. Pathway analysis revealed alterations in pathways associated with oxidative phosphorylation, hedgehog and parathyroid hormone signaling, cAMP/Protein Kinase A (PKA) signaling, immune responses, cytoskeletal remodeling and focal adhesion.ConclusionsThis profiling study has identified potential new biomarkers to predict patient outcome in OSA and new pathways that may be targeted for therapeutic intervention.