Ultra-wideband microwave precisely and accurately predicts sheepmeat hot carcase GR tissue depth.

A portable ultra-wideband microwave system (MiS) coupled with an antipodal slot Vivaldi patch antenna (VPA) was used as an objective measurement technology to predict sheep meat carcase GR tissue depth, tested against AUS-MEAT national accreditation standards. Experiment one developed the MiS GR tissue depth prediction equation using lamb carcasses (n = 832) from two slaughter groups. To create the prediction equations, a two layered machine learning stacking ensemble technique was used. The performance of this equation was tested within the dataset using a k-fold cross validation (k = 5), which demonstrated excellent precision and accuracy with an average R2 of 0.91, RMSEP 2.11, bias 0.39 and slope 0.03. Experiment two tested the prediction equation against the AUS-MEAT GR tissue depth accreditation framework which stipulates predictions from a device must assign the correct fat score, with a tolerance of ±2 mm of the score boundary, and 90% accuracy. For a device to be accredited three measurements captured within the same device, as well as measurements across three different devices, must meet the AUS-MEAT error thresholds. Three MiS devices scanned lamb carcases (n = 312) across three slaughter days. All three MiS devices met the AUS-MEAT accreditation thresholds, accurately predicting GR tissue depth 96.1-98.4% of the time. Between the different devices, the measurement accuracy was 99.4-100%, and within the same device, the measurement accuracy was 99.7-100%. Based on these results MiS achieved AUS-MEAT device accreditation as an objective technology to predict GR tissue depth.

Predicting lamb carcase composition from tissue depth measured at a single point with an ultrawide-band microwave scanner.

This study evaluated the ability of portable ultra-wide band microwave system (MiS) to predict lamb carcase computed tomography (CT) determined composition % of fat, lean muscle and bone. Lamb carcases (n = 343) from 6 slaughter groups were MiS scanned at the C-site (45 mm from spine midline at the 12th /13th rib) prior to CT scanning to determine the proportion of fat, muscle and bone. A machine learning ensemble stacking technique was used to construct the MiS prediction equations. Predictions were pooled and divided in 5 groups stratified for each CT composition trait (fat, lean or bone%) and a k-fold cross validation (k = 5) technique was used to test the predictions. MiS predicted CT fat% with an average RMSEP of 2.385, R2 0.78, bias 0.156 and slope 0.095. The prediction of CT lean% had an average RMSEP of 2.146, R2 0.64, bias 0.172 and slope 0.117. CT bone% prediction had an average RMSEP of 0.990, R2 0.75, bias 0.051 and slope 0.090. Predictions for CT bone% met AUS-MEAT device accreditation error tolerances on the whole range of the dataset. Predictions for CT lean% and fat% met AUS-MEAT error tolerances on a constrained dataset.

Prediction of lamb carcase C-site fat depth and GR tissue depth using a non-invasive portable microwave system versus body condition scoring.

This study compared portable ultra-wide band microwave system (MiS) versus body condition score to predict C-site fat depth, GR tissue depth and eye muscle depth (EMD) in lambs. Experiment 1 assessed MiS and condition score to predict ultrasound measured C-site and EMD (n = 1549). Precision and accuracy was greatest for the MiS measurement with liveweight included in the model, with a C-site predicted RMSEP of 0.58 mm, R2 0.60 and bias of 0.021 mm and an EMD predicted RMSEP of 2.27 mm, R2 0.72 and bias of 0.088 mm. Experiment 2 (n = 900) assessed pre-slaughter MiS scanning and condition scoring to predict carcase GR tissue depth, C-site fat depth and EMD. MiS performed better than condition score for all three carcase trait predictions, regardless of the inclusion of liveweight, with the highest precision and accuracy for GR tissue depth determination with a RMSEP of 3.68 mm, R2 0.63 and bias 0.072 mm.

Ultrawide band microwave system as a non-invasive technology to predict beef carcase fat depth.

A portable ultra-wide band microwave system (MiS) coupled with an open-ended coaxial probe (OCP) or Antipodal Vivaldi Antenna (VPA) was tested as a non-invasive objective measurement to predict beef carcase single site fat depth at commercial abattoirs. Experiment one tested the effectiveness of MiS coupled with a VPA. The VPA was used to predict hot carcase P8 (fat depth on the rump) across 4 slaughter groups (n = 241). The VPA was also used to predict cold carcase rib fat (at the quartering site, 75% along the rib eye muscle) across 5 slaughter groups (n = 598). Experiment two tested the ability of MiS coupled with OCP to measure hot carcase P8 across two slaughter groups (n = 435). A machine learning stacking ensemble method was used to create the prediction equations. Datasets were grouped by prediction trait (P8 or ribfat) and probe/antenna then randomly divided into 5 groups based on tissue depth. Precision was greatest using OCP to predict P8 fat depth with a RMSEP of 2.47 mm and R2 of 0.70. The VPA precision was similar for the two tissue depths assessed, hot carcase P8 had an average RMSEP of 2.86 mm and R2 of 0.58 compared to cold carcase rib fat RMSEP of 2.60 mm and R2 of 0.55.

Prediction of lamb carcase C-site fat depth and GR tissue depth using a non-invasive portable microwave system.

The experiment evaluated the ability of portable ultra-wide band microwave coupled with a Vivaldi patch antenna to predict carcase C-site fat and GR tissue depth. For C-site, 1070 lambs, across 8 slaughter groups were scanned and for GR, 286 lambs across 2 slaughter groups. Prediction equations for reflected microwave signals were constructed with a partial least squares regression two-components model and a machine learning Ensemble Stacking technique. Models were trained and validated using cross validation methods in actual datasets and then in datasets balanced for tissue depth. The precision and accuracy indicators of microwave predicted C-site fat depth across pooled and balanced datasets were RMSEP 1.53 mm, R2 0.54, and bias of 0.03 mm. The precision and accuracy for GR tissue depth across pooled and balanced datasets were RMSEP 2.57 mm, R2 0.79 and bias of 0.33 mm. Using the AUS-MEAT fat score accreditation framework this device was able to accurately predict GR 92.7% of the time.

A short-term pharmacodynamic model for monitoring aggrecanase activity: injection of monosodium iodoacetate (MIA) in rats and assessment of aggrecan neoepitope release in synovial fluid using novel ELISAs.

OBJECTIVE: To develop a short-term in vivo model in rats, with an enzyme-linked immunosorbent assay (ELISA) readout for specific aggrecanase-cleaved aggrecan fragments, to facilitate testing of aggrecanase inhibitors. METHODS: Monosodium iodoacetate (MIA), a metabolic inhibitor, was injected into the right knee joint of male Lewis rats and the release of aggrecanase-cleaved fragments of aggrecan containing the NITEGE or ARGN neoepitope was measured in the synovial fluid at 7 days post MIA injection using novel ELISAs. The ELISAs utilize a commercial antibody directed against the hyaluronic-acid binding region (HABR) of aggrecan, in combination with either an alpha-NITEGE antibody (NITEGE ELISA) or an alpha-ARGS/BC3 antibody (ARGS ELISA), to detect aggrecanase-cleavage of aggrecan within the interglobular domain (IGD). Aggrecan fragments present in in vitro digests, in cytokine-treated cartilage explant culture supernatants and in rat synovial fluid lavage samples were detected and quantified using the two ELISAs. Small molecule inhibitors of aggrecanase activity were dosed orally on days 3-7 to determine their ability to inhibit MIA-induced generation of the NITEGE and ARGN neoepitopes measured in the rat synovial fluid. RESULTS: The NITEGE assay was shown to specifically detect the N-terminal fragment of aggrecan comprising the G1 domain and the NITEGE neoepitope sequence. This assay can readily measure aggrecanase-cleaved bovine, human and rat aggrecan without the need for deglycosylation. The ARGS assay specifically detects C-terminal fragments of aggrecan comprising the ARGS/ARGN neoepitope and the G2 domain. Keratan sulfate (KS) residues of aggrecan interfere with this ELISA, and hence this assay works well with native rat articular cartilage aggrecan (that lacks KS residues) and with deglycosylated bovine and human aggrecan. Injection of MIA into the rat knee joints resulted in a time-dependent increase in the release of aggrecanase-cleaved aggrecan fragments into the synovial fluid and treatment with an aggrecanase inhibitor resulted in a dose-dependent inhibition of the generation of these neoepitopes. CONCLUSIONS: We have established a short-term in vivo model in rats that involves measurement of synovial fluid biomarkers that are dependent on aggrecanase activity in the joint. The short duration of the model combined with the mechanistic biomarker readout makes it very useful for the initial in vivo screening of aggrecanase inhibitors prior to testing them in time and resource-intensive disease models of osteoarthritis (OA).

Development of a novel clinical biomarker assay to detect and quantify aggrecanase-generated aggrecan fragments in human synovial fluid, serum and urine.

OBJECTIVE: Proteolytic degradation of aggrecan in articular cartilage is a hallmark feature of osteoarthritis (OA). The present study was aimed at developing a sensitive enzyme linked immunosorbent assay (ELISA) for the detection of aggrecanase-cleaved fragments of aggrecan in human serum and urine to facilitate the clinical development of aggrecanase inhibitors for OA. METHODS: The BC3 monoclonal antibody that detects the ARGS neoepitope sequence in aggrecanase-cleaved aggrecan was engineered and optimized using complementarity determining region (CDR)-saturation mutagenesis to improve its binding affinity to the neoepitope. A sandwich ELISA (BC3-C2 ELISA) was developed using the optimized alpha-ARGS antibody (BC3-C2) as capture antibody and a commercially available antibody directed against the hyaluronic-acid binding region (HABR) of aggrecan as detection antibody. Aggrecanase-cleaved fragments of aggrecan present in in vitro digests, human cartilage explant culture supernatants and in human synovial fluid, serum and urine were detected and quantified using this ELISA. RESULTS: The optimized antibody had a 4-log improvement in affinity for the ARGS containing peptide compared to the parental BC3 antibody, while maintaining the ability to not cross-react with a spanning peptide. The BC3-C2 ELISA demonstrated the ability to detect aggrecanase-cleaved aggrecan fragments in the native state, without the need for deglycosylation. This ELISA was able to measure aggrecanase-generated ARGS containing aggrecan fragments in human articular cartilage (HAC) explant cultures in the basal state (without cytokine stimulation). Treatment with an aggrecanase inhibitor resulted in a dose-dependent inhibition of ARGS neoepitope released into the culture supernatant. The ELISA assay also enabled the detection of ARGS containing fragments in human synovial fluid, serum and urine, suggesting its potential utility as a biomarker of aggrecanase activity. CONCLUSIONS: We have developed a novel ELISA using an optimized ARGS antibody and have demonstrated for the first time, an ELISA-based measurement of aggrecan degradation products in human serum and urine. This assay has the potential to serve as a mechanistic drug activity biomarker in the clinic and is expected to significantly impact/accelerate the clinical development of aggrecanase inhibitors and other disease modifying drugs for OA.