Sensor data classification for the indication of lameness in sheep

Lameness is a vital welfare issue in most sheep farming countries, including the UK. The pre-detection at the farm level could prevent the disease from becoming chronic. The development of wearable sensor technologies enables the idea of remotely monitoring the changes in animal movements which relate to lameness. In this study, 3D-acceleration, 3D-orientation, and 3D-linear acceleration sensor data were recorded at ten samples per second via the sensor attached to sheep neck collar. This research aimed to determine the best accuracy among various supervised machine learning techniques which can predict the early signs of lameness while the sheep are walking on a flat field. The most influencing predictors for lameness indication were also addressed here. The experimental results revealed that the Decision Tree classifier has the highest accuracy of 75.46%, and the orientation sensor data (angles) around the neck are the strongest predictors to differentiate among severely lame, mildly lame and sound classes of sheep

Viperin mRNA is a novel target for the human RNase MRP/RNase P endoribonuclease

RNase MRP is a conserved endoribonuclease, in humans consisting of a 267-nucleotide RNA associated with 7–10 proteins. Mutations in its RNA component lead to several autosomal recessive skeletal dysplasias, including cartilage-hair hypoplasia (CHH). Because the known substrates of mammalian RNase MRP, pre-ribosomal RNA, and RNA involved in mitochondrial DNA replication are not likely involved in CHH, we analyzed the effects of RNase MRP (and the structurally related RNase P) depletion on mRNAs using DNA microarrays. We confirmed the upregulation of the interferon-inducible viperin mRNA by RNAi experiments and this appeared to be independent of the interferon response. We detected two cleavage sites for RNase MRP/RNase P in the coding sequence of viperin mRNA. This is the first study providing direct evidence for the cleavage of a mRNA by RNase MRP/RNase P in human cells. Implications for the involvement in the pathophysiology of CHH are discussed

Interplay between Kinase Domain Autophosphorylation and F-Actin Binding Domain in Regulating Imatinib Sensitivity and Nuclear Import of BCR-ABL

BACKGROUND: The constitutively activated BCR-ABL tyrosine kinase of chronic myeloid leukemia (CML) is localized exclusively to the cytoplasm despite the three nuclear localization signals (NLS) in the ABL portion of this fusion protein. The NLS function of BCR-ABL is re-activated by a kinase inhibitor, imatinib, and in a kinase-defective BCR-ABL mutant. The mechanism of this kinase-dependent inhibition of the NLS function is not understood. METHODOLOGY/PRINCIPAL FINDINGS: By examining the subcellular localization of mutant BCR-ABL proteins under conditions of imatinib and/or leptomycin B treatment to inhibit nuclear export, we have found that mutations of three specific tyrosines (Y232, Y253, Y257, according to ABL-1a numbering) in the kinase domain can inhibit the NLS function of kinase-proficient and kinase-defective BCR-ABL. Interestingly, binding of imatinib to the kinase-defective tyrosine-mutant restored the NLS function, suggesting that the kinase domain conformation induced by imatinib-binding is critical to the re-activation of the NLS function. The C-terminal region of ABL contains an F-actin binding domain (FABD). We examined the subcellular localization of several FABD-mutants and found that this domain is also required for the activated kinase to inhibit the NLS function; however, the binding to F-actin per se is not important. Furthermore, we found that some of the C-terminal deletions reduced the kinase sensitivity to imatinib. CONCLUSIONS/SIGNIFICANCE: Results from this study suggest that an autophosphorylation-dependent kinase conformation together with the C-terminal region including the FABD imposes a blockade of the BCR-ABL NLS function. Conversely, conformation of the C-terminal region including the FABD can influence the binding affinity of imatinib for the kinase domain. Elucidating the structural interactions among the kinase domain, the NLS region and the FABD may therefore provide insights on the design of next generation BCR-ABL inhibitors for the treatment of CML

c-Abl phosphorylation of ΔNp63α is critical for cell viability

The p53 family member p63 has been shown to be critical for growth, proliferation and chemosensitivity. Here we demonstrate that the c-Abl tyrosine kinase phosphorylates the widely expressed ΔNp63α isoform and identify multiple sites by mass spectrometry in vitro and in vivo. Phopshorylation by c-Abl results in greater protein stability of both ectopically expressed and endogenous ΔNp63α. c-Abl phosphorylation of ΔNp63α induces its binding to Yes-associated protein (YAP) and silencing of YAP by siRNA reduces the c-Abl-induced increase of ΔNp63α levels. We further show that cisplatin induces c-Abl phosphorylation of ΔNp63α and its binding to YAP. Overexpression of ΔNp63α, but not the c-Abl phosphosites mutant, protects cells from cisplatin treatment. Finally, we demonstrate the rescue of p63 siRNA-mediated loss of viability with p63siRNA insensitive construct of ΔNp63α but not the phosphosites mutant. These results demonstrate that c-Abl phosphorylation of ΔNp63α regulates its protein stability, by inducing binding of YAP, and is critical for cell viability

Sensor data classification for the indication of lameness in sheep

Lameness is a vital welfare issue in most sheep farming countries, including the UK. The pre-detection at the farm level could prevent the disease from becoming chronic. The development of wearable sensor technologies enables the idea of remotely monitoring the changes in animal movements which relate to lameness. In this study, 3D-acceleration, 3D-orientation, and 3D-linear acceleration sensor data were recorded at ten samples per second via the sensor attached to sheep neck collar. This research aimed to determine the best accuracy among various supervised machine learning techniques which can predict the early signs of lameness while the sheep are walking on a flat field. The most influencing predictors for lameness indication were also addressed here. The experimental results revealed that the Decision Tree classifier has the highest accuracy of 75.46%, and the orientation sensor data (angles) around the neck are the strongest predictors to differentiate among severely lame, mildly lame and sound classes of sheep

Recording behaviour of indoor-housed farm animals automatically using machine vision technology: a systematic review

Large-scale phenotyping of animal behaviour traits is time consuming and has led to increased demand for technologies that can automate these procedures. Automated tracking of animals has been successful in controlled laboratory settings, but recording from animals in large groups in highly variable farm settings presents challenges. The aim of this review is to provide a systematic overview of the advances that have occurred in automated, high throughput image detection of farm animal behavioural traits with welfare and production implications. Peer-reviewed publications written in English were reviewed systematically following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. After identification, screening, and assessment for eligibility, 108 publications met these specifications and were included for qualitative synthesis. Data collected from the papers included camera specifications, housing conditions, group size, algorithm details, procedures, and results. Most studies utilized standard digital colour video cameras for data collection, with increasing use of 3D cameras in papers published after 2013. Papers including pigs (across production stages) were the most common (n = 63). The most common behaviours recorded included activity level, area occupancy, aggression, gait scores, resource use, and posture. Our review revealed many overlaps in methods applied to analysing behaviour, and most studies started from scratch instead of building upon previous work. Training and validation sample sizes were generally small (mean±s.d. groups = 3.8±5.8) and in data collection and testing took place in relatively controlled environments. To advance our ability to automatically phenotype behaviour, future research should build upon existing knowledge and validate technology under commercial settings and publications should explicitly describe recording conditions in detail to allow studies to be reproduced

Hierarchical Modeling of Activation Mechanisms in the ABL and EGFR Kinase Domains: Thermodynamic and Mechanistic Catalysts of Kinase Activation by Cancer Mutations

Structural and functional studies of the ABL and EGFR kinase domains have recently suggested a common mechanism of activation by cancer-causing mutations. However, dynamics and mechanistic aspects of kinase activation by cancer mutations that stimulate conformational transitions and thermodynamic stabilization of the constitutively active kinase form remain elusive. We present a large-scale computational investigation of activation mechanisms in the ABL and EGFR kinase domains by a panel of clinically important cancer mutants ABL-T315I, ABL-L387M, EGFR-T790M, and EGFR-L858R. We have also simulated the activating effect of the gatekeeper mutation on conformational dynamics and allosteric interactions in functional states of the ABL-SH2-SH3 regulatory complexes. A comprehensive analysis was conducted using a hierarchy of computational approaches that included homology modeling, molecular dynamics simulations, protein stability analysis, targeted molecular dynamics, and molecular docking. Collectively, the results of this study have revealed thermodynamic and mechanistic catalysts of kinase activation by major cancer-causing mutations in the ABL and EGFR kinase domains. By using multiple crystallographic states of ABL and EGFR, computer simulations have allowed one to map dynamics of conformational fluctuations and transitions in the normal (wild-type) and oncogenic kinase forms. A proposed multi-stage mechanistic model of activation involves a series of cooperative transitions between different conformational states, including assembly of the hydrophobic spine, the formation of the Src-like intermediate structure, and a cooperative breakage and formation of characteristic salt bridges, which signify transition to the active kinase form. We suggest that molecular mechanisms of activation by cancer mutations could mimic the activation process of the normal kinase, yet exploiting conserved structural catalysts to accelerate a conformational transition and the enhanced stabilization of the active kinase form. The results of this study reconcile current experimental data with insights from theoretical approaches, pointing to general mechanistic aspects of activating transitions in protein kinases

Intracellular retention of ABL kinase inhibitors determines commitment to apoptosis in CML cells

Clinical development of imatinib in CML established continuous target inhibition as a paradigm for successful tyrosine kinase inhibitor (TKI) therapy. However, recent reports suggested that transient potent target inhibition of BCR-ABL by highdose TKI (HD-TKI) pulse-exposure is sufficient to irreversibly commit cells to apoptosis. Here, we report a novel mechanism of prolonged intracellular TKI activity upon HD-TKI pulse-exposure (imatinib, dasatinib) in BCR-ABL-positive cells. Comprehensive mechanistic exploration revealed dramatic intracellular accumulation of TKIs which closely correlated with induction of apoptosis. Cells were rescued from apoptosis upon HD-TKI pulse either by repetitive drug wash-out or by overexpression of ABC-family drug transporters. Inhibition of ABCB1 restored sensitivity to HD-TKI pulse-exposure. Thus, our data provide evidence that intracellular drug retention crucially determines biological activity of imatinib and dasatinib. These studies may refine our current thinking on critical requirements of TKI dose and duration of target inhibition for biological activity of TKIs.Daniel B. Lipka, Marie-Christine Wagner, Marek Dziadosz, Tina Schnöder, Florian Heidel, Mirle Schemionek, Junia V. Melo, Thomas Kindler, Carsten Müller-Tidow, Steffen Koschmieder and Thomas Fische