Automatic detection of break-over phase onset in horses using hoof-mounted inertial measurement unit sensors

A prolonged break-over phase might be an indication of a variety of musculoskeletal disorders and can be measured with optical motion capture (OMC) systems, inertial measurement units (IMUs) and force plates. The aim of this study was to present two algorithms for automatic detection of the break-over phase onset from the acceleration and angular velocity signals measured by hoof-mounted IMUs in walk and trot on a hard surface. The performance of these algorithms was evaluated by internal validation with an OMC system and a force plate separately. Seven Warmblood horses were equipped with two wireless IMUs which were attached to the lateral wall of the right front (RF) and hind (RH) hooves. Horses were walked and trotted over a force plate for internal validation while simultaneously the 3D position of three reflective markers, attached to lateral heel, lateral toe and lateral coronet of each hoof, were measured by six infrared cameras of an OMC system. The performance of the algorithms was evaluated by linear mixed model analysis. The acceleration algorithm was the most accurate with an accuracy between -9 and 23 ms and a precision around 24 ms (against OMC system), and an accuracy between -37 and 20 ms and a precision around 29 ms (against force plate), depending on gait and hoof. This algorithm seems promising for quantification of the break-over phase onset although the applicability for clinical purposes, such as lameness detection and evaluation of trimming and shoeing techniques, should be investigated more in-depth

Variation in detected adverse events using trigger tools: A systematic review and meta-analysis

Adverse event (AE) detection is a major patient safety priority. However, despite extensive research on AEs, reported incidence rates vary widely.; This study aimed: (1) to synthesize available evidence on AE incidence in acute care inpatient settings using Trigger Tool methodology; and (2) to explore whether study characteristics and study quality explain variations in reported AE incidence.; Systematic review and meta-analysis.; To identify relevant studies, we queried PubMed, EMBASE, CINAHL, Cochrane Library and three journals in the patient safety field (last update search 25.05.2022). Eligible publications fulfilled the following criteria: adult inpatient samples; acute care hospital settings; Trigger Tool methodology; focus on specialty of internal medicine, surgery or oncology; published in English, French, German, Italian or Spanish. Systematic reviews and studies addressing adverse drug events or exclusively deceased patients were excluded. Risk of bias was assessed using an adapted version of the Quality Assessment Tool for Diagnostic Accuracy Studies 2. Our main outcome of interest was AEs per 100 admissions. We assessed nine study characteristics plus study quality as potential sources of variation using random regression models. We received no funding and did not register this review.; Screening 6,685 publications yielded 54 eligible studies covering 194,470 admissions. The cumulative AE incidence was 30.0 per 100 admissions (95% CI 23.9-37.5; I2 = 99.7%) and between study heterogeneity was high with a prediction interval of 5.4-164.7. Overall studies' risk of bias and applicability-related concerns were rated as low. Eight out of nine methodological study characteristics did explain some variation of reported AE rates, such as patient age and type of hospital. Also, study quality did explain variation.; Estimates of AE studies using trigger tool methodology vary while explaining variation is seriously hampered by the low standards of reporting such as the timeframe of AE detection. Specific reporting guidelines for studies using retrospective medical record review methodology are necessary to strengthen the current evidence base and to help explain between study variation

Survey of Hemileia vastatrix races from Peru to identify potential coffee mutants with disease resistance

info:eu-repo/semantics/publishedVersio

Comprehensive screening and quantification of veterinary drugs in milk using UPLC–ToF-MS

Ultra-performance liquid chromatography combined with time-of-flight mass spectrometry (UPLC–ToF-MS) has been used for screening and quantification of more than 100 veterinary drugs in milk. The veterinary drugs represent different classes including benzimidazoles, macrolides, penicillins, quinolones, sulphonamides, pyrimidines, tetracylines, nitroimidazoles, tranquillizers, ionophores, amphenicols and non-steroidal anti-inflammatory agents (NSAIDs). After protein precipitation, centrifugation and solid-phase extraction (SPE), the extracts were analysed by UPLC–ToF-MS. From the acquired full scan data the drug-specific ions were extracted for construction of the chromatograms and evaluation of the results. The analytical method was validated according to the EU guidelines (2002/657/EC) for a quantitative screening method. At the concentration level of interest (MRL level) the results for repeatability (%RSD < 20% for 86% of the compounds), reproducibility (%RSD < 40% for 96% of the compounds) and the accuracy (80–120% for 88% of the compounds) were satisfactory. Evaluation of the CCβ values and the linearity results demonstrates that the developed method shows adequate sensitivity and linearity to provide quantitative results. Furthermore, the method is accurate enough to differentiate between suspected and negative samples or drug concentrations below or above the MRL. A set of 100 samples of raw milk were screened for residues. No suspected (positive) results were obtained except for the included blind reference sample containing sulphamethazine (88 μg/l) that tested positive for this compound. UPLC–ToF-MS combines high resolution for both LC and MS with high mass accuracy which is very powerful for the multi-compound analysis of veterinary drugs. The technique seems to be powerful enough for the analysis of not only veterinary drugs but also organic contaminants like pesticides, mycotoxins and plant toxins in one single method

Enhancing Crop Gene Pools with Beneficial Traits Using Wild Relatives

This review covers genetic resources from wild relatives; barriers and approaches to interspecific gene transfer; beneficial traits from wild relatives that contribute to the gene pool; biotechnological approaches to increase the utilization of wild relatives in crop improvement; and some results of usage of wild relatives in plant breeding

Identification of candidate genome regions controlling disease resistance in Arachis

<p>Abstract</p> <p>Background</p> <p>Worldwide, diseases are important reducers of peanut (<it>Arachis hypogaea</it>) yield. Sources of resistance against many diseases are available in cultivated peanut genotypes, although often not in farmer preferred varieties. Wild species generally harbor greater levels of resistance and even apparent immunity, although the linkage of agronomically un-adapted wild alleles with wild disease resistance genes is inevitable. Marker-assisted selection has the potential to facilitate the combination of both cultivated and wild resistance loci with agronomically adapted alleles. However, in peanut there is an almost complete lack of knowledge of the regions of the <it>Arachis </it>genome that control disease resistance.</p> <p>Results</p> <p>In this work we identified candidate genome regions that control disease resistance. For this we placed candidate disease resistance genes and QTLs against late leaf spot disease on the genetic map of the A-genome of <it>Arachis</it>, which is based on microsatellite markers and legume anchor markers. These marker types are transferable within the genus <it>Arachis </it>and to other legumes respectively, enabling this map to be aligned to other <it>Arachis </it>maps and to maps of other legume crops including those with sequenced genomes. In total, 34 sequence-confirmed candidate disease resistance genes and five QTLs were mapped.</p> <p>Conclusion</p> <p>Candidate genes and QTLs were distributed on all linkage groups except for the smallest, but the distribution was not even. Groupings of candidate genes and QTLs for late leaf spot resistance were apparent on the upper region of linkage group 4 and the lower region of linkage group 2, indicating that these regions are likely to control disease resistance.</p