Dynamic Behaviour of High Performance of Sand Surfaces Used in the Sports Industry

The sand surface is considered a critical injury and performance contributing factor in different sports, from beach volleyball to greyhound racing. However, there is still a significant gap in understanding the dynamic behaviour of sport sand surfaces, particularly their vibration behaviour under impact loads. The purpose of this research was to introduce different measurement techniques to the study of sports sand surface dynamic behaviour. This study utilised an experimental drop test, accelerometry, in-situ moisture content and firmness data, to investigate the possible correlation between the sand surface and injuries. The analysis is underpinned by data gathered from greyhound racing and discussed where relevant.</jats:p

An In Vitro Barrier Model of the Human Submandibular Salivary Gland Epithelium Based on a Single Cell Clone of Cell Line HTB-41: Establishment and Application for Biomarker Transport Studies

The blood–saliva barrier (BSB) consists of the sum of the epithelial cell layers of the oral mucosa and salivary glands. In vitro models of the BSB are inevitable to investigate and understand the transport of salivary biomarkers from blood to saliva. Up to now, standardized, cell line-based models of the epithelium of the submandibular salivary gland are still missing for this purpose. Therefore, we established epithelial barrier models of the submandibular gland derived from human cell line HTB-41 (A-253). Single clone isolation resulted in five different clones (B2, B4, B9, D3, and F11). Clones were compared to the parental cell line HTB-41 using measurements of the transepithelial electrical resistance (TEER), paracellular marker permeability assays and analysis of marker expression for acinar, ductal, and myoepithelial cells. Two clones (B9, D3) were characterized to be of acinar origin, one clone (F11) to be of myoepithelial origin and one isolation (B4) derived from two cells, to be presumably a mixture of acinar and ductal origin. Clone B2, presumably of ductal origin, showed a significantly higher paracellular barrier compared to other clones and parental HTB-41. The distinct molecular identity of clone B2 was confirmed by immunofluorescent staining, qPCR, and flow cytometry. Experiments with ferritin, a biomarker for iron storage, demonstrated the applicability of the selected model based on clone B2 for transport studies. In conclusion, five different clones originating from the submandibular gland cell line HTB-41 were successfully characterized and established as epithelial barrier models. Studies with the model based on the tightest clone B2 confirmed its suitability for transport studies in biomarker research

The Development of a Standardized Protocol for Quantifying Equestrian Eventing Cross-Country Ground

The ground has long been cited as a key contributing factor for injury risk in the cross-country phase of eventing. The current study aimed to develop a practically useful standardized protocol for measuring eventing cross country ground. Data collection was split into three phases: Phase 1 (Validation), Phase 2 (Expansion of data set), and Phase 3 (Threshold establishment). During Phase 1, data from nine event courses were collected using an Orono Biomechanical Surface Tester (OBST), Vienna Surface Tester (VST), Lang Penetrometer, Going Stick, and moisture meter. Using linear regression, 80% of the variability in cushioning measured with the OBST was predicted from moisture and VST measurements (p < 0.001). In Phase 2, objective data from 81 event courses and subjective assessments from 180 event riders were collected. In Phase 3, k-means cluster analysis was used to classify the courses into ten clusters based on average course measurements of moisture, cushioning, firmness, stiffness, depth, and coefficient of restitution. Based on cluster membership, course average subjective data (16 courses) were compared using a General Linear Model. Significant differences (p < 0.05) in subjective impact firmness (p = 0.038) and subjective cushioning (p = 0.010) were found between clusters. These data and cluster thresholds provide an event course baseline for future comparisons

Methyl-binding domain protein-based DNA isolation from human blood serum combines DNA analyses and serum-autoantibody testing

<p>Abstract</p> <p>Background</p> <p>Circulating cell free DNA in serum as well as serum-autoantibodies and the serum proteome have great potential to contribute to early cancer diagnostics via non invasive blood tests. However, most DNA preparation protocols destroy the protein fraction and therefore do not allow subsequent protein analyses. In this study a novel approach based on methyl binding domain protein (MBD) is described to overcome the technical difficulties of combining DNA and protein analysis out of one single serum sample.</p> <p>Methods</p> <p>Serum or plasma samples from 98 control individuals and 54 breast cancer patients were evaluated upon silica membrane- or MBD affinity-based DNA isolation via qPCR targeting potential DNA methylation markers as well as by protein-microarrays for tumor-autoantibody testing.</p> <p>Results</p> <p>In control individuals, an average DNA level of 22.8 ± 25.7 ng/ml was detected applying the silica membrane based protocol and 8.5 ± 7.5 ng/ml using the MBD-approach, both values strongly dependent on the serum sample preparation methods used. In contrast to malignant and benign tumor serum samples, cell free DNA concentrations were significantly elevated in sera of metastasizing breast cancer patients. Technical evaluation revealed that serum upon MBD-based DNA isolation is suitable for protein-array analyses when data are consistent to untreated serum samples.</p> <p>Conclusion</p> <p>MBD affinity purification allows DNA isolations under native conditions retaining the protein function, thus for example enabling combined analyses of DNA methylation and autoantigene-profiles from the same serum sample and thereby improving minimal invasive diagnostics.</p

Novel Methods for Surface EMG Analysis and Exploration Based on Multi-Modal Gaussian Mixture Models

<div><p>This paper introduces a new method for data analysis of animal muscle activation during locomotion. It is based on fitting Gaussian mixture models (GMMs) to surface EMG data (sEMG). This approach enables researchers/users to isolate parts of the overall muscle activation within locomotion EMG data. Furthermore, it provides new opportunities for analysis and exploration of sEMG data by using the resulting Gaussian modes as atomic building blocks for a hierarchical clustering. In our experiments, composite peak models representing the general activation pattern per sensor location (one sensor on the long back muscle, three sensors on the gluteus muscle on each body side) were identified per individual for all 14 horses during walk and trot in the present study. Hereby we show the applicability of the method to identify composite peak models, which describe activation of different muscles throughout cycles of locomotion.</p></div