Identification of approximate symmetries in biological development

Virtually all forms of life, from single-cell eukaryotes to complex, highly differentiated multicellular organisms, exhibit a property referred to as symmetry. However, precise measures of symmetry are often difficult to formulate and apply in a meaningful way to biological systems, where symmetries and asymmetries can be dynamic and transient, or be visually apparent but not reliably quantifiable using standard measures from mathematics and physics. Here, we present and illustrate a novel measure that draws on concepts from information theory to quantify the degree of symmetry, enabling the identification of approximate symmetries that may be present in a pattern or a biological image. We apply the measure to rotation, reflection and translation symmetries in patterns produced by a Turing model, as well as natural objects (algae, flowers and leaves). This method of symmetry quantification is unbiased and rigorous, and requires minimal manual processing compared to alternative measures. The proposed method is therefore a useful tool for comparison and identification of symmetries in biological systems, with potential future applications to symmetries that arise during development, as observed in vivo or as produced by mathematical models. This article is part of the theme issue ‘Recent progress and open frontiers in Turing’s theory of morphogenesis’.

Space: The Re-Visioning Frontier of Biological Image Analysis with Graph Theory, Computational Geometry, and Spatial Statistics

Every biological image contains quantitative data that can be used to test hypotheses about how patterns were formed, what entities are associated with one another, and whether standard mathematical methods inform our understanding of biological phenomena. In particular, spatial point distributions and polygonal tessellations are particularly amendable to analysis with a variety of graph theoretic, computational geometric, and spatial statistical tools such as: Voronoi polygons; Delaunay triangulations; perpendicular bisectors; circumcenters; convex hulls; minimal spanning trees; Ulam trees; Pitteway violations; circularity; Clark-Evans spatial statistics; variance to mean ratios; Gabriel graphs; and, minimal spanning trees. Furthermore, biologists have developed a number of empirically related correlations for polygonal tessellations such as: Lewis’s law (the number of edges of convex polygons are positively correlated with the areas of these polygons): Desch’s Law (the number of edges of convex polygons are positively correlated with the perimeters of these polygons); and Errara’s Law (daughter cell areas should be roughly half that of their parent cells’ areas). We introduce a new Pitteway Law that the number of sides of the convex polygons in a Voronoi tessellation of biological epithelia is proportional to the minimal interior angle of the convex polygons as angles less than 90 degrees result in Pitteway violations of the Delaunay dual of the Voronoi tessellation.

The Value of Biological Image Technology in Improving Athletes’ Motor Skills

Objective. To explore the value of biological image technology in improving athletes’ motor skills. Methods. Golfers were given biofeedback relaxation training, and the variation trend and influence of biofeedback training on athletes’ heart rate variability were explored by monitoring and feedback evaluation of athletes’ heart rate variability. Results. Biofeedback relaxation training can help athletes improve the balance of sympathetic nerve and parasympathetic nerve, effectively inhibit the activity of sympathetic nerve, enhance the tension, effectively increase the heart rate variability of athletes, and strengthen the ability of psychological relaxation. Conclusion. Part of the research results show that biofeedback training can enhance athletes’ athletic performance and improve their athletic performance to a certain extent.

REDUCING THE SPORTS INJURY THROUGH FUNCTION MOVEMENT BIOLOGICAL IMAGE DATA SCREENING

ABSTRACT Introduction Among the many cases of sports injuries, the incidence of musculoskeletal injuries remains high. After a musculoskeletal injury occurs, athletes often need to suspend training and undergo rehabilitation. A suitable sport mode requires athletes to have sufficient joint range of motion, core stability, and balance ability in different positions to complete various complex movements in training and competition. Objective The paper analyzes the impact of warm-up exercises before the test on the test results of functional sports biological image data screening ( FMS TM ) and provides references for unifying test conditions, checking the reliability of FMS TM repeated tests, and discussing the comparability of the research results. Methods The paper used the same password and process to test 12 young male volleyball professional athletes without warm-up and warm-up. The two-dimensional motion analysis system Dartfish Pursuit 8.0 was used to analyze the video data recorded by the two cameras simultaneously. Results In the two tests before and after, the hurdle step score (1.75±0.62 vs. 2.42±0.52) and the total score (13.50±2.20 vs. 16.42±2.15) were significantly higher than those without the warm-up test (P<0.01). Besides, in squats (1.58±0.67 vs. 1.92±0.67), straight lunges (2.00±0.43 vs. 2.50±0.52), active straight leg lifts (1.50±0.67 vs. 2.00±0.60), rotation stability (1.42) ±0.52 vs. 1.92±0.29) showed a significant increase in the score (P<0.05). Conclusions Warm-up exercises before the test can improve the test results. This abnormal movement pattern observed only by visual inspection may not truly reflect the “dysfunction” of the movement. In the case of ignoring the pre-test warm-up factors, feedback on sports performance and formulating training strategies, this conclusion of predicting injury risk and evaluating training effects may have specific limitations in its reference value. Level of evidence II; Therapeutic studies - investigation of treatment results.

EFFECT OF METABOLIC ENZYMES ON ACCELERATION ABILITY IN EXERCISE FATIGUE

ABSTRACT Introduction Study the relationship between the metabolic enzyme and the biological image, filtered by an adaptive filtering algorithm. Objective The research aims to In this study, human metabolic enzymes were evaluated by electrocardiogram and electromyogram images, and an adaptive filtering algorithm removed the noises in the images. Methods The electrocardiogram and electromyogram images at different periods were obtained, and the calculation method and application scope of the adaptive filtering algorithm were analysed. Results Adaptive filter was designed by the combination of adaptive filtering algorithm and dynamic information. Therefore, the artefact of the image was removed. Conclusions The adaptive filtering algorithm can effectively remove the noise or artefact in electrocardiogram and electromyogram signals. The optimal image information can be obtained. Level of evidence II; Therapeutic studies - investigation of treatment results.

IMPROVED BIOLOGICAL IMAGE TRACKING ALGORITHM OF ATHLETE’S CERVICAL SPINE HEALTH

ABSTRACT Introduction This paper research an improved biological image tracking algorithm of athlete’s cervical spine health under color feedback. Objective A new algorithm is proposed to improve the accuracy of detection and tracking. Methods In this study, the first thing is to apply the color feedback algorithm to improve and optimize the Improved Camshift algorithm. The optimized algorithm was used to track the center of the image, and the video was processed frame by frame. The center position of the tracking frame was obtained. Results The average number of head twists per person is 39 times. Among the three groups, children twisted the least, and older adults twisted the most. Conclusion The algorithm proposed in this study has certain effectiveness and superiority and can be well applied to detecting the number of head twists during exercise. Level of evidence II; Therapeutic studies - investigation of treatment results.

Space: The Re-visioning Frontier of Biological Image Analysis with Graph Theory, Computational Geometry, and Spatial Statistics

Every biological image contains quantitative data that can be used to test hypotheses about how patterns were formed, what entities are associated with one another, and whether standard mathematical methods inform our understanding of biological phenomena. In particular, spatial point distributions and polygonal tessellations are particularly amendable to analysis with a variety of graph theoretic, computational geometric, and spatial statistical tools such as: Voronoi Polygons; Delaunay Triangulations; Perpendicular Bisectors; Circumcenters; Convex Hulls; Minimal Spanning Trees; Ulam Trees; Pitteway Violations; Circularity; Clark-Evans spatial statistics; Variance to Mean Ratios; Gabriel Graphs; and, Minimal Spanning Trees. Furthermore, biologists have developed a number of empirically related correlations for polygonal tessellations such as: Lewis’s Law (the number of edges of convex polygons are positively correlated with the areas of these polygons): Desch’s Law (the number of edges of convex polygons are positively correlated with the perimeters of these polygons); and Errara’s Law (daughter cell areas should be roughly half that of their parent cells’ areas). We introduce a new Pitteway Law that the number of sides of the convex polygons in a Voronoi tessellation of biological epithelia is proportional to the minimal interior angle of the convex polygons as angles less than 90 degrees result in Pitteway violations of the Delaunay dual of the Voronoi tessellation.

ANALYSIS OF ULTRASOUND IMAGE BIOLOGICAL IMAGE ALGORITHM IN THE RESTORATION OF MUSCLE GROUP MOVEMENT FUNCTION

ABSTRACT Objective: By studying the recognition effect of ultrasonic biological image data analysis on muscle group motion function, the evaluation value and significance of ultrasonic biomedical image combination algorithm on muscle group motion function are discussed. Methods: A Gabor filtering algorithm is proposed to smooth the original image. The MVEF algorithm is used to enhance the ultrasonic image and binary further the image again. Using the principle of the Hove transform, the thickness of the muscle is automatically estimated. Results: The square of correlation coefficients of the manual measurement method, Gabor filtering algorithm and MVEF algorithm are 91.3%, 91.3% and 87.8%, respectively. The difference between the manual measurement and the estimation based on the Gabor filtering algorithm is 1.45 ± 0.48mm. The difference between the results of manual measurement and the MVEF algorithm is 1.38 ± 0.56mm. The computation time of the MVEF algorithm and Gabor algorithm are 5 seconds and 0.3 seconds, respectively. Conclusions: The algorithm proposed in this study can effectively measure the muscle thickness, fast, convenient and accurate, and can reflect the contractility of skeletal muscle well, which is of great value for the recognition and evaluation of muscle group movement function. Level of evidence II; Therapeutic studies - investigation of treatment results.

FUNCTIONAL ACTION BIOLOGICAL IMAGE DATA SCREENING METHOD TO REDUCE SPORTS INJURY

ABSTRACT Introduction: The Functional Movement Test (FMS) is an evaluation method for the basic movement patterns of the human body that is designed by Gray Cook. Objective: This paper explores the application value of functional action test (FMS) biological image data in the risk assessment of sports injuries of Chinese rugby players. Methods: Taking the active national football team and provincial football players as the object, the standard FMS test is used to collect the data to determine the best deadline for the total FMS score. Results: The area under the ROC curve (AUC) of the overall athletes, men and women was significantly different from the assumption of AUC=0.5, which were 0.780 (P=0.000), 0.877 (P=0.001), 0.7130 (P=0.013); The best cutoff points corresponding to the total score of FMS are 13.5 points, 15.5 points, and 13.5 points, respectively. The chi-square test showed that the prevalence of the positive group (the total FMS score was less than the corresponding cutoff point) was significantly higher than the negative group (the total FMS score was greater than the corresponding cutoff point) (P<0.01). The OR values of the total athlete, male and female FMS total score positive groups were 25.85 (95%CI: 3.34∼200.23), 25.00 (95%CI: 2.36∼264.80), 14.22 (95%CI: 1.76∼114.92). Conclusions: Among Chinese rugby players, the total score of FMS has a strong correlation with non-contact sports injuries. The score is 13.5 for women and 15.5 for men. Level of evidence II; Therapeutic studies - investigation of treatment results.