mtDNA Single-Nucleotide Variants Associated with Type 2 Diabetes.

Type 2 diabetes (T2D) is a chronic systemic disease with a complex etiology, characterized by insulin resistance and mitochondrial dysfunction in various cell tissues. To explore this relationship, we conducted a secondary analysis of complete mtDNA sequences from 1261 T2D patients and 1105 control individuals. Our findings revealed significant associations between certain single-nucleotide polymorphisms (SNPs) and T2D. Notably, the variants m.1438A>G (rs2001030) (controls: 32 [27.6%], T2D: 84 [72.4%]; OR: 2.46; 95%CI: 1.64-3.78; p < 0.001), m.14766C>T (rs193302980) (controls: 498 [36.9%], T2D: 853 [63.1%]; OR: 2.57, 95%CI: 2.18-3.04, p < 0.001), and m.16519T>C (rs3937033) (controls: 363 [43.4%], T2D: 474 [56.6%]; OR: 1.24, 95%CI: 1.05-1.47, p = 0.012) were significantly associated with the likelihood of developing diabetes. The variant m.16189T>C (rs28693675), which has been previously documented in several studies across diverse populations, showed no association with T2D in our analysis (controls: 148 [13.39] T2D: 171 [13.56%]; OR: 1.03; 95%CI: 0.815-1.31; p = 0.83). These results provide evidence suggesting a link between specific mtDNA polymorphisms and T2D, possibly related to association rules, topological patterns, and three-dimensional conformations associated with regions where changes occur, rather than specific point mutations in the sequence.

Biomechanics Assessment of Kinematic Parameters of Low-Sprint Start in High-Performance Athletes Using Three Dimensional Motion Capture System

ABSTRACT In a sprint start, the athlete takes up a position with their hands just behind a line, arms vertical, feet generally placed about a shoe length apart, and the hips rising above the line of the head. Mistakes in this position influence the execution of the low-sprint start, and can drastically influence the initial running speed and acceleration achieved by the athlete. Common mistakes occur due to the misconception that athletes must also lean forward, bringing the shoulders ahead of their hands and putting pressure on them. A standard approach to identify sprint start mistakes is to use a stick or weighted string to drop down from the shoulders. The effective implementation of this approach depends on the coach's experience and remains a significant challenge. In this study, a three-dimensional motion capture system with the Vicon® Plug-in-Gait model was used to characterize the kinematic parameters that influence the execution of low-sprint start in six high-performance athletes. The main kinematic parameters are reaction time, stride length, and stride time. The obtained results demonstrate the potential utility of a three-dimensional motion capture system to assess the kinematic parameters of low-sprint start in high-performance athletes.

Risk factors and association of body composition components for lumbar disc herniation in Northwest, Mexico.

The goal of this study was to investigate the association of body composition components and to elucidate whether any of these components is a risk factor for Lumbar Disc Herniation (LDH). The group of study consisted of 90 adults involved in a physical activity program due to overweight and obesity. 19 adults with medical diagnostic through Magnetic Resonance Imaging with LDH. Body composition data was obtained with a bioelectrical impedance analyzer. Descriptive statistics and principal components analysis permitted to analyze the information's structure and to visualize information clusters. A logistic regression analysis allowed us to find the association between some of the variables of body composition with LDH. The Degree of Obesity, Body Mass Index, Visceral Fat Area and the Abdominal Circumference resulted associated (P values of 0.0388, 0.0171, 0.0055 and 0.0032, respectively). The application of Odd Ratio allowed us to declare the Visceral Fat Area and Abdominal Circumference as risk factors to develop Lumbar Disk Herniation. Our results provide a new record for future studies, and support for prescription of physical activity and changes in diet, to correct or prevent the development of LDH in the population of Baja California.

Benefit of oxytocin released by cervix stimulation in Mexican Holstein cattle.

OBJECTIVE: The aim of this research is to investigate the relationship level of oxytocin released and the tactile stimulation of the cervix in Holstein cattle from the northwestern arid regions in México. MATERIALS AND METHODS: The cervixes of 10 Holstein Friesian dairy cows in mid-lactation were manually stimulated for 60 sec. Oxytocin released in the blood was analyzed before and after stimulation. The enzyme-linked immunosorbent assay was used in the analysis to make oxytocin detectable by spectrometry techniques and by converting the luminescence absorbance of each sample into pg per mol. RESULTS: The study revealed that tactile stimulation of the cervix increased oxytocin levels. The highest increase in oxytocin level was 10,940.8222 pg/mol, while the lowest increase in oxytocin level was 1,830.94254 pg/mol. Besides, the milk production by tactile stimulation of the cervix had a higher milk yield and a p-value of 9.4 × 10-4 (p < 0.05) in comparison to the monthly average without tactile stimulation. CONCLUSION: Tactile stimulation of the cervix activates the Ferguson reflex and increases the oxytocin released in the blood and increases the milk released from the alveolar glands.

Genome-Wide SNP Signal Intensity Scanning Revealed Genes Differentiating Cows with Ovarian Pathologies from Healthy Cows.

Hypoplasia and ovarian cysts are the most common ovarian pathologies in cattle. In this genome-wide study we analyzed the signal intensity of 648,315 Single Nucleotide Polymorphisms (SNPs) and identified 1338 genes differentiating cows with ovarian pathologies from healthy cows. The sample consisted of six cows presenting an ovarian pathology and six healthy cows. SNP signal intensities were measured with a genotyping process using the Axiom Genome-Wide BOS 1 SNPchip. Statistical tests for equality of variance and mean were applied to SNP intensities, and significance p-values were obtained. A Benjamini-Hochberg multiple testing correction reveled significant SNPs. Corresponding genes were identified using the Bovine Genome UMD 3.1 annotation. Principal Components Analysis (PCA) confirmed differentiation. An analysis of Copy Number Variations (CNVs), obtained from signal intensities, revealed no evidence of association between ovarian pathologies and CNVs. In addition, a haplotype frequency analysis showed no association with ovarian pathologies. Results show that SNP signal intensity, which captures not only information for base-pair genotypes elucidation, but the amount of fluorescence nucleotide synthetization produced in an enzymatic reaction, is a rich source of information that, by itself or in combination with base-pair genotypes, might be used to implement differentiation, prediction and diagnostic procedures, increasing the scope of applications for Genotyping Microarrays.

A Solar Position Sensor Based on Image Vision.

Solar collector technologies operate with better performance when the Sun beam direction is normal to the capturing surface, and for that to happen despite the relative movement of the Sun, solar tracking systems are used, therefore, there are rules and standards that need minimum accuracy for these tracking systems to be used in solar collectors' evaluation. Obtaining accuracy is not an easy job, hence in this document the design, construction and characterization of a sensor based on a visual system that finds the relative azimuth error and height of the solar surface of interest, is presented. With these characteristics, the sensor can be used as a reference in control systems and their evaluation. The proposed sensor is based on a microcontroller with a real-time clock, inertial measurement sensors, geolocation and a vision sensor, that obtains the angle of incidence from the sunrays' direction as well as the tilt and sensor position. The sensor's characterization proved how a measurement of a focus error or a Sun position can be made, with an accuracy of 0.0426° and an uncertainty of 0.986%, which can be modified to reach an accuracy under 0.01°. The validation of this sensor was determined showing the focus error on one of the best commercial solar tracking systems, a Kipp & Zonen SOLYS 2. To conclude, the solar tracking sensor based on a vision system meets the Sun detection requirements and components that meet the accuracy conditions to be used in solar tracking systems and their evaluation or, as a tracking and orientation tool, on photovoltaic installations and solar collectors.

Analysis of copy number variations in Mexican Holstein cattle using axiom genome-wide Bos 1 array.

Recently, for copy number variation (CNV) analysis, bovine researchers have focused mainly on the use of genome-wide SNP genotyping arrays. One of the highest densities commercially available SNPchips for cattle is the Affymetrix axiom genome-wide Bos 1, which assays 648,315 informative SNPs across the whole bovine genome. Here, we describe the microarray data, quality controls and validation implemented in a study published in Genetics and Molecular Research Journal in 2015 [1]. The microarray raw data has been deposited into Gene Expression Omnibus under accession #GSE54813.

High density LD-based structural variations analysis in cattle genome.

Genomic structural variations represent an important source of genetic variation in mammal genomes, thus, they are commonly related to phenotypic expressions. In this work, ∼ 770,000 single nucleotide polymorphism genotypes from 506 animals from 19 cattle breeds were analyzed. A simple LD-based structural variation was defined, and a genome-wide analysis was performed. After applying some quality control filters, for each breed and each chromosome we calculated the linkage disequilibrium (r2) of short range (≤ 100 Kb). We sorted SNP pairs by distance and obtained a set of LD means (called the expected means) using bins of 5 Kb. We identified 15,246 segments of at least 1 Kb, among the 19 breeds, consisting of sets of at least 3 adjacent SNPs so that, for each SNP, r2 within its neighbors in a 100 Kb range, to the right side of that SNP, were all bigger than, or all smaller than, the corresponding expected mean, and their P-value were significant after a Benjamini-Hochberg multiple testing correction. In addition, to account just for homogeneously distributed regions we considered only SNPs having at least 15 SNP neighbors within 100 Kb. We defined such segments as structural variations. By grouping all variations across all animals in the sample we defined 9,146 regions, involving a total of 53,137 SNPs; representing the 6.40% (160.98 Mb) from the bovine genome. The identified structural variations covered 3,109 genes. Clustering analysis showed the relatedness of breeds given the geographic region in which they are evolving. In summary, we present an analysis of structural variations based on the deviation of the expected short range LD between SNPs in the bovine genome. With an intuitive and simple definition based only on SNPs data it was possible to discern closeness of breeds due to grouping by geographic region in which they are evolving.