Principal components analysis to evaluate complex association of polymorphisms in ACE and ACTN3 genes and the extent of cardiovascular adaptive changes in elite athletes.

BACKGROUND: Present article aims at clarifying the association of ACE and ACTN3 polymorphisms with adaptive heart changes in elite athletes from power, endurance and mixed sport disciplines using the principal component analysis (PCA). METHODS: Overall, 281 elite male athletes are divided into three groups: strength-type sports, endurance and mixed sports. After anthropometric measurements, physical and ultrasound examination of the heart, the athletes were exposed to a physical load test. All groups were analyzed for functional ACE and ACTN3 polymorphisms. In order to convert a set of examined, possibly correlated adaptive cardiovascular changes into a set of values of linearly uncorrelated variables we used principal component analysis (PCA). RESULTS: The type of sport significantly affects not only the athlete's anthropometric characteristics, but also on the scope and specificity of the investigated adaptive cardiovascular changes. Athletes from the mixed group of sports showed the best working efficiency of the heart. PCA showed that the type of sport, but not genetic predisposition affects the co-adaptation of complex traits. CONCLUSIONS: Effect of genotype, type of sport and their interaction on observed variability in morpho-functional cardiovascular adaptive changes in elite athletes can be used for a better understanding of the clinical phenomenon of athlete's heart and sudden cardiac death syndrome.

Assessment of Type 2 Diabetes Risk in Young Women with Polycystic Ovary Syndrome.

Women with polycystic ovary syndrome (PCOS) are at increased risk for dysglycemia and type 2 diabetes compared to healthy BMI-matched women of reproductive age: robust evidence exists supporting this notion. The presence of altered glycemic status in young women with the syndrome presents a distinct challenge for the clinician for several reasons. Firstly, the reported incidence of this disorder varies among the limited available studies. Furthermore, there is a lack of consensus on the best screening method, which women to screen, at what frequency, and which strategies need to be implemented to reduce the above risk. We provide data regarding the prevalence of dysglycemia in young women suffering from PCOS and the pathophysiological mechanisms underlying the disorder. In addition, we present evidence suggesting universal screening with the oral glucose tolerance test in young women with the syndrome, irrespective of age or BMI status, to identify and manage glycemic abnormalities in a timely manner. Regarding follow-up, oral glucose testing should be carried out at regular intervals if there are initial abnormal findings or predisposing factors. Finally, the efficacy of a well-balanced diet in conjunction with regular exercise and the use of non-pharmacologic agents in this specific population is discussed.

Proper death certification in the time of the COVID-19 pandemic: Forensic perspective.

It is well known that the quality of death certificates determines the accuracy of public health mortality data. In the light of a pandemic, forensic pathologists must understand the true definition of a COVID-19 death and the requirements for filling out the death certificate, as these are critical for maintaining accurate and trustworthy mortality data. To determine the scope and evolution of the COVID-19 epidemic, accurate death certification is critical. We believe that COVID-19 should be enlisted under part II or section "note" (if it exists in DC form in a particular country) of the DC in all suicide instances and putrefied bodies with positive autopsy swabs for SARS-CoV-2. In addition to our suggestions for the completion of the DC in some COVID-19 instances, we feel that forensic pathologists should follow the WHO criteria for proper DC completion in COVID-19 cases. Better physician education at this stage of the pandemic would increase adherence to existing (WHO and CDC) standards. As a result, forensic pathologists with competence in death certification could help by teaching treating physicians in this area.

An in-frame deletion mutation in the degron tail of auxin coreceptor IAA2 confers resistance to the herbicide 2,4-D in Sisymbrium orientale.

The natural auxin indole-3-acetic acid (IAA) is a key regulator of many aspects of plant growth and development. Synthetic auxin herbicides such as 2,4-D mimic the effects of IAA by inducing strong auxinic-signaling responses in plants. To determine the mechanism of 2,4-D resistance in a Sisymbrium orientale (Indian hedge mustard) weed population, we performed a transcriptome analysis of 2,4-D-resistant (R) and -susceptible (S) genotypes that revealed an in-frame 27-nucleotide deletion removing nine amino acids in the degron tail (DT) of the auxin coreceptor Aux/IAA2 (SoIAA2). The deletion allele cosegregated with 2,4-D resistance in recombinant inbred lines. Further, this deletion was also detected in several 2,4-D-resistant field populations of this species. Arabidopsis transgenic lines expressing the SoIAA2 mutant allele were resistant to 2,4-D and dicamba. The IAA2-DT deletion reduced binding to TIR1 in vitro with both natural and synthetic auxins, causing reduced association and increased dissociation rates. This mechanism of synthetic auxin herbicide resistance assigns an in planta function to the DT region of this Aux/IAA coreceptor for its role in synthetic auxin binding kinetics and reveals a potential biotechnological approach to produce synthetic auxin-resistant crops using gene-editing.

The relationship between functional capacity and left ventricular strain in patients with uncomplicated type 2 diabetes.

OBJECTIVE: We aimed to evaluate the association between functional capacity and left ventricular (LV) mechanics in the patients with uncomplicated type 2 diabetes. METHODS: The present cross-sectional study included 80 controls and 70 uncomplicated diabetic patients. These participants underwent laboratory analysis, comprehensive echocardiographic examination and cardiopulmonary exercise testing. RESULTS: Global longitudinal (-21.6 ±â€Š2.8 vs. -18.4 ±â€Š2.3%, P < 0.001) and circumferential (-22.0 ±â€Š2.9 vs. -19.5 ±â€Š2.6%, P < 0.001) strains were significantly reduced in diabetic participants. The same was found for longitudinal and circumferential endocardial, mid-myocardial and epicardial strains. Peak oxygen uptake (27.0 ±â€Š4.3 vs. 20.7 ±â€Š4.0 ml/kg/min, P < 0.001) and oxygen pulse (14.1 ±â€Š3.0 vs. 11.6 ±â€Š3.2 ml/beat, P < 0.001) were significantly lower in the diabetic group, while ventilation/carbon dioxide slope was significantly higher in these patients. In the whole study population glycosylated hemoglobin, as well as LV endocardial longitudinal and circumferential strains were independently of other clinical and echocardiographic parameters of LV structure, systolic and diastolic function associated with peak oxygen consumption and oxygen pulse. CONCLUSION: Our investigation showed that diabetes equally affected all LV myocardial layers. Endocardial LV longitudinal and circumferential strains, as well as glycosylated hemoglobin - main parameter of glucose regulation, were independently associated with functional capacity in the whole study population. These findings indicate that determination of LV strain and functional capacity could detect subclinical target organ damage and prevent development of further complications in uncomplicated diabetes mellitus patients.

Association between functional capacity and heart rate variability in patients with uncomplicated type 2 diabetes.

OBJECTIVE: We sought to investigate functional capacity, heart rate variability (HRV), as well as their relationship in the patients with uncomplicated type 2 diabetes. METHODS: This cross-sectional observational study included 62 controls and 53 uncomplicated diabetic patients. Included subjects underwent laboratory analysis, 24-h ECG Holter monitoring and cardiopulmonary exercise testing. RESULTS: All parameters of time and frequency domain of HRV were decreased in the diabetic patients. Oxygen uptake at ventilatory threshold (18.3 ± 3.9 vs. 14.6 ± 3.6 mL/kg/min, p < .001), peak oxygen uptake (peak VO2) (27.8 ± 4.1 vs. 19.5 ± 4.3, mL/kg/min, p < .001) and oxygen pulse were significantly lower in the diabetic group, whereas ventilation/carbon dioxide ratio and ventilation/carbon dioxide slope (25.4 ± 2.5 vs. 28.6 ± 3.9, p < .001) were significantly higher in this group. Furthermore, heart rate recovery in the first minute was significantly lower in the diabetic group (26 ± 5 vs. 23 ± 5 beats/min, p = .003). In the whole study population HbA1c and SDNN were independently of other clinical and HRV parameters associated with peak VO2, ventilation/carbon dioxide slope and heart rate recovery in the first minute. CONCLUSIONS: Our investigation showed that both functional capacity and HRV were significantly impaired in uncomplicated diabetic patients. HbA1c, an important parameter of glucose regulation, was independently associated with HRV parameters and functional capacity in the whole study population. This reveals a potentially important role of determination of functional capacity and cardiac autonomic function as important markers of preclinical damage in diabetic population.

Improved classification accuracy of powdery mildew infection levels of wine grapes by spatial-spectral analysis of hyperspectral images.

BACKGROUND: Hyperspectral imaging is an emerging means of assessing plant vitality, stress parameters, nutrition status, and diseases. Extraction of target values from the high-dimensional datasets either relies on pixel-wise processing of the full spectral information, appropriate selection of individual bands, or calculation of spectral indices. Limitations of such approaches are reduced classification accuracy, reduced robustness due to spatial variation of the spectral information across the surface of the objects measured as well as a loss of information intrinsic to band selection and use of spectral indices. In this paper we present an improved spatial-spectral segmentation approach for the analysis of hyperspectral imaging data and its application for the prediction of powdery mildew infection levels (disease severity) of intact Chardonnay grape bunches shortly before veraison. RESULTS: Instead of calculating texture features (spatial features) for the huge number of spectral bands independently, dimensionality reduction by means of Linear Discriminant Analysis (LDA) was applied first to derive a few descriptive image bands. Subsequent classification was based on modified Random Forest classifiers and selective extraction of texture parameters from the integral image representation of the image bands generated. Dimensionality reduction, integral images, and the selective feature extraction led to improved classification accuracies of up to [Formula: see text] for detached berries used as a reference sample (training dataset). Our approach was validated by predicting infection levels for a sample of 30 intact bunches. Classification accuracy improved with the number of decision trees of the Random Forest classifier. These results corresponded with qPCR results. An accuracy of 0.87 was achieved in classification of healthy, infected, and severely diseased bunches. However, discrimination between visually healthy and infected bunches proved to be challenging for a few samples, perhaps due to colonized berries or sparse mycelia hidden within the bunch or airborne conidia on the berries that were detected by qPCR. CONCLUSIONS: An advanced approach to hyperspectral image classification based on combined spatial and spectral image features, potentially applicable to many available hyperspectral sensor technologies, has been developed and validated to improve the detection of powdery mildew infection levels of Chardonnay grape bunches. The spatial-spectral approach improved especially the detection of light infection levels compared with pixel-wise spectral data analysis. This approach is expected to improve the speed and accuracy of disease detection once the thresholds for fungal biomass detected by hyperspectral imaging are established; it can also facilitate monitoring in plant phenotyping of grapevine and additional crops.