Yazar "Kurtoglu, Ahmet" seçeneğine göre listele

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    Isokinetic knee strength as a predictor of cardiorespiratory responses during loaded aerobic capacity test in elite athletes
    (Nature Portfolio, 2025) Car, Bekir; Kurtoglu, Ahmet; Atar, Ozdemir; Turkmen, Musa; Eken, Ozgur; Soyler, Mehmet; Aldhahi, Monira I.
    This study aimed to investigate the predictive capacity of knee isokinetic strength parameters on cardiorespiratory responses during aerobic capacity test (ACT). It provides novel insights into the interplay between muscular strength and cardiorespiratory function through comparative analyses of loaded and unloaded ACT protocols in elite athletes. Thirty elite modern pentathlon athletes (age: 21.43 +/- 0.77 years) underwent isokinetic knee strength assessments at angular velocities of 60 degrees/s and 240 degrees/s. Cardiorespiratory parameters-average breath volume (ABV), average breath frequency (ABF), auxiliary oxygen density (AOD), and heart rate (HR)-were recorded during the Bruce Protocol conducted under two conditions: unloaded and with a 10 kg loaded vest. Relationships between isokinetic strength metrics and cardiorespiratory parameters were analyzed using linear regression models. There were no significant differences in ABV, ABF, or AOD between loaded and unloaded ACT conditions (p > .05). However, HR was significantly lower during loaded ACT (p < .05). Linear regression revealed that at 60 degrees/s, several knee strength parameters, including peak torque extension (PT-EXT), peak torque flexion (PT-FLX), total work flexion (TW-FLX), average power flexion (AP-FLX), and agonist strength (AGANT), significantly predicted ABV during loaded ACT (R-2 = 0.804, p = .004). A similar pattern was observed at 240 degrees/s, where comparable predictors explained a significant variance in ABV (R-2 = 0.761, p = .012). No significant predictive relationships were identified during unloaded ACT. Isokinetic knee strength parameters significantly predict cardiorespiratory responses during loaded ACT but not during unloaded protocols. These findings suggest that isokinetic strength assessments may be a valuable tool for optimizing ACT prescription and monitoring training adaptations in elite athletes.
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    Machine Learning-Based Validation of LDHC and SLC35G2 Methylation as Epigenetic Biomarkers for Food Allergy
    (Mdpi, 2025) Kilicarslan, Sabire; Cicekliyurt, Meliha Merve Hiz; Kilicarslan, Serhat; Hassan, Dina S. M.; Samee, Nagwan Abdel; Kurtoglu, Ahmet
    Background: Food allergies represent a growing global health concern, yet the current diagnostic methods often fail to distinguish between true allergies and food sensitivities, leading to misdiagnoses and inadequate treatment. Epigenetic alterations, such as DNA methylation (DNAm), may offer novel biomarkers for precise diagnosis. Methods: This study employed a computational machine learning framework integrated with DNAm data to identify potential biomarkers and enhance diagnostic accuracy. Differential methylation analysis was performed using the limma package to identify informative CpG features, which were then analyzed with advanced algorithms, including SVM (polynomial and RBF kernels), k-NN, Random Forest, and artificial neural networks (ANN). Deep learning via a stacked autoencoder (SAE) further enriched the analysis by uncovering epigenetic patterns and reducing feature dimensionality. To ensure robustness, the identified biomarkers were independently validated using the external dataset GSE114135. Results: The hybrid machine learning models revealed LDHC and SLC35G2 methylation as promising biomarkers for food allergy prediction. Notably, the methylation pattern of the LDHC gene showed significant potential in distinguishing individuals with food allergies from those with food sensitivity. Additionally, the integration of machine learning and deep learning provided a robust platform for analyzing complex epigenetic data. Importantly, validation on GSE114135 confirmed the reproducibility and reliability of these findings across independent cohorts. Conclusions: This study demonstrates the potential of combining machine learning with DNAm data to advance precision medicine in food allergy diagnosis. The results highlight LDHC and SLC35G2 as robust epigenetic biomarkers, validated across two independent datasets (GSE114134 and GSE114135). These findings underscore the importance of developing clinical tests that incorporate these biomarkers to reduce misdiagnosis and lay the groundwork for exploring epigenetic regulation in allergic diseases.
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    Sex-Specific Associations Between 2D:4D Digit Ratio and Physical Fitness in Prepubertal Children: Evidence from Standardized Agility, Strength, and Endurance Assessments
    (Mdpi, 2025) Akgul, Fatih; Kurtoglu, Ahmet; Ciftci, Rukiye; Eken, Ozgur; Car, Bekir; Sanal, Alperen; Aldhahi, Monira I.
    Background: The second-to-fourth digit ratio (2D:4D) serves as a non-invasive proxy for prenatal androgen exposure. While its relationship with adult athletic ability is well documented, evidence for its association with childhood physical fitness remains inconsistent, and links between 2D:4D and objective fitness measures in prepubertal children are unclear. Methods: In this cross-sectional study, 338 prepubertal children (181 girls, 157 boys; aged 5-12 years) underwent precise measurement of right- and left-hand 2D:4D ratios (intra-class correlation coefficient = 0.94). Physical fitness was evaluated using standardized tests: the Illinois agility run, bent-arm hang, and standing long jump. Results: Among boys, higher 2D:4D ratios were modestly associated with prolonged bent-arm hang performance (beta = 0.19, q = 0.04) and shorter Illinois agility times (beta = -0.19, q = 0.04). No significant associations were observed in girls. All effect sizes were small, suggesting subtle, sex-dependent influences rather than robust predictors of performance. Conclusions: These findings indicate that prenatal hormonal environment may exert a limited, sex-specific influence on early physical fitness characteristics. Although biologically informative, the observed associations are insufficient for direct application in talent identification in sports. Longitudinal research incorporating direct hormonal measurements and broader populations is recommended to clarify developmental mechanisms and causal pathways.