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Cyclophosphamide (CP) is an alkylating anticancer drug with broad clinical application that is highly effective in the treatment of cancer and non-malignant diseases. However, the main limiting effect of CP is multi-organ toxicity due to damage to normal tissues. The aim of this study is to compare the hepatoprotective potential of selenium (Se) and boron (B) in CP-induced liver injury in experimental rats. The rats were randomly divided into six equal groups: Control (saline), 200 mg/kg CP (administered once on the fourth day of the experiment), 1.5 mg/kg Se (administered once/time daily for 6 days), 20 mg/kg B (administered once/time daily for 6 days), Se + CP and B + CP administered intraperitoneally (i.p.). Administration of CP leads to an increase in the levels of apoptotic markers (Bax, caspase-3), the apoptotic signaling pathway (Nrf2), oxidative stress indicators (TOS, OSI), lipid peroxidation markers (MPO, MDA), inflammation levels (NF-kB, TNF-α, IL-1β, IL -6), liver function markers (ALT, AST, ALP), while apoptosis markers (Bcl-2), apoptosis pathway (Keap-1), oxidative stress indicator (TAS), inflammation (IL -10) and intracellular antioxidant defense system (SOD, CAT, GPx and GSH) decreased. In addition, degeneration of hepatocytes and congestion in the central veins were observed. In contrast, in the groups administered Se and B with CP, the changes that occurred were reversed. However, it was found that Se protects the liver slightly better against CP damage than B. The protective effect of Se and B against the toxic effects of CP on the antioxidant markers SOD, CAT and GPx1 was also investigated in silico. The in silico results were consistent with the in vivo results for SOD and CAT, but not for GPx1.

Abstract Dental fillings, frequently used in dentistry to address various dental tissue issues, may pose problems when not aligned with the anatomical contours and physiology of dental and periodontal tissues. Our study aims to detect the prevalence and distribution of normal and overhanging filling restorations using a deep CNN architecture trained through supervised learning, on panoramic radiography images. A total of 10480 fillings and 2491 overhanging fillings were labeled using CranioCatch software from 2473 and 1850 images, respectively. After the data obtaining phase, validation (80%), training 10%), and test-groups (10%) were formed from images for both labelling. The YOLOv5x architecture was used to develop the AI model. The model’s performance was assessed through a confusion matrix and sensitivity, precision, and F1 score values of the model were calculated. For filling, sensitivity is 0.95, precision is 0.97, and F1 score is 0.96; for overhanging were determined to be 0.86, 0.89, and 0.87, respectively. The results demonstrate the capacity of the YOLOv5 algorithm to segment dental radiographs efficiently and accurately and demonstrate proficiency in detecting and distinguishing between normal and overhanging filling restorations.

The aim of this study was to investigate the effect of plyometric training on vertical jump performance in tennis athletes. The research group of the study consisted of 25 volunteer tennis athletes between the ages of 12–17. The average age of the athletes in the experimental group (n=12) was 13.75 ± 2.00 years and the average age of the athletes in the control group (n=13) was 13.23 ± 1.30 years. Plyometric training was applied for 8 weeks. Before and after the training period, height, body weight, active jumping (CMJ), active jump with arms free (CMJFA), horizontal jump (HJ), drop jump (DJ), and squat jump (SJ) tests were performed. When the CMJ, SJ and HJ pre-test–post-test results of the experimental group athletes participating in the study were compared, a statistically significant difference (p < .05) was found. However, no statistically significant difference was found when the CMJFA and DJ pre-test–post-test results of the athletes were compared. Although there was no statistically significant difference, 9,46% positive improvement was found in the CMJFA height and 5,50% positive improvement was found in the DJ height of the experimental group athletes. When the test results of the experimental and control group athletes were compared between the groups, a statistically significant difference (p < .05) was found in the SJ test, while no statistically significant difference was found between the groups in the CMJ, HJ, CMJFA, and DJ tests. While a test × group interaction was observed in the SJ test, this interaction was due to the in-group improvements of the experimental group. In conclusion; Plyometric training is thought to be an effective training to improve vertical jump performance (CMJ, SJ, and DJ) in tennis athletes. Testing the benefits of plyometric training on vertical jump with longer-term interventions (≥10 weeks) will provide researchers with clearer findings.

In this study, it was aimed to determine the 21st century learner skills usage levels (cognitive skills, autonomous skills, collaboration and flexibility skills, and innovation skills) of Turkish language teacher candidates in terms of some variables (gender, grade level, success status). In this study, singular screening, causal comparison and relational screening models were used together within the framework of quantitative research approaches. The respondents were 259 students studying in Turkish Language Teaching Program of Turkish and Social Sciences Department at Balikesir University Necatibey College of Education in the 2018-2019 academic year. The "21st Century Learner Skills Usage Scale" developed by Orhan Göksün (2016) was used as the data collection tool. The scoring of the five-point Likert-type scale consisting of 31 items was made from never (1) to always (5). The 31 items in the scale were gathered under four factors as cognitive skills, autonomous skills, collaboration and flexibility skills, and innovation skills. In the analysis of the data obtained, mean for descriptive analysis, t-test and analysis of variance techniques for comparisons made by the related variables were used. In the study, it was found that the 21st century learner skills usage levels of Turkish language teacher candidates differed in favor of males only in the innovation skills dimension of the scale. It was concluded that as the grade level and grade point average increased, the level of 21st century learner skills use of the participants also increased.

This research was conducted to determine whether there are differences between the norm values used in the evaluation of children who train in different sports and physical education lessons according to the chronological age and biological age of the children. The research group consists of a total of 239 male students of 13 (n=116) and 14 (n=123) chronological years, who study in grades 7 and 8. In addition, the biological ages of the students who make up the research group are calculated and divided into 13(N=140) and 14 (n=86) biological age groups. Within the scope of the research, heights, body weights, body mass indexes and body fat percentages of students were determined as anthropometric variables. Hand grip, leg strength, flexibility, horizontal and vertical jump, medicine ball throwing, ball throwing and sprint running skills were measured as motoric performance variables. The differences of variables according to chronological age and biological age were calculated by the Independent-Samples t-test. According to age groups, the arithmetic mean (x) is shown as 10%. While establishing the norm, the ratings accepted as Canadian criteria were used. In our study, significant differences were found between body weights in 13 and 14 age groups according to both chronological age and biological age. While there is a similarity in 13 age group in terms of heights, difference in favor of biological age was calculated in 14 age group. Even if there is no difference in the comparisons made for the bio motor abilities that are the subject of our study, percentage differences were found in comparing norm values in 10% slices according to chronological age and biological age. Thanks to norm values generated according to both chronological and biological age, the physical condition of the children, strengths and weaknesses related to the level of students in physical education classes, according to the separation of the application groups of children directed to the appropriate sport or the athletes and the students about training programs that will be applied to the course content it is envisaged that the results of this research will provide guidance. In this way, it is thought that by dividing the chronological age and biological age in children, a possible loss of motivation will be prevented in both physical education and training and competitions.

Background: This cross-sectional study aims to investigate the retino-choroidal degenerative effects of periodontitis, metabolic syndrome (Mets), and the combination of these diseases using optical coherence tomography (OCT) measurements. Methods: Ninety-two patients selected according to inclusion criteria were divided into four groups: systemically and periodontally healthy (control), systemically healthy periodontitis (PD), periodontally healthy metabolic syndrome (MetS), and periodontitis and metabolic syndrome combined (PD-MetS). The systemic inflammatory–oxidative effects of periodontitis and MetS were biochemically evaluated using the serum TNF-α level, IL-1β/IL-10 ratio, and oxidative stress index (OSI: TOS/TAS). Retinal (AMT, pRNFLT, and GCL + T) and choroidal (SFCT) morphometric measurements and vascular evaluations (foveal capillary density) were performed via OCT Angio with swept-source technology. Results: Both periodontitis and Mets cause systemic inflammatory stress characterized by significant increases in the IL-1β/IL-10 ratio and OSI (p < 0.05). Compared to the control group, the AMT was significantly thinner in the MetS group, the pRNFLT was significantly thinner in the PD-MetS group, and the SFCT was significantly thinner in both groups (p < 0.05). The GCL+ was slightly thicker in the Mets groups. (p > 0.05) Foveal capillary density did not differ significantly among the groups. (p > 0.05). Conclusions: Periodontitis-related inflammatory stress alone causes changes in retinal and subfoveal choroidal thicknesses that are not statistically significant. On the other hand, when combined with Mets, it may significantly provoke the retinal neurodegenerative effects of this disease.

Abstract Background Panoramic radiographs, in which anatomic landmarks can be observed, are used to detect cases closely related to pediatric dentistry. The purpose of the study is to investigate the success and reliability of the detection of maxillary and mandibular anatomic structures observed on panoramic radiographs in children using artificial intelligence. Methods A total of 981 mixed images of pediatric patients for 9 different pediatric anatomic landmarks including maxillary sinus, orbita, mandibular canal, mental foramen, foramen mandible, incisura mandible, articular eminence, condylar and coronoid processes were labelled, the training was carried out using 2D convolutional neural networks (CNN) architectures, by giving 500 training epochs and Pytorch-implemented YOLO-v5 models were produced. The success rate of the AI model prediction was tested on a 10% test data set. Results A total of 14,804 labels including maxillary sinus (1922), orbita (1944), mandibular canal (1879), mental foramen (884), foramen mandible (1885), incisura mandible (1922), articular eminence (1645), condylar (1733) and coronoid (990) processes were made. The most successful F1 Scores were obtained from orbita (1), incisura mandible (0.99), maxillary sinus (0.98), and mandibular canal (0.97). The best sensitivity values were obtained from orbita, maxillary sinus, mandibular canal, incisura mandible, and condylar process. The worst sensitivity values were obtained from mental foramen (0.92) and articular eminence (0.92). Conclusions The regular and standardized labelling, the relatively larger areas, and the success of the YOLO-v5 algorithm contributed to obtaining these successful results. Automatic segmentation of these structures will save time for physicians in clinical diagnosis and will increase the visibility of pathologies related to structures and the awareness of physicians.

BackgroundTürkiye confirmed its first case of SARS-CoV-2 on March 11, 2020, coinciding with the declaration of the global COVID-19 pandemic. Subsequently, Türkiye swiftly increased testing capacity and implemented genomic sequencing in 2020. This paper describes Türkiye’s journey of establishing genomic surveillance as a middle-income country with limited prior sequencing capacity and analyses sequencing data from the first two years of the pandemic. We highlight the achievements and challenges experienced and distill globally relevant lessons.MethodsWe tracked the evolution of the COVID-19 pandemic in Türkiye from December 2020 to February 2022 through a timeline and analysed epidemiological, vaccination, and testing data. To investigate the phylodynamic and phylogeographic aspects of SARS-CoV-2, we used Nextstrain to analyze 31,629 high-quality genomes sampled from seven regions nationwide.ResultsTürkiye’s epidemiological curve, mirroring global trends, featured four distinct waves, each coinciding with the emergence and spread of variants of concern (VOCs). Utilizing locally manufactured kits to expand testing capacity and introducing variant-specific quantitative reverse transcription polymerase chain reaction (RT-qPCR) tests developed in partnership with a private company was a strategic advantage in Türkiye, given the scarcity and fragmented global supply chain early in the pandemic. Türkiye contributed more than 86,000 genomic sequences to global databases by February 2022, ensuring that Turkish data was reflected globally. The synergy of variant-specific RT-qPCR kits and genomic sequencing enabled cost-effective monitoring of VOCs. However, data analysis was constrained by a weak sequencing sampling strategy and fragmented data management systems, limiting the application of sequencing data to guide the public health response. Phylodynamic analysis indicated that Türkiye’s geographical position as an international travel hub influenced both national and global transmission of each VOC despite travel restrictions.ConclusionThis paper provides valuable insights into the testing and genomic surveillance systems adopted by Türkiye during the COVID-19 pandemic, proposing important lessons for countries developing national systems. The findings underscore the need for robust testing and sampling strategies, streamlined sample referral, and integrated data management with metadata linkage and data quality crucial for impactful epidemiological analysis. We recommend developing national genomic surveillance strategies to guide sustainable and integrated expansion of capacities built for COVID-19 and to optimize the effective utilization of sequencing data for public health action.

The relationship between the reaction time and the total running time of male (n=407) and female (n=345) athletes competing in the 60-meter wind sprint branch at the world indoor championships between 2006 and 2022 and the competition hour was examined in this study. Statistically significant and negative relationships were found between competition hour and athletes' reaction times, competition hour and athletes' competition result ratings in both genders (rho lt;0.040; p lt;0.05). When the subject is examined in terms of the stages of the competitions, no relationship was found for both genders in the final stage while the same relationships were preserved in the semi-final stage. At the qualification stage, a positive relationship was observed between the competition hour and the reaction time in both men (rho=0.25) and women (rho=0.22). In particular, it will be important that the competition time zones in the qualification stage are in similar circadian zones so as not to create a disadvantage among the athletes, and that the competition programs should be prepared by taking the performance-limiting and performance-supporting time zones into account.

The participation of individuals with special needs in performance sports has been increasing from past to present. As in athletes with normal development, stages are planned and implemented in accordance with the goals of high-level performance sports. This study aims to determine the functional threshold power (FTP), VO2max and anaerobic threshold values of a cyclist with special needs to create performance prediction for athletes in similar disability groups. Fırat Uğur, a 26-year-old athlete with special needs who has been participating in cycling competitions for three years and has a body weight of 68 kg and a height of 180.5 cm, participated in the current study. In the findings obtained from the study, the normalized power value of the athlete was found as 204.3 watts, the FTP value as 204.3 watts and the relative power value as 3.00 watts / kg. The athlete's VO2max value was 48.3 ml/kg/min; VO2max load was 298 watts, and VO2max heart rate was 175 beats/min, anaerobic threshold VO2 value was 24.7 ml/kg/min, anaerobic threshold load was 103 watts and anaerobic threshold heart rate was 127 beats/min. When the research findings of the cyclists with special needs were compared with the results obtained from the current study, Fırat Uğur's findings were at lower levels. Considering that the athlete has only participated in competitions as a performance athlete for three years, it can be predicted that he will increase his performance level in the following years. It is recommended that the athlete's training be prepared according to the findings obtained and that the performance development be followed with measurements to be made at regular intervals.

Objectives: The purpose of this study was to evaluate the effectiveness of dental caries segmentation on the panoramic radiographs taken from children in primary dentition, mixed dentition, and permanent dentition with Artificial Intelligence (AI) models developed using the deep learning method. Methods: This study used 6075 panoramic radiographs taken from children aged between 4 and 14 to develop the AI model. The radiographs included in the study were divided into three groups: primary dentition (n: 1857), mixed dentition (n: 1406), and permanent dentition (n: 2812). The U-Net model implemented with PyTorch library was used for the segmentation of caries lesions. A confusion matrix was used to evaluate model performance. Results: In the primary dentition group, the sensitivity, precision, and F1 scores calculated using the confusion matrix were found to be 0.8525, 0.9128, and 0.8816, respectively. In the mixed dentition group, the sensitivity, precision, and F1 scores calculated using the confusion matrix were found to be 0.7377, 0.9192, and 0.8185, respectively. In the permanent dentition group, the sensitivity, precision, and F1 scores calculated using the confusion matrix were found to be 0.8271, 0.9125, and 0.8677, respectively. In the total group including primary, mixed, and permanent dentition, the sensitivity, precision, and F1 scores calculated using the confusion matrix were 0.8269, 0.9123, and 0.8675, respectively. Conclusions: Deep learning-based AI models are promising tools for the detection and diagnosis of caries in panoramic radiographs taken from children with different dentition.