Yaşlanmayla birlikte ağız ve çevresindeki dokularda gözlenen yapısal ve fonksiyonel değişiklikler

Yaşlanmanın organizma üzerindeki majör etkileri arasında, ağız boşluğunda ve dolayısıyla onu çevreleyen dokularda meydana gelen değişiklikler önemli bir yer tutar. Bu yapısal değişikliklere bağlı olarak gelişen ağız, diş ve dişeti hastalıkları yaşlanmanın doğal bir sonucu değildir. Yaşlanmayla oluşan değişikliklerle hastalık durumunda görülen değişiklikler arasındaki fark her zaman net olmadığından bu iki durum arasındaki sınırı belirlemek çoğu zaman mümkün değildir. Bu nedenle yaşlanma süreci nedeniyle doku ve organlarda ortaya çıkan değişiklerin ilgili doku ve organlardaki hastalıkların doğru tanısı ve tedavisi için bilinmesi önemlidir. Bu derlemenin amacı yaşlanma süreciyle birlikte dişler, periodonsiyum, dişleri çevreleyen kemik, ağız mukozası, çiğneme kasları, tükürük bezleri ve çene ekleminde meydana gelen yapısal ve fonksiyonel değişikliklerle ilgili bilgi vermektir.Anahtar Kelimeler:Yaşlanma, dişler, tükürük bezleri, oral mukoz

Lateral sefalometrik görüntülerde servikal vertebra morfolojisinin görsel ve yazılım destekli analizinde gözlemci uyumu

Amaç: Bu çalışmanın amacı, servikal vertebra morfolojisini görsel ve geliştirilen bilgisayar destekli yazılımla inceleyerek farkları değerlendirmek, kemik yaşı tayininde kullanılabilecek yazılım için veri oluşturmaktır.Gereç ve Yöntemler: Çeşitli tanı ve tedavi prosedürleri için Süleyman Demirel Üniversitesi Diş Hekimliği Fakültesi’ne başvuran, kronolojik yaşları 120 ile 228 ay arasında değişen 100 bireyin dijital lateral sefalometrik radyografı seçildi. tüm radyograflardaki C2, C3 ve C4 vertebraların morfolojileri iki klinisyen tarafından görsel olarak Baccetti metoduna uygun olarak değerlendirilip kaydedildi. Aynı görüntüler, iki bilgisayar mühendisi tarafından görüntülerin bölütlenmesi için C# programlama dilinde geliştirilen bir yazılıma .JPEG formatında aktarıldı. Bilgisayar destekli metod için vertebralarda noktalar, aynı iki radyolog tarafından işaretlendi ve vertebraların morfolojileri, işaretlenen noktalar yardımıyla görsel olarak tekrar değerlendirildi. Birbiriyle ilişkili noktalar arasındaki mesafeler ve bu mesafelerin oranları yazılım aracılığıyla hesaplandı. Bu hesaplamalar kullanılarak servikal vertebra morfolojileri yazılım tarafından belirlendi. Servikal vertebra morfolojilerinin belirlenmesinde gözlemci uyumları kappa testi uygulanarak belirlendi.Bulgular: Konkavite varlığı değerlendirmesinde, gözlemciler arası uyum, görsel incelemede orta (Kappa: 0.452), yazılım destekli incelemede orta (Kappa: 0.568), yazılım incelemesinde önemli (Kappa: 0.630) bulundu. Gövde şekli değerlendirmesinde, gözlemciler arası uyum, görsel inceleme, yazılım destekli inceleme ve yazılım incelemesi için düşük olarak bulundu. Hem vertebra şekli hem de vertebra konkavitesi değerlendirmesinde görsel incelemedeki gözlemciler arası uyum orta düzeyde iken; yazılım desteği ve yazılım incelemesinde gözlemciler arası uyum artmaktaydı.Sonuç: Bu çalışma ile elde edilen verilere göre, lateral sefalometrik radyograflarda servikal vertebra morfolojisinin belirlenmesinde, yazılım desteği ile gözlemciler arası uyum artmaktadır. Vertebra morfolojisinin değerlendirilmesinde insan faktörünün etkisini azaltmak, klinik kararlarda standardizasyonu arttırabilir.ANAHTAR KELİMELER Kemik yaşı ölçümü, Servikal Vertebra, radyografi, yazılı

Recent Advances in Health Biotechnology During Pandemic

The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which emerged in 2019, cut the epoch that will make profound fluctuates in the history of the world in social, economic, and scientific fields. Urgent needs in public health have brought with them innovative approaches, including diagnosis, prevention, and treatment. To exceed the coronavirus disease 2019 (COVID-19) pandemic, various scientific authorities in the world have procreated advances in real time polymerase chain reaction (RT-PCR) based diagnostic tests, rapid diagnostic kits, the development of vaccines for immunization, and the purposing pharmaceuticals for treatment. Diagnosis, treatment, and immunization approaches put for- ward by scientific communities are cross-fed from the accrued knowledge of multidisciplinary sciences in health biotechnology. So much so that the pandemic, urgently prioritized in the world, is not only viral infections but also has been the pulsion in the development of novel approaches in many fields such as diagnosis, treatment, translational medicine, virology, mi- crobiology, immunology, functional nano- and bio-materials, bioinformatics, molecular biol- ogy, genetics, tissue engineering, biomedical devices, and artificial intelligence technologies. In this review, the effects of the COVID-19 pandemic on the development of various scientific areas of health biotechnology are discussed

Comparison of the Effect of the Time Under the Three Primary Color Lighting of Led Production Before Scanning of Phosphorus Plates

Purpose This study aims to compare the effect of light exposure in red, green and blue (RGB) colors prior to scanning of the PSP plates. Materials Methods An Arduino-based system is produced for standardized light exposure to the irradiated PSP plates. The system consisted of an Arduino Mega 2560 developer board, 2 RGB LED light sources, a TSL2591 digital light sensor and a DHT11 temperature and humidity sensor. A light-tight platform is produced with additive manufacturing and electronical units are integrated into this platform. A two-step alloy was used to create contrast. PSP system (VistaScan, Dürr Dental, Germany) is irradiated with fixed parameters of 70 kV, 8 mA and 0.5 seconds. Scanning of the PSPs were delayed for 1-,3-,5-, and 10-minutes, and half of the active surfaces are exposed to RGB lights independently in full brightness (PWM) and calibrated with lux while the rest is protected. MGVs are measured in 6 regions per image. The MGV differences in regions between conditions were examined by Kruskal-Wallis test. A p-valu

Validation of cervical vertebral maturation stages: Artificial intelligence vs human observer visual analysis

Introduction: This study aimed to develop an artificial neural network (ANN) model for cervical vertebral maturation (CVM) analysis and validate the model's output with the results of human observers. Methods: A total of 647 lateral cephalograms were selected from patients with 10-30 years of chronological age (mean +/- standard deviation, 15.36 +/- 4.13 years). New software with a decision support system was developed for manual labeling of the dataset. A total of 26 points were marked on each radiograph. The CVM stages were saved on the basis of the final decision of the observer. Fifty-four image features were saved in text format. A new subset of 72 radiographs was created according to the classification result, and these 72 radiographs were visually evaluated by 4 observers. Weighted kappa (w kappa) and Cohen's kappa (c kappa) coefficients and percentage agreement were calculated to evaluate the compatibility of the results. Results: Intraobserver agreement ranges were as follows: w kappa = 0.92-0.98, c kappa = 0.65-0.85, and 70.8%-87.5%. Interobserver agreement ranges were as follows: w kappa = 0.76-0.92, c kappa = 0.4-0.65, and 50%-72.2%. Agreement between the ANN model and observers 1, 2, 3, and 4 were as follows: w kappa = 0.85 (c kappa = 0.52, 59.7%), w kappa = 0.8 (c kappa = 0.4, 50%), w kappa = 0.87 (c kappa = 0.55, 62.5%), and w kappa = 0.91 (c kappa = 0.53, 61.1%), respectively (P < 0.001). An average of 58.3% agreement was observed between the ANN model and the human observers. Conclusions: This study demonstrated that the developed ANN model performed close to, if not better than, human observers in CVM analysis. By generating new algorithms, automatic classification of CVM with artificial intelligence may replace conventional evaluation methods used in the future

Using artificial intelligence models to evaluate envisaged points initially: A pilot study

The morphology of the finger bones in hand-wrist radiographs (HWRs) can be considered as a radiological skeletal maturity indicator, along with the other indicators. This study aims to validate the anatomical landmarks envisaged to be used for classification of the morphology of the phalanges, by developing classical neural network (NN) classifiers based on a sub-dataset of 136 HWRs. A web-based tool was developed and 22 anatomical landmarks were labeled on four region of interests (proximal (PP3), medial (MP3), distal (DP3) phalanges of the third and medial phalanx (MP5) of the fifth finger) and the epiphysis-diaphysis relationships were saved as "narrow,'' "equal,'' "capping'' or "fusion'' by three observers. In each region, 18 ratios and 15 angles were extracted using anatomical points. The data set is analyzed by developing two NN classifiers, without (NN-1) and with (NN-2) the 5-fold cross-validation. The performance of the models was evaluated with percentage of agreement, Cohen's (c kappa) and Weighted (w kappa) Kappa coefficients, precision, recall, F1-score and accuracy (statistically significance: p 0.05) and 0.91 among regions. The average performance was found to be promising except the regions without adequate samples and the anatomical points are validated to be used in the future studies, initially

Evaluation of a Decision Support System Developed with Deep Learning Approach for Detecting Dental Caries with Cone-Beam Computed Tomography Imaging

This study aims to investigate the effect of using an artificial intelligence (AI) system (Diagnocat, Inc., San Francisco, CA, USA) for caries detection by comparing cone-beam computed tomography (CBCT) evaluation results with and without the software. 500 CBCT volumes are scored by three dentomaxillofacial radiologists for the presence of caries separately on a five-point confidence scale without and with the aid of the AI system. After visual evaluation, the deep convolutional neural network (CNN) model generated a radiological report and observers scored again using AI interface. The ground truth was determined by a hybrid approach. Intra- and inter-observer agreements are evaluated with sensitivity, specificity, accuracy, and kappa statistics. A total of 6008 surfaces are determined as ‘presence of caries’ and 13,928 surfaces are determined as ‘absence of caries’ for ground truth. The area under the ROC curve of observer 1, 2, and 3 are found to be 0.855/0.920, 0.863/0.917, and 0.747/0.903, respectively (unaided/aided). Fleiss Kappa coefficients are changed from 0.325 to 0.468, and the best accuracy (0.939) is achieved with the aided results. The radiographic evaluations performed with aid of the AI system are found to be more compatible and accurate than unaided evaluations in the detection of dental caries with CBCT images