Search

A few cases of pneumonia were reported by Wuhan Municipal Health Commission in Wuhan, Hubei Province, Republic of China and this mysterious pneumonia was recognized as novel coronavirus disease (COVID-19) in the course of time on 31 December 2019. Based on the literature knowledge, COVID-19 outbreak came into existence through an animal-to-human transmission, then continued human-to-human diffusion. Especially dentists among the medical professionals are at high-risk group of SARS-CoV-2 virus contamination because of several routine dental procedures having the risk to convey the SARS-CoV-2 virus via droplets and close contact. In this mini-review, it was aimed to give information about patient management during COVID-19 pandemic for dental practitioners, periodontologists and dental hygienists.

Background We report a nosocomial outbreak caused by Burkholderia cepacia that occurred among six patients admitted in the medical and surgical intensive care unit between 04 March 2019 and 02 April 2019 in Istanbul, Turkey. Methods The outbreak investigation was launched on 11 March 2019 five days after the detection of B. cepacia in four different patients. We defined potential reservoirs and started environmental screening. We sampled the liquid solutions used in patient care activities. Pulse-field gel electrophoresis (PFGE) was performed to determine the genetic relatedness of environmental and patient samples. Results Burkholderia cepacia was isolated in tracheal aspiration cultures of six patients. Three out of six patients developed healthcare-associated pneumoniae due to B. cepacia. Environmental cultures in the ICUs revealed B. cepacia growth in 2% chlorhexidine-gluconate mouthwash solution that been used in the colonized patients as well as in samples obtained from the unused products. PFGE revealed the patient and a specific batch of chlorhexidine mouthwash solution samples had a 96% similarity. Conclusion Contamination of medical solutions used in critical patient care could cause outbreaks and should be detected early by infection control teams. Graphic abstract

Background Ralstonia pickettii is an opportunistic waterborne microbe which can survive in many kinds of solutions. Contamination of these solutions may result as outbreaks, which can be mortal for immuncompromised patients. Herein we report an outbreak of R. pickettii related to contaminated saline infusion in our center. Methods This study was conducted in Ankara Pediatric City Hospital. An outbreak occured in Pediatric Hematology and Oncology Unit between August 28, 2019 and September 13, 2019. When the outbreak occured, infection control team began an investigation. Environmental samples were collected in order to find the source of the outbreak. Results A total of 11 patients with catheter related blood stream infection caused by R. pickettii who were diagnosed with leukemia were affected. None of the patients infected with R. pickettii died during the outbreak. A total of seventy environmental samples were cultured with the purpose of finding the source of outbreak. R. pickettii grew in normal saline solution culture and all isolates had the same clone of R. pickettii. The outbreak lasted two weeks and was controlled by stopping the usage and sending back the saline solutions belonging to the same manufacturing batch. Conclusions We reported an outbreak of R. pickettii BSIs in highly immunocompromised patients due to contaminated intravascular solution, which was rapidly controlled by infection control measures. Vigilant surveillance by hospital infection control teams and prompt investigation to identify the source of nosocomial infections are crucial to stop an outbreak.

The aim of this study is to recommend an automatic caries detection and segmentation model based on the Convolutional Neural Network (CNN) algorithms in dental bitewing radiographs using VGG-16 and U-Net architecture and evaluate the clinical performance of the model comparing to human observer. A total of 621 anonymized bitewing radiographs were used to progress the Artificial Intelligence (AI) system (CranioCatch, Eskisehir, Turkey) for the detection and segmentation of caries lesions. The radiographs were obtained from the Radiology Archive of the Department of Oral and Maxillofacial Radiology of the Faculty of Dentistry of Ordu University. VGG-16 and U-Net implemented with PyTorch models were used for the detection and segmentation of caries lesions, respectively. The sensitivity, precision, and F-measure rates for caries detection and caries segmentation were 0.84, 0.81; 0.84, 0.86; and 0.84, 0.84, respectively. Comparing to 5 different experienced observers and AI models on external radiographic dataset, AI models showed superiority to assistant specialists. CNN-based AI algorithms can have the potential to detect and segmentation of dental caries accurately and effectively in bitewing radiographs. AI algorithms based on the deep-learning method have the potential to assist clinicians in routine clinical practice for quickly and reliably detecting the tooth caries. The use of these algorithms in clinical practice can provide to important benefit to physicians as a clinical decision support system in dentistry.

The hippocampus, which has a central role in cognitive and behavioral activities, is one of the most sensitive parts of the brain to systemic inflammatory diseases. This animal study aims to comprehensively investigate the possible inflammatory, oxidative, and apoptotic effects of periodontitis on the hippocampus.Sixteen male Sprague-Dawley rats were randomly assigned to two groups: control and experimental periodontitis (Ep). In the Ep group, periodontitis was induced by placing 3.0 sutures sub-paramarginally around the necks of right and left mandibular first molars and maintaining the ligatures in place for 5 weeks. Following the euthanasia, mandibula and hippocampus samples were collected bilaterally. Alveolar bone loss was measured histomorphometrically and radiologically on the right and left mandibles. On the right hippocampal sections histological (Caspase-3, TNF-α, and 8-OHdG) and the left hippocampal sections, biochemical (IL-1β, AβHistopathological changes associated with periodontitis were limited (p .05). A slight increase in caspase-3 positive neuron density in EP rats showed that apoptotic changes were also limited (p .05). 8-OHdG activity, on the other hand, was significantly higher compared to controls (p .05). In biochemical analysis, there was a significant increase in IL-1β levels and oxidative membrane damage (MDA) (p .05) whereas AβPeriodontitis causes marked increases in IL-1β levels and oxidative stress in the hippocampus, but limited degenerative and apoptotic changes.

BackgroundPanoramic radiography is an imaging method for displaying maxillary and mandibular teeth together with their supporting structures. Panoramic radiography is frequently used in dental imaging due to its relatively low radiation dose, short imaging time, and low burden to the patient. We verified the diagnostic performance of an artificial intelligence (AI) system based on a deep convolutional neural network method to detect and number teeth on panoramic radiographs.MethodsThe data set included 2482 anonymized panoramic radiographs from adults from the archive of Eskisehir Osmangazi University, Faculty of Dentistry, Department of Oral and Maxillofacial Radiology. A Faster R-CNN Inception v2 model was used to develop an AI algorithm (CranioCatch, Eskisehir, Turkey) to automatically detect and number teeth on panoramic radiographs. Human observation and AI methods were compared on a test data set consisting of 249 panoramic radiographs. True positive, false positive, and false negative rates were calculated for each quadrant of the jaws. The sensitivity, precision, and F-measure values were estimated using a confusion matrix.ResultsThe total numbers of true positive, false positive, and false negative results were 6940, 250, and 320 for all quadrants, respectively. Consequently, the estimated sensitivity, precision, and F-measure were 0.9559, 0.9652, and 0.9606, respectively.ConclusionsThe deep convolutional neural network system was successful in detecting and numbering teeth. Clinicians can use AI systems to detect and number teeth on panoramic radiographs, which may eventually replace evaluation by human observers and support decision making.

Signalized intersection management systems have become more efficient with the help of developments in communication and detector systems. Especially, Adaptive Signal Management Systems (ASMS) is planned intersections to adapt to variable traffic parameters. However, previous approaches developed to measure the efficiency of signalized intersections are not compatible with the continuous change of control parameters such as cycle length and phase plans. In this study, a delay estimation model (DÖM) has been developed for intersections managed with ASMS using the deep learning approach. The efficiency of the DÖM has been analyzed by comparing the performances with artificial neural network (ANN) models and analytical models. In addition, DÖM and ANN models were trained with different input variables and their performances were investigated. The data used for modeling were collected from the intersection managed by ASMS in Kırıkkale province by making observations. These observations were made according to vehicle types and delay observations of 6331 vehicles in a total of 487 cycles were made. Analysis results showed that the DÖM model predicts the actual delays with error percentages approximately 2 times lower than the ANN model, and approximately 5 times lower than the analytical models. This study revealed that DÖM is an effective performance measurement model for signalized intersections operating with variable timing., Sinyalize kavşak yönetim sistemleri, haberleşme ve detektör sistemlerindeki gelişmeler sayesinde daha verimli hale gelmiştir. Özellikle Adaptif Sinyal Yönetim Sistemleri (ASYS), kavşakları değişken trafik parametrelerine uyum sağlayacak biçimde planlanmaktadır. Fakat, sinyalize kavşakların etkinliğinin ölçülmesi için geliştirilen geçmiş yaklaşımlar, devre süresi, faz düzeni gibi, denetim parametrelerinin sürekli değişimine uyumlu değildir. Bu çalışmada, derin öğrenme yaklaşımı kullanılarak ASYS ile yönetilen kavşaklar için bir gecikme tahmin modeli (DÖM) geliştirilmiştir. Performanslar yapay sinir ağı (YSA) modelleri ve analitik modellerle karşılaştırılarak DÖM'ün verimliliği analiz edilmiştir. Ayrıca, DÖM ve YSA modelleri, farklı girdi değişkenleri ile eğitilerek performansları araştırılmıştır. Modellemeler için kullanılan veriler Kırıkkale ili sınırları içindeki ASYS' leyle yönetilen kavşaktan, gözlemler yapılarak toplandı. Bu gözlemler araç türlerine göre yapılmış ve toplam 487 adet devrede 6331 adet taşıtın gecikme gözlemi gerçekleştirilmiştir. Analiz sonuçları, DÖM modelinin, gerçek değerleri YSA modelinden yaklaşık 2 kat, analitik modellerden yaklaşık 5 kat daha düşük hata yüzdeleri ile tahmin ettiğini göstermiştir. Bu çalışma, derin öğrenme yaklaşımının, değişken zamanlama ile çalışan sinyalize kavşaklar için etkin bir performans ölçüm modeli olduğunu ortaya koymuştur.

Hypoglossal canal (HC) which begins from very slightly above the inner part of the anterolateral portion of the foramen magnum and is located above the occipital condyle of the occipital bone. The aim of this study is to examine HC morphology and variations using cone beam computed tomography (CBCT). The morphology and types of HC were investigated with 303 CBCT images (606 side). Type 1 variation in 606 HC examined becomes the most commonly observed type (57.3%) while type 5 variation was the least common type of variation (0.8%). Type 1 HC was statistically higher in males (p=0.004). Because of HC, which is an anthropologically important point and enters the field of images in CBCT scan, it is recommended that dental radiologists should be aware of their variations and be wary of the pathologies that may occur in this region.

Purpose: The aim of this study was to compare the bone collection capacity of bur drill systems used in implant surgery with different diameters, lengths, and drilling speeds. Materials and methods: This study was performed on bovine ribs. Two bur drill systems were studied: Implantium (Dentium) and Straumann (Institut Straumann). The groups were divided into subgroups according to the bur diameter. As a result, there were four Implantium subgroups (3.3, 3.8, 4.3, and 4.8 mm) and three Straumann subgroups (3.3, 4.1, and 4.8 mm). In addition, for each bur diameter, the bone collection capacities of the drill systems were evaluated at three different drilling speeds (150, 250, and 400 rpm) and two bur lengths (10 and 12 mm). The diameter, length, and speed changes were performed, and the results were compared between the two drill systems. Results: The mean bone weight collected by using the Straumann burs was higher than that of the Implantium burs at each drilling speed and bur length. Using the Straumann system, the different drilling speeds/lengths of the burs had no impact on the bone collection capacity, irrespective of the bur diameter (P > .05). However, the drilling speeds/lengths of the Implantium system resulted in a statistically significant difference in the same diameters (P < .05). Conclusion: Both bur systems were suitable for autogenous graft collection for bone grafting in implant surgery, but the Straumann burs were more successful than the Implantium burs.

Aim: The present study is aimed to assess the segmentation success of an artificial intelligence (AI) system based on the deep convolutional neural network (D-CNN) method for the segmentation of masseter muscles on ultrasonography (USG) images. Materials and Methods: This retrospective study was carried out by using the radiology archive of the Department of Oral and Maxillofacial Radiology of the Faculty of Dentistry in Ankara University. A total of 195 anonymized USG images were used in this retrospective study. The deep learning process was performed using U-net, Pyramid Scene Parsing Network (PSPNet), and Fuzzy Petri Net (FPN) architectures. Muscle thickness was assessed using USG by manual segmentation and measurements using USG’s software. The neural network model (CranioCatch, Eskisehir-Turkey) was then used to determine the muscles, following automatic measurements of the muscles. Accuracy, ROC area under the curve (AUC), and Precision-Recall Curves (PRC) AUC were calculated in the test dataset and compare a human observer and the AI model. Manual segmentation and measurements were compared statistically with AI ( P < .05). The Mann–Whitney U test was used to analyze whether there is a statistically significant difference between the predicted values and the actual values. Results: The AI models detected and segmented all test muscle data for FPN and U-net, while only two cases of muscles were not detected by PSPNet (false negatives). Accuracies of FPN, PSPNet, and U-net were estimated as 0.985, 0.947, and 0.969, respectively. Receiver operating characteristic scores of FPN, PSPNet, and U-net were estimated as 0.977, 0.934, and 0.969, respectively. The D-CNN measurements of the muscles were similar to manual measurements. There was no significant difference between the two measurement methods in three groups ( P > .05). Conclusion: The proposed AI system approach for the analysis of USG images seems to be promising for automatic masseter muscle segmentation and measurement of thickness. This method can help surgeons, radiologists, and other professionals such as physical therapists in evaluating the time correctly and saving time for diagnosis.

OBJECTIVES The present study was performed to compare the effectiveness of Ankaferd Blood Stopper® (ABS) with enamel matrix derivatives (EMD) for treating fenestration defects in rats. MATERIALS AND METHODS Forty-eight male Wistar rats were randomly divided into six groups (each n = 8). Fenestration defects were created in all rats, to which ABS, EMD, or saline (S) was then applied. The rats were grouped and sacrificed at one of two different time points, as follows: ABS-10-group, ABS-treatment/sacrifice on day 10; EMD-10-group, EMD-treatment/sacrifice on day 10; S-10-group, S-treatment/sacrifice on day 10; ABS-38-group, ABS-treatment/sacrifice on day 38; EMD-38-group, EMD-treatment/sacrifice on day 38; and S-38-group, S-treatment/sacrifice on day 38. Then, histomorphometric analysis including measurements of new bone area (NBA) and new bone ratio (NBR), and immunohistochemical analysis including the determination of osteopontin (OPN) and type-III-collagen (C-III) expression were performed. RESULTS The NBA and NBR were significantly higher in the ABS-10-group and EMD-10-group compared to the S-10-group (p

Amaç: Bu çalışmanın amacı yapay zeka (Artificial Intelligence) (AI) sistemleri kullanılarak dental panoramik radyografik görüntülerden alveoler kemik kaybını tespit etmektir.Gereç ve Yöntem: Bu çalışmada toplam 2276 panoramik radyografik görüntü kullanıldı. Bunların 1137'si kemik yıkımı olan vakalara aitken, 1139'u periodontal olarak sağlıklıydı. Veri kümesi eğitim (n = 1856), doğrulama (n = 210) ve test seti (n = 210) olarak üç bölüme ayrıldı. Veri setindeki tüm görüntüler eğitimden önce 1472x718 piksel olarak yeniden boyutlandırıldı. Açık kaynaklı python programlama dili ve OpenCV, NumPy, Pandas ve Matplotlib kütüphaneleri etkili bir şekilde kullanılarak rastgele bir dizi oluşturuldu. Ön işleme için önceden eğitilmiş bir Google Net Inception v3 CNN ağı kullanılmış ve veri setleri aktarım öğrenimi kullanılarak eğitildi. Tanısal performans, duyarlılık, özgüllük, kesinlik, doğruluk ve F1 skoru kullanılarak konfüzyon matrisi ile değerlendirildi.Bulgular: Kemik kaybı olan 105 olgunun 99'u AI sistemi ile tespit edildi. Duyarlılık 0.94, özgüllük 0.88, hassasiyet 0.89, doğruluk 0.91 ve F1 skoru 0.91 idi.Sonuç: Konvolüsyon nöral ağ modeli periodontal kemik kayıplarını belirlemede başarılıdır. Gelecekte tanı ve tedavi planlamasında hekimlerin çalışmasını kolaylaştıran bir sistem olarak kullanılabilir., Objectives: The aim of this study was to detect alveolar bone loss from dental panoramic radiographic images using artificial intelligence systems.Material and Methods: A total of 2276 panoramic radiographic images were used in this study. While 1137 of them belong to cases with bone destruction, 1139 were periodontally healthy. The dataset is divided into three parts as training (n=1856) , validation (n=210) and testing set (n= 210). All images in the data set were resized to 1472x718 pixels before training. A random sequence was created using the open-source python programming language and OpenCV, NumPy, Pandas, and Matplotlib libraries effectively. A pre-trained Google Net Inception v3 CNN network was used for preprocessing and data sets were trained using transfer learning. Diagnostic performance was evaluated with the confusion matrix using sensivitiy, specificity, precision, accuracy and F1 score.Results: Of the 105 cases with bone loss, 99 were detected by the AI system. Sensitivity was 0.94, specificity 0.88, precision 0.89, accuracy 0.91 and F1 score 0.91. Conclusion: The convolutional neural network model is successful in determining periodontal bone losses. It can be used as a system to facilitate the work of physicians in diagnosis and treatment planning in the future.

Amaç: İnfluenza rutin tanısında yüksek duyarlılık ve özgüllüğü nedeniyle real-time PCR testi tercih edilmektedir. Ancak PCR testlerinin yüksek maliyet ve deneyimli personel gereksinimi, laboratuvar ortamına ve cihazlarına ihtiyaç duyulması, numune transferi ve hekime sonucun ulaşmasında geçen süre gibi nedenlerle hasta başı kullanılan hızlı influenza tanı testlerinin kullanımı gündeme gelmiştir. Bu çalışmanın amacı, influenza enfeksiyonu tanısında kullanılan 3 farklı hızlı tanı testinin gerçek zamanlı RT-PCR yöntemi ile karşılaştırılması ve tanısal performansının belirlenmesidir.Yöntem: Çalışmamıza 2017-2018 influenza sezonunda laboratuvarımıza gönderilen toplam 209 solunum yolu örneği dahil edilmiştir. Örnekler Humasis Influenza antigen card plus (Kore), SD Biosensor Standard-Q Influenza A/B (Kore) ve SD Biosensor Standard-F Influenza A/B FIA (Kore) hızlı antijen tanı kitleri ile üretici firmaların önerileri doğrultusunda test edilmiştir.Bulgular: Çalışmamızda Humasis kiti ile İnfluenza A için duyarlılık %80,99, İnfluenza B için %68,66 hesaplanmıştır. SD Biosensor Standard Q Influenza A/B ve SD Biosensor Standard F Influenza A/B FIA kiti ile her iki virüs için de duyarlılık %70’in altında bulunmuştur. Humasis kitinin duyarlılığı diğer kitlere oranla daha yüksek saptanır- ken özgüllük tüm kitlerde %90’ın üzerinde belirlenmiştir.Sonuç: Bu çalışma ile hızlı antijen testlerinin, influenza virüs aktivitesinin yoğun olduğu influenza sezonu dönemi veya salgın durumlarında influenza virüs enfeksiyonu tanısında tarama testi veya destekleyici test olarak kullanılabileceği sonucuna varılmıştır., Aim: Due to its high sensitivity and specificity, real-time PCR testing is preferred for routine diagnosis. However, for PCR tests, the use of rapid influenza diagnostic tests at bedside due to reasons such as high cost, experienced personnel, laboratory conditions and equipment requirement, sample transfer and test time has come to the fore. Purpose of the study was to compare three different diagnostic tests used in the diagnosis of influenza infection with the real-time RT-PCR method and to determine the diagnostic performance.Methods: A total of 209 respiratory tract samples sent to our laboratory during the 2017-2018 influenza season were included in our study. The samples were tested with Humasis Influenza antigen card plus, SD Biosensor Standard-Q Influenza A/B, and SD Biosensor Standard-F Influenza A/B FIA rapid antigen diagnostic kits according to the recommendations of the manufacturers.Results: In our study, susceptibility was calculated 80.99% for influenza A and 68.66% for influenza B with Humasis kit. With the SD Biosensor Standard Q Influenza A/B and the SD Biosensor Standard F Influenza A/B FIA kit, the sensitivity for both viruses was below 70%. While the sensitivity of the humasis kit was higher than the other kits, the specificity was higher than 90% in all kits.Conclusion: n this study, it was concluded that rapid antigen tests can be used as a screening test or supportive test for the diagnosis of influenza virus infection during the influenza season period or epidemic conditions during which influenza virus activity is intense.

Aim of the study: Ultrasonographic examination of intraosseous jaw pathologies may reveal interesting incidental, mobile hyperechoic particles (“snowflakes”) in anechoic areas. Purpose of this study is to explain and discuss this snowing-like ultrasonographic feature of intraosseous jaw pathologies. Material and methods: This study included 113 patients admitted to our clinic for examination: 43 (38.05%) males and 70 (61.9%) females with a mean age of 34.9 ± 17.2 years (range: 6–72 years). A total of 120 intraosseous lesions were evaluated prior to surgery using ultrasonography; these included non-neoplastic, odontogenic, and non-odontogenic lesions. Results: In total, 5 (4.1%) of the 120 lesions exhibited snowing-like feature on ultrasonography, including 2 (1.6% of total) of 3 incisive canal cysts, 2 (1.6% of total) of 7 dentigerous cysts, and 1 (0.8% of total) of 19 odontogenic keratocysts. Conclusions: Snowflakes evident on ultrasonography of intraosseous jaw lesions may be specific to certain pathologies. Future studies correlating radiologic and pathologic features of intraosseous jaw lesions should focus on ultrasonographic snowing-like appearance in different types of lesions and explore why they occur.

Due to the fact that social networks are becoming more and more popular, many users are continuously active social networking users. Active users are constantly sharing what they see and think. Social network users follow the people they are interested in, comment on their messages and forward them to other people. In this way, there is a huge amount of data generated by users on social networks. Besides; in addition to textual sharing, image and video sharing are also available through mobile phones with a camera. In this study, text and image-based semantic inference methods in social networks were investigated. The advantages of different semantic inference methods are emphasized. Finally, information was given on what can be done in this area in the future., Sosyal ağların gün geçtikçe daha popüler hale gelmesi sebebiyle, çok sayıda kullanıcı sürekli olarak aktif sosyal ağ kullanıcısı durumundadır. Aktif kullanıcılar sürekli olarak gördüklerini ve düşündüklerini paylaşmaktadır. Sosyal ağ kullanıcıları ilgilendikleri kişileri takip etmekte, mesajlarına yorum yapmakta ve diğer kişilere iletmektedir. Bu şekilde, sosyal ağlarda kullanıcılar tarafından üretilen çok büyük miktarda veri bulunmaktadır. Bunun yanında; kameralı cep telefonları sayesinde metinsel paylaşımlar yanında görüntü ve video paylaşımları da yapılmaktadır. Bu çalışmada, sosyal ağlarda metin ve görüntü tabanlı anlamsal çıkarım yöntemleri incelenmiştir. Farklı anlamsal çıkarım yöntemlerinin, kullanıldığı alanlara göre avantajları vurgulanmıştır. Son olarak da, bu alanda gelecekte ne gibi çalışmalar yapılabileceğine dair bilgiler verilmiştir.

Objectives: The present study aimed to evaluate the performance of a Faster Region-based Convolutional Neural Network (R-CNN) algorithm for tooth detection and numbering on periapical images. Methods: The data sets of 1686 randomly selected periapical radiographs of patients were collected retrospectively. A pre-trained model (GoogLeNet Inception v3 CNN) was employed for pre-processing, and transfer learning techniques were applied for data set training. The algorithm consisted of: (1) the Jaw classification model, (2) Region detection models, and (3) the Final algorithm using all models. Finally, an analysis of the latest model has been integrated alongside the others. The sensitivity, precision, true-positive rate, and false-positive/negative rate were computed to analyze the performance of the algorithm using a confusion matrix. Results: An artificial intelligence algorithm (CranioCatch, Eskisehir-Turkey) was designed based on R-CNN inception architecture to automatically detect and number the teeth on periapical images. Of 864 teeth in 156 periapical radiographs, 668 were correctly numbered in the test data set. The F1 score, precision, and sensitivity were 0.8720, 0.7812, and 0.9867, respectively. Conclusion: The study demonstrated the potential accuracy and efficiency of the CNN algorithm for detecting and numbering teeth. The deep learning-based methods can help clinicians reduce workloads, improve dental records, and reduce turnaround time for urgent cases. This architecture might also contribute to forensic science.

Bayrakdar, M. Enes/0000-0001-9446-0988 WOS: 000473916000001 The collaboration of users in communication systems is defined as cooperative communication. The cognitive radio, i.e. dynamic spectrum access technique, is a wireless communication technology that provides a great chance for unlicensed users to exploit the frequency bands in an opportunistic way. A wireless sensor network is a widely used communication technology composing of spatially distributed independent sensors in order to monitor physical or environmental circumstances. In this work, a new technique that unlicensed users become a cooperative relay when they are in idle mode is proposed. Along with the proposed technique, unlicensed users help sensor nodes as a cooperative relay when they are in idle mode. Similarly, sensor nodes help unlicensed users for detecting idle frequency bands while in sleep mode. By preventing any disruption that remote users may be exposed owing to signal attenuation, the proposed cooperative relay utilises amplify and forward based cooperative communication protocol. Thanks to this approach; the overall network has greater performance than wireless sensor network that does not use cooperative communication based dynamic access technique in terms of throughput, energy, and delay.

Background and Study Aim. The aim of this study is to determine the effect of e-sports on physical activity level and body composition. Material and Methods. The athletes who participated in the study were 19.92± 2.21 years of age, 1.73±0.04 m body height and 78.35±6.52 kg body weight. A total of 137 athletes participated in the study, including 27 from Turkey, 47 from South Korea and 63 from the United States (USA). The data was collected by e-mail from the sports clubs. The athletes who representing their country in international competitions involved in the study. The data obtained were evaluated in the SPSS program. Results. According to the findings of the study, the body mass index (BMI) of e-sport athletes is 26.03±1.85, the number of physical activity steps is 6646±3400 and the daily e-sport hours are 9.34±1.12. The BMI was determined as USA 26.12, South Korea 26.02 and Turkey 25.84 respectively. The number of physical activity steps was identified as 5255 steps in the US, 7785 steps in South Korea and 7909 steps in Turkey. The daily e-sports hour is set at US 9.63 hours, Turkey 9.29 hours and South Korea 8.97 hours. In comparison of country-based athletes, there was a significant difference between physical activity level and daily e-sports hours at p, Предпосылки и цель исследования. Цель данного исследования - определить влияние киберспорта на уровень физической активности и композицию тела.Материал и методы. Возраст спортсменов, принимавших участие в исследовании, составлял 19,92 ± 2,21 года, рост составлял 1,73 ± 0,04 м, масса тела - 78,35 ± 6,52 кг. Всего в исследовании приняли участие 137 спортсменов, в том числе 27 из Турции, 47 из Южной Кореи и 63 из США. Данные были получены от спортивных клубов по электронной почте. В исследовании участвовали спортсмены, представляющие свою страну на международных соревнованиях. Полученные данные оценивались в программе SPSS.Результаты. Согласно результатам исследования, индекс массы тела (ИМТ) спортсменов, занимающихся киберспортом, составляет 26,03 ± 1,85, количество шагов физической активности - 6646 ± 3400, а ежедневные часы киберспорта - 9,34 ± 1,12. ИМТ был определен как США 26,12, Южная Корея 26,02 и Турция 25,84 соответственно. Количество шагов физической активности было определено как 5255 шагов в США, 7785 шагов в Южной Корее и 7909 шагов в Турции. Ежедневное время занятий киберспортом установлено на уровне 9,63 часа в США, 9,29 часа в Турции и 8,97 часа в Южной Корее. По сравнению со спортсменами из страны была выявлена ​​значительная разница между уровнем физической активности и дневными часами занятий киберспортом при p, Передумови та мета дослідження. Мета даного дослідження - визначити вплив кіберспорту на рівень фізичної активності і композицію тіла.Матеріал і методи. Вік спортсменів, які брали участь в дослідженні, становив 19,92 ± 2,21 року, зрост становив 1,73 ± 0,04 м, маса тіла - 78,35 ± 6,52 кг. Всього в дослідженні взяли участь 137 спортсменів, в тому числі 27 з Туреччини, 47 з Південної Кореї і 63 з США. Дані були отримані від спортивних клубів по електронній пошті. У дослідженні брали участь спортсмени, що представляють свою країну на міжнародних змаганнях. Отримані дані оцінювалися в програмі SPSS.Результати. Згідно з результатами дослідження, індекс маси тіла (ІМТ) спортсменів, які займаються кіберспортом, становить 26,03 ± 1,85, кількість кроків фізичної активності - 6646 ± 3400, а щоденні заняття кіберспортом - 9,34 ± 1,12 годин. ІМТ був визначений як США 26,12, Південна Корея 26,02 і Туреччина 25,84 відповідно. Кількість кроків фізичної активності було визначено як 5255 кроків в США, 7785 кроків в Південній Кореї і 7909 кроків в Туреччині. Щоденний час занять кіберспортом встановлено на рівні 9,63 години в США, 9,29 години в Туреччині і 8,97 години в Південній Кореї. У порівнянні зі спортсменами з країни була виявлена ​​значна різниця між рівнем фізичної активності та денними годинами занять кіберспортом при p

The authors compared the morphological features of the Eustachian tube (ET) between patients with cleft lip and palate (CL/P) and normal controls using cone-beam computed tomography (CBCT). CBCT images of 51 CL/P patients (28 males and 23 females, mean age: 18.5 ± 8.0 years) and a control group of 52 patients (22 males and 30 females, mean age: 25.23 ± 10.65 years) were retrospectively evaluated. The Eustachian tube angle (ETA), Eustachian tube length (EL), and auditory tube angle (ATA) were measured on CBCT images. The ETA, EL, and ATA in the CL/P and normal control groups were 30.4 ± 6.2 and 36.7 ± 7.5°; 24.7 ± 3.7 and 27.7 ± 4.3 mm; and 142.4 ± 7.8 and 136.3 ± 4.1°, respectively. All between-group differences were statistically significant (all P 0.05). There were no significant between-gender differences in either group (all P 0.05). Continuous variables were compared using the Mann-Whitney U-test. The morphological features of the ET, measured via multiplanar reconstruction CBCT, differed between CL/P patients and normal controls. CBCT can be used to evaluate ET morphological features.

The aim of this experimental rat study was to investigate the potential inflammatory effects of periodontitis on cardiac left ventricular tissue and the therapeutic activity of melatonin on these effects.Twenty-four male Sprague-Dawley rats were randomly divided into three groups: control, experimental periodontitis (Ep), and Ep-melatonin (Ep-Mel). Experimental periodontitis was induced by placing and maintaining 3.0 silk ligatures at a peri marginal position on the left and right mandibular first molars for 5 weeks. Afterward, following the removal of ligatures, melatonin (10 mg/body weight) to Ep-Mel group, and vehicle (saline) to Ep and control groups were administered intraperitoneally for 14 days. On the first day of the eighth week, mandibular and cardiac left ventricular tissue samples were obtained following the euthanasia of the rats in all groups. Alveolar bone loss measurements were made on histological and microcomputed tomographic slices. Cardiac tissue levels of malondialdehyde (MDA), glutathione (GSH), superoxide dismutase (SOD), catalase (CAT), matrix metalloproteinase-9 (MMP-9), and cardiac Troponin-T (cTnT) were evaluated by appropriate biochemical methods.Measurements made on the histological and microcomputed tomographic slices showed that melatonin significantly limits the ligature-induced periodontal tissue destruction (P 0.01). In addition, melatonin was detected to cause a significant decrease of MDA, MMP-9, and cTnT levels which were found to be significantly higher on rats with Ep (P 0.05) while having no significant effect on antioxidant levels (GSH, SOD, and CAT) (P 0.05).Melatonin might be regarded as an important supportive therapeutic agent to reduce the early degenerative changes and possible hypertrophic remodeling at cardiac left ventricular tissues provoked by periodontitis-related bacteria and/or periodontal inflammation.

WOS: 000515270500001 PubMed: 32058800 Background: Human beta-defensin-2 is an antimicrobial weapon peptide with antibiotic properties secreted by the oral cavity to protect the host against microbial attack. The interindividual differences of defensin expression profiles due to genetic variation might be partly responsible for differences in disease susceptibility. Aims: The objective of this study was to examine whether variation in the human beta-defensin-2 gene (DEFB4A) is associated with chronic periodontitis (CP). Materials and Methods: This case-control study analyzed two promoter polymorphisms in DEFB4A with potential functional consequences in DNA samples collected from 200 unrelated individuals using Sanger sequencing. Results: The DEFB4A rs1339258595 promoter polymorphism is associated with CP risk and clinical attachment level (CAL) but the rs3762040 polymorphism is not. Carriers of the T allele (rs1339258595) were approximately three times less likely to develop periodontitis compared with noncarriers (p = 0.0004, odds ratio = 0.35). Consistent with a protective role, the carriers of T allele had a lower CAL compared with the wild-type (G) allele. Moreover, the wild-type diplotype (GGGG) had a significantly higher risk of tooth loss compared with other diplotypes (p = 0.016). Conclusion: This study demonstrates that genetic variation in the promoter region of DEFB4A likely affects resistance to periodontal infection and might be a potential marker for CP risk and severity. Teaching Staff Training Program project by the council of higher education in Turkey [KAEK 2014/518] This study was supported by the Teaching Staff Training Program project by the council of higher education in Turkey (KAEK 2014/518).

The aim of this study was to analyze the effects of 12-week regular zumba exercises on antropometric properties. A total of 20 women who participated in the study were consisted of 10 for experimental group and 10 for control group with a mean age of 38.25 ± 4.22 who performed regular zumba exercise for 12 weeks. In the research, two measurements were taken as pre and post tests. In the study, body fat percentage measurements were taken by bioelectrical impedance analyses method and ciccumference measurements were taken by tape measure. The data obtained at the end of the research were evaluated in SPSS program. Arithmetic mean, standard deviation values of the measurements, intra and intergroup differences and percentage development differences were obtained. According to the findings of the research, a significant difference of p

Objectives:Crimean-Congo hemorrhagic fever (CCHF) is seen in our country with fatality rate of 5% since 2002. It was aimed to reveal if there were any differences responsible from fatalities in M segments of CCHF viruses detected in patients’ sera in Tokat province, reporting the most of the cases in Turkey.Materials and Methods:Nineteen patients, applying to hospital whom, nine were later ex and 10 were discharged with cure, from the same regions of Tokat districts between March to August 2014, which is the period of most number of CCHFV cases reported, were included. Viral RNA was isolated, M segment region was amplified and sequence analysis was performed.Results:Obtained M segment nucleotide sequences were found to be in Europe clade having close relation with Russian and Kosovo strains on the same branches of the phylogenetic tree. Seven out of 19 viruses were in a different group because they had R1532K mutation like Russian and Kosovo strains and L1601F mutation which was not found to exist in the genotypes reported from Turkey, before.Conclusion:In this study, Turkey/Almus01/2014 M segment analysis was found identical in a couple living in Almus, whom one of them had died while one was discharged from hospital with cure, suggesting individual factors were also responsible from fatality, not only viral strain. On certain periods although suspicion of high mortality rate occurs, at the end of each disease season, fatality stays on the same rate, suggesting there are not any viral mutations increasing fatality. Data on this study support this hypothesis.

Rapid laboratory diagnosis in acute viral infections in the central nervous system (CNS) is important for the direction of treatment. In this study, we aimed to evaluate viral agents detected by real-time polymerase chain reaction (PCR) in cerebrospinal fluid (CSF) samples sent to the national virology reference laboratory for the diagnosis of acute CNS viral infection in the 0 to 18 age group. The results of 5,255 CSF samples submitted to the laboratory between January 1, 2009, and February 14, 2018, were retrospectively reviewed. Test results of CSF samples tested with the multiplex real-time PCR panel (Fast Track Diagnostics/Viral Meningitis commercial kit, Luxembourg) kit were evaluated. PCR positivity was detected in 216 (4.11%) of the 5,255 CSF samples tested. The most common agents were enteroviruses 92 (42.6%) and herpes simplex virus-1 (HSV-1) 87 (40.2%) while varicella-zoster virus (VZV) 24 (11.1%), mumps virus 10 (4.62%), parechovirus 2 (0.92%), and herpes simplex virus-2 (HSV-2) 1 (0.46%) were less often identified. Considering the possibility that a wide variety of microorganisms may be agents of CNS infections, the performing of routine laboratory tests with multiple, fast, and reliable nucleic acid tests such as multiplex PCR provides a practical and effective approach. In addition to the identification of agents, retrospective studies of the incidence of agents will shed light on the clinical approaches in terms of the agents to be considered in the preliminary diagnosis. We consider that our results are valuable in terms of the high number of samples examined by the national virology reference laboratory over a 9-year period, and will contribute to clinicians' understanding of the epidemiology of meningitis in our country, and assist in identifying when and how to investigate patients for possible meningitis.

Bayrakdar, M. Enes/0000-0001-9446-0988 WOS: 000503800700001 A priority-based data communication approach, developed by employing cognitive radio capacity for sensor nodes in a wireless terrestrial sensor network (TSN), has been proposed. Data sensed by a sensor node-an unlicensed user-were prioritized, taking sensed data importance into account. For data of equal priority, a first come first serve algorithm was used. Non-preemptive priority scheduling was adopted, in order not to interrupt any ongoing transmissions. Licensed users used a nonpersistent, slotted, carrier sense multiple access (CSMA) technique, while unlicensed sensor nodes used a nonpersistent CSMA technique for lossless data transmission, in an energy-restricted, TSN environment. Depending on the analytical model, the proposed wireless TSN environment was simulated using Riverbed software, and to analyze sensor network performance, delay, energy, and throughput parameters were examined. Evaluating the proposed approach showed that the average delay for sensed, high priority data was significantly reduced, indicating that maximum throughput had been achieved using wireless sensor nodes with cognitive radio capacity.

WOS: 000508136400005 There are fundamentally two different communication media in wireless underground sensor networks. The first of these is a solid medium where the sensor nodes are buried underground and wirelessly transmit data from underground to aboveground. The second is an underground medium such as tunnel, cave etc. and the data is transmitted from underground to the aboveground through partially solid medium. The quality of conununication is greatly influenced by the humidity of the soil in both environments. The placement of wireless underground sensor nodes at hard-to-reach locations makes energy efficient work compulsory. In this paper, rule based collector station selection scheme is proposed for lossless data transmission in underground sensor networks. In order for sensor nodes to transmit energy-efficient lossless data, rulebased selection operations are carried out with the help of fuzzy logic. The proposed wireless underground sensor network is simulated using Riverbed software, and fuzzy logic-based selection scheme is implemented utilizing Matlab software. In order to evaluate the performance of the sensor network; the parameters of delay, throughput and energy consumption are investigated. Examining performance evaluation results, it is seen that average delay and maximum throughput are accomplished in the proposed underground sensor network. Under these conditions, it has been shown that the most appropriate collector station selection decision is made with the aim of minimizing energy consumption.

Background The aim of this study was to evaluate the success of the artificial intelligence (AI) system in implant planning using three-dimensional cone-beam computed tomography (CBCT) images. Methods Seventy-five CBCT images were included in this study. In these images, bone height and thickness in 508 regions where implants were required were measured by a human observer with manual assessment method using InvivoDental 6.0 (Anatomage Inc. San Jose, CA, USA). Also, canals/sinuses/fossae associated with alveolar bones and missing tooth regions were detected. Following, all evaluations were repeated using the deep convolutional neural network (Diagnocat, Inc., San Francisco, USA) The jaws were separated as mandible/maxilla and each jaw was grouped as anterior/premolar/molar teeth region. The data obtained from manual assessment and AI methods were compared using Bland–Altman analysis and Wilcoxon signed rank test. Results In the bone height measurements, there were no statistically significant differences between AI and manual measurements in the premolar region of mandible and the premolar and molar regions of the maxilla (p > 0.05). In the bone thickness measurements, there were statistically significant differences between AI and manual measurements in all regions of maxilla and mandible (p Conclusions Development of AI systems and their using in future for implant planning will both facilitate the work of physicians and will be a support mechanism in implantology practice to physicians.

Objective: In this study, we aimed to analyze the demographic characteristics, symptoms, and comorbidities of 504 patients hospitalized for COVID-19. We also sought to describe the relationship between these features and intensive care unit (ICU) admission and mortality. Material and Methods: This study is a descriptive study involving 504 COVID-19 patients hospitalized between 16.03.2020 and 07.05.2020 at Istanbul University’s Faculty of Medicine Hospital. Information about the patients was obtained from the hospital automation system and evaluated retrospectively. Results: The average age of the 504 patients was 56±15.14, and 59.1% of them were male. The proportion of the patients admitted into ICU 11.9% and for 8.52% of them the disease resulted in death. Real time polymerase chain reaction (RT-PCR) test results were positive for 60.5% of the patients. The median time spent in the hospital was eight days. Fifty six percent of the patients had at least one accompanying comorbid disease, with hypertension (39.3%) and diabetes (20.8%) being the most common. Being 65 years old or older (p

In this paper, a monitoring technique based on the wireless sensor network is investigated. The sensor nodes used for monitoring are developed in a simulation environment. Accordingly, the structure and workflow of wireless sensor network nodes are designed. Time-division multiple access (TDMA) protocol has been chosen as the medium access technique to ensure that the designed technique operates in an energy-efficient manner and packet collisions are not experienced. Fading channels, i.e., no interference, Ricean and Rayleigh, are taken into consideration. Energy consumption is decreased with the help of ad-hoc communication of sensor nodes. Throughput performance for different wireless fading channels and energy consumption are evaluated. The simulation results show that the sensor network can quickly collect medium information and transmit data to the processing center in real time. Besides, the proposed technique suggests the usefulness of wireless sensor networks in the terrestrial areas. WOS:000557361400007 2-s2.0-85074493501

Background: Various variants of the covid-19 have started to attract attention recently. The clinical course of these variants and possible predictive parameters are being investigated. This study aimed to examine the relationship between thiol levels, which are indicators of oxidative stress, and variant covid-19 types. Methods: In this cross-sectional study, patients with a diagnosis of classic covid-19 and patients with a diagnosis of variant covid-19 with mild and moderate symptoms followed in the clinical observatory of Ankara city hospital were included in the study group. The patients were divided into two groups according to the covid-19 type as variant and classic covid-19, and a healthy control group is added for comparison. A complete blood count and thiol analysis are performed from the venous blood samples. Obtained results were compared between groups, and the ROC analysis is performed. Results: Thiol levels were significantly lower in patients with a diagnosis of Covid-19 compared to the control group. In terms of WBC, lymphocyte, neutrophil, NLR, ferritin and thiol parameters, patients with variant covid-19 differed significantly from patients with a classic covid-19 diagnosis. Thiol levels’ cut-off values to distinguish between variant covid-19 patients and control group from classical covid-19 patients were almost identical (423 and 422 µmol/L, respectively). Conclusions: It seems possible to use thiol as a sensitive, specific and cost-effective marker to suspect variant covid-19 cases. Since this study is probably the first example in this subject, it would form a basis for further studies. Keywords: Covid-19, SARS-CoV-2, variant covid-19, thiol, oxidative stress.

BACKGROUND/OBJECTIVES Obesity and periodontitis are systemic subclinical inflammatory diseases with established negative renal effects. The aim of this animal study was to thoroughly investigate the possible effects of these two diseases on renal structure and function. METHODS Thirty-two male Sprague Dawley rats were divided into four groups: control (C), obesity (Ob), experimental periodontitis (Ep), and Ob + Ep. The first 16 weeks of the experiment were aimed for the induction of obesity and the last 5 weeks for the induction of periodontitis. Throughout the experimental period, the C and Ep groups were fed standard rat chow, while the Ob groups (Ob and Ob + Ep) were fed high-fat rat chow. Right after the establishment of obesity, periodontal tissue destruction was achieved by placing 3.0 silk sutures in sub-paramarginal position around the cervices of mandibular right-left first molar teeth and preserving them for 5 weeks. On the last day of the 22nd week, following blood collection, all rats were euthanized, and kidneys and mandibles were collected. Alveolar bone loss was measured on microcomputed tomographic slices. Histopathological evaluations (light microscopy, semi-quantitative analysis of renal corpuscle area, and immunohistochemical analysis of caspase-3 activity) were done on right kidneys and biochemical evaluations (malonyl-aldehyde [MDA], glutathione [GSH], total oxidant status [TOS], total antioxidant status [TAS], oxidative stress [OSI], tumor necrosis factor-α [TNF-α], interleukin-1β [IL-1β], matrix metalloproteinase [MMP]-8, MMP-9, and cathepsin D [CtD] levels) were done on left kidneys. Renal functional status was evaluated with levels of serum creatinine, urea, and cystatin C. RESULTS Periodontal bone loss was significantly higher in the Ep and Ob + Ep groups, compared with the C and Ob groups (p .05). While the atypical glomeruli score was significantly higher in the Ob + Ep group than in all other groups (p

Bayrakdar, M. Enes/0000-0001-9446-0988 WOS: 000501371400015 PubMed: 31741289 In this work, the IEEE 802.11af technology-based wireless sensor network for health data monitoring with priority classes is proposed. In IEEE 802.11af technology, a White Space Device (WSD), a Station (STA), and an Access Point (AP) communicate through television white spectrum opportunistically without causing any harmful interference to licensed` services. In the proposed network; WSDs, STA, and AP employ Frequency Division Multiple Access (FDMA) technique with the aim of communicating through the white space spectrum determined by White Space Map (WSM). WSD collects health data such as body temperature and blood pressure from an implant or on-body sensors. The priority class is determined according to the emergency of a patient as red, yellow, and green. After obtaining the analytical model of the proposed network, the simulation model is carried out using Riverbed Modeler. The graphical results prove the validity and applicability of the proposed network in terms of delay (0.17 s) and energy consumption (4.7 mJ/s) without any spectrum cost for priority-based health data monitoring. Graphical abstract Cognitive radio based IEEE 802.11af environment for priority based health data monitoring.

Bayrakdar, M. Enes/0000-0001-9446-0988 WOS: 000503399200083 Wireless underground sensor networks are the new area of research. It is widely used in many engineering applications, from smart irrigation to security and precision agriculture. Some of the application areas of wireless underground sensor networks are underground with space, such as tunnel, cave, and so on, while some consist of no spaced underground solid areas as well. In this context, wireless underground sensor networks have recently become very important for precision agriculture purposes. In this paper, a smart insect pest detection technique with qualified underground wireless sensor nodes for precision agriculture has been investigated with a mathematical simulation model. In a simulated smart technique, insect pest detection is assumed to be carried out with a qualified acoustic sensor. In order to evaluate the performance of the underground network structure, the received signal strength and path loss parameters are examined. As the depth distance increases, the increase in path loss of communication has been revealed. The obtained performance evaluation result reveals the need for signal transmission with different transmitter power for depth-based communication in wireless underground sensor networks.

Background Colorectal cancer (CRC) screening rates are low in the general population and among health care providers. The aim of this study was to evaluate the CRC screening practices of general surgeons who provide specialized diagnostic testing and CRC treatment and to examine the CRC screening behaviors of their first-degree family members. Methods A cross-sectional survey was conducted among general surgeons who attended the 21st National Surgical Congress in Turkey held from April 11th to 15th, 2018. The survey included items on demographics, screening-related attitude, CRC screening options, barriers to CRC screening, and surgeons’ annual volumes of CRC cases. Results A total of 530 respondents completed the survey. Almost one-third of the responding surgeons (29.4%, n = 156) were aged over 50 years, among whom approximately half (47.1%, n = 74) reported having undergone CRC screening and preferring a colonoscopy as the screening modality (78.4%). Among general surgeons aged 50 years and older, high-volume surgeons (≥25 CRC cases per year) were more likely to undergo screening compared with low-volume surgeons (n = 210) of their first-degree relatives were up-to-date with CRC screening, mostly with colonoscopy. Compared to low-volume surgeons aged below 50 years, high-volume surgeons’ first-degree relatives were more likely to be up-to-date with CRC screening. Conclusion The survey results demonstrated that routine screening for CRC among surgeons and/or their first-degree relatives is currently not performed at the desired level. However, high-volume surgeons are more likely to participate in routine screening.

The aim of the present study is to identify the prevalence of radix entomolaris in mandibular first and second molars and to determine morphological classifications and associations with other root and canals. Mandibular first and second molar teeth of 850 Turkish patients were evaluated using cone-beam computed tomography. A total of 2800 mandibular first molars and second molars were screened. The CBCT examination was performed at five different axial levels. The prevalence of total radix entomolaris, unilateral–bilateral, right–left side and gender distributions, and the classification of radix entomolaris’s canal configurations were measured. Radix entomolaris was found in 2.9% (n = 25) of the patients and 1.2% (n = 34) of the teeth. The prevalence of radix entomolaris in mandibular first molars was higher than in mandibular second molars (p

Aim: Bilateral sagittal split ramus osteotomy (BSSRO) is commonly used to correct mandibular deformities. The first cut for this osteotomy is performed on the medial aspect above the lingula. During this procedure; The most feared intraoperative complication, the undesired fracture. Most of the BSSRO complications consist of condyle fracture or buccal/lingual plate fracture. The aim of this study was to determined the distance between the lingula and the sigmoid notch which is a surgical importance for BSSRO. Material and Methods: This retrospective study composed of the cone beam computed tomography images that were obtained at the our clinic. The sample compromised 70 patients (32 males and 38 females, with an age range of 12 to 28 years). The perpendicular distance between the fixed plane and upper limit of lingula was measured. The sample comprised 70 subjects (32 males and 38 females, with an age range of 12 to 28 years). The obtained data were statistically evaluated. Results: The minimum distance of the between fixed plane passing from sigmoid notch with lingula was found as a minimum of 4.80mm and a maximum of 19.20mm (mean±std. dev.= 11.99mm±2.40, n=140). The right and left side measurement ranged from 4.80mm to 16.4mm (mean±std. dev=11.34mm±2.26, n=70) and 7.72mm to 19.20mm (mean±std. dev.= 12.64mm±2.39, n=70), respectively. Conclusion: The findings obtained in this study provide a guideline for surgeons performing BSSRO on young populations in Turkey. Pre-procedural three-dimensional evaluation provides valuable information to prevent undesirable fractures. Keywords : Horizontal Ramus Osteotomy, CBCT, Sagittal Split Osteotomy SAGITTAL SPLIT RAMUS OSTEOTOMISINDE RAMUS KESISI ICIN GUVENILIR SINIRLARIN KONIK ISINLI BILGISAYARLI TOMOGRAFI ILE BELIRLENMESI: RETROSPEKTIF PILOT CALISMA OZ Amac : Bilateral sagittal split ramus osteotomisi, mandibular deformiteleri duzeltmek icin siklikla kullanilan cerrahi bir yontemdir. Bu osteotomi icin ilk kesi lingula uzerinden gecen bir hat uzerinde gerceklestirilir. Bu cerrahi sirasinda en korkulan intraoperatif komplikasyon istenmeyen kirik olusumudur. Operasyon esnasinda hem proksimal hem de distal segmentlerde kirik olusabilir. Bu calismanin amaci, guvenli bir bilateral sagittal split ramus osteotomisi icin cerrahi onemi olan lingula ve sigmoid centik arasindaki mesafeyi belirlemektir. Gerec ve Yontem: Bu retrospektif calisma, klinigimizde cesitli dental sebeplerle elde edilen konik isinli bilgisayarli tomografi goruntuleri uzerinde gerceklestirildi. Aksiyel duzlem, sigmoid centikten gececek sekilde konumlandirilarak, olusturulan sabit duzlem ile lingula ust siniri arasindaki dikey mesafe olculdu. Orneklem 70 kisinin (12-28 yas araliginda, 32 erkek, 38 kadin) verilerini icermekteydi. Veriler istatistiksel olarak degerlendirildi. Bulgular: Minimum mesafe 4.8 mm maksimum mesafe 19 mm olarak bulundu (ort±std sapma=11,99 mm±2.40, n=140). Sag ve sol taraf olcumleri sirasiyla 4.80 mm’den16.4mm’ye (ort±std. sapma= 11.34mm± 2.26, n=70), 7.72mm’den 19.20mm’ye (std. dev.= 12.64mm±2.39, n=70) degismekteydi. Sonuc : Bu calismada elde edilen bulgular genc Turk populasyonuna bilateral sagittal split ramus osteotomisi icin cerrahlara bir rehber olabilir. Prosedur oncesi uc boyutlu degerlendirme, istenmeyen frakturlerin onlenmesinde degerli bilgiler saglar. Anahtar Kelimeler: Horizontal Ramus Kesisi, KIBT, Sagittal Split Osteotomisi

Background The aim of this study was to evaluate the levels of serum and gingival crevicular fluid (GCF) human beta-defensin-2 (hBD-2), an antimicrobial peptide that takes roles in inflammatory diseases, in patients with chronic periodontitis (CP). Subjects and Methods A total of one hundred and one individuals, 59 controls and 42 patients with CP, participated in this study. Clinical index measurements were recorded during the periodontal examination, and radiographic evaluation was also performed. The serum and gingival crevicular fluid (GCF) samples were taken from all of the participants, and the hBD-2 levels were determined biochemically by enzyme-linked immunosorbent assay (ELISA). Results In our study, hBD-2 GCF levels in CP (stages II-IV periodontitis based on the new 2018 classification of periodontal diseases) group (2.77 ng/30 s) were higher than in the periodontally healthy (2.51 ng/30 s;p = .047) individuals. In contrast, serum hBD-2 levels in CP (2.92 ng/ml) were lower compared with those in healthy controls (7.75 ng/ml,p < .001). Conclusion Interestingly, our results showed that while higher hBD-2 GCF levels are associated with CP, lower serum hBD-2 levels were detected in CP.

Telemedicine offers an excellent opportunity to provide continuing health care for those in need during local/global pandemics and disasters. It provides a safe and effective communication tool between health professionals and can be used as "forward triage"to manage medical/dental emergencies and to minimize the contact between the patients and clinicians during the coronavirus disease (COVID-19) pandemic. Patients with noncommunicable diseases, like cancer, diabetes, cardiovascular, or chronic respiratory diseases, may present with critical health problems due to less access to health care systems during global disasters; opportunities for screening oral mucosa might be significantly disrupted, leading to delayed diagnosis of malignant/potentially malignant lesions. Telemedicine and oral health care associated mobile applications should be implemented to provide equal access to care, to eliminate unnecessary visits to health centers, and to improve practical coordination between professionals and health facilities. © Society for Disaster Medicine and Public Health, Inc. 2021.

Objectives The goal of this study was to develop and evaluate the performance of a new deep-learning (DL) artificial intelligence (AI) model for diagnostic charting in panoramic radiography. Methods One thousand eighty-four anonymous dental panoramic radiographs were labeled by two dento-maxillofacial radiologists for ten different dental situations: crown, pontic, root-canal treated tooth, implant, implant-supported crown, impacted tooth, residual root, filling, caries, and dental calculus. AI Model CranioCatch, developed in Eskisehir, Turkey and based on a deep CNN method, was proposed to be evaluated. A Faster R-CNN Inception v2 (COCO) model implemented with the TensorFlow library was used for model development. The assessment of AI model performance was evaluated with sensitivity, precision, and F1 scores. Results When the performance of the proposed AI model for detecting dental conditions in panoramic radiographs was evaluated, the best sensitivity values were obtained from the crown, implant, and impacted tooth as 0.9674, 0.9615, and 0.9658, respectively. The worst sensitivity values were obtained from the pontic, caries, and dental calculus, as 0.7738, 0.3026, and 0.0934, respectively. The best precision values were obtained from pontic, implant, implant-supported crown as 0.8783, 0.9259, and 0.8947, respectively. The worst precision values were obtained from residual root, caries, and dental calculus, as 0.6764, 0.5096, and 0.1923, respectively. The most successful F1 Scores were obtained from the implant, crown, and implant-supported crown, as 0.9433, 0.9122, and 0.8947, respectively. Conclusion The proposed AI model has promising results at detecting dental conditions in panoramic radiographs, except for caries and dental calculus. Thanks to the improvement of AI models in all areas of dental radiology, we predict that they will help physicians in panoramic diagnosis and treatment planning, as well as digital-based student education, especially during the pandemic period.

OBJECTIVE We aimed to present the radiologic characteristics of maxillofacial soft tissue calcifications with a comparison of cone beam computed tomography (CBCT) and panoramic radiography (PR) findings. MATERIALS AND METHODS The study was based on CBCT images obtained for different purposes between October 2017 and September 2018. The absence, location and radiological characteristics of some calcifications were evaluated in 252 patients. Statistical analysis was performed with SPSS version 21.0; P

This randomized clinical trial aimed to compare the efficacy of an oral irrigator and an interdental brush in patients with peri-implant mucositis clinically and biochemically at different time points (at baseline and at the 2nd, 4th, and 12th weeks). Forty-five patients with at least one implant with peri-implant mucositis were included in the present study (n = 45). The patients were divided into three groups: oral irrigator + toothbrush (OI group, n = 15), interdental brush + toothbrush (IB group, n = 15), and toothbrush only (control) (C group, n = 15). The modified plaque index (mPlI), modified sulcus bleeding index (mSBI), probing pocket depth (PPD), probing attachment level (PAL), and bleeding on probing (BOP) were recorded at baseline and at the 2nd, 4th, and 12th weeks. The levels of interleukin 1 beta (IL-1β), transforming growth factor-beta (TGF-β), tissue-type plasminogen activator (t-PA), and plasminogen activator inhibitor-1 (PAI-1) were also determined in the peri-implant crevicular fluid samples biochemically. The mSBI and t-PA at the 2nd week (p = 0.003; p = 0.003); the mPlI, mSBI, BOP, t-PA, and PAI-1 at the 4th week (p

The current study aimed to investigate the possible relationship between periodontal status and sexual dysfunction in perimenopausal women.This study was conducted on 106 participants. After the evaluation of the sexual functioning of participants with the Female Sexual Function Index (FSFI), their periodontal status and decayed-missing-filled teeth (DMFT) were assessed using appropriate indexes and obtained results were recorded for comparisons. Participants were divided into two groups by the periodontal status. Patients with periodontitis were grouped by the stage and the extent of the disease. Besides, participants were grouped according to the bleeding on probing (BOP) ratios for more detailed analyses.A negative significant correlation was observed between total FSFI scores and each of the clinical periodontal parameters. Total FSFI scores and the scores of arousal, lubrication, orgasm, satisfaction, and pain domains were significantly lower in periodontitis patients (p .05). When the patients were grouped as having localized or generalized periodontitis or whether they had stage-I, -II, and -III periodontitis, no statistically significant differences were observed in the distribution of general sexual dysfunction parameters across the groups (p .05).Periodontal status in perimenopausal women may be associated with sexual dysfunction.

Ultrasound is a method used in medical imaging since the 1950s. It is a noninvasive, relatively cheap imaging method that has important advantages including easy to use and free of ionizing radiation. Technological developments have led to significant improvements in ultrasound imaging over time. Advances in ultrasonography imaging contain improvements in signal processing, imaging methods, and clinical practice.

Poliomyelitis was a disease feared worldwide, striking suddenly and paralysing mainly children for life. Monitoring of suspected cases of poliomyelitis is carried out with Acute Flaccid Paralysis (AFP) surveillance in Turkey. This study examines national data of AFP surveillance and the epidemiology of enteroviruses (EV) in Turkey from 2000 to 2019 and gives an overview of the detected serotypes of EVs. A total of 13,640 samples collected from patients with 5216 AFP pre-diagnosed cases (2 samples from each patient) and 3,208 contacts, during a 20-year period (2000–2019) were investigated. All isolated polioviruses were tested for their wild or vaccine origin according to the WHO recommended protocol by PCR and sequencing analysis were performed. Enterovirus positivity was detected in a total of 915 cases, which were identified as 204 Sabin-like polio virus (SLPV) and 711 non-polio enterovirus (NPEV). Of the 204 SLPV, 141 (69.1%) AFP were detected in patients and 63 (30.9%) were detected in samples taken from their contacts. Of the 711 NPEVs, 516 (72.5%) were from AFP cases and 195 (27.5%) were detected in samples taken from their contacts. It is concluded that the reason for the higher detection rate of NPEV in samples from AFP pre-diagnosed cases is attributed to the polio vaccination rates reaching 97% between 2008 and 2019 in Turkey. The most frequently detected NPEV serotypes were Coxackie A24, B3, and Echo 30. This retrospective study is the first comprehensive study in Turkey to evaluate the results of the AFP surveillance in the last 20 years.

Radiological examination has an important place in dental practice, and it is frequently used in intraoral imaging. The correct numbering of teeth on radiographs is a routine practice that takes time for the dentist. This study aimed to propose an automatic detection system for the numbering of teeth in bitewing images using a faster Region-based Convolutional Neural Networks (R-CNN) method.The study included 1125 bite-wing radiographs of patients who attended the Faculty of Dentistry of Ordu University from 2018 to 2019. A faster R-CNN an advanced object identification method was used to identify the teeth. The confusion matrix was used as a metric and to evaluate the success of the model.The deep CNN system (CranioCatch, Eskisehir, Turkey) was used to detect and number teeth in bitewing radiographs. Of 715 teeth in 109 bite-wing images, 697 were correctly numbered in the test data set. The F1 score, precision and sensitivity were 0.9515, 0.9293 and 0.9748, respectively.A CNN approach for the analysis of bitewing images shows promise for detecting and numbering teeth. This method can save dentists time by automatically preparing dental charts.

Objectives: Myroides spp. is an environmental pathogen and causes disease in immunocompromised patients. In this study, we report an outbreak of urinary tract infections caused by M. odoratimimus in a university hospital in Turkey. Methods: A total of 25 M. odoratimimus strains isolated from the clinical samples of 20 patients in our intensive care units and clinics were included in the study. Phenotypic and genotypic identification of isolates was performed using conventional methods, VITEK®-2 automated identification system, Matrix Assisted Laser Desorption/Ionisation-Time of Flight Mass Spectrometry and 16S-RNA Microbial Diagnosis methods. In addition, Repetitive Extragenic Palindromic Elements (REP) PCR Assay method was applied for molecular epidemiological analysis. Results: All cases were diagnosed with nosocomial urinary tract infection, except for one case diagnosed with nosocomial bacteraemia. One of the M. odoratimimus isolates was sensitive to piperacillin/tazobactam (MIC: ≤4 µg/ml) and one isolate was moderately sensitive to cefepime (MIC: 16 µg/ml). Other M. odoratimimus isolates were resistant to the tested antibiotics of beta lactams, monobactams, carbapenems, aminoglycosides, fluoroquinolones and sulphonamides. When 10 isolates were evaluated with the REP PCR method, DNA finger print similarities were visually determined and there was a similar DNA pattern among them. Myroides source was not detected in environmental samples. Conclusion: Clinicians should consider that Myroides spp. isolates with multiple and broad-spectrum drug resistance may be a serious nosocomial pathogen like Pseudomonas aeruginosa or Acinetobacter baumannii. In order to choose the best treatment regimen, this atypical pathogen needs to be quickly identified and antibiotic susceptibility tests performed.

Two main aims of this animal study were to inspect the possible effects of periodontitis on the structure and functions of the kidneys and the therapeutic effectiveness of melatonin.Twenty-four male Sprague-Dawley rats were randomly divided into three groups: control, experimental periodontitis (Ep), and Ep-melatonin (Ep-Mel). Periodontitis was induced by placing 3.0-silk sutures sub-paramarginally around the cervix of right-left mandibular first molars and maintaining the sutures for 5 weeks. Then melatonin (10 mg/kg body weight/day, 14 days), and the vehicle was administered intraperitonally. Mandibular and kidney tissue samples were obtained following the euthanasia. Periodontal bone loss was measured via histological and microcomputed tomographic slices. On right kidney histopathological and immunohistochemical, and on the left kidney biochemical (malonyl-aldehyde [MDA], glutathione, oxidative stress [OSI], tumor necrosis factor [TNF]-α, interleukin [IL]-1β, matrix metalloproteinase [MMP]-8, MMP-9, and cathepsin D levels) evaluations were performed. Renal functional status was analyzed by levels of serum creatinine, urea, cystatin-C, and urea creatinine.Melatonin significantly restricted ligature-induced periodontal bone loss (P 0 .01) and suppressed the levels of proinflammatory cytokines (TNF-α and IL-1β), oxidative stress (MDA and OSI), and proteases (MMP-8, MMP-9, and CtD) that was significantly higher in the kidneys of the rats with periodontitis (P 0.05). In addition, periodontitis-related histological damages and apoptotic activity were also significantly lower in the Ep-Mel group (P 0.05). However, the markers of renal function of the Ep group were detected slightly impaired in comparison with the control group (P 0.05); and the therapeutic activity of melatonin was limited (P 0.05).Melatonin restricts the periodontitis-induced inflammatory stress, apoptosis, and structural but not functional impairments.