Background: Stenotrophomonas maltophilia is a non-fermentative gram-negativebacillus which is widely recognised as an important nosocomial pathogen causing pneumonia,blood-stream, wound and urinary tract infections, particularly in immunosuppressed patients. Theaim of this study was to evaluate a nosocomial outbreak of by S. maltophilia in an intensive careunit of a tertiary hospital and evaluate unexpected multiclonality.Methods: A total of 11 isolates from respiratory cultures in intensive care unit of a 24 bedtertiary hospital obtained over a one months period and one isolate obtained from the nebuliserduring environmental screening were investigated. The bacteria were identified by Phoenix 100system. The clonal relatedness was evaluated by PFGE and semi-automated repetitive sequencebasedPCR. Genotyping tests were repeated for 10 serial subcultures.Results: PFGE and DiversiLab yielded 10 genotypic profiles for 12 isolates. Four to eightdifferent genotypes were observed from 10 subcultures of the same isolate.Conclusion: We conclude that, high genetic diversity and supposed multiclonalappearance of the outbreak isolates may be due to changing profiles during subcultures mostprobably depending on hypermutation.

Purpose: The aim of this study was to assess the performance of a deep learning system for permanent tooth germ detection on pediatric panoramic radiographs. Materials and Methods: In total, 4518 anonymized panoramic radiographs of children between 5 and 13 years of age were collected. YOLOv4, a convolutional neural network (CNN)-based object detection model, was used to automatically detect permanent tooth germs. Panoramic images of children processed in LabelImg were trained and tested in the YOLOv4 algorithm. True-positive, false-positive, and false-negative rates were calculated. A confusion matrix was used to evaluate the performance of the model. Results: The YOLOv4 model, which detected permanent tooth germs on pediatric panoramic radiographs, provided an average precision value of 94.16% and an F1 value of 0.90, indicating a high level of significance. The average YOLOv4 inference time was 90 ms. Conclusion The detection of permanent tooth germs on pediatric panoramic X-rays using a deep learning-based approach may facilitate the early diagnosis of tooth deficiency or supernumerary teeth and help dental practitioners find more accurate treatment options while saving time and effort.

ABSTRACT The first dental examination is a major step that is affected by many factors and determines the dental treatment process. The main objective of this study was to evaluate the association of child temperament with child dental anxiety, parental dental anxiety, dental behaviour and dental caries. The study consisted of 100 children aged 3 to 6 who were attending their first dental examination and their accompanying parents. The Facial Image Scale (FIS), Frankl’s Behaviour Scale (FBS), Corah’s Dental Anxiety Scale (CDAS) and the Short Temperament Scale for Children (STSC) were used for assessment. The DMFT (decayed, missing and filled teeth) score of each child was recorded. Children who exhibited negative behaviour on the FBS had the highest rhythmicity scores (p = 0.008). The mean DMFT score of children in the rhythmicity temperamental dimension was relatively high (p = 0.008). The parents of children defined as negative on the FBS had high dental anxiety levels on CDAS (p < 0.001). Children whose parents had higher dental anxiety levels showed higher dental anxiety (p = 0.007). The success rate of dental treatment procedures may be increased by improving dentists’ knowledge of dental anxiety related to the child’s temperament and integrating parental support to reduce dental anxiety.
Dental Care for Children ; Dental Anxiety ; Cognitive Behavioral Therapy ; Temperament ; Dental Caries

Purpose: The aim of this study was to evaluate the ability of 18F-FDG PET/CT texture analysis to predict the exact pathological outcome of thyroid incidentalomas. Methods: 18F-FDG PET/CT images between March 2010 and September 2018 were retrospectively reviewed in patients with focal 18F-FDG uptake in the thyroid gland and who underwent fine needle aspiration biopsy from this area. The focal uptake in the thyroid gland was drawn in 3D with 40% SUVmax threshold. Features were extracted from volume of interest (VOI) using the LIFEx package. The features obtained were compared in benign and malignant groups, and statistically significant variables were evaluated by receiver operating curve (ROC) analysis. The correlation between the variables with area under curve (AUC) value over 0.7 was examined; variables with correlation coefficient less than 0.6 were evaluated with machine learning algorithms. Results: Sixty patients (70% train set, 30% test set) were included in the study. In univariate analysis, a statistically significant difference was observed in 6 conventional parameters, 5 first-, and 16 second-order features between benign and malignant groups in train set (p < 0.05). The feature with the highest benign-malignant discriminating power was GLRLMRLNU (AUC:0.827). AUC value of SUVmax was calculated as 0.758. GLRLMRLNU and SUVmax were evaluated to build a model to predict the exact pathology outcome. Random forest algorithm showed the best accuracy and AUC (78.6% and 0.849, respectively). Conclusion In the differentiation of benign-malignant thyroid incidentalomas, GLRLMRLNU and SUVmax combination may be more useful than SUVmax to predict the outcome.

Purpose: Portal hypertension (PH) and its complications have a significant impact on morbidity and mortality. This study aimed to evaluate the etiology; clinical, laboratory, and endoscopic findings; treatment approaches; long-term outcomes; and prognosis of pediatric PH. Methods: This retrospective study included 222 pediatric patients diagnosed with PH between 1998 and 2016, and data encompassing clinical, laboratory, and radiological features; treatments; and complications were analyzed. Results: The most common causes of PH were portal vein thrombosis (20.3%), progressive familial intrahepatic cholestasis (18.9%), and biliary atresia (12.2%). Among the enrolled patients, 131 (59.0%) were included in the cirrhotic group and 91 (41.0%) in the noncirrhotic group. Hepatomegaly and increased transaminase levels were more frequent in the cirrhotic group than in the non-cirrhotic group. Additionally, portal gastropathy, esophageal varices, and variceal bleeding were more frequent in the non-cirrhotic group, whereas ascites, hepatopulmonary syndrome and hepatic encephalopathy were more common in the cirrhotic group. The incidence of hepatomegaly was higher in the presinusoidal group than in the prehepatic group (p<0.001). Hyperbilirubinemia was more frequent in the prehepatic group (p=0.046). The frequency of esophageal varices was similar between the prehepatic and presinusoidal groups; however, variceal bleeding was more frequent in the prehepatic group (p=0.002). Conclusion Extrahepatic portal vein obstruction, genetic-metabolic diseases, and biliary atresia were the most prevalent causes of PH in our country. In patients with PH, hepatomegaly, increased transaminase levels, and synthesis dysfunction were suggestive of cirrhotic PH. Notably, PH in patients without cirrhosis might be more severe than that in those with cirrhosis.