Machine learning assessment of dental age classification based on cone-beam CT images: a different approach.

OBJECTIVES: Machine learning (ML) algorithms are a portion of artificial intelligence that may be used to create more accurate algorithmic procedures for estimating an individual's dental age or defining an age classification. This study aims to use ML algorithms to evaluate the efficacy of pulp/tooth area ratio (PTR) in cone-beam CT (CBCT) images to predict dental age classification in adults. METHODS: CBCT images of 236 Turkish individuals (121 males and 115 females) from 18 to 70 years of age were included. PTRs were calculated for six teeth in each individual, and a total of 1416 PTRs encompassed the study dataset. Support vector machine, classification and regression tree, and random forest (RF) models for dental age classification were employed. The accuracy of these techniques was compared. To facilitate this evaluation process, the available data were partitioned into training and test datasets, maintaining a proportion of 70% for training and 30% for testing across the spectrum of ML algorithms employed. The correct classification performances of the trained models were evaluated. RESULTS: The models' performances were found to be low. The models' highest accuracy and confidence intervals were found to belong to the RF algorithm. CONCLUSIONS: According to our results, models were found to be low in performance but were considered as a different approach. We suggest examining the different parameters derived from different measuring techniques in the data obtained from CBCT images in order to develop ML algorithms for age classification in forensic situations.

Rehabilitation Methods for Patients with Geographic Atrophy due to Age-Related Macular Degeneration and Effects of Rehabilitation on Quality of Life.

Purpose: The purpose of the study is to evaluate the low vision rehabilitation methods and to investigate the effect of visual rehabilitation on quality of life in patients with low vision due to geographic atrophy from age-related macular degeneration (ARMD). Methods: The better-seeing eye of 78 patients with geographic atrophy due to ARMD were included in the study. Sociodemographic characteristics, ophthalmological examination findings, and preferred low vision aids for near and distant were recorded. Fifty-seven patients who preferred to use a low vision aid device in daily life were considered as a rehabilitation group, whereas 21 patients who did not use any device were considered as a control group. The National Eye Institute Visual Function Questionnaire (NEI-VFQ-25) was applied to all patients at the initial examination and at least 6 months after the initial examination. Results: In the rehabilitation group, statistically significant increases were found in the overall composite score, and general vision, near and distance activities, social functioning, mental health, role difficulties, and dependency subscale scores of the NEI-VFQ-25 quality of life scale after low vision rehabilitation (p=0.009 for general vision, p < 0.001; for others). In the control group, there was no statistically significant change in any of the subscale scores or the overall score of the scale (p > 0.05). All patients (n = 78) were recommended to use at least one low vision aid for near vision. Hyperocular glasses were recommended for 77 patients (98.72%), magnifiers for 15 patients (19.23%), electro-optical devices for 2 patients (2.56%), and telemicroscope for one patient (1.28%). Furthermore, 17 patients (21.8%) were prescribed more than one low vision aids. However, for distance vision, only 29 patients (37.18%) received a recommendation for a low vision aid. Conclusions: Low vision patients with ARMD-related geographic atrophy should meet with low vision aids as soon as possible and should be included in low vision rehabilitation programs.

Overexpression of the PTEN Gene in Myocardial Tissues of Coronary Bypass Surgery Patients. / Superexpressão Gênica PTEN em Tecidos Miocárdicos de Pacientes de Cirurgia de Revascularização Miocárdica.

BACKGROUND: Coronary artery disease is a complex disorder that causes death worldwide. One of the genes involved in developing this disease may be PTEN. OBJECTIVES: This study aimed to investigate the PTEN gene and protein expression in tissue and blood samples taken from coronary bypass surgery patients. METHODS: Molecular studies were performed at Erciyes University Genome and Stem Cell Center (GENKOK). Right atrial appendage and blood samples were taken from the central vein of 22 coronary bypass surgery patients before starting and ending cardiopulmonary bypass. PTEN expression was determined using quantitative real-time PCR and western blot analysis. The significance level was accepted as p<0.05. RESULTS: There was no significant difference in the PTEN gene expression in blood samples taken before and after cardiopulmonary bypass. However, a substantial increase in both protein and gene expression levels of P-PTEN and PTEN was observed in the tissue samples. Myocardial expression of the PTEN gene was significantly increased at the end of the cardiopulmonary bypass. PTEN gene expression in the post-cardiopulmonary bypass period was increased when compared to the pre-bypass period, but it was insignificant when compared to healthy controls. CONCLUSION: This study first revealed the role of the PTEN gene by analyzing both mRNA and protein expression in coronary bypass patients, appearing in both myocardial tissue and blood samples. Increased levels of PTEN may be a marker in myocardial tissue for patients with coronary artery disease.

FUNDAMENTO: A doença arterial coronariana é um distúrbio complexo que causa morte em todo o mundo. Um dos genes envolvidos no desenvolvimento dessa doença pode ser o PTEN. OBJETIVOS: Nosso objetivo foi investigar a expressão gênica e proteica do PTEN em amostras de tecido e sangue retiradas de pacientes submetidos à cirurgia de revascularização miocárdica. MÉTODOS: Foram realizados estudos moleculares no Centro de estudos do genoma humano e células-tronco da Universidade Erciyes (GENKOK). Amostras do apêndice atrial direito e de sangue foram coletadas da veia central de 22 pacientes submetidos à cirurgia de revascularização miocárdica antes de iniciar e terminar a circulação extracorpórea. A expressão do PTEN foi determinada usando PCR quantitativo em tempo real e análise de Western Blot. O nível de significância aceito foi de p<0,05. RESULTADOS: Não houve diferença significativa na expressão gênica do PTEN em amostras de sangue coletadas antes e depois da circulação extracorpórea. Entretanto, foi observado um aumento substancial nos níveis de expressão gênica e proteica de P-PTEN e PTEN nas amostras de tecido. A expressão gênica miocárdica PTEN aumentou significativamente ao final da circulação extracorpórea. A expressão gênica do PTEN no período pós-circulação extracorpórea aumentou em comparação com o período pré-circulação extracorpórea, mas não foi um aumento significativo em comparação com sujeitos saudáveis do grupo de controle. CONCLUSÃO: Este estudo revelou pela primeira vez o papel do gene PTEN analisando a expressão de mRNA e de proteína em pacientes com revascularização miocárdica, que se manifesta tanto em tecido miocárdico quanto em amostras de sangue. O aumento dos níveis de PTEN pode ser um marcador no tecido miocárdico para pacientes com doença arterial coronariana.

The parental COVID-19 anxiety and emotional exhaustion in healthcare workers: exploring the roles of resilience, prosocialness, and optimism.

Healthcare workers (HCWs) also became the main protagonist of the tragic pandemic story. They have had a markedly higher risk of becoming infected with COVID-19. Outside work, healthcare workers with children have experienced mental health challenges, including the worry that they may carry COVID-19 home and infect their children. Based on these, the current study aimed to examine the effect of parental COVID-19 anxiety on emotional exhaustion and identify the roles of resilience, prosocialness, and optimism in this relationship. The findings demonstrated that prosocialness moderated the relationship between personal COVID-19 anxiety and emotional exhaustion by alleviating the depleting effects of personal COVID-19 anxiety. At the same time, prosocialness reinforced the negative effect of resilience on emotional exhaustion. On the other side, optimism moderated the relationship between parental COVID-19 anxiety and resilience by alleviating the adverse effect of parental COVID-19 anxiety. Moreover, it buffered the exacerbating effect of parental anxiety on personal anxiety. In conclusion, promoting personal resources (i.e., resilience, prosocialness, and optimism) seems an excellent way to mitigate the adverse consequences of the pandemic on mental health. Furthermore, the increment in parental mental health problems during COVID-19 pandemic may have long-term effects on children. Considering this perspective, we need to develop a proactive approach for parents' now and children's futures.

Superexpressão Gênica PTEN em Tecidos Miocárdicos de Pacientes de Cirurgia de Revascularização Miocárdica / Overexpression of the PTEN Gene in Myocardial Tissues of Coronary Bypass Surgery Patients

Resumo Fundamento: A doença arterial coronariana é um distúrbio complexo que causa morte em todo o mundo. Um dos genes envolvidos no desenvolvimento dessa doença pode ser o PTEN. Objetivos: Nosso objetivo foi investigar a expressão gênica e proteica do PTEN em amostras de tecido e sangue retiradas de pacientes submetidos à cirurgia de revascularização miocárdica. Métodos: Foram realizados estudos moleculares no Centro de estudos do genoma humano e células-tronco da Universidade Erciyes (GENKOK). Amostras do apêndice atrial direito e de sangue foram coletadas da veia central de 22 pacientes submetidos à cirurgia de revascularização miocárdica antes de iniciar e terminar a circulação extracorpórea. A expressão do PTEN foi determinada usando PCR quantitativo em tempo real e análise de Western Blot. O nível de significância aceito foi de p<0,05. Resultados: Não houve diferença significativa na expressão gênica do PTEN em amostras de sangue coletadas antes e depois da circulação extracorpórea. Entretanto, foi observado um aumento substancial nos níveis de expressão gênica e proteica de P-PTEN e PTEN nas amostras de tecido. A expressão gênica miocárdica PTEN aumentou significativamente ao final da circulação extracorpórea. A expressão gênica do PTEN no período pós-circulação extracorpórea aumentou em comparação com o período pré-circulação extracorpórea, mas não foi um aumento significativo em comparação com sujeitos saudáveis do grupo de controle. Conclusão: Este estudo revelou pela primeira vez o papel do gene PTEN analisando a expressão de mRNA e de proteína em pacientes com revascularização miocárdica, que se manifesta tanto em tecido miocárdico quanto em amostras de sangue. O aumento dos níveis de PTEN pode ser um marcador no tecido miocárdico para pacientes com doença arterial coronariana.

Abstract Background: Coronary artery disease is a complex disorder that causes death worldwide. One of the genes involved in developing this disease may be PTEN. Objectives: This study aimed to investigate the PTEN gene and protein expression in tissue and blood samples taken from coronary bypass surgery patients. Methods: Molecular studies were performed at Erciyes University Genome and Stem Cell Center (GENKOK). Right atrial appendage and blood samples were taken from the central vein of 22 coronary bypass surgery patients before starting and ending cardiopulmonary bypass. PTEN expression was determined using quantitative real-time PCR and western blot analysis. The significance level was accepted as p<0.05. Results: There was no significant difference in the PTEN gene expression in blood samples taken before and after cardiopulmonary bypass. However, a substantial increase in both protein and gene expression levels of P-PTEN and PTEN was observed in the tissue samples. Myocardial expression of the PTEN gene was significantly increased at the end of the cardiopulmonary bypass. PTEN gene expression in the post-cardiopulmonary bypass period was increased when compared to the pre-bypass period, but it was insignificant when compared to healthy controls. Conclusion: This study first revealed the role of the PTEN gene by analyzing both mRNA and protein expression in coronary bypass patients, appearing in both myocardial tissue and blood samples. Increased levels of PTEN may be a marker in myocardial tissue for patients with coronary artery disease.

Outcomes of transcorneal electrical stimulation therapy in the early stages of retinitis pigmentosa.

BACKGROUND: To investigate the effect of transcorneal electrical stimulation (TES) therapy in patients with retinitis pigmentosa (RP). METHODS: We performed TES therapy in 21 patients with RP in 12 sessions with 1-week intervals. The following parameters obtained before and after the TES therapy were compared statistically; the best corrected visual acuity (BCVA, logMAR), Ishihara color vision level, multifocal electroretinography (mf-ERG) response, automated visual field (VF) outcome, and the 25-item low vision quality-of-life (LVQOL) questionnaire points. RESULTS: The mean age of patients (6 females; 15 males) was 31.67 ± 9.80 years (20-50 years). While increases in BCVA level, color vision level, mf-ERG response in p1 amplitude of ring 1, and LVQOL questionnaire points were statistically significant, changes in VF test and other mf-ERG responses were not. Twenty of the patients (95.24%) stated that they were satisfied with the TES therapy. No considerable side effect was observed in any patient due to the therapy. DISCUSSION: The TES therapy may be an effective and safe treatment modality in slowing the RP progression, especially in the early stages of the disease. Longer-term follow-ups in larger patient populations are warranted.

Evidence for Diverse Prognosis in High-Grade Serous Ovarian Carcinoma: Solid, Pseudoendometrioid, and Transitional-Like; So-Called "SET Morphology" and Progesterone Receptor Status.

OBJECTIVE: High-grade serous ovarian carcinoma (HGSC) is one of the major tumors of the gynecological system with a poor survival rate and variable microscopic appearance. It was suggested that SET (solid, pseudo-endometrioid and transitional-like) morphology in ovarian HGSC is predictably associated with BRCA deficiencies. In this study, we investigated the microscopic patterns and some immunohistochemical markers predicting the prognosis of serous carcinoma. MATERIAL AND METHOD: We re-evaluated 305 HGSC ovarian resections morphologically and calculated the SET morphology percentages for each case. Morphological and immunohistochemical data correlated with the survival and post-treatment disease progression data. RESULTS: The median age at diagnosis was 57 years and the median follow-up period was 3.1 years. The median overall survival (OS) of ovarian carcinoma in SET-predominant tumors (n=60) was 81 months, while for tumors with SET non-dominant morphology (n=63) and non-SET morphology (n=182) it was 59.7 and 44.7 months, respectively. CONCLUSION: Predominant (more than 50%) SET morphology was significantly associated with increased survival rates of HGSC. Immunohistochemically, p53, ERCC1, ER, and PR antibodies were applied and only PR antibody positivity was found to be associated with borderline statistical significance for increased survival rates. Our results suggest that SET morphology may be a potential predictive and prognostic marker in managing the treatment strategies of HGSC.

Effect of Serum Albumin Changes on Mortality in Patients with Peritoneal Dialysis: A Joint Modeling Approach and Personalized Dynamic Risk Predictions.

Peritoneal dialysis (PD) is a frequently used and growing therapy for end-stage renal diseases (ESRD). Survival analysis of PD patients is an ongoing research topic in the field of nephrology. Several biochemical parameters (e.g., serum albumin, creatinine, and blood urea nitrogen) are measured repeatedly in the follow-up period; however, baseline or averaged values are primarily associated with mortality. Although this strategy is not incorrect, it leads to information loss, resulting in erroneous conclusions and biased estimates. This retrospective study used the trajectory of common renal function indexes in PD patients and mainly investigated the association between serum albumin change and mortality. Furthermore, we considered patient-specific variability in serum albumin change and obtained personalized dynamic risk predictions for selected patients at different follow-up thresholds to investigate the effect of serum albumin trajectories on patient-specific mortality. We included 417 patients from the Erciyes University Nephrology Department whose data were retrospectively collected using medical records. A joint modeling approach for longitudinal and survival data was used to investigate the relationship between serum albumin trajectory and mortality of PD patients. Results showed that averaged serum albumin levels were not associated with mortality. However, serum albumin change was significantly and inversely associated with mortality (HR: 2.43, 95% CI: 1.48 to 4.16). Risk of death was positively associated with peritonitis rate, hemodialysis history, and the total number of comorbid and renal diseases with hazard ratios 1.74, 3.21, and 1.41. There was also significant variability between patients. The personalized risk predictions showed that overall survival estimates were not representative for all patients. Using the patient-specific trajectories provided better survival predictions within the follow-up period as more data become available in serum albumin levels. In conclusion, using the trajectory of risk predictors via an appropriate statistical method provided better predictive accuracy and prevented biased findings. We also showed that personalized risk predictions were much informative than overall estimations in the presence of significant patient variability. Furthermore, personalized estimations may play an essential role in monitoring and managing patients during the follow-up period.

Retinal choroidal and retinal nerve fiber layer thickness in former preterm and full-term infants aged 4 to 8 years.

PURPOSE: To compare the retinal thickness at the fovea center, peripapillary retinal nerve fiber layer (RNFL) thickness and choroidal thickness (CT) in former preterm and full-term infants. METHODS: A total of 121 healthy children aged 4-8 years were divided 4 groups: group 1; children born on time, group 2; preterm children without a history of retinopathy of prematurity (ROP), group 3; preterm children with a history of spontaneously regressed ROP and group 4; preterm children who underwent diode laser photocoagulation for ROP. The retinal thickness at the fovea, peripapillary RNFL thickness at global, superior, inferior, nasal and temporal quadrants and submacular CT at 7 different points were measured by using spectral-domain optical coherence tomography. RESULTS: The mean retinal thickness at the fovea center was statistically higher, whereas the mean RNFL thickness values in global, nasal, superior and inferior quadrants were statistically lower in group 4. No difference was found in the mean submacular CT value of any point between the groups. CONCLUSION: Transpupillary diode laser photocoagulation treatment for ROP seems to cause an increase in macular thickness and a decrease in RNFL thickness.

Association between Dietary Glycaemic Index and Glycaemic Load and Adiposity Indices in Polycystic Ovary Syndrome.

Objective: Obesity is a key contributor to metabolic and reproductive outcomes in polycystic ovary syndrome (PCOS). The role of the dietary glycemic index (GI) and load (GL), and adiposity has been debated and studies on PCOS are scarce. We aimed to compare the dietary GI and GL and several anthropometric measurements in PCOS and control women. The association between dietary GI and GL and adiposity indices was examined in this cross-sectional study.Methods and materials: A study population consisted of 65 previously diagnosed with PCOS and 65 healthy women. All participants underwent detailed anthropometric, dietary and physical activity evaluation and categorized based on GI and GL tertiles.Results: When dietary GL was adjusted for age, physical activity level (PAL), and duration of diagnosis, there was a statistically significant inverse association between dietary GL and waist/hip ratio (WHR) (OR: 0.136; 95% CI: 0.021-0.874; p = 0.036) in women with PCOS. Both dietary GI (OR: 8.869; 95% CI: 1.194-65.910; p = 0.033 for tertile 2 in adjustment model) and GL (OR: 7.200; 95% CI: 1.635-31.712; p = 0.009 for tertile 3 in crude model; OR: 5.801; 95% CI: 1.242-27.096; p = 0.025 for tertile 3 in adjustment model) positively associated with WHR in healthy subjects. Also, positive association was observed between dietary GI and waist/height ratio (WHtR) (OR: 0.229; 95% CI: 0.063-0.826; p = 0.024 for tertile 2; OR: 0.277; 95% CI: 0.078-0.988; p = 0.048 for tertile 3) in healthy controls, however after adjustment for age and PAL, statistical significance was lost (OR: 1.051; 95% CI: 0.152-7.261; p = 0.959 for tertile 2; OR: 1.522; 95% CI: 0.225-10.297; p = 0.667 for tertile 3).Conclusion: The results of this study consistent with the literature that PCOS is associated with increased adiposity indices. There was no association between dietary GI/GL and BMI, WC, WHtR, and ABSI but dietary GL was inversely associated WHR in PCOS patients.

MLSeq: Machine learning interface for RNA-sequencing data.

BACKGROUND AND OBJECTIVE: In the last decade, RNA-sequencing technology has become method-of-choice and prefered to microarray technology for gene expression based classification and differential expression analysis since it produces less noisy data. Although there are many algorithms proposed for microarray data, the number of available algorithms and programs are limited for classification of RNA-sequencing data. For this reason, we developed MLSeq, to bring not only frequently used classification algorithms but also novel approaches together and make them available to be used for classification of RNA sequencing data. This package is developed using R language environment and distributed through BIOCONDUCTOR network. METHODS: Classification of RNA-sequencing data is not straightforward since raw data should be preprocessed before downstream analysis. With MLSeq package, researchers can easily preprocess (normalization, filtering, transformation etc.) and classify raw RNA-sequencing data using two strategies: (i) to perform algorithms which are directly proposed for RNA-sequencing data structure or (ii) to transform RNA-sequencing data in order to bring it distributionally closer to microarray data structure, and perform algorithms which are developed for microarray data. Moreover, we proposed novel algorithms such as voom (an acronym for variance modelling at observational level) based nearest shrunken centroids (voomNSC), diagonal linear discriminant analysis (voomDLDA), etc. through MLSeq. MATERIALS: Three real RNA-sequencing datasets (i.e cervical cancer, lung cancer and aging datasets) were used to evalute model performances. Poisson linear discriminant analysis (PLDA) and negative binomial linear discriminant analysis (NBLDA) were selected as algorithms based on dicrete distributions, and voomNSC, nearest shrunken centroids (NSC) and support vector machines (SVM) were selected as algorithms based on continuous distributions for model comparisons. Each algorithm is compared using classification accuracies and sparsities on an independent test set. RESULTS: The algorithms which are based on discrete distributions performed better in cervical cancer and aging data with accuracies above 0.92. In lung cancer data, the most of algorithms performed similar with accuracies of 0.88 except that SVM achieved 0.94 of accuracy. Our voomNSC algorithm was the most sparse algorithm, and able to select 2.2% and 6.6% of all features for cervical cancer and lung cancer datasets respectively. However, in aging data, sparse classifiers were not able to select an optimal subset of all features. CONCLUSION: MLSeq is comprehensive and easy-to-use interface for classification of gene expression data. It allows researchers perform both preprocessing and classification tasks through single platform. With this property, MLSeq can be considered as a pipeline for the classification of RNA-sequencing data.

Accuracy of the use of radiographic visibility of root pulp in the mandibular third molar as a maturity marker at age thresholds of 18 and 21.

Evaluation of the radiographic visibility of root pulp in mandibular third molars has been suggested as an alternative method for estimation of legal age threshold in living individuals when the root apices are mature. Here, we assessed the accuracy of this method for age thresholds of 18 and 21 years. A sample of 463 panoramic radiographs of individuals aged between 16 and 34 years was examined. The root pulp visibility of the mandibular third molars was scored; the stages ranged from 0 to 3. A receiver operating characteristic (ROC) curve and the area under the ROC curve (AUC) were used to select optimal cut-offs for 18- and 21-year-old thresholds. As prognostic predictors, the selected cut-offs were stages 1 and 2 for the 18- and 21-year-old thresholds of both sexes, respectively. For the 18-year-old threshold, the AUC, sensitivity and specificity were 0.829, 83.1% and 66.7% in females; and 0.930, 89.4% and 90.9% in males, respectively. For the 21-year-old threshold, the AUC, sensitivity and specificity were 0.874, 72.8% and 92.0% in females; and 0.906, 85.5% and 88.2% in males, respectively. The accuracy of the method for estimating the 18- and 21-year-old thresholds ranged from moderate to high. Therefore, the method must be used in conjunction with other age estimation methods, especially to predict whether a female has reached 18 years of age.

Investigation of protein quaternary structure via stoichiometry and symmetry information.

The Protein Data Bank (PDB) is the single worldwide archive of experimentally-determined three-dimensional (3D) structures of proteins and nucleic acids. As of January 2017, the PDB housed more than 125,000 structures and was growing by more than 11,000 structures annually. Since the 3D structure of a protein is vital to understand the mechanisms of biological processes, diseases, and drug design, correct oligomeric assembly information is of critical importance. Unfortunately, the biologically relevant oligomeric form of a 3D structure is not directly obtainable by X-ray crystallography, whilst in solution methods (NMR or single particle EM) it is known from the experiment. Instead, this information may be provided by the PDB Depositor as metadata coming from additional experiments, be inferred by sequence-sequence comparisons with similar proteins of known oligomeric state, or predicted using software, such as PISA (Proteins, Interfaces, Structures and Assemblies) or EPPIC (Evolutionary Protein Protein Interface Classifier). Despite significant efforts by professional PDB Biocurators during data deposition, there remain a number of structures in the archive with incorrect quaternary structure descriptions (or annotations). Further investigation is, therefore, needed to evaluate the correctness of quaternary structure annotations. In this study, we aim to identify the most probable oligomeric states for proteins represented in the PDB. Our approach evaluated the performance of four independent prediction methods, including text mining of primary publications, inference from homologous protein structures, and two computational methods (PISA and EPPIC). Aggregating predictions to give consensus results outperformed all four of the independent prediction methods, yielding 83% correct, 9% wrong, and 8% inconclusive predictions, when tested with a well-curated benchmark dataset. We have developed a freely-available web-based tool to make this approach accessible to researchers and PDB Biocurators (http://quatstruct.rcsb.org/).

The Relationship Between Blood Pressure and Sleep Duration in Turkish Children: A Cross-Sectional Study.

OBJECTIVE: As in adults, hypertension is also an important risk factor for cardiovascular disease in children. We aimed to evaluate the effect of sleep duration on blood pressure in normal weight Turkish children aged between 11-17 years. METHODS: This cross-sectional study was conducted in the primary and secondary schools of the two central and ten outlying districts of Kayseri, Turkey. Subjects were 2860 children and adolescents (1385 boys, 1475 girls). Systolic and diastolic blood pressures were measured according to the recommendations of the Fourth Report of the National High Blood Pressure Education Program Working Group on High Blood Pressure in Children and Adolescents. Sleep duration was classified as follows: ≤8 hours, 8.1-8.9 hours, 9.0-9.9 hours or ≥10 hours. RESULTS: For short sleeper boys and girls (participants with a sleep duration ≤8 h) the prevalence of prehypertension and hypertension was 35.0% and 30.8%, respectively. In univariate binary logistic regression analyses (age-adjusted), each unit increment in sleep duration (hours) in boys and girls, decreased the prehypertension and hypertension risk by 0.89 [odds ratio (OR)] [confidance interval (CI); 0.82-0.98] and 0.88 (OR) (CI; 0.81-0.97), respectively (p<0.05). In multiple binary logistic regression analyses [age- and body mass index (BMI)-adjusted] the location of the school and sleep duration categories were shown to be the most important factors for prehypertension and hypertension in both genders, while household income was the most important factor, only in boys. CONCLUSIONS: A sleep duration ≤8 h is an independent risk factor for prehypertension and hypertension in Turkish children aged 11-17 years.

voomDDA: discovery of diagnostic biomarkers and classification of RNA-seq data.

RNA-Seq is a recent and efficient technique that uses the capabilities of next-generation sequencing technology for characterizing and quantifying transcriptomes. One important task using gene-expression data is to identify a small subset of genes that can be used to build diagnostic classifiers particularly for cancer diseases. Microarray based classifiers are not directly applicable to RNA-Seq data due to its discrete nature. Overdispersion is another problem that requires careful modeling of mean and variance relationship of the RNA-Seq data. In this study, we present voomDDA classifiers: variance modeling at the observational level (voom) extensions of the nearest shrunken centroids (NSC) and the diagonal discriminant classifiers. VoomNSC is one of these classifiers and brings voom and NSC approaches together for the purpose of gene-expression based classification. For this purpose, we propose weighted statistics and put these weighted statistics into the NSC algorithm. The VoomNSC is a sparse classifier that models the mean-variance relationship using the voom method and incorporates voom's precision weights into the NSC classifier via weighted statistics. A comprehensive simulation study was designed and four real datasets are used for performance assessment. The overall results indicate that voomNSC performs as the sparsest classifier. It also provides the most accurate results together with power-transformed Poisson linear discriminant analysis, rlog transformed support vector machines and random forests algorithms. In addition to prediction purposes, the voomNSC classifier can be used to identify the potential diagnostic biomarkers for a condition of interest. Through this work, statistical learning methods proposed for microarrays can be reused for RNA-Seq data. An interactive web application is freely available at http://www.biosoft.hacettepe.edu.tr/voomDDA/.

The effect of demographic and disease variables on Schneiderian membrane thickness and appearance.

OBJECTIVES: The purpose of this study was to evaluate the prevalence of sinus mucosal thickening (MT) and mucosal appearance (MA) in a patient population as detected with cone beam computed tomography (CBCT) and to determine the effects of various disease and demographic factors on MT and MA. STUDY DESIGN: The retrospective study consisted of CBCT images of 1000 maxillary arches in 500 patients. The arches were divided into 3 groups (atrophic, partially atrophic, and nonatrophic) according to the type of the maxillary dental crest. The CBCT scans were assessed to detect the prevalence of maxillary sinus MT and MA. χ2 analysis was used to determine the significance of association of periodontal bone loss (PBL), periapical (PA) status, alveolar crest type, age, and gender on sinus MT and MA. RESULTS: MT was significantly associated with PBL (P = .004), PA status (P = .001), and gender (P < .01). MA was significantly associated with PBL (P = .038), PA status (P = .009), and gender (P < .020). There were no significant associations between age or crest type and either MT or MA. CONCLUSIONS: Periodontal bone loss, PA lesions, and gender may have an association with MT of the maxillary sinus.

geneSurv: An interactive web-based tool for survival analysis in genomics research.

Survival analysis methods are often used in cancer studies. It has been shown that the combination of clinical data with genomics increases the predictive performance of survival analysis methods. But, this leads to a high-dimensional data problem. Fortunately, new methods have been developed in the last decade to overcome this problem. However, there is a strong need for easily accessible, user-friendly and interactive tool to perform survival analysis in the presence of genomics data. We developed an open-source and freely available web-based tool for survival analysis methods that can deal with high-dimensional data. This tool includes classical methods, such as Kaplan-Meier, Cox proportional hazards regression, and advanced methods, such as penalized Cox regression and Random Survival Forests. It also offers an optimal cutoff determination method based on maximizing several test statistics. The tool has a simple and interactive interface, and it can handle high dimensional data through feature selection and ensemble methods. To dichotomize gene expressions, geneSurv can identify optimal cutoff points. Users can upload their microarray, RNA-Seq, chip-Seq, proteomics, metabolomics or clinical data as a nxp dimensional data matrix, where n refers to samples and p refers to genes. This tool is available free at www.biosoft.hacettepe.edu.tr/geneSurv. All source code is available at https://github.com/selcukorkmaz/geneSurv under the GPL-3 license.

A comprehensive simulation study on classification of RNA-Seq data.

RNA sequencing (RNA-Seq) is a powerful technique for the gene-expression profiling of organisms that uses the capabilities of next-generation sequencing technologies. Developing gene-expression-based classification algorithms is an emerging powerful method for diagnosis, disease classification and monitoring at molecular level, as well as providing potential markers of diseases. Most of the statistical methods proposed for the classification of gene-expression data are either based on a continuous scale (eg. microarray data) or require a normal distribution assumption. Hence, these methods cannot be directly applied to RNA-Seq data since they violate both data structure and distributional assumptions. However, it is possible to apply these algorithms with appropriate modifications to RNA-Seq data. One way is to develop count-based classifiers, such as Poisson linear discriminant analysis and negative binomial linear discriminant analysis. Another way is to bring the data closer to microarrays and apply microarray-based classifiers. In this study, we compared several classifiers including PLDA with and without power transformation, NBLDA, single SVM, bagging SVM (bagSVM), classification and regression trees (CART), and random forests (RF). We also examined the effect of several parameters such as overdispersion, sample size, number of genes, number of classes, differential-expression rate, and the transformation method on model performances. A comprehensive simulation study is conducted and the results are compared with the results of two miRNA and two mRNA experimental datasets. The results revealed that increasing the sample size, differential-expression rate and decreasing the dispersion parameter and number of groups lead to an increase in classification accuracy. Similar with differential-expression studies, the classification of RNA-Seq data requires careful attention when handling data overdispersion. We conclude that, as a count-based classifier, the power transformed PLDA and, as a microarray-based classifier, vst or rlog transformed RF and SVM classifiers may be a good choice for classification. An R/BIOCONDUCTOR package, MLSeq, is freely available at https://www.bioconductor.org/packages/release/bioc/html/MLSeq.html.

Applicability of Cameriere's and Drusini's age estimation methods to a sample of Turkish adults.

OBJECTIVES: The aim of this study was to investigate the applicability of Drusini's and Cameriere's methods to a sample of Turkish people. METHODS: Panoramic images of 200 individuals were allocated into two groups as study and test groups and examined by two observers. Tooth coronal indexes (TCI), which is the ratio between coronal pulp cavity height and crown height, were calculated in the mandibular first and second premolars and molars. Pulp/tooth area ratios (ARs) were calculated in the maxillary and mandibular canine teeth. Study group measurements were used to derive a regression model. Test group measurements were used to evaluate the accuracy of the regression model. Pearson's correlation coefficients and regression analysis were used. RESULTS: The correlations between TCIs and age were -0.230, -0.301, -0.344 and -0.257 for mandibular first premolar, second premolar, first molar and second molar, respectively. Those for the maxillary canine (MX) and mandibular canine (MN) ARs were -0.716 and -0.514, respectively. The MX ARs were used to build the linear regression model that explained 51.2% of the total variation, with a standard error of 9.23 years. The mean error of the estimates in test group was 8 years and age of 64% of the individuals were estimated with an error of <±10 years which is acceptable in forensic age prediction. CONCLUSIONS: The low correlation coefficients between age and TCI indicate that Drusini's method was not applicable to the estimation of age in a Turkish population. Using Cameriere's method, we derived a regression model.

Morphometric study of the true S1 and S2 of the normal and dysmorphic sacralized sacra.

BACKGROUND/AIM: This study aimed to generate data for the S1 and S2 alar pedicle and body and the alar orientations for both dysmorphic and normal sacra. MATERIALS AND METHODS: The study comprised two groups: Group N consisted of 53 normal sacra and Group D included 10 dysmorphic sacra. Various features such as alar pedicle circumference; anterior, middle, and posterior axis of the sacral ala; sacral body height and width; and sagittal thickness were measured. RESULTS: In group N, the median anterior axis of the alae was observed to be 30° on the right and 25° on the left, the median midline axis was found to be 20° on the right and 15° on the left, and the median posterior alar axis was -15° on the right and -20° on the left. The true S1 and S2 alar pedicle circumferences were observed to be significantly smaller in group D, which demonstrated a shorter S1 alar pedicle mean circumference, significantly narrower S1 body mean width, and considerably tapered sagittal thickness. CONCLUSION: Our analysis indicated that dysmorphic sacra have a lower sagittal thickness and width of bodies and smaller alar pedicles, which explains the difficulties in their percutaneous fixation.