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Otitis media with effusion (OME) is defined as a middle ear disease that occurs with the accumulation of fluid in the posterior part of the eardrum, usually without any symptoms. When OME disease is not treated, some negative consequences arise that deeply affect the education, social and cultural life of the patient. OME disease is a difficult issue to diagnose by specialists. In this article, autoendoscopic images of the eardrum have been classified using deep learning methods to help specialists in the diagnosis of OME. In this study, a hybrid deep model based on artificial intelligence is proposed. In the proposed hybrid model, feature maps were obtained using Efficientnetb0 and Densenet201 architectures from both the original dataset and the improved dataset using the gaussian method. Then, the merging process was applied to these feature maps. Unnecessary features are eliminated by applying NCA dimension reduction to the combined feature map. The most valuable features obtained at the end of the optimization process are classified in different machine learning classifiers. The proposed model reached a very competitive accuracy value of 98.20% in the SVM classifier.

Legged robots are very popular topics in the robotic field owing to walking on hard terrain. In the current study, the walking of a bipedal robot that is legged robot was aimed. For this purpose, the system was examined and an artificial neural network was designed. After, the neural network was trained by using the Deep Deterministic Policy Gradient (DDPG) and the Proximal Policy Optimization (PPO) algorithms. After the training process, the PPO algorithm was formed better training performance than the DDPG algorithm. Also, the optimal noise standard deviation of the PPO algorithm was investigated. The results were shown that the best results were obtained by using 0.50. The system was tested by utilizing the artificial neural networks that trained the PPO algorithm which has got 0.50 noise standard deviation. According to the test result, the total reward was calculated as 274.334 and the walking task was achieved by purposed structure. As a result, the current study has formed the basis for controlling a bipedal robot and the PPO noise standard deviation selection.

Background Organ transplantation reduces mortality and morbidity in patients with end-stage organ failure. The number of living organ donations is not enough to meet the current organ transplantation need; therefore, there is an urgent need for organ donation from cadavers. We aimed to determine the organ donation rates and reveal the obstacles against donation. Methods This study is designed as a retrospective multicenter study consisting of eight university hospitals, three training and research hospitals, 26 state hospitals, and 74 private hospitals in nine provinces in Turkey. A total of 1,998 patients diagnosed with brain death between January 2011 to April 2019 were examined through the electronic medical records data system. Results Median patient age was 38 (IQR: 19–57), and 1,275 (63.8%) patients were male. The median time between the intensive care unit admission and brain death diagnosis was 56 (IQR:2–131) hours. The most commonly used confirmatory diagnostic test was computed tomography in 216 (30.8%) patients, and the most common cause of brain death was intraparenchymal hemorrhage with 617 (30.9%) patients. A total of 1,646 (82.4%) families refused to permit organ donation. The most common reasons for refusal were family disagreement (68%), social/relative pressure (24%), and religious beliefs (8%). Conclusions Many families refuse permission for organ donation; some of the provinces included in this study experienced years of exceptionally high refusal rates.

Purpose: To evaluate fixation characteristics in amblyopia using macular analyzer integrity assessment (MAIA) microperimetry and to investigate the factors affecting fixation stability.Methods: This prospective, cross-sectional study enrolled a total of 58 amblyopic patients (8-55 years old). Average threshold macular sensitivity (AT) and fixation characteristics were assessed using the MAIA microperimetry (CenterVue, Padova, Italy). Two Bivariate contour ellipse areas (BCEA) fixation indices (63% and 95% proportional values) and the percentage of fixation points within 1° and 2° from the fovea (P1 and P2) were used to assess fixation stability. Results: AT and fixation stability parameters (P1, P2, BCEA 63%, BCEA 95%) were worse in the amblyopic eyes (p The eccentric fixation was 48% in the amblyopic eyes (25% in anisometropic group, 52% in strabismic group, 69% in combined group) and 32% in the non-amblyopic eye. The preferred fixation eccentricity in amblyopic eyes was significantly greater than the non-amblyopic eyes (p=0.004), and there was a negative correlation between preferred fixation eccentricity and BCVA (p=0.012, r=-.327).Conclusions: Our data showed a decrease in fixation stability, a positive correlation between fixation stability and BCVA, and a negative correlation between preferred fixation eccentricity and BCVA in amblyopic eyes. This result made us think that microperimetric acoustic biofeedback fixation training, which is used to increase fixation stability in low vision rehabilitation, may also be a useful approach in amblyopia.

Background: One of the most challenging operations in children for anesthesiologists and surgeons is foreign body aspiration. Bronchospasm and desaturation may lead to bradycardia and even death. Objectives: The study aimed to evaluate the effect of preoperative dexamethasone and β2 agonist (salbutamol) administration on children who had foreign body aspiration during the rigid bronchoscopy on these undesired complications. Methods: Children were divided into two groups via random numbers table, independent of their clinical conditions. β2 agonist (salbutamol) (2.5 mg < 20 kg, 5 mg > 20 kg) and dexamethasone (0.5 mg/kg) were administrated to group 1, 30 minutes before the operation. The same agents were administrated to group 2 during anesthesia induction. The occurrence of bronchospasm, desaturation, and bradycardia was evaluated. Results: There were 27 children in each group. There was no statistically significant difference between the two groups’ time periods between the onset of the symptoms and procedure (P > 0.05). The two groups were similar in clinical aspects. Clinically, periods of spasm and desaturation were shorter, and patients recovered faster in group 1, but the bronchospasm numbers, desaturation, and bradycardia periods were similar in both groups. Conclusions: The results seem statistically similar. Since the periods of spasm and desaturation were shorter, and patients recovered faster in patients with preoperative administration of β2 agonists (salbutamol) and dexamethasone, we may suggest that a larger data set in future studies may lead to more significant results and a better conclusion.

Urine sediment examination is one of the main tests used in the diagnosis of many diseases. Thanks to this test, many diseases can be detected in advance. Examining the results of this test is an intensive and time-consuming process. Therefore, it is very important to automatically interpret the urine sediment test results using computer-aided systems. In this study, a data set consisting of eight classes was used. The data set used in the study consists of 8509 particle images obtained by examining the particles in the urine sediment. A hybrid model based on textural and Convolutional Neural Networks (CNN) was developed to classify the images in the related data set. The features obtained using textural-based methods and the features obtained from CNN-based architectures were combined after optimizing using the Minimum Redundancy Maximum Relevance (mRMR) method. In this way, we aimed to extract different features of the same image. This increased the performance of the proposed model. The CNN-based ResNet50 architecture and textural-based Local Binary Pattern (LBP) method were used for feature extraction. Finally, the optimized and combined feature map was classified at different machine learning classifiers. In order to compare the performance of the model proposed in the study, results were also obtained from different CNN architectures. A high accuracy value of 96.0% was obtained in the proposed model.

Background: the aim of this study was to investigate the effects of apocynin (APO) on hormone levels, the blood-testis barrier, and oxidative biomarkers in monosodium glutamate (MSG) induced testicular degeneration. Methods: Sprague Dawley male rats (150–200 g; n = 32) were randomly distributed into four groups: control, APO, MSG, and MSG + APO. MSG and MSG + APO groups were administered MSG (120 mg/kg) for 28 days. Moreover, the APO and MSG + APO groups received APO (25 mg/kg) during the last five days of the experiment. All administrations were via oral gavage. Finally, biochemical analyses were performed based on the determination of testosterone, follicle-stimulating hormone (FSH), luteinizing hormone (LH), malondialdehyde (MDA), glutathione (GSH), and superoxide dismutase (SOD), as well as light and transmission electron microscopic examinations, assessment of sperm parameters, ZO-1, occludin, NOX-2, and TUNEL immunohistochemistry were evaluated. Results: MSG increased both the oxidative stress level and apoptosis, decreased cell proliferation, and caused degeneration in testis morphology including in the blood-testis barrier. Administration of apocynin reversed all the deteriorated morphological and biochemical parameters in the MSG + APO group. Conclusions: apocynin is considered to prevent testicular degeneration by maintaining the integrity of the blood-testis barrier with balanced hormone and oxidant/antioxidant levels.

Purpose: Case load in working setting, excessive working hours, encountering with traumatic incidents frequently, concern of being sued might increase the level of stress for midwives and affect their psychological resilience negatively. The present study was conducted to identify the effect of secondary traumatic stress level of midwives on psychological resilience. Methods: The study was a descriptive study conducted in 2020 with midwives assigned at delivery rooms of State hospitals in Türkiye. Results: Every one out of three midwives was identified to meet all the criteria regarding Post-Traumatic Stress Disorder. It was also identified that those midwives who are young, single, experiencing dissatisfaction in their profession, having more working hours and shifts monthly had higher secondary traumatic stress scores (p

Probiotics have been defined as “living microorganisms that create health benefits in the host when taken in sufficient amounts. Recent developments in the understanding of the relationship between the microbiom and its host have shown evidence about the promising potential of probiotics to improve certain health problems. However, today, there are some confusions about traditional and new generation foods containing probiotics, naming and classifications of them in scientific studies and also their marketing. To clarify this confusion, the Food and Drug Administration (FDA) declared that it has made a new category definition called "live biotherapeutic products" (LBPs). Accordingly, the FDA has designated LBPs as “a biological product that: i)contains live organisms, such as bacteria; ii)is applicable to the prevention, treatment, or cure of a disease/condition of human beings; and iii) is not a vaccine”. The accumulated literature focused on LBPs to determine effective strains in health and disease, and often focused on obesity, diabetes, and certain diseases like inflammatory bowel disease (IBD).However, microbiome also play an important role in the pathogenesis of diseases that age day by day in the modern world via gut-brain axis. Herein, we discuss the novel roles of LBPs in some gut-brain axis related conditions in the light of recent studies. This article may be of interest to a broad readership including those interested in probiotics as LBPs, their health effects and safety, also gut-brain axis.