The Contribution of Explainable Machine Learning Algorithms Using ROI-based Brain Surface Morphology Parameters in Distinguishing Early-onset Schizophrenia From Bipolar Disorder.

RATIONALE AND OBJECTIVES: To differentiate early-onset schizophrenia (EOS) from early-onset bipolar disorder (EBD) using surface-based morphometry measurements and brain volumes using machine learning (ML) algorithms. METHOD: High-resolution T1-weighted images were obtained to measure cortical thickness (CT), gyrification, gyrification index (GI), sulcal depth (SD), fractal dimension (FD), and brain volumes. After the feature selection step, ML classifiers were applied for each feature set and the combination of them. The SHapley Additive exPlanations (SHAP) technique was implemented to interpret the contribution of each feature. FINDINGS: 144 adolescents (16.2 ± 1.4 years, female=39%) with EOS (n = 81) and EBD (n = 63) were included. The Adaptive Boosting (AdaBoost) algorithm had the highest accuracy (82.75%) in the whole dataset that includes all variables from Destrieux atlas. The best-performing algorithms were K-nearest neighbors (KNN) for FD subset, support vector machine (SVM) for SD subset, and AdaBoost for GI subset. The KNN algorithm had the highest accuracy (accuracy=79.31%) in the whole dataset from the Desikan-Killiany-Tourville atlas. CONCLUSION: This study demonstrates the use of ML in the differential diagnosis of EOS and EBD using surface-based morphometry measurements. Future studies could focus on multicenter data for the validation of these results.

Experience with an Affective Robot Assistant for Children with Hearing Disabilities.

This study presents an assistive robotic system enhanced with emotion recognition capabilities for children with hearing disabilities. The system is designed and developed for the audiometry tests and rehabilitation of children in a clinical setting and includes a social humanoid robot (Pepper), an interactive interface, gamified audiometry tests, sensory setup and a machine/deep learning based emotion recognition module. Three scenarios involving conventional setup, tablet setup and setup with the robot+tablet are evaluated with 16 children having cochlear implant or hearing aid. Several machine learning techniques and deep learning models are used for the classification of the three test setups and for the classification of the emotions (pleasant, neutral, unpleasant) of children using the recorded physiological signals by E4 wristband. The results show that the collected signals during the tests can be separated successfully and the positive and negative emotions of children can be better distinguished when they interact with the robot than in the other two setups. In addition, the children's objective and subjective evaluations as well as their impressions about the robot and its emotional behaviors are analyzed and discussed extensively.

Automatic Emotion Recognition in Children with Autism: A Systematic Literature Review.

The automatic emotion recognition domain brings new methods and technologies that might be used to enhance therapy of children with autism. The paper aims at the exploration of methods and tools used to recognize emotions in children. It presents a literature review study that was performed using a systematic approach and PRISMA methodology for reporting quantitative and qualitative results. Diverse observation channels and modalities are used in the analyzed studies, including facial expressions, prosody of speech, and physiological signals. Regarding representation models, the basic emotions are the most frequently recognized, especially happiness, fear, and sadness. Both single-channel and multichannel approaches are applied, with a preference for the first one. For multimodal recognition, early fusion was the most frequently applied. SVM and neural networks were the most popular for building classifiers. Qualitative analysis revealed important clues on participant group construction and the most common combinations of modalities and methods. All channels are reported to be prone to some disturbance, and as a result, information on a specific symptoms of emotions might be temporarily or permanently unavailable. The challenges of proper stimuli, labelling methods, and the creation of open datasets were also identified.

[Tularemia Outbreak and After; Effect of Seasonal Changes]. / Tularemi Salgini ve Sonrasi; Mevsimsel Degisikliklerin Etkisi.

Tularemia is a zoonotic infectious disease caused by Francisella tularensis. In Yozgat, a total of 525 cases were identified between 2010 and 2016. A serious epidemic occurred with a total of 442 cases in 2010 and 2011 and the number of cases decreased in the later years. In our study, we investigated the association of seasonal factors (temperature, humidity, amount of precipitation, wind speed) with the tularemia epidemic which occurred in 2010 and 2011 and with the decrease in the number of cases in the later years. This study included tularemia cases seen in Yozgat and its districts between 2010 and 2016. Tularemia was defined as a microagglutination test (MAT) result of ≥ 1/160 or a 4-fold increase in MAT titer between two tests at least two weeks apart, in the presence of consistent clinical findings. Seasonal factors were recorded. The conformity of data to normal distribution was analyzed using the ShapiroWilk test. The Mann-Whitney U test was used with the results of Monte Carlo simulations to compare differences between two independent groups in terms of quantitative data. It was found that tularemia cases are more frequently seen in the spring and winter. Meteorological data showed that wind force was statistically significantly higher in the epidemic years than in the other years (p< 0.05). No statistically significant difference was found between mean air temperature, amount of precipitation, and humidity (p> 0.05). Our study found that wind velocity was significantly higher in the epidemic years than in the other years (p< 0.05) and this increase in wind velocity may have caused an increase in tick population and distribution. We believe that, rather than causing direct transmission of tularemia to humans, the increased tick population plays a key role in the maintenance of the life cycle of tularemia by causing transmission to rodents and domestic animals.

Seroprevalence of Crimean-Congo hemorrhagic fever among health care workers in a hospital in an endemic region of Turkey.

INTRODUCTION: Crimean-Congo Hemorrhagic Fever (CCHF) can also be transmitted through unprotected contact directly with blood or body fluids as well as from laboratories. This study aimed to determine the seroprevalence of CCHF disease in the employees of the State Hospital of Yozgat Province, located in Central Anatolia of Turkey, and also to present the risk factors for healthcare workers. METHODOLOGY: A total of 112 volunteer employees of Yozgat State Hospital were included in the study. The study volunteers were divided into two groups: one having had a contact with CCHF patients and patient's samples and the other a non-contact group. RESULTS: In the contact group, 2 (2.9%) out of 67 subjects tested positive for anti-CCHF IgG; however, in the non-contact group, none of the subjects tested positive (Fisher's exact test p > 0.05). Of the two employees who tested positive, one was working at the microbiology laboratory and the other was from the emergency department. CONCLUSION: Although cases of nosocomial transmission of CCHF have been reported previously, questions on the mode of transmission of the disease are still unanswered. The risk factors for the disease should, therefore, be identified in order to take the necessary measures.

The comparison of various disinfectants? efficacy on Staphylococcus aureus and Pseudomonas aeruginosa biofilm layers

Background/aim: Because biofilms are resistant to antibiotics and biocides, they usually cause chronic persistent infections, which are arduous to cure and have high mortality and morbidity. Our study aimed to investigate the efficiency of orthophthalaldehyde, peracetic acid, hydrogen peroxide, and sodium hypochlorite on Pseudomonas aeruginosa and Staphylococcus aureus biofilm layers and live microbial cells. Materials and methods: Biofilm layers were determined by crystal violet assay and live microbial cells were determined using a resazurin assay. Results: For Pseudomonas aeruginosa, sodium hypochlorite showed the most influential disinfection because it diminished 83.6% of the biofilm layer and decreased 99.7% of live microbial cells. For Staphylococcus aureus, hydrogen peroxide was determined the most active disinfectant with 80.3% reduction of the biofilm layer. Sodium hypochlorite was also determined to be the most efficient disinfectant with 99.8% reduction of live microbial cells. Sodium hypochlorite was the most influential disinfectant on biofilm layers and live microbial cells of both microorganisms. Conclusion: We concluded that if we use sodium hypochlorite at a high level as a disinfectant for both surfaces and medical equipment, it is beneficial to prevent infections related to biofilms. More studies about prevention of biofilm occurrence and standardization of the methods for investigating disinfectants? effects are necessary.

Interactive Games with an Assistive Robotic System for Hearing-Impaired Children.

This paper presents an assistive robotic system, which can recognize and express sign language words from a predefined set, within interactive games to communicate with and teach hearing-impaired children sign language. The robotic system uses audio, visual and tactile feedback for interaction with the children and the teacher/researcher.

Spontaneous intracranial hypotension presenting with coma: a case report and literature review.

Spontaneous intracranial hypotension is characterized by orthostatic headache in the absence of a history of head trauma or lumbar puncture, and diagnosis is confirmed by a specific cerebrospinal fluid pressure and neuroimaging findings. It rarely presents with coma. A 62-year-old man presented with progressive cognitive decline of 2 to 4 weeks' duration. He was diagnosed with spontaneous intracranial hypotension according to cerebrospinal fluid pressure and neuroimaging findings, and treated conservatively.

[Ocular toxoplasmosis developed after liver transplantation]. / Karaciger Transplantasyonu Sonrasi Gelisen Oküler Toksoplazmoz.

Ocular toxoplasmosis after solid organ transplantation occurs usually within the first three months of primary infection or reactivation of latent infection. There are a few reports of ocular toxoplasmosis following liver transplantation in the literature, however, no reports were detected in the national data. In this report a 35-year-old female patient diagnosed as ocular toxoplasmosis following reactivation in the second year after liver transplantation, was presented. The case was successfully treated with trimethoprim/sulfamethoxazole and clindamycin. This case was presented to emphasize late presentation of toxoplasmosis in transplantation patients and to withdraw attention to the importance of serological investigations done before transplantation.