Remote Neuropscyhological Assessment: Teleneuropsychology.

Introduction: Teleneuropsychology, which includes the remote application of neuropsychological tests to patients via telephone or videoconferencing, can expand access to health services for patients who reside in distant areas or have mobility restrictions. With the emergence of the COVID-19 pandemic, there has been a significant increase in the use of teleneuropsychology in cognitive assessment. In this review, the aim was to critically review the results of studies conducted in the field of teleneuropsychology and the fundamental principles related to tele-neuropsychological assessment. Additionally, the "guideline for home-based teleneuropsychology" developed for Türkiye's practices is outlined in this review. Method: A literature search was conducted using the Web of Science and PubMed databases to include all types of articles related to the subject. Results: The results of studies on in-clinic and home-based teleneuropsychological assessment indicate that tests that assess cognitive functions such as attention, memory, executive functions, and language, particularly those based on verbal administration, can be reliably applied through teleneuropsychological assessment. However, there are factors to consider when referring patients for teleneuropsychological assessment, selecting tests for assessment, and making ethical considerations. Additionally, it is important to follow recommended steps for both the clinician and the patient and/or their caregiver before and during the interview in order for the assessment to be carried out effectively. Conclusion: Although direct contact with the patient is an essential element in clinical neuropsychology practice, when necessary, teleneuropsychological assessment performed by trained experts following appropriate application procedures can be a good alternative to face-to-face evaluations.

Measuring social determinants of health in the All of Us Research Program.

To accelerate medical breakthroughs, the All of Us Research Program aims to collect data from over one million participants. This report outlines processes used to construct the All of Us Social Determinants of Health (SDOH) survey and presents the psychometric characteristics of SDOH survey measures in All of Us. A consensus process was used to select SDOH measures, prioritizing concepts validated in diverse populations and other national cohort surveys. Survey item non-response was calculated, and Cronbach's alpha was used to analyze psychometric properties of scales. Multivariable logistic regression models were used to examine associations between demographic categories and item non-response. Twenty-nine percent (N = 117,783) of eligible All of Us participants submitted SDOH survey data for these analyses. Most scales had less than 5% incalculable scores due to item non-response. Patterns of item non-response were seen by racial identity, educational attainment, income level, survey language, and age. Internal consistency reliability was greater than 0.80 for almost all scales and most demographic groups. The SDOH survey demonstrated good to excellent reliability across several measures and within multiple populations underrepresented in biomedical research. Bias due to survey non-response and item non-response will be monitored and addressed as the survey is fielded more completely.

Antecedents to and outcomes associated with teacher-child relationship perceptions in early childhood: Further evidence for child-driven effects.

Preschool teachers' perceptions about relationships with students (teacher-child relationships [TCRs]) predict children's subsequent social competence (SC) and academic progress. Why this is so remains unclear. Do TCRs shape children's development, or do child attributes influence both TCRs and subsequent development? Relations between TCRs and other measures were examined for 185 preschoolers (107 girls, 89 longitudinal, and ~75% European American). Teachers rated TCRs and child social/affective behaviors. Teacher-child interactions (TCIs) and children's affect expressiveness were observed. Child SC and receptive vocabulary were assessed. TCRs were significantly correlated with each type of outcome. TCIs, SC, expressed affect, and teacher-rated behaviors also predicted TCRs longitudinally. Results suggest that TCR ratings predict subsequent adaptation because they summarize children's behavioral profiles rather than on TCR quality per se.

The effect of psychotic proneness and psychopathy on theory of mind.

This study aimed to investigate the interaction between positive psychotic experiences and psychopathic traits on the theory of mind in a non-clinical sample. The results showed that distinct constructs of psychopathy can lead to distinct theory of mind profiles when interacting with psychotic proneness.

The relationship between PM10 and SO2 exposure and Covid-19 infection rates in Turkey using nomenclature of territorial units for statistics level 1 regions.

The Covid-19 pandemic, which has been affecting the world since December 2019, has become one of the biggest problems of the 21st century. There are studies stating that the contagiousness of the Covid-19 pandemic, which is transmitted from person to person, increases more with environmental factors such as air pollution, and accordingly, there is an increase in the number of cases. In this study, a panel regression model to investigate the effect of air pollution concentrations such as PM10 and SO2 as environmental factors and population density on the monthly mean number of Covid-19 cases for 12 regions at the nomenclature of territorial units for statistics (NUTS) level 1 in Turkey between June 2020 and November 2020, and a linear regression model to investigate the effect at the regional level. we used. Based on the model results, we concluded that a small increase in air pollution indicators led to an increase in the number of Covid-19 cases in Turkey and its regions. It is very important to identify preventable environmental factors in order to prevent and minimize the effects of respiratory tract diseases and rapidly spreading pandemic diseases such as Covid-19. Accordingly, we can conclude that countries should take some measures, especially on air pollution, in order to develop public health and pandemic/disease management strategies and to reduce the risk of respiratory diseases.

An Investigation of Affective Personality Traits in Alzheimer's Disease: SEEKING as a Possible Predictor for Early-Stage Alzheimer's Dementia.

OBJECTIVE: The aim of the current study was to investigate affective personality traits in Alzheimer's disease, a neurodegenerative condition mainly characterized by episodic memory impairment. METHOD: The sample included 69 participants from 3 diagnostic categories. Twenty-five participants were diagnosed with subjective cognitive impairment (SCI), 26 participants were diagnosed with mild cognitive impairment of the amnestic type (aMCI), and the remaining 18 participants were diagnosed with early-stage Alzheimer's dementia (ADD). Diagnostic labels were given as a result of detailed neurological, neuropsychological, and neuroradiological assessment. Affective personality traits were assessed via Affective Neuroscience Personality Scales (ANPS). RESULTS: The only significant intergroup difference was obtained for the SEEKING subscale of ANPS. Here, ADD group scored significantly lower compared to the SCI group. The results of logistic regression analysis also indicated that SEEKING score successfully predicted early-stage ADD diagnosis. CONCLUSION: The results suggest that a specific personality constellation characterized by reduced investment in the outside world might be associated with Alzheimer's disease, either as a risk factor or a byproduct of the neurodegenerative process initiated by AD pathology.

The Clinical Characteristics of Patients With Pyoderma Gangrenosum in a Tertiary Referral Hospital: A Retrospective Cohort Study.

Since pyoderma gangrenosum (PG) is a rare neutrophilic dermatosis, epidemiological and clinical data on the disease are scarce. In this single-center retrospective study, we aim to evaluate the clinical characteristics, underlying systemic associations and treatment modalities in patients with PG in a university hospital between 2014 and 2022. It is known that PG most commonly affects the lower extremities, but extracutaneous involvement should also be kept in mind. PG is usually associated with various comorbidities that share a similar inflammatory pathogenesis with the disease. The prevalence of PG-related comorbidities varies in different studies, arthritis and solid organ malignancies were observed most frequently in the current study. Non-PG-related comorbidities including diabetes mellitus, hypertension and peripheral vascular disease can adversely affect wound healing and limit treatment options; therefore, a holistic approach to patients with PG is crucial. Consistent with literature, the mainstay of treatment for PG is systemic corticosteroids and cyclosporine. However, the implementation of biologic agents in treatment-resistant patients is an increasingly important issue in the literature. Antitumor necrosis factors (anti-TNFs) are the most commonly preferred biological therapies, and these agents seem to have paved the way for a paradigm shift in the treatment of PG. In the present study, a relatively high per cent of (23.3%) patients treated with anti-TNFs, most commonly infliximab (87.5%). Recurrence was observed in 46.7% of our patients in the follow-up period and the relapse rate was found to be higher in patients using multiple systemic agents compared to those using single agents (64.7% vs 23.1%, P < .05). In conclusion, we emphasize that early diagnosis and treatment by considering the patient's comorbidities are important in preventing complications, and biologic treatments seem particularly promising in treatment-resistant patients.

Identification of ALX3 Gene Promoter Hypermethylation as a Potential Biomarker for Lung Cancer.

BACKGROUND/AIM: Recent studies imply the significance of promoter CpG methylation as a biomarker for various cancer types in different genes. ALX3 is one of the candidate genes with prominent promoter methylation status change. In this study, the methylation status of ALX3 gene promoter and its expression was analyzed in lung cancer cell lines and clinical samples from The Cancer Genome Atlas Program (TCGA) program. MATERIALS AND METHODS: Methylation status was screened using the COBRA Assay, and gene expression in two cancer (A549 & H1299) and one normal (Beas 2B) lung cell lines was determined using RT-PCR. RESULTS: ALX3 gene promoter was found to be hypermethylated in both lung cancer cell lines compared to normal cells. However, no difference in the expression of this gene was observed. In addition to our in vitro findings, DNA Methylation and RNA-seq data of 413 adenocarcinoma samples from TCGA-LUAD dataset were analyzed. ALX3 gene was found to be hypermethylated in tumor compared to normal samples. Interestingly, the expression level of ALX3 gene in tumors was found to be higher than that in normal samples. CONCLUSION: ALX3 gene promoter hypermethylation could serve as a biomarker in lung cancer.

Analysis of facial emotion expression in eating occasions using deep learning.

Eating is experienced as an emotional social activity in any culture. There are factors that influence the emotions felt during food consumption. The emotion felt while eating has a significant impact on our lives and affects different health conditions such as obesity. In addition, investigating the emotion during food consumption is considered a multidisciplinary problem ranging from neuroscience to anatomy. In this study, we focus on evaluating the emotional experience of different participants during eating activities and aim to analyze them automatically using deep learning models. We propose a facial expression-based prediction model to eliminate user bias in questionnaire-based assessment systems and to minimize false entries to the system. We measured the neural, behavioral, and physical manifestations of emotions with a mobile app and recognize emotional experiences from facial expressions. In this research, we used three different situations to test whether there could be any factor other than the food that could affect a person's mood. We asked users to watch videos, listen to music or do nothing while eating. This way we found out that not only food but also external factors play a role in emotional change. We employed three Convolutional Neural Network (CNN) architectures, fine-tuned VGG16, and Deepface to recognize emotional responses during eating. The experimental results demonstrated that the fine-tuned VGG16 provides remarkable results with an overall accuracy of 77.68% for recognizing the four emotions. This system is an alternative to today's survey-based restaurant and food evaluation systems.

The effectiveness of psychoanalytic psychotherapy in individuals diagnosed with PTSD due to torture and severe human right violations.

INTRODUCTION: Various psychotherapies have been applied to individuals who have been subjected to torture and severe human rights violations. However, studies assessing the ef-fectiveness of such therapies are limited. Psy-choanalytic psychotherapy is said to be used frequently in practice for these patient groups. Yet, there are scarcely any studies assessing its efficacy. In this study, we aim to assess the effectiveness of psychoanalytic psychotherapy in patients with PTSD associated with torture and severe human rights violations. METHODS: 70 patients who were diagnosed with PTSD due to being tortured and severe human rights violations in accordance with DSM-IV-TR and who applied to the Human Rights Foundation of Turkey were given psy-choanalytic psychotherapy. CGI-S and CGI-I scales were applied to the patients (in Months 1, 3, 6, 9, and 12); and the patients' continu-ity of therapy and the changes in their recov-ery during the one-year psychotherapy period were assessed. RESULTS: 38 (54.3%) of the patients were female. Their mean age was 37.7 years (SD= 12.25), while their mean baseline CGI-S score was 4.67. The drop-out rate was 34%. The mean length of treatment was 21.9 ses-sions (SD = 20.30). Mean scores for CGI-I scale were 3.46, 2.95, 2.23, 2.00, and 1.54 for months 1, 3, 6, 9 and 12 respectively. As the number of sessions increased, the final CGI-I scores of the patients improved significantly towards recovery.75.4% of the pa-tients benefited from the treatment in general according to their final CGI-I score. CONCLUSIONS: Considering the limited liter-ature in the field, this study has provided sig-nificant data on the effectiveness of the use of psychoanalytic psychotherapy in individuals diagnosed with PTSD related to torture and severe human rights violations, despite its lim-itations such as not involving a control group, not having been conducted blindly and ran-domized and being based on a single scale.

Deep learning-based user experience evaluation in distance learning.

The Covid-19 pandemic caused uncertainties in many different organizations, institutions gained experience in remote working and showed that high-quality distance education is a crucial component in higher education. The main concern in higher education is the impact of distance education on the quality of learning during such a pandemic. Although this type of education may be considered effective and beneficial at first glance, its effectiveness highly depends on a variety of factors such as the availability of online resources and individuals' financial situations. In this study, the effectiveness of e-learning during the Covid-19 pandemic is evaluated using posted tweets, sentiment analysis, and topic modeling techniques. More than 160,000 tweets, addressing conditions related to the major change in the education system, were gathered from Twitter social network and deep learning-based sentiment analysis models and topic models based on latent dirichlet allocation (LDA) algorithm were developed and analyzed. Long short term memory-based sentiment analysis model using word2vec embedding was used to evaluate the opinions of Twitter users during distance education and also, a topic model using the LDA algorithm was built to identify the discussed topics in Twitter. The conducted experiments demonstrate the proposed model achieved an overall accuracy of 76%. Our findings also reveal that the Covid-19 pandemic has negative effects on individuals 54.5% of tweets were associated with negative emotions whereas this was relatively low on emotion reports in the YouGov survey and gender-rescaled emotion scores on Twitter. In parallel, we discuss the impact of the pandemic on education and how users' emotions altered due to the catastrophic changes allied to the education system based on the proposed machine learning-based models.

Cognitive functions among healthy older adults using online social networking.

Online social network sites provide possibilities to enhance social relationships and engage in cognitive activities for older adults. The present study aimed to investigate the relationship between the use of one social network site, Facebook, and cognitive functions in older adults considering different dimensions of Facebook use together with different cognitive functions. Seventy healthy older adults completed the use of Facebook form, Multidimensional Scale of Perceived Social Support, and Social Network Index. Their cognitive functions were measured with Digit Span Tasks, Free and Cued Selective Reminding Test, Letter and Category Fluency Tests, Stroop Test, Digit Symbol Substitution Test, and Trail Making Test (TMT-A and TMT-B). After controlling for age, gender, education level, we found that Facebook users performed better on TMT-A compared to non-users. Among Facebook users, the length of having an account, the network size, the daily duration of use, and the frequency of active and passive use correlated with cognitive performance after controlling offline sociality. These findings, which need confirmation by experimental and longitudinal studies, suggested that being connected to a larger network via more prolonged and active use of social media might be associated with higher cognitive functioning.

Elevated sTREM2 and NFL levels in patients with sepsis associated encephalopathy.

PURPOSE: Sepsis-associated encephalopathy (SAE) is a common manifestation of sepsis that may lead to cognitive decline. Our aim was to investigate whether the neurofilament light chain (NFL) and soluble triggering receptor expressed on myeloid cells 2 (sTREM2) could be utilized as prognostic biomarkers in SAE. MATERIALS AND METHODS: In this prospective observational study, baseline serum levels of sTREM2 and cerebrospinal fluid (CSF) levels of sTREM2 and NFL were measured by ELISA in 11 SAE patients and controls. Patients underwent daily neurological examination. Brain magnetic resonance imaging (MRI) and standard electroencephalography (EEG) were performed. Cognitive dysfunction was longitudinally assessed after discharge in 4 SAE patients using the Mini-Mental State Examination (MMSE) and Addenbrooke's Cognitive Examination-Revised (ACE-R) tests. RESULTS: SAE patients showed higher CSF sTREM2 and NFL levels than controls. sTREM2 and NFL levels were not correlated with the severity measures of sepsis. Three months after discharge, 2 SAE patients displayed ACE-R scores congruent with mild cognitive impairment (MCI), persisting in one patient 12 months after discharge. SAE patients with MCI showed higher CSF NFL levels, bacteremia, and abnormal brain MRI. Patients with increased serum/CSF sTREM2 levels showed trends towards displaying poorer attention/orientation and visuo-spatial skills. CONCLUSIONS: sTREM2 and NFL levels may serve as a prognostic biomarker for cognitive decline in SAE. These results lend further support for the involvement of glial activation and neuroaxonal degeneration in the physiopathology of SAE.

Neuropsychiatric outcomes and caregiver distress in primary progressive aphasia.

BACKGROUND: In this study, we aimed to outline the neuropsychiatric consequences of primary progressive aphasia (PPA) and to understand how neuropsychiatric symptomatology affects distress in caregivers. METHODS: The Neuropsychiatric Inventory (NPI) including the distress index (NPI-Distress) was used. Additional information about the caregiver burden was obtained using Zarit Burden Interview (ZBI). NPI, NPI-Distress, and ZBI data from 17 patients with a clinical diagnosis of PPA were compared with 10 stroke aphasia patients. Neuropsychiatric symptomatology was investigated based on three clusters; Mood, Frontal/Comportmental, and Psychotic/Disruptive. Additionally, the Activities of Daily Living Questionnaire (ADLQ) was used to outline the functional impairment. Twelve healthy controls were included to compare the neurocognitive test scores with PPA and stroke aphasia groups. RESULTS: A greater number of neuropsychiatric symptoms were observed in the PPA group compared to the stroke aphasia group. The number of symptoms in Mood, and Frontal/Comportmental clusters were greater than the number of symptoms in Psychotic/Disruptive clusters in the PPA group, whereas no significant relationship between the number of symptoms and symptom clusters was found in the stroke aphasia group. In the PPA group, a strong correlation was found between the NPI-Frequency × Severity scores and the NPI-Distress scores. Moreover, the NPI-Distress scores in the PPA group strongly correlated with the ZBI scores. Scores for anxiety, irritability/lability, and apathy had a stronger correlation with the NPI-Distress scores compared to the other NPI symptoms. The Communication subscale was the most impaired domain in the PPA group. Travel, and Employment and Recreation subscales showed greater functional impairment in the stroke aphasia group compared to the PPA group. CONCLUSIONS: Neuropsychiatric symptoms in PPA in our study were more frequent than previously reported. Furthermore, the distress index of the NPI was not only correlated with the severity of the neuropsychiatric symptoms but also reflected the overall burden on the caregivers in the PPA group.

Skeletal description of Pelophylax caralitanus (Anura: Ranidae): Comparison with other ranids.

A description of the skeletal development of ranids is scarce despite being well known in the family Ranidae. Herein, the description of several species of two genera representing the family Ranidae from Turkey is studied wherein the larval and adult cranial skeletons of Pelophylax caralitanus are described and compared with that of the water frog (Pelophylax bedriagae) and mountain frog (Rana macrocnemis). The data are based on cleared and double-stained specimens of 20 Gosner developmental Stages (26-46). The first element to ossify in P. caralitanus is the parasphenoid (Stage 30), followed by the exoccipitals (Stage 34) and prootics (Stage 35). The metamorphic climax commences at Stage 42 during which several modifications to the chondrocranium will unfold. In addition, ranids demonstrate remarkable differences between the water (Pelophylax sp.) and mountain (Rana sp.) frog species: (a) the ventromedial bridge between the corpora of the suprarostral cartilage in the larval upper jaw, (b) the number of processes of the central corpus in the hyobranchial skeleton, and (c) the differences in the ossification time and sequence between Pelophylax sp. and Rana sp. A detailed description of the larval osteological features of P. caralitanus conforms to the current phylogenetic position and provides a model for comparison with other ranids.

The evaluation of disease awareness, caregiver burden, and workday loss in caregivers of COPD patients.

BACKGROUND: Our aim is to determine the caregiver burden of chronic obstructive lung disease (COPD) patient's caregivers, and to determine whether there is a workday loss. METHODS: 252 COPD patients and their caregivers were included. Disease information of the patients were recorded and a questionnaire was applied. Socio-demographic characteristics of the caregivers were recorded and a questionnaire consisting of 24 questions including COPD disease, treatment and loss of working days, and the Zarit Scale were used. RESULTS: 128(50.8%) of the patients according to GOLD were group-D, 97(38.5%) of the patient's relatives were working, 62(24.7%) were not able to go to work for 1-14 days, and 125(57.1%) spent outside the home from 1-14 nights, because those accompanied to patients. In univariate analysis were detected modified medical research council (mMRC) (p < 0.001), CAT (p < 0.001), the number of comorbidities of patients (p = 0.027), forced expiratory volume in 1 FEV1cc (p = 0.009), FEV1% (p < 0.001), the presence of long term oxygen therapy (LTOT), and the number of comorbidities of the patient's relatives (p = 0.06) increased the care load. In multiple linear regression analysis, age (p = 0.03), COPD assessment test (CAT) score (p = 0.001), FEV1% (<0.068) and the number of comorbidities of patients (p = 0.01) and the number of comorbidities of caregivers (p = 0.003) increased the caregiving burden. DISCUSSION: In COPD increases caregiving burden. This burden is greater in symptomatic patients and when comorbidities are present. Psychosocial and legal regulations should be investigated and solutions should be produced for the caregivers of COPD patients.