Utilizing Phase Locking Value to Determine Neurofeedback Treatment Responsiveness in Attention Deficit Hyperactivity Disorder.

BACKGROUND: Neurofeedback is a non-invasive brain training technique used to enhance and treat hyperactivity disorder by altering the patterns of brain activity. Nonetheless, the extent of enhancement by neurofeedback varies among individuals/patients and many of them are irresponsive to this treatment technique. Therefore, several studies have been conducted to predict the effectiveness of neurofeedback training including the theta/beta protocol with a specific emphasize on slow cortical potential (SCP) before initiating treatment, as well as examining SCP criteria according to age and sex criteria in diverse populations. While some of these studies failed to make accurate predictions, others have demonstrated low success rates. This study explores functional connections within various brain lobes across different frequency bands of electroencephalogram (EEG) signals and the value of phase locking is used to predict the potential effectiveness of neurofeedback treatment before its initiation. METHODS: This study utilized EEG data from the Mendelian database. In this database, EEG signals were recorded during neurofeedback sessions involving 60 hyperactive students aged 7-14 years, irrespective of sex. These students were categorized into treatable and non-treatable. The proposed method includes a five-step algorithm. Initially, the data underwent preprocessing to reduce noise using a multi-stage filtering process. The second step involved extracting alpha and beta frequency bands from the preprocessed EEG signals, with a particular emphasis on the EEG recorded from sessions 10 to 20 of neurofeedback therapy. In the third step, the method assessed the disparity in brain signals between the two groups by evaluating functional relationships in different brain lobes using the phase lock value, a crucial data characteristic. The fourth step focused on reducing the feature space and identifying the most effective and optimal electrodes for neurofeedback treatment. Two methods, the probability index (p-value) via a t-test and the genetic algorithm, were employed. These methods showed that the optimal electrodes were in the frontal lobe and central cerebral cortex, notably channels C3, FZ, F4, CZ, C4, and F3, as they exhibited significant differences between the two groups. Finally, in the fifth step, machine learning classifiers were applied, and the results were combined to generate treatable and non-treatable labels for each dataset. RESULTS: Among the classifiers, the support vector machine and the boosting method demonstrated the highest accuracy when combined. Consequently, the proposed algorithm successfully predicted the treatability of individuals with hyperactivity in a short time and with limited data, achieving an accuracy of 90.6% in the neurofeedback method. Additionally, it effectively identified key electrodes in neurofeedback treatment, reducing their number from 32 to 6. CONCLUSIONS: This study introduces an algorithm with a 90.6% accuracy for predicting neurofeedback treatment outcomes in hyperactivity disorder, significantly enhancing treatment efficiency by identifying optimal electrodes and reducing their number from 32 to 6. The proposed method enables the prediction of patient responsiveness to neurofeedback therapy without the need for numerous sessions, thus conserving time and financial resources.

Comparison Static and Dynamic Ultrasound Techniques of DDH: The Role of the Patient's Position.

Objectives: The ultrasound examination of the hip joint is performed in the static (Graf) technique in the lateral recumbent position and in the dynamic technique in the supine position. This study compares the two static and dynamic techniques and assesses the role of the patient's position in the examination of DDH. Methods: This cross-sectional study was conducted in 2020-2021 at Akbar Hospital, Mashhad University of Medical Sciences, Iran. 126 patients suspected of having DDH (199 hip) infants were enrolled in the study. All ultrasound examinations were performed with two static and dynamic techniques by a pediatric radiologist. Results: In the static and dynamic ultrasound examinations, the average alpha angle was 51.57 ± 6.41 degrees, and 53.41 ± 6.94 degrees, respectively. These changes were not statistically significant (P = 0.312). The relationship and agreement between instability with dynamic technique and instability with static technique (IIC unstable, D, III, and IV) were investigated. Significant agreement (Kappa=0.77 (95% CI: 0.66-0.87) with excellent clinical significance was obtained between the two ultrasound examination method. Also, in terms of DDH types in the static method with instability types in the dynamic method, a substantial agreement was found between the two examination methods (Kappa =0.67; (95% CI: 0.59-0.75) with good clinical significance. Conclusion: In the ultrasound examination of DDH with static and dynamic techniques, the change in the alpha angle was not statistically significant. Therefore, the hand of the radiologist is open in measuring alpha angles and there is no need to emphasize a specific position. The type of DDH in the static technique completely corresponded to the type of stability or instability in the dynamic technique.

Tic disorder in allergic rhinitis children and adolescents: a case-control study.

BACKGROUND: Allergic rhinitis is the most common allergic disease. It can accompany psychological disorders such as tic disorders due to the prolonged course of the symptoms of allergic rhinitis. This pioneer case-control study aims to investigate tic disorders in children and adolescents under 18 years of age diagnosed with allergic rhinitis. METHOD: The case group in this study consisted of patients who had both allergic rhinitis and tic disorders. Patients with allergic rhinitis without tic disorders were also enrolled as the control group with matched gender and age. Demographic characteristics, tic classifications, and contributing factors for allergic rhinitis and tic disorders were studied among the cases. Tic disorders were evaluated using DSM-5 criteria for the classification of tic disorders. RESULTS: 47 patients in the case group and 47 patients in the control group were included in this study. 53.2% and 46.8% were males and females in the case group, respectively. The mean age of the patients was 10.46 ± 3.97 years old. Sound tics were more common among the patients compared to motor tics. Patients with concomitant AR and tic disorders had more days per week with AR symptoms (P-value ≤ 0.001; OR (every day vs. three days a week = 11.02(2.98, 40.76))). Most patients with sound tick were women (p: 0.026), and most patients with motion tic were in the Provisional tic disorder group (p: 0.001). The history of infantile eczema was seen more in patients without sound tic (p: 0.025), and otitis media was significantly less common among patients with sound tics (p: 0.026). Provisional tic disorder was the most common class among the patients. In the case group (coexistence between allergic rhinitis and tic) compared to the control group, patients had significantly more days with AR symptoms per week. CONCLUSION: This preliminary study indicates that Provisional tic disorder was the most common classification of tic among patients with allergic rhinitis, especially in patients with motor tics. Asthma in motor tics, a history of food allergy in infancy, and a history of infantile eczema were also common among patients with vocal tics. Also, patients with allergic rhinitis and tic had more severe disease (more symptoms per week) than those with rhinitis alone. These findings emphasize the association of tic disorders with immunological pathways.

Enhancing the accuracy of electroencephalogram-based emotion recognition through Long Short-Term Memory recurrent deep neural networks.

Introduction: Emotions play a critical role in human communication, exerting a significant influence on brain function and behavior. One effective method of observing and analyzing these emotions is through electroencephalography (EEG) signals. Although numerous studies have been dedicated to emotion recognition (ER) using EEG signals, achieving improved accuracy in recognition remains a challenging task. To address this challenge, this paper presents a deep-learning approach for ER using EEG signals. Background: ER is a dynamic field of research with diverse practical applications in healthcare, human-computer interaction, and affective computing. In ER studies, EEG signals are frequently employed as they offer a non-invasive and cost-effective means of measuring brain activity. Nevertheless, accurately identifying emotions from EEG signals poses a significant challenge due to the intricate and non-linear nature of these signals. Methods: The present study proposes a novel approach for ER that encompasses multiple stages, including feature extraction, feature selection (FS) employing clustering, and classification using Dual-LSTM. To conduct the experiments, the DEAP dataset was employed, wherein a clustering technique was applied to Hurst's view and statistical features during the FS phase. Ultimately, Dual-LSTM was employed for accurate ER. Results: The proposed method achieved a remarkable accuracy of 97.5% in accurately classifying emotions across four categories: arousal, valence, liking/disliking, dominance, and familiarity. This high level of accuracy serves as strong evidence for the effectiveness of the deep-learning approach to emotion recognition (ER) utilizing EEG signals. Conclusion: The deep-learning approach proposed in this paper has shown promising results in emotion recognition using EEG signals. This method can be useful in various applications, such as developing more effective therapies for individuals with mood disorders or improving human-computer interaction by allowing machines to respond more intelligently to users' emotional states. However, further research is needed to validate the proposed method on larger datasets and to investigate its applicability to real-world scenarios.

Microplastics identification in water by TGA-DSC Method: Maharloo Lake, Iran.

Nowadays, one of the biggest challenges is the lack of coordination between the microplastic identification methods used by researchers. To advance our global understanding of microplastic contamination and address the knowledge gaps, we require acceptable or similar identification methods or instruments designed to support the quantitative characterization of the microplastics data. In the current study, we focused on the thermogravimetric analysis (TGA) with differential scanning calorimetry (DSC) method which is usually used experimentally by other researchers, while we tried to look at this method in a real aquatic environment, Maharloo Lake and its Rivers. A number of 22 sites were chosen for sampling microplastics from water. The mean and median of total organic matter percentage for rivers samples (mean = 88%;median = 88%) was similar to the Maharloo lake (mean = 88.33%; median = 89%), suggesting the existence of a robust potential sink. The differentiation of the organic matter part into labile (e.g., carbon aliphatic and polysaccharides), recalcitrant (e.g., aromatic compounds and most plastics), and refractory fractions was implemented and the results indicated that labile organic matter was dominant in both the lake and the rivers, while recalcitrant and refractory fractions were lower. The river's average labile and refractory fractions were similar to the lake. Although the overall results of the study show combining TGA techniques with other analytical procedures can improve the technical quality of polymers, interpreting the complex information of those measurements requires a high level of expertise and the technology is still maturing.

Mental Health Status of Healthcare Workers During the Coronavirus Disease 2019 Pandemic: A Survey of Hospitals in Shiraz, Iran.

BACKGROUND: Healthcare workers (HCWs) directly or indirectly involved in the coronavirus disease 2019 (COVID-19) treatment process may experience severe mental consequences of the pandemic. Hence, this study aimed to evaluate the mental health status of HCWs in hospitals affiliated with Shiraz University of Medical Sciences, Iran. MATERIALS AND METHODS: This cross-sectional study was performed on 503 HCWs from five hospitals in Shiraz, including one COVID-19 front-line hospital, two COVID-19 second-line hospitals, and two without COVID-19 wards. Then, to assess the levels of anxiety, depression, insomnia, and post-traumatic stress disorder (PTSD) among HCWs, the Persian versions of the Hospital Anxiety and Depression Scale (HADS), Insomnia Severity Index (ISI), and Global Psychotrauma Screen (GPS) questionnaires were placed, respectively. RESULTS: The mean age of participants was 33.94±8.26 years, and 252 (50.1%) were females. Anxiety, depression, insomnia, and moderate to high levels of PTSD were observed in 40.4%, 37.8%, 24.5%, and 71% of participants, respectively. A history of mental disorders was associated with all four outcomes (P0.05). Females gender and living with elderly and/or children were correlated with anxiety and PTSD (P0.05). Working at COVID-19 front- and second-line hospitals were similarly linked to higher insomnia and PTSD levels (P0.05). Also, working in COVID-19 wards or non-clinical settings was associated with anxiety and depression (P0.05). CONCLUSION: Most of the HCWs in this study may experience mental difficulties. Some factors may increase their risk of experiencing these difficulties. Hence, in the crisis era, mental health monitoring and identification of groups with predisposing factors are required to provide appropriate care as quickly as feasible.

EEG Spectral Power Analysis: A Comparison Between Heroin Dependent and Control Groups.

Previous studies indicated that heroin abuse would result in abnormal functional organization of the brain. However, studies of heroin abuse- related brain dysfunction are scarce. The purpose of the present study was to investigate heroin effects on brain function by studying relationships between Electroencephalograph (EEG) spectral power and heroin abuse. The resting EEG signals were acquired from 15 male heroin dependent group and 15 male control group. The differences in the EEG components of each group were evaluated using the statistical Mann-Whitney examination and Davis Bouldin Index. The results show that heroin dependent group has an attenuated relative beta-2 power compared with other EEG frequency sub bands. Nevertheless, the results indicate heroin dependent group have an increase of power spectrum density for theta at all locations, as well as delta in the temporal, frontal and central areas compared with control group. Compared to control group, the heroin dependent group decreased its spectral power more than the control group in all three alpha bands. The present findings using the Davis Bouldin Index provide evidence that alpha-3 band in the FZ channel is more affected by heroin abuse than other frequency sub bands.

Asthma and COPD Overlap Syndrome (ACOS): Risk Factors and Contributing Factors.

Background:The exact description of asthma and chronic obstructive pulmonary disease overlap syndrome (ACOS) is uncertain. This study aims to determine the frequency and symptoms of ACOS and to verify certain risk factors associated with ACOS. Methods:Severe asthmatic patients with and without ACOS above 40 years old participated in this cross-sectional study. The receiver operating curve analysis (ROC) was used to assess the best cutoff values of age, body mass index (BMI), and spirometric data to distinguish asthma patients with overlap syndrome from asthma patients without overlap syndrome. Univariable and multivariable binary logistic regression was used to determine demographic and clinical factors that were associated with ACOS and asthma. Results:Of the 88 patients, 46 (52.2%) had ACOS and 42 (47.7%) had just severe asthma. The mean age of ACOS patients (Sd) was 54.91(12.57) years and in asthma-only patients was 48.69 (13.51). The ROC analysis for age and BMI showed that age ⩾ 49 years and BMI ⩾ 27 kg/m2were the best predictors of ACOS in this study. Spirometry data showed that the forced vital capacity (FVC) (lit) > 2.16, forced expiratory volume in the first second (FEV1) > 69, FEV1 / FVC > 96.5, and FVC (%) > 63 cut points could be used to determine the diagnostic criteria between ACOS and asthma only, respectively. Multivariate modeling showed that among the demographic and clinical variables, only age over 49 years (odds ratio [OR], 3.53 [95% CI, 1.07-11.63]p= 0.025) and living in a big city (OR, 7.42 [95% CI, 1.75-31.49]p= 0.007) were significant. Conclusion:Age over 49 and BMI above 27 have a significant association with ACOS. Also, living in a big city is considered to be another risk factor for ACOS compared with asthma. Spirometry can help distinguish ACOS from severe asthma in this study.

The effect of moderate endurance training on gastrocnemius retinol-binding protein 4 and insulin resistance in streptozotocin-induced diabetic rats.

BACKGROUND: Retinol-binding protein 4 (RBP4) is suggested to be involved in the occurrence of insulin resistance. There are contradictory studies about the effects of exercise training on RBP4 levels and insulin resistance. Hence, we designed this study to investigate the impact of moderate endurance training on gastrocnemius RBP4 and insulin resistance in streptozotocin (STZ)-induced diabetic rats. METHOD: Forty male albino Wistar rats were randomly divided into four groups: healthy control (HC), diabetic control (DC), healthy training (HT), and diabetic training (DT). Animals in HT and DT groups ran on a treadmill on the basis of overload principle for 6 weeks, three sessions per week. Rats in DC and DT groups are affected by diabetes using STZ (50 mg/kg of body weight). Gastrocnemius RBP4 content was measured using an enzyme-linked immunosorbent assay kit. Data were analyzed by one-way analysis of variance at P < 0.05 level. RESULTS: Serum blood glucose level (P = 0.001) and insulin resistance (P = 0.001) increased in DC compared with HC group, whereas serum insulin (P = 0.001) and gastrocnemius RBP4 (P = 0.001) reduced. However, there were no significant differences between serum blood glucose level (P = 0.384), insulin resistance (P = 0.999), and RBP4 (P = 0.999) content in DT compared with HT group. CONCLUSION: Moderate endurance training reduces blood glucose level and subsequently improves insulin sensitivity by decreasing gastrocnemius RBP4 content independent of insulin.

The Effect of Tai Chi Exercise on the Risk and Fear of Falling in Older Adults: a Randomized Clinical Trial.

BACKGROUND: Falling and fear of falling are among the most common problems of the elderly, which can cause illness, isolation, dependency and reduced quality of life in elderly. Exercise is recommended to prevent falling injuries in the elderly. AIM: This study aimed to examine the effect of Tai Chi exercise on the risk and fear of falling in older adults. MATERIALS AND METHODS: In this randomized clinical trial, a total of 60 male and female elderly were randomly divided into two groups: Tai Chi exercise and control (daily activities) groups. Tai Chi exercise protocol in the intervention group consisted of 3 sessions per week for 10 weeks. The risk and fear of falling were assessed in subjects by using standardized questionnaires, including Berg's Balance Scale and Fall Efficacy Scale-International (FES-I) before initiating the protocol, at the end of 4th, 8th weeks and at the end of exercise period. RESULTS: Two groups were matched in terms of age, gender, education, and body mass index. Baseline values of risk of falling and fear of falling were not significantly different between the two groups (P>0.05). The score of fear of falling at the end of 4th, 8th weeks and at the end of exercise period was significantly different between the two groups (P<0.05) and it decreased in the intervention group, but the risk of falling reduced after 8 and 10 weeks in the intervention group (P<0.001). CONCLUSION: Performing Tai Chi exercises for at least four weeks could reduce fear of falling and reduce the risk of falls in older adults after 8 weeks.

Retained Surgical Gauze Presenting With Gross Hematuria: A Case Report.

Gossipyboma is a mass which is made around a cotton sponge or abdominal compress retained in a patient during surgery accidentally. Patients manifest with either acute or chronic symptoms due to complications. Here in wereported an 89-year-old man case of transvesical migration of gossipyboma who presented with gross hematuria with a history of transvesical prostatectomy 6 years ago. Patient underwent exploratory laparotomy with repairing of the bladder and peritoneum. He had no complications during surgery and was subsequently discharged.