The Antitumor Effect of Topotecan Loaded Thiolated Chitosan-Dextran Nanoparticles for Intravitreal Chemotherapy: A Xenograft Retinoblastoma Model

Purpose: This research intended to fabricate the thiolated chitosan-dextran nanoparticles (NPs) containing topotecan (TPH-CMD-TCS-NPs) to assess the ability of NPs in improving the efficacy of intravitreal chemotherapy of retinoblastoma in a rabbit xenograft model. Methods: The coacervation process was used to produce the NPs. The cellular uptake of Cyanine-3 (CY3)-labeled NPs were investigated in human retinoblastoma Y79 cells using confocal microscopy. Also, the prepared TPH-CMD-TCS-NPs were tested in vitro by the tetrazolium dyes II (XTT) and flow cytometry in order to assess their cytotoxicity. In addition, a rabbit xenograft model of retinoblastoma was developed to test the antitumor effectiveness of TPH-CMD-TCS-NPs through intravitreal administration. Results: NPs had a mean diameter, polydispersity index, and zeta potential of 30 ± 4 nm, 0.24 ± 0.03 and +10 ± 3 mV, respectively. NPs (IC50s 40.40 compared to 126.20 nM, P = 0.022) were more effective than free topotecan as a dose-based feature. The tumor reaction to intravitreal chemotherapy with NPs was measured by evaluating the percentage of necrosis in the tumor tissue (91 ± 2%) and vitreous seeds (89 ± 9%) through hematoxylin and eosin (H&E) staining. In comparison with the control group, the TPHCMD- TCs-NPs treated group showed a significant decrease in tumor volume seven days after the intravitreal injection (P = 0.039). No significant changes were found in the ERG parameters after the intravitreal injection of TPH-CMD-TCs-NPs or TPH (P > 0.05). Conclusion: This investigation revealed definitive antitumor efficacy of TPH-CMD-TCSNPs by intravitreal administration in the rabbit xenograft retinoblastoma model

Assessing the Effects of Alzheimer Disease on EEG Signals Using the Entropy Measure: A Meta-analysis

Introduction: Alzheimer disease (AD) is the most prevalent neurodegenerative disorder and a type of dementia. About 80% of dementia in older adults is due to AD. According to multiple research articles, AD is associated with several changes in EEG signals, such as slow rhythms, reduction in complexity and functional associations, and disordered functional communication between different brain areas. This research focuses on the entropy parameter. Methods: In this study, the keywords “Entropy,” “EEG,” and “Alzheimer” were used. In the initial search, 102 articles were found. In the first stage, after investigating the Abstracts of the articles, the number of them was reduced to 62, and upon further review of the remaining articles, the number of articles was reduced to 18. Some papers have used more than one entropy of EEG signals to compare, and some used more than one database. So, 25 entropy measures were considered in this meta-analysis. We used the Standardized Mean Difference (SMD) to find the effect size and compare the effects of AD on the entropy of the EEG signal in healthy people. Funnel plots were used to investigate the bias of meta-analysis. Results: According to the articles, entropy seems to be a good benchmark for comparing the EEG signals between healthy people and AD people.  Conclusion: It can be concluded that AD can significantly affect EEG signals and reduce the entropy of EEG signals

Brain Connectivity Reflected in Electroencephalogram Coherence in Individuals With Autism: A Meta-analysis

Introduction: Many theories have been proposed about the etiology of autism. One is related to brain connectivity in patients with autism. Several studies have reported brain connectivity changes in autism disease. This study was performed on Electroencephalogram (EEG) studies that evaluated patients with autism, using functional brain connectivity, and compared them with typically-developing individuals. Methods: Three scientific databases of ScienceDirect, Medline (PubMed), and BioMed Central were systematically searched through their online search engines. Comprehensive Meta-analysis software analyzed the obtained data. Results: The systematic search led to 10 papers, in which EEG coherence was used to obtain the brain connectivity of people with autism. To determine the effect size, Cohen’s d parameter was used. In the first meta-analysis, the study of the maximum effect size was considered, and all significant effect sizes were evaluated in the second meta-analysis. The effect size was assessed using a random-effects model in both meta-analyses. The results of the first meta-analysis indicated that heterogeneity was not present among the studies (Q=13.345, P>0.1). The evaluation of all effect sizes in the second meta-analysis showed a significant lack of homogeneity among the studies (Q=56.984, P=0.0001). Conclusion: On the whole, autism was found to be related to neural connectivity, and the present research showed the difference in the EEG coherence of people with autism and healthy people. These conclusions require further studies with more extensive data, considering different brain regions, and novel analysis techniques for assessing brain connectivity

Investigation of Brain Functional Networks in Children Suffering from Attention Deficit Hyperactivity Disorder

Here is the pre-processed EEG dataset for ADHD and the Healthy control group while they were facing four facial emotions (Angry, Happy, Neutral, and Sad). They saw 60 images of facial expression for each emotions. Each participant's data is put in a folder named from P1 to P52. P31 and P43 have been removed from the data list due to noisy data. P15 to P17, P22 to P43, and P51 and P52 are labeled as ADHD group and the rest are healthy group. In each folder (e.g., P1) there are five folders. A refers to Angry epochs, H refers to happy epochs, N refers to neutral epochs, and S refers to Sad epoch, as well as the channel location. The matrix for each emotions is with the size of 62*1536*60 refering to channels*samples*epochs Cite: Dini, H., Farnaz.Ghassemi & Sendi, M.S.E. Investigation of Brain Functional Networks in Children Suffering from Attention Deficit Hyperactivity Disorder. Brain Topogr 33, 733–750 (2020). https://doi.org/10.1007/s10548-020-00794-

Emotional Face Recognition in Children With Attention Deficit/Hyperactivity Disorder: Evidence From Event Related Gamma Oscillation

Introduction: Children with attention-deficit/hyperactivity disorder (ADHD) have some impairment in emotional relationship which can be due to problems in emotional processing. The present study investigated neural correlates of early stages of emotional face processing in this group compared with typically developing children using the Gamma Band Activity (GBA). Methods: A total of 19 children diagnosed with ADHD (Combined type) based on DSM-IV classification were compared with 19 typically developing children matched on age, gender, and IQ. The participants performed an emotional face recognition while their brain activities were recorded using an event-related oscillation procedure. Results: The results indicated that ADHD children compared to normal group showed a significant reduction in the gamma band activity, which is thought to reflect early perceptual emotion discrimination for happy and angry emotions (P<0.05).&nbsp; Conclusion: The present study supports the notion that individuals with ADHD have some impairments in early stage of emotion processing which can cause their misinterpretation of emotional faces

Converting high-dimensional complex networks to lower-dimensional ones preserving synchronization features

Studying the stability of synchronization of coupled oscillators is one of the prominent topics in network science. However, in most cases, the computational cost of complex network analysis is challenging because they consist of a large number of nodes. This study includes overcoming this obstacle by presenting a method for reducing the dimension of a large-scale network, while keeping the complete region of stable synchronization unchanged. To this aim, the first and last non-zero eigenvalues of the Laplacian matrix of a large network are preserved using the eigen-decomposition method and Gram-Schmidt orthogonalization. The method is only applicable to undirected networks and the result is a weighted undirected network with smaller size. The reduction method is studied in a large-scale a small-world network of Sprott-B oscillators. The results show that the trend of the synchronization error is well maintained after node reduction for different coupling schemes

Early Posterior Negativity as Facial Emotion Recognition Index in Children With Attention Deficit Hyperactivity Disorder

Introduction: Studies indicate that children with Attention Deficit Hyperactivity Disorder (ADHD) have deficits in social and emotional functions. It can be hypothesized that these children have some deficits in early stages of facial emotion discrimination. Based on this hypothesis, the present study investigated neural correlates of early visual processing during emotional face recognition in this group compared with typically developing children using the Event-Related Potentials (ERPs).  Methods: Nineteen boys between the ages of 7 and 11 years diagnosed with ADHD (Combined type) based on DSM-IV-TR classification were compared with 19 typically developing children matched on age and gender. The participants performed an emotional face recognition task while their brain activities were recorded using the event-related potentials procedure.  Results: A significant reduction in the Early Posterior Negativity (EPN) for happy and angry faces has been revealed in ADHD children compared to normal ones (P<0.05). Conclusion: The present study supports the notion that individuals with ADHD have some impairments in early stage of emotion processing which can leading to their misinterpretation of emotion in faces