Machine learning models effectively distinguish attention-deficit/hyperactivity disorder using event-related potentials

Accurate diagnosis of Attention-Deficit/Hyperactivity Disorder (ADHD) is a significant challenge. Misdiagnosis has significant negative medical side effects. Due to the complex nature of this disorder, there is no computational expert system for diagnosis. Recently, automatic diagnosis of ADHD by machine learning analysis of brain signals has received an increased attention. This paper aimed to achieve an accurate model to discriminate between ADHD patients and healthy controls by pattern discovery. Event-Related Potentials (ERP) data were collected from ADHD patients and healthy controls. After pre-processing, ERP signals were decomposed and features were calculated for different frequency bands. The classification was carried out based on each feature using seven machine learning algorithms. Important features were then selected and combined. To find specific patterns for each model, the classification was repeated using the proposed patterns. Results indicated that the combination of complementary features can significantly improve the performance of the predictive models. The newly developed features, defined based on band power, were able to provide the best classification using the Generalized Linear Model, Logistic Regression, and Deep Learning with the average accuracy and Receiver operating characteristic curve > %99.85 and > 0.999, respectively. High and low frequencies (Beta, Delta) performed better than the mid, frequencies in the discrimination of ADHD from control. Altogether, this study developed a machine learning expert system that minimises misdiagnosis of ADHD and is beneficial for the evaluation of treatment efficacy.Graphical abstract      

Reproducibility of swallow-induced cortical BOLD positive and negative fMRI activity

Functional MRI (fMRI) studies have demonstrated that a number of brain regions (cingulate, insula, prefrontal, and sensory/motor cortices) display blood oxygen level-dependent (BOLD) positive activity during swallow. Negative BOLD activations and reproducibility of these activations have not been systematically studied. The aim of our study was to investigate the reproducibility of swallow-related cortical positive and negative BOLD activity across different fMRI sessions. We studied 16 healthy volunteers utilizing an fMRI event-related analysis. Individual analysis using a general linear model was used to remove undesirable signal changes correlated with motion, white matter, and cerebrospinal fluid. The group analysis used a mixed-effects multilevel model to identify active cortical regions. The volume and magnitude of a BOLD signal within each cluster was compared between the two study sessions. All subjects showed significant clustered BOLD activity within the known areas of cortical swallowing network across both sessions. The cross-correlation coefficient of percent fMRI signal change and the number of activated voxels across both positive and negative BOLD networks were similar between the two studies (r ≥ 0.87, P < 0.0001). Swallow-associated negative BOLD activity was comparable to the well-defined "default-mode" network, and positive BOLD activity had noticeable overlap with the previously described "task-positive" network. Swallow activates two parallel cortical networks. These include a positive and a negative BOLD network, respectively, correlated and anticorrelated with swallow stimulus. Group cortical activity maps, as well as extent and amplitude of activity induced by volitional swallowing in the cortical swallowing network, are reproducible between study sessions.     

Riyadh Mother and Baby Multicenter Cohort Study: The Cohort Profile

Objectives

To assess the effects of non-communicable diseases, such as diabetes, hypertension and obesity, on the mother and the infant.

Methods

A multicentre cohort study was conducted in three hospitals in the city of Riyadh in Saudi Arabia. All Saudi women and their babies who delivered in participating hospitals were eligible for recruitment. Data on socio-demographic characteristics in addition to the maternal and neonatal outcomes of pregnancy were collected. The cohort demographic profile was recorded and the prevalence of maternal conditions including gestational diabetes, pre-gestational diabetes, hypertensive disorders in pregnancy and obesity were estimated.

Findings

The total number of women who delivered in participating hospitals during the study period was 16,012 of which 14,568 women participated in the study. The mean age of the participants was 29 ± 5.9 years and over 40% were university graduates. Most of the participants were housewives, 70% were high or middle income and 22% were exposed to secondhand smoke. Of the total cohort, 24% were married to a first cousin. More than 68% of the participants were either overweight or obese. The preterm delivery rate was 9%, while 1.5% of the deliveries were postdate. The stillbirth rate was 13/1000 live birth. The prevalence of gestational diabetes was 24% and that of pre-gestational diabetes was 4.3%. The preeclampsia prevalence was 1.1%. The labour induction rate was 15.5% and the cesarean section rate was 25%.

Conclusion

Pregnant women in Saudi Arabia have a unique demographic profile. The prevalence of obesity and diabetes in pregnancy are among the highest in the world.     

Use of hydrogen cyanamide for apple and plum thinning

Effects of various concentrations of Dormex (a.i. 49% hydrogen cyanamide) on fruit thinning of Rome Beauty apple (Malus domestica Borkh.), Friar and Simka plums (Prunus salicina Lindley) were studied. A full bloom application of Dormex at all tested concentrations decreased Rome Beauty apple fruit set and yield, and increased fruit weight. Dormex at 0.25% (v/v) resulted in adequate apple thinning, indicated by production of an optimum fruit weight (320 g). Prebloom and full bloom applications of Dormex at greater than 0.75% reduced plum fruit set and yield in Friar. Full bloom application of Dormex at 0.50% showed a satisfactory fruit set, yield, and fruit weight in Friar plum. Prebloom Dormex application had no significant effect on `Simka' plum fruit set or yield, but full bloom application decreased fruit set and yield.     

Comparative GO: A Web Application for Comparative Gene Ontology and Gene Ontology-Based Gene Selection in Bacteria

Availabilityhttp://turing.ersa.edu.au/BacteriaGO.     

Modelling the Effects of Water Stress and Temperature on Seed Germination of Radish and Cantaloupe

Cantaloupe (Cucumis melo L.) and radish (Raphanus sativus L.) are considered as important vegetables with potential for national and international markets due to their sugars, vitamins and minerals. This study arranged, therefore, to simultaneously investigate the effect of temperature (T) and water potential (ψ) on seed germination (SG) of these plants using two hydrothermal time (HTT) models and to determine cardinal Ts and base water potential (ψ_b(50)) for both species. The results indicated that SG of both species was more affected by ψ than T (p ≤ 0.001). At Ts below an optimum temperature (T_o) the ψ_b(50) was constant (− 0.582 and − 0.760 MPa for radish and cantaloupe, respectively) and then increased linearly by 0.0481 and 0.0446 MPa °C⁻¹ as T increased above T_o (as thermoinhibition) until 0 MPa at the ceiling temperature (T_c), respectively. As the first report, however, we observed that the T at which ψ_b(50) begins to change was the same here (that is, T_d = T_o), when determined by either model for both species. This result suggests that the assumption in Rowse and Finch-Savage’s model (T_d is often less and or very close to T_o) may be invalid in some cases. For both species, the base temperature (T_b) and T_o were not affected by ψ and were constant while there was an exception only for T_c for which the value declined with decreasing ψs (more negative). In general, the estimated T_b, T_o and T_c were 9.64, 21.3 and 33.0 °C for radish and 11.8, 28.3 and 45.7 °C for cantaloupe in the control condition (ψ = 0 MPa), respectively. The HTT models used here and their parameters, each with strengths and weaknesses, can be used as a predictive tool in both cantaloupe and radish SG simulation models. However, at first, we need to select an appropriate HTT model based on SG behavior of plant species and then use the best model for quantifying the response of SG across Ts and ψs.

     

Increase of autophagy and attenuation of apoptosis by Salvigenin promote survival of SH-SY5Y cells following treatment with H2O2

Oxidative stress is a major component of harmful cascades activated in neurodegenerative disorders. Here, we tried to elucidate the possible neuroprotective effect of Salvigenin, a natural polyphenolic compound, on oxidative stress-induced apoptosis and autophagy in human neuroblastoma SH-SY5Y cells. We measured cell viability by MTT test and found that 25?μM is the best protective concentration of Salvigenin. GSH and SOD assays suggested that Salvigenin activates antioxidant factors. At the same time, measurement of ER stress-associated proteins including calpain and caspase-12 showed the ability of Salvigenin to decrease ER stress. We found that Salvigenin could decrease the apoptotic factors. Salvigenin inhibited H₂O₂-induced caspase-3 which is a hallmark of apoptosis in addition to reducing Bax\Bcl-2 ratio by 1.45 fold. Additionally, Salvigenin increased the levels of autophagic factors. Our results showed an increase in LC3-II/LC3-I ratio, Atg7, and Atg12 in the presence of 25?μM of Salvigenin by about 1.28, 1.25, and 1.54 folds, respectively, compared to H₂O₂-treated cells. So it seems that H₂O₂ cytotoxicity mainly results from apoptosis. Besides, Salvigenin helps cells to survive by inhibiting apoptosis and enhancing autophagy that opens a new horizon for the future experiments.     

The emerging role of miR-200 family in metastasis: focus on EMT,CSCs, angiogenesis,and anoikis

Introduction

Cancer is the second major threat to human society and one of the main challenges facing healthcare systems. One of the main problems of cancer care is the metastases of cancer cells that cause 90% of deaths due to cancer. Multiple molecular mechanisms are involved in cancer cell metastasis. Therefore, a better understanding of these molecular mechanisms is necessary for designing restrictive strategies against cancer cell metastasis. Accumulating data suggests that MicroRNAs (miRNAs) are involved in metastasis and invasion of human tumors through regulating multiple genes expression levels that are involved in molecular mechanisms of metastasis. The goal of this review is to present the molecular pathways by which the miR 200 family manifests its effects on EMT, cancer stem cells, angiogenesis, anoikis, and the effects of tumor cell metastases.

Methods

A detailed literature search was conducted to find information about the role of the miR-200 family in the processes involved in metastasis in various databases.

Results

Numerous lines of evidence revealed an association between the mir-200 family and metastasis of human tumors by impressing processes such as cancer stem cells, EMT, angiogenesis, and anoikis.

Conclusions

Understanding the molecular mechanisms associated with metastasis in which the miR-200 family is involved can be effective in treating metastatic cancers.

Graphic abstract