Structural differences among children, adolescents, and adults with attention-deficit/hyperactivity disorder and abnormal Granger causality of the right pallidum and whole-brain.

Attention-deficit/hyperactivity disorder (ADHD) is a childhood mental health disorder that often persists to adulthood and is characterized by inattentive, hyperactive, or impulsive behaviors. This study investigated structural and effective connectivity differences through voxel-based morphometry (VBM) and Granger causality analysis (GCA) across child, adolescent, and adult ADHD patients. Structural and functional MRI data consisting of 35 children (8.64 ± 0.81 years), 40 adolescents (14.11 ± 1.83 years), and 39 adults (31.59 ± 10.13 years) was obtained from New York University Child Study Center for the ADHD-200 and UCLA dataset. Structural differences in the bilateral pallidum, bilateral thalamus, bilateral insula, superior temporal cortex, and the right cerebellum were observed among the three ADHD groups. The right pallidum was positively correlated with disease severity. The right pallidum as a seed precedes and granger causes the right middle occipital cortex, bilateral fusiform, left postcentral gyrus, left paracentral lobule, left amygdala, and right cerebellum. Also, the anterior cingulate cortex, prefrontal cortex, left cerebellum, left putamen, left caudate, bilateral superior temporal pole, middle cingulate cortex, right precentral gyrus, and the left supplementary motor area demonstrated causal effects on the seed region. In general, this study showed the structural differences and the effective connectivity of the right pallidum amongst the three ADHD age groups. Our work also highlights the evidence of the frontal-striatal-cerebellar circuits in ADHD and provides new insights into the effective connectivity of the right pallidum and the pathophysiology of ADHD. Our results further demonstrated that GCA could effectively explore the interregional causal relationship between abnormal regions in ADHD.

Gender Differences in Dynamic Functional Network Connectivity in Pediatric and Adult Patients with Attention-Deficit/Hyperactivity Disorder.

Attention-deficit/hyperactivity disorder (ADHD) persistence into adulthood depends on gender, with 60% female and 35% male cases. This study sought to investigate gender differences in dynamic functional network connectivity (FNC) using resting-state functional magnetic resonance imaging data of pediatric ADHD patients (female: N = 24; 11.02 ± 2.60 years, male: N = 20;11.87 ± 2.62 years) and adult ADHD patients (female = 19; 31.11 ± 10.40 years, males: N = 20;32.05 ± 10.10 years). We identified nine and eight networks in pediatrics and adult data, respectively, using group independent component analysis (GICA). Each age group was clustered into four states using K-means. Significant gender differences in the pediatric group were only found in temporal profiles, particularly in "fraction of time" (FOT) and "mean dwell time" (MDT), but not in FNC. FOT spent by the female pediatric group in state 4 showed a negative relationship with hyperactivity severity. Compared with the adult male group, reduced connectivity was observed within the visual network (VN), between the VN and default-mode network (DMN), and frontoparietal network, as well as between the DMN and cerebellum networks in female adult ADHD patients. Significant FOT and MDT differences were observed between the two groups in state 3. Our results imply gender differences in ADHD, especially in the adult group. Furthermore, given the gender differences observed, our work provides insights into the pathophysiology of ADHD subserved by gender. Impact statement Attention-deficit/hyperactivity disorder (ADHD) symptoms differ between genders; however, little has been done to determine gender differences in pediatric and adult ADHD patients. The present work presents the first gender-specific dynamic functional network connectivity study for different age groups of ADHD patients and highlights the discrepancies between male and female ADHD patients, particularly in the adult group, which may be due to the persistence of inattentive symptoms in female ADHD patients from childhood into adulthood. Given the gender differences observed in the current study, clinicians could consider treatment strategies that target each gender in each age group. The present work provides further insight into the connectivity patterns of the resting-state network in ADHD and may also serve as a basis for future sex-specific studies in different age groups in other disorders.

Effect of surgical mask on fMRI signals during task and rest.

Wearing a face mask has become essential to contain the spread of COVID-19 and has become mandatory when collecting fMRI data at most research institutions. Here, we investigate the effects of wearing a surgical mask on fMRI data in n = 37 healthy participants. Activations during finger tapping, emotional face matching, working memory tasks, and rest were examined. Preliminary fMRI analyses show that despite the different mask states, resting-state signals and task activations were relatively similar. Resting-state functional connectivity showed negligible attenuation patterns in mask-on compared with mask-off. Task-based ROI analysis also demonstrated no significant difference between the two mask states under each contrast investigated. Notwithstanding the overall insignificant effects, these results indicate that wearing a face mask during fMRI has little to no significant effect on resting-state and task activations.

Differences in Disrupted Dynamic Functional Network Connectivity Among Children, Adolescents, and Adults With Attention Deficit/Hyperactivity Disorder: A Resting-State fMRI Study.

Attention deficit hyperactivity disorder (ADHD) is one of the most widespread mental disorders and often persists from childhood to adulthood, and its symptoms vary with age. In this study, we aim to determine the disrupted dynamic functional network connectivity differences in adult, adolescent, and child ADHD using resting-state functional magnetic resonance imaging (rs-fMRI) data consisting of 35 children (8.64 ± 0.81 years), 40 adolescents (14.11 ± 1.83 years), and 39 adults (31.59 ± 10.13 years). We hypothesized that functional connectivity is time-varying and that there are within- and between-network connectivity differences among the three age groups. Nine functional networks were identified using group ICA, and three FC-states were recognized based on their dynamic functional network connectivity (dFNC) pattern. Fraction of time, mean dwell time, transition probability, degree-in, and degree-out were calculated to measure the state dynamics. Higher-order networks including the DMN, SN, and FPN, and lower-order networks comprising the SMN, VN, SC, and AUD were frequently distributed across all states and were found to show connectivity differences among the three age groups. Our findings imply abnormal dynamic interactions and dysconnectivity associated with different ADHD, and these abnormalities differ between the three ADHD age groups. Given the dFNC differences between the three groups in the current study, our work further provides new insights into the mechanism subserved by age difference in the pathophysiology of ADHD and may set the grounds for future case-control studies in the individual age groups, as well as serving as a guide in the development of treatment strategies to target these specific networks in each age group.

Common abnormality of gray matter integrity in substance use disorder and obsessive-compulsive disorder: A comparative voxel-based meta-analysis.

The objective of the current study is to determine robust transdiagnostic brain structural markers for compulsivity by capitalizing on the increasing number of case-control studies examining gray matter volume (GMV) alterations in substance use disorders (SUD) and obsessive-compulsive disorder (OCD). Voxel-based meta-analysis within the individual disorders and conjunction analysis were employed to reveal common GMV alterations between SUDs and OCD. Meta-analytic coordinates and signed brain volumetric maps determining directed (reduced/increased) GMV alterations between the disorder groups and controls served as the primary outcome. The separate meta-analysis demonstrated that SUD and OCD patients exhibited widespread GMV reductions in frontocortical regions including prefrontal, cingulate, and insular. Conjunction analysis revealed that the left inferior frontal gyrus (IFG) consistently exhibited decreased GMV across all disorders. Functional characterization suggests that the IFG represents a core hub in the cognitive control network and exhibits bidirectional (Granger) causal interactions with the striatum. Only OCD showed increased GMV in the dorsal striatum with higher changes being associated with more severe OCD symptomatology. Together the findings demonstrate robustly decreased GMV across the disorders in the left IFG, suggesting a transdiagnostic brain structural marker. The functional characterization as a key hub in the cognitive control network and casual interactions with the striatum suggest that deficits in inhibitory control mechanisms may promote compulsivity and loss of control that characterize both disorders.

CISI: A Tool for Predicting Cross-interaction or Self-interaction of Monoclonal Antibodies Using Sequences.

Monoclonal antibodies (mAbs) are one of the robust classes of therapeutic proteins. Their stability, specificity, and high solubility allow the successful development and commercialization of antibody-based drugs. Though with these characteristics, mAbs projects are often suspended due to self- or cross-interaction of monoclonal antibodies. This is one of the main reasons which causes the development of mAbs into drugs taking forever and expensive. CISI is short for cross-interaction or self-interaction of mAbs. It can be quantified by several assays. The assays such as poly-specificity reagent and cross-interaction chromatography can measure cross-interaction of mAbs. Self-interaction can be assayed through clone self-interaction by biolayer interferometry and affinity-capture self-interaction nanoparticle spectroscopy. To save time and money, we developed a model called CISI which can predict cross-interaction or self-interaction based on tripeptide composition. It showed 88.20% accuracy, 90.22% sensitivity, 86.05% specificity, 0.78 Mathew correlation coefficient, and 0.96 area under the receiver operating characteristic (ROC) curve (AUC) in the leave-one-out cross-validation. CISI is freely available at http://i.uestc.edu.cn/eli/cgi-bin/cisi.pl.