Replication of a neuroimaging biomarker for striatal dysfunction in psychosis.

To bring biomarkers closer to clinical application, they should be generalizable, reliable, and maintain performance within the constraints of routine clinical conditions. The functional striatal abnormalities (FSA), is among the most advanced neuroimaging biomarkers in schizophrenia, trained to discriminate diagnosis, with post-hoc analyses indicating prognostic properties. Here, we attempt to replicate its diagnostic capabilities measured by the area under the curve (AUC) in receiver operator characteristic curves discriminating individuals with psychosis (n = 101) from healthy controls (n = 51) in the Human Connectome Project for Early Psychosis. We also measured the test-retest (run 1 vs 2) and phase encoding direction (i.e., AP vs PA) reliability with intraclass correlation coefficients (ICC). Additionally, we measured effects of scan length on classification accuracy (i.e., AUCs) and reliability (i.e., ICCs). Finally, we tested the prognostic capability of the FSA by the correlation between baseline scores and symptom improvement over 12 weeks of antipsychotic treatment in a separate cohort (n = 97). Similar analyses were conducted for the Yeo networks intrinsic connectivity as a reference. The FSA had good/excellent diagnostic discrimination (AUC = 75.4%, 95% CI = 67.0-83.3%; in non-affective psychosis AUC = 80.5%, 95% CI = 72.1-88.0%, and in affective psychosis AUC = 58.7%, 95% CI = 44.2-72.0%). Test-retest reliability ranged between ICC = 0.48 (95% CI = 0.35-0.59) and ICC = 0.22 (95% CI = 0.06-0.36), which was comparable to that of networks intrinsic connectivity. Phase encoding direction reliability for the FSA was ICC = 0.51 (95% CI = 0.42-0.59), generally lower than for networks intrinsic connectivity. By increasing scan length from 2 to 10 min, diagnostic classification of the FSA increased from AUC = 71.7% (95% CI = 63.1-80.3%) to 75.4% (95% CI = 67.0-83.3%) and phase encoding direction reliability from ICC = 0.29 (95% CI = 0.14-0.43) to ICC = 0.51 (95% CI = 0.42-0.59). FSA scores did not correlate with symptom improvement. These results reassure that the FSA is a generalizable diagnostic - but not prognostic - biomarker. Given the replicable results of the FSA as a diagnostic biomarker trained on case-control datasets, next the development of prognostic biomarkers should be on treatment-response data.

Common and distinct functional brain network abnormalities in adolescent, early-middle adult, and late adult major depressive disorders.

BACKGROUND: The age-related heterogeneity in major depressive disorder (MDD) has received significant attention. However, the neural mechanisms underlying such heterogeneity still need further investigation. This study aimed to explore the common and distinct functional brain abnormalities across different age groups of MDD patients from a large-sample, multicenter analysis. METHODS: The analyzed sample consisted of a total of 1238 individuals including 617 MDD patients (108 adolescents, 12-17 years old; 411 early-middle adults, 18-54 years old; and 98 late adults, > = 55 years old) and 621 demographically matched healthy controls (60 adolescents, 449 early-middle adults, and 112 late adults). MDD-related abnormalities in brain functional connectivity (FC) patterns were investigated in each age group separately and using the whole pooled sample, respectively. RESULTS: We found shared FC reductions among the sensorimotor, visual, and auditory networks across all three age groups of MDD patients. Furthermore, adolescent patients uniquely exhibited increased sensorimotor-subcortical FC; early-middle adult patients uniquely exhibited decreased visual-subcortical FC; and late adult patients uniquely exhibited wide FC reductions within the subcortical, default-mode, cingulo-opercular, and attention networks. Analysis of covariance models using the whole pooled sample further revealed: (1) significant main effects of age group on FCs within most brain networks, suggesting that they are decreased with aging; and (2) a significant age group × MDD diagnosis interaction on FC within the default-mode network, which may be reflective of an accelerated aging-related decline in default-mode FCs. CONCLUSIONS: To summarize, these findings may deepen our understanding of the age-related biological and clinical heterogeneity in MDD.

Altered single-subject gray matter structural networks in social anxiety disorder.

Previous fMRI studies have reported more random brain functional graph configurations in social anxiety disorder (SAD). However, it is still unclear whether the same configurations would occur in gray matter (GM) graphs. Structural MRI was performed on 49 patients with SAD and on 51 age- and gender-matched healthy controls (HC). Single-subject GM networks were obtained based on the areal similarities of GM, and network topological properties were analyzed using graph theory. Group differences in each topological metric were compared, and the structure-function coupling was examined. These network measures were further correlated with the clinical characteristics in the SAD group. Compared with controls, the SAD patients demonstrated globally decreased clustering coefficient and characteristic path length. Altered topological properties were found in the fronto-limbic and sensory processing systems. Altered metrics were associated with the illness duration of SAD. Compared with the HC group, the SAD group exhibited significantly decreased structural-functional decoupling. Furthermore, structural-functional decoupling was negatively correlated with the symptom severity in SAD. These findings highlight less-optimized topological configuration of the brain structural networks in SAD, which may provide insights into the neural mechanisms underlying the excessive fear and avoidance of social interactions in SAD.

The alpha-2A-adrenergic receptor gene polymorphism modulates gray matter structural networks, visual memory, and inhibitory cognitive control in children with attention deficit/hyperactivity disorder.

The ADRA2A-1291 C > G polymorphism and deficits in visual memory and inhibitory control were associated with attention deficit hyperactivity disorder (ADHD). The present study aimed to examine whether the ADRA2A G/G genotype affected gray matter (GM) networks in ADHD and whether these gene-brain modulations were associated with cognitive function in ADHD. Seventy-five drug-naïve ADHD children and 70 healthy controls were recruited. The GM networks were obtained based on areal similarities of GM, and network topological properties were analyzed using graph theory. Visual memory and inhibitory control were assessed by the visual memory test and the Stroop test, respectively. SNP genotyping of rs1800544 was performed. A significant interaction between ADHD diagnosis and gene polymorphism was observed in the nodal degree of the left inferior parietal lobule and left inferior (opercular) frontal gyrus. In the ADHD group, nodal efficiency in the left inferior (orbital) frontal gyrus in ADHD with G/G was lower than that in ADHD without G/G. Moreover, the ADRA2A-modulated alterations in nodal properties were associated with visual memory and inhibitory control. Our findings provide novel gene-brain behavior association evidence that GM network alterations, especially in the frontoparietal loop, were related to visual memory and inhibitory control in ADHD children with ADRA2A-G/G.

Altered controllability of white matter networks and related brain function changes in first-episode drug-naive schizophrenia.

Understanding how structural connectivity alterations affect aberrant dynamic function using network control theory will provide new mechanistic insights into the pathophysiology of schizophrenia. The study included 140 drug-naive schizophrenia patients and 119 healthy controls (HCs). The average controllability (AC) quantifying capacity of brain regions/networks to shift the system into easy-to-reach states was calculated based on white matter connectivity and was compared between patients and HCs as well as functional network topological and dynamic properties. The correlation analysis between AC and duration of untreated psychosis (DUP) were conducted to characterize the controllability progression pattern without treatment effects. Relative to HCs, patients exhibited reduced AC in multiple nodes, mainly distributed in default mode network (DMN), visual network (VN), and subcortical regions, and increased AC in somatomotor network. These networks also had impaired functional topology and increased temporal variability in dynamic functional connectivity analysis. Longer DUP was related to greater reductions of AC in VN and DMN. The current study highlighted potential structural substrates underlying altered functional dynamics in schizophrenia, providing a novel understanding of the relationship of anatomic and functional network alterations.

Effects of phase encoding direction on test-retest reliability of human functional connectome.

The majority of human connectome studies in the literature based on functional magnetic resonance imaging (fMRI) data use either an anterior-to-posterior (AP) or a posterior-to-anterior (PA) phase encoding direction (PED). However, whether and how PED would affect test-retest reliability of functional connectome is unclear. Here, in a sample of healthy subjects with two sessions of fMRI scans separated by 12 weeks (two runs per session, one with AP, the other with PA), we tested the influence of PED on global, nodal, and edge connectivity in the constructed brain networks. All data underwent the state-of-the-art Human Connectome Project (HCP) pipeline to correct for phase-encoding-related distortions before entering analysis. We found that at the global level, the PA scans showed significantly higher intraclass correlation coefficients (ICCs) for global connectivity compared with AP scans, which was particularly prominent when using the Seitzman-300 atlas (versus the CAB-NP-718 atlas). At the nodal level, regions most strongly affected by PED were consistently mapped to the cingulate cortex, temporal lobe, sensorimotor areas, and visual areas, with significantly higher ICCs during PA scans compared with AP scans, regardless of atlas. Better ICCs were also observed during PA scans at the edge level, in particular when global signal regression (GSR) was not performed. Further, we demonstrated that the observed reliability differences between PEDs may relate to a similar effect on the reliability of temporal signal-to-noise ratio (tSNR) in the same regions (that PA scans were associated with higher reliability of tSNR than AP scans). Averaging the connectivity outcome from the AP and PA scans could increase median ICCs, especially at the nodal and edge levels. Similar results at the global and nodal levels were replicated in an independent, public dataset from the HCP-Early Psychosis (HCP-EP) study with a similar design but a much shorter scan session interval. Our findings suggest that PED has significant effects on the reliability of connectomic estimates in fMRI studies. We urge that these effects need to be carefully considered in future neuroimaging designs, especially in longitudinal studies such as those related to neurodevelopment or clinical intervention.

Evaluating test-retest reliability and sex-/age-related effects on temporal clustering coefficient of dynamic functional brain networks.

The multilayer dynamic network model has been proposed as an effective method to understand the brain function. In particular, derived from the definition of clustering coefficient in static networks, the temporal clustering coefficient provides a direct measure of the topological stability of dynamic brain networks and shows potential in predicting altered brain functions. However, test-retest reliability and demographic-related effects on this measure remain to be evaluated. Using a data set from the Human Connectome Project (157 male and 180 female healthy adults; 22-37 years old), the present study investigated: (1) the test-retest reliability of temporal clustering coefficient across four repeated resting-state functional magnetic resonance imaging scans as measured by intraclass correlation coefficient (ICC); and (2) sex- and age-related effects on temporal clustering coefficient. The results showed that (1) the temporal clustering coefficient had overall moderate test-retest reliability (ICC > 0.40 over a wide range of densities) at both global and subnetwork levels, (2) female subjects showed significantly higher temporal clustering coefficient than males at both global and subnetwork levels, particularly within the default-mode and subcortical regions, and (3) temporal clustering coefficient of the subcortical subnetwork was positively correlated with age in young adults. The results of sex effects were robustly replicated in an independent REST-meta-MDD data set, while the results of age effects were not. Our findings suggest that the temporal clustering coefficient is a relatively reliable and reproducible approach for identifying individual differences in brain function, and provide evidence for demographically related effects on the human brain dynamic connectomes.

Prefrontal-cerebellar dynamics during post-success and post-error cognitive controls in major psychiatric disorders.

BACKGROUND: Difficulty in cognitive adjustment after a conflict or error is a hallmark for many psychiatric disorders, yet the underlying neural correlates are not fully understood. We have previously shown that post-success and post-error cognitive controls are associated with distinct mechanisms particularly related to the prefrontal-cerebellar circuit, raising the possibility that altered dynamic interactions in this circuit may underlie mental illness. METHODS: This study included 136 patients with three diagnosed disorders [48 schizophrenia (SZ), 49 bipolar disorder (BD), 39 attention deficit hyperactivity disorder (ADHD)] and 89 healthy controls who completed a stop-signal task during fMRI scans. Brain activations for concurrent, post-success, and post-error cognitive controls were analyzed and compared between groups. Dynamic causal modeling was applied to investigate prefrontal-cerebellar effective connectivity patterns during post-success and post-error processing. RESULTS: No significant group differences were observed for brain activations and overall effective connectivity structures during post-success and post-error conditions. However, significant group differences were shown for the modulational effect on top-down connectivity from the prefrontal cortex to the cerebellum during post-error trials (pFWE = 0.02), which was driven by reduced modulations in both SZ and ADHD. During post-success trials, there were significantly decreased modulational effect on bottom-up connectivity from the cerebellum to the prefrontal cortex in ADHD (pFWE = 0.04) and decreased driving input to the cerebellum in SZ (pFWE = 0.04). CONCLUSIONS: These findings suggest that patients with SZ and ADHD are associated with insufficient neural modulation on the prefrontal-cerebellar circuit during post-success and post-error cognitive processing, a phenomenon that may underlie cognitive deficits in these disorders.

The Cerebellum and Cognitive Function: Anatomical Evidence from a Transdiagnostic Sample.

Multiple lines of evidence across human functional, lesion, and animal data point to a cerebellar role, in particular of crus I, crus II, and lobule VIIB, in cognitive function. However, a mapping of distinct facets of cognitive function to cerebellar structure is missing. We analyzed structural neuroimaging data from the Healthy Brain Network (HBN). Cerebellar parcellation was performed with a validated automated segmentation pipeline (CERES) and stringent visual quality check (n = 662 subjects retained from initial n = 1452). Canonical correlation analyses (CCA) examined regional gray matter volumetric (GMV) differences in association to cognitive function (quantified with NIH Toolbox Cognition domain, NIH-TB), accounting for psychopathology severity, age, sex, scan location, and intracranial volume. Multivariate CCA uncovered a significant correlation between two components entailing a latent cognitive canonical (NIH-TB subscales) and a brain canonical variate (cerebellar GMV and intracranial volume, ICV), surviving bootstrapping and permutation procedures. The components correspond to partly shared cerebellar-cognitive function relationship with a first map encompassing cognitive flexibility (r = 0.89), speed of processing (r = 0.65), and working memory (r = 0.52) associated with regional GMV in crus II (r = 0.57) and lobule X (r = 0.59) and a second map including the crus I (r = 0.49) and lobule VI (r = 0.49) associated with working memory (r = 0.51). We show evidence for a structural subspecialization of the cerebellum topography for cognitive function in a transdiagnostic sample.

Altered single-subject gray matter structural networks in drug-naïve attention deficit hyperactivity disorder children.

Altered topological organization of brain structural covariance networks has been observed in attention deficit hyperactivity disorder (ADHD). However, results have been inconsistent, potentially related to confounding medication effects. In addition, since structural networks are traditionally constructed at the group level, variabilities in individual structural features remain to be well characterized. Structural brain imaging with MRI was performed on 84 drug-naïve children with ADHD and 83 age-matched healthy controls. Single-subject gray matter (GM) networks were obtained based on areal similarities of GM, and network topological properties were analyzed using graph theory. Group differences in each topological metric were compared using nonparametric permutation testing. Compared with healthy subjects, GM networks in ADHD patients demonstrated significantly altered topological characteristics, including higher global and local efficiency and clustering coefficient, and shorter path length. In addition, ADHD patients exhibited abnormal centrality in corticostriatal circuitry including the superior frontal gyrus, orbitofrontal gyrus, medial superior frontal gyrus, precentral gyrus, middle temporal gyrus, and pallidum (all p < .05, false discovery rate [FDR] corrected). Altered global and nodal topological efficiencies were associated with the severity of hyperactivity symptoms and the performance on the Stroop and Wisconsin Card Sorting Test tests (all p < .05, FDR corrected). ADHD combined and inattention subtypes were differentiated by nodal attributes of amygdala (p < .05, FDR corrected). Alterations in GM network topologies were observed in drug-naïve ADHD patients, in particular in frontostriatal loops and amygdala. These alterations may contribute to impaired cognitive functioning and impulsive behavior in ADHD.

Functional connectome-wide associations of schizophrenia polygenic risk.

Schizophrenia is a highly heritable mental disorder characterized by functional dysconnectivity across the brain. However, the relationships between polygenic risk factors and connectome-wide neural mechanisms are unclear. Here, combining genetic and multiparadigm fMRI data of 623 healthy Caucasian adults drawn from the Human Connectome Project, we found that higher schizophrenia polygenic risk scores were significantly correlated with lower functional connectivity in a large-scale brain network primarily encompassing the visual system, default-mode system, and frontoparietal system. Such correlation was robustly observed across multiple fMRI paradigms, suggesting a brain-state-independent neural phenotype underlying individual genetic liability to schizophrenia. Moreover, using an independent clinical dataset acquired from the Consortium for Neuropsychiatric Phenomics, we further demonstrated that the connectivity of the identified network was reduced in patients with schizophrenia and significantly correlated with general cognitive ability. These findings provide the first evidence for connectome-wide associations of schizophrenia polygenic risk at the systems level and suggest that disrupted integration of sensori-cognitive information may be a hallmark of genetic effects on the brain that contributes to the pathogenesis of schizophrenia.

Load-dependent inverted U-shaped connectivity of the default mode network in schizophrenia during a working-memory task: evidence from a replication functional MRI study.

BACKGROUND: Working-memory deficit is associated with aberrant degree distribution of the brain connectome in schizophrenia. However, the brain neural mechanism underlying the degree redistribution pattern in schizophrenia is still uncertain. METHODS: We examined the functional degree distribution of the connectome in 81 patients with schizophrenia and 77 healthy controls across different working-memory loads during an n-back task. We tested the associations between altered degree distribution and clinical symptoms, and we conducted functional connectivity analyses to investigate the neural mechanism underlying altered degree distribution. We repeated these analyses in a second independent data set of 96 participants. In the second data set, we employed machine-learning analysis to study whether the degree distribution pattern of one data set could be used to discriminate between patients with schizophrenia and controls in the other data set. RESULTS: Patients with schizophrenia showed decreased centrality in the dorsal posterior cingulate cortex (dPCC) for the "2-back versus 0-back" contrast compared to healthy controls. The dPCC centrality pattern across all working-memory loads was an inverted U shape, with a left shift of this pattern in patients with schizophrenia. This reduced centrality was correlated with the severity of delusions and related to reduced functional connectivity between the dPCC and the dorsal precuneus. We replicated these results with the second data set, and the machine-learning analyses achieved an accuracy level of 71%. LIMITATIONS: We used a limited n-back paradigm that precluded the examination of higher working-memory loads. CONCLUSION: Schizophrenia is characterized by a load-dependent reduction of centrality in the dPCC, related to the severity of delusions. We suggest that restoring dPCC centrality in the presence of cognitive demands might have a therapeutic effect on persistent delusions in people with schizophrenia.

Analysis of and Experimental Research on a Hydraulic Traction System Based on a Digital Hydraulic Transformer.

In this study, we designed a new type of digital hydraulic transformer using four gear-pump/motor units with a displacement ratio of 20:21:22:23 and two control valve groups that consist of four solenoid directional valves. The driving gear shafts of the four gear-pump/motor units are fixedly connected to achieve synchronous rotation. The two control valve groups are respectively installed through an integrated valve block on the inlet and outlet of each gear-pump/motor unit. With the objective of reducing the installed power and energy consumption of hydraulic traction systems, we propose a new energy-saving hydraulic system based on a digital hydraulic transformer. This hydraulic system uses a digital hydraulic transformer as a pressure/flow control element. By controlling the power on/off states of eight solenoid directional valves, the digital hydraulic transformer can realize a change in output flow and then a change in speed of the hydraulic cylinder piston rod. Through the theoretical derivation and simulation analysis of the hydraulic system pressure/flow change process, and the experimental verification of the built hydraulic traction system based on the experimental platform, a conclusion is drawn that the proposed digital hydraulic transformer can change the output pressure/flow of a hydraulic system through a binary digital control, verifying the feasibility of the pressure change principle of the designed digital hydraulic transformer and the rationality of the hydraulic traction system circuit.

Identifying neural signatures mediating behavioral symptoms and psychosis onset: High-dimensional whole brain functional mediation analysis.

Along the pathway from behavioral symptoms to the development of psychotic disorders sits the multivariate mediating brain. The functional organization and structural topography of large-scale multivariate neural mediators among patients with brain disorders, however, are not well understood. Here, we design a high-dimensional brain-wide functional mediation framework to investigate brain regions that intermediate between baseline behavioral symptoms and future conversion to full psychosis among individuals at clinical high risk (CHR). Using resting-state functional magnetic resonance imaging (fMRI) data from 263 CHR subjects, we extract an α brain atlas and a ß brain atlas: the former underlines brain areas associated with prodromal symptoms and the latter highlights brain areas associated with disease onset. In parallel, we identify and separate mediators that potentially positively and negatively mediate symptoms and psychosis, respectively, and quantify the effect of each neural mediator on disease development. Taken together, these results paint a brain-wide picture of neural markers that are potentially mediating behavioral symptoms and the development of psychotic disorders; additionally, they underscore a statistical framework that is useful to uncover large-scale intermediating variables in a regulatory biological system.

Distinct and temporally associated neural mechanisms underlying concurrent, postsuccess, and posterror cognitive controls: Evidence from a stop-signal task.

Cognitive control is built upon the interactions of multiple brain regions. It is currently unclear whether the involved regions are temporally separable in relation to different cognitive processes and how these regions are temporally associated in relation to different task performances. Here, using stop-signal task data acquired from 119 healthy participants, we showed that concurrent and poststop cognitive controls were associated with temporally distinct but interrelated neural mechanisms. Specifically, concurrent cognitive control activated regions in the cingulo-opercular network (including the dorsal anterior cingulate cortex [dACC], insula, and thalamus), together with superior temporal gyrus, secondary motor areas, and visual cortex; while regions in the fronto-parietal network (including the lateral prefrontal cortex [lPFC] and inferior parietal lobule) and cerebellum were only activated during poststop cognitive control. The associations of activities between concurrent and poststop regions were dependent on task performance, with the most notable difference in the cerebellum. Importantly, while concurrent and poststop signals were significantly correlated during successful cognitive control, concurrent activations during erroneous trials were only correlated with posterror activations in the fronto-parietal network but not cerebellum. Instead, the cerebellar activation during posterror cognitive control was likely to be driven secondarily by posterror activation in the lPFC. Further, a dynamic causal modeling analysis demonstrated that postsuccess cognitive control was associated with inhibitory connectivity from the lPFC to cerebellum, while excitatory connectivity from the lPFC to cerebellum was present during posterror cognitive control. Overall, these findings suggest dissociable but temporally related neural mechanisms underlying concurrent, postsuccess, and posterror cognitive control processes in healthy individuals.

Characteristics of the corpus callosum in chronic schizophrenia treated with clozapine or risperidone and those never-treated.

BACKGROUND: The corpus callosum (CC) deficits have been well documented in chronic schizophrenia. However, the long-term impacts of antipsychotic monotherapies on callosal anatomy remain unclear. This cross-sectional study sought to explore micro- and macro-structural characteristics of the CC in never-treated patients and those with long-term mono-antipsychotic treatment. METHODS: The study included 23 clozapine-treated schizophrenia patients (CT-SCZ), 19 risperidone-treated schizophrenia patients (RT-SCZ), 23 never-treated schizophrenia patients (NT-SCZ), and 35 healthy controls (HCs). High resolution structural images and diffusion tensor imaging (DTI) data for each participant were obtained via a 3.0 T MR scanner. FreeSurfer was used to examine the volumes and fractional anisotropy (FA) values of the CC for each participant. RESULTS: There were significant deficits in the total and sub-regional CC volume and white matter integrity in NT-SCZ in comparison with healthy subjects. Compared with NT-SCZ, both CT-SCZ and RT-SCZ showed significantly increased FA values in the anterior CC region, while only RT-SCZ showed significantly increased volume in the mid-anterior CC region. Moreover, the volume of the mid-anterior CC region was significantly smaller in CT-SCZ compared to HCs. No correlations of clinical symptoms with callosal metrics were observed in schizophrenia patients. CONCLUSIONS: Our findings provide insight into micro- and macro-structural characteristics of the CC in chronic schizophrenia patients with or without antipsychotics. These results suggest that the pathology itself is responsible for cerebral abnormalities in schizophrenia and that chronic exposure to antipsychotics may have an impact on white matter structure of schizophrenia patients, especially in those with risperidone treatment.

Inhibition of cIAP1 as a strategy for targeting c-MYC-driven oncogenic activity.

Protooncogene c-MYC, a master transcription factor, is a major driver of human tumorigenesis. Development of pharmacological agents for inhibiting c-MYC as an anticancer therapy has been a longstanding but elusive goal in the cancer field. E3 ubiquitin ligase cIAP1 has been shown to mediate the activation of c-MYC by destabilizing MAD1, a key antagonist of c-MYC. Here we developed a high-throughput assay for cIAP1 ubiquitination and identified D19, a small-molecule inhibitor of E3 ligase activity of cIAP1. We show that D19 binds to the RING domain of cIAP1 and inhibits the E3 ligase activity of cIAP1 by interfering with the dynamics of its interaction with E2. Blocking cIAP1 with D19 antagonizes c-MYC by stabilizing MAD1 protein in cells. Furthermore, we show that D19 and an improved analog (D19-14) promote c-MYC degradation and inhibit the oncogenic function of c-MYC in cells and xenograft animal models. In contrast, we show that activating E3 ubiquitin ligase activity of cIAP1 by Smac mimetics destabilizes MAD1, the antagonist of MYC, and increases the protein levels of c-MYC. Our study provides an interesting example using chemical biological approaches for determining distinct biological consequences from inhibiting vs. activating an E3 ubiquitin ligase and suggests a potential broad therapeutic strategy for targeting c-MYC in cancer treatment by pharmacologically modulating cIAP1 E3 ligase activity.

Toward Leveraging Human Connectomic Data in Large Consortia: Generalizability of fMRI-Based Brain Graphs Across Sites, Sessions, and Paradigms.

While graph theoretical modeling has dramatically advanced our understanding of complex brain systems, the feasibility of aggregating connectomic data in large imaging consortia remains unclear. Here, using a battery of cognitive, emotional and resting fMRI paradigms, we investigated the generalizability of functional connectomic measures across sites and sessions. Our results revealed overall fair to excellent reliability for a majority of measures during both rest and tasks, in particular for those quantifying connectivity strength, network segregation and network integration. Processing schemes such as node definition and global signal regression (GSR) significantly affected resulting reliability, with higher reliability detected for the Power atlas (vs. AAL atlas) and data without GSR. While network diagnostics for default-mode and sensori-motor systems were consistently reliable independently of paradigm, those for higher-order cognitive systems were reliable predominantly when challenged by task. In addition, based on our present sample and after accounting for observed reliability, satisfactory statistical power can be achieved in multisite research with sample size of approximately 250 when the effect size is moderate or larger. Our findings provide empirical evidence for the generalizability of brain functional graphs in large consortia, and encourage the aggregation of connectomic measures using multisite and multisession data.

Reliability of an fMRI paradigm for emotional processing in a multisite longitudinal study: Clarification and implications for statistical power.

In this commentary, we clarify the meaning of the generalizability-theory-based coefficients reported in our multisite reliability study of fMRI measures of regional brain activation during an emotion processing task (Gee et al., Human Brain Mapping 2015;36:2558-2579). While the original paper reported generalizability and dependability coefficients based on the design of our traveling subjects study (in which each subject was scanned twice at each of eight sites), those coefficients are of limited applicability outside of the reliability study context. Here we report generalizability and dependability coefficients that represent the reliability one can expect for a multisite study, in which a given subject is scanned once on a scanner drawn randomly from the pool of available scanners (i.e., analogous to the more typical multisite study design). We also characterize the implications of a multisite versus single-site study design for statistical power, including Figure 1 that shows sample size requirements to detect activation in two key nodes of the emotion processing circuitry given observed differences in reliability of measurement between single-site and multisite designs.

Reliability of functional magnetic resonance imaging activation during working memory in a multisite study: Clarification and implications for statistical power.

In this technical note, we clarify the meaning of the generalizability-theory based coefficients reported in our multisite reliability study of fMRI measures of regional brain activation during working memory processing (Forsyth et al., Neuroimage 2014;97:51-52). While the original paper reported generalizability and dependability coefficients based on the design of our traveling subjects study (in which each subject was scanned twice at each of eight sites), those coefficients are of limited applicability outside of the reliability study context. Here we report generalizability and dependability coefficients that represent the reliability one can expect for a multisite study in which a given subject is scanned once on a scanner drawn randomly from the pool of available scanners (i.e., analogous to the more typical multisite study design). We also characterize the implications of a multisite versus single site study design for statistical power, including a figure that shows sample size requirements to detect activation in two key nodes of the working memory circuitry given observed differences in reliability of measurement between single and multisite designs.