Spatiotemporal responses to emotional conflict and its psychiatric correlates in adolescents with epilepsy using magnetoencephalography.

People with epilepsy often suffer from comorbid psychiatric disorders, which negatively affects their quality of life. Emotion regulation is an important cognitive process that is impaired in individuals with psychiatric disorders, such as depression. Adults with epilepsy also show difficulties in emotion regulation, particularly during later-stage, higher-order cognitive processing. Yet, the spatiotemporal and frequency correlates of these functional brain deficits in epilepsy remain unknown, as do the nature of these deficits in adolescent epilepsy. Here, we aim to elucidate the spatiotemporal profile of emotional conflict processing in adolescents with epilepsy, relative to controls, using magnetoencephalography (MEG) and relate these findings to anxiety and depression symptom severity assessed with self-report scales. We hypothesized to see blunted brain activity during emotional conflict in adolescents with epilepsy, relative to controls, in the posterior parietal, prefrontal and cingulate cortices due to their role in explicit and implicit regulation around participant response (500-1000 ms). We analyzed MEG recordings from 53 adolescents (28 epilepsy [14focal,14generalized], 25 controls) during an emotional conflict task. We showed that while controls exhibited behavioral interference to emotional conflict, adolescents with epilepsy failed to exhibit this normative response time pattern. Adolescents with epilepsy showed blunted brain responses to emotional conflict in brain regions related to error evaluation and learning around the average response time (500-700 ms), and in regions involved in decision making during post-response monitoring (800-1000 ms). Interestingly, behavioral patterns and psychiatric symptom severity varied between epilepsy subgroups, wherein those with focal epilepsy showed preserved response time interference. Thus, brain responses were regressed with depression and anxiety levels for each epilepsy subgroup separately. Analyses revealed that under activation in error evaluation regions (500-600 ms) predicted anxiety and depression in focal epilepsy, while regions related to learning (600-700 ms) predicted anxiety in generalized epilepsy, suggesting differential mechanisms of dysfunction in these subgroups. Despite similar rates of anxiety and depression across the groups, adolescents with epilepsy still exhibited deficits in emotional conflict processing in brain and behavioral responses. This suggests that these deficits may exist independently from psychopathology and may stem from underlying dysfunctions that predispose these individuals to develop both disorders. Findings such as these may provide potential targets for future research and therapies.

Leveraging expertise and optimizing clinical research: Initial success of a pediatric epilepsy surgery collaborative.

OBJECTIVE: Improve data-driven research to inform clinical decision-making with pediatric epilepsy surgery patients by expanding the Pediatric Epilepsy Research Consortium Epilepsy Surgery (PERC-Surgery) Workgroup to include neuropsychological data. This article reports on the process and initial success of this effort and characterizes the cognitive functioning of the largest multi-site pediatric epilepsy surgery cohort in the United States. METHODS: Pediatric neuropsychologists from 18 institutions completed surveys regarding neuropsychological practice and the impact of involvement in the collaborative. Neuropsychological data were entered through an online database. Descriptive analyses examined the survey responses and cognitive functioning of the cohort. Statistical analyses examined which patients were evaluated and if composite scores differed by domain, demographics, measures used, or epilepsy characteristics. RESULTS: Positive impact of participation was evident by attendance, survey responses, and the neuropsychological data entry of 534 presurgical epilepsy patients. This cohort, ages 6 months to 21 years, were majority White and non-Hispanic, and more likely to have private insurance. Mean intelligence quotient (IQ) scores were below to low average, with weaknesses in working memory and processing speed. Full-scale IQ (FSIQ) was lowest for patients with younger age at seizure onset, daily seizures, and magnetic resonance imaging (MRI) abnormalities. SIGNIFICANCE: We established a collaborative network and fundamental infrastructure to address questions outlined by the Epilepsy Research Benchmarks. There is a wide range in the age and IQ of patients considered for pediatric epilepsy surgery, yet it appears that social determinants of health impact access to care. Consistent with other national cohorts, this US cohort has a downward shift in IQ associated with seizure severity.

Dynamic dentin: A quantitative microscopic assessment of age and spatial changes to matrix architecture, peritubular dentin, and collagens types I and III.

To investigate age and site-related changes to human dentin collagen, sound human teeth collected from donors aged 13-29 (young) and 50-74 (aged) years (n = 9/group) were cut to shallow and deep sites. Dentin collagen orientation and fibril bundling was investigated using the Picrosirius Red (PSR) stain observed under cross-polarized light microscopy (Pol), and collagen distribution was investigated using Confocal Laser Scanning Microscopy (CLSM). Collagen types III to I distribution in peritubular dentin (PTD) was revealed using Herovici stain and brightfield microscopy. Image analysis software and linear mixed modelling quantified outcomes. In situ dentin collagen was observed using Xenon Plasma Focussed Ion Beam Scanning Electron Microscopy (Xe PFIB-SEM). The PSR-Pol analysis revealed less coherently aligned and more bundled collagen fibrils in aged dentin (P = 0.005). Deep inner dentin collagen in both groups were less coherently aligned with reduced bundling. Regardless of age, CLSM showed collagen distribution remained stable; and more collagen type III was detectable in PTD located in inner dentin (Young: P = 0.006; Aged: P = 0.008). Observations following Xe PFIB-SEM cross-sectioning showed apatite-like deposits surrounding large intratubular collagen fibers, and evidence of smaller intertubular dentin collagen fibrils in situ. In conclusion, aging changes collagen network architecture, but not distribution or content.

Exploration of baseline and early changes in neurocognitive characteristics as predictors of treatment response to bupropion, sertraline, and placebo in the EMBARC clinical trial.

BACKGROUND: Treatment for major depressive disorder (MDD) is imprecise and often involves trial-and-error to determine the most effective approach. To facilitate optimal treatment selection and inform timely adjustment, the current study investigated whether neurocognitive variables could predict an antidepressant response in a treatment-specific manner. METHODS: In the two-stage Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care (EMBARC) trial, outpatients with non-psychotic recurrent MDD were first randomized to an 8-week course of sertraline selective serotonin reuptake inhibitor or placebo. Behavioral measures of reward responsiveness, cognitive control, verbal fluency, psychomotor, and cognitive processing speeds were collected at baseline and week 1. Treatment responders then continued on another 8-week course of the same medication, whereas non-responders to sertraline or placebo were crossed-over under double-blinded conditions to bupropion noradrenaline/dopamine reuptake inhibitor or sertraline, respectively. Hamilton Rating for Depression scores were also assessed at baseline, weeks 8, and 16. RESULTS: Greater improvements in psychomotor and cognitive processing speeds within the first week, as well as better pretreatment performance in these domains, were specifically associated with higher likelihood of response to placebo. Moreover, better reward responsiveness, poorer cognitive control and greater verbal fluency were associated with greater likelihood of response to bupropion in patients who previously failed to respond to sertraline. CONCLUSION: These exploratory results warrant further scrutiny, but demonstrate that quick and non-invasive behavioral tests may have substantial clinical value in predicting antidepressant treatment response.

Effect of dentine site on resin and cement adaptation tested using X-ray and electron microscopy to evaluate bond durability and adhesive interfaces.

Glass ionomer (GI) cements and self-etch (SE) or universal adhesives after etching (ER) adapt variably with dentine. Dentine characteristics vary with depth (deep/shallow), location (central/peripheral), and microscopic site (intertubular/peritubular). To directly compare adhesion to dentine, non-destructive imaging and testing are required. Here, GI, ER, and SE adapted at different dentine depths, locations, and sites were investigated using micro-CT, xenon plasma focused ion beam scanning electron microscopy (Xe PFIB-SEM), and energy dispersive X-ray spectroscopy (EDS). Extracted molars were prepared to deep or shallow slices and treated with the three adhesives. Micro-CT was used to compare changes to air volume gaps, following thermocycling, and statistically analysed using a quantile regression model and Fisher's exact test. The three adhesives performed similarly across dentine depths and locations, yet no change or overall increases and decreases in gaps at all dentine depths and locations were measured. The Xe PFIB-SEM-milled dentine-adhesive interfaces facilitated high-resolution characterization, and element profiling revealed variations across the tooth-material interfaces. Dentine depth and location had no impact on adhesive durability, although microscopic differences were observed. Here we demonstrate how micro-CT and Xe PFIB-SEM can be used to compare variable dental materials without complex multi-stage specimen preparation to minimize artefacts.

Eukaryote-Conserved Methylarginine Is Absent in Diplomonads and Functionally Compensated in Giardia.

Methylation is a common posttranslational modification of arginine and lysine in eukaryotic proteins. Methylproteomes are best characterized for higher eukaryotes, where they are functionally expanded and evolved complex regulation. However, this is not the case for protist species evolved from the earliest eukaryotic lineages. Here, we integrated bioinformatic, proteomic, and drug-screening data sets to comprehensively explore the methylproteome of Giardia duodenalis-a deeply branching parasitic protist. We demonstrate that Giardia and related diplomonads lack arginine-methyltransferases and have remodeled conserved RGG/RG motifs targeted by these enzymes. We also provide experimental evidence for methylarginine absence in proteomes of Giardia but readily detect methyllysine. We bioinformatically infer 11 lysine-methyltransferases in Giardia, including highly diverged Su(var)3-9, Enhancer-of-zeste and Trithorax proteins with reduced domain architectures, and novel annotations demonstrating conserved methyllysine regulation of eukaryotic elongation factor 1 alpha. Using mass spectrometry, we identify more than 200 methyllysine sites in Giardia, including in species-specific gene families involved in cytoskeletal regulation, enriched in coiled-coil features. Finally, we use known methylation inhibitors to show that methylation plays key roles in replication and cyst formation in this parasite. This study highlights reduced methylation enzymes, sites, and functions early in eukaryote evolution, including absent methylarginine networks in the Diplomonadida. These results challenge the view that arginine methylation is eukaryote conserved and demonstrate that functional compensation of methylarginine was possible preceding expansion and diversification of these key networks in higher eukaryotes.

Discovery and replication of cerebral blood flow differences in major depressive disorder.

Major depressive disorder (MDD) is a serious, heterogeneous disorder accompanied by brain-related changes, many of which are still to be discovered or refined. Arterial spin labeling (ASL) is a neuroimaging technique used to measure cerebral blood flow (CBF; perfusion) to understand brain function and detect differences among groups. CBF differences have been detected in MDD, and may reveal biosignatures of disease-state. The current work aimed to discover and replicate differences in CBF between MDD participants and healthy controls (HC) as part of the EMBARC study. Participants underwent neuroimaging at baseline, prior to starting study medication, to investigate biosignatures in MDD. Relative CBF (rCBF) was calculated and compared between 106 MDD and 36 HC EMBARC participants (whole-brain Discovery); and 58 MDD EMBARC participants and 58 HC from the DLBS study (region-of-interest Replication). Both analyses revealed reduced rCBF in the right parahippocampus, thalamus, fusiform and middle temporal gyri, as well as the left and right insula, for those with MDD relative to HC. Both samples also revealed increased rCBF in MDD relative to HC in both the left and right inferior parietal lobule, including the supramarginal and angular gyri. Cingulate and prefrontal regions did not fully replicate. Lastly, significant associations were detected between rCBF in replicated regions and clinical measures of MDD chronicity. These results (1) provide reliable evidence for ASL in detecting differences in perfusion for multiple brain regions thought to be important in MDD, and (2) highlight the potential role of using perfusion as a biosignature of MDD.

Reward related ventral striatal activity and differential response to sertraline versus placebo in depressed individuals.

Medications to treat major depressive disorder (MDD) are not equally effective across patients. Given that neural response to rewards is altered in MDD and given that reward-related circuitry is modulated by dopamine and serotonin, we examined, for the first time, whether reward-related neural activity moderated response to sertraline, an antidepressant medication that targets these neurotransmitters. A total of 222 unmedicated adults with MDD randomized to receive sertraline (n = 110) or placebo (n = 112) in the Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study completed demographic and clinical assessments, and pretreatment functional magnetic resonance imaging while performing a reward task. We tested whether an index of reward system function in the ventral striatum (VS), a key reward circuitry region, moderated differential response to sertraline versus placebo, assessed with the Hamilton Rating Scale for Depression (HSRD) over 8 weeks. We observed a significant moderation effect of the reward index, reflecting the temporal dynamics of VS activity, on week-8 depression levels (Fs ≥ 9.67, ps ≤ 0.002). Specifically, VS responses that were abnormal with respect to predictions from reinforcement learning theory were associated with lower week-8 depression symptoms in the sertraline versus placebo arms. Thus, a more abnormal pattern of pretreatment VS dynamic response to reward expectancy (expected outcome value) and prediction error (difference between expected and actual outcome), likely reflecting serotonergic and dopaminergic deficits, was associated with better response to sertraline than placebo. Pretreatment measures of reward-related VS activity may serve as objective neural markers to advance efforts to personalize interventions by guiding individual-level choice of antidepressant treatment.

Positive and negative valence systems in major depression have distinct clinical features, response to antidepressants, and relationships with immunomarkers.

BACKGROUND: Heterogeneity in major depressive disorder (MDD) is well recognized but not well understood. Core depressive features are reward and emotional symptoms, which reflect dysfunctions in the positive valence (PV) and negative valence (NV) systems, respectively. This study assessed whether PV and NV systems (based on selected symptoms) were associated with different clinical features, antidepressant response, and levels of immunomarkers in adults with MDD. METHODS: These analyses used data from combining medications to enhance depression outcomes study (N = 665; n = 166 for immunomarkers). PV and NV symptom scores were extracted from the clinician-rated 30-item Inventory of Depressive Symptomatology. Correlational analyses were conducted. RESULTS: PV and NV symptom scores were substantially associated with different clinical features. PV symptoms (impaired motivation, impaired energy, and anhedonia) were independently associated with female gender (p < .001), older age (p = .012), and higher cognitive and physical impairment (p < .001) according to the 7-item Cognitive and Physical Functioning Questionnaire. Conversely, NV symptoms (anxiety and interpersonal sensitivity) were independently associated with younger age (p = .013), more anxious comorbidities (p = .001 for generalized anxiety disorder and p = .002 for social phobia) and other commonly associated noncriterion symptoms (p < .001). Overall, PV symptoms were more responsive to antidepressants than NV symptoms (p < .0001; Cohen's d = .455). A PV symptom score was positively correlated with the concentration of three proinflammatory and one anti-inflammatory factor. In contrast, an NV symptom score was negatively associated with only one proinflammatory immunomarker. CONCLUSIONS: PV and NV system functions appear to be reflected in selected clinical symptoms that differentially relate to other clinical features, treatment outcomes, and immunological function.

Personalized prediction of antidepressant v. placebo response: evidence from the EMBARC study.

BACKGROUND: Major depressive disorder (MDD) is a highly heterogeneous condition in terms of symptom presentation and, likely, underlying pathophysiology. Accordingly, it is possible that only certain individuals with MDD are well-suited to antidepressants. A potentially fruitful approach to parsing this heterogeneity is to focus on promising endophenotypes of depression, such as neuroticism, anhedonia, and cognitive control deficits. METHODS: Within an 8-week multisite trial of sertraline v. placebo for depressed adults (n = 216), we examined whether the combination of machine learning with a Personalized Advantage Index (PAI) can generate individualized treatment recommendations on the basis of endophenotype profiles coupled with clinical and demographic characteristics. RESULTS: Five pre-treatment variables moderated treatment response. Higher depression severity and neuroticism, older age, less impairment in cognitive control, and being employed were each associated with better outcomes to sertraline than placebo. Across 1000 iterations of a 10-fold cross-validation, the PAI model predicted that 31% of the sample would exhibit a clinically meaningful advantage [post-treatment Hamilton Rating Scale for Depression (HRSD) difference ⩾3] with sertraline relative to placebo. Although there were no overall outcome differences between treatment groups (d = 0.15), those identified as optimally suited to sertraline at pre-treatment had better week 8 HRSD scores if randomized to sertraline (10.7) than placebo (14.7) (d = 0.58). CONCLUSIONS: A subset of MDD patients optimally suited to sertraline can be identified on the basis of pre-treatment characteristics. This model must be tested prospectively before it can be used to inform treatment selection. However, findings demonstrate the potential to improve individual outcomes through algorithm-guided treatment recommendations.

Harmonization of cortical thickness measurements across scanners and sites.

With the proliferation of multi-site neuroimaging studies, there is a greater need for handling non-biological variance introduced by differences in MRI scanners and acquisition protocols. Such unwanted sources of variation, which we refer to as "scanner effects", can hinder the detection of imaging features associated with clinical covariates of interest and cause spurious findings. In this paper, we investigate scanner effects in two large multi-site studies on cortical thickness measurements across a total of 11 scanners. We propose a set of tools for visualizing and identifying scanner effects that are generalizable to other modalities. We then propose to use ComBat, a technique adopted from the genomics literature and recently applied to diffusion tensor imaging data, to combine and harmonize cortical thickness values across scanners. We show that ComBat removes unwanted sources of scan variability while simultaneously increasing the power and reproducibility of subsequent statistical analyses. We also show that ComBat is useful for combining imaging data with the goal of studying life-span trajectories in the brain.

Development and evaluation of a multimodal marker of major depressive disorder.

This study aimed to identify biomarkers of major depressive disorder (MDD), by relating neuroimage-derived measures to binary (MDD/control), ordinal (severe MDD/mild MDD/control), or continuous (depression severity) outcomes. To address MDD heterogeneity, factors (severity of psychic depression, motivation, anxiety, psychosis, and sleep disturbance) were also used as outcomes. A multisite, multimodal imaging (diffusion MRI [dMRI] and structural MRI [sMRI]) cohort (52 controls and 147 MDD patients) and several modeling techniques-penalized logistic regression, random forest, and support vector machine (SVM)-were used. An additional cohort (25 controls and 83 MDD patients) was used for validation. The optimally performing classifier (SVM) had a 26.0% misclassification rate (binary), 52.2 ± 1.69% accuracy (ordinal) and r = .36 correlation coefficient (p < .001, continuous). Using SVM, R2 values for prediction of any MDD factors were <10%. Binary classification in the external data set resulted in 87.95% sensitivity and 32.00% specificity. Though observed classification rates are too low for clinical utility, four image-based features contributed to accuracy across all models and analyses-two dMRI-based measures (average fractional anisotropy in the right cuneus and left insula) and two sMRI-based measures (asymmetry in the volume of the pars triangularis and the cerebellum) and may serve as a priori regions for future analyses. The poor accuracy of classification and predictive results found here reflects current equivocal findings and sheds light on challenges of using these modalities for MDD biomarker identification. Further, this study suggests a paradigm (e.g., multiple classifier evaluation with external validation) for future studies to avoid nongeneralizable results.

A Novel Strategy to Identify Placebo Responders: Prediction Index of Clinical and Biological Markers in the EMBARC Trial.

BACKGROUND: One in three clinical trial patients with major depressive disorder report symptomatic improvement with placebo. Strategies to mitigate the effect of placebo responses have focused on modifying study design with variable success. Identifying and excluding or controlling for individuals with a high likelihood of responding to placebo may improve clinical trial efficiency and avoid unnecessary medication trials. METHODS: Participants included those assigned to the placebo arm (n = 141) of the Establishing Moderators and Biosignatures for Antidepressant Response in Clinical Care (EMBARC) trial. The elastic net was used to evaluate 283 baseline clinical, behavioral, imaging, and electrophysiological variables to identify the most robust yet parsimonious features that predicted depression severity at the end of the double-blind 8-week trial. Variables retained in at least 50% of the 100 imputed data sets were used in a Bayesian multiple linear regression model to simultaneously predict the probabilities of response and remission. RESULTS: Lower baseline depression severity, younger age, absence of melancholic features or history of physical abuse, less anxious arousal, less anhedonia, less neuroticism, and higher average theta current density in the rostral anterior cingulate predicted a higher likelihood of improvement with placebo. The Bayesian model predicted remission and response with an actionable degree of accuracy (both AUC > 0.73). An interactive calculator was developed predicting the likelihood of placebo response at the individual level. CONCLUSION: Easy-to-measure clinical, behavioral, and electrophysiological assessments can be used to identify placebo responders with a high degree of accuracy. Development of this calculator based on these findings can be used to identify potential placebo responders.

Cortical thickness is not associated with current depression in a clinical treatment study.

BACKGROUND: Reduced cortical thickness is a candidate biological marker of depression, although findings are inconsistent. This could reflect analytic heterogeneity, such as use of region-wise cortical thickness based on the Freesurfer Desikan-Killiany (DK) atlas or surface-based morphometry (SBM). The Freesurfer Destrieux (DS) atlas (more, smaller regions) has not been utilized in depression studies. This could also reflect differential gender and age effects. METHODS: Cortical thickness was collected from 170 currently depressed adults and 52 never-depressed adults. Visually inspected and approved Freesurfer-generated surfaces were used to extract cortical thickness estimates according to the DK atlas (68 regions) and DS atlas (148 regions) for region-wise analysis (216 total regions) and for SBM. RESULTS: Overall, except for small effects in a few regions, the two region-wise approaches generally failed to discriminate depressed adults from nondepressed adults or current episode severity. Differential effects by age and gender were also rare and small in magnitude. Using SBM, depressed adults showed a significantly thicker cluster in the left supramarginal gyrus than nondepressed adults (P = 0.047) but there were no associations with current episode severity. CONCLUSIONS: Three analytic approaches (i.e., DK atlas, DS atlas, and SBM) converge on the notion that cortical thickness is a relatively weak discriminator of current depression status. Differential age and gender effects do not appear to represent key moderators. Robust associations with demographic factors will likely hinder translation of cortical thickness into a clinically useful biomarker. Hum Brain Mapp, 2017. © 2017 Wiley Periodicals, Inc. Hum Brain Mapp 38:4370-4385, 2017. © 2017 Wiley Periodicals, Inc.

A COMPREHENSIVE EXAMINATION OF WHITE MATTER TRACTS AND CONNECTOMETRY IN MAJOR DEPRESSIVE DISORDER.

BACKGROUND: Major depressive disorder (MDD) is a debilitating disorder characterized by widespread brain abnormalities. The literature is mixed as to whether or not white matter abnormalities are associated with MDD. This study sought to examine fractional anisotropy (FA) in white matter tracts in individuals with MDD using diffusion tensor imaging (DTI). METHODS: 139 participants with MDD and 39 healthy controls (HC) in a multisite study were included. DTI scans were acquired in 64 directions and FA was determined in the brain using four methods: region of interest (ROI), tract-based spatial statistics (TBSS), and diffusion tractography. Diffusion connectometry was used to identify white matter pathways associated with MDD. RESULTS: There were no significant differences when comparing FA in MDD and HC groups using any method. In the MDD group, there was a significant relationship between depression severity and FA in the right medial orbitofrontal cortex, and between age of onset of MDD and FA in the right caudal anterior cingulate cortex using the ROI method. There was a significant relationship between age of onset and connectivity in the thalamocortical radiation, inferior longitudinal fasciculus, and cerebellar tracts using diffusion connectometry. CONCLUSIONS: The lack of group differences in FA and connectometry analysis may result from the clinically heterogenous nature of MDD. However, the relationship between FA and depression severity may suggest a state biomarker of depression that should be investigated as a potential indicator of response. Age of onset may also be a significant clinical feature to pursue when studying white matter tracts.

Test-retest reliability of freesurfer measurements within and between sites: Effects of visual approval process.

In the last decade, many studies have used automated processes to analyze magnetic resonance imaging (MRI) data such as cortical thickness, which is one indicator of neuronal health. Due to the convenience of image processing software (e.g., FreeSurfer), standard practice is to rely on automated results without performing visual inspection of intermediate processing. In this work, structural MRIs of 40 healthy controls who were scanned twice were used to determine the test-retest reliability of FreeSurfer-derived cortical measures in four groups of subjects-those 25 that passed visual inspection (approved), those 15 that failed visual inspection (disapproved), a combined group, and a subset of 10 subjects (Travel) whose test and retest scans occurred at different sites. Test-retest correlation (TRC), intraclass correlation coefficient (ICC), and percent difference (PD) were used to measure the reliability in the Destrieux and Desikan-Killiany (DK) atlases. In the approved subjects, reliability of cortical thickness/surface area/volume (DK atlas only) were: TRC (0.82/0.88/0.88), ICC (0.81/0.87/0.88), PD (0.86/1.19/1.39), which represent a significant improvement over these measures when disapproved subjects are included. Travel subjects' results show that cortical thickness reliability is more sensitive to site differences than the cortical surface area and volume. To determine the effect of visual inspection on sample size required for studies of MRI-derived cortical thickness, the number of subjects required to show group differences was calculated. Significant differences observed across imaging sites, between visually approved/disapproved subjects, and across regions with different sizes suggest that these measures should be used with caution.

A Flatworm from the Genus Waminoa (Acoela: Convolutidae) Associated with Bleached Corals in Western Australia.

A flatworm isolated from bleached colonies of the coral Coscinaraea marshae at Rottnest Island, Western Australia, is described using a combination of morphological and molecular systematics. This flatworm shares morphological features characteristic of the genus Waminoa (Acoelomorpha: Acoela), including the presence of two algal symbionts, but appears to have genital regions different from those of other described species of Waminoa. The design of new oligonucleotide primers enabled the amplification of partial 18S rDNA of the Rottnest Island acoel specimens, and phylogenetic analysis positioned them within Waminoa, confirming their placement in the genus. Furthermore, Waminoa specimens from Rottnest Island grouped into a sister clade to Waminoa brickneri, indicating that the morphological and genetic differences observed are most likely intraspecific and due to geographic variation. As such, we name these Rottnest Island specimens W. cf. brickneri, but highlight that key differences warrant further exploration before assignment to this species can be confirmed. This is the first acoel flatworm described from Western Australia and contributes to our understanding of the diversity and evolutionary relationship of the Acoela.

Memory impairment exhibited by veterans with Gulf War Illness.

Roughly 26-32% of US veterans, who served in the first Gulf War, report suffering from chronic health problems ( Golomb, 2008 , Proceedings of the National Academies of Science, 105, 4295). The present study investigated the memory deficits reported by these ill Gulf War veterans (GWV) using a face-name associative memory paradigm administered during functional magnetic resonance imaging (fMRI). The fMRI data confirmed memory performance on the memory task to be related to the amount of activation in the left hippocampus observed during the study. In addition, ill-GWV demonstrated decreased memory performance relative to unaffected GWV on this memory test, providing evidence of memory deficits using an objective measure of memory.

Investigating parasites in three dimensions: trends in volume microscopy.

To best understand parasite, host, and vector morphologies, host-parasite interactions, and to develop new drug and vaccine targets, structural data should, ideally, be obtained and visualised in three dimensions (3D). Recently, there has been a significant uptake of available 3D volume microscopy techniques that allow collection of data across centimetre (cm) to Angstrom (Å) scales by utilising light, X-ray, electron, and ion sources. Here, we present and discuss microscopy tools available for the collection of 3D structural data, focussing on electron microscopy-based techniques. We highlight their strengths and limitations, such that parasitologists can identify techniques best suited to answer their research questions. Additionally, we review the importance of volume microscopy to the advancement of the field of parasitology.

Reward Behavior Disengagement, a Neuroeconomic Model-Based Objective Measure of Reward Pathology in Depression: Findings from the EMBARC Trial.

The probabilistic reward task (PRT) has identified reward learning impairments in those with major depressive disorder (MDD), as well as anhedonia-specific reward learning impairments. However, attempts to validate the anhedonia-specific impairments have produced inconsistent findings. Thus, we seek to determine whether the Reward Behavior Disengagement (RBD), our proposed economic augmentation of PRT, differs between MDD participants and controls, and whether there is a level at which RBD is high enough for depressed participants to be considered objectively disengaged. Data were gathered as part of the Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study, a double-blind, placebo-controlled clinical trial of antidepressant response. Participants included 195 individuals with moderate to severe MDD (Quick Inventory of Depressive Symptomatology (QIDS-SR) score ≥ 15), not in treatment for depression, and with complete PRT data. Healthy controls (n = 40) had no history of psychiatric illness, a QIDS-SR score < 8, and complete PRT data. Participants with MDD were treated with sertraline or placebo for 8 weeks (stage I of the EMBARC trial). RBD was applied to PRT data using discriminant analysis, and classified MDD participants as reward task engaged (n = 137) or reward task disengaged (n = 58), relative to controls. Reward task engaged/disengaged groups were compared on sociodemographic features, reward-behavior, and sertraline/placebo response (Hamilton Depression Rating Scale scores). Reward task disengaged MDD participants responded only to sertraline, whereas those who were reward task engaged responded to sertraline and placebo (F(1293) = 4.33, p = 0.038). Reward task engaged/disengaged groups did not differ otherwise. RBD was predictive of reward impairment in depressed patients and may have clinical utility in identifying patients who will benefit from antidepressants.