Estradiol effects on an emotional interference task in adolescents with current and remitted depression.

Attentional biases to emotional stimuli are thought to reflect vulnerability for mood disorder onset and maintenance. This study examined the association between the endogenous sex hormone estradiol and emotional attentional biases in adolescent females with either current or remitted depression. Three groups of participants (mean age ± SD) completed the Emotional Interrupt Task: 1) 20 adolescent females (15.1 ± 1.83 years) currently diagnosed with Major Depressive Disorder (MDD), 2) 16 adolescent females (16.4 ± 1.31 years) who had experienced at least one episode of MDD in their lifetime but currently met criteria for MDD in remission, and 3) 30 adolescent female (15.4 ± 1.83 years) healthy controls. Attentional interference (AI) scores were calculated as differences in target response reaction time between trials with emotional facial expressions versus neutral facial expressions. Estradiol levels were assayed by Salimetrics LLC using saliva samples collected within 30 min of waking on assessment days. Robust multiple regression with product terms evaluated estradiol's main effect on AI scores, as well as hypothesized estradiol × diagnostic group interactions. Although neither mean estradiol levels nor mean AI scores in the current-MDD and remitted-MDD groups differed from controls, the relationship between estradiol and overall AI score differed between control adolescents and the remitted-MDD group. Specifically, the remitted-MDD adolescents performed worse (i.e., showed greater attentional interference) when they had higher estradiol; no significant relationship existed in the current-MDD group. Because this finding was driven by angry and not happy stimuli, it appears higher estradiol levels were associated with greater susceptibility to the attention-capturing effects of negatively-valenced emotional content in girls at risk for MDD from prior history.

Diblock bottlebrush polymer in a non-polar medium: Self-assembly, surface forces, and superlubricity.

Whilst bottlebrush polymers have been studied in aqueous media for their conjectured role in biolubrication, surface forces and friction mediated by bottlebrush polymers in non-polar media have not been previously reported. Here, small-angle neutron scattering (SANS) showed that a diblock bottlebrush copolymer (oligoethyleneglycol acrylate/ethylhexyl acrylate; OEGA/EHA) formed spherical core-shell aggregates in n-dodecane (a model oil) in the polymer concentration range 0.1-2.0 wt%, with a radius of gyration Rg âˆ¼ 7 nm, comprising 40-65 polymer molecules per aggregate. The surface force apparatus (SFA) measurements revealed purely repulsive forces between surfaces bearing inhomogeneous polymer layers of thickness L âˆ¼ 13-23 nm, attributed to adsorption of a mixture of polymer chains and surface-deformed micelles. Despite the surface inhomogeneity, the polymer layers could mediate effective lubrication, demonstrating superlubricity with the friction coefficient as low as µ ∼ 0.003. The analysis of velocity-dependence of friction using the Eyring model shed light on the mechanism of the frictional process. That is, the friction mediation was consistent with the presence of nanoscopic surface aggregates, with possible contributions from a gel-like network formed by the polymer chains on the surface. These unprecedented results, correlating self-assembled polymer micelle structure with the surface forces and friction the polymer layers mediate, highlight the potential of polymers with the diblock bottlebrush architecture widespread in biological living systems, in tailoring desired surface interactions in non-polar media.

Evaluating Indices for Non-invasive Myocardial Recovery Assessment in LVAD-Supported Heart Failure Patients.

Accurate assessment of myocardial recovery (MR) under left ventricular assist device (LVAD) support is essential for clinicians to manage heart failure patients. However, current techniques for assessing MR are time-consuming, invasive, and infrequent. Measuring MR using indices derived from LVAD operating data instead provides a potential real-time alternative. Several of these indices for assessing the MR of LVAD-supported heart failure patients were collated from the literature and subject to a comprehensive comparative analysis. The objective of this analysis was to determine the most accurate index for assessing systolic cardiac function under LVAD-support, characterized by maximal end-systolic elastance (Emax), while remaining insensitive to preload & afterload. The indices were compared in computational simulation, utilizing an LVAD + cardiovascular system model to sweep through a large array of Emax and resistance conditions. Results demonstrated the index that correlated best with Emax, showing the highest accuracy, was the ratio between maximum flow acceleration and flow pulsatility (average R2 =0.9790). The same index also exhibited the lowest % variation (sensitivity) to preload & afterload (1.32% & 13.53% respectively). However, opportunities for improvement remain among current recovery assessment indices, with this study providing a baseline of performance for potential future indices to improve upon.Clinical relevance- This study presents a potential real-time measure of native cardiac function in LVAD-supported heart failure patients to support patient management and further recovery.

Age-related, multivariate associations between white matter microstructure and behavioral performance in three executive function domains.

The executive function (EF) domains of working memory (WM), response inhibition (RI), and set shifting (SS) show maturational gains and are linked to neuroimaging-measured brain changes. This study explored ways in which maturation-linked differences in EF abilities are systematically associated with white matter microstructural differences from adolescence into young adulthood. Diffusion tensor imaging (DTI) and nine neurocognitive tests were collected from 120 healthy subjects ages 12-24. Analyses across the white matter skeleton were performed, focusing on fractional anisotropy (FA). Data were 'fused' using a multivariate technique (CCA+jICA), producing four independent components (ICs) depicting white matter FA values that covaried with test performance. Correlations between age and IC loading coefficients identified three EF-DTI profiles that may change developmentally. In one, SS performance was linked to greater reliance on the FA of ventral brain tracts, and less on dorsal tracts with age. In another, white matter microstructure was related to a pattern of strong WM and weak SS that became more pronounced with age. A final IC revealed that younger individuals with low RI and high WM/SS skills typically matured out of this cognitive imbalance, underscored by white matter changes with age. These novel multivariate results begin to emphasize the complexity of brain structure-cognition relationships in adolescents and young adults.

Estimation of Left Ventricular Stroke Work for Rotary Left Ventricular Assist Devices.

Continuous monitoring of left ventricular stroke work (LVSW) may improve the medical management of patients with rotary left ventricular assist devices (LVAD). However, implantable pressure-volume sensors are limited by measurement drift and hemocompatibility. Instead, estimator algorithms derived from rotary LVAD signals may be a suitable alternative. An LVSW estimator algorithm was developed and evaluated in a range of in vitro and ex vivo cardiovascular conditions during full assist (closed aortic valve [AoV]) and partial assist (opening AoV) mode. For full assist, the LVSW estimator algorithm was based on LVAD flow, speed, and pump pressure head, whereas for partial assist, the LVSW estimator combined the full assist algorithm with an estimate of AoV flow. During full assist, the LVSW estimator demonstrated a good fit in vitro and ex vivo (R 2 : 0.97 and 0.86, respectively) with errors of ± 0.07 J. However, LVSW estimator performance was reduced during partial assist, with in vitro : R 2 : 0.88 and an error of ± 0.16 J and ex vivo : R 2 : 0.48 with errors of ± 0.11 J. Further investigations are required to improve the LVSW estimate with partial assist; however, this study demonstrated promising results for a continuous estimate of LVSW for rotary LVADs.

Changes in neural activity following a randomized trial of cognitive behavioral therapy for hoarding disorder.

OBJECTIVE: Cognitive behavioral therapy (CBT) is efficacious for hoarding disorder (HD), though results are modest. HD patients show an increase in activity in the dorsal anterior cingulate cortex (dACC) when making decisions. The aim of this study is to determine whether CBT's benefits follow improvements in dACC dysfunction or abnormalities previously identified in other brain regions. METHOD: In this randomized clinical trial of 64 treatment-seeking HD patients, patients received group CBT, delivered weekly for 16 weeks, versus wait list. Functional magnetic resonance imaging was used to examine neural activity during simulated decisions about whether to acquire and discard objects. RESULTS: During acquiring decisions, activity decreased in several regions, including right dorsolateral prefrontal, right anterior intraparietal area, both right and left medial intraparietal areas, left and right amygdala, and left accumbens. During discarding decisions, activity decreased in right and left dorsolateral prefrontal, right and left rostral cingulate, left anterior ventral insular cortex, and right medial intraparietal areas. None of the a priori brain parcels of interest significantly mediated symptom reduction. Moderation effects were found for left rostral cingulate, right and left caudal cingulate, and left medial intraparietal parcels. CONCLUSIONS: Therapeutic benefits of CBT for HD do not appear to be mediated by changes in dACC activation. However, pretreatment dACC activation predicts outcome. Findings suggest the need to re-evaluate emerging neurobiological models of HD and our understanding of how CBT affects the brain in HD, and perhaps shift focuses to new neural target discovery and target engagement trials. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Subsequent cancers within 5 years from initial diagnosis of childhood cancer. Patterns and risks in the population of Great Britain.

BACKGROUND: Patterns and risks of subsequent primary tumours (SPTs) among long-term survivors of childhood cancer have been extensively described, but much less is known about early SPTs (ESPTs) occurring within 5 years after initial diagnosis. PROCEDURE: We carried out a population-based study of ESPTs following childhood cancer throughout Britain, using the National Registry of Childhood Tumours. The full study series comprised all ESPTs occurring among 56,620 children whose initial cancer diagnosis was in the period 1971-2010. Frequencies of ESPT were calculated for the entire cohort. For analyses of risk, follow-up began 92 days after initial diagnosis. RESULTS: ESPT developed in 0.4% of children overall, 0.52% of those initially diagnosed at age less than 1 year and 0.38% of those diagnosed at age 1-14 years. Standardised incidence ratio (SIR) was 7.7 (95% confidence interval [CI]: 6.7-8.9), overall 9.5 (95% CI: 7.1-12.5) for children initially diagnosed in 1981-1990 and 6.5-7.5 for those from earlier and later decades. SIR by type of first cancer ranged from 4.4 (95% CI: 1.8-9.1) for Wilms tumour to 13.1 (95% CI: 7.7-21.0) for non-Hodgkin lymphoma. SIR by type of ESPT ranged from 2.0 (95% CI: 1.0-3.4) for acute lymphoblastic leukaemia to 66.6 (95% CI: 52.3-83.6) for acute myeloid leukaemia. Predisposition syndromes were known to be implicated in 21% of children with ESPT and suspected in another 5%. CONCLUSIONS: This study provides an overview of the patterns and risks of ESPTs in a large population where many children received therapy that is still in widespread use. Further research will be needed to monitor and understand changes in risk as childhood cancer treatment continues to evolve.

An Unobtrusive Human Activity Recognition System Using Low Resolution Thermal Sensors, Machine and Deep Learning.

Given the aging population, healthcare systems need to be established to deal with health issues such as injurious falls. Wearable devices can be used to detect falls. However, most wearable devices are obtrusive, and patients generally do not like or may forget to wear them. In this study, we developed an unobtrusive monitoring system using infrared technology to unobtrusively detect locations and recognize human activities such as sitting, standing, walking, lying, and falling. We prototyped a system consisting of two 24×32 thermal array sensors and collected data from healthy young volunteers performing ten different scenarios. A supervised deep learning (DL)-based approach classified activities and detected locations from images. The performance of the DL approach was also compared with the machine learning (ML)-based methods. In addition, we fused the data of two sensors and formed a stereo system, which resulted in better performance compared to a single sensor. Furthermore, to detect critical activities such as falling and lying on floor, we performed a binary classification in which one class was falling plus lying on floor and another class was all the remaining activities. Using the DL-based algorithm on the stereo dataset to recognize activities, overall average accuracy and F1-score were achieved as 97.6%, and 0.935, respectively. These scores for location detection were 97.3%, and 0.927, respectively. These scores for binary classification were 97.9%, and 0.945, respectively. Our results suggest the proposed system recognized human activities, detected locations, and detected critical activities namely falling and lying on floor accurately.

Food cue reactivity in successful laparoscopic gastric banding: A sham-deflation-controlled pilot study.

Laparoscopic adjustable gastric banding (LAGB) offers a unique opportunity to examine the underlying neuronal mechanisms of surgically assisted weight loss due to its instant, non-invasive, adjustable nature. Six participants with stable excess weight loss (%EWL ≥ 45) completed 2 days of fMRI scanning 1.5-5 years after LAGB surgery. In a within-subject randomized sham-controlled design, participants underwent (sham) removal of ∼ 50% of the band's fluid. Compared to sham-deflation (i.e., normal band constriction) of the band, in the deflation condition (i.e., decreasing restriction) participants showed significantly lower activation in the anterior (para)cingulate, angular gyrus, lateral occipital cortex, and frontal cortex in response to food images (p < 0.05, whole brain TFCE-based FWE corrected). Higher activation in the deflation condition was seen in the fusiform gyrus, inferior temporal gyrus, lingual gyrus, lateral occipital cortex. The findings of this within-subject randomized controlled pilot study suggest that constriction of the stomach through LAGB may indirectly alter brain activation in response to food cues. These neuronal changes may underlie changes in food craving and food preference that support sustained post-surgical weight-loss. Despite the small sample size, this is in agreement with and adds to the growing literature of post-bariatric surgery changes in behavior and control regions.

Structural language impairment in Autism Spectrum Disorder versus Loss of Autism Diagnosis: Behavioral and neural characteristics.

This study probed for structural language impairment using behavioral and functional neuroimaging methods in individuals with Autism Spectrum Disorder (ASD) and those diagnosed with ASD in childhood who no longer meet criteria for ASD, referred to as Loss of Autism Diagnosis (LAD1). Participants were drawn from Fein et al. (2013): ASD (n = 35), LAD (n = 31), and Neurotypical (NT; n = 34). Criteria for structural language impairment were: Scores ≤ 82 on Clinical Evaluation of Language Fundamentals-4 (CELF) Core Language, an omnibus measure of language; and scores ≤ 7 on CELF Recalling Sentences, a clinical marker of structural language impairment. Task-based fMRI examined lateralization of significantly activated language-related brain regions in groups with structural language impairment (LI2) versus normal-range language (LN3), collapsed across ASD, LAD1, and NT status. Results showed no ASD versus LAD group differences in the proportion of participants with structural language impairment according to either metric (Recalling Sentences or Core Language). Functional MRI results indicated greater left hemisphere lateralization within significantly activated regions in the LI2 group. Structural language abilities were not meaningfully associated with either social abilities or lifetime ADHD symptoms in LI2 subgroups, further suggesting the presence of structural language impairment. Findings indicate the presence of persistent structural language difficulty even in the absence of ASD symptoms in some individuals within the LAD1 group and unique patterns of language-related neural specialization for language function in LI2 relative to LN3.

Effects of the Fyn kinase inhibitor saracatinib on ventral striatal activity during performance of an fMRI monetary incentive delay task in individuals family history positive or negative for alcohol use disorder. A pilot randomised trial.

Altered striatal regulation of the GluN2B subunit of N-methyl-D-aspartate (NMDA) glutamate receptors by the Fyn/Src family of protein tyrosine kinases has been implicated in animal alcohol consumption. Previously, we have described differences between individuals positive (FHP) and negative (FHN) for familial alcohol use disorder (AUD) in the ventral striatal (VS) activation associated with monetary incentive delay task (MIDT) performance during functional magnetic resonance imaging (fMRI). Here, we used AZD0530 (saracatinib), a centrally active Fyn/Src inhibitor to probe the role of Fyn/Src regulation of NMDA receptors (NMDAR) in VS activation differences between FHP and FHN individuals during fMRI MIDT performance. We studied 21 FHN and 22 FHP individuals, all without AUD. In two sessions, spaced 1 week apart, we administered 125 mg of saracatinib or placebo in a double-blind manner, prior to measuring VS signal during fMRI MIDT performance. MIDT comprises reward prospect, anticipation, and outcome phases. During the initial (prospect of reward) task phase, there was a significant group-by-condition interaction such that, relative to placebo, saracatinib reduced VS BOLD signal in FHP and increased it in FHN individuals. This study provides the first human evidence that elevated signaling in striatal protein kinase A-dependent pathways may contribute to familial AUD risk via amplifying the neural response to the prospect of reward. As Fyn kinase is responsible for NMDAR upregulation, these data are consistent with previous evidence for upregulated NMDAR function within reward circuitry in AUD risk. These findings also suggest a possible therapeutic role for Src/Fyn kinase inhibitors in AUD risk.

An Unobtrusive Fall Detection System Using Low Resolution Thermal Sensors and Convolutional Neural Networks.

Human activity recognition has many potential applications. In an aged care facility, it is crucial to monitor elderly patients and assist them in the case of falls or other needs. Wearable devices can be used for such a purpose. However, most of them have been proven to be obtrusive, and patients reluctate or forget to wear them. In this study, we used infrared technology to recognize certain human activities including sitting, standing, walking, laying in bed, laying down, and falling. We evaluated a system consisting of two 24×32 thermal array sensors. One infrared sensor was installed on side and another one was installed on the ceiling of an experimental room capturing the same scene. We chose side and overhead mounts to compare the performance of classifiers. We used our prototypes to collect data from healthy young volunteers while performing eight different scenarios. After that, we converted data coming from the sensors into images and applied a supervised deep learning approach. The scene was captured by a visible camera and the video from the visible camera was used as the ground truth. The deep learning network consisted of a convolutional neural network which automatically extracted features from infrared images. Overall average F1-score of all classes for the side mount was 0.9044 and for the overhead mount was 0.8893. Overall average accuracy of all classes for the side mount was 96.65% and for the overhead mount was 95.77%. Our results suggested that our infrared-based method not only could unobtrusively recognize human activities but also was reasonably accurate.

Cannabis and Driving.

As more states in the U.S legalize recreational and medicinal cannabis, rates of driving under the influence of this drug are increasing significantly. Aspects of this emerging public health issue potentially pit science against public policy. The authors believe that the legal cart is currently significantly ahead of the scientific horse. Issues such as detection procedures for cannabis-impaired drivers, and use of blood THC levels to gauge impairment, should rely heavily on current scientific knowledge. However, there are many, often unacknowledged research gaps in these and related areas, that need to be addressed in order provide a more coherent basis for public policies. This review focuses especially on those areas. In this article we review in a focused manner, current information linking cannabis to motor vehicle accidents and examine patterns of cannabis-impairment of driving related behaviors, their time courses, relationship to cannabis dose and THC blood levels, and compare cannabis and alcohol-impaired driving patterns directly. This review also delves into questions of alcohol-cannabis combinations and addresses the basis for of per-se limits in cannabis driving convictions. Finally, we distinguish between areas where research has provided clear answers to the above questions, areas that remain unclear, and make recommendations to fill gaps in current knowledge.

Spatially clustered count data provide more efficient search strategies in invasion biology and disease control.

Geographic profiling, a mathematical model originally developed in criminology, is increasingly being used in ecology and epidemiology. Geographic profiling boasts a wide range of applications, such as finding source populations of invasive species or breeding sites of vectors of infectious disease. The model provides a cost-effective approach for prioritizing search strategies for source locations and does so via simple data in the form of the positions of each observation, such as individual sightings of invasive species or cases of a disease. In doing so, however, classic geographic profiling approaches fail to make the distinction between those areas containing observed absences and those areas where no data were recorded. Absence data are generated via spatial sampling protocols but are often discarded during the inference process. Here we construct a geographic profiling model that resolves these issues by making inferences via count data, analyzing a set of discrete sentinel locations at which the number of encounters has been recorded. Crucially, in our model this number can be zero. We verify the ability of this new model to estimate source locations and other parameters of practical interest via a Bayesian power analysis. We also measure model performance via real-world data in which the model infers breeding locations of mosquitoes in bromeliads in Miami-Dade County, Florida, USA. In both cases, our novel model produces more efficient search strategies by shifting focus from those areas containing observed absences to those with no data, an improvement over existing models that treat these areas equally. Our model makes important improvements upon classic geographic profiling methods, which will significantly enhance real-world efforts to develop conservation management plans and targeted interventions.

Effects of weather and season on human brain volume.

We present an exploratory cross-sectional analysis of the effect of season and weather on Freesurfer-derived brain volumes from a sample of 3,279 healthy individuals collected on two MRI scanners in Hartford, CT, USA over a 15 year period. Weather and seasonal effects were analyzed using a single linear regression model with age, sex, motion, scan sequence, time-of-day, month of the year, and the deviation from average barometric pressure, air temperature, and humidity, as covariates. FDR correction for multiple comparisons was applied to groups of non-overlapping ROIs. Significant negative relationships were found between the left- and right- cerebellum cortex and pressure (t = -2.25, p = 0.049; t = -2.771, p = 0.017). Significant positive relationships were found between left- and right- cerebellum cortex and white matter between the comparisons of January/June and January/September. Significant negative relationships were found between several subcortical ROIs for the summer months compared to January. An opposing effect was observed between the supra- and infra-tentorium, with opposite effect directions in winter and summer. Cohen's d effect sizes from monthly comparisons were similar to those reported in recent psychiatric big-data publications, raising the possibility that seasonal changes and weather may be confounds in large cohort studies. Additionally, changes in brain volume due to natural environmental variation have not been reported before and may have implications for weather-related and seasonal ailments.

An Examination of the Association Between Subjective Distress and Functional Connectivity During Discarding Decisions in Hoarding Disorder.

BACKGROUND: Individuals with hoarding disorder (HD) demonstrate exaggerated subjective distress and hyperactivation of cingulate and insular cortex regions when discarding personal possessions. No prior study has sought to determine whether this subjective distress is associated with specific profiles of abnormal brain function in individuals with HD. METHODS: We used multimodal canonical correlation analysis plus joint independent component analysis to test whether five hoarding-relevant domains of subjective distress when deciding to discard possessions (anxiety, sadness, monetary value, importance, and sentimental attachment) are associated with functional magnetic resonance imaging-measured whole-brain functional connectivity in 72 participants with HD and 44 healthy controls. RESULTS: Three extracted components differed between HD participants and healthy control subjects. Each of these components depicted an abnormal profile of functional connectivity in HD participants relative to control subjects during discarding decisions, and a specific distress response profile. One component pair showed a relationship between anxiety ratings during discarding decisions and connectivity among the pallidum, perirhinal ectorhinal cortex, and dorsolateral prefrontal cortex. Another component comprised sadness ratings during discarding decisions and connectivity in the pallidum, nucleus accumbens, amygdala, and dorsolateral prefrontal cortex. The third component linked HD brain connectivity in several dorsolateral prefrontal cortex regions with perceived importance ratings during discarding decisions. CONCLUSIONS: The findings indicate that in patients with HD, the subjective intensity of anxiety, sadness, and perceived possession importance is related to abnormal functional connectivity in key frontal and emotional processing brain regions. The findings are discussed in terms of emerging neurobiological models of HD.

Measuring Within-Session and Between-Session Compliance in Hoarding Disorder: A Preliminary Investigation of the Psychometric Properties of the CBT Compliance Measure (CCM) and Patient Exposure/Response Prevention Adherence Scale for Hoarding (PEAS-H).

Hoarding disorder (HD) is a new psychiatric diagnosis in Diagnostic and Statistical Manual of Mental Disorders-Fifth edition and preliminary evidence suggests that cognitive-behavioral treatments are effective in treating this condition. However, it has been demonstrated that individuals with HD generally display poor compliance during treatment, which may lead to poor outcomes. Treatment compliance can be conceptualized as either within-session or between-session compliance, but currently there are no validated measures of within-session or between-session compliance specifically for HD. The aim of this study was to provide an initial validation of the CBT Compliance Measure and the Patient Exposure/Response Prevention Adherence Scale for Hoarding in a sample of participants with HD who were undergoing group cognitive behavioral therapy (CBT) for HD (N = 70). Both measures, which were administered at each relevant treatment session, demonstrated a unidimensional structure, good reliability, as well as predictive validity, and are thus promising in the measurement of within-session and between-session compliance with CBT for HD.

Combined resistance and aerobic exercise intervention improves fitness, insulin resistance and quality of life in survivors of childhood haemopoietic stem cell transplantation with total body irradiation.

PURPOSE: To investigate the effects of a supervised combined resistance and aerobic training programme on cardiorespiratory fitness, body composition, insulin resistance and quality of life (QoL) in survivors of childhood haematopoietic stem cell transplantation (HSCT) with total body irradiation (TBI). PARTICIPANTS: HSCT/TBI survivors (n = 20; 8 females). Mean (range) for age at study and time since HSCT/TBI was 16.7 (10.9-24.5) and 8.4 (2.3-16.0) years, respectively. METHODS: After a 6-month run-in, participants undertook supervised 45- to 60-minute resistance and aerobic training twice weekly for 6 months, with a 6-month follow-up. The following assessments were made at 0, 6 (start of exercise programme), 12 (end of exercise programme) and 18 months: Body composition via dual energy X-ray absorptiometry, homeostatic model assessment of insulin resistance (HOMA-IR), cardiorespiratory fitness (treadmill-based peak rate of oxygen uptake (VO2 peak) test), QoL questionnaires (36-Item Short Form Health Survey (SF-36) and Minneapolis-Manchester Quality of Life Instrument (MMQL). RESULTS: Results expressed as mean (standard deviation) or geometric mean (range). There were significant improvements in VO2 peak (35.7 (8.9) vs 41.7 (16.1) mL/min/kg, P = 0.05), fasted plasma insulin (16.56 (1.48-72.8) vs 12.62 (1.04-54.97) mIU/L, P = 0.03) and HOMA-IR (3.65 (0.30-17.26) vs 2.72 (0.22-12.89), P = 0.02) after the exercise intervention. There were also significant improvements in the SF-36 QoL general health domain (69.7 (14.3) vs 72.7 (16.0), P = 0.001) and the MMQL school domain (69.1 (25.2) vs (79.3 (21.6), P = 0.03) during the exercise intervention. No significant changes were observed in percentage body fat, fat mass or lean mass. CONCLUSION: The supervised 6-month combined resistance and aerobic exercise programme significantly improved cardiorespiratory fitness, insulin resistance and QoL in childhood HSCT/TBI survivors, with no change in body composition, suggesting a metabolic training effect on muscle. These data support a role for targeted physical rehabilitation services in this group at high risk of diabetes and cardiovascular disease.

Neural correlates of non-specific skin conductance responses during resting state fMRI.

Skin conductance responses (SCRs) reliably occur in the absence of external stimulation. However, the neural correlates of these non-specific SCRs have been less explored than brain activity associated with stimulus-elicited SCRs. This study modeled spontaneous skin conductance responses observed during an unstructured resting state fMRI scan in 58 adolescents. A Finite Impulse Response (FIR) fMRI model was used to detect any type of hemodynamic response shape time-locked to non-specific SCRs; the shape of these responses was then carefully characterized. The strongest evidence for signal change was found in several sub-regions of sensorimotor cortex. There also was evidence for engagement of discrete areas within the lateral surfaces of the parietal lobe, cingulate cortex, fronto-insular operculum, and both visual and auditory primary processing areas. The hemodynamic profile measured by FIR modeling clearly resembled an event-related response. However, it was a complex response, best explained by two quickly successive, but opposing neuronal impulses across all brain regions - a brief positive response that begins several seconds prior to the SCR with a much longer negative neuronal impulse beginning shortly after the SCR onset. Post hoc exploratory analyses linked these two hemodynamic response phases to different emotion-related individual differences. In conclusion, this study shows the neural correlates of non-specific SCRs are a widespread, cortical network of brain regions engaged in a complex, seemingly biphasic fashion. This bimodal response profile should be considered in replication studies that attempt to directly link brain activity to possible homeostatic mechanisms or seek evidence for alternative mechanisms.