Increased BDNF levels and NTRK2 gene association suggest a disruption of BDNF/TrkB signaling in autism

The brain-derived neurotrophic factor (BDNF), a neurotrophin fundamental for brain development and function, has previously been implicated in autism. In this study, the levels of BDNF in platelet-rich plasma were compared between autistic and control children, and the role of two genetic factors that might regulate this neurotrophin and contribute to autism etiology, BDNF and NTRK2, was examined. We found that BDNF levels in autistic children (n = 146) were significantly higher (t = 6.82; P < 0.0001) than in control children (n = 50) and were positively correlated with platelet serotonin distribution (r = 0.22; P = 0.004). Heritability of BDNF was estimated at 30% and therefore candidate genes BDNF and NTRK2 were tested for association with BDNF level distribution in this sample, and with autism in 469 trio families. Genetic association analysis provided no evidence for BDNF or NTRK2 as major determinants of the abnormally increased BDNF levels in autistic children. A significant association with autism was uncovered for six single nucleotide polymorphisms (SNPs) [0.004 (Z((1df)) = 2.85) < P < 0.039 (Z((1df)) = 2.06)] and multiple haplotypes [5 × 10(-4) (χ((3df)) = 17.77) < P < 0.042 (χ((9df)) = 17.450)] in the NTRK2 gene. These results do not withstand correction for multiple comparisons, however, reflect a trend toward association that supports a role of NTRK2 as a susceptibility factor for the disorder. Genetic variation in the BDNF gene had no impact on autism risk. By substantiating the previously observed increase in BDNF levels in autistic children in a larger patient set, and suggesting a genetic association between NTRK2 and autism, this study integrates evidence from multiple levels supporting the hypothesis that alterations in BDNF/tyrosine kinase B (TrkB) signaling contribute to an increased vulnerability to autism

Mental Health Mediates the Association Between Gender-Based Violence and HIV Treatment Engagement in US Women

Background: Gender-based violence (GBV) is associated with poorer engagement in HIV care and treatment. However, there is a dearth of research on the psychological (eg, mental health) and structural (eg, food insecurity) factors that mediate and moderate this association. GBV could lead to poor mental health, which in turn affects adherence, whereas food insecurity could worsen the effect of GBV on engagement in care. This study uses data from the Women's Interagency HIV Study to address these gaps. Methods: Women completed 6 assessments from 2013 to 2016 on GBV, mental health, food insecurity, adherence to antiretroviral therapy, and missed HIV care appointments in the past 6 months. Multilevel logistic regression models estimated associations between GBV and engagement in care and whether associations were mediated by depression, generalized anxiety disorder (GAD), and posttraumatic stress disorder (PTSD) and moderated by food insecurity. Results: GBV was associated with higher odds of suboptimal adherence (adjusted odds ratio: 1.88; 95% confidence interval: 1.24 to 2.87) and missed appointments (adjusted odds ratio: 1.76; 95% confidence interval: 1.16 to 2.67). The association between GBV and adherence was mediated by depressive symptoms, GAD, and PTSD, accounting for 29.7%, 15.0%, and 16.5%, respectively, of the total association. The association between GBV and missed appointments was mediated by depression and GAD, but not PTSD, with corresponding figures of 25.2% and 19.7%. Associations did not differ by food insecurity. Conclusions: GBV is associated with suboptimal engagement in care, which may be explained by mental health. Interventions should address women's mental health needs, regardless of food insecurity, when improving engagement in HIV care

Mechanisms linking gender-based violence to worse HIV treatment and care outcomes among women in the United States

Objective:To test whether substance use mediates the associations between gender-based violence (GBV) and suboptimal adherence to antiretroviral therapy (ART), and GBV and poor engagement in care, among women living with HIV (WLHIV) in the United States (US).Design:We analyzed longitudinal data collected among 1717 WLHIV in the Women's Interagency HIV Study (WIHS).Methods:From 2013 to 2017, WLHIV completed semi-annual assessments on GBV, substance use, and HIV treatment and care. Adjusted multilevel logistic regression models were built to estimate the impact of GBV on; suboptimal (<95%) adherence and at least one missed HIV care appointment without rescheduling in the past 6 months. Mediation analyses were performed to test whether heavy drinking and illicit drug use mediated the associations between GBV and the two HIV outcomes.Results:The mean age was 47 (standard deviation = 9), 5% reported experiencing GBV, 17% reported suboptimal adherence and 15% reported at least one missed appointment in the past 6 months. Women who experienced GBV had a significantly higher odds of suboptimal adherence [adjusted odds ratio (aOR) = 1.99; 95% confidence interval (CI) = 1.40-2.83] and missed appointments (aOR = 1.92, 95% CI = 1.32-2.33). Heavy drinking and illicit drug use mediated 36 and 73% of the association between GBV and suboptimal adherence and 29 and 65% of the association between GBV and missed appointments, respectively.Conclusions:Substance use is an underlying mechanism through which GBV affects outcomes along the HIV care continuum among WLHIV in the US. To optimize HIV treatment and care among women, interventions should address the combined epidemics of substance use, violence, and HIV

The impact of the metabotropic glutamate receptor and other gene family interaction networks on autism

Although multiple reports show that defective genetic networks underlie the aetiology of autism, few have translated into pharmacotherapeutic opportunities. Since drugs compete with endogenous small molecules for protein binding, many successful drugs target large gene families with multiple drug binding sites. Here we search for defective gene family interaction networks (GFINs) in 6,742 patients with the ASDs relative to 12,544 neurologically normal controls, to find potentially druggable genetic targets. We find significant enrichment of structural defects (P≤2.40E-09, 1.8-fold enrichment) in the metabotropic glutamate receptor (GRM) GFIN, previously observed to impact attention deficit hyperactivity disorder (ADHD) and schizophrenia. Also, the MXD-MYC-MAX network of genes, previously implicated in cancer, is significantly enriched (P≤3.83E-23, 2.5-fold enrichment), as is the calmodulin 1 (CALM1) gene interaction network (P≤4.16E-04, 14.4-fold enrichment), which regulates voltage-independent calcium-activated action potentials at the neuronal synapse. We find that multiple defective gene family interactions underlie autism, presenting new translational opportunities to explore for therapeutic interventions

The Physics of Star Cluster Formation and Evolution

© 2020 Springer-Verlag. The final publication is available at Springer via https://doi.org/10.1007/s11214-020-00689-4.Star clusters form in dense, hierarchically collapsing gas clouds. Bulk kinetic energy is transformed to turbulence with stars forming from cores fed by filaments. In the most compact regions, stellar feedback is least effective in removing the gas and stars may form very efficiently. These are also the regions where, in high-mass clusters, ejecta from some kind of high-mass stars are effectively captured during the formation phase of some of the low mass stars and effectively channeled into the latter to form multiple populations. Star formation epochs in star clusters are generally set by gas flows that determine the abundance of gas in the cluster. We argue that there is likely only one star formation epoch after which clusters remain essentially clear of gas by cluster winds. Collisional dynamics is important in this phase leading to core collapse, expansion and eventual dispersion of every cluster. We review recent developments in the field with a focus on theoretical work.Peer reviewe

Velocity-space sensitivity of the time-of-flight neutron spectrometer at JET

The velocity-space sensitivities of fast-ion diagnostics are often described by so-called weight functions. Recently, we formulated weight functions showing the velocity-space sensitivity of the often dominant beam-target part of neutron energy spectra. These weight functions for neutron emission spectrometry (NES) are independent of the particular NES diagnostic. Here we apply these NES weight functions to the time-of-flight spectrometer TOFOR at JET. By taking the instrumental response function of TOFOR into account, we calculate time-of-flight NES weight functions that enable us to directly determine the velocity-space sensitivity of a given part of a measured time-of-flight spectrum from TOFOR

On the mechanisms governing gas penetration into a tokamak plasma during a massive gas injection

A new 1D radial fluid code, IMAGINE, is used to simulate the penetration of gas into a tokamak plasma during a massive gas injection (MGI). The main result is that the gas is in general strongly braked as it reaches the plasma, due to mechanisms related to charge exchange and (to a smaller extent) recombination. As a result, only a fraction of the gas penetrates into the plasma. Also, a shock wave is created in the gas which propagates away from the plasma, braking and compressing the incoming gas. Simulation results are quantitatively consistent, at least in terms of orders of magnitude, with experimental data for a D 2 MGI into a JET Ohmic plasma. Simulations of MGI into the background plasma surrounding a runaway electron beam show that if the background electron density is too high, the gas may not penetrate, suggesting a possible explanation for the recent results of Reux et al in JET (2015 Nucl. Fusion 55 093013)

Relationship of edge localized mode burst times with divertor flux loop signal phase in JET

A phase relationship is identified between sequential edge localized modes (ELMs) occurrence times in a set of H-mode tokamak plasmas to the voltage measured in full flux azimuthal loops in the divertor region. We focus on plasmas in the Joint European Torus where a steady H-mode is sustained over several seconds, during which ELMs are observed in the Be II emission at the divertor. The ELMs analysed arise from intrinsic ELMing, in that there is no deliberate intent to control the ELMing process by external means. We use ELM timings derived from the Be II signal to perform direct time domain analysis of the full flux loop VLD2 and VLD3 signals, which provide a high cadence global measurement proportional to the voltage induced by changes in poloidal magnetic flux. Specifically, we examine how the time interval between pairs of successive ELMs is linked to the time-evolving phase of the full flux loop signals. Each ELM produces a clear early pulse in the full flux loop signals, whose peak time is used to condition our analysis. The arrival time of the following ELM, relative to this pulse, is found to fall into one of two categories: (i) prompt ELMs, which are directly paced by the initial response seen in the flux loop signals; and (ii) all other ELMs, which occur after the initial response of the full flux loop signals has decayed in amplitude. The times at which ELMs in category (ii) occur, relative to the first ELM of the pair, are clustered at times when the instantaneous phase of the full flux loop signal is close to its value at the time of the first ELM