Defining the disturbance in cortical glutamate and GABA function in psychosis and its origins and consequences

It is widely thought that the onset of psychotic symptoms in schizophrenia may arise from an early neurotoxic phase, possibly related to oxidative stress or inflammation, and a late residual damage phase associated with persistent negative symptoms. We tested this hypothesis in a 3-centre study using magnetic resonance spectroscopy (MRS) to determine whether abnormalities in glutamate, glutamine and GABA content in anterior cingulate cortex (ACC) differed between people with minimally treated ‘Recent’ onset schizophrenia and an ‘Established’ group with > 10 years of treatment. We tested whether neurochemical abnormalities were i) mediated by raised circulating inflammatory cytokine concentrations, c-reactive protein (CRP) and interleukin-6 (IL-6), or depletion of glutathione and ii) associated with ratings of positive and negative symptoms. Relative to age-matched controls, the Established group showed significantly greater reduction in ACC glutamate than the Recent group, which did not differ from controls. This effect was not attributable to antipsychotic drug exposure. Patient ACC glutathione was negatively correlated with age. IL-6 was increased in both clinical groups, while increases in CRP were greater in the Established than Recent group. Elevated CRP was entirely accounted for by greater antipsychotic drug exposure and BMI, while residual elevation in IL-6 in the Established group did not account for their lower ACC glutamate. GABA was reduced relative to controls across ACC and occipital voxels. This reduction was not associated with drug treatment, BMI or cytokine levels. Only ACC GABA content correlated significantly with symptoms, lower content with greater positive and negative symptoms across both groups

Dopamine and Glutamate in Antipsychotic-Responsive Compared With Antipsychotic-Nonresponsive Psychosis: A Multicenter Positron Emission Tomography and Magnetic Resonance Spectroscopy Study (STRATA)

The variability in the response to antipsychotic medication in schizophrenia may reflect between-patient differences in neurobiology. Recent cross-sectional neuroimaging studies suggest that a poorer therapeutic response is associated with relatively normal striatal dopamine synthesis capacity but elevated anterior cingulate cortex (ACC) glutamate levels. We sought to test whether these measures can differentiate patients with psychosis who are antipsychotic responsive from those who are antipsychotic nonresponsive in a multicenter cross-sectional study. 1H-magnetic resonance spectroscopy (1H-MRS) was used to measure glutamate levels (Glucorr) in the ACC and in the right striatum in 92 patients across 4 sites (48 responders [R] and 44 nonresponders [NR]). In 54 patients at 2 sites (25 R and 29 NR), we additionally acquired 3,4-dihydroxy-6-[18F]fluoro-L-phenylalanine (18F-DOPA) positron emission tomography (PET) to index striatal dopamine function (Kicer, min−1). The mean ACC Glucorr was higher in the NR than the R group after adjustment for age and sex (F1,80 = 4.27; P = .04). This was associated with an area under the curve for the group discrimination of 0.59. There were no group differences in striatal dopamine function or striatal Glucorr. The results provide partial further support for a role of ACC glutamate, but not striatal dopamine synthesis, in determining the nature of the response to antipsychotic medication. The low discriminative accuracy might be improved in groups with greater clinical separation or increased in future studies that focus on the antipsychotic response at an earlier stage of the disorder and integrate other candidate predictive biomarkers. Greater harmonization of multicenter PET and 1H-MRS may also improve sensitivity

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Global data set of long-term summertime vertical temperature profiles in 153 lakes

Climate change and other anthropogenic stressors have led to long-term changes in the thermal structure, including surface temperatures, deepwater temperatures, and vertical thermal gradients, in many lakes around the world. Though many studies highlight warming of surface water temperatures in lakes worldwide, less is known about long-term trends in full vertical thermal structure and deepwater temperatures, which have been changing less consistently in both direction and magnitude. Here, we present a globally-expansive data set of summertime in-situ vertical temperature profiles from 153 lakes, with one time series beginning as early as 1894. We also compiled lake geographic, morphometric, and water quality variables that can influence vertical thermal structure through a variety of potential mechanisms in these lakes. These long-term time series of vertical temperature profiles and corresponding lake characteristics serve as valuable data to help understand changes and drivers of lake thermal structure in a time of rapid global and ecological change

Global data set of long-term summertime vertical temperature profiles in 153 lakes

Measurement(s) : temperature of water, temperature profile Technology Type(s) : digital curation Factor Type(s) : lake location, temporal interval Sample Characteristic - Environment : lake, reservoir Sample Characteristic - Location : global Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.14619009Climate change and other anthropogenic stressors have led to long-term changes in the thermal structure, including surface temperatures, deepwater temperatures, and vertical thermal gradients, in many lakes around the world. Though many studies highlight warming of surface water temperatures in lakes worldwide, less is known about long-term trends in full vertical thermal structure and deepwater temperatures, which have been changing less consistently in both direction and magnitude. Here, we present a globally-expansive data set of summertime in-situ vertical temperature profiles from 153 lakes, with one time series beginning as early as 1894. We also compiled lake geographic, morphometric, and water quality variables that can influence vertical thermal structure through a variety of potential mechanisms in these lakes. These long-term time series of vertical temperature profiles and corresponding lake characteristics serve as valuable data to help understand changes and drivers of lake thermal structure in a time of rapid global and ecological change

Correction to: Cluster identification, selection, and description in Cluster randomized crossover trials: the PREP-IT trials

An amendment to this paper has been published and can be accessed via the original article