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This study aimed to evaluate the dose-dependent brain temperature effects of transcranial photobiomodulation (t-PBM). Thirty adult subjects with major depressive disorder were randomized to three t-PBM sessions with different doses (low: 50 mW/cm2, medium: 300 mW/cm2, high: 850 mW/cm2) and a sham treatment. The low and medium doses were administered in continuous wave mode, while the high dose was administered in pulsed wave mode. A 3T MRI scanner was used to perform proton magnetic resonance spectroscopy (1H-MRS). A voxel with a volume of 30 × 30 × 15 mm3 was placed on the left prefrontal region. Brain temperature (°C) was derived by analyzing 1H-MRS spectrum chemical shift differences between the water (~ 4.7 ppm) and N-acetyl aspartate (NAA) (~ 2.01 ppm) peaks. After quality control of the data, the following group numbers were available for both pre- and post-temperature estimations: sham (n = 10), low (n = 11), medium (n = 10), and high (n = 8). We did not detect significant temperature differences for any t-PBM-active or sham groups post-irradiation (p-value range = 0.105 and 0.781). We also tested for potential differences in the pre-post variability of brain temperature in each group. As for t-PBM active groups, the lowest fluctuation (variance) was observed for the medium dose (σ2 = 0.29), followed by the low dose (σ2 = 0.47), and the highest fluctuation was for the high dose (σ2 = 0.67). t-PBM sham condition showed the overall lowest fluctuation (σ2 = 0.11). Our 1H-MRS thermometry results showed no significant brain temperature elevations during t-PBM administration.

IntroductionThe pre-processing of analytical data in metabolomics must be considered as a whole to allow the construction of a global and unique object for any further simultaneous data analysis or multivariate statistical modelling. For 1D 1H-NMR metabolomics experiments, best practices for data pre-processing are well defined, but not yet for 2D experiments (for instance COSY in this paper).ObjectiveBy considering the added value of a second dimension, the objective is to propose two workflows dedicated to 2D NMR data handling and preparation (the Global Peak List and Vectorization approaches) and to compare them (with respect to each other and with 1D standards). This will allow to detect which methodology is the best in terms of amount of metabolomic content and to explore the advantages of the selected workflow in distinguishing among treatment groups and identifying relevant biomarkers. Therefore, this paper explores both the necessity of novel 2D pre-processing workflows, the evaluation of their quality and the evaluation of their performance in the subsequent determination of accurate (2D) biomarkers.MethodsTo select the more informative data source, MIC (Metabolomic Informative Content) indexes are used, based on clustering and inertia measures of quality. Then, to highlight biomarkers or critical spectral zones, the PLS-DA model is used, along with more advanced sparse algorithms (sPLS and L-sOPLS).ResultsResults are discussed according to two different experimental designs (one which is unsupervised and based on human urine samples, and the other which is controlled and based on spiked serum media). MIC indexes are shown, leading to the choice of the more relevant workflow to use thereafter. Finally, biomarkers are provided for each case and the predictive power of each candidate model is assessed with cross-validated measures of RMSEP.ConclusionIn conclusion, it is shown that no solution can be universally the best in every case, but that 2D experiments allow to clearly find relevant cross peak biomarkers even with a poor initial separability between groups. The MIC measures linked with the candidate workflows (2D GPL, 2D vectorization, 1D, and with specific parameters) lead to visualize which data set must be used as a priority to more easily find biomarkers. The diversity of data sources, mainly 1D versus 2D, may often lead to complementary or confirmatory results.

Alterations in glutamatergic neurotransmission are implicated in the pathophysiology of depression, and the glutamatergic system represents a treatment target for depression. To summarize the nature of glutamatergic alterations in patients with depression, we conducted a meta-analysis of proton magnetic resonance (1H-MRS) spectroscopy studies examining levels of glutamate. We used the search terms: depress* AND (MRS OR “magnetic resonance spectroscopy”). The search was performed with MEDLINE, Embase, and PsycINFO. The inclusion criteria were 1H-MRS studies comparing levels of glutamate + glutamine (Glx), glutamate, or glutamine between patients with depression and healthy controls. Standardized mean differences (SMD) were calculated to assess group differences in the levels of glutamatergic neurometabolites. Forty-nine studies met the eligibility criteria, which included 1180 patients and 1066 healthy controls. There were significant decreases in Glx within the medial frontal cortex (SMD = −0.38; 95% CI, −0.69 to −0.07) in patients with depression compared with controls. Subanalyses revealed that there was a significant decrease in Glx in the medial frontal cortex in medicated patients with depression (SMD = −0.50; 95% CI, −0.80 to −0.20), but not in unmedicated patients (SMD = −0.27; 95% CI, −0.76 to 0.21) compared with controls. Overall, decreased levels of glutamatergic metabolites in the medial frontal cortex are linked with the pathophysiology of depression. These findings are in line with the hypothesis that depression may be associated with abnormal glutamatergic neurotransmission.

•The reproducibility assessment of magnetic resonance spectroscopy was explored.•CV and ICC showed good reliability of within- and between- scanning sessions.•Bland-Altman plots indicated strong agreement in the repeated measurements.•Pearson correlation coefficients showed great reproducibility across three machines.•It revealed higher reproducibility for the intra-vendor than the inter-vendor. Proton magnetic resonance spectroscopy (1H-MRS) has potential in clinical diagnosis and understanding the mechanism of illnesses. However, its application is limited by the lack of standardization in data acquisition and processing across time points and between different magnetic resonance imaging (MRI) system vendors. This study examines whether metabolite concentrations obtained from different sessions, scanner models, and vendors can be reliably reproduced and combined for diagnostic analysis-an important consideration for rare disease research. Participants underwent magnetic resonance scanning once on two separate days within one week (one session per day, each including two 1H-MRS scans without subject movement) on each machine. Absolute metabolite concentrations were analyzed for reliability of within- and between- session using the coefficient of variation (CV), intraclass correlation coefficient (ICC) and Bland-Altman (BA) plot, and for reproducibility across the machines using the Pearson correlation coefficient. As for within- and between- session, most of the CV values for a group of all the first or second scans of a session, and from each session were below 20 %, and most of ICCs ranged from moderate (0.4≤ICC<0.59) to excellent (ICC≥0.75), which indicated high reliability. Most of the BA plots had the line of equality between 95 % confidence interval of bias (mean difference), therefore the differences over scanning time could be negligible. Majority of the Pearson correlation coefficients approached 1 with statistical significance (P < 0.001), showing high reproducibility across the three scanners. Additionally, the intra-vendor reproducibility was greater than the inter-vendor ones. [Display omitted]

In schizophrenia, abnormal neural metabolite concentrations may arise from cortical damage following neuroinflammatory processes implicated in acute episodes. Inflammation is associated with increased glutamate, whereas the antioxidant glutathione may protect against inflammation-induced oxidative stress. We hypothesized that patients with stable schizophrenia would exhibit a reduction in glutathione, glutamate, and/or glutamine in the cerebral cortex, consistent with a post-inflammatory response, and that this reduction would be most marked in patients with “residual schizophrenia”, in whom an early stage with positive psychotic symptoms has progressed to a late stage characterized by long-term negative symptoms and impairments. We recruited 28 patients with stable schizophrenia and 45 healthy participants matched for age, gender, and parental socio-economic status. We measured glutathione, glutamate and glutamine concentrations in the anterior cingulate cortex (ACC), left insula, and visual cortex using 7T proton magnetic resonance spectroscopy (MRS). Glutathione and glutamate were significantly correlated in all three voxels. Glutamine concentrations across the three voxels were significantly correlated with each other. Principal components analysis (PCA) produced three clear components: an ACC glutathione–glutamate component; an insula-visual glutathione–glutamate component; and a glutamine component. Patients with stable schizophrenia had significantly lower scores on the ACC glutathione–glutamate component, an effect almost entirely leveraged by the sub-group of patients with residual schizophrenia. All three metabolite concentration values in the ACC were significantly reduced in this group. These findings are consistent with the hypothesis that excitotoxicity during the acute phase of illness leads to reduced glutathione and glutamate in the residual phase of the illness.

•Recent advances in MRS now allow for event-related functional MRS, with temporal resolution in the order of seconds.•We provide a user guide for experimental design, data acquisition and analysis considerations for event-related fMRS.•We use simulations to determine optimal settings to detect event-related changes in GABA.•We provide a critical perspective on the appropriate interpretation of event-related fMRS. Proton-Magnetic Resonance Spectroscopy (MRS) is a non-invasive brain imaging technique used to measure the concentration of different neurochemicals. “Single-voxel” MRS data is typically acquired across several minutes, before individual transients are averaged through time to give a measurement of neurochemical concentrations. However, this approach is not sensitive to more rapid temporal dynamics of neurochemicals, including those that reflect functional changes in neural computation relevant to perception, cognition, motor control and ultimately behaviour. In this review we discuss recent advances in functional MRS (fMRS) that now allow us to obtain event-related measures of neurochemicals. Event-related fMRS involves presenting different experimental conditions as a series of trials that are intermixed. Critically, this approach allows spectra to be acquired at a time resolution in the order of seconds. Here we provide a comprehensive user guide for event-related task designs, choice of MRS sequence, analysis pipelines, and appropriate interpretation of event-related fMRS data. We raise various technical considerations by examining protocols used to quantify dynamic changes in GABA, the primary inhibitory neurotransmitter in the brain. Overall, we propose that although more data is needed, event-related fMRS can be used to measure dynamic changes in neurochemicals at a temporal resolution relevant to computations that support human cognition and behaviour.

Background:Nonalcoholic fatty liver disease is very frequent in type 2 diabetes, with increased risk of further development of liver fibrosis. Animal studies have shown that GLP-1 receptor agonists may reduce liver lipogenesis. However, data in humans are scarce.Objective:To study the effect of liraglutide 1.2 mg/d on liver fat content (LFC) in patients with uncontrolled type 2 diabetes and to evaluate the factors potentially associated with liraglutide-induced modification of LFC.Design, Setting, Participants:LFC was measured by proton magnetic resonance spectroscopy before and after 6 months of liraglutide treatment in 68 patients with uncontrolled type 2 diabetes mellitus.Intervention:Liraglutide 1.2 mg/d.Outcome measure:Change in LFC.Results:Treatment with liraglutide was associated with a significant decrease in body weight, HbA1C, and a marked relative reduction in LFC of 31% (P < 0.0001). No significant modification of LFC was observed in a parallel group of patients 6 months after intensification of the antidiabetic treatment with insulin. The reduction in LFC and body weight were highly correlated (r = 0.490; P < 0.0001). In multivariate analysis, the reduction in LFC was independently associated with baseline LFC (P < 0.0001), age (P = 0.010), and reduction in body weight (P < 0.0001), triglycerides (P = 0.019), and HbA1c (P = 0.034). In the patients who had no significant decrease in body weight, no significant reduction in LFC was observed.Conclusions:Six months of treatment with liraglutide 1.2 mg/d significantly reduced LFC in patients with inadequately controlled type 2 diabetes and this effect was mainly driven by body weight reduction. Further studies are needed to confirm that this reduction in LFC may significantly reduce fibrosis progression.We show in 68 patients with type 2 diabetes that 6 months of treatment with liraglutide significantly reduced liver fat content and that body weight reduction was the main driver of liver fat decrease.

Motivation levels vary across individuals, yet the underlying mechanisms driving these differences remain elusive. The dorsomedial prefrontal cortex/dorsal anterior cingulate cortex (dmPFC/dACC) and the anterior insula (aIns) play crucial roles in effort-based decision-making. Here, we investigate the influence of lactate, a key metabolite involved in energy metabolism and signaling, on decisions involving both physical and mental effort, as well as its effects on neural activation. Using proton magnetic resonance spectroscopy and functional MRI in 63 participants, we find that higher lactate levels in the dmPFC/dACC are associated with reduced motivation for physical effort, a relationship mediated by neural activity within this region. Additionally, plasma and dmPFC/dACC lactate levels correlate, suggesting a systemic influence on brain metabolism. Supported by path analysis, our results highlight lactate’s role as a modulator of dmPFC/dACC activity, hinting at a neurometabolic mechanism that integrates both peripheral and central metabolic states with brain function in effort-based decision-making.

Cognitive-behavioral therapy (CBT) is effective for pediatric obsessive-compulsive disorder (OCD), but non-response is common. Brain glutamate (Glu) signaling may contribute to OCD pathophysiology and moderate CBT outcomes. We assessed whether Glu measured with magnetic resonance spectroscopy (MRS) was associated with OCD and/or CBT response. Youths aged 7-17 years with DSM-IV OCD and typically developing controls underwent 3 T proton echo-planar spectroscopic imaging (PEPSI) MRS scans of pregenual anterior cingulate cortex (pACC) and ventral posterior cingulate cortex (vPCC)-regions possibly affected by OCD-at baseline. Controls returned for re-scan after 8 weeks. OCD youth-in a randomized rater-blinded trial-were re-scanned after 12-14 weeks of CBT or after 8 weeks of minimal-contact waitlist; waitlist participants underwent a third scan after crossover to 12-14 weeks of CBT. Forty-nine children with OCD (mean age 12.2±2.9 years) and 29 controls (13.2±2.2 years) provided at least one MRS scan. At baseline, Glu did not differ significantly between OCD and controls in pACC or vPCC. Within controls, Glu was stable from scan-to-scan. Within OCD subjects, a treatment-by-scan interaction (p=0.034) was observed, driven by pACC Glu dropping 19.5% from scan-to-scan for patients randomized to CBT, with minor increases (3.8%) for waitlist participants. The combined OCD participants (CBT-only plus waitlist-CBT) also showed a 16.2% (p=0.004) post-CBT decrease in pACC Glu. In the combined OCD group, within vPCC, lower pre-CBT Glu predicted greater post-CBT improvement in symptoms (CY-BOCS; r=0.81, p=0.00025). Glu may be involved in the pathophysiology of OCD and may moderate response to CBT.

Impaired cognitive flexibility represents a widespread symptom in psychiatric disorders, including major depressive disorder (MDD), a disease, characterized by an imbalance of neurotransmitter concentrations. While memory formation is mostly associated with glutamate, also gamma-Aminobutyric acid (GABA) and serotonin show attributions in a complex interplay between neurotransmitter systems. Treatment with selective serotonin reuptake inhibitors (SSRIs) does not solely affect the serotonergic system but shows downstream effects on GABA- and glutamatergic neurotransmission, potentially helping to restore cognitive function via neuroplastic effects. Hence, this study aims to elaborate the effects of associative relearning and SSRI treatment on GABAergic and glutamatergic function within and between five brain regions using magnetic resonance spectroscopy imaging (MRSI). In this study, healthy subjects were randomized into four groups which underwent three weeks of an associative relearning paradigm, with or without emotional connotation, under SSRI (10mg escitalopram) or placebo administration. MRSI measurements, using a spiral-encoded, 3D-GABA-edited MEGA-LASER sequence at 3T, were performed on the first and last day of relearning. Mean GABA+/tCr (GABA+ = GABA + macromolecules; tCr = total creatine) and Glx/tCr (Glx = glutamate + glutamine) ratios were quantified in a ROI-based approach for the hippocampus, insula, putamen, pallidum and thalamus, using LCModel. A total of 66 subjects ((37 female, mean age ± SD = 25.4±4.7) for Glx/tCr and 58 subjects (32 female, mean age ± SD = 25.1±4.7) for GABA+/tCr were included in the final analysis. A significant measurement by region and treatment (SSRI vs placebo) interaction on Glx/tCr ratios was found (pcor=0.017), with post hoc tests confirming differential effects on hippocampus and thalamus (pcor=0.046). Moreover, treatment by time comparison, for each ROI independently, showed a reduction of hippocampal Glx/tCr ratios after SSRI treatment (puncor=0.033). No significant treatment effects on GABA+/tCr ratios or effects of relearning condition on any neurotransmitter ratio could be found. Here, we showed a significant SSRI- and relearning-driven interaction effect of hippocampal and thalamic Glx/tCr levels, suggesting differential behavior based on different serotonin transporter and receptor densities. Moreover, an indication for Glx/tCr adaptions in the hippocampus after three weeks of SSRI treatment could be revealed. Our findings are in line with animal studies reporting glutamate adaptions in the hippocampus following chronic SSRI intake. Due to the complex interplay of serotonin and hippocampal function, involving multiple serotonin receptor subtypes on glutamatergic cells and GABAergic interneurons, the interpretation of underlying neurobiological actions remains challenging.