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Cherix, A.

Publications and source records attributed to Cherix, A..

6 recordsLinked to original sources

Longitudinal neurochemical profiling after experimental stroke using edited MR spectroscopy

Background: Alterations in excitatory and inhibitory neurotransmission contribute to stroke pathology and recovery, yet longitudinal assessment of these changes in vivo remains limited. We investigated the feasibility of longitudinal edited proton magnetic resonance spectroscopy (1H-MRS) to quantify {gamma}-aminobutyric acid (GABA) and glutamate following experimental focal cerebral ischaemia. Methods: Male rats underwent endothelin-1-induced striatal ischaemia or sham surgery. Longitudinal edited 1H-MRS was performed at baseline and 2-, 7- and 30-days post-stroke at 7-tesla with a MEGA-sLASER sequence. A voxel was positioned within the ipsilesional motor cortex adjacent to the lesion. Behavioural outcomes (grip strength, adhesive removal and CatWalk gait analysis) were assessed alongside spectroscopy, and immunohistochemistry for Iba1, GFAP and ICAM-1 was performed at 30 days. Results: Stroke induced a transient reduction in GABA+/tCr within the ipsilesional motor cortex, with significantly lower concentrations than sham animals at 7 days (p<0.05), returning to baseline by 30 days. Glutamate/tCr and GABA/glutamate ratio were unchanged throughout the study. Behavioural deficits were mild, with significant effects on motor outcomes such as grip strength, gait swing speed and paw placement, while sensory areas of the brain seemed largely unaffected. Histological analysis revealed no persistent differences in cortical Iba1, GFAP or ICAM-1 immunoreactivity at 30 days. Conclusions: Longitudinal 1H-MRS is a feasible approach for monitoring dynamic changes in inhibitory neurochemistry following experimental stroke. The transient reduction in peri-lesional GABA, despite minimal behavioural impairment and an absence of persistent cortical inflammation, supports the use of edited spectroscopy as a translational tool to investigate neurochemical mechanisms underlying network dynamics in post-stroke recovery.

neuroscience↗

A hippocampal neuroimaging signature of neurovascular insulin signalling links metabolism to mood

Depression is a leading cause of global disability and is increasingly linked to systemic metabolic dysfunctions, including insulin resistance. However, the biological pathways connecting metabolic state to affective symptoms are unresolved. A growing body of evidence indicates that insulin, beyond its role in systemic glucose homeostasis, supports brain metabolism, synaptic function and cognition, yet its contribution to mood regulation remains unclear. Here, we identify a human hippocampal metabolic signature associated with glycaemic variation in individuals with depression. Using multimodal neuroimaging, we show that hippocampal concentrations of GABA and lactate correlate with HbA1c and with mood severity, while functional connectivity between the hippocampus and the default mode network tracks affective symptoms independently of adiposity. To causally probe these relationships, we generated a mouse model of hippocampus-specific insulin receptor depletion. Unexpectedly, reducing insulin signalling at the blood brain barrier enhanced neuronal metabolism and attenuated anxiety-like behaviour. Notably, hippocampal lactate and GABA levels similarly tracked anxiety-related behaviour in mice, mirroring their association with symptom severity in humans. Together, these findings identify a conserved neurometabolic signature linking hippocampal insulin signalling to affective state, and reveal that brain insulin resistance exerts context- and cell-type-specific effects on behaviour. This work establishes a mechanistic basis for brain insulin resistance in depression and highlights the hippocampus as a critical hub for metabolic modulation of mood.

neuroscience↗

Non-invasive measurement of neurotransmitter-specific glucose metabolism in the human brain using proton-observed proton-edited 13C-MRS (POPE13C-MRS)

Non-invasive measurement of neurotransmitter-specific glucose metabolism in the human brain remains a major challenge, limiting mechanistic insight into excitatory-inhibitory imbalance across neurological and psychiatric disorders. Existing approaches either lack neurotransmitter specificity or require specialised hardware that constrains clinical applicability. Here, we introduce proton-observed proton-edited 13C magnetic resonance spectroscopy (POPE13C-MRS), an approach that enables non-invasive detection of glutamate, GABA, and lactate metabolism using standard proton MRI hardware. The method combines administration of 13C-labelled glucose with targeted proton editing to detect 1H-13C satellite resonances. Using a cross-species proof-of-concept approach, we demonstrate consistent detection of neurotransmitter-specific 13C labelling in mice and feasibility in the human brain at ultra-high field. POPE13C-MRS provides a readout of glutamatergic and GABAergic metabolism, enabling in vivo assessment of excitatory-inhibitory metabolic balance. This establishes a means for probing neurometabolic coupling with potential applications in translational and clinical neuroscience.

neuroscience↗

In vivo quantification of creatine kinase kinetics in mouse brain using 31P-MRS at 7 Tesla

31P-MRS is a method of choice for studying neuroenergetics in vivo, but its application in the mouse brain have been limited, often restricted to ultra-high field (>7 Tesla) MRI scanners. Establishing its feasibility on more readily available preclinical 7 Tesla (T) scanners would create new opportunities to study metabolism and physiology in murine models of brain disorders. Here, we demonstrate that the apparent forward rate constant (kf) of creatine kinase (CK) can be accurately quantified using a progressive saturation-transfer approach in the mouse brain at 7T. We also find that a reduction of approximately 20% in the breathing rate of anesthetized mice can lead to a 36% increase in kf attributable to a drop in intracellular pH and mitochondrial ATP production. To achieve this, we used a test-retest analysis to assess the reliability and repeatability of 31P-MRS acquisition, analysis and experimental design protocols. We report that most 31P-containing metabolites can be reliably measured using a localized 3D-ISIS sequence, which showed highest SNR amplitude, SNR consistency and minimal T2 relaxation signal loss. Using this protocol, our study identifies, for the first time, key physiological factors influencing mouse brain energy homeostasis in vivo and provides a methodological basis that will guide future studies interested in implementing 31P-MRS on preclinical 7T scanners.

neuroscience↗

Deletion of Crtc1 leads to hippocampal neuroenergetic impairments associated with depressive-like behavior

Mood disorders (MD) are a major burden on society as their biology remains poorly understood, challenging both diagnosis and therapy. Among many observed biological dysfunctions, homeostatic dysregulation, such as metabolic syndrome (MeS), shows considerable comorbidity with MD. Recently, CREB-regulated transcription coactivator 1 (CRTC1), a regulator of brain metabolism, was proposed as a promising factor to understand this relationship. Searching for imaging biomarkers and associating them with pathophysiological mechanisms using preclinical models, can provide significant insight into these complex psychiatric diseases and help the development of personalized healthcare. Here, we used neuroimaging technologies to show that deletion of Crtc1 in mice leads to an imaging fingerprint of hippocampal metabolic impairment related to depressive-like behavior. By identifying the underlying molecular/physiological origin, we could assign an energy-boosting mood-stabilizing treatment, ebselen, which rescued behavior and neuroimaging markers. Finally, our results point towards the GABAergic system as a potential therapeutic target for behavioral dysfunctions related to metabolic disorders. This study provides new insights on Crtc1s and MeSs relationship to MD and establishes depression-related markers with clinical potential.

neuroscience↗

Metabolic signature in nucleus accumbens for anti-depressant-like effects of acetyl-L-carnitine: An in vivo 1H-magnetic resonance spectroscopy study at 14 T

BackgroundEmerging evidence suggests that hierarchical status may provide vulnerability to develop stress-induced depression. Energy metabolism in the nucleus accumbens (NAc) was recently related to hierarchical status and vulnerability to develop depression-like behavior. Acetyl-L-carnitine (LAC), a mitochondria-boosting supplement, has shown promising antidepressant-like effects opening promising therapeutic strategies for restoring energy balance in depressed patients. Here, we investigated the metabolic impact in the NAc of antidepressant LAC treatment in chronically stressed mice.\n\nMethodMice were characterized for emotional behaviors and social rank. They were then exposed to chronic restraint stress (CRS) for 21 days and subsequently tested in a social behavior (SB) test. A group of mice was also given LAC supplementation during the 7 last CRS days. Mice were then tested in the SB and forced swim tests (FST) and scanned in vivo using 1H-magnetic resonance spectroscopy (1H-MRS) to quantitatively assess the NAc neurochemical profile.\n\nResultsDominant, but not subordinate, mice showed behavioral vulnerability to CRS. In the NAc, dominant mice showed reduced levels of several energy-related metabolites. LAC treatment counteracted stress-induced behavioral changes in dominant mice, and normalized levels of taurine, phosphocreatine, glutamine and phosphocholine in the NAc. No major accumbal metabolic changes were observed in subordinate mice.\n\nConclusionHigh social rank is confirmed as a vulnerability factor to develop chronic stress-induced depressive-like behaviors. We reveal a metabolic signature in the NAc for the antidepressant-like effects of LAC in vulnerable mice, characterized by restoration of stress-induced alterations in neuroenergetics and lipid function.

neuroscience↗