Towards a glutamate hypothesis of depression: an emerging frontier of neuropsychopharmacology for mood disorders.

Stroke survivors are often affected by psychological distress and neuropsychiatric disturbances. About one-third of stroke survivors experience depression, anxiety or apathy, which are the most common neuropsychiatric sequelae of stroke. Neuropsychiatric sequelae are disabling, and can have a negative influence on recovery, reduce quality of life and lead to exhaustion of the caregiver. Despite the availability of screening instruments and effective treatments, neuropsychiatric disturbances attributed to stroke are currently underdiagnosed and undertreated. Stroke severity, stroke-related disabilities, cerebral small vessel disease, previous psychiatric disease, poor coping strategies and unfavourable psychosocial environment influence the presence and severity of the psychiatric sequelae of stroke. Although consistent associations between psychiatric disturbances and specific stroke locations have yet to be confirmed, functional MRI studies are beginning to unveil the anatomical networks that are disrupted in stroke-associated psychiatric disorders. Evidence regarding biochemical and genetic biomarkers for stroke-associated psychiatric disorders is still limited, and better understanding of the biological determinants and pathophysiology of these disorders is needed. Investigation into the management of these conditions must be continued, and should include pilot studies to assess the benefits of innovative behavioural interventions and large-scale cooperative randomized controlled pharmacological trials of drugs that are safe to use in patients with stroke.

Neuropsychiatric sequelae of stroke

The role of NMDA receptors in the pathophysiology and treatment of mood disorders.

Neuropsychiatric manifestations are common post stroke. Depression has a prevalence rate of 9% to 34% in the initial 3 to 6 months following stroke and is the most common neuropsychiatric sequel of stroke. Poststroke depression (PSD) has a significant adverse impact on the course of rehabilitation following stroke, resulting in overall impaired functional outcome. An increased risk of suicide and increased mortality have been reported. The association of depression and stroke is well established, highly complex, and multifactorial in origin, and the etiology of PSD involves size, location and number of lesions, stroke subtype, stroke severity, social handicap, and family support. Additionally, depression itself is an independent risk factor for stroke. In this article, we review the complex pathogenesis of PSD and summarize pharmacological treatment options. Because of recent important results that may relate to underlying cellular restorative processes, we focus on early prophylactic treatment, particularly as it involves selective serotonin uptake inhibitors (SSRIs). There is a recently recognized synergy between functional recovery and depression prophylaxis. New evidence that antidepressants, and SSRIs in particular, can make a substantial contribution to stroke recovery is explored.

Poststroke Depression: A Review Emphasizing the Role of Prophylactic Treatment and Synergy with Treatment for Motor Recovery

Plasma levels of glutamate during stroke is associated with development of post-stroke depression.

In recent studies, the glutamate (Glu) level has been quantified using the modified STEAM sequence on 3T MRI. We enrolled 15 healthy volunteers and a group of 51 patients who experienced stroke for the first time and had a good prognosis. The patients with infarction were divided into three groups according to their scores by using the DSM-IV diagnostic criteria for major depressive disorder and the 17-item Hamilton Depression Rating Scale (HDRS). We studied the association between post-stroke depression and 1H-MRS measurements in unaffected frontal lobes. Single-voxel proton magnetic resonance spectroscopy (1H-MRS) was performed to assess N-acetylaspartate/creatine (NAA)/Cr, (Glu)/Cr, choline (Cho)/Cr, and myoinositol (mI)/Cr ratios in stroke patients. The 11 patients (21.5%) who met the criteria for depression and 9 patients (17.6%) who had a high score for HDRS, (>14) but were not depressed, had a significantly higher Glu/Cr ratio than patients who scored ≤14 on HDRS and control groups (p < 0.001). No differences were found in NAA/Cr, Cho/Cr, or mI/Cr between the groups after stroke. These findings suggest that post-stroke depression is accompanied by changes in glutamate levels in the frontal lobe.

Glutamate level detection by magnetic resonance spectroscopy in patients with post-stroke depression

Metabolites are important biomarkers in human body fluids, conveying direct information of cellular activities and physical conditions. Metabolite detection has long been a research hotspot in the field of biology and medicine. Surface-enhanced Raman spectroscopy (SERS), based on the molecular "fingerprint" of Raman spectrum and the enormous signal enhancement (down to a single-molecule level) by plasmonic nanomaterials, has proven to be a novel and powerful tool for metabolite detection. SERS provides favorable properties such as ultra-sensitive, label-free, rapid, specific, and non-destructive detection processes. In this review, we summarized the progress in recent 10 years on SERS-based sensing of endogenous metabolites at the cellular level, in tissues, and in biofluids, as well as drug metabolites in biofluids. We made detailed discussions on the challenges and optimization methods of SERS technique in metabolite detection. The combination of SERS with modern biomedical technology were also anticipated. 

https://doi.org/10.1016/j.mtbio.2022.100205

Human metabolite detection by surface-enhanced Raman spectroscopy

Accurate diagnosis of cancer subtypes is a great guide for the development of surgical plans and prognosis in the clinic. Raman spectroscopy, combined with the machine learning algorithm, has been demonstrated to be a powerful tool for tumor identification. However, the analysis and classification of Raman spectra for biological samples with complex compositions are still challenges. In addition, the signal-to-noise ratio of the spectra also influences the accuracy of the classification. Herein, we applied the variational autoencoder (VAE) to Raman spectra for downscaling and noise reduction simultaneously. We validated the performance of the VAE algorithm at the cellular and tissue levels. VAE successfully downscaled high-dimensional Raman spectral data to two-dimensional (2D) data for three subtypes of non-small cell lung cancer cells and two subtypes of kidney cancer tissues. Gaussian naïve bayes was applied to subtype discrimination with the 2D data after VAE encoding at both the cellular and tissue levels, significantly outperforming the discrimination results using original spectra. Therefore, the analysis of Raman spectroscopy based on VAE and machine learning has great potential for rapid diagnosis of tumor subtypes.

Accurate Tumor Subtype Detection with Raman Spectroscopy via Variational Autoencoder and Machine Learning

Accurate and effective tumor diagnosis, detection, and treatment are key for improving the survival rates of patients. Chimeric antigen receptor T (CAR-T) cell therapy has shown remarkable clinical success in eradicating hematologic malignancies. However, the hostile microenvironment in solid tumors severely prevents CAR-T cells from migrating and from infiltrating and killing malignant cells. Tumor microenvironment modulation strategies have attracted much attention in the field of cancer immunotherapy. Multifunctional nanoplatforms that integrate the advantages of different therapeutic techniques can allow for the multimodal synergistic treatment of tumors. In this study, a biocompatible, tumor-targeting, on-demand approach combining CAR-T cell immunotherapy and a chemo-photothermal therapy nanoplatform (FA-Gd-GERTs@Ibrutinib) based on gadolinium-loaded gap-enhanced Raman tags (Gd-GERTs) has been developed for multimodal imaging, and it provides a reliable treatment strategy for solid tumor immunotherapy via microenvironment reconstruction. In our study, folate (FA) receptor targeted molecules are used to improve the accuracy and sensitivity of computed tomography/magnetic resonance/Raman multimodal tumor imaging. The photothermal effect of the nanoprobe can promote the angiogenesis of lymphoma tissue, destroy the extracellular matrix, loosen compact tissue, stimulate chemokine secretion, and effectively enhance the infiltration ability in the case of non-Hodgkin's lymphoma, without dampening the CD19 CAR-T cell activity. The treatment results in tumor-bearing mice proved the existence of excellent synergistic therapy; photothermal therapy improves the accumulation and effector function of CAR-T cells within solid tumors. It is believed that multifunctional nanomaterials with targeted multi-modal imaging capabilities that support combination therapy can provide an efficient route for accurate diagnosis and efficient treatment.

Multifunctional theranostic nanoparticles for multi-modal imaging-guided CAR-T immunotherapy and chemo-photothermal combinational therapy of non-Hodgkin's lymphoma.

Surface-enhanced Raman scattering (SERS) nanoprobes have attracted particular interests in the field of bioimaging owing to their high sensitivity and specificity of the fingerprint spectrum. However, the limited signal-to-background ratio (SBR) in SERS imaging and the requirement to perform imaging in a dark environment have largely hindered its biomedical application. To circumvent this, we have developed a type of bio-orthogonal nanoprobes for SERS imaging with an ultrahigh SBR and ambient light anti-interference ability. The core-shell nanoprobes exhibit strongly enhanced Raman signals and depress the background from photoluminescence of metallic nanoparticles by off-resonance excitation and from the Raman scattering and auto-fluorescence of tissues by near-infrared laser excitation. Such nanoprobes have achieved an SBR of over 100 in SERS bioimaging, 5 times higher than the traditional on-resonant nanoprobes, and their bio-orthogonal signal in the Raman-silent region renders the anti-interference capability under ambient light. The development of these SERS probes opens up a new era for the future applications of Raman imaging in clinical medicine.

Jian-Lin Ye

Papers

Glutamate level detection by magnetic resonance spectroscopy in patients with post-stroke depression

Human metabolite detection by surface-enhanced Raman spectroscopy

Accurate Tumor Subtype Detection with Raman Spectroscopy via Variational Autoencoder and Machine Learning

Multifunctional theranostic nanoparticles for multi-modal imaging-guided CAR-T immunotherapy and chemo-photothermal combinational therapy of non-Hodgkin's lymphoma.

Surface-Enhanced Raman Scattering Bioimaging with an Ultrahigh Signal-to-Background Ratio under Ambient Light.