Amino acid metabolism in glioma: in vivo MR-spectroscopic detection of alanine as a potential biomarker of poor survival in glioma patients.

PURPOSE: Reprogramming of amino acid metabolism is relevant for initiating and fueling tumor formation and growth. Therefore, there has been growing interest in anticancer therapies targeting amino acid metabolism. While developing personalized therapeutic approaches to glioma, in vivo proton magnetic resonance spectroscopy (MRS) is a valuable tool for non-invasive monitoring of tumor metabolism. Here, we evaluated MRS-detected brain amino acids and myo-inositol as potential diagnostic and prognostic biomarkers in glioma. METHOD: We measured alanine, glycine, glutamate, glutamine, and myo-inositol in 38 patients with MRI-suspected glioma using short and long echo-time single-voxel PRESS MRS sequences. The detectability of alanine, glycine, and myo-inositol and the (glutamate + glutamine)/total creatine ratio were evaluated against the patients' IDH mutation status, CNS WHO grade, and overall survival. RESULTS: While the detection of alanine and non-detection of myo-inositol significantly correlated with IDH wildtype (p = 0.0008, p = 0.007, respectively) and WHO grade 4 (p = 0.01, p = 0.04, respectively), glycine detection was not significantly associated with either. The ratio of (glutamate + glutamine)/total creatine was significantly higher in WHO grade 4 than in 2 and 3. We found that the overall survival was significantly shorter in glioma patients with alanine detection (p = 0.00002). CONCLUSION: Focusing on amino acids in MRS can improve its diagnostic and prognostic value in glioma. Alanine, which is visible at long TE even in the presence of lipids, could be a relevant indicator for overall survival.

Emerging Role of Functional Magnetic Resonance Spectroscopy (MRS) to Monitor Response to Kinase Inhibitors in Cancer.

Inhibitors of kinases involved in signaling and other intracellular pathways, have revolutionized cancer treatment by providing highly targeted and effective therapies. However, timely monitoring treatment response remains a considerable challenge since conventional methods such as assessing changes in tumor volume do not adequately capture early responses or resistance development, due to the predominantly cytostatic rather than cytotoxic effect of kinase inhibitors. Magnetic resonance spectroscopy (MRS) is a non-invasive imaging technique that can provide insights into cellular metabolism by detecting changes in metabolite concentrations. By measuring metabolite levels, MRS offers a means to assess treatment response in real-time, providing earlier indications of efficacy or resistance compared to conventional imaging modalities. Bruton's Tyrosine Kinase (BTK) is a critical enzyme involved in B-cell receptor signaling. BTK inhibitors have been approved for the treatment of Mantle Cell Lymphoma (MCL) and other B-cell malignancies. Recent studies involving genome-scale gene expression, metabolomic, and fluxomic analyses have demonstrated that ibrutinib, an index BTK inhibitor, profoundly affects the key metabolic pathways in MCL cells., including glycolysis, glutaminolysis, pentose shunt, TCA cycle and phospholipid metabolism. Importantly, the effects of ibrutinib on MCL cells directly and proportionately correlates with their sensitivity to the drug. Consequently, changes in specific metabolite concentrations detectable non-invasively by MRS such as lactate and alanine reflecting mostly the status of cellular glycolysis and glutaminolysis, respectively, have emerged as potential biomarkers for predicting response and resistance of MCL cells to BTK inhibition, both in vitro and in vivo. Preparations to validate the utility of these biomarkers in clinical setting are under way. These studies may pave the way to monitor therapeutic response to kinase inhibitors also in other types of cancer.

Improvements in precision and accuracy of complex- relative to real-domain linear combination model spectral fitting not necessarily recovered by zero filling.

Although the information obtained from in vivo proton magnetic resonance spectroscopy (1H MRS) presents a complex-valued spectrum, spectral quantification generally employs linear combination model (LCM) fitting using the real spectrum alone. There is currently no known investigation comparing fit results obtained from LCM fitting over the full complex data versus the real data and how these results might be affected by common spectral preprocessing procedure zero filling. Here, we employ linear combination modeling of simulated and measured spectral data to examine two major ideas: first, whether use of the full complex rather than real-only data can provide improvements in quantification by linear combination modeling and, second, to what extent zero filling might influence these improvements. We examine these questions by evaluating the errors of linear combination model fits in the complex versus real domains against three classes of synthetic data: simulated Lorentzian singlets, simulated metabolite spectra excluding the baseline, and simulated metabolite spectra including measured in vivo baselines. We observed that complex fitting provides consistent improvements in fit accuracy and precision across all three data types. While zero filling obviates the accuracy and precision benefit of complex fitting for Lorentzian singlets and metabolite spectra lacking baselines, it does not necessarily do so for complex spectra including measured in vivo baselines. Overall, performing linear combination modeling in the complex domain can improve metabolite quantification accuracy relative to real fits alone. While this benefit can be similarly achieved via zero filling for some spectra with flat baselines, this is not invariably the case for all baseline types exhibited by measured in vivo data.

The Impact of MRI-Based Advanced Neuroimaging on Neurooncologists' Clinical Decision-Making in Patients With Posttreatment High-Grade Glioma: A Prospective Survey-Based Study.

Background: Advanced MRI-based neuroimaging techniques, such as perfusion and spectroscopy, have been increasingly incorporated into routine follow-up protocols in patients treated for high-grade glioma (HGG), to help differentiate tumor progression from treatment effect. However, these techniques' influence on clinical management remains poorly understood. Objective: To evaluate the impact of MRI-based advanced neuroimaging on clinical decision-making in patients with HGG in the posttreatment setting. Methods: This prospective study, performed at a comprehensive cancer center from March 1, 2017, to October 31, 2020, included adult patients treated by chemoradiation for WHO grade 4 diffuse glioma who underwent MRIbased advanced neuroimaging (comprising multiple perfusion imaging sequences and spectroscopy) to further evaluate findings on conventional MRI equivocal for tumor progression versus treatment effect. The ordering neuro-oncologists completed surveys before and after each advanced neuroimaging session. The percent of care episodes with a change between the intended and actual management plan on the surveys conducted before and after advanced neuroimaging, respectively, was computed and compared with a previously published percent using the Wald test for independent samples proportions. Results: The study included 63 patients (mean age, 55±13 years; 36 women, 27 men) who underwent 70 advanced neuroimaging sessions. Ordering neuro-oncologists' intended and actual management plans on the surveys completed before and after advanced neuroimaging, respectively, differed in 44% (31/70, [95% CI: 33-56%]) of episodes, which differed from the previously published frequency of 8.5% (5/59) (p<.001). These management plan changes included selection of a different plan for 6/8 episodes with an intended plan to enroll patients in a clinical trial, 12/19 episodes with an intended plan to change chemotherapeutic agents, 4/8 episodes with an intended plan of surgical intervention, and 1/2 episodes with an intended plan of re-irradiation. The ordering neuro-oncologists found advanced neuroimaging to be helpful in 93% (95% CI: 87%-99%) (65/70) of episodes. Conclusion: Neuro-oncologists' management plans changed in a substantial fraction of adult patients with HGG who underwent advanced neuroimaging to further evaluate conventional MRI findings equivocal for tumor progression versus treatment effect. Clinical Impact: The findings support incorporation of advanced neuroimaging into HGG posttreatment monitoring protocols.

Brain metabolites are associated with sleep architecture and cognitive functioning in older adults.

Sleep deficits are a possible risk factor for development of cognitive decline and dementia in older age. Research suggests that neuroinflammation may be a link between the two. This observational, cross-sectional study evaluated relationships between sleep architecture, neuroinflammation and cognitive functioning in healthy older adults. Twenty-two adults aged ≥60 years underwent whole-brain magnetic resonance spectroscopic imaging (in vivo method of visualizing increased brain temperatures as a proxy for neuroinflammation), supervised laboratory-based polysomnography, and comprehensive neurocognitive testing. Multiple regressions were used to assess relationships between magnetic resonance spectroscopic imaging-derived brain temperature and metabolites related to inflammation (choline; myo-inositol; N-acetylaspartate), sleep efficiency, time and % N3 sleep and cognitive performance. Choline, myo-inositol and N-acetylaspartate were associated with sleep efficiency and cognitive performance. Higher choline and myo-inositol in the bilateral frontal lobes were associated with slower processing speed and lower sleep efficiency. Higher choline and myo-inositol in bilateral frontoparietal regions were associated with better cognitive performance. Higher N-acetylaspartate around the temporoparietal junction and adjacent white matter was associated with better visuospatial function. Brain temperature was not related to cognitive or sleep outcomes. Our findings are consistent with the limited literature regarding neuroinflammation and its relationships with sleep and cognition in older age, which has implicated ageing microglia and astrocytes in circadian dysregulation, impaired glymphatic clearance and increased blood-brain barrier integrity, with downstream effects of neurodegeneration and cognitive decline. Inflammatory processes remain difficult to measure in the clinical setting, but magnetic resonance spectroscopic imaging may serve as a marker of the relationship between neuroinflammation, sleep and cognitive decline in older adults.

Exercise-induced changes in intramuscular total creatine concentration measured with 1H magnetic resonance spectroscopy: A pilot study.

Total amount of creatine (Cr) and phosphocreatine, or total creatine (tCr), may have a significant impact on the performance of skeletal muscles. In sports such as bodybuilding, it is popular to take Cr supplements to maintain tCr level. However, no study has explored the quantitative relationship between exercise intensity and the induced change in muscle's tCr. In this well-controlled study, straight-leg plantar flexion with specific load and duration was performed by 10 healthy subjects inside an MRI scanner, immediately followed by 1H MR spectroscopy (MRS) for measuring tCr concentration in gastrocnemius. For repeatability assessment, the experiment was repeated for each subject on two different days. Across all the subjects, baseline tCr was 46.6 ± 2.4 mM, ranging from 40.6 to 50.1 mM; with exercise, tCr significantly decreased by 10.9% ± 1.0% with 6-lb load and 21.0% ± 1.3% with 12-lb load (p < 0.0001). Between two different days, baseline tCr, percentage decrease induced by exercise with a 6-lb and 12-lb load differed by 2.2% ± 2.3%, 11.7% ± 6.0% and 4.9% ± 3.2%, respectively. In conclusion, the proposed protocol of controlled exercise stimulation and MRS acquisition can reproducibly monitor tCr level and its exercise-induced change in skeletal muscles. The measured tCr level is sensitive to exercise intensity, so can be used to quantitatively assess muscle performance or fatigue.

Multimodal investigation of neuropathology and neurometabolites in mild cognitive impairment and late-life depression with 11C-PiB beta-amyloid PET and 7T magnetic resonance spectroscopy.

Positron emission tomography (PET) and magnetic resonance spectroscopy (1H-MRS) are complementary techniques that can be applied to study how proteinopathy and neurometabolism relate to cognitive deficits in preclinical stages of Alzheimer's disease (AD)-mild cognitive impairment (MCI) and late-life depression (LLD). We acquired beta-amyloid (Aß) PET and 7 T 1H-MRS measures of GABA, glutamate, glutathione, N-acetylaspartate, N-acetylaspartylglutamate, myo-inositol, choline, and lactate in the anterior and posterior cingulate cortices (ACC, PCC) in 13 MCI and 9 LLD patients, and 13 controls. We used linear regression to examine associations between metabolites, Aß, and cognitive scores, and whether metabolites and Aß explained cognitive scores better than Aß alone. In the ACC, higher Aß was associated with lower GABA in controls but not MCI or LLD patients, but results depended upon MRS data quality control criteria. Greater variance in California Verbal Learning Test scores was better explained by a model that combined ACC glutamate and Aß deposition than by models that only included one of these variables. These findings identify preliminary associations between Aß, neurometabolites, and cognition.

Metabolic signatures derived from whole-brain MR-spectroscopy identify early tumor progression in high-grade gliomas using machine learning.

PURPOSE: Recurrence for high-grade gliomas is inevitable despite maximal safe resection and adjuvant chemoradiation, and current imaging techniques fall short in predicting future progression. However, we introduce a novel whole-brain magnetic resonance spectroscopy (WB-MRS) protocol that delves into the intricacies of tumor microenvironments, offering a comprehensive understanding of glioma progression to inform expectant surgical and adjuvant intervention. METHODS: We investigated five locoregional tumor metabolites in a post-treatment population and applied machine learning (ML) techniques to analyze key relationships within seven regions of interest: contralateral normal-appearing white matter (NAWM), fluid-attenuated inversion recovery (FLAIR), contrast-enhancing tumor at time of WB-MRS (Tumor), areas of future recurrence (AFR), whole-brain healthy (WBH), non-progressive FLAIR (NPF), and progressive FLAIR (PF). Five supervised ML classification models and a neural network were developed, optimized, trained, tested, and validated. Lastly, a web application was developed to host our novel calculator, the Miami Glioma Prediction Map (MGPM), for open-source interaction. RESULTS: Sixteen patients with histopathological confirmation of high-grade glioma prior to WB-MRS were included in this study, totaling 118,922 whole-brain voxels. ML models successfully differentiated normal-appearing white matter from tumor and future progression. Notably, the highest performing ML model predicted glioma progression within fluid-attenuated inversion recovery (FLAIR) signal in the post-treatment setting (mean AUC = 0.86), with Cho/Cr as the most important feature. CONCLUSIONS: This study marks a significant milestone as the first of its kind to unveil radiographic occult glioma progression in post-treatment gliomas within 8 months of discovery. These findings underscore the utility of ML-based WB-MRS growth predictions, presenting a promising avenue for the guidance of early treatment decision-making. This research represents a crucial advancement in predicting the timing and location of glioblastoma recurrence, which can inform treatment decisions to improve patient outcomes.

A crisis awareness chain warning management model for patients with difficulties cooperating with magnetic resonance examinations.

OBJECTIVE: This case-control study tested a crisis awareness-based chain warning management model for patients with difficulties cooperating with magnetic resonance imaging (MRI) examinations. METHODS: All participants experienced difficulties cooperating with MRI examinations and underwent cranial magnetic resonance spectroscopy (MRS) and MRI at the same hospital in China. The control group (n = 1233) underwent examinations from January to June 2023 and received routine nursing care (pre-examination safety notification, instructions on cooperating during the examination, post-examination observation). A crisis awareness chain warning management model was implemented for the intervention group (n = 1352), who underwent examinations from July to December 2023. The groups were compared on average time for examination completion, quality of care and occurrence of complications. Data were collected using a self-devised data collection form. RESULTS: The average length of time to complete MRS and MRI was shorter for intervention group patients than for control group patients. The intervention group showed better pre-examination preparation, examination success rate, image quality attainment rate, and one-time examination success rate, and lower incidence of examination-related complications. CONCLUSION: This management model could increase MRI examination efficiency, improve quality of care, reduce complications and increase nurses' understanding of nursing continuity and crisis awareness.

Metabolite profile in hereditary spastic paraplegia analyzed using magnetic resonance spectroscopy: a cross-sectional analysis in a longitudinal study.

Background: Hereditary Spastic Paraplegias (HSP) are genetic neurodegenerative disorders affecting the corticospinal tract. No established neuroimaging biomarker is associated with this condition. Methods: A total of 46 patients affected by HSP, genetically and clinically evaluated and tested with SPRS scores, and 46 healthy controls (HC) matched by age and gender underwent a single-voxel Magnetic Resonance Spectroscopy sampling (MRS) of bilateral pre-central and pre-frontal regions. MRS data were analyzed cross-sectionally (at T0 and T1) and longitudinally (T0 vs. T1). Results: Statistically significant data showed that T0 mI/Cr in the pre-central areas of HSP patients was higher than in HC. In the left (L) pre-central area, NAA/Cr was significantly lower in HSP than in HC. In the right (R) pre-frontal area, NAA/Cr was significantly lower in HSP patients than in HC. HSP SPG4 subjects had significantly lower Cho/Cr concentrations in the L pre-central area compared to HC. Among the HSP subjects, non-SPG4 patients had significantly higher mI/Cr in the L pre-central area compared to SPG4 patients. In the R pre-frontal area, NAA/Cr was reduced, and ml/Cr was higher in non-SPG4 patients compared to SPG4 patients. Comparing "pure" and "complex" forms, NAA/Cr was higher in pHSP than in cHSP in the R pre-central and R pre-frontal areas. The longitudinal analysis, which involved fewer patients (n = 30), showed an increase in mI/Cr concentration in the L pre-frontal area among HSP subjects with respect to baseline. The patients had significantly higher SPRS scores at follow-up, with a significant positive correlation between SPRS scores and mI/Cr in the L pre-central area, while in bilateral pre-frontal areas, lower SPRS scores corresponded to higher NAA/Cr concentrations. To explore the discriminating power of MRS in correctly identifying HSP and controls, an inference tree methodology classified HSP subjects and controls with an overall accuracy of 73.9%, a sensitivity of 87.0%, and a specificity of 60.9%. Conclusion: This pilot study indicates that brain MRS is a valuable approach that could potentially serve as an objective biomarker in HSP.

Whole-Heart Histological and Electroanatomic Assessment of Postinfarction Cardiac Magnetic Resonance Imaging Scar and Conducting Channels.

BACKGROUND: Cardiac magnetic resonance imaging (CMR)-defined ventricular scar and anatomic conduction channels (CMR-CCs) offer promise in delineating ventricular tachycardia substrate. No studies have validated channels with coregistered histology, nor have they ascertained the histological characteristics of deceleration zones (DZs) within these channels. We aimed to validate CMR scar and CMR-CCs with whole-heart histology and electroanatomic mapping in a postinfarction model. METHODS: Five sheep underwent anteroseptal infarction. CMR (116±20 days post infarct) was postprocessed using ADAS-3-dimensional, varying pixel intensity thresholds (5545, 6040, 6535, and 7030). DZs were identified by electroanatomic mapping (129±12 days post infarct). Explanted hearts were sectioned and stained with Picrosirius red, and whole-heart histopathologic shells were generated. Scar topography as well as percentage fibrosis, adiposity, and remaining viable myocardium within 3 mm histological biopsies and within CMR-CCs were determined. RESULTS: Using the standard 6040 thresholding, CMR had 83.8% accuracy for identifying histological scar in the endocardium (κ, 0.666) and 61.4% in the epicardium (κ, 0.276). Thirty-seven CMR-CCs were identified by varying thresholding; 23 (62%) were unique. DZs colocalized to 19 of 23 (83%) CMR-CCs. Twenty (87%) CMR-CCs were histologically confirmed. Within-channel histological fibrosis did not differ by the presence of DZs (P=0.242). Within-channel histological adiposity was significantly higher at sites with versus without DZs (24.1% versus 8.3%; P<0.001). CONCLUSIONS: Postprocessed CMR-derived scars and channels were validated by histology and electroanatomic mapping. Regions of CMR-CCs at sites of DZs had higher adiposity but similar fibrosis than regions without DZs, suggesting that lipomatous metaplasia may contribute to arrhythmogenicity of postinfarction scar.

On the impact of B0 shimming algorithms on single-voxel MR spectroscopy.

PURPOSE: To assess the impact of different B0 shimming algorithms on MRS. METHODS: B0 field maps and single-voxel MR spectroscopy were acquired in the prefrontal cortex of five volunteers at 3 T using five different B0 shimming approaches. B0 shimming was achieved using Siemens' proprietary shim algorithm, in addition to the Pseudo-Inverse (PI), Quadratic Programming (QuadProg), Least Squares (LSq), and Gradient optimization (Grad) algorithms. The standard deviation of the shimmed B0 field, as well as the SNR and FWHM of the measured metabolites, was used to evaluate the performance of each B0 shimming algorithm. RESULTS: Compared to Siemens's shim, significant reductions (p < 0.01) in the standard deviation of the B0 field distribution within the MRS voxel were observed for the PI, QuadProg, and Grad algorithms (3.8 Hz, 7.3 Hz, and 3.9 Hz respectively, compared to 11.5 Hz for Siemens), but not for the LSq (12.9 Hz) algorithm. Moreover, significantly increased SNR and reduced FWHM for the N-acetylaspartate metabolite were consistent with the improvement in B0 homogeneity for the aforementioned shimming algorithms. CONCLUSION: Here, we demonstrate that the choice of B0 shimming algorithm can have a significant impact on the quality of MR spectra and that significant improvements in spectrum quality could be achieved by using alternatives to the default vendor approach.

Lipidomics by Nuclear Magnetic Resonance Spectroscopy and Liquid Chromatography-High-Resolution Mass Spectrometry in Osteosarcoma: A Pilot Study.

Cancer is a complex disease that can also affect the younger population; however, it is responsible for a relatively high mortality rate of children and youth, especially in low- and middle-income countries (LMICs). Besides that, lipidomic studies in this age range are scarce. Therefore, we analyzed blood serum samples from young patients (12 to 35 years) with bone sarcoma (osteosarcoma) and compared their lipidomics to the ones from the control group of samples, named healthy control (HC group), using NMR and LC-MS techniques. Furthermore, differences in the lipidomic profiles between OS patients with and without metastasis indicate higher glycerophosphocholine (GPC) and glycerophospholipid (GPL) levels in osteosarcoma and increased cholesterol, choline, polyunsaturated fatty acids (PUFAs), and glycerols during the metastasis. These differences, detected in the peripheral blood, could be used as biomarkers for liquid biopsy.

Saliva and plasma metabolome changes during anoestrus, the oestrous cycle and early gestation in the mare: A pilot study.

Successful reproductive management of domestic mammals depends primarily upon timely identification of oestrous cycle stages. There is a need to develop an alternative non-invasive, welfare-friendly, accurate and reliable method to identify reproductive cycle stages. This is of particular interest for horse breeders, because horses are high-value farm animals that require careful management and individual monitoring. Saliva sampling is non-invasive, painless and welfare-friendly. Thus, we performed a metabolomic analysis of equine saliva during different reproductive stages to identify changes in the salivary metabolome during anoestrus, the oestrous cycle and early gestation. We compared the saliva and plasma metabolomes to investigate the relationship between the two fluids according to the physiological stage. We collected saliva and plasma samples from six mares during seasonal anoestrus, during the follicular phase 3 days, 2 days and 1 day before ovulation and the day when ovulation was detected, during the luteal phase 6 days after ovulation, and during early gestation 18 days after ovulation and insemination. Metabolome analysis was performed by proton-nuclear magnetic resonance spectroscopy. We identified 58 and 51 metabolites in saliva and plasma, respectively. The levels of four metabolites or groups of metabolites in saliva and five metabolites or groups of metabolites in plasma showed significant modifications during the 4 days until ovulation, ie 3 days prior to and on the day of ovulation. The levels of 11 metabolites or groups of metabolites in saliva and 17 metabolites or groups of metabolites in plasma were significantly different between the seasonal anoestrus and the ovarian cyclicity period. The physiological mechanisms involved in the onset of ovarian cyclicity and in ovulation induced modifications of the metabolome both in plasma and saliva. The metabolites whose salivary levels changed during the reproductive cycle could be potential salivary biomarkers to detect the reproductive stage in a welfare friendly production system. In particular, we propose creatine and alanine as candidate salivary biomarkers of ovulation and of the onset of ovarian cyclicity, respectively. However, extensive validation of their reliability is required. Our study contributes to extend to domestic mammals the use of saliva as a non-invasive alternative diagnostic fluid for reproduction in a welfare-friendly production system.

Evidence for S331-G-S-L within the amyloid core of myocilin olfactomedin domain fibrils based on low-resolution 3D solid-state NMR spectra.

Myocilin-associated glaucoma is a protein-conformational disorder associated with formation of a toxic amyloid-like aggregate. Numerous destabilizing single point variants, distributed across the myocilin olfactomedin ß-propeller (OLF, myocilin residues 245-504, 30 kDa) are associated with accelerated disease progression. In vitro, wild type (WT) OLF can be promoted to form thioflavin T (ThT)-positive fibrils under mildly destabilizing (37°C, pH 7.2) conditions. Consistent with the notion that only a small number of residues within a protein are responsible for amyloid formation, 3D 13C-13C solid-state NMR spectra show that OLF fibrils are likely to be composed of only about one third of the overall sequence. Here, we probe the residue composition of fibrils formed de novo from purified full-length OLF. We were able to make sequential assignments consistent with the sequence S331-G-S-L334. This sequence appears once within a previously identified amyloid-prone region (P1, G326AVVYSGSLYFQ) internal to OLF. Since nearly half of the pairs of adjacent residues (di-peptides) in OLF occur only once in the primary structure and almost all the 3-residue sequences (tri-peptides) are unique, remarkably few sequential assignments are necessary to uniquely identify specific regions of the amyloid core. This assignment approach could be applied to other systems to expand our molecular comprehension of how folded proteins undergo fibrillization.

Diffusion magnetic resonance spectroscopy captures microglial reactivity related to gut-derived systemic lipopolysaccharide: A preliminary study.

Neuroinflammation is a key component underlying multiple neurological disorders, yet non-invasive and cost-effective assessment of in vivo neuroinflammatory processes in the central nervous system remains challenging. Diffusion weighted magnetic resonance spectroscopy (dMRS) has shown promise in addressing these challenges by measuring diffusivity properties of different neurometabolites, which can reflect cell-specific morphologies. Prior work has demonstrated dMRS utility in capturing microglial reactivity in the context of lipopolysaccharide (LPS) challenges and serious neurological disorders, detected as changes of microglial metabolite diffusivity properties. However, the extent to which such dMRS metrics are capable of detecting subtler and more nuanced levels of neuroinflammation in populations without overt neuropathology is unknown. Here we examined the relationship between intrinsic, gut-derived levels of systemic LPS and dMRS-based apparent diffusion coefficients (ADC) of choline, creatine, and N-acetylaspartate (NAA) in two brain regions: the thalamus and the corona radiata. Higher plasma LPS concentrations were significantly associated with increased ADC of choline and NAA in the thalamic region, with no such relationships observed in the corona radiata for any of the metabolites examined. As such, dMRS may have the sensitivity to measure microglial reactivity across populations with highly variable levels of neuroinflammation, and holds promising potential for widespread applications in both research and clinical settings.

Maternal prenatal immune activation associated with brain tissue microstructure and metabolite concentrations in newborn infants.

Few human studies have assessed the association of prenatal maternal immune activation (MIA) with measures of brain development and psychiatric risk in newborn offspring. Our goal was to identify the effects of MIA during the 2nd and 3rd trimesters of pregnancy on newborn measures of brain metabolite concentrations, tissue microstructure, and motor development. This was a prospective longitudinal cohort study conducted with nulliparous pregnant women who were aged 14 to 19 years and recruited in their 2nd trimester, as well as their children who were followed through 14 months of age. MIA was indexed by maternal interleukin-6 (IL-6) and C-reactive protein (CRP) in both trimesters of pregnancy. Primary outcomes included: (1) newborn brain metabolite concentrations as ratios to creatine (N-acetylaspartate (NAA)/creatine (Cr) and choline (Cho)/Cr) measured using Magnetic Resonance Spectroscopy; (2) newborn fractional anisotropy and mean diffusivity, measured using Diffusion Tensor Imaging; and (3) indices of motor development, assessed prenatally and postnatally at ages 4- and 14-months. Maternal IL-6 and CRP levels associated significantly with both metabolites in the putamen, thalamus, insula, and the internal capsule. Maternal IL-6 associated significantly with fractional anisotropy in the putamen, caudate, thalamus, insula, and precuneus, and with mean diffusivity in the inferior parietal and middle temporal gyrus. CRP associated significantly with fractional anisotropy in the thalamus, insula, and putamen. Significant associations were found in common regions across imaging modalities, though the direction of associations differed by immune marker. In addition, both maternal IL-6 and CRP (in both trimesters) prenatally associated significantly with offspring motor development at 4- and 14-months of age. The left thalamus mediated effects of IL-6 on postnatal motor development. These findings demonstrate that levels of MIA in mid- to late pregnancy in a generally healthy sample associate with tissue characteristics in newborn brain regions that primarily support motor integration and coordination, as well as behavioral regulation. Those brain effects may contribute to differences in motor development.

Endometrial cancer risk stratification using MRI radiomics: corroborating with choline metabolism.

BACKGROUND AND PURPOSE: Radiomics offers little explainability. This study aims to develop a radiomics model (Rad-Score) using diffusion-weighted imaging (DWI) to predict high-risk patients for nodal metastasis or recurrence in endometrial cancer (EC) and corroborate with choline metabolism. MATERIALS AND METHODS: From August 2015 to July 2018, 356 EC patients were enrolled. Rad-Score was developed using LASSO regression in a training cohort (n = 287) and validated in an independent test cohort (n = 69). MR spectroscopy (MRS) was also used in 230 patients. Nuclear MRS measured choline metabolites in 70 tissue samples. The performance was compared against European Society for Medical Oncology (ESMO) risk groups. A P < .05 denoted statistical significance. RESULTS: Rad-Score achieved 71.1% accuracy in the training and 71.0% in the testing cohorts. Incorporating clinical parameters of age, tumor type, size, and grade, Rad-Signature reached accuracies of 73.2% in training and 75.4% in testing cohorts, closely matching the performance to the post-operatively based ESMO's 70.7% and 78.3%. Rad-Score was significantly associated with increased total choline levels on MRS (P = .034) and tissue levels (P = .019). CONCLUSIONS: Development of a preoperative radiomics risk score, comparable to ESMO clinical standard and associated with altered choline metabolism, shows translational relevance for radiomics in high-risk EC patients. TRIAL REGISTRATION: This study was registered in ClinicalTrials.gov on 2015-08-01 with Identifier NCT02528864.

Natural Products Dereplication: Databases and Analytical Methods.

The development of efficient methods for dereplication has been critical in the re-emergence of the research in natural products as a source of drug leads. Current dereplication workflows rapidly identify already known bioactive secondary metabolites in the early stages of any drug discovery screening campaign based on natural extracts or enriched fractions. Two main factors have driven the evolution of natural products dereplication over the last decades. First, the availability of both commercial and public large databases of natural products containing the key annotations against which the biological and chemical data derived from the studied sample are searched for. Second, the considerable improvement achieved in analytical technologies (including instrumentation and software tools) employed to obtain robust and precise chemical information (particularly spectroscopic signatures) on the compounds present in the bioactive natural product samples. This chapter describes the main methods of dereplication, which rely on the combined use of large natural product databases and spectral libraries, alongside the information obtained from chromatographic, UV-Vis, MS, and NMR spectroscopic analyses of the samples of interest.

Lower distress intolerance is associated with higher glutathione levels in adolescent cannabis users.

Cannabis (CB) use and psychological stressors increase oxidative stress in the brain. Glutathione (GSH), the most abundant antioxidant in the brain, protects against oxidative stress. Furthermore, distress intolerance, the inability to tolerate psychological or physiological stress is a risk factor for CB use. The relationship between CB use, brain GSH levels and distress intolerance remains unknown. Therefore, we examined GSH levels in the anterior cingulate cortex (ACC), as a measure of oxidative stress, and its relationship with distress intolerance in adolescent CB users and healthy controls (HC). Sixteen HC and 17 CB-using adolescents were included in the analysis. GSH levels were measured in the ACC using a metabolite-edited proton magnetic resonance spectroscopy sequence on a 3 T scanner. Distress intolerance was assessed using the Distress Intolerance Index (DII) and CB use was evaluated using a structured clinical interview. In the CB group, lower CSF-corrected GSH levels in the ACC were correlated with higher DII scores. However, no significant between group differences were observed for ACC CSF-corrected GSH levels or on DII scores. No significant correlations were observed in the HC group between GSH levels and DII. Our findings suggests that the association between lower GSH levels and greater distress intolerance in CB users might reflect alterations in the balance between protective and oxidative stress conditions linked to the ability to tolerate distress. Further examination into this relationship can provide important insights into neurobiological correlates and risk factors associated with CB use to help inform preventive and treatment targets in the future.