Structural disconnectivity in postoperative delirium: A perioperative two-center cohort study in older patients.

BACKGROUND: Structural disconnectivity was found to precede dementia. Global white matter abnormalities might also be associated with postoperative delirium (POD). METHODS: We recruited older patients (≥65 years) without dementia that were scheduled for major surgery. Diffusion kurtosis imaging metrics were obtained preoperatively, after 3 and 12 months postoperatively. We calculated fractional anisotropy (FA), mean diffusivity (MD), mean kurtosis (MK), and free water (FW). A structured and validated delirium assessment was performed twice daily. RESULTS: Of 325 patients, 53 patients developed POD (16.3%). Preoperative global MD (standardized beta 0.27 [95% confidence interval [CI] 0.21-0.32] p < 0.001) was higher in patients with POD. Preoperative global MK (-0.07 [95% CI -0.11 to (-0.04)] p < 0.001) and FA (0.07 [95% CI -0.10 to (-0.04)] p < 0.001) were lower. When correcting for baseline diffusion, postoperative MD was lower after 3 months (0.05 [95% CI -0.08 to (-0.03)] p < 0.001; n = 183) and higher after 12 months (0.28 [95% CI 0.20-0.35] p < 0.001; n = 45) among patients with POD. DISCUSSION: Preoperative structural disconnectivity was associated with POD. POD might lead to white matter depletion 3 and 12 months after surgery.

Evaluating E-Health Literacy, Knowledge, Attitude, and Health Online Information in Portuguese University Students: A Cross-Sectional Study.

BACKGROUND: The main objective of the present study was to assess e-health literacy in a sample of Portuguese university students and its association with the level of knowledge and seeking for COVID-19-related information. METHODS: This cross-sectional online study was conducted on Portuguese university students. All students completed a questionnaire consisting of demographic characteristics, e-health Literacy Scale (eHEALS), and a questionnaire about knowledge, attitude, and health online information seeking. RESULTS: A total of 534 students (76.8% women), with a mean age of 24.3 years old (SD = 7.8), participated in this cross-sectional study, 53.0% of students were from non-health sciences. The mean score of eHEALS literacy was 28.8 (SD = 5.6). Most students (71.1%) classified the Internet as a useful, or very useful, tool in helping them make health related decisions. The use of the Internet as a tool to research health information for a period of two or more hours (OR = 1.9; CI 95% = 1.2; 3.4), to search online for health information on professional websites (OR = 2.3; CI 95% = 1.4; 3.6), to search in official media (OR = 2.3; CI 95% = 1.4; 3.9), and to study in the field of health sciences (OR = 1.6; CI 95% = 1.1; 2.6) increased the likelihood of having sufficient e-health literacy. CONCLUSION: From a public health perspective, there is a need to develop programs that increase health literacy among university students.

CerS6-dependent ceramide synthesis in hypothalamic neurons promotes ER/mitochondrial stress and impairs glucose homeostasis in obese mice.

Dysregulation of hypothalamic ceramides has been associated with disrupted neuronal pathways in control of energy and glucose homeostasis. However, the specific ceramide species promoting neuronal lipotoxicity in obesity have remained obscure. Here, we find increased expression of the C16:0 ceramide-producing ceramide synthase (CerS)6 in cultured hypothalamic neurons exposed to palmitate in vitro and in the hypothalamus of obese mice. Conditional deletion of CerS6 in hypothalamic neurons attenuates high-fat diet (HFD)-dependent weight gain and improves glucose metabolism. Specifically, CerS6 deficiency in neurons expressing pro-opiomelanocortin (POMC) or steroidogenic factor 1 (SF-1) alters feeding behavior and alleviates the adverse metabolic effects of HFD feeding on insulin sensitivity and glucose tolerance. POMC-expressing cell-selective deletion of CerS6 prevents the diet-induced alterations of mitochondrial morphology and improves cellular leptin sensitivity. Our experiments reveal functions of CerS6-derived ceramides in hypothalamic lipotoxicity, altered mitochondrial dynamics, and ER/mitochondrial stress in the deregulation of food intake and glucose metabolism in obesity.

Is There More to Olive Oil than Healthy Lipids?

The Mediterranean diet is a healthy dietary pattern whose main characteristic is olive oil consumption. The potential health benefits of olive oil have been extensively investigated and the present review provides the more recent clinical evidence supporting the positive impact of olive oil intake on human health. PubMed (n = 227) and Scopus (n = 308) databases were searched for published clinical studies in English over the past six years (October 2016 to December 2022), following key word searches of "olive oil" and "health". Major findings associated olive oil with antioxidant and anti-inflammatory effects, improvement in endothelial function and lipid profile, prevention of obesity, diabetes, cardiovascular and neurodegenerative diseases, and modulation of the gut microbiota. These benefits are attributed to the nutritional composition of olive oil, which has a high content of monounsaturated fatty acids (MUFA) (oleic acid in particular) and minor compounds such as polyphenols (oleuropein and hydroxytyrosol). Although additional research continues to be required, the more recently generated evidence supports the potential of olive oil to contribute beneficially to health and to the prevention and management of a variety of non-communicable diseases, as a consequence of the synergism between its components' complexity.

The Metabolic and Analytical Changes of Healthy Volunteers upon Intake of Portuguese Extra Virgin Olive Oil: A Comparison Study between Pre- and Post-Intervention.

(1) Background: Extra virgin olive oil (EVOO) is studied mostly for its health benefits in preventing non-communicable chronic diseases, particularly within a Mediterranean dietary pattern. However, few studies have addressed the effect of EVOO in healthy individuals, prior to an established disease. This study aims to evaluate the impact of Northern Portuguese polyphenol-rich EVOO (NPPR-EVOO) consumption on various important clinical parameters in healthy adult volunteers. (2) Methods: This quasi-experimental intervention study assessed the impact of NPPR-EVOO for a period of 100 days. Serum total cholesterol, HbA1c, HDL-c, LDL-c, and CRP, and anthropometric measures-waist and hip perimeters, hand grip strength, and body fat-were assessed and food logs were analyzed. (3) Results: Serum HbA1c (5.12 ± 0.32%; 4.93 ± 0.24, p = 0.000) and LDL-c (96.50 ± 28.57 mg/dL; 87.41 ± 31.38 mg/dL, p = 0.017) significantly decreased following NPPR-EVOO. Also, daily energy significantly increased, but no changes in other dietary parameters, or anthropometry, were seen. Adherence to the Mediterranean diet did not explain the differences found in individuals regarding serum lipid profile and HbA1c, reinforcing the role of EVOO's effect. (4) Conclusions: NPPR-EVOO lowered the serum levels of LDL cholesterol and HbA1c, providing clues on the effect of EVOO-putative health benefits. These results pave the way for a deeper exploration of EVOO as a functional food.

Neoadjuvant Gastric Cancer Treatment and Associated Nutritional Critical Domains for the Optimization of Care Pathways: A Systematic Review.

(1) Background: Gastric cancer patients are known to be at a high risk of malnutrition, sarcopenia, and cachexia, and the latter impairs the patient's nutritional status during their clinical course and also treatment response. A clearer identification of nutrition-related critical points during neoadjuvant treatment for gastric cancer is relevant to managing patient care and predicting clinical outcomes. The aim of this systematic review was to identify and describe nutrition-related critical domains associated with clinical outcomes. (2) Methods: We performed a systematic review (PROSPERO ID:CRD42021266760); (3) Results: This review included 14 studies compiled into three critical domains: patient-related, clinical-related (disease and treatment), and healthcare-related. Body composition changes during neoadjuvant chemotherapy (NAC) accounted for the early termination of chemotherapy and reduced overall survival. Sarcopenia was confirmed to have an independent prognostic value. The role of nutritional interventions during NAC has not been fully explored. (4) Conclusions: Understanding critical domain exposures affecting nutritional status will enable better clinical approaches to optimize care plans. It may also provide an opportunity for the mitigation of poor nutritional status and sarcopenia and their deleterious clinical consequences.

Impact of the COVID-19 pandemic on the mental and physical health and overall wellbeing of university students in Portugal.

Throughout the pandemic of COVID-19 caused by SARS-CoV-2, university students were considered a vulnerable risk group for mental health impairment and wellbeing deterioration. This study aimed at evaluating the pandemic's impact on the physical and mental health and wellbeing among students of a Portuguese university. This cross-sectional study included 913 participants and ran from June to October 2020. Data collected included sociodemographics, three mental health self-report questionnaires (Depression Anxiety Stress Scale, Eating Disorder Examination Questionnaire and Brief COPE) and lifestyle practices (eating and sleeping patterns, media, and entertainment habits) during the first months of the pandemic, which included a 72-day full national lockdown. Descriptive and correlational statistical analysis were conducted. Students' food habits changed during the pandemic, namely on the consumption of snacks and fast food and, overall, less balanced meals became more prevalent. Additionally, almost 70% of the students reported Body Mass Index changes, while 59% went through sleep pattern changes-these were more pronounced in women and younger students. Over half (67%) of the inquirees exhibited an increase in their stress, depression, and generalized anxiety symptoms. Also, the study demonstrates that students' lifestyles trended negatively during the pandemic and highlights how important regular psychological, health monitoring and emotional support is, amongst this somehow overlooked population throughout the pandemic. Universities should provide support to overcome challenges in future stressful situations. This study might have an impact on how universities and higher education systems approach their students in terms of mental and physical health monitoring and promotion in future situations, non-related with COVID. Moreover, it has a large sample of students well characterized in terms of mental and physical health, which might be of interest for future comparison with other worldwide group of students throughout stressful situations, such as tragic events, wars, pandemics.

Use of Support Vector Machines Approach via ComBat Harmonized Diffusion Tensor Imaging for the Diagnosis and Prognosis of Mild Traumatic Brain Injury: A CENTER-TBI Study.

The prediction of functional outcome after mild traumatic brain injury (mTBI) is challenging. Conventional magnetic resonance imaging (MRI) does not do a good job of explaining the variance in outcome, as many patients with incomplete recovery will have normal-appearing clinical neuroimaging. More advanced quantitative techniques such as diffusion MRI (dMRI), can detect microstructural changes not otherwise visible, and so may offer a way to improve outcome prediction. In this study, we explore the potential of linear support vector classifiers (linearSVCs) to identify dMRI biomarkers that can predict recovery after mTBI. Simultaneously, the harmonization of fractional anisotropy (FA) and mean diffusivity (MD) via ComBat was evaluated and compared for the classification performances of the linearSVCs. We included dMRI scans of 179 mTBI patients and 85 controls from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI), a multi-center prospective cohort study, up to 21 days post-injury. Patients were dichotomized according to their Extended Glasgow Outcome Scale (GOSE) scores at 6 months into complete (n = 92; GOSE = 8) and incomplete (n = 87; GOSE <8) recovery. FA and MD maps were registered to a common space and harmonized via the ComBat algorithm. LinearSVCs were applied to distinguish: (1) mTBI patients from controls and (2) mTBI patients with complete from those with incomplete recovery. The linearSVCs were trained on (1) age and sex only, (2) non-harmonized, (3) two-category-harmonized ComBat, and (4) three-category-harmonized ComBat FA and MD images combined with age and sex. White matter FA and MD voxels and regions of interest (ROIs) within the John Hopkins University (JHU) atlas were examined. Recursive feature elimination was used to identify the 10% most discriminative voxels or the 10 most discriminative ROIs for each implementation. mTBI patients displayed significantly higher MD and lower FA values than controls for the discriminative voxels and ROIs. For the analysis between mTBI patients and controls, the three-category-harmonized ComBat FA and MD voxel-wise linearSVC provided significantly higher classification scores (81.4% accuracy, 93.3% sensitivity, 80.3% F1-score, and 0.88 area under the curve [AUC], p < 0.05) compared with the classification based on age and sex only and the ROI approaches (accuracies: 59.8% and 64.8%, respectively). Similar to the analysis between mTBI patients and controls, the three-category-harmonized ComBat FA and MD maps voxelwise approach yields statistically significant prediction scores between mTBI patients with complete and those with incomplete recovery (71.8% specificity, 66.2% F1-score and 0.71 AUC, p < 0.05), which provided a modest increase in the classification score (accuracy: 66.4%) compared with the classification based on age and sex only and ROI-wise approaches (accuracy: 61.4% and 64.7%, respectively). This study showed that ComBat harmonized FA and MD may provide additional information for diagnosis and prognosis of mTBI in a multi-modal machine learning approach. These findings demonstrate that dMRI may assist in the early detection of patients at risk of incomplete recovery from mTBI.

Coping as a Mediator and Moderator between Psychological Distress and Disordered Eating Behaviors and Weight Changes during the COVID-19 Pandemic.

Previous research has already shown the negative impact of the COVID-19 pandemic on college students' well-being and mental health. Eating problems and weight gain due to changes in eating habits and physical activity experienced during this period have also been noticed. However, few studies have explored the role of students' resources as used during the COVID-19 pandemic, such as coping strategies. This study aimed to (1) explore the associations among psychological distress, disordered eating, coping strategies, and weight changes; (2) examine the moderating role of coping strategies in the process of weight gain and weight loss; and (3) study the mediating role of coping strategies in the process of weight gain and weight loss. The participants in this study were 772 students at a Portuguese university. The data collected included sociodemographic data and three self-reported questionnaires (Depression, Anxiety, and Stress Scale; Eating Disorder Examination Questionnaire; Brief COPE) during the first few months of the pandemic, which included a 72-day full national lockdown. The results showed that depression, anxiety, stress, and disordered eating were related to increased weight. Guilt, denial, self-distraction, use of substances, and behavior disinvestment were also related to increased weight. Behavioral disinvestment had a strong mediating effect on weight gain. Additionally, planning, positive reframing, and acceptance all showed a moderating effect between psychological distress and weight changes. In conclusion, coping strategies allow for a better understanding of the mechanisms by which psychological distress and disordered eating were related to weight changes during the pandemic.

Validation of cross-sectional and longitudinal ComBat harmonization methods for magnetic resonance imaging data on a travelling subject cohort.

Background: The growth in multi-center neuroimaging studies generated a need for methods that mitigate the differences in hardware and acquisition protocols across sites i.e., scanner effects. ComBat harmonization methods have shown promise but have not yet been tested on all the data types commonly studied with magnetic resonance imaging (MRI). This study aimed to validate neuroCombat, longCombat and gamCombat on both structural and diffusion metrics in both cross-sectional and longitudinal data. Methods: We used a travelling subject design whereby 73 healthy volunteers contributed 161 scans across two sites and four machines using one T1 and five diffusion MRI protocols. Scanner was defined as a composite of site, machine and protocol. A common pipeline extracted two structural metrics (volumes and cortical thickness) and two diffusion tensor imaging metrics (mean diffusivity and fractional anisotropy) for seven regions of interest including gray and (except for cortical thickness) white matter regions. Results: Structural data exhibited no significant scanner effect and therefore did not benefit from harmonization in our particular cohort. Indeed, attempting harmonization obscured the true biological effect for some regions of interest. Diffusion data contained marked scanner effects and was successfully harmonized by all methods, resulting in smaller scanner effects and better detection of true biological effects. LongCombat less effectively reduced the scanner effect for cross-sectional white matter data but had a slightly lower probability of incorrectly finding group differences in simulations, compared to neuroCombat and gamCombat. False positive rates for all methods and all metrics did not significantly exceed 5%. Conclusions: Statistical harmonization of structural data is not always necessary and harmonization in the absence of a scanner effect may be harmful. Harmonization of diffusion MRI data is highly recommended with neuroCombat, longCombat and gamCombat performing well in cross-sectional and longitudinal settings.

Global and regional ecological boundaries explain abrupt spatial discontinuities in avian frugivory interactions.

Species interactions can propagate disturbances across space via direct and indirect effects, potentially connecting species at a global scale. However, ecological and biogeographic boundaries may mitigate this spread by demarcating the limits of ecological networks. We tested whether large-scale ecological boundaries (ecoregions and biomes) and human disturbance gradients increase dissimilarity among plant-frugivore networks, while accounting for background spatial and elevational gradients and differences in network sampling. We assessed network dissimilarity patterns over a broad spatial scale, using 196 quantitative avian frugivory networks (encompassing 1496 plant and 1004 bird species) distributed across 67 ecoregions, 11 biomes, and 6 continents. We show that dissimilarities in species and interaction composition, but not network structure, are greater across ecoregion and biome boundaries and along different levels of human disturbance. Our findings indicate that biogeographic boundaries delineate the world's biodiversity of interactions and likely contribute to mitigating the propagation of disturbances at large spatial scales.

Presurgical diffusion metrics of the thalamus and thalamic nuclei in postoperative delirium: A prospective two-centre cohort study in older patients.

BACKGROUND: The thalamus seems to be important in the development of postoperative delirium (POD) as previously revealed by volumetric and diffusion magnetic resonance imaging. In this observational cohort study, we aimed to further investigate the impact of the microstructural integrity of the thalamus and thalamic nuclei on the incidence of POD by applying diffusion kurtosis imaging (DKI). METHODS: Older patients without dementia (≥65 years) who were scheduled for major elective surgery received preoperative DKI at two study centres. The DKI metrics fractional anisotropy (FA), mean diffusivity (MD), mean kurtosis (MK) and free water (FW) were calculated for the thalamus and - as secondary outcome - for eight predefined thalamic nuclei and regions. Low FA and MK and, conversely, high MD and FW, indicate aspects of microstructural abnormality. To assess patients' POD status, the Nursing Delirium Screening Scale (Nu-DESC), Richmond Agitation Sedation Scale (RASS), Confusion Assessment Method (CAM) and Confusion Assessment Method for the Intensive Care Unit score (CAM-ICU) and chart review were applied twice a day after surgery for the duration of seven days or until discharge. For each metric and each nucleus, logistic regression was performed to assess the risk of POD. RESULTS: This analysis included the diffusion scans of 325 patients, of whom 53 (16.3 %) developed POD. Independently of age, sex and study centre, thalamic MD was statistically significantly associated with POD [OR 1.65 per SD increment (95 %CI 1.17 - 2.34) p = 0.004]. FA (p = 0.84), MK (p = 0.41) and FW (p = 0.06) were not significantly associated with POD in the examined sample. Exploration of thalamic nuclei also indicated that only the MD in certain areas of the thalamus was associated with POD. MD was increased in bilateral hemispheres, pulvinar nuclei, mediodorsal nuclei and the left anterior nucleus. CONCLUSIONS: Microstructural abnormalities of the thalamus and thalamic nuclei, as reflected by increased MD, appear to predispose to POD. These findings affirm the thalamus as a region of interest in POD research.

Parallel transmit (pTx) with online pulse design for task-based fMRI at 7 T.

PURPOSE: Parallel transmission (pTx) is an approach to improve image uniformity for ultra-high field imaging. In this study, we modified an echo planar imaging (EPI) sequence to design subject-specific pTx pulses online. We compared its performance against EPI with conventional circularly polarised (CP) pulses. METHODS: We compared the pTx-EPI and CP-EPI sequences in a short EPI acquisition protocol and for two different functional paradigms in six healthy volunteers (2 female, aged 23-36 years, mean age 29.2 years). We chose two paradigms that are typically affected by signal dropout at 7 T: a visual objects localiser to determine face/scene selective brain regions and a semantic-processing task. RESULTS: Across all subjects, pTx-EPI improved whole-brain mean temporal signal-to-noise ratio (tSNR) by 11.0% compared to CP-EPI. We also compared the ability of pTx-EPI and CP-EPI to detect functional activation for three contrasts over the two paradigms: face > object and scene > object for the visual objects localiser and semantic association > pattern matching for the semantic-processing paradigm. Across all three contrasts, pTx-EPI showed higher median z-scores and detected more active voxels in relevant areas, as determined from previous 3 T studies. CONCLUSION: We have demonstrated a workflow for EPI acquisitions with online per-subject pulse calculations. We saw improved performance in both tSNR and functional acquisitions from pTx-EPI. Thus, we believe that online calculation pTx-EPI is robust enough for future fMRI studies, especially where activation is expected in brain areas liable to significant signal dropout.

Sensitivity of Diffusion MRI to White Matter Pathology: Influence of Diffusion Protocol, Magnetic Field Strength, and Processing Pipeline in Systemic Lupus Erythematosus.

There are many ways to acquire and process diffusion MRI (dMRI) data for group studies, but it is unknown which maximizes the sensitivity to white matter (WM) pathology. Inspired by this question, we analyzed data acquired for diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) at 3T (3T-DTI and 3T-DKI) and DTI at 7T in patients with systemic lupus erythematosus (SLE) and healthy controls (HC). Parameter estimates in 72 WM tracts were obtained using TractSeg. The impact on the sensitivity to WM pathology was evaluated for the diffusion protocol, the magnetic field strength, and the processing pipeline. Sensitivity was quantified in terms of Cohen's d for group comparison. Results showed that the choice of diffusion protocol had the largest impact on the effect size. The effect size in fractional anisotropy (FA) across all WM tracts was 0.26 higher when derived by DTI than by DKI and 0.20 higher in 3T compared with 7T. The difference due to the diffusion protocol was larger than the difference due to magnetic field strength for the majority of diffusion parameters. In contrast, the difference between including or excluding different processing steps was near negligible, except for the correction of distortions from eddy currents and motion which had a clearly positive impact. For example, effect sizes increased on average by 0.07 by including motion and eddy correction for FA derived from 3T-DTI. Effect sizes were slightly reduced by the incorporation of denoising and Gibbs-ringing removal (on average by 0.011 and 0.005, respectively). Smoothing prior to diffusion model fitting generally reduced effect sizes. In summary, 3T-DTI in combination with eddy current and motion correction yielded the highest sensitivity to WM pathology in patients with SLE. However, our results also indicated that the 3T-DKI and 7T-DTI protocols used here may be adjusted to increase effect sizes.

Post-acute blood biomarkers and disease progression in traumatic brain injury.

There is substantial interest in the potential for traumatic brain injury to result in progressive neurological deterioration. While blood biomarkers such as glial fibrillary acid protein (GFAP) and neurofilament light have been widely explored in characterizing acute traumatic brain injury (TBI), their use in the chronic phase is limited. Given increasing evidence that these proteins may be markers of ongoing neurodegeneration in a range of diseases, we examined their relationship to imaging changes and functional outcome in the months to years following TBI. Two-hundred and three patients were recruited in two separate cohorts; 6 months post-injury (n = 165); and >5 years post-injury (n = 38; 12 of whom also provided data ∼8 months post-TBI). Subjects underwent blood biomarker sampling (n = 199) and MRI (n = 172; including diffusion tensor imaging). Data from patient cohorts were compared to 59 healthy volunteers and 21 non-brain injury trauma controls. Mean diffusivity and fractional anisotropy were calculated in cortical grey matter, deep grey matter and whole brain white matter. Accelerated brain ageing was calculated at a whole brain level as the predicted age difference defined using T1-weighted images, and at a voxel-based level as the annualized Jacobian determinants in white matter and grey matter, referenced to a population of 652 healthy control subjects. Serum neurofilament light concentrations were elevated in the early chronic phase. While GFAP values were within the normal range at ∼8 months, many patients showed a secondary and temporally distinct elevations up to >5 years after injury. Biomarker elevation at 6 months was significantly related to metrics of microstructural injury on diffusion tensor imaging. Biomarker levels at ∼8 months predicted white matter volume loss at >5 years, and annualized brain volume loss between ∼8 months and 5 years. Patients who worsened functionally between ∼8 months and >5 years showed higher than predicted brain age and elevated neurofilament light levels. GFAP and neurofilament light levels can remain elevated months to years after TBI, and show distinct temporal profiles. These elevations correlate closely with microstructural injury in both grey and white matter on contemporaneous quantitative diffusion tensor imaging. Neurofilament light elevations at ∼8 months may predict ongoing white matter and brain volume loss over >5 years of follow-up. If confirmed, these findings suggest that blood biomarker levels at late time points could be used to identify TBI survivors who are at high risk of progressive neurological damage.

Correcting for Superficial Bias in 7T Gradient Echo fMRI.

The arrival of submillimeter ultra high-field fMRI makes it possible to compare activation profiles across cortical layers. However, the blood oxygenation level dependent (BOLD) signal measured by gradient echo (GE) fMRI is biased toward superficial layers of the cortex, which is a serious confound for laminar analysis. Several univariate and multivariate analysis methods have been proposed to correct this bias. We compare these methods using computational simulations of 7T fMRI data from regions of interest (ROI) during a visual attention paradigm. We also tested the methods on a pilot dataset of human 7T fMRI data. The simulations show that two methods-the ratio of ROI means across conditions and a novel application of Deming regression-offer the most robust correction for superficial bias. Deming regression has the additional advantage that it does not require that the conditions differ in their mean activation over voxels within an ROI. When applied to the pilot dataset, we observed strikingly different layer profiles when different attention metrics were used, but were unable to discern any differences in laminar attention across layers when Deming regression or ROI ratio was applied. Our simulations demonstrates that accurate correction of superficial bias is crucial to avoid drawing erroneous conclusions from laminar analyses of GE fMRI data, and this is affirmed by the results from our pilot 7T fMRI data.

Peripheral inflammation is associated with micro-structural and functional connectivity changes in depression-related brain networks.

Inflammation is associated with depressive symptoms and innate immune mechanisms are likely causal in some cases of major depression. Systemic inflammation also perturbs brain function and microstructure, though how these are related remains unclear. We recruited N = 46 healthy controls, and N = 83 depressed cases stratified by CRP (> 3 mg/L: N = 33; < 3 mg/L: N = 50). All completed clinical assessment, venous blood sampling for C-reactive protein (CRP) assay, and brain magnetic resonance imaging (MRI). Micro-structural MRI parameters including proton density (PD), a measure of tissue water content, were measured at 360 cortical and 16 subcortical regions. Resting-state fMRI time series were correlated to estimate functional connectivity between individual regions, as well as the sum of connectivity (weighted degree) of each region. Multiple tests for regional analysis were controlled by the false discovery rate (FDR = 5%). We found that CRP was significantly associated with PD in precuneus, posterior cingulate cortex (pC/pCC) and medial prefrontal cortex (mPFC); and with functional connectivity between pC/pCC, mPFC and hippocampus. Depression was associated with reduced weighted degree of pC/pCC, mPFC, and other nodes of the default mode network (DMN). Thus CRP-related increases in proton density-a plausible marker of extracellular oedema-and changes in functional connectivity were anatomically co-localised with DMN nodes that also demonstrated significantly reduced hubness in depression. We suggest that effects of peripheral inflammation on DMN node micro-structure and connectivity may mediate inflammatory effects on depression.

Diffusional Kurtosis Imaging in the Diffusion Imaging in Python Project.

Diffusion-weighted magnetic resonance imaging (dMRI) measurements and models provide information about brain connectivity and are sensitive to the physical properties of tissue microstructure. Diffusional Kurtosis Imaging (DKI) quantifies the degree of non-Gaussian diffusion in biological tissue from dMRI. These estimates are of interest because they were shown to be more sensitive to microstructural alterations in health and diseases than measures based on the total anisotropy of diffusion which are highly confounded by tissue dispersion and fiber crossings. In this work, we implemented DKI in the Diffusion in Python (DIPY) project-a large collaborative open-source project which aims to provide well-tested, well-documented and comprehensive implementation of different dMRI techniques. We demonstrate the functionality of our methods in numerical simulations with known ground truth parameters and in openly available datasets. A particular strength of our DKI implementations is that it pursues several extensions of the model that connect it explicitly with microstructural models and the reconstruction of 3D white matter fiber bundles (tractography). For instance, our implementations include DKI-based microstructural models that allow the estimation of biophysical parameters, such as axonal water fraction. Moreover, we illustrate how DKI provides more general characterization of non-Gaussian diffusion compatible with complex white matter fiber architectures and gray matter, and we include a novel mean kurtosis index that is invariant to the confounding effects due to tissue dispersion. In summary, DKI in DIPY provides a well-tested, well-documented and comprehensive reference implementation for DKI. It provides a platform for wider use of DKI in research on brain disorders and in cognitive neuroscience.

Metabolic derangements are associated with impaired glucose delivery following traumatic brain injury.

Metabolic derangements following traumatic brain injury are poorly characterized. In this single-centre observational cohort study we combined 18F-FDG and multi-tracer oxygen-15 PET to comprehensively characterize the extent and spatial pattern of metabolic derangements. Twenty-six patients requiring sedation and ventilation with intracranial pressure monitoring following head injury within a Neurosciences Critical Care Unit, and 47 healthy volunteers were recruited. Eighteen volunteers were excluded for age over 60 years (n = 11), movement-related artefact (n = 3) or physiological instability during imaging (n = 4). We measured cerebral blood flow, blood volume, oxygen extraction fraction, and 18F-FDG transport into the brain (K1) and its phosphorylation (k3). We calculated oxygen metabolism, 18F-FDG influx rate constant (Ki), glucose metabolism and the oxygen/glucose metabolic ratio. Lesion core, penumbra and peri-penumbra, and normal-appearing brain, ischaemic brain volume and k3 hotspot regions were compared with plasma and microdialysis glucose in patients. Twenty-six head injury patients, median age 40 years (22 male, four female) underwent 34 combined 18F-FDG and oxygen-15 PET at early, intermediate, and late time points (within 24 h, Days 2-5, and Days 6-12 post-injury; n = 12, 8, and 14, respectively), and were compared with 20 volunteers, median age 43 years (15 male, five female) who underwent oxygen-15, and nine volunteers, median age 56 years (three male, six female) who underwent 18F-FDG PET. Higher plasma glucose was associated with higher microdialysate glucose. Blood flow and K1 were decreased in the vicinity of lesions, and closely related when blood flow was <25 ml/100 ml/min. Within normal-appearing brain, K1 was maintained despite lower blood flow than volunteers. Glucose utilization was globally reduced in comparison with volunteers (P < 0.001). k3 was variable; highest within lesions with some patients showing increases with blood flow <25 ml/100 ml/min, but falling steeply with blood flow lower than 12 ml/100 ml/min. k3 hotspots were found distant from lesions, with k3 increases associated with lower plasma glucose (Rho -0.33, P < 0.001) and microdialysis glucose (Rho -0.73, P = 0.02). k3 hotspots showed similar K1 and glucose metabolism to volunteers despite lower blood flow and oxygen metabolism (P < 0.001, both comparisons); oxygen extraction fraction increases consistent with ischaemia were uncommon. We show that glucose delivery was dependent on plasma glucose and cerebral blood flow. Overall glucose utilization was low, but regional increases were associated with reductions in glucose availability, blood flow and oxygen metabolism in the absence of ischaemia. Clinical management should optimize blood flow and glucose delivery and could explore the use of alternative energy substrates.

Neuroanatomical Substrates and Symptoms Associated With Magnetic Resonance Imaging of Patients With Mild Traumatic Brain Injury.

Importance: Persistent symptoms after mild traumatic brain injury (mTBI) represent a major public health problem. Objective: To identify neuroanatomical substrates of mTBI and the optimal timing for magnetic resonance imaging (MRI). Design, Setting, and Participants: This prospective multicenter cohort study encompassed all eligible patients from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study (December 19, 2014, to December 17, 2017) and a local cohort (November 20, 2012, to December 19, 2013). Patients presented to the hospital within 24 hours of an mTBI (Glasgow Coma Score, 13-15), satisfied local criteria for computed tomographic scanning, and underwent MRI scanning less than 72 hours (MR1) and 2 to 3 weeks (MR2) after injury. In addition, 104 control participants were enrolled across all sites. Data were analyzed from January 1, 2019, to December 31, 2020. Exposure: Mild TBI. Main Outcomes and Measures: Volumes and diffusion parameters were extracted via automated bespoke pipelines. Symptoms were measured using the Rivermead Post Concussion Symptoms Questionnaire in the short term and the extended Glasgow Outcome Scale at 3 months. Results: Among the 81 patients included in the analysis (73 CENTER-TBI and 8 local), the median age was 45 (interquartile range [IQR], 24-59; range, 14-85) years, and 57 (70.4%) were male. Structural sequences were available for all scans; diffusion data, for 73 MR1 and 79 MR2 scans. After adjustment for multiple comparisons between scans, visible lesions did not differ significantly, but cerebral white matter volume decreased (MR2:MR1 ratio, 0.98; 95% CI, 0.96-0.99) and ventricular volume increased (MR2:MR1 ratio, 1.06; 95% CI, 1.02-1.10). White matter volume was within reference limits on MR1 scans (patient to control ratio, 0.99; 95% CI, 0.97-1.01) and reduced on MR2 scans (patient to control ratio, 0.97; 95% CI, 0.95-0.99). Diffusion parameters changed significantly between scans in 13 tracts, following 1 of 3 trajectories. Symptoms measured by Rivermead Post Concussion Symptoms Questionnaire scores worsened in the progressive injury phenotype (median, +5.00; IQR, +2.00 to +5.00]), improved in the minimal change phenotype (median, -4.50; IQR, -9.25 to +1.75), and were variable in the pseudonormalization phenotype (median, 0.00; IQR, -6.25 to +9.00) (P = .02). Recovery was favorable for 33 of 65 patients (51%) and was more closely associated with MR1 than MR2 (area under the curve, 0.87 [95% CI, 0.78-0.96] vs 0.75 [95% CI, 0.62-0.87]; P = .009). Conclusions and Relevance: These findings suggest that advanced MRI reveals potential neuroanatomical substrates of mTBI in white matter and is most strongly associated with odds of recovery if performed within 72 hours, although future validation is required.