Metabolites and MRI-Derived Markers of AD/ADRD Risk in a Puerto Rican Cohort.

Objective: Several studies have examined metabolomic profiles in relation to Alzheimer's disease and related dementia (AD/ADRD) risk; however, few studies have focused on minorities, such as Latinos, or examined Magnetic-Resonance Imaging (MRI)-based outcomes. Methods: We used multiple linear regression, adjusted for covariates, to examine the association between metabolite concentration and MRI-derived brain age deviation. Metabolites were measured at baseline with untargeted metabolomic profiling (Metabolon, Inc). Brain age deviation (BAD) was calculated at wave 4 (~ 9 years from Boston Puerto Rican Health Study (BPRHS) baseline) as chronologic age, minus MRI-estimated brain age, representing the rate of biological brain aging relative to chronologic age. We also examined if metabolites associated with BAD were similarly associated with hippocampal volume and global cognitive function at wave 4 in the BPRHS. Results: Several metabolites, including isobutyrylcarnitine, propionylcarnitine, phenylacetylglutamine, phenylacetylcarnitine (acetylated peptides), p-cresol-glucuronide, phenylacetylglutamate, and trimethylamine N-oxide (TMAO) were inversely associated with brain age deviation. Taurocholate sulfate, a bile salt, was marginally associated with better brain aging. Most metabolites with negative associations with brain age deviation scores also were inversely associations with hippocampal volumes and wave 4 cognitive function. Conclusion: The metabolites identifiedin this study are generally consistent with prior literature and highlight the role of BCAA, TMAO and microbially derived metabolites in cognitive decline.

Corrigendum: APOE4 allele-specific associations between diet, multimodal biomarkers, and cognition among Puerto Rican adults in Massachusetts.

[This corrects the article DOI: 10.3389/fnagi.2023.1285333.].

APOE4 allele-specific associations between diet, multimodal biomarkers, and cognition among Puerto Rican adults in Massachusetts.

Background: Apolipoprotein E (APOE) is the strongest genetic risk factor for sporadic Alzheimer's Disease (AD), and the ε4 allele (APOE4) may interact with lifestyle factors that relate to brain structural changes, underlying the increased risk of AD. However, the exact role of APOE4 in mediating interactions between the peripheral circulatory system and the central nervous system, and how it may link to brain and cognitive aging requires further elucidation. In this analysis, we investigated the association between APOE4 carrier status and multimodal biomarkers (diet, blood markers, clinical diagnosis, brain structure, and cognition) in the context of gene-environment interactions. Methods: Participants were older adults from a longitudinal observational study, the Boston Puerto Rican Health Study (BPRHS), who self-identified as of Puerto Rican descent. Demographics, APOE genotype, diet, blood, and clinical data were collected at baseline and at approximately 12th year, with the addition of multimodal brain magnetic resonance imaging (MRI) (T1-weighted and diffusion) and cognitive testing acquired at 12-year. Measures were compared between APOE4 carriers and non-carriers, and associations between multimodal variables were examined using correlation and multivariate network analyses within each group. Results: A total of 156 BPRHS participants (mean age at imaging = 68 years, 77% female, mean follow-up 12.7 years) with complete multimodal data were included in the current analysis. APOE4 carriers (n = 43) showed reduced medial temporal lobe (MTL) white matter (WM) microstructural integrity and lower mini-mental state examination (MMSE) score than non-carriers (n = 113). This pattern was consistent with an independent sample from the Alzheimer's Disease Neuroimaging Initiative (ADNI) of n = 283 non-Hispanic White adults without dementia (mean age = 75, 40% female). Within BPRHS, carriers showed distinct connectivity patterns between multimodal biomarkers, characterized by stronger direct network connections between baseline diet/blood markers with 12-year blood/clinical measures, and between blood markers (especially lipids and cytokines) and WM. Cardiovascular burden (i.e., hypertension and diabetes status) was associated with WM integrity for both carriers and non-carriers. Conclusion: APOE4 carrier status affects interactions between dietary factors, multimodal blood biomarkers, and MTL WM integrity across ~12 years of follow-up, which may reflect increased peripheral-central systems crosstalk following blood-brain barrier breakdown in carriers.

Human-to-monkey transfer learning identifies the frontal white matter as a key determinant for predicting monkey brain age.

The application of artificial intelligence (AI) to summarize a whole-brain magnetic resonance image (MRI) into an effective "brain age" metric can provide a holistic, individualized, and objective view of how the brain interacts with various factors (e.g., genetics and lifestyle) during aging. Brain age predictions using deep learning (DL) have been widely used to quantify the developmental status of human brains, but their wider application to serve biomedical purposes is under criticism for requiring large samples and complicated interpretability. Animal models, i.e., rhesus monkeys, have offered a unique lens to understand the human brain - being a species in which aging patterns are similar, for which environmental and lifestyle factors are more readily controlled. However, applying DL methods in animal models suffers from data insufficiency as the availability of animal brain MRIs is limited compared to many thousands of human MRIs. We showed that transfer learning can mitigate the sample size problem, where transferring the pre-trained AI models from 8,859 human brain MRIs improved monkey brain age estimation accuracy and stability. The highest accuracy and stability occurred when transferring the 3D ResNet [mean absolute error (MAE) = 1.83 years] and the 2D global-local transformer (MAE = 1.92 years) models. Our models identified the frontal white matter as the most important feature for monkey brain age predictions, which is consistent with previous histological findings. This first DL-based, anatomically interpretable, and adaptive brain age estimator could broaden the application of AI techniques to various animal or disease samples and widen opportunities for research in non-human primate brains across the lifespan.

Association of Diabetes and Hypertension With Brain Structural Integrity and Cognition in the Boston Puerto Rican Health Study Cohort.

BACKGROUND AND OBJECTIVES: The Boston Puerto Rican Health Study (BPRHS) is a longitudinal study following self-identified Puerto Rican older adults living in the Greater Boston area. Studies have shown higher prevalence of hypertension (HTN) and type 2 diabetes (T2D) within this ethnic group compared to age-matched non-Hispanic White adults. In this study, we investigated the associations of HTN and T2D comorbidity on brain structural integrity and cognitive capacity in community-dwelling Puerto Rican adults and compared these measures with older adult participants (non-Hispanic White and Hispanic) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and National Alzheimer's Coordinating Center (NACC) databases. METHODS: BPRHS participants who underwent brain MRI and cognitive testing were divided into 4 groups based on their HTN and T2D status: HTN-/T2D-, HTN+/T2D-, HTN-/T2D+, and HTN+/T2D+. We assessed microstructural integrity of white matter (WM) pathways using diffusion MRI, brain macrostructural integrity using hippocampal volumes, and brain age using T1-weighted MRI and cognitive test scores. BPRHS results were then compared with results from non-Hispanic White and Hispanic participants from the ADNI and NACC databases. RESULTS: The prevalence of HTN was almost 2 times (66.7% vs 38.7%) and of T2D was 5 times (31.8% vs 6.6.%) higher in BPRHS than in ADNI non-Hispanic White participants. Diffusion MRI showed clear deterioration patterns in major WM tracts in the HTN+/T2D+ group and, to a lesser extent, in the HTN+/T2D- group compared to the HTN-/T2D- group. HTN+/T2D+ participants also had the smallest hippocampal volume and larger brain aging deviations. Trends toward lower executive function and global cognitive scores were observed in HTN+/T2D+ relative to HTN-/T2D- individuals. MRI measures and the Mini-Mental State Examination (MMSE) scores from the HTN+/T2D+ BPRHS group resembled those of ADNI White participants with progressive mild cognitive impairment (MCI), while the BPRHS HTN-/T2D- participants resembled participants with stable MCI. The BPRHS was not significantly different from the ADNI + NACC Hispanic cohort on imaging or MMSE measures. DISCUSSION: The effects of T2D and HTN comorbidity led to greater brain structural disruptions than HTN alone. The high prevalence of HTN and T2D in the Puerto Rican population may be a key factor contributing to health disparities in cognitive impairment in this group compared to non-Hispanic White adults in the same age range. TRIAL REGISTRATION INFORMATION: ClinicalTrials.gov identifier: NCT01231958.

Brain signatures based on structural MRI: Classification for MCI, PMCI, and AD.

Structural MRI (sMRI) provides valuable information for understanding neurodegenerative illnesses such as Alzheimer's Disease (AD) since it detects the brain's cerebral atrophy. The development of brain networks utilizing single imaging data-sMRI is an understudied area that has the potential to provide a network neuroscientific viewpoint on the brain. In this paper, we proposed a framework for constructing a brain network utilizing sMRI data, followed by the extraction of signature networks and important regions of interest (ROIs). To construct a brain network using sMRI, nodes are defined as regions described by the brain atlas, and edge weights are determined using a distance measure called the Sorensen distance between probability distributions of gray matter tissue probability maps. The brain signatures identified are based on the changes in the networks of disease and control subjects. To validate the proposed methodology, we first identified the brain signatures and critical ROIs associated with mild cognitive impairment (MCI), progressive MCI (PMCI), and Alzheimer's disease (AD) with 60 reference subjects (15 each of control, MCI, PMCI, and AD). Then, 200 examination subjects (50 each of control, MCI, PMCI, and AD) were selected to evaluate the identified signature patterns. Results demonstrate that the proposed framework is capable of extracting brain signatures and has a number of potential applications in the disciplines of brain mapping, brain communication, and brain network-based applications.

3D multi-scale residual fully convolutional neural network for segmentation of extremely large-sized kidney tumor.

BACKGROUND AND OBJECTIVE: We propose a novel deep neural network, the 3D Multi-Scale Residual Fully Convolutional Neural Network (3D-MS-RFCNN) to improve segmentation in extremely large-sized kidney tumors. METHOD: The multi-scale approach with a deep neural network is applied to capture global contextual features. Our method, 3D-MS-RFCNN, consists of two encoders and one decoder as a single complete network. One of the encoders is designed for capturing global contextual information by using the low-resolution, down-sampled data from input images. In the decoder, features from the encoder for global contextual features are concatenated with up-sampled features from the previous layer and features from the other encoder. Ensemble learning strategy is also applied. RESULTS: We evaluated the performance of our proposed method using the KiTS public dataset and the in-house hospital dataset. When compared with the state-of-the-art method, Res3D U-Net, our model, 3D-MS-RFCNN, demonstrated greater accuracy (0.9390 dice score for KiTS dataset and 0.8575 dice score for external dataset) for segmenting extremely large-sized kidney tumors. CONCLUSIONS: Our proposed network shows significantly improved segmentation performance of extremely large-sized targets. This study can be usefully employed in the field of medical image analysis.

Association of the tissue microstructural diffusivity and translocator protein PET in Gulf War Illness.

About a third of all United States veterans who served in the 1991 Gulf War (GW) report a range of chronic health symptoms including fatigue, neurocognitive symptoms, and musculoskeletal pain. There is growing evidence supporting the detrimental effects of maladaptive neuroimmune reactions in this multi-symptom illness. Indeed, recent studies using positron emission tomography (PET) using the radioligand [11C]PBR28, which binds the neuroinflammation marker 18 â€‹kDa translocator protein (TSPO), and diffusion magnetic resonance imaging (dMRI) have independently identified the anterior cingulate (ACC) and midcingulate cortices (MCC) as key regions for differentiating GWI veterans from healthy controls (HC). Here, we used integrated (i.e., simultaneous) PET/MRI imaging techniques, paired with dMRI processing methods (neurite density imaging, NDI, and free-water diffusion tensor model to single-shell high-order dMRI), to directly evaluate the relationship between ACC and MCC microstructural tissue parameters, TSPO signal and clinical parameters in the same cohorts of 10 GWI veterans and 19 â€‹HCs. Within the regions evaluated, TSPO signal elevations were associated with restricted diffusivity in the extracellular compartment, while clinical measures were best explained by neurite density and cellular structure complexity measures. Our study is the first to provide evidence of a relationship between PET and dMRI modalities in GWI and suggests that microstructural changes in the ACC and MCC are correlated to mood symptoms and cognitive performances in GWI veterans.

Brain-Immune Interactions as the Basis of Gulf War Illness: Clinical Assessment and Deployment Profile of 1990-1991 Gulf War Veterans in the Gulf War Illness Consortium (GWIC) Multisite Case-Control Study.

The Boston University-based Gulf War Illness Consortium (GWIC) is a multidisciplinary initiative developed to provide detailed understanding of brain and immune alterations that underlie Gulf War illness (GWI), the persistent multisymptom disorder associated with military service in the 1990-1991 Gulf War. The core GWIC case-control clinical study conducted in-depth brain and immune evaluation of 269 Gulf War veterans (223 GWI cases, 46 controls) at three U.S. sites that included clinical assessments, brain imaging, neuropsychological testing, and analyses of a broad range of immune and immunogenetic parameters. GWI cases were similar to controls on most demographic, military, and deployment characteristics although on average were two years younger, with a higher proportion of enlisted personnel vs. officers. Results of physical evaluation and routine clinical lab tests were largely normal, with few differences between GWI cases and healthy controls. However, veterans with GWI scored significantly worse than controls on standardized assessments of general health, pain, fatigue, and sleep quality and had higher rates of diagnosed conditions that included hypertension, respiratory and sinus conditions, gastrointestinal conditions, and current or lifetime depression and post-traumatic stress disorder. Among multiple deployment experiences/exposures reported by veterans, multivariable logistic regression identified just two significant GWI risk factors: extended use of skin pesticides in theater (adjusted OR = 3.25, p = 0.005) and experiencing mild traumatic brain injury during deployment (OR = 7.39, p = 0.009). Gulf War experiences associated with intense stress or trauma (e.g., participation in ground combat) were not associated with GWI. Data and samples from the GWIC project are now stored in a repository for use by GWI researchers. Future reports will present detailed findings on brain structure and function, immune function, and association of neuroimmune measures with characteristics of GWI and Gulf War service.

The relationship of age and hypertension with cognition and gray matter cerebral blood volume in a rhesus monkey model of human aging.

The goal of this study was to investigate whether alterations in cerebral microvasculature, as measured by cerebral blood volume (CBV), contribute to age- and hypertension-related impairments in cognitive function with a focus on executive function and memory. Data were collected on 19 male rhesus monkeys ranging from 6.4 to 21.6 years of age. Hypertension was induced through surgical coarctation of the thoracic aorta. We assessed whether performance on tasks of memory and executive function corresponded to CBV in either the hippocampus or prefrontal cortex. We found a relationship between duration of hypertension and CBV in the gray matter of the prefrontal cortex, but not the hippocampus. No relationships were found with the degree of hypertension or age. Increased prefrontal CBV was related to greater impairment in executive function while hippocampal CBV was not related to memory performance. These findings suggest that duration, but not severity, of hypertension or age are important factors underlying alterations in brain microvasculature and that executive function is more vulnerable than memory function. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

The integrated stress response mediates necrosis in murine Mycobacterium tuberculosis granulomas.

The mechanism by which only some individuals infected with Mycobacterium tuberculosis develop necrotic granulomas with progressive disease while others form controlled granulomas that contain the infection remains poorly defined. Mice carrying the sst1-suscepible (sst1S) genotype develop necrotic inflammatory lung lesions, similar to human tuberculosis (TB) granulomas, which are linked to macrophage dysfunction, while their congenic counterpart (B6) mice do not. In this study we report that (a) sst1S macrophages developed aberrant, biphasic responses to TNF characterized by superinduction of stress and type I interferon pathways after prolonged TNF stimulation; (b) the late-stage TNF response was driven via a JNK/IFN-ß/protein kinase R (PKR) circuit; and (c) induced the integrated stress response (ISR) via PKR-mediated eIF2α phosphorylation and the subsequent hyperinduction of ATF3 and ISR-target genes Chac1, Trib3, and Ddit4. The administration of ISRIB, a small-molecule inhibitor of the ISR, blocked the development of necrosis in lung granulomas of M. tuberculosis-infected sst1S mice and concomitantly reduced the bacterial burden. Hence, induction of the ISR and the locked-in state of escalating stress driven by the type I IFN pathway in sst1S macrophages play a causal role in the development of necrosis in TB granulomas. Interruption of the aberrant stress response with inhibitors such as ISRIB may offer novel host-directed therapy strategies.

Neuroimaging Markers for Studying Gulf-War Illness: Single-Subject Level Analytical Method Based on Machine Learning.

Gulf War illness (GWI) refers to the multitude of chronic health symptoms, spanning from fatigue, musculoskeletal pain, and neurological complaints to respiratory, gastrointestinal, and dermatologic symptoms experienced by about 250,000 GW veterans who served in the 1991 Gulf War (GW). Longitudinal studies showed that the severity of these symptoms often remain unchanged even years after the GW, and these veterans with GWI continue to have poorer general health and increased chronic medical conditions than their non-deployed counterparts. For better management and treatment of this condition, there is an urgent need for developing objective biomarkers that can help with simple and accurate diagnosis of GWI. In this study, we applied multiple neuroimaging techniques, including T1-weighted magnetic resonance imaging (T1W-MRI), diffusion tensor imaging (DTI), and novel neurite density imaging (NDI) to perform both a group-level statistical comparison and a single-subject level machine learning (ML) analysis to identify diagnostic imaging features of GWI. Our results supported NDI as the most sensitive in defining GWI characteristics. In particular, our classifier trained with white matter NDI features achieved an accuracy of 90% and F-score of 0.941 for classifying GWI cases from controls after the cross-validation. These results are consistent with our previous study which suggests that NDI measures are sensitive to the microstructural and macrostructural changes in the brain of veterans with GWI, which can be valuable for designing better diagnosis method and treatment efficacy studies.

Hippocampal Resting-State Functional Connectivity Patterns are More Closely Associated with Severity of Subjective Memory Decline than Whole Hippocampal and Subfield Volumes.

The goal of this study was to examine whether hippocampal volume or resting-state functional connectivity (rsFC) patterns are associated with subjective memory decline (SMD) in cognitively normal aged adults. Magnetic resonance imaging data from 53 participants (mean age: 71.9 years) of the Boston University Alzheimer's Disease Center registry were used in this cross-sectional study. Separate analyses treating SMD as a binary and continuous variable were performed. Subfield volumes were generated using FreeSurfer v6.0, and rsFC strength between the head and body of the hippocampus and the rest of the brain was calculated. Decreased left whole hippocampal volume and weaker rsFC strength between the right body of the hippocampus and the default mode network (DMN) were found in SMD+. Cognitive Change Index score was not correlated with volumetric measures but was inversely correlated with rsFC strength between the right body of the hippocampus and 6 brain networks, including the DMN, task control, and attentional networks. These findings suggest that hippocampal rsFC patterns reflect the current state of SMD in cognitively normal adults and may reflect subtle memory changes that standard neuropsychological tests are unable to capture.

Alterations in high-order diffusion imaging in veterans with Gulf War Illness is associated with chemical weapons exposure and mild traumatic brain injury.

The complex etiology behind Gulf War Illness (GWI) has been attributed to the combined exposure to neurotoxicant chemicals, brain injuries, and some combat experiences. Chronic GWI symptoms have been shown to be associated with intensified neuroinflammatory responses in animal and human studies. To investigate the neuroinflammatory responses and potential causes in Gulf War (GW) veterans, we focused on the effects of chemical/biological weapons (CBW) exposure and mild traumatic brain injury (mTBI) during the war. We applied a novel MRI diffusion processing method, Neurite density imaging (NDI), on high-order diffusion imaging to estimate microstructural alterations of brain imaging in Gulf War veterans with and without GWI, and collected plasma proinflammatory cytokine samples as well as self-reported health symptom scores. Our study identified microstructural changes specific to GWI in the frontal and limbic regions due to CBW and mTBI, and further showed distinctive microstructural patterns such that widespread changes were associated with CBW and more focal changes on diffusion imaging were observed in GW veterans with an mTBI during the war. In addition, microstructural alterations on brain imaging correlated with upregulated blood proinflammatory cytokine markers TNFRI and TNFRII and with worse outcomes on self-reported symptom measures for fatigue and sleep functioning. Taken together, these results suggest TNF signaling mediated inflammation affects frontal and limbic regions of the brain, which may contribute to the fatigue and sleep symptoms of the disease and suggest a strong neuroinflammatory component to GWI. These results also suggest exposures to chemical weapons and mTBI during the war are associated with different patterns of peripheral and central inflammation and highlight the brain regions vulnerable to further subtle microscale morphological changes and chronic signaling to nearby glia.

Defining the optimal target for anterior thalamic deep brain stimulation in patients with drug-refractory epilepsy.

OBJECTIVE: The anterior thalamic nucleus (ATN) is a common target for deep brain stimulation (DBS) for the treatment of drug-refractory epilepsy. However, no atlas-based optimal DBS (active contacts) target within the ATN has been definitively identified. The object of this retrospective study was to analyze the relationship between the active contact location and seizure reduction to establish an atlas-based optimal target for ATN DBS. METHODS: From among 25 patients who had undergone ATN DBS surgery for drug-resistant epilepsy between 2016 and 2018, those who had follow-up evaluations for more than 1 year were eligible for study inclusion. After an initial stimulation period of 6 months, patients were classified as responsive (≥ 50% median decrease in seizure frequency) or nonresponsive (< 50% median decrease in seizure frequency) to treatment. Stimulation parameters and/or active contact positions were adjusted in nonresponsive patients, and their responsiveness was monitored for at least 1 year. Postoperative CT scans were coregistered nonlinearly with preoperative MR images to determine the center coordinate and atlas-based anatomical localizations of all active contacts in the Montreal Neurological Institute (MNI) 152 space. RESULTS: Nineteen patients with drug-resistant epilepsy were followed up for at least a year following bilateral DBS electrode implantation targeting the ATN. Active contacts located more adjacent to the center of gravity of the anterior half of the ATN volume, defined as the anterior center (AC), were associated with greater seizure reduction than those not in this location. Intriguingly, the initially nonresponsive patients could end up with much improved seizure reduction by adjusting the active contacts closer to the AC at the final postoperative follow-up. CONCLUSIONS: Patients with stimulation targeting the AC may have a favorable seizure reduction. Moreover, the authors were able to obtain additional good outcomes after electrode repositioning in the initially nonresponsive patients. Purposeful and strategic trajectory planning to target this optimal region may predict favorable outcomes of ATN DBS.

Increased Functional Connectivity Within Intrinsic Neural Networks in Chronic Stroke Following Treatment with Red/Near-Infrared Transcranial Photobiomodulation: Case Series with Improved Naming in Aphasia.

Objective: To examine effects of four different transcranial, red/near-infrared (NIR), light-emitting diode (tLED) protocols on naming ability in persons with aphasia (PWA) due to left hemisphere (LH) stroke. This is the first study to report beneficial effects from tLED therapy in chronic stroke, and parallel changes on functional magnetic resonance imaging (fMRI). Materials and methods: Six PWA, 2-18 years poststroke, in whom 18 tLED treatments were applied (3 × /week, 6 weeks) using LED cluster heads: 500 mW, red (633 nm) and NIR (870 nm), 22.48 cm2, 22.2 mW/cm2. Results: After Protocol A with bilateral LED placements, including midline, at scalp vertex over left and right supplementary motor areas (L and R SMAs), picture naming was not improved. P1 underwent pre-/postovert, picture-naming task-fMRI scans; P2 could not. After Protocol A, P1 showed increased activation in LH and right hemisphere, including L and R SMAs. After Protocol B with LEDs only on ipsilesional, LH side, naming ability significantly improved for P1 and P2; the fMRI scans for P1 then showed activation only on the ipsilesional LH side. After Protocol C with LED placements on ipsilesional LH side, plus one midline placement over mesial prefrontal cortex (mPFC) at front hairline, a cortical node of the default mode network (DMN), P3 and P4 had only moderate/poor response, and no increase in functional connectivity on resting-state functional-connectivity MRI. After Protocol D, however, with LED placements on ipsilesional LH side, plus over two midline nodes of DMN, mPFC, and precuneus (high parietal) simultaneously, P5 and P6 each had good response with significant increase in functional connectivity within DMN, p < 0.0005; salience network, p < 0.0005; and central executive network, p < 0.05. Conclusions: NIR photons can affect surface brain cortex areas subjacent to where LEDs are applied on the scalp. Improved naming ability was present with optimal Protocol D. Transcranial photobiomodulation may be an additional noninvasive therapy for stroke.

Long-term effects of curcumin in the non-human primate brain.

Curcumin has recently been shown to be a potential treatment for slowing or ameloriating cognitive decline during aging in our nonhuman primate model of normal aging. In these same monkeys, we studied for the first time the neurological impacts of long-term curcumin treatments using longitudinal magnetic resonance imaging (MRI). Sixteen rhesus monkeys received curcumin or a vehicle control for 14-18 months. We applied a combination of structural and diffusion MRI to determine whether the curcumin resulted in structural or functional changes in focal regions of the brain. The longitudinal imaging revealed decreased microscale diffusivity (mD) measurements mainly in the hippocampus and basal forebrain structures of curcumin treated animals. Changes in generalized fractional anisotropy (GFA) and grey matter density (GMd) measurements indicated an increased grey matter density in cortical ROIs with improved white matter integrity in limbic, cerebellar, and brain stem regions. These findings suggest that noticeable changes in the neuronal environment could be induced from long-term curcumin treatments. Results may provide a neurological basis on the recent findings demonstrating improved spatial working memory and motor function in nonhuman primates.

Corticosterone potentiates DFP-induced neuroinflammation and affects high-order diffusion imaging in a rat model of Gulf War Illness.

Veterans of the 1991 Gulf War were potentially exposed to a variety of toxic chemicals, including sarin nerve agent and pesticides, which have been suspected to be involved in the development of Gulf War Illness (GWI). Several of these exposures cause a neuroinflammatory response in mice, which may serve as a basis for the sickness behavior-like symptoms seen in veterans with GWI. Furthermore, conditions mimicking the physiological stress experienced during the war can exacerbate this effect. While neuroinflammation has been observed post-exposure using animal models, it remains a challenge to evaluate neuroinflammation and its associated cellular and molecular changes in vivo in veterans with GWI. Here, we evaluated neuroimmune-associated alterations in intact brains, applying our existing GWI mouse model to rats, by exposing them to 4days of corticosterone (CORT; 200mg/L in the drinking water), to mimic high physiological stress, followed by a single injection of the sarin nerve agent surrogate, diisopropyl fluorophosphate (DFP; 1.5mg/kg, i.p.). Then, we evaluated the neuroinflammatory responses using qPCR of cytokine mRNA and also examined brain structure with a novel high-order diffusion MRI. We found a CORT-enhancement of DFP-induced neuroinflammation, extending our mouse GWI model to the rat. High order diffusion MRI revealed different patterns among the different treatment groups. Particularly, while the CORT+DFP rats had more restricted spatial patterns in the hippocampus and the hypothalamus, the highest and most wide-spread differences were shown in DFP-treated rats compared to the controls in the thalamus, the amygdala, the piriform cortex and the ventral tegmental area. The association of these diffusion changes with neuroinflammatory cytokine expression indicates the potential for GW-relevant exposures to result in connectivity changes in the brain. By transferring this high order diffusion MRI into in vivo imaging in veterans with GWI, we can achieve further insights on the trajectories of the neuroimmune response over time and its impacts on behavior and potential neurological damage.

Retained executive abilities in mild cognitive impairment are associated with increased white matter network connectivity.

PURPOSE: To describe structural network differences in individuals with mild cognitive impairment (MCI) with high versus low executive abilities, as reflected by measures of white matter connectivity using diffusion tensor imaging (DTI). MATERIALS AND METHODS: This was a retrospective, cross-sectional study. Of the 128 participants from the Alzheimer's Disease Neuroimaging Initiative database who had both a DTI scan as well as a diagnosis of MCI, we used an executive function score to classify the top 15 scoring patients as high executive ability, and the bottom-scoring 16 patients as low executive ability. Using a regions-of-interest-based analysis, we constructed networks and calculated graph theory measures on the constructed networks. We used automated tractography in order to compare differences in major white matter tracts. RESULTS: The high executive ability group yielded greater network size, density and clustering coefficient. The high executive ability group reflected greater fractional anisotropy bilaterally in the inferior and superior longitudinal fasciculi. CONCLUSIONS: The network measures of the high executive ability group demonstrated greater white matter integrity. This suggests that white matter reserve may confer greater protection of executive abilities. Loss of this reserve may lead to greater impairment in the progression to Alzheimer's disease dementia. KEY POINTS: • The MCI high executive ability group yielded a larger network. • The MCI high executive ability group had greater FA in numerous tracts. • White matter reserve may confer greater protection of executive abilities. • Loss of executive reserve may lead to greater impairment in AD dementia.