Increased brain fractional perfusion in obesity using intravoxel incoherent motion (IVIM) MRI metrics.

OBJECTIVE: This research seeks to shed light on the associations between brain perfusion, cognitive function, and mental health in individuals with and without obesity. METHODS: In this study, we employed the noninvasive intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) technique to examine brain fractional perfusion (FP) in two groups: individuals with obesity (N = 72) and healthy controls (N = 66). Additionally, we investigated potential associations between FP, cognitive function, and depressive symptoms in the participants with and without obesity. Finally, artificial intelligence algorithms (Boruta analysis) were also used. RESULTS: Participants with obesity exhibited increased FP within dopaminergic brain circuits, particularly involving prefrontal cortex areas, anterior and posterior sections of the cingulate cortex, the right striatum, and the midbrain. Additionally, these individuals demonstrated lower working memory and higher depressive symptoms compared to the control group. Notably, higher FP in the inferior temporal and occipital cortices correlated with greater depressive symptoms, whereas increased FP in the right ventral caudate and the midbrain was associated with better working memory performance. A link between inflammatory and metabolic variables, with a particular emphasis on monocytes, and FP in obesity was also evidenced by Boruta analysis. CONCLUSIONS: Increased brain perfusion in individuals with obesity is associated with cognitive function and mental health through interaction with metabolic and inflammatory factors.

Unraveling the gut-brain connection: The association of microbiota-linked structural brain biomarkers with behavior and mental health.

AIM: The gut microbiota can influence human behavior. However, due to the massive multiple-testing problem, research into the relationship between microbiome ecosystems and the human brain faces drawbacks. This problem arises when attempting to correlate thousands of gut bacteria with thousands of brain voxels. METHODS: We performed brain magnetic resonance imaging (MRI) scans on 133 participants and applied machine-learning algorithms (Ridge regressions) combined with permutation tests. Using this approach, we were able to correlate specific gut bacterial families with brain MRI signals, circumventing the difficulties of massive multiple testing while considering sex, age, and body mass index as confounding factors. RESULTS: The relative abundance (RA) of the Selenomonadaceae, Clostridiaceae, and Veillonellaceae families in the gut was associated with altered cerebellar, visual, and frontal T2-mapping and diffusion tensor imaging measures. Conversely, decreased relative abundance of the Eubacteriaceae family was also linked to T2-mapping values in the cerebellum. Significantly, the brain regions associated with the gut microbiome were also correlated with depressive symptoms and attentional deficits. CONCLUSIONS: Our analytical strategy offers a promising approach for identifying potential brain biomarkers influenced by gut microbiota. By gathering a deeper understanding of the microbiota-brain connection, we can gain insights into the underlying mechanisms and potentially develop targeted interventions to mitigate the detrimental effects of dysbiosis on brain function and mental health.

Consumption of ultra-processed foods is associated with depression, mesocorticolimbic volume, and inflammation.

BACKGROUND: The consumption of ultra-processed foods and drinks (UPF) has been associated with depression and inflammation and preclinical studies showed that some UPF components disrupt the amygdala-hippocampal complex. We combine diet, clinical and brain imaging data to investigate the relationship between the UPF consumption, depressive symptoms, and brain volumes in humans, considering interactions with obesity, and the mediation effect of inflammation biomarkers. METHODS: One-hundred fifty-two adults underwent diet, depressive symptoms, anatomic magnetic resonance imaging assessments and laboratory tests. Relationships between the % of UPF consumption (in grams) of the total diet, depressive symptoms, and gray matter brain volumes were explored using several adjusted regression models, and in interaction with the presence of obesity. Whether inflammatory biomarkers (i.e., white blood cell count, lipopolysaccharide-binding protein, c-reactive protein) mediate the previous associations was investigated using R mediation package. RESULTS: High UPF consumption was associated with higher depressive symptoms in all participants (ß = 0.178, CI = 0.008-0.261) and in those with obesity (ß = 0.214, CI = -0.004-0.333). Higher consumption was also associated with lower volumes in the posterior cingulate cortex and the left amygdala, which in the participants with obesity also encompassed the left ventral putamen and the dorsal frontal cortex. White blood count levels mediated the association between UPF consumption and depressive symptoms (p = 0.022). LIMITATIONS: The present study precludes any causal conclusions. CONCLUSIONS: UPF consumption is associated with depressive symptoms and lower volumes within the mesocorticolimbic brain network implicated in reward processes and conflict monitoring. Associations were partially dependent on obesity and white blood cell count.

Plasma acylcarnitines and gut-derived aromatic amino acids as sex-specific hub metabolites of the human aging metabolome.

Aging biology entails a cell/tissue deregulated metabolism that affects all levels of biological organization. Therefore, the application of "omic" techniques that are closer to phenotype, such as metabolomics, to the study of the aging process should be a turning point in the definition of cellular processes involved. The main objective of the present study was to describe the changes in plasma metabolome associated with biological aging and the role of sex in the metabolic regulation during aging. A high-throughput untargeted metabolomic analysis was applied in plasma samples to detect hub metabolites and biomarkers of aging incorporating a sex/gender perspective. A cohort of 1030 healthy human adults (45.9% females, and 54.1% males) from 50 to 98 years of age was used. Results were validated using two independent cohorts (1: n = 146, 53% females, 30-100 years old; 2: n = 68, 70% females, 19-107 years old). Metabolites related to lipid and aromatic amino acid (AAA) metabolisms arose as the main metabolic pathways affected by age, with a high influence of sex. Globally, we describe changes in bioenergetic pathways that point to a decrease in mitochondrial ß-oxidation and an accumulation of unsaturated fatty acids and acylcarnitines that could be responsible for the increment of oxidative damage and inflammation characteristic of this physiological process. Furthermore, we describe for the first time the importance of gut-derived AAA catabolites in the aging process describing novel biomarkers that could contribute to better understand this physiological process but also age-related diseases.

The Longitudinal Changes in Subcutaneous Abdominal Tissue and Visceral Adipose Tissue Volumetries Are Associated with Iron Status.

Excess iron is known to trigger adipose tissue dysfunction and insulin resistance. Circulating markers of iron status have been associated with obesity and adipose tissue in cross-sectional studies. We aimed to evaluate whether iron status is linked to changes in abdominal adipose tissue longitudinally. Subcutaneous abdominal tissue (SAT) and visceral adipose tissue (VAT) and its quotient (pSAT) were assessed using magnetic resonance imaging (MRI), at baseline and after one year of follow-up, in 131 (79 in follow-up) apparently healthy subjects, with and without obesity. Insulin sensitivity (euglycemic- hyperinsulinemic clamp) and markers of iron status were also evaluated. Baseline serum hepcidin (p = 0.005 and p = 0.002) and ferritin (p = 0.02 and p = 0.01)) were associated with an increase in VAT and SAT over one year in all subjects, while serum transferrin (p = 0.01 and p = 0.03) and total iron-binding capacity (p = 0.02 and p = 0.04) were negatively associated. These associations were mainly observed in women and in subjects without obesity, and were independent of insulin sensitivity. After controlling for age and sex, serum hepcidin was significantly associated with changes in subcutaneous abdominal tissue index (iSAT) (ß = 0.406, p = 0.007) and visceral adipose tissue index (iVAT) (ß = 0.306, p = 0.04), while changes in insulin sensitivity (ß = 0.287, p = 0.03) and fasting triglycerides (ß = -0.285, p = 0.03) were associated with changes in pSAT. These data indicated that serum hepcidin are associated with longitudinal changes in SAT and VAT, independently of insulin sensitivity. This would be the first prospective study evaluating the redistribution of fat according to iron status and chronic inflammation.

Microbiota alterations in proline metabolism impact depression.

The microbiota-gut-brain axis has emerged as a novel target in depression, a disorder with low treatment efficacy. However, the field is dominated by underpowered studies focusing on major depression not addressing microbiome functionality, compositional nature, or confounding factors. We applied a multi-omics approach combining pre-clinical models with three human cohorts including patients with mild depression. Microbial functions and metabolites converging onto glutamate/GABA metabolism, particularly proline, were linked to depression. High proline consumption was the dietary factor with the strongest impact on depression. Whole-brain dynamics revealed rich club network disruptions associated with depression and circulating proline. Proline supplementation in mice exacerbated depression along with microbial translocation. Human microbiota transplantation induced an emotionally impaired phenotype in mice and alterations in GABA-, proline-, and extracellular matrix-related prefrontal cortex genes. RNAi-mediated knockdown of proline and GABA transporters in Drosophila and mono-association with L. plantarum, a high GABA producer, conferred protection against depression-like states. Targeting the microbiome and dietary proline may open new windows for efficient depression treatment.

The effect of external stimulation on functional networks in the aging healthy human brain.

Understanding the brain changes occurring during aging can provide new insights for developing treatments that alleviate or reverse cognitive decline. Neurostimulation techniques have emerged as potential treatments for brain disorders and to improve cognitive functions. Nevertheless, given the ethical restrictions of neurostimulation approaches, in silico perturbation protocols based on causal whole-brain models are fundamental to gaining a mechanistic understanding of brain dynamics. Furthermore, this strategy could serve to identify neurophysiological biomarkers differentiating between age groups through an exhaustive exploration of the global effect of all possible local perturbations. Here, we used a resting-state fMRI dataset divided into middle-aged (N =310, <65 years) and older adults (N =310, $\geq $65) to characterize brain states in each group as a probabilistic metastable substate (PMS) space. We showed that the older group exhibited a reduced capability to access a metastable substate that overlaps with the rich club. Then, we fitted the PMS to a whole-brain model and applied in silico stimulations in each node to force transitions from the brain states of the older- to the middle-aged group. We found that the precuneus was the best stimulation target. Overall, these findings could have important implications for designing neurostimulation interventions for reversing the effects of aging on whole-brain dynamics.

Higher agreement in endovascular treatment decision-making than in parametric quantifications among automated CT perfusion software packages in acute ischemic stroke.

BACKGROUND AND OBJECTIVE: Estimates of parameters used to select patients for endovascular thrombectomy (EVT) for acute ischemic stroke differ among software packages for automated computed tomography (CT) perfusion analysis. To determine impact of these differences in decision making, we analyzed intra-observer and inter-observer agreement in recommendations about whether to perform EVT based on perfusion maps from 4 packages. METHODS: Perfusion CT datasets from 63 consecutive patients with suspected acute ischemic stroke were retrospectively postprocessed with 4 packages of Minerva, RAPID, Olea, and IntelliSpace Portal (ISP). We used Pearson correlation coefficients and Bland-Altman analysis to compare volumes of infarct core, penumbra, and mismatch calculated by Minerva and RAPID. We used kappa analysis to assess agreement among decisions of 3 radiologists about whether to recommend EVT based on maps generated by 4 packages. RESULTS: We found significant differences between using Minerva and RAPID to estimate penumbra (67.39±41.37mL vs. 78.35±45.38 mL, p < 0.001) and mismatch (48.41±32.03 vs. 61.27±32.73mL, p < 0.001), but not of infarct core (p = 0.230). Pearson correlation coefficients were 0.94 (95%CI:0.90-0.96) for infarct core, 0.87 (95%CI:0.79-0.91) for penumbra, and 0.72 (95%CI:0.57-0.83) for mismatch volumes (p < 0.001). Limits of agreements were (-21.22-25.02) for infarct core volumes, (-54.79-32.88) for penumbra volumes, and (-60.16-34.45) for mismatch volumes. Final agreement for EVT decision-making was substantial between Minerva vs. RAPID (k = 0.722), Minerva vs. Olea (k = 0.761), and RAPID vs. Olea (k = 0.782), but moderate for ISP vs. the other three. CONCLUSIONS: Despite quantitative differences in estimates of infarct core, penumbra, and mismatch using 4 software packages, their impact on radiologists' decisions about EVT is relatively small.

Obesity-associated deficits in inhibitory control are phenocopied to mice through gut microbiota changes in one-carbon and aromatic amino acids metabolic pathways.

BACKGROUND: Inhibitory control (IC) is critical to keep long-term goals in everyday life. Bidirectional relationships between IC deficits and obesity are behind unhealthy eating and physical exercise habits. METHODS: We studied gut microbiome composition and functionality, and plasma and faecal metabolomics in association with cognitive tests evaluating inhibitory control (Stroop test) and brain structure in a discovery (n=156), both cross-sectionally and longitudinally, and in an independent replication cohort (n=970). Faecal microbiota transplantation (FMT) in mice evaluated the impact on reversal learning and medial prefrontal cortex (mPFC) transcriptomics. RESULTS: An interplay among IC, brain structure (in humans) and mPFC transcriptomics (in mice), plasma/faecal metabolomics and the gut metagenome was found. Obesity-dependent alterations in one-carbon metabolism, tryptophan and histidine pathways were associated with IC in the two independent cohorts. Bacterial functions linked to one-carbon metabolism (thyX,dut, exodeoxyribonuclease V), and the anterior cingulate cortex volume were associated with IC, cross-sectionally and longitudinally. FMT from individuals with obesity led to alterations in mice reversal learning. In an independent FMT experiment, human donor's bacterial functions related to IC deficits were associated with mPFC expression of one-carbon metabolism-related genes of recipient's mice. CONCLUSION: These results highlight the importance of targeting obesity-related impulsive behaviour through the induction of gut microbiota shifts.

Whole-Brain Dynamics in Aging: Disruptions in Functional Connectivity and the Role of the Rich Club.

Normal aging causes disruptions in the brain that can lead to cognitive decline. Resting-state functional magnetic resonance imaging studies have found significant age-related alterations in functional connectivity across various networks. Nevertheless, most of the studies have focused mainly on static functional connectivity. Studying the dynamics of resting-state brain activity across the whole-brain functional network can provide a better characterization of age-related changes. Here, we employed two data-driven whole-brain approaches based on the phase synchronization of blood-oxygen-level-dependent signals to analyze resting-state fMRI data from 620 subjects divided into two groups (middle-age group (n = 310); age range, 50-64 years versus older group (n = 310); age range, 65-91 years). Applying the intrinsic-ignition framework to assess the effect of spontaneous local activation events on local-global integration, we found that the older group showed higher intrinsic ignition across the whole-brain functional network, but lower metastability. Using Leading Eigenvector Dynamics Analysis, we found that the older group showed reduced ability to access a metastable substate that closely overlaps with the so-called rich club. These findings suggest that functional whole-brain dynamics are altered in aging, probably due to a deficiency in a metastable substate that is key for efficient global communication in the brain.

Obesity Impairs Short-Term and Working Memory through Gut Microbial Metabolism of Aromatic Amino Acids.

The gut microbiome has been linked to fear extinction learning in animal models. Here, we aimed to explore the gut microbiome and memory domains according to obesity status. A specific microbiome profile associated with short-term memory, working memory, and the volume of the hippocampus and frontal regions of the brain differentially in human subjects with and without obesity. Plasma and fecal levels of aromatic amino acids, their catabolites, and vegetable-derived compounds were longitudinally associated with short-term and working memory. Functionally, microbiota transplantation from human subjects with obesity led to decreased memory scores in mice, aligning this trait from humans with that of recipient mice. RNA sequencing of the medial prefrontal cortex of mice revealed that short-term memory associated with aromatic amino acid pathways, inflammatory genes, and clusters of bacterial species. These results highlight the potential therapeutic value of targeting the gut microbiota for memory impairment, specifically in subjects with obesity.

Bariatric Surgery-Induced Changes in Intima-Media Thickness and Cardiovascular Risk Factors in Class 3 Obesity: A 3-Year Follow-Up Study.

OBJECTIVE: The impact of weight loss induced by bariatric surgery (BS) and nonsurgical approaches on cardiovascular risk factors (CVRFs) has not been fully elucidated. We assessed the effects of BS and a nonsurgical approach on carotid intima-media thickness (CIMT) and CVRFs in participants with class 3 obesity. METHODS: A total of 87 participants with obesity (59 women; 46 [37-52] years old; BMI, 43 [40-47]) and 75 controls were recruited; 21 (25%) participants with obesity underwent BS. BMI, blood pressure, cholesterol, triglycerides, fasting plasma glucose, C-reactive protein, CIMT, and Framingham Risk Score were measured at baseline and at 3-year follow-up. Independent factors for reduction in CIMT were analyzed. The literature on the effects of BS and CIMT was reviewed. RESULTS: After BS, BMI decreased from 45.45 to 27.28 (P < 0.001), and mean CIMT decreased from 0.64 mm (0.56-0.75 mm) to 0.54 mm (0.46-0.65) mm (P < 0.012), equivalent to 0.005 mm/kg of weight lost. At 3-year follow-up, participants who had undergone BS had similar CIMT and CVRFs to the control group. No changes in CVRFs were seen related to the nonsurgical approach. BMI reduction after BS had the strongest independent association with decreased CIMT. CONCLUSIONS: Weight loss after BS decreases CIMT and CVRFs in middle-aged participants with class 3 obesity, resulting in CIMT similar to that observed in lean participants.

The Aging Imageomics Study: rationale, design and baseline characteristics of the study population.

Biomarkers of aging are urgently needed to identify individuals at high risk of developing age-associated disease or disability. Growing evidence from population-based studies points to whole-body magnetic resonance imaging's (MRI) enormous potential for quantifying subclinical disease burden and for assessing changes that occur with aging in all organ systems. The Aging Imageomics Study aims to identify biomarkers of human aging by analyzing imaging, biopsychosocial, cardiovascular, metabolomic, lipidomic, and microbiome variables. This study recruited 1030 participants aged ≥50 years (mean 67, range 50-96 years) that underwent structural and functional MRI to evaluate the brain, large blood vessels, heart, abdominal organs, fat, spine, musculoskeletal system and ultrasonography to assess carotid intima-media thickness and plaques. Patients were notified of incidental findings detected by a certified radiologist when necessary. Extensive data were also collected on anthropometrics, demographics, health history, neuropsychology, employment, income, family status, exposure to air pollution and cardiovascular status. In addition, several types of samples were gathered to allow for microbiome, metabolomic and lipidomic profiling. Using big data techniques to analyze all the data points from biological phenotyping together with health records and lifestyle measures, we aim to cultivate a deeper understanding about various biological factors (and combinations thereof) that underlie healthy and unhealthy aging.

Glycated Hemoglobin, but not Insulin Sensitivity, is Associated with Memory in Subjects with Obesity.

OBJECTIVE: Obesity has been related to later-life dementia. Serum glucose levels and insulin resistance are known to influence cognition in individuals with diabetes. This study aimed to evaluate memory function in middle-aged individuals with obesity in association with glucose metabolism and brain iron content. METHODS: This was a cross-sectional case-control study including 121 participants aged 27.2 to 66.6 years (56 without obesity, 65 with obesity) stratified according to sex and menopausal status. Insulin sensitivity, body composition, brain iron content, and memory function were evaluated by euglycemic hyperinsulinemic clamp, dual-energy x-ray absorptiometry, magnetic resonance relaxometry (R2*), and California Verbal Learning Test, respectively. RESULTS: Women with obesity, but not men, had lower scores in some California Verbal Learning Tests in association with metabolic parameters and increased brain iron content compared with controls. Fasting plasma glucose, glycated hemoglobin (HbA1c; within normal range), and R2* were negatively associated with memory scores, whereas insulin sensitivity showed positive associations. Remarkably, only HbA1c levels and R2* in the right inferior fronto-orbital region remained significant after controlling for age, sex, education, and BMI. CONCLUSIONS: Impairments in memory function in middle-aged women with obesity are associated with HbA1c levels and brain iron content independently of insulin sensitivity. These results may have implications in the design of therapeutic strategies in women with obesity.

Macrovascular Networks on Contrast-Enhanced Magnetic Resonance Imaging Improves Survival Prediction in Newly Diagnosed Glioblastoma.

A higher degree of angiogenesis is associated with shortened survival in glioblastoma. Feasible morphometric parameters for analyzing vascular networks in brain tumors in clinical practice are lacking. We investigated whether the macrovascular network classified by the number of vessel-like structures (nVS) visible on three-dimensional T1-weighted contrast⁻enhanced (3D-T1CE) magnetic resonance imaging (MRI) could improve survival prediction models for newly diagnosed glioblastoma based on clinical and other imaging features. Ninety-seven consecutive patients (62 men; mean age, 58 ± 15 years) with histologically proven glioblastoma underwent 1.5T-MRI, including anatomical, diffusion-weighted, dynamic susceptibility contrast perfusion, and 3D-T1CE sequences after 0.1 mmol/kg gadobutrol. We assessed nVS related to the tumor on 1-mm isovoxel 3D-T1CE images, and relative cerebral blood volume, relative cerebral flow volume (rCBF), delay mean time, and apparent diffusion coefficient in volumes of interest for contrast-enhancing lesion (CEL), non-CEL, and contralateral normal-appearing white matter. We also assessed Visually Accessible Rembrandt Images scoring system features. We used ROC curves to determine the cutoff for nVS and univariate and multivariate cox proportional hazards regression for overall survival. Prognostic factors were evaluated by Kaplan-Meier survival and ROC analyses. Lesions with nVS > 5 were classified as having highly developed macrovascular network; 58 (60.4%) tumors had highly developed macrovascular network. Patients with highly developed macrovascular network were older, had higher volumeCEL, increased rCBFCEL, and poor survival; nVS correlated negatively with survival (r = -0.286; p = 0.008). On multivariate analysis, standard treatment, age at diagnosis, and macrovascular network best predicted survival at 1 year (AUC 0.901, 83.3% sensitivity, 93.3% specificity, 96.2% PPV, 73.7% NPV). Contrast-enhanced MRI macrovascular network improves survival prediction in newly diagnosed glioblastoma.

Resting-State Functional Connectivity Magnetic Resonance Imaging and Outcome After Acute Stroke.

Background and Purpose- Physiological effects of stroke are best assessed over entire brain networks rather than just focally at the site of structural damage. Resting-state functional magnetic resonance imaging can map functional-anatomic networks by analyzing spontaneously correlated low-frequency activity fluctuations across the brain, but its potential usefulness in predicting functional outcome after acute stroke remains unknown. We assessed the ability of resting-state functional magnetic resonance imaging to predict functional outcome after acute stroke. Methods- We scanned 37 consecutive reperfused stroke patients (age, 69±14 years; 14 females; 3-day National Institutes of Health Stroke Scale score, 6±5) on day 3 after symptom onset. After imaging preprocessing, we used a whole-brain mask to calculate the correlation coefficient matrices for every paired region using the Harvard-Oxford probabilistic atlas. To evaluate functional outcome, we applied the modified Rankin Scale at 90 days. We used region of interest analyses to explore the functional connectivity between regions and graph-computation analysis to detect differences in functional connectivity between patients with good functional outcome (modified Rankin Scale score ≤2) and those with poor outcome (modified Rankin Scale score >2). Results- Patients with good outcome had greater functional connectivity than patients with poor outcome. Although 3-day National Institutes of Health Stroke Scale score was the most accurate independent predictor of 90-day modified Rankin Scale (84.2%), adding functional connectivity increased accuracy to 94.7%. Preserved bilateral interhemispheric connectivity between the anterior inferior temporal gyrus and superior frontal gyrus and decreased connectivity between the caudate and anterior inferior temporal gyrus in the left hemisphere had the greatest impact in favoring good prognosis. Conclusions- These data suggest that information about functional connectivity from resting-state functional magnetic resonance imaging may help predict 90-day stroke outcome.

High-permeability region size on perfusion CT predicts hemorrhagic transformation after intravenous thrombolysis in stroke.

OBJECTIVE: Blood-brain barrier (BBB) permeability has been proposed as a predictor of hemorrhagic transformation (HT) after tissue plasminogen activator (tPA) administration; however, the reliability of perfusion computed tomography (PCT) permeability imaging for predicting HT is uncertain. We aimed to determine the performance of high-permeability region size on PCT (HPrs-PCT) in predicting HT after intravenous tPA administration in patients with acute stroke. METHODS: We performed a multimodal CT protocol (non-contrast CT, PCT, CT angiography) to prospectively study patients with middle cerebral artery occlusion treated with tPA within 4.5 hours of symptom onset. HT was graded at 24 hours using the European-Australasian Acute Stroke Study II criteria. ROC curves selected optimal volume threshold, and multivariate logistic regression analysis identified predictors of HT. RESULTS: The study included 156 patients (50% male, median age 75.5 years). Thirty-seven (23,7%) developed HT [12 (7,7%), parenchymal hematoma type 2 (PH-2)]. At admission, patients with HT had lower platelet values, higher NIHSS scores, increased ischemic lesion volumes, larger HPrs-PCT, and poorer collateral status. The negative predictive value of HPrs-PCT at a threshold of 7mL/100g/min was 0.84 for HT and 0.93 for PH-2. The multiple regression analysis selected HPrs-PCT at 7mL/100g/min combined with platelets and baseline NIHSS score as the best model for predicting HT (AUC 0.77). HPrs-PCT at 7mL/100g/min was the only independent predictor of PH-2 (OR 1, AUC 0.68, p = 0.045). CONCLUSIONS: HPrs-PCT can help predict HT after tPA, and is particularly useful in identifying patients at low risk of developing HT.

The Gut Metagenome Changes in Parallel to Waist Circumference, Brain Iron Deposition, and Cognitive Function.

Context: Microbiota perturbations seem to exert modulatory effects on emotional behavior, stress-, and pain-modulation systems in adult animals; however, limited information is available in humans. Objective: To study potential relationships among the gut metagenome, brain microstructure, and cognitive performance in middle-aged, apparently healthy, obese and nonobese subjects after weight changes. Design: This is a longitudinal study over a 2-year period. Setting: A tertiary public hospital. Patients or Other Participants: Thirty-five (18 obese) apparently healthy subjects. Intervention(s): Diet counseling was provided to all subjects. Obese subjects were followed every 6 months. Main Outcome Measure(s): Brain relaxometry (using magnetic resonance R2*), cognitive performance (by means of cognitive tests), and gut microbiome composition (shotgun). Results: R2* increased in both obese and nonobese subjects, independent of weight variations. Changes in waist circumference, but not in body mass index, were associated with brain iron deposition (R2*) in the striatum, amygdala, and hippocampus in parallel to visual-spatial constructional ability and circulating beta amyloid Aß42 levels. These changes were linked to shifts in gut microbiome in which the relative abundance of bacteria belonging to Caldiserica and Thermodesulfobacteria phyla were reciprocally associated with raised R2* in different brain nuclei. Of note, the increase in bacteria belonging to Tenericutes phylum was parallel to decreased R2* gain in the striatum, serum Aß42 levels, and spared visual-spatial constructional ability. Interestingly, metagenome functions associated with circulating and brain iron stores are involved in bacterial generation of siderophores. Conclusions: Changes in the gut metagenome are associated longitudinally with cognitive function and brain iron deposition.

Diffusion tensor imaging as a prognostic biomarker for motor recovery and rehabilitation after stroke.

PURPOSE: Despite improved acute treatment and new tools to facilitate recovery, most patients have motor deficits after stroke, often causing disability. However, motor impairment varies considerably among patients, and recovery in the acute/subacute phase is difficult to predict using clinical measures alone, particularly in severely impaired patients. Accurate early prediction of recovery would help rationalize rehabilitation goals and improve the design of trials testing strategies to facilitate recovery. METHODS: We review the role of diffusion tensor imaging (DTI) in predicting motor recovery after stroke, in monitoring treatment response, and in evaluating white matter remodeling. We critically appraise DTI studies and discuss their limitations, and we explore directions for future study. RESULTS: Growing evidence suggests that combining clinical scores with information about corticospinal tract (CST) integrity can improve predictions about motor outcome. The extent of CST damage on DTI and/or the overlap between the CST and a lesion are key prognostic factor that determines motor performance and outcome. Three main strategies to quantify stroke-related CST damage have been proposed: (i) measuring FA distal to the stroke area, (ii) measuring the number of fibers that go through the stroke with tractography, and (iii) measuring the overlap between the stroke and a CST map derived from healthy age- and gender-matched controls. CONCLUSION: Recovery of motor function probably involves remodeling of the CST proper and/or a greater reliance on alternative motor tracts through spontaneous and treatment-induced plasticity. DTI-metrics represent promising clinical biomarkers to predict motor recovery and to monitor and predict the response to neurorehabilitative interventions.