Normalization of cerebral hemodynamics after hematopoietic stem cell transplant in children with sickle cell disease.

Children with sickle cell disease (SCD) demonstrate cerebral hemodynamic stress and are at high risk of strokes. We hypothesized that curative hematopoietic stem cell transplant (HSCT) normalizes cerebral hemodynamics in children with SCD compared with pre-transplant baseline. Whole-brain cerebral blood flow (CBF) and oxygen extraction fraction (OEF) were measured by magnetic resonance imaging 1 to 3 months before and 12 to 24 months after HSCT in 10 children with SCD. Three children had prior overt strokes, 5 children had prior silent strokes, and 1 child had abnormal transcranial Doppler ultrasound velocities. CBF and OEF of HSCT recipients were compared with non-SCD control participants and with SCD participants receiving chronic red blood cell transfusion therapy (CRTT) before and after a scheduled transfusion. Seven participants received matched sibling donor HSCT, and 3 participants received 8 out of 8 matched unrelated donor HSCT. All received reduced-intensity preparation and maintained engraftment, free of hemolytic anemia and SCD symptoms. Pre-transplant, CBF (93.5 mL/100 g/min) and OEF (36.8%) were elevated compared with non-SCD control participants, declining significantly 1 to 2 years after HSCT (CBF, 72.7 mL/100 g per minute; P = .004; OEF, 27.0%; P = .002), with post-HSCT CBF and OEF similar to non-SCD control participants. Furthermore, HSCT recipients demonstrated greater reduction in CBF (-19.4 mL/100 g/min) and OEF (-8.1%) after HSCT than children with SCD receiving CRTT after a scheduled transfusion (CBF, -0.9 mL/100 g/min; P = .024; OEF, -3.3%; P = .001). Curative HSCT normalizes whole-brain hemodynamics in children with SCD. This restoration of cerebral oxygen reserve may explain stroke protection after HSCT in this high-risk patient population.

A Critical Role for ERO1α in Arterial Thrombosis and Ischemic Stroke.

BACKGROUND: Platelet adhesion and aggregation play a crucial role in arterial thrombosis and ischemic stroke. Here, we identify platelet ERO1α (endoplasmic reticulum oxidoreductase 1α) as a novel regulator of Ca2+ signaling and a potential pharmacological target for treating thrombotic diseases. METHODS: Intravital microscopy, animal disease models, and a wide range of cell biological studies were utilized to demonstrate the pathophysiological role of ERO1α in arteriolar and arterial thrombosis and to prove the importance of platelet ERO1α in platelet activation and aggregation. Mass spectrometry, electron microscopy, and biochemical studies were used to investigate the molecular mechanism. We used novel blocking antibodies and small-molecule inhibitors to study whether ERO1α can be targeted to attenuate thrombotic conditions. RESULTS: Megakaryocyte-specific or global deletion of Ero1α in mice similarly reduced platelet thrombus formation in arteriolar and arterial thrombosis without affecting tail bleeding times and blood loss following vascular injury. We observed that platelet ERO1α localized exclusively in the dense tubular system and promoted Ca2+ mobilization, platelet activation, and aggregation. Platelet ERO1α directly interacted with STIM1 (stromal interaction molecule 1) and SERCA2 (sarco/endoplasmic reticulum Ca2+-ATPase 2) and regulated their functions. Such interactions were impaired in mutant STIM1-Cys49/56Ser and mutant SERCA2-Cys875/887Ser. We found that ERO1α modified an allosteric Cys49-Cys56 disulfide bond in STIM1 and a Cys875-Cys887 disulfide bond in SERCA2, contributing to Ca2+ store content and increasing cytosolic Ca2+ levels during platelet activation. Inhibition of Ero1α with small-molecule inhibitors but not blocking antibodies attenuated arteriolar and arterial thrombosis and reduced infarct volume following focal brain ischemia in mice. CONCLUSIONS: Our results suggest that ERO1α acts as a thiol oxidase for Ca2+ signaling molecules, STIM1 and SERCA2, and enhances cytosolic Ca2+ levels, promoting platelet activation and aggregation. Our study provides evidence that ERO1α may be a potential target to reduce thrombotic events.

Impact of Sleep Disorders and Disturbed Sleep on Brain Health: A Scientific Statement From the American Heart Association.

Accumulating evidence supports a link between sleep disorders, disturbed sleep, and adverse brain health, ranging from stroke to subclinical cerebrovascular disease to cognitive outcomes, including the development of Alzheimer disease and Alzheimer disease-related dementias. Sleep disorders such as sleep-disordered breathing (eg, obstructive sleep apnea), and other sleep disturbances, as well, some of which are also considered sleep disorders (eg, insomnia, sleep fragmentation, circadian rhythm disorders, and extreme sleep duration), have been associated with adverse brain health. Understanding the causal role of sleep disorders and disturbances in the development of adverse brain health is complicated by the common development of sleep disorders among individuals with neurodegenerative disease. In addition to the role of sleep disorders in stroke and cerebrovascular injury, mechanistic hypotheses linking sleep with brain health and biomarker data (blood-based, cerebrospinal fluid-based, and imaging) suggest direct links to Alzheimer disease-specific pathology. These potential mechanisms and the increasing understanding of the "glymphatic system," and the recognition of the importance of sleep in poststroke recovery, as well, support a biological basis for the indirect (through the worsening of vascular disease) and direct (through specific effects on neuropathology) connections between sleep disorders and brain health. Given promising evidence for the benefits of treatment and prevention, sleep disorders and disturbances represent potential targets for early treatment that may improve brain health more broadly. In this scientific statement, we discuss the evidence supporting an association between sleep disorders and disturbances and poor brain health ranging from stroke to dementia and opportunities for prevention and early treatment.

Accuracy of TrUE-Net in comparison to established white matter hyperintensity segmentation methods: An independent validation study.

White matter hyperintensities (WMH) are nearly ubiquitous in the aging brain, and their topography and overall burden are associated with cognitive decline. Given their numerosity, accurate methods to automatically segment WMH are needed. Recent developments, including the availability of challenge data sets and improved deep learning algorithms, have led to a new promising deep-learning based automated segmentation model called TrUE-Net, which has yet to undergo rigorous independent validation. Here, we compare TrUE-Net to six established automated WMH segmentation tools, including a semi-manual method. We evaluated the techniques at both global and regional level to compare their ability to detect the established relationship between WMH burden and age. We found that TrUE-Net was highly reliable at identifying WMH regions with low false positive rates, when compared to semi-manual segmentation as the reference standard. TrUE-Net performed similarly or favorably when compared to the other automated techniques. Moreover, TrUE-Net was able to detect relationships between WMH and age to a similar degree as the reference standard semi-manual segmentation at both the global and regional level. These results support the use of TrUE-Net for identifying WMH at the global or regional level, including in large, combined datasets.

Peripheral sensory stimulation elicits global slow waves by recruiting somatosensory cortex bilaterally.

Slow waves (SWs) are globally propagating, low-frequency (0.5- to 4-Hz) oscillations that are prominent during sleep and anesthesia. SWs are essential to neural plasticity and memory. However, much remains unknown about the mechanisms coordinating SW propagation at the macroscale. To assess SWs in the context of macroscale networks, we recorded cortical activity in awake and ketamine/xylazine-anesthetized mice using widefield optical imaging with fluorescent calcium indicator GCaMP6f. We demonstrate that unilateral somatosensory stimulation evokes bilateral waves that travel across the cortex with state-dependent trajectories. Under anesthesia, we observe that rhythmic stimuli elicit globally resonant, front-to-back propagating SWs. Finally, photothrombotic lesions of S1 show that somatosensory-evoked global SWs depend on bilateral recruitment of homotopic primary somatosensory cortices. Specifically, unilateral lesions of S1 disrupt somatosensory-evoked global SW initiation from either hemisphere, while spontaneous SWs are largely unchanged. These results show that evoked SWs may be triggered by bilateral activation of specific, homotopically connected cortical networks.

CSF-Based Volumetric Imaging Biomarkers Highlight Incidence and Risk Factors for Cerebral Edema After Ischemic Stroke.

BACKGROUND: Cerebral edema has primarily been studied using midline shift or clinical deterioration as end points, which only captures the severe and delayed manifestations of a process affecting many patients with stroke. Quantitative imaging biomarkers that measure edema severity across the entire spectrum could improve its early detection, as well as identify relevant mediators of this important stroke complication. METHODS: We applied an automated image analysis pipeline to measure the displacement of cerebrospinal fluid (ΔCSF) and the ratio of lesional versus contralateral hemispheric cerebrospinal fluid (CSF) volume (CSF ratio) in a cohort of 935 patients with hemispheric stroke with follow-up computed tomography scans taken a median of 26 h (interquartile range 24-31) after stroke onset. We determined diagnostic thresholds based on comparison to those without any visible edema. We modeled baseline clinical and radiographic variables against each edema biomarker and assessed how each biomarker was associated with stroke outcome (modified Rankin Scale at 90 days). RESULTS: The displacement of CSF and CSF ratio were correlated with midline shift (r = 0.52 and - 0.74, p < 0.0001) but exhibited broader ranges. A ΔCSF of greater than 14% or a CSF ratio below 0.90 identified those with visible edema: more than half of the patients with stroke met these criteria, compared with only 14% who had midline shift at 24 h. Predictors of edema across all biomarkers included a higher National Institutes of Health Stroke Scale score, a lower Alberta Stroke Program Early CT score, and lower baseline CSF volume. A history of hypertension and diabetes (but not acute hyperglycemia) predicted greater ΔCSF but not midline shift. Both ΔCSF and a lower CSF ratio were associated with worse outcome, adjusting for age, National Institutes of Health Stroke Scale score, and Alberta Stroke Program Early CT score (odds ratio 1.7, 95% confidence interval 1.3-2.2 per 21% ΔCSF). CONCLUSIONS: Cerebral edema can be measured in a majority of patients with stroke on follow-up computed tomography using volumetric biomarkers evaluating CSF shifts, including in many without visible midline shift. Edema formation is influenced by clinical and radiographic stroke severity but also by chronic vascular risk factors and contributes to worse stroke outcomes.

Toward Automated Detection of Silent Cerebral Infarcts in Children and Young Adults With Sickle Cell Anemia.

BACKGROUND: Silent cerebral infarcts (SCI) in sickle cell anemia (SCA) are associated with future strokes and cognitive impairment, warranting early diagnosis and treatment. Detection of SCI, however, is limited by their small size, especially when neuroradiologists are unavailable. We hypothesized that deep learning may permit automated SCI detection in children and young adults with SCA as a tool to identify the presence and extent of SCI in clinical and research settings. METHODS: We utilized UNet-a deep learning model-for fully automated SCI segmentation. We trained and optimized UNet using brain magnetic resonance imaging from the SIT trial (Silent Infarct Transfusion). Neuroradiologists provided the ground truth for SCI diagnosis, while a vascular neurologist manually delineated SCI on fluid-attenuated inversion recovery and provided the ground truth for SCI segmentation. UNet was optimized for the highest spatial overlap between automatic and manual delineation (dice similarity coefficient). The optimized UNet was externally validated using an independent single-center prospective cohort of SCA participants. Model performance was evaluated through sensitivity and accuracy (%correct cases) for SCI diagnosis, dice similarity coefficient, intraclass correlation coefficient (metric of volumetric agreement), and Spearman correlation. RESULTS: The SIT trial (n=926; 31% with SCI; median age, 8.9 years) and external validation (n=80; 50% with SCI; age, 11.5 years) cohorts had small median lesion volumes of 0.40 and 0.25 mL, respectively. Compared with the neuroradiology diagnosis, UNet predicted SCI presence with 100% sensitivity and 74% accuracy. In magnetic resonance imaging with SCI, UNet reached a moderate spatial agreement (dice similarity coefficient, 0.48) and high volumetric agreement (intraclass correlation coefficient, 0.76; ρ=0.72; P<0.001) between automatic and manual segmentations. CONCLUSIONS: UNet, trained using a large pediatric SCA magnetic resonance imaging data set, sensitively detected small SCI in children and young adults with SCA. While additional training is needed, UNet may be integrated into the clinical workflow as a screening tool, aiding in SCI diagnosis.

A Multivariate Functional Connectivity Approach to Mapping Brain Networks and Imputing Neural Activity in Mice.

Temporal correlation analysis of spontaneous brain activity (e.g., Pearson "functional connectivity," FC) has provided insights into the functional organization of the human brain. However, bivariate analysis techniques such as this are often susceptible to confounding physiological processes (e.g., sleep, Mayer-waves, breathing, motion), which makes it difficult to accurately map connectivity in health and disease as these physiological processes affect FC. In contrast, a multivariate approach to imputing individual neural networks from spontaneous neuroimaging data could be influential to our conceptual understanding of FC and provide performance advantages. Therefore, we analyzed neural calcium imaging data from Thy1-GCaMP6f mice while either awake, asleep, anesthetized, during low and high bouts of motion, or before and after photothrombotic stroke. A linear support vector regression approach was used to determine the optimal weights for integrating the signals from the remaining pixels to accurately predict neural activity in a region of interest (ROI). The resultant weight maps for each ROI were interpreted as multivariate functional connectivity (MFC), resembled anatomical connectivity, and demonstrated a sparser set of strong focused positive connections than traditional FC. While global variations in data have large effects on standard correlation FC analysis, the MFC mapping methods were mostly impervious. Lastly, MFC analysis provided a more powerful connectivity deficit detection following stroke compared to traditional FC.

The Moderating Role of Motivation in the Real-Time Associations of Fatigue, Cognitive Complaints, and Pain With Depressed Mood Among Stroke Survivors: An Ecological Momentary Assessment Study.

OBJECTIVE: Stroke symptoms fluctuate during the day as stroke survivors participate in daily activities. Understanding the real-time associations among stroke symptoms and depressed mood, as well as the role of motivation for daily activities, informs, and post-stroke symptom management in the context of everyday living. This study aimed to (1) investigate the real-time associations of fatigue, cognitive complaints, and pain with depressed mood and (2) examine the role of motivation for daily activity participation as a potential moderator of these associations in stroke survivors. DESIGN: A prospective cohort study involving 7 days of ecological momentary assessment (EMA), during which participants completed 8 EMA surveys per day. Multilevel modeling was used to analyze data. SETTING: Community. PARTICIPANTS: Forty community-dwelling stroke survivors (N=40). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: EMA measures of depressed mood, stroke symptoms (physical and mental fatigue, cognitive complaints, and pain), and motivation (autonomous motivation, controlled motivation). RESULTS: Higher levels of within- and between-person physical fatigue, mental fatigue, cognitive complaints, and pain were momentarily associated with greater depressed mood (Ps<.001). Within-person autonomous motivation significantly buffered the momentary associations of physical fatigue (B=-0.06, P<.001), mental fatigue (B=-0.04, P=.032), and pain (B=-0.21, P<.001) with depressed mood. CONCLUSIONS: Findings indicate the momentary associations of fatigue, cognitive complaints, and pain with depressed mood in stroke survivors. Autonomous motivation underpinning daily activity participation was found to buffer the associations of fatigue and pain with depressed mood. Promoting autonomous motivation for daily activity participation may be viable for preventing and mitigating poststroke depression.

Post-stroke Depressive Symptoms and Cognitive Performances: A Network Analysis.

OBJECTIVE: To examine the relationships between post-stroke depression and cognition using network analysis. In particular, we identified central depressive symptoms, central cognitive performances, and bridge components that connect these 2 constructs. DESIGN: An observational study. We applied network analysis to analyze baseline data to visualize and quantify the relationships between depression and cognition. SETTING: Home and Community. PARTICIPANTS: 202 participants with mild-to-moderate stroke (N=202; mean age: 59.7 years; 55% men; 55% Whites; 90% ischemic stroke). INTERVENTION: Not applicable. MAIN OUTCOME MEASURES: Patient Health Questionnaire (PHQ-8) for depressive symptoms and the NIH Toolbox Cognitive Battery for cognitive performances. RESULTS: Depressive symptoms were positively intercorrelated with the network, with symptoms from similar domains clustered together. Mood (expected influence=1.58), concentration (expected influence=0.67), and guilt (expected influence=0.63) were the top 3 central depressive symptoms. Cognitive performances also showed similar network patterns, with executive function (expected influence=0.89), expressive language (expected influence=0.68), and processing speed (expected influence=0.48) identified as the top 3 central cognitive performances. Psychomotor functioning (bridge expected influence=2.49) and attention (bridge expected influence=1.10) were the components connecting depression and cognition. CONCLUSIONS: The central and bridge components identified in this study might serve as targets for interventions against these deficits. Future trials are needed to compare the effectiveness of interventions targeting the central and bridge components vs general interventions treating depression and cognitive impairment as a homogenous clinical syndrome.

Neurotoxic and cardiotoxic effects of N-methyl-1-(naphthalen-2-yl)propan-2-amine (methamnetamine) and 1-phenyl-2-pyrrolidinylpentane (prolintane).

Two synthetic phenylethylamines, N-methyl-1-(naphthalen-2-yl)propan-2-amine (MNA) and 1-phenyl-2-pyrrolidinylpentane (prolintane), are being abused by people seeking hallucinogens for pleasure. These new psychotropic substances may provoke problems because there is no existing information about their toxicity and pharmacological behaviors. Therefore, we evaluated the safety of nerves and cardiovascular systems by determining toxicity after MNA and prolintane drugs administrations to mice and rat. Consequently, side effects such as increased spontaneous motion and body temperature were observed in oral administration of MNA. In addition, both substances reduced motor coordination levels. The IHC tests were conducted to see whether the immune response also shows abnormalities in brain tissue compared to the control group. It has been confirmed that the length of allograft inflammatory factor 1(IBA-1), an immune antibody known as microglia marker, has been shortened. We identified that a problem with the contact between synapses and neurons might be possibly produced. In the assessment of the cardiac toxicity harmfulness, no substances have been confirmed to be toxic to myocardial cells, but at certain concentrations, they have caused the QT prolongation, an indicator of ventricular arrhythmia. In addition, the hERG potassium channel, the biomarker of the QT prolongation, has been checked for inhibition. The results revealed that the possibility of QT prolongation through the hERG channel could not be excluded, and the two substances can be considered toxic that may cause ventricular arrhythmia. In sum, this study demonstrated that the possibility of toxicity in MNA and prolintane compounds might bring many harmful effects on nerves and hearts.

White matter hyperintensity longitudinal morphometric analysis in association with Alzheimer disease.

INTRODUCTION: Vascular damage in Alzheimer's disease (AD) has shown conflicting findings particularly when analyzing longitudinal data. We introduce white matter hyperintensity (WMH) longitudinal morphometric analysis (WLMA) that quantifies WMH expansion as the distance from lesion voxels to a region of interest boundary. METHODS: WMH segmentation maps were derived from 270 longitudinal fluid-attenuated inversion recovery (FLAIR) ADNI images. WLMA was performed on five data-driven WMH patterns with distinct spatial distributions. Amyloid accumulation was evaluated with WMH expansion across the five WMH patterns. RESULTS: The preclinical group had significantly greater expansion in the posterior ventricular WM compared to controls. Amyloid significantly associated with frontal WMH expansion primarily within AD individuals. WLMA outperformed WMH volume changes for classifying AD from controls primarily in periventricular and posterior WMH. DISCUSSION: These data support the concept that localized WMH expansion continues to proliferate with amyloid accumulation throughout the entirety of the disease in distinct spatial locations.

Oxygen Metabolic Stress and White Matter Injury in Patients With Cerebral Small Vessel Disease.

BACKGROUND: Chronic hypoxia-ischemia is a putative mechanism underlying the development of white matter hyperintensities (WMH) and microstructural disruption in cerebral small vessel disease. WMH fall primarily within deep white matter (WM) watershed regions. We hypothesized that elevated oxygen extraction fraction (OEF), a signature of hypoxia-ischemia, would be detected in the watershed where WMH density is highest. We further hypothesized that OEF would be elevated in regions immediately surrounding WMH, at the leading edge of growth. METHODS: In this cross-sectional study conducted from 2016 to 2019 at an academic medical center in St Louis, MO, participants (age >50) with a range of cerebrovascular risk factors underwent brain magnetic resonance imaging using pseudocontinuous arterial spin labeling, asymmetric spin echo, fluid-attenuated inversion recovery and diffusion tensor imaging to measure cerebral blood flow (CBF), OEF, WMH, and WM integrity, respectively. We defined the physiologic watershed as a region where CBF was below the 10th percentile of mean WM CBF in a young healthy cohort. We conducted linear regression to evaluate the relationship between CBF and OEF with structural and microstructural WM injury defined by fluid-attenuated inversion recovery WMH and diffusion tensor imaging, respectively. We conducted ANOVA to determine if OEF was increased in proximity to WMH lesions. RESULTS: In a cohort of 42 participants (age 50-80), the physiologic watershed region spatially overlapped with regions of highest WMH lesion density. As CBF decreased and OEF increased, WMH density increased. Elevated watershed OEF was associated with greater WMH burden and microstructural disruption, after adjusting for vascular risk factors. In contrast, WM and watershed CBF were not associated with WMH burden or microstructural disruption. Moreover, OEF progressively increased while CBF decreased, in concentric contours approaching WMH lesions. CONCLUSIONS: Chronic hypoxia-ischemia in the watershed region may contribute to cerebral small vessel disease pathogenesis and development of WMH. Watershed OEF may hold promise as an imaging biomarker to identify individuals at risk for cerebral small vessel disease progression.

Silent Infarcts, White Matter Integrity, and Oxygen Metabolic Stress in Young Adults With and Without Sickle Cell Trait.

BACKGROUND: Individuals with sickle cell anemia have heightened risk of stroke and cognitive dysfunction. Given its high prevalence globally, whether sickle cell trait (SCT) is a risk factor for neurological injury has been of interest; however, data have been limited. We hypothesized that young, healthy adults with SCT would show normal cerebrovascular structure and hemodynamic function. METHODS: As a case-control study, young adults with (N=25, cases) and without SCT (N=24, controls) underwent brain magnetic resonance imaging to quantify brain volume, microstructural integrity (fractional anisotropy), silent cerebral infarcts (SCI), intracranial stenosis, and aneurysms. Pseudocontinuous arterial spin labeling and asymmetric spin echo sequences measured cerebral blood flow and oxygen extraction fraction, respectively, from which cerebral metabolic oxygen demand was calculated. Imaging metrics were compared between SCT cases and controls. SCI volume was correlated with baseline characteristics. RESULTS: Compared with controls, adults with SCT demonstrated similar normalized brain volumes (SCT 0.80 versus control 0.81, P=0.41), white matter fractional anisotropy (SCT 0.41 versus control 0.43, P=0.37), cerebral blood flow (SCT 62.04 versus control, 61.16 mL/min/100 g, P=0.67), oxygen extraction fraction (SCT 0.27 versus control 0.27, P=0.31), and cerebral metabolic oxygen demand (SCT 2.71 versus control 2.70 mL/min/100 g, P=0.96). One per cohort had an intracranial aneurysm. None had intracranial stenosis. The SCT cases and controls showed similar prevalence and volume of SCIs; however, in the subset of participants with SCIs, the SCT cases had greater SCI volume versus controls (0.29 versus 0.07 mL, P=0.008). Of baseline characteristics, creatinine was mildly elevated in the SCT cohort (0.9 versus 0.8 mg/dL, P=0.053) and correlated with SCI volume (ρ=0.49, P=0.032). In the SCT cohort, SCI distribution was similar to that of young adults with sickle cell anemia. CONCLUSIONS: Adults with SCT showed normal cerebrovascular structure and hemodynamic function. These findings suggest that healthy individuals with SCT are unlikely to be at increased risk for early or accelerated ischemic brain injury.

Normal aging in mice is associated with a global reduction in cortical spectral power and network-specific declines in functional connectivity.

Normal aging is associated with a variety of neurologic changes including declines in cognition, memory, and motor activity. These declines correlate with neuronal changes in synaptic structure and function. Degradation of brain network activity and connectivity represents a likely mediator of age-related functional deterioration resulting from these neuronal changes. Human studies have demonstrated both general decreases in spontaneous cortical activity and disruption of cortical networks with aging. Current techniques used to study cerebral network activity are hampered either by limited spatial resolution (e.g. electroencephalography, EEG) or limited temporal resolution (e.g., functional magnetic resonance imaging, fMRI). Here we utilize mesoscale imaging of neuronal activity in Thy1-GCaMP6f mice to characterize neuronal network changes in aging with high spatial resolution across a wide frequency range. We show that while evoked activity is unchanged with aging, spontaneous neuronal activity decreases across a wide frequency range (0.01-4 Hz) involving all regions of the cortex. In contrast to this global reduction in cortical power, we found that aging is associated with functional connectivity (FC) deterioration of select networks including somatomotor, cingulate, and retrosplenial nodes. These changes are corroborated by reductions in homotopic FC and node degree within somatomotor and visual cortices. Finally, we found that whole-cortex delta power and delta band node degree correlate with exploratory activity in young but not aged animals. Together these data suggest that aging is associated with global declines in spontaneous cortical activity and focal deterioration of network connectivity, and that these reductions may be associated with age-related behavioral declines.

Cerebral oxygen metabolic stress is increased in children with sickle cell anemia compared to anemic controls.

Patients with sickle cell anemia (SCA) experience cerebral metabolic stress with an increase in oxygen extraction fraction (OEF) to compensate for reduced oxygen carrying capacity due to anemia. It remains unclear if anemia alone drives this metabolic stress. Using MRI, we collected voxel-wise OEF measurements to test our hypothesis that OEF would be elevated in anemic controls without SCA (AC) compared to healthy controls (HC), but OEF would be even higher in SCA compared to AC. Brain MRIs (N = 159) were obtained in 120 participants (34 HC, 27 AC, 59 SCA). While hemoglobin was lower in AC versus HC (p < 0.001), hemoglobin was not different between AC and SCA cohorts (p = 0.459). Whole brain OEF was higher in AC compared to HC (p < 0.001), but lower compared to SCA (p = 0.001). Whole brain OEF remained significantly higher in SCA compared to HC (p = 0.001) while there was no longer a difference between AC versus HC (p = 0.935) in a multivariate model controlling for age and hemoglobin. OEF peaked within the border zone regions of the brain in both SCA and AC cohorts, but the volume of white matter with regionally elevated OEF in AC was smaller (1.8%) than SCA (58.0%). While infarcts colocalized within regions of elevated OEF, more SCA participants had infarcts than AC (p < 0.001). We conclude that children with SCA experience elevated OEF compared to AC and HC after controlling for the impact of anemia, suggesting that there are other pathophysiologic factors besides anemia contributing to cerebral metabolic stress in children with SCA.

Single nucleotide variations in ZBTB46 are associated with post-thrombolytic parenchymal haematoma.

Haemorrhagic transformation is a complication of recombinant tissue-plasminogen activator treatment. The most severe form, parenchymal haematoma, can result in neurological deterioration, disability, and death. Our objective was to identify single nucleotide variations associated with a risk of parenchymal haematoma following thrombolytic therapy in patients with acute ischaemic stroke. A fixed-effect genome-wide meta-analysis was performed combining two-stage genome-wide association studies (n = 1904). The discovery stage (three cohorts) comprised 1324 ischaemic stroke individuals, 5.4% of whom had a parenchymal haematoma. Genetic variants yielding a P-value < 0.05 1 × 10-5 were analysed in the validation stage (six cohorts), formed by 580 ischaemic stroke patients with 12.1% haemorrhagic events. All participants received recombinant tissue-plasminogen activator; cases were parenchymal haematoma type 1 or 2 as defined by the European Cooperative Acute Stroke Study (ECASS) criteria. Genome-wide significant findings (P < 5 × 10-8) were characterized by in silico functional annotation, gene expression, and DNA regulatory elements. We analysed 7 989 272 single nucleotide polymorphisms and identified a genome-wide association locus on chromosome 20 in the discovery cohort; functional annotation indicated that the ZBTB46 gene was driving the association for chromosome 20. The top single nucleotide polymorphism was rs76484331 in the ZBTB46 gene [P = 2.49 × 10-8; odds ratio (OR): 11.21; 95% confidence interval (CI): 4.82-26.55]. In the replication cohort (n = 580), the rs76484331 polymorphism was associated with parenchymal haematoma (P = 0.01), and the overall association after meta-analysis increased (P = 1.61 × 10-8; OR: 5.84; 95% CI: 3.16-10.76). ZBTB46 codes the zinc finger and BTB domain-containing protein 46 that acts as a transcription factor. In silico studies indicated that ZBTB46 is expressed in brain tissue by neurons and endothelial cells. Moreover, rs76484331 interacts with the promoter sites located at 20q13. In conclusion, we identified single nucleotide variants in the ZBTB46 gene associated with a higher risk of parenchymal haematoma following recombinant tissue-plasminogen activator treatment.

Depressive Symptomatology and Functional Status Among Stroke Survivors: A Network Analysis.

OBJECTIVE: To (1) characterize poststroke depressive symptom network and identify the symptoms most central to depression and (2) examine the symptoms that bridge depression and functional status. DESIGN: Secondary data analysis of the Stroke Recovery in Underserved Population database. Networks were estimated using regularized partial correlation models. Topology, network stability and accuracy, node centrality and predictability, and bridge statistics were investigated. SETTING: Eleven inpatient rehabilitation facilities across 9 states of the United States. PARTICIPANTS: Patients with stroke (N=1215) who received inpatient rehabilitation. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: The Center for Epidemiologic Studies Depression Scale and FIM were administered at discharge from inpatient rehabilitation. RESULTS: Depressive symptoms were positively intercorrelated within the network, with stronger connections between symptoms within the same domain. "Sadness" (expected influence=1.94), "blues" (expected influence=1.14), and "depressed" (expected influence=0.97) were the most central depressive symptoms, whereas "talked less than normal" (bridge expected influence=-1.66) emerged as the bridge symptom between depression and functional status. Appetite (R2=0.23) and sleep disturbance (R2=0.28) were among the least predictable symptoms, whose variance was less likely explained by other symptoms in the network. CONCLUSIONS: Findings illustrate the potential of network analysis for discerning the complexity of poststroke depressive symptomology and its interplay with functional status, uncovering priority treatment targets and promoting more precise clinical practice. This study contributes to the need for expansion in the understanding of poststroke psychopathology and challenges clinicians to use targeted intervention strategies to address depression in stroke rehabilitation.

Ecological Momentary Assessment of Real-World Functional Behaviors in Individuals With Stroke: A Longitudinal Observational Study.

OBJECTIVE: To validate and characterize real-world functional behaviors in individuals after stroke. DESIGN: Longitudinal observational study using ecological momentary assessment (EMA) as a real-time assessment of functional behaviors in natural contexts. Wilcoxon rank-sum tests, Fisher exact tests, and Spearman correlations were used to analyze data. SETTING: Community. PARTICIPANTS: Individuals with mild to moderate stroke (N=212). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Individuals were assessed 5 times daily for 14 days with EMA surveys to determine what, with whom, and where individuals were doing activities and appraise mental, somatic, and cognitive symptoms. Individuals also completed standardized assessments during laboratory visits, including Lawton Instrumental Activities of Daily Living Scale, Activity Card Sort, Patient-Reported Outcome Measurement Information System, and Quality of Life in Neurological Disorders. RESULTS: Most individuals (median age, 60 years; 55% male) were ischemic stroke (90%) and had mild stroke severity (median National Institutes of Health Stroke Scale, 2). A total of 14,140 EMA surveys were analyzed. Individuals were home 78% of the time; primarily participated in passive, unproductive activities (27%), especially watching television and resting; and participated least in physical activities (4%). EMA was sensitive to indicators of poststroke disability; unemployed individuals reported fewer vocational activities but more activities of daily living (ADL) and passive activities than employed counterparts. Users of mobility devices and individuals with cognitive problems spent significantly less time on vocational activities and more on ADL than nonusers and those without cognitive problems. Our data supported the validity of EMA methods in stroke, with small to moderate correlations of EMA with in-laboratory measures of daily functioning (r=-0.30 to 0.35, P<.05) and very large correlations between EMA and in-laboratory measures of symptoms, especially those measuring same constructs (r=-0.64 to 0.79, P<.0001). CONCLUSIONS: Our findings reveal that EMA tracked poststroke functioning precisely. EMA may be beneficial in examining poststroke functional recovery, in monitoring patients for home-based interventions, and for longitudinal research.

Accelerating Prediction of Malignant Cerebral Edema After Ischemic Stroke with Automated Image Analysis and Explainable Neural Networks.

BACKGROUND: Malignant cerebral edema is a devastating complication of stroke, resulting in deterioration and death if hemicraniectomy is not performed prior to herniation. Current approaches for predicting this relatively rare complication often require advanced imaging and still suffer from suboptimal performance. We performed a pilot study to evaluate whether neural networks incorporating data extracted from routine computed tomography (CT) imaging could enhance prediction of edema in a large diverse stroke cohort. METHODS: An automated imaging pipeline retrospectively extracted volumetric data, including cerebrospinal fluid (CSF) volumes and the hemispheric CSF volume ratio, from baseline and 24 h CT scans performed in participants of an international stroke cohort study. Fully connected and long short-term memory (LSTM) neural networks were trained using serial clinical and imaging data to predict those who would require hemicraniectomy or die with midline shift. The performance of these models was tested, in comparison with regression models and the Enhanced Detection of Edema in Malignant Anterior Circulation Stroke (EDEMA) score, using cross-validation to construct precision-recall curves. RESULTS: Twenty of 598 patients developed malignant edema (12 required surgery, 8 died). The regression model provided 95% recall but only 32% precision (area under the precision-recall curve [AUPRC] 0.74), similar to the EDEMA score (precision 28%, AUPRC 0.66). The fully connected network did not perform better (precision 33%, AUPRC 0.71), but the LSTM model provided 100% recall and 87% precision (AUPRC 0.97) in the overall cohort and the subgroup with a National Institutes of Health Stroke Scale (NIHSS) score ≥ 8 (p = 0.0001 vs. regression and fully connected models). Features providing the most predictive importance were the hemispheric CSF ratio and NIHSS score measured at 24 h. CONCLUSIONS: An LSTM neural network incorporating volumetric data extracted from routine CT scans identified all cases of malignant cerebral edema by 24 h after stroke, with significantly fewer false positives than a fully connected neural network, regression model, and the validated EDEMA score. This preliminary work requires prospective validation but provides proof of principle that a deep learning framework could assist in selecting patients for surgery prior to deterioration.