Characterizing the Relationship Between Arterial Carbon Dioxide Trajectory and Serial Brain Biomarkers with Central Nervous System Injury During Veno-Venous Extracorporeal Membrane Oxygenation: A Prospective Cohort Study.

BACKGROUND: Central nervous system (CNS) injury following initiation of veno-venous extracorporeal membrane oxygenation (VV-ECMO) is common. An acute decrease in partial pressure of arterial carbon dioxide (PaCO2) following VV-ECMO initiation has been suggested as an etiological factor, but the challenges of diagnosing CNS injuries has made discerning a relationship between PaCO2 and CNS injury difficult. METHODS: We conducted a prospective cohort study of adult patients undergoing VV-ECMO for acute respiratory failure. Arterial blood gas measurements were obtained prior to initiation of VV-ECMO, and at every 2-4 h for the first 24 h. Neuroimaging was conducted within the first 7-14 days in patients who were suspected of having neurological injury or unable to be examined because of sedation. We collected blood biospecimens to measure brain biomarkers [neurofilament light (NF-L); glial fibrillary acidic protein (GFAP); and phosphorylated-tau 181] in the first 7 days following initiation of VV-ECMO. We assessed the relationship between both PaCO2 over the first 24 h and brain biomarkers with CNS injury using mixed methods linear regression. Finally, we explored the effects of absolute change of PaCO2 on serum levels of neurological biomarkers by separate mixed methods linear regression for each biomarker using three PaCO2 exposures hypothesized to result in CNS injury. RESULTS: In our cohort, 12 of 59 (20%) patients had overt CNS injury identified on head computed tomography. The PaCO2 decrease with VV-ECMO initiation was steeper in patients who developed a CNS injury (- 0.32%, 95% confidence interval - 0.25 to - 0.39) compared with those without (- 0.18%, 95% confidence interval - 0.14 to - 0.21, P interaction < 0.001). The mean concentration of NF-L increased over time and was higher in those with a CNS injury (464 [739]) compared with those without (127 [257]; P = 0.001). GFAP was higher in those with a CNS injury (4278 [11,653] pg/ml) compared with those without (116 [108] pg/ml; P < 0.001). The mean NF-L, GFAP, and tau over time in patients stratified by the three thresholds of absolute change of PaCO2 showed no differences and had no significant interaction for time. CONCLUSIONS: Although rapid decreases in PaCO2 following initiation of VV-ECMO were slightly greater in patients who had CNS injuries versus those without, data overlap and absence of relationships between PaCO2 and brain biomarkers suggests other pathophysiologic variables are likely at play.

A new approach towards highly sensitive detection of endogenous N-acetylaspartic acid, N-acetylglutamic acid, and N-acetylaspartylglutamic acid in brain tissues based on strong anion exchange monolith microextraction coupled with UHPLC-MS/MS.

A novel in-tube solid-phase microextraction coupled with an ultra-high performance liquid chromatography-mass spectrometry method has been established for simultaneous quantification of three crucial brain biomarkers N-acetylaspartic acid (NAA), N-acetylglutamic acid (NAG), and N-acetylaspartylglutamic acid (NAAG). A polymer monolith with quaternary ammonium as the functional group was designed and exhibited efficient enrichment of target analytes through strong anion exchange interaction. Under the optimized conditions, the proposed method displayed wide linear ranges (0.1-80 nM for NAA and NAG, 0.2-160 nM for NAAG) with good precision (RSDs were lower than 15%) and low limits of detection (0.019-0.052 nM), which is by far the most sensitive approach for NAA, NAG, and NAAG determination. Furthermore, this approach has been applied to measure the target analytes in mouse brain samples, and endogenous NAA, NAG, and NAAG were successfully detected and quantified from only around 5 mg of cerebral cortex, cerebellum, and hippocampus. Compared with existing methods, the newly developed method in the current study provides highest sensitivity and lowest sample consumption for NAA, NAG, and NAAG measurements, which would potentially be utilized in determining and tracking these meaningful brain biomarkers in diseases or treatment processes, benefiting the investigations of pathophysiology and treatment of brain disorders.

Neurofilament light chain: A potential biomarker for cerebrovascular disease in children with sickle cell anaemia.

Cerebrovascular injury frequently occurs in children with sickle cell anaemia (SCA). Limited access to magnetic resonance imaging and angiography (MRI-MRA) in sub-Saharan Africa impedes detection of clinically unapparent cerebrovascular injury. Blood-based brain biomarkers of cerebral infarcts have been identified in non-SCA adults. Using plasma samples from a well-characterized cross-sectional sample of Ugandan children with SCA, we explored relationships between biomarker levels and MRI-detected cerebral infarcts and transcranial Doppler (TCD) arterial velocity. Testing was performed using a 4-plex panel of brain injury biomarkers, including neurofilament light chain (NfL), a central nervous system neuron-specific protein. Mean biomarker levels from the SCA group (n = 81) were similar to those from non-SCA sibling controls (n = 54). Within the SCA group, NfL levels were significantly higher in those with MRI-detected infarcts compared to no infarcts, and higher with elevated TCD velocity versus normal velocity. Elevated NfL remained strongly associated with MRI-detected infarcts after adjusting for sex and age. All non-SCA controls and SCA participants lacking MRI-detected infarcts had low NfL levels. These data suggest potential utility of plasma-based NfL levels to identify children with SCA cerebrovascular injury. Replication and prospective studies are needed to confirm these novel findings and the clinical utility of NfL versus MRI imaging.

Brain biomarkers and cognition across adulthood.

Understanding the associations between brain biomarkers (BMs) and cognition across age is of paramount importance. Five hundred and sixty-two participants (19-80 years old, 16 mean years of education) were studied. Data from structural T1, diffusion tensor imaging, fluid-attenuated inversion recovery, and resting-state functional magnetic resonance imaging scans combined with a neuropsychological evaluation were used. More specifically, the measures of cortical, entorhinal, and parahippocampal thickness, hippocampal and striatal volume, default-mode network and fronto-parietal control network, fractional anisotropy (FA), and white matter hyperintensity (WMH) were assessed. z-Scores for three cognitive domains measuring episodic memory, executive function, and speed of processing were computed. Multiple linear regressions and interaction effects between each of the BMs and age on cognition were examined. Adjustments were made for age, sex, education, intracranial volume, and then, further, for general cognition and motion. BMs were significantly associated with cognition. Across the adult lifespan, slow speed was associated with low striatal volume, low FA, and high WMH burden. Poor executive function was associated with low FA, while poor memory was associated with high WMH burden. After adjustments, results were significant for the associations: speed-FA and WMH, memory-entorhinal thickness. There was also a significant interaction between hippocampal volume and age in memory. In age-stratified analyses, the most significant associations for the young group occurred between FA and executive function, WMH, and memory, while for the old group, between entorhinal thickness and speed, and WMH and speed, executive function. Unique sets of BMs can explain variation in specific cognitive domains across adulthood. Such results provide essential information about the neurobiology of aging.

Elevated serum S-100ß in patients with septic shock is associated with delirium.

BACKGROUND: A high prevalence of delirium is observed in sepsis, yet specific markers for this brain dysfunction in sedated patients are still lacking. Cytoplasmic low molecular weight calcium-binding protein, S-100ß, is a commonly used nonspecific marker for brain injury. Here, we evaluated whether delirium is associated with increases in S-100ß levels. METHODS: This observational study included 22 patients with septic shock. Delirium was assessed by CAM-ICU and blood samples were obtained to measure inflammatory (CRP, PCT, IL-6, IL-17, TNF-α) and cerebral biomarkers (S-100ß, NSE, HAB42, SUBP). Patients were categorized according to the presence of delirium. RESULTS: Delirium was present in 10/22 of the patients (45.5%). Serum S-100ß levels were above the laboratory cutoff value of 0.15 µg/L in 13/22 (59.1%) of the patients. The odds ratio for risk of developing delirium in cases with an S-100ß >0.15 µg/L was 18.0 (95%CI, 1.7-196.3, P = 0.011). Patients with delirium had higher plasma levels of IL-6 compared to those without; 138.3 pg/mL [28.0-296.7] vs 53.6 pg/mL [109.3-505, P = 0.050]. There was a positive correlation between S100 ß and IL-6 levels (r = 0.489, P = 0.021). Delirium patients had higher SOFA scores; 10 [5-9] vs 7[8-10.5], P = 0.036. CONCLUSIONS: Delirium in septic shock was associated with an elevated protein S-100ß when using a laboratory cutoff value of 0.15 µg/L and with more severe organ dysfunction during the ICU stay.

Revealing the Structural Neural Circuitry of Attention Deficit Hyperactivity Disorder With Diffusion MRI: Implications for Future Diagnosis and Treatment.

OBJECTIVE: Rates of attention deficit hyperactivity disorder (ADHD) diagnosis and psychostimulant prescriptions continue to rise, yet there are no clear diagnostic tests or biomarkers for the disorder. The purpose of this article is to highlight the role of diffusion MRI in bolstering a neurobiologic conceptualization of ADHD and how this holds promise for optimizing future diagnosis. CONCLUSION: Diffusion MRI is a powerful neuroimaging tool for noninvasive assessment of the structural neural circuitry underlying brain function and behavior. Though the modality is still in its infancy, diffusion MRI studies are showing neural network disruption in ADHD consistent with findings from other imaging modalities. Given the mounting evidence of brain-behavior correlates in ADHD, it is likely that imaging-based biomarkers will one day be incorporated into clinical diagnosis and treatment evaluation. Until then, diffusion MRI findings serve to validate ADHD as a brain-based disorder with immediate public health implications for individuals with ADHD.

Classification of Mild Cognitive Impairment Using Functional Near-Infrared Spectroscopy-Derived Biomarkers With Convolutional Neural Networks.

OBJECTIVE: To date, early detection of mild cognitive impairment (MCI) has mainly depended on paper-based neuropsychological assessments. Recently, biomarkers for MCI detection have gained a lot of attention because of the low sensitivity of neuropsychological assessments. This study proposed the functional near-infrared spectroscopy (fNIRS)-derived data with convolutional neural networks (CNNs) to identify MCI. METHODS: Eighty-two subjects with MCI and 148 healthy controls (HC) performed the 2-back task, and their oxygenated hemoglobin (HbO2) changes in the prefrontal cortex (PFC) were recorded during the task. The CNN model based on fNIRS-derived spatial features with HbO2 slope within time windows was trained to classify MCI. Thereafter, the 5-fold cross-validation approach was used to evaluate the performance of the CNN model. RESULTS: Significant differences in averaged HbO2 values between MCI and HC groups were found, and the CNN model could better discriminate MCI with over 89.57% accuracy than the Korean version of the Montreal Cognitive Assessment (MoCA) (89.57%). Specifically, the CNN model based on HbO2 slope within the time window of 20-60 seconds from the left PFC (96.09%) achieved the highest accuracy. CONCLUSION: These findings suggest that the fNIRS-derived spatial features with CNNs could be a promising way for early detection of MCI as a surrogate for a conventional screening tool and demonstrate the superiority of the fNIRS-derived spatial features with CNNs to the MoCA.

Applications of near-infrared spectroscopy in epilepsy, with a focus on mitochondrial disorders.

Mitochondrial diseases are inherited disorders that impede the mitochondria's ability to produce sufficient energy for the cells. They can affect different parts of the body, notably the brain. Neurological symptoms and epilepsy are prevalent in patients with mitochondrial disorders. The epileptogenicity of mitochondrial disorder is a complex process involving the intricate interplay between abnormal energy metabolism and neuronal activity. Several modalities have been used to detect seizures in different disorders including mitochondrial disorders. EEG serve as the gold standard for diagnosis and localization, commonly complemented by additional imaging modalities to enhance source localization. In the current work, we propose the use of functional near-infrared spectroscopy (fNIRS) to identify the occurrence of epilepsy and seizure in patients with mitochondrial disorders. fNIRS proves an advantageous imaging technique due to its portability and insensitivity to motion especially for imaging infants and children. It has added a valuable factor to our understanding of energy metabolism and neuronal activity. Its real-time monitoring with high spatial resolution supplements traditional diagnostic tools such as EEG and provides a comprehensive understanding of seizure and epileptogenesis. The utility of fNIRS extends to its ability to detect changes in Cytochrome c oxidase (CcO) which is a crucial enzyme in cellular respiration. This facet enhances our insight into the metabolic dimension of epilepsy related to mitochondrial dysfunction. By providing valuable insights into both energy metabolism and neuronal activity, fNIRS emerges as a promising imaging technique for unveiling the complexities of mitochondrial disorders and their neurological manifestations.

A Pilot Study Investigating the Use of Serum Glial Fibrillary Acidic Protein to Monitor Changes in Brain White Matter Integrity After Repetitive Head Hits During a Single Collegiate Football Game.

Repetitive head hits (RHHs) in sports and military settings are increasingly recognized as a risk factor for adverse neurological outcomes, but they are not currently tracked. Blood-based biomarkers of concussion have recently been shown to increase after nonconcussive RHHs during a single sporting contest, raising the possibility that they could be used in real time to monitor the brain's early response to repeated asymptomatic head hits. To test this hypothesis, we measured GFAP in serum immediately before (T0), immediately after (T1) and 45 min (T2) after a single collegiate football game in 30 athletes. Glial fibrillary acidic protein (GFAP) changes were correlated with three measures of head impact exposure (number of hits, total linear acceleration, and total rotational acceleration captured by helmet impact sensors) and to changes in brain white matter (WM) integrity, estimated by regional changes in fractional anisotropy (FA) and mean diffusivity (MD) on diffusion tensor imaging from 24 h before (T1) to 48 h after (T3) the game. To account for the potentially confounding effects of physical exertion on GFAP, correlations were adjusted for kilocalories of energy expended during the game measured by wearable body sensors. All 30 participants were male with a mean age of 19.5 ± 1.2 years. No participant had a concussion during the index game. We observed a significant increase in GFAP from T0 to T1 (mean 79.69 vs. 91.95 pg/mL, p = 0.008) and from T0 to T2 (mean 79.69 vs. 99.21 pg/mL, p < 0.001). WM integrity decreased in multiple WM regions but was statistically significant in the right fornix (mean % FA change -1.43, 95% confidence interval [CI]: -2.20, -0.66). T0 to T2 increases in GFAP correlated with reduced FA in the left fornix, right fornix, and right medical meniscus and with increased MD in the right fornix (r-values ranged from 0.59 to 0.61). Adjustment for exertion had minimal effect on these correlations. GFAP changes did not correlate to head hit exposure, but after adjustment for exertion, T0 to T2 increases correlated with all three hit metrics (r-values ranged from 0.69 to 0.74). Thus, acute elevations in GFAP after a single collegiate football game of RHHs correlated with in-game head hit exposure and with reduced WM integrity 2 days later. These results suggest that GFAP may be a biologically relevant indicator of the brain's early response to RHHs during a single sporting event. Developing tools to measure the neurological response to RHHs on an individual level has the potential to provide insight into the heterogeneity in adverse outcomes after RHH exposure and for developing effective and personalized countermeasures. Owing to the small sample size, these findings should be considered preliminary; validation in a larger, independent cohort is necessary.

Comparing Brain and Blood Lipidome Changes following Single and Repetitive Mild Traumatic Brain Injury in Rats.

Traumatic brain injury (TBI) is a major health concern in the United States and globally, contributing to disability and long-term neurological problems. Lipid dysregulation after TBI is underexplored, and a better understanding of lipid turnover and degradation could point to novel biomarker candidates and therapeutic targets. Here, we investigated overlapping lipidome changes in the brain and blood using a data-driven discovery approach to understand lipid alterations in the brain and serum compartments acutely following mild TBI (mTBI) and the potential efflux of brain lipids to peripheral blood. The cortices and sera from male and female Sprague-Dawley rats were analyzed via ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS) in both positive and negative ion modes following single and repetitive closed head impacts. The overlapping lipids in the data sets were identified with an in-house data dictionary for investigating lipid class changes. MS-based lipid profiling revealed overall increased changes in the serum compartment, while the brain lipids primarily showed decreased changes. Interestingly, there were prominent alterations in the sphingolipid class in the brain and blood compartments after single and repetitive injury, which may suggest efflux of brain sphingolipids into the blood after TBI. Genetic algorithms were used for predictive panel selection to classify injured and control samples with high sensitivity and specificity. These overlapping lipid panels primarily mapped to the glycerophospholipid metabolism pathway with Benjamini-Hochberg adjusted q-values less than 0.05. Collectively, these results detail overlapping lipidome changes following mTBI in the brain and blood compartments, increasing our understanding of TBI-related lipid dysregulation while identifying novel biomarker candidates.

Cardiovascular Disease and Alzheimer's Disease: The Heart-Brain Axis.

Cardiovascular disease (CVD) remains one of the leading causes of morbidity and mortality in aging adults across the United States. Prior studies indicate that the presence of atherosclerosis, the pathogenic basis of CVD, is linked with dementias. Alzheimer's disease (AD) and AD-related dementias are a major public health challenge in the United States. Recent studies indicate that ≈3.7 million Americans ≥65 years of age had clinical AD in 2017, with projected increases to 9.3 million by 2060. Treatment options for AD remain limited. Development of disease-modifying therapies are challenging due, in part, to the long preclinical window of AD. The preclinical incubation period of AD starts in midlife, providing a critical window for identification and optimization of AD risk factors. Studies link AD with CVD risk factors such as hypertension, inflammation, and dyslipidemia. Both AD and CVD are progressive diseases with decades-long development periods. CVD can clinically manifest several years earlier than AD, making CVD and its risk factors a potential predictor of future AD. The current review focuses on the state of literature on molecular and metabolic pathways modulating the heart-brain axis underlying the potential association of midlife CVD risk factors and their effect on AD and related dementias. Further, we explore potential CVD/dementia preventive strategies during the window of opportunity in midlife and the future of research in the field in the multiomics and novel biomarker use era.

Effects of Physical Exertion on Early Changes in Blood-Based Brain Biomarkers: Implications for the Acute Point of Care Diagnosis of Concussion.

Blood-based brain biomarkers (BBM) such as glial fibrillary acidic protein (GFAP) and ubiquitin carboxy-terminal hydrolase L1 (UCH-L1) have potential to aid in the diagnosis of concussion. Recently developed point-of-care test devices would enable BBMs to be measured in field settings such military and sport environments within minutes of a suspicious head hit. However, head hits in these environments typically occur in the setting of vigorous physical exertion, which can itself increase BBMs levels. Thus, efforts to develop BBMs as acute concussion aids in field settings need to account for the effects of physical exertion. To determine the acute effects of physical exertion on the BBMs, we measured GFAP, UCH-L1, tau, and neurofilament light chain (NF-L) immediately before, immediately after, and 45 min after a single workout session consisting of aerobic and resistance exercises in 30 collegiate football players. Subjects wore body sensors measuring several aspects of exertion and underwent diffusion tensor imaging 24 h before and 48 h after exertion. All subjects were male with a mean age of 19.5 ± 1.2 years. The mean duration of activity during the workout session was 94 ± 31 min. There was a significant decrease in serum GFAP immediately after (median decrease of 27.76%, p < 0.0001) and a significant increase in serum UCH-L1 45 min after (median increase of 37.11%, p = 0.016) exertion, compared with pre-exertion baseline. No significant changes in tau or NF-L were identified. The duration of exertion had a significant independent linear correlation to the increase in serum UCHL1 from pre-exertion to 45 min after exertion (r = 0.68, p = 0.004). There were no significant pre- to post-exertional changes in any of the 39 examined brain white matter regions, and biomarker changes did not correlate to variation in white matter integrity in any of these regions. Thus, exertion appeared to be associated with immediate decreases in serum GFAP and very acute (45 min) increases in UCH-L1. These changes were related to the duration of exertion, but not to changes in brain white matter integrity. Our results have important implications for how these BBMs might be used to aid in the on-scene diagnosis of concussion occurring in the setting of physical exertion.

Quantifying the reproducibility of graph neural networks using multigraph data representation.

Graph neural networks (GNNs) have witnessed an unprecedented proliferation in tackling several problems in computer vision, computer-aided diagnosis and related fields. While prior studies have focused on boosting the model accuracy, quantifying the reproducibility of the most discriminative features identified by GNNs is still an intact problem that yields concerns about their reliability in clinical applications in particular. Specifically, the reproducibility of biological markers across clinical datasets and distribution shifts across classes (e.g., healthy and disordered brains) is of paramount importance in revealing the underpinning mechanisms of diseases as well as propelling the development of personalized treatment. Motivated by these issues, we propose, for the first time, reproducibility-based GNN selection (RG-Select), a framework for GNN reproducibility assessment via the quantification of the most discriminative features (i.e., biomarkers) shared between different models. To ascertain the soundness of our framework, the reproducibility assessment embraces variations of different factors such as training strategies and data perturbations. Despite these challenges, our framework successfully yielded replicable conclusions across different training strategies and various clinical datasets. Our findings could thus pave the way for the development of biomarker trustworthiness and reliability assessment methods for computer-aided diagnosis and prognosis tasks. RG-Select code is available on GitHub at https://github.com/basiralab/RG-Select.

Elevated brain-derived cell-free DNA among patients with first psychotic episode - a proof-of-concept study.

Schizophrenia is a common, severe, and debilitating psychiatric disorder. Despite extensive research there is as yet no biological marker that can aid in its diagnosis and course prediction. This precludes early detection and intervention. Imaging studies suggest brain volume loss around the onset and over the first few years of schizophrenia, and apoptosis has been proposed as the underlying mechanism. Cell-free DNA (cfDNA) fragments are released into the bloodstream following cell death. Tissue-specific methylation patterns allow the identification of the tissue origins of cfDNA. We developed a cocktail of brain-specific DNA methylation markers, and used it to assess the presence of brain-derived cfDNA in the plasma of patients with a first psychotic episode. We detected significantly elevated neuron- (p=0.0013), astrocyte- (p=0.0016), oligodendrocyte- (p=0.0129), and whole brain-derived (p=0.0012) cfDNA in the plasma of patients during their first psychotic episode (n=29), compared with healthy controls (n=31). Increased cfDNA levels were not correlated with psychotropic medications use. Area under the curve (AUC) was 0.77, with 65% sensitivity at 90% specificity in patients with a psychotic episode. Potential interpretations of these findings include increased brain cell death, disruption of the blood-brain barrier, or a defect in clearance of material from dying brain cells. Brain-specific cfDNA methylation markers can potentially assist early detection and monitoring of schizophrenia and thus allow early intervention and adequate therapy.

Review of Applications of Near-Infrared Spectroscopy in Two Rare Disorders with Executive and Neurological Dysfunction: UCD and PKU.

Studying rare diseases, particularly those with neurological dysfunction, is a challenge to researchers and healthcare professionals due to their complexity and small population with geographical dispersion. Universal and standardized biomarkers generated by tools such as functional neuroimaging have been forged to collect baseline data as well as treatment effects. However, the cost and heavily infrastructural requirement of those technologies have substantially limited their availability. Thus, developing non-invasive, portable, and inexpensive modalities has become a major focus for both researchers and clinicians. When considering neurological disorders and diseases with executive dysfunction, EEG is the most convenient tool to obtain biomarkers which can correlate the objective severity and clinical observation of these conditions. However, studies have also shown that EEG biomarkers and clinical observations alone are not sensitive enough since not all the patients present classical phenotypical features or EEG evidence of dysfunction. This article reviews disorders, including two rare disorders with neurological dysfunction and the usefulness of functional near-infrared spectroscopy (fNIRS) as a non-invasive optical modality to obtain hemodynamic biomarkers of diseases and for screening and monitoring the disease.

Titrating the Translational Relevance of a Low-Level Repetitive Head Impact Model.

Recently, there has been increased attention in the scientific community to the phenomenon of sub-concussive impacts, those hits to the head that do not cause the signs and symptoms of a concussion. Some authors suggest that sub-concussive impacts may alter behavior and cognition, if sustained repetitively, but the mechanisms underlying these changes are not well-defined. Here, we adapt our well-established weight drop model of repetitive mild traumatic brain injury (rmTBI) to attempt to produce a model of low-level repetitive head impacts (RHI). The model was modified to eliminate differences in latency to right following impact and gross behavioral changes after a single cluster of hits. Further, we varied our model in terms of repetition of impact over a 4-h span to mimic the repeated sub-concussive impacts that may be experienced by an athlete within a single day of play. To understand the effects of a single cluster of RHIs, as well as the effect of an increased impact frequency within the cluster, we evaluated classical behavioral measures, serum biomarkers, cortical protein quantification, and immunohistochemistry both acutely and sub-acutely following the impacts. In the absence of gross behavioral changes, the impact protocol did generate pathology, in a dose-dependent fashion, in the brain. Evaluation of serum biomarkers revealed limited changes in GFAP and NF-L, which suggests that their diagnostic utility may not emerge until the exposure to low-level head impacts reaches a certain threshold. Robust decreases in both IL-1ß and IL-6 were observed in the serum and the cortex, indicating downregulation of inflammatory pathways. These experiments yield initial data on pathology and biomarkers in a mouse model of low-level RHIs, with relevance to sports settings, providing a starting point for further exploration of the potential role of anti-inflammatory processes in low-level RHI outcomes, and how these markers may evolve with repeated exposure.

The Contribution of Bilingualism to Cognitive Functioning and Regional Brain Volume in Normal and Abnormal Aging.

We examined the association between bilingualism, executive function (EF), and brain volume in older monolinguals and bilinguals who spoke English, Spanish, or both, and were cognitively normal (CN) or diagnosed with Mild Cognitive Impairment (MCI) or dementia. Gray matter volume (GMV) was higher in language and EF brain regions among bilinguals, but no differences were found in memory regions. Neuropsychological performance did not vary across language groups over time; however, bilinguals exhibited reduced Stroop interference and lower scores on Digit Span Backwards and category fluency. Higher scores on Digit Span Backwards were associated with a younger age of English acquisition, and a greater degree of balanced bilingualism was associated with lower scores in category fluency. The initial age of cognitive decline did not differ between language groups. The influence of bilingualism appears to be reflected in increased GMV in language and EF regions, and to a lesser degree, in EF.

The Association Between Functional Assessment and Structural Brain Biomarkers in an Ethnically Diverse Sample With Normal Cognition, Mild Cognitive Impairment, or Dementia.

OBJECTIVE: To investigate the association between the functional activities questionnaire (FAQ) and brain biomarkers (bilateral hippocampal volume [HV], bilateral entorhinal volume [ERV], and entorhinal cortical thickness [ERT]) in cognitively normal (CN) individuals, mild cognitive impairment (MCI), or dementia. METHOD: In total, 226 participants (137 females; mean age = 71.76, SD = 7.93; Hispanic Americans = 137; European Americans = 89) were assessed with a comprehensive clinical examination, a neuropsychological battery, a structural magnetic resonance imaging, and were classified as CN or diagnosed with MCI or dementia. Linear regression analyses examined the association between functional activities as measured by the FAQ on brain biomarkers, including HV, ERV, and ERT, controlling for age, education, global cognition, gender, and ethnicity. RESULTS: The FAQ significantly predicted HV, ERV, and ERT for the entire sample. However, this association was not significant for ERV and ERT when excluding the dementia group. The FAQ score remained a significant predictor of HV for the non-dementia group. Age, education, gender, ethnicity, Montreal Cognitive Assessment score, and FAQ were also significant predictors of HV for the overall sample, suggesting that younger Hispanic females with fewer years of education, higher global mental status, and better functioning, were more likely to have larger HV. CONCLUSION: FAQ scores were related to HV in older adults across clinical groups (CN, MCI, and dementia), but its association with the entorhinal cortex was driven by individuals with dementia. Demographic variables, including ethnicity, additionally influenced these associations.

S100B and its relation to cerebral oxygenation in neonates and infants undergoing surgery for congenital heart disease.

OBJECTIVES: Neonates and infants undergoing surgery for congenital heart disease are at risk for developmental impairment. Hypoxic-ischemic brain injury might be one contributing factor. We aimed to investigate the perioperative release of the astrocyte protein S100B and its relation to cerebral oxygenation. METHODS: Serum S100B was measured before and 0, 12, 24, and 48 hours after surgery. Cerebral oxygen saturation was derived by near-infrared spectroscopy. S100B reference values based on preoperative samples; concentrations above the 75th percentile were defined as elevated. Patients with elevated S100B at 24 or 48 hours were compared to cases with S100B in the normal range. Neonates (≤28 days) and infants (>28 and ≤365 days) were analyzed separately due to age-dependent release of S100B. RESULTS: Seventy-four patients underwent 94 surgical procedures (neonates, n = 38; infants, n = 56). S100B concentrations were higher in neonates before and after surgery at all time points (P ≤ .015). Highest values were noticed immediately after surgery. Postoperative S100B was elevated after 15 (40.5%) surgeries in neonates. There was no difference in pre-, intra-, or postoperative cerebral oxygenation. In infants, postoperative S100B was elevated after 23 (41.8%) procedures. Preoperative cerebral oxygen saturations tended to be lower (53 ± 12% vs 59 ± 12%, P = .069) and arterial-cerebral oxygen saturation difference was higher (35 ± 11% vs 28 ± 11%, P = .018) in infants with elevated postoperative S100B. In the early postoperative course, cerebral oxygen saturation was lower (54 ± 13% vs 63 ± 12%, P = .011) and arterial-cerebral oxygen saturation difference was wider (38 ± 11% vs 30 ± 10%, P = .008). Cerebral oxygen saturation was also lower for the entire postoperative course (62 ± 18% vs 67 ± 9%, P = .047). CONCLUSIONS: Postoperative S100B was elevated in about 40% of neonates and infants undergoing cardiac surgery. Infants with elevated postoperative S100B had impaired perioperative cerebral tissue oxygenation. No relation between S100B and cerebral oxygenation could be demonstrated in neonates.

Cardiac Surgery and the Blood-Brain Barrier.

Neurologic abnormality after cardiac surgery is common, and neurologic complications after cardiac surgery are among the most devastating problems that can occur in the postoperative period. Disruption of the blood-brain barrier (BBB) plays an important role in these complications. Assessment of the BBB integrity relies on cognitive testing, MRI, and measurement of brain biomarkers. In applying these methods, up to 50% of cardiac patients show some degree of BBB disruption and most of these abnormalities are short lived. To date there is no single test or measure that can predict BBB disruption in cardiac surgery.