Serum miR-502: A potential biomarker in the diagnosis of concussion in a pilot study of patients with normal structural brain imaging

Establishing a diagnosis of concussion within the context of competitive sport is frequently difficult due to the heterogeneity of presentation. Over the years, many endogenous proteins, including the recent Food and Drug Administration approved for mild-to-moderate traumatic brain injury, glial fibrillary acid protein and ubiquitin carboxy-terminal hydrolase, have been studied as potential biomarkers for the diagnosis of mild traumatic brain injury. Recently, a new class of potential biomarkers, the microRNAs, has shown promise as indicators of traumatic brain injury. In this pilot study, we have analysed the ability of pre-validated serum microRNAs (mi-425-5p and miR-502) to diagnose concussion, in cases without structural pathology. Their performance has been assessed alongside a set of identified protein biomarkers for traumatic brain injury in cohort of 41 concussed athletes. Athletes with a confirmed concussion underwent blood sampling after 48 h from concussion along with magnetic resonance imaging. Serum mi-425-5p and miR-502 were analysed by quantitative reverse transcription polymerase chain reaction, and digital immunoassay was used to determine serum concentrations of ubiquitin carboxy-terminal hydrolase, glial fibrillary acid protein, neurofilament light and Tau. Results were matched with 15 healthy volunteers. No structural/haemorrhagic pathology was identified. Protein biomarkers demonstrated variability among groups reflecting previous performance in the literature. Neurofilament light was the only marker to positively correlate with symptoms reported and SCAT5 scores. Despite the sub optimal timing of sampling beyond the optimal window for many of the protein biomarkers measured, miR-502 was significantly downregulated at all time points within a week form concussion ictus, showing a diagnostic sensitivity in cases beyond 48 h and without structural pathology

Quantitative MRI brain in congenital adrenal hyperplasia: in vivo assessment of the cognitive and structural impact of steroid hormones

Abstract Context Brain white matter hyper-intensities are seen on routine clinical imaging in 46% of adults with congenital adrenal hyperplasia (CAH). The extent and functional relevance of these abnormalities have not been studied using quantitative MRI analysis. Objective To examine white matter microstructure, neural volumes and CNS metabolites in CAH due to 21-hydroxylase deficiency (21OHD) and to determine whether identified abnormalities are associated with cognition, glucocorticoid and androgen exposure. Design, setting and participants A cross-sectional study at a tertiary hospital including 19 females (18-50 years) with 21OHD and 19 age-matched healthy females. Main outcome measure Recruits underwent cognitive assessment and brain imaging including; diffusion weighted imaging of white matter, T1-weighted volumetry and magnetic resonance spectroscopy for neural metabolites. We evaluated white matter microstructure using tract-based spatial statistics. We compared cognitive scores, neural volumes and metabolites between groups and relationships between glucocorticoid exposure, MRI and neurologic outcomes. Results Patients with 21OHD had widespread reductions in white matter structural integrity, reduced volumes of right hippocampus, bilateral thalami, cerebellum and brainstem, and reduced mesial temporal lobe total choline content. Working memory, processing speed, and digit span and matrix reasoning scores were reduced in patients with 21OHD, despite similar education and intelligence to controls. 21OHD individuals exposed to higher glucocorticoid doses had greater abnormalities in white matter microstructure and cognitive performance. Conclusion For the first time we demonstrate that 21OHD and current glucocorticoid replacement regimens have a profound impact on brain morphology and function. If reversible, these CNS markers represent a potential target for treatment

The hippocampus as the switchboard between perception and memory.

Adaptive memory recall requires a rapid and flexible switch from external perceptual reminders to internal mnemonic representations. However, owing to the limited temporal or spatial resolution of brain imaging modalities used in isolation, the hippocampal–cortical dynamics supporting this process remain unknown. We thus employed an object-scene cued recall paradigm across two studies, including intracranial electroencephalography (iEEG) and high-density scalp EEG. First, a sustained increase in hippocampal high gamma power (55 to 110 Hz) emerged 500 ms after cue onset and distinguished successful vs. unsuccessful recall. This increase in gamma power for successful recall was followed by a decrease in hippocampal alpha power (8 to 12 Hz). Intriguingly, the hippocampal gamma power increase marked the moment at which extrahippocampal activation patterns shifted from perceptual cue toward mnemonic target representations. In parallel, source-localized EEG alpha power revealed that the recall signal progresses from hippocampus to posterior parietal cortex and then to medial prefrontal cortex. Together, these results identify the hippocampus as the switchboard between perception and memory and elucidate the ensuing hippocampal–cortical dynamics supporting the recall process.post-print1844 K

Data-driven re-referencing of intracranial EEG based on independent component analysis (ICA)

Background: Intracranial recordings from patients implanted with depth electrodes are a valuable source of information in neuroscience. They allow for the unique opportunity to record brain activity with high spatial and temporal resolution. A common pre-processing choice in stereotactic EEG (S-EEG) is to re-reference the data with a bipolar montage. In this, each channel is subtracted from its neighbor, to reduce commonalities between channels and isolate activity that is spatially confined. New Method: We challenge the assumption that bipolar reference effectively performs this task. To extract local activity, the distribution of the signal source of interest, interfering distant signals, and noise need to be considered. Referencing schemes with fixed coefficients can decrease the signal to noise ratio (SNR) of the data, they can lead to mislocalization of activity and consequently to misinterpretation of results. We propose to use Independent Component Analysis (ICA), to derive filter coefficients that reflect the statistical dependencies of the data at hand. Results: We describe and demonstrate this on human S-EEG recordings. In a simulation with real data, we quantitatively show that ICA outperforms the bipolar referencing operation in sensitivity and importantly in specificity when revealing local time series from the superposition of neighboring channels. Comparison with Existing Method: We argue that ICA already performs the same task that bipolar referencing pursues, namely undoing the linear superposition of activity and will identify activity that is local. Conclusions: When investigating local sources in human S-EEG, ICA should be preferred over re-referencing the data with a bipolar montage

Investigation into repetitive concussion in sport (RECOS): study protocol of a prospective, exploratory, observational cohort study

Sport-related concussion management remains a diagnostic dilemma to clinicians in all strata of care, coaching staff and players alike. The lack of objective diagnostic and prognostic biomarkers and over-reliance on subjective clinical assessments carries a significant health risk of undiagnosed concussive episodes and early return to play before full recovery increasing the risk of sustaining additional concussion, and leading to long-term sequelae and/or unfavourable outcome. To identify a set of parameters (neuroimaging with neurophysiological, biological and neuropsychological tests) that may support pitch-side and outpatient clinical decision-making in order to objectively diagnose concussion, determine the severity of injury, guide a safe return to play and identify the potential predictors of the long-term sequelae of concussion. An exploratory, observational, prospective, cohort study recruiting between 2017 and 2020. The participants will have a baseline preseason screening (brain imaging, neuropsychological assessments, serum, urine and saliva sampling). If a screened player later suffers a concussion and/or multiple concussions then he/she will be assessed again with the same protocol within 72 hours, and their baseline data will be used as internal control as well as normative data. Inferential statistical analysis will be performed to determine correlations between biological, imaging techniques and neuropsychological assessments. This study was approved by the East of England-Essex Research Ethics Committee on 22 September 2017-REC 17/EE/0275; IRAS 216703. The results of this study will be presented at national and international conferences and submitted for publication in peer reviewed journals. ISRCTN16974791; Pre-results. [Abstract copyright: © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY. Published by BMJ.

Hippocampal neurons code individual episodic memories in humans

The hippocampus is an essential hub for episodic memory processing. However, how human hippocampal single neurons code multi-element associations remains unknown. In particular, it is debated whether each hippocampal neuron represents an invariant element within an episode or whether single neurons bind together all the elements of a discrete episodic memory. Here we provide evidence for the latter hypothesis. Using single-neuron recordings from a total of 30 participants, we show that individual neurons, which we term episode-specific neurons, code discrete episodic memories using either a rate code or a temporal firing code. These neurons were observed exclusively in the hippocampus. Importantly, these episode-specific neurons do not reflect the coding of a particular element in the episode (that is, concept or time). Instead, they code for the conjunction of the different elements that make up the episode

Metabolite selection for machine learning in childhood brain tumour classification

MRS can provide high accuracy in the diagnosis of childhood brain tumours when combined with machine learning. A feature selection method such as principal component analysis is commonly used to reduce the dimensionality of metabolite profiles prior to classification. However, an alternative approach of identifying the optimal set of metabolites has not been fully evaluated, possibly due to the challenges of defining this for a multi‐class problem. This study aims to investigate metabolite selection from in vivo MRS for childhood brain tumour classification. Multi‐site 1.5 T and 3 T cohorts of patients with a brain tumour and histological diagnosis of ependymoma, medulloblastoma and pilocytic astrocytoma were retrospectively evaluated. Dimensionality reduction was undertaken by selecting metabolite concentrations through multi‐class receiver operating characteristics and compared with principal component analysis. Classification accuracy was determined through leave‐one‐out and k‐fold cross‐validation. Metabolites identified as crucial in tumour classification include myo‐inositol (P < 0.05, AUC = 0 . 81 ± 0 . 01 ), total lipids and macromolecules at 0.9 ppm (P < 0.05, AUC = 0 . 78 ± 0 . 01 ) and total creatine (P < 0.05, AUC = 0 . 77 ± 0 . 01 ) for the 1.5 T cohort, and glycine (P < 0.05, AUC = 0 . 79 ± 0 . 01 ), total N‐acetylaspartate (P < 0.05, AUC = 0 . 79 ± 0 . 01 ) and total choline (P < 0.05, AUC = 0 . 75 ± 0 . 01 ) for the 3 T cohort. Compared with the principal components, the selected metabolites were able to provide significantly improved discrimination between the tumours through most classifiers (P < 0.05). The highest balanced classification accuracy determined through leave‐one‐out cross‐validation was 85% for 1.5 T 1H‐MRS through support vector machine and 75% for 3 T 1H‐MRS through linear discriminant analysis after oversampling the minority. The study suggests that a group of crucial metabolites helps to achieve better discrimination between childhood brain tumours

Prolonged Confusional state as first manifestation of COVID-19

A 77 year old gentleman, normally fit and well, was admitted with acute confusion. On admission GCS was 14/15, vital signs were within the normal limits and bilateral crepitation at the lung base. Head CT scan normal. CXR showed some air space opacification. Investigations revealed hyponatraemia, raised CRP and positive for COVID-19. Treated with antibiotics and intravenous saline, sodium returned to normal. Delirium remained unchanged four weeks post incidence. Neurological manifestations were documented in patients with COVID-19, however no report has shown delirium as a primary manifestation. This case illustrates acute confusion may be the only presenting symptom of COVID-19 without overt lung disease.</p

Case Report - MRI findings in Kallmann syndrome

Kallmann syndrome (KS) is a neuronal migration disorder characterised by hypogonadotrophic hypogonadism and anosmia or hyposmia. Five patients with clinical findings suggestive of KS were evaluated with MRI. All patients had abnormalities of olfactory system. Olfactory bulbs were absent in all patients. Olfactory sulci were absent in 3 patients and hypoplastic in 2 patients. Anterior pituitary was hypoplastic in two patients. The MRI findings in KS are characteristic and MRI is a useful adjunct to the diagnosis of KS