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Background Knowledge of the window of SARS-CoV-2 infectiousness is crucial in developing policies to curb transmission. Mathematical modelling based on scarce empirical evidence and key assumptions has driven isolation and testing policy, but real-world data are needed. We aimed to characterise infectiousness across the full course of infection in a real-world community setting. Methods The Assessment of Transmission and Contagiousness of COVID-19 in Contacts (ATACCC) study was a UK prospective, longitudinal, community cohort of contacts of newly diagnosed, PCR-confirmed SARS-CoV-2 index cases. Household and non-household exposed contacts aged 5 years or older were eligible for recruitment if they could provide informed consent and agree to self-swabbing of the upper respiratory tract. The primary objective was to define the window of SARS-CoV-2 infectiousness and its temporal correlation with symptom onset. We quantified viral RNA load by RT-PCR and infectious viral shedding by enumerating cultivable virus daily across the course of infection. Participants completed a daily diary to track the emergence of symptoms. Outcomes were assessed with empirical data and a phenomenological Bayesian hierarchical model. Findings Between Sept 13, 2020, and March 31, 2021, we enrolled 393 contacts from 327 households (the SARS-CoV-2 pre-alpha and alpha variant waves); and between May 24, 2021, and Oct 28, 2021, we enrolled 345 contacts from 215 households (the delta variant wave). 173 of these 738 contacts were PCR positive for more than one timepoint, 57 of which were at the start of infection and comprised the final study population. The onset and end of infectious viral shedding were captured in 42 cases and the median duration of infectiousness was 5 (IQR 3–7) days. Although 24 (63%) of 38 cases had PCR-detectable virus before symptom onset, only seven (20%) of 35 shed infectious virus presymptomatically. Symptom onset was a median of 3 days before both peak viral RNA and peak infectious viral load (viral RNA IQR 3–5 days, n=38; plaque-forming units IQR 3–6 days, n=35). Notably, 22 (65%) of 34 cases and eight (24%) of 34 cases continued to shed infectious virus 5 days and 7 days post-symptom onset, respectively (survival probabilities 67% and 35%). Correlation of lateral flow device (LFD) results with infectious viral shedding was poor during the viral growth phase (sensitivity 67% [95% CI 59–75]), but high during the decline phase (92% [86–96]). Infectious virus kinetic modelling suggested that the initial rate of viral replication determines the course of infection and infectiousness. Interpretation Less than a quarter of COVID-19 cases shed infectious virus before symptom onset; under a crude 5-day self-isolation period from symptom onset, two-thirds of cases released into the community would still be infectious, but with reduced infectious viral shedding. Our findings support a role for LFDs to safely accelerate deisolation but not for early diagnosis, unless used daily. These high-resolution, community-based data provide evidence to inform infection control guidance. Funding National Institute for Health and Care Research.

Machine learning models deployed on medical imaging tasks must be equipped with out-of-distribution detection capabilities in order to avoid erroneous predictions. It is unsure whether out-of-distribution detection models reliant on deep neural networks are suitable for detecting domain shifts in medical imaging. Gaussian Processes can reliably separate in-distribution data points from out-of-distribution data points via their mathematical construction. Hence, we propose a parameter efficient Bayesian layer for hierarchical convolutional Gaussian Processes that incorporates Gaussian Processes operating in Wasserstein-2 space to reliably propagate uncertainty. This directly replaces convolving Gaussian Processes with a distance-preserving affine operator on distributions. Our experiments on brain tissue-segmentation show that the resulting architecture approaches the performance of well-established deterministic segmentation algorithms (U-Net), which has not been achieved with previous hierarchical Gaussian Processes. Moreover, by applying the same segmentation model to out-of-distribution data (i.e., images with pathology such as brain tumors), we show that our uncertainty estimates result in out-of-distribution detection that outperforms the capabilities of previous Bayesian networks and reconstruction-based approaches that learn normative distributions. To facilitate future work our code is publicly available., Comment: Published in Journal of Machine Learning for Biomedical Imaging: Special Issue: Information Processing in Medical Imaging (IPMI) 2021

Long-term outcomes are difficult to predict after paediatric traumatic brain injury. The presence or absence of focal brain injuries often do not explain cognitive, emotional and behavioural disabilities that are common and disabling. In adults, traumatic brain injury produces progressive brain atrophy that can be accurately measured and is associated with cognitive decline. However, the effect of paediatric traumatic brain injury on brain volumes is more challenging to measure because of its interaction with normal brain development. Here we report a robust approach to the individualized estimation of brain volume following paediatric traumatic brain injury and investigate its relationship to clinical outcomes. We first used a large healthy control dataset (n > 1200, age 8–22) to describe the healthy development of white and grey matter regions through adolescence. Individual estimates of grey and white matter regional volume were then generated for a group of moderate/severe traumatic brain injury patients injured in childhood (n = 39, mean age 13.53 ± 1.76, median time since injury = 14 months, range 4–168 months) by comparing brain volumes in patients to age-matched controls. Patients were individually classified as having low or normal brain volume. Neuropsychological and neuropsychiatric outcomes were assessed using standardized testing and parent/carer assessments. Relative to head size, grey matter regions decreased in volume during normal adolescence development whereas white matter tracts increased in volume. Traumatic brain injury disrupted healthy brain development, producing reductions in both grey and white matter brain volumes after correcting for age. Of the 39 patients investigated, 11 (28%) had at least one white matter tract with reduced volume and seven (18%) at least one area of grey matter with reduced volume. Those classified as having low brain volume had slower processing speed compared to healthy controls, emotional impairments, higher levels of apathy, increased anger and learning difficulties. In contrast, the presence of focal brain injury and microbleeds were not associated with an increased risk of these clinical impairments. In summary, we show how brain volume abnormalities after paediatric traumatic brain injury can be robustly calculated from individual T1 MRI using a large normative dataset that allows the effects of healthy brain development to be controlled for. Using this approach, we show that volumetric abnormalities are common after moderate/severe traumatic brain injury in both grey and white matter regions, and are associated with higher levels of cognitive, emotional and behavioural abnormalities that are common after paediatric traumatic brain injury.

Objectives This study aims to understand the acceptability of social robots and the adaptation of the Hybrid-Face Robot for dementia care in India. Methods We conducted a focus group discussion and in-depth interviews with persons with dementia (PwD), their caregivers, professionals in the field of dementia , and technical experts in robotics to collect qualitative data. Results This study explored the following themes: Acceptability of Robots in Dementia Care in India, Adaptation of Hybrid-Face Robot and Future of Robots in Dementia Care. Caregivers and PwD were open to the idea of social robot use in dementia care; caregivers perceived it to help with the challenges of caregiving and positively viewed a future with robots. Discussion This study is the first of its kind to explore the use of social robots in dementia care in India by highlighting user needs and requirements that determine acceptability and guiding adaptation.

Glial fibrillary acidic protein (GFAP) is a discriminative blood biomarker for many neurological diseases, such as traumatic brain injury. Detection of GFAP in buffer solutions using biosensors has been demonstrated, but accurate quantification of GFAP in patient samples has not been reported, yet in urgent need. Herein, we demonstrate a robust on-chip graphene field-effect transistor (GFET) biosensing method for sensitive and ultrafast detection of GFAP in patient plasma. Patients with moderate–severe traumatic brain injuries, defined by the Mayo classification, are recruited to provide plasma samples. The binding of target GFAP with the specific antibodies that are conjugated on a monolayer GFET device triggers the shift of its Dirac point, and this signal change is correlated with the GFAP concentration in the patient plasma. The limit of detection (LOD) values of 20 fg/mL (400 aM) in buffer solution and 231 fg/mL (4 fM) in patient plasma have been achieved using this approach. In parallel, for the first time, we compare our results to the state-of-the-art single-molecule array (Simoa) technology and the classic enzyme-linked immunosorbent assay (ELISA) for reference. The GFET biosensor shows competitive LOD to Simoa (1.18 pg/mL) and faster sample-to-result time (

Reduced glomerular filtration rate (GFR) can progress to kidney failure. Risk factors include genetics and diabetes mellitus (DM), but little is known about their interaction. We conducted genome-wide association meta-analyses for estimated GFR based on serum creatinine (eGFR), separately for individuals with or without DM (nDM = 178,691, nnoDM = 1,296,113). Our genome-wide searches identified (i) seven eGFR loci with significant DM/noDM-difference, (ii) four additional novel loci with suggestive difference and (iii) 28 further novel loci (including CUBN) by allowing for potential difference. GWAS on eGFR among DM individuals identified 2 known and 27 potentially responsible loci for diabetic kidney disease. Gene prioritization highlighted 18 genes that may inform reno-protective drug development. We highlight the existence of DM-only and noDM-only effects, which can inform about the target group, if respective genes are advanced as drug targets. Largely shared effects suggest that most drug interventions to alter eGFR should be effective in DM and noDM. Published version The Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) supported the meta-analysis—Project-ID 387509280—SFB1350 (Subproject C6 to I.M.H.). A.M.H., B.R., and R.T. were supported by VACSR&D MVP grant CX001897. This research is based on data from the Million Veteran Program, Office of Research and Development, Veterans Health Administration, and was supported by VACSR&D MVP grant CX001897 (A.M.H.). This publication does not represent the views of the Department of Veteran Affairs or the United States Government. We conducted this research using the UK Biobank resource under the application number 20272.

Background Transcranial direct current stimulation (tDCS) is a form of noninvasive brain stimulation whose potential as a cognitive therapy is hindered by our limited understanding of how participant and experimental factors influence its effects. Using functional MRI to study brain networks, we have previously shown in healthy controls that the physiological effects of tDCS are strongly influenced by brain state. We have additionally shown, in both healthy and traumatic brain injury (TBI) populations, that the behavioral effects of tDCS are positively correlated with white matter (WM) structure. Objectives In this study we investigate how these two factors, WM structure and brain state, interact to shape the effect of tDCS on brain network activity. Methods We applied anodal, cathodal and sham tDCS to the right inferior frontal gyrus (rIFG) of healthy (n = 22) and TBI participants (n = 34). We used the Choice Reaction Task (CRT) performance to manipulate brain state during tDCS. We acquired simultaneous fMRI to assess activity of cognitive brain networks and used Fractional Anisotropy (FA) as a measure of WM structure. Results We find that the effects of tDCS on brain network activity in TBI participants are highly dependent on brain state, replicating findings from our previous healthy control study in a separate, patient cohort. We then show that WM structure further modulates the brain-state dependent effects of tDCS on brain network activity. These effects are not unidirectional - in the absence of task with anodal and cathodal tDCS, FA is positively correlated with brain activity in several regions of the default mode network. Conversely, with cathodal tDCS during CRT performance, FA is negatively correlated with brain activity in a salience network region. Conclusions Our results show that experimental and participant factors interact to have unexpected effects on brain network activity, and that these effects are not fully predictable by studying the factors in isolation., Highlights • We replicated the brain state and polarity dependent effects of tDCS. • White matter structure influences tDCS's state-dependent changes in neural activity • The parameters of tDCS may operate under a hierarchy of influence.

Multiple sclerosis (MS) is an inflammatory and demyelinating neurological disease of the central nervous system. Image-based biomarkers, such as lesions defined on magnetic resonance imaging (MRI), play an important role in MS diagnosis and patient monitoring. The detection of newly formed lesions provides crucial information for assessing disease progression and treatment outcome. Here, we propose a deep learning-based pipeline for new MS lesion detection and segmentation, which is built upon the nnU-Net framework. In addition to conventional data augmentation, we employ imaging and lesion-aware data augmentation methods, axial subsampling and CarveMix, to generate diverse samples and improve segmentation performance. The proposed pipeline is evaluated on the MICCAI 2021 MS new lesion segmentation challenge (MSSEG-2) dataset. It achieves an average Dice score of 0.510 and F1 score of 0.552 on cases with new lesions, and an average false positive lesion number nFP of 0.036 and false positive lesion volume VFP of 0.192 mm3 on cases with no new lesions. Our method outperforms other participating methods in the challenge and several state-of-the-art network architectures.

Sex differences have been identified in many diseases associated with dysregulated immune responses, including Alzheimer’s disease (AD), for which approximately two-thirds of patients are women. An accumulating body of research indicates that microglia may play a causal role in the pathogenesis of this disease. We hypothesised that sex differences in the transcriptome of human myeloid cells may contribute to the sex difference observed in AD prevalence. To explore this, we assessed bulk and single-nuclear RNA sequencing data sets generated from four human derived myeloid cell populations: post-mortem microglial nuclei, peripheral monocytes, monocyte-derived macrophages (MDMs) and induced pluripotent stem cell derived microglial-like cells (MGLs). We found that expression of AD risk genes, gene signatures associated with the inflammatory response in AD, and genes related to proinflammatory immune responses were enriched in microglial nuclei isolated from aged female donors without ante-mortem neurological disease, relative to those from males. In addition, these inflammation-associated gene sets were found to be enriched in peripheral monocytes isolated from postmenopausal women and in MDMs obtained from premenopausal individuals relative to age-matched males. Expression of these gene sets did not differ in MDMs derived from women whose blood was sampled across the menstrual cycle or in MGLs cultured with 17β-oestradiol. This suggests that the observed gene set enrichments in myeloid cells from women were not being driven by acute hormonal influences. Together, these data support the hypothesis that the increased prevalence of AD in women may be partly explained by a myeloid cell phenotype biased towards expression of biological processes relevant to AD.

Genome-wide association studies (GWASs) have identified genetic loci associated with the risk of Alzheimer’s disease (AD), but the molecular mechanisms by which they confer risk are largely unknown. We conducted a metabolome-wide association study (MWAS) of AD-associated loci from GWASs using untargeted metabolic profiling (metabolomics) by ultraperformance liquid chromatography–mass spectrometry (UPLC-MS). We identified an association of lactosylceramides (LacCer) with AD-related single-nucleotide polymorphisms (SNPs) in ABCA7 ( P = 5.0 × 10 −5 to 1.3 × 10 −44 ). We showed that plasma LacCer concentrations are associated with cognitive performance and genetically modified levels of LacCer are associated with AD risk. We then showed that concentrations of sphingomyelins, ceramides, and hexosylceramides were altered in brain tissue from Abca7 knockout mice, compared with wild type (WT) ( P = 0.049–1.4 × 10 −5 ), but not in a mouse model of amyloidosis. Furthermore, activation of microglia increases intracellular concentrations of hexosylceramides in part through induction in the expression of sphingosine kinase, an enzyme with a high control coefficient for sphingolipid and ceramide synthesis. Our work suggests that the risk for AD arising from functional variations in ABCA7 is mediated at least in part through ceramides. Modulation of their metabolism or downstream signaling may offer new therapeutic opportunities for AD.

Cell stress and impaired oxidative phosphorylation are central to mechanisms of synaptic loss and neurodegeneration in the cellular pathology of Alzheimer’s disease (AD). In this study, we quantified the in vivo expression of the endoplasmic reticulum stress marker, sigma 1 receptor (S1R), using [ 11 C]SA4503 positron emission tomography (PET), the mitochondrial complex I (MC1) with [ 18 F]BCPP-EF, and the presynaptic vesicular protein SV2A with [ 11 C]UCB-J in 12 patients with early AD and in 16 cognitively normal controls. We integrated these molecular measures with assessments of regional brain volumes and cerebral blood flow (CBF) measured with magnetic resonance imaging arterial spin labeling. Eight patients with AD were followed longitudinally to estimate the rate of change of the physiological and structural pathology markers with disease progression. The patients showed widespread increases in S1R (≤ 27%) and regional reduction in MC1 (≥ −28%) and SV2A (≥ −25%) radioligand binding, brain volume (≥ −23%), and CBF (≥ −26%). [ 18 F]BCPP-EF PET MC1 binding (≥ −12%) and brain volumes (≥ −5%) showed progressive reductions over 12 to 18 months, suggesting that they both could be used as pharmacodynamic indicators in early-stage therapeutics trials. Associations of reduced MC1 and SV2A and increased S1R radioligand binding with reduced cognitive performance in AD, although exploratory, suggested a loss of metabolic functional reserve with disease. Our study thus provides in vivo evidence for widespread, clinically relevant cellular stress and bioenergetic abnormalities in early AD.

In mice, social defeat stress (SDS), an ethological model for psychosocial stress, induces sleep. Such sleep could enable resilience, but how stress promotes sleep is unclear. Activity-dependent tagging revealed a subset of ventral tegmental area γ-aminobutyric acid (GABA)–somatostatin (VTA Vgat-Sst ) cells that sense stress and drive non–rapid eye movement (NREM) and REM sleep through the lateral hypothalamus and also inhibit corticotropin-releasing factor (CRF) release in the paraventricular hypothalamus. Transient stress enhances the activity of VTA Vgat-Sst cells for several hours, allowing them to exert their sleep effects persistently. Lesioning of VTA Vgat-Sst cells abolished SDS-induced sleep; without it, anxiety and corticosterone concentrations remained increased after stress. Thus, a specific circuit allows animals to restore mental and body functions by sleeping, potentially providing a refined route for treating anxiety disorders.

Background Astrocytes provide a vital support to neurons in normal and pathological conditions. In Alzheimer’s disease (AD) brains, reactive astrocytes have been found surrounding amyloid plaques, forming an astrocytic scar. However, their role and potential mechanisms whereby they affect neuroinflammation, amyloid pathology, and synaptic density in AD remain unclear. Methods To explore the role of astrocytes on Aβ pathology and neuroinflammatory markers, we pharmacologically ablated them in organotypic brain culture slices (OBCSs) from 5XFAD mouse model of AD and wild-type (WT) littermates with the selective astrocytic toxin L-alpha-aminoadipate (L-AAA). To examine the effects on synaptic circuitry, we measured dendritic spine number and size in OBCSs from Thy-1-GFP transgenic mice incubated with synthetic Aβ42 or double transgenics Thy-1-GFP/5XFAD mice treated with LAAA or vehicle for 24 h. Results Treatment of OBCSs with L-AAA resulted in an increased expression of pro-inflammatory cytokine IL-6 in conditioned media of WTs and 5XFAD slices, associated with changes in microglia morphology but not in density. The profile of inflammatory markers following astrocytic loss was different in WT and transgenic cultures, showing reductions in inflammatory mediators produced in astrocytes only in WT sections. In addition, pharmacological ablation of astrocytes led to an increase in Aβ levels in homogenates of OBCS from 5XFAD mice compared with vehicle controls, with reduced enzymatic degradation of Aβ due to lower neprilysin and insulin-degrading enzyme (IDE) expression. Furthermore, OBSCs from wild-type mice treated with L-AAA and synthetic amyloid presented 56% higher levels of Aβ in culture media compared to sections treated with Aβ alone, concomitant with reduced expression of IDE in culture medium, suggesting that astrocytes contribute to Aβ clearance and degradation. Quantification of hippocampal dendritic spines revealed a reduction in their density following L-AAA treatment in all groups analyzed. In addition, pharmacological ablation of astrocytes resulted in a decrease in spine size in 5XFAD OBCSs but not in OBCSs from WT treated with synthetic Aβ compared to vehicle control. Conclusions Astrocytes play a protective role in AD by aiding Aβ clearance and supporting synaptic plasticity.

Following hyperacute management after traumatic brain injury (TBI), most patients receive treatment which is inadequate or inappropriate, and delayed. This results in suboptimal rehabilitation outcome and avoidable detrimental chronic effects on patients’ recovery. This worsens long-term disability, and magnifies costs to the individual and society. We believe that accurate diagnosis (at the level of pathology, impairment and function) of the causes of disability is a prerequisite for appropriate care and for accessing effective rehabilitation. An expert-led, integrated care pathway is needed to deliver accurate and timely diagnosis and optimal treatment at all stages during a TBI patient’s care. We propose the introduction of a specialist interdisciplinary traumatic brain injury team, led by a neurosciences-trained brain injury consultant. This team would engage acutely and for a longer term after TBI to provide accurate diagnoses, which guides subsequent management and rehabilitation. This approach would also encourage more efficient collaboration between research and the clinic. We propose that the current major trauma network is leveraged to introduce and evaluate this proposal. Improvements to patient outcomes through this approach would lead to reduced personal, societal and economic impact of TBI.

Purpose To achieve rapid, low specific absorption rate (SAR) super-resolution imaging by exploiting the characteristic magnetization off-resonance profile in SSFP. Theory and methods In the presented technique, low flip angle unbalanced SSFP imaging is used to acquire a series of images at a low nominal resolution that are then combined in a super-resolution strategy analogous to non-linear structured illumination microscopy. This is demonstrated in principle via Bloch simulations and synthetic phantoms, and the performance is quantified in terms of point-spread function (PSF) and SNR for gray and white matter from field strengths of 0.35T to 9.4T. A k-space reconstruction approach is proposed to account for B0 effects. This was applied to reconstruct super-resolution images from a test object at 9.4T. Results Artifact-free super-resolution images were produced after incorporating sufficient preparation time for the magnetization to approach the steady state. High-resolution images of a test object were obtained at 9.4T, in the presence of considerable B0 inhomogeneity. For gray matter, the highest achievable resolution ranges from 3% of the acquired voxel dimension at 0.35T, to 9% at 9.4T. For white matter, this corresponds to 3% and 10%, respectively. Compared to an equivalent segmented gradient echo acquisition at the optimal flip angle, with a fixed TR of 8 ms, gray matter has up to 34% of the SNR at 9.4T while using a ×10 smaller flip angle. For white matter, this corresponds to 29% with a ×11 smaller flip angle. Conclusion This approach achieves high degrees of super-resolution enhancement with minimal RF power requirements.

Vestibular Agnosia - where peripheral vestibular activation triggers the usual reflex nystagmus response but with attenuated or no self-motion perception - is found in brain disease with disrupted cortical network functioning, e.g. traumatic brain injury (TBI) or neurodegeneration (Parkinson’s Disease). Patients with acute focal hemispheric lesions (e.g. stroke) do not manifest vestibular agnosia. Thus brain network mapping techniques, e.g. resting state functional MRI (rsfMRI), are needed to interrogate functional brain networks mediating vestibular agnosia. Whole-brain rsfMRI was acquired from 39 prospectively recruited acute TBI patients with preserved peripheral vestibular function, along with self-motion perceptual thresholds during passive yaw rotations in the dark. Following quality-control checks, 25 patient scans were analyzed. TBI patients were classified as having vestibular agnosia (n = 11) or not (n = 14) via laboratory testing of self-motion perception. Using independent component analysis, we found altered functional connectivity in the right superior longitudinal fasciculus and left rostral prefrontal cortex in vestibular agnosia. Moreover, regions of interest analyses showed both inter-hemispheric and intra-hemispheric network disruption in vestibular agnosia. In conclusion, our results show that vestibular agnosia is mediated by bilateral anterior and posterior network dysfunction and reveal the distributed brain mechanisms mediating vestibular self-motion perception.

ObjectiveTo explore the causal relationships between sleep, major depressive disorder (MDD), and Alzheimer disease (AD).MethodsWe conducted bidirectional 2-sample Mendelian randomization analyses. Genetic associations were obtained from the largest genome-wide association studies currently available in UK Biobank (n = 446,118), Psychiatric Genomics Consortium (n = 18,759), and International Genomics of Alzheimer's Project (n = 63,926). We used the inverse variance–weighted Mendelian randomization method to estimate causal effects and weighted median and Mendelian randomization–Egger for sensitivity analyses to test for pleiotropic effects.ResultsWe found that higher risk of AD was significantly associated with being a “morning person” (odds ratio [OR] 1.01, p = 0.001), shorter sleep duration (self-reported: β = −0.006, p = 1.9 × 10−4; accelerometer based: β = −0.015, p = 6.9 × 10−5), less likely to report long sleep (β = −0.003, p = 7.3 × 10−7), earlier timing of the least active 5 hours (β = −0.024, p = 1.7 × 10−13), and a smaller number of sleep episodes (β = −0.025, p = 5.7 × 10−14) after adjustment for multiple comparisons. We also found that higher risk of AD was associated with lower risk of insomnia (OR 0.99, p = 7 × 10−13). However, we did not find evidence that these abnormal sleep patterns were causally related to AD or for a significant causal relationship between MDD and risk of AD.ConclusionWe found that AD may causally influence sleep patterns. However, we did not find evidence supporting a causal role of disturbed sleep patterns for AD or evidence for a causal relationship between MDD and AD.

Multiple biomarkers can capture different facets of Alzheimer's disease. However, statistical models of biomarkers to predict outcomes in Alzheimer's rarely model nonlinear interactions between these measures. Here, we used Gaussian Processes to address this, modelling nonlinear interactions to predict progression from mild cognitive impairment (MCI) to Alzheimer's over 3 years, using Alzheimer's Disease Neuroimaging Initiative (ADNI) data. Measures included: demographics, APOE4 genotype, CSF (amyloid‐β42, total tau, phosphorylated tau), [18F]florbetapir, hippocampal volume and brain‐age. We examined: (a) the independent value of each biomarker; and (b) whether modelling nonlinear interactions between biomarkers improved predictions. Each measured added complementary information when predicting conversion to Alzheimer's. A linear model classifying stable from progressive MCI explained over half the variance (R2 = 0.51, p, Alzheimer's disease progression is multi‐faceted. Here, we used demographic, genetic, neuroimaging and CSF measures to predict progression to Alzheimer's in people with mild cognitive impairment. We found that all measures provide unique information to improve predictions. Furthermore, by modelling nonlinear interactions between biomarkers, improved fit of predictive models was achieved.

ObjectivesTo understand SARS-Co-V-2 infection and transmission in UK nursing homes in order to develop preventive strategies for protecting the frail elderly residents.DesignAn outbreak investigation.Setting4 nursing homes affected by COVID-19 outbreaks in central London.Participants394 residents and 70 staff in nursing homes.InterventionsTwo point-prevalence surveys one week apart where residents underwent SARS-CoV-2 testing and had relevant symptoms documented. Asymptomatic staff from three of the four homes were also offered SARS-CoV-2 testing.Main outcome measuresAll-cause mortality, and mortality attributed to COVID-19 on death certificates. Prevalence of SARS-CoV-2 infection and symptoms in residents and staff.ResultsOverall, 26% (95% confidence interval 22 to 31) of residents died over the two-month period. All-cause mortality increased by 203% (95% CI 70 to 336). Systematic testing identified 40% (95% CI 35 to 46) of residents, of whom 43% (95% CI 34 to 52) were asymptomatic and 18% (95% CI 11 to 24) had atypical symptoms, as well as 4% (95% CI -1 to 9) of asymptomatic staff who tested positive for SARS-CoV-2.ConclusionsThe SARS-CoV-2 outbreak was associated with a very high mortality rate in residents of nursing homes. Systematic testing of all residents and a representative sample of staff identified high rates of SARS-CoV-2 positivity across the four nursing homes, highlighting a potential for regular screening to prevent future outbreaks.

Aortic dimensions and distensibility are key risk factors for aortic aneurysms and dissections, as well as for other cardiovascular and cerebrovascular diseases. We present genome-wide associations of ascending and descending aortic distensibility and area derived from cardiac magnetic resonance imaging (MRI) data of up to 32,590 Caucasian individuals in UK Biobank. We identify 102 loci (including 27 novel associations) tagging genes related to cardiovascular development, extracellular matrix production, smooth muscle cell contraction and heritable aortic diseases. Functional analyses highlight four signalling pathways associated with aortic distensibility (TGF-β, IGF, VEGF and PDGF). We identify distinct sex-specific associations with aortic traits. We develop co-expression networks associated with aortic traits and apply phenome-wide Mendelian randomization (MR-PheWAS), generating evidence for a causal role for aortic distensibility in development of aortic aneurysms. Multivariable MR suggests a causal relationship between aortic distensibility and cerebral white matter hyperintensities, mechanistically linking aortic traits and brain small vessel disease.

We experience the world through multiple senses simultaneously. To better understand mechanisms of multisensory processing we ask whether inputs from two senses (auditory and visual) can interact and drive plasticity in neural-circuits of the primary visual cortex (V1). Using genetically-encoded voltage and calcium indicators, we find coincident audio-visual experience modifies both the supra and subthreshold response properties of neurons in L2/3 of mouse V1. Specifically, we find that after audio-visual pairing, a subset of multimodal neurons develops enhanced auditory responses to the paired auditory stimulus. This cross-modal plasticity persists over days and is reflected in the strengthening of small functional networks of L2/3 neurons. We find V1 processes coincident auditory and visual events by strengthening functional associations between feature specific assemblies of multimodal neurons during bouts of sensory driven co-activity, leaving a trace of multisensory experience in the cortical network., Sensory stimuli usually arrive simultaneously but the neural-circuit mechanisms that combine multiple streams of sensory information are incompletely understood. The authors here show that visual-auditory pairing drives plasticity in multi-modal neuron networks within the mouse visual cortex.

Publisher's version (útgefin grein)., Both short and long sleep are associated with an adverse lipid profile, likely through different biological pathways. To elucidate the biology of sleep-associated adverse lipid profile, we conduct multi-ancestry genome-wide sleep-SNP interaction analyses on three lipid traits (HDL-c, LDL-c and triglycerides). In the total study sample (discovery + replication) of 126,926 individuals from 5 different ancestry groups, when considering either long or short total sleep time interactions in joint analyses, we identify 49 previously unreported lipid loci, and 10 additional previously unreported lipid loci in a restricted sample of European-ancestry cohorts. In addition, we identify new gene-sleep interactions for known lipid loci such as LPL and PCSK9. The previously unreported lipid loci have a modest explained variance in lipid levels: most notable, gene-short-sleep interactions explain 4.25% of the variance in triglyceride level. Collectively, these findings contribute to our understanding of the biological mechanisms involved in sleep-associated adverse lipid profiles., This project was supported by a grant from the US National Heart, Lung, and Blood Institute (NHLBI) of the National Institutes of Health (R01HL118305). This research was supported in part by the Intramural Research Program of the National Human Genome Research Institute, National Institutes of Health. Tuomas O. Kilpeläinen was supported by the Danish Council for Independent Research (DFF–6110-00183) and the Novo Nordisk Foundation (NNF18CC0034900, NNF17OC0026848 and NNF15CC0018486). Diana van Heemst was supported by the European Commission funded project HUMAN (Health-2013-INNOVATION-1-602757). Susan Redline was supported in part by NIH R35HL135818 and HL11338. Study-specific acknowledgements can be found in the Supplementary Notes 2 and 4. The data on coronary artery disease have been contributed by the Myocardial Infarction Genetics and CARDIoGRAM investigators, and have been downloaded from www.CARDIOGRAMPLUSC4D.ORG.

While psychedelics may have therapeutic potential for treating mental health disorders such as depression, further research is needed to better understand their biological effects and mechanisms of action when considering the development of future novel therapy approaches. Psychedelic research could potentially benefit from the integration of metabonomics by proton nuclear magnetic resonance (1H NMR) spectroscopy which is an analytical chemistry-based approach that can measure the breakdown of drugs into their metabolites and their metabolic consequences from various biofluids. We have performed a systematic review with the primary aim of exploring published literature where 1H NMR analysed psychedelic substances including psilocin, lysergic acid diethylamide (LSD), LSD derivatives, N,N-dimethyltryptamine (DMT), 5-methoxy-N,N-dimethyltryptamine (5-MeO-DMT) and bufotenin. The second aim was to assess the benefits and limitations of 1H NMR spectroscopy-based metabolomics as a tool in psychedelic research and the final aim was to explore potential future directions. We found that the most current use of 1H NMR in psychedelic research has been for the structural elucidation and analytical characterisation of psychedelic molecules and that no papers used 1H NMR in the metabolic profiling of biofluids, thus exposing a current research gap and the underuse of 1H NMR. The efficacy of 1H NMR spectroscopy was also compared to mass spectrometry, where both metabonomics techniques have previously shown to be appropriate for biofluid analysis in other applications. Additionally, potential future directions for psychedelic research were identified as real-time NMR, in vivo1H nuclear magnetic resonance spectroscopy (MRS) and 1H NMR studies of the gut microbiome. Further psychedelic studies need to be conducted that incorporate the use of 1H NMR spectroscopy in the analysis of metabolites both in the peripheral biofluids and in vivo to determine whether it will be an effective future approach for clinical and naturalistic research.

We propose a new framework for estimating neuroimaging-derived “brain-age” at a local level within the brain, using deep learning. The local approach, contrary to existing global methods, provides spatial information on anatomical patterns of brain ageing. We trained a U-Net model using brain MRI scans from n = 3,463 healthy people (aged 18–90 years) to produce individualised 3D maps of brain-predicted age. When testing on n = 692 healthy people, we found a median (across participant) mean absolute error (within participant) of 9.5 years. Performance was more accurate (MAE around 7 years) in the prefrontal cortex and periventricular areas. We also introduce a new voxelwise method to reduce the age-bias when predicting local brain-age “gaps.” To validate local brain-age predictions, we tested the model in people with mild cognitive impairment or dementia using data from OASIS3 (n = 267). Different local brain-age patterns were evident between healthy controls and people with mild cognitive impairment or dementia, particularly in subcortical regions such as the accumbens, putamen, pallidum, hippocampus, and amygdala. Comparing groups based on mean local brain-age over regions-of-interest resulted in large effects sizes, with Cohen's d values >1.5, for example when comparing people with stable and progressive mild cognitive impairment. Our local brain-age framework has the potential to provide spatial information leading to a more mechanistic understanding of individual differences in patterns of brain ageing in health and disease.

An overreliance on commercial, kit-based RNA extraction in the molecular diagnoses of infectious disease presents a challenge in the event of supply chain disruptions and can potentially hinder testing capacity in times of need. In this study, we adapted a well-established, robust TRIzol-based RNA extraction protocol into a high-throughput format through miniaturization and automation. The workflow was validated by RT-qPCR assay for SARS-CoV-2 detection to illustrate its scalability without interference to downstream diagnostic sensitivity and accuracy. This semi-automated, kit-free approach offers a versatile alternative to prevailing integrated solid-phase RNA extraction proprietary systems, with the added advantage of improved cost-effectiveness for high volume acquisition of quality RNA whether for use in clinical diagnoses or for diverse molecular applications.

Background Amyloid-β (Aβ) PET has emerged as clinically useful for more accurate diagnosis of patients with cognitive decline. Aβ deposition is a necessary cause or response to the cellular pathology of Alzheimer’s disease (AD). Usual clinical and research interpretation of amyloid PET does not fully utilise all information regarding the spatial distribution of signal. We present a data-driven, spatially informed classifier to boost the diagnostic power of amyloid PET in AD. Methods Voxel-wise k-means clustering of amyloid-positive voxels was performed; clusters were mapped to brain anatomy and tested for their associations by diagnostic category and disease severity with 758 amyloid PET scans from volunteers in the AD continuum from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). A machine learning approach based on this spatially constrained model using an optimised quadratic support vector machine was developed for automatic classification of scans for AD vs non-AD pathology. Results This classifier boosted the accuracy of classification of AD scans to 81% using the amyloid PET alone with an area under the curve (AUC) of 0.91 compared to other spatial methods. This increased sensitivity to detect AD by 15% and the AUC by 9% compared to the use of a composite region of interest SUVr. Conclusions The diagnostic classification accuracy of amyloid PET was improved using an automated data-driven spatial classifier. Our classifier highlights the importance of considering the spatial variation in Aβ PET signal for optimal interpretation of scans. The algorithm now is available to be evaluated prospectively as a tool for automated clinical decision support in research settings.

Accurate, reliable, and cost-effective immunosensors are clinically important for the early diagnosis and monitoring of progressive diseases, and multiplexed sensing is a promising strategy for the next generation of diagnostics. This strategy allows for the simultaneous detection and quantification of multiple biomarkers with significantly enhanced reproducibility and reliability, whilst requiring smaller sample volumes, fewer materials, and shorter average analysis time for individual biomarkers than individual tests. In this opinionated review, we compare different techniques for the development of multiplexed immunosensors. We review the state-of-the-art approaches in the field of multiplexed immunosensors using electrical, electrochemical, and optical methods. The barriers that prevent translating this sensing strategy into clinics are outlined together with the potential solutions. We also share our vision on how multiplexed immunosensors will continue their evolution in the coming years.

When mice are exposed to external warmth, nitric oxide synthase (NOS1) neurons in the median and medial preoptic (MnPO/MPO) hypothalamus induce sleep and concomitant body cooling. However, how these neurons regulate baseline sleep and body temperature is unknown. Using calcium photometry, we show that NOS1 neurons in MnPO/MPO are predominantly NREM and REM active, especially at the boundary of wake to NREM transitions, and in the later parts of REM bouts, with lower activity during wakefulness. In addition to releasing nitric oxide, NOS1 neurons in MnPO/MPO can release GABA, glutamate and peptides. We expressed tetanus-toxin light-chain in MnPO/MPO NOS1 cells to reduce vesicular release of transmitters. This induced changes in sleep structure: over 24 h, mice had less NREM sleep in their dark (active) phase, and more NREM sleep in their light (sleep) phase. REM sleep episodes in the dark phase were longer, and there were fewer REM transitions between other vigilance states. REM sleep had less theta power. Mice with synaptically blocked MnPO/MPO NOS1 neurons were also warmer than control mice at the dark-light transition (ZT0), as well as during the dark phase siesta (ZT16-20), where there is usually a body temperature dip. Also, at this siesta point of cooled body temperature, mice usually have more NREM, but mice with synaptically blocked MnPO/MPO NOS1 cells showed reduced NREM sleep at this time. Overall, MnPO/MPO NOS1 neurons promote both NREM and REM sleep and contribute to chronically lowering body temperature, particularly at transitions where the mice normally enter NREM sleep., Frontiers in Neuroscience, 15, ISSN:1662-453X, ISSN:1662-4548

Background: Peripheral neuropathy can be caused by diabetes mellitus and HIV infection, and often leaves patients with treatment-resistant neuropathic pain. To better treat this condition, we need greater understanding of the pathogenesis, as well as objective biomarkers to predict treatment response. Magnetic resonance imaging (MRI) has a firm place as a biomarker for diseases of the central nervous system (CNS), but until recently has had little role for disease of the peripheral nervous system.Objectives: To review the current state-of-the-art of peripheral nerve MRI in diabetic and HIV symmetrical polyneuropathy. We used systematic literature search methods to identify all studies currently published, using this as a basis for a narrative review to discuss major findings in the literature. We also assessed risk of bias, as well as technical aspects of MRI and statistical analysis.Methods: Protocol was pre-registered on NIHR PROSPERO database. MEDLINE, Web of Science and EMBASE databases were searched from 1946 to 15th August 2020 for all studies investigating either diabetic or HIV neuropathy and MRI, focusing exclusively on studies investigating symmetrical polyneuropathy. The NIH quality assessment tool for observational and cross-sectional cohort studies was used for risk of bias assessment.Results: The search resulted in 18 papers eligible for review, 18 for diabetic neuropathy and 0 for HIV neuropathy. Risk of bias assessment demonstrated that studies generally lacked explicit sample size justifications, and some may be underpowered. Whilst most studies made efforts to balance groups for confounding variables (age, gender, BMI, disease duration), there was lack of consistency between studies. Overall, the literature provides convincing evidence that DPN is associated with larger nerve cross sectional area, T2-weighted hyperintense and hypointense lesions, evidence of nerve oedema on Dixon imaging, decreased fractional anisotropy and increased apparent diffusion coefficient compared with controls. Analysis to date is largely restricted to the sciatic nerve or its branches.Conclusions: There is emerging evidence that various structural MR metrics may be useful as biomarkers in diabetic polyneuropathy, and areas for future direction are discussed. Expanding this technique to other forms of peripheral neuropathy, including HIV neuropathy, would be of value.Systematic Review Registration: (identifier: CRD 42020167322) https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=167322.

BACKGROUND Salt substitutes with reduced sodium levels and increased potassium levels have been shown to lower blood pressure, but their effects on cardiovascular and safety outcomes are uncertain. METHODS We conducted an open-label, cluster-randomized trial involving persons from 600 villages in rural China. The participants had a history of stroke or were 60 years of age or older and had high blood pressure. The villages were randomly assigned in a 1:1 ratio to the intervention group, in which the participants used a salt substitute (75% sodium chloride and 25% potassium chloride by mass), or to the control group, in which the participants continued to use regular salt (100% sodium chloride). The primary outcome was stroke, the secondary outcomes were major adverse cardiovascular events and death from any cause, and the safety outcome was clinical hyperkalemia. RESULTS A total of 20,995 persons were enrolled in the trial. The mean age of the participants was 65.4 years, and 49.5% were female, 72.6% had a history of stroke, and 88.4% a history of hypertension. The mean duration of follow-up was 4.74 years. The rate of stroke was lower with the salt substitute than with regular salt (29.14 events vs. 33.65 events per 1000 person-years; rate ratio, 0.86; 95% confidence interval [CI], 0.77 to 0.96; P=0.006), as were the rates of major cardiovascular events (49.09 events vs. 56.29 events per 1000 person-years; rate ratio, 0.87; 95% CI, 0.80 to 0.94; P

Axonal injury is a key determinant of long-term outcomes after traumatic brain injury (TBI) but has been difficult to measure clinically. Fluid biomarker assays can now sensitively quantify neuronal proteins in blood. Axonal components such as neurofilament light (NfL) potentially provide a diagnostic measure of injury. In the multicenter BIO-AX-TBI study of moderate-severe TBI, we investigated relationships between fluid biomarkers, advanced neuroimaging, and clinical outcomes. Cerebral microdialysis was used to assess biomarker concentrations in brain extracellular fluid aligned with plasma measurement. An experimental injury model was used to validate biomarkers against histopathology. Plasma NfL increased after TBI, peaking at 10 days to 6 weeks but remaining abnormal at 1 year. Concentrations were around 10 times higher early after TBI than in controls (patients with extracranial injuries). NfL concentrations correlated with diffusion MRI measures of axonal injury and predicted white matter neurodegeneration. Plasma TAU predicted early gray matter atrophy. NfL was the strongest predictor of functional outcomes at 1 year. Cerebral microdialysis showed that NfL concentrations in plasma and brain extracellular fluid were highly correlated. An experimental injury model confirmed a dose-response relationship of histopathologically defined axonal injury to plasma NfL. In conclusion, plasma NfL provides a sensitive and clinically meaningful measure of axonal injury produced by TBI. This reflects the extent of underlying damage, validated using advanced MRI, cerebral microdialysis, and an experimental model. The results support the incorporation of NfL sampling subacutely after injury into clinical practice to assist with the diagnosis of axonal injury and to improve prognostication.

The ventral tegmental area (VTA), an important source of dopamine, regulates goal- and reward-directed and social behaviors, wakefulness, and sleep. Hyperactivation of dopamine neurons generates behavioral pathologies. But any roles of non-dopamine VTA neurons in psychiatric illness have been little explored. Lesioning or chemogenetically inhibiting VTA GABAergic (VTA(Vgat)) neurons generated persistent wakefulness with mania-like qualities: locomotor activity was increased; sensitivity to D-amphetamine was heightened; immobility times decreased on the tail suspension and forced swim tests; and sucrose preference increased. Furthermore, after sleep deprivation, mice with lesioned VTA(Vgat)neurons did not catch up on lost sleep, even though they were starting from a sleep-deprived baseline, suggesting that sleep homeostasis was bypassed. The mania-like behaviors, including the sleep loss, were reversed by valproate, and re-emerged when treatment was stopped. Lithium salts and lamotrigine, however, had no effect. Low doses of diazepam partially reduced the hyperlocomotion and fully recovered the immobility time during tail suspension. The mania like-behaviors mostly depended on dopamine, because giving D1/D2/D3 receptor antagonists reduced these behaviors, but also partially on VTA(Vgat)projections to the lateral hypothalamus (LH). Optically or chemogenetically inhibiting VTA(Vgat)terminals in the LH elevated locomotion and decreased immobility time during the tail suspension and forced swimming tests. VTA(Vgat)neurons help set an animal's (and perhaps human's) mental and physical activity levels. Inputs inhibiting VTA(Vgat)neurons intensify wakefulness (increased activity, enhanced alertness and motivation), qualities useful for acute survival. In the extreme, however, decreased or failed inhibition from VTA(Vgat)neurons produces mania-like qualities (hyperactivity, hedonia, decreased sleep)., Molecular Psychiatry, 26 (9), ISSN:1359-4184, ISSN:1476-5578

The recognition, diagnosis and management of mild traumatic brain injuries are difficult and confusing. It is unclear how the severity and number of injuries sustained relate to brain injuries, such as diffuse axonal injury, diffuse vascular injury and progressive neurodegeneration. Advances in neuroimaging techniques enable the investigation of neuropathologies associated with acute and long-term effects of injury. Head injuries are the most commonly reported injury seen during professional rugby. There is increased vigilance for the immediate effects of these injuries in matches, but there has been surprisingly little research investigating the longer-term effects of rugby participation. Here, we present a longitudinal observational study investigating the relationship of exposure to rugby participation and sub-acute head injuries in professional adult male and female rugby union and league players using advanced MRI. Diffusion tensor imaging and susceptibility weighted imaging was used to assess white matter structure and evidence of axonal and diffuse vascular injury. We also studied changes in brain structure over time using Jacobian Determinant statistics extracted from serial volumetric imaging. We tested 41 male and 3 female adult elite rugby players, of whom 21 attended study visits after a head injury, alongside 32 non-sporting controls, 15 non-collision-sport athletic controls and 16 longitudinally assessed controls. Eighteen rugby players participated in the longitudinal arm of the study, with a second visit at least 6 months after their first scan. Neuroimaging evidence of either axonal injury or diffuse vascular injury was present in 23% (10/44) of players. In the non-acutely injured group of rugby players, abnormalities of fractional anisotropy and other diffusion measures were seen. In contrast, non-collision-sport athletic controls were not classified as showing abnormalities. A group level contrast also showed evidence of sub-acute injury using diffusion tensor imaging in rugby players. Examination of longitudinal imaging revealed unexpected reductions in white matter volume in the elite rugby players studied. These changes were not related to self-reported head injury history or neuropsychological test scores and might indicate excess neurodegeneration in white matter tracts affected by injury. Taken together, our findings suggest an association of participation in elite adult rugby with changes in brain structure. Further well-designed large-scale studies are needed to understand the impact of both repeated sports-related head impacts and head injuries on brain structure, and to clarify whether the abnormalities we have observed are related to an increased risk of neurodegenerative disease and impaired neurocognitive function following elite rugby participation., Using advanced neuroimaging techniques to study a group of professional rugby players, Zimmerman et al. report evidence of both cross-sectional and longitudinal imaging abnormalities in the white matter. Their findings suggest an association of participation in elite adult rugby with changes in brain structure., Graphical Abstract Graphical Abstract

To monitor innate immune responses in the CNS, the 18 kDa Translocator protein (TSPO) is a frequently used target for PET imaging. The frequent assumption that increased TSPO expression in the human CNS reflects pro‐inflammatory activation of microglia has been extrapolated from rodent studies. However, TSPO expression does not increase in activated human microglia in vitro. Studies of multiple sclerosis (MS) lesions reveal that TSPO is not restricted to pro‐inflammatory microglia/macrophages, but also present in homeostatic or reparative microglia. Here, we investigated quantitative relationships between TSPO expression and microglia/macrophage phenotypes in white matter and lesions of brains with MS pathology. In white matter from brains with no disease pathology, normal appearing white matter (NAWM), active MS lesions and chronic active lesion rims, over 95% of TSPO+ cells are microglia/macrophages. Homeostatic microglial markers in NAWM and control tissue are lost/reduced in active lesions and chronic active lesion rims, reflecting cell activation. Nevertheless, pixel analysis of TSPO+ cells (n = 12,225) revealed that TSPO expression per cell is no higher in active lesions and chronic active lesion rims (where myeloid cells are activated) relative to NAWM and control. This data suggests that whilst almost all the TSPO signal in active lesions, chronic active lesion rims, NAWM and control is associated with microglia/macrophages, their TSPO expression predominantly reflects cell density and not activation phenotype. This finding has implications for the interpretation of TSPO PET signal in MS and other CNS diseases, and further demonstrates the limitation of extrapolating TSPO biology from rodents to humans., MAIN POINTS Increased TSPO in the MS brain is due to an increase in microglia/macrophage cell density rather than activation of these cells.TSPO expression per microglia is similar in control and MS brain regardless of their activation state or morphology.

Background:Excessive alcohol consumption is associated with damage to various organs, but its multi-organ effects have not been characterised across the usual range of alcohol drinking in a large general population sample.Methods:We assessed global effect sizes of alcohol consumption on quantitative magnetic resonance imaging phenotypic measures of the brain, heart, aorta, and liver of UK Biobank participants who reported drinking alcohol.Results:We found a monotonic association of higher alcohol consumption with lower normalised brain volume across the range of alcohol intakes (–1.7 × 10−3 ± 0.76 × 10−3 per doubling of alcohol consumption, p=3.0 × 10−14). Alcohol consumption was also associated directly with measures of left ventricular mass index and left ventricular and atrial volume indices. Liver fat increased by a mean of 0.15% per doubling of alcohol consumption.Conclusions:Our results imply that there is not a ‘safe threshold’ below which there are no toxic effects of alcohol. Current public health guidelines concerning alcohol consumption may need to be revisited.Funding:See acknowledgements.

Neurovascular injury is often observed in traumatic brain injury (TBI). However, the relationship between mechanical forces and vascular injury is still unclear. A key question is whether the complex anatomy of vasculature plays a role in increasing forces in cerebral vessels and producing damage. We developed a high-fidelity multiscale finite element model of the rat brain featuring a detailed definition of the angioarchitecture. Controlled cortical impacts were performed experimentally and in-silico. The model was able to predict the pattern of blood–brain barrier damage. We found strong correlation between the area of fibrinogen extravasation and the brain area where axial strain in vessels exceeds 0.14. Our results showed that adjacent vessels can sustain profoundly different axial stresses depending on their alignment with the principal direction of stress in parenchyma, with a better alignment leading to larger stresses in vessels. We also found a strong correlation between axial stress in vessels and the shearing component of the stress wave in parenchyma. Our multiscale computational approach explains the unrecognised role of the vascular anatomy and shear stresses in producing distinct distribution of large forces in vasculature. This new understanding can contribute to improving TBI diagnosis and prevention.

To further fulfil their missions of promoting teaching, education and research in neurology and related clinical-academic disciplines, the Guarantors of Brain and the Brain journal family invited delegates to the first Brain Conference in Spring of this year. This event aimed to deliver excellent teaching and scientific presentations across a broad spectrum of neuroscience fields, with the key aim of making the content as accessible as possible. We hoped to capitalize on the benefits of an online format, whilst trying to capture a little of the joy of the in-person meeting. This article reports on the approach and practical choices made to achieve these goals, and we hope this will provide some guidance and advice to others organizing their own online conference., Li et al. report on what went on ‘behind the scenes’ of the first Brain Conference, which took place in March 2021. Programming, technology and organizational choices are described, as well as reflections on what went well and what should be improved for future events.

BackgroundAs life expectancy grows, so do the challenges of caring for an aging population. Older adults, including people with dementia, want to live independently and feel in control of their lives for as long as possible. Assistive technologies powered by artificial intelligence and internet of things devices are being proposed to provide living environments that support the users’ safety, psychological, and medical needs through remote monitoring and interventions.ObjectiveThis study investigates the functional, psychosocial, and environmental needs of people living with dementia, their caregivers, clinicians, and health and social care service providers toward the design and implementation of smart home systems.MethodsWe used an iterative user-centered design approach comprising 9 substudies. First, semistructured interviews (9 people with dementia, 9 caregivers, and 10 academic and clinical staff) and workshops (35 pairs of people with dementia and caregivers, and 12 health and social care clinicians) were conducted to define the needs of people with dementia, home caregivers, and professional stakeholders in both daily activities and technology-specific interactions. Then, the spectrum of needs identified was represented via patient–caregiver personas and discussed with stakeholders in a workshop (14 occupational therapists; 4 National Health Service pathway directors; and 6 researchers in occupational therapy, neuropsychiatry, and engineering) and 2 focus groups with managers of health care services (n=8), eliciting opportunities for innovative care technologies and public health strategies. Finally, these design opportunities were discussed in semistructured interviews with participants of a smart home trial involving environmental sensors, physiological measurement devices, smartwatches, and tablet-based chatbots and cognitive assessment puzzles (10 caregivers and 2 people with dementia). A thematic analysis revealed factors that motivate household members to use these technologies.ResultsOutcomes of these activities include a qualitative and quantitative analysis of patient, caregiver, and clinician needs and the identification of challenges and opportunities for the design and implementation of remote monitoring systems in public health pathways.ConclusionsParticipatory design methods supported the triangulation of stakeholder perspectives to aid the development of more patient-centered interventions and their translation to clinical practice and public health strategy. We discuss the implications and limitations of our findings, the value and the applicability of our methodology, and directions for future research.

Annotation and identification of metabolite biomarkers is critical for their biological interpretation in metabolic phenotyping studies, presenting a significant bottleneck in the successful implementation of untargeted metabolomics. Here, a systematic multi-step protocol was developed for the purification and de novo structural elucidation of urinary metabolites. The protocol is most suited for instances where structure elucidation and metabolite annotation are critical for the downstream biological interpretation of metabolic phenotyping studies. First, a bulk urine pool was desalted using ion-exchange resins enabling large-scale fractionation using precise iterations of analytical scale chromatography. Primary urine fractions were collected and assembled into a “fraction bank” suitable for long-term laboratory storage. Secondary and tertiary fractionations exploited differences in selectivity across a range of reversed-phase chemistries, achieving the purification of metabolites of interest yielding an amount of material suitable for chemical characterisation. To exemplify the application of the systematic workflow in a diverse set of cases, four metabolites with a range of physico-chemical properties were selected and purified from urine and subjected to chemical formula and structure elucidation by respective magnetic resonance mass spectrometry (MRMS) and NMR analyses. Their structures were fully assigned as teterahydropentoxyline, indole-3-acetic-acid-O-glucuronide, p-cresol glucuronide, and pregnanediol-3-glucuronide. Unused effluent was collected, dried and returned to the fraction bank, demonstrating the viability of the system for repeat use in metabolite annotation with a high degree of efficiency.

Parkinson’s disease (PD), Parkinson’s disease with dementia (PDD) and dementia with Lewy bodies (DLB) are three clinically, genetically and neuropathologically overlapping neurodegenerative diseases collectively known as the Lewy body diseases (LBDs). A variety of molecular mechanisms have been implicated in PD pathogenesis, but the mechanisms underlying PDD and DLB remain largely unknown, a knowledge gap that presents an impediment to the discovery of disease-modifying therapies. Transcriptomic profiling can contribute to addressing this gap, but remains limited in the LBDs. Here, we applied paired bulk-tissue and single-nucleus RNA-sequencing to anterior cingulate cortex samples derived from 28 individuals, including healthy controls, PD, PDD and DLB cases (n = 7 per group), to transcriptomically profile the LBDs. Using this approach, we (i) found transcriptional alterations in multiple cell types across the LBDs; (ii) discovered evidence for widespread dysregulation of RNA splicing, particularly in PDD and DLB; (iii) identified potential splicing factors, with links to other dementia-related neurodegenerative diseases, coordinating this dysregulation; and (iv) identified transcriptomic commonalities and distinctions between the LBDs that inform understanding of the relationships between these three clinical disorders. Together, these findings have important implications for the design of RNA-targeted therapies for these diseases and highlight a potential molecular “window” of therapeutic opportunity between the initial onset of PD and subsequent development of Lewy body dementia. Supplementary Information The online version contains supplementary material available at 10.1007/s00401-021-02343-x.

The heart muscle diseases hypertrophic (HCM) and dilated (DCM) cardiomyopathies are leading causes of sudden death and heart failure in young, otherwise healthy, individuals. We conducted genome-wide association studies and multi-trait analyses in HCM (1,733 cases), DCM (5,521 cases) and nine left ventricular (LV) traits (19,260 UK Biobank participants with structurally normal hearts). We identified 16 loci associated with HCM, 13 with DCM and 23 with LV traits. We show strong genetic correlations between LV traits and cardiomyopathies, with opposing effects in HCM and DCM. Two-sample Mendelian randomization supports a causal association linking increased LV contractility with HCM risk. A polygenic risk score explains a significant portion of phenotypic variability in carriers of HCM-causing rare variants. Our findings thus provide evidence that polygenic risk score may account for variability in Mendelian diseases. More broadly, we provide insights into how genetic pathways may lead to distinct disorders through opposing genetic effects.

The lateral preoptic (LPO) hypothalamus is a center for NREM and REM sleep induction and NREM sleep homeostasis. Although LPO is needed for NREM sleep, we found that calcium signals were, surprisingly, highest in REM sleep. Furthermore, and equally surprising, NMDA receptors in LPO were the main drivers of excitation. Deleting the NMDA receptor GluN1 subunit from LPO abolished calcium signals in all cells and produced insomnia. Mice of both sexes had highly fragmented NREM sleep-wake patterns and could not generate conventionally classified REM sleep. The sleep phenotype produced by deleting NMDA receptors depended on where in the hypothalamus the receptors were deleted. Deleting receptors from the anterior hypothalamic area (AHA) did not influence sleep-wake states. The sleep fragmentation originated from NMDA receptors on GABA neurons in LPO. Sleep fragmentation could be transiently overcome with sleeping medication (zolpidem) or sedatives (dexmedetomidine; Dex). By contrast, fragmentation persisted under high sleep pressure produced by sleep deprivation (SD), mice had a high propensity to sleep but woke up. By analyzing changes in δ power, sleep homeostasis (also referred to as "sleep drive") remained intact after NMDA receptor ablation. We suggest NMDA glutamate receptor activation stabilizes firing of sleep-on neurons and that mechanisms of sleep maintenance differ from that of the sleep drive itself.

Aging is a complex process that differentially impacts multiple cognitive, sensory, neuronal and molecular processes. Technological innovations now allow for parallel investigation of neuronal circuit function, structure and molecular composition in the brain of awake behaving adult mice. Thus, mice have become a critical tool to better understand how aging impacts the brain. However, a more granular systems-based approach, which considers the impact of age on key features relating to neural processing, is required. Here, we review evidence probing the impact of age on the mouse brain. We focus on a range of processes relating to neuronal function, including cognitive abilities, sensory systems, synaptic plasticity and calcium regulation. Across many systems, we find evidence for prominent age-related dysregulation even before 12 months of age, suggesting that emerging age-related alterations can manifest by late adulthood. However, we also find reports suggesting that some processes are remarkably resilient to aging. The evidence suggests that aging does not drive a parallel, linear dysregulation of all systems, but instead impacts some processes earlier, and more severely, than others. We propose that capturing the more fine-scale emerging features of age-related vulnerability and resilience may provide better opportunities for the rejuvenation of the aged brain.

Aberrant neural oscillations hallmark numerous brain disorders. Here, we first report a method to track the phase of neural oscillations in real-time via endpoint-corrected Hilbert transform (ecHT) that mitigates the characteristic Gibbs distortion. We then used ecHT to show that the aberrant neural oscillation that hallmarks essential tremor (ET) syndrome, the most common adult movement disorder, can be transiently suppressed via transcranial electrical stimulation of the cerebellum phase-locked to the tremor. The tremor suppression is sustained shortly after the end of the stimulation and can be phenomenologically predicted. Finally, we use feature-based statistical-learning and neurophysiological-modelling to show that the suppression of ET is mechanistically attributed to a disruption of the temporal coherence of the aberrant oscillations in the olivocerebellar loop, thus establishing its causal role. The suppression of aberrant neural oscillation via phase-locked driven disruption of temporal coherence may in the future represent a powerful neuromodulatory strategy to treat brain disorders., Aberrant synchronous oscillations have been associated with numerous brain disorders, including essential tremor. The authors show that synchronous cerebellar activity can casually affect essential tremor and that its underlying mechanism may be related to the temporal coherence of the tremulous movement.

Cognitive impairment after traumatic brain injury remains hard to predict. This is partly because axonal injury, which is of fundamental importance, is difficult to measure clinically. Advances in MRI allow axonal injury to be detected after traumatic brain injury, but the most sensitive approach is unclear. Here, we compare the performance of diffusion tensor imaging, neurite orientation dispersion and density-imaging and volumetric measures of brain atrophy in the identification of white-matter abnormalities after traumatic brain injury. Thirty patients with moderate–severe traumatic brain injury in the chronic phase and 20 age-matched controls had T1-weighted and diffusion MRI. Neuropsychological tests of processing speed, executive functioning and memory were used to detect cognitive impairment. Extensive abnormalities in neurite density index and orientation dispersion index were observed, with distinct spatial patterns. Fractional anisotropy and mean diffusivity also indicated widespread abnormalities of white-matter structure. Neurite density index was significantly correlated with processing speed. Slower processing speed was also related to higher mean diffusivity in the corticospinal tracts. Lower white-matter volumes were seen after brain injury with greater effect sizes compared to diffusion metrics; however, volume was not sensitive to changes in cognitive performance. Volume was the most sensitive at detecting change between groups but was not specific for determining relationships with cognition. Abnormalities in fractional anisotropy and mean diffusivity were the most sensitive diffusion measures; however, neurite density index and orientation dispersion index may be more spatially specific. Lower neurite density index may be a useful metric for examining slower processing speed., Graphical Abstract Graphical Abstract, There are various methods to assess white-matter damage after traumatic brain injury, including neurite orientation and dispersion imaging. Bourke et al. found that volumetric differences were the most sensitive to group differences between patients and controls. However, diffusion measures provide greater specificity in relation to cognitive performance after moderate–severe brain injury.

Finding early disease markers using non-invasive and widely available methods is essential to develop a successful therapy for Alzheimer’s Disease. Few studies to date have examined urine, the most readily available biofluid. Here we report the largest study to date using comprehensive metabolic phenotyping platforms (NMR spectroscopy and UHPLC-MS) to probe the urinary metabolome in-depth in people with Alzheimer’s Disease and Mild Cognitive Impairment. Feature reduction was performed using metabolomic Quantitative Trait Loci, resulting in the list of metabolites associated with the genetic variants. This approach helps accuracy in identification of disease states and provides a route to a plausible mechanistic link to pathological processes. Using these mQTLs we built a Random Forests model, which not only correctly discriminates between people with Alzheimer’s Disease and age-matched controls, but also between individuals with Mild Cognitive Impairment who were later diagnosed with Alzheimer’s Disease and those who were not. Further annotation of top-ranking metabolic features nominated by the trained model revealed the involvement of cholesterol-derived metabolites and small-molecules that were linked to Alzheimer’s pathology in previous studies.

Supplemental Digital Content is available in the text., Serum urate has been implicated in hypertension and cardiovascular disease, but it is not known whether it is exerting a causal effect. To investigate this, we performed Mendelian randomization analysis using data from UK Biobank, Million Veterans Program and genome-wide association study consortia, and meta-analysis of randomized controlled trials. The main Mendelian randomization analyses showed that every 1-SD increase in genetically predicted serum urate was associated with an increased risk of coronary heart disease (odds ratio, 1.19 [95% CI, 1.10–1.30]; P=4×10−5), peripheral artery disease (1.12 [95% CI, 1.03–1.21]; P=9×10−3), and stroke (1.11 [95% CI, 1.05–1.18]; P=2×10−4). In Mendelian randomization mediation analyses, elevated blood pressure was estimated to mediate approximately one-third of the effect of urate on cardiovascular disease risk. Systematic review and meta-analysis of randomized controlled trials showed a favorable effect of urate-lowering treatment on systolic blood pressure (mean difference, −2.55 mm Hg [95% CI, −4.06 to −1.05]; P=1×10−3) and major adverse cardiovascular events in those with previous cardiovascular disease (odds ratio, 0.40 [95% CI, 0.22–0.73]; P=3×10−3) but no significant effect on major adverse cardiovascular events in all individuals (odds ratio, 0.67 [95% CI, 0.44–1.03]; P=0.07). In summary, these Mendelian randomization and clinical trial data support an effect of higher serum urate on increasing blood pressure, which may mediate a consequent effect on cardiovascular disease risk. High-quality trials are necessary to provide definitive evidence on the specific clinical contexts where urate lowering may be of cardiovascular benefit.

Brain structure in later life reflects both influences of intrinsic aging and those of lifestyle, environment and disease. We developed a deep neural network model trained on brain MRI scans of healthy people to predict “healthy” brain age. Brain regions most informative for the prediction included the cerebellum, hippocampus, amygdala and insular cortex. We then applied this model to data from an independent group of people not stratified for health. A phenome-wide association analysis of over 1,410 traits in the UK Biobank with differences between the predicted and chronological ages for the second group identified significant associations with over 40 traits including diseases (e.g., type I and type II diabetes), disease risk factors (e.g., increased diastolic blood pressure and body mass index), and poorer cognitive function. These observations highlight relationships between brain and systemic health and have implications for understanding contributions of the latter to late life dementia risk.

The relationship between biomechanics and pathology after brain injury is poorly understood. Using computational modelling, Donat et al. show that mechanical strain immediately after injury predicts the extent of post-traumatic axonal pathology, helping us better understand outcomes following head impacts in humans., The relationship between biomechanical forces and neuropathology is key to understanding traumatic brain injury. White matter tracts are damaged by high shear forces during impact, resulting in axonal injury, a key determinant of long-term clinical outcomes. However, the relationship between biomechanical forces and patterns of white matter injuries, associated with persistent diffusion MRI abnormalities, is poorly understood. This limits the ability to predict the severity of head injuries and the design of appropriate protection. Our previously developed human finite element model of head injury predicted the location of post-traumatic neurodegeneration. A similar rat model now allows us to experimentally test whether strain patterns calculated by the model predicts in vivo MRI and histology changes. Using a controlled cortical impact, mild and moderate injuries (1 and 2 mm) were performed. Focal and axonal injuries were quantified with volumetric and diffusion 9.4 T MRI at 2 weeks post injury. Detailed analysis of the corpus callosum was conducted using multi-shell diffusion MRI and histopathology. Microglia and astrocyte density, including process parameters, along with white matter structural integrity and neurofilament expression were determined by quantitative immunohistochemistry. Linear mixed effects regression analyses for strain and strain rate with the employed outcome measures were used to ascertain how well immediate biomechanics could explain MRI and histology changes. The spatial pattern of mechanical strain and strain rate in the injured cortex shows good agreement with the probability maps of focal lesions derived from volumetric MRI. Diffusion metrics showed abnormalities in the corpus callosum, indicating white matter changes in the segments subjected to high strain, as predicted by the model. The same segments also exhibited a severity-dependent increase in glia cell density, white matter thinning and reduced neurofilament expression. Linear mixed effects regression analyses showed that mechanical strain and strain rate were significant predictors of in vivo MRI and histology changes. Specifically, strain and strain rate respectively explained 33% and 28% of the reduction in fractional anisotropy, 51% and 29% of the change in neurofilament expression and 51% and 30% of microglia density changes. The work provides evidence that strain and strain rate in the first milliseconds after injury are important factors in determining patterns of glial and axonal injury and serve as experimental validators of our computational model of traumatic brain injury. Our results provide support for the use of this model in understanding the relationship of biomechanics and neuropathology and can guide the development of head protection systems, such as airbags and helmets.