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The largest research grant ever given for neurodevelopmental conditions has been awarded by the Innovative Medicines Initiative to an international consortium academically led by the Institute of Psychiatry, Psychology & Neuroscience (IoPPN) at King’s College London.
Quantifying local field potential dynamics with amplitude and frequency stability between ON and OFF medication and stimulation in Parkinson's disease.
Neural oscillations are critical to understanding the synchronisation of neural activities and their relevance to neurological disorders. For instance, the amplitude of beta oscillations in the subthalamic nucleus has gained extensive attention, as it has been found to correlate with medication status and the therapeutic effects of continuous deep brain stimulation in people with Parkinson's disease. However, the frequency stability of subthalamic nucleus beta oscillations, which has been suggested to be associated with dopaminergic information in brain states, has not been well explored. Moreover, the administration of medicine can have inverse effects on changes in frequency and amplitude. In this study, we proposed a method based on the stationary wavelet transform to quantify the amplitude and frequency stability of subthalamic nucleus beta oscillations and evaluated the method using simulation and real data for Parkinson's disease patients. The results suggest that the amplitude and frequency stability quantification has enhanced sensitivity in distinguishing pathological conditions in Parkinson's disease patients. Our quantification shows the benefit of combining frequency stability information with amplitude and provides a new potential feedback signal for adaptive deep brain stimulation.
The effect of sodium-glucose co-transporter 2 inhibitors on outcomes after cardiac resynchronization therapy.
AIMS: The trials upon which recommendations for the use of cardiac resynchronization therapy (CRT) in heart failure used optimal medical therapy (OMT) before sodium-glucose co-transporter 2 inhibitors (SGLT2i). Moreover, the SGLT2i heart failure trials included only a small proportion of participants with CRT, and therefore, it remains uncertain whether SGLT2i should be considered part of OMT prior to CRT. METHODS AND RESULTS: We compared electrocardiogram (ECG) and echocardiographic responses to CRT as well as hospitalization and mortality rates in consecutive patients undergoing implantation at a large tertiary centre between January 2019 to June 2022 with and without SGLT2i treatment. Three hundred seventy-four participants were included aged 74.0 ± 11.5 years (mean ± standard deviation), with a left ventricular ejection fraction (LVEF) of 31.8 ± 9.9% and QRS duration of 161 ± 29 ms. The majority had non-ischaemic cardiomyopathy (58%) and were in NYHA Class II/III (83.6%). These characteristics were similar between patients with (n = 66) and without (n = 308) prior SGLT2i treatment. Both groups demonstrated similar evidence of response to CRT in terms of QRS duration shortening, and improvements in LVEF, left ventricular end-diastolic inner-dimension (LVIDd) and diastolic function (E/A and e/e'). While there was no difference in rates of hospitalization (for heart failure or overall), mortality was significantly lower in patients treated with SGLT2i compared with those who were not (6.5 vs. 16.6%, P = 0.049). CONCLUSIONS: We observed an improvement in mortality in patients undergoing CRT prescribed SGLT2i compared with those not prescribed SGLT2i, despite similar degrees of reverse remodelling. The authors recommend starting SGLT2i prior to CRT implantation, where it does not delay implantation.
Structural and Cognitive Mechanisms of Group Cohesion in Primates.
Group-living creates stresses that, all else equal, naturally lead to group fragmentation, and hence loss of the benefits that group-living provides. How species that live in large stable groups counteract these forces is not well understood. I use comparative data on grooming networks and cognitive abilities in primates to show that living in large, stable groups has involved a series of structural solutions designed to create chains of 'friendship' (friends-of-friends effects), increased investment in bonding behaviours (made possible by dietary adjustments) to ensure that coalitions work effectively, and neuronally expensive cognitive skills of the kind known to underpin social relationships in humans. The first ensures that individuals synchronise their activity cycles; the second allows the stresses created by group-living to be defused; and the third allows a large number of weak ties to be managed. Between them, these create a form of multilevel sociality based on strong versus weak ties similar to that found in human social networks. In primates, these strategies appear successively at quite specific group sizes, suggesting that they are solutions to 'glass ceilings' that would otherwise limit the range of group sizes that animals can live in (and hence the habitats they can occupy). This sequence maps closely onto the grades now known to underpin the Social Brain Hypothesis and the fractal pattern that is known to optimise information flow round networks.
Higher-order thalamocortical circuits are specified by embryonic cortical progenitor types in the mouse brain.
The sensory cortex receives synaptic inputs from both first-order and higher-order thalamic nuclei. First-order inputs relay simple stimulus properties from the periphery, whereas higher-order inputs relay more complex response properties, provide contextual feedback, and modulate plasticity. Here, we reveal that a cortical neuron's higher-order input is determined by the type of progenitor from which it is derived during embryonic development. Within layer 4 (L4) of the mouse primary somatosensory cortex, neurons derived from intermediate progenitors receive stronger higher-order thalamic input and exhibit greater higher-order sensory responses. These effects result from differences in dendritic morphology and levels of the transcription factor Lhx2, which are specified by the L4 neuron's progenitor type. When this mechanism is disrupted, cortical circuits exhibit altered higher-order responses and sensory-evoked plasticity. Therefore, by following distinct trajectories, progenitor types generate diversity in thalamocortical circuitry and may provide a general mechanism for differentially routing information through the cortex.
Association of symptom severity and cerebrospinal fluid alterations in recent onset psychosis in schizophrenia-spectrum disorders - An individual patient data meta-analysis.
Neuroinflammation and blood-cerebrospinal fluid barrier (BCB) disruption could be key elements in schizophrenia-spectrum disorderś(SSDs) etiology and symptom modulation. We present the largest two-stage individual patient data (IPD) meta-analysis, investigating the association of BCB disruption and cerebrospinal fluid (CSF) alterations with symptom severity in first-episode psychosis (FEP) and recent onset psychotic disorder (ROP) individuals, with a focus on sex-related differences. Data was collected from PubMed and EMBASE databases. FEP, ROP and high-risk syndromes for psychosis IPD were included if routine basic CSF-diagnostics were reported. Risk of bias of the included studies was evaluated. Random-effects meta-analyses and mixed-effects linear regression models were employed to assess the impact of BCB alterations on symptom severity. Published (6 studies) and unpublished IPD from n = 531 individuals was included in the analyses. CSF was altered in 38.8 % of individuals. No significant differences in symptom severity were found between individuals with and without CSF alterations (SMD = -0.17, 95 %CI -0.55-0.22, p = 0.341). However, males with elevated CSF/serum albumin ratios or any CSF alteration had significantly higher positive symptom scores than those without alterations (SMD = 0.34, 95 %CI 0.05-0.64, p = 0.037 and SMD = 0.29, 95 %CI 0.17-0.41p = 0.005, respectively). Mixed-effects and simple regression models showed no association (p > 0.1) between CSF parameters and symptomatic outcomes. No interaction between sex and CSF parameters was found (p > 0.1). BCB disruption appears highly prevalent in early psychosis and could be involved in positive symptomś severity in males, indicating potential difficult-to-treat states. This work highlights the need for considering BCB breakdownand sex-related differences in SSDs clinical trials and treatment strategies.
Redefining Diabetic Cardiomyopathy: Perturbations in Substrate Metabolism at the Heart of its Pathology.
Cardiovascular disease represents the leading cause of death in people with diabetes, most notably from macrovascular diseases such as myocardial infarction or heart failure. Diabetes also increases the risk of a specific form of cardiomyopathy referred to as diabetic cardiomyopathy (DbCM), originally defined as ventricular dysfunction in the absence of underlying coronary artery disease and/or hypertension. Herein, we provide an overview on the key mediators of DbCM, with an emphasis on the role for perturbations in cardiac substrate metabolism. We discuss key mechanisms regulating metabolic dysfunction in DbCM, with additional focus on the role of metabolites as signalling molecules within the diabetic heart. Furthermore, we discuss the preclinical approaches to target these perturbations to alleviate DbCM. With several advancements in our understanding, we propose "diastolic dysfunction in the presence of altered myocardial metabolism in a person with diabetes, but absence of other known causes of cardiomyopathy and/or hypertension", as a new definition for, or approach to classify, DbCM. However, we recognize that no definition can fully explain the complexity of why some individuals with DbCM exhibit diastolic dysfunction, whereas others develop systolic dysfunction. Due to DbCM sharing pathological features with heart failure with preserved ejection fraction (HFpEF), the latter of which is more prevalent in the diabetic population, it is imperative to determine whether effective management of DbCM decreases HFpEF prevalence.
From dawn till dusk: Time-adaptive bayesian optimization for neurostimulation.
Stimulation optimization has garnered considerable interest in recent years in order to efficiently parametrize neuromodulation-based therapies. To date, efforts focused on automatically identifying settings from parameter spaces that do not change over time. A limitation of these approaches, however, is that they lack consideration for time dependent factors that may influence therapy outcomes. Disease progression and biological rhythmicity are two sources of variation that may influence optimal stimulation settings over time. To account for this, we present a novel time-varying Bayesian optimization (TV-BayesOpt) for tracking the optimum parameter set for neuromodulation therapy. We evaluate the performance of TV-BayesOpt for tracking gradual and periodic slow variations over time. The algorithm was investigated within the context of a computational model of phase-locked deep brain stimulation for treating oscillopathies representative of common movement disorders such as Parkinson's disease and Essential Tremor. When the optimal stimulation settings changed due to gradual and periodic sources, TV-BayesOpt outperformed standard time-invariant techniques and was able to identify the appropriate stimulation setting. Through incorporation of both a gradual "forgetting" and periodic covariance functions, the algorithm maintained robust performance when a priori knowledge differed from observed variations. This algorithm presents a broad framework that can be leveraged for the treatment of a range of neurological and psychiatric conditions and can be used to track variations in optimal stimulation settings such as amplitude, pulse-width, frequency and phase for invasive and non-invasive neuromodulation strategies.
MorpheusNet: Resource efficient sleep stage classifier for embedded on-line systems.
Sleep Stage Classification (SSC) is a labor-intensive task, requiring experts to examine hours of electrophysiological recordings for manual classification. This is a limiting factor when it comes to leveraging sleep stages for therapeutic purposes. With increasing affordability and expansion of wearable devices, automating SSC may enable deployment of sleep-based therapies at scale. Deep Learning has gained increasing attention as a potential method to automate this process. Previous research has shown accuracy comparable to manual expert scores. However, previous approaches require sizable amount of memory and computational resources. This constrains the ability to classify in real time and deploy models on the edge. To address this gap, we aim to provide a model capable of predicting sleep stages in real-time, without requiring access to external computational sources (e.g., mobile phone, cloud). The algorithm is power efficient to enable use on embedded battery powered systems. Our compact sleep stage classifier can be deployed on most off-the-shelf microcontrollers (MCU) with constrained hardware settings. This is due to the memory footprint of our approach requiring significantly fewer operations. The model was tested on three publicly available data bases and achieved performance comparable to the state of the art, whilst reducing model complexity by orders of magnitude (up to 280 times smaller compared to state of the art). We further optimized the model with quantization of parameters to 8 bits with only an average drop of 0.95% in accuracy. When implemented in firmware, the quantized model achieves a latency of 1.6 seconds on an Arm Cortex-M4 processor, allowing its use for on-line SSC-based therapies.
Genome-wide analysis in over 1 million individuals of European ancestry yields improved polygenic risk scores for blood pressure traits.
Hypertension affects more than one billion people worldwide. Here we identify 113 novel loci, reporting a total of 2,103 independent genetic signals (P
Social and environmental transmission spread different sets of gut microbes in wild mice.
Gut microbes shape many aspects of organismal biology, yet how these key bacteria transmit among hosts in natural populations remains poorly understood. Recent work in mammals has emphasized either transmission through social contacts or indirect transmission through environmental contact, but the relative importance of different routes has not been directly assessed. Here we used a novel radio-frequency identification-based tracking system to collect long-term high-resolution data on social relationships, space use and microhabitat in a wild population of mice (Apodemus sylvaticus), while regularly characterizing their gut microbiota with 16S ribosomal RNA profiling. Through probabilistic modelling of the resulting data, we identify positive and statistically distinct signals of social and environmental transmission, captured by social networks and overlap in home ranges, respectively. Strikingly, microorganisms with distinct biological attributes drove these different transmission signals. While the social network effect on microbiota was driven by anaerobic bacteria, the effect of shared space was most influenced by aerotolerant spore-forming bacteria. These findings support the prediction that social contact is important for the transfer of microorganisms with low oxygen tolerance, while those that can tolerate oxygen or form spores may be able to transmit indirectly through the environment. Overall, these results suggest social and environmental transmission routes can spread biologically distinct members of the mammalian gut microbiota.
Developing psychological treatments for psychosis.
Evidence shows that talking with patients about psychotic experiences can be beneficial. The key question is therefore: which psychological methods can help patients most? This editorial presents ten principles for the design and development of effective psychological treatments. These principles are perceptible characteristics of successful interventions.
Opaque Ontology: Neuroimaging Classification of ICD-10 Diagnostic Groups in the UK Biobank.
BACKGROUND: The use of machine learning to classify diagnostic cases versus controls defined based on diagnostic ontologies such as the ICD-10 from neuroimaging features is now commonplace across a wide range of diagnostic fields. However, transdiagnostic comparisons of such classifications are lacking. Such transdiagnostic comparisons are important to establish the specificity of classification models, set benchmarks, and assess the value of diagnostic ontologies. RESULTS: We investigated case-control classification accuracy in 17 different ICD-10 diagnostic groups from Chapter V (mental and behavioral disorders) and Chapter VI (diseases of the nervous system) using data from the UK Biobank. Classification models were trained using either neuroimaging (structural or functional brain MRI feature sets) or socio-demographic features. Random forest classification models were adopted using rigorous shuffle splits to estimate stability as well as accuracy of case-control classifications. Diagnostic classification accuracies were benchmarked against age classification (oldest versus youngest) from the same feature sets and against additional classifier types (K-nearest neighbors and linear support vector machine). In contrast to age classification accuracy, which was high for all feature sets, few ICD-10 diagnostic groups were classified significantly above chance (namely, demyelinating diseases based on structural neuroimaging features, and depression based on socio-demographic and functional neuroimaging features). CONCLUSION: These findings highlight challenges with the current disease classification system, leading us to recommend caution with the use of ICD-10 diagnostic groups as target labels in brain-based disease prediction studies.
Epistasis, core-genome disharmony, and adaptation in recombining bacteria.
Recombination of short DNA fragments via horizontal gene transfer (HGT) can introduce beneficial alleles, create genomic disharmony through negative epistasis, and create adaptive gene combinations through positive epistasis. For non-core (accessory) genes, the negative epistatic cost is likely to be minimal because the incoming genes have not co-evolved with the recipient genome and are frequently observed as tightly linked cassettes with major effects. By contrast, interspecific recombination in the core genome is expected to be rare because disruptive allelic replacement is likely to introduce negative epistasis. Why then is homologous recombination common in the core of bacterial genomes? To understand this enigma, we take advantage of an exceptional model system, the common enteric pathogens Campylobacter jejuni and C. coli that are known for very high magnitude interspecies gene flow in the core genome. As expected, HGT does indeed disrupt co-adapted allele pairings, indirect evidence of negative epistasis. However, multiple HGT events enable recovery of the genome's co-adaption between introgressing alleles, even in core metabolism genes (e.g., formate dehydrogenase). These findings demonstrate that, even for complex traits, genetic coalitions can be decoupled, transferred, and independently reinstated in a new genetic background-facilitating transition between fitness peaks. In this example, the two-step recombinational process is associated with C. coli that are adapted to the agricultural niche.IMPORTANCEGenetic exchange among bacteria shapes the microbial world. From the acquisition of antimicrobial resistance genes to fundamental questions about the nature of bacterial species, this powerful evolutionary force has preoccupied scientists for decades. However, the mixing of genes between species rests on a paradox: 0n one hand, promoting adaptation by conferring novel functionality; on the other, potentially introducing disharmonious gene combinations (negative epistasis) that will be selected against. Taking an interdisciplinary approach to analyze natural populations of the enteric bacteria Campylobacter, an ideal example of long-range admixture, we demonstrate that genes can independently transfer across species boundaries and rejoin in functional networks in a recipient genome. The positive impact of two-gene interactions appears to be adaptive by expanding metabolic capacity and facilitating niche shifts through interspecific hybridization. This challenges conventional ideas and highlights the possibility of multiple-step evolution of multi-gene traits by interspecific introgression.
Molecular mechanism of complement inhibition by the trypanosome receptor ISG65.
African trypanosomes replicate within infected mammals where they are exposed to the complement system. This system centres around complement C3, which is present in a soluble form in serum but becomes covalently deposited onto the surfaces of pathogens after proteolytic cleavage to C3b. Membrane-associated C3b triggers different complement-mediated effectors which promote pathogen clearance. To counter complement-mediated clearance, African trypanosomes have a cell surface receptor, ISG65, which binds to C3b and which decreases the rate of trypanosome clearance in an infection model. However, the mechanism by which ISG65 reduces C3b function has not been determined. We reveal through cryogenic electron microscopy that ISG65 has two distinct binding sites for C3b, only one of which is available in C3 and C3d. We show that ISG65 does not block the formation of C3b or the function of the C3 convertase which catalyses the surface deposition of C3b. However, we show that ISG65 forms a specific conjugate with C3b, perhaps acting as a decoy. ISG65 also occludes the binding sites for complement receptors 2 and 3, which may disrupt recruitment of immune cells, including B cells, phagocytes, and granulocytes. This suggests that ISG65 protects trypanosomes by combining multiple approaches to dampen the complement cascade.
Test-Retest Reproducibility of Reduced-Field-of-View Density-Weighted CRT MRSI at 3T.
Quantifying an imaging modality's ability to reproduce results is important for establishing its utility. In magnetic resonance spectroscopic imaging (MRSI), new acquisition protocols are regularly introduced which improve upon their precursors with respect to signal-to-noise ratio (SNR), total acquisition duration, and nominal voxel resolution. This study has quantified the within-subject and between-subject reproducibility of one such new protocol (reduced-field-of-view density-weighted concentric ring trajectory (rFOV-DW-CRT) MRSI) by calculating the coefficient of variance of data acquired from a test-retest experiment. The posterior cingulate cortex (PCC) and the right superior corona radiata (SCR) were selected as the regions of interest (ROIs) for grey matter (GM) and white matter (WM), respectively. CVs for between-subject and within-subject were consistently around or below 15% for Glx, tCho, and Myo-Ins, and below 5% for tNAA and tCr.