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Over one third of the estimated 3 million people with epilepsy in the United States are medication resistant. Responsive neurostimulation from chronically implanted electrodes provides a promising treatment alternative to resective surgery. However, determining optimal personalized stimulation parameters, including when and where to intervene to guarantee a positive patient outcome, is a major open challenge.Network neuroscience and control theory offer useful tools that may guide improvements in parameter selection for control of anomalous neural activity. Here we use a method to characterize dynamic controllability across consecutive effective connectivity (EC) networks based on regularized partial correlations between implanted electrodes during the onset, propagation, and termination regimes of 34 seizures. We estimate regularized partial correlation adjacency matrices from 1-s time windows of intracranial electrocorticography recordings using the Graphical Least Absolute Shrinkage and Selection Operator (GLASSO). Average and modal controllability metrics calculated from each resulting EC network track the time-varying controllability of the brain on an evolving landscape of conditionally dependent network interactions. We show that average controllability increases throughout a seizure and is negatively correlated with modal controllability throughout. Our results support the hypothesis that the energy required to drive the brain to a seizure-free state from an ictal state is smallest during seizure onset, yet we find that applying control energy at electrodes in the seizure onset zone may not always be energetically favorable. Our work suggests that a low-complexity model of time-evolving controllability may offer insights for developing and improving control strategies targeting seizure suppression.

A 66-year-old woman reported 10 days of generalised weakness, falls and memory ‘glitches’. She had developed left-sided ophthalmic herpes zoster 3 months before but was otherwise well. MR scan of brain showed acute left-sided ischaemic strokes and CT cerebral angiogram identified marked stenoses of the left anterior and middle cerebral arteries. We suspected varicella-zoster virus vasculopathy, confirmed by cerebrospinal fluid analysis. Initially she had further ischaemic strokes despite intravenous acyclovir, prednisone, aspirin and clopidogrel. However, after prolonged acyclovir and prednisone, there were no new infarcts though imaging of left anterior and middle cerebral artery vessel walls showed persistent inflammation. Varicella zoster vasculopathy can cause recurrent ischaemic strokes, even in immunocompetent people with no cardiovascular risk factors, and despite long-term antiviral therapy.

Pierre Guermonprez and colleagues have worked out how a subset of dendritic cells expands in individuals with severe malaria. Plasmodium infection causes an accumulation of xanthine in infected red blood cells. The researchers found that type I interferon triggers an increase in the enzyme that metabolizes xanthine to uric acid. Uric acid then acts on mast cells to release Flt3 ligand, an important regulator of dendritic cells, which in turn stimulate T cells to respond to the infection. Innate sensing mechanisms trigger a variety of humoral and cellular events that are essential to adaptive immune responses. Here we describe an innate sensing pathway triggered by Plasmodium infection that regulates dendritic cell homeostasis and adaptive immunity through Flt3 ligand (Flt3l) release. Plasmodium- induced Flt3l release in mice requires Toll-like receptor (TLR) activation and type I interferon (IFN) production. We found that type I IFN supports the upregulation of xanthine dehydrogenase, which metabolizes the xanthine accumulating in infected erythrocytes to uric acid. Uric acid crystals trigger mast cells to release soluble Flt3l from a pre-synthesized membrane-associated precursor. During infection, Flt3l preferentially stimulates expansion of the CD8-α + dendritic cell subset or its BDCA3 + human dendritic cell equivalent and has a substantial impact on the magnitude of T cell activation, mostly in the CD8 + compartment. Our findings highlight a new mechanism that regulates dendritic cell homeostasis and T cell responses to infection.

Network neuroscience applied to epilepsy holds promise to map pathological networks, localize seizure generators, and inform targeted interventions to control seizures. However, incomplete sampling of the epileptic brain because of sparse placement of intracranial electrodes may affect model results. In this study, we evaluate the sensitivity of several published network measures to incomplete spatial sampling and propose an algorithm using network subsampling to determine confidence in model results. We retrospectively evaluated intracranial EEG data from 28 patients implanted with grid, strip, and depth electrodes during evaluation for epilepsy surgery. We recalculated global and local network metrics after randomly and systematically removing subsets of intracranial EEG electrode contacts. We found that sensitivity to incomplete sampling varied significantly across network metrics. This sensitivity was largely independent of whether seizure onset zone contacts were targeted or spared from removal. We present an algorithm using random subsampling to compute patient-specific confidence intervals for network localizations. Our findings highlight the difference in robustness between commonly used network metrics and provide tools to assess confidence in intracranial network localization. We present these techniques as an important step toward translating personalized network models of seizures into rigorous, quantitative approaches to invasive therapy. Network neuroscience applied to epileptic brains seeks to identify pathological neural connections that promote and maintain seizures, and holds promise to guide surgical planning in patients with intractable epilepsy. However, sampling of the epileptic network in intracranial EEG recording is limited by the choice of where to place intracranial electrodes, which is highly variable within and between epilepsy centers. The effect of incomplete spatial sampling generated by sparse electrode placement on network statistics is unknown. Here, we determine the sensitivity of several network statistics to incomplete spatial sampling, and we propose a method using electrode subsampling to determine patient-specific confidence intervals in network model predictions.

Over one third of the estimated 3 million people with epilepsy in the US are medication resistant. Responsive neurostimulation from chronically implanted electrodes provides a promising treatment option and alternative to resective surgery. However, determining personalized optimal stimulation parameters, including when and where to intervene to guarantee a positive patient outcome, is a major open challenge. Network neuroscience and control theory offer useful tools that may guide improvements in parameter selection for control of anomalous neural activity. Here we use a novel method to characterize dynamic controllability across consecutive effective connectivity (EC) networks based on regularized partial correlations between implanted electrodes during the onset, propagation, and termination phases of thirty-four seizures. We estimate regularized partial correlation adjacency matrices from one-second time windows of intracranial electrocorticography recordings using the Graphical Least Absolute Shrinkage and Selection Operator (GLASSO). Average and modal controllability metrics calculated from each resulting EC network track the time-varying controllability of the brain on an evolving landscape of conditionally dependent network interactions. We show that average controllability increases throughout a seizure and is negatively correlated with modal controllability throughout. Furthermore, our results support the hypothesis that the energy required to drive the brain to a seizure-free state from an ictal state is smallest during seizure onset; yet, we find that applying control energy at electrodes in the seizure onset zone may not always be energetically favorable. Our work suggests that a low-complexity model of time-evolving controllability may offer new insights for developing and improving control strategies targeting seizure suppression.

How does the human brain's structural scaffold give rise to its intricate functional dynamics? This is a central challenge in translational neuroscience, particularly in epilepsy, a disorder that affects over 50 million people worldwide. Treatment for medication-resistant focal epilepsy is often structural - through surgery, devices or focal laser ablation - but structural targets, particularly in patients without clear lesions, are largely based on functional mapping via intracranial EEG (iEEG). Unfortunately, the relationship between structural and functional connectivity in the seizing brain is poorly understood. In this study, we quantify structure-function coupling, specifically between white matter connections and iEEG, across preictal and ictal periods in 45 seizures from 9 patients with unilateral drug-resistant focal epilepsy. We use High Angular Resolution Diffusion Imaging (HARDI) tractography to construct structural connectivity networks and correlate these networks with time-varying broadband and frequency-specific functional networks derived from coregistered iEEG. Across all frequency bands, we find significant increases in structure-function coupling from preictal to ictal periods. We demonstrate that short-range structural connections are primarily responsible for this increase in coupling. Finally, we find that spatiotemporal patterns of structure-function coupling are stereotyped, and a function of each patient's individual anatomy. These results suggest that seizures harness the underlying structural connectome as they propagate. Our findings suggest that the relationship between structural and functional connectivity in epilepsy may inform current and new therapies to map and alter seizure spread, and pave the way for better-targeted, patient-specific interventions.

Focal epilepsy is a clinical condition arising from disordered brain networks. Network models hold promise to map these networks, localize seizure generators, and inform targeted interventions to control seizures. However, incomplete sampling of epileptic brain due to sparse placement of intracranial electrodes may profoundly affect model results. In this study, we evaluate the robustness of several published network measures applied to intracranial electrode recordings and propose an algorithm, using network resampling, to determine confidence in model results. We retrospectively subsampled intracranial EEG data from 28 patients who were implanted with grid, strip, and depth electrodes during evaluation for epilepsy surgery. We recalculated global and local network metrics after both randomly and systematically resampling subsets of intracranial EEG electrode contacts. We found that sensitivity to incomplete sampling varied significantly across network metrics, and that this sensitivity was independent of the distance of removed contacts from the seizure onset zone. We present an algorithm, using random resampling, to compute patient-specific confidence intervals for network localizations on both global and nodal network statistics. Our findings highlight the difference in robustness between commonly used network metrics and provide tools to assess confidence in intracranial network localization. We present these techniques as an important step toward assessing the accuracy of intracranial electrode implants and translating personalized network models of seizures into rigorous, quantitative approaches to invasive therapy.

Regulatory T cells (Tregs) hold promise for treating autoimmune disease and transplant rejection, yet generation of autologous products for adoptive transfer can suffer donor variability and slow turnaround, limiting their use in urgent indications. We therefore examine whether allogeneic, pre-manufactured (‘off-the-shelf’) Tregs could overcome these barriers. In a human skin-xenograft model, HLA-mismatched Tregs are swiftly eliminated by recipient CD8 + T cells and fail to protect grafts. Stringent matching of HLA class I and II restores efficacy but is clinically impractical. Using non-viral CRISPR editing we disrupt B2M and CIITA while inserting an HLA-E- B2M fusion, generating hypo-immunogenic Tregs that evade both T and NK cell attack. Engineered cells retain FOXP3 stability and potent in vitro suppression, and after a single low-dose infusion, prolong human skin graft survival in a humanized mouse model comparably to autologous Tregs. Histology and spatial transcriptomics reveal minimal cytotoxic infiltration and enrichment of immunoregulatory and tissue-repair programmes. Multiplex HLA engineering thus enables ready-to-use allogeneic Tregs that withstand host immune attack for adoptive transfer. Adoptive regulatory T cell (Treg) therapy holds promise for the treatment of a range of immunopathological conditions. Here the authors explore the HLA engineering of allogenic Treg products that avoid T cell and NK cell attack and maintain immunomodulatory function in a human skin-xenograft model.

Background Hand fractures are common and sometimes require surgery to restore function. Placement of Kirschner wires (K-wires) is the most common form of surgical fixation. After placement, a key decision is whether to bury the end of a K-wire or leave it protruding from the skin (exposed). A recent systematic review found no evidence to support either approach and a national clinician and surgeon survey demonstrated further uncertainty. We aim to determine the design of a definitive randomised controlled trial assessing the cost and clinical effectiveness of buried versus exposed Kirschner wires for adults with metacarpal or phalangeal fractures. Methods We will employ three methodologies: a national service evaluation of current clinical practice, patient and surgeon focus groups and a consensus meeting to finalise the protocol for a randomised controlled trial. For the service evaluation, all outcomes will be summarised using descriptive statistics overall and split by group (buried versus exposed K-wires). Information collected in the patient focus groups will be analysed thematically. The surgeon consensus meeting will address each part of the design in turn and through discussion agree a final protocol. Discussion The study may be monitored, or audited in accordance with the current approved protocol, Good Clinical Practice (GCP), relevant regulations and standard operating procedures. The Chief Investigator will submit and, where necessary, obtain approval from the above parties for all substantial amendments to the original approved documents. A feasibility study report will be published by the Wire Study Steering committee. Additional members of the steering group and citable collaborators will be listed within the manuscript and their roles identified.

A previously healthy 44-year-old Caucasian man presented with recurrent syncope and was found to have a complete heart block with a ventricular rate of 24 bpm. No biochemical abnormalities were identified. Tick borne illnesses were ruled out. Paced echocardiogram revealed left ventricular systolic dysfunction with septal hypokinesis. Chest radiography and subsequent CT scan did not reveal adenopathy. However, a positron emission tomography scan demonstrated increased fluorodeoxyglucose uptake in the spleen, a right retro-clavicular lymph node, right ventricle and the interventricular septum of the heart. Excision biopsy of the retro-clavicular lymph node revealed non-caseating granulomas consistent with sarcoidosis. Complete heart block persisted despite steroid treatment. A pacemaker/biventricular implantable cardioverter defibrillator was placed for complete heart block and primary prevention of ventricular tachycardia and sudden cardiac death.