Glutamate acts on acid-sensing ion channels to worsen ischaemic brain injury.

Glutamate is traditionally viewed as the first messenger to activate NMDAR (N-methyl-D-aspartate receptor)-dependent cell death pathways in stroke1,2, but unsuccessful clinical trials with NMDAR antagonists implicate the engagement of other mechanisms3-7. Here we show that glutamate and its structural analogues, including NMDAR antagonist L-AP5 (also known as APV), robustly potentiate currents mediated by acid-sensing ion channels (ASICs) associated with acidosis-induced neurotoxicity in stroke4. Glutamate increases the affinity of ASICs for protons and their open probability, aggravating ischaemic neurotoxicity in both in vitro and in vivo models. Site-directed mutagenesis, structure-based modelling and functional assays reveal a bona fide glutamate-binding cavity in the extracellular domain of ASIC1a. Computational drug screening identified a small molecule, LK-2, that binds to this cavity and abolishes glutamate-dependent potentiation of ASIC currents but spares NMDARs. LK-2 reduces the infarct volume and improves sensorimotor recovery in a mouse model of ischaemic stroke, reminiscent of that seen in mice with Asic1a knockout or knockout of other cation channels4-7. We conclude that glutamate functions as a positive allosteric modulator for ASICs to exacerbate neurotoxicity, and preferential targeting of the glutamate-binding site on ASICs over that on NMDARs may be strategized for developing stroke therapeutics lacking the psychotic side effects of NMDAR antagonists.

Selective Vulnerability of GABAergic Inhibitory Interneurons to Bilirubin Neurotoxicity in the Neonatal Brain.

Hyperbilirubinemia (HB) is a key risk factor for hearing loss in neonates, particularly premature infants. Here we report that bilirubin (BIL)-dependent cell death in auditory brainstem of neonatal mice of both sexes is significantly attenuated by ZD7288, a blocker for hyperpolarization-activated cyclic nucleotide-gated (HCN) channel mediated current (Ih), or by genetic deletion of HCN1. GABAergic inhibitory interneurons predominantly express HCN1, on which BIL selectively acts to increase their intrinsic excitability and mortality by enhancing HCN1 activity and Ca2+-dependent membrane targeting. Chronic BIL elevation in neonatal mice in vivo increases the fraction of spontaneously active interneurons and their firing frequency, Ih and death, compromising audition at young adult stage in HCN1+/+, but not in HCN1-/- genotype. We conclude that HB preferentially targets HCN1 to injure inhibitory interneurons, fueling a feedforward loop in which lessening inhibition cascades hyperexcitability, Ca2+ overload, neuronal death and auditory impairments. These findings rationalize HCN1 as a potential target for managing HB encephalopathy.Significance Statement This study demonstrated that bilirubin preferentially targets GABAergic interneurons where it facilitates not only gating of HCN1 channels but also targeting of intracellular HCN1 to plasma membrane in calcium-dependent manner, resulting in neuronal hyperexcitability, injury and sensory dysfunction. These findings implicate HCN1 channel not only as a potential driver for auditory abnormalities in neonatal patients with bilirubin encephalopathy, but also potential intervention target for clinical management of neurological impairments associated with severe jaundice. Selective vulnerability of interneurons to neurotoxicity may be of general significance for understanding other forms of brain injury.

neuromaps: structural and functional interpretation of brain maps.

Imaging technologies are increasingly used to generate high-resolution reference maps of brain structure and function. Comparing experimentally generated maps to these reference maps facilitates cross-disciplinary scientific discovery. Although recent data sharing initiatives increase the accessibility of brain maps, data are often shared in disparate coordinate systems, precluding systematic and accurate comparisons. Here we introduce neuromaps, a toolbox for accessing, transforming and analyzing structural and functional brain annotations. We implement functionalities for generating high-quality transformations between four standard coordinate systems. The toolbox includes curated reference maps and biological ontologies of the human brain, such as molecular, microstructural, electrophysiological, developmental and functional ontologies. Robust quantitative assessment of map-to-map similarity is enabled via a suite of spatial autocorrelation-preserving null models. neuromaps combines open-access data with transparent functionality for standardizing and comparing brain maps, providing a systematic workflow for comprehensive structural and functional annotation enrichment analysis of the human brain.

Structural white matter properties and cognitive resilience to tau pathology.

INTRODUCTION: We assessed whether macro- and/or micro-structural white matter properties are associated with cognitive resilience to Alzheimer's disease pathology years prior to clinical onset. METHODS: We examined whether global efficiency, an indicator of communication efficiency in brain networks, and diffusion measurements within the limbic network and default mode network moderate the association between amyloid-ß/tau pathology and cognitive decline. We also investigated whether demographic and health/risk factors are associated with white matter properties. RESULTS: Higher global efficiency of the limbic network, as well as free-water corrected diffusion measures within the tracts of both networks, attenuated the impact of tau pathology on memory decline. Education, age, sex, white matter hyperintensities, and vascular risk factors were associated with white matter properties of both networks. DISCUSSION: White matter can influence cognitive resilience against tau pathology, and promoting education and vascular health may enhance optimal white matter properties. HIGHLIGHTS: Aß and tau were associated with longitudinal memory change over ∼7.5 years. White matter properties attenuated the impact of tau pathology on memory change. Health/risk factors were associated with white matter properties.

Spatially heterogeneous structure-function coupling in haemodynamic and electromagnetic brain networks.

The relationship between structural and functional connectivity in the brain is a key question in connectomics. Here we quantify patterns of structure-function coupling across the neocortex, by comparing structural connectivity estimated using diffusion MRI with functional connectivity estimated using both neurophysiological (MEG-based) and haemodynamic (fMRI-based) recordings. We find that structure-function coupling is heterogeneous across brain regions and frequency bands. The link between structural and functional connectivity is generally stronger in multiple MEG frequency bands compared to resting state fMRI. Structure-function coupling is greater in slower and intermediate frequency bands compared to faster frequency bands. We also find that structure-function coupling systematically follows the archetypal sensorimotor-association hierarchy, as well as patterns of laminar differentiation, peaking in granular layer IV. Finally, structure-function coupling is better explained using structure-informed inter-regional communication metrics than using structural connectivity alone. Collectively, these results place neurophysiological and haemodynamic structure-function relationships in a common frame of reference and provide a starting point for a multi-modal understanding of structure-function coupling in the brain.

Differentially targeted seeding reveals unique pathological alpha-synuclein propagation patterns.

Parkinson's disease is a progressive neurodegenerative disorder characterized by the intracellular accumulation of insoluble alpha-synuclein aggregates into Lewy bodies and neurites. Increasing evidence indicates that Parkinson's disease progression results from the spread of pathologic alpha-synuclein through neuronal networks. However, the exact mechanisms underlying the propagation of abnormal proteins in the brain are only partially understood. The objective of this study was first to describe the long-term spatiotemporal distributions of Lewy-related pathology in mice injected with alpha-synuclein preformed fibrils and then to recreate these patterns using a computational model that simulates in silico the spread of pathologic alpha-synuclein. In this study, 87 2-3-month-old non-transgenic mice were injected with alpha-synuclein preformed fibrils to generate a comprehensive post-mortem dataset representing the long-term spatiotemporal distributions of hyperphosphorylated alpha-synuclein, an established marker of Lewy pathology, across the 426 regions of the Allen Mouse Brain Atlas. The mice were injected into either the caudoputamen, nucleus accumbens or hippocampus, and followed over 24 months with pathologic alpha-synuclein quantified at seven intermediate time points. The pathologic patterns observed at each time point in this high-resolution dataset were then compared to those generated using a Susceptible-Infected-Removed (SIR) computational model, an agent-based model that simulates the spread of pathologic alpha-synuclein for every brain region taking simultaneously into account the effect of regional brain connectivity and Snca gene expression. Our histopathological findings showed that differentially targeted seeding of pathological alpha-synuclein resulted in unique propagation patterns over 24 months and that most brain regions were permissive to pathology. We found that the SIR model recreated the observed distributions of pathology over 24 months for each injection site. Null models showed that both Snca gene expression and connectivity had a significant influence on model fit. In sum, our study demonstrates that the combination of normal alpha-synuclein concentration and brain connectomics contributes to making brain regions more vulnerable to the pathological process, providing support for a prion-like spread of pathologic alpha-synuclein. We propose that this rich dataset and the related computational model will help test new hypotheses regarding mechanisms that may alter the spread of pathologic alpha-synuclein in the brain.

Tough photoluminescent hydrogels doped with lanthanide.

Photoluminescent hydrogels have emerged as novel soft materials with potential applications in many fields. Although many photoluminescent hydrogels have been fabricated, their scope of usage has been severely limited by their poor mechanical performance. Here, a facile strategy is reported for preparing lanthanide (Ln)-alginate/polyacrylamide (PAAm) hydrogels with both high toughness and photoluminescence, which has been achieved by doping Ln(3+) ions (Ln = Eu, Tb, Eu/Tb) into alginate/PAAm hydrogel networks, where Ln(3+) ions serve as both photoluminescent emitters and physical cross-linkers. The resulting hydrogels exhibit versatile advantages including excellent mechanical properties (∼ MPa strength, ≈ 20 tensile strains, ≈ 10(4) kJ m(-3) energy dissipation), good photoluminescent performance, tunable emission color, excellent processability, and cytocompatibility. The developed tough photoluminescent hydrogels hold great promises for expanding the usage scope of hydrogels.

Systematic evaluation of fMRI data-processing pipelines for consistent functional connectomics.

Functional interactions between brain regions can be viewed as a network, enabling neuroscientists to investigate brain function through network science. Here, we systematically evaluate 768 data-processing pipelines for network reconstruction from resting-state functional MRI, evaluating the effect of brain parcellation, connectivity definition, and global signal regression. Our criteria seek pipelines that minimise motion confounds and spurious test-retest discrepancies of network topology, while being sensitive to both inter-subject differences and experimental effects of interest. We reveal vast and systematic variability across pipelines' suitability for functional connectomics. Inappropriate choice of data-processing pipeline can produce results that are not only misleading, but systematically so, with the majority of pipelines failing at least one criterion. However, a set of optimal pipelines consistently satisfy all criteria across different datasets, spanning minutes, weeks, and months. We provide a full breakdown of each pipeline's performance across criteria and datasets, to inform future best practices in functional connectomics.

Decoding Early Psychoses: Unraveling Stable Microstructural Features Associated With Psychopathology Across Independent Cohorts.

BACKGROUND: Patients with early psychosis (EP) (within 3 years after psychosis onset) show significant variability, which makes predicting outcomes challenging. Currently, little evidence exists for stable relationships between neural microstructural properties and symptom profiles across EP diagnoses, which limits the development of early interventions. METHODS: A data-driven approach, partial least squares correlation, was used across 2 independent datasets to examine multivariate relationships between white matter properties and symptomatology and to identify stable and generalizable signatures in EP. The primary cohort included patients with EP from the Human Connectome Project for Early Psychosis (n = 124). The replication cohort included patients with EP from the Feinstein Institute for Medical Research (n = 78) as part of the MEND (Multimodal Evaluation of Neural Disorders) Project. Both samples included individuals with schizophrenia, schizoaffective disorder, and psychotic mood disorders. RESULTS: In both cohorts, a significant latent component corresponded to a symptom profile that combined negative symptoms, primarily diminished expression, with specific somatic symptoms. Both latent components captured comprehensive features of white matter disruption, primarily a combination of subcortical and frontal association fibers. Strikingly, the partial least squares model trained on the primary cohort accurately predicted microstructural features and symptoms in the replication cohort. Findings were not driven by diagnosis, medication, or substance use. CONCLUSIONS: This data-driven transdiagnostic approach revealed a stable and replicable neurobiological signature of microstructural white matter alterations in EP across diagnoses and datasets, showing strong covariance of these alterations with a unique profile of negative and somatic symptoms. These findings suggest the clinical utility of applying data-driven approaches to reveal symptom domains that share neurobiological underpinnings.

Decoding Early Psychoses: Unraveling Stable Microstructural Features Associated with Psychopathology Across Independent Cohorts.

Background: Early Psychosis patients (EP, within 3 years after psychosis onset) show significant variability, making outcome predictions challenging. Currently, little evidence exists for stable relationships between neural microstructural properties and symptom profiles across EP diagnoses, limiting the development of early interventions. Methods: A data-driven approach, Partial Least Squares (PLS) correlation, was used across two independent datasets to examine multivariate relationships between white matter (WM) properties and symptomatology, to identify stable and generalizable signatures in EP. The primary cohort included EP patients from the Human Connectome Project-Early Psychosis (n=124). The replication cohort included EP patients from the Feinstein Institute for Medical Research (n=78). Both samples included individuals with schizophrenia, schizoaffective disorder, and psychotic mood disorders. Results: In both cohorts, a significant latent component (LC) corresponded to a symptom profile combining negative symptoms, primarily diminished expression, with specific somatic symptoms. Both LCs captured comprehensive features of WM disruption, primarily a combination of subcortical and frontal association fibers. Strikingly, the PLS model trained on the primary cohort accurately predicted microstructural features and symptoms in the replication cohort. Findings were not driven by diagnosis, medication, or substance use. Conclusions: This data-driven transdiagnostic approach revealed a stable and replicable neurobiological signature of microstructural WM alterations in EP, across diagnoses and datasets, showing a strong covariance of these alterations with a unique profile of negative and somatic symptoms. This finding suggests the clinical utility of applying data-driven approaches to reveal symptom domains that share neurobiological underpinnings.

Bilirubin gates the TRPM2 channel as a direct agonist to exacerbate ischemic brain damage.

Stroke prognosis is negatively associated with an elevation of serum bilirubin, but how bilirubin worsens outcomes remains mysterious. We report that post-, but not pre-, stroke bilirubin levels among inpatients scale with infarct volume. In mouse models, bilirubin increases neuronal excitability and ischemic infarct, whereas ischemic insults induce the release of endogenous bilirubin, all of which are attenuated by knockout of the TRPM2 channel or its antagonist A23. Independent of canonical TRPM2 intracellular agonists, bilirubin and its metabolic derivatives gate the channel opening, whereas A23 antagonizes it by binding to the same cavity. Knocking in a loss of binding point mutation for bilirubin, TRPM2-D1066A, effectively antagonizes ischemic neurotoxicity in mice. These findings suggest a vicious cycle of stroke injury in which initial ischemic insults trigger the release of endogenous bilirubin from injured cells, which potentially acts as a volume neurotransmitter to activate TRPM2 channels, aggravating Ca2+-dependent brain injury.

Benchmarking functional connectivity by the structure and geometry of the human brain.

The brain's structural connectivity supports the propagation of electrical impulses, manifesting as patterns of coactivation, termed functional connectivity. Functional connectivity emerges from the underlying sparse structural connections, particularly through polysynaptic communication. As a result, functional connections between brain regions without direct structural links are numerous, but their organization is not completely understood. Here we investigate the organization of functional connections without direct structural links. We develop a simple, data-driven method to benchmark functional connections with respect to their underlying structural and geometric embedding. We then use this method to reweigh and reexpress functional connectivity. We find evidence of unexpectedly strong functional connectivity among distal brain regions and within the default mode network. We also find unexpectedly strong functional connectivity at the apex of the unimodal-transmodal hierarchy. Our results suggest that both phenomena-functional modules and functional hierarchies-emerge from functional interactions that transcend the underlying structure and geometry. These findings also potentially explain recent reports that structural and functional connectivity gradually diverge in transmodal cortex. Collectively, we show how structural connectivity and geometry can be used as a natural frame of reference with which to study functional connectivity patterns in the brain.

Time-resolved structure-function coupling in brain networks.

The relationship between structural and functional connectivity in the brain is a key question in systems neuroscience. Modern accounts assume a single global structure-function relationship that persists over time. Here we study structure-function coupling from a dynamic perspective, and show that it is regionally heterogeneous. We use a temporal unwrapping procedure to identify moment-to-moment co-fluctuations in neural activity, and reconstruct time-resolved structure-function coupling patterns. We find that patterns of dynamic structure-function coupling are region-specific. We observe stable coupling in unimodal and transmodal cortex, and dynamic coupling in intermediate regions, particularly in insular cortex (salience network) and frontal eye fields (dorsal attention network). Finally, we show that the variability of a region's structure-function coupling is related to the distribution of its connection lengths. Collectively, our findings provide a way to study structure-function relationships from a dynamic perspective.

Network topology of the marmoset connectome.

The brain is a complex network of interconnected and interacting neuronal populations. Global efforts to understand the emergence of behavior and the effect of perturbations depend on accurate reconstruction of white matter pathways, both in humans and in model organisms. An emerging animal model for next-generation applied neuroscience is the common marmoset (Callithrix jacchus). A recent open respository of retrograde and anterograde tract tracing presents an opportunity to systematically study the network architecture of the marmoset brain (Marmoset Brain Architecture Project; http://www.marmosetbrain.org). Here we comprehensively chart the topological organization of the mesoscale marmoset cortico-cortical connectome. The network possesses multiple nonrandom attributes that promote a balance between segregation and integration, including near-minimal path length, multiscale community structure, a connective core, a unique motif composition, and multiple cavities. Altogether, these structural attributes suggest a link between network architecture and function. Our findings are consistent with previous reports across a range of species, scales, and reconstruction technologies, suggesting a small set of organizational principles universal across phylogeny. Collectively, these results provide a foundation for future anatomical, functional, and behavioral studies in this model organism.

Signal propagation via cortical hierarchies.

The wiring of the brain is organized around a putative unimodal-transmodal hierarchy. Here we investigate how this intrinsic hierarchical organization of the brain shapes the transmission of information among regions. The hierarchical positioning of individual regions was quantified by applying diffusion map embedding to resting-state functional MRI networks. Structural networks were reconstructed from diffusion spectrum imaging and topological shortest paths among all brain regions were computed. Sequences of nodes encountered along a path were then labeled by their hierarchical position, tracing out path motifs. We find that the cortical hierarchy guides communication in the network. Specifically, nodes are more likely to forward signals to nodes closer in the hierarchy and cover a range of unimodal and transmodal regions, potentially enriching or diversifying signals en route. We also find evidence of systematic detours, particularly in attention networks, where communication is rerouted. Altogether, the present work highlights how the cortical hierarchy shapes signal exchange and imparts behaviorally relevant communication patterns in brain networks.

Alterations in pituitary-thyroid axis function among opioid-dependent subjects after acute and protracted abstinence.

The aim of the present study was to investigate the changes in the pituitary-thyroid axis (PTA) and the time course of the hormonal alterations in subjects with opioid dependence after abstinence. Blood samples from in-patients with opioid dependence and age- and sex-matched healthy controls were collected. The severity of opioid abuse and of withdrawal symptoms was assessed. Results were compared between patients with opioid dependence (n = 30) and healthy controls (n = 30). We found that free triiodothyronine and free thyroxine levels were comparable with healthy controls while thyroid-stimulating hormone (TSH) was lower in patients in acute opioid abstinence period. Also, TSH levels in patients remained lower than controls after 30 days of abstinence. These results indicate that PTA function is altered in opioid-dependent subjects. These data highlight the importance of screening the thyroid function for individuals with chronic opioid dependence.

Etching Anode Foil with Branch Tunnels for Aluminum Electrolytic Capacitors.

Al foil for high-voltage aluminum electrolytic capacitor was first D.C. etched in HCl-H2SO4 mixed acidic solution to form main tunnels and then D.C. etched in natural NaCl solution containing 0.1% H2C2O4 and different trace amounts of Zn(NO3)2. Between the two etching processes, Zn nuclei were deposited on the interior surface of the main tunnels by the natural occluded corrosion cell effect to form micro Zn-Al galvanic local cells. The effects of Zn nuclei on the cross-section etching and electrochemical behavior of Al foil were investigated using scanning electron microscopy, polarization curve measurement, and electrochemical impedance spectroscopy. The sub-branch tunnels can form along the main tunnels owing to the formation of Zn-Al micro-batteries, in which Zn is the cathode and Al is the anode. Increasing Zn(NO3)2 concentration increases the number of Zn nuclei that can serve as sites for branch tunnel initiation along the main tunnels, thereby enhancing the specific capacitance of etched Al foil.

Dysfunction of the hypothalamic-pituitary-adrenal axis in opioid dependent subjects: effects of acute and protracted abstinence.

OBJECTIVES: The function of the Hypothalamic-Pituitary-Adrenal (HPA) axis during opioid dependence has been inconsistent. We compared HPA axis measures between subjects during methadone stabilization and drug-free detoxification with healthy controls. METHODS: Sixty heroin dependent patients received either non-opiate treatment (NOT) with benzodiazepines and clonidine (n = 30) or methadone stabilization treatment (MT, n = 30), and their serum levels of corticotropin releasing hormone (CRH), adrenocorticotropic hormone (ACTH), and cortisol (COR) were measured and compared to those of healthy, nondependent controls. RESULTS: Compared with healthy controls, CRH was significantly lower (p < .001) while COR was higher (p < .001) during acute withdrawal in the NOT group. CRH and COR was lower (p < .001), while ACTH was normal in the MT group compared to healthy controls. CONCLUSIONS: Our findings suggest that chronic opioid dependence may cause reduced function of the HPA axis, while opioid withdrawal may decrease the response of the pituitary to CRH and increase the adrenal response to ACTH.

Angiotensin II and insulin crosstalk in the cardiovascular system.

Under normal physiology, insulin exerts vasodilatory and pro-survival actions via the phosphatidylinositol 3-kinase (PI3-kinase) pathway and vasoconstrictive and mitogenic actions via the mitogen-activated protein kinase (MAPK) pathway in the vasculature. In the insulin resistant states, insulin signals through the PI3-kinase pathway are blunted but its signals through the MAPK cascade remain intact. This imbalance predisposes insulin resistant patients to hypertension and atherosclerosis. The renin-angiotensin system (RAS) is expressed both systemically and locally in the cardiovascular system. Insulin resistance up-regulates the local RAS which contributes to the pathogenesis of hypertension, heart failure, and atherosclerosis. Angiotensin II impairs insulin signaling, induces inflammation via the NF-kappaB pathway, reduces nitric oxide availability and facilitates vasoconstriction, leading to insulin resistance and endothelial dysfunction. Thus the RAS, insulin resistance and inflammation perpetuate each other and coordinately contribute to endothelial dysfunction, vascular injury and atherosclerosis. RAS inhibition decreases cardiovascular and renal morbidity and mortality and the incidence of new onset Type 2 diabetes.