Explore the vast range of titles available.

A bstract Heisenberg time evolution under a chaotic many-body Hamiltonian H transforms an initially simple operator into an increasingly complex one, as it spreads over Hilbert space. Krylov complexity, or ‘K-complexity’, quantifies this growth with respect to a special basis, generated by H by successive nested commutators with the operator. In this work we study the evolution of K-complexity in finite-entropy systems for time scales greater than the scrambling time t s > log( S ). We prove rigorous bounds on K-complexity as well as the associated Lanczos sequence and, using refined parallelized algorithms, we undertake a detailed numerical study of these quantities in the SYK 4 model, which is maximally chaotic, and compare the results with the SYK 2 model, which is integrable. While the former saturates the bound, the latter stays exponentially below it. We discuss to what extent this is a generic feature distinguishing between chaotic vs. integrable systems.

A bstract We apply a notion of quantum complexity, called “Krylov complexity”, to study the evolution of systems from integrability to chaos. For this purpose we investigate the integrable XXZ spin chain, enriched with an integrability breaking deformation that allows one to interpolate between integrable and chaotic behavior. K-complexity can act as a probe of the integrable or chaotic nature of the underlying system via its late-time saturation value that is suppressed in the integrable phase and increases as the system is driven to the chaotic phase. We furthermore ascribe the (under-)saturation of the late-time bound to the amount of disorder present in the Lanczos sequence, by mapping the complexity evolution to an auxiliary off-diagonal Anderson hopping model. We compare the late-time saturation of K-complexity in the chaotic phase with that of random matrix ensembles and find that the chaotic system indeed approaches the RMT behavior in the appropriate symmetry class. We investigate the dependence of the results on the two key ingredients of K-complexity: the dynamics of the Hamiltonian and the character of the operator whose time dependence is followed.

A bstract There are various definitions of the concept of complexity in Quantum Field Theory as well as for finite quantum systems. For several of them there are conjectured holographic bulk duals. In this work we establish an entry in the AdS/CFT dictionary for one such class of complexity, namely Krylov or K-complexity. For this purpose we work in the double-scaled SYK model which is dual in a certain limit to JT gravity, a theory of gravity in AdS 2 . In particular, states on the boundary have a clear geometrical definition in the bulk. We use this result to show that Krylov complexity of the infinite-temperature thermofield double state on the boundary of AdS 2 has a precise bulk description in JT gravity, namely the length of the two-sided wormhole. We do this by showing that the Krylov basis elements, which are eigenstates of the Krylov complexity operator, are mapped to length eigenstates in the bulk theory by subjecting K-complexity to the bulk-boundary map identifying the bulk/boundary Hilbert spaces. Our result makes extensive use of chord diagram techniques and identifies the Krylov basis of the boundary quantum system with fixed chord number states building the bulk gravitational Hilbert space.

A bstract Quantum complexity, suitably defined, has been suggested as an important probe of late-time dynamics of black holes, particularly in the context of AdS/CFT. A notion of quantum complexity can be effectively captured by quantifying the spread of an operator in Krylov space as a consequence of time evolution. Complexity is expected to behave differently in chaotic many-body systems, as compared to integrable ones. In this paper we investigate Krylov complexity for the case of interacting integrable models at finite size and find that complexity saturation is suppressed as compared to chaotic systems. We associate this behavior with a novel localization phenomenon on the Krylov chain by mapping the theory of complexity growth and spread to an Anderson localization hopping model with off-diagonal disorder, and find that localization is enhanced in the integrable case due to a stronger disorder in the hopping amplitudes, inducing an effective suppression of Krylov complexity. We demonstrate this behavior for an interacting integrable model, the XXZ spin chain, and show that the same behavior results from a phenomenological model that we define: this model captures the essential features of our analysis and is able to reproduce the behaviors we observe for chaotic and integrable systems via an adjustable disorder parameter.

A bstract In this paper we study the notion of complexity under time evolution in chaotic quantum systems with holographic duals. Continuing on from our previous work, we turn our attention to the issue of Krylov complexity upon the insertion of a class of single-particle operators in the double-scaled SYK model. Such an operator is described by a matter-chord insertion, which splits the theory into left/right sectors, allowing us, via chord-diagram technology, to compute two different notions of complexity associated to the operator insertion: first a Krylov operator complexity, and second the Krylov complexity of a state obtained by an operator acting on the thermofield double state. We will provide both an analytic proof and detailed numerical evidence, that both Krylov complexities arise from a recursively defined basis of states characterized by a constant total chord number. As a consequence, in all cases we are able to establish that Krylov complexity is given by the expectation value of a length operator acting on the Hilbert space of the theory, expressed in terms of basis states, organized by left and right chord number. We find analytic expressions for the semiclassical limit of K-complexity, and study how the size of the operator encodes the scrambling dynamics upon the matter insertion in Krylov language. We furthermore determine the effective Hamiltonian governing the evolution of K-complexity, showing that evolution on the Krylov chain can equivalently be understood as a particle moving in a Morse potential. A particular type of triple scaling limit allows to access the gravitational sector of the theory, in which the geometrical nature of K-complexity is assured by virtue of being a total chord length, in an analogous fashion to what was found in [ 1 ] for the K-complexity of the thermofield double state.

Chlorpyrifos is an organophosphate pesticide associated with numerous health effects including motor performance decrements. While many studies have focused on the health effects following acute chlorpyrifos poisonings, almost no studies have examined the effects on motoneurons following occupational-like exposures. The main objective of this study was to examine the broad effects of repeated occupational-like chlorpyrifos exposures on spinal motoneuron soma size relative to motor activity. To execute our objective, adult rats were exposed to chlorpyrifos via oral gavage once a day, five days a week for two weeks. Chlorpyrifos exposure effects were assessed either three days or two months following the last exposure. Three days following the last repeated chlorpyrifos exposure, there were transient effects in open-field motor activity and plasma cholinesterase activity levels. Two months following the chlorpyrifos exposures, there were delayed effects in sensorimotor gating, pro-inflammatory cytokines and spinal lumbar motoneuron soma morphology. Overall, these results offer support that subacute repeated occupational-like chlorpyrifos exposures have both short-term and longer-term effects in motor activity, inflammation, and central nervous system mechanisms.

Transcranial direct current stimulation (tDCS) has shown therapeutic potential to mitigate symptoms of various neurological disorders. Studies from our group and others used rodent models to demonstrate that tDCS modulates synaptic plasticity. We previously showed that 30 minutes of 0.25 mA tDCS administered to rats induced significant enhancement in the synaptic plasticity of hippocampal neurons. It has also been shown that tDCS induces expression of proteins known to mediate synaptic plasticity. This increase in synaptic plasticity may underly the observed therapeutic benefits of tDCS. However, the anti-inflammatory benefits of tDCS have not been thoroughly elucidated. Here we report that three sessions of tDCS spaced 1-3 weeks apart can significantly reduce levels of several inflammatory cytokines in brains of healthy rats. Rats receiving tDCS experienced enhanced synaptic plasticity without detectable improvement in behavioral tests or significant changes in astrocyte activation. The tDCS-mediated reduction in inflammatory cytokine levels supports the potential use of tDCS as a countermeasure against inflammation and offer additional support for the hypothesis that cytokines contribute to the modulation of synaptic plasticity.

Muscle proprioceptive afferents provide feedback critical for successful execution of motor tasks via specialized mechanoreceptors housed within skeletal muscles: muscle spindles, supplied by group Ia and group II afferents, and Golgi tendon organs, supplied by group Ib afferents. The morphology of these proprioceptors and their associated afferents has been studied extensively in the cat soleus, and to a lesser degree, in the rat; however, quantitative analyses of proprioceptive innervation in the mouse soleus are comparatively limited. The present study employed genetically-encoded fluorescent reporting systems to label and analyze muscle spindles, Golgi tendon organs, and the proprioceptive sensory neuron subpopulations supplying them within the intact mouse soleus muscle using high magnification confocal microscopy. Total proprioceptive receptors numbered 11.3 ± 0.4 and 5.2 ± 0.2 for muscle spindles and Golgi tendon organs, respectively, and these receptor counts varied independently (n = 27 muscles). Analogous to findings in the rat, muscle spindles analyzed were most frequently supplied by two proprioceptive afferents, and in the majority of instances, both were classified as primary endings using established morphological criteria. Secondary endings were most frequently observed when spindle associated afferents totaled three or more. The mean diameter of primary and secondary afferent axons differed significantly, but the distributions overlap more than previously observed in cat and rat studies.

The vascular niche of malignant gliomas is a key compartment that shapes the immunosuppressive brain tumor microenvironment (TME). The blood-brain-barrier (BBB) consisting of specialized endothelial cells (ECs) and perivascular cells forms a tight anatomical and functional barrier critically controlling transmigration and effector function of immune cells. During neuroinflammation and tumor progression, the metabolism of the essential amino acid tryptophan (Trp) to metabolites such as kynurenine has long been identified as an important metabolic pathway suppressing immune responses. Previous studies have demonstrated that indoleamine-2,3-dioxygenase-1 (IDO1), a key rate-limiting enzyme in tryptophan catabolism, is expressed within the TME of high-grade gliomas. Here, we investigate the role of endothelial IDO1 (eIDO1) expression for brain tumor immunity. Single-cell RNA sequencing data revealed that in human glioma tissue, IDO1 is predominantly expressed by activated ECs showing a JAK/STAT signaling pathway-related CXCL11+ gene expression signature. In a syngeneic experimental glioma model, eIDO1 is induced by low-dose tumor irradiation. However, cell type-specific ablation of eIDO1 in experimental gliomas did not alter frequency and phenotype of tumor-infiltrating T cells nor tumor growth. Taken together these data argue against a dominant role of eIDO1 for brain tumor immunity.

Progressive multiple sclerosis (MS) is characterized by unrelenting neurodegeneration, which causes cumulative disability and is refractory to current treatments. Drug development to prevent disease progression is an urgent clinical need yet is constrained by an incomplete understanding of its complex pathogenesis. Using spatial transcriptomics and proteomics on fresh-frozen human MS brain tissue, we identified multicellular mechanisms of progressive MS pathogenesis and traced their origin in relation to spatially distributed stages of neurodegeneration. By resolving ligand–receptor interactions in local microenvironments, we discovered defunct trophic and anti-inflammatory intercellular communications within areas of early neuronal decline. Proteins associated with neuronal damage in patient samples showed mechanistic concordance with published in vivo knockdown and central nervous system (CNS) disease models, supporting their causal role and value as potential therapeutic targets in progressive MS. Our findings provide a new framework for drug development strategies, rooted in an understanding of the complex cellular and signaling dynamics in human diseased tissue that facilitate this debilitating disease. By complementing spatial transcriptomics with high-resolution proteomics, Kaufmann et al. tracked a gradient of disease severity across the brains of patients with progressive multiple sclerosis, uncovering new therapeutic opportunities to slow disease.