Connectome-based modelling of neurodegenerative diseases: towards precision medicine and mechanistic insight.

Neurodegenerative diseases are the most common cause of dementia. Although their underlying molecular pathologies have been identified, there is substantial heterogeneity in the patterns of progressive brain alterations across and within these diseases. Recent advances in neuroimaging methods have revealed that pathological proteins accumulate along specific macroscale brain networks, implicating the network architecture of the brain in the system-level pathophysiology of neurodegenerative diseases. However, the extent to which 'network-based neurodegeneration' applies across the wide range of neurodegenerative disorders remains unclear. Here, we discuss the state-of-the-art of neuroimaging-based connectomics for the mapping and prediction of neurodegenerative processes. We review findings supporting brain networks as passive conduits through which pathological proteins spread. As an alternative view, we also discuss complementary work suggesting that network alterations actively modulate the spreading of pathological proteins between connected brain regions. We conclude this Perspective by proposing an integrative framework in which connectome-based models can be advanced along three dimensions of innovation: incorporating parameters that modulate propagation behaviour on the basis of measurable biological features; building patient-tailored models that use individual-level information and allowing model parameters to interact dynamically over time. We discuss promises and pitfalls of these strategies for improving disease insights and moving towards precision medicine.

Frontotemporal lobar degeneration targets brain regions linked to expression of recently evolved genes.

In frontotemporal lobar degeneration (FTLD), pathological protein aggregation in specific brain regions is associated with declines in human-specialized social-emotional and language functions. In most patients, disease protein aggregates contain either TDP-43 (FTLD-TDP) or tau (FTLD-tau). Here, we explored whether FTLD-associated regional degeneration patterns relate to regional gene expression of human accelerated regions (HARs), conserved sequences that have undergone positive selection during recent human evolution. To this end, we used structural neuroimaging from patients with FTLD and human brain regional transcriptomic data from controls to identify genes expressed in FTLD-targeted brain regions. We then integrated primate comparative genomic data to test our hypothesis that FTLD targets brain regions linked to expression levels of recently evolved genes. In addition, we asked whether genes whose expression correlates with FTLD atrophy are enriched for genes that undergo cryptic splicing when TDP-43 function is impaired. We found that FTLD-TDP and FTLD-tau subtypes target brain regions with overlapping and distinct gene expression correlates, highlighting many genes linked to neuromodulatory functions. FTLD atrophy-correlated genes were strongly enriched for HARs. Atrophy-correlated genes in FTLD-TDP showed greater overlap with TDP-43 cryptic splicing genes and genes with more numerous TDP-43 binding sites compared with atrophy-correlated genes in FTLD-tau. Cryptic splicing genes were enriched for HAR genes, and vice versa, but this effect was due to the confounding influence of gene length. Analyses performed at the individual-patient level revealed that the expression of HAR genes and cryptically spliced genes within putative regions of disease onset differed across FTLD-TDP subtypes.

Conical Intersections at Interfaces Revealed by Phase-Cycling Interface-Specific Two-Dimensional Electronic Spectroscopy (i2D-ES).

Conical intersections (CIs) hold significant stake in manipulating and controlling photochemical reaction pathways of molecules at interfaces and surfaces by affecting molecular dynamics therein. Currently, there is no tool for characterizing CIs at interfaces and surfaces. To this end, we have developed phase-cycling interface-specific two-dimensional electronic spectroscopy (i2D-ES) and combined it with advanced computational modeling to explore nonadiabatic CI dynamics of molecules at the air/water interface. Specifically, we integrated the phase locked pump pulse pair with an interface-specific electronic probe to obtain the two-dimensional interface-specific responses. We demonstrate that the nonadiabatic transitions of an interface-active azo dye molecule that occur through the CIs at the interface have different kinetic pathways from those in the bulk water. Upon photoexcitation, two CIs are present: one from an intersection of an optically active S2 state with a dark S1 state and the other from the intersection of the progressed S1 with the ground state S0. We find that the molecular conformations in the ground state are different for interfacial molecules. The interfacial molecules are intimately correlated with the locally populated excited state S2 being farther away from the CI region. This leads to slower nonadiabatic dynamics at the interface than in bulk water. Moreover, we show that the nonadiabatic transition from the S1 dark state to the ground state is significantly longer at the interface than that in the bulk, which is likely due to the orientationally restricted configuration of the excited state at the interface. Our findings suggest that orientational configurations of molecules manipulate reaction pathways at interfaces and surfaces.

Quantitative Signal Analysis of Sum-Frequency Scattering Experiments from Aerosol Surfaces.

Droplet interfaces are instrumental in processes of biology, engineering, production, and environmental systems. The chemical and physical properties of heterogeneous interfaces are known to be different from those of their underlying bulk phases, and different again when considering the curved surface of submicron aerosol droplets. The recently developed technique of vibrational sum-frequency scattering (VSFS) spectroscopy from airborne particles has emerged as an interface-specific method for the in situ analysis of this unique system. While the technique has shown promise in debut works, a quantitative analysis of the VSFS system has not yet been performed. Here we provide a comprehensive analysis of a VSFS spectrometer with reference to the well-documented planar analog. We decompose the VSFS signal into coherent and incoherent as well as resonant and nonresonant components as a function of incident pulse delay time. We then quantify and compare resonant and nonresonant VSFS and VSFG experimental data using the same laser and detection systems. Using the air/water interface as a guide, we show that the resonant and nonresonant contributions to the SF responses are comparable for the two systems by extracting second-order susceptibilities and hyperpolarizabilities, and using them to estimate single-particle susceptibilities. A quantitative analysis of the signal detection systems for the scattering and planar geometries is made, and conversion efficiencies for VSFG, VSFS, and other nonlinear scattering experiments are compared. Lastly, the possibility of a low-repetition (1 kHz) VSFS spectrometer is considered, determining that it may be possible with modern laser technology but is inevitably less efficient than a high-repetition (100 kHz) system. Though this multistep analysis we obtain a better understanding of the components of the VSFS signal from aerosol particles, further validate the feasibility of the experiments, and provide insight to those wishing to conduct similar experiments and how they may be improved.

Network Connectivity Alterations across the MAPT Mutation Clinical Spectrum.

OBJECTIVE: Microtubule-associated protein tau (MAPT) mutations cause frontotemporal lobar degeneration, and novel biomarkers are urgently needed for early disease detection. We used task-free functional magnetic resonance imaging (fMRI) mapping, a promising biomarker, to analyze network connectivity in symptomatic and presymptomatic MAPT mutation carriers. METHODS: We compared cross-sectional fMRI data between 17 symptomatic and 39 presymptomatic carriers and 81 controls with (1) seed-based analyses to examine connectivity within networks associated with the 4 most common MAPT-associated clinical syndromes (ie, salience, corticobasal syndrome, progressive supranuclear palsy syndrome, and default mode networks) and (2) whole-brain connectivity analyses. We applied K-means clustering to explore connectivity heterogeneity in presymptomatic carriers at baseline. Neuropsychological measures, plasma neurofilament light chain, and gray matter volume were compared at baseline and longitudinally between the presymptomatic subgroups defined by their baseline whole-brain connectivity profiles. RESULTS: Symptomatic and presymptomatic carriers had connectivity disruptions within MAPT-syndromic networks. Compared to controls, presymptomatic carriers showed regions of connectivity alterations with age. Two presymptomatic subgroups were identified by clustering analysis, exhibiting predominantly either whole-brain hypoconnectivity or hyperconnectivity at baseline. At baseline, these two presymptomatic subgroups did not differ in neuropsychological measures, although the hypoconnectivity subgroup had greater plasma neurofilament light chain levels than controls. Longitudinally, both subgroups showed visual memory decline (vs controls), yet the subgroup with baseline hypoconnectivity also had worsening verbal memory and neuropsychiatric symptoms, and extensive bilateral mesial temporal gray matter decline. INTERPRETATION: Network connectivity alterations arise as early as the presymptomatic phase. Future studies will determine whether presymptomatic carriers' baseline connectivity profiles predict symptomatic conversion. ANN NEUROL 2023;94:632-646.

Neuropsychiatric symptoms and imbalance of atrophy in behavioral variant frontotemporal dementia.

Behavioral variant frontotemporal dementia is characterized by heterogeneous frontal, insular, and anterior temporal atrophy patterns that vary along left-right and dorso-ventral axes. Little is known about how these structural imbalances impact clinical symptomatology. The goal of this study was to assess the frequency of frontotemporal asymmetry (right- or left-lateralization) and dorsality (ventral or dorsal predominance of atrophy) and to investigate their clinical correlates. Neuropsychiatric symptoms and structural images were analyzed for 250 patients with behavioral variant frontotemporal dementia. Frontotemporal atrophy was most often symmetric while left-lateralized (9%) and right-lateralized (17%) atrophy were present in a minority of patients. Atrophy was more often ventral (32%) than dorsal (3%) predominant. Patients with right-lateralized atrophy were characterized by higher severity of abnormal eating behavior and hallucinations compared to those with left-lateralized atrophy. Subsequent analyses clarified that eating behavior was associated with right atrophy to a greater extent than a lack of left atrophy, and hallucinations were driven mainly by right atrophy. Dorsality analyses showed that anxiety, euphoria, and disinhibition correlated with ventral-predominant atrophy. Agitation, irritability, and depression showed greater severity with a lack of regional atrophy, including in dorsal regions. Aberrant motor behavior and apathy were not explained by asymmetry or dorsality. This study provides additional insight into how anatomical heterogeneity influences the clinical presentation of patients with behavioral variant frontotemporal dementia. Behavioral symptoms can be associated not only with the presence or absence of focal atrophy, but also with right/left or dorsal/ventral imbalance of gray matter volume.

In Situ Probing of the Surface Properties of Droplets in the Air.

Surface properties of nanodroplets and microdroplets are intertwined with their immense applicability in biology, medicine, production, catalysis, the environment, and the atmosphere. However, many means for analyzing droplets and their surfaces are destructive, non-interface-specific, not conducted under ambient conditions, require sample substrates, conducted ex situ, or a combination thereof. For these reasons, a technique for surface-selective in situ analyses under any condition is necessary. This feature article presents recent developments in second-order nonlinear optical scattering techniques for the in situ interfacial analysis of aerosol droplets in the air. First, we describe the abundant utilization of such droplets across industries and how their unique surface properties lead to their ubiquitous usage. Then, we describe the fundamental properties of droplets and their surfaces followed by common methods for their study. We next describe the fundamental principles of sum-frequency generation (SFG) spectroscopy, the Langmuir adsorption model, and how they are used together to describe adsorption processes at planar liquid and droplet surfaces. We also discuss the history of developments of second-order scattering from droplets suspended in dispersive media and introduce second-harmonic scattering (SHS) and sum-frequency scattering (SFS) spectroscopies. We then go on to outline the developments of SHS, electronic sum-frequency scattering (ESFS), and vibrational sum-frequency scattering (VSFS) from droplets in the air and discuss the fundamental insights about droplet surfaces that the techniques have provided. Finally, we describe some of the areas of nonlinear scattering from airborne droplets which need improvement as well as potential future directions and utilizations of SHS, ESFS, and VSFS throughout environmental systems, interfacial chemistry, and fundamental physics. The goal of this feature article is to spread knowledge about droplets and their unique surface properties as well as introduce second-order nonlinear scattering to a broad audience who may be unaware of recent progress and advancements in their applicability.

Dynamic autonomic nervous system states arise during emotions and manifest in basal physiology.

The outflow of the autonomic nervous system (ANS) is continuous and dynamic, but its functional organization is not well understood. Whether ANS patterns accompany emotions, or arise in basal physiology, remain unsettled questions in the field. Here, we searched for brief ANS patterns amidst continuous, multichannel physiological recordings in 45 healthy older adults. Participants completed an emotional reactivity task in which they viewed video clips that elicited a target emotion (awe, sadness, amusement, disgust, or nurturant love); each video clip was preceded by a pre-trial baseline period and followed by a post-trial recovery period. Participants also sat quietly for a separate 2-min resting period to assess basal physiology. Using principal components analysis and unsupervised clustering algorithms to reduce the second-by-second physiological data during the emotional reactivity task, we uncovered five ANS states. Each ANS state was characterized by a unique constellation of patterned physiological changes that differentiated among the trials of the emotional reactivity task. These ANS states emerged and dissipated over time, with each instance lasting several seconds on average. ANS states with similar structures were also detectable in the resting period but were intermittent and of smaller magnitude. Our results offer new insights into the functional organization of the ANS. By assembling short-lived, patterned changes, the ANS is equipped to generate a wide range of physiological states that accompany emotions and that contribute to the architecture of basal physiology.

A dynamic gradient architecture generates brain activity states.

The human brain exhibits a diverse yet constrained range of activity states. While these states can be faithfully represented in a low-dimensional latent space, our understanding of the constitutive functional anatomy is still evolving. Here we applied dimensionality reduction to task-free and task fMRI data to address whether latent dimensions reflect intrinsic systems and if so, how these systems may interact to generate different activity states. We find that each dimension represents a dynamic activity gradient, including a primary unipolar sensory-association gradient underlying the global signal. The gradients appear stable across individuals and cognitive states, while recapitulating key functional connectivity properties including anticorrelation, modularity, and regional hubness. We then use dynamical systems modeling to show that gradients causally interact via state-specific coupling parameters to create distinct brain activity patterns. Together, these findings indicate that a set of dynamic, intrinsic spatial gradients interact to determine the repertoire of possible brain activity states.

Default Mode Network quantitative diffusion and resting-state functional magnetic resonance imaging correlates in sporadic Creutzfeldt-Jakob disease.

Grey matter involvement is a well-known feature in sporadic Creutzfeldt-Jakob disease (sCJD), yet precise anatomy-based quantification of reduced diffusivity is still not fully understood. Default Mode Network (DMN) areas have been recently demonstrated as selectively involved in sCJD, and functional connectivity has never been investigated in prion diseases. We analyzed the grey matter involvement using a quantitatively multi-parametric MRI approach. Specifically, grey matter mean diffusivity of 37 subjects with sCJD was compared with that of 30 age-matched healthy controls with a group-wise approach. Differences in mean diffusivity were also examined between the cortical (MM(V)1, MM(V)2C, and VV1) and subcortical (VV2 and MV2K) subgroups of sCJD for those with autopsy data available (n = 27, 73%). We also assessed resting-state functional connectivity of both ventral and dorsal components of DMN in a subset of subject with a rs-fMRI dataset available (n = 17). Decreased diffusivity was predominantly present in posterior cortical regions of the DMN, but also outside of the DMN in temporal areas and in a few limbic and frontal areas, in addition to extensive deep nuclei involvement. Both subcortical and cortical sCJD subgroups showed decreased diffusivity subcortically, whereas only the cortical type expressed significantly decreased diffusivity cortically, mainly in parietal, occipital, and medial-inferior temporal cortices bilaterally. Interestingly, we found abnormally increased connectivity in both dorsal and ventral components of the DMN in sCJD subjects compared with healthy controls. The significance and possible utility of functional imaging as a biomarker for tracking disease progression in prion disease needs to be explored further.

In Situ Detection of Chemical Compositions at Nanodroplet Surfaces and In-Nanodroplet Phases.

Small-volume nanodroplets play an increasingly common role in chemistry and biology. Such nanodroplets are believed to have unique chemical and physical properties at the interface between a droplet and its surrounding medium, however, they are underexamined. In this study, we present the novel technique of vibrational sum frequency scattering (VSFS) spectroscopy as an interface-specific, high-performance method for the in situ investigation of nanodroplets with sub-micron radii; as well as the droplet bulk through simultaneous hyper-Raman scattering (HRS) spectroscopy. We use laboratory-generated nanodroplets from aqueous alcohol solutions to demonstrate this technique's ability to separate the vibrational phenomena which take place at droplet surfaces from the underlying bulk phase. In addition, we systemically examine interfacial spectra of nanodroplets containing methanol, ethanol, 1-propanol, and 1-butanol through VSFS. Furthermore, we demonstrate interfacial differences between such nanodroplets and their analogous planar surfaces. The sensitivity of this technique to probe droplet surfaces with few-particle density at standard conditions validates VSFS as an analytical technique for the in situ investigation of small nanodroplets, providing breakthrough information about these species of ever-increasing relevance.

Salience Network Atrophy Links Neuron Type-Specific Pathobiology to Loss of Empathy in Frontotemporal Dementia.

Each neurodegenerative syndrome reflects a stereotyped pattern of cellular, regional, and large-scale brain network degeneration. In behavioral variant of frontotemporal dementia (bvFTD), a disorder of social-emotional function, von Economo neurons (VENs), and fork cells are among the initial neuronal targets. These large layer 5 projection neurons are concentrated in the anterior cingulate and frontoinsular (FI) cortices, regions that anchor the salience network, a large-scale system linked to social-emotional function. Here, we studied patients with bvFTD, amyotrophic lateral sclerosis (ALS), or both, given that these syndromes share common pathobiological and genetic factors. Our goal was to determine how neuron type-specific TAR DNA-binding protein of 43 kDa (TDP-43) pathobiology relates to atrophy in specific brain structures and to loss of emotional empathy, a cardinal feature of bvFTD. We combined questionnaire-based empathy assessments, in vivo structural MR imaging, and quantitative histopathological data from 16 patients across the bvFTD/ALS spectrum. We show that TDP-43 pathobiology within right FI VENs and fork cells is associated with salience network atrophy spanning insular, medial frontal, and thalamic regions. Gray matter degeneration within these structures mediated loss of emotional empathy, suggesting a chain of influence linking the cellular, regional/network, and behavioral levels in producing signature bvFTD clinical features.

State and trait characteristics of anterior insula time-varying functional connectivity.

The human anterior insula (aINS) is a topographically organized brain region, in which ventral portions contribute to socio-emotional function through limbic and autonomic connections, whereas the dorsal aINS contributes to cognitive processes through frontal and parietal connections. Open questions remain, however, regarding how aINS connectivity varies over time. We implemented a novel approach combining seed-to-whole-brain sliding-window functional connectivity MRI and k-means clustering to assess time-varying functional connectivity of aINS subregions. We studied three independent large samples of healthy participants and longitudinal datasets to assess inter- and intra-subject stability, and related aINS time-varying functional connectivity profiles to dispositional empathy. We identified four robust aINS time-varying functional connectivity modes that displayed both "state" and "trait" characteristics: while modes featuring connectivity to sensory regions were modulated by eye closure, modes featuring connectivity to higher cognitive and emotional processing regions were stable over time and related to empathy measures.

Electronic Conductance Resonance in Non-Redox-Active Proteins.

Bioelectronics research has mainly focused on redox-active proteins because of their role in biological charge transport. In these proteins, electronic conductance is a maximum when electrons are injected at the known redox potential of the protein. It has been shown recently that many non-redox-active proteins are good electronic conductors, though the mechanism of conduction is not yet understood. Here, we report single-molecule measurements of the conductance of three non-redox-active proteins, maintained under potential control in solution, as a function of electron injection energy. All three proteins show a conductance resonance at a potential ∼0.7 V removed from the nearest oxidation potential of their constituent amino acids. If this shift reflects a reduction of reorganization energy in the interior of the protein, it would account for the long-range conductance observed when carriers are injected into the interior of a protein.

Evidence of corticofugal tau spreading in patients with frontotemporal dementia.

Common neurodegenerative diseases feature progressive accumulation of disease-specific protein aggregates in selectively vulnerable brain regions. Increasing experimental evidence suggests that misfolded disease proteins exhibit prion-like properties, including the ability to seed corruptive templating and self-propagation along axons. Direct evidence for transneuronal spread in patients, however, remains limited. To test predictions made by the transneuronal spread hypothesis in human tissues, we asked whether tau deposition within axons of the corticospinal and corticopontine pathways can be predicted based on clinical syndromes and cortical atrophy patterns seen in frontotemporal lobar degeneration (FTLD). Sixteen patients with Pick's disease, 21 with corticobasal degeneration, and 3 with FTLD-MAPT were included, spanning a range of clinical syndromes across the frontotemporal dementia (FTD) spectrum. Cortical involvement was measured using a neurodegeneration score, a tau score, and a composite score based on semiquantitative ratings and complemented by an MRI-based cortical atrophy W-map based on antemortem imaging. Midbrain cerebral peduncle and pontine base descending fibers were divided into three subregions, representing prefrontopontine, corticospinal, and parieto-temporo-occipital fiber pathways. Tau area fraction was calculated in each subregion and related to clinical syndrome and cortical measures. Within each clinical syndrome, there were predicted relationships between cortical atrophy patterns and axonal tau deposition in midbrain cerebral peduncle and pontine base. Between syndromes, contrasting and predictable patterns of brainstem axonal tau deposition emerged, with, for example, greater tau in prefrontopontine fibers in behavioral variant FTD and in corticospinal fibers in corticobasal syndrome. Finally, semiquantitative and quantitative cortical degeneration scores predicted brainstem axonal tau deposition based on anatomical principles. Taken together, these findings provide important human evidence in support of axonal tau spreading in patients with specific forms of tau-related neurodegeneration.

Neuropathological correlates of structural and functional imaging biomarkers in 4-repeat tauopathies.

Neurodegenerative dementia syndromes are characterized by spreading of pathological protein deposition along syndrome-specific neural networks. Structural and functional MRI measures can assess the integrity of these networks and have been proposed as biomarkers of disease progression for clinical trials. The relationship between in vivo imaging measures and pathological features, at the single subject level, remains largely unknown. Patient-specific maps of atrophy and seed-based intrinsic connectivity disruption, as compared to normal controls, were obtained for 27 patients subsequently diagnosed with progressive supranuclear palsy (n = 16, seven males, age at death 68.9 ± 6.0 years, imaging-to-pathology interval = 670.2 ± 425.1 days) or corticobasal degeneration (n = 11, two males, age at death 66.7 ± 5.4 years, imaging-to-pathology interval = 696.2 ± 482.2 days). A linear mixed effect model with crossed random effects was used to test regional and single-subject level associations between post-mortem regional measures of neurodegeneration and tau inclusion burden, on the one hand, and regional volume loss and seed-based intrinsic connectivity reduction, on the other. A significant association was found between tau inclusion burden and in vivo volume loss, at the regional level and independent of neurodegeneration severity, in both progressive supranuclear palsy [n = 340 regions; beta 0.036; 95% confidence interval (CI): 0.001, 0.072; P = 0.046] and corticobasal degeneration (n = 215 regions; beta 0.044; 95% CI: 0.009, 0.079; P = 0.013). We also found a significant association between post-mortem neurodegeneration and in vivo volume loss in both progressive supranuclear palsy (n = 340 regions; beta 0.155; 95% CI: 0.061, 0.248; P = 0.001) and corticobasal degeneration (n = 215 regions; beta 0.277; 95% CI: 0.104, 0.450; P = 0.002). We found a significant association between regional neurodegeneration and intrinsic connectivity dysfunction in corticobasal degeneration (n = 215 regions; beta 0.074; 95% CI: 0.005, 0.143; P = 0.035), but no other associations between post-mortem measures of tauopathy and intrinsic connectivity dysfunction reached statistical significance. Our data suggest that in vivo structural imaging measures reflect independent contributions from neurodegeneration and tau burden in progressive supranuclear palsy and corticobasal degeneration. Seed-based measures of intrinsic connectivity dysfunction showed less reliable predictive value when used as in vivo biomarkers of tauopathy. The findings provide important guidance for the use of imaging biomarkers as indirect in vivo assays of microscopic pathology.

Network Architecture Underlying Basal Autonomic Outflow: Evidence from Frontotemporal Dementia.

The salience network is a distributed neural system that maintains homeostasis by regulating autonomic nervous system activity and social-emotional function. Here we examined how within-network connectivity relates to individual differences in human (including males and females) baseline parasympathetic and sympathetic nervous activity. We measured resting autonomic nervous system physiology in 24 healthy controls and 23 patients with behavioral variant frontotemporal dementia (bvFTD), a neurodegenerative disease characterized by baseline autonomic deficits. Participants also underwent structural and task-free fMRI. First, we used voxel-based morphometry to determine whether salience network atrophy was associated with lower baseline respiratory sinus arrhythmia (a parasympathetic measure) and skin conductance level (a sympathetic measure) in bvFTD. Next, we examined whether functional connectivity deficits in 21 autonomic-relevant, salience network node-pairs related to baseline autonomic dysfunction. Lower baseline respiratory sinus arrhythmia was associated with smaller volume in left ventral anterior insula (vAI), weaker connectivity between bilateral vAI and bilateral anterior cingulate cortex (ACC), and stronger connectivity between bilateral ACC and bilateral hypothalamus/amygdala. Lower baseline skin conductance level, in contrast, was associated with smaller volume in inferior temporal gyrus, dorsal mid-insula, and hypothalamus; weaker connectivity between bilateral ACC and right hypothalamus/amygdala; and stronger connectivity between bilateral dorsal anterior insula and periaqueductal gray. Our results suggest that baseline parasympathetic and sympathetic tone depends on the integrity of lateralized salience network hubs (left vAI for parasympathetic and right hypothalamus/amygdala for sympathetic) and highly calibrated ipsilateral and contralateral network connections. In bvFTD, deficits in this system may underlie resting parasympathetic and sympathetic disruption.SIGNIFICANCE STATEMENT The salience network maintains homeostasis and regulates autonomic nervous system activity. Whether within-network connectivity patterns underlie individual differences in resting parasympathetic and sympathetic nervous system activity, however, is not well understood. We measured baseline autonomic nervous system activity in healthy controls and patients with behavioral variant frontotemporal dementia, a neurodegenerative disease characterized by resting autonomic deficits, and probed how salience network dysfunction relates to diminished parasympathetic and sympathetic outflow. Our results indicate that baseline parasympathetic and sympathetic tone are the product of complex, opposing intranetwork nodal interactions and depend on the integrity of highly tuned, lateralized salience network hubs (i.e., left ventral anterior insula for parasympathetic activity and right hypothalamus/amygdala for sympathetic activity).

The Longitudinal Trajectory of Default Mode Network Connectivity in Healthy Older Adults Varies As a Function of Age and Is Associated with Changes in Episodic Memory and Processing Speed.

The default mode network (DMN) supports memory functioning and may be sensitive to preclinical Alzheimer's pathology. Little is known, however, about the longitudinal trajectory of this network's intrinsic functional connectivity (FC). In this study, we evaluated longitudinal FC in 111 cognitively normal older human adults (ages 49-87, 46 women/65 men), 92 of whom had at least three task-free fMRI scans (n = 353 total scans). Whole-brain FC and three DMN subnetworks were assessed: (1) within-DMN, (2) between anterior and posterior DMN, and (3) between medial temporal lobe network and posterior DMN. Linear mixed-effects models demonstrated significant baseline age × time interactions, indicating a nonlinear trajectory. There was a trend toward increasing FC between ages 50-66 and significantly accelerating declines after age 74. A similar interaction was observed for whole-brain FC. APOE status did not predict baseline connectivity or change in connectivity. After adjusting for network volume, changes in within-DMN connectivity were specifically associated with changes in episodic memory and processing speed but not working memory or executive functions. The relationship with processing speed was attenuated after covarying for white matter hyperintensities (WMH) and whole-brain FC, whereas within-DMN connectivity remained associated with memory above and beyond WMH and whole-brain FC. Whole-brain and DMN FC exhibit a nonlinear trajectory, with more rapid declines in older age and possibly increases in connectivity early in the aging process. Within-DMN connectivity is a marker of episodic memory performance even among cognitively healthy older adults.SIGNIFICANCE STATEMENT Default mode network and whole-brain connectivity, measured using task-free fMRI, changed nonlinearly as a function of age, with some suggestion of early increases in connectivity. For the first time, longitudinal changes in DMN connectivity were shown to correlate with changes in episodic memory, whereas volume changes in relevant brain regions did not. This relationship was not accounted for by white matter hyperintensities or mean whole-brain connectivity. Functional connectivity may be an early biomarker of changes in aging but should be used with caution given its nonmonotonic nature, which could complicate interpretation. Future studies investigating longitudinal network changes should consider whole-brain changes in connectivity.

Minimum spanning tree analysis of the human connectome.

One of the challenges of brain network analysis is to directly compare network organization between subjects, irrespective of the number or strength of connections. In this study, we used minimum spanning tree (MST; a unique, acyclic subnetwork with a fixed number of connections) analysis to characterize the human brain network to create an empirical reference network. Such a reference network could be used as a null model of connections that form the backbone structure of the human brain. We analyzed the MST in three diffusion-weighted imaging datasets of healthy adults. The MST of the group mean connectivity matrix was used as the empirical null-model. The MST of individual subjects matched this reference MST for a mean 58%-88% of connections, depending on the analysis pipeline. Hub nodes in the MST matched with previously reported locations of hub regions, including the so-called rich club nodes (a subset of high-degree, highly interconnected nodes). Although most brain network studies have focused primarily on cortical connections, cortical-subcortical connections were consistently present in the MST across subjects. Brain network efficiency was higher when these connections were included in the analysis, suggesting that these tracts may be utilized as the major neural communication routes. Finally, we confirmed that MST characteristics index the effects of brain aging. We conclude that the MST provides an elegant and straightforward approach to analyze structural brain networks, and to test network topological features of individual subjects in comparison to empirical null models.

Chemoenzymatic macrocycle synthesis using resorcylic acid lactone thioesterase domains.

A key missing tool in the chemist's toolbox is an effective biocatalyst for macrocyclization. Macrocycles limit the conformational flexibility of small molecules, often improving their ability to bind selectively and with high affinity to a target, making them a privileged structure in drug discovery. Macrocyclic natural product biosynthesis offers an obvious starting point for biocatalyst discovery via the native macrocycle forming biosynthetic mechanism. Herein we demonstrate that the thioesterase domains (TEs) responsible for macrocyclization of resorcylic acid lactones are promising catalysts for the chemoenzymatic synthesis of 12- to 18-member ring macrolactones and macrolactams. The TE domains responsible for zearalenone and radicicol biosynthesis successfully generate resorcylate-like 12- to 18-member macrolactones and a 14-member macrolactam. In addition these enzymes can also macrolactonize a non-resorcylate containing depsipeptide, suggesting they are versatile biocatalysts. Simple saturated omega-hydroxy acyl chains are not macrocyclized, nor are the alpha-beta unsaturated derivatives, clearly outlining the scope of the substrate tolerance. These data dramatically expand our understanding of substrate tolerance of these enzymes and are consistent with our understanding of the role of TEs in iterative polyketide biosynthesis. In addition this work shows these TEs to be the most substrate tolerant polyketide macrocyclizing enzymes known, accessing resorcylate lactone and lactams as well as cyclicdepsipeptides, which are highly biologically relevant frameworks.