A mariner's tale: Invasive endotracheal Mycobacterium marinum infection.

Mycobacterium marinum is a ubiquitous water-borne non-tuberculous mycobacterial (NTM) pathogen. In humans, M. marinum infections are acquired through direct inoculation of skin wounds and are almost exclusively localized to skin and soft tissues. Pulmonary infection with M. marinum is extremely rare, and to our knowledge, invasive endobronchial disease has not been reported. Here, we present a case of a 71-year-old immunocompetent male surfer with invasive endotracheal M. marinum granulomatous disease. The patient was successfully cured with a regimen of azithromycin 250 mg daily, ethambutol 900 mg (15 mg/kg) daily and rifampicin 600 mg daily for 12 months following culture conversion. This case highlights several important concepts: Firstly, M. marinum infection, including invasive endobronchial infection, should be considered a rare cause of NTM pulmonary disease. Secondly, endotracheal infection can be successfully eradicated with this selected therapeutic regimen. Finally, the absence of M. marinum skin or soft-tissue infection in this patient, raises the possibility that human disease might also be acquired via inhalation of M. marinum contaminated water in rare circumstances.

Anti-synthetase syndrome associated interstitial lung disease after combination dual immune checkpoint inhibition.

Immune checkpoint inhibitors (ICIs) unleash potent anti-tumour responses but with frequent off-target immune-mediated adverse events (irAE). ICIs can induce a spectrum of rheumatologic manifestations including inflammatory arthritis, Sjögren's syndrome, scleroderma and systemic lupus erythematosus. Here, we describe a case of antisynthetase syndrome associated interstitial lung disease (ILD) following dual Programmed Cell Death 1 and Cytotoxic T Lymphocyte-Associated Protein 4 checkpoint inhibition in a patient with metastatic melanoma. Initial treatment course was complicated by a number of irAEs including pneumonitis, colitis and thyroiditis. Suspicion of an underlying systemic rheumatic disease was heightened by the severe, relapsing and fibrosing nature of the interstitial pneumonitis. A diagnosis of amyopathic antisynthetase syndrome was made upon detection of circulating aminoacyl-tRNA synthetase (anti-EJ) autoantibodies. Intensification of induction immunosuppression followed by maintenance mycophenolate, prednisone and monthly intravenous immunoglobulin achieved long-term disease control. Detection of de novo ICI-induced inflammatory myositis ILD requires a high index of suspicion and carries important prognostic and treatment implications.

Pulmonary involvement in Anti-Neutrophil Cytoplasmic Antibody Associated Vasculitis: A single centre case series.

Anti-Neutrophil Cytoplasmic Antibody associated Vasculitides (AAV) comprise a rare group of disorders in which respiratory tract involvement is variable and often severe. The rarity and heterogeneity of AAV makes this a challenging condition to diagnose and manage. In this single-centre case series of 44 patients with AAV-associated respiratory disease, we provide an overview of disease manifestations, management aspects and treatment outcomes. Data from this case series highlight the real-world diagnostic and therapeutic challenges of the AAV respiratory disease spectrum; including uncertainties in the management of fibrosing interstitial lung disease, tracheobronchial stenosis and diffuse alveolar haemorrhage.

Right heart strain assessment on CTPA following acute pulmonary embolism: Interobserver variability between expert radiologists and physicians.

BACKGROUND: Accuracy of right heart strain (RHS) measured on computed tomography pulmonary angiogram (CTPA) scans by non-radiologists is unknown. We assessed inter-observer variability of four RHS features and determined the accuracy of measurements by respiratory physicians. METHOD: 1560 consecutive patients with acute PE were identified, and those who had a CTPA and an echocardiogram within 24-h included. CTPAs were independently scored prospectively by two radiologists, two thoracic physicians and a specialist registrar. Inter-observer variability was assessed, and diagnostic accuracy compared to echocardiography. RESULTS: 182 patients (median age 62.8 years, IQR 49.8-71.5) with acute PE (7.7% high-risk, 40.7% intermediate high-risk, 31.3% intermediate low-risk and 20.3% low-risk) were included. Right ventricle to left ventricle diameter ratio (RV:LV) measurement had low inter-observer variability among the radiologists and non-radiologists with interclass correlation coefficient (ICC) of 0.95 (95%CI 0.92-0.97) and 0.96 (95%CI 0.94-0.97) respectively. RV:LV ratio had high diagnostic accuracy compared to RV dilatation on echocardiography (AUC 0.89, 95%CI 0.84-0.94 for radiologists and AUC 0.84, 95%CI 0.77-0.90 for non-radiologists). Main pulmonary artery to ascending aorta diameter ratio (MPA:Ao) measurement also had excellent agreement amongst the radiologists and non-radiologists (ICC 0.93 (95%CI 0.88-0.96) and 0.92 (95%CI 0.81-0.96) respectively). Significant variability was seen in the assessment of subjective features of RHS (leftward bowing of interventricular septum and contrast reflux into inferior vena cava) amongst the non-radiologists. CONCLUSION: RV:LV and MPA:Ao diameter ratios on CTPA measured by non-radiologists have low inter-observer variability and good agreement with radiologists, and can be reliably used where an expert report is unavailable.

Alveolar crystal burden in stone workers with artificial stone silicosis.

BACKGROUND AND OBJECTIVE: An epidemic of silicosis has emerged due to a failure to control risks associated with exposure to high-silica content respirable dust generated while working with artificial stone products. Methods for quantification of alveolar crystal burden are needed to advance our understanding of the pathobiology of silica-related lung injury as well as assisting in the diagnosis, clinical management and prognostication of affected workers. The objective of this study was to develop and validate novel methods to quantify alveolar crystal burden in bronchoalveolar lavage (BAL) fluid from patients with artificial stone silicosis. METHODS: New methods to quantify and analyse alveolar crystal in BAL from patients with artificial stone silicosis were developed. Crystals were isolated and counted by microscopy and alveolar crystal burden was calculated using a standard curve generated by titration of respirable α-Quartz. The utility of the assay was then assessed in 23 patients with artificial stone silicosis. RESULTS: Alveolar crystal burden was greater in patients with silicosis (0.44 picograms [pg]/cell [0.08-3.49]) compared to patients with other respiratory diagnoses (0.057 pg/cell [0.01-0.34]; p < 0.001). Alveolar crystal burden was positively correlated with years of silica exposure (ρ = 0.49, p = 0.02) and with decline in diffusing capacity of the lungs for carbon monoxide (ρ = -0.50, p = 0.02). CONCLUSION: Alveolar crystal burden quantification differentiates patients with silicosis from patients with other respiratory disorders. Furthermore, crystal burden is correlated with the rate of decline in lung function in patients with artificial stone silicosis.

Inferior outcomes in lung transplant recipients with serum Pseudomonas aeruginosa specific cloaking antibodies.

BACKGROUND: Chronic Lung Allograft Dysfunction (CLAD) limits long-term survival following lung transplantation. Colonization of the allograft by Pseudomonas aeruginosa is associated with an increased risk of CLAD and inferior overall survival. Recent experimental data suggests that 'cloaking' antibodies targeting the O-antigen of the P. aeruginosa lipopolysaccharide cell wall (cAbs) attenuate complement-mediated bacteriolysis in suppurative lung disease. METHODS: In this retrospective cohort analysis of 123 lung transplant recipients, we evaluated the prevalence, risk factors and clinical impact of serum cAbs following transplantation. RESULTS: cAbs were detected in the sera of 40.7% of lung transplant recipients. Cystic fibrosis and younger age were associated with increased risk of serum cAbs (CF diagnosis, OR 6.62, 95% CI 2.83-15.46, p < .001; age at transplant, OR 0.69, 95% CI 0.59-0.81, p < .001). Serum cAbs and CMV mismatch were both independently associated with increased risk of CLAD (cAb, HR 4.34, 95% CI 1.91-9.83, p < .001; CMV mismatch (D+/R-), HR 5.40, 95% CI 2.36-12.32, p < .001) and all-cause mortality (cAb, HR 2.75, 95% CI 1.27-5.95, p = .010, CMV mismatch, HR 3.53, 95% CI 1.62-7.70, p = .002) in multivariable regression analyses. CONCLUSIONS: Taken together, these findings suggest a potential role for 'cloaking' antibodies targeting P. aeruginosa LPS O-antigen in the immunopathogenesis of CLAD.

Dopamine depletion alters macroscopic network dynamics in Parkinson's disease.

Parkinson's disease is primarily characterized by diminished dopaminergic function; however, the impact of these impairments on large-scale brain dynamics remains unclear. It has been difficult to disentangle the direct effects of Parkinson's disease from compensatory changes that reconfigure the functional signature of the whole brain network. To examine the causal role of dopamine depletion in network-level topology, we investigated time-varying network structure in 37 individuals with idiopathic Parkinson's disease, both ON and OFF dopamine replacement therapy, along with 50 age-matched, healthy control subjects using resting state functional MRI. By tracking dynamic network-level topology, we found that the Parkinson's disease OFF state was associated with greater network-level integration than in the ON state. The extent of integration in the OFF state inversely correlated with motor symptom severity, suggesting that a shift toward a more integrated network topology may be a compensatory mechanism associated with preserved motor function in the dopamine depleted OFF state. Furthermore, we were able to demonstrate that measures of both cognitive and brain reserve (i.e. premorbid intelligence and whole brain grey matter volume) had a positive relationship with the relative increase in network integration observed in the dopaminergic OFF state. This suggests that each of these factors plays an important role in promoting network integration in the dopaminergic OFF state. Our findings provide a mechanistic basis for understanding the Parkinson's disease OFF state and provide a further conceptual link with network-level reconfiguration. Together, our results highlight the mechanisms responsible for pathological and compensatory change in Parkinson's disease.

Publisher Correction: Human cognition involves the dynamic integration of neural activity and neuromodulatory systems.

In the version of this article initially published, Kaylena A. Ehgoetz Martens' name was misspelled as Kayla. The error has been corrected in the HTML and PDF versions of the article.

Human cognition involves the dynamic integration of neural activity and neuromodulatory systems.

The human brain integrates diverse cognitive processes into a coherent whole, shifting fluidly as a function of changing environmental demands. Despite recent progress, the neurobiological mechanisms responsible for this dynamic system-level integration remain poorly understood. Here we investigated the spatial, dynamic, and molecular signatures of system-wide neural activity across a range of cognitive tasks. We found that neuronal activity converged onto a low-dimensional manifold that facilitates the execution of diverse task states. Flow within this attractor space was associated with dissociable cognitive functions, unique patterns of network-level topology, and individual differences in fluid intelligence. The axes of the low-dimensional neurocognitive architecture aligned with regional differences in the density of neuromodulatory receptors, which in turn relate to distinct signatures of network controllability estimated from the structural connectome. These results advance our understanding of functional brain organization by emphasizing the interface between neural activity, neuromodulatory systems, and cognitive function.

Neural correlates of emotional valence processing in Parkinson's disease: dysfunction in the subcortex.

Parkinson's disease (PD) is frequently accompanied by cognitive and neuropsychiatric symptoms including impairments in affective processing. Despite this, mechanisms underlying vulnerability to deficits in affective processing remain unclear. In this study, we utilized functional Magnetic Resonance Imaging (fMRI) and an Affective Go-NoGo paradigm, to examine the neural correlates of emotional valence processing in PD. Results suggest that PD is associated with aberrant processing of emotional valence in subcortical limbic structures. Specifically, we found significant group-by-valence interactions in the ventral striatum and amygdala in response to words of differing emotional valence. Our findings contribute to a broader understanding of affective processing in PD and may provide insights into the mechanisms underlying vulnerability to mood disorders in PD.

Dopamine depletion impairs gait automaticity by altering cortico-striatal and cerebellar processing in Parkinson's disease.

Impairments in motor automaticity cause patients with Parkinson's disease to rely on attentional resources during gait, resulting in greater motor variability and a higher risk of falls. Although dopaminergic circuitry is known to play an important role in motor automaticity, little evidence exists on the neural mechanisms underlying the breakdown of locomotor automaticity in Parkinson's disease. This impedes clinical management and is in great part due to mobility restrictions that accompany the neuroimaging of gait. This study therefore utilized a virtual reality gait paradigm in conjunction with functional MRI to investigate the role of dopaminergic medication on lower limb motor automaticity in 23 patients with Parkinson's disease that were measured both on and off dopaminergic medication. Participants either operated foot pedals to navigate a corridor ('walk' condition) or watched the screen while a researcher operated the paradigm from outside the scanner ('watch' condition), a setting that controlled for the non-motor aspects of the task. Step time variability during walk was used as a surrogate measure for motor automaticity (where higher variability equates to reduced automaticity), and patients demonstrated a predicted increase in step time variability during the dopaminergic "off" state. During the "off" state, subjects showed an increased blood oxygen level-dependent response in the bilateral orbitofrontal cortices (walk>watch). To estimate step time variability, a parametric modulator was designed that allowed for the examination of brain regions associated with periods of decreased automaticity. This analysis showed that patients on dopaminergic medication recruited the cerebellum during periods of increasing variability, whereas patients off medication instead relied upon cortical regions implicated in cognitive control. Finally, a task-based functional connectivity analysis was conducted to examine the manner in which dopamine modulates large-scale network interactions during gait. A main effect of medication was found for functional connectivity within an attentional motor network and a significant condition by medication interaction for functional connectivity was found within the striatum. Furthermore, functional connectivity within the striatum correlated strongly with increasing step time variability during walk in the off state (r=0.616, p=0.002), but not in the on state (r=-0.233, p=0.284). Post-hoc analyses revealed that functional connectivity in the dopamine depleted state within an orbitofrontal-striatal limbic circuit was correlated with worse step time variability (r=0.653, p<0.001). Overall, this study demonstrates that dopamine ameliorates gait automaticity in Parkinson's disease by altering striatal, limbic and cerebellar processing, thereby informing future therapeutic avenues for gait and falls prevention.

Subcortical contributions to large-scale network communication.

Higher brain function requires integration of distributed neuronal activity across large-scale brain networks. Recent scientific advances at the interface of subcortical brain anatomy and network science have highlighted the possible contribution of subcortical structures to large-scale network communication. We begin our review by examining neuroanatomical literature suggesting that diverse neural systems converge within the architecture of the basal ganglia and thalamus. These findings dovetail with those of recent network analyses that have demonstrated that the basal ganglia and thalamus belong to an ensemble of highly interconnected network hubs. A synthesis of these findings suggests a new view of the subcortex, in which the basal ganglia and thalamus form part of a core circuit that supports large-scale integration of functionally diverse neural signals. Finally, we close with an overview of some of the major opportunities and challenges facing subcortical-inclusive descriptions of large-scale network communication in the human brain.

The Dynamics of Functional Brain Networks: Integrated Network States during Cognitive Task Performance.

Higher brain function relies upon the ability to flexibly integrate information across specialized communities of brain regions; however, it is unclear how this mechanism manifests over time. In this study, we used time-resolved network analysis of fMRI data to demonstrate that the human brain traverses between functional states that maximize either segregation into tight-knit communities or integration across otherwise disparate neural regions. Integrated states enable faster and more accurate performance on a cognitive task, and are associated with dilations in pupil diameter, suggesting that ascending neuromodulatory systems may govern the transition between these alternative modes of brain function. Together, our results confirm a direct link between cognitive performance and the dynamic reorganization of the network structure of the brain.

A hierarchy of timescales explains distinct effects of local inhibition of primary visual cortex and frontal eye fields.

Within the primate visual system, areas at lower levels of the cortical hierarchy process basic visual features, whereas those at higher levels, such as the frontal eye fields (FEF), are thought to modulate sensory processes via feedback connections. Despite these functional exchanges during perception, there is little shared activity between early and late visual regions at rest. How interactions emerge between regions encompassing distinct levels of the visual hierarchy remains unknown. Here we combined neuroimaging, non-invasive cortical stimulation and computational modelling to characterize changes in functional interactions across widespread neural networks before and after local inhibition of primary visual cortex or FEF. We found that stimulation of early visual cortex selectively increased feedforward interactions with FEF and extrastriate visual areas, whereas identical stimulation of the FEF decreased feedback interactions with early visual areas. Computational modelling suggests that these opposing effects reflect a fast-slow timescale hierarchy from sensory to association areas.

Estimation of dynamic functional connectivity using Multiplication of Temporal Derivatives.

Functional connectivity provides an informative and powerful framework for exploring brain organization. Despite this, few statistical methods are available for the accurate estimation of dynamic changes in functional network architecture. To date, the majority of existing statistical techniques have assumed that connectivity structure is stationary, which is in direct contrast to emerging data that suggests that the strength of connectivity between regions is variable over time. Therefore, the development of statistical methods that enable exploration of dynamic changes in functional connectivity is currently of great importance to the neuroscience community. In this paper, we introduce the 'Multiplication of Temporal Derivatives' (MTD) and then demonstrate the utility of this metric to: (i) detect dynamic changes in connectivity using data from a novel state-switching simulation; (ii) accurately estimate graph structure in a previously-described 'ground-truth' simulated dataset; and (iii) identify task-driven alterations in functional connectivity. We show that the MTD is more sensitive than existing sliding-window methods in detecting dynamic alterations in connectivity structure across a range of correlation strengths and window lengths in simulated data. In addition to the temporal precision offered by MTD, we demonstrate that the metric is also able to accurately estimate stationary network structure in both simulated and real task-based data, suggesting that the method may be used to identify dynamic changes in network structure as they evolve through time.

Estimating Large-Scale Network Convergence in the Human Functional Connectome.

The study of resting-state networks provides an informative paradigm for understanding the functional architecture of the human brain. Although investigating specialized resting-state networks has led to significant advances in our understanding of brain organization, the manner in which information is integrated across these networks remains unclear. Here, we have developed and validated a data-driven methodology for describing the topography of resting-state network convergence in the human brain. Our results demonstrate the importance of an ensemble of cortical and subcortical regions in supporting the convergence of multiple resting-state networks, including the rostral anterior cingulate, precuneus, posterior cingulate cortex, posterior parietal cortex, dorsal prefrontal cortex, along with the caudate head, anterior claustrum, and posterior thalamus. In addition, we have demonstrated a significant correlation between voxel-wise network convergence and global brain connectivity, emphasizing the importance of resting-state network convergence in facilitating global brain communication. Finally, we examined the convergence of systems within each of the individual resting-state networks in the brain, revealing the heterogeneity by which individual resting-state networks balance the competing demands of specialized processing against the integration of information. Together, our results suggest that the convergence of resting-state networks represents an important organizational principle underpinning systems-level integration in the human brain.

Dopaminergic basis for impairments in functional connectivity across subdivisions of the striatum in Parkinson's disease.

The pathological hallmark of Parkinson's disease is the degeneration of dopaminergic nigrostriatal neurons, leading to depletion of striatal dopamine. Recent neuroanatomical work has identified pathways for communication across striatal subdivisions, suggesting that the striatum provides a platform for integration of information across parallel corticostriatal circuits. The aim of this study was to investigate whether dopaminergic dysfunction in Parkinson's disease was associated with impairments in functional connectivity across striatal subdivisions, which could potentially reflect reduced integration across corticostriatal circuits. Utilizing resting-state functional magnetic resonance imaging (fMRI), we analyzed functional connectivity in 39 patients with Parkinson's disease, both "on" and "off" their regular dopaminergic medications, along with 40 age-matched healthy controls. Our results demonstrate widespread impairments in connectivity across subdivisions of the striatum in patients with Parkinson's disease in the "off" state. The administration of dopaminergic medication significantly improved connectivity across striatal subdivisions in Parkinson's disease, implicating dopaminergic deficits in the pathogenesis of impaired striatal interconnectivity. In addition, impaired striatal interconnectivity in the Parkinson's disease "off" state was associated with pathological decoupling of the striatum from the thalamic and sensorimotor (SM) networks. Specifically, we found that although the strength of striatal interconnectivity was positively correlated with both (i) the strength of internal thalamic connectivity, and (ii) the strength of internal SM connectivity, in both healthy controls and the Parkinson's disease "on" state, these relationships were absent in Parkinson's disease when in the "off" state. Taken together our findings emphasize the central role of dopamine in integrated striatal function and the pathological consequences of striatal dopamine denervation in Parkinson's disease.