Publications

BACKGROUND: Functional neurological disorder (FND) is a condition at the intersection of neurology and psychiatry. Individuals with FND exhibit corticolimbic abnormalities, yet little is known about the role of white matter tracts in the pathophysiology of FND. This study characterized between-group differences in microstructural integrity, and correlated fiber bundle integrity with symptom severity, physical disability, and illness duration. METHODS: A diffusion tensor imaging (DTI) study was performed in 32 patients with mixed FND compared to 36 healthy controls. Diffusion-weighted magnetic resonance images were collected along with patient-reported symptom severity, physical disability (Short Form Health Survey-36), and illness duration data. Weighted-degree and link-level graph theory and probabilistic tractography analyses characterized fractional anisotropy (FA) values across cortico-subcortical connections. Results were corrected for multiple comparisons. RESULTS: Compared to controls, FND patients showed reduced FA in the stria terminalis/fornix, medial forebrain bundle, extreme capsule, uncinate fasciculus, cingulum bundle, corpus callosum, and striatal-postcentral gyrus projections. Except for the stria terminalis/fornix, these differences remained significant adjusting for depression and anxiety. In within-group analyses, physical disability inversely correlated with stria terminalis/fornix and medial forebrain bundle FA values; illness duration negatively correlated with stria terminalis/fornix white matter integrity. A FND symptom severity composite score did not correlate with FA in patients. CONCLUSIONS: In this first DTI study of mixed FND, microstructural differences were observed in limbic and associative tracts implicated in salience, defensive behaviors, and emotion regulation. These findings advance our understanding of neurocircuit pathways in the pathophysiology of FND.

In this work, we present an unsupervised domain adaptation (UDA) method, named Panoptic Domain Adaptive Mask R-CNN (PDAM), for unsupervised instance segmentation in microscopy images. Since there currently lack methods particularly for UDA instance segmentation, we first design a Domain Adaptive Mask R-CNN (DAM) as the baseline, with cross-domain feature alignment at the image and instance levels. In addition to the image- and instance-level domain discrepancy, there also exists domain bias at the semantic level in the contextual information. Next, we, therefore, design a semantic segmentation branch with a domain discriminator to bridge the domain gap at the contextual level. By integrating the semantic- and instance-level feature adaptation, our method aligns the cross-domain features at the panoptic level. Third, we propose a task re-weighting mechanism to assign trade-off weights for the detection and segmentation loss functions. The task re-weighting mechanism solves the domain bias issue by alleviating the task learning for some iterations when the features contain source-specific factors. Furthermore, we design a feature similarity maximization mechanism to facilitate instance-level feature adaptation from the perspective of representational learning. Different from the typical feature alignment methods, our feature similarity maximization mechanism separates the domain-invariant and domain-specific features by enlarging their feature distribution dependency. Experimental results on three UDA instance segmentation scenarios with five datasets demonstrate the effectiveness of our proposed PDAM method, which outperforms state-of-the-art UDA methods by a large margin.

BACKGROUND AND PURPOSE: Lower reward responsiveness has been associated with fatigue in multiple sclerosis (MS). However, association of MS-related fatigue with damage to the mesocorticolimbic reward pathway (superolateral medial forebrain bundle [slMFB]) has not been assessed. We investigated the association of fatigue and depression with slMFB damage in MS patients stratified based on longitudinal fatigue patterns. METHODS: Patient stratification: 1. Sustained Fatigue (SF): latest two Modified Fatigue Impact Scale (MFIS) >= 38 (n = 26); 2. Reversible Fatigue (RF): latest MFIS < 38, and at least one previous MFIS >= 38 (n = 25); 3. Never Fatigued (NF): >= 5 consecutive MFIS < 38 (n = 42); 4. Healthy Controls (n = 6). Diffusion MRI-derived measures of fractional anisotropy (FA), axial (AD), mean (MD), and radial diffusivity (RD) of the slMFB were compared between the groups. Depression was assessed using the Center for Epidemiologic Studies-Depression Scale (CES-D). RESULTS: Depressed (CES-D >= 16) SF patients showed significantly higher MD and RD than nondepressed SF and RF, and depressed RF patients, and significantly lower FA than nondepressed SF and depressed RF patients in their left slMFB. Depressed SF patients showed significantly higher left slMFB MD and AD than healthy controls. CONCLUSION: Microstructural changes to the left slMFB may play a role in the comorbid development of fatigue and depression in MS.

BACKGROUND: Occupational exposures at the WTC site after 11 September 2001 have been associated with presumably inflammatory chronic lower airway diseases. AIMS: In this study, we describe the trajectories of expiratory air flow decline, identify subgroups with adverse progression, and investigate the association of those trajectories with quantitative computed tomography (QCT) imaging measurement of increased and decreased lung density. METHODS: We examined the trajectories of expiratory air flow decline in a group of 1,321 former WTC workers and volunteers with at least three periodic spirometries, and using QCT-measured low (LAV%, -950 HU) and high (HAV%, from -600 to -250 HU) attenuation volume percent. We calculated the individual regression line slopes for first-second forced expiratory volume (FEV slope), identified subjects with rapidly declining ("accelerated decliners") and increasing ("improved"), and compared them to subjects with "intermediate" (0 to -66.5 mL/year) FEV slope. We then used multinomial logistic regression to model those three trajectories, and the two lung attenuation metrics. RESULTS: The mean longitudinal FEV slopes for the entire study population, and its intermediate, decliner, and improved subgroups were, respectively, -40.4, -34.3, -106.5, and 37.6 mL/year. In unadjusted and adjusted analyses, LAV% and HAV% were both associated with "accelerated decliner" status (OR , 95% CI 2.37, 1.41-3.97, and 1.77, 1.08-2.89, respectively), compared to the intermediate decline. CONCLUSIONS: Longitudinal FEV decline in this cohort, known to be associated with QCT proximal airway inflammation metric, is also associated with QCT indicators of increased and decreased lung density. The improved FEV trajectory did not seem to be associated with lung density metrics.

In this work, we propose a theoretical framework based on maximum profile likelihood for pairwise and groupwise registration. By an asymptotic analysis, we demonstrate that maximum profile likelihood registration minimizes an upper bound on the joint entropy of the distribution that generates the joint image data. Further, we derive the congealing method for groupwise registration by optimizing the profile likelihood in closed form, and using coordinate ascent, or iterative model refinement. We also describe a method for feature based registration in the same framework and demonstrate it on groupwise tractographic registration. In the second part of the article, we propose an approach to deep metric registration that implements maximum likelihood registration using deep discriminative classifiers. We show further that this approach can be used for maximum profile likelihood registration to discharge the need for well-registered training data, using iterative model refinement. We demonstrate that the method succeeds on a challenging registration problem where the standard mutual information approach does not perform well.

OBJECTIVES: Muscle wasting is a recognised extra-pulmonary complication in chronic obstructive pulmonary disease and has been associated with increased risk of death. Acute respiratory exacerbations are associated with reduction of muscle function, but there is a paucity of data on their long-term effect. This study explores the relationship between acute respiratory exacerbations and long-term muscle loss using serial measurements of CT derived pectoralis muscle area (PMA). DESIGN AND SETTING: Participants were included from two prospective, longitudinal, observational, multicentre cohorts of ever-smokers with at least 10 pack-year history. PARTICIPANTS: The primary analysis included 1332 (of 2501) participants from Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) and 4384 (of 10 198) participants from Genetic Epidemiology of COPD (COPDGene) who had complete data from their baseline and follow-up visits. INTERVENTIONS: PMA was measured on chest CT scans at two timepoints. Self-reported exacerbation data were collected from participants in both studies through the use of periodic longitudinal surveys. MAIN OUTCOME MEASURES: Age-related and excess muscle loss over time. RESULTS: Age, sex, race and body mass index were associated with baseline PMA. Participants experienced age-related decline at the upper end of reported normal ranges. In ECLIPSE, the exacerbation rate over time was associated with an excess muscle area loss of 1.3% (95% CI 0.6 to 1.9, p<0.001) over 3 years and in COPDGene with an excess muscle area loss of 2.1% (95% CI 1.2 to 2.8, p<0.001) over 5 years. Excess muscle area decline was absent in 273 individuals who participated in pulmonary rehabilitation. CONCLUSIONS: Exacerbations are associated with accelerated skeletal muscle loss. Each annual exacerbation was associated with the equivalent of 6 months of age-expected decline in muscle mass. Ameliorating exacerbation-associated muscle loss represents an important therapeutic target.

The reaction of [Re(CO)3(THF)(μ-Br)]2 or [Re(CO)5X] (X = Cl, Br, I) with the diaryl-2-azabutadienes [(RS)2C[double bond, length as m-dash]C(H)-N[double bond, length as m-dash]CAr2] containing two thioether arms at the 4,4-position forms the luminescent S,N-chelate complexes fac-[(OC)3ReX(RS)2C[double bond, length as m-dash]C(H)-N[double bond, length as m-dash]CAr2] (1a-h). The halide abstraction by silver triflate converts [(OC)3ReCl(PhS)2C[double bond, length as m-dash]C(H)-N[double bond, length as m-dash]CPh2] (1c) to [(OC)3Re(OS([double bond, length as m-dash]O)2CF3)(PhS)2C[double bond, length as m-dash]C(H)-N[double bond, length as m-dash]CPh2] (1j) bearing a covalently bound triflate ligand. The cyclic voltammograms reveal reversible S^N ligand-centred reduction and irreversible oxidation waves for all complexes. The crystal structures of nine octahedral complexes have been determined along with that of (NaphtylS)2C[double bond, length as m-dash]C(H)-N[double bond, length as m-dash]CPh2 (L6). A rich system of weak non-covalent intermolecular secondary interactions through CHX(Cl, Br)Re, CHO, COπ(Ph), CHπCO, CHO and CHS contacts has been evidenced. The photophysical properties have been investigated by steady-state and time-resolved absorption (fs transient absorption, fs-TAS) and emission (ns-TCSPC and ps-Streak camera) spectroscopy in 2-MeTHF solution at 298 and 77 K. The emission bands are composed of either singlet (450 < λmax < 535 nm) and/or triplet emissions (at 77 K only, λmax < 640 nm, or appearing as a tail at λ > 600 nm), which decay in a multiexponential manner for the fluorescence (short ps (i.e.

Amyotrophic Lateral Sclerosis-Frontotemporal Dementia (ALS-FTD) may present typical behavioral variant FTD symptoms. This study aims to determine whether profile and severity of cognitive-behavioral symptoms in ALS/ALS-FTD are predicted by regional cortical atrophy. The hypothesis is that executive dysfunction can be predicted by dorsolateral prefrontal cortical (dlPFC) atrophy, apathy by dorsomedial PFC (dmPFC) and anterior cingulate cortical (ACC) atrophy, disinhibition by orbitofrontal cortical (OFC) atrophy. 3.0 Tesla MRI scans were acquired from 22 people with ALS or ALS-FTD. Quantitative cortical thickness analysis was performed with FreeSurfer. A priori-defined regions of interest (ROI) were used to measure cortical thickness in each participant and calculate magnitude of atrophy in comparison to 115 healthy controls. Spearman correlations were used to evaluate associations between frontal ROI cortical thickness and cognitive-behavioral symptoms, measured by Neuropsychiatric Inventory Questionnaire (NPI-Q) and Clinical Dementia Rating (CDR) scale. ALS-FTD participants exhibited variable degrees of apathy (NPI-Q/apathy: 1.6 ± 1.2), disinhibition (NPI-Q/disinhibition: 1.2 ± 1.2), executive dysfunction (CDR/judgment-problem solving: 1.7 ± 0.8). Within the ALS-FTD group, executive dysfunction correlated with dlPFC atrophy (ρ:-0.65;p < 0.05); similar trends were seen for apathy with ACC (ρ:-0.53;p < 0.10) and dmPFC (ρ:-0.47;p < 0.10) atrophy, for disinhibition with OFC atrophy (ρ:-0.51;p < 0.10). Compared to people with ALS, those with ALS-FTD showed more diffuse atrophy involving precentral gyrus, prefrontal, temporal regions. Profile and severity of cognitive-behavioral symptoms in ALS-FTD are predicted by regional prefrontal atrophy. These findings are consistent with established brain-behavior models and support the role of quantitative MRI in diagnosis, management, counseling, monitoring and prognostication for a neurodegenerative disorder with diverse phenotypes.