The management of breast cancer-related lymphoedema

Lymphoedema is a chronic debilitating condition characterised by an accumulation of protein-rich fluid in interstitial spaces due to insufficient functioning of the lymphatic system. The condition may be referred to as primary (congenital malformation) or secondary (damage to the lymphatic system) lymphoedema. Lymphoedema is currently incurable, but can be alleviated with appropriate treatment. However, if ignored, it can progress and become difficult to manage. 

Increased functional sensorimotor network efficiency relates to disability in multiple sclerosis

BACKGROUND: Network abnormalities could help explain physical disability in multiple sclerosis (MS), which remains poorly understood. OBJECTIVE: This study investigates functional network efficiency changes in the sensorimotor system. METHODS: We included 222 MS patients, divided into low disability (LD, Expanded Disability Status Scale (EDSS) ⩽3.5, n = 185) and high disability (HD, EDSS ⩾6, n = 37), and 82 healthy controls (HC). Functional connectivity was assessed between 23 sensorimotor regions. Measures of efficiency were computed and compared between groups using general linear models corrected for age and sex. Binary logistic regression models related disability status to local functional network efficiency (LE), brain volumes and demographics. Functional connectivity patterns of regions important for disability were explored. RESULTS: HD patients demonstrated significantly higher LE of the left primary somatosensory cortex (S1) and right pallidum compared to LD and HC, and left premotor cortex compared to HC only. The logistic regression model for disability (R2 = 0.38) included age, deep grey matter volume and left S1 LE. S1 functional connectivity was increased with prefrontal and secondary sensory areas in HD patients, compared to LD and HC. CONCLUSION: Clinical disability in MS associates with functional sensorimotor increases in efficiency and connectivity, centred around S1, independent of structural damage

Higher-order functional connectivity analysis of resting-state functional magnetic resonance imaging data using multivariate cumulants

Blood-level oxygenation-dependent (BOLD) functional magnetic resonance imaging (fMRI) is the most common modality to study functional connectivity in the human brain. Most research to date has focused on connectivity between pairs of brain regions. However, attention has recently turned towards connectivity involving more than two regions, that is, higher-order connectivity. It is not yet clear how higher-order connectivity can best be quantified. The measures that are currently in use cannot distinguish between pairwise (i.e., second-order) and higher-order connectivity. We show that genuine higher-order connectivity can be quantified by using multivariate cumulants. We explore the use of multivariate cumulants for quantifying higher-order connectivity and the performance of block bootstrapping for statistical inference. In particular, we formulate a generative model for fMRI signals exhibiting higher-order connectivity and use it to assess bias, standard errors, and detection probabilities. Application to resting-state fMRI data from the Human Connectome Project demonstrates that spontaneous fMRI signals are organized into higher-order networks that are distinct from second-order resting-state networks. Application to a clinical cohort of patients with multiple sclerosis further demonstrates that cumulants can be used to classify disease groups and explain behavioral variability. Hence, we present a novel framework to reliably estimate genuine higher-order connectivity in fMRI data which can be used for constructing hyperedges, and finally, which can readily be applied to fMRI data from populations with neuropsychiatric disease or cognitive neuroscientific experiments.</p

Longitudinal Network Changes and Conversion to Cognitive Impairment in Multiple Sclerosis

OBJECTIVE: To characterize functional network changes related to conversion to cognitive impairment in a large sample of MS patients over a period of 5 years. METHODS: 227 MS patients and 59 healthy controls (HCs) of the Amsterdam MS cohort underwent neuropsychological testing and resting-state fMRI at two time points (time-interval 4.9±0.9 years). At both baseline and follow-up, patients were categorized as cognitively preserved (CP, N=123), mildly impaired (MCI, Z<-1.5 on ≥2 cognitive tests, N=32) or impaired (CI, Z<-2 on ≥2 tests, N=72) and longitudinal conversion between groups was determined. Network function was quantified using eigenvector centrality, a measure of regional network importance, which was computed for individual resting-state networks at both time-points. RESULTS: Over time, 18.9% of patients converted to a worse phenotype; 22/123 CP patients (17.9%) converted from CP to MCI, 10/123 from CP to CI (8.1%) and 12/32 MCI patients converted to CI (37.5%). At baseline, DMN centrality was higher in CI compared to controls (P=.05). Longitudinally, ventral attention network (VAN) importance increased in CP, driven by stable CP and CP-to-MCI converters (P<.05). CONCLUSIONS: Of all patients, 19% worsened in their cognitive status over five years. Conversion from intact cognition to impairment is related to an initial disturbed functioning of the VAN, then shifting towards DMN dysfunction in CI. As the VAN normally relays information to the DMN, these results could indicate that in MS, normal processes crucial for maintaining overall network stability are progressively disrupted as patients clinically progress

Feasibility of detecting atrophy relevant for disability and cognition in multiple sclerosis using 3D-FLAIR

BACKGROUND AND OBJECTIVES: Disability and cognitive impairment are known to be related to brain atrophy in multiple sclerosis (MS), but 3D-T1 imaging required for brain volumetrics is often unavailable in clinical protocols, unlike 3D-FLAIR. Here our aim was to investigate whether brain volumes derived from 3D-FLAIR images result in similar associations with disability and cognition in MS as do those derived from 3D-T1 images. METHODS: 3T-MRI scans of 329 MS patients and 76 healthy controls were included in this cross-sectional study. Brain volumes were derived using FreeSurfer on 3D-T1 and compared with brain volumes derived with SynthSeg and SAMSEG on 3D-FLAIR. Relative agreement was evaluated by calculating the intraclass correlation coefficient (ICC) of the 3D-T1 and 3D-FLAIR volumes. Consistency of relations with disability and average cognition was assessed using linear regression, while correcting for age and sex. The findings were corroborated in an independent validation cohort of 125 MS patients. RESULTS: The ICC between volume measured with FreeSurfer and those measured on 3D-FLAIR for brain, ventricle, cortex, total deep gray matter and thalamus was above 0.74 for SAMSEG and above 0.91 for SynthSeg. Worse disability and lower average cognition were similarly associated with brain (adj. R2 = 0.24-0.27, p < 0.01; adj. R2 = 0.26-0.29, p < 0.001) ventricle (adj. R2 = 0.27-0.28, p < 0.001; adj. R2 = 0.19-0.20, p < 0.001) and deep gray matter volumes (adj. R2 = 0.24-0.28, p < 0.001; adj. R2 = 0.27-0.28, p < 0.001) determined with all methods, except for cortical volumes derived from 3D-FLAIR. DISCUSSION: In this cross-sectional study, brain volumes derived from 3D-FLAIR and 3D-T1 show similar relationships to disability and cognitive dysfunction in MS, highlighting the potential of these techniques in clinical datasets

Disability in multiple sclerosis is related to thalamic connectivity and cortical network atrophy.

BACKGROUND: Thalamic atrophy is proposed to be a major predictor of disability progression in multiple sclerosis (MS), while thalamic function remains understudied. OBJECTIVES: To study how thalamic functional connectivity (FC) is related to disability and thalamic or cortical network atrophy in two large MS cohorts. METHODS: Structural and resting-state functional magnetic resonance imaging (fMRI) was obtained in 673 subjects from Amsterdam (MS: N = 332, healthy controls (HC): N = 96) and Graz (MS: N = 180, HC: N = 65) with comparable protocols, including disability measurements in MS (Expanded Disability Status Scale, EDSS). Atrophy was measured for the thalamus and seven well-recognized resting-state networks. Static and dynamic thalamic FC with these networks was correlated with disability. Significant correlates were included in a backward multivariate regression model. RESULTS: Disability was most strongly related (adjusted R2 = 0.57, p < 0.001) to higher age, a progressive phenotype, thalamic atrophy and increased static thalamic FC with the sensorimotor network (SMN). Static thalamus-SMN FC was significantly higher in patients with high disability (EDSS ⩾ 4) and related to network atrophy but not thalamic atrophy or lesion volumes. CONCLUSION: The severity of disability in MS was related to increased static thalamic FC with the SMN. Thalamic FC changes were only related to cortical network atrophy, but not to thalamic atrophy

Interaction specificity of Arabidopsis 14-3-3 proteins with phototropin receptor kinases

Phototropin receptor kinases play an important roles in optimising plant growth in response to blue light. Much is known regarding their photochemical reactivity, yet little progress has been made to identify downstream signalling components. Here, we isolated several interacting proteins for Arabidopsis phototropin 1 (phot1) by yeast two-hybrid screening. These include members of the NPH3/RPT2 (NRL) protein family, proteins associated with vesicle trafficking, and the 14-3-3 lambda (?) isoform from Arabidopsis . 14-3-3? and phot1 were found to colocalise and interact in vivo. Moreover, 14-3-3 binding to phot1 was limited to non-epsilon 14-3-3 isoforms and was dependent on key sites of receptor autophosphorylation. No 14-3-3 binding was detected for Arabidopsis phot2, suggesting that 14-3-3 proteins represent specific mode of phot1 signalling

Loss of ‘Small-World’ Networks in Alzheimer's Disease: Graph Analysis of fMRI Resting-State Functional Connectivity

BACKGROUND: Local network connectivity disruptions in Alzheimer's disease patients have been found using graph analysis in BOLD fMRI. Other studies using MEG and cortical thickness measures, however, show more global long distance connectivity changes, both in functional and structural imaging data. The form and role of functional connectivity changes thus remains ambiguous. The current study shows more conclusive data on connectivity changes in early AD using graph analysis on resting-state condition fMRI data. METHODOLOGY/PRINCIPAL FINDINGS: 18 mild AD patients and 21 healthy age-matched control subjects without memory complaints were investigated in resting-state condition with MRI at 1.5 Tesla. Functional coupling between brain regions was calculated on the basis of pair-wise synchronizations between regional time-series. Local (cluster coefficient) and global (path length) network measures were quantitatively defined. Compared to controls, the characteristic path length of AD functional networks is closer to the theoretical values of random networks, while no significant differences were found in cluster coefficient. The whole-brain average synchronization does not differ between Alzheimer and healthy control groups. Post-hoc analysis of the regional synchronization reveals increased AD synchronization involving the frontal cortices and generalized decreases located at the parietal and occipital regions. This effectively translates in a global reduction of functional long-distance links between frontal and caudal brain regions. CONCLUSIONS/SIGNIFICANCE: We present evidence of AD-induced changes in global brain functional connectivity specifically affecting long-distance connectivity. This finding is highly relevant for it supports the anterior-posterior disconnection theory and its role in AD. Our results can be interpreted as reflecting the randomization of the brain functional networks in AD, further suggesting a loss of global information integration in disease

A randomized trial predicting response to cognitive rehabilitation in multiple sclerosis:Is there a window of opportunity?

BACKGROUND: Cognitive training elicits mild-to-moderate improvements in cognitive functioning in people with multiple sclerosis (PwMS), although response heterogeneity limits overall effectiveness. OBJECTIVE: To identify patient characteristics associated with response and non-response to cognitive training. METHODS: Eighty-two PwMS were randomized into a 7-week attention training (n = 58, age = 48.4 ± 10.2 years) or a waiting-list control group (n = 24, age = 48.5 ± 9.4 years). Structural and functional magnetic resonance imaging (MRI) was obtained at baseline and post-intervention. Twenty-one healthy controls (HCs, age = 50.27 ± 10.15 years) were included at baseline. Responders were defined with a reliable change index of 1.64 on at least 2/6 cognitive domains. General linear models and logistic regression were applied. RESULTS: Responders (n = 36) and non-responders (n = 22) did not differ on demographics, clinical variables and baseline cognition and structural MRI. However, non-responders exhibited a higher baseline functional connectivity (FC) between the default-mode network (DMN) and the ventral attention network (VAN), compared with responders (p = 0.018) and HCs (p = 0.001). Conversely, responders exhibited no significant baseline differences in FC compared with HCs. Response to cognitive training was predicted by lower DMN-VAN FC (p = 0.004) and DMN-frontoparietal FC (p = 0.029) (Nagelkerke R(2) = 0.25). CONCLUSION: An intact pre-intervention FC is associated with cognitive training responsivity in pwMS, suggesting a window of opportunity for successful cognitive interventions