Acute transverse myelitis and psoriasiform dermatitis associated with Sjoegren’s syndrome: a case report

BACKGROUND: Clinical complications of Sjoegren’s syndrome include myelitis and skin manifestations. There is scarce observational data and a lack of randomised controlled studies regarding the treatment of Sjoegren’s syndrome in the presence of such complications. CASE PRESENTATION: Here we report the case of a 41-year-old Caucasian female patient with biopsy-proven Sjoegren’s syndrome who initially presented with generalized exanthema and subsequently developed acute extensive transverse myelitis. In view of the rapid deterioration we opted for an intensive treatment using a combination of corticosteroid pulse therapy, plasmapheresis and cyclophosphamide, which we later changed to rituximab. Under that treatment the skin manifestations resolved entirely whereas transverse myelitis showed incomplete remission. CONCLUSION: Severe neurological and dermatological complications may occur in Sjoegren’s syndrome. This suggests a close yet currently unclear pathogenetic relationship. Intensive immunosuppressant treatment resulted in significant improvement of both symptom clusters. Skin manifestations may precede other severe complications in Sjoegren’s syndrome and therefore require particular attention

Spatial signatures of anesthesia-induced burst-suppression differ between primates and rodents

During deep anesthesia, the electroencephalographic (EEG) signal of the brain alternates between bursts of activity and periods of relative silence (suppressions). The origin of burst-suppression and its distribution across the brain remain matters of debate. In this work, we used functional magnetic resonance imaging (fMRI) to map the brain areas involved in anesthesia-induced burst-suppression across four mammalian species: humans, long-tailed macaques, common marmosets, and rats. At first, we determined the fMRI signatures of burst-suppression in human EEG-fMRI data. Applying this method to animal fMRI datasets, we found distinct burst-suppression signatures in all species. The burst-suppression maps revealed a marked inter-species difference: in rats, the entire neocortex engaged in burst-suppression, while in primates most sensory areas were excluded-predominantly the primary visual cortex. We anticipate that the identified species-specific fMRI signatures and whole-brain maps will guide future targeted studies investigating the cellular and molecular mechanisms of burst-suppression in unconscious states

Brain network integration dynamics are associated with loss and recovery of consciousness induced by sevoflurane

Funder: Canadian Institute for Advanced Research; Id: http://dx.doi.org/10.13039/100007631Funder: Gates Cambridge Trust; Id: http://dx.doi.org/10.13039/501100005370Funder: Queens College CambridgeFunder: Stephen Erskine FellowshipFunder: Royal College Of Anaesthetists; Id: http://dx.doi.org/10.13039/501100001297Funder: British Oxygen ProfessorshipFunder: Technische Universität München; Id: http://dx.doi.org/10.13039/501100005713Abstract: The dynamic interplay of integration and segregation in the brain is at the core of leading theoretical accounts of consciousness. The human brain dynamically alternates between a sub‐state where integration predominates, and a predominantly segregated sub‐state, with different roles in supporting cognition and behaviour. Here, we combine graph theory and dynamic functional connectivity to compare resting‐state functional MRI data from healthy volunteers before, during, and after loss of responsiveness induced with different concentrations of the inhalational anaesthetic, sevoflurane. We show that dynamic states characterised by high brain integration are especially vulnerable to general anaesthesia, exhibiting attenuated complexity and diminished small‐world character. Crucially, these effects are reversed upon recovery, demonstrating their association with consciousness. Higher doses of sevoflurane (3% vol and burst‐suppression) also compromise the temporal balance of integration and segregation in the human brain. Additionally, we demonstrate that reduced anticorrelations between the brain's default mode and executive control networks dynamically reconfigure depending on the brain's state of integration or segregation. Taken together, our results demonstrate that the integrated sub‐state of brain connectivity is especially vulnerable to anaesthesia, in terms of both its complexity and information capacity, whose breakdown represents a generalisable biomarker of loss of consciousness and its recovery

Energy Informatics - Current and Future Research Directions

Due to the increasing importance of producing and consuming energy more sustainably, Energy Informatics (EI) has evolved into a thriving research area within the CS/IS community. The arti- cle attempts to characterize this young and dynamic field of research by de- scribing current EI research topics and methods and provides an outlook of how the field might evolve in the fu- ture. It is shown that two general re- search questions have received the most attention so far and are likely to dominate the EI research agenda in the coming years: How to leverage infor- mation and communication technol- ogy (ICT) to (1) improve energy effi- ciency, and (2) to integrate decentral- ized renewable energy sources into the power grid. Selected EI streams are reviewed, highlighting how the re- spective research questions are broken down into specific research projects and how EI researchers have made con- tributions based on their individual academic background

Fronto-parietal connectivity is a non-static phenomenon with characteristic changes during unconsciousness.

BACKGROUND: It has been previously shown that loss of consciousness is associated with a breakdown of dominating fronto-parietal feedback connectivity as assessed by electroencephalogram (EEG) recordings. Structure and strength of network connectivity may change over time. Aim of the current study is to investigate cortico-cortical connectivity at different time intervals during consciousness and unconsciousness. For this purpose, EEG symbolic transfer entropy (STEn) was calculated to indicate cortico-cortical information transfer at different transfer times. METHODS: The study was performed in 15 male volunteers. 29-channel EEG was recorded during consciousness and propofol-induced unconsciousness. EEG data were analyzed by STEn, which quantifies intensity and directionality of the mutual information flow between two EEG channels. STEn was computed over fronto-parietal channel pair combinations (10 s length, 0.5-45 Hz total bandwidth) to analyze changes of intercortical directional connectivity. Feedback (fronto → parietal) and feedforward (parieto → frontal) connectivity was calculated for transfer times from 25 ms to 250 ms in 5 ms steps. Transfer times leading to maximum directed interaction were identified to detect changes of cortical information transfer (directional connectivity) induced by unconsciousness (p<0.05). RESULTS: The current analyses show that fronto-parietal connectivity is a non-static phenomenon. Maximum detected interaction occurs at decreased transfer times during propofol-induced unconsciousness (feedback interaction: 60 ms to 40 ms, p = 0.002; feedforward interaction: 65 ms to 45 ms, p = 0.001). Strength of maximum feedback interaction decreases during unconsciousness (p = 0.026), while no effect of propofol was observed on feedforward interaction. During both consciousness and unconsciousness, intensity of fronto-parietal interaction fluctuates with increasing transfer times. CONCLUSION: Non-stationarity of directional connectivity may play a functional role for cortical network communication as it shows characteristic changes during propofol-induced unconsciousness

Design criteria for the leg of a walking machine derived by biological inspiration from quadrupedal mammals

International audienc

White-matter lesions drive deep gray-matter atrophy in early multiple sclerosis: support from structural MRI

Background: In MS, the relationship between lesions within cerebral white matter (WM) and atrophy within deep gray matter (GM) is unclear. Objective: To investigate the spatial relationship between WM lesions and deep GM atrophy. Methods: We performed a cross-sectional structural magnetic resonance imaging (MRI) study (3 Tesla) in 249 patients with clinically-isolated syndrome or relapsing-remitting MS (Expanded Disability Status Scale score: median, 1.0; range, 0-4) and in 49 healthy controls. Preprocessing of T1-weighted and fluid-attenuated T2-weighted images resulted in normalized GM images and WM lesion probability maps. We performed two voxel-wise analyses: 1. We localized GM atrophy and confirmed that it is most pronounced within deep GM; 2. We searched for a spatial relationship between WM lesions and deep GM atrophy; to this end we analyzed WM lesion probability maps by voxel-wise multiple regression, including four variables derived from maxima of regional deep GM atrophy (caudate and pulvinar, each left and right). Results: Atrophy of each deep GM region was explained by ipsilateral WM lesion probability, in the area most densely connected to the respective deep GM region. Conclusion: We demonstrated that WM lesions and deep GM atrophy are spatially related. Our results are best compatible with the hypothesis that WM lesions contribute to deep GM atrophy through axonal pathology

Fluctuating character of directional cortical fronto-parietal connectivity in EEG.

<p>Values of directional connectivity (median, 25^th and 75^th percentile) are illustrated with regard to increasing transfer times from 25 ms to 250 ms (A: feedback ; B feedforward ; black: conscious; grey: unconscious).</p

Maximum fronto-parietal EEG connectivity after the first onset (25 ms≤ transfer time ≤80 ms).

<p>The upper diagrams (A: feedback ; B feedforward ) show a significant decrease of transfer time leading to maximum connectivity from consciousness to unconsciousness (grey dots: individual values; black: median with interquartile range; *: p<0.05). The lower diagrams show corresponding values of maximum and in EEG (grey dots: individual values; black: median with interquartile range; *: p<0.05) and values of the surrogate based and (boxplots).</p