1,466 research outputs found
Spectral Graph Convolutions for Population-based Disease Prediction
Exploiting the wealth of imaging and non-imaging information for disease
prediction tasks requires models capable of representing, at the same time,
individual features as well as data associations between subjects from
potentially large populations. Graphs provide a natural framework for such
tasks, yet previous graph-based approaches focus on pairwise similarities
without modelling the subjects' individual characteristics and features. On the
other hand, relying solely on subject-specific imaging feature vectors fails to
model the interaction and similarity between subjects, which can reduce
performance. In this paper, we introduce the novel concept of Graph
Convolutional Networks (GCN) for brain analysis in populations, combining
imaging and non-imaging data. We represent populations as a sparse graph where
its vertices are associated with image-based feature vectors and the edges
encode phenotypic information. This structure was used to train a GCN model on
partially labelled graphs, aiming to infer the classes of unlabelled nodes from
the node features and pairwise associations between subjects. We demonstrate
the potential of the method on the challenging ADNI and ABIDE databases, as a
proof of concept of the benefit from integrating contextual information in
classification tasks. This has a clear impact on the quality of the
predictions, leading to 69.5% accuracy for ABIDE (outperforming the current
state of the art of 66.8%) and 77% for ADNI for prediction of MCI conversion,
significantly outperforming standard linear classifiers where only individual
features are considered.Comment: International Conference on Medical Image Computing and
Computer-Assisted Interventions (MICCAI) 201
Clinical outcome of SARS-CoV-2 infection in 7 adults with Duchenne muscular dystrophy attending a specialist neuromuscular centre
Due to their frailty and cardiorespiratory compromise adults with DMD are considered extremely vulnerable and at high risk of severe infection should they contract COVID-19. We report 7 adults with DMD aged 17–26 years who tested positive on a nasopharyngeal PCR swab for SARS-CoV-2. Despite long term corticosteroid treatment, severe respiratory compromise requiring night-time ventilation and receiving treatment for moderate to severe cardiomyopathy, none of the patients developed moderate to severe symptoms; in fact two remained asymptomatic and two developed only anosmia and reduced sensation. The remaining three developed transient fever with or without sore throat, cough and runny nose. All recovered fully without complication and no patient required hospitalization
Linear models of activation cascades: analytical solutions and coarse-graining of delayed signal transduction
Cellular signal transduction usually involves activation cascades, the
sequential activation of a series of proteins following the reception of an
input signal. Here we study the classic model of weakly activated cascades and
obtain analytical solutions for a variety of inputs. We show that in the
special but important case of optimal-gain cascades (i.e., when the
deactivation rates are identical) the downstream output of the cascade can be
represented exactly as a lumped nonlinear module containing an incomplete gamma
function with real parameters that depend on the rates and length of the
cascade, as well as parameters of the input signal. The expressions obtained
can be applied to the non-identical case when the deactivation rates are random
to capture the variability in the cascade outputs. We also show that cascades
can be rearranged so that blocks with similar rates can be lumped and
represented through our nonlinear modules. Our results can be used both to
represent cascades in computational models of differential equations and to fit
data efficiently, by reducing the number of equations and parameters involved.
In particular, the length of the cascade appears as a real-valued parameter and
can thus be fitted in the same manner as Hill coefficients. Finally, we show
how the obtained nonlinear modules can be used instead of delay differential
equations to model delays in signal transduction.Comment: 18 pages, 7 figure
Novel Neurovascular Protective Agents: Effects of INV-155, INV-157, INV-159, and INV-161 versus Lipoic Acid and Captopril in a Rat Stroke Model
Background. Lipoic acid (LA), which has significant antioxidant properties, may also function as a potent neuroprotectant. The synthetic compounds INV-155, INV-157, INV-159, and INV-161 are physiochemical combinations of lipoic acid and captopril. We sought to determine if these compounds have neuroprotective potential following middle cerebral artery occlusion (MCAO) in rats. Methods. Male Sprague-Dawley rats were injected intravenously with captopril (1–50 mg/kg) 30 minutes prior to MCAO. Blood pressure, heart rate, baroreceptor reflex sensitivity, and infarct size were measured. In addition, dose response effect on infarct size and cardiovascular parameters was determined using INV-155, INV-157, INV-159, and INV-161 and compared to captopril and LA. Results. Pretreatment with captopril and LA at all doses tested was neuroprotective. The compounds INV-159 (0.5–10 mg/kg) and INV-161 (1–10 mg/kg) produced a significant,dose-dependent decrease in infarct size. In contrast, INV-155 and INV-157 had no effect on infarct size. Conclusions. Combined pretreatment with captopril potentiated the neuroprotective benefit observed following LA alone. Both INV-159 and INV-161 were also neuroprotective. These results suggest that patients taking combinations of captopril and LA, either as combination therapy or in the form of INV-159 or INV-161, may also benefit from significant protection against cerebral infarction
Evaluating 35 Methods to Generate Structural Connectomes Using Pairwise Classification
There is no consensus on how to construct structural brain networks from
diffusion MRI. How variations in pre-processing steps affect network
reliability and its ability to distinguish subjects remains opaque. In this
work, we address this issue by comparing 35 structural connectome-building
pipelines. We vary diffusion reconstruction models, tractography algorithms and
parcellations. Next, we classify structural connectome pairs as either
belonging to the same individual or not. Connectome weights and eight
topological derivative measures form our feature set. For experiments, we use
three test-retest datasets from the Consortium for Reliability and
Reproducibility (CoRR) comprised of a total of 105 individuals. We also compare
pairwise classification results to a commonly used parametric test-retest
measure, Intraclass Correlation Coefficient (ICC).Comment: Accepted for MICCAI 2017, 8 pages, 3 figure
Cytoskeletal changes during poliovirus infection in an intestinal cell line
Background and Objectives: Although polioviral replication has been extensively studied, cytoskeletal changes in the host cell during poliovirus replication have not been extensively investigated. We studied the ultrastructural and cytoskeletal changes in host cells during poliovirus infection. Methods: Fluorescence staining of filamentous actin with a fluorescein-isothiocynate labelled mycotoxin, in the absence and presence of microfilament inhibitors cytochalasins B and D, and electron microscopy were used to investigate the role and fate of actin microfilaments during poliovirus infection, morphogenesis and release in an intestinal cell line, HRT-18. Results: At 10 h post-infection, fluorescence staining of actin showed focal areas of fluorescence in the cytoplasm. By 16 h, these became more prominent and increased in number, and by 18-22 h they coalesced to enclose areas of the cytoplasm. These changes in the actin profile were confirmed by electron microscopy, where small actin bundles appeared in association with vesicles, increased in size, number and thickness, enclosed areas of cytoplasm with numerous vesicles and were finally seen in association with crystalline arrays of virus near the periphery of the cells. The addition of microfilament inhibitors cytochalasins B and D, after the initial period of adsorption resulted in complete inhibition of changes in the actin profile and of viral release, indicating that microfilament inhibitors prevented both polymerization of actin and movement of the virus within the cell. Interpretation and Conclusion: In poliovirus infection, both intracellular movement and release of virus appear to be related to cytoskeletal changes, particularly involving actin microfilaments
Cosmological models with bulk viscosity in presence of adiabatic matter creation and with G, c and Lambda variables
Some properties of cosmological models with a time variable bulk viscous
coefficient in presence of adiabatic mater creation and G, c, Lambda variables
are investigated in the framework of flat FRW line element. We trivially find a
set of solutions through Dimensional Analysis. In all the studied cases it is
found that the behaviour of these constants is inversely prportional to the
cosmic time.Comment: 12 pages. We have been rewriting and completing the bibliography of
this paper. Submitted to General Relativity and Gravitatio
A double-blinded randomised controlled trial exploring the effect of anodal transcranial direct current stimulation and uni-lateral robot therapy for the impaired upper limb in sub-acute and chronic stroke
BACKGROUND:Neurorehabilitation technologies such as robot therapy (RT) and transcranial Direct Current Stimulation (tDCS) can promote upper limb (UL) motor recovery after stroke. OBJECTIVE:To explore the effect of anodal tDCS with uni-lateral and three-dimensional RT for the impaired UL in people with sub-acute and chronic stroke. METHODS:A pilot randomised controlled trial was conducted. Stroke participants had 18 one-hour sessions of RT (Armeo®Spring) over eight weeks during which they received 20 minutes of either real tDCS or sham tDCS during each session. The primary outcome measure was the Fugl-Meyer assessment (FMA) for UL impairments and secondary were: UL function, activities and stroke impact collected at baseline, post-intervention and three-month follow-up. RESULTS:22 participants (12 sub-acute and 10 chronic) completed the trial. No significant difference was found in FMA between the real and sham tDCS groups at post-intervention and follow-up (p = 0.123). A significant ‘time’ x ‘stage of stroke’ was found for FMA (p = 0.016). A higher percentage improvement was noted in UL function, activities and stroke impact in people with sub-acute compared to chronic stroke. CONCLUSIONS:Adding tDCS did not result in an additional effect on UL impairment in stroke. RT may be of more benefit in the sub-acute than chronic phase
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