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Myasthenia gravis (MG) is a rare condition that impairs function at the neuromuscular junction of skeletal muscles, seen less commonly in children. Causes include autoimmune MG, congenital myasthenic syndromes, and transient neonatal myasthenia gravis. Symptoms of weakness, hypotonia, and fatigability can be reasonably explained by more common causes, thus children with MG disorders commonly experience delays in treatment with severe consequences. This leads to the progression of disease and serious complications including myasthenic crises and exacerbations. We describe 5 cases of MG, which illustrate clinical and genetic challenges in establishing diagnosis and subsequent consequences of delayed diagnosis., Competing Interests: Disclosure The authors have nothing to disclose., (Copyright © 2023 Elsevier Inc. All rights reserved.)

The ICML 2013 Workshop on Challenges in Representation Learning(1) focused on three challenges: the black box learning challenge, the facial expression recognition challenge, and the multimodal learning challenge. We describe the datasets created for these challenges and summarize the results of the competitions. We provide suggestions for organizers of future challenges and some comments on what kind of knowledge can be gained from machine learning competitions., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

A recent application of a crowd computing platform to develop highly predictive in silico models for use in the drug discovery process is described. The platform, Kaggle™, exploits a competitive dynamic that results in model optimization as the competition unfolds. Here, this dynamic is described in detail and compared with more-conventional modeling strategies. The complete and full structure of the underlying dataset is disclosed and some thoughts as to the broader utility of such 'gamification' approaches to the field of modeling are offered., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

Motor imagery (MI) brain-computer interfaces (BCIs) translate a subject's motor intention to a command signal. Most MI BCIs use power features in the mu or beta rhythms, while several results have been reported using a measure of phase synchrony, the phase-locking value (PLV). In this study, we investigated the performance of various phase-based features, including instantaneous phase difference (IPD) and PLV, for control of a MI BCI. Patterns of phase synchrony differentially appear over the motor cortices and between the primary motor cortex (M1) and supplementary motor area (SMA) during MI. Offline results, along with preliminary online sessions, indicate that IPD serves as a robust control signal for differentiating between MI classes, and that the phase relations between channels are relatively stable over several months. Offline and online trial-level classification accuracies based on IPD ranged from 84% to 99%, whereas the performance for the corresponding amplitude features ranged from 70% to 100%.

Background: We evaluated the potential of bioluminescence imaging (BLI) for early tumor detection, demonstrating occult sites of disseminated disease and assessing disease progression in a murine model of neuroblastoma., Methods: Neuroblastoma cells engineered to express the enzyme firefly luciferase were used to establish localized tumors and disseminated disease in SCID mice. Bioluminescent signal intensity was measured at serial time points, and compared with traditional methods of evaluating tumor growth., Results: Bioluminescence imaging detected subcutaneous and retroperitoneal tumors weeks before they were palpable or appreciable by ultrasound. Bioluminescent signal intensity at both sites then paralleled tumor growth. After intravenous administration of tumor cells, BLI revealed disseminated disease in the liver, lungs, and bone marrow, again weeks before any gross disease was present. The presence of tumor within these sites at early time points was confirmed by reverse transcriptase-polymerase chain reaction. Finally, BLI permitted a real-time, noninvasive, quantitative method for following response to therapy in a model of minimal residual disease., Conclusion: Bioluminescence imaging detects tumor much earlier than traditional methods. In addition, it can detect, quantify, and follow micrometastasis in real-time during disease progression. This methodology is extremely valuable for studying tumor tissue tropism, mechanisms of metastasis, and response to therapy in murine tumor models.

Cancers are believed to arise from cancer stem cells (CSCs), but it is not known if these cells remain dependent upon the niche microenvironments that regulate normal stem cells. We show that endothelial cells interact closely with self-renewing brain tumor cells and secrete factors that maintain these cells in a stem cell-like state. Increasing the number of endothelial cells or blood vessels in orthotopic brain tumor xenografts expanded the fraction of self-renewing cells and accelerated the initiation and growth of tumors. Conversely, depletion of blood vessels from xenografts ablated self-renewing cells from tumors and arrested tumor growth. We propose that brain CSCs are maintained within vascular niches that are important targets for therapeutic approaches.