FedTruth: Byzantine-Robust and Backdoor-Resilient Federated Learning Framework

Federated Learning (FL) enables collaborative machine learning model training across multiple parties without sharing raw data. However, FL's distributed nature allows malicious clients to impact model training through Byzantine or backdoor attacks, using erroneous model updates. Existing defenses measure the deviation of each update from a 'ground-truth model update.' They often rely on a benign root dataset on the server or use trimmed mean or median for clipping, both methods having limitations. We introduce FedTruth, a robust defense against model poisoning in FL. FedTruth doesn't assume specific data distributions nor requires a benign root dataset. It estimates a global model update with dynamic aggregation weights, considering contributions from all benign clients. Empirical studies demonstrate FedTruth's efficacy in mitigating the impacts of poisoned updates from both Byzantine and backdoor attacks

From Cellular Characteristics to Disease Diagnosis: Uncovering Phenotypes with Supercells

Cell heterogeneity and the inherent complexity due to the interplay of multiple molecular processes within the cell pose difficult challenges for current single-cell biology. We introduce an approach that identifies a disease phenotype from multiparameter single-cell measurements, which is based on the concept of ‘‘supercell statistics’’, a single-cell-based averaging procedure followed by a machine learning classification scheme. We are able to assess the optimal tradeoff between the number of single cells averaged and the number of measurements needed to capture phenotypic differences between healthy and diseased patients, as well as between different diseases that are difficult to diagnose otherwise. We apply our approach to two kinds of single-cell datasets, addressing the diagnosis of a premature aging disorder using images of cell nuclei, as well as the phenotypes of two non-infectious uveitides (the ocular manifestations of Behc¸et’s disease and sarcoidosis) based on multicolor flow cytometry. In the former case, one nuclear shape measurement taken over a group of 30 cells is sufficient to classify samples as healthy or diseased, in agreement with usual laboratory practice. In the latter, our method is able to identify a minimal set of 5 markers that accurately predict Behc¸et’s disease and sarcoidosis. This is the first time that a quantitative phenotypic distinction between these two diseases has been achieved. To obtain this clear phenotypic signature, about one hundred CD8+ T cells need to be measured. Although the molecular markers identified have been reported to be important players in autoimmune disorders, this is the first report pointing out that CD8+ T cells can be used to distinguish two systemic inflammatory diseases. Beyond these specific cases, the approach proposed here is applicable to datasets generated by other kinds of state-of-the-art and forthcoming single-cell technologies, such as multidimensional mass cytometry, single-cell gene expression, and single-cell full genome sequencing techniques.Fil: Candia, Julian Marcelo. University of Maryland; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Física de Líquidos y Sistemas Biológicos. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Física de Líquidos y Sistemas Biológicos; ArgentinaFil: Maunu, Ryan. University of Maryland; Estados UnidosFil: Driscoll, Meghan. University of Maryland; Estados UnidosFil: Biancotto, Angélique. National Institutes of Health; Estados UnidosFil: Dagur, Pradeep. National Institutes of Health; Estados UnidosFil: McCoy Jr., J Philip. National Institutes of Health; Estados UnidosFil: Nida Sen, H.. National Institutes of Health; Estados UnidosFil: Wei, Lai. National Institutes of Health; Estados UnidosFil: Maritan, Amos. Università di Padova; ItaliaFil: Cao, Kan. University of Maryland; Estados UnidosFil: Nussenblatt, Robert B. National Institutes of Health; Estados UnidosFil: Banavar, Jayanth R.. University of Maryland; Estados UnidosFil: Losert, Wolfgang. University of Maryland; Estados Unido

First results of material charging in the space environment

A satellite experiment, designed to measure potential charging of typical thermal control materials at near geosynchronous altitude, was flown as part of the SCATHA program. Direct observations of charging of typical satellite materials in a natural charging event ( 5 keV) are presented. The results show some features which differ significantly from previous laboratory simulations of the environment

Combined Face-Brain Morphology and Associated Neurocognitive Correlates in Fetal Alcohol Spectrum Disorders

BACKGROUND: Since the 1970s, a range of facial, neurostructural, and neurocognitive adverse effects have been shown to be associated with prenatal alcohol exposure. Typically, these effects are studied individually and not in combination. Our objective is to improve the understanding of the teratogenic effects of prenatal alcohol exposure by simultaneously considering face-brain morphology and neurocognitive measures. METHODS: Participants were categorized as control (n = 47), fetal alcohol syndrome (FAS, n = 22), or heavily exposed (HE) prenatally, but not eligible for a FAS diagnosis (HE, n = 50). Structural brain MRI images and high-resolution 3D facial images were analyzed using dense surface models of features of the face and surface shape of the corpus callosum (CC) and caudate nucleus (CN). Asymmetry of the CN was evaluated for correlations with neurocognitive measures. RESULTS: (i) Facial growth delineations for FAS, HE, and controls are replicated for the CN and the CC. (ii) Concordance of clinical diagnosis and face-based control-FAS discrimination improves when the latter is combined with specific brain regions. In particular, midline facial regions discriminate better when combined with a midsagittal profile of the CC. (iii) A subset of HE individuals was identified with FAS-like CN dysmorphism. The average of this HE subset was FAS-like in its facial dysmorphism. (iv) Right-left asymmetry found in the CNs of controls is not apparent for FAS, is diminished for HE, and correlates with neurocognitive measures in the combined FAS and HE population. CONCLUSIONS: Shape analysis which combines facial regions with the CN, and with the CC, better identify those with FAS. CN asymmetry was reduced for FAS compared to controls and is strongly associated with general cognitive ability, verbal learning, and recall in those with prenatal alcohol exposure. This study further extends the brain-behavior relationships known to be vulnerable to alcohol teratogenesis

Simultaneous occurrence of cerebellar medulloblastoma and pituitary adenoma: A case report

This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

Analysis of Overlapped and Noisy Hydrogen/Deuterium Exchange Mass Spectra

This document is the Accepted Manuscript version of a Published Work that appeared in final form in the Journal of the American Chemical Society, copyright © American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see http://doi.org/10.1007/s13361-013-0727-5.Noisy and overlapped mass spectrometry data hinders the sequence coverage that can be obtained from Hydrogen Deuterium exchange analysis, and places a limit on the complexity of the samples that can be studied by this technique. Advances in instrumentation have addressed these limits, but as the complexity of the biological samples under investigation increases, these problems are reencountered. Here we describe the use of binomial distribution fitting with asymmetric linear squares regression for calculating the accurate deuterium content for mass envelopes of low signal or that contain significant overlap. The approach is demonstrated with a test data set of HIV Env gp140 wherein inclusion of the new analysis regime resulted in obtaining exchange data for 42 additional peptides, improving the sequence coverage by 11%. At the same time, the precision of deuterium uptake measurements was improved for nearly every peptide examined. The improved processing algorithms also provide an efficient method for deconvolution of bimodal mass envelopes and EX1 kinetic signatures. All these functions and visualization tools have been implemented in the new version of the freely available software, HX-Express v2