507 research outputs found
DeepPrivacy: A Generative Adversarial Network for Face Anonymization
We propose a novel architecture which is able to automatically anonymize
faces in images while retaining the original data distribution. We ensure total
anonymization of all faces in an image by generating images exclusively on
privacy-safe information. Our model is based on a conditional generative
adversarial network, generating images considering the original pose and image
background. The conditional information enables us to generate highly realistic
faces with a seamless transition between the generated face and the existing
background. Furthermore, we introduce a diverse dataset of human faces,
including unconventional poses, occluded faces, and a vast variability in
backgrounds. Finally, we present experimental results reflecting the capability
of our model to anonymize images while preserving the data distribution, making
the data suitable for further training of deep learning models. As far as we
know, no other solution has been proposed that guarantees the anonymization of
faces while generating realistic images.Comment: Accepted to ISVC 201
Routes for breaching and protecting genetic privacy
We are entering the era of ubiquitous genetic information for research,
clinical care, and personal curiosity. Sharing these datasets is vital for
rapid progress in understanding the genetic basis of human diseases. However,
one growing concern is the ability to protect the genetic privacy of the data
originators. Here, we technically map threats to genetic privacy and discuss
potential mitigation strategies for privacy-preserving dissemination of genetic
data.Comment: Draft for comment
Population genetics of trypanosoma brucei rhodesiense: clonality and diversity within and between foci
African trypanosomes are unusual among pathogenic protozoa in that they can undergo their complete morphological life cycle in the tsetse fly vector with mating as a non-obligatory part of this development. Trypanosoma brucei rhodesiense, which infects humans and livestock in East and Southern Africa, has classically been described as a host-range variant of the non-human infective Trypanosoma brucei that occurs as stable clonal lineages. We have examined T. b. rhodesiense populations from East (Uganda) and Southern (Malawi) Africa using a panel of microsatellite markers, incorporating both spatial and temporal analyses. Our data demonstrate that Ugandan T. b. rhodesiense existed as clonal populations, with a small number of highly related genotypes and substantial linkage disequilibrium between pairs of loci. However, these populations were not stable as the dominant genotypes changed and the genetic diversity also reduced over time. Thus these populations do not conform to one of the criteria for strict clonality, namely stability of predominant genotypes over time, and our results show that, in a period in the mid 1990s, the previously predominant genotypes were not detected but were replaced by a novel clonal population with limited genetic relationship to the original population present between 1970 and 1990. In contrast, the Malawi T. b. rhodesiense population demonstrated significantly greater diversity and evidence for frequent genetic exchange. Therefore, the population genetics of T. b. rhodesiense is more complex than previously described. This has important implications for the spread of the single copy T. b. rhodesiense gene that allows human infectivity, and therefore the epidemiology of the human disease, as well as suggesting that these parasites represent an important organism to study the influence of optional recombination upon population genetic dynamics
A major genetic locus in <i>Trypanosoma brucei</i> is a determinant of host pathology
The progression and variation of pathology during infections can be due to components from both host or pathogen, and/or the interaction between them. The influence of host genetic variation on disease pathology during infections with trypanosomes has been well studied in recent years, but the role of parasite genetic variation has not been extensively studied. We have shown that there is parasite strain-specific variation in the level of splenomegaly and hepatomegaly in infected mice and used a forward genetic approach to identify the parasite loci that determine this variation. This approach allowed us to dissect and identify the parasite loci that determine the complex phenotypes induced by infection. Using the available trypanosome genetic map, a major quantitative trait locus (QTL) was identified on T. brucei chromosome 3 (LOD = 7.2) that accounted for approximately two thirds of the variance observed in each of two correlated phenotypes, splenomegaly and hepatomegaly, in the infected mice (named <i>TbOrg1</i>). In addition, a second locus was identified that contributed to splenomegaly, hepatomegaly and reticulocytosis (<i>TbOrg2</i>). This is the first use of quantitative trait locus mapping in a diploid protozoan and shows that there are trypanosome genes that directly contribute to the progression of pathology during infections and, therefore, that parasite genetic variation can be a critical factor in disease outcome. The identification of parasite loci is a first step towards identifying the genes that are responsible for these important traits and shows the power of genetic analysis as a tool for dissecting complex quantitative phenotypic traits
In vivo tau pathology is associated with synaptic loss and altered synaptic function
BACKGROUND: The mechanism of synaptic loss in Alzheimer’s disease is poorly understood and may be associated with tau pathology. In this combined positron emission tomography (PET) and magnetoencephalography (MEG) study, we aimed to investigate spatial associations between regional tau pathology ([{18}^F]flortaucipir PET), synaptic density (synaptic vesicle 2A [11C]UCB-J PET) and synaptic function (MEG) in Alzheimer’s disease. METHODS: Seven amyloid-positive Alzheimer’s disease subjects from the Amsterdam Dementia Cohort underwent dynamic 130-minV [{18}^F]flortaucipir PET, dynamic 60-min [{11}^C]UCB-J PET with arterial sampling and 2 × 5-min resting-state MEG measurement. [{18^}F]flortaucipir- and [{11}^C]UCB-J-specific binding (binding potential, BPND) and MEG spectral measures (relative delta, theta and alpha power; broadband power; and peak frequency) were assessed in cortical brain regions of interest. Associations between regional [{18}^F]flortaucipir BPND, [{11}^C]UCB-J BP_{ND} and MEG spectral measures were assessed using Spearman correlations and generalized estimating equation models. RESULTS: Across subjects, higher regional [{18}^F]flortaucipir uptake was associated with lower [{11}^C]UCB-J uptake. Within subjects, the association between [{11}^C]UCB-J and [{18}^F]flortaucipir depended on within-subject neocortical tau load; negative associations were observed when neocortical tau load was high, gradually changing into opposite patterns with decreasing neocortical tau burden. Both higher [{18}^F]flortaucipir and lower [{11}^C]UCB-J uptake were associated with altered synaptic function, indicative of slowing of oscillatory activity, most pronounced in the occipital lobe. CONCLUSIONS: These results indicate that in Alzheimer’s disease, tau pathology is closely associated with reduced synaptic density and synaptic dysfunction
Adaptive Evolution of the Myo6 Gene in Old World Fruit Bats (Family: Pteropodidae)
PMCID: PMC3631194This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Polymorphisms of the prion protein gene and their effects on litter size and risk evaluation for scrapie in Chinese Hu sheep
It is well known that scrapie is a fatal, neurodegenerative disease in sheep and goat, which belongs to the group of transmissible spongiform encephalopathies (TSEs) or prion diseases. It has been confirmed that the polymorphisms of prion protein gene (PRNP) at codons 136, 154, and 171 have strong relationship with scrapie in sheep. In the present study, nine polymorphisms of PRNP at codons 136, 154, and 171 and other six loci (at codons 101, 112, 127, 137, 138, and 152) were detected in 180 Chinese Hu sheep. All the alleles at codons 136, 154, and 171 have been identified and resulted in three new genotypes. The frequencies of predominant alleles were 85% (A136), 99.40% (R154), and 37.78% (Q171), respectively. The predominant haplotype ARQ has a relatively high frequency of 57.77%. The frequencies of dominant genotypes of ARR/ARQ and ARQ/ARQ were 30 and 26.67%, respectively. Three new found genotypes named ARQ/TRK, ARQ/TRR, and TRR/TRQ had the same lower frequencies (0.56%). The relationship of PRNP genotype with scrapie risk and litter size showed that the predominant genotypes are corresponded to the risk score of R1 (1.67%), R2 (32.22%), and R3 (42.22%). Just at the first parity, the individuals with ARH/ARH genotype had significantly larger litter size than the mean value and those with ARQ/ARQ and ARR/ARQ genotypes. In short, this study provided preliminary information about alleles and genotypes of PRNP in Chinese Hu sheep. It could be concluded that Hu sheep has a low susceptibility to natural scrapie, and the predominant PRNP genotype at least has no significant effect on litter size
A Myo6 Mutation Destroys Coordination between the Myosin Heads, Revealing New Functions of Myosin VI in the Stereocilia of Mammalian Inner Ear Hair Cells
Myosin VI, found in organisms from Caenorhabditis elegans to humans, is essential for auditory and vestibular function in mammals, since genetic mutations lead to hearing impairment and vestibular dysfunction in both humans and mice. Here, we show that a missense mutation in this molecular motor in an ENU-generated mouse model, Tailchaser, disrupts myosin VI function. Structural changes in the Tailchaser hair bundles include mislocalization of the kinocilia and branching of stereocilia. Transfection of GFP-labeled myosin VI into epithelial cells and delivery of endocytic vesicles to the early endosome revealed that the mutant phenotype displays disrupted motor function. The actin-activated ATPase rates measured for the D179Y mutation are decreased, and indicate loss of coordination of the myosin VI heads or ‘gating’ in the dimer form. Proper coordination is required for walking processively along, or anchoring to, actin filaments, and is apparently destroyed by the proximity of the mutation to the nucleotide-binding pocket. This loss of myosin VI function may not allow myosin VI to transport its cargoes appropriately at the base and within the stereocilia, or to anchor the membrane of stereocilia to actin filaments via its cargos, both of which lead to structural changes in the stereocilia of myosin VI–impaired hair cells, and ultimately leading to deafness
Does gamma-aminobutyric acid (GABA) influence the development of chronic inflammation in rheumatoid arthritis?
<p>Abstract</p> <p>Background</p> <p>Recent studies have demonstrated a role for spinal p38 MAP kinase (MAPK) in the development of chronic inflammation and peripheral arthritis and a role for GABA in the inhibition of p38 MAPK mediated effects. Integrating these data suggests that GABA may play a role in downregulating mechanisms that lead to the production of proinflammatory agents such as interleukin-1, interleukin-6, and matrix metalloproteinase 3 – agents implicated in the pathogenesis of rheumatoid arthritis (RA). Genetic studies have also associated RA with members of the p38 MAPK pathway.</p> <p>Hypothesis</p> <p>We propose a hypothesis for an inefficient GABA signaling system that results in unchecked proinflammatory cytokine production via the p38 MAPK pathway. This model also supports the need for increasing research in the integration of immunology and neuroscience.</p
Automatic de-identification of textual documents in the electronic health record: a review of recent research
<p>Abstract</p> <p>Background</p> <p>In the United States, the Health Insurance Portability and Accountability Act (HIPAA) protects the confidentiality of patient data and requires the informed consent of the patient and approval of the Internal Review Board to use data for research purposes, but these requirements can be waived if data is de-identified. For clinical data to be considered de-identified, the HIPAA "Safe Harbor" technique requires 18 data elements (called PHI: Protected Health Information) to be removed. The de-identification of narrative text documents is often realized manually, and requires significant resources. Well aware of these issues, several authors have investigated automated de-identification of narrative text documents from the electronic health record, and a review of recent research in this domain is presented here.</p> <p>Methods</p> <p>This review focuses on recently published research (after 1995), and includes relevant publications from bibliographic queries in PubMed, conference proceedings, the ACM Digital Library, and interesting publications referenced in already included papers.</p> <p>Results</p> <p>The literature search returned more than 200 publications. The majority focused only on structured data de-identification instead of narrative text, on image de-identification, or described manual de-identification, and were therefore excluded. Finally, 18 publications describing automated text de-identification were selected for detailed analysis of the architecture and methods used, the types of PHI detected and removed, the external resources used, and the types of clinical documents targeted. All text de-identification systems aimed to identify and remove person names, and many included other types of PHI. Most systems used only one or two specific clinical document types, and were mostly based on two different groups of methodologies: pattern matching and machine learning. Many systems combined both approaches for different types of PHI, but the majority relied only on pattern matching, rules, and dictionaries.</p> <p>Conclusions</p> <p>In general, methods based on dictionaries performed better with PHI that is rarely mentioned in clinical text, but are more difficult to generalize. Methods based on machine learning tend to perform better, especially with PHI that is not mentioned in the dictionaries used. Finally, the issues of anonymization, sufficient performance, and "over-scrubbing" are discussed in this publication.</p
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