Quantifying Privacy: A Novel Entropy-Based Measure of Disclosure Risk

It is well recognised that data mining and statistical analysis pose a serious treat to privacy. This is true for financial, medical, criminal and marketing research. Numerous techniques have been proposed to protect privacy, including restriction and data modification. Recently proposed privacy models such as differential privacy and k-anonymity received a lot of attention and for the latter there are now several improvements of the original scheme, each removing some security shortcomings of the previous one. However, the challenge lies in evaluating and comparing privacy provided by various techniques. In this paper we propose a novel entropy based security measure that can be applied to any generalisation, restriction or data modification technique. We use our measure to empirically evaluate and compare a few popular methods, namely query restriction, sampling and noise addition.Comment: 20 pages, 4 figure

Cystinosis: practical tools for diagnosis and treatment

Cystinosis is the major cause of inherited Fanconi syndrome, and should be suspected in young children with failure to thrive and signs of renal proximal tubular damage. The diagnosis can be missed in infants, because not all signs of renal Fanconi syndrome are present during the first months of life. In older patients cystinosis can mimic idiopathic nephrotic syndrome due to focal and segmental glomerulosclerosis. Measuring elevated white blood cell cystine content is the corner stone for the diagnosis. The diagnosis is confirmed by molecular analysis of the cystinosin gene. Corneal cystine crystals are invariably present in all patients with cystinosis after the age of 1 year. Treatment with the cystine depleting drug cysteamine should be initiated as soon as possible and continued lifelong to prolong renal function survival and protect extra-renal organs. This educational feature provides practical tools for the diagnosis and treatment of cystinosis

Hsp90 orchestrates transcriptional regulation by Hsf1 and cell wall remodelling by MAPK signalling during thermal adaptation in a pathogenic yeast

Acknowledgments We thank Rebecca Shapiro for creating CaLC1819, CaLC1855 and CaLC1875, Gillian Milne for help with EM, Aaron Mitchell for generously providing the transposon insertion mutant library, Jesus Pla for generously providing the hog1 hst7 mutant, and Cathy Collins for technical assistance.Peer reviewedPublisher PD

A Profile Likelihood Analysis of the Constrained MSSM with Genetic Algorithms

The Constrained Minimal Supersymmetric Standard Model (CMSSM) is one of the simplest and most widely-studied supersymmetric extensions to the standard model of particle physics. Nevertheless, current data do not sufficiently constrain the model parameters in a way completely independent of priors, statistical measures and scanning techniques. We present a new technique for scanning supersymmetric parameter spaces, optimised for frequentist profile likelihood analyses and based on Genetic Algorithms. We apply this technique to the CMSSM, taking into account existing collider and cosmological data in our global fit. We compare our method to the MultiNest algorithm, an efficient Bayesian technique, paying particular attention to the best-fit points and implications for particle masses at the LHC and dark matter searches. Our global best-fit point lies in the focus point region. We find many high-likelihood points in both the stau co-annihilation and focus point regions, including a previously neglected section of the co-annihilation region at large m_0. We show that there are many high-likelihood points in the CMSSM parameter space commonly missed by existing scanning techniques, especially at high masses. This has a significant influence on the derived confidence regions for parameters and observables, and can dramatically change the entire statistical inference of such scans.Comment: 47 pages, 8 figures; Fig. 8, Table 7 and more discussions added to Sec. 3.4.2 in response to referee's comments; accepted for publication in JHE

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

HIV-1 Disease Progression Is Associated with Bile-Salt Stimulated Lipase (BSSL) Gene Polymorphism

Background: DC-SIGN expressed by dendritic cells captures HIV-1 resulting in trans-infection of CD4+ T-lymphocytes. However, BSSL (bile-salt stimulated lipase) binding to DC-SIGN interferes with HIV-1 capture. DC-SIGN binding properties of BSSL associate with the polymorphic repeated motif of BSSL exon 11. Furthermore, BSSL binds to HIV-1 co-receptor CXCR4. We hypothesized that BSSL modulates HIV-1 disease progression and emergence of CXCR4 using HIV-1 (X4) variants. Results: The relation between BSSL genotype and HIV-1 disease progression and emergence of X4 variants was studied using Kaplan Meier and multivariate Cox proportional hazard analysis in a cohort of HIV-1 infected men having sex with men (n = 334, with n = 130 seroconverters). We analyzed the association of BSSL genotype with set-point viral load and CD4 cell count, both pre-infection and post-infection at viral set-point. The number of repeats in BSSL exon 11 were highly variable ranging from 10 to 18 in seropositive individuals and from 5-17 in HRSN with 16 repeats being dominant (>80% carry at least one allele with 16 repeats). We defined 16 to 18 repeats as high (H) and less than 16 repeats as low (L) repeat numbers. Homozygosity for the high (H) repeat number BSSL genotype (HH) correlated with high CD4 cell numbers prior to infection (p = 0.007). In HIV-1 patients, delayed disease progression was linked to the HH BSSL genotype (RH = 0.462 CI = 0.282-0.757, p = 0.002) as was delayed emergence of X4 variants (RH = 0.525, 95% CI = 0.290-0.953, p = 0.034). The LH BSSL genotype, previously found to be associated with enhanced DC-SIGN binding of human milk, was identified to correlate with accelerated disease progression in our cohort of HIV-1 infected MSM (RH = 0.517, 95% CI = 0.328-0.818, p = 0.005). Conclusion: We identify BSSL as a marker for HIV-1 disease progression and emergence of X4 variants. Additionally, we identified a relation between BSSL genotype and CD4 cell counts prior to infectio

Generalized Connective Tissue Disease in Crtap-/- Mouse

Mutations in CRTAP (coding for cartilage-associated protein), LEPRE1 (coding for prolyl 3-hydroxylase 1 [P3H1]) or PPIB (coding for Cyclophilin B [CYPB]) cause recessive forms of osteogenesis imperfecta and loss or decrease of type I collagen prolyl 3-hydroxylation. A comprehensive analysis of the phenotype of the Crtap-/- mice revealed multiple abnormalities of connective tissue, including in the lungs, kidneys, and skin, consistent with systemic dysregulation of collagen homeostasis within the extracellular matrix. Both Crtap-/- lung and kidney glomeruli showed increased cellular proliferation. Histologically, the lungs showed increased alveolar spacing, while the kidneys showed evidence of segmental glomerulosclerosis, with abnormal collagen deposition. The Crtap-/- skin had decreased mechanical integrity. In addition to the expected loss of proline 986 3-hydroxylation in α1(I) and α1(II) chains, there was also loss of 3Hyp at proline 986 in α2(V) chains. In contrast, at two of the known 3Hyp sites in α1(IV) chains from Crtap-/- kidneys there were normal levels of 3-hydroxylation. On a cellular level, loss of CRTAP in human OI fibroblasts led to a secondary loss of P3H1, and vice versa. These data suggest that both CRTAP and P3H1 are required to maintain a stable complex that 3-hydroxylates canonical proline sites within clade A (types I, II, and V) collagen chains. Loss of this activity leads to a multi-systemic connective tissue disease that affects bone, cartilage, lung, kidney, and skin

Country-specific birth weight and length in type 1 diabetes high-risk HLA genotypes in combination with prenatal characteristics

Objective:To examine the relationship between high-risk human leukocyte antigen (HLA) genotypes for type 1 diabetes and birth size in combination with prenatal characteristics in different countries.Study Design:Four high-risk HLA genotypes were enrolled in the Environmental determinants of Diabetes in the Young study newborn babies from the general population in Finland, Germany, Sweden and the United States. Stepwise regression analyses were used to adjust for country, parental physical characteristics and environmental factors during pregnancy.Result:Regression analyses did not reveal differences in birth size between the four type 1 diabetes high-risk HLA genotypes. Compared with DQ 4/8 in each country, (1) DQ 2/2 children were heavier in the United States (P=0.028) mostly explained however, by parental weight; (2) DQ 2/8 (P=0.023) and DQ 8/8 (P=0.046) children were longer in Sweden independent of parents height and as well as (3) in the United States for DQ 2/8 (P=0.023), but again dependent on parental height.Conclusion:Children born with type 1 diabetes high-risk HLA genotypes have comparable birth size. Longitudinal follow-up of these children should reveal whether birth size differences between countries contribute to the risk for islet autoimmunity and type 1 diabetes.Journal of Perinatology advance online publication, 28 April 2011; doi:10.1038/jp.2011.26