Rosacea and perioral dermatitis: a single‐center retrospective analysis of the clinical presentation of 1032 patients

Background Rosacea is a common chronic inflammatory cutaneous disorder affecting nearly 5.5 % of the adult population. Our aim was to evaluate the prevalence and epidemiology of rosacea and perioral dermatitis (POD) in an ambulatory care setting. Methods We retrospectively analyzed medical data of patients with a confirmed diagnosis of rosacea or perioral dermatitis (POD) presenting at our university hospital outpatient clinic during a 3‐year period. Results Out of 1032 patients, 81.5 % were diagnosed with rosacea and 18.5 % with POD. Overall prevalence was 1.4 % for rosacea and 0.3 % for POD. 69.3 % of the analyzed patients were female. Overall mean age was 49.3 ± 7.7 (1–92) years; the women’s average age was less than the men’s. Patients with POD were younger and predominantly female, whereas patients with phymatous rosacea were older and predominantly male. The most common phenotypes were papulopustular rosacea (68.4 %), erythematotelangiectatic rosacea (22.5 %), and phymatous rosacea (8.0 %). Special forms of rosacea were diagnosed in 15.8 % of the patients; the most frequent were ocular rosacea (6.9 %) and steroid‐induced rosacea (5.4 %). Conclusions The large patient cohort analyzed in our study provides a good estimate of the frequency of the rosacea subtypes, special forms and of perioral dermatitis in a hospital‐based outpatient care setting

Divergent in situ expression of IL-31 and IL-31RA between bullous pemphigoid and pemphigus vulgaris

Bullous pemphigoid (BP) and pemphigus vulgaris (PV) are two major autoimmune blistering skin diseases. Unlike PV, BP is accompanied by intense pruritus, suggesting possible involvement of the pruritogenic cytokine IL-31. However, the underlying mechanisms of the clinical difference between BP and PV in terms of pruritus are not fully understood. To compare the expression levels of IL-31 and its receptor IL-31RA in the lesional skin, including peripheral nerves in BP and PV patients, immunohistochemical staining for IL-31 and IL-31RA was performed in skin samples of BP and PV patients and healthy controls (HC). The IL-31RA-expressing area in epidermis and peripheral nerves was analysed using ImageJ and the percentage of positive cells for IL-31/IL-31RA in dermal infiltrating cells was manually quantified. Quantitative analyses revealed that IL-31/IL-31RA expressions in the epidermis and dermal infiltrate were significantly increased in BP compared to PV and HC. The difference between BP and PV became more obvious when advanced bullous lesions were compared. Peripheral nerves in BP lesions presented significantly higher IL-31RA expression compared to PV lesions. In conclusion, we found significantly augmented expressions of IL-31/IL-31RA in BP lesions, including peripheral nerves, in comparison to PV. These results suggest a possible contribution of IL-31/IL-31RA signalling to the difference between BP and PV in the facilitation of pruritus and local skin inflammation, raising the possibility of therapeutic targeting of the IL-31/IL-31RA pathway in BP patients

BARD1 serum autoantibodies for the detection of lung cancer

Purpose Currently the screening for lung cancer for risk groups is based on Computed Tomography (CT) or low dose CT (LDCT); however, the lung cancer death rate has not decreased significantly with people undergoing LDCT. We aimed to develop a simple reliable blood test for early detection of all types of lung cancer based on the immunogenicity of aberrant forms of BARD1 that are specifically upregulated in lung cancer. Methods ELISA assays were performed with a panel of BARD1 epitopes to detect serum levels of antibodies against BARD1 epitopes. We tested 194 blood samples from healthy donors and lung cancer patients with a panel of 40 BARD1 antigens. Using fitted Lasso logistic regression we determined the optimal combination of BARD1 antigens to be used in ELISA for discriminating lung cancer from healthy controls. Random selection of samples for training sets or validations sets was applied to validate the accuracy of our test. Results Fitted Lasso logistic regression models predict high accuracy of the BARD1 autoimmune antibody test with an AUC = 0.96. Validation in independent samples provided and AUC = 0.86 and identical AUCs were obtained for combined stages 1-3 and late stage 4 lung cancers. The BARD1 antibody test is highly specific for lung cancer and not breast or ovarian cancer. Conclusion The BARD1 lung cancer test shows higher sensitivity and specificity than previously published blood tests for lung cancer detection and/or diagnosis or CT scans, and it could detect all types and all stages of lung cancer. This BARD1 lung cancer test could therefore be further developed as i) screening test for early detection of lung cancers in high-risk groups, and ii) diagnostic aid in complementing CT scan

Wavelet penalized likelihood estimation in generalized functional models

The paper deals with generalized functional regression. The aim is to estimate the influence of covariates on observations, drawn from an exponential distribution. The link considered has a semiparametric expression: if we are interested in a functional influence of some covariates, we authorize others to be modeled linearly. We thus consider a generalized partially linear regression model with unknown regression coefficients and an unknown nonparametric function. We present a maximum penalized likelihood procedure to estimate the components of the model introducing penalty based wavelet estimators. Asymptotic rates of the estimates of both the parametric and the nonparametric part of the model are given and quasi-minimax optimality is obtained under usual conditions in literature. We establish in particular that the LASSO penalty leads to an adaptive estimation with respect to the regularity of the estimated function. An algorithm based on backfitting and Fisher-scoring is also proposed for implementation. Simulations are used to illustrate the finite sample behaviour, including a comparison with kernel and splines based methods

Epidermal Transglutaminase (TGase 3) Is Required for Proper Hair Development, but Not the Formation of the Epidermal Barrier

Transglutaminases (TGase), a family of cross-linking enzymes present in most cell types, are important in events as diverse as cell-signaling and matrix stabilization. Transglutaminase 1 is crucial in developing the epidermal barrier, however the skin also contains other family members, in particular TGase 3. This isoform is highly expressed in the cornified layer, where it is believed to stabilize the epidermis and its reduction is implicated in psoriasis. To understand the importance of TGase 3 in vivo we have generated and analyzed mice lacking this protein. Surprisingly, these animals display no obvious defect in skin development, no overt changes in barrier function or ability to heal wounds. In contrast, hair lacking TGase 3 is thinner, has major alterations in the cuticle cells and hair protein cross-linking is markedly decreased. Apparently, while TGase 3 is of unique functional importance in hair, in the epidermis loss of TGase 3 can be compensated for by other family members

Wavelet-based identification of DNA focal genomic aberrations from single nucleotide polymorphism arrays

<p>Abstract</p> <p>Background</p> <p>Copy number aberrations (CNAs) are an important molecular signature in cancer initiation, development, and progression. However, these aberrations span a wide range of chromosomes, making it hard to distinguish cancer related genes from other genes that are not closely related to cancer but are located in broadly aberrant regions. With the current availability of high-resolution data sets such as single nucleotide polymorphism (SNP) microarrays, it has become an important issue to develop a computational method to detect driving genes related to cancer development located in the focal regions of CNAs.</p> <p>Results</p> <p>In this study, we introduce a novel method referred to as the wavelet-based identification of focal genomic aberrations (WIFA). The use of the wavelet analysis, because it is a multi-resolution approach, makes it possible to effectively identify focal genomic aberrations in broadly aberrant regions. The proposed method integrates multiple cancer samples so that it enables the detection of the consistent aberrations across multiple samples. We then apply this method to glioblastoma multiforme and lung cancer data sets from the SNP microarray platform. Through this process, we confirm the ability to detect previously known cancer related genes from both cancer types with high accuracy. Also, the application of this approach to a lung cancer data set identifies focal amplification regions that contain known oncogenes, though these regions are not reported using a recent CNAs detecting algorithm GISTIC: SMAD7 (chr18q21.1) and FGF10 (chr5p12).</p> <p>Conclusions</p> <p>Our results suggest that WIFA can be used to reveal cancer related genes in various cancer data sets.</p