Lupus band test for diagnostic evaluation in systemic lupus erythematosus

Background The lupus band test (LBT) using a sample of clinically normal skin was proposed as a useful diagnostic test for systemic lupus erythematosus (SLE). It is mostly performed to help diagnosing SLE in patients with insufficient clinical and serological profiles. However, most published studies on its utility are outdated and the results remain controversial. Objectives To determine the diagnostic performance of LBT on non-lesion sun-protected (NLSP) and sun-exposed (NLSE) skin for SLE. Methods Consecutively presenting patients with clinical and serological suspicion of SLE who had LBT performed on non-lesion skin during January 2012 to August 2021 were retrospectively studied. LBT performed on either NLSE or NLSP skin biopsies were all included. Laboratory characteristics, number, types and patterns of deposited immunoreactants and disease activity were also assessed. Results LBT was performed in 57 patients with suspected SLE. LBT was positive in 18/57, 9/28 and 6/21 patients in overall non-lesion, NLSE and NLSP, respectively. Of all patients, 23 patients were diagnosed with SLE and 34 patients with other diseases. Overall, the sensitivity and specificity of LBT on non-lesion skin was 56.5% and 88.2%, respectively. The ability of the test to discriminate between those with and without SLE, assessed by the area under the Receiver-Operating Characteristic curve, was 0.72 (0.61–0.84). The sensitivity and specificity of LBT on NLSE skin was 58.3% and 87.5% while those of NLSP skin, were 57.1% and 85.7%, respectively. We found no significant correlation between the positivity of LBT and overall disease activity. Types, number and pattern of deposited immunoreactants also showed no correlation with disease activity (all p > 0.05). Conclusions Used as a diagnostic adjunct, non-lesion LBT is still of value for diagnosing SLE in inconclusive cases.

Interactions of host defense and hyper-keratinization in psoriasis

Objectives: To understand the crosstalk between the host and microbiota in psoriatic skin, using a systems biology approach based on transcriptomics and microbiome profiling. Methods: We collected the skin tissue biopsies and swabs in both lesion and non-lesion skin of 13 patients with psoriasis (PsO), 15 patients with psoriatic arthritis (PsA), and healthy skin from 12 patients with ankylosing spondylitis (AS). We performed transcriptome sequencing and metagenomics profiling on the local skin sites to study the similarities and differences in the molecular profiles between the three conditions, and the associations between the host defense and microbiota dynamic. Results: We found that lesion and non-lesional samples were remarkably different in terms of their transcriptome profiles. Functional annotation of differentially expressed genes (DEGs) showed a major enrichment in neutrophil activation. By using co-expression gene networks, we identified a gene module that was associated with local psoriasis severity at the site of biopsy. From this module, we extracted a "core" set of genes that were functionally involved in neutrophil activation, epidermal cell differentiation and response to bacteria. Skin microbiome analysis revealed that the abundance of Enhydrobacter, Micrococcus and Leptotrichia were significantly correlated with the "core network" of genes. Conclusions: We identified a core network that regulates inflammation and hyper-keratinization in psoriatic skin, and is associated with local disease severity and microbiome composition.

Skin Cancer Image Segmentation Based on Symmetrical Threshold Contour Algorithm

Image segmentation is a process of identifying sub patterns in a given image. The purpose of skin cancer image segmentation is to represent it ina meaningful way for effectiveanalysis. Segmentation of skin cancer image is mostly used to detect the boundaries and objects present in a skin lesion. This approach describes the skin cancer image segmentation based on symmetrical threshold contour algorithm with similar thresholding values for segmentation of the accurate cancerous lesion. Skin cancer lesion shape and structure is the most important parameter in this method. In this paper, skin cancer image contour detection isbased on symmetrical thresholding algorithm using MATLAB soft ware.

CTNNBIP1 modulates keratinocyte differentiation through promoting the transcription of β-catenin/TCF-complex downstream genes

Background: During psoriasis initiation and development, deregulations in signaling pathways and gene expression are observed. Methods: Herein, we downloaded seven sets of microarray mRNA expression profiles showing differentially-expressed genes in psoriasis lesion skin and non-lesion skin tissues and three sets of RNA-seq data and analyzed these online data attempting to screen for crucial genes related to keratinocyte differentiation and psoriasis development. Results: The expression of catenin beta interacting protein 1 (CTNNBIP1) was remarkably downregulated within psoriasis lesion skin tissue samples compared to that within non-lesion skin tissues based on both online data and experimental results. In response to a period of different therapies, respectively, CTNNBIP1 expression could be rescued in lesion skin tissues. Within IMQ-induced psoriasis-like dermatitis in mice, CTNNBIP1 silence further aggravated psoriatic phenotypes. In human immortalized keratinocytes, HaCaT cells, CTNNBIP1 silence significantly inhibited cell apoptosis and promoted cell proliferation. Regarding the molecular mechanism, CTNNBIP1 silence in HaCaT cells promoted β-catenin nucleus translocation, enhanced the transcriptional activity of TCF4, and increased β-catenin/TCF-complex downstream c-Myc and cyclin D1 proteins while decreased the late differentiation marker filaggrin. In contrast to CTNNBIP1, the expression of c-Myc and cyclin D1 showed to be dramatically upregulated within psoriasis lesion tissue samples than that within non-lesion tissue samples. Within tissues, c-Myc and cyclin D1 showed to be negatively correlated with CTNNBIP1, respectively. Conclusions: We identify CTNNBIP1 as an abnormally downregulated gene in psoriasis. CTNNBIP1 silence significantly disturbs the differentiation of keratinocytes through promoting the transcription of β-catenin/TCF-complex downstream genes.

Correlation between Serum Leptin Level with Type and Number of Lesion Skin Tag

BACKGROUND: Skin tag is a benign tumour of connective tissue in the skin, sessile or pedunculated, skin-like to brownish coloured and often arises in the flexure area. Etiopathogenesis of skin tag is still unclear, but one of the aetiology is associated with leptin hormone. AIM: To determine the correlation between leptin serum level with type and number of the lesion skin tag. METHODS: This study is an observational analytic study with a cross-sectional design involving 33 skin tag patients. Diagnosis of skin tag was based on history and clinical examination; we conducted blood sampling and measurement of serum leptin level to the patients. RESULTS: We found the mean serum leptin level of skin tag patients were highest on the type of lesion mixed (31.54 ± 12.85 ng/ml). The mean number of skin tag lesions was 13.6 ± 5.8 lesions. There is a very high positive correlation between serum leptin level with a number of skin tag (r = 0.86) with p < 0.05 and significant correlation between serum leptin level with the type of lesions (p = 0.037). CONCLUSION: Serum leptin level has a very high positive correlation to a number of skin tag and significant correlation between serum leptin level with the type of lesion.