PubMed Health⌕ Search

PubMed · 15293060

UVA1-induced decrease in dermal neuron-specific enolase (NSE) in acrosclerosis.

Abstract

Besides its role in small-cell carcinoma of the lung, elevated serum levels of neuron-specific enolase (NSE) have recently been reported to be associated with autoimmune rheumatic disorders such as systemic sclerosis. Serum NSE seems to correlate with disease activity as well as Rodnan skin score. The aim of the study was to assess the neuromodulatory effects of conventional UVA1 phototherapy on acrosclerosis as an additional mechanism besides an assumed T cell apoptosis, collagenase induction and angiogenesis. Punch skin biopsies of acrosclerotic skin lesions taken before and after treatment from four patients were evaluated immunohistochemically for the presence of NSE, S100 and neurofilament. Immunolabeling revealed a UVA-induced decrease in dermal NSE expression. In contrast, no alteration in neurofilament+ cells could be detected. In line with the findings of a previous investigation, a high number of S100+ cells were detected in most specimens. We demonstrated a UVA1-induced reduction in dermal NSE levels correlating with a softening of former sclerotic lesions. Even though the origin and the functional mechanisms remain obscure, NSE might be relevant directly within sclerotic skin lesions and may possibly be used as a diagnostic marker at least in SSc-associated acrosclerotic skin.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Frank Breuckmann, Carolin Appelhans, Andreas Bastian, Markus Stuecker, Peter Altmeyer, Alexander Kreuter. 2004. UVA1-induced decrease in dermal neuron-specific enolase (NSE) in acrosclerosis.. https://doi.org/10.1007/s00403-004-0495-y

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Global Genomic Surveillance.

Global genomic surveillance has emerged as a foundational pillar of public health in the twenty-first century, enabling real-time tracking of pathogen evolution and informing outbreak response. This chapter examines the strategic architecture of global genomic surveillance, focusing on its application to arboviruses such as chikungunya virus (CHIKV). It explores the integration of genomic data with epidemiological, clinical, and environmental information within a One Health framework, while addressing critical challenges in governance, equity, and interoperability. The discussion covers the entire genomic surveillance workflow, from sample collection and sequencing to bioinformatic analysis and phylogenetic inference, and highlights the transformative role of artificial intelligence (AI) in predictive surveillance. By analyzing global initiatives, operational barriers, and emerging technologies, this chapter underscores the necessity of sustainable, equitable, and interoperable genomic systems to proactively address current and future infectious disease threats.

Humans↗

Systematic Dissection of Key Driver Perturbation Signatures in Single Cells via ECCITE-seq.

CRISPR screens, such as expanded CRISPR-compatible cellular indexing of transcriptomes and epitopes by sequencing (ECCITE-seq), enable the simultaneous measurement of transcriptomes, gRNA identity, and cell-surface protein expression at single-cell resolution to systematically interrogate gene function. This platform provides a powerful and scalable experimental approach for validating disease-associated regulators identified by large-scale association studies and other computational methods, including network-based analyses of multi-omics data. Here, as an example application, we describe an ECCITE-seq framework to characterize the transcriptomic consequences of perturbing multiple neuronal key driver genes associated with Alzheimer's disease (AD) in human-induced pluripotent stem cell (hiPSC)-derived neurons. More broadly, by integrating customized pooled gRNA libraries with different CRISPR effectors across multiple cell types, this approach allows for the assessment of the regulatory impact of candidate genes implicated in development and disease processes.

Humans↗

Identification of Genome-Wide Chromatin Structural Aberration in Cancer by Hi-C Analysis.

Aberrant three-dimensional genome organization is a hallmark of cancer, often driving oncogene activation through mechanisms such as enhancer hijacking. High-throughput chromosome conformation capture (Hi-C) maps these interactions on a genome-wide scale. Unlike earlier dilution-based methods, in situ Hi-C performs proximity ligation within intact nuclei, minimizing random ligation noise and enabling fine-scale structure detection. This chapter describes an optimized in situ Hi-C protocol tailored for cancer cell lines using MboI digestion and biotin-mediated pull-down to generate high-complexity libraries. We further outline a computational workflow that extends beyond standard topological mapping of compartments and topologically associating domains to identify cancer-specific aberrations. Specifically, we focus on detecting chromosomal rearrangements (structural variants) and characterizing the distinct circular topology of extrachromosomal DNA. This integrated experimental and analytical framework provides the necessary tools to dissect the spatial dysregulation underlying tumor evolution.

Humans↗