Epidermal naevi (EN) are considered mosaic disorders. Postzygotic mutations are thought to occur during early embryogenesis. They are usually arranged along Blaschko's lines and tend to be noted either at birth or shortly thereafter. Skin tumours arising on EN are occasionally reported, with ongoing discussion as to whether these are collision tumours or a malignant transformation of the EN. We describe a 76-year-old woman with segmentally arranged seborrhoeic keratoses that showed impending atypia and, in one lesion, even overt malignant transformation. In biopsies from various lesions we found FGFR3 and PIK3CA hotspot mutations but there was no consistent pattern of mutations explaining the premalignant or malignant growth. So far it is unclear whether the precancerous changes as noted in this elderly patient can be taken as an unusual manifestation of one of the established types of EN, or whether this may represent a separate disorder that could be called 'SASKIA naevus'. The acronym would stand for segmentally arranged seborrhoeic keratoses with impending atypia.

Download full-text PDF

Source
http://dx.doi.org/10.1111/bjd.13562DOI Listing

Publication Analysis

Top Keywords

segmentally arranged
12
arranged seborrhoeic
12
seborrhoeic keratoses
12
keratoses impending
12
impending atypia
12
malignant transformation
8
atypia squamous
4
squamous cell
4
cell carcinoma
4
carcinoma elderly
4

Similar Publications

Force Map-Enhanced Segmentation of a Lightweight Model for the Early Detection of Cervical Cancer.

Diagnostics (Basel)

February 2025

Department of Computer Engineering, Gachon University, Sujeong-gu, Seongnam-si 461-701, Gyeonggi-do, Republic of Korea.

Accurate and efficient segmentation of cervical cells is crucial for the early detection of cervical cancer, enabling timely intervention and treatment. Existing segmentation models face challenges with complex cellular arrangements, such as overlapping cells and indistinct boundaries, and are often computationally intensive, which limits their deployment in resource-constrained settings. In this study, we introduce a lightweight and efficient segmentation model specifically designed for cervical cell analysis.

View Article and Find Full Text PDF

ZraS is a metal sensor integral to ZraPSR, a two-component signaling system found in enterobacters. It belongs to a family of bifunctional sensor histidine kinases (SHKs) and is speculated to sense zinc-induced stress on the bacterial envelope. Information on the structure-function relationship of sensor kinases is elusive due to the lack of full-length structures, intrinsically dynamic behavior, and difficulty trapping them in active state conformations.

View Article and Find Full Text PDF

Innovations in self-assembly and aggregate engineering have led to membranes that better balance water permeability with salt rejection, overcoming traditional trade-offs. Here we demonstrate a strategy that uses multivalent H-bond interactions at the nano-confined space to manipulate controllable and organized crystallization. Specifically, we design amphiphilic oligomers featuring hydrophobic segments with strongly polar end-capped motifs.

View Article and Find Full Text PDF

A Novel Fragmentation-based Approach for Accurate Segmentation of Small-Sized Brain Tumors in MRI Images.

Curr Med Imaging

March 2025

Department of Computer Engineering, College of IT Convergence, Gachon University, Seongnam 13120, Republic of Korea.

Aims: In the dynamic landscape of healthcare, integrating Artificial Intelligence paradigms has become essential for sophisticated brain image analysis, especially in tumor detection. This research addresses the need for heightened learning precision in handling sensitive medical images by introducing the Fragmented Segment Detection Technique.

Background: The ever-evolving healthcare landscape demands advanced methods for brain image analysis, particularly in detecting tumors.

View Article and Find Full Text PDF

Synthetic data generation emerges as a strategy to mitigate data scarcity in digital pathology, where complicated tissue and cellular features are correlated with cancer diagnosis. The synthesis of such visuals, however, suffers from limited inter class diversity and scarcity of cellular annotations. Current methodologies struggle with capturing the broad spectrum of pathology features, causing unpredictable objects and defected fidelity.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!