An Optimized and Advanced Algorithm for the Quantification of Immunohistochemical Biomarkers in Keratinocytes.

Advancements in pathology have given rise to software applications intended to minimize human error and improve efficacy of image analysis. Still, the subjectivity of image quantification performed manually and the limitations of the most ubiquitous tissue stain analysis software requiring parameters tuned by the observer, reveal the need for a highly accurate, automated nuclear quantification software specific to immunohistochemistry, with improved precision and efficiency compared with the methods currently in use. We present a method for the quantification of immunohistochemical biomarkers in keratinocyte nuclei proposed to overcome these limitations, contributing sensitive shape-focused segmentation, accurate nuclear detection, and automated device-independent color assessment, without observer-dependent analysis parameters.

Cutaneous changes in diabetic patients: Primed for aberrant healing?

Cutaneous manifestations affect most patients with diabetes mellitus, clinically presenting with numerous dermatologic diseases from xerosis to diabetic foot ulcers (DFUs). Skin conditions not only impose a significantly impaired quality of life on individuals with diabetes but also predispose patients to further complications. Knowledge of cutaneous biology and the wound healing process under diabetic conditions is largely limited to animal models, and studies focusing on biology of the human condition of DFUs remain limited. In this review, we discuss the critical molecular, cellular, and structural changes to the skin in the hyperglycaemic and insulin-resistant environment of diabetes with a focus specifically on human-derived data. Elucidating the breadth of the cutaneous manifestations coupled with effective diabetes management is important for improving patient quality of life and averting future complications including wound healing disorders.