In health, the non-recirculating nature and long-term persistence of tissue-resident memory T cells (TRMs) in tissues protects against invading pathogens. In disease, pathogenic TRMs contribute to the recurring traits of many skin diseases. We aimed to conduct a systematic literature review on the current understanding of the role of TRMs in skin diseases and identify gaps as well as future research paths. EMBASE, PubMed, SCOPUS, Web of Science, Clinicaltrials.gov and WHO Trials Registry were searched systematically for relevant studies from their inception to October 2020. Included studies were reviewed independently by two authors. This study was conducted in accordance with the PRISMA-S guidelines. This protocol was registered with the PROSPERO database (ref: CRD42020206416). We identified 96 studies meeting the inclusion criteria. TRMs have mostly been investigated in murine skin and in relation to infectious skin diseases. Pathogenic TRMs have been characterized in various skin diseases including psoriasis, vitiligo and cutaneous T-cell lymphoma. Studies are needed to discover biomarkers that may delineate TRMs poised for pathogenic activity in skin diseases and establish to which extent TRMs are contingent on the local skin microenvironment. Additionally, future studies may investigate the effects of current treatments on the persistence of pathogenic TRMs in human skin.

Background: Dead Sea climatotherapy (DSC) is a treatment option for psoriasis in Denmark. However, the response to DSC has not been particularly well studied. Aim: We sought to determine effectiveness and response duration of DSC on psoriasis-related outcome parameters. Methods: Eighteen patients participated in a 4-week treatment program in Ein Gedi in Israel. Treatment, consisting of sun exposure and bathing, was individualized. Results: DSC was associated with a mean 13.0-point reduction (88%) in Psoriasis Area and Severity Index and a mean reduction of 2.3 (76.7%) on the 5-point Investigator's Global Assessment Scale. Furthermore, patients' quality of life improved measured by the Dermatology Quality of Life Index and EuroQol 5D index values. The mean time from treatment end to reappearance of visible skin symptoms was 93.8 days (SD: 62.5, range: 31–219 days). Conclusions: Our results confirm that DSC has an immediate effect on skin manifestations and improves quality of life, but long-term disease control is not observed.

Psoriasis is a chronic inflammatory skin disease, in which molecular and cellular changes retain following clinical resolution of psoriatic lesions, a form of disease memory (‘molecular scar’) that may reestablish the psoriatic inflammation. The increasing evidence of the benefits from early intervention in other immune‐mediated diseases prompts the question of whether early systemic intervention, such as biologics, in new‐onset cutaneous psoriasis may lead to improved clinical response and sustained remission by averting an inflammatory disease memory. Herein, we review the current evidence on early intervention and disease memory in psoriasis. The evidence is sparse and inconsistent, although an early intervention within 2 years of disease‐onset may provide a more favourable long‐term prognosis in psoriasis. However, ongoing randomised clinical trials will explore whether early intervention with biologics in new‐onset psoriasis will be an effective treatment strategy, and whether it prevents the molecular and cellular changes potentially underlying the inflammatory disease memory.

Quantification of osteoclasts to assess bone resorption is a time-consuming and tedious process. Since the inception of bone histomorphometry and manual counting of osteoclasts using bright-field microscopy, several approaches have been proposed to accelerate the counting process using both free and commercially available software. However, most of the present alternatives depend on manual or semi-automatic color segmentation and do not take advantage of artificial intelligence (AI). The present study directly compare estimates of osteoclast-covered surfaces (Oc.S/BS) obtained by the conventional manual method using a bright-field microscope to that obtained by a new AI-assisted method. We present a detailed step-by-step guide for the AI-based method. Tibiae from Wistar rats were either enzymatically stained for TRAP or immunostained for cathepsin K to identify osteoclasts. We found that estimation of Oc.S/BS by the new AI-assisted method was considerably less time-consuming, while still providing similar results to the conventional manual method. In addition, the retrainable AI-module used in the present study allows for fully automated overnight batch processing of multiple annotated sections. • Bone histomorphometry • AI-assisted osteoclast identification • TRAP and cathepsin K

Immunohistochemical quantification of inflammatory cells in skin biopsies is a valuable tool for diagnosing skin diseases and assessing treatment response. The quantification of individual cells in biopsies is time-consuming, tedious, and difficult. In this study, we presented and compared two methods for the quantification of CD8⁺ T cells in skin biopsies from patients with psoriasis using both commercial software (Adobe Photoshop) and open-source software (Qupath). In addition, we provided a detailed, step-by-step description of both methods. The methods are scalable by replacing the CD8 antibody with other antibodies to target different cells. Moreover, we investigated the correlation between quantifying CD8⁺ cells normalized to area or epidermal length and cell classifications, compared cell classifications in QuPath with threshold classifications in Photoshop, and analyzed the impact of data normalization to epidermal length or area on inflammatory cell densities in skin biopsies from patients with psoriasis. We found a satisfactory correlation between normalizing data to epidermal length and area for psoriasis skin. However, when non-lesional and lesional skin samples were compared, a significant underestimation of inflammatory cell density was found when data were normalized to area instead of epidermal length. Finally, Bland–Altman plots comparing Qupath and Photoshop to quantify inflammatory cell density demonstrated a good agreement between the two methods.