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Record W2994441082 · doi:10.1101/867531

Measles skin rash: infection of lymphoid and myeloid cells in the dermis precedes viral dissemination to keratinocytes in the epidermis

2019· preprint· en· W2994441082 on OpenAlexaff
Brigitta M. Laksono, Paola Fortugno, Bernadien M. Nijmeijer, Rory D. de Vries, Sonia Cordisco, Stefan van Nieuwkoop, Thijs Kuiken, Teunis B. H. Geijtenbeek, W. Paul Duprex, Francesco Brancati, Rik L. de Swart

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2019
Typepreprint
Languageen
FieldMedicine
TopicVirology and Viral Diseases
Canadian institutionsInstitute of Infection and Immunity
Fundersnot available
KeywordsDermisRashEpidermis (zoology)KeratinocyteBiologyImmunologyHuman skinMeasles virusPsoriasisEx vivoPapillary dermisImmune systemMeaslesPathologyIn vivoVirologyMedicineDermatologyIn vitroVaccination

Abstract

fetched live from OpenAlex

Abstract Measles is characterised by fever and a maculopapular skin rash, which is associated with immune clearance of measles virus (MV)-infected cells. Histopathological analyses of skin biopsies from humans and non-human primates (NHPs) with measles rash have identified MV-infected keratinocytes and mononuclear cells in the epidermis, around hair follicles and near sebaceous glands. Here, we address the pathogenesis of measles skin rash by combining data from experimentally infected NHPs, ex vivo infection of human skin sheets and in vitro infection of primary human keratinocytes. Longitudinal analysis of the skin of experimentally MV-infected NHPs demonstrated that infection in the skin precedes onset of rash by several days. MV infection was initiated in lymphoid and myeloid cells in the dermis before dissemination to the epidermal keratinocytes. These data were in good concordance with ex vivo MV infections of human skin sheets, in which dermal cells were more targeted than the epidermal ones. To address viral dissemination to the epidermis and to determine whether the dissemination is receptor-dependent, we performed experimental infections of primary keratinocytes collected from healthy or nectin-4-deficient donors. These experiments demonstrated that MV infection of keratinocytes is nectin-4-dependent, and nectin-4 expression was higher in differentiated than in proliferating keratinocytes. Based on these data, we hypothesise that measles skin rash is initiated by migrating MV-infected lymphocytes that infect dermal skin-resident CD150 + immune cells. The infection is subsequently disseminated from the dermal papillae to nectin-4 + keratinocytes in the basal epidermis. Lateral spread of MV infection is observed in the superficial epidermis, most likely due to the higher level of nectin-4 expression on differentiated keratinocytes. Finally, MV-infected cells are cleared by infiltrating immune cells, causing hyperaemia and oedema, which give the appearance of morbilliform skin rash. Author Summary Several viral infections are associated with skin rash, including parvovirus B19, human herpesvirus type 6, dengue virus and rubella virus. However, the archetype virus infection that leads to skin rash is measles. Although all of these viral exanthemata often appear similar, their pathogenesis is different. In the case of measles, the appearance of skin rash is a sign that the immune system is clearing MV-infected cells from the skin. How the virus reaches the skin and is locally disseminated remains unknown. Here we combine observations and expertise from pathologists, dermatologists, virologists and immunologists to delineate the pathogenesis of measles skin rash. We show that MV infection of dermal myeloid and lymphoid cells precedes viral dissemination to the epidermal keratinocytes. We speculate that immune-mediated clearance of these infected cells results in hyperaemia and oedema, explaining the redness of the skin and the slightly elevated spots of the morbilliform rash.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.257
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2019
Admission routes1
Has abstractyes

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