A prospective study of cutaneous findings in newborns in the United States: correlation with race, ethnicity, and gestational status using updated classification and nomenclature.

OBJECTIVE: To provide incidence data based on ethnicity, prematurity, and body site for vascular, pigmented, and other common congenital cutaneous findings; to compare these results with previously published prospective studies; and to define updated nomenclature, classification, clinical course, and prognostic factors for the pediatric practitioner to promote a better understanding of benign versus more worrisome birthmarks. STUDY DESIGN: This prospective study enrolled 594 infants in San Diego, California. Cutaneous examination was performed by pediatric dermatologists in the first 48 hours of life, with subsequent longitudinal contact via telephone, and repeat evaluations if any new lesions were reported by parents. Incidence rates were calculated by ethnicity and prematurity status. RESULTS: The most common vascular lesion was nevus simplex (83%), followed by infantile hemangioma (4.5% by age 3 months), capillary malformation (0.3%), and rapidly involuting congenital hemangioma (0.3%). Pigmented lesions seen at birth included dermal melanocytosis (20%), congenital melanocytic nevi (2.4%), and café au lait macules (2%). Other common skin findings were erythema toxicum neonatorum (7%), milia (8%), and sebaceous gland hyperplasia (42.6%). CONCLUSION: This study of congenital cutaneous lesions, using current nomenclature and data acquired by pediatric cutaneous lesion experts, provides data regarding the role of race and ethnicity in the incidence of birthmarks, and provides valid data on the prevalence of infantile hemangioma.

Identification of cardioviruses related to Theiler's murine encephalomyelitis virus in human infections.

Cardioviruses comprise a genus of picornaviruses that cause severe illnesses in rodents, but little is known about the prevalence, diversity, or spectrum of disease of such agents among humans. A single cardiovirus isolate, Saffold virus, was cultured in 1981 in stool from an infant with fever. Here, we describe the identification of a group of human cardioviruses that have been cloned directly from patient specimens, the first of which was detected using a pan-viral microarray in respiratory secretions from a child with influenza-like illness. Phylogenetic analysis of the nearly complete viral genome (7961 bp) revealed that this virus belongs to the Theiler's murine encephalomyelitis virus (TMEV) subgroup of cardioviruses and is most closely related to Saffold virus. Subsequent screening by RT-PCR of 719 additional respiratory specimens [637 (89%) from patients with acute respiratory illness] and 400 cerebrospinal fluid specimens from patients with neurological disease (aseptic meningitis, encephalitis, and multiple sclerosis) revealed no evidence of cardiovirus infection. However, screening of 751 stool specimens from 498 individuals in a gastroenteritis cohort resulted in the detection of 6 additional cardioviruses (1.2%). Although all 8 human cardioviruses (including Saffold virus) clustered together by phylogenetic analysis, significant sequence diversity was observed in the VP1 gene (66.9%-100% pairwise amino acid identities). These findings suggest that there exists a diverse group of novel human Theiler's murine encephalomyelitis virus-like cardioviruses that hitherto have gone largely undetected, are found primarily in the gastrointestinal tract, can be shed asymptomatically, and have potential links to enteric and extraintestinal disease.

Development and Assessment of an Artificial Intelligence-Based Tool for Skin Condition Diagnosis by Primary Care Physicians and Nurse Practitioners in Teledermatology Practices.

Importance: Most dermatologic cases are initially evaluated by nondermatologists such as primary care physicians (PCPs) or nurse practitioners (NPs). Objective: To evaluate an artificial intelligence (AI)-based tool that assists with diagnoses of dermatologic conditions. Design, Setting, and Participants: This multiple-reader, multiple-case diagnostic study developed an AI-based tool and evaluated its utility. Primary care physicians and NPs retrospectively reviewed an enriched set of cases representing 120 different skin conditions. Randomization was used to ensure each clinician reviewed each case either with or without AI assistance; each clinician alternated between batches of 50 cases in each modality. The reviews occurred from February 21 to April 28, 2020. Data were analyzed from May 26, 2020, to January 27, 2021. Exposures: An AI-based assistive tool for interpreting clinical images and associated medical history. Main Outcomes and Measures: The primary analysis evaluated agreement with reference diagnoses provided by a panel of 3 dermatologists for PCPs and NPs. Secondary analyses included diagnostic accuracy for biopsy-confirmed cases, biopsy and referral rates, review time, and diagnostic confidence. Results: Forty board-certified clinicians, including 20 PCPs (14 women [70.0%]; mean experience, 11.3 [range, 2-32] years) and 20 NPs (18 women [90.0%]; mean experience, 13.1 [range, 2-34] years) reviewed 1048 retrospective cases (672 female [64.2%]; median age, 43 [interquartile range, 30-56] years; 41 920 total reviews) from a teledermatology practice serving 11 sites and provided 0 to 5 differential diagnoses per case (mean [SD], 1.6 [0.7]). The PCPs were located across 12 states, and the NPs practiced in primary care without physician supervision across 9 states. The NPs had a mean of 13.1 (range, 2-34) years of experience and practiced in primary care without physician supervision across 9 states. Artificial intelligence assistance was significantly associated with higher agreement with reference diagnoses. For PCPs, the increase in diagnostic agreement was 10% (95% CI, 8%-11%; P < .001), from 48% to 58%; for NPs, the increase was 12% (95% CI, 10%-14%; P < .001), from 46% to 58%. In secondary analyses, agreement with biopsy-obtained diagnosis categories of maglignant, precancerous, or benign increased by 3% (95% CI, -1% to 7%) for PCPs and by 8% (95% CI, 3%-13%) for NPs. Rates of desire for biopsies decreased by 1% (95% CI, 0-3%) for PCPs and 2% (95% CI, 1%-3%) for NPs; the rate of desire for referrals decreased by 3% (95% CI, 1%-4%) for PCPs and NPs. Diagnostic agreement on cases not indicated for a dermatologist referral increased by 10% (95% CI, 8%-12%) for PCPs and 12% (95% CI, 10%-14%) for NPs, and median review time increased slightly by 5 (95% CI, 0-8) seconds for PCPs and 7 (95% CI, 5-10) seconds for NPs per case. Conclusions and Relevance: Artificial intelligence assistance was associated with improved diagnoses by PCPs and NPs for 1 in every 8 to 10 cases, indicating potential for improving the quality of dermatologic care.

A deep learning system for differential diagnosis of skin diseases.

Skin conditions affect 1.9 billion people. Because of a shortage of dermatologists, most cases are seen instead by general practitioners with lower diagnostic accuracy. We present a deep learning system (DLS) to provide a differential diagnosis of skin conditions using 16,114 de-identified cases (photographs and clinical data) from a teledermatology practice serving 17 sites. The DLS distinguishes between 26 common skin conditions, representing 80% of cases seen in primary care, while also providing a secondary prediction covering 419 skin conditions. On 963 validation cases, where a rotating panel of three board-certified dermatologists defined the reference standard, the DLS was non-inferior to six other dermatologists and superior to six primary care physicians (PCPs) and six nurse practitioners (NPs) (top-1 accuracy: 0.66 DLS, 0.63 dermatologists, 0.44 PCPs and 0.40 NPs). These results highlight the potential of the DLS to assist general practitioners in diagnosing skin conditions.

Doxycycline indirectly inhibits proteolytic activation of tryptic kallikrein-related peptidases and activation of cathelicidin.

The increased abundance and activity of cathelicidin and kallikrein 5 (KLK5), a predominant trypsin-like serine protease (TLSP) in the stratum corneum, have been implicated in the pathogenesis of rosacea, a disorder treated by the use of low-dose doxycycline. Here we hypothesized that doxycycline can inhibit activation of tryptic KLKs through an indirect mechanism by inhibition of matrix metalloproteinases (MMPs) in keratinocytes. The capacity of doxycycline to directly inhibit enzyme activity was measured in surface collections of human facial skin and extracts of cultured keratinocytes by fluorescence polarization assay against fluorogenic substrates specific for MMPs or TLSPs. Doxycycline did inhibit MMP activity but did not directly inhibit serine protease activity against a fluorogenic substrate specific for TLSPs. However, when doxycycline or other MMP inhibitors were added to live keratinocytes during the production of tryptic KLKs, this treatment indirectly resulted in decreased TLSP activity. Furthermore, doxycycline under these conditions inhibited the generation of the cathelicidin peptide LL-37 from its precursor protein hCAP18, a process dependent on KLK activity. These results demonstrate that doxycycline can prevent cathelicidin activation, and suggest a previously unknown mechanism of action for doxycycline through inhibiting generation of active cathelicidin peptides.

TLR2 expression is increased in rosacea and stimulates enhanced serine protease production by keratinocytes.

A diverse environment challenges skin to maintain temperature, hydration, and electrolyte balance while also maintaining normal immunological function. Rosacea is a common skin disease that manifests unique inflammatory responses to normal environmental stimuli. We hypothesized that abnormal function of innate immune pattern recognition could explain the enhanced sensitivity of patients with rosacea, and observed that the epidermis of patients with rosacea expressed higher amounts of Toll-like receptor 2 (TLR2) than normal patients. Increased expression of TLR2 was not seen in other inflammatory skin disorders such as atopic dermatitis or psoriasis. Overexpression of TLR2 on keratinocytes, treatment with TLR2 ligands, and analysis of TLR2-deficient mice resulted in a calcium-dependent release of kallikrein 5 from keratinocytes, a critical protease involved in the pathogenesis of rosacea. These observations show that abnormal TLR2 function may explain enhanced inflammatory responses to environmental stimuli and can act as a critical element in the pathogenesis of rosacea.