No fun in the sun - AI study finds protection from sunburn might be hampered by insect repellents.

Study using machine learning and ex vivo skin biopsies reveal combination of sunscreen and insect repellent reduce UV protection.
No fun in the sun - AI study finds protection from sunburn might be hampered by insect repellents.
Like

Share this post

Choose a social network to share with, or copy the URL to share elsewhere

This is a representation of how your post may appear on social media. The actual post will vary between social networks

Explore the Research

BioMed Central
BioMed Central BioMed Central

Computational histology reveals that concomitant application of insect repellent with sunscreen impairs UV protection in an ex vivo human skin model - Parasites & Vectors

Background Histological alterations such as nuclear abnormalities are sensitive biomarkers associated with diseases, tissue injury and environmental insults. While visual inspection and human interpretation of histology images are useful for initial characterization, such low-throughput procedures suffer from inherent limitations in terms of reliability, objectivity and reproducibility. Artificial intelligence and digital morphometry offer unprecedented opportunities to quickly and accurately assess nuclear morphotypes in relation to tissue damage including skin injury. Methods In this work, we designed NoxiScore, a pipeline providing an integrated, deep learning-based software solution for fully automated and quantitative analysis of nucleus-related features in histological sections of human skin biopsies. We used this pipeline to evaluate the efficacy and safety of three dermato-cosmetic products massively sold at the time of the study in the Montpellier area (South of France): a sunscreen containing UV filters, a mosquito repellent (with synthetic active ingredient IR3535) and a product combining a natural insect repellent plus a sunscreen. Hematoxylin and eosin or hematoxylin-eosin saffron staining was performed to assess skin structure before morphometric parameter computation. Results We report the identification of a specific nuclear feature based on variation in texture information that can be used to assess skin tissue damage after oxidative stress or UV exposure. Our data show that application of the commercial sun cream provided efficient protection against UV effects in our ex vivo skin model, whereas application of the mosquito repellent as a single product exerted no protective or toxic effect. Notably, we found that concurrent application of the insect repellent with the sunscreen significantly decreased the UVB protective effect of the sunscreen. Last, histometric analysis of human skin biopsies from multiple donors indicates that the sunscreen-insect repellent combo displayed variable levels of protection against UV irradiation. Conclusions To our knowledge, our study is the first to evaluate the potential toxicity of combining real-life sunscreen and insect repellent products using ex vivo human skin samples, which most closely imitate the cutaneous physiology. The NoxiScore wet-plus-dry methodology has the potential to provide information about the pharmaco-toxicological profile of topically applied formulations and may also be useful for diagnostic purposes and evaluation of the skin exposome including pesticide exposure, air pollution and water contaminants. Graphical Abstract

Most of us enjoy a sunny day, and as we grab our sunglasses and dust off our sandals, many of us rely on two common products—sunscreen and insect repellent—to protect our skin from harmful UV rays and the bite of pesky, and potentially dangerous, insects. The latter is particularly relevant in light of the expanding distribution of day-biting insects, such as Aedes aegypti, known to transmit several arboviruses, and sandflies that can transmit leishmaniasis, to name but a few. But a new study has revealed an unexpected consequence when these two products are used together: reduced UV protection.

In a recent research study published in Parasites & Vectors, scientists used an advanced AI-powered deep-learning method called NoxiScore to analyze skin biopsies after applying sunscreen, insect repellent, and a combination of both. The results? When sunscreen and insect repellent were applied together, the UV-blocking power of the sunscreen was significantly impaired.

A deep-learning based pipeline to assess the concomitant use of sunscreen and insect repellents.

The authors describe using ex vivo human skin biopsies in their study, arguing that this simulates real-world conditions in a controlled environment, allowing them to study the direct effects of multiple products, including sun screen and insect repellent combinations, on human skin cells. This potentially provides more accurate and relevant results than the use of artificial or animal models, making this a more reliable and ethical way of studying the toxicity and effectiveness of these products on skin.

The authors applied different combinations of sunscreen and insect repellent on the skin biopsies before exposing them to UVB irradiation in the lab, or to sunlight in real-life settings. The following were tested:

  1. sunscreen containing UV filters alone.
  2. sunscreen containing UV filters and a mosquito repellent with synthetic active ingredient IR3535 (sunscreen first, followed by a mosquito repellent as often recommended).
  3. A commercial preparation of a natural insect repellent plus sunscreen (‘combo’).

The researchers developed and used an image analysis pipeline, starting with the application of the “treatment” to the ex vivo skin biopsies, then the preparation and digitalization of histological samples for the production of high-resolution images and finally the AI-assisted image processing and computational analysis of the data.

Graphic abstract showing ex vivo human skin model and machine learning pipeline. From Computational histology reveals that concomitant application of insect repellent with sunscreen impairs UV protection in an ex vivo human skin model  https://parasitesandvectors.biomedcentral.com/articles/10.1186/s13071-025-06712-3
Graphic abstract showing ex vivo human skin model and machine learning pipeline. From Computational histology reveals that concomitant application of insect repellent with sunscreen impairs UV protection in an ex vivo human skin model  https://parasitesandvectors.biomedcentral.com/articles/10.1186/s13071-025-06712-3

The results showed that while sunscreen alone effectively protected against UV exposure, the insect repellent, especially when mixed with the sunscreen, reduced the sunscreen's ability to protect the skin from UVB rays. This could lead to greater susceptibility to skin damage and even increase the risk of skin cancer in the long term.

Food for thought:

This study highlights the importance of considering how multiple products interact and underscores the need for better safety testing of combined products. While insect repellents help prevent insect-borne diseases, and sunscreens protect us from UV-induced skin damage, this research shows that combining the two may compromise both forms of protection. 

The researchers argue that using deep-learning AI delivers precise, consistent and objective cell analysis, rapidly processing large amounts of data and identifying patterns and abnormalities in the skin samples. Because it is an efficient and rapid process it is a scalable analysis method and can provide predictive modelling of how the combination of insect repellent and sunscreen might impact UV protection and overall skin health.  The integration of ex vivo human skin biopsies and deep learning software into a high throughput pipeline is a very innovative approach that could have applications from skin product toxicity to diagnostic and evaluation of numerous skin issues due to exposures and irritants.   

AI statement - I used ChatGPT to help develop an outline for the blog, which I expanded and edited.

Please sign in or register for FREE

If you are a registered user on Research Communities by Springer Nature, please sign in

Follow the Topic

Skin models
Life Sciences > Biological Sciences > Biological Techniques > Biological Models > Skin models
Artificial Intelligence
Mathematics and Computing > Computer Science > Artificial Intelligence
Malaria
Life Sciences > Health Sciences > Biomedical Research > Medical Microbiology > Infectious Diseases > Malaria
Viral Vectors
Life Sciences > Biological Sciences > Microbiology > Virology > Viral Epidemiology > Viral Vectors
Parasitology
Life Sciences > Biological Sciences > Microbiology > Parasitology
Dermatology
Life Sciences > Health Sciences > Clinical Medicine > Dermatology

Related Collections

With collections, you can get published faster and increase your visibility.

Artificial intelligence, parasites, and parasitic diseases

Publishing Model: Open Access

Deadline: Dec 31, 2025

The LCNTDR Collection: Advances in scientific research for NTD control

Neglected tropical diseases (NTDs) are a diverse group of 20 diseases that affect over 1.7 billion people globally. These diseases are considered “neglected” because they disproportionately affect people living in poverty, and until recently, were largely overlooked by the international community. Over the past several years, there have been major advances in the areas of advocacy, control implementation funding, cross-sectoral collaboration and drug donation for NTDs. Many new tools are available for NTD diagnosis and the goals of control, elimination and eradication are becoming more feasible. In order to ensure the most effective and efficient use of resources to tackle NTDs, evidence-based research (performed in conjunction with country-based control implementation programmes) must constantly be taking place to evaluate NTD strategies. The London Centre for Neglected Tropical Disease Research (LCNTDR) was launched in 2013 with the aim of providing focused operational and research support for NTDs. LCNTDR, a joint initiative of the Natural History Museum, the London School of Hygiene & Tropical Medicine, the Royal Veterinary College, the Partnership for Child Development, the SCI Foundation (formerly known as the Schistosomiasis Control Initiative) and Imperial College London, undertakes interdisciplinary research to build the evidence base around the design, implementation, monitoring and evaluation of NTD programmes. This series features recent advances in scientific research for NTDs executed by LCNTDR member institutions and their collaborators. It aims to highlight the wide range of work being undertaken by the LCNTDR towards achieving the United Nations Sustainable Development Goals well as supporting the objectives of the World Health Organization road map for neglected tropical disease 2021-2030.

Publishing Model: Open Access

Deadline: Ongoing