Evaluation of diffuse reflectance spectroscopy for predicting age, species, and cuticular resistance of Anopheles gambiae s.l under laboratory conditions.

Mid-infrared spectroscopy (MIRS) combined with machine learning analysis has shown potential for quick and efficient identification of mosquito species and age groups. However, current technology to collect spectra is destructive to the sample and does not allow targeting specific tissues of the mosquito, limiting the identification of other important biological traits such as insecticide resistance. Here, we assessed the use of a non-destructive approach of MIRS for vector surveillance, micro diffuse reflectance spectroscopy (µDRIFT) using mosquito legs to identify species, age and cuticular insecticide resistance within the Anopheles gambiae s.l. complex. These mosquitoes are the major vectors of malaria in Africa and the focus on surveillance in malaria control programs. Legs required significantly less scanning time and showed more spectral consistence compared to other mosquito tissues. Machine learning models were able to identify An. gambiae and An. coluzzii with an accuracy of 0.73, two ages groups (3 and 10 days old) with 0.77 accuracy and we obtained accuracy of 0.75 when identifying cuticular insecticide resistance. Our results highlight the potential of different mosquito tissues and µDRIFT as tools for biological trait identification on mosquitoes that transmit malaria. These results can guide new ways of identifying mosquito traits which can help the creation of innovative surveillance programs by adapting new technology into mosquito surveillance and control tools.

Changes in Oxygenation Levels During Moderate Altitude Simulation (Hypoxia-Induced): A Pilot Study Investigating the Impact of Skin Pigmentation in Pulse Oximetry.

The current COVID-19 pandemic has shown us that the pulse oximeter is a key medical device for monitoring blood-oxygen levels non-invasively in patients with chronic or acute illness. It has also emphasised limitations in accuracy for individuals with darker skin pigmentation, calling for new methods to provide better measurements. The aim of our study is to identify the impact of skin pigmentation on pulse oximeter measurements. We also explored the benefits of a multi-wavelength approach with an induced change of arterial oxygen saturation. A total of 20 healthy volunteers were recruited. We used time domain diffuse reflectance spectroscopy (TDDRS) from a broad band light source, collecting spectra from the index finger along with three different pulse oximeters used simultaneously for monitoring purposes. Five acute hypoxic events were induced by administering 11% FiO2, produced by a Hypoxico altitude training system, for 120 sec through a face mask with a one-way valve. Our multi-wavelength approach revealed a correlation between the signature of skin pigmentation and the dynamic range of oxygen saturation measurements. Principal component analysis (PCA) showed separation between a range of different pigmented volunteers (PC1 = 56.00%) and oxygen saturation (PC2 = 22.99%). This emphasises the need to take into account skin pigmentation in oximeter measurements. This preliminary study serves to validate the need to better understand the impact of skin pigmentation absorption on optical readings in pulse oximeters. Multi-wavelength approaches have the potential to enable robust and accurate measurements across diverse populations.