The study and applications of in vivo skin optics have been openly documented as early as the year 1954, or possibly earlier. To date, challenges in analyzing the complexities of this field remain, with wide scopes requiring more scrutiny. Recent advances in spectroscopic research and multivariate analytics allow a closer look into applications potentially for detecting or monitoring diseases. One of the challenges in this field is in establishing a reference for applications which correspond to certain bandwidths. This article reviews the scope on past research on skin spectroscopy, and the clinical aspects which have or may have applications on disease detection or enhancing diagnostics. A summary is supplied on the technicalities surrounding the measurements reported in literature, focused towards the wavelength-dependent applications in themes central to the respective research. Analytics on the topology of the papers' data cited in this work is also provided for a statistical perspective. In short, this paper strives to immediately inform the reader with possible applications via the spectroscopic devices at hand. Graphical Abstract .
Classifying and quantifying mosquito activity includes a plethora of categories, ranging from measuring flight speeds, repellency, feeding rates, and specific behaviors such as home entry, swooping and resting, among others. Entomologists have been progressing more toward using machine vision for efficiency for this endeavor. Digital methods have been used to study the behavior of insects in labs, for instance via three-dimensional tracking with specialized cameras to observe the reaction of mosquitoes towards human odor, heat and CO2, although virtually none was reported for several important fields, such as repellency studies which have a significant need for a proper response quantification. However, tracking mosquitoes individually is a challenge and only limited number of specimens can be studied. Although tracking large numbers of individual insects is hailed as one of the characteristics of an ideal automated image-based tracking system especially in 3D, it also is a costly method, often requiring specialized hardware and limited access to the algorithms used for mapping the specimens. The method proposed contributes towards (a) unlimited open source use, (b) a low-cost setup, (c) complete guide for any entomologist to adapt in terms of hardware and software, (d) simple to use, and (e) a lightweight data output for collective behavior analysis of mosquitoes. The setup is demonstrated by testing a simple response of mosquitoes in the presence of human odor versus control, one session with continuous human presence as a stimuli and the other with periodic presence. A group of female Aedes aegypti (Linnaeus) mosquitoes are released into a white-background chamber with a transparent acrylic panel on one side. The video feed of the mosquitoes are processed using filtered contours in a threshold-adjustable video. The mosquitoes in the chamber are mapped on the raster where the coordinates of each mosquito are recorded with the corresponding timestamp. The average distance of the blobs within the frames against time forms a spectra where behavioral patterns can be observed directly, whether any collective effect is observed. With this method, 3D tracking will not be required and a more straightforward data output can be obtained.
There are many products claiming to be an electronic solution towards repelling mosquitoes. Several reviews were published in debunking these claims. However, there is a lack of a systematic study on effects of electromagnetic (EM) or more specifically, radio frequency (RF) waves against mosquitoes due to the conclusions made in those years. Therefore, we attempt to establish a fundamental study on female Aedes Aegypti (Linnaeus) mosquitoes by quantifying the collective behavior of the mosquitoes against a continuous stream of low-powered RF signals via a broadband horn antenna using image processing methods. By examining the average lateral and vertical positions of the mosquitoes versus frequency and time, the data shows negligible consistency in the reactions of the mosquitoes toward the different frequencies ranging from 10 to 20,000.00 MHz, with a step of 10 MHz. This was done by examining 33 hours of spatiotemporal data, which was divided into three sessions. All three sessions showed totally different convolutions in the positions in arbitrary units based on the raster scan of the image processing output. Several frequencies apparently showed up to 0.2-70% shift in both lateral and vertical components along the spectrum, without repeatability for all three sessions. This study contributes to the following: A pilot study for establishing the collective effects of RF against mosquitoes, open-source use, and finally a low-cost and easily adaptable platform for the study of EM effects against any insects.
Dengue diagnostics have come a long way. Attempts at breaking away from lab-oriented dengue detection, such as NS1 antigen, IgM or IgG antibodies detection have extensively received numerous coverage. As a result, rapid detection tests (RDTs) have started to gain inroads in medical practice. Rapid detection tests notwithstanding, analysis of blood serum is still a relatively complicated task. This includes the necessity of phlebotomy, centrifugation for blood serum, and other reagent-based tests. Therefore, a non-invasive method of dengue detection was considered. In this study, we present the utility of diffuse reflectance skin spectroscopy (bandwidth of 200-2500nm) on the forearm during the triaging period for dengue screening potential. This is performed with multivariate analysis of 240 triaged febrile/suspected dengue patients. The data is then scrutinized for its clinical validity to be included as either confirmed or probable dengue, or a control group. Based on discriminant analysis of several data normalization models, we can predict the patients' clinical dengue-positivity at ranges of accuracy between ~93-98% depending on mode of the data, with a probably optimal sensitivity and specificity to the clinical diagnosis of ~89% and ~100% respectively. From the outcomes of this study, we recommend further trials with cautious optimism. With these findings, it is hoped that the elusive non-invasive detection of tropical diseases may gain platform in the near future.