Biology subjects

Ranford-Cartwright, L.

Publications and source records attributed to Ranford-Cartwright, L..

3 recordsLinked to original sources

bioRxiv2019

Detection of malaria in insectary-reared Anopheles gambiae using near-infrared spectroscopy

Large-scale surveillance of mosquito populations is crucial to assess the intensity of vector-borne disease transmission and the impact of control interventions. However, there is a lack of accurate, cost-effective and high-throughput tools for mass-screening of vectors. This study demonstrates proof-of-concept that near-infrared spectroscopy (NIRS) is capable of rapidly identifying laboratory strains of human malaria infection in African mosquito vectors. By using partial least square regression models based on malaria-infected and uninfected Anopheles gambiae mosquitoes, we showed that NIRS can detect oocyst- and sporozoite-stage Plasmodium falciparum infections with 88% and 95% accuracy, respectively. Accurate, low-cost, reagent-free screening of mosquito populations enabled by NIRS could revolutionize surveillance and elimination strategies for the most important human malaria parasite in its primary African vector species. Further research is needed to evaluate how the method performs in the field following adjustments in the training datasets to include data from wild-caught infected and uninfected mosquitoes.

epidemiology↗

bioRxiv2018

Prediction of malaria mosquito species and population age structure using mid-infrared spectroscopy and supervised machine learning

Despite the global efforts made in the fight against malaria, the disease is resurging. One of the main causes is the resistance that Anopheles mosquitoes, vectors of the disease, have developed to insecticides. Anopheles must survive for at least 12 days to possibly transmit malaria. Therefore, to evaluate and improve malaria vector control interventions, it is imperative to monitor and accurately estimate the age distribution of mosquito populations as well as total population sizes. However, estimating mosquito age is currently a slow, imprecise, and labour-intensive process that can only distinguish under-from over-four-day-old female mosquitoes. Here, we demonstrate a machine-learning based approach that utilizes mid-infrared spectra of mosquitoes to characterize simultaneously, and with unprecedented accuracy, both age and species identity of females of the malaria vectors Anopheles gambiae and An. arabiensis mosquitoes within their respective populations. The prediction of the age structures was statistically indistinguishable from true modelled distributions. The method has a negligible cost per mosquito, does not require highly trained personnel, is substantially faster than current techniques, and so can be easily applied in both laboratory and field settings. Our results show that, with larger mid-infrared spectroscopy data sets, this technique can be further improved and expanded to vectors of other diseases such as Zika and Dengue.

bioinformatics↗

bioRxiv2017

Detection Of Human Disease Conditions By Single-Cell Morpho-Rheological Phenotyping Of Whole Blood

Blood is arguably the most important bodily fluid and its analysis provides crucial health status information. A first routine measure to narrow down diagnosis in clinical practice is the differential blood count, determining the frequency of all major blood cells. What is lacking to advance initial blood diagnostics is an unbiased and quick functional assessment of blood that can narrow down the diagnosis and generate specific hypotheses. To address this need, we introduce the continuous, cell-by-cell morpho-rheological (MORE) analysis of whole blood, without labeling, enrichment or separation, at rates of 1,000 cells/sec. In a drop of blood we can identify all major blood cells and characterize their pathological changes in several disease conditions in vitro and in patient samples. This approach takes previous results of mechanical studies on specifically isolated blood cells to the level of application directly in whole blood and adds a functional dimension to conventional blood analysis.

biophysics↗