Graded Atmospheres of Volatile Pyrethroid Overlaid on Host Cues Can Be Established and Quantified Within a Novel Flight Chamber for Mosquito Behavior Studies

Prediction of malaria positivity using patients' demographic and environmental features and clinical symptoms to complement parasitological confirmation before treatment

BACKGROUND

Current malaria diagnosis methods that rely on microscopy and Histidine Rich Protein-2 (HRP2)-based rapid diagnostic tests (RDT) have drawbacks that necessitate the development of improved and complementary malaria diagnostic methods to overcome some or all these limitations. Consequently, the addition of automated detection and classification of malaria using laboratory methods can provide patients with more accurate and faster diagnosis. Therefore, this study used a machine-learning model to predict Plasmodium falciparum (Pf) antigen positivity (presence of malaria) based on sociodemographic behaviour, environment, and clinical features.

METHOD

Data from 200 Nigerian patients were used to develop predictive models using nested cross-validation and sequential backward feature selection (SBFS), with 80% of the dataset randomly selected for training and optimisation and the remaining 20% for testing the models. Outcomes were classified as Pf-positive or Pf-negative, corresponding to the presence or absence of malaria, respectively.

RESULTS

Among the three machine learning models examined, the penalised logistic regression model had the best area under the receiver operating characteristic curve for the training set (AUC = 84%; 95% confidence interval [CI]: 75-93%) and test set (AUC = 83%; 95% CI: 63-100%). Increased odds of malaria were associated with higher body weight (adjusted odds ratio (AOR) = 4.50, 95% CI: 2.27 to 8.01, p < 0.0001). Even though the association between the odds of having malaria and body temperature was not significant, patients with high body temperature had higher odds of testing positive for the Pf antigen than those who did not have high body temperature (AOR = 1.40, 95% CI: 0.99 to 1.91, p = 0.068). In addition, patients who had bushes in their surroundings (AOR = 2.60, 95% CI: 1.30 to 4.66, p = 0.006) or experienced fever (AOR = 2.10, 95% CI: 0.88 to 4.24, p = 0.099), headache (AOR = 2.07; 95% CI: 0.95 to 3.95, p = 0.068), muscle pain (AOR = 1.49; 95% CI: 0.66 to 3.39, p = 0.333), and vomiting (AOR = 2.32; 95% CI: 0.85 to 6.82, p = 0.097) were more likely to experience malaria. In contrast, decreased odds of malaria were associated with age (AOR = 0.62, 95% CI: 0.41 to 0.90, p = 0.012) and BMI (AOR = 0.47, 95% CI: 0.26 to 0.80, p = 0.006).

CONCLUSION

Newly developed routinely collected baseline sociodemographic, environmental, and clinical features to predict Pf antigen positivity may be a valuable tool for clinical decision-making.

Engineered Human Tissue as A New Platform for Mosquito Bite-Site Biology Investigations

Vector-borne diseases transmitted through the bites of hematophagous arthropods, such as mosquitoes, continue to be a significant threat to human health globally. Transmission of disease by biting arthropod vectors includes interactions between (1) saliva expectorated by a vector during blood meal acquisition from a human host, (2) the transmitted vector-borne pathogens, and (3) host cells present at the skin bite site. Currently, the investigation of bite-site biology is challenged by the lack of model 3D human skin tissues for in vitro analyses. To help fill this gap, we have used a tissue engineering approach to develop new stylized human dermal microvascular bed tissue approximates-complete with warm blood-built with 3D capillary alginate gel (Capgel) biomaterial scaffolds. These engineered tissues, termed a Biologic Interfacial Tissue-Engineered System (BITES), were cellularized with either human dermal fibroblasts (HDFs) or human umbilical vein endothelial cells (HUVECs). Both cell types formed tubular microvessel-like tissue structures of oriented cells (82% and 54% for HDFs and HUVECs, respectively) lining the unique Capgel parallel capillary microstructures. Female Aedes (Ae.) aegypti mosquitoes, a prototypic hematophagous biting vector arthropod, swarmed, bit, and probed blood-loaded HDF BITES microvessel bed tissues that were warmed (34-37 °C), acquiring blood meals in 151 ± 46 s on average, with some ingesting ≳4 µL or more of blood. Further, these tissue-engineered constructs could be cultured for at least three (3) days following blood meal acquisitions. Altogether, these studies serve as a powerful proof-of-concept demonstration of the innovative BITES platform and indicate its potential for the future investigation of arthropod bite-site cellular and molecular biology.