Towards a precise test for malaria diagnosis in the Brazilian Amazon: comparison among field microscopy, a rapid diagnostic test, nested PCR, and a computational expert system based on artificial neural networks

Abstract Background Accurate malaria diagnosis is mandatory for the treatment and management of severe cases. Moreover, individuals with asymptomatic malaria are not usually screened by health care facilities, which further complicates disease control efforts. The present study compared the performances of a malaria rapid diagnosis test (RDT), the thick blood smear method and nested PCR for the diagnosis of symptomatic malaria in the Brazilian Amazon. In addition, an innovative computational approach was tested for the diagnosis of asymptomatic malaria. Methods The study was divided in two parts. For the first part, passive case detection was performed in 311 individuals with malaria-related symptoms from a recently urbanized community in the Brazilian Amazon. A cross-sectional investigation compared the diagnostic performance of the RDT Optimal-IT, nested PCR and light microscopy. The second part of the study involved active case detection of asymptomatic malaria in 380 individuals from riverine communities in Rondônia, Brazil. The performances of microscopy, nested PCR and an expert computational system based on artificial neural networks (MalDANN) using epidemiological data were compared. Results Nested PCR was shown to be the gold standard for diagnosis of both symptomatic and asymptomatic malaria because it detected the major number of cases and presented the maximum specificity. Surprisingly, the RDT was superior to microscopy in the diagnosis of cases with low parasitaemia. Nevertheless, RDT could not discriminate the Plasmodium species in 12 cases of mixed infections (Plasmodium vivax + Plasmodium falciparum). Moreover, the microscopy presented low performance in the detection of asymptomatic cases (61.25% of correct diagnoses). The MalDANN system using epidemiological data was worse that the light microscopy (56% of correct diagnoses). However, when information regarding plasma levels of interleukin-10 and interferon-gamma were inputted, the MalDANN performance sensibly increased (80% correct diagnoses). Conclusions An RDT for malaria diagnosis may find a promising use in the Brazilian Amazon integrating a rational diagnostic approach. Despite the low performance of the MalDANN test using solely epidemiological data, an approach based on neural networks may be feasible in cases where simpler methods for discriminating individuals below and above threshold cytokine levels are available.

A simple-versatile approach to achieve all-Si-based optical micro-cavities

At present, solid thin films are recognized by their well established and mature processing technology that is able to produce components which, depending on their main characteristics, can perform either passive or active functions. Additionally, Si-based materials in the form of thin films perfectly match the concept of miniaturized and low-consumption devices-as required in various modern technological applications. Part of these aspects was considered in the present work that was concerned with the study of optical micro-cavities entirely based on silicon and silicon nitride thin films. The structures were prepared by the sputtering deposition method which, due to the adopted conditions (atmosphere and deposition rate) and arrangement of layers, provided cavities operating either in the visible (at ~ 670 nm) or in the near-infrared (at ~ 1560 nm) wavelength ranges. The main differential of the work relies on the construction of optical microcavities with a reduced number of periods whose main properties can be changed by thermal annealing treatments. The work also discusses the angle-dependent behavior of the optical transmission profiles as well as the use of the COMSOL software package to simulate the microcavities.