Development of technologies to support the diagnosis of infectious diseases and cancer to support the primary health care

54/2017). Publisher Copyright: © 2022, The Author(s).Purpose: Primary Health Care (PHC) is the coordinator of health care in Brazil and needs to be strengthened in the diagnostic field to increase health care quality. Aiming to improve the diagnostic tools currently available in PHC, this work describes the process of development and validation of two point-of-care biomedical devices for screening patients with syphilis or different kinds of cancer. Methods: The development of these devices followed nine stages of action based on the requirements established by the Ministry of Health. During development, both systems followed the stages of circuit planning, software simulation to verify the components used, cost assessment for the acquisition of features, simulation in contact matrix, development of the embedded system, and planning of the printed circuit board and storage box. Results: Both devices underwent preliminary functionality tests to assess their quality. The performance tests applied on the device to diagnose syphilis performed 8,733,194 requests, with a flow of 2426 requests/second, reaching the desired parameters of robustness, integrity, durability, and stability. In addition, functioning tests on the cancer-screening device indicated the ability to detect standard fluorescence in a minimal (150 uL) sample volume. Conclusions: Together, the methodology used for developing the devices resulted in promising equipment to improve the diagnosis and meet the requirements for executing technologies for testing and triaging patients in PHC.publishersversionpublishe

Minimum plot size to evaluate potato tuber yield traits

<div><p>ABSTRACT The proper plot size is essential to reduce experimental error and thereby maximize precision of data obtained in an experiment. The objective of this work was to estimate the minimum number of plants per plot to assess tuber yield traits of potato genotypes. Four advanced potato clones (F161-07-02, F189-06-09, F97-08-07 and F131-08-06) of the breeding program of Embrapa were evaluated. The experiment was conducted in the fall season of 2015, in Canoinhas, Santa Catarina State, Brazil. A randomized complete block design with two replications of 20-plant two-row plots was used. At 112 days after planting, plants of each plot were individually harvested and evaluated for tuber yield traits. The modified maximum curvature and the repeatability methods were used to estimate the minimum plant number to represent the genotypes in each plot. We found that 10 to 14 plants per plot are enough to guarantee an adequate precision and predict the real value of the individuals for tuber yield traits in experiments of two replications, considering an R2 of 90% for the repeatability method.</p></div

Performance of potato cultivars under different planting spacing in a naturally-infested soil by Ralstonia solanacearum

<p></p><p>ABSTRACT In recent years, Brazilian potato cultivars were released, such as BRSIPR Bel and BRS Camila, as alternatives to the imported cultivars, traditionally planted in Brazil. We evaluated the cultivars BRSIPR Bel, BRS Camila and Agata growing under four planting spacing (15, 20, 25 and 30 cm among seeds in line) in a field naturally infested with Ralstonia solanacearum in Brasilia, Brazil. The experimental design was a split plot with four replications, spacing as plots and cultivars as subplots. At 59 days after planting (DAP), the incidence of plants with symptoms of bacterial wilt was evaluated and during harvest, at 116 DAP, total mass of tubers, mass of marketable tubers, total number of tubers, and number of marketable tubers were evaluated. ‘BRSIPR Bel’, ‘Agata’ and ‘BRS Camila’ presented susceptibility levels to bacterial wilt of 20, 30 and 80% of symptomatic plants at 59 DAP, respectively. In response to a higher bacterial wilt susceptibility, ‘BRS Camila’ had the lowest yield. No effect of plant spacing was observed. ‘BRSIPR Bel’ and ‘Agata’ had a higher resistance level in comparison to ‘BRS Camila’, which led to a higher productivity under the evaluated conditions.</p><p></p

Osteoporosis screening using machine learning and electromagnetic waves

Abstract Osteoporosis is a disease characterized by impairment of bone microarchitecture that causes high socioeconomic impacts in the world because of fractures and hospitalizations. Although dual-energy X-ray absorptiometry (DXA) is the gold standard for diagnosing the disease, access to DXA in developing countries is still limited due to its high cost, being present only in specialized hospitals. In this paper, we analyze the performance of Osseus, a low-cost portable device based on electromagnetic waves that measures the attenuation of the signal that crosses the medial phalanx of a patient’s middle finger and was developed for osteoporosis screening. The analysis is carried out by predicting changes in bone mineral density using Osseus measurements and additional common risk factors used as input features to a set of supervised classification models, while the results from DXA are taken as target (real) values during the training of the machine learning algorithms. The dataset consisted of 505 patients who underwent osteoporosis screening with both devices (DXA and Osseus), of whom 21.8% were healthy and 78.2% had low bone mineral density or osteoporosis. A cross-validation with k-fold = 5 was considered in model training, while 20% of the whole dataset was used for testing. The obtained performance of the best model (Random Forest) presented a sensitivity of 0.853, a specificity of 0.879, and an F1 of 0.859. Since the Random Forest (RF) algorithm allows some interpretability of its results (through the impurity check), we were able to identify the most important variables in the classification of osteoporosis. The results showed that the most important variables were age, body mass index, and the signal attenuation provided by Osseus. The RF model, when used together with Osseus measurements, is effective in screening patients and facilitates the early diagnosis of osteoporosis. The main advantages of such early screening are the reduction of costs associated with exams, surgeries, treatments, and hospitalizations, as well as improved quality of life for patients