Elemental profiles in distant tissues during tumor progression.

BACKGROUND: Essential elements have functions in tumor progression by promoting protumoral cellular processes, such as proliferation, and migration, among others. Obtaining an understanding of how these elements relate to tumor progression processes is of great importance for research. Elemental profile studies in distant tissues, which can be modulated by tumor cells to promote metastasis, have not been sufficiently investigated. The main goal of this study is to evaluate multielemental distribution during tumor progression, focusing on tumor tissue and distant tissues that may be affected. METHODS: Tumor progression in vivo was simulated by inoculating C57BL/6 mice with Lewis Lung Carcinoma (LLC) cells. Samples of the primary tumor and distant tissues were collected during 5 weeks of tumor progression for the control and experimental (tumor-bearing) groups. The biological samples were analyzed using the synchrotron radiation X-Ray fluorescence technique. Data on the concentration of P, S, K, Ca, Mn, Fe, Cu, and Zn in the samples were obtained and statistically analyzed to evaluate the distribution of the elements during tumor progression in the primary tumor as well as distant tissues. RESULTS: It was possible to observe significant changes in the concentrations' distribution of P, S, K, Ca, Mn, Fe, and Cu in distant tissues caused by the presence of tumor cells. It was also possible to detect a greater similarity between tumor tissue (which has the lung as tissue of origin) and a tissue of non-origin, such as the liver, which is an unprecedented result. Moreover, changes in the distributions of concentrations were detected and studied over time for the different tissues analyzed, such as primary tumor, liver and lung, in Control and Tumor groups. CONCLUSIONS: Among other results, this paper could explore the modulation of distant tissues caused by the presence of a primary tumor. This could be achieved by the evaluation of several elements of known biological importance allowing the study of different biological processes involved in cancer. The role of essential elements as modulators of the tumor microenvironment is a relevant aspect of tumor progression and this work is a contribution to the field of tumoral metallomics.

Neonatal mortality rates in Brazilian municipalities: from 1996 to 2017.

OBJECTIVES: Neonatal mortality is a global public health problem, and the efforts to reduce child mortality is one of the goals of the 2030 Agenda for Sustainable Development, launched in 2015 by the United Nations. The availability of historical neonatal mortality rates (NMR) data in Brazilian municipalities is crucial to evaluate trends at local, regional and national level, identifying gaps and vulnerable territories. Therefore, the objective of this article is to offer an integrated dataset containing monthly data in a historical series from 1996 to 2017 with information on all births, neonatal deaths, and NMR (total, early and late components) enriched with information related to the municipality. DATA DESCRIPTION: It is a dataset of historical data with information on the number of births, the number of neonatal deaths, the neonatal mortality rate (including early and late), and geographic information for each month (between January 1996 and December 2017) and Brazilian municipality.

An analysis of malaria in the Brazilian Legal Amazon using divergent association rules.

In data analysis, the mining of frequent patterns plays an important role in the discovery of associations and correlations between data. During this process, it is common to produce thousands of association rules (ARs), making the study of each one arduous. This problem weakens the process of finding useful information. There is a scientific effort to develop approaches capable of filtering interesting patterns, balancing the number of ARs produced with the goal of not being trivial and known by specialists. However, even when such approaches are adopted, the number of produced ARs can still be high. This work contributes by presenting Divergent Association Rules Approach (DARA), a novel approach for obtaining ARs that presents themselves in divergence with the data distribution. DARA is applied right after traditional approaches to filtering interesting patterns. To validate our approach, we studied the dataset related to the occurrence of malaria in the Brazilian Legal Amazon. The discovered patterns highlight that ARs brought relevant insights from the data. This article contributes both in the medical and computer science fields since this novel computational approach enabled new findings regarding malaria in Brazil.

An integrated dataset of malaria notifications in the Legal Amazon.

OBJECTIVES: Malaria is an infectious disease that annually presents around 200,000 cases in Brazil. The availability of data on malaria is crucial for enabling and supporting studies that can promote actions to prevent it. Therefore, the goal of this paper is to contribute to such studies by offering an integrated dataset containing data on reported and suspected cases of malaria in the Brazilian Legal Amazon comprising the period from the years 2009 to 2019. DATA DESCRIPTION: This paper presents a dataset with all medical records of patients who were tested for malaria in the Brazilian Legal Amazon from 2009 to 2019. The dataset has 40 attributes and 22,923,977 records of suspected cases of malaria. Around 12% of the data correspond to confirmed cases of malaria. The attributes include data regarding the notifications, examinations, as well as personal patient information, which are organized into health regions.