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Article ; Online: No BRAF p.V600E mutation detection in ameloblastoma liquid biopsy-based analysis by ddPCR.

Gomes, Isadora Pereira / Miguita, Lucyene / Gomes-Fernandes, Bianca / Coura, Bruna Pizziolo / Castro, Wagner Henriques de / Carneiro, Juliana Garcia / De Marco, Luiz Armando / Gomez, Ricardo Santiago / Bastos-Rodrigues, Luciana / Gomes, Carolina Cavalieri

Oral oncology

2023 Volume 149, Page(s) 106666

MeSH term(s)	Humans ; Ameloblastoma/diagnosis ; Ameloblastoma/genetics ; Liquid Biopsy ; Polymerase Chain Reaction ; Mutation ; Proto-Oncogene Proteins B-raf/genetics
Chemical Substances	Proto-Oncogene Proteins B-raf (EC 2.7.11.1)
Language	English
Publishing date	2023-12-25
Publishing country	England
Document type	Letter
ZDB-ID	1120465-5
ISSN	1879-0593 ; 0964-1955 ; 1368-8375
ISSN (online)	1879-0593
ISSN	0964-1955 ; 1368-8375
DOI	10.1016/j.oraloncology.2023.106666
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Article ; Online: Getting knowledge to provide care: prevalence and factors associated with Sexually Transmitted Infections in immigrants from Goiás.

Silva, Carla de Almeida / Silva, Grazielle Rosa da Costa / Martins, Thaynara Lorrane Silva / Moura, Winny Éveny Alves / Gomes, Davi Oliveira / Bandeira, Gabriela Nolasco / Carneiro, Megmar Aparecida Dos Santos / Gonzalez, Roxana Isabel Cardozo / Pacheco, Leonora Rezende / Zanchetta, Margareth Santos / Lima, Juliana de Oliveira Roque E / Teles, Sheila Araujo / Caetano, Karlla Antonieta Amorim

Revista da Escola de Enfermagem da U S P

2024 Volume 57, Issue spe, Page(s) e20230034

Abstract: Objective: To estimate the prevalence of Sexually Transmitted Infections (STIs) in immigrants and refugees living in the metropolitan region of Goiânia, Goiás.: Method: This is a cross-sectional and analytical study. Data collection was carried out ... ...

Abstract	Objective: To estimate the prevalence of Sexually Transmitted Infections (STIs) in immigrants and refugees living in the metropolitan region of Goiânia, Goiás. Method: This is a cross-sectional and analytical study. Data collection was carried out from July 2019 to January 2020 and 308 immigrants and refugees were included in the sample. All were underwent face-to-face interviews and were tested for HIV, Syphilis, and Hepatitis B, using rapid tests. Results: The general prevalence for any of the STIs investigated was 8.8% (95%CI 6.0% - 12.3%), being 5.8% (95%CI 3.6% - 8.9%) for Hepatitis B, 2.3% for Syphilis (95%CI 1.00% - 4.4%) and 0.7% for HIV (95%CI 0.1% - 2.1%). Multiple analysis, using logistic regression, showed that the variables male gender (OR = 2.7) and length of time living in Brazil (OR = 2.6) were significantly associated with STIs (p < 0.05). Conclusion: The results of this study suggest that STIs are a health problem in immigrants/refugees, which appear to be enhanced with the length of migration in the country. Public policies that guarantee health care for this population shall be considered.
MeSH term(s)	Male ; Humans ; Syphilis/epidemiology ; Brazil/epidemiology ; Cross-Sectional Studies ; Prevalence ; Sexually Transmitted Diseases/epidemiology ; Hepatitis B ; Emigrants and Immigrants ; HIV Infections/epidemiology
Language	Portuguese
Publishing date	2024-01-08
Publishing country	Brazil
Document type	Journal Article
ZDB-ID	2411320-7
ISSN	1980-220X ; 1980-220X
ISSN (online)	1980-220X
ISSN	1980-220X
DOI	10.1590/1980-220X-REEUSP-2023-0034en
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Article ; Online: Motor imagery classification using sparse representations: an exploratory study.

de Menezes, José Antonio Alves / Gomes, Juliana Carneiro / de Carvalho Hazin, Vitor / Dantas, Júlio César Sousa / Rodrigues, Marcelo Cairrão Araújo / Dos Santos, Wellington Pinheiro

Scientific reports

2023 Volume 13, Issue 1, Page(s) 15585

Abstract: The non-stationary nature of the EEG signal poses challenges for the classification of motor imagery. sparse representation classification (SRC) appears as an alternative for classification of untrained conditions and, therefore, useful in motor imagery. ...

Abstract	The non-stationary nature of the EEG signal poses challenges for the classification of motor imagery. sparse representation classification (SRC) appears as an alternative for classification of untrained conditions and, therefore, useful in motor imagery. Empirical mode decomposition (EMD) deals with signals of this nature and appears at the rear of the classification, supporting the generation of features. In this work we evaluate the combination of these methods in a multiclass classification problem, comparing them with a conventional method in order to determine if their performance is regular. For comparison with SRC we use multilayer perceptron (MLP). We also evaluated a hybrid approach for classification of sparse representations with MLP (RSMLP). For comparison with EMD we used filtering by frequency bands. Feature selection methods were used to select the most significant ones, specifically Random Forest and Particle Swarm Optimization. Finally, we used data augmentation to get a more voluminous base. Regarding the first dataset, we observed that the classifiers that use sparse representation have results equivalent to each other, but they outperform the conventional MLP model. SRC and SRMLP achieve an average accuracy of [Formula: see text] and [Formula: see text] respectively while the MLP is [Formula: see text], representing a gain between [Formula: see text] and [Formula: see text]. The use of EMD in relation to other feature processing techniques is not superior. However, EMD does not influence negatively, there is an opportunity for improvement. Finally, the use of data augmentation proved to be important to obtain relevant results. In the second dataset, we did not observe the same results. Models based on sparse representation (SRC, SRMLP, etc.) have on average a performance close to other conventional models, but without surpassing them. The best sparse models achieve an average accuracy of [Formula: see text] among the subjects in the base, while other model reach [Formula: see text]. The improvement of self-adaptive mechanisms that respond efficiently to the user's context is a good way to achieve improvements in motor imagery applications. However, other scenarios should be investigated, since the advantage of these methods was not proven in all datasets studied. There is still room for improvement, such as optimizing the dictionary of sparse representation in the context of motor imagery. Investing efforts in synthetically increasing the training base has also proved important to reduce the costs of this group of applications.
Language	English
Publishing date	2023-09-20
Publishing country	England
Document type	Journal Article
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-023-42790-y
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Article ; Online: COVID-19's influence on cardiac function: a machine learning perspective on ECG analysis.

Gomes, Juliana Carneiro / de Santana, Maíra Araújo / Masood, Aras Ismael / de Lima, Clarisse Lins / Dos Santos, Wellington Pinheiro

Medical & biological engineering & computing

2023 Volume 61, Issue 5, Page(s) 1057–1081

Abstract: In December 2019, the spread of the SARS-CoV-2 virus to the world gave rise to probably the biggest public health problem in the world: the COVID-19 pandemic. Initially seen only as a disease of the respiratory system, COVID-19 is actually a blood ... ...

Abstract	In December 2019, the spread of the SARS-CoV-2 virus to the world gave rise to probably the biggest public health problem in the world: the COVID-19 pandemic. Initially seen only as a disease of the respiratory system, COVID-19 is actually a blood disease with effects on the respiratory tract. Considering its influence on hematological parameters, how does COVID-19 affect cardiac function? Is it possible to support the clinical diagnosis of COVID-19 from the automatic analysis of electrocardiography? In this work, we sought to investigate how COVID-19 affects cardiac function using a machine learning approach to analyze electrocardiography (ECG) signals. We used a public database of ECG signals expressed as photographs of printed signals, obtained in the context of emergency care. This database has signals associated with abnormal heartbeat, myocardial infarction, history of myocardial infarction, COVID-19, and healthy heartbeat. We propose a system to support the diagnosis of COVID-19 based on hybrid deep architectures composed of pre-trained convolutional neural networks for feature extraction and Random Forests for classification. We investigated the LeNet, ResNet, and VGG16 networks. The best results were obtained with the VGG16 and Random Forest network with 100 trees, with attribute selection using particle swarm optimization. The instance size has been reduced from 4096 to 773 attributes. In the validation step, we obtained an accuracy of 94%, kappa index of 0.91, and sensitivity, specificity, and area under the ROC curve of 100%. This work showed that the influence of COVID-19 on cardiac function is quite considerable: COVID-19 did not present confusion with any heart disease, nor with signs of healthy individuals. It is also possible to build a solution to support the clinical diagnosis of COVID-19 in the context of emergency care from a non-invasive and technologically scalable solution, based on hybrid deep learning architectures.
MeSH term(s)	Humans ; COVID-19/diagnosis ; SARS-CoV-2 ; Pandemics ; Machine Learning ; Electrocardiography ; Myocardial Infarction/diagnosis
Language	English
Publishing date	2023-01-20
Publishing country	United States
Document type	Journal Article
ZDB-ID	282327-5
ISSN	1741-0444 ; 0025-696X ; 0140-0118
ISSN (online)	1741-0444
ISSN	0025-696X ; 0140-0118
DOI	10.1007/s11517-023-02773-7
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Article ; Online: Evaluation of factors predicting the benefit from systemic oncological treatment for severely ill hospitalized patients: a retrospective study.

Neves, Milena Brachmans Mascarenhas / Neves, Yuri Costa Sarno / Bomonetto, Juliana Vieira Biason / Matos, Priscila Prais Carneiro / Giglio, Auro Del / Cubero, Daniel de Iracema Gomes

BMC palliative care

2023 Volume 22, Issue 1, Page(s) 131

Abstract: Background: Patients with cancer in the disease's end-stage with poor performance represent a challenging clinical scenario, as they have high chance of a fatal outcome due to clinical conditions, oncological emergencies, and/or metastatic disease. This ...

Abstract	Background: Patients with cancer in the disease's end-stage with poor performance represent a challenging clinical scenario, as they have high chance of a fatal outcome due to clinical conditions, oncological emergencies, and/or metastatic disease. This study examines the factors predicting the potential benefit of "urgent" chemotherapy during hospitalization in this setting, thus addressing a research gap. Methods: This retrospective observational study was conducted in the largest cancer center in the outskirts of São Paulo. It identified factors predicting the benefit from antineoplastic treatment in severe in-hospital patients admitted during 2019-2020, considering post-chemotherapy survival time as the main dependent variable. Data were retrieved from medical records. All patients aged ≥ 18 years, with an ECOG-PS score ≥ 2, and undergoing non-elective systemic cancer treatment were included. Results: This study evaluated 204 records, of which 89 were included in the final analysis. A statistically significant association with the worse outcome (death within 30 days of chemotherapy) was found with higher ECOG performance status; chemotherapy dose reduction; lower values of serum albumin, hemoglobin, and creatinine clearance; and higher values of leukocytes, neutrophils, direct bilirubin, urea, and C-reactive protein. In the multivariate analysis, only albumin remained statistically associated with the outcome (hazard ratio = 0.35; confidence interval: 0.14, 0.90; p = 0.034). Conclusions: Serum albumin and other clinical and laboratory variables might be associated with early post-treatment deaths in patients with cancer. The study data might help guide the decision to administer systemic treatment in this scenario and manage critically ill patients. This study adds to our knowledge of the factors predicting the objective benefits from "heroic" or "urgent" chemotherapy for hospitalized and severely ill patients with cancer.
MeSH term(s)	Humans ; Retrospective Studies ; Brazil ; Medical Oncology ; Inpatients ; Albumins
Chemical Substances	Albumins
Language	English
Publishing date	2023-09-06
Publishing country	England
Document type	Observational Study ; Journal Article
ZDB-ID	2091556-1
ISSN	1472-684X ; 1472-684X
ISSN (online)	1472-684X
ISSN	1472-684X
DOI	10.1186/s12904-023-01256-8
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Article ; Online: Genomic investigation on genes related to mercury metabolism in Amazonian indigenous populations.

Carvalho, Victor Hugo Valente / Rodrigues, Juliana Carla Gomes / Vinagre, Lui Wallacy Morikawa Souza / Pereira, Esdras Edgar Batista / Monte, Natasha / Fernandes, Marianne Rodrigues / Ribeiro-Dos-Santos, André Maurício / Guerreiro, João Farias / Ribeiro-Dos-Santos, Ândrea / Dos Santos, Sidney Emanuel Batista / Dos Santos, Ney Pereira Carneiro

The Science of the total environment

2024 Volume 923, Page(s) 171232

Abstract: Studies have identified elevated levels of mercury in Amazonian Indigenous individuals, highlighting them as one of the most exposed to risks. In the unique context of the Brazilian Indigenous population, it is crucial to identify genetic variants with ... ...

Abstract	Studies have identified elevated levels of mercury in Amazonian Indigenous individuals, highlighting them as one of the most exposed to risks. In the unique context of the Brazilian Indigenous population, it is crucial to identify genetic variants with clinical significance to better understand vulnerability to mercury and its adverse effects. Currently, there is a lack of research on the broader genomic profile of Indigenous people, particularly those from the Amazon region, concerning mercury contamination. Therefore, the aim of this study was to assess the genomic profile related to the processes of mercury absorption, distribution, metabolism, and excretion in 64 Indigenous individuals from the Brazilian Amazon. We aimed to determine whether these individuals exhibit a higher susceptibility to mercury exposure. Our study identified three high-impact variants (GSTA1 rs1051775, GSTM1 rs1183423000, and rs1241704212), with the latter two showing a higher frequency in the study population compared to global populations. Additionally, we discovered seven new variants with modifier impact and a genomic profile different from the worldwide populations. These genetic variants may predispose the study population to more harmful mercury exposure compared to global populations. As the first study to analyze broader genomics of mercury metabolism pathways in Brazilian Amazonian Amerindians, we emphasize that our research aims to contribute to public policies by utilizing genomic investigation as a method to identify populations with a heightened susceptibility to mercury exposure.
MeSH term(s)	Humans ; Mercury/analysis ; Indians, South American/genetics ; Indigenous Peoples ; Genomics ; Brazil
Chemical Substances	Mercury (FXS1BY2PGL)
Language	English
Publishing date	2024-02-23
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	121506-1
ISSN	1879-1026 ; 0048-9697
ISSN (online)	1879-1026
ISSN	0048-9697
DOI	10.1016/j.scitotenv.2024.171232
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Article ; Online: Physical and Mechanical Characterization of Titica Vine (

da Cunha, Juliana Dos Santos Carneiro / Nascimento, Lucio Fabio Cassiano / da Luz, Fernanda Santos / Monteiro, Sergio Neves / Lemos, Maurício Ferrapontoff / da Silva, Cristina Gomes / Simonassi, Noan Tonini

Polymers

2021 Volume 13, Issue 23

Abstract: Titica vine ( ...

Abstract	Titica vine (
Language	English
Publishing date	2021-11-24
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2527146-5
ISSN	2073-4360 ; 2073-4360
ISSN (online)	2073-4360
ISSN	2073-4360
DOI	10.3390/polym13234079
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Article ; Online: Frequency of germline genetic variants in women with a personal or family history of breast cancer from Brazil.

Pereira, Júlia Zanon / Carneiro, Juliana Garcia / Vieira, Mariana Sousa / Valente, Bruna Mattioly / de Oliveira, Pâmella Zorzan / Mello, Carolina Lins / de Campos, Caroline Leonel Vasconcelos / Gomes, Karina Braga

Molecular biology reports

2022 Volume 49, Issue 10, Page(s) 9509–9520

Abstract: Background: About 5-10% of breast cancer cases are related to genetic and hereditary factors. The application of Next Generation Sequencing (NGS) in oncology has allowed the identification of genetic variants present in several genes related to the ... ...

Abstract	Background: About 5-10% of breast cancer cases are related to genetic and hereditary factors. The application of Next Generation Sequencing (NGS) in oncology has allowed the identification of genetic variants present in several genes related to the increased risk of breast cancer. This study aimed to determine the frequency of germline genetic variants in patients with a family and/or personal history of breast cancer. Methods: An analysis of positive reports from NGS panels was carried out in female individuals with a personal and/or family history of breast cancer, present in the database of a private laboratory in Brazil. Results: From about 2000 reports, 183 individuals presented 219 different germline genetic variants. The genes with the highest number of variants were BRCA2 (16.0%), ATM (15.0%) and BRCA1 (12.8%). Among the variants found, 78 were either pathogenic or probably pathogenic, accounting for 35% of all variants discovered. The gene with the highest proportion of pathogenic/probably pathogenic variants was TP53 (80%) and the most frequent pathogenic variant was also reported in this gene (c.1010G > A p.(Arg337His)). Furthermore, the study obtained a high proportion of variants of uncertain significance (VUS) (65%) and approximately 32% of the variants found were in genes of moderate penetrance. Conclusions: Our results could improve the risk estimation and clinical follow-up of Brazilian patients with a history of breast cancer.
MeSH term(s)	BRCA1 Protein/genetics ; Brazil/epidemiology ; Breast Neoplasms/epidemiology ; Breast Neoplasms/genetics ; Breast Neoplasms/pathology ; Female ; Genes, BRCA2 ; Genetic Predisposition to Disease ; Germ Cells ; Germ-Line Mutation/genetics ; Humans
Chemical Substances	BRCA1 Protein
Language	English
Publishing date	2022-08-18
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	186544-4
ISSN	1573-4978 ; 0301-4851
ISSN (online)	1573-4978
ISSN	0301-4851
DOI	10.1007/s11033-022-07840-0
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Article ; Online: Motor imagery classification using sparse representations

José Antonio Alves de Menezes / Juliana Carneiro Gomes / Vitor de Carvalho Hazin / Júlio César Sousa Dantas / Marcelo Cairrão Araújo Rodrigues / Wellington Pinheiro dos Santos

Scientific Reports, Vol 13, Iss 1, Pp 1-

an exploratory study

2023 Volume 24

Abstract: Abstract The non-stationary nature of the EEG signal poses challenges for the classification of motor imagery. sparse representation classification (SRC) appears as an alternative for classification of untrained conditions and, therefore, useful in motor ...

Abstract	Abstract The non-stationary nature of the EEG signal poses challenges for the classification of motor imagery. sparse representation classification (SRC) appears as an alternative for classification of untrained conditions and, therefore, useful in motor imagery. Empirical mode decomposition (EMD) deals with signals of this nature and appears at the rear of the classification, supporting the generation of features. In this work we evaluate the combination of these methods in a multiclass classification problem, comparing them with a conventional method in order to determine if their performance is regular. For comparison with SRC we use multilayer perceptron (MLP). We also evaluated a hybrid approach for classification of sparse representations with MLP (RSMLP). For comparison with EMD we used filtering by frequency bands. Feature selection methods were used to select the most significant ones, specifically Random Forest and Particle Swarm Optimization. Finally, we used data augmentation to get a more voluminous base. Regarding the first dataset, we observed that the classifiers that use sparse representation have results equivalent to each other, but they outperform the conventional MLP model. SRC and SRMLP achieve an average accuracy of $$75.95\%$$ 75.95 % and $$82.51\%$$ 82.51 % respectively while the MLP is $$72.38\%$$ 72.38 % , representing a gain between $$4.93\%$$ 4.93 % and $$14\%$$ 14 % . The use of EMD in relation to other feature processing techniques is not superior. However, EMD does not influence negatively, there is an opportunity for improvement. Finally, the use of data augmentation proved to be important to obtain relevant results. In the second dataset, we did not observe the same results. Models based on sparse representation (SRC, SRMLP, etc.) have on average a performance close to other conventional models, but without surpassing them. The best sparse models achieve an average accuracy of $$95.43\%$$ 95.43 % among the subjects in the base, while other model reach $$98.33\%$$ 98.33 % . The ...
Keywords	Medicine ; R ; Science ; Q
Subject code	004
Language	English
Publishing date	2023-09-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Periodontitis in individuals with few remaining teeth and a high gingival bleeding index increases the probability of dyslipidemia.

Gomes-Filho, Isaac Suzart / Freitas, Taciane Oliveira Bet / Cruz, Simone Seixas da / Trindade, Soraya Castro / Figueiredo, Ana Claudia Morais Godoy / Couto Souza, Paulo Henrique / Cerqueira, Eneida de Moraes Marcílio / Hintz, Alexandre Marcelo / Carneiro, Daline Oliveira / Lacerda, Juliana Andrade de / Seymour, Gregory John / Scannapieco, Frank Andrew / Loomer, Peter Michael / Passos-Soares, Johelle de Santana

Journal of periodontology

2023 Volume 94, Issue 10, Page(s) 1243–1253

Abstract: Background: Dyslipidemia, a silent multifactorial condition, is characterized by changes in blood lipid levels, affecting all socioeconomic strata, increasing the risk for atherosclerotic diseases. This study investigated whether there is an association ...

Abstract	Background: Dyslipidemia, a silent multifactorial condition, is characterized by changes in blood lipid levels, affecting all socioeconomic strata, increasing the risk for atherosclerotic diseases. This study investigated whether there is an association between dyslipidemia and the combined exposure of periodontitis plus the number of remaining teeth, gingival bleeding, or caries. Methods: A two-center cross-sectional study was conducted involving 1270 individuals, with a minimum age of 18 years. Socioeconomic and demographic data, health conditions, lifestyle parameters, and anthropometric, biochemical, and oral clinical examinations were performed. The exposures considered were the presence of periodontitis, dental caries, number of remaining teeth, and gingival bleeding. The outcome was dyslipidemia as defined by the Brazilian Guidelines on Dyslipidemia and Prevention of Atherosclerosis. The combined associations between periodontitis plus other oral health conditions and dyslipidemia were estimated using confounder-adjusted prevalence ratios (PR Results: The occurrence of dyslipidemia was 70.1% and periodontitis was 84.1%. A positive association between periodontitis and dyslipidemia existed: PR Conclusion: Periodontitis combined with fewer than 11 teeth doubled the likelihood of being diagnosed with dyslipidemia.
MeSH term(s)	Humans ; Adolescent ; Dental Caries ; Cross-Sectional Studies ; Periodontitis/complications ; Periodontitis/epidemiology ; Mouth Diseases ; Probability
Language	English
Publishing date	2023-06-13
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	390921-9
ISSN	1943-3670 ; 0022-3492 ; 1049-8885 ; 0095-960X
ISSN (online)	1943-3670
ISSN	0022-3492 ; 1049-8885 ; 0095-960X
DOI	10.1002/JPER.23-0091
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