JOSE EDUARDO KRIEGER
Projetos de Pesquisa
Unidades Organizacionais
Departamento de Cardio-Pneumologia, Faculdade de Medicina - Docente
Instituto do Coração, Hospital das Clínicas, Faculdade de Medicina
LIM/13 - Laboratório de Genética e Cardiologia Molecular, Hospital das Clínicas, Faculdade de Medicina - Líder
Instituto do Coração, Hospital das Clínicas, Faculdade de Medicina
LIM/13 - Laboratório de Genética e Cardiologia Molecular, Hospital das Clínicas, Faculdade de Medicina - Líder
62 resultados
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conferenceObject PREDICTORS OF CORONARY ARTERY CALCIFICATION INCIDENCE IN SEVERE HYPERCHOLESTEROLEMIA(2023) MARTE, Ana; MINAME, Marcio Hiroshi; PARDI, Estevao Magalhaes; GANEM, Lucas; MIZUTA, Marjorie Hayashida; ROCHA, Viviane Zorzanelli; PEREIRA, Alexandre Costa; KRIEGER, Jose Eduardo; SANTOS, RaulconferenceObject Common Molecular Signature for Human Endothelial Dysfunction Associated With Abnormalities in Blood Flow, Lipids, Inflammation and Hypoxia(2019) SOUSA, Iguaracy P.; SOUZA, Vinicius de; TEIXEIRA, Samantha K.; KRIEGER, Jose E.conferenceObject Influence of genetic polymorphisms of alpha-adrenergic receptors, endothelial nitric oxide synthase and bradykinin receptor B2 on treadmill exercise test responses(2012) NUNES, R. A. Belo; BARROSO, L. P.; SCHMIDT, R. T.; BARRETO, D. D.; FREITAS, H. F.; PEREIRA, A. C.; KRIEGER, J. E.; MANSUR, A. J.Purpose: Treadmill exercise testing responses have been associated with cardiovascular prognosis in individuals without overt heart disease. Neurohumoral and nitric oxide responses may influence cardiovascular performance during exercise. The aim of this study was evaluate associations between genetic polymorphisms of alpha-adrenergic receptors (ADRA1A, ADRA2A and ADRA2B), endothelial nitric oxide synthase (eNOS) and bradykin receptor B2 (BK2R) and treadmill exercise test responses in individuals without overt heart disease. Method: We enrolled 766 (417 women and 349 men) asymptomatic subjects. We selected the following variables during a maximal symptom-limited treadmill exercise test: exercise capacity, chronotropic reserve, maximum heart-rate achieved, heart-rate recovery, exercise systolic blood pressure, exercise diastolic blood pressure and systolic blood pressure recovery. Genotypes for the ADRA1A Arg347Cys (rs1048101), ADRA2A C1780T (rs553668), ADRA2B Del 301-303 (rs28365031), eNOS T786C (rs2070744), eNOS Glu298Asp (rs1799983) and BK2R (rs5810761) polymorphisms were assessed by polymerase chain reaction (PCR) followed by high resolution melting analysis. Laboratory and demographic data were collected for all participants. Statistical analysis was performed with multiple regression models for women and men. Results: The genotype frequencies were under Hardy-Weinberg equilibrium, except for the ADRA2B Del301-303 polymorphism. In the multivariated analysis the ADRA2A C1780T polymorphism was significantly associated with exercise diastolic blood pressure in both sexes. Exercise diastolic blood pressure was higher in individuals with TT genotype than in C allel carriers (P=0.003 for women; P=0.007 for men) (Table 1). The other polymorphisms did not influence significantly the treadmill exercise test responses. Conclusion: The ADRA2A C1780T influenced the exercise diastolic blood pressure in both sexes. This finding suggests that this polymorphism may be a marker of blood pressure response during exercise.conferenceObject Fully Automated Quantification of Cardiac Indices from Cine MRI Using a Combination of Convolution Neural Networks(2020) PEREIRA, Renato F.; REBELO, Marina S.; MORENO, Ramon A.; MARCO, Anderson G.; LIMA, Daniel M.; ARRUDA, Marcelo A. F.; KRIEGER, Jose E.; GUTIERREZ, Marco A.Cardiovascular magnetic resonance imaging (CMRI) is one of the most accurate non-invasive modalities for evaluation of cardiac function, especially the left ventricle (LV). In this modality, the manual or semi-automatic delineation of LV by experts is currently the standard clinical practice for chambers segmentation. Despite these efforts, global quantification of LV remains a challenge. In this work, a combination of two convolutional neural network (CNN) architectures for quantitative evaluation of the LV is described, which estimates the cavity and the myocardium areas, endocardial cavity dimensions in three directions, and the myocardium regional wall thickness in six radial directions. The method was validated in CMRI exams of 56 patients (LVQuan19 dataset) and evaluated by metrics Dice Index, Mean Absolute Error, and Correlation with superior performance compared to the state-of-the-art methods. The combination of the CNN architectures provided a simpler yet fully automated approach, requiring no specialist interaction.- Trypanosoma cruzi cardiomyocyte infection promotes innate immune response and metabolic rewiring(2022) VENTURINI, Gabriela; ALVIM, Juliana; PADILHA, Kallyandra; TOEPFER, Christopher; GORHAM, Joshua; BIAGI, Diogo; SCHENKMAN, Sergio; CARVALHO, Valdemir; SALGUEIRO, Jessica; CARDOZO, Karina; KRIEGER, Jose; PEREIRA, Alexandre; SEIDMAN, Jonathan; SEIDMAN, Christine
- IoT Medical Device Architecture to Estimate Non-invasive Arterial Blood Pressure(2022) MORENO, Ramon; DIAS, Felipe; ARRUDA, Marcelo; OLIVEIRA, Filipe; BULHOES, Thiago; KRIEGER, Jose; GUTIERREZ, MarcoHigh blood pressure (BP) is the leading cause of death worldwide. Besides being a treatable condition, alongside medication and a healthy diet, it requires regular BP measurements to assess whether a patient is properly responding to treatment. There have been many attempts to use the photoplethysmography (PPG) signal to estimate BP continuously, but there has yet to be an effective solution. This work presents our efforts to develop a new method for estimating BP from PPG and infrastructure to collect, process, and store this information. PPG signal is measured from a smartband; our App reads the data from the smartband to a smartphone, processes them using a machine learning method, and estimates BP, which is sent to a server that stores and displays the data
conferenceObject Selection of candidate genes for hypertension on rat chromosome 4 from shr using expression profilling in kidney and subcongenic strain development(2013) TEIXEIRA, Samantha Kuwada; RODRIGUES, Mariliza Velho; MORALES, Marcelo Marcos; KRIEGER, Jose Eduardo- CardioBERTpt: Transformer-based Models for Cardiology Language Representation in Portuguese(2023) SCHNEIDER, Elisa Terumi Rubel; GUMIEL, Yohan Bonescki; SOUZA, Joao Vitor Andrioli de; MUKAI, Lilian Mie; OLIVEIRA, Lucas Emanuel Silva e; REBELO, Marina de Sa; GUTIERREZ, Marco Antonio; KRIEGER, Jose Eduardo; TEODORO, Douglas; MORO, Claudia; PARAISO, Emerson CabreraContextual word embeddings and the Transformers architecture have reached state-of-the-art results in many natural language processing (NLP) tasks and improved the adaptation of models for multiple domains. Despite the improvement in the reuse and construction of models, few resources are still developed for the Portuguese language, especially in the health domain. Furthermore, the clinical models available for the language are not representative enough for all medical specialties. This work explores deep contextual embedding models for the Portuguese language to support clinical NLP tasks. We transferred learned information from electronic health records of a Brazilian tertiary hospital specialized in cardiology diseases and pre-trained multiple clinical BERT-based models. We evaluated the performance of these models in named entity recognition experiments, fine-tuning them in two annotated corpora containing clinical narratives. Our pre-trained models outperformed previous multilingual and Portuguese BERT-based models for cardiology and multi-specialty environments, reaching the state-of-the-art for analyzed corpora, with 5.5% F1 score improvement in TempClinBr (all entities) and 1.7% in SemClinBr (Disorder entity) corpora. Hence, we demonstrate that data representativeness and a high volume of training data can improve the results for clinical tasks, aligned with results for other languages.
- Automated radiographic bone suppression with deep convolutional neural networks(2021) CARDENAS, Diego Armando Cardona; FERREIRA JUNIOR, Jose Raniery; MORENO, Ramon Alfredo; REBELO, Marina de Fatima de Sa; KRIEGER, Jose Eduardo; GUTIERREZ, Marco AntonioDual-energy subtraction (DES) is a technique that separates soft tissue from bones in a chest radiograph (CR). As DES requires specialized equipment, we propose an automatic method based on convolutional neural networks (CNNs) to generate virtual soft tissue images. A dataset comprising 35 pairs of CR and its soft-tissue version split in training (28 image pairs) and testing (7 image pairs) sets were used with data augmentation. We tested two types of images: the lung region's cropped image and the segmented lung image. The ribs suppression was treated as a local problem, so each image was divided into 784 patches. The U-Net architecture was used to perform bone suppression. We tested two types of loss functions: mean squared error (L-mse) and L-sm, which combines L-mse with the structural similarity index measure (SSIM). Due to the patches overlapping, it was necessary to interpolate the gray levels on the reconstructed image from the predicted patches. Evaluations were based on SSIM and root mean square error (RMSE) over the reconstructed lung area. The combination that presented the best results used the loss L-sm and the segmented lung image as input to the U-Net (SSIM of 0.858 and RMSE of 0.033). We observed that the U-Net has poor performance when trained with cropped images containing all information from the chest cavity and how the loss using local information can improve CR rib bone suppression. Our results suggest that it is possible removing the rib bones accurately in CR using CNN and a patch-based approach.y
conferenceObject USE OF STEM CELLS ISOLATED FROM URINE (USCS) AND USC-DERIVED EXOSOMES TO REDUCE ISCHEMIA-REPERFUSION LESIONS DURING KIDNEY TRANSPLANTATION: DEVELOPMENT OF THE IN VITRO PROOF OF CONCEPT(2018) STEICHEN, C.; CRESTANI, T.; NAIMI, A.; BRISHOUAL, S.; GIRAUD, S.; KRIEGER, J.; HAUET, T.