Cláudia Freitas

Hospital de Santo António

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Venceslau Hespanhol

Universidade do Porto

Gabriela Fernandes

Universidade do Porto

Hélder Novais Bastos

Hospital de São João

A. Cunha

University of Trás-os-Montes and Alto Douro

Tânia Pereira

University of Coimbra

Hélder P. Oliveira

Universidade do Porto

José Luís Costa

Thermo Fisher Scientific (United States)

Mariana Serino

Hospital Braga

Francisco Silva

Universidade do Porto

Vanessa Santos

Universidade Cruzeiro do Sul

Cooperative Institutions

Universidade do Porto

Park University

Hospital de São João

i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto

Centro Hospitalar do Porto

INESC TEC

Weatherford College

Universidade de São Paulo

University of Lisbon

Chinese Academy of Sciences

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Physiologic and lung function outcomes of home mechanical ventilation in chronic hypercapnic COPD patients

Cláudia Freitas Mariana Serino David Araújo Tiago Pinto Miguel Gonçalves

Introduction: Evidence that support the efficacy of Home Mechanical Ventilation (HMV) in chronic hypercapnic COPD patients is increasing. However, studies on long term physiologic effects of this therapy are lacking. We aimed to define the long-term impact of HMV on respiratory physiologic parameters and lung function among chronic hypercapnic COPD patients. Methods: Lung function tests and blood gas parameters of COPD patients were analyzed before and at least 6 months after HMV. Results: 108 patients were included, 72,2% were males with a mean age of 69,8±9,1. HMV was started during an exacerbation in 15,3% of patients. Spontaneous timed mode was used with mean IPAP=19,1±3,8cmH2O, EPAP=6,0±1,2cmH2O, RR=15,4±1,7breaths/min and 56,5% had supplementary oxygen therapy. Mean daily use was 92,0% during a mean of 7:36±3:55h, mostly during the night. Mean tidal volume achieved was 638,9±192,4mL. Mean time of HMV use was 49,0±27,2 months. After HMV initiation, paO2 (69,8 vs 61,8 mmHg; p<0,001), paCO2 (45,1 vs 57,0 mmHg; p<0,001) and HCO3- (28,4 vs 33,1 mEq/L; p<0,001) improved. Also, an increase in FEV1%predicted (39,9 vs 35,7; p=0,04) and a decrease in RV%predicted (158 vs 204; p=0,01) was seen. A trend for TLC% (112,0 vs 125,7; p=0,07) improvement was also noticed. No differences in 6-minute walk test were found. Conclusions: HMV is efficient not only in hypercapnia and hypoxia correction but also in hyperinsuflation and expiratory airflow limitation improvement among chronic hypercapnia COPD patients.

Arterial blood

10.1183/13993003.congress-2020.375

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The Role of Liquid Biopsy in Early Diagnosis of Lung Cancer

Frontiers in Oncology (2021)

Cláudia Freitas Catarina Sousa Francisco Machado Mariana Serino Vanessa Santos

Liquid biopsy is an emerging technology with a potential role in the screening and early detection of lung cancer. Several liquid biopsy-derived biomarkers have been identified and are currently under ongoing investigation. In this article, we review the available data on the use of circulating biomarkers for the early detection of lung cancer, focusing on the circulating tumor cells, circulating cell-free DNA, circulating micro-RNAs, tumor-derived exosomes, and tumor-educated platelets, providing an overview of future potential applicability in the clinical practice. While several biomarkers have shown exciting results, diagnostic performance and clinical applicability is still limited. The combination of different biomarkers, as well as their combination with other diagnostic tools show great promise, although further research is still required to define and validate the role of liquid biopsies in clinical practice.

Liquid biopsy

Circulating tumor cell

Clinical Practice

10.3389/fonc.2021.634316

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Citations (71)

Airway stents in malignant central airway obstruction

Pulmonology (2021)

Mariana Serino Cláudia Freitas Sandra Saleiro Bruno Cabrita Miguel Ángel Ruiz Conde

Airway obstruction

10.1016/j.pulmoe.2021.02.003

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Modified Glasgow Prognostic Score – a predictor of survival in malignant pleural effusion

Beatriz Martins Mariana Serino Pedro Magalhães Ferreira Rita A. Trovisco David Barros Coelho

Introduction: Malignant pleural effusions (MPE) are common complications in cancer patients, associated with poor prognosis. Biomarkers of systemic inflammation have been reported as potential prognostic predictors in cancer, and are the basis of some prognostic scores, such as the modified Glasgow Prognostic Score (mGPS). We aimed to assess survival in patients with MPE based on the mGPS. Methods: We retrospectively assessed demographic and clinical data from patients with confirmed MPE. The mGPS was defined as: C-reactive protein (CRP)>10 mg/L and albumin<35 g/L – score 2 (poor prognosis), CRP>10 mg/L and albumin ≥35 g/L - score 1 (intermediate), CRP≤10 mg/L – score 0 (good). Survival was analyzed with Kaplan-Meier curves and compared by log-rank test. Multivariate analysis was performed using Cox regression analysis. Results: We studied 164 patients with MPE (47.8% male, mean age of 66.4±13.6 years) with an ECOG-PS score ≥2 in 35.4% of cases. Specific cancer treatment was given to 104 (63.4%) patients. Concerning mGPS, 21.3% had score 0, 23.8% score 1 and 54.9% score 2. A higher score in mGPS was associated with a worse survival (p<0.001). Overall, the median survival was 3.0 (95% CI 2.04-3.96) months, and when stratified according to mGPS scores was 9.0 (95% CI 3.22-14,77) months in score 0, 4.0 (95% CI 2.65-5.35) months in score 1 and 1.0 (95% CI 0.03-1.98) months in score 2. After adjusting for age, sex and ECOG-PS, independent predictors of survival were systemic treatment (HR 0.37, p<0.001), lung cancer as the primary site (HR 2.68, p<0.001) and mGPS (2 vs 0 HR 2.08 p<.001). Conclusion: In our series, mGPS was an independent prognostic indicator for survival of patients with MPE.

10.1183/13993003.congress-2021.pa3102

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213 IN VITRO DEVELOPMENT OF BOVINE EMBRYOS IN THE PRESENCE OF GROWTH HORMONE, INSULIN-LIKE GROWTH FACTOR-1, AND INSULIN IN OOCYTE MATURATION AND EMBRYO CULTURE MEDIA

Reproduction Fertility and Development (2008)

C. B. Ponchirolli-Schneider Cláudia Freitas Fernanda da Cruz Landim‐Alvarenga

The addition of hormones and growth factors to bovine IVM and IVC media has been reported to affect early embryonic development by enhancing the blastocyst formation rate and quality of embryos produced. The purpose of this study was to investigate the influence of adding growth hormone (GH), insulin-like growth factor-1 (IGF-1), and insulin to IVM and IVC media. Blastocyst production rate and blastocyst quality, as verified by the number of cells with DNA fragmentation, were evaluated. Ovaries from an abattoir were transported to the laboratory and COC were selected and cultured in IVM medium 199 (Earle's salts, Sigma, St. Louis, MO, USA), 10% fetal calf serum (Sigma), 50 µg mL–1 of sodium pyruvate, 1 µg mL–1 of estradiol (Sigma), 50 µg mL–1 of hCG (Profasi hp�, 5000 IU, Serono Inc., Rockland, MA, USA), 5 µg mL–1 of FSH (Folltropin�, Vetrepharm, Ontario, Canada), and 75 µg mL–1 of gentamicin sulfate for 24 h. After IVF (18 h), zygotes were partially denuded and transferred to IVC medium HTF (HTF�, Irvine Scientific, Santa Ana, CA, USA) and BME (BME�, Sigma), in a 1:1 proportion (HTF:BME), 0.6% BSA (Sigma), 0.01% myoinositol (Sigma), and 75 µg mL–1 of gentamicin sulfate, at 38.5�C, in a humidified atmosphere of 5% CO2 in air, supplemented with 10% fetal calf serum at Day 3 of culture. Three different experiments were performed. The first and second experiments were analyzed using the chi-square test (P < 0.05). The third experiment was analyzed with the general linear model of SAS� (SAS Institute Inc., Cary, NC, USA) and the Tukey test (P < 0.1). In the first experiment, oocytes were cultured in IVM medium supplemented with GH (10 ng mL–1), IGF-1 (100 ng mL–1), insulin (1 µg mL–1), or all 3 combined. In the second experiment, IVC medium was supplemented with GH, IGF-1, insulin, or all 3 combined (same concentrations as above). In the third experiment, the quality of the embryos produced in the first 2 experiments was determined by the percentage of cells with DNA fragmentation. After 96 h of culture, embryos were stained with orange acridin (100 µg mL–1) and propidium iodide (100 µg mL–1) and slides were evaluated by fluorescence microscopy (450 to 490 nm). Rates of blastocyst production (blastocysts/oocytes) in the first experiment (29, 28, 28, 26, and 28% for control, GH, IGF-1, insulin, or all 3 combined, respectively) and in the second experiment (35, 35, 36, 35, and 31%) were not statistically different among the groups. In the third experiment, the addition of GH, IGF-1, or insulin to IVM medium did not affect the DNA fragmentation rate (11, 5, 2, 12, and 12%). However, the addition of insulin to IVC medium led to a higher DNA fragmentation rate (24%), when compared with the other groups (11, 10, 6, and 8% for control, GH, IGF-1, and all 3 combined). The addition of GH or IGF-1 to bovine IVM and IVC media did not affect the blastocyst production rate or the quality of embryos produced. The quality of embryos cultured in the presence of insulin was negatively affected.

Sodium pyruvate

Embryo quality

In vitro maturation

10.1071/rdv20n1ab213

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Sharing Biomedical Data: Strengthening AI Development in Healthcare

Healthcare (2021)

Tânia Pereira Joana Morgado Francisco Silva Michele M. Pelter Vasco Dias

Artificial intelligence (AI)-based solutions have revolutionized our world, using extensive datasets and computational resources to create automatic tools for complex tasks that, until now, have been performed by humans. Massive data is a fundamental aspect of the most powerful AI-based algorithms. However, for AI-based healthcare solutions, there are several socioeconomic, technical/infrastructural, and most importantly, legal restrictions, which limit the large collection and access of biomedical data, especially medical imaging. To overcome this important limitation, several alternative solutions have been suggested, including transfer learning approaches, generation of artificial data, adoption of blockchain technology, and creation of an infrastructure composed of anonymous and abstract data. However, none of these strategies is currently able to completely solve this challenge. The need to build large datasets that can be used to develop healthcare solutions deserves special attention from the scientific community, clinicians, all the healthcare players, engineers, ethicists, legislators, and society in general. This paper offers an overview of the data limitation in medical predictive models; its impact on the development of healthcare solutions; benefits and barriers of sharing data; and finally, suggests future directions to overcome data limitations in the medical field and enable AI to enhance healthcare. This perspective is dedicated to the technical requirements of the learning models, and it explains the limitation that comes from poor and small datasets in the medical domain and the technical options that try or can solve the problem related to the lack of massive healthcare data.

Data Sharing

10.3390/healthcare9070827

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Citations (33)

Pre-Training Autoencoder for Lung Nodule Malignancy Assessment Using CT Images

Applied Sciences (2020)

Francisco Silva Tânia Pereira Julieta Frade José Mendes Cláudia Freitas

Lung cancer late diagnosis has a large impact on the mortality rate numbers, leading to a very low five-year survival rate of 5%. This issue emphasises the importance of developing systems to support a diagnostic at earlier stages. Clinicians use Computed Tomography (CT) scans to assess the nodules and the likelihood of malignancy. Automatic solutions can help to make a faster and more accurate diagnosis, which is crucial for the early detection of lung cancer. Convolutional neural networks (CNN) based approaches have shown to provide a reliable feature extraction ability to detect the malignancy risk associated with pulmonary nodules. This type of approach requires a massive amount of data to model training, which usually represents a limitation in the biomedical field due to medical data privacy and security issues. Transfer learning (TL) methods have been widely explored in medical imaging applications, offering a solution to overcome problems related to the lack of training data publicly available. For the clinical annotations experts with a deep understanding of the complex physiological phenomena represented in the data are required, which represents a huge investment. In this direction, this work explored a TL method based on unsupervised learning achieved when training a Convolutional Autoencoder (CAE) using images in the same domain. For this, lung nodules from the Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI) were extracted and used to train a CAE. Then, the encoder part was transferred, and the malignancy risk was assessed in a binary classification—benign and malignant lung nodules, achieving an Area Under the Curve (AUC) value of 0.936. To evaluate the reliability of this TL approach, the same architecture was trained from scratch and achieved an AUC value of 0.928. The results reported in this comparison suggested that the feature learning achieved when reconstructing the input with an encoder-decoder based architecture can be considered an useful knowledge that might allow overcoming labelling constraints.

Autoencoder

Transfer of learning

Binary classification

10.3390/app10217837

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Maternal country of birth and in-hospital exclusive breastfeeding: results from a Portuguese study

European Journal of Public Health (2019)

Catiuscia Lisi Cláudia Freitas Henrique Barros

Abstract Background Breastfeeding provides benefits for children, mothers, society and the environment. The promotion of optimal breastfeeding, from an early stage in life is, therefore, a public health priority. Infant feeding can be influenced by maternal country of birth. However, studies carried out in European settings point to inconsistent findings. This study aims to compare first day in-hospital exclusive breastfeeding among migrant and native women in Portugal. Methods This study is based on a national project on perinatal health among migrants and natives in Portugal (baMBINO). Out of 39 public maternity units in mainland Portugal, 32 were enrolled. Women aged 18 years old or older with a live birth were recruited. The final sample included 5109 participants (2431 natives and 2678 migrants). Logistic regression was used to assess the association between maternal country of birth and in-hospital exclusive breastfeeding. Results Migrant participants included women from Portuguese-speaking African countries (PSAC) (49,7%), Brazil (18%), Eastern Europe (10.2%), other European countries (9.6%), Asia (5.5%) and other countries (7.0%). No differences were found between migrants and natives, with the exception of women from PSAC who were more likely to exclusively breastfeed during the first day of hospital stay (aOR 1.34 CI95% 1.05-1.72), irrespective of maternal age, education, parity, type of pregnancy, reproductive assistance, tobacco use, gestational age, newborn birth weight, mode of delivery and antenatal care. Conclusions In Portugal, women from PSAC are more likely to exclusively breastfeed their babies during the first day of hospital stay when compared to native women. Strategies to maintain healthy breastfeeding practices in this population are fundamental. Key messages Women from PSAC are more likely to breastfeed exclusively in the first day after delivery than Portuguese natives. They should be supported in the maintenance of optimal breastfeeding practices.

Breastfeeding Promotion

10.1093/eurpub/ckz186.068

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Citations (2)

Comprehensive Perspective for Lung Cancer Characterisation Based on AI Solutions Using CT Images

Journal of Clinical Medicine (2020)

Tânia Pereira Cláudia Freitas José Luís Costa Joana Morgado Francisco Silva

Lung cancer is still the leading cause of cancer death in the world. For this reason, novel approaches for early and more accurate diagnosis are needed. Computer-aided decision (CAD) can be an interesting option for a noninvasive tumour characterisation based on thoracic computed tomography (CT) image analysis. Until now, radiomics have been focused on tumour features analysis, and have not considered the information on other lung structures that can have relevant features for tumour genotype classification, especially for epidermal growth factor receptor (EGFR), which is the mutation with the most successful targeted therapies. With this perspective paper, we aim to explore a comprehensive analysis of the need to combine the information from tumours with other lung structures for the next generation of CADs, which could create a high impact on targeted therapies and personalised medicine. The forthcoming artificial intelligence (AI)-based approaches for lung cancer assessment should be able to make a holistic analysis, capturing information from pathological processes involved in cancer development. The powerful and interpretable AI models allow us to identify novel biomarkers of cancer development, contributing to new insights about the pathological processes, and making a more accurate diagnosis to help in the treatment plan selection.

Radiogenomics

Personalized Medicine

10.3390/jcm10010118

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Citations (20)

A CASE OF IMMUNE MEDIATED ENDOCARDITIS

Annals of Allergy Asthma & Immunology (2024)

G. Robertson C. Tillson Cláudia Freitas Eliyahu C. Rosman Gina Coscia

10.1016/j.anai.2024.08.667

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