Machine learning and feature selection methods for egfr mutation status prediction in lung cancer

The evolution of personalized medicine has changed the therapeutic strategy from classical chemotherapy and radiotherapy to a genetic modification targeted therapy, and although biopsy is the traditional method to genetically characterize lung cancer tumor, it is an invasive and painful procedure for the patient. Nodule image features extracted from computed tomography (CT) scans have been used to create machine learning models that predict gene mutation status in a noninvasive, fast, and easy-to-use manner. However, recent studies have shown that radiomic features extracted from an extended region of interest (ROI) beyond the tumor, might be more relevant to predict the mutation status in lung cancer, and consequently may be used to significantly decrease the mortality rate of patients battling this condition. In this work, we investigated the relation between image phenotypes and the mutation status of Epidermal Growth Factor Receptor (EGFR), the most frequently mutated gene in lung cancer with several approved targeted-therapies, using radiomic features extracted from the lung containing the nodule. A variety of linear, nonlinear, and ensemble predictive classification models, along with several feature selection methods, were used to classify the binary outcome of wild-type or mutant EGFR mutation status. The results show that a comprehensive approach using a ROI that included the lung with nodule can capture relevant information and successfully predict the EGFR mutation status with increased performance compared to local nodule analyses. Linear Support Vector Machine, Elastic Net, and Logistic Regression, combined with the Principal Component Analysis feature selection method implemented with 70% of variance in the feature set, were the best-performing classifiers, reaching Area Under the Curve (AUC) values ranging from 0.725 to 0.737. This approach that exploits a holistic analysis indicates that information from more extensive regions of the lung containing the nodule allows a more complete lung cancer characterization and should be considered in future radiogenomic studies.This work is financed by the ERDF—European Regional Development Fund through the Operational Programme for Competitiveness and Internationalisation—COMPETE 2020 Programme and by National Funds through the Portuguese funding agency, FCT—Fundação para a Ciência e a Tecnologia within project POCI-01-0145-FEDER-030263

Comprehensive perspective for lung cancer characterisation based on AI solutions using CT images

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.This work is financed by the ERDF–European Regional Development Fund through the Operational Programme for Competitiveness and Internationalisation–COMPETE 2020 Programme and by National Funds through the Portuguese funding agency, FCT–Fundação para a Ciência e a Tecnologia within project POCI-01-0145-FEDER-030263

Restor(y)ing meaning: reading Manoel de Oliveira’s Non ou a Vã Glória de Mandar

Manoel de Oliveira’s Non ou a Vã Glória de Mandar (1990) is a landmark in Lusophone cinema’s revisitation of the history of Portuguese expansion and colonial conflicts. This article aims at analysing the film’s political import by extrapolating from Jacques Rancière’s meditation on the ‘aesthetic regime’ and from Manoel de Oliveira’s references to Derridean deconstruction. Non and Oliveira’s filming praxis both exceed and disrupt the filmmaker’s personal logocentric and teleological theories of history and cinema

Treatment planning systems dosimetry auditing project in Portugal

BACKGROUND AND PURPOSE: The Medical Physics Division of the Portuguese Physics Society (DFM_SPF) in collaboration with the IAEA, carried out a national auditing project in radiotherapy, between September 2011 and April 2012. The objective of this audit was to ensure the optimal usage of treatment planning systems. The national results are presented in this paper. MATERIAL AND METHODS: The audit methodology simulated all steps of external beam radiotherapy workflow, from image acquisition to treatment planning and dose delivery. A thorax CIRS phantom lend by IAEA was used in 8 planning test-cases for photon beams corresponding to 15 measuring points (33 point dose results, including individual fields in multi-field test cases and 5 sum results) in different phantom materials covering a set of typical clinical delivery techniques in 3D Conformal Radiotherapy. RESULTS: All 24 radiotherapy centers in Portugal have participated. 50 photon beams with energies 4-18 MV have been audited using 25 linear accelerators and 32 calculation algorithms. In general a very good consistency was observed for the same type of algorithm in all centres and for each beam quality. CONCLUSIONS: The overall results confirmed that the national status of TPS calculations and dose delivery for 3D conformal radiotherapy is generally acceptable with no major causes for concern. This project contributed to the strengthening of the cooperation between the centres and professionals, paving the way to further national collaborations

The Ethnomedicine of the Haya people of Bugabo ward, Kagera Region, north western Tanzania

\ud The Kagera region, in north western Tanzania, is endowed with a strong culture of traditional medicine that is well supported by a rich diversity of medicinal plants. However, most of the plants in this region have not been documented nor evaluated for safety and efficacy. As an initiative in that direction, this study documented the knowledge on medicinal plant use by traditional healers of Bugabo Ward in Bukoba District. Key informants were selected with the help of local government officials and information on their knowledge and use of plants for therapeutic purposes was gathered using a semi-structured interview format. In this study 94 plant species representing 84 genera and 43 families were found to be commonly used in the treatment of a variety of human ailments. The family Asteraceae had the highest number of species being used as traditional medicines. The study revealed that Malaria is treated using the highest number of different medicinal species (30), followed by skin conditions (19), maternal illnesses and sexually transmitted diseases (14), respiratory diseases (11) and yellow fever, Herpes simplex and peptic ulcers (10). Majority of the species are used to treat less than five different diseases/conditions each and leaves were the most commonly used part, comprising 40% of all the reports on use of plant parts. Trees comprised the most dominant growth form among all plants used for medicinal purposes in the study area. Bugabo Ward has a rich repository of medicinal plants and this reinforces the need for an extensive and comprehensive documentation of medicinal plants in the area and a concomitant evaluation of their biological activity as a basis for developing future medicines.\u

Inhibition of IL-10 Production by Maternal Antibodies against Group B Streptococcus GAPDH Confers Immunity to Offspring by Favoring Neutrophil Recruitment

Group B Streptococcus (GBS) is the leading cause of neonatal pneumonia, septicemia, and meningitis. We have previously shown that in adult mice GBS glycolytic enzyme glyceraldehyde-3-phosphate dehydrogenase (GAPDH) is an extracellular virulence factor that induces production of the immunosuppressive cytokine interleukin-10 (IL-10) by the host early upon bacterial infection. Here, we investigate whether immunity to neonatal GBS infection could be achieved through maternal vaccination against bacterial GAPDH. Female BALB/c mice were immunized with rGAPDH and the progeny was infected with a lethal inoculum of GBS strains. Neonatal mice born from mothers immunized with rGAPDH were protected against infection with GBS strains, including the ST-17 highly virulent clone. A similar protective effect was observed in newborns passively immunized with anti-rGAPDH IgG antibodies, or F(ab')2 fragments, indicating that protection achieved with rGAPDH vaccination is independent of opsonophagocytic killing of bacteria. Protection against lethal GBS infection through rGAPDH maternal vaccination was due to neutralization of IL-10 production soon after infection. Consequently, IL-10 deficient (IL-10−/−) mice pups were as resistant to GBS infection as pups born from vaccinated mothers. We observed that protection was correlated with increased neutrophil trafficking to infected organs. Thus, anti-rGAPDH or anti-IL-10R treatment of mice pups before GBS infection resulted in increased neutrophil numbers and lower bacterial load in infected organs, as compared to newborn mice treated with the respective control antibodies. We showed that mothers immunized with rGAPDH produce neutralizing antibodies that are sufficient to decrease IL-10 production and induce neutrophil recruitment into infected tissues in newborn mice. These results uncover a novel mechanism for GBS virulence in a neonatal host that could be neutralized by vaccination or immunotherapy. As GBS GAPDH is a structurally conserved enzyme that is metabolically essential for bacterial growth in media containing glucose as the sole carbon source (i.e., the blood), this protein constitutes a powerful candidate for the development of a human vaccine against this pathogen

Antimalarial Activity and Mechanisms of Action of Two Novel 4-Aminoquinolines against Chloroquine-Resistant Parasites

Chloroquine (CQ) is a cost effective antimalarial drug with a relatively good safety profile (or therapeutic index). However, CQ is no longer used alone to treat patients with Plasmodium falciparum due to the emergence and spread of CQ-resistant strains, also reported for P. vivax. Despite CQ resistance, novel drug candidates based on the structure of CQ continue to be considered, as in the present work. One CQ analog was synthesized as monoquinoline (MAQ) and compared with a previously synthesized bisquinoline (BAQ), both tested against P. falciparum in vitro and against P. berghei in mice, then evaluated in vitro for their cytotoxicity and ability to inhibit hemozoin formation. Their interactions with residues present in the NADH binding site of P falciparum lactate dehydrogenase were evaluated using docking analysis software. Both compounds were active in the nanomolar range evaluated through the HRPII and hypoxanthine tests. MAQ and BAQ derivatives were not toxic, and both compounds significantly inhibited hemozoin formation, in a dose-dependent manner. MAQ had a higher selectivity index than BAQ and both compounds were weak PfLDH inhibitors, a result previously reported also for CQ. Taken together, the two CQ analogues represent promising molecules which seem to act in a crucial point for the parasite, inhibiting hemozoin formation