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1. Binding energies of ethanol and ethylamine on interstellar water ices: synergy between theory and experiments

Author

Perrero, Jessica, Vitorino, Julie, Congiu, Emanuele, Ugliengo, Piero, Rimola, Albert, and Dulieu, François

Subjects
Physics - Chemical Physics, Astrophysics - Astrophysics of Galaxies
Abstract

Experimental and computational chemistry are two disciplines to conduct research in Astrochemistry, providing essential reference data for both astronomical observations and modeling. These approaches not only mutually support each other, but also serve as complementary tools to overcome their respective limitations. We characterized the binding energies (BEs) of ethanol (CH$_3$CH$_2$OH) and ethylamine (CH$_3$CH$_2$NH$_2$), two interstellar complex organic molecules (iCOMs), onto crystalline and amorphous water ices through density functional theory (DFT) calculations and temperature programmed desorption (TPD) experiments. Experimentally, CH$_3$CH$_2$OH and CH$_3$CH$_2$NH$_2$ behave similarly, in which desorption temperatures are higher on the water ices than on a bare gold surface. Computed cohesive energies of pure ethanol and ethylamine bulk structures allow describing the BEs of the pure species deposited on the gold surface, as extracted from the TPD curve analyses. The BEs of submonolayer coverages of CH$_3$CH$_2$OH and CH$_3$CH$_2$NH$_2$ on the water ices cannot be directly extracted from TPD due to their co-desorption with water, but they are computed through DFT calculations, and found to be greater than the cohesive energy of water. The behaviour of CH$_3$CH$_2$OH and CH$_3$CH$_2$NH$_2$ is different when depositing adsorbate multilayers on the amorphous ice, in that, according to their computed cohesive energies, ethylamine layers present weaker interactions compared to ethanol and water. Finally, from the computed BEs of ethanol, ethylamine and water, we can infer that the snow-lines of these three species in protoplanetary disks will be situated at different distances from the central star. It appears that a fraction of ethanol and ethylamine is already frozen on the grains in the water snow-lines, causing their incorporation in water-rich planetesimals., Comment: 18 pages, 7 figures, accepted for publication in PCCP

Published
2024
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2. Adversarial Evasion Attack Efficiency against Large Language Models

Author

Vitorino, João, Maia, Eva, and Praça, Isabel

Subjects
Computer Science - Computation and Language, Computer Science - Machine Learning
Abstract

Large Language Models (LLMs) are valuable for text classification, but their vulnerabilities must not be disregarded. They lack robustness against adversarial examples, so it is pertinent to understand the impacts of different types of perturbations, and assess if those attacks could be replicated by common users with a small amount of perturbations and a small number of queries to a deployed LLM. This work presents an analysis of the effectiveness, efficiency, and practicality of three different types of adversarial attacks against five different LLMs in a sentiment classification task. The obtained results demonstrated the very distinct impacts of the word-level and character-level attacks. The word attacks were more effective, but the character and more constrained attacks were more practical and required a reduced number of perturbations and queries. These differences need to be considered during the development of adversarial defense strategies to train more robust LLMs for intelligent text classification applications., Comment: 9 pages, 1 table, 2 figures, DCAI 2024 conference

Published
2024

3. Efficient Network Traffic Feature Sets for IoT Intrusion Detection

Author

Silva, Miguel, Vitorino, João, Maia, Eva, and Praça, Isabel

Subjects
Computer Science - Cryptography and Security, Computer Science - Machine Learning, Computer Science - Networking and Internet Architecture
Abstract

The use of Machine Learning (ML) models in cybersecurity solutions requires high-quality data that is stripped of redundant, missing, and noisy information. By selecting the most relevant features, data integrity and model efficiency can be significantly improved. This work evaluates the feature sets provided by a combination of different feature selection methods, namely Information Gain, Chi-Squared Test, Recursive Feature Elimination, Mean Absolute Deviation, and Dispersion Ratio, in multiple IoT network datasets. The influence of the smaller feature sets on both the classification performance and the training time of ML models is compared, with the aim of increasing the computational efficiency of IoT intrusion detection. Overall, the most impactful features of each dataset were identified, and the ML models obtained higher computational efficiency while preserving a good generalization, showing little to no difference between the sets., Comment: 10 pages, 9 tables, DCAI 2024 conference

Published
2024

4. Reliable Feature Selection for Adversarially Robust Cyber-Attack Detection

Author

Vitorino, João, Silva, Miguel, Maia, Eva, and Praça, Isabel

Subjects
Computer Science - Cryptography and Security, Computer Science - Machine Learning, Computer Science - Networking and Internet Architecture
Abstract

The growing cybersecurity threats make it essential to use high-quality data to train Machine Learning (ML) models for network traffic analysis, without noisy or missing data. By selecting the most relevant features for cyber-attack detection, it is possible to improve both the robustness and computational efficiency of the models used in a cybersecurity system. This work presents a feature selection and consensus process that combines multiple methods and applies them to several network datasets. Two different feature sets were selected and were used to train multiple ML models with regular and adversarial training. Finally, an adversarial evasion robustness benchmark was performed to analyze the reliability of the different feature sets and their impact on the susceptibility of the models to adversarial examples. By using an improved dataset with more data diversity, selecting the best time-related features and a more specific feature set, and performing adversarial training, the ML models were able to achieve a better adversarially robust generalization. The robustness of the models was significantly improved without their generalization to regular traffic flows being affected, without increases of false alarms, and without requiring too many computational resources, which enables a reliable detection of suspicious activity and perturbed traffic flows in enterprise computer networks., Comment: 24 pages, 17 tables, Annals of Telecommunications journal. arXiv admin note: substantial text overlap with arXiv:2402.16912

Published
2024
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5. An Adversarial Robustness Benchmark for Enterprise Network Intrusion Detection

Author

Vitorino, João, Silva, Miguel, Maia, Eva, and Praça, Isabel

Subjects
Computer Science - Cryptography and Security, Computer Science - Machine Learning, Computer Science - Networking and Internet Architecture
Abstract

As cyber-attacks become more sophisticated, improving the robustness of Machine Learning (ML) models must be a priority for enterprises of all sizes. To reliably compare the robustness of different ML models for cyber-attack detection in enterprise computer networks, they must be evaluated in standardized conditions. This work presents a methodical adversarial robustness benchmark of multiple decision tree ensembles with constrained adversarial examples generated from standard datasets. The robustness of regularly and adversarially trained RF, XGB, LGBM, and EBM models was evaluated on the original CICIDS2017 dataset, a corrected version of it designated as NewCICIDS, and the HIKARI dataset, which contains more recent network traffic. NewCICIDS led to models with a better performance, especially XGB and EBM, but RF and LGBM were less robust against the more recent cyber-attacks of HIKARI. Overall, the robustness of the models to adversarial cyber-attack examples was improved without their generalization to regular traffic being affected, enabling a reliable detection of suspicious activity without costly increases of false alarms., Comment: 15 pages, 8 tables, 2 figures, FPS 2023 conference

Published
2024

13. An efficient topology optimization algorithm for large-scale three-dimensional structures

Author

Vitorino, Alfredo and Gomes, Francisco A. M.

Subjects
Mathematics - Optimization and Control, 74B05, 90C30, 65K05, 65F10
Abstract

Designing the topology of three-dimensional structures is a challenging problem due to its memory and time consumption. In this paper, we present a robust and efficient algorithm for solving large-scale 3D topology optimization problems. The robustness of the algorithm is ensured by adopting a globally convergent sequential linear programming method with a stopping criterion based on the first-order optimality conditions of the nonlinear problem. To increase the algorithm's efficiency, it is combined with a multiresolution scheme that employs different discretizations to deal with displacement, design, and density variables. In addition, the time spent solving the linear equilibrium systems is substantially reduced using multigrid as a preconditioner for the conjugate gradient method. Since multiresolution can lead to the appearance of unwanted artefacts in the structure, we propose an adaptive strategy for increasing the degree of the displacement elements, with a technique for suppressing unnecessary variables that provides accurate solutions with a moderate impact on the algorithm's performance. We also propose a new thresholding strategy, based on gradient information, to obtain structures composed only by solid or void regions. Computational experiments carried out in Matlab prove that the new algorithm effectively generates high-resolution structures at a low computational cost.

Published
2023

17. SoK: Realistic Adversarial Attacks and Defenses for Intelligent Network Intrusion Detection

Author

Vitorino, João, Praça, Isabel, and Maia, Eva

Subjects
Computer Science - Cryptography and Security, Computer Science - Machine Learning, Computer Science - Networking and Internet Architecture
Abstract

Machine Learning (ML) can be incredibly valuable to automate anomaly detection and cyber-attack classification, improving the way that Network Intrusion Detection (NID) is performed. However, despite the benefits of ML models, they are highly susceptible to adversarial cyber-attack examples specifically crafted to exploit them. A wide range of adversarial attacks have been created and researchers have worked on various defense strategies to safeguard ML models, but most were not intended for the specific constraints of a communication network and its communication protocols, so they may lead to unrealistic examples in the NID domain. This Systematization of Knowledge (SoK) consolidates and summarizes the state-of-the-art adversarial learning approaches that can generate realistic examples and could be used in real ML development and deployment scenarios with real network traffic flows. This SoK also describes the open challenges regarding the use of adversarial ML in the NID domain, defines the fundamental properties that are required for an adversarial example to be realistic, and provides guidelines for researchers to ensure that their future experiments are adequate for a real communication network., Comment: 31 pages, 3 tables, 6 figures, Computers and Security journal

Published
2023
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20. KAT6A mutations in Arboleda-Tham syndrome drive epigenetic regulation of posterior HOXC cluster.

Author

Spendlove, Sarah, Wei, Angela, Bondhus, Leroy, Nava, Aileen, de L Vitorino, Francisca, Amano, Seth, Lee, Jacob, Echeverria, Gesenia, Gomez, Dianne, Garcia, Benjamin, Arboleda, Valerie, and Singh, Meghna

Subjects
Humans, Histones, Epigenesis, Genetic, Proteomics, Chromatin, Mutation, Transcription Factors, Homeodomain Proteins, Histone Acetyltransferases
Abstract

Arboleda-Tham Syndrome (ARTHS) is a rare genetic disorder caused by heterozygous, de novo mutations in Lysine(K) acetyltransferase 6A (KAT6A). ARTHS is clinically heterogeneous and characterized by several common features, including intellectual disability, developmental and speech delay, and hypotonia, and affects multiple organ systems. KAT6A is the enzymatic core of a histone-acetylation protein complex; however, the direct histone targets and gene regulatory effects remain unknown. In this study, we use ARTHS patient (n = 8) and control (n = 14) dermal fibroblasts and perform comprehensive profiling of the epigenome and transcriptome caused by KAT6A mutations. We identified differential chromatin accessibility within the promoter or gene body of 23% (14/60) of genes that were differentially expressed between ARTHS and controls. Within fibroblasts, we show a distinct set of genes from the posterior HOXC gene cluster (HOXC10, HOXC11, HOXC-AS3, HOXC-AS2, and HOTAIR) that are overexpressed in ARTHS and are transcription factors critical for early development body segment patterning. The genomic loci harboring HOXC genes are epigenetically regulated with increased chromatin accessibility, high levels of H3K23ac, and increased gene-body DNA methylation compared to controls, all of which are consistent with transcriptomic overexpression. Finally, we used unbiased proteomic mass spectrometry and identified two new histone post-translational modifications (PTMs) that are disrupted in ARTHS: H2A and H3K56 acetylation. Our multi-omics assays have identified novel histone and gene regulatory roles of KAT6A in a large group of ARTHS patients harboring diverse pathogenic mutations. This work provides insight into the role of KAT6A on the epigenomic regulation in somatic cell types.

Published
2023

21. Low microbial diversity, yeast prevalence, and nematode-trapping fungal presence in fungal colonization and leaf microbiome of Serjania erecta

Author

Samylla Tássia Ferreira de Freitas, Fabiano Guimarães Silva, Layara Alexandre Bessa, Ueric José Borges de Souza, Damiana Souza Santos Augusto, Giselle Santos de Faria, and Luciana Cristina Vitorino

Subjects
Cerrado plant microbiome, Endophytic fungi, Epiphytic fungi, Nematode-trapping fungi, Metagenomic study, Medicine, Science
Abstract

Abstract Medicinal plant microbiomes undergo selection due to secondary metabolite presence. Resident endophytic/epiphytic microorganisms directly influence plant’s bioactive compound synthesis. Hypothesizing low microbial diversity in Serjania erecta leaves, we assessed leaf colonization by epiphytic and endophytic fungi. Given its traditional medicinal importance, we estimated diversity in the endophytic fungal microbiome. Analyses included scanning electron microscopy (SEM), isolation of cultivable species, and metagenomics. Epiphytic fungi interacted with S. erecta leaf tissues, horizontally transmitted via stomata/trichome bases, expressing traits for nematode trapping. Cultivable endophytic fungi, known for phytopathogenic habits, didn’t induce dysbiosis symptoms. This study confirms low leaf microbiome diversity in S. erecta, with a tendency towards more fungal species, likely due to antibacterial secondary metabolite selection. The classification of Halicephalobus sp. sequence corroborated the presence of nematode eggs on the epidermal surface of S. erecta by SEM. In addition, we confirmed the presence of methanogenic archaea and a considerable number of methanotrophs of the genus Methylobacterium. The metagenomic study of endophytic fungi highlighted plant growth-promoting yeasts, mainly Malassezia, Leucosporidium, Meyerozyma, and Hannaella. Studying endophytic fungi and S. erecta microbiomes can elucidate their impact on beneficial bioactive compound production, on the other hand, it is possible that the bioactive compounds produced by this plant can recruit specific microorganisms, impacting the biological system.

Published
2024
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22. From Data to Action: Exploring AI and IoT-driven Solutions for Smarter Cities

Author

Dias, Tiago, Fonseca, Tiago, Vitorino, João, Martins, Andreia, Malpique, Sofia, and Praça, Isabel

Subjects
Computer Science - Machine Learning, Computer Science - Computer Vision and Pattern Recognition, Electrical Engineering and Systems Science - Systems and Control
Abstract

The emergence of smart cities demands harnessing advanced technologies like the Internet of Things (IoT) and Artificial Intelligence (AI) and promises to unlock cities' potential to become more sustainable, efficient, and ultimately livable for their inhabitants. This work introduces an intelligent city management system that provides a data-driven approach to three use cases: (i) analyze traffic information to reduce the risk of traffic collisions and improve driver and pedestrian safety, (ii) identify when and where energy consumption can be reduced to improve cost savings, and (iii) detect maintenance issues like potholes in the city's roads and sidewalks, as well as the beginning of hazards like floods and fires. A case study in Aveiro City demonstrates the system's effectiveness in generating actionable insights that enhance security, energy efficiency, and sustainability, while highlighting the potential of AI and IoT-driven solutions for smart city development., Comment: 10 pages, 8 Figures, accepted for DCAI2023

Published
2023
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23. The cervical microbiota of Hispanics living in Puerto Rico is nonoptimal regardless of HPV status.

Author

Vargas-Robles, Daniela, Romaguera, Josefina, Alvarado-Velez, Ian, Tosado-Rodríguez, Eduardo, Dominicci-Maura, Anelisse, Sanchez, Maria, Wiggin, Kara, Martinez-Ferrer, Magaly, Forney, Larry, Godoy-Vitorino, Filipa, and Gilbert, Jack

Subjects
16S rRNA genes, cervical lesions, cervicovaginal microbiota, human papilloma viruses (HPV), Female, Humans, Pregnancy, Bacteria, Hispanic or Latino, Microbiota, Papillomavirus Infections, Puerto Rico, RNA, Ribosomal, 16S, Cervix Uteri
Abstract

The cervicovaginal microbiota is influenced by host physiology, immunology, lifestyle, and ethnicity. We hypothesized that there would be differences in the cervicovaginal microbiota among pregnant, nonpregnant, and menopausal women living in Puerto Rico (PR) with and without human papillomavirus (HPV) infection and cervical cancer. We specifically wanted to determine if the microbiota is associated with variations in cervical cytology. A total of 294 women, including reproductive-age nonpregnant (N = 196), pregnant (N = 37), and menopausal (N = 61) women, were enrolled. The cervicovaginal bacteria were characterized by 16S rRNA amplicon sequencing, the HPV was genotyped with SPF10-LiPA, and cervical cytology was quantified. High-risk HPV (HR-HPV, 67.3%) was prevalent, including genotypes not covered by the 9vt HPV vaccine. Cervical lesions (34%) were also common. The cervical microbiota was dominated by Lactobacillus iners. Pregnant women in the second and third trimesters exhibited a decrease in diversity and abundance of microbes associated with bacterial vaginosis. Women in menopause had greater alpha diversity, a greater proportion of facultative and strictly anaerobic bacteria, and higher cervicovaginal pH than premenopausal women. Cervical lesions were associated with greater alpha diversity. However, no significant associations between the microbiota and HPV infection (HR or LR-HPV types) were found. The cervicovaginal microbiota of women living in Puerto Rican were either dominated by L. iners or diverse microbial communities regardless of a womans physiological stage. We postulate that the microbiota and the high prevalence of HR-HPV increase the risk of cervical lesions among women living in PR. IMPORTANCE In the enclosed manuscript, we provide the first in-depth characterization of the cervicovaginal microbiota of Hispanic women living in Puerto Rico (PR), using a 16S rRNA approach, and include women of different physiological stages. Surprisingly we found that high-risk HPV was ubiquitous with a prevalence of 67.3%, including types not covered by the 9vt HPV vaccine. We also found highly diverse microbial communities across women groups-with a reduction in pregnant women, but dominated by nonoptimal Lactobacillus iners. Additionally, we found vaginosis-associated bacteria as Dialister spp., Gardnerella spp., Clostridium, or Prevotella among most women. We believe this is a relevant and timely article expanding knowledge on the cervicovaginal microbiome of PR women, where we postulate that these highly diverse communities are conducive to cervical disease.

Published
2023

35. Adversarial Robustness and Feature Impact Analysis for Driver Drowsiness Detection

Author

Vitorino, João, Rodrigues, Lourenço, Maia, Eva, Praça, Isabel, and Lourenço, André

Subjects
Computer Science - Machine Learning, Electrical Engineering and Systems Science - Systems and Control
Abstract

Drowsy driving is a major cause of road accidents, but drivers are dismissive of the impact that fatigue can have on their reaction times. To detect drowsiness before any impairment occurs, a promising strategy is using Machine Learning (ML) to monitor Heart Rate Variability (HRV) signals. This work presents multiple experiments with different HRV time windows and ML models, a feature impact analysis using Shapley Additive Explanations (SHAP), and an adversarial robustness analysis to assess their reliability when processing faulty input data and perturbed HRV signals. The most reliable model was Extreme Gradient Boosting (XGB) and the optimal time window had between 120 and 150 seconds. Furthermore, SHAP enabled the selection of the 18 most impactful features and the training of new smaller models that achieved a performance as good as the initial ones. Despite the susceptibility of all models to adversarial attacks, adversarial training enabled them to preserve significantly higher results, especially XGB. Therefore, ML models can significantly benefit from realistic adversarial training to provide a more robust driver drowsiness detection., Comment: 10 pages, 2 tables, 3 figures, AIME 2023 conference

Published
2023
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36. Constrained Adversarial Learning and its applicability to Automated Software Testing: a systematic review

Author

Vitorino, João, Dias, Tiago, Fonseca, Tiago, Maia, Eva, and Praça, Isabel

Subjects
Computer Science - Software Engineering, Computer Science - Machine Learning
Abstract

Every novel technology adds hidden vulnerabilities ready to be exploited by a growing number of cyber-attacks. Automated software testing can be a promising solution to quickly analyze thousands of lines of code by generating and slightly modifying function-specific testing data to encounter a multitude of vulnerabilities and attack vectors. This process draws similarities to the constrained adversarial examples generated by adversarial learning methods, so there could be significant benefits to the integration of these methods in automated testing tools. Therefore, this systematic review is focused on the current state-of-the-art of constrained data generation methods applied for adversarial learning and software testing, aiming to guide researchers and developers to enhance testing tools with adversarial learning methods and improve the resilience and robustness of their digital systems. The found constrained data generation applications for adversarial machine learning were systematized, and the advantages and limitations of approaches specific for software testing were thoroughly analyzed, identifying research gaps and opportunities to improve testing tools with adversarial attack methods., Comment: 32 pages, 5 tables, 2 figures, Information and Software Technology journal

Published
2023

37. Towards Adversarial Realism and Robust Learning for IoT Intrusion Detection and Classification

Author

Vitorino, João, Praça, Isabel, and Maia, Eva

Subjects
Computer Science - Cryptography and Security, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

The Internet of Things (IoT) faces tremendous security challenges. Machine learning models can be used to tackle the growing number of cyber-attack variations targeting IoT systems, but the increasing threat posed by adversarial attacks restates the need for reliable defense strategies. This work describes the types of constraints required for a realistic adversarial cyber-attack example and proposes a methodology for a trustworthy adversarial robustness analysis with a realistic adversarial evasion attack vector. The proposed methodology was used to evaluate three supervised algorithms, Random Forest (RF), Extreme Gradient Boosting (XGB), and Light Gradient Boosting Machine (LGBM), and one unsupervised algorithm, Isolation Forest (IFOR). Constrained adversarial examples were generated with the Adaptative Perturbation Pattern Method (A2PM), and evasion attacks were performed against models created with regular and adversarial training. Even though RF was the least affected in binary classification, XGB consistently achieved the highest accuracy in multi-class classification. The obtained results evidence the inherent susceptibility of tree-based algorithms and ensembles to adversarial evasion attacks and demonstrates the benefits of adversarial training and a security by design approach for a more robust IoT network intrusion detection and cyber-attack classification., Comment: 19 pages, 5 tables, 7 figures, Annals of Telecommunications journal

Published
2023
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39. Hipertensión intracraneal idiopática y COVID 19

Author

Vitorino Modesto dos Santos

Subjects
n/a, Medicine
Abstract

La patogénesis de la hipertensión intracraneal idiopática (HII) involucra factores hormonales, inmunes, metabólicos y vasculares1-4. Esta entidad poco común afecta frecuentemente a mujeres jóvenes con exceso de peso, y provoca dolor de cabeza, cambios visuales y de estabilidad o cognitivos, ansiedad y depresión; y puede seguir a la infección por COVID-19 o a las vacunas1-4. Además de la IIH, el virus SARS-CoV-2 se asocia con accidente cerebrovascular, deterioro de la conciencia, papiloflebitis, neuritis óptica y otras neuropatías craneales diversas1-4. También son dignas de mención las complicaciones neurooftálmicas tras las vacunas COVID-19, como ejemplos de trombosis cerebral arterial o venosa, hemorragia intracerebral, neuropatía óptica isquémica anterior bilateral y neuropatía craneal posvacunación2. Las herramientas obligatorias son el examen neurológico preciso, la resonancia magnética del cerebro, la evaluación de la presión del líquido cefalorraquídeo y las determinaciones de laboratorio. Recientemente leí el estudio de caso publicado en esta Revista por Therán León JS, et al. sobre una mujer de 26 años con infección por SARS-CoV-2 y HII, que presentó cefalea, discapacidad visual y papiledema, los cuales fueron manejados exitosamente4. La resonancia magnética (RM) de cráneo fue normal y la punción lumbar reveló líquido cefalorraquídeo normal, pero la presión era alta (40 cm H2O); sus síntomas se aliviaron con punción lumbar y 500 mg de acetazolamida 2 veces al día4. Los autores comentaron sobre el bloqueo de los vasos linfáticos por parte del SARS-CoV-2, que aumenta la resistencia a la salida del LCR y provoca HII, y las células endoteliales capilares que expresan el receptor ACE2 del virus, lo que podría favorecer su naturaleza neuroinvasiva4. En este sentido, parece útil añadir algunos comentarios sobre otros artículos muy recientes1-3. Carazo-Barrios L, et al. evaluó la evolución del dolor de cabeza, la ansiedad y la depresión entre 112 pacientes con HII durante la pandemia de COVID-19 (92% mujeres) con una edad promedio de 36,6 ± 9,2 años, un tiempo medio desde el diagnóstico de 6,25 ± 5,66 años, y detectó un empeoramiento significativo de la ansiedad y la depresión debido al encierro1. En cuanto al tratamiento de la HII, se observó un incremento de una escala de no tratamiento a medicación oral o a procedimiento quirúrgico en el 12,5% de los casos durante el confinamiento; y los autores sugirieron estudios sobre el impacto a mediano y largo plazo en los casos de HII1. Feizi M, et al. revisaron los trastornos neurooftálmicos relacionados con la infección y la vacunación por COVID-19, que pueden ocurrir hasta en un 30% de los casos, principalmente con infección grave2. Los cambios incluyeron encefalomielitis aguda diseminada, ageusia, anosmia, alteración de la conciencia, trombosis venosa cerebral, enfermedad asociada a la glicoproteína de oligodendrocitos de mielina, neuromielitis óptica, encefalopatía posterior reversible, además de los accidentes cerebrovasculares2. El mecanismo implica tormenta de citoquinas, génesis retardada de autoanticuerpos, invasión directa, disfunción endotelial, hipercoagulación, hipoxia y menor tolerancia inmune2. Thakur S, et al. reportaron una mujer de 49 años que recibió una dosis única de la vacuna aproximadamente cuatro meses antes, y presentó hipertensión intracraneal que le provocó visión borrosa; y debido a la positividad de su prueba rápida de antígeno SARS-CoV-2, fue ingresada en la sala de aislamiento y luego se sometió a una cirugía óptica endoscópica3. Como los dolores de cabeza persistentes en COVID 19 pueden presagiar una HII, que es una complicación inusual, los autores destacaron el papel de un diagnóstico precoz y un tratamiento oportuno de estos casos desde la atención primaria, con el objetivo de evitar una evolución de daño visual irreversible3. El autor cree firmemente que los comentarios aquí incluidos podrían aumentar el interés y la conciencia de los lectores sobre la hipótesis de un trastorno del sistema nervioso central relacionado con la infección o la vacunación por COVID-19, favoreciendo el diagnóstico precoz.

Published
2024
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40. The extent of postpartum cardiac reverse remodeling is reflected in urine proteome

Author

Ana F. Ferreira, Fábio Trindade, Maria J. Azevedo, Juliana Morais, Thibaut Douché, Sílvia O. Diaz, Francisca A. Saraiva, Carla Sousa, Ana P. Machado, Mariette Matondo, Adelino Leite-Moreira, Carla Ramalho, Rui Vitorino, Inês Falcão-Pires, and António S. Barros

Subjects
Pregnancy, Cardiovascular reverse remodeling, Cardiovascular risk factor, Hemodynamic overload, Urine, Proteome, Medicine, Science
Abstract

Abstract The association of postpartum cardiac reverse remodeling (RR) with urinary proteome, particularly in pregnant women with cardiovascular (CV) risk factors who show long-term increased risk of cardiovascular disease and mortality is unknown. We aim to profile the urinary proteome in pregnant women with/without CV risk factors to identify proteins associated with postpartum RR. Our study included a prospective cohort of 32 healthy and 27 obese and/or hypertensive and/or diabetic pregnant women who underwent transthoracic echocardiography, pulse-wave-velocity, and urine collection at the 3rd trimester and 6 months postpartum. Shotgun HPLC–MS/MS profiled proteins. Generalized linear mixed-effects models were used to identify associations between urinary proteins and left ventricle mass (LVM), a surrogate of RR. An increase in arterial stiffness was documented from 3rd trimester to 6 months after delivery, being significantly elevated in women with CV risk factors. In addition, the presence of at least one CV risk factor was associated with worse LVM RR. We identified 6 and 11 proteins associated with high and low LVM regression, respectively. These proteins were functionally linked with insulin-like growth factor (IGF) transport and uptake regulation by IGF binding-proteins, platelet activation, signaling and aggregation and the immune system’s activity. The concentration of IGF-1 in urine samples was associated with low LVM regression after delivery. Urinary proteome showed a predicting potential for identifying pregnant women with incomplete postpartum RR.

Published
2024
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41. Wildlife conservation through traditional values: alarming numbers of crocodile attacks reported from Timor-Leste

Author

Sebastian Brackhane, Yusuke Fukuda, Flaminio M.E. Xavier, Vitorino de Araujo, Marcal Gusmao, Josh Trindade, Demétrio do Amaral de Carvalho, Rui Dos Reis Pires, and Grahame Webb

Subjects
Crocodylus porosus, Global South, human–wildlife conflict, saltwater crocodile, Timor-Leste, traditional beliefs, General. Including nature conservation, geographical distribution, QH1-199.5
Abstract

On the IUCN Red List the saltwater crocodile Crocodylus porosus is categorized globally as Least Concern, with national populations ranging from fully recovered to extinct. The saltwater crocodile population of the Southeast Asian island nation of Timor-Leste was severely depleted by colonial hunting but has recovered since independence in 2002. During 2007–2014 there was a 23-fold increase in reported crocodile attacks (104 documented attacks), concomitant with a 2% annual increase in the human population. Public tolerance to attacks and the reluctance to harm crocodiles are entwined with reverence of crocodiles as sacred beings by most but not all Timorese people. In 2022, 7–8 years after our previous assessment, we visited five sites on the south coast of Timor-Leste in Lautém, Viqueque, Manufahí and Cova Lima municipalities. High rates of crocodile attacks continue. We obtained 35 records of attacks for 2015–2022 (34% fatal). In the municipalities where crocodile attacks occurred (Lautém, Viqueque, Cova Lima), the sacred status of crocodiles prevented inhabitants from harming them in retribution. In Manufahí, where no attacks were reported, such traditional values never existed and crocodiles were hunted for subsistence and to improve safety. The design of a context-specific crocodile management programme that respects the reverence attributed to crocodiles by most people but reduces the risk of people being attacked by crocodiles is a conservation management challenge for the government of Timor-Leste. The developing tourism industry, which relies on coastal beaches and reefs, is jeopardized by the risk of crocodile attacks.

Published
2024
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42. Natural Disasters’ Impact on Water Quality and Public Health: A Case Study of the Cyclonic Season (2019–2023)

Author

Sérgio Mateus Chilaule, Xadreque Vitorino Macuacua, Alfredo Pedro Mabica, Nelson Alexandre Miranda, Henrique dos Santos Pereira, Eduardo Samo Gudo, Tatiana Marrufo, Santiago García-López, and Myriam Lopes

Subjects
climate change, flood, water quality, waterborne diseases, integrated water resources management, Environmental pollution, TD172-193.5
Abstract

The impact of climate change has made weather events more extreme, unpredictable and frequent. In the last 4 years, Mozambique has been devastated by 8 major cyclones, resulting in material and human damage and affecting the functioning of basic local services, such as in the water and health sectors. In this study, we explored the environmental components of the climate–water quality–disease relationship that could drive the dynamics of waterborne diseases. Statistical models and geospatial information technologies (GITs) were used to analyse water quality and the relationship with waterborne diseases between 2016 and 2023. Results indicate that water quality is the main element, between precipitation natural disasters and waterborne diseases, on which a relevant public health intervention can act to ameliorate the future negative impacts of climate change and disease incidence. The results of this study also showed that the quality of water affected mainly by heavy rain events varies in different regions and in different seasons.

Published
2024
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44. Sex-related variations in the morphological structure of puma (Puma concolor Linnaeus, 1771) ear skin

Author

Gabriela Pereira de Oliveira Lira, Leonardo Vitorino Costa de Aquino, Samara Lima Olindo, Matheus Barbosa do Nascimento, Herlon Victor Rodrigues Silva, and Alexsandra Fernandes Pereira

Subjects
Biobanks, Conservation strategies, Histomorphometry, Wild felids., Agriculture, Biology (General), QH301-705.5
Abstract

The ear tissue of vulnerable felines, such as the puma, holds potential biological material for creating biobanks. However, skin composition can differ significantly between individuals of the of the same species and even between sexes, based on different environments. Therefore, identifying morphological similarities across these populations is crucial for developing accurate protocols. This study aimed to characterize and evaluate the structure and composition of ear skin in both a male and a female puma using histological techniques. Histomorphometric analysis revealed a total thickness of 304.65 µm and 238.95 µm for the male and the female, respectively. The epidermis was notably thinner in the female compared to the male. Specifically, the thickness of the basal, spinous, and corneum layers in the female was 2.62 µm, 10.07 µm, and 3.15 µm, respectively, compared to 3.49 µm, 13.94 µm, and 3.66 µm in the male, respectively. Melanocytes, keratinocytes, and fibroblasts totaled 26, 24, and 50 cells in the male and 21, 25, and 54 cells in the female. Moreover, chondrocytes (male: n=33 and female: n=41) and perichondrium (male=13.99 µm and female=9.05 µm) were observed in the cartilage. These results demonstrate the histomorphometric differences and similarities between a male and a female puma, consistent with observation in other felines. This information is relevant for a targeted approach for establishing biobanks for this species.

Published
2024
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45. Child Health and Mortality Prevention Surveillance (CHAMPS): Manhiça site description, Mozambique [version 3; peer review: 2 approved]

Author

Fabíola Fernandes, Maria Maixenchs, Inácio Mandomando, Charfudin Sacoor, Ariel Nhacolo, Pio Vitorino, Rita Mabunda, Khátia Munguambe, Edgar Jamisse, Quique Bassat, Marcelino Garrine, Elísio Xerinda, Amílcar Magaço, Carla Carrilho, António Sitoe, Tacilta Nhampossa, Percina Chirinda, Natalia Rakislova, Bento Nhancale, Sara Ajanovic, Arsénio Nhacolo, Arsénia Massinga, Marta Valente, Clara Menéndez, Justina Bramugy, Rosauro Varo, and Jaume Ordi

Subjects
Manhiça site description, Health and Demographic Surveillance System, morbidity surveillance, Mozambique, child mortality, post-mortem, eng, Medicine
Abstract

The Manhiça Health Research Centre (Manhiça HDSS) was established in 1996 in Manhiça, a rural district at Maputo Province in the southern part of Mozambique with approximately 49,000 inhabited households, a total population of 209.000 individuals, and an annual estimated birth cohort of about 5000 babies. Since 2016, Manhiça HDSS is implementing the Child Health and Mortality Prevention Surveillance (CHAMPS) program aiming to investigate causes of death (CoD) in stillbirths and children under the age of 5 years using an innovative post-mortem technique known as Minimally Invasive Tissue sampling (MITS), comprehensive pathogen screening using molecular methods, clinical record abstraction and verbal autopsy. Both in-hospital and community pediatric deaths are investigated using MITS. For this, community-wide socio-demographic approaches (notification of community deaths by key informants, formative research involving several segments of the community, availability of free phone lines for notification of medical emergencies and deaths, etc.) are conducted alongside to foster community awareness, involvement and adherence as well as to compute mortality estimates and collect relevant information of health and mortality determinants. The main objective of this paper is to describe the Manhiça Health and Demographic Surveillance System (HDSS) site and the CHAMPS research environment in place including the local capacities among its reference hospital, laboratories, data center and other relevant areas involved in this ambitious surveillance and research project, whose ultimate aim is to improve child survival through public health actions derived from credible estimates and understanding of the major causes of childhood mortality in Mozambique.

Published
2024
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46. Child Health and Mortality Prevention Surveillance (CHAMPS): Manhiça site description, Mozambique [version 2; peer review: 2 approved]

Author

Fabíola Fernandes, Maria Maixenchs, Inácio Mandomando, Charfudin Sacoor, Ariel Nhacolo, Pio Vitorino, Rita Mabunda, Khátia Munguambe, Edgar Jamisse, Quique Bassat, Marcelino Garrine, Elísio Xerinda, Amílcar Magaço, Carla Carrilho, António Sitoe, Tacilta Nhampossa, Percina Chirinda, Natalia Rakislova, Bento Nhancale, Sara Ajanovic, Arsénio Nhacolo, Arsénia Massinga, Marta Valente, Clara Menéndez, Justina Bramugy, Rosauro Varo, and Jaume Ordi

Subjects
Manhiça site description, Health and Demographic Surveillance System, morbidity surveillance, Mozambique, child mortality, post-mortem, eng, Medicine
Abstract

The Manhiça Health Research Centre (Manhiça HDSS) was established in 1996 in Manhiça, a rural district at Maputo Province in the southern part of Mozambique with approximately 49,000 inhabited households, a total population of 209.000 individuals, and an annual estimated birth cohort of about 5000 babies. Since 2016, Manhiça HDSS is implementing the Child Health and Mortality Prevention Surveillance (CHAMPS) program aiming to investigate causes of death (CoD) in stillbirths and children under the age of 5 years using an innovative post-mortem technique known as Minimally Invasive Tissue sampling (MITS), comprehensive pathogen screening using molecular methods, clinical record abstraction and verbal autopsy. Both in-hospital and community pediatric deaths are investigated using MITS. For this, community-wide socio-demographic approaches (notification of community deaths by key informants, formative research involving several segments of the community, availability of free phone lines for notification of medical emergencies and deaths, etc.) are conducted alongside to foster community awareness, involvement and adherence as well as to compute mortality estimates and collect relevant information of health and mortality determinants. The main objective of this paper is to describe the Manhiça Health and Demographic Surveillance System (HDSS) site and the CHAMPS research environment in place including the local capacities among its reference hospital, laboratories, data center and other relevant areas involved in this ambitious surveillance and research project, whose ultimate aim is to improve child survival through public health actions derived from credible estimates and understanding of the major causes of childhood mortality in Mozambique.

Published
2024
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47. Effect of a Bacillus velezensis and Lysinibacillus fusiformis-based biofertilizer on phosphorus acquisition and grain yield of soybean

Author

Luciana Cristina Vitorino, Elias José da Silva, Marilene Silva Oliveira, Isabella de Oliveira Silva, Lorraine da Silva Santos, Maria Andréia Corrêa Mendonça, Thais Cristina Sousa Oliveira, and Layara Alexandre Bessa

Subjects
endophytic bacteria, insoluble phosphorus, phosphate mineralization, rhizobacteria, phosphate solubilization, Plant culture, SB1-1110
Abstract

IntroductionPhosphate-solubilizing bacteria that function through acidification (organic acid synthesis) or mineralization (production of enzymes such as phytase and phosphatases) have been explored as a biotechnological alternative to enhance plant access to phosphorus (P) retained in organic and inorganic forms in agricultural soils. This study tested the hypothesis that applying a biofertilizer composed of a recognized phosphate-solubilizing bacterium (Bacillus velezensis – endophytic strain BVPS01) and an underexplored plant growth-promoting bacterium (Lysinibacillus fusiformis – endophytic strain BVPS02) would improve the growth and grain yield of Glycine max L. plants.MethodsInitial in vitro tests assessed the functional traits of these bacteria, and a mix of strains BVPS01 and BVPS02 was produced and tested under field conditions to evaluate its agronomic efficiency.ResultsThe results confirmed the hypothesis that the tested biofertilizer enhances the agronomic performance of G. max plants in the field. The B. velezensis strain (BVPS01) was found to be more effective than the L. fusiformis strain (BVPS02) in solubilizing phosphates via the phosphatase enzyme production pathway, indicated by the expression of the phoC and phoD genes. In contrast, L. fusiformis was more effective in solubilizing phosphates through organic acid and phytase-related pathways, in addition to synthesizing indole-3-acetic acid and increasing the mitotic index in the root meristem of G. max plants. These strains exhibited biological compatibility, and the formulated product based on these rhizobacteria enhanced root development and increased the number of nodules and flowers, positively affecting 1000-grain weight, grain yield, and grain P content.DiscussionThus, the tested biofertilizer demonstrated potential to improve root growth and increase both the yield and quality of soybean crops, making it a sustainable and low-cost strategy.

Published
2024
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48. Complicações Pós-Operatórias em Pacientes Transplantados Renais em Centro de Transplantes do Sul de Minas Gerais

Author

Bruno Matida Bonando, Francisco Samuel Silva de Freitas, Vinicius Gobbi, Beatriz Soares Fagundes e Silva, Luciano Magalhães Vitorino, and José Henrique Gomes Torres

Subjects
Transplante de Rim, Complicações Pós-Operatórias, Insuficiência Renal Crônica, Specialties of internal medicine, RC581-951, Special situations and conditions, RC952-1245, Surgery, RD1-811
Abstract

Introdução: As complicações vasculares, urológicas e clínicas podem ocorrer em pacientes submetidos ao transplante renal. Diversos fatores podem influenciar a ocorrência desses eventos, frequentemente demandando reinternações hospitalares. Os serviços de transplantes geralmente se encontram em grandes centros urbanos. No sul do estado de Minas Gerais (MG), há uma cidade com população menor que 100 mil habitantes que dispõe de serviço de transplante. Não há disponível na literatura a prevalência de complicações pós-operatórias em pacientes operados em pequenos centros populacionais. Objetivos: O objetivo do estudo foi descrever as complicações pós-operatórias de pacientes submetidos ao transplante renal em serviço de uma pequena cidade do sul de MG. Métodos: Estudo retrospectivo e descritivo. Utilizaram-se os prontuários digitalizados de pacientes submetidos ao transplante renal (n = 55) no período de 2015 a 2020. Resultados: Dos 55 pacientes analisados, 28 (50,9%) estavam na faixa etária de 40 a 59 anos. A maioria era de indivíduos brancos [41 (74,5%)]. A principal etiologia da doença renal crônica foi de caráter indeterminado (40%). As complicações ocorreram em 61,8% dos pacientes, sendo a maioria de causa cirúrgica (52,9%), especialmente de origem vascular. Não houve diferença significativa na taxa de complicações em relação às variáveis sociodemográficas e clínicas (p > 0,05), exceto quanto à variável hemodiálise (p < 0,001). Conclusão: As complicações cirúrgicas vasculares apresentaram maior prevalência no pós-operatório de pacientes submetidos ao transplante renal em serviço situado em pequena cidade do sul de MG.

Published
2024

49. Prevalência de transtornos psiquiátricos de pessoas em situação de rua em um grande centro urbano no Brasil

Author

Luciano Magalhães Vitorino, Regis Rodrigues Vieira, and Mário Vicente Campos Guimarães

Subjects
Pessoas mal alojadas, Transtornos mentais, Estudos transversais., Medicine (General), R5-920, Public aspects of medicine, RA1-1270
Abstract

Introdução: O presente estudo visa descrever as condições de saúde mental mais prevalentes na população de rua em um grande centro urbano brasileiro. Objetivo: Descrever as condições de saúde mental mais prevalentes na população de moradores de rua em um grande centro urbano brasileiro. Métodos: Este é um estudo transversal realizado nas regiões centrais e periferias da cidade de São Paulo (SP), Brasil. Para a descrição dos transtornos psiquiátricos utilizamos o Patient Health Questionnaire-9 (PHQ-9) para sintomas depressivos, item 9 do Inventário de Depressão de Beck para ideação suicida, pergunta autorreferida para uso de álcool e drogas ilícitas e item 3 do PHQ-9 para qualidade do sono. Resultados: A média de idade dos participantes foi de 44,54 (desvio padrão — DP=12,63) anos, e a maioria era do sexo masculino (n=342; 75%). Quanto à frequência de transtornos psiquiátricos identificados, 49,6% (n=226) dos participantes apresentaram sintomas depressivos, 29,8% (n=136) exibiram ideação suicida, 55,7% (n=254) informaram uso de álcool semanalmente, 34,2% (n=156) informaram usar drogas ilícitas semanalmente e 62,3% (n=284) tinham problemas com sono. Conclusões: A prevalência de condições que afetam a saúde mental entre os participantes é alta. Estes resultados poderão auxiliar profissionais de saúde na elaboração de estratégias de prevenção e tratamento nessa população, pouco estudada.

Published
2024
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50. Shifts in the gut microbiota of sea urchin Diadema antillarum associated with the 2022 disease outbreak

Author

Juliana M. Ruiz-Barrionuevo, Elif Kardas, Ruber Rodríguez-Barreras, Marcos A. Quiñones-Otero, Claudia P. Ruiz-Diaz, Carlos Toledo-Hernández, and Filipa Godoy-Vitorino

Subjects
Diadema antillarum, sea urchin, gut microbiota, outbreak, 16S rRNA, Puerto Rico, Microbiology, QR1-502
Abstract

IntroductionIn recent decades, Caribbean coral reefs have lost many vital marine species due to diseases. The well-documented mass mortality event of the long-spined black sea urchin Diadema antillarum in the early 1980s stands out among these collapses. This die-off killed over 90% of D. antillarum changing the reefscape from coral to algal-dominated. Nearly 40 years later, D. antillarum populations have yet to recover. In early 2022, a new mortality event of D. antillarum was reported along the Caribbean, including Puerto Rico.MethodsThis study identifies the gut microbiota changes associated with the D. antillarum during this mortality event. It contrasts them with the bacterial composition of gut samples from healthy individuals collected in 2019 by using 16S rRNA sequencing analyses.ResultsNotably, the die-off group’s core microbiome resembled bacteria commonly found in the human skin and gut, suggesting potential anthropogenic contamination and wastewater pollution as contributing factors to the 2022 dysbiosis. The animals collected in 2022, especially those with signs of disease, lacked keystone taxa normally found in Diadema including Photobacterium and Propionigenium.DiscussionThe association between human microbes and disease stages in the long-spined urchin D. antillarum, especially in relation to anthropogenic contamination, highlights a complex interplay between environmental stressors and marine health. While these microbes might not be the direct cause of death in this species of sea urchins, their presence and proliferation can indicate underlying issues, such as immune depletion due to pollution, habitat destruction, or climate change, that ultimately compromise the health of these marine organisms.

Published
2024
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