An integrated analysis of COVID-19 impacts on energy and environment: Lessons learnt.

Carbon neutrality, sustainable development and reducing our impact on the environment is the top priority in future measures. The COVID-19 pandemic brought challenges to every sector at a global scale but can provide valuable insight to reach these goals. The main objective of this work is to provide an integrated analysis of the impact of the COVID-19 pandemic, focused on energy and its related aspects, i.e., environment and costs. Mainland Portugal was used as a case study and two years were analysed, one pre pandemic (2019) and another post pandemic (2020). In 2020, the majority of sectors - Transport, Services, Industry and Agriculture & Fisheries - show a reduction of energy consumption, atmospheric emissions, carbon footprint and related monetary and social costs. In contrast, the Domestic sector presents an overall increase, with maximums of 25.4% in electricity consumption (during Spring), 0.72% in the PM10 (particulate matter) and NOx (nitrogen dioxides) emissions (in Summer), and 2.9% in carbon footprint (in Spring). The integrated analysis proposed in this work was crucial to identify the paths to a post pandemic world focused on the different aspects of sustainability - new concepts of mobility and workplace, as well as increased investment in energy performance and renewable energy sources. This study showed that changing our energy consumption patterns could significantly affect future greenhouse gas emissions, and contribute to the sustainable growth of the economy, while maintaining good progress towards climate-neutral goals.

COVID-19 Pandemic Impact on Liver Donation in the Largest Brazilian Transplantation Center.

BACKGROUND: COVID-19 has spread worldwide and has become a public health emergency and a pandemic of international concern. The solid organ donation system was no different. This study aimed to investigate the effect of COVID-19 on the liver transplant (LT) system in Brazilian territory. METHODS: We retrospectively reviewed all liver donor records allocated in São Paulo State, Brazil, 1 year before and 1 year during the COVID-19 pandemic. We defined the pre-COVID-19 (PRE) period as between April 2019 and April 2020 and the post-COVID-19 (POST) period as between April 2020 and April 2021. Moreover, we compared LT performed in our institution during these periods. To evaluate outcomes, we compared 30-day survival after LT. RESULTS: In the PRE period, 1452 livers were offered for donation in São Paulo State and other Brazilian territories. Of these, 592 were used in LT. In the POST period, 1314 livers were offered for donation, but only 477 were used in LT. Organ refusal was higher in the POST period (P < .05). Our center performed 127 and 156 LTs in these periods, respectively, and an increase above 20% was significant (P = .039). There was no difference in 30-day survival between the periods (87.2% vs 87.9%, P > .5, respectively). CONCLUSIONS: The COVID-19 pandemic harmed potential and allocated donors and LTs performed. However, it is possible to maintain the LT volume of a transplant center without compromising survival outcomes through preventive strategies against COVID-19 propagation.

Active Distribution Networks with Microgrid and Distributed Energy Resources Optimization Using Hierarchical Model

Distribution networks have undergone a series of changes, with the insertion of distributed energy resources, such as distributed generation, energy storage systems, and demand response, allowing the consumers to produce energy and have an active role in distribution systems. Thus, it is possible to form microgrids. From the active grid’s point of view, it is necessary to plan the operation considering the distributed resources and the microgrids connected to it, aiming to ensure the maintenance of grid economy and operational safety. So, this paper presents the proposition of a hierarchical model for planning the daily operation of active distribution grids with microgrids. In this case, the entire grid operation is optimized considering the results from the microgrid optimization itself. If none of the technical constraints, for example voltage levels, are reached, the grid is optimized, however, if there are some violations in the constraints feedback is sent to the internal microgrid optimization to be run again. Several scenarios are evaluated to verify the iteration among the controls in a coordinated way allowing the optimization of the operation of microgrids, as well as of the distribution network. A coordinated and hierarchical operation of active distribution networks with microgrids, specifically when they have distributed energy resources allocated and operated in an optimized way, results in a reduction in operating costs, losses, and greater flexibility and security of the whole system.

Evaluation of the Microbiological Effectiveness of Three Accessible Mask Decontamination Methods and Their Impact on Filtration, Air Permeability and Physicochemical Properties.

The need to secure public health and mitigate the environmental impact associated with the massified use of respiratory protective devices (RPD) has been raising awareness for the safe reuse of decontaminated masks by individuals and organizations. Among the decontamination treatments proposed, in this work, three methods with the potential to be adopted by households and organizations of different sizes were analysed: contact with nebulized hydrogen peroxide (H2O2); immersion in commercial bleach (NaClO) (sodium hypochlorite, 0.1% p/v); and contact with steam in microwave steam-sanitizing bags (steam bag). Their decontamination effectiveness was assessed using reference microorganisms following international standards (issued by ISO and FDA). Furthermore, the impact on filtration efficiency, air permeability and several physicochemical and structural characteristics of the masks, were evaluated for untreated masks and after 1, 5 and 10 cycles of treatment. Three types of RPD were analysed: surgical, KN95, and cloth masks. Results demonstrated that the H2O2 protocol sterilized KN95 and surgical masks (reduction of >6 log10 CFUs) and disinfected cloth masks (reduction of >3 log10 CFUs). The NaClO protocol sterilized surgical masks, and disinfected KN95 and cloth masks. Steam bags sterilized KN95 and disinfected surgical and cloth masks. No relevant impact was observed on filtration efficiency.

Long-term prevalence of taste and olfactory dysfunction in COVID-19 patients: A cross-sectional study.

OBJECTIVES: The objectives of the study were to investigate the long-term prevalence of taste disorder (TD) and olfactory disorder (OD) and associated risk factors in the non-hospitalized southeastern Brazil population of COVID-19 patients. METHODS: This cross-sectional open survey evaluated possible long-term OD and TD in non-hospitalized patients who had been diagnosed with COVID-19 for more than 30 days, through an online self-report questionnaire. Demographic data, comorbidities, symptoms, and the intensity of OD and TD at the time of diagnosis and at the time of completing the questionnaire were evaluated. RESULTS: Three hundred five responses were included. The reported prevalence of OD and TD was 72.9% and 67.4%, respectively, in the moment of diagnosis; after a mean follow-up period of 179 days, 45% and 50% still had some degree of the symptoms. There was a positive correlation between age and the high prevalence of OD (p = 0.02). However, there was no correlation between age and TD (p = 0.961) and weight in relation to OD/TD (p = 0.500 and p = 0.636, respectively). CONCLUSION: This study observed a high long-term prevalence of OD and TD associated with COVID-19, with a low recovery rate during the study period. There was a positive association between older participants and the prevalence of OD.

Enrichment analysis on regulatory subspaces: A novel direction for the superior description of cellular responses to SARS-CoV-2.

STATEMENT: Enrichment analysis of cell transcriptional responses to SARS-CoV-2 infection from biclustering solutions yields broader coverage and superior enrichment of GO terms and KEGG pathways against alternative state-of-the-art machine learning solutions, thus aiding knowledge extraction. MOTIVATION AND METHODS: The comprehensive understanding of the impacts of SARS-CoV-2 virus on infected cells is still incomplete. This work aims at comparing the role of state-of-the-art machine learning approaches in the study of cell regulatory processes affected and induced by the SARS-CoV-2 virus using transcriptomic data from both infectable cell lines available in public databases and in vivo samples. In particular, we assess the relevance of clustering, biclustering and predictive modeling methods for functional enrichment. Statistical principles to handle scarcity of observations, high data dimensionality, and complex gene interactions are further discussed. In particular, and without loos of generalization ability, the proposed methods are applied to study the differential regulatory response of lung cell lines to SARS-CoV-2 (α-variant) against RSV, IAV (H1N1), and HPIV3 viruses. RESULTS: Gathered results show that, although clustering and predictive algorithms aid classic stances to functional enrichment analysis, more recent pattern-based biclustering algorithms significantly improve the number and quality of enriched GO terms and KEGG pathways with controlled false positive risks. Additionally, a comparative analysis of these results is performed to identify potential pathophysiological characteristics of COVID-19. These are further compared to those identified by other authors for the same virus as well as related ones such as SARS-CoV-1. The findings are particularly relevant given the lack of other works utilizing more complex machine learning algorithms within this context.

Liver transplant after SARS-CoV-2 infection: A systematic review.

BACKGROUND: The Coronavirus 19 (COVID-19) pandemic has dramatically impacted liver organ transplantation. The American Society of Transplantation recommends a minimum of 28 days after symptom resolution for organ donation. However, the exact time for transplantation for recipients is unknown. Considering that mortality on the waiting list for patients with MELD >25 or fulminant hepatitis is higher than that of COVID-19, the best time for surgery after SARS-CoV-2 infection remains undetermined. This study aims to expand the current knowledge regarding the Liver Transplantation (LT) time for patients after COVID-19 and to provide transplant physicians with essential decision-making tools to manage these critically ill patients during the pandemic. METHODS: Systematic review of patients who underwent liver transplantation after diagnosis of COVID-19. The MEDLINE, PubMed, Cochrane, Lilacs, Embase, and Scielo databases were searched until June 20, 2021. The MESH terms used were "COVID-19" and "Liver transplantation". RESULTS: 558 articles were found; of these 13 articles and a total of 18 cases of COVID-19 prior to liver transplantation were reported. The mean age was 38.7±14.6, with male prevalence. Most had mild symptoms of COVID. Five patients have specific treatment for COVID-19 with convalescent plasm or remdesivir/oseltamivir, just one patient received hydroxychloroquine, and 12 patients received only symptomatic treatment. The median time between COVID-19 to LT was 19 days (13.5‒44.5). Deceased donor liver transplantation accounted for 61% of cases, while living donor transplantation was 39%. CONCLUSION: Despite the concerns regarding the postoperative evolution, the mortality of patients with high MELD or fulminant hepatitis transplanted shortly after COVID-19 diagnosis does not seem to be higher. (PROSPERO, registration number = CRD42021261790).

Evolutionary history of the SARS-CoV-2 Gamma variant of concern (P.1): a perfect storm.

Our goal was to describe in more detail the evolutionary history of Gamma and two derived lineages (P.1.1 and P.1.2), which are part of the arms race that SARS-CoV-2 wages with its host. A total of 4,977 sequences of the Gamma strain of SARS-CoV-2 from Brazil were analyzed. We detected 194 sites under positive selection in 12 genes/ORFs: Spike, N, M, E, ORF1a, ORF1b, ORF3, ORF6, ORF7a, ORF7b, ORF8, and ORF10. Some diagnostic sites for Gamma lacked a signature of positive selection in our study, but these were not fixed, apparently escaping the action of purifying selection. Our network analyses revealed branches leading to expanding haplotypes with sites under selection only detected when P.1.1 and P.1.2 were considered. The P.1.2 exclusive haplotype H_5 originated from a non-synonymous mutational step (H3509Y) in H_1 of ORF1a. The selected allele, 3509Y, represents an adaptive novelty involving ORF1a of P.1. Finally, we discuss how phenomena such as epistasis and antagonistic pleiotropy could limit the emergence of new alleles (and combinations thereof) in SARS-COV-2 lineages, maintaining infectivity in humans, while providing rapid response capabilities to face the arms race triggered by host immuneresponses.

Introduction of SARS-CoV-2 C.37 (WHO VOI lambda) in the Sao Paulo State, Southeast Brazil.

The Lambda variants of interest (VOI) (C37/GR/452Q.V1/21G) was initially reported in Lima, Peru but has gained rapid dissemination through other Latin American countries. Nevertheless, the dissemination and molecular epidemiology of the Lambda VOI in Brazil is unknown apart from a single case report. In this respect, we characterized the circulation of the SARS-CoV-2 Lambda VOI (C37/GR/452Q.V1/21G) in Sao Paulo State, Brazil. From March to June 2021, we identified seven Lambda isolates in a set of approximately 8000 newly sequenced genomes of the Network for Pandemic Alert of Emerging SARS-CoV-2 variants from Sao Paulo State. Interestingly, in three of the positive patients, the Lambda VOI infection was probably related to a contact transmission. These individuals were fully vaccinated to COVID-19 and presented mild symptoms. The remaining positive for Lambda VOI individuals showed different levels of COVID-19 symptoms and one of them needed hospitalization (score 5, WHO). In our study, we present a low level of Lambda VOI circulation in the Sao Paulo State. This reinforces the essential role of molecular surveillance for the effective SARS-CoV-2 pandemic response, especially in regard to circulating variants.

Transitioning the Teaching/Learning Process to Online Environment During the COVID-19 Pandemic

The adaptation of both teachers and students to the application of pedagogical techniques in remote teaching/learning platforms of a Portuguese technology and engineering school of a higher education institution, due to the confinement imposed by the safety measures taken against the COVID-19 pandemic, is presented in this paper. The teachers’ behavior and students’ attitude concerning the change to remote teaching and learning methods is analysed. The actions taken, the difficulties experienced by the academic community in the transition from face-to-face to remote education, in particular the changeover of technical-scientific and pedagogical components in the course units, the evaluation of the teaching-learning process and the improvement needs are presented. Considerations on possible solutions and some relevant conclusions are also pointed out, showing that both teachers and students are not ready to switch to new digital means of education. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Conceptual Maps Applied to Remote/Virtual Laboratories for Active Learning

The active construction of knowledge in a laboratory environment requires the application of a set of pedagogical techniques in order to avoid rote learning in engineering education. This paper presents the implementation of conceptual maps in laboratory context of an engineering course unit as an active pedagogical approach to foster the students’ meaningful learning in times of COVID pandemic. Different methodologies of laboratory work are first presented, as well as the meaning of conceptual map. Then, an application example on how the conceptual map was introduced in a first laboratory class of Electrical Engineering, and also the students’ experiences and difficulties encountered when dealing with the practical implementation of conceptual maps, is illustrated. Finally, some relevant conclusions about the implementation of this active pedagogical approach are given, in particular the development of the students’ meaningful learning by exploring relationships between concepts, ideas or propositions, by addressing the most important differences and by revealing inconsistencies on the topics studied. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Enrichment analysis on regulatory subspaces: a novel direction for the superior description of cellular responses to SARS-CoV-2 (preprint)

Statement: The enrichment analysis of discriminative cell transcriptional responses to SARS-CoV-2 infection using biclustering produces a broader set of superiorly enriched GO terms and KEGG pathways against alternative state-of-the-art machine learning approaches, unraveling novel knowledge. Motivation and methods: The comprehensive understanding of the impacts of the SARS-CoV-2 virus on infected cells is still incomplete. This work identifies and analyses the main cell regulatory processes affected and induced by SARS-CoV-2, using transcriptomic data from several infectable cell lines available in public databases and in vivo samples. We propose a new class of statistical models to handle three major challenges, namely the scarcity of observations, the high dimensionality of the data, and the complexity of the interactions between genes. Additionally, we analyse the function of these genes and their interactions within cells to compare them to ones affected by IAV (H1N1), RSV and HPIV3 in the target cell lines. Results: Gathered results show that, although clustering and predictive algorithms aid classic functional enrichment analysis, recent pattern-based biclustering algorithms significantly improve the number and quality of the detected biological processes. Additionally, a comparative analysis of these processes is performed to identify potential pathophysiological characteristics of COVID-19. These are further compared to those identified by other authors for the same virus as well as related ones such as SARS-CoV-1. This approach is particularly relevant due to a lack of other works utilizing more complex machine learning tools within this context.

Ocular Involvement in COVID-19: Conjunctivitis and More. / Okuläre Mitbeteiligung bei COVID-19: Konjunktivitis und mehr.

Since the beginning of 2020, SARS-CoV-2, the pathogen of COVID-19, has led to a global pandemic that also affects ophthalmology. Ophthalmologists can be confronted at any time with potentially COVID-19 associated ocular symptoms or manifestations in patients and also become infected through close patient contact. Even without systemic infection, the ocular surface can come into direct contact with aerosols or liquids containing SARS-CoV-2 particles. A smear infection through hand-to-eye contact is also possible. A purely isolated ocular infection has not yet been shown. Rather, it seems that ocular complications occur in the context of a systemic infection. However, ocular symptoms can also be the first symptom of COVID-19. The most common ocular complication of COVID-19 is mild follicular conjunctivitis. Haemorrhagic conjunctivitis, dry eye disease, episcleritis, or retinal involvement can also occur less frequently. There are currently no evidence-based therapy recommendations for COVID-19 associated diseases of the ocular surface. Artificial tears might be helpful for symptom relief. There is no evidence for antiviral, antibiotic, or anti-inflammatory therapies, but these medications might be used in individual cases. Potential intraocular complications include retinal artery occlusions and haemorrhages, as well as cotton wool spots caused by complement-mediated thrombotic angiopathy. Neuro-ophthalmological complications including Miller-Fisher syndrome or infarct-related central blindness can also occur in very rare cases. Knowledge of potential transmission routes and personal protective equipment is just as essential for each ophthalmologist as a basic knowledge of potential ocular symptoms and complications.

Predictability of COVID-19 Hospitalizations, Intensive Care Unit Admissions, and Respiratory Assistance in Portugal: Longitudinal Cohort Study.

BACKGROUND: In the face of the current COVID-19 pandemic, the timely prediction of upcoming medical needs for infected individuals enables better and quicker care provision when necessary and management decisions within health care systems. OBJECTIVE: This work aims to predict the medical needs (hospitalizations, intensive care unit admissions, and respiratory assistance) and survivability of individuals testing positive for SARS-CoV-2 infection in Portugal. METHODS: A retrospective cohort of 38,545 infected individuals during 2020 was used. Predictions of medical needs were performed using state-of-the-art machine learning approaches at various stages of a patient's cycle, namely, at testing (prehospitalization), at posthospitalization, and during postintensive care. A thorough optimization of state-of-the-art predictors was undertaken to assess the ability to anticipate medical needs and infection outcomes using demographic and comorbidity variables, as well as dates associated with symptom onset, testing, and hospitalization. RESULTS: For the target cohort, 75% of hospitalization needs could be identified at the time of testing for SARS-CoV-2 infection. Over 60% of respiratory needs could be identified at the time of hospitalization. Both predictions had >50% precision. CONCLUSIONS: The conducted study pinpoints the relevance of the proposed predictive models as good candidates to support medical decisions in the Portuguese population, including both monitoring and in-hospital care decisions. A clinical decision support system is further provided to this end.

Management of thyroid disorders during the COVID-19 outbreak: a position statement from the Thyroid Department of the Brazilian Society of Endocrinology and Metabolism (SBEM).

This position statement was prepared to guide endocrinologists on the best approach to managing thyroid disorders during the coronavirus disease (COVID-19) pandemic. The most frequent thyroid hormonal findings in patients with COVID-19, particularly in individuals with severe disease, are similar to those present in the non-thyroidal illness syndrome and require no intervention. Subacute thyroiditis has also been reported during COVID-19 infection. Diagnosis and treatment of hypothyroidism during the COVID-19 pandemic may follow usual practice; however, should avoid frequent laboratory tests in patients with previous controlled disease. Well-controlled hypo and hyperthyroidism are not associated with an increased risk of COVID-19 infection or severity. Newly diagnosed hyperthyroidism during the pandemic should be preferably treated with antithyroid drugs (ATDs), bearing in mind the possibility of rare side effects with these medications, particularly agranulocytosis, which requires immediate intervention. Definitive treatment of hyperthyroidism (radioiodine therapy or surgery) may be considered in those cases that protective protocols can be followed to avoid COVID-19 contamination or once the pandemic is over. In patients with moderate Graves' ophthalmopathy (GO) not at risk of visual loss, glucocorticoids at immunosuppressive doses should be avoided, while in those with severe GO without COVID-19 and at risk of vision loss, intravenous glucocorticoid is the therapeutic choice. Considering that most of the thyroid cancer cases are low risk and associated with an excellent prognosis, surgical procedures could and should be postponed safely during the pandemic period. Additionally, when indicated, radioiodine therapy could also be safely postponed as long as it is possible.

Genomic monitoring unveil the early detection of the SARS-CoV-2 B.1.351 lineage (20H/501Y.V2) in Brazil (preprint)

Sao Paulo State, the most populous area in Brazil, currently experiences a second wave of the COVID-19 pandemic which overwhelmed the healthcare system. Recently, due to the paucity of SARS-CoV-2 complete genome sequences, we established a Network for Pandemic Alert of Emerging SARS-CoV-2 Variants to rapidly understand the spread of SARS-CoV-2 and monitor in nearly real-time the circulating SARS-CoV-2 variants into the state. Through full genome analysis of 217 SARS-CoV-2 complete genome sequences obtained from the largest regional health departments we were able to identify the co-circulation of multiple SARS-CoV-2 lineages such as i) B.1.1 (0.92%), ii) B.1.1.1 (0.46%), iii) B.1.1.28 (25.34%), iv) B.1.1.7 (5.99%), v) B.1.566 (1.84%), vi) P.1 (64.05%), and P.2 (0.92%). Further our analysis allowed the detection, for the first time in Brazil of the South African variant of concern (VOC), the B.1.351 (501Y.V2) (0.46%). The identified lineage was characterized by the presence of the following mutations: ORF1ab: T265I, R724K, S1612L, K1655N, K3353R, SGF 3675_F3677del, P4715L, E5585D; Spike: D80A, D215G, L242_L244del, A262D, K417N, E484K, N501Y, D614G, A701V, C1247F; ORF3a: Q57H, S171L, E: P71L; ORF7b: Y10F, N: T205I; ORF14: L52F. Origin of the most recent common ancestor of this genomic variant was inferred to be between middle October to late December 2020. Analysis of generated sequences demonstrated the predominance of the P.1 lineage and allowed the early detection of the South African strain for the first time in Brazil. Our findings highlight the importance to increase active monitoring to ensure the rapid detection of new SARS-CoV-2 variants with a potential impact in pandemic control and vaccination strategies.