Background The SARS-CoV-2 pandemic was responsible for the death of millions of people around the world, which accelerated the study of vaccines. The BTN161b2 mRNA COVID-19 is a messenger RNA vaccine that encodes the spike protein of the virus. However, the duration of the protection conferred by this vaccine and factors associated with immune responses require validation in large cohorts. Methods Here, we present data of humoral immune response to vaccination in 4264 healthcare workers, tested before (T0) and 15 and 90 days (T1 and T2, respectively) following vaccination. Peripheral blood was collected for immunological analysis using the Quant SARS-CoV-2 IgG II Chemiluminescent Microparticle Immunoassay (CMIA) to determine anti-spike IgG, receptor binding domain (RBD), S1 subunit of SARS-CoV-2. Findings At T0, 96·8% (n=4129) of participants had IgG antibodies non-reactive to anti-SARS-CoV-2. Fifteen days after completing the vaccination, the IgG overall median titer was significantly elevated (21·7x10 3 AU/mL). Both for uni- and multivariate logistic regression analyses women presented higher antibody levels than men, independent of age. Titers were significantly altered among age groups, decreasing by each increase in 10-year of age. At 3 months after completing the vaccination, anti-SARS-CoV-2 IgG titers were 6·3-fold diminished. This real-world post-vaccination data confirmed production of a frequent and elevated anti-SARS-CoV-2 IgG titers, associated with high protection rates. Females and younger participants had higher titer 15 days after vaccination, and despite the significant reduction from 15-to-90 days, those with higher pre-vaccination titers maintained higher levels throughout the remaining timepoints. Interpretation These findings support the need to track humoral immunity kinetics to uncover viral susceptibility and eventually implement re-vaccination, particularly in groups prone to lower humoral immune response. Funding No external funding was received to conduct this study.

This article reports the findings of an empirical study about Automated Text Clustering applied to scientific articles and newspaper texts in Brazilian Portuguese, the objective was to find the most effective computational method able to cluster the input of texts in their original groups. The study covered four experiments, each experiment had four procedures: 1. Corpus Selections (a set of texts is selected for clustering), 2. Word Class Selections (Nouns, Verbs and Adjectives are chosen from each text by using specific algorithms), 3. Filtering Algorithms (a set of terms is selected from the results of the preview stage, a semantic weight is also inserted for each term and an index is generated for each text), 4. Clustering Algorithms (the clustering algorithms Simple K-Means, sIB and EM are applied to the indexes). After those procedures, clustering correctness and clustering time statistical results were collected. The sIB clustering algorithm is the best choice for both scientific and newspaper corpus, under the condition that the sIB clustering algorithm asks for the number of clusters as input before running (for the newspaper corpus, 68.9% correctness in 1 minute and for the scientific corpus, 77.8% correctness in 1 minute). The EM clustering algorithm additionally guesses the number of clusters without user intervention, but its best case is less than 53% correctness. Considering the experiments carried out, the results of human text classification and automated clustering are distant; it was also observed that the clustering correctness results vary according to the number of input texts and their topics.

A proper description of the immune response to SARS-CoV-2 will be critical for the assessment of protection elicited after both infection and vaccination. Uncoupled T and B cell responses have been described in acute and convalescent patients and exposed individuals. We assessed the potential usefulness of whole blood stimulation assays to identify functional cellular immune responses to SARS-CoV-2. Blood from COVID-19 recovered individuals (5 months after infection) and negative subjects was stimulated for 24 hours with HLA predicted peptide “megapools” of the Spike and Nucleoprotein, or the mixture of them. After stimulation, cytokines were quantified using a beads-based multiplex assay. Interleukin-2 and IFN-γ were found to be specific biomarkers of SARS-CoV-2 cellular response. Using the Spike and Nucleoprotein mixture, 91.3% of COVID-19 recovered individuals presented an IL-2 stimulation index over the cut-off, while 82.6% showed IFN-γ. All the negative individuals presented an IL-2 response under the cut-off, while 5.3% of these subjects presented positive IFN-γ stimulation indexes. Moreover, IL-2 production correlated with IgG levels for Spike 1, RBD, and Nucleocapsid. In conclusion, we demonstrate the potential of whole blood stimulation assays and the quantification of IL-2 and IFN-γ for the analysis of SARS-CoV-2 functional cellular responses.

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Introduction: Chromium has been responsible for occupational skin disease, both irritant and/or allergic contact dermatitis. In order to minimize this problem, regulatory measures limiting its use have been implemented. The impact of these regulations should be monitored over time. Material and Methods: A retrospective study from 2009 to 2018 was carried out in the Department of Dermatology to assess the temporal trend of chromium sensitization evaluated by patch testing with potassium dichromate 0.5% pet, particularly considering age, sex and its relationship with occupational activity. Results: 3277 individuals were studied, 2369 females (72.29%) and 908 males (27.71%). Of those 621 (18.95%) fulfilled criteria for occupational contact dermatitis. Chromium allergy was found in 118 (3.60%) patients, 64 females (54.4%) and 54 males (45.76%). We found that male patients were significantly more frequent (45.76% vs 27.03%; p<0.001), as well as occupational dermatitis (31.35% vs 18.47%; p<0.001), hand dermatitis (53.54% vs 23.52%; p<0.001) and age above 40 years (70.34% vs 56.76%; p=0.003). Discussion/Conclusion: The results show a high prevalence (3.60%) of chromium positive patch tests. In our study, there has not been a significant decrease in sensitization to chromium over the years. Interestingly cases classically related to this allergy (cement in the building industry) are no longer the main cause of the problem. We found other sources such as leather as a main cause of allergic sensitization, suggesting a change of the panorama.

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RESUMO Este artigo descreve um estudo sobre o fenômeno da referenciação a partir de um corpus textual extraído do YouTube. O objetivo é verificar a utilização dos referentes em postagens positivas, negativas ou neutras, e como essa verificação contribuiria   para as técnica de análise de sentimentos automática ou semiautomática. Emprega-se a análise de conteúdo e do discurso como métodos de pesquisa, além de software de análise estatística para coleta de frequências de palavras. Conclui-se que a identificação de aspectos de comunicação e informação, tais como os referentes mais utilizados, a não pureza de postagens positivas e negativas, além, da necessidade de criar um critério para a interpretação de dados textuais, podem melhorar o processo de análise de sentimentos.Palavras-chave: Análise de Sentimentos; Análise de Conteúdo; Corpus; Referenciação.ABSTRACT This article describes a study about the phenomenon of referenciation  by using a textual corpus extracted from YouTube. The purpose is to verify how the referents appear in positive, negative, or neutral posts and how this verification can affect the techniques directed to automated or semi-automated sentiment analysis. We applied content and discourse analysis as research methods, and statistical analysis software for the collection of word frequencies. The conclusion is that the identification of communication and information aspects, such as the most used referents, the non-purity of positive and negative posts, and the need to create a criterion for interpreting textual data can improve sentiment analyses process.Keywords: Sentiment Analysis; Content Analysis; Corpus; Reference.