Hofmeister Effect in Confined Spaces: Halogen Ions and Single Molecule Detection

AbstractDespite extensive research in the nanopore-sensing field, there is a paucity of experimental studies that investigate specific ion effects in confined spaces, such as in nanopores. Here, the effect of halogen anions on a simple bimolecular complexation reaction between monodisperse poly(ethylene glycol) (PEG) and α-hemolysin nanoscale pores have been investigated at the single-molecule level. The anions track the Hofmeister ranking according to their influence upon the on-rate constant. An inverse relationship was demonstrated for the off-rate and the solubility of PEG. The difference among anions spans several hundredfold. Halogen anions play a very significant role in the interaction of PEG with nanopores although, unlike K+, they do not bind to PEG. The specific effect appears dominated by a hydration-dehydration process where ions and PEG compete for water. Our findings provide what we believe to be novel insights into physicochemical mechanisms involved in single-molecule interactions with nanopores and are clearly relevant to more complicated chemical and biological processes involving a transient association of two or more molecules (e.g., reception, signal transduction, enzyme catalysis). It is anticipated that these findings will advance the development of devices with nanopore-based sensors for chemical and biological applications

Extracellular enolase of Candida albicans is involved in colonization of mammalian intestinal epithelium

Enolase is secreted by C. albicans and is present in its biofilms although its extracellular function is unknown. Here we show that extracellular enolase mediates the colonization of small intestine mucosa by C. albicans. Assays using intestinal mucosa disks show that C. albicans adhesion is inhibited, in a dose dependent mode, either by pretreatment of intestinal epithelium mucosa disks with recombinant C. albicans enolase (70% at 0.5 mg/ml enolase) or by pretreatment of C. albicans yeasts with anti-enolase antibodies (48% with 20 µg antiserum). Also using flow cytometry, immunoblots of conditioned media and confocal microscopy we demonstrate that enolase is present in biofilms and that the extracellular enolase is not an artifact due to cell lysis, but must represent functional secretion of a stable form. This is the first direct evidence that C. albicans extracellular enolase mediates colonization on its primary translocation site. Also, because enolase is encoded by a single locus in C. albicans, its dual role peptide, as glycolytic enzyme and extracellular peptide, is a remarkable example of gene sharing in fungi

IFN-gamma Plays a Unique Role in Protection against Low Virulent Trypanosoma cruzi Strain

Background: T. cruzi strains have been divided into six discrete typing units (DTUs) according to their genetic background. These groups are designated T. cruzi I to VI. In this context, amastigotes from G strain (T. cruzi I) are highly infective in vitro and show no parasitemia in vivo. Here we aimed to understand why amastigotes from G strain are highly infective in vitro and do not contribute for a patent in vivo infection. Methodology/Principal Findings: Our in vitro studies demonstrated the first evidence that IFN-gamma would be associated to the low virulence of G strain in vivo. After intraperitoneal amastigotes inoculation in wild-type and knockout mice for TNF-alpha, Nod2, Myd88, iNOS, IL-12p40, IL-18, CD4, CD8 and IFN-gamma we found that the latter is crucial for controlling infection by G strain amastigotes. Conclusions/Significance: Our results showed that amastigotes from G strain are highly infective in vitro but did not contribute for a patent infection in vivo due to its susceptibility to IFN-gamma production by host immune cells. These data are useful to understand the mechanisms underlying the contrasting behavior of different T. cruzi groups for in vitro and in vivo infection.CAPES [3038.005295/2011-40]CAPESFAPEMIGFAPEMIG [APQ-00621-11]CNPqCNPqFAPESPFAPESP [10-50959-4

O ensino de química para deficientes visuais: concepções dos formadores de professores acerca da inclusão

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ELABORAÇÃO DE UM OBJETO VIRTUAL DE APRENDIZAGEM PARA O ENSINO DE QUÍMICA: A INDÚSTRIA FARMACÊUTICA ‘REMEDIAR’

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Stroke outcome measurements from electronic medical records : cross-sectional study on the effectiveness of neural and nonneural classifiers

Background: With the rapid adoption of electronic medical records (EMRs), there is an ever-increasing opportunity to collect data and extract knowledge from EMRs to support patient-centered stroke management. Objective: This study aims to compare the effectiveness of state-of-the-art automatic text classification methods in classifying data to support the prediction of clinical patient outcomes and the extraction of patient characteristics from EMRs. Methods: Our study addressed the computational problems of information extraction and automatic text classification. We identified essential tasks to be considered in an ischemic stroke value-based program. The 30 selected tasks were classified (manually labeled by specialists) according to the following value agenda: tier 1 (achieved health care status), tier 2 (recovery process), care related (clinical management and risk scores), and baseline characteristics. The analyzed data set was retrospectively extracted from the EMRs of patients with stroke from a private Brazilian hospital between 2018 and 2019. A total of 44,206 sentences from free-text medical records in Portuguese were used to train and develop 10 supervised computational machine learning methods, including state-of-the-art neural and nonneural methods, along with ontological rules. As an experimental protocol, we used a 5-fold cross-validation procedure repeated 6 times, along with subject-wise sampling. A heatmap was used to display comparative result analyses according to the best algorithmic effectiveness (F1 score), supported by statistical significance tests. A feature importance analysis was conducted to provide insights into the results. Results: The top-performing models were support vector machines trained with lexical and semantic textual features, showing the importance of dealing with noise in EMR textual representations. The support vector machine models produced statistically superior results in 71% (17/24) of tasks, with an F1 score >80% regarding care-related tasks (patient treatment location, fall risk, thrombolytic therapy, and pressure ulcer risk), the process of recovery (ability to feed orally or ambulate and communicate), health care status achieved (mortality), and baseline characteristics (diabetes, obesity, dyslipidemia, and smoking status). Neural methods were largely outperformed by more traditional nonneural methods, given the characteristics of the data set. Ontological rules were also effective in tasks such as baseline characteristics (alcoholism, atrial fibrillation, and coronary artery disease) and the Rankin scale. The complementarity in effectiveness among models suggests that a combination of models could enhance the results and cover more tasks in the future. Conclusions: Advances in information technology capacity are essential for scalability and agility in measuring health status outcomes. This study allowed us to measure effectiveness and identify opportunities for automating the classification of outcomes of specific tasks related to clinical conditions of stroke victims, and thus ultimately assess the possibility of proactively using these machine learning techniques in real-world situations

Factors Associated with Tuberculosis Treatment Default in an Endemic Area of the Brazilian Amazon: A Case Control-Study

SETTING: Treatment default is a serious problem in tuberculosis control because it implies persistence of infection source, increased mortality, increased relapse rates and facilitates the development of resistant strains. OBJECTIVE: This study analyzed tuberculosis treatment default determinants in the Amazonas State to contribute in planning appropriate control interventions. DESIGN: Observational study with a retrospective cohort using Brazilian Disease Notification System data from 2005 to 2010. A nested case control study design was used. Patients defaulting from treatment were considered as 'cases' and those completing treatment as 'controls'. In the analysis, 11,312 tuberculosis patients were included, 1,584 cases and 9,728 controls. RESULTS: Treatment default was observed to be associated to previous default (aOR 3.20; p<0.001), HIV positivity (aOR 1.62; p<0.001), alcoholism (aOR 1.51; p<0.001), low education level (aOR 1.35; p<0.001) and other co-morbidities (aOR 1.31; p = 0.05). Older patients (aOR 0.98; p = 0.001) and DOT (aOR 0,72; p<0.01) were considered as protective factor for default. CONCLUSIONS: Associated factors should be considered in addressing care and policy actions to tuberculosis control. Information on disease and treatment should be intensified and appropriate to the level of education of the population, in order to promote adherence to treatment and counter the spread of multidrug resistance to anti-TB drugs

High anti-SARS-CoV-2 antibody seroconversion rates before the second wave in Manaus, Brazil, and the protective effect of social behaviour measures: results from the prospective DETECTCoV-19 cohort

Background: The city of Manaus, Brazil, has seen two collapses of the health system due to the COVID-19 pandemic. We report anti-SARS-CoV-2 nucleocapsid IgG antibody seroconversion rates and associated risk factors in Manaus residents before the second wave of the epidemic in Brazil. Methods: A convenience sample of adult (aged ≥18 years) residents of Manaus was recruited through online and university website advertising into the DETECTCoV-19 study cohort. The current analysis of seroconversion included a subgroup of DETECTCoV-19 participants who had at least two serum sample collections separated by at least 4 weeks between Aug 19 and Oct 2, 2020 (visit 1), and Oct 19 and Nov 27, 2020 (visit 2). Those who reported (or had no data on) having a COVID-19 diagnosis before visit 1, and who were positive for anti-SARS-CoV-2 nucleocapsid IgG antibodies at visit 1 were excluded. Using an in-house ELISA, the reactivity index (RI; calculated as the optical density ratio of the sample to the negative control) for serum anti-SARS-CoV-2 nucleocapsid IgG antibodies was measured at both visits. We calculated the incidence of seroconversion (defined as RI values ≤1·5 at visit 1 and ≥1·5 at visit 2, and a ratio >2 between the visit 2 and visit 1 RI values) during the study period, as well as incidence rate ratios (IRRs) through cluster-corrected and adjusted Poisson regression models to analyse associations between seroconversion and variables related to sociodemographic characteristics, health access, comorbidities, COVID-19 exposure, protective behaviours, and symptoms. Findings: 2496 DETECTCoV-19 cohort participants returned for a follow-up visit between Oct 19 and Nov 27, 2020, of whom 204 reported having COVID-19 before the first visit and 24 had no data regarding previous disease status. 559 participants were seropositive for anti-SARS-CoV-2 nucleocapsid IgG antibodies at baseline. Of the remaining 1709 participants who were seronegative at baseline, 71 did not meet the criteria for seroconversion and were excluded from the analyses. Among the remaining 1638 participants who were seronegative at baseline, 214 showed seroconversion at visit 2. The seroconversion incidence was 13·06% (95% CI 11·52–14·79) overall and 6·78% (5·61–8·10) for symptomatic seroconversion, over a median follow-up period of 57 days (IQR 54–61). 48·1% of seroconversion events were estimated to be asymptomatic. The sample had higher proportions of affluent and higher-educated people than those reported for the Manaus city population. In the fully adjusted and corrected model, risk factors for seroconversion before visit 2 were having a COVID-19 case in the household (IRR 1·49 [95% CI 1·21–1·83]), not wearing a mask during contact with a person with COVID-19 (1·25 [1·09–1·45]), relaxation of physical distancing (1·31 [1·05–1·64]), and having flu-like symptoms (1·79 [1·23–2·59]) or a COVID-19 diagnosis (3·57 [2·27–5·63]) between the first and second visits, whereas working remotely was associated with lower incidence (0·74 [0·56–0·97]). Interpretation: An intense infection transmission period preceded the second wave of COVID-19 in Manaus. Several modifiable behaviours increased the risk of seroconversion, including non-compliance with non-pharmaceutical interventions measures such as not wearing a mask during contact, relaxation of protective measures, and non-remote working. Increased testing in high-transmission areas is needed to provide timely information about ongoing transmission and aid appropriate implementation of transmission mitigation measures. Funding: Ministry of Education, Brazil; Fundação de Amparo à Pesquisa do Estado do Amazonas; Pan American Health Organization (PAHO)/WHO.World Health OrganizationRevisión por pare