Temporal validation of the MMCD score to predict kidney replacement therapy and in-hospital mortality in COVID-19 patients.

BACKGROUND: Acute kidney injury has been described as a common complication in patients hospitalized with COVID-19, which may lead to the need for kidney replacement therapy (KRT) in its most severe forms. Our group developed and validated the MMCD score in Brazilian COVID-19 patients to predict KRT, which showed excellent performance using data from 2020. This study aimed to validate the MMCD score in a large cohort of patients hospitalized with COVID-19 in a different pandemic phase and assess its performance to predict in-hospital mortality. METHODS: This study is part of the "Brazilian COVID-19 Registry", a retrospective observational cohort of consecutive patients hospitalized for laboratory-confirmed COVID-19 in 25 Brazilian hospitals between March 2021 and August 2022. The primary outcome was KRT during hospitalization and the secondary was in-hospital mortality. We also searched literature for other prediction models for KRT, to assess the results in our database. Performance was assessed using area under the receiving operator characteristic curve (AUROC) and the Brier score. RESULTS: A total of 9422 patients were included, 53.8% were men, with a median age of 59 (IQR 48-70) years old. The incidence of KRT was 8.8% and in-hospital mortality was 18.1%. The MMCD score had excellent discrimination and overall performance to predict KRT (AUROC: 0.916 [95% CI 0.909-0.924]; Brier score = 0.057). Despite the excellent discrimination and overall performance (AUROC: 0.922 [95% CI 0.914-0.929]; Brier score = 0.100), the calibration was not satisfactory concerning in-hospital mortality. A random forest model was applied in the database, with inferior performance to predict KRT requirement (AUROC: 0.71 [95% CI 0.69-0.73]). CONCLUSION: The MMCD score is not appropriate for in-hospital mortality but demonstrates an excellent predictive ability to predict KRT in COVID-19 patients. The instrument is low cost, objective, fast and accurate, and can contribute to supporting clinical decisions in the efficient allocation of assistance resources in patients with COVID-19.

Yellow Leaf Disease Resistance and Melanaphis sacchari Preference in Commercial Sugarcane Cultivars.

Sugarcane yellow leaf disease (YLD) caused by sugarcane yellow leaf virus (ScYLV) is a major threat for the sugarcane industry worldwide, and the aphid Melanaphis sacchari is its main vector. Breeding programs in Brazil have provided cultivars with intermediate resistance to ScYLV, whereas the incidence of ScYLV has been underestimated partly due to the complexity of YLD symptom expression and identification. Here, we evaluated YLD symptoms in a field assay using eight sugarcane genotypes comprising six well-established commercial high-sucrose cultivars, one biomass yield cultivar, and a susceptible reference under greenhouse conditions, along with estimation of virus titer through RT-qPCR from leaf samples. Additionally, a free-choice bioassay was used to determine the number of aphids feeding on the SCYLV-infected cultivars. Most of the cultivars showed some degree of resistance to YLD, while also revealing positive RT-qPCR results for ScYLV and virus titers with non-significant correlation with YLD severity. The cultivars IACSP01-5503 and IACBIO-266 were similar in terms of aphid preference and ScYLV resistance traits, whereas the least preferred cultivar by M. sacchari, IACSP96-7569, showed intermediate symptoms but similar virus titer to the susceptible reference, SP71-6163. We conclude that current genetic resistance incorporated into sugarcane commercial cultivars does not effectively prevent the spread of ScYLV by its main aphid vector.

A quantitative analysis of the impact of explicit incorporation of recency, seasonality and model specialization into fine-grained tourism demand prediction models.

Forecasting is of utmost importance for the Tourism Industry. The development of models to predict visitation demand to specific places is essential to formulate adequate tourism development plans and policies. Yet, only a handful of models deal with the hard problem of fine-grained (per attraction) tourism demand prediction. In this paper, we argue that three key requirements of this type of application should be fulfilled: (i) recency-forecasting models should consider the impact of recent events (e.g. weather change, epidemics and pandemics); (ii) seasonality-tourism behavior is inherently seasonal; and (iii) model specialization-individual attractions may have very specific idiosyncratic patterns of visitations that should be taken into account. These three key requirements should be considered explicitly and in conjunction to advance the state-of-the-art in tourism prediction models. In our experiments, considering a rich set of indoor and outdoor attractions with environmental and social data, the explicit incorporation of such requirements as features into the models improved the rate of highly accurate predictions by more than 320% when compared to the current state-of-the-art in the field. Moreover, they also help to solve very difficult prediction cases, previously poorly solved by the current models. We also investigate the performance of the models in the (simulated) scenarios in which it is impossible to fulfill all three requirements-for instance, when there is not enough historical data for an attraction to capture seasonality. All in all, the main contributions of this paper are the proposal and evaluation of a new information architecture for fine-grained tourism demand prediction models as well as a quantification of the impact of each of the three aforementioned factors on the accuracy of the learned models. Our results have both theoretical and practical implications towards solving important touristic business demands.

Multi-modality cardiac imaging in the management of diabetic heart disease.

Diabetic heart disease is a major healthcare problem. Patients with diabetes show an excess of death from cardiovascular causes, twice as high as the general population and those with diabetes type 1 and longer duration of the disease present with more severe cardiovascular complications. Premature coronary artery disease and heart failure are leading causes of morbidity and reduced life expectancy. Multimodality cardiac imaging, including echocardiography, cardiac computed tomography, nuclear medicine, and cardiac magnetic resonance play crucial role in the diagnosis and management of different pathologies included in the definition of diabetic heart disease. In this review we summarise the utility of multi-modality cardiac imaging in characterising ischaemic and non-ischaemic causes of diabetic heart disease and give an overview of the current clinical practice. We also describe emerging imaging techniques enabling early detection of coronary artery inflammation and the non-invasive characterisation of the atherosclerotic plaque disease. Furthermore, we discuss the role of MRI-derived techniques in studying altered myocardial metabolism linking diabetes with the development of diabetic cardiomyopathy. Finally, we discuss recent data regarding the use of artificial intelligence applied to large imaging databases and how those efforts can be utilised in the future in screening of patients with diabetes for early signs of disease.

Good clinical practice recommendations in allergen immunotherapy: Position paper of the Brazilian Association of Allergy and Immunology - ASBAI.

Background: Allergen Immunotherapy (AIT) represents one of the pillars in the treatment of allergic diseases. AIT is the only therapeutic strategy with curative potential, promoting the reduction of drug use and long-term symptom control even after the end of the treatment. The European Academy of Allergy, Asthma and Immunology (EAACI) guidelines, position papers of World Allergy Organization (WAO), and the US Practice Parameters are the leading official documents that set scientific standard for the use of AIT in the world. The use of AIT in Brazil has specific regional conditions due to the pattern of allergen sensitization, as well as genetic, socioeconomic, and cultural characteristics, climate conditions, and the availability of allergenic extracts. The most prevalent house dust mites are Dermatophagoides pteronyssinus, Dermatophagoides farinae and their allergens have the highest clinical relevance. Blomia tropicalis is also very frequent. This position paper has been prepared by the Brazilian Association of Allergy and Clinical Immunology (ASBAI) Taskforce on AIT for respiratory allergy and Hymenoptera venom allergy. Objective: According to the current scientific literature adapted to the Brazilian reality, this position paper aims to establish the main recommendations for the good clinical practice parameters for AIT in Brazil. Methods: A systematic review using the Pub Med and Cochrane databases was performed, and the websites of major allergy and immunology organizations were consulted. The research was limited to English language literature and was conducted between March 30, 2002, and March 30, 2022. The terms used for the research were: Allergen Immunotherapy, sublingual immunotherapy (SLIT), subcutaneous immunotherapy (SCIT), venom-specific immunotherapy (VIT), and allergen extract. Results: The several recommendations that establish the clinical practices for AIT recommended by the main Allergy, Asthma and Immunology world organizations were analyzed and adapted to the Brazilian situation. Conclusion: This position paper establishes the main recommendations for the effective clinical practice of AIT in Brazil, using current knowledge of evidence-based medicine and precision medicine.

Infodemics and health misinformation: a systematic review of reviews.

Objective: To compare and summarize the literature regarding infodemics and health misinformation, and to identify challenges and opportunities for addressing the issues of infodemics. Methods: We searched MEDLINE®, Embase®, Cochrane Library of Systematic Reviews, Scopus and Epistemonikos on 6 May 2022 for systematic reviews analysing infodemics, misinformation, disinformation and fake news related to health. We grouped studies based on similarity and retrieved evidence on challenges and opportunities. We used the AMSTAR 2 approach to assess the reviews' methodological quality. To evaluate the quality of the evidence, we used the Grading of Recommendations Assessment, Development and Evaluation guidelines. Findings: Our search identified 31 systematic reviews, of which 17 were published. The proportion of health-related misinformation on social media ranged from 0.2% to 28.8%. Twitter, Facebook, YouTube and Instagram are critical in disseminating the rapid and far-reaching information. The most negative consequences of health misinformation are the increase of misleading or incorrect interpretations of available evidence, impact on mental health, misallocation of health resources and an increase in vaccination hesitancy. The increase of unreliable health information delays care provision and increases the occurrence of hateful and divisive rhetoric. Social media could also be a useful tool to combat misinformation during crises. Included reviews highlight the poor quality of published studies during health crises. Conclusion: Available evidence suggests that infodemics during health emergencies have an adverse effect on society. Multisectoral actions to counteract infodemics and health misinformation are needed, including developing legal policies, creating and promoting awareness campaigns, improving health-related content in mass media and increasing people's digital and health literacy.

Semantic Academic Profiler (SAP): a framework for researcher assessment based on semantic topic modeling.

Recent efforts have focused on identifying multidisciplinary teams and detecting co-Authorship Networks based on exploring topic modeling to identify researchers' expertise. Though promising, none of these efforts perform a real-life evaluation of the quality of the built topics. This paper proposes a Semantic Academic Profiler (SAP) framework that allows summarizing articles written by researchers to automatically build research profiles and perform online evaluations regarding these built profiles. SAP exploits and extends state-of-the-art Topic Modeling strategies based on Cluwords considering n-grams and introduces a new visual interface able to highlight the main topics related to articles, researchers and institutions. To evaluate SAP's capability of summarizing the profile of such entities as well as its usefulness for supporting online assessments of the topics' quality, we perform and contrast two types of evaluation, considering an extensive repository of Brazilian curricula vitae: (1) an offline evaluation, in which we exploit a traditional metric (NPMI) to measure the quality of several data representations strategies including (i) TFIDF, (ii) TFIDF with Bi-grams, (iii) Cluwords, and (iv) CluWords with Bi-grams; and (2) an online evaluation through an A/B test where researchers evaluate their own built profiles. We also perform an online assessment of SAP user interface through a usability test following the SUS methodology. Our experiments indicate that the CluWords with Bi-grams is the best solution and the SAP interface is very useful. We also observed essential differences in the online and offline assessments, indicating that using both together is very important for a comprehensive quality evaluation. Such type of study is scarce in the literature and our findings open space for new lines of investigation in the Topic Modeling area.

Laser-power dependence effects on the structural stability of nanocomposite catalysts studied by Raman spectroscopy: On the structure-activity correlations in glycerol acetylation.

Structural properties of binary CeAl, CeMn, NiAl, CeZr, SnTi and ZrMn nanocomposite oxide catalysts were monitored towards the Laser Raman spectroscopy investigations providing new insights to control catalytic applications upon temperature ranges at which the laser power was varied. The lattice vibrational properties were investigated by varying the incident laser power during Raman measurements from 0.017 mW to 4.0 mW. Structural changes in nanocomposites were achieved upon increasing laser power, which induced local heating disorder causing the sintering of CeMn, SnTi, and ZrMn nanocomposites. The laser-power dependence effects on the structural stability of CeAl, NiAl, and CeZr were observed with high amounts of oxygen vacancy defects over CeAl upon laser power heating. Both CeMn and ZrMn exhibited phase transitions from MnO2 to α-Mn2O3 being the use of the latter nanocomposites limited to work at 1.1 mW. The structure-activity correlations for the nanocomposite oxide catalysts were evaluated through the acetylation of glycerol with acetic acid reaction to produce valuable acetins. Remarkable shifts in the Raman bands wavenumbers and other spectral changes in the lattice mode were caused by laser-induced phenomena accounting for the undesired phase formation and particle growths, as well. This resulted in a low catalytic performance of the NiAl, SnTi, CeMn and ZrMn owing to the thermal effects. Contrary, CeAl and CeZr were more active for acetins products avoiding the phase transformations due to their structural stability at high temperatures, which in turn avoided leaching of the active Ce sites during the reaction.

A new porphyrin as selective substrate-based inhibitor of breast cancer resistance protein (BCRP/ABCG2).

The ABCG2 transporter plays a pivotal role in multidrug resistance, however, no clinical trial using specific ABCG2 inhibitors have been successful. Although ABC transporters actively extrude a wide variety of substrates, photodynamic therapeutic agents with porphyrinic scaffolds are exclusively transported by ABCG2. In this work, we describe for the first time a porphyrin derivative (4B) inhibitor of ABCG2 and capable to overcome multidrug resistance in vitro. The inhibition was time-dependent and 4B was not itself transported by ABCG2. Independently of the substrate, the porphyrin 4B showed an IC50 value of 1.6 µM and a mixed type of inhibition. This compound inhibited the ATPase activity and increased the binding of the conformational-sensitive antibody 5D3. A thermostability assay confirmed allosteric protein changes triggered by the porphyrin. Long-timescale molecular dynamics simulations revealed a different behavior between the ABCG2 porphyrinic substrate pheophorbide a and the porphyrin 4B. Pheophorbide a was able to bind in three different protein sites but 4B showed one binding conformation with a strong ionic interaction with GLU446. The inhibition was selective toward ABCG2, since no inhibition was observed for P-glycoprotein and MRP1. Finally, this compound successfully chemosensitized cells that overexpress ABCG2. These findings reinforce that substrates may be a privileged source of chemical scaffolds for identification of new inhibitors of multidrug resistance-linked ABC transporters.

First Report of a Mastrevirus (Geminiviridae) Transmitted by the Corn Leafhopper.

Maize striate mosaic virus (MSMV; genus Mastrevirus) was recently reported in maize plants in Brazil and also detected by metagenomic analyses in the corn leafhopper, Dalbulus maidis (DeLong & Wolcott). Although these findings suggested that D. maidis is a potential vector, no transmission studies have been performed. Here, we tested the transmission of MSMV by D. maidis from field-collected infected plants and plants infected with MSMV via leafhopper-mediated transmission in the laboratory; all plants were confirmed positive for MSMV by PCR. In each one of three transmission replicates, aviruliferous D. maidis nymphs and adults were confined together on a source plant during a 4-day acquisition access period (AAP) and subsequently transferred to healthy maize seedlings (10 individuals per test plant) in a series of 4-day inoculation access periods (IAPs). We also tested transmission by the corn aphid, Rhopalosiphum maidis (Fitch) and by mechanical inoculation of healthy maize seedlings. Only D. maidis transmitted MSMV, with overall transmission rates of 29.4 and 39.5% on field-collected infected plants and 18.5% on infected plants in laboratory. D. maidis transmitted MSMV until the third (8 to 12 days after the AAP) or fourth successive IAP (12 to 16 days), with gradual loss in transmission efficiency and rate of viruliferous insects over time, suggesting a persistent but nonpropagative mode of transmission. Infected test plants showed mottling symptoms with mild chlorotic streaks and height reduction. This is the first report of transmission of a mastrevirus by D. maidis, facilitating the completion of Koch's postulate for MSMV.

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.

Effect of Sugarcane Cultivars Infected with Sugarcane Yellow Leaf Virus (ScYLV) on Feeding Behavior and Biological Performance of Melanaphis sacchari (Hemiptera: Aphididae).

Sugarcane yellow leaf virus (ScYLV), Polerovirus, Luteoviridae, is one of the main viruses that infect sugarcane worldwide. The virus is transmitted by the aphid Melanaphis sacchari in a persistent, circulative manner. To better understand the interactions between ScYLV, sugarcane genotypes and M. sacchari, we explored the effect of sugarcane cultivars on the feeding behavior and biological performance of the vector. The number of nymphs, adults, winged, total number of aphids and dead aphids was assayed, and an electrical penetration graph (EPG) was used to monitor the stylet activities. Multivariate analysis showed changes in the vector's behavior and biology on cultivars, identifying specific groups of resistance. In the cultivar 7569, only 5.5% of the insects were able to stay longer on sustained phloem ingestion, while in the other seven cultivars these values varied from 20% to 60%. M. sacchari showed low phloem activities in cultivars 7569 and Bio266. Overall, cultivar 7569 showed the worst biological performance of aphids, with the insects presenting mechanical difficulties for feeding and a shorter duration of the phloem period, and thus being considered the most resistant. We conclude that ScYLV virus infection in different sugarcane cultivars induced specific changes in the host plant, modifying the behavior of its main vector, which may favor or impair virus transmission.

Antitumoral activity of liraglutide, a new DNMT inhibitor in breast cancer cells in vitro and in vivo.

Breast cancer (BC) is the most frequently diagnosed female cancer and second leading cause of death. Despite the discovery of many antineoplastic drugs for BC, the current therapy is not totally efficient. In this study, we investigated the potential of repurposing the well-known diabetes type II drug liraglutide to modulate epigenetic modifications in BC cells lines in vitro and in vivo via Ehrlich mice tumors models. The in vitro results revealed a significant reduction on cell viability, migration, DNMT activity and displayed lower levels of global DNA methylation in BC cell lines after liraglutide treatment. The interaction between liraglutide and the DNMT enzymes resulted in a decrease profile of DNA methylation for the CDH1, ESR1 and ADAM33 gene promoter regions and, consequently, increased their gene and protein expression levels. To elucidate the possible interaction between liraglutide and the DNMT1 protein, we performed an in silico study that indicates liraglutide binding in the catalytic cleft via hydrogen bonds and salt bridges with the interdomain contacts and disturbs the overall enzyme conformation. The in vivo study was also able to reveal that liraglutide and the combined treatment of liraglutide and paclitaxel or methotrexate were effective in reducing tumor growth. Moreover, the modulation of CDH1 and ADAM33 mouse gene expression by DNA demethylation suggests a role for liraglutide in DNMT activity in vivo. Altogether, these results indicate that liraglutide may be further analysed as a new adjuvant treatment for BC.

Genome-wide approaches for the identification of markers and genes associated with sugarcane yellow leaf virus resistance.

Sugarcane yellow leaf (SCYL), caused by the sugarcane yellow leaf virus (SCYLV) is a major disease affecting sugarcane, a leading sugar and energy crop. Despite damages caused by SCYLV, the genetic base of resistance to this virus remains largely unknown. Several methodologies have arisen to identify molecular markers associated with SCYLV resistance, which are crucial for marker-assisted selection and understanding response mechanisms to this virus. We investigated the genetic base of SCYLV resistance using dominant and codominant markers and genotypes of interest for sugarcane breeding. A sugarcane panel inoculated with SCYLV was analyzed for SCYL symptoms, and viral titer was estimated by RT-qPCR. This panel was genotyped with 662 dominant markers and 70,888 SNPs and indels with allele proportion information. We used polyploid-adapted genome-wide association analyses and machine-learning algorithms coupled with feature selection methods to establish marker-trait associations. While each approach identified unique marker sets associated with phenotypes, convergences were observed between them and demonstrated their complementarity. Lastly, we annotated these markers, identifying genes encoding emblematic participants in virus resistance mechanisms and previously unreported candidates involved in viral responses. Our approach could accelerate sugarcane breeding targeting SCYLV resistance and facilitate studies on biological processes leading to this trait.

Queixas das puérperas que procuram o banco de leite humano de uma maternidade escola em maceió, alagoas / Complaints from puerperalsolicitingthe Human Milk Bank of a maternity school in Maceió, Alagoas / Quejas de puérperas que buscan el Banco de Leche Humana de una escuela de maternidad en Maceió, Alagoas

Introdução:O Aleitamento Materno é o modo mais seguro, natural e saudável de nutrição para um recém-nascido, por issoo aleitamento materno exclusivo é recomendado até os seis meses de vida.É sabido, os inúmeros benefíciosdessa alimentação, porém pesquisadores apontam uma baixa frequência do aleitamento materno.Objetivo:Identificaras principais queixas que acometem as doadoras de leite humano, que procuram o Banco de Leite Humano de uma Maternidade Escola em Alagoas. Metodologia:Estudo transversal, realizado através de registros cadastrais de 2.909 puérperas doadoras entre 2015 a 2018. Foramcoletadasas principais queixas das nutrizes erealizou-se uma análise descritivasobre as mais prevalentes.Resultados:A faixa etária mais frequente das puérperas foram 28 e 39 anos. As principais queixas relatadas foram: hiperlactaçãoe lesão mamária-mamas cheias (13,5%) e fissuras (5,6%). Foram encontradas associações estatisticamente significativas entre as queixas e as idades maternas -fissuras: 29 anos; mamas cheias: 25,9 anos. A doação voluntária do leite fora o principal motivo da procura ao Banco de Leite Humano, pois no serviço recebiam informações sobre a importância e os benefícios do aleitamento.Conclusões:É perceptível, que a busca ao Banco de Leite Humanopelas puérperas demonstra escassez de informações, sendo esse serviço fundamental na orientação e condutadesses problemas (AU).

Introduction: Breastfeeding is the safest, most natural,and healthy way of nutrition for a newborn baby. Exclusive breastfeeding is recommended up to six months of life. There are many benefits to breastfeeding, but researchers point out a low frequency of breastfeeding.Objective: To identify the main complaints that affect human milk donors who seek the Human Milk Bank of a Maternity School in Alagoas. Methodology: Cross-sectional study, conducted through registry records of 2,909 child donors between 2015 and 2018. The mothers' main complaints were collected, and a descriptive analysis of the most prevalent was carried out. Results: The most frequent age group of puerperal women was 28 and 39 years old. The main complaints reported were:hyper lactation and breast lesions -full breasts (13.5%) and fissures (5.6%). Statistically significant associations were found between the complaints and maternal age -clefts: 29 years; full breasts: 25.9 years. The voluntary donation of milk was the main reason for the demand to the Human Milk Bank because it received information about the importance and benefits of breastfeeding.Conclusions: It is noticeable that the Human Milk Bank search for puerperal shows a scarcity of information, and this service is fundamental in guiding and conducting these problems (AU).

Introducción:La lactancia materna es la forma más segura, natural y saludable de nutrición para un recién nacido. Se recomienda la lactancia materna exclusiva hasta los seis meses de vida. Son muchos los beneficios de la lactancia materna, pero los investigadores señalan una baja frecuencia de la misma.Objetivo:Identificar las principales quejas que afectan a las donantes de leche humana que acuden al Banco de Leche Humana de una Maternidad de Alagoas. Metodología:Estudio transversal, realizado a través de registros de 2.909 niños donantes entre 2015 y 2018. Se recogieron las principales quejas de las madres y se realizó un análisis descriptivo de las más prevalentes.Resultados:El grupo de edad más frecuente de las puérperas fue de 28 y 39 años. Las principales quejas referidas fueron: hiperlactancia y lesiones mamarias -senos llenos (13,5%) y fisuras(5,6%). Se encontraron asociaciones estadísticamente significativas entre las quejas y la edad materna -fisuras: 29 años; senos llenos: 25,9 años. La donación voluntaria de leche fue el principal motivo de demanda al Banco de Leche Humana, ya que recibióinformación sobre la importancia y los beneficios de la lactancia materna. Conclusiones:Se observa que la búsqueda del Banco de Leche Humana para las puérperas muestra una escasez de información, siendo este servicio fundamental para orientar y conducir estos problemas (AU).

Impact of Big Data Analytics on People's Health: Overview of Systematic Reviews and Recommendations for Future Studies.

BACKGROUND: Although the potential of big data analytics for health care is well recognized, evidence is lacking on its effects on public health. OBJECTIVE: The aim of this study was to assess the impact of the use of big data analytics on people's health based on the health indicators and core priorities in the World Health Organization (WHO) General Programme of Work 2019/2023 and the European Programme of Work (EPW), approved and adopted by its Member States, in addition to SARS-CoV-2-related studies. Furthermore, we sought to identify the most relevant challenges and opportunities of these tools with respect to people's health. METHODS: Six databases (MEDLINE, Embase, Cochrane Database of Systematic Reviews via Cochrane Library, Web of Science, Scopus, and Epistemonikos) were searched from the inception date to September 21, 2020. Systematic reviews assessing the effects of big data analytics on health indicators were included. Two authors independently performed screening, selection, data extraction, and quality assessment using the AMSTAR-2 (A Measurement Tool to Assess Systematic Reviews 2) checklist. RESULTS: The literature search initially yielded 185 records, 35 of which met the inclusion criteria, involving more than 5,000,000 patients. Most of the included studies used patient data collected from electronic health records, hospital information systems, private patient databases, and imaging datasets, and involved the use of big data analytics for noncommunicable diseases. "Probability of dying from any of cardiovascular, cancer, diabetes or chronic renal disease" and "suicide mortality rate" were the most commonly assessed health indicators and core priorities within the WHO General Programme of Work 2019/2023 and the EPW 2020/2025. Big data analytics have shown moderate to high accuracy for the diagnosis and prediction of complications of diabetes mellitus as well as for the diagnosis and classification of mental disorders; prediction of suicide attempts and behaviors; and the diagnosis, treatment, and prediction of important clinical outcomes of several chronic diseases. Confidence in the results was rated as "critically low" for 25 reviews, as "low" for 7 reviews, and as "moderate" for 3 reviews. The most frequently identified challenges were establishment of a well-designed and structured data source, and a secure, transparent, and standardized database for patient data. CONCLUSIONS: Although the overall quality of included studies was limited, big data analytics has shown moderate to high accuracy for the diagnosis of certain diseases, improvement in managing chronic diseases, and support for prompt and real-time analyses of large sets of varied input data to diagnose and predict disease outcomes. TRIAL REGISTRATION: International Prospective Register of Systematic Reviews (PROSPERO) CRD42020214048; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=214048.

Posicionamento da Associação Brasileira de Alergia e Imunologia sobre o manejo da imunoterapia específica com alérgenos (ITA) em pacientes vacinados contra COVID­19 / Position statement of the Brazilian Association of Allergy and Immunology on the management of allergen-specific immunotherapy (AIT) in patients vaccinated against COVID­19

A pandemia de COVID-19 representa um grande desafio para todas as especialidades médicas. A imunoterapia com alérgenos (ITA) é considerada o único procedimento terapêutico capaz de modificar a história natural das doenças alérgicas, e caracteriza o estado da arte na área de Alergia e Imunologia. Esta estratégia terapêutica de imunomodulação é capaz de promover a remissão e controle das doenças alérgicas por períodos prolongados, mesmo após o seu término. Existem poucos dados em relação ao emprego da ITA em pacientes vacinados contra COVID-19, e até o momento não há um posicionamento oficial das sociedades internacionais da área de Alergia e Imunologia Clínica. Este documento tem como objetivo estabelecer recomendações práticas para o manejo da ITA em pacientes que receberam a vacina contra COVID-19. Os fenômenos imunológicos envolvidos na imunoprofilaxia vacinal e no mecanismo de ação da ITA foram comparados, proporcionando o estabelecimento de recomendações precisas.

The COVID-19 pandemic represents a serious challenge for all medical specialties. Allergen-specific immunotherapy (AIT) is considered the only therapeutic procedure capable of modifying the natural history of allergic diseases and characterizes the state of the art in the field of allergy and immunology. This therapeutic strategy of immunomodulation is able to promote remission and control of allergic diseases for prolonged periods, even after cessation. There are few data regarding use of AIT in patients vaccinated against COVID-19 and, to date, there is no official position statement published by international allergy and clinical immunology societies. This document aims to establish practical recommendations for the management of AIT in patients who have received the COVID-19 vaccine. The immunological mechanisms involved in immunoprophylaxis with vaccines and the mechanism of action of AIT have been compared to provide a solid basis for establishing precise recommendations.

Mechanistic basis of breast cancer resistance protein inhibition by new indeno[1,2-b]indoles.

The ATP-binding cassette transporter ABCG2 mediates the efflux of several chemotherapeutic drugs, contributing to the development of multidrug resistance (MDR) in many cancers. The most promising strategy to overcome ABCG2-mediated MDR is the use of specific inhibitors. Despite many efforts, the identification of new potent and specific ABCG2 inhibitors remains urgent. In this study, a structural optimization of indeno[1,2-b]indole was performed and a new generation of 18 compounds was synthesized and tested as ABCG2 inhibitors. Most compounds showed ABCG2 inhibition with IC50 values below 0.5 µM. The ratio between cytotoxicity (IG50) and ABCG2 inhibition potency (IC50) was used to identify the best inhibitors. In addition, it was observed that some indeno[1,2-b]indole derivatives produced complete inhibition, while others only partially inhibited the transport function of ABCG2. All indeno[1,2-b]indole derivatives are not transported by ABCG2, and even the partial inhibitors are able to fully chemosensitize cancer cells overexpressing ABCG2. The high affinity of these indeno[1,2-b]indole derivatives was confirmed by the strong stimulatory effect on ABCG2 ATPase activity. These compounds did not affect the binding of conformation-sensitive antibody 5D3 binding, but stabilized the protein structure, as revealed by the thermostabilization assay. Finally, a docking study showed the indeno[1,2-b]indole derivatives share the same binding site as the substrate estrone-3-sulfate.

Sugarcane mosaic virus mediated changes in cytosine methylation pattern and differentially transcribed fragments in resistance-contrasting sugarcane genotypes.

Sugarcane mosaic virus (SCMV) is the causal agent of sugarcane mosaic disease (SMD) in Brazil; it is mainly controlled by using resistant cultivars. Studies on the changes in sugarcane transcriptome provided the first insights about the molecular basis underlying the genetic resistance to SMD; nonetheless, epigenetic modifications such as cytosine methylation is also informative, considering its roles in gene expression regulation. In our previous study, differentially transcribed fragments (DTFs) were obtained using cDNA-amplified fragment length polymorphism by comparing mock- and SCMV-inoculated plants from two sugarcane cultivars with contrasting responses to SMD. In this study, the identification of unexplored DTFs was continued while the same leaf samples were used to evaluate SCMV-mediated changes in the cytosine methylation pattern by using methylation-sensitive amplification polymorphism. This analysis revealed minor changes in cytosine methylation in response to SCMV infection, but distinct changes between the cultivars with contrasting responses to SMD, with higher hypomethylation events 24 and 72 h post-inoculation in the resistant cultivar. The differentially methylated fragments (DMFs) aligned with transcripts, putative promoters, and genomic regions, with a preponderant distribution within CpG islands. The transcripts found were associated with plant immunity and other stress responses, epigenetic changes, and transposable elements. The DTFs aligned with transcripts assigned to stress responses, epigenetic changes, photosynthesis, lipid transport, and oxidoreductases, in which the transcriptional start site is located in proximity with CpG islands and tandem repeats. Real-time quantitative polymerase chain reaction results revealed significant upregulation in the resistant cultivar of aspartyl protease and VQ protein, respectively, selected from DMF and DTF alignments, suggesting their roles in genetic resistance to SMD and supporting the influence of cytosine methylation in gene expression. Thus, we identified new candidate genes for further validation and showed that the changes in cytosine methylation may regulate important mechanisms underlying the genetic resistance to SMD.