The inflammatory microenvironment of the lung at the time of infection governs innate control of SARS-CoV-2 replication.

Severity of COVID-19 is affected by multiple factors; however, it is not understood how the inflammatory milieu of the lung at the time of SARS-CoV-2 exposure affects the control of viral replication. Here, we demonstrate that immune events in the mouse lung closely preceding SARS-CoV-2 infection affect viral control and identify innate immune pathways that limit viral replication. Pulmonary inflammatory stimuli including resolved, antecedent respiratory infections with or influenza, ongoing pulmonary infection, ovalbumin/alum-induced asthma, or airway administration of TLR ligands and recombinant cytokines all establish an antiviral state in the lung that restricts SARS-CoV-2 replication.

Childhood obesity is associated with a high degree of metabolic disturbance in children from Brazilian semi-arid region.

Projected to impact 310 million children by the next decade, childhood obesity is linked to serious health issues like metabolic disturbance and cardiovascular diseases. This study introduces a novel approach for the integrated assessment of inflammatory, glycemic and lipid disorders in obese children in resources-limited settings and also identifies key factors contributing to these changes. Conducting a cross-sectional analysis of 231 children aged 5-12 years from public schools in Brazil's semi-arid region, the research involved collecting medical history, anthropometric measurements, and blood samples to analyze glycemic and lipid profiles, along with C-reactive protein levels.

Machine learning algorithms using national registry data to predict loss to follow-up during tuberculosis treatment.

Background: Identifying patients at increased risk of loss to follow-up (LTFU) is key to developing strategies to optimize the clinical management of tuberculosis (TB). The use of national registry data in prediction models may be a useful tool to inform healthcare workers about risk of LTFU. Here we developed a score to predict the risk of LTFU during anti-TB treatment (ATT) in a nationwide cohort of cases using clinical data reported to the Brazilian Notifiable Disease Information System (SINAN).

The inflammatory microenvironment of the lung at the time of infection governs innate control of SARS-CoV-2 replication.

SARS-CoV-2 infection leads to vastly divergent clinical outcomes ranging from asymptomatic infection to fatal disease. Co-morbidities, sex, age, host genetics and vaccine status are known to affect disease severity. Yet, how the inflammatory milieu of the lung at the time of SARS-CoV-2 exposure impacts the control of viral replication remains poorly understood.

The impact of ZIKV infection on gene expression in neural cells over time.

Zika virus (ZIKV) outbreak caused one of the most significant medical emergencies in the Americas due to associated microcephaly in newborns. To evaluate the impact of ZIKV infection on neuronal cells over time, we retrieved gene expression data from several ZIKV-infected samples obtained at different time point post-infection (pi). Differential gene expression analysis was applied at each time point, with more differentially expressed genes (DEG) identified at 72h pi.

An integrative multi-omics approach to characterize interactions between tuberculosis and diabetes mellitus.

Tuberculosis-diabetes mellitus (TB-DM) is linked to a distinct inflammatory profile, which can be assessed using multi-omics analyses. Here, a machine learning algorithm was applied to multi-platform data, including cytokines and gene expression in peripheral blood and eicosanoids in urine, in a Brazilian multi-center TB cohort. There were four clinical groups: TB-DM(n = 24), TB only(n = 28), DM(HbA1c ≥ 6.

Machine learning algorithms using national registry data to predict loss to follow- up during tuberculosis treatment.

Background: Identifying patients at increased risk of loss to follow-up (LTFU) is key to developing strategies to optimize the clinical management of tuberculosis (TB). The use of national registry data in prediction models may be a useful tool to inform healthcare workers about risk of LTFU. Here we developed a score to predict the risk of LTFU during anti-TB treatment (ATT) in a nationwide cohort of cases using clinical data reported to the Brazilian Notifiable Disease Information System (SINAN).

BACH1 promotes tissue necrosis and Mycobacterium tuberculosis susceptibility.

Oxidative stress triggers ferroptosis, a form of cellular necrosis characterized by iron-dependent lipid peroxidation, and has been implicated in Mycobacterium tuberculosis (Mtb) pathogenesis. We investigated whether Bach1, a transcription factor that represses multiple antioxidant genes, regulates host resistance to Mtb. We found that BACH1 expression is associated clinically with active pulmonary tuberculosis.

Another tick bites the dust: exploring the association of microbial composition with a broad transmission competence of tick vector species.

Some tick species are competent to transmit more than one pathogen while other species are, until now, known to be competent to transmit only one single or any pathogen. Such a difference in vector competence for one or more pathogens might be related to the microbiome, and understanding what differentiates these two groups of ticks could help us control several diseases aiming at the bacteria groups that contribute to such a broad vector competence. Using 16S rRNA from tick species that could be classified into these groups, genera such as Rickettsia and Staphylococcus seemed to be associated with such a broad vector competence.

A multi-center, prospective cohort study of whole blood gene expression in the tuberculosis-diabetes interaction.

Diabetes mellitus (DM) increases tuberculosis (TB) severity. We compared blood gene expression in adults with pulmonary TB, with or without diabetes mellitus (DM) from sites in Brazil and India. RNA sequencing (RNAseq) performed at baseline and during TB treatment.

In silico transcriptional analysis of mRNA and miRNA reveals unique biosignatures that characterizes different types of diabetes.

Diabetes (DM) has a significant impact on public health. We performed an in silico study of paired datasets of messenger RNA (mRNA) micro-RNA (miRNA) transcripts to delineate potential biosignatures that could distinguish prediabetes (pre-DM), type-1DM (T1DM) and type-2DM (T2DM). Two publicly available datasets containing expression values of mRNA and miRNA obtained from individuals diagnosed with pre-DM, T1DM or T2DM, and normoglycemic controls (NC), were analyzed using systems biology approaches to define combined signatures to distinguish different clinical groups.

A recursive sub-typing screening surveillance system detects the appearance of the ZIKV African lineage in Brazil: Is there a risk of a new epidemic?

There is currently no system to track the emergence of Zika virus (ZIKV) subtypes. We developed a surveillance system able to retrieve sequence submissions and further classify distinct ZIKV genotypes in the world. This approach was able to detect a new occurrence of ZIKV from an African lineage in Brazil in 2019.

Systems biology analysis of publicly available transcriptomic data reveals a critical link between AKR1B10 gene expression, smoking and occurrence of lung cancer.

Background: Cigarette smoking is associated with an increased risk of developing respiratory diseases and various types of cancer. Early identification of such unfavorable outcomes in patients who smoke is critical for optimizing personalized medical care.

Methods: Here, we perform a comprehensive analysis using Systems Biology tools of publicly available data from a total of 6 transcriptomic studies, which examined different specimens of lung tissue and/or cells of smokers and nonsmokers to identify potential markers associated with lung cancer.

Effects of 10-valent pneumococcal conjugate (PCV10) vaccination on the nasopharyngeal microbiome.

Pathogenic bacteria, such as Streptococcus pneumoniae, Staphylococcus aureus, Haemophilus influenzae and Moraxella catarrhalis, are important vaccine targets. The 10-valent pneumococcal conjugate vaccine (PCV10) acts on 10 differents S. pneumoniae serovars.

Meta-Analysis of HTLV-1-Infected Patients Identifies CD40LG and GBP2 as Markers of ATLL and HAM/TSP Clinical Status: Two Genes Beat as One.

Human T-lymphotropic virus 1 (HTLV-1) was the first recognized human retrovirus. Infection can lead to two main symptomatologies: adult T-cell lymphoma/leukemia (ATLL) and HTLV-1 associated myelopathy/tropical spastic paraparesis (HAM/TSP). Each manifestation is associated with distinct characteristics, as ATLL presents as a leukemia-like disease, while HAM/TSP presents as severe inflammation in the central nervous system, leading to paraparesis.

Follow up of a robust meta-signature to identify Zika virus infection in Aedes aegypti: another brick in the wall.

The mosquito Aedes aegypti is the main vector of several arthropod-borne diseases that have global impacts. In a previous meta-analysis, our group identified a vector gene set containing 110 genes strongly associated with infections of dengue, West Nile and yellow fever viruses. Of these 110 genes, four genes allowed a highly accurate classification of infected status.