Papillary Thyroid Cancer (PTC) is an endocrine malignancy in which BRAFV600E oncogenic mutation induces the most aggressive phenotype. In this way, considering that lncRNAs are arising as key players in oncogenesis, it is of high interest the identification of BRAFV600E-associated long noncoding RNAs, which can provide possible candidates for secondary mechanisms of BRAF-induced malignancy in PTC. In this study, we identified differentially expressed lncRNAs correlated with BRAFV600E in PTC and, also, extended the cohort of paired normal and PTC samples to more accurately identify differentially expressed lncRNAs between these conditions. Indirectly validated targets of the differentially expressed lncRNAs in PTC compared to matched normal samples demonstrated an involvement in surface receptors responsible for signal transduction and cell adhesion, as well as, regulation of cell death, proliferation and apoptosis. Targets of BRAFV600E-correlated lncRNAs are mainly involved in calcium signaling pathway, ECM-receptor interaction and MAPK pathway. In summary, our study provides candidate lncRNAs that can be either used for future studies related to diagnosis/prognosis or as targets for PTC management.

The skin is our largest organ and the outermost protective barrier. Its aging reflects both intrinsic and extrinsic processes resulting from the constant insults it is exposed to. Aging in the skin is accompanied by specific epigenetic modifications, accumulation of senescent cells, reduced cellular proliferation/tissue renewal, altered extracellular matrix, and a proinflammatory environment favoring undesirable conditions, including disease onset. Macrophages (Mφ) are the most abundant immune cell type in the skin and comprise a group of heterogeneous and plastic cells that are key for skin homeostasis and host defense. However, they have also been implicated in orchestrating chronic inflammation during aging. Since Mφ are related to innate and adaptive immunity, it is possible that age-modified skin Mφ promote adaptive immunity exacerbation and exhaustion, favoring the emergence of proinflammatory pathologies, such as skin cancer. In this review, we will highlight recent findings pertaining to the effects of aging hallmarks over Mφ, supporting the recognition of such cell types as a driving force in skin inflammaging and age-related diseases. We will also present recent research targeting Mφ as potential therapeutic interventions in inflammatory skin disorders and cancer.

Background: Although the pancreatic ductal adenocarcinoma (PDAC) presents high mortality and metastatic potential, there is a lack of effective therapies and a low survival rate for this disease. This PDAC scenario urges new strategies for diagnosis, drug targets, and treatment. Methods: We performed a gene expression microarray meta-analysis of the tumor against normal tissues in order to identify differentially expressed genes (DEG) shared among all datasets, named core-genes (CG). We confirmed the CG protein expression in pancreatic tissue through The Human Protein Atlas. It was selected five genes with the highest area under the curve (AUC) among these proteins with expression confirmed in the tumor group to train an artificial neural network (ANN) to classify samples. Results: This microarray included 461 tumor and 187 normal samples. We identified a CG composed of 40 genes, 39 upregulated, and one downregulated. The upregulated CG included proteins and extracellular matrix receptors linked to actin cytoskeleton reorganization. With the Human Protein Atlas, we verified that fourteen genes of the CG are translated, with high or medium expression in most of the pancreatic tumor samples. To train our ANN, we selected the best genes (AHNAK2, KRT19, LAMB3, LAMC2, and S100P) to classify the samples based on AUC using mRNA expression. The network classified tumor samples with an f1-score of 0.83 for the normal samples and 0.88 for the PDAC samples, with an average of 0.86. The PDAC-ANN could classify the test samples with a sensitivity of 87.6 and specificity of 83.1. Conclusion: The gene expression meta-analysis and confirmation of the protein expression allow us to select five genes highly expressed PDAC samples. We could build a python script to classify the samples based on RNA expression. This software can be useful in the PDAC diagnosis.

Infections caused by Staphylococcus aureus lead to skin infections, as well as soft tissues and bone infections. Given the communal resistance to antibiotics developed by strains of this bacterium, photodynamic therapy emerges as a promising alternative treatment to control and cure infections. Females of the Balb/C mice were infected with 10 CFU of methicillin-resistant S. aureus (MRSA) and divided into four distinct groups: P-L- (negative control group), P+L- (group exposed only to curcumin), P-L+ (group exposed only to LED incidence of 450 nm, 75 mW/cm, and 54 J/cm for 10 min), and P+L+ (group exposed to curcumin followed by 10 min of LED irradiation) (n = 24). The mice were euthanized 48 and 72 h after infection, and biologic materials were collected for analysis of the bacterial load, peripheral blood leukocyte counts, and draining lymph nodes cell counts. The normalization of data was checked and the ANOVA test was applied. The bacterial load in the draining lymph node of P+L+ group was lower when compared to the control groups 72 h post infection (p < 0.0001), indicating that the LED incidence associated with curcumin controls of the staphylococci intradermal infection. The number of the total lymph node cells shows to be lower than control groups in the two availed times (p < 0.01). The histological analysis and the counting of white blood cells did not show differences among cells in the blood and in the tissue of infection. This is the first report showing that photodynamic therapy may be effective against MRSA infection in a murine model of intradermal infection.

Background: Although the pancreatic ductal adenocarcinoma (PDAC) presents high mortality and metastatic potential, there is a lack of effective therapies and a low survival rate for this disease. This PDAC scenario urges new strategies for diagnosis, drug targets, and treatment. Methods:We performed a gene expression microarray meta-analysis of the tumor against healthy tissues in order to identify differentially expressed genes shared among all datasets, named core-genes (CG). We confirmed the pancreatic expressed proteins of the CG through The Human Protein Atlas. The five most expressed proteins in the tumor group were selected to train an artificial neural network to classify samples. 2 Results: This microarray included 110 tumor and 77 healthy samples. We identified a CG composed of 60 genes, 58 upregulated and two downregulated. The upregulated CG included proteins and extracellular matrix receptors linked to actin cytoskeleton reorganization. With the Human Protein Atlas, we verified that thirteen genes of the CG are translated, with high or medium expression in most of the pancreatic tumor samples. To train our artificial neural network, we used the five most expressed genes (KRT19, LAMC2, MELK, MET, TOP2A). The artificial neural network model (PDAC-ANN) classified the train samples with sensitivity of 0.95, specificity of 0.9, and f1-score of 0.93. The PDAC-ANN could classify the test samples with a sensitivity of 0.97, specificity of 0.88, and f1-score 0.94. Conclusion:The gene expression meta-analysis and confirmation of the protein expression allow us to select five genes highly expressed PDAC samples. We could build a python script to classify the samples based on mRNA expression. This software can be useful in the PDAC diagnosis.1 5 migration, and metastasis. The PDAC-ANN trained using gene expression information could classify the samples in normal and PDAC with an f1-score of 0.94 and sensitivity = 0.97. The PDAC-ANN tool can only be used when the gene expression information from KRT19, LAMC2, MELK, MET, and TOP2A are available, in addition to min-max gene expression values rescaling. The PDAC-ANN is a free tool (Additional file 4) that can support in the pancreatic ductal adenocarcinoma diagnosis.

Methicillin-resistant Staphylococcus aureus (MRSA) is responsible for high morbidity and mortality rates. Citral has been studied in the pharmaceutical industry and has shown antimicrobial activity. This study aimed to analyze the antimicrobial activity of citral in inhibiting biofilm formation and modulating virulence genes, with the ultimate goal of finding a strategy for treating infections caused by MRSA strains. Citral showed antimicrobial activity against MRSA isolates with minimum inhibitory concentration (MIC) values between 5 mg/mL (0.5%) and 40 mg/mL (4%), and minimum bactericidal concentration (MBC) values between 10 mg/mL (1%) and 40 mg/mL (4%). The sub-inhibitory dose was 2.5 mg/mL (0.25%). Citral, in an antibiogram, modulated synergistically, antagonistically, or indifferent to the different antibiotics tested. Prior to evaluating the antibiofilm effects of citral, we classified the bacteria according to their biofilm production capacity. Citral showed greater efficacy in the initial stage, and there was a significant reduction in biofilm formation compared to the mature biofilm. qPCR was used to assess the modulation of virulence factor genes, and icaA underexpression was observed in isolates 20 and 48. For icaD, seg, and sei, an increase was observed in the expression of ATCC 33,591. No significant differences were found for eta and etb. Citral could be used as a supplement to conventional antibiotics for MRSA infections.

Arboviral diseases are disseminated all over the world. In Brazil, they remain neglected, alerting public authorities to possible outbreaks. Over here, we report the

Staphylococcus aureus is a Gram-positive bacterium that is considered an important human pathogen. Due to its virulence and ability to acquire mechanisms of resistance to antibiotics, the clinical severity of S. aureus infection is driven by inflammatory responses to the bacteria. Thus, the present study aimed to investigate the modulating role of citral in inflammation caused by S. aureus infection. For this, we used an isolate obtained from a nasal swab sample of a healthy child attending a day-care centre in Vitória da Conquista, Bahia, Brazil. The role of citral in modulating immunological factors against S. aureus infection was evaluated by isolating and cultivating human peripheral blood mononuclear cells. The monocytes were treated with 4%, 2%, and 1% citral before and after inoculation with S. aureus. The cells were analysed by immunophenotyping of monocyte cell surface molecules (CD54, CD282, CD80, HLA-DR, and CD86) and cytokine dosage (IL-1β, IL-6, IL-10, IL-12p70, IL-23, IFN-γ, TGF-β, and TNF-α), and evaluated for the expression of 84 genes related to innate and adaptive immune system responses. GraphPad Prism software and variables with P values < 0.05, were used for statistical analysis. Our data demonstrated citral’s action on the expression of surface markers involved in recognition, presentation, and migration, such as CD14, CD54, and CD80, in global negative regulation of inflammation with inhibitory effects on NF-κB, JNK/p38, and IFN pathways. Consequently, IL-1β, IL-6, IL-12p70, IL-23, IFN-γ, and TNF-α cytokine expression was reduced in groups treated with citral and groups treated with citral at 4%, 2%, and 1% and infected, and levels of anti-inflammatory cytokines such as IL-10 were increased. Furthermore, citral could be used as a supporting anti-inflammatory agent against infections caused by S. aureus. There are no data correlating citral, S. aureus, and the markers analysed here; thus, our study addresses this gap in the literature.