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Background: Violence is a worldwide public health challenge and has been linked to depression in many settings. Depression is higher in women and differential exposure to violence is a potential risk factor – especially in countries with high-levels of violence. This paper provides a comprehensive characterization of the association between violence victimization and depression in Brazil, focusing on sex/gender inequalities. Methods: We used data from the 2019 wave of the National Health Survey (PNS) in Brazil to assess whether respondents had depression (using PHQ-9) and if they were victims of violence, differentiating by the type of violence, the frequency of victimization, and the primary aggressor. We used logit models to assess the association between victimization and the likelihood of having depression. We predicted probabilities of being depressed, considering the interaction between violence victimization and sex/gender, to analyze the differences between men and women. Results: Rates of violence victimization and depression were higher among women than among men. The odds of being depressed were 3.8 (95%CI: 3.5–4.2) times higher among victims of violence than among non-victims, and 2.3 (95%CI: 2.1–2.6) times higher among women than among men, adjusting for socioeconomic factors. For any given income level, racial/ethnic or age group, victims of violence who were women had the highest predicted probabilities of being depressed – e.g., 29.4% (95%CI: 26.1–32.8) for lower-income women, 28.9% (95%CI: 24.4–33.2) for black women, and 30.4% (95%CI: 25.4–35.4) for younger women that suffered violence. Over one in three women that suffered multiple types of violence, experienced violence more frequently, or where the aggressor was an intimate partner or another family member were predicted to have depression. Conclusions: Being a victim of violence was strongly associated with higher risk of depression in Brazil, with women more likely to be both victims of violence and develop depression. Frequent, sexual, physical or psychological violence, and intimate partners or family member perpetrators were major risk factors for depression and should be a public health priority. [ABSTRACT FROM AUTHOR]

Simple Summary: Papillary thyroid cancer is not an aggressive cancer, even when metastasis are present; therefore, treatment has been downgraded in recent years. However rare, mortality exists and finding the factors associated with mortality is essential and has not yet been fully accomplished; the answer probably lies in molecular factors. This study aimed to find MicroRNAs related to death in metastatic patients and found that patients who died due to progression of PTC had higher expression levels of miR-101-3p, miR-17-5p, and miR-191-5p compared with those of patients with stable metastatic disease. These findings are new in the literature and may open new doors in differentiating the patients who need more aggressive treatment from those who do not. Papillary thyroid carcinoma (PTC) is the most common neoplasm of the endocrine system and has an excellent long-term prognosis, with low rates of distant metastatic disease. Although infrequent, there are cases of deaths directly related to PTC, especially in patients with metastatic disease, and the factors that could be associated with this unfavorable outcome remain a major challenge in clinical practice. Recently, research into genetic factors associated with PTC has gained ground, especially mutations in the TERT promoter and BRAF gene. However, the role of microRNAs remains poorly studied, especially in those patients who have an unfavorable outcome at follow-up. This paper aims to evaluate molecular markers related to the different pathological processes of PTC, as well as the histological characteristics of the neoplasm, and to compare this profile with prognosis and death from the disease using an analysis of patients treated for metastatic disease in a single tertiary cancer center. Evaluation of microRNA expression in paraffin-embedded tumor specimens was carried out by quantitative PCR using the TaqMan® Low Density Array (TLDA) system. Metastatic patients who died from progression of PTC had higher expressions of miR-101-3p, miR-17-5p, and miR-191-5p when compared to patients with stable metastatic disease. These findings are of great importance but should be considered as preliminary because of the small sample. [ABSTRACT FROM AUTHOR]

• The project 'Tropical Biomass & Carbon' and its main product TB&C App is introduced. • TB&C App is an user-friendly tool that estimates C stored in forests of Brazil. • Model performance analysis proved reliability >95% of the TB&C App's models. • Carbon in Amazonian forests can be accurately and precisely estimated. • A dataset containing 64,000 plots with forest variables is delivered as supplement. This article introduces the Tropical Biomass & Carbon Application – the 'TB&C App', a web application available on the permanent link www.tropicalbiomass.com. The TB&C App requires as input attributes 'the smallest and largest diameters', 'number of trees ha−1', basal area ha−1, and 'parameters of the diameter (beta) distribution' describing stand structure. The App delivers outputs at two levels: (1) Stand level, including mean aboveground biomass (AGB) and carbon (AGC), in Mg ha−1, along with confidence intervals (CIs) as measures of uncertainty, and; (2) Tree level estimates, with AGB and diameter for every simulated tree. Phase 1 of the project TB&C comprises four Brazilian forest (and non-forest) formations: Campinarana, Floresta estacional, Floresta ombrofila , and Savana. This article aims to (i) describe the algorithm written for the TB&C App, and (ii) present results of Phase 1. This first phase counts on a standardized database of 1,428 trees with field-measured dry AGB, from plots across the different formations, which is the largest tree-biomass database compiled so far in Brazil. Model uncertainties were incorporated into the modeling process, allowing computation of CIs through an uncertainty approach. The total variance of residuals of AGB was also modeled, aiming at predicting CIs as a function of the quantity of AGB. An analysis of reliability of the equations implemented in the TB&C App indicates that more than 95% (n = 64,000) of the true AGB's fit into the CI outputted by the TB&C App. A comparison with other approaches in the literature shows significant agreement with previous estimates and more conservative estimates where previously-published estimates disagreed with the TB&C App. We cite as advantages of the TB&C App; (i) reliability of the outputs, (ii) a user-friendly layout, (iii) AGB and AGC estimates provided along with robust CIs, and (iv) estimates at the stand and tree levels with consistent totals. A biomass dataset containing information on 64,000 plots is also delivered as supplement of this paper. [ABSTRACT FROM AUTHOR]