Impact of HIV-Associated Conditions on Mortality in People Commencing Anti-Retroviral Therapy in Resource Limited Settings

To identify associations between specific WHO stage 3 and 4 conditions diagnosed after ART initiation and all cause mortality for patients in resource-limited settings (RLS). DESIGN, SETTING: Analysis of routine program data collected prospectively from 25 programs in eight countries between 2002 and 2010

Optical Properties And Antiangiogenic Activity Of A Chalcone Derivate

Chalcones and their derivatives exhibit numerous pharmacological activities such as antibacterial, antifungal, cytotoxic, antinociceptive and anti-inflammatory. Recently, they have been assessed aiming for novel application in nonlinear optics and in the treatment of immune diseases and cancers. In this study, we investigate the optical properties of synthetic chalcona 1E,4E-1-(4-chlorophenyl)-5-(2,6,6-trimethylcyclohexen-1-yl)penta-1,4-dien-3-one (CAB7β) and its antiangiogenic potential using the chorioallantoic membrane (CAM) with the S180 sarcoma cell line. Experimental and theoretical results show intense absorption in the UVA-UVC region, which is associated with a π → π* transition with intramolecular charge transfer from the trimethyl-cyclohexen-1-yl ring to the chlorophenyl ring. Quantum chemical calculations of the first hyperpolarizability, accounting for both solvent and frequency dispersion effects, are in very good concordance with hyper-Rayleigh scattering measurements. In addition, two-photon absorption allowed band centered at 650 nm was observed. Concerning antiangiogenic activity, CAB7β causes a significant reduction in the total number, junctions, length and caliber of blood vessels stimulated by S180 cells reducing the presence of blood vessels, inflammatory cells and others elements related to angiogenic process. It is found that CAB7β is a versatile compound and a promising candidate for linear and nonlinear optical applications, in therapy against sarcoma and phototherapy

Association of BMI Category Change with TB Treatment Mortality in HIV-Positive Smear-Negative and Extrapulmonary TB Patients in Myanmar and Zimbabwe

OBJECTIVE: The HIV epidemic has increased the proportion of patients with smear-negative and extrapulmonary tuberculosis (TB) diagnoses, with related higher rates of poor TB treatment outcomes. Unlike in smear-positive pulmonary TB, no interim markers of TB treatment progress are systematically used to identify individuals most at risk of mortality. The objective of this study was to assess the association of body mass index (BMI) change at 1 month (±15 days) from TB treatment start with mortality among HIV-positive individuals with smear-negative and extrapulmonary TB. METHODS AND FINDINGS: A retrospective cohort study of adult HIV-positive new TB patients in Médecins Sans Frontières (MSF) treatment programmes in Myanmar and Zimbabwe was conducted using Cox proportional hazards regression to estimate the association between BMI category change and mortality. A cohort of 1090 TB patients (605 smear-negative and 485 extrapulmonary) was followed during TB treatment with mortality rate of 28.9 per 100 person-years. In multivariable analyses, remaining severely underweight or moving to a lower BMI category increased mortality (adjusted hazard ratio 4.05, 95% confidence interval 2.77-5.91, p<0.001) compared with remaining in the same or moving to a higher BMI category. CONCLUSIONS: We found a strong association between BMI category change during the first month of TB treatment and mortality. BMI category change could be used to identify individuals most at risk of mortality during TB treatment among smear-negative and extrapulmonary patients

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost