Lamivudine and zidovudine-loaded nanostructures : green chemistry preparation for pediatric oral administration

Here, we report on the development of lipid-based nanostructures containing zidovudine (1 mg/mL) and lamivudine (0.5 mg/mL) for oral administration in the pediatric population, eliminating the use of organic solvents, which is in accordance with green chemistry principles. The formulations were obtained by ultrasonication using monoolein (MN) or phytantriol (PN), which presented narrow size distributions with similar mean particle sizes (~150 nm) determined by laser diffraction. The zeta potential and the pH values of the formulations were around 4.0 mV and 6.0, respectively. MN presented a slightly higher incorporation rate compared to PN. Nanoemulsions were obtained when using monoolein, while cubosomes were obtained when using phytantriol, as confirmed by Small-Angle X-ray Scattering. The formulations enabled drug release control and protection against acid degradation. The drug incorporation was effective and the analyses using an electronic tongue indicated a difference in palatability between the nanotechnological samples in comparison with the drug solutions. In conclusion, PN was considered to have the strongest potential as a novel oral formulation for pediatric HIV treatment

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

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

Cognition and renal function: findings from a Brazilian population

ABSTRACT Introduction: The prevalence of chronic kidney disease (CKD) is increasing, with a potential impact in the risk of acceleration of dementia. The potential association between glomerular filtration rate (eGFR) and cognitive performance was scarcely studied. The aim of this study was to evaluate cognitive performance levels across different degrees of kidney function. Methods: We analyzed 240 outpatients in a nephrology service, classified according to eGFR: Advanced (≤ 30ml/min/1.73m2), Moderate (30,1ml/min/1.73m2 to ≤ 60ml/min/1.73m2), and Mild CKD (> 60ml/min/1.73m2). Word list memory, Semantic fluency, Mental State Mini Exam and Trail Making Test (TMT) were applied to evaluate cognitive performance. In the TMT, lower scores are associated with better cognition. In linear regression, cognitive function was considered as dependent variables while groups based on eGFR were considered explanatory variables. The group with eGFR > 60ml/min was the reference and models were adjusted for confounding factors. Results: In our population (n = 240) 64 patients (26.7%) were classified as having advanced, 98(40,8%) moderate, and 78(32,5%) mild. There was no statistical difference among them in MMSE or in the verbal fluency test. However, comparing to mild, patients with advanced CKD presented significantly worse cognitive performance measured by TMTA [50,8s ± 31.1s versus 66,6s ± 35,7s (p = 0.016)] and TMTB [92,7s ± 46,2s versus 162,4s ± 35,7s (p < 0.001)]. Significantly lower TMTB scores (CI95%) 33,0s (4,5-61,6s) were observed in patients with mild compared to advanced CKD in the multivariate analysis adjusting for age, education, sex, diabetes, and alcohol use. Conclusion: Advanced CKD is independently associated with poorer cognitive performance measured by an executive performance test compared to mild CKD

Creatinine clearance predicts longitudinal phosphate levels irrespective of achieved area Kt/V: A peritoneal dialysis-MONDO analysis

Serum phosphate (PO4) is associated with worse outcomes among kidney failure patients, and its dialysis clearance is not well predicted by small solute kinetics. Guidelines in peritoneal dialysis (PD) recommend using urea Kt/V over creatinine clearance (CrCl) to monitor dialysis adequacy. We hypothesize that this recommendation may lead to suboptimal PO4 control. We designed this study to evaluate if CrCl predicts longitudinal PO4 irrespective of achieved Kt/V

Creatinine clearance predicts longitudinal phosphate levels irrespective of achieved area Kt/V: A peritoneal dialysis-MONDO analysis

Serum phosphate (PO4) is associated with worse outcomes among kidney failure patients, and its dialysis clearance is not well predicted by small solute kinetics. Guidelines in peritoneal dialysis (PD) recommend using urea Kt/V over creatinine clearance (CrCl) to monitor dialysis adequacy. We hypothesize that this recommendation may lead to suboptimal PO4 control. We designed this study to evaluate if CrCl predicts longitudinal PO4 irrespective of achieved Kt/V

Serum biomarkers of iron stores are associated with worse physical health-related quality of life in nondialysis-dependent chronic kidney disease patients with or without anemia

International audienceBACKGROUND: Iron deficiency (ID) is a common condition in nondialysis-dependent chronic kidney disease (NDD-CKD) patients that is associated with poorer clinical outcomes. However, the effect of ID on health-related quality of life (HRQoL) in this population is unknown. We analyzed data from a multinational cohort of NDD-CKD Stages 3-5 patients to test the association between transferrin saturation (TSAT) index and ferritin with HRQoL. METHODS: Patients from Brazil (n = 205), France (n = 2015) and the USA (n = 293) in the Chronic Kidney Disease Outcomes and Practice Patterns Study (CKDopps, 2013-2019) were included. We evaluated the association of TSAT and ferritin (and functional and absolute ID, defined as TSAT ≤20% and ferritin ≥300 or <50 ng/mL) on pre-specified HRQoL measures, including the 36-item Kidney Disease Quality of Life physical component summary (PCS) and mental component summary (MCS) as the primary outcomes. Models were adjusted for confounders including hemoglobin (Hb). RESULTS: TSAT ≤15% and ferritin <50 ng/mL and ≥300 ng/mL were associated with worse PCS scores, but not with MCS. Patients with composite TSAT ≤20% and ferritin <50 or ≥300 ng/mL had lower functional status and worse PCS scores than those with a TSAT of 20-30% and ferritin 50-299 ng/mL. Patients with a lower TSAT were less likely to perform intense physical activity. Adjustment for Hb only slightly attenuated the observed effects. CONCLUSIONS: Low TSAT levels, as well as both low TSAT with low ferritin and low TSAT with high ferritin, are associated with worse physical HRQoL in NDD-CKD patients, even after accounting for Hb level. Interventional studies of iron therapy on HRQoL among NDD-CKD individuals are needed to confirm these findings