Protective effect of N-acetylcysteine on the toxicity of silver nanoparticles:Bioavailability and toxicokinetics in Enchytraeus crypticus

We previously demonstrated that N-acetylcysteine (NAC) could reduce the toxicity of silver (Ag) materials (nanoparticles (NPs) and Ag nitrate) to the soil invertebrate Enchytraeus crypticus (Oligochaeta). It remains however, unclear whether the antitoxic mechanism of NAC was caused by NAC-Ag binding in the soil or inside the organisms. This study aimed at determining the bioavailability of Ag in the soil in a 21-day toxicity test as well as the Ag uptake and elimination kinetics in E. crypticus exposed to AgNPs in LUFA 2.2 standard soil amended with low (100 mg/kg dry soil) and high (600 mg/kg dry soil) NAC concentrations. The addition of NAC to the soil alleviated the toxicity of AgNPs by decreasing the internal Ag concentration of E. crypticus in a dose-dependent manner. Indeed, NAC reduced the binding of Ag to the soil, which probably was due to the formation of soluble but biologically unavailable Ag-cysteine complexes. The reduced Ag uptake in the enchytraeids was explained from an increased elimination at high NAC levels. These findings reinforce the view that metal complexing-compounds like NAC play a key role in the modulation of AgNP toxicity and bioavailability in terrestrial environments. Further, it may inform on the potential of NAC as a remediation solution for Ag or other metal-contaminated soils

Leucine-Rich Diet Modulates the Metabolomic and Proteomic Profile of Skeletal Muscle during Cancer Cachexia

Background: Cancer-cachexia induces a variety of metabolic disorders, including skeletal muscle imbalance. Alternative therapy, as nutritional supplementation with leucine, shows a modulatory effect over tumour damage in vivo and in vitro. Method: Adult rats distributed into Control (C), Walker tumour-bearing (W), control fed a leucine-rich diet (L), and tumour-bearing fed a leucine-rich diet (WL) groups had the gastrocnemius muscle metabolomic and proteomic assays performed in parallel to in vitro assays. Results: W group presented an affected muscle metabolomic and proteomic profile mainly related to energy generation and carbohydrates catabolic processes, but leucine-supplemented group (WL) recovered the energy production. In vitro assay showed that cell proliferation, mitochondria number and oxygen consumption were higher under leucine effect than the tumour influence. Muscle proteomics results showed that the main affected cell component was mitochondria, leading to an impacted energy generation, including impairment in proteins of the tricarboxylic cycle and carbohydrates catabolic processes, which were modulated and improved by leucine treatment. Conclusion: In summary, we showed a beneficial effect of leucine upon mitochondria, providing information about the muscle glycolytic pathways used by this amino acid, where it can be associated with the preservation of morphometric parameters and consequent protection against the effects of cachexia

Butyrate Protects Mice from Clostridium difficile-Induced Colitis through an HIF-1-Dependent Mechanism

Antibiotic-induced dysbiosis is a key factor predisposing intestinal infection by Clostridium difficile. Here, we show that interventions that restore butyrate intestinal levels mitigate clinical and pathological features of C. difficile-induced colitis. Butyrate has no effect on C. difficile colonization or toxin production. However, it attenuates intestinal inflammation and improves intestinal barrier function in infected mice, as shown by reduced intestinal epithelial permeability and bacterial translocation, effects associated with the increased expression of components of intestinal epithelial cell tight junctions. Activation of the transcription factor HIF-1 in intestinal epithelial cells exerts a protective effect in C. difficile-induced colitis, and it is required for butyrate effects. We conclude that butyrate protects intestinal epithelial cells from damage caused by C. difficile toxins via the stabilization of HIF-1, mitigating local inflammatory response and systemic consequences of the infection

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

Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

Funder: European Society of Intensive Care Medicine; doi: http://dx.doi.org/10.13039/501100013347Funder: Flemish Society for Critical Care NursesAbstract: Purpose: Intensive care unit (ICU) patients are particularly susceptible to developing pressure injuries. Epidemiologic data is however unavailable. We aimed to provide an international picture of the extent of pressure injuries and factors associated with ICU-acquired pressure injuries in adult ICU patients. Methods: International 1-day point-prevalence study; follow-up for outcome assessment until hospital discharge (maximum 12 weeks). Factors associated with ICU-acquired pressure injury and hospital mortality were assessed by generalised linear mixed-effects regression analysis. Results: Data from 13,254 patients in 1117 ICUs (90 countries) revealed 6747 pressure injuries; 3997 (59.2%) were ICU-acquired. Overall prevalence was 26.6% (95% confidence interval [CI] 25.9–27.3). ICU-acquired prevalence was 16.2% (95% CI 15.6–16.8). Sacrum (37%) and heels (19.5%) were most affected. Factors independently associated with ICU-acquired pressure injuries were older age, male sex, being underweight, emergency surgery, higher Simplified Acute Physiology Score II, Braden score 3 days, comorbidities (chronic obstructive pulmonary disease, immunodeficiency), organ support (renal replacement, mechanical ventilation on ICU admission), and being in a low or lower-middle income-economy. Gradually increasing associations with mortality were identified for increasing severity of pressure injury: stage I (odds ratio [OR] 1.5; 95% CI 1.2–1.8), stage II (OR 1.6; 95% CI 1.4–1.9), and stage III or worse (OR 2.8; 95% CI 2.3–3.3). Conclusion: Pressure injuries are common in adult ICU patients. ICU-acquired pressure injuries are associated with mainly intrinsic factors and mortality. Optimal care standards, increased awareness, appropriate resource allocation, and further research into optimal prevention are pivotal to tackle this important patient safety threat