Direct Visualization of the Action of Triton X-100 on Giant Vesicles of Erythrocyte Membrane Lipids

The raft hypothesis proposes that microdomains enriched in sphingolipids, cholesterol, and specific proteins are transiently formed to accomplish important cellular tasks. Equivocally, detergent-resistant membranes were initially assumed to be identical to membrane rafts, because of similarities between their compositions. in fact, the impact of detergents in membrane organization is still controversial. Here, we use phase contrast and fluorescence microscopy to observe giant unilamellar vesicles (GUVs) made of erythrocyte membrane lipids (erythro-GUVs) when exposed to the detergent Triton X-100 (TX-100). We clearly show that TX-100 has a restructuring action on biomembranes. Contact with TX-100 readily induces domain formation on the previously homogeneous membrane of erythro-GUVs at physiological and room temperatures. the shape and dynamics of the formed domains point to liquid-ordered/liquid-disordered (Lo/Ld) phase separation, typically found in raft-like ternary lipid mixtures. the Ld domains are then separated from the original vesicle and completely solubilized by TX-100. the insoluble vesicle left, in the Lo phase, represents around 2/3 of the original vesicle surface at room temperature and decreases to almost 1/2 at physiological temperature. This chain of events could be entirely reproduced with biomimetic GUVs of a simple ternary lipid mixture, 2:1:2 POPC/SM/chol (phosphatidylcholine/sphyngonnyelin/cholesterol), showing that this behavior will arise because of fundamental physicochemical properties of simple lipid mixtures. This work provides direct visualization of TX-100-induced domain formation followed by selective (Ld phase) solubilization in a model system with a complex biological lipid composition.Brazilian Research foundationsFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)TNCT-FaxCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Univ Estadual Campinas, Inst Biol, Dept Bioquim, Campinas, SP, BrazilUniversidade Federal de São Paulo, Dept Biofis, São Paulo, BrazilUniversidade Federal de São Paulo, Dept Biofis, São Paulo, BrazilFAPESP: 2009/0904-1FAPESP: 2012/10442-8FAPESP: 2010/18516-5CNPq: 479993/2011-4CNPq: 472054/2011-2Web of Scienc

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

Effect of temperature, different detergents and local anesthetics in the isolation of detergent-resistant membranes from human erythrocytes

Objectives: To investigate the effects of temperature, various detergents and anesthetics on the isolation of detergent-resistant-membranes (DRMs) from human erythrocytes. Design and Methods: DRMs were isolated by ultracentrifugating detergent-treated whole RBCs in sucrose density gradients. Results: After incubation of cells at 37°C with either Triton X-100 or C12E8, it was possible to isolate DRMs with the same cholesterol content as DRMs prepared at 4°C, but with a strongly reduced content of total and of specific DRM marker proteins (stomatin, flotillin-2), indicating that physiological temperature facilitates solubilisation of membrane proteins while maintaining the resistance of cholesterol. Detergents ASB-14, ASB-16 and CHAPS used at the same concentration as Triton X-100 and C12E8 did not allow the isolation of DRMs from erythrocytes at 4°C. No significant changes in cholesterol and total protein contents were found in DRMs isolated from cells previously treated with lidocaine, prilocaine and bupivacaine and extracted by Triton X-100

Solid Lipid Nanoparticles for Dibucaine Sustained Release

Dibucaine (DBC) is among the more potent long-acting local anesthetics (LA), and it is also one of the most toxic. Over the last decades, solid lipid nanoparticles (SLN) have been developed as promising carriers for drug delivery. In this study, SLN formulations were prepared with the aim of prolonging DBC release and reducing its toxicity. To this end, SLN composed of two different lipid matrices and prepared by two different hot-emulsion techniques (high-pressure procedure and sonication) were compared. The colloidal stability of the SLN formulations was tracked in terms of particle size (nm), polydispersity index (PDI), and zeta potential (mV) for 240 days at 4 °C; the DBC encapsulation efficiency was determined by the ultrafiltration/centrifugation method. The formulations were characterized by differential scanning calorimetry (DSC), electron paramagnetic resonance (EPR), and release kinetic experiments. Finally, the in vitro cytotoxicity against 3T3 fibroblast and HaCaT cells was determined, and the in vivo analgesic action was assessed using the tail flick test in rats. Both of the homogenization procedures were found suitable to produce particles in the 200 nm range, with good shelf stability (240 days) and high DBC encapsulation efficiency (~72⁻89%). DSC results disclosed structural information on the nanoparticles, such as the lower crystallinity of the lipid core vs. the bulk lipid. EPR measurements provided evidence of DBC partitioning in both SLNs. In vitro (cytotoxicity) and in vivo (tail flick) experiments revealed that the encapsulation of DBC into nanoparticles reduces its intrinsic cytotoxicity and prolongs the anesthetic effect, respectively. These results show that the SLNs produced are safe and have great potential to extend the applications of dibucaine by enhancing its bioavailability

Venetoclax Shows Low Therapeutic Activity in BCL2-Positive Relapsed/Refractory Peripheral T-Cell Lymphoma: A Phase 2 Study of the Fondazione Italiana Linfomi

Patients with relapsed/refractory (R/R) peripheral T-cell lymphoma (PTCL) have a poor prognosis, with an expected survival of less than 1 year using standard salvage therapies. Recent advances in our understanding of the biology of PTCL have led to identifying B-Cell Lymphoma 2 (BCL2) protein as a potential therapeutic target. BLC2 inhibitor venetoclax was investigated in a prospective phase II trial in patients with BCL2-positive R/R PTCL after at least one previous standard line of treatment (NCT03552692). Venetoclax given alone at a dosage of 800 mg/day resulted in one complete response (CR) and two stable diseases (SDs) among 17 enrolled patients. The majority of patients (88.2%) interrupted the treatment due to disease progression. No relationship with BCL2 expression was documented. At a median follow-up of 8 months, two patients are currently still on treatment (one CR and one SD). No case of tumor lysis syndrome was registered. Therefore, venetoclax monotherapy shows activity in a minority of patients whose biological characteristics have not yet been identified. Clinical Trial Registration: www.clinicaltrials.gov (NCT03552692, EudraCT number 2017-004630-29)