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

Rationale, study design, and analysis plan of the Alveolar Recruitment for ARDS Trial (ART): Study protocol for a randomized controlled trial

Background: Acute respiratory distress syndrome (ARDS) is associated with high in-hospital mortality. Alveolar recruitment followed by ventilation at optimal titrated PEEP may reduce ventilator-induced lung injury and improve oxygenation in patients with ARDS, but the effects on mortality and other clinical outcomes remain unknown. This article reports the rationale, study design, and analysis plan of the Alveolar Recruitment for ARDS Trial (ART). Methods/Design: ART is a pragmatic, multicenter, randomized (concealed), controlled trial, which aims to determine if maximum stepwise alveolar recruitment associated with PEEP titration is able to increase 28-day survival in patients with ARDS compared to conventional treatment (ARDSNet strategy). We will enroll adult patients with ARDS of less than 72 h duration. The intervention group will receive an alveolar recruitment maneuver, with stepwise increases of PEEP achieving 45 cmH(2)O and peak pressure of 60 cmH2O, followed by ventilation with optimal PEEP titrated according to the static compliance of the respiratory system. In the control group, mechanical ventilation will follow a conventional protocol (ARDSNet). In both groups, we will use controlled volume mode with low tidal volumes (4 to 6 mL/kg of predicted body weight) and targeting plateau pressure <= 30 cmH2O. The primary outcome is 28-day survival, and the secondary outcomes are: length of ICU stay; length of hospital stay; pneumothorax requiring chest tube during first 7 days; barotrauma during first 7 days; mechanical ventilation-free days from days 1 to 28; ICU, in-hospital, and 6-month survival. ART is an event-guided trial planned to last until 520 events (deaths within 28 days) are observed. These events allow detection of a hazard ratio of 0.75, with 90% power and two-tailed type I error of 5%. All analysis will follow the intention-to-treat principle. Discussion: If the ART strategy with maximum recruitment and PEEP titration improves 28-day survival, this will represent a notable advance to the care of ARDS patients. Conversely, if the ART strategy is similar or inferior to the current evidence-based strategy (ARDSNet), this should also change current practice as many institutions routinely employ recruitment maneuvers and set PEEP levels according to some titration method.Hospital do Coracao (HCor) as part of the Program 'Hospitais de Excelencia a Servico do SUS (PROADI-SUS)'Brazilian Ministry of Healt

Pupila dilatada fixa (síndrome de Urrets-Zavalia) após ceratoplastia lamelar profunda

A Síndrome de Urrets-Zavalia apresenta achados oculares bem descritos, porém sua fisiopatologia ainda é incerta. A isquemia iriana é o mecanismo proposto mais comum. Descrevemos dois casos submetidos à ceratoplastia lamelar profunda (CLP) realizadas pelo mesmo cirugião que desenvolveram a síndrome. No primeiro caso, a indicação cirúrgica foi para o tratamento de opacidade corneana e, no segundo, para o de ceratocone. No pós-operatório, ambos os pacientes evoluíram com pupila dilatada fixa que não regrediu totalmente apesar do tratamento administrado

Postoperative subconjunctival corticosteroid injection to prevent pterygium recurrence

Purpose: To report the outcome of postoperative subconjunctival injection of triamcinolone in eyes that underwent pterygium surgery and were at risk for recurrence.Methods: Twelve eyes of 11 patients with primary (7 eyes) or recurrent (5 eyes) pterygia underwent excision and conjunctival autografting (4 eyes, 33.3%), an-miotic membrane grafting (6 eyes, 50%), or both (2 eyes, 16.6%). All of these eyes had signs that were considered to be risk factors for recurrence (conjunctival inflammation, hemorrhage, granuloma, and fibrovascular proliferation); accordingly, they also underwent subconjunctival injection of triamcinolone.Results: Among the 11 patients, there were 8 (72.7%) men and 3 (27.3%) women; the mean age was 41 years (range, 20 - 56 years). In 5 (41.7%) eyes, the pterygium was graded as T2 (intermediate) and in 7 (58.3%) eyes was graded as T3 (fleshy). The time between surgery and the first injection ranged from 2 to 5 weeks (mean, 3.4 weeks), and 1 - 3 injections were necessary (mean, 1.7) to achieve the desired effect. After injection, 1 (8.3%) eye developed inflammation, and 2 (16.7%) eyes from another patient developed intraocular hypertension that was controlled with a topical P-blocker. The follow-up after the last injection ranged from 8 to 36 months (mean, 14.5 months); only 1 recurrence (grade 3) occurred during this period.Conclusions: The postoperative use of subconjunctival triamcinclone seems to benefit patients at increased risk of pterygium recurrence. It is relatively safe and is accompanied by few complications, but controlled and prospective studies are necessary to confirm its efficacy.Univ Fed Sao Paulo, Dept Ophthalmol, External Dis & Cornea Serv, BR-04023062 Sao Paulo, BrazilUniv Fed Sao Paulo, Dept Ophthalmol, External Dis & Cornea Serv, BR-04023062 Sao Paulo, BrazilWeb of Scienc

Evaluation of Hemagglutination Activity of Chitosan Nanoparticles Using Human Erythrocytes

Chitosan is a polysaccharide composed of randomly distributed chains of β-(1-4) D-glucosamine and N-acetyl-D-glucosamine. This compound is obtained by partial or total deacetylation of chitin in acidic solution. The chitosan-based hemostatic agents have been gaining much attention in the management of bleeding. The aim of this study was to evaluate in vitro hemagglutination activity of chitosan nanoparticles using human erythrocytes. The preparation of nanoparticles was achieved by ionotropic gelification technique followed by neutralization with NaOH 1 mol/L−1. The hemagglutination activity was performed on a solution of 2% erythrocytes (pH 7.4 on PBS) collected from five healthy volunteers. The hemolysis determination was made by spectrophotometric analysis. Chitosan nanoparticle solutions without NaOH addition changed the reddish colour of the wells into brown, suggesting an oxidative reaction of hemoglobin and possible cell lysis. All neutralized solutions of chitosan nanoparticles presented positive haemagglutination, without any change in reaction color. Chitosan nanoparticles presented hemolytic activity ranging from 186.20 to 223.12%, while neutralized solutions ranged from 2.56 to 72.54%, comparing to distilled water. Results highlight the need for development of new routes of synthesis of chitosan nanoparticles within human physiologic pH