Hyaluronidase recruits mesenchymal-like cells to the lung and ameliorates fibrosis

Hyaluronidases (HYALs) comprise a group of enzymes that degrade hyaluronic acid (HA). In this report, we reveal that a single intranasal inoculation of HYAL induces an increase in mononuclear cells within the bronchoalveolar space demonstrating a mesenchymal-like phenotype, expressing stem cell antigen-1 (SCA-1), CD44 and CD73 but not CD34, CD45, CD3, CD4, CD8 or CD19. This influx of mesenchymal stem cell (MSC)-like cells was dependent on leukotriene production within the lung parenchyma. These findings prompted experiments demonstrating that HYAL treatment potently blocked bleomycin-induced lung injury and fibrosis while decreasing transforming growth factor (TGF)-β production and collagen deposition. These data suggest that HYAL is a novel and promising tool to use autologous MSC-like cells in the treatment of pulmonary fibrosis

Understanding Interorganizational Learning Based on Social Spaces and Learning Episodes

Different organizational settings have been gaining ground in the world economy, resulting in a proliferation of different forms of strategic alliances that translate into a growth in the number of organizations that have started to deal with interorganizational relationships with different actors. These circumstances reinforce Crossan, Lane, White and Djurfeldt (1995) and Crossan, Mauer and White (2011) in exploring what authors refer to as the fourth, interorganizational, level of learning. These authors, amongst others, suggest that the process of interorganizational learning (IOL) warrants investigation, as its scope of analysis needs widening and deepening. Therefore, this theoretical essay is an attempt to understand IOL as a dynamic process found in interorganizational cooperative relationships that can take place in different structured and unstructured social spaces and that can generate learning episodes. According to this view, IOL is understood as part of an organizational learning continuum and is analyzed within the framework of practical rationality in an approach that is less cognitive and more social-behavioral

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

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

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

Topical application of HYAL accelerates wound closure in full-thickness excisional wounds.

<p>(A) Representative photographs taken from the 150 mm diameter full-thickness wounds of the Wistar rats. Macroscopic changes in skin wound sites induced by topical application of vehicle, HYAL 16 U and HYAL 32 U at day 0 (picture taken immediately after injury) 2, 5, 7, 10, 14 and day 21 are shown. (B) Rate of wound closure induced by topical application of vehicle (control group), HYAL 16 U and HYAL 32 U at day 2, 5, 7, 10, 14 and day 21 are given. Data are expressed as percentage of reduction area from the original wound size (day zero). Values are mean ± SEM (n = 8 to 16 wounds/group), *<i>P</i><0.05, **<i>P</i><0.01, ***<i>P</i><0.001 compared to control group by two-way-ANOVA.</p