Skin Tissue Models

Skin Tissue Models provides a translational link for biomedical researchers on the interdisciplinary approaches to skin regeneration. As the skin is the largest organ in the body, engineered substitutes have critical medical application to patients with disease and injury - from burn wounds and surgical scars, to vitiligo, psoriasis and even plastic surgery. This volume offers readers preliminary description of the normal structure and function of mammalian skin, exposure to clinical problems and disease, coverage of potential therapeutic molecules and testing, skin substitutes, models as study platforms of skin biology and emerging technologies. The editors have created a table of contents which frames the relevance of skin tissue models for researchers as platforms to study skin biology and therapeutic approaches for different skin diseases, for clinicians as tissue substitutes, and for cosmetic and pharmaceutical industries as alternative test substrates that can replace animal models. Offers descriptions of the normal structure/function of mammalian skin, exposure to clinical problems, and more Presents coverage of skin diseases (cancer, genodermatoses, vitiligo and psoriasis) that extends to clinical requirements and skin diseases in vitro models Addresses legal requirements and ethical concerns in drugs and cosmetics in vitro testing Edited and authored by internationally renowned group of researchers, presenting the broadest coverage possible. © 2018 Elsevier Inc. All rights reserved.(undefined)info:eu-repo/semantics/publishedVersio

Pre-selection of fibroblasts subsets prompt prevascularization of tissue engineered skin analogues

The papillary and reticular dermis harbors phenotypically distinct fibroblasts, whose functions such as maintenance of skin's microvasculature are also distinct. Thus, we hypothesized that pre-selection of the subpopulations of fibroblasts would benefit the generation of skin tissue engineered (TE) constructs, promoting their prevascularization in vitro. We first isolated papillary and reticular fibroblasts using fluorescence-activated cell sorting and studied the effect of their secretome and extracellular matrix (ECM) on human dermal microvascular endothelial cell (hDMEC) organization. Subsequently, we developed a bilayered 3D polymeric structure with distinct layer-associated features to house the subpopulations of fibroblasts, to generate a skin analogue. Both papillary and reticular fibroblasts were able to stimulate capillary-like network formation in a Matrigel assay. However, the secretome of the two subpopulations was substantially different, being enriched in VEGF, IGF-1, and Angio-1 in the case of papillary fibroblasts and in HGF and FGF-2 for the reticular subset. In addition, the fibroblast subpopulations deposited varied levels of ECM proteins, more collagen I and laminin was produced by the reticular subset, but these differences did not impact hDMEC organization. Vessel-like structures with lumens were observed earlier in the 3D skin analogue prepared with the sorted fibroblasts, although ECM deposition was not affected by the cell's pre-selection. Moreover, a more differentiated epidermal layer was obtained in the skin analogue formed by the sorted fibroblasts, confirming that its whole structure was not affected. Overall, we provide evidence that pre-selection of papillary and reticular fibroblasts is relevant for promoting the in vitro prevascularization of skin TE constructs.The authors would like to acknowledge the financial support from the Consolidator Grant “ECM_INK” (ERC-2016- COG-726061), to the FSE/POCH (Fundo Social Europeu através do Programa Operacional do Capital Humano) under the scope of the PD/169/2013, NORTE-08-5369-FSE-000037 (H.R. M.)

Stem cell-containing hyaluronic acid-based spongy hydrogels for integrated diabetic wound healing

The detailed pathophysiology of diabetic foot ulcers is yet to be established and improved treatments are still required. We propose a strategy that directs inflammation, neovascularization, and neoinnervation of diabetic wounds. Aiming to potentiate a relevant secretome for nerve regeneration, stem cells were precultured in hyaluronic acid-based spongy hydrogels under neurogenic/standard media before transplantation into diabetic mice full-thickness wounds. Acellular spongy hydrogels and empty wounds were used as controls. Reepithelialization was attained 4 weeks after transplantation independently of the test groups, whereas a thicker and more differentiated epidermis was observed for the cellular spongy hydrogels. A switch from the inflammatory to the proliferative phase of wound healing was revealed for all the experimental groups 2 weeks after injury, but a significantly higher M2(CD163 þ )/M1(CD86 þ ) subtype ratio was observed in the neurogenic preconditioned group that also failed to promote neoinnervation. A higher number of intraepidermal nerve fibers were observed for the unconditioned group probably due to a more controlled transition from the inflammatory to the proliferative phase. Overall, stem cell-containing spongy hydrogels represent a promising approach to enhance diabetic wound healing by positively impacting re-epithelialization and by modulating the inflammatory response to promote a successful neoinnervation.The authors would like to acknowledge Gene2Skin Project (H2020-TWINN2015-692221) and Fundac¸a˜o para a Cieˆncia e Tecnologia for SFRH/BD/ 78025/2011 (LPdS), SFRH/BPD/96611/2013 (MTC), SFRH/BPD/101886/2014 (RPP), SFRH/BPD/101952/2014 (TCS) grants. Moreover, the authors would also like to acknowledge Teresa Oliveira for histology support, Andreia Carvalho for hASCs supply, Luca Gasperini for cell profiler analysis, and Manuela E. L. Lago and Carla M. Abreu for intraepidermal nerve fiber quantification.info:eu-repo/semantics/publishedVersio

Age effects on EEG correlates of the Wisconsin card sorting test

Body and brain undergo several changes with aging. One of the domains in which these changes are more remarkable relates with cognitive performance. In the present work, electroencephalogram (EEG) markers (power spectral density and spectral coherence) of age-related cognitive decline were sought whilst the subjects performed the Wisconsin Card Sorting Test (WCST). Considering the expected age-related cognitive deficits, WCST was applied to young, mid-age and elderly participants, and the theta and alpha frequency bands were analyzed. From the results herein presented, higher theta and alpha power were found to be associated with a good performance in the WCST of younger subjects. Additionally, higher theta and alpha coherence were also associated with good performance and were shown to decline with age and a decrease in alpha peak frequency seems to be associated with aging. Additionally, inter-hemispheric long-range coherences and parietal theta power were identified as age-independent EEG correlates of cognitive performance. In summary, these data reveals age-dependent as well as age-independent EEG correlates of cognitive performance that contribute to the understanding of brain aging and related cognitive deficits.The work was partially funded by the European Commission (FP7): “SwitchBox” (Contract HEALTH‐F2‐2010‐259772) and co‐financed by the Portuguese North Regional Operational Program (ON.2 – O Novo Norte) under the National Strategic Reference Framework (QREN), through the European Regional Development Fund (FEDER). This work was also co‐sponsored by FCT – Foundation for Science and Technology and Compete Program with the project reference FCOMP‐01‐0124‐FEDER‐021145 (PTDC/SAU‐ENB/118383/2010) and Agência De Inovação “DoIT ‐ Desenvolvimento e Operacionalização da Investigação de Translação” (project no. 13853, PPS4‐MyHealth), funded by Fundo Europeu de Desenvolvimento Regional (FEDER) through the Programa Operacional Factores de Competitividade (POFC)

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

Design and baseline characteristics of the finerenone in reducing cardiovascular mortality and morbidity in diabetic kidney disease trial

Background: Among people with diabetes, those with kidney disease have exceptionally high rates of cardiovascular (CV) morbidity and mortality and progression of their underlying kidney disease. Finerenone is a novel, nonsteroidal, selective mineralocorticoid receptor antagonist that has shown to reduce albuminuria in type 2 diabetes (T2D) patients with chronic kidney disease (CKD) while revealing only a low risk of hyperkalemia. However, the effect of finerenone on CV and renal outcomes has not yet been investigated in long-term trials. Patients and Methods: The Finerenone in Reducing CV Mortality and Morbidity in Diabetic Kidney Disease (FIGARO-DKD) trial aims to assess the efficacy and safety of finerenone compared to placebo at reducing clinically important CV and renal outcomes in T2D patients with CKD. FIGARO-DKD is a randomized, double-blind, placebo-controlled, parallel-group, event-driven trial running in 47 countries with an expected duration of approximately 6 years. FIGARO-DKD randomized 7,437 patients with an estimated glomerular filtration rate >= 25 mL/min/1.73 m(2) and albuminuria (urinary albumin-to-creatinine ratio >= 30 to <= 5,000 mg/g). The study has at least 90% power to detect a 20% reduction in the risk of the primary outcome (overall two-sided significance level alpha = 0.05), the composite of time to first occurrence of CV death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure. Conclusions: FIGARO-DKD will determine whether an optimally treated cohort of T2D patients with CKD at high risk of CV and renal events will experience cardiorenal benefits with the addition of finerenone to their treatment regimen. Trial Registration: EudraCT number: 2015-000950-39; ClinicalTrials.gov identifier: NCT02545049