ECM-enriched alginate hydrogels for bioartificial pancreas: an ideal niche to improve insulin secretion and diabetic glucose profile

Introduction: The success of a bioartificial pancreas crucially depends on ameliorating encapsulated beta cells survival and function. By mimicking the cellular in vivo niche, the aim of this study was to develop a novel model for beta cells encapsulation capable of establishing an appropriate microenvironment that supports interactions between cells and extracellular matrix (ECM) components. Methods: ECM components (Arg-Gly-Asp, abbreviated as RGD) were chemically incorporated in alginate hydrogels (alginate-RGD). After encapsulation, INS-1E beta cells outcome was analyzed in vitro and after their implantation in an animal model of diabetes. Results: Our alginate-RGD model demonstrated to be a good in vitro niche for supporting beta cells viability, proliferation, and activity, namely by improving the key feature of insulin secretion. RGD peptides promoted cell–matrix interactions, enhanced endogenous ECM components expression, and favored the assembly of individual cells into multicellular spheroids, an essential configuration for proper beta cell functioning. In vivo, our pivotal model for diabetes treatment exhibited an improved glycemic profile of type 2 diabetic rats, where insulin secreted from encapsulated cells was more efficiently used. Conclusions: We were able to successfully introduce a novel valuable function in an old ally in biomedical applications, the alginate. The proposed alginate-RGD model stands out as a promising approach to improve beta cells survival and function, increasing the success of this therapeutic strategy, which might greatly improve the quality of life of an increasing number of diabetic patients worldwide.The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by FCT/MEC through National Funds and co-financed by FEDER through the PT2020 Partnership Agreement under the 4293 Unit I&D, FCT Strategic Project PEst-C/SAU/UI3282/2011-2013 and UID/NEU/04539/2013, FCT in the framework of project UID/BIM/04293/2013, FCT in the framework of project IF/00939/2013/CP1179/CT0001, FCT for Joana Crisóstomo (grant number SFRH/BD/72964/2010), FCT for Sílvia J Bidarra (grant number SFRH/BPD/80571/2011), and FCT and POPH/ESF (EC) for Cristina C Barrias research position FCT Investigator (IF2013)

Simple method for sub-diffraction resolution imaging of cellular structures on standard confocal microscopes by three-photon absorption of quantum dots

This study describes a simple technique that improves a recently developed 3D sub-diffraction imaging method based on three-photon absorption of commercially available quantum dots. The method combines imaging of biological samples via tri-exciton generation in quantum dots with deconvolution and spectral multiplexing, resulting in a novel approach for multi-color imaging of even thick biological samples at a 1.4 to 1.9-fold better spatial resolution. This approach is realized on a conventional confocal microscope equipped with standard continuous-wave lasers. We demonstrate the potential of multi-color tri-exciton imaging of quantum dots combined with deconvolution on viral vesicles in lentivirally transduced cells as well as intermediate filaments in three-dimensional clusters of mouse-derived neural stem cells (neurospheres) and dense microtubuli arrays in myotubes formed by stacks of differentiated C2C12 myoblasts

Experimental bond behaviour of GFRP and masonry bricks under impulsive loading

Fibre Reinforced Polymers have become a popular material for strengthening of masonry structures. The performance of this technique is strongly dependent on the bond between the FRP and the substrate. Understanding the strain rate effect on these materials and strengthening techniques is important for proper design and proper modelling of these systems under impacts or blast loads. This work aims to study the behaviour of the bond between GFRP and brick at different strain rates. A Drop Weight Impact Machine specially developed for pull-off tests (single shear tests) is used with different masses and different heights introducing different deformation rates. The strain rate effect on the failure mode, shear capacity and effective bond length is determined from the experimental results. Empirical relations of dynamic increase factors (DIF) for these materials and techniques are also presented.This work was performed under Project CH-SECURE (PTDC/EMC/120118/2010) funded by the Portuguese Foundation of Science and Technology – FCT. The authors acknowledge the support. The first author also acknowledges the support from his PhD FCT grant with the reference SFRH/BD/45436/2008

Donor Killer Immunoglobulin Receptor Gene Content and Ligand Matching and Outcomes of Pediatric Patients with Juvenile Myelomonocytic Leukemia Following Unrelated Donor Transplantation

Natural killer (NK) cell determinants predict relapse-free survival after allogeneic hematopoietic cell transplantation (HCT) for acute myelogenous leukemia, and previous studies have shown a beneficial graft-versus-leukemia effect in patients with juvenile myelomonocytic leukemia (JMML). However, whether NK cell determinants predict protection against relapse for JMML patients undergoing HCT is unknown. Therefore, we investigated NK cell-related donor and recipient immunogenetics as determinants of HCT outcomes in patients with JMML. Patients with JMML (age 0 to 3 (HR, 0.52; 95% CI, 0.29 to 0.95; P = .032), centromeric A/B score (HR, 0.57; 95% CI, 033 to 0.98; P = .041), and telomeric A/B score (HR, 0.58; 95% CI, 0.34 to 1.00; P = .048). To our knowledge, this is the first study analyzing the association of NK cell determinants and outcomes in JMML HCT recipients. This study identifies potential benefits of donor KIR-B genotypes in reducing aGVHD. Our findings warrant further study of the role of NK cells in enhancing the graft-versus-leukemia effect via recognition of JMML blasts

Simultaneous saccharification and fermentation of hydrothermal pretreated lignocellulosic biomass: evaluation of process performance under multiple stress conditions

Industrial lignocellulosic bioethanol processes are exposed to different environmental stresses (such as inhibitor compounds, high temperature, and high solid loadings). In this study, a systematic approach was followed where the liquid and solid fractions were mixed to evaluate the influence of varied solid loadings, and different percentages of liquor were used as liquid fraction to determine inhibitor effect. Ethanol production by simultaneous saccharification and fermentation (SSF) of hydrothermally pretreated Eucalyptus globulus wood (EGW) was studied under combined diverse stress operating conditions (3038 °C, 6080 g of liquor from hydrothermal treatment or autohydrolysis (containing inhibitor compounds)/100 g of liquid and liquid to solid ratio between 4 and 6.4 g liquid in SSF/g unwashed pretreated EGW) using an industrial Saccharomyces cerevisiae strain supplemented with low-cost byproducts derived from agro-food industry. Evaluation of these variables revealed that the combination of temperature and higher solid loadings was the most significant variable affecting final ethanol concentration and cellulose to ethanol conversion, whereas solid and autohydrolysis liquor loadings had the most significant impact on ethanol productivity. After optimization, an ethanol concentration of 54 g/L (corresponding to 85 % of conversion and 0.51 g/Lh of productivity at 96 h) was obtained at 37 °C using 60 % of autohydrolysis liquor and 16 % solid loading (liquid to solid ratio of 6.4 g/g). The selection of a suitable strain along with nutritional supplementation enabled to produce noticeable ethanol titers in quite restrictive SSF operating conditions, which can reduce operating cost and boost the economic feasibility of lignocellulose-to-ethanol processes.The authors thank the financial support from the Strategic Project of UID/BIO/04469/2013 CEB Unit and A Romaní postdoctoral grant funded by Xunta of Galicia (Plan I2C, 2014)

Predicting progression of mild cognitive impairment to dementia using neuropsychological data: a supervised learning approach using time windows

Background: Predicting progression from a stage of Mild Cognitive Impairment to dementia is a major pursuit in current research. It is broadly accepted that cognition declines with a continuum between MCI and dementia. As such, cohorts of MCI patients are usually heterogeneous, containing patients at different stages of the neurodegenerative process. This hampers the prognostic task. Nevertheless, when learning prognostic models, most studies use the entire cohort of MCI patients regardless of their disease stages. In this paper, we propose a Time Windows approach to predict conversion to dementia, learning with patients stratified using time windows, thus fine-tuning the prognosis regarding the time to conversion. Methods: In the proposed Time Windows approach, we grouped patients based on the clinical information of whether they converted (converter MCI) or remained MCI (stable MCI) within a specific time window. We tested time windows of 2, 3, 4 and 5 years. We developed a prognostic model for each time window using clinical and neuropsychological data and compared this approach with the commonly used in the literature, where all patients are used to learn the models, named as First Last approach. This enables to move from the traditional question "Will a MCI patient convert to dementia somewhere in the future" to the question "Will a MCI patient convert to dementia in a specific time window". Results: The proposed Time Windows approach outperformed the First Last approach. The results showed that we can predict conversion to dementia as early as 5 years before the event with an AUC of 0.88 in the cross-validation set and 0.76 in an independent validation set. Conclusions: Prognostic models using time windows have higher performance when predicting progression from MCI to dementia, when compared to the prognostic approach commonly used in the literature. Furthermore, the proposed Time Windows approach is more relevant from a clinical point of view, predicting conversion within a temporal interval rather than sometime in the future and allowing clinicians to timely adjust treatments and clinical appointments.FCT under the Neuroclinomics2 project [PTDC/EEI-SII/1937/2014, SFRH/BD/95846/2013]; INESC-ID plurianual [UID/CEC/50021/2013]; LASIGE Research Unit [UID/CEC/00408/2013