Evaluation of Morphological, Biological and Chemical Properties for Breeding on New Fodder-Grass Cultivars

Our work is an attempt to emphasize the importance of grass morphological, biological and chemical properties in the process of development of new forage cultivars. Results of our investigations indicate that there are realistic possibilities of developing grass cultivars with improved nutritive properties. However, breeding works can only be effective if a wide range of different properties can be taken into consideration and if, simultaneously, mutual correlations occurring between them are also considered. High mutability of properties revealed by lower taxonomic units of the species observed in Poland indicates that they can constitute a valuable material for breeding work on forage cultivars

A Self-Organized ECM-Mimetic Model Based on an Amphiphilic Multiblock Silk-Elastin-Like co-Recombinamer with a Concomitant Dual Physical Gelation Process

Although significant progress has been made in the area of injectable hydrogels for biomedical applications and model cell niches, further improvements are still needed, especially in terms of mechanical performance, stability, and biomimicry of the native fibrillar architecture found in the extracellular matrix (ECM). This work focuses on the design and production of a silk-elastin-based injectable multiblock corecombinamer that spontaneously forms a stable physical nanofibrillar hydrogel under physiological conditions. That differs from previously reported silk-elastin-like polymers on a major content and predominance of the elastin-like part, as well as a more complex structure and behavior of such a part of the molecule, which is aimed to obtain well-defined hydrogels. Rheological and DSC experiments showed that this system displays a coordinated and concomitant dual gelation mechanism. In a first stage, a rapid, thermally driven gelation of the corecombinamer solution takes place once the system reaches body temperature due to the thermal responsiveness of the elastin-like (EL) parts and the amphiphilic multiblock design of the corecombinamer. A bridged micellar structure is the dominant microscopic feature of this stage, as demonstrated by AFM and TEM. Completion of the initial stage triggers the second, which is comprised of a stabilization, reinforcement, and microstructuring of the gel. FTIR analysis shows that these events involve the formation of β-sheets around the silk motifs. The emergence of such β-sheet structures leads to the spontaneous self-organization of the gel into the final fibrous structure. Despite the absence of biological cues, here we set the basis of the minimal structure that is able to display such a set of physical properties and undergo microscopic transformation from a solution to a fibrous hydrogel. The results point to the potential of this system as a basis for the development of injectable fibrillar biomaterial platforms toward a fully functional, biomimetic, artificial extracellular matrix, and cell niches.Este trabajo forma parte de Proyectos de Investigación financiados por la Comisión Europea a través del Fondo Europeo de Desarrollo Regional (ERDF), por el del MINECO (MAT2013-41723-R, MAT2013- 42473-R, PRI-PIBAR-2011-1403 y MAT2012-38043), la Junta de Castilla y León (VA049A11, VA152A12 y VA155A12) y el Instituto de Salud Carlos III bajo el Centro en Red de Medicina Regenerativa y Terapia Celular de Castilla y León

Prediction of overall survival for patients with metastatic castration-resistant prostate cancer : development of a prognostic model through a crowdsourced challenge with open clinical trial data

Background Improvements to prognostic models in metastatic castration-resistant prostate cancer have the potential to augment clinical trial design and guide treatment strategies. In partnership with Project Data Sphere, a not-for-profit initiative allowing data from cancer clinical trials to be shared broadly with researchers, we designed an open-data, crowdsourced, DREAM (Dialogue for Reverse Engineering Assessments and Methods) challenge to not only identify a better prognostic model for prediction of survival in patients with metastatic castration-resistant prostate cancer but also engage a community of international data scientists to study this disease. Methods Data from the comparator arms of four phase 3 clinical trials in first-line metastatic castration-resistant prostate cancer were obtained from Project Data Sphere, comprising 476 patients treated with docetaxel and prednisone from the ASCENT2 trial, 526 patients treated with docetaxel, prednisone, and placebo in the MAINSAIL trial, 598 patients treated with docetaxel, prednisone or prednisolone, and placebo in the VENICE trial, and 470 patients treated with docetaxel and placebo in the ENTHUSE 33 trial. Datasets consisting of more than 150 clinical variables were curated centrally, including demographics, laboratory values, medical history, lesion sites, and previous treatments. Data from ASCENT2, MAINSAIL, and VENICE were released publicly to be used as training data to predict the outcome of interest-namely, overall survival. Clinical data were also released for ENTHUSE 33, but data for outcome variables (overall survival and event status) were hidden from the challenge participants so that ENTHUSE 33 could be used for independent validation. Methods were evaluated using the integrated time-dependent area under the curve (iAUC). The reference model, based on eight clinical variables and a penalised Cox proportional-hazards model, was used to compare method performance. Further validation was done using data from a fifth trial-ENTHUSE M1-in which 266 patients with metastatic castration-resistant prostate cancer were treated with placebo alone. Findings 50 independent methods were developed to predict overall survival and were evaluated through the DREAM challenge. The top performer was based on an ensemble of penalised Cox regression models (ePCR), which uniquely identified predictive interaction effects with immune biomarkers and markers of hepatic and renal function. Overall, ePCR outperformed all other methods (iAUC 0.791; Bayes factor >5) and surpassed the reference model (iAUC 0.743; Bayes factor >20). Both the ePCR model and reference models stratified patients in the ENTHUSE 33 trial into high-risk and low-risk groups with significantly different overall survival (ePCR: hazard ratio 3.32, 95% CI 2.39-4.62, p Interpretation Novel prognostic factors were delineated, and the assessment of 50 methods developed by independent international teams establishes a benchmark for development of methods in the future. The results of this effort show that data-sharing, when combined with a crowdsourced challenge, is a robust and powerful framework to develop new prognostic models in advanced prostate cancer.Peer reviewe

Stratification of amyotrophic lateral sclerosis patients: a crowdsourcing approach

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease where substantial heterogeneity in clinical presentation urgently requires a better stratification of patients for the development of drug trials and clinical care. In this study we explored stratification through a crowdsourcing approach, the DREAM Prize4Life ALS Stratification Challenge. Using data from > 10,000 patients from ALS clinical trials and 1479 patients from community-based patient registers, more than 30 teams developed new approaches for machine learning and clustering, outperforming the best current predictions of disease outcome. We propose a new method to integrate and analyze patient clusters across methods, showing a clear pattern of consistent and clinically relevant sub-groups of patients that also enabled the reliable classification of new patients. Our analyses reveal novel insights in ALS and describe for the first time the potential of a crowdsourcing to uncover hidden patient sub-populations, and to accelerate disease understanding and therapeutic development

Investigations on seed retention strength in spikelets of Lolium multiflorum

Investigations were carried out in 2008–2009 to assess the seed retention strength in spikelets of various Lolium multiflorum genotypes depending on their growth stages. The cultivars (Turtetra and Mitos), breeding strains (SZD 1021, SZD 1022, SZD 1023, SZD 216 and SZD 228) and ecotypes were used. With the aid of a special testing machine, retention strength of successive flowers/kernels in spikelets as well as strength required to rachilla breaking of selected spikelets were determined. It was found that the examined Lolium multiflorum genotypes were characterised by specificity regarding seed retention strength in spikelets. This biological feature was smaller for top flowers/kernels and increased with the movement down the spikelet. It was found that in the examined genotypes of Italian ryegrass the seed retention strength in spikelets in the analysed consecutive growth stages was smallest in spikelets situated in the upper part of the inflorescence and the highest in the lower part