PBAT based composites reinforced with microcrystalline cellulose obtained from softwood almond shells

This study explores the processability, mechanical, and thermal properties of biocompostable composites based on poly (butylene adipate-co-terephthalate) (PBAT) as polymer matrix and microcrystalline cellulose (MCC) derived from softwood almond (Prunus dulcis) shells (as-MCC) as filler at two different weight concentration, i.e., 10 wt% and 20 wt%. The materials were processed by melt mixing and a commercial MCC (c-MCC) was used as filler comparison. The fibrillar shape of as-MCC particles was found to change the rheological behavior of PBAT, particularly at the highest concentration. The melt mixing processing allowed obtaining a uniform dispersion of both kinds of fillers, slightly reducing the L/D ratio of as-MCC fibers. The as-MCC particles led to a higher increase of the elastic modulus of PBAT if compared to the c-MCC counterparts. Both the MCC fillers caused a drastic reduction of the elongation at break, although it was higher than 120% also at the highest filler concentrations. DSC analysis revealed that both MCC fillers poorly affected the matrix crystallinity, although as-MCC induced a slight PBAT crystallinity increase from 8.8% up to 10.9% for PBAT/as-MCC 20%. Therefore, this work demonstrates the great potential of MCC particles derived from almond shells as filler for biocompostable composites fabrication

Phase field approach to optimal packing problems and related Cheeger clusters

In a fixed domain of $\Bbb{R}^N$ we study the asymptotic behaviour of optimal clusters associated to $\alpha$-Cheeger constants and natural energies like the sum or maximum: we prove that, as the parameter $\alpha$ converges to the "critical" value $\Big (\frac{N-1}{N}\Big ) _+$, optimal Cheeger clusters converge to solutions of different packing problems for balls, depending on the energy under consideration. As well, we propose an efficient phase field approach based on a multiphase Gamma convergence result of Modica-Mortola type, in order to compute $\alpha$-Cheeger constants, optimal clusters and, as a consequence of the asymptotic result, optimal packings. Numerical experiments are carried over in two and three space dimensions

Environmental and Agro-Economic Sustainability of Olive Orchards Irrigated with Reclaimed Water under Deficit Irrigation

This study explores the effects of the adoption of reclaimed water (RW) as source of irrigation in conjunction with the application of deficit irrigation strategies in an olive orchard (different genotypes) located within the “Valle dei Margi” farmhouse (Eastern Sicily). Specifically, the RW was obtained in situ by treating the wastewater coming from the farmhouse throughout a treatment wetland system (TW). The effects of RW on crop water status (CWS) was assessed by conducting plant-based measurements (i.e., leaf water potential, Ψ, and leaves relative water content, RWC) and determining satellite-based biophysical indicators. An economical and environmental evaluation of the proposed sustainable irrigation practices was carried out by using the life cycle assessment (LCA) approach.The RW quality showed high variability due to fluctuations in the number of customers at the farmhouse during the Covid-19 pandemic period. However, high removal efficiency of the overall TW was reached even if the RW quality did not always accomplish with the limits of the Italian regulations. A strong impact in the variation of Ψ was observed among the olive orchard under the different water regimes, evidencing how CWS performances are greatly conditioned by the genotype. However, no differences in leaves RWC and in satellite-based biophysical indicators were detected, despite the severe water deficit imposed (i.e., 50% of irrigation water reduction). Finally, the results of the LCA analysis underlined that the use of RW may permit to obtain important gains both in economic and environmental terms, thus representing a valid strategy for the olive cultivation

Proteasome inhibitors in medullary thyroid carcinoma: time to restart with clinical trials?

IntroductionMedullary thyroid cancer (MTC) is a rare thyroid tumour whose management in advanced stages is challenging, despite effective therapeutic options having expanded in recent years. Proteasome inhibitors (PrIn) have shown the ability to improve patient outcomes, including survival and quality of life, in several malignancies, due to their ability to impair cell proliferation and cause apoptosis through the inhibition of the proteasome activity. Consequently, these drugs could represent a useful tool, alone or in combination with other treatments, in MTC patients.Aim of the studyThis review aims to summarize the available in vitro and in vivo data about the role of PrIn in MTC.Materials and methodsWe performed an extensive search for relevant data sources, including full-published articles in international online databases (PubMed, Web of Science, Scopus), preliminary reports in selected international meeting abstract repositories, and short articles published as supplements of international meetings, by using the following terms: medullary thyroid carcinoma, proteasome inhibitors, bortezomib, carfilzomib, ixazomib, delanzomib, marizomib, oprozomib, and MG132. Additionally, we conducted with the same keywords, an in-depth search in registered clinical trials repositories.ResultsOur search revealed in vitro studies in human and murine MTC cell lines, based on the use of PrIns, both alone and in combination with other anticancer drugs, and two pertinent clinical trials.ConclusionWe found a strong discrepancy between the evidence of PrIns effects in preclinical studies, and the scarcity or early interruption of clinical trials. We might speculate that difficulties in enrolling patients, as happens in other rare diseases, may have discouraged trials’ implementation in favor of drugs already approved for MTC. However, given the concrete improvement in the comprehension of the molecular basis of PrIn effects in MTC, new clinical trials with accurate inclusion criteria of enrollment might be warranted, in order to ascertain whether this treatment, alone or in combination with other drugs, could indeed represent an option to enhance the therapeutic response, and to ultimately improve patients’ outcome and survival

Probabilistic evaluation of process model matching techniques

Process model matching refers to the automatic identification of corresponding activities between two process models. It represents the basis for many advanced process model analysis techniques such as the identification of similar process parts or process model search. A central problem is how to evaluate the performance of process model matching techniques. Often, not even humans can agree on a set of correct correspondences. Current evaluation methods, however, require a binary gold standard, which clearly defines which correspondences are correct. The disadvantage of this evaluation method is that it does not take the true complexity of the matching problem into account and does not fairly assess the capabilities of a matching technique. In this paper, we propose a novel evaluation method for process model matching techniques. In particular, we build on the assessment of multiple annotators to define probabilistic notions of precision and recall. We use the dataset and the results of the Process Model Matching Contest 2015 to assess and compare our evaluation method. We found that our probabilistic evaluation method assigns different ranks to the matching techniques from the contest and allows to gain more detailed insights into their performance

CD133 Is a Marker of Bioenergetic Stress in Human Glioma

Mitochondria dysfunction and hypoxic microenvironment are hallmarks of cancer cell biology. Recently, many studies have focused on isolation of brain cancer stem cells using CD133 expression. In this study, we investigated whether CD133 expression is regulated by bioenergetic stresses affecting mitochondrial functions in human glioma cells. First, we determined that hypoxia induced a reversible up-regulation of CD133 expression. Second, mitochondrial dysfunction through pharmacological inhibition of the Electron Transport Chain (ETC) produced an up-regulation of CD133 expression that was inversely correlated with changes in mitochondrial membrane potential. Third, generation of stable glioma cells depleted of mitochondrial DNA showed significant and stable increases in CD133 expression. These glioma cells, termed rho0 or ρ0, are characterized by an exaggerated, uncoupled glycolytic phenotype and by constitutive and stable up-regulation of CD133 through many cell passages. Moreover, these ρ0 cells display the ability to form “tumor spheroids” in serumless medium and are positive for CD133 and the neural progenitor cell marker, nestin. Under differentiating conditions, ρ0 cells expressed multi-lineage properties. Reversibility of CD133 expression was demonstrated by transfering parental mitochondria to ρ0 cells resulting in stable trans-mitochondrial “cybrid” clones. This study provides a novel mechanistic insight about the regulation of CD133 by environmental conditions (hypoxia) and mitochondrial dysfunction (genetic and chemical). Considering these new findings, the concept that CD133 is a marker of brain tumor stem cells may need to be revised