On the Complexity of Recognizing Iterated Differences of Polyhedra

The iterated difference of polyhedra $V = P_1 \backslash ( P_2 \backslash (... P_k ) ... )$ has been proposed independently in [Zwie-Aart-Wess92] and [Shon93] as a sufficient condition for $V$ to be exactly computable by a two-layered neural network. An algorithm checking whether $V$ included in $R^d$ is an iterated difference of polyhedra is proposed in [Zwie-Aart-Wess92]. However, this algorithm is not practically usable because it has a high computational complexity and it was only conjectured to stop with a negative answer when applied to a region which is not an iterated difference of polyhedra. This paper sheds some light on the nature of iterated difference of polyhedra. The outcomes are\,: (i) an algorithm which always stops after a small number of iterations, (ii) sufficient conditions for this algorithm to be polynomial and (iii) the proof that an iterated difference of polyhedra can be exactly computed by a two-layered neural network using only essential hyperplanes

Workplace learning from a socio-cultural perspective: creating developmental space during the general practice clerkship

Workplace learning in undergraduate medical education has predominantly been studied from a cognitive perspective, despite its complex contextual characteristics, which influence medical students’ learning experiences in such a way that explanation in terms of knowledge, skills, attitudes and single determinants of instructiveness is unlikely to suffice. There is also a paucity of research which, from a perspective other than the cognitive or descriptive one, investigates student learning in general practice settings, which are often characterised as powerful learning environments. In this study we took a socio-cultural perspective to clarify how students learn during a general practice clerkship and to construct a conceptual framework that captures this type of learning. Our analysis of group interviews with 44 fifth-year undergraduate medical students about their learning experiences in general practice showed that students needed developmental space to be able to learn and develop their professional identity. This space results from the intertwinement of workplace context, personal and professional interactions and emotions such as feeling respected and self-confident. These forces framed students’ participation in patient consultations, conversations with supervisors about consultations and students’ observation of supervisors, thereby determining the opportunities afforded to students to mind their learning. These findings resonate with other conceptual frameworks and learning theories. In order to refine our interpretation, we recommend that further research from a socio-cultural perspective should also explore other aspects of workplace learning in medical education

Production of medium-chain fatty acids and higher alcohols by a synthetic co-culture grown on carbon monoxide or syngas

Synthesis gas, a mixture of CO, H2, and CO2, is a promising renewable feedstock for bio-based production of organic chemicals. Production of medium-chain fatty acids can be performed via chain elongation, utilizing acetate and ethanol as main substrates. Acetate and ethanol are main products of syngas fermentation by acetogens. Therefore, syngas can be indirectly used as a substrate for the chain elongation process.ERC Grant (Project 323009) and the Gravitation Grant (Project 024.002.002) of the Netherlands Ministry of Education, Culture and Science, and the Netherlands Science Foundation (NWO

Evaluation of antimicrobial effectiveness of pimaricin-loaded thermosensitive nanohydrogels in grape juice

Pimaricin-loaded poly(N-isopropylacrylamide) nanohydrogels with and without acrylic acid, were evaluated as food-spoilage inhibitors in a model system and a real food product: grape juice. Pimaricin was proposed as a non-allergenic alternative to sulphites for protecting juices against recontamination. However, pimaricin may degrade under conditions and treatments (heating, acidification, lighting) commonly applied in producing fresh juices. Nanohydrogel encapsulation may be a feasible procedure to avoid pimaricin degradation, improving its antimicrobial activity. Pimaricin-free nanohydrogels did not affect the growth of the indicator yeast either in the food model system or in grape juice. Conversely, pimaricin-loaded nanohydrogels effectively inhibited the growth of the indicator yeast. In some cases, the inhibition was extended even further than using free pimaricin. For instance, in the food model system, pimaricin-loaded nanohydrogels with acrylic acid (NPPNIPA-20AA(5)) prevented the yeast growth for more than 81 h while free pimaricin was only effective for 12 h. Despite pimaricin-loaded nanohydrogels without acrylic acid (NPPNIPA(5)) were able to reduce maximum yeast growth, as in all treatments with pimaricin, the extent of the inhibitory effect was not significantly (p>0.05) different to that achieved with free pimaricin. In grape juice, both free pimaricin and NPPNIPA-20AA(5) treatment completely inhibited the growth of the indicator yeast until the end of the bioassay. However, the latter provided similar inhibition levels using a smaller amount of pimaricin due to PNIPA-20AA(5) protection and its controlled release from the nanohydrogel. Therefore, nanohydrogel encapsulation may help to optimise antifungal treatments and decrease the incidence of food allergies.Funded by grant (MAT 2006-11662-CO3-CO2-C01/MAT 2010-21509-C03-01/EUI 2008-00115) from the “Ministerio de Educación y Ciencia” (Spain). Grant (SFRH/BPD/87910/2012) from the Fundação para a Ciência e Tecnologia (FCT, Portugal). Marie Curie COFUND Postdoctoral Research Fellow

Scale-up of an intensified bioprocess for the expansion of bovine adipose-derived stem cells (bASCs) in stirred tank bioreactors

Cultivated meat is an emerging field, aiming to establish the production of animal tissue for human consumption in an in vitro environment, eliminating the need to raise and slaughter animals for their meat. To realise this, the expansion of primary cells in a bioreactor is needed to achieve the high cell numbers required. The aim of this study was to develop a scalable, microcarrier based, intensified bioprocess for the expansion of bovine adipose-derived stem cells as precursors of fat and muscle tissue. The intensified bioprocess development was carried out initially in spinner flasks of different sizes and then translated to fully controlled litre scale benchtop bioreactors. Bioprocess intensification was achieved by utilising the previously demonstrated bead-to-bead transfer phenomenon and through the combined addition of microcarrier and medium to double the existing surface area and working volume in the bioreactor. Choosing the optimal time point for the additions was critical in enhancing the cell expansion. A significant fold increase of 114.19 ± 1.07 was obtained at the litre scale in the intensified bioprocess compared to the baseline (**p < .005). The quality of the cells was evaluated pre- and post-expansion and the cells were found to maintain their phenotype and differentiation capacity

The genetic architecture of low-temperature adaptation in the wine yeast Saccharomyces cerevisiae

[Background] Low-temperature growth and fermentation of wine yeast can enhance wine aroma and make them highly desirable traits for the industry. Elucidating response to cold in Saccharomyces cerevisiae is, therefore, of paramount importance to select or genetically improve new wine strains. As most enological traits of industrial importance in yeasts, adaptation to low temperature is a polygenic trait regulated by many interacting loci.[Results] In order to unravel the genetic determinants of low-temperature fermentation, we mapped quantitative trait loci (QTLs) by bulk segregant analyses in the F13 offspring of two Saccharomyces cerevisiae industrial strains with divergent performance at low temperature. We detected four genomic regions involved in the adaptation at low temperature, three of them located in the subtelomeric regions (chromosomes XIII, XV and XVI) and one in the chromosome XIV. The QTL analysis revealed that subtelomeric regions play a key role in defining individual variation, which emphasizes the importance of these regions’ adaptive nature.[Conclusions] The reciprocal hemizygosity analysis (RHA), run to validate the genes involved in low-temperature fermentation, showed that genetic variation in mitochondrial proteins, maintenance of correct asymmetry and distribution of phospholipid in the plasma membrane are key determinants of low-temperature adaptation.This work has been financially supported from the Spanish Government through MINECO and FEDER funds (AGL2013-47300-C3-3-R and PCIN-2015-143 grants) and from Generalitat Valenciana through PROMETEOII/2014/042 grant, awarded to JMG. This study has been carried out in the context of the European Project ERA-IB “YeastTempTation” EGR thanks the Spanish government for an FPI grant BES-2011-044498 and MM also thanks the Generalitat Valenciana for a VALi+d ACIF/2015/194 grant. We acknowledge support of the publication fee by the CSIC Open Access Publication Support Initiative through its Unit of Information Resources for Research (URICI).Peer reviewe

Bistability and Bacterial Infections

Bacterial infections occur when the natural host defenses are overwhelmed by invading bacteria. The main component of the host defense is impaired when neutrophil count or function is too low, putting the host at great risk of developing an acute infection. In people with intact immune systems, neutrophil count increases during bacterial infection. However, there are two important clinical cases in which they remain constant: a) in patients with neutropenic-associated conditions, such as those undergoing chemotherapy at the nadir (the minimum clinically observable neutrophil level); b) in ex vivo examination of the patient's neutrophil bactericidal activity. Here we study bacterial population dynamics under fixed neutrophil levels by mathematical modelling. We show that under reasonable biological assumptions, there are only two possible scenarios: 1) Bacterial behavior is monostable: it always converges to a stable equilibrium of bacterial concentration which only depends, in a gradual manner, on the neutrophil level (and not on the initial bacterial level). We call such a behavior type I dynamics. 2) The bacterial dynamics is bistable for some range of neutrophil levels. We call such a behavior type II dynamics. In the bistable case (type II), one equilibrium corresponds to a healthy state whereas the other corresponds to a fulminant bacterial infection. We demonstrate that published data of in vitro Staphylococcus epidermidis bactericidal experiments are inconsistent with both the type I dynamics and the commonly used linear model and are consistent with type II dynamics. We argue that type II dynamics is a plausible mechanism for the development of a fulminant infection

Visualization and Curve-Parameter Estimation Strategies for Efficient Exploration of Phenotype Microarray Kinetics

The Phenotype MicroArray (OmniLog® PM) system is able to simultaneously capture a large number of phenotypes by recording an organism's respiration over time on distinct substrates. This technique targets the object of natural selection itself, the phenotype, whereas previously addressed '-omics' techniques merely study components that finally contribute to it. The recording of respiration over time, however, adds a longitudinal dimension to the data. To optimally exploit this information, it must be extracted from the shapes of the recorded curves and displayed in analogy to conventional growth curves.The free software environment R was explored for both visualizing and fitting of PM respiration curves. Approaches using either a model fit (and commonly applied growth models) or a smoothing spline were evaluated. Their reliability in inferring curve parameters and confidence intervals was compared to the native OmniLog® PM analysis software. We consider the post-processing of the estimated parameters, the optimal classification of curve shapes and the detection of significant differences between them, as well as practically relevant questions such as detecting the impact of cultivation times and the minimum required number of experimental repeats.We provide a comprehensive framework for data visualization and parameter estimation according to user choices. A flexible graphical representation strategy for displaying the results is proposed, including 95% confidence intervals for the estimated parameters. The spline approach is less prone to irregular curve shapes than fitting any of the considered models or using the native PM software for calculating both point estimates and confidence intervals. These can serve as a starting point for the automated post-processing of PM data, providing much more information than the strict dichotomization into positive and negative reactions. Our results form the basis for a freely available R package for the analysis of PM data