The Role of Local Inflammation and Hypoxia in the Formation of Hypertrophic Scars—A New Model in the Duroc Pig

Hypertrophic scars continue to be a major burden, especially after burns. Persistent inflammation during wound healing appears to be the precipitating aspect in pathologic scarring. The lack of a standardized model hinders research from fully elucidating pathophysiology and therapy, as most therapeutic approaches have sparse evidence. The goal of this project was to investigate the mechanisms of scar formation after prolonged wound inflammation and to introduce a method for generating standardized hypertrophic scars by inducing prolonged inflammation. Four wound types were created in Duroc pigs: full-thickness wounds, burn wounds, and both of them with induced hyperinflammation by resiquimod. Clinical assessment (Vancouver Scar Scale), tissue oxygenation by hyperspectral imaging, histologic assessment, and gene expression analysis were performed at various time points during the following five months. Native burn wounds as well as resiquimod-induced full-thickness and burn wounds resulted in more hypertrophic scars than full-thickness wounds. The scar scale showed significantly higher scores in burn- and resiquimod-induced wounds compared with full-thickness wounds as of day 77. These three wound types also showed relative hypoxia compared with uninduced full-thickness wounds in hyperspectral imaging and increased expression of HIF1a levels. The highest number of inflammatory cells was detected in resiquimod-induced full-thickness wounds with histologic features of hypertrophic scars in burn and resiquimod-induced wounds. Gene expression analysis revealed increased inflammation with only moderately altered fibrosis markers. We successfully created hypertrophic scars in the Duroc pig by using different wound etiologies. Inflammation caused by burns or resiquimod induction led to scars similar to human hypertrophic scars. This model may allow for the further investigation of the exact mechanisms of pathological scars, the role of hypoxia and inflammation, and the testing of therapeutic approaches.     

Serum miR-373-3p and miR-194-5p Are Associated with Early Tumor Progression during FOLFIRINOX Treatment in Pancreatic Cancer Patients: A Prospective Multicenter Study

In this study, we explored the predictive value of serum microRNA (miRNA) expression for early tumor progression during FOLFIRINOX chemotherapy and its association with overall survival (OS) in patients with pancreatic ductal adenocarcinoma (PDAC). A total of 132 PDAC patients of all disease stages were included in this study, of whom 25% showed progressive disease during FOLFIRINOX according to the RECIST criteria. MiRNA expression was analyzed in serum collected before the start and after one cycle of chemotherapy. In the discovery cohort (n = 12), a 352-miRNA RT-qPCR panel was used. In the validation cohorts (total n = 120), miRNA expression was detected using individual RT-qPCR miRNA primers. Before the start of FOLFIRINOX, serum miR-373-3p expression was higher in patients with progressive disease compared to patients with disease control after FOLFIRINOX (Log2 fold difference (FD) 0.88, p = 0.006). MiR-194-5p expression after one cycle of FOLFIRINOX was lower in patients with progressive disease (Log2 FD −0.29, p = 0.044). Both miRNAs were predictors of early tumor progression in a multivariable model including disease stage and baseline CA19-9 level (miR-373-3p odds ratio (OR) 3.99, 95% CI 1.10–14.49; miR-194-5p OR 0.91, 95% CI 0.83–0.99). MiR-373-3p and miR-194-5p did not show an association with OS after adjustment for disease stage, baseline CA19-9, and chemotherapy response. In conclusion, high serum miR-373-3p before the start and low serum miR-194-5p after one cycle are associated with early tumor progression during FOLFIRINOX.     

Detection of toxins involved in foodborne diseases caused by Gram‐positive bacteria

Bacterial toxins are food safety hazards causing about 10% of all reported foodborne outbreaks in Europe. Pertinent to Gram‐positive pathogens, the most relevant toxins are emetic toxin and diarrheal enterotoxins of Bacillus cereus, neurotoxins of Clostridium botulinum, enterotoxin of Clostridium perfringens, and a family of enterotoxins produced by Staphylococcus aureus and some other staphylococci. These toxins are the most important virulence factors of respective foodborne pathogens and a primary cause of the related foodborne diseases. They are proteins or peptides that differ from each other in their size, structure, toxicity, toxicological end points, solubility, and stability, types of food matrix to which they are mostly related to. These differences influence the characteristics of required detection methods. Therefore, detection of these toxins in food samples, or detection of toxin production capacity in the bacterial isolate, remains one of the cornerstones of microbial food analysis and an essential tool in understanding the relevant properties of these toxins. Advanced research has led into new insights of the incidence of toxins, mechanisms of their production, their physicochemical properties, and their toxicological mode of action and dose‐response profile. This review focuses on biological, immunological, mass spectrometry, and molecular assays as the most commonly used detection and quantification methods for toxins of B. cereus, C. botulinum, C. perfringens, and S. aureus. Gathered and analyzed information provides a comprehensive blueprint of the existing knowledge on the principles of these assays, their application in food safety, limits of detection and quantification, matrices in which they are applicable, and type of information they provide to the user.     

Emissionsbewertung von biologischen Abfallbehandlungsanlagen mittels optischer Fernmesstechnik

Measuring greenhouse gas emissions at biological waste treatment facilities, especially methane (CH₄), represents an important precondition for reliably assessing the relevance of these emissions, and for justifying measures to avoid their release. In the context of recording emitted methane loads, sites characterized by large quantities of diffuse emissions are highly problematic, as to date it has been extremely difficult from a technical perspective to measure them with an acceptable degree of accuracy. A micrometeorological method in combination with an optical remote sensing system (open-path Tunable Diode Laser Absorption Spectroscopy—OP-TDLS) is currently being used to address emission-relevant questions concerning landfills and other waste management sites (biogas plants, composting areas at mechanical-biological waste treatment facilities, composting facilities, etc.) at the Institute of Waste Management (Vienna University of Natural Resources and Life Sciences). The potential offered by this method for measuring emissions at composting and anaerobic digestion facilities is illustrated on the basis of two case studies. The method allows large areas to be quickly scanned without affecting gas flows on the surface/at the outlet. The results indicate that the amount of CH₄ released by biogas plants and composting facilities fluctuates considerably in the course of a day. Given the comparatively long measurement periods, it was possible to interpret the emissions from both operational and meteorological perspectives. In comparison with conventional, small-scale measurement methods (e.g. chamber measurements), the optical remote sensing system allowed diffuse and temporary emission sources to be more easily recorded, and over a longer period of time.     

Modifications of paper and paperboard surfaces with a nanostructured polymer coating

Organic nanoparticles synthesized by imidization of styrene-maleic anhydride copolymers are deposited as a top-coating onto paper and paperboard substrates from a stable aqueous dispersion with maximum solid content of 35 wt.%. The morphology, physical characteristics and chemical surface properties of the coatings are discussed in this paper, using scanning electron microscopy, atomic force microscopy, contact angle measurements and Raman spectroscopy. Due to the high glass transition temperature of the polymer nanoparticles, a unique micro- to nanoscale structured coating is formed that favourably improves the gloss, printing properties (ink-jet printing test and off-set printing test), surface hydrophobicity (maximum water contact angle 140°) and water repellence (reduction of Cobb-values). The interaction of the nanoparticle coatings with the cellulosic paper web results in improvement of the mechanical paper strength and is attributed to hydrogen-bonding between the nanoparticles and the cellulosic fibers.     

Simulation of sequential data: An enhanced reinforcement learning approach

The present study aims at contributing to the current state-of-the art of activity-based travel demand modelling by presenting a framework to simulate sequential data. To this end, the suitability of a reinforcement learning approach to reproduce sequential data is explored. Additionally, as traditional reinforcement learning techniques are not capable of learning efficiently in large state and action spaces with respect to memory and computational time requirements on the one hand, and of generalizing based on infrequent visits of all state-action pairs on the other hand, the reinforcement learning technique as used in most applications, is enhanced by means of regression tree function approximation.Three reinforcement learning algorithms are implemented to validate their applicability: the traditional Q-learning and Q-learning with bucket-brigade updating are tested against the improved reinforcement learning approach with a CART function approximator. These methods are applied on data of 26 diary days. The results are promising and show that the proposed techniques offer great opportunity of simulating sequential data. Moreover, the reinforcement learning approach improved by introducing a regression tree function approximator learns a more optimal solution much faster than the two traditional Q-learning approaches.