In order to limit the energy demand of buildings, a possible strategy consists in the storage of thermal energy using phase change materials (PCMs). In this work, an innovative PCM-enhanced plaster, fully formulated by using materials coming from natural resources, was developed. The PCM (i.e., a biodegradable material from agricultural resources having a melting temperature of 23 °C) was shape-stabilized with a direct absorption method by using a proper combination of different inorganic powders, taking into account also the final cost of the product and the processability issues. The most important physical properties of the plaster were then investigated following the European standards and compared with those of a natural hydraulic lime commercial plaster. The optimized PCM-enhanced plaster could be classified as a lightweight plaster (LW class according to UNI EN 1015-10) with compressive strength CSI (UNI EN 1015-11) and water absorption class W2 (UNI EN 1015-18). Differential scanning calorimetry tests confirmed the thermal energy storage capability of the PCM-enhanced plaster, even though plaster processing operations slightly decreased the specific melting enthalpy of the PCM within the plaster. Moreover, small-scale simulations were performed through the monitoring of the inner temperature of an insulated box, in which a plaster layer was applied on the internal walls, during heating and cooling ramps. These tests confirmed the thermal energy storage capability of the newly developed plaster around the PCM melting temperature interval.
The establishment of aging clocks based on DNA methylation highlighted the strong link between epigenetic alterations and aging. However, the connection between DNA methylation changes at clock sites and their effect on cellular function remains unclear. We hypothesize that chromatin accessibility, a readout that integrates many epigenetic mechanisms, may connect epigenetic changes with their downstream effects. Here we generated chromatin accessibility profiles from peripheral blood mononuclear cells of 157 human donors and used them to construct a novel aging clock with a median absolute error on prediction of 5.69 years. Moreover, by comparing our chromatin accessibility data to matched transcriptomic profiles, we show that the genomic sites relevant for chromatin accessibility-based age predictions also undergo transcriptional changes during aging and that chromatin accessibility predicts age better than gene expression. This chromatin accessibility clock could therefore be used to investigate the direct effect of aged epigenetic states on cellular function.
Motivation Recently, several computational modeling approaches, such as agent-based models, have been applied to study the interaction dynamics between immune and tumor cells in human cancer. However, each tumor is characterized by a specific and unique tumor microenvironment, emphasizing the need for specialized and personalized studies of each cancer scenario. Results We present MAST, a hybrid Multi-Agent Spatio-Temporal model which can be informed using a data-driven approach to simulate unique tumor subtypes and tumor-immune dynamics starting from high throughput sequencing data. It captures essential components of the tumor microenvironment by coupling a discrete agent-based model with a continuous partial differential equations-based model. The application to real data of human colorectal cancer tissue investigating the spatio-temporal evolution and emergent properties of four simulated human colorectal cancer subtypes, along with their agreement with current biological knowledge of tumors and clinical outcome endpoints in a patient cohort, endorse the validity of our approach. Availability MAST, implemented in Python language, is freely available with an open-source license through GitLab (https://gitlab.com/sysbiobig/mast), and a Docker image is provided to ease its deployment. Submitted software version and test data are available in Zenodo, at https://dx.doi.org/10.5281/zenodo.7267745. Supplementary information Supplementary data are available at Bioinformatics Advances online.
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