Thermal Transport and Physical Characteristics of Silver-Reinforced Biodegradable Nanolubricant

In this investigation, the thermal transport behavior of biodegradable lubricant reinforced with silver nanostructures (AgNs) at various filler fractions of 0.01, 0.05, 0.10, and 0.20 weight percent was evaluated over a temperature scan analysis, ranging from room temperature up to 60 °C. The experimental results revealed significant gradual enhancements in thermal conductivity as AgNs concentration and evaluating temperatures were increased. These improvements showed the important role of nanostructures’ interaction within the biodegradable lubricant. The thermal conductivity performance improved for nanolubricants ranging from 6.5% at 30 °C and 0.20 wt.% AgNs content up to a maximum 32.2%, which was obtained at 60 °C with 0.20 wt.% AgNs concentration. On the other hand, the thermal stability of reinforced lubricants was assessed through thermogravimetric kinetics analyses. The predictive curves resulting from the analyses indicated that there is an enhancement in both the onset temperature for decomposition and the percentage conversion under isothermal conditions for lubricants reinforced with AgNs. Specifically, the results show that the required temperature to achieve a 5% conversion is 100 °C higher than that calculated for bare lubricant. Moreover, the predictive analyses indicate that there is a delay in the decomposition time at isothermal conditions

Adipose tissue from metabolic syndrome mice induces an aberrant miRNA signature highly relevant in prostate cancer development

Prostate cancer (PCa) remains an important public health concern in Western countries. Metabolic syndrome (MeS) is a cluster of pathophysiological disorders with increasing prevalence in the general population that is a risk factor for PCa. Several studies have determined that a crosstalk between white adipose tissue (WAT) and solid tumors favors cancer aggressiveness. In this work, our main goal was to investigate the interaction between WAT and PCa cells through microRNAs (miRNAs), in MeS mice. We developed a MeS-like disease model using C57BL/6J mice chronically fed with high-fat diet (HFD) that were inoculated with TRAMP-C1 PCa cells. A group of five miRNAs (mmu-miR-221-3p, 27a-3p, 34a-5p, 138-5p, and 146a-5p) were increased in gonadal WAT (gWAT), tumors, and plasma of MeS mice compared to control animals. Three of these five miRNAs were detected in the media from gWAT and TRAMP-C1 cell cocultures, and significantly increased in MeS context. More importantly, hsa-miR-221-3p, 146a-5p, and 27a-3p were increased in bloodstream of PCa patients compared to healthy donors. Using miRNA microarrays, we found that 121 miRNAs were differentially released to the coculture media between HFD-gWAT and tumor cells compared to control diet-gWAT and tumor cells. Target genes for the 66 most deregulated miRNAs were involved in common pathways, mainly related to fatty acid metabolism, ER protein processing, amino acid degradation, PI3K AKT signaling, and PCa. Our findings show for the first time a signature of five miRNAs as important players involved in the interaction between WAT and PCa in MeS mice. Further research will be necessary to track these miRNAs in the interaction between these tissues as well as their role in PCa patients with MeS.Fil: Massillo, Cintia Lorena. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; ArgentinaFil: Duca, Rocío Belén. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; ArgentinaFil: Lacunza, Ezequiel. Universidad Nacional de La Plata. Facultad de Ciencias Médicas. Centro de Investigaciones Inmunológicas Básicas y Aplicadas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; ArgentinaFil: Dalton, Guillermo Nicolás. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; ArgentinaFil: Farré, Paula Lucía. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; ArgentinaFil: Taha, Nicolás. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; ArgentinaFil: Piccioni, Flavia Valeria. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; ArgentinaFil: Scalise, Georgina Daniela. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; ArgentinaFil: Gardner, Kevin. Columbia University; Estados UnidosFil: de Siervi, Adriana. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; Argentin

Neuromatch Academy: a 3-week, online summer school in computational neuroscience

Neuromatch Academy (https://academy.neuromatch.io; (van Viegen et al., 2021)) was designed as an online summer school to cover the basics of computational neuroscience in three weeks. The materials cover dominant and emerging computational neuroscience tools, how they complement one another, and specifically focus on how they can help us to better understand how the brain functions. An original component of the materials is its focus on modeling choices, i.e. how do we choose the right approach, how do we build models, and how can we evaluate models to determine if they provide real (meaningful) insight. This meta-modeling component of the instructional materials asks what questions can be answered by different techniques, and how to apply them meaningfully to get insight about brain function