Patterning of ferroelectric nanodot arrays using a silicon nitride shadow mask

We grew well-ordered arrays of ferroelectric Pb (Zr0.2 Ti0.8) O3 (PZT) nanodots on a SrRu O3 SrTi O3 substrate by pulsed laser deposition. A silicon nitride shadow mask with ordered holes was used for patterning of the PZT arrays. Each dot has a height of ???15 nm and a diameter of ???120 nm with a similar dome shape over a large area. The ferroelectric properties of individual PZT dots were investigated by piezoresponse force microscopy. A single dot could be polarized individually and the polarized state remained unrelaxed to ???20 min.open232

Isolation may select for earlier and higher peak viral load but shorter duration in SARS-CoV-2 evolution

During the COVID-19 pandemic, human behavior change as a result of nonpharmaceutical interventions such as isolation may have induced directional selection for viral evolution. By combining previously published empirical clinical data analysis and multi-level mathematical modeling, we find that the SARS-CoV-2 variants selected for as the virus evolved from the pre-Alpha to the Delta variant had earlier and higher peak in viral load dynamics but a shorter duration of infection. Selection for increased transmissibility shapes the viral load dynamics, and the isolation measure is likely to be a driver of these evolutionary transitions. In addition, we show that a decreased incubation period and an increased proportion of asymptomatic infection are also positively selected for as SARS-CoV-2 mutated to adapt to human behavior (i.e., Omicron variants). The quantitative information and predictions we present here can guide future responses in the potential arms race between pandemic interventions and viral evolution

SUMO-Specific Protease 2 (SENP2) Is an Important Regulator of Fatty Acid Metabolism in Skeletal Muscle

Small ubiquitin-like modifier (SUMO)-specific proteases (SENPs) that reverse protein modification by SUMO are involved in the control of numerous cellular processes, including transcription, cell division, and cancer development. However, the physiological function of SENPs in energy metabolism remains unclear. Here, we investigated the role of SENP2 in fatty acid metabolism in C2C12 myotubes and in vivo. In C2C12 myotubes, treatment with saturated fatty acids, like palmitate, led to nuclear factor-B-mediated increase in the expression of SENP2. This increase promoted the recruitment of peroxisome proliferator-activated receptor (PPAR) and PPAR, through desumoylation of PPARs, to the promoters of the genes involved in fatty acid oxidation (FAO), such as carnitine-palmitoyl transferase-1 (CPT1b) and long-chain acyl-CoA synthetase 1 (ACSL1). In addition, SENP2 overexpression substantially increased FAO in C2C12 myotubes. Consistent with the cell culture system, muscle-specific SENP2 overexpression led to a marked increase in the mRNA levels of CPT1b and ACSL1 and thereby in FAO in the skeletal muscle, which ultimately alleviated high-fat diet-induced obesity and insulin resistance. Collectively, these data identify SENP2 as an important regulator of fatty acid metabolism in skeletal muscle and further implicate that muscle SENP2 could be a novel therapeutic target for the treatment of obesity-linked metabolic disorders.11116Ysciescopu

Resin tapping in Pinus pinaster: effects on growth and response function to climate

Dendrocronología sobre Pinus pinaster, como la recolección de resina y los factores climáticos han afectado a su crecimiento

ResearchFlow: Understanding the Knowledge Flow between Academia and Industry

Understanding, monitoring, and predicting the flow of knowledge between academia and industry is of critical importance for a variety of stakeholders, including governments, funding bodies, researchers, investors, and companies. To this purpose, we introduce ResearchFlow, an approach that integrates semantic technologies and machine learning to quantifying the diachronic behaviour of research topics across academia and industry. ResearchFlow exploits the novel Academia/Industry DynAmics (AIDA) Knowledge Graph in order to characterize each topic according to the frequency in time of the related i) publications from academia, ii) publications from industry, iii) patents from academia, and iv) patents from industry. This representation is then used to produce several analytics regarding the academia/industry knowledge flow and to forecast the impact of research topics on industry. We applied ResearchFlow to a dataset of 3.5M papers and 2M patents in Computer Science and highlighted several interesting patterns. We found that 89.8% of the topics first emerge in academic publications, which typically precede industrial publications by about 5.6 years and industrial patents by about 6.6 years. However this does not mean that academia always dictates the research agenda. In fact, our analysis also shows that industrial trends tend to influence academia more than academic trends affect industry. We evaluated ResearchFlow on the task of forecasting the impact of research topics on the industrial sector and found that its granular characterization of topics improves significantly the performance with respect to alternative solutions

Modeling lipid accumulation in oleaginous fungi in chemostat cultures. II: Validation of the chemostat model using yeast culture data from literature

A model that predicts cell growth, lipid accumulation and substrate consumption of oleaginous fungi in chemostat cultures (Meeuwse et al. in Bioproc Biosyst Eng. doi:10.1007/s00449-011-0545-8, 2011) was validated using 12 published data sets for chemostat cultures of oleaginous yeasts and one published data set for a poly-hydroxyalkanoate accumulating bacterial species. The model could describe all data sets well with only minor modifications that do not affect the key assumptions, i.e. (1) oleaginous yeasts and fungi give the highest priority to C-source utilization for maintenance, second priority to growth and third priority to lipid accumulation, and (2) oleaginous yeasts and fungi have a growth rate independent maximum specific lipid production rate. The analysis of all data showed that the maximum specific lipid production rate is in most cases very close to the specific production rate of membrane and other functional lipids for cells growing at their maximum specific growth rate. The limiting factor suggested by Ykema et al. (in Biotechnol Bioeng 34:1268–1276, 1989), i.e. the maximum glucose uptake rate, did not give good predictions of the maximum lipid production rate

The molecular dynamic simulation on impact and friction characters of nanofluids with many nanoparticles system

Impact and friction model of nanofluid for molecular dynamics simulation was built which consists of two Cu plates and Cu-Ar nanofluid. The Cu-Ar nanofluid model consisted of eight spherical copper nanoparticles with each particle diameter of 4 nm and argon atoms as base liquid. The Lennard-Jones potential function was adopted to deal with the interactions between atoms. Thus motion states and interaction of nanoparticles at different time through impact and friction process could be obtained and friction mechanism of nanofluids could be analyzed. In the friction process, nanoparticles showed motions of rotation and translation, but effected by the interactions of nanoparticles, the rotation of nanoparticles was trapped during the compression process. In this process, agglomeration of nanoparticles was very apparent, with the pressure increasing, the phenomenon became more prominent. The reunited nanoparticles would provide supporting efforts for the whole channel, and in the meantime reduced the contact between two friction surfaces, therefore, strengthened lubrication and decreased friction. In the condition of overlarge positive pressure, the nanoparticles would be crashed and formed particles on atomic level and strayed in base liquid

A cellular model of memory reconsolidation involves reactivation-induced destabilization and restabilization at the sensorimotor synapse in Aplysia.

The memory reconsolidation hypothesis suggests that a memory trace becomes labile after retrieval and needs to be reconsolidated before it can be stabilized. However, it is unclear from earlier studies whether the same synapses involved in encoding the memory trace are those that are destabilized and restabilized after the synaptic reactivation that accompanies memory retrieval, or whether new and different synapses are recruited. To address this issue, we studied a simple nonassociative form of memory, long-term sensitization of the gill- and siphon-withdrawal reflex in Aplysia, and its cellular analog, long-term facilitation at the sensory-to-motor neuron synapse. We found that after memory retrieval, behavioral long-term sensitization in Aplysia becomes labile via ubiquitin/proteasome-dependent protein degradation and is reconsolidated by means of de novo protein synthesis. In parallel, we found that on the cellular level, long-term facilitation at the sensory-to-motor neuron synapse that mediates long-term sensitization is also destabilized by protein degradation and is restabilized by protein synthesis after synaptic reactivation, a procedure that parallels memory retrieval or retraining evident on the behavioral level. These results provide direct evidence that the same synapses that store the long-term memory trace encoded by changes in the strength of synaptic connections critical for sensitization are disrupted and reconstructed after signal retrieval

IL23 and TGF-ß diminish macrophage associated metastasis in pancreatic carcinoma

Abstract The precise role of tumor associated macrophages remains unclear in pancreatic ductal adenocarcinoma (PDAC) while TGF-ß has an unclear role in metastases formation. In order to understand the role of IL23, an interleukin associated with macrophage polarization, we investigated IL23 in the context of TGF-ß expression in PDAC. We hypothesized that IL23 expression is associated with metastatic development and survival in PDAC. We investigated IL23 and TGF-ß protein expression on resected PDAC patient tumor sections who were divided into short-term (30 months) survivors. Panc-1 cells treated with IL23, TGF-ß, macrophages, or combinations thereof, were orthotopically implanted into NSG mice. Patients in the long-term survivor group had higher IL23 protein expression (P = 0.01). IL23 expression was linearly correlated with TGF-ß expression in patients in the short-term survivor group (P = 0.038). Macrophages induce a higher rate of PDAC metastasis in the mouse model (P = 0.02), which is abrogated by IL23 and TGF-ß treatment (P < 0.001). Macrophages serve a critical role in PDAC tumor growth and metastasis. TGF-ß contributes to a less tumorigenic TME through regulation of macrophages. Macrophages increases PDAC primary tumor growth and metastases formation while combined IL23 and TGF-ß pre-treatment diminishes these processes