Low Dielectric Constant Photocurable Fluorinated Poly (Phthalazinone Ether) Ink with Excellent Mechanical Properties and Heat Resistance.

The photosensitive resins for 3D printing technology have been widely applied throughout the advanced communication field due to their merits of high molding accuracy and fast processing speed. Regardless, they, in particular, should have better mechanical properties, heat resistance, and dielectric properties. Herein, photocurable fluorinated poly (phthalazinone ether) (FSt-FPPE) was utilized as a prepolymer to improve the performance of photosensitive resin. A series of UV-curable inks named FST/DPGs were prepared with FSt-FPPE and acrylic diluents of different mass fractions. The FST/DPGs were cured into films by UV curing and post-treatment. After curing, their properties were characterized in detail. In terms of heat resistance, glass transition temperature (Tg) could reach 233 °C and the 5% thermal decomposition temperature (Td5%) was 371 °C. The tensile strength surprisingly reached 61.5 MPa, and the dielectric constant (Dk) could be significantly reduced to 2.75. Additionally, FST/DPGs were successfully employed in UV-assisted direct writing (DIW) to print 3D objects that benefited from their commendable fluidity and rapid curing speed. A stiff cylinder sample with a smooth surface and distinct pattern was ultimately obtained, indicating their remarkable 3D printing adaptation. Such photosensitive resin for UV-assisted DIW exhibits tremendous potential in the electronic industry.

The Emerging Role of Extracellular Vesicles from Mesenchymal Stem Cells and Macrophages in Pulmonary Fibrosis: Insights into miRNA Delivery.

Pulmonary fibrosis is a type of chronic, progressive, fibrotic lung disease of unclear cause with few treatment options. Cell therapy is emerging as a promising novel modality for facilitating lung repair. Mesenchymal stem cell (MSC)-based and macrophage-based cell therapies are regarded as promising strategies to promote lung repair, due to incredible regenerative potential and typical immunomodulatory function, respectively. Extracellular vesicles (EVs), including exosomes and microvesicles, are cell-derived lipid-bilayer membrane vesicles that are secreted from virtually every cell and are involved in intercellular communication by delivering expansive biological cargos to recipients. This review provides a deep insight into the recent research progress concerning the effects of MSC and macrophage-associated EVs on the pathogenesis of pulmonary fibrosis. In addition to discussing their respective vital roles, we summarize the importance of cross-talk, as macrophages are vital for MSCs to exert their protective effects through two major patterns, including attenuating macrophage activation and M1 phenotype macrophage polarization. Moreover, miRNAs are selectively enriched into EVs as essential components, and consideration is given to the particular effects of EV-associated miRNAs.

Varied clinical significance of ATP-binding cassette C sub-family members for lung adenocarcinoma.

ABSTRACT: Lung adenocarcinoma (LUAD) is a lethal malignancy worldwide and a major public health concern. We explored the potential clinical significance for LUAD of ATP-binding cassette (ABC), sub-family C, consisting of ABCC1-6, 8-12, and cystic fibrosis transmembrane conductance regulator (CFTR).Five hundred LUAD patients from The Cancer Genome Atlas database were used for analysis, including differential expression and diagnostic and prognostic significance. Oncomine and MERAV databases were used to validate differential expression and diagnostic significance. A risk score model was constructed using prognosis-related ABCC members. Prognosis-related genes were further explored to correlate their expression with tumor stage progression. Interaction networks, including biological processes and metabolic pathways, were constructed using Cytoscape software and STRING website.ABCC1-3 consistently showed high expression in tumor tissues (all P ≤ 0.05). Most datasets indicated that ABCC5, 10, and 11 were highly expressed in tumor tissues whereas ABCC6, 9, and CFTR were highly expressed in nontumor tissues (all P ≤ 0.05). Diagnostic significance of ABCC3 and ABCC5 was consistently assessed and validated in three datasets (all area under the curve > 0.700) whereas ABCC6, 8, 10, 11, and CFTR were assessed in The Cancer Genome Atlas dataset and validated in one dataset (all area under the curve > 0.700). Prognostic analysis indicated that ABCC2, 6, and 8 mRNA expression was associated with survival of LUAD (all adjusted P ≤ .037). The risk score model constructed using ABCC2, 6, and 8 suggested prognostic significance for survival predictions. ABCC2 expression was associated with tumor stage, whereas ABCC6 and 8 were not. Interaction networks indicated that they were involved in establishment of localization, ion transport, plasma membrane, apical plasma membrane, adenylyl nucleotide binding, ABC transporters, ABC transporter disorders, ABC-family-protein-mediated transport, and bile secretion.Differentially expressed ABCC2 and ABCC5 might be diagnostic whereas ABCC2, 6, and 8 may be prognostic biomarkers for LUAD, possibly through ABC-family-mediated transporter disorders.

In situ soil moisture and temperature network in genhe watershed and saihanba area in China.

The dataset presented in this article is related to the work "Evaluation and Analysis of SMAP, AMSR2, and MEaSUREs Freeze/Thaw Products in China [1]". Soil moisture and temperature are important variables of land-atmosphere energy exchange, monitoring vegetation growth, predicting drought disasters and climate and hydrological modelling [2], [3], [4], [5], [6]. This work provides detailed information on in situ soil moisture and temperature data network established in the Genhe watershed and Saihanba area in China, respectively. The Genhe watershed represents the complex surface heterogeneity in Northeast China. Therefore, data from 22 in situ sites were established in the Genhe watershed since March 2016 to improve the dynamic analysis and modeling of remotely sensed information for complex land surfaces. Saihanba is currently China's largest manmade forest and has a unique alpine wetland and a complete aquatic ecosystem. There are 29 in situ sites deployed in Saihanba since August 2018 for studying the cold temperate continental monsoon climate and estimating forest carbon storage capacity and carbon emissions from manmade forests. Soil temperature and permittivity data in the network were measured using ECH2O EC-5TM probes (Decagon Devices, Inc., Washington, USA, https://www.metergroup.com/) and XingShiTu (XST) probes (BEIJING XST Co., Ltd., www.xingshitu.com) every 30 min at depths of 3, 5, and 10 cm for the Genhe watershed continuous automatic observation network, and depths of 5 and 10 cm for the Saihanba continuous automatic observation network. In the Genhe watershed, soil moisture and soil temperature data in the network were automatically collected using the EM50 data collection system. The Saihanba area has the XST data collection system to record soil temperature and permittivity. The permittivity data collected with the XST data collector were transformed to soil moisture data (volumetric water content) based on the formula developed by [7]. The datasets of the Genhe watershed and Saihanba area consist of raw data acquired by the data collector and processed data of soil moisture and temperature. The Saihanba dataset also includes the calibration data based on soil texture. The result of temporal variations analysis in observed data in the Genhe Watershed and the processing in observed data in the saihanba area show that the long-term in situ soil moisture and temperature datasets can be used for the validation/calibration and improvement of the soil moisture and soil freeze/thaw algorithm.

The Complicate Observations and Multi-Parameter Land Information Constructions on Allied Telemetry Experiment (COMPLICATE).

The Complicate Observations and Multi-Parameter Land Information Constructions on Allied Telemetry Experiment (COMPLICATE) comprises a network of remote sensing experiments designed to enhance the dynamic analysis and modeling of remotely sensed information for complex land surfaces. Two types of experimental campaigns were established under the framework of COMPLICATE. The first was designed for continuous and elaborate experiments. The experimental strategy helps enhance our understanding of the radiative and scattering mechanisms of soil and vegetation and modeling of remotely sensed information for complex land surfaces. To validate the methodologies and models for dynamic analyses of remote sensing for complex land surfaces, the second campaign consisted of simultaneous satellite-borne, airborne, and ground-based experiments. During field campaigns, several continuous and intensive observations were obtained. Measurements were undertaken to answer key scientific issues, as follows: 1) Determine the characteristics of spatial heterogeneity and the radiative and scattering mechanisms of remote sensing on complex land surfaces. 2) Determine the mechanisms of spatial and temporal scale extensions for remote sensing on complex land surfaces. 3) Determine synergist inversion mechanisms for soil and vegetation parameters using multi-mode remote sensing on complex land surfaces. Here, we introduce the background, the objectives, the experimental designs, the observations and measurements, and the overall advances of COMPLICATE. As a result of the implementation of COMLICATE and for the next several years, we expect to contribute to quantitative remote sensing science and Earth observation techniques.

[Modeling of CO2 fluxes at cropland by using SiB3 model].

The aim is to study the influence of different vegetation types on CO2 fluxes at the same site, taking farmland as the object by using the simple biosphere model (SiB3) , select different vegetation types in Suzhou Dongshan site as input parameters of model to simulate CO2 fluxes, and compare with the observational data in Suzhou Dongshan site during 2011-04-16 to 2011-06-30. Results show that using corn as the site vegetation type input model to simulate CO2 fluxes showed a very good diurnal variation agreement compared to the measured data, but selecting the ordinary crop type input model to simulate CO2 fluxes, CO2 fluxes during the daytime in April and May were undervalued, and CO2 fluxes in June were overvalued; when we select the tea type to input the model, the simulated results significantly overestimated CO2 fluxes during the daytime in May and June. In addition, when using SiB3 model to simulate the daily CO2 fluxes, all three vegetation types input model can effectively simulate daily CO2 fluxes, but not significantly. It shows that choosing the right type vegetation input SiB3 model can effectively simulate the diurnal variation of CO2 fluxes, but can not effectively improve the daily CO2 fluxes simulation.

[Study of the microwave emissivity characteristics over different land cover types].

The microwave emissivity over land is very important for describing the characteristics of the lands, and it is also a key factor for retrieving the parameters of land and atmosphere. Different land covers have their emission behavior as a function of structure, water content, and surface roughness. In the present study the global land surface emissivities were calculated using six month (June, 2003-August, 2003, Dec, 2003-Feb, 2004) AMSR-E L2A brightness temperature, MODIS land surface temperature and the layered atmosphere temperature, and humidity and pressure profiles data retrieved from MODIS/Aqua under clear sky conditions. With the information of IGBP land cover types, "pure" pixels were used, which are defined when the fraction cover of each land type is larger than 85%. Then, the emissivity of sixteen land covers at different frequencies, polarization and their seasonal variation were analyzed respectively. The results show that the emissivity of vegetation including forests, grasslands and croplands is higher than that over bare soil, and the polarization difference of vegetation is smaller than that of bare soil. In summer, the emissivity of vegetation is relatively stable because it is in bloom, therefore the authors can use it as its emissivity in our microwave emissivity database over different land cover types. Furthermore, snow cover can heavily impact the change in land cover emissivity, especially in winter.