3D Printing of Flexible BaTiO3/Polydimethylsiloxane Piezocomposite with Aligned Particles for Enhanced Energy Harvesting.

With the rapid development of human-machine interactions and artificial intelligence, the demand for wearable electronic devices is increasing uncontrollably all over the world; however, an unsustainable power supply for such sensors continues to restrict their applications. In the present work, piezoelectric barium titanate (BaTiO3) ceramic powder with excellent properties was prepared from milled precursors through a solid-state reaction. To fabricate a flexible device, the as-prepared BaTiO3 powder was mixed with polydimethylsiloxane (PDMS) polymer. The BaTiO3/PDMS ink with excellent rheological properties was extruded smoothly by direct ink writing technology (DIW). BaTiO3 particles were aligned due to the shear stress effect during the printing process. Subsequently, the as-printed composite was assembled into a sandwich-type device for effective energy harvesting. It was observed that the maximum output voltage and current of this device reached 68 V and 720 nA, respectively, for a BaTiO3 content of 6 vol %. Therefore, the material extrusion-based three-dimensional (3D) printing technique can be used to prepare flexible piezoelectric composites for efficient energy harvesting.

Understanding the Impacts of Different Impurities on Elemental Mercury Removal by CaS in Chemical Looping Combustion of Coal: A First Principle Study.

CaSO4 has the advantages of abundant yield, high oxygen-carrying capacity, low cost, and no heavy metal pollution, making it promising as an oxygen carrier for chemical looping combustion (CLC). In comparison with other oxygen carriers, CaS as the reduced product of CaSO4 exhibits superior adsorption efficiency for Hg0 in the flue gas. In this paper, density functional theory (DFT) was used to investigate the adsorption mechanism of Hg0 on the adsorbent surface of CaS(001). The adsorption energies of different oxidized mercury species such as HgS, HgCl, and HgBr over the CaS surface were summarized. Furthermore, the effects of various flue gas components including SO2, H2S, S, HCl, Cl2, CO, H2, H2O, and C on Hg0 adsorption over the CaS(001) surface were evaluated. The results show that Hg0 can be adsorbed on the CaS(001) surface in a chemisorption manner with a reaction energy of -65.1 kJ/mol. The adsorption energy of different forms of mercury on the CaS(001) surface varies greatly, and mercury in the oxidized state is more easily captured by CaS. SO2 inhibits while other flue gas components promote Hg0 adsorption over the CaS surface. Overall, CaS tends to adsorb mercury in the reduction reactor and release mercury when CaS is re-oxidized to CaSO4 in the oxidation reactor. This is detrimental to mercury removal in the CLC of coal. This study sheds light on the migration and transformation of mercury in the CLC of coal with CaSO4 as the oxygen carrier.

Motion-resistant structured illumination microscopy based on principal component analysis.

Structured illumination microscopy (SIM) has become one of the most significant super-resolution techniques in bioscience for observing live-cell dynamics, thanks to fast full-field imaging and low photodamage. However, artifact-free SIM super-resolution reconstruction requires precise knowledge about variable environment-sensitive illumination parameters. Conventional algorithms typically, under the premise of known and reliable constant phase shifts, compensate for residual parameters, which will be easily broken by motion factors such as environment and medium perturbations, and sample offsets. In this Letter, we propose a robust motion-resistant SIM algorithm based on principal component analysis (mrPCA-SIM), which can efficiently compensate for nonuniform pixel shifts and phase errors in each raw illumination image. Experiments demonstrate that mrPCA-SIM achieves more robust imaging quality in complex, unstable conditions compared with conventional methods, promising a more compatible and flexible imaging tool for live cells.

[Single-cell transcriptome analysis of multigrade glioma heterogeneity and immune microenvironment revealed potential prognostic biomarkers].

Glioma, the most common intrinsic tumor of the central nervous system, is characterized by its high incidence and poor prognosis. The aim of this study was to identify differentially expressed genes (DEGs) between glioblastoma multiforme (GBM) and low-grade glioma (LGG) to explore prognostic factors of different grades of gliomas. Single-cell transcriptome sequencing data of gliomas were collected from the NCBI Gene Expression Omnibus (GEO), which included a total of 29 097 cell samples from three datasets. For the analysis of human gliomas of different grades, 21 071 cells were obtained by filtering, and 70 genes were screened from differentially expressed genes by gene ontology (GO) analysis, Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis, from which the gene DLL3 was focused by reviewing the literature. The TCGA-based gene expression profiling interactive analysis (GEPIA) database was used to explore the survival curves of genes in LGG and GBM, and the gene expression profiling interactive analysis and tumor immune estimation resource (TIMER) database was used to study the expression of key genes in gliomas of different grades, predicting biomarkers that were closely related to immunotherapy. The cBioPortal database was used to explore the relationship between DLL3 expression and 25 immune checkpoints. Gene set enrichment analysis (GSEA) further identified pathways associated with central genes. Finally, the efficacy of biomarkers in prognosis and prediction was validated in the Chinese glioma genome atlas (CGGA). These results demonstrated that prognostic genes are associated with tumor proliferation and progression. Analysis of biological information and survival suggested that these genes might serve as a promising prognostic biomarker and as new targets for selecting therapeutic strategies.

[Analysis of progress characteristics of retinoblastoma based on single cell transcriptome sequencing].

Retinoblastoma (RB) is the most common intraocular malignant tumor in infants and young children. The key causative factors in the progression of RB remain unclear. Therefore, identifying genes closely associated with RB progression may provide important clues for disease diagnosis and gene therapy. However, tumor tissues have strong cellular heterogeneity. There may be significant differences in cell function and gene expression among cells in different pathological states. In this study, we downloaded single-cell transcriptome sequencing data of RB tumors and adjacent tissues from the GEO public database. Subsequently, we analyzed RB tumor transcriptional profiles with different disease duration at the single-cell level and identified cell groups and gene sets potentially associated with RB progression. The results showed that the tumor tissue and the adjacent tissues had overall consistency in the single-cell transcriptional map, but there were obvious differences in the distribution proportions of G1 phase cells, G2 phase cells, and microglia cells of cone precursors in RB tumor and the adjacent tissues. Furthermore, the role of three cell populations in the progression of RB tumors was emphatically analyzed. We found that in the early stage of RB tumors, cone precursor cells proliferated abnormally in G1 phase. With the progression of RB tumors, the proportion of cone precursor cells in G2 phase increased significantly. Meanwhile, the results of differential analysis of microglial populations during RB progression showed that the key genes mainly involved in immune response include RPL23, B2M, and HLA superfamily genes. This study provides new perspectives and data resources for the research of RB pathogenesis and progress.

Decoding the Immune Microenvironment of Clear Cell Renal Cell Carcinoma by Single-Cell Profiling to Aid Immunotherapy.

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of kidney cancer, and it is the major cause of kidney cancer death. Understanding tumor immune microenvironments (TMEs) is critical in cancer immunotherapies. Here, we studied the immune characterization at single-cell resolution by integrating public data of ccRCC across different tissue types, and comparing the transcriptome features and tumor TME differences in tumors, normal adjacent tissue, and peripheral blood. A total of 16 different types of cell components of ccRCC were identified. We revealed that there is an overall increase in T-cell and myeloid populations in tumor-infiltrated immune cells compared to normal renal tissue, and the B-cell population in the tumor showed a sharp decrease, which indicates that the cells in tumor tissue undergo strong immune stress. In addition, the cell-cell communication analysis revealed specific or conserved signals in different tissue types, which may aid to uncover the distinct immune response. By combining and analyzing publicly available ccRCC bulk RNA-seq datasets, 10 genes were identified as marker genes in specific cell types, which were significantly associated with poor prognosis. Of note, UBE2C, which may be a good indicator of tumor proliferation, is positively associated with reductions in overall survival and highly associated with tumor grade. Our integrated analysis provides single-cell transcriptomic profiling of ccRCC and their TME, and it unmasked new correlations between gene expression, survival outcomes, and immune cell-type components, enabling us to dissect the dynamic variables in the tumor development process. This resource provides deeper insight into the transcriptome features and immune response of ccRCC and will be helpful in kidney cancer immunotherapy.

Oxygen-Induced Elemental Mercury Oxidation in Chemical Looping Combustion of Coal.

Mercury emission is an important issue during chemical looping combustion (CLC) of coal. The aim of this work is to explore the effects of different flue gas components (e.g., HCl, NO, SO2, and CO2) on mercury transformation in the flue gas cooling process. A two-stage simulation method is used to reveal the reaction mechanism of these gases affecting elemental mercury (Hg0) oxidation. Furthermore, using this method, Hg0 oxidation by eight oxygen carriers (Co3O4, CaSO4, CeO2, Fe2O3, Al2O3, Mn2O3, SiO2, and CuO) commonly used in CLC are investigated and their Hg0 oxidation efficiencies were compared with the existing experimental results. The results show that HCl, NO, and CO2 promote Hg0 oxidation during flue gas cooling, while SO2 inhibits Hg0 oxidation. The stronger the oxygen release capacity of oxygen carriers, the higher the oxidation efficiency of Hg0 becomes. The order of Hg0 removal efficiency from high to low is Co3O4, CuO, Mn2O3, CaSO4, Fe2O3, CeO2, Al2O3, and SiO2, and this sequence is in good agreement with the existing experimental results. Different flue gas components directly or indirectly affect the O2 content, thus affecting the content of gaseous oxidized mercury (Hg2+). Different oxygen carriers have different oxygen release capacities and different Hg0 oxidation efficiencies. Therefore, O2 is the core species affecting the mercury transformation in CLC.