Current understanding and applications of the cold sintering process

In traditional ceramic processing techniques, high sintering temperature is necessary to achieve fully dense microstructures. But it can cause various problems including warpage, overfiring, element evaporation, and polymorphic transformation. To overcome these drawbacks, a novel processing technique called “cold sintering process (CSP)” has been explored by Randall et al. CSP enables densification of ceramics at ultra-low temperature (≤ 300 °C) with the assistance of transient aqueous solution and applied pressure. In CSP, the processing conditions including aqueous solution, pressure, temperature, and sintering duration play critical roles in the densification and properties of ceramics, which will be reviewed. The review will also include the applications of CSP in solid-state rechargeable batteries. Finally, the perspectives about CSP is proposed

Conformation of Pyrene-Labeled Amylose in DMSO Characterized with the Fluorescence Blob Model

Amylose and poly­(methyl acrylate) were randomly labeled with pyrene to yield a series of Py-Amylose and Py-PMA constructs, and their ability to form excimer in DMSO was characterized quantitatively by steady-state and time-resolved fluorescence. First, the ratio of the fluorescence intensity of the excimer over that of the monomer, namely the <i>I</i>_E/<i>I</i>_M ratio, was obtained from the fluorescence spectra. Second, the product ⟨<i>k</i>_blob × <i>N</i>_blob⟩ was obtained from the fluorescence blob model (FBM) analysis of the fluorescence decays. Both <i>I</i>_E/<i>I</i>_M and ⟨<i>k</i>_blob × <i>N</i>_blob⟩ yielded similar values when expressed in terms of moles of pyrene per backbone atom for Py-Amylose and Py-PMA. Since <i>I</i>_E/<i>I</i>_M and ⟨<i>k</i>_blob × <i>N</i>_blob⟩ reflect the efficiency of pyrene excimer formation, the similar behavior observed for both parameters obtained for rigid amylose and flexible PMA could only be rationalized by postulating that amylose adopted a compact helical conformation in DMSO. To confirm whether this was possible, molecular mechanics optimizations were conducted with the HyperChem program on Py-Amylose assuming a helical conformation for amylose in DMSO. Two pyrene labels were found to overlap properly, and thus form excimer efficiently, if they were separated by no more than five anhydroglucose units up and down the amylose helix around the anhydroglucose unit bearing the reference pyrene label. This result suggested that excimer formation would not occur if two pyrene labels were separated by more than 5 + 5 + 1 = 11 anhydroglucose units, in perfect agreement with our findings that ⟨<i>N</i>_blob⟩ obtained from the FBM analysis of the fluorescence decays acquired with the Py-Amylose solutions in DMSO equaled 11 ± 2. The good agreement between simulations and experiments led to the conclusion that amylose must adopt a helical conformation in DMSO

Table1_Identification of functional TF-miRNA-hub gene regulatory network associated with ovarian endometriosis.XLSX

Endometriosis (EMs), one of the most common gynecological diseases, seriously affects the health and wellness of women; however, the underlying pathogenesis remains unclear. This study focused on dysregulated genes and their predicted transcription factors (TFs) and miRNAs, which may provide ideas for further mechanistic research. The microarray expression dataset GSE58178, which included six ovarian endometriosis (OE) samples and six control samples, was downloaded from the Gene Expression Omnibus (GEO) to identify differentially expressed genes (DEGs). Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to study the cellular and organism-level functions of DEGs. The protein-protein interaction (PPI) network was built and visualized using Cytoscape, and modules and hub genes were explored using various algorithms. Furthermore, we predicted miRNAs and TFs of hub genes using online databases, and constructed the TF-miRNA-hub gene network. There were 124 upregulated genes and 66 downregulated genes in EMs tissues. GO enrichment analysis showed that DEGs were concentrated in reproductive structure development and collagen-containing extracellular matrix, while KEGG pathway analysis showed that glycolysis/gluconeogenesis and central carbon metabolism in cancer require further exploration. Subsequently, HIF1A, LDHA, PGK1, TFRC, and CD9 were identified as hub genes, 22 miRNAs and 34 TFs were predicted to be upstream regulators of hub genes, and these molecules were pooled together. In addition, we found three key feedback loops in the network, MYC-miR-34a-5p-LDHA, YY1-miR-155-5p-HIF1A, and RELA-miR-93-5p-HIF1A, which may be closely related to OE development. Taken together, our study structured a TF-miRNA-hub gene network to decipher the molecular mechanism of OE, which may provide novel insights for clinical diagnosis and treatment.</p

Table3_Identification of functional TF-miRNA-hub gene regulatory network associated with ovarian endometriosis.XLSX

Endometriosis (EMs), one of the most common gynecological diseases, seriously affects the health and wellness of women; however, the underlying pathogenesis remains unclear. This study focused on dysregulated genes and their predicted transcription factors (TFs) and miRNAs, which may provide ideas for further mechanistic research. The microarray expression dataset GSE58178, which included six ovarian endometriosis (OE) samples and six control samples, was downloaded from the Gene Expression Omnibus (GEO) to identify differentially expressed genes (DEGs). Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to study the cellular and organism-level functions of DEGs. The protein-protein interaction (PPI) network was built and visualized using Cytoscape, and modules and hub genes were explored using various algorithms. Furthermore, we predicted miRNAs and TFs of hub genes using online databases, and constructed the TF-miRNA-hub gene network. There were 124 upregulated genes and 66 downregulated genes in EMs tissues. GO enrichment analysis showed that DEGs were concentrated in reproductive structure development and collagen-containing extracellular matrix, while KEGG pathway analysis showed that glycolysis/gluconeogenesis and central carbon metabolism in cancer require further exploration. Subsequently, HIF1A, LDHA, PGK1, TFRC, and CD9 were identified as hub genes, 22 miRNAs and 34 TFs were predicted to be upstream regulators of hub genes, and these molecules were pooled together. In addition, we found three key feedback loops in the network, MYC-miR-34a-5p-LDHA, YY1-miR-155-5p-HIF1A, and RELA-miR-93-5p-HIF1A, which may be closely related to OE development. Taken together, our study structured a TF-miRNA-hub gene network to decipher the molecular mechanism of OE, which may provide novel insights for clinical diagnosis and treatment.</p

Table2_Identification of functional TF-miRNA-hub gene regulatory network associated with ovarian endometriosis.XLSX

Endometriosis (EMs), one of the most common gynecological diseases, seriously affects the health and wellness of women; however, the underlying pathogenesis remains unclear. This study focused on dysregulated genes and their predicted transcription factors (TFs) and miRNAs, which may provide ideas for further mechanistic research. The microarray expression dataset GSE58178, which included six ovarian endometriosis (OE) samples and six control samples, was downloaded from the Gene Expression Omnibus (GEO) to identify differentially expressed genes (DEGs). Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to study the cellular and organism-level functions of DEGs. The protein-protein interaction (PPI) network was built and visualized using Cytoscape, and modules and hub genes were explored using various algorithms. Furthermore, we predicted miRNAs and TFs of hub genes using online databases, and constructed the TF-miRNA-hub gene network. There were 124 upregulated genes and 66 downregulated genes in EMs tissues. GO enrichment analysis showed that DEGs were concentrated in reproductive structure development and collagen-containing extracellular matrix, while KEGG pathway analysis showed that glycolysis/gluconeogenesis and central carbon metabolism in cancer require further exploration. Subsequently, HIF1A, LDHA, PGK1, TFRC, and CD9 were identified as hub genes, 22 miRNAs and 34 TFs were predicted to be upstream regulators of hub genes, and these molecules were pooled together. In addition, we found three key feedback loops in the network, MYC-miR-34a-5p-LDHA, YY1-miR-155-5p-HIF1A, and RELA-miR-93-5p-HIF1A, which may be closely related to OE development. Taken together, our study structured a TF-miRNA-hub gene network to decipher the molecular mechanism of OE, which may provide novel insights for clinical diagnosis and treatment.</p

Data_Sheet_1_Factors associated with access to healthcare services for older adults with limited activities of daily living.docx

BackgroundLimited studies focused on the situation and related factors of access to healthcare services for older adults with limited activities of daily living (ADL) in China. This study explores factors associated with access to healthcare services of them based on Andersen's healthcare utilization model (namely, need, predisposing, and enabling dimensions).MethodsA total of 3,980 participants aged 65 years and older adults with limited ADL from the latest wave (2018) of the Chinese Longitudinal Healthy Longevity Survey (CLHLS) were included. Binary logistic regression was used to explore the influencing factors.ResultsFactors in enabling dimension were associated with access to healthcare services for older adults with limited ADL. Those who lived with better economic status (fair vs poor, OR = 2.98, P ConclusionAccess to healthcare services for older adults with ADL limitation was mainly related to the factors of economic status, affordability for daily life, and living regions in enabling dimension. Strategies focused on health insurance, healthcare system, barrier-free facilities, and social support were proposed to increase the access to healthcare services for participants, which could benefit their health.</p

Data_Sheet_1_I determine my learning path, or not? A study of different learner control conditions in online video-based learning.docx

Learner control is an important instructional design in video-based learning. This study assessed two conditions: a full learner control where learners direct their learning path, and a hybrid learner control where learners follow the instructor-set path but still enjoy certain aspects of control. Two groups of university students participated in this study by learning statistics through online video courses. The findings show that the full learner control condition attained higher learning performance than the hybrid learner control condition, but spent more time than the latter. The full learner control condition scored higher than the hybrid condition in the difficult sections of video-based learning; but no significant difference was found in the easy section. There was a significant difference between the two conditions in learning agency, but no differences in cognitive load and affective and cognitive engagement. Hierarchical regression analysis indicated differences between the full and the hybrid learner control conditions in the factors predicting overall scores. The findings carry important contributions and implications for the research and practice of instructional designs in online video-based learning such as MOOCs.</p

Vicinal Diamination of Arenes with Domino Aryne Precursors

Vicinal diamination of domino aryne precursors was achieved with sulfamides. The reaction proceeds through a two-aryne pathway, accepting two N-nucleophiles at the 1,2-positions of an arene ring. Symmetrical and unsymmetrical diaminobenzenes were readily obtained

Effects of calcium input frequencies on the activation of calmodulin.

<p>Dependence of calmodulin activation on calcium input frequencies in models without or with targets. Each curve represents a time course of normalized active calmodulin, stimulated by a train of calcium inputs at a specific frequency. Although the frequency differs between curves, the total number of calcium inputs and the input size remain the same (100 inputs, 34560 molecules for each input). (a) Calmodulin activation in the model where calcineurin and CaMKII are not present. (b) Calmodulin activation in the model where calcineurin and CaMKII are present. From 10 to 70 Hz, the duration of calmodulin activation increases while, as the frequency increases, the duration of calcium stimulation decreases.</p

Calcium-spike-frequency dependent synaptic plasticity.

<p>(a) Ratio of calcineurin to CaMKII activated area. Each point represents the ratio of activated areas, upon the stimulation by a train of calcium inputs at a specific frequency (for the detailed calculation of “activated area”, see the methods section) (b) Difference between kinase (CaMKII) activity and phosphatase (calcineurin and PP1) activities. Enzyme activity is calculated as the product of an enzyme's activated area and its catalytic constant towards the GluR1 subunit of the AMPA receptor. Each point corresponds to a specific calcium spike frequency. For both graphs, stimulation at each frequency is composed of 100 calcium inputs with the same input size.</p