Continuity, change and challenge: unearthing the (fr)agility of teacher education

In this final article, we bring together the issues raised by authors included in this special issue. We start by describing the current situation in our own countries, partly to highlight the different ways in which nations are responding in the longer term to the pandemic, but also to draw attention to the similarity of experience – of educators using digital technology, of concern with maintaining the supply of teachers, of the challenges relating to lockdowns – during its peak. We then reflect on the systemic issues that have been raised by the authors in this issue: what we call the (fr)agility of the teacher education system, in which educators’ adaptive response to the pandemic and subsequent desire for change can be met by institutional resistance; the multiple questions raised by the use of digital technologies; and the challenges relating to teacher and teacher educator adaptability and/or agility. In the final section, we reflect on what we (might) have learned from the pandemic and consider a future agenda for teacher educators.</p

Integrated Analysis of Long Noncoding RNA and mRNA Expression Profile in Advanced Laryngeal Squamous Cell Carcinoma

<div><p>Long non-coding RNA (lncRNA) plays an important role in tumorigenesis. However, the expression pattern and function of lncRNAs in laryngeal squamous cell carcinoma (LSCC) are still unclear. To investigate the aberrantly expressed lncRNAs and mRNAs in advanced LSCC, we screened lncRNA and mRNA expression profiles in 9 pairs of primary Stage IVA LSCC tissues and adjacent non-neoplastic tissues by lncRNA and mRNA integrated microarrays. Gene Ontology and pathway analysis were performed to find out the significant function and pathway of the differentially expressed mRNAs, gene-gene functional interaction network and ceRNA network were constructed to select core mRNAs, and lncRNA-mRNA expression correlation network was built to identify the interactions between lncRNA and mRNA. qRT-PCR was performed to further validate the expressions of selected lncRNAs and mRNAs in advanced LSCC. We found 1459 differentially expressed lncRNAs and 2381 differentially expressed mRNAs, including 846 up-regulated lncRNAs and 613 down-regulated lncRNAs, 1542 up-regulated mRNAs and 839 down-regulated mRNAs. The mRNAs ITGB1, HIF1A, and DDIT4 were selected as core mRNAs, which are mainly involved in biological processes, such as matrix organization, cell cycle, adhesion, and metabolic pathway. LncRNA-mRNA expression correlation network showed LncRNA NR_027340, MIR31HG were positively correlated with ITGB1, HIF1A respectively. LncRNA SOX2-OT was negatively correlated with DDIT4. qRT-PCR further validated the expression of these lncRNAs and mRNAs. The work provides convincing evidence that the identified lncRNAs and mRNAs are potential biomarkers in advanced LSCC for further future studies.</p></div

LncRNA-mRNA expression correlation network analysis of core mRNAs and their correlated lncRNAs in advanced LSCC.

<p>In the network, nodes represent mRNAs, nodes with yellow rings represent lncRNAs, and the size of the node’s area represents the value of betweenness centrality. Red color indicates up-regulation and blue indicates down-regulation relative to adjacent non-neoplastic tissues. The lines between nodes indicate a correlative relationship within the group, solid line represents positive correlation, and the dotted line represents negative correlation. (A) LncRNA-mRNA expression correlation network of core mRNAs in cancer tissues. (B) LncRNA-mRNA expression correlation network of core mRNAs in adjacent non-neoplastic tissues.</p

Clinical characteristics of 39 patients with laryngeal cancer.

<p>Clinical characteristics of 39 patients with laryngeal cancer.</p

Gene-gene functional interaction network analysis of differentially expressed mRNAs in advanced LSCC.

<p>In the network, a node represents a gene, red color indicates up-regulation and blue color indicates down-regulation, the size of the node’s area represents the value of betweenness centrality. The nodes connect by an edge. The indicators a, b, c, p, u, m, inh, ex, dep, ind are abbreviation of activation, binding, compound, phosphorylation, ubiquitination, missing interaction, inhibition, expression, dephosphorylation, indirect effect respectively. (A) PIK3R1 signal network. (B) ITGB1 signal network. (C) HIF1A signal network.</p

qRT-PCR analysis of relative expression levels of selected lncRNAs and mRNAs.

<p>The bars represent standard deviations, and the asterisks above the bars denote statistically significant differences from the control group, P<0.05.</p

Primers used for qRT-PCR.

<p>Primers used for qRT-PCR.</p

CeRNA network analysis of differentially expressed mRNAs, lncRNAs, and miRNAs in advanced LSCC.

<p>In the network, nodes represent mRNAs, nodes with yellow rings represent lncRNAs, squares represent miRNAs, and the size of the node’s area represents the value of betweenness centrality. Red color indicates up-regulation, blue color indicates down-regulation, and edges indicate target interactions.</p

Core mRNAs selected by gene-gene functional interaction network.

<p>Core mRNAs selected by gene-gene functional interaction network.</p

Hierarchical clustering of aberrant expressed lncRNAs and mRNAs detected in advanced LSCC.

<p>Red color indicates over expression and green color indicates low expression. Every column represents a tissue sample and every row represents an lncRNA/mRNA probe. C represents cancer tissues and N represents adjacent normal tissues. (A) lncRNA hierarchical clustering. (B) mRNA hierarchical clustering.</p