␤-Catenin is a bifunctional protein participating in both cell adhesion and canonical Wnt signaling. In cell adhesion, it bridges the transmembrane cadherin and the actin-binding protein ␣-catenin and is essential for adherens junction formation, whereas in canonical Wnt signaling, it shuttles between the cytosol and nucleus and functions as an essential transcriptional activator. Schmidtea mediterranea ␤-catenin-1 was identified as a determinant of antero-posterior polarity during body regeneration by mediating Wnt signaling. Here we show that S. mediterranea ␤-catenin-2 is specifically expressed in epithelial cells in the gut and pharynx, where it has a putative role in mediating cell adhesion. We show evidence that planarian ␤-catenin-1 and -2 have distinct biochemical properties. ␤-Catenin-1 can interact with the components of the canonical Wnt signaling pathway but not with ␣-catenin, whereas ␤-catenin-2 interacts with cell adhesion molecules, including E-cadherin and ␣-catenin, but not with Wnt signaling components. Consistent with their specific function, ␤-catenin-1 is a potent transcriptional activator, whereas ␤-catenin-2 has no transcriptional activity. Protein sequence alignment also indicates that the planarian ␤-catenin-1 and -2 retain distinct critical residues and motifs, which are in agreement with the differences in their biochemical properties. At last, phylogenetic analysis reveals a probable Platyhelminthes-specific structural and functional segregation from which the monofunctional ␤-catenins evolved. Our results thus identify the first two monofunctional ␤-catenins in metazoans.

This study examined lexical bundles (LBs) used differently by Chinese and American PhD students of linguistics in their dissertation abstracts. Two corpora were built, with each having 700 dissertation abstracts produced by Chinese and American PhD students of linguistics, respectively. The study then used lexical analysis software to retrieve frequently used three-word LBs, from which LBs having different frequencies at a significant level across the two corpora were identified and termed as bundles used differently (BUDs). BUDs were then categorized and analyzed manually in terms of structure, function, and distribution in rhetorical moves. The major findings were: (1) 57.14% of the frequently used LBs were BUDs, of which 90.67% had occurrences in both corpora. The BUDs distributed inequivalently across categories and moves, with the text-oriented category and the move of Result having the most BUDs; and (2) BUDs exhibited two major patterns: the Chinese and American students filled different constituents into structurally and functionally similar constructions, and used LBs of dissimilar functions to fulfill the same communicative purposes. These findings indicate that variations in LB use have a high pedagogic value and confirm the need for using corpora to identify and teach core genre-specific vocabularies to second/foreign language learners.

This article presents an analysis of the evolving representations of feminism on Weibo, China’s foremost microblogging platform, employing a corpus-based methodology. The self-compiled corpus comprised 334,871 feminism-related posts from 2019 to 2022. Using the Sketch Engine corpus analysis tool, noun bigrams containing 女权 ( feminism) were extracted, categorized, and compared to discern the portrayals and their transformations. The findings revealed a significant shift in feminism’s depiction, with an increased emphasis on its radical and aggressive aspects, and a decline in its portrayal as a quest for female privilege. During this period, the perception of feminism as an emerging social movement expanded, and the distinction between various forms of feminism and feminists based on different attributes became more prevalent, resulting in a marginally reduced representation of them as a unified entity. This research enriches the existing literature by emphasizing the dynamic portrayals of feminism on China’s social media and offering novel insights into its assessment.

Corpus linguistics has become increasingly important to both language researchers and teachers over the past three decades. As a popular practice of corpus linguistics, Data-Driven Learning (DDL) sees a rapidly growing body of research as well as instruction in the field. There is, however, a lack of comprehensive literature reviews that summarize the effectiveness, learners’ perception, as well as factors affecting the success of DDL to guide its practices. In response, this study analyzes previous DDL research to show the feasibility of the activities in EFL classrooms. For the purpose, we collected and analyzed relevant research articles from 19 journals in the discipline of applied linguistics. Our analysis revealed that while DDL has been proved generally effective in improving learners’ target language proficiency with respect to a variety of linguistic aspects, a set of its drawbacks have been elicited from the learners. The results indicate the instructors’ need to take into account the learner as well as technique background before the introduction of DDL into their classrooms.

The purpose of this study is to determine how embedded music affects verbal memory in the language of Mandarin Chinese. For this purpose, an experiment was conducted where 40 college students were recruited as the participants. Specifically, they were first randomly allocated into four groups, namely the ‘Reading Group’, the ‘Ambient-music Group’, the ‘Embedded-music Group’, and the ‘Finger-tapping Group’. They were then tested for verbal recall of a lyric in terms of both short-term memory and long-term memory. The results showed that the ‘Ambient-music Group’ scored the highest, followed by the ‘Reading Group’, while the ‘Finger-tapping Group’ ranked the third, and the ‘Embedded-music Group’ was at the bottom. The results that the sung version of a lyric was recalled worse than the spoken version conforms to the recent findings, as compared with traditional notions that music can facilitate the memory of language.