Minjiang University

Retrograde transport from endosomes to the trans-Golgi network (TGN) is essential for intracellular trafficking, yet its molecular mechanism remains poorly understood. In Fusarium graminearum, 10 Rab GTPases associated with the Golgi-associated retrograde protein (GARP) complex were identified through immunoprecipitation followed by mass spectrometry (IP-MS). Among these, only the deletion of FgRAB6 disrupted the proper localisation of the GARP complex to the TGN. FgRab6 directly interacts with the GARP subunit FgVps52 via a conserved Q73 residue, which is critical for fungal growth and pathogenicity. Notably, this Q73-dependent interaction is evolutionarily conserved across eukaryotic species. Upon GTP activation, FgRab6 recruits FgVps52 to the TGN, thereby facilitating the assembly of the GARP complex through the sequential recruitment of additional subunits, including FgVps51, FgVps53 and FgVps54. The fully assembled GARP complex subsequently recruits the retromer complex and ensures the precise localisation of the SNARE proteins FgSnc1, FgTlg1 and FgTlg2 at the endosomes and the TGN. Disruption of this pathway severely compromises fungal development and virulence. Collectively, these findings identify a FgRab6-GARP-retromer-coordinated vesicle trafficking pathway that mediates the retrograde transport of SNARE proteins, which is critical for the pathogenicity of F. graminearum. This work provides new mechanistic insights into vesicular transport and highlights potential targets for antifungal intervention.

The homogeneity and heterogeneity across modalities are critical factors that influence multimodal fusion. In Multimodal Sentiment Analysis (MSA), the inherent textual information within the audio modality induces cross-modality homogeneity with the text modality. Conversely, the mutual independence between text and vision modalities results in their cross-modal heterogeneity. Although existing disentangle-based methods achieve notable performance gains by separating modality features into distinct subspaces, they overlook the characteristics of cross-modality heterogeneity and homogeneity among different modalities. To this end, we propose a novel Modality-aware Disentangle and Fusion (MDF) framework to investigate the role of core modality features. Specifically, we first use text as the anchor to disentangle the audio modality and extract its unique modality-specific features, thereby establishing cross-modal heterogeneity among text, audio, and vision. We then introduce a Cross-Modality Heterogeneity Enhancement (CHE) module to refine these features, further reinforcing their heterogeneous characteristics. Finally, a Modality Adaptive Weighting (MAW) module is employed to dynamically assign weights to the text, sound, and vision modalities based on their potential contributions to sentiment prediction, achieving a more effective multimodal representation for MSA. Experimental evaluations on different benchmarks demonstrate MDF's superiority, with extensive ablation studies confirming its effectiveness.

The representation of immigrants in the media has been a long-standing and contentious issue in public, political, and social discourse. In today’s increasingly complex geopolitical landscape, the portrayal of immigrants has become even more controversial. This study employs Sinclair’s model of Extended Units of Meaning to examine the representation of immigrants in written media discourse using the enTenTen21 corpora on Sketch Engine. Utilizing a corpus-based approach, the study focuses on collocates, semantic preference, and semantic prosody of the node word ‘immigrant’. Semantic preference is determined using the UCREL Semantic Analysis System (USAS), while semantic prosody is identified through a textual analysis of concordance lines of collocates of the node word. The findings reveal a dominant transnational narrative framed by a semantic preference for government, law, and order. Government-related collocates such as ‘illegal’ and ‘deportation’ carry a dominant negative semantic prosody that constructs immigrants as a threat, while ethnically-specific collocates such as ‘Mexican’ and ‘Asian’ exhibit a positive prosody, highlighting a humanitarian narrative towards vulnerable immigrant groups. Yet, competing narratives (threat and vulnerability) coexist around collocates like ‘refugee’ and ‘undocumented’. The coexistence of these patterns demonstrates that the meaning of immigrant is constructed through competing extended units of meaning within the global news media context.