MAFW: A Large-scale, Multi-modal, Compound Affective Database for Dynamic Facial Expression Recognition in the Wild

Dynamic facial expression recognition (FER) databases provide important data support for affective computing and applications. However, most FER databases are annotated with several basic mutually exclusive emotional categories and contain only one modality, e.g., videos. The monotonous labels and modality cannot accurately imitate human emotions and fulfill applications in the real world. In this paper, we propose MAFW, a large-scale multi-modal compound affective database with 10,045 video-audio clips in the wild. Each clip is annotated with a compound emotional category and a couple of sentences that describe the subjects' affective behaviors in the clip. For the compound emotion annotation, each clip is categorized into one or more of the 11 widely-used emotions, i.e., anger, disgust, fear, happiness, neutral, sadness, surprise, contempt, anxiety, helplessness, and disappointment. To ensure high quality of the labels, we filter out the unreliable annotations by an Expectation Maximization (EM) algorithm, and then obtain 11 single-label emotion categories and 32 multi-label emotion categories. To the best of our knowledge, MAFW is the first in-the-wild multi-modal database annotated with compound emotion annotations and emotion-related captions. Additionally, we also propose a novel Transformer-based expression snippet feature learning method to recognize the compound emotions leveraging the expression-change relations among different emotions and modalities. Extensive experiments on MAFW database show the advantages of the proposed method over other state-of-the-art methods for both uni- and multi-modal FER. Our MAFW database is publicly available from https://mafw-database.github.io/MAFW.Comment: This paper has been accepted by ACM MM'2

Network pharmacology, molecular docking, combined with experimental verification to explore the role and mechanism of shizhifang decoction in the treatment of hyperuricemia

Ethnopharmacological relevance: Shizhifang Decoction, a traditional Chinese medicine prescription formulated by Professor Zheng Pingdong of Shuguang Hospital, has been widely utilized in clinical settings for the treatment of hyperuricemia due to its proven safety and efficacy. Objective: In this study, we used network pharmacology, molecular docking technology, and experimental validation to elucidate the therapeutic effects and underlying mechanisms of Shizhifang Decoction in managing hyperuricemia. Methods: Quality control and component identification of the freeze-dried powder of Shizhifang Decoction were conducted using ultra-high performance liquid chromatography-tandem quadrupole time-of-flight mass spectrometry. Active ingredients and their corresponding targets were obtained from Traditional Chinese Medicine Systems Pharmacology, Traditional Chinese Medicine Information Database, The Encyclopedia of Traditional Chinese Medicine, and other databases. Disease-related targets for hyperuricemia were collected from GeneCards and DisGeNET databases. The Venny platform is used to screen common targets for drug active ingredients and diseases. Subsequently, we constructed an active component-target-disease interaction network using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database, create a component disease common target network using Cytoscape 3.9.1 software, from which core targets were selected. Import common targets into the Database for Annotation, Visualization and Integrated Discovery (DAVID) for Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway analysis. Molecular docking was then conducted to validate the binding capacity of key active ingredients and their associated targets in Shizhifang Decoction. The theoretical predictions were further confirmed through in vitro and in vivo experiments. Result: A total of 35 active ingredients and 597 action targets were identified, resulting in 890 disease-related targets for hyperuricemia. After comprehensive analysis, 99 common targets were determined. Protein-protein interaction network analysis revealed crucial relationships between these targets and hyperuricemia. Among them, 12 core targets (CASP3, IL1B, IL6, TNF, TP53, GAPDH, PTGS2, MYC, INS, VEGFA, ESR1, PPARG) were identified. Gene Ontology enrichment analysis demonstrated significant associations with the regulation of inflammatory response, cell apoptosis, and the positive regulation of extracellular regulated protein kinases 1 and extracellular regulated protein kinases 2 cascades. Kyoto Encyclopedia of Genes and Genomes pathway analysis highlighted inflammation and apoptosis-related pathways as critical mediators of Shizhifang Decoction's effects on hyperuricemia. Molecular docking studies further supported the interactions between apoptosis-related proteins and active ingredients in the extracellular regulated protein kinases 1/2 signaling pathway. In vitro experiments confirmed the downregulation of apoptosis-related proteins (caspase-3, Bax, Bcl-2) and the inhibition of the extracellular regulated protein kinases 1/2 signaling pathway by Shizhifang Decoction. These findings were also validated in animal models, demonstrating the potential of Shizhifang Decoction to mitigate renal injury induced by hyperuricemia through extracellular regulated protein kinases 1/2-mediated inhibition of renal tubular epithelial cell apoptosis. Conclusion: Our study provides valuable insights into the main mechanism by which Shizhifang Decoction ameliorates hyperuricemia. By targeting the ERK1/2 signaling pathway and modulating cell apoptosis, Shizhifang Decoction exhibits promising therapeutic potential for the treatment of hyperuricemia. These findings support the continued exploration and development of Shizhifang Decoction as a potential herbal remedy for hyperuricemia management

Gene editing with an oxathiapiprolin resistance selection marker reveals that PuLLP, a loricrin-like protein, is required for oospore development in Pythium ultimum

Abstract Oomycetes, such as Pythium species, contain numerous devastating plant pathogens that inflict substantial economic losses worldwide. Although CRISPR/Cas9-based genome editing is available, the selection markers available for genetic transformation in these species are limited. In this study, a mutated version of the Phytophthora capsici oxysterol-binding protein-related protein 1 (PcMuORP1), known to confer oxathiapiprolin resistance, was introduced into the CRISPR/Cas9 system for in situ complementation in Pythium ultimum. We targeted PuLLP, which encodes a loricrin-like protein, and showed significant downregulation when the Puf RNA-binding protein-encoding gene PuM90 was knocked out. The PuLLP knockout mutants could not produce oospores, indicating a similar biological function as PuM90. The reintroduction of PuLLP into the knockout mutant using PcMuORP1 as a selection marker restored oospore production. Further comparisons with the conventional selection marker NPTII indicated that PcMuORP1 could be applied at a lower concentration and cost, resulting in a higher screening efficiency. Successive subculturing in the absence of selective pressure showed that PcMuORP1 had little long-term effect on the fitness of transformants. Hence, it could be reused as an alternative selection marker. This study demonstrates the successful implementation of the PcMuORP1 gene as a selection marker in the genetic transformation of Py. ultimum and reveals the loricrin-like protein PuLLP as a sexual reproduction-related factor downstream of the Puf RNA-binding protein PuM90. Overall, these results will help accelerate the functional genomic investigation of oomycetes