Sememe knowledge and auxiliary information enhanced approach for sarcasm detection

Sarcasm expression is a pervasive literary technique in which people intentionally express the opposite of what is implied. Accurate detection of sarcasm in a text can facilitate the understanding of speakers’ true intentions and promote other natural language processing tasks, especially sentiment analysis tasks. Since sarcasm is a kind of implicit sentiment expression and speakers deliberately confuse the audience, it is challenging to detect sarcasm only by text. Existing approaches based on machine learning and deep learning achieved unsatisfactory performance when handling sarcasm text with complex expression or needing specific background knowledge to understand. Especially, due to the characteristics of the Chinese language itself, sarcasm detection in Chinese is more difficult. To alleviate this dilemma on Chinese sarcasm detection, we propose a sememe and auxiliary enhanced attention neural model, SAAG. At the word level, we introduce sememe knowledge to enhance the representation learning of Chinese words. Sememe is the minimum unit of meaning, which is a fine-grained portrayal of a word. At the sentence level, we leverage some auxiliary information, such as the news title, to learning the representation of the context and background of sarcasm expression. Then, we construct the representation of text expression progressively and dynamically. The evaluation on a sarcasm dateset, consisting of comments on news text, reveals that our proposed approach is effective and outperforms the state-of-the-art models

Morphological Characterization and Transcriptional Regulation of Corolla Closure in Ipomoea purpurea

Corolla closure protects pollen from high-temperature stress during pollen germination and fertilization in the ornamental plant morning glory (Ipomoea purpurea). However, the morphological nature of this process and the molecular events underpinning it remain largely unclear. Here, we examined the cellular and gene expression changes that occur during corolla closure in the I. purpurea. We divided the corolla closure process into eight stages (S0-S7) based on corolla morphology. During flower opening, bulliform cells appear papillate, with pigments in the adaxial epidermis of the corolla. These cells have distinct morphology from the smaller, flat cells in the abaxial epidermis in the corolla limb and intermediate of the corolla. During corolla closure, the bulliform cells of the adaxial epidermis severely collapse compared to cells on the abaxial side. Analysis of transparent tissue and cross sections revealed that acuminate veins in the corolla are composed of spiral vessels that begin to curve during corolla closure. When the acuminate veins were compromised, the corolla failed to close normally. We performed transcriptome analysis to obtain a time-course profile of gene expression during the process from the open corolla stage (S0) to semi-closure (S3). Genes that were upregulated from S0 to S1 were enriched in the polysaccharide degradation pathway, which positively regulates cell wall reorganization. Senescence-related transcription factor genes were expressed beginning at S1, leading to the activation of downstream autophagy-related genes at S2. Genes associated with peroxisomes and ubiquitin-mediated proteolysis were upregulated at S3 to enhance reactive oxygen species scavenging and protein degradation. Therefore, bulliform cells and acuminate veins play essential roles in corolla closure. Our findings provide a global understanding of the gene regulatory processes that occur during corolla closure in I. purpurea

Elevated exhaustion levels of NK and CD8⁺ T cells as indicators for progression and prognosis of COVID-19 disease.

BackgroundSevere Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) induced Coronavirus Disease 2019 (COVID-19) has posed a global threat to public health. The immune system is crucial in defending and eliminating the virus and infected cells. However, immune dysregulation may result in the rapid progression of COVID-19. Here, we evaluated the subsets, phenotypic and functional characteristics of natural killer (NK) and T cells in patients with COVID-19 and their associations with disease severity.MethodsDemographic and clinical data of COVID-19 patients enrolled in Wuhan Union Hospital from February 25 to February 27, 2020, were collected and analyzed. The phenotypic and functional characteristics of NK cells and T cells subsets in circulating blood and serum levels of cytokines were analyzed via flow cytometry. Then the LASSO logistic regression model was employed to predict risk factors for the severity of COVID-19.ResultsThe counts and percentages of NK cells, CD4(+) T cells, CD8(+) T cells and NKT cells were significantly reduced in patients with severe symptoms. The cytotoxic CD3(-)CD56(dim)CD16(+) cell population significantly decreased, while the CD3(-)CD56(dim)CD16(-) part significantly increased in severe COVID-19 patients. More importantly, elevated expression of regulatory molecules, such as CD244 and programmed death-1 (PD-1), on NK cells and T cells, as well as decreased serum cytotoxic effector molecules including perforin and granzyme A, were detected in patients with COVID-19. The serum IL-6, IL-10, and TNF-alpha were significantly increased in severe patients. Moreover, the CD3(-)CD56(dim)CD16(-) cells were screened out as an influential factor in severe cases by LASSO logistic regression.ConclusionsThe functional exhaustion and other subset alteration of NK and T cells may contribute to the progression and improve the prognosis of COVID-19. Surveillance of lymphocyte subsets may in the future enable early screening for signs of critical illness and understanding the pathogenesis of this disease