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The rapid development of the Internet and the continuous expansion of social media have brought a wealth of social event information,and the task of social event classification has become increasingly challenging.Making full use of image-level and text-level information is the key to social event classification.However,most of existing methods have the following limitations:1) Most of the existing multi-modal methods have an ideal assumption that the samples of each modality are sufficient and complete,but in real applications this assumption does not always hold and there will be cases where a certain modality of events is missing;2) Most methods simply concatenate image features and text features of social events to obtain multi-modal features to classify social events.To address these challenges,this paper proposes a dual variational multi-modal attention network(DVMAN) for social event classification to address the limitations of these existing methods.In the DVMAN network,this paper proposes a novel dual variational autoencoders network to generate public representations of social events and further reconstruct the missing modal information in incomplete social event learning.Through distribution alignment and cross-reconstruction alignment,image and text latent representations are doubly aligned to mitigate the gap between different modalities,and for the mis-sing modality information,a generative model is utilized to synthesize its latent representations.In addition,this paper designs a multi-modal fusion module to integrate the fine-grained information of images and texts of social events,so as to realize the complementation and enhancement of information between modalities.This paper conducts extensive experiments on two publicly available event datasets,compared with the existing advanced methods,the accuracy of DVMAN improves by more than 4%.It demonstrates the superior performance of the proposed method for social event classification.

Background: Ear and temporal bone squamous cell carcinoma (ETBSCC) is a rare and aggressive malignant tumor with minimal clinicopathological studies. The object of this study was to retrospectively evaluate the predictive effect of clinicopathological variables on the 5‐year overall survival (OS) rate of ETBSCC patients in a single tertiary medical center in Tianjin, China. Methods: A cohort of 44 patients with diagnosed ETBSCC from December 2012 to August 2022 were retrospectively studied. Univariate and multivariate analysis were, respectively, performed for the assessment of clinicopathological predictors, including sex, age, history of chronic suppurative otitis media (CSOM), lesion side, diameter, the choice of surgical approach, parotidectomy, neck dissection, adjuvant therapies, T stage, lymph node metastasis, tumor grade, margin, perineural invasion (PNI), and Ki‐67 index. Results: Seventeen females and 27 males were included, with the mean age of 65 years old, ranging from 36 to 89 years. The 5‐year OS rate was 43% (mean 51 months, 95% confidence interval [CI] = 39–64). Significant prediction of a worse prognosis for 5‐year OS rate was observed under univariate analysis for advanced T stage, positive margin, identified PNI, and higher Ki‐67 index, respectively. Advanced T stage was confirmed to be an independent prognostic factor strongly affecting 5‐year OS rate among this cohort of patients using a multivariate cox proportional hazard model. Conclusion: We found that clinicopathological parameters, especially postoperative pathological parameters, play a critical role in predicting the prognosis of ETBSCC patients. [ABSTRACT FROM AUTHOR]

The development of iridium complexes as potent anticancer agents has received increasing attention in recent years. In this study, four cyclometalated Ir(iii) complexes with good photophysical properties and potent anticancer activity have been synthesized and characterized. They are taken up by human lung adenocarcinoma A549 cells very quickly and specifically target mitochondria. Mechanism studies reveal that one of them, namely IrM2, induces paraptosis accompanied by excessive mitochondria-derived cytoplasmic vacuoles. Meanwhile, IrM2 affects the ubiquitin–proteasome system (UPS) and mitogen-activated protein kinase (MAPK) signaling pathways. Furthermore, IrM2 rapidly induces a series of mitochondria-related dysfunctional events, including the loss of mitochondrial membrane potential, cellular ATP depletion, mitochondrial respiration inhibition and reactive oxygen species (ROS) elevation. The rapid loss of mitochondrial functions, elevation of ROS and impairment of the UPS induced by IrM2 lead to the collapse of mitochondria and the subsequent cytoplasmic vacuolation before the cells are ready to start the mechanisms of apoptosis and/or autophagy. Among the ROS, superoxide anion radicals play a critical role in IrM2-mediated cell death. In vivo studies reveal that IrM2 can significantly inhibit tumor growth in a mouse model. This work gives useful insights into the design and anticancer mechanisms of new metal-based anticancer agents. [ABSTRACT FROM AUTHOR]