Construction of an Emotional Lexicon of Patients With Breast Cancer: Development and Sentiment Analysis.

BACKGROUND: The innovative method of sentiment analysis based on an emotional lexicon shows prominent advantages in capturing emotional information, such as individual attitudes, experiences, and needs, which provides a new perspective and method for emotion recognition and management for patients with breast cancer (BC). However, at present, sentiment analysis in the field of BC is limited, and there is no emotional lexicon for this field. Therefore, it is necessary to construct an emotional lexicon that conforms to the characteristics of patients with BC so as to provide a new tool for accurate identification and analysis of the patients' emotions and a new method for their personalized emotion management. OBJECTIVE: This study aimed to construct an emotional lexicon of patients with BC. METHODS: Emotional words were obtained by merging the words in 2 general sentiment lexicons, the Chinese Linguistic Inquiry and Word Count (C-LIWC) and HowNet, and the words in text corpora acquired from patients with BC via Weibo, semistructured interviews, and expressive writing. The lexicon was constructed using manual annotation and classification under the guidance of Russell's valence-arousal space. Ekman's basic emotional categories, Lazarus' cognitive appraisal theory of emotion, and a qualitative text analysis based on the text corpora of patients with BC were combined to determine the fine-grained emotional categories of the lexicon we constructed. Precision, recall, and the F1-score were used to evaluate the lexicon's performance. RESULTS: The text corpora collected from patients in different stages of BC included 150 written materials, 17 interviews, and 6689 original posts and comments from Weibo, with a total of 1,923,593 Chinese characters. The emotional lexicon of patients with BC contained 9357 words and covered 8 fine-grained emotional categories: joy, anger, sadness, fear, disgust, surprise, somatic symptoms, and BC terminology. Experimental results showed that precision, recall, and the F1-score of positive emotional words were 98.42%, 99.73%, and 99.07%, respectively, and those of negative emotional words were 99.73%, 98.38%, and 99.05%, respectively, which all significantly outperformed the C-LIWC and HowNet. CONCLUSIONS: The emotional lexicon with fine-grained emotional categories conforms to the characteristics of patients with BC. Its performance related to identifying and classifying domain-specific emotional words in BC is better compared to the C-LIWC and HowNet. This lexicon not only provides a new tool for sentiment analysis in the field of BC but also provides a new perspective for recognizing the specific emotional state and needs of patients with BC and formulating tailored emotional management plans.

Pharmacological effects and mechanisms of bee venom and its main components: Recent progress and perspective.

Bee venom (BV), a type of defensive venom, has been confirmed to have favorable activities, such as anti-tumor, neuroprotective, anti-inflammatory, analgesic, anti-infectivity effects, etc. This study reviewed the recent progress on the pharmacological effects and mechanisms of BV and its main components against cancer, neurological disorders, inflammatory diseases, pain, microbial diseases, liver, kidney, lung and muscle injury, and other diseases in literature during the years 2018-2021. The related target proteins of BV and its main components against the diseases include Akt, mTOR, JNK, Wnt-5α, HIF-1α, NF-κB, JAK2, Nrf2, BDNF, Smad2/3, AMPK, and so on, which are referring to PI3K/Akt/mTOR, MAPK, Wnt/ß-catenin, HIF-1α, NF-κB, JAK/STAT, Nrf2/HO-1, TrkB/CREB/BDNF, TGF-ß/Smad2/3, and AMPK signaling pathways, etc. Further, with the reported targets, the potential effects and mechanisms on diseases were bioinformatically predicted via Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, disease ontology semantic and enrichment (DOSE) and protein-protein interaction (PPI) analyses. This review provides new insights into the therapeutic effects and mechanisms of BV and its main components on diseases.

Lotus Bee Pollen Extract Inhibits Isoproterenol-Induced Hypertrophy via JAK2/STAT3 Signaling Pathway in Rat H9c2 Cells.

Bee pollen possesses an anti-cardiomyocyte injury effect by reducing oxidative stress levels and inhibiting inflammatory response and apoptosis, but the possible effect mechanism has rarely been reported. This paper explores the effect of the extract of lotus bee pollen (LBPE) on cardiomyocyte hypertrophy (CH) and its mechanism. The main components of LBPE were identified via UPLC-QTOF MS. An isoproterenol-induced rat H9c2 CH model was subsequently used to evaluate the protection of LBPE on cells. LBPE (100, 250 and 500 µg∙mL-1) reduced the surface area, total protein content and MDA content, and increased SOD activity and GSH content in CH model in a dose-dependent manner. Meanwhile, quantitative real-time PCR trials confirmed that LBPE reduced the gene expression levels of CH markers, pro-inflammatory cytokines and pro-apoptosis factors, and increased the Bcl-2 mRNA expression and Bcl-2/Bax ratio in a dose-dependent manner. Furthermore, target fishing, bioinformatics analysis and molecular docking suggested JAK2 could be a pivotal target protein for the main active ingredients in the LBPE against CH. Ultimately, Western blot (WB) trials confirmed that LBPE can dose-dependently inhibit the phosphorylation of JAK2 and STAT3. The results show that LBPE can protect against ISO-induced CH, possibly via targeting the JAK2/STAT3 pathway, also suggesting that LBPE may be a promising candidate against CH.