Newspapers, Images and Income Support Policy

[EN] To what extent do different newspapers have different kinds of images associated with articles on the same topic? We investigate this research question by considering one of the most important Income Support Policies implemented in Italy in recent times (‘Reddito di cittadinanza’ - RdC) which generated a strong debate in public opinion. Focussing on the national wide media, we downloaded images associated with articles about RdC and by means of Image Captioning algorithms, we generate the description of them. Results show that different newspapers have images containing different objects. Some topics emerging from images published by newspapers are very exclusive and the sentiment associated with the text extracted from the images has a wide heterogeneity. Furthermore, right-hand newspapers show a lower sentiment compared with left-hand newspapers. Overall, the results confirm that the ideological stance associated with different media outlets is reflected also in the images associated with articles and that the integration of Image Captioning algorithms and Natural Language Processes is very promising in this research area.Cruciata, P.; Perfetto, C.; Resce, G. (2023). Newspapers, Images and Income Support Policy. Editorial Universitat Politècnica de València. 161-169. https://doi.org/10.4995/CARMA2023.2023.1645616116

Text mining methods for innovation studies: limits and future perspectives

[EN] This study offers alternative and promising approaches to word count methods, largely used to develop innovation indicators from unstructured text. We propose a method based on Information Retrieval (IR) and word-embedding models to tackle the semantic ellipsis, one of the main issues of word count methods. We test our IR model by investigating the concept of collaboration and comparing our approach with a baseline corresponding to the keyword search. To ensure the best performances, we use several ways to represent queries and documents in a vector space and three pre-trained word-embedding models. The results prove that our approach can alleviate the semantic ellipsis problem. Indeed, the IR model developed outperforms the classical keyword search in terms of F1-score and Recall. Moreover, we create a combined method that achieves the highest F1-score. These preliminary results can facilitate the creation of reliable innovation indicators from unstructured textual data substituting or complementing survey-based questionnaires.Cruciata, P.; Pulizzotto, D.; Beaudry, C. (2022). Text mining methods for innovation studies: limits and future perspectives. En 4th International Conference on Advanced Research Methods and Analytics (CARMA 2022). Editorial Universitat Politècnica de València. 147-154. https://doi.org/10.4995/CARMA2022.2022.1507614715

0-shot text classification for web-based environmental indicators: Pilot study on B-Corp data

[EN] This paper proposes a tool that uses web-based information to generate a proxy for the environmental culture indicator developed by B-Lab. The tool is based on recent advances in Natural Language Processing (NLP), such as pre-trained language models like BART that better capture the semantic facets of natural language. The algorithm and data provide several advantages, including real-time analysis, minimal building cost, granularity, and a large sample size, making it appealing. The Zero-shot text classification task is used to create an indicator of companies' environmental culture, which was chosen due to the urgency created by recent climatic events, pushing for increased environmental protection and sustainability culture promotion. The tool was tested on the B-CORP dataset, which provides scores on environmental performance. Results indicate that scores for certain environmental topics generated by the tool are correlated with B-Lab's environmental indicator. This research open door to the possibility of predicting the environmental readiness of the companies base on web-based indicators.Cruciata, P.; Pulizzotto, D.; Héroux-Vaillancourt, M.; Beaudry, C. (2023). 0-shot text classification for web-based environmental indicators: Pilot study on B-Corp data. Editorial Universitat Politècnica de València. 179-186. https://doi.org/10.4995/CARMA2023.2023.1646317918

METHYLOMIC SIGNATURE AND MOLECULAR MODELLING TO BETTER UNDERSTAND AUTOPHAGY INDUCED BY PHYTOCHEMICAL IN CACO-2 CELLS

The binomial “autophagy-cancer” is intricate and methylomic studies can help to understand it by changing point of view from a gene level to an -omic one. Recently, autophagy-modulating properties of several phytochemicals have attracted attention in anticancer research. We evaluated whether Indicaxanthin (IND), the peculiar known beneficial phytochemical of prickly pear, seasonally available in the southern Italy, could induce autophagy in Caco2 cells, and whether it results from an epigenomic modification and/or a direct molecular interaction. IND increased autophagy in Caco-2 cells; the methylomic signature, obtained by Reduced Representation Bisulfite Sequencing (15 million of clusters) reported that 14 main genes of autophagy, showed a different methylation consistent with the induction of this phenomenon. Among these: MTOR, ATG13, BECN1, TFEB, ATG3, WIPI2, TECPR1, SNAP29, VPS11, VPS16. By traditional approaches we confirmed the demethylation of BECN1 gene and the increase of Beclin1 levels. By in-silico molecular modelling, we displayed a possible interference of IND, by competitive mechanisms, in the Beclin1-Bcl2 interaction. Methylomic signature and molecular modelling has been helpful to understand autophagy IND-induced in intestinal epithelial tumour cells. Our results suggest that the pro-autophagic action promoted by this phytochemical involves both epigenomic modulation and post-translation mechanisms by direct interaction with key targets of autophagy pathway

Genotoxicity and epigenotoxicity of carbazole-derived molecules on mcf-7 breast cancer cells

The carbazole compounds PK9320 (1-(9-ethyl-7-(furan-2-yl)-9H-carbazol-3-yl)-N-methylmethanamine) and PK9323 (1-(9-ethyl-7-(thiazol-4-yl)-9H-carbazol-3-yl)-N-methylmethanamine), second-generation analogues of PK083 (1-(9-ethyl-9H-carbazol-3-yl)-N-methylmethanamine), restore p53 signaling in Y220C p53-mutated cancer cells by binding to a mutation-induced surface crevice and acting as molecular chaperones. In the present paper, these three molecules have been tested for mutant p53-independent genotoxic and epigenomic effects on wild-type p53 MCF-7 breast adenocarcinoma cells, employing a combination of Western blot for phospho-γH2AX histone, Comet assay and methylation-sensitive arbitrarily primed PCR to analyze their intrinsic DNA damageinducing and DNA methylation-changing abilities. We demonstrate that small modifications in the substitution patterns of carbazoles can have profound effects on their intrinsic genotoxic and epigenetic properties, with PK9320 and PK9323 being eligible candidates as “anticancer compounds” and “anticancer epi-compounds” and PK083 a “damage-corrective” compound on human breast adenocarcinoma cells. Such different properties may be exploited for their use as anticancer agents and chemical probes