Linguistic profile automated characterisation in pluripotential clinical high-risk mental state (CHARMS) conditions: methodology of a multicentre observational study.

INTRODUCTION: Language is usually considered the social vehicle of thought in intersubjective communications. However, the relationship between language and high-order cognition seems to evade this canonical and unidirectional description (ie, the notion of language as a simple means of thought communication). In recent years, clinical high at-risk mental state (CHARMS) criteria (evolved from the Ultra-High-Risk paradigm) and the introduction of the Clinical Staging system have been proposed to address the dynamicity of early psychopathology. At the same time, natural language processing (NLP) techniques have greatly evolved and have been successfully applied to investigate different neuropsychiatric conditions. The combination of at-risk mental state paradigm, clinical staging system and automated NLP methods, the latter applied on spoken language transcripts, could represent a useful and convenient approach to the problem of early psychopathological distress within a transdiagnostic risk paradigm. METHODS AND ANALYSIS: Help-seeking young people presenting psychological distress (CHARMS+/- and Clinical Stage 1a or 1b; target sample size for both groups n=90) will be assessed through several psychometric tools and multiple speech analyses during an observational period of 1-year, in the context of an Italian multicentric study. Subjects will be enrolled in different contexts: Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), Section of Psychiatry, University of Genoa-IRCCS Ospedale Policlinico San Martino, Genoa, Italy; Mental Health Department-territorial mental services (ASL 3-Genoa), Genoa, Italy; and Mental Health Department-territorial mental services (AUSL-Piacenza), Piacenza, Italy. The conversion rate to full-blown psychopathology (CS 2) will be evaluated over 2 years of clinical observation, to further confirm the predictive and discriminative value of CHARMS criteria and to verify the possibility of enriching them with several linguistic features, derived from a fine-grained automated linguistic analysis of speech. ETHICS AND DISSEMINATION: The methodology described in this study adheres to ethical principles as formulated in the Declaration of Helsinki and is compatible with International Conference on Harmonization (ICH)-good clinical practice. The research protocol was reviewed and approved by two different ethics committees (CER Liguria approval code: 591/2020-id.10993; Comitato Etico dell'Area Vasta Emilia Nord approval code: 2022/0071963). Participants will provide their written informed consent prior to study enrolment and parental consent will be needed in the case of participants aged less than 18 years old. Experimental results will be carefully shared through publication in peer-reviewed journals, to ensure proper data reproducibility. TRIAL REGISTRATION NUMBER: DOI:10.17605/OSF.IO/BQZTN.

Analysing Deception in Witness Memory through Linguistic Styles in Spontaneous Language.

The act of lying and its detection have raised interest in many fields, from the legal system to our daily lives. Considering that testimonies are commonly based on linguistic parameters, natural language processing, a research field concerned with programming computers to process and analyse natural language texts or speech, is a topic of interest on this front. This study aimed to examine the linguistic styles of simulated deception and true testimonies collected with the aim of studying witness memory. Study participants were asked to act as a witness of a crime by retelling the story they had just read. Cognitive interviewing techniques were used to collect testimony under two conditions: truth and simulated deception. A sample of 48 participants volunteered to participate in the study. Analyses of the linguistic indicators and content were carried out. Specifically, we performed a comparison of testimonies of the same participant by condition to analyse the variation between (i) lexical and (ii) linguistic features and (iii) content and speech characteristics (disfluencies) depending on the narrative condition. Concerning lexical properties, adjectives were the most-varying grammatical category between truthful and deceptive testimonies. Furthermore, in the linguistic analysis, we observed that truthful testimonies were generally longer than deceptive ones in terms of the number of words and sentences and also characterised by more articulated sentence structures, and these differences were also statistically significant. Regarding the analysis of the content, cognitive criteria (details) and admitting lack of memory were more present in truthful statements. By providing an objective measure, these results are of interest in developing NLP tools for assessing the credibility of testimonies in forensics.

Natural language processing in low back pain and spine diseases: A systematic review.

Natural Language Processing (NLP) is a discipline at the intersection between Computer Science (CS), Artificial Intelligence (AI), and Linguistics that leverages unstructured human-interpretable (natural) language text. In recent years, it gained momentum also in health-related applications and research. Although preliminary, studies concerning Low Back Pain (LBP) and other related spine disorders with relevant applications of NLP methodologies have been reported in the literature over the last few years. It motivated us to systematically review the literature comprised of two major public databases, PubMed and Scopus. To do so, we first formulated our research question following the PICO guidelines. Then, we followed a PRISMA-like protocol by performing a search query including terminologies of both technical (e.g., natural language and computational linguistics) and clinical (e.g., lumbar and spine surgery) domains. We collected 221 non-duplicated studies, 16 of which were eligible for our analysis. In this work, we present these studies divided into sub-categories, from both tasks and exploited models' points of view. Furthermore, we report a detailed description of techniques used to extract and process textual features and the several evaluation metrics used to assess the performance of the NLP models. However, what is clear from our analysis is that additional studies on larger datasets are needed to better define the role of NLP in the care of patients with spinal disorders.

Linguistically-Based Comparison of Different Approaches to Building Corpora for Text Simplification: A Case Study on Italian.

In this paper, we present an overview of existing parallel corpora for Automatic Text Simplification (ATS) in different languages focusing on the approach adopted for their construction. We make the main distinction between manual and (semi)-automatic approaches in order to investigate in which respect complex and simple texts vary and whether and how the observed modifications may depend on the underlying approach. To this end, we perform a two-level comparison on Italian corpora, since this is the only language, with the exception of English, for which there are large parallel resources derived through the two approaches considered. The first level of comparison accounts for the main types of sentence transformations occurring in the simplification process, the second one examines the results of a linguistic profiling analysis based on Natural Language Processing techniques and carried out on the original and the simple version of the same texts. For both levels of analysis, we chose to focus our discussion mostly on sentence transformations and linguistic characteristics that pertain to the morpho-syntactic and syntactic structure of the sentence.

Food semantics on pro-anorexia websites in Italy.

INTRODUCTION: The term pro-ana (pro-anorexia) means the spread of restrictive eating behaviors and anorectic advices in virtual spaces written by teenagers. The purpose of this pilot study consists in a qualitative and quantitative analysis of foods contained in a linguistic corpus made up of users' comments on pro-ana websites. METHOD: The corpus of pro-ana websites was analyzed through the T2K tool based on word-frequency processing. RESULTS: The results show conversations regarding beverages, products of vegetable origin (fruit, vegetables) and low-calorie foods, with a tendency to limit the fear linked to the choice of high-calorie foods through reassuring and reconcilable language labels ("light", "sugar free"). CONCLUSIONS: These findings specify the food semantics on pro-ana websites associated to an anorectic vocabulary with restrictive diets. The results could be used to characterize the most common food as risk factors within the eating disorders framework.

Overexpression of the cohesin-core subunit SMC1A contributes to colorectal cancer development.

BACKGROUND: Cancer cells are characterized by chromosomal instability (CIN) and it is thought that errors in pathways involved in faithful chromosome segregation play a pivotal role in the genesis of CIN. Cohesin forms a large protein ring that binds DNA strands by encircling them. In addition to this central role in chromosome segregation, cohesin is also needed for DNA repair, gene transcription regulation and chromatin architecture. Though mutations in both cohesin and cohesin-regulator genes have been identified in many human cancers, the contribution of cohesin to cancer development is still under debate. METHODS: Normal mucosa, early adenoma, and carcinoma samples deriving from 16 subjects affected by colorectal cancer (CRC) were analyzed by OncoScan for scoring both chromosome gains and losses (CNVs) and loss of heterozygosity (LOH). Then the expression of SMC1A was analyzed by immunochemistry in 66 subjects affected by CRC. The effects of SMC1A overexpression and mutated SMC1A were analyzed in vivo using immunocompromised mouse models. Finally, we measured global gene expression profiles in induced-tumors by RNA-seq. RESULTS: Here we showed that SMC1A cohesin core gene was present as extra-copies, mutated, and overexpressed in human colorectal carcinomas. We then demonstrated that cohesin overexpression led to the development of aggressive cancers in immunocompromised mice through gene expression dysregulation. CONCLUSION: Collectively, these results support a role of defective cohesin in the development of human colorectal cancer.