Conectar
by Michele Salvagno, Alessandro De Cassai, Stefano Zorzi, Mario Zaccarelli, Marco Pasetto, Elda Diletta Sterchele, Dmytro Chumachenko, Alberto Giovanni Gerli, Razvan Azamfirei, Fabio Silvio Taccone
Natural Language Processing (NLP) is a subset of artificial intelligence that enables machines to understand and respond to human language through Large Language Models (LLMs)‥ These models have diverse applications in fields such as medical research, scientific writing, and publishing, but concerns such as hallucination, ethical issues, bias, and cybersecurity need to be addressed. To understand the scientific community’s understanding and perspective on the role of Artificial Intelligence (AI) in research and authorship, a survey was designed for corresponding authors in top medical journals. An online survey was conducted from July 13th, 2023, to September 1st, 2023, using the SurveyMonkey web instrument, and the population of interest were corresponding authors who published in 2022 in the 15 highest-impact medical journals, as ranked by the Journal Citation Report. The survey link has been sent to all the identified corresponding authors by mail. A total of 266 authors answered, and 236 entered the final analysis. Most of the researchers (40.6%) reported having moderate familiarity with artificial intelligence, while a minority (4.4%) had no associated knowledge. Furthermore, the vast majority (79.0%) believe that artificial intelligence will play a major role in the future of research. Of note, no correlation between academic metrics and artificial intelligence knowledge or confidence was found. The results indicate that although researchers have varying degrees of familiarity with artificial intelligence, its use in scientific research is still in its early phases. Despite lacking formal AI training, many scholars publishing in high-impact journals have started integrating such technologies into their projects, including rephrasing, translation, and proofreading tasks. Efforts should focus on providing training for their effective use, establishing guidelines by journal editors, and creating software applications that bundle multiple integrated tools into a single platform.
by Sarah J. Wright, Michele J. Grimm
The brachial plexus is a set of nerves that innervate the upper extremity and may become injured during the birthing process through an injury known as Neonatal Brachial Plexus Palsy. Studying the mechanisms of these injuries on infant cadavers is challenging due to the justifiable sensitivity surrounding testing. Thus, these specimens are generally unavailable to be used to investigate variations in brachial plexus injury mechanisms. Finite Element Models are an alternative way to investigate the response of the neonatal brachial plexus to loading. Finite Element Models allow a virtual representation of the neonatal brachial plexus to be developed and analyzed with dimensions and mechanical properties determined from experimental studies. Using ABAQUS software, a two-dimensional brachial plexus model was created to analyze how stresses and strains develop within the brachial plexus. The main objectives of this study were (1) to develop a model of the brachial plexus and validate it against previous literature, and (2) to analyze the effect of stress on the nerve roots based on variations in the angles between the nerve roots and the spinal cord. The predicted stress for C5 and C6 was calculated as 0.246 MPa and 0.250 MPa, respectively. C5 and C6 nerve roots experience the highest stress and the largest displacement in comparison to the lower nerve roots, which correlates with clinical patterns of injury. Even small (+/- 3 and 6 degrees) variations in nerve root angle significantly impacted the stress at the proximal nerve root. This model is the first step towards developing a complete three-dimensional model of the neonatal brachial plexus to provide the opportunity to more accurately assess the effect of the birth process on the stretch within the brachial plexus and the impact of biological variations in structure and properties on the risk of Neonatal Brachial Plexus Palsy.
by Francesco Di Gennaro, Francesco Vladimiro Segala, Giacomo Guido, Mariacristina Poliseno, Laura De Santis, Alessandra Belati, Carmen Rita Santoro, Irene Francesca Bottalico, Carmen Pellegrino, Roberta Novara, Luisa Frallonardo, Mariangela Cormio, Michele Camporeale, Sergio Cotugno, Vincenzo Giliberti, Stefano Di Gregorio, Valentina Totaro, Nicola Catucci, Anna De Giosa, Roberta Giusto, Ilaria Viviana Lanera, Gioacchino Angarano, Sergio Lo Caputo, Annalisa Saracino
High School students, recognized as a high-risk group for sexually transmitted infections (STIs), were the focal point of an educational campaign in Southern Italy to share information and good practices about STIs and HIV/AIDS. A baseline survey comprising 76 items was conducted via the REDCap platform to assess students’ initial knowledge, attitudes, and practices (KAP) related to STIs and HIV/AIDS. Sociodemographic variables were also investigated. The association between variables and KAP score was assessed by Kruskal-Wallis’ or Spearman’s test, as appropriate. An ordinal regression model was built to estimate the effect size, reported as odds ratio (OR) with a 95% confidence interval (CI), for achieving higher KAP scores among students features. On a scale of 0 to 29, 1702 participants achieved a median KAP score of 14 points. Higher scores were predominantly reported by students from classical High Schools (OR 3.19, 95% C.I. 1.60–6.33, p
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