Application of the eye tracking technology in medicine: a bibliometric analysis

Eye tracking provides a quantitative measure of eye movements during different activities. We report the results from a bibliometric analysis to investigate trends in eye tracking research applied to the study of different medical conditions. We conducted a search on the Web of Science Core Collection (WoS) database and analyzed the dataset of 2456 retrieved articles using VOSviewer and the Bibliometrix R package. The most represented area was psychiatry (503, 20.5%) followed by neuroscience (465, 18.9%) and psychology developmental (337, 13.7%). The annual scientific production growth was 11.14% and showed exponential growth with three main peaks in 2011, 2015 and 2017. Extensive collaboration networks were identified between the three countries with the highest scientific production, the USA (35.3%), the UK (9.5%) and Germany (7.3%). Based on term co-occurrence maps and analyses of sources of articles, we identified autism spectrum disorders as the most investigated condition and conducted specific analyses on 638 articles related to this topic which showed an annual scientific production growth of 16.52%. The majority of studies focused on autism used eye tracking to investigate gaze patterns with regards to stimuli related to social interaction. Our analysis highlights the widespread and increasing use of eye tracking in the study of different neurological and psychiatric conditions

Iterative threshold‐based Naïve bayes classifer

The iterative Threshold-based Naïve Bayes (iTb-NB) classifier is introduced as a (simple) improved version of the previously introduced non-iterative Threshold-based Naïve Bayes (Tb-NB) classifier. iTb-NB starts from a Natural Language text-corpus and allows the user to quantify with a numeric value a sentiment (positive or negative) from a specific test. Differently from Tb-NB, iTb-NB is an algorithm aimed at estimating multiple threshold values that concur to refine Tb-NB’s decision rules when classifying a text into positive (negative) based on its content. Observations with sentiment scores close to the threshold are marked to be reclassified, hence a new decision rule is defined for them. Such “iterative” process improves the quality of predictions w.r.t. Tb-NB but keeping the possibility to utilize its results as the input of useful post-hoc analyses. The effectiveness of iTb-NB is evaluated analyzing hotel guests’ reviews from all hotels located in the Sardinia region and available on Booking.com. Furthermore, iTb-NB is compared with Tb-NB in terms of model accuracy, resistance to noise, and computational efficiency

Using sentiment analysis to evaluate the impact of the COVID-19 outbreak on Italy’s country reputation and stock market performance

During the recent Coronavirus disease 2019 (COVID-19) outbreak, the microblogging service Twitter has been widely used to share opinions and reactions to events. Italy was one of the frst European countries to be severely afected by the outbreak and to establish lockdown and stay-at-home orders, potentially leading to country reputation damage. We resort to sentiment analysis to investigate changes in opinions about Italy reported on Twitter before and after the COVID-19 outbreak. Using diferent lexicons-based methods, we fnd a breakpoint corresponding to the date of the frst established case of COVID-19 in Italy that causes a relevant change in sentiment scores used as a proxy of the country’s reputation. Next, we demonstrate that sentiment scores about Italy are associated with the values of the FTSE-MIB index, the Italian Stock Exchange main index, as they serve as early detection signals of changes in the values of FTSE-MIB. Lastly, we evaluate whether diferent machine learning classifers were able to determine the polarity of tweets posted before and after the outbreak with a diferent level of accuracy

Gluten-Free Diet and Other Celiac Disease Therapies: Current Understanding and Emerging Strategie

A lifelong gluten-free diet (GFD) is the only treatment for celiac disease and other gluten-related disorders. Nevertheless, strict adherence to the GFD is often challenging due to concerns about social isolation, risk of gluten contaminations, high cost, poor quality and the taste of gluten-free products. Moreover, although the GFD is effective in achieving mucosal healing, it may lead to dietary imbalances due to nutrient deficiencies over a long period of time. To overcome these issues, several gluten-free wheat flours have been developed to create products that closely resemble their gluten-containing counterparts. Furthermore, given the critical importance of adhering to the GFD, it becomes essential to promote adherence and monitor possible voluntary or involuntary transgressions. Various methods, including clinical assessment, questionnaires, serology for celiac disease, duodenal biopsies and the detection of Gluten Immunogenic Peptides (GIPs) are employed for this purpose, but none are considered entirely satisfactory. Since adherence to the GFD poses challenges, alternative therapies should be implemented in the coming years to improve treatment efficacy and the quality of life of patients with celiac disease. The aim of this narrative review is to explore current knowledge of the GFD and investigate its future perspectives, focusing on technology advancements, follow-up strategies and insights into a rapidly changing future

A mouse mammary tumor virus env-like exogenous sequence is strictly related to progression of human sporadic breast carcinoma

A viral etiology of human breast cancer (HBC) has been postulated for decades since the identification of mouse mammary tumor virus (MMTV). The detection of MMTV env-like exogenous sequences (MMTVels) in 30% to 40% of invasive HBCs increased attention to this hypothesis. Looking for MMTVels during cancer progression may contribute to a better understanding of their role in HBC. Herein, we analyzed HBC preinvasive lesions for the presence of MMTVels. Samples were obtained by laser microdissection of FFPE tissues: 20 usual-type ductal hyperplasias, 22 atypical ductal hyperplasias (ADHs), 49 ductal carcinomas in situ (DCISs), 20 infiltrating ductal carcinomas (IDCs), and 26 normal epithelial cells collateral to a DCIS or an IDC. Controls included reductive mammoplastic tissue, thyroid and colon carcinoma, and blood samples from healthy donors. MMTVels were detected by fluorescence-nested PCR. DNA samples from the tissues of nine patients were analyzed by real-time quantitative PCR, revealing a different viral load correlated with stage of progression. Furthermore, as never previously described, the presence of MMTVels was investigated by chromogenic in situ hybridization. MMTVels were found in 19% of normal epithelial cells collateral to a DCIS or an IDC, 27% of ADHs, 82% of DCISs, and 35% of IDCs. No MMTVels were found in the control samples. Quantitative PCR and chromogenic in situ hybridization confirmed these results. These data could contribute to our understanding of the role of MMTVels in HBC. (Am J Pathol 2011, 179:2083-2090; DOI: 10.1016/j.ajpath.2011.06.046

High prevalence of clustered tuberculosis cases in peruvian migrants in Florence, Italy.

Tuberculosis is a leading cause of morbidity for Peruvian migrants in Florence, Italy, where they account for about 20% of yearly diagnosed cases. A retrospective study on cases notified in Peruvian residents in Florence in the period 2001-2010 was carried out and available Mycobacterium tuberculosis strains were genotyped (MIRU-VNTR-24 and Spoligotyping). One hundred thirty eight cases were retrieved. Genotyping performed in 87 strains revealed that 39 (44.8%) belonged to 12 clusters. Assuming that in each cluster the transmission of tuberculosis from the index case took place in Florence, a large proportion of cases could be preventable by improving early diagnosis of contagious cases and contact tracing