The flashbulb-like nature of memory for the first COVID-19 case and the impact of the emergency. A cross-national survey.

Flashbulb memories (FBMs) refer to vivid and long-lasting autobiographical memories for the circumstances in which people learned of a shocking and consequential public event. A cross-national study across eleven countries aimed to investigate FBM formation following the first COVID-19 case news in each country and test the effect of pandemic-related variables on FBM. Participants had detailed memories of the date and others present when they heard the news, and had partially detailed memories of the place, activity, and news source. China had the highest FBM specificity. All countries considered the COVID-19 emergency as highly significant at both the individual and global level. The Classification and Regression Tree Analysis revealed that FBM specificity might be influenced by participants' age, subjective severity (assessment of COVID-19 impact in each country and relative to others), residing in an area with stringent COVID-19 protection measures, and expecting the pandemic effects. Hierarchical regression models demonstrated that age and subjective severity negatively predicted FBM specificity, whereas sex, pandemic impact expectedness, and rehearsal showed positive associations in the total sample. Subjective severity negatively affected FBM specificity in Turkey, whereas pandemic impact expectedness positively influenced FBM specificity in China and negatively in Denmark.

Perceived climate change risk and global green activism among young people.

In recent years, the increasing number of natural disasters has raised concerns about the sustainability of our planet's future. As young people comprise the generation that will suffer from the negative effects of climate change, they have become involved in a new climate activism that is also gaining interest in the public debate thanks to the Fridays for Future (FFF) movement. This paper analyses the results of a survey of 1,138 young people in a southern Italian region to explore their perceptions of the extent of environmental problems and their participation in protests of green movements such as the FFF. The statistical analyses perform an ordinal classification tree using an original impurity measure considering both the ordinal nature of the response variable and the heterogeneity of its ordered categories. The results show that respondents are concerned about the threat of climate change and participate in the FFF to claim their right to a healthier planet and encourage people to adopt environmentally friendly practices in their lifestyles. Young people feel they are global citizens, connected through the Internet and social media, and show greater sensitivity to the planet's environmental problems, so they are willing to take effective action to demand sustainable policies from decision-makers. When planning public policies that will affect future generations, it is important for policymakers to know the demands and opinions of key stakeholders, especially young people, in order to plan the most appropriate measures, such as climate change mitigation.

Effectiveness of benralizumab in severe eosinophilic asthma: Distinct sub-phenotypes of response identified by cluster analysis.

BACKGROUND: Benralizumab is effective in severe eosinophilic asthma (SEA), but suboptimal responses are observed in some patients. Although several factors have been associated with benralizumab response, no cluster analysis has yet been undertaken to identify different responsiveness sub-phenotypes. OBJECTIVE: To identify SEA sub-phenotypes with differential responsiveness to benralizumab. METHODS: One hundred and five patients diagnosed with SEA who had completed 6 months of benralizumab treatment were included in a hierarchical cluster analysis based on a set of clinical variables that can be easily collected in routine practice (age, age at disease onset, disease length, allergen sensitization status, blood eosinophil count, IgE levels, FEV1 % predicted, nasal polyposis, bronchiectasis). RESULTS: Four clusters were identified: Clusters 2 and 3 included patients with high levels of both IgE and eosinophils (type-2 biomarkers high), whereas Clusters 1 and 4 included patients with only one type-2 biomarker at a high level: IgE in Cluster 1 and eosinophils in Cluster 4. Clusters 2 and 3 (both type-2 biomarkers high) showed the highest response rate to benralizumab in terms of elimination of exacerbations (79% and 80% respectively) compared to Clusters 1 and 4 (52% and 60% respectively). When super-response (the absence of exacerbation without oral corticosteroid use) was assessed, Cluster 2, including patients with more preserved lung function than the other clusters, but comparable exacerbation rate, oral corticosteroid use and symptom severity, was the most responsive cluster (87.5% of patients). CONCLUSIONS: Our cluster analysis identified benralizumab differential response sub-phenotypes in SEA, with the potential of improving disease treatment and precision management.

Effectiveness and safety of dupilumab in patients with chronic rhinosinusitis with nasal polyps and associated comorbidities: a multicentric prospective study in real life.

BACKGROUND: Biologics are currently one of the main treatment options for a number of diseases. The IgG4 monoclonal antibody dupilumab targets the Interleukin-4 receptor alpha chain, thus preventing the biological effects of the cytokines IL-4 and IL-13, that are essential for the Th2 response. Several controlled trials showed that dupilumab is effective and safe in patients with atopic dermatitis (AD), severe asthma and chronic rhinosinusitis with nasal polyps (CRSwNP), thus resulting in approval by regulatory agencies. Aim of the study was to evaluate the efficacy and safety of dupilumab in adult patients with CRSwNP stratified by common overlapping comorbid conditions. METHODS: We performed a multicenter, observational, prospective study enrolling adult patients with severe CRSwNP who had started dupilumab treatment in the context of standard care from January 2021 to October 2021. Data were collected from twentynine Italian secondary care centers for allergy and clinical immunology, all of which were part of the Italian Society of Allergy, Asthma and Clinical Immunology (SIAAIC). A number of efficacy parameters were used. Patient data were compared using the Wilcoxon test for paired data. All statistical analyses were performed with SPSS version 20 (IBM, Armonk, NY, USA). RESULTS: In total, 82 patients with nasal polyposis were identified. A significant improvement was detected for all the applied efficacy parameters, i.e. 22-item Sino-Nasal Outcome Test (SNOT-22) and bilateral endoscopic nasal polyp score (NPS) scores for CRSwNP, Rhinitis Control Scoring System (RCSS) and Rhinoconjunctivitis Quality of Life Questionnaire (RQLQ) scores for allergic perennial rhinitis, Forced Expiratory Volume in the 1st second (FEV1) and Asthma Quality of Life Questionnaire (AQLQ) scores for asthma, Eczema Area and Severity Index (EASI) and Dermatology Life Quality Index (DLQI) scores for AD. A non-significant improvement was also obtained in the Urticaria Activity Score over 7 days (UAS7) for chronic spontaneous urticaria. Treatment with dupilumab was well tolerated. CONCLUSIONS: These data suggest that dupilumab treatment in patients suffering from CRSwNP and associated comorbidities may be suitable. Such outcome, although confirmation by trials is warranted, suggests the possibility to treat different disorders with a single therapy, with favorable effects especially under the cost-effectiveness aspect.

Improvement of MEFV gene variants classification to aid treatment decision making in familial Mediterranean fever.

OBJECTIVE: FMF is an inherited autoinflammatory syndrome caused by mutations in the MEFV gene. MEFV variants are still largely classified as acvariant of uncertain significance, or with unresolved classification, posing significant challenges in FMF diagnosis. Rare Exome Variant Ensemble Learner (REVEL) is a recently developed variant metapredictor tool. To reduce the number of MEFV variants with ambiguous classification, we extracted REVEL scores for all missense variants present in the INFEVERS database, and analysed its correlation with expert-based classification and localization in the MEFV-encoded pyrin functional domains. METHODS: The data set of 216 MEFV missense variants was divided into four categories (likely benign, variant of uncertain significance, likely pathogenic and unresolved). Variants were plotted onto the pyrin protein, the distribution of REVEL scores in each category was computed and means, confidence intervals, and area under the receiver operating curve were calculated. RESULTS: We observed a non-random distribution of pathogenic variants along the pyrin functional domains. The REVEL scores demonstrated a good correlation with the consensus classification of the International Study Group for Systemic Autoinflammatory Diseases. Sensitivity, specificity and accuracy were calculated for different cut-off values of REVEL scores and a gene-specific-threshold of 0.298 was computed with confidence boundary limits. This cut-off value allowed us to propose a reclassification of 96 MEFV gene variants, thus reducing the variant of uncertain significance proportion from 61.6% to 17.6%. CONCLUSION: The combination of available expert information with sensitive predictor tools could result in a more accurate interpretation of clinical consequences of MEFV gene variants, and to a better genetic counselling and patient management.

A text data mining approach to the study of emotions triggered by new advertising formats during the COVID-19 pandemic.

Under the influence of the health emergency triggered by the COVID-19 pandemic, many brands changed their communication strategy and included more or less explicit references to the principles of solidarity and fraternity in their TV commercials to boost the confidence and hope of Italian families during the lockdown. The traditional attitudes of the advertising format, which focused on product characteristics, were relegated to the background in order to reinforce the "brand image" through words, signs, hashtags and music that spread empathetic messages to all those who needed to regain hope and trust in a time of extreme emotional fragility. The objective of this paper is to identify the emotions and brand awareness during the lockdown using text mining techniques by measuring customer sentiment expressed on the Twitter social network. Our proposal starts from an unstructured corpus of 20,982 tweets processed with text data mining techniques to identify patterns and trends in people's posts related to specific hashtags and TV ads produced during the COVID-19 pandemic. The innovations in the brand's advertising among consumers seem to have triggered some sense of appreciation and gratitude, as well as a strong sense of belonging that was not present before, as the TV ads were perceived as a disruptive element in consumers' tweets. Although this effect is clearly documented, in this paper we demonstrate its transitory nature, in the sense that the frequency of occurrence of terms associated with an emotional dimension peaks during the weeks of lockdown, and then gradually decreases.