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This narrative review aims to update the current evidence and offer insight into the new non-invasive ultrasound techniques used to early identify degenerative vascular changes in subjects with periodontitis and to investigate if these methodologies could be useful to identify subclinical cardiovascular disease (CVD) dysfunction in periodontitis patients and to monitor changes in CVD risk after periodontal treatment.

Simona Santonocito, Alessandro Polizzi, Giuseppe Palazzo, Francesco Indelicato, Gaetano Isola Department of General Surgery and Surgical-Medical Specialties, School of Dentistry, University of Catania, Catania, ItalyCorrespondence: Gaetano IsolaUnit of Periodontology, Department of General Surgery and Surgical-Medical Specialties, School of Dentistry, University of Catania, Via S. Sofia 78, Catania, 95123, ItalyTel/Fax +390953782453Email gaetano.isola@unict.itAbstract: In the last few decades, growing evidence have shown a possible impact of diet and nutrients on oral health. This review aims to describe, in the light of current knowledge, the role of diet, nutrients, and micronutrients in periodontal health and periodontal diseases. A variety of macronutrients and micronutrients could have an impact on periodontal health. The balanced intake of unprocessed complex carbohydrates, vegetable proteins, omega-3 fatty acids, minerals, and vitamins positively affects periodontal inflammation. On the other way, refined carbohydrates, non-vegetable proteins, proinflammatory saturated fatty acids and an unbalanced supply of vitamins and minerals may increase periodontal inflammation. This review will discuss the current evidence that shows how a healthy and balanced diet has anti-inflammatory and protective effects on periodontal health. Therefore, it appears that adopting a correct lifestyle and diet should be encouraged in patients with oral and periodontal disease.Keywords: periodontitis, nutrition, diet, macronutrients, micronutrients, oral health

The de novo design of small molecule-binding proteins has seen exciting recent progress; however, high-affinity binding and tunable specificity typically require laborious screening and optimization after computational design. We developed a computational procedure to design a protein that recognizes a common pharmacophore in a series of poly(ADP-ribose) polymerase-1 inhibitors. One of three designed proteins bound different inhibitors with affinities ranging from

The continual emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOCs) poses a major challenge to vaccines and antiviral therapeutics due to their extensive evasion of immunity. Aiming to develop potent and broad-spectrum anticoronavirus inhibitors, we generated A1-(GGGGS)7-HR2m (A1L35HR2m) by introducing an angiotensin-converting enzyme 2 (ACE2)-derived peptide A1 to the N terminus of the viral HR2-derived peptide HR2m through a long flexible linker, which showed significantly improved antiviral activity. Further cholesterol (Chol) modification at the C terminus of A1L35HR2m greatly enhanced the inhibitory activities against SARS-CoV-2, SARS-CoV-2 VOCs, SARS-CoV, and Middle East respiratory syndrome coronavirus (MERS-CoV) pseudoviruses, with IC50 values ranging from 0.16 to 5.53 nM. A1L35HR2m-Chol also potently inhibits spike-protein-mediated cell-cell fusion and the replication of authentic Omicron BA.2.12.1, BA.5, and EG.5.1. Importantly, A1L35HR2m-Chol distributed widely in respiratory tract tissue and had a long half-life (>10 h) in vivo. Intranasal administration of A1L35HR2m-Chol to K18-hACE2 transgenic mice potently inhibited Omicron BA.5 and EG.5.1 infection both prophylactically and therapeutically.

Evidence to date indicates that compassion and empathy are health-enhancing qualities. Research points to interventions and practices involving compassion and empathy being beneficial, as well as being salient outcomes of contemplative practices such as mindfulness. Advancing the science of compassion and empathy requires that we select measures best suited to evaluating effectiveness of training and answering research questions. The objective of this scoping review was to 1) determine what instruments are currently available for measuring empathy and compassion, 2) assess how and to what extent they have been validated, and 3) provide an online tool to assist researchers and program evaluators in selecting appropriate measures for their settings and populations. A scoping review and broad evidence map were employed to systematically search and present an overview of the large and diverse body of literature pertaining to measuring compassion and empathy. A search string yielded 19,446 articles, and screening resulted in 559 measure development or validation articles reporting on 503 measures focusing on or containing subscales designed to measure empathy and/or compassion. For each measure, we identified the type of measure, construct being measured, in what context or population it was validated, response set, sample items, and how many different types of psychometrics had been assessed for that measure. We provide tables summarizing these data, as well as an open-source online interactive data visualization allowing viewers to search for measures of empathy and compassion, review their basic qualities, and access original citations containing more detail. Finally, we provide a rubric to help readers determine which measure(s) might best fit their context.

Cyber-wisdom is the ability to know and do the right thing at the right time, when using digital technologies, and is a concept that is gaining attention from educators. Whilst the theory and practice of cyber-wisdom education is established, to date there has been no attempt to investigate how the virtue of cyber-wisdom might be measured. This is a lacuna as it limits future research in the area, including, in particular, proximal evaluations of cyber-wisdom interventions. This article introduces a new four-component measure of cyber-wisdom, which is relevant to how the virtue may be cultivated in practice via formal education and the teaching of what is generally referred to as digital citizenship education. The measure was piloted with 1,331 13--16 year-olds. The findings provide initial evidence that cyber-wisdom literacy, reasoning, reflection, and motivation can be measured. This study provides preliminary validation of cyber-wisdom sub-measures that might be used in evaluations of educational interventions that seek to help children and adolescents live with wisdom in the digital age.

There is a dearth of studies exploring how younger children engage in civic life, what may be expected of them given their age, and what instruments may be used to capture their levels of civic engagement. Addressing these questions, this article presents key findings from a pilot study that aimed to create a validated instrument designed to measure the civic engagement of primary school children. Based on a survey administered to 655 primary school children aged 9-11 across England, this article focuses on the new measure that was specifically designed, and then tested and validated through both exploratory and confirmatory analyses. The findings validate a tripartite measure of civic engagement that assesses the civic attitudes, actions and awareness of 9-11-year-olds. This measure was found to be both practical and efficient in its administration, and it has been shown to be easily comprehensible by this age group. This new measure addresses an important gap in the literature on civic engagement in children, providing researchers with a validated tool to effectively measure civic engagement in 9-11-year-olds. The findings have implications for both researchers and educators interested in designing and evaluating interventions aimed at promoting civic engagement among younger children.

Objective: Self-report symptom inventories are commonly used in adult ADHD assessment, and research indicates they should be interpreted with caution. This study investigated one self-report symptom inventory for adult ADHD in a clinical sample. Method: Archival data were used to evaluate diagnostic utility of the Conners Adult ADHD Rating Scale--Self-Report: Long Version (CAARS-S:L) in a sample of 122 adults seeking ADHD assessment. Results: Overall, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) estimates for the ADHD Index and other CAARS-S:L scales demonstrated weak accuracy. Anxiety and depression were the most common diagnoses present when a false positive on the ADHD Index was observed. PPV and specificity for the ADHD Index were higher in males compared to females. Conclusion: The CAARS-S:L may be useful for screening purposes in some cases, but should not be the main method used for diagnostic purposes. Clinical implications of findings are discussed.

The promise of community benefit from health data linked at scale is often missing the perspective of communities themselves. This paper outlines a recent project on developing a peer research and public engagement methodology to build community-designed linked and open wellbeing data hubs. Drawing on action research and appreciative inquiry, we aimed to develop a novel method to engage community on the use of linked local data. In Spring 2023 we recruited and trained 15 community researchers in Widnes, UK to co-design and run a project on what feeling well meant for their community. We trained our community researchers in listening skills, methods, and data concepts. Over Summer 2023, they interviewed over 200 of their fellow residents. We then ran three design workshops to analyse their findings and co-design a data and community insights hub with local policymakers and voluntary sector representatives. Through repeated, comparative semi-structured interviews we tracked the community researchers’ progress. We used thematic analysis to explore the benefits and challenges at each stage of the project: recruitment, training, and field work. Benefits ranged from the practical value of capacity building through the research training to the key role of confidence in how community researchers perceived their own success during the project. Challenges ranged from more esoteric concepts like managing expectations of impact to practical concerns around diversity and interview recruitment. Overall, the project evidenced the value of peer research methodologies in involving public in data science both for the participants but also to wider community.

BackgroundIn obstructive hypertrophic cardiomyopathy (HOCM), disopyramide is used in patients who remain symptomatic despite β-blockers or verapamil. However, effectiveness of disopyramide therapy has not been clearly established due to inconsistent definition of responders and the insufficient length of follow-ups reported in literature. To address these shortcomings, we have conducted a retrospective analysis from detailed databases with long follow-up, from two HCM Referral Centers.Methods62 symptomatic HOCM patients (43% women, age 52 ± 14 years) with left ventricular (LV) outflow tract gradient (LVOTG) ≥ 50 mmHg at rest or during provocation, were recruited from two Italian Centers. Disopyramide was added as second-line therapy in the patients in whom symptoms persisted despite classic pharmacologic treatment. Patients in NYHA class > II at baseline who reached NYHA class II or I, and patients in NYHA class II at baseline who reached NYHA class I or symptoms stabilization were defined as responders.ResultsAt follow-up, (mean 4.4 years, IQR 1.1–6.6 years), 47 patients (76%) were responders, whereas 15 (24%) were no-responders. Responders showed larger LV diastolic volume index (LVEDVi) at baseline as compared to no-responders (61 ± 14 vs. 49 ± 16 ml, respectively, p = 0.018), and, at follow-up, reached lower LVOTG than no-responders (43 ± 32 vs. 66 ± 28 mmHg, respectively, p = 0.013), with a LVOTG

BackgroundHeterogeneous mental health outcomes during the COVID-19 pandemic are documented in the general population. Such heterogeneity has not been systematically assessed in youth with autism spectrum disorder (ASD) and related neurodevelopmental disorders (NDD). To identify distinct patterns of the pandemic impact and their predictors in ASD/NDD youth, we focused on pandemic-related changes in symptoms and access to services.MethodsUsing a naturalistic observational design, we assessed parent responses on the Coronavirus Health and Impact Survey Initiative (CRISIS) Adapted For Autism and Related neurodevelopmental conditions (AFAR). Cross-sectional AFAR data were aggregated across 14 European and North American sites yielding a clinically well-characterized sample of N = 1275 individuals with ASD/NDD (age = 11.0 ± 3.6 years; n females = 277). To identify subgroups with differential outcomes, we applied hierarchical clustering across eleven variables measuring changes in symptoms and access to services. Then, random forest classification assessed the importance of socio-demographics, pre-pandemic service rates, clinical severity of ASD-associated symptoms, and COVID-19 pandemic experiences/environments in predicting the outcome subgroups.ResultsClustering revealed four subgroups. One subgroup-broad symptom worsening only (20%)-included youth with worsening across a range of symptoms but with service disruptions similar to the average of the aggregate sample. The other three subgroups were, relatively, clinically stable but differed in service access: primarily modified services (23%), primarily lost services (6%), and average services/symptom changes (53%). Distinct combinations of a set of pre-pandemic services, pandemic environment (e.g., COVID-19 new cases, restrictions), experiences (e.g., COVID-19 Worries), and age predicted each outcome subgroup.LimitationsNotable limitations of the study are its cross-sectional nature and focus on the first six months of the pandemic.ConclusionsConcomitantly assessing variation in changes of symptoms and service access during the first phase of the pandemic revealed differential outcome profiles in ASD/NDD youth. Subgroups were characterized by distinct prediction patterns across a set of pre- and pandemic-related experiences/contexts. Results may inform recovery efforts and preparedness in future crises; they also underscore the critical value of international data-sharing and collaborations to address the needs of those most vulnerable in times of crisis.

Educationalists', researchers', and policy makers' work on children's digital resilience has marginalised the role of the broader context within which digital resilience is constituted, experienced and derived. We aimed to address this lacuna by exploring how pre-teen's digital resilience operates as a dynamic socio-ecological process. Addressing this aim, we employed participatory methods and thematically analysed eight focus groups with children aged 8-12 years (n = 59) and 20 telephone interviews with parents/carers and teachers of 8-12-year-olds and internet safety experts to examine this issue. We used purposive sampling and collected data over three months (January-March 2020). Our analysis constructed a matrix of main themes, constituent, and cross-cutting sub-themes. By placing this within a socio-ecological framework, we illustrate how pre-teens' digital resilience operates within and across differing four levels (individual, home, community and societal) and four domains (learning, recognising, managing, and recovery). The paper advances the literature by illustrating how children can be supported to build and show digital resilience within and across different levels and domains. It is argued that digital resilience should be re-conceptualised as a collective endeavour involving children at an individual level, parents/carers within home environments, youth workers, civil society, teachers, and schools at a community level, along with governments, policymakers, and the education system and internet corporations at a societal level. We conclude by providing practice and research recommendations guiding those supporting children to facilitate opportunities to thrive online.

Background: Retaining highly qualified science, technology, engineering, and mathematics (STEM) teachers is imperative for meeting demands of the twenty-first century STEM workforce. While multiple studies have revealed several factors that influence teacher retention, little work has examined how these factors interact with one another. This study explored the relationship between two critical factors that relate to teachers' decisions to remain in the profession: teacher identity and communities of practice (CoP) networks. Results: Drawing upon scholarship on science teacher identity, CoP, and social network theory, we demonstrate a quantitative relationship between perceived network bridging roles and career commitment, which is mediated through teacher identity. Conclusions: The findings from this study have both implications for scholarship in teacher retention and science teacher identity development. Potential solutions for improving novice teachers' self-image through providing opportunities to grow their professional networks both locally and regionally/nationally are suggested.