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The “Healthcare workers’ wellbeing [Benessere Operatori]” project is an exploratory longitudinal study assessing healthcare workers’ mental health at three different time points over a 14-month period during the COVID-19 pandemic. We collected socio-demographic and work-related information and assessed the perceived social support, coping strategies, and levels of depression, anxiety, insomnia, anger, burnout, and PTSD symptoms. In total, 325 Italian healthcare workers (i.e. physicians, nurses, other healthcare workers, and clerks) participated in the first initial survey and either the second or third subsequent survey. Participants reported subclinical levels of psychiatric symptoms that remained mostly unchanged across time, except for an increase in stress, depression, state anger, and emotional exhaustion symptoms. Despite subclinical levels, healthcare workers’ distress can adversely affect the quality of care, patient satisfaction, and medical error rates. Therefore, implementing interventions to improve healthcare workers’ wellbeing is required.

Aims Alterations of the exocrine pancreas have been reported in type 1 diabetes, but their contribution to the pathogenesis of the disease is poorly understood. Here, we investigated markers of exocrine pancreas dysfunction in individuals at-risk of developing type 1 diabetes. Methods Serum P-amylase and lipase levels were assessed in samples obtained from healthy controls, patients with new onset type 1 diabetes, relatives participating to the TrialNet Pathway to Prevention who were, at blood collection, autoantibody negative or positive for a single autoantibody (low-risk individuals), and positive for multiple autoantibodies (high-risk individuals). Linear mixed models were adopted to estimate variation of pancreatic enzymes among the groups and to evaluate the influence of high-risk HLA genotypes and residual beta cell function on exocrine pancreas function. Results In adults, but not children, reduced levels of P-amylase and lipase were shown in at-risk individuals, including (for P-amylase levels only) those at low-risk, and in T1Dnew. Furthermore, while high-risk HLA genotypes negatively affected P-amylase levels in autoantibody negative adult individuals, fasting C-peptide levels did not correlate with pancreatic enzyme levels. Conclusions Exocrine pancreas dysfunction precedes the onset of type 1 diabetes in adult at-risk individuals and may be unrelated to fasting C-peptide levels.

Long-range gene editing by homology-directed repair (HDR) in hematopoietic stem/progenitor cells (HSPCs) often relies on viral transduction with recombinant adeno-associated viral vector (AAV) for template delivery. Here, we uncover unexpected load and prolonged persistence of AAV genomes and their fragments, which trigger sustained p53-mediated DNA damage response (DDR) upon recruiting the MRE11-RAD50-NBS1 (MRN) complex on the AAV inverted terminal repeats (ITRs). Accrual of viral DNA in cell-cycle-arrested HSPCs led to its frequent integration, predominantly in the form of transcriptionally competent ITRs, at nuclease on- and off-target sites. Optimized delivery of integrase-defective lentiviral vector (IDLV) induced lower DNA load and less persistent DDR, improving clonogenic capacity and editing efficiency in long-term repopulating HSPCs. Because insertions of viral DNA fragments are less frequent with IDLV, its choice for template delivery mitigates the adverse impact and genotoxic burden of HDR editing and should facilitate its clinical translation in HSPC gene therapy.

This contribution explores in a new statistical perspective the antibody responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in 141 coronavirus disease 2019 (COVID-19) patients exhibiting a broad range of clinical manifestations. This cohort accurately reflects the characteristics of the first wave of the SARS-CoV-2 pandemic in Italy. We determined the IgM, IgA, and IgG levels towards SARS-CoV-2 S1, S2, and NP antigens, evaluating their neutralizing activity and relationship with clinical signatures. Moreover, we longitudinally followed 72 patients up to 9 months postsymptoms onset to study the persistence of the levels of antibodies. Our results showed that the majority of COVID-19 patients developed an early virus-specific antibody response. The magnitude and the neutralizing properties of the response were heterogeneous regardless of the severity of the disease. Antibody levels dropped over time, even though spike reactive IgG and IgA were still detectable up to 9 months. Early baseline antibody levels were key drivers of the subsequent antibody production and the long-lasting protection against SARS-CoV-2. Importantly, we identified anti-S1 IgA as a good surrogate marker to predict the clinical course of COVID-19. Characterizing the antibody response after SARS-CoV-2 infection is relevant for the early clinical management of patients as soon as they are diagnosed and for implementing the current vaccination strategies.

During the last year, mass screening campaigns have been carried out to identify immunological response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and establish a possible seroprevalence. The obtained results gained new importance with the beginning of the SARS-CoV-2 vaccination campaign, as the lack of doses has persuaded several countries to introduce different policies for individuals who had a history of COVID-19. Lateral flow assays (LFAs) may represent an affordable tool to support population screening in low-middle-income countries, where diagnostic tests are lacking and epidemiology is still widely unknown. However, LFAs have demonstrated a wide range of performance, and the question of which one could be more valuable in these settings still remains. We evaluated the performance of 11 LFAs in detecting SARS-CoV-2 infection, analyzing samples collected from 350 subjects. In addition, samples from 57 health care workers collected at 21 to 24 days after the first dose of the Pfizer-BioNTech vaccine were also evaluated. LFAs demonstrated a wide range of specificity (92.31% to 100%) and sensitivity (50% to 100%). The analysis of postvaccination samples was used to describe the most suitable tests to detect IgG response against S protein receptor binding domain (RBD). Tuberculosis (TB) therapy was identified as a potential factor affecting the specificity of LFAs. This analysis identified which LFAs represent a valuable tool not only for the detection of prior SARS-CoV-2 infection but also for the detection of IgG elicited in response to vaccination. These results demonstrated that different LFAs may have different applications and the possible risks of their use in high-TB-burden settings. IMPORTANCE Our study provides a fresh perspective on the possible employment of SARS-CoV-2 LFA antibody tests. We developed an in-depth, large-scale analysis comparing LFA performance to enzyme-linked immunosorbent assay (ELISA) and electrochemiluminescence immunoassay (ECLIA) and evaluating their sensitivity and specificity in identifying COVID-19 patients at different time points from symptom onset. Moreover, for the first time, we analyzed samples of patients undergoing treatment for endemic poverty-related diseases, especially tuberculosis, and we evaluated the impact of this therapy on test specificity in order to assess possible performance in TB high-burden countries.

The possibility to rely on rapid and accurate diagnostic techniques has proved itself crucial during the last year to contain the spreading of SARS-CoV-2 infection [1]. Even if quantitative RT-PCR (RT-qPCR) on NasoPharyngeal Swabs (NPS) is still considered the standard for COVID19 diagnosis, saliva has been evaluated in several studies as a possible alternative to NPS and is currently extensively utilised in South Korea, Germany, and Japan [2, 3]. Nonetheless, the use of saliva is still debated, and a rigorous standardisation of the analysis protocol is greatly needed [4–6]. The application of point of care (POC) technologies on saliva, able to rapidly perform highly specific and sensitive molecular testing, could prove invaluable to allow the diagnosis also in challenging and remote settings by simplifying and speeding up the diagnostic process [1]. Acknowledgements:We thank DiaSorin Italia and Cepheid Italia for providing the reagents to perform the study free of charge.

BackgroundQuantitative RT-PCR on NasoPharyngeal Swab (NPS) is still considered the standard for the diagnosis of SARS-CoV-2 infection, even if saliva has been evaluated in several studies as a possible alternative. The use of point of care (POC) platforms, providing highly specific results performed on saliva could simplify the diagnosis of COVID-19 and contribute to contain the spreading of SARS-CoV-2.MethodsWe assess the sensitivity and specificity of molecular testing performed on saliva in comparison to NPS using two different POC platforms (DiaSorin Simplexa™ and Cepheid Xpert®). NPS and saliva were collected prospectically from asymptomatic health care workers and mildly symptomatic patients. Moreover, the stability of saliva samples after storage at -80°C for up to 45 days was tested.ResultsThe obtained results in comparison to NPS demonstrated for both DiaSorin Simplexa™ and Xpert® Xpress a specificity of 100% and a sensitivity of 90.24%. The overall agreement between the tests performed on saliva was 98%. A positive correlation in Ct values detected on saliva and on NPS was identified for all the targets shared by the tests in analysis (Orf1ab, E and N2). Both S Ct values and Orf1ab Ct values were not significantly different before and after the freezing in the tested saliva samples.ConclusionThe obtained results demonstrated an overall performance of saliva comparable to NPS, confirming that RT-PCR performed using POCs on saliva could represent a valid public health solution for controlling SARS-CoV-2 pandemic.

Alterations of the exocrine pancreas have been reported in type 1 diabetes, but their contribution to the pathogenesis of the disease is poorly understood. Here, we investigated markers of exocrine pancreas dysfunction in individuals at-risk of developing type 1 diabetes.Serum P-amylase and lipase levels were assessed in samples obtained from healthy controls, patients with new onset type 1 diabetes, relatives participating to the TrialNet Pathway to Prevention who were, at blood collection, autoantibody negative or positive for a single autoantibody (low-risk individuals), and positive for multiple autoantibodies (high-risk individuals). Linear mixed models were adopted to estimate variation of pancreatic enzymes among the groups and to evaluate the influence of high-risk HLA genotypes and residual beta cell function on exocrine pancreas function.In adults, but not children, reduced levels of P-amylase and lipase were shown in at-risk individuals, including (for P-amylase levels only) those at low-risk, and in T1Dnew. Furthermore, while high-risk HLA genotypes negatively affected P-amylase levels in autoantibody negative adult individuals, fasting C-peptide levels did not correlate with pancreatic enzyme levels.Exocrine pancreas dysfunction precedes the onset of type 1 diabetes in adult at-risk individuals and may be unrelated to fasting C-peptide levels.

BackgroundDuring the last year, mass screening campaigns have been carried out to identify immunological response to SARS-CoV-2 and establish a possible seroprevalence. The obtained results gained new importance with the beginning of SARS-CoV-2 vaccination campaign, as the lack of doses has persuaded several countries to introduce different policies for individuals who had a history of COVID 19.LFAs may represent an affordable tool to support population screening in LMICs, where diagnostic tests are lacking, and epidemiology is still widely unknown. However, LFAs have demonstrated a wide range of performance and the question of which one could be more valuable in these settings still remains.MethodsWe evaluated the performance of 11 LFAs in detecting SARS-CoV-2 infection, analysing samples collected from 350 subjects. In addition, samples from 57 health care workers collected at 21-24 days after the first dose of Pfizer-BioNTech vaccine were also evaluated.FindingsLFAs demonstrated a wide range of specificity (92.31% to 100%) and sensitivity (50 to 100%). The analysis of serum samples post vaccination was used to describe the most suitable tests to detect IgG response against S protein RBD. History of TB therapy was identified as a potential factor affecting the specificity of LFAs.ConclusionsThis analysis identified which LFAs represent a valuable tool not only for the detection of prior SARS-CoV-2 infection, but also to detect IgG elicited in response to vaccination. These results demonstrated that different LFAs may have different applications and the possible risks of their use in high TB burden settings.

Significance The global outbreak of COVID-19 infections generated an unprecedented need to develop novel therapeutic strategies. The SARS-CoV-2 virus enters host cells after binding to the angiotensin-converting enzyme 2 (ACE2), but whether renin−angiotensin−aldosterone system inhibitors (RAASi) are beneficial remains controversial. Standard statistical approaches may fail in assessing medications effects, due to multiple sources of bias in COVID-19 case series collected on an emergency basis. We present a data-driven approach to tackle these challenges. Multilayer risk stratifications were derived for assessing drugs effect, while Bayesian networks were estimated, to analyze dependencies among risk factors’ and treatments’ impact on survival. We provide strong evidence for protectivity of RAASi on hospitalized patients that call for randomized controlled trials of RAASi as COVID-19 treatment option., As the COVID-19 pandemic is spreading around the world, increasing evidence highlights the role of cardiometabolic risk factors in determining the susceptibility to the disease. The fragmented data collected during the initial emergency limited the possibility of investigating the effect of highly correlated covariates and of modeling the interplay between risk factors and medication. The present study is based on comprehensive monitoring of 576 COVID-19 patients. Different statistical approaches were applied to gain a comprehensive insight in terms of both the identification of risk factors and the analysis of dependency structure among clinical and demographic characteristics. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus enters host cells by binding to the angiotensin-converting enzyme 2 (ACE2), but whether or not renin−angiotensin−aldosterone system inhibitors (RAASi) would be beneficial to COVID-19 cases remains controversial. The survival tree approach was applied to define a multilayer risk stratification and better profile patient survival with respect to drug regimens, showing a significant protective effect of RAASi with a reduced risk of in-hospital death. Bayesian networks were estimated, to uncover complex interrelationships and confounding effects. The results confirmed the role of RAASi in reducing the risk of death in COVID-19 patients. De novo treatment with RAASi in patients hospitalized with COVID-19 should be prospectively investigated in a randomized controlled trial to ascertain the extent of risk reduction for in-hospital death in COVID-19.

Background: COVID-19 forced healthcare workers to work in unprecedented and critical circumstances, exacerbating already-problematic and stressful working conditions. The “Healthcare workers’ wellbeing (Benessere Operatori)” project aimed at identifying psychological and personal factors, influencing individuals’ responses to the COVID-19 pandemic. Methods: 291 healthcare workers took part in the project by answering an online questionnaire twice (after the first wave of COVID-19 and during the second wave) and completing questions on socio-demographic and work-related information, the Depression Anxiety Stress Scale-21, the Insomnia Severity Index, the Impact of Event Scale-Revised, the State-Trait Anger Expression Inventory-2, the Maslach Burnout Inventory, the Multidimensional Scale of Perceived Social Support, and the Brief Cope. Results: Higher levels of worry, worse working conditions, a previous history of psychiatric illness, being a nurse, older age, and avoidant and emotion-focused coping strategies seem to be risk factors for healthcare workers’ mental health. High levels of perceived social support, the attendance of emergency training, and problem-focused coping strategies play a protective role. Conclusions: An innovative, and more flexible, data mining statistical approach (i.e., a regression trees approach for repeated measures data) allowed us to identify risk factors and derive classification rules that could be helpful to implement targeted interventions for healthcare workers.

The development of international surveys on children’s learning like PISA, PIRLS and TIMSS—delivering comparable achievement measures across educational systems—has revealed large cross-country variability in average performance and in the degree of inequality across social groups. A key question is whether and how institutional differences affect the level and distribution of educational outcomes. In this contribution, we discuss the difference-in-differences strategies employed in the existing literature to evaluate the effect of early tracking on learning inequalities exploiting international assessments administered at different age/grades. In their seminal paper, Hanushek and Woessmann (Econ J 116:C63–C76, 2006) analyze with two-step estimation the effect of early tracking onoverallinequalities, measured by test scores’ variability indexes. Later work of other scholars in the economics and sociology of education focuses instead on inequalities among children of differentfamily background, using individual-level models on pooled data from different countries and assessments. In this contribution, we show that individual pooled difference-in-differences models are quite restrictive and that in essence they estimate the effect of tracking by double differentiating the estimated cross-sectional family background regression coefficients between tracking regimes and learning assessments. Starting from a simple learning growth model, we show that if test scores at different surveys are not measured on the same scale, as occurs for international learning assessments, pooled individual models may deliver severely biased results. Instead, the scaling problem does not affect the two-step approach. For this reason, we suggest using two-step estimation also to analyzefamily-backgroundachievement inequalities. Against this background, using PIRLS-2006 and PISA-2012 we conduct two-step analyses, finding new evidence that early tracking fosters both overall inequalities and family background differentials in reading literacy.

Targeted gene editing in hematopoietic stem cells (HSCs) is a promising treatment for several diseases. However, the limited efficiency of homology-directed repair (HDR) in HSCs and the unknown impact of the procedure on clonal composition and dynamics of transplantation have hampered clinical translation. Here, we apply a barcoding strategy to clonal tracking of edited cells (BAR-Seq) and show that editing activates p53, which substantially shrinks the HSC clonal repertoire in hematochimeric mice, although engrafted edited clones preserve multilineage and self-renewing capacity. Transient p53 inhibition restored polyclonal graft composition. We increased HDR efficiency by forcing cell-cycle progression and upregulating components of the HDR machinery through transient expression of the adenovirus 5 E4orf6/7 protein, which recruits the cell-cycle controller E2F on its target genes. Combined E4orf6/7 expression and p53 inhibition resulted in HDR editing efficiencies of up to 50% in the long-term human graft, without perturbing repopulation and self-renewal of edited HSCs. This enhanced protocol should broaden applicability of HSC gene editing and pave its way to clinical translation. Transient p53 inhibition and induced cell-cycle progression increase clonal engraftment and homology-directed repair in hematopoietic stem cells.

Aim To radiographically evaluate the effect of immediate implant placement plus alveolar ridge preservation (ARP) with a deproteneized bovine bone mineral and a collagen matrix (IMPL/DBBM/CM) as compared to ARP (DBBM/CM) or spontaneous healing (SH) on vertical and horizontal bone dimensional changes after 4 months of healing. Materials and methods Thirty patients requiring extraction of one single-rooted tooth or premolar were randomly assigned to IMPL/DBBM/CM, ARP DBBM/CM or SH. Cone-beam computed tomography (CBCT) scans, performed before tooth extraction and after 4 months, were superimposed in order to assess changes in ridge height at the buccal and lingual aspect and in ridge width at 1 mm, 3 mm and 5 mm apical to the bone crest. Kruskal-Wallis test was applied for comparison of differences between groups. Results No statistically significant differences between the groups were observed for the vertical bone resorption of the buccal and the lingual side, while significant differences were found between SH group (-3.37 +/- 1.55 mm; -43.2 +/- 25.1%) and both DBBM/CM (-1.56 +/- 0.76 mm; -19.2 +/- 9.1%) and IMPL/DBBM/CM (-1.29 +/- 0.38 mm; -14.9 +/- 4.9%) groups in the horizontal dimension at the most coronal aspect. Conclusion Ridge preservation techniques using DBBM and CM reduce the horizontal bone morphological changes that occur, mostly in the coronal portion of the buccal bone plate following tooth extraction, when compared to spontaneous healing. This is true regardless of whether immediate implant placement is performed or not.

A broad literature focused on the effectiveness of tertiary education. In classical models, a performance indicator is regressed on a set of characteristics of the individuals and fixed effects at the institution level. The FE coefficients are interpreted as the pure value added of the universities. The innovative contribution of the present paper resides in the use of Bayesian network (BN) analysis to assess the effectiveness of tertiary education. The results of an empirical study focused on Italian universities are discussed, to present the use of BN as a decision support tool for policy-making purposes.

To test the factorial structure of the Italian version of the Insomnia Severity Index (ISI) using a confirmatory approach and to assess its psychometric properties. ISI questionnaire was completed by 272 patients (average age 41.28, range 18-73) with insomnia diagnosis performed by a sleep medicine physician and retrospectively enrolled in the study. All patients underwent Cognitive Behavioral Treatment for Insomnia (CBT-I) and completed sleep diaries before starting the treatment. Data from sleep diaries were analyzed for assessing concurrent validity of the ISI. Confirmatory factor analysis (CFA) for ordinal Likert-type items was applied to compare four competing models proposed in the literature. 244 patients, out of the 272, completed the ISI at the end of CBT-I. A comparison of ISI score before and after treatment was performed. The CFA analysis confirmed the presence of three main factors conceptualized as severity and impact of the disease along with sleep satisfaction. Significant correlations of the first three items of the questionnaire, investigating three different subtypes of insomnia, and the subjective measures from the sleep diaries were found, thus supporting the concurrent validity of the test. Sleep efficiency (SE) had a significant inverse correlation with the severity and satisfaction factors and with ISI's total score. After CBT-I treatment, a significant reduction of ISI's scores was observed, thus confirming the effectiveness of the CBT-I treatment. The internal reliability coefficient was 0.75. The ISI questionnaire maintains good psychometric properties in the Italian version, thus confirming that this instrument is reliable for detecting insomnia severity and identifying patients' symptoms.

Pulmonary infections caused by Mycobacterium abscessus (MA) have increased over recent decades affecting individuals with underlying pathologies such as chronic obstructive pulmonary disease, bronchiectasis and, especially, cystic fibrosis. The lack of a representative and standardized model of chronic infection in mice has limited steps forward in the field of MA pulmonary infection. To overcome this challenge we refined the method of agar beads to establish MA chronic infection in immunocompetent mice. We evaluated bacterial count, lung pathology and markers of inflammation and we performed longitudinal studies with magnetic resonance imaging (MRI) up to three months after MA infection. In this model, MA was able to establish a persistent lung infection up to two months and with minimal systemic spread. Lung histopathological analysis revealed granulomatous inflammation around bronchi characterized by the presence of neutrophils, lymphocytes and aggregates of vacuolated foamy cells, mimicking the damage observed in humans. Furthermore, MA lung lesions were successfully monitored for the first time by MRI. The availability of this murine model and the introduction of the successfully longitudinal monitoring of the murine lung lesions with MRI pave the way for further investigations on the impact of MA pathogenesis and the efficacy of novel treatments.

Correctly recognizing emotions is an essential skill to manage interpersonal relationships in everyday life. Facial expression represents the most powerful mean to convey important information on emotional and cognitive states during interactions with others. In this paper, we analyze physiological responses triggered by an emotion recognition test, which requires the processing of facial cues. In particular, we evaluate the modulation of several Heart Rate Variability indices, collected during the Reading the Mind in the Eyes Test, accounting for test difficulty (derived from a Rasch analysis), test performances, demographic and psychological characteristics of the participants. The main idea is that emotion recognition is associated with the Autonomic Nervous System and, as a consequence, with the Heart Rate Variability. The principal goal of our study was to explore the complexity of the collected measures and their possible interactions by applying a class of flexible models, i.e., the latent class mixed models. Actually, this modelling strategy allows for the identification of clusters of subjects characterized by similar longitudinal trajectories. Both univariate and multivariate latent class mixed models were used. In fact, while the interpretation of the Heart Rate Variability indices is very difficult when considered individually, a joint evaluation provides a better description of the Autonomic Nervous System state.

SETTING: Screening for latent tuberculous infection (LTBI) of groups at high risk of active tuberculosis (TB) is a key component of the End TB Strategy.OBJECTIVE: To conduct a retrospective descriptive analysis of LTBI rates among foreign-born individuals applying to shelters in the metropolitan area of Milan, Italy.DESIGN: All foreign-born individuals registering for accommodation centres in the city of Milan from November 2009 to April 2017 were screened for active TB and LTBI. Individuals aged 10 mm were offered confirmatory testing with QuantiFERON (R)-TB Gold In-Tube (QFT-GIT).RESULTS: Of the 2666 TST-positive migrants aged 250/100 000 person-years.CONCLUSION: Our data showed a high proportion of LTBI among individuals coming from intermediate TB burden countries.

UKMYC5 is a 96-well microtitre plate designed by theComprehensive Resistance Prediction for Tuberculosis: an International Consortium(CRyPTIC) to enable the measurement of minimum inhibitory concentrations (MICs) of 14 different anti-TB compounds for >30,000 clinical tuberculosis isolates. Unlike the MYCOTB plate, on which UKMYC5 is based, the plate included two new (bedaquiline and delamanid) and two repurposed (clofazimine and linezolid) compounds. UKMYC5 plates were tested by seven laboratories on four continents using a panel of 19 external quality assessment (EQA) strains, including H37Rv. To assess the optimal combination of reading method and incubation time, MICs were measured from each plate by two readers using three methods (mirrored-box, microscope and Vizion™ Digital viewing system) after 7, 10, 14 and 21 days incubation. In addition, all EQA strains were whole-genome sequenced and phenotypically characterized by 7H10/7H11 agar proportion method (APM) and MGIT960. We conclude that the UKMYC5 plate is optimally read using the Vizion™ system after 14 days incubation, achieving an inter-reader agreement of 97.9% and intra- and inter-laboratory reproducibilities of 95.6% and 93.1%, respectively. The mirrored-box had similar reproducibilities. Strains classified as resistant by APM, MGIT960 or the presence of mutations known to confer resistance consistently record elevated MICs compared with those strains classified as susceptible. Finally, the UKMYC5 plate records intermediate MICs for one strain which the APM measured MICs close the applied critical concentration, providing early evidence that the UKMYC5 plate can quantitatively measure the magnitude of resistance to anti-TB compounds due to specific genetic variation.

In this paper, we provide a comprehensive picture of social selectivity in higher education in Italy by focusing on enrolment and two alternative indicators of success: retention and timely completion. The existing literature has shown that young individuals of disadvantaged backgrounds have lower enrolment probabilities and higher chances of withdrawal. This paper analyses the size and features of this cumulative disadvantage, shaping the chances of high-school leavers of eventually attaining the university degree. We analyse whether social background inequalities are stronger at enrolment or at later outcomes, and how these inequalities vary with previous schooling experience. We confirm previous evidence that disadvantaged groups with respect to enrolment are also disadvantaged on persistence, add new findings on timely completion and show that cumulative inequalities are very strong. Inequalities are strongest among students holding technical and vocational high-school qualifications and weakest among well-performing students from lyceums. In addition, we examine the role of labour market conditions and whether they explain geographical differences. Enrolment, retention and timely completion probabilities appear negatively related to local youth unemployment rates, suggesting that with poor labour market prospects, individuals lose motivation and reduce their engagement in education.

BACKGROUND. Neutrophils and their inflammatory mediators are key pathogenic components in multiple autoimmune diseases, while their role in human type 1 diabetes (T1D), a disease that progresses sequentially through identifiable stages prior to the clinical onset, is not well understood. We previously reported that the number of circulating neutrophils is reduced in patients with T1D and in presymptomatic at-risk subjects. The aim of the present work was to identify possible changes in circulating and pancreas-residing neutrophils throughout the disease course to better elucidate neutrophil involvement in human T1D. METHODS. Data collected from 389 subjects at risk of developing T1D, and enrolled in 4 distinct studies performed by TrialNet, were analyzed with comprehensive statistical approaches to determine whether the number of circulating neutrophils correlates with pancreas function. To obtain a broad analysis of pancreas-infiltrating neutrophils throughout all disease stages, pancreas sections collected worldwide from 4 different cohorts (i.e., nPOD, DiViD, Siena, and Exeter) were analyzed by immunohistochemistry and immunofluorescence. Finally, circulating neutrophils were purified from unrelated nondiabetic subjects and donors at various T1D stages and their transcriptomic signature was determined by RNA sequencing. RESULTS. Here, we show that the decline in β cell function is greatest in individuals with the lowest peripheral neutrophil numbers. Neutrophils infiltrate the pancreas prior to the onset of symptoms and they continue to do so as the disease progresses. Of interest, a fraction of these pancreas-infiltrating neutrophils also extrudes neutrophil extracellular traps (NETs), suggesting a tissue-specific pathogenic role. Whole-transcriptome analysis of purified blood neutrophils revealed a unique molecular signature that is distinguished by an overabundance of IFN-associated genes; despite being healthy, said signature is already present in T1D-autoantibody-negative at-risk subjects. CONCLUSIONS. These results reveal an unexpected abnormality in neutrophil disposition both in the circulation and in the pancreas of presymptomatic and symptomatic T1D subjects, implying that targeting neutrophils might represent a previously unrecognized therapeutic modality. FUNDING. Juvenile Diabetes Research Foundation (JDRF), NIH, Diabetes UK.

Tuberculosis elimination requires an effective strategy to diagnose and treat people infected with Mycobacterium tuberculosis who would otherwise be at high risk of developing and transmitting active disease [1, 2]. The diagnostic tools for latent tuberculosis infection (LTBI) are the tuberculin skin test (TST) and the T-cell interferon-γ release assays (IGRAs). Two IGRAs are commercially available, QuantiFERON-TB Gold In-Tube (QFT-GIT) (Qiagen, Hilden, Germany) and T-SPOT.TB (Oxford Immunotec, Abingdon, UK). Compared to the TST, IGRAs offer operational advantages and higher specificity in the bacille Calmette–Guérin (BCG)-vaccinated population [3], and they are at least as sensitive for LTBI [4]. However, IGRAs have limitations: reduced sensitivity in children and immunocompromised subjects, including HIV-infected individuals [3, 4]; failure to discriminate between active tuberculosis and LTBI; and poor correlation with the risk of progression to active disease [3].

Background: Breast Cancer susceptibility genes 1 and 2 are implicated in hereditary breast and ovarian cancer and women can test for the presence of these genes prior to developing cancer. The goal of this study is to examine psychological distress, quality of life, and active coping mechanisms in a sample of women during the pre-test stage of the genetic counseling process, considering that pre-test distress can be an indicator of post-test distress. We also wanted to identify if subgroups of women, defined based on their health status, were more vulnerable to developing distress during the genetic counseling process. Methods: This study included 181 female participants who accessed a Cancer Genetic Counseling Clinic. The participants were subdivided into three groups on the basis of the presence of a cancer diagnosis: Affected patients, Ex-patients, and Unaffected participants. Following a self-report questionnaire, a battery of tests was administered to examine psychological symptomatology, quality of life, and coping mechanisms. Results: The results confirm that the genetic counseling procedure is not a source of psychological distress. Certain participants were identified as being more vulnerable than others; in the pre-test phase, they reported on average higher levels of distress and lower quality of life. These participants were predominantly Ex-patients and Affected patients, who may be at risk of distress during the counseling process. Conclusions: These findings highlight that individuals who take part in the genetic counseling process are not all the same regarding pre-test psychological distress. Attention should be paid particularly to Ex-patients and Affected patients by the multidisciplinary treating team.

Introductionto date, studies on the relationship between Theory of Mind (ToM) and eating disorders (ED) have never considered binge eating disorder (BED).Aims a) to assess ToM abilities in a sample of patients suffering from BED comparing them with healthy controls; b) to evaluate the influence of several variables (demographic, clinical and neuropsychological dimensions, attachment styles, traumatic events, comorbid Axis I and II disorders) on ToM abilities.Methodswe assessed ToM in a sample of 20 BED patients and 22 women from the general population using the Reading the Mind in the Eyes Test (RMET) and the Faux Pas Test (FPT).Resultsregarding the first aim, the comparison between groups showed that the clinical group scored significantly lower than the control group on the RMET as well as on FPT. Regarding the second aim, two different multiple regression models were performed: one for the RMET and one for the FPT. Both of them led to significant results. When modeling RMET score, it emerged that age and Binge Eating Scale significantly reduce the score, while vocabulary and drive for thinness have a positive effect (r2 = 0.62). When modeling FPT score, we found that central coherence and binge eating significantly reduce the total score (r2 = 0.33).Conclusionsour study begins to shed light on the relationship between ToM and BED; in particular, it suggests that BED patients have lower mentalization skills than healthy controls and ToM abilities are partially influenced by clinical variables related to eating pathology.Disclosure of interestThe authors have not supplied their declaration of competing interest.

In this article, we compare alternative missing imputation methods in the presence of ordinal data, in the framework of CUB (Combination of Uniform and (shifted) Binomial random variable) models. Various imputation methods are considered, as are univariate and multivariate approaches. The first step consists of running a simulation study designed by varying the parameters of the CUB model, to consider and compare CUB models as well as other methods of missing imputation. We use real datasets on which to base the comparison between our approach and some general methods of missing imputation for various missing data mechanisms.

Modelling relationships between variables has been a major challenge for statisticians in a wide range of application areas. In conducting customer satisfaction surveys, one main objective, is to identify the drivers to overall satisfaction (or dissatisfaction) in order to initiate proactive actions for containing problems and/or improving customer satisfaction. Bayesian Networks (BN) combine graphical analysis with Bayesian analysis to represent relations linking measured and target variables. Such graphical maps are used for diagnostic and predictive analytics. This paper is about the use of BN in the analysis of customer survey data. We propose an approach to sensitivity analysis for identifying the drivers of overall satisfaction. We also address the problem of selection of robust networks. Moreover, we show how such an analysis generates high information quality (InfoQ) and can be effectively combined with an integrated analysis considering various models. (C) 2014 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license

Identifying latently infected individuals is crucial for the elimination of tuberculosis (TB). We evaluated for the first time the performance of a new type of interferon-γ release assay, QuantiFERON-TB Plus (QFT-Plus), which includes an additional antigen tube (TB2), stimulating both CD4+ and CD8+ T-cells in contacts of TB patients.Contacts were screened for latent TB infection by tuberculin skin test, QFT-Plus and QuantiFERON-TB Gold in Tube (QFT-GIT).In 119 TB contacts, the overall agreement between QFT-Plus and QFT-GIT was high, with a Cohen's κ of 0.8. Discordant results were found in 12 subjects with negative QFT-GIT and positive QFT-Plus results. In analyses of markers of TB exposure and test results, the average time spent with the index case was the strongest risk factor for positivity in each of these tests. The difference in interferon-γ production between the two antigen tubes (TB2−TB1) was used as an estimate of CD8+ stimulation provided by the TB2. TB2−TB1 values >0.6 IU·mL−1 were significantly associated with proximity to the index case and European origin.QFT-Plus has a stronger association with surrogate measures of TB exposure than QFT-GIT in adults screened for latent TB infection. Interferon-γ response in the new antigen tube used an indirect estimate of specific CD8+ response correlates with increased Mycobacterium tuberculosis exposure, suggesting a possible role in identifying individuals with recent infection.

This chapter is about features and capabilities of the R software that support information quality (InfoQ). The examples provided, with their R code, are designed to show how InfoQ can be achieved by treating with R InfoQ components and dimensions.