Progettazione e realizzazione di un'applicazione per supporti tablet attraverso RDF e HTML5 come sussidio alle attività di divulgazione e di didattica nel Museo di Palazzo Reale di Pisa

La presente tesi è stata svolta presso il Laboratorio PERCRO di Pisa. L'esigenza di questo lavoro nasce dal desiderio di dotare l'utente di un supporto di tipo tecnologico che lo accompagni durante la visita all'interno del Museo di Palazzo Reale di Pisa. L'obiettivo è stato quindi quello di realizzare un'applicazione, da utilizzare su supporti tablet, che fornisca una serie di informazioni riguardante i ritratti della famiglia dei Medici, così da regalare al visitatore un'esperienza il più completa possibile. Si è trattato quindi di scegliere il linguaggio utilizzato per la costruzione del programma e il metodo di archiviazione delle informazioni, apprenderne il loro funzionamento, decidere il criterio di implementazione dei dati all'interno dell'applicazione, scrivere il codice nel linguaggio scelto, importare ed elaborare le immagini, inserire i contenuti, realizzare una fase di testing con conseguenti eventuali modifiche, eseguire una breve analisi su possibili ulteriori potenzialità da sviluppare in futuro. La parte più complessa del lavoro è risultata essere l'inserimento dei dati all'interno dell'applicazione; infatti la scelta di utilizzare un'ontologia, al posto di un più comune sistema di archiviazione, ha reso ancora più complessa questa fase del lavoro. Questo perché, a fronte degli innumerevoli e sostanziali vantaggi di una scelta di questo tipo, si è resa preliminarmente necessaria l'acquisizione di una profonda conoscenza dei suoi metodi applicativi. Concludendo, il lavoro svolto può essere sintetizzato nelle seguenti fasi: definizione, sulla base delle richieste del Museo, del prodotto finale desiderato, selezione degli strumenti e delle tecnologie impiegate per la creazione dell'interfaccia, scelta della costruzione di un'ontologia anziché della immediata compilazione di un database, studio e approfondimento delle tecniche di applicazione, trasferimento della conoscenza all'interno del programma e, infine, elenco dei possibili sviluppi futuri

Telomere length shortening is associated with treatment-free remission in chronic myeloid leukemia patients

We studied telomere length in 32 CML patients who discontinued imatinib after achieving complete molecular remission and 32 age-sex-matched controls. The relative telomere length (RTL) was determined by q-PCR as the telomere to single copy gene (36B4) ratio normalized to a reference sample (K-562 DNA). Age-corrected RTL (acRTL) was also obtained. The 36-month probability of treatment-free remission (TFR) was 59.4 %. TFR patients showed shorter acRTL compared to relapsed (mean ± SD = 0.01 ± 0.14 vs 0.20 ± 0.21; p = 0.01). TFR was significantly higher in CML patients with acRTL ≤0.09 (78.9 vs 30.8 %, p = 0.002). CML stem cells harboring longer telomeres possibly maintain a proliferative potential after treatment discontinuation

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic

Psychopathology, psychosocial factors and obesity

The aims of this study were to evaluate the association between obesity and socio-demographic and psychopathological variables in a clinical sample of patients referred to a center for the diagnosis and treatment of obesity, compared with a homogeneous sample of normal-weight subjects.Aims. The aims of this study were to evaluate the association between obesity and socio-demographic and psychopathological variables in a clinical sample of patients referred to a center for the diagnosis and treatment of obesity, compared with a homogeneous sample of normal-weight subjects. Methods. In the context of a research project regarding obesity and psychopathology, a multivariate logistic regression analysis was used to examine the association between obesity and the demographic and clinical variables, on the basis of the data set of a consecutive sample of 293 obese patients (48 males, 245 females, mean age: 45.41±13.55, mean body mass index [BMI] 35.6±6.2) compared with a control group of 293 non-obese subjects (48 males, 245 females, mean age 45.66±13.86, mean BMI 21.8±2.06). All subjects were assessed by structured clinical interview, the Structured Clinical Interview for Diagnosis for axis I DSM-IV (SCID-I) and for axis II DSM-IV (SCID-II). Results. Multivariate statistical analysis showed that the status of housewife and the presence of lifetime axis I and II psychiatric diagnosis in general, and of depressive, anxiety, eating and some personality disorders in particular, significantly increased the likelihood of being overweight/obese. The likelihood for different combinations of risk factors increased from a value of 32.3% for an individual not exposed to any risk factor, to a value of 86.7% for those exposed to all risk factors considered. Conclusions.The presence of an axis I and/or II diagnosis and housewife status are both independently associated with an increased likelihood of being overweight/obese. The interaction of these factors increases this likelihood. Even taking into account the limits of the study, in particular of its cross-sectional nature, these findings may have important implications in both prevention and treatment of obesity