Search

Introduction: Aging has significant economic and social implications leading to an increase in chronic diseases and reduced autonomy of the elderly. Sleep disorders are common in the elderly, manifesting reduced sleep quality. Objective/Purpose: The study aimed to measure the prevalence of sleep disorders in older adults and assess sex differences in sleep quality and sleep problems. Method: A cross-sectional study based on an online survey was performed according to the STROBE checklist, using pre-validated questionnaires (Pittsburgh Sleep Quality Index) distributed to a sample of older adults. This is the first study evaluating sex differences in sleep quality and problems in the Italian population context using the Pittsburgh Sleep Quality Index assessment tool. The study was conducted in a university hospital in Rome from October 2020 to November 2020, on patients aged >65 years, independent in activities of daily living, with comorbidities and on treatment with up to 2 medications. Results: 59 patients were included in the study, with an average age of 71.12 years. The results show that among males, the prevalence of poor sleep quality was 51.9%, while among females, the prevalence of poor sleep quality was 62.5%. According to Shapiro-Wilk, the Pittsburgh Sleep Quality Index was not normally distributed. Pittsburgh Sleep Quality Index total scores in males did not differ significantly from females. Conclusions: Considering scientific literature, recent studies have highlighted the prevalence of sleep disorders in the elderly population and their underreporting. Providing early intervention not only improves the sleep quality of these people but may also reduce the risk of experiencing adverse health outcomes and susceptibility to frailty.

ABSTRACTBackground The question of whether influenza vaccine effectiveness (VE) wanes over the winter season is still open and some contradictory findings have been reported. This study investigated the possible decline in protection provided by the available influenza vaccines.Research design and methods An individual-level pooled analysis of six test-negative case-control studies conducted in Italy between the 2018/2019 and 2022/2023 seasons was performed. Multivariable logistic regression analyses were performed to estimate weekly change in the odds of testing positive for influenza 14 days after vaccination.Results Of 6490 patients included, 1633 tested positive for influenza. Each week that had elapsed since vaccination was associated with an increase in the odds of testing positive for any influenza (4.9%; 95% CI: 2.0–8.0%) and for A(H3N2) (6.5%; 95% CI: 2.9–10.3%). This decline in VE was, however, significant only in children and older adults. A similar increase in the odds of testing positive was seen when the dataset was restricted to vaccinees only. Conversely, VE waning was less evident for A(H1N1)pdm09 or B strains.Conclusions Significant waning of VE, especially against influenza A(H3N2), may be one of the factors associated with suboptimal end-of-season VE. Next-generation vaccines should provide more durable protection against A(H3N2).

Abstract We are in the era of Health 4.0 when novel technologies are providing tools capable of improving the quality and safety of the services provided. Our project involves the integration of different technologies (AI, big data, robotics, and telemedicine) to create a unique system for patients admitted to intensive care units suffering from infectious diseases capable of both increasing the personalization of care and ensuring a safer environment for caregivers.

Propose: This pilot study aimed to apply the central tenets of bloodless surgery and to analyze the effectiveness of specific preoperative, intraoperative, and postoperative strategies to minimize the risk for blood transfusion after gynecological surgery in a specific group of patients who refused blood products. Methods: A total of 83 patients undergoing gynecological surgery were included in the study. Forty-two patients received preoperatively oral iron, acid folic, and vitamin B12 supplementation in the 30 days before surgery, and 41 patients did not receive therapy. Results: No significant differences were found when comparing the two study groups. The implementation of all procedures to maintain a bloodless surgery has been helpful, in association with the other available procedures, in achieving optimal management and maintenance of hemoglobin levels, even in the most critical situations. Conclusion: In conclusion, implementing the bloodless approach as much as possible could guarantee the patient better and safer clinical and care management. Furthermore, well-designed research is required to clarify further the effects of bloodless surgery in gynecological patients.

IntroductionThe primary objective of this research is to examine acrophobia, a widely prevalent and highly severe phobia characterized by an overwhelming dread of heights, which has a substantial impact on a significant proportion of individuals worldwide. The objective of our study was to develop a real-time and precise instrument for evaluating levels of acrophobia by utilizing electroencephalogram (EEG) signals.MethodsEEG data was gathered from a sample of 18 individuals diagnosed with acrophobia. Subsequently, a range of classifiers, namely Support Vector Classifier (SVC), K-nearest Neighbors (KNN), Random Forest (RF), Decision Tree (DT), Adaboost, Linear Discriminant Analysis (LDA), Convolutional Neural Network (CNN), and Artificial Neural Network (ANN), were employed in the analysis. These methodologies encompass both machine learning (ML) and deep learning (DL) techniques.ResultsThe Convolutional Neural Network (CNN) and Artificial Neural Network (ANN) models demonstrated notable efficacy. The Convolutional Neural Network (CNN) model demonstrated a training accuracy of 96% and a testing accuracy of 99%, whereas the Artificial Neural Network (ANN) model attained a training accuracy of 96% and a testing accuracy of 97%. The findings of this study highlight the effectiveness of the proposed methodology in accurately categorizing real-time degrees of acrophobia using EEG data. Further investigation using correlation matrices for each level of acrophobia showed substantial EEG frequency band connections. Beta and Gamma mean values correlated strongly, suggesting cognitive arousal and acrophobic involvement could synchronize activity. Beta and Gamma activity correlated strongly with acrophobia, especially at higher levels.DiscussionThe results underscore the promise of this innovative approach as a dependable and sophisticated method for evaluating acrophobia. This methodology has the potential to make a substantial contribution toward the comprehension and assessment of acrophobia, hence facilitating the development of more individualized and efficacious therapeutic interventions.

Gastric cancer (GC) is a significant healthcare concern, and the identification of high-risk patients is crucial. Indeed, gastric precancerous conditions present significant diagnostic challenges, particularly early intestinal metaplasia (IM) detection. This study developed a deep learning system to assist in IM detection using image patches from gastric corpus examined using virtual chromoendoscopy in a Western country. Utilizing a retrospective dataset of endoscopic images from Sant’Andrea University Hospital of Rome, collected between January 2020 and December 2023, the system extracted 200 × 200 pixel patches, classifying them with a voting scheme. The specificity and sensitivity on the patch test set were 76% and 72%, respectively. The optimization of a learnable voting scheme on a validation set achieved a specificity of 70% and sensitivity of 100% for entire images. Despite data limitations and the absence of pre-trained models, the system shows promising results for preliminary screening in gastric precancerous condition diagnostics, providing an explainable and robust Artificial Intelligence approach.

Among numerous public health actions, the Prevention Departments of Local Health Authorities take charge of the migrant asylum-seeking population for health assessments, for the implementation of preventive activities, and for any consequent actions. This report describes two cases of tuberculosis in Belluno Province managed by a multidisciplinary team made up of healthcare workers that involved numerous diagnostic, clinical, and prophylactic implications, as well as an analysis of the epidemiological aspects related to the incidence of cases along the migration route. Although the cases occurred in a northeastern Italian territory, the management methods described here may represent good practices to share on this operational line, which can promote the strengthening of cooperation between Health Authorities and Emergency Reception Centers to correctly identify cases of active tuberculosis that may not have been initially screen-detected.

Abstract Background The FLURESP project is a public health research funded by the European Commission, with the objective to design a methodological framework to assess the cost-effectiveness of existing public health measures against human influenza pandemics. A dataset has been specifically collected in the frame of the Italian health system. As most of interventions against human influenza are relavant against other respiratory diseases pandemics, potential interests in COVID-19 are discussed. Methods Ten public health measures against human influenza pandemics pandemic were selected to be also relevant to other respiratory virus pandemics such as COVID 19: individual (hand washing, using masks), border control (quarantine, fever screening, border closure), community infection (school closure, class dismissal, social distancing, limitation of public transport), reduction of secondary infections (implementation of antibiotic therapy guidelines), pneumococcal vaccination for at-risk people, development of Intensive Care Unit (ICU) capacity, implementation of life support equipments in ICU, screening interventions, vaccination programs targeting health professional and targeting general population. Results Using mortality reduction as effectiveness criteria, the most cost-effective strategies are “reduction of secondary infections” and “implementation of life support equipment in ICU”. The least cost-effective option whatever the level of pandemic events are screening interventions and mass vaccination. Conclusions A number of intervention strategies against human influenza pandemics appears relevant against every respiratory virus, including the COVID-19 event. Measures against pandemics should be considered according to their expected effectiveness but also their costs for the society because they impose substantial burden to the population, confirming the interest of considering cost-effectiveness of public health measures to enlighten decision making.

ABSTRACT: Objectives: In this study, we aimed to investigate the relative vaccine effectiveness (rVE) of the MF59-adjuvanted trivalent (aTIV) and non-adjuvanted quadrivalent (QIVe) egg-based standard-dose vaccines against severe laboratory-confirmed influenza. Methods: This test-negative case-control study was conducted in a hospital setting during four recent Italian influenza seasons (from 2018/19 to 2021/22). The clinical outcome was severe acute respiratory infection (SARI) with laboratory confirmation diagnosed among subjects aged ≥65 years. rVE of aTIV versus QIVe was estimated through propensity score matching followed by logistic regression. Results: The influenza virus circulated to a significant extent only during the 2018/19 and 2019/20 seasons. The final population included 512 vaccinated older adults, of which 83 were cases and 429 were test-negative controls. aTIV and QIVe users differed substantially from the point of view of several baseline characteristics. The propensity score adjusted rVE of aTIV vs QIVe was 59.2% (95% CI: 14.6%, 80.5%), 54.7% (95% CI: -28.7%, 84.0%) and 56.9% (95% CI: -7.8%, 82.8%) against any influenza, A(H1N1)pdm09 and A(H3N2), respectively. Conclusion: aTIV was more effective than QIVe in preventing laboratory-confirmed SARI. The benefits of aTIV may be obscured by confounding indication.

IntroductionDevelopment of Robust and Innovative Vaccine Effectiveness (DRIVE) was a European public–private partnership (PPP) that aimed to provide annual, brand-specific estimates of influenza vaccine effectiveness (IVE) for regulatory and public health purposes. DRIVE was launched in 2017 under the umbrella of the Innovative Medicines Initiative (IMI) and conducted IVE studies from its pilot season in 2017–2018 to its final season in 2021–2022.MethodsIn 2021–2022, DRIVE conducted four primary care-based test-negative design (TND) studies (Austria, Italy, Iceland, and England; involving >1,000 general practitioners), nine hospital-based TND studies (France, Iceland, Italy, Romania, and Spain, for a total of 21 hospitals), and one population-based cohort study in Finland. In the TND studies, patients with influenza-like illness (primary care) or severe acute respiratory infection (hospital) were enrolled, and laboratory tested for influenza using RT-PCR. Study contributor-specific IVE was calculated using logistic regression, adjusting for age, sex, and calendar time, and pooled by meta-analysis.ResultsIn 2021–2022, pooled confounder-adjusted influenza vaccine effectiveness (IVE) estimates against laboratory-confirmed influenza (LCI) overall and per type and subtype/lineage was produced, albeit with wide confidence intervals (CI). The limited circulation of influenza in Europe did not allow the network to reach the optimal sample size to produce precise IVE estimates for all the brands included. The most significant IVE estimates were 76% (95% CI 23%−93%) for any vaccine and 81% (22%−95%) for Vaxigrip Tetra in adults ≥65 years old and 64% (25%−83%) for Fluenz Tetra in children (TND primary care setting), 85% (12%−97%) for any vaccine in adults 18–64 years (TND hospital setting), and 38% (1%−62%) in children 6 months−6 years (population-based cohort, mixed setting).DiscussionOver five seasons, DRIVE collected data on >35,000 patients, more than 60 variables, and 13 influenza vaccines. DRIVE demonstrated that estimating brand-specific IVE across Europe is possible, but achieving sufficient sample size to obtain precise estimates for all relevant stratifications remains a challenge. Finally, DRIVE's network of study contributors and lessons learned have greatly contributed to the development of the COVID-19 vaccine effectiveness platform COVIDRIVE.

In this paper, we use two Fractional-Order Chaotic Systems (FOCS)—one for the sender and one for the receiver—to determine the optimal synchronisation for a secure communication technique. With the help of the Step-By-Step Sliding-Mode Observer (SBS-SMO), this synchronisation is accomplished. An innovative optimisation method, known as the artificial Harris hawks optimisation (HHO), was employed to enhance the observer’s performance. This method eliminates the random parameter selection process and instead selects the optimal values for the observer. In a short amount of time, the secret message that could have been in the receiver portion (signal, voice, etc.) was successfully recovered using the proposed scheme. The experimental validation of the numerical results was carried out with the assistance of an Arduino microcontroller and several electronic components. In addition, the findings of the experiments were compared with the theoretical calculations, revealing a satisfactory level of agreement.

Eye-tracking systems have emerged as valuable tools in various research fields, including psychology, medicine, marketing, car safety, and advertising. However, the high costs of the necessary specialized hardware prevent the widespread adoption of these systems. Appearance-based gaze estimation techniques offer a cost-effective alternative that can rely solely on RGB cameras, albeit with reduced accuracy. Therefore, the aim of our work was to present a real-time eye-tracking system with low-end hardware that leverages appearance-based techniques while overcoming their drawbacks to make reliable gaze data accessible to more users. Our system employs fast and light machine learning algorithms from an external library called MediaPipe to identify 3D facial landmarks. Additionally, it uses a series of widely recognized computer vision techniques, like morphological transformations, to effectively track eye movements. The precision and accuracy of the developed system in recognizing saccades and fixations when the eye movements are mainly horizontal were tested through a quantitative comparison with the EyeLink 1000 Plus, a professional eye tracker. Based on the encouraging registered results, we think that it is possible to adopt the presented system as a tool to quickly retrieve reliable gaze information.

For this work, a preliminary study proposed virtual interfaces for remote psychotherapy and psychology practices. This study aimed to verify the efficacy of such approaches in obtaining results comparable to in-presence psychotherapy, when the therapist is physically present in the room. In particular, we implemented several joint machine-learning techniques for distance detection, camera calibration and eye tracking, assembled to create a full virtual environment for the execution of a psychological protocol for a self-induced mindfulness meditative state. Notably, such a protocol is also applicable for the desensitization phase of EMDR therapy. This preliminary study has proven that, compared to a simple control task, such as filling in a questionnaire, the application of the mindfulness protocol in a fully virtual setting greatly improves concentration and lowers stress for the subjects it has been tested on, therefore proving the efficacy of a remote approach when compared to an in-presence one. This opens up the possibility of deepening the study, to create a fully working interface which will be applicable in various on-field applications of psychotherapy where the presence of the therapist cannot be always guaranteed.

The extraordinary vaccination campaigns of the COVID-19 pandemic era put organizational and operational systems to the test in numerous territorial contexts. In the Veneto region, the activation of population vaccination centers (CVPs) guaranteed the provision of vaccines to mountain areas. These centers, drive-in and building-based, improved the efficiency of dose administration in relation to similar conditions where healthcare workers (HCWs) were routinely involved in clinics. Overall, a comparison of the two models investigated, with the same numbers of HCWs involved and the same opening hours for the vaccination sites, has shown that the CVPs are able to guarantee three times as many vaccines administered, compared with the traditional outpatient model. This study aims to provide a detailed analysis of the adopted organizational model, highlighting the best practices and improvements required to guarantee a timely and effective public health response, and evaluating the opportunities to deploy these innovative methods actively in a standard context.

ObjectiveTo evaluate the impact of the COVID-19 pandemic on first and follow-up visits for cancer outpatients.MethodsThis is a multicenter retrospective observational study involving three Comprehensive Cancer Care Centers (CCCCs): IFO, including IRE and ISG in Rome, AUSL-IRCCS of Reggio Emilia, and IRCCS Giovanni Paolo II in Bari) and one oncology department in a Community Hospital (Saint'Andrea Hospital, Rome). From 1 January 2020 and 31 December 2021, we evaluated the volume of outpatient consultations (first visits and follow-up), comparing them with the pre-pandemic year (2019). Results were analyzed by quarter according to the Rt (real-time indicator used to assess the evolution of the pandemic). IFO and IRCCS Giovanni Paolo II were “COVID-free” while AUSL-IRCCS RE was a “COVID-mixed” Institute. Depending on the Rt, Sain't Andrea Hospital experienced a “swinging” organizational pathway (COVID-free/ COVID-mixed).ResultsRegarding the “first appointments”, in 2020 the healthcare facilities operating in the North and Center of Italy showed a downward trend. In 2021, only AUSL-IRCCS RE showed an upward trend. Regarding the “follow-up”, only AUSL IRCCS RE showed a slight up-trend in 2020. In 2021, IFO showed an increasing trend, while S. Andrea Hospital showed a negative plateau. Surprisingly, IRCCS Giovanni Paolo II in Bari showed an uptrend for both first appointment and follow-ups during pandemic and late pandemic except for the fourth quarter of 2021.ConclusionsDuring the first pandemic wave, no significant difference was observed amongst COVID-free and COVID-mixed Institutes and between CCCCs and a Community Hospital. In 2021 (“late pandemic year”), it has been more convenient to organize COVID-mixed pathway in the CCCCs rather than to keep the Institutions COVID-free. A swinging modality in the Community Hospital did not offer positive results in term of visit volumes. Our study about the impact of COVID-19 pandemic on visit volume in cancer outpatients may help health systems to optimize the post-pandemic use of resources and improve healthcare policies.

Abstract Background Nonthyroidal Illness Syndrome (NTIS) can be detected in many critical illnesses. Recently, we demonstrated that this condition is frequently observed in COVID-19 patients too and it is correlated with the severity the disease. However, the exact mechanism through which thyroid hormones influence the course of COVID-19, as well as that of many other critical illnesses, is not clear yet and treatment with T4, T3 or a combination of both is still controversial. Aim of this study was to analyze body composition in COVID-19 patients in search of possible correlation with the thyroid function. Methods and findings We report here our experience performed in 74 critically ill COVID-19 patients hospitalized in the intensive care unit (ICU) of our University Hospital in Rome. In these patients, we evaluated the thyroid hormone function and body composition by Bioelectrical Impedance Analysis (BIA) during the acute phase of the disease at admission in the ICU. To examine the effects of thyroid function on BIA parameters we analyzed also 96 outpatients, affected by thyroid diseases in different functional conditions. We demonstrated that COVID-19 patients with low FT3 serum values exhibited increased values of the Total Body Water/Free Fat Mass (TBW/FFM) ratio. Patients with the lowest FT3 serum values had also the highest level of TBW/FFM ratio. This ratio is an indicator of the fraction of FFM as water and represents one of the best-known body-composition constants in mammals. We found an inverse correlation between FT3 serum values and this constant. Reduced FT3 serum values in COVID-19 patients were correlated with the increase in the total body water (TBW), the extracellular water (ECW) and the sodium/potassium exchangeable ratio (Na e :K e ), and with the reduction of the intracellular water (ICW). No specific correlation was observed in thyroid patients at different functional conditions between any BIA parameters and FT3 serum values, except for the patient with myxedema, that showed a picture similar to that seen in COVID-19 patients with NTIS. Since the Na+/K+ pump is a well-known T3 target, we measured the mRNA expression levels of the two genes coding for the two major isoforms of this pump. We demonstrated that COVID-19 patients with NTIS had lower levels of mRNA of both genes in the peripheral blood mononuclear cells (PBMC)s obtained from our patients during the acute phase of the disease. In addition, we retrieved data from transcriptome analysis, performed on human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CM)s treated with T3 and we demonstrated that in these cells T3 is able to stimulate the expression of these two genes in a dose-dependent manner. Conclusions In conclusion, we demonstrated that measurement of BIA parameters is a useful method to analyze water and salt retention in COVID-19 patients hospitalized in ICU and, in particular, in those that develop NTIS. Our results indicate that NTIS has peculiar similarities with myxedema seen in severe hypothyroid patients, albeit it occurs more rapidly. The Na+/K+ pump is a possible target of T3 action, involved in the pathogenesis of the anasarcatic condition observed in our COVID-19 patients with NTIS. Finally, measurement of BIA parameters may represent good endpoints to evaluate the benefit of future clinical interventional trials, based on the administration of T3 in patients with NTIS.

Abstract Clinical outcomes of COVID-19 patients are worsened by the presence of co-morbidities, especially cancer leading to elevated mortality rates. SARS-CoV-2 infection is known to alter immune system homeostasis. Whether cancer patients developing COVID-19 present alterations of immune functions which might contribute to worse outcomes have so far been poorly investigated. We conducted a multi-omic analysis of immunological parameters in peripheral blood mononuclear cells (PBMCs) of COVID-19 patients with and without cancer. Healthy donors and SARS-CoV-2-negative cancer patients were also included as controls. At the infection peak, cytokine multiplex analysis of blood samples, cytometry by time of flight (CyTOF) cell population analyses, and Nanostring gene expression using Pancancer array on PBMCs were performed. We found that eight pro-inflammatory factors (IL-6, IL-8, IL-13, IL-1ra, MIP-1a, IP-10) out of 27 analyzed serum cytokines were modulated in COVID-19 patients irrespective of cancer status. Diverse subpopulations of T lymphocytes such as CD8+T, CD4+T central memory, Mucosal-associated invariant T (MAIT), natural killer (NK), and γδ T cells were reduced, while B plasmablasts were expanded in COVID-19 cancer patients. Our findings illustrate a repertoire of aberrant alterations of gene expression in circulating immune cells of COVID-19 cancer patients. A 19-gene expression signature of PBMCs is able to discriminate COVID-19 patients with and without solid cancers. Gene set enrichment analysis highlights an increased gene expression linked to Interferon α, γ, α/β response and signaling which paired with aberrant cell cycle regulation in cancer patients. Ten out of the 19 genes, validated in a real-world consecutive cohort, were specific of COVID-19 cancer patients independently from different cancer types and stages of the diseases, and useful to stratify patients in a COVID-19 disease severity-manner. We also unveil a transcriptional network involving gene regulators of both inflammation response and proliferation in PBMCs of COVID-19 cancer patients.

Abstract Background Autophagy is an intracellular degradation system that removes unnecessary or dysfunctional components and recycles them for other cellular functions. Over the years, a mutual regulation between lipid metabolism and autophagy has been uncovered. Methods This is a narrative review discussing the connection between SCD1 and the autophagic process, along with the modality through which this crosstalk can be exploited for therapeutic purposes. Results Fatty acids, depending on the species, can have either activating or inhibitory roles on autophagy. In turn, autophagy regulates the mobilization of fat from cellular deposits, such as lipid droplets, and removes unnecessary lipids to prevent cellular lipotoxicity. This review describes the regulation of autophagy by lipid metabolism in cancer cells, focusing on the role of stearoyl-CoA desaturase 1 (SCD1), the key enzyme involved in the synthesis of monounsaturated fatty acids. SCD1 plays an important role in cancer, promoting cell proliferation and metastasis. The role of autophagy in cancer is more complex since it can act either by protecting against the onset of cancer or by promoting tumor growth. Mounting evidence indicates that autophagy and lipid metabolism are tightly interconnected. Conclusion Here, we discuss controversial findings of SCD1 as an autophagy inducer or inhibitor in cancer, highlighting how these activities may result in cancer promotion or inhibition depending upon the degree of cancer heterogeneity and plasticity.

Obesity is a chronic multifactorial pathology determined by many factors, including incorrect eating habits and a low level of physical activity. There is an urgent need to promote a persistent change in lifestyle in obese subjects, but very few individuals maintain long-term results achieved after diet therapies. Therapeutic Education (TE) has taken over an important role as a multidisciplinary intervention aimed at improving lifestyle and at acquiring new skills for the management of the disease. However, only a small portion of patients can maintain participation in such programs and fully benefit from them. Assistive technologies, and in particular assistive social robots, are powerful tools to boost independence and improve participation in educational activities. The aim of the research work described in this article is to evaluate the effect of employing a social robot as a therapeutic educational robot helping the expert therapist in the education activity. This article describes the implementation, deployment, and evaluation of a social educational robot used as a TE assistant. Although we cannot provide statistically significant results due to the limited number of people involved in the experimental protocol, all experimental results show a positive trend, indicating that the robot can enhance the social interactions between the patients and the therapist and among the patients, thus bringing to better overall results of the TE sessions, measured with standard tests for obesity management.

Abstract Background Low T3 syndrome is frequent in patients admitted to intensive care units for critical illness and pneumonia. It has been reported also in patients with COVID-19, Hodgkin disease and chronic lymphocytic leukemia. We analyzed the clinical relevance of Low T3 syndrome in COVID-19 patients and, in particular, in those with associated hematological malignancies. Methods Sixty-two consecutive patients, hospitalized during the first wave of SARS-CoV-2 outbreak in Sant’Andrea University Hospital in Rome, were subdivided in 38 patients (Group A), showing low levels of FT3, and in 24 patients (Group B), with normal FT3 serum values. During the acute phase of the disease, we measured serum, radiologic and clinical disease severity markers and scores, in search of possible correlations with FT3 serum values. In addition, in 6 COVID-19 patients, 4 with Low T3 syndrome, including 2 with a hematological malignancy, and 2 with normal FT3 values, we performed, high-dimensional single-cell analysis by mass cytometry, multiplex cytokine assay and gene expression profiling in peripheral blood mononuclear cells (PBMC). Results Low FT3 serum values were correlated with increased Absolute Neutrophil Count, NLR and dNLR ratios and with reduced total count of CD3+, CD4+ and CD8+ T cells. Low FT3 values correlated also with increased levels of inflammation, tissue damage and coagulation serum markers as well as with SOFA, LIPI and TSS scores. The CyTOF analysis demonstrated reduction of the effector memory and terminal effector subtypes of the CD4+ T lymphocytes. Multiplex cytokine assay indicates that mainly IL-6, IP-10 and MCAF changes are associated with FT3 serum levels, particularly in patients with coexistent hematological malignancies. Gene expression analysis using Nanostring identified four genes differently expressed involved in host immune response, namely CD38, CD79B, IFIT3 and NLRP3. Conclusions Our study demonstrates that low FT3 serum levels are associated with severe COVID-19. Our multi-omics approach suggests that T3 is involved in the immune response in COVID-19 and coexistent hematological malignancy and new possible T3 target genes in these patients have been identified.

Background and ObjectiveNonthyroidal Illness Syndrome (NTIS) occurs in approximately 70% of patients admitted to Intensive Care Units (ICU)s and has been associated with increased risk of death. Whether patients with NTIS should receive treatment with thyroid hormones (TH)s is still debated. Since many interventional randomized clinical trials (IRCT)s were not conclusive, current guidelines do not recommend treatment for these patients. In this review, we analyze the reasons why TH treatment did not furnish convincing results regarding possible beneficial effects in reported IRCTs.MethodsWe performed a review of the metanalyses focused on NTIS in critically ill patients. After a careful selection, we extracted data from four metanalyses, performed in different clinical conditions and diseases. In particular, we analyzed the type of TH supplementation, the route of administration, the dosages and duration of treatment and the outcomes chosen to evaluate the results.ResultsWe observed a marked heterogeneity among the IRCTs, in terms of type of TH supplementation, route of administration, dosages and duration of treatment. We also found great variability in the primary outcomes, such as prevention of neurological alterations, reduction of oxygen requirements, restoration of endocrinological and clinical parameters and reduction of mortality.ConclusionsNTIS is a frequent finding in critical ill patients. Despite several available IRCTs, it is still unclear whether NTIS should be treated or not. New primary endpoints should be identified to adequately validate the efficacy of TH treatment and to obtain a clear answer to the question raised some years ago.

Abstract Ras gene family members play a relevant role in cancer, especially when they are mutated. However, they may play additional roles in other conditions beside cancer. We performed gene expression analysis using the NanoString PanCancer IO 360 panel in the peripheral blood mononuclear cell (PBMC) of six COVID-19 patients and we found that H-Ras gene was significantly upregulated, while both K-Ras and N-Ras genes were downregulated. In particular, H-Ras gene upregulation was more evident in COVID-19 patients with a more severe disease. We compared our results with those obtained by analyzing two different and independent datasets, including a total of 53 COVID-19 patients, in which the gene expression analysis was performed using the Immunology_V2 panel. Comparative analysis of the H-Ras gene expression in these patients confirmed our preliminary results. In both of them, in fact, we were able to confirm the upregulation of the expression of the H-Ras gene. The exact role of this specific upregulation of the H-Ras gene in response to SARS-CoV-2 infection and its possible role in cancer still remains to be elucidated. In conclusion, H-Ras gene participates to the host immune response to SARS-CoV-2 virus infection, especially in patients affected by the most severe form of the COVID-19.

Data transmission is the most critical operation for mobile sensors networks in term of energy waste. Particularly in pervasive healthcare sensors network it is paramount to preserve the quality of service also by means of energy saving policies. Communication and data transmission are among the most critical operation for such devises in term of energy waste. In this paper we present a novel approach to increase battery life-span by means of shorter transmission due to data compression. On the other hand, since this latter operation has a non-neglectable energy cost, we developed a compression efficiency estimator based on the evaluation of the absolute and relative entropy. Such algorithm provides us with a fast mean for the evaluation of data compressibility. Since mobile wireless sensor networks are prone to battery discharge-related problems, such an evaluation can be used to improve the electrical efficiency of data communication. In facts the developed technique, due to its independence from the string or file length, is extremely robust both for small and big data files, as well as to evaluate whether or not to compress data before transmission. Since the proposed solution provides a quantitative analysis of the source's entropy and the related statistics, it has been implemented as a preprocessing step before transmission. A dynamic threshold defines whether or not to invoke a compression subroutine. Such a subroutine should be expected to greatly reduce the transmission length. On the other hand a data compression algorithm should be used only when the energy gain of the reduced transmission time is presumably greater than the energy used to run the compression software. In this paper we developed an automatic evaluation system in order to optimize the data transmission in mobile sensor networks, by compressing data only when this action is presumed to be energetically efficient. We tested the proposed algorithm by using the Canterbury Corpus as well as standard pictorial data as benchmark test. The implemented system has been proven to be time-inexpensive with respect to a compression algorithm. Finally the computational complexity of the proposed approach is virtually neglectable with respect to the compression and transmission routines themselves.

Coronavirus disease (COVID-19) caused by the SARS-CoV-2 virus continues to afflict many countries around the world. The resurgence of COVID-19 cases and deaths in many countries shows a complacency in adhering to preventive guidelines. Consequently, vaccination continues to be a crucial intervention to reduce the effects of this pandemic. This study investigated the impact of preventive measures and COVID-19 vaccination on the infection, medication, and hospitalization. A cross-sectional online survey was conducted between 23 December 2021 and 12 March 2022 in Algeria. To evaluate the effectiveness of strategies aimed at avoiding and minimizing SARS-CoV-2 infection and severity, a questionnaire was created and validated. Descriptive statistics and logistic regression analyses were computed to identify associations between dependent and independent variables. Variables with a p-value of < 0.05 were considered statistically significant. Our results indicated that out of 2294 answers received, only 16% of our sample was vaccinated, and more than 60% did not apply preventive guidelines. As a result, 45% were infected with SARS-CoV-2, 75% took treatment (even preventive), and 9% were hospitalized. The logistic regression showed that the impact of preventive measures on the unvaccinated is statistically not significant (OR: 0.764, 95% CI = 0. 555–1.052; p = 0.09). However, this relationship changes significantly for people who are vaccinated (OR: 0.108, 95% CI = 0.047–0.248; p < 0.0001). Our results also demonstrated that the impact of protective measures on non-vaccinated individuals is statistically significant in reducing the need to receive anti-COVID-19 treatments (OR: 0.447, 95% CI = 0.321–0.623; p < 0.0001). Furthermore, the results showed that the impact of preventive measures on the non-vaccinated population is also statistically significant in reducing the risk of hospitalization (OR: 0.211, 95% CI = 0.081–0.548; p < 0.0001). Moreover, vaccinated individuals who neglect preventive measures must take the COVID-19 medication at a rate of 3.77 times (OR: 3.77) higher than those who follow preventive measures and are vaccinated. In short, our findings demonstrate the importance of combining preventive measures and vaccination in order to fight against the pandemic. Therefore, we advise the Ministry of Health and relevant authorities to put more effort into enhancing public knowledge about the COVID-19 infection and vaccination through education and awareness initiatives. Parallel to implementing vaccination as additional preventive strategy, behavioral change initiatives must be improved to encourage adherence to COVID-19 prevention recommendations.

Following an extremely low incidence of influenza during the first waves of the ongoing COVID-19 pandemic, the 2021/22 Northern Hemisphere winter season saw a resurgence of influenza virus circulation. The aim of this study was to describe epidemiology of severe acute respiratory infections (SARIs) among Italian adults and estimate the 2021/22 season influenza vaccine effectiveness. For this purpose, a test-negative case-control study was conducted in a geographically representative sample of Italian hospitals. Of 753 SARI patients analyzed, 2.5% (N = 19) tested positive for influenza, most of which belonged to the A(H3N2) subtype. Phylogenetic analysis showed that these belonged to the subclade 3C.2a1b.2a.2, which was antigenically different from the 2021/22 A(H3N2) vaccine component. Most (89.5%) cases were registered among non-vaccinated individuals, suggesting a protective effect of influenza vaccination. Due to a limited number of cases, vaccine effectiveness estimated through the Firth’s penalized logistic regression was highly imprecise, being 83.4% (95% CI: 25.8–97.4%) and 83.1% (95% CI: 22.2–97.3%) against any influenza type A and A(H3N2), respectively. Exclusion of SARS-CoV-2-positive controls from the model did not significantly change the base-case estimates. Within the study limitations, influenza vaccination appeared to be effective against laboratory-confirmed SARI.

In the course of 2022, an epidemic of monkeypox (MPX) arose worldwide. In order to assess the level of knowledge of the Italian adults regarding the new emerging disease, its prevention and their level of worrying and the acceptance of a possible vaccination, a web questionnaire was spread nationwide. A total of 1352 individuals (mean age 54.5 ± 13.4, 52.4% males) completed the questionnaire. Only 26. 7% of the sample were aware of the burden of the epidemic at the moment of the investigation; 47.1% were not able to identify the transmission route, nor the main symptoms (48.9%); and 54.2% were hesitant toward a possible MPXV vaccination, mainly because of a lack of confident in vaccines (38.5%). A low level of worrying about the disease was registered (mean score 2.3 ± 1.2 on a 5-point scale). In the regression analysis performed considering MPX knowledge as outcome, a lower level of knowledge was associated with higher age (OR 1.378, CI95% 0.998–1.904), working or studying in a nonhealthcare setting (OR 0.046, CI95% 0.033–0.066), being single (OR 0.624, CI95% 0.455–0.856) and having mass media as the main source of information (OR 0.332, CI95% 0.158–0.696). These findings indicate as of the time of this investigation, the communication about the MPXV epidemic was not effective in determining a good level of knowledge about the disease and its transmission among Italian adults. This highlights the need to improve risk communication strategies.

In many developed cities around the world, vehicle sharing is becoming an increasingly popular form of green transportation. While such services are associated with lower emissions and easier mobility, their management poses a significant challenge. In this paper, we examine a dataset collected in Barcelona during the months of august and september 2020 in order to investigate relocation strategies and user clustering. By proposing a neighborhood area split and relating it to user demand, we propose two different areas based on majority demand and users’ requests and provide interpretations of both. We then aim to identify groups of similar users using a variant of Recency Frequency Monetary/Duration (RFM or RFD) clustering that extends to GPS coordinates of voyages in order to differentiate scores based on economic and geographical factors; furthermore, a user-based clustering approach was used to maximize client preferences. As a result of our analysis, the sharing company may be able to make more informed decisions regarding where to focus its resources. In fact, we find that the majority of the demand is concentrated in an area that represents 7.47 percent of the city’s area. Additionally, we propose a discount-based approach in order to influence the user’s behavior in parking the vehicle where it is most needed.

Background: Thyroid hormones (TH)s are master regulators of mitochondrial activity and biogenesis. Nonthyroidal illness syndrome (NTIS) is generally considered an adaptative response to reduced energy that is secondary to critical illness, including COVID-19. COVID-19 has been associated with profound changes in the cell energy metabolism, especially in the cells of the immune system, with a central role played by the mitochondria, considered the power units of every cell. Infection by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) affects and alters mitochondrial functions, both to influence its intracellular survival and to evade host immunity. Aim of the study: This study was undertaken to analyze the oxidative balance and mitochondrial respiration in COVID-19 patients with and without NTIS to elucidate the role that thyroid hormones (TH)s play in this context. Methods: In our cohort of 54 COVID-19 patients, admitted to our University Hospital during the COVID-19 pandemic, we evaluated the generation of reactive oxygen species (ROS) by measuring the serum levels of derivatives of reactive oxygen metabolites (dROMs), and we analyzed the antioxidant capacity by measuring the serum biological antioxidant potential (BAP). We then analyzed the mitochondrial respiration in peripheral blood mononuclear cells (PBMC)s of 28 of our COVID-19 patients, using the seahorse instrument (Agilent). Results were correlated with the serum levels of THs and, in particular, of FT3. In addition, the role of T3 on bioelectrical impedance analysis (BIA) and mitochondrial respiration parameters was directly evaluated in two COVID-19 patients with NTIS, in which treatment with synthetic liothyronine (LT3) was given both in vivo and in vitro. Results: In our COVID-19 patients with NTIS, the dROMs values were significantly lower and the BAP values were significantly higher. Consequently, the oxidative stress index (OSi), measured as BAP/dROMs ratio was reduced compared to that observed in COVID-19 patients without NTIS, indicating a protective role exerted by NTIS on oxidative stress. In our COVID-19 patients, the mitochondrial respiration, measured in PBMCs, was reduced compared to healthy controls. Those with NTIS showed a reduced maximal respiratory capacity and a reduced proton leak, compared to those with normal FT3 serum values. Such lowered mitochondrial respiratory capacity makes the cells more vulnerable to bioenergetic exhaustion. In a pilot study involving two COVID-19 patients with NTIS, we could reinforce our previous observation regarding the role of T3 in the maintenance of adequate peripheral hydroelectrolytic balance. In addition, in these two patients, we demonstrated that by treating their PBMCs with LT3, both in vitro and in vivo, all mitochondrial respiration parameters significantly increased. Conclusions: Our results regarding the reduction in the serum levels of the reactive oxygen species (ROS) of COVID-19 patients with NTIS support the hypothesis that NTIS could represent an adaptative response to severe COVID-19. However, beside this beneficial effect, we demonstrate that, in the presence of an acute reduction of FT3 serum levels, the mitochondrial respiration is greatly impaired, with a consequent establishment of a hypoenergetic state of the immune cells that may hamper their capacity to react to massive viral infection.

In order to obtain optimized elementary devices (photovoltaic modules, power transistors for energy efficiency, high-efficiency sensors) it is necessary to increase the energy conversion efficiency of these devices. A very effective approach to achieving this goal is to increase the absorption of incident radiation. A promising strategy to increase this absorption is to use very thin regions of active material and trap photons near these surfaces. The most effective and cost-effective method of achieving such optical entrapment is the Raman scattering from excited nanoparticles at the plasmonic resonance. The field of plasmonics is the study of the exploitation of appropriate layers of metal nanoparticles to increase the intensity of radiation in the semiconductor by means of near-field effects produced by nanoparticles. In this paper, we focus on the use of metal nanoparticles as plasmonic nanosensors with extremely high sensitivity, even reaching single-molecule detection. The study conducted in this paper was used to optimize the performance of a prototype of a plasmonic photovoltaic cell made at the Institute for Microelectronics and Microsystems IMM of Catania, Italy. This prototype was based on a multilayer structure composed of the following layers: glass, AZO, metal and dielectric. In order to obtain good results, it is necessary to use geometries that orthogonalize the absorption of light, allowing better transport of the photocarriers—and therefore greater efficiency—or the use of less pure materials. For this reason, this study is focused on optimizing the geometries of these multilayer plasmonic structures. More specifically, in this paper, by means of a neurocomputing procedure and an electromagnetic fields analysis performed by the finite elements method (FEM), we established the relationship between the thicknesses of Aluminum-doped Zinc oxide (AZO), metal, dielectric and their main properties, characterizing the plasmonic propagation phenomena as the optimal wavelengths values at the main interfaces AZO/METAL and METAL/DIELECTRIC.

The paper presents research on a specific approach to the issue of computed tomography with an incomplete data set. The case of incomplete information is quite common, for example when examining objects of large size or difficult to access. Algorithms devoted to this type of problems can be used to detect anomalies in coal seams that pose a threat to the life of miners. The most dangerous example of such an anomaly may be a compressed gas tank, which expands rapidly during exploitation, at the same time ejecting rock fragments, which are a real threat to the working crew. The approach presented in the paper is an improvement of the previous idea, in which the detected objects were represented by sequences of points. These points represent rectangles, which were characterized by sequences of their parameters. This time, instead of sequences in the representation, there are sets of objects, which allow for the elimination of duplicates. As a result, the reconstruction is faster. The algorithm presented in the paper solves the inverse problem of finding the minimum of the objective function. Heuristic algorithms are suitable for solving this type of tasks. The following heuristic algorithms are described, tested and compared: Aquila Optimizer (AQ), Firefly Algorithm (FA), Whale Optimization Algorithm (WOA), Butterfly Optimization Algorithm (BOA) and Dynamic Butterfly Optimization Algorithm (DBOA). The research showed that the best algorithm for this type of problem turned out to be DBOA.

Abstract Background The aim of the study was to explore lifestyle of undergraduate students in southern Italy and to investigate their determinants. Methods An anonymous, web-based questionnaire investigating weight and its perception, smoking and alcohol use, achievement of recommended levels of physical activity and time spent daily in screen-based sedentary behaviors was administered to students attending two universities in southern Italy. Age, gender, city, type of degree course attended, occupational status and residential status were considered as possible demographic determinants. Results The majority of the participants reported a normal weight (71.2%), were non-smokers (66.6%), occasional alcohol consumers (60.5%) and insufficiently active (62.6%), with a reported mean screen time exceeding 2 h per day. Gender, city, type of degree course and occupational status were found to be associated with lifestyle by regression analysis. Normal weight, overweight and obese students were generally properly aware of their weight condition; however, weight misperceptions were registered among normal and underweight undergraduates. Conclusions This study highlighted some critical issues regarding lifestyles of university students that suggest the need for health promotion interventions targeted mainly on physical activity.

Background: Evidence on influenza vaccine effectiveness (VE) in preventing mortality and morbidity in the elderly is weak. Our aim was to measure the VE against severe outcomes in the elderly. Methods: We conducted a multicentre hospital-based test-negative design (TND) case-control study, during the 2017/18 season, in four Italian hospitals. The study population included individuals aged ≥65 years hospitalized with Severe Acute Respiratory Infections (SARI). Patients were classified as cases and controls based on the results of the PCR influenza testing. We estimated VE by virus subtypes and specific VE for the trivalent adjuvanted vaccine (TIVadj). Results: 502 patients with SARI were enrolled: 118 (23.5%) tested positive (cases) and 384 (76.5%) tested negative (controls) for influenza. The adjusted VE of 48.5% for all vaccines was comparable to the adjusted VE for the TIVadj vaccine (48.3%). Adjusted VE for the TIVadj vaccine was 67.5% for A(H1N1)pdm09 and 44.5% for B viruses. Conclusion: We show a moderate adjusted VE of the TIVadj against all viruses, a good adjusted VE against A(H1N1)pdm09 strains and a moderate adjusted VE against B strains, despite a mismatch between the B circulating lineage and the lineage included in the vaccine. This is likely due to the cross-protection among B strains induced by the TIVadj in elderly patients.

Historically, vaccinations have enabled the eradication, elimination, and control of many debilitating diseases [...]

Background On 9th January 2020, China CDC reported a novel coronavirus (later named SARS-CoV-2) as the causative agent of the coronavirus disease 2019 (COVID-19). Identifying the first appearance of virus is of epidemiological importance to tracking and mapping the spread of SARS-CoV-2 in a country. We therefore conducted a retrospective observational study to detect SARS-CoV-2 in oropharyngeal samples collected from hospitalized patients with a Severe Acute Respiratory Infection (SARI) enrolled in the DRIVE (Development of Robust and Innovative Vaccine Effectiveness) study in five Italian hospitals (CIRI-IT BIVE hospitals network) (1st November 2019 – 29th February 2020). Objectives To acquire new information on the real trend in SARS-CoV-2 infection during pandemic phase I and to determine the possible early appearance of the virus in Italy. Materials and methods Samples were tested for influenza [RT-PCR assay (A/H1N1, A/H3N2, B/Yam, B/Vic)] in accordance with the DRIVE study protocol. Subsequently, swabs underwent molecular testing for SARS-COV-2. [one-step real-time multiplex retro-transcription (RT) PCR]. Results In the 1683 samples collected, no evidence of SARS-CoV-2 was found. Moreover, 28.3% (477/1683) of swabs were positive for influenza viruses, the majority being type A (358 vs 119 type B). A/H3N2 was predominant among influenza A viruses (55%); among influenza B viruses, B/Victoria was prevalent. The highest influenza incidence rate was reported in patients aged 0–17 years (40.3%) followed by those aged 18–64 years (24.4%) and ≥65 years (14.8%). Conclusions In Italy, some studies have shown the early circulation of SARS-CoV-2 in northern regions, those most severely affected during phase I of the pandemic. In central and southern regions, by contrast no early circulation of the virus was registered. These results are in line with ours. These findings highlight the need to continue to carry out retrospective studies, in order to understand the epidemiology of the novel coronavirus, to better identify the clinical characteristics of COVID-19 in comparison with other acute respiratory illnesses (ARI), and to evaluate the real burden of COVID-19 on the healthcare system.

Awareness of the importance of the microbial contamination of air and surfaces has increased significantly during the COVID-19 pandemic. The aim of this study was to evaluate the presence of bacteria and fungi in the air and on surfaces within some critical areas of large supermarkets with and without an ozonation system. Surveys were conducted in four supermarkets belonging to the same commercial chain of an Apulian city in June 2021, of which two (A and B) were equipped with an ozonation system, and two (C and D) did not have any air-diffused remediation treatment. There was a statistically significant difference in the total bacterial count (TBC) and total fungal count (TFC) in the air between A/B and C/D supermarkets (p = 0.0042 and p = 0.0002, respectively). Regarding surfaces, a statistically significant difference in TBC emerged between A/B and C/D supermarkets (p = 0.0101). To the best of our knowledge, this is the first study evaluating the effect of ozone on commercial structures in Italy. Future investigations, supported by a multidisciplinary approach, will make it possible to deepen the knowledge on this method of sanitation, in light of any other epidemic/pandemic waves.

Over the last few years, the phenomenon of fake news has become an important issue, especially during the worldwide COVID-19 pandemic, and also a serious risk for the public health. Due to the huge amount of information that is produced by the social media such as Facebook and Twitter it is becoming difficult to check the produced contents manually. This study proposes an automatic fake news detection system that supports or disproves the dubious claims while returning a set of documents from verified sources. The system is composed of multiple modules and it makes use of different techniques from machine learning, deep learning and natural language processing. Such techniques are used for the selection of relevant documents, to find among those, the ones that are similar to the tested claim and their stances. The proposed system will be used to check medical news and, in particular, the trustworthiness of posts related to the COVID-19 pandemic, vaccine and cure.

Public health workers (PHWs) have experienced substantial workload changes because of their role in managing measures to limit the spread of COVID-19. The study’s aim was to assess lifestyle changes in Italian PHWs during the pandemic. PHWs attending an annual meeting completed an anonymous questionnaire assessing their sociodemographic and behavioral characteristics and lifestyle changes during the pandemic. A total of 1000 questionnaires were completed. Most participants (63.5% women, mean age 40 ± 13.1 years) were of normal weight (61.5%), non-smokers (81.9%), had a total screen time of ≥5 h/day (83.1%), and slept at least 6 h/night (88.7%). Approximately one-third consumed sweet foods every day (30%) and did not engage in physical activity (34.6%). Current sweet food consumption, physical activity, and sleep were associated with changes in these behaviors in the last 2 years (Tau-b = 0.155; Tau-b = −0.175; Tau-b = −0.276, respectively, p < 0.001). An increase in remote working was associated with worse sleep (odds ratio (OR) 2.065, 95% confidence interval (CI) 1.482–2.877) and diet (OR 1.982, 95% CI 1.385–2.838), and increased tablet/PC use (OR 3.314, 95% CI 2.358–4.656). Health promotion measures are needed to support the adoption of healthy lifestyles in this population during the current pandemic.

Rainfall estimation based on the impact of rain on electromagnetic waves is a novel methodology that has had notable advancements during the last few years. Many studies conducted on this topic in the past considered only the electromagnetic waves with frequencies greater than 10 GHz since the rainfall impact on the electromagnetic wave attenuation is reduced at lower frequencies. Over the last few years, some authors have demonstrated that there can be a non-negligible attenuation even on the signals received on a global system for mobile communications mobile terminal in presence of rain. In this paper, we propose a new classification method based on a probabilistic neural network to obtain an accurate classification between four rainfall intensities (no rain, weak rain, moderate rain, and heavy rain). The innovative rainfall classification method is based on three received signal level (RSL) local features of the 4G/LTE: the instantaneous RSL, the average RSL value, and its variance calculated by using a sliding window. The proposed method exhibits good performance, obtaining an overall correct classification rate of 96.7%. Almost all papers on this topic present in the literature focus on electromagnetic waves with frequencies greater than 10 GHz, in which the rain impact is more relevant, according to the rain attenuation model. However, only the 4G/LTE signal has such widespread geographic coverage, so the proposed classification method can provide noticeable improvements in the creation of rainfall maps with higher spatial resolution.

In Italy, at the end of 2020, a voluntary immunization plan against COVID-19 was introduced, involving elderly among the first target categories. The aim of this study was to assess, through an online questionnaire, the acceptance of COVID-19 vaccination in a sample of older adults from southern Italy. Of a total of 1041 respondents (41.7% males, mean age 76.6 ± 6.5), 965 (92.7%) were vaccinated or willing to be vaccinated against COVID-19, although less than half of the sample was favorable to vaccinations and agreed with mandatory immunization. Acceptance of COVID-19 vaccination was found to be positively related with higher educational level (OR = 1.875, CI95% = 1.113–3.161; p = 0.018) and having social/mass media as a main source of information (OR = 2.415 CI95% = 1.358–4.296, p = 0.003). On the contrary, an inverse relationship was found between acceptance of COVID-19 vaccination and having fulfilled the questionnaire after the introduction of green pass (OR = 0.218, CI95% = 0.129–0.369; p < 0.001). Therefore, although this evidence needs to be further confirmed, it is possible to agree with previous studies reporting that compulsory measures, such as green pass implementation, must be accompanied by effective education and information strategies of the target population.

At the end of 2020, the Italian Ministry of Health launched a national vaccination campaign to counteract the COVID-19 pandemic. The present study aimed at appraising levels of knowledge about and acceptance of COVID-19 vaccination in a sample of Italian undergraduates during the first phase of the immunization plan. A web-based questionnaire was administered to students attending universities in Bari, Naples, and Rome during the period February–April 2021. Of the total of 3226 participants, 91.9% were keen to receive a COVID-19 vaccination. More than 80% gave correct answers to questions about COVID-19 vaccine administration, functioning, and effects on community health. However, only 63.8% identified the correct composition of the available vaccines. Knowledge was found to be related to sociodemographic features and COVID-19 vaccination acceptance (p < 0.05). COVID-19 vaccination acceptance was found to be related to having a previous vaccination against influenza (OR 3.806, CI 95% 1.181–12.267; p = 0.025) and knowledge (OR 4.759, CI 95% 2.106–10.753; p = 0.000). These results show a good level of awareness about COVID-19 vaccination in this population, which may indicate the effectiveness of communication strategies accompanying the COVID-19 immunization campaign in Italy.

The coronavirus disease 2019 (COVID-19) pandemic has led to the adoption of restriction measures that have had notable consequences on the health and wellbeing of individuals. This survey was carried out on a sample of 905 Albanian undergraduates to assess their knowledge about COVID-19 and their health-related behaviors and communication changes during lockdown. The students were invited to complete a pre-validated questionnaire during lessons. The results show that the majority of the surveyed students were able to answer correctly about the main epidemiological features of the disease. The level of knowledge was proven to be proportional to the students’ education level (enrollment year and age). No considerable relationship emerged with respect to diet or smoking. On the other hand, a relevant portion of the sample (37.6%) declared decreased physical activity (PA). Finally, a notable increase in the intensity and frequency of communication with their peers and with their parents was declared by 34.7% and 50.8% of the sample, respectively. Lifestyle variables were found to be mutually related, as were communication outcomes. The participants showed a satisfactory awareness regarding the COVID-19 epidemic. However, the registered reduction in PA may represent a public health issue and should be addressed with adequate policies. The use of electronic media seems to have increased communication habits in this population group.

Every season, circulating influenza viruses change; therefore, vaccines must be reformulated each year. We aimed to estimate vaccine effectiveness (VE) against severe influenza infection for the 2018/19 season in Italy. We conducted a test-negative design case-control study at five Italian hospitals. We estimated influenza VE against severe acute respiratory infection (SARI) requiring hospitalisation overall, and by virus subtype, vaccine brand, and age. The 2018/19 season was characterised by A(H1N1)pmd09 and A(H3N2) influenza viruses. Vaccine coverage among

Starting from 2013, the number of unvaccinated people alarmingly increased in Italy; therefore, in 2017 a new Vaccine National Plan was approved. Healthcare workers (HCWs), especially public health professionals (PHPs, i.e., workers in in the sector of hygiene and preventive medicine), have an important role in informing and promoting vaccinations. In this context, the Italian Study Group of Hospital Hygiene of the Italian Society of Hygiene, Preventive Medicine and Public Health (GISIO-SItI) conducted a national survey to assess knowledge, attitude, and practices towards recommended vaccinations among PHPs. The survey was conducted during October 2019 with an anonymous questionnaire distributed to PHPs attending the 52° SItI National Congress. Overall, 57.1% of operators answered correctly to all seven recommended vaccinations, 12.8% reported to be vaccinated for all seven recommended vaccinations, while 30% were naturally immunized. A higher immunization coverage was reported for anti-hepatitis B (88.9%) and measles (86.1%), and 81.3% of the participants reported being offered the influenza vaccination during the 2018/2019 season. The majority of our sample indicated that hepatitis B (95%) and influenza (93.7%) were the recommended vaccines for HCWs, while less was known regarding varicella, pertussis, diphtheria, and tetanus boosters every 10 years. PHPs who were vaccinated (or who intended to be vaccinated) were more likely to recommend vaccinations to their patients and provided a reassuring example to those hesitant patients. Finally, this is the first study that identified good algorithms (using the techniques of machine learning as Random Forest and Deep Learning) to predict the knowledge of PHPs regarding recommended vaccinations with possible applications in other national and international contexts.

Background/purpose: According to WHO recommendations, 12-year-olds are considered an important target group for evaluating the level of dental caries among children with permanent teeth, and are often chosen for international comparisons. The aim of the present study was to evaluate the current oral health status of 12-year-old children in southeast Italy, stratified by gender and residential area. Materials and methods: The survey was conducted on 431 children enrolled by multistage cluster sampling. A dental caries experience index (decayed, missing, and filled permanent teeth; DMFT) was recorded at schools by a team of examiners trained at the start of the study. Statistical analyses by Chi-square, Fisher's exact, and Wilcoxon tests were performed using SAS version 9.1 software for PCs. We applied the Zero-Inflated Negative Binomial regression model in the STATA package. Results: Caries prevalence was recorded in 38.3% of the sample. Estimated means and 95% confidence intervals of the DMFT index by gender were: 1.15 (0.91–1.39) for males, 1.26 (1.02–1.5) for females, and 1.21 (1.03–1.39) for the total sample. The D component of the index was dominant. The mean number of caries found in southeast Italy was significantly higher than the national mean (t=3.125, P=0.002), but significantly lower than the mean for south Italy (t=−2.125, P=0.03). Results of the regression model showed that only the mother and father's nationality and educational level contributed to the DMFT. Conclusions: The oral health situation of 12-year-old children from southeast Italy seems to be in line with that in other Western European countries.

In this paper we devise a neural-network-based model to improve the production workflow of organic solar cells (OSCs). The investigated neural model is used to reckon the relation between the OSC’s generated power and several device’s properties such as the geometrical parameters and the active layers thicknesses. Such measurements were collected during an experimental campaign conducted on 80 devices. The collected data suggest that the maximum generated power depends on the active layer thickness. The mathematical model of such a relation has been determined by using a feedforward neural network (FFNN) architecture as a universal function approximator. The performed simulations show good agreement between simulated and experimental data with an overall error of about 9%. The obtained results demonstrate that the use of a neural model can be useful to improve the OSC manufacturing processes.

We investigated Legionella and Pseudomonas contamination of hot water in a cross-sectional multicentric survey in Italy. Chemical parameters (hardness, free chlorine, and trace elements) were determined. Legionella spp. were detected in 33 (22.6%) and Pseudomonas spp. in 56 (38.4%) of 146 samples. Some factors associated with Legionella contamination were heater type, tank distance and capacity, water plant age, and mineral content. Pseudomonas presence was influenced by water source, hardness, free chlorine, and temperature. Legionella contamination was associated with a centralized heater, distance from the heater point >10 m, and a water plant >10 years old. Furthermore, zinc levels of 50 μg/L appeared to be protective against Legionella colonization. Legionella species and serogroups were differently distributed according to heater type, water temperature, and free chlorine, suggesting that Legionella strains may have a different sensibility and resistance to environmental factors and different ecologic niches.