Transperineal Laser Ablation (TPLA) Treatment of Focal Low-Intermediate Risk Prostate Cancer.

Background: This interventional pilot study aimed to evaluate the short-term (3 years) efficacy of focal laser ablation (FLA) in treating the index lesion of low-intermediate-risk prostate cancer, along with assessing the safety of the procedure (ClinicalTrials.gov ID NCT04045756). Methods: Forty patients aged between 46 and 86 with histologically proven organ-confined prostate cancer and low-to-intermediate progression risk were included. FLA was performed under percutaneous fusion magnetic resonance/ultrasound guidance in a Day Hospital setting under local anesthesia. Patients underwent regular clinical and functional assessments through the international index of erectile function (IIEF-5) and the International Prostatism Symptom Score (IPSS), PSA measurements, post-procedure MRI scans, and biopsies at 36 months or if positive findings were detected earlier. Statistical analyses were conducted to assess trends in PSA levels and cavity dimensions over time. Results: Forty patients were initially included, with fifteen lost to follow-up. At 36 months, a mean PSA reduction of 60% was observed, and 80% of MRI scans showed no signs of in-field clinically significant residual/recurrent cancer. Biopsies at 36 months revealed no malignant findings in 20 patients. No deterioration in sexual function or urinary symptoms was recorded. Conclusions: FLA appears to be safe, feasible, and effective in the index lesion treatment of low-intermediate-risk prostate cancer, with a high rate of tumor eradication and preservation of quality of life.

Vaccine Hesitancy, Knowledge, and COVID-19 Vaccination in a Sample of Italian and Albanian Healthcare Students Attending an University in Albania.

BACKGROUND: Vaccine hesitancy (VH) has increased over the past decade with large geographical variations between countries, posing a threat to global public health. This phenomenon is growing in the general population as well as among healthcare workers (HCWs), who are the most reliable source of vaccine-related information for patients. Special attention must therefore be paid to medical students, who are the future HCWs. METHODS: We conducted a cross-sectional study (November 2022-January 2023) on all the Albanian and Italian students attending medical science courses at the Catholic University "Our Lady of Good Counsel" (Tirane, Albania) to investigate VH and the factors contributing to it (using the Vaccination Attitude Examination Scale-VAX), including COVID-19 vaccination. Vaccine knowledge was assessed using the Zingg and Siegrist Scale. Students were asked to voluntarily answer an anonymous questionnaire. RESULTS: 689 questionnaires were collected (58.8% Albanians, 72.3% female; 70.4% aged 20-25 years; 70.4% attending the Medicine and Surgery course). Generally, students showed low VH, especially Italians (p < 0.001); however, some hesitancy was observed regarding the potential long-term effects of vaccines, especially among Albanians (p < 0.05). The results also showed a significant difference in vaccine knowledge scores between different course years (χ2 = 90.058; df = 40; p = < 0.001) and different degree courses (χ2 = 89.932; df = 40; p = < 0.001). With regard to COVID-19 vaccination, being of Albanian origin significantly increases the risk of not being vaccinated (OR = 7.215; 95%CI 3.816-13.640, p < 0.001), highlighting possible differences in vaccine coverage and policy between the two countries. CONCLUSION: Vaccine hesitancy should be addressed at early stages during medical sciences courses, in order to protect future healthcare workers, to preserve essential health services, and reduce the risk of further pandemics.

Lung clearance index short-term variability in cystic fibrosis: a pre-post pulmonary exacerbation study.

BACKGROUND: Multiple Breath washout (MBW) represents an important tool to detect early a possible pulmonary exacerbation especially in Cystic Fibrosis (CF) disease. Lung clearance index (LCI) is the most commonly reported multiple breath washout (MBW) index and in the last years was used as management measure for evaluation. Our aim was to analyze clinical utility of LCI index variability in pulmonary exacerbation in CF after intravenous (IV) antibiotic therapy. METHODS: A single-center study was conducted at CF Unit of Bambino Gesù Children's Hospital among hospitalized > 3 years patients for pulmonary exacerbations and treated with antibiotic IV treatment for 14 days. MBW and spirometry were evaluated within 72 h of admission to hospital and at the end of hospitalization. Descriptive analysis was conducted and correlations between quantitative variables were investigated. RESULTS: Fifty-seven patients (M22/F35) with an average age 18.56 (± 8.54) years were enrolled. LCI2.5 was significantly reduced at the end of antibiotic treatment in both pediatric and adult populations with an average reduction of -6,99%; 37/57 patients denoted an improvement, 20/57 are stable or worsened in LCI2.5 values and 4/57 (7.02%) had a significant deterioration (> 15%) at end of treatment. On the contrary a significative elevation of FEV1 and FVC were found, respectively of + 7,30% and of + 5,46%. A positive good correlection among LCI 2.5 and Scond (rho = + 0,615, p = 0.000) and LCI 2.5 and Sacin (rho = + 0,649, p = 0.000) and a negative strong correlation between FEV1 and LCI 2.5 were found in post treatment period. A similar modification of LCI 2.5 and FEV1 was noticed in both adult and pediatric population. CONCLUSIONS: LCI may have a role in the routine clinical care of both adult and pediatric CF patients as a good tool to assess response to IV antibiotic end-therapy in the same way as FEV1.

A novel, integrated approach for understanding and investigating Healthcare Associated Infections: A risk factors constellation analysis.

INTRODUCTION: Healthcare-associated infections (HAIs) and antimicrobial resistance (AMR) are major public health threats in upper- and lower-middle-income countries. Electronic health records (EHRs) are an invaluable source of data for achieving different goals, including the early detection of HAIs and AMR clusters within healthcare settings; evaluation of attributable incidence, mortality, and disability-adjusted life years (DALYs); and implementation of governance policies. In Italy, the burden of HAIs is estimated to be 702.53 DALYs per 100,000 population, which has the same magnitude as the burden of ischemic heart disease. However, data in EHRs are usually not homogeneous, not properly linked and engineered, or not easily compared with other data. Moreover, without a proper epidemiological approach, the relevant information may not be detected. In this retrospective observational study, we established and engineered a new management system on the basis of the integration of microbiology laboratory data from the university hospital "Policlinico Tor Vergata" (PTV) in Italy with hospital discharge forms (HDFs) and clinical record data. All data are currently available in separate EHRs. We propose an original approach for monitoring alert microorganisms and for consequently estimating HAIs for the entire period of 2018. METHODS: Data extraction was performed by analyzing HDFs in the databases of the Hospital Information System. Data were compiled using the AREAS-ADT information system and ICD-9-CM codes. Quantitative and qualitative variables and diagnostic-related groups were produced by processing the resulting integrated databases. The results of research requests for HAI microorganisms and AMR profiles sent by the departments of PTV from 01/01/2018 to 31/12/2018 and the date of collection were extracted from the database of the Complex Operational Unit of Microbiology and then integrated. RESULTS: We were able to provide a complete and richly detailed profile of the estimated HAIs and to correlate them with the information contained in the HDFs and those available from the microbiology laboratory. We also identified the infection profile of the investigated hospital and estimated the distribution of coinfections by two or more microorganisms of concern. Our data were consistent with those in the literature, particularly the increase in mortality, length of stay, and risk of death associated with infections with Staphylococcus spp, Pseudomonas aeruginosa, Klebsiella pneumoniae, Clostridioides difficile, Candida spp., and Acinetobacter baumannii. Even though less than 10% of the detected HAIs showed at least one infection caused by an antimicrobial resistant bacterium, the contribution of AMR to the overall risk of increased mortality was extremely high. CONCLUSIONS: The increasing availability of health data stored in EHRs represents a unique opportunity for the accurate identification of any factor that contributes to the diffusion of HAIs and AMR and for the prompt implementation of effective corrective measures. That said, artificial intelligence might be the future of health data analysis because it may allow for the early identification of patients who are more exposed to the risk of HAIs and for a more efficient monitoring of HAI sources and outbreaks. However, challenges concerning codification, integration, and standardization of health data recording and analysis still need to be addressed.

Biological risk in Italian prisons: data analysis from the second to the fourth wave of COVID-19 pandemic.

BACKGROUND: The management of COVID-19 in Italian prisons triggered considerable concern at the beginning of the pandemic due to numerous riots which resulted in inmate deaths, damages and prison breaks. The aim of this study is to shed some light, through analysis of the infection and relevant disease parameters, on the period spanning from the second to the fourth wave of the outbreak in Italy's prisons. METHODS: Reproductive number (Rt) and Hospitalisation were calculated through a Eulerian approach applied to differential equations derived from compartmental models. Comparison between trends was performed through paired t-test and linear regression analyses. RESULTS: The infection trends (prevalence and Rt) show a high correlation between the prison population and the external community. Both the indices appear to be lagging 1 week in prison. The prisoners' Rt values are not statistically different from those of the general population. The hospitalisation trend of inmates strongly correlates with the external population's, with a delay of 2 weeks. The magnitude of hospitalisations in prison is less than in the external community for the period analysed. CONCLUSIONS: The comparison with the external community revealed that in prison the infection prevalence was greater, although Rt values showed no significant difference, and the hospitalisation rate was lower. These results suggest that the consistent monitoring of inmates results in a higher infection prevalence while a wide vaccination campaign leads to a lower hospitalisation rate. All three indices demonstrate a lag of 1 or 2 weeks in prison. This delay could represent a useful time-window to strengthen planned countermeasures.

Using Machine Learning to Explore Shared Genetic Pathways and Possible Endophenotypes in Autism Spectrum Disorder.

Autism spectrum disorder (ASD) is a heterogeneous condition, characterized by complex genetic architectures and intertwined genetic/environmental interactions. Novel analysis approaches to disentangle its pathophysiology by computing large amounts of data are needed. We present an advanced machine learning technique, based on a clustering analysis on genotypical/phenotypical embedding spaces, to identify biological processes that might act as pathophysiological substrates for ASD. This technique was applied to the VariCarta database, which contained 187,794 variant events retrieved from 15,189 individuals with ASD. Nine clusters of ASD-related genes were identified. The 3 largest clusters included 68.6% of all individuals, consisting of 1455 (38.0%), 841 (21.9%), and 336 (8.7%) persons, respectively. Enrichment analysis was applied to isolate clinically relevant ASD-associated biological processes. Two of the identified clusters were characterized by individuals with an increased presence of variants linked to biological processes and cellular components, such as axon growth and guidance, synaptic membrane components, or transmission. The study also suggested other clusters with possible genotype-phenotype associations. Innovative methodologies, including machine learning, can improve our understanding of the underlying biological processes and gene variant networks that undergo the etiology and pathogenic mechanisms of ASD. Future work to ascertain the reproducibility of the presented methodology is warranted.

Hesitancy toward Childhood Vaccinations: Preliminary Results from an Albanian Nursing Staff's Investigation.

Healthcare professionals are important models for their patients since their individual knowledge and attitudes toward vaccination can influence the patient's willingness to adhere to vaccination campaigns. After developing a structured questionnaire, it was administered to a sample of nursing staff working in public vaccination centers in Albania (December 2020-January 2021), in order to conduct a preliminary investigation aimed at describing knowledge, attitudes, beliefs, and hesitancy toward childhood vaccinations. Among the sample of nurses involved in the administration of vaccines (n.64, 92% females), most of them were confident about vaccines and favorable to childhood vaccinations (90%). However, when specifically investigating beliefs, nearly a quarter of the sample showed to be hesitant; 22% were unsure or partially agreed that vaccines might cause conditions such as autism and multiple sclerosis. A high risk of hesitancy was identified in the youngest staff especially when their work experience was below 10 years or when they graduated less than 10 years before (OR: 5.3, CI: 1.4-19.5; and OR: 4.2 CI: 1.2-14.6). Similarly, a low acceptance rate (54%) was detected for future childhood SARS-CoV-2 vaccines among the nurses, which is a sign of high levels of vaccine hesitancy. With regard to knowledge about childhood vaccine contraindications, none of the nurses identified all the ten correct answers, while only 13% answered at least six questions correctly. These preliminary results highlight the need of investigating more Albanian nursing staff's knowledge and attitudes toward child vaccinations, therefore investing in tailored training. Due to the ongoing Covid-19 pandemic and the roll-out of mass vaccination, the role of healthcare workers remains crucial and needs more support to manage the changing public opinion as well as quickly evolving vaccine technologies.

A High-Performance Gamma Spectrometer for Unmanned Systems Based on Off-the-Shelf Components.

Since the Fukushima Daiichi Nuclear Power Plant accident in March 2011, the technology available for unmanned aerial vehicles (UAVs) for radiation monitoring has improved greatly. Remote access to radiation-contaminated areas not only eliminates unnecessary exposure of civilians or military personnel, but also allows workers to explore inaccessible places. Hazardous levels of radioactive contamination can be expected as a result of accidents in the nuclear power industry or as a result of the intentional release of radioactive materials for terrorist purposes (dirty bombs, building contamination, etc.). The possibility to detect, identify, and characterize radiation and nuclear material using mobile and remote sensing platforms is a common requirement in the radiation sensing community. The technology has applications in homeland security and law enforcement, customs and border protection, nuclear power plant safety and security, nuclear waste monitoring, environmental recovery, and the military. In this work, the authors have developed, implemented, and characterized a gamma-ray detection and spectroscopy system capable of operating on a UAV. The system was mainly developed using open-source software and affordable hardware components to reduce development and maintenance costs and provide satisfactory performance as a detection instrument. The designed platform can be used to perform mapping or localization tasks to improve the risk assessment process for first responders during the management of radiological and nuclear incidents. First, the design process of the system is described; the result of the characterization of the platform is then presented together with the use of the prototype installed on a UAV in an exercise simulating a radiological and nuclear contamination scenario.

Biological Risk in Italian Prisons: From the COVID-19 Management to the Development of a Standardized Model for Emergency Response.

Within the confinements of critical infrastructures, the COVID-19 pandemic is posing a series of challenges to Health Management. In the spotlight of highly contagious and quick spreading diseases within such enclosed facilities, whether it be a detention facility or otherwise, the health and safety of those living within its internment is paramount. This paper aims to highlight the specific challenges and the possible solutions to counteract this problem, starting from the lessons learnt from the Italian prison system case study. Following the general description of the available resources within the Italian prisons, the study aimed at specifically describing the first counteracting measures deployed by the Italian prison authorities during the first phase of the COVID-19 outbreak (February-July 2020). The aim was to propose an integrated plan capable of responding to a biological threat within the prisons. In particular, the study describes the actions and technical features that, in accordance with national and international legal frameworks and the relevant organisational bodies that run the Italian Prison Service, had been adopted in managing, right from the start, the COVID-19 pandemic until Summer 2020. Available information and data showed the ability of the prison administration to comply almost completely with WHO's technical and human rights recommendations and also, in successfully handling prison emergencies both in terms of the sick and the deceased in line with the epidemiological framework of the general population. In addition, the paper proposes a draft of guidelines that should involve the National Health Service and the Prison Service that are aimed at supporting the local prison facilities with drawing up their own biological incident contingency plans. An approved, legal, standardised plan could increase the awareness of prison managers. It could even increase their self-confidence, in particular, with regard to cases of dispute and their ability to respond to them. In fact, it is valuable and forward-thinking to be able to demonstrate that every endeavour has been taken and that 'certified' best practices have been put in place in accordance with the national standards.

Clustering Analysis Supports the Detection of Biological Processes Related to Autism Spectrum Disorder.

Genome sequencing has identified a large number of putative autism spectrum disorder (ASD) risk genes, revealing possible disrupted biological pathways; however, the genetic and environmental underpinnings of ASD remain mostly unanswered. The presented methodology aimed to identify genetically related clusters of ASD individuals. By using the VariCarta dataset, which contains data retrieved from 13,069 people with ASD, we compared patients pairwise to build "patient similarity matrices". Hierarchical-agglomerative-clustering and heatmapping were performed, followed by enrichment analysis (EA). We analyzed whole-genome sequencing retrieved from 2062 individuals, and isolated 11,609 genetic variants shared by at least two people. The analysis yielded three clusters, composed, respectively, by 574 (27.8%), 507 (24.6%), and 650 (31.5%) individuals. Overall, 4187 variants (36.1%) were common to the three clusters. The EA revealed that the biological processes related to the shared genetic variants were mainly involved in neuron projection guidance and morphogenesis, cell junctions, synapse assembly, and in observational, imitative, and vocal learning. The study highlighted genetic networks, which were more frequent in a sample of people with ASD, compared to the overall population. We suggest that itemizing not only single variants, but also gene networks, might support ASD etiopathology research. Future work on larger databases will have to ascertain the reproducibility of this methodology.

Enhancing Radiation Detection by Drones through Numerical Fluid Dynamics Simulations.

This study addresses the optimization of the location of a radioactive-particle sensor on a drone. Based on the analysis of the physical process and of the boundary conditions introduced in the model, computational fluid dynamics simulations were performed to analyze how the turbulence caused by drone propellers may influence the response of the sensors. Our initial focus was the detection of a small amount of radioactivity, such as that associated with a release of medical waste. Drones equipped with selective low-cost sensors could be quickly sent to dangerous areas that first responders might not have access to and be able to assess the level of danger in a few seconds, providing details about the source terms to Radiological-Nuclear (RN) advisors and decision-makers. Our ultimate application is the simulation of complex scenarios where fluid-dynamic instabilities are combined with elevated levels of radioactivity, as was the case during the Chernobyl and Fukushima nuclear power plant accidents. In similar circumstances, accurate mapping of the radioactive plume would provide invaluable input-data for the mathematical models that can predict the dispersion of radioactivity in time and space. This information could be used as input for predictive models and decision support systems (DSS) to get a full situational awareness. In particular, these models may be used either to guide the safe intervention of first responders or the later need to evacuate affected regions.

Supporting Iraqi Kurdistan Health Authorities in Post-conflict Recovery: The Development of a Health Monitoring System.

Background: Iraq has endured several conflicts and socio-political tensions that have disrupted its public health system. Nowadays, because health data are not collected on a routine basis, the country still lacks proper statistics and, consequently, response plans to meet present and future health needs of its population. An international partnership is developing in the Iraqi Kurdistan a Health Monitoring System with the aim of supporting evidence-based health policy decisions. Methods: The pilot phase for assessing the feasibility of the programme was launched in 2015. In 2018 the implementation phase began. The first step was to choose the software platform and the coding system, as well as to identify the public hospitals (PH) and Public Health Centers (PHC) to be included in the e-health system. The technical infrastructure of each PHC or PH was updated. The staff of each center was trained in the use of the e-health system and in disease coding. Several seminars introduced regional and district health managers to the basic concepts of data-driven decision making. A local team of experts was trained to create a highly specialized staff with the objective of "training the trainers" and ensuring the future self-sufficiency of the system. Results: By September 2019, 59 PHC and PH were entering data in the Health Monitoring System, while 258 health operators (medical doctors, administrative staff, nurses, statisticians, IT and public health specialists, pharmacists) have been already trained. Currently, more than 600,000 disease events have been collected. Additionally, further 734 medical doctors, statisticians, and health managers have been trained on the basics of public health practice. The goal during the next 3 years is to reach 120 operative centers within the region, envisaging a subsequent expansion of the system to all Iraq. Conclusions: The creation of a functioning health monitoring system is feasible also in regions characterized by socio-political tensions. However, multiple stakeholder partnerships are essential. The provision of an e-health information system, coupled with the establishment of a team of local experts, allows the routinely and timely collection of health information, facilitating prompt responses to present and emerging needs, while guiding the formulation and evaluation of health policies.

Viral bioterrorism: Learning the lesson of Ebola virus in West Africa 2013-2015.

Among the potential biological agents suitable as a weapon, Ebola virus represents a major concern. Classified by the CDC as a category A biological agent, Ebola virus causes severe hemorrhagic fever, characterized by high case-fatality rate; to date, no vaccine or approved therapy is available. The EVD epidemic, which broke out in West Africa since the late 2013, has got the issue of the possible use of Ebola virus as biological warfare agent (BWA) to come to the fore once again. In fact, due to its high case-fatality rate, population currently associates this pathogen to a real and tangible threat. Therefore, its use as biological agent by terrorist groups with offensive purpose could have serious repercussions from a psychosocial point of view as well as on closely sanitary level. In this paper, after an initial study of the main characteristics of Ebola virus, its potential as a BWA was evaluated. Furthermore, given the spread of the epidemic in West Africa in 2014 and 2015, the potential dissemination of the virus from an urban setting was evaluated. Finally, it was considered the actual possibility to use this agent as BWA in different scenarios, and the potential effects on one or more nation's stability.

Ebola virus disease 2013-2014 outbreak in west Africa: an analysis of the epidemic spread and response.

The Ebola virus epidemic burst in West Africa in late 2013, started in Guinea, reached in a few months an alarming diffusion, actually involving several countries (Liberia, Sierra Leone, Nigeria, Senegal, and Mali). Guinea and Liberia, the first nations affected by the outbreak, have put in place measures to contain the spread, supported by international organizations; then they were followed by the other nations affected. In the present EVD outbreak, the geographical spread of the virus has followed a new route: the achievement of large urban areas at an early stage of the epidemic has led to an unprecedented diffusion, featuring the largest outbreak of EVD of all time. This has caused significant concerns all over the world: the potential reaching of far countries from endemic areas, mainly through fast transports, induced several countries to issue information documents and health supervision for individuals going to or coming from the areas at risk. In this paper the geographical spread of the epidemic was analyzed, assessing the sequential appearance of cases by geographic area, considering the increase in cases and mortality according to affected nations. The measures implemented by each government and international organizations to contain the outbreak, and their effectiveness, were also evaluated.