Cancer and Pregnancy: Estimates in Italy from Record-Linkage Procedures between Cancer Registries and the Hospital Discharge Database

Simple Summary Concurrence of pregnancy and cancer diagnosis is an uncommon but not rare event: about 1 pregnancy-associated cancer (PAC) out of 1000 pregnancies is the estimation currently available. This frequency is growing due to postponing childbearing to age groups more at risk of cancer. Interest in this topic is both epidemiological and clinical: improvement of diagnostic and therapeutic techniques makes management of cancer increasingly compatible with pregnancy. The occurrence of PAC challenges women and clinicians who need to manage the two events, safeguarding fetal outcomes without changing the maternal prognosis. This retrospective study aims to provide estimates for PAC and its time trend in Italy by analyzing cross-referenced data from population-based cancer registries and hospital discharges. The proposed methodology is applicable to other populations with available data from Cancer Registries linkable at an individual level with hospitalizations.Abstract The aim of this study is to describe the frequency and trend of pregnancy-associated cancer (PAC) in Italy, an increasingly relevant phenomenon due to postponing age at childbirth. To this purpose, a population-based retrospective longitudinal study design based on cohorts of women aged 15-49 diagnosed with cancer and concomitant pregnancy is proposed. The study uses 19 population-based Cancer Registries, covering about 22% of Italy, and linked at an individual level with Hospital Discharge Records. A total of 2,861,437 pregnancies and 3559 PAC are identified from 74,165 women of the cohort with a rate of 1.24 PAC per 1000 pregnancies. The most frequent cancer site is breast (24.3%), followed by thyroid (23.9%) and melanoma (14.3%). The most frequent outcome is delivery (53.1%), followed by voluntary termination of pregnancy and spontaneous abortion (both 12.0%). The trend of PAC increased from 2003 to 2015, especially when the outcome is delivery, thus confirming a new attitude of clinicians to manage cancer throughout pregnancy. This represents the first attempt in Italy to describe PAC from Cancer Registries data; the methodology is applicable to other areas with the same data availability. Evidence from this study is addressed to clinicians for improving clinical management of women with PAC

Mobile robot guidance using cellular neural networks and fuzzy logic

We show how a Cellular Neural Networks based im­age processing system together with a Tuzzy Logic controller are capable of providing the necessary signal processing to guide an autonomous mobile robot in a maze drawn on the fl.oor. In this way, a non-trivial navigation task is obtained by very sim­ple hardware, making real autonomous operation feasible. An autonomous line-following robot has been first simulated and is currently being imple­roented by simulating the CNN with a DSP, while the fuzzy algorithms run on a 386-microprocessor ­based microcontroller

Mycoplasma hominis Induces Mediastinitis after a Tonsillar Abscess

Mycoplasma hominis is commonly involved in genitourinary tract infections. We report a 59-year-old man who developed a M. hominis-associated mediastinitis following acute tonsillar infection

AN EARTH OBSERVATION COGNITIVE SYSTEM IN RESPONSE TO SARS-COVID-19 EMERGENCY

The pandemic emergency caused by the spread of COVID-19 has stressed the importance of promptly identifying new epidemic clusters and patterns, to ensure the implementation of local risk containment measures and provide the needed healthcare to the population. In this framework, artificial intelligence, GIS, geospatial analysis and space assets can play a crucial role. Social media analytics can be used to trigger Earth Observation (EO) satellite acquisitions over potential new areas of human aggregation. Similarly, EO satellites can be used jointly with social media analytics to systematically monitor wellknown areas of aggregation (green urban areas, public markets, etc.). The information that can be obtained from the Earth Cognitive System 4 COVID-19 (ECO4CO) are both predictive, aiming to identify possible new clusters of outbreaks, and at the same time supervisorial, by monitoring infrastructures (i.e. traffic jams, parking lots) or specific categories (i.e. teenagers, doctors, teachers, etc.). In this perspective, the technologies described in this paper will allow us to reach individuals involved in risky aggregation clusters and to investigate their health status. The ECO4CO data lake will be integrated with ad hoc data obtained by sanitary structures to understand trends and dynamics, to assess criticalities with respect to medical response and supplies, and to test possibilities useful to tackle potential future emergencies. The System will also provide geographical information on the spread of the infection which will allow an appropriate context-specific public health response to the epidemic. In the present study that is co-funded by ESA Space Solutions, the ECO4CO space asset-based system aims to reply to the emergency of the actual pandemic through the following pillars: • Cluster Area Identification: a predictive data analytics service using social media and news to automatically identify possible new outbreaks; • Epidemiological study and public health intervention: an applied and interdisciplinary approach which combines sanitary-epidemiological-clinical, geo-technological and geographical components and competences; • Intelligent Satellite Tasking: an autonomous system able to task EO data acquisitions; • Object Detection: a deep learning service able to identify objects and people gathering or movements from images and videos; • Tracking: an intelligent service able to track devices detected in a specific location, identifying suspect patterns or anomalies; • Logistic Planning: a predictive data analytics service to identify stock of medical centers and match them against future needs of medical supplies

Case Report Mycoplasma hominis Induces Mediastinitis after a Tonsillar Abscess

Mycoplasma hominis is commonly involved in genitourinary tract infections. We report a 59-year-old man who developed a M. hominis-associated mediastinitis following acute tonsillar infection

Abstracts from the 23rd Italian congress of Cystic Fibrosis and the 13th National congress of Cystic Fibrosis Italian Society

Cystic Fibrosis (CF) occurs most frequently in caucasian populations. Although less common, this disorder have been reported in all the ethnicities. Currently, there are more than 2000 described sequence variations in CFTR gene, uniformly distributed and including variants pathogenic and benign (CFTR1:www.genet.sickkids.on.ca/). To date,only a subset have been firmily established as variants annotated as disease-causing (CFTR2: www.cftr2.org). The spectrum and the frequency of individual CFTR variants, however, vary among specific ethnic groups and geographic areas. Genetic screening for CF with standard panels of CFTR mutations is widely used for the diagnosis of CF in newborns and symptomatic patients, and to diagnose CF carrier status. These screening panels have an high diagnostic sensitivity (around 85%) for CFTR mutations in caucasians populations but very low for non caucasians. Developed in the last decade, Next-Generation Sequencing (NGS) has been the last breakthrough technology in genetic studies with a substantial reduction in cost per sequenced base and a considerable enhancement of the sequence generation capabilities. Extended CFTR gene sequencing in NGS includes all the coding regions, the splicing sites and their flankig intronic regions, deep intronic regions where are localized known mutations,the promoter and the 5'-3' UTR regions. NGS allows the analysis of many samples concurrently in a shorter period of time compared to Sanger method . Moreover, NGS platforms are able to identify CFTR copy number variation (CNVs), not detected by Sanger sequencing. This technology has provided new and reliable approaches to molecular diagnosis of CF and CFTR-Related Disorders. It also allows to improve the diagnostic sensitivity of newborn and carrier screeningmolecular tests. In fact, bioinformatics tools suitable for all the NGS platforms can filter data generated from the gene sequencing, and analyze only mutations with well-established disease liability. This approach allows the development of targeted mutations panels with a higher number of frequent CF mutations for the target populationcompared to the standard panels and a consequent enhancement of the diagnostic sensitivity. Moreover, in the emerging challenge of diagnosing CF in non caucasians patients, the possibility of customize a NGS targeted mutations panel should increase the diagnostic sensitivity when the target population has different ethnicities