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Article ; Online: Monitoring the West Nile virus outbreaks in Italy using open access data

Marco Mingione / Francesco Branda / Antonello Maruotti / Massimo Ciccozzi / Sandra Mazzoli

Scientific Data, Vol 10, Iss 1, Pp 1-

2023 Volume 11

Abstract: Abstract This paper introduces a comprehensive dataset on West Nile virus outbreaks that have occurred in Italy from September 2012 to November 2022. We have digitized bulletins published by the Italian National Institute of Health to demonstrate the ... ...

Abstract	Abstract This paper introduces a comprehensive dataset on West Nile virus outbreaks that have occurred in Italy from September 2012 to November 2022. We have digitized bulletins published by the Italian National Institute of Health to demonstrate the potential utilization of this data for the research community. Our aim is to establish a centralized open access repository that facilitates analysis and monitoring of the disease. We have collected and curated data on the type of infected host, along with additional information whenever available, including the type of infection, age, and geographic details at different levels of spatial aggregation. By combining our data with other sources of information such as weather data, it becomes possible to assess potential relationships between West Nile virus outbreaks and environmental factors. We strongly believe in supporting public oversight of government epidemic management, and we emphasize that open data play a crucial role in generating reliable results by enabling greater transparency.
Keywords	Science ; Q
Subject code	306
Language	English
Publishing date	2023-11-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Molecular Epidemiology of HIV-1 in African Countries

Marta Giovanetti / Massimo Ciccozzi / Cristina Parolin / Alessandra Borsetti

Pathogens, Vol 9, Iss 1072, p

A Comprehensive Overview

2020 Volume 1072

Abstract: The human immunodeficiency virus type 1 (HIV-1) originated in non-human primates in West-central Africa and continues to be a major global public health issue, having claimed almost 33 million lives so far. In Africa, it is estimated that more than 20 ... ...

Abstract	The human immunodeficiency virus type 1 (HIV-1) originated in non-human primates in West-central Africa and continues to be a major global public health issue, having claimed almost 33 million lives so far. In Africa, it is estimated that more than 20 million people are living with HIV/Acquired Immunodeficiency Syndrome (AIDS) and that more than 730,000 new HIV-1 infections still occur each year, likely due to low access to testing. The high genetic variability of HIV-1, due to a fast replication cycle and high mutation rate, may cause the generation of many viral variants in a single infected patient during a single day. Therefore, the active monitoring and characterization of the HIV-1 subtypes and recombinant forms circulating through African countries poses a significant challenge to more specific diagnoses, treatments, care, and intervention strategies. In this review, a concise characterization of all the subtypes and recombinant forms circulating in Africa is presented to highlight the magnitude of the HIV-1 threat among the African countries and to understand virus genetic diversity and dispersion dynamics better.
Keywords	HIV-1 ; Africa ; subtypes ; circulating recombinant form (CRF) ; recombinant ; Medicine ; R
Subject code	306
Language	English
Publishing date	2020-12-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Machine Learning analysis of high-grade serous ovarian cancer proteomic dataset reveals novel candidate biomarkers

Federica Farinella / Mario Merone / Luca Bacco / Adriano Capirchio / Massimo Ciccozzi / Daniele Caligiore

Scientific Reports, Vol 12, Iss 1, Pp 1-

2022 Volume 12

Abstract: Abstract Ovarian cancer is one of the most common gynecological malignancies, ranking third after cervical and uterine cancer. High-grade serous ovarian cancer (HGSOC) is one of the most aggressive subtype, and the late onset of its symptoms leads in ... ...

Abstract	Abstract Ovarian cancer is one of the most common gynecological malignancies, ranking third after cervical and uterine cancer. High-grade serous ovarian cancer (HGSOC) is one of the most aggressive subtype, and the late onset of its symptoms leads in most cases to an unfavourable prognosis. Current predictive algorithms used to estimate the risk of having Ovarian Cancer fail to provide sufficient sensitivity and specificity to be used widely in clinical practice. The use of additional biomarkers or parameters such as age or menopausal status to overcome these issues showed only weak improvements. It is necessary to identify novel molecular signatures and the development of new predictive algorithms able to support the diagnosis of HGSOC, and at the same time, deepen the understanding of this elusive disease, with the final goal of improving patient survival. Here, we apply a Machine Learning-based pipeline to an open-source HGSOC Proteomic dataset to develop a decision support system (DSS) that displayed high discerning ability on a dataset of HGSOC biopsies. The proposed DSS consists of a double-step feature selection and a decision tree, with the resulting output consisting of a combination of three highly discriminating proteins: TOP1, PDIA4, and OGN, that could be of interest for further clinical and experimental validation. Furthermore, we took advantage of the ranked list of proteins generated during the feature selection steps to perform a pathway analysis to provide a snapshot of the main deregulated pathways of HGSOC. The datasets used for this study are available in the Clinical Proteomic Tumor Analysis Consortium (CPTAC) data portal ( https://cptac-data-portal.georgetown.edu/ ).
Keywords	Medicine ; R ; Science ; Q
Subject code	006 ; 004
Language	English
Publishing date	2022-02-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Prevention of HBV Reactivation in Hemato-Oncologic Setting during COVID-19

Caterina Sagnelli / Antonello Sica / Massimiliano Creta / Alessandra Borsetti / Massimo Ciccozzi / Evangelista Sagnelli

Pathogens, Vol 11, Iss 567, p

2022 Volume 567

Abstract: Onco-hematologic patients are highly susceptible to SARS-CoV-2 infection and, once infected, frequently develop COVID-19 due to the immunosuppression caused by tumor growth, chemotherapy and immunosuppressive therapy. In addition, COVID-19 has also been ... ...

Abstract	Onco-hematologic patients are highly susceptible to SARS-CoV-2 infection and, once infected, frequently develop COVID-19 due to the immunosuppression caused by tumor growth, chemotherapy and immunosuppressive therapy. In addition, COVID-19 has also been recognized as a further cause of HBV reactivation, since its treatment includes the administration of corticosteroids and some immunosuppressive drugs. Consequently, onco-hematologic patients should undergo SARS-CoV-2 vaccination and comply with the rules imposed by lockdowns or other forms of social distancing. Furthermore, onco-hematologic facilities should be adapted to new needs and provided with numerically adequate health personnel vaccinated against SARS-CoV-2 infection. Onco-hematologic patients, both HBsAg-positive and HBsAg-negative/HBcAb-positive, may develop HBV reactivation, made possible by the support of the covalently closed circular DNA (cccDNA) persisting in the hepatocytic nuclei of patients with an ongoing or past HBV infection. This occurrence must be prevented by administering high genetic barrier HBV nucleo(t)side analogues before and throughout the antineoplastic treatment, and then during a long-term post-treatment follow up. The prevention of HBV reactivation during the SARS-CoV-2 pandemic is the topic of this narrative review.
Keywords	COVID-19 ; SARS-CoV-2 ; hepatitis B virus ; reactivation ; chemotherapy ; immunosuppression ; Medicine ; R
Subject code	610
Language	English
Publishing date	2022-05-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Evaluating the COVID-19 impact in Italian regions via multi criteria analysis.

Francesca Santucci / Martina Nobili / Luca Faramondi / Gabriele Oliva / Bianca Mazzà / Antonio Scala / Massimo Ciccozzi / Roberto Setola

PLoS ONE, Vol 18, Iss 5, p e

2023 Volume 0285452

Abstract: Italy was the first European country to be significantly impacted by the COVID-19 pandemic. The lack of similar previous experiences and the initial uncertainty regarding the new virus resulted in an unpredictable health crisis with 243,506 total ... ...

Abstract	Italy was the first European country to be significantly impacted by the COVID-19 pandemic. The lack of similar previous experiences and the initial uncertainty regarding the new virus resulted in an unpredictable health crisis with 243,506 total confirmed cases and 34,997 deaths between February and July 2020. Despite the panorama of precariousness and the impelling calamity, the country successfully managed many aspects of the early stages of the health and socio-economic crisis. Nevertheless, many disparities can be identified at the regional level. The study aims to determine which aspects of regional management were considered more important by the citizens regarding economic and health criteria. A survey was designed to gather responses from the population on the Italian regions' response and provide a ranking of the regions. The 29-item online survey was provided to 352 individuals, and the collected data were analyzed using the Analytic Hierarchy Process methodology. The results show a general agreement in considering of greater relevance the healthcare policies rather than the economic countermeasures adopted by regional governments. Our analysis associated a weight of 64% to the healthcare criteria compared to the economic criteria with a weight of 36%. In addition to the results obtained from the Analytic Hierarchy Process, the sample's composition was analyzed to provide an overall assessment of the Italian regions. To do so, we collected objective data for each region and multiplied them by the overall weight obtained for each sub-criteria. Looking at the propensity to vaccination or the belief in a relation between COVID-19 and 5G according to age and educational qualification helps understand how public opinion is structured according to cultural and anthropological differences.
Keywords	Medicine ; R ; Science ; Q
Language	English
Publishing date	2023-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Joining Forces against Antibiotic Resistance

Eleonora Cella / Marta Giovanetti / Francesca Benedetti / Fabio Scarpa / Catherine Johnston / Alessandra Borsetti / Giancarlo Ceccarelli / Taj Azarian / Davide Zella / Massimo Ciccozzi

Pathogens, Vol 12, Iss 1074, p

The One Health Solution

2023 Volume 1074

Abstract: Antibiotic resistance is a significant global health concern that affects both human and animal populations. The One Health approach acknowledges the interconnectedness of human health, animal health, and the environment. It emphasizes the importance of ... ...

Abstract	Antibiotic resistance is a significant global health concern that affects both human and animal populations. The One Health approach acknowledges the interconnectedness of human health, animal health, and the environment. It emphasizes the importance of collaboration and coordination across these sectors to tackle complex health challenges such as antibiotic resistance. In the context of One Health, antibiotic resistance refers to the ability of bacteria to withstand the efficacy of antibiotics, rendering them less effective or completely ineffective in treating infections. The emergence and spread of antibiotic-resistant bacteria pose a threat to human and animal health, as well as to the effectiveness of medical treatments and veterinary interventions. In particular, One Health recognizes that antibiotic use in human medicine, animal agriculture, and the environment are interconnected factors contributing to the development and spread of antibiotic resistance. For example, the misuse and overuse of antibiotics in human healthcare, including inappropriate prescribing and patient non-compliance, can contribute to the selection and spread of resistant bacteria. Similarly, the use of antibiotics in livestock production for growth promotion and disease prevention can contribute to the development of antibiotic resistance in animals and subsequent transmission to humans through the food chain. Addressing antibiotic resistance requires a collaborative One Health approach that involves multiple participants, including healthcare professionals, veterinarians, researchers, and policymakers.
Keywords	antimicrobial resistance ; antibiotic resistance ; One Health ; Medicine ; R
Subject code	360
Language	English
Publishing date	2023-08-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Khosta

Fabio Scarpa / Elena Imperia / Alessandra Ciccozzi / Stefano Pascarella / Miriana Quaranta / Marta Giovanetti / Alessandra Borsetti / Nicola Petrosillo / Massimo Ciccozzi

Infectious Disease Reports, Vol 15, Iss 31, Pp 307-

A Genetic and Structural Point of View of the Forgotten Virus

2023 Volume 318

Abstract: Bats are well-known to be natural reservoirs of various zoonotic coronaviruses, which have caused outbreaks of severe acute respiratory syndrome (SARS) and the COVID-19 pandemic in 2002 and 2019, respectively. In late 2020, two new Sarbecoviruses were ... ...

Abstract	Bats are well-known to be natural reservoirs of various zoonotic coronaviruses, which have caused outbreaks of severe acute respiratory syndrome (SARS) and the COVID-19 pandemic in 2002 and 2019, respectively. In late 2020, two new Sarbecoviruses were found in Russia, isolated in Rhinolophus bats, i.e., Khosta-1 in R. ferrumequinum and Khosta-2 in R. hipposideros . The potential danger associated with these new species of Sarbecovirus is that Khosta-2 has been found to interact with the same entry receptor as SARS-CoV-2. Our multidisciplinary approach in this study demonstrates that Khosta-1 and -2 currently appear to be not dangerous with low risk of spillover, as confirmed by prevalence data and by phylogenomic reconstruction. In addition, the interaction between Khosta-1 and -2 with ACE2 appears weak, and furin cleavage sites are absent. While the possibility of a spillover event cannot be entirely excluded, it is currently highly unlikely. This research further emphasizes the importance of assessing the zoonotic potential of widely distributed batborne CoV in order to monitor changes in genomic composition of viruses and prevent spillover events (if any).
Keywords	bat SARS-like coronaviruses ; SARS-CoV-like viruses ; horseshoe bats ; Rhinolophus ; khosta viruses ; sarbecovirus ; Other systems of medicine ; RZ201-999
Language	English
Publishing date	2023-06-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Application of the ARIMA model on the COVID-2019 epidemic dataset

Domenico Benvenuto / Marta Giovanetti / Lazzaro Vassallo / Silvia Angeletti / Massimo Ciccozzi

Data in Brief, Vol 29, Iss , Pp - (2020)

2020

Abstract: Coronavirus disease 2019 (COVID-2019) has been recognized as a global threat, and several studies are being conducted using various mathematical models to predict the probable evolution of this epidemic. These mathematical models based on various factors ...

Abstract	Coronavirus disease 2019 (COVID-2019) has been recognized as a global threat, and several studies are being conducted using various mathematical models to predict the probable evolution of this epidemic. These mathematical models based on various factors and analyses are subject to potential bias. Here, we propose a simple econometric model that could be useful to predict the spread of COVID-2019. We performed Auto Regressive Integrated Moving Average (ARIMA) model prediction on the Johns Hopkins epidemiological data to predict the epidemiological trend of the prevalence and incidence of COVID-2019. For further comparison or for future perspective, case definition and data collection have to be maintained in real time. Keywords: COVID-2019 epidemic, ARIMA model, Forecast, Infection control
Keywords	Computer applications to medicine. Medical informatics ; R858-859.7 ; Science (General) ; Q1-390
Language	English
Publishing date	2020-04-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: The Biological Properties of the SARS-CoV-2 Cameroon Variant Spike

Stefano Pascarella / Martina Bianchi / Marta Giovanetti / Domenico Benvenuto / Alessandra Borsetti / Roberto Cauda / Antonio Cassone / Massimo Ciccozzi

Pathogens, Vol 11, Iss 814, p

An Intermediate between the Alpha and Delta Variants

2022 Volume 814

Abstract: An analysis of the structural effect of the mutations of the B.1.640.2 (IHU) Spike Receptor Binding Domain (RBD) and N-terminal Domain (NTD) is reported along with a comparison with the sister lineage B.1.640.1. and a selection of variants of concern. ... ...

Abstract	An analysis of the structural effect of the mutations of the B.1.640.2 (IHU) Spike Receptor Binding Domain (RBD) and N-terminal Domain (NTD) is reported along with a comparison with the sister lineage B.1.640.1. and a selection of variants of concern. The effect of the mutations on the RBD–ACE2 interaction was also assessed. The structural analysis applied computational methods that are able to carry out in silico mutagenesis to calculate energy minimization and the folding energy variation consequent to residue mutations. Tools for electrostatic calculation were applied to quantify and display the protein surface electrostatic potential. Interactions at the RBD–ACE2 interface were scrutinized using computational tools that identify the interactions and predict the contribution of each interface residue to the stability of the complex. The comparison among the RBDs shows that the most evident differences between the variants is in the distribution of the surface electrostatic potential: that of B.1.640.1 is as that of the Alpha RBD, while B.1.640.2 appears to have an intermediate surface potential pattern with characteristics between those of the Alpha and Delta variants. Moreover, the B.1.640.2 Spike includes the mutation E484K that in other variants has been suggested to be involved in immune evasion. These properties may hint at the possibility that B.1.640.2 emerged with a potentially increased infectivity with respect to the sister B.1.640.1 variant, but significantly lower than that of the Delta and Omicron variants. However, the analysis of their NTD domains highlights deletions, destabilizing mutations and charge alterations that can limit the ability of the B.1.640.1 and B.1.640.2 variants to interact with cellular components, such as cell surface receptors.
Keywords	B.1.640.2 ; B.1.640.1 ; IHU ; Alpha variant ; Delta variant ; NTD ; Medicine ; R
Subject code	612
Language	English
Publishing date	2022-07-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Implications of Possible HBV-Driven Regulation of Gene Expression in Stem Cell-like Subpopulation of Huh-7 Hepatocellular Carcinoma Cell Line

Ayse Banu Demir / Domenico Benvenuto / Bilge Karacicek / Yasemin Erac / Silvia Spoto / Silvia Angeletti / Massimo Ciccozzi / Metiner Tosun

Journal of Personalized Medicine, Vol 12, Iss 2065, p

2022 Volume 2065

Abstract: Elevated levels of STIM1, an endoplasmic reticulum Ca 2+ sensor/buffering protein, appear to be correlated with poor cancer prognosis in which microRNAs are also known to play critical roles. The purpose of this study is to investigate possible HBV ... ...

Abstract	Elevated levels of STIM1, an endoplasmic reticulum Ca 2+ sensor/buffering protein, appear to be correlated with poor cancer prognosis in which microRNAs are also known to play critical roles. The purpose of this study is to investigate possible HBV origins of specific microRNAs we identified in a stem cell-like subpopulation of Huh-7 hepatocellular carcinoma (HCC) cell lines with enhanced STIM1 and/or Orai1 expression that mimicked poor cancer prognosis. Computational strategies including phylogenetic analyses were performed on miRNome data we obtained from an EpCAM- and CD133-expressing Huh-7 HCC stem cell-like subpopulation with enhanced STIM1 and/or Orai1 expression originally cultured in the present work. Results revealed two putative regions in the HBV genome based on the apparent clustering pattern of stem loop sequences of microRNAs, including miR3653. Reciprocal analysis of these regions identified critical human genes, of which their transcripts are among the predicted targets of miR3653, which was increased significantly by STIM1 or Orai1 enhancement. Briefly, this study provides phylogenetic evidence for a possible HBV-driven epigenetic remodeling that alters the expression pattern of Ca 2+ homeostasis-associated genes in STIM1 - or Orai1 overexpressing liver cancer stem-like cells for a possible mutual survival outcome. A novel region on HBV-X protein may affect liver carcinogenesis in a genotype-dependent manner. Therefore, detection of the viral genotype would have a clinical impact on prognosis of HBV-induced liver cancers.
Keywords	hepatocellular carcinoma ; HBx ; miR3653 ; epithelial–mesenchymal transition (EMT) ; molecular evolution ; Medicine ; R
Subject code	570
Language	English
Publishing date	2022-12-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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