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  1. Article ; Online: Book review

    Andrea de Lorenzo

    Heart Vessels and Transplantation, Vol 6, Iss

    "Medicine: The Definitive Illustrated History" by Steve Parker

    2022  Volume 3

    Keywords history of medicine ; Diseases of the circulatory (Cardiovascular) system ; RC666-701
    Language English
    Publishing date 2022-09-01T00:00:00Z
    Publisher Center for Scientific Research and Development of Education.
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article ; Online: Gender Disparities and Outcomes Of Acute Coronary Syndromes In Brazil.

    Lorenzo, Andrea De

    Arquivos brasileiros de cardiologia

    2018  Volume 111, Issue 5, Page(s) 654–655

    MeSH term(s) Acute Coronary Syndrome ; Brazil ; Female ; Humans ; Male ; Prognosis ; Registries ; Sex Factors
    Language Portuguese
    Publishing date 2018-11-28
    Publishing country Brazil
    Document type Editorial ; Comment
    ZDB-ID 730261-7
    ISSN 1678-4170 ; 0066-782X
    ISSN (online) 1678-4170
    ISSN 0066-782X
    DOI 10.5935/abc.20180210
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 548: Show issues Location:
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  3. Article ; Online: Addiction biotypes: a paradigm shift for future treatment strategies?

    Pettorruso, Mauro / Di Lorenzo, Giorgio / De Risio, Luisa / Di Carlo, Francesco / d'Andrea, Giacomo / Martinotti, Giovanni

    Molecular psychiatry

    2024  

    Language English
    Publishing date 2024-01-19
    Publishing country England
    Document type Journal Article
    ZDB-ID 1330655-8
    ISSN 1476-5578 ; 1359-4184
    ISSN (online) 1476-5578
    ISSN 1359-4184
    DOI 10.1038/s41380-024-02423-w
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    Zs.A 4812: Show issues Location:
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  4. Article ; Online: Increased Severity of COVID-19 in People with Obesity: Are We Overlooking Plausible Biological Mechanisms?

    Tibiriçá, Eduardo / De Lorenzo, Andrea

    Obesity (Silver Spring, Md.)

    2020  Volume 28, Issue 8, Page(s) 1374

    MeSH term(s) Betacoronavirus ; COVID-19 ; Coronavirus ; Coronavirus Infections ; Humans ; Obesity ; Pandemics ; Pneumonia, Viral ; Respiratory Distress Syndrome ; SARS-CoV-2
    Keywords covid19
    Language English
    Publishing date 2020-07-06
    Publishing country United States
    Document type Letter ; Comment
    ZDB-ID 2230457-5
    ISSN 1930-739X ; 1071-7323 ; 1930-7381
    ISSN (online) 1930-739X
    ISSN 1071-7323 ; 1930-7381
    DOI 10.1002/oby.22887
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  5. Article ; Online: SPREAD: Spatiotemporal Pathogen Relationships and Epidemiological Analysis Dashboard.

    De Ruvo, Andrea / De Luca, Alessandro / Bucciacchio, Andrea / Castelli, Pierluigi / Di Lorenzo, Alessio / Radomski, Nicolas / Di Pasquale, Adriano

    Veterinaria italiana

    2024  

    Abstract: In the scope of public health, the rapid identification and control of infectious disease outbreaks are a paramount concern. Traditional surveillance methods often face challenges in effectively combining genetic, geographical, and temporal data, which ... ...

    Abstract In the scope of public health, the rapid identification and control of infectious disease outbreaks are a paramount concern. Traditional surveillance methods often face challenges in effectively combining genetic, geographical, and temporal data, which is crucial for a comprehensive understanding of disease transmission dynamics. Addressing this critical need, the Spatiotemporal Phylogenomic Research and Epidemiological Analysis Dashboard (SPREAD) emerges as an innovative standalone web-based application. SPREAD integrates several modules for detailed genomic relationships, pinpointing genetically close pathogens, and spatial mapping, providing in-depth views of how diseases spread across populations and territories, with significant advantage to manage both bacteria and viruses based on allele and variant calling, respectively. Designed for broad accessibility, SPREAD operates seamlessly within web browsers, eliminating the need for sophisticated IT infrastructure and facilitating its use across various public health contexts. Its intuitive interface ensures that users can effortlessly navigate complex datasets, facilitating widespread access to advanced surveillance capabilities. Through its initial deployments, SPREAD has proven instrumental in quickly identifying transmission clusters, significantly aiding in the formulation of prompt and targeted public health responses. Through the integration of state-of-the-art technology with a focus on user-centered design, SPREAD offers a promising solution that highlights the potential of digital health innovations.
    Language English
    Publishing date 2024-03-20
    Publishing country Italy
    Document type Journal Article
    ZDB-ID 2536397-9
    ISSN 1828-1427 ; 0505-401X
    ISSN (online) 1828-1427
    ISSN 0505-401X
    DOI 10.12834/VetIt.3476.23846.1
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  6. Article ; Online: Colloidal Quantum Dots for Explosive Detection: Trends and Perspectives.

    De Iacovo, Andrea / Mitri, Federica / De Santis, Serena / Giansante, Carlo / Colace, Lorenzo

    ACS sensors

    2024  Volume 9, Issue 2, Page(s) 555–576

    Abstract: Sensitive, accurate, and reliable detection of explosives has become one of the major needs for international security and environmental protection. Colloidal quantum dots, because of their unique chemical, optical, and electrical properties, as well as ... ...

    Abstract Sensitive, accurate, and reliable detection of explosives has become one of the major needs for international security and environmental protection. Colloidal quantum dots, because of their unique chemical, optical, and electrical properties, as well as easy synthesis route and functionalization, have demonstrated high potential to meet the requirements for the development of suitable sensors, boosting the research in the field of explosive detection. Here, we critically review the most relevant research works, highlighting three different mechanisms for explosive detection based on colloidal quantum dots, namely photoluminescence, electrochemical, and chemoresistive sensing. We provide a comprehensive overview and an extensive discussion and comparison in terms of the most relevant sensor parameters. We highlight advantages, limitations, and challenges of quantum dot-based explosive sensors and outline future research directions for the advancement of knowledge in this surging research field.
    MeSH term(s) Quantum Dots/chemistry ; Explosive Agents
    Chemical Substances Explosive Agents
    Language English
    Publishing date 2024-02-02
    Publishing country United States
    Document type Journal Article ; Review
    ISSN 2379-3694
    ISSN (online) 2379-3694
    DOI 10.1021/acssensors.3c02097
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  7. Article ; Online: An Evolutionary Computation Approach for Twitter Bot Detection

    Luigi Rovito / Lorenzo Bonin / Luca Manzoni / Andrea De Lorenzo

    Applied Sciences, Vol 12, Iss 5915, p

    2022  Volume 5915

    Abstract: Bot accounts are automated software programs that act as legitimate human profiles on social networks. Identifying these kinds of accounts is a challenging problem due to the high variety and heterogeneity that bot accounts exhibit. In this work, we use ... ...

    Abstract Bot accounts are automated software programs that act as legitimate human profiles on social networks. Identifying these kinds of accounts is a challenging problem due to the high variety and heterogeneity that bot accounts exhibit. In this work, we use genetic algorithms and genetic programming to discover interpretable classification models for Twitter bot detection with competitive qualitative performance, high scalability, and good generalization capabilities. Specifically, we use a genetic programming method with a set of primitives that involves simple mathematical operators. This enables us to discover a human-readable detection algorithm that exhibits a detection accuracy close to the top state-of-the-art methods on the TwiBot-20 dataset while providing predictions that can be interpreted, and whose uncertainty can be easily measured. To the best of our knowledge, this work is the first attempt at adopting evolutionary computation techniques for detecting bot profiles on social media platforms.
    Keywords machine learning ; explainable AI ; cybersecurity ; supervised learning ; binary classification ; evolutionary computation ; Technology ; T ; Engineering (General). Civil engineering (General) ; TA1-2040 ; Biology (General) ; QH301-705.5 ; Physics ; QC1-999 ; Chemistry ; QD1-999
    Subject code 006
    Language English
    Publishing date 2022-06-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  8. Article ; Online: Prolongation of the QT Interval and Myocardial Ischemia Are More Pieces of the "Metabolically Unhealthy Obesity" Puzzle.

    De Lorenzo, Andrea

    The American journal of cardiology

    2017  Volume 120, Issue 5, Page(s) 891

    MeSH term(s) Humans ; Myocardial Ischemia ; Obesity
    Language English
    Publishing date 2017-06-15
    Publishing country United States
    Document type Letter ; Comment
    ZDB-ID 80014-4
    ISSN 1879-1913 ; 0002-9149
    ISSN (online) 1879-1913
    ISSN 0002-9149
    DOI 10.1016/j.amjcard.2017.06.008
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    Ui IV Zs.73: Show issues Location:
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  9. Article ; Online: Importance of the evaluation of systemic microvascular flow and reactivity in critically ill patients with coronavirus disease 2019 - COVID-19.

    Tibirica, Eduardo / De Lorenzo, Andrea

    Microvascular research

    2020  Volume 131, Page(s) 104028

    Abstract: Amidst the pandemic that has mesmerized the entire world, as it has not spared anyone according to any specific characteristic, some conditions have, in fact, emerged as risk factors for a complicated evolution of COVID-19. Older age, cardiovascular ... ...

    Abstract Amidst the pandemic that has mesmerized the entire world, as it has not spared anyone according to any specific characteristic, some conditions have, in fact, emerged as risk factors for a complicated evolution of COVID-19. Older age, cardiovascular disease including hypertension, diabetes and pulmonary disease, have been associated with more severe presentations and/or adverse prognosis. In this letter to the editor, we propose that the link between cardiovascular and metabolic diseases and the higher incidence and worse prognosis of COVID-19 patients is the (micro) vascular endothelium.
    MeSH term(s) Angiotensin-Converting Enzyme Inhibitors/pharmacology ; Betacoronavirus ; COVID-19 ; Coronavirus Infections/complications ; Coronavirus Infections/pathology ; Critical Illness ; Cytokines/metabolism ; Diabetes Complications ; Endothelium, Vascular/pathology ; Hemodynamics ; Humans ; Hypertension/complications ; Incidence ; Inflammation ; Lasers ; Microcirculation ; Pandemics ; Perfusion ; Phenotype ; Pneumonia, Viral/complications ; Pneumonia, Viral/pathology ; Prognosis ; Risk Factors ; SARS-CoV-2
    Chemical Substances Angiotensin-Converting Enzyme Inhibitors ; Cytokines
    Keywords covid19
    Language English
    Publishing date 2020-06-09
    Publishing country United States
    Document type Letter
    ZDB-ID 80307-8
    ISSN 1095-9319 ; 0026-2862
    ISSN (online) 1095-9319
    ISSN 0026-2862
    DOI 10.1016/j.mvr.2020.104028
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    Zs.A 746: Show issues Location:
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  10. Article ; Online: Waste Material Classification: A Short-Wave Infrared Discrete-Light-Source Approach Based on Light-Emitting Diodes.

    Manakkakudy, Anju / De Iacovo, Andrea / Maiorana, Emanuele / Mitri, Federica / Colace, Lorenzo

    Sensors (Basel, Switzerland)

    2024  Volume 24, Issue 3

    Abstract: Waste material classification is a challenging yet important task in waste management. The realization of low-cost waste classification systems and methods is critical to meet the ever-increasing demand for efficient waste management and recycling. In ... ...

    Abstract Waste material classification is a challenging yet important task in waste management. The realization of low-cost waste classification systems and methods is critical to meet the ever-increasing demand for efficient waste management and recycling. In this paper, we demonstrate a simple, compact and low-cost classification system based on optical reflectance measurements in the short-wave infrared for the segregation of waste materials such as plastics, paper, glass, and aluminium. The system comprises a small set of LEDs and one single broadband photodetector. All devices are controlled through low-cost and low-power electronics, and data are gathered and managed via a computer interface. The proposed system reaches accuracy levels as high as 94.3% when considering seven distinct materials and 97.0% when excluding the most difficult to classify, thus representing a valuable proof-of-concept for future system developments.
    Language English
    Publishing date 2024-01-26
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2052857-7
    ISSN 1424-8220 ; 1424-8220
    ISSN (online) 1424-8220
    ISSN 1424-8220
    DOI 10.3390/s24030809
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