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Article ; Online: Artificial intelligence: is it the right time for clinical laboratories?

Padoan, Andrea / Plebani, Mario

Clinical chemistry and laboratory medicine

2022 Volume 60, Issue 12, Page(s) 1859–1861

MeSH term(s)	Humans ; Artificial Intelligence ; Laboratories, Clinical ; Big Data ; Clinical Laboratory Services
Language	English
Publishing date	2022-10-24
Publishing country	Germany
Document type	Editorial
ZDB-ID	1418007-8
ISSN	1437-4331 ; 1434-6621 ; 1437-8523
ISSN (online)	1437-4331
ISSN	1434-6621 ; 1437-8523
DOI	10.1515/cclm-2022-1015
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Zs.A 121: Show issues

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Article ; Online: The Impact of Pre-Analytical Conditions on Human Serum Peptidome Profiling.

Padoan, Andrea

Proteomics. Clinical applications

2018 Volume 12, Issue 3, Page(s) e1700183

Abstract: The successful use of proteomic technology for the discovery of clinically relevant, new candidate biomarkers, especially in the low molecular weight range (peptidome), calls for a careful consideration of standardized operating procedures (SOP) for pre- ... ...

Abstract	The successful use of proteomic technology for the discovery of clinically relevant, new candidate biomarkers, especially in the low molecular weight range (peptidome), calls for a careful consideration of standardized operating procedures (SOP) for pre-analytical variables, including samples handling and storage. The current lack of standardization, widely considered a relevant source of random and systematic errors, underlies the uncertainty of analytical results and poor comparability, especially in multi-centric or inter-laboratory studies. In their recent study, Tsuchida et al. used the MALDI-TOF/MS technique to investigate the effect of long-term storage at -20 °C, -80 °C, and in liquid nitrogen on serum samples obtained for peptidomic analyses. The authors have also evaluated the effects of different sample thawing modalities. By including results from the same series as that reported on in a previous publication, they have effectively defined some important requirements for the peptidomic analysis of serum samples (e.g., maximum time intervals between venepuncture and serum separation [1 h], minimum temperature for long-term sera storage temperature [-80 °C], ideal conditions for sample thawing).
MeSH term(s)	Biomarkers ; Humans ; Molecular Weight ; Proteomics ; Serum ; Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
Chemical Substances	Biomarkers
Language	English
Publishing date	2018-03-15
Publishing country	Germany
Document type	Journal Article ; Comment
ZDB-ID	2261788-7
ISSN	1862-8354 ; 1862-8346
ISSN (online)	1862-8354
ISSN	1862-8346
DOI	10.1002/prca.201700183
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Zs.A 6575: Show issues

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Article ; Online: Flowing through laboratory clinical data: the role of artificial intelligence and big data.

Padoan, Andrea / Plebani, Mario

Clinical chemistry and laboratory medicine

2022 Volume 60, Issue 12, Page(s) 1875–1880

Abstract: During the last few years, clinical laboratories have faced a sea change, from facilities producing a high volume of low-cost test results, toward a more integrated and patient-centered service. Parallel to this paradigm change, the digitalization of ... ...

Abstract	During the last few years, clinical laboratories have faced a sea change, from facilities producing a high volume of low-cost test results, toward a more integrated and patient-centered service. Parallel to this paradigm change, the digitalization of healthcare data has made an enormous quantity of patients' data easily accessible, thus opening new scenarios for the utilization of artificial intelligence (AI) tools. Every day, clinical laboratories produce a huge amount of information, of which patients' results are only a part. The laboratory information system (LIS) may include other "relevant" compounding data, such as internal quality control or external quality assessment (EQA) results, as well as, for example, timing of test requests and of blood collection and exams transmission, these data having peculiar characteristics typical of big data, as volume, velocity, variety, and veracity, potentially being used to generate value in patients' care. Despite the increasing interest expressed in AI and big data in laboratory medicine, these topics are approaching the discipline slowly for several reasons, attributable to lack of knowledge and skills but also to poor or absent standardization, harmonization and problematic regulatory and ethical issues. Finally, it is important to bear in mind that the mathematical postulation of algorithms is not sufficient for obtaining useful clinical tools, especially when biological parameters are not evaluated in the appropriate context. It is therefore necessary to enhance cooperation between laboratory and AI experts, and to coordinate and govern processes, thus favoring the development of valuable clinical tools.
MeSH term(s)	Humans ; Big Data ; Artificial Intelligence ; Algorithms ; Delivery of Health Care ; Knowledge
Language	English
Publishing date	2022-07-18
Publishing country	Germany
Document type	Journal Article
ZDB-ID	1418007-8
ISSN	1437-4331 ; 1434-6621 ; 1437-8523
ISSN (online)	1437-4331
ISSN	1434-6621 ; 1437-8523
DOI	10.1515/cclm-2022-0653
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Zs.A 121: Show issues

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Article ; Online: Plasma lipids paediatric reference intervals: Indirect estimation using a large 14-year database.

Galozzi, Paola / Padoan, Andrea / Moretti, Carlo / Aita, Ada / Basso, Daniela

Journal of pediatric gastroenterology and nutrition

2024

Abstract: Objectives: Establishing direct reference intervals (RIs) for paediatric patients is a very challenging endeavour. Indirect RIs can address this problem, using existing clinical laboratory databases from real-world data research. Compared to the ... ...

Abstract	Objectives: Establishing direct reference intervals (RIs) for paediatric patients is a very challenging endeavour. Indirect RIs can address this problem, using existing clinical laboratory databases from real-world data research. Compared to the traditional direct method, the indirect approach is highly practical, widely applicable, and low-cost. Considering the relevance of dyslipidemia in the paediatric age, to provide better laboratory services to the local paediatric population, we established population-specific lipid RIs via data mining. Methods: Our laboratory information system was searched for cholesterol (TC), triglycerides (TG), low-density lipoprotein (LDL) and high-density lipoprotein (HDL) of patients aged less than 18 years, performed from January 2009 until December 2022. RIs were estimated using RefineR algorithm. Results: Values from 215,594 patients were initially collected. After refining data on the basis of specific exclusion criteria that left 17,933 patients, we determined the RIs for each analyte, including corresponding 95% confidence interval (95% CI). Age and sex partitions were required for proper stratification of the heterogenous subpopulations. Age-related variations in TC and TG values were observed mainly in children until 5 years. RIs were defined for children less than 3 years and for those of 3-18 years. In our population, the obtained RIs were comparable with those of the literature, but the upper TG limit in subjects under the age of 3 (2.03 mmol/L with 95% CI: 1.45-2.86) was lower than that previously reported. Conclusions: Our RIs, necessary for paediatric lipid monitoring, are tailored to the serviced patient population as should be done whenever possible.
Language	English
Publishing date	2024-04-12
Publishing country	United States
Document type	Journal Article
ZDB-ID	603201-1
ISSN	1536-4801 ; 0277-2116
ISSN (online)	1536-4801
ISSN	0277-2116
DOI	10.1002/jpn3.12210
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Zs.A 1728: Show issues

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Article ; Online: Artificial intelligence and laboratory data in rheumatic diseases.

Galozzi, Paola / Basso, Daniela / Plebani, Mario / Padoan, Andrea

Clinica chimica acta; international journal of clinical chemistry

2023 Volume 546, Page(s) 117388

Abstract: Artificial intelligence (AI)-based medical technologies are rapidly evolving into actionable solutions for clinical practice. Machine learning (ML) algorithms can process increasing amounts of laboratory data such as gene expression immunophenotyping ... ...

Abstract	Artificial intelligence (AI)-based medical technologies are rapidly evolving into actionable solutions for clinical practice. Machine learning (ML) algorithms can process increasing amounts of laboratory data such as gene expression immunophenotyping data and biomarkers. In recent years, the analysis of ML has become particularly useful for the study of complex chronic diseases, such as rheumatic diseases, heterogenous conditions with multiple triggers. Numerous studies have used ML to classify patients and improve diagnosis, to stratify the risk and determine disease subtypes, as well as to discover biomarkers and gene signatures. This review aims to provide examples of ML models for specific rheumatic diseases using laboratory data and some insights into relevant strengths and limitations. A better understanding and future application of these analytical strategies could facilitate the development of precision medicine for rheumatic patients.
MeSH term(s)	Humans ; Artificial Intelligence ; Algorithms ; Machine Learning ; Rheumatic Diseases/diagnosis ; Biomarkers
Chemical Substances	Biomarkers
Language	English
Publishing date	2023-05-13
Publishing country	Netherlands
Document type	Journal Article ; Review
ZDB-ID	80228-1
ISSN	1873-3492 ; 0009-8981
ISSN (online)	1873-3492
ISSN	0009-8981
DOI	10.1016/j.cca.2023.117388
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Ud II Zs.173: Show issues

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Article ; Online: Inflammation, Autoinflammation and Autoimmunity in Inflammatory Bowel Diseases.

Padoan, Andrea / Musso, Giulia / Contran, Nicole / Basso, Daniela

Current issues in molecular biology

2023 Volume 45, Issue 7, Page(s) 5534–5557

Abstract: In this review, the role of innate and adaptive immunity in the pathogenesis of inflammatory bowel diseases (IBD) is reported. In IBD, an altered innate immunity is often found, with increased Th17 and decreased Treg cells infiltrating the intestinal ... ...

Abstract	In this review, the role of innate and adaptive immunity in the pathogenesis of inflammatory bowel diseases (IBD) is reported. In IBD, an altered innate immunity is often found, with increased Th17 and decreased Treg cells infiltrating the intestinal mucosa. An associated increase in inflammatory cytokines, such as IL-1 and TNF-α, and a decrease in anti-inflammatory cytokines, such as IL-10, concur in favoring the persistent inflammation of the gut mucosa. Autoinflammation is highlighted with insights in the role of inflammasomes, which activation by exogenous or endogenous triggers might be favored by mutations of NOD and NLRP proteins. Autoimmunity mechanisms also take place in IBD pathogenesis and in this context of a persistent immune stimulation by bacterial antigens and antigens derived from intestinal cells degradation, the adaptive immune response takes place and results in antibodies and autoantibodies production, a frequent finding in these diseases. Inflammation, autoinflammation and autoimmunity concur in altering the mucus layer and enhancing intestinal permeability, which sustains the vicious cycle of further mucosal inflammation.
Language	English
Publishing date	2023-06-30
Publishing country	Switzerland
Document type	Journal Article ; Review
ZDB-ID	2000024-8
ISSN	1467-3045 ; 1467-3037
ISSN (online)	1467-3045
ISSN	1467-3037
DOI	10.3390/cimb45070350
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Zs.A 5122: Show issues

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Article ; Online: The Autocatalytic Chemical Reaction of a Soluble Biopolymer Derived from Municipal Biowaste.

Padoan, Elio / Montoneri, Enzo / Baglieri, Andrea / Contillo, Francesco / Francavilla, Matteo / Negre, Michéle

Molecules (Basel, Switzerland)

2024 Volume 29, Issue 2

Abstract: The paper discusses the perspectives of further implementation of the autocatalytic properties of a soluble biopolymer (SBP) derived from municipal biowastes for the realisation of a biorefinery producing value-added bio-products for consumer use. The ... ...

Abstract	The paper discusses the perspectives of further implementation of the autocatalytic properties of a soluble biopolymer (SBP) derived from municipal biowastes for the realisation of a biorefinery producing value-added bio-products for consumer use. The reaction of an SBP and water is reported to cause the depolymerisation and oxidation of the pristine SBP organic matter with the formation of carboxyl-functionalised polymers having lower molecular weight and CO
MeSH term(s)	Humans ; Hydrogen Peroxide ; Biopolymers ; Polymers ; Carbon ; Water
Chemical Substances	Hydrogen Peroxide (BBX060AN9V) ; Biopolymers ; Polymers ; Carbon (7440-44-0) ; Water (059QF0KO0R)
Language	English
Publishing date	2024-01-18
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	1413402-0
ISSN	1420-3049 ; 1431-5165 ; 1420-3049
ISSN (online)	1420-3049
ISSN	1431-5165 ; 1420-3049
DOI	10.3390/molecules29020485
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Zs.MO 81: Show issues

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Article ; Online: Risk of SARS-CoV-2 Reinfection in Children Within the 12 Months Following Mild COVID-19: Insights From a Survey Study.

Di Chiara, Costanza / Boracchini, Riccardo / Cantarutti, Anna / Kakkar, Fatima / Oletto, Andrea / Padoan, Andrea / Donà, Daniele / Giaquinto, Carlo

The Pediatric infectious disease journal

2024 Volume 43, Issue 4, Page(s) e128–e130

Abstract: Understanding the correlation between immune response and protection from COVID-19 will play a pivotal role in predicting the effectiveness of vaccines in children. We studied SARS-CoV-2 reinfection risk in children 12 months post-mild COVID-19. Children ...

Abstract	Understanding the correlation between immune response and protection from COVID-19 will play a pivotal role in predicting the effectiveness of vaccines in children. We studied SARS-CoV-2 reinfection risk in children 12 months post-mild COVID-19. Children under 5 years old exhibited lower reinfection risk than older infected or vaccinated siblings during 12 months postimmunization.
MeSH term(s)	Child ; Humans ; Child, Preschool ; SARS-CoV-2 ; COVID-19 ; Reinfection/epidemiology ; Siblings
Language	English
Publishing date	2024-01-18
Publishing country	United States
Document type	Journal Article
ZDB-ID	392481-6
ISSN	1532-0987 ; 0891-3668
ISSN (online)	1532-0987
ISSN	0891-3668
DOI	10.1097/INF.0000000000004233
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Article ; Online: Mild Chemical Treatment of Unsorted Urban Food Wastes.

Padoan, Elio / Montoneri, Enzo / Baglieri, Andrea / Francavilla, Matteo / Negre, Michèle

Molecules (Basel, Switzerland)

2023 Volume 28, Issue 22

Abstract: Municipal biowastes are conventionally treated by assessed anaerobic and aerobic fermentation to produce biogas, anaerobic digestate, and compost. Low-temperature hydrolysis and the oxidation of the digestate and compost, which are still at the ... ...

Abstract	Municipal biowastes are conventionally treated by assessed anaerobic and aerobic fermentation to produce biogas, anaerobic digestate, and compost. Low-temperature hydrolysis and the oxidation of the digestate and compost, which are still at the experimental stage, are known to yield water-soluble value-added chemical specialities for use in different sectors of the chemical industry and in agriculture. The present paper reports the application of the two chemical reactions to the biowastes before fermentation. The products obtained in this manner are compared with those obtained from the chemical reactions applied to the fermented biowastes. Based on the experimental results, the paper discusses the expected environmental and economic benefits of the above chemical processes and products in comparison with the products obtained by other known biotechnologies for the valorisation of biomass as a feedstock for the biobased chemical industry. The results point out that a sustainable biowaste-based refinery that produces biofuel and biobased chemicals may be developed by integrating chemical and fermentation technologies.
MeSH term(s)	Refuse Disposal/methods ; Food ; Agriculture/methods ; Fermentation ; Biotechnology ; Biofuels
Chemical Substances	Biofuels
Language	English
Publishing date	2023-11-20
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	1413402-0
ISSN	1420-3049 ; 1431-5165 ; 1420-3049
ISSN (online)	1420-3049
ISSN	1431-5165 ; 1420-3049
DOI	10.3390/molecules28227670
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Zs.MO 81: Show issues

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Article ; Online: Rising adoption of artificial intelligence in scientific publishing: evaluating the role, risks, and ethical implications in paper drafting and review process.

Carobene, Anna / Padoan, Andrea / Cabitza, Federico / Banfi, Giuseppe / Plebani, Mario

Clinical chemistry and laboratory medicine

2023 Volume 62, Issue 5, Page(s) 835–843

Abstract: Background: In the rapid evolving landscape of artificial intelligence (AI), scientific publishing is experiencing significant transformations. AI tools, while offering unparalleled efficiencies in paper drafting and peer review, also introduce notable ... ...

Abstract	Background: In the rapid evolving landscape of artificial intelligence (AI), scientific publishing is experiencing significant transformations. AI tools, while offering unparalleled efficiencies in paper drafting and peer review, also introduce notable ethical concerns. Content: This study delineates AI's dual role in scientific publishing: as a co-creator in the writing and review of scientific papers and as an ethical challenge. We first explore the potential of AI as an enhancer of efficiency, efficacy, and quality in creating scientific papers. A critical assessment follows, evaluating the risks vs. rewards for researchers, especially those early in their careers, emphasizing the need to maintain a balance between AI's capabilities and fostering independent reasoning and creativity. Subsequently, we delve into the ethical dilemmas of AI's involvement, particularly concerning originality, plagiarism, and preserving the genuine essence of scientific discourse. The evolving dynamics further highlight an overlooked aspect: the inadequate recognition of human reviewers in the academic community. With the increasing volume of scientific literature, tangible metrics and incentives for reviewers are proposed as essential to ensure a balanced academic environment. Summary: AI's incorporation in scientific publishing is promising yet comes with significant ethical and operational challenges. The role of human reviewers is accentuated, ensuring authenticity in an AI-influenced environment. Outlook: As the scientific community treads the path of AI integration, a balanced symbiosis between AI's efficiency and human discernment is pivotal. Emphasizing human expertise, while exploit artificial intelligence responsibly, will determine the trajectory of an ethically sound and efficient AI-augmented future in scientific publishing.
MeSH term(s)	Humans ; Artificial Intelligence ; Publishing ; Benchmarking ; Research Personnel
Language	English
Publishing date	2023-11-30
Publishing country	Germany
Document type	Journal Article
ZDB-ID	1418007-8
ISSN	1437-4331 ; 1434-6621 ; 1437-8523
ISSN (online)	1437-4331
ISSN	1434-6621 ; 1437-8523
DOI	10.1515/cclm-2023-1136
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