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Article: A Note on the Global Income Distribution Curve ('The Elephant').

Palestrini, Antonio / Gatti, Domenico Delli / Gallegati, Mauro / Hosseiny, Ali

Nonlinear dynamics, psychology, and life sciences

2024 Volume 28, Issue 2, Page(s) 289–300

Abstract: In this work, our objective is to explain the decline in the income share of the middle class and the increase in the share of the wealthy - a global empirical phenomenon, commonly referred to as 'The Elephant' (Lakner & Milanovic, 2013; Milanovic, 2016) ...

Abstract	In this work, our objective is to explain the decline in the income share of the middle class and the increase in the share of the wealthy - a global empirical phenomenon, commonly referred to as 'The Elephant' (Lakner & Milanovic, 2013; Milanovic, 2016) - by examining the different life-cycle income paths of heterogeneous income classes and the varying tax burden on labor and capital income. The model investigates the diverse life-cycle paths and their nonlinear behavior among the income classes under scrutiny. This approach enables us to dynamically analyze the divergence in the income distribution using one of the more important models in economics: The life-cycle and permanent-income framework.
Language	English
Publishing date	2024-03-20
Publishing country	United States
Document type	Journal Article
ZDB-ID	2004049-0
ISSN	1573-6652 ; 1090-0578
ISSN (online)	1573-6652
ISSN	1090-0578
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Article ; Online: g-CXR-Net: A Graphic Application for the Rapid Recognition of SARS-CoV-2 from Chest X-Rays

Gatti, Domenico L

medRxiv

Abstract: g-CXR-Net is a graphic application for the rapid recognition of SARS-CoV-2 from Antero/Posterior chest X-rays. It employs the Artificial Intelligence engine of CXR-Net (arXiv:2103.00087) to generate masks of the lungs overlapping the heart and large vasa, ...

Abstract	g-CXR-Net is a graphic application for the rapid recognition of SARS-CoV-2 from Antero/Posterior chest X-rays. It employs the Artificial Intelligence engine of CXR-Net (arXiv:2103.00087) to generate masks of the lungs overlapping the heart and large vasa, probabilities for Covid vs. non-Covid assignment, and high resolution heat maps that identify the SARS associated lung regions.
Keywords	covid19
Language	English
Publishing date	2021-06-09
Publisher	Cold Spring Harbor Laboratory Press
Document type	Article ; Online
DOI	10.1101/2021.06.06.21258428
Database	COVID19

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Article: V for vaccines and variants.

Delli Gatti, Domenico / Reissl, Severin / Turco, Enrico

Journal of evolutionary economics

2023 , Page(s) 1–56

Abstract: In the context of the Covid-19 pandemic, we evaluate the effects of vaccines and virus variants on epidemiological and macroeconomic outcomes by means of Monte Carlo simulations of a macroeconomic-epidemiological agent-based model calibrated using data ... ...

Abstract	In the context of the Covid-19 pandemic, we evaluate the effects of vaccines and virus variants on epidemiological and macroeconomic outcomes by means of Monte Carlo simulations of a macroeconomic-epidemiological agent-based model calibrated using data from the Lombardy region of Italy. From simulations we infer that vaccination plays the role of a
Language	English
Publishing date	2023-06-01
Publishing country	Germany
Document type	Journal Article
ZDB-ID	1459309-9
ISSN	1432-1386 ; 0936-9937
ISSN (online)	1432-1386
ISSN	0936-9937
DOI	10.1007/s00191-023-00818-6
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Article ; Online: On the Origin of Hemoglobin Cooperativity under Non-equilibrium Conditions.

Scrima, Rosella / Fugetto, Sabino / Capitanio, Nazzareno / Gatti, Domenico L

Discoveries (Craiova, Romania)

2022 Volume 10, Issue 2, Page(s) e146

Abstract: Abnormal hemoglobins can have major consequences for tissue delivery of oxygen. Correct diagnosis of hemoglobinopathies with altered oxygen affinity requires a determination of hemoglobin oxygen dissociation curve, which relates the hemoglobin oxygen ... ...

Abstract	Abnormal hemoglobins can have major consequences for tissue delivery of oxygen. Correct diagnosis of hemoglobinopathies with altered oxygen affinity requires a determination of hemoglobin oxygen dissociation curve, which relates the hemoglobin oxygen saturation to the partial pressure of oxygen in the blood. Determination of the oxygen dissociation curve of human hemoglobin is typically carried out under conditions in which hemoglobin is in equilibrium with O2 at each partial pressure. However, in the human body due to the fast transit of red blood cells through tissues hemoglobin oxygen exchanges occur under non-equilibrium conditions. We describe the determination of non-equilibrium oxygen dissociation curve and show that under these conditions the true nature of hemoglobin cooperativity is revealed as emerging solely from the consecutive binding of oxygen to each one of the four subunits of hemoglobin until the entire tetramer is saturated. We call this form of cooperativity the sequential cooperativity of hemoglobin and define the simplest model that includes it as the minimalist model of hemoglobin. A single instantiation of this model accounts for ~70% of hemoglobin cooperativity under non-equilibrium conditions. The total cooperativity of hemoglobin can be viewed more correctly as the summation of two instantiations of the minimalist model (each one corresponding to a tetramer of low and high affinity for O2, respectively) in equilibrium with each other, as in the Monod-Wyman-Changeux model of hemoglobin. In addition to offering new insights on the nature of hemoglobin reaction with oxygen, the methodology described here for the determination of hemoglobin non-equilibrium oxygen dissociation curve provides a simple, fast, low-cost alternative to complex spectrophotometric methods, which is expected to be particularly valuable in regions where hemoglobinopathies are a significant public health problem, but where highly specialized laboratories capable of determining a traditional oxygen dissociation curve are not easily accessible.
Language	English
Publishing date	2022-06-30
Publishing country	Romania
Document type	Journal Article
ISSN	2359-7232
ISSN (online)	2359-7232
DOI	10.15190/d.2022.5
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Book ; Online: Reinforcement Learning for Combining Search Methods in the Calibration of Economic ABMs

Glielmo, Aldo / Favorito, Marco / Chanda, Debmallya / Gatti, Domenico Delli

2023

Abstract: Calibrating agent-based models (ABMs) in economics and finance typically involves a derivative-free search in a very large parameter space. In this work, we benchmark a number of search methods in the calibration of a well-known macroeconomic ABM on real ...

Abstract	Calibrating agent-based models (ABMs) in economics and finance typically involves a derivative-free search in a very large parameter space. In this work, we benchmark a number of search methods in the calibration of a well-known macroeconomic ABM on real data, and further assess the performance of "mixed strategies" made by combining different methods. We find that methods based on random-forest surrogates are particularly efficient, and that combining search methods generally increases performance since the biases of any single method are mitigated. Moving from these observations, we propose a reinforcement learning (RL) scheme to automatically select and combine search methods on-the-fly during a calibration run. The RL agent keeps exploiting a specific method only as long as this keeps performing well, but explores new strategies when the specific method reaches a performance plateau. The resulting RL search scheme outperforms any other method or method combination tested, and does not rely on any prior information or trial and error procedure. Comment: 9 pages and 5 figures, presented at the AAAI bridge program 'AI for Financial Institutions' (https://aaai23.bankit.art/), at the ICLR bridge program 'AI4ABM' (https://ai4abm.org/workshop_iclr2023/) and at ICAIF '23 (https://ai-finance.org/). Proceedings of the Fourth ACM International Conference on AI in Finance, (ICAIF 23), Association for Computing Machinery, New York, NY, USA
Keywords	Computer Science - Machine Learning ; Computer Science - Artificial Intelligence ; Computer Science - Multiagent Systems ; Economics - General Economics ; J.4 ; I.6.3
Subject code	006
Publishing date	2023-02-23
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Biapenem inactivation by B2 metallo β-lactamases: energy landscape of the post-hydrolysis reactions.

Gatti, Domenico L

PloS one

2012 Volume 7, Issue 1, Page(s) e30079

Abstract: Background: The first line of defense by bacteria against β-lactam antibiotics is the expression of β-lactamases, which cleave the amide bond of the β-lactam ring. In the reaction of biapenem inactivation by B2 metallo β-lactamases (MβLs), after the β- ... ...

Abstract	Background: The first line of defense by bacteria against β-lactam antibiotics is the expression of β-lactamases, which cleave the amide bond of the β-lactam ring. In the reaction of biapenem inactivation by B2 metallo β-lactamases (MβLs), after the β-lactam ring is opened, the carboxyl group generated by the hydrolytic process and the hydroxyethyl group (common to all carbapenems) rotate around the C5-C6 bond, assuming a new position that allows a proton transfer from the hydroxyethyl group to C2, and a nucleophilic attack on C3 by the oxygen atom of the same side-chain. This process leads to the formation of a bicyclic compound, as originally observed in the X-ray structure of the metallo β-lactamase CphA in complex with product. Methodology/principal findings: QM/MM and metadynamics simulations of the post-hydrolysis steps in solution and in the enzyme reveal that while the rotation of the hydroxyethyl group can occur in solution or in the enzyme active site, formation of the bicyclic compound occurs primarily in solution, after which the final product binds back to the enzyme. The calculations also suggest that the rotation and cyclization steps can occur at a rate comparable to that observed experimentally for the enzymatic inactivation of biapenem only if the hydrolysis reaction leaves the N4 nitrogen of the β-lactam ring unprotonated. Conclusions/significance: The calculations support the existence of a common mechanism (in which ionized N4 is the leaving group) for carbapenems hydrolysis in all MβLs, and suggest a possible revision of mechanisms for B2 MβLs in which the cleavage of the β-lactam ring is associated with or immediately followed by protonation of N4. The study also indicates that the bicyclic derivative of biapenem has significant affinity for B2 MβLs, and that it may be possible to obtain clinically effective inhibitors of these enzymes by modification of this lead compound.
MeSH term(s)	Aeromonas hydrophila/enzymology ; Algorithms ; Anti-Infective Agents/chemistry ; Anti-Infective Agents/metabolism ; Bacterial Proteins/chemistry ; Bacterial Proteins/metabolism ; Bridged Bicyclo Compounds, Heterocyclic/chemistry ; Bridged Bicyclo Compounds, Heterocyclic/metabolism ; Catalytic Domain ; Crystallography, X-Ray ; Hydrolysis ; Kinetics ; Models, Chemical ; Models, Molecular ; Molecular Dynamics Simulation ; Protein Binding ; Protein Conformation ; Substrate Specificity ; Thermodynamics ; Thienamycins/chemistry ; Thienamycins/metabolism ; beta-Lactamases/chemistry ; beta-Lactamases/metabolism
Chemical Substances	Anti-Infective Agents ; Bacterial Proteins ; Bridged Bicyclo Compounds, Heterocyclic ; Thienamycins ; beta-Lactamases (EC 3.5.2.6) ; biapenem (YR5U3L9ZH1)
Language	English
Publishing date	2012-01-12
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ISSN	1932-6203
ISSN (online)	1932-6203
DOI	10.1371/journal.pone.0030079
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Article ; Online: Genomic surveillance of carbapenem-resistant Klebsiella pneumoniae reveals a prolonged outbreak of extensively drug-resistant ST147 NDM-1 during the COVID-19 pandemic in the Apulia region (Southern Italy).

Loconsole, Daniela / Sallustio, Anna / Sacco, Davide / Santantonio, Marilina / Casulli, Daniele / Gatti, Domenico / Accogli, Marisa / Parisi, Antonio / Zagaria, Riccardo / Colella, Vito / Centrone, Francesca / Chironna, Maria

Journal of global antimicrobial resistance

2024 Volume 36, Page(s) 260–266

Abstract: Objectives: The recent worldwide spread of New Delhi metallo-beta-lactamase-producing Klebsiella pneumoniae (NDM-KP) in health-care settings remains a concern. The aim of the study was to describe an outbreak of extensively drug-resistant ST147 NDM-1-KP ...

Abstract	Objectives: The recent worldwide spread of New Delhi metallo-beta-lactamase-producing Klebsiella pneumoniae (NDM-KP) in health-care settings remains a concern. The aim of the study was to describe an outbreak of extensively drug-resistant ST147 NDM-1-KP in the Apulia region of Southern Italy that occurred between 2020 and 2022 through genomic surveillance of carbapenem-resistant Enterobacterales. Methods: A total of 459 carbapenem-resistant KP isolates collected from patients hospitalised with bloodstream infections were tested using a commercial multiplex real-time polymerase chain reaction to identify carbapenemase genes. A subset of 27 isolates was subjected to whole-genome sequencing. Core-genome multilocus sequence typing was performed by analysing a panel of 4884 genes. Results: Molecular testing revealed that 104 (22.6%) isolates carried the carbapenemase NDM gene. Phylogenetic analysis of the 27 isolates subjected to whole-genome sequencing revealed high genetic relatedness among strains. All isolates were resistant to all first-line antibiotics. Virulome analysis identified the ybt locus, the two well-recognised virulence factors iucABCDiutA and rmpA, and the genes encoding the type 3 pilus virulence factor. Plasmids IncFIB(pkPHS1), IncFIB(pNDM-Mar), IncFIB(pQil), IncHI1B(pNDM-MAR), IncR, and Col(pHAD28) were identified in all isolates. Moreover, further analysis identified the IncFIB-type plasmid carrying the NDM-1 genes. Conclusion: The increasing circulation of extensively drug-resistant NDM-1 ST147 KP strains in Southern Italy in recent years is worrisome, because these clones pose a real risk, particularly in hospital settings. Genomic surveillance is a crucial tool for early identification of emerging threats such as the spread of high-risk pathogens. Rapid infection control measures and antimicrobial stewardship are key to preventing further spread of hypervirulent KP strains.
MeSH term(s)	Humans ; Klebsiella pneumoniae ; Phylogeny ; Pandemics ; Klebsiella Infections/epidemiology ; Drug Resistance, Multiple, Bacterial/genetics ; COVID-19/epidemiology ; Carbapenems/pharmacology ; Carbapenem-Resistant Enterobacteriaceae/genetics ; Genomics ; Disease Outbreaks ; Italy/epidemiology ; Virulence Factors
Chemical Substances	Carbapenems ; Virulence Factors
Language	English
Publishing date	2024-01-26
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	2710046-7
ISSN	2213-7173 ; 2213-7173
ISSN (online)	2213-7173
ISSN	2213-7173
DOI	10.1016/j.jgar.2024.01.015
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Article: Borrowing constraints and monetary policy

Assenza, Tiziana / Delli Gatti, Domenico

Dynamic modeling, empirical macroeconomics, and finance : essays in honor of Willi Semmler , p. 89-120

the inflation tax-net worth channel

2016 , Page(s) 89–120

Author's details	Tiziana Assenza and Domenico Delli Gatti
Keywords	Money-in-the-utility function model ; Geldpolitik ; Inflationsrate ; Geldpolitische Transmission ; Liquiditätsbeschränkung ; Monetäre Wachstumstheorie
Language	English
Publisher	Springer
Publishing place	Switzerland
Document type	Article
ISBN	978-3-319-39885-3 ; 3-319-39885-7
Database	ECONomics Information System

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Article ; Online: A Hybrid Pipeline for Covid-19 Screening Incorporating Lungs Segmentation and Wavelet Based Preprocessing of Chest X-Rays

Abdulah, Haikal / Huber, Benjamin / Abdallah, Hassan / Palese, Luigi L / Soltanian-Zadeh, Hamid / Gatti, Domenico L

medRxiv

Abstract: We have developed a two-module pipeline for the detection of SARS-CoV-2 from chest X-rays (CXRs). Module 1 is a traditional convnet that generates masks of the lungs overlapping the heart and large vasa. Module 2 is a hybrid convnet that preprocesses ... ...

Abstract	We have developed a two-module pipeline for the detection of SARS-CoV-2 from chest X-rays (CXRs). Module 1 is a traditional convnet that generates masks of the lungs overlapping the heart and large vasa. Module 2 is a hybrid convnet that preprocesses CXRs and corresponding lung masks by means of the Wavelet Scattering Transform, and passes the resulting feature maps through an Attention block and a cascade of Separable Atrous Multiscale Convolutional Residual blocks to produce a class assignment as Covid or non-Covid. Module 1 was trained on a public dataset of 6395 CXRs with radiologist annotated lung contours. Module 2 was trained on a dataset of 2362 non-Covid and 1435 Covid CXRs acquired at the Henry Ford Health System Hospital in Detroit. Six distinct cross-validation models, were combined into an ensemble model that was used to classify the CXR images of the test set. An intuitive graphic interphase allows for rapid Covid vs. non-Covid classification of CXRs, and generates high resolution heat maps that identify the affected lung regions.
Keywords	covid19
Language	English
Publishing date	2022-03-13
Publisher	Cold Spring Harbor Laboratory Press
Document type	Article ; Online
DOI	10.1101/2022.03.13.22272311
Database	COVID19

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Book ; Online: Molecular dynamics without molecules

Schwing, Gregory / Palese, Luigi L. / Fernández, Ariel / Schwiebert, Loren / Gatti, Domenico L.

searching the conformational space of proteins with generative neural networks

2022

Abstract: All-atom and coarse-grained molecular dynamics are two widely used computational tools to study the conformational states of proteins. Yet, these two simulation methods suffer from the fact that without access to supercomputing resources, the time and ... ...

Abstract	All-atom and coarse-grained molecular dynamics are two widely used computational tools to study the conformational states of proteins. Yet, these two simulation methods suffer from the fact that without access to supercomputing resources, the time and length scales at which these states become detectable are difficult to achieve. One alternative to such methods is based on encoding the atomistic trajectory of molecular dynamics as a shorthand version devoid of physical particles, and then learning to propagate the encoded trajectory through the use of artificial intelligence. Here we show that a simple textual representation of the frames of molecular dynamics trajectories as vectors of Ramachandran basin classes retains most of the structural information of the full atomistic representation of a protein in each frame, and can be used to generate equivalent atom-less trajectories suitable to train different types of generative neural networks. In turn, the trained generative models can be used to extend indefinitely the atom-less dynamics or to sample the conformational space of proteins from their representation in the models latent space. We define intuitively this methodology as molecular dynamics without molecules, and show that it enables to cover physically relevant states of proteins that are difficult to access with traditional molecular dynamics. Comment: 12 pages, 9 figures, 3 tables
Keywords	Quantitative Biology - Quantitative Methods ; Computer Science - Artificial Intelligence ; Quantitative Biology - Biomolecules
Subject code	541
Publishing date	2022-06-08
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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