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  1. Book: Cell migrations: causes and functions

    La Porta, Caterina A. M. / Zapperi, Stefano

    (Advances in experimental medicine and biology ; 1146)

    2019  

    Author's details Caterina La Porta, Stefano Zapperi editors
    Series title Advances in experimental medicine and biology ; 1146
    Collection
    Language English
    Size vii, 135 Seiten, Illustrationen
    Publisher Springer
    Publishing place Cham
    Publishing country Switzerland
    Document type Book
    HBZ-ID HT020274188
    ISBN 978-3-030-17592-4 ; 9783030175931 ; 3-030-17592-8 ; 3030175936
    Database Catalogue ZB MED Medicine, Health

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    In stock of ZB MED Cologne/Königswinter

    Shelf markLoan statusLocation
    Zs A 3192 -1146- not available for loan Zeitschriften-Lesesaal

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  2. Article ; Online: The Response of Triple-Negative Breast Cancer to Neoadjuvant Chemotherapy and the Epithelial-Mesenchymal Transition.

    Zapperi, Stefano / La Porta, Caterina A M

    International journal of molecular sciences

    2023  Volume 24, Issue 7

    Abstract: It would be highly desirable to find prognostic and predictive markers for triple-negative breast cancer (TNBC), a strongly heterogeneous and invasive breast cancer subtype often characterized by a high recurrence rate and a poor outcome. Here, we ... ...

    Abstract It would be highly desirable to find prognostic and predictive markers for triple-negative breast cancer (TNBC), a strongly heterogeneous and invasive breast cancer subtype often characterized by a high recurrence rate and a poor outcome. Here, we investigated the prognostic and predictive capabilities of ARIADNE, a recently developed transcriptomic test focusing on the epithelial-mesenchymal transition. We first compared the stratification of TNBC patients obtained by ARIADNE with that based on other common pathological indicators, such as grade, stage and nodal status, and found that ARIADNE was more effective than the other methods in dividing patients into groups with different disease-free survival statistics. Next, we considered the response to neoadjuvant chemotherapy and found that the classification provided by ARIADNE led to statistically significant differences in the rates of pathological complete response within the groups.
    MeSH term(s) Humans ; Triple Negative Breast Neoplasms/drug therapy ; Triple Negative Breast Neoplasms/genetics ; Neoadjuvant Therapy/methods ; Epithelial-Mesenchymal Transition/genetics ; Disease-Free Survival ; Gene Expression Profiling ; Antineoplastic Combined Chemotherapy Protocols/therapeutic use
    Language English
    Publishing date 2023-03-29
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2019364-6
    ISSN 1422-0067 ; 1422-0067 ; 1661-6596
    ISSN (online) 1422-0067
    ISSN 1422-0067 ; 1661-6596
    DOI 10.3390/ijms24076422
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Harnessing deep learning to forecast local microclimate using global climate data.

    Zanchi, Marco / Zapperi, Stefano / La Porta, Caterina A M

    Scientific reports

    2023  Volume 13, Issue 1, Page(s) 21062

    Abstract: Microclimate is a complex non-linear phenomenon influenced by both global and local processes. Its understanding holds a pivotal role in the management of natural resources and the optimization of agricultural procedures. This phenomenon can be ... ...

    Abstract Microclimate is a complex non-linear phenomenon influenced by both global and local processes. Its understanding holds a pivotal role in the management of natural resources and the optimization of agricultural procedures. This phenomenon can be effectively monitored in local areas by employing models that integrate physical laws and data-driven algorithms relying on climate data and terrain conformation. Climate data can be acquired from nearby meteorological stations when available, but in their absence, global climate datasets describing 10 km-scale areas are often utilized. The present research introduces an innovative microclimate model that combines physical laws and deep learning to reproduce temperature and relative humidity variations at the meter-scale within a study area located in the Lombardian foothills. The model is exploited to perform a comparative study investigating whether employing the global climate dataset ERA5 as input reduces model's accuracy in reproducing the microclimate variations compared to using data collected by the Lombardy Regional Environment Protection Agency (ARPA) from a nearby meteorological station. The comparative analysis shows that using local meteorological data as inputs provides more accurate results for microclimate modeling. However, in situations where local data is not available, the use of global climate data remains a viable and reliable approach.
    Language English
    Publishing date 2023-11-29
    Publishing country England
    Document type Journal Article
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/s41598-023-48028-1
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Book ; Online: Extreme value theory and the St. Petersburg paradox in the failure statistics of wires

    Taloni, Alessandro / Zapperi, Stefano

    2021  

    Abstract: The fracture stress of materials typically depends on the sample size and is traditionally explained in terms of extreme value statistics. A recent work reported results on the carrying capacity of long polyamide and polyester wires and interpret the ... ...

    Abstract The fracture stress of materials typically depends on the sample size and is traditionally explained in terms of extreme value statistics. A recent work reported results on the carrying capacity of long polyamide and polyester wires and interpret the results in terms of a probabilistic argument known as the St. Petersburg paradox. Here, we show that the same results can be better explained in terms of extreme value statistics. We also discuss the relevance of rate dependent effects.
    Keywords Condensed Matter - Statistical Mechanics ; Condensed Matter - Materials Science ; Physics - Applied Physics
    Publishing date 2021-02-05
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: Immune Profile of SARS-CoV-2 Variants of Concern.

    La Porta, Caterina A M / Zapperi, Stefano

    Frontiers in digital health

    2021  Volume 3, Page(s) 704411

    Abstract: The spread of the current Sars-Cov-2 pandemics leads to the development of mutations that are constantly monitored because they could affect the efficacy of vaccines. Three recently identified mutated strains, known as variants of concern, are rapidly ... ...

    Abstract The spread of the current Sars-Cov-2 pandemics leads to the development of mutations that are constantly monitored because they could affect the efficacy of vaccines. Three recently identified mutated strains, known as variants of concern, are rapidly spreading worldwide. Here, we study possible effects of these mutations on the immune response to Sars-Cov-2 infection using NetTepi a computational method based on artificial neural networks that considers binding and stability of peptides obtained by proteasome degradation for widely represented HLA class I alleles present in human populations as well as the T-cell propensity of viral peptides that measures their immune response. Our results show variations in the number of potential highly ranked peptides ranging between 0 and 20% depending on the specific HLA allele. The results can be useful to design more specific vaccines.
    Language English
    Publishing date 2021-07-09
    Publishing country Switzerland
    Document type Journal Article
    ISSN 2673-253X
    ISSN (online) 2673-253X
    DOI 10.3389/fdgth.2021.704411
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: Classification of triple negative breast cancer by epithelial mesenchymal transition and the tumor immune microenvironment.

    Font-Clos, Francesc / Zapperi, Stefano / La Porta, Caterina A M

    Scientific reports

    2022  Volume 12, Issue 1, Page(s) 9651

    Abstract: Triple-negative breast cancer (TNBC) accounts for about 15-20% of all breast cancers and differs from other invasive breast cancer types because it grows and spreads rapidly, it has limited treatment options and typically worse prognosis. Since TNBC does ...

    Abstract Triple-negative breast cancer (TNBC) accounts for about 15-20% of all breast cancers and differs from other invasive breast cancer types because it grows and spreads rapidly, it has limited treatment options and typically worse prognosis. Since TNBC does not express estrogen or progesterone receptors and little or no human epidermal growth factor receptor (HER2) proteins are present, hormone therapy and drugs targeting HER2 are not helpful, leaving chemotherapy only as the main systemic treatment option. In this context, it would be important to find molecular signatures able to stratify patients into high and low risk groups. This would allow oncologists to suggest the best therapeutic strategy in a personalized way, avoiding unnecessary toxicity and reducing the high costs of treatment. Here we compare two independent patient stratification strategies for TNBC based on gene expression data: The first is focusing on the epithelial mesenchymal transition (EMT) and the second on the tumor immune microenvironment. Our results show that the two stratification strategies are not directly related, suggesting that the aggressiveness of the tumor can be due to a multitude of unrelated factors. In particular, the EMT stratification is able to identify a high-risk population with high immune markers that is, however, not properly classified by the tumor immune microenvironment based strategy.
    MeSH term(s) Epithelial-Mesenchymal Transition/genetics ; Humans ; Prognosis ; Receptors, Progesterone/genetics ; Receptors, Progesterone/metabolism ; Triple Negative Breast Neoplasms/pathology ; Tumor Microenvironment/genetics
    Chemical Substances Receptors, Progesterone
    Language English
    Publishing date 2022-06-10
    Publishing country England
    Document type Journal Article
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/s41598-022-13428-2
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Book ; Online: Predicting Creep Failure by Machine Learning -- Which Features Matter?

    Hiemer, Stefan / Moretti, Paolo / Zapperi, Stefano / Zaiser, Michael

    2022  

    Abstract: Spatial and temporal features are studied with respect to their predictive value for failure time prediction in subcritical failure with machine learning (ML). Data are generated from simulations of a novel, brittle random fuse model (RFM), as well as ... ...

    Abstract Spatial and temporal features are studied with respect to their predictive value for failure time prediction in subcritical failure with machine learning (ML). Data are generated from simulations of a novel, brittle random fuse model (RFM), as well as elasto-plastic finite element simulations (FEM) of a stochastic plasticity model with damage, both models considering stochastic thermally activated damage/failure processes in disordered materials. Fuse networks are generated with hierarchical and nonhierarchical architectures. Random forests - a specific ML algorithm - allow us to measure the feature importance through a feature's average error reduction. RFM simulation data are found to become more predictable with increasing system size and temperature. Increasing the load or the scatter in local materials properties has the opposite effect. Damage accumulation in these models proceeds in stochastic avalanches, and statistical signatures such as avalanche rate or magnitude have been discussed in the literature as predictors of incipient failure. However, in the present study such features proved of no measurable use to the ML models, which mostly rely on global or local strain for prediction. This suggests the strain as viable quantity to monitor in future experimental studies as it is accessible via digital image correlation.
    Keywords Condensed Matter - Materials Science
    Subject code 612
    Publishing date 2022-08-14
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  8. Book ; Online: Size effects in micro and nanoscale materials fracture

    Taloni, Alessandro / Vodret, Michele / Costantini, Giulio / Zapperi, Stefano

    2022  

    Abstract: Micro and nanoscale materials have remarkable mechanical properties, such as enhanced strength and toughness, but usually display sample-to-sample fluctuations and non-trivial size effects, a nuisance for engineering applications and an intriguing ... ...

    Abstract Micro and nanoscale materials have remarkable mechanical properties, such as enhanced strength and toughness, but usually display sample-to-sample fluctuations and non-trivial size effects, a nuisance for engineering applications and an intriguing problem for science. Our understanding of size-effects in small-scale materials has progressed considerably in the past few years thanks to a growing number of experimental measurements on carbon based nanomaterials, such as graphene carbon nanotubes, and on crystalline and amorphous micro/nanopillars and micro/nanowires. At the same time, increased computational power allowed atomistic simulations to reach experimentally relevant sample sizes. From the theoretical point of view, the standard analysis and interpretation of experimental and computational data relies on traditional extreme value theories developed decades ago for macroscopic samples, with recent work extending some of the limiting assumptions of the original theories. In this review, we discuss the recent experimental and numerical literature on micro and nanoscale fracture size effects, illustrate existing theories pointing out their advantages and limitations and finally provide a tutorial for analyzing fracture data from micro and nanoscale samples. We discuss a broad spectrum of materials but provide at the same time a unifying theoretical framework that should be helpful for materials scientists working on micro and nanoscale mechanics.
    Keywords Condensed Matter - Materials Science ; Condensed Matter - Statistical Mechanics
    Publishing date 2022-06-09
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  9. Article ; Online: Estimating the Binding of Sars-CoV-2 Peptides to HLA Class I in Human Subpopulations Using Artificial Neural Networks.

    La Porta, Caterina A M / Zapperi, Stefano

    Cell systems

    2020  Volume 11, Issue 4, Page(s) 412–417.e2

    Abstract: Epidemiological studies show that SARS-CoV-2 infection leads to severe symptoms only in a fraction of patients, but the determinants of individual susceptibility to the virus are still unknown. The major histocompatibility complex (MHC) class I exposes ... ...

    Abstract Epidemiological studies show that SARS-CoV-2 infection leads to severe symptoms only in a fraction of patients, but the determinants of individual susceptibility to the virus are still unknown. The major histocompatibility complex (MHC) class I exposes viral peptides in all nucleated cells and is involved in the susceptibility to many human diseases. Here, we use artificial neural networks to analyze the binding of SARS-CoV-2 peptides with polymorphic human MHC class I molecules. In this way, we identify two sets of haplotypes present in specific human populations: the first displays weak binding with SARS-CoV-2 peptides, while the second shows strong binding and T cell propensity. Our work offers a useful support to identify the individual susceptibility to COVID-19 and illustrates a mechanism underlying variations in the immune response to SARS-CoV-2. A record of this paper's transparent peer review process is included in the Supplemental Information.
    MeSH term(s) Betacoronavirus/immunology ; Haplotypes ; Histocompatibility Antigens Class I/chemistry ; Histocompatibility Antigens Class I/genetics ; Histocompatibility Antigens Class I/immunology ; Humans ; Neural Networks, Computer ; Peptides/chemistry ; Peptides/immunology ; Polymorphism, Genetic ; Protein Binding ; SARS-CoV-2 ; Viral Proteins/chemistry ; Viral Proteins/immunology
    Chemical Substances Histocompatibility Antigens Class I ; Peptides ; Viral Proteins
    Keywords covid19
    Language English
    Publishing date 2020-09-10
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2854138-8
    ISSN 2405-4720 ; 2405-4712
    ISSN (online) 2405-4720
    ISSN 2405-4712
    DOI 10.1016/j.cels.2020.08.011
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: Role of body temperature variations in bat immune response to viral infections.

    Fumagalli, Maria Rita / Zapperi, Stefano / La Porta, Caterina A M

    Journal of the Royal Society, Interface

    2021  Volume 18, Issue 180, Page(s) 20210211

    Abstract: The ability of bats to coexist with viruses without being harmed is an interesting issue that is still under investigation. Here we use a mathematical model to show that the pattern of body temperature variations observed in bats between day and night is ...

    Abstract The ability of bats to coexist with viruses without being harmed is an interesting issue that is still under investigation. Here we use a mathematical model to show that the pattern of body temperature variations observed in bats between day and night is responsible for their ability to keep viruses in check. From the dynamical systems point of view, our model displays an intriguing quasi-periodic behaviour that might be relevant in making the system robust by avoiding viral escape due to perturbations in the body temperature cycle.
    MeSH term(s) Animals ; Body Temperature ; Chiroptera ; Immunity ; Virus Diseases/veterinary ; Viruses
    Language English
    Publishing date 2021-07-28
    Publishing country England
    Document type Journal Article
    ZDB-ID 2156283-0
    ISSN 1742-5662 ; 1742-5689
    ISSN (online) 1742-5662
    ISSN 1742-5689
    DOI 10.1098/rsif.2021.0211
    Database MEDical Literature Analysis and Retrieval System OnLINE

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