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Institution

University of Modena and Reggio Emilia

EducationModena, Italy
About: University of Modena and Reggio Emilia is a education organization based out in Modena, Italy. It is known for research contribution in the topics: Population & Transplantation. The organization has 8179 authors who have published 22418 publications receiving 671337 citations. The organization is also known as: Università degli Studi di Modena e Reggio Emilia & Universita degli Studi di Modena e Reggio Emilia.


Papers
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Journal ArticleDOI
TL;DR: A systematic evaluation of the value of AI-based decision support in skin tumor diagnosis demonstrates the superiority of human–computer collaboration over each individual approach and supports the potential of automated approaches in diagnostic medicine.
Abstract: The rapid increase in telemedicine coupled with recent advances in diagnostic artificial intelligence (AI) create the imperative to consider the opportunities and risks of inserting AI-based support into new paradigms of care Here we build on recent achievements in the accuracy of image-based AI for skin cancer diagnosis to address the effects of varied representations of AI-based support across different levels of clinical expertise and multiple clinical workflows We find that good quality AI-based support of clinical decision-making improves diagnostic accuracy over that of either AI or physicians alone, and that the least experienced clinicians gain the most from AI-based support We further find that AI-based multiclass probabilities outperformed content-based image retrieval (CBIR) representations of AI in the mobile technology environment, and AI-based support had utility in simulations of second opinions and of telemedicine triage In addition to demonstrating the potential benefits associated with good quality AI in the hands of non-expert clinicians, we find that faulty AI can mislead the entire spectrum of clinicians, including experts Lastly, we show that insights derived from AI class-activation maps can inform improvements in human diagnosis Together, our approach and findings offer a framework for future studies across the spectrum of image-based diagnostics to improve human-computer collaboration in clinical practice

353 citations

Journal ArticleDOI
TL;DR: Patients with a related disease, limb-girdle muscular dystrophy 2D (LGMD2D), have reduced numbers of this pericyte subset and thus produce too few mesoangioblasts for use in autologous cell therapy.
Abstract: Mesoangioblasts are stem/progenitor cells derived from a subset of pericytes found in muscle that express alkaline phosphatase. They have been shown to ameliorate the disease phenotypes of different animal models of muscular dystrophy and are now undergoing clinical testing in children affected by Duchenne's muscular dystrophy. Here, we show that patients with a related disease, limb-girdle muscular dystrophy 2D (LGMD2D), which is caused by mutations in the gene encoding α-sarcoglycan, have reduced numbers of this pericyte subset and thus produce too few mesoangioblasts for use in autologous cell therapy. Hence, we reprogrammed fibroblasts and myoblasts from LGMD2D patients to generate human induced pluripotent stem cells (iPSCs) and developed a protocol for the derivation of mesoangioblast-like cells from these iPSCs. The iPSC-derived mesoangioblasts were expanded and genetically corrected in vitro with a lentiviral vector carrying the gene encoding human α-sarcoglycan and a promoter that would ensure expression only in striated muscle. When these genetically corrected human iPSC-derived mesoangioblasts were transplanted into α-sarcoglycan-null immunodeficient mice, they generated muscle fibers that expressed α-sarcoglycan. Finally, transplantation of mouse iPSC-derived mesoangioblasts into α-sarcoglycan-null immunodeficient mice resulted in functional amelioration of the dystrophic phenotype and restoration of the depleted progenitors. These findings suggest that transplantation of genetically corrected mesoangioblast-like cells generated from iPSCs from LGMD2D patients may be useful for treating this type of muscular dystrophy and perhaps other forms of muscular dystrophy as well.

350 citations

Journal ArticleDOI
TL;DR: A review of recent studies on the use of microbial antagonists to control diseases incited by soilborne and airborne plant pathogenic bacteria and fungi highlights Streptomyces spp..-mediated functional traits, such as enhancement of plant growth and biocontrol of phytopathogens.
Abstract: There has been many recent studies on the use of microbial antagonists to control diseases incited by soilborne and airborne plant pathogenic bacteria and fungi, in an attempt to replace existing methods of chemical control and avoid extensive use of fungicides, which often lead to resistance in plant pathogens. In agriculture, plant growth-promoting and biocontrol microorganisms have emerged as safe alternatives to chemical pesticides. Streptomyces spp. and their metabolites may have great potential as excellent agents for controlling various fungal and bacterial phytopathogens. Streptomycetes belong to the rhizosoil microbial communities and are efficient colonizers of plant tissues, from roots to the aerial parts. They are active producers of antibiotics and volatile organic compounds, both in soil and in planta, and this feature is helpful for identifying active antagonists of plant pathogens and can be used in several cropping systems as biocontrol agents. Additionally, their ability to promote plant growth has been demonstrated in a number of crops, thus inspiring the wide application of streptomycetes as biofertilizers to increase plant productivity. The present review highlights Streptomyces spp.-mediated functional traits, such as enhancement of plant growth and biocontrol of phytopathogens.

349 citations

Journal ArticleDOI
TL;DR: The results support the conclusion that α6 rather than α3 is the partner of β2 in the nicotinic modulation of DA neurons, and show that α 6−/− mice might be useful tools to understand the mechanisms of nicotine addiction, although some developmental compensation might occur in these mice.
Abstract: The alpha6 subunit of the nicotinic acetylcholine receptor (nAChR) is expressed at very high levels in dopaminergic (DA) neurons. However, because of the lack of pharmacological tools selective for alpha6-containing nAChRs, the role of this subunit in the etiology of nicotine addiction remains unknown. To provide new tools to investigate this issue, we generated an alpha6 nAChR knock-out mouse. Homozygous null mutants (alpha6-/-) did not exhibit any gross neurological or behavioral deficits. A careful anatomic and molecular examination of alpha6-/- mouse brains demonstrated the absence of developmental alterations in these animals, especially in the visual and dopaminergic pathways, where the alpha6 subunit is normally expressed at the highest levels. On the other hand, receptor autoradiography revealed a decrease in [3H]nicotine, [3H]epibatidine, and [3H]cytisine high-affinity binding in the terminal fields of retinal ganglion cells of alpha6-/- animals, whereas high-affinity [125I]alpha-conotoxinMII (alphaCtxMII) binding completely disappeared in the brain. Moreover, inhibition of [3H]epibatidine binding on striatal membranes, using unlabeled alphaCtxMII or cytisine, revealed the absence of alphaCtxMII-sensitive and cytisine-resistant [3H]epibatidine binding sites in alpha6-/- mice, although the total amount of binding was unchanged. Because alphaCtxMII, a toxin formerly thought to be specific for alpha3beta2-containing nAChRs, is known to partially inhibit nicotine-induced dopamine release, these results support the conclusion that alpha6 rather than alpha3 is the partner of beta2 in the nicotinic modulation of DA neurons. They further show that alpha6-/- mice might be useful tools to understand the mechanisms of nicotine addiction, although some developmental compensation might occur in these mice.

349 citations


Authors

Showing all 8322 results

NameH-indexPapersCitations
Carlo M. Croce1981135189007
Gregory Y.H. Lip1693159171742
Geoffrey Burnstock141148899525
Peter M. Rothwell13477967382
Claudio Franceschi12085659868
Lorenzo Galluzzi11847771436
Leonardo M. Fabbri10956660838
David N. Reinhoudt107108248814
Stefano Pileri10063543369
Andrea Bizzeti99116846880
Brian K. Shoichet9828140313
Dante Gatteschi9772748729
Roberta Sessoli9542441458
Thomas A. Buchholz9349433409
Pier Luigi Zinzani9285735476
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202376
2022230
20212,354
20202,083
20191,633
20181,450