scispace - formally typeset
Search or ask a question
Institution

Istituto Italiano di Tecnologia

FacilityGenoa, Italy
About: Istituto Italiano di Tecnologia is a facility organization based out in Genoa, Italy. It is known for research contribution in the topics: Humanoid robot & Robot. The organization has 4561 authors who have published 14595 publications receiving 437558 citations. The organization is also known as: Italian Institute of Technology & IIT.
Topics: Humanoid robot, Robot, Graphene, iCub, Population


Papers
More filters
Journal ArticleDOI
TL;DR: The alignment of temporal integration windows to input changes found here may serve to actively organize the temporal processing of continuous sensory input.

107 citations

Journal ArticleDOI
TL;DR: It is demonstrated that FUS and these microRNAs are linked by a feed-forward regulatory loop where FUS upregulates miR-141/200a, which in turn impact FUS protein synthesis, and reveals a possible correlation between deregulation of this regulatory circuit and ALS pathogenesis.
Abstract: While the physiologic functions of the RNA-binding protein FUS still await thorough characterization, the pathonegetic role of FUS mutations in amyotrophic lateral sclerosis (ALS) is clearly established. Here we find that a human FUS mutation that leads to increased protein expression, and was identified in two ALS patients with severe outcome, maps to the seed sequence recognized by miR-141 and miR-200a in the 3'-UTR of FUS. We demonstrate that FUS and these microRNAs are linked by a feed-forward regulatory loop where FUS upregulates miR-141/200a, which in turn impact FUS protein synthesis. We also show that Zeb1, a target of miR-141/200a and transcriptional repressor of these two microRNAs, is part of the circuitry and reinforces it. Our results reveal a possible correlation between deregulation of this regulatory circuit and ALS pathogenesis, and open interesting perspectives in the treatment of these mutations through ad hoc-modified microRNAs.

106 citations

Journal ArticleDOI
TL;DR: The kinetic analysis of a peptide fluctuating between various microstates inside the nanopore enabled a detailed picture of the free energy description of its interaction with the α-HL nanopore, and when studied at the limit of vanishingly low transmembrane potentials, this provided a thermodynamic description of peptide reversible binding to and within the β-barrel domain.
Abstract: We report on the ability to control the dynamics of a single peptide capture and passage across a voltage-biased, α-hemolysin nanopore (α-HL), under conditions that the electroosmotic force exerted on the analyte dominates the electrophoretic transport. We demonstrate that by extending outside the nanopore, the electroosmotic force is able to capture a peptide at either the lumen or vestibule entry of the nanopore, and transiently traps it inside the nanopore, against the electrophoretic force. Statistical analysis of the resolvable dwell-times of a metastable trapped peptide, as it occupies either the β-barrel or vestibule domain of the α-HL nanopore, reveals rich kinetic details regarding the direction and rates of stochastic movement of a peptide inside the nanopore. The presented approach demonstrates the ability to shuttle and study molecules along the passage pathway inside the nanopore, allows to identify the mesoscopic trajectory of a peptide exiting the nanopore through either the vestibule or β-barrel moiety, thus providing convincing proof of a molecule translocating the pore. The kinetic analysis of a peptide fluctuating between various microstates inside the nanopore, enabled a detailed picture of the free energy description of its interaction with the α-HL nanopore. When studied at the limit of vanishingly low transmembrane potentials, this provided a thermodynamic description of peptide reversible binding to and within the α-HL nanopore, under equilibrium conditions devoid of electric and electroosmotic contributions.

106 citations

Journal ArticleDOI
23 Feb 2011-ACS Nano
TL;DR: It is demonstrated that a pure physical stimulus, that is, a nanoscale variation of surface topography, may play per se a significant role in determining the morphological, genetic, and proteomic profile of bacteria.
Abstract: Bacterial adhesion onto inorganic/nanoengineered surfaces is a key issue in biotechnology and medicine, because it is one of the first necessary steps to determine a general pathogenic event. Understanding the molecular mechanisms of bacteria−surface interaction represents a milestone for planning a new generation of devices with unanimously certified antibacterial characteristics. Here, we show how highly controlled nanostructured substrates impact the bacterial behavior in terms of morphological, genomic, and proteomic response. We observed by atomic force microscopy (AFM) and scanning electron microscopy (SEM) that type-1 fimbriae typically disappear in Escherichia coli adherent onto nanostructured substrates, as opposed to bacteria onto reference glass or flat gold surfaces. A genetic variation of the fimbrial operon regulation was consistently identified by real time qPCR in bacteria interacting with the nanorough substrates. To gain a deeper insight into the molecular basis of the interaction mechan...

106 citations

Journal ArticleDOI
TL;DR: In this paper, a silicon MEMS-based capacitive sensing array is presented, which has the ability to resolve forces in the sub mN range, provides directional response to applied loading and has the capability to differentiate between surface textures.

106 citations


Authors

Showing all 4601 results

NameH-indexPapersCitations
Marc G. Caron17367499802
Paolo Vineis134108886608
Michele Parrinello13363794674
Alex J. Barker132127384746
Tomaso Poggio13260888676
Shuai Liu129109580823
Giacomo Rizzolatti11729897242
Yehezkel Ben-Ari11045944293
Daniele Piomelli10450549009
Bruno Scrosati10358066572
Wolfgang J. Parak10246943307
Liberato Manna9849444780
Muhammad Imran94305351728
Ole Isacson9334530460
Luigi Ambrosio9376139688
Network Information
Related Institutions (5)
École Polytechnique Fédérale de Lausanne
98.2K papers, 4.3M citations

93% related

ETH Zurich
122.4K papers, 5.1M citations

92% related

Massachusetts Institute of Technology
268K papers, 18.2M citations

90% related

Carnegie Mellon University
104.3K papers, 5.9M citations

90% related

Georgia Institute of Technology
119K papers, 4.6M citations

90% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202313
2022109
20211,576
20201,618
20191,439
20181,381