67 research outputs found
In vivo study of the bioavailability and metabolic profile of (poly)phenols after sous-vide artichoke consumption
Artichokes are a rich source of (poly)phenols, mainly caffeoylquinic acids, but little is known about their bioavailability from this source. This study investigated the absorption, metabolism and excretion of (poly)phenols after sous-vide artichoke consumption (5776 µmol of (poly)phenols) by healthy volunteers. Seventy-six (poly)phenol metabolites were identified by UHPLC-MS/MS using authentic standards, including acyl-quinic acids plus C6–C3, C6–C1, C6–C2, C6–C1–N, C6–C0 metabolites, and their phase-II conjugates. The major metabolites were 3ʹ-methoxy-4ʹ-hydroxycinnamic acid, 3ʹ-methoxycinnamic acid-4ʹ-sulfate, and 4ʹ-hydroxycinnamic acid-3ʹ-sulfate, which appeared early in plasma (Tmax 6 h). The 24 h urinary recovery averaged 8.9% (molar basis) of the (poly)phenols consumed. Hepatic beta-oxidation of 3ʹ,4ʹ-dihydroxycinnamic acid and methylated conjugates occurred, but was limited (<0.04%). 3ʹ-Methylation exceeded 4ʹ-methylation and interindividual variability was high, especially for gut microbial metabolites (up to 168-fold)
Energy loss in a strongly coupled anisotropic plasma
We study the energy loss of a rotating infinitely massive quark moving, at
constant velocity, through an anisotropic strongly-coupled N=4 plasma from
holography. It is shown that, similar to the isotropic plasma, the energy loss
of the rotating quark is due to either the drag force or radiation with a
continuous crossover from drag-dominated regime to the radiation dominated
regime. We find that the anisotropy has a significant effect on the energy loss
of the heavy quark, specially in the crossover regime. We argue that the energy
loss due to radiation in anisotropic media is less than the isotropic case.
Interestingly this is similar to analogous calculations for the energy loss in
weakly coupled anisotropic plasma.Comment: 26+1 pages, 10 figures, typos fixe
Class-modeling analysis reveals T-cell homeostasis disturbances involved in loss of immune control in elite controllers
Despite long-lasting HIV replication control, a significant proportion of elite controller (EC) patients may experience CD4 T-cell loss. Discovering perturbations in immunological parameters could help our understanding of the mechanisms that may be operating in those patients experiencing loss of immunological control.
Methods A case–control study was performed to evaluate if alterations in different T-cell homeostatic parameters can predict CD4 T-cell loss in ECs by comparing data from EC patients showing significant CD4 decline (cases) and EC patients showing stable CD4 counts (controls). The partial least-squares–class modeling (PLS-CM) statistical methodology was employed to discriminate between the two groups of patients, and as a predictive model.
Results
Herein, we show that among T-cell homeostatic alterations, lower levels of naïve and recent thymic emigrant subsets of CD8 cells and higher levels of effector and senescent subsets of CD8 cells as well as higher levels of exhaustion of CD4 cells, measured prior to CD4 T-cell loss, predict the loss of immunological control.
Conclusions
These data indicate that the parameters of T-cell homeostasis may identify those EC patients with a higher proclivity to CD4 T-cell loss. Our results may open new avenues for understanding the mechanisms underlying immunological progression despite HIV replication control, and eventually, for finding a functional cure through immune-based clinical trials.projects RD12/0017/0031, RD16/0025/
0013, and SAF2015-66193-R as part of the Health Research and Development
Strategy, State Plan for Scientific and Technical Research and Innovation (2008–
2011 and 2013–2016) and cofinanced by the Institute of Health Carlos III (ISCIII),
Sub-Directorate General for Research Assessment and Promotion and European
Regional Development Fund. NR is a Miguel Servet investigator from the ISCIII
(CP14/00198), Madrid, Spain. C Restrepo was funded by project RD12/0017/
0031 and is currently funded by project RD16/0025/0013. M García is a
predoctoral student co-funded by grant CP14/00198 and an Intramural
Research Scholarship from Instituto de Investigación Sanitaria-Fundación Jiménez
Díaz (IIS-FJD)
Computational Approaches to Explainable Artificial Intelligence:Advances in Theory, Applications and Trends
Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear artificial neural systems, excel at extracting high-level features from data. DL has demonstrated human-level performance in real-world tasks, including clinical diagnostics, and has unlocked solutions to previously intractable problems in virtual agent design, robotics, genomics, neuroimaging, computer vision, and industrial automation. In this paper, the most relevant advances from the last few years in Artificial Intelligence (AI) and several applications to neuroscience, neuroimaging, computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-of-the-art in AI methods, models and applications within a collection of works presented at the 9 International Conference on the Interplay between Natural and Artificial Computation (IWINAC). The works presented in this paper are excellent examples of new scientific discoveries made in laboratories that have successfully transitioned to real-life applications
Computational approaches to explainable artificial intelligence: Advances in theory, applications and trends
Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear artificial neural systems, excel at extracting high-level features from data. DL has demonstrated human-level performance in real-world tasks, including clinical diagnostics, and has unlocked solutions to previously intractable problems in virtual agent design, robotics, genomics, neuroimaging, computer vision, and industrial automation. In this paper, the most relevant advances from the last few years in Artificial Intelligence (AI) and several applications to neuroscience, neuroimaging, computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-of-the-art in AI methods, models and applications within a collection of works presented at the 9th International Conference on the Interplay between Natural and Artificial Computation (IWINAC). The works presented in this paper are excellent examples of new scientific discoveries made in laboratories that have successfully transitioned to real-life applications.MCIU - Nvidia(UMA18-FEDERJA-084
Computational approaches to Explainable Artificial Intelligence:Advances in theory, applications and trends
Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear artificial neural systems, excel at extracting high-level features from data. DL has demonstrated human-level performance in real-world tasks, including clinical diagnostics, and has unlocked solutions to previously intractable problems in virtual agent design, robotics, genomics, neuroimaging, computer vision, and industrial automation. In this paper, the most relevant advances from the last few years in Artificial Intelligence (AI) and several applications to neuroscience, neuroimaging, computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-of-the-art in AI methods, models and applications within a collection of works presented at the 9th International Conference on the Interplay between Natural and Artificial Computation (IWINAC). The works presented in this paper are excellent examples of new scientific discoveries made in laboratories that have successfully transitioned to real-life applications.</p
Test beam performance of a CBC3-based mini-module for the Phase-2 CMS Outer Tracker before and after neutron irradiation
The Large Hadron Collider (LHC) at CERN will undergo major upgrades to increase the instantaneous luminosity up to 5–7.5×10 cms. This High Luminosity upgrade of the LHC (HL-LHC) will deliver a total of 3000–4000 fb-1 of proton-proton collisions at a center-of-mass energy of 13–14 TeV. To cope with these challenging environmental conditions, the strip tracker of the CMS experiment will be upgraded using modules with two closely-spaced silicon sensors to provide information to include tracking in the Level-1 trigger selection. This paper describes the performance, in a test beam experiment, of the first prototype module based on the final version of the CMS Binary Chip front-end ASIC before and after the module was irradiated with neutrons. Results demonstrate that the prototype module satisfies the requirements, providing efficient tracking information, after being irradiated with a total fluence comparable to the one expected through the lifetime of the experiment
Beam test performance of a prototype module with Short Strip ASICs for the CMS HL-LHC tracker upgrade
The Short Strip ASIC (SSA) is one of the four front-end chips designed for the upgrade of the CMS Outer Tracker for the High Luminosity LHC. Together with the Macro-Pixel ASIC (MPA) it will instrument modules containing a strip and a macro-pixel sensor stacked on top of each other. The SSA provides both full readout of the strip hit information when triggered, and, together with the MPA, correlated clusters called stubs from the two sensors for use by the CMS Level-1 (L1) trigger system. Results from the first prototype module consisting of a sensor and two SSA chips are presented. The prototype module has been characterized at the Fermilab Test Beam Facility using a 120 GeV proton beam
Selection of the silicon sensor thickness for the Phase-2 upgrade of the CMS Outer Tracker
During the operation of the CMS experiment at the High-Luminosity LHC the silicon sensors of the Phase-2 Outer Tracker will be exposed to radiation levels that could potentially deteriorate their performance. Previous studies had determined that planar float zone silicon with n-doped strips on a p-doped substrate was preferred over p-doped strips on an n-doped substrate. The last step in evaluating the optimal design for the mass production of about 200 m of silicon sensors was to compare sensors of baseline thickness (about 300 μm) to thinned sensors (about 240 μm), which promised several benefits at high radiation levels because of the higher electric fields at the same bias voltage. This study provides a direct comparison of these two thicknesses in terms of sensor characteristics as well as charge collection and hit efficiency for fluences up to 1.5 × 10 n/cm. The measurement results demonstrate that sensors with about 300 μm thickness will ensure excellent tracking performance even at the highest considered fluence levels expected for the Phase-2 Outer Tracker
Comparative evaluation of analogue front-end designs for the CMS Inner Tracker at the High Luminosity LHC
The CMS Inner Tracker, made of silicon pixel modules, will be entirely replaced prior to the start of the High Luminosity LHC period. One of the crucial components of the new Inner Tracker system is the readout chip, being developed by the RD53 Collaboration, and in particular its analogue front-end, which receives the signal from the sensor and digitizes it. Three different analogue front-ends (Synchronous, Linear, and Differential) were designed and implemented in the RD53A demonstrator chip. A dedicated evaluation program was carried out to select the most suitable design to build a radiation tolerant pixel detector able to sustain high particle rates with high efficiency and a small fraction of spurious pixel hits. The test results showed that all three analogue front-ends presented strong points, but also limitations. The Differential front-end demonstrated very low noise, but the threshold tuning became problematic after irradiation. Moreover, a saturation in the preamplifier feedback loop affected the return of the signal to baseline and thus increased the dead time. The Synchronous front-end showed very good timing performance, but also higher noise. For the Linear front-end all of the parameters were within specification, although this design had the largest time walk. This limitation was addressed and mitigated in an improved design. The analysis of the advantages and disadvantages of the three front-ends in the context of the CMS Inner Tracker operation requirements led to the selection of the improved design Linear front-end for integration in the final CMS readout chip
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