1,440 research outputs found
Mathematical modelling plant signalling networks
During the last two decades, molecular genetic studies and the completion of the sequencing of the Arabidopsis thaliana genome have increased knowledge of hormonal regulation in plants. These signal transduction pathways act in concert through gene regulatory and signalling networks whose main components have begun to be elucidated. Our understanding of the resulting cellular processes is hindered by the complex, and sometimes counter-intuitive, dynamics of the networks, which may be interconnected through feedback controls and cross-regulation. Mathematical modelling provides a valuable tool to investigate such dynamics and to perform in silico experiments that may not be easily carried out in a laboratory. In this article, we firstly review general methods for modelling gene and signalling networks and their application in plants. We then describe specific models of hormonal perception and cross-talk in plants. This sub-cellular analysis paves the way for more comprehensive mathematical studies of hormonal transport and signalling in a multi-scale setting
MSW management strategies for the city of Rome: a comparative assessment
In this paper, on the basis of a detailed characterisation of the
Municipal Solid Waste (MSW) generated in the city of Rome, different integrated management strategies regarding both source separation of selected fractions and the treatment and disposal of the residual commingled waste were compared and discussed in terms of achievable material and energy recovery.
The main findings of this study, that can be extended to other regions
characterised by similar environmental policies and social and economical
conditions, showed that source separation percentages cannot realistically exceed certain maximum percentages, particularly when they are addressed at selecting waste fractions for recycling. Regarding the management of the residual commingled waste, thermal treatment of all the fractions for which no further material recovery can be realistically pursued resulted the most convenient strategy in terms of recoverable thermal energy
Inference of the genetic network regulating lateral root initiation in Arabidopsis thaliana
Regulation of gene expression is crucial for organism growth, and it is one of the challenges in Systems Biology to reconstruct the underlying regulatory biological networks from transcriptomic data. The formation of lateral roots in Arabidopsis thaliana is stimulated by a cascade of regulators of which only the interactions of its initial elements have been identified. Using simulated gene expression data with known network topology, we compare the performance of inference algorithms, based on different approaches, for which ready-to-use software is available. We show that their performance improves with the network size and the inclusion of mutants. We then analyse two sets of genes, whose activity is likely to be relevant to lateral root initiation in Arabidopsis, by integrating sequence analysis with the intersection of the results of the best performing methods on time series and mutants to infer their regulatory network. The methods applied capture known interactions between genes that are candidate regulators at early stages of development. The network inferred from genes significantly expressed during lateral root formation exhibits distinct scale-free, small world and hierarchical properties and the nodes with a high out-degree may warrant further investigation
Worse Physical Disability Is Associated With the Expression of PD-1 on Inflammatory T-Cells in Multiple Sclerosis Patients With Older Appearing Brains
Background: Magnetic Resonance Imaging (MRI) analysis method “brain-age” paradigm could offer an intuitive prognostic metric (brain-predicted age difference: brain-PAD) for disability in Multiple Sclerosis (MS), reflecting structural brain health adjusted for aging. Equally, cellular senescence has been reported in MS using T-cell biomarker CD8+CD57+. Objective: Here we explored links between MRI-derived brain-age and blood-derived cellular senescence. We examined the value of combining brain-PAD with CD8+CD57+(ILT2+PD-1+) T-cells when predicting disability score in MS and considered whether age-related biological mechanisms drive disability. Methods: Brain-age analysis was applied to T1-weighted MRI images. Disability was assessed and peripheral blood was examined for CD8+CD57+ T-cell phenotypes. Linear regression models were used, adjusted for sex, age and normalized brain volume. Results: We included 179 mainly relapsing-remitting MS patients. A high brain-PAD was associated with high physical disability (mean brain-PAD = +6.54 [5.12–7.95]). CD8+CD57+(ILT2+PD-1+) T-cell frequency was neither associated with disability nor with brain-PAD. Physical disability was predicted by the interaction between brain-PAD and CD8+CD57+ILT2+PD-1+ T-cell frequency (AR2 = 0.196), yet without improvement compared to brain-PAD alone (AR2 = 0.206; AICc = 1.8). Conclusion: Higher frequency of CD8+CD57+ILT2+PD-1+ T-cells in the peripheral blood in patients with an older appearing brain was associated with worse disability scores, suggesting a role of these cells in the development of disability in MS patients with poorer brain health
Multicolor flow cytometry-based cellular phenotyping identifies osteoprogenitors and inflammatory cells in the osteoarthritic subchondral bone unit
Antimicrobial and antibiofilm activities of new synthesized Silver Ultra-NanoClusters (SUNCs) against Helicobacter pylori
Helicobacter pylori colonizes approximately 50% of the world\u2019s population and it is the cause of chronic gastritis, peptic ulcer disease and gastric cancer. The increase of antibiotic resistance is one of the biggest challenges of our century due to its constant increase. In order to identify an alternative or adjuvant strategy to the standard antibiotic therapy, the in vitro activity of newly synthesized Silver Ultra-NanoClusters (SUNCs), characterized by an average size inferior to 5 nm, against clinical strains of Helicobacter pylori, with different antibiotic susceptibilities, was evaluated in this study. MICs and MBCs were determined by the broth microdilution method, whereas the effect of drug combinations by the checkerboard assay. The Minimum Biofilm Eradication Concentration (MBEC) was measured using AlamarBlue (AB) assay and Colony Forming Unit (CFU) counts. The cytotoxicity was evaluated by performing the MTT assay on AGS cell line.
The inhibitory activity was expressed in terms of bacteriostatic and bactericidal potential, with MIC50, MIC90, and MBC50 of 0.33 mg/L against planktonic Helicobacter pylori strains. Using the fractional inhibitory concentration index, SUNCs showed synergism with metronidazole in one clinical strain, and very close to synergistic effect on the reference strain; the combination with clarythromicin evidenced an effect very close to synergism on both strains considered. The biofilm eradication was obtained after treatment with 2X, 3X and 4X MIC value.
Moreover, SUNCs showed low toxicity on human cells and was effective in eradicating a mature biofilm produced by H. pylori. The data presented in this study demonstrate that SUNCs could represent a novel strategy for the treatment of H. pylori infections either alone or in combination with metronidazole
In-room test results at CNAO of an innovative PT treatments online monitor (Dose Profiler)
The use of C, He and O ions as projectiles in Particle Therapy (PT) treatments is getting more and more widespread as a consequence of their enhanced relative biological effectiveness and oxygen enhancement ratio, when compared to the protons one. The advantages related to the incoming radiation improved efficacy are requiring an accurate online monitor of the dose release spatial distribution. Such monitor is necessary to prevent unwanted damage to the tissues surrounding the tumour that can arise, for example, due to morphological changes occurred in the patient during the treatment with respect to the initial CT scan. PT treatments with ions can be monitored by detecting the secondary radiation produced by the primary beam interactions with the patient body along the path towards the target volume. Charged fragments produced in the nuclear process of projectile fragmentation can be emitted at large angles with respect to the incoming beam direction and can be detected with high efficiency in a nearly background-free environment. The Dose Profiler (DP) detector, developed within the INSIDE project, is a scintillating fibre tracker that allows an online reconstruction and backtracking of such secondary charged fragments. The construction and preliminary in-room tests performed on the DP, carried out using the 12C ions beam of the CNAO treatment centre using an anthropomorphic phantom as a target, will be reviewed in this contribution. The impact of the secondary fragments interactions with the patient body will be discussed in view of a clinical application. Furthermore, the results implications for a pre-clinical trial on CNAO patients, foreseen in 2019, will be discussed
Analysis of time-profiles with in-beam PET monitoring in charged particle therapy
Background: Treatment verification with PET imaging in charged particle
therapy is conventionally done by comparing measurements of spatial
distributions with Monte Carlo (MC) predictions. However, decay curves can
provide additional independent information about the treatment and the
irradiated tissue. Most studies performed so far focus on long time intervals.
Here we investigate the reliability of MC predictions of space and time (decay
rate) profiles shortly after irradiation, and we show how the decay rates can
give an indication about the elements of which the phantom is made up.
Methods and Materials: Various phantoms were irradiated in clinical and
near-clinical conditions at the Cyclotron Centre of the Bronowice proton
therapy centre. PET data were acquired with a planar 16x16 cm PET system.
MC simulations of particle interactions and photon propagation in the phantoms
were performed using the FLUKA code. The analysis included a comparison between
experimental data and MC simulations of space and time profiles, as well as a
fitting procedure to obtain the various isotope contributions in the phantoms.
Results and conclusions: There was a good agreement between data and MC
predictions in 1-dimensional space and decay rate distributions. The fractions
of C, O and C that were obtained by fitting the decay
rates with multiple simple exponentials generally agreed well with the MC
expectations. We found a small excess of C in data compared to what was
predicted in MC, which was clear especially in the PE phantom.Comment: 9 pages, 5 figures, 1 table. Proceedings of the 20th International
Workshop on Radiation Imaging Detectors (iWorid2018), 24-28 June 2018,
Sundsvall, Swede
- …