Phase Shift Plus Interpolation: a scheme for high performance echo-reconstructive imaging

Echo-reconstruction techniques for non-intrusive imaging have wide application, from subsurface and underwater imaging to medical and industrial diagnostics. The techniques are based on experiments in which a collection of short acoustic or electromagnetic impulses, emitted at the surface, illuminate a certain volume and are backscattered by inhomogeneities of the medium. The inhomogeneities act as reecting surfaces or interfaces which cause signal echoing; the echoes are then recorded at the surface and processed through a "computational lens" defined by a propagation model to yield an image of the same inhomogeneities. The most sophisticated of these processing techniques involve simple acoustic imaging in seismic exploration, for which the huge data sets and stringent performance requirements make high performance computing essential. Migration, based on the scalar wave equation, is the standard imaging technique for seismic applications [1]. In the migration process, the recorded pressure waves are used as initial conditions for a wave field governed by the scalar wave equation in an inhomogeneous medium. Any migration technique begins with an a priori estimate of the velocity field obtained from well logs and an empirical analysis of seismic traces. By interpreting migrated data, comparing the imaged interfaces with the discontinuities of the estimated velocity model, insuficiencies of the velocity field can be detected and the estimate improved [2], allowing the next migration step to image more accurately. The iterative process (turnaround) of correcting to a velocity model consistent with the migrated data can last several computing weeks, and is particularly crucial for imaging complex geological structures, including those which are interesting for hydrocarbon prospecting. Subsurface depth imaging, being as it is the outcome of repeated steps of 3D seismic data migration, requires Gbytes of data which must be reduced, transformed, visualized and interpreted to obtain meaningful information. Severe performance requirements have led in the direction of high performance computing hardware and techniques. In addition, an enormous effort has historically gone into simplifying the migration model so as to reduce the cost of the operation while retaining the essential features of the wave propagation. The phase-shift-plus-interpolation (PSPI) algorithm can be an effective method for seismic migration using the "one-way" scalar wave equation; it is particularly well suited to data parallelism because of, among other things, its decoupling of the problem in the frequency domain.126-132Pubblicat

3D spectral reverse time migration with no-wraparound absorbing conditions

Comparative studies of methods of reverse time migration (RTM) show that spectral methods for calculating the Laplacian impose the least stringent demands on discretization stepsize; thus with spectral methods, the grid refinements often required by other methods can be avoided. Implemented with absorbing boundary conditions, which are energy-tuned to give good absorption at the boundaries, these spectral methods can be used effectively for migration, without suffering the problems of wraparound which have traditionally plagued them (Furumyra and Takenaka, 1995).1925-192

Metainference: A Bayesian Inference Method for Heterogeneous Systems

Modelling a complex system is almost invariably a challenging task. The incorporation of experimental observations can be used to improve the quality of a model, and thus to obtain better predictions about the behavior of the corresponding system. This approach, however, is affected by a variety of different errors, especially when a system populates simultaneously an ensemble of different states and experimental data are measured as averages over such states. To address this problem we present a Bayesian inference method, called metainference, that is able to deal with errors in experimental measurements as well as with experimental measurements averaged over multiple states. To achieve this goal, metainference models a finite sample of the distribution of models using a replica approach, in the spirit of the replica-averaging modelling based on the maximum entropy principle. To illustrate the method we present its application to a heterogeneous model system and to the determination of an ensemble of structures corresponding to the thermal fluctuations of a protein molecule. Metainference thus provides an approach to model complex systems with heterogeneous components and interconverting between different states by taking into account all possible sources of errors.Comment: 29 pages, 10 figure

Metainference: a Bayesian inference method for heterogeneous systems

Modeling a complex system is almost invariably a challenging task. The incorporation of experimental observations can be used to improve the quality of a model and thus to obtain better predictions about the behavior of the corresponding system. This approach, however, is affected by a variety of different errors, especially when a system simultaneously populates an ensemble of different states and experimental data are measured as averages over such states. To address this problem, we present a Bayesian inference method, called “metainference,” that is able to deal with errors in experimental measurements and with experimental measurements averaged over multiple states. To achieve this goal, metainference models a finite sample of the distribution of models using a replica approach, in the spirit of the replica-averaging modeling based on the maximum entropy principle. To illustrate the method, we present its application to a heterogeneous model system and to the determination of an ensemble of structures corresponding to the thermal fluctuations of a protein molecule. Metainference thus provides an approach to modeling complex systems with heterogeneous components and interconverting between different states by taking into account all possible sources of errors

Heterogeneity of determining disease severity, clinical course and outcomes in systemic sclerosis-associated interstitial lung disease: a systematic literature review

Objective: The course of systemic sclerosis-associated interstitial lung disease (SSc-ILD) is highly variable and different from continuously progressive idiopathic pulmonary fibrosis (IPF). Most proposed definitions of progressive pulmonary fibrosis or SSc-ILD severity are based on the research data from patients with IPF and are not validated for patients with SSc-ILD. Our study aimed to gather the current evidence for severity, progression and outcomes of SSc-ILD. Methods: A systematic literature review to search for definitions of severity, progression and outcomes recorded for SSc-ILD was performed according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines in Medline, Embase, Web of Science and Cochrane Library up to 1 August 2023. Results: A total of 9054 papers were reviewed and 342 were finally included. The most frequent tools used for the definition of SSc-ILD progression and severity were combined changes of carbon monoxide diffusing capacity (DLCO) and forced vital capacity (FVC), isolated FVC or DLCO changes, high-resolution CT (HRCT) extension and composite algorithms including pulmonary function test, clinical signs and HRCT data. Mortality was the most frequently reported long-term event, both from all causes or ILD related. Conclusions: The studies presenting definitions of SSc-ILD 'progression', 'severity' and 'outcome' show a large heterogeneity. These results emphasise the need for developing a standardised, consensus definition of severe SSc-ILD, to link a disease specific definition of progression as a surrogate outcome for clinical trials and clinical practice

Angiogenic and anti-inflammatory properties of micro-fragmented fat tissue and its derived mesenchymal stromal cells.

BACKGROUND: Adipose-derived mesenchymal stromal cells (Ad-MSCs) are a promising tool for advanced cell-based therapies. They are routinely obtained enzymatically from fat lipoaspirate (LP) as SVF, and may undergo prolonged ex vivo expansion, with significant senescence and decline in multipotency. Besides, these techniques have complex regulatory issues, thus incurring in the compelling requirements of GMP guidelines. Hence, availability of a minimally manipulated, autologous adipose tissue would have remarkable biomedical and clinical relevance. For this reason, a new device, named Lipogems® (LG), has been developed. This ready-to-use adipose tissue cell derivate has been shown to have in vivo efficacy upon transplantation for ischemic and inflammatory diseases. To broaden our knowledge, we here investigated the angiogenic and anti-inflammatory properties of LG and its derived MSC (LG-MSCs) population. METHODS: Human LG samples and their LG-MSCs were analyzed by immunohistochemistry for pericyte, endothelial and mesenchymal stromal cell marker expression. Angiogenesis was investigated testing the conditioned media (CM) of LG (LG-CM) and LG-MSCs (LG-MSCs-CM) on cultured endothelial cells (HUVECs), evaluating proliferation, cord formation, and the expression of the adhesion molecules (AM) VCAM-1 and ICAM-1. The macrophage cell line U937 was used to evaluate the anti-inflammatory properties, such as migration, adhesion on HUVECs, and release of RANTES and MCP-1. RESULTS: Our results indicate that LG contained a very high number of mesenchymal cells expressing NG2 and CD146 (both pericyte markers) together with an abundant microvascular endothelial cell (mEC) population. Substantially, both LG-CM and LG-MSC-CM increased cord formation, inhibited endothelial ICAM-1 and VCAM-1 expression following TNFα stimulation, and slightly improved HUVEC proliferation. The addition of LG-CM and LG-MSC-CM strongly inhibited U937 migration upon stimulation with the chemokine MCP-1, reduced their adhesion on HUVECs and significantly suppressed the release of RANTES and MCP-1. CONCLUSIONS: Our data indicate that LG micro-fragmented adipose tissue retains either per se, or in its embedded MSCs content, the capacity to induce vascular stabilization and to inhibit several macrophage functions involved in inflammation

Small-molecule sequestration of amyloid-β as a drug discovery strategy for Alzheimer's disease.

Disordered proteins are challenging therapeutic targets, and no drug is currently in clinical use that modifies the properties of their monomeric states. Here, we identify a small molecule (10074-G5) capable of binding and sequestering the intrinsically disordered amyloid-β (Aβ) peptide in its monomeric, soluble state. Our analysis reveals that this compound interacts with Aβ and inhibits both the primary and secondary nucleation pathways in its aggregation process. We characterize this interaction using biophysical experiments and integrative structural ensemble determination methods. We observe that this molecule increases the conformational entropy of monomeric Aβ while decreasing its hydrophobic surface area. We also show that it rescues a Caenorhabditis elegans model of Aβ-associated toxicity, consistent with the mechanism of action identified from the in silico and in vitro studies. These results illustrate the strategy of stabilizing the monomeric states of disordered proteins with small molecules to alter their behavior for therapeutic purposes

Drug-releasing mesenchymal cells strongly suppress B16 lung metastasis in a syngeneic murine model

Mesenchymal stromal cells (MSCs) are considered an important therapeutic tool in cancer therapy. They possess intrinsic therapeutic potential and can also be in vitro manipulated and engineered to produce therapeutic molecules that can be delivered to the site of diseases, through their capacity to home pathological tissues. We have recently demonstrated that MSCs, upon in vitro priming with anti-cancer drug, become drug-releasing mesenchymal cells (Dr-MCs) able to strongly inhibit cancer cells growth

PLUMED: a portable plugin for free-energy calculations with molecular dynamics

Here we present a program aimed at free-energy calculations in molecular systems. It consists of a series of routines that can be interfaced with the most popular classical molecular dynamics (MD) codes through a simple patching procedure. This leaves the possibility for the user to exploit many different MD engines depending on the system simulated and on the computational resources available. Free-energy calculations can be performed as a function of many collective variables, with a particular focus on biological problems, and using state-of-the-art methods such as metadynamics, umbrella sampling and Jarzynski-equation based steered MD. The present software, written in ANSI-C language, can be easily interfaced with both fortran and C/C++ codes.Comment: to be submitted to Computer Physics Communication