לוח שנה משולב

Much has been written of the potential of ultra-high field MR scanners, such as 7 tesla, due to their inherently higher signal-to-noise ratio (SNR). This native boost is of great use in making techniques that operate in a low SNR regime, such as spectroscopy, more viable. Application of spectroscopic techniques at 7 tesla also come with a secondary, yet perhaps more important benefit in increased spectral resolution. This can allow for the quantitative investigation of metabolites that are difficult to resolve and measure reliably at lower field strengths.
This seminar will relate early experiences in spectroscopy from the Siemens Terra 7T system at the University of Glasgow. This will include the optimisation of single voxel techniques for clinical studies, such as the measurement of glutamate in neuroinflammatory conditions, as well as an update on development work, such as a spectral 2D correlated spectroscopy (COSY) acquisition for investigation of glioma tumours, including a focus on 2-hydorxyglutarate. It will also cover the development of a novel MR spectroscopic imaging (MRSI) technique based on the EPSI sequence, which will allow for high resolution, full spectral bandwidth 7T acquisitions in a clinically viable time, by application of compressed sensing methods

The dwarf galaxies orbiting the Milky Way are the oldest, least luminous, most dark matter-dominated, and least chemically evolved stellar systems known. To begin, I will provide a brief introduction to these galaxies, highlighting the recent discovery of large numbers of ultra-faint dwarf galaxies. I will then explain how we can measure their dark matter content and describe some of the numerous ways that dwarfs are being used to constrain the properties of dark matter. Finally, I will show how chemical abundance measurements of dwarf galaxy stars provided critical insight into r-process nucleosynthesis prior to the LIGO discovery of a neutron star merger.

Engineering vascularized constructs represents a key challenge in tissue engineering. Sufficient vascularization in engineered tissues can be achieved through coordinated application of improved biomaterial systems with proper cell types. We have shown that vessel network maturity levels and morphology are highly regulated by matrix composition and analyzed the vasculogenic dynamics within the constructs. We also explored the effect of mechanical forces on vessels organization and demonstrated that morphogenesis of 3D vascular networks is regulated by tensile forces. Revealing the cues controlling vascular network properties and morphology can enhance tissue vascularization and improve graft integration prospects.

TBA

We have shown that microorganisms (bacteria, yeast and fungi) were present in clouds and were metabolically active. As a consequence a new scientific question rose: are they able to modify the chemical composition of clouds and be an alternative route to radical chemistry?
In the past we have mainly studied the biotransformation of simple carbon compounds (acetate, succinate, formate, methanol, formaldehyde), and oxidants (H2O2). We showed that biodegradation rates were within the same range of order than photo-transformation rates.
More recently we investigated their potential biodegradation activity towards atmospheric pollutants.
Using GCxGC-HRMS technique we were able to detect and identify over 100 semi-volatile compounds in 3 cloud samples collected at the puy de Dôme station (1465 m, France). Among these compounds, 10 priority pollutants from the US EPA list were identified and quantified.
We focused our work on the biodegradation of phenol and catechol in clouds using two strategies.
1) A metatranscriptomic analysis showed in cloud activity of microorganisms. We detected transcripts of genes coding for phenol monooxygenases (and phenol hydroxylases) and catechol 1,2-dioxygenases. These enzymes were likely from Gamma-proteobacteria (Acinetobacter and Pseudomonas genera).
2) 145 bacterial strains isolated from cloud water were screened for their phenol degradation capabilities, 93% of them (mainly Pseudomonas and Rhodococcus strains) were positive. These findings highlighted the possibility of phenol degradation by microorganisms in clouds.
To go further we measured the biodegradation rates of Phenol and Catechol by one of the most active strain (Rhodococcus enclensis) and compared them with the transformation rates resulting from the reactivity of °OH and NO3°radicals. In the cloud water phase, both phenol transformation rates were within the same range of order, while biodegradation of catechol was ten times quicker than chemical transformation. The experimentally derived biodegradation rates were included in a multiphase box model to compare the chemical loss rates of phenol and catechol in both the gas and aqueous phases to their biodegradation rate in the aqueous phase under atmospheric conditions.
In conclusion our results suggest that cloud microorganisms could play a role in atmospheric chemistry.

The conversion of physical analog signals to the digital domain for further processing inevitably entails loss of information.The famous Shannon-Nyquist theorem has become a landmark in analog to digital conversion and the development of digital signal processing algorithms. However, in many modern applications, the signal bandwidths have increased tremendously, while the acquisition capabilities have not scaled sufficiently fast. Furthermore, the resulting high rate digital data requires storage, communication and processing at very high rates which is computationally expensive and requires large amounts of power. In this talk, we present a framework for sampling and processing a wide class of wideband analog signals at rates far below Nyquist by exploiting signal structure and the processing task. We then show how these ideas can be used to overcome fundamental resolution limits in optical microscopy, ultrasound imaging, quantum systems and more. We demonstrate the theory through several demos of real-time sub-Nyquist prototypes and devices operating beyond the standard resolution limits combining high spatial resolution with short integration time.