Diffusion-weighted SPECIAL improves the detection of J-coupled metabolites at ultra-high magnetic field

A new sequence for single-voxel diffusion-weighted 1H MRS (DWS), named DW-SPECIAL, is proposed to improve the detection and subsequent estimation of the diffusion properties of strongly J-coupled metabolites. It combines the semi-adiabatic SPECIAL sequence with a stimulated echo (STE) diffusion block. Acquisitions with DW-SPECIAL and STE-LASER, the current gold-standard for rodent DWS experiments at high fields, were performed at 14.1T on phantoms and in vivo on the rat brain. The apparent diffusion coefficient and intra-stick diffusivity (Callaghan's model) were fitted and compared between the sequences for glutamate, glutamine (Gln), myo-inositol, taurine, total N-acetylaspartate, total choline, total creatine and the macromolecules. The shorter echo time achieved with DW-SPECIAL (18 ms against 33 ms with STE-LASER) substantially limited the metabolites' signal loss caused by J-evolution. In addition, DW-SPECIAL preserved the main advantages of STE-LASER: absence of cross-terms, diffusion time during a STE and limited sensitivity to B1 inhomogeneities. In vivo, compared to STE-LASER, DW-SPECIAL yielded the same spectral quality and reduced the Cramer Rao Lower Bounds (CRLB) for J-coupled metabolites, irrespective of the b-value. DW-SPECIAL also reduced the standard deviation of the metabolites' diffusion estimates based on individual animal fitting without loss of accuracy compared to the fit on the averaged decay. We conclude that due to its reduced echo time, DW-SPECIAL can serve as an alternative to STE-LASER when strongly J-coupled metabolites like Gln are investigated, thereby extending the range of accessible metabolites in the context of DWS acquisitions.Comment: Submitted to Magnetic Resonance in Medecin

Noise-reduction techniques for 1H-FID-MRSI at 14.1T: Monte-Carlo validation & in vivo application

Proton magnetic resonance spectroscopic imaging (1H-MRSI) is a powerful tool that enables the multidimensional non-invasive mapping of the neurochemical profile at high-resolution over the entire brain. The constant demand for higher spatial resolution in 1H-MRSI led to increased interest in post-processing-based denoising methods aimed at reducing noise variance. The aim of the present study was to implement two noise-reduction techniques, the Marchenko-Pastur principal component analysis (MP-PCA) based denoising and the low-rank total generalized variation (LR-TGV) reconstruction, and to test their potential and impact on preclinical 14.1T fast in vivo 1H-FID-MRSI datasets. Since there is no known ground truth for in vivo metabolite maps, additional evaluations of the performance of both noise-reduction strategies were conducted using Monte-Carlo simulations. Results showed that both denoising techniques increased the apparent signal-to-noise ratio SNR while preserving noise properties in each spectrum for both in vivo and Monte-Carlo datasets. Relative metabolite concentrations were not significantly altered by either methods and brain regional differences were preserved in both synthetic and in vivo datasets. Increased precision of metabolite estimates was observed for the two methods, with inconsistencies noted on lower concentrated metabolites. Our study provided a framework on how to evaluate the performance of MP-PCA and LR-TGV methods for preclinical 1H-FID MRSI data at 14.1T. While gains in apparent SNR and precision were observed, concentration estimations ought to be treated with care especially for low-concentrated metabolites.Comment: Brayan Alves and Dunja Simicic are joint first authors. Currently in revision for NMR in Biomedicin

Engineers without Borders

Engineers Without Borders (EWB) chapter at Rowan University is a multidisciplinary team of students and faculty that work towards providing sustainable solutions to real world problems. During the academic year of 2018-2019, the team has worked on one international project located in India and three different local projects located in New Jersey. The projects for the academic year of 2018-2019 were: Ranshet Ashram School, Maharashtra, India Resilient Roots Garden, Camden NJ Ronald McDonald House, Camden, NJ Cedar Run Wildlife Refuge, Medford, N

Fast high-resolution metabolite mapping in the rat brain using 1H-FID-MRSI at 14.1T

Magnetic resonance spectroscopic imaging (MRSI) enables the simultaneous non-invasive acquisition of MR spectra from multiple spatial locations inside the brain. While 1H-MRSI is increasingly used in the human brain, it is not yet widely applied in the preclinical settings, mostly because of difficulties specifically related to very small nominal voxel size in the rodent brain and low concentration of brain metabolites, resulting in low signal-to-noise ratio SNR. In this context, we implemented a free induction decay 1H-MRSI sequence (1H-FID-MRSI) in the rat brain at 14.1T. We combined the advantages of 1H-FID-MRSI with the ultra-high magnetic field to achieve higher SNR, coverage and spatial resolution in the rodent brain, and developed a custom dedicated processing pipeline with a graphical user interface: MRS4Brain toolbox. LCModel fit, using the simulated metabolite basis-set and in-vivo measured MM, provided reliable fits for the data at acquisition delays of 1.3 and 0.94 ms. The resulting Cram\'er-Rao lower bounds were sufficiently low (<40%) for eight metabolites of interest, leading to highly reproducible metabolic maps. Similar spectral quality and metabolic maps were obtained between 1 and 2 averages, with slightly better contrast and brain coverage due to increased SNR in the latter case. Furthermore, the obtained metabolic maps were accurate enough to confirm the previously known brain regional distribution of some metabolites. The acquisitions proved high repeatability over time. We demonstrated that the increased SNR and spectral resolution at 14.1T can be translated into high spatial resolution in 1H-FID-MRSI of the rat brain in 13 minutes, using the sequence and processing pipeline described herein. High-resolution 1H-FID-MRSI at 14.1T provided reproducible and high-quality metabolic mapping of brain metabolites with significantly reduced technical limitations.Comment: Dunja Simicic and Brayan Alves are joint first author

Measuring Vibrations from Video Feeds

By using a high-speed camera, researchers at MIT in 2014 where able to recover human speech from videos of minute vibrations of objects in a room. For example, in one experiment a 2,200fps camera was positioned outside a room behind sound-proof glass, videoing an empty crisp packet on the floor inside the room, while a researcher shouted “Mary had a little lamb” at the crisp packet. By detecting minute oscillations of the crisp packet of 1 μm (0.001 mm), and using hours of computer processing, a ten second audio clip could be produced that was recognisably “Mary had a little lamb” in an American accent. The purpose of this study group was to investigate whether this tech- nique could be used in practice, with emphasis on the recovery of intel- ligible speech from a video feed of a room. During the week, the group investigated several aspects of the problem, including: • how much an object vibrates due to sound; • what can be done to maximize the vibration; • how the MIT technique detects minute vibrations in videos; • what affects the quality of the resulting recording; and • how good a recording is needed for intelligible speech. It was discovered the MIT experiments would not have recovered intel- ligible speech from an ordinary conversation; their success depended on loud sounds and prior knowledge of “Mary had a little lamb”. Camera vibrations were also ignored by MIT; these are expected to be signifi- cant, but the technique could be adapted to be resilient to them. Other possibilities for enhancing their technique, by exploiting resonances or reflections, are discussed in the report. A high-speed low-noise cam- era is essential, and any existing video footage (such as from CCTV) is unlikely to be of sufficient quality. Further experiments with high-end high-speed cameras are needed to assess the feasibility of the technique in practice

C-type cytochrome-initiated reduction of bacterial lytic polysaccharide monooxygenases

The release of glucose from lignocellulosic waste for subsequent fermentation into biofuels holds promise for securing humankind's future energy needs. The discovery of a set of copper-dependent enzymes known as lytic polysaccharide monooxygenases (LPMOs) has galvanised new research in this area. LPMOs act by oxidatively introducing chain breaks into cellulose and other polysaccharides, boosting the ability of cellulases to act on the substrate. Although several proteins have been implicated as electron sources in fungal LPMO biochemistry, no equivalent bacterial LPMO electron donors have been previously identified, although the proteins Cbp2D and E from Cellvibrio japonicus have been implicated as potential candidates. Here we analyse a small c-type cytochrome (CjX183) present in Cellvibrio japonicus Cbp2D, and show that it can initiate bacterial CuII/I LPMO reduction and also activate LPMO-catalyzed cellulose-degradation. In the absence of cellulose, CjX183-driven reduction of the LPMO results in less H2O2 production from O2, and correspondingly less oxidative damage to the enzyme than when ascorbate is used as the reducing agent. Significantly, using CjX183 as the activator maintained similar cellulase boosting levels relative to the use of an equivalent amount of ascorbate. Our results therefore add further evidence to the impact that the choice of electron source can have on LPMO action. Furthermore, the study of Cbp2D and other similar proteins may yet reveal new insight into the redox processes governing polysaccharide degradation in bacteria

Data integration in eHealth: a domain/disease specific roadmap

The paper documents a series of data integration workshops held in 2006 at the UK National e-Science Centre, summarizing a range of the problem/solution scenarios in multi-site and multi-scale data integration with six HealthGrid projects using schizophrenia as a domain-specific test case. It outlines emerging strategies, recommendations and objectives for collaboration on shared ontology-building and harmonization of data for multi-site trials in this domain

Design and development of a digital intervention for workplace stress and mental health (EMPOWER)

Purpose: We describe the design and development of the European Platform to Promote health and wellbeing in the workplace (EMPOWER) digital intervention that provides an integrative user programme meeting the needs of employees and employers in addressing work stress. Results: A user-centred design process was followed from January 2020 until November 2021. A tailored algorithm was developed to provide support at the individual employee level and the company level. Each element of the digital intervention was developed in English and then translated in Spanish, English, Polish and Finnish. The digital intervention consists of a website and a mobile application (app) that provides algorithm-based personalised content after assessing a user's somatic and psychological symptoms, work functioning, and psychosocial risk factors for work stress. It has a public section and an employer portal that provides recommendations to reduce psychosocial risks in their company based upon clustered input from employees. Usability testing was conducted and showed high ease of use and completion of tasks by participants. Conclusion: The EMPOWER digital intervention is a tailored multimodal intervention addressing wellbeing, work stress, mental and physical health problems, and work productivity. This will be used in a planned RCT in four countries to evaluate its effectiveness

Study protocol of EMPOWER : A Cluster Randomized trial of a multimodal eHealth intervention for promoting mental health in the workplace following a Stepped Wedge Trial Design

Objective: This article describes the EMPOWER study, a controlled trial aiming to determine the effectiveness and cost-effectiveness of an eHealth intervention to prevent common health problems and reduce presenteeism and absenteeism in the workplace. Intervention: The EMPOWER intervention spans universal, secondary and tertiary prevention and consists of an eHealth platform delivered via a website and a smartphone app designed to guide employees throughout different modules according to their specific profiles. Design: A stepped-wedge cluster randomized trial will be implemented in four countries (Finland, Poland, Spain and UK) with employees from small and medium enterprises (SMEs) and public agencies. Companies will be randomly allocated in one of three groups with different times at which the intervention is implemented. The intervention will last 7 weeks. Employees will answer several questionnaires at baseline, pre- and post-intervention and follow-up. Outcome measures: The main outcome is presenteeism. Secondary outcomes include depression, anxiety, insomnia, stress levels, wellbeing and absenteeism. Analyses will be conducted at the individual level using the intention-to-treat approach and mixed models. Additional analyses will evaluate the intervention effects according to gender, country or type of company. Cost-effectiveness and cost-utility analyses [based on the use of quality-adjusted life-years (QALYS)] will consider a societal, employers’ and employees’ perspective