Theoretical rationalisation for the mechanism of N-heterocyclic carbene-halide reductive elimination at CuIII, AgIII and AuIII

Reductive elimination of imidazolium salts from CuIII is extremely sensitive to the anionic ligand (X or Y) type on Cu (e.g. ΔG‡ ranges from 4.7 kcal mol-1 to 31.8 kcal mol-1, from chloride to benzyl). Weakly σ-donating ligands dramatically accelerate reductive elimination. Comparison with Ag/Au shows that the HOMO energy, strength of M-NHC and M-Y bonds and inherent stability of MIII with respect to MI are critical to governing reaction feasibility

A precision medicine initiative for Alzheimer's disease: the road ahead to biomarker-guided integrative disease modeling

After intense scientific exploration and more than a decade of failed trials, Alzheimer’s disease (AD) remains a fatal global epidemic. A traditional research and drug development paradigm continues to target heterogeneous late-stage clinically phenotyped patients with single 'magic bullet' drugs. Here, we propose that it is time for a paradigm shift towards the implementation of precision medicine (PM) for enhanced risk screening, detection, treatment, and prevention of AD. The overarching structure of how PM for AD can be achieved will be provided through the convergence of breakthrough technological advances, including big data science, systems biology, genomic sequencing, blood-based biomarkers, integrated disease modeling and P4 medicine. It is hypothesized that deconstructing AD into multiple genetic and biological subsets existing within this heterogeneous target population will provide an effective PM strategy for treating individual patients with the specific agent(s) that are likely to work best based on the specific individual biological make-up. The Alzheimer’s Precision Medicine Initiative (APMI) is an international collaboration of leading interdisciplinary clinicians and scientists devoted towards the implementation of PM in Neurology, Psychiatry and Neuroscience. It is hypothesized that successful realization of PM in AD and other neurodegenerative diseases will result in breakthrough therapies, such as in oncology, with optimized safety profiles, better responder rates and treatment responses, particularly through biomarker-guided early preclinical disease-stage clinical trials

Dynamic behaviour of interphases and its implication on high-energy-density cathode materials in lithium-ion batteries

Undesired electrode-electrolyte interactions prevent the use of many high-energy-density cathode materials in practical lithium-ion batteries. Efforts to address their limited service life have predominantly focused on the active electrode materials and electrolytes. Here an advanced three-dimensional chemical and imaging analysis on a model material, the nickel-rich layered lithium transition-metal oxide, reveals the dynamic behaviour of cathode interphases driven by conductive carbon additives (carbon black) in a common nonaqueous electrolyte. Region-of-interest sensitive secondary-ion mass spectrometry shows that a cathode-electrolyte interphase, initially formed on carbon black with no electrochemical bias applied, readily passivates the cathode particles through mutual exchange of surface species. By tuning the interphase thickness, we demonstrate its robustness in suppressing the deterioration of the electrode/electrolyte interface during high-voltage cell operation. Our results provide insights on the formation and evolution of cathode interphases, facilitating development of in situ surface protection on high-energy-density cathode materials in lithium-based batteries.ope

Blood-based biomarkers for Alzheimer disease: mapping the road to the clinic.

Biomarker discovery and development for clinical research, diagnostics and therapy monitoring in clinical trials have advanced rapidly in key areas of medicine - most notably, oncology and cardiovascular diseases - allowing rapid early detection and supporting the evolution of biomarker-guided, precision-medicine-based targeted therapies. In Alzheimer disease (AD), breakthroughs in biomarker identification and validation include cerebrospinal fluid and PET markers of amyloid-β and tau proteins, which are highly accurate in detecting the presence of AD-associated pathophysiological and neuropathological changes. However, the high cost, insufficient accessibility and/or invasiveness of these assays limit their use as viable first-line tools for detecting patterns of pathophysiology. Therefore, a multistage, tiered approach is needed, prioritizing development of an initial screen to exclude from these tests the high numbers of people with cognitive deficits who do not demonstrate evidence of underlying AD pathophysiology. This Review summarizes the efforts of an international working group that aimed to survey the current landscape of blood-based AD biomarkers and outlines operational steps for an effective academic-industry co-development pathway from identification and assay development to validation for clinical use.I recieved an honorarium from Roche Diagnostics for my participation in the advisory panel meeting leading to this pape

Multiscale multifactorial approaches for engineering tendon substitutes

The physiology of tendons and the continuous strains experienced daily make tendons very prone to injury. Excessive and prolonged loading forces and aging also contribute to the onset and progression of tendon injuries, and conventional treatments have limited efficacy in restoring tendon biomechanics. Tissue engineering and regenerative medicine (TERM) approaches hold the promise to provide therapeutic solutions for injured or damaged tendons despite the challenging cues of tendon niche and the lack of tendon-specific factors to guide cellular responses and tackle regeneration. The roots of engineering tendon substitutes lay in multifactorial approaches from adequate stem cells sources and environmental stimuli to the construction of multiscale 3D scaffolding systems. To achieve such advanced tendon substitutes, incremental strategies have been pursued to more closely recreate the native tendon requirements providing structural as well as physical and chemical cues combined with biochemical and mechanical stimuli to instruct cell behavior in 3D architectures, pursuing mechanically competent constructs with adequate maturation before implantation.Authors acknowledge the project “Accelerating tissue engineering and personalized medicine discoveries by the integration of key enabling nanotechnologies, marinederived biomaterials and stem cells,” supported by Norte Portugal Regional Operational Programme (NORTE 2020), under the Portugal 2020 Partnership Agreement, through the European Regional Development Fund (ERDF). Authors acknowledge the H2020 Achilles Twinning Project No. 810850, and also the European Research Council CoG MagTendon No. 772817, and the FCT Project MagTT PTDC/CTM-CTM/ 29930/2017 (POCI-01-0145-FEDER-29930

Spatiotemporal modeling of microbial metabolism

Background Microbial systems in which the extracellular environment varies both spatially and temporally are very common in nature and in engineering applications. While the use of genome-scale metabolic reconstructions for steady-state flux balance analysis (FBA) and extensions for dynamic FBA are common, the development of spatiotemporal metabolic models has received little attention. Results We present a general methodology for spatiotemporal metabolic modeling based on combining genome-scale reconstructions with fundamental transport equations that govern the relevant convective and/or diffusional processes in time and spatially varying environments. Our solution procedure involves spatial discretization of the partial differential equation model followed by numerical integration of the resulting system of ordinary differential equations with embedded linear programs using DFBAlab, a MATLAB code that performs reliable and efficient dynamic FBA simulations. We demonstrate our methodology by solving spatiotemporal metabolic models for two systems of considerable practical interest: (1) a bubble column reactor with the syngas fermenting bacterium Clostridium ljungdahlii; and (2) a chronic wound biofilm with the human pathogen Pseudomonas aeruginosa. Despite the complexity of the discretized models which consist of 900 ODEs/600 LPs and 250 ODEs/250 LPs, respectively, we show that the proposed computational framework allows efficient and robust model solution. Conclusions Our study establishes a new paradigm for formulating and solving genome-scale metabolic models with both time and spatial variations and has wide applicability to natural and engineered microbial systems