Catalytic Activity of Microbially Formed Palladium Nanoparticles

The applications of palladium are wide and varied, but characteristics such as its catalytic nature allow it to be widely used in chemical and electrochemical industries. However, with the cost of palladium on the rise, alternative methods have been investigated to accommodate demands. Due to the enhanced catalytic nature of nanoparticles, palladium nanoparticles have been investigated as a viable cost reduction strategy to incorporate into catalytic systems. Common techniques for the formation of nanoparticles involve either physical or chemical methods. However, more economical and non-toxic alternatives exist in the form of biological methods. In this study, microbially-formed palladium nanoparticles were synthesized using a solution of sodium tetrachloropalladate and the metal reducing properties of Clostridium pasteurianum BC1. These palladium nanoparticles were then purified through a simple centrifugation process and characterized for their morphology, chemical, and electrocatalytic characteristics. Heat treatments and immobilized microbial cultures were also utilized to improve the catalytic performance. Morphology, size, and composition of palladium nanoparticle samples were determined using scanning electron microscopy, transmission electron microscopy, dynamic light scattering analysis, energy dispersive X-ray spectroscopy, and X-ray diffraction. Electrochemical behavior was investigated via cyclic voltammetry using a traditional three electrode set-up consisting of a modified glassy carbon working electrode, a platinum wire counter electrode, and a Ag│AgCl reference electrode in a potassium hydroxide solution.Scanning electron microscopy and transmission electron microscopy revealed consistent spherical morphology throughout all samples. Dynamic light scattering analysis revealed the average size of palladium nanoparticles formed using suspended cultures to be approximately 20 nm. The average size of palladium nanoparticles formed using immobilized cultures was found to be 15 nm. Energy dispersive X-ray spectroscopy and X-ray diffraction showed the nanoparticles in the non-heat treated samples consist only of palladium, while palladium and palladium oxides were present in heat treated samples. Finally, cyclic voltammetry revealed that palladium nanoparticles formed using suspended microbial cultures performed poorly with respect to abiotic controls, in terms of mass activity with average mass activities of 7 mAmg-1 and 93 mAmg-1, respectively. An increase in palladium nanoparticle catalytic performance was observed after utilizing immobilized microbial cultures to synthesize the nanoparticles via sodium alginate gel entrapment. The average mass activities of nanoparticles formed using suspended cultures and immobilized cultures was measured to be 7 mAmg-1 and 130 mAmg-1, respectively. Further improvements in catalyst performance were explored using heat treatment methods by heating palladium nanoparticle samples at 400 °C. Comparatively, it was found that the electrochemical activity observed in heat treated palladium nanoparticles formed using immobilized microbial cultures greatly exceeded that of heat treated palladium nanoparticles formed in suspended microbial cultures with average mass activities of 177 mAmg-1 and 43 mAmg-1, respectively.To our knowledge, this is the first study that evaluates the electrochemical catalytic activity of microbially-formed palladium nanoparticles. The results of this study aim to support the use of nanoparticles formed using facile and environmentally-friendly microbial synthesis methods as a suitable alternative as opposed to standard physical and chemical synthesis methods

Current trends in glioblastoma multiforme treatment: radiation therapy and immune checkpoint inhibitors.

Glioblastoma multiforme (GBM) is the most common primary brain cancer. Even with aggressive combination therapy, the median life expectancy for patients with GBM remains approximately 14 months. In order to improve the outcomes of patients with GBM, the development of newer treatments is critical. The concept of using the immune system as a therapeutic option has been suggested for several decades; by harnessing the body's adaptive immune mechanisms, immunotherapy could provide a durable and targeted treatment against cancer. However, many cancers, including GBM, have developed mechanisms that protect tumor cells from being recognized and eliminated by the immune system. For new immunotherapeutic regimens to be successful, overcoming immunosuppression via immune checkpoint signaling should be taken into consideration

Concert recording 2021-04-21

[Track 1]. Concerto no. 7 in E minor for flute and piano. I. Allegro / François Devienne -- [Track 2]. Serenade for flute and piano, op. 35 / Howard Hanson -- [Track 3]. Deep blue for flute and piano / Ian Clarke -- [Track 4]. Fantasia in D major for flute solo / Friedrich Kuhlau

A Simplified Crossing Fiber Model in Diffusion Weighted Imaging

Diffusion MRI (dMRI) is a vital source of imaging data for identifying anatomical connections in the living human brain that form the substrate for information transfer between brain regions. dMRI can thus play a central role toward our understanding of brain function. The quantitative modeling and analysis of dMRI data deduces the features of neural fibers at the voxel level, such as direction and density. The modeling methods that have been developed range from deterministic to probabilistic approaches. Currently, the Ball-and-Stick model serves as a widely implemented probabilistic approach in the tractography toolbox of the popular FSL software package and FreeSurfer/TRACULA software package. However, estimation of the features of neural fibers is complex under the scenario of two crossing neural fibers, which occurs in a sizeable proportion of voxels within the brain. A Bayesian non-linear regression is adopted, comprised of a mixture of multiple non-linear components. Such models can pose a difficult statistical estimation problem computationally. To make the approach of Ball-and-Stick model more feasible and accurate, we propose a simplified version of Ball-and-Stick model that reduces parameter space dimensionality. This simplified model is vastly more efficient in the terms of computation time required in estimating parameters pertaining to two crossing neural fibers through Bayesian simulation approaches. Moreover, the performance of this new model is comparable or better in terms of bias and estimation variance as compared to existing models

Evaluation of the Primary Care Mental Health Specialist role: Final Report

This report details an evaluation to assess the impact of the new primary care mental health specialist (PCMHS) role in Kent and Medway. The evaluation was undertaken by the Centre for Health Services Studies (CHSS) at the University of Kent and was conducted June 2013 to December 2014. The evaluation was commissioned by NHS Kent and Medway and supported by Kent and Medway Commissioning Support. The evaluation encompasses six CCG areas across Kent and Medway, with 13 PCMHS employed in these areas (see Table 1-1 for breakdown). The number of posts per CCG is dependent on the amount CCGs invest (roughly equating to population size), rather than prevalence of illness. The PCMHS have been seconded from Kent and Medway NHS and Social Care Partnership Trust (KMPT) for the duration of the pilot, and are either community psychiatric nurses (CPN) or occupational therapists (OT) by profession. The majority of PCMHS are hosted by a voluntary organisation (mcch); three are hosted by GP practices and two by a community Interest Company, Invicta CIC. The main objectives of the evaluation are: 1. To assess the impact on patients by capturing their experience of the service; 2. To assess the impact by capturing experiences of those delivering the service (i.e., PCMHS); 3. To assess the impact by capturing experiences of other professions who work alongside the service (i.e., mental health professionals in secondary care, GPs); 4. To assess the economic cost of the new service via a unit cost analysis

cis-regulatory circuits regulating NEK6 kinase overexpression in transformed B cells Are super-enhancer independent

Alterations in distal regulatory elements that control gene expression underlie many diseases, including cancer. Epigenomic analyses of normal and diseased cells have produced correlative predictions for connections between dysregulated enhancers and target genes involved in pathogenesis. However, with few exceptions, these predicted cis-regulatory circuits remain untested. Here, we dissect cis-regulatory circuits that lead to overexpression of NEK6, a mitosis-associated kinase, in human B cell lymphoma. We find that only a minor subset of predicted enhancers is required for NEK6 expression. Indeed, an annotated super-enhancer is dispensable for NEK6 overexpression and for maintaining the architecture of a B cell-specific regulatory hub. A CTCF cluster serves as a chromatin and architectural boundary to block communication of the NEK6 regulatory hub with neighboring genes. Our findings emphasize that validation of predicted cis-regulatory circuits and super-enhancers is needed to prioritize transcriptional control elements as therapeutic targets