Porous two-dimensional materials (MXenes) for high capacity energy storage

Energy storage is becoming a key challenge of the 21st century as the global energy system transitions away from the use of fossil fuels, which have been linked to damaging climate change and increasing air pollution. Electrochemical energy storage devices, such as batteries and supercapacitors, offer great potential to enable the clean energy transition, but require significant improvements to their performance characteristics such as energy density, power density and lifetime. The design and study of new electrode materials is key to achieving these improvements. MXenes are a new class of two-dimensional transition metal carbides and nitrides which have shown early promise in the field of electrochemical energy storage. Particularly interesting is the discovery of pseudocapacitive intercalation as their charge storage mechanism, since this could enable high power and energy densities with long cycling lifetimes into one device. However, the performance of MXene electrodes greatly depends on the electrode architecture, with multilayered or restacked MXenes showing unsatisfactory performances. This thesis reports on the development of pillaring techniques to increase the interlayer spacing between MXene (Ti3C2 and Mo2TiC2) sheets creating porous electrode architectures. This is shown to lead to large increases in the interlayer spacings, with up to 60-fold increases in the specific surface areas, among the highest reported for MXenes to-date. The pillared MXenes are then tested in a variety of systems for metal-ion capacitor applications, including organic Li-ion and Na-ion and aqueous Zn-ion systems. It was found that the pillared materials outperformed the non-pillared materials in each system studied, with improvements in capacities, rate capabilities, cycling stabilities and coulombic efficiencies. In addition, the pillaring and electrochemical mechanisms are studied using a combination of microscopy, spectroscopy and electrochemical techniques, providing important understanding to assist with the further development of this field

Pre-trial inter-laboratory analytical validation of the FOCUS4 personalised therapy trial.

INTRODUCTION: Molecular characterisation of tumours is increasing personalisation of cancer therapy, tailored to an individual and their cancer. FOCUS4 is a molecularly stratified clinical trial for patients with advanced colorectal cancer. During an initial 16-week period of standard first-line chemotherapy, tumour tissue will undergo several molecular assays, with the results used for cohort allocation, then randomisation. Laboratories in Leeds and Cardiff will perform the molecular testing. The results of a rigorous pre-trial inter-laboratory analytical validation are presented and discussed. METHODS: Wales Cancer Bank supplied FFPE tumour blocks from 97 mCRC patients with consent for use in further research. Both laboratories processed each sample according to an agreed definitive FOCUS4 laboratory protocol, reporting results directly to the MRC Trial Management Group for independent cross-referencing. RESULTS: Pyrosequencing analysis of mutation status at KRAS codons12/13/61/146, NRAS codons12/13/61, BRAF codon600 and PIK3CA codons542/545/546/1047, generated highly concordant results. Two samples gave discrepant results; in one a PIK3CA mutation was detected only in Leeds, and in the other, a PIK3CA mutation was only detected in Cardiff. pTEN and mismatch repair (MMR) protein expression was assessed by immunohistochemistry (IHC) resulting in 6/97 discordant results for pTEN and 5/388 for MMR, resolved upon joint review. Tumour heterogeneity was likely responsible for pyrosequencing discrepancies. The presence of signet-ring cells, necrosis, mucin, edge-effects and over-counterstaining influenced IHC discrepancies. CONCLUSIONS: Pre-trial assay analytical validation is essential to ensure appropriate selection of patients for targeted therapies. This is feasible for both mutation testing and immunohistochemical assays and must be built into the workup of such trials. TRIAL REGISTRATION NUMBER: ISRCTN90061564

Urinary nandrolone metabolite detection after ingestion of a nandrolone precursor

Introduction: Quantities of various anabolic/ androgenic steroids have been found in dietary supplements without their presence being disclosed on the label. The aim of this study was to quantify the excretion patterns of the diagnostic metabolites, 19-norandrosterone (19-NA) and 19-noretiocholanolone (19-NE), after ingestion of small doses of 19-nor-4-androstene-3,17- dione (19-norandrostenedione). Methods: Eleven males and nine females entered the laboratory in the morning following an overnight fast. An initial urine sample was collected and volunteers then ingested 500 mL of water containing 5 g of creatine monohydrate and either 1.0 μg, 2.5 μg or 5.0 μg of 19-norandrostendione. The volume of each urine void was measured and an aliquot taken. Samples were analysed for the metabolites 19-NA and 19-NE by GCMS. Results Baseline urinary 19-NA concentrations were 0.19±0.14 ng/mL. Ingestion of the supplement resulted in peak mean urinary 19-NA concentrations of 0.68±0.36 ng/mL, 1.56±0.86 ng/mL, and 3.89±3.11 ng/mL in the 1.0μg, 2.5μg or 5.0μg trials respectively. Under current WADA regulations, ingestion of the 1.0 μg dose produced 0 positive doping tests, 5 subjects (20%) tested positive in the 2.5 μg trial and 15 subjects (75%) had urinary 19- NA concentrations exceeding 2 ng/mL after ingesting creatine containing 5.0 μg of the steroid. The recovery of the ingested dose was highly variable between individuals, with values ranging from 11 - 84 % (mean±SD = 47 ± 18%). Conclusions: Ingestion of trace amounts of 19-norandrostendione can result in transient elevations of urinary 19-NA and 19- NE concentrations. The addition of as little as 2.5 μg of 19-norandrostendione to a supplement (0.00005% contamination) appears sufficient to result in a doping violation in some individuals

Effect of exercise and heat-induced hypohydration on brain volume

Purpose: The aim of the present study was to quantify changes in brain volume following exercise/heat-induced hypohydration in man. Methods: Eight active men completed intermittent exercise in a warm environment, until 2.9 ± 0.1 % of body mass was lost. Subjects remained hypohydrated for two hours following the end of exercise. Brain volume was measured before, immediately following, and 1h and 2h after exercise using MRI (Philips 3T Achieva). Measures of subjective feelings and core body temperature were also monitored. Blood samples were drawn to determine serum electrolyte concentrations and osmolality and to allow calculation of changes in blood and plasma volumes. Results: Brain volume was not influenced by hypohydration (0.2 ± 0.4 %; ES 0.2; P = 0.310). Reductions in ventricular (4.0 ± 1.8 %; ES 4.6; P < 0.001) and CSF (3.1 ± 1.9%; ES 3.3; P = 0.003) volumes were observed following exercise. Compared with pre-exercise levels, serum osmolality was elevated throughout the 2h post-exercise period (+10 ± 2 mosmol/kg; P < 0.001). Core temperature increased from 37.1 ± 0.3oC at rest to 39.3 ± 0.5oC at the end of exercise (P = 0.001). Conclusions: These data demonstrate that brain volume remains unchanged in response to moderate hypohydration and the presence of serum hyperosmolality, suggesting that mechanisms are in place to defend brain volume

Metabolic profiling of human saliva before and after induced physiological stress by ultra-high performance liquid chromatography-ion mobility-mass spectrometry

A method has been developed for metabolite profiling of the salivary metabolome based on protein precipitation and ultra-high performance liquid chromatography coupled with ion mobility-mass spectrometry (UHPLC–IM–MS). The developed method requires 0.5 mL of human saliva, which is easily obtainable by passive drool. Standard protocols have been established for the collection, storage and pre-treatment of saliva. The use of UHPLC allows rapid global metabolic profiling for biomarker discovery with a cycle time of 15 min. Mass spectrometry imparts the ability to analyse a diverse number of species reproducibly over a wide dynamic range, which is essential for profiling of biofluids. The combination of UHPLC with IM–MS provides an added dimension enabling complex metabolic samples to be separated on the basis of retention time, ion mobility and mass-to-charge ratio in a single chromatographic run. The developed method has been applied to targeted metabolite identification and untargeted metabolite profiling of saliva samples collected before and after exercise-induced physiological stress. δ-Valerolactam has been identified as a potential biomarker on the basis of retention time, MS/MS spectrum and ion mobility drift time

Experimental investigation of energy storage properties and thermal conductivity of a novel organic phase change material/MXene as A new class of nanocomposites

Energy storage is a global critical issue and important area of research as most of the renewable sources of energy are intermittent. In this research work, recently emerged inorganic nanomaterial (MXene) is used for the first time with paraffin wax as a phase change material (PCM) to improve its thermo-physical properties. This paper focuses on preparation, characterization, thermal properties and thermal stability of new class of nanocomposites induced with MXene nanoparticles in three different concentrations. Acquired absorbance (UV-Vis) for nanocomposite with loading concentration of 0.3 wt.% of MXene achieved ~39% enhancement in comparison with the pure paraffin wax. Thermal conductivity measurement for nanocomposites in a solid state is performed using a KD2 PRO decagon. The specific heat capacity (cp) of PCM based MXene is improved by introducing MXene. The improvement of cp is found to be 43% with 0.3 wt.% of MXene loaded in PCM. The highest thermal conductivity increment is found to be 16% at 0.3 wt.% concentration of MXene in PCM. Decomposition temperature of this new class of nanocomposite with 0.3 wt.% mass fraction is increased by ~6%. This improvement is beneficial in thermal energy storage and heat transfer applications

Image-based consensus molecular subtype (imCMS) classification of colorectal cancer using deep learning

OBJECTIVE Complex phenotypes captured on histological slides represent the biological processes at play in individual cancers, but the link to underlying molecular classification has not been clarified or systematised. In colorectal cancer (CRC), histological grading is a poor predictor of disease progression, and consensus molecular subtypes (CMSs) cannot be distinguished without gene expression profiling. We hypothesise that image analysis is a cost-effective tool to associate complex features of tissue organisation with molecular and outcome data and to resolve unclassifiable or heterogeneous cases. In this study, we present an image-based approach to predict CRC CMS from standard H&E sections using deep learning. DESIGN Training and evaluation of a neural network were performed using a total of n=1206 tissue sections with comprehensive multi-omic data from three independent datasets (training on FOCUS trial, n=278 patients; test on rectal cancer biopsies, GRAMPIAN cohort, n=144 patients; and The Cancer Genome Atlas (TCGA), n=430 patients). Ground truth CMS calls were ascertained by matching random forest and single sample predictions from CMS classifier. RESULTS Image-based CMS (imCMS) accurately classified slides in unseen datasets from TCGA (n=431 slides, AUC)=0.84) and rectal cancer biopsies (n=265 slides, AUC=0.85). imCMS spatially resolved intratumoural heterogeneity and provided secondary calls correlating with bioinformatic prediction from molecular data. imCMS classified samples previously unclassifiable by RNA expression profiling, reproduced the expected correlations with genomic and epigenetic alterations and showed similar prognostic associations as transcriptomic CMS. CONCLUSION This study shows that a prediction of RNA expression classifiers can be made from H&E images, opening the door to simple, cheap and reliable biological stratification within routine workflows

Conclusions of the II International and IV Spanish Hydration Congress. Toledo, Spain, 2nd-4th December, 2015

Water is the major component of our organism representing about 60% of total body weight in adults and has to be obtained through the consumption of different foods and beverages as part of our diet. Water is an essential nutrient performing important functions, including transport of other nutrients, elimination of waste products, temperature regulation, lubrication and structural support. In this context, hydration through water has an essential role in health and wellness, which has been highly acknowledged in recent years among the health community experts such as nutritionists, dietitians, general practitioners, pharmacists, educators, as well as by physical activity and sport sciences experts and the general population

Phylogenetic ctDNA analysis depicts early-stage lung cancer evolution.

The early detection of relapse following primary surgery for non-small-cell lung cancer and the characterization of emerging subclones, which seed metastatic sites, might offer new therapeutic approaches for limiting tumour recurrence. The ability to track the evolutionary dynamics of early-stage lung cancer non-invasively in circulating tumour DNA (ctDNA) has not yet been demonstrated. Here we use a tumour-specific phylogenetic approach to profile the ctDNA of the first 100 TRACERx (Tracking Non-Small-Cell Lung Cancer Evolution Through Therapy (Rx)) study participants, including one patient who was also recruited to the PEACE (Posthumous Evaluation of Advanced Cancer Environment) post-mortem study. We identify independent predictors of ctDNA release and analyse the tumour-volume detection limit. Through blinded profiling of postoperative plasma, we observe evidence of adjuvant chemotherapy resistance and identify patients who are very likely to experience recurrence of their lung cancer. Finally, we show that phylogenetic ctDNA profiling tracks the subclonal nature of lung cancer relapse and metastasis, providing a new approach for ctDNA-driven therapeutic studies