In vitro and preclinical systematic dose-effect studies of Auger electron- and beta particle-emitting radionuclides and external beam radiation for cancer treatment:Dose-effect relationship for Auger electrons and beta particles

Purpose. Despite a rise in clinical use of radiopharmaceutical therapies, the biological effects of radionuclides and their relationship with absorbed radiation dose are poorly understood. Here, we set out to define this relationship for Auger electron-emitters [99mTc]TcO4─ and [123I]I─, and β--particle-emitter [188Re]ReO4─. Studies were carried out using genetically-modified cells that permitted direct radionuclide comparisons. Methods and Materials. Triple-negative MDA-MB-231 breast cancer cells, expressing the human sodium/iodide symporter (hNIS) and green fluorescent protein (GFP; MDA-MB-231.hNIS-GFP) were used. In vitro radiotoxicity of [99mTc]TcO4─, [123I]I─ and [188Re]ReO4─ was determined using clonogenic assays. Radionuclide uptake, efflux, and subcellular location were used to calculate nuclear-absorbed doses using the Medical Internal Radiation Dose formalism. In vivo studies were performed using female NSG mice bearing orthotopic MDA-MB-231.hNIS-GFP tumors and compared to X-ray-treated (12.6-15 Gy) and untreated cohorts. Absorbed dose per unit activity in tumors and NIS-expressing organs were extrapolated to reference human adult models using OLINDA/EXM®. Results. [99mTc]TcO4− and [123I]I─ reduced the survival fraction only in hNIS-expressing cells, whereas [188Re]ReO4─ reduced survival fraction in hNIS-expressing and parental cells. [123I]I─ required 2.4-fold and 1.5-fold lower decays/cell to achieve 37% survival compared to [99mTc]TcO4− and [188Re]ReO4─, respectively, following 72 hours incubation. Additionally, [99mTc]TcO4−, [123I]I─ and [188Re]ReO4─ had superior cell killing effectiveness in vitro compared to X-rays. In vivo, X-ray led to a greater median survival compared to [188Re]ReO4─ and [123I]I─ (54 days versus 45 and 43 days, respectively). Unlike the X-ray cohort, no metastases were visualized in the radionuclide-treated cohorts. Extrapolated human absorbed doses of [188Re]ReO4─ to a 1 g tumor were 13.8-fold and 11.2-fold greater than for [123I]I─ in female and male models, respectively. Conclusions. This work reports reference dose-effect data using cell and tumor models for [99mTc]TcO4─, [123I]I─, and [188Re]ReO4─, for the first time. We further demonstrate the tumor controlling effects of [123I]I─, and [188Re]ReO4─ in comparison to EBRT

Determinants of high electrical energy demand in UK homes: Appliance ownership and use

This paper provides an analysis of the appliance ownership and use factors contributing to high electrical energy demand in UK homes. The data were collected during a large-scale, city-wide survey, carried out in Leicester, UK, in 2009–2010. Annual electricity consumption and appliance ownership and use were established for 183 dwellings and an odds ratio analysis used to identify the factors that led to high electricity consumption. Many of the appliance ownership and use factors have not previously been studied for the UK domestic sector. The results of this study should be of key interest to government policy makers and energy supply companies interested in the underlying drivers of the highly positively skewed distribution of UK domestic electricity use. The study identifies those appliances that could be targeted for technical improvements or subjected to campaigns to encourage more energy efficient use in order to reduce electricity consumption among high demand households. This paper builds on earlier work by the current authors which identified the households (socio-demographic and dwelling characteristics) most likely to be high electricity consumers. The current work provides the basis for advice and guidance to those households that would enable them to, over time, reduce their electricity use

Gene expression levels assessed by oligonucleotide microarray analysis and quantitative real-time RT-PCR – how well do they correlate?

BACKGROUND: The use of microarray technology to assess gene expression levels is now widespread in biology. The validation of microarray results using independent mRNA quantitation techniques remains a desirable element of any microarray experiment. To facilitate the comparison of microarray expression data between laboratories it is essential that validation methodologies be critically examined. We have assessed the correlation between expression scores obtained for 48 human genes using oligonucleotide microarrays and the expression levels for the same genes measured by quantitative real-time RT-PCR (qRT-PCR). RESULTS: Correlations with qRT-PCR data were obtained using microarray data that were processed using robust multi-array analysis (RMA) and the MAS 5.0 algorithm. Our results indicate that when identical transcripts are targeted by the two methods, correlations between qRT-PCR and microarray data are generally strong (r = 0.89). However, we observed poor correlations between qRT-PCR and RMA or MAS 5.0 normalized microarray data for 13% or 16% of genes, respectively. CONCLUSION: These results highlight the complementarity of oligonucleotide microarray and qRT-PCR technologies for validation of gene expression measurements, while emphasizing the continuing requirement for caution in interpreting gene expression data

A Genome-Wide Gene Function Prediction Resource for Drosophila melanogaster

Predicting gene functions by integrating large-scale biological data remains a challenge for systems biology. Here we present a resource for Drosophila melanogaster gene function predictions. We trained function-specific classifiers to optimize the influence of different biological datasets for each functional category. Our model predicted GO terms and KEGG pathway memberships for Drosophila melanogaster genes with high accuracy, as affirmed by cross-validation, supporting literature evidence, and large-scale RNAi screens. The resulting resource of prioritized associations between Drosophila genes and their potential functions offers a guide for experimental investigations

COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records

BACKGROUND: Updatable estimates of COVID-19 onset, progression, and trajectories underpin pandemic mitigation efforts. To identify and characterise disease trajectories, we aimed to define and validate ten COVID-19 phenotypes from nationwide linked electronic health records (EHR) using an extensible framework. METHODS: In this cohort study, we used eight linked National Health Service (NHS) datasets for people in England alive on Jan 23, 2020. Data on COVID-19 testing, vaccination, primary and secondary care records, and death registrations were collected until Nov 30, 2021. We defined ten COVID-19 phenotypes reflecting clinically relevant stages of disease severity and encompassing five categories: positive SARS-CoV-2 test, primary care diagnosis, hospital admission, ventilation modality (four phenotypes), and death (three phenotypes). We constructed patient trajectories illustrating transition frequency and duration between phenotypes. Analyses were stratified by pandemic waves and vaccination status. FINDINGS: Among 57 032 174 individuals included in the cohort, 13 990 423 COVID-19 events were identified in 7 244 925 individuals, equating to an infection rate of 12·7% during the study period. Of 7 244 925 individuals, 460 737 (6·4%) were admitted to hospital and 158 020 (2·2%) died. Of 460 737 individuals who were admitted to hospital, 48 847 (10·6%) were admitted to the intensive care unit (ICU), 69 090 (15·0%) received non-invasive ventilation, and 25 928 (5·6%) received invasive ventilation. Among 384 135 patients who were admitted to hospital but did not require ventilation, mortality was higher in wave 1 (23 485 [30·4%] of 77 202 patients) than wave 2 (44 220 [23·1%] of 191 528 patients), but remained unchanged for patients admitted to the ICU. Mortality was highest among patients who received ventilatory support outside of the ICU in wave 1 (2569 [50·7%] of 5063 patients). 15 486 (9·8%) of 158 020 COVID-19-related deaths occurred within 28 days of the first COVID-19 event without a COVID-19 diagnoses on the death certificate. 10 884 (6·9%) of 158 020 deaths were identified exclusively from mortality data with no previous COVID-19 phenotype recorded. We observed longer patient trajectories in wave 2 than wave 1. INTERPRETATION: Our analyses illustrate the wide spectrum of disease trajectories as shown by differences in incidence, survival, and clinical pathways. We have provided a modular analytical framework that can be used to monitor the impact of the pandemic and generate evidence of clinical and policy relevance using multiple EHR sources. FUNDING: British Heart Foundation Data Science Centre, led by Health Data Research UK

Telomerecat: A ploidy-agnostic method for estimating telomere length from whole genome sequencing data.

Telomere length is a risk factor in disease and the dynamics of telomere length are crucial to our understanding of cell replication and vitality. The proliferation of whole genome sequencing represents an unprecedented opportunity to glean new insights into telomere biology on a previously unimaginable scale. To this end, a number of approaches for estimating telomere length from whole-genome sequencing data have been proposed. Here we present Telomerecat, a novel approach to the estimation of telomere length. Previous methods have been dependent on the number of telomeres present in a cell being known, which may be problematic when analysing aneuploid cancer data and non-human samples. Telomerecat is designed to be agnostic to the number of telomeres present, making it suited for the purpose of estimating telomere length in cancer studies. Telomerecat also accounts for interstitial telomeric reads and presents a novel approach to dealing with sequencing errors. We show that Telomerecat performs well at telomere length estimation when compared to leading experimental and computational methods. Furthermore, we show that it detects expected patterns in longitudinal data, repeated measurements, and cross-species comparisons. We also apply the method to a cancer cell data, uncovering an interesting relationship with the underlying telomerase genotype

Publisher Correction: Telomerecat: A ploidy-agnostic method for estimating telomere length from whole genome sequencing data.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper

Moving on up: the HCA workforce development escalator at Kingston University

Robust continuing professional development for associate practitioners (APs) and healthcare assistants (HCAs) is essential for ensuring excellent care for patients, job satisfaction and career progression. Registered nurse mentors also need know that APs and HCAs have the knowledge and skill to undertake a delegated task safely. The Faculty of Health, Social Care and Education at Kingston University, recently rated top in the NHS Health Education performance ratings in London, is committed to developing APs and HCAs. This article provides APs and HCAs with an overview of the education and training offered at Kingston University, and how this relates to the proposed Care Certificate being piloted by Health Education England, Skills for Care and Skill for Health (2014) . </jats:p