34 research outputs found
Directed assembly of optoelectronically active alkyl-<i>π</i>-conjugated molecules by adding <i>n</i>-alkanes or <i>π</i>-conjugated species
Supramolecular assembly can yield ordered structures by taking advantage of the cumulative effect of multiple non-covalent interactions between adjacent molecules. The thermodynamic origin of many self-assembled structures in water is the balance between the hydrophilic and hydrophobic segments of the molecule. Here, we show that this approach can be generalized to use solvophobic and solvophilic segments of fully hydrophobic alkylated fullerene molecules. Addition of n-alkanes results in their assembly--due to the antipathy of C60 towards n-alkanes--into micelles and hexagonally packed gel-fibres containing insulated C60 nanowires. The addition of pristine C60 instead directs the assembly into lamellar mesophases by increasing the proportion of π-conjugated material in the mixture. The assembled structures contain a large fraction of optoelectronically active material and exhibit comparably high photoconductivities. This method is shown to be applicable to several alkyl-π-conjugated molecules, and can be used to construct organized functional materials with π-conjugated sections
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Predictors of the experience of a Cytosponge test: analysis of patient survey data from the BEST3 trial
Availability of data and materials: The trial protocol, statistical analysis plan, and statistical report are available via the University of Cambridge data repository (https://www.data.cam.ac.uk/repository). Datasets will be available from R Fitzgerald ([email protected]) on request.Copyright © The Author(s) 2023. Background: The Cytosponge is a cell-collection device, which, coupled with a test for trefoil factor 3 (TFF3), can be used to diagnose Barrett’s oesophagus, a precursor condition to oesophageal adenocarcinoma. BEST3, a large pragmatic, randomised, controlled trial, investigated whether offering the Cytosponge-TFF3 test would increase detection of Barrett’s. Overall, participants reported mostly positive experiences. This study reports the factors associated with the least positive experience. Methods: Patient experience was assessed using the Inventory to Assess Patient Satisfaction (IAPS), a 22-item questionnaire, completed 7–14 days after the Cytosponge test. Study cohort: All BEST3 participants who answered ≥ 15 items of the IAPS (N = 1458). Statistical analysis: A mean IAPS score between 1 and 5 (5 indicates most negative experience) was calculated for each individual. ‘Least positive’ experience was defined according to the 90th percentile. 167 (11.4%) individuals with a mean IAPS score of ≥ 2.32 were included in the ‘least positive’ category and compared with the rest of the cohort. Eleven patient characteristics and one procedure-specific factor were assessed as potential predictors of the least positive experience. Multivariable logistic regression analysis using backwards selection was conducted to identify factors independently associated with the least positive experience and with failed swallow at first attempt, one of the strongest predictors of least positive experience. Results: The majority of responders had a positive experience, with an overall median IAPS score of 1.7 (IQR 1.5–2.1). High (OR = 3.01, 95% CI 2.03–4.46, p < 0.001) or very high (OR = 4.56, 95% CI 2.71–7.66, p < 0.001) anxiety (relative to low/normal anxiety) and a failed swallow at the first attempt (OR = 3.37, 95% CI 2.14–5.30, p < 0.001) were highly significant predictors of the least positive patient experience in multivariable analyses. Additionally, sex (p = 0.036), height (p = 0.032), alcohol intake (p = 0.011) and education level (p = 0.036) were identified as statistically significant predictors. Conclusion: We have identified factors which predict patient experience. Identifying anxiety ahead of the procedure and discussing particular concerns with patients or giving them tips to help with swallowing the capsule might help improve their experience. Trial registration ISRCTN68382401.The BEST3 trial was funded by Cancer Research UK (C14478/A21047), National Institute for Health Research covering service support costs, the UK National Health Service funding excess treatment costs and Medtronic providing funding for Cytosponge devices and TFF3 antibodies. RCF is funded by a Programme Grant from the Medical Research Council (RG84369) and is CI for the BEST3 trial and the Innovate UK funded DELTA study. JO was supported by PDS’s Cancer Research UK programme Grant (C8162/A16892) and is currently supported by the Barts Charity (EMSG1K1R). RM was supported by PDS’ Cancer Research UK Cancer Prevention Clinical Trials Unit funding (Grant No.: C8162/A25356). SGS is supported by a Yorkshire Cancer Research Fellowship. JW is funded by a Cancer Research UK career development fellowship (C7492/A17219). BG was funded as part of the DELTA study by Innovate UK (Grant No. 41162). FW is supported by the Cancer Research UK CanTest Grant [C8640/A23385]. RL is supported by the Intramural Research Program of the US National Institutes of Health/National Cancer Institute
Genomic epidemiology of SARS-CoV-2 in a UK university identifies dynamics of transmission
AbstractUnderstanding SARS-CoV-2 transmission in higher education settings is important to limit spread between students, and into at-risk populations. In this study, we sequenced 482 SARS-CoV-2 isolates from the University of Cambridge from 5 October to 6 December 2020. We perform a detailed phylogenetic comparison with 972 isolates from the surrounding community, complemented with epidemiological and contact tracing data, to determine transmission dynamics. We observe limited viral introductions into the university; the majority of student cases were linked to a single genetic cluster, likely following social gatherings at a venue outside the university. We identify considerable onward transmission associated with student accommodation and courses; this was effectively contained using local infection control measures and following a national lockdown. Transmission clusters were largely segregated within the university or the community. Our study highlights key determinants of SARS-CoV-2 transmission and effective interventions in a higher education setting that will inform public health policy during pandemics.</jats:p
Integrating Artificial Intelligence Tools in the Clinical Research Setting: The Ovarian Cancer Use Case.
Artificial intelligence (AI) methods applied to healthcare problems have shown enormous potential to alleviate the burden of health services worldwide and to improve the accuracy and reproducibility of predictions. In particular, developments in computer vision are creating a paradigm shift in the analysis of radiological images, where AI tools are already capable of automatically detecting and precisely delineating tumours. However, such tools are generally developed in technical departments that continue to be siloed from where the real benefit would be achieved with their usage. Significant effort still needs to be made to make these advancements available, first in academic clinical research and ultimately in the clinical setting. In this paper, we demonstrate a prototype pipeline based entirely on open-source software and free of cost to bridge this gap, simplifying the integration of tools and models developed within the AI community into the clinical research setting, ensuring an accessible platform with visualisation applications that allow end-users such as radiologists to view and interact with the outcome of these AI tools
Identification of genetic loci associated with ear-emergence in bread wheat
The original publication can be found at www.springerlink.comA doubled haploid population constructed from a cross between the South Australian wheat cultivars ‘Trident’ and ‘Molineux’ was grown under winter field conditions, under field conditions over summer and under artificial light both with and without vernalisation. The duration from planting to ear-emergence was recorded and QTL associated with heading date were detected using a previously constructed genetic linkage map. Associations were shown with chromosomal regions syntenous to previously identified photoperiod (Ppd-B1) and vernalisation (Vrn-A1) sensitive loci. Additional QTL associated with time to heading were also identified on chromosomes 1A, 2A, 2B, 6D, 7A and 7B. Comparisons between the genetic associations observed under the different growing conditions allowed the majority of these loci to be classified as having either photoperiod-sensitive, vernalisation-sensitive or earliness per se actions. The identification of a photoperiod-sensitive QTL on chromosome 1A provides evidence for a wheat gene possibly homoeologous to Ppd-H2 previously identified on chromosome 1H of barley. The occurrence of a putative major gene for photoperiod sensitivity observed on chromosome 7A is presented. The combined additive effects at these loci accounted for more than half the phenotypic variance in the duration from planting to ear-emergence in this population. The possible role of these loci on the adaptation of wheat in Australia is discussed