580 research outputs found
Taking direction: new dramaturgies of science from the Splice Symposium and the Performing Science Conference
Medical performance and the ‘inaccessible’ experience of illness: An exploratory study
© 2016 Medical Humanities. All rights reserved. We report a survey of audience members’ responses (147 questionnaires collected at seven performances) and 10 in-depth interviews (five former patients and two family members, three medical practitioners) to bloodlines, a medical performance exploring the experience of haematopoietic stem-cell transplant as treatment for acute leukaemia. Performances took place in 2014 and 2015. The article argues that performances that are created through interdisciplinary collaboration can convey otherwise ‘inaccessible’ illness experiences in ways that audience members with personal experience recognise as familiar, and find emotionally affecting. In particular such performances are adept at interweaving ‘objectivist’ (objective, medical) and ‘subjectivist’ (subjective, emotional) perspectives of the illness experience, and indeed, at challenging such distinctions. We suggest that reflecting familiar yet hard-to-articulate experiences may be beneficial for the ongoing emotional recovery of people who have survived serious disease, particularly in relation to the isolation that they experience during and as a consequence of their treatment
The stem cell organisation, and the proliferative and gene expression profile of Barrett's epithelium, replicates pyloric-type gastric glands
Objective: Barrett's oesophagus shows appearances described as ‘intestinal metaplasia’, in structures called ‘crypts’ but do not typically display crypt architecture. Here, we investigate their relationship to gastric glands.
Methods: Cell proliferation and migration within Barrett's glands was assessed by Ki67 and iododeoxyuridine (IdU) labelling. Expression of mucin core proteins (MUC), trefoil family factor (TFF) peptides and LGR5 mRNA was determined by immunohistochemistry or by in situ hybridisation, and clonality was elucidated using mitochondrial DNA (mtDNA) mutations combined with mucin histochemistry.
Results: Proliferation predominantly occurs in the middle of Barrett's glands, diminishing towards the surface and the base: IdU dynamics demonstrate bidirectional migration, similar to gastric glands. Distribution of MUC5AC, TFF1, MUC6 and TFF2 in Barrett's mirrors pyloric glands and is preserved in Barrett's dysplasia. MUC2-positive goblet cells are localised above the neck in Barrett's glands, and TFF3 is concentrated in the same region. LGR5 mRNA is detected in the middle of Barrett's glands suggesting a stem cell niche in this locale, similar to that in the gastric pylorus, and distinct from gastric intestinal metaplasia. Gastric and intestinal cell lineages within Barrett's glands are clonal, indicating derivation from a single stem cell.
Conclusions: Barrett's shows the proliferative and stem cell architecture, and pattern of gene expression of pyloric gastric glands, maintained by stem cells showing gastric and intestinal differentiation: neutral drift may suggest that intestinal differentiation advances with time, a concept critical for the understanding of the origin and development of Barrett's oesophagus
Raman Spectroscopy-Based Cancer Diagnostic Platform For Pathology Classification In Barrett’s Oesophagus And Its Integration Into Clinic
Introduction/ Background
Raman spectroscopy (RS) has been shown to accurately classify tissue pathology in a variety of conditions and organ systems. Much of this work has been performed using Raman microspectrometers on tissue sections.
Despite the demonstrated potential as an accurate cancer diagnostic tool, RS is yet to be adopted by the clinic for histopathology review. The Stratified Medicine through Advanced Raman Technologies (SMART) consortium has begun to address some of the hurdles (e.g. tissue sample preparation, data collection, pre-processing and transferability) in its adoption for cancer diagnosis. SMART is a multicentre industry-clinical-academic collaboration with the aim of developing a pathology platform for advanced diagnosis, using developments in hardware and software. Renishaw’s Streamline™ Raman imaging technology enables the collection of Raman spectra much faster without compromising signal to noise
Aims
This study aims to assess the ability of this technique to accurately classify tissue pathology, using an oesophageal tissue model. This demonstrates the project’s mission to deliver a robust Raman based diagnostic platform to enable clinical researchers to stage cancer, define tumour margin, build cancer diagnostic models and discover novel disease bio markers.
Methods
Tissue was collected from the oesophagus in patients undergoing endoscopy or resection. Specimens were collected from patients with Barrett’s oesophagus (BO), dysplasia and adenocarcinoma, and snap frozen in liquid nitrogen. 8μm tissue sections were placed onto calcium fluoride slides for spectroscopic measurement and with contiguous sections stained with haematoxylin and eosin (H&E) for histological comparison. Raman spectra were collected across homogeneous regions of tissue pathology, using Streamline™ acquisitions of 60 seconds/line, at 1.1μm spatial resolution. Classification models were constructed to discriminate pathology subtypes.
Results
Advanced multivariate statistical analysis tools were used to develop pathology classification models, which were then tested using leave-one-out cross-validation. Each sample was then classified using a ‘voting classification’ for all pixels from one sample. The sensitivity and specificity of this pathology classification model using RS to discriminate dysplasia/adenocarcinoma from BO produced sensitivity and specificities >80%.
By combining multivariate statistical analysis with Streamlineâ„¢ Raman acquisition of spectral data, we have demonstrated good sensitivities and specificities. This study illustrates the potential of non-invasive rapid Raman spectral mapping measurements and development of a robust and validated oesophageal classification model that are able to classify tissue pathology, providing a diagnostic tool for researchers and clinicians with potential application to other pathology and tissue types
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