Surface enhanced Raman scattering

Imperial Users onl

Out of the ashes : an innovative service response following a hostel fire

When the Earlsferry Hostel, a home for twenty one people with an intellectually disability, was severely damaged by fire in 1989, the Authority for Intellectually Handicapped Persons (Alli) decided to provide alternative living arrangements which most ideally suited the needs and aspirations of the individual residents. This decision was in line with the Alli Home Environment Services Plan. This monograph describes the organisation of these living arrangements which included a transition program to independent living, living with supportive neighbours, shared housing rented from the State Housing Authority, Homeswest, and living in a coresidency situation. The monograph also looks at the assessment of client and staff outcomes and the costs of the project compared to running the Hostel. Finally, it discusses the issues which were crucial to the project\u27s success and which would be of benefit to those undertaking a similar transition

NGSQC: cross-platform quality analysis pipeline for deep sequencing data

Abstract Background While the accuracy and precision of deep sequencing data is significantly better than those obtained by the earlier generation of hybridization-based high throughput technologies, the digital nature of deep sequencing output often leads to unwarranted confidence in their reliability. Results The NGSQC (N ext G eneration S equencing Q uality C ontrol) pipeline provides a set of novel quality control measures for quickly detecting a wide variety of quality issues in deep sequencing data derived from two dimensional surfaces, regardless of the assay technology used. It also enables researchers to determine whether sequencing data related to their most interesting biological discoveries are caused by sequencing quality issues. Conclusions Next generation sequencing platforms have their own share of quality issues and there can be significant lab-to-lab, batch-to-batch and even within chip/slide variations. NGSQC can help to ensure that biological conclusions, in particular those based on relatively rare sequence alterations, are not caused by low quality sequencing.http://deepblue.lib.umich.edu/bitstream/2027.42/112794/1/12864_2010_Article_3466.pd

INTEGRATE: Gene fusion discovery using whole genome and transcriptome data

While next-generation sequencing (NGS) has become the primary technology for discovering gene fusions, we are still faced with the challenge of ensuring that causative mutations are not missed while minimizing false positives. Currently, there are many computational tools that predict structural variations (SV) and gene fusions using whole genome (WGS) and transcriptome sequencing (RNA-seq) data separately. However, as both WGS and RNA-seq have their limitations when used independently, we hypothesize that the orthogonal validation from integrating both data could generate a sensitive and specific approach for detecting high-confidence gene fusion predictions. Fortunately, decreasing NGS costs have resulted in a growing quantity of patients with both data available. Therefore, we developed a gene fusion discovery tool, INTEGRATE, that leverages both RNA-seq and WGS data to reconstruct gene fusion junctions and genomic breakpoints by split-read mapping. To evaluate INTEGRATE, we compared it with eight additional gene fusion discovery tools using the well-characterized breast cell line HCC1395 and peripheral blood lymphocytes derived from the same patient (HCC1395BL). The predictions subsequently underwent a targeted validation leading to the discovery of 131 novel fusions in addition to the seven previously reported fusions. Overall, INTEGRATE only missed six out of the 138 validated fusions and had the highest accuracy of the nine tools evaluated. Additionally, we applied INTEGRATE to 62 breast cancer patients from The Cancer Genome Atlas (TCGA) and found multiple recurrent gene fusions including a subset involving estrogen receptor. Taken together, INTEGRATE is a highly sensitive and accurate tool that is freely available for academic use

Multi-institutional analysis shows that low PCAT-14 expression associates with poor outcomes in prostate cancer

AbstractBackgroundLong noncoding RNAs (lncRNAs) are an emerging class of relatively underexplored oncogenic molecules with biological and clinical significance. Current inadequacies for stratifying patients with aggressive disease presents a strong rationale to systematically identify lncRNAs as clinical predictors in localized prostate cancer.ObjectiveTo identify RNA biomarkers associated with aggressive prostate cancer.Design, setting, and participantsRadical prostatectomy microarray and clinical data was obtained from 910 patients in three published institutional cohorts: Mayo Clinic I (N=545, median follow-up 13.8 yr), Mayo Clinic II (N=235, median follow-up 6.7 yr), and Thomas Jefferson University (N=130, median follow-up 9.6 yr).Outcome measurements and statistical analysisThe primary clinical endpoint was distant metastasis-free survival. Secondary endpoints include prostate cancer-specific survival and overall survival. Univariate and multivariate Cox regression were used to evaluate the association of lncRNA expression and these endpoints.Results and limitationsAn integrative analysis revealed Prostate Cancer Associated Transcript-14 (PCAT-14) as the most prevalent lncRNA that is aberrantly expressed in prostate cancer patients. Down-regulation of PCAT-14 expression significantly associated with Gleason score and a greater probability of metastatic progression, overall survival, and prostate cancer-specific mortality across multiple independent datasets and ethnicities. Low PCAT-14 expression was implicated with genes involved in biological processes promoting aggressive disease. In-vitro analysis confirmed that low PCAT-14 expression increased migration while overexpressing PCAT-14 reduced cellular growth, migration, and invasion.ConclusionsWe discovered that androgen-regulated PCAT-14 is overexpressed in prostate cancer, suppresses invasive phenotypes, and lower expression is significantly prognostic for multiple clinical endpoints supporting its significance for predicting metastatic disease that could be used to improve patient management.Patient summaryWe discovered that aberrant prostate cancer associated transcript-14 expression during prostate cancer progression is prevalent across cancer patients. Prostate cancer associated transcript-14 is also prognostic for metastatic disease and survival highlighting its importance for stratifying patients that could benefit from treatment intensification

The clonal evolution of metastatic colorectal cancer

Tumor heterogeneity and evolution drive treatment resistance in metastatic colorectal cancer (mCRC). Patient-derived xenografts (PDXs) can model mCRC biology; however, their ability to accurately mimic human tumor heterogeneity is unclear. Current genomic studies in mCRC have limited scope and lack matched PDXs. Therefore, the landscape of tumor heterogeneity and its impact on the evolution of metastasis and PDXs remain undefined. We performed whole-genome, deep exome, and targeted validation sequencing of multiple primary regions, matched distant metastases, and PDXs from 11 patients with mCRC. We observed intricate clonal heterogeneity and evolution affecting metastasis dissemination and PDX clonal selection. Metastasis formation followed both monoclonal and polyclonal seeding models. In four cases, metastasis-seeding clones were not identified in any primary region, consistent with a metastasis-seeding-metastasis model. PDXs underrepresented the subclonal heterogeneity of parental tumors. These suggest that single sample tumor sequencing and current PDX models may be insufficient to guide precision medicine

The RESOLVE Trial for people with chronic low back pain: Statistical analysis plan

Background: Statistical analysis plans describe the planned data management and analysis for clinical trials. This supports transparent reporting and interpretation of clinical trial results. This paper reports the statistical analysis plan for the RESOLVE clinical trial. The RESOLVE trial assigned participants with chronic low back pain to graded sensory-motor precision training or sham-control. Results: We report the planned data management and analysis for the primary and secondary outcomes. The primary outcome is pain intensity at 18-weeks post randomization. We will use mixed-effects models to analyze the primary and secondary outcomes by intention-to-treat. We will report adverse effects in full. We also describe analyses if there is non-adherence to the interventions, data management procedures, and our planned reporting of results. Conclusion: This statistical analysis plan will minimize the potential for bias in the analysis and reporting of results from the RESOLVE trial. Trial registration: ACTRN12615000610538 (https://www.anzctr.org.au/Trial/Registration/ TrialReview.aspx?id=368619). © 2020 Associac¸ao˜ Brasileira de Pesquisa e Pos-Graduac ´ ¸ao˜ em Fisioterapia. Published by Elsevier Editora Ltda. All rights reserved

Prognosis of acute low back pain: design of a prospective inception cohort study

BACKGROUND: Clinical guidelines generally portray acute low back pain as a benign and self-limiting condition. However, evidence about the clinical course of acute low back pain is contradictory and the risk of subsequently developing chronic low back pain remains uncertain. There are few high quality prognosis studies and none that have measured pain, disability and return to work over a 12 month period. This study aims to provide the first estimates of the one year prognosis of acute low back pain (pain of less than 2 weeks duration) in patients consulting primary care practitioners. A secondary aim is to identify factors that are associated with the prognosis of low back pain. METHODS/DESIGN: The study is a prospective inception cohort study. Consecutive patients consulting general medical practitioners, physiotherapists and chiropractors in the Sydney metropolitan region will complete a baseline questionnaire regarding their back pain. Subsequently these patients will be followed up by telephone 6 weeks, 3 months and 12 months after the initial consultation. Patients will be considered to have recovered from the episode of back pain if they have no pain and no limitation of activity, and have returned to pre-injury work status. Life tables will be generated to determine the one year prognosis of acute low back pain. Prognostic factors will be assessed using Cox regression. DISCUSSION: This study will provide the first estimates of the one year prognosis of acute low back pain in a representative sample of primary care patients