The benefits of education and of useful knowledge, generally diffused through a community, are essential to the preservation of a free government.
n his keynote address at the 1996 American Association for Higher Education Assessment and Quality Conference, Peter Ewe11 identified a number of data sources for I good practice indicators that can be used to assess and make inferences about student outcomes. One of these, syllabus review, has received relatively little attention in the literature. In this article, we describe a syllabus analysis project undertaken in two departments at a public, two-year college. The project cost little outside of time but yielded important insights into what learning activities faculty expected of their students, standards within courses, and the clarity with which information about courses is conveyed. The project fostered a variety of professional development activities centering on the structuring of courses and the clear articulation of course practices, rules, and guidelines.The project also fostered a variety of professional development activities centering on the structuring of courses and the clear articulation of course practices, rules, and guidelines.The project was conceived and carried out by a trio comprising one administrator, the director of research, and two faculty members, the chairs of the Historical and Policy Studies Department and the Behavioral and Social Studies Department at Oakton Community College in Des Plaines, Illinois. A third faculty member assisted in the coding of some of the syllabi.
Background Recent evidence suggests a role for the gut microbiome in the development and progression of many diseases and many studies have been carried out to analyse the microbiome using a variety of methods. In this study, we compare MinION sequencing with meta-transcriptomics and amplicon-based sequencing for microbiome analysis of colorectal tumour tissue samples. Methods DNA and RNA were extracted from 11 colorectal tumour samples. 16S rRNA amplicon sequencing and MinION sequencing was carried out using genomic DNA, and RNA-Sequencing for meta-transcriptomic analysis. Non-human MinION and RNA-Sequencing reads, and 16S rRNA amplicon sequencing reads were taxonomically classified using a database built from available RefSeq bacterial and archaeal genomes and a k-mer based algorithm in Kraken2. Concordance between the three platforms at different taxonomic levels was tested on a per-sample basis using Spearman's rank correlation. Results The average number of reads per sample using RNA-Sequencing was greater than 129 times that generated using MinION sequencing. However, the average read length of MinION sequences was more than 13 times that of RNA or 16S rRNA amplicon sequencing. Taxonomic assignment using 16S sequencing was less reliable beyond the genus level, and both RNA-Sequencing and MinION sequencing could detect greater numbers of phyla and genera in the same samples, compared to 16S sequencing. Bacterial species associated with colorectal cancer, Fusobacterium nucleatum, Parvimonas micra, Bacteroides fragilis and Porphyromonas gingivalis, were detectable using MinION, RNA-Sequencing and 16S rRNA amplicon sequencing data.
Background and Objective Upper tract urothelial carcinoma (UTUC) is rare in comparison to urothelial carcinoma of the bladder or renal cell carcinoma. UTUC may present with loin pain, haematuria or alternatively can be identified as an incidental finding on imaging. There are often delays to diagnosis as haematuria clinics are efficient for bladder and renal cancer but less effective for UTUC. The diagnosis and treatment of UTUC is more challenging, as it often requires two operations and multiple MDT discussions. Diagnosis must be certain to avoid unnecessary radical surgery. We found that our patients were experiencing significant delays to definitive surgery. Our patients currently follow the pathway for bladder and renal cancer, as there is no UTUC pathway at or trust or published in the literature. We audited our diagnostic pathway to see how we could tailor the pathway to be more effective for patients with UTUC. This will ensure that more patients will meet the NHS 62-day targets. Materials and Methods A retrospective review of patients management pathway from December 2008 to December 2018. Patients were identified by the pathological code for UTUC. Results A total of 62 patients underwent nephroureterectomy during a 10-year period. 48 patients were analysed. The median waiting time for haematuria clinic from referral was 21days, a further 73 days to ureterorenoscopy and biopsy, and then 14 days to definitive nephroureterectomy. Only one patient met the NHS 62-day treatment target. Our waiting times are comparable with other published international series. We have implemented a new UTUC pathway to streamline the diagnosis and management of UTUC. Some patients with UTUC will still have inevitable delays as diagnosis can be very challenging but this new pathway should improve the patient journey and reduce the waiting times significantly.
Recent evidence suggests a role for the gut microbiome in the development and progression of colorectal cancer. In this study we compare MinION sequencing with meta-transcriptomics and amplicon-based sequencing for microbiome analysis of colorectal tumour tissue samples. DNA and RNA were extracted from 11 colorectal tumour samples. RNA-Sequencing, 16S rRNA amplicon sequencing and MinION genomic sequencing was carried out and resulting data used as input for taxonomic classification using Kraken2. Taxonomic concordance between the three platforms at different taxonomic levels was tested on a per sample basis. The average number of reads per sample using RNA-Sequencing was more than 129 times that generated using MinION sequencing. However, the average read length of MinION sequences was more than 13 times that of RNA or 16S rRNA amplicon sequencing. 16S sequencing was less informative beyond the genus level, and both RNA-Sequencing and MinION sequencing could detect more phyla and genera in the same samples, compared to 16S sequencing. Long-read sequences generated using MinION sequencing can compensate for low numbers of reads for bacterial classification. MinION sequencing can discriminate between bacterial strains and plasmids and shows potential as a tool for microbiome sequencing of colorectal cancers in a clinical setting.
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