Yield of Surveillance Colonoscopy in Older Adults with a History of Polyps: A Systematic Review and Meta-Analysis.

BACKGROUND: The benefit of surveillance colonoscopy in older adults is not well described. AIMS: To quantify the detection of colorectal cancer (CRC) and advanced polyps during surveillance colonoscopy in older adults with a history of colon polyps. METHODS: We conducted a systematic review (MEDLINE, Cochrane Library, Web of Science, and Embase) for all published studies through May 2020 in adults age > 70 undergoing surveillance colonoscopy. The main outcome was CRC and advanced polyps detection. We performed meta-analysis to pool results by age (>70 vs. 50-70). RESULTS: The search identified 6239 studies, of which 569 underwent full-text review and 64 data abstraction, of which 19 were included. The risk of detecting CRC (N = 11) was higher in those >70 compared to 50-70 (risk ratio 1.5 (95% CI 1.1-2.2); risk difference 0.8% (95% CI -0.2%-1.8%)). Similarly, the risk of detecting advanced polyps (N = 8) was higher in those >70 compared to 50-70 (risk ratio 1.3 (95% CI 1.2-1.3), risk difference 2.7% (95% CI 1.3%-4.0%)). Most studies did not stratify results by baseline polyp risk. CONCLUSIONS: The detection of CRC and advanced polyps during surveillance colonoscopy in older individuals was higher than in younger controls; however, the absolute risk increase for both was small. These differences must be weighed against competing medical problems and limited life expectancy in older adults when making decisions about surveillance colonoscopy. More primary data on the risks of CRC and advanced polyps accounting for number of past colonoscopies, prior polyp risk, and duration of time since last polyp are needed.

An Introduction to the Saccharomyces Genome Database (SGD).

The Saccharomyces Genome Database (SGD) is a well-established, key resource for researchers studying Saccharomyces cerevisiae. In addition to updating and maintaining the official genomic sequence of this highly studied organism, SGD provides integrated data regarding gene functions and phenotypes, which are extracted from the published literature. The vast amount and variety of data housed in the database can prove challenging to navigate for the first-time user. Therefore, this chapter serves as an introduction describing how to search the database in order to discover new information. We introduce the different types of pages on the website, and describe how to manipulate the tables and diagrams therein to display, download, or analyze the data using various SGD tools.

Updated regulation curation model at the Saccharomyces Genome Database.

Database URL: http://www.yeastgenome.org.

Biomarkers' Responses to Reductive Dechlorination Rates and Oxygen Stress in Bioaugmentation Culture KB-1TM.

Using mRNA transcript levels for key functional enzymes as proxies for the organohalide respiration (OHR) rate, is a promising approach for monitoring bioremediation populations in situ at chlorinated solvent-contaminated field sites. However, to date, no correlations have been empirically derived for chlorinated solvent respiring, Dehalococcoides mccartyi (DMC) containing, bioaugmentation cultures. In the current study, genome-wide transcriptome and proteome data were first used to confirm the most highly expressed OHR-related enzymes in the bioaugmentation culture, KB-1TM, including several reductive dehalogenases (RDases) and a Ni-Fe hydrogenase, Hup. Different KB-1™ DMC strains could be resolved at the RNA and protein level through differences in the sequence of a common RDase (DET1545-like homologs) and differences in expression of their vinyl chloride-respiring RDases. The dominant strain expresses VcrA, whereas the minor strain utilizes BvcA. We then used quantitative reverse-transcriptase PCR (qRT-PCR) as a targeted approach for quantifying transcript copies in the KB-1TM consortium operated under a range of TCE respiration rates in continuously-fed, pseudo-steady-state reactors. These candidate biomarkers from KB-1TM demonstrated a variety of trends in terms of transcript abundance as a function of respiration rate over the range: 7.7 × 10-12 to 5.9 × 10-10 microelectron equivalents per cell per hour (µeeq/cell∙h). Power law trends were observed between the respiration rate and transcript abundance for the main DMC RDase (VcrA) and the hydrogenase HupL (R² = 0.83 and 0.88, respectively), but not transcripts for 16S rRNA or three other RDases examined: TceA, BvcA or the RDase DET1545 homologs in KB1TM. Overall, HupL transcripts appear to be the most robust activity biomarker across multiple DMC strains and in mixed communities including DMC co-cultures such as KB1TM. The addition of oxygen induced cell stress that caused respiration rates to decline immediately (>95% decline within one hour). Although transcript levels did decline, they did so more slowly than the respiration rate observed (transcript decay rates between 0.02 and 0.03 per hour). Data from strain-specific probes on the pangenome array strains suggest that a minor DMC strain in KB-1™ that harbors a bvcA homolog preferentially recovered following oxygen stress relative to the dominant, vcrA-containing strain.

Saccharomyces genome database informs human biology.

The Saccharomyces Genome Database (SGD; http://www.yeastgenome.org) is an expertly curated database of literature-derived functional information for the model organism budding yeast, Saccharomyces cerevisiae. SGD constantly strives to synergize new types of experimental data and bioinformatics predictions with existing data, and to organize them into a comprehensive and up-to-date information resource. The primary mission of SGD is to facilitate research into the biology of yeast and to provide this wealth of information to advance, in many ways, research on other organisms, even those as evolutionarily distant as humans. To build such a bridge between biological kingdoms, SGD is curating data regarding yeast-human complementation, in which a human gene can successfully replace the function of a yeast gene, and/or vice versa. These data are manually curated from published literature, made available for download, and incorporated into a variety of analysis tools provided by SGD.

Outreach and online training services at the Saccharomyces Genome Database.

The Saccharomyces Genome Database (SGD; www.yeastgenome.org ), the primary genetics and genomics resource for the budding yeast S. cerevisiae , provides free public access to expertly curated information about the yeast genome and its gene products. As the central hub for the yeast research community, SGD engages in a variety of social outreach efforts to inform our users about new developments, promote collaboration, increase public awareness of the importance of yeast to biomedical research, and facilitate scientific discovery. Here we describe these various outreach methods, from networking at scientific conferences to the use of online media such as blog posts and webinars, and include our perspectives on the benefits provided by outreach activities for model organism databases. Database URL: http://www.yeastgenome.org.

Curated protein information in the Saccharomyces genome database.

Due to recent advancements in the production of experimental proteomic data, the Saccharomyces genome database (SGD; www.yeastgenome.org ) has been expanding our protein curation activities to make new data types available to our users. Because of broad interest in post-translational modifications (PTM) and their importance to protein function and regulation, we have recently started incorporating expertly curated PTM information on individual protein pages. Here we also present the inclusion of new abundance and protein half-life data obtained from high-throughput proteome studies. These new data types have been included with the aim to facilitate cellular biology research. Database URL: : www.yeastgenome.org.

Integration of new alternative reference strain genome sequences into the Saccharomyces genome database.

The Saccharomyces Genome Database (SGD; http://www.yeastgenome.org/) is the authoritative community resource for the Saccharomyces cerevisiae reference genome sequence and its annotation. To provide a wider scope of genetic and phenotypic variation in yeast, the genome sequences and their corresponding annotations from 11 alternative S. cerevisiae reference strains have been integrated into SGD. Genomic and protein sequence information for genes from these strains are now available on the Sequence and Protein tab of the corresponding Locus Summary pages. We illustrate how these genome sequences can be utilized to aid our understanding of strain-specific functional and phenotypic differences.Database URL: www.yeastgenome.org.

The Saccharomyces Genome Database Variant Viewer.

The Saccharomyces Genome Database (SGD; http://www.yeastgenome.org) is the authoritative community resource for the Saccharomyces cerevisiae reference genome sequence and its annotation. In recent years, we have moved toward increased representation of sequence variation and allelic differences within S. cerevisiae. The publication of numerous additional genomes has motivated the creation of new tools for their annotation and analysis. Here we present the Variant Viewer: a dynamic open-source web application for the visualization of genomic and proteomic differences. Multiple sequence alignments have been constructed across high quality genome sequences from 11 different S. cerevisiae strains and stored in the SGD. The alignments and summaries are encoded in JSON and used to create a two-tiered dynamic view of the budding yeast pan-genome, available at http://www.yeastgenome.org/variant-viewer.