![silent sifter silent sifter](https://s3.manualzz.com/store/data/054038246_1-e30ebc01cd332a07299b0aa4a6928891-360x466.png)
SILENT SIFTER SKIN
A comparison of the protein binding mechanisms of our identified “in litero” clinical respiratory sensitizers shows that acylation is a prevalent protein binding mechanism, in contrast to Michael addition and Schiff base formation common to skin sensitizers. Further, these results have immediate implications for the development and refinement of predictive tools to distinguish between skin and respiratory sensitizers.
![silent sifter silent sifter](https://www.vector15.com/wp-content/uploads/2013/05/SSv25_pref_best.png)
This approach successfully identified 28 chemicals that can be considered as human respiratory sensitizers and used to evaluate the performance of NAMs as part of a weight of evidence approach to identify novel respiratory sensitizers. Clinical diagnostic criteria were defined around exposure history, respiratory effects, and specific immune response to conclusively demonstrate occupational asthma as a result of sensitization, rather than irritation. The literature retrieved for each of these candidate chemicals was sifted to identify relevant case reports and studies, and then evaluated by applying defined selection criteria.
![silent sifter silent sifter](https://4.imimg.com/data4/QI/HE/MY-98804/green-leaf-sifter-250x250.jpg)
We utilized the EPA-developed Abstract Sifter literature review tool to maximize the retrieval of publications relevant to respiratory effects in humans for each chemical in a list of chemicals suspected of inducing respiratory sensitization. In this context, we have developed an “in litero” approach to identify cases of low molecular weight chemical exposures leading to respiratory sensitization in clinical literature. In order to support the evaluation of New Approach Methodologies in development, we sought to establish a reference set of low molecular weight respiratory sensitizers based on case reports of occupational asthma. ĭespite decades of investigation, test methods to identify respiratory sensitizers remain an unmet regulatory need. Together, these query and sifting capabilities provide a powerful search. The sifter terms are highlighted by giving each the color of the term on the Main sheet. Double- clicking on any cell in the row (except the cell containing the PMID) takes the end-user to the Abstract sheet where the title and abstract of that citation are shown ( Figure 1b).
![silent sifter silent sifter](https://www.vector15.com/wp-content/uploads/2020/10/SS_Card2-234x300.png)
Similarly, new PubMed queries can be run, altered, and rerun. Sifting by entering terms and sorting can be repeated. The Main sheet's citations can be sorted by these counts. The Abstract Sifter returns the number of occurrences of each term found in the title and abstract com- bined. If a researcher is looking for neurological effects in studies where rats were dosed with chlorpyrifos, the researcher could type the term "mg/kg" in the spreadsheet cell B3, "rat" in C3, and "brain" in D3 ( Figure 1a inset). For example, the query for "chlorpyrifos" returned over 4,000 PubMed citations. The sifter feature provides a novel and effective way to narrow search results with large number of citations to find articles of interest. results of the query stored in the Main sheet can be browsed like any other data in a spreadsheet. For performance purposes, if the number of articles exceeds 5,000, the query will not be run and the user is encouraged to re-word the query to return fewer. Every new search will clear results from the previous query. All citations are thus parsed for title, abstract, authors, publication year, journal, and PubMed identifier, and the data is inserted into rows in the Main sheet. The citations are downloaded from PubMed by the Abstract Sifter, parsed by pattern matching algorithms coded in VBA. The first response returned by the E-utility is the number of articles found that satisfy the query. When the query entry is finished, the user then clicks on Submit and the query is sent to the NCBI PubMed E-utility. In fact, any query run in PubMed can be executed in the Sifter. However, these queries can be more complex. For the example in Figure 1a, the end-user has entered the simple query "chlorpyrifos". To start, the end-user clicks on the Query PubMed button at the top of the screen and enters any PubMed query of interest. The Main sheet is where the basic functions operate, including the novel functionality called "sifting". Abstract Sifter application workbook contains seven sheets: ReadMe, Main, Abstract, Notes, Log, and Landscape, and SampleQueries.