Leukocyte Reduction Filters Are Reliable and Economic Source for Natural Killer Cell Preparation.

Background: An issue that hinders researchers' access to Natural Killer (NK) cells is their low proportion in peripheral blood leukocytes. This issue is currently addressed by methods involving a series of differentiation and expansions that are time-consuming and expensive. Objective: We have investigated whether the used leukocyte reduction filters, a by-product in the blood transfusion practice that currently is considered waste, can be utilized as a source of the NK cells. Methods: Following the blood donation of 46 donors based on the Iranian Blood Transfusion Organization's protocols, a sample of peripheral blood of each donor and the leukocyte reduction filter used in their donation procedure have been obtained. The entrapped cells were flushed back from the leukocyte reduction filters. Both groups of samples were analyzed using an automatic hematological analyzer. NK cell isolation was done by the MACS negative selection method. The samples have been comparatively analyzed utilizing flow cytometry data of NK cells' subpopulation compositions, viability, degranulation patterns, and cytotoxic capacity against the K562 cell line. Results: Every major leukocyte population was abundant in the samples extracted from the used leukocyte reduction filters. The NK cells extracted from leukocyte reduction filters did not show any statistically meaningful differences (P<0.5) from peripheral blood samples in terms of subpopulation composition, viability, degranulation potency, and cytotoxic capacity. Conclusion: Used leukocyte reduction filters can be considered an economic, easy to obtain, and robust source of abundant research-grade NK cells.

rbioapi: user-friendly R interface to biologic web services' API.

SUMMARY: Many packages serve as an interface between R language and the Application Programming Interface (API) of databases and web services. There is usually a 'one-package to one-service' correspondence, which poses challenges such as consistency to the users and scalability to the developers. This, among other issues, has motivated us to develop a package as a framework to facilitate the implementation of API resources in the R language. This R package, rbioapi, is a consistent, user-friendly and scalable interface to biological and medical databases and web services. To date, rbioapi fully supports Enrichr, JASPAR, miEAA, PANTHER, Reactome, STRING and UniProt. We aim to expand this list by collaborations and contributions and gradually make rbioapi as comprehensive as possible. AVAILABILITY AND IMPLEMENTATION: rbioapi is deposited in CRAN under the https://cran.r-project.org/package=rbioapi address. The source code is publicly available in a GitHub repository at https://github.com/moosa-r/rbioapi/. Also, the documentation website is available at https://rbioapi.moosa-r.com. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.