NADFaq Editorial Team
Editorial Collective
PhD, MD, and research review contributors
The NADFaq editorial team is a collective of contributors with backgrounds in molecular biology, pharmacology, gerontology, and clinical medicine. NADFaq operates as a science-first knowledge base; current editorial practice excludes paid placements, affiliate relationships, and sponsored content. All funding and operational details are disclosed at /conflict-of-interest, and any material change to that policy requires a public update before new content is commissioned. Editorial workflow follows a documented path. Every piece — reference article, directory entry, research summary, or blog post — is drafted against the evidence-grading framework at /methodology, which assigns a strong / moderate / emerging / preclinical tier to each claim based on the weight and quality of underlying studies. Citations must include PMID or DOI identifiers, and preprints are flagged inline rather than treated as primary evidence. Before publication, a minimum of two contributors with relevant subject-matter credentials review the piece: one for scientific accuracy against the source literature, one for clarity, scope, and adherence to the site's E-E-A-T standards. Reviewers cannot review content in which they hold any declared conflict of interest. Two date fields are maintained on every article: the original date of publication and the date of last review. When new primary literature materially changes a claim, the article is revised, the review date is updated, and substantive edits are logged in a changelog at the bottom of the piece. Minor corrections (typos, broken links, formatting) do not trigger a review-date update. Readers who identify an inaccuracy can flag it via the contact form; confirmed errors are corrected within seven days and annotated transparently. Named, individually-bylined articles replace the editorial-team collective byline as the contributor roster expands. Each named contributor carries a Person schema profile with verified credentials, institutional affiliation, and external authority links (ORCID, Google Scholar, PubMed author ID) to support machine-readable authority signals for both traditional search and AI citation surfaces.