scientific-db-pubmed-database

# PubMed Database Use this skill when a task needs biomedical literature from PubMed rather than general web search. ## When to Use - Searching MEDLINE or life-sciences literature. - Building PubMed queries with MeSH terms, field tags, dates, or article types. - Looking up PMIDs, abstracts, publication metadata, or related citations. - Running systematic-review search passes that need repeatable search strings. - Using NCBI E-utilities directly from Python, shell, or another HTTP client. ## Query Construction Start with the research question, split it into concepts, then combine concepts with Boolean operators. ```text concept_1 AND concept_2 AND filter synonym_a OR synonym_b NOT exclusion_term ``` Useful PubMed field tags: - `[ti]`: title - `[ab]`: abstract - `[tiab]`: title or abstract - `[au]`: author - `[ta]`: journal title abbreviation - `[mh]`: MeSH term - `[majr]`: major MeSH topic - `[pt]`: publication type - `[dp]`: date of publication - `[la]`: language Examples: ```text diabetes mellitus[mh] AND treatment[tiab] AND systematic review[pt] AND 2023:2026[dp] (metformin[nm] OR insulin[nm]) AND diabetes mellitus, type 2[mh] AND randomized controlled trial[pt] smith ja[au] AND cancer[tiab] AND 2026[dp] AND english[la] ``` ## MeSH and Subheadings Prefer MeSH when the concept has a stable controlled-vocabulary term. Combine MeSH with title/abstract terms when the topic is new or terminology varies. Correct subheading syntax puts the subheading before the field tag: ```text diabetes mellitus, type 2/drug therapy[mh] cardiovascular diseases/prevention & control[mh] ``` Use `[majr]` only when the topic must be central to the paper. It can improve precision but may miss relevant work. ## Filters Publication types: - `clinical trial[pt]` - `meta-analysis[pt]` - `randomized controlled trial[pt]` - `review[pt]` - `systematic review[pt]` - `guideline[pt]` Date filters: ```text 2026[dp] 2020:2026[dp] 2026/03/15[dp] ``` Availability filters: ```text free full text[sb] hasabstract[text] ``` ## E-utilities Workflow NCBI E-utilities supports repeatable API workflows: 1. `esearch.fcgi`: search and return PMIDs. 2. `esummary.fcgi`: return lightweight article metadata. 3. `efetch.fcgi`: fetch abstracts or full records in XML, MEDLINE, or text. 4. `elink.fcgi`: find related articles and linked resources. Use an email and API key for production scripts. Store API keys in environment variables, never in committed files or command history. ```python import os import time import requests BASE = "https://eutils.ncbi.nlm.nih.gov/entrez/eutils" def esearch(query: str, retmax: int = 20) -> list[str]: params = { "db": "pubmed", "term": query, "retmode": "json", "retmax": retmax, "tool": "ecc-pubmed-search", "email": os.environ.get("NCBI_EMAIL", ""), } api_key = os.environ.get("NCBI_API_KEY") if api_key: params["api_key"] = api_key response = requests.get(f"{BASE}/esearch.fcgi", params=params, timeout=30) response.raise_for_status() time.sleep(0.35) return response.json()["esearchresult"]["idlist"] pmids = esearch("hypertension[mh] AND randomized controlled trial[pt] AND 2024:2026[dp]") print(pmids) ``` For batches, prefer NCBI history server parameters (`usehistory=y`, `WebEnv`, `query_key`) instead of passing very long PMID lists through URLs. ## Output Discipline For each search pass, record: - exact search string - database searched - date searched - filters used - result count - export format - any manual exclusions Example: ```markdown | Database | Date searched | Query | Filters | Results | | --- | --- | --- | --- | ---: | | PubMed | 2026-05-11 | `sickle cell disease[mh] AND CRISPR[tiab]` | 2020:2026[dp], English | 42 | ``` ## Review Checklist - Are field tags valid PubMed tags? - Are MeSH terms paired with free-text synonyms for newer topics? - Is the date range explicit and appropriate? - Does the search log include enough detail to reproduce the query? - Are API keys loaded from the environment? - Does HTTP code call `raise_for_status()` or otherwise handle non-200 responses before parsing? - Are rate limits respected? ## References - [PubMed help](https://pubmed.ncbi.nlm.nih.gov/help/) - [NCBI E-utilities documentation](https://www.ncbi.nlm.nih.gov/books/NBK25501/) - [NCBI API key guidance](https://support.nlm.nih.gov/kbArticle/?pn=KA-05317) - NCBI support: <eutilities@ncbi.nlm.nih.gov>