Pubmed Search

PubMed Search

[!note] Vault audit 2026-07-24 — USE-4 Use this for a single raw PubMed query (Entrez search → results); for a multi-DB scholarly search use paper-lookup, and for a synthesized briefing/report use pubmed-summariser (PubMed briefing) or lit-synthesizer (PubMed+bioRxiv report with citation graph). Distinguishing axis: single query vs multi-DB lookup vs synthesized report.

Search NCBI PubMed for scientific literature using BioPython's Entrez module.

When to Use

• User asks to find papers on a topic
• User wants recent publications in a field
• User asks for references or citations
• User wants to know the state of research on a topic

How to Execute

1. Set up Entrez

import os
from Bio import Entrez
Entrez.email = os.environ["NCBI_EMAIL"]   # REQUIRED: your own working address.
# NCBI policy requires a real, reachable contact address — it emails heavy users
# before blocking their IP. Never ship a placeholder: any value silences
# Biopython's "Email address is not specified" warning, so a bad address fails silently.

2. Search PubMed

# Search
handle = Entrez.esearch(db="pubmed", term="CRISPR delivery methods", retmax=20, sort="date")
record = Entrez.read(handle)
handle.close()

id_list = record["IdList"]
print(f"Found {record['Count']} results, showing top {len(id_list)}")

3. Fetch article details

# Fetch details
handle = Entrez.efetch(db="pubmed", id=id_list, rettype="xml")
records = Entrez.read(handle)
handle.close()

for article in records['PubmedArticle']:
    medline = article['MedlineCitation']
    pmid = str(medline['PMID'])
    title = medline['Article']['ArticleTitle']
    
    # Get authors
    authors = medline['Article'].get('AuthorList', [])
    first_author = f"{authors[0].get('LastName', '')} {authors[0].get('Initials', '')}" if authors else "Unknown"
    
    # Get journal and year
    journal = medline['Article']['Journal']['Title']
    pub_date = medline['Article']['Journal']['JournalIssue'].get('PubDate', {})
    year = pub_date.get('Year', 'N/A')
    
    # Get abstract
    abstract_parts = medline['Article'].get('Abstract', {}).get('AbstractText', [])
    abstract = ' '.join(str(a) for a in abstract_parts)[:300]
    
    print(f"PMID: {pmid}")
    print(f"Title: {title}")
    print(f"Authors: {first_author} et al.")
    print(f"Journal: {journal} ({year})")
    print(f"Abstract: {abstract}...")
    print(f"Link: https://pubmed.ncbi.nlm.nih.gov/{pmid}/")
    print()

4. Output format

Report in the caller's own format — plain text for a CLI, Markdown where it renders. Do not emit chat-app markup. Per result: title, first author et al., journal, year, PMID, and the canonical https://pubmed.ncbi.nlm.nih.gov/<PMID>/ link. Lead with the total hit count and how many you are showing. Use the PMIDs actually returned by the search — never invent one.

5. Advanced searches

Support these query patterns:

• "CRISPR"[Title] AND "delivery"[Title] — title-specific
• "2026"[Date - Publication] — date filter
• "Nature"[Journal] — journal filter
• review[Publication Type] — type filter

6. Follow-up suggestions

After showing results, suggest:

• "Want me to summarize any of these papers?"
• "Should I search with different keywords?"
• "Want me to find related papers to any of these?"