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PubMed Literature Search

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from $1.00 / 1,000 dataset items

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PubMed Literature Search

PubMed Literature Search

Keyless biomedical literature search over PubMed (NCBI E-utilities, no API key). Filter by recency. Output: one JSON item per paper (title, journal, pubdate, PMID, PubMed URL, first authors).

Pricing

from $1.00 / 1,000 dataset items

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jedi solana

jedi solana

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Keyless biomedical literature search over PubMed (NCBI E-utilities, no API key). Filter by recency. Output: one JSON item per paper (title, journal, pubdate, PMID, PubMed URL, first authors).

What you get

Every run writes a dataset with one row per record:

{
"rank": 1,
"pmid": "42691481",
"doi": "10.1021/acssensors.6c01512",
"title": "Development of a Colorimetric and Raman Dual-Mode Biosensor for Point-of-Care Bacterial Detection Based on CRISPR/dCas9-Mediated Self-Assembly.",
"journal": "ACS sensors",
"journalAbbr": "ACS Sens",
"pubdate": "2026 9 03",
"authors": [
"Ni Qun",
"Jiao Jingran",
"Jiao Ruibao",
"Luo Caijie",
"Ye Junfeng",
"Pan Kai",
"Hang Xiubing",
"Yao Li",
"Wu Guolin",
"Zhao Qihong",
"Bo Qingli",
"Qin Panzhu"
],
"n_authors": 12,
"abstract": "Timely and reliable identification of bacterial infections in emergency settings remains a major challenge. To address this challenge, here we utilized CRISPR/dCas9-mediated self-assembly to develop a colorimetric and Raman dual-mode biosensor (referred to as dCARD) and applied it to point-of-care bacterial detection. Briefly, dCARD utilized the CRISPR/dCas9-mediated precise recognition of target ",
"citedBy": null,
"url": "https://pubmed.ncbi.nlm.nih.gov/42691481/",
"scores": {
"recency": 40,
"journalRankProxy": 0,
"termCoverage": 20
},
"relevanceRecencyScore": 60,
"isNew": true,
"newSin

Input

{
"query": "CRISPR",
"limit": 10,
"sort": "date"
}
FieldTypeDescription
querystringQuery: the query parameter. Default: "CRISPR".
limitintegerLimit: the limit parameter. Default: 10.
sortstringSort: the sort parameter. Default: "date".

Use cases

  • Monitor on a schedule — run this Actor on a timer and get a fresh, normalized snapshot every time; diff the datasets to see what changed.
  • Feed a dashboard or model — clean, one-JSON-item-per-record output is ready to pipe into a spreadsheet, database, or LLM prompt without any post-processing.
  • Research & due diligence — pull a structured set of records for a topic, name, or window without scraping the public source by hand.

Limits & notes

  • No API key, no login: it only reads public endpoints/feeds. If the upstream source is degraded, the run still succeeds and returns an honest status item instead of failing.
  • Results reflect what the public source returned at run time (top-N windows, newest-first where applicable).
  • Pay-per-event via synthetic events: each default-dataset item is billed through apify-default-dataset-item ($0.001 per item), plus apify-actor-start.
  • Free to try on the free plan; PPE pricing applies to paid-plan users.

Categories

EDUCATION, OTHER