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Why we love this skill
This skill serves as a reliable guide for biomedical research, ensuring highly accurate and verifiable research information through structured searches, multi-stage literature screening, and rigorous impact factor (IF) checks.
Instructions
The core of this process is: first, use multiple queries to perform a reproducible initial screening in PubMed/NCBI E-utilities, then use PMID for deduplication and abstract evidence grading; only a small number of key documents enter the PMC/BioC full-text review; in-text citations must be clickable; complete bibliographic information must be listed at the end of the article; IF can only be conservatively checked through publicly accessible sources, and cannot be assumed to have JCR or local databases, cannot be guessed, and low-confidence matches cannot be treated as definitive results.
1. Preprocessing after a user initiates a search
1.1 First, analyze the user's question.
After receiving a user's question, the natural language question is first broken down into structured elements.
Must be identified:
• Research subjects: genes, proteins, drugs, channels, cell types, tissues, diseases, and models.
• Biological systems: humans, mice, rats, zebrafish, organoids, retina, brain regions, cell lines, etc.
• Relationship types: expression, regulation, function, mechanism, phenotype, death, survival, treatment, toxicity, development, degeneration, etc.
• Evidence requirements: Whether direct evidence, mechanistic evidence, full-text evidence, charts, dosage parameters, and experimental methods are required.
• Time range: unlimited time, the last 5 years, the last 1 year, the latest developments, and classic literature.
• Output types: short answer, representative literature, review summary, experimental design suggestions, evidence table, mechanism diagram.
Example:
User issue:
"Please help me find literature related to retinal organoid death."
Structured decomposition (example):
• Core models: retinal organoid, retina organoid, hPSC-derived retinal organoid, optic cup organoid.
• Phenotype: cell death, apoptosis, degeneration, survival loss, stress, necrosis.
• Related cells: photoreceptor, cone, rod, retinal ganglion cell, Müller glia.
• Potential mechanisms: oxidative stress, ER stress, mitochondrial dysfunction, hypoxia, inflammation, ferroptosis, necroptosis.
• Evidence objectives: Prioritize original studies that directly observe cell death/apoptosis/degeneration in human or animal retinal organoids; then look for literature on indirect mechanisms.
1.2 Keyword Segmentation Principles (Example)
Don't just write one search query. Prepare at least three categories of terms for each concept.
Category 1: Precise words.
• retinal organoid
• retina organoid
• human retinal organoid
• hPSC-derived retinal organoid
• iPSC-derived retinal organoid
The second category: synonyms and hypernyms.
• optic cup organoid
• 3D retinal culture
• stem cell-derived retina
• retinal differentiation
• retinal tissue model
The third category: mechanism and phenotypic terms.
• apoptosis
• cell death
• degeneration
• survival
• stress
• oxidative stress
• ER stress
• mitochondrial dysfunction
• hypoxia
• necroptosis
• ferroptosis
If the user specifies the cell type, add:
• photoreceptor
• cone
• rod
• retinal ganglion cell
• Müller glia
• bipolar cell
• amacrine cell
If the user specifies the species or origin, add:
• human
• mouse
• rat
• zebrafish
• hESC
• iPSC
• pluripotent stem cell
1.3 Generating hierarchical search queries
Generate at least 3–6 queries. Each query corresponds to a search objective.
First layer: Direct evidence retrieval.
Used to find literature that directly matches the target model and target phenotype.
```text
("retinal organoid" OR "retina organoid" OR "human retinal organoid") AND (apoptosis OR "cell death" OR degeneration)
```
Second layer: Extended model retrieval.
Used to capture literature where the author did not use the precise term "retinal organoid" but it is actually relevant.
```text
("optic cup organoid" OR "3D retinal culture" OR "stem cell-derived retina") AND (survival OR apoptosis OR stress)
```
Third layer: Mechanism-specific search.
Used to verify specific pathways or mechanisms.
```text
("retinal organoid" OR "retina organoid") AND ("oxidative stress" OR "ER stress" OR hypoxia OR mitochondria)
```
Fourth layer: Cell type specific search.
```text
("retinal organoid" OR "retina organoid") AND (photoreceptor OR cone OR rod OR "retinal ganglion cell") AND (death OR apoptosis OR degeneration)
```
Fifth layer: Disease model retrieval.
```text
("retinal organoid" OR "retina organoid") AND (disease OR degeneration OR dystrophy OR retinitis OR glaucoma)
```
Sixth layer: Review/background search.
```text
("retinal organoid" OR "retina organoid") AND (review OR protocol OR model)
```
Research
2. What methods and websites were used for the search?
2.1 Preferred: PubMed / NCBI E-utilities
PubMed is the preferred tool for searching biomedical literature. Do not default to scraping PubMed pages. Use the NCBI E-utilities API instead.
2.1.1 ESearch: Retrieving PMID using a query
interface:
```text
https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi
```
parameter:
```text
db=pubmed
term=
retmode=json
retmax=20
sort=relevance
```
You can also sort by time:
```text
sort=pub+date
```
Example:
```text
https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi?db=pubmed&term=(%22retinal%20organoid%22%20OR%20%22retina%20organoid%22)%20AND%20(apoptosis%20OR%20%22cell%20death%22)&retmode=json&retmax=20&sort=relevance
```
Read from the return:
```text
esearchresult.idlist
```
This is the PMID list.
2.1.2 ESummary: Obtaining Literature Metadata
interface:
```text
https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esummary.fcgi
```
parameter:
```text
db=pubmed
id=PMID1,PMID2,PMID3
retmode=json
```
Extracted fields:
• PMID
• title
• fulljournalname
• source/journal abbreviation
• pubdate
• authors
• DOI and PMCID in articleids
• volume, issue, pages
2.1.3 EFetch: Retrieving Summary and XML Details
interface:
```text
https://eutils.ncbi.nlm.nih.gov/entrez/eutils/efetch.fcgi
```
parameter:
```text
db=pubmed
id=PMID1,PMID2
retmode=xml
rettype=abstract
```
Extracted fields:
• ArticleTitle
• AbstractText
• Journal Title
• ISOAbbreviation
• ISSN / eISSN
• PubDate
• DOI
• PMCID
• MeSH terms
2.1.4 Batch Retrieval Strategy
Recommended process:
1. Call ESearch for each query.
2. For each query, select the first 5–20 results.
3. Merge all PMIDs.
4. Use PMID to remove duplicates.
5. Use ESummary / EFetch to retrieve metadata and abstract data in batches.
6. In the initial screening stage, only read the metadata and abstract; do not start by reading the full text.
────────────────
2.2 Second Phase: Full Review of PMC/BioC Documents
The full text will only be included in the following cases:
• Users request to read the full text carefully.
• The abstract is insufficient to determine the mechanism.
• Requires charts, experimental methods, concentrations, dosages, IC50, EC50, Kd, and Ki.
• A small number of key PMIDs have been identified and require review on a case-by-case basis.
2.2.1 PMID to PMCID
interface:
```text
https://www.ncbi.nlm.nih.gov/pmc/utils/idconv/v1.0/?ids=
```
If PMCID is returned, it means that PMC may have open full text.
2.2.2 Prioritize BioC JSON
interface:
```text
https://www.ncbi.nlm.nih.gov/research/bionlp/RESTful/pmcoa.cgi/BioC_json/
```
Advantages: Highly structured, suitable for extracting main text paragraphs.
2.2.3 Try PMC XML when BioC is unavailable
interface:
```text
https://www.ncbi.nlm.nih.gov/pmc/articles/
```
Skip when extracting the main text:
• references
• bibliography
• Acknowledgments
• author contributions
• competing interests
Full text review must include a stop criterion:
• Each document is scanned only once.
• By default, only paragraphs related to the question are extracted.
• If the target field is not matched, mark it as "No direct evidence found".
• Avoid repeatedly scraping keywords.
────────────────
2.3 bioRxiv / medRxiv
Used to supplement the latest preprints.
You can use the official API:
```text
https://api.biorxiv.org/details/biorxiv/YYYY-MM-DD/YYYY-MM-DD
https://api.biorxiv.org/details/medrxiv/YYYY-MM-DD/YYYY-MM-DD
```
You can also use a regular search as a supplement:
```text
site:biorxiv.org retinal organoid apoptosis
site:medrxiv.org retina organoid degeneration
```
Preprints must be labeled:
```text
This is a preprint and has not been peer-reviewed.
```
────────────────
2.4 Crossref/OpenAlex/Unpaywall
Used to complete DOI, open full-text address, and publication information.
Crossref:
```text
https://api.crossref.org/works?query.title=