Evidence map›Paper›PMID 42693238›Full record

ArticleExperimental & molecular medicine2026

Proteomic analysis of pancreatic endocrine cells by mechanistic single-cell isolation identifies membrane pathways.

Lihi Grinberg, Worood Sirhan, Marina Kurtz, Michael Assa, Assaf Malka, Shira Perez, Corine Katina, Yishai Levin, Ron Piran

Abstract read
In one paragraph

Article in Experimental & molecular medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Lihi GrinbergThe Regenerative Medicine and Diabetes Laboratory, The Azrieli Faculty of Medicine, Bar-Ilan University, Safed, Israel.
Worood SirhanThe Regenerative Medicine and Diabetes Laboratory, The Azrieli Faculty of Medicine, Bar-Ilan University, Safed, Israel.
Marina KurtzThe Genomic Center, The Azrieli Faculty of Medicine, Bar-Ilan University, Safed, Israel.
Michael AssaThe Microscopy Center, The Azrieli Faculty of Medicine, Bar-Ilan University, Safed, Israel.
Assaf MalkaThe Regenerative Medicine and Diabetes Laboratory, The Azrieli Faculty of Medicine, Bar-Ilan University, Safed, Israel.
Shira PerezThe Genomic Center, The Azrieli Faculty of Medicine, Bar-Ilan University, Safed, Israel.
Corine KatinaThe Nancy and Stephen Grand Israel National Center for Personalized Medicine, The Weizmann Institute of Science, Rehovot, Israel.
Yishai LevinThe Nancy and Stephen Grand Israel National Center for Personalized Medicine, The Weizmann Institute of Science, Rehovot, Israel. yishai.levin@weizmann.ac.il.ORCID http://orcid.org/0000-0002-7279-0246
Ron PiranThe Regenerative Medicine and Diabetes Laboratory, The Azrieli Faculty of Medicine, Bar-Ilan University, Safed, Israel. ron.piran@biu.ac.il.ORCID http://orcid.org/0000-0001-7751-696X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To better understand diabetes and normoglycemia, pancreatic islet biology requires a precise molecular understanding of islet cell types at both the transcriptomic and proteomic levels. While transcriptomic analyses are well established, comprehensive proteomic characterization has been lacking, limiting our knowledge of islet molecular complexity. Here we introduce a nonenzymatic, mechanistic single-cell isolation technology using laser microdissection (LMD7), facilitating proteomic and transcriptomic analysis of physically isolated α-, β- and δ-cells from fresh-frozen, unfixed pancreatic tissue. This mechanistic approach avoids enzymatic digestion and chemical fixation, preserving the cells' native molecular state before processing. Given the limited existing proteomic data, we supplemented our findings with transcriptomic analysis generated using the same method and compared our results with data from enzymatically isolated cells, obtained by fluorescence-activated cell sorting and compiled by others. Our analysis revealed that enzymatic digestion alters gene expression patterns, particularly those of membrane-associated proteins, underscoring the impact of isolation techniques on biological outcomes. We identified cell-type-specific proteins typically underrepresented in pancreatic single-cell transcriptomic datasets. β-cells exhibited enrichment in vesicle trafficking proteins, α-cells displayed distinct calcium-dependent action potential machinery and δ-cells showed elevated expression of focal adhesion-related proteins. In addition, we report an inverse molecular relationship between β- and δ-cells, potentially driven by transcriptional regulators such as Mlxipl. By establishing robust molecular profiles directly from intact pancreatic tissue, this work provides a reference point for future pathological comparisons, offering a framework to investigate how diabetes and other endocrine disorders reshape islet cell biology.

Indexed as

Cell MembraneIslets of LangerhansProteomeProteomicsSingle-Cell AnalysisAnimalsCell SeparationGene Expression ProfilingGlucagon-Secreting CellsInsulin-Secreting CellsMiceProteome

Identifiers

PMID42693238
PMCPMC13633244

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.