Evidence map›Paper›PMID 40483521›Full record

ReviewDiabetology & metabolic syndrome2025

Nature's blueprint for sugar metabolism: translating bee and ant strategies into human diabetes therapies.

Fahrul Nurkolis, Raffaele Romano, Antonello Santini

Abstract readReview
In one paragraph

Review in Diabetology & metabolic syndrome, 2025. 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

3 authors.

Fahrul NurkolisMaster of Basic Medical Science, Faculty of Medicine, Universitas Airlangga, Surabaya, 60131, Indonesia. Fahrul.nurkolis.mail@gmail.com.
Raffaele RomanoDepartment of Agricultural Sciences, University of Napoli Federico II, Via Università 100, 80055, Portici, Italy. rafroman@unina.it.
Antonello SantiniDepartment of Pharmacy, University of Napoli Federico II, Via Domenico Montesano, 49, 80131, Naples, Italy. asantini@unina.it.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite advances in pharmacological treatments, diabetes mellitus remains a significant global health challenge, characterized by chronic hyperglycemia and associated metabolic dysfunctions. Effective and sustainable glycemic control remains elusive, prompting exploration into unconventional sources of metabolic insights. Social insects, in particular bees and ants, exhibit remarkable physiological adaptations enabling them to thrive on carbohydrate-rich diets without developing metabolic disorders typical in humans. This review investigates the bees and ants metabolic strategies to avoid metabolic disorders like diabetes, focusing on their enzymatic pathways such as trehalose metabolism, specialized hormonal regulation involving insulin-like peptides, adipokinetic hormones, and genetic and epigenetic mechanisms underpinning their metabolic resilience. By systematically comparing these insect adaptations with human metabolic systems, the proposed study identifies potential translational applications, including engineered probiotics, gene-editing approaches, and bioactive compounds for diabetes management. Furthermore, it explores technical, ethical, and ecological considerations for translating insect-derived metabolic mechanisms into human therapies. Highlighting both opportunities and challenges, this review emphasizes the need for interdisciplinary research to responsibly integrate nature-inspired solutions into modern diabetes care.

Indexed as

AntsBeesDiabetes mellitusInsulin-like peptidesMetabolic resilienceMetabolic syndromeMolecular metabolismTrehalose metabolism

Identifiers

PMID40483521
PMCPMC12144844

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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 OpenQuestion graph.