Evidence map›Paper›PMID 40843203›Full record

ArticleFrontiers in nutrition2025

Stage-specific metabolic allocation: nutrient investment strategies during

Tingting Zhou, Ningbo Huangfu, Li Wang, Junyu Luo, Jinjie Cui, Xiangzhen Zhu, Sumei Wan, Xueke Gao

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in nutrition, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Habitat suitability for the soybean aphid,Frontiers in plant science · 2026
    Article
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

8 authors.

Tingting Zhou *College of Life Science and Technology, Tarim University, Xinjiang, China.
Ningbo Huangfu *Research Base of Zhengzhou University, State Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Henan, Anyang, China.
Li WangResearch Base of Zhengzhou University, State Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Henan, Anyang, China.
Junyu LuoResearch Base of Zhengzhou University, State Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Henan, Anyang, China.
Jinjie CuiResearch Base of Zhengzhou University, State Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Henan, Anyang, China.
Xiangzhen ZhuResearch Base of Zhengzhou University, State Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Henan, Anyang, China.
Sumei WanCollege of Agriculture, Tarim University, Xinjiang, China.
Xueke GaoResearch Base of Zhengzhou University, State Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Henan, Anyang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Parasitic wasps are key biological control agents that rely on precise nutrient allocation to regulate host exploitation and optimize their own development. Nutrients, particularly lipids and energy-related metabolites, play a critical role in shaping stage-specific growth and survival strategies in parasitic wasps. Methods: To analyze the allocation patterns of metabolite resources during development of parasitoid wasps, the multi-omics analysis was employed to systematically investigate nutrient dynamics across three growth periods in Results: Here, a total of 753 metabolites were detected by untargeted metabolomics, with numerous nutritionally critical compounds including amino acids, fatty acids and carbohydrates showed stage-specific variations. A total of 31 fatty acids (11 SFAs, 9 MUFAs, 11 PUFAs) were identified by targeted fatty acid detection, exhibiting a notable variation across development notably, PUFAs remained consistently dominant throughout all stages, suggesting their essential role in parasitoid growth. Correlation analysis further indicated that Discussion: This study presented the first comprehensive metabolomic atlas of

Indexed as

fatty acidgrowth periodsmetabolitesmulti-omicsparasitic wasps

Identifiers

PMID40843203
PMCPMC12364644

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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.