Evidence map›Paper›PMID 31795078›Full record

ArticleInternational journal of molecular sciences2019

Growth and Metabolic Response of Chinese Perch to Different Dietary Protein-to-Energy Ratios in Artificial Diets.

Muhammad Shoaib Alam, Xu-Fang Liang, Liwei Liu, Shan He, Yulan Kuang, Seyed Hossein Hoseinifar, Farman Ullah Dawar

Open access · goldAbstract read
In one paragraph

Article in International journal of molecular sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
3.0field-weighted citation impact, top 9% of its field
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

8 citing papers in PubMed, 29 citations in OpenAlex.

  1. Article
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  4. Article
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  7. Article
  8. The Digestive Function ofAnimals : an open access journal from MDPI · 2021
    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

7 authors at 3 institutions in 3 countries.

Muhammad Shoaib AlamCollege of Fisheries, Chinese Perch Research Center, Huazhong Agricultural University, Wuhan 430070, China.ORCID 0000-0001-7443-7027
Xu-Fang LiangCollege of Fisheries, Chinese Perch Research Center, Huazhong Agricultural University, Wuhan 430070, China.
Liwei LiuCollege of Fisheries, Chinese Perch Research Center, Huazhong Agricultural University, Wuhan 430070, China.
Shan HeCollege of Fisheries, Chinese Perch Research Center, Huazhong Agricultural University, Wuhan 430070, China.
Yulan KuangCollege of Fisheries, Chinese Perch Research Center, Huazhong Agricultural University, Wuhan 430070, China.
Seyed Hossein HoseinifarDepartment of Fisheries, Faculty of Fisheries and Environmental Sciences, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, 4918943464, Iran.
Farman Ullah DawarDepartment of Zoology, Kohat University of Science and Technology (KUST), Kohat, Khyber Pakhtunkhwa 26000, Pakistan.
Huazhong Agricultural University · CNGorgan University of Agricultural Sciences and Natural Resources · IRKohat University of Science and Technology · PK

Funding

Agriculture Research System of China CARS-46National Natural Science Foundation of China 31772822 and 31602131
6 · The paper itself

Abstract

The effect of dietary nutrients on novel farm species has always garnered wide research and economic interest. Chinese perch, an economically important carnivorous fish, accepts an artificial diet after taming, so it is essential to evaluate and optimize the nutritional and metabolic demands of this species. However, little is known about the effect of an artificial diet on the growth and metabolism of Chinese perch. Therefore, the present study evaluated the growth and metabolic responses of Chinese perch to experimental diets with different dietary protein/energy (P/E) ratios. Five isoenergetic diets (18 kJ/g) with graded levels of P/E ratios of 30.58, 33.22, 35.90, 38.6, and 41.35 mg/kJ (named A, B, C, D, and E) were formulated. A total of 225 Chinese perch (64.89 ± 0.28 g) were divided into five groups (triplicate tanks for each group), distributed into 15 (350 L) fiberglass tanks, and fed twice a day at 4% of fish wet body weight with the respective P/E ratio diets for 10 weeks. Compared with the other groups, Chinese perch in Group C showed significantly improved growth performance, weight gain (WG), specific growth rate (SGR), viscerosomatic index (VSI), hepatosomatic index (HSI), intraperitoneal fat (IPF), feed utilization, feed intake (FI), feed conversion ratio (FCR), protein efficiency ratio (PER), protein retention efficiency (PRE), energy retention efficiency (ERE), and feed efficiency (FE) as well as whole-body, muscle, and liver composition. Chinese perch in Group A, on the other hand, had the lowest growth performance, feed utilization, and body composition compared with the other groups. The activities of nitrogen metabolism-related enzymes (alanine aminotransferase (ALT), aspartate aminotransferase (AST) glutamate dehydrogenase (GDH), and adenosine 5'-monophosphate deaminase (AMPD)) as well as the mRNA expression of the

Indexed as

Body CompositionDietEnergy MetabolismAlanine TransaminaseAMP-Activated Protein Kinase KinasesAMP DeaminaseAnimal Nutritional Physiological PhenomenaAnimalsAspartate AminotransferasesDietary ProteinsFisheriesFish ProteinsGlutamate DehydrogenasePerchesPro-OpiomelanocortinProtein KinasesAlanine TransaminaseAMP-Activated Protein Kinase KinasesAMP DeaminaseAspartate AminotransferasesDietary ProteinsFish ProteinsGlutamate DehydrogenasePro-OpiomelanocortinProtein KinasesTOR Serine-Threonine KinasesAMPKbody compositionChinese perchenergy homeostasisgrowth and metabolismmTOR pathwaysnitrogen metabolismprotein/energy ratioprotein synthesis

Identifiers

PMID31795078
PMCPMC6928951
OpenAlexW2990835903

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.