Evidence map›Paper›PMID 33879267›Full record

ArticleJournal of animal science and biotechnology2021

Impact of sugar beet pulp and wheat bran on serum biochemical profile, inflammatory responses and gut microbiota in sows during late gestation and lactation.

Qinghui Shang, Sujie Liu, Hansuo Liu, Shad Mahfuz, Xiangshu Piao

Open access · goldAbstract read
In one paragraph

Article in Journal of animal science and biotechnology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
50citing papers in PubMed, 1 pooled it
3.8field-weighted citation impact, top 5% 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

50 citing papers in PubMed, 1 synthesis or guideline pooled it, 67 citations in OpenAlex.

  1. Pooled it
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  20. Effects of spent substrate of oyster mushroom (Frontiers in microbiology · 2024
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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

5 authors at 1 institution in 1 country.

Qinghui ShangState Key Laboratory of Animal Nutrition, College of Animal Science and Technology, China Agricultural University, No. 2 Yuanmingyuan West Road, Beijing, 100193, China.
Sujie LiuState Key Laboratory of Animal Nutrition, College of Animal Science and Technology, China Agricultural University, No. 2 Yuanmingyuan West Road, Beijing, 100193, China.
Hansuo LiuState Key Laboratory of Animal Nutrition, College of Animal Science and Technology, China Agricultural University, No. 2 Yuanmingyuan West Road, Beijing, 100193, China.
Shad MahfuzState Key Laboratory of Animal Nutrition, College of Animal Science and Technology, China Agricultural University, No. 2 Yuanmingyuan West Road, Beijing, 100193, China.
Xiangshu PiaoState Key Laboratory of Animal Nutrition, College of Animal Science and Technology, China Agricultural University, No. 2 Yuanmingyuan West Road, Beijing, 100193, China. piaoxsh@cau.edu.cn.ORCID http://orcid.org/0000-0001-8191-3028
China Agricultural University · CN

Funding

Beijing Municipal Natural Science Foundation 6202019National Natural Science Foundation of China 31772612
6 · The paper itself

Abstract

backgroundSows are frequently subjected to various stresses during late gestation and lactation, which trigger inflammatory response and metabolic disorders. Dietary fiber can influence animal health by modulating gut microbiota and their by-products, with the effects depending upon the source of the dietary fiber. This study aimed to evaluate the impacts of different fiber sources on body condition, serum biochemical parameters, inflammatory responses and fecal microbiota in sows from late gestation to lactation.

methodsForty-five multiparous sows (Yorkshire × Landrace; 3-6 parity) were assigned to 1 of 3 dietary treatments from d 85 of gestation to the end of lactation (d 21 post-farrowing): a control diet (CON, a corn-soybean meal diet), a sugar beet pulp diet (SBP, 20% SBP during gestation and 10% SBP during lactation), and a wheat bran diet (WB, 30% WB during gestation and 15% WB during lactation).

resultsCompared with CON, supplementation of SBP decreased (P < 0.05) lactation BW loss, reduced (P < 0.05) serum concentration of total cholesterol, non-esterified fatty acids, interleukin-6 and tumor necrosis factor-α, and increased (P < 0.05) fecal water content on d 110 of gestation and d 21 of lactation, while supplementation of WB reduced (P < 0.05) serum concentration of total cholesterol on d 110 of gestation, increased (P < 0.05) fecal water content and decreased (P < 0.05) serum interleukin-6 concentration on d 110 of gestation and d 21 of lactation. In addition, sows fed SBP had lower (P < 0.01) abundance of Clostridium_sensu_stricto_1 and Terrisporobacter than those fed CON, but had greater (P < 0.05) abundance of Christensenellaceae_R-7_group and Ruminococcaceae_UCG-002 than those fed the other two diets on d 110 of gestation. On d 21 of lactation, supplementation of SBP decreased (P < 0.05) the abundance of Firmicutes and Lactobacillus, but enriched (P < 0.05) the abundance of Christensenellaceae_R-7_group, Prevotellaceae_NK3B31_group, Ruminococcaceae_UCG-002, Prevotellaceae_UCG_001 and unclassified_f__Lachnospiraceae compared with WB. Compared with CON, sows fed SBP had greater (P < 0.05) fecal concentrations of acetate, butyrate and total SCFAs during gestation and lactation, while sows fed WB only had greater (P < 0.05) fecal concentration of butyrate during lactation.

conclusionsSupplementation of dietary fiber during late gestation and lactation could improve sow metabolism and gut health, and SBP was more effective than WB.

Indexed as

Dietary fiber sourceGut microbiotaInflammatory responseSerum biochemical profileSow

Identifiers

PMID33879267
PMCPMC8059298
OpenAlexW3156614133

What OpenQuestion holds

Textmetadata
LicenceCC BY
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 OpenQuestion graph.