Evidence map›Paper›PMID 32349376›Full record

ArticleAnimals : an open access journal from MDPI2020

Milk Metabolomics Reveals Potential Biomarkers for Early Prediction of Pregnancy in Buffaloes Having Undergone Artificial Insemination.

Donato de Nicola, Francesco Vinale, Angela Salzano, Giada d'Errico, Anastasia Vassetti, Nunzia D'Onofrio, Maria Luisa Balestrieri, Gianluca Neglia

Open access · goldAbstract read
In one paragraph

Article in Animals : an open access journal from MDPI, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.5field-weighted citation impact, top 18% 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

5 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. 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 at 4 institutions in 1 country.

Donato de NicolaDepartment of Veterinary Medicine and Animal Production, University of Naples "Federico II", 80137 Naples, Italy.
Francesco VinaleDepartment of Veterinary Medicine and Animal Production, University of Naples "Federico II", 80137 Naples, Italy.
Angela SalzanoDepartment of Veterinary Medicine and Animal Production, University of Naples "Federico II", 80137 Naples, Italy.
Giada d'ErricoDepartment of Agricultural Sciences, University of Naples "Federico II", 80055 Portici (NA), Italy.
Anastasia VassettiDepartment of Agricultural Sciences, University of Naples "Federico II", 80055 Portici (NA), Italy.
Nunzia D'OnofrioDepartment of Precision Medicine, University of Campania Luigi Vanvitelli, 80138 Naples, Italy.
Maria Luisa BalestrieriDepartment of Precision Medicine, University of Campania Luigi Vanvitelli, 80138 Naples, Italy.
Gianluca NegliaDepartment of Veterinary Medicine and Animal Production, University of Naples "Federico II", 80137 Naples, Italy.
University of Naples Federico II · ITFederico II University Hospital · ITUniversity of Campania "Luigi Vanvitelli" · ITInstitute for Sustainable Plant Protection · IT

Funding

Ministero dell'Istruzione, dell'Università e della Ricerca Linfa 03PE_00026_1Ministero dell'Istruzione, dell'Università e della Ricerca Marea 03PE_00106Regione Campania STRABUF -B68H19005200009Università degli Studi della Campania Luigi Vanvitelli VALERE 2019 Program
6 · The paper itself

Abstract

This study aimed to identify potential biomarkers for early pregnancy diagnosis in buffaloes subjected to artificial insemination (AI). The study was carried out on 10 pregnant and 10 non-pregnant buffaloes that were synchronized by Ovsynch-Timed Artificial Insemination Program and have undergone the first AI. Furthermore, milk samples were individually collected ten days before AI (the start of the synchronization treatment), on the day of AI, day 7 and 18 after AI, and were analyzed by LC-MS. Statistical analysis was carried out by using Mass Profile Professional (Agilent Technologies, Santa Clara, CA, USA). Metabolomic analysis revealed the presence of several metabolites differentially expressed between pregnant and non-pregnant buffaloes. Among these, a total of five metabolites were identified by comparison with an online database and a standard compound as acetylcarnitine (3-Acetoxy-4-(trimethylammonio)butanoate), arginine-succinic acid hydrate, 5'-O-{[3-({4-[(3aminopropyl)amino]butyl}amino)propyl]carbamoyl}-2'-deoxyadenosine, N-(1-Hydroxy-2-hexadecanyl)pentadecanamide, and N-[2,3-Bis(dodecyloxy)propyl]-L-lysinamide). Interestingly, acetylcarnitine was dominant in milk samples collected from non-pregnant buffaloes. The results obtained from milk metabolic profile and hierarchical clustering analysis revealed significant differences between pregnant and non-pregnant buffaloes, as well as in the metabolite expression. Overall, the findings indicate the potential of milk metabolomics as a powerful tool to identify biomarkers of early pregnancy in buffalo undergoing AI.

Indexed as

artificial inseminationbuffaloLC–MSmetabolomemilkN-acetyl carnitinepregnancy

Identifiers

PMID32349376
PMCPMC7277816
OpenAlexW3018834401

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.