Evidence map›Paper›PMID 39717273›Full record

ArticleFrontiers in microbiology2024

Machine learning-enhanced assessment of potential probiotics from healthy calves for the treatment of neonatal calf diarrhea.

Yuting Zhai, Miju Kim, Peixin Fan, Sharath Rajeev, Sun Ae Kim, J Danny Driver, Klibs N Galvão, Christina Boucher, Kwangcheol C Jeong

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Review
  6. Host-associatedCurrent research in food 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

9 authors.

Yuting Zhai *Department of Animal Sciences, University of Florida, Gainesville, FL, United States.
Miju Kim *Department of Animal Sciences, University of Florida, Gainesville, FL, United States.
Peixin FanDepartment of Animal Sciences, University of Florida, Gainesville, FL, United States.
Sharath RajeevEmerging Pathogens Institute, University of Florida, Gainesville, FL, United States.
Sun Ae KimDepartment of Food Science and Biotechnology, Ewha Womans University, Seoul, Republic of Korea.
J Danny DriverDepartment of Animal Sciences, University of Florida, Gainesville, FL, United States.
Klibs N GalvãoDepartment of Large Animal Clinical Sciences, University of Florida, Gainesville, FL, United States.
Christina BoucherDepartment of Computer and Information Science and Engineering, University of Florida, Gainesville, FL, United States.
Kwangcheol C JeongDepartment of Animal Sciences, University of Florida, Gainesville, FL, United States.

Funding

Developing Computational Methods for Surveillance of Antimicrobial Resistant AgentsR01AI141810 · NIAID · UNIVERSITY OF FLORIDA · PI BOUCHER, CHRISTINA, PROSPERI, MATTIA · 2019 to 2023
$2.1M
NIAID NIH HHS R01 AI141810
6 · The paper itself

Abstract

Neonatal calf diarrhea (NCD) remains a significant contributor to calf mortality within the first 3 weeks of life, prompting widespread antibiotic use with associated concerns about antimicrobial resistance and disruption of the calf gut microbiota. Recent research exploring NCD treatments targeting gut microbiota dysbiosis has highlighted probiotic supplementation as a promising and safe strategy for gut homeostasis. However, varying treatment outcomes across studies suggest the need for efficient treatment options. In this study, we evaluated the potential of probiotics

Indexed as

gut microbiomehost specificitymachine learningneonatal calf diarrheaprobiotics

Identifiers

PMID39717273
PMCPMC11663915

What OpenQuestion holds

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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.