Evidence map›Paper›PMID 39729016›Full record

ArticleVeterinary sciences2024

Subclinical Mastitis in Lacaune Sheep: Etiologic Agents, the Effect on Milk Characteristics, and an Evaluation of Infrared Thermography and the YOLO Algorithm as a Preprocessing Tool for Advanced Analysis.

Marios Lysitsas, Georgios Botsoglou, Dimitris Dimitriadis, Sofia Termatzidou, Panagiota Kazana, Grigorios Tsoumakas, Constantina N Tsokana, Eleni Malissiova, Vassiliki Spyrou, Charalambos Billinis and 1 more

Abstract read
In one paragraph

Article in Veterinary sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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

11 authors.

Marios LysitsasFaculty of Veterinary Science, University of Thessaly, 43100 Karditsa, Greece.ORCID 0009-0007-0648-6004
Georgios BotsoglouSchool of Informatics, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece.
Dimitris DimitriadisSchool of Informatics, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece.ORCID 0000-0002-9404-0331
Sofia TermatzidouDepartment of Animal Science, University of Thessaly, 41334 Larissa, Greece.ORCID 0009-0003-5061-7957
Panagiota KazanaDepartment of Agriculture, University of Ioannina, 47100 Arta, Greece.
Grigorios TsoumakasSchool of Informatics, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece.ORCID 0000-0002-7879-669X
Constantina N TsokanaSchool of Veterinary Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece.ORCID 0000-0003-4180-6310
Eleni MalissiovaDepartment of Animal Science, University of Thessaly, 41334 Larissa, Greece.ORCID 0000-0001-8956-2269
Vassiliki SpyrouDepartment of Animal Science, University of Thessaly, 41334 Larissa, Greece.
Charalambos BillinisFaculty of Veterinary Science, University of Thessaly, 43100 Karditsa, Greece.ORCID 0000-0002-2209-9772
George ValiakosFaculty of Veterinary Science, University of Thessaly, 43100 Karditsa, Greece.ORCID 0000-0002-3869-5026

Funding

Greece and the European Union M16SYN2-00202
6 · The paper itself

Abstract

This study aimed to investigate the incidence of subclinical mastitis (SCM), the implicated pathogens, and their impact on milk quality in dairy sheep in Greece. Furthermore, we preliminarily evaluated infrared thermography and the application of AI tools for the early, non-invasive diagnosis of relevant cases. In total, 660 milk samples and over 2000 infrared thermography images were obtained from 330 phenotypically healthy ewes. Microbiological investigations, a somatic cell count (SCC), and milk chemical analyses were performed. Infrared images were analyzed using the FLIR Research Studio software (version 3.0.1). The You Only Look Once version 8 (YOLOv8) algorithm was employed for the automatic detection of the udder's region of interest. A total of 157 mammary glands with SCM were identified in 122/330 ewes (37.0%). The most prevalent pathogen was staphylococci (136/160, 86.6%). Considerable resistance was detected to tetracycline (29.7%), ampicillin (28.6%), and sulfamethoxazole-trimethoprim (23.6%). SCM correlated with high total mesophilic count (TMC) values and decreased milk fat, lactose, and protein content. A statistically significant variation (

Indexed as

antimicrobial resistancecoagulase-negativeinfrared thermographyLacaunesomatic cell countstaphylococcisubclinical mastitisthermal imagesYOLO algorithm

Identifiers

PMID39729016
PMCPMC11680135

What Socratic 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 Socratic graph.