The potential of herbal extracts containing bioactive compounds to strengthen immunity could contribute to reducing antimicrobial use in poultry. This study aimed at developing a reliable and robust methodological pipeline to assess the ability of herbal extracts to strengthen chicken innate defenses, especially concerning inflammation and oxidative stress. This methodology was applied to L. (MEL) extract, recognized for its biological activities including antioxidant and anti-inflammatory properties. Different methods were used to (1). guarantee the quality of MEL extract and its capacity to stimulate the innate immune system; (2). evaluate the relevance of an model to mimic inflammatory and oxidative stress challenges to replace LPS injection in chickens; (3). analyse the effects of feed supplemented with MEL extract on inflammation and oxidative stress induced ; (4). assess the effects of MEL extract on the redox balance, health, welfare and performance in broilers exposed to suboptimal starting conditions through a large-scale approach. The quality of MEL extract preparations, through phytochemical quantification of rosmarinic acid (RA), revealed varying concentrations of RA in the different MEL extracts. RA concentrations remained stable for at least 9 months and in feed three months after incorporating MEL extract. When incubated with chicken cell lines MEL extract showed potential metabolic activation and ability to stimulate immune functions but induced cytotoxicity at high concentrations. The original model of inflammation developed on chicken blood cells enabled inflammation and oxidative stress biomarkers to be expressed and revealed antioxidative and anti-inflammatory properties of blood cells from chickens fed MEL extract. The experimental model of chicken suboptimal starting conditions validated beneficial effects of MEL extract on the redox balance and also evidenced improved performance during the growth phase, a tendency for fewer muscle defects but a higher severity of pododermatitis lesions without affecting other welfare indicators. This study grouped methods and tools that could be combined according to the plant extract, the needs of professionals working in poultry production systems and staff responsible for animal health, welfare and feeding.
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http://dx.doi.org/10.3389/fvets.2021.759456 | DOI Listing |
Ann N Y Acad Sci
January 2025
Hainan Institute, Zhejiang University, Sanya, China.
In this paper, we introduce FUSION-ANN, a novel artificial neural network (ANN) designed for acoustic emission (AE) signal classification. FUSION-ANN comprises four distinct ANN branches, each housing an independent multilayer perceptron. We extract denoised features of speech recognition such as linear predictive coding, Mel-frequency cepstral coefficient, and gammatone cepstral coefficient to represent AE signals.
View Article and Find Full Text PDFNat Commun
January 2025
Lands of the O'odham and Yaqui peoples, Native Nations Institute, Udall Center for Studies in Public Policy, University of Arizona, Tucson, AZ, USA.
In the age of big data and open science, what processes are needed to follow open science protocols while upholding Indigenous Peoples' rights? The Earth Data Relations Working Group (EDRWG), convened to address this question and envision a research landscape that acknowledges the legacy of extractive practices and embraces new norms across Earth science institutions and open science research. Using the National Ecological Observatory Network (NEON) as an example, the EDRWG recommends actions, applicable across all phases of the data lifecycle, that recognize the sovereign rights of Indigenous Peoples and support better research across all Earth Sciences.
View Article and Find Full Text PDFJ Voice
January 2025
Department of Electrical-Electronics Engineering, Erciyes University, Kayseri, Turkey. Electronic address:
Early diagnosis and referral are crucial in the treatment of voice disorders. Contemporary investigations have indicated the efficacy of voice pathology detection systems in significantly contributing to the evaluation of voice disorders, facilitating early diagnosis of such pathologies. These systems leverage machine learning methodologies, widely applied across diverse domains, and exhibit particular potential in the realm of voice pathology classification.
View Article and Find Full Text PDFFront Physiol
December 2024
Department of Nephrology, People's Hospital of Zhengzhou University, Zhengzhou, China.
The assessment of vascular accessibility in patients undergoing hemodialysis is predominantly reliant on manual inspection, a method that is associated with several limitations. In this study, we propose an alternative approach by recording the acoustic signals produced by the arteriovenous fistula (AVF) and employing deep learning techniques to analyze these sounds as an objective complement to traditional AVF evaluation methods. Auscultation sounds were collected from 800 patients, with each recording lasting between 24 and 30 s.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Faculty of Medicine and Health Technology, Tampere University, 33720 Tampere, Finland.
Extracting behavioral information from animal sounds has long been a focus of research in bioacoustics, as sound-derived data are crucial for understanding animal behavior and environmental interactions. Traditional methods, which involve manual review of extensive recordings, pose significant challenges. This study proposes an automated system for detecting and classifying animal vocalizations, enhancing efficiency in behavior analysis.
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