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Abstract: The agricultural economy heavily relies on poultry production, making accurate forecasting of poultry data crucial for optimizing revenue, streamlining resource utilization, and maximizing productivity. This research introduces a novel application of the N-BEATS architecture for multi-dimensional poultry data forecasting with enhanced interpretability through an integrated Explainable AI (XAI) framework. Leveraging its advanced capabilities in time series modeling, N-BEATS is applied to predict multiple facets of poultry disease diagnostics using a multivariate dataset comprising key environmental parameters. The methodology empowers decision-making in poultry farm management by providing transparent and interpretable forecasts. Experimental results demonstrate that N-BEATS outperforms conventional deep learning models, including LSTM, GRU, RNN, and CNN, across various error metrics, achieving MAE of 0.172, RMSE of 0.313, MSLE of 0.042, R-squared of 0.034, and RMSLE of 0.204. The positive R-squared value indicates the model’s robustness against underfitting and overfitting, surpassing the performance of other models with negative R-squared values. This study establishes N-BEATS as a superior and interpretable solution for complex, multi-dimensional forecasting challenges in poultry production, with significant implications for enhancing predictive analytics in agriculture.
Keywords: poultry, livestock, forecasting, epidemiology, humidity, veterinary diseases, polynomials
Published in DiRROS: 09.09.2025; Views: 227; Downloads: 86
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Abstract: Extended-spectrum beta-lactamase (ESBL)-producing Escherichia coli is a critical antimicrobial-resistant pathogen. While well-studied in humans and animals, its presence in the environment remains underexplored. This study analyses the genotypes and plasmid composition of ESBL-producing E. coli from human and environmental sources in Northeastern Slovenia. Freshwater and sediment samples were collected bimonthly during one year at ten sites, including rivers, lakes, and wastewater treatment plant (WWTP) influents. Human isolates were collected during the same period and geographic area. Whole-genome sequencing and bioinformatic analyses were conducted to evaluate genetic relatedness, antimicrobial resistance genes, and plasmid composition. Among 414 sequenced isolates (230 human, 184 environmental), 108 multilocus sequence types (MLST-ST) were identified, with 20 STs shared between sources. Core-genome MLST (cgMLST) revealed 59 clonal clusters, six of which included both human and environmental isolates. The dominant ESBL gene was blaCTX−M-15 (59 % of all ESBL isolates), and 54 % of all ESBL isolates carried ESBL genes on plasmids. Plasmid cluster AA474, found across different sources, STs, and locations, was linked to multiple ESBL genes, suggesting a key role in resistance dissemination. Despite shared STs, ESBL genes, and plasmids between humans and the environment, cgMLST analysis indicated limited clonal spread. This suggest that transmission between humans and the environment remains restricted and is more often linked to spread of plasmids than of strains.
Keywords: one health, environment, water, sediment, epidemiology, plasmids, ST1193
Published in DiRROS: 27.06.2025; Views: 394; Downloads: 343
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Abstract: In the beginning of 2020, the outbreak of the COVID-19 pandemic led to a crisis in which diagnostic methods for the genome detection of SARS-CoV-2 were urgently needed. Based on the very early publication of the basic principles for a diagnostic test for the genome detection of SARS-CoV-2, the first noncommercial laboratory-developed tests (LDTs) and commercial tests were introduced. As there was considerable uncertainty about the reliability and performance of different tests and different laboratories, INSTAND established external quality assessment (EQA) schemes for the detection of SARS-CoV-2 starting in April 2020. In close partnership in a scientific network, the EQA schemes were enhanced, especially the April, June and November 2020 terms. The enhancement included: (i) immediate provision of suitable virus including variants of concern at the beginning of the pandemic outbreak, (ii) short frequency of EQA schemes, (iii) concentration dependency of the testing and sensitivity check, achieved by using SARS-CoV-2-positive samples from a 10-fold dilution series of the same starting material, (iv) specificity check of the testing, achieved by using SARS-CoV-2-negative samples containing human coronaviruses or MERS CoV, (v) revealed samples for orientation on test performance during an ongoing or at the start of an EQA scheme using a pre-quantified SARS-CoV-2-positive EQA sample with a low viral RNA load of only 1 570 copies/mL assigned by digital PCR (dPCR) in June 2020 and (vi) quantified reference materials based on the experiences of the first two EQA schemes with dPCR-assigned values in copies/mL beginning in November 2020 for self-evaluation of the applied test system. This manuscript summarizes the results of a total of 13 EQA schemes for the detection of SARS-CoV-2 between April 2020 and June 2023 in which a total of 1 413 laboratories from 49 countries participated. The qualitative results for the detection of SARS-CoV-2-positive samples were between 95.8 % and 99.7 % correct positive, excluding extremely low concentration samples. For all SARS-CoV-2-negative EQA samples, the qualitative success rates ranged from 95.1 % to 99.4 % correct negative results. The widely varying values for the cycle threshold (Ct)/crossing point (Cq) reported for the different target genes and test systems were striking. A few laboratories reported quantitative results in copies/mL for several VOCs with an acceptable rate of over 93 % correct positive results in the majority of cases. The description of the enhanced EQA schemes for SARS-CoV-2 detection in terms of timing and scope can serve as a blueprint for the rapid development of a quality assessment of diagnostics for an emerging pathogen.
Keywords: COVID-19 pandemic, SARS-CoV-2, virus genome detection tests, reference materials, external quality assessment, laboratory medicine, epidemiology
Published in DiRROS: 18.06.2025; Views: 420; Downloads: 405
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Abstract: Abstract: In recent decades, the rapid spread of various communication media has led to changes in traditional eating habits. In the Mediterranean region, the classic (Mediterranean) dietary pattern has been lost as a result. This has led to a shift in eating habits towards unhealthy eating patterns, which in turn has resulted in an inadequate distribution of body composition. It is known that, among other things, the number of non-communicable diseases increases with the inadequate distribution of body composition. The aim of our study was to examine the level of adherence to the Mediterranean diet (MD) of older adults in the Mediterranean region in relation to specific body composition parameters. This study included 521 older adults with a mean age of 69.6 ± 6.3 years. Body composition was measured using the BIA 101 Anniversary device (Akern s.r.l., Florence, Italy) and adherence to the MD was assessed using the MEDLIFE index questionnaire. This study found significant differences in body composition between males and females. The mean adherence to the MD was 17.0 ± 3.3 points among the participants and there was higher adherence in females (p = 0.002, ηp 2 = 0.019). A multiple linear regression was performed to assess the relationship between the body composition parameters and MD. Multiple linear regression models were significant for reactance, fat mass (%), fat-free mass (%), skeletal muscle index, and total body water (%), with specific individual MEDLIFE items such as the consumption of processed meat, meat, white meat, fruit, vegetables, olive oil and limiting snacks between meals. Moreover, promising correlations were found between certain MD characteristics and BIA parameters, but the overall health effects of the MD remain unclear.
Keywords: nutrition, elderly, body composition, healthy ageing, epidemiology
Published in DiRROS: 28.10.2024; Views: 660; Downloads: 458
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Abstract: Tomato brown rugose fruit virus (ToBRFV) has recently emerged as a major disease of tomatoes and peppers. ToBRFV is a seed- and contact-transmitted virus. In Slovenia, ToBRFV RNA was detected in samples of wastewater, river, and water used to irrigate plants. Even though the source of detected RNA could not be clearly established, this raised the question of the significance of the detection of ToBRFV in water samples and experimental studies were performed to address this question. The data presented here confirm that the release of virus particles from the roots of infected plants is a source of infectious ToBRFV particles in water and that the virus can remain infective up to four weeks in water stored at room temperature, while its RNA can be detected for much longer. These data also indicate that irrigation with ToBRFV-contaminated water can lead to plant infection. In addition, it has been shown that ToBRFV circulated in drain water in commercial tomato greenhouses from other European countries and that an outbreak of ToBRFV can be detected by regular monitoring of drain water. A simple method for concentrating ToBRFV from water samples and a comparison of the sensitivity of different methods, including the determination of the highest ToBRFV dilution still capable of infecting test plants, were also investigated. The results of our studies fill the knowledge gaps in the epidemiology and diagnosis of ToBRFV, by studying the role of water-mediated transmission, and provide a reliable risk assessment to identify critical points for monitoring and control.
Keywords: tomato brown rugose fruit virus, tomato, hydroponics, water-linked epidemiology, survival
Published in DiRROS: 12.07.2024; Views: 964; Downloads: 774
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