Genetic legacy and adaptive signatures: investigating the history, diversity, and selection signatures in Rendena cattle resilient to eighteenth century rinderpest epidemics.

BACKGROUND: Rendena is a dual-purpose cattle breed, which is primarily found in the Italian Alps and the eastern areas of the Po valley, and recognized for its longevity, fertility, disease resistance and adaptability to steep Alpine pastures. It is categorized as 'vulnerable to extinction' with only 6057 registered animals in 2022, yet no comprehensive analyses of its molecular diversity have been performed to date. The aim of this study was to analyse the origin, genetic diversity, and genomic signatures of selection in Rendena cattle using data from samples collected in 2000 and 2018, and shed light on the breed's evolution and conservation needs. RESULTS: Genetic analysis revealed that the Rendena breed shares genetic components with various Alpine and Po valley breeds, with a marked genetic proximity to the Original Braunvieh breed, reflecting historical restocking efforts across the region. The breed shows signatures of selection related to both milk and meat production, environmental adaptation and immune response, the latter being possibly the result of multiple rinderpest epidemics that swept across the Alps in the eighteenth century. An analysis of the Rendena cattle population spanning 18 years showed an increase in the mean level of inbreeding over time, which is confirmed by the mean number of runs of homozygosity per individual, which was larger in the 2018 sample. CONCLUSIONS: The Rendena breed, while sharing a common origin with Brown Swiss, has developed distinct traits that enable it to thrive in the Alpine environment and make it highly valued by local farmers. Preserving these adaptive features is essential, not only for maintaining genetic diversity and enhancing the ability of this traditional animal husbandry to adapt to changing environments, but also for guaranteeing the resilience and sustainability of both this livestock system and the livelihoods within the Rendena valley.

One-Day Molecular Detection of Salmonella and Campylobacter in Chicken Meat: A Pilot Study.

Salmonella and Campylobacter ssp. are bacterial pathogens responsible for most foodborne infections in EU countries. Poultry serves as a reservoir for these pathogens, and its important role in the meat industry makes it essential to develop a rapid detection assay able to provide results in one day. Indeed, the rapid identification of foodborne pathogens is an important instrument for the monitoring and prevention of epidemic outbreaks. To date, Salmonella and Campylobacter screening is mainly conducted through molecular methods (PCR or real-time PCR) performed after 18-24 h long enrichments. In this study, we evaluated short enrichments (0, 2, 4, and 6 h) combined with a colorimetric loop-mediated isothermal AMPlification (LAMP) or real-time PCR to detect Salmonella and Campylobacter in poultry meat contaminated at different concentration levels (101, 103, and 105 CFU/g). Our results show that real-time PCR allows the detection of Salmonella and Campylobacter, even after shorter enrichment times than prescribed by ISO references; particularly, it detected Salmonella down to 101 CFU/g since T0 and Campylobacter from 103 CFU/g since T0. Detection with LAMP was comparable to real-time PCR without the requirement of a thermal cycler and with shorter execution times. These characteristics make colorimetric LAMP a valid alternative when one-day results are needed, improving the timely identification of positive meat batches, even in the absence of specialized instrumentation.

Predictive Protein Toxicity and Its Use in Risk Assessment.

In the EU novel proteins used in food or feed are assessed for their potential toxic effects in humans and livestock animals. The discovery of clear molecular features linked to the toxicity of a protein may be an important step towards the use of predictive protein toxicity in risk assessment.

Nonlinear impairment compensation using expectation maximization for dispersion managed and unmanaged PDM 16-QAM transmission.

In this paper, we show numerically and experimentally that expectation maximization (EM) algorithm is a powerful tool in combating system impairments such as fibre nonlinearities, inphase and quadrature (I/Q) modulator imperfections and laser linewidth. The EM algorithm is an iterative algorithm that can be used to compensate for the impairments which have an imprint on a signal constellation, i.e. rotation and distortion of the constellation points. The EM is especially effective for combating non-linear phase noise (NLPN). It is because NLPN severely distorts the signal constellation and this can be tracked by the EM. The gain in the nonlinear system tolerance for the system under consideration is shown to be dependent on the transmission scenario. We show experimentally that for a dispersion managed polarization multiplexed 16-QAM system at 14 Gbaud a gain in the nonlinear system tolerance of up to 3 dB can be obtained. For, a dispersion unmanaged system this gain reduces to 0.5 dB.