Assessment of antibiotic resistance and virulence in Escherichia coli strains isolated from poultry in Spain.

Colibacillosis is a disease caused by avian pathogenic Escherichia coli (APEC) isolates which results in significant morbidity and mortality in poultry, as well as in economic loses. In order to identify APEC strains in a population of 898 E. coli isolates from poultry samples collected from different avian flocks located in the Valencian Region, Spain, we analysed the most significantly related to highly-pathogenic colibacillosis virulence-associated genes (VAGs) (hlyF, iroN, iss, iutA and ompT) by multiplex real-time polymerase chain reaction (RT-PCR).

Tracking the Prevalence of Antibiotic Resistance in Within the Spanish Poultry Industry: Insights from a One Health Approach.

/: Antimicrobial resistance (AMR) in species from poultry production represents a significant public health threat due to the potential transmission of AMR through the food chain. This study aimed to examine the relative prevalence, resistance patterns, and mannitol fermentation capacity of isolates from various poultry production systems in Spain over a seven-year period (2017-2023). : A total of 215 isolates were analyzed.

Production of polyhydroxybutyrate by pure and mixed cultures of purple non-sulfur bacteria: A review.

Purple non-sulfur bacteria (PNSB), most commonly called photobacteria, are a group of photoheterotrophic bacteria well known for their ability to produce hydrogen while degrading several carbon substrates, such as organic acids and carbohydrates, as well as organic matter in wastewater and effluents from other processes, such as dark fermentation. Given that this group of photobacteria is also capable of accumulating polyhydroxybutyrate (PHB) as a storage compound, this review paper aims to present and discuss the different operational and nutritional conditions reported in the literature that favor PHB production by PNSB in order to guide the process conditions that should be used. A comparison of the accumulated PHB content among different PNSB strains on several carbon and nitrogen sources and concentrations is also outlined.

Diagnosis of undesired scenarios in hydrogen production by photo-fermentation.

This study presents the use of a machine learning method from the artificial intelligence area, such as the support vector machines, applied to the construction of data-based classification models for diagnosing undesired scenarios in the hydrogen production process by photo-fermentation, which was carried out by an immobilized photo-bacteria consortium. The diagnosis models were constructed with data obtained from simulations run with a mechanistic model of the process and assessed on both modelled and experimental batches. The results revealed a 100% diagnosis performance in those batches where light intensity was below and above an optimum operation range.

Fault diagnosis of a benchmark fermentation process: a comparative study of feature extraction and classification techniques.

This paper investigates fault diagnosis in batch processes and presents a comparative study of feature extraction and classification techniques applied to a specific biotechnological case study: the fermentation process model by Birol et al. (Comput Chem Eng 26:1553-1565, 2002), which is a benchmark for advanced batch processes monitoring, diagnosis and control. Fault diagnosis is achieved using four approaches on four different process scenarios based on the different levels of noise so as to evaluate their effects on the performance.