Bagaza Virus in Wild Birds, Portugal, 2021.

Bagaza virus emerged in Spain in 2010 and was not reported in other countries in Europe until 2021, when the virus was detected by molecular methods in a corn bunting and several red-legged partridges in Portugal. Sequencing revealed high similarity between the 2021 strains from Portugal and the 2010 strains from Spain.

Time Series Segmentation Based on Stationarity Analysis to Improve New Samples Prediction.

A wide range of applications based on sequential data, named time series, have become increasingly popular in recent years, mainly those based on the Internet of Things (IoT). Several different machine learning algorithms exploit the patterns extracted from sequential data to support multiple tasks. However, this data can suffer from unreliable readings that can lead to low accuracy models due to the low-quality training sets available. Detecting the change point between high representative segments is an important ally to find and thread biased subsequences. By constructing a framework based on the Augmented Dickey-Fuller (ADF) test for data stationarity, two proposals to automatically segment subsequences in a time series were developed. The former proposal, called Change Detector segmentation, relies on change detection methods of data stream mining. The latter, called ADF-based segmentation, is constructed on a new change detector derived from the ADF test only. Experiments over real-file IoT databases and benchmarks showed the improvement provided by our proposals for prediction tasks with traditional Autoregressive integrated moving average (ARIMA) and Deep Learning (Long short-term memory and Temporal Convolutional Networks) methods. Results obtained by the Long short-term memory predictive model reduced the relative prediction error from 1 to 0.67, compared to time series without segmentation.

Connectivity at the human-wildlife interface: starling movements relate to carriage of E. coli.

Synanthropic bird species in human, poultry or livestock environments can increase the spread of pathogens and antibiotic-resistant bacteria between wild and domestic animals. We present the first telemetry-based spatial networks for a small songbird. We quantified landscape connectivity exerted by spotless starling movements, and aimed to determine if connectivity patterns were related to carriage of potential pathogens. We captured 28 starlings on a partridge farm in 2020 and tested them for Avian influenza virus, West Nile virus WNV, Avian orthoavulavirus 1, Coronavirus, Salmonella spp. and Escherichia coli. We did not detect any viruses or Salmonella, but one individual had antibodies against WNV or cross-reacting Flaviviruses. We found E. coli in 61 % (17 of 28) of starlings, 76 % (13 of 17) of which were resistant to gentamicin, 12 % (2 of 17) to cefotaxime/enrofloxacin and 6 % (1 of 17) were phenotypic extended spectrum beta-lactamase (ESBL) carriers. We GPS-tracked 17 starlings and constructed spatial networks showing how their movements (i.e. links) connect different farms with nearby urban and natural habitats (i.e. nodes with different attributes). Using E. coli carriage as a proxy for acquisition/dispersal of bacteria, we found differences across spatial networks constructed for E. coli positive (n = 7) and E. coli negative (n = 9) starlings. We used Exponential Random Graph Models to reveal significant differences between networks. In particular, an urban roost was more connected to other sites by movements of E. coli positive than by movements of E. coli negative starlings. Furthermore, an open pine forest used mainly for roosting was more connected to other sites by movements of E. coli negative than by movements of E. coli positive starlings. Using E. coli as a proxy for a potential pathogen carried by starlings, we reveal the pathways of spread that starlings could provide between farms, urban and natural habitats.

Seasonal changes in bird communities on poultry farms and house sparrow-wild bird contacts revealed by camera trapping.

Introduction: Wild birds are considered reservoirs of poultry pathogens although transmission routes have not been conclusively established. Here we use camera trapping to study wild bird communities on commercial layer and red-legged partridge farms over a one-year timeframe. We also analyze direct and indirect interactions of other bird species with the house sparrow (Passer domesticus), a potential bridge host. Methods: We conducted camera trapping events between January 2018 and October 2019, in two caged layer farms, one free-range layer farm, and two red-legged partridge farms in South-Central Spain. Results and Discussion: We observed wild bird visits on all types of farms, with the significantly highest occurrence on red-legged partridge farms where food and water are more easily accessible, followed by commercial caged layer farms, and free-range chicken farms. The house sparrow (Passer domesticus) followed by spotless starlings (Sturnus unicolor) was the most encountered species on all farms, with the highest frequency in caged layer farms. On partridge farms, the house sparrow accounted for 58% of the wild bird detections, while on the free-range chicken farm, it made up 11% of the detections. Notably, the breeding season, when food and water are scarce in Mediterranean climates, saw the highest number of wild bird visits to the farms. Our findings confirm that the house sparrow, is in direct and indirect contact with layers and red-legged partridges and other wild birds independent of the type of farm. Contacts between house sparrows and other bird species were most frequent during the breeding season followed by the spring migration period. The species most frequently involved in interactions with the house sparrow belonged to the order Passeriformes. The study provides a comparative description of the composition and seasonal variations of bird communities in different types of layer/ poultry farms in Southern Spain i.e. a Mediterranean climate. It confirms the effectiveness of biosecurity measures that restrict access to feed and water. Additionally, it underscores the importance of synanthropic species, particularly the house sparrow, as potential bridge vector of avian pathogens.

Detection and genetic characterization of blaESBL-carrying plasmids of cloacal Escherichia coli isolates from white stork nestlings (Ciconia ciconia) in Spain.

OBJECTIVES: This study aimed to characterize Escherichia coli isolates from cloacal samples of white stork nestlings, with a special focus on extended-spectrum ß-lactamases (ESBLs)-producing E. coli isolates and their plasmid content. METHODS: Cloacal samples of 88 animals were seeded on MacConkey-agar and chromogenic-ESBL plates to recover E. coli and ESBL-producing E. coli. Antimicrobial susceptibility was screened using the disc diffusion method, and the genotypic characterization was performed by polymerase chain reaction (PCR) and subsequent sequencing. S1 nuclease Pulsed-Field-Gel-Electrophoresis (PFGE), Southern blotting, and conjugation essays were performed on ESBL-producing E. coli, as well as whole-genome sequencing by short- and long-reads. The four blaESBL-carrying plasmids were completely sequenced. RESULTS: A total of 113 non-ESBL-producing E. coli isolates were collected on antibiotic-free MacConkey-agar, of which 27 (23.9%) showed a multidrug-resistance (MDR) phenotype, mainly associated with ß-lactam-phenicol-sulfonamide resistance (blaTEM/cmlA/floR/sul1/sul2/sul3). Moreover, four white stork nestlings carried ESBL-producing E. coli (4.5%) with the following characteristics: blaSHV-12/ST38-D, blaSHV-12/ST58-B1, blaCTX-M-1/ST162-B1, and blaCTX-M-32/ST155-B1. Whole-genome sequencing followed by Southern blot hybridizations on S1-PFGE gels in ESBL-positive isolates proved that the blaCTX-M-1 gene and one of the blaSHV-12 genes were carried by IncI1/pST3 plasmids, while the second blaSHV-12 gene and the blaCTX-M-32 gene were located on IncF plasmids. The two blaSHV-12 genes and the two blaCTX-M genes had similar but non-identical close genetic environments, as all four genes were flanked by a variety of insertion sequences. CONCLUSION: The role played by several genetic platforms in the mobility of ESBL genes allows for interchangeability on a remarkably small scale (gene-plasmid-clones), which may support the spread of ESBL genes.

Bagaza virus and Plasmodium spp. coinfection in red-legged partridges (Alectoris rufa), in Southern Spain 2019.

Flaviviruses such as West Nile (WNV), Usutu (USUV) and Bagaza (BAGV) virus and avian malaria parasites are vector borne pathogens that circulate naturally between avian and mosquito hosts. WNV and USUV and potentially also BAGV constitute zoonoses. Temporal and spatial cocirculation and coinfection with Plasmodium spp., and West Nile virus has been documented in birds and mosquito vectors, and fatally USUV-infected passerines coinfected with Plasmodium spp. had more severe lesions. Also, WNV, USUV and BAGV have been found to cocirculate. Yet little is known about the interaction of BAGV and malaria parasites during consecutive or coinfections of avian hosts. Here we report mortality of free-living red-legged partridges in a hunting estate in Southern Spain that were coinfected with BAGV and Plasmodium spp. The outbreak occurred in the area where BAGV first emerged in Europe in 2010 and where cocirculation of BAGV, USUV and WNV was confirmed in 2011 and 2013. Partridges were found dead in early October 2019. Birds had mottled locally pale pectoral muscles, enlarged, congestive greenish-black tinged livers and enlarged kidneys. Microscopically congestion and predominantly mononuclear inflammatory infiltrates were evident and Plasmodium phanerozoites were present in the liver, spleen, kidneys, muscle and skin. Molecular testing and sequencing detected Plasmodium spp. and BAGV in different tissues of the partridges, and immunohistochemistry confirmed the presence and colocalization of both pathogens in the liver and spleen. Due to the importance of the red-legged partridge in the ecosystem of the Iberian Peninsula and as driver of regional economy such mortalities are of concern. Such outbreaks may reflect climate change related shifts in host, vector and pathogen ecology and interactions that could emerge similarly for other pathogens.

PSIONplusm Server for Accurate Multi-Label Prediction of Ion Channels and Their Types.

Computational prediction of ion channels facilitates the identification of putative ion channels from protein sequences. Several predictors of ion channels and their types were developed in the last quindecennial. While they offer reasonably accurate predictions, they also suffer a few shortcomings including lack of availability, parallel prediction mode, single-label prediction (inability to predict multiple channel subtypes), and incomplete scope (inability to predict subtypes of the voltage-gated channels). We developed a first-of-its-kind PSIONplusm method that performs sequential multi-label prediction of ion channels and their subtypes for both voltage-gated and ligand-gated channels. PSIONplusm sequentially combines the outputs produced by three support vector machine-based models from the PSIONplus predictor and is available as a webserver. Empirical tests show that PSIONplusm outperforms current methods for the multi-label prediction of the ion channel subtypes. This includes the existing single-label methods that are available to the users, a naïve multi-label predictor that combines results produced by multiple single-label methods, and methods that make predictions based on sequence alignment and domain annotations. We also found that the current methods (including PSIONplusm) fail to accurately predict a few of the least frequently occurring ion channel subtypes. Thus, new predictors should be developed when a larger quantity of annotated ion channels will be available to train predictive models.

Distributed Selection of Continuous Features in Multilabel Classification Using Mutual Information.

Multilabel learning is a challenging task demanding scalable methods for large-scale data. Feature selection has shown to improve multilabel accuracy while defying the curse of dimensionality of high-dimensional scattered data. However, the increasing complexity of multilabel feature selection, especially on continuous features, requires new approaches to manage data effectively and efficiently in distributed computing environments. This article proposes a distributed model for mutual information (MI) adaptation on continuous features and multiple labels on Apache Spark. Two approaches are presented based on MI maximization, and minimum redundancy and maximum relevance. The former selects the subset of features that maximize the MI between the features and the labels, whereas the latter additionally minimizes the redundancy between the features. Experiments compare the distributed multilabel feature selection methods on 10 data sets and 12 metrics. Results validated through statistical analysis indicate that our methods outperform reference methods for distributed feature selection for multilabel data, while MIM also reduces the runtime in orders of magnitude.

Sonophotocatalytic oxidation of elemental sulphur on titanium dioxide.

The effect of ultrasound on the photocatalytic oxidation kinetics of elemental sulphur particles catalyzed by titanium dioxide was studied using a conductivity method to follow the reaction. The simultaneous use of photocatalyst and ultrasound have a positive effect on the reaction. The zero-order oxidation rate constant of sulphur, reached after an activation period of approximately 150 min, was about 20 times higher when the reactor was sonicated, using an ultrasonic processor of 30 kHz, compared to the rate found in its absence. Finally, when the amount of sulphur is changed in the reactor, saturation kinetics seems to be the most appropriate model to describe the oxidation process in the presence of ultrasound and, in the other hand, when titanium dioxide was increased, a maximum rate was achieved when 0.56 g/L TiO2 were used.

Speeding-Up Association Rule Mining With Inverted Index Compression.

The growing interest in data storage has made the data size to be exponentially increased, hampering the process of knowledge discovery from these large volumes of high-dimensional and heterogeneous data. In recent years, many efficient algorithms for mining data associations have been proposed, facing up time and main memory requirements. Nevertheless, this mining process could still become hard when the number of items and records is extremely high. In this paper, the goal is not to propose new efficient algorithms but a new data structure that could be used by a variety of existing algorithms without modifying its original schema. Thus, our aim is to speed up the association rule mining process regardless the algorithm used to this end, enabling the performance of efficient implementations to be enhanced. The structure simplifies, reorganizes, and speeds up the data access by sorting data by means of a shuffling strategy based on the hamming distance, which achieve similar values to be closer, and considering both an inverted index mapping and a run length encoding compression. In the experimental study, we explore the bounds of the algorithms' performance by using a wide number of data sets that comprise either thousands or millions of both items and records. The results demonstrate the utility of the proposed data structure in enhancing the algorithms' runtime orders of magnitude, and substantially reducing both the auxiliary and the main memory requirements.

Antigenic properties of phage displayed peptides comprising disulfide-bonded loop of the immunodominant region of HIV-1 gp41.

The HIV-1 envelope glycoprotein gp41 contains Cys(X)5Cys motif, which has been shown to elicit a strong antibody response in almost all HIV-1 infected individuals. This disulfide-bonded loop region is conserved in most retroviruses suggesting the existence of an essential function in virus life cycle. In this study, we displayed the peptides comprising 12 amino acids of the immunodominant loop of gp41 on the surface of M13 phage as N-terminal fusions to the minor coat protein pIII and major coat protein pVIII of the phage and demonstrated that cysteine loop containing peptide expressed on phage recognized 62 out of 63 (98.4%) HIV-1 positive samples but not control negative sera while phage bearing linear peptides detected 4-30% of HIV-1-positive sera. The main advantage of phage-based ELISA or other antibody detection-based diagnostic tests of HIV-infection to be used for massive screening in developing countries is the reproducible, simple, rapid and low-cost production of recombinant antigens.

Weighted data gravitation classification for standard and imbalanced data.

Gravitation is a fundamental interaction whose concept and effects applied to data classification become a novel data classification technique. The simple principle of data gravitation classification (DGC) is to classify data samples by comparing the gravitation between different classes. However, the calculation of gravitation is not a trivial problem due to the different relevance of data attributes for distance computation, the presence of noisy or irrelevant attributes, and the class imbalance problem. This paper presents a gravitation-based classification algorithm which improves previous gravitation models and overcomes some of their issues. The proposed algorithm, called DGC+, employs a matrix of weights to describe the importance of each attribute in the classification of each class, which is used to weight the distance between data samples. It improves the classification performance by considering both global and local data information, especially in decision boundaries. The proposal is evaluated and compared to other well-known instance-based classification techniques, on 35 standard and 44 imbalanced data sets. The results obtained from these experiments show the great performance of the proposed gravitation model, and they are validated using several nonparametric statistical tests.