Parasitological status of vicuñas (Vicugna vicugna) from southeastern Peru and its relationship with fiber quality.

We aim to describe the parasitic population in vicuñas from three Andean communities and its relationship with fiber quality using 115 fecal and 22 fiber samples, classified according to sex, age, body condition score, and management system. Coproparasitologic diagnostic revealed that 84.4% of animals presented at least one type of parasite egg/oocyst. Most frequent parasite egg/oocyst were Strongyle-type eggs (54.8%) and Eimeria punoensis (38.3%). Wild vicuñas had a higher prevalence of Strongyle-type eggs (91.4%) than semi-captive (38.8%) animals, and age was significative to Eimeria infection; crias had the highest frequency (100%) when compared to yearlings (84.2%) and adults (49.4%). Larvae identification revealed a strong influence of domestic animals on vicuña parasite community, presenting the first report of Bunostomum phlebotomum and Gaigeria pachyscelis in vicuñas from southeastern Peru. Females had a significantly finer diameter of fiber (13.05 ± 0.73 µm) than males (14.22 ± 1.22 µm), and infection with Eimeria spp. affected negatively fiber diameter and resistance. Our results provide data for disease surveillance and encourage further parasitological studies in vicuñas.

Genetic diversity and zoonotic potential of rotavirus A strains in the southern Andean highlands, Peru.

Interspecies transmission is an important mechanism of evolution and contributes to rotavirus A (RVA) diversity. In order to evaluate the detection frequency, genetic diversity, epidemiological characteristics and zoonotic potential of RVA strains in faecal specimens from humans and animals cohabiting in the same environment in the department of Cusco, Peru, by molecular analysis, 265 faecal specimens were obtained from alpacas, llamas, sheep and shepherd children, and tested for RVA by RT-PCR. Genotyping was performed by multiplex PCR and sequence analysis. Rotavirus A was detected in 20.3% of alpaca, 47.5% of llama, 100% of sheep and 33.3% of human samples. The most common genetic constellations were G3-P[40]-I8-E3-H6 in alpacas, G1/G3-P[8]-I1-E1-H1 in llamas, G1/G3/G35-P[1]/P[8]-I1-E1-H1 in sheep and G3-P[40]-I1/I8-E3-H1 in humans. The newly described genotypes P[40] and P[50] were identified in all host species, including humans. Genotyping showed that the majority of samples presented coinfection with two or more RVA strains. These data demonstrate the great genetic diversity of RVA in animals and humans in Cusco, Peru. Phylogenetic analysis suggested that the strains represent zoonotic transmission among the species studied. Due to the characteristics of the human and animal populations in this study (cohabitation of different host species in conditions of poor sanitation and hygiene), the occurrence of zoonoses is a real possibility.

Molecular epidemiology of coronavirus in faeces of Brazilian calves and Peruvian camelid herds.

INTRODUCTION: The enteric disorders represent a serious hazard for bovine and camelid breeding. The aim of this study was to examine the frequency of detection and molecular characteristics of enteric coronavirus (CoV) infections in cattle, alpaca, and llama herds bred in family-based farms in Brazil and Peru. METHODOLOGY: Stool samples were collected from calves from Brazil and camelids from Peru for detection and characterization of CoV by reverse transcription polymerase chain reaction (RT-PCR) and sequence analysis. RESULTS: 46.5% (47/101) samples from calves and 26.8% (70/261) from alpaca tested positive for CoV. All strains belong to lineage A1 of the Betacoronavirus genus. Phylogenetic analysis showed high identity between CoV strains detected in calves and alpacas. CONCLUSIONS: This study characterised CoV strains from dairy cattle herds in the state of Rio de Janeiro, Brazil, and indicated that this virus is spread among the state herds. The results also indicate widespread circulation of CoV among the alpacas of Cuzco, Peru.

Whole-genome characterization of a Peruvian alpaca rotavirus isolate expressing a novel VP4 genotype.

The SA44 isolate of Rotavirus A (RVA) was identified from a neonatal Peruvian alpaca presenting with diarrhea, and the full-length genome sequence of the isolate (designated RVA/Alpaca-tc/PER/SA44/2014/G3P[40]) was determined. Phylogenetic analyses showed that the isolate possessed the genotype constellation G3-P[40]-I8-R3-C3-M3-A9-N3-T3-E3-H6, which differs considerably from those of RVA strains isolated from other species of the order Artiodactyla. Overall, the genetic constellation of the SA44 strain was quite similar to those of RVA strains isolated from a bat in Asia (MSLH14 and MYAS33). Nonetheless, phylogenetic analyses of each genome segment identified a distinct combination of genes. Several sequences were closely related to corresponding gene sequences in RVA strains from other species, including human (VP1, VP2, NSP1, and NSP2), simian (VP3 and NSP5), bat (VP6 and NSP4), and equine (NSP3). The VP7 gene sequence was closely related to RVA strains from a Peruvian alpaca (K'ayra/3368-10; 99.0% nucleotide and 99.7% amino acid identity) and from humans (RCH272; 95% nucleotide and 99.0% amino acid identity). The nucleotide sequence of the VP4 gene was distantly related to other VP4 sequences and was designated as the reference strain for the new P[40] genotype. This unique genetic makeup suggests that the SA44 strain emerged from multiple reassortment events between bat-, equine-, and human-like RVA strains.

Outbreak of diarrhea among preweaning alpacas (Vicugna pacos) in the southern Peruvian highland.

INTRODUCTION: Infections, particularly diarrheal infections, are a major cause of neonatal death in South American camelids. The aim of this study was to identify the pathogens that could have caused the recent diarrhea outbreak among the alpacas in Silli, Cusco, located in the southern Peruvian highland. METHODOLOGY: Spleen, kidney, and intestine tissue along with fecal and intestinal lavage samples were obtained from 50 one- to five-week-old alpacas and analyzed for the presence of parasites, bacteria, and viruses. RESULTS: Laboratory testing of the 50 crias included in this study revealed that 80% were infected with Eimeria spp., 40% with coronavirus, 34% with E. coli, 32% with rotavirus, 22% with Clostridium spp., and 20% with Cryptosporidium spp. Of these 50 alpaca crias, 20 presented with a single infection (19 positive for Eimeria spp. and 1 positive for rotavirus). Co-infections with up to four pathogens occurred in 60% of the samples. The significance of such infections is not clear, but it is noteworthy that the animals suffering from necrotic and/or hemorrhagic enteritis presented with quadruple infections. It is likely that co-infections increase the severity of the disease. CONCLUSIONS: These data show that multiple pathogens circulate among young alpaca crias and could be associated with diarrheal disease in these animals. The findings from this study warrant the provision of subsidies for future assessment of the potential economic impact of these infections on the productivity of the Peruvian alpaca industry.

Diffusion approximation-based simulation of stochastic ion channels: which method to use?

To study the effects of stochastic ion channel fluctuations on neural dynamics, several numerical implementation methods have been proposed. Gillespie's method for Markov Chains (MC) simulation is highly accurate, yet it becomes computationally intensive in the regime of a high number of channels. Many recent works aim to speed simulation time using the Langevin-based Diffusion Approximation (DA). Under this common theoretical approach, each implementation differs in how it handles various numerical difficulties-such as bounding of state variables to [0,1]. Here we review and test a set of the most recently published DA implementations (Goldwyn et al., 2011; Linaro et al., 2011; Dangerfield et al., 2012; Orio and Soudry, 2012; Schmandt and Galán, 2012; Güler, 2013; Huang et al., 2013a), comparing all of them in a set of numerical simulations that assess numerical accuracy and computational efficiency on three different models: (1) the original Hodgkin and Huxley model, (2) a model with faster sodium channels, and (3) a multi-compartmental model inspired in granular cells. We conclude that for a low number of channels (usually below 1000 per simulated compartment) one should use MC-which is the fastest and most accurate method. For a high number of channels, we recommend using the method by Orio and Soudry (2012), possibly combined with the method by Schmandt and Galán (2012) for increased speed and slightly reduced accuracy. Consequently, MC modeling may be the best method for detailed multicompartment neuron models-in which a model neuron with many thousands of channels is segmented into many compartments with a few hundred channels.

Mathematical analysis and modeling of motion direction selectivity in the retina.

Motion detection is one of the most important and primitive computations performed by our visual system. Specifically in the retina, ganglion cells producing motion direction-selective responses have been addressed by different disciplines, such as mathematics, neurophysiology and computational modeling, since the beginnings of vision science. Although a number of studies have analyzed theoretical and mathematical considerations for such responses, a clear picture of the underlying cellular mechanisms is only recently emerging. In general, motion direction selectivity is based on a non-linear asymmetric computation inside a receptive field differentiating cell responses between preferred and null direction stimuli. To what extent can biological findings match these considerations? In this review, we outline theoretical and mathematical studies of motion direction selectivity, aiming to map the properties of the models onto the neural circuitry and synaptic connectivity found in the retina. Additionally, we review several compartmental models that have tried to fill this gap. Finally, we discuss the remaining challenges that computational models will have to tackle in order to fully understand the retinal motion direction-selective circuitry.

More stable productivity of semi natural grasslands than sown pastures in a seasonally dry climate.

In the Neotropics the predominant pathway to intensify productivity is generally thought to be to convert grasslands to sown pastures, mostly in monoculture. This article examines how above-ground net primary productivity (ANPP) in semi-natural grasslands and sown pastures in Central America respond to rainfall by: (i) assessing the relationships between ANPP and accumulated rainfall and indices of rainfall distribution, (ii) evaluating the variability of ANPP between and within seasons, and (iii) estimating the temporal stability of ANPP. We conducted sequential biomass harvests during 12 periods of 22 days and related those to rainfall. There were significant relationships between ANPP and cumulative rainfall in 22-day periods for both vegetation types and a model including a linear and quadratic term explained 74% of the variation in the data. There was also a significant correlation between ANPP and the number of rainfall events for both vegetation types. Sown pastures had higher ANPP increments per unit rainfall and higher ANPP at the peak of the rainy season than semi-natural grasslands. In contrast, semi-natural grasslands showed higher ANPP early in the dry season. The temporal stability of ANPP was higher in semi-natural grasslands than in the sown pastures in the dry season and over a whole annual cycle. Our results reveal that, contrary to conventional thinking amongst pasture scientists, there appears to be no increase in ANPP arising from replacing semi-natural grasslands with sown pastures under prevailing pasture management practices in seasonally dry climates, while the temporal distribution of ANPP is more even in semi-natural grasslands. Neither sown pastures nor semi-natural grasslands are productive towards the end of the dry season, indicating the potential importance of the widespread practice of retaining tree cover in pastures.