Experimental bio-artificial liver: Importance of the architectural design on ammonia detoxification performance

AIM To determine the influence of the construction design over the biological component's performance in an experimental bio-artificial liver (BAL) device. METHODS Two BAL models for liver microorgans (LMOs) were constructed. First, we constructed a cylindrical BAL and tested it without the biological component to establish its correct functioning. Samples of blood and biological compartment (BC) fluid were taken after 0, 60, and 120 min of perfusion. Osmolality, hematocrit, ammonia and glucose concentrations, lactate dehydrogenase (LDH) release (as a LMO viability parameter), and oxygen consumption and ammonia metabolizing capacity (as LMO functionality parameters) were determined. CPSI and OTC gene expression and function were measured. The second BAL, a "flat bottom" model, was constructed using a 25 cm2 culture flask while maintaining all other components between the models. The BC of both BALs had the same capacity (approximately 50 cm3) and both were manipulated with the same perfusion system. The performances of the two BALs were compared to show the influence of architecture. RESULTS The cylindrical BAL showed a good exchange of fluids and metabolites between blood and the BC, reflected by the matching of osmolalities, and glucose and ammonia concentration ratios after 120 min of perfusion. No hemoconcentration was detected, the hematocrit levels remained stable during the whole study, and the minimal percentage of hemolysis (0.65% ± 0.10%) observed was due to the action of the peristaltic pump. When LMOs were used as biological component of this BAL they showed similar values to the ones obtained in a Normothermic Reoxygenation System (NRS) for almost all the parameters assayed. After 120 min, the results obtained were: LDH release (%): 14.7 ± 3.1 in the BAL and 15.5 ± 3.2 in the NRS (n = 6); oxygen consumption (μmol/min·g wet tissue): 1.16 ± 0.21 in the BAL and 0.84 ± 0.15 in the NRS (n = 6); relative expression of Cps1 and Otc: 0.63 ± 0.12 and 0.67 ± 0.20, respectively, in the BAL, and 0.86 ± 0.10 and 0.82 ± 0.07, respectively, in the NRS (n = 3); enzymatic activity of CPSI and OTC (U/g wet tissue): 3.03 ± 0.86 and 222.0 ± 23.5, respectively, in the BAL, and 3.12 ± 0.73 and 228.8 ± 32.8, respectively, in the NRS (n = 3). In spite of these similarities, LMOs as a biological component of the cylindrical BAL were not able to detoxify ammonia at a significant level (not detected vs 35.1% ± 7.0% of the initial 1 mM NH4 + dose in NRS, n = 6). Therefore, we built a second BAL with an entirely different design that offers a flat base BC. When LMOs were placed in this "flat bottom" device they were able to detoxify 49.3% ± 8.8% of the initial ammonia overload after 120 min of perfusion (n = 6), with a detoxification capacity of 13.2 ± 2.2 μmol/ g wet tissue. CONCLUSION In this work, we demonstrate the importance of adapting the BAL architecture to the biological component characteristics to obtain an adequate BAL performance.Fil: Pizarro, María Dolores. Universidad Nacional del Litoral; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Mamprin, María Eugenia. Universidad Nacional de Rosario; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Daurelio, Lucas Damian. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Litoral; ArgentinaFil: Rodriguez, Joaquin Valentin. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Rosario; ArgentinaFil: Mediavilla, Maria Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Rosario; Argentin

Goat Milk Nutritional Quality Software-Automatized Individual Curve Model Fitting, Shape Parameters Calculation and Bayesian Flexibility Criteria Comparison

SPSS syntax was described to evaluate the individual performance of 49 linear and non-linear models to fit the milk component evolution curve of 159 Murciano-Granadina does selected for genotyping analyses. Peak and persistence for protein, fat, dry matter, lactose, and somatic cell counts were evaluated using 3107 controls (3.91 ± 2.01 average lactations/goat). Best-fit (adjusted R 2 ) values (0.548, 0.374, 0.429, and 0.624 for protein, fat, dry matter, and lactose content, respectively) were reached by the five-parameter logarithmic model of Ali and Schaeffer (ALISCH), and for the three-parameter model of parabolic yield-density (PARYLDENS) for somatic cell counts (0.481). Cross-validation was performed using the Minimum Mean-Square Error (MMSE). Model comparison was performed using Residual Sum of Squares (RSS), Mean-Squared Prediction Error (MSPE), adjusted R 2 and its standard deviation (SD), Akaike (AIC), corrected Akaike (AICc), and Bayesian information criteria (BIC). The adjusted R 2 SD across individuals was around 0.2 for all models. Thirty-nine models successfully fitted the individual lactation curve for all components. Parametric and computational complexity promote variability-capturing properties, while model flexibility does not significantly (p > 0.05) improve the predictive and explanatory potential. Conclusively, ALISCH and PARYLDENS can be used to study goat milk composition genetic variability as trustable evaluation models to face future challenges of the goat dairy industry

Bayesian Analysis of the Association between Casein Complex Haplotype Variants and Milk Yield, Composition, and Curve Shape Parameters in Murciano-Granadina Goats

Considering casein haplotype variants rather than SNPs may maximize the understanding of heritable mechanisms and their implication on the expression of functional traits related to milk production. Effects of casein complex haplotypes on milk yield, milk composition, and curve shape parameters were used using a Bayesian inference for ANOVA. We identified 48 single nucleotide polymorphisms (SNPs) present in the casein complex of 159 unrelated individuals of diverse ancestry, which were organized into 86 haplotypes. The Ali and Schaeffer model was chosen as the best fitting model for milk yield (Kg), protein, fat, dry matter, and lactose (%), while parabolic yield-density was chosen as the best fitting model for somatic cells count (SCC × 103 sc/mL). Peak and persistence for all traits were computed respectively. Statistically significant differences (p < 0.05) were found for milk yield and components. However, no significant difference was found for any curve shape parameter except for protein percentage peak. Those haplotypes for which higher milk yields were reported were the ones that had higher percentages for protein, fat, dry matter, and lactose, while the opposite trend was described by somatic cells counts. Conclusively, casein complex haplotypes can be considered in selection strategies for economically important traits in dairy goats

Software-Automatized Individual Lactation Model Fitting, Peak and Persistence and Bayesian Criteria Comparison for Milk Yield Genetic Studies in Murciano-Granadina Goats

SPSS model syntax was defined and used to evaluate the individual performance of 49 linear and non-linear models to fit the lactation curve of 159 Murciano-Granadina goats selected for genotyping analyses. Lactation curve shape, peak and persistence were evaluated for each model using 3107 milk yield controls with an average of 3.78 ± 2.05 lactations per goat. Best fit (Adjusted R2) values (0.47) were reached by the five-parameter logarithmic model of Ali and Schaeffer. Three main possibilities were detected: non-fitting (did not converge), standard (Adjusted R2 over 75%) and atypical curves (Adjusted R2 below 75%). All the goats fitted for 38 models. The ability to fit different possible functional forms for each goat, which progressively increased with the number of parameters comprised in each model, translated into a higher sensitivity to explaining curve shape individual variability. However, for models for which all goats fitted, only moderate increases in explanatory and predictive potential (AIC, AICc or BIC) were found. The Ali and Schaeffer model reported the best fitting results to study the genetic variability behind goat milk yield and perhaps enhance the evaluation of curve parameters as trustable future selection criteria to face the future challenges offered by the goat dairy industry

Goat Milk Nutritional Quality Software-Automatized Individual Curve Model Fitting, Shape Parameters Calculation and Bayesian Flexibility Criteria Comparison

SPSS syntax was described to evaluate the individual performance of 49 linear and non-linear models to fit the milk component evolution curve of 159 Murciano-Granadina does selected for genotyping analyses. Peak and persistence for protein, fat, dry matter, lactose, and somatic cell counts were evaluated using 3107 controls (3.91 ± 2.01 average lactations/goat). Best-fit (adjusted R2) values (0.548, 0.374, 0.429, and 0.624 for protein, fat, dry matter, and lactose content, respectively) were reached by the five-parameter logarithmic model of Ali and Schaeffer (ALISCH), and for the three-parameter model of parabolic yield-density (PARYLDENS) for somatic cell counts (0.481). Cross-validation was performed using the Minimum Mean-Square Error (MMSE). Model comparison was performed using Residual Sum of Squares (RSS), Mean-Squared Prediction Error (MSPE), adjusted R2 and its standard deviation (SD), Akaike (AIC), corrected Akaike (AICc), and Bayesian information criteria (BIC). The adjusted R2 SD across individuals was around 0.2 for all models. Thirty-nine models successfully fitted the individual lactation curve for all components. Parametric and computational complexity promote variability-capturing properties, while model flexibility does not significantly (p > 0.05) improve the predictive and explanatory potential. Conclusively, ALISCH and PARYLDENS can be used to study goat milk composition genetic variability as trustable evaluation models to face future challenges of the goat dairy industry

Does the Acknowledgement of αS1-Casein Genotype Affect the Estimation of Genetic Parameters and Prediction of Breeding Values for Milk Yield and Composition Quality-Related Traits in Murciano-Granadina?

A total of 2090 lactation records for 710 Murciano-Granadina goats were collected during the years 2005–2016 and analyzed to investigate the influence of the αS1-CN genotype on milk yield and components (protein, fat, and dry matter). Goats were genetically evaluated, including and excluding the αS1-CN genotype, in order to assess its repercussion on the efficiency of breeding models. Despite no significant differences being found for milk yield, fat and dry matter heritabilities, protein production heritability considerably increased after aS1-CN genotype was included in the breeding model (+0.23). Standard errors suggest that the consideration of genotype may improve the model’s efficiency, translating into more accurate genetic parameters and breeding values (PBV). Genetic correlations ranged from −0.15 to −0.01 between protein/dry matter and milk yield/protein and fat content, while phenotypic correlations were −0.02 for milk/protein and −0.01 for milk/fat or protein content. For males, the broadest range for reliability (RAP) (0.45–0.71) was similar to that of females (0.37–0.86) when the genotype was included. PBV ranges broadened while the maximum remained similar (0.61–0.77) for males and females (0.62–0.81) when the genotype was excluded, respectively. Including the αS1-CN genotype can increase production efficiency, milk profitability, milk yield, fat, protein and dry matter contents in Murciano-Granadina dairy breeding programs

Sexual Dimorphism for Coping Styles Complements Traditional Methods for Sex Determination in a Multivariety Endangered Hen Breed

Sex determination is key to designing endangered poultry population conservation and breeding programs when sex distribution departs from Hardy–Weinberg equilibrium. A total of 112 Utrerana chickens (28 per variety, partridge, black, white, and franciscan) were selected for hatching day sexing. Sex assignation was performed through 10 methods. Three sex assignment criteria comprised criteria found in literature, opposite criteria to that in the literature, and composite criteria combining methods reporting the highest predictive success from the previous ones. This study aims to determine which method combinations may more successfully determine sex across the four varieties of Utrerana endangered hen breed to tailor noninvasive early specific models to determine sex in local chicken populations. Although the explanatory power of the three assignation criteria is equal (75%), assignation criteria 2 resulted to be the most efficient as it correctly assigns males more frequently. Only methods 3 (English method), 5 (general down feathers coloration), 7 (wing fan), and 10 (behavior/coping styles) reported significant differences regardless of the variety, hence, are appropriate for early sexing. Sex confirmation was performed at 1.5 months old. Identifying sex proportions enhances genetic management tasks in endangered populations, complementing more standardized techniques, which may result inefficient given the implicit diversity found in local populations

Effect of three commercial extenders on sperm motility and fertility in liquid ram semen stored at 15 °C or 5 °C

The effect of different extenders on sperm motility and fertility was evaluated during liquid storage of ram semen at 5 °C and 15 °C. The semen was collected, pooled and diluted in three commercial extenders: Inra 96® (INRA) based on skimmed milk, Biladyl® A fraction (BIL) based on egg yolk, and Ovixcell® (OVIX) based on soybean lecithin. Then, sperm motility was evaluated at 0, 6, 24, 48, 72 and 96 h. In order to evaluate fertility, samples stored at 15 °C were used after dilution in INRA and OVIX. Results showed that progressive motility was significantly higher up to 72 h of storage in sperm samples maintained at 5 °C in comparison with 15 °C, similarly for each tested diluent. When samples were stored at 5 °C in OVIX, kinematic parameters such as velocity (except curvilinear velocity, VCL), trajectory [linearity (LIN), straightness (STR), wobble (WOB)], amplitude of lateral head displacement (ALH) and beat/cross frequency (BCF) were higher than in INRA and BIL. No significant differences in pregnancy rate were detected between INRA (62.6%) and OVIX (58.9%). In conclusion, liquid storage at 5 °C with OVIX extender is an interesting option since non-animal components are used, and this extender offers similar in vitro and in vivo efficacy as other extenders containing animal components

Bird diversity and conservation in the lower delta of the Paraná River, Argentina

The Delta of the Paraná River, one of the most important wetlands in South America, harbors subtropicaland temperate bird species. Although this region is key for biodiversity conservation, aspects such as speciescomposition and conservation status, and their relationship with vegetation types are poorly known. Herewe described bird richness and composition of this area, with emphasis on the relationship between vegetationtype and the presence of key bird species. We compiled systematic studies conducted during the 2007-2020 periodand performed new surveys to elaborate a checklist of bird species and assess completeness. We reviewed a total of 12 studies distributed along five landscape units and nine vegetation types. We recorded 245 species, though the species accumulation curve indicates that the number of species could be even higher for the area. Most species were recorded in freshwater marshes, watercourses and grasslands in Entre Ríos. We identified 14 (5.7%) threatened species (e.g., Spartonoica maluroides, Limnoctites rectirostris and Sporophila palustris), most of them registered in grassland and freshwater marshes. To our best knowledge, the list of species is the most comprehensive one for the area, showing that 23.7% lf all bird species known for Argentina. Our results suggest the importance of freshwater marshes, watercourses and grasslands as key vegetation types for birds.Fil: Fracassi, Natalia Gabriela. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires Norte. Estación Experimental Agropecuaria Delta del Paraná; ArgentinaFil: Sica, Yanina Vanesa. Universidad Nacional de San Martín. Instituto de Investigación e Ingeniería Ambiental. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigación e Ingeniería Ambiental; ArgentinaFil: Magnano, Andrea Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto Argentino de Investigaciones de las Zonas Áridas. Provincia de Mendoza. Instituto Argentino de Investigaciones de las Zonas Áridas. Universidad Nacional de Cuyo. Instituto Argentino de Investigaciones de las Zonas Áridas; ArgentinaFil: Vaccaro, Anahí Sofía. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Ecología, Genética y Evolución de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Ecología, Genética y Evolución de Buenos Aires; ArgentinaFil: Landó, Roberto. Arauco Argentina Sociedad Anonima (arauco Argentina Sa);Fil: Artero, Diego. Arauco Argentina Sociedad Anonima (arauco Argentina Sa);Fil: Gavier Pizarro, Gregorio. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Recursos Naturales. Instituto de Recursos Biológicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Bó, Roberto Fabián. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ecología, Genética y Evolución; ArgentinaFil: Somma, Daniel Jorge. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires Norte. Estación Experimental Agropecuaria Delta del Paraná; ArgentinaFil: Quintana, Ruben Dario. Universidad Nacional de San Martín. Instituto de Investigación e Ingeniería Ambiental. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigación e Ingeniería Ambiental; ArgentinaFil: Rodriguez, María José. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Museo Argentino de Ciencias Naturales "Bernardino Rivadavia"; ArgentinaFil: Cabanne, Gustavo Sebastián. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Museo Argentino de Ciencias Naturales "Bernardino Rivadavia"; Argentin

Conceptos, aportes y teorías: ¿Cómo diseñar una ciudad ideal?

In the article we propose the different perspectives that are given by scientists, urban planners, architects and writers regarding how they shape an ideal city; Each one Emphasizes how the design of this should be, thanks to their contributions we can identify the characteristics and on which the ideal city is based.En el artículo planteamos las diferentes perspectivas que se dan por parte de los científicos, urbanistas, arquitectos y escritores con respecto a cómo ellos plasman una ciudad ideal; cada uno Enfatiza en cómo deben ser el diseño de ésta, gracias a sus aportes podemos identificar las características y de que se fundamenta la una ciudad ideal