Feasibility and effectiveness of a two-tiered intervention involving training and a new consultation model for patients with palliative care needs in primary care: A before-after study.

BACKGROUND: Evidence suggests that involving General Practitioners in the care of patients with palliative care needs may improve patient outcomes. AIM: To evaluate whether a two-tiered intervention involving training in palliative care and a new consultation model in primary care for patients with palliative care needs is feasible and could reduce patients' symptom burden. DESIGN: Before-after study including an internal pilot. SETTING/PARTICIPANTS: Nine general practitioners working in a health region in Portugal and 53 patients with palliative care needs from their patient lists were recruited. General Practitioners received training in palliative care and used a new primary palliative care consultation model, with medical consultations every 3 weeks for 12 weeks. The primary outcome was physical symptom burden, self-reported using the Integrated Palliative care Outcome Scale (IPOS) patient version (min.0-max.1000). Secondary outcomes included emotional symptoms (min.0-max.400) and communication/practical issues (min.0-max.300). RESULTS: Of the 35/53 patients completed the 12-week intervention (mean age 72.53 years, SD = 13.45; 54.7% female). All had advanced disease: one third had cancer (n = 13), one third had congestive heart failure (n = 12); others had chronic kidney disease and chronic obstructive pulmonary disease. After the 12 weeks of intervention, there was a reduction in physical symptom burden [mean difference from baseline of 71.42 (95%CI 37.01-105.85) with a medium-large effect size (0.71], and in emotional symptom burden [mean difference 42.86 (95%CI 16.14-69.58), with a medium effect size (0.55)]. No difference was found for communication/practical issues. CONCLUSIONS: Our intervention can be effective in reducing patients' physical and emotional symptoms. TRIAL REGISTRATION: ClinicalTrials.gov ID - NCT05244590. Registration: 14th February 2022.

Diagnostic evaluation of institutions as a basis for designing the Brazilian maturity model of telehealth services.

BACKGROUND: The number and specificities of telehealth service units that expanded their services and diversified with the COVID-19 pandemic in Brazil need to be discovered. The objective of this manuscript is to present a methodology for the diagnostic evaluation of 19 telehealth units from different regions of the country for federal governmental decision-making. METHODS: A cross-sectional quantitative and qualitative study was carried out in the form of a census based on administrative records with an online survey and in-depth interviews with local telehealth managers. RESULTS: Despite the discontinuity of regular funding, the results point to a diversity of initiatives and advances. Citizenship, sustainability, security, and budget management are recurring themes in the maturity analysis of telehealth services after the advent of the pandemic. CONCLUSION: It is necessary for Brazil to build a resilient model of the maturity of telehealth services that contemplates the different regional scenarios.

Genomic analysis of feed efficiency traits in beef cattle using random regression models.

Feed efficiency plays a major role in the overall profitability and sustainability of the beef cattle industry, as it is directly related to the reduction of the animal demand for input and methane emissions. Traditionally, the average daily feed intake and weight gain are used to calculate feed efficiency traits. However, feed efficiency traits can be analysed longitudinally using random regression models (RRMs), which allow fitting random genetic and environmental effects over time by considering the covariance pattern between the daily records. Therefore, the objectives of this study were to: (1) propose genomic evaluations for dry matter intake (DMI), body weight gain (BWG), residual feed intake (RFI) and residual weight gain (RWG) data collected during an 84-day feedlot test period via RRMs; (2) compare the goodness-of-fit of RRM using Legendre polynomials (LP) and B-spline functions; (3) evaluate the genetic parameters behaviour for feed efficiency traits and their implication for new selection strategies. The datasets were provided by the EMBRAPA-GENEPLUS beef cattle breeding program and included 2920 records for DMI, 2696 records for BWG and 4675 genotyped animals. Genetic parameters and genomic breeding values (GEBVs) were estimated by RRMs under ssGBLUP for Nellore cattle using orthogonal LPs and B-spline. Models were compared based on the deviance information criterion (DIC). The ranking of the average GEBV of each test week and the overall GEBV average were compared by the percentage of individuals in common and the Spearman correlation coefficient (top 1%, 5%, 10% and 100%). The highest goodness-of-fit was obtained with linear B-Spline function considering heterogeneous residual variance. The heritability estimates across the test period for DMI, BWG, RFI and RWG ranged from 0.06 to 0.21, 0.11 to 0.30, 0.03 to 0.26 and 0.07 to 0.27, respectively. DMI and RFI presented within-trait genetic correlations ranging from low to high magnitude across different performance test-day. In contrast, BWG and RWG presented negative genetic correlations between the first 3 weeks and the other days of performance tests. DMI and RFI presented a high-ranking similarity between the GEBV average of week eight and the overall GEBV average, with Spearman correlations and percentages of individuals selected in common ranging from 0.95 to 1.00 and 93 to 100, respectively. Week 11 presented the highest Spearman correlations (ranging from 0.94 to 0.98) and percentages of individuals selected in common (ranging from 85 to 94) of BWG and RWG with the average GEBV of the entire period of the test. In conclusion, the RRM using linear B-splines is a feasible alternative for the genomic evaluation of feed efficiency. Heritability estimates of DMI, RFI, BWG and RWG indicate enough additive genetic variance to achieve a moderate response to selection. A new selection strategy can be adopted by reducing the performance test to 56 days for DMI and RFI selection and 77 days for BWG and RWG selection.

Effect of kelp gull harassment on southern right whale calf survival: a long-term capture-recapture analysis.

Kelp gulls (Larus dominicanus) commonly feed on the skin and blubber of surfacing southern right whales (SRW, Eubalaena australis) in the near shore waters of Península Valdés (PV), Argentina. Mothers and especially calves respond to gull attacks by changing their swimming speeds, resting postures and overall behaviour. Gull-inflicted wounds per calf have increased markedly since the mid-1990s. Unusually high mortality of young calves occurred locally after 2003, and increasing evidence points to gull harassment as a factor contributing to the excess deaths. After leaving PV, calves undertake a long migration with their mothers to summer feeding areas; their health during this strenuous exertion is likely to affect their probabilities of first-year survival. To explore the effects of gull-inflicted wounds on calf survival, we analysed 44 capture-recapture observations between 1974 and 2017, for 597 whales photo-identified in their years of birth between 1974 and 2011. We found a marked decrease in first-year survival associated with an increase in wound severity over time. Our analysis supports recent studies indicating that gull harassment at PV may impact SRW population dynamics.

Ecologically driven differences in individual diet specialization across three populations of Guiana dolphin.

Populations usually considered foraging generalists may include specialized individuals that feed on a restricted subset of the prey spectrum consumed by the population. By analyzing the time series of δ13C and δ15N values in sequential growth layer groups within tooth dentin, we measured population- and individual-level variation in resource use of three populations of Guiana dolphins (Sotalia guianensis)-Caravelas River, Babitonga Bay, and Norte Bay-along a latitudinal gradient in the southwestern Atlantic Ocean. We show that the Guiana dolphin at Caravelas River is a generalist population consisting of individual dietary specialists, likely due to the absence of other resident dolphin populations thus allowing individuals to target prey across a wide range of habitats. The Babitonga Bay population is also composed of individual specialists potentially due to the selective foraging behavior of some individuals on high-quality prey sources within and near the bay. In contrast, the Norte Bay population comprises individual generalists, which likely reflects its distinctive cohesive social organization, coexistence with two other dolphin species, and an opportunistic foraging strategy in response to resource fluctuations inherent to the southern limit of the species distribution. Although the Guiana dolphin is generally considered to be a dietary generalist at the population level, our findings reveal that the total niche width of populations and the degree of individual diet specialization are highly context dependent, suggesting dietary plasticity that may be related to a latitudinal gradient in resource availability and environmental conditions.

Statistical analysis of blast-induced vibration near an open pit mine.

Blast-induced vibration may be harmful to facilities in the vicinity of operating mines, mainly causing structural damage and human discomfort. This study presents an application of multivariate statistics to predict vibration levels regarding their potential to cause structural damage and human discomfort. An extensive seismic monitoring campaign was executed in a large open-pit iron ore mine, near a small village, to gather a dataset for a predictive multivariate analysis. Ten blasting events have produced a dataset of 158 valid measurements. Three classes of vibration peak velocity were adopted from legal standards, which later supported a cluster analysis. Then, it was possible to compare how much these two classification modalities respond to discriminant analysis. The next step was to carry out a principal component analysis (PCA) from the original database, and, comparatively, to plot both the scores concerning the classes derived from the vibration standard and those from the groups obtained from cluster analysis. PCA has considerably explained the data variability, while the three classes from cluster analysis resulted very similar to the corresponding ones from the vibration standards. The results have demonstrated that multivariate statistics may be applied to manage blasting-induced vibration and its deleterious effects with few adjustments and automation.

NASA POWER satellite meteorological system is a good tool for obtaining estimates of the temperature-humidity index under Brazilian conditions compared to INMET weather stations data.

Heat stress negatively affects livestock, with undesirable effects on animals' production and reproduction. Temperature and humidity index (THI) is a climatic variable used worldwide to study the effect of heat stress on farm animals. Temperature and humidity data can be obtained in Brazil through the National Institute of Meteorology (INMET), but complete data may not be available due to temporary failures on weather stations. An alternative to obtaining meteorological data is the National Aeronautics and Space Administration Prediction of Worldwide Energy Resources (NASA POWER) satellite-based weather system. We aimed to compare THI estimates obtained from INMET weather stations and NASA POWER meteorological information sources using Pearson correlation and linear regression. After quality check, data from 489 INMET weather stations were used. The hourly, average daily and maximum daily THI were evaluated. We found greater correlations and better regression evaluation metrics when average daily THI values were considered, followed by maximum daily THI, and hourly THI. NASA POWER satellite-based weather system is a suitable tool for obtaining the average and maximum THI values using information collected from Brazil, showing high correlations with THI estimates from INMET and good regression evaluation metrics, and can assist studies that aim to analyze the impact of heat stress on livestock production in Brazil, providing additional data to complement the existing information available in the INMET database.

Genomic prediction in Brazilian Guzerá cattle: application of a single-step approach to productive and reproductive traits.

This study aimed to investigate the feasibility of genomic prediction for productive and reproductive traits in Guzerá cattle using single-step genomic best linear unbiased prediction (ssGBLUP). Evaluations included the 305-day cumulative yields (first lactation, in kg) of milk, lactose, protein, fat, and total solids; adjusted body weight (kg) at the ages of 450, 365, and 210 days; and age at first calving (in days), from a database containing 197,283 measurements from Guzerá males and females born between 1954 and 2018. The pedigree included 433,823 animals spanning up to 14 overlapping generations. A total of 1618 animals were genotyped. The analyses were performed using ssGBLUP and traditional BLUP methods. Predictive ability and bias were accessed using cross-validation: predictive ability was similar between the methods and ranged from 0.27 to 0.47 for the genomic-based model and from 0.30 to 0.45 for the pedigree-based model; the bias was also similar between the methods, ranging from 0.88 to 1.35 in the genomic-based model and from 0.96 to 1.41 in the pedigree-based model. The individual accuracies of breeding values were evidently increased in the genomic evaluation, with values ranging from 0.41 to 0.56 in the genomic-based model and from 0.26 to 0.54 in the pedigree-based model. Even based on a small number of genotyped animals and a small database for some traits, the results suggest that ssGBLUP is feasible and may be applied to national genetic evaluation of the breed to increase the accuracy of breeding values without greatly impacting predictive ability and bias.

Genomic prediction and genetic correlations estimated for milk production and fatty acid traits in Walloon Holstein cattle using random regression models.

The aims of this study were to: (1) estimate genetic correlation for milk production traits (milk, fat and protein yields and fat and protein contents) and fatty acids (FA: C16:0, C18:1 cis-9, LCFA, SFA, and UFA) over days in milk, (2) investigate the performance of genomic predictions using single-step GBLUP (ssGBLUP) based on random regression models (RRM), and (3) identify the optimal scaling and weighting factors to be used in the construction of the H matrix. A total of 302 684 test-day records of 63.875 first lactation Walloon Holstein cows were used. Positive genetic correlations were found between milk yield and fat and protein yield (rg from 0.46 to 0.85) and between fat yield and milk FA (rg from 0.17 to 0.47). On the other hand, negative correlations were estimated between fat and protein contents (rg from -0.22 to -0.59), between milk yield and milk FA (rg from -0.22 to -0.62), and between protein yield and milk FA (rg from -0.11 to -0.19). The selection for high fat content increases milk FA throughout lactation (rg from 0.61 to 0.98). The test-day ssGBLUP approach showed considerably higher prediction reliability than the parent average for all milk production and FA traits, even when no scaling and weighting factors were used in the H matrix. The highest validation reliabilities (r2 from 0.09 to 0.38) and less biased predictions (b1 from 0.76 to 0.92) were obtained using the optimal parameters (i.e., ω = 0.7 and α = 0.6) for the genomic evaluation of milk production traits. For milk FA, the optimal parameters were ω = 0.6 and α = 0.6. However, biased predictions were still observed (b1 from 0.32 to 0.81). The findings suggest that using ssGBLUP based on RRM is feasible for the genomic prediction of daily milk production and FA traits in Walloon Holstein dairy cattle.

Random regression test-day models to describe milk production and fatty acid traits in first lactation Walloon Holstein cows.

We investigated the use of different Legendre polynomial orders to estimate genetic parameters for milk production and fatty acid (FA) traits in the first lactation Walloon Holstein cows. The data set comprised 302,684 test-day records of milk yield, fat and protein contents, and FAs generated by mid-infrared (MIR) spectroscopy, C16:0 (palmitic acid), C18:1 cis-9 (oleic acid), LCFAs (long-chain FAs), SFAs (saturated FAs) and UFAs (unsaturated FAs) were studied. The models included random regression coefficients for herd-year of calving (h), additive genetic (a) and permanent environment (p) effects. The selection of the best random regression model (RRM) was based on the deviance information criterion (DIC), and genetic parameters were estimated via a Bayesian approach. For all analysed random effects, DIC values decreased as the order of the Legendre polynomials increased. Best-fit models had fifth-order (degree 4) for the p effect and ranged from second- to fifth-order (degree 1-4) for the a and h effects (LEGhap: LEG555 for milk yield and protein content; LEG335 for fat content and SFA; LEG545 for C16:0 and UFA; and LEG535 for C18:1 cis-9 and LCFA). Based on the best-fit models, an effect of overcorrection was observed in early lactation (5-35 days in milk [DIM]). On the contrary, third-order (LEG333; degree 2) models showed flat residual trajectories throughout lactation. In general, the estimates of genetic variance tended to increase over DIM, for all traits. Heritabilities for milk production traits ranged from 0.11 to 0.58. Milk FA heritabilities ranged from low-to-high magnitude (0.03-0.56). High Spearman correlations (>0.90 for all bulls and >0.97 for top 100) were found among breeding values for 155 and 305 DIM between the best RRM and LEG333 model. Therefore, third-order Legendre polynomials seem to be most parsimonious and sufficient to describe milk production and FA traits in Walloon Holstein cows.

Searching for causal relationships among latent variables concerning performance, carcass, and meat quality traits in broilers.

In causal relationship studies, the latent variables may summarize the phenotypes in theoretical traits according to their phenotypic correlations, improving the understanding of causal relationships between broilers phenotypes. In this study, we aimed to investigate potential causal relationships among latent variables in broilers using a structural equation model in the context of genetic analysis. The data used in this study comprised 14 traits in broilers with 2,017 records each, and 104,154 animals in pedigree. Four latent variables (WEIGHT, LOSSES, COLOUR, and VISCERA) were defined and validated using Bayesian Confirmatory Factor Analysis. Subsequently, a search for causal linkage structures was performed, obtaining a single causal link structure between the latent variables. Then, this information was used to fit the structural equation model (SEM). The results from the SEM indicated positive causal effects of the variables WEIGHT and LOSSES on the variables VISCERA and COLOUR, respectively, with structural coefficient estimates of 1.006 and 0.040, respectively. On the other hand, an antagonist causal effect of the variable WEIGHT on the variable LOSSES was verified, with a structural coefficient estimate of -4.333. These results highlight the causal relationship between performance and meat quality traits, which may be associated with the natural processes involved in the conversion of muscle into meat and the structural changes in muscle tissues due to intense selection for high growth rates in broilers.

Estimation of genetic parameters and inbreeding depression in Piau pig breed.

This study is aimed at estimating genetic parameters, effective population size, inbreeding, and inbreeding depression for birth weight, weaning weight, and average pre-weaning daily weight gain (ADG) in Piau pigs. We used information from 3841 Piau pigs, and four linear models were fitted in single-trait analyses, including or excluding maternal genetic effect, common litter effect, or a combination. The adjustments of the models were compared using the likelihood ratio test, in which the model that presented the best fit for each trait was used to estimate the (co)variance components. The inbreeding depression effect was evaluated using a linear model that included the fixed effects of sex, parity order, contemporary group, and inbreeding coefficient as a fixed covariate. The weights at birth and weaning showed low direct heritabilities (0.08 and 0.05, respectively), while the ADG showed moderate heritability (0.20). The weight at birth showed high genetic correlations with the weight at weaning (0.90) and the ADG (0.82). The weight at weaning and the ADG also showed a high genetic correlation (0.99). There was an inbreeding increase over the generations and a reduction in the effective population size. In the last generation evaluated, all the animals were inbred, the average inbreeding coefficient was 0.07, and the effective population size was 20.8. A significant inbreeding effect on ADG was observed, where an increase of 1% in the inbreeding coefficient resulted in a decrease of 0.005 g in the ADG. Thus, increasing effective population size is mandatory for controlling inbreeding and reducing the loss of variability in this Piau pig population.

Ecological divergence and speciation in common bottlenose dolphins in the western South Atlantic.

Coastal and offshore ecotypes of common bottlenose dolphins have been recognized in the western South Atlantic, and it is possible that trophic niche divergence associated with social interactions is leading them to genetic and phenotypic differentiation. The significant morphological differentiation observed between these ecotypes suggests they represent two different subspecies. However, there is still a need to investigate whether there is congruence between morphological and genetic data to rule out the possibility of ecophenotypic variation accompanied by gene flow. Mitochondrial DNA (mtDNA) control region sequence data and 10 microsatellite loci collected from stranded and biopsied dolphins sampled in coastal and offshore waters of Brazil as well as 106 skulls for morphological analyses were used to determine whether the morphological differentiation was supported by genetic differentiation. There was congruence among the data sets, reinforcing the presence of two distinct ecotypes. The divergence may be relatively recent, however, given the moderate values of mtDNA nucleotide divergence (dA = 0.008), presence of one shared mtDNA haplotype and possibly low levels of gene flow (around 1% of migrants per generation). Results suggest the ecotypes may be in the process of speciation and reinforce they are best described as two different subspecies until the degree of nuclear genetic divergence is thoroughly evaluated: Tursiops truncatus gephyreus (coastal ecotype) and T. t. truncatus (offshore ecotype). The endemic distribution of T. t. gephyreus in the western South Atlantic and number of anthropogenic threats in the area reinforces the importance of protecting this ecotype and its habitat.

Should commercial sex workers have unrestricted healthcare access across the world?

We argue commercial sex workers have rights to healthcare and psychosocial support. While decriminalization is not legally enacted in most countries, we would suggest these workers rights include freedom from harassment and opportunities to lead healthy lives. The need for healthcare access for all is heightened in the COVID-19 pandemic where some people flout rules on lockdown by engaging with commercial sex workers and may unwittingly spread SARS-CoV-2 in so doing. Unrestricted healthcare access without stigma for commercial sex workers protects them, and has a beneficial societal effect on those who engage with them and on their contacts.

Virtual Reality Cognitive Training Among Individuals With Alcohol Use Disorder Undergoing Residential Treatment: Pilot Randomized Controlled Trial.

BACKGROUND: Alcohol use disorder (AUD) has been associated with diverse physical and mental morbidities. Among the main consequences of chronic and excessive alcohol use are cognitive and executive deficits. Some of these deficits may be reversed in specific cognitive and executive domains with behavioral approaches consisting of cognitive training. The advent of computer-based interventions may leverage these improvements, but randomized controlled trials (RCTs) of digital interactive-based interventions are still scarce. OBJECTIVE: The aim of this study is to explore whether a cognitive training approach using VR exercises based on activities of daily living is feasible for improving the cognitive function of patients with AUD undergoing residential treatment, as well as to estimate the effect size for this intervention to power future definitive RCTs. METHODS: This study consisted of a two-arm pilot RCT with a sample of 36 individuals recovering from AUD in a therapeutic community; experimental group participants received a therapist-guided, VR-based cognitive training intervention combined with treatment as usual, and control group participants received treatment as usual without cognitive training. A comprehensive neuropsychological battery of tests was used both at pre- and postassessments, including measurement of global cognition, executive functions, attention, visual memory, and cognitive flexibility. RESULTS: In order to control for potential effects of global cognition and executive functions at baseline, these domains were controlled for in the statistical analysis for each individual outcome. Results indicate intervention effects on attention in two out of five outcomes and on cognitive flexibility in two out of six outcomes, with effect sizes in significant comparisons being larger for attention than for cognitive flexibility. Patient retention in cognitive training was high, in line with previous studies. CONCLUSIONS: Overall, the data suggest that VR-based cognitive training results in specific contributions to improving attention ability and cognitive flexibility of patients recovering from AUD. TRIAL REGISTRATION: ClinicalTrials.gov NCT04505345; https://clinicaltrials.gov/show/NCT04505345.

Autoregressive model for genetic evaluation of longitudinal reproductive traits in Brazilian Holstein cattle.

Reproductive efficiency is major determinant of the dairy herd profitability. Thus, reproductive traits have been widely used as selection objectives in the current dairy cattle breeding programs. We aimed to evaluate strategies to model days open (DO), calving interval (CI) and daughter pregnancy rate (DPR) in Brazilian Holstein cattle. These reproductive traits were analysed by the autoregressive (AR) model and compared with classical repeatability (REP) model using 127,280, 173,092 and 127,280 phenotypic records, respectively. The first three calving orders of cows from 1,469 Holstein herds were used here. The AR model reported lower values for Akaike Information Criteria and Mean Square Errors, as well as larger model probabilities, for all evaluated traits. Similarly, larger additive genetic and lower residual variances were estimated from AR model. Heritability and repeatability estimates were similar for both models. Heritabilities for DO, CI and DPR were 0.04, 0.07 and 0.04; and 0.05, 0.06 and 0.04 for AR and REP models, respectively. Individual EBV reliabilities estimated from AR for DO, CI and DPR were, in average, 0.29, 0.30 and 0.29 units higher than those obtained from REP model. Rank correlation between EBVs obtained from AR and REP models considering the top 10 bulls ranged from 0.72 to 0.76; and increased from 0.98 to 0.99 for the top 100 bulls. The percentage of coincidence between selected bulls from both methods increased over the number of bulls included in the top groups. Overall, the results of model-fitting criteria, genetic parameters estimates and EBV predictions were favourable to the AR model, indicating that it may be applied for genetic evaluation of longitudinal reproductive traits in Brazilian Holstein cattle.

Applying an association weight matrix in weighted genomic prediction of boar taint compounds.

Biological information regarding markers and gene association may be used to attribute different weights for single nucleotide polymorphism (SNP) in genome-wide selection. Therefore, we aimed to evaluate the predictive ability and the bias of genomic prediction using models that allow SNP weighting in the genomic relationship matrix (G) building, with and without incorporating biological information to obtain the weights. Firstly, we performed a genome-wide association studies (GWAS) in data set containing single- (SL) or a multi-line (ML) pig population for androstenone, skatole and indole levels. Secondly, 1%, 2%, 5%, 10%, 30% and 50% of the markers explaining the highest proportions of the genetic variance for each trait were selected to build gene networks through the association weight matrix (AWM) approach. The number of edges in the network was computed and used to derive weights for G (AWM-WssGBLUP). The single-step GBLUP (ssGBLUP) and weighted ssGBLUP (WssGBLUP) were used as standard scenarios. All scenarios presented predictive abilities different from zero; however, the great overlap in their confidences interval suggests no differences among scenarios. Most of scenarios of based on AWM provide overestimations for skatole in both SL and ML populations. On the other hand, the skatole and indole prediction were no biased in the ssGBLUP (S1) in both SL and ML populations. Most of scenarios based on AWM provide no biased predictions for indole in both SL and ML populations. In summary, using biological information through AWM matrix and gene networks to derive weights for genomic prediction resulted in no increase in predictive ability for boar taint compounds. In addition, this approach increased the number of analyses steps. Thus, we can conclude that ssGBLUP is most appropriate for the analysis of boar taint compounds in comparison with the weighted strategies used in the present work.

Autoregressive single-step model for genomic evaluation of longitudinal reproductive traits in portuguese holstein cattle.

We investigated the applicability of ssGBLUP methodology under the autoregressive model (H-AR) for genomic evaluation of longitudinal reproductive traits in Portuguese Holstein cattle. The genotype data of 1,230 bulls and 1,645 cows were considered in our study. The reproductive traits evaluated were interval from calving to first service (ICF), calving interval (CI) and daughter pregnancy rate (DPR) measured during the first four parities. Reliability and rank correlation were used to compare the H-AR with the traditional pedigree-based autoregressive models (A-AR). In addition, a validation study was performed considering different scenarios. Higher genomic estimated breeding values (GEBV) reliabilities were obtained for genotyped bulls when evaluated under the H-AR model, with emphasis on bulls with less than 9 daughters. For this group, the averages of GEBV reliabilities corresponded to 0.62, 0.69 and 0.62 for ICF, CI and DPR, respectively, while the averages obtained by the A-AR model were 0.27, 0.15 and 0.16. The validation study was favourable to H-AR. The best results were observed in the scenario where genotyped cows were combined with contributing bulls (genotyped bulls with daughter or relationship information in the population). Overall, the results suggest that ssGBLUP methodology under the autoregressive model is a feasible and applicable approach to be used in genomic analyses of longitudinal reproductive traits in Portuguese Holstein cattle.

[Implementation of telemedicine in the Americas: Barriers and facilitatorsBarreiras e facilitadores para a implementação da telemedicina nas Américas]. / Barreras y facilitadores a la implementación de la telemedicina en las Américas.

With millions of people in the world in situations of physical distancing because of COVID-19, information and communication technology (ICT) has become as one of the principal means of interaction and collaboration. The following advantages of ICT have been cited since the start of the new millennium: increased access to information and service delivery, educational strengthening, quality control of screening programs, and reduction of health care costs. In the case of telemedicine, however, a number of barriers-especially technological, human and social, psychosocial, anthropological, economic, and governance-related-have stood in the way of its adoption. The past 20 years have seen an increase in the availability of resources and technical capacity, improvements in digital education, empowerment of patients regarding their treatment, and increased public interest in this area. Successes have included the use of interdisciplinary teams, academic and professional networking, and virtual medical consultations. After reviewing the state of telemedicine in the Region of the Americas, the authors recommend the urgent adoption of measures aimed at implementing national telemedicine policies and programs, including a regulatory framework and adequate funding. Implementation of the measures should be integrated and interoperable and include the support of academic networks and the collaboration of specialized institutions. The policies should generate an enabling context that ensures sustainability of the progress achieved, bearing in mind the possible barriers mentioned.

Com milhões de pessoas no mundo em situação de distanciamento físico devido à COVID-19, as tecnologias da informação e comunicação (TICs) se enquadraram como um dos meios principais de interação e colaboração. Já no início deste milênio, começaram a ser mencionadas as seguintes vantagens: maior acesso à informação e à prestação de serviços; fortalecimento da educação; controle de qualidade dos programas de detecção e redução dos custos na atenção à saúde. No entanto, entre as principais barreiras de adoção da telemedicina se encontram as de caráter: tecnológico; humano e social; psicossocial e antropológico; de governança e econômico. Nestes 20 anos, houve um aumento nos recursos e na capacidade técnica, uma melhora na educação digital, um empoderamento do paciente em seu tratamento e um maior interesse público nessa área. Em especial, são consideradas bem-sucedidas a constituição de equipes interdisciplinares e as redes acadêmicas e profissionais, e as consultas médicas virtuais. Após revisar o estado da telemedicina na Região das Américas, os autores recomendam a adoção de medidas urgentes para implementar políticas e programas nacionais de telemedicina, incluindo o marco normativo e o orçamento necessário. Essa implementação deve ser realizada de maneira integral e interoperável e sustentada por redes acadêmicas, de parceria e instituições especializadas. Tais políticas devem gerar um contexto favorável, dando sustentabilidade ao avanço obtido e considerando os aspectos mencionados nas possíveis barreiras.

Non-replicability circumstances in a neural network model with Hodgkin-Huxley-type neurons.

Building upon previous experiments can be used to accomplish new goals. In computing, it is imperative to reuse computer code to continue development on specific projects. Reproducibility is a fundamental building block in science, and experimental reproducibility issues have recently been of great concern. It may be surprising that reproducibility is also of concern in computational science. In this study, we used a previously published code to investigate neural network activity and we were unable to replicate our original results. This led us to investigate the code in question, and we found that several different aspects, attributable to floating-point arithmetic, were the cause of these replicability issues. Furthermore, we uncovered other manifestations of this lack of replicability in other parts of the computation with this model. The simulated model is a standard system of ordinary differential equations, very much like those commonly used in computational neuroscience. Thus, we believe that other researchers in the field should be vigilant when using such models and avoid drawing conclusions from calculations if their qualitative results can be substantially modified through non-reproducible circumstances.