Incidence of myopia in Swedish schoolchildren: A longitudinal study.

PURPOSE: The prevalence of myopia in Scandinavia tends to be lower than in other parts of the world. This study aimed to investigate the incidence of myopia and its predictors in Swedish children to characterise this trend. METHODS: A 2-year longitudinal study was conducted following a cohort of schoolchildren aged 8-16 years. Myopia was defined as a spherical equivalent refraction (SER) ≤ -0.50 D. The study enrolled 128 participants, 70 (55%) females with a mean age of 12.0 years (SD = 2.4). RESULTS: The cumulative incidence of myopia during the follow-up period was 5.5%, and the incidence rate of myopia was 3.2 cases per 100 person-years. Participants with myopia at baseline exhibited a faster increase in refractive error during the follow-up period. Likewise, participants with two myopic parents exhibited a more marked change towards myopia, regardless of their initial refractive error. CONCLUSION: In the current study, similar to prevalence, the incidence of myopia was low when compared with other parts of the world. These results lead us to formulate a new hypothesis that the normal emmetropisation process may be protected by low educational pressure practised in Sweden during early childhood. Further research is necessary to test this new hypothesis.

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.

Hippocampal memory reactivation during sleep is correlated with specific cortical states of the retrosplenial and prefrontal cortices.

Episodic memories are thought to be stabilized through the coordination of cortico-hippocampal activity during sleep. However, the timing and mechanism of this coordination remain unknown. To investigate this, we studied the relationship between hippocampal reactivation and slow-wave sleep up and down states of the retrosplenial cortex (RTC) and prefrontal cortex (PFC). We found that hippocampal reactivations are strongly correlated with specific cortical states. Reactivation occurred during sustained cortical Up states or during the transition from up to down state. Interestingly, the most prevalent interaction with memory reactivation in the hippocampus occurred during sustained up states of the PFC and RTC, while hippocampal reactivation and cortical up-to-down state transition in the RTC showed the strongest coordination. Reactivation usually occurred within 150-200 msec of a cortical Up state onset, indicating that a buildup of excitation during cortical Up state activity influences the probability of memory reactivation in CA1. Conversely, CA1 reactivation occurred 30-50 msec before the onset of a cortical down state, suggesting that memory reactivation affects down state initiation in the RTC and PFC, but the effect in the RTC was more robust. Our findings provide evidence that supports and highlights the complexity of bidirectional communication between cortical regions and the hippocampus during sleep.

New statistical process control charts for overdispersed count data based on the Bell distribution.

Poisson distribution is a popular discrete model used to describe counting information, from which traditional control charts involving count data, such as the c and u charts, have been established in the literature. However, several studies recognize the need for alternative control charts that allow for data overdispersion, which can be encountered in many fields, including ecology, healthcare, industry, and others. The Bell distribution, recently proposed by Castellares et al. (2018), is a particular solution of a multiple Poisson process able to accommodate overdispersed data. It can be used as an alternative to the usual Poisson (which, although not nested in the Bell family, is approached for small values of the Bell distribution) Poisson, negative binomial, and COM-Poisson distributions for modeling count data in several areas. In this paper, we consider the Bell distribution to introduce two new exciting, and useful statistical control charts for counting processes, which are capable of monitoring count data with overdispersion. The performance of the so-called Bell charts, namely Bell-c and Bell-u charts, is evaluated by the average run length in numerical simulation. Some artificial and real data sets are used to illustrate the applicability of the proposed control charts.

Predictors of problems reported on the EQ-5D-3L dimensions among people with impaired vision in northern Portugal.

BACKGROUND: The EQ-5D index often fails to detect the effect of ophthalmic diseases and sight loss. Investigating predictors of individual EQ-5D health dimensions might reveal the underlying reasons. The aim of this study was to investigate predictors of health dimension ratings obtained with the EQ-5D-3L from participants with impaired vision representing a spectrum of eye diseases. METHODS: Observational cross-sectional study with participants recruited at four public hospitals in Portugal. Outpatients with visual acuity of 0.30 logMAR(6/12) or worse in the better-seeing eye were invited to participate. Participants completed two instruments: the EQ-5D-3L (measures participants' perceived health-related quality-of-life) and the Massof Activity Inventory (measures visual ability-ability to perform vision-related activities). This study used logistic regression models to identify factors associated with responses to the EQ-5D-3L. RESULTS: The study included 492 participants, mean age 63.4 years (range = 18-93), 50% females. The most common diagnosis was diabetic retinopathy (37%). The mean visual acuity in the better seeing eye was 0.65 logMAR (SD = 0.48) and the mean visual ability was 0.62 logits (SD = 2.04), the correlation between the two was r = - 0.511 (p < 0.001). Mobility and self-care were the health dimensions with the fewest problems (1% reported extreme problems), anxiety and depression the dimension with the most problems (24% reported extreme problems). ROC curve analysis showed that the EQ-5D index was a poor predictor of cases of vision impairment whilst visual ability given was a good predictor of cases of vision impairment. Visual ability was an independent predictor of the response for all dimensions, higher ability was always associated with a reduced odds of reporting problems. The odds of reporting problems were increased for females in 3 out of 5 dimensions. Comorbidities, visual acuity and age-category were predictors of the odds of reporting problems for one dimension each. CONCLUSIONS: The odds of reporting problems for the five health dimensions of the EQ-5D-3L were strongly influenced by the ability to perform vision-related activities (visual ability). The EQ-5D index showed poor performance at detecting vision impairment. These findings are informative and relevant for the clinic and for research evaluating the impact of eye diseases and disease treatments in ophthalmology.

The use of dried blood spots for the serological evaluation of SARS-CoV-2 antibodies.

BACKGROUND: To determine if dried blood spot specimens (DBS) can reliably detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies, we compared the SARS-CoV-2 IgG antibody response in paired serum and eluates from DBS specimens. METHODS: A total of 95 paired DBS and serum samples were collected from 74 participants (aged 1-63 years) as part of a household cohort study in Melbourne, Australia. SARS-CoV-2 IgG antibodies specific for the receptor-binding domain (RBD) and S1 proteins between serum and eluates from DBS specimens were compared using an FDA-approved ELISA method. RESULTS: Among the 74 participants, 42% (31/74) were children and the rest were adults. A total of 16 children and 13 adults were SARS-CoV-2 positive by polymerase chain reaction. The IgG seropositivity rate was similar between serum and DBS specimens (18.9% (18/95) versus 16.8% (16/95)), respectively. Similar RBD and S1-specific IgG levels were detected between serum and DBS specimens. Serum IgG levels strongly correlated with DBS IgG levels (r = 0.99, P < 0.0001) for both SARS-CoV-2 proteins. Furthermore, antibodies remained stable in DBS specimens for >3 months. CONCLUSIONS: DBS specimens can be reliably used as an alternative to serum samples for SARS-CoV-2 antibody measurement. The use of DBS specimens would facilitate serosurveillance efforts particularly in hard-to-reach populations and inform public health responses including COVID-19 vaccination strategies.

A systematic review and meta-analysis of the effectiveness and adverse events of gabapentin and pregabalin for sciatica pain.

AIM: This SR aims to assess the effectiveness of pregabalin and gabapentin on pain and disability caused by acute sciatica and the adverse events associated with their clinical use. DESIGN: Systematic review. DATABASES: Electronic databases of Cochrane Central Register of Controlled Trials, MEDLINE, EMBASE, and Clinical Trials.gov were searched from their inception until March 1st of 2021. SELECTION CRITERIA: Randomized trials (RCT) with adults>18 years old with acute sciatica for a minimum of 1 week and a maximum of 1 year (at least moderate pain). DATA TREATMENT: The outcomes were pain, disability and adverse events. Data was summarized using odds ratio and mean difference. GRADE was used to calculate the level of evidence. RESULTS: Eight RCT involving 747 participants were included. The effect of pregabalin was assessed in 3 RCT and in one three-arm trial (pregabalin vs limaprost vs a combination of limaprost and pregabalin). Two trials assessed the effect of gabapentin compared with placebo and one compared with tramadol. One study assessed the effect of gabapentin vs pregabalin in a crossover head-to-head trial. A statistically significant improvement on leg pain at 2 weeks and leg pain with movement at 3 and 4 months was found in a RCT comparing gabapentin with placebo. There were no statistically differences on the remaining time periods assessed for leg pain, low back pain and functional disability. CONCLUSIONS: This SR provides clear evidence for lack of effectiveness of pregabalin and gabapentin for sciatica pain management. In view of this, its routine clinical use cannot be supported.

Impact of COVID-19 Infection on Patients with Cancer: Experience in a Latin American Country: The ACHOCC-19 Study.

INTRODUCTION: The ACHOCC-19 study was performed to characterize COVID-19 infection in a Colombian oncological population. METHODOLOGY: Analytical cohort study of patients with cancer and COVID-19 infection in Colombia. From April 1 to October 31, 2020. Demographic and clinical variables related to cancer and COVID-19 infection were collected. The primary outcome was 30-day mortality from all causes. The association between the outcome and the prognostic variables was analyzed using logistic regression models and survival analysis with Cox regression. RESULTS: The study included 742 patients; 72% were >51 years. The most prevalent neoplasms were breast (132, 17.77%), colorectal (92, 12.34%), and prostate (81, 10.9%). Two hundred twenty (29.6%) patients were asymptomatic and 96 (26.3%) died. In the bivariate descriptive analysis, higher mortality occurred in patients who were >70 years, patients with lung cancer, ≥2 comorbidities, former smokers, receiving antibiotics, corticosteroids, and anticoagulants, residents of rural areas, low socioeconomic status, and increased acute-phase reactants. In the logistic regression analysis, higher mortality was associated with Eastern Cooperative Oncology Group performance status (ECOG PS) 3 (odds ratio [OR] 28.67; 95% confidence interval [CI], 8.2-99.6); ECOG PS 4 (OR 20.89; 95% CI, 3.36-129.7); two complications from COVID-19 (OR 5.3; 95% CI, 1.50-18.1); and cancer in progression (OR 2.08; 95% CI, 1.01-4.27). In the Cox regression analysis, the statistically significant hazard ratios (HR) were metastatic disease (HR 1.58; 95% CI, 1.16-2.16), cancer in progression (HR 1.08; 95% CI, 1.24-2.61) cancer in partial response (HR 0.31; 95% CI, 0.11-0.88), use of steroids (HR 1.44; 95% CI, 1.01-2.06), and use of antibiotics (HR 2.11; 95% CI, 1.47-2.95). CONCLUSION: In our study, patients with cancer have higher mortality due to COVID-19 infection if they have active cancer, metastatic or progressive cancer, ECOG PS >2, and low socioeconomic status. IMPLICATIONS FOR PRACTICE: This study's findings raise the need to carefully evaluate patients with metastatic cancer, in progression, and with impaired Eastern Cooperative Oncology Group status to define the relevance of cancer treatment during the pandemic, consider the risk/benefit of the interventions, and establish clear and complete communication with the patients and their families about the risk of complications. There is also the importance of offering additional support to patients with low income and residence in rural areas so that they can have more support during cancer treatment.

A toolbox of immunoprecipitation-grade monoclonal antibodies to human transcription factors.

A key component of efforts to address the reproducibility crisis in biomedical research is the development of rigorously validated and renewable protein-affinity reagents. As part of the US National Institutes of Health (NIH) Protein Capture Reagents Program (PCRP), we have generated a collection of 1,406 highly validated immunoprecipitation- and/or immunoblotting-grade mouse monoclonal antibodies (mAbs) to 737 human transcription factors, using an integrated production and validation pipeline. We used HuProt human protein microarrays as a primary validation tool to identify mAbs with high specificity for their cognate targets. We further validated PCRP mAbs by means of multiple experimental applications, including immunoprecipitation, immunoblotting, chromatin immunoprecipitation followed by sequencing (ChIP-seq), and immunohistochemistry. We also conducted a meta-analysis that identified critical variables that contribute to the generation of high-quality mAbs. All validation data, protocols, and links to PCRP mAb suppliers are available at http://proteincapture.org.

On Posterior Properties of the Two Parameter Gamma Family of Distributions.

The gamma distribution has been extensively used in many areas of applications. In this paper, considering a Bayesian analysis we provide necessary and sufficient conditions to check whether or not improper priors lead to proper posterior distributions. Further, we also discuss sufficient conditions to verify if the obtained posterior moments are finite. An interesting aspect of our findings are that one can check if the posterior is proper or improper and also if its posterior moments are finite by looking directly in the behavior of the proposed improper prior. To illustrate our proposed methodology these results are applied in different objective priors.

Weighted Lindley frailty model: estimation and application to lung cancer data.

In this paper, we propose a novel frailty model for modeling unobserved heterogeneity present in survival data. Our model is derived by using a weighted Lindley distribution as the frailty distribution. The respective frailty distribution has a simple Laplace transform function which is useful to obtain marginal survival and hazard functions. We assume hazard functions of the Weibull and Gompertz distributions as the baseline hazard functions. A classical inference procedure based on the maximum likelihood method is presented. Extensive simulation studies are further performed to verify the behavior of maximum likelihood estimators under different proportions of right-censoring and to assess the performance of the likelihood ratio test to detect unobserved heterogeneity in different sample sizes. Finally, to demonstrate the applicability of the proposed model, we use it to analyze a medical dataset from a population-based study of incident cases of lung cancer diagnosed in the state of São Paulo, Brazil.

Genetic contribution to lipid target achievement with statin therapy: a prospective study.

Statin therapy response is highly variable. Variants of lipid metabolism genes and statin pharmacokinetic modulators could play a role, however, the impact of most of these variants remains unconfirmed. A prospective and multicenter study included 252 patients was carried out in order to assess, according to achievement of LDL-C or non-HDL-C therapeutic targets and quantitative changes in lipid profiles, the impact of CETP, ABCA1, CYP2D6, and CYP2C9 gene candidate variants on the simvastatin, atorvastatin, and rosuvastatin response. Patients carrier ABCA1 rs2230806 and CYP2D6*3 variants are less likely to achieve therapeutic lipid targets (p = 0.020, OR = 0.59 [0.37, 0.93]; p = 0.040, OR = 0.23 [0.05, 0.93], respectively). Among CETP variants, rs708272 was linked to a 10.56% smaller reduction in LDL-C with rosuvastatin (95% CI = [1.27, 19.86] %; p = 0.028). In contrast, carriers of rs5882 had a 13.33% greater reduction in LDL-C (95% CI = [25.38, 1.28]; p = 0.032). If these findings are confirmed, ABCA1, CYP2D6, and CETP genotyping could be used to help predict which statin and dosage is appropriate in order to improve personalized medicine.

Azacitidine with or without eltrombopag for first-line treatment of intermediate- or high-risk MDS with thrombocytopenia.

Azacitidine treatment of myelodysplastic syndromes (MDSs) generally exacerbates thrombocytopenia during the first treatment cycles. A Study of Eltrombopag in Myelodysplastic Syndromes Receiving Azacitidine (SUPPORT), a phase 3, randomized, double-blind, placebo-controlled study, investigated the platelet supportive effects of eltrombopag given concomitantly with azacitidine. International Prognostic Scoring System intermediate-1, intermediate-2, or high-risk MDS patients with baseline platelets <75 × 109/L were randomized 1:1 to eltrombopag (start, 200 mg/d [East Asians, 100 mg/d], maximum, 300 mg/d [East Asians, 150 mg/d]) or placebo, plus azacitidine (75 mg/m2 subcutaneously once daily for 7 days every 28 days). The primary end point was the proportion of patients platelet transfusion-free during cycles 1 through 4 of azacitidine therapy. Based on planned interim analyses, an independent data monitoring committee recommended stopping the study prematurely because efficacy outcomes crossed the predefined futility threshold and for safety reasons. At termination, 28/179 (16%) eltrombopag and 55/177 (31%) placebo patients met the primary end point. Overall response (International Working Group criteria; complete, marrow, or partial response) occurred in 20% and 35% of eltrombopag and placebo patients, respectively, by investigator assessment. There was no difference in hematologic improvement in any cell lineage between the 2 arms. There was no improvement in overall or progression-free survival. Adverse events with ≥10% occurrence in the eltrombopag vs placebo arm were febrile neutropenia and diarrhea. Compared with azacitidine alone, eltrombopag plus azacitidine worsened platelet recovery, with lower response rates and a trend toward increased progression to acute myeloid leukemia. This trial was registered at www.clinicaltrials.gov as #NCT02158936.

The M4 insulator, the TM2 matrix attachment region, and the double copy of the heavy chain gene contribute to the enhanced accumulation of the PHB-01 antibody in tobacco plants.

The expression of recombinant proteins in plants is a valuable alternative to bioreactors using mammalian cell systems. Ease of scaling, and their inability to host human pathogens, enhance the use of plants to generate complex therapeutic products such as monoclonal antibodies. However, stably transformed plants expressing antibodies normally have a poor accumulation of these proteins that probably arise from the negative positional effects of their flanking chromatin. The induction of boundaries between the transgenes and the surrounding DNA using matrix attachment regions (MAR) and insulator elements may minimize these effects. With the PHB-01 antibody as a model, we demonstrated that the insertion of DNA elements, the TM2 (MAR) and M4 insulator, flanking the transcriptional cassettes that encode the light and heavy chains of the PHB-01 antibody, increased the protein accumulation that remained stable in the first plant progeny. The M4 insulator had a stronger effect than the TM2, with over a twofold increase compared to the standard construction. This effect was probably associated with an enhancer-promoter interference. Moreover, transgenic plants harboring two transcriptional units encoding for the PHB-01 heavy chain combined with both TM2 and M4 elements enhanced the accumulation of the antibody. In summary, the M4 combined with a double transcriptional unit of the heavy chain may be a suitable strategy for potentiating PHB-01 production in tobacco plants.

Multiplexed Biomarker Panels Discriminate Zika and Dengue Virus Infection in Humans.

Zika virus (ZIKV) and dengue virus (DENV) are closely related flaviviruses that cause widespread, acute febrile illnesses, notably microcephaly for fetuses of infected pregnant women. Detecting the viral cause of these illnesses is paramount to determine risks to patients, counsel pregnant women, and help fight outbreaks. A combined diagnostic algorithm for ZIKV and DENV requires Reverse transcription polymerase chain reaction (RT-PCR) and IgM antibody detection. RT-PCR differentiates between DENV and ZIKV infections during the acute phases of infection, but differentiation based on IgM antibodies is currently nearly impossible in endemic areas. We have developed a ZIKV/DENV protein array and tested it with serum samples collected from ZIKV- and DENV-infected patients and healthy subjects in Puerto Rico. Our analyses reveal a biomarker panel that are capable of discriminating ZIKV and DENV infections with high accuracy, including Capsid protein from African ZIKV strain MR766, and other 5 pair of proteins (NS1, NS2A, NS3, NS4B and NS5) from ZIKV and DENV respectively. Both sensitivity and specificity of the test for ZIKV from DENV are around 90%. We propose that the ZIKV/DENV protein array will be used in future studies to discriminate patients infected with ZIKV from DENV.

Cost-effectiveness of basic vision rehabilitation (The basic VRS-effect study): study protocol for a randomised controlled trial.

PURPOSE: To investigate the cost-effectiveness of a basic vision rehabilitation service (basic-VRS) in Portugal. We designed a parallel group, randomised controlled trial whose aim is to compare the effects and costs of 'usual low vision care' with a 'basic-VRS intervention' on self-reported visual ability and other psychosocial and health-related quality-of-life outcomes. METHODS: The trial will recruit participants that meet the following inclusion criteria: (1) visual acuity between 0.4-1.0 logMAR in the better-seeing eye, (2) cause of vision loss is diabetic retinopathy or age-related macular degeneration, (3) 18 years or older and iv) live in the community (not in nursing homes or other type of institution). Participants will be randomised to one of the study arms consisting of immediate intervention and delayed intervention. The delayed intervention group will receive 'usual care' or no intervention in the first 12 weeks. Visual acuity, contrast sensitivity and retinal structure will be assessed during the study. RESULTS: The primary outcome measure is visual ability, which will be evaluated with the Massof Activity Inventory, we expect that the intervention will raise the overall person measure or visual ability. Reading, health-related quality-of-life, anxiety and depression and social support will be also assessed. The analysis will be undertaken on an intention-to-treat basis. A cost-effectiveness analysis will be performed to provide information about the cost per unit of utility. To evaluate the cost-effectiveness of the intervention we will adopt the perspective of the healthcare system. CONCLUSION: This study will provide additional evidence about the effects of basic-VRS on self-reported visual ability. Findings from this study should also contribute to better planning of low vision provision and, consequently, may contribute to reduce barriers to basic-VRS.

Precipitated sdLDL: An easy method to estimate LDL particle size.

BACKGROUND: LDL-C lowering is the main measure in cardiovascular disease prevention but a residual risk of ischemic events still remains. Alterations of lipoproteins, specially, increase in small dense LDL (sdLDL) particles are related to this risk. OBJECTIVE: To investigate the potential use of sdLDL cholesterol concentration (sdLDL-C) isolated by an easy precipitation method and to assess the impact of a set of clinical and biochemical variables determined by NMR on sdLDL concentration. METHODS: sdLDL-C and NMR lipid profile were performed in 85 men samples. Association among them was evaluated using Pearson coefficients (rxy ). A multivariate regression was performed to identify the influence of NMR variables on sdLDL-C. RESULTS: A strong association between sdLDL-C and LDLLDL-P (rxy  = 0.687) and with LDL-Z (rxy  = -0.603) was found. The multivariate regression explained a 56.8% in sdLDL-C variation (P = 8.77.10-12). BMI, ApoB, triglycerides, FFA, and LDL-Z showed a significant contribution. The most important ones were ApoB and LDL-Z; a 1nm increase (LDL-Z) leads to decrease 126 nmol/L in sdLDL-C. CONCLUSION: The association between sdLDL-C, LDL-Z, and LDL-P is clear. From a large number of variables, especially LDL-Z and apoB influence on sdLDL-C. Results show that the smaller the LDL size, the higher their cholesterol concentration. Therefore, sdLDL-C determination by using this easy method would be useful to risk stratification and to uncover cardiovascular residual risk.

Genomic evaluation for novel stayability traits in Nellore cattle.

Cow stayability plays a major role on the overall profitability of the beef cattle industry, as it is directly related to reproductive efficiency and cow's longevity. Stayability (STAY63) is usually defined as the ability of the cow to calve at least three times until 76 months of age. This is a late-measured and lowly heritable trait, which consequently constrains genetic progress per time unit. Thus, the use of genomic information associated with novel stayability traits measured earlier in life will likely result in higher prediction accuracy and faster genetic progress for cow longevity. In this study, we aimed to compare pedigree-based and single-step GBLUP (ssGBLUP) methods as well as to estimate genetic correlations between the proposed stayability traits: STAY42, STAY53 and STAY64, which are measured at 52, 64 and 76 months of cow's age, considering at least 2, 3 and 4 calving, respectively. ssGBLUP yielded the highest prediction accuracy for all traits. The heritability estimates for STAY42, STAY53, STAY63 and STAY64 were 0.090, 0.151, 0.152 and 0.143, respectively. The genetic correlations between traits ranged from 0.899 (STAY42 and STAY53) to 0.985 (STAY53 and STAY63). The high genetic correlation between STAY42 and STAY53 suggests that besides being related to cow longevity, STAY53 is also associated with the early-stage reproductive efficiency. Thus, STAY53 is recommended as a suitable selection criterion for reproductive efficiency due to its higher heritability, favourable genetic correlation with other traits, and measured earlier in life, compared with the conventional stayability trait, that is STAY63.

Prediction of Sensory Parameters of Cured Ham: A Study of the Viability of the Use of NIR Spectroscopy and Artificial Neural Networks.

Dry-cured ham is a high-quality product owing to its organoleptic characteristics. Sensory analysis is an essential part of assessing its quality. However, sensory assessment is a laborious process which implies the availability of a trained tasting panel. The aim of this study was the prediction of dry-ham sensory characteristics by means of an instrumental technique. To do so, an artificial neural network (ANN) model for the prediction of sensory parameters of dry-cured hams based on NIR spectral information was developed and optimized. The NIR spectra were obtained with a fiber-optic probe applied directly to the ham sample. In order to achieve this objective, the neural network was designed using 28 sensory parameters analyzed by a trained panel for sensory profile analysis as output data. A total of 91 samples of dry-cured ham matured for 24 months were analyzed. The hams corresponded to two different breeds (Iberian and Iberian x Duroc) and two different feeding systems (feeding outdoors with acorns or feeding with concentrates). The training algorithm and ANN architecture (the number of neurons in the hidden layer) used for the training were optimized. The parameters of ANN architecture analyzed have been shown to have an effect on the prediction capacity of the network. The Levenberg-Marquardt training algorithm has been shown to be the most suitable for the application of an ANN to sensory parameters.

NIR Spectroscopy for Discriminating and Predicting the Sensory Profile of Dry-Cured Beef "Cecina".

For Protected Geographical Indication (PGI)-labeled products, such as the dry-cured beef meat "cecina de León", a sensory analysis is compulsory. However, this is a complex and time-consuming process. This study explores the viability of using near infrared spectroscopy (NIRS) together with artificial neural networks (ANN) for predicting sensory attributes. Spectra of 50 samples of cecina were recorded and 451 reflectance data were obtained. A feedforward multilayer perceptron ANN with 451 neurons in the input layer, a number of neurons varying between 1 and 30 in the hidden layer, and a single neuron in the output layer were optimized for each sensory parameter. The regression coefficient R squared (RSQ > 0.8 except for odor intensity) and mean squared error of prediction (MSEP) values obtained when comparing predicted and reference values showed that it is possible to predict accurately 23 out of 24 sensory parameters. Although only 3 sensory parameters showed significant differences between PGI and non-PGI samples, the optimized ANN architecture applied to NIR spectra achieved the correct classification of the 100% of the samples while the residual mean squares method (RMS-X) allowed 100% of non-PGI samples to be distinguished.