Insights Into Preaggregation Control of Y-Series Nonfullerene Acceptors in Liquid State for Highly Efficient Binary Organic Solar Cells.

Leveraging breakthroughs in Y-series nonfullerene acceptors (NFAs), organic solar cells (OSCs) have achieved impressive power conversion efficiencies (PCEs) exceeding 19%. However, progress in advancing OSCs has decelerated due to constraints in realizing the full potential of the Y-series NFAs. Herein, a simple yet effective solid additive-induced preaggregation control method employing 2-chloro-5-iodopyridine (PDCI) is reported to unlock the full potential of the Y-series NFAs. Specifically, PDCI interacts predominantly with Y-series NFAs enabling enhanced and ordered phase-aggregation in solution. This method leads to a notable improvement and a redshifted absorption of the acceptor phase during film formation, along with improved crystallinity. Moreover, the PDCI-induced preaggregation of NFAs in the solution enables ordered molecule packing during the film-formation process through delicate intermediate states transition. Consequently, the PDCI-induced preaggregated significantly improves the PCE of PM6:Y6 OSCs from 16.12% to 18.12%, among the best values reported for PM6:Y6 OSCs. Importantly, this approach is universally applicable to other Y-series NFA-based OSCs, achieving a champion PCE of 19.02% for the PM6:BTP-eC9 system. Thus, the preaggregation control strategy further unlocks the potential of Y-series NFAs, offering a promising avenue for enhancing the photovoltaic performance of Y-series NFA-based OSCs.

Effects of meteorology and lunar cycle on the post-thawing quality of avian sperm.

Introduction: Various climatological and lunar cycle parameters have a direct impact on animal reproduction, and in the case of the avian species, spermatozoa are extremely sensitive to heat stress. These parameters could influence sperm freezability, which will ultimately affect post-thawing semen quality, being sperm motility in roosters a relevant indicator of this quality as it is highly related to fertility. Therefore, the objective of the present study is to determine which are the climatological and lunar cycle parameters that have a greater effect on sperm freezability in roosters. Methods: Sperm was obtained from 16 Utrerana breed roosters and a total of 27 replicates were performed. A pool was made with those ejaculates that met the minimum quality criteria for each replicate, and four freezing-thawing samples per replicate were analyzed. The straws were thawed, and sperm motility was evaluated, classifying the results obtained into four seminal quality groups according to the guidelines of the Food and Agriculture Organization of the United Nations (Group 1: Good, Group 2: Satisfactory, Group 3: Acceptable but undesirable and Group 4: Unsatisfactory). The following traits were recorded for each day of semen collection: maximum temperature, minimum temperature, maximum barometric pressure, minimum barometric pressure, maximum gust, wind direction, mean wind speed, sunshine hours, rainfall, moon phase, and percentage of illuminated lunar surface over the total area. Results: A discriminant canonical analysis was performed to determine which of these parameters offered the most information when classifying an ejaculate in each quality group, with minimum temperature, the new moon as moon phase, minimum barometric pressure, and rainfall being the most significant variables. Discussion: According to the results obtained, semen quality decreases when temperature and precipitation are lower, pressure is higher, and when there is a new moon phase. Therefore, these environmental conditions should be avoided for sperm collection and processing.

Analysis of Endangered Andalusian Black Cattle (Negra Andaluza) Reveals Genetic Reservoir for Bovine Black Trunk.

This comprehensive study on the Andalusian Black cattle breed reveals a substantial population decline, with the average herd size decreasing significantly from 305.54 to 88.28 animals per herd. This decline is primarily attributed to agricultural changes and the introduction of foreign meat-focused breeds. The male-to-female ratio shift is noteworthy, with more cows than bulls, impacting selection intensity for both genders. Inbreeding levels, though relatively low historically (5.94%) and currently (7.23%), raise concerns as 37.08% historically and 48.82% currently of the animals exhibit inbreeding. Positive assortative mating is evident, reflected by the increasing non-random mating coefficient (α). Key ancestors play a crucial role in shaping genetic diversity, with one ancestor significantly influencing the current genetic pool and the top 10 ancestors contributing substantially. Breed maintains a conservation index of 2.75, indicating relatively high genetic diversity. Recent conservation efforts have led to an increase in registered animals. The Cañadas Reales, historical transhumance routes, may have contributed to genetic connections among provinces. Challenges include the historical bottleneck, demographic changes, and potential impacts from reproductive practices. The Andalusian Black breed's conservation necessitates ongoing efforts in genealogical registration, targeted breeding programs, and collaborative initiatives to address the observed demographic shifts and ensure sustainable genetic diversity.

Discriminant canonical analysis as a tool for genotype traceability testing based on turkey meat and carcass traits.

The present study aims to develop a statistical tool for turkey breed traceability testing based on meat and carcass quality characteristics. To this end, a comprehensive meta-analysis was performed, collecting data from a total of 75 studies approaching meat and carcass attributes of 37 turkey strains and landraces since the late 1960s. A total of 22 meat and carcass traits were considered variables, grouped in the following clusters: carcass dressing traits, muscle fiber properties, pH, colorimetry, water-capacity traits, texture-related attributes, and nutritional composition of the meat. Once the multicollinearity analysis allowed the deletion of redundant variables, cold carcass weight, slaughter weight, muscle fiber diameter, sex-female, carcass/piece weight, meat redness, ashes, pH24, meat lightness, moisture, fat, and water-holding capacity showed explanatory properties in the discriminating analysis (p < 0.05). In addition, strong positive and negative correlations were found among those variables studied. Carcass traits were positively associated, particularly slaughter weight and cold carcass weight (+0.561). Among meat physical traits, pH showed positive correlations with drip loss (+0.490) and pH24 (+0.327), and water-holding capacity was positively associated with cholesterol (+0.434) and negatively associated with collagen (-0.398). According to nutritional traits, fat and ash showed a strong correlation (+0.595), and both were negatively associated with moisture (-0.375 and -0.498, respectively). Strong negative correlations were found as well between meat protein and fat (-0.460) and between collagen and cholesterol (-0.654). Finally, the Mahalanobis distance suggested a clustering pattern based on meat and carcass characteristics that report information about interbreeding and variety proximity. This study establishes a departure point in the development of a tool for breed traceability guaranteeing aimed at enhancing distinguished, local breed-based turkey meat.

Modeling Climate Change Effects on Genetic Diversity of an Endangered Horse Breed Using Canonical Correlations.

The historical increase in the occurrence of extreme weather events in Spain during the last thirty years makes it a perfect location for the evaluation of climate change. Modeling the effects of climate change on domestic animals' genetic diversity may help to anticipate challenging situations. However, animal populations' short life cycle and patent lack of historical information during extended periods of time drastically compromise the evaluation of climate change effects. Locally adapted breeds' gene pool is the base for their improved resilience and plasticity in response to climate change's extreme climatic conditions. The preservation of these domestic resources offers selection alternatives to breeders who seek such improved adaptability. The Spanish endangered autochthonous Hispano-Arabian horse breed is perfectly adapted to the conditions of the territory where it was created, developed, and widespread worldwide. The possibility to trace genetic diversity in the Hispano-Arabian breed back around seven decades and its global ubiquity make this breed an idoneous reference subject to act as a model for other international populations. Climate change's shaping effects on the genetic diversity of the Hispano-Arabian horse breed's historical population were monitored from 1950 to 2019 and evaluated. Wind speed, gust speed, or barometric pressure have greater repercussions than extreme temperatures on genetic diversity. Extreme climate conditions, rather than average modifications of climate, may push breeders/owners to implement effective strategies in the short to medium term, but the effect will be plausible in the long term due to breed sustainability and enhanced capacity of response to extreme climate events. When extreme climatic conditions occur, breeders opt for mating highly diverse unrelated individuals, avoiding the production of a large number of offspring. People in charge of domestic population conservation act as catalyzers of the regulatory changes occurring during breeds' climate change adaptive process and may identify genes conferring their animals with greater adaptability but still maintaining enhanced performance. This model assists in determining how owners of endangered domestic populations should plan their breeding strategies, seeking the obtention of animals more resilient and adapted to climate-extreme conditions. This efficient alternative is focused on the obtention of increased profitability from this population and in turn ensuring their sustainability.

Evaluation of the effect of the addition of an olive oil-derived antioxidant (Pectoliv-80A) in the extender for cryopreservation of rooster sperm through the use of a discriminant statistical tool.

During the poultry sperm cryopreservation process, an excess of reactive oxygen species is generated resulting in oxidative stress which harms the quality of avian spermatozoa. To counteract this effect, the addition of exogenous antioxidants, such as Pectoliv-80A (a by-product of olive oil), to the cryopreservation diluent is interesting. For this purpose, 16 roosters belonging to the Utrerana avian breed were used. Six semen pools (from the 6 different replicates) were divided into 4 aliquots corresponding to different concentrations of Pectoliv-80A that were tested (0, 300, 400, and 500 µg/mL), and the cryopreservation process was carried out. To evaluate post-thawing semen quality, different parameters such as motility, membrane functionality, reactive oxygen species production, lipid peroxidation, and acrosome integrity were studied. A discriminant canonical analysis was used to determine both the differences between the Pectoliv-80A concentration groups and the discriminant power of the aforementioned parameter used for semen evaluation. Total motility and membrane functionality were reported to be the most discriminant variables for differentiating the different antioxidant enrichment groups and concluded that concentrations of 300 µg/mL showed the most desirable quality of post-thawing semen. The present study could lead to the optimization of both cryopreservation and quality evaluation techniques of the sperm of rooster species, that support the conservation program of endangered local breeds.

Identification of novel biomarkers in the early diagnosis of malignant melanoma by untargeted liquid chromatography coupled to high-resolution mass spectrometry-based metabolomics: a pilot study.

BACKGROUND: Malignant melanoma (MM) is a highly aggressive form of skin cancer whose incidence continues to rise worldwide. If diagnosed at an early stage, it has an excellent prognosis, but mortality increases significantly at advanced stages after distant spread. Unfortunately, early detection of aggressive melanoma remains a challenge. OBJECTIVES: To identify novel blood-circulating biomarkers that may be useful in the diagnosis of MM to guide patient counselling and appropriate disease management. METHODS: In this study, 105 serum samples from 26 healthy patients and 79 with MM were analysed using an untargeted approach by liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) to compare the metabolomic profiles of both conditions. Resulting data were subjected to both univariate and multivariate statistical analysis to select robust biomarkers. The classification model obtained from this analysis was further validated with an independent cohort of 12 patients with stage I MM. RESULTS: We successfully identified several lipidic metabolites differentially expressed in patients with stage I MM vs. healthy controls. Three of these metabolites were used to develop a classification model, which exhibited exceptional precision (0.92) and accuracy (0.94) when validated on an independent sample. CONCLUSIONS: These results demonstrate that metabolomics using LC-HRMS is a powerful tool to identify and quantify metabolites in bodily fluids that could serve as potential early diagnostic markers for MM.

Melanoma is a type of skin cancer that can be deadly if it is not detected at an early stage. Unfortunately, the early detection of melanoma is challenging. Our team has developed a model that could be used to predict whether a person has stage I malignant melanoma based on blood serum analysis. The model was trained on data from a group of people with melanoma and it was found to be accurate in predicting melanoma at an early stage. This means that the model could be used to identify people who have skin cancer before it progresses and becomes more complicated to treat. Although the researchers recommend that further studies are conducted to validate the model in a larger population of people, this research could help with the early diagnosis of melanoma and work toward improving survival rates.

Discriminant Analysis and Data Mining CHAID Decision Tree as Tools to Evaluate the Buffering Effect of Hydroxytyrosol on Reactive Oxygen Species in Rooster Sperm Cryopreservation.

Sperm cryopreservation is effective in safeguarding genetic biodiversity in avian species. However, during this process, spermatozoa are very susceptible to plasma membrane peroxidation in the presence of high concentrations of reactive oxygen species (ROS). To mitigate this effect, the addition of exogenous antioxidants, such as hydroxytyrosol (3,4-dihydroxyphenylethanol; HT), an antioxidant derived from olive oil, to the cryopreservation sperm diluent, could be useful. To verify this, a cryopreservation diluent was supplemented with different concentrations (0 µg/mL, 50 µg/mL, 100 µg/mL, and 150 µg/mL) of HT. For this, semen was collected in 10 replicates from 16 roosters of the Utrerana avian breed, and a pool was prepared with the optimum quality ejaculates in each replicate. After cryopreservation, spermatozoa were thawed and different in vitro semen quality parameters were evaluated. A discriminant canonical analysis (DCA) was carried out and revealed that total motility (TM; Lambda = 0.301, F = 26,173), hypo-osmotic swelling test (HOST; Lambda = 0.338, F = 22,065), and amplitude of lateral head displacement (ALH, Lambda = 0.442; F = 14,180) were the variables with the highest discriminant power. Finally, a chi-squared automatic interaction detection (CHAID) decision tree (DT) was performed excluding fresh semen samples and ROS was found to be the most valuable variable to discriminate between the different established freezing groups. Samples in the absence of HT or with low concentrations of this antioxidant showed less desirable ROS values in cryopreserved rooster semen. The present study could lead to the improvement of cryopreservation techniques for the genetic material of local poultry breeds and optimize the conservation programs of endangered native avian breeds.

Study of Meat and Carcass Quality-Related Traits in Turkey Populations through Discriminant Canonical Analysis.

The present research aimed to determine the main differences in meat and carcass quality traits among turkey genotypes worldwide and describe the clustering patterns through the use of a discriminant canonical analysis (DCA). To achieve this goal, a comprehensive meta-analysis of 75 documents discussing carcass and meat characteristics in the turkey species was performed. Meat and carcass attributes of nine different turkey populations were collected and grouped in terms of the following clusters: carcass dressing traits, muscle fiber properties, pH, color-related traits, water-retaining characteristics, texture-related traits, and meat chemical composition. The Bayesian ANOVA analysis reported that the majority of variables statistically differed (p < 0.05), and the multicollinearity analysis revealed the absence of redundancy problems among variables (VIF < 5). The DCA reported that cold carcass weight, slaughter weight, sex-male, carcass/piece weight, and the protein and fat composition of meat were the traits explaining variability among different turkey genotypes (Wilks' lambda: 0.488, 0.590, 0.905, 0.906, 0.937, and 0.944, respectively). The combination of traits in the first three dimensions explained 94.93% variability among groups. Mahalanobis distances cladogram-grouped populations following a cluster pattern and suggest its applicability as indicative of a turkey genotype's traceability.

Prediction models using artificial intelligence and longitudinal data from electronic health records: a systematic methodological review.

OBJECTIVE: To describe and appraise the use of artificial intelligence (AI) techniques that can cope with longitudinal data from electronic health records (EHRs) to predict health-related outcomes. METHODS: This review included studies in any language that: EHR was at least one of the data sources, collected longitudinal data, used an AI technique capable of handling longitudinal data, and predicted any health-related outcomes. We searched MEDLINE, Scopus, Web of Science, and IEEE Xplorer from inception to January 3, 2022. Information on the dataset, prediction task, data preprocessing, feature selection, method, validation, performance, and implementation was extracted and summarized using descriptive statistics. Risk of bias and completeness of reporting were assessed using a short form of PROBAST and TRIPOD, respectively. RESULTS: Eighty-one studies were included. Follow-up time and number of registers per patient varied greatly, and most predicted disease development or next event based on diagnoses and drug treatments. Architectures generally were based on Recurrent Neural Networks-like layers, though in recent years combining different layers or transformers has become more popular. About half of the included studies performed hyperparameter tuning and used attention mechanisms. Most performed a single train-test partition and could not correctly assess the variability of the model's performance. Reporting quality was poor, and a third of the studies were at high risk of bias. CONCLUSIONS: AI models are increasingly using longitudinal data. However, the heterogeneity in reporting methodology and results, and the lack of public EHR datasets and code sharing, complicate the possibility of replication. REGISTRATION: PROSPERO database (CRD42022331388).

Discriminant canonical tool for inferring the effect of αS1, αS2, ß, and κ casein haplotypes and haplogroups on zoometric/linear appraisal breeding values in Murciano-Granadina goats.

Genomic tools have shown promising results in maximizing breeding outcomes, but their impact has not yet been explored. This study aimed to outline the effect of the individual haplotypes of each component of the casein complex (αS1, ß, αS2, and κ-casein) on zoometric/linear appraisal breeding values. A discriminant canonical analysis was performed to study the relationship between the predicted breeding value for 17 zoometric/linear appraisal traits and the aforementioned casein gene haplotypic sequences. The analysis considered a total of 41,323 zoometric/linear appraisal records from 22,727 primiparous does, 17,111 multiparous does, and 1,485 bucks registered in the Murciano-Grandina goat breed herdbook. Results suggest that, although a lack of significant differences (p > 0.05) was reported across the predictive breeding values of zoometric/linear appraisal traits for αS1, αS2, and κ casein, significant differences were found for ß casein (p < 0.05). The presence of ß casein haplotypic sequences GAGACCCC, GGAACCCC, GGAACCTC, GGAATCTC, GGGACCCC, GGGATCTC, and GGGGCCCC, linked to differential combinations of increased quantities of higher quality milk in terms of its composition, may also be connected to increased zoometric/linear appraisal predicted breeding values. Selection must be performed carefully, given the fact that the consideration of apparently desirable animals that present the haplotypic sequence GGGATCCC in the ß casein gene, due to their positive predicted breeding values for certain zoometric/linear appraisal traits such as rear insertion height, bone quality, anterior insertion, udder depth, rear legs side view, and rear legs rear view, may lead to an indirect selection against the other zoometric/linear appraisal traits and in turn lead to an inefficient selection toward an optimal dairy morphological type in Murciano-Granadina goats. Contrastingly, the consideration of animals presenting the GGAACCCC haplotypic sequence involves also considering animals that increase the genetic potential for all zoometric/linear appraisal traits, thus making them recommendable as breeding animals. The relevance of this study relies on the fact that the information derived from these analyses will enhance the selection of breeding individuals, in which a desirable dairy type is indirectly sought, through the haplotypic sequences in the ß casein locus, which is not currently routinely considered in the Murciano-Granadina goat breeding program.

Analysis of the Genetic Parameters for Dairy Linear Appraisal and Zoometric Traits: A Tool to Enhance the Applicability of Murciano-Granadina Goats Major Areas Evaluation System.

Selection for zoometrics defines individuals' productive longevity, endurance, enhanced productive abilities and consequently, their long-term profitability. When zoometric analysis is aimed at large highly selected populations or in those at different levels of selection, linear appraisal systems (LAS) provide a timely response. This study estimates genetic and phenotypic parameters for zoometric/LAS traits in Murciano-Granadina goats, estimating genetic and phenotypic correlations among all traits, and determining whether major area selection would be appropriate or if adaptability strategies may need to be followed. Heritability estimates for the zoometric/LAS traits were low to high, ranging from 0.09 to 0.43, and the accuracy of estimation has improved after decades, rendering standard errors negligible. Scale inversion of specific traits may need to be performed before major areas selection strategies are implemented. Genetic and phenotypic correlations suggests that negative selection against thicker bones and higher rear insertion heights indirectly results in the optimization of selection practices in the rest of the traits, especially those in the structure, capacity and mammary system major areas. The integration and implementation of the strategies proposed within the Murciano-Granadina breeding program maximizes selection opportunities and the sustainable international competitiveness of the Murciano-Granadina goat in the dairy goat breed panorama.

Design and Validation of a Test to Evaluate the Execution Time and Decision-Making in Technical-Tactical Football Actions (Passing and Driving).

Reaction time and decision-making (DMA) in football have usually been evaluated using edited images or videos of game situations. The purpose of this research is to design and validate a test that simultaneously evaluates execution time (ET) and decision-making (DMA) in the subcategories of type of action (TA) and direction of movement (DM). METHODOLOGY: A quantitative, cross-sectional, and descriptive study of 30 young players. A total of 32 stimuli were programmed, corresponding to 64 responses, from which the total index (TI) was obtained from the division between DMA and ET. RESULTS: The content validity index (CVI = 0.78) showed a high degree of consensus among experts. In the validation process, the intraclass correlation coefficient (ICC) was used to assess intraclass and interobserver reliability, and a moderate level of agreement was found between subjects for the TA (ICC = 0.593) and ET (ICC = 0.602) and a moderate high level of concordance for DM (ICC = 0.804) and TI (ICC = 0.855). Regarding interobserver reliability, an excellent level of agreement was found for all variables: TA (ICC = 0.998), DM (ICC = 0.998), ET (ICC = 1.000), and TI (ICC = 1.000). For the relationship between intraobserver and interobserver variables, statistical significance was established as p < 0.01. Finally, the intraobserver ETM (5.40%) and interobserver ETM (0.42%) was low compared with the reference value (5.9%). CONCLUSION: The designed test meets the validity criteria since the variables show sufficient intraclass reliability (test-retest) and reliability among observers.

Analysis of Sports Supplement Consumption in 1688 Federated Road Cyclists.

The widespread use of sports supplements (SS) to enhance athletic performance extends to cyclists, although little research has been conducted on this subject within this sport. This descriptive and cross-sectional study involved 1688 federated road cyclists, aiming to analyse the pattern of SS consumption concerning the degree of scientific evidence and different categories. This study categorised SS based on the groups and subgroups established by the Australian Sport Institute (AIS, 2023) based on the level of evidence. Our results showed that 62.5% of the sample cyclists used SS, with an average of 12.2 ± 8.6 supplements consumed per participant. Health status (78.2%), pharmacies (62.5%), and medical doctors (45.7%) were the main reasons, purchase sites, and sources of information for SS consumption, respectively. The most prevalent SS consumed were Sports Gels (94%), Sports Bars (89.3%), and Sports Drinks (73.8%). Notably, 80% of the top ten most consumed SS belonged to the group with the highest level of evidence according to the AIS, with an average of 6.9 ± 3.2 supplements per participant. However, 23.3% of the total SS consumers used prohibited substances. In conclusion, while the prevalence of SS consumption among road cyclists is considerable and the primary sources for purchasing SS and obtaining advice are reliable, there is a notable prevalence of prohibited substance use within the sample.

Discriminant Canonical Analysis as a tool to determine traces of endangered native hen breed introgression through egg hatchability phenomics.

Objective: The main objective of this study was to develop a pipeline to detect phenogenomic introgression across different multivariety breeds and to validate such classification focusing on external egg and hatchability-related traits using a discriminant canonical analysis approach. Methods: For this, 1368 eggs belonging a flock of 94 endangered Spanish autochthonous breed breeding hens (Andalusian Tufted, Blue Andalusian, Spanish White-Faced, and Utrerana) and a control outgroup comprising 32 eggs belonging to 4 Araucana hens were considered. Multicollinearity analysis of hatchability-related traits revealed embryonic mortality, embryonic mortality in the second stage of incubation, viable hatching chick, major diameter, and minor diameter should be discarded from the analysis (VIF≤5) given they did not significantly contribute to variability explanation potential of the discriminant model. Results: A stepwise discriminant canonical analysis was developed and egg weight, shape index, hatchability, and fertility variables reported the highest discriminant power (Wilks' Lambda values of 0.7861, 0.7871, 0.8076, and 0.9457, respectively). The first two functions explained 85.25% intergroup variability. Interbreed and varieties proximity was evaluated using Mahalanobis distances representation and data mining cross-validation allowed to detect genetic introgression between different genotypes. Conclusion: Easily collectable traits as egg weight and shape index must be considered for the development of breeding programs as a measure to ensure breed protection. The model may be translatable to other endangered breeds to optimize avian breeds conservation plans worldwide.

Bayesian evaluation of the effect of non-genetic factors on the phenomics for quality-related milk nutrients and yield in Murciano-Granadina goats.

The aim of this study was to evaluate the effect of non-genetic factors on the variability of milk production and composition using Bayesian linear regression. We analyzed 2594 milk records from 159 dairy goats from the breeding nucleus of the Murciano-Granadina breed. Bayesian linear regression was used to determine the effects of non-genetic factors on the phenomics for quality-related milk nutrients and yield. Multivariate regression model significantly explained 21.5%, 40.0%, 41.5%, 44.3%, 44.6%, and 47.5% of the variability in somatic cell count (SCC, sc/mL), lactose (%), protein (%), milk yield (kg), fat (%), and dry matter (%), respectively. Although the aforementioned factor combination significantly conditions milk production and composition, SCC may be particularly affected by collateral factors. Milking routine and drying period factors are reference predictors to be considered in the evaluation of milk production and composition progression. Drying period extensions positively repercussed on milk yield and lactose content, but negatively affected fat, protein, dry matter contents, and somatic cell count. Variability across drying years may depend on the drying season rather than the drying month course, except for milk yield, for which an increasing trend was reported from winter to summer. Including drying period-related non-genetic factors in genetic evaluations improves the accuracy of the regression models and permits to boost the commercial possibilities and profitability of local breeds.

Data Mining as a Tool to Infer Chicken Carcass and Meat Cut Quality from Autochthonous Genotypes.

The present research aims to develop a carcass quality characterization methodology for minority chicken populations. The clustering patterns described across local chicken genotypes by the meat cuts from the carcass were evaluated via a comprehensive meta-analysis of ninety-one research documents published over the last 20 years. These documents characterized the meat quality of native chicken breeds. After the evaluation of their contents, thirty-nine variables were identified. Variables were sorted into eight clusters as follows; weight-related traits, water-holding capacity, colour-related traits, histological properties, texture-related traits, pH, content of flavour-related nucleotides, and gross nutrients. Multicollinearity analyses (VIF ≤ 5) were run to discard redundancies. Chicken sex, firmness, chewiness, L* meat 72 h post-mortem, a* meat 72 h post-mortem, b* meat 72 h post-mortem, and pH 72 h post-mortem were deemed redundant and discarded from the study. Data-mining chi-squared automatic interaction detection (CHAID)-based algorithms were used to develop a decision-tree-validated tool. Certain variables such as carcass/cut weight, pH, carcass yield, slaughter age, protein, cold weight, and L* meat reported a high explanatory potential. These outcomes act as a reference guide to be followed when designing studies of carcass quality-related traits in local native breeds and market commercialization strategies.

Data mining-based discriminant analysis as a tool for the study of egg quality in native hen breeds.

Despite the wide biodiversity of avian species of zootechnical interest in Spain, projects aimed at characterizing these genotypes and their products are necessary. External and internal egg quality traits were measured in 819 eggs laid by hens of 10 different genotypes: White, Franciscan, Black and Partridge varieties of Utrerana, Blue Andalusian, Spanish White-Faced, Andalusian Tufted White and Black varieties, Araucana; and Leghorn Lohmann LSL-Classic lineage (commercial hybrid line) hen breeds. After multicollinearity analysis of egg quality-related traits was performed (VIF ≤ 4), major diameter, minor diameter, egg weight, and albumen height were deemed redundant explanatory variables and discarded. A stepwise discriminant canonical analysis was developed to cluster eggs across hen genotypes considering egg quality attributes. Shell a* and b* variables reported the highest discriminant power (Wilks' lambda: 0.699 and 0.729, respectively). The first two discriminant functions captured 60.48% of the variance across groups (F1: 39.36%; F2: 21.12%). Clear quality differentiation signs are evidenced for Mediterranean native breeds' eggs when compared to Leghorn's eggs. Consequently, this evidence of egg quality differentiation may favor the standardization of breed- and variety-linked distinctive products, which may open new market opportunities based on the existence of a wide spectrum of diet or culinary applications.

Can the Supido Radar Be Used for Measuring Ball Speed during Soccer Kicking? A Reliability and Concurrent Validity Study of a New Low-Cost Device.

The aim was to analyze the reliability and validity of a low-cost instrument, based on a radar system, to quantify the kicking ball speed in soccer. A group of 153 male soccer players (under-13, n = 53; under-15, n = 54; under-18, n = 46) participated in this study. Each player performed three kicks on the goal in a standardized condition while the ball speed was measured with three different devices: one Radar Stalker ATS II® (reference criterion) and two Supido Radar® (Supido-front of the goal and Supido-back of the goal). The standard error of measurement (SEM) expressed as a coefficient of variation (CV) and the intraclass correlation coefficient (ICC) were employed for assessing the reliability of each instrument. Stalker and Supido-back showed very high absolute (CV = 4.0-5.4%) and relative (ICC = 0.945-0.958) reliability, whereas Supido-front resulted in moderate to low reliability scores (CV = 7.4-15%, ICC = 0.134-0.693). In addition, Lin's concordance correlation coefficient (CCC) values revealed an 'almost perfect' agreement between Stalker and Supido-back for the average (r = 0.99) and maximal (r = 0.98) ball speed, regardless of the ball speed range analyzed. However, Supido-front resulted in a poor degree of concordance (CCC = 0.688) and a high magnitude of error (17.0-37.5 km·h-1) with the reference Stalker radar gun. The Supido Radar® placed behind the goal could be considered a reliable and valid device for measuring ball speed in soccer.

Treatment of Metastatic Melanoma at First Diagnosis: Review of the Literature.

Metastatic melanoma (MM) is a pathological entity with a very poor prognosis that, until a few decades ago, had a low response rate to systemic treatments. Fortunately, in the last few years, new therapies for metastatic melanoma have emerged. Currently, targeted therapy and immunotherapy are the mainstays of the therapeutic arsenal available for patients with unresectable or metastatic melanoma. However, both clinical evolution and drug efficacy in melanoma patients are very different depending on the stage at which it is diagnosed. In fact, the aggressiveness of melanoma is different depending on whether it debuts directly as metastatic disease or if what occurs is a relapse after a first diagnosis at an early stage, although the biological determinants are largely unknown. Another key aspect in the clinical management of metastatic melanoma at first diagnosis strives in the different prognosis of melanoma of unknown primary (MUP) compared to melanoma of known primary (MPK). Understanding the mechanisms behind this, and the repercussion of implementing targeted and immune therapies in this specific form is crucial for designing diagnosis and treatment decision algorithms that optimize the current strategies. In this review article, we recapitulate the information available thus far regarding the epidemiology and response to immunotherapy treatments or targeted therapy in patients diagnosed with metastatic melanoma as a first diagnosis, with especial emphasis on the emerging specific information of the subpopulation formed by MUP patients.