EFFECT OF SPECIFIC ENDURANCE ON THE PHYSICAL RESPONSES OF YOUNG ATHLETES DURING SOCCER SMALL-SIDED GAMES

This study aimed to compare the physical responses of soccer players with different levels of specific endurance during SSG performed by teams balanced according to athletes’ specific endurance. Eighteen U-17 athletes from a team that participated in national competitions took part in this study. The Yo-Yo Intermittent Recovery Test Level 2 (YIRT2) was used to measure the athletes’ specific endurance. Then, athletes were allocated to two groups balanced according to their positional status and YIRT2 scores: in Group1 players with the highest results in the YIRT2 and in Group 2 with the lower YIRT2 scores. Athletes played twofour-minute bou ts of 3vs.3 small-sided games with goalkeepers with four minutes of passive rest. Total distance covered, average speed, and accelerations were obtained by GPS devices carried by each player. Group 1 presented higher total distance covered (large effect size), higher average speed (large effect size), and higher total distance covered in accelerations above 1 m·s-2 (moderate effect size), compared to Group 2. We concluded that specific endurance can partially influence physical responses of young soccer athletes during small-sided games. This information is important to appropriately prescribe small-sided games during the training process, possibly by grouping together athletes with similar specific endurance and, therefore, promoting an adequate stimulus to better-conditioned athletes.Key words: Yo-Yo Test, motor profile, Global Positioning System, acceleration demand</p

Chromosomal painting of the sandpiper (Actitis macularius) detects several fissions for the Scolopacidae family (Charadriiformes).

BACKGROUND: The Scolopacidae family (Suborder Scolopaci, Charadriiformes) is composed of sandpipers and snipes; these birds are long-distance migrants that show great diversity in their behavior and habitat use. Cytogenetic studies in the Scolopacidae family show the highest diploid numbers for order Charadriiformes. This work analyzes for the first time the karyotype of Actitis macularius by classic cytogenetics and chromosome painting. RESULTS: The species has a diploid number of 92, composed mostly of telocentric pairs. This high 2n is greater than the proposed 80 for the avian ancestral putative karyotype (a common feature among Scolopaci), suggesting that fission rearrangements have formed smaller macrochromosomes and microchromosomes. Fluorescence in situ hybridization using Burhinus oedicnemus whole chromosome probes confirmed the fissions in pairs 1, 2, 3, 4 and 6 of macrochromosomes. CONCLUSION: Comparative analysis with other species of Charadriiformes studied by chromosome painting together with the molecular phylogenies for the order allowed us to raise hypotheses about the chromosomal evolution in suborder Scolopaci. From this, we can establish a clear idea of how chromosomal evolution occurred in this suborder

Chromosomal painting in Charadrius collaris Vieillot, 1818 and Vanellus chilensis Molina, 1782 and an analysis of chromosomal signatures in Charadriiformes.

Charadriiformes represent one of the largest orders of birds; members of this order are diverse in morphology, behavior and reproduction, making them an excellent model for studying evolution. It is accepted that the avian putative ancestral karyotype, with 2n = 80, remains conserved for about 100 million years. So far, only a few species of Charadriiformes have been studied using molecular cytogenetics. Here, we performed chromosome painting on metphase chromosomes of two species of Charadriidae, Charadrius collaris and Vanellus chilensis, with whole chromosome paint probes from Burhinus oedicnemus. Charadrius collaris has a diploid number of 76, with both sex chromosomes being submetacentric. In V. chilensi a diploid number of 78 was identified, and the Z chromosome is submetacentric. Chromosome painting suggests that chromosome conservation is a characteristic common to the family Charadriidae. The results allowed a comparative analysis between the three suborders of Charadriiformes and the order Gruiformes using chromosome rearrangements to understand phylogenetic relationships between species and karyotypic evolution. However, the comparative analysis between the Charadriiformes suborders so far has not revealed any shared rearrangements, indicating that each suborder follows an independent evolutionary path, as previously proposed. Likewise, although the orders Charadriiformes and Gruiformes are placed on sister branches, they do not share any signature chromosomal rearrangements

SYSTEMATIC MAPPING OF QUALITY OF LIFE INDICATORS: Englishan analysis of dimensions for the Brazilian Amazon

A Amazônia é vislumbrada conjuntamente como um espaço onde emergem as mais diversas diferenças, tanto dentro como fora da região. Estabelecer formas de medir essas diversidades pelo prisma da qualidade de vida e bem-estar de suas populações é uma iniciativa urgente a ser satisfeita. Assim, este artigo apresenta a aplicação da metodologia PICOC para mapeamento dos indicadores das ações que representam a qualidade de vida e bem-estar da população da Amazônia brasileira. Foi realizado um mapeamento sistemático em cinco bases científicas para mapear os trabalhos publicados no período de 2017 a 2021. Como resultados, foram encontrados 31 índices relacionados à qualidade de vida e bem-estar dispostos nas dimensões de meio ambiente, saúde,educação, governança, programas sociais e renda. As dimensões de meio ambiente, saúde, educação, governança e programas sociais e renda são as principais recorrências. Os achados permitiram como contribuições: (i) quantificar e qualificar os trabalhos, listando suas fontes, ano de publicação, área de aplicação e repositório de origem; (ii) identificar as dimensões mais recorrentes dos indicadores encontrados; (iii) relacionar os índices às quantidades de dimensões que os compõem.The Amazon has been jointly glimpsed as a space where a wide range of differences emerge, both within and outside the region. Establishing ways to measure these diversities through the prism of the quality of life and well-being of their populations is an urgent initiative to be satisfied. Thus, this article presents the application of the PICOC methodology for mapping the indicators from the actions that represent the quality of life and welfare of the population of the Brazilian Amazon. A systematic mapping was carried out in five scientific databases in order to map works published in the period from 2017 to 2021. As results, 31 indices related to quality of life and well-being were found arranged in the dimensions of environment, health, education, governance, social programs, and income. The dimensions of environment, health, education, governance, and social programs and income are the main recurrences. The findings allowed as contributions: (i) quantify and qualify the works, listing their sources, year of publication, area of application and repository of origin; (ii) identify the most recurrent dimensions of the indicators found; (iii) relate the indexes to the quantities of dimensions that compose them.La Amazonía se ha vislumbrado en conjunto como un espacio donde emerge una amplia gama de diferencias, tanto dentro como fuera de la región. Establecer formas de medir estas diversidades através del prisma de la calidad de vida y el bienestar de sus poblaciones es una iniciativa urgente a ser satisfecha. Así, este artículo presenta la aplicación de la metodología PICOC para el mapeo de los indicadores de las acciones que representan la calidad de vida y el bienestar de la población de laAmazonía brasileña. Se realizó un mapeo sistemático en cinco bases de datos científicas con el fin de mapear trabajos publicados en el período de 2017 a 2021. Como resultados se encontraron 31 índices relacionados con calidad de vida y bienestar ordenados en las dimensiones medio ambiente, salud, educación, gobernanza, programas sociales e ingresos. Las dimensiones de medio ambiente, salud, educación, gobernabilidad y programas sociales e ingresos son las principales recurrencias. Los hallazgos permitidos como aportes: (i) cuantificar y calificar los trabajos, relacionando sus fuentes, año de publicación, área de aplicación y repositorio de origen; (ii) identificar las dimensiones más recurrentes de los indicadores encontrados; (iii) relacionar los índices con las cantidades de dimensiones que los componen.