Luteal dynamics in goats: morphological and endocrine features

The aim of this study was to establish the morphologic and endocrine characteristics of luteal dynamics in goats. It was used Toggenburg female goats that showed natural estrus in a 48-hour interval. After estrus, ultrasonographic evaluations of the ovaries were daily performed during 21 days using a portable device (5MHz probe). Blood sample was collected for plasma progresterone (P4) determination. Corpora lutea were detected for the first time on day 5 and progressively increased in size until D9 (1.26 ± 0.08 cm²), with no variation on subsequent days. In females with one ovulation, the first visualization of the corpora lutea was earlier than in those with multiple ovulation (4.54 ± 0.18 vs 5.74 ± 0.25 days). At the moment of the first visualization, luteal area was smaller in animals with single ovulation. Plasma P4 concentration progressively increased until day 9 and it did not show significant increase until luteolysis, characterized by a sharp decrease in P4 concentration, reaching values below 1 ng/mL in 24 hours. The luteal area slowly and gradually decreased in size. It was observed a significant positive correlation between P4 concentration and area during luteogenesis and luteolysis (r = 0.63 and r = 0.50, respectively). When corpus luteum reached its maximum size (D9), female with more than one corpora lutea, with a greater luteal tissue area, did not show P4 concentration higher than those with one ovulation (5.92 ± 0.59 vs 7.04 ± 0.79 ng/mL). These results show that luteal dynamics in Toggenbur goats follow a similar pattern to those observed in other goat breeds and luteal tissue growth was positively correlated with corpora lutea functionality.Objetivou-se neste estudo estabelecer as características morfológicas e endócrinas da dinâmica luteal em cabras. Foram utilizadas fêmeas da raça Toggenburg que manifestaram estro natural em um intervalo de 48 horas. Após o estro, foram realizadas avaliações ultrassonográficas diárias dos ovários durante 21 dias, utilizando-se um aparelho portátil (5 MHz). Amostras de sangue foram coletadas para dosagem de progesterona (P4) no plasma. Os corpos lúteos foram detectados pela primeira vez no D5 e aumentaram progressivamente de tamanho até o D9 (1,26 ± 0,08 cm²), não havendo variação nos dias subsequentes. Nas fêmeas com uma ovulação, a primeira visualização do corpo lúteo foi mais precoce que naquelas com ovulação múltipla (4,54 ± 0,18 vs 5,74 ± 0,25 dias). No momento da primeira visualização, a área luteal foi menor nos animais com uma ovulação. A concentração plasmática de P4 aumentou progressivamente até o D9 e não apresentou aumento significativo até o momento da luteólise, caracterizada por uma acentuada queda da concentração de P4, atingindo valores inferiores a 1 ng/mL em um intervalo de 24 horas. A área luteal diminuiu de forma lenta e gradual. Foi observada uma correlação positiva significativa entre a área e a concentração de P4 durante a lutegêonese e a luteólise (r = 0,63 e r = 0,50; respectivamente). No dia em que o corpo lúteo atinge sua área máxima (D9), as fêmeas com mais de um corpo lúteo, com maior área de tecido luteal, não apresentaram concentração de P4 superior à daquelas com uma ovulação (5,92 ± 0,59 vs 7,04 ± 0,79 ng/mL). Esses resultados indicam que a dinâmica luteal em caprinos da raça Toggenburg segue padrões semelhantes aos observados em outras raças e em outras espécies e que o crescimento de tecido luteal refletiu positivamente na funcionalidade do corpo lúteo

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time, and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space. While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes, vast areas of the tropics remain understudied. In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity, but it remains among the least known forests in America and is often underrepresented in biodiversity databases. To worsen this situation, human-induced modifications may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge, it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost