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Registro completo
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Biblioteca (s) : |
INIA La Estanzuela. |
Fecha : |
19/07/2022 |
Actualizado : |
02/12/2022 |
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
Autor : |
HYDE, K.A.; AGUIAR, F.L.N.; ALVES, B.G.; ALVES, K.A.; GASTAL, G.D.A.; GASTAL, M.O.; GASTAL, E.L. |
Afiliación : |
KENDALL A HYDE, Animal Science, School of Agricultural Sciences, Southern Illinois University, Carbondale, Illinois, USA.; FRANCISCO L N AGUIAR, Animal Science, School of Agricultural Sciences, Southern Illinois University, Carbondale, Illinois, USA.; BENNER G ALVES, Animal Science, School of Agricultural Sciences, Southern Illinois University, Carbondale, Illinois, USA.; KELE A ALVES, Animal Science, School of Agricultural Sciences, Southern Illinois University, Carbondale, Illinois, USA.; GUSTAVO DESIRE ANTUNES GASTAL, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay./Animal Science, School of Agricultural Sciences, Southern Illinois University, Carbondale, Illinois, USA.; MELBA O GASTAL, Animal Science, School of Agricultural Sciences, Southern Illinois University, Carbondale, Illinois, USA.; EDUARDO L GASTAL, Animal Science, School of Agricultural Sciences, Southern Illinois University, Carbondale, Illinois, USA. |
Título : |
Preantral follicle population and distribution in the horse ovary. |
Fecha de publicación : |
2022 |
Fuente / Imprenta : |
Reproduction & Fertility, 2022, Volume 3, Issue 2, Page 90-102. OPEN ACCESS. doi: https://doi.org/10.1530/RAF-21-0100 |
ISSN : |
2633-8386 |
DOI : |
10.1530/RAF-21-0100 |
Idioma : |
Inglés |
Notas : |
Article history: Received in final form 25 March 2022; Accepted 4 April 2022; Accepted Manuscript published online 4 April 2022. -- Corresponding author: Gastal, E.L.; School of Agricultural Sciences, Southern Illinois University, Carbondale, IL, United States; email:egastal@siu.edu -- |
Contenido : |
Abstract:
Characterization of the ovarian preantral follicle population is a necessary step to improve understanding of folliculogenesis and ovarian physiology. Therefore, in the present study, the preantral follicle population in the equine ovary in young and old mares was investigated according to follicular morphology, follicular class, distance from the geometric center using ovarian maps, and follicular density within ovarian portions (lateral vs intermediary) and regions (dorsal vs ventral). Ovaries were collected from an abattoir and histologically processed for evaluation, and the follicle population was calculated. Overall, in the current detailed study, a higher preantral follicle population per mare ovary (mean: 82,206 ± 50,022; range: 1477 to 773,091) than originally reported was identified. Additionally, a mare age effect was observed in the follicle population (young: 152,664 vs old: 11,750) and the spatial distribution of morphologically normal and abnormal follicles and the density and population of follicular classes. These results demonstrate that, in addition to the preantral follicle population in the mare ovary being comparable to that of other species, the location and spatial distribution of these follicles is dynamic and varies depending on mare age and follicle status (i.e. morphology and developmental stage). The characterization of the distribution and population of preantral follicles in the mare ovary provided by this study can potentially aid in improving reproductive studies and assisted reproductive techniques and may expand the understanding of mechanisms involving ovarian plasticity and follicular migration. © 2022 The authors. MenosAbstract:
Characterization of the ovarian preantral follicle population is a necessary step to improve understanding of folliculogenesis and ovarian physiology. Therefore, in the present study, the preantral follicle population in the equine ovary in young and old mares was investigated according to follicular morphology, follicular class, distance from the geometric center using ovarian maps, and follicular density within ovarian portions (lateral vs intermediary) and regions (dorsal vs ventral). Ovaries were collected from an abattoir and histologically processed for evaluation, and the follicle population was calculated. Overall, in the current detailed study, a higher preantral follicle population per mare ovary (mean: 82,206 ± 50,022; range: 1477 to 773,091) than originally reported was identified. Additionally, a mare age effect was observed in the follicle population (young: 152,664 vs old: 11,750) and the spatial distribution of morphologically normal and abnormal follicles and the density and population of follicular classes. These results demonstrate that, in addition to the preantral follicle population in the mare ovary being comparable to that of other species, the location and spatial distribution of these follicles is dynamic and varies depending on mare age and follicle status (i.e. morphology and developmental stage). The characterization of the distribution and population of preantral follicles in the mare ovary provided by this study can potentially aid in... Presentar Todo |
Palabras claves : |
Equine ovarian plasticity; Folliculogenesis; Preantral follicles; Spatial distribution and population??. |
Thesagro : |
CABALLOS. |
Asunto categoría : |
-- |
URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/16663/1/RAF-21-0100.pdf
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Marc : |
LEADER 02854naa a2200289 a 4500 001 1063439 005 2022-12-02 008 2022 bl uuuu u00u1 u #d 022 $a2633-8386 024 7 $a10.1530/RAF-21-0100$2DOI 100 1 $aHYDE, K.A. 245 $aPreantral follicle population and distribution in the horse ovary.$h[electronic resource] 260 $c2022 500 $aArticle history: Received in final form 25 March 2022; Accepted 4 April 2022; Accepted Manuscript published online 4 April 2022. -- Corresponding author: Gastal, E.L.; School of Agricultural Sciences, Southern Illinois University, Carbondale, IL, United States; email:egastal@siu.edu -- 520 $aAbstract: Characterization of the ovarian preantral follicle population is a necessary step to improve understanding of folliculogenesis and ovarian physiology. Therefore, in the present study, the preantral follicle population in the equine ovary in young and old mares was investigated according to follicular morphology, follicular class, distance from the geometric center using ovarian maps, and follicular density within ovarian portions (lateral vs intermediary) and regions (dorsal vs ventral). Ovaries were collected from an abattoir and histologically processed for evaluation, and the follicle population was calculated. Overall, in the current detailed study, a higher preantral follicle population per mare ovary (mean: 82,206 ± 50,022; range: 1477 to 773,091) than originally reported was identified. Additionally, a mare age effect was observed in the follicle population (young: 152,664 vs old: 11,750) and the spatial distribution of morphologically normal and abnormal follicles and the density and population of follicular classes. These results demonstrate that, in addition to the preantral follicle population in the mare ovary being comparable to that of other species, the location and spatial distribution of these follicles is dynamic and varies depending on mare age and follicle status (i.e. morphology and developmental stage). The characterization of the distribution and population of preantral follicles in the mare ovary provided by this study can potentially aid in improving reproductive studies and assisted reproductive techniques and may expand the understanding of mechanisms involving ovarian plasticity and follicular migration. © 2022 The authors. 650 $aCABALLOS 653 $aEquine ovarian plasticity 653 $aFolliculogenesis 653 $aPreantral follicles 653 $aSpatial distribution and population?? 700 1 $aAGUIAR, F.L.N. 700 1 $aALVES, B.G. 700 1 $aALVES, K.A. 700 1 $aGASTAL, G.D.A. 700 1 $aGASTAL, M.O. 700 1 $aGASTAL, E.L. 773 $tReproduction & Fertility, 2022, Volume 3, Issue 2, Page 90-102. OPEN ACCESS. doi: https://doi.org/10.1530/RAF-21-0100
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INIA La Estanzuela (LE) |
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Biblioteca (s) : |
INIA Las Brujas. |
Fecha actual : |
14/02/2023 |
Actualizado : |
14/02/2023 |
Tipo de producción científica : |
Informes Agroclimáticos |
Autor : |
INIA (INSTITUTO NACIONAL DE INVESTIGACIÓN AGROPECUARIA); GRAS |
Afiliación : |
UNIDAD DE AGROCLIMA Y SISTEMAS DE INFORMACIÓN, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
Título : |
Informe agroclimático 2023- Situación a Enero. |
Fecha de publicación : |
2023 |
Fuente / Imprenta : |
Montevideo (UY): INIA, 2023. |
Páginas : |
6 p. |
Serie : |
(Informe Agroclimático; Año 18, No.01) |
Idioma : |
Español |
Notas : |
Equipo de trabajo INIA-GRAS (Unidad de Agtech y sistemas de Información): Adrián Cal, Guadalupe Tiscornia, Carlos Schiavi, Gabriel García. |
Contenido : |
Contenido. Síntesis de la Situación Agroclimática de Enero-- Perspectivas Climáticas Trimestrales elaboradas por el IRI de la Universidad de Columbia (Más información puede encontrarse en el sitio del IRI: http://www.iri.columbia.edu) -- Índice de Vegetación (NDVI) -- Precipitaciones -- Porcentaje de Agua Disponible (PAD) -- Agua No Retenida (ANR) -- Índice de Bienestar Hídrico (IBH) -- Perspectivas Climáticas Feb-Mar-Abr elaboradas por el IRI de la Universidad de Columbia. Destacamos para este mes: INIA Termoestrés. Previsión de condiciones ambientales que causan estrés calórico en bovinos de carne y leche. Link directo: http://www.inia.uy/gras/Alertas-y-herramientas/Prevision-ITH-Vacunos/INIA-Termoestres |
Palabras claves : |
AGTECH; AGUA NO RETENIDA (ANR); BOLETIN AGROCLIMÁTICO; CARACTERIZACIÓN AGROCLIMÁTICA; DIRECCION VIENTO; ESTACIONES AGROMETEOROLOGICAS; ESTACIONES AUTOMATICAS; ESTACIONES INIA; ESTADO DEL TIEMPO; GRAFICAS AGROCLIMATICAS; GRAS; ÍNDICE DE BIENESTAR HÍDRICO (IBH); ÍNDICE DE VEGETACIÓN (NDVI); INFORMACION SATELITAL; INFORME AGROCLIMÁTICO 2023; INUNDACIONES; LLUVIAS DIARIAS; MAXIMA; MEDIA; MINIMA; PANEL SOLAR; PERSPECTIVAS CLIMATICAS; PLUVIOMETRO; PORCENTAJE DE AGUA DISPONIBLE (PAD); PRECIPITACION NACIONAL; PRECIPITACIONES; PREVENCION HELADAS; PRONOSTICO; SENSOR; SISTEMAS DE INFORMACIÓN Y TRANSFORMACIÓN DIGITAL - INIA; TANQUE A; TERMOCUPLAS; TERMOHIDROGRAFO; VARIABLES AGROCLIMATICAS; VELETA. |
Thesagro : |
AGROCLIMATOLOGIA; CAMBIO CLIMÁTICO; CLIMA; CLIMATOLOGIA; ESTACIONES METEOROLOGICAS; ESTRES HIDRICO; EVAPOTRANSPIRACION; HUMEDAD; HUMEDAD RELATIVA; LLUVIA; METEOROLOGIA; PERSPECTIVAS; PLUVIOMETROS; PRONOSTICO DEL TIEMPO; SENSORES; SISTEMAS; SISTEMAS DE INFORMACION; SISTEMAS DE INFORMACION GEOGRAFICOS; TEMPERATURA; TERMOMETROS. |
Asunto categoría : |
P40 Meteorología y climatología |
URL : |
http://www.inia.uy/Publicaciones/Documentos%20compartidos/Informe%20agroclimatico%20INIA-GRAS%20Enero%20de%202023.pdf
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Marc : |
LEADER 03190nam a2200817 a 4500 001 1063961 005 2023-02-14 008 2023 bl uuuu u0uu1 u #d 100 1 $aINIA (INSTITUTO NACIONAL DE INVESTIGACIÓN AGROPECUARIA) 245 $aInforme agroclimático 2023- Situación a Enero.$h[electronic resource] 260 $aMontevideo (UY): INIA$c2023 300 $a6 p. 490 $a(Informe Agroclimático; Año 18, No.01) 500 $aEquipo de trabajo INIA-GRAS (Unidad de Agtech y sistemas de Información): Adrián Cal, Guadalupe Tiscornia, Carlos Schiavi, Gabriel García. 520 $aContenido. Síntesis de la Situación Agroclimática de Enero-- Perspectivas Climáticas Trimestrales elaboradas por el IRI de la Universidad de Columbia (Más información puede encontrarse en el sitio del IRI: http://www.iri.columbia.edu) -- Índice de Vegetación (NDVI) -- Precipitaciones -- Porcentaje de Agua Disponible (PAD) -- Agua No Retenida (ANR) -- Índice de Bienestar Hídrico (IBH) -- Perspectivas Climáticas Feb-Mar-Abr elaboradas por el IRI de la Universidad de Columbia. Destacamos para este mes: INIA Termoestrés. Previsión de condiciones ambientales que causan estrés calórico en bovinos de carne y leche. Link directo: http://www.inia.uy/gras/Alertas-y-herramientas/Prevision-ITH-Vacunos/INIA-Termoestres 650 $aAGROCLIMATOLOGIA 650 $aCAMBIO CLIMÁTICO 650 $aCLIMA 650 $aCLIMATOLOGIA 650 $aESTACIONES METEOROLOGICAS 650 $aESTRES HIDRICO 650 $aEVAPOTRANSPIRACION 650 $aHUMEDAD 650 $aHUMEDAD RELATIVA 650 $aLLUVIA 650 $aMETEOROLOGIA 650 $aPERSPECTIVAS 650 $aPLUVIOMETROS 650 $aPRONOSTICO DEL TIEMPO 650 $aSENSORES 650 $aSISTEMAS 650 $aSISTEMAS DE INFORMACION 650 $aSISTEMAS DE INFORMACION GEOGRAFICOS 650 $aTEMPERATURA 650 $aTERMOMETROS 653 $aAGTECH 653 $aAGUA NO RETENIDA (ANR) 653 $aBOLETIN AGROCLIMÁTICO 653 $aCARACTERIZACIÓN AGROCLIMÁTICA 653 $aDIRECCION VIENTO 653 $aESTACIONES AGROMETEOROLOGICAS 653 $aESTACIONES AUTOMATICAS 653 $aESTACIONES INIA 653 $aESTADO DEL TIEMPO 653 $aGRAFICAS AGROCLIMATICAS 653 $aGRAS 653 $aÍNDICE DE BIENESTAR HÍDRICO (IBH) 653 $aÍNDICE DE VEGETACIÓN (NDVI) 653 $aINFORMACION SATELITAL 653 $aINFORME AGROCLIMÁTICO 2023 653 $aINUNDACIONES 653 $aLLUVIAS DIARIAS 653 $aMAXIMA 653 $aMEDIA 653 $aMINIMA 653 $aPANEL SOLAR 653 $aPERSPECTIVAS CLIMATICAS 653 $aPLUVIOMETRO 653 $aPORCENTAJE DE AGUA DISPONIBLE (PAD) 653 $aPRECIPITACION NACIONAL 653 $aPRECIPITACIONES 653 $aPREVENCION HELADAS 653 $aPRONOSTICO 653 $aSENSOR 653 $aSISTEMAS DE INFORMACIÓN Y TRANSFORMACIÓN DIGITAL - INIA 653 $aTANQUE A 653 $aTERMOCUPLAS 653 $aTERMOHIDROGRAFO 653 $aVARIABLES AGROCLIMATICAS 653 $aVELETA 700 1 $aGRAS
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