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65. Bovinos e a restauração ecológica: vilões ou benfeitores?

Author

ALBUQUERQUE, L. B. de, FERREIRA, I. C., MALAQUIAS, J. V., LIDIAMAR BARBOSA DE ALBUQUERQUE, CPAC, ISABEL CRISTINA FERREIRA, CPAC, and JUACI VITORIA MALAQUIAS, CPAC.

Subjects
Bovino, Recuperação do Solo, Restauração ecológica
Abstract

Mesmo em pastagens, a restauração ecológica pode ser uma aliada do produtor quando utilizada para acelerar a recuperação de áreas degradadas, trazendo benefícios em relação a saúde, integridade e sustentabilidade da propriedade rural.

Published
2020

66. Predictors of mortality in solid organ transplant recipients with bloodstream infections due to carbapenemase-producing Enterobacterales: The impact of cytomegalovirus disease and lymphopenia

Author

Perez-Nadales, E., Gutierrez-Gutierrez, B., Natera, A. M., Abdala, E., Reina Magalhaes, M., Mularoni, A., Monaco, F., Camera Pierrotti, L., Pinheiro Freire, M., Iyer, R. N., Mehta Steinke, S., Grazia Calvi, E., Tumbarello, M., Falcone, M., Fernandez-Ruiz, M., Costa-Mateo, J. M., Rana, M. M., Mara Varejao Strabelli, T., Paul, M., Carmen Farinas, M., Clemente, W. T., Roilides, E., Munoz, P., Dewispelaere, L., Loeches, B., Lowman, W., Hock Tan, B., Escudero-Sanchez, R., Bodro, M., Antonio Grossi, P., Soldani, F., Gunseren, F., Nestorova, N., Pascual, A., Martinez-Martinez, L., Aguado, J., Rodriguez-Bano, J., Torre-Cisneros, J., Wan Song, A. T., Andraus, W., Carneiro D'Albuquerque, L. A., David-Neto, E., Jota de Paula, F., Rossi, F., Ostrander, D., Avery, R., Rizzi, M., Losito, A. R., Raffaelli, F., Del Giacomo, P., Tiseo, G., Lora-Tamayo, J., San-Juan, R., Gracia-Ahufinger, I., Caston, J., Ruiz, Y. A., Altman, D. R., Campos, S. V., Bar-Sinai, N., Koppel, F., Arnaiz de las Revillas Almajano, F., Gonzalez Rico, C., Fernandez Martinez, M., Mourao, P. H. O., Neves, F. A., Ferreira, J., Pyrpasopoulou, A., Iosifidis, E., Romiopoulos, I., Minero, M. V., Sanchez-Carrillo, C., Lardo, S., Coussement, J., Dodemont, M., Jiayun, K., Martin-Davila, P., Fortun, J., Almela, M., Moreno, A., Linares, L., Gasperina, D. D., Balsamo, M. L., Rovelli, C., Concia, E., Chiesi, S., Salerno, D. N., Ogunc, D., Pilmis, B., Seminari, E. M., Carratala, J., Dominguez, A., Cordero, E., Lepe, J. A., Montejo, M., Merino de Lucas, E., Eriksson, B. M., van Delden, C., Manuel, O., Arslan, H., Kocak Tufan, Z., Kazak, E., David, M., Lease, E., Cornaglia, G., Akova, M., European Commission, Ministerio de Ciencia, Innovación y Universidades (España), Instituto de Salud Carlos III, and Universidad de Cantabria

Subjects
medicine.medical_specialty, Combination therapy, infectious disease, 030230 surgery, Settore MED/17 - MALATTIE INFETTIVE, Logistic regression, clinical research/practice, 03 medical and health sciences, 0302 clinical medicine, infection and infectious agents - bacterial, Internal medicine, medicine, Immunology and Allergy, Pharmacology (medical), organ transplantation in general, Infection and infectious agents - bacterial, Transplantation, Infectious disease, Receiver operating characteristic, business.industry, Hazard ratio, Confidence interval, Organ transplantation in general, antibiotic drug resistance, Cohort, Clinical research/practice, Antibiotic drug resistance, business, Cohort study
Abstract

Treatment of carbapenemase‐producing Enterobacterales bloodstream infections in solid organ transplant recipients is challenging. The objective of this study was to develop a specific score to predict mortality in solid organ transplant recipients with carbapenemase‐producing Enterobacterales bloodstream infections. A multinational, retrospective (2004‐2016) cohort study (INCREMENT‐SOT, ClinicalTrials.gov NCT02852902) was performed. The main outcome variable was 30‐day all‐cause mortality. The INCREMENT‐SOT‐CPE score was developed using logistic regression. The global cohort included 216 patients. The final logistic regression model included the following variables: INCREMENT‐CPE mortality score ≥8 (8 points), no source control (3 points), inappropriate empirical therapy (2 points), cytomegalovirus disease (7 points), lymphopenia (4 points), and the interaction between INCREMENT‐CPE score ≥8 and CMV disease (minus 7 points). This score showed an area under the receiver operating characteristic curve of 0.82 (95% confidence interval [CI] 0.76‐0.88) and classified patients into 3 strata: 0‐7 (low mortality), 8‐11 (high mortality), and 12‐17 (very‐high mortality). We performed a stratified analysis of the effect of monotherapy vs combination therapy among 165 patients who received appropriate therapy. Monotherapy was associated with higher mortality only in the very‐high (adjusted hazard ratio [HR] 2.82, 95% CI 1.13‐7.06, P = .03) and high (HR 9.93, 95% CI 2.08‐47.40, P = .004) mortality risk strata. A score‐based algorithm is provided for therapy guidance., This work was supported by Plan Nacional de I+D+i 2013‐2016 and Instituto de Salud Carlos III, Subdirección General de Redes y Centros de Investigación Cooperativa, Ministerio de Ciencia, Innovación y Universidades, Spanish Network for Research in Infectious Diseases [REIPI RD16/0016/0008; RD16/0016/0001, RD16/0016/0002, RD16/0016/00010] ‐ co‐financed by European Development Regional Fund “A way to achieve Europe”, Operative program Intelligent Growth 2014‐2020; ESCMID Study Group for Infections in Compromised Hosts [ESGICH grant to JMA]; Sociedad Andaluza de Trasplante de Órgano Sólido [SATOT grant to LMM]; ESCMID Study Group for Bloodstream Infections and Sepsis (ESGBIS); and ESCMID Study Group for Antimicrobial Resistance Surveillance (ESGARS).

Published
2020

67. Predictors of mortality in solid organ transplant recipients with bloodstream infections due to carbapenemase-producing Enterobacterales: The impact of cytomegalovirus disease and lymphopenia

Author

Perez-Nadales E, Gutierrez-Gutierrez B, Natera A, Abdala E, Magalhaes M, Mularoni A, Monaco F, Pierrotti L, Freire M, Iyer R, Steinke S, Calvi E, Tumbarello M, Falcone M, Fernandez-Ruiz M, Costa-Mateo J, Rana M, Strabelli T, Paul M, Farinas M, Clemente W, Roilides E, Munoz P, Dewispelaere L, Loeches B, Lowman W, Tan B, Escudero-Sanchez R, Bodro M, Grossi P, Soldani F, Gunseren F, Nestorova N, Pascual A, Martinez-Martinez L, Aguado J, Rodriguez-Bano J, Torre-Cisneros J, Song A, Andraus W, D'Albuquerque L, David-Neto E, de Paula F, Rossi F, Ostrander D, Avery R, Rizzi M, Losito A, Raffaelli F, Del Giacomo P, Tiseo G, Lora-Tamayo J, San-Juan R, Gracia-Ahufinger I, Caston J, Ruiz Y, Altman D, Campos S, Bar-Sinai N, Koppel F, Almajano F, Rico C, Martinez M, Mourao P, Neves F, Ferreira J, Pyrpasopoulou A, Iosifidis E, Romiopoulos I, Minero M, Sanchez-Carrillo C, Lardo S, Coussement J, Dodemont M, Jiayun K, Martin-Davila P, Fortun J, Almela M, Moreno A, Linares L, Gasperina D, Balsamo M, Rovelli C, Concia E, Chiesi S, Salerno D, Ogunc D, Pilmis B, Seminari E, Carratala J, Dominguez A, Cordero E, Lepe J, Montejo M, de Lucas E, Eriksson B, van Delden C, Manuel O, Arslan H, Tufan Z, Kazak E, David M, Lease E, Cornaglia G, Akova M, REIPI INCREMENT-SOT Investigators, Swiss Transplant Cohort Study, and ESGARS-ESCMID Study Grp Antimicrob

Subjects
infection and infectious agents - bacterial, clinical research, infectious disease, antibiotic drug resistance, organ transplantation in general, practice
Abstract

Treatment of carbapenemase-producing Enterobacterales bloodstream infections in solid organ transplant recipients is challenging. The objective of this study was to develop a specific score to predict mortality in solid organ transplant recipients with carbapenemase-producing Enterobacterales bloodstream infections. A multinational, retrospective (2004-2016) cohort study (INCREMENT-SOT, ClinicalTrials.gov NCT02852902) was performed. The main outcome variable was 30-day all-cause mortality. The INCREMENT-SOT-CPE score was developed using logistic regression. The global cohort included 216 patients. The final logistic regression model included the following variables: INCREMENT-CPE mortality score >= 8 (8 points), no source control (3 points), inappropriate empirical therapy (2 points), cytomegalovirus disease (7 points), lymphopenia (4 points), and the interaction between INCREMENT-CPE score >= 8 and CMV disease (minus 7 points). This score showed an area under the receiver operating characteristic curve of 0.82 (95% confidence interval [CI] 0.76-0.88) and classified patients into 3 strata: 0-7 (low mortality), 8-11 (high mortality), and 12-17 (very-high mortality). We performed a stratified analysis of the effect of monotherapy vs combination therapy among 165 patients who received appropriate therapy. Monotherapy was associated with higher mortality only in the very-high (adjusted hazard ratio [HR] 2.82, 95% CI 1.13-7.06, P = .03) and high (HR 9.93, 95% CI 2.08-47.40, P = .004) mortality risk strata. A score-based algorithm is provided for therapy guidance.

Published
2020

70. Abstracts

Author

Rosemberg, S., Telxelra, M. J., Alves, V. A. F., Perry J. R., Ang L. C., Bilbao J. M., Muller P. J., Min, Kyung -Whan, Cashman, Robert, Brumback, Roger A., Rao, C., Deloso, D., Anderson, V., Seymour, A., Wrzolek, M., Abdu, A., Swanson, R., Honavar, M., Waters, K. B., Wise, S. M., Kubota, T., Sato, K., Kabuto, M., Nakagawa, T., Kitai, R., Nitta, H., Yamashita, J., Vital, C., Rivel, J., Sangalli, F., Benjelloun, B., Vital, A., Leger, F., Riemens, V., Epardeau, B., Guerin, J., Coindre, J. M., Ruchoux, M. M., Dhellemmes, P., Hamon, M., Lecomte, M., Hassoun, J., Yagishita, Saburo, Kawano, Nobuyuki, Kameya, Toru, Bowman, R., Liwnicz, B. H., Peckham, N., Barbosa-Coutinho, L. M., Hilbig, L. M., Hilbig, A., Loiseau, H., Mouton, L., Delisle, H. B., Rummens, C., Akai, F., Taneda, M., Iwasaki, H., Suzuki, Y., Tsanaclis, A. M. C., Aguiar, P. H. P., Logullo, A. F., Matamores, M. R., Yacubian, A., Komatsu, H., Oka, H., Suwa, T., Stoltenburg-Didinger, G., Gotzia, C., Benndorf, G., Kepes, J. J., Baba-Ahmed, R., Wong, K., Raisanen, J., Taylor, S. L., McDermott, M. W., Gutin, P., Havlioglu, Necat, Manepalli, Anantha, Galindo, Lorenzo, Sotelo-Avila, Cirilo, Grosso, Leonard, Kavavattathayyil, S., Chen, P., Wrzolek, M. A., Cook, J., Woodward, D. E., Tracqui, P., Cruywagen, G. C., Murray, J. D., Bartoo, G. T., Alvord, Jr., E. C., Szymas, Janusz, Jelonek, Jacek, Krawiec, Krzysztof, Slowinski, Roman, Coons, S. W., Johnson, P. C., Uro, E., Bousquet, P. H., Delisle, M. B., Rangueil, C. H. U., Torp, S. H., Johannesen, E., Lindboe, C. F., Beil, Michael, Kato, S., Morita, T., Kato, M., Herz, F., Hirano, A., Ohama, E., Albuquerque, L., Pimentel, J., Távora, L., Antunes, N. L., Weis, S., Protopapa, D., Mäerz, U., Winkler, P. A., Reulen, H. J., Mehraein, P., Di, Xiao, Reifenberger, Julia, Reifenberger, Guido, Liu, Lu, James, C. David, Wechsler, Wolfgang, Collins, V. Peter, McLendon, R. E., Batra, S. K., Friedman, H. S., Rasheed, B. K. A., Bigner, D. D., Bigner, S. K., Patt, S., Thiel, G., Labrousse, F., de Néchaud, B., Gomès, D., Daumas-Duport, C., Allarmargot, C., Dupouey, P., Vrionis, F., Qi, P., Cherington, V., Cano, G., Wu, J., Lampson, L. A., Chen, A., Vortmeyer, A. O., Slack, R. S., Skerjanc, I. S., Lach, B., Craig, J., Jardine, K., McBurney, M. W., Macaulay, R. J. B., Dimitroulakos, J., Becker, L. E., Yeger, H., Rhodes, C. Harker, Honsinger, Charles, Sorenson, George D., Goumnerova L. C., Segal R. A., Kwon Y. K., Stiles C. D., Pomeroy S. L., Guha, A., Lau, N., Pawson, A., Engel, Ute, Gutowski, Nick J., Bevan, Karen, Noble, Mark, Gladson, C. L., Pijuan, V., Olman, M. A., Gillespie, G. Y., Yacoub, I., Yamasaki, T., Enomoto, K., Moritake, K., Akiyama, Y., Kawahara, M., Maeno, T., Merzak, A., Parker, C., Koocheckpour, S., Sherbet, G. V., Pilkington, G. J., Martin, K., Akinwunmi, J., Rooprai, H. K., Kennedy, A., Linke, A., Ognjenovic, N., Fujiwara, T., Matsumoto, Y., Miyake, K., Shin, M., Nagao, S., Pulido-Cejudo, G., Jamison, K., Hugenholtz, H., Campione-Piccardo, J., Maidment, S. L., Lins, C., Takyia, C. M., Garcia-Abreu, J., Rodrigues, F. F., Duarte, F., Chagas, C., Chneiweiss, H., and Neto, V. Moura

Published
1995
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72. P-49: Nutritional Characteristics of a High Absorption Oral Diet for Short Bowel Syndrome: Experience of a Brazilian Intestinal Rehabilitation Center

Author

Lee A, Dias M, Albuquerque A, Rocha M, Rodrigues M, Queiroz M, Galvão F, Waitzberg D, and Carneiro D’Albuquerque L

Subjects
Transplantation, medicine.medical_specialty, business.industry, Internal medicine, medicine, Intestinal rehabilitation, Short bowel syndrome, medicine.disease, business, Absorption (electromagnetic radiation), Gastroenterology
Published
2021
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74. Predictors of mortality in solid organ transplant recipients with bloodstream infections due to carbapenemase-producing Enterobacterales : The impact of cytomegalovirus disease and lymphopenia

Author

Perez-Nadales, Elena, Gutierrez-Gutierrez, Belen, Natera, Alejandra M., Abdala, Edson, Magalhaes, Maira Reina, Mularoni, Alessandra, Monaco, Francesco, Pierrotti, Ligia Camera, Freire, Maristela Pinheiro, Iyer, Ranganathan N., Steinke, Seema Mehta, Calvi, Elisa Grazia, Tumbarello, Mario, Falcone, Marco, Fernandez-Ruiz, Mario, Maria Costa-Mateo, Jose, Rana, Meenakshi M., Varejao Strabelli, Tania Mara, Paul, Mical, Carmen Farinas, Maria, Clemente, Wanessa Trindade, Roilides, Emmanuel, Munoz, Patricia, Dewispelaere, Laurent, Loeches, Belen, Lowman, Warren, Tan, Ban Hock, Escudero-Sanchez, Rosa, Bodro, Marta, Grossi, Paolo Antonio, Soldani, Fabio, Gunseren, Filiz, Nestorova, Nina, Pascual, Alvaro, Martinez-Martinez, Luis, Maria Aguado, Jose, Rodriguez-Bano, Jesus, Torre-Cisneros, Julian, Song, A. T. Wan, Andraus, W., Carneiro D'Albuquerque, L. A., David-Neto, E., de Paula, F. Jota, Rossi, F., Ostrander, D., Avery, R., Rizzi, M., Losito, A. R., Raffaelli, F., Del Giacomo, P., Tiseo, G., Lora-Tamayo, J., San-Juan, R., Gracia-Ahufinger, I, Caston, J., Ruiz, Y. A., Altman, D. R., Campos, S. , V, Bar-Sinai, N., Koppel, F., de las Revillas Almajano, F. Arnaiz, Gonzalez Rico, C., Fernandez Martinez, M., Mourao, P. H. O., Neves, F. A., Ferreira, J., Pyrpasopoulou, A., Iosifidis, E., Romiopoulos, I, Minero, M. , V, Sanchez-Carrillo, C., Lardo, S., Coussement, J., Dodemont, M., Jiayun, K., Martin-Davila, P., Fortun, J., Almela, M., Moreno, A., Linares, L., Gasperina, D. D., Balsamo, M. L., Rovelli, C., Concia, E., Chiesi, S., Salerno, D. N., Ogunc, D., Pilmis, B., Seminari, E. M., Carratala, J., Dominguez, A., Cordero, E., Lepe, J. A., Montejo, M., Merino de Lucas, E., Eriksson, Britt-Marie, van Delden, C., Manuel, O., Arslan, H., Tufan, Z. Kocak, Kazak, E., David, M., Lease, E., Cornaglia, G., Akova, M., Perez-Nadales, Elena, Gutierrez-Gutierrez, Belen, Natera, Alejandra M., Abdala, Edson, Magalhaes, Maira Reina, Mularoni, Alessandra, Monaco, Francesco, Pierrotti, Ligia Camera, Freire, Maristela Pinheiro, Iyer, Ranganathan N., Steinke, Seema Mehta, Calvi, Elisa Grazia, Tumbarello, Mario, Falcone, Marco, Fernandez-Ruiz, Mario, Maria Costa-Mateo, Jose, Rana, Meenakshi M., Varejao Strabelli, Tania Mara, Paul, Mical, Carmen Farinas, Maria, Clemente, Wanessa Trindade, Roilides, Emmanuel, Munoz, Patricia, Dewispelaere, Laurent, Loeches, Belen, Lowman, Warren, Tan, Ban Hock, Escudero-Sanchez, Rosa, Bodro, Marta, Grossi, Paolo Antonio, Soldani, Fabio, Gunseren, Filiz, Nestorova, Nina, Pascual, Alvaro, Martinez-Martinez, Luis, Maria Aguado, Jose, Rodriguez-Bano, Jesus, Torre-Cisneros, Julian, Song, A. T. Wan, Andraus, W., Carneiro D'Albuquerque, L. A., David-Neto, E., de Paula, F. Jota, Rossi, F., Ostrander, D., Avery, R., Rizzi, M., Losito, A. R., Raffaelli, F., Del Giacomo, P., Tiseo, G., Lora-Tamayo, J., San-Juan, R., Gracia-Ahufinger, I, Caston, J., Ruiz, Y. A., Altman, D. R., Campos, S. , V, Bar-Sinai, N., Koppel, F., de las Revillas Almajano, F. Arnaiz, Gonzalez Rico, C., Fernandez Martinez, M., Mourao, P. H. O., Neves, F. A., Ferreira, J., Pyrpasopoulou, A., Iosifidis, E., Romiopoulos, I, Minero, M. , V, Sanchez-Carrillo, C., Lardo, S., Coussement, J., Dodemont, M., Jiayun, K., Martin-Davila, P., Fortun, J., Almela, M., Moreno, A., Linares, L., Gasperina, D. D., Balsamo, M. L., Rovelli, C., Concia, E., Chiesi, S., Salerno, D. N., Ogunc, D., Pilmis, B., Seminari, E. M., Carratala, J., Dominguez, A., Cordero, E., Lepe, J. A., Montejo, M., Merino de Lucas, E., Eriksson, Britt-Marie, van Delden, C., Manuel, O., Arslan, H., Tufan, Z. Kocak, Kazak, E., David, M., Lease, E., Cornaglia, G., and Akova, M.

Abstract

Treatment of carbapenemase-producing Enterobacterales bloodstream infections in solid organ transplant recipients is challenging. The objective of this study was to develop a specific score to predict mortality in solid organ transplant recipients with carbapenemase-producing Enterobacterales bloodstream infections. A multinational, retrospective (2004-2016) cohort study (INCREMENT-SOT, ClinicalTrials.gov NCT02852902) was performed. The main outcome variable was 30-day all-cause mortality. The INCREMENT-SOT-CPE score was developed using logistic regression. The global cohort included 216 patients. The final logistic regression model included the following variables: INCREMENT-CPE mortality score >= 8 (8 points), no source control (3 points), inappropriate empirical therapy (2 points), cytomegalovirus disease (7 points), lymphopenia (4 points), and the interaction between INCREMENT-CPE score >= 8 and CMV disease (minus 7 points). This score showed an area under the receiver operating characteristic curve of 0.82 (95% confidence interval [CI] 0.76-0.88) and classified patients into 3 strata: 0-7 (low mortality), 8-11 (high mortality), and 12-17 (very-high mortality). We performed a stratified analysis of the effect of monotherapy vs combination therapy among 165 patients who received appropriate therapy. Monotherapy was associated with higher mortality only in the very-high (adjusted hazard ratio [HR] 2.82, 95% CI 1.13-7.06, P = .03) and high (HR 9.93, 95% CI 2.08-47.40, P = .004) mortality risk strata. A score-based algorithm is provided for therapy guidance.

Published
2020
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78. Genome‐wide interaction study reveals epistatic interactions for beef lipid‐related traits in Nellore cattle.

Author

Amorim, S. T., Stafuzza, N. B., Kluska, S., Peripolli, E., Pereira, A. S. C., Muller da Silveira, L. F., de Albuquerque, L. G., and Baldi, F.

Subjects
LIPOPROTEIN receptors, PHYSIOLOGY, CATTLE, MEAT quality, GENETIC variation, LIPIDS, LOW density lipoprotein receptors
Abstract

Summary: Gene–gene interactions cause hidden genetic variation in natural populations and could be responsible for the lack of replication that is typically observed in complex traits studies. This study aimed to identify gene–gene interactions using the empirical Hilbert–Schmidt Independence Criterion method to test for epistasis in beef fatty acid profile traits of Nellore cattle. The dataset contained records from 963 bulls, genotyped using a 777 962k SNP chip. Meat samples of Longissimus muscle, were taken to measure fatty acid composition, which was quantified by gas chromatography. We chose to work with the sums of saturated (SFA), monounsaturated (MUFA), polyunsaturated (PUFA), omega‐3 (OM3), omega‐6 (OM6), SFA:PUFA and OM3:OM6 fatty acid ratios. The SNPs in the interactions where P<10‐8 were mapped individually and used to search for candidate genes. Totals of 602, 3, 13, 23, 13, 215 and 169 candidate genes for SFAs, MUFAs, PUFAs, OM3s, OM6s and SFA:PUFA and OM3:OM6 ratios were identified respectively. The candidate genes found were associated with cholesterol, lipid regulation, low‐density lipoprotein receptors, feed efficiency and inflammatory response. Enrichment analysis revealed 57 significant GO and 18 KEGG terms (P < 0.05), most of them related to meat quality and complementary terms. Our results showed substantial genetic interactions associated with lipid profile, meat quality, carcass and feed efficiency traits for the first time in Nellore cattle. The knowledge of these SNP–SNP interactions could improve understanding of the genetic and physiological mechanisms that contribute to lipid‐related traits and improve human health by the selection of healthier meat products. [ABSTRACT FROM AUTHOR]

Published
2022
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84. Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Author

Brown, P., Zhou, Y., Tan, A. -C., El-Esawi, M. A., Liehr, T., Blanck, O., Gladue, D. P., Almeida, G. M. F., Cernava, T., Sorzano, C. O., Yeung, A. W. K., Engel, M. S., Chandrasekaran, A. R., Muth, T., Staege, M. S., Daulatabad, S. V., Widera, D., Zhang, J., Meule, A., Honjo, K., Pourret, O., Yin, C. -C., Zhang, Z., Cascella, M., Flegel, W. A., Goodyear, C. S., van Raaij, M. J., Bukowy-Bieryllo, Z., Campana, L. G., Kurniawan, N. A., Lalaouna, D., Huttner, F. J., Ammerman, B. A., Ehret, F., Cobine, P. A., Tan, E. -C., Han, H., Xia, W., Mccrum, C., Dings, R. P. M., Marinello, F., Nilsson, H., Nixon, B., Voskarides, K., Yang, L., Costa, V. D., Bengtsson-Palme, J., Bradshaw, W., Grimm, D. G., Kumar, N., Martis, E., Prieto, D., Sabnis, S. C., Amer, S. E. D. R., Liew, A. W. C., Perco, P., Rahimi, F., Riva, G., Zhang, C., Devkota, H. P., Ogami, K., Basharat, Z., Fierz, W., Siebers, R., Tan, K. H., Boehme, K. A., Brenneisen, P., Brown, J. A. L., Dalrymple, B. P., Harvey, D. J., Ng, G., Werten, S., Bleackley, M., Dai, Z., Dhariwal, R., Gelfer, Y., Hartmann, M. D., Miotla, P., Tamaian, R., Govender, P., Gurney-Champion, O. J., Kauppila, J. H., Zhang, X., Echeverria, N., Subhash, S., Sallmon, H., Tofani, M., Bae, T., Bosch, O., Cuiv, P. O., Danchin, A., Diouf, B., Eerola, T., Evangelou, E., Filipp, F., Klump, H., Kurgan, L., Smith, S. S., Terrier, O., Tuttle, N., Ascher, D. B., Janga, S. C., Schulte, L. N., Becker, D., Browngardt, C., Bush, S. J., Gaullier, G., Ide, K., Meseko, C., Werner, G. D. A., Zaucha, J., Al-Farha, A. A., Greenwald, N. F., Popoola, S. I., Rahman, S., Xu, J., Yang, S. Y., Hiroi, N., Alper, O. M., Baker, C. I., Bitzer, M., Chacko, G., Debrabant, B., Dixon, R., Forano, E., Gilliham, M., Kelly, S., Klempnauer, K. -H., Lidbury, B. A., Lin, M. Z., Lynch, I., Ma, W., Maibach, E. W., Mather, D. E., Nandakumar, K. S., Ohgami, R. S., Parchi, P., Tressoldi, P., Xue, Y., Armitage, C., Barraud, P., Chatzitheochari, S., Coelho, L. P., Diao, J., Doxey, A. C., Gobet, A., Hu, P., Kaiser, S., Mitchell, K. M., Salama, M. F., Shabalin, I. G., Song, H., Stevanovic, D., Yadollahpour, A., Zeng, E., Zinke, K., Alimba, C. G., Beyene, T. J., Cao, Z., Chan, S. S., Gatchell, M., Kleppe, A., Piotrowski, M., Torga, G., Woldesemayat, A. A., Cosacak, M. I., Haston, S., Ross, S. A., Williams, R., Wong, A., Abramowitz, M. K., Effiong, A., Lee, S., Abid, M. B., Agarabi, C., Alaux, C., Albrecht, D. R., Atkins, G. J., Beck, C. R., Bonvin, A. M. J. J., Bourke, E., Brand, T., Braun, R. J., Bull, J. A., Cardoso, P., Carter, D., Delahay, R. M., Ducommun, B., Duijf, P. H. G., Epp, T., Eskelinen, E. -L., Fallah, M., Farber, D. 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M., Valenti, A., Verlot, P., Walker, M., Wang, J., Welter, D., Winslade, M., Wu, D., Wu, Y. -R., Xiao, H., Xu, B., Xu, Z., Yang, D., Yang, M., Yankilevich, P., You, Y., Yu, C., Zhan, J., Zhang, G., Zhang, K., Zhang, T., Zhao, G., Zhao, J., Zhou, X., Zhu, Z., Ajani, P. A., Anazodo, U. C., Bagloee, S. A., Bail, K., Bar, I., Bathelt, J., Benkeser, D., Bernier, M. L., Blanchard, A. M., Boakye, D. W., Bonatsos, V., Boon, M. H., Bouboulis, G., Bromfield, E., Brown, J., Bul, K. C. M., Burton, K. J., Butkowski, E. G., Carroll, G., Chao, F., Charrier, E. E., Chen, Y. -C., Chenguang, Choi, J. R., Christoffersen, T., Comel, J. C., Cosse, C., Cui, Y., van Dessel, P., Dhaval, Diodato, D., Duffey, M., Dutt, A., Egea, L. G., El-Said, M., Faye, M., Fernandez-Fernandez, B., Foley, K. G., Founou, L. L., Fu, F., Gadelkareem, R. A., Galimov, E., Garip, G., Gemmill, A., Gouil, Q., Grey, J., Gridneva, Z., Grothe, M. J., Grebert, T., Guerrero, F., Guignard, L., Haenssgen, M. J., Hasler, D., Holgate, J. Y., Huang, A., Hulse-Kemp, A. M., Jean-Quartier, C., Jeon, S. -M., Jia, Y., Jutzeler, C., Kalatzis, P., Karim, M., Karsay, K., Keitel, A., Kempe, A., Keown, J. R., Khoo, C. M., Khwaja, N., Kievit, R. A., Kosanic, S., Koutoukidis, D. A., Kramer, P., Kumar, D., Kirag, N., Lanza, G., Le, T. D., Leem, J. W., Leightley, D., Leite, A., Lercher, L., Li, Y., Lim, R., Lima, L. R. A., Lin, L., Ling, T., Liu, Y., Liu, Z., Lu, Y., Lum, F. M., Luo, H., Machhi, J., Macleod, A., Macwan, I., Madala, H. R., Madani, N., de Maio, N., Makowiecki, K., Mallinson, D. J., Margelyte, R., Maria, C., Markonis, Y., Marsili, L., Mavoa, S., Mcwilliams, L., Megersa, M., Souto-Maior, C., Menichetti, J., Mercieca-Bebber, R., Miller, J. J., Minde, D. -P. M., Minges, A., Mishra, E., Mishra, V. R., Moores, C., Morrice, N., Moskalensky, A. E., Navarin, N., Negera, E., Nolet, P., Nordberg, A., Norden, R., Nowicki, J. P., Olova, N., Olszewski, P., Onzima, R., Pan, C. -L., Park, C., Park, D. I., Park, S., Patil, C. D., Pedro, S. A., Perry, S. R., Peter, J., Peterson, B. M., Pezzuolo, A., Pozdnyakov, I., Qian, S., Qin, L., Rafe, A., Raote, I., Raza, A., Rebl, H., Refai, O., Regan, T., Richa, T., Richardson, M. F., Robinson, K. R., Rossoni, L., Rouet, R., Safaei, S., Schneeberger, P. H. H., Schwotzer, D., Sebastian, A., Selinski, J., Seltmann, S., Sha, F., Shalev, N., Shang, J. -L., Singer, J., Singh, M., Smith, T., Solomon-Moore, E., Song, L., Soraggi, S., Stanley, R., Steckhan, N., Strobl, F., Subissi, L., Supriyanto, I., Surve, C. R., Suzuki, T., Syme, C., Sorelius, K., Tang, Y., Tantawy, M., Tennakoon, S., Teseo, S., Toelzer, C., Tomov, N., Tovar, M., Tran, L., Tripathi, S., Tuladhar, A. M., Ukubuiwe, A. C., Ung, C. O. L., Valgepea, K., Vatanparast, H., Vidal, A., Wang, Q., Watari, R., Webster, R., Wei, J., Wibowo, D., Wingenbach, T. S. H., Xavier, R. M., Xiao, S., Xiong, P., Xu, S., Yao, R., Yao, W., Yin, Q., Zaitsu, M., Zeineb, Z., Zhan, X. -Y., Zhang, R., Zhang, W., Zheng, S., Zhou, B., Ahmad, H., Akinwumi, S. A., Albery, G. F., Alhowimel, A., Ali, J., Alshehri, M., Alsuhaibani, M., Anikin, A., Azubuike, S. O., Bach-Mortensen, A., Baltiansky, L., Bartas, M., Belachew, K. Y., Bhardwaj, V., Binder, K., Bland, N. S., Boah, M., Bullen, B., Calabro', Giovanna Elisa, Callahan, T. J., Cao, B., Chalmers, K., Chang, W., Che, Z., Chen, A. T. Y., Chen, Z., Choi, Y., Chowdhury, M. A. K., Christensen, M. R., Cooke, R. S. C., Cottini, M., Covington, N. V., Cunningham, C., Delarocque, J., Devos, L., Dhar, A. R., Ding, K. -F., Dong, K., Dong, Z., Dreyer, N., Ekstrand, C., Fardet, T., Feleke, B. E., Feurer, T., Freitas, A., Gao, T., Gebremedhin, Giganti, F., Grabowski, P., Guerra-Mora, J. R., Guo, C., Guo, X., Gupta, H., He, S., Heijne, M., Heinemann, S., Hogrebe, A., Huang, Z., Iskander-Rizk, S., Iyer, L. M., Jahan, Y., James, A. S., Joel, E., Joffroy, B., Jegousse, C., Kambondo, G., Karnati, P., Kaya, C., Ke, A., Kelly, D., Kickert, R., Kidibule, P. E., Kieselmann, J. P., Kim, H. J., Kitazawa, T., Lamberts, A., Liang, H., Linn, S. N., Litfin, T., Liusuo, W., Lygirou, V., Mahato, A. K., Mai, Z. -M., Major, R. W., Mali, S., Mallis, P., Mao, W., Marvin-Dowle, K., Mason, L. D., Merideth, B., Merino-Plaza, M. J., Merlaen, B., Messina, R., Mishra, A. K., Muhammad, J., Musinguzi, C., Nanou, A., Naqash, A., Nguyen, J. T., Nguyen, T. T. H., Ni, D., Nida, Notcovich, S., Ohst, B., Ollivier, Q. R., Osses, D. F., Peng, X., Plantinga, A., Pulia, M., Rafiq, M., Raman, A., Raucher-Chene, Rawski, R., Ray, A., Razak, L. A., Rudolf, K., Rusch, P., Sadoine, M. L., Schmidt, A., Schurr, R., Searles, S., Sharma, S., Sheehan, B., Shi, C., Shohayeb, B., Sommerlad, A., Strehlow, J., Sun, X., Sundar, R., Taherzadeh, G., Tahir, N. D. M., Tang, J., Testa, J., Tian, Z., Tingting, Q., Verheijen, G. P., Vickstrom, C., Wang, T., Wang, X., Wang, Z., Wei, P., Wilson, A., Wyart, Yassine, A. -A., Yousefzadeh, A., Zare, A., Zeng, Z., Zhang, H., Zhou, J., Zhu, D., Adamo, V., Adeyemo, A. A., Aggelidou, M., Al-Owaifeer, A. M., Al-Riyami, A. Z., Alzghari, S. K., Andersen, V., Angus, K., Asaduzzaman, M., Asady, H., Ato, D., Bai, X., Baines, R. L., Ballantyne, M., Ban, B., Beck, J., Ben-Nafa, W., Black, E., Blancher, A., Blankstein, R., Bodagh, N., Borges, P., Brooks, A., Brox-Ponce, J., Brunetti, A., Canham, C. D., Carninci, P., Carvajal, R., Chang, S. C., Chao, J., Chatterjee, P., Chen, L., Chhatriwalla, A. K., Chikowe, I., Chuang, T. -J., Collevatti, R. G., Cornejo, D. A. V., Cuenda, A., Dao, M., Dauga, D., Deng, Z., Devkota, K., Doan, L. V., Elewa, Y. H. A., Fan, D., Faruk, M., Feifei, S., Ferguson, T. S., Fleres, F., Foster, E. J., Foster, S., Furer, T., Gao, Y., Garcia-Rivera, E. J., Gazdar, A., George, R. B., Ghosh, S., Gianchecchi, E., Gleason, J. M., Hackshaw, A., Hall, A., Hall, R., Harper, P., Hogg, W. E., Huang, G., Hunter, K. E., Ijzerman, A. P., Jesus, C., Jian, G., Lewis, J. S., Kanj, S. S., Kaur, H., Kheir, F., Kichatova, V. S., Kiyani, M., Klein, R., Kovesi, T., Kraschnewski, J. L., Kumar, A. P., Labutin, D., Lazo-Langner, A., Leclercq, G., Li, M., Li, Q., Li, T., Liao, W. -T., Liao, Z. -Y., Lin, J., Lizer, J., Lobreglio, G., Lowies, C., Lu, C., Majeed, H., Martin, A., Martinez-Sobrido, L., Meresh, E., Middelveen, M., Mohebbi, A., Mota, J., Mozaheb, Z., Muyaya, L., Nandhakumar, A., Ng, S. H. X., Obeidat, M., Oh, D. -H., Owais, M., Pace-Asciak, P., Panwar, A., Patterson, C., Penagos-Tabaree, F., Pianosi, P. T., Pinzi, V., Pridans, C., Psaroulaki, A., Pujala, R. K., Pulido-Arjona, L., Qi, P. -F., Rahman, P., Rai, N. K., Rassaf, T., Refardt, J., Ricciardi, Walter, Riess, O., Rovas, A., Sacks, F. M., Saleh, S., Sampson, C., Schmutz, A., Sepanski, R., Sharma, N., Spearman, P., Subramaniapillai, M., Swali, R., Tan, C. M., Tellechea, J. I., Thomas, L. -M., Tong, X., Vavvas, D. G., Veys, R., Vitriol, V., Wang, H. -D., Waugh, J., Webb, S. A., Williams, B. A., Workman, A. D., Xiang, T., Xie, L. -X., Xu, T., Yang, C., Yoon, J. G., Yuan, C. M., Zaritsky, A., Zhao, H., Zuckerman, H., Lyu, R., Pullan, W., Calabro G. E. (ORCID:0000-0003-0259-3797), and Ricciardi W. (ORCID:0000-0002-5655-688X)

Abstract

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science.

Published
2019

85. Short note: Splenic abscess

Author

HERMAN, P., OLIVEIRA E SILVA, A., CHAIB, E., D'ALBUQUERQUE, L. C., PUGLIESE, V., MACHADO, M. C. C., and PINOTTI, H. W.

Published
1995

86. Reaction norm for yearling weight in beef cattle using single-step genomic evaluation

Author

Oliveira, D. P. [UNESP], Lourenco, D. A. L., Tsuruta, S., Misztal, I., Santos, D. J. A. [UNESP], Araujo Neto, F. R. de, Aspilcueta-Borquis, R. R., Baldi, F. [UNESP], Carvalheiro, R. [UNESP], Camargo, G. M. F. de [UNESP], Albuquerque, L. G. [UNESP], Tonhati, H. [UNESP], Universidade Estadual Paulista (Unesp), Univ Georgia, Fed Inst Sci & Technol Goiano, and Fed Univ Grande Dourados UFGD

Subjects
performance traits, genotype by environment, Bos taurus indicus, genomic prediction
Abstract

Made available in DSpace on 2018-11-29T08:13:36Z (GMT). No. of bitstreams: 0 Previous issue date: 2018-01-01 Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) When the environment on which the animals are raised is very diverse, selecting the best sires for different environments may require the use of models that account for genotype by environment interaction (G x E). The main objective of this study was to evaluate the existence of G x E for yearling weight (YW) in Nellore cattle using reaction norm models with only pedigree and pedigree combined with genomic relationships. Additionally, genomic regions associated with each environment gradient were identified. A total of 67,996 YW records were used in reaction norm models to calculate EBV and genomic EBV. The method of choice for genomic evaluations was single-step genomic BLUP (ssGBLUP). Traditional and genomic models were tested on the ability to predict future animal performance. Genetic parameters for YW were obtained with the average information restricted maximum likelihood method, with and without adding genomic information for 5,091 animals. Additive genetic variances explained by windows of 200 adjacent SNP were used to identify genomic regions associated with the environmental gradient. Estimated variance components for the intercept and the slope in traditional and genomic models were similar. In both models, the observed changes in heritabilities and genetic correlations for YW across environments indicate the occurrence of genotype by environment interactions. Both traditional and genomic models were capable of identifying the genotype by environment interaction; however, the inclusion of genomic information in reaction norm models improved the ability to predict animals' future performance by 7.9% on average. The proportion of genetic variance explained by the top SNP window was 0.77% for the regression intercept (BTA5) and 0.82% for the slope (BTA14). Single-step GBLUP seems to be a suitable model to predict genetic values for YW in different production environments. Sao Paulo State Univ, Dept Anim Sci, FCAV, BR-14884900 Jaboticabal, Brazil Univ Georgia, Dept Anim & Dairy Sci, Athens, GA 30602 USA Fed Inst Sci & Technol Goiano, Campus Rio Verde, BR-75901970 Rio Verde, Go, Brazil Fed Univ Grande Dourados UFGD, Coll Agr Sci, Dourados, MS, Brazil Sao Paulo State Univ, Dept Anim Sci, FCAV, BR-14884900 Jaboticabal, Brazil CAPES: PDSE 012708/2013-05 FAPESP: 2009/16118-5

Published
2018

87. MÉTODOS DE CONTROLE DE BRAQUIÁRIA (Urochloa decumbens Stapf.) EM ÁREA DE RESTAURAÇÃO ECOLÓGICA DE MATA RIPÁRIA, DF

Author

BARBOSA, J. B. M., GOMES, W. B., MALAQUIAS, J. V., AQUINO, F. de G., ALBUQUERQUE, L. B. de, JUACI VITORIA MALAQUIAS, CPAC, FABIANA DE GOIS AQUINO, CPAC, and LIDIAMAR BARBOSA DE ALBUQUERQUE, CPAC.

Subjects
Controle do capim, Mata ripária, Braquiária, Restauração ecológica
Abstract

Made available in DSpace on 2019-12-18T18:32:10Z (GMT). No. of bitstreams: 1 JuaciMetodosdecontroledebraquiaria.pdf: 945019 bytes, checksum: 1b150762012b4700ef75302a08b2a292 (MD5) Previous issue date: 2018

Published
2018

90. Genome‐enabled prediction of reproductive traits in Nellore cattle using parametric models and machine learning methods.

Author

Alves, A. A. C., Espigolan, R., Bresolin, T., Costa, R. M., Fernandes Júnior, G. A., Ventura, R. V., Carvalheiro, R., and Albuquerque, L. G.

Subjects
PARAMETRIC modeling, MACHINE learning, ARTIFICIAL neural networks, GENETIC correlations, RANDOM forest algorithms, CATTLE
Abstract

Summary: This study aimed to assess the predictive ability of different machine learning (ML) methods for genomic prediction of reproductive traits in Nellore cattle. The studied traits were age at first calving (AFC), scrotal circumference (SC), early pregnancy (EP) and stayability (STAY). The numbers of genotyped animals and SNP markers available were 2342 and 321 419 (AFC), 4671 and 309 486 (SC), 2681 and 319 619 (STAY) and 3356 and 319 108 (EP). Predictive ability of support vector regression (SVR), Bayesian regularized artificial neural network (BRANN) and random forest (RF) were compared with results obtained using parametric models (genomic best linear unbiased predictor, GBLUP, and Bayesian least absolute shrinkage and selection operator, BLASSO). A 5‐fold cross‐validation strategy was performed and the average prediction accuracy (ACC) and mean squared errors (MSE) were computed. The ACC was defined as the linear correlation between predicted and observed breeding values for categorical traits (EP and STAY) and as the correlation between predicted and observed adjusted phenotypes divided by the square root of the estimated heritability for continuous traits (AFC and SC). The average ACC varied from low to moderate depending on the trait and model under consideration, ranging between 0.56 and 0.63 (AFC), 0.27 and 0.36 (SC), 0.57 and 0.67 (EP), and 0.52 and 0.62 (STAY). SVR provided slightly better accuracies than the parametric models for all traits, increasing the prediction accuracy for AFC to around 6.3 and 4.8% compared with GBLUP and BLASSO respectively. Likewise, there was an increase of 8.3% for SC, 4.5% for EP and 4.8% for STAY, comparing SVR with both GBLUP and BLASSO. In contrast, the RF and BRANN did not present competitive predictive ability compared with the parametric models. The results indicate that SVR is a suitable method for genome‐enabled prediction of reproductive traits in Nellore cattle. Further, the optimal kernel bandwidth parameter in the SVR model was trait‐dependent, thus, a fine‐tuning for this hyper‐parameter in the training phase is crucial. [ABSTRACT FROM AUTHOR]

Published
2021
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92. Prediction of meat quality traits in Nelore cattle by near-infrared reflectance spectroscopy

Author

Magalhães, A F B, Teixeira, G H de A, Ríos, A C H, Silva, D B dos S, Mota, L F M, Muniz, M M M, Medeiros-De-morais, Camilo De lelis, de Lima, K M G, Cunha Júnior, L C, Baldi, F, Carvalheiro, R, Oliveira, H N de, Chardulo, L A L, Albuquerque, L G de, Magalhães, A F B, Teixeira, G H de A, Ríos, A C H, Silva, D B dos S, Mota, L F M, Muniz, M M M, Medeiros-De-morais, Camilo De lelis, de Lima, K M G, Cunha Júnior, L C, Baldi, F, Carvalheiro, R, Oliveira, H N de, Chardulo, L A L, and Albuquerque, L G de

Abstract

The main definition for meat quality should include factors that affect consumer appreciation of the product. Physical laboratory analyses are necessary to identify factors that affect meat quality and specific equipment is used for this purpose, which is expensive and destructive, and the analyses are usually time consuming. An alternative method to performing several beef analyses is near-infrared reflectance spectroscopy (NIRS), which permits to reduce costs and to obtain faster, simpler, and non-destructive measurements. The objective of this study was to evaluate the feasibility of NIRS to predict shear force (WBSF), marbling, and color (*a=redness; b*=yellowness and L*=lightness) in meat samples of uncastrated male Nelore cattle, that were approximately 2-year-old. Samples of longissimus thoracis (n=644) were collected and spectra were obtained prior to meat quality analysis. Multivariate calibration was performed by partial least squares regression. Several preprocessing techniques were evaluated alone and in combination: raw data, reduction of spectral range, multiplicative scatter correction, and 1st derivative. Accuracies of the calibration models were evaluated using the root mean square error of calibration (RMSEC), root mean square error of prediction (RMSEP), coefficient of determination in the calibration (R²C) and prediction (R²P) groups. Among the different preprocessing techniques, the reduction of spectral range provided the best prediction accuracy for all traits. The NIRS showed a better performance to predict WBSF (RMSEP = 1.42kg, R²P = 0.40) and b* color (RMSEP = 1.21, R²P = 0.44), while its ability to accurately predict L* (RMSEP = 1.98, R²P = 0.16) and a* (RMSEP = 1.42, R²P = 0.17) was limited. NIRS was unsuitable to predict subjective meat quality traits such as marbling in Nelore cattle.

Published
2018

93. Outcomes of Carbotaxol in Carcinosarcoma : a Retrospective Study At The Brazilian National Cancer institute (inca)

Author

Lope da Silva, J., Albuquerque, L., Gasparotto, A. Letícia, Lima de Aguiar, B. Regina, and Rodrigues, D. de Soussa Barros

Abstract

Objectives: Endometrial carcinosarcomas (EC) are rare metaplastic tumors with dual composition of mesenchymal and epithelial elements, seen as a good example of epithelial-mesenchymal transition (EMT). The current study evaluated the efficacy and safety of Carbotaxol (CT) as adjuvant and first-line (1L) palliative treatment for women with carcinosarcoma.Methods: This retrospective cohort of patients (pts) with EC treated with 3qw Carbotaxol at INCA between January 2012 and January 2017 assessed overall survival (OS), disease-free survival (DFS), progression-free survival (PFS), response rate (RR), and tolerability. All analyses were performed with the SPSS software, version 18.0.Results: A total of 48 pts were enrolled, median age 66.1 years, mostly with stage III disease (43.8%). The median OS for all pts was 21.5 m. For stage IV, OS was 11.1 m. The median DFS for pts treated with adjuvant CT was 20.5 m. For the 21 stage IV pts treated with 1L CT, the median PFS was 6.9 m and median OS was 12.3 m; partial response occured in 9.5%, stable disease in 28.6% and disease progression in 57.1%. The main side effects were asthenia, alopecia, vomiting and myelotoxicity.Conclusions: The combination of carboplatin and paclitaxel has been shown to be effective and safe for the treatment of EH. Staging was confirmed as a strong prognostic factor. The adverse events were manageable and there were no chemo-related deaths. The results were quite similar to those previously reported by multicenter studies.

Published
2017

94. Genome scan for postmortem carcass traits in Nellore cattle

Author

Júnior, G. A. Fernandes [UNESP], Costa, R. B. [UNESP], De Camargo, G. M.F. [UNESP], Carvalheiro, R. [UNESP], Rosa, G. J.M., Baldi, F. [UNESP], Garcia, D. A. [UNESP], Gordo, D. G.M. [UNESP], Espigolan, R. [UNESP], Takada, L. [UNESP], Magalhães, A. F.B. [UNESP], Bresolin, T. [UNESP], Feitosa, F. L.B. [UNESP], Chardulo, L. A.L. [UNESP], De Oliveira, H. N. [UNESP], De Albuquerque, L. G. [UNESP], Universidade Estadual Paulista (Unesp), CNPq, Univ Wisconsin, Dept Zootecnia, and University of Wisconsin–Madison

Subjects
beef cattle, genome-wide association study, backfat thickness, carcass weight, single-step genomic BLUP approach, ribeye area
Abstract

Made available in DSpace on 2018-11-26T17:55:57Z (GMT). No. of bitstreams: 0 Previous issue date: 2016-10-01 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Carcass traits measured after slaughter are economically relevant traits in beef cattle. In general, the slaughter house payment system is based on HCW. Ribeye area (REA) is associated with the amount of the meat in the carcass, and a minimum of backfat thickness (BFT) is necessary to protect the carcass during cooling. The aim of this study was to identify potential genomic regions harboring candidate genes affecting those traits in Nellore cattle. The data set used in the present study consisted of 1,756 Nellore males with phenotype records. A subset of 1,604 animals had both genotypic and phenotypic information. Genotypes were generated based on a panel with 777,962 SNPs from the Illumina Bovine HD chip. The SNP effects were calculated based on the genomic breeding values obtained by using the single-step GBLUP approach and a genomic matrix re-weighting procedure. The proportion of the variance explained by moving windows of 100 consecutive SNPs was used to assess potential genomic regions harboring genes with major effects on each trait. The top 10 non-overlapping SNP-windows explained 8.72%, 11.38%, and 9.31% of the genetic variance for REA, BFT, and HCW, respectively. These windows are located on chromosomes 5, 7, 8, 10, 12, 20, and 29 for REA; chromosomes 6, 8, 10, 13, 16, 17, 18, and 24 for BFT; and chromosomes 4, 6, 7, 8, 14, 16, 17, and 21 for HCW. For REA, there were identified genes (CDKN2A and CDKN2B) involved in the cell cycle biological process which affects many aspects of animal growth and development. The SLC38A1 and SLC38A2 genes, both from SLC38 AA transporter family, was also associated with REA. The AA transporters are essential for cell growth and proliferation, acting as carriers of tissue nutrient supplies. Various genes identified for BFT (SORCS2, AQP3, AQP7, CDC42BPA, ASIP, and ACSS2) have been associated with lipid metabolism in different mammal species. One of the most promising genes identified for HCW was the PLAG1. There is evidence, in the literature, that this gene is located in putative QTL affecting carcass weight in beef cattle. Our results showed several genomic regions containing plausible candidate genes that may be associated with carcass traits in Nellore cattle. Besides contributing to a better understanding of the genetic control of carcass traits, the identified genes can also be helpful for further functional genomic studies. UNESP, Fac Ciencias Agr & Vet, BR-14884000 Jaboticabal, SP, Brazil CNPq, Brasilia, DF, Brazil Univ Wisconsin, Madison, WI 53706 USA UNESP, Fac Med Vet & Zootecnia, BR-18618970 Botucatu, SP, Brazil Dept Zootecnia, Via Acesso Paulo Donato Castellane S-N, BR-14884900 Jaboticabal, SP, Brazil UNESP, Fac Ciencias Agr & Vet, BR-14884000 Jaboticabal, SP, Brazil UNESP, Fac Med Vet & Zootecnia, BR-18618970 Botucatu, SP, Brazil FAPESP: 2009/16118-5 FAPESP: 2015/06140-4

Published
2016

95. Comparison of models for the genetic evaluation of reproductive traits with censored data in Nellore cattle

Author

Garcia, D. A. [UNESP], Rosa, G. J. M., Valente, B. D., Carvalheiro, R. [UNESP], Albuquerque, L. G. [UNESP], Universidade Estadual Paulista (Unesp), University of Wisconsin–Madison, and Univ Wisconsin

Subjects
Days to calving, Beef cattle, Age at first calving, Bayesian models
Abstract

Made available in DSpace on 2018-12-11T17:28:44Z (GMT). No. of bitstreams: 0 Previous issue date: 2016-06-01 Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) In typical genetic evaluation, often some females have missing records due to reproductive failure and due to voluntary and involuntary culling before the breeding season. These partially or unobserved phenotypes are known as censored records and their inclusion into genetic evaluations might lead to better inferences and breeding value predictions. Then, the objective was to compare prediction ability of models in which the phenotypic expression of age at the first calving (AFC) and days to calving (DC) were considered to be censored and uncensored in a Nellore cattle population. Age at first calving and days to calving were analyzed as following: uncensored animals (LM); penalization of 21 d (PLM); censored records simulated from truncated normal distributions (CLM); threshold-linear model in which censored records were handled as missing (TLM) or coded as the upper AFC/DC value within contemporary group (PTLM); and Weibull frailty hazard model (WM). Pearson correlations (PC), the percentage of the 10% best bulls in common (pTOP10%), accuracy of estimated breeding values (r), and a cross-validation scheme were performed. Heritability estimates for AFC were 0.18, 0.12, 0.12, 0.17, 0.14, and 0.07 for LM, PLM, CLM, TLM, PTLM, and WM, respectively. PC and pTOP10% were higher among linear models and smaller between these models and WM. The models provided similar r of sire breeding values. Heritability estimates for DC were 0.03, 0.08, 0.06, 0.02, 0.07, and 0.10 for LM, PLM, CLM, TLM, PTLM, and WM, respectively. Strongly associated predictions were observed in CLM, PLM, PTLM, and WM. The highest coincidence levels of sires in the TOP10% were between CLM, PLM, and PTLM. The r of sire breeding values obtained applying CLM, PLM, PTLM, and WM were similar and higher than those obtained with LM and TLM. In terms of prediction ability, WM, PLM, TLM, and PTLM showed similar prediction performance for AFC. On the other hand, CLM, PLM, PTLM, and WM showed the similar prediction ability for DC Therefore, these models would be recommended to perform genetic evaluation of age at first calving and days to calving in this Nellore population. Department of Animal Science UNESP, Prof. Paulo Donato Castellani Road Department of Animal Science University of Wisconsin–Madison, 1675 Observatory Drive Department of Animal Science UNESP, Prof. Paulo Donato Castellani Road CAPES: 1817-12-4 FAPESP: 2009/15010-6

Published
2016

96. Genetic parameter estimates for carcass traits and visual scores including or not genomic information

Author

Gordo, D. G. M. [UNESP], Espigolan, R. [UNESP], Tonussi, R. L. [UNESP], Junior, G. A. F. [UNESP], Bresolin, T. [UNESP], Braga Magalhaes, A. F. [UNESP], Feitosa, F. L. [UNESP], Baldi, F. [UNESP], Carvalheiro, R. [UNESP], Tonhati, H. [UNESP], Oliveira, H. N. de [UNESP], Chardulo, L. A. L. [UNESP], Albuquerque, L. G. de [UNESP], Universidade Estadual Paulista (Unesp), and Dept Zootecnia

Subjects
beef cattle, single nucleotide polymorphism, fat thickness, longissimus muscle area, heritability, genetic correlation
Abstract

Made available in DSpace on 2018-11-26T17:55:50Z (GMT). No. of bitstreams: 0 Previous issue date: 2016-05-01 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) The objective of this study was to determine whether visual scores used as selection criteria in Nellore breeding programs are effective indicators of carcass traits measured after slaughter. Additionally, this study evaluated the effect of different structures of the relationship matrix (A and H) on the estimation of genetic parameters and on the prediction accuracy of breeding values. There were 13,524 animals for visual scores of conformation (CS), finishing precocity (FP), and muscling (MS) and 1,753, 1,747, and 1,564 for LM area (LMA), backfat thickness (BF), and HCW, respectively. Of these, 1,566 animals were genotyped using a high-density panel containing 777,962 SNP. Six analyses were performed using multitrait animal models, each including the 3 visual scores and 1 carcass trait. For the visual scores, the model included direct additive genetic and residual random effects and the fixed effects of contemporary group (defined by year of birth, management group at yearling, and farm) and the linear effect of age of animal at yearling. The same model was used for the carcass traits, replacing the effect of age of animal at yearling with the linear effect of age of animal at slaughter. The variance and covariance components were estimated by the REML method in analyses using the numerator relationship matrix (A) or combining the genomic and the numerator relationship matrices (H). The heritability estimates for the visual scores obtained with the 2 methods were similar and of moderate magnitude (0.23-0.34), indicating that these traits should response to direct selection. The heritabilities for LMA, BF, and HCW were 0.13, 0.07, and 0.17, respectively, using matrix A and 0.29, 0.16, and 0.23, respectively, using matrix H. The genetic correlations between the visual scores and carcass traits were positive, and higher correlations were generally obtained when matrix H was used. Considering the difficulties and cost of measuring carcass traits postmortem, visual scores of CS, FP, and MS could be used as selection criteria to improve HCW, BF, and LMA. The use of genomic information permitted the detection of greater additive genetic variability for LMA and BF. For HCW, the high magnitude of the genetic correlations with visual scores was probably sufficient to recover genetic variability. The methods provided similar breeding value accuracies, especially for the visual scores. Univ Estadual Paulista, Fac Ciencias Agr & Vet, BR-14884900 Jaboticabal, SP, Brazil Univ Estadual Paulista, Fac Med Vet & Zootecnia, BR-18618970 Botucatu, SP, Brazil Dept Zootecnia, Via Acesso Paulo Donato Castellane S-N, BR-14884900 Jaboticabal, SP, Brazil Univ Estadual Paulista, Fac Ciencias Agr & Vet, BR-14884900 Jaboticabal, SP, Brazil Univ Estadual Paulista, Fac Med Vet & Zootecnia, BR-18618970 Botucatu, SP, Brazil FAPESP: 2009/16118-5 FAPESP: 2014/11537-8

Published
2016

97. Genetic parameters for milk yield of Bubalus bubalis using unadjusted and adjusted milk production for days in milk

Author

Tonhati, H. [UNESP], Baldi, F. S. [UNESP], Laureano, M. M.M. [UNESP], Albuquerque, L. G. [UNESP], Universidade Estadual Paulista (Unesp), Universidade Estadual Paulista (UNESP), and CAPES

Subjects
Spearman correlations, Genetic parameters, Lactation length, Milk production, Spearman correlations, Milk production, lcsh:Animal culture, Genetic parameters, Lactation length, lcsh:SF1-1100
Abstract

Submitted by Guilherme Lemeszenski (guilherme@nead.unesp.br) on 2014-02-26T17:18:33Z No. of bitstreams: 1 WOS000207598400042.pdf: 120641 bytes, checksum: 956b0ad7b27c7f0d2d13df6f51dba419 (MD5) Made available in DSpace on 2014-02-26T17:18:33Z (GMT). No. of bitstreams: 1 WOS000207598400042.pdf: 120641 bytes, checksum: 956b0ad7b27c7f0d2d13df6f51dba419 (MD5) Previous issue date: 2007-01-01 Submitted by Vitor Silverio Rodrigues (vitorsrodrigues@reitoria.unesp.br) on 2014-05-20T13:18:02Z No. of bitstreams: 1 WOS000207598400042.pdf: 120641 bytes, checksum: 956b0ad7b27c7f0d2d13df6f51dba419 (MD5) Made available in DSpace on 2014-05-20T13:18:02Z (GMT). No. of bitstreams: 1 WOS000207598400042.pdf: 120641 bytes, checksum: 956b0ad7b27c7f0d2d13df6f51dba419 (MD5) Previous issue date: 2007-01-01 Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) The objectives of this study were to estimate genetic parameters for unadjusted and adjusted milk production for 270 and 305 days of lactation and, subsequently, to verify the coincidence of rank of 2%, 5%, 20% and 40% best sires selected based on both models. Complete lactations from 90 or 150 days of lactation to 270 or 350 days of lactation were considered in the analyses. Milk production was adjusted for lactation length by multiplicative correction factors, or by including lactation length as a covariable in the model. Heritabilities, genetic correlations and breeding values were estimated for each trait, and variance and covariance components were estimated by restricted maximum likelihood methodology. Heritability estimates varied from 0.16 to 0.27. Genetic correlations between unadjusted and adjusted milk production for lactation length were higher than 0.64. Heritabilities for adjusted milk production were higher than heritabilities for unadjusted milk production for lactation length. In situations with high selection intensity, probably, modifications will happen in the rank of bulls and/or in the bulls chosen for mating if records are adjusted or unadjusted for 305 days. Univ São Paulo State, Dept Zootecnia, Fac Ciências Agr & Vet, UNESP, BR-14884000 Jaboticabal, SP, Brazil CNPq, FAPESP, CAPES, Campinas, SP, Brazil Univ São Paulo State, Dept Zootecnia, Fac Ciências Agr & Vet, UNESP, BR-14884000 Jaboticabal, SP, Brazil

Published
2010

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