Effect of amino acid blend as alternative to antibiotics for growing pigs.

This study aimed to evaluate the effect of supplementing arginine (Arg) + glutamine (Gln) replacing antibiotics on performance, immune response, and antioxidant capacity of pigs in the growing phase. One hundred fifty 63-d-old pigs with initial body weight (BW) of 25.0 ± 1.46 kg were distributed in a randomized block design, with three treatments and ten replicates. The three diets were control; antibiotic, control + 100 mg/kg tiamulin and 506 mg/kg oxytetracycline; amino acid, control + 10 g/kg Arg and 2 g/kg Gln. Dietary treatments were fed from 63 to 77 d. Following the treatment period, all pigs were fed the control diet from 77 to 90 d. Data were analyzed using GLIMMIX and UNIVARIATE in SAS 9.4. From 63 to 70 d, pigs fed diets with antibiotics had improved (P < 0.05) average daily feed intake, average daily weight gain (ADG), gain to feed ratio (G:F), and 70-d BW compared to those fed control or amino acid diets. From 70 to 77 d, including antibiotics in the diet increased (P < 0.05) ADG and 77-d BW. From 77 to 90 d, pigs fed control or amino acid diets had greater (P < 0.05) ADG than those fed an antibiotic diet. From 63 to 90 d, although pig performance was not affected (P > 0.05), growth curve of pigs fed the antibiotic diets was different (P < 0.05) from those fed the control and amino acids diets. At 70 d, serum tumor necrosis factor-α and diamine oxidase (DAO) were lower (P < 0.05) in pigs fed the antibiotic diet than the control diet, and pigs fed the amino acid diet had intermediate results. Ferric reducing antioxidant power (FRAP) was lower (P < 0.05) in pigs fed the amino acid diet than the antibiotic diet, and pigs fed the control diet had intermediate results. Serum immunoglobulin A was lower (P < 0.05) in pigs fed the antibiotic diet. At 77 d, DAO and serum immunoglobulin G were lower (P < 0.05) in pigs fed the antibiotic diet. FRAP was lower (P < 0.05) in pigs fed the amino acid and control diets. Serum malondialdehyde was higher (P < 0.05) in pigs fed the amino acid diet than those fed the control diet, and pigs fed the antibiotic diet had intermediate results. At 90 d, antibiotics or amino acids did not affect (P > 0.05) serum parameters. Amino acid blend supplementation at the selected doses in this study did not positively affect growing pigs. Although from 63 to 77 d, antibiotics improved performance, when considering the overall study period, growing pigs did not benefit from a diet containing antibiotics.

Dietary antibiotics have been used in pig farming practices to avoid health problems, improving animal growth performance. However, antimicrobial resistance due to the use of antibiotics in farms is considered to be a global health challenge. Arginine and glutamine are amino acids with potential to improve gut health, immune function, and growth performance. Thus, the study aimed to evaluate the supplementation of those amino acids as an alternative to the use of dietary antibiotic for pigs. Moreover, after a 14-d treatment phase, we still monitor the pigs to evaluate the carryover effects of the antibiotics and amino acids. Amino acid supplementation at the selected doses in this study did not positively affect pigs. Although during the treatment phase, antibiotics improved performance, when considering the overall study period, pigs did not benefit from a diet containing antibiotics. Thus, antibiotics caused transient alterations in pig performance and should be further investigated, potentially guiding future research on its use and alternative technologies.

Cell cycle and aging, morphogenesis, and response to stimuli genes are individualized biomarkers of glioblastoma progression and survival.

BACKGROUND: Glioblastoma is a complex multifactorial disorder that has swift and devastating consequences. Few genes have been consistently identified as prognostic biomarkers of glioblastoma survival. The goal of this study was to identify general and clinical-dependent biomarker genes and biological processes of three complementary events: lifetime, overall and progression-free glioblastoma survival. METHODS: A novel analytical strategy was developed to identify general associations between the biomarkers and glioblastoma, and associations that depend on cohort groups, such as race, gender, and therapy. Gene network inference, cross-validation and functional analyses further supported the identified biomarkers. RESULTS: A total of 61, 47 and 60 gene expression profiles were significantly associated with lifetime, overall, and progression-free survival, respectively. The vast majority of these genes have been previously reported to be associated with glioblastoma (35, 24, and 35 genes, respectively) or with other cancers (10, 19, and 15 genes, respectively) and the rest (16, 4, and 10 genes, respectively) are novel associations. Pik3r1, E2f3, Akr1c3, Csf1, Jag2, Plcg1, Rpl37a, Sod2, Topors, Hras, Mdm2, Camk2g, Fstl1, Il13ra1, Mtap and Tp53 were associated with multiple survival events.Most genes (from 90 to 96%) were associated with survival in a general or cohort-independent manner and thus the same trend is observed across all clinical levels studied. The most extreme associations between profiles and survival were observed for Syne1, Pdcd4, Ighg1, Tgfa, Pla2g7, and Paics. Several genes were found to have a cohort-dependent association with survival and these associations are the basis for individualized prognostic and gene-based therapies. C2, Egfr, Prkcb, Igf2bp3, and Gdf10 had gender-dependent associations; Sox10, Rps20, Rab31, and Vav3 had race-dependent associations; Chi3l1, Prkcb, Polr2d, and Apool had therapy-dependent associations. Biological processes associated glioblastoma survival included morphogenesis, cell cycle, aging, response to stimuli, and programmed cell death. CONCLUSIONS: Known biomarkers of glioblastoma survival were confirmed, and new general and clinical-dependent gene profiles were uncovered. The comparison of biomarkers across glioblastoma phases and functional analyses offered insights into the role of genes. These findings support the development of more accurate and personalized prognostic tools and gene-based therapies that improve the survival and quality of life of individuals afflicted by glioblastoma multiforme.