Salmonella spp. is an important pathogen to both public and swine industry. The aim of this study was to investigate the distribution of Salmonella serovar and antibiotics susceptibility of the isolates from Korean swine producing systems. A total of 63 (5.28%) Salmonella spp. was isolated from 1,194 samples (977 fecal materials and 67 organ samples). The predominant Salmonella (S.) enterica serotype and serovar was group B (69.8%) and S. Typhimurium (47.6%), S. Derby (20.6%) and S. Heidelberg (1.6%). But S. Cholerasuis which is characterized host specific by septicemia and enteritis to pigs was not isolated. Antimicrobial susceptibility of the isolates varies as follows: Norfloxacine (75%), Ciprofloxacin (67.5%), Amikacin (60%), Colistin (60%), Enrofloxacin (55%). All of isolates were resistant to Erythromycin, Penicillin, Tetracycline and Lincomycin. The results of this study provided useful information regarding antimicrobial susceptibility and resistance patterns to treat salmonellosis and to prevent emergence of multidrug resistance Salmonella.
Amikacin ; Anti-Bacterial Agents ; Ciprofloxacin ; Colistin ; Drug Resistance, Multiple ; Enteritis ; Erythromycin ; Fluoroquinolones ; Lincomycin ; Norfloxacin ; Penicillins ; Salmonella ; Salmonella Infections ; Sepsis ; Swine ; Tetracycline

The C-terminal domain of RNA polymerase II is an unusual series of repeated residues appended to the C-terminus of the largest subunit and serves as a flexible binding scaffold for numerous nuclear factors. The binding of these factors is determined by the phosphorylation patterns on the repeats in the domain. In this study, we generated a synthetic antibody library by replacing the third heavy chain complementarity-determining region of an anti-HER2 (human epidermal growth factor receptor 2) antibody (trastuzumab) with artificial sequences of 7–18 amino-acid residues. From this library, antibodies were selected that were specific to serine phosphopeptides that represent typical phosphorylation patterns on the functional unit (YSPTSPS)₂ of the RNA polymerase II C-terminal domain (CTD). Antibody clones pCTD-1stS2 and pCTD-2ndS2 showed specificity for peptides with phosphoserine at the second residues of the first or second heptamer repeat, respectively. Additional clones specifically reacted to peptides with phosphoserine at the fifth serine of the first repeat (pCTD-1stS5), the seventh residue of the first repeat and fifth residue of the second repeat (pCTD-S7S5) or the seventh residue of either the first or second repeat (pCTD-S7). All of these antibody clones successfully reacted to RNA polymerase II in immunoblot analysis. Interestingly, pCTD-2ndS2 precipitated predominately RNA polymerase II from the exonic regions of genes in genome-wide chromatin immunoprecipitation sequencing analysis, which suggests that the phosphoserine at the second residue of the second repeat of the functional unit (YSPTSPS)2 is a mediator of exon definition.
Antibodies ; Chromatin Immunoprecipitation ; Clone Cells ; Complementarity Determining Regions ; DNA-Directed RNA Polymerases* ; Exons* ; Peptides ; Phosphopeptides ; Phosphorylation* ; Phosphoserine ; Receptor, Epidermal Growth Factor ; RNA Polymerase II* ; RNA* ; Sensitivity and Specificity ; Serine

Background/Aims: Combination immunotherapy, exemplified by atezolizumab plus bevacizumab, has become the standard of care for inoperable hepatocellular carcinoma (HCC). However, the lack of predictive biomarkers and limited understanding of response mechanisms remain a challenge. Methods: Using data from the IMbrave150plus cohort, we applied an immune signature score (ISS) predictor to stratify HCC patients treated with atezolizumab plus bevacizumab or with sorafenib alone into potential high and low response groups. By applying multiple statistical approaches including a Bayesian covariate prediction algorithm, we refined the signature to 10 key genes (ISS10) for clinical use while maintaining similar predictive power to the full model. We further validated ISS10 in an independent HCC cohort treated with nivolumab plus ipilimumab. Results: The study identified a significant association between the ISS and treatment response. Among patients classified as high responders, those treated with the atezolizumab plus bevacizumab combination exhibited improved overall and progression-free survival as well as better objective response rate compared to those treated with sorafenib. We also observed a significant correlation between ISS10 and response to nivolumab plus ipilimumab treatment. Analysis of immune cell subpopulations revealed distinct characteristics associated with ISS subtypes. In particular, the ISS10 high subtype displayed a more favorable immune environment with higher proportions of antitumor macrophages and activated T-cells, potentially explaining its better response. Conclusions Our study suggests that ISS and ISS10 are promising predictive biomarkers for enhanced therapeutic outcomes in HCC patients undergoing combination immunotherapy. These markers are crucial for refining patient stratification and personalized treatment approaches to advance the effectiveness of standard-of-care regimens.

Background/Aims: Combination immunotherapy, exemplified by atezolizumab plus bevacizumab, has become the standard of care for inoperable hepatocellular carcinoma (HCC). However, the lack of predictive biomarkers and limited understanding of response mechanisms remain a challenge. Methods: Using data from the IMbrave150plus cohort, we applied an immune signature score (ISS) predictor to stratify HCC patients treated with atezolizumab plus bevacizumab or with sorafenib alone into potential high and low response groups. By applying multiple statistical approaches including a Bayesian covariate prediction algorithm, we refined the signature to 10 key genes (ISS10) for clinical use while maintaining similar predictive power to the full model. We further validated ISS10 in an independent HCC cohort treated with nivolumab plus ipilimumab. Results: The study identified a significant association between the ISS and treatment response. Among patients classified as high responders, those treated with the atezolizumab plus bevacizumab combination exhibited improved overall and progression-free survival as well as better objective response rate compared to those treated with sorafenib. We also observed a significant correlation between ISS10 and response to nivolumab plus ipilimumab treatment. Analysis of immune cell subpopulations revealed distinct characteristics associated with ISS subtypes. In particular, the ISS10 high subtype displayed a more favorable immune environment with higher proportions of antitumor macrophages and activated T-cells, potentially explaining its better response. Conclusions Our study suggests that ISS and ISS10 are promising predictive biomarkers for enhanced therapeutic outcomes in HCC patients undergoing combination immunotherapy. These markers are crucial for refining patient stratification and personalized treatment approaches to advance the effectiveness of standard-of-care regimens.

Background/Aims: Combination immunotherapy, exemplified by atezolizumab plus bevacizumab, has become the standard of care for inoperable hepatocellular carcinoma (HCC). However, the lack of predictive biomarkers and limited understanding of response mechanisms remain a challenge. Methods: Using data from the IMbrave150plus cohort, we applied an immune signature score (ISS) predictor to stratify HCC patients treated with atezolizumab plus bevacizumab or with sorafenib alone into potential high and low response groups. By applying multiple statistical approaches including a Bayesian covariate prediction algorithm, we refined the signature to 10 key genes (ISS10) for clinical use while maintaining similar predictive power to the full model. We further validated ISS10 in an independent HCC cohort treated with nivolumab plus ipilimumab. Results: The study identified a significant association between the ISS and treatment response. Among patients classified as high responders, those treated with the atezolizumab plus bevacizumab combination exhibited improved overall and progression-free survival as well as better objective response rate compared to those treated with sorafenib. We also observed a significant correlation between ISS10 and response to nivolumab plus ipilimumab treatment. Analysis of immune cell subpopulations revealed distinct characteristics associated with ISS subtypes. In particular, the ISS10 high subtype displayed a more favorable immune environment with higher proportions of antitumor macrophages and activated T-cells, potentially explaining its better response. Conclusions Our study suggests that ISS and ISS10 are promising predictive biomarkers for enhanced therapeutic outcomes in HCC patients undergoing combination immunotherapy. These markers are crucial for refining patient stratification and personalized treatment approaches to advance the effectiveness of standard-of-care regimens.

Background/Aims: Combination immunotherapy, exemplified by atezolizumab plus bevacizumab, has become the standard of care for inoperable hepatocellular carcinoma (HCC). However, the lack of predictive biomarkers and limited understanding of response mechanisms remain a challenge. Methods: Using data from the IMbrave150plus cohort, we applied an immune signature score (ISS) predictor to stratify HCC patients treated with atezolizumab plus bevacizumab or with sorafenib alone into potential high and low response groups. By applying multiple statistical approaches including a Bayesian covariate prediction algorithm, we refined the signature to 10 key genes (ISS10) for clinical use while maintaining similar predictive power to the full model. We further validated ISS10 in an independent HCC cohort treated with nivolumab plus ipilimumab. Results: The study identified a significant association between the ISS and treatment response. Among patients classified as high responders, those treated with the atezolizumab plus bevacizumab combination exhibited improved overall and progression-free survival as well as better objective response rate compared to those treated with sorafenib. We also observed a significant correlation between ISS10 and response to nivolumab plus ipilimumab treatment. Analysis of immune cell subpopulations revealed distinct characteristics associated with ISS subtypes. In particular, the ISS10 high subtype displayed a more favorable immune environment with higher proportions of antitumor macrophages and activated T-cells, potentially explaining its better response. Conclusions Our study suggests that ISS and ISS10 are promising predictive biomarkers for enhanced therapeutic outcomes in HCC patients undergoing combination immunotherapy. These markers are crucial for refining patient stratification and personalized treatment approaches to advance the effectiveness of standard-of-care regimens.