High Concentrations of the Antibiotic Spiramycin in Wastewater Lead to High Abundance of Ammonia-Oxidizing Archaea in Nitrifying Populations

To evaluate the potential effects of antibiotics on ammonia-oxidizing microbes, multiple tools including quantitative PCR (qPCR), 454-pyrosequencing, and a high-throughput functional gene array (GeoChip) were used to reveal the distribution of ammonia-oxidizing archaea (AOA) and archaeal <i>amoA</i> (Arch-<i>amoA</i>) genes in three wastewater treatment systems receiving spiramycin or oxytetracycline production wastewaters. The qPCR results revealed that the copy number ratios of Arch-<i>amoA</i> to ammonia-oxidizing bacteria (AOB) <i>amoA</i> genes were the highest in the spiramycin full-scale (5.30) and pilot-scale systems (1.49 × 10^–1), followed by the oxytetracycline system (4.90 × 10^–4), with no Arch-<i>amoA</i> genes detected in the control systems treating sewage or inosine production wastewater. The pyrosequencing result showed that the relative abundance of AOA affiliated with Thaumarchaeota accounted for 78.5–99.6% of total archaea in the two spiramycin systems, which was in accordance with the qPCR results. Mantel test based on GeoChip data showed that Arch-<i>amoA</i> gene signal intensity correlated with the presence of spiramycin (<i>P</i> < 0.05). Antibiotics explained 25.8% of variations in <i>amoA</i> functional gene structures by variance partitioning analysis. This study revealed the selection of AOA in the presence of high concentrations of spiramycin in activated sludge systems

Association between circulating ANGPTL levels and general medical status (n = 800).

<p>A generalized linear model was used. All variables listed were included in the model. ANGPTL, Angiopoietin-like protein; β, regression coefficient; 95% CI, 95% confidence interval; P, probability; and CKD, chronic kidney disease.</p

Baseline characteristics of study population subjects.

<p>Data is shown as the median or interquartile range (IQR); BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; HbA_1C, hemoglobin A_1C; LDL, low-density lipoprotein; HDL, high-density lipoprotein; AST, aspartate transaminase; ALT, alanine transaminase; GGT, gamma-glutamyltransferase; eGFR, estimated glomerular filtration rate; Hb, hemoglobin; and hs-CRP, high-sensitivity C reactive protein.</p

Association between circulating ANGPTL4 levels and laboratory tests relevant to impaired glycometabolism, hepatic impairment or inflammation (n = 800).

<p>A generalized linear model was used. To evaluate HbA_1C or glucose, each covariate was adjusted by all variables listed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0193731#pone.0193731.t003" target="_blank">Table 3</a>, minus the impaired glyometabolism category. To evaluate AST, ALT, or GGT, each covariate was adjusted by all variables listed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0193731#pone.0193731.t003" target="_blank">Table 3</a>, minus the hepatic impairment category. To evaluate hs-CRP, each covariate was adjusted by all variables listed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0193731#pone.0193731.t003" target="_blank">Table 3</a>, minus inflammation. β, regression coefficient; 95% CI, 95% confidence interval; HbA_1C, hemoglobin A_1C; AST, aspartate transaminase; ALT, alanine transaminase; GGT, Gamma-glutamyltransferase; and hs-CRP, high sensitivity C reactive protein.</p

Baseline characteristics of subjects of study population.

<p>Data is shown as the percentage or 95% confidence interval (95%CI). CKD, chronic kidney disease.</p

Association between circulating ANGPTL3 levels and lab values relevant to hepatic impairment or inflammation (n = 800).

<p>A generalized linear model was used. To evaluate AST, ALT or GGT, covariates were adjusted by all variables listed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0193731#pone.0193731.t003" target="_blank">Table 3</a>, minus the hepatic impairment category. To evaluate hs-CRP, covariates were adjusted by all variables listed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0193731#pone.0193731.t003" target="_blank">Table 3</a>, minus the inflammation category. β, regression coefficient; 95% CI, 95% confidence interval; AST, aspartate transaminase; ALT, alanine transaminase; GGT, gamma-glutamyltransferase; and hs-CRP, high sensitivity C reactive protein.</p

Association between circulating ANGPTL8 levels and laboratory tests relevant to obesity, impaired glycometabolism, or dyslipidemia (n = 800).

<p>A generalized linear model was used. To evaluate BMI, each covariate was adjusted by all variables listed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0193731#pone.0193731.t003" target="_blank">Table 3</a>, minus obesity. To evaluate HbA1C or glucose, each covariate was adjusted by all variables listed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0193731#pone.0193731.t003" target="_blank">Table 3</a>, minus the impaired glycometabolism catergory. To evaluate HDL, LDL or triglyceride, each covariate was adjusted by all variables listed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0193731#pone.0193731.t003" target="_blank">Table 3</a>, minus the dyslipidemia category. BMI, body mass index; HbA1C, hemoglobin A1C; HDL, high-density lipoprotein cholesterol; LDL, low-density lipoprotein cholesterol; TG, triglyceride; β, regression coefficient; and 95% CI, 95% confidence interval.</p

Association of circulating ANGPTL 3, 4, and 8 levels with medical status in a population undergoing routine medical checkups: A cross-sectional study - Fig 1

<p>Distribution of circulating levels of (A) ANGPTL3, (B) ANGPTL4, and (C) ANGPTL8. IQR, Interquartile range (n = 988).</p

Racial/ethnic disparities in the distribution and effect of type and number of high-risk criteria on mortality in prostate cancer patients treated with radiotherapy

To assess differences in the distribution of type and number of D’Amico high-risk criteria (DHRCs) according to race/ethnicity (R/E) and their effect on cancer-specific mortality (CSM) in prostate cancer (PCa) patients treated with external beam radiotherapy (RT). In the SEER database (2004–2016), we identified 31,002 PCa patients treated with RT with at least one DHRCs, namely PSA >20 ng/dL, biopsy Gleason Grade Group 4–5, and clinical T stage ≥T2c. Competing risks regression (CRR) model tested the association between DHRCs and 5-year CSM in all R/E subgroups. Of 31,002 patients, 20,894 (67%) were Caucasian, 5256 (17%) were African American, 2868 (9.3%) were Hispanic-Latino, and 1984 (6.4%) were Asian. The distributions of individual DHRCs and combinations of two DHRCs differed according to R/E, but not for the combination of three DHRCs. The effect related to the presence of a single DHRC, and combinations of two or three DHRCs on absolute CSM rates was lowest in Asians (1.2–6.8%), followed by in African Americans (2.3–12.2%) and Caucasians (2.3–12.1%), and highest in Hispanic/Latinos (1.7–13.8%). However, the opposite effect was observed in CRR, where hazard ratios were highest in Asians vs. other R/Es: Asians 1.00–2.59 vs. others 0.5–1.83 for one DHRC, Asians 3.4–4.75 vs. others 0.66–3.66 for two DHRCs, and Asians 7.22 vs. others 3.03–4.99 for all three DHRCs. R/E affects the proportions of DHRCs. Moreover, within the four examined R/E groups, the effect of DHRCs on absolute and relative CSM metrics also differed. Therefore, R/E-specific considerations may be warranted in high-risk PCa patients treated with RT.</p