Occurrence and effects of pharmaceuticals in estuaries

Pharmaceuticals have been identified as emerging contaminants of concern due to their widespread occurrence in the aquatic environment and potential to be biologically active, yet the implications of their presence in the environment is not fully known. There is a plethora of pharmaceuticals commercially available making it unfeasible to carry out detailed investigations on all of these compounds, and prioritisation schemes can provide a useful tool to determine how best to direct resources. Different prioritisation schemes were carried out on the fifty most prescribed drugs in the UK, and their results were compared in order to assess the efficacy of these schemes. Many failed to accurately identify these risks, but a holistic approach using more than one method to generate a priority list of compounds, may provide better protection for the environment. To date, most monitoring and ecotoxicological studies have focused on pharmaceuticals in freshwater, and there is less understanding of their occurrence and effects in estuaries. In order to gain insight into their spatio-temporal patterns, five pharmaceuticals were monitored in the Humber Estuary every other month for twelve months. Patterns in their spatial and temporal occurrence were related to source points, consumption patterns and environmental conditions. Eleven further estuaries were monitored to give an overall picture of pharmaceutical pollution in the UK. The Humber Estuary contained highest levels of pharmaceuticals and concentrations of ibuprofen were the highest measured globally. Finally, ragworms (Hediste diversicolor) were exposed to diclofenac and metformin in a controlled experimental exposure, and the expression of selected target genes, ATP synthase and c-amp activated protein kinase was measured. Highest levels of metformin (1 µg l-1) were found to significantly increase expression of ATP synthase, indicating that this drug induces environmental stress in H. diversicolor. Overall, this body of research has further contributed to the knowledge of pharmaceuticals as emerging contaminants in estuaries, and information on the occurrence, current levels and biological effects of the drugs studied may be of interest to regulators in their management decisions for such environments

Exercise Increases Bone in SEIPIN Deficient Lipodystrophy, Despite Low Marrow Adiposity

Exercise, typically beneficial for skeletal health, has not yet been studied in lipodystrophy, a condition characterized by paucity of white adipose tissue, with eventual diabetes, and steatosis. We applied a mouse model of global deficiency of Bscl2 (SEIPIN), required for lipid droplet formation. Male twelve-week-old B6 knockouts (KO) and wild type (WT) littermates were assigned six-weeks of voluntary, running exercise (E) versus non-exercise (N=5-8). KO weighed 14% less than WT (p=0.01) and exhibited an absence of epididymal adipose tissue; KO liver Plin1 via qPCR was 9-fold that of WT (p=0.04), consistent with steatosis. Bone marrow adipose tissue (BMAT), unlike white adipose, was measurable, although 40.5% lower in KO vs WT (p=0.0003) via 9.4T MRI/advanced image analysis. SEIPIN ablation’s most notable effect marrow adiposity was in the proximal femoral diaphysis (-56% KO vs WT, p=0.005), with relative preservation in KO-distal-femur. Bone via μCT was preserved in SEIPIN KO, though some quality parameters were attenuated. Running distance, speed, and time were comparable in KO and WT. Exercise reduced weight (-24% WT-E vs WT p<0.001) but not in KO. Notably, exercise increased trabecular BV/TV in both (+31%, KO-E vs KO, p=0.004; +14%, WT-E vs WT, p=0.006). The presence and distribution of BMAT in SEIPIN KO, though lower than WT, is unexpected and points to a uniqueness of this depot. That trabecular bone increases were achievable in both KO and WT, despite a difference in BMAT quantity/distribution, points to potential metabolic flexibility during exercise-induced skeletal anabolism

Correlation between C-reactive protein and BMD by sex.

Correlation between C-reactive protein and femoral neck BMD among A) all respondents, B) females, and C) males. Correlation between C-reactive protein and spine BMD among D) all respondents, E) females, and F) males. Plotted line indicates trendline, with slope of Kendall’s tau. Correlations assessed using non-parametric Kendall’s rank correlation test.</p

Modeling to identify best predictor of BMD.

A reliable, widely available method to detect osteoporosis prior to fracture is needed. Serum levels of C-reactive protein may independently predict low bone mineral density (BMD) and high fracture risk. Existing empirical data focus on sexually and/or racially homogenous populations. This study tests the hypotheses that: C-reactive protein (1) negatively correlates with BMD and (2) fracture history, and (3) independently predicts BMD and fracture history in a diverse population. NHANES 2017–2020 pre-pandemic cycle data were analyzed in R studio. Strength and direction of relationships (-1 to +1) between variables were determined using Kendall’s rank correlation coefficient (τ). Linear models were optimized to predict femoral neck or lumbar spine BMD. C-reactive protein positively correlated with femoral (τ = 0.09, p2 = 0.022, p = 0.0001) and spine BMD (R2 = 0.028, p2 = 0.015, p2 = 0.24, p2 = 0.21, p</div

Correlation between Frx history and C-reactive protein or BMD.

Correlation of Frx history with A) C-reactive protein, B) femoral neck BMD, and C) spine BMD. Correlations assessed using non-parametric Kendall’s rank correlation test.</p

Respondent demographics.

A reliable, widely available method to detect osteoporosis prior to fracture is needed. Serum levels of C-reactive protein may independently predict low bone mineral density (BMD) and high fracture risk. Existing empirical data focus on sexually and/or racially homogenous populations. This study tests the hypotheses that: C-reactive protein (1) negatively correlates with BMD and (2) fracture history, and (3) independently predicts BMD and fracture history in a diverse population. NHANES 2017–2020 pre-pandemic cycle data were analyzed in R studio. Strength and direction of relationships (-1 to +1) between variables were determined using Kendall’s rank correlation coefficient (τ). Linear models were optimized to predict femoral neck or lumbar spine BMD. C-reactive protein positively correlated with femoral (τ = 0.09, p2 = 0.022, p = 0.0001) and spine BMD (R2 = 0.028, p2 = 0.015, p2 = 0.24, p2 = 0.21, p</div

Variation in BMD and C-reactive protein by sex and race.

Femoral neck BMD (g/cm2) by A) sex and B) race. Spine BMD (g/cm2) by C) sex and D) race. C-reactive protein (mg/L) by E) sex and F) race. Boxplots denote the 1st, 2nd (median), and 3rd quartiles, with all data points plotted. For statistical comparison by sex, non-parametric, unpaired, two-tailed t-tests were used. For comparison by race, non-parametric one-way ANOVA was used, followed by Wilcoxon signed rank test with adjustment for false discovery rate.</p

Correlation between C-reactive protein and spine BMD by race.

Correlation between C-reactive protein and spine BMD among individuals identifying as A) Hispanic, B) non-Hispanic (NH) white, C) NH black, D) NH Asian, or E) multiracial (multi). Plotted line indicates trendline, with slope of Kendall’s tau. Correlations assessed using non-parametric Kendall’s rank correlation test.</p

Modeling to predict BMD and history of Frx from C0.

Modeling to predict BMD and history of Frx from C0.</p

Femoral neck and spine BMD, but not C-reactive protein, differ by sex.

Distribution of A) femoral neck BMD (g/cm2), B) spine BMD (g/cm2), and C) C-reactive protein (mg/L) in the sample population. Individuals identifying as male are coded in blue, as female in red, and the overlap in purple. Bin size was optimized for each variable using the Freedman-Diaconis method.</p