Relevance of tributary inflows for driving molecular composition of dissolved organic matter (DOM) in a regulated river system.

River regulation by dams can alter flow regimes and organic matter dynamics, but less is known about how unregulated tributaries regulate organic matter composition and processing in the regulated river below the confluence. This study reports on water chemistry, especially dissolved organic matter (DOM) concentration and composition (dissolved organic carbon (DOC), organic nitrogen (DON), organic phosphorus (DOP) and combined amino acids (DCAA)) along the regulated Tumut and unregulated Goobarragandra (tributary) rivers under different flow conditions (base flow vs storm event) in south-east Australia. The tributary was significantly different from regulated and downstream sites during base flow conditions with higher temperature, pH, buffering capacity, DOC and nutrient concentrations (DON, DOP, DCAA). DOM characterisation by spectrometry and size exclusion chromatography revealed that the tributary contained a higher proportion of terrestrially derived humic-like and fulvic-like DOM. In contrast, regulated and downstream sites contained higher proportion of microbially derived DOM such as low molecular weight neutrals and protein-like components. Storm pulses of tributary flows into the regulated system, influenced both concentration and composition of DOM at the downstream site, which more strongly resembled the tributary site than the regulated site during the storm event. Additionally, we found that the tributary supplied fresh DOM, including small organic molecules to the regulated system during storm events. The presence of these different types of labile DOM can increase primary productivity and ecological functioning within regulated river reaches downstream of tributary junctions. This has important implications for the protection of unregulated tributary inflows within regulated river basins.

Learning from the Outside In: Incorporating Wilderness Medicine into Traditional Emergency Medicine Education.

[Full article available at http://rimed.org/rimedicaljournal-2019-02.asp].

Application of a Plug-and-Play Immunogenicity Assay in Cynomolgus Monkey Serum for ADCs at Early Stages of Drug Development.

Immunogenicity assessment during early stages of nonclinical biotherapeutic development is not always warranted. It is rarely predictive for clinical studies and evidence for the presence of anti-drug antibodies (ADAs) may be inferred from the pharmacokinetic (PK) profile. However, collecting and banking samples during the course of the study are prudent for confirmation and a deeper understanding of the impact on PK and safety. Biotherapeutic-specific ADA assays commonly developed can require considerable time and resources. In addition, the ADA assay may not be ready when needed if the study of PK and safety data triggers assay development. During early stages of drug development for antibody-drug conjugates (ADCs), there is the added complication of the potential inclusion of several molecular variants in a study, differing in the linker and/or drug components. To simplify analysis of ADAs at this stage, we developed plug-and-play generic approaches for both the assay format and the data analysis steps. Firstly, the assay format uses generic reagents to detect ADAs. Secondly, we propose a cut point methodology based on animal specific baseline variability instead of a population data approach. This assay showed good sensitivity, drug tolerance, and reproducibility across a variety of antibody-derived biotherapeutics without the need for optimization across molecules.

Utilizing design of experiments to characterize assay robustness.

BACKGROUND: Design of experiments (DOE) is a systematic approach to assess the effects of many factors on a response of an assay. This paper provides a case study whereby DOE was successfully utilized to evaluate robustness parameters for a ligand-binding assay (LBA). METHODOLOGY: A 24-run Plackett-Burman design was developed to investigate factors that may have caused a lack of robustness in this particular LBA. We modeled five main effects and their ten two-way interactions, using the standard curve signal as the response. RESULTS: By utilizing DOE, we were able to quickly identify the factors that affected our assay's performance. The lack of robustness was attributed to the handling of the coat reagent. Factors that had an adverse effect on the coat material were vortexing and freeze-thaw cycles. CONCLUSION: We recommend that a robustness DOE be conducted prior to the validation of an assay for early identification of critical factors that may impact assay performance.