Predicting recreational water quality and public health safety in urban estuaries using Bayesian Networks.

To support the reactivation of urban rivers and estuaries for bathing while ensuring public safety, it is critical to have access to real-time information on microbial water quality and associated health risks. Predictive modelling can provide this information, though challenges concerning the optimal size of training data, model transferability, and communication of uncertainty still need attention. Further, urban estuaries undergo distinctive hydrological variations requiring tailored modelling approaches. This study assessed the use of Bayesian Networks (BNs) for the prediction of enterococci exceedances and extrapolation of health risks at planned bathing sites in an urban estuary in Sydney, Australia. The transferability of network structures between sites was assessed. Models were validated using a novel application of the k-fold walk-forward validation procedure and further tested using independent compliance and event-based sampling datasets. Learning curves indicated the model's sensitivity reached a minimum performance threshold of 0.8 once training data included ≥ 400 observations. It was demonstrated that Semi-Naïve BN structures can be transferred while maintaining stable predictive performance. In all sites, salinity and solar exposure had the greatest influence on Posterior Probability Distributions (PPDs), when combined with antecedent rainfall. The BNs provided a novel and transparent framework to quantify and visualise enterococci, stormwater impact, health risks, and associated uncertainty under varying environmental conditions. This study has advanced the application of BNs in predicting recreational water quality and providing decision support in urban estuarine settings, proposed for bathing, where uncertainty is high.

Brain uptake of diazepam and phenytoin in a genetic animal model of absence epilepsy.

1. Although many studies have assessed changes to brain uptake of anti-epileptic drugs (AEDs) in chemically and electrically induced seizure models, there are limited data available on changes to brain uptake of AEDs in spontaneous seizure animal models, such as genetic absence epilepsy. 2. In the present study, the brain uptake of diazepam and phenytoin was assessed in a genetic mouse model of absence seizures harbouring a human GABA(A) receptor gamma2-subunit gene GABRG2 mutation (R43Q) and results were compared with those obtained during acute seizures induced by subcutaneous administration of pentylenetetrazole (PTZ; 90 mg/kg). Diazepam and phenytoin were administered intraperitoneally at doses of 2 and 30 mg/kg, respectively, and brain and plasma concentrations were determined 60 min after administration using liquid chromatography-mass spectrometry. 3. Although the brain uptake of phenytoin was significantly reduced following PTZ administration, no changes were observed in phenytoin disposition in the genetic absence epilepsy model. Similarly, the brain uptake of diazepam was significantly enhanced following PTZ administration, but it was not affected in absence epilepsy. 4. The cerebrovascular plasma volume (assessed by administration of the non-absorbable marker [(14)C]-inulin) was not significantly different in saline-treated compared with PTZ-treated mice and in wild-type compared with mutant R43Q mice. 5. These results demonstrate that although the brain uptake of AEDs may be altered in acute seizure models, similar changes to brain uptake may not be observed in the non-convulsive genetic absence epileptic model.