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.

AB1531-HPR ECOLOGICAL MOMENTARY ASSESSMENT OF THE SYMPTOMS IN SJÖGREN’S SYNDROME: DEVELOPMENT AND VALIDATION OF A DEDICATED WebApp

Background

Primary Sjögren’s syndrome (pSS) is a rare systemic autoimmune disease with no specific treatment at present. To better assess patient symptoms, we have developed a web application (WebApp) to collect patient symptom intensity on a regular basis.

Objectives

To measure the daily variability of symptoms using the WebApp. We also evaluated its ease of use.

Methods

45 consecutive patients with pSS were included in 3 referral centers. Symptoms were assessed during the baseline and 3 month visits. We collected the VAS relating to fatigue, dryness and pain as well as the ESSPRI score. Patients used the WebApp daily for 3 months. The variability of symptoms over time was assessed by the predicted median error. This value was determined using a linear regression model, in order to predict the value at the 3rd month, then this value was compared to the actual value collected at the 3rd month during the clinical visit. The ease of use of the WebApp was assessed using a satisfaction score (SUS score).

Results

Of the 45 patients included, 91.1% were women with an average age of 57 years, and low systemic disease activity (84.4% had an ESSDAI score below 5). The intensity of the symptoms collected during the clinical visits was similar at baseline and at 3 months. The values ​​of the median error for each measurement are between 0.5 and 0.8. The 3-month predicted median error values ​​ranged from 2 to -3. The patients all used the web application for 3 months with good attendance (80% of data completion) and were satisfied with this tool (median SUS score = 90).

Conclusion

Symptoms of pSS fluctuate from day to day in the majority of patients, making a point measurement imprecise. The developed WebApp is easy to use, and could allow more sensitive detection of the effect of a therapeutic intervention. This tool will soon be evaluated during prospective interventional clinical trials.

Acknowledgements

I would like to thanks all people who have helped and were directly or indirectly involved in this study.

Disclosure of Interests

None declared

Quantitative microbial risk assessment of a non-membrane based indirect potable water reuse system using Bayesian networks

Risk-based approaches are used to define performance standards for water and wastewater treatment to meet health-based targets and to ensure safe and reliable water quality for desired end use. In this study, a screening level QMRA for a non-membrane based indirect potable reuse (IPR) system utilizing the sequential managed aquifer recharge technology (SMART) concept was conducted. Ambient removals of norovirus, Campylobacter and Cryptosporidium in advanced water treatment (AWT) steps were combined in a probabilistic QMRA utilizing Bayesian networks constructed in Netica. Results revealed that all pathogens complied with disease burden at the 95th percentile, and according to the assumptions taken about pathogen removal, Cryptosporidium was the pathogen with the greatest risk. Through systematic sensitivity analysis, targeted scenario analysis, and backwards inferencing, critical control points for each pathogen were determined, demonstrating the usefulness of Bayesian networks as a diagnostic tool in quantifying risk of water reuse treatment scenarios.

Functional redundancy and compensation: Deletion of multiple murine Crisp genes reveals their essential role for male fertility

Mammalian Cysteine-RIch Secretory Protein (CRISP) family includes four members present in sperm and reported to regulate Ca²⁺ channels and fertilization. Based on our previous observations using single knockouts models and suggesting the existence of functional compensation among CRISP proteins, we investigated their relevance for male fertility by generating multiple Crisp gene mutants by CRISPR/Cas9 technology. Whereas targeting of Crisp1 and Crisp3 yielded subfertile males with early embryo developmental defects, the same deletion in zygotes from fertile Crisp2^-/- .Crisp4^-/- mice led to the generation of both triple and quadruple knockout mice exhibiting a complete or severe disruption of male fertility due to a combination of sperm transport, fertilization, and embryo developmental defects linked to intracellular Ca²⁺ dysregulation. These observations reveal that CRISP proteins are essential for male fertility and organize in functional modules that contribute distinctly to fertility success, bringing insights into the mechanisms underlying functional redundancy/compensation in protein families and emphasizing the importance of generating multiple and not just single knockout which might be masking the true functional relevance of family genes.

Robust evaluation of performance monitoring options for ozone disinfection in water recycling using Bayesian analysis

Ozonation of wastewater has gained popularity because of its effectiveness in removing colour, UV absorbance, trace organic chemicals, and pathogens. Due to the rapid reaction of ozone with organic compounds, dissolved ozone is often not measurable and therefore, the common disinfection controlling parameter, concentration integrated over contact time (CT) cannot be obtained. In such cases, alternative parameters have been shown to be useful as surrogate measures for microbial removal including change in UV₂₅₄ absorbance (ΔUVA), change in total fluorescence (ΔTF), or O₃:TOC (or O₃:DOC). Although these measures have shown promise, a number of caveats remain. These include uncertainties in the associations between these measurements and microbial inactivation. Furthermore, previous use of seeded microorganisms with higher disinfection sensitivity compared to autochthonous microorganisms could lead to overestimation of appropriate log credits. In our study, secondary treated wastewater from a full-scale plant was ozonated in a bench-scale reactor using five increasing ozone doses. During the experiments, removal of four indigenous microbial indicators representing viruses, bacteria and protozoa were monitored concurrent with ΔUVA, ΔTF, O₃:DOC and PARAFAC derived components. Bayesian methods were used to fit linear regression models, and the uncertainty in the posterior predictive distributions and slopes provided a comparison between previously reported results and those reported here. Combined results indicated that all surrogate parameters were useful in predicting the removal of microorganisms, with a better fit to the models using ΔUVA, ΔTF in most cases. Average adjusted determination coefficients for fitted models were high (R²_adjusted>0.47). With ΔUVA, one unit decrease in LRV corresponded with a UVA mean reduction of 15-20% for coliforms, 59% for C. perfringens spores, and 11% for somatic coliphages. With ΔTF, a one unit decrease in LRV corresponded with a TF mean reduction of 18-23% for coliforms, 71% for C. perfringens spores, and 14% for somatic coliphages. Compared to previous studies also analysed, our results suggest that microbial reductions were more conservative for autochthonous than for seeded microorganisms. The findings of our study suggested that site-specific analyses should be conducted to generate models with lower uncertainty and that indigenous microorganisms are useful for the measurement of system performance even when censored observations are obtained.

Virus removal by ultrafiltration: Understanding long-term performance change by application of Bayesian analysis

Ultrafiltration is an effective barrier to waterborne pathogens including viruses. Challenge testing is commonly used to test the inherent reliability of such systems. Performance validation seeks to demonstrate the adequate reliability of the treatment system. Appropriate and rigorous data analysis is an essential aspect of validation testing. In this study we used Bayesian analysis to assess the performance of a full-scale ultrafiltration system which was validated and revalidated after five years of operation. A hierarchical Bayesian model was used to analyse a number of similar ultrafiltration membrane skids working in parallel during the two validation periods. This approach enhanced our ability to obtain accurate estimations of performance variability, especially when the sample size of some system skids was limited. This methodology enabled the quantitative estimation of uncertainty in the performance parameters and generation of predictive distributions incorporating those uncertainties. The results indicated that there was a decrease in the mean skid performance after five years of operation of approximately 1 log reduction value (LRV). Interestingly, variability in the LRV also reduced, with standard deviations from the revalidation data being decreased by a mean 0.37 LRV compared with the original validation data. The model was also useful in comparing the operating performance of the various parallel skids within the same year. Evidence of differences was obtained in 2015 for one of the membrane skids. A hierarchical Bayesian analysis of validation data provides robust estimations of performance and the incorporation of probabilistic analysis which is increasingly important for comprehensive quantitative risk assessment purposes.

Bayesian belief network modelling of chlorine disinfection for human pathogenic viruses in municipal wastewater

Chlorine disinfection of biologically treated wastewater is practiced in many locations prior to environmental discharge or beneficial reuse. The effectiveness of chlorine disinfection processes may be influenced by several factors, such as pH, temperature, ionic strength, organic carbon concentration, and suspended solids. We investigated the use of Bayesian multilayer perceptron (BMLP) models as efficient and practical tools for compiling and analysing free chlorine and monochloramine virus disinfection performance as a multivariate problem. Corresponding to their relative susceptibility, Adenovirus 2 was used to assess disinfection by monochloramine and Coxsackievirus B5 was used for free chlorine. A BMLP model was constructed to relate key disinfection conditions (CT, pH, turbidity) to observed Log Reduction Values (LRVs) for these viruses at constant temperature. The models proved to be valuable for incorporating uncertainty in the chlor(am)ination performance estimation and interpolating between operating conditions. Various types of queries could be performed with this model including the identification of target CT for a particular combination of LRV, pH and turbidity. Similarly, it was possible to derive achievable LRVs for combinations of CT, pH and turbidity. These queries yielded probability density functions for the target variable reflecting the uncertainty in the model parameters and variability of the input variables. The disinfection efficacy was greatly impacted by pH and to a lesser extent by turbidity for both types of disinfections. Non-linear relationships were observed between pH and target CT, and turbidity and target CT, with compound effects on target CT also evidenced. This work demonstrated that the use of BMLP models had considerable ability to improve the resolution and understanding of the multivariate relationships between operational parameters and disinfection outcomes for wastewater treatment.

Modelling pathogen log10 reduction values achieved by activated sludge treatment using naïve and semi naïve Bayes network models

Risk management for wastewater treatment and reuse have led to growing interest in understanding and optimising pathogen reduction during biological treatment processes. However, modelling pathogen reduction is often limited by poor characterization of the relationships between variables and incomplete knowledge of removal mechanisms. The aim of this paper was to assess the applicability of Bayesian belief network models to represent associations between pathogen reduction, and operating conditions and monitoring parameters and predict AS performance. Naïve Bayes and semi-naïve Bayes networks were constructed from an activated sludge dataset including operating and monitoring parameters, and removal efficiencies for two pathogens (native Giardia lamblia and seeded Cryptosporidium parvum) and five native microbial indicators (F-RNA bacteriophage, Clostridium perfringens, Escherichia coli, coliforms and enterococci). First we defined the Bayesian network structures for the two pathogen log10 reduction values (LRVs) class nodes discretized into two states (< and ≥ 1 LRV) using two different learning algorithms. Eight metrics, such as Prediction Accuracy (PA) and Area Under the receiver operating Curve (AUC), provided a comparison of model prediction performance, certainty and goodness of fit. This comparison was used to select the optimum models. The optimum Tree Augmented naïve models predicted removal efficiency with high AUC when all system parameters were used simultaneously (AUCs for C. parvum and G. lamblia LRVs of 0.95 and 0.87 respectively). However, metrics for individual system parameters showed only the C. parvum model was reliable. By contrast individual parameters for G. lamblia LRV prediction typically obtained low AUC scores (AUC < 0.81). Useful predictors for C. parvum LRV included solids retention time, turbidity and total coliform LRV. The methodology developed appears applicable for predicting pathogen removal efficiency in water treatment systems generally.

Gremlin: a novel mediator of epithelial mesenchymal transition and fibrosis in chronic allograft nephropathy

BACKGROUND

Chronic allograft nephropathy (CAN) is the most frequent cause of chronic dysfunction and late loss of renal allografts. Epithelial mesenchymal transition (EMT) has been identified as responsible for the presence of activated interstitial fibroblasts (myofibroblasts) and transforming growth factor beta (TGF-beta)/Smad is the key signaling mediator. It has been proposed that the bone morphogenetic protein 7 (BMP-7) antagonist, Gremlin, could participate in EMT, as a downstream mediator of TGF-beta.

METHODS

We evaluated 33 renal allograft biopsies, 16 of which showed CAN, versus 17 controls. By in situ hybridization we studied the expression of TGF-beta and Gremlin mRNA. Gremlin, BMP-7, E-cadherin, and alpha-smooth muscle actin (alpha-SMA) proteins were evaluated by immunohistochemistry and Smad3 activation by Southwestern. In cultured human tubuloepithelial cells (HK2 cell line), Gremlin induction by TGF-beta was studied by confocal microscopy.

RESULTS

Among renal biopsies of transplanted patients with CAN, we detected up-regulation of TGF-beta in colocalization with Gremlin (RNA and protein), mainly in areas of tubulointerstitial fibrosis. In the same tubules, we observed decreased expression of E-cadherin and induction of vimentin and alpha-SMA. BMP-7 was significantly decreased in the CAN biopsies. In addition, HK2 stimulated with TGF-beta (1 ng/mL) induced Gremlin production at 72 hours.

CONCLUSION

We postulated that Gremlin is a downstream mediator of TGF-beta, suggesting a role for Gremlin in EMT observed in CAN.

Factors influencing boar sperm cryosurvival1

Optimal sperm cryopreservation is a prerequisite for the sustainable commercial application of frozen-thawed boar semen for AI. Three experiments were performed to identify factors influencing variability of postthaw sperm survival among 464 boar ejaculates. Sperm-rich ejaculate fractions were cryopre-served using a standard freezing-thawing procedure for 0.5-mL plastic straws and computer-controlled freezing equipment. Postthaw sperm motility (assessed with a computer-assisted semen analysis system) and viability (simultaneously probed by flow cytometry analysis after triple-fluorescent stain), evaluated 30 and 150 min postthaw, were used to estimate the success of cryopreservation. In the first experiment, 168 unselected ejaculates (1 ejaculate/boar), from boars of 6 breeds with a wide age range (8 to 48 mo), were cryopreserved over a 12-mo period to evaluate the predictive value of boar (breed and age), semen collection, transport variables (season of ejaculate collection, interval between collections, and ejaculate temperature exposure), initial semen traits, and sperm quality before freezing on sperm survival after freezing-thawing. In Exp. 2, 4 ejaculates from each of 29 boars, preselected according to their initial semen traits and sperm quality before freezing, were collected and frozen over a 6-mo period to evaluate the influence of interboar and intraboar ejaculate variability in the survival of sperm after cryopreservation. In Exp. 3, 12 ejaculates preselected as for Exp. 2, from each of 15 boars with known good sperm cryosurvival, were collected and frozen over a 12-mo period to estimate the sustainability of sperm cryosurvival between ejaculates over time. Boar and semen collection and transport variables were not predictive of sperm cryosurvival among ejaculates. Initial semen traits and sperm quality variables observed before freezing explained 23.2 and 10.9%, respectively, of the variation in postthaw sperm motility and viability. However, more that 70% of total variance observed in postthaw sperm quality variables among ejaculates was explained by boar. This indicates that boar is the most important (P < 0.001) factor explaining the variability among ejaculates in sperm cryosurvival, with most (14 of the 15 boars in Exp. 3) showing consistent (P > 0.05) sperm cryosurvival over time.

11 TIME OF INSEMINATION RELATIVE TO OVULATION EXPLAINS FERTILITY VARIATIONS OFFROZEN - THAWED SPERMATOZOA BETWEEN FARMS

Swine fertility after AI with frozen-thawed spermatozoa varies between trials. As thawed spermatozoa have an extremely limited life span in the female genital tract, fertility of frozen-thawed spermatozoa depends mainly on the time of insemination relative to ovulation. The objective of this study was to evaluate whether the time of insemination relative to ovulation could explain the farm differences in fertility when frozen-thawed spermatozoa are used. Pooled sperm-rich fractions collected from three mature Pietrain boars were diluted in lactose/egg-yolk/glicerol/Orvus-ES-Paste extender, loaded in 0.5-mL straws (1 × 109 cells/mL), and frozen under controlled conditions (Carvajal et al. 2003 J. Androl. 25, 389–396). Thawing was conducted in a waterbath at 37°C for 20 s. Inseminations were performed using the deep intrauterine insemination technique (Martínez et al. 2002 Reproduction 123, 167–170) with 1 × 109 thawed spermatozoa (post-thaw motility >50%) diluted in 5 mL of Beltsville thaw solution (BTS). Ninety-seven and 82 weaned sows (parity 2–7) in farms A and B, respectively, were twice inseminated at 30 and 36 h after onset of estrus (estrus detection was performed twice a day by allowing females nose-to-nose contact with a mature boar and by applying back pressure). At insemination time, both ovaries were checked for ovulation by transrectal ultrasonography and sows were classified into three groups: F sows (follicles visible during the two examinations), O sows (ovulation visible during at least one examination), and C sows (corpora lutea visible during both examinations). Data were analysed with ANOVA and chi-square test, and are reported as % or mean ± SEM. Overall farrowing rates differed (P < 0.01) between farms: 70.1% (68/97) and 51.22% (42/82) in farms A and B, respectively. Litter size did not differ (P > 0.05) between farms (9.18 ± 0.24 and 9 ± 0.39 in farms A and B, respectively). Distribution of sows among F, O, and C groups differed (P < 0.05) between farms. Seventeen (17.52%), 70 (72.16%), and 10 (10.31%) sows in farm A and 33 (40.24%), 24 (29.27%), and 25 (30.49%) sows in farm B were classified as F, O, and C, respectively. Fertility in F, O, or C sows did not differ (P > 0.05) between farms. Farrowing rates and litter size in O sows (82.98% and 9.45 ± 0.23) were higher (P < 0.05) than in F (48% and 8.67 ± 0.54) and C (48.57% and 7.55 ± 0.62) sows. We can conclude that time of insemination relative to ovulation explains fertility differences between farms when frozen-thawed spermatozoa are used. This work was supported by INIA (RZ01-019) and INFO (CARM).

92THE ADDITION OF SEMINAL PLASMA FROM INDIVIDUAL BOARS TO FREEZING EXTENDER CAN IMPROVE THE POST-THAW SPERM SURVIVAL

Contradictory results have been reported about the effect of seminal plasma (SP) on the freezability of mammalian spermatozoa. In pigs, current methods for sperm cryopreservation involve removing seminal plasma. Therefore, no conclusive evidence of the potential effect of SP on the freezability of boar spermatozoa has been reported. In this study, we evaluate the effect of the addition of low concentrations of SP from individual boars to the freezing extender on post-thaw sperm survival. Sperm cryopreservation procedure included: dilution of sperm-rich fraction in Beltsville Thaw Solution extender (BTS), cooling to 17°C for 16h, centrifugation at 2400g for 3min, dilution in lactose/egg-yolk/glycerol/Equex Stem (freezing extender) to a final concentration of 1×109 spermmL−1, dispensing into 0.5-mL straws, and freezing in a programmable cell freezer at 20°Cmin−1. Thawing was carried out in a waterbath at 37°C for 20s. Post-thaw sperm survival was assessed by progressive sperm motility (PSM) using a CASA system (SCA); plasma membrane integrity (PMI) and acrosome membrane integrity (AMI) were assessed by flow cytometric procedures (SYBR-14/PI and FITC-PNA/PI, respectively) at 30 and 150min post-thawing in BTS-diluted thaw spermatozoa held in a waterbath at 37°C. Four individual seminal plasma donors (SP1 to SP4) were selected in a preliminary study in which 48 ejaculates from 12 boars (4 ejaculates/boar) were cryopreserved. Then the boars were classified into 3 groups (good, moderate and bad freezers) based on their post-thaw sperm survival. SP1 and SP2 were good freezers (&gt;60% PSM and PMI), SP3 was a moderate freezer (40–60% PSM and PMI) and SP4 was a bad freezer (&lt;40% PSM and PMI). In the main experiment, pooled sperm-rich fractions collected from 9 mature hybrid boars were divided into five aliquots and each was diluted with freezing extender supplemented with 0% (control) or 10% of SP (1–4). Data from eight replicates were analyzed as a split plot design using a PROMIXED model. The addition of SP to freezing extender had a significant effect (P&lt;0.05) on post-thaw sperm survival compared to control. Moreover, there were significant differences (P&lt;0.05) between SP donors. PSM, PMI and AMI were significantly (P&lt;0.05) higher in SP1 (56.71±4.30; 57.16±4.01 and 57.22±4.01, respectively) and SP2 (59.48±4.30; 60.17±4.01 and 60.05±4.01, respectively) compared to control (50.39±4.30; 49.98±4.01 and 49.54±4.01, respectively). There were no differences (P&gt;0.05) between SP3, SP4 and control. These results indicate that the addition of SP from particular boars (good freezers) to freezing extender may improve post-thaw sperm survival. Individual differences in the SP composition should explain the above results. Supported by INIA (RZ01-019) and MCYT (AGL2001-0471).

Groundwater contamination by azinphos methyl in the northern Patagonic Region (Argentina)

Approximately 30 groundwater monitoring wells, under a fruit production field, in the Valley of the Neuquen River (Northern Patagonic, Argentina), to which different pesticides have been applied, were sampled eleven times between October 1995 and March 1997. Azinphos methyl was the main pesticide applied and it was detected with the highest frequency in groundwater wells during the period of intensive pesticide application in the Southern Hemisphere. Dimethoate, methidathion, fosmet, cipermethrin, carbaryl, propoxur, carbofuran, benomyl and carbendazim were also detected with lower frequency. The characteristic of the area under study was alkaline soil, with an organic matter content below 2.5% and texture sandy clay loam. The half life of azinphos methyl in soils was 166.2 days in the sun light for horizon A and 194.15 in the dark for horizon B. Leaching of azinphos methyl through the different soil horizons was minimum. On the basis of our lysimeter laboratory data, in which most of the pesticide was adsorbed into the soil column and only small quantities leachate, we inferred that the impact of azinphos methyl on groundwater would be minimal. However, field data indicates that there is a persistence of azinphos methyl in groundwater during the application season.