Rock, C. | Search bioRxiv

bioRxiv2020

Glycation and Serum Albumin Infiltration Contribute to the Structural Degeneration of Bioprosthetic Heart Valves

BackgroundBioprosthetic heart valves (BHV) are widely used to treat heart valve disease but are fundamentally limited by structural valve degeneration (SVD). Non-calcific mechanisms of SVD entirely account for approximately 30% of SVD cases and contribute to calcific SVD but remain understudied. Glycation mechanisms have not been previously associated with SVD, despite being established as degenerative in collagenous native tissues. ObjectivesTo determine whether blood component infiltration-based glycation and concomitant human serum albumin (HSA) deposition contribute mechanistically to SVD. MethodsImmunohistochemistry (IHC) was used to identify advanced glycation end-products (AGEs) and serum albumin accumulation in 45 aortic valve BHV explanted due to SVD, glutaraldehyde-treated bovine pericardium (BP) incubated in vitro in glyoxal and HSA, and rat subcutaneous BP implants. Structural impacts of glycation-related mechanisms were evaluated by second harmonic generation (SHG) collagen imaging. Hydrodynamic effects of valve glycation and concomitant HSA exposure were studied with an ISO-5840-compliant pulse duplicator system using surgical grade BHV. ResultsAll 45 clinical explants and in vitro-incubated BP demonstrated accumulated AGE and HSA compared to un-implanted, un-exposed BHV. SHG revealed instigation of collagen malalignment similar to that in SVD explants by glycation and HSA infiltration. Rat subdermal explants also showed AGE and serum albumin accumulation. Pulse duplication demonstrated significantly reduced orifice area and increased pressure gradient and peak fluid velocity following glyoxal and HSA incubations. ConclusionsGlycation and concomitant HSA infiltration occur in clinical BHV and contribute to structural and functional degeneration of leaflet tissue, thus representing novel, interacting mechanisms of BHV SVD.

bioengineering↗

bioRxiv2020

Complex interactions between weather, and microbial and physiochemical water quality impact the likelihood of detecting foodborne pathogens in agricultural water

Agricultural water is an important source of foodborne pathogens on produce farms. Managing water-associated risks does not lend itself to one-size-fits-all approaches due to the heterogeneous nature of freshwater environments, and because environmental conditions affect the likelihood of pathogen contamination and the relationship between indicator organism levels (e.g., E. coli) and pathogen presence. To improve our ability to develop location-specific risk management practices, a study was conducted in two produce-growing regions to (i) characterize the relationship between E. coli levels and pathogen presence in agricultural water, and (ii) identify environmental factors associated with pathogen detection. Three AZ and six NY waterways were sampled longitudinally using 10-L grab samples (GS) and 24-h Moore swabs (MS). Regression showed that the likelihood of Salmonella detection (Odds Ratio [OR]=2.18), and eaeA-stx codetection (OR=6.49) was significantly greater for MS compared to GS, while the likelihood of detecting L. monocytogenes was not. Regression also showed that eaeA-stx codetection in AZ (OR=50.2) and NY (OR=18.4), and Salmonella detection in AZ (OR=4.4) were significantly associated with E. coli levels, while Salmonella detection in NY was not. Random forest analysis indicated that interactions between environmental factors (e.g., rainfall, temperature, turbidity) (i) were associated with likelihood of pathogen detection and (ii) mediated the relationship between E. coli levels and likelihood of pathogen detection. Our findings suggest that (i) environmental heterogeneity, including interactions between factors, affects microbial water quality, and (ii) E. coli levels alone may not be a suitable indicator of the food safety risks. Instead, targeted methods that utilize environmental and microbial data (e.g., models that use turbidity and E. coli levels to predict when there is a high or low risk of surface water being contaminated by pathogens) are needed to assess and mitigate the food safety risks associated with preharvest water use. By identifying environmental factors associated with an increased likelihood of detecting pathogens in agricultural water, this study provides information that (i) can be used to assess when pathogen contamination of agricultural water is likely to occur, and (ii) facilitate development of targeted interventions for individual water sources, providing an alternative to existing one-size-fits-all approaches.

microbiology↗