In a previous study, the lung function, as indicated by the tidal volume, minute volume, and peak inspiration flow, decreased during 90 days of exposure to silver nanoparticles and was accompanied by inflammatory lesions in the lung morphology. Therefore, this study investigated the recovery from such lung function changes in rats following the cessation of 12 weeks of nanoparticle exposure. Male and female rats were exposed to silver nanoparticles (14-15 nm diameter) at concentrations of 0.66 × 10(6) particles/cm(3) (49 μg/m(3), low dose), 1.41 × 10(6) particles/cm(3) (117 μg/m(3), middle dose), and 3.24 × 10(6) particles/cm(3) (381 μg/m(3), high dose) for 6 h/day in an inhalation chamber for 12 weeks. The rats were then allowed to recover. The lung function was measured every week during the exposure period and after the cessation of exposure, plus animals were sacrificed after the 12-week exposure period, and 4 weeks and 12 weeks after the exposure cessation. An exposure-related lung function decrease was measured in the male rats after the 12-week exposure period and 12 weeks after the exposure cessation. In contrast, the female rats did not show a consistent lung function decrease either during the exposure period or following the exposure cessation. The histopathology showed a gradual recovery from the lung inflammation in the female rats, whereas the male rats in the high-dose group exhibited persistent inflammation throughout the 12-week recovery period. Therefore, the present results suggest a potential persistence of lung function changes and inflammation induced by silver nanoparticle exposure above the no observed adverse effect level.

Silver nanoparticles are known to be distributed in many tissues after oral or inhalation exposure. Thus, understanding the tissue clearance of such distributed nanoparticles is very important to understand the behavior of silver nanoparticles in vivo. For risk assessment purposes, easy clearance indicates a lower overall cumulative toxicity. Accordingly, to investigate the clearance of tissue silver concentrations following oral silver nanoparticle exposure, Sprague–Dawley rats were assigned to 3 groups: control, low dose (100 mg/kg body weight), and high dose (500 mg/kg body weight), and exposed to two different sizes of silver nanoparticles (average diameter 10 and 25 nm) over 28 days. Thereafter, the rats were allowed to recover for 4 months. Regardless of the silver nanoparticle size, the silver content in most tissues gradually decreased during the 4-month recovery period, indicating tissue clearance of the accumulated silver. The exceptions were the silver concentrations in the brain and testes, which did not clear well, even after the 4-month recovery period, indicating an obstruction in transporting the accumulated silver out of these tissues. Therefore, the results showed that the size of the silver nanoparticles did not affect their tissue distribution. Furthermore, biological barriers, such as the blood–brain barrier and blood-testis barrier, seemed to play an important role in the silver clearance from these tissues.

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e Bacterial resistance is among the most serious threats to human health globally, and many bacterial isolates have emerged that are resistant to all antibiotics in monotherapy. Aminoglycosides are often used in combination therapies against severe infections by multidrug-resistant bacteria. However, models quantifying different antibacterial effects of aminoglycosides are lacking. While the mode of aminoglycoside action on protein synthesis has often been studied, their disruptive action on the outer membrane of Gram-negative bacteria remains poorly characterized. Here, we developed a novel quantitative model for these two mechanisms of aminoglycoside action, phenotypic tolerance at high bacterial densities, and adaptive bacterial resistance in response to an aminoglycoside (tobramycin) against three Pseudomonas aeruginosa strains. At low-intermediate tobramycin concentrations (<4 mg/liter), bacterial killing due to the effect on protein synthesis was most important, whereas disruption of the outer membrane was the predominant killing mechanism at higher tobramycin concentrations (>8 mg/liter). The extent of killing was comparable across all inocula; however, the rate of bacterial killing and growth was substantially lower at the 10 8.9 CFU/ml inoculum than that at the lower inocula. At 1 to 4 mg/liter tobramycin for strain PAO1-RH, there was a 0.5-to 6-h lag time of killing that was modeled via the time to synthesize hypothetical lethal protein(s). Disruption of the outer bacterial membrane by tobramycin may be critical to enhance the target site penetration of antibiotics used in synergistic combinations with aminoglycosides and thereby combat multidrug-resistant bacteria. The two mechanisms of aminoglycoside action and the new quantitative model hold great promise to rationally design novel, synergistic aminoglycoside combination dosage regimens.T he rapid rise of multidrug-resistant (MDR) bacteria and a severe shortage of effective antibiotics are causing a global health crisis (1, 2). This situation is particularly daunting given the lack of new antibiotics in the pipeline for infections associated with Gram-negative bacteria that are resistant to all available monotherapies (3). The lack of effective monotherapies has forced physicians to use empirical antibiotic combinations for which a strong foundation on the mechanism(s) of synergy is not available (4, 5).Aminoglycosides have been used since the 1970s, but their different mechanisms of action against Gram-negatives are not well understood at a quantitative level. While it is well known that aminoglycosides affect protein synthesis (6), their disruption of the outer membrane of Gram-negative bacteria has not been studied as often (7-10). Kadurugamuwa et al. (11,12) covalently conjugated aminoglycosides to albumin and showed that these conjugated aminoglycosides can cause rapid and extensive killing of Pseudomonas aeruginosa (Ͼ3 log 10 ) without entering the bacterial cells and thus without inhibiting protein synthesis. The outer membrane of Gram-negati...

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Abstract. Mechanistic modeling greatly benefits from automated pre-and post-processing of model code and modeling results. While S-ADAPT provides many state-of-the-art parametric population estimation methods, its pre-and post-processing capabilities are limited. Our objective was to develop a fully automated, open-source pre-and post-processor for nonlinear mixed-effects modeling in S-ADAPT. We developed a new translator tool (SADAPT-TRAN) based on Perl scripts. These scripts (a) automatically translate the core model components into robust Fortran code, (b) perform extensive mutual error checks across all input files and the raw dataset, (c) extend the options of the Monte Carlo Parametric Expectation Maximization (MC-PEM) algorithm, and (d) improve the numerical robustness of the model code. The post-processing scripts automatically summarize the results of one or multiple models as tables and, by generating problem specific R scripts, provide an extended series of standard and covariatestratified diagnostic plots. The SADAPT-TRAN package substantially improved the efficiency to specify, debug, and evaluate models and enhanced the flexibility of using the MC-PEM algorithm for parallelized estimation in S-ADAPT. The parameter variability model can take any combination of normally, lognormally, or logistically distributed parameters and the SADAPT-TRAN package can automatically generate the Fortran code required to specify between occasion variability. Extended estimation features are available to avoid local minima, estimate means with negligible variances, and estimate variances for fixed means. The SADAPT-TRAN package significantly facilitated model development in S-ADAPT, reduced model specification errors, and provided useful error messages for beginner and advanced users. This benefit was greatest for complex mechanistic models.

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