Comparison of predicted and real propofol and remifentanil concentrations in plasma and brain tissue during target-controlled infusion: a prospective observational study.

Target-controlled infusion systems are increasingly used to administer intravenous anaesthetic drugs to achieve a user-specified plasma or effect-site target concentration. While several studies have investigated the ability of the underlying pharmacokinetic-dynamic models to predict plasma concentrations, there are no data on their performance in predicting drug concentrations in the human brain. We assessed the predictive performance of the Marsh propofol model and Minto remifentanil model for plasma and brain tissue concentrations. Plasma samples were obtained during neurosurgery from 38 patients, and brain tissue samples from nine patients. Propofol and remifentanil concentrations were measured using gas chromatography mass spectrometry and liquid chromatography tandem mass spectrometry. Data were analysed from the nine patients in whom both plasma and brain samples were simultaneously obtained. For the Minto model (five patients), the median performance error was 72% for plasma and -14% for brain tissue concentration predictions. The model tended to underestimate plasma remifentanil concentrations, and to overestimate brain tissue remifentanil concentrations. For the Marsh model (five patients), the median prediction errors for plasma and brain tissue concentrations were 12% and 81%, respectively. However, when the data from all blood propofol assays (36 patients) were analysed, the median prediction error was 11%, with overprediction in 15 (42%) patients and underprediction in 21 (58%). These findings confirm earlier reports demonstrating inaccuracy for commonly used pharmacokinetic-dynamic models for plasma concentrations and extend these findings to the prediction of effect-site concentrations.

Outcome in patient-specific PEEK cranioplasty: A two-center cohort study of 40 implants.

OBJECTIVE: The best material choice for cranioplasty following craniectomy remains a subject to discussion. Complication rates after cranioplasty tend to be high. Computer-assisted 3-dimensional modelling of polyetheretherketone (PEEK) was recently introduced for cranial reconstruction. The aim of this study was to evaluate patient- and surgery-related characteristics and risk factors that predispose patients to cranioplasty complications. MATERIAL AND METHODS: This retrospective study included a total of 40 cranial PEEK implants in 38 patients, performed at two reference centers in the Netherlands from 2011 to 2014. Complications were registered and patient- and surgery-related data were carefully analysed. RESULTS: The overall complication rate of PEEK cranioplasty was 28%. Complications included infection (13 %), postoperative haematoma (10 %), cerebrospinal fluid leak (2.5 %) and wound-related problems (2.5 %). All postoperative infections required removal of the implant. Nonetheless removed implants could be successfully re-used after re-sterilization. CONCLUSION: Although overall complication rates after PEEK cranioplasty remain high, outcomes are satisfactory, as our results compare favourably to recent literature reports on cranial vault reconstruction.

Designing optimal calcium phosphate scaffold-cell combinations using an integrative model-based approach.

Bone formation is a very complex physiological process, involving the participation of many different cell types and regulated by countless biochemical, physical and mechanical factors, including naturally occurring or synthetic biomaterials. For the latter, calcium phosphate (CaP)-based scaffolds have proven to stimulate bone formation, but at present still result in a wide range of in vivo outcomes, which is partly related to the suboptimal use and combination with osteogenic cells. To optimize CaP scaffold selection and make their use in combination with cells more clinically relevant, this study uses an integrative approach in which mathematical modeling is combined with experimental research. This paper describes the development and implementation of an experimentally informed bioregulatory model of the effect of calcium ions released from CaP-based biomaterials on the activity of osteogenic cells and mesenchymal stem cell driven ectopic bone formation. The amount of bone formation predicted by the mathematical model corresponds to the amount measured experimentally under similar conditions. Moreover, the model is also able to qualitatively predict the experimentally observed impaired bone formation under conditions such as insufficient cell seeding and scaffold decalcification. A strategy was designed in silico to overcome the negative influence of a low initial cell density on the bone formation process. Finally, the model was applied to design optimal combinations of calcium-based biomaterials and cell culture conditions with the aim of maximizing the amount of bone formation. This work illustrates the potential of mathematical models as research tools to design more efficient and cell-customized CaP scaffolds for bone tissue engineering applications.

Optic tract edema sign and craniopharyngiomas.

Two patients with craniopharyngioma presenting with the "optic tract edema sign" are described. This sign is seen in a majority of craniopharyngiomas and can be of help in the differentiation with other suprasellar masses such as pituitary adenomas, meningiomas, germinomas and lymphomas. Nevertheless it has to be emphasized that the sign is not absolute and can be seen now and then in these other tumors.

On the selection of relevant environmental factors to predict microbial dynamics in solidified media.

Several studies have shown that food structure causes slower growth rates and narrower growth boundaries of bacteria compared to laboratory media. In predictive microbiology, both a(w) or corresponding solute concentration (mainly NaCl) have been used as a growth influencing factor for kinetic models or growth/no growth interface models. The majority of these models have been based on data generated in liquid broth media with NaCl as the predominant a(w) influencing solute. However, in complex food systems, other a(w) influencing components might be present, next to NaCl. In this study, the growth rate of Salmonella typhimurium was studied in the growth region and the growth/no growth response was tested in Tryptic Soy Broth at 20 degrees C at varying gelatin concentration (0, 10, 50 g L(-1) gelatin), pH (3.25-5.5) and water activity (a(w)) (0.929-0.996). From the viewpoint of water activity, the results suggest that NaCl is the main a(w) affecting compound. However, gelatin seemed to have an effect on medium a(w) too. Moreover, there is also an interaction effect between NaCl and gelatin. From the microbial viewpoint, the results confirmed that the a(w) decreasing effect of gelatin is less harmful to cells than the effect of Na(+) ions. The unexpected shift of the growth/no growth interface to more severe conditions when going from a liquid medium to a medium with 10 g L(-1) gelatin is more pronounced when formulating the models in terms of a(w) than in terms of NaCl concentrations. At 50 g L(-1) gelatin, the model factored with NaCl concentration shifts to milder conditions (concordant to literature results) while the model with a(w) indicates a further shift to more severe conditions, which is due to the water activity lowering effect of gelatin and the interaction between gelatin and NaCl. The results suggest that solute concentration should be used instead of a(w), both for kinetic models in the growth region and for growth/no growth interface models, if the transferability of models to solid foods is to be increased.

Evaluation of a mathematical model structure describing the effect of (gel) structure on the growth of Listeria innocua, Lactococcus lactis and Salmonella Typhimurium.

AIMS: To evaluate a novel secondary model structure (Int J Food Microbiol 2008; 128: 67) that describes the effect of medium structure on the maximum specific growth rate (mu(max)) of Salmonella Typhimurium on the growth of S. Typhimurium, Listeria innocua, Lactococcus lactis and Listeria monocytogenes. METHODS AND RESULTS: In the present study, the novel secondary model is validated for S. Typhimurium in more realistic media, namely, pasteurized milk and a cheese mimicking medium. The predictions were accurate. Next, the secondary model structure was evaluated in a two step and a global regression procedure on literature data. On the one hand, the growth of two other micro-organisms, namely L. innocua and L. lactis, in monoculture for varying gelatine concentrations was tested and on the other hand the growth rate of L. monocytogenes was fitted in a broth of which the viscosity was altered with polyvinylpyrrolidone. The model was able to describe the effect of increasing gelatine concentration or viscosity accurately. CONCLUSIONS: The proposed secondary model structure is able to describe the effect of gelatine concentration on the mu(max) of the micro-organisms tested in this study. SIGNIFICANCE AND IMPACT OF THE STUDY: In predictive microbiology, much attention has been paid to the effect of food structure on the mu(max) of bacteria. However, to the authors' knowledge, a lack of secondary models still exists to describe this effect. Although the proposed model is empirical, the model parameters have clear biological meaning. The predictive power of the model to describe the effect of food structure is clearly illustrated.

Extracting information on the evolution of living- and dead-cell fractions of Salmonella Typhimurium colonies in gelatin gels based on microscopic images and plate-count data.

AIMS: The aim of this study was to extract information on cell number and colony volume dynamics of Salmonella Typhimurium colonies. METHODS AND RESULTS: Both cell number and colony volume of Salmonella Typhimurium in gelatin were monitored during the exponential and the stationary phase with varying pH and water activity, by plate counts and microscopic image analysis respectively. The exponential growth rates of cell numbers and colony volumes were correlated. The exponential growth rate of cell numbers was estimated based on this correlation and a secondary model that describes the effect of pH and water activity on the growth rate of the colony volumes. During the stationary phase, the cell number was constant, while colony volume increased, thus indicating the formation of a dead fraction. Models were developed to describe the living and dead population. CONCLUSIONS: By comparing colony volumes and cell numbers, the formation of dead fraction can be noticed from the beginning of the stationary phase, which indicates that the stationary phase is a dynamic - including both cell death and cell growth - rather than a static phase. SIGNIFICANCE AND IMPACT OF THE STUDY: This study was the first to investigate the proportion of living and dead bacteria within a stationary colony quantitatively.

Effect of pH, water activity and gel micro-structure, including oxygen profiles and rheological characterization, on the growth kinetics of Salmonella Typhimurium.

In this study, the growth of Salmonella Typhimurium in Tryptic Soy Broth was examined at different pH (4.50-5.50), water activity a(w) (0.970-0.992) and gelatin concentration (0%, 1% and 5% ) at 20 degrees C. Experiments in TSB with 0% gelatin were carried out in shaken erlenmeyers, in the weak 1% gelatin media in petri plates and in the firm 5% gelatin media in gel cassettes. A quantification of gel strength was performed by rheological measurements and the influence of oxygen supply on the growth of S. Typhimurium was investigated. pH, as well as a(w) as well as gelatin concentration had an influence on the growth rate. Both in broth and in gelatinized media, lowering pH or water activity caused a decrease of growth rate. In media with 1% gelatin a reduction of growth rate and maximal cell density was observed compared to broth at all conditions. However, the effects of decreasing pH and a(w) were less pronounced. A further increase in gelatin concentration to 5% gelatin caused a small or no additional drop of growth rate. The final oxygen concentration dropped from 5.5 ppm in stirred broth to anoxic values in petri plates, also when 0% and 5% gelatin media were tested in this recipient. Probably, not stirring the medium, which leads to anoxic conditions, has a more pronounced effect on the growth rate of S. Typhimurium then medium solidness. Finally, growth data were fitted with the primary model of Baranyi and Roberts [Baranyi, J. and Roberts, T. A., 1994. A dynamic approach to predicting bacterial growth in food. International Journal of Food Microbiology 23, 277-294]. An additional factor was introduced into the secondary model of Ross et al. [Ross, T. and Ratkowsky, D. A. and Mellefont, L. A. and McMeekin, T. A., 2003. Modelling the effects of temperature, water activity, pH and lactic acid concentration on the growth rate of Escherichia coli. International Journal of Food Microbiology 82, 33-43.] to incorporate the effect of gelatin concentration, next to the effect of pH and a(w). A two step and a global regression procedure were applied. Both procedures were able to fit the data well, but the global regression procedure led to smaller standard errors on the parameters.

Validation of a model for growth of Lactococcus lactis and Listeria innocua in a structured gel system: effect of monopotassium phosphate.

The effect of monopotassium phosphate (KH(2)PO(4)) on the chemical environment and on growth of Listeria innocua and Lactococcus lactis in coculture were investigated in a liquid and in a gelled microbiological medium at 12 degrees C and an initial pH of 6.2. As expected, addition of KH(2)PO(4) to both the liquid and gelled media resulted in an increase in buffering capacity. This effect on buffering capacity changed the profiles of lactic acid dissociation and pH evolution. At all gelatin concentrations studied, addition of KH(2)PO(4) increased the growth rate and the stationary cell concentration of L. lactis. In addition, the growth rate of L. innocua slightly increased but, in contrast, the stationary cell concentration remained unchanged. A new class of predictive models developed previously in our research team to quantify the effect of food model gel structure on microbial growth [Antwi, M., Bernaerts, K., Van Impe, J. F., Geeraerd, A. H., 2007. Modelling the combined effect of food model system and lactic acid on L. innocua and L. lactis growth in mono- and coculture. International Journal of Food Microbiology 120, 71-84] was applied. Our analysis indicate that KH(2)PO(4) influenced the parameters of the chemical and microbiological subprocesses of the model. Nonetheless, the growth model satisfactorily predicted the stationary cell concentration when (i) the undissociated lactic acid concentrations at which L. innocua and L. lactis growth cease were chosen as previously reported, and (ii) all other parameters of the chemical and microbiological subprocesses were computed for each medium. This confirms that the undissociated lactic acid concentrations at which growth ceases is a unique property of a bacterium and does not, within our case study, depend on growth medium. The study indicates that microbial growth depends on the interplay between the individual food components which affect the physicochemical properties of the food, such as the buffering capacity. Towards future research, it can be concluded that mathematical models which embody the effect of buffering capacity are needed for accurate predictions of microbial growth in food systems.

Inactivation of Escherichia coli and Shigella in acidic fruit and vegetable juices by peroxidase systems.

AIMS: To study the bactericidal properties of the lactoperoxidase (LPER)-thiocyanate and soybean peroxidase (SBP)-thiocyanate systems at low pH, their efficiency for inactivation of Escherichia coli and Shigella in acidic fruit and vegetable juices, their effect on colour stability of the juices and interaction with ascorbic acid. METHODS AND RESULTS: Three-strain cocktails of E. coli and Shigella spp. in selected juices were supplemented with the LPER or SBP system. Within 24 h at 20 degrees C, the LPER system inactivated both cocktails by > or = 5 log10 units in apple, 2-5 log10 units in orange and < or = 1 log10 unit in tomato juices. In the presence of SBP, browning was significant in apple juice and white grape juice, slight in pink grape juice and absent in orange or tomato juice. Ascorbic acid protected E. coli and Shigella against inactivation by the LPER system, and peroxidase systems significantly reduced the ascorbic acid content of juices. CONCLUSIONS: Our results suggest a different specificity of LPER and SBP for SCN-, phenolic substrates of browning and ascorbic acid in acidic juices. The LPER system appeared a more appropriate candidate than the SBP system for biopreservation of juices. SIGNIFICANCE AND IMPACT OF THE STUDY: This work may open perspectives towards the development of LPER or other peroxidases as biopreservatives in acidic foods.