Modeling the growth rate and lag time of different strains of Salmonella enterica and Listeria monocytogenes in ready-to-eat lettuce

The growth parameters (growth rate, mu and lag time, lambda) of three different strains each of Salmonella enterica and Listeria monocytogenes in minimally processed lettuce (MPL) and their changes as a function of temperature were modeled. MPL were packed under modified atmosphere (5% O-2, 15% CO2 and 80% N-2), stored at 7-30 degrees C and samples collected at different time intervals were enumerated for S. enterica and L monocytogenes. Growth curves and equations describing the relationship between mu and lambda as a function of temperature were constructed using the DMFit Excel add-in and through linear regression, respectively. The predicted growth parameters for the pathogens observed in this study were compared to ComBase, Pathogen modeling program (PMP) and data from the literature. High R-2 values (0.97 and 0.93) were observed for average growth curves of different strains of pathogens grown on MPL Secondary models of mu and lambda for both pathogens followed a linear trend with high R2 values (>0.90). Root mean square error (RMSE) showed that the models obtained are accurate and suitable for modeling the growth of S. enterica and L monocytogenes in MP lettuce. The current study provides growth models for these foodborne pathogens that can be used in microbial risk assessment. (C) 2011 Elsevier Ltd. All rights reserved.

Predictive factors of contact lens case contamination

PURPOSE: To examine the relationship between contact lens (CL) case contamination and various potential predictive factors. METHODS: 74 subjects were fitted with lotrafilcon B (CIBA Vision) CLs on a daily wear basis for 1 month. Subjects were randomly assigned one of two polyhexamethylene biguanide (PHMB) preserved disinfecting solutions with the corresponding regular lens case. Clinical evaluations were conducted at lens delivery and after 1 month, when cases were collected for microbial culture. A CL care non-compliance score was determined through administration of a questionnaire and the volume of solution used was calculated for each subject. Data was examined using backward stepwise binary logistic regression. RESULTS: 68% of cases were contaminated. 35% were moderately or heavily contaminated and 36% contained gram-negative bacteria. Case contamination was significantly associated with subjective dryness symptoms (OR 4.22, CI 1.37–13.01) (P<0.05). There was no association between contamination and subject age, ethnicity, gender, average wearing time, amount of solution used, non-compliance score, CL power and subjective redness (P>0.05). The effect of lens care system on case contamination approached significance (P=0.07). Failure to rinse the case with disinfecting solution following CL insertion (OR 2.51, CI 0.52–12.09) and not air drying the case (OR 2.31, CI 0.39–13.35) were positively correlated with contamination; however, did not reach statistical significance. CONCLUSIONS: Our results suggest that case contamination may influence subjective comfort. It is difficult to predict the development of case contamination from a variety of clinical factors. The efficacy of CL solutions, bacterial resistance to disinfection and biofilm formation are likely to play a role. Further evaluation of these factors will improve our understanding of the development of case contamination and its clinical impact.

PK/DB: database for pharmacokinetic properties and predictive in silico ADME models

The study of pharmacokinetic properties (PK) is of great importance in drug discovery and development. In the present work, PK/DB (a new freely available database for PK) was designed with the aim of creating robust databases for pharmacokinetic studies and in silico absorption, distribution, metabolism and excretion (ADME) prediction. Comprehensive, web-based and easy to access, PK/DB manages 1203 compounds which represent 2973 pharmacokinetic measurements, including five models for in silico ADME prediction (human intestinal absorption, human oral bioavailability, plasma protein binding, bloodbrain barrier and water solubility).

Mastoiditis in children: a prospective, observational study comparing clinical presentation, microbiology, computed tomography, surgical findings and histology

The aim of this study was to obtain comprehensive data on clinical presentation, microbiology, computed tomography, surgical findings and histology in acute, sub-acute and chronic mastoiditis. We performed a prospective, observational study in children under 16 years of age presenting to our institution during the 2-year period beginning in April 2000. The children were examined and their condition treated in accordance with a standardized protocol elaborated by the paediatric, otolaryngology (ORL) and radiology departments. Thirty-eight patients were hospitalized (22 with acute mastoiditis, seven with sub-acute mastoiditis, nine with chronic mastoiditis). There were 30 complications present in 21 patients (55%). Streptococcus pyogenes was the most common pathogen (7/24 cases), followed by Streptococcus pneumoniae (4/24 cases). Mastoid surgery was performed in 29 patients. Histology of mastoid tissue revealed predominantly acute inflammation in two cases, mixed acute/chronic inflammation in 19 cases and predominantly chronic inflammation in seven cases. Radiologic data were evaluated retrospectively. Spiral, volume-based high-resolution (HR) computed tomography (CT) of the temporal bone had a sensitivity of 100%, specificity of 38%, positive predictive value (PPV) of 50% and negative predictive value (NPV) of 100% in detecting coalescence of mastoid trabeculae. Cranial CT with contrast had a sensitivity of 80%, specificity of 94%, PPV of 80% and NPV of 94% in identifying intra-cranial extension. Conclusion: histological evidence suggests that sub-acute/chronic infection underlies not only sub-acute and chronic mastoiditis, but most cases of acute mastoiditis as well. HR-CT of the temporal bone is effective in ruling out coalescence. Cranial CT is valuable in identifying intra-cranial extension. Cranial and HR-CT are recommended in the examination of children with mastoiditis.

Semi-active control for structural vibration based on predictive algorithm [Chinese title = 基于预测算法的结构振动半主动控制]

Based on Newmark-β method, a structural vibration response is predicted. Through finding the appropriate control force parameters within certain ranges to optimize the objective function, the predictive control of the structural vibration is achieved. At the same time, the numerical simulation analysis of a two-storey frame structure with magneto-rheological (MR) dampers under earthquake records is carried out, and the parameter influence on structural vibration reduction is discussed. The results demonstrate that the semi-active control based on Newmark-β predictive algorithm is better than the classical control strategy based on full-state feedback control and has remarkable advantages of structural vibration reduction and control robustness.

A new predictive current control technique for multilevel converters

Multilevel inverters provide an attractive solution for power electronics when both reduced harmonic contents and high voltages are required. In this paper, a novel predictive current control technique is proposed for a three-phase multilevel inverter, which controls the capacitors voltages and load currents with low switching losses. The advantage of this contribution is that the technique can be applied to more voltage levels without significantly changing the control circuit. The three-phase three-level inverter with a pure inductive load has been implemented to track reference currents using analogue circuits and programmable logic device.

Dengue fever and el nino-southern oscillation in Queensland, Australia : a time series predictive model

Background It remains unclear over whether it is possible to develop an epidemic forecasting model for transmission of dengue fever in Queensland, Australia. Objectives To examine the potential impact of El Niño/Southern Oscillation on the transmission of dengue fever in Queensland, Australia and explore the possibility of developing a forecast model of dengue fever. Methods Data on the Southern Oscillation Index (SOI), an indicator of El Niño/Southern Oscillation activity, were obtained from the Australian Bureau of Meteorology. Numbers of dengue fever cases notified and the numbers of postcode areas with dengue fever cases between January 1993 and December 2005 were obtained from the Queensland Health and relevant population data were obtained from the Australia Bureau of Statistics. A multivariate Seasonal Auto-regressive Integrated Moving Average model was developed and validated by dividing the data file into two datasets: the data from January 1993 to December 2003 were used to construct a model and those from January 2004 to December 2005 were used to validate it. Results A decrease in the average SOI (ie, warmer conditions) during the preceding 3–12 months was significantly associated with an increase in the monthly numbers of postcode areas with dengue fever cases (β=−0.038; p = 0.019). Predicted values from the Seasonal Auto-regressive Integrated Moving Average model were consistent with the observed values in the validation dataset (root-mean-square percentage error: 1.93%). Conclusions Climate variability is directly and/or indirectly associated with dengue transmission and the development of an SOI-based epidemic forecasting system is possible for dengue fever in Queensland, Australia.

A prospective study of personality features predictive of early adolescent alcohol misuse

Personality factors implicated in alcohol misuse have been extensively investigated in adult populations. Fewer studies have clarified the robustness of personality dimensions in predicting early onset alcohol misuse in adolescence. The aim of this study was to examine the predictive utility of two prominent models of personality (Cloninger, 1987; Eysenck & Eysenck, 1975) in emergent alcohol misuse in adolescence. One hundred and 92 secondary school students (mean age = 13.8 years, SD = 0.5) were administered measures of personality (Revised Junior Eysenck Personality Questionnaire – abbreviated; Temperament scale of Junior Temperament and Character Inventory) and drinking behavior (quantity and frequency of consumption, Alcohol Use Disorders Identification Test) at Time 1. At 12-month follow-up, 170 students (88.5%) were retained. Hierarchical multiple regressions revealed the dimensions of psychoticism, extraversion, and Novelty-Seeking to be the most powerful predictors of future alcohol misuse in adolescents. Results provide support for the etiological relevance of these dimensions in the development of early onset alcohol misuse. Findings can be used to develop early intervention programs that target personality risk factors for alcohol misuse in high-risk youth.