Cardinal Parameters Research Articles

Shear‐driven flow of an ionic fluid in a narrow vertical channel under a Hall electric field

AbstractThis paper focuses on demonstrating the shear‐driven convective flow of an ionic optically thin fluid in a narrow channel formed by two vertical parallel plates subject to a Hall electric field. The Hall electric field induces Hall currents, amending the flow dynamics of the ionic fluid. The setup involves a stationary left wall and a right wall that either undergoes impulsive motion (IM) or accelerated motion (AM), which initiates the fluid flow. A unified closed‐form solution for flow‐regulating equations is derived by harnessing the Laplace transform (LT) approach. The upshots of cardinal parameters on the velocity components and temperature distributions, shear stresses, and rate of heat transfer (RHT) are elucidated via graphics for both IM and AM scenarios. The graphs reveal that an intensification in the Hall parameter notably boosts the velocity components in both IM and AM cases. The primary and secondary velocities are consistently higher for IM than AM. The magnitude of shear stresses at the moving wall is always greater for IM than AM. Additionally, the shear stresses at the moving wall are notably greater for IM than AM, and the RHT at the moving wall reduces as the radiation parameter amplifies. The significant findings of this research have potential applications in electromagnetic propulsion systems, like plasma or ion thrusters, commonly employed in propelling spacecraft.

Inter-strain variability on the cardinal parameters (pH and Aw) of clinical and food isolates of Listeria monocytogenes using turbidimetric measurements

Listeria monocytogenes is a foodborne pathogen which, in 2021, was considered the fifth most commonly reported zoonosis in humans in the European Union (EU). Ready-to-eat (RTE) fishery products, deli meats or soft cheeses have been mostly involved in food safety alerts and outbreaks in the last years. Hurdle technology by food industries has been widely used to enhance the safety of foods. Among the barriers, the application of acid and osmotic stress during processing is extensively used worldwide. This study aims to gain knowledge about the inter-strain variability of twenty-six clinical and food L. monocytogenes isolates with the estimation of their cardinal parameters using turbidimetric measurements. To analyse the data and to obtain the estimated cardinal values, a common statistical procedure was set up. The estimation of cardinal parameters showed a high inter-strain variability of L. monocytogenes, and no correlation was observed between Aw min and pHmin values for the studied strains. By grouping the strains in clinical, meat and fish origin, it was observed that strains from the meat group presented the lowest average pHmin values (4.57), thus showing potential acid adaptation. This work contributes to gain knowledge of the inter-strain variability of L. monocytogenes in relation with pH and Aw cardinal values, as well as provide a starting point for future validation studies in fish and meat food matrices.

Modelling growth of Bacillus cereus in paneer by one-step parameter estimation.

Bacillus cereus phylogenetic group III and IV strains are commonly associated with food products and cause toxin mediated foodborne diseases. These pathogenic strains have been identified from milk and dairy products, such as reconstituted infant formula and several cheeses. Paneer is a fresh, soft cheese originating from India that is prone to foodborne pathogen contamination, such as by Bacillus cereus. However, there are no reported studies of B. cereus toxin formation in paneer or predictive models quantifying growth of the pathogen in paneer under different environmental conditions. This study assessed enterotoxin-producing potential of B. cereus group III and IV strains, isolated from dairy farm environments, in fresh paneer. Growth of a four-strain cocktail of toxin-producing B. cereus strains was measured in freshly prepared paneer incubated at 5-55°C and modelled using a one-step parameter estimation combined with bootstrap re-sampling to generate confidence intervals for model parameters. The pathogen grew in paneer between 10 and 50°C and the developed model fit the observed data well (R2=0.972, RMSE=0.321 log10CFU/g). The cardinal parameters for B. cereus growth in paneer along with the 95% confidence intervals were: μopt 0.812 log10CFU/g/h (0.742, 0.917); Topt is 44.177°C (43.16, 45.49); Tmin is 4.405°C (3.973, 4.829); Tmax is 50.676°C (50.367, 51.144). The model developed can be used in food safety management plans and risk assessments to improve safety of paneer while also adding to limited information on B. cereus growth kinetics in dairy products.

Cardinal models to describe the effect of temperature and pH on the growth of Anoxybacillus flavithermus & Bacillus licheniformis

Anoxybacillus flavithermus and Bacillus licheniformis are among the predominant spore-formers of heat-processed foods. To our knowledge, no systematic analysis of growth kinetic data of A. flavithermus or B. licheniformis is currently available. In the present study, the growth kinetics of A. flavithermus and B. licheniformis in broth at various temperature and pH conditions were studied. Cardinal models were used to model the effect of the above-mentioned factors on the growth rates. The estimated values for the cardinal parameters Tmin,Topt,Tmax,pHmin and pH1/2 for A. flavithermus were 28.70 ± 0.26, 61.23 ± 0.16 and 71.52 ± 0.32 °C, 5.52 ± 0.01 and 5.73 ± 0.01, respectively, while for B. licheniformis they were 11.68 ± 0.03, 48.05 ± 0.15, 57.14 ± 0.01 °C, 4.71 ± 0.01 and 5.670 ± 0.08, respectively. The growth behaviour of these spoilers was also investigated in a pea beverage at 62 and 49 °C, respectively, to adjust the models to this product. The adjusted models were further validated at static and dynamic conditions and demonstrated good performance with 85.7 and 97.4% of predicted populations for A. flavithermus and B. licheniformis, respectively, being within the −10%–10% relative error (RE) zone. The developed models can be useful tools in assessing the potential of spoilage of heat-processed foods including plant-based milk alternatives.

The Structure and Diagnostic Accuracy of the QbTest in Pediatric ADHD: A Retrospective Clinical Study

Objective: The QbTest that combines a continuous performance task (CPT) with a motion-tracking system may help identify attention deficit hyperactivity disorder (ADHD). This study examined the structure and diagnostic ability of the QbTest in children and adolescents. Method: Retrospective data from 1,274 children and adolescents were analyzed. The study assessed data on a principal component analysis (PCA), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Results: The QbActivity component included the variables micro-events, distance, area, and time active; the QbImpulsivity included normalized commissions and commissions (anticipatory errors were added in a version for 6–12-year-olds only); and the QbInattention included omissions, reaction time, and reaction time variation. Sensitivity ranged between 22% and 50%, specificity 79% and 96%, PPVs 40% and 95%, and NPVs 24% and 66%. Conclusion: The structure of the QbTest with three cardinal parameters and nine/ten CPT and motion analysis variables was supported. The diagnostic accuracy was found to be poor to moderate. Given that this is a retrospective study, the interpretation of diagnostic accuracy should be considered within this context.

A Predictive Growth Model for Pro-technological and Probiotic Lacticaseibacillus paracasei Strains Fermenting White Cabbage.

Bacterial strains belonging to Lacticaseibacillus paracasei species are generally used as starters in food fermentations and/or as probiotics. In the current study, the growth cardinal parameters of four L. paracasei strains (IMPC2.1, IMPC4.1, P40 and P101), isolated from table olives or human source, were determined. Strains were grown in liquid medium and incubated at several temperatures (10 values from 5.5°C–40°C) and pH (15 values from 3.2 to 9.1) along the growth range. The cardinal temperature model was used to describe temperature effects on the maximum specific growth rate of L. paracasei whereas new equations were developed for the effect of pH. The estimated Tmin values ranged between −0.97°C and 1.95°C and were lower than 0°C for strains IMPC4.1 and P101. Strain P40 was able to grow in the most restricted range of temperature (from 1.95°C to 37.46°C), while strain IMPC4.1 was estimated to survive at extreme conditions showing the lowest pHmin. Maximum specific growth rates of L. paracasei IMPC2.1 in white cabbage (Brassica oleracea var. capitata) were used to calculate the correction factor (Cf) defined as the bias between the bacterial maximum specific growth rate in broth and in the food matrix. A simple bi-linear model was also developed for the effect of temperature on the maximum population density reached in white cabbage. This information was further used to simulate the growth of L. paracasei strains in cabbage and predict the time to reach the targeted probiotic level (7 log10 CFU/g) using in silico simulations. This study demonstrates the potential of the predictive microbiology to predict the growth of beneficial and pro-technological strains in foods in order to optimize the fermentative process.

Models of the water activity effect on microbial growth rate and initiation.

The role water activity, aw, plays in microbial growth by itself or in conjunction with other factors, notably temperature and pH, has been described mathematically by different algebraic models obtained by fitting experimental growth rate vs. aw relationships. Many of these models have one, two, or all three cardinal parameters, namely the minimal, optimal, and maximal aw, in their formulation. Although they all have good fit as judged by statistical criteria, their different mathematical structures have different ramifications concerning the threshold aw for growth initiation, and the growth pattern around and beyond the optimal aw level where it exists. The focus of this review is on the biological implications of the different growth rate vs. aw models inferred exclusively from their mathematical properties, leaving out any statistical fit considerations. It also describes a recently proposed single-parameter model of monotonic or the monotonic part of experimental growth rate vs. aw curves, which can be combined with a decay term to produce a general conceptual model of peaked and monotonic microbial growth rate vs. aw relationships over the entire aw range. KEY POINTS: • Traditional and new growth rate vs. aw models are presented and their implications compared. • Analogy between aw and the temperature or pH effect on microbial growth rate is reassessed. • Cardinal parameters alone do not establish a unique growth rate vs. aw relationship.

A Comparative Clinical Study of Khanda Shunthi and Prasarni Avleha in the Management of Amavata with Special Reference to Rheumatoid Arthritis

Background: Amavata is the most common form of inflammatory arthopathy seen in India. Among adult population below the age of 50 years this is the most common form of arthritis. For the present study, on Amavata as shaman therapy, Khanda Shunthi and Prasarni Avleha the Ushnaveeryadravya medicaments were chosen.
 Aims & Objective: The present research work aimed at to evaluate efficacy and establish safe use of Khanda Shunthi and Prasarni Aavaleha in Amavata.
 Materials & Methods: 40 subjects of Amavata fulfilling the inclusion criteria were selected from OPD and IPD of Desh Bhagat Ayurvedic Hospital, Mandi Gobindgarh, Punjab and randomly divided into two groups, group A and B, comprising each of 20 patients. Group-A subjects received Khanda Shunthi for 60 days, Group-B subjects received Prasarni Avaleha for 60 days. Assessments were done on 0th and 60th day of treatment.
 Results and Conclusions: In both the groups, highly significant results were observed in all the cardinal parameters with P value for fever and Hb are greater than 0.05 hence there is no significant difference in effect of Group A and Group B on fever and Hb. P values for all other symptoms are less than 0.05 hence we conclude that there is significant difference in effect of group A and group B on pain, swelling, stiffness, fever, ESR, walking time and grip strength. On comparison group A treatment is more effective than group B for all assessment criteria.

Development and validation of a predictive model for the effect of temperature, pH and water activity on the growth kinetics of Bacillus coagulans in non-refrigerated ready-to-eat food products

A cardinal model (CM) for the effects of temperature (range: 32–59 °C), pH (range: 5.0–8.5) and water activity (aw) (range: 0.980–0.995) on Bacillus coagulans DSM 1 growth rate was developed in brain heart infusion broth (BHI), using the Bioscreen C method and further validated in selected food products. The estimated values for the cardinal parameters Tmin, Topt, Tmax, pHmin, pHopt, pHmax, awmin and awopt were 23.77 ± 0.19 °C, 52.89 ± 0.01 °C, 59.37 ± 0.07 °C, 4.70 ± 0.02, 6.43 ± 0.02, 8.56 ± 0.01, 0.969 ± 0.0007 and 0.998 ± 0.0011, respectively. The growth behaviour of B. coagulans was studied in five commercial non-refrigerated ready-to-eat food products under static conditions at 53 °C in order to estimate the optimum specific growth rate for each tested food product. The developed models were validated in the five selected food products under four different dynamic temperature profiles by comparing predicted and observed growth behaviour of B. coagulans. The validation results indicated a good performance of the model for all tested products with the overall Bias factor (Bf) and Accuracy factor (Af) estimated at 1.00 and 1.12, respectively. The developed model can be considered an effective tool in predicting B. coagulans growth and spoilage risks of non-refrigerated ready-to-eat food products during distribution and storage.

Monitoring medication response in ADHD: what can continuous performance tests tell us?

Documenting effectiveness of ADHD medication is essential throughout the course of treatment. A rating scale and a continuous performance test (CPT) with motion tracking were used to study the effect of ADHD medication including compliance during one year. Children (N = 78, age 6–18 years) with ADHD were tested with the QbTest at baseline, visit 1 (1 month after baseline) and visit 5 (12 months after baseline). The ADHD-Rating scale was rated by investigator interview at the same visits. QbTest results and ADHD-RS ratings showed reductions in symptoms on all cardinal parameters of the QbTest and on all ADHD-RS subscales between baseline and 1 month and between baseline and 12 months. There was a weak but significant correlation between the total change scores on the two measures from baseline to 1 month. Eighteen participants dropped out of the study before visit 5; at baseline, these children showed significantly lower results on the inattention parameter of the QbTest, with faster reaction time and lower variation in reaction time, suggesting they suffered less problems with inattention. Both the QbTest and the ADHD-RS showed robust ADHD symptom improvements indicative of medication effect, and the QbTest results might also predict non-compliance of medication. Further research is warranted to increase knowledge about reliable monitoring of long-term medication and compliance.

Investigation of a hybrid solar thermochemical water-splitting hydrogen production cycle and coal-fueled molten carbonate fuel cell power plant

Increasing electricity demand in the world’s energy portfolio and the focus on reducing carbon emission footprints has led to broad research into flexible and efficient energy conversion systems. The integration of various energy conversion systems is an efficient approach to meet sustainable energy technologies’ demand in the future. In this study, a brainchild integration process of the solar thermochemical water-splitting hydrogen production cycle and coal-fueled molten carbonate fuel cell coupled with a gas turbine is proposed, modeled, and simulated in AspenTech v9.1. The Zinc/Zinc-oxide thermochemical cycle directly utilizes the solar high-temperature reactor thereby avoiding the need for non-renewable power, thus increasing the efficiency of the system. The molten carbonate fuel cell feeds on the syngas produced by the coal gasification and the oxygen and hydrogen of the thermochemical cycle. The heat of the fuel cell is further exploited by a gas turbine. A sensitivity analysis is conducted to appraise cardinal parameters on system performance indicating the fuel cell pressure, voltage, and current density as the most influential parameters. The concentrated solar power provides 5.88 MW of heat for the thermochemical cycle encompassing 434 parabolic dishes. The molten carbonate fuel cell has a 63% and 61% LHV and HHV efficiency, respectively, and the system has a total efficiency of approximately 85%, producing 13.63 MW of electricity.

Development and validation of an extended predictive model for the effect of pH and water activity on the growth kinetics of Geobacillus stearothermophilus in plant-based milk alternatives

The cardinal model for the effect of temperature on Geobacillus stearothermophilus ATCC 7953 growth developed by Kakagianni, Gougouli, & Koutsoumanis, 2016 was expanded for the effect of pH and water activity (aw). The effect of pH (range: 5.7–8.5) and aw (range: 0.985–0.999) on G. stearothermophilus growth rate was studied in tryptone soy broth (TSB) using the Bioscreen C method and further modelled using a Cardinal Model (CM). The estimated values for the cardinal parameters pHmin,pHopt,pHmax,awmin, and awopt were 5.65 ± 0.14, 6.74 ± 0.03, 8.71 ± 0.03, 0.984 ± 0.007 and 0.998 ± 0.001, respectively. The growth behaviour of G. stearothermophilus was investigated in 7 commercial non-refrigerated plant-based milk alternatives under static conditions (62 °C) and the estimated maximum specific growth rates were used to determine the optimum growth rate for each product. The developed model was validated against observed growth of G. stearothermophilus in the 7 products during storage at non-isothermal conditions (testing 4 different temperature profiles). The validation results showed a good performance of the model with overall Bias factor (Bf) = 1.06 and Accuracy factor (Af) = 1.12. The developed model can be used as an effective tool by the food industry in predicting spoilage of plant-based milk alternatives during distribution and storage at retail and domestic levels.

A stochastic approach for modelling the effects of temperature on the growth rate of Bacillus cereus sensu lato

A stochastic model that predicts the maximum specific growth rate (μmax) of Bacillus cereus sensu lato as a function of temperature was developed. The model integrates the intra-species variability by incorporating distributions of cardinal parameters (Tmin, Topt, Tmax) in the model. Growth rate data were generated for 22 strains, covering 5 major phylogenetic groups of B. cereus, and their cardinal temperatures identified. Published growth rate data were also incorporated in the model fitting, resulting in a set of 33 strains. Based on their cardinal temperatures, we identified clusters of Bacillus cereus strains that show similar response to temperature and these clusters were considered separately in the stochastic model. Interestingly, the μopt values for psychrotrophic strains were found to be significantly lower than those obtained for mesophilic strains. The model developed within this work takes into account some correlations existing between parameters (μopt, Tmin, Topt, Tmax). In particular, the relationship highlighted between the b-slope of the Ratkowsky model and Tmin (doi: https://doi.org/10.3389/fmicb.2017.01890) was adapted to the case of the popular Cardinal Temperature Model. This resulted in a reduced model in which μopt is replaced by a function of Tmin, Topt and 2 strain-independent parameters. A correlation between the Tmin parameter and the experimental minimal growth temperature was also highlighted and integrated in the model for improved predictions near the temperature growth limits. Compared to the classical approach, the model developed in this study leads to improved predictions for temperatures around Tmin and more realistic tails for the predicted distributions of μmax. It can be useful for describing the variability of the Bacillus cereus Group in Quantitative Microbial Risk Assessment (QMRA). An example of application of the stochastic model to Reconstituted Infant Formulae (RIF) was proposed.

Modeling Bacillus cereus Growth and Cereulide Formation in Cereal-, Dairy-, Meat-, Vegetable-Based Food and Culture Medium.

This study describes the simultaneous Bacillus cereus growth and cereulide formation, in culture medium and cereal-, dairy-, meat-, and vegetable-based food matrices. First, bacterial growth experiments were carried out under a wide range of temperatures (from 9 to 45°C), using the emetic reference strain F4810/72, in the above-mentioned matrices. Then, the generated data were put in a modeling framework where the response variable was a vector of two components: the concentration of B. cereus and that of its toxin, cereulide. Both were considered time-, temperature- and matrix-dependent. The modeling was carried out in a series of steps: the parameters fitted in one step became the response variable of the following step. Using the square root link function, the maximum specific growth rate of the organism and the time to the appearance of quantifiable cereulide were modeled against temperature by cardinal parameters models (CPM), for each matrix. Finally, a validation study was carried out on an independent data set obtained in the same matrices and using various Bacillus cereus strains. Results showed that both growth and toxin-formation depended on the food matrix and on the environment but not in the same way. Thus, the matrix (culture medium), where the highest growth rate of B. cereus was observed, was not the medium where the shortest time to quantifiable cereulide occurred. While the cereal-based matrix generated the smallest growth rates (0.41-times smaller than culture medium did), quantifiable cereulide appeared in it at earlier times compared to the other tested matrices. In fact, three groups of matrices could be distinguished based on their ability to support cereulide formation (1) the cereal-based matrix (highest), (2) the culture medium and the dairy-based matrix (intermediate), and (3) the meat- and vegetable-based matrices (lowest). This ranking between the matrices is quite different from that based on their suitability to the growth of the organism. Our models can be used in HACCP studies, to improve shelf-life predictions and, generally, microbiological food safety assessments of products for which B. cereus is the main concern.

The Impact of Methylphenidate on QbTest Performance of Children with ADHD: A Retrospective Clinical Study.

IntroductionThe Quantified behavior Test (QbTest), which combines a continuous performance task (CPT) and motion tracking, provides data for the core signs of attention-deficit/hyperactivity disorder (ADHD): attention, hyperactivity, and impulsivity. This study aimed to evaluate the performance of children and adolescents with ADHD on the QbTest before and after a single methylphenidate (MPH) dose.Subjects and MethodsThis retrospective chart review study included data from 149 children and 215 adolescents who completed the QbTest. A summary index of the CPT and motion capture data on the QbTest is provided by three cardinal parameters: QbActivity, QbImpulsivity, and QbInattention. The test was performed twice on the same day, before and up to three hours after MPH intake. A decrease by ≥ 0.5 in a cardinal parameter score was considered an improvement, whereas an increase by ≥ 0.5 a deterioration.ResultsQbActivity improvement after MPH intake was present in 71.7% and 76.2% of the children and adolescents, respectively. QbImpulsivity improvement was observed in 50.4% of the children and 44.7% of the adolescents, and QbInattention improvement in 85.1% and 91.1% of the children and adolescents, respectively. All three parameters improved simultaneously in 27.7% of the children and 28.7% of the adolescents. The likelihood that one parameter deteriorated after MPH use was greater if that parameter was within the normal range before medication. This was most pronounced for QbImpulsivity. Among male adolescents, QbInattention improvement was often accompanied by QbImpulsivity deterioration.ConclusionThe QbTest inattention and motor activity parameters improved markedly after a single MPH dose in children and adolescents with ADHD, while less so for impulsivity. Improvement of one parameter is not necessarily associated with improvement of the other two, and deterioration, especially regarding impulsivity, may occur. If confirmed, these results highlight the need for optimization and individualization of MPH treatment, while monitoring all aspects of the ADHD symptomatology based on the QbTest performance.

Growth characterization and predictive behavior of Eurotium species in a feedstuff matrix

Animal feeds are characterized by low water activity values. Nevertheless, fungal contamination with Eurotium species are quite common, causing nutritional depletion, spoilage and economic losses.The aim of this work was to assess Eurotium amstelodami, E. chevalieri, E. repens and E. rubrum growth in a feed matrix at different conditions of water activity (0.71–0.97) and temperature (5, 15, 25, 30 and 37°C).It was found that Eurotium species are able to grow in a wide range of water activity and temperature in a short period of time (7 days) and faster than in synthetic media. Rosso and probabilistic models were applied in order to determine the limiting and optimum growth conditions as well as growth probability at certain combinations of environmental factors. Both models provided an accurate fit to the cardinal parameters and good performance for growth/no growth cases.This is the first report assessing the growth parameters of Eurotium species directly in animal feed. Data obtained in the present study is useful to predict and avoid Eurotium species growth in animal feed.

Cardinal parameter meta-regression models describing Listeria monocytogenes growth in broth

Since Listeria monocytogenes has a high case-fatality rate, substantial research has been devoted to estimate its growth rate under different conditions of temperature, pH and water activity (aw). In this study, published findings on L. monocytogenes growth in broth were extracted and unified by constructing meta-regression models based on cardinal models for (i) temperature (CM[T]), (ii) temperature and pH (CM[T][pH]), and (iii) temperature, pH and aw (CM[T][pH][aw]). After assessing all the sources retrieved between 1988 until 2017, forty-nine primary studies were considered appropriate for inclusion. Apart from the modelling variables, study characteristics such as: type of broth (BHI, TSB, TPB), reading method (colony-forming-units, CFU; or binary-dilution optical density methods, OD), inoculum concentration and strain serotype, were also extracted. Meta-regressions based on CM[T] and CM[T][pH] were fitted on subsets of the 2009 growth rate measures and revealed that type of broth and reading method significantly modulated the cardinal parameter estimates. In the most parsimonious CM[T][pH][aw] meta-regression model, whereby the variability due to type of broth was extracted in a nested random-effects structure, the optimum growth rate μopt of L. monocytogenes was found to be lower when measured as CFU (0.947 log CFU/h; SE = 0.094 log CFU/h) than when measured as OD (1.289 log CFU/h; SE = 0.092 log CFU/h). Such a model produced the following cardinal estimates: Tmin = -1.273 °C (SE = 0.179 °C), Topt = 37.26 °C (SE = 0.688 °C), Tmax = 45.12 °C (SE = 0.013 °C), pHmin = 4.303 (SE = 0.014), pHopt = 7.085 (SE = 0.080), pHmax = 9.483 (SE = 0.080), awmin = 0.894 (SE = 0.002) and awopt = 0.995 (SE = 0.001). Integrating the outcomes from numerous L. monocytogenes growth experiments, this meta-analysis has estimated pooled cardinal parameters that can be used as reference values in quantitative risk assessment studies.

The polyphasic ontogeny of the discoidal Late Devonian ammonoid Acrimeroceras

The Late Devonian ammonoid species Acrimeroceras falcisulcatum and A. stella have similar-shaped discoidal adult conchs. Their conch morphology and its ontogenetic development are described and analysed. Despite great similarities in their adult conch morphology, they can be clearly distinguished by differences in the shape of their juvenile whorl profile and by the growth trajectories of their cardinal conch parameters: conch width index, umbilical width index and whorl expansion rate. Quantification of ontogenetic change in the two species demonstrates that the stratigraphically younger species A. falcisulcatum possesses the less complex ontogeny compared to the stratigraphically older A. stella. The closely related genus Paratornoceras (early Famennian) and the unrelated Late Visean Calygirtyoceras show juvenile conch morphology and ontogenetic trajectories very similar to Acrimeroceras stella. This similarity can be seen as iterative independent unfolding of homoplastic characters, possibly linked to size-dependence of the functional morphology of the conchs.

One-Step Analysis for Listeria monocytogenes Growth in Ready-to-Eat Braised Beef at Dynamic and Static Conditions

This study aimed to estimate the growth parameters of Listeria monocytogenes growth in ready-to-eat (RTE) braised beef by one-step dynamic and static kinetic analysis. The Baranyi model and cardinal parameters model were integrated into a dynamic and static model to estimate the kinetic parameters under one dynamic condition (-20 to 40.0°C) and eight static conditions (4, 8, 15, 20, 30, 35, 37, and 40°C). Based on the dynamic and static methods, the respective dynamic and static results for estimated growth boundaries of L. monocytogenes in RTE braised beef were from -2.5 and -2.7°C to 40.5 and 40.7°C with optimal specific growth rates of 1.078 and 0.913 per h at temperatures of 35.7 and 35.0°C. Temperature effects on the specific growth rate and lag period were developed and used to simulate the change of the physiological state of inocula during the bacterial growth. Subsequently, three additional dynamic temperature profiles were implemented for external validation. The root mean square error of the model developed by dynamic regression (0.19 log CFU/g) is slightly better than that of the model developed by static regression (0.23 log CFU/g). Comparing the validation results, one-step dynamic analysis might be a preferable method for prediction, especially when the growth approaches the stationary phase. Generally, both one-step dynamic and static analyses could be used to accurately predict L. monocytogenes growth in RTE braised beef under fluctuating temperatures.

Growth of Clostridium perfringens in cooked chicken during cooling: One-step dynamic inverse analysis, sensitivity analysis, and Markov Chain Monte Carlo simulation

The objective of this study was to determine the kinetic parameters and apply Markov Chain Monte Carlo (MCMC) simulation to predict the growth of Clostridium perfringens from spores in cooked ground chicken meat during dynamic cooling. Inoculated samples were exposed to various cooling conditions to observe dynamic growth. A combination of 4 cooling profiles was used in one-step inverse analysis with the Baranyi model as the primary model and the cardinal parameters model as the secondary model. Six kinetic parameters of the Baranyi model and the cardinal parameters model, including Q0, Ymax, μopt, Tmin, Topt, and Tmax, were estimated.The estimated Tmin, Topt, and Tmax were 14.8, 42.9, and 50.5 °C, respectively, with a μopt of 5.25 h−1 and maximum cell density of 8.4 log CFU/g. Correlation analysis showed that both Q0 and Ymax are weakly correlated to other parameters, while the remaining parameters are mostly mildly to strongly correlated with each other. Although it may be difficult to estimate highly correlated parameters using a single temperature profile, one-step analysis with multiple different temperature profiles helped estimate them successfully.The estimated parameters were used as the prior information to construct the posterior distribution for Bayesian analysis. MCMC simulation was used to predict the bacterial growth using different dynamic temperature profiles for validation of the accuracy of the predictive models. The MCMC simulation results showed that the Bayesian analysis produced more accurate predictions of bacterial growth during cooling than the deterministic method. With Bayesian analysis, the root-mean-square-error (RMSE) of prediction was only 0.1 log CFU/g with all residual errors within ±0.25 log CFU/g. Therefore, Bayesian analysis is recommended for predicting the growth of C. perfringens in cooked meat during cooling.