Modeling Microbial Inactivation by Pulsed Electric Field

Peleg, Micha

doi:10.1007/978-3-319-32886-7_43

Cited by 5 publications

(2 citation statements)

References 20 publications

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“…The modeling conducted by Singh et al (2017) has a lower error, which is less than 5% with an electric field intensity of 9-21 kV/cm, but its application has not been reported at lower electric field intensities. Similar modeling was also carried out by Peleg (2017) by giving a treatment using an electric field of 8.0 -20.0 kV/cm.…”

Section: Discussionmentioning

confidence: 99%

Modeling of Inactivation of Biofilm Composing Bacteria with Low Intensity Electric Field: Prediction of Lowest Intensity and Mechanism

Tirono¹,

Suhariningsih²

2021

JST

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Sterilization using high-intensity electric fields is detrimental to health if safety is inadequate, so it is necessary to study the possibility of sterilization using low-intensity electric fields. This study aims to determine the lowest electric field intensity and treatment time to deactivate the bacteria that make up the biofilms and explain the mechanism of inactivation. The study samples were biofilms from the bacteria Pseudomonas aeruginosa and Staphylococcus epidermidis grown on the catheter. The modeling formula was developed from the Pockels effect and the Weibull distribution with the treatment using a square pulse-shaped electric field with a pulse width of 50 μs and an intensity of 2.0-4.0 kV/ cm. The results showed that the threshold for irreversible electroporation of both samples occurred in the treatment using an electric field with an intensity of 3.5 kV/cm and 3.75 kV/ cm, respectively, where the size and type of Gram of bacteria influenced. Moreover, the time of the treatment had an effect when irreversible electroporation occurred. However, when there was reversible electroporation, the effect of treatment time on the reduction in the number of bacteria was not significant. Also, changes in conductivity affected the reduction in the number of bacteria when reversible electroporation occurred.

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Section: Discussionmentioning

confidence: 99%

Modeling of Inactivation of Biofilm Composing Bacteria with Low Intensity Electric Field: Prediction of Lowest Intensity and Mechanism

Tirono¹,

Suhariningsih²

2021

JST

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“…1) or the onset of inactivation after sustained growth [24]. At least in principle, stochastic models can also be written for scenarios that include cell division, injury and damage repair [36] and simultaneous activation and inactivation of bacterial spores [11].…”

Section: Runmentioning

confidence: 99%

Microbial Dose-Response Curves and Disinfection Efficacy Models Revisited

Peleg

2020

Food Eng Rev

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The same term "dose-response curve" describes the relationship between the number of ingested microbes or their logarithm, and the probability of acute illness or death (type I), and between a disinfectant's dose and the targeted microbe's survival ratio (type II), akin to survival curves in thermal and non-thermal inactivation kinetics. The most common model of type I curves is the cumulative form of the beta-Poisson distribution which is sometimes indistinguishable from the lognormal or Weibull distribution. The most notable survival kinetics models in static disinfection are of the Chick-Watson-Hom's kind. Their published dynamic versions, however, should be viewed with caution. A microbe population's type II dose-response curve, static and dynamic, can be viewed as expressing an underlying spectrum of individual vulnerabilities (or resistances) to the particular disinfectant. Therefore, such a curve can be described mathematically by the flexible Weibull distribution, whose scale parameter is a function of the disinfectant's intensity, temperature, and other factors. But where the survival ratio's drop is so steep that the static dose-response curve resembles a step function, the Fermi distribution function becomes a suitable substitute. The utility of the CT (or Ct) concept primarily used in water disinfection is challenged on theoretical grounds and its limitations highlighted. It is suggested that stochastic models of microbial inactivation could be used to link the fates of individual viruses or bacteria to their manifestation in the survival curve's shape. Although the emphasis is on viruses and bacteria, most of the discussion is relevant to fungi, protozoa, and perhaps worms too.

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Deterministic and stochastic survival models of injured ozonated Giardia cysts

Peleg

2022

Appl Microbiol Biotechnol

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Modeling Microbial Inactivation by Pulsed Electric Field

Cited by 5 publications

References 20 publications

Modeling of Inactivation of Biofilm Composing Bacteria with Low Intensity Electric Field: Prediction of Lowest Intensity and Mechanism

Modeling of Inactivation of Biofilm Composing Bacteria with Low Intensity Electric Field: Prediction of Lowest Intensity and Mechanism

Microbial Dose-Response Curves and Disinfection Efficacy Models Revisited

Deterministic and stochastic survival models of injured ozonated Giardia cysts

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