Interaction of low frequency external electric fields and pancreatic β-cell: a mathematical modeling approach to identify the influence of excitation parameters

2018 · Harm · Low evidence

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HarmLow evidencePaper 1818

Using simulations of a mathematical human β-cell model, the authors report that an external electric field can influence membrane electrical activity and perhaps insulin secretion when the field amplitude exceeds a threshold. They also report that waveform an…

Study snapshot

Publicationmanual · 2018
Study typeother
Reported directionHarm
Evidence ratingLow

Abstract

Interaction of low frequency external electric fields and pancreatic β-cell: a mathematical modeling approach to identify the influence of excitation parameters Farashi S, Sasanpour P, Rafii-Tabar H. Interaction of low frequency external electric fields and pancreatic β-cell: a mathematical modeling approach to identify the influence of excitation parameters. Int J Radiat Biol. 2018 Nov;94(11):1038-1048. doi: 10.1080/09553002.2018.1478162. Abstract PURPOSE: Although the effect of electromagnetic fields on biological systems has attracted attraction in recent years, there has not been any conclusive result concerning the effects of interaction and the underlying mechanisms involved. Besides the complexity of biological systems, the parameters of the applied electromagnetic field have not been estimated in most of the experiments. MATERIALS AND METHODS: In this study, we have used computational approach in order to find the excitation parameters of an external electric field which produces sensible effects in the function of insulin secretory machinery, whose failure triggers the diabetes disease. A mathematical model of the human β-cell has been used and the effects of external electric fields with different amplitudes, frequencies and wave shapes have been studied. RESULTS: The results from our simulations show that the external electric field can influence the membrane electrical activity and perhaps the insulin secretion when its amplitude exceeds a threshold value. Furthermore, our simulations reveal that different waveforms have distinct effects on the β-cell membrane electrical activity and the characteristic features of the excitation like frequency would change the interaction mechanism. CONCLUSION: The results could help the researchers to investigate the possible role of the environmental electromagnetic fields on the promotion of diabetes disease. ncbi.nlm.nih.gov

Machine Enhanced Logic

AI evidence extraction

Structured fields below were generated from the paper’s abstract and metadata to make the evidence easier to inspect. Automated extraction may be incomplete or incorrect; verify important details against the original paper.

Study typeother
Effect directionharm
PopulationHuman pancreatic β-cell (mathematical model)
Sample sizeNot supplied
ExposureELF
Evidence strengthLowConfidence: 78% · Peer reviewed: yes

Main findings

Using simulations of a mathematical human β-cell model, the authors report that an external electric field can influence membrane electrical activity and perhaps insulin secretion when the field amplitude exceeds a threshold. They also report that waveform and excitation features such as frequency produce distinct effects and may change the interaction mechanism.

Outcomes measured

  • β-cell membrane electrical activity
  • Insulin secretion (modeled/indirect)

Limitations

  • Computational/modeling study rather than empirical measurements in humans/animals/cells
  • Threshold amplitude value is mentioned but not quantified in the abstract
  • Insulin secretion effects are described as possible/indirect ("perhaps")
  • Environmental relevance of modeled field parameters is not established in the abstract
View raw extracted JSON
{
  "publication_year": 2018,
  "study_type": "other",
  "exposure": {
    "band": "ELF",
    "source": "external electric field (modeled)",
    "frequency_mhz": null,
    "sar_wkg": null,
    "duration": null
  },
  "population": "Human pancreatic β-cell (mathematical model)",
  "sample_size": null,
  "outcomes": [
    "β-cell membrane electrical activity",
    "Insulin secretion (modeled/indirect)"
  ],
  "main_findings": "Using simulations of a mathematical human β-cell model, the authors report that an external electric field can influence membrane electrical activity and perhaps insulin secretion when the field amplitude exceeds a threshold. They also report that waveform and excitation features such as frequency produce distinct effects and may change the interaction mechanism.",
  "effect_direction": "harm",
  "limitations": [
    "Computational/modeling study rather than empirical measurements in humans/animals/cells",
    "Threshold amplitude value is mentioned but not quantified in the abstract",
    "Insulin secretion effects are described as possible/indirect (\"perhaps\")",
    "Environmental relevance of modeled field parameters is not established in the abstract"
  ],
  "evidence_strength": "low",
  "confidence": 0.78,
  "peer_reviewed_likely": "yes",
  "stance": "concern",
  "stance_confidence": 0.66,
  "summary": "This paper uses a computational mathematical model of a human pancreatic β-cell to study how low-frequency external electric fields with varying amplitudes, frequencies, and waveforms could affect β-cell function. Simulations suggest membrane electrical activity can be influenced when field amplitude exceeds a threshold, with waveform and frequency altering the response. The authors propose the results may help guide research on whether environmental electromagnetic fields could play a role in diabetes promotion.",
  "key_points": [
    "The study is a mathematical modeling/simulation analysis of external electric field interactions with a human β-cell model.",
    "Simulations suggest an external electric field may alter β-cell membrane electrical activity above a threshold amplitude.",
    "The authors suggest insulin secretion could potentially be affected, based on modeled changes in electrical activity.",
    "Different waveforms are reported to produce distinct effects on modeled membrane activity.",
    "Frequency and other excitation characteristics are reported to change the interaction mechanism in the model.",
    "The work is framed as helping identify excitation parameters that could produce measurable biological effects in experiments."
  ],
  "categories": [
    "Mechanisms",
    "Modeling",
    "ELF Fields",
    "Diabetes/Metabolic"
  ],
  "tags": [
    "Computational Modeling",
    "Mathematical Model",
    "External Electric Field",
    "Low Frequency",
    "Pancreatic Beta Cells",
    "Membrane Electrical Activity",
    "Insulin Secretion",
    "Waveform Effects",
    "Frequency Dependence",
    "Diabetes"
  ],
  "keywords": [
    "electromagnetic fields",
    "external electric field",
    "low frequency",
    "pancreatic β-cell",
    "mathematical model",
    "membrane electrical activity",
    "insulin secretion",
    "waveform",
    "frequency",
    "diabetes"
  ],
  "suggested_hubs": [],
  "social": {
    "tweet": "Modeling study: simulations of a human pancreatic β-cell suggest low-frequency external electric fields may alter membrane electrical activity above a threshold amplitude, with waveform and frequency shaping the response (Int J Radiat Biol, 2018).",
    "facebook": "A computational study using a mathematical model of a human pancreatic β-cell reports that low-frequency external electric fields could influence membrane electrical activity above a threshold amplitude, and that waveform and frequency change the modeled response. The authors suggest this may guide research on possible links to diabetes mechanisms.",
    "linkedin": "In a 2018 International Journal of Radiation Biology paper, researchers used a mathematical human β-cell model to explore how low-frequency external electric fields (varying amplitude, frequency, waveform) might affect membrane electrical activity and potentially insulin secretion. Simulations indicate threshold-dependent effects and waveform/frequency-specific responses, proposed as a guide for future experimental work."
  }
}
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AI-extracted fields are generated from the abstract and metadata and may be incomplete or incorrect. This material is for informational purposes and is not medical advice.

Identifiers and source

DOI: 10.1080/09553002.2018.1478162
PubMed: Not supplied

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