Evidence map›Paper›PMID 39966846›Full record

ArticleJournal of biological engineering2025

Bioelectric profiling of Rickettsia montanensis in Vero cells utilizing dielectrophoresis.

Negar Farhang Doost, Sai Deepika Reddy Yaram, Kayla Wagner, Harshit Garg, Soumya K Srivastava

Abstract read
In one paragraph

Article in Journal of biological engineering, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Machine Learning-Based Detection ofPathogens (Basel, Switzerland) · 2026
    Article
  2. Article
  3. Article
  4. Article
  5. Dielectrophoretic Profiling ofACS measurement science au · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Negar Farhang DoostDepartment of Chemical and Biomedical Engineering, West Virginia University, 1306 Evansdale Dr., PO Box 6102, Morgantown, WV, 26506-6102, USA.
Sai Deepika Reddy YaramDepartment of Chemical and Biomedical Engineering, West Virginia University, 1306 Evansdale Dr., PO Box 6102, Morgantown, WV, 26506-6102, USA.
Kayla WagnerDepartment of Chemical and Biomedical Engineering, West Virginia University, 1306 Evansdale Dr., PO Box 6102, Morgantown, WV, 26506-6102, USA.
Harshit GargDepartment of Biochemical Engineering and Biotechnology, Indian Institute of Technology- Delhi, Delhi, India.
Soumya K SrivastavaDepartment of Chemical and Biomedical Engineering, West Virginia University, 1306 Evansdale Dr., PO Box 6102, Morgantown, WV, 26506-6102, USA. soumya.srivastava@mail.wvu.edu.

Funding

SCH: Machine LEarning & MicrofluiDics for Multimodal Sensing of TiCk-bOrne Diseases(MEDICO)R01AI174300 · NIAID · WEST VIRGINIA UNIVERSITY · PI SRIVASTAVA, SOUMYA K · 2022 to 2025
$1.2M
NIAID NIH HHS R01 AI174300NIH HHS 1R01AI174300
6 · The paper itself

Abstract

Rickettsia is an intracellular bacteria transmitted to humans through ticks, lice, fleas, or their feces, causing acute symptoms such as fever, headache, rashes, and muscle aches. Detecting rickettsial diseases is challenging due to limitations in current methods such as negative results, low sensitivity, and high cost. These limitations highlight the need for improved detection methods. Dielectrophoresis (DEP) offers a promising alternative to develop a point-of-care economical, label-free, and sensitive diagnostic tool. By exposing cells to non-uniform electric fields one can measure the electrical properties of the cells which are different and unique based on the cell type. By comparing the dielectric profiles of healthy and infected cells, DEP could be utilized to design a rapid, cost-effective diagnostic tool. Initial steps involve characterizing the electrophysiological properties of Vero cells infected with Rickettsia montanensis to develop this new detection tool. This study found significant differences in electrical parameters between healthy and Rickettsia spp. infected Vero cells, particularly at a medium conductivity of 500 µS/cm. Moreover, we found that the dielectric spectrum showed the greatest differences between healthy and Rickettsia spp. infected Vero cells at medium conductivity of 500 µS/cm, with significantly different dielectrophoretic crossover frequencies (no DEP force region). These findings suggest that dielectrophoretic detection of infected cells could serve as a quick, cost-effective, label-free, and sensitive alternative for developing a point-of-care diagnostic tool for Rickettsial infections.

Indexed as

Bioelectric signaturesDiagnostic toolDielectrophoresisElectrophysiological propertiesRickettsia montanensisRocky mountain spotted fever

Identifiers

PMID39966846
PMCPMC11837300

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.