Substantial research over the past two decades has established that magnetic fields affect fundamental cellular processes, including gene expression. However, since biological cells and subcellular components exhibit diamagnetic behavior and are therefore subjected to very small magnetic forces that cannot directly compete with the viscoelastic and bioelectric intracellular forces responsible for cellular machinery functions, it becomes challenging to understand cell-magnetic field interactions and to reveal the mechanisms through which these interactions differentially influence gene expression in cells. The limited understanding of the molecular mechanisms underlying biomagnetic effects has hindered progress in developing effective therapeutic applications of magnetic fields. This review examines the expanding body of literature on genetic events during static and low-frequency magnetic field exposure, focusing particularly on how changes in gene expression interact with cellular machinery. To address this, we conducted a systematic review utilizing extensive search strategies across multiple databases. We explore the intracellular mechanisms through which transcription functions may be modified by a magnetic field in contexts where other cellular signaling pathways are also activated by the field. This review summarizes key findings in the field, outlines the connections between magnetic fields and gene expression changes, identifies critical gaps in current knowledge, and proposes directions for future research. LEVEL OF EVIDENCE: NA TECHNICAL EFFICACY: Stage 4.
Background: As ferroptosis is a key factor in renal fibrosis (RF), iron deposition monitoring may help evaluating RF. The capability of quantitative susceptibility mapping (QSM) for detecting iron deposition in RF remains uncertain.
Purpose: To investigate the potential of QSM to detect iron deposition in RF.
Study type: Animal model.
Animal model: Eighty New Zealand rabbits were randomly divided into control (N = 10) and RF (N = 70) groups, consisting of baseline, 7, 14, 21, and 28 days (N = 12 in each), and longitudinal (N = 10) subgroups. RF was induced via unilateral renal arteria stenosis.
Field strength/sequence: 3 T, QSM with gradient echo, arterial spin labeling with gradient spin echo.
Assessment: Bilateral kidney QSM values (χ) in the cortex (χCO) and outer medulla (χOM) were evaluated with histopathology.
Statistical tests: Analysis of variance, Kruskal-Wallis, Spearman's correlation, and the area under the receiver operating characteristic curve (AUC). P < 0.05 was significant.
Results: In fibrotic kidneys, χCO decreased at 7 days ([-6.69 ± 0.98] × 10-2 ppm) and increased during 14-28 days ([-1.85 ± 2.11], [0.14 ± 0.58], and [1.99 ± 0.60] × 10-2 ppm, respectively), while the χOM had the opposite trend. Both significantly correlated with histopathology (|r| = 0.674-0.849). AUC of QSM for distinguishing RF degrees was 0.692-0.993. In contralateral kidneys, the χCO initially decreased ([-6.67 ± 0.84] × 10-2 ppm) then recovered to baseline ([-4.81 ± 0.89] × 10-2 ppm), while the χOM at 7-28 days ([2.58 ± 1.40], [2.25 ± 1.83], [2.49 ± 2.11], [2.43 ± 1.32] × 10-2 ppm, respectively) were significantly higher than baseline ([0.54 ± 0.18] × 10-2 ppm).
Data conclusion: Different iron deposition patterns were observed in RF with QSM values, suggesting the potential of QSM for iron deposition monitoring in RF.
Plain language summary: Renal fibrosis (RF) is a common outcome in most kidney diseases, leading to scarring and loss of kidney function. Increasing evidence suggests that abnormal iron metabolism plays an important role in RF. This study used a technique called quantitative susceptibility mapping (QSM) to measure kidney iron levels in rabbits with RF. Specifically, rabbits with advanced RF exhibited higher kidney iron concentrations, and moderate to strong correlations between QSM values and histopathology demonstrated that QSM could accurately detect changes in iron levels and assess RF severity. Overall, QSM shows promise as a tool for monitoring iron deposition in RF progression.
Evidence level: 2 TECHNICAL EFFICACY: Stage 3.
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