Association Between the XRCC1, GSTM1, and GSTT1 Polymorphisms in Model of Thyroid Cancer: A Meta-Analysis.

Thyroid cancer is the most common malignant tumor of the endocrine system, and its incidence is increasing worldwide each year. This study aimed to explore the association between XRCC1, GSTM1, and GSTT1 polymorphisms in the model of thyroid cancer. The experiment was conducted by searching PubMed, Embase, and Web of Science, with the last search performed in March 2022. A total of 12 studies were included in this meta-analysis, with sample sizes ranging from 211 to 1124. The proportion of XRCC1 polymorphisms (rs25489, GG) in thyroid cancer was slightly lower than that of the normal control group, but the difference was not statistically significant (Mean difference=1.13, 95% CI: 0.99-1.28, p=0.08). The proportion of XRCC1 polymorphisms (rs25489, GA) in thyroid cancer was significantly lower than that of the normal control group (Mean difference=1.32, 95% CI: 1.16-1.52, p<0.00001). The proportion of XRCC1 polymorphisms (rs25489, AA) in thyroid cancer was slightly lower than that of the normal control group, but again, the difference was not statistically significant (Mean difference=0.78, 95% CI: 0.61-1.01, p=0.06). Similarly, the proportion of XRCC1 polymorphisms (rs25487, GG) and (rs25487, GA) in thyroid cancer was lower than that of the normal control group, but the differences were not statistically significant (p=0.22 and p=0.49, respectively). In conclusion, this study found that the proportion of XRCC1 polymorphisms (rs25489, AA) in thyroid cancer was lower than that of the normal control group.

Assessing the ecological loss of mining areas in Taiwan.

Mines are mostly located in the mountains and national forestlands in Taiwan. The development and use of mines have severely damaged the environment. Despite the long history of mining, the value of forest ecological services lost during mining operations have not yet been incorporated into the expenses borne by miners, and miners are not liable for compensation for ecological damage. This study evaluated the forest ecosystem service benefits lost since mining began, with the aim of providing future reference for calculating ecological damage related to mining. We investigated Mount Taibai mines in Yilan (northeast Taiwan) and Mount Yongshi mines in Hualian (east Taiwan), which are richly forested areas. According to Article 13 of the Mining Act in Taiwan, mining rights have a limitation of 20 years, and the two mines in this study have been in operation for 20 years. By using four ecological services-forest production, carbon sequestration, water resource replenishment, and forest recreation-we estimated the loss of ecological values in both mining regions. The result indicated that the loss of total forest production benefits over 20 years was 7,498.6 k New Taiwanese dollars (NTD) in Mount Taibai mines and 6,543.1 k NTD for Mount Yongshi mines, while the loss for the total carbon sequestration benefits over 20 years was 19,950 k NTD in Mount Taibai mines and 17,400 k NTD in Mount Yongshi mines. The loss of value for the total water conservation benefits over 20 years was 11,160 k NTD in Mount Taibai mines and 5,070 k NTD in Mount Yongshi mines. The loss value of forest recreation over 20 years was 1,443,855 k NTD for the two mines.

TNFα antagonist in combination with PD-1 blocker to prevent or retard malignant transformation of B[a]P-induced chronic lung inflammation.

Benzo[a]pyrene (B[a]P) is a typical complete carcinogen in tobacco, but its mechanism of inducing the development of chronic pneumonia and consequent lung cancer is unclear. Here we elucidated the role of myeloid-derived suppressor cells (MDSCs) in developing B[a]P-induced chronic lung inflammation and efficacy of immunotherapy in preventing subsequent malignant transformation. Our study showed that as B[a]P could induce the accumulation of MDSCs in lung tissues and enhance the immunosuppressive effect regulated by cytokines and metabolites, thereby promoting the formation of immunosuppressive microenvironment, where effector T cells were exhausted, NK cells were dysfunctional, regulatory T (Treg) cells were expanded, polarized alveolar macrophages were transformed from M1 to M2. Subsequently, we performed the immunotherapy to block TNFɑ only or both TNFɑ and PD-1 at the early- or middle-stage of B[a]P-induced chronic lung inflammation to ameliorate the immunosuppressive microenvironment. We found that TNFɑ antagonist alone or with PD-1 blocker was shown to exert therapeutic effects on malignant transformation at the early stage of B[a]P-induced chronic lung inflammation. Taken together, our findings demonstrated that B[a]P-induced chronic lung inflammation resulted in the accumulation of MDSCs in lung tissues and exercise their immunosuppressive functions, thereby developing an immunosuppressive microenvironment, thus TNFɑ antagonist alone or with PD-1 blocker could prevent or retard the malignant transformation of B[a]P-induced chronic lung inflammation.

Accelerating cardiac diffusion tensor imaging combining local low-rank and 3D TV constraint.

OBJECTIVE: Diffusion tensor magnetic resonance imaging (DT-MRI, or DTI) is a promising technique for invasively probing biological tissue structures. However, DTI is known to suffer from much longer acquisition time with respect to conventional MRI and the problem is worsened when dealing with in vivo acquisitions. Therefore, faster DTI for both ex vivo and in vivo scans is highly desired. MATERIALS AND METHODS: This paper proposes a new compressed sensing (CS) reconstruction method that employs local low-rank (LLR) model and three-dimensional (3D) total variation (TV) constraint to reconstruct cardiac diffusion-weighted (DW) images from highly undersampled k-space data. The LLR model takes the set of DW images corresponding to different diffusion gradient directions as a 3D image volume and decomposes the latter into overlapping 3D blocks. Then, the 3D blocks are stacked as two-dimensional (2D) matrix. Finally, low-rank property is applied to each block matrix and the 3D TV constraint to the 3D image volume. The underlying constrained optimization problem is finally solved using the first-order fast method. The proposed method is evaluated on real ex vivo cardiac DTI data as a prerequisite to in vivo cardiac DTI applications. RESULTS: The results on real human ex vivo cardiac DTI images demonstrate that the proposed method exhibits lower reconstruction errors for DTI indices, including fractional anisotropy (FA), mean diffusivities (MD), transverse angle (TA), and helix angle (HA), compared to existing CS-based DTI image reconstruction techniques. CONCLUSION: The proposed method provides better reconstruction quality and more accurate DTI indices in comparison with the state-of-the-art CS-based DW image reconstruction methods.

Uptake and depuration of eight fluoroquinolones (FQs) in common carp (Cyprinus carpio).

Fluoroquinolones (FQs) are extensively used in humans and animals, which have aroused wide attention due to the emergence of FQ resistant bacteria and frequent detection in water, sediment and organism. However, little information is available about the bioconcentration and tissue distribution of FQs in fish. In the present study, we investigated the uptake and depuration of eight FQs (balofloxacin (BAL), enoxacin (ENO), enrofloxacin (ENR), fleroxacin (FLE), lomefloxacin (LOM), moxifloxacin (MOX), ofloxacin (OFL), sparfloxacin (SPA)) in common carp under controlled laboratory conditions. The results showed that all target FQs could accumulate in fish tissues, and had a similar tendency over time during the whole uptake and depuration periods. The uptake rate constant (k1), depuration rate constant (k2) and half-lives (t1/2) were in the ranges of 0.007-3.599 L/(kg·d), 0.051-0.283 d-1 and 2.4-10.7 d, respectively. The ranges of bioconcentration factors (BCFs) were 0.24-39.55 L/kg, 0.21-24.97 L/kg and 0.04-1.07 L/kg in liver, kidney and muscle, respectively. BCFs of eight FQs decreased in the order: MOX > ENR > ENO ≈ BAL ≈ FLE ≈ OFL ≈ LOM ≈ SPA, which may be correlated with the substituents at positions 7 and 8 of the basic quinolone nucleus and the metabolic capacity. Besides, BCFs were relative with pH-adjusted distribution coefficient (log D), suggesting that molecular status of ionizable compounds strongly influenced the bioconcentration processes. The present study provides important insights for understanding the bioconcentration and tissues distribution of FQs.

Generalization of intravoxel incoherent motion model by introducing the notion of continuous pseudodiffusion variable.

PURPOSE: A generalized intravoxel incoherent motion (IVIM) model, called the GIVIM, was proposed to better account for complex perfusion present in the tissues having various vessels and flow regimes, such as the liver. THEORY AND METHODS: The notions of continuous pseudodiffusion variable as well as perfusion fraction density function were introduced to describe the presence of multiple perfusion components in a voxel. The mean and standard deviation of Gaussian perfusion fraction density function were then used to define two new parameters, the mean pseudodiffusivity ( D¯) and pseudodiffusion dispersion (σ). The GIVIM model was evaluated by testing whether or not it can reflect hepatic perfusion difference caused by flow-compensated imaging sequences having different diffusion times. Also, D¯ was compared with D* in the standard IVIM model. RESULTS: The values of both D* and D¯ decreased after flow compensation and further decreased when shortening diffusion time. D¯ exhibited reduced variance in comparison with D*. In addition, σ also showed its sensitivity to hepatic perfusion difference caused by the flow-compensated imaging sequences. CONCLUSION: The GIVIM model has the ability to better describe multicomponent perfusion without lengthening acquisition time and knowing in advance the number and/or the variety of perfusion components. Magn Reson Med 76:1594-1603, 2016. © 2015 International Society for Magnetic Resonance in Medicine.

Characteristics and distribution research on extracellular polymer substance extracted from sewage sludge.

Extracellular polymer substance (EPS) is an important substance in sludge dewatering process and can be divided into slime, loosely bound EPS(LB-EPS) and tightly bound EPS(TB-EPS). The major components in different EPS layers in mechanical dewatered sludge (sample D) and sludge from thickening tank (sample U) were analyzed in the study. Results showed that, for all sludge samples, protein content in slime was much higher than that in LB-EPS and TB-EPS. In addition, from the results of total EPS content in four sludge samples (U: 98.68 mg gvss⁻¹, US (sample U+SDS): 135.27 mg gvss⁻¹, D:138.16 mg gvss⁻¹, DS:211.21 mg gvss⁻¹), it was found that sodium dodecyl sulfate (SDS) extracted more EPS content from sludge, which proved that SDS might cause substantial release of EPS, especially PN from sludge. Increase PS content in LB-EPS, and TB-EPS as addition of SDS, implied sensibility of cells in sludge to SDS. Differential Scanning Calorimetry found that bound water proportion in four different sludge samples ranged as follows: as D>DS>US>U. Results from other analytical techniques,such as FTIR and NMR, were also given the supported proof for the distribution changes of EPS and bound water.

Analytical model of optical fluence inside multiple cylindrical inhomogeneities embedded in an otherwise homogeneous turbid medium for quantitative photoacoustic imaging.

We present an analytical model of optical fluence for multiple cylindrical inhomogeneities embedded in an otherwise homogeneous turbid medium. The model is based on the diffusion equation and represents the optical fluence distribution inside and outside inhomogeneities as a series of modified Bessel functions. We take into account the interplay between cylindrical inhomogeneities by introducing new boundary conditions on the surface of inhomogeneities. The model is compared with the numerical solution of the diffusion equation with NIRFAST software. The fluences inside the inhomogeneities obtained by the two methods are in close agreement. This permits the use of the model as a forward model for quantitative photoacoustic imaging.

A novel joint problem of routing, scheduling, and variable-width channel allocation in WMNs.

This paper investigates a novel joint problem of routing, scheduling, and channel allocation for single-radio multichannel wireless mesh networks in which multiple channel widths can be adjusted dynamically through a new software technology so that more concurrent transmissions and suppressed overlapping channel interference can be achieved. Although the previous works have studied this joint problem, their linear programming models for the problem were not incorporated with some delicate constraints. As a result, this paper first constructs a linear programming model with more practical concerns and then proposes a simulated annealing approach with a novel encoding mechanism, in which the configurations of multiple time slots are devised to characterize the dynamic transmission process. Experimental results show that our approach can find the same or similar solutions as the optimal solutions for smaller-scale problems and can efficiently find good-quality solutions for a variety of larger-scale problems.

Atmospheric CO2 and 14CO2 observations at the northern foot of the Qinling Mountains in China: Temporal characteristics and source quantification.

A two-year (March 2021 to February 2023) continuous atmospheric CO2 and a one-year regular atmospheric 14CO2 measurement records were measured at the northern foot of the Qinling Mountains in Xi'an, China, aiming to study the temporal characteristics of atmospheric CO2 and the contributions from the sources of fossil fuel CO2 (CO2ff) and biological CO2 (CO2bio) fluxes. The two-year mean CO2 mole fraction was 442.2 ± 16.3 ppm, with a yearly increase of 4.7 ppm (i.e., 1.1 %) during the two-year observations. Seasonal CO2 mole fractions were the highest in winter (452.1 ± 17.7 ppm) and the lowest in summer (433.5 ± 13.3 ppm), with the monthly CO2 levels peaking in January and troughing in June. Diurnal CO2 levels peaked at dawn (05:00-07:00) in spring, summer and autumn, and at 10:00 in winter. 14C analysis revealed that the excess CO2 (CO2ex, atmospheric CO2 minus background CO2) at this site was mainly from CO2ff emissions (67.0 ± 26.8 %), and CO2ff mole fractions were the highest in winter (20.6 ± 17.7 ppm). Local CO enhancement above the background mole fraction (ΔCO) was significantly (r = 0.74, p < 0.05) positively correlated with CO2ff in a one-year measurement, and ΔCO:CO2ff showed a ratio of 23 ± 6 ppb/ppm during summer and winter sampling days, much lower than previous measurements and suggesting an improvement in combustion efficiency over the last decade. CO2bio mole fractions also peaked in winter (14.2 ± 9.6 ppm), apparently due to biomass combustion and the lower and more stable wintertime atmospheric boundary layer. The negative CO2bio values in summer indicated that terrestrial vegetation of the Qinling Mountains had the potential to uptake atmospheric CO2 during the corresponding sampling days. This site is most sensitive to local emissions from Xi'an and to short distance transportation from the southern Qinling Mountains through the valleys.

Explainable geospatial-artificial intelligence models for the estimation of PM2.5 concentration variation during commuting rush hours in Taiwan.

PM2.5 concentrations are higher during rush hours at background stations compared to the average concentration across these stations. Few studies have investigated PM2.5 concentration and its spatial distribution during rush hours using machine learning models. This study employs a geospatial-artificial intelligence (Geo-AI) prediction model to estimate the spatial and temporal variations of PM2.5 concentrations during morning and dusk rush hours in Taiwan. Mean hourly PM2.5 measurements were collected from 2006 to 2020, and aggregated into morning (7 a.m.-9 a.m.) and dusk (4 p.m.-6 p.m.) rush-hour mean concentrations. The Geo-AI prediction model was generated by integrating kriging interpolation, land-use regression, machine learning, and a stacking ensemble approach. A forward stepwise variable selection method based on the SHapley Additive exPlanations (SHAP) index was used to identify the most influential variables. The performance of the Geo-AI models for morning and dusk rush hours had accuracy scores of 0.95 and 0.93, respectively and these results were validated, indicating robust model performance. Spatially, PM2.5 concentrations were higher in southwestern Taiwan for morning rush hours, and suburban areas for dusk rush hours. Key predictors included kriged PM2.5 values, SO2 concentrations, forest density, and the distance to incinerators for both morning and dusk rush hours. These PM2.5 estimates for morning and dusk rush hours can support the development of alternative commuting routes with lower concentrations.

Vertical measurements of atmospheric CO2 and 14CO2 at the northern foot of the Qinling Mountains in China.

The CO2 and 14CO2 levels in air samples from the northern foot of the Qinling Mountains (Xi'an, China) were determined. In 2021, a hexacopter unmanned aerial vehicle sampled air at different heights, from near-ground to 2000 m. The objectives of this study were to determine vertical characteristics of CO2 and 14CO2, the sources of different-height CO2, and the influence of air mass transport. The CO2 concentrations mainly exhibited a slight decreasing trend with increasing height during summer observations, which was in contrast to the increasing trend that was followed by a subsequent gradual decreasing trend during early winter observations, with peak CO2 levels (443.4 ± 0.4-475.7 ± 0.5 ppm) at 100-500 m. The variation in vertical concentrations from 20 to 1000 m in early winter observations (21.6 ± 19.3 ppm) was greater than that in summer observations (14.6 ± 14.3 ppm), and the maximum vertical variation from 20 to ∼2000 m reached 61.1 ppm. Combining Δ14C and δ13C vertical measurements, the results showed that fossil fuel CO2 (CO2ff, 56.1 ± 15.2 %), which mainly come from coal combustion (81.2 ± 3.4 %), was the main contributor to CO2 levels in excess of the background level (CO2ex) during early winter observations. In contrast, biological CO2 (CO2bio) dominated CO2ex in summer observations. The vertical distributions of CO2ff in early winter observations and CO2bio in summer observations were consistent with those of CO2 during early winter and summer observations, respectively. The strong correlation between winter CO2bio and ΔCO (r = 0.81, p < 0.01) indicated that biomass burning was the main contributor to CO2bio during early winter observations. Approximately half of the air masses originated from the Guanzhong Basin during observations. The results provide insights into the vertical distribution of different-sources of atmospheric CO2 in scientific support of formulating carbon emission-reduction strategies.

Describing movement learning using metric learning.

Analysing movement learning can rely on human evaluation, e.g. annotating video recordings, or on computing means in applying metrics on behavioural data. However, it remains challenging to relate human perception of movement similarity to computational measures that aim at modelling such similarity. In this paper, we propose a metric learning method bridging the gap between human ratings of movement similarity in a motor learning task and computational metric evaluation on the same task. It applies metric learning on a Dynamic Time Warping algorithm to derive an optimal set of movement features that best explain human ratings. We evaluated this method on an existing movement dataset, which comprises videos of participants practising a complex gesture sequence toward a target template, as well as the collected data that describes the movements. We show that it is possible to establish a linear relationship between human ratings and our learned computational metric. This learned metric can be used to describe the most salient temporal moments implicitly used by annotators, as well as movement parameters that correlate with motor improvements in the dataset. We conclude with possibilities to generalise this method for designing computational tools dedicated to movement annotation and evaluation of skill learning.

T cell-mediated tumor killing patterns in head and neck squamous cell carcinoma identify novel molecular subtypes, with prognosis and therapeutic implications.

As an important process in cancer immunotherapy, T cell-mediated tumor killing (TTK) enhances the immune response of patients. However, the role of TTK in Head and Neck Squamous Cell Carcinoma (HNSCC) patients still needs further exploration. Therefore, we comprehensively analyzed the gene expression information and clinical characteristics of 1063 HNSCC in five cohorts. Univariate regression, differential expression analysis, and gene mutation profiling were combined to identify the important genes regulating the sensitivity of tumor cells to T cell-mediated killing (GSTTK) in HNSCC. A total of 20 GSTTK were identified as important genes of HNSCC. Patients were divided into C1 and C2 subgroups (TTK patterns) and displayed significant prognostic differences. Patients with C2 subtype had dismal prognosis characteristic compared to C1 subtype in all validation cohorts. Patients with C1 subgroup exhibited robust immune profile and C1 subgroup patients were significantly enriched in metabolically relevant functions. Notably, the multi-omics analysis found that C1 subgroup have higher mutation burden and C2 subgroup patients had significantly higher copy number variation. Drug sensitivity analysis found that multiple first-line chemotherapeutic drugs were more sensitive in patients with subgroup C1. In conclusion, the establishment of GSTTK provides guidance and assistance to clinicians in the personalized management and treatment of HNSCC patients.

Interpretatively automated identification of circulating tumor cells from human peripheral blood with high performance.

The detection and analysis of circulating tumor cells (CTCs) would be of aid in a precise cancer diagnosis and an efficient prognosis assessment. However, traditional methods that rely heavily on the isolation of CTCs based on their physical or biological features suffer from intensive labor, thus being unsuitable for rapid detection. Furthermore, currently available intelligent methods are short of interpretability, which creates a lot of uncertainty during diagnosis. Therefore, we propose here an automated method that takes advantage of bright-field microscopic images with high resolution, so as to take an insight into cell patterns. Specifically, the precise identification of CTCs was achieved by using an optimized single-shot multi-box detector (SSD)-based neural network with integrated attention mechanism and feature fusion modules. Compared to the conventional SSD system, our method exhibited a superior detection performance with the recall rate of 92.2%, and the maximum average precision (AP) value of 97.9%. To note, the optimal SSD-based neural network was combined with advanced visualization technology, i.e., the gradient-weighted class activation mapping (Grad-CAM) for model interpretation, and the t-distributed stochastic neighbor embedding (T-SNE) for data visualization. Our work demonstrates for the first time the outstanding performance of SSD-based neural network for CTCs identification in human peripheral blood environment, showing great potential for the early detection and continuous monitoring of cancer progression.

Advances in understanding the pathogenesis of post-traumatic epilepsy: a literature review.

Severe head trauma can lead to seizures. Persistent epileptic seizures and their progression are associated with the severity of trauma. Although case reports have revealed that early use of anti-seizure drugs after trauma can prevent epilepsy, clinical case-control studies have failed to confirm this phenomenon. To date, many brain trauma models have been used to study the correlation between post-traumatic seizures and related changes in neural circuit function. According to these studies, neuronal and glial responses are activated immediately after brain trauma, usually leading to significant cell loss in injured brain regions. Over time, long-term changes in neural circuit tissues, especially in the neocortex and hippocampus, lead to an imbalance between excitatory and inhibitory neurotransmission and an increased risk of spontaneous seizures. These changes include alterations in inhibitory interneurons and the formation of new, over-recurrent excitatory synaptic connections. In this study, we review the progress of research related to post-traumatic epilepsy to better understand the mechanisms underlying the initiation and development of post-traumatic seizures and to provide theoretical references for the clinical treatment of post-traumatic seizures.

Correction: A molecularly imprinted antibiotic receptor on magnetic nanotubes for the detection and removal of environmental oxytetracycline.

Correction for 'A molecularly imprinted antibiotic receptor on magnetic nanotubes for the detection and removal of environmental oxytetracycline' by Jixiang Wang et al., J. Mater. Chem. B, 2022, 10, 6777-6783, https://doi.org/10.1039/D2TB00497F.

When herpes simplex virus encephalitis meets antiviral innate immunity.

Herpes simplex virus (HSV) is the most common pathogen of infectious encephalitis, accounting for nearly half of the confirmed cases of encephalitis. Its clinical symptoms are often atypical. HSV PCR in cerebrospinal fluid is helpful for diagnosis, and the prognosis is usually satisfactory after regular antiviral treatment. Interestingly, some patients with recurrent encephalitis have little antiviral effect. HSV PCR in cerebrospinal fluid is negative, but glucocorticoid has a significant effect after treatment. Specific antibodies, such as the NMDA receptor antibody, the GABA receptor antibody, and even some unknown antibodies, can be isolated from cerebrospinal fluid, proving that the immune system contributes to recurrent encephalitis, but the specific mechanism is still unclear. Based on recent studies, we attempt to summarize the relationship between herpes simplex encephalitis and innate immunity, providing more clues for researchers to explore this field further.

USP7- and PRMT5-dependent G3BP2 stabilization drives de novo lipogenesis and tumorigenesis of HNSC.

GTPase-activating protein-binding protein 2 (G3BP2) is a key stress granule-associated RNA-binding protein responsible for the formation of stress granules (SGs). Hyperactivation of G3BP2 is associated with various pathological conditions, especially cancers. Emerging evidence indicates that post-translational modifications (PTMs) play critical roles in gene transcription, integrate metabolism and immune surveillance. However, how PTMs directly regulate G3BP2 activity is lacking. Here, our analyses identify a novel mechanism that PRMT5-mediated G3BP2-R468me2 enhances the binding to deubiquitinase USP7, which ensures the deubiquitination and stabilization of G3BP2. Mechanistically, USP7- and PRMT5-dependent G3BP2 stabilization consequently guarantee robust ACLY activation, which thereby stimulating de novo lipogenesis and tumorigenesis. More importantly, USP7-induced G3BP2 deubiquitination is attenuated by PRMT5 depletion or inhibition. PRMT5-activity dependent methylation of G3BP2 is required for its deubiquitination and stabilization by USP7. Consistently, G3BP2, PRMT5 and G3BP2 R468me2 protein levels were found positively correlated in clinical patients and associated with poor prognosis. Altogether, these data suggest that PRMT5-USP7-G3BP2 regulatory axis serves as a lipid metabolism reprogramming mechanism in tumorigenesis, and unveil a promising therapeutic target in the metabolic treatment of head and neck squamous carcinoma.

Research progress on correlations between trace element levels and epilepsy.

Research investigating the correlation between human trace element levels and disease alterations is growing. Epilepsy, a common nervous system disease, has also been found to be closely related to abnormal levels of trace elements. Studies continue to explore mechanisms of various trace elements involved in epileptic seizures through experimental animal models of epilepsy. Thus, we reviewed the research progress on the correlation between trace element levels and epilepsy in recent years and found that the trace elements most closely related to epilepsy are mainly metal ions such as selenium, iron, copper, zinc, and manganese. These results indicate that the changes in some trace elements are closely related to the increase in epilepsy susceptibility. In addition, after treatment with drugs and a ketogenic diet, the concentration of trace elements in the serum of patients with epilepsy changes. In other words, the abnormality of trace element concentrations is of great significance in the occurrence and development of epilepsy. This article is a literature update on the potential role of trace element imbalance in the development of epilepsy, providing new references for the subsequent prevention and treatment of epilepsy.