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Pyridines and cyclopropanes are important structural units in chemistry. Herein, we introduce a photoredox-catalyzed approach for the ring opening and 1,3-oxypyridylation of aryl cyclopropanes using 4-cyanopyridines and carboxylic acids. This sequential process involves single-electron oxidation of the aryl cyclopropane, leading to nucleophilic ring opening and radical pyridylation at the benzylic position. The redox-neutral reaction exhibits high regioselectivity under mild reaction conditions, offering a broad substrate scope and wide applicability.

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BACKGROUND: In magnetic resonance imaging (MRI), maintaining a highly uniform main magnetic field (B0) is essential for producing detailed images of human anatomy. Passive shimming (PS) is a technique used to enhance B0 uniformity by strategically arranging shimming iron pieces inside the magnet bore. Traditionally, PS optimization has been implemented using linear programming (LP), posing challenges in balancing field quality with the quantity of iron used for shimming. PURPOSE: In this work, we aimed to improve the efficacy of passive shimming that has the advantages of balancing field quality, iron usage, and harmonics in an optimal manner and leads to a smoother field profile. METHODS: This study introduces a hybrid algorithm that combines particle swarm optimization with sequential quadratic programming (PSO-SQP) to enhance shimming performance. Additionally, a regularization method is employed to reduce the iron pieces' weight effectively. RESULTS: The simulation study demonstrated that the magnetic field was improved from 462  to 3.6 ppm, utilizing merely 1.2 kg of iron in a 40 cm diameter spherical volume (DSV) of a 7T MRI magnet. Compared to traditional optimization techniques, this method notably enhanced magnetic field uniformity by 96.7% and reduced the iron weight requirement by 81.8%. CONCLUSION: The results indicated that the proposed method is expected to be effective for passive shimming.

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Soil reconstruction is a critical step in the restoration of environments affected by mining activities. This paper provides a comprehensive review of the significant role that microbial processes play in expediting soil structure formation, particularly within the context of mining environment restoration. Coal gangue and flotation tailings, despite their low carbon content and large production volumes, present potential substrates for soil reclamation. These coal-based solid waste materials can be utilized as substrates to produce high-quality soil and serve as an essential carbon source to enhance poor soil conditions. However, extracting active organic carbon components from coal-based solid waste presents a significant challenge due to its complex mineral composition. This article offers a thorough review of the soilization process of coal-based solid waste under the influence of microorganisms. It begins by briefly introducing the primary role of in situ microbial remediation technology in the soilization process. It then elaborates on various improvements to soil structure under the influence of microorganisms, including the enhancement of soil aggregate structure and soil nutrients. The article concludes with future recommendations aimed at improving the efficiency of soil reconstruction and restoration, reducing environmental risks, and promoting its application in complex environments. This will provide both theoretical and practical support for more effective environmental restoration strategies.

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Porous cage materials with certain dimensions, sizes, shapes, and functions have been regarded as promising materials for sample preparation, chromatographic separation, and detection process. In contrast to infinite frameworks such as metal-organic frameworks or covalent organic frameworks, porous cage materials are constructed from discrete molecules containing at least one internal cavity. The well-defined cavities in porous cage materials provide opportunities for non-covalent interactions. These interactions can be programmed into the ligand design or supramolecular cage constructing using the cages as building blocks, offering various host-guest recognition with great selectivity. In this review, we desire to elucidate the fundamental principles governing the design and fabrication of porous cage materials with well-defined cavities, good solvent processability, and modifiable groups, the applications of these porous cage materials in sample preparation, chromatographic separation, and detection were discussed. The recent advantages of porous cage materials for the analysis process were summarized. We state the potential of these materials and provide an outlook for further application strategies. We expect that this review can inspire interest in the porous cage materials research area for analysis.

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Biomarkers and their concentration levels are critical indicators of metabolomics for clinical applications. Rapid and sensitive analysis methods are essential for realizing timely and efficient quantitation of those significant biomarkers. In this work, a self-driven microfluidic immunosensor was developed for rapid all-in-one separation, enrichment, and detection of biomarkers. This immunosensor was constructed from a cyclic olefin copolymer (COC) channel layer and a polydimethylsiloxane (PDMS) sensing layer. The COC channel layer was modified through protein adsorption, immobilization, and remaining active site blocking. The obtained hydrophilic microchannels not only reduce the nonspecific adsorption, but also provide stable capillary-driven flow generation with linear velocities up to 20 mm/s for aqueous solution auto-injection. The PDMS sensing layer was modified using capture antibodies to accomplish affinity recognition of target biomarkers. Procalcitonin (PCT) and serum amyloid A (SAA) were selected as model biomarkers in the feasibility study on applying the self-driven microfluidic immunosensor to bioassay. The limits of detection of PCT and SAA were 7.9 ng/L and 7.6 µg/L, respectively. Moreover, the whole process can be accomplished within 60 min with excellent selectivity and reproducibility. In clinical serum sample analysis, satisfactory recoveries were achieved for PCT and SAA in the ranges of 85.0-103.0% and 95.5-106.0%, respectively, with relative standard deviations less than 5.3%. The method accuracy was further confirmed by the results of commercial immunoassay kits. This simple and easily operated immunosensor provides a rapid and sensitive biomarker analysis tool, and promotes the further development of automated and easy-to-use microfluidic immunoassays.

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OBJECTIVES: Previous studies have shown that microstructural alterations in white matter (WM) could contribute to the symptom manifestation and support the dysconnectivity hypothesis in schizophrenia patients. These alterations were pervasive, non-specific, and reported inconsistently across the literature. This study aimed to specifically investigate the microstructure alterations of the posterior limb of the internal capsule (PLIC) in first-episode, drug-naive schizophrenia patients. Utilizing a multicompartmental biophysical model, we further explored the correlation between these alterations and syndrome scale scores. METHODS: Thirty-two individuals with first-episode, drug-naive schizophrenia (FES) and thirty demographically matched healthy controls were enrolled. High-resolution multi-shell diffusion MRI data were collected, followed by the application of a three-compartment Neurite Orientation Dispersion and Density Imaging (NODDI) model to scrutinize the alterations in white matter microstructure. Changes in sensory and motor fibers within the PLIC were specifically focused on. Additionally, the correlation between these pathological changes and scores on the Positive and Negative Syndrome Scale (PANSS) was investigated. RESULTS: The Neurite density index (NDI) in the left PLIC was significantly lower in FES patients compared to healthy individuals, and positively correlated with PANSS positive syndrome scores (r = 0.0379, p = 0.046). In the sensory component (left superior thalamic radiation within PLIC, STR_P), the NDI was significantly elevated (p < 0.0001). Conversely, the NDI in the motor component (left corticospinal tract within PLIC, CST_P) was reduced (p = 0.007) in FES patients compared to healthy individuals, and strongly correlated with PANSS positive syndrome scores (p < 0.020) and PANSS total scores (p < 0.045). Moreover, the NDI deviation of STR from total PLIC (fSTR_P) and NDI deviation in STR_P and CST_P compared to PLIC region (fPLIC) were significantly higher in FES patients than in healthy controls (p < 0.00001), with an area under the curve (AUC) of fPLIC reaching 0.872. CONCLUSION: The study's findings provided new insights into the discrepancy of white matter microstructure changes associated with the sensory and motor fibers in the PLIC region in FES patients. These results contribute to the growing body of evidence suggesting that WM microstructural alterations play a critical role in schizophrenia pathophysiology.

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BACKGROUND: Epilepsy and depression have complicated bidirectional relationships. Our study aimed to explore the field of epilepsy comorbid with depression in a bibliometric perspective from 2014-2023. AIM: To improve our understanding of epilepsy and depression by evaluating the relationship between epilepsy and depression, bibliometric analyses were performed. METHODS: Epilepsy and depression-related publications from the last decade were retrieved from the Web of Science Core Collection. We conducted bibliometric and visual analysis using VOSviewer and CiteSpace, examining authorships, countries, institutions, journals of publication, co-citations of references, connections between keywords, clusters of keywords, and keywords with citation bursts. RESULTS: Over the past ten years, we collected 1045 research papers focusing on the field of epilepsy and comorbid depression. Publications on epilepsy and depression have shown a general upward trend over time, though with some fluctuations. The United States, with 287 articles, and the University of Melbourne, contributing 34 articles, were the top countries and institutions, respectively. In addition, in the field of epilepsy and depression, Professor Lee, who has published 30 articles, was the most contributing author. The hot topics pay attention to the quality of life in patients with epilepsy and depression. CONCLUSION: We reported that quality of life and stigma in patients with epilepsy comorbid with depression are possible future hot topics and directions in the field of epilepsy and depression research.

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Moral disengagement is an important aggressive and moral cognition. The mechanisms of changes in moral disengagement remain unclear, especially at the within-person level. We attempted to clarify this by exploring the serial effects of personal relative deprivation and hostility on civic moral disengagement. We conducted a three-wave longitudinal survey with 1058 undergraduates (63.61% women; mean age = 20.97). The results of the random intercept cross-lagged panel model showed that personal relative deprivation at Wave 1 and hostility at Wave 2 formed a serial effect on the within-person changes in civic moral disengagement at Wave 3, and the longitudinal indirect effect test showed that the within-person dynamics in hostility at Wave 2 acted as a mediator. The results of multiple group analysis across genders further showed that the longitudinal indirect role of hostility at Wave 2 was only observed for men, but not for women, which indicates the moderating effect of gender. These findings facilitate an understanding of the mechanisms of aggressive cognitions at the within-person level and offer implications for the prevention and intervention of aggression from the perspective of moral cognition.

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Early diagnosis of abnormal electrocardiogram (ECG) signals can provide useful information for the prevention and detection of arrhythmia diseases. Due to the similarities in Normal beat (N) and Supraventricular Premature Beat (S) categories and imbalance of ECG categories, arrhythmia classification cannot achieve satisfactory classification results under the inter-patient assessment paradigm. In this paper, a multi-path parallel deep convolutional neural network was proposed for arrhythmia classification. Furthermore, a global average RR interval was introduced to address the issue of similarities between N vs. S categories, and a weighted loss function was developed to solve the imbalance problem using the dynamically adjusted weights based on the proportion of each class in the input batch. The MIT-BIH arrhythmia dataset was used to validate the classification performances of the proposed method. Experimental results under the intra-patient evaluation paradigm and inter-patient evaluation paradigm showed that the proposed method could achieve better classification results than other methods. Among them, the accuracy, average sensitivity, average precision, and average specificity under the intra-patient paradigm were 98.73%, 94.89%, 89.38%, and 98.24%, respectively. The accuracy, average sensitivity, average precision, and average specificity under the inter-patient paradigm were 91.22%, 89.91%, 68.23%, and 95.23%, respectively.

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Although the mechanisms of development of aggression have been focused on day by day, the complicated effects of distal and proximal factors on the development of social aggression in emerging adults have not been uncovered. A serial cascade model of aggression was proposed to address this issue. A longitudinal investigation over 2.5 years was conducted to test this model by exploring the serial cascade effects of relative deprivation (a representative of distal factors) and anger rumination (a representative of proximal factors) on the development of social aggression. A total of 1113 Chinese university students (Mage = 18.95 ± 0.96, 63.10% female) from six universities in five areas participated in this study. The results suggest that developmental trajectories and longitudinal changes in anger rumination mediate the relationship between developmental trajectories and longitudinal changes in relative deprivation and social aggression, and developmental trajectories and changes in relative deprivation mediate the longitudinal relationship between anger rumination and social aggression. These findings support the serial cascade effects of distal and proximal factors on the development of aggression and expand upon the general aggression model (GAM).

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Escherichia coli O157:H7 is one of the most susceptible foodborne pathogens, easily causing food poisoning and other health risks. It is of great significance to establish a quantitative method with higher sensitivity and less time consumption for foodborne pathogens analysis. The Raman-silent signal has a good performance for avoiding interference from the food matrix so as to achieve accurate signal differentiation. In this work, we presented a preparation-mapping all-in-one method for digital mapping analysis. We prepared a functionalized Raman-silent polymer label of Escherichia coli O157:H7, which was captured on a porous 4-mercaptophenylboric acid@Ag foam chip. To improve accuracy and widen the detection range, a digital mapping quantitative strategy was employed in data extraction and processing. By transfer mapping information into digitized statistical results, the limitation of obtaining reproducible intensity values just by randomly selected spots on the substrate can be addressed. With a wide linear range of 1.0 × 101-1.0 × 105 CFU mL-1 and a limit of detection of 4.4 CFU mL-1, this all-in-one method had good sensitivity performance. Also, this method achieved good precision and selectivity in a series of experiments and was successfully applied to the analysis of beverage samples.

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Cellular sensitivity to ferroptosis is primarily regulated by mechanisms mediating lipid hydroperoxide detoxification. We show that inositol-requiring enzyme 1 (IRE1α), an endoplasmic reticulum (ER) resident protein critical for the unfolded protein response (UPR), also determines cellular sensitivity to ferroptosis. Cancer and normal cells depleted of IRE1α gain resistance to ferroptosis, while enhanced IRE1α expression promotes sensitivity to ferroptosis. Mechanistically, IRE1α's endoribonuclease activity cleaves and down-regulates the mRNA of key glutathione biosynthesis regulators glutamate-cysteine ligase catalytic subunit (GCLC) and solute carrier family 7 member 11 (SLC7A11). This activity of IRE1α is independent of its role in regulating the UPR and is evolutionarily conserved. Genetic deficiency and pharmacological inhibition of IRE1α have similar effects in inhibiting ferroptosis and reducing renal ischemia-reperfusion injury in mice. Our findings reveal a previously unidentified role of IRE1α to regulate ferroptosis and suggests inhibition of IRE1α as a promising therapeutic strategy to mitigate ferroptosis-associated pathological conditions.

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BACKGROUND: Benign prostatic hyperplasia (BPH) is the most common disease in elderly men. There is increasing evidence that periodontitis increases the risk of BPH, but the specific mechanism remains unclear. This study aimed to explore the role and mechanism of the key periodontal pathogen Porphyromonas gingivalis (P. gingivalis) in the development of BPH. METHODS: The subgingival plaque (Sp) and prostatic fluid (Pf) of patients with BPH concurrent periodontitis were extracted and cultured for 16S rDNA sequencing. Ligature-induced periodontitis, testosterone-induced BPH and the composite models in rats were established. The P. gingivalis and its toxic factor P. gingivalis lipopolysaccharide (P.g-LPS) were injected into the ventral lobe of prostate in rats to simulate its colonization of prostate. P.g-LPS was used to construct the prostate cell infection model for mechanism exploration. RESULTS: P. gingivalis, Streptococcus oralis, Capnocytophaga ochracea and other oral pathogens were simultaneously detected in the Pf and Sp of patients with BPH concurrent periodontitis, and the average relative abundance of P. gingivalis was found to be the highest. P. gingivalis was detected in both Pf and Sp in 62.5% of patients. Simultaneous periodontitis and BPH synergistically aggravated prostate histological changes. P. gingivalis and P.g-LPS infection could induce obvious hyperplasia of the prostate epithelium and stroma (epithelial thickness was 2.97- and 3.08-fold that of control group, respectively), and increase of collagen fibrosis (3.81- and 5.02-fold that of control group, respectively). P. gingivalis infection promoted prostate cell proliferation, inhibited apoptosis, and upregulated the expression of inflammatory cytokines interleukin-6 (IL-6; 4.47-fold), interleukin-6 receptor-α (IL-6Rα; 5.74-fold) and glycoprotein 130 (gp130; 4.47-fold) in prostatic tissue. P.g-LPS could significantly inhibit cell apoptosis, promote mitosis and proliferation of cells. P.g-LPS activates the Akt pathway through IL-6/IL-6Rα/gp130 complex, which destroys the imbalance between proliferation and apoptosis of prostate cells, induces BPH. CONCLUSION: P. gingivalis was abundant in the Pf of patients with BPH concurrent periodontitis. P. gingivalis infection can promote BPH, which may affect the progression of BPH via inflammation and the Akt signaling pathway.

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Soil formation is a complex process that starts from the biological development. The ecological principles and biological function in soil are of great importance, whereas their response to anthropogenic intervention has been poorly understood. In this study, a 150-day microcosmic experiment was conducted with the addition of sludge and/or fermented wood chips (FWC) to promote the soil maturation. The results showed that, compared to the control (natural development without anthropogenic intervention), sludge, FWC, and their combination increased the availability of carbon, nitrogen, and potassium, and promoted the soil aggregation. They also enhanced the cellulase activity, microbial biomass carbon (MBC) and bacterial diversity, indicating that anthropogenic interventions promoted the maturation of sand soil. Molecular ecology network and functional analyses indicated that soil maturation was accomplished with the enhancement of ecosystem functionality and stability. Specifically, sludge promoted a transition in bacterial community function from denitrification to nitrification, facilitated the degradation of easily degradable organic matter, and enhanced the autotrophic nutritional mode. FWC facilitated the transition of bacterial function from denitrification to ammonification, promoted the degradation of recalcitrant organic matter, and simultaneously enhanced both autotrophic and heterotrophic nutritional modes. Although both sludge and FWC promoted the soil functionality, they showed distinct mechanistic actions, with sludge enhancing the physical structure, and FWC altering chemical composition. It is also worth emphasizing that sludge and FWC exhibited a synergistic effect in promoting biological development and ecosystem stability, thereby providing an effective avenue for soil maturation.

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Proactive aggression refers to deliberate and unprovoked behavior, typically motivated by personal gain or expected reward. Reward expectancy is generally recognized as a critical factor that may influence proactive aggression, but its neural mechanisms remain unknown. We conducted a task-based functional magnetic resonance imaging (fMRI) experiment to investigate the relationship between reward expectancy and proactive aggression. 37 participants (20 females, mean age = 20.8 ± 1.42, age range = 18-23 years) completed a reward-harm task. In the experiment, reward valence expectancy and reward possibility expectancy were manipulated respectively by varying amounts (low: 0.5-1.5 yuan; high: 10.5-11.5 yuan) and possibilities (low: 10%-30%; high: 70%-90%) of money that participants could obtain by choosing to aggress. Participants received fMRI scans throughout the experiment. Brain activation regions associated with reward expectancy mainly involve the middle frontal gyrus, lingual gyrus, inferior temporal gyrus, anterior cuneus, caudate nucleus, inferior frontal gyrus, cingulate gyrus, anterior central gyrus, and posterior central gyrus. Associations between brain activation and reward expectancy in the left insula, left middle frontal gyrus, left thalamus, and right middle frontal gyrus were found to be related to proactive aggression. Furthermore, the brain activation regions primarily involved in proactive aggression induced by reward expectancy were the insula, inferior frontal gyrus, inferior temporal gyrus, pallidum, and caudate nucleus. Under conditions of high reward expectancy, participants engage in more proactive aggressive behavior. Reward expectancy involves the activation of reward- and social-cognition-related brain regions, and these associations are instrumental in proactive aggressive decisions.

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BACKGROUND: Nanozymes, a new class of nanomaterials, have emerged as promising substitutes for enzymes in biosensor design due to their exceptional stability, affordability, and ready availability. While nanozymes address many limitations of natural enzymes, they still face challenges, particularly in achieving the catalytic activity levels of their natural counterparts. This indicates the need for enhancing the sensitivity of biosensors based on nanozymes. The catalytic activity of nanozyme can be significantly improved by regulating its size, morphology, and surface composition of nanomaterial. RESULTS: In this work, a kind of hollow core-shell structure was designed to enhance the catalytic activity of nanozymes. The hollow core-shell structure material consists of a nanozymes core layer, a hollow layer, and a MOF shell layer. Taking the classic peroxidase like Fe3O4 as an example, the development of a novel nanozyme@MOF, specifically p-Fe3O4@PDA@ZIF-67, is detailed, showcasing its application in enhancing the sensitivity of sensors based on Fe3O4 nanozymes. This innovative nanocomposite, featuring that MOF layer was designed to adsorb the signal molecules of the sensor to improve the utilization rate of reactive oxygen species generated by the nanozymes catalyzed reactions and the hollow layer was designed to prevent the active sites of nanozymes from being cover by the MOF layer. The manuscript emphasizes the nanocomposite's remarkable sensitivity in detecting hydrogen peroxide (H2O2), coupled with high specificity and reproducibility, even in complex environments like milk samples. SIGNIFICANCE AND NOVELTY: This work firstly proposed and proved that Fe3O4 nanozyme@MOF with hollow layer structure was designed to improve the catalytic activity of the Fe3O4 nanozyme and the sensitivity of the sensors based on Fe3O4 nanozyme. This research marks a significant advancement in nanozyme technology, demonstrating the potential of structural innovation in creating high-performance, sensitive, and stable biosensors for various applications.

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Moral identity is an important moral variable which has positive moral functions, such as contributing to prosocial behaviours, reducing antisocial behaviours, and resisting the risk factors of antisocial behaviours. However, little is known about the neural correlates of moral identity and the neural basis of the effect of moral identity on the risk factors of antisocial behaviours, including moral disengagement. In this study, we explored these issues in 142 college students by estimating the regional homogeneity (ReHo) through resting-state functional magnetic resonance imaging (fMRI). The whole-brain correlation analyses found that higher internalized moral identity was correlated with higher ReHo in the precuneus. Furthermore, the ReHo in the precuneus was negatively correlated with moral disengagement, suggesting positive moral functions of the neural mechanisms of moral identity. These findings deepen our understanding of individual differences in moral identity and provide inspiration for the education of moral identity and the intervention for moral disengagement from the perspective of the brain.

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Objective.Myocardial infarction (MI) is one of the most threatening cardiovascular diseases. This paper aims to explore a method for using an algorithm to autonomously classify MI based on the electrocardiogram (ECG).Approach.A detection method of MI that fuses continuous T-wave area (C_TWA) feature and ECG deep features is proposed. This method consists of three main parts: (1) The onset of MI is often accompanied by changes in the shape of the T-wave in the ECG, thus the area of the T-wave displayed on different heartbeats will be quite different. The adaptive sliding window method is used to detect the start and end of the T-wave, and calculate the C_TWA on the same ECG record. Additionally, the coefficient of variation of C_TWA is defined as the C_TWA feature of the ECG. (2) The multi lead fusion convolutional neural network was implemented to extract the deep features of the ECG. (3) The C_TWA feature and deep features of the ECG were fused by soft attention, and then inputted into the multi-layer perceptron to obtain the detection result.Main results.According to the inter-patient paradigm, the proposed method reached a 97.67% accuracy, 96.59% precision, and 98.96% recall on the PTB dataset, as well as reached 93.15% accuracy, 93.20% precision, and 95.14% recall on the clinical dataset.Significance.This method accurately extracts the feature of the C_TWA, and combines the deep features of the signal, thereby improving the detection accuracy and achieving favorable results on clinical datasets.

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This paper presents a novel method based on leveraging physics-informed neural networks for magnetic resonance electrical property tomography (MREPT). MREPT is a noninvasive technique that can retrieve the spatial distribution of electrical properties (EPs) of scanned tissues from measured transmit radiofrequency (RF) in magnetic resonance imaging (MRI) systems. The reconstruction of EP values in MREPT is achieved by solving a partial differential equation derived from Maxwell's equations that lacks a direct solution. Most conventional MREPT methods suffer from artifacts caused by the invalidation of the assumption applied for simplification of the problem and numerical errors caused by numerical differentiation. Existing deep learning-based (DL-based) MREPT methods comprise data-driven methods that need to collect massive datasets for training or model-driven methods that are only validated in trivial cases. Hence we proposed a model-driven method that learns mapping from a measured RF, its spatial gradient and Laplacian to EPs using fully connected networks (FCNNs). The spatial gradient of EP can be computed through the automatic differentiation of FCNNs and the chain rule. FCNNs are optimized using the residual of the central physical equation of convection-reaction MREPT as the loss function ( L) . To alleviate the ill condition of the problem, we added multiconstraints, including the similarity constraint between permittivity and conductivity and the l1 norm of spatial gradients of permittivity and conductivity, to the L . We demonstrate the proposed method with a three-dimensional realistic head model, a digital phantom simulation, and a practical phantom experiment at a 9.4T animal MRI system.

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