Transcriptomic analysis unveils alterations in the genetic expression profile of tree peony (Paeonia suffruticosa Andrews) infected by Alternaria alternata.

BACKGROUND: Black spot disease in tree peony caused by the fungal necrotroph A. alternata, is a primary limiting factor in the production of the tree peony. The intricate molecular mechanisms underlying the tree peony resistance to A. alternata have not been thoroughly investigated. RESULTS: The present study utilized high-throughput RNA sequencing (RNA-seq) technology to conduct global expression profiling, revealing an intricate network of genes implicated in the interaction between tree peony and A. alternata. RNA-Seq libraries were constructed from leaf samples and high-throughput sequenced using the BGISEQ-500 sequencing platform. Six distinct libraries were characterized. M1, M2 and M3 were derived from leaves that had undergone mock inoculation, while I1, I2 and I3 originated from leaves that had been inoculated with the pathogen. A range of 10.22-11.80 gigabases (Gb) of clean bases were generated, comprising 68,131,232 - 78,633,602 clean bases and 56,677 - 68,996 Unigenes. A grand total of 99,721 Unigenes were acquired, boasting a mean length of 1,266 base pairs. All these 99,721 Unigenes were annotated in various databases, including NR (Non-Redundant, 61.99%), NT (Nucleotide, 45.50%), SwissProt (46.32%), KEGG (Kyoto Encyclopedia of Genes and Genomes, 49.33%), KOG (clusters of euKaryotic Orthologous Groups, 50.18%), Pfam (Protein family, 47.16%), and GO (Gene Ontology, 34.86%). In total, 66,641 (66.83%) Unigenes had matches in at least one database. By conducting a comparative transcriptome analysis of the mock- and A. alternata-infected sample libraries, we found differentially expressed genes (DEGs) that are related to phytohormone signalling, pathogen recognition, active oxygen generation, and circadian rhythm regulation. Furthermore, multiple different kinds of transcription factors were identified. The expression levels of 10 selected genes were validated employing qRT-PCR (quantitative real-time PCR) to confirm RNA-Seq data. CONCLUSIONS: A multitude of transcriptome sequences have been generated, thus offering a valuable genetic repository for further scholarly exploration on the immune mechanisms underlying the tree peony infected by A. alternata. While the expression of most DEGs increased, a few DEGs showed decreased expression.

Baseline gut microbiome as a predictive biomarker of response to probiotic adjuvant treatment in gout management.

Gout is characterized by dysregulation of uric acid (UA) metabolism, and the gut microbiota may serve as a regulatory target. This two-month randomized, double-blind, placebo-controlled trial aimed to investigate the additional benefits of coadministering Probio-X alongside febuxostat. A total of 160 patients with gout were randomly assigned to either the probiotic group (n = 120; Probio-X [1 ×1011 CFU/day] with febuxostat) or the placebo group (n = 40; placebo material with febuxostat). Coadministration of Probio-X significantly decreased serum UA levels and the rate of acute gout attacks (P < 0.05). Based on achieving a target sUA level (360 µmol/L) after the intervention, the probiotic group was further subdivided into probiotic-responsive (ProA; n = 54) and probiotic-unresponsive (ProB; n = 66) subgroups. Post-intervention clinical indicators, metagenomic, and metabolomic changes in the ProB and placebo groups were similar, but differed from those in the ProA group, which exhibited significantly lower levels of acute gout attack, gout impact score, serum indicators (UA, XOD, hypoxanthine, and IL-1ß), and fecal gene abundances of UA-producing pathways (KEGG orthologs of K13479 and K01487; gut metabolic modules for formate conversion and lactose and galactose degradation). Additionally, the ProA group showed significantly higher levels (P < 0.05) of gut SCFAs-producing bacteria and UA-related metabolites (xanthine, hypoxanthine, bile acids) after the intervention. Finally, we established a gout metagenomic classifier to predict probiotic responsiveness based on subjects' baseline gut microbiota composition. Our results indicate that probiotic-driven therapeutic responses are highly individual, with the probiotic-responsive cohort benefitting significantly from probiotic coadministration.

Estimation of Vehicle Dynamic Parameters Based on the Two-Stage Estimation Method.

Vehicle dynamic parameters are of vital importance to establish feasible vehicle models which are used to provide active controls and automated driving control. However, most vehicle dynamics parameters are difficult to obtain directly. In this paper, a new method, which requires only conventional sensors, is proposed to estimate vehicle dynamic parameters. The influence of vehicle dynamic parameters on vehicle dynamics often involves coupling. To solve the problem of coupling, a two-stage estimation method, consisting of multiple-models and the Unscented Kalman Filter, is proposed in this paper. During the first stage, the longitudinal vehicle dynamics model is used. Through vehicle acceleration/deceleration, this model can be used to estimate the distance between the vehicle centroid and vehicle front, the height of vehicle centroid and tire longitudinal stiffness. The estimated parameter can be used in the second stage. During the second stage, a single-track with roll dynamics vehicle model is adopted. By making vehicle continuous steering, this vehicle model can be used to estimate tire cornering stiffness, the vehicle moment of inertia around the yaw axis and the moment of inertia around the longitudinal axis. The simulation results show that the proposed method is effective and vehicle dynamic parameters can be well estimated.

A New Trajectory Tracking Algorithm for Autonomous Vehicles Based on Model Predictive Control.

Trajectory tracking is a key technology for precisely controlling autonomous vehicles. In this paper, we propose a trajectory-tracking method based on model predictive control. Instead of using the forward Euler integration method, the backward Euler integration method is used to establish the predictive model. To meet the real-time requirement, a constraint is imposed on the control law and the warm-start technique is employed. The MPC-based controller is proved to be stable. The simulation results demonstrate that, at the cost of no or a little increase in computational time, the tracking performance of the controller is much better than that of controllers using the forward Euler method. The maximum lateral errors are reduced by 69.09%, 47.89% and 78.66%. The real-time performance of the MPC controller is good. The calculation time is below 0.0203 s, which is shorter than the control period.

Danger peptide signaling enhances internalization of a geminivirus symptom determinant in plant cells during infection.

Geminiviruses are DNA viruses that cause severe diseases in diverse species of plants, resulting in considerable agricultural losses worldwide. C4 proteins are a major symptom determinant in several geminiviruses, including Beet severe curly top virus (BSCTV). Here, we uncovered a novel mechanism by which danger peptide signaling enhances the internalization of BSCTV C4 in plant cells. Previous studies showed that this signaling is important for activation of bacterium- and fungus-triggered immune responses, but its function in plant-virus interactions was previously unknown. Pep1 RECEPTOR1 (PEPR1) and PEPR2 are receptor kinases recognized by Peps (plant elicitor peptides) in the danger peptide pathway. We found that BSCTV C4 up-regulated and interacted with PEPR2 but not PEPR1. The Pep1-PEPR2 complex stimulated the internalization of C4 in both Arabidopsis and Nicotiana benthamiana cells. Furthermore, C4 induced callus formation in Arabidopsis, which was suppressed by PEPR2 overexpression but enhanced in the pepr2 mutants. In the presence of Pep1, overexpression of PEPR2 suppressed BSCTV infection in N. benthamiana. Exogenous Pep1 also reduced BSCTV infection in Arabidopsis in a PEPR2-dependent manner. Thus, PEPR2 recognizes the symptom determinant C4 and enhances its internalization mediated by danger peptides, suppressing BSCTV infection.

[In vitro culture of the testis tissue of BALB/c mice with spermatogenic dysfunction].

OBJECTIVE: To explore the pathways of development and maturation of the testis tissue in mice with spermatogenic dysfunction in vitro. METHODS: Sixty-eight 8-week-old BALB/c male mice were randomly divided into four groups of equal number, normal control, Sertoli cell only syndrome (SCOS), severe hypo-spermatogenesis (H-S1), and mild hypo-spermatogenesis (H-S2), and the models were established in the latter three groups by intraperitoneal injection of busulfan at 40 mg/kg for 4, 6 and 8 weeks, respectively. The testis tissues of the mice were cultured with the agarose gel method in vitro till the 4th week, followed by determination of the expressions of the marker proteins STRA8 at meiotic initiation, SCP3 during meiosis, and TNP1 after meiosis by immunohistochemistry. The development and maturation of the germ cells during the in vitro culture were evaluated, and their apoptosis detected by TUNEL. RESULTS: The more severe the testicular tissue injury, the lower the expression of the STRA8 protein in the SCOS, H-S1 and H-S2 groups as compared with the normal control before in vitro culture on agarose gel (P < 0.05), and the STRA8 expression was significantly upregulated in the former three groups after 4 weeks of culturing (P < 0.05). The expression of SCP3 was the lowest in the SCOS but the highest in the H-S2 group before culturing (P < 0.05), and was not as high as that in the control, though increased after 4 weeks of culturing. TNP1 was positively expressed in all the mice of the control, some individuals of the H-S1 and H-S2 groups (P< 0.05), but not in the SCOS group at 4 weeks. The apoptosis of germ cells was significantly increased in the SCOS but decreased in the H-S groups compared with that in the normal control after 4 weeks of culturing (P< 0.05). CONCLUSIONS: In vitro culture on agarose gel induces the meiosis of the testis tissue in BALB/c mice with spermatogenic dysfunction, and the effect is even better in those with mild spermatogenic dysfunction.

S-acylation of a geminivirus C4 protein is essential for regulating the CLAVATA pathway in symptom determination.

Geminiviruses, such as beet severe curly top virus (BSCTV), are a group of DNA viruses that cause severe plant diseases and agricultural losses. The C4 protein is a major symptom determinant in several geminiviruses; however, its regulatory mechanism and molecular function in plant cells remain unclear. Here, we show that BSCTV C4 is S-acylated in planta, and that this post-translational lipid modification is necessary for its membrane localization and functions, especially its regulation of shoot development of host plants. Furthermore, the S-acylated form of C4 interacts with CLAVATA 1 (CLV1), an important receptor kinase in meristem maintenance, and consequentially affects the expression of WUSCHEL, a major target of CLV1. The abnormal development of siliques in Arabidopsis thaliana infected with BSCTV is also dependent on the S-acylation of C4, implying a potential role of CLAVATA signaling in this process. Collectively, our results show that S-acylation is essential for BSCTV C4 function, including the regulation of the CLAVATA pathway, during geminivirus infection.

A two-phase procedure for non-normal quantitative trait genetic association study.

BACKGROUND: The nonparametric trend test (NPT) is well suitable for identifying the genetic variants associated with quantitative traits when the trait values do not satisfy the normal distribution assumption. If the genetic model, defined according to the mode of inheritance, is known, the NPT derived under the given genetic model is optimal. However, in practice, the genetic model is often unknown beforehand. The NPT derived from an uncorrected model might result in loss of power. When the underlying genetic model is unknown, a robust test is preferred to maintain satisfactory power. RESULTS: We propose a two-phase procedure to handle the uncertainty of the genetic model for non-normal quantitative trait genetic association study. First, a model selection procedure is employed to help choose the genetic model. Then the optimal test derived under the selected model is constructed to test for possible association. To control the type I error rate, we derive the joint distribution of the test statistics developed in the two phases and obtain the proper size. CONCLUSIONS: The proposed method is more robust than existing methods through the simulation results and application to gene DNAH9 from the Genetic Analysis Workshop 16 for associated with Anti-cyclic citrullinated peptide antibody further demonstrate its performance.

A marginal rank-based inverse normal transformation approach to comparing multiple clinical trial endpoints.

The increase in incidence of obesity and chronic diseases and their health care costs have raised the importance of quality diet on the health policy agendas. The healthy eating index is an important measure for diet quality which consists of 12 components derived from ratios of dependent variables with distributions hard to specify, measurement errors and excessive zero observations difficult to model parametrically. Hypothesis testing involving data of such nature poses challenges because the widely used multiple comparison procedures such as Hotelling's T(2) test and Bonferroni correction may suffer from substantial loss of efficiency. We propose a marginal rank-based inverse normal transformation approach to normalizing the marginal distribution of the data before employing a multivariate test procedure. Extensive simulation was conducted to demonstrate the ability of the proposed approach to adequately control the type I error rate as well as increase the power of the test, with data particularly from non-symmetric or heavy-tailed distributions. The methods are exemplified with data from a dietary intervention study for type I diabetic children. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.

Elevated Serum Inflammatory Cytokines in Lupus Nephritis Patients, in Association with Promoted hsa-miR-125a.

BACKGROUND: Systemic lupus erythematosus (SLE) is a clinically heterogeneous, human systemic autoimmune disease characterized by autoantibody formation. MicroRNAs (miRNA) have emerged as an important new class of modulators of gene expression and have been confirmed to regulate the lymphocyte tolerance and autoimmunity in SLE. METHODS: In this study, we investigated the serum miRNA profile in lupus nephritis (LN) patients with microarray technology. TaqMan-based stem-loop real-time polymerase chain reaction was used for validation. We also examined the serum cytokines and chemokines, such as IL-ß, IL-6, TNF-ß, and IP-10, and then analyzed the association of the upregulated IL-ß, IL-6, TNF-α, and IP-10 with each miRNA. RESULTS: Microarray analysis of miRNA indicated 17 upregulated miRNAs in LN patients. Such upregulation of hsa-miR-150, hsa-miR-200c, hsa-miR-181a, hsa-miR-125a, and hsa-miR-675 was also confirmed by RT-qPCR. We also recognized the significant upregulation of serum IL-ß, IL-6, TNF-α, and IP-10 in those LN patients. Moreover, the upregulated IL-ß, IL-6, and TNF-α was significantly associated with serum hsa-miR-125a. CONCLUSIONS: Our study recognized the upregulation of miRNAs such as hsa-miR-150, hsa-miR-200c, hsa-miR-181a, hsa-miR-125a, and hsa-miR-675 and the upregulation of such cytokines and chemokines as IL-ß, IL-6, TNF-α, and IP-10. The upregulated miR-125a contributed to the upregulation of inflammatory IL-ß, IL-6, and TNF-α in LN. Our findings demonstrate that miR-125a can be a novel biomarker for SLE, and help elucidate pathogenic mechanisms of lupus nephritis.

RNA-Seq derived identification of differential transcription in the chrysanthemum leaf following inoculation with Alternaria tenuissima.

BACKGROUND: A major production constraint on the important ornamental species chrysanthemum is black spot which is caused by the necrotrophic fungus Alternaria tenuissima. The molecular basis of host resistance to A. tenuissima has not been studied as yet in any detail. Here, high throughput sequencing was taken to characterize the transcriptomic response of the chrysanthemum leaf to A. tenuissima inoculation. RESULTS: The transcriptomic data was acquired using RNA-Seq technology, based on the Illumina HiSeq™ 2000 platform. Four different libraries derived from two sets of leaves harvested from either inoculated or mock-inoculated plants were characterized. Over seven million clean reads were generated from each library, each corresponding to a coverage of >350,000 nt. About 70% of the reads could be mapped to a set of chrysanthemum unigenes. Read frequency was used as a measure of transcript abundance and therefore as an identifier of differential transcription in the four libraries. The differentially transcribed genes identified were involved in photosynthesis, pathogen recognition, reactive oxygen species generation, cell wall modification and phytohormone signalling; in addition, a number of varied transcription factors were identified. A selection of 23 of the genes was transcription-profiled using quantitative RT-PCR to validate the RNA-Seq output. CONCLUSIONS: A substantial body of chrysanthemum transcriptomic sequence was generated, which led to a number of insights into the molecular basis of the host response to A. tenuissima infection. Although most of the differentially transcribed genes were up-regulated by the presence of the pathogen, those involved in photosynthesis were down-regulated.

Phylogenetic and transcription analysis of chrysanthemum WRKY transcription factors.

WRKY transcription factors are known to function in a number of plant processes. Here we have characterized 15 WRKY family genes of the important ornamental species chrysanthemum (Chrysanthemum morifolium). A total of 15 distinct sequences were isolated; initially internal fragments were amplified based on transcriptomic sequence, and then the full length cDNAs were obtained using RACE (rapid amplification of cDNA ends) PCR. The transcription of these 15 genes in response to a variety of phytohormone treatments and both biotic and abiotic stresses was characterized. Some of the genes behaved as would be predicted based on their homology with Arabidopsis thaliana WRKY genes, but others showed divergent behavior.

[Study on pharmacokinetics of geniposide in mice administrated by xingnaojing microemulsion and mPEG2000-PLA modified xingnaojing microemulsion].

An HPLC method for the determination of geniposide concentration in mouse plasma was developed and the pharmacokinetics after intranasal administration of Xingnaojing microemulsion (XNJ-M) and mPEG2000-PLA modified Xingnaojing microemulsion (XNJ-MM) were investigated. Eighty mice were treated by XNJ-M and XNJ-MM nasally. The plasma samples were collected at different times and the drug in samples was detected by HPLC. The pharmacokinetic parameters were calculated by the software of Kinetica. The pharmacokinetic parameters of geniposide of XNJ-M were C(max) (4.36 +/- 2.69) mg x L(-1), t(max) 1 min, MRT (29.73 +/- 4.54) min, AUC (53.63 +/- 14.03) mg x L(-1) x min. The pharmacokinetic parameters of geniposide of XNJ-MM were C(max) (9.75 +/- 4.14) mg x L(-1), t(max) 1 min, MRT(22.34 +/- 2.90) min, AUC (131.87 +/- 40.13) mg x L(-1) x min. Geniposide can be absorbed into blood in a higher degree after intranasal administration with XNJ-MM compared to XNJ-M, which maybe caused by its less irritating and more absorption.

Practical Probabilistic Model-Based Reinforcement Learning by Integrating Dropout Uncertainty and Trajectory Sampling.

This article addresses the prediction stability, prediction accuracy, and control capability of the current probabilistic model-based reinforcement learning (MBRL) built on neural networks. A novel approach to dropout-based probabilistic ensembles with trajectory sampling (DPETS) is proposed, where the system uncertainty is stably predicted by combining the Monte Carlo dropout (MC Dropout) and trajectory sampling in one framework. Its loss function is designed to correct the fitting error of neural networks for more accurate prediction of probabilistic models. The state propagation in its policy is extended to filter the aleatoric uncertainty for superior control capability. Evaluated by several Mujoco benchmark control tasks under additional disturbances and one practical robot arm manipulation task, DPETS outperforms related MBRL approaches in both average return and convergence velocity while achieving superior performance than well-known model-free baselines with significant sample efficiency. The open-source code of DPETS is available at https://github.com/mrjun123/DPETS.

Reprogramming Macrophage Polarization, Depleting ROS by Astaxanthin and Thioketal-Containing Polymers Delivering Rapamycin for Osteoarthritis Treatment.

Osteoarthritis (OA) is a chronic joint disease characterized by synovitis and joint cartilage destruction. The severity of OA is highly associated with the imbalance between M1 and M2 synovial macrophages. In this study, a novel strategy is designed to modulate macrophage polarization by reducing intracellular reactive oxygen species (ROS) levels and regulating mitochondrial function. A ROS-responsive polymer is synthesized to self-assemble with astaxanthin and autophagy activator rapamycin to form nanoparticles (NP@PolyRHAPM ). In vitro experiments show that NP@PolyRHAPM significantly reduced intracellular ROS levels. Furthermore, NP@PolyRHAPM restored mitochondrial membrane potential, increased glutathione (GSH) levels, and promoted intracellular autophagy, hence successfully repolarizing M1 macrophages into the M2 phenotype. This repolarization enhanced chondrocyte proliferation and vitality while inhibiting apoptosis. In vivo experiments utilizing an anterior cruciate ligament transection (ACLT)-induced OA mouse model revealed the anti-inflammatory and cartilage-protective effects of NP@PolyRHAPM , effectively mitigating OA progression. Consequently, the findings suggest that intra-articular delivery of ROS-responsive nanocarrier systems holds significant promise as a potential and effective therapeutic strategy for OA treatment.

The Critical Analysis of Membranes toward Sustainable and Efficient Vanadium Redox Flow Batteries.

Vanadium redox flow batteries (VRFB) are a promising technology for large-scale storage of electrical energy, combining safety, high capacity, ease of scalability, and prolonged durability; features which have triggered their early commercial implementation. Furthering the deployment of VRFB technologies requires addressing challenges associated to a pivotal component: the membrane. Examples include vanadium crossover, insufficient conductivity, escalated costs, and sustainability concerns related to the widespread adoption of perfluoroalkyl-based membranes, e.g., perfluorosulfonic acid (PFSA). Herein, recent advances in high-performance and sustainable membranes for VRFB, offering insights into prospective research directions to overcome these challenges, are reviewed. The analysis reveals the disparities and trade-offs between performance advances enabled by PFSA membranes and composites, and the lack of sustainability in their final applications. The potential of PFSA-free membranes and present strategies to enhance their performance are discussed. This study delves into vital membrane parameters to enhance battery performance, suggesting protocols and design strategies to achieve high-performance and sustainable VRFB membranes.

Immune Cell-Derived Exosomes in Inflammatory Disease and Inflammatory Tumor Microenvironment: A Review.

Inflammation is a common feature of many inflammatory diseases and tumors, and plays a decisive role in their development. Exosomes are extracellular vesicles unleashed by assorted types of cells, and it is widely known that exosomes of different immune cell sources play different functions. Exosome production has recently been reported for immune cells comprising macrophages, T cells, B cells, and dendritic cells (DCs). Immune cell-derived exosomes are involved in a variety of inflammatory responses.Herein, we summarize and review the role of macrophages, T cells, B cells, and dendritic cells (DC) in inflammatory diseases, with a focus on the role of immune cell-derived exosomes in osteoarthritis, rheumatoid arthritis, and the inflammatory tumor microenvironment (TME).These findings are expected to be important for developing new treatments for inflammatory diseases and ameliorating tumor-related inflammation.

Identification of 1,3,4-Thiadiazolyl-Containing Thiazolidine-2,4-dione Derivatives as Novel PTP1B Inhibitors with Antidiabetic Activity.

Forty-one 1,3,4-thiadiazolyl-containing thiazolidine-2,4-dione derivatives (MY1-41) were designed and synthesized as protein tyrosine phosphatase 1B (PTP1B) inhibitors with activity against diabetes mellitus (DM). All synthesized compounds (MY1-41) presented potential PTP1B inhibitory activities, with half-maximal inhibitory concentration (IC50) values ranging from 0.41 ± 0.05 to 4.68 ± 0.61 µM, compared with that of the positive control lithocholic acid (IC50 = 9.62 ± 0.14 µM). The most potent compound, MY17 (IC50 = 0.41 ± 0.05 µM), was a reversible, noncompetitive inhibitor of PTP1B. Circular dichroism spectroscopy and molecular docking were employed to analyze the binding interaction between MY17 and PTP1B. In HepG2 cells, MY17 treatment could alleviate palmitic acid (PA)-induced insulin resistance by upregulating the expression of phosphorylated insulin receptor substrate and protein kinase B. In vivo, oral administration of MY17 could reduce the fasting blood glucose level and improve glucose tolerance and dyslipidemia in mice suffering from DM.

Insomnia and stress: the mediating roles of frontoparietal network.

Insomnia is a widespread health problem among adults, and it impairs cognitive control and emotional regulation functions. Stress and insomnia are positively correlated, and their vicious cycle has been widely reported. In this study, we explore the neural biomarkers of insomnia from the perspective of whole-brain functional connectivity and investigate the neural mechanisms underlying the association between stress and insomnia. The current study was conducted on a cross-sectional sample (N = 430). First, we investigated the correlation between perceived stress and insomnia. Second, we applied connectome-based predictive modeling (CPM) to determine the neuromarkers of insomnia. Finally, we explored the neural basis underlying the association between perceived stress and insomnia. A significant positive correlation was found between perceived stress and insomnia in the present research. Results of CPM revealed the following as the neural substrates supporting insomnia: the emotion regulation circuit involving repetitive negative thinking and the cognitive control circuit involving attention control. According to further results from mediation analysis, the frontoparietal network supporting cognitive emotion regulation is an important neural mechanism that maintains the correlation between stress and insomnia. The present study offers a profound insight into the alterations of brain activity related to insomnia, and it further investigates the neural underpinnings of the robust association between stress and insomnia. This study also opens new avenues for neural interventions to alleviate stress-related insomnia.

Posttraumatic growth modulates the response to negative emotions related to COVID-19: An event-related potentials study.

There is increasing interest in identifying how posttraumatic growth (PTG) impacts emotional processing following traumatic events (e.g., the COVID-19 pandemic). Previous research suggests that high PTG levels may lead to enduring changes in positive emotional processing. Despite this fact, little is known regarding brain activation and responses to stressful emotional stimuli. The present study utilised event-related potentials (ERPs) to investigate whether individual differences in emotional responses toward neutral and negative emotional stimuli related to COVID-19 are related to self-reported PTG levels. A total of 77 participants were analysed: 21 in the high PTG group and 56 in the control group. The amplitude of the N2 was smaller in the high PTG group compared to the control group under both negative and neutral conditions. When viewing the negative emotion pictures (vs. neutral pictures), the N2 amplitude significantly decreased for the high PTG group in the right occipital and frontal-parietal areas, whereas no significant change was observed among the control group. In the time window Late Positive Potential (LPP) 600-1000 ms, emotional stimuli and the group interaction were significant. Viewing negative pictures (vs. neutral pictures) decreased the LPP 600-1000 ms amplitudes for the control group, mainly originating from the brain's frontal regions. However, there were no such significant differences for the PTG group. Due to the limited sample size and cultural differences, the applicability of these results to other regions or countries needs to be verified. The presented findings suggest that the impact of PTG during emotional response is reflected in both bottom-up (evidenced by the early ERP components) and top-down (evidenced by the later ERP components) processes. Individuals with high PTG may use a meditation-related emotional regulation strategy of acceptance at the basic stage and non-judgement at a later stage.