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Recognition of various human emotions holds significant value in numerous real-world scenarios. This paper focuses on the multimodal fusion of speech and text for emotion recognition. A 39-dimensional Mel-frequency cepstral coefficient (MFCC) was used as a feature for speech emotion. A 300-dimensional word vector obtained through the Glove algorithm was used as the feature for text emotion. The bidirectional gate recurrent unit (BiGRU) method in deep learning was added for extracting deep features. Subsequently, it was combined with the multi-head self-attention (MHA) mechanism and the improved sparrow search algorithm (ISSA) to obtain the ISSA-BiGRU-MHA method for emotion recognition. It was validated on the IEMOCAP and MELD datasets. It was found that MFCC and Glove word vectors exhibited superior recognition effects as features. Comparisons with the support vector machine and convolutional neural network methods revealed that the ISSA-BiGRU-MHA method demonstrated the highest weighted accuracy and unweighted accuracy. Multimodal fusion achieved weighted accuracies of 76.52 %, 71.84 %, 66.72 %, and 62.12 % on the IEMOCAP, MELD, MOSI, and MOSEI datasets, suggesting better performance than unimodal fusion. These results affirm the reliability of the multimodal fusion recognition method, showing its practical applicability.

Abstract Background Hepatocellular carcinoma (HCC) is the most prevalent form of liver cancer, with a high mortality rate and poor prognosis. Mutated or dysregulated transcription factors (TFs) are significantly associated with carcinogenesis. The aim of this study was to develop a TF-related prognostic risk model to predict the prognosis and guide the treatment of HCC patients. Methods RNA sequencing data were obtained from the TCGA database. The ICGC and GEO databases were used as validation datasets. The consensus clustering algorithm was used to classify the molecular subtypes of TFs. Kaplan‒Meier survival analysis and receiver operating characteristic (ROC) analysis were applied to evaluate the prognostic value of the model. The immunogenic landscape differences of molecular subtypes were evaluated by the TIMER and xCell algorithms. Autodock analysis was used to predict possible binding sites of trametinib to TFs. RT‒PCR was used to verify the effect of trametinib on the expression of core TFs. Results According to the differential expression of TFs, HCC samples were divided into two clusters (C1 and C2). The survival time, signaling pathways, abundance of immune cell infiltration and responses to chemotherapy and immunotherapy were significantly different between C1 and C2. Nine TFs with potential prognostic value, including HMGB2, ESR1, HMGA1, MYBL2, TCF19, E2F1, FOXM1, CENPA and ZIC2, were identified by Cox regression analysis. HCC patients in the high-risk group had a poor prognosis compared with those in the low-risk group (p

BackgroundHepatocellular carcinoma (HCC) is the most common type of cancer and causes a significant number of cancer-related deaths worldwide. The molecular mechanisms underlying the development of HCC are complex, and the heterogeneity of HCC has led to a lack of effective prognostic indicators and drug targets for clinical treatment of HCC. Previous studies have indicated that the unfolded protein response (UPR), a fundamental pathway for maintaining endoplasmic reticulum homeostasis, is involved in the formation of malignant characteristics such as tumor cell invasiveness and treatment resistance. The aims of our study are to identify new prognostic indicators and provide drug treatment targets for HCC in clinical treatment based on UPR-related genes (URGs).MethodsGene expression profiles and clinical information were downloaded from the TCGA, ICGC and GEO databases. Consensus cluster analysis was performed to classify the molecular subtypes of URGs in HCC patients. Univariate Cox regression and machine learning LASSO algorithm were used to establish a risk prognosis model. Kaplan–Meier and ROC analyses were used to evaluate the clinical prognosis of URGs. TIMER and XCell algorithms were applied to analyze the relationships between URGs and immune cell infiltration. Real time-PCR was performed to analyze the effect of sorafenib on the expression levels of four URGs.ResultsMost URGs were upregulated in HCC samples. According to the expression pattern of URGs, HCC patients were divided into two independent clusters. Cluster 1 had a higher expression level, worse prognosis, and higher expression of immunosuppressive factors than cluster 2. Patients in cluster 1 were more prone to immune escape during immunotherapy, and were more sensitive to chemotherapeutic drugs. Four key UPR genes (ATF4, GOSR2, PDIA6 and SRPRB) were established in the prognostic model and HCC patients with high risk score had a worse clinical prognosis. Additionally, patients with high expression of four URGs are more sensitive to sorafenib. Moreover, ATF4 was upregulated, while GOSR2, PDIA6 and SRPRB were downregulated in sorafenib-treated HCC cells.ConclusionThe UPR-related prognostic signature containing four URGs exhibits high potential application value and performs well in the evaluation of effects of chemotherapy/immunotherapy and clinical prognosis.

Abstract Film dielectric capacitors have been widely used in high‐power electronic equipment. The design of microstructure and the choice of fillers play an important role in nanocomposites' energy storage density. Machine learning methods can classify and summarise the limited data and then explore the promising composite structure. In this work, a dataset has been established, which contained a large amount of data on the maximum energy storage density of nanocomposites. Though using processed visual image information to express the internal information of composite, the prediction accuracy of the prediction models built by three machine learning algorithms increase from 84.1% to 91.9%, 80.9% to 68.9%, 70.6% to 81.6%, respectively. By calculating the branch weight in the random forest prediction model, the influence degree of different descriptors on the energy storage performance of nanocomposites is analysed. A total of 10 groups of composites with different structure and filler amount were prepared in the laboratory, which were used to verify the reliability of prediction models. Finally, the effective filler's structure is explored by three prediction models and some suggestions for the interface design of filler are given.

Abstract Dielectric capacitors play an important role in advanced electronic and power systems such as portable electronic devices, hybrid electric vehicles and electronic weapon systems, and the improvement of energy storage density will have a positive effect on reducing the volume and weight of equipment. Here, a series of single‐layer dielectrics with boron nitride nanosheets (BNNSs) uniformly dispersed and multilayer dielectrics with BNNSs showing a positive gradient distribution (PGD) and inverse gradient distribution (IGD) in the poly(vinylidene fluoride‐trifluoroethylene‐chlorotrifluoroethylene) (P[VDF‐TrFE‐CTFE]) matrix were prepared by high‐speed electrospinning and hot press technology. It is found that the best performance is observed inthe lowest interlayer gradient component in both PGD and IGD composite dielectrics. However, the performance of PGD is better than that of IGD, and the 3‐5‐3 multilayer dielectric in the positive gradient structure has the best electrical performance. Its maximum energy storage density of the 3‐5‐3 composite dielectrics is 12.93 J/cm3 at the applied electric field of 380 kV/mm. The above research results show that the gradient structure design plays an important role in optimising the breakdown strength and energy storage characteristics of composite dielectrics.

Abstract Background To elucidate the influence of childhood asthma on adult height after consideration of genetic heterogeneity in height. Methods Based on the UK Biobank, we conducted a matched cohort study, including 13,602 European individuals with asthma diagnosed before 18 years old and 136,008 matched unexposed individuals without such an experience. Ascertainment of asthma was based on self-reported data (97.6%) or clinical diagnosis in healthcare registers (2.4%). We studied three height outcomes, including (1) the attained adult height (in centimeters), (2) the height deviation measured as the difference between a person’s rank of genetically determined height (based on generated polygenetic risk score) and their rank of attained adult height in the study population (deviation in % of height order after standardization), and (3) the presence of height deficit comparing genetically determined and attained height (yes or no). We applied linear mixed-effect models to assess the associations of asthma diagnosed at different ages with attained adult height and height deviation, and conditional logistic regression models to estimate the associations of asthma with the risk of height deficit. Results 40.07% (59,944/149,610) of the study participants were born before 1950, and most of them were men (57.65%). After controlling for multiple covariates, childhood asthma was associated with shorter attained adult height, irrespective of age at asthma diagnosis. However, in the analysis of height deviation (deviation in %), we observed the greatest height deviation among individuals with asthma diagnosed before 4 years of age (− 2.57 [95% CI − 4.14 to − 1.00] and − 2.80 [95% CI − 4.06 to − 1.54] for the age of ≤ 2 and 3–4 years, respectively). The magnitude of height deviation in relation to asthma declined thereafter and became null after age 6. Similarly, there was a statistically significant height deficit in relation to an asthma diagnosis at ages ≤ 2 and 3–4 (odds ratios = 1.21, 95% CI 1.04 to 1.40, and 1.15, 95% CI 1.02 to 1.29) but not thereafter. The result pattern was similar when separately analyzing asthma with or without inhaled glucocorticoid (ICS) use, despite that the estimates were consistently stronger among asthma individuals who used ICS. Conclusions Our results suggest a notable association of childhood asthma, primarily asthma diagnosed at an early age, with adult height, after consideration of genetic heterogeneity in height and use of ICS. This finding highlights the need for surveillance on the growth problems among children with asthma.

BackgroundSuicidal behaviors, including suicide deaths and attempts, are major public health concerns. However, previous suicide models required a huge amount of input features, resulting in limited applicability in clinical practice. ObjectiveWe aimed to construct applicable models (ie, with limited features) for short- and long-term suicidal behavior prediction. We further validated these models among individuals with different genetic risks of suicide. MethodsBased on the prospective cohort of UK Biobank, we included 223 (0.06%) eligible cases of suicide attempts or deaths, according to hospital inpatient or death register data within 1 year from baseline and randomly selected 4460 (1.18%) controls (1:20) without such records. We similarly identified 833 (0.22%) cases of suicidal behaviors 1 to 6 years from baseline and 16,660 (4.42%) corresponding controls. Based on 143 input features, mainly including sociodemographic, environmental, and psychosocial factors; medical history; and polygenic risk scores (PRS) for suicidality, we applied a bagged balanced light gradient-boosting machine (LightGBM) with stratified 10-fold cross-validation and grid-search to construct the full prediction models for suicide attempts or deaths within 1 year or between 1 and 6 years. The Shapley Additive Explanations (SHAP) approach was used to quantify the importance of input features, and the top 20 features with the highest SHAP values were selected to train the applicable models. The external validity of the established models was assessed among 50,310 individuals who participated in UK Biobank repeated assessments both overall and by the level of PRS for suicidality. ResultsIndividuals with suicidal behaviors were on average 56 years old, with equal sex distribution. The application of these full models in the external validation data set demonstrated good model performance, with the area under the receiver operating characteristic (AUROC) curves of 0.919 and 0.892 within 1 year and between 1 and 6 years, respectively. Importantly, the applicable models with the top 20 most important features showed comparable external-validated performance (AUROC curves of 0.901 and 0.885) as the full models, based on which we found that individuals in the top quintile of predicted risk accounted for 91.7% (n=11) and 80.7% (n=25) of all suicidality cases within 1 year and during 1 to 6 years, respectively. We further obtained comparable prediction accuracy when applying these models to subpopulations with different genetic susceptibilities to suicidality. For example, for the 1-year risk prediction, the AUROC curves were 0.907 and 0.885 for the high (>2nd tertile of PRS) and low (

Hepatocellular carcinoma (HCC) is a cancer that is sensitive to ferroptosis, and immunotherapy has emerged as a promising treatment for HCC patients. However, the prognostic potential of ferroptosis-related genes (FRGs) and the effect of ferroptosis on the tumor immune microenvironment in HCC remain largely obscure. Here, we analyzed the expression pattern of FRGs using the TCGA, ICGC and GEO databases. The expression of most FRGs was upregulated in HCC tissues compared with normal liver tissues. Three independent clusters were determined by consensus clustering analysis based on FRG expression in HCC. Cluster 3 exhibited higher expression, unfavorable prognosis, and higher histological tumor stage and grade than clusters 1 and 2. CIBERSORT analysis indicated different infiltrating levels of various immune cells among the three clusters. Moreover, most immune checkpoint genes were highly expressed in cluster 3. Univariate Cox regression and LASSO regression analyses were performed to develop a five FRG-based prognostic risk model using the TCGA and ICGC datasets. Kaplan–Meier analysis and ROC curves were performed to verify the prognostic potential of the risk model. A nomogram containing independent prognostic factors was further developed. Compared with low-risk patients, high-risk HCC patients exhibited worse overall survival (OS). In addition, this risk model was significantly correlated with the infiltrating levels of six major types of immune cells in HCC. Finally, the relationships between the five FRGs and drug sensitivity were investigated. The present study suggests that the five FRGs could elucidate the molecular mechanisms of HCC and lead to a new direction for the improvement of predictive, preventive, and personalized medicine for HCC.

ObjectiveAccumulated studies have explored gene polymorphisms and circulating levels of tumor necrosis factor (TNF)-α and insulin-like growth factor (IGF)-1 in the etiology of ischemic stroke (IS). Of the numerous etiopathological factors for IS, a single-nucleotide polymorphism (SNP) rs1800629 located in the TNF-α gene promoter region and increased levels of TNF-α were found to be associated with IS in different ethnic backgrounds. However, the published results are inconsistent and inconclusive. The primary objective of this meta-analysis was to investigate the concordance between rs1800629 polymorphism and IS. A secondary aim was to explore circulating levels of TNF-α and IGF-1 with IS in different ethnic backgrounds and different sourced specimens.MethodsIn this study, we examined whether rs1800629 genetic variant and levels of TNF-α and IGF-1 were related to the etiology of IS by performing a meta-analysis. Relevant case-control studies were retrieved by database searching and systematically selected according to established inclusion criteria.ResultsA total of 47 articles were identified that explored the relationship between the rs1800629 polymorphism and levels of TNF-α and IGF-1 with IS risk susceptibility. Statistical analyses revealed a significant association between the rs1800629 polymorphism and levels of TNF-α and IGF-1 with IS pathogenesis.ConclusionOur findings demonstrated that the TNF-α rs1800629 polymorphism, the increased levels of TNF-α, and decreased levels of IGF-1 were involved in the etiology of IS.

Heat shock factor 2 (HSF2), a transcription factor, plays significant roles in corticogenesis and spermatogenesis by regulating various target genes and signaling pathways. However, its expression, clinical significance and correlation with tumor-infiltrating immune cells across cancers have rarely been explored. In the present study, we comprehensively investigated the expression dysregulation and prognostic significance of HSF2, and the relationship with clinicopathological parameters and immune infiltration across cancers. The mRNA expression status of HSF2 was analyzed by TCGA, GTEx, and CCLE. Kaplan-Meier analysis and Cox regression were applied to explore the prognostic significance of HSF2 in different cancers. The relationship between HSF2 expression and DNA methylation, immune infiltration of different immune cells, immune checkpoints, tumor mutation burden (TMB), and microsatellite instability (MSI) were analyzed using data directly from the TCGA database. HSF2 expression was dysregulated in the human pan-cancer dataset. High expression of HSF2 was associated with poor overall survival (OS) in BRCA, KIRP, LIHC, and MESO but correlated with favorable OS in LAML, KIRC, and PAAD. The results of Cox regression and nomogram analyses revealed that HSF2 was an independent factor for KIRP, ACC, and LIHC prognosis. GO, KEGG, and GSEA results indicated that HSF2 was involved in various oncogenesis- and immunity-related signaling pathways. HSF2 expression was associated with TMB in 9 cancer types and associated with MSI in 5 cancer types, while there was a correlation between HSF2 expression and DNA methylation in 27 types of cancer. Additionally, HSF2 expression was correlated with immune cell infiltration, immune checkpoint genes, and the tumor immune microenvironment in various cancers, indicating that HSF2 could be a potential therapeutic target for immunotherapy. Our findings revealed the important roles of HSF2 across different cancer types.

Objective: Accumulated evidence has implicated that brain-derived neurotrophic factor (BDNF) gene polymorphisms play a role in the etiology of obsessive-compulsive disorder (OCD). A single nucleotide polymorphism in the coding exon of the BDNF gene at position 66, Val66Met (rs6265), is found to be associated with OCD in different populations, but results linking Val66Met with OCD have been inconsistent and inconclusive. In our study we performed a meta-analysis to further examine whether rs6265 genetic variants are involved in the etiology of OCD.Methods: By searching databases, relevant case-control studies were retrieved; using established inclusion criteria, we selected eligible studies for analysis.Results: Thirteen studies were identified that examined the association between the rs6265 polymorphism and OCD. After statistical analyses, no significant association was found between the rs6265 polymorphism and OCD (OR = 1.07, 95% CI = 1.00–1.15, P = 0.06 for genotype; OR = 1.06, 95% CI = 0.98–1.15, P = 0.15 for allele). However, in gender-specific analysis, female Val carriers might be a risk factor for OCD (OR = 1.36, 95% CI = 1.03–1.80, P = 0.03 for genotype; OR = 1.15, 95% CI = 1.01–1.32, P = 0.04 for allele).Conclusion: Our updated meta-analysis suggests that female carriers of the Val66Met BDNF polymorphism might be more suspectable to develop OCD.

Hepatocellular carcinoma (HCC) is one of the most common malignancies and ranks as the second leading cause of cancer-related mortality worldwide. Heat shock factor 2 (HSF2) is a transcription factor that plays a critical role in development, particularly corticogenesis and spermatogenesis. However, studies examining the expression and prognostic value of HSF2 and its association with tumor-infiltrating immune cells in HCC are still rare. In the present study, we found that HSF2 expression was significantly upregulated in HCC tissues compared with normal liver tissues using the TCGA, ICGC, GEO, UALCAN, HCCDB and HPA databases. High HSF2 expression was associated with shorter survival of patients with HCC. Cox regression analyses and nomogram were used to evaluate the association of HSF2 expression with the prognosis of patients with HCC. Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and gene set enrichment analysis (GSEA) revealed that HSF2 was associated with various signaling pathways, including the immune response. Notably, HSF2 expression was significantly correlated with the infiltration levels of different immune cells using the TIMER database and CIBERSORT algorithm. HSF2 expression also displayed a significant correlation with multiple immune marker sets in HCC tissues. Knockdown of HSF2 significantly inhibited the proliferation, migration, invasion and colony formation ability of HCC cells. In summary, we explored the clinical significance of HSF2 and provided a therapeutic basis for the early diagnosis, prognostic judgment, and immunotherapy of HCC.

Ambient air pollution is composed of a heterogeneous mixture of gaseous and solid particle compounds in which primary particles are emitted directly into the atmosphere, such as diesel soot, while secondary particles are created through physicochemical transformation. Particulate matter (PM), especially fine and ultrafine particles, can be inhaled and deposited in the alveolar cavities and penetrate into circulation. An association between high levels of air pollutants and human disease has been known for more than half a century and increasing evidence demonstrates a strong link between exposure on PM and the development of systemic diseases such as cardiovascular and neurological disorders. Experimental animal models have been extensively used to study the underlying mechanism caused by environmental exposure to ambient PM. Due to their availability, quality, cost, and genetically modified strains, rodent models have been widely used. Some common exposure approaches include intranasal instillation, intratracheal instillation, nose-only inhalation, whole-body inhalation, and intravenous injection have been reviewed with a brief summary of its performance, merit, limitation, and application. We hope this would provide a useful reference in advancing experimental researches about air pollution human health and disease development.

The studies on the origin of versatile oxidation pathways toward targeted pollutants in the single-atom catalysts (SACs)/peroxymonosulfate (PMS) systems were always associated with the coordination structures rather than the perspective of pollutant characteristics, and the analysis of mechanism commonality is lacking. In this work, a variety of single-atom catalysts (M-SACs, M: Fe, Co, and Cu) were fabricated via a pyrolysis process using lignin as the complexation agent and substrate precursor. Sixteen kinds of commonly detected pollutants in various references were selected, and their lnkobs values in M-SACs/PMS systems correlated well (R² = 0.832 to 0.883) with their electrophilic indexes (reflecting the electron accepting/donating ability of the pollutants) as well as the energy gap (R² = 0.801 to 0.840) between the pollutants and M-SACs/PMS complexes. Both the electron transfer process (ETP) and radical pathways can be significantly enhanced in the M-SACs/PMS systems, while radical oxidation was overwhelmed by the ETP oxidation toward the pollutants with lower electrophilic indexes. In contrast, pollutants with higher electrophilic indexes represented the weaker electron-donatingcapacity to the M-SACs/PMS complexes, which resulted in the weaker ETP oxidation accompanied with noticeable radical oxidation. In addition, the ETP oxidation in different M-SACs/PMS systems can be regulated via the energy gaps between the M-SACs/PMS complexes and pollutants. As a result, the Fenton-like activities in the M-SACs/PMS systems could be well modulated by the reaction pathways, which were determined by both electrophilic indexes of pollutants and single-atom sites. This work provided a strategy to establish PMS-based AOP systems with tunable oxidation capacities and pathways for high-efficiency organic decontamination. [ABSTRACT FROM AUTHOR]

Objective: To determine whether moxibustion had an anti-inflammatory effect on rheumatoid arthritis (RA) by regulating Annexin 1 expression and interfering with the phospholipaseA2 signaling pathway., Methods: Thirty male Sprague-Dawley rats were randomly categorized into five groups (six rats per group): blank control (CON) group, RA model (RA) group, moxibustion (MOX) group, Annexin 1 lentiviral intervention (RNAi-Anxa1) group, and Annexin 1 lentiviral intervention + moxibustion (RNAi-Anxa1 + MOX) group. The rats in the RNAi-Anxa1 and the RNAi-Anxa1 + MOX groups were injected with the lentiviral vector-mediated RNAi-Anxa1 into the rat foot pad. An experimental RA rat model was established by injecting Freund's complete adjuvant (FCA) into the RA, MOX, RNAi-Anxa1, and RNAi-Anxa1 + MOX groups. Rats in the MOX and RNAi-Anxa1 + MOX groups received moxibustion treatment. After modeling, using moxibustion "Shenshu (BL23)" and "Zusanli (ST36)", each point is 5 times, bilateral alternating, once a day, 6 times for a course of treatment, between the courses of rest for a one day. A total of three treatment courses were conducted. Both bilateral pad thicknesses were measured using Vernier calipers on experimental days 1, 7, 14, 21, and 28. The expression of cPLA2α signaling in the synovium of diseased joints was observed using Western blot. The pathology of the rat ankle synovium was observed using hematoxylin-eosin (HE) staining. Interleukin (IL)-1β, IL-10, prostaglandin E2 (PGE2), and leukotriene B4 (LTB4) were detected using enzyme-linked immunosorbent assay., Results: Moxibustion increased the levels of Annexin 1 and decreased the inflammatory response in rats with RA. After increasing the expression of Annexin 1, the phosphorylated expression of cPLA2α was inhibited, the serum levels of IL-1β, PGE2, and LTB4 decreased, and the level of IL-10 increased. In moxibustion treated RA rats after the Annexin 1 lentiviral intervention, the serum levels of IL-1β, PGE2, LTB4, and IL-10 were almost unchanged., Conclusion: Moxibustion enhanced the negative regulation of the cPLA2α signaling pathway, increased the synovial Annexin 1 expression, inhibited the cPLA2α signaling pathway, indirectly inhibited the expression of downstream inflammatory factors, and played a role in reducing inflammation.

Objective: To test the hypothesis that moxibustion may inhibit rheumatoid arthritis (RA) synovial inflammation by regulating the expression of macrophage migration inhibitory factor (MIF)/glucocorticoids (GCs)., Methods: Fifty male Sprague-Dawley rats were randomly divided into five groups ( n = 10 each): blank Control (CON) group, RA Model (RA) group, Moxibustion (MOX) group, MIF inhibitor (S,R)-3-(4-hydroxyphenyl)-4,5-dihydro-5-isoxazole acetic acid methyl ester (ISO-1) group, and Moxibustion + MIF inhibitor ISO-1 (MOX + ISO-1) group. Rats in the ISO-1 group and ISO-1 + MOX group were intraperitoneally injected with the inhibitor ISO-1. The rats in the RA group, ISO-1 group, MOX group, and ISO-1 + MOX group were injected with Freund's complete adjuvant (FCA) in the right hind footpad to establish an experimental RA rat model. In the MOX group and MOX + ISO-1 group, rats were treated with Moxa. The thickness of the footpads of the rats in each group was measured at three-time points before, after modeling and after moxibustion treatment. The contents of serum MIF, corticosterone (CORT), tumor necrosis factor-α (TNF-α) and interleukin-1β (IL-1β) were detected by enzyme-linked immunosorbent assay; and the contents of synovial MIF were detected by Western blot. Hematoxylin-eosin (HE) staining method was used to observe the pathological changes of synovial tissue under a section light microscope, and pathological scoring was performed according to the grading standard of the degree of synovial tissue disease., Results: Moxibustion was found to reduce the level of MIF and alleviate inflammation in RA rats in this study. In addition, after inhibiting the expression of MIF, the level of CORT increased, and the level of TNF-α decreased. Treating RA rats with inhibited MIF by moxibustion, the level of CORT was almost unchanged, but the level of TNF-α further decreased. The correlation analysis data suggested that MIF was positively related to the expression of TNF-α and negatively correlated with the expression of CORT., Conclusion: Reducing MIF to increase CORT and decrease TNF-α by moxibustion treatment in RA. MIF may be a factor for moxibustion to regulate the expression of CORT, but the expression of TNF-α is due to the incomplete regulation of the MIF. This study added to the body of evidence pointing to moxibustion's anti-inflammatory mechanism in the treatment of RA.