This study was designed to explore the potential mechanisms of electroacupuncture (EA) in treating inflammatory bowel disease‐ (IBD‐) related anxiety and mood disorders. A colitis model was induced in rats with 2, 4, 6‐trinitrohydrosulfonic acid (TNBS), followed by ST36 and SP6 targeted therapy by EA or sham EA treatment. The elevated plus maze (EPM) and open‐field test (OFT) were performed to assess the state of anxiety and depression‐like behavior. Tests were carried out by 16S rDNA amplification sequence, ¹H nuclear magnetic resonance (¹H NMR) spectroscopy, immunofluorescence staining, and enzyme‐linked immunosorbent assay (ELISA). The analyses detailed metabolic alterations and the Toll‐like receptor 4 (TLR4) signaling pathway/NOD‐like receptor protein 3 (NLRP3) inflammasome in rats’ hippocampal region. Furthermore, the activity of the hypothalamic‐pituitary adrenal (HPA) axis and gut microbiome was assessed. As a result of treatment, EA significantly improved in the behavioral tests and altered the composition of the gut microbiome through a significant increase in the density of short chain fatty acids (SCFAs) producers mainly including Ruminococcaceae, Phascolarctobacterium, and Akkermansiaceae. EA upregulated the metabolites of the hippocampus mainly containing l‐glutamine and gamma‐aminobutyric acid (GABA), as well as ZO‐1 expression. Whereas the treatment blocked the TLR4/nuclear factor‐ kappa B (NF‐κB) signaling pathways and NLRP3 inflammasomes, along with downregulating the interleukin‐ (IL‐) 1β level. The hyperactivity of the HPA axis was also diminished. In conclusion, EA at ST36 and SP6 attenuated anxiety and depression‐like behavior in colitis model rats through their effects on the gut microbiome by modulating the hippocampal inflammatory response and metabolic disorders, as well as the HPA axis. This study provides evidence for clinical application of EA to serve as an adjunctive treatment for IBD‐related anxiety and depression.

Background. Resting-state functional MRI is widely used in migraine research. However, the pathophysiology and imaging markers specific for migraine pathologies are not well understood. In this study, we combined both structural and functional images to explore the concurrence and process of migraines. Methods. Thirty-four patients with a history of migraine without aura presenting during the interictal period (MwoA-DI), 10 patients with migraine without aura presenting during the acute attack (MwoA-DA), and 32 healthy controls (HCs) were recruited in this study. All participants underwent scanning via MRI. Voxel-based morphometry (VBM) and seed-based resting-state functional connectivity (rs-FC) analysis were used to detect the brain structural and associated brain functional connectivity. Results. In VBM analysis, a decrease of gray matter volume (GMV) in the middle frontal cortex was found in MwoA patients compared with HCs. The GMV of the middle frontal cortex had a negative correction with the duration of disease. In rs-FC analysis, the left middle frontal cortex (lower, VBM result) in both the MwoA-DA and the HC groups showed significantly increased functional connectivity with the left middle frontal cortex (upper) and left superior frontal cortex compared with MwoA-DI. The left middle frontal cortex (lower) in the MwoA-DI group also showed decreased functional connectivity in the left posterior cingulate cortex (PCC) compared with the HC group. The left middle frontal cortex (lower) in the MwoA-DA group demonstrated significantly increased functional connectivity in the left cerebellum lobule VI compared with the HC group. Conclusions. Our results demonstrated that the middle frontal cortex may serve as an important target in the frequency and severity of migraines due to its role in pain regulation through the default mode network, especially in the PCC. In addition, the cerebellum may modulate the pathophysiology of migraines by serving as a communication point between the cortex and the brainstem.

Some studies have developed machine learning (ML) models for the prediction of pneumonitis following immunotherapy and radiotherapy for patients with lung cancer (LC). However, the prediction accuracy of these models remains a topic of debate. Thus, this study aims to summarize the advantages of ML methods in the early prediction of radiation pneumonitis (RP) and checkpoint inhibitor pneumonitis (CIP) in LC patients. PubMed, Cochrane, Embase, and Web of Science were searched up to March 23, 2025. The Prediction Model Risk of Bias Assessment Tool (PROBAST) was utilized to explore the risk of bias (RoB) in the included studies. A subgroup analysis was conducted based on variables including radiomics, dosiomics, and clinical characteristics. Fifty-six studies comprising 12,803 LC patients were included. Of these, 43 studies focused on the early prediction of RP, 11 studies on CIP, and 2 studies on differentiating RP and CIP. The meta-analysis revealed that the c-index of dosiomics-based models, radiomics-based models, and models based on radiomics and clinical characteristics for predicting RP was 0.82 (95% CI: 0.76–0.87), 0.80 (95% CI: 0.71–0.89), and 0.90 (95% CI: 0.86–0.94), respectively. In the prediction of CIP, the c-index for the clinical characteristics model was 0.83 (95% CI: 0.81–0.85), while the integrated radiomics and clinical characteristics model achieved a c-index of 0.86 (95% CI: 0.80–0.92). The ML-based models exhibit strong performance for predicting RP and CIP. Models that integrate dosiomics and radiomics demonstrate superior predictive performance for RP. In addition, hybrid models combining radiomics with clinical features provide excellent predictive value for CIP.

Visceral pain caused by inflammatory bowel disease (IBD) greatly diminishes the quality of life in affected patients. Yet, the mechanism of how IBD causes visceral pain is currently not fully understood. Previous studies have suggested that the central nervous system (CNS) and gut-brain axis (GBA) play an important role in IBD-inducing visceral pain. As one of the treatments for IBD, electroacupuncture (EA) has been used to treat various types of pain and gastrointestinal diseases in clinical practice. However, whether EA relieves the visceral pain of IBD through the gut-brain axis has not been confirmed. To verify the relationship between visceral pain and CNS, the following experiments were conducted. ¹H-NMR analysis was performed on the prefrontal cortex (PFC) tissue obtained from IBD rat models to determine the link between the metabolites and their role in EA treatment against visceral pain. Western blot assay was employed for detecting the contents of glutamate transporter excitatory amino acid transporters 2 (EAAT2) and the glutamate receptor N-methyl-D-aspartate (NMDA) to verify whether EA treatment can alleviate neurotoxic symptoms induced by abnormal increases of glutamate. Study results showed that the glutamate content was significantly increased in the PFC of TNBS-induced IBD rats. This change was reversed after EA treatment. This process was associated with increased EAAT2 expression and decreased expression of NMDA receptors in the PFC. In addition, an increase in intestinal glutamic-metabolizing bacteria was observed. In conclusion, this study suggests that EA treatment can relieve visceral pain by reducing glutamine toxicity in the PFC, and serves an alternative clinical utility.

Background: This study employs a longitudinal research design to investigate the impact of depression as an independent risk factor on the incidence of pain among middle-aged and elderly populations, with the objective of providing evidence for early intervention strategies to reduce pain-related disability and improve quality of life in aging populations. Methods: This study utilized baseline data from the 2011 wave of the China Health and Retirement Longitudinal Study (CHARLS). Participants aged ≥ 45 years without baseline pain were included (n = 4,966), with three follow-up assessments conducted in 2013, 2015, and 2018. Pain occurrence was defined as the first self-reported pain episode during follow-up. Depressive symptoms were assessed using the 10-item Center for Epidemiologic Studies Depression Scale (CESD-10) (score ≥ 10). Multivariable Cox regression was used to assess the impact of depression and various demographic factors on pain occurrence, and stratified analysis was conducted to further clarify the independence of depression as a risk factor. Results: Among 4,966 participants, depressive symptoms were significantly associated with higher pain incidence (HR = 1.35, 95% CI: 1.25– 1.47). Other predictors included female sex (HR = 1.55), arthritis (HR = 1.61), Activities of Daily Living/ Instrumental Activities of Daily Living (ADL/IADL) dysfunction (HR = 1.23), and chronic diseases (lung/kidney/digestive). Subgroup analyses identified a significant ADL/IADL-pain interaction (P = 0.001), with no other depression-related interactions observed. Conclusion: Depression serves as an independent predictor of pain onset among middle-aged and elderly populations in China, and this relationship is further complicated by functional decline. Early screening for depressive symptoms and functional decline may help alleviate pain-related disability in elderly populations. Future research should investigate the dynamic relationship between pain and depression across different disease subtypes and treatment contexts.