Journal of Integrative Medicine-Jim最新文献

Objective: Acute pancreatitis (AP) is a potentially life-threatening inflammatory disease with limited therapeutic options. Although honokiol has shown beneficial effects in animal models of AP, the mitochondrial mechanisms underlying these effects remain poorly understood. This study investigated whether honokiol protects against AP by activating the mitochondrial deacetylase sirtuin 3 (SIRT3) and regulating oxidative phosphorylation (OXPHOS) function.

Methods: A mouse model of caerulein-induced AP was established to assess the temporal expression of SIRT3 and the effects of its pharmacological inhibition. The efficacy of honokiol was evaluated in vivo using an AP mouse model and in vitro using 266-6 cells and primary pancreatic acinar cells. Proteomic analysis was performed to identify SIRT3-regulated mitochondrial proteins and pathways. Protein-protein docking and immunoprecipitation were used to validate the interaction and acetylation of the respiratory complex subunits.

Results: SIRT3 expression was markedly reduced in AP, while its inhibition exacerbated disease severity, confirming a protective role. Honokiol treatment restored SIRT3 expression, alleviated inflammation and mitochondrial damage, and partially rescued OXPHOS protein expression. The proteomic profiling identified three candidate OXPHOS subunits-adenosine triphosphate synthase membrane subunit K, cytochrome c1 (CYC1) and ubiquinol-cytochrome c reductase hinge protein-that were restored by honokiol treatment. The protein-protein docking analysis revealed strong binding affinity between SIRT3 and CYC1. The immunoprecipitation assay further confirmed that honokiol reduced the acetylation of CYC1, indicating that this effect is mediated by SIRT3 activity.

Conclusion: Honokiol activates SIRT3 and promotes deacetylation of the respiratory complex Ⅲ subunit CYC1, contributing to OXPHOS restoration and mitochondrial protection in AP. These findings suggest a previously unrecognized SIRT3-CYC1 signaling axis underlying honokiol's mitochondrial protective effects in AP. Please cite this article as: Miao YF, Yao JQ, Peng Y, Bai D, Fan SH, Li HY, Jin W, Lu Y. Honokiol protects against acute pancreatitis by activating SIRT3 to restore mitochondrial oxidative phosphorylation and alleviate hyperacetylation. J Integr Med. 2026; Epub ahead of print.

Objective: This study used machine learning methods to develop a model that can offer personalized acupoint prescriptions for patients based on their symptoms, enhancing both the efficiency and effectiveness of acupuncture and moxibustion therapy (AMT).

Methods: We first preprocessed textual AMT data to build an acupoint prescription database designed for machine learning applications. Then, based on data analysis, we selected the hierarchical classification model hierarchical attention-based recurrent neural network (HARNN) to determine acupoint prescriptions based on symptoms. Computational experiments were conducted using 5-fold cross-validation to evaluate the model's performance, with intersection over union (IoU) as the primary evaluation metric. Finally, to enhance model interpretability, the local interpretable model-agnostic explanation (LIME) method was applied to visualize prediction results and improve its clinical applicability.

Results: On the original dataset of 5000 samples, HARNN achieved an IoU of 0.883 in predicting acupoint prescriptions. After data augmentation, the IoU reached 0.954 in 5-fold cross-validation, and 0.932 on a test set of 1000 original samples. The use of LIME enabled intuitive visualization of the model's prediction rationale, thereby enhancing the model's reliability.

Conclusion: This study developed a hierarchical and interpretable machine learning model that predicts acupoint prescriptions based on symptoms, integrating HARNN for hierarchical classification and LIME for interpretability, which provides an effective technical approach and methodology for the intellectualization of AMT. Please cite this article as: Yang H, Wu R, Nakata M, Ge QW. A hierarchical and interpretable machine learning model for acupoint determination. J Integr Med. 2026; Epub ahead of print.

Objective: Progressive ground-glass nodules (GGNs) are associated with a risk of malignancy. Early identification and intervention are crucial for lung cancer prevention. Traditional Chinese medicine (TCM) has advantages of syndrome differentiation, holistic adjustment, and whole-process management. In this study, we built a risk assessment model based on the integration of TCM symptoms and imaging features to identify risks of GGN progression and to guide personalized TCM management and treatment.

Methods: This study enrolled 864 patients with GGNs from January 2015 to December 2023. Assessment factors included general demographic information, TCM symptoms, and imaging features. Machine learning algorithms were used to screen risk factors, regression models were used to establish GGN progression risk assessment models, and a nomogram was used to assess the risk of progression.

Results: Age, second-hand smoke exposure, acid reflux, breast or abdominal pain, chest tightness, depression, heartburn, tongue with little coating, and the diameter of the largest pulmonary nodule were significant risk factors for GGN progression. In the nomogram model, the TCM symptom of acid reflux made the highest contribution. The constructed model using these key factors was used to assess the risk of GGN progression. The receiver operating characteristic curve showed that the area under the curve (AUC) in the training set was 0.70 (95% CI [0.65, 0.75]), and the AUC in the test set was 0.74 (95% CI [0.65, 0.82]).

Conclusion: This study was the first to establish a GGN progression risk assessment model using TCM clinical symptoms and imaging features. The model can help individuals and doctors better understand the health status and take timely preventive measures. Please cite this article as: Maolan A, Yu LH, Li Y, Yan ZS, Xiang XH, Wang LF, Guo QJ, Hu JQ, Zhang GH, Ren XL, Li J, Sun TH, Yang W, Liu R, Hua BJ. A progression risk assessment model for pulmonary ground-glass nodules based on traditional Chinese medicine clinical symptoms combined with imaging. J Integr Med. 2026; Epub ahead of print.

Objective: Non-small cell lung cancer (NSCLC), a leading cause of cancer-related mortality, presents a poor prognosis due to its tendency to metastasize and its resistance to standard therapies. Montanine (MTN), a naturally occurring alkaloid, has recently shown potential as an anticancer agent. However, the specific mechanisms through which it exerts its anticancer effects are still largely unknown. This study investigates the anti-NSCLC potential of MTN by utilizing integrative network pharmacology alongside in vitro and in vivo experimental validations.

Methods: Genes targeted by MTN in NSCLC were identified and subjected to functional enrichment analysis to elucidate the most enriched signaling pathways. A protein-protein interaction network was constructed to identify the interactions of potential targets. Adrenoceptor β2 (ADRB2) expression in lung cancer was analyzed using data from The Cancer Genome Atlas and Gene Expression Omnibus datasets. The effects of MTN on NSCLC cell lines, including migration, proliferation, viability and apoptosis, were assessed in vitro. MTN-related mechanisms were investigated using quantitative reverse transcription-polymerase chain reaction and Western blotting. Furthermore, an in vivo lung cancer metastasis experiment was performed in rats using a tail vein assay.

Results: MTN at nontoxic doses significantly reduced cell migration and lung colonization in an in vivo metastasis study (P < 0.05). Network pharmacology revealed 29 targets of MTN in NSCLC, highlighting ADRB2 as a primary target linked to poor prognosis in lung cancer. In vitro studies confirmed that MTN notably upregulated ADRB2 expression and downregulated epithelial-mesenchymal transition (EMT) signaling pathways, which was further enhanced by terbutaline sulfate, an ADRB2 activator.

Conclusion: MTN is a promising therapeutic agent for NSCLC by suppressing the migration via ADRB2 and EMT mechanisms. Please cite this article as: Iksen I, Singharajkomron N, Wongtayan A, Wattanathamsan O, Choonhapan A, Wademonkolgorn S, Nguyen HM, Hoang THX, Nguyen HT, Pongrakhananon V. Unveiling the antimetastatic activity and molecular mechanism of montanine in lung cancer cells via the integration of network pharmacology approaches with in vitro and in vivo investigations. J Integr Med. 2026; Epub ahead of print.