Transcription repression of estrogen receptor alpha by ghrelin/Gq/11/YAP signaling in granulosa cells promotes polycystic ovary syndrome.

Polycystic ovarian syndrome (PCOS) is a prevalent endocrinological disorder affected by ghrelin. This study aimed to investigate the molecular mechanisms underlying the effects of ghrelin on PCOS manifestations in mice and to assess the therapeutic potential of ghrelin. Female C57BL/6 mice were subcutaneously injected with 6 mg/100 g dehydroepiandrosterone (DHEA) for 20 days to induce PCOS. Alterations in reproductive cycles, ovarian morphology, serum sex hormone levels, and related signaling markers were examined. Furthermore, ghrelin-induced effects on granulosa cells and the role of ghrelin/Gq/11/ Yes-associated protein (YAP) signaling were studied by silencing Gαq/11 or YAP using si-RNAs. Finally, we evaluated the therapeutic potential of anti-ghrelin antibodies in DHEA-induced PCOS mice. DHEA administration led to significant PCOS-associated changes including weight gain, disrupted estrous cycles, ovarian morphological alterations, and hormonal imbalances in mice, with elevated Gαq/11 and acylated ghrelin expression, which was also noted in PCOS patients. However, treatment with anti-ghrelin antibodies effectively managed DHEA-induced damage in PCOS mice. In vitro, ghrelin exposure resulted in granulosa cell injury and modulated estrogen receptors alpha (ERα) and YAP protein levels, whereas silencing YAP and Gαq/11 reversed ghrelin-induced detrimental effects and up-regulated ERα expression. This study revealed that DHEA-induced PCOS traits in mice could be improved by anti-ghrelin antibodies, with the ghrelin/Gq/11/YAP signaling pathway identified as a crucial mediator in granulosa cells, affecting ERα transcription to regulate PCOS. These findings suggest a potential therapeutic strategy for the treatment of PCOS.

The distribution of the extrachromosomal DNA molecules in early lung cancer.

Lung cancer (LC) is a highly lethal cancer worldwide. Research on the distribution and nature of extrachromosomal DNA molecules (EcDNAm) in early LC is scarce. In this study, after removing linear DNA and mitochondrial circular DNA, EcDNAm were extracted from two paired LC tissue samples and amplified using rolling circle amplification. High throughput extrachromosomal DNA (EcDNA) or RNA sequencing and bioinformatics analysis were subsequently utilized to explore the distribution and nature of the EcDNAm. Additionally, to elucidate the role of oncogenes with large EcDNAm sizes, gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses were performed. The RNA sequencing results revealed significant differences in certain genes between tumors and corresponding normal samples. At the same time, slight distinctions were observed between relapsed and non-relapsed tumor samples. The nature of the EcDNAm was compared between LC samples and matched normal samples. There was a tendency for the number of EcDNAm with longer size (EcDNA) and its containing driver oncogenes to be higher in cancer samples. Enrichment analysis of the cancer samples revealed enrichment in biological processes, such as positive regulation of protein localization, axon development, and in-utero embryonic development. This study highlights the universal distribution and characteristics of EcDNAm in early LC. Moreover, our work fills the investigation of the EcDNAm gap and future studies should focus on the application of EcDNA as a potential biomarker in patients with early LC.

[Species diversity of dark septate endophytes in tundra plants of Changbai Mountains, Northeast China]. / é•¿ç™½å±±è‹”åŽŸæ¤ç‰©æ·±è‰²æœ‰éš”å† ç”ŸçœŸèŒç‰©ç§å¤šæ ·æ€§.

We isolated the dark septate endophytic (DSE) fungi from roots of typical plant species in the tundra of Changbai Mountains Nature Reserve, including Rhododendron aureum, R. conferentiatum, Vaccinium uliginosum, and Dryas octopetala, and studied their colonization. We further investigated the DSE community composition and species diversity of the four tundra plant species by using morphological characteristics combined with rDNA ITS sequence analysis. The results showed that DSE formed a typical structure of "microsclerotia" in roots of the four plant species. A total of 69 strains of DSE fungi were isolated from the root samples, belonging to 10 genera, and 12 species. They were Phialocephala fortinii, Alternaria alternata, A. tenuissima, Epicocum nigrum, Canariomyces microsporus, Colletotrichum spaethianum, C. camelliae, Leptophoria sp., Cladosporium cladosporioides, Phoma sp., Cadophora sp., and Discosia italica, respectively. The DSE fungal species diversity was rich, and all these fungal species were firstly reported as DSE fungi in the alpine tundra belt of China. Among them, Phialocephala fortinii was the common and dominant species of all tundra plants. The Simpson, Pielou, and Shannon diversity indices of DSE fungi of the four plant species of tundra differed significantly. Our results showed that tundra plants have rich diversity of DSE fungi, and they can form a good symbiotic relationship, which enhance the adaptability of tundra plants to the harsh environment.

Gated Recurrent Neural Network for Predicting the Plasmonic Colloid Composition from Spectra.

In current research on the synthesis of colloidal nanostructures, the size and morphology of nanoparticles still exhibit certain dispersion and variation from batch to batch. Characterization of size distribution and morphology distribution of nanoparticles often requires techniques such as scanning electron microscopy or transmission electron microscopy, which involve high vacuum environments, are time-consuming, and costly. Experienced researchers can roughly estimate the size and distribution of nanostructure from spectra for a given synthetic route, but the accuracy is often limited. This paper reports the potential of using neural networks to accurately predict the composition of colloidal nanostructures from spectra. We address several fundamental issues in neural network prediction of colloidal composition. We first demonstrate the prediction of the composition of a colloidal binary mixture of gold nanoparticles using a gated recurrent neural network (GRU). The evolution of prediction errors for scattering, absorption, and extinction spectra of nanostructures with sizes ranging from 5 to 120 nm are analyzed. Furthermore, we demonstrate that the neural network model operates robustly under white noise in experimental testing scenarios. Compared to fully connected neural networks, the gated recurrent unit exhibits better testing accuracy in spectral prediction. When confronted with experimental data that deviates from simulation outputs, minor adjustments to the training set can allow the predictions to align closely with the experimental spectra, paving the way for the characterization of complex colloidal compositions with artificial intelligence.

When is it necessary to perform biopsy in asymptomatic postmenopausal women with incidental finding of thickened endometrium?

OBJECTIVE: To determine the cutoff value for endometrial thickness (ET) that prompts a biopsy in asymptomatic postmenopausal women with an incidental finding of thickened endometrium, and to develop a risk prediction model. METHODS: This is a retrospective cohort analysis of the clinical records of the Hysteroscopic Center of Fu Xing Hospital, Capital Medical University, Beijing, China. We collected asymptomatic postmenopausal women who presented with an ET of ≥4 mm (double-layer) as an incidental finding. We stratified the participants into non-malignant and malignant groups based on pathology results and assessed differences between the two groups. A receiver operating characteristic curve (ROC) was used to identify the cutoff value of ET for predicting endometrial malignancy. Logistic regression models were also constructed to predict the risk of malignancy. RESULTS: A total of 581 consecutive eligible cases were included. The optimal cutoff value for ET was 8 mm, with a maximum area under the curve (AUC) of 0.755 (95 % CI: 0.645-0.865). In addition to ET, the regression model incorporated diabetes, blood flow signal, BMI, and hypertension to predict the risk of malignancy. A ROC curve constructed for the model yielded an AUC of 0.834 (95 % CI: 0.744-0.924). CONCLUSION: It is reasonable to offer hysteroscopy and visually-directed endometrial biopsy for asymptomatic postmenopausal women when ET is 8 mm or above. For those with an ET between 4 and 8 mm, further decision to perform biopsy should be determined on an individual basis, considering risk factors and blood flow signals of the endometrium.

The Antidiabetic Potential of Probiotics: A Review.

Diabetes has become one of the most prevalent global epidemics, significantly impacting both the economy and the health of individuals. Diabetes is associated with numerous complications, such as obesity; hyperglycemia; hypercholesterolemia; dyslipidemia; metabolic endotoxemia; intestinal barrier damage; insulin-secretion defects; increased oxidative stress; and low-grade, systemic, and chronic inflammation. Diabetes cannot be completely cured; therefore, current research has focused on developing various methods to control diabetes. A promising strategy is the use of probiotics for diabetes intervention. Probiotics are a class of live, non-toxic microorganisms that can colonize the human intestine and help improve the balance of intestinal microbiota. In this review, we summarize the current clinical studies on using probiotics to control diabetes in humans, along with mechanistic studies conducted in animal models. The primary mechanism by which probiotics regulate diabetes is improved intestinal barrier integrity, alleviated oxidative stress, enhanced immune response, increased short-chain fatty acid production, etc. Therefore, probiotic supplementation holds great potential for the prevention and management of diabetes.

Sargassum pallidum reduces inflammation to exert antidepressant effect by regulating intestinal microbiome and ERK1/2/P38 signaling pathway.

Immune inflammation is one of the main factors in the pathogenesis of depression. It is an effective and active way to find more safe and effective anti-inflammatory depressant drugs from plant drugs. The purpose of this study is to explore the potential of marine plant Sargassum pallidum (Turn).C.Ag. (Haihaozi, HHZ) in the prevention and treatment of depression and to explain the related mechanism. Phytochemical analysis showed that alkaloids, terpenes, and organic acids are the main constituents. In vitro and in vivo activity studies showed the anti-neuroinflammatory and antidepressant effect of Sargassum pallidum, furthermore, confirmed that 7-Hydroxycoumarin, Scoparone, and Kaurenoic Acid are important plant metabolites in Sargasum pallidum for anti-neuroinflammation. Mechanism exploration showed that inhibition of ERK1/2/p38 inflammatory signaling pathway contributing to the antidepressant effect of Sargassum pallidum in reducing intestinal inflammatory levels. This study confirmed the value of Sargassum pallidum and its rich plant metabolites in anti-inflammatory depression, providing a new choice for the follow-up research and development of antidepressant drugs.

Therapeutic inhibition of the JAK-STAT pathway in the treatment of inflammatory bowel disease.

Inflammatory bowel disease (IBD) encompasses a group of non-specific chronic intestinal inflammatory conditions of unclear etiology. The current treatment and long-term management primarily involve biologics. Nevertheless, some patients experience treatment failure or intolerance to biologics [1], making these patients a primary focus of IBD research. The Janus kinase (JAK)-Signal Transducers and Activator of Transcription (STAT) signal transduction pathway is crucial to the regulation of immune and inflammatory responses [2], and plays an important role in the pathogenesis of IBD. JAK inhibitors alleviate IBD by suppressing the transmission of JAK-STAT signaling pathway. As the first small-molecule oral inhibitor for IBD, JAK inhibitors greatly improved the treatment of IBD and have demonstrated significant efficacy, with tofacitinib and upadacitinib being approved for the treatment of ulcerative colitis (UC) [3]. JAK inhibitors can effectively alleviate intestinal inflammation in IBD patients who have failed to receive biologics, which may bring new treatment opportunities for refractory IBD patients. This review aims to elucidate the crucial roles of JAK-STAT signal transduction pathway in IBD pathogenesis, examine its role in various cell types within IBD, and explore the research progress of JAK inhibitors as therapeutic agents, paving the road for new IBD treatment strategies.

Tumor microenvironment biomarkers predicting pathological response to neoadjuvant chemoimmunotherapy in locally advanced esophageal squamous cell carcinoma: post-hoc analysis of a single center, phase 2 study.

BACKGROUND: Neoadjuvant chemoimmunotherapy has a promising effect on locally advanced esophageal squamous cell carcinoma (ESCC). However, reliable biomarkers robustly predicting therapeutic response are still lacking. METHODS: Formalin-fixed and paraffin-embedded pre-neoadjuvant chemoimmunotherapy biopsy samples from locally advanced ESCC patients were collected. Cohort 1 composed of 66 locally advanced ESCC patients from a prospective clinical trial (NCT04506138) received two cycles of camrelizumab in combination with nab-paclitaxel and carboplatin every 3 weeks. Cohort 2 included 48 patients receiving various types of immune checkpoint inhibitors with (nab-)paclitaxel and platinum-based chemotherapy as neoadjuvant therapy. Cohort 3 consisted of 27 ESCC patients receiving neoadjuvant treatment of toripalimab with chemotherapy and was used as the external validation dataset. Targeted RNA sequencing, immunohistochemistry for programmed death ligand 1 (PD-L1), and multiplex immunofluorescence (mIF) imaging were performed. RESULTS: Integration of targeted RNA sequencing, PD-L1 immunohistochemistry, and mIF revealed a significant immune-suppressive microenvironment with higher neutrophil infiltration, enriched TGF-ß, and cell cycle pathways in non-pathological complete response (non-pCR) patients. NK, activated CD4+ T cell infiltration, interferon-gamma, antigen processing and presentation, and other immune response signatures were significantly associated with pCR. Based on discovered tumor microenvironmental characteristics and their closely related genes were screened. Consequently, a seven-gene neoadjuvant chemoimmunotherapy risk prediction signature (NCIRPs) model, was constructed. In addition to cohort 1, this model alone or with PD-L1-combined positive score (CPS) demonstrated a higher prediction accuracy of pathological response than PD-L1 CPS or other routinely used immune signatures, such as IFN-γ, in cohorts 2 and 3. Neither prognostic association nor correlation with response to chemoradiotherapy was observed in The Cancer Genome Atlas Program ESCC dataset or in ESCC patients in the neoadjuvant chemoradiotherapy cohort (cohort 4). CONCLUSION: The NCIRPs model that was developed and validated using treatment-naïve endoscopic samples from the largest ESCC neoadjuvant chemoimmunotherapy dataset represents a robust and clinically meaningful approach to select a putative responder for neoadjuvant chemoimmunotherapy in locally advanced ESCC patients.

[Effect of Selinexor on Proliferation and Apoptosis of Acute Myeloid Leukemia Kasumi-1 Cells].

OBJECTIVE: To investigate the effects of selinexor, a inhibitor of nuclear export protein 1 (XPO1) on the proliferation inhibition and apoptosis of Kasumi-1 cells in acute myeloid leukemia (AML). METHODS: MTS method was used to detect the inhibitory effect of different concentrations of selinexor on the proliferation of Kasumi-1 cells at different time points. The apoptosis rate and cell cycle changes after treatment with different concentration of selinexor were detected by flow cytometry. RESULTS: Selinexor inhibited the growth of Kasumi-1 cells at different time points in a concentration-dependent manner (r 24 h=0.7592, r 48 h=0.9456, and r 72 h=0.9425). Selinexor inhibited Kasumi-1 cells growth in a time-dependent manner (r =0.9057 in 2.5 µmol/L group, r =0.9897 in 5 µmol/L group and r =0.9994 in 10 µmol/L group). Selinexor could induce apoptosis of Kasumi-1 cells in a dose-dependent manner (r =0.9732), and the apoptosis of Kasumi-1 cells was more obvious with the increase of drug concentration. The proportion of G0/G1 phase was significantly increased and the proportion of S phase was significantly decreased after the treatment of Kasumi-1 cells by selinexor. With the increase of drug concentration, the proportion of Kasumi-1 cells cycle arrest in G0/G1 phase was increased and the cell synthesis was decreased. CONCLUSION: Selinexor can promote the death of tumor cells by inhibiting Kasumi-1 cells proliferation, inducing apoptosis and blocking cell cycle.

Single-cell RNA-seq reveals heterogeneity in metastatic renal cell carcinoma and effect of anti-angiogenesis therapy in the pancreas metastatic lesion.

Metastatic clear cell renal cell carcinoma has heterogenous tumor microenvironment (TME). Among the metastatic lesions, pancreas metastasis is rare and controversy in treatment approaches. Here, extensive primary and metastatic lesion samples were included by single-cell RNA-seq to decipher the distinct metastasis TME. The hypoxic and inflammatory TME of pancreas metastasis was decoded in this study, and the activation of PAX8-myc signaling, and metabolic reprogramming were observed. The active components including endothelial cells, fibroblasts and T cells were profiled. Meanwhile, we also evaluated the effect of anti-angiogenesis treatment in the pancreas metastasis patient. The potential mechanisms of pancreatic tropism, instability of genome, and the response of immunotherapy were also discussed in this work. Taken together, our findings suggest a clue to the heterogeneity in metastasis TME and provide evidence for the treatment of pancreas metastasis in renal cell carcinoma patients.

A predictive model for prognostic risk stratification of early-stage NSCLC based on clinicopathological and miRNA panel.

OBJECTIVE: The 5-year survival rate of early-stage non-small cell lung cancer (NSCLC) is still not optimistic. We aimed to construct prognostic tools using clinicopathological (CP) and serum 8-miRNA panel to predict the risk of overall survival (OS) in early-stage NSCLC. MATERIALS AND METHODS: A total of 799 patients with early-stage NSCLC, treated between April 2008 and September 2019, were included in this study. A sub-group of patients with serum samples, 280, were analyzed for miRNA profiling. The primary endpoint of the study was OS. The CP panel for prognosis was developed using multivariate and forward stepwise selection analyses. The serum 8-miRNA panel was developed using the miRNAs that were significant for prognosis, screened using real-time quantitative PCR (qPCR) followed by differential, univariate and Cox regression analyses. The combined model was developed using CP panel and serum 8-miRNA panel. The predictive performance of the panels and the combined model was evaluated using the area under curve (AUC) values of receiver operating characteristics (ROC) curves and Kaplan-Meier survival analysis. RESULT: The prognostic panels and the combined model (comprising CP panel and serum 8-miRNA panel) was used to classify the patients into high-risk and low-risk groups. The OS rates of these two groups were significantly different (P<0.05). The two panels had higher AUC than the two guidelines, and the combined model had the highest AUC. The AUC of the combined model (AUC=0.788; 95 %CI 0.706-0.871) was better than that of the National Comprehensive Cancer Network (NCCN) guideline (AUC=0.601; 95 %CI 0.505-0.697) and Chinese Society of Clinical Oncology (CSCO) guideline (AUC=0.614; 95 %CI 0.520-0.708). CONCLUSION: The combined model based on CP panel and serum 8-miRNA panel allows better prognostic risk stratification of patients with early-stage NSCLC to predict risk of OS.

Ecological assessment of water quality in freshwater wetlands based on the effect of environmental heterogeneity on phytoplankton communities in Northeast China.

Phytoplankton community characterized by strong vitality response to environmental change in freshwater ecosystems. This study aims to evaluate the effectiveness of using phytoplankton diversity as a water quality indicator in wetlands, and find out the main environmental variables affecting the distribution of phytoplankton. From 2020 to 2021, we examined phytoplankton assemblages and water environmental variables in spring, summer, and autumn at eight sampling sites from Hulanhe Wetland, Northeast (NE) China. The results showed that Bacillariophyta was the dominant species. Phytoplankton composition and abundance differed among sampling sites in each season; the abundance in summer (613.71 × 104 ind. L-1) was higher than that in autumn and spring. The water quality assessment of the trophic state index (TSI) based on the four physicochemical indicators was compared with phytoplankton diversity indices, which indicated that the phytoplankton community was stable, and these two indices were significantly lower in summer than in spring and autumn. According to redundancy analysis (RDA), total phosphorus (TP) and nitrogen (TN) were the main environmental variables affecting the distribution of phytoplankton. Temperature and dissolved oxygen (DO) changes also played a role, and their impact on the community was discussed. This work can provide relevant scientific references on the usefulness of phytoplankton diversity structure in assessing water quality in cold regions, in which the succession can be significantly affected by nutrients and temperatures.

Unbiasedly decoding the tumor microenvironment with single-cell multiomics analysis in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy with a poor prognosis and limited therapeutic options. Research on the tumor microenvironment (TME) of PDAC has propelled the development of immunotherapeutic and targeted therapeutic strategies with a promising future. The emergence of single-cell sequencing and mass spectrometry technologies, coupled with spatial omics, has collectively revealed the heterogeneity of the TME from a multiomics perspective, outlined the development trajectories of cell lineages, and revealed important functions of previously underrated myeloid cells and tumor stroma cells. Concurrently, these findings necessitated more refined annotations of biological functions at the cell cluster or single-cell level. Precise identification of all cell clusters is urgently needed to determine whether they have been investigated adequately and to identify target cell clusters with antitumor potential, design compatible treatment strategies, and determine treatment resistance. Here, we summarize recent research on the PDAC TME at the single-cell multiomics level, with an unbiased focus on the functions and potential classification bases of every cellular component within the TME, and look forward to the prospects of integrating single-cell multiomics data and retrospectively reusing bulk sequencing data, hoping to provide new insights into the PDAC TME.

Attention-guided context asymmetric fusion networks for the liver tumor segmentation of computed tomography images.

Background: Liver tumor segmentation based on medical imaging is playing an increasingly important role in liver tumor research and individualized therapeutic decision-making. However, it remains a challenging in terms of the accuracy of automatic segmentation of liver tumors. Therefore, we aimed to develop a novel deep neural network for improving the results from the automatic segmentation of liver tumors. Methods: This paper proposes the attention-guided context asymmetric fusion network (AGCAF-Net), combining attention guidance and fusion context modules on the basis of a residual neural network for the automatic segmentation of liver tumors. According to the attention-guided context block (AGCB), the feature map is first divided into multiple small blocks, the local correlation between features is calculated, and then the global nonlocal fusion module (GNFM) is used to obtain the global information between pixels. Additionally, the context pyramid module (CPM) and asymmetric semantic fusion module (AFM) are used to obtain multiscale features and resolve the feature mismatch during feature fusion, respectively. Finally, we used the liver tumor segmentation benchmark (LiTS) dataset to verify the efficiency of our designed network. Results: Our results showed that AGCAF-Net with AFM and CPM is effective in improving the accuracy of liver tumor segmentation, with the Dice coefficient increasing from 82.5% to 84.1%. The segmentation results of liver tumors by AGCAF-Net were superior to those of several state-of-the-art U-net methods, with a Dice coefficient of 84.1%, a sensitivity of 91.7%, and an average symmetric surface distance of 3.52. Conclusions: AGCAF-Net can obtain better matched and accurate segmentation in liver tumor segmentation, thus effectively improving the accuracy of liver tumor segmentation.

Dynamic m6A mRNA methylation reveals the involvement of AcALKBH10 in ripening-related quality regulation in kiwifruit.

Kiwifruit ripening is a complex and highly coordinated process that occurs in conjunction with the formation of fruit edible quality. The significance of epigenetic changes, particularly the impact of N6-methyladenosine (m6A) RNA modification on fruit ripening and quality formation, has been largely overlooked. We monitored m6A levels and gene expression changes in kiwifruit at four different stages using LC-MS/MS, MeRIP, RNA-seq, and validated the function of AcALKBH10 through heterologous transgenic expression in tomato. Notable m6A modifications occurred predominantly at the stop codons and the 3' UTRs and exhibited a gradual reduction in m6A levels during the fruit ripening process. Moreover, these m6A modifications in the aforementioned sites demonstrated a discernible inverse relationship with the levels of mRNA abundance throughout the ripening process, suggesting a repression effect of m6A modification in the modulation of kiwifruit ripening. We further demonstrated that AcALKBH10 rather than AcECT9 predominantly regulates m6A levels in ripening-related genes, thereby exerting the regulatory control over the ripening process and the accumulation of soluble sugars and organic acids, ultimately influencing fruit ripening and quality formation. In conclusion, our findings illuminate the epi-regulatory mechanism involving m6A in kiwifruit ripening, offering a fresh perspective for cultivating high-quality kiwifruit with enhanced nutritional attributes.

Crystal structure and function analysis of 6-phosphogluconate dehydrogenase in Mycobacterium tuberculosis.

6-phosphogluconate dehydrogenase (6PGDH) is an essential enzyme in energy metabolism and redox reactions, and represents a potential drug target for the development of therapies targeting trypanosomes, plasmodium, or other pathogens. Tuberculosis, caused by Mycobacterium tuberculosis, is a contagious disease that severely affects human health, with approximately one-third of the world's population infected. However, the protein structure, exact oligomeric state, and catalytic mechanism of 6PGDH in Mycobacterium tuberculosis (Mt6PGDH) have remained largely unknown. In this study, we successfully purified and determined the structure of Mt6PGDH, revealing its function as a tetramer in both solution and crystal states. Through structural comparisons, we clarified the tetramer formation mechanism and the oligomeric organization of short-chain 6PGDHs. Additionally, we identified key residues for coenzyme recognition and catalytic activity. This work not only deepens our understanding of the enzymatic function of Mt6PGDH but also lays a foundation for the development of drugs targeting this enzyme.

Inhalation of Curcumae Rhizoma volatile oil attenuates depression-like behaviours via activating the Nrf2 pathway to alleviate oxidative stress and improve mitochondrial dysfunction.

OBJECTIVES: Curcumae Rhizoma (CR) is a traditional Chinese medicine used frequently in clinics, which contains volatile components that exhibit various active effects. This study explores the effect of Curcumae Rhizoma volatile oil (CRVO) on depressive mice and its possible mechanism of action. METHODS: Chemical composition of CRVO was analysed by GC-MS. DPPH and ABTS free radical scavenging assays were used to evaluate the in vitro antioxidant capacity of CRVO. A chronic unpredictable mild stress (CUMS) model was used to evaluate the antidepressant effect of CRVO. The effects of CRVO on oxidative stress in vivo were investigated using Nissl staining, ELISA and transmission electron microscopy. The Nrf2/HO-1/NQO1 signalling pathway was detected by western blotting and immunofluorescence. ML385, a Nrf2 inhibitor was used to validate the effect of Nrf2 on CUMS mice with CRVO treatment. KEY FINDINGS: Phytochemical analysis showed that CRVO is rich in its characteristic components, including curzerene (31.1%), curdione (30.56%), and germacrone (12.44%). In vivo, the administration of CRVO significantly ameliorated CUMS-induced depressive-like behaviours. In addition, inhalation of CRVO significantly alleviated the oxidative stress caused by CUMS and improved neuronal damage and mitochondrial dysfunction. The results of mechanistic studies showed that the mechanism of action is related to the Nrf2/HO-1/NQO1 pathway and the antioxidant and antidepressant effects of CRVO were weakened when ML385 was used. CONCLUSIONS: In summary, by regulating the Nrf2 pathway, inhalation of CRVO can reduce oxidative stress in depressed mice, thereby reducing neuronal damage and mitochondrial dysfunction to alleviate depression-like behaviours. Our study offers a prospective research foundation to meet the diversity of clinical medication.