1.KDM5A/cGAS-STING–mediated microglial activation contributes to prenatal fine particulate matter induced cerebral cortical injury in offspring mice
Wenke NIE ; Li ZHOU ; Siqi WANG ; Chao SONG ; Hang YU ; Wanwei LI ; Mengxiao LUAN ; Lu SUN ; Li YU
Journal of Environmental and Occupational Medicine 2026;43(3):270-277
Background Prenatal exposure to fine particulate matter (PM2.5) is closely associated with cortical damage and neuroinflammation in offspring. The cyclic guanosine monophosphate–adenosine monophosphate synthase (cGAS)–stimulator of interferon genes (STING) signaling pathway is a key regulator of inflammation and may be subject to epigenetic regulation. Objective To investigate the role of cGAS-STING pathway activation in PM2.5-induced cortical damage in offspring mice during pregnancy and the underlying epigenetic regulatory mechanisms. Methods Open field tests were used to assess depressive-like behavior in offspring mice. Morphological analysis was conducted to evaluate cortical damage and microglial activation in offspring brains. Real-time fluorescent quantitative PCR (RT-qPCR) and Western blot (WB) were performed to detect changes in the expression of key molecules in the cGAS-STING pathway in cortical tissue. A PM2.5-induced microglial cell injury model was established in BV2 cells. Microglial activation was observed, cell viability was measured using the Cell Counting Kit-8 (CCK-8), and the expression levels of inducible nitric oxide synthase (iNOS) and key molecules in the cGAS-STING pathway were detected by RT-qPCR and WB. Bioinformatics analysis was performed to explore the epigenetic regulatory association between the STING signaling pathway and lysine-specific demethylase 5A (KDM5A). Changes in KDM5A mRNA and protein expression, as well as the protein level of histone H3 lysine 4 trimethylation (H3K4me3), were detected in an in vitro PM2.5 injury model. Using small interfering RNA (siRNA) technology, the KDM5A gene was silenced in BV2 cells exposed to PM2.5. The protein expression of H3K4me3 was detected to evaluate improvements in microglial activation, changes in inflammatory markers such as iNOS and mannose receptor (CD206), and alterations in the cGAS-STING pathway. Results Compared with the control group, the total distance of offspring mice in the PM2.5 group was significantly reduced, and both the distance traveled and the time spent in the central area of the open field were significantly decreased (P<0.01, P<0.001), indicating depressive-like behavior in the offspring mice. Compared with the control group, the offspring mice in the PM2.5 group exhibited disorganized cortical structure and significantly activated microglia (P<0.01), with significantly increased mRNA and protein levels of cGAS and STING (P<0.05, P<0.01, or P<0.001). The in vitro experiments demonstrated that the PM2.5 treatment induced BV2 cells to polarize toward the M1 phenotype, exhibiting a distinct amoeboid morphology, with upregulated expression of the pro-inflammatory factor iNOS (P<0.05, P<0.01, or P<0.001) and activation of the cGAS-STING pathway (P<0.05, P<0.01). The analysis of RNA-seq data from KDM5A knockout cells revealed significantly downregulated STING expression, suggesting that KDM5A may activate the STING signaling pathway. The in vitro experiments further confirmed that the PM2.5-treated BV2 cells exhibited significantly elevated mRNA and protein levels of KDM5A (P<0.01), while the H3K4me3 protein levels were markedly reduced (P<0.05). After silencing KDM5A in BV2 cells exposed to PM2.5, compared with the PM2.5+siNC group, the PM2.5+siKDM5A group showed no obvious microglial activation and polarized toward the M2 phenotype, with significantly decreased expression levels of iNOS, cluster of differentiation 16 (CD16), and interleukin-1β (P<0.05, P<0.01), and significantly increased expression levels of anti-inflammatory factors CD206, YM1, and interleukin-10 (P<0.01, P<0.001). Meanwhile, the expression levels of cGAS and STING were also reduced (P<0.05, P<0.01). Conclusion KDM5A activates microglia through the cGAS-STING pathway, thereby contributing to PM2.5-induced cortical damage in offspring mice during pregnancy.
2.Prediction of postoperative pulmonary complications in video-assisted thoracic surgery for lung cancer based on cardiopulmonary exercise testing and machine learning
Lei GUO ; Fusong LIU ; Zhilong OU ; Lan GUO ; Tiantian LI ; Chongfeng ZHOU ; Kun LUAN ; Xiaoman CHEN ; Yucheng WEI
Chinese Journal of Clinical Thoracic and Cardiovascular Surgery 2026;33(01):44-52
Objective To develop a predictive model for postoperative pulmonary complications (PPC) following video-assisted thoracic surgery (VATS) in lung cancer patients by integrating cardiopulmonary exercise testing (CPET) parameters and machine learning techniques. Methods A retrospective analysis was conducted on patients with early-stage non-small cell lung cancer who underwent CPET and VATS at Guangdong Provincial People’s Hospital between October 2021 and July 2023. Patients were divided into a PPC group and a non-PPC group. The least absolute shrinkage and selection operator (LASSO) regression was used to select important features associated with PPC. Six machine learning algorithms were utilized to construct prediction models, including logistic regression, support vector machine, k-nearest neighbors, random forest, gradient boosting machine, and extreme gradient boosting. The optimal model was interpreted using SHapley Additive exPlanations (SHAP). Results A total of 325 patients were included, with an average age of 60.36 years, and 55.1% were male. Significant differences were observed between the PPC and non-PPC groups in age, diabetes, coronary heart disease, surgical approach, forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), FVC% predicted, peak oxygen uptake (peak VO2), anaerobic threshold (AT), and ventilatory equivalent for carbon dioxide slope (VE/VCO2 slope) (P<0.05). In the predictive model constructed by selecting 7 key features using LASSO regression, the random forest model demonstrated the best overall performance across various metrics, with an area under the receiver operating curve of 0.930, an F1 score of 0.836, and a Brier score of 0.133 in the training set. It also exhibited good predictive ability and calibration in the test set. SHAP analysis ranked feature importance as follows: peak VO2, VE/VCO2 slope, age, FEV1, smoking history, diabetes, and surgical approach. Conclusion Integrating CPET parameters, the random forest model can effectively identify high-risk patients for PPC and has the potential for clinical application.
3.Expert consensus on the diagnosis and treatment of cemental tear.
Ye LIANG ; Hongrui LIU ; Chengjia XIE ; Yang YU ; Jinlong SHAO ; Chunxu LV ; Wenyan KANG ; Fuhua YAN ; Yaping PAN ; Faming CHEN ; Yan XU ; Zuomin WANG ; Yao SUN ; Ang LI ; Lili CHEN ; Qingxian LUAN ; Chuanjiang ZHAO ; Zhengguo CAO ; Yi LIU ; Jiang SUN ; Zhongchen SONG ; Lei ZHAO ; Li LIN ; Peihui DING ; Weilian SUN ; Jun WANG ; Jiang LIN ; Guangxun ZHU ; Qi ZHANG ; Lijun LUO ; Jiayin DENG ; Yihuai PAN ; Jin ZHAO ; Aimei SONG ; Hongmei GUO ; Jin ZHANG ; Pingping CUI ; Song GE ; Rui ZHANG ; Xiuyun REN ; Shengbin HUANG ; Xi WEI ; Lihong QIU ; Jing DENG ; Keqing PAN ; Dandan MA ; Hongyu ZHAO ; Dong CHEN ; Liangjun ZHONG ; Gang DING ; Wu CHEN ; Quanchen XU ; Xiaoyu SUN ; Lingqian DU ; Ling LI ; Yijia WANG ; Xiaoyuan LI ; Qiang CHEN ; Hui WANG ; Zheng ZHANG ; Mengmeng LIU ; Chengfei ZHANG ; Xuedong ZHOU ; Shaohua GE
International Journal of Oral Science 2025;17(1):61-61
Cemental tear is a rare and indetectable condition unless obvious clinical signs present with the involvement of surrounding periodontal and periapical tissues. Due to its clinical manifestations similar to common dental issues, such as vertical root fracture, primary endodontic diseases, and periodontal diseases, as well as the low awareness of cemental tear for clinicians, misdiagnosis often occurs. The critical principle for cemental tear treatment is to remove torn fragments, and overlooking fragments leads to futile therapy, which could deteriorate the conditions of the affected teeth. Therefore, accurate diagnosis and subsequent appropriate interventions are vital for managing cemental tear. Novel diagnostic tools, including cone-beam computed tomography (CBCT), microscopes, and enamel matrix derivatives, have improved early detection and management, enhancing tooth retention. The implementation of standardized diagnostic criteria and treatment protocols, combined with improved clinical awareness among dental professionals, serves to mitigate risks of diagnostic errors and suboptimal therapeutic interventions. This expert consensus reviewed the epidemiology, pathogenesis, potential predisposing factors, clinical manifestations, diagnosis, differential diagnosis, treatment, and prognosis of cemental tear, aiming to provide a clinical guideline and facilitate clinicians to have a better understanding of cemental tear.
Humans
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Dental Cementum/injuries*
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Consensus
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Diagnosis, Differential
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Cone-Beam Computed Tomography
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Tooth Fractures/therapy*
4.Current Progress of 5-Methylcytosine RNA Methylation in Non-Neoplastic Kidney Diseases.
Chen ZHANG ; Zi-Xia ZHAO ; Wu SI ; Jun-Jun LUAN ; Hua ZHOU
Acta Academiae Medicinae Sinicae 2025;47(1):86-94
RNA methylation is a key process in the epigenetic regulation of post-transcriptional gene expression.5-Methylcytosine(m5C)is a type of RNA methylation,commonly existing in eukaryotic mRNA and non-coding RNAs.It mainly regulates transfer RNA stability,ribosomal RNA assembly,and mRNA translation,stability,and translation.RNA methylation is dynamically reversible and regulated by methyltransferase,demethylase,and methylation recognition protein.It has been confirmed that aberrant m5C RNA methylation is involved in the pathogenesis of non-neoplastic kidney diseases.This article summarizes the current progress of m5C RNA methylation associated with non-neoplastic acute and chronic kidney diseases,aiming to provide potential targets for the diagnosis and treatment of such diseases.
Humans
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Methylation
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5-Methylcytosine/metabolism*
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Kidney Diseases/metabolism*
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Epigenesis, Genetic
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RNA Methylation
5.Deep learning-based fusion of color and spectral features from hyperspectral imaging for the origin identification of Salvia miltiorrhiza
Bai RUIBIN ; Xiong FENG ; Wang HUI ; Luan MEIQI ; Zhou JUNHUI ; Wan XIUFU ; Zhao ZIHAN ; Zhang XIAOBO ; Zhang CHU ; Yang JIAN
Science of Traditional Chinese Medicine 2025;3(3):250-258
Background:Salvia miltiorrhiza Bunge,commonly known as"Danshen"in China due to the distinctive red color of its roots,is one of the most widely used traditional Chinese medicines.It is cultivated in various regions across China,and environmental differences among these regions can affect the secondary metabolites of plants,thereby influencing the quality of S.miltiorrhiza.In recent years,increasing demand for S.miltiorrhiza has exacerbated the problem of origin fraud.Therefore,ensuring the authenticity of its geo-graphical origin is crucial for the sustainable development of the industry.Objective:The red coloration of S.miltiorrhiza is closely associated with the content of its primary active compounds,particularly tanshinones.Therefore,both its internal chemical composition and external color characteristics serve as key indicators for quality assessment.This study utilized hyperspectral imaging technology to evaluate its potential in classifying the geographical origin of S.miltiorrhiza.Methods:Spectral data reflecting the internal chemical properties of S.miltiorrhiza were integrated with color information represent-ing its external features through 3 levels of data fusion.These fused datasets were then combined with deep learning algorithms to achieve accurate origin classification.Results:The results demonstrated that the Transformer model combined with soft-voting decision-level fusion achieved the highest classification accuracy of 98.72%by integrating image color and short-wave infrared spectral data.Conclusion:This study demonstrates that integrating hyperspectral imaging spectral data with color information provides a reliable and innovative approach for verifying the authenticity and traceability of S.miltiorrhiza.
6.Deep learning-based fusion of color and spectral features from hyperspectral imaging for the origin identification of Salvia miltiorrhiza
Ruibin BAI ; Feng XIONG ; Hui WANG ; Meiqi LUAN ; Junhui ZHOU ; Xiufu WAN ; Zihan ZHAO ; Xiaobo ZHANG ; Chu ZHANG ; Jian YANG
Science of Traditional Chinese Medicine 2025;3(3):250-258
Background: Salvia miltiorrhiza Bunge, commonly known as “Danshen” in China due to the distinctive red color of its roots, is one of the most widely used traditional Chinese medicines. It is cultivated in various regions across China, and environmental differences among these regions can affect the secondary metabolites of plants, thereby influencing the quality of S. miltiorrhiza. In recent years, increasing demand for S. miltiorrhiza has exacerbated the problem of origin fraud. Therefore, ensuring the authenticity of its geographical origin is crucial for the sustainable development of the industry. Objective: The red coloration of S. miltiorrhiza is closely associated with the content of its primary active compounds, particularly tanshinones. Therefore, both its internal chemical composition and external color characteristics serve as key indicators for quality assessment. This study utilized hyperspectral imaging technology to evaluate its potential in classifying the geographical origin of S. miltiorrhiza. Methods: Spectral data reflecting the internal chemical properties of S. miltiorrhiza were integrated with color information representing its external features through 3 levels of data fusion. These fused datasets were then combined with deep learning algorithms to achieve accurate origin classification. Results: The results demonstrated that the Transformer model combined with soft-voting decision-level fusion achieved the highest classification accuracy of 98.72% by integrating image color and short-wave infrared spectral data. Conclusion: This study demonstrates that integrating hyperspectral imaging spectral data with color information provides a reliable and innovative approach for verifying the authenticity and traceability of S. miltiorrhiza.
7.TCMLCM: an intelligent question-answering model for traditional Chinese medicine lung cancer based on the KG2TRAG method
Chunfang ZHOU ; Qingyue GONG ; Wendong ZHAN ; Jinyang ZHU ; Huidan LUAN
Digital Chinese Medicine 2025;8(1):36-45
[Objective] :
To improve the accuracy and professionalism of question-answering (QA) model in traditional Chinese medicine (TCM) lung cancer by integrating large language models with structured knowledge graphs using the knowledge graph (KG) to text-enhanced retrieval-augmented generation (KG2TRAG) method.
[Methods] :
The TCM lung cancer model (TCMLCM) was constructed by fine-tuning ChatGLM2-6B on the specialized datasets Tianchi TCM, HuangDi, and ShenNong-TCM-Dataset, as well as a TCM lung cancer KG. The KG2TRAG method was applied to enhance the knowledge retrieval, which can convert KG triples into natural language text via ChatGPT-aided linearization, leveraging large language models (LLMs) for context-aware reasoning. For a comprehensive comparison, MedicalGPT, HuatuoGPT, and BenTsao were selected as the baseline models. Performance was evaluated using bilingual evaluation understudy (BLEU), recall-oriented understudy for gisting evaluation (ROUGE), accuracy, and the domain-specific TCM-LCEval metrics, with validation from TCM oncology experts assessing answer accuracy, professionalism, and usability.
[Results] :
The TCMLCM model achieved the optimal performance across all metrics, including a BLEU score of 32.15%, ROUGE-L of 59.08%, and an accuracy rate of 79.68%. Notably, in the TCM-LCEval assessment specific to the field of TCM, its performance was 3% − 12% higher than that of the baseline model. Expert evaluations highlighted superior performance in accuracy and professionalism.
[Conclusion]
TCMLCM can provide an innovative solution for TCM lung cancer QA, demonstrating the feasibility of integrating structured KGs with LLMs. This work advances intelligent TCM healthcare tools and lays a foundation for future AI-driven applications in traditional medicine.
8.Cancer therapy-related interstitial lung disease.
Chengzhi ZHOU ; Haiyi DENG ; Yilin YANG ; Fei WANG ; Xinqing LIN ; Ming LIU ; Xiaohong XIE ; Tao LUAN ; Nanshan ZHONG
Chinese Medical Journal 2025;138(3):264-277
With the increasing utilization of cancer therapy, the incidence of lung injury associated with these treatments continues to rise. The recognition of pulmonary toxicity related to cancer therapy has become increasingly critical, for which interstitial lung disease (ILD) is a common cause of mortality. Cancer therapy-related ILD (CT-ILD) can result from a variety of treatments including chemotherapy, targeted therapy, immune checkpoint inhibitors, antibody-drug conjugates, and radiotherapy. CT-ILD may progress rapidly and even be life-threatening; therefore, prompt diagnosis and timely treatment are crucial for effective management. This review aims to provide valuable information on the risk factors associated with CT-ILD; elucidate its underlying mechanisms; discuss its clinical features, imaging, and histological manifestations; and emphasize the clinical-related views of its diagnosis. In addition, this review provides an overview of grading, typing, and staging treatment strategies used for the management of CT-ILD.
Humans
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Lung Diseases, Interstitial/diagnosis*
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Neoplasms/therapy*
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Risk Factors
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Immune Checkpoint Inhibitors/adverse effects*
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Antineoplastic Agents/therapeutic use*
9.Salidroside alleviates PM2.5-induced pulmonary fibrosis through PINK1/Parkin
Ruixi ZHOU ; Wenbo WU ; Limin ZHANG ; Meina WU ; Chen LIU ; Siqi LI ; Xiaohong LI ; Mengxiao LUAN ; Qin WANG ; Li YU ; Yumei LIU ; Wanwei LI
Journal of Environmental and Occupational Medicine 2025;42(10):1240-1246
Background Existing studies have confirmed that fine particulate matter (PM2.5)is one of the important factors inducing pulmonary fibrosis. Pulmonary fibrosis is the terminal stage of a major category of lung diseases characterized by the destruction of tissue structure, and eventually leading lung ventilation and ventilation dysfunction. No effective pulmonary fibrosis treatment is available yet. Objective To investigate the protective effect of salidroside on pulmonary fibrosis induced by the exposure of PM2.5 and its molecular mechanism. Methods Seventy 7-week-old male C57BL/6 mice were randomly divided into four groups: control group (intratracheal instillation of normal saline + saline by gavage, n=25), Sal group (intratracheal instillation of normal saline + Sal 60 mg·kg−1 by gavage, n=10), PM2.5 group (intratracheal instillation of PM2.5 5 mg·kg−1 + saline by gavage, n=10), and Sal + PM2.5 group (intratracheal instillation of PM2.5 5 mg·kg−1 +Sal 60 mg·kg−1 by gavage, n=10). The mice were administered by gavage once daily, intratracheal instillation once every 3 d, and every 3 d constituted an experimental cycle. At the end of the 26-30th cycles, 3 mice in the control group and 3 mice in the PM2.5 group were randomly sacrificed, and the lung tissues were collected for Masson staining to verify whether the pulmonary fibrosis model was successfully established. After 30 cycles, the model was successfully constructed. After 1 week of continuous observation, the mice were sacrificed, and the blood and lung tissues of the mice were collected to make lung tissue sections. Assay kits were correspondingly employed to detect oxidative stress indicators such as serum malondialdehyde (MDA) and superoxide dismutase (SOD). Western blotting was used to detect the expression of fibrosis-related proteins (Collagen-III, α-SMA), mitochondrial dynamics-related proteins (MFN1, Drp1), and mitophagy-related proteins (PINK1, Parkin, and LC3). Results Compared with the control group, the weight gain rate of the PM2.5 group was slowed down (P<0.05), which was alleviated by the Sal intervention (P<0.05). The lung coefficient increased after the PM2.5 exposure (P<0.05), which was alleviated by Sal intervention. Compared with the control group, the PM2.5 group showed severe alveolar structure damage, inflammatory cell infiltration, and blue collagen deposition, and significantly increased the lung injury score, collagen volume fraction (CVF), Szapiel score, and Ashcroft score (P<0.05), as well as serum oxidative stress levels (P<0.05). The protein expression levels of Collagen-III, α-SMA, Drp1, PINK1, Parkin, and LC3 II/I were increased (P<0.05), and the expression of MFN1 was decreased (P<0.05). Compared with the PM2.5 group, the Sal intervention alleviated lung injury, reduced inflammatory cell infiltration and collagen deposition, showing decreased lung injury score, CVF, Szapiel score, and Ashcroft score (P<0.05), and decreased serum oxidative stress levels (P<0.05); the protein expression levels of Collagen-III, α-SMA, PINK1, Parkin, and LC3 II/I were decreased (P<0.05), the expression level of Drp1 was decreased, and the expression level of MFN1 was increased. Conclusion In the process of pulmonary fibrosis induced by PM2.5 exposure in mice, Sal may affect mitochondrial autophagy through PINK1/Parkin pathway and play a protective role. The specific mechanism needs to be further verified.
10.Effects of human oligodendrocyte precursor cell transplantation on cere-bral white matter in mice with vascular dementia
Jie ZHOU ; Weipeng LIU ; Hui YANG ; Zhaoyan WANG ; Qian WANG ; Zuo LUAN ; Suqing QU
Chinese Journal of Pathophysiology 2025;41(5):843-850
AIM:We investigated the survival,migration and differentiation abilities of human oligodendro-cyte precursor cells(hOPC)in the brains of mice with vascular dementia(VaD),the effects of hOPC on cerebral white matter,and the underlying mechanisms.METHODS:Mouse VaD model was constructed using the bilateral common ca-rotid artery stenosis method,and the mice were randomly divided into sham,VaD and hOPC groups.Eight weeks after model establishment,the mice in VaD and hOPC groups received equal volume of vehicle(PBS)and hOPC solution,re-spectively,through the corpus callosum.Survival,migration and differentiation of hOPC in the brain were observed by im-munofluorescence staining at 4 and 12 weeks after transplantation.Twelve weeks after transplantation,the effects of hOPC on mouse brain white matter were detected by immunofluorescence staining of myelin basic protein(MBP),myelin-associ-ated glycoprotein(MAG),neurofilament protein 200(NF200)and non-phosphorylated neurofilament H(using monoclo-nal antibody SMI32),and by water maze experiments.Paracrine signaling by hOPC was explored using immunofluores-cence staining for vascular endothelial growth factor(VEGF).RESULTS:The hOPC survived in the brains of VaD mice for 12 weeks,migrated to damaged white matter areas,and partially differentiated into mature oligodendrocytes(approxi-mately 64%).Twelve weeks after transplantation,hOPC significantly increased the fluorescence intensity of MBP,MAG,and NF200(P<0.05 or P<0.01)and decreased the fluorescence intensity of SMI32(P<0.01).The VEGF expression in hOPC-treated mice was significantly higher than that in sham and VaD groups(P<0.01).The difference in water maze test performance between hOPC and sham groups was not statistically significant(P>0.05).The mice in hOPC group had a shorter latency than those in VaD group(P<0.05 or P<0.01),and performed more platform crossings than those in VaD group(P<0.05).CONCLUSION:The hOPC can survive,migrate and differentiate in the brains of VaD mice,attenuate cerebral white matter lesions,and improve cognitive function.These improvements may be attributed to cell replacement and paracrine effects.

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