1.Explainable Machine Learning Model for Predicting Prognosis in Patients with Malignant Tumors Complicated by Acute Respiratory Failure: Based on the eICU Collaborative Research Database in the United States
Zihan NAN ; Linan HAN ; Suwei LI ; Ziyi ZHU ; Qinqin ZHU ; Yan DUAN ; Xiaoting WANG ; Lixia LIU
Medical Journal of Peking Union Medical College Hospital 2026;17(1):98-108
To develop and validate a model for predicting intensive care unit (ICU) mortality risk in patients with malignant tumors complicated by acute respiratory failure (ARF) based on an explainable machine learning framework. Clinical data of patients with malignant tumors and ARF were extracted from the eICU Collaborative Research Database in the United States, including demographic characteristics, comorbidities, vital signs, laboratory test indicators, and major interventions within the first 24 hours after ICU admission.The study outcome was ICU death.Enrolled patients were randomly divided into a training set and a validation set at a ratio of 7:3.Predictor variables were selected using least absolute shrinkage and selection operator (LASSO) regression.Five machine learning algorithms-extreme gradient boosting (XGBoost), support vector machine (SVM), Logistic regression, multilayer perceptron (MLP), and C5.0 Decision Tree-were employed to construct predictive models.Model performance was evaluated based on the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and other metrics.The optimal model was further interpreted using the Shapley additive explanations (SHAP) algorithm. A total of 3196 patients with malignant tumors complicated by ARF were included.The training set comprised 2, 261 patients and the validation set 935 patients; 683 patients died during ICU stay, while 2513 survived.LASSO regression ultimately selected 12 variables closely associated with patient ICU outcomes, including sepsis comorbidity, use of vasoactive drugs, and within the first 24 hours after ICU admission: minimum mean arterial pressure, maximum heart rate, maximum respiratory rate, minimum oxygen saturation, minimum serum bicarbonate, minimum blood urea nitrogen, maximum white blood cell count, maximum mean corpuscular volume, maximum serum potassium, and maximum blood glucose.After model evaluation, the XGBoost model demonstrated the best performance.The AUCs for predicting ICU mortality risk in the training and validation sets were 0.940 and 0.763, respectively; accuracy was 88.3% and 81.2%;sensitivity was 98.5% and 95.9%.Its predictive performance also remained optimal in sensitivity analyses.SHAP analysis indicated that the top five variables contributing to the model's predictions were minimum oxygen saturation, minimum serum bicarbonate, minimum mean arterial pressure, use of vasoactive drugs, and maximum white blood cell count. This study successfully developed a mortality risk prediction model for ICU patients with malignant tumors complicated by ARF based on a large-scale dataset and performed explainability analysis.The model aids clinicians in early identification of high-risk patients and implementing individualized interventions.
2.Effects of oral non-peptidic thrombopoietin receptor agonists on hepatic enzyme in adult patients with immune thrombocytopenia:a meta-analysis
Tiantian LU ; Nan SHEN ; Suyue ZHU ; Jingjing YAN
China Pharmacy 2026;37(4):510-515
OBJECTIVE To systematically evaluate the effects of oral non-peptidic thrombopoietin receptor agonists (TPO-RAs) on hepatic enzyme in adult patients with immune thrombocytopenia. METHODS A comprehensive literature search was conducted in PubMed, Web of Science, CNKI, Wanfang database and the Chinese Medical Association Journal Full-Text Database to collect randomized controlled trials (RCTs) comparing oral non-peptidic TPO-RAs (intervention group) with placebo or conventional therapy (control group). All databases were searched from their inception to June 2025. After literature screening, data extraction and quality assessment of the included studies, meta-analysis was conducted using RevMan 5.4.1 software. RESULTS Twelve RCTs comprising 1 388 patients were included, with 971 in the intervention group and 417 in the control group. Meta-analysis results showed that there were no significant differences between the two groups in terms of the incidence of hepatic enzyme elevation[OR=1.24, 95%CI (0.77, 1.99), P =0.37 ] , the incidence of hepatic enzyme elevation in patients treated for ≥6 weeks[OR=1.21, 95%CI (0.73, 1.99), P =0.46 ] , and the incidence of severe hepatic enzyme elevation[OR=1.39, 95%CI(0.46, 4.20), P =0.55 ] . Subgroup analysis showed that there were no significant differences in the incidence of hepatic enzyme elevation between the intervention group and control group among patients using eltrombopag[OR=1.57,95%CI(0.85,2.87), P =0.15 ] , avatrombopag[OR=0.88,95%CI (0.09,8.46), P =0.91 ] , and hetrombopag[OR=1.04,95%CI(0.30,3.65), P =0.95 ] , respectively. CONCLUSIONS Oral non-peptidic TPO-RAs do not significantly increase the risk of hepatic enzyme elevation in adult patients with immune thrombocytopenia, and show an overall favorable hepatic safety profile.
3.Application advances, ethical dilemmas, and future directions of large language models in lung cancer diagnosis and treatment
Zhizhen REN ; Yufan XI ; Xu ZHU ; Yijie LUO ; Geting HUANG ; Junqiao SONG ; Xiuyuan XU ; Nan CHEN ; Qiang PU
Chinese Journal of Clinical Thoracic and Cardiovascular Surgery 2026;33(03):353-362
Lung cancer is a leading cause of cancer-related morbidity and mortality worldwide. Coupled with the substantial workload, the clinical management of lung cancer is challenged by the critical need to efficiently and accurately process increasingly complex medical information. In recent years, large language models (LLMs) technology has undergone explosive development, demonstrating unique advantages in handling complex medical data by leveraging its powerful natural language processing capabilities, and its application value in the field of lung cancer diagnosis and treatment is continuously increasing. The paper systematically analyzes that the exceptional potential of LLMs in lung cancer auxiliary diagnosis, tumor feature extraction, automatic staging, progression/outcome analysis, treatment recommendations, medical documentation generation, and patient education. However, they face critical technical and ethical challenges including inconsistent performance in complex integrated decision-making (e.g., TNM staging, personalized treatment suggestions) and "black box" opacity issues, along with dilemmas such as training data biases, model hallucinations, data privacy concerns, and cross-lingual adaptation challenges ("data colonization"). Future directions should prioritize constructing high-quality multimodal corpora specific to lung cancer, developing interpretable and compliant specialized models, and achieving seamless integration with existing clinical workflows. Through dual drivers of technological innovation and ethical standardization, LLMs should be prudently advanced for holistic lung cancer management processes, ultimately promoting efficient, standardized, and personalized diagnosis and treatment practices.
4.Effect and Mechanism of Liangyi Paste on Hepatic Lipid Deposition in Naturally Aged Mice with High-fat Diet via Cuproptosis/Oxidative Stress Pathway
Meiling ZHANG ; Yuanguang DONG ; Xiaofei SUN ; Jiaxin WANG ; Yu LIU ; Jingxuan ZHU ; Qun WANG ; Nan SONG ; Guoyuan SUI ; Lianqun JIA
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(9):91-99
ObjectiveTaking the cuproptosis/oxidative stress pathway as the entry point, this study investigated the effect and mechanism of Liangyi Paste on hepatic lipid deposition in naturally aged mice fed with a high-fat diet. MethodsAfter adaptive feeding, 80 ten-week-old male C57BL/6 mice were used. Thirty of them were randomly divided into three groups (10 mice per group): The 12-month-old control group (12MCON), the 15-month-old control group (15MCON), and the 15-month-old group with a high-fat diet (15MHFD). The 12MCON and 15MCON groups were continuously fed a standard diet, while the 15MHFD group started receiving a high-fat diet at 12 months of age. Tissue samples were collected at the corresponding time points for each group. The remaining 50 mice were randomly divided into five groups (10 mice per group): the 20-month-old control group (20MCON), the model group, and the low-, medium-, and high-dose Liangyi Paste groups (2.91 , 5.82 , 11.64 g·kg-1·d-1, respectively). The 20MCON group was continuously fed a standard diet, while the other groups started receiving a high-fat diet at 15 months of age. At 18 months of age, the Liangyi Paste groups were administered the corresponding doses of Liangyi Paste by gavage, while the 20MCON and model groups were given an equal volume of saline by gavage. After 8 weeks of continuous gavage (when the mice reached 20 months of age), tissue samples were collected. Hepatic TG levels were measured using assay kits; liver histology and lipid deposition were observed via hematoxylin-eosin (HE) and oil red O staining; reactive oxygen species (ROS) were detected by enzyme-linked immunosorbent assay (ELISA); Cu2+, superoxide dismutase (SOD), and malondialdehyde (MDA) levels were measured by colorimetry; mRNA and protein expression of genes related to cuproptosis and oxidative stress pathways were analyzed by Real-time polymerase chain reaction(Real-time PCR) and Wes automated protein expression system. ResultsCompared with 12MCON, the 15MCON group showed significantly increased hepatic TG, Cu2+, ROS, and MDA levels (P<0.01), decreased SOD (P<0.01), hepatocyte swelling, and disordered arrangement. The mRNA and protein levels of ferredoxin 1 (FDX1), dihydrolipoamide S-acetyltransferase (DLAT), heat shock protein 70 (HSP70), dihydrolipoamide dehydrogenase (DLD), pyruvate dehydrogenase E1 subunit-β (PDHB), nuclear factor erythroid 2-related factor 2 (Nrf2), and peroxisome proliferator-activated receptor γ (PPARγ) were significantly elevated (P<0.05, P<0.01). Compared with 15MCON group, the 15MHFD and 20MCON groups exhibited further increases in TG, Cu2+, ROS, and MDA (P<0.01), reduced SOD (P<0.01), and aggravated hepatocyte swelling and disorder. There were increased lipid droplets with mild vacuolization in the 15MHFD group, and no significant lipid deposition was observed in the 20MCON group. FDX1, DLAT, HSP70, DLD, PDHB, Nrf2, and PPARγ mRNA and protein levels were significantly increased (P<0.05, P<0.01). Compared with 20MCON group, the model group demonstrated markedly elevated TG, Cu2+, ROS, and MDA (P<0.01), reduced SOD (P<0.01), severe hepatic steatosis, and upregulated expression of FDX1, DLAT, HSP70, DLD, PDHB, Nrf2, and PPARγ mRNA and proteins (P<0.05, P<0.01). All abnormalities were significantly reversed after Liangyi Paste treatment. ConclusionLiangyi paste can ameliorate hepatic lipid deposition in naturally aged mice with a high-fat diet by modulating the cuproptosis/oxidative stress pathway.
5.Modified Ditan Tang Regulates Biorhythm-related Genes in Rat Model of Non-alcoholic Fatty Liver Disease
Zhiwen PANG ; Yu LIU ; Nan SONG ; Jie WANG ; Jingxuan ZHU ; Zhen HUA ; Yupeng PEI ; Qun WANG
Chinese Journal of Experimental Traditional Medical Formulae 2025;31(6):115-124
ObjectiveTo investigate the effects of modified Ditan tang on genes related to the transcription-translation feedback loop (TTFL) of biorhythm in the rat model of non-alcoholic fatty liver disease (NAFLD) and its mechanism for prevention and treatment of NAFLD. MethodsSixty-five healthy SPF male SD rats were randomly assigned into blank (n=20), model (n=15), and low-, medium-, and high-dose (2.68, 5.36, and 10.72 g·kg-1·d-1, respectively) modified Ditan tang (n=10) groups. Other groups except the blank group were fed a high-fat diet for 12 weeks. The modified Ditan tang groups were treated with the decoction at corresponding doses by gavage, and the blank and model groups were treated with an equal volume of normal saline from the 9th week for 4 weeks. The levels of triglyceride (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), aspartate aminotransferase (AST), and alanine aminotransferase (ALT) in the serum were measured by an automatic biochemical analyzer. TG and non-esterified fatty acid (NEFA) assay kits were used to measure the levels of TG and NEFA in the liver. The pathological changes in the hypothalamus and liver were observed by hematoxylin-eosin staining, and the lipid deposition in the liver was observed by oil red O staining. The levels of brain-muscle ARNT-like protein 1 (BMAL1/ARNTL) in the hypothalamus and liver were determined by immunohistochemical staining. The mRNA and protein levels of BMAL1, circadian locomotor output cycles kaput (CLOCK), period circadian clock 2 (PER2), and cryptochrome1 (Cry1) in the hypothalamus and liver were determined by Real-time PCR and Western blot, respectively. ResultsCompared with the blank group, the model group showed elevated levels of TG, TC, LDL-C, AST, and ALT (P<0.01) and a lowered level of HDL-C (P<0.05) in the serum, elevated levels of TG and NEFA in the liver (P<0.01), pyknosis and deep staining of hypothalamic neuron cells, and a large number of vacuoles in the brain area. In addition, the model group showed lipid deposition in the liver, up-regulated mRNA and protein levels of CLOCK and BMAL1 (P<0.01), and down-regulated mRNA and protein levels of Cry1 and PER2 (P<0.01) in the hypothalamus and liver. Compared with the model group, all the three modified Ditan tang groups showed lowered levels of TG, TC, LDL-C, ALT, and AST (P<0.05, P<0.01) and an elevated level of HDL-C (P<0.05) in the serum, and lowered levels of TG and NEFA (P<0.05, P<0.01) in the liver. Furthermore, the three groups showed alleviated pyknosis and deep staining of hypothalamic neuron cells, reduced lipid deposition in the liver, down-regulated mRNA and protein levels of CLOCK and BMAL1 (P<0.05, P<0.01), and up-regulated mRNA and protein levels of Cry1 and PER2 (P<0.05, P<0.01) in the hypothalamus and liver. ConclusionModified Ditan tang can reduce lipid deposition in the liver and regulate the expression of CLOCK, BMAL1, Cry1, and PER2 in the TTFL of NAFLD rats.
6.Determination method of plasma concentrations of 7 anti-tumor drugs and its application
Jinxiu LYU ; Nan YAN ; Wenjun XU ; Jing ZHAO ; Hua ZHU ; Pengzhou HANG
China Pharmacy 2025;36(4):475-481
OBJECTIVE To establish a method for simultaneous determination of 7 anti-tumor drugs (irinotecan, capecitabine, paclitaxel, docetaxel, tamoxifen, letrozole and methotrexate) in human plasma and apply it to the clinic. METHODS After precipitating with a methanol-acetonitrile mixture (1∶ 1, V/V) containing 0.1% formic acid, liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to determine the plasma concentration, using deuterium isotopes of each analyte as internal standards. The chromatography was performed on the Agilent Eclipse Plus C18 column with a gradient elution of water (containing 0.1% formic acid+0.04% 5 mmol/L ammonium formate) as mobile phase A and acetonitrile (containing 0.1% formic acid) as mobile phase B. The flow rate was 0.6 mL/min, and the column temperature was set at 40 ℃ . The sample size was 10 μL, and the analysis lasted for 5.5 min. Electrospray ionization was used in positive and negative ion mode, and multiple reaction monitoring mode was used. The ion pairs used for quantitative analysis were m/z 587.1→167.1 (irinotecan), m/z 360.1→244.1 (capecitabine), m/z 876.4→308.0 (paclitaxel), m/z 830.3→304.2 (docetaxel), m/z 372.1→129.1 (tamoxifen), m/z 284.1→242.1 (letrozole), and m/z 455.0→ 308.0 (methotrexate). A total of 97 patients with malignant tumors in our hospital were selected to measure the plasma concentrations of 7 anti-tumor drugs using the above method. RESULTS The linear ranges of irinotecan, capecitabine, paclitaxel, docetaxel, tamoxifen, letrozole and methotrexate were 2-1 000 ng/mL (r=0.994 3), 20-10 000 ng/mL (r=0.997 5), 2-1 000 ng/mL (r=0.997 9), 1-500 ng/mL (r=0.995 8), 1-500 ng/mL (r=0.995 2), 1-500 ng/mL (r=0.996 4), 10-5 000 (r=0.997 7), respectively. The quantitative lower limits were 2, 20, 2, 1, 1, 1 and 10 ng/mL; RSDs of intra-assay precision were 0.08%-14.86% (n=6). RSDs of inter-batch precision were 1.51%-11.55% (n=3), and the accuracies were 89.17%-114.93% (n=6). The matrix effects ranged from 89.89%-119.74% (n=6). RSDs of the stability tests were 1.98%-14.88% (n=6). The results of E-mail:hangpengzhou@163.com clinical application showed, the average plasma concentrations of irinotecan, capecitabine, paclitaxel and docetaxel were 704.09, 909.40, 36.45, 150.43 ng/mL, respectively. The values of the coefficient of variation were 25.24%, 62.65%, 122.69%, and 92.27%. CONCLUSIONS The established LC-MS/MS method is simple and rapid, and can be used for the simultaneous determination of 7 commonly used anti-tumor drugs in the plasma of patients with malignancy.
7.Research progress of nano drug delivery system based on metal-polyphenol network for the diagnosis and treatment of inflammatory diseases
Meng-jie ZHAO ; Xia-li ZHU ; Yi-jing LI ; Zi-ang WANG ; Yun-long ZHAO ; Gao-jian WEI ; Yu CHEN ; Sheng-nan HUANG
Acta Pharmaceutica Sinica 2025;60(2):323-336
Inflammatory diseases (IDs) are a general term of diseases characterized by chronic inflammation as the primary pathogenetic mechanism, which seriously affect the quality of patient′s life and cause significant social and medical burden. Current drugs for IDs include nonsteroidal anti-inflammatory drugs, corticosteroids, immunomodulators, biologics, and antioxidants, but these drugs may cause gastrointestinal side effects, induce or worsen infections, and cause non-response or intolerance. Given the outstanding performance of metal polyphenol network (MPN) in the fields of drug delivery, biomedical imaging, and catalytic therapy, its application in the diagnosis and treatment of IDs has attracted much attention and significant progress has been made. In this paper, we first provide an overview of the types of IDs and their generating mechanisms, then sort out and summarize the different forms of MPN in recent years, and finally discuss in detail the characteristics of MPN and their latest research progress in the diagnosis and treatment of IDs. This research may provide useful references for scientific research and clinical practice in the related fields.
9.Role of artificial intelligence in medical image analysis.
Lu WANG ; Shimin ZHANG ; Nan XU ; Qianqian HE ; Yuming ZHU ; Zhihui CHANG ; Yanan WU ; Huihan WANG ; Shouliang QI ; Lina ZHANG ; Yu SHI ; Xiujuan QU ; Xin ZHOU ; Jiangdian SONG
Chinese Medical Journal 2025;138(22):2879-2894
With the emergence of deep learning techniques based on convolutional neural networks, artificial intelligence (AI) has driven transformative developments in the field of medical image analysis. Recently, large language models (LLMs) such as ChatGPT have also started to achieve distinction in this domain. Increasing research shows the undeniable role of AI in reshaping various aspects of medical image analysis, including processes such as image enhancement, segmentation, detection in image preprocessing, and postprocessing related to medical diagnosis and prognosis in clinical settings. However, despite the significant progress in AI research, studies investigating the recent advances in AI technology in the aforementioned aspects, the changes in research hotspot trajectories, and the performance of studies in addressing key clinical challenges in this field are limited. This article provides an overview of recent advances in AI for medical image analysis and discusses the methodological profiles, advantages, disadvantages, and future trends of AI technologies.
Artificial Intelligence
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Humans
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Image Processing, Computer-Assisted/methods*
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Neural Networks, Computer
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Deep Learning
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Diagnostic Imaging/methods*
10.Gypenoside L Regulates piR-hsa-2804461/FKBP8/Bcl-2 Axis to Promote Apoptosis and Inhibit Ovarian Cancer
Yuanguang DONG ; Yinying SUN ; Mingdian YUAN ; Ying YANG ; Jiaxin WANG ; Jingxuan ZHU ; Nan SONG
Chinese Journal of Experimental Traditional Medical Formulae 2025;31(11):98-106
ObjectiveTo explore the molecular mechanism by which gypenoside L (Gyp-L) promotes apoptosis and inhibits ovarian cancer (OC) through the FK506-binding protein (FKBP) prolyl isomerase 8 (FKBP8)/B-cell lymphoma-2 (Bcl-2) axis, with the piR-hsa-2804461 pathway as a breakthrough point. MethodsThe effects of different concentrations of Gyp-L and cis-platinum on the proliferation of OVCAR3 cells were determined by the cell count kit-8 method to identify the appropriate intervention concentration for subsequent experiments. OVCAR3 cells were allocated into blank, low-dose Gyp-L (Gyp-L-L, 50 µmol·L-1), high-dose Gyp-L (Gyp-L-H, 100 µmol·L-1), and cis-platinum (15 µmol·L-1) groups. The migration, colony formation, and apoptosis of OVCAR3 cells were detected by the cell scratch assay, colony formation assay, and flow cytometry, respectively. The mRNA levels of piR-hsa-2804461 and FKBP8/Bcl-2 axis-related genes in OVCAR3 cells were determined by Real-time PCR, and the expression levels of FKBP8/Bcl-2 axis-related proteins were determined by simple Western blot. Further, an OVCAR3 cell model with piR-hsa-2804461 knocked out was constructed. The cells were allocated into blank, NC-inhibitor, inhibitor, NC-inhibitor+Gyp-L, and inhibitor+Gyp-L groups. The colony formation of OVCAR3 cells was detected by the colony formation assay. The mRNA levels of piR-hsa-2804461 and FKBP8/Bcl-2 axis-related genes and the expression levels of FKBP8/Bcl-2 axis-related proteins were determined by Real-time PCR and simple Western blotting, respectively. ResultsGyp-L inhibited the migration and proliferation (P<0.01), promoted the apoptosis (P<0.05), up-regulated the mRNA level of piR-hsa-2804461 (P<0.05), and down-regulated the mRNA and protein levels of FKBP8 and Bcl-2 (P<0.05) in OVCAR3 cells. Furthermore, Gyp-L increased the mRNA and protein levels of Bcl-2-associated X protein (Bax), cysteinyl aspartate-specific proteinase (Caspase)-3, and Caspase-9, which are related to the FKBP8/Bcl-2 axis (P<0.05). ConclusionGyp-L may promote apoptosis by regulating the piR-hsa-2804461/FKBP8/Bcl-2 axis, thus affecting the occurrence of ovarian cancer.

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