Objective To analyze the epidemiological characteristics and disease burden of liver cancer in Guangdong Province in 2020, and to provide a scientific foundation for the development of regionalized prevention and control strategies for liver cancer. Methods According to the cancer registry data of Guangdong Province, the incidence, mortality and age-standardized rate by Chinese standard population in 2020 were calculated to analyze the epidemiological characteristics of liver cancer. The disability adjusted life years (DALYs), year of life loss (YLL), year of lived with disability (YLD), and cause-eliminated life expectancy were used to assess the disease burden of liver cancer. Results In 2020, the crude incidence rate and the age-standardized incidence rate of liver cancer in Guangdong Province were 27.79/100 000 and 20.84/100 000，respectively, and the crude mortality rate and the age-standardized mortality rate of liver cancer were 25.49/100,000 and 17.64/100 000, respectively. The total DALY and DALY rate of liver cancer in Guangdong Province were 515 311 person-years and 513.83/100 000, respectively. After eliminating the causes of death from liver cancer, the life expectancy in Guangdong Province increased from 84.60 years to 84.99 years. All indicators consistently demonstrated that the burden of liver cancer was higher in males than that in females, and the burden of liver cancer was higher in rural areas than that in urban areas. Conclusion Liver cancer in Guangdong Province exhibits a high incidence, mortality and disease burden level in 2020. There are obvious differences of gender, age and region in cancer burden. It is necessary to strengthen liver cancer screening and diagnosis and treatment in men, the elderly and those in rural areas to reduce the burden of liver cancer gradually in Guangdong Province.

ObjectiveHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） and GC-triple quadrupole MS（GC-QqQ-MS） in combination with non-targeted and targeted metabolomics were employed to systematically analyze the chemical composition differences of Xihuangwan prepared with natural musk and artificial musk， and establish an identification system for them. MethodsThe volatile components of 9 batches of Xihuangwan samples from 8 manufacturers were analyzed by HS-SPME-GC-MS non-targeted metabolomics， and identified by comparing their MS data with the National Institute of Standards and Technology（NIST） spectral library. Orthogonal partial least squares-discriminant analysis（OPLS-DA） was used to identify differential volatile components of Xihuangwan prepared with natural musk and artificial musk. Additionally， GC-QqQ-MS targeted metabolomics was applied to quantify the levels of α-pinene， β-elemene， muscone， dehydroepiandrosterone， bornyl acetate， and octyl acetate in 27 batches of samples from 9 manufacturers. Cluster analysis， principal component analysis（PCA）， and partial least squares-discriminant analysis（PLS-DA） were conducted to further explore the differences in volatile components between Xihuangwan samples prepared with natural musk and artificial musk. ResultsNon-targeted metabolomics identified 291 volatile compounds in Xihuangwan， including alkanes， esters， alkanes， alcohols， ketones， naphthalenes and others. OPLS-DA analysis revealed distinct separation between Xihuangwan samples containing artificial musk（A1， C1， D1， E1， F1， G1， I1） and those containing natural musk（H1， H3）. A total of 30 differential metabolites were identified. The relative contents of these 30 differential metabolites were visualized using a radar chart， revealing significant differences in the levels of octanol， borneol acetate and muscone. Cluster analysis and PCA results from targeted metabolomics indicated that Xihuangwan could be classified into two distinct groups：one composed of natural musk（H1， H3） and the other of artificial musk， sample H2. PLS-DA identified muscone， octyl acetate， and dehydroepiandrosterone as key differential volatile components. Although no significant difference was observed in the content of octyl acetate between the two groups， statistically significant differences were found for muscone and dehydroepiandrosterone（P<0.05）. ConclusionMuscone and dehydroepiandrosterone can be used for the differentiation of Xihuangwan samples containing natural musk from those containing artificial musk. This study systematically and comprehensively analyzed the differences in the types and contents of major volatile components in Xihuangwan prepared with natural musk and artificial musk， providing a scientific basis for quality evaluation and control of Xihuangwan.

ObjectiveHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） and GC-triple quadrupole MS（GC-QqQ-MS） in combination with non-targeted and targeted metabolomics were employed to systematically analyze the chemical composition differences of Xihuangwan prepared with natural musk and artificial musk， and establish an identification system for them. MethodsThe volatile components of 9 batches of Xihuangwan samples from 8 manufacturers were analyzed by HS-SPME-GC-MS non-targeted metabolomics， and identified by comparing their MS data with the National Institute of Standards and Technology（NIST） spectral library. Orthogonal partial least squares-discriminant analysis（OPLS-DA） was used to identify differential volatile components of Xihuangwan prepared with natural musk and artificial musk. Additionally， GC-QqQ-MS targeted metabolomics was applied to quantify the levels of α-pinene， β-elemene， muscone， dehydroepiandrosterone， bornyl acetate， and octyl acetate in 27 batches of samples from 9 manufacturers. Cluster analysis， principal component analysis（PCA）， and partial least squares-discriminant analysis（PLS-DA） were conducted to further explore the differences in volatile components between Xihuangwan samples prepared with natural musk and artificial musk. ResultsNon-targeted metabolomics identified 291 volatile compounds in Xihuangwan， including alkanes， esters， alkanes， alcohols， ketones， naphthalenes and others. OPLS-DA analysis revealed distinct separation between Xihuangwan samples containing artificial musk（A1， C1， D1， E1， F1， G1， I1） and those containing natural musk（H1， H3）. A total of 30 differential metabolites were identified. The relative contents of these 30 differential metabolites were visualized using a radar chart， revealing significant differences in the levels of octanol， borneol acetate and muscone. Cluster analysis and PCA results from targeted metabolomics indicated that Xihuangwan could be classified into two distinct groups：one composed of natural musk（H1， H3） and the other of artificial musk， sample H2. PLS-DA identified muscone， octyl acetate， and dehydroepiandrosterone as key differential volatile components. Although no significant difference was observed in the content of octyl acetate between the two groups， statistically significant differences were found for muscone and dehydroepiandrosterone（P<0.05）. ConclusionMuscone and dehydroepiandrosterone can be used for the differentiation of Xihuangwan samples containing natural musk from those containing artificial musk. This study systematically and comprehensively analyzed the differences in the types and contents of major volatile components in Xihuangwan prepared with natural musk and artificial musk， providing a scientific basis for quality evaluation and control of Xihuangwan.

BACKGROUND: This study aimed to investigate programmed death-ligand 1 tumor proportion score in predicting the safety and efficacy of PD-1/PD-L1 antibody-based therapy in treating patients with advanced non-small cell lung cancer (NSCLC) in a real-world setting. METHODS: This retrospective, multicenter, observational study enrolled adult patients who received PD-1/PD-L1 antibody-based therapy in China and met the following criteria: (1) had pathologically confirmed, unresectable stage III-IV NSCLC; (2) had a baseline PD-L1 tumor proportion score (TPS); and (3) had confirmed efficacy evaluation results after PD-1/PD-L1 treatment. Logistic regression, Kaplan-Meier analysis, and Cox regression were used to assess the progression-free survival (PFS), overall survival (OS), and immune-related adverse events (irAEs) as appropriate. RESULTS: A total of 409 patients, 65.0% ( n = 266) with a positive PD-L1 TPS (≥1%) and 32.8% ( n = 134) with PD-L1 TPS ≥50%, were included in this study. Cox regression confirmed that patients with a PD-L1 TPS ≥1% had significantly improved PFS (hazard ratio [HR] 0.747, 95% confidence interval [CI] 0.573-0.975, P = 0.032). A total of 160 (39.1%) patients experienced 206 irAEs, and 27 (6.6%) patients experienced 31 grade 3-5 irAEs. The organs most frequently associated with irAEs were the skin (52/409, 12.7%), thyroid (40/409, 9.8%), and lung (34/409, 8.3%). Multivariate logistic regression revealed that a PD-L1 TPS ≥1% (odds ratio [OR] 1.713, 95% CI 1.054-2.784, P = 0.030) was an independent risk factor for irAEs. Other risk factors for irAEs included pretreatment absolute lymphocyte count >2.5 × 10 9 /L (OR 3.772, 95% CI 1.377-10.329, P = 0.010) and pretreatment absolute eosinophil count >0.2 × 10 9 /L (OR 2.006, 95% CI 1.219-3.302, P = 0.006). Moreover, patients who developed irAEs demonstrated improved PFS (13.7 months vs. 8.4 months, P <0.001) and OS (28.0 months vs. 18.0 months, P = 0.007) compared with patients without irAEs. CONCLUSIONS A positive PD-L1 TPS (≥1%) was associated with improved PFS and an increased risk of irAEs in a real-world setting. The onset of irAEs was associated with improved PFS and OS in patients with advanced NSCLC receiving PD-1/PD-L1-based therapy.
Humans ; Carcinoma, Non-Small-Cell Lung/metabolism* ; Male ; Female ; Retrospective Studies ; Middle Aged ; Lung Neoplasms/metabolism* ; Aged ; B7-H1 Antigen/metabolism* ; Programmed Cell Death 1 Receptor/metabolism* ; Adult ; Aged, 80 and over ; Immune Checkpoint Inhibitors/therapeutic use*

To investigate the mechanism of Qitu Erzhi Decoction(QTEZ) in ameliorating chemotherapy-induced myelosuppression and the focus of its decomposed formulae on the effects of hematopoietic cells of the three lineages, respectively. Ultra performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry(UPLC-Q-TOF-MS) was used to identify the components of QTEZ intestinal absorption liquid and obtain the target sites, which were intersected with chemotherapy-induced myelosuppression targets collected from several databases, including OMIM, and an interaction network was established based on network pharmacology for Gene Ontology(GO) functional analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway analysis. Hematopoietic stem cells of mice were taken after intraperitoneal injection of 5-fluorouracil for myelosuppression modeling and randomly divided into the model group, Qitu Erzhi group, Astragali Radix-Angelicae Sinensis Radix group, Ligustri Lucidi Fructus-Ecliptae Herba group, Psoraleae Fructus-Cuscutae Semen group, and positive drug group, which were given the corresponding traditional Chinese medicine intestinal absorption liquid and the positive drug granulocyte colony-stimulating factor, respectively. The normal hematopoietic stem cells were taken as the control group and were given the intervention of normal saline. The proliferation of hematopoietic progenitor cells of three lineages was observed by flow cytometry, and the cell cycle and colony formation assay were observed. Western blot was used to verify the effect of QTEZ on the pathway proteins including phosphoinositide 3-kinase(PI3K), phosphorylated PI3K(p-PI3K), protein kinase B(AKT), and phosphorylated AKT(p-AKT). RT-qPCR and Western blot were used to detect the effects of QTEZ on cell cycle-related targets such as CDK inhibitor 1(P21), cyclin D1(CCND1), and cyclin-dependent kinase 4(CDK4). The results showed that a total of 158 components were identified by QTEZ, and 375 component and disease intersecting targets were obtained, 21 core components and 40 core targets were obtained after constructing the network, and GO and KEGG enrichment showed signaling pathways such as PI3K/AKT. QTEZ and its decomposed formulae could promote the 5-fluorouracil-blocked cell cycle to resume operation, and all of them had different degrees of restoration effects on the set of colonies, among which QTEZ had the best restoration effect, and the Astragali Radix-Angelicae Sinensis Radix group had a focused effect on colony forming unit-erythrocyte. Western blot results indicated that there was no significant difference in the expression levels of pathway proteins among the groups. RT-qPCR and Western blot results showed that QTEZ could down-regulate P21 and up-regulate the protein and mRNA expression of CDK4 and CCND1. In conclusion, QTEZ and its decomposed formulas can exert a protective effect on hematopoietic stem cells with 5-fluorouracil-induced myelosuppression by promoting the normal operation of the cell cycle and colony formation, and the mechanism may be related to the down-regulation of the cell cycle-related targets of P21 and the up-regulation of CDK4 and CCND1. In addition, Astragali Radix-Angelicae Sinensis Radix can have a targeted protective effect on erythrocytes.
Animals ; Drugs, Chinese Herbal/chemistry* ; Network Pharmacology ; Mice ; Fluorouracil/adverse effects* ; Male ; Antineoplastic Agents/adverse effects* ; Hematopoietic Stem Cells/cytology* ; Humans ; Signal Transduction/drug effects*

This paper aimed to use non-targeted urine metabolomics to reveal the potential biomarkers of toxicity in rats with hepatic injury induced by aqueous extracts of Dictamni Cortex(ADC). Forty-eight SD rats were randomly assigned to a blank group and high-dose, medium-dose, and low-dose ADC groups, with 12 rats in each group(half male and half female), and they were administered orally for four weeks. The hepatic injury in SD rats was assessed by body weight, liver weight/index, biochemical index, L-glutathione(GSH), malondialdehyde(MDA), and pathological alterations. The qPCR was utilized to determine the expression of metabolic enzymes in the liver and inflammatory factors. Differential metabolites were screened using principal component analysis(PCA) and partial least squares-discriminant analysis(PLS-DA), followed by a metabolic pathway analysis. The Mantel test was performed to assess differential metabolites and abnormally expressed biochemical indexes, obtaining potential biomarkers. The high-dose ADC group showed a decrease in body weight and an increase in liver weight and index, resulting in hepatic inflammatory cell infiltration and hepatic steatosis. In addition, this group showed elevated levels of MDA, cytochrome P450(CYP) 3A1, interleukin-1β(IL-1β), and tumor necrosis factor-α(TNF-α), as well as lower levels of alanine transaminase(ALT) and GSH. A total of 76 differential metabolites were screened from the blank and high-dose ADC groups, which were mainly involved in the pentose phosphate pathway, tryptophan metabolism, purine metabolism, pentose and glucuronic acid interconversion, galactose metabolism, glutathione metabolism, and other pathways. The Mantel test identified biomarkers of hepatotoxicity induced by ADC in SD rats, including glycineamideribotide, dIDP, and galactosylglycerol. In summary, ADC induced hepatotoxicity by disrupting glucose metabolism, ferroptosis, purine metabolism, and other pathways in rats, and glycineamideribotide, dIDP, and galactosylglycerol could be employed as the biomarkers of its toxicity.
Animals ; Male ; Rats, Sprague-Dawley ; Rats ; Metabolomics ; Biomarkers/metabolism* ; Liver/metabolism* ; Drugs, Chinese Herbal/adverse effects* ; Female ; Chemical and Drug Induced Liver Injury/metabolism* ; Glutathione/metabolism* ; Humans

The rapid development of artificial intelligence (AI), especially generative AI (GenAI), has already brought, and will continue to bring, revolutionary changes to our daily production and life, as well as create new opportunities and challenges for diagnostic and therapeutic practices in the medical field. Haihe Hospital of Tianjin University collaborates with the National Supercomputer Center in Tianjin, Tianjin University, and other institutions to carry out research in areas such as smart healthcare, smart services, and smart management. We have conducted research and development of a full-process disease diagnosis and treatment assistance system based on GenAI in the field of smart healthcare. The development of this project is of great significance. The first goal is to upgrade and transform the hospital's information center, organically integrate it with existing information systems, and provide the necessary computing power storage support for intelligent services within the hospital. We have implemented the localized deployment of three models: Tianhe "Tianyuan", WiNGPT, and DeepSeek. The second is to create a digital avatar of the chief physician/chief physician's voice and image by integrating multimodal intelligent interaction technology. With generative intelligence as the core, this solution provides patients with a visual medical interaction solution. The third is to achieve deep adaptation between generative intelligence and the entire process of patient medical treatment. In this project, we have developed assistant tools such as intelligent inquiry, intelligent diagnosis and recognition, intelligent treatment plan generation, and intelligent assisted medical record generation to improve the safety, quality, and efficiency of the diagnosis and treatment process. This study introduces the content of a full-process disease diagnosis and treatment assistance system, aiming to provide references and insights for the digital transformation of the healthcare industry.
Artificial Intelligence ; Humans ; Delivery of Health Care ; Generative Artificial Intelligence

OBJECTIVE: Hepatocellular carcinoma (HCC) is sensitive to ferroptosis, a new form of programmed cell death that occurs in most tumor types. However, the mechanism through which ferroptosis modulates HCC remains unclear. This study aimed to investigate the oncogenic role and prognostic value of FANCD2 and provide novel insights into the prognostic assessment and prediction of immunotherapy. METHODS: Using clinicopathological parameters and bioinformatic techniques, we comprehensively examined the expression of FANCD2 macroscopically and microcosmically. We conducted univariate and multivariate Cox regression analyses to identify the prognostic value of FANCD2 in HCC and elucidated the detailed molecular mechanisms underlying the involvement of FANCD2 in oncogenesis by promoting iron-related death. RESULTS: FANCD2 was significantly upregulated in digestive system cancers with abundant immune infiltration. As an independent risk factor for HCC, a high FANCD2 expression level was associated with poor clinical outcomes and response to immune checkpoint blockade. Gene set enrichment analysis revealed that FANCD2 was mainly involved in the cell cycle and CYP450 metabolism. CONCLUSION To the best of our knowledge, this is the first study to comprehensively elucidate the oncogenic role of FANCD2. FANCD2 has a tumor-promoting aspect in the digestive system and acts as an independent risk factor in HCC; hence, it has recognized value for predicting tumor aggressiveness and prognosis and may be a potential biomarker for poor responsiveness to immunotherapy.
Humans ; Carcinoma, Hepatocellular/diagnosis* ; Liver Neoplasms/diagnosis* ; Immunotherapy ; Fanconi Anemia Complementation Group D2 Protein/metabolism* ; Prognosis ; Male ; Female ; Middle Aged ; Biomarkers, Tumor/metabolism*

OBJECTIVE: Cigarette smoking exacerbates the progression of pulmonary tuberculosis (TB). The role of tertiary lymphoid structures (TLS) in chronic lung diseases has gained attention; however, it remains unclear whether smoking-exacerbated lung damage in TB is associated with TLS. This study aimed to analyze the characteristics of pulmonary TLS in smokers with TB and to explore the possible role of TLS in smoking-related lung injury in TB. METHODS: Lung tissues from 36 male patients (18 smokers and 18 non-smokers) who underwent surgical resection for pulmonary TB were included in this study. Pathological and immunohistological analyses were conducted to evaluate the quantity of TLS, and chest computed tomography (CT) was used to assess the severity of lung lesions. The correlation between the TLS quantity and TB lesion severity scores was analyzed. The immune cells and chemokines involved in TLS formation were also evaluated and compared between smokers and non-smokers. RESULTS: Smoker patients with TB had significantly higher TLS than non-smokers ( P < 0.001). The TLS quantity in both the lung parenchyma and peribronchial regions correlated with TB lesion severity on chest CT (parenchyma: r = 0.5767; peribronchial: r = 0.7373; both P < 0.001). Immunohistochemical analysis showed increased B cells, T cells, and C-X-C motif chemokine ligand 13 (CXCL13) expression in smoker patients with TB ( P < 0.001). CONCLUSION Smoker TB patients exhibited increased pulmonary TLS, which was associated with exacerbated lung lesions on chest CT, suggesting that cigarette smoking may exacerbate lung damage by promoting TLS formation.
Humans ; Male ; Tuberculosis, Pulmonary/immunology* ; Middle Aged ; Tertiary Lymphoid Structures/pathology* ; Adult ; Lung/pathology* ; Smoking/adverse effects* ; Smokers ; Aged ; Tomography, X-Ray Computed

OBJECTIVE: To investigate the characteristics of gut microbiota changes in patients with acute myeloid leukemia (AML) undergoing induction chemotherapy and to explore the relationship between infectious complications and gut microbiota. METHODS: Fecal samples were collected from 37 newly diagnosed AML patients at four time points: before induction chemotherapy, during chemotherapy, during the neutropenic phase, and during the recovery phase. Metagenomic sequencing was used to analyze the dynamic changes in gut microbiota. Correlation analyses were conducted to assess the relationship between changes in gut microbiota and the occurrence of infectious complications. RESULTS: During chemotherapy, the gut microbiota α-diversity (Shannon index) of AML patients exhibited significant fluctuations. Specifically, the diversity decreased significantly during induction chemotherapy, further declined during the neutropenic phase (P < 0.05, compared to baseline), and gradually recovered during the recovery phase, though not fully returning to baseline levels.The abundances of beneficial bacteria, such as Firmicutes and Bacteroidetes, gradually decreased during chemotherapy, whereas the abundances of opportunistic pathogens, including Enterococcus, Klebsiella, and Escherichia coli, progressively increased.Analysis of the dynamic changes in gut microbiota of seven patients with bloodstream infections revealed that the bloodstream infection pathogens could be detected in the gut microbiota of the corresponding patients, with their abundance gradually increasing during the course of infection. This finding suggests that bloodstream infections may be associated with opportunistic pathogens originating from the gut microbiota.Compared to non-infected patients, the baseline samples of infected patients showed a significantly lower relative abundance of Bacteroidetes (P < 0.05). Regression analysis indicated that Bacteroidetes abundance is an independent predictive factor for infectious complications (P < 0.05, OR =13.143). CONCLUSION During induction chemotherapy in AML patients, gut microbiota α-diversity fluctuates significantly, and the abundance of opportunistic pathogens increase, which may be associated with bloodstream infections. Patients with lower baseline Bacteroidetes abundance are more prone to infections, and its abundance can serve as an independent predictor of infectious complications.
Humans ; Gastrointestinal Microbiome ; Leukemia, Myeloid, Acute/microbiology* ; Induction Chemotherapy ; Feces/microbiology* ; Male ; Female ; Middle Aged