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.

Objective Based on the visualization graph analysis of the research hotspots of Angelica sinensis, predict the future research trends, and provide references for the next step of Angelica sinensis research. Methods Chinese and English literatures on Angelica sinensis collected from CNKI, WanFang, VIP and Web of Science from 2012 to 2022 were retrieved. CiteSpace 6.1.R6 software was used to perform visualization econometrics analysis on the number of publications, authors, institutions, journals, keywords and other topics. Results 3490 Chinese literatures and 409 English literatures were included. Visual knowledge map analysis showed that Gansu University of Chinese Medicine and Nanjing University of Chinese Medicine were the research institutions with the largest number of literature publications in Chinese and English respectively. Journals published mainly include Shizhen Traditional Chinese Medicine and Materia medica, Evidence-based Complementary and Alternative Medicine. Current research hotspots include the effects of Angelica sinensis polysaccharides, volatile oils, and ferulic acid on the hematopoietic system, chronic diseases, and cognitive impairment, as well as clinical efficacy evaluations of classic prescriptions containing Angelica sinensis and their modified formulations. The research trend was characterized by a focus on the pharmacological study of Danggui Buxue Tang,employing various experimental approaches such as network pharmacology, serum pharmacology, and metabolomics to elucidate the mechanisms of Angelica sinensis. Conclusion The pharmacological effects of Angelica sinensis and its compound were extensive, which should be further researched.

ObjectiveThis paper aims to investigate the material basis of the anti-inflammatory efficacy and mechanism of action of Bushen Tongdu prescription （BSTDP）. MethodsThe chemical components of BSTDP and its blood-absorbed components in vivo were systematically identified by using ultra-performance liquid chromatography-linear ion trap-electrostatic field orbitrap high-resolution mass spectrometry （UPLC-LIT-Orbitrap-MS）. Network pharmacology was employed to screen blood-absorbed bioactive components and potential targets of this formula. A protein-protein interaction （PPI） network of core targets was constructed to conduct enrichment analysis. Molecular docking was further utilized to verify the binding affinity between key components and targets. The inflammatory model was established and verified in vivo by using a transgenic zebrafish Tg （mpx： GFP）. At three days post-fertilization （3 dpf）， larvae of zebrafish were randomly assigned to blank group， model group， positive drug dexamethasone acetate group （75 μmol·L^-1）， and BSTDP groups with low， medium， and high doses （500， 1 000， and 2 000 mg·L^-1）. The distribution and quantity of neutrophils in the yolk sac region were observed under a fluorescence microscope. The mRNA expression levels of key genes in the toll-like receptor 4 （TLR4）/myeloid differentiation factor 88 （MyD88）/nuclear factor kappa-B （NF-κB） signaling pathway and inflammatory factors including interleukin （IL）-1β， IL-6， and tumor necrosis factor-α （TNF-α） were detected by Real-time quantitative polymerase chain reaction （Real-time PCR）. ResultsA total of 120 chemical components were identified in BSTDP， among which 26 original components were confirmed by using serum pharmacochemical methods. A total of 227 common targets linking rheumatoid arthritis （RA） and the blood-absorbed components were screened by network pharmacology. It is suggested that pseudobrucine， vomicine， sinapine， rehmannioside， cinnamyl alcohol glycoside， and methylephedrine exert anti-inflammatory effects by acting on core targets including protein kinase B1 （Akt1）， signal transducer and activator of transcription 3 （STAT3）， tumor necrosis factor （TNF）， TLR4， mitogen-activated protein kinase 14 （MAPK14）， and phosphatidylinositol-4，5-bisphosphate 3-kinase catalytic subunit α （PIK3CA）， thereby modulating multiple signaling pathways such as TLR4 and NF-κB. In vivo verification in zebrafish demonstrates that the maximum tolerable concentration of Bushen Tongdu Formula is 2 000 mg·L^-1. Compared to those in the blank group， zebrafish in the model group showed a significantly higher number of neutrophils in the yolk sac region （P<0.01） and rising mRNA levels of TLR4， MyD88， NF-κB， TNF-α， IL-6， and IL-1β （P<0.01）. Compared to that in the model group， the number of neutrophils was significantly reduced in BSTDP groups with medium and high doses， as well as the dexamethasone acetate group （P<0.05， P<0.01）. There was no statistically significant difference in the low dose group. The mRNA expression levels of TLR4， MyD88， NF-κB， TNF-α， IL-6， and IL-1β were significantly down-regulated （P<0.05， P<0.01）. ConclusionThis paper identifies the material basis of the efficacy of BSTDP， demonstrating that the formula can exert an anti-inflammatory effect through the TLR4/MyD88/NF-κB signaling pathway. The results provide scientific experimental evidence for its further clinical application.

ObjectiveThis paper aims to investigate the material basis of the anti-inflammatory efficacy and mechanism of action of Bushen Tongdu prescription （BSTDP）. MethodsThe chemical components of BSTDP and its blood-absorbed components in vivo were systematically identified by using ultra-performance liquid chromatography-linear ion trap-electrostatic field orbitrap high-resolution mass spectrometry （UPLC-LIT-Orbitrap-MS）. Network pharmacology was employed to screen blood-absorbed bioactive components and potential targets of this formula. A protein-protein interaction （PPI） network of core targets was constructed to conduct enrichment analysis. Molecular docking was further utilized to verify the binding affinity between key components and targets. The inflammatory model was established and verified in vivo by using a transgenic zebrafish Tg （mpx： GFP）. At three days post-fertilization （3 dpf）， larvae of zebrafish were randomly assigned to blank group， model group， positive drug dexamethasone acetate group （75 μmol·L^-1）， and BSTDP groups with low， medium， and high doses （500， 1 000， and 2 000 mg·L^-1）. The distribution and quantity of neutrophils in the yolk sac region were observed under a fluorescence microscope. The mRNA expression levels of key genes in the toll-like receptor 4 （TLR4）/myeloid differentiation factor 88 （MyD88）/nuclear factor kappa-B （NF-κB） signaling pathway and inflammatory factors including interleukin （IL）-1β， IL-6， and tumor necrosis factor-α （TNF-α） were detected by Real-time quantitative polymerase chain reaction （Real-time PCR）. ResultsA total of 120 chemical components were identified in BSTDP， among which 26 original components were confirmed by using serum pharmacochemical methods. A total of 227 common targets linking rheumatoid arthritis （RA） and the blood-absorbed components were screened by network pharmacology. It is suggested that pseudobrucine， vomicine， sinapine， rehmannioside， cinnamyl alcohol glycoside， and methylephedrine exert anti-inflammatory effects by acting on core targets including protein kinase B1 （Akt1）， signal transducer and activator of transcription 3 （STAT3）， tumor necrosis factor （TNF）， TLR4， mitogen-activated protein kinase 14 （MAPK14）， and phosphatidylinositol-4，5-bisphosphate 3-kinase catalytic subunit α （PIK3CA）， thereby modulating multiple signaling pathways such as TLR4 and NF-κB. In vivo verification in zebrafish demonstrates that the maximum tolerable concentration of Bushen Tongdu Formula is 2 000 mg·L^-1. Compared to those in the blank group， zebrafish in the model group showed a significantly higher number of neutrophils in the yolk sac region （P<0.01） and rising mRNA levels of TLR4， MyD88， NF-κB， TNF-α， IL-6， and IL-1β （P<0.01）. Compared to that in the model group， the number of neutrophils was significantly reduced in BSTDP groups with medium and high doses， as well as the dexamethasone acetate group （P<0.05， P<0.01）. There was no statistically significant difference in the low dose group. The mRNA expression levels of TLR4， MyD88， NF-κB， TNF-α， IL-6， and IL-1β were significantly down-regulated （P<0.05， P<0.01）. ConclusionThis paper identifies the material basis of the efficacy of BSTDP， demonstrating that the formula can exert an anti-inflammatory effect through the TLR4/MyD88/NF-κB signaling pathway. The results provide scientific experimental evidence for its further clinical application.

OBJECTIVE To investigate the neuroprotective effect and mechanism of eleutheroside B （ELB） on Parkinson’s disease （PD） model mice by regulating the IκB kinase β （IKKβ）/nuclear factor-κB （NF-κB） signaling pathway. METHODS Fifty mice were randomly divided into normal control group， model group， positive control group （selegiline hydrochloride， 10 mg/kg）， and ELB low-dose and high-dose groups （80， 160 mg/kg）， with 10 mice in each group. Each group was given relevant medicine or normal saline intragastrically for 14 consecutive days. Starting from the 10th day of administration， the model group and all administration groups were intraperitoneally injected with 1-methyl-4-phenyl-1，2，3，6-tetrahydropyridine （MPTP） 30 mg/kg， for five consecutive days to establish the chronic PD model. After the last administration for 24 h， six mice were randomly selected from each group to test their behavioral abilities； detect the levels of interleukin-1β （IL-1β）， IL-10， tumor necrosis factor-α （TNF-α） in brain tissue and their mRNA expressions were measured， and positive expression of tyrosine hydroxylase （TH）， protein expressions of TH， α -synuclein （ α -syn）， ionized calcium-binding adaptor molecule 1 （Iba-1）， as well as phosphorylation levels of IKKβ and NF-κB p65 proteins in the brain tissue were detected. The ultrastructure of neurons in substantia nigra was observed. RESULTS Compared with the model group， rotarod endurance time and climbing score of each administration group （except for the ELB low-dose group） were increased significantly （ P ＜0.05）， while the levels and mRNA expressions of IL-1β， TNF-α， α -syn， and Iba-1， as well as phosphorylation levels of IKKβ and NF-κB p65 proteins in brain tissue were decreased significantly （except for TNF-α in the ELB low-dose group）. Conversely， the level and mRNA expression of IL-10 （except for the ELB low-dose group）， TH positive expression and protein expressions were significantly increased （ P ＜0.05）. Typical neurodegenerative pathological changes， such as neuronal karyopyknosis， mitochondrial swelling and vacuolization， and endoplasmic reticulum dilation， all showed varying degrees of improvement. CONCLUSIONS ELB may exert neuroprotective effects by inhibiting the activation of the IKKβ/NF-κB signaling pathway， alleviating inflammatory responses， reducing abnormal α -syn aggregation and neuronal loss， and further improving motor dysfunction in PD mice.

BACKGROUND:Currently,treatment method for knee osteoarthritis includes oral medicine,joint cavity drug injection,and physiotherapy,but the curative effect is limited.Existing studies have confirmed that silicon-based bioceramics can promote cartilage and subchondral bone repair and vascular regeneration.OBJECTIVE:To explore the effect of different concentrations of silicon-based bioceramics injected into the knee joint cavity in the treatment of knee osteoarthritis in rats.METHODS:Silicon-based bioceramics-calcium silicate was prepared.Twenty-five SD rats were randomly divided into five groups,with five rats in each group.The healthy group did not receive any intervention,and the modeling group,low-dose calcium silicate group,high-dose calcium silicate group,and saline group used anterior cruciate ligament transection to establish bilateral knee osteoarthritis models.Four weeks after modeling,0.05 mL of 50 and 100 mg/mL calcium silicate solution were injected into the knee joint cavity in the low-dose calcium silicate group and high-dose calcium silicate group,respectively,and 0.05 mL of saline was injected into the knee joint cavity in the saline group,once a week for 4 consecutive weeks.In the fifth week of administration,bilateral knee joint Micro-CT detection,knee joint cartilage hematoxylin-eosin staining,and modified Mankin score were performed.RESULTS AND CONCLUSION:(1)Micro-CT quantitative analysis showed that compared with the healthy group,the volume fraction and number of trabeculae of the medial tibial plateau in the modeling group decreased(P＜0.05),and the separation of trabeculae increased(P＜0.05).Compared with the modeling group,the volume fraction and number of trabeculae of the medial tibial plateau in the low-dose calcium silicate group and the saline group increased(P＜0.05),and the separation of trabeculae decreased(P＜0.05).(2)Hematoxylin-eosin staining showed that the cartilage surface of the healthy group and the low-dose calcium silicate group was relatively smooth and flat,the chondrocytes were evenly distributed,without clustered chondrocytes,the tide line was complete,and the staining was uniform;the cartilage surface of the high-dose calcium silicate group was slightly uneven,the middle and deep cells were disordered,with a small number of clustered chondrocytes,the tide line was discontinuous,and the staining was uneven;the cartilage surface of the saline group and the modeling group was obviously rough,the cells were disordered,with a large number of clustered chondrocytes,the tide line disappeared,and the staining was uneven.The modified Mankin score of the healthy group was lower than that of the high-dose calcium silicate group,the saline group,and the modeling group(P＜0.05).The modified Mankin score of the high-dose calcium silicate group and the low-dose calcium silicate group was lower than that of the saline group and the modeling group(P＜0.05).(3)The results show that calcium silicate knee joint injection has a certain effect in the treatment of knee osteoarthritis.Compared with 100 mg/mL calcium silicate solution,50 mg/mL calcium silicate solution can promote the recovery of subchondral bone and cartilage.

Owing to its inherent advantages—such as being non-destructive, rapid, highly molecule-specific, and minimally interfered with by moisture—Raman spectroscopy has been widely adopted in the fields of skin barrier function assessment, monitoring the transdermal penetration of active cosmetic ingredients, and the identification and quality control of cosmetic products. Despite these strengths, the practical application of this technique faces a significant bottleneck: the strong fluorescence background generated by endogenous skin components and exogenous cosmetic additives. Endogenous skin substances, such as structural proteins (e.g., collagen and elastin), metabolic coenzymes (e.g., nicotinamide adenine dinucleotide), and pigments (e.g., melanin), together with exogenous cosmetic constituents like organic colorants, chemical sunscreens, and fragrances, often possess strong absorption and emission characteristics. When excited by lasers, these components produce a fluorescence background that can be 10⁶ to 10⁸ times stronger than the Raman scattering signals, effectively masking the inherently weak vibrational fingerprint information. In recent years, driven by the rapid development of optoelectronic hardware and artificial intelligence algorithms, fluorescence suppression strategies have evolved from isolated, single-method approaches into comprehensive, multi-level synergistic systems. These systems are categorized into three distinct tiers: sample preparation, signal acquisition, and data processing. At the sample preparation level, techniques such as photobleaching and surface-enhanced Raman spectroscopy (SERS) are employed to eliminate or bypass the generation of fluorescence at the source. At the signal acquisition level, instrumental improvements—including the use of long-wavelength near-infrared excitation (typically 785 nm or 1 064 nm), confocal spatial filtering, and shifted excitation Raman difference spectroscopy (SERDS)— are utilized to physically isolate Raman signals from the fluorescence background. Furthermore, at the data processing level, numerical baseline correction methods such as polynomial fitting, penalized least squares (e.g., airPLS, arPLS), wavelet transform, and derivative algorithms are increasingly integrated into the analytical pipeline to extract Raman spectral features from mixed signals without increasing hardware costs or acquisition time. This review provides a systematic categorization and critical evaluation of these fluorescence suppression methods, detailing their underlying principles, technical advantages, and inherent limitations in diverse experimental setups. By focusing on critical application scenarios—including skin barrier assessment, percutaneous absorption monitoring, the routine quality control of cosmetics, and the emerging field of portable on-site detection—this paper explores the current state of technique selection and optimization. Finally, the article discusses future development trends, emphasizing the necessity of constructing adaptive, tiered suppression strategies, developing intelligent and automated data processing algorithms, and promoting the integration of portable, multi-modal diagnostic devices. The objective of this review is to provide a comprehensive technical reference to facilitate the transition of Raman spectroscopy from a specialized laboratory tool into a routine, robust analytical platform for advancements in skin science and cosmetic research.

Gastric cancer remains a highly prevalent malignancy worldwide, with surgical resection currently constituting the cornerstone of treatment aimed at improving long-term patient survival. Owing to their notable advantages, including reduced surgical trauma and accelerated postoperative recovery, minimally invasive procedures are progressively supplanting conventional open surgery and have become the mainstream approach in gastric cancer management. Concurrently, the rapid advancement of artificial intelligence (AI) technologies has enabled real-time intraoperative monitoring of surgical scenes, thereby furnishing novel technical support for adjunctive decision-making, surgical navigation, and skill assessment during gastrectomy. This article provides a systematic review of the current status of AI applications in minimally invasive gastric cancer surgery, with a particular focus on research progress pertaining to instrument recognition, surgical phase identification, delineation of normal anatomical structures, detection of metastatic foci, and early warning of intraoperative adverse events. Furthermore, we discuss the potential value of AI in enhancing surgical efficiency, ensuring patient safety, and optimizing surgical education. On this basis, we further analyze the principal challenges and inherent risks confronting current AI systems, with the aim of informing future technological innovation and facilitating clinical translation.

ObjectiveTo investigate the risk factors for post-acute pancreatitis diabetes mellitus （PPDM-A） in patients with acute pancreatitis （AP）， to construct a nomogram prediction model， and to provide a reference for the development of individualized treatment regimens. MethodsA total of 351 patients with AP who were admitted to Xuzhou Municipal Hospital Affiliated to Xuzhou Medical University from June 2021 to January 2025 were prospectively enrolled， and they were randomly divided into modeling group with 246 patients and validation group with 105 patients at a ratio of 7∶3. According to the presence or absence of PPDM-A in the patients with AP， the modeling group was further divided into PPDM-A group with 86 patients and non-PPDM-A group with 160 patients. Clinical data were collected from all patients. The least absolute shrinkage and selection operator （LASSO） regression analysis was used to determine independent variables， and a Logistic regression analysis was used to investigate the influencing factors for PPDM-A. R software was used to construct a nomogram model. The receiver operating characteristic curve was used to assess the discriminatory ability of the model， and the Hosmer-Lemeshow test was used to test the model fitting degree， and the calibration curve was used to evaluate the model consistency； and decision curve analysis （DCA） was used to assess its clinical application value. The independent-samples t test was used for comparison of continuous data between two groups， and the chi-square test was used for comparison of categorical data between two groups. ResultsAmong the 246 patients， 86 developed PPDM-A， resulting in an incidence rate of 34.96%. There were significant differences between the PPDM-A group and the non-PPDM-A group in the proportion of patients with an age of ≥60 years （65.12% vs 40.62%， P<0.05）， male sex （75.58% vs 55.63%， P<0.05）， a body mass index （BMI） of ≥24 kg/m² （63.95% vs 37.50%， P<0.05）， alcoholic AP （56.98% vs 36.87%， P<0.05）， moderate-to-severe AP （54.65% vs 35.00%， P<0.05）， or a computed tomography severity index （CTSI） score of ≥4 points （48.84% vs 28.75%， P<0.05）， as well as significant differences in the levels of blood calcium （1.46±0.35 mmol/L vs 1.89±0.37 mmol/L， P<0.05） and random blood glucose （Glu） （17.68±4.12 mmol/L vs 11.68±4.27 mmol/L， P<0.05）. The LASSO regression analysis obtained 8 independent variables. The Logistic regression analysis showed that age， sex， BMI， alcoholic AP， moderate-to-severe AP， CTSI score， and Glu were risk factors for PPDM-A （all P<0.05）， while blood calcium was a protective factor （P<0.05）. The model had an area under the ROC curve （AUC） of 0.932 （95% confidence interval ［CI］： 0.903 — 0.962） in the modeling group， and the Hosmer-Lemeshow goodness-of-fit test yielded χ²=7.346 （P=0.728）， the accuracy of model fitting was good； the calibration curve showed that the predicted probability was consistent with the actual probability， indicating that the consistency was good. The model had an AUC of 0.835 （95%CI： 0.753 — 0.917） in the validation group， and the Hosmer-Lemeshow goodness-of-fit test yielded χ²=7.014 （P=0.711）， the accuracy of model fitting was good； the calibration curve showed that the predicted probability was consistent with the actual probability， indicating that the consistency was good. The DCA results of the modeling group showed that the model exhibited a high clinical value in evaluating PPDM-A when the threshold probability was 0.13 — 0.94. ConclusionAge， sex， BMI， alcoholic AP， moderate-to-severe AP， blood calcium， CTSI score， and Glu are influencing factors for PPDM-A. The nomogram model constructed based on the above influencing factors shows good performance in predicting the risk of PPDM-A and can thus provide a reference for developing prevention strategies for PPDM-A in clinical practice.

Background: Alzheimer’s disease (AD) is the most prevalent neurodegenerative disorder. Cellular drug screening represents a key approach in the preclinical discovery of AD therapeutics. Moreover, selecting an appropriate cellular model is essential for exploring the mechanisms underlying AD pathogenesis. Objective: This study aimed to establish a progressive strategy integrating cell model construction, monomer evaluation, and effective component group-based drug discovery for the development of novel therapeutics targeting AD. Methods: A novel AD12 cell line stably expressing the double-transgenic genes amyloid precursor protein (APP)695/presenilin 1(PS1)-ΔE9 was first constructed and subjected to lipopolysaccharide (LPS) stimulation. The resulting LPS-induced neuroinflammatory response was characterized using metabolomic analysis. Subsequently, 16 alkaloids derived from traditional Chinese medicine(TCM) were screened with the LPS-AD12 cell model. Molecular docking was then performed to assess the binding affinity of benzoylaconitine (BAC) with APP and PS1 proteins. A targeted metabolomics approach focusing on amino acids and the tricarboxylic acid (TCA) cycle was applied to BAC-treated LPS-AD12 cells. Finally, aconite extract was administered to five-familial-AD-mutations(5xFAD) transgenic mice, and therapeutic efficacy was evaluated through phenotypic and metabolomic analyses. Results: LPS stimulation induced neuroinflammation in AD12 cells, characterized by elevated levels of interleukin-6, amyloid-β (Aβ ), and PS1. The primary metabolic pathways affected in AD12 cells included alanine, aspartate, and glutamate metabolism, as well as arginine biosynthesis. Notably, BAC significantly reduced the levels of Aβ and interleukin-6 in LPS-AD12 cells. Furthermore, molecular docking analyses revealed a strong binding affinity of BAC with APP and PS1 proteins. Targeted metabolomics analysis indicated that the pharmacological activity of BAC was primarily associated with its anti-inflammatory effects, modulation of the cholinergic signaling pathway, and regulation of energy metabolism. Behavioral experiments in 5xFAD mice, together with immunofluorescence assessments of brain tissues (amyloid-β, glial fibrillary acidic protein, and ionized calcium-binding adapter molecule 1), demonstrated that aconite extract treatment significantly alleviated AD-related symptoms. In addition, metabolomics-based mechanistic analyses revealed that serine, acetylcholine, ornithine, and gamma-aminobutyric acid exhibited consistent trends in both brain tissue and serum samples from treated mice. Conclusion: This study established a novel AD12 cell model and an effective, reliable LPS-induced cell-based screening system. Additionally, we proposed a new drug discovery strategy integrating cell model construction, monomer evaluation, and effective component group-based drug discovery. This screening system has the potential to accelerate the identification of anti-AD agents and provides a feasible framework for subsequent in-depth investigations into new drug development from TCM, thereby contributing to the modernization of TCM-derived therapeutics.