OBJECTIVE To screen and quantitatively analyze the quality marker （Q-Marker） associated with anti-renal fibrosis in Shenqi shenshuai mixture （SQSS）， so as to provide references for the analysis of pharmacodynamic substances and new drug transformation of SQSS. METHODS The chemical components of SQSS were characterized by untargeted metabolomics. Combined with network pharmacology， gene expression omnibus （GEO） and connectivity map （CMAP） databases， the anti-renal fibrosis Q-Markers of SQSS were screened. HPLC-MS/MS was applied to determine the contents of Q-Markers in 10 batches of SQSS. RESULTS A total of 1 319 compounds were identified from SQSS via untargeted metabolomics，and 84 active ingredients with anti-renal fibrosis activity were further screened out， such as formononetin. Nine anti-renal fibrosis Q-Markers were obtained by network pharmacology and GEO database， including berberine， quercetin， honokiol， nicotinamide， daidzein， coumarin， kaempferol， formononetin and amygdalin. The quantitative results showed that the average contents of the above components （excluding amygdalin） in 10 batches of SQSS were 2.523， 1.942， 26.848， 1.415， 0.692， 0.171， 0.374， 7.401 μg/mL， respectively. CONCLUSIONS Nine anti-renal fibrosis Q-Markers of SQSS were screened in this study， and the contents of eight among them were determined. The results can provide a basis for elucidating the pharmacodynamic material basis and promoting the new drug transformation of SQSS.

Liver cancer is one of the world's serious diseases today because of its high frequency and fatality rate, genetic differences, and limited effectiveness of late-stage therapy. Although chemotherapy, targeted therapy, immunotherapy, ablation and transarterial chemoembolisation (TACE) have improved the disease control of some patients, recurrence and acquired resistance are still common, especially for tumors that are hypoxic, nutrient-deprived, acidic-stressed, vascularly insufficient and exposed to repeated drug pressure. A bad environment will cause a change in the quality-control system and metabolism of cancer cells, and as a result, lysosomes have started to alter. In addition to the above catabolic functions of lysosomes, they also take part in autophagic flux, substrate recycling, iron and lipid metabolism, nutrient sensing, drug distribution, membrane repair and cell death signalling. Under the stress of therapy in liver cancer cells, increased lysosomal acidification and enhanced terminal degradation lead to prolonged autophagy; TFEB/TFE3 promotes the formation of new lysosomes and lysophagosomes to sequester weakly basic drugs, thereby reducing the concentration of active drugs and mitigating proteotoxicity and oxidative stress to promote cell survival. The above processes produce a lysosome-dependent resistant phenotype that is particularly relevant to sorafenib and doxorubicin and other drugs whose effectiveness can be reduced by protective autophagy or changes in intracellular location. Conversely, the same dependency on lysosomal homeostasis is also a vulnerability. Natural products and monomeric compounds derived from Chinese herbal medicines have various structures, multiple target regulation capabilities, and the potential to act on several lysosome-related nodes simultaneously. Based on the evidence in this review, it is believed that such compounds may sensitise liver cancer cells by inhibiting V-ATPase-mediated acid hydrolysis, obstructing late-stage autophagy-mediated degradation, disrupting lysosomal calcium or membrane homeostasis, causing lysosomal membrane permeabilisation, reducing compensatory lysosomal biogenesis, promoting ferritin degradation and ferroptosis, or enhancing acid-responsive intracellular delivery. Agents that impair lysosomal function and protective autophagy, compounds that convert enlarged or drug-sequestering lysosomes into lethal targets, and nanodelivery systems that exploit the acidic environment of endolysosomes to co-deliver natural products with chemotherapeutic drugs are examples. Lysosome-targeted intervention will have different effects under different circumstances; for example, inhibiting autophagy may result in an increase in cytotoxic stress in some areas, whereas overstimulation of autophagy or iron release from lysosomes may induce autophagic cell death or ferroptosis in other areas. Therefore, the design of therapy should take into account the status of the tumour microenvironment, autophagic flux, lysosomal pH, TFEB/TFE3 activity, drug sequestration capacity, ferroptosis sensitivity, dosing sequence and delivery route. This review systematically examines the lysosomal homeostasis in the microenvironment of liver cancer, the mechanisms through which lysosomal adaptation contributes to chemoresistance, and the rationale for combining natural products with standard agents such as sorafenib and doxorubicin. Based on basic lysosome biology, pharmacodynamic and delivery data have also been collected; as a result, some applications for future studies have been proposed, such as dynamic monitoring of autophagy flux, in vivo spatial measurements of lysosomal functions, rational optimisation of combination therapy timings, and safety assessments in immunocompetent liver cancer models prior to clinical translation. Translation difficulties are also evident, such as insufficient tumour selectivity, pharmacokinetic limitations, compensatory lysosomal regeneration, toxicity to normal liver and immune cells, and a lack of validated predictive biomarkers. A new way will be found to use biomarkers to divide the patient group, optimize nanoparticles for better delivery, design specific schedules for combined treatments based on the problem they cause within the cell, etc., thereby overcoming drug resistance and reducing the harm patients suffer from toxic treatments. This system can help select biomarkers and rational drug pairs for the next round of lysosome-centred precision trials.

OBJECTIVE To screen and quantitatively analyze the quality marker （Q-Marker） associated with anti-renal fibrosis in Shenqi shenshuai mixture （SQSS）， so as to provide references for the analysis of pharmacodynamic substances and new drug transformation of SQSS. METHODS The chemical components of SQSS were characterized by untargeted metabolomics. Combined with network pharmacology， gene expression omnibus （GEO） and connectivity map （CMAP） databases， the anti-renal fibrosis Q-Markers of SQSS were screened. HPLC-MS/MS was applied to determine the contents of Q-Markers in 10 batches of SQSS. RESULTS A total of 1 319 compounds were identified from SQSS via untargeted metabolomics，and 84 active ingredients with anti-renal fibrosis activity were further screened out， such as formononetin. Nine anti-renal fibrosis Q-Markers were obtained by network pharmacology and GEO database， including berberine， quercetin， honokiol， nicotinamide， daidzein， coumarin， kaempferol， formononetin and amygdalin. The quantitative results showed that the average contents of the above components （excluding amygdalin） in 10 batches of SQSS were 2.523， 1.942， 26.848， 1.415， 0.692， 0.171， 0.374， 7.401 μg/mL， respectively. CONCLUSIONS Nine anti-renal fibrosis Q-Markers of SQSS were screened in this study， and the contents of eight among them were determined. The results can provide a basis for elucidating the pharmacodynamic material basis and promoting the new drug transformation of SQSS.

Generative artificial intelligence(Gen-AI), an important branch of artificial intelligence(AI), has attracted increasing attention in medical image analysis and clinical decision support.Different from traditional discriminative models, Gen-AI can generate high-quality and diverse new data by learning the underlying distribution features of data. It exhibits unique advantages in alleviating insufficient training samples, mitigating uneven data distribution, and improving the generalization ability of models. Ophthalmology is highly dependent on multimodal imaging, making it a particularly suitable field for the application of Gen-AI. This review summarizes recent advances in major Gen-AI techniques, including generative adversarial networks, diffusion models, and large language models, and discusses their applications in ophthalmic disease screening and diagnosis, image synthesis and data augmentation, prognostic prediction, and individualized treatment planning. It also analyzes challenges in the course of clinical translation, including data quality, model credibility, ethical supervision and other issues, so as to provide references for its standardized application.

ObjectiveTo identify protein biomarkers and potential therapeutic targets associated with metabolic dysfunction-associated fatty liver disease （MAFLD） through an integrative multi-omics analysis. MethodsLarge-scale plasma protein quantitative trait locus data were integrated with MAFLD genome-wide association study data， and a proteome-wide Mendelian randomization analysis was performed. Summary data-based Mendelian Randomization （SMR）/heterogeneity in dependent instruments （HEIDI） test and colocalization analysis were used to assess significant proteins. The independent samples t-test was used for comparison of continuous data with homogeneity of variance between two groups， and the Welch-corrected t-test was used for comparison of continuous data with heterogeneity of variance. The transcriptomic validation results were compared with the Mendelian randomization results to evaluate the changing trends of gene expression， and boxplots were used to display the expression distribution of candidate genes between groups. ResultsAmong 7 130 proteins analyzed， 40 showed a causal relationship with MAFLD， among which 26 increased the risk of MAFLD and 14 exerted a protective effect against MAFLD （FDR<0.05）. Nine proteins were supported by SMR/HEIDI （P_SMR<0.05， P_HEIDI>0.05）， and 14 showed a strong colocalization signal （PPH₄>0.9）. The transcriptomic analysis identified 5 differentially expressed proteins （all P<0.05）， i.e.， adenosine diphosphate-ribosylation factor-like GTPase 2， insulin-like growth factor binding protein 2， casein kinase 1 delta （CSNK1D）， leucine-rich repeat neuronal 1， and moesin （MSN）. In vitro validation showed upregulated expression levels of MSN （1.612±0.346 vs 0.569±0.077， P<0.05）， 14-3-3 protein theta （YWHAQ） （1.267±0.126 vs 0.313±0.029， P<0.05）， and CSNK1D （0.871±0.025 vs 0.431±0.080， P<0.05） and a downregulated expression level of histone deacetylase 8 （0.637±0.059 vs 1.097±0.260， P<0.05） in the MAFLD cell model. Functional annotation showed that CSNK1D participated in circadian and metabolic regulation， YWHAQ modulated the Hippo pathway and lipid signal transduction， and MSN was associated with cytoskeletal remodeling and fibrogenic responses. ConclusionThe integrative proteogenomic analysis in this study shows that CSNK1D， YWHAQ， and MSN may be key mediators in the pathogenesis of MAFLD. These proteins have the potential to serve as novel biomarkers and therapeutic targets， providing new directions for research on disease mechanisms and the development of intervention strategies.

Objective:To investigate the clinical manifestations, pathological features, and genetic variant characteristics of children with glycogen storage disease type Ⅸa (GSD Ⅸa).Methods:A retrospective case series analysis was conducted to collected and analyzed the medical history, biochemical markers, liver ultrasound results, liver histopathological findings, genotypes, treatment regimens, and follow-up data of 4 pediatric patients diagnosed with GSD IXa in the Department of Infectious Diseases at Xiamen Children′s Hospital from January 2018 to May 2024. All patients were confirmed by genetic testing.Results:All 4 pediatric patients diagnosed with GSD Ⅸa were male. The ages of onset were 8 months, 2 years, 3 years and 3 months, 1 year and 5 months, respectively, with initial presentations including chronic diarrhea (Case 1), incidentally detected transaminase elevation during routine examinations (Cases 2 and 3), and delayed motor development (Case 4). Diagnosis was confirmed at ages 10 months, 3 years, 3 years 4 months and 1 year 6 months, respectively.At diagnosis, anthropometric parameters and biochemical profiles revealed:Height: 68 cm (< P3), 96 cm ( P25-50), 94 cm ( P3-10), and 94 cm ( P3-10).Weight: 7 kg (< P3), 17 kg ( P90-97), 14.4 kg ( P25-50), and 10.5 kg ( P25-50).Alanine aminotransferase: 299, 500, 271, and 313 U/L (reference range 0-40 U/L).Aspartate aminotransferase: 285, 543, 337 and 357 U/L (reference range 0-40 U/L).Fasting glucose: 2.80, 3.67, 2.98, and 3.66 mmol/L (reference range 3.90-6.10 mmol/L).Lactate: 4.3, 2.1, 1.3, and 2.6 mmol/L (reference range 0.5-2.2 mmol/L).Triglycerides: 5.22, 1.38, 1.32, and 1.88 mmol/L (reference range 0.56-1.70 mmol/L).Case 1 exhibited poor adherence to uncooked cornstarch therapy during initial treatment, with no significant improvement in biochemical parameters. Follow-up imaging at age 4 revealed hepatic adenoma. Subsequent improvement in therapeutic compliance led to biochemical normalization, reduced hepatic adenoma size, and growth parameters of 113 cm ( P10-25) and 26 kg ( P90-97) at 6 years 2 months. Cases 2-4 demonstrated biochemical improvement with regular uncooked cornstarch therapy and no evidence of hepatic adenoma.Liver histopathology in Cases 1-3 confirmed glycogen accumulation consistent with GSD, without cirrhotic changes. Genetic analysis identified PHKA2 variations in all cases: 2 missense variants, 1 frameshift variant and 1 nonsense variant. The c.2839dup and c.3267G>A variants represent novel pathogenic mutations. Conclusions:GSD Ⅸa in pediatric patients is predominantly characterized by hepatomegaly, hepatic dysfunction, and hypoglycemia. While uncooked cornstarch therapy typically yields favorable prognoses, a subset of patients may develop hepatic adenomas. Notably, children with hepatic adenoma exhibited younger age of onset, significant growth retardation, and more severe metabolic disturbances, suggesting that hepatic adenoma development may be closely linked to the severity of metabolic dysregulation.

Objective:This study aimed to evaluate the value of CT-based radiomics machine learning models in predicting spread through air spaces(STAS)in lung adenocarcinoma(LUAD)and to determine the optimal peritumoral analysis region.Methods:Data from 378 pa-tients who underwent non-small cell lung cancer surgery at Zhejiang Cancer Hospital between January 2013 to January 2017 were retro-spectively analyzed.Logistic regression,random forest,and XGBoost models were constructed using regions extending 0,3,6,9,and 12 mm outward from the tumor margin.Results:The XGBoost model using the 6 mm peritumoral region performed best on the test set,with an AUC-ROC of 0.855(95%CI:0.756-0.950),followed by the XGBoost model using the 9 mm region.Decision curve analysis(DCA)indicated that the XGBoost models for the 6 mm and 9 mm regions had higher net clinical benefits.Feature analysis revealed that some wavelet trans-form features significantly contributed to STAS prediction.Conclusions:This preliminary study suggests that CT-based radiomics machine learning models have predictive value for STAS.The XGBoost model based on the 6 mm peritumoral region demonstrated the best perform-ance,and holds promise in assisting preoperative assessment.

Arsenic is a semi-metal,and lipid-soluble arsenic compounds are one of the widespread forms in the environment and food chain,but there is a lack of standards for lipid-soluble arsenic compounds,which is one of the bottlenecks in the current analytical detection and toxicological studies of organic arsenic.In this study,four saturated arsenic-containing hydrocarbons,AsHC 318,AsHC 332,AsHC 346,and AsHC 374(The number is relative molecular mass),were successfully synthesized in three steps by using dimethylarsinic acid,potassium iodide,sodium hydroxide,and four brominated alkanes(1-Bromotetradecane,1-bromopentadecane,1-bromohexadecane,and 1-bromooctadecane)as raw materials.The structures of these four saturated arsenic-containing hydrocarbons were characterized by proton nuclear magnetic resonance(1H NMR)spectroscopy,13C nuclear magnetic resonance(13C NMR)spectroscopy,and high-resolution mass spectrometry(HR-MS).The yields of the method were 8%-10%,and the synthesized compounds could be used in subsequent toxicity evaluation experiments to assess the toxic effects and mechanisms of action of arsenic-containing hydrocarbons.This study provided an effective method for synthesis of arsenic-containing hydrocarbons,enriching the synthesis methods of arsenic-containing hydrocarbons,and provided raw materials for the subsequent toxicological studies of arsenic-containing hydrocarbons.

A 12-year-old boy was admitted with symptoms of cough and fever lasting over a month, accompanied by weight loss 2 kg. Prior anti-infective treatments proved ineffective in alleviating the symptoms. Chest imaging revealed diffuse interstitial pulmonary edema in the right lung with obstructed lymphatic drainage. Combined with histopathological examinations, the diagnosis was confirmed as lung cancer with pulmonary lymphangitic carcinomatosis. The patient underwent chemotherapy with docetaxel and carboplatin, yet the disease progressively worsened, resulting in death three months after diagnosis. This case highlights lung cancer should not be overlooked in patients with persistent respiratory symptoms of unknown etiology. Early imaging examinations, along with necessary pathological evaluations, are crucial for timely detection and diagnosis. The presence of pulmonary lymphangitic carcinomatosis often indicates an advanced-stage of cancer, associated with a poor prognosis.
Humans ; Male ; Lung Neoplasms/complications* ; Child ; Carcinoma/drug therapy*

Research in photodynamic therapy (PDT) primarily focuses on enhancing light penetration depth, improving oxygen supply, and optimizing photosensitizer delivery. Notably, the delivery efficiency of the photosensitizer is crucial for therapeutic efficacy. Carboxyl-substituted phthalocyanines, as important photosensitizing molecules, possess unique chemical modification sites that enable direct targeted delivery or integration into diverse delivery systems. Their synthesis predominantly employs mixed- or cross-condensation, selective synthesis, and axial modification strategies to introduce carboxyl groups. However, their inherent hydrophobicity significantly hinders effective delivery. To address this limitation, modifications with peptides or quaternary ammonium salt derivatives may facilitate precise delivery to tumor cells and pathogens. With advances in nanotechnology, carboxyl-substituted phthalocyanines can serve as key photosensitizer modules, effectively integrated into nanomaterials such as biomacromolecules, inorganic metals, and polymers for both active and passive delivery. Recently, researchers have exploited the π-π stacking and other intermolecular forces among carboxyl-substituted phthalocyanine molecules to drive their self-assembly into nano-micelles, enabling carrier-free delivery or co-delivery with other therapeutic agents for synergistic effects. This review systematically outlines the synthesis strategies for carboxyl-substituted phthalo-cyanines. Taking mono-carboxyl-substituted zinc phthalocyanine as a model molecule, the performance of three delivery modalities were compared: single-molecule targeted delivery, nanocarrier-encapsulated delivery, and carrier-free self-assembled delivery, in terms of PDT efficacy, biocompatibility, and imaging-guided tracing capabilities, to provide a systematic technical framework for the rational design of novel modular photosensitizers and to advance the clinical translation of PDT in precision oncology and anti-infective therapy.
Photochemotherapy/methods* ; Indoles/administration & dosage* ; Isoindoles ; Photosensitizing Agents/administration & dosage* ; Drug Delivery Systems ; Humans