ObjectiveTo analyze the pharmacodynamic substance basis of Shangkeling Spray and its potential mechanisms in intervening knee osteoarthritis （KOA） using ultra-performance liquid chromatography-tandem mass spectrometry （UPLC-MS）， network pharmacology， and molecular docking technology. MethodsUPLC-MS was used to identify the chemical components of Shangkeling Spray. Pharmacokinetic properties were employed to screen potential active ingredients. Network pharmacology methods were utilized to collect potential targets of these ingredients and the pathological gene set of KOA. An "active ingredient-disease" target network was constructed using databases such as STRING. Gene Ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） functional enrichment analyses were performed using clusterProfiler. Libraries including NumPy were employed to calculate shortest path lengths to identify dominant pharmacodynamic links. Core gene clusters were identified using MCODE， validated through the Gene Expression Omnibus （GEO） database， and molecular docking was performed between key active ingredients and core targets. ResultsA total of 322 and 314 chemical components were identified under positive and negative ion modes， respectively， with 410 components in total after de-duplication， mainly including flavonoids， coumarins， terpenoids， organic acids， and alkaloids. Analysis of the "active ingredient-disease" network identified "development and regeneration"， "cell growth and death"， "immune system"， and "nervous system" as the dominant pharmacodynamic links of Shangkeling Spray in the treatment of KOA. Molecular docking showed that key active ingredients， such as bletillin A， formononetin， morin， oxymatrine， aconitine， gallic acid， curdione， apigenin， naringenin， and oleanolic acid， tightly bound to functional domains of 10 key targets including Jun proteins（JUN）， interleukin-6 （IL-6）， protein kinase B1 （Akt1）， Caspase-3， nuclear transcription factor-κB subunit p65（RELA）， nuclear factor-kappaB1（NF-κB1）， Cyclin D₁， mammalian target of rapamycin（mTOR）， tumor necrosis factor （TNF）， and Fos proto-oncogene protein （FOS）. These interactions synergistically regulated the phosphatidylinositol 3-kinase （PI3K）/Akt/mTOR-related signaling axis and nervous system-related pathways， mediating cartilage repair， reducing inflammation and pain， and improving KOA. ConclusionThis study preliminarily clarifies the pharmacodynamic substance basis of Shangkeling Spray and suggests that its main active ingredients may improve KOA by synergistically regulating the PI3K/Akt/mTOR-related pathways， providing a reference for subsequent exploration of its substance benchmark and mechanism of action.

Background and aims:Environmental pollutants,particularly organochlorine insecticides like endosulfan(ENDO),are increasingly linked to liver toxicity and related diseases.Despite its widespread historical use,the mechanisms underlying ENDO-induced liver damage remain poorly understood.This study aims to elucidate the cellular and molecular mechanisms of ENDO-induced hepatotoxicity.Methods:C57BL/6 mice were exposed to ENDO for two weeks.Single-cell RNA sequencing(scRNA-seq)was subsequently performed on mouse livers to explore ENDO-induced hepatotoxicity at the single-cell level.Differentially expressed genes(DEGs)across cell types and treatments were identified and then subjected to pathway enrichment to uncover key biological processes affected by ENDO.Transcription factor(TF)regulatory network,pseudotime trajectory,and cellular communication analysis were used to explore the molecular and cellular changes after ENDO exposure.Results:ENDO not only caused direct hepatocyte injury but also activated hepatic stellate cells and lymphocytes,triggering inflammatory responses with upregulation of multiple key chemokines and cytotoxic genes.Additionally,ENDO exposure led to the recruitment and activation of myeloid cells,contributing to the inflammatory milieu.An increase in intercellular communication and changes to the hepatic microenvironment,especially the interaction between activated hepatic stellate cells and CD8+T cells were observed,further implicating these processes in ENDO-induced liver damage.Conclusions:This study provides new insights into the cellular and molecular mechanisms underlying liver injury induced by organochlorine insecticides like ENDO.Key genes and pathways involved in ENDO-associated liver toxicity have been identified at a single-cell resolution.These findings suggest that altered cellular communications and inflammatory responses may play pivotal roles in the pathogenesis of ENDO-induced liver injury.

Gastrointestinal (GI) cancers are a leading cause of cancer morbidity and mortality worldwide. Despite advances in treatment, cancer relapse remains a significant challenge, necessitating novel therapeutic strategies. In this study, we engineered nanobody-based chimeric antigen receptor (CAR) natural killer (NK) cells targeting cadherin 17 (CDH17) for the treatment of GI tumors. In addition, to enhance the efficacy of CAR-NK cells, we also incorporated CV1, a CD47-SIRPα axis inhibitor, to evaluate the anti-tumor effect of this combination. We found that CDH17-CAR-NK cells effectively eliminated GI cancers cells in a CDH17-dependent manner. CDH17-CAR-NK cells also exhibit potent in vivo anti-tumor effects in cancer cell-derived xenograft and patient-derived xenograft mouse models. Additionally, the anti-tumor activity of CDH17-CAR-NK cells is synergistically enhanced by CD47-signal regulatory protein α (SIRPα) axis inhibitor CV1, likely through augmented macrophages activation and an increase in M1-phenotype macrophages in the tumor microenvironment. Collectively, our findings suggest that CDH17-targeting CAR-NK cells are a promising strategy for GI cancers. The combination of CDH17-CAR-NK cells with CV1 emerges as a potential combinatorial approach to overcome the limitations of CAR-NK therapy. Further investigations are warranted to speed up the clinical translation of these findings.

Photodynamic immunotherapy is a promising strategy for cancer treatment. However, the dysfunctional tumor vasculature results in tumor hypoxia and the low efficiency of drug delivery, which in turn restricts the anticancer effect of photodynamic immunotherapy. In this study, we designed photosensitive lipid nanoparticles. The synthesized PFBT@Rox Lip nanoparticles could produce type I/II reactive oxygen species (ROS) by electron or energy transfer through PFBT under light irradiation. Moreover, this nanosystem could alleviate tumor hypoxia and promote vascular normalization through Roxadustat. Upon irradiation with white light, the ROS produced by PFBT@Rox Lip nanoparticles in situ dysregulated calcium homeostasis and triggered endoplasmic reticulum stress, which further promoted the release of damage-associated molecular patterns, enhanced antigen presentation, and stimulated an effective adaptive immune response, ultimately priming the tumor microenvironment (TME) together with the hypoxia alleviation and vessel normalization by Roxadustat. Indeed, in vivo results indicated that PFBT@Rox Lip nanoparticles promoted M1 polarization of tumor-associated macrophages, recruited more natural killer cells, and augmented infiltration of T cells, thereby leading to efficient photodynamic immunotherapy and potentiating the anti-primary and metastatic tumor efficacy of PD-1 antibody. Collectively, photodynamic immunotherapy with PFBT@Rox Lip nanoparticles efficiently program TME through the induction of immunogenicity and oxygenation, and effectively suppress tumor growth through immunogenic cell death and enhanced anti-tumor immunity.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Objective We aimed to investigate the effect of ferroptosis on Shenling Baizhu Powder,a compound prescription of Chinese herbal medicine,in improving testicular spermatogenic function in hyperuricemic mice with spermatogenic dysfunction. Methods Sixty BALB/c mice were randomly divided into normal group,model group,Shenling Baizhu Powder high-,medium-,and low-dose groups (20.14,10.07,5.04 g/kg,by gavage),and ferrostatin-1(Fer-1) group (0.8 mg/kg,by tail vein injection),with 10 mice each group. Except for the normal group,the other groups were intraperitoneally injected with potassium oxonate suspension[600mg/(kg·d)]for 7 days to establish the hyperuricemic model,and then the corresponding intervention was given for consecutive 14 days. Content of serum uric acid (UA),testicular Fe2+,reduced glutathione (GSH),malondialdehyde (MDA) and superoxide dismutase (SOD) activity were detected by biochemical method. Epididymal and testicular indices were measured. The spermatogenic function of testes was evaluated by eosin-hematoxylin staining. Sperm quality was detected by an automatic animal sperm analyzer. Prussian blue staining was used to detect iron deposition in testicular tissue. Immunohistochemistry was used to detect the related protein expressions of acyl-coenzyme A synthetase long-chain family member 4 (ACSL4) and glutathione peroxidase 4 (GPX4) in testicular tissue. Western blotting was used to detect the related protein expression levels of nuclear factor erythroid 2-related factor 2 (Nrf2)/heme oxygenase-1(HO-1)/GPX4 signaling pathway in testicular tissue. Results Compared with the normal group,the contents of serum UA,MDA,and Fe2+in the testis tissue of the model group were increased,the GSH content and SOD activity were decreased,the epididymal and testicular index,testicular spermatogenic function,sperm density and activity rate were decreased,and the iron deposition and ACSL4 protein expression in the testis tissue were increased. The expressions of kelch-like ECH-associated protein-1 (Keap1) and Nrf2 were increased. The expressions of nuclear Nrf2,HO-1,GPX4,and recombinant solute carrier family 7 member 11 (SLC7A11) protein were decreased (P<0.01). Compared with the model group,the above indexes in the Shenling Baizhu Powder groups and the Fer-1 group were improved to varying degrees (P<0.05,P<0.01). Conclusion Shenling Baizhu Powder can inhibit the ferroptosis of testicular cells through the Nrf2/HO-1/GPX4 signaling pathway,and improve the testicular spermatogenic function of mice with hyperuricemia spermatogenic dysfunction.

OBJECTIVES: Shear wave elastography (SWE) is a novel quantitative elastography technique that can assess the hardness of different tissues. This study introduces a novel shear wave parameter-frequency of mass characteristic (f_mass)-and investigates its correlation, along with other shear wave parameters, with the histopathological features and immunohistochemical (IHC) biomarkers of invasive breast cancer (IBC). The study aims to explore whether SWE can provide useful information for IBC treatment and prognosis. METHODS: With the pathological results as the gold standard, 258 malignant breast lesions were collected, and all patients underwent conventional ultrasound and SWE examinations. The SWE parameters [maximum elastic value (E_max), minimum elastic value (E_min), mean elastic value (E_mean), standard deviation of elastic value of the whole lesion (E_sd)] and f_mass] in the transverse and longitudinal orthogonal sections were measured, and their correlations with the prognostic factors of IBC [including tumor diameters, axillary lymph node (ALN) metastasis, lymphatic vessel invasion (LVI), calcification, histological type, histological grade, and IHC biomarkers (ER, PR, HER-2, Ki-67), and molecular subtypes] were analyzed. The correlations between the SWE parameters of the transverse and longitudinal sections of the tumors with different prognostic factors and the above indicators were analyzed. At the same time, the receiver operating characteristic (ROC) curve was used to analyze the efficacy of f_mass in predicting ER and PR expression. RESULTS: E_mean, E_max, E_sd, and f_mass were correlated with tumor diameters; E_mean, E_max and E_sd were correlated with histological types and histological grades. E_max and E_sd were correlated with ALN metastasis, LVI and pathological types. In the IHC biomarker-labeled masses, f_mass was correlated with ER and PR (both P<0.05), and E_mean, E_max, and E_sd were correlated with HER-2 and Ki-67 (all P<0.05). E_mean, E_max, and f_mass were all correlated with breast cancer subtypes (all P<0.05), and E_mean and E_max were higher in Luminal B [HER-2(+)] breast cancer, while f_mass was lower in HER-2(+) and triple-negative breast cancer. Among the statistically significant prognostic factors, the P values of the transverse sections of the masses were all less than or equal to those of the longitudinal sections. The AUC of f_mass in the transverse sections of the masses for predicting ER and PR expression were 0.73 (95% CI 0.65 to 0.80) and 0.67 (95% CI 0.60 to 0.74), respectively, with the optimal cut-off values being 76.50 and 60.66, the sensitivities being 72.45% and 81.98%, the specificities being 66.13% and 45.35%, and the accuracies being 70.93% and 69.77%, respectively. The AUC of f_mass in the longitudinal sections of the masses for predicting ER and PR expression were 0.74 (95% CI 0.67 to 0.81) and 0.65 (95% CI 0.58 to 0.72), respectively, with the optimal cut-off values being 131.8 and 137.5, the sensitivities being 69.90% and 66.28%, the specificities being 72.58% and 60.47%, and the accuracies being 70.54% and 64.34%, respectively. The f_mass in the transverse sections of the masses was more statistically significant. CONCLUSIONS The poor prognosis factors of IBC are related to high E_mean, E_min, E_max, E_sd, and low f_mass. The f_mass can predict the expression of ER and PR, and the transverse cut data are more meaningful. SWE is helpful for predicting the invasiveness of IBC.
Humans ; Breast Neoplasms/metabolism* ; Female ; Elasticity Imaging Techniques/methods* ; Biomarkers, Tumor/metabolism* ; Middle Aged ; Adult ; Prognosis ; Immunohistochemistry ; Neoplasm Invasiveness ; Receptor, ErbB-2/metabolism* ; Aged ; Lymphatic Metastasis ; Receptors, Estrogen/metabolism* ; Receptors, Progesterone/metabolism* ; Ki-67 Antigen/metabolism*