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.

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.

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.

OBJECTIVE To provide reference for medication therapy management （MTM） of diabetic patients complicated with cardiovascular disease. METHODS A 63-year-old male diabetic patient who suffered from temporary headache every morning after percutaneous coronary intervention （PCI） visited the neurology department of our hospital， and then was recommended to the pharmaceutical outpatient department. The pharmacists thought that the patient’s symptoms of headache， severe constipation and hyperuricemia were more likely induced by the medication used. The pharmacists further found that his atherosclerotic cardiovascular disease （ASCVD） influencing factors such as blood pressure， heart rate， blood glucose and blood lipids did not reach standard. The pharmacists provided MTM services for the patient through pharmacy inquiry and adverse drug reactions judgement， medication evaluation， medication reconciliation， medication education and pharmacy follow-up. RESULTS Through fifteen MTM services for thirteen weeks， the pharmacists reconciliated and optimized the medication therapy plan， discontinued the use of Isosorbide mononitrate sustained-release tablets， Nifedipine controlled-release tablets， and Indapamide tablets， which caused adverse drug reactions； the number of drugs was adjusted from fifteen to seven， and the symptom of headache disappeared； severe constipation had also been significantly improved， and hyperuricemia dropped to normal range. The ASCVD influencing factors of blood pressure， heart rate， fasting plasma glucose， glycosylated hemoglobin， low-density lipoprotein cholesterol and uric acid were reduced from ＞140/90 mmHg（1 mmHg＝0.133 kPa）， 70-80 beats per minute， 7.71 mmol/L， 7.2%， 2.13 mmol/L and 494 μmol/L before MTM services to ＜130/80 mmHg， 55-60 beats per minute， 6.22 mmol/L， 6.3%， 1.55 mmol/L and 348 μmol/L after MTM services. CONCLUSIONS The pharmacists providing MTM services to the patients can improve their quality of life and therapeutic efficacy， reduce medication risks， and enhance the level of rational drug use in hospitals and pharmaceutical service capabilities.

Glaucocalyxin A （GLA） is a natural diterpenoid extracted from Isodon amethystoides belonging to Labiatae. Modern pharmacological research has shown that GLA has anti-inflammatory， anti-tumor， anti-fibrotic， osteoporosis-ameliorating， and cardiovascular system-protecting activities and good biosafety. However， the low content in plants， poor solubility， high metabolic rate， and low bioavailability limit the application of GLA. To address these issues， researchers have studied the total synthesis， structural modification， and nanomedicine development of GLA. By reviewing the available studies about GLA in the past five years， we summarize the research progress in the total synthesis， pharmacological activities and mechanisms， and in vivo metabolic transformation， aiming to provide a theoretical basis for clarifying the specific mechanisms underlying the pharmacological activities of GLA and for further research， development， and clinical applications of GLA.

Hepatocellular carcinoma （HCC） is the sixth most common cancer in the world. In recent years， the clinical early diagnosis and treatment protocols of HCC have been improved， whereas the prognosis of patients is still not satisfactory， which is due to the fact that the mechanism of HCC development has not been fully elucidated. Therefore， it is of great significance to explore the molecular mechanisms and key regulatory links of hepatocellular carcinoma development to further improve the diagnosis and treatment of HCC in China. Epigenetics has become a research hotspot because of its reversibility and easy regulation. According to relevant studies， HCC involves the accumulation of multiple genetic and epigenetic changes during the initiation， promotion， and progression stages. HCC is categorized as infantile malnutrition with accumulation， hypochondriac pain， tympan ites， and abdominal mass in traditional Chinese medicine （TCM）. In the treatment of HCC， TCM with low toxicity， multi-targets， and multi-mechanisms can inhibit tumor growth， alleviate the clinical symptoms， and enhance the quality of life of the patients. Chinese medicines and their active ingredients exert anti-HCC effects through epigenetic regulation of DNA methylation， histone modification， and non-coding RNA. Abnormal gene expression due to epigenetic regulation disorders is involved in all stages of HCC development. There are few studies on epigenetic regulation in TCM treatment of HCC， and there is still much room for development in basic and clinical trials. This paper reviews the mechanism of epigenetic regulation in HCC and summarizes the experimental results of TCM research on the related mechanism， with a view to providing a theoretical basis for future research on the mechanism of HCC development and clinical diagnosis and treatment of hepatocellular carcinoma with TCM.