BACKGROUND:Macrophage polarization plays a key role in chronic inflammatory joint diseases such as rheumatoid arthritis.Cerium dioxide(CeO2)nanoparticles have a wide range of biomedical applications such as modulating the local inflammatory microenvironment of tissues.OBJECTIVE:To investigate the role of CeO2 nanoparticles on macrophage polarization and inflammatory factor expression,as well as inflammatory modulation in a co-culture system of macrophages and fibroblasts.METHODS:(1)CeO2 nanoparticles were dispersed and observed morphologically by transmission electron microscopy.(2)Human leukemia monocytes(THP-1)were induced to differentiate and establish the M1 macrophage pro-inflammatory cell model of rheumatoid arthritis.The cells were divided into M0 group(undifferentiated macrophages),M1 group(successful macrophage modeling),CeO2 nanoparticle treatment group(M1 group with CeO2 nanoparticle treatment),and dexamethasone control group(M1 group with dexamethasone treatment)and incubated for 48 hours.The effects of CeO2 nanoparticles on the expression of inflammatory factors(endogenous nitric oxide synthase,CD86,CD80)in M1 macrophages and M1 macrophage phenotype(CD80,CD206)were detected by RT-qPCR,western blot assay,and flow cytometry.(3)A co-culture system of macrophages and fibroblasts was established,and CeO2 nanoparticles acted on the upper macrophages.The regulation of CeO2 nanoparticles on the expression of inflammatory factors(interleukin-6,tumor necrosis factor-α,cyclooxygenase-2,and endogenous nitric oxide synthase)of fibroblasts in the co-culture system was observed at the mRNA and protein levels.RESULTS AND CONCLUSION:(1)Transmission electron microscopy showed that the diameter of CeO2 nanoparticles was(19.5±2.0)nm.(2)Compared with the M0 group,the mRNA of endogenous nitric oxide synthase and CD86,and the protein expression of endogenous nitric oxide synthase and CD80 in the M1 group were upregulated.Compared with the M1 group,the mRNA expression of endogenous nitric oxide synthase and CD86,and the protein expression of endogenous nitric oxide synthase and CD80 in the CeO2 nanoparticle treatment group were downregulated.Flow cytometry showed that 20 nm CeO2 nanoparticles downregulated the number of M1 macrophages.(3)Compared with the M1 group,20 nm CeO2 nanoparticles downregulated the mRNA and protein expression of inflammatory factors(tumor necrosis factor α,interleukin 6,cyclooxygenase 2,and endogenous nitric oxide synthase)in the co-culture system HFL1 cells.(4)The results showed that 20 nm CeO2 nanoparticles can alleviate inflammation in the co-culture system by inhibiting the expression of pro-inflammatory factors in M1 macrophages,providing a new idea for the treatment of inflammatory diseases such as rheumatoid arthritis.

BACKGROUND:Macrophage polarization plays a key role in chronic inflammatory joint diseases such as rheumatoid arthritis.Cerium dioxide(CeO2)nanoparticles have a wide range of biomedical applications such as modulating the local inflammatory microenvironment of tissues.OBJECTIVE:To investigate the role of CeO2 nanoparticles on macrophage polarization and inflammatory factor expression,as well as inflammatory modulation in a co-culture system of macrophages and fibroblasts.METHODS:(1)CeO2 nanoparticles were dispersed and observed morphologically by transmission electron microscopy.(2)Human leukemia monocytes(THP-1)were induced to differentiate and establish the M1 macrophage pro-inflammatory cell model of rheumatoid arthritis.The cells were divided into M0 group(undifferentiated macrophages),M1 group(successful macrophage modeling),CeO2 nanoparticle treatment group(M1 group with CeO2 nanoparticle treatment),and dexamethasone control group(M1 group with dexamethasone treatment)and incubated for 48 hours.The effects of CeO2 nanoparticles on the expression of inflammatory factors(endogenous nitric oxide synthase,CD86,CD80)in M1 macrophages and M1 macrophage phenotype(CD80,CD206)were detected by RT-qPCR,western blot assay,and flow cytometry.(3)A co-culture system of macrophages and fibroblasts was established,and CeO2 nanoparticles acted on the upper macrophages.The regulation of CeO2 nanoparticles on the expression of inflammatory factors(interleukin-6,tumor necrosis factor-α,cyclooxygenase-2,and endogenous nitric oxide synthase)of fibroblasts in the co-culture system was observed at the mRNA and protein levels.RESULTS AND CONCLUSION:(1)Transmission electron microscopy showed that the diameter of CeO2 nanoparticles was(19.5±2.0)nm.(2)Compared with the M0 group,the mRNA of endogenous nitric oxide synthase and CD86,and the protein expression of endogenous nitric oxide synthase and CD80 in the M1 group were upregulated.Compared with the M1 group,the mRNA expression of endogenous nitric oxide synthase and CD86,and the protein expression of endogenous nitric oxide synthase and CD80 in the CeO2 nanoparticle treatment group were downregulated.Flow cytometry showed that 20 nm CeO2 nanoparticles downregulated the number of M1 macrophages.(3)Compared with the M1 group,20 nm CeO2 nanoparticles downregulated the mRNA and protein expression of inflammatory factors(tumor necrosis factor α,interleukin 6,cyclooxygenase 2,and endogenous nitric oxide synthase)in the co-culture system HFL1 cells.(4)The results showed that 20 nm CeO2 nanoparticles can alleviate inflammation in the co-culture system by inhibiting the expression of pro-inflammatory factors in M1 macrophages,providing a new idea for the treatment of inflammatory diseases such as rheumatoid arthritis.

Background: Diabetic peripheral neuropathy (DPN) is a common chronic complication of diabetes mellitus that significantly impairs patients’ quality of life. Traditional Chinese medicine (TCM), as a major component of complementary and alternative medicine, has accumulated numerous effective formulas for the clinical management of DPN. However, systematic approaches for optimizing TCM formulas remain limited. Objective: To establish a pathway-oriented approach for TCM formula optimization and to evaluate the efficacy and mechanisms of the optimized formula in DPN. Methods: We developed 2 formula optimization algorithms that defined pathway-oriented herbal correlation (HC) and herbal contribution (HO) to screen and construct a new herbal formula, Qihongtongbi (QHTB), for treating Qi deficiency and blood stasis syndrome complicated with DPN. An animal experiment was subsequently conducted to evaluate the therapeutic effectiveness of QHTB. A total of 32 specific-pathogen-free male ob/ob mice (18–20 g) were randomly divided into 4 groups: model, Mudan Granules (MDG), QHTB low- and high-dose groups (n = 8). Ten male C57BL/6J mice (18–20 g) served as the control group. Metabolomics analysis was further employed to elucidate the biological mechanisms underlying the effects of QHTB. Results: Based on our previous study on TCM medication patterns for treating DPN, 22 candidate herbs were selected for formula optimization. The top 5 candidate herbs (total HC = 25.24 × 10 ) exhibited HC values comparable to those of MDG (total HC = 26.1 × 10 ). These herbs were Carthamus tinctorius L. (HC = 5.40 × 10 ), Astragalus mongholicus Bunge (HC = 5.23 × 10 ), Salvia miltiorrhiza Bunge (HC = 5.15 × 10 ), Commiphora myrrha (T. Nees) Engl. (HC = 5.02 × 10 ), and Glycyrrhiza glabra L. (HC = 4.44 × 10 ). HO analysis showed that the cumulative HO of these 5 herbs exceeded 50%. In vivo experiments demonstrated that, compared with the model group, QHTB significantly lowered blood glucose (P < 0.05), enhanced nerve conduction velocity (P < 0.01), improved nociceptive hypersensitivity (P < 0.01), and ameliorated sciatic nerve morphology, with efficacy comparable to MDG. Serum and fecal metabolomics further revealed that QHTB exerted multipathway regulatory effects, among which nicotinate and nicotinamide metabolism represented a key mechanism. Conclusion: In summary, this study provides a methodological reference for the systematic optimization of TCM formulas.

ObjectiveTo understand the epidemiological distribution and gene evolutionary variation of influenza A (H3N2) viruses in Fengxian District, Shanghai, in the surveillance year of 2023, and to provide a reference basis for influenza prevention and control. MethodsThe prevalence of influenza virus in Fengxian District in the 2023 influenza surveillance year (April 2023‒March 2024) was analyzed. The hemagglutinin (HA) gene, neuraminidase (NA) gene, and amino acid sequences of 75 strains of H3N2 influenza viruses were compared with the vaccine reference strain for similarity matching and phylogenetic evolutionary analysis, in addition to an analysis of gene characterization and variation. ResultsIn Fengxian District, there was a mixed epidemic of H3N2 and H1N1 in the spring of 2023, with H3N2 being the predominant subtype in the second half of the year, and Victoria B becoming the predominant subtype in the spring of 2024. A total of 75 influenza strains of H3N2 with HA and NA genes were distributed in the 3C.2a1b.2a.2a.2a.3a.1 and B.4 branches, with overall similarity to the reference strain of the 2024 vaccine higher than that of the reference strain of the 2022 and 2023 vaccine. Compared with the 2023 vaccine reference strain, three antigenic sites and one receptor binding site were changed in HA, with three glycosylation sites reduced and two glycosylation sites added; where as in NA seven antigenic sites and the 222nd resistance site changed with two glycosylation sites reduced. ConclusionThe risk of antigenic variation and drug resistance of H3N2 in this region is high, and it is necessary to strengthen the publicity and education on the 2024 influenza vaccine and long-term monitoring of influenza virus prevalence and variation levels.

Drug development remains a critical issue in the field of biomedicine.With the rapid advancement of information technologies such as artificial intelligence(AI)and the advent of the big data era,AI-assisted drug development has become a new trend,particularly in predicting drug-target associations.To address the challenge of drug-target prediction,AI-driven models have emerged as powerful tools,of-fering innovative solutions by effectively extracting features from complex biological data,accurately modeling molecular interactions,and precisely predicting potential drug-target outcomes.Traditional machine learning(ML),network-based,and advanced deep learning architectures such as convolutional neural networks(CNNs),graph convolutional networks(GCNs),and transformers play a pivotal role.This review systematically compiles and evaluates AI algorithms for drug-and drug combination-target predictions,highlighting their theoretical frameworks,strengths,and limitations.CNNs effectively identify spatial patterns and molecular features critical for drug-target interactions.GCNs provide deep insights into molecular interactions via relational data,whereas transformers increase prediction accu-racy by capturing complex dependencies within biological sequences.Network-based models offer a systematic perspective by integrating diverse data sources,and traditional ML efficiently handles large datasets to improve overall predictive accuracy.Collectively,these AI-driven methods are transforming drug-target predictions and advancing the development of personalized therapy.This review summa-rizes the application of AI in drug development,particularly in drug-target prediction,and offers rec-ommendations on models and algorithms for researchers engaged in biomedical research.It also provides typical cases to better illustrate how AI can further accelerate development in the fields of biomedicine and drug discovery.

Traditional Chinese medicine (TCM) is characterized by complex, multicomponent herbal formulations that challenge the conventional“one drug, one target” paradigm. Network pharmacology, through the construction of multilayered drug-target-disease networks, provides a systematic framework for unraveling TCM’s multitarget and multipathway mechanisms. Recent advancements in artificial intelligence, particularly large language models (LLMs), further enhance data integration, target identification, and clinical decision-making. This review synthesizes current progress in the application of network pharmacology and LLMs in TCM, highlighting their potential to deepen mechanistic insights and optimize drug discovery. By bridging traditional medical wisdom with modern computational tools, this integrative approach aims to advance the scientific validation of TCM and foster innovative healthcare solutions.

BACKGROUND: In the interim analysis of MONARCH plus, adding abemaciclib to endocrine therapy (ET) improved progression-free survival (PFS) and objective response rate (ORR) in predominantly Chinese postmenopausal women with HR+/HER2- advanced breast cancer (ABC). This study presents the final pre-planned PFS analysis. METHODS: In the phase III MONARCH plus study, postmenopausal women in China, India, Brazil, and South Africa with HR+/HER2- ABC without prior systemic therapy in an advanced setting (cohort A) or progression on prior ET (cohort B) were randomized (2:1) to abemaciclib (150 mg twice daily [BID]) or placebo plus: anastrozole (1.0 mg/day) or letrozole (2.5 mg/day) (cohort A) or fulvestrant (500 mg on days 1 and 15 of cycle 1 and then on day 1 of each subsequent cycle) (cohort B). The primary endpoint was PFS of cohort A. Secondary endpoints included cohort B PFS (key secondary endpoint), ORR, overall survival (OS), safety, and health-related quality of life (HRQoL). RESULTS: In cohort A (abemaciclib: n  = 207; placebo: n  = 99), abemaciclib plus a non-steroidal aromatase inhibitor improved median PFS vs . placebo (28.27 months vs . 14.73 months, hazard ratio [HR]: 0.476; 95% confidence interval [95% CI]: 0.348-0.649). In cohort B (abemaciclib: n  = 104; placebo: n  = 53), abemaciclib plus fulvestrant improved median PFS vs . placebo (11.41 months vs . 5.59 months, HR: 0.480; 95% CI: 0.322-0.715). Abemaciclib numerically improved ORR. Although immature, a trend toward OS benefit with abemaciclib was observed (cohort A: HR: 0.893, 95% CI: 0.553-1.443; cohort B: HR: 0.512, 95% CI: 0.281-0.931). The most frequent grade ≥3 adverse events in the abemaciclib arms were neutropenia, leukopenia, anemia (both cohorts), and lymphocytopenia (cohort B). Abemaciclib did not cause clinically meaningful changes in patient-reported global health, functioning, or most symptoms vs . placebo. CONCLUSIONS: Abemaciclib plus ET led to improvements in PFS and ORR, a manageable safety profile, and sustained HRQoL, providing clinical benefit without a high toxicity burden or reduced quality of life. TRIAL REGISTRATION ClinicalTrials.gov (NCT02763566).
Humans ; Female ; Fulvestrant/therapeutic use* ; Breast Neoplasms/metabolism* ; Aminopyridines/therapeutic use* ; Benzimidazoles/therapeutic use* ; Middle Aged ; Aromatase Inhibitors/therapeutic use* ; Aged ; Receptor, ErbB-2/metabolism* ; Adult ; Letrozole/therapeutic use* ; Antineoplastic Combined Chemotherapy Protocols/therapeutic use* ; Anastrozole/therapeutic use*

Objective : To investigate the factors affecting the outcome of high-risk human papillomavirus ( HR- HPV) infection in patients with normal cervix examined by colposcopy in Hefei area and the relationship between persistent HR-HPV infection and cervical cytology． Methods : Data of colposcopy patients were collected from 478 HR-HPV infected patients with normal cervix through colposcopy．Their age，number of sexual partners，contracep- tive methods and other relevant basic information were recorded．Vaginal interferon use，HR-HPV infection at year 1 and year 2，and cervical liquid-based cytology test ( LCT) results were tracked，univariate and multivariate ana- lyses were performed based on basic information，and ROC curves were plotted． Results : The HR-HPV clearance rate at 1 year was 59. 41% ，and the clearance rate at 2 years was 66. 75%．The other 12 types of infection ( 31， 33，35，39，45，51，52，56，58，59，66，68) were more common than the 16 and 18 types．Univariate and mult- ivariate analyses showed that age＞50 years，number of sexual partners ≥2，and history of cervical conectomy in- creased the risk of persistent HR-HPV infection ( χge = 21. 676，P ＜0. 001; χumber of sexual partners = 8. 262，P =0. 004; χistory of cervical conectomy = 11. 267，P = 0. 001 ) ． The risk of HR-HPV infection was significantly lower when condom or vaginal interferon was used ( χondom use = 10. 885，P = 0. 001; χnterferon use = 4. 099，P = 0. 043) ．The area under the ROC curve (AUC) of combined diagnosis of HR-HPV persistent infection was higher than that of single diagnosis，and the AUC of combined diagnosis was 0. 737．Persistent HR-HPV infection was an independent risk factor for abnormal LCT，and the AUC predicted by the model was 0. 755．No cancer was found in patients with persistent HR-HPV infection for 2 years，and the proportion of abnormal LCT was higher than that in patients with negative HR-HPV．The difference was statistically significant ( χ2 = 39. 64，P＜0. 001) ． Conclusion The combined ROC model constructed for patients＞50 years old，with multiple sexual partners，history of cervical surgery， no vaginal interferon use，and no condom use has certain value in predicting persistent HR-HPV infection，and per- sistent HR-HPV infection has predictive value in predicting LCT abnormalities．

Transarterial radioembolization (TARE) is a widely utilized therapeutic approach for hepatocellular carcinoma (HCC), however, the clinical implementation is constrained by the stringent preparation conditions of radioembolization agents. Herein, we incorporated the superstable homogeneous iodinated formulation technology (SHIFT), simultaneously utilizing an enhanced solvent form in a carbon dioxide supercritical fluid environment, to encapsulate radionuclides (such as ¹³¹I,¹⁷⁷Lu, or ¹⁸F) with lipiodol for the preparation of radiolipiodol. The resulting radiolipiodol exhibited exceptional stability and ultra-high labeling efficiency (≥99%) and displayed notable intratumoral radionuclide retention and in vivo stability more than 2 weeks following locoregional injection in subcutaneous tumors in mice and orthotopic liver tumors in rats and rabbits. Given these encouraging findings, ¹⁸F was authorized as a radiotracer in radiolipiodol for clinical trials in HCC patients, and showed a favorable tumor accumulation, with a tumor-to-liver uptake ratio of ≥50 and minimal radionuclide leakage, confirming the feasibility of SHIFT for TARE applications. In the context of transforming from preclinical to clinical screening, the preparation of radiolipiodol by SHIFT represents an innovative physical strategy for radionuclide encapsulation. Hence, this work offers a reliable and efficient approach for TARE in HCC, showing considerable promise for clinical application (ChiCTR2400087731).