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.

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).

Adolescent depression is increasingly recognized as a serious mental health disorder with distinct clinical and molecular features. Using single-nucleus RNA sequencing, we identified cell-specific transcriptomic changes in the nucleus accumbens (NAc), particularly in astrocytes, of adolescent macaques exhibiting depressive-like behaviors. The level of diacylglycerol kinase beta was significantly reduced in neurons and glial cells of depressed macaques, while FKBP5 levels increased in glial cells. Disruption of GABAergic synapses and disruption of D-glutamine and D-glutamate metabolism were linked to depressive phenotypes in medium spiny neurons (MSNs) and subtypes of astrocytes. Communication pathways between astrocytes and D1/D2-MSNs were also disrupted, involving factors like bone morphogenetic protein-6 and Erb-B2 receptor tyrosine kinase-4. Bulk transcriptomic and proteomic analyses corroborated these findings, and FKBP5 upregulation was confirmed by qRT-PCR, western blotting, and immunofluorescence in the NAc of rats and macaques with chronic unpredictable mild stress. Our results highlight the specific roles of different cell types in adolescent depression in the NAc, offering potential targets for new antidepressant therapies.
Animals ; Nucleus Accumbens/metabolism* ; Male ; Transcriptome ; Depression/genetics* ; Astrocytes/metabolism* ; Neurons/metabolism* ; Rats

Approximately 20% to 30% of the global workforce is engaged in shift work. As a significant cause of circadian disruption, shift work is closely associated with an increased risk for periodontitis. Nevertheless, how shift work-related circadian disruption functions in periodontitis remains unknown. Herein, we employed a simulated shift work model constructed by controlling the environmental light-dark cycles and revealed that shift work-related circadian disruption exacerbated the progression of experimental periodontitis. RNA sequencing and in vitro experiments indicated that downregulation of the core circadian protein brain and muscle ARNT-like protein 1 (BMAL1) and activation of the Gasdermin D (GSDMD)-mediated pyroptosis were involved in the pathogenesis of that. Mechanically, BMAL1 regulated GSDMD-mediated pyroptosis by suppressing NOD-like receptor protein 3 (NLRP3) inflammasome signaling through modulating nuclear receptor subfamily 1 group D member 1 (NR1D1), and inhibiting Gsdmd transcription via directly binding to the E-box elements in its promoter. GSDMD-mediated pyroptosis accelerated periodontitis progression, whereas downregulated BMAL1 under circadian disruption further aggravated periodontal destruction by increasing GSDMD activity. And restoring the level of BMAL1 by circadian recovery and SR8278 injection alleviated simulated shift work-exacerbated periodontitis via lessening GSDMD-mediated pyroptosis. These findings provide new evidence and potential interventional targets for circadian disruption-accelerated periodontitis.
Pyroptosis/physiology* ; ARNTL Transcription Factors/metabolism* ; Animals ; Periodontitis/etiology* ; Mice ; Phosphate-Binding Proteins/metabolism* ; Shift Work Schedule/adverse effects* ; Intracellular Signaling Peptides and Proteins/metabolism* ; Mice, Inbred C57BL ; Male ; Disease Models, Animal ; Gasdermins

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, offering 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 accuracy 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 summarizes the application of AI in drug development, particularly in drug-target prediction, and offers recommendations 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.

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.

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.

Objective To explore the potential role and underlying mechanism of the functionally uncharacterized gene Gm49394 on regulating β-cell apoptosis under diabetic conditions.Methods The expression and translational activity of Gm49394 in pancreatic β-cell lines and non-β-cell lines were validated using RNA fluorescence in situ hybridization(RNA-FISH),quantitative real-time PCR(qPCR),Western blotting,and immunofluorescence(IF)assay.The β-cell lines(NIT-1/Min6)with Gm49394 overexpression or knockdown were constructed.The proliferation,apoptosis,mitochondrial function,as well as oxidative stress and endoplasmic reticulum stress markers in these β-cell lines under physiological homeostasis or pathological stress conditions,such as high glucose(30 mmol/L),inflammation(10 ng/mL IFN-γ alone or combined with 10 ng/mL IL-6),and hydrogen peroxide(100 μmol/L H2O2)were detected by flow cytometry and Western blotting.Results RNA-FISH and qPCR indicated that Gm49394 was specifically expressed in pancreatic β-cell lines and up-regulated under high glucose or inflammatory stimulation.IF assay and Western blotting showed that Gm49394 had protein-coding activity.Flow cytometry and Western blotting identified that Gm49394 overexpression did not affect β-cell proliferation,but promoted β-cell apoptosis and increased reactive oxygen species(ROS)and mitochondrial superoxide(MitoSOX)levels in β cells under physiological homeostasis or pathological stress conditions(P<0.05).Under physiological conditions,Gm49394 knockdown failed to induce significant alterations on β-cell apoptosis,ROS,or MitoSOX levels.Under pathological stress conditions,Gm49394 knockdown significantly suppressed β-cell proliferation,apoptosis,as well as oxidative and endoplasmic reticulum stress(P<0.05).Conclusion Gm49394 may promote β-cell apoptosis via oxidative stress and endoplasmic reticulum stress.