Aim To explore the mechanism by which dioscin regulates IL-17+γδT cells in the treatment of arthritis.Methods A collagen-induced arthritis(CIA)model was established in DBA/1 mice using bovine type Ⅱ collagen.The mice were randomly divid-ed into the CIA model group,methotrexate(MTX)positive control group,and dioscin low-dose(Dioscin-L),medium-dose(Dioscin-M),and high-dose(Dios-cin-H)groups.After intervention,the therapeutic effects were evaluated using scoring methods.Joint pathological damage was analyzed by hematoxylin and eosin(HE)staining.The levels of anti-collagen-spe-cific antibodies and the pro-inflammatory cytokine IL-17 were measured by ELISA.The expressions of γδT cells and their subtypes,as well as the secretion level of IL-17,were detected by flow cytometry.Results Dioscin significantly reduced the arthritis severity score in collagen-induced arthritis(CIA)mice,alleviated joint pathological damage,inhibited the production of IL-17 by splenic lymphocytes and the levels of anti-col-lagen-specific antibodies total IgG and IgG3,and de-creased the proportion of γδT cells in the lymph nodes,splenic γδT cells,and the Vδ4+T-cell subset.The level of IL-17 produced by the Vδ4 subtype in the lymph nodes of the intervention groups was lower than that in the model group,but the difference was not sta-tistically significant.Conclusion Dioscin has signifi-cant therapeutic effect on CIA,and its mechanism may be through the inhibition of γδT cells,but it is unlikely to be related to IL-17 derived from γδT cells.

Objective To investigate the dosimetric differences in preoperative short-course volumetric modulated arc therapy(VMAT)for rectal cancer using different fluence smoothing(FS)levels in the Monaco Treatment Planning System(Monaco TPS).Methods Twenty rectal cancer patients who received preoperative neoadjuvant short-course VMAT at some hospital from September 2021 to December 2022 were retrospectively selected.Four groups of radiotherapy plans were formulated using the Monaco TPS for each case,which were classified into an off group,a low group,a medium group and a high group based on the FS levels.Then the four groups were compared in terms of the dosimetric parameters,monitor unit and number of the segments in the planning target volume(PTV)and organ at risk(OAR).Statistical analysis was performed using SPSS 27.0 software.Results All the four groups had the doses to the target volume meeting clinical requirements,which had no significant differences in the doses to 5％(D5％)and 95％(D95％)to the target volume and the maximum dose(Dmax),minimum dose(Dmin),mean dose(Dmean)and conformity index(all P＞0.05).Statistical differences were found between the homogeneity indexes of the four groups(P＜0.05),with the medium group behaving the best.The number of the segments rose while the mornitor units decreased siginificantly with the increase of FS levels,with the differences being statistically significant(P＜0.05).There were no significant differences between the V25,V20,V15 and V10 of the small intestine,the V25 and V20 of the bladder and the V15 and V10 of the left and right femur(all P＞0.05).Conclusion In preoperative short-course VMAT for rectal cancer,clinical requirements can be met with different FS levels in the Monaco TPS,and medium-level FS results in optimal overall dose distribution in terms of treatment planning.[Chinese Medical Equipment Journal,2025,46(5):48-53]

Aim To explore the mechanism by which dioscin regulates IL-17+γδT cells in the treatment of arthritis.Methods A collagen-induced arthritis(CIA)model was established in DBA/1 mice using bovine type Ⅱ collagen.The mice were randomly divid-ed into the CIA model group,methotrexate(MTX)positive control group,and dioscin low-dose(Dioscin-L),medium-dose(Dioscin-M),and high-dose(Dios-cin-H)groups.After intervention,the therapeutic effects were evaluated using scoring methods.Joint pathological damage was analyzed by hematoxylin and eosin(HE)staining.The levels of anti-collagen-spe-cific antibodies and the pro-inflammatory cytokine IL-17 were measured by ELISA.The expressions of γδT cells and their subtypes,as well as the secretion level of IL-17,were detected by flow cytometry.Results Dioscin significantly reduced the arthritis severity score in collagen-induced arthritis(CIA)mice,alleviated joint pathological damage,inhibited the production of IL-17 by splenic lymphocytes and the levels of anti-col-lagen-specific antibodies total IgG and IgG3,and de-creased the proportion of γδT cells in the lymph nodes,splenic γδT cells,and the Vδ4+T-cell subset.The level of IL-17 produced by the Vδ4 subtype in the lymph nodes of the intervention groups was lower than that in the model group,but the difference was not sta-tistically significant.Conclusion Dioscin has signifi-cant therapeutic effect on CIA,and its mechanism may be through the inhibition of γδT cells,but it is unlikely to be related to IL-17 derived from γδT cells.

mRNA therapy is an emerging treatment that has become a frontier and hot topic in the field of biomedicine.To explore the trend in the development of mRNA therapy,this paper conducts an analysis from the perspectives of papers and patents,examining multiple dimensions including development trend,research areas,and high-value research.The study reveals the following findings:Global research in mRNA therapy is growing rapidly.Basic research mainly focuses on oncology,chemistry-multidisciplinary,biochemistry and molecular biology,while applied research centers on mRNA concerning genetic engineering,isolation,synthesis,purification,and the development of medicines.High-value research mainly centers on topics such as mRNA delivery,composition,manufacture,modification,and the development of various mRNA-based therapies.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Computational analysis can accurately detect drug-gene interactions (DGIs) cost-effectively. However, transductive learning models are the hotspot to reveal the promising performance for unknown DGIs (both drugs and genes are present in the training model), without special attention to the unseen DGIs (both drugs and genes are absent in the training model). In view of this, this study, for the first time, proposed an inductive learning-based model for the precise identification of unseen DGIs. In our study, by integrating disease nodes to avoid data sparsity, a multi-relational drug-disease-gene (DDG) graph was constructed to achieve effective fusion of data on DDG intro-relationships and inter-actions. Following the extraction of graph features by utilizing graph embedding algorithms, our next step was the retrieval of the attributes of individual gene and drug nodes. In this way, a hybrid feature characterization was represented by integrating graph features and node attributes. Machine learning (ML) models were built, enabling the fulfillment of transductive predictions of unknown DGIs. To realize inductive learning, this study generated an innovative idea of transforming known node vectors derived from the DDG graph into representations of unseen nodes using node similarities as weights, enabling inductive predictions for the unseen DGIs. Consequently, the final model was superior to existing models, with significant improvement in predicting both external unknown and unseen DGIs. The practical feasibility of our model was further confirmed through case study and molecular docking. In summary, this study establishes an efficient data-driven approach through the proposed modeling, suggesting its value as a promising tool for accelerating drug discovery and repurposing.

OBJECTIVE: To elucidate the role and mechanism of microRNA-145-5p (miR-145-5p) in hypoxia-induced pyroptosis of human alveolar epithelial cells. METHODS: In vitro, human alveolar epithelial cell line BEAS-2B was cultured. Cells in the logarithmic growth phase were cultured to 80% confluence and then used for the experiment. (1) BEAS-2B cells were cultured under 1% O₂ hypoxic condition, with a normoxic control group. Western blotting was employed to detect the expressions of pyroptosis marker proteins [NOD-like receptor protein 3 (NLRP3), Gasdermin D N-terminal domain (GSDMD-N), and caspase-1] in cells cultured for 24 hours. Real-time fluorescent quantitative reverse transcription-polymerase chain reaction (RT-PCR) was used to detect the expression of miR-145-5p in cells cultured for 6 hours and 12 hours. (2) Cells were transfected with 30 nmol/L miR-145-5p mimic to overexpress miR-145-5p expression under normoxic condition or 30 nmol/L miR-145-5p inhibitor to suppress miR-145-5p expression under hypoxic condition. Control group and negative control group were respectively set up. After 24 hours of cell culture, Western blotting was used to detect the expressions of pyroptosis marker proteins and nuclear factor-E2-related factor 2 (Nrf2) in cells. Flow cytometry was applied to detect the level of reactive oxygen species (ROS) in cells. The target genes of miR-145-5p were predicted by miR target gene prediction software miRWalk and verified by Western blotting. (3) Under hypoxic condition, cells were transfected with 6.94 ng/μL silent information regulator 5 (Sirt5) overexpression plasmid or pretreated with 12.5 mmol/L N-acetyl-L-cysteine (NAC) as an ROS inhibitor. The empty plasmid group and control group were set up. After 24 hours of cell culture, Western blotting was used to detect the expressions of Sirt5, Nrf2, and pyroptosis marker proteins in cells. Flow cytometry was used to detect the level of ROS in cells. RESULTS: (1) Compared with the normoxic control group, the expression levels of pyroptosis marker proteins in the 24-hour hypoxia group was significantly increased, indicating that hypoxia could induce pyroptosis in BEAS-2B cells. The expression level of miR-145-5p in cells gradually increased with the extension of hypoxia induction time, indicating that hypoxia could cause the increase of miR-145-5p expression level. (2) The expression levels of pyroptosis marker proteins in cells of miR-145-5p mimic group significantly increased under normoxic condition as compared with the control and negative control groups [NLRP3 protein (NLRP3/β-actin): 1.58±0.07 vs. 1.00±0.01, 0.98±0.07, GSDMD-N protein (GSDMD-N/β-actin): 1.71±0.03 vs. 1.01±0.01, 0.85±0.03, caspase-1 protein (caspase-1/β-actin): 2.33±0.04 vs. 1.01±0.01, 1.05±0.04, all P < 0.05], Nrf2 protein expression level was significantly decreased (Nrf2/β-actin: 0.79±0.03 vs. 1.00±0.01, 1.03±0.04, both P < 0.05), ROS level was significantly up-regulated (fluorescence intensity: 1.74±0.03 vs. 1.00±0.01, 0.92±0.03, both P < 0.05). Under hypoxia condition, compared with control group and negative control group, the expression levels of pyroptosis marker proteins in miR-145-5p inhibitor group were significantly decreased [NLRP3 protein (NLRP3/β-actin): 0.21±0.04 vs. 1.70±0.02, 1.63±0.04; GSDMD-N protein (GSDMD-N/β-actin): 1.32±0.02 vs. 2.51±0.02, 2.72±0.03; caspase-1 protein (caspase-1/β-actin): 0.56±0.01 vs. 2.77±0.02, 3.12±0.03; all P < 0.05], Nrf2 protein expression level was significantly increased (Nrf2/β-actin: 1.57±0.04 vs. 1.22±0.01, 1.28±0.04, both P < 0.05), ROS level was significantly down-regulated (fluorescence intensity: 0.64±0.05 vs. 1.87±0.04, 1.70±0.07, both P < 0.05). The results indicated that miR-145-5p could promote cell pyrodeath. The predictive result of miRWalk showed that the 3' untranslated region (3'UTR) of Sirt5 had complementary base binding sites with miR-145-5p. The expression level of Sirt5 protein in cells of miR-145-5p mimic group was significantly lower than that of control group and negative control group under normoxic condition (Sirt5/β-actin: 0.59±0.03 vs. 1.00±0.01, 1.01±0.03, both P < 0.05), which verified that Sirt5 was the target gene of miR-145-5p. (3) The occurrence of pyrodeath could be partially reversed by transfection with Sirt5 overexpression plasmid or adding ROS inhibitor NAC into cells, and Sirt5 overexpression could also up-regulate Nrf2 expression and eliminate intracellular ROS. CONCLUSION In human alveolar epithelial cells, miR-145-5p can down-regulate Nrf2 by targeting Sirt5, thereby increasing ROS expression and inducing pyrodeath.
Humans ; MicroRNAs ; Pyroptosis ; Cell Hypoxia ; Alveolar Epithelial Cells/cytology* ; Cell Line ; NLR Family, Pyrin Domain-Containing 3 Protein ; Caspase 1/metabolism* ; Epithelial Cells/metabolism* ; Gasdermins ; Phosphate-Binding Proteins

This study aimed to investigate the effects of caffeoylquinic acids from Erigeron breviscapus(EBCQA) on cognitive impairment and mitochondrial dysfunction in Alzheimer's disease(AD), and to explore its underlying mechanisms. The impacts of EBCQA on paralysis, β-amyloid(Aβ) oligomerization, and mRNA expression of mitophagy-related genes [PTEN-induced putative kinase 1(PINK1) homolog-encoding gene pink-1, Parkin homolog-encoding gene pdr-1, Bcl-2 interacting coiled-coil protein 1(Beclin 1) homolog-encoding gene bec-1, microtubule-associated protein 1 light chain 3(LC3) homolog-encoding gene lgg-1, autophagic adapter protein 62(p62) homolog-encoding gene sqst-1] were examined in the AD Caenorhabditis elegans CL4176 model, along with mitochondrial functions including adenosine triphosphate(ATP) content, enzyme activities of mitochondrial respiratory chain complexes Ⅰ,Ⅲ, and Ⅳ, and mitochondrial membrane potential. Additionally, the effects of EBCQA on the green fluorescent protein(GFP)/red fluorescent protein from Discosoma sp.(DsRed) ratio, the expression of phosphatidylethanolamine-modified and GFP-labeled LGG-1(PE-GFP::LGG-1)/GFP-labeled LGG-1(GFP::LGG-1), and GFP-labeled SQST-1(GFP::SQST-1) proteins were investigated in transgenic C. elegans strains. The effect of EBCQA on paralysis was further evaluated after RNA interference(RNAi)-mediated suppression of the pink-1 and pdr-1 genes in CL4176 strain. An AD rat model was established through intraperitoneal injection of D-galactose and intragastric administration of aluminum trichloride. The effects of β-nicotinamide mononucleotide(NMN) and EBCQA on learning and memory ability, neuronal morphology, mitophagy occurrence, mitophagy-related protein expression(PINK1, Parkin, Beclin 1, LC3-Ⅱ/LC3-Ⅰ, p62), and mitochondrial functions(ATP content; enzyme activities of mitochondrial respiratory chain complexes Ⅰ, Ⅲ, and Ⅳ; mitochondrial membrane potential) were investigated in this AD rat model. The results showed that EBCQA delayed paralysis onset in the CL4176 strain, reduced Aβ oligomer formation, and upregulated the mRNA expression levels of lgg-1, bec-1, pink-1, and pdr-1, while downregulating sqst-1 mRNA expression. EBCQA also enhanced ATP content, mitochondrial membrane potential, and the activities of mitochondrial respiratory chain complexes Ⅰ, Ⅲ, and Ⅳ. Furthermore, EBCQA improved the PE-GFP::LGG-1/GFP::LGG-1 ratio, reduced GFP::SQST-1 expression, and decreased the GFP/DsRed ratio. Notably, the ability of EBCQA to delay paralysis was significantly reduced following RNAi-mediated suppression of pink-1 and pdr-1 in CL4176 strain. In AD rats, the administration of NMN or EBCQA significantly improved learning and memory, restored neuronal morphology in the hippocampus, increased autophagosome numbers, and upregulated the expression of PINK1, Parkin, Beclin 1, and the LC3-Ⅱ/LC3-Ⅰ ratio, while reducing p62 expression. Additionally, the treatment with NMN or EBCQA both elevated ATP content, mitochondrial respiratory chain complex Ⅰ, Ⅲ, and Ⅳ activities, and mitochondrial membrane potential in the hippocampus. The above findings indicate that EBCQA improves cognitive impairment and mitochondrial dysfunction in AD, possibly through activation of PINK1/Parkin-mediated mitophagy.
Animals ; Alzheimer Disease/psychology* ; Mitophagy/drug effects* ; Mitochondria/genetics* ; Caenorhabditis elegans/metabolism* ; Ubiquitin-Protein Ligases/genetics* ; Cognitive Dysfunction/physiopathology* ; Rats ; Protein Kinases/genetics* ; Humans ; Male ; Disease Models, Animal ; Caenorhabditis elegans Proteins/genetics* ; Drugs, Chinese Herbal/administration & dosage*

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.