ObjectiveTo investigate the effect of laminin subunit α3 （LAMA3） on the epithelial-mesenchymal transition （EMT）， invasion， and metastasis abilities of pancreatic cancer （PC）. MethodsA comprehensive analysis was performed for tumor- and EMT-related databases to identify the EMT genes associated with PC， especially LAMA3. The methods of qRT-PCR and Western blot were used to measure the expression level of LAMA3 in PC tissue and cell lines； immunofluorescence assay was used to determine the localization of LAMA3 in PANC-1 cells； Transwell assay was used to investigate the effect of LAMA3 on the invasion and migration abilities of PC cells. The t-test was used for comparison of continuous data between groups. ResultsThe analysis of the TCGA database identified 3 EMT-related oncogenes for PC， i.e.， LAMA3， AREG， and SDC1. The LASSO-Cox regression model showed that LAMA3 had the most significant impact on the prognosis of PC （risk score=0.256 1×LAMA3+0.043 1×SDC1+0.071 4×AREG）. The Cox model and nomogram showed that the high expression of LAMA3 was an independent risk factor for the poor prognosis of PC （hazard ratio=1.32， 95% confidence interval： 1.07‍ ‍—‍ 1.62， P<0.01）. Experimental results showed that there was a significant increase in the expression of LAMA3 in pancreatic cancer tissue compared with the normal pancreatic tissue. Compared with the HPDE cell line， there were varying degrees of increase in the expression of LAMA3 in pancreatic cancer AsPC-1， BxPC-3， PANC-1， MIA PaCa-2， and SW1990 cell lines， with the highest expression level in PANC-1 cells. The enrichment analysis showed that LAMA3 was associated with the biological processes and signaling pathways such as EMT， collagen metabolism， extracellular matrix degradation， the TGF-β pathway， and the PI3K pathway. After the knockdown of LAMA3， there were significant reductions in the expression levels of N-Cadherin， Vimentin， and Snail， while there was a significant increase in the expression level of E-Cadherin. Transwell assay showed that there were significant reductions in the invasion and migration abilities of PANC-1 cells after the knockdown of LAMA3. ConclusionLAMA3 is highly expressed in PC and can promote the EMT， invasion， and migration of PC cells， and therefore， LAMA3 may be used as a novel diagnostic marker and a new therapeutic target for PC.

BACKGROUND: Salvianolate is a compound mainly composed of salvia magnesium acetate, which is extracted from the Chinese herb Salvia miltiorrhiza . In recent years, salvianolate injection has been widely used in the treatment of cardiovascular diseases, but the mechanism of how it can alleviate cardiotoxicity remains unclear. METHODS: The cardiac injury model was constructed by treatment with doxorubicin (Dox) or azithromycin (Azi) in zebrafish larvae. Heart phenotype, heart rate, and cardiomyocyte apoptosis were observed in the study. RNA-sequencing (RNA-seq) analysis was used to explore the underlying mechanism of salvianolate treatment. Moreover, cardiomyocyte autophagy was assessed by in situ imaging. In addition, the miR-30a/becn1 axis regulation by salvianolate was further investigated. RESULTS: Salvianolate treatment reduced the proportion of pericardial edema, recovered heart rate, and inhibited cardiomyocyte apoptosis in Dox/Azi-administered zebrafish larvae. Mechanistically, salvianolate regulated the lysosomal pathway and promoted autophagic flux in zebrafish cardiomyocytes. The expression level of becn1 was increased in Dox-induced myocardial tissue injury after salvianolate administration; overexpression of becn1 in cardiomyocytes alleviated the Dox/Azi-induced cardiac injury and promoted autophagic flux in cardiomyocytes, while becn1 knockdown blocked the effects of salvianolate. In addition, miR-30a, negatively regulated by salvianolate, partially inhibited the cardiac amelioration of salvianolate by targeting becn1  directly. CONCLUSION This study has proved that salvianolate reduces cardiomyopathy by regulating autophagic flux through the miR-30a/becn1 axis in zebrafish and is a potential drug for adjunctive Dox/Azi therapy.
Animals ; Zebrafish ; MicroRNAs/genetics* ; Autophagy/drug effects* ; Myocytes, Cardiac/metabolism* ; Cardiomyopathies/metabolism* ; Beclin-1/genetics* ; Apoptosis/drug effects* ; Plant Extracts/therapeutic use* ; Doxorubicin

Rheumatoid arthritis (RA) represents a persistent autoimmune condition distinguished by a multifaceted etiology that encompasses both genetic and environmental factors. Recent progress in understanding the mechanisms behind RA pathogenesis has delved into the critical role of epigenetic regulatory processes, including DNA methylation, histone modifications, and the regulation by microRNAs (miRNAs). These findings provide new insights into the intricate nature of RA and pave the way for innovative therapeutic strategies. This review consolidates the latest developments in the epigenetic regulation of RA, concentrating on how these mechanisms affect the dysregulated signaling pathways associated with the disease. We analyze the roles of specific proteins that function as 'writers', 'erasers', and 'readers' in epigenetic modifications, highlighting their potential as targets for therapeutic intervention. Additionally, in view of the significance of miRNAs in the pathogenesis of RA, we deliberate on their involvement in disease progression and explore miRNA-based treatment strategies. By integrating these diverse epigenetic dimensions, this review offers a comprehensive epigenetic perspective on RA pathogenesis and identifies promising avenues for future research and therapeutic interventions.

Objective To explore the automated identification and diameter measurement methods for inferior vena cava (IVC) based on clinical ultrasound images of IVC. Methods An automated identification and localization method based on topology and automatic tracking algorithm was proposed. Tracking algorithm was used for identifying and continuously locating to improve the efficiency and accuracy of measurement. Tests were conducted on 18 sets of ultrasound data collected from 18 patients in intensive care unit (ICU),with clinicians' measurements as the gold standard. Results The recognition accuracy of the automated method was 94.44％ (17/18),and the measurement error of IVC diameter was within the range of±1.96s (s was the standard deviation). The automated method could replace the manual method. Conclusion The proposed IVC automated identification and localization algorithm based on topology and automatic tracking algorithm has high recognition success rate and IVC diameter measurement accuracy. It can assist clinicians in identifying and locating IVC,so as to improve the accuracy of IVC measurement.

Objective To explore the risk factors of complicating urogenic sepsis after percutaneous nephrolithotripsy(PCNL)and construct a nomogram prediction model.Methods The data of 291 patients with stage 1 PCNL in 940 Hospital of Joint Logistics Support Force from October 2016 to October 2021 were retrospectively analyzed.The patients were divided into the sepsis group and non-sepsis group according to whether complicating urogenic sepsis after operation.The general data,stone-related data,operation-related data and laboratory detection related data were included.The independent risk factors were screened by the univariate and multivariate logistic regression analysis,and the nomogram prediction model was constructed.Results The results of univariate and multivariate logistic regression analysis showed that age≥60 years old(OR=6.438,95％CI:1.548-26.769),urinary leukocyte 3+(OR=5.651,95％CI:1.614-31.766),urinary nitrite positive(OR=7.117,95％CI:1.190-42.561),operation time≥90 min(OR=4.626,95％CI:1.137-18.817)and perfusion volume 30 L(OR=3.312,95％CI:1.090-10.061)were the independent risk factors of postoperative complicating urogenic sepsis.C-index of the constructed nomogram prediction model in the modeling samples was 0.937,the calibrated C-index was 0.914,and the model predictive efficien-cy was good.Conclusion Age ≥60 years old,urinary leukocyte 3+,urinary nitrite positive,operation time 90 min and perfusion volume ≥30 L are the independent risk factors for complicating urogenic sepsis after PCNL;the constructed nomogram prediction model has a good predictive efficiency for the occurrence of post-operative urogenic sepsis.

Objective:To evaluate the feasibility of using MRI-only simulation images for dose calculation of both photon and proton radiotherapy for nasopharyngeal carcinoma cases.Methods:T 1-weighted MRI images and CT images of 100 patients with nasopharyngeal carcinoma treated with radiotherapy in Cancer Hospital of Chinese Academy of Medical Sciences from January 2020 to December 2021 were retrospectively analyzed. MRI images were converted to generate pseudo-CT images by using deep learning network models. The training set, validation set and test set included 70 cases, 10 cases and 20 cases, respectively. Convolutional neural network (CNN) and cycle-consistent generative adversarial neural network (CycleGAN) were exploited. Quantitative assessment of image quality was conducted by using mean absolute error (MAE) and structural similarity (SSIM), etc. Dose assessment was performed by using 3D-gamma pass rate and dose-volume histogram (DVH). The quality of pseudo-CT images generated was statistically analyzed by Wilcoxon signed-rank test. Results:The MAE of the CNN and CycleGAN was (91.99±19.98) HU and (108.30±20.54) HU, and the SSIM was 0.97±0.01 and 0.96±0.01, respectively. In terms of dosimetry, the accuracy of pseudo-CT for photon dose calculation was higher than that of the proton plan. For CNN, the gamma pass rate (3 mm/3%) of the photon radiotherapy plan was 99.90%±0.13%. For CycleGAN, the value was 99.87%±0.34%. The gamma pass rates of proton radiotherapy plans were 98.65%±0.64% (CNN, 3 mm/3%) and 97.69%±0.86% (CycleGAN, 3 mm/3%). For DVH, the dose calculation accuracy in the photon plan of pseudo-CT was better than that of the proton plan.Conclusions:The deep learning-based model generated accurate pseudo-CT images from MR images. Most dosimetric differences were within clinically acceptable criteria for photon and proton radiotherapy, demonstrating the feasibility of an MRI-only workflow for radiotherapy of nasopharyngeal cancer. However, compared with the raw CT images, the error of the CT value in the nasal cavity of the pseudo-CT images was relatively large and special attention should be paid during clinical application.

Circular RNA(circRNA)is an emerging class of endogenous non-coding RNA,which is widely expressed in the brain and plays an important role in a variety of biological processes.Research has shown that circRNA plays a key role in physiological and pathological processes of the brain,such as neurodevelopment,synaptic plasticity and neurodegenerative diseases through a variety of mecha-nisms such as adsorption of microRNA,binding to proteins and translation of peptides.In the field of drug addiction,the expression of circRNA is significantly changed in animal models and brains of addicts,and the regulation involves neural adaptation in brain regions that form the reward circuit such as the nucleus accumbens and prefrontal cortex.Additionally,addiction-related circRNAs are closely associated with neurotransmitter systems,signaling pathways,and neuroinflammatory responses,and they influ-ence the formation and maintenance of drug addiction by modulating gene expression networks related to drug addiction.Here,the biogenesis and regulatory mechanism of circRNA as well as its important role in brain function and drug addiction are reviewed in order to provide a new perspective for explora-tions of the pathological mechanism of drug addiction.

Objective To explore the inhibitory effect of Sidaxue, a traditional Miao herbal medicine formula, on articular bone and cartilage destruction and synovial neovascularization in rats with collagen-induced arthritis (CIA). Methods In a SD rat model of CIA, we tested the effects of daily gavage of Sidaxue at low, moderate and high doses (10, 20, and 40 g/kg, respectively) for 21 days, with Tripterygium glycosides (GTW) as the positive control, on swelling in the hind limb plantar regions by arthritis index scoring. Pathologies in joint synovial membrane of the rats were observed with HE staining, and serum TNF-α and IL-1β levels were detected with ELISA. The expressions of NF-κB p65, matrix metalloproteinase 1 (MMP1), MMP2 and MMP9 at the mRNA and protein levels in the synovial tissues were detected using real-time PCR and Western blotting. Network pharmacology analysis was conducted to identify the important target proteins in the pathways correlated with the therapeutic effects of topical Sidaxue treatment for RA, and the core target proteins were screened by topological analysis. Results Treatment with GTW and Sidaxue at the 3 doses all significantly alleviated plantar swelling, lowered arthritis index scores, improved cartilage and bone damage and reduced neovascularization in CIA rats (P<0.05), and the effects of Sidaxue showed a dose dependence. Both GTW and Sidaxue treatments significantly lowered TNF-α, IL-1β, NF-κB p65, MMP1, MMP2, and MMP9 mRNA and protein expressions in the synovial tissues of CIA rats (P<0.05). Network pharmacological analysis identified MMPs as the core proteins associated with topical Sidaxue treatment of RA. Conclusion Sidaxue alleviates articular bone and cartilage damages and reduces synovial neovascularization in CIA rats possibly by downregulating MMPs via the TNF-α/IL-1β/NF-κB-MMP1, 2, 9 signaling pathway, and MMPs probably plays a key role in mediating the effect of Sidaxue though the therapeutic pathways other than oral administration.

Objective This study aimed to reveal critical genes regulating peri-implantitis during its development and construct a diagnostic model by using random forest(RF)and artificial neural network(ANN).Methods GSE-33774,GSE106090,and GSE57631 datasets were obtained from the GEO database.The GSE33774 and GSE106090 da-tasets were analyzed for differential expression and functional enrichment.The protein-protein interaction networks(PPI)and RF screened vital genes.A diagnostic model for peri-implantitis was established using ANN and validated on the GSE33774 and GSE57631 datasets.A transcription factor-gene interaction network and a transcription factor-micro-RNA(miRNA)regulatory network were also established.Results A total of 124 differentially expressed genes(DEGs)involved in the regulation of peri-implantitis were screened.Enrichment analysis showed that DEGs were mainly associated with immune receptor activity and cytokine receptor activity and were mainly involved in processes such as leukocyte and neutrophil migration.The PPI and RF screened six essential genes,namely,CD38,CYBB,FCGR2A,SELL,TLR4,and CXCL8.The receiver oper-ating characteristic curve(ROC)indicated that the ANN model had an excellent diagnostic performance.FOXC1,GA-TA2,and NF-κB1 may be essential transcription factors in peri-implantitis,and hsa-miR-204 may be a key miRNA.Con-clusion The diagnostic model of peri-implantitis constructed by RF and ANN has high confidence,and CD38,CYBB,FCGR2A,SELL,TLR4,and CXCL8 are potential diagnostic markers.FOXC1,GATA2,and NF-κB1 may be essential transcription factors in peri-implantitis,and hsa-miR-204 plays a vital role as a critical miRNA.

Objective This study aims to investigate the role of genes related to fatty acid metabolism in periodon-titis through machine learning and bioinformatics methods.Methods Periodontitis datasets GSE10334 and GSE-16134 were downloaded from the GEO database,and the fatty acid metabolism-related gene sets were obtained from the GeneCards database.Differentially expressed fatty acid metabolism-related genes(DEFAMRGs)in periodontitis were screened using the"limma"R package.Functional enrichment and pathway analyses were conducted.Recursive Feature Elimination,Least Absolute Shrinkage and Selection Operator,and Boruta algorithm were used to determine hub DEFAMRGs and construct diagnostic models with internal and external validation.Subtypes of periodontitis relat-ed to hub DEFAMRGs were constructed using consis-tency clustering analysis.CIBERSORT was used to ana-lyze immune cell infiltration in gingival tissues and ex-plore the correlation between hub DEFAMRGs and im-mune cells.Results A total of 113 periodontitis DE-FAMRGs were screened out as a result.The enrichment analysis results indicate that DEFAMRGs are mainly associat-ed with immune inflammatory responses and immune cell chemotaxis.Finally,8 hub DEFAMRGs(BTG2,CXCL12,FABP4,CLDN10,PPBP,RGS1,LGALSL,and RIF1)were identified and a diagnostic model(AUC=0.967)was con-structed,based on which periodontitis was divided into two subtypes.In addition,there is a significant correlation be-tween hub DEFAMRGs and different immune cell populations,with mast cells and dendritic cells showing higher cor-relation.Conclusion This study provides new insights and ideas for the occurrence and development mechanism of periodontitis and proposes a diagnostic model based on hub DEFAMRGs to provide new directions for diagnosis and treatment.