Objective To explore the relationship between circadian rhythm genes and the occurrence, development, prognosis, and tumor microenvironment (TME) of lung adenocarcinoma (LUAD). Methods The Cancer Genome Atlas data were used to evaluate the expression, copy number variation, and somatic mutation frequency of circadian gene sets in LUAD. Gene ontology, Kyoto encyclopedia of genes and genomes, and gene set enrichment analysis were used to explore the potential mechanisms by which circadian rhythm genes affected LUAD progression. Cox regression, least absolute shrinkage and selection operator regression, support vector machine recursive feature elimination, and random forest screened circadian genes and established prognostic models, and on this basis constructed nomogram to predict patients’ 1-, 3-, and 5-year survival rates. Kaplan-Meier survival curves, receiver operating characteristic (ROC) curves, and time-dependent ROC curves were drawn to evaluate the predictive ability of the model, and the external dataset of GEO further verified the prognostic value of the prediction model. In addition, we evaluated the association of the prognostic model with immune cells and immune checkpoint genes. Single cell RNA sequencing (scRNA-seq) analysis was used to explore the molecular characteristics between prognostically relevant circadian genes and different immune cell populations in TME. Results Differentially expressed circadian rhythm genes were mainly enriched in biological processes related to cGMP-PKG signaling pathway, lipid and atherosclerosis, and JAK-STAT signaling pathway. Seven circadian rhythm genes: LGR4, CDK1, KLF10, ARNTL2, RORA, NPAS2, PTGDS were screened out, and a RiskScore model was established. According to the median RiskScore, samples were divided into a high-risk group and a low-risk group. Compared with patients in the low-risk group, patients in the high-risk group showed a poorer prognosis (P<0.001). Immunological characterization analysis showed that there were differences in the infiltration of multiple immune cells between the low-risk group and high-risk group. Most immune checkpoint genes had higher expression levels in the high-risk group than those in the low-risk group, and RiskScore was positively correlated with the expression of CD276, TNFSF4, PDCD1LG2, CD274, and TNFRSF9, and negatively correlated with the expression of CD40LG and TNFSF15. The scRNA-seq analysis showed that RORA and KLF10 were mainly expressed in natural killer cells. Conclusion The prognostic model based on seven feature circadian rhythm genes has certain predictive value for predicting survival of LUAD patients. Dysregulated expression of circadian genes may regulate the occurrence, progression as well as prognosis of LUAD through affecting TME, which provides a possible direction for finding potential strategies for treating LUAD from the perspective of mechanism by which circadian disorder affects immune cells.

Objective To determine the prognostic biomarkers and new therapeutic targets of the lung adenocarcinoma (LUAD), based on which to establish a prediction model for the survival of LUAD patients. Methods An integrative analysis was conducted on gene expression and clinicopathologic data of LUAD, which were obtained from the UCSC database. Subsequently, various methods, including screening of differentially expressed genes (DEGs), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and Gene Set Enrichment Analysis (GSEA), were employed to analyze the data. Cox regression and least absolute shrinkage and selection operator (LASSO) regression were used to establish an assessment model. Based on this model, we constructed a nomogram to predict the probable survival of LUAD patients at different time points (1-year, 2-year, 3-year, 5-year, and 10-year). Finally, we evaluated the predictive ability of our model using Kaplan-Meier survival curves, receiver operating characteristic (ROC) curves, and time-dependent ROC curves. The validation group further verified the prognostic value of the model. Results The different-grade pathological subtypes' DEGs were mainly enriched in biological processes such as metabolism of xenobiotics by cytochrome P450, natural killer cell-mediated cytotoxicity, antigen processing and presentation, and regulation of enzyme activity, which were closely related to tumor development. Through Cox regression and LASSO regression, we constructed a reliable prediction model consisting of a five-gene panel (MELTF, MAGEA1, FGF19, DKK4, C14ORF105). The model demonstrated excellent specificity and sensitivity in ROC curves, with an area under the curve (AUC) of 0.675. The time-dependent ROC analysis revealed AUC values of 0.893, 0.713, and 0.632 for 1-year, 3-year, and 5-year survival, respectively. The advantage of the model was also verified in the validation group. Additionally, we developed a nomogram that accurately predicted survival, as demonstrated by calibration curves and C-index. Conclusion We have developed a prognostic prediction model for LUAD consisting of five genes. This novel approach offers clinical practitioners a personalized tool for making informed decisions regarding the prognosis of their patients.

In response to the high cost and time consumption of medical image annotation,and issues such as the imprecision of unlabeled data segmentation in semi-supervised medical image segmentation,loss of image edge information,and delayed parameter updates,a semi-supervised medical image segmentation method based on consistency regularization is presented.Firstly,an uncertainty measurement method based on the dual perspectives of entropy and variance is designed to assess the uncertainty of predictions for unlabeled data,jointly evaluating the uncertainty of unlabeled data from the perspectives of entropy and variance.Then,edge-preserving noise based on the Canny operator is used to retain image edge information and important structures,thereby avoiding the potential blurring of organ edges that may result from the addition of random noise.Finally,a semi-supervised residual-driven segmentation method based on the mean teacher framework is developed,with a Frobenius norm regularization term in the exponential moving average scheme to enhance the performance of mean teacher.The proposed method is validated on the publicly available multi-organ segmentation benchmark dataset BTCV and brain tumor segmentation dataset BraTS 2019.In the case of 40%labeled data in the BTCV dataset,Dice similarity coefficient and standardized surface distance are 77.42%and 79.47%,respectively.In the case of 20%labeled data in the BraTS 2019 dataset,the proposed method achieve a Dice similarity coefficient of 83.89%,a Jaccard coefficient of 74.21%,an average surface distance of 2.34 mm,and a 95%Hausdorff distance of 9.08 mm,demonstrating its superiority.

Objective:To assess the clinicopathological characteristics of non-muscle-invasive bladder cancers (NMIBC) with high expression of human epidermal growth factor receptor 2 (HER2) and to examine the prognostic values of HER2 expression in NMIBC patients with intravesical anthracycline instillation.Methods:A total of 221 NMIBC samples diagnosed between January 1, 2017 and April 15, 2024 were collected. Their clinical, diagnostic and treatment features were analyzed. The expression of HER2 protein and the Ki-67 proliferation index were assessed using immunohistochemistry (IHC). For the patients with HER2 high-expression (IHC 3+), the clinical pathological features (age, gender, tumor grade, Ki-67 expression level, tumor size, and tumor number) were compared with those without (i.e., HER2 IHC 0/1+/2+). The impact of HER2 expression on the recurrence-free survival (RFS) of patients with intravesical anthracycline (epirubicin or pirarubicin) instillation after transurethral resection of bladder tumor (TURBT) was evaluated.Results:Among the 221 NMIBC patients, 30 (13.6%) were HER2 IHC 3+, 142 (64.3%) HER 2+, 46 (20.8%) HER2 1+, and 3 (1.4%) HER2 IHC 0. The proportion of high-grade tumors in patients with HER2 high-expression was higher than that in patients without (83.3% versus 44.5%, P<0.001). Additionally, a high Ki-67 index (≥20%) was more commonly noted in HER2 high-expression tumors ( P=0.003). In the patients treated with intravesical anthracycline instillation, HER2 high-expression was associated with a shorter RFS ( P<0.001). Conclusion:HER2 high-expression seems to be not only associated with worse clinicopathological features of NMIBC but also a poor RFS in NMIBC patients treated with anthracycline instillation after TURBT.

Osteoarthritis (OA) causes chronic pain that significantly impairs quality of life, with current treatments often proving insufficient and accompanied by adverse effects. Recent research has identified the dorsal root ganglion (DRG) and its resident macrophages as crucial mediators of chronic OA pain through neuroinflammation driven by macrophage polarization. We present a novel injectable thermo-sensitive hydrogel system, KAF@PLEL, designed to deliver an anti-inflammatory peptide (KAF) specifically to the DRG. This biodegradable hydrogel enables sustained KAF release, promoting the reprogramming of DRG macrophages from pro-inflammatory to anti-inflammatory phenotypes. Through comprehensive in vitro and in vivo studies, we evaluated the hydrogel's biocompatibility, effects on macrophage polarization, and therapeutic efficacy in chronic OA pain management. The system demonstrated significant capabilities in preserving macrophage mitochondrial function, suppressing neuroinflammation, alleviating chronic OA pain, reducing cartilage degradation, and improving motor function in OA rat models. The sustained-release properties of KAF@PLEL enabled prolonged therapeutic effects while minimizing systemic exposure and side effects. These findings suggest that KAF@PLEL represents a promising therapeutic approach for improving outcomes in OA patients through targeted, sustained treatment.

Japanese encephalitis virus(JEV)belongs to the genus Flavivirus and the family Flavi-viridae,and is classified as a single-stranded,positive-sense RNA virus.The disease known as Japa-nese encephalitis(JE),which results from JEV infection,is a viral zoonosis that is prevalent worldwide and poses a significant public health concern.JEV infection activates a variety of signa-ling pathways,leading to a series of changes that are crucial to the virus's pathogenesis.Among these pathways,Toll-like receptors(TLRs)are particularly significant,and their diverse range and complex signal transduction mechanisms present substantial challenges for the prevention and con-trol of JEV.Currently,there is no specific treatment for JEV.Although some vaccines have been developed to prevent JE,eradicating JEV remains difficult due to its zoonotic transmission cycle and the limited efficacy of the available vaccines.This article reviews the alterations in various TLR signaling pathways induced by JEV infection in the host,aiming to provide insights into the patho-genic mechanisms of JEV and to identify potential new antiviral targets.

Porcine reproductive and respiratory syndrome virus(PRRSV)is the pathogen of porcine reproductive and respiratory syndrome(PRRS),and its infection mainly causes abortion,stillbirth in sows and piglet respiratory infections,which are widely prevalent in the world and seriously jeopardize the development of the world's animal husbandry industry.PRRSV infection of the host is capable of inducing significant immunosuppression,and in recent years,the study of the mecha-nism of PRRSV immunosuppression has become a hot topic,with studies showing that numerous PRRSV proteins are involved in the regulation of host innate immunity and elucidating the mecha-nism by which PRRSV proteins modulate host innate immunity.In this paper,we reviewed the progress of research on the interaction mechanism between PRRSV proteins and host innate im-munity to provide a theoretical basis for a comprehensive understanding of the pathogenesis of PRRSV and the prevention and control of PRRS.

To identify clinical viral diseases characterized by reproductive disorders and abortion,a quadruple qPCR method was established for simultaneous detection of PRV,PPV,PCV2 and AS-FV.Four pairs of specific primers and probes were designed according to the conserved genes of four viruses in the NCBI gene bank.The annealing temperature,primer concentration and probe concentration of the reaction were optimized,and the specificity,sensitivity and repeatability of the method were tested.The results showed that the method could not detect other pathogens except the target ones.The minimum detection limit of PRV,PPV,PCV2 and ASFV was 10 copies.Intra-group and inter-group repeatability tests showed that the coefficient of variation of C,values be-tween different batches was less than 3％,indicating that the method was highly specific,sensitive and stable.Establishment of an efficient and sensitive quadruple qPCR method provides technical reference for the clinical prevention and control of porcine pseudorabies virus disease,porcine circo-virus disease,porcine parvovirus disease and African swine fever.

This study investigates the effects of pseudorabies virus(PRV)infection on the antiviral immune signaling pathways and type Ⅰ interferon factors in mouse trigeminal ganglion(TG)cells.In this experiment,primary TG cells were infected with PRV at a multiplicity of infection(MOI)of 1,while mice were infected via a drop-nose method using 106,29 TCID50 of PRV.Real-time fluorescence quantitative PCR(qPCR),Western blot and ELISA were used to assess gene tran-scription,protein expression,and the secretion of IFN-α and IFN-β.The results indicated that PRV infection of mouse TG primary cells led to alterations in the gene and protein expression of RIG-Ⅰ,MAVS,and IRF3,as well as the phosphorylation of IRF3 and IKBα both in vivo and ex vivo.ELISA results showed that PRV infection could regulate the secretion of IFN-α and IFN-β in mouse primary TG cells and mouse TGs.The results of RIG-Ⅰ signaling pathway-related proteins and the secretion of IFN-a and IFN-β were analyzed using Western blot after using siRNA to interfere with RIG-Ⅰ expression in TG cells.The results showed that siRIG-Ⅰ successfully inter-fered with RIG-Ⅰ protein expression in TG cells and caused changes in the expression of down-stream proteins such as MAVS and IRF3,and also regulated the secretion of IFN-α and IFN-β in TG cells.Furthermore,the results indicated that PRV infection induced the expression of RIG-Ⅰ in mouse TG progenitor cells,regulating the antiviral immune response of type Ⅰ interferon factors in TG cells through the RIG-Ⅰ-MAVS-IRF3 signaling axis.Notably,PRV inhibited the expression of IRF3 in TG cells while significantly upregulating the expression of IFN-β during the later stages of infection,which may be an important factor in the important reason for the rapid mortality ob-served in mice during the late stages of PRV infection.This experiment elucidates part of the anti-viral immune mechanism mediated by the RIG-Ⅰ-MAVS-IRF3 signaling pathway in regulating type Ⅰ interferon factor after PRV infection of mouse TG cells,as well as the discovery of differ-ent trends of IRF3 protein changes in vivo and ex vivo,laying the groundwork for future in-depth studies.