Age-related macular degeneration (AMD) is a disease that affects the vision of elderly individuals worldwide. Although current therapeutics have shown effectiveness against AMD, some patients may remain unresponsive and continue to experience disease progression. Therefore, in-depth knowledge of the mechanism underlying AMD pathogenesis is urgently required to identify potential drug targets for AMD treatment. Recently, studies have suggested that dysfunction of mitochondria can lead to the aggregation of reactive oxygen species (ROS) and activation of the cyclic GMP-AMP synthase (cGAS)/stimulator of interferon genes (STING) innate immunity pathways, ultimately resulting in sterile inflammation and cell death in various cells, such as cardiomyocytes and macrophages. Therefore, combining strategies targeting mitochondrial dysfunction and inflammatory mediators may hold great potential in facilitating AMD management. Notably, emerging evidence indicates that natural products targeting mitochondrial quality control (MQC) and the cGAS/STING innate immunity pathways exhibit promise in treating AMD. Here, we summarize phytochemicals that could directly or indirectly influence the MQC and the cGAS/STING innate immunity pathways, as well as their interconnected mediators, which have the potential to mitigate oxidative stress and suppress excessive inflammatory responses, thereby hoping to offer new insights into therapeutic interventions for AMD treatment.

Age-related macular degeneration(AMD)is a disease that affects the vision of elderly individuals worldwide.Although current therapeutics have shown effectiveness against AMD,some patients may remain unresponsive and continue to experience disease progression.Therefore,in-depth knowledge of the mechanism underlying AMD pathogenesis is urgently required to identify potential drug targets for AMD treatment.Recently,studies have suggested that dysfunction of mitochondria can lead to the ag-gregation of reactive oxygen species(ROS)and activation of the cyclic GMP-AMP synthase(cGAS)/stimulator of interferon genes(STING)innate immunity pathways,ultimately resulting in sterile inflammation and cell death in various cells,such as cardiomyocytes and macrophages.Therefore,combining strategies targeting mitochondrial dysfunction and inflammatory mediators may hold great potential in facilitating AMD management.Notably,emerging evidence indicates that natural products targeting mitochondrial quality control(MQC)and the cGAS/STING innate immunity pathways exhibit promise in treating AMD.Here,we summarize phytochemicals that could directly or indirectly influence the MQC and the cGAS/STING innate immunity pathways,as well as their interconnected mediators,which have the potential to mitigate oxidative stress and suppress excessive inflammatory responses,thereby hoping to offer new insights into therapeutic interventions for AMD treatment.

Sepsis is one of the common severe diseases caused by the dysregulated host response to infection， which seriously threatens the life and health of human beings all over the world. The incidence and mortality of the disease are extremely high， and it has always been an urgent problem to be solved in the field of acute and critical diseases. At present， anti-infection， fluid resuscitation， mechanical ventilation and other programs are most used in clinic to treat sepsis， but their poor prognosis and high cost and other issues remain to be resolved. Therefore， it is necessary to explore a new， efficient， safe and inexpensive drug and treatment model at this stage. The treatment of traditional Chinese medicine （TCM） is based on syndrome differentiation and holistic concept. It can effectively regulate the progression of sepsis， maintain the homeostasis of the body， and has fewer adverse reactions. It has achieved good clinical results. In recent years， a large number of studies have shown that TCM can reduce the inflammatory response by regulating the Toll-like receptor 4（TLR4） signaling pathway， thereby reducing the severity and mortality of sepsis patients. However， there is still a lack of systematic exposition of TCM regulating TLR4 signaling pathway in the treatment of sepsis. Therefore， this article summarizes the relationship between TLR4 signaling pathway and sepsis and the mechanism of TCM in the disease by searching and consulting relevant literature in recent years. It is found that some Chinese medicine monomers and active ingredients， Chinese medicine compounds and Chinese medicine preparations can effectively reduce systemic inflammatory response， repair organ damage and improve the prognosis of sepsis by inhibiting the activation of TLR4 signaling pathway. However， due to various limitations， some studies have directly focused on the differential expression and function of TLR4， ignoring the downstream molecular expression and phenotypic effects of TLR4. The alternative mechanism， relationship and specific molecular mechanism of the pathway are still unclear. There are problems such as unclear pharmacokinetics and unclear mechanism in the pro- and anti-inflammatory balance， which need to be further studied and explored in order to provide new ideas for the potential treatment and drug development for sepsis.

Objective To explore the performance of a new multimodal feature fusion classification model based on distance matching and discriminative representation learning for differentiating high-grade glioma(HGG)from solitary brain metastasis(SBM).Methods We collected multi-parametric magnetic resonance imaging(MRI)data from 61 patients with HGG and 60 with SBM,and delineated regions of interest(ROI)on T1WI,T2WI,T2-weighted fluid attenuated inversion recovery(T2_FLAIR)and post-contrast enhancement T1WI(CE_T1WI)images.The radiomics features were extracted from each sequence using Pyradiomics and fused using a multimodal feature fusion classification model based on distance matching and discriminative representation learning to obtain a classification model.The discriminative performance of the classification model for differentiating HGG from SBM was evaluated using five-fold cross-validation with metrics of specificity,sensitivity,accuracy,and the area under the ROC curve(AUC)and quantitatively compared with other feature fusion models.Visual experiments were conducted to examine the fused features obtained by the proposed model to validate its feasibility and effectiveness.Results The five-fold cross-validation results showed that the proposed multimodal feature fusion classification model had a specificity of 0.871,a sensitivity of 0.817,an accuracy of 0.843,and an AUC of 0.930 for distinguishing HGG from SBM.This feature fusion method exhibited excellent discriminative performance in the visual experiments.Conclusion The proposed multimodal feature fusion classification model has an excellent ability for differentiating HGG from SBM with significant advantages over other feature fusion classification models in discrimination and classification tasks between HGG and SBM.

Objective To evaluate the performance of magnetic resonance imaging(MRI)multi-sequence feature imputation and fusion mutual model based on sequence deletion in differentiating high-grade glioma(HGG)from low-grade glioma(LGG).Methods We retrospectively collected multi-sequence MR images from 305 glioma patients,including 189 HGG patients and 116 LGG patients.The region of interest(ROI)of T1-weighted images(T1WI),T2-weighted images(T2WI),T2 fluid attenuated inversion recovery(T2_FLAIR)and post-contrast enhancement T1WI(CE_T1WI)were delineated to extract the radiomics features.A mutual-aid model of MRI multi-sequence feature imputation and fusion based on sequence deletion was used for imputation and fusion of the feature matrix with missing data.The discriminative ability of the model was evaluated using 5-fold cross-validation method and by assessing the accuracy,balanced accuracy,area under the ROC curve(AUC),specificity,and sensitivity.The proposed model was quantitatively compared with other non-holonomic multimodal classification models for discriminating HGG and LGG.Class separability experiments were performed on the latent features learned by the proposed feature imputation and fusion methods to observe the classification effect of the samples in two-dimensional plane.Convergence experiments were used to verify the feasibility of the model.Results For differentiation of HGG from LGG with a missing rate of 10%,the proposed model achieved accuracy,balanced accuracy,AUC,specificity,and sensitivity of 0.777,0.768,0.826,0.754 and 0.780,respectively.The fused latent features showed excellent performance in the class separability experiment,and the algorithm could be iterated to convergence with superior classification performance over other methods at the missing rates of 30%and 50%.Conclusion The proposed model has excellent performance in classification task of HGG and LGG and outperforms other non-holonomic multimodal classification models,demonstrating its potential for efficient processing of non-holonomic multimodal data.

Objective To explore the performance of a new multimodal feature fusion classification model based on distance matching and discriminative representation learning for differentiating high-grade glioma(HGG)from solitary brain metastasis(SBM).Methods We collected multi-parametric magnetic resonance imaging(MRI)data from 61 patients with HGG and 60 with SBM,and delineated regions of interest(ROI)on T1WI,T2WI,T2-weighted fluid attenuated inversion recovery(T2_FLAIR)and post-contrast enhancement T1WI(CE_T1WI)images.The radiomics features were extracted from each sequence using Pyradiomics and fused using a multimodal feature fusion classification model based on distance matching and discriminative representation learning to obtain a classification model.The discriminative performance of the classification model for differentiating HGG from SBM was evaluated using five-fold cross-validation with metrics of specificity,sensitivity,accuracy,and the area under the ROC curve(AUC)and quantitatively compared with other feature fusion models.Visual experiments were conducted to examine the fused features obtained by the proposed model to validate its feasibility and effectiveness.Results The five-fold cross-validation results showed that the proposed multimodal feature fusion classification model had a specificity of 0.871,a sensitivity of 0.817,an accuracy of 0.843,and an AUC of 0.930 for distinguishing HGG from SBM.This feature fusion method exhibited excellent discriminative performance in the visual experiments.Conclusion The proposed multimodal feature fusion classification model has an excellent ability for differentiating HGG from SBM with significant advantages over other feature fusion classification models in discrimination and classification tasks between HGG and SBM.

Objective To evaluate the performance of magnetic resonance imaging(MRI)multi-sequence feature imputation and fusion mutual model based on sequence deletion in differentiating high-grade glioma(HGG)from low-grade glioma(LGG).Methods We retrospectively collected multi-sequence MR images from 305 glioma patients,including 189 HGG patients and 116 LGG patients.The region of interest(ROI)of T1-weighted images(T1WI),T2-weighted images(T2WI),T2 fluid attenuated inversion recovery(T2_FLAIR)and post-contrast enhancement T1WI(CE_T1WI)were delineated to extract the radiomics features.A mutual-aid model of MRI multi-sequence feature imputation and fusion based on sequence deletion was used for imputation and fusion of the feature matrix with missing data.The discriminative ability of the model was evaluated using 5-fold cross-validation method and by assessing the accuracy,balanced accuracy,area under the ROC curve(AUC),specificity,and sensitivity.The proposed model was quantitatively compared with other non-holonomic multimodal classification models for discriminating HGG and LGG.Class separability experiments were performed on the latent features learned by the proposed feature imputation and fusion methods to observe the classification effect of the samples in two-dimensional plane.Convergence experiments were used to verify the feasibility of the model.Results For differentiation of HGG from LGG with a missing rate of 10%,the proposed model achieved accuracy,balanced accuracy,AUC,specificity,and sensitivity of 0.777,0.768,0.826,0.754 and 0.780,respectively.The fused latent features showed excellent performance in the class separability experiment,and the algorithm could be iterated to convergence with superior classification performance over other methods at the missing rates of 30%and 50%.Conclusion The proposed model has excellent performance in classification task of HGG and LGG and outperforms other non-holonomic multimodal classification models,demonstrating its potential for efficient processing of non-holonomic multimodal data.

Sepsis is a life-threatening Organ Dysfunction disease caused by the dysregulated response of the body to infection.It is characterized by fever,chills,shortness of breath,altered consciousness,and even severe complications such as Multiple Organ Dysfunction Syndrome(MODS).The morbidity and mortality of this disease are high year after year,and there are problems such as large consumption of medical resources and poor prognosis,which seriously affect the quality of life and economic burden of patients.Therefore,it is important to explore new treatments with high efficiency,safety and low cost.The disease pathogenesis is complex,including inflammation imbalance is the main pathogenesis of sepsis.Mitogen-Activated Protein Kinases(MAPK)signaling pathway is a signaling pathway activated by environmental factors or inflammatory factors,which mediates proliferation,differentiation,inflammatory response and apoptosis,and plays a key role in the occurrence and development of sepsis.At present,antibiotics,fluid resuscitation and mechanical ventilation are the main methods for clinical treatment of sepsis.Although they can curb the progress of some diseases,some treatment effects are not good.A large amount of literature has confirmed that Chinese medicine intervention in sepsis has significant advantages,its through many channels,regulation and control of multiple targets,MAPK signaling pathways,inhibit inflammation,strengthening immune defense and effective in the treatment of sepsis,sepsis is current research hotspot.However,there is still a lack of systematic reviews on the regulation of MAPK signaling pathway by traditional Chinese medicine in the treatment of sepsis.Therefore,based on the retrieval database sepsis related literature at home and abroad in recent years,a systemic summary of MAPK signal pathway and sepsis relations and the role of traditional Chinese medicine in them,will be new drugs for the treatment of sepsis and development provides new theoretical support.

Sepsis is a life-threatening Organ Dysfunction disease caused by the dysregulated response of the body to infection.It is characterized by fever,chills,shortness of breath,altered consciousness,and even severe complications such as Multiple Organ Dysfunction Syndrome(MODS).The morbidity and mortality of this disease are high year after year,and there are problems such as large consumption of medical resources and poor prognosis,which seriously affect the quality of life and economic burden of patients.Therefore,it is important to explore new treatments with high efficiency,safety and low cost.The disease pathogenesis is complex,including inflammation imbalance is the main pathogenesis of sepsis.Mitogen-Activated Protein Kinases(MAPK)signaling pathway is a signaling pathway activated by environmental factors or inflammatory factors,which mediates proliferation,differentiation,inflammatory response and apoptosis,and plays a key role in the occurrence and development of sepsis.At present,antibiotics,fluid resuscitation and mechanical ventilation are the main methods for clinical treatment of sepsis.Although they can curb the progress of some diseases,some treatment effects are not good.A large amount of literature has confirmed that Chinese medicine intervention in sepsis has significant advantages,its through many channels,regulation and control of multiple targets,MAPK signaling pathways,inhibit inflammation,strengthening immune defense and effective in the treatment of sepsis,sepsis is current research hotspot.However,there is still a lack of systematic reviews on the regulation of MAPK signaling pathway by traditional Chinese medicine in the treatment of sepsis.Therefore,based on the retrieval database sepsis related literature at home and abroad in recent years,a systemic summary of MAPK signal pathway and sepsis relations and the role of traditional Chinese medicine in them,will be new drugs for the treatment of sepsis and development provides new theoretical support.

BACKGROUND: LY01005 (Goserelin acetate sustained-release microsphere injection) is a modified gonadotropin-releasing hormone (GnRH) agonist injected monthly. This phase III trial study aimed to evaluated the efficacy and safety of LY01005 in Chinese patients with prostate cancer. METHODS: We conducted a randomized controlled, open-label, non-inferiority trial across 49 sites in China. This study included 290 patients with prostate cancer who received either LY01005 or goserelin implants every 28 days for three injections. The primary efficacy endpoints were the percentage of patients with testosterone suppression ≤50 ng/dL at day 29 and the cumulative probability of testosterone ≤50 ng/dL from day 29 to 85. Non-inferiority was prespecified at a margin of -10%. Secondary endpoints included significant castration (≤20 ng/dL), testosterone surge within 72 h following repeated dosing, and changes in luteinizing hormone, follicle-stimulating hormone, and prostate specific antigen levels. RESULTS: On day 29, in the LY01005 and goserelin implant groups, testosterone concentrations fell below medical-castration levels in 99.3% (142/143) and 100% (140/140) of patients, respectively, with a difference of -0.7% (95% confidence interval [CI], -3.9% to 2.0%) between the two groups. The cumulative probabilities of maintaining castration from days 29 to 85 were 99.3% and 97.8%, respectively, with a between-group difference of 1.5% (95% CI, -1.3% to 4.4%). Both results met the criterion for non-inferiority. Secondary endpoints were similar between groups. Both treatments were well-tolerated. LY01005 was associated with fewer injection-site reactions than the goserelin implant (0% vs . 1.4% [2/145]). CONCLUSION: LY01005 is as effective as goserelin implants in reducing testosterone to castration levels, with a similar safety profile. TRIAL REGISTRATION ClinicalTrials.gov, NCT04563936.
Humans ; Male ; Antineoplastic Agents, Hormonal/therapeutic use* ; East Asian People ; Gonadotropin-Releasing Hormone/agonists* ; Goserelin/therapeutic use* ; Prostate-Specific Antigen ; Prostatic Neoplasms/drug therapy* ; Testosterone