1.Preparation and evaluation of long-acting light-protective nanogel based on fullerenol-cerium oxide composite system
Tianlong ZHANG ; Jia LIU ; Qing ZHAO ; Yue ZHOU ; Ming YANG ; Qianyu LUO
China Pharmacy 2025;36(17):2106-2112
OBJECTIVE To develop a long-acting light-protective nanogel with both physical barrier and chemical clearance functions, and evaluate its performance. METHODS The photoprotective nanogel composed of mussel mucin and sodium hyaluronate was constructed based on a fullerenol-cerium oxide composite nano system, namely fullerenol-cerium oxide nanogel (FCN), and was characterized. The antioxidant capacity of FCN was evaluated using in vitro free radical scavenging experiments; its UV shielding ability was assessed by using an SPF value detector; its biosafety was assessed according to the requirements of the Guidelines for Drug Safety Evaluation; skin adhesion was assessed using small animal 3D live imaging technology; its sun protection ability was assessed through skin sunscreen detection and histopathological observation. RESULTS The average particle sizes of cerium oxide and fullerenol nanoparticles in FCN were about 20 and 10 nm, respectively, and FCN exhibited good UV absorption and free radical scavenging abilities. SPF value of FCN was 58.95±0.82, and the ultraviolet A protection level value was 6.21±0.15. No pathogenic colonies such as Staphylococcus aureus, were detected in the nanogel, and the contents of lead, arsenic, mercury and cadmium all met the standards for pharmaceutical excipients; FCN group did not show any irritating reactions such as erythema, edema, or desquamation; blood biochemical indicators of the FCN group were within the normal reference range. The material clearance rate of mice in the artificial sweat flushing group was less than 30%, while the material clearance rate of mice in the dry cleaning group reached about 92%. The mice in the protective group did not show obvious erythema or ulcer formation throughout the experiment. Histopathology showed that the fibers were arranged in an orderly manner, and the number of collagen fibers was close to that of the control group. CONCLUSIONS The FCN formulation constructed in this study meets the relevant requirements of the Chinese Pharmacopoeia, has good safety and skin compatibility, and achieves dual synergistic protection of UV shielding and free radical scavenging.
2.Wenxia Changfu Formula inhibits NSCLC metastasis by halting TAMs-induced epithelial-mesenchymal transition via antagonisticallymodulating CCL18.
Qianyu BI ; Mengran WANG ; Li LUO ; Beiying ZHANG ; Siyuan LV ; Zengna WANG ; Xuming JI
Chinese Journal of Natural Medicines (English Ed.) 2025;23(7):838-847
Our previous research demonstrated that the Wenxia Changfu Formula (WCF), as a neoadjuvant therapy, inhibits M2 macrophage infiltration in the tumor microenvironment and prevents lung cancer metastasis. Given tumor-associated macrophages (TAMs) in epithelial-mesenchymal transition (EMT), this study investigated whether WCF impedes lung cancer metastasis by attenuating TAM-induced EMT in non-small cell lung cancer (NSCLC) cells. Utilizing a co-culture model treated with or without WCF, we observed that WCF downregulated cluster of differentiation 163 (CD163) expression in macrophages, reduced CCL18 levels in the conditioned medium, and inhibited the growth, invasion, and EMT of NSCLC cells induced by macrophage co-culture. Manipulation of CCL18 levels and Src overexpression in NSCLC cells revealed that WCF's effects are mediated through CCL18 and Src signaling. In vivo, WCF inhibited recombinant CCL18 (rCCL18)-induced tumor metastasis in nude mice by blocking Src signaling. These findings indicate that WCF inhibits NSCLC metastasis by impeding TAM-induced EMT via antagonistic modulation of CCL18, providing evidence for its potential development and clinical application in NSCLC patients.
Epithelial-Mesenchymal Transition/drug effects*
;
Carcinoma, Non-Small-Cell Lung/metabolism*
;
Humans
;
Animals
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Lung Neoplasms/metabolism*
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Chemokines, CC/antagonists & inhibitors*
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Mice
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Mice, Nude
;
Drugs, Chinese Herbal/administration & dosage*
;
Cell Line, Tumor
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Neoplasm Metastasis
;
Tumor-Associated Macrophages/drug effects*
;
Mice, Inbred BALB C
;
Signal Transduction/drug effects*
3.Multiparametric MRI to Predict Gleason Score Upgrading and Downgrading at Radical Prostatectomy Compared to Presurgical Biopsy
Jiahui ZHANG ; Lili XU ; Gumuyang ZHANG ; Daming ZHANG ; Xiaoxiao ZHANG ; Xin BAI ; Li CHEN ; Qianyu PENG ; Zhengyu JIN ; Hao SUN
Korean Journal of Radiology 2025;26(5):422-434
Objective:
This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy.
Materials and Methods:
Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP.
Results:
The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001).
Conclusion
Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.
4.Multiparametric MRI to Predict Gleason Score Upgrading and Downgrading at Radical Prostatectomy Compared to Presurgical Biopsy
Jiahui ZHANG ; Lili XU ; Gumuyang ZHANG ; Daming ZHANG ; Xiaoxiao ZHANG ; Xin BAI ; Li CHEN ; Qianyu PENG ; Zhengyu JIN ; Hao SUN
Korean Journal of Radiology 2025;26(5):422-434
Objective:
This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy.
Materials and Methods:
Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP.
Results:
The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001).
Conclusion
Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.
5.Multiparametric MRI to Predict Gleason Score Upgrading and Downgrading at Radical Prostatectomy Compared to Presurgical Biopsy
Jiahui ZHANG ; Lili XU ; Gumuyang ZHANG ; Daming ZHANG ; Xiaoxiao ZHANG ; Xin BAI ; Li CHEN ; Qianyu PENG ; Zhengyu JIN ; Hao SUN
Korean Journal of Radiology 2025;26(5):422-434
Objective:
This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy.
Materials and Methods:
Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP.
Results:
The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001).
Conclusion
Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.
6.Multiparametric MRI to Predict Gleason Score Upgrading and Downgrading at Radical Prostatectomy Compared to Presurgical Biopsy
Jiahui ZHANG ; Lili XU ; Gumuyang ZHANG ; Daming ZHANG ; Xiaoxiao ZHANG ; Xin BAI ; Li CHEN ; Qianyu PENG ; Zhengyu JIN ; Hao SUN
Korean Journal of Radiology 2025;26(5):422-434
Objective:
This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy.
Materials and Methods:
Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP.
Results:
The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001).
Conclusion
Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.
7.Multiparametric MRI to Predict Gleason Score Upgrading and Downgrading at Radical Prostatectomy Compared to Presurgical Biopsy
Jiahui ZHANG ; Lili XU ; Gumuyang ZHANG ; Daming ZHANG ; Xiaoxiao ZHANG ; Xin BAI ; Li CHEN ; Qianyu PENG ; Zhengyu JIN ; Hao SUN
Korean Journal of Radiology 2025;26(5):422-434
Objective:
This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy.
Materials and Methods:
Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP.
Results:
The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001).
Conclusion
Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.
8.Brain functional networks in children with spastic cerebral palsy and their correlation with motor function as analyzed based on fNIRS
Yangyang CAO ; Xiaokang TANG ; Qianyu GUO ; Jun WANG ; Dengna ZHU ; Gongxun CHEN ; Yuhang ZHANG ; Junying YUAN ; Juan SONG ; Yiran XU
Chinese Journal of Physical Medicine and Rehabilitation 2025;47(11):998-1004
Objective:To explore the characteristics of the brain functional networks in children with spastic cerebral palsy (SCP) while at rest and to correlate them with motor functioning.Methods:Thirty-six children with SCP were enrolled as the SCP group, while thirty-four age-matched healthy children were recruited as the control group (the HC group). Functional near-infrared spectroscopy was used to detect changes in the concentration of oxygenated hemoglobin in the children′s cerebral cortex while at rest. The left prefrontal cortex (LPFC), right prefrontal cortex (RPFC), left motor cortex (LMC), and right motor cortex (RMC) were selected as regions of interest. Phase locking values (PLVs) were used to evaluate the strength of functional connectivity (FC) among these brain regions, and graph theory methods were applied to analyze the topological properties of the brain networks. Motor functioning was assessed using the gross motor function measure (GMFM).Results:The analyses of FC strength revealed that the SCP group had significantly weaker FC among all of the regions of interest while at rest compared to the HC group. Their PLVs for LPFC-RPFC, LPFC-RMC, RPFC-RMC and LMC-RMC connectivity were all significantly smaller. Graph theory analysis showed that the SCP group had significantly lower global efficiency (GE) and smaller clustering coefficients (CCs) and network density (D), while their characteristic path lengths were significantly longer. According to the correlation analysis, the PLVs for LMC-RMC connections in the SCP group were positively correlated with their scores on dimensions D and E of the GMFM ( r=0.496 and r=0.579 respectively). GE ( r=0.587 and r=0.642) and CC ( r=0.318 and r=0.759) showed similar significant positive correlations with GMFM dimensions D and E. Conclusions:At rest, the functional networks in the brains of children with SCP exhibit abnormalities closely associated with their motor dysfunction.
9.Effect of TINCR-MAF:MAFB transcription factor network on proliferation and differentiation of human kerathnocytes
Jinfen ZHENG ; Cuiping SHI ; Yunxia LING ; Dehua ZHANG ; Qianyu ZHAI ; Lijia ZHU ; Doukou JIANG ; Xiaohong WANG ; Yonghui LAI
The Journal of Practical Medicine 2025;41(4):509-514
Objective To explore the impact of the TINCR-MAF:MAFB transcription factor network on the expression of proliferation and differentiation-related genes in keratinocytes,to verify the role of this network in the occurrence and development of psoriasis and its potential mechanisms.Methods Employed RNA interference technology to knock down TINCR gene expression,and the proliferation ability of keratinocytes was assessed using the CCK-8 method.Additionally,qRT-PCR and Western blot analyses were conducted to evaluate the RNA and protein expression levels of TINCR,MAFB,and KLF4 genes.Immunohistochemical methods were used to detect the expression of KLF4 protein in psoriasis tissues.Results After TINCR gene siRNA interference,the proliferation ability of keratinocytes significantly decreased at 24,48,and 72 hours(P<0.001),indicating that the TINCR gene plays a critical role in cell proliferation.The results of qRT-PCR and Western blot analyses showed that the RNA and protein expression levels of TINCR,MAFB,and KLF4 genes were significantly reduced(P<0.001),suggesting that TINCR may influence the differentiation of keratinocytes by regulating the expression of MAFB transcription factor and KLF4 differentiation-related genes.Furthermore,immunohistochemical results indicated that the expression of KLF4 protein was significantly elevated in psoriasis tissues compared to normal skin tissues,suggesting that KLF4 plays an important role in the pathogenesis of psoriasis.Conclusions The TINCR-MAF:MAFB transcription factor network may participate in the occurrence and development of psoriasis by affecting the proliferation and differentiation of keratinocytes.This finding provides a new perspective on the pathogenesis of psoriasis and potential targets for future therapeutic strategies.
10.Protective effect of Liraglutide inrats with diabetic kidney disease by regulating nuclear factor E2-related factor 2/glutathione peroxidase 4 ferroptosis signaling pathway
Dong LIANG ; Qianyu LIN ; Min YANG ; Mengjie LI ; Wenhua XING ; Ning YU ; Yunqi LIU ; Xiaomin ZHANG
Chinese Journal of Diabetes 2025;33(4):299-303
Objective To investigate the protective effect of Liraglutide in rats with diabetic kidney disease(DKD)by regulating the nuclear factor E2-related factor 2(Nrf2)/glutathione peroxidase 4(GPX4)ferroptosis signaling pathway.Methods Twelve male Sprague-Dawley(SD)rats were randomly divided into normal control(NC)group,DKD group,and Liraglutide treatment(Lir)group,with 4 rats in each group.The 24 hUAlb,TC,TG,LDL-C,serum creatinine(Scr),BUN,ferrous ion(Fe2+),the activity of glutathione peroxidase(GSH-Px),and malondialdehyde(MDA)were detected in each group.Hematoxylin and eosin(HE),periodic acid-Schiff(PAS),and periodic acid-silver methenamine-Masson(PASM-Masson)staining were used to observe the pathological changes of the kidneys.Immunofluorescence was performed to detect the localization and expression of reactive oxygen species(ROS)in the renal tissue.The protein expressions of Nrf2 and GPX4 were detected by Western blot.Results Compared with the NC group,the levels of 24 hUAlb,Scr,BUN,TC,TG,LDL-C,MDA,ROS,and Fe2+were increased(P<0.05 or P<0.01),while the expressions of GSH-Px,Nrf2,and GPX4 proteins were decreased in the DKD group(P<0.01).Compared with the DKD group,the levels of 24 hUAlb,BUN,TC,TG,LDL-C,MDA,ROS,and Fe2+were decreased(P<0.05 or P<0.01),and the expressions of GSH-Px,Nrf2,and GPX4 proteins were increased in the Lir group(P<0.01).Conclusions Liraglutide may exert a protective effect in DKD by upregulating the Nrf2/GPX4 signaling pathway and inhibiting ferroptosis.

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