Collagen-based materials, renowned for their biocompatibility and minimal immunogenicity, serve as exemplary substrates in a myriad of biomedical applications. Collagen-based micro/nanogels, in particular, are valued for their increased surface area, tunable degradation rates, and ability to facilitate targeted drug delivery, making them instrumental in advanced therapeutics and tissue engineering endeavors. Although extensive reviews on micro/nanogels exist, they tend to cover a wide range of biomaterials and lack a specific focus on collagen-based materials. The current review offers an in-depth look into the manufacturing technologies, drug release mechanisms, and biomedical applications of collagen-based micro/nanogels to address this gap. First, we provide an overview of the synthetic strategies that allow the precise control of the size, shape, and mechanical strength of these collagen-based micro/nanogels by controlling the degree of cross-linking of the materials. These properties are crucial for their performance in biomedical applications. We then highlight the environmental responsiveness of these collagen-based micro/nanogels, particularly their sensitivity to enzymes and pH, which enables controlled drug release under various pathological conditions. The discussion then expands to include their applications in cancer therapy, antimicrobial treatments, bone tissue repair, and imaging diagnosis, emphasizing their versatility and potential in these critical areas. The challenges and future perspectives of collagen-based micro/nanogels in the field are discussed at the end of the review, with an emphasis on the translation to clinical practice. This comprehensive review serves as a valuable resource for researchers, clinicians, and scientists alike, providing insights into the current state and future directions of collagen-based micro/nanogel research and development.
Collagen/chemistry* ; Drug Delivery Systems/methods* ; Humans ; Tissue Engineering/methods* ; Animals ; Biocompatible Materials/chemistry*

Xiaoaiping (XAP) Injection demonstrates the anti-prostate cancer (PCa) effects, yet the underlying mechanism remains unclear. This study aims to investigate the impact of XAP on PCa and elucidate its mechanism of action. PCa cell proliferation was evaluated using a cell counting kit-8 (CCK-8) assay. Cell apoptosis was assessed through Hoechst staining and Western blotting assays. Proteomics technology was employed to identify key molecules and significant signaling pathways modulated by XAP in PCa cells. To further validate potential key genes and important pathways, a series of assays were conducted, including acridine orange (AO) staining, transmission electron microscopy, and immunofluorescence assays. The molecular mechanism of XAP against PCa in vivo was examined using a PC3 xenograft mouse model. Results demonstrated that XAP significantly inhibited cell proliferation in multiple PCa cell lines. In C4-2 and prostate cancer cell line-3 (PC3) cells, XAP induced cellular apoptosis, evidenced by reduced B-cell lymphoma 2 (Bcl-2) levels and elevated Bcl-2-associated X (Bax) levels. Proteomic, immunofluorescence, and quantitative reverse transcription-polymerase chain reaction (qRT-PCR) investigations revealed a strong correlation between forkhead box O3a (FoxO3a) autophagic degradation and the anti-PCa action of XAP. XAP hindered autophagy by reducing the expression levels of autophagy-related protein 5 (Atg5)/autophagy-related protein 12 (Atg12) and enhancing FoxO3a expression and nuclear translocation. Furthermore, XAP exhibited potent anti-PCa action in PC3 xenograft mice and triggered FoxO3a nuclear translocation in tumor tissue. These findings suggest that XAP induces PCa apoptosis via inhibition of FoxO3a autophagic degradation, potentially offering a novel perspective on XAP injection as an effective anticancer therapy for PCa.
Male ; Humans ; Prostatic Neoplasms/physiopathology* ; Autophagy/drug effects* ; Animals ; Drugs, Chinese Herbal/pharmacology* ; Proteomics ; Mice ; Apoptosis/drug effects* ; Cell Line, Tumor ; Cell Proliferation/drug effects* ; Forkhead Box Protein O3/genetics* ; Xenograft Model Antitumor Assays ; Mice, Nude ; Mice, Inbred BALB C

Objective:To explore the predictive factors for ureteral stone impaction preoperatively and to construct a nomogram prediction model for impacted ureteral stones.Methods:A retrospective analysis was conducted on the clinical data of 209 patients with ureteral stones treated at The Second Affiliated Hospital of Zhengzhou University from July 2023 to June 2024. There were 164 males（78.5%）and 45 females（21.5%）. The age was 49（47，57）years，and the body mass index（BMI）was 25.10（23.55，27.24）kg/m2. Of the patients，85（40.7%）had comorbid hypertension and 85（40.7%）had comorbid diabetes. Stones were located on the left side in 124 patients（59.3%）and on the right side in 85 patients（40.7%）. Hydronephrosis was present in 169 patients（80.9%），and urine culture was positive in 29 patients（13.9%）. Patients were divided into impacted and non-impacted groups based on the presence or absence of ureteral stone impaction. Univariate and multivariate logistic regression analyses were performed to determine independent predictive factors for impacted ureteral stones. A nomogram model was constructed based on these results. The performance of the predictive model was evaluated using receiver operating characteristic（ROC）curves，calibration plots，and decision curve analysis（DCA）.Results:Among the 209 patients in this study，85（40.7%）experienced ureteral stone impaction. The impacted group had a significantly higher neutrophil-to-lymphocyte ratio（NLR）than the non-impacted group（3.91 ± 2.05 vs. 3.25 ± 2.10， P = 0.024），a higher rate of hydronephrosis［81.2%（69/85）vs. 80.6%（100/124）， P = 0.002］，larger stone surface area［（64.96 ± 39.96）mm2 vs.（51.86 ± 39.80）mm2， P = 0.021］，greater ureteral wall thickness（UWT）［（3.96 ± 1.37）mm vs.（3.06 ± 1.33）mm， P < 0.001］，and a higher ratio of the upper ureter diameter（D1）to the lower ureter diameter（D2）（DDR）（2.87 ± 1.58 vs. 2.00 ± 0.99， P < 0.001）. Univariate analysis showed that NLR，hydronephrosis，stone length，stone surface area，UWT，D1，D2，and DDR were statistically significant（ P < 0.05）. After multivariate logistic regression analysis，the following items were identified as independent predictors of impacted ureteral stones：NLR（ OR = 1.205，95% CI 1.026 - 1.415， P = 0.023），hydronephrosis（ OR = 1.840，95% CI 1.236 - 2.740， P = 0.003），stone length（ OR = 1.587，95% CI 1.142 - 2.206， P = 0.006），ureteral wall thickness（UWT）（ OR = 1.643，95% CI 1.263 - 2.136， P < 0.001），and DDR（ OR = 2.907，95% CI 1.040 - 8.130， P = 0.042）.Based on these independent predictive factors，a nomogram prediction model for impacted ureteral stones was constructed. The area under the ROC curve was 0.797（95% CI 0.737 - 0.858），and the calibration curve showed good consistency. The decision curve suggested that the model had good clinical net benefit. Conclusions:NLR，hydronephrosis，stone length，UWT，and DDR are all independent predictors for impacted ureteral stones. The nomogram model constructed based on these factors has good predictive performance.

Objective:To explore the independent factors influencing extraprostatic extension (EPE) after radical prostatectomy(RP) in patients with clinically localized prostate cancer by utilizing the Surveillance, Epidemiology, and End Results (SEER) database. A nomogram model was developed and externally validated.Methods:Clinical and pathological data of 20 916 clinically localized prostate cancer patients (T 1-2N 0M 0) who underwent RP between 2010 and 2021 were extracted from the SEER database. The mean age was (61.71±7.09) years old, and a total of 17 835 patients (85.3%) were married.There were 2 243 patients (10.7%) with prostate-specific antigen (PSA) <4 ng/ml, 14 831 patients (70.9%) with ≥4 and <10 ng/ml, and 2 965 patients (14.2%) with ≥10 and <20 ng/ml. There were 14 870 patients (71.1%) with clinical staging of stage T 1, and 6 046 patients (28.9%) with T 2. There were 48 patients (0.2%) with pathological staging of stage T 1, 15 794 (75.5%) with T 2, 5 001(23.9%) with T 3, and 73 (0.3%) with T 4 stage after radical surgery.The patients of SEER database were divided into training and internal validation groups in a 7∶3 ratio by using stratified sampling. Additionally, data were collected for 75 clinically localized prostate cancer patients who underwent RP at the Second Affiliated Hospital of Zhengzhou University from September 2019 to September 2024, serving as the external validation group.The mean age was(65.39±7.45) years old. Among them, 73 (97.3%) were married. There were 2 patients (2.7%) with PSA <4 ng/ml, 17 patients (22.7%) with ≥4 and <10 ng/ml, and 34 patients (45.3%) with ≥10 and <20 ng/ml. There were 47 patients (62.7%) with clinical staging of stage T 1, and 28 patients (37.3%) with T 2. There were 7 patients (9.3%) with pathological staging of stage T 1, 48 patients (64.0%)with T 2, 18 patients (24.0%) with T 3, and 2 patients (2.7%) with T 4 stage after radical surgery. All patients were categorized into organ-confined (OC) and EPE groups based on post-surgical pathology. Univariate and multivariate logistic regression analyses, with a stepwise backward selection, were performed on the training group to identify independent risk factors of EPE, which were used to construct a nomogram model. Model performance was assessed using receiver operating characteristic (ROC) curve area under the curve (AUC), calibration curves, and decision curve analysis (DCA) for the training group, internal validation group, and external validation group. Results:EPE was observed in 3 585 cases (24.5%), 1 489 cases (23.8%), and 20 cases (26.7%) in the training, internal validation, and external validation groups, respectively. Logistic regression analyses identified preoperative age ( OR=1.026, P<0.001), PSA levels (≥10 and <20 ng/ml: OR=1.790, P<0.001; ≥20 ng/ml: OR=2.683, P<0.001), tumor maximum diameter (10-20 mm: OR=2.051, P<0.001; >20 mm: OR=3.937, P<0.001), biopsy Gleason score (score 7: OR=1.911, P<0.001; score 8: OR=2.906, P<0.001; score 9: OR = 5.278, P<0.001; score 10: OR=4.421, P=0.003), number of positive biopsy cores (≥4 cores: OR=1.260, P<0.001), and their proportion of total cores ( OR=1.012, P<0.001) as independent predictors of EPE. The nomogram model demonstrated good predictive performance, with AUC of 0.741, 0.748, and 0.724 in the training, internal validation, and external validation groups, respectively. Calibration and DCA curves confirmed the model’s excellent stability and generalizability. Conclusions:Age, PSA levels, maximum tumor diameter, biopsy Gleason score, number of positive biopsy cores, and their proportion of total cores are independent predictors of EPE after RP in clinically localized prostate cancer. The constructed model effectively predicts the risk of EPE occurrence.

Objective:To explore the independent factors influencing extraprostatic extension (EPE) after radical prostatectomy(RP) in patients with clinically localized prostate cancer by utilizing the Surveillance, Epidemiology, and End Results (SEER) database. A nomogram model was developed and externally validated.Methods:Clinical and pathological data of 20 916 clinically localized prostate cancer patients (T 1-2N 0M 0) who underwent RP between 2010 and 2021 were extracted from the SEER database. The mean age was (61.71±7.09) years old, and a total of 17 835 patients (85.3%) were married.There were 2 243 patients (10.7%) with prostate-specific antigen (PSA) <4 ng/ml, 14 831 patients (70.9%) with ≥4 and <10 ng/ml, and 2 965 patients (14.2%) with ≥10 and <20 ng/ml. There were 14 870 patients (71.1%) with clinical staging of stage T 1, and 6 046 patients (28.9%) with T 2. There were 48 patients (0.2%) with pathological staging of stage T 1, 15 794 (75.5%) with T 2, 5 001(23.9%) with T 3, and 73 (0.3%) with T 4 stage after radical surgery.The patients of SEER database were divided into training and internal validation groups in a 7∶3 ratio by using stratified sampling. Additionally, data were collected for 75 clinically localized prostate cancer patients who underwent RP at the Second Affiliated Hospital of Zhengzhou University from September 2019 to September 2024, serving as the external validation group.The mean age was(65.39±7.45) years old. Among them, 73 (97.3%) were married. There were 2 patients (2.7%) with PSA <4 ng/ml, 17 patients (22.7%) with ≥4 and <10 ng/ml, and 34 patients (45.3%) with ≥10 and <20 ng/ml. There were 47 patients (62.7%) with clinical staging of stage T 1, and 28 patients (37.3%) with T 2. There were 7 patients (9.3%) with pathological staging of stage T 1, 48 patients (64.0%)with T 2, 18 patients (24.0%) with T 3, and 2 patients (2.7%) with T 4 stage after radical surgery. All patients were categorized into organ-confined (OC) and EPE groups based on post-surgical pathology. Univariate and multivariate logistic regression analyses, with a stepwise backward selection, were performed on the training group to identify independent risk factors of EPE, which were used to construct a nomogram model. Model performance was assessed using receiver operating characteristic (ROC) curve area under the curve (AUC), calibration curves, and decision curve analysis (DCA) for the training group, internal validation group, and external validation group. Results:EPE was observed in 3 585 cases (24.5%), 1 489 cases (23.8%), and 20 cases (26.7%) in the training, internal validation, and external validation groups, respectively. Logistic regression analyses identified preoperative age ( OR=1.026, P<0.001), PSA levels (≥10 and <20 ng/ml: OR=1.790, P<0.001; ≥20 ng/ml: OR=2.683, P<0.001), tumor maximum diameter (10-20 mm: OR=2.051, P<0.001; >20 mm: OR=3.937, P<0.001), biopsy Gleason score (score 7: OR=1.911, P<0.001; score 8: OR=2.906, P<0.001; score 9: OR = 5.278, P<0.001; score 10: OR=4.421, P=0.003), number of positive biopsy cores (≥4 cores: OR=1.260, P<0.001), and their proportion of total cores ( OR=1.012, P<0.001) as independent predictors of EPE. The nomogram model demonstrated good predictive performance, with AUC of 0.741, 0.748, and 0.724 in the training, internal validation, and external validation groups, respectively. Calibration and DCA curves confirmed the model’s excellent stability and generalizability. Conclusions:Age, PSA levels, maximum tumor diameter, biopsy Gleason score, number of positive biopsy cores, and their proportion of total cores are independent predictors of EPE after RP in clinically localized prostate cancer. The constructed model effectively predicts the risk of EPE occurrence.

Objective:To explore the predictive factors for ureteral stone impaction preoperatively and to construct a nomogram prediction model for impacted ureteral stones.Methods:A retrospective analysis was conducted on the clinical data of 209 patients with ureteral stones treated at The Second Affiliated Hospital of Zhengzhou University from July 2023 to June 2024. There were 164 males（78.5%）and 45 females（21.5%）. The age was 49（47，57）years，and the body mass index（BMI）was 25.10（23.55，27.24）kg/m2. Of the patients，85（40.7%）had comorbid hypertension and 85（40.7%）had comorbid diabetes. Stones were located on the left side in 124 patients（59.3%）and on the right side in 85 patients（40.7%）. Hydronephrosis was present in 169 patients（80.9%），and urine culture was positive in 29 patients（13.9%）. Patients were divided into impacted and non-impacted groups based on the presence or absence of ureteral stone impaction. Univariate and multivariate logistic regression analyses were performed to determine independent predictive factors for impacted ureteral stones. A nomogram model was constructed based on these results. The performance of the predictive model was evaluated using receiver operating characteristic（ROC）curves，calibration plots，and decision curve analysis（DCA）.Results:Among the 209 patients in this study，85（40.7%）experienced ureteral stone impaction. The impacted group had a significantly higher neutrophil-to-lymphocyte ratio（NLR）than the non-impacted group（3.91 ± 2.05 vs. 3.25 ± 2.10， P = 0.024），a higher rate of hydronephrosis［81.2%（69/85）vs. 80.6%（100/124）， P = 0.002］，larger stone surface area［（64.96 ± 39.96）mm2 vs.（51.86 ± 39.80）mm2， P = 0.021］，greater ureteral wall thickness（UWT）［（3.96 ± 1.37）mm vs.（3.06 ± 1.33）mm， P < 0.001］，and a higher ratio of the upper ureter diameter（D1）to the lower ureter diameter（D2）（DDR）（2.87 ± 1.58 vs. 2.00 ± 0.99， P < 0.001）. Univariate analysis showed that NLR，hydronephrosis，stone length，stone surface area，UWT，D1，D2，and DDR were statistically significant（ P < 0.05）. After multivariate logistic regression analysis，the following items were identified as independent predictors of impacted ureteral stones：NLR（ OR = 1.205，95% CI 1.026 - 1.415， P = 0.023），hydronephrosis（ OR = 1.840，95% CI 1.236 - 2.740， P = 0.003），stone length（ OR = 1.587，95% CI 1.142 - 2.206， P = 0.006），ureteral wall thickness（UWT）（ OR = 1.643，95% CI 1.263 - 2.136， P < 0.001），and DDR（ OR = 2.907，95% CI 1.040 - 8.130， P = 0.042）.Based on these independent predictive factors，a nomogram prediction model for impacted ureteral stones was constructed. The area under the ROC curve was 0.797（95% CI 0.737 - 0.858），and the calibration curve showed good consistency. The decision curve suggested that the model had good clinical net benefit. Conclusions:NLR，hydronephrosis，stone length，UWT，and DDR are all independent predictors for impacted ureteral stones. The nomogram model constructed based on these factors has good predictive performance.

Objective To investigate the expression of miR-204 and silence information regulator 1(SIRT1)in colorectal cancer and their clinical value.Methods Cancer tissue specimens and paracancer tissue specimens of 60 patients with colorectal cancer treated in Department of Gastrointestinal Surgery of Affiliated Hospital of Jiaxing University from May 2018 to June 2020 were collected as study objects.Real time fluorogenic quantitative polymerase chain reaction was used to detect the gene expression of miR-204 and SIRT1,and the correlation between miR-204 and SIRT1 gene expression was compared by Pearson analysis.Immunohistochemical SABC method was used to detect SIRT1 protein expression,and relationship between different SIRT1 protein expression and clinicopathological features was compared.Kaplan-Meier method was used to analyze the survival difference of colorectal cancer patients with different SIRT1 protein expression.Results The mRNA expression of miR-204 gene in cancer tissues was significantly lower than that in paracancer tissues(P<0.05),and the mRNA expression of SIRT1 gene was significantly higher than that in paracancer tissues(P<0.05).Pearson correlation analysis showed that miR-204 was negatively correlated with SIRT1 mRNA expression in both paracancer tissues and cancer tissues(r=-0.647,-0.737,P<0.05).The expression of SIRT1 protein was correlated with the differentiation level,invasion level,lymph node metastasis and TNM stage of colorectal cancer(P<0.05),but not with patient age,gender,tumor size and tumor site(P>0.05).Kaplan-Meier analysis showed that the survival rate of patients with positive expression of SIRT1 in cancer tissues was significantly lower than that of patients with negative expression of SIRT1(χ2=5.001,P=0.025).Conclusion The expression of miR-204 is down-regulated and SIRT1 expression is up-regulated in colorectal cancer tissues,which may jointly promote the metastasis and invasion of colorectal cancer and affect the prognosis of patients through mutual influence.

Objective:To investigate the application value of combining Prostate Imaging Reporting and Data System (PI-RADS v2.1) score and Systemic Immune-Inflammation Index (SII) in predicting pathological upgrading in patients with localized prostate cancer after radical prostatectomy(RP).Methods:A retrospective analysis was conducted on clinical data from 76 patients with localized prostate cancer who underwent prostate biopsy and radical prostatectomy at the Second Affiliated Hospital of Zhengzhou University between September 2019 and May 2024. The median age was 68 (65, 71) years. Total prostate-specific antigen (tPSA) was 17.4 (8.4, 30.9) ng/ml, and prostate volume was 43.1 (29.9, 58.9) ml. PI-RADS scores were ≤3 in 22 cases (28.9%) and >3 in 54 cases (71.1%). According to the International Society of Urological Pathology (ISUP) grading of biopsy specimens, 31 patients (40.8%) were classified as Group <3 and 45 patients (59.2%) as Group ≥3. Postoperatively, 25 patients (32.9%) were classified as ISUP Group <3, and 51 patients (67.1%) as Group ≥3. Pathological upgrading was defined as either: ①a higher ISUP grade in postoperative specimens compared to biopsy specimens or; ②benign prostate tissue identified in biopsy specimens but confirmed as prostate cancer postoperatively. Clinical data were compared between the pathological upgrade and non-upgrade groups. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors for pathological upgrading and to construct a nomogram model. Receiver operating characteristic (ROC) curves were used to evaluate the predictive performance of individual indicators (PI-RADS, SII, %PSA, and the proportion of tumor tissue in biopsy specimens) and the combined nomogram model. Internal validation was conducted using cross-validation, and calibration and decision curves were generated to assess the nomogram′s accuracy and clinical net benefit.Results:Among the 76 patients included, 10 (13.2%) experienced pathological downgrading, 36 (47.4%) had consistent grading, and 30 (39.5%) experienced pathological upgrading. The platelet-to-lymphocyte ratio (PLR) [118.2(93.5, 139.1) vs. 95.2(79.3, 116.4), P=0.021], SII [394.8(331.0, 513.6) vs. 338.8(217.2, 407.8), P=0.002], and the number of cases with a PI-RADS score >3 [26 cases(86.7%) vs. 28 cases(60.9%), P=0.015] were significantly higher in the pathological upgrade group than in the non-upgrade group. Conversely, the percentage of positive biopsy cores [35.9%(12.6%, 51.8%) vs. 43.8%(21.0%, 92.1%), P=0.045], the proportion of tumor tissue in biopsy specimens [6.9%(1.3%, 20.1%) vs. 19.3%(9.1%, 58.4%), P<0.01], and the number of cases in ISUP biopsy Group ≥3 [12 cases (40.0%) vs. 33 cases (71.7%), P=0.006] were significantly lower in the upgrade group (all P < 0.05). Univariate and multivariate logistic regression analyses showed that PI-RADS score( OR=17.111, 95% CI 2.388-122.592, P<0.01), SII( OR=1.009, 95% CI 1.001-1.016, P=0.028), %PSA ( OR=0.003, 95% CI 0.002-0.004, P<0.01), and the proportion of tumor tissue in biopsy specimens ( OR=0.899, 95% CI 0.837-0.966, P<0.01) were independent predictors of pathological upgrading. The area under the ROC curve (AUC) for PI-RADS, SII, %PSA, and the proportion of tumor tissue in biopsy specimens were 0.607, 0.711, 0.618, and 0.778, respectively. The combined AUC for %PSA and the proportion of tumor tissue was 0.791, while the combined AUC of the four-indicator nomogram model was 0.914. The DeLong test indicated a statistically significant difference in diagnostic performance between the two models ( P<0.01). Calibration and decision curves demonstrated good accuracy and clinical net benefit for the nomogram model. Conclusions:The PI-RADS v2.1 score and SII have significant predictive value for pathological upgrading after radical prostatectomy in prostate cancer. A nomogram model combining PI-RADS, SII, %PSA, and the proportion of tumor tissue in biopsy specimens shows excellent predictive performance.

Objective Screening for sensitive biomarkers for predicting and analyzing drug-induced renal toxicity,accelerates drug early development.Methods Focuses on epithelial cells of proximal convoluted tubules in human renal cortex(human kidney-2,HK-2)cells as the research object,screening for highly sensitive biomarkers using three nephrotoxic drugs(cisplatin,gentamicin,and aristolochic acid Ⅰ).Results The sensitivity of biomarkers in intracellular fluid is higher than in extracellular fluid,compared to detecting a single biomarker in the intracellular fluid.The combined detection of β2-microglobulin(β2-MG)and neutrophil gelatinase-associated lipocalin(NGAL)improved the accuracy of renal toxicity evaluation.Conclusion Based on the HK-2 cell model,the combined detection of β2-MG and NGAL in intracellular fluid can be used to predict renal toxicity in the drug's early development stage.

Objective:To discuss the protective effect of ginsenoside Rh1(G-Rh1)on kidney injury in the diabetic mellitus(DM)mice,and to clarify its mechanism.Methods:The diabetic kidney disease(DKD)model was prepared by using the high-fat,high-sugar diet combined with intraperitoneal injection of streptozotocin(STZ).A total of 48 C57/BL6 model mice were randomly divided into model group,nuclear factor erythroid 2-related factor 2(Nrf2)inhibitor ML385 group(ML385 group)(30 mg·kg-1),G-Rh1 group(30 mg·kg-1),and G-Rh1+ML385 group(30 mg·kg-1 G-Rh1+30 mg·kg-1 ML385),and there were 12 mice in each group.Additionally,12 C57/BL6 mice were selected as control group.After treated for 8 weeks,automatic analyzer was used to detect the levels of fasting blood glucose(FBG),blood urea nitrogen(BUN),and serum creatinine(Scr)in serum of the mice in various groups,as well as 24 h urinary protein(24 h UP)levels in urine,and the kidney index was calculated;kits were used to detect the activities of superoxide dismutase(SOD)and lactate dehydrogenase(LDH),and the levels of malondialdehyde(MDA)in kidney tissue of the mice in various groups;Western blotting method was used to detect the expression levels of Nrf2 and heme oxygenase-1(HO-1)proteins in kidney tissue of the mice in various groups.Results:Compared with control group,the levels of FBG and kidney indexes in serum of the mice in model group,ML385 group,and G-Rh1+ML385 group were significantly increased(P<0.01),and the level of FBG in serum of the mice in G-Rh1 group was significantly increased(P<0.01);compared with model group,the kidney index of the mice in ML385 group was significantly increased(P<0.05),while the levels of FBG and kidney index of the mice in G-Rh1 group were significantly decreased(P<0.05 or P<0.01);compared with G-Rh1 group,the level of FBG and kidney index of the mice in G-Rh1+ML385 group were significantly increased(P<0.01).Compared with control group,the levels of BUN and Scr in serum,and 24 h UP in urine of the mice in model group,ML385 group,G-Rh1 group,and G-Rh1+ML385 group were significantly increased(P<0.01);compared with model group,the level of BUN in serum and 24 h UP in urine of the mice in ML385 group were significantly increased(P<0.05),while the levels of BUN and Scr in serum,and 24 h UP in urine of the mice in G-Rh1 group were significantly decreased(P<0.01);compared with G-Rh1 group,the levels of BUN and Scr in serum,and 24 h UP in urine of the mice in G-Rh1+ML385 group were significantly increased(P<0.01).Compared with control group,the activities of SOD in kidney tissue of the mice in model group,ML385 group,G-Rh1 group,and G-Rh1+ML385 group were significantly decreased(P<0.01),while the levels of MDA and LDH activities were significantly increased(P<0.01);compared with model group,the activity of SOD in kidney tissue of the mice in ML385 group was significantly decreased(P<0.05),and the level of MDA was significantly increased(P<0.05);the activity of SOD in kidney tissue of the mice in of G-Rh1 group was significantly increased(P<0.01),and the level of MDA and activity of LDH were significantly decreased(P<0.01);compared with G-Rh1 group,the activity of SOD in kidney tissue of the mice in G-Rh1+ML385 group was significantly decreased(P<0.01),and the level of MDA and activity of LDH were significantly increased(P<0.01).Compared with control group,the expression levels of Nrf2 and HO-1 proteins in kidney tissue of the mice in model group,ML385 group,G-Rh1 group,and G-Rh1+ML385 group were significantly decreased(P<0.05 or P<0.01);compared with model group,the expression levels of Nrf2 and HO-1 proteins in kidney tissue of the mice in ML385 group and G-Rh1+ML385 group were significantly decreased(P<0.05),while the expression levels of Nrf2 and HO-1 proteins in kidney tissue of the mice in G-Rh1 group were significantly increased(P<0.01);compared with G-Rh1 group,the expression levels of Nrf2 and HO-1 proteins in kidney tissue of the mice in G-Rh1+ML385 group were significantly decreased(P<0.01).Conclusion:Ginsenoside Rh1 reduces the oxidative stress and improves the kidney function,providing protective effects on kidney injury in the DM mice,and its mechanism may be related to the activation of the Nrf2/HO-1 signaling pathway.