Objective: To prepare the erythrocyte-liposome drug delivery system to enhance the therapeutic effect of drugs on tumors and inhibit tumor metastasis. Methods: This study prepared and characterized paclitaxel (PTX)-plerixafor (AMD3100) liposomes (Lips), developed the erythrocyte-liposome drug delivery system, and evaluated its targeting efficiency and therapeutic efficacy through a series of in vitro cellular and in vivo animal experiments. Results: The particle size of PTX-AMD-Lips was (186.4±0.83) nm. Drug encapsulation efficiency of PTX-AMD-Lips was (75.50±5.27)% for PTX and (88.31±2.45)% for AMD. The Binding efficiency between RBC and liposomes in the drug delivery system was (69.93±2.55)%. Vitro cellular experiments revealed that PTX-AMD-Lips significantly inhibited tumor cell migration. In vivo animal experiments, the erythrocyte-liposome drug delivery system significantly increased drug accumulation in the lungs. At the experimental endpoint, the quantitative fluorescence signal of tumor size measured (4.04±0.44)×10 for the PTX-Lips group, and (5.14±3.40)×10 for the RBC-PTX-AMD-Lips group. Conclusion: The erythrocyte-liposome drug delivery system could enhance the lung-specific targeting capability of liposomes, kill tumor cells and suppress further metastasis effectively.

Purpose: Gold-standard urodynamic examination is widely used in the diagnosis and treatment of lower urinary tract dysfunction. The purpose of urodynamic quality control is to standardize urodynamic examination and ensure its clinical reference value. In our study, we attempted to use a deep learning (DL) algorithm model, mainly for the recognition of typical urodynamic signal, to help physicians complete high-quality urodynamic examinations. Methods: Urodynamic image data from 2 cohorts of adult patients with neurogenic bladder were used: (1) 300 patients with neurogenic bladder in our center from 2012 to 2018 (1,960 images used to train and validate the DL model); and (2) 100 patients with neurogenic bladder from 2020 to 2021 (695 images used to test the performance of the DL model). This resulted in a total of 2,655 images to train, validate and test the DL algorithm to predict the urdynamic signals. Results: Yolov5l had the best detection performance and the highest comprehensive index score (F1, 0.81; mean average precision, 0.83). Our study is a retrospective single-center study, and the generalization ability of the model has not been verified. Conclusions DL algorithms can help operators identify typical urodynamic signals in real time, improve the interpretation and quality of urodynamic examination, and benefit patients.

Objective: To analyze the distribution characteristics of immunoglobulin A (IgA) concentration in Nanning Zhuang blood donors by measuring the concentration of plasma IgA. Methods: Enzyme-linked immunosorbent assay (ELISA) was performed to measure the absorbance of 2 000 plasma samples from Zhuang blood donors. The IgA concentration in samples was calculated using the ELISA Calc regression/fitting technology program. Results: The standard curve demonstrated that ELISA detection of plasma IgA concentration exhibited good precision. The frequency of IgA deficiency was 0/2 000. No statistically significant difference in the distribution of IgA concentration was observed between males and females (P>0.05). The distribution of IgA concentration varied significantly across age groups: younger individuals (18-39 years old) had lower plasma IgA levels (mg/dL) compared to older individuals (40-56 years old): 5-89.99 mg/dL group, 8.80% (176/2 000) vs 17.20% (344/2 000); 90-450 mg/dL group,20.65% (413/2 000) vs 51.20% (1 024/2 000); >450 mg/dL group, 0.45%, (9/2 000) vs 1.70% (34/2 000), P<0.05. No significant difference in IgA concentration was found among different ABO blood types in Zhuang blood donors (P>0.05). Spearman correlation analysis revealed a positive correlation between age and IgA concentration (R =0.114, P<0.05). Conclusion: No individuals with IgA deficiency were screened out among the Zhuang blood donors in Nanning area, and plasma IgA levels progressively increase with age.

Purpose: Gold-standard urodynamic examination is widely used in the diagnosis and treatment of lower urinary tract dysfunction. The purpose of urodynamic quality control is to standardize urodynamic examination and ensure its clinical reference value. In our study, we attempted to use a deep learning (DL) algorithm model, mainly for the recognition of typical urodynamic signal, to help physicians complete high-quality urodynamic examinations. Methods: Urodynamic image data from 2 cohorts of adult patients with neurogenic bladder were used: (1) 300 patients with neurogenic bladder in our center from 2012 to 2018 (1,960 images used to train and validate the DL model); and (2) 100 patients with neurogenic bladder from 2020 to 2021 (695 images used to test the performance of the DL model). This resulted in a total of 2,655 images to train, validate and test the DL algorithm to predict the urdynamic signals. Results: Yolov5l had the best detection performance and the highest comprehensive index score (F1, 0.81; mean average precision, 0.83). Our study is a retrospective single-center study, and the generalization ability of the model has not been verified. Conclusions DL algorithms can help operators identify typical urodynamic signals in real time, improve the interpretation and quality of urodynamic examination, and benefit patients.

Purpose: Gold-standard urodynamic examination is widely used in the diagnosis and treatment of lower urinary tract dysfunction. The purpose of urodynamic quality control is to standardize urodynamic examination and ensure its clinical reference value. In our study, we attempted to use a deep learning (DL) algorithm model, mainly for the recognition of typical urodynamic signal, to help physicians complete high-quality urodynamic examinations. Methods: Urodynamic image data from 2 cohorts of adult patients with neurogenic bladder were used: (1) 300 patients with neurogenic bladder in our center from 2012 to 2018 (1,960 images used to train and validate the DL model); and (2) 100 patients with neurogenic bladder from 2020 to 2021 (695 images used to test the performance of the DL model). This resulted in a total of 2,655 images to train, validate and test the DL algorithm to predict the urdynamic signals. Results: Yolov5l had the best detection performance and the highest comprehensive index score (F1, 0.81; mean average precision, 0.83). Our study is a retrospective single-center study, and the generalization ability of the model has not been verified. Conclusions DL algorithms can help operators identify typical urodynamic signals in real time, improve the interpretation and quality of urodynamic examination, and benefit patients.

Objective: To investigate the efficacy of implantable neuromuscular electrical stimulation system on stress urinary incontinence (SUI) model in female rats. Methods: A total of 21 female infertile SD rats were randomly divided into the control，sham stimulation，and stimulation groups，with 7 rats in each group.All rats received vaginal dilation (VD) to simulate postpartum SUI.One week after VD，the control group was given normal feeding，stimulators were implanted in the pelvic floor muscles of the sham stimulation and stimulation groups.The sham stimulation group received normal feeding for 2 weeks，and the stimulation group received pelvic floor electrical stimulation (PFES) for 2 consecutive weeks.The leak point pressure (LPP) of each rat was measured with cystometry before VD (baseline value)，1 week after VD，and 2 weeks after PFES. Results: In the control group and sham stimulation group，LPP increased after 2 weeks of treatment compared with that after 1 week of VD，but it still did not return to the baseline level (P<0.001).In the stimulation group，after 2 consecutive weeks of PFES，LPP increased significantly compared with that 1 week after VD，and returned to the baseline value (P>0.05).There was no significant difference in the LPP baseline values and levels after 1 week of VD among the 3 groups (P>0.05).The LPP in the stimulation group after 2 weeks of PFES was significantly higher than that in the sham stimulation group and stimulation group (P<0.001). Conclusion: The implantable neuromuscular electrical stimulation system is effective in short-term intervention of SUI in female rats，the further studies are needed to confirm the long-term efficacy and safety of the system，the optimal stimulation sites，optimal stimulation parameters，and potential mechanisms of action.

Objective: To analyze the chemical constituents of Shanxiangyuanye (Turpiniae Folium) through liquid chromatography-tandem mass spectrometry (LC-MS/MS) method, and to evaluate their anti-oxidant, hypoglycemic, and anti-glycation activities related to diabetic complications. Methods: The supernatant of Shanxiangyuanye (Turpiniae Folium) (TFS), obtained following water extraction and alcohol precipitation, was analyzed by LC-MS/MS. Antioxidant activity of TFS in vitro was evaluated using three experimental approaches: the 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging assay, the 2,2’-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS+) radical cation decolorization assay, and the hydroxyl (·OH) radical scavenging assay. To comprehensively evaluate hypoglycemic potential, α-glucosidase inhibition was measured to analyze in vitro hypoglycemic activity. Subsequently, in vitro models were developed to examine anti-glycation activity through the bovine serum albumin (BSA)-fructose (Fru), BSA-methylglyoxal (MGO), BSA-glyoxal (GO), and D-arginine (Arg)-MGO systems, with particular attention to the inhibitory effects of TFS. Furthermore, the concentrations of fructosamine, protein carbonyls, sulfhydryl groups, and β-amyloid in the glycation solution were quantified using the BSA-Fru model following 7-d of incubation at 37 °C. Results: Using LC-MS/MS analysis in both positive and negative ion modes, we identified 750 chemical components in TFS, primarily including organic acids, amino acids, and their derivatives. In vitro activity studies demonstrated that TFS exhibited remarkable free radical scavenging capacity, with half-maximal inhibitory concentrations (IC50) of 0.47, 1.56, and 0.36 mg/mL against DPPH, ABTS+, and ·OH radicals, respectively. Regarding hypoglycemic activity, TFS dose-dependently inhibited α-glucosidase activity (IC50 = 0.21 mg/mL), displaying comparable efficacy to the clinical drug acarbose (IC50 = 0.23 mg/mL). Notably, TFS intervened in the glycation process: IC50 values were 0.22, 1.91 – 4.96, and 4.09 mg/mL in the BSA-Fru, BSA-MGO/GO, and Arg-MGO models, respectively, with the most prominent inhibitory effects observed in the BSA-Fru model. Furthermore, although TFS may not effectively preserve thiol groups in BSA or reduce thiol oxidation during glycation, it significantly reduces fructosamine levels (in a dose-dependent manner), decreases β-amyloid formation, and inhibits protein carbonylation (P < 0.000 1). Conclusion The findings demonstrate that TFS exhibits a complex chemical composition with potent antioxidant, hypoglycemic, and anti-glycation activities. These results provide compelling scientific evidence supporting TFS’s potential as a natural adjuvant for diabetes prevention and complication management, while laying a solid foundation for its applications in functional food development and adjunctive antidiabetic therapeutics.