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.

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.

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.

Cerebral organoids are three-dimensional nerve cultures induced by embryonic stem cells(ESCs)or induced pluripotent stem cells(iPSCs)that mimic the structure and function of human brain.With the continuous optimization of cerebral organoid culture technology and the combination with emerging technologies such as organ transplantation,gene editing and organoids-on-chip,complex brain tissue structures such as functional vascular structures and neural circuits have been produced,which provides new methods and ideas for studying human brain development and diseases.This article reviews the latest advances in brain organoid technology,describes its application in neurological diseases and advances in stroke modeling and transplantation treatment.

Post-stroke cognitive impairment(PSCI)is mainly manifested as learning and memory disorders.Highly enriched RNA m6A methylation modification in mammalian brain is involved in glial cell-mediated neuroinflammation.Given that neuroinflammation is the main mechanism for neural damage and spatial and memory impairment of PSCI,it is speculated that RNA m6A methylation modification can regulate the inflammatory response of glial cells after stroke to improve PSCI.This review summarizes and analyzes the role of RNA m6A methylation modification in the development of PSCI and analyzes its detailed mechanism of regulating glial cell-mediated inflammation,which will provide reference for researchers in this field.

BACKGROUND:Long non-coding RNAs(lncRNAs),as important regulators of the inflammatory response,are involved in the immune-inflammation-brain crosstalk mechanism after ischemic stroke and have the potential to become a therapeutic agent for neurological dysfunction after ischemic stroke. OBJECTIVE:To analyze and summarize the molecular mechanism of lncRNA acting on glial cells involved in the neuroimmuno-inflammatory cascade response after ischemic stroke and the associated signaling pathways,pointing out that lncRNAs have the potential to regulate inflammation after ischemic stroke. METHODS:PubMed was searched using the search terms of"ischemic stroke,long non-coding RNA,neuroinflammation,immune function,signal pathway,microglia,astrocytes,oligodendrocyte,mechanism,"and 63 relevant documents were finally included for review. RESULTS AND CONCLUSION:In the early stage of ischemic stroke,the death of nerve cells due to ischemia and hypoxia activates the innate immune response of the brain,promoting the secretion of inflammatory factors and inducing blood-brain barrier damage and a series of inflammatory cascades responses.As an important pathogenesis factor in ischemic stroke,the neuroimmuno-inflammatory cascade has been proved to seriously affect the prognosis of patients with ischemic stroke,and it needs to be suppressed promptly in the early stage.Neuroinflammation after ischemic stroke usually induces abnormal expression of a large number of lncRNAs that mediate a series of neuro-immune-inflammatory crosstalk mechanisms through regulating the polarization of microglia,astrocytes and oligodendrocytes to exert post-stroke neuroprotective effects.LncRNAs,as important regulatory factors of the inflammatory response,inhibit the neuroimmuno-inflammatory cascade response after ischemic stroke through regulating nuclear factor-κB,lncRNA-miRNA-mRNA axis,Rho-ROCK,MAPK,AKT,ERK and other signaling pathways to effectively improve neurological impairment after ischemic stroke.Most of experimental studies on the interaction between lncRNAs and ischemic stroke are based on a middle cerebral artery occlusion model or a cerebral ischemia-reperfusion injury model,but no clinical trials have been conducted.Therefore,it remains to be further explored about whether lncRNAs can be safely applied in clinical practice.At present,there are many therapeutic drugs for the treatment of ischemic stroke,but there are relatively few studies on the application of lncRNAs,exosomes and other transplantation technologies for the treatment of ischemic stroke using tissue engineering technology,which need to be further explored.lncRNA has become an important target for the treatment of ischemic stroke with its relative stability and high specificity.In future studies,more types of inflammatory lncRNAs that function under ischemic-hypoxia conditions should continue to be explored,in order to provide new research directions for the treatment of neuroinflammation after ischemic stroke.

Objective To investigate the influence of type 2 diabetes mellitus(T2DM)on cognitive function and the effective connectivity with in the default mode network(DMN)in the brain.Methods A total of 93 hospitalized patients diagnosed with T2DM were enrolled in this study as T2DM group from The First Affiliated Hospital of Guangzhou University of Chinese Medicine during September 2021 to December 2022.Simultaneously,108 healthy individuals were recruited from the community as normal control(NC)group.The cognitive functions were evaluated in the two groups.A random dynamic causal modeling approach was employed to analyze the effective connectivity within DMN in both groups.Additionally,Pearson correlation analysis was performed to examine the association between differential connectivity,clinical indicators,and cognitive scores in both groups.Results In comparison to the NC group,T2DM individuals exhibited statistically significant reductions in scores in the auditory verbal learning test(AVLT)for immediate recall and the digit symbol substitution test(DSST)(P＜0.05).Additionally,they displayed a notable decrease in effective connectivity from the left lateral parietal cortex(LLPC)to the posterior cingulate cortex(PCC),as well as from the LLPC to the right lateral parietal cortex(RLPC)within the DMN(P＜0.05).Pearson correlation analysis unveiled a negative association between HbA1c levels and the strength of effective connectivity from LLPC to PCC.Conversely,a positive correlation was observed between AVLT(immediate)scores and the strength of effective connectivity from LLPC to PCC and LLPC to RLPC.Additionally,DSST scores displayed a positive correlation with the strength of effective connectivity from LLPC to PCC(P＜0.05).Conclusion Patients with T2DM display compromised effective connectivity from LLPC to PCC and LLPC to RLPC within the DMN network,and this alteration may associated with cognitive impairment.