Objective To establish a highly efficient and sensitive technical system for the identification and analysis of platycodin-type saponins, systematically compare the differences in platycodin-type saponins among Platycodon grandiflorum from different producing areas, and provide scientific references for the screening of high-quality Platycodon grandiflorum resources, authenticity evaluation, and construction of standardized quality control systems. Methods A total of 45 batches of P. grandiflorum medicinal materials from 3 producing areas （Anhui, Henan, and Jilin, with 15 batches per area） were selected as research objects. Qualitative identification and semi-quantitative analysis of saponin components were performed based on ultra-high performance liquid chromatography-quadrupole-time-of-flight tandem mass spectrometry （UHPLC-Q-TOF/MS） technology. Meanwhile, two multivariate statistical methods, principal component analysis （PCA） and partial least squares-discriminant analysis （PLS-DA）, were combined to analyze the differences in platycodin-type saponins of Platycodon grandiflorus from different producing areas. Results A total of 28 saponin components were identified from Platycodon grandiflorus of the three producing areas. PCA results showed that there were minor differences in platycodin-type saponins between Henan Platycodon grandiflorus and Jilin Platycodon grandiflorus, while Anhui P. grandiflorum exhibited significant differences from both. PLS-DA further screened 15 major differential compounds. Among them, the contents of 6 components including 3''-O-acetylpolygalacin D2 and platycodin H in Anhui Platycodon grandiflorus were higher than those in Henan and Jilin Platycodon grandiflorus; platycodigenic acid A had the highest content in Jilin Platycodon grandiflorus; the contents of platycodin D3, polygalacin J, and polygalacin D were relatively higher in Henan Platycodon grandiflorus. Conclusion This study clarified the characteristic differences in core components of Platycodon grandiflorus from the three major producing areas, which provided an important theoretical basis for the screening of high-quality Platycodon grandiflorus resources, elucidation of the mechanism underlying its authenticity, and construction of a standardized quality control system.

ObjectiveTo analyze the etiological characteristics and risk factors of autosomal dominant polycystic kidney disease （ADPKD） complicated with urinary tract infection （UTI）. MethodsA retrospective analysis was performed on 244 patients with ADPKD admitted to the Department of Nephrology. The patients were stratified into a study group （n=138） and a control group （n=106） according to the presence or absence of concurrent UTI. All patients in the study group underwent etiological testing and drug susceptibility testing. Clinical data of both groups were collected to identify the risk factors for ADPKD complicated with UTI. ResultsA total of 105 pathogens were detected in 138 cases in the study group， including 79 Gram-negative bacteria， 20 Gram-positive bacteria and 6 fungi. Escherichia coli showed a relatively high resistance rate to ampicillin， piperacillin and ciprofloxacin. Enterococcus faecalis had a relatively high resistance rate to tetracycline. There were statistically significant differences between the study group and the control group in terms of gender， history of urinary tract infection， C-reactive protein （CRP）， increased urine red blood cells， increased urine white blood cells， increased percentage of neutrophils， blood sodium， blood calcium， total cholesterol， serum iron and transferrin saturation （P<0.05）. Multivariate binary Logistic regression analysis revealed that female gender （OR=2.236， P=0.004）， history of urinary tract infection （OR=2.383， P=0.002）， increased urine white blood cells （OR=2.726， P=0.001）， increased percentage of neutrophils （OR=1.040， P=0.010）， elevated C-reactive protein （OR=1.011， P=0.007） and elevated blood calcium （OR=4.389， P=0.024） were risk factors of urinary tract infection in ADPKD patients （P<0.05）. ConclusionThe main pathogens of UTI in patients with ADPKD are Gram-negative bacteria. Female， previous history of urinary tract infection， urinary leukocytosis， increased percentage of neutrophils， increased CRP and increased serum calcium are risk factors of UTI.

Peptide receptor radionuclide therapy (PRRT) with radiolabeled SSTR2 agonists is a treatment option that is highly effective in controlling metastatic and progressive neuroendocrine tumors (NETs). Previous studies have shown that an SSTR2 agonist combined with albumin binding moiety Evans blue (denoted as ¹⁷⁷Lu-EB-TATE) is characterized by a higher tumor uptake and residence time in preclinical models and in patients with metastatic NETs. This study aimed to enhance the in vivo stability, pharmacokinetics, and pharmacodynamics of ¹⁷⁷Lu-EB-TATE by replacing the maleimide-thiol group with a polyethylene glycol chain, resulting in a novel EB conjugated SSTR2-targeting radiopharmaceutical, ¹⁷⁷Lu-LNC1010, for PRRT. In preclinical studies, ¹⁷⁷Lu-LNC1010 exhibited good stability and SSTR2-binding affinity in AR42J tumor cells and enhanced uptake and prolonged retention in AR42J tumor xenografts. Thereafter, we presented the first-in-human dose escalation study of ¹⁷⁷Lu-LNC1010 in patients with advanced/metastatic NETs. ¹⁷⁷Lu-LNC1010 was well-tolerated by all patients, with minor adverse effects, and exhibited significant uptake and prolonged retention in tumor lesions, with higher tumor radiation doses than those of ¹⁷⁷Lu-EB-TATE. Preliminary PRRT efficacy results showed an 83% disease control rate and a 42% overall response rate after two ¹⁷⁷Lu-LNC1010 treatment cycles. These encouraging findings warrant further investigations through multicenter, prospective, and randomized controlled trials.

Objective: To construct prediction models of female stress urinary incontinence (SUI), and evaluate the efficacy of each model, so as to provide reference for the early diagnosis of SUI. Methods: Female SUI patients treated in our hospital during Oct. 2019 and Oct. 2023 and healthy women undergoing physical examination during the same period were involved. Women 42 days after delivery were included in the postpartum group (n=611), and perimenopausal and postmenopausal women were included in the non-postpartum group (n=409). The number of random seeds was set and the participants were divided into the training and verification sets in a ratio of 7∶3. Relevant clinical data were collected, and meaningful variables were screened using single factor and Lasso regression, which were then incorporated into the K-nearest neighbor method (KNN), support vector machine (SVM)，decision tree (DT) and random forest (RF) algorithms. The sensitivity, specificity, accuracy and area under the receiver operating characteristic curve (AUC) of the models were calculated to screen out the optimal model. Results: There were 352 SUI patients (57.6%) in the postpartum group. According to single factor and Lasso regression, significant variables included age, body mass index (BMI), maximum rapid muscle stage, parity, bladder neck mobility (BND), urethral rotation angle (URA), lateral perineal incision, past incontinence, and constipation. In the verification set, the AUC of KNN，SVM，DT and RF models were 0.881，0.878，0.750 and 0.905,respectively; the AUC, accuracy, F1 index and Kappa value of RF model were the largest. In the non-postpartum group, there were 260 SUI patients, accounting for 63.6%. The significant variables were age，BMI, maximum value and recovery time of fast muscle stage, mean value of slow muscle stage, post-resting stage variability, vaginal delivery, past incontinence, and constipation. In the verification set, the AUC of KNN,SVM，DT and RF models were 0.819,0.805，0.603 and 0.830, respectively; the AUC, accuracy, Kappa value of the RF model were the largest. Conclusion: This study successfully established 4 prediction models for the incidence of SUI in women at 42 days postpartum, perimenopausal and postmenopausal women based on machine learning. Among them, the model adopting the RF algorithm had the best prediction efficiency.

Objective:To explore the effectiveness of nursing based on the Roy model in patients with Guillain-Barre syndrome (GBS) .Methods:Convenience sampling was used to select 55 patients with GBS at the First People's Hospital of Shangqiu between January 2020 and May 2024 as study subjects. Patients were divided into an intervention group ( n=28) and a control group ( n=27). Control group received conventional nursing, while intervention group received nursing based on Roy adaptation model. The recovery time, psychological state, and social support of the two groups of patients were compared. Results:Intervention group demonstrated shorter recovery times, lower anxiety and depression scores, and higher Social Support Rating Scale scores compared to control group, with all differences being statistically significant ( P<0.05) . Conclusions:The Roy model nursing in this study of GBS patients, effectively improves recovery outcomes, psychological state, and social support among GBS patients through comprehensive assessment, personalized nursing intervention, and ongoing evaluation.

Objective:To explore the effectiveness of nursing based on the Roy model in patients with Guillain-Barre syndrome (GBS) .Methods:Convenience sampling was used to select 55 patients with GBS at the First People's Hospital of Shangqiu between January 2020 and May 2024 as study subjects. Patients were divided into an intervention group ( n=28) and a control group ( n=27). Control group received conventional nursing, while intervention group received nursing based on Roy adaptation model. The recovery time, psychological state, and social support of the two groups of patients were compared. Results:Intervention group demonstrated shorter recovery times, lower anxiety and depression scores, and higher Social Support Rating Scale scores compared to control group, with all differences being statistically significant ( P<0.05) . Conclusions:The Roy model nursing in this study of GBS patients, effectively improves recovery outcomes, psychological state, and social support among GBS patients through comprehensive assessment, personalized nursing intervention, and ongoing evaluation.

Objective To explore the association between plasma fibrinogen(FBG)levels and the risk of in-hospital mortality among patients with septic shock.Methods The clinical data of 563 patients diagnosed with septic shock in the Intensive Care Unit(ICU)of Shenzhen Second People's Hospital from August 1,2018,to December 31,2020,were collected.Patient demographic information,basic vital signs,and blood routine and biochemical indices upon admission were gathered.Moreover,the Acute Physiology and Chronic Health Evaluation Ⅱ(APACHEⅡ)scores were calculated.Binary logistic regression analysis was conducted to explore the correlation between plasma fibrinogen levels and in-hospital mortality in patients with septic shock.Additionally,a generalized additive model(GAM)and smoothed curve fitting were employed to investigate the nonlinear relationship between plasma fibrinogen and in-hospital mortality.Receiver operating characteristic(ROC)curves were constructed for FBG and APACHEⅡ scores to predict in-hospital mortality in septic shock patients.The area under the curve(AUC)was computed to compare the predictive efficacies of the two.Furthermore,a segmented linear regression model was utilized for quantification.Results Binary logistic regression analysis demonstrated a significant negative correlation between plasma fibrinogen levels and in-hospital mortality among patients with septic shock(P<0.05).GAM modeling and smoothed curve fitting disclosed a nonlinear association between plasma fibrinogen levels and in-hospital mortality,with an inflection point at 5.54 g/L.The segmented linear regression model indicated that,to the left of the inflection point(FBG≤5.54 g/L),for every 1 g/L decrease in plasma fibrinogen,the risk of death increased by 24.5%(OR=0.755,P=0.003).Conversely,to the right of the inflection point(FBG>5.54 g/L),the relationship was not statistically significant(OR=1.049,P=0.685).The findings of the subgroup analyses indicated that the characteristics of the subgroups did not alter the relationship between blood fibrinogen levels and in-hospital mortality.Conclusion There is a nonlinear relationship between FBG levels and in-hospital mortality in patients with septic shock,which has predictive value for evaluating the risk of in-hospital mortality in this patient cohort.

Objective:To analyze the interference of an exogenous glucose test on urinary creatinine-related renal injury biomarkers in patients with chronic kidney disease (CKD).Methods:This cross-sectional study enrolled CKD patients who visited Peking University First Hospital between October 2023 and March 2024. The patients (age: 50±18 years) included 90 males and 70 females. Fresh morning urine samples were collected, totaling 160 samples. Each urine sample was divided into 5 aliquots,each containing 225 μl. One aliquot received 75 μl of deionized water as the control. The other aliquots received 75 μl of glucose solutions at concentrations of 120, 480, 960, and 1200 mmol/L, resulting in final glucose concentrations of 30, 120, 240, and 300 mmol/L in the urine samples, respectively. Urinary creatinine in each sample was measured using both the enzymatic method and the picric acid (Jaffe) method. The following ratios were calculated: urinary albumin-to-creatinine ratio (uACR), urinary protein-to-creatinine ratio (uPCR), urinary transferrin-to-creatinine ratio (uTRF/uCr), urinary α1-microglobulin-to-creatinine ratio (uA1M/uCr), urinary immunoglobulin G-to-creatinine ratio (uIgG/uCr), and urinary N-acetyl-β-D-glucosaminidase-to-creatinine ratio (uNAG/uCr).Results:Under high glucose concentrations, significant differences ( P<0.05) were observed between the enzymatic method and the picric acid method in measuring urinary creatinine-related renal injury biomarkers. At glucose concentrations of 30, 120, 240, and 300 mmol/L, the mean percentage biases for creatinine measured by the enzymatic method were -0.19%, -0.27%, -0.20%, and -0.21%, respectively. The mean percentage biases for creatinine measured by the picric acid method were 0.78%, 1.26%, 1.35%, and 1.38%, respectively, showing an increasing deviation between the results before and after glucose addition as the glucose concentration rose. For uACR measurement, the mean absolute biases using the enzymatic method were -0.01, 1.27, 0.95, and 1.10 mg/g at the respective glucose concentrations. Using the picric acid method, the mean absolute biases for uACR were -11.69, -14.98, -16.91, and-18.51 mg/g. The biases of the picric acid method were significantly higher than the those of the enzymatic method, and the absolute value of the mean biases increased with rising glucose concentration. For uPCR, uTRF/uCr, uA1M/uCr, uNAG/uCr, and uIgG/uCr, the deviations measured by the enzymatic method were consistently smaller than those measured by the picric acid method. Conclusions:The measurement of creatinine and related renal injury biomarkers by the enzymatic method is less affected by glucose concentration. In contrast, the measurement results obtained using the picric acid method are significantly affected by glucose concentration.

Objective To explore the association between plasma fibrinogen(FBG)levels and the risk of in-hospital mortality among patients with septic shock.Methods The clinical data of 563 patients diagnosed with septic shock in the Intensive Care Unit(ICU)of Shenzhen Second People's Hospital from August 1,2018,to December 31,2020,were collected.Patient demographic information,basic vital signs,and blood routine and biochemical indices upon admission were gathered.Moreover,the Acute Physiology and Chronic Health Evaluation Ⅱ(APACHEⅡ)scores were calculated.Binary logistic regression analysis was conducted to explore the correlation between plasma fibrinogen levels and in-hospital mortality in patients with septic shock.Additionally,a generalized additive model(GAM)and smoothed curve fitting were employed to investigate the nonlinear relationship between plasma fibrinogen and in-hospital mortality.Receiver operating characteristic(ROC)curves were constructed for FBG and APACHEⅡ scores to predict in-hospital mortality in septic shock patients.The area under the curve(AUC)was computed to compare the predictive efficacies of the two.Furthermore,a segmented linear regression model was utilized for quantification.Results Binary logistic regression analysis demonstrated a significant negative correlation between plasma fibrinogen levels and in-hospital mortality among patients with septic shock(P<0.05).GAM modeling and smoothed curve fitting disclosed a nonlinear association between plasma fibrinogen levels and in-hospital mortality,with an inflection point at 5.54 g/L.The segmented linear regression model indicated that,to the left of the inflection point(FBG≤5.54 g/L),for every 1 g/L decrease in plasma fibrinogen,the risk of death increased by 24.5%(OR=0.755,P=0.003).Conversely,to the right of the inflection point(FBG>5.54 g/L),the relationship was not statistically significant(OR=1.049,P=0.685).The findings of the subgroup analyses indicated that the characteristics of the subgroups did not alter the relationship between blood fibrinogen levels and in-hospital mortality.Conclusion There is a nonlinear relationship between FBG levels and in-hospital mortality in patients with septic shock,which has predictive value for evaluating the risk of in-hospital mortality in this patient cohort.

Objective:To analyze the interference of an exogenous glucose test on urinary creatinine-related renal injury biomarkers in patients with chronic kidney disease (CKD).Methods:This cross-sectional study enrolled CKD patients who visited Peking University First Hospital between October 2023 and March 2024. The patients (age: 50±18 years) included 90 males and 70 females. Fresh morning urine samples were collected, totaling 160 samples. Each urine sample was divided into 5 aliquots,each containing 225 μl. One aliquot received 75 μl of deionized water as the control. The other aliquots received 75 μl of glucose solutions at concentrations of 120, 480, 960, and 1200 mmol/L, resulting in final glucose concentrations of 30, 120, 240, and 300 mmol/L in the urine samples, respectively. Urinary creatinine in each sample was measured using both the enzymatic method and the picric acid (Jaffe) method. The following ratios were calculated: urinary albumin-to-creatinine ratio (uACR), urinary protein-to-creatinine ratio (uPCR), urinary transferrin-to-creatinine ratio (uTRF/uCr), urinary α1-microglobulin-to-creatinine ratio (uA1M/uCr), urinary immunoglobulin G-to-creatinine ratio (uIgG/uCr), and urinary N-acetyl-β-D-glucosaminidase-to-creatinine ratio (uNAG/uCr).Results:Under high glucose concentrations, significant differences ( P<0.05) were observed between the enzymatic method and the picric acid method in measuring urinary creatinine-related renal injury biomarkers. At glucose concentrations of 30, 120, 240, and 300 mmol/L, the mean percentage biases for creatinine measured by the enzymatic method were -0.19%, -0.27%, -0.20%, and -0.21%, respectively. The mean percentage biases for creatinine measured by the picric acid method were 0.78%, 1.26%, 1.35%, and 1.38%, respectively, showing an increasing deviation between the results before and after glucose addition as the glucose concentration rose. For uACR measurement, the mean absolute biases using the enzymatic method were -0.01, 1.27, 0.95, and 1.10 mg/g at the respective glucose concentrations. Using the picric acid method, the mean absolute biases for uACR were -11.69, -14.98, -16.91, and-18.51 mg/g. The biases of the picric acid method were significantly higher than the those of the enzymatic method, and the absolute value of the mean biases increased with rising glucose concentration. For uPCR, uTRF/uCr, uA1M/uCr, uNAG/uCr, and uIgG/uCr, the deviations measured by the enzymatic method were consistently smaller than those measured by the picric acid method. Conclusions:The measurement of creatinine and related renal injury biomarkers by the enzymatic method is less affected by glucose concentration. In contrast, the measurement results obtained using the picric acid method are significantly affected by glucose concentration.