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.

BACKGROUND: Rheumatoid arthritis (RA) is a systemic autoimmune disease characterized by chronic inflammation and joint destruction. Iguratimod (IGU) is a novel conventional synthetic disease-modifying antirheumatic drugs (csDMARD) with good efficacy and safety for the treatment of active RA in China and Japan. However, the long-term effects of IGU on the progression of bone destruction or radiographic progression in patients with active RA remain unknown. We aimed to investigate the efficacy and safety of iguratimod (IGU), a combination of methotrexate (MTX) and IGU, and IGU in patients with active rheumatoid arthritis (RA) who were naïve to MTX. METHODS: This multicenter, double-blind, randomized, non-inferiority clinical trial was conducted at 28 centers for over 52 weeks in China. In total, 911 patients were randomized (1:1:1) to receive MTX monotherapy (10-15 mg weekly, n = 293), IGU monotherapy (25 mg twice daily, n = 297), or IGU + MTX (10-15 mg weekly for MTX and 25 mg twice daily for IGU, n = 305) for 52 weeks. The patients' clinical characteristics, Simplified Disease Activity Index (SDAI), Clinical Disease Activity Index (CDAI), disease activity score in 28 joints-C-reactive protein (DAS28-CRP) level, and disease activity score in 28 joints-erythrocyte sedimentation rate (DAS28-ESR) were assessed at baseline. The primary endpoints were the proportion of patients with ≥20% improvement according to the American College of Rheumatology (ACR20) response and changes in the van der Heijde-modified total Sharp score (vdH-mTSS) at week 52. RESULTS: The proportions of patients achieving an ACR20 response at week 52 were 77.44%, 77.05 %, and 65.87% for IGU monotherapy, IGU + MTX, and MTX monotherapy, respectively. The non-inferiority of IGU monotherapy to MTX monotherapy was established with the ACR20 (11.57%; 95% confidence interval [CI], 4.35-18.79%; P <0.001) and vdH-mTSS (-0.37; 95% CI, -1.22-0.47; P = 0.022). IGU monotherapy was also superior to MTX monotherapy in terms of ACR20 ( P = 0.002) but not the vdH-mTSS. The superiority of IGU + MTX over MTX monotherapy was confirmed in terms of the ACR20 (11.18%; 95% CI, 3.99-18.37%; P = 0.003), but not in the vdH-mTSS (-0.68; 95% CI, -1.46-0.11; P = 0.091). However, the difference in the incidence rates of adverse events was not statistically significant. CONCLUSIONS: IGU monotherapy/IGU + MTX showed a more favorable clinical response than did MTX monotherapy. IGU may have some clinical benefits over MTX in terms of radiographic progression, implying that IGU may be considered as an initial therapeutic option for patients with active RA. TRIAL REGISTRATION https://classic.clinicaltrials.gov/ , NCT01548001.
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Antirheumatic Agents/therapeutic use* ; Arthritis, Rheumatoid/drug therapy* ; Chromones/adverse effects* ; Double-Blind Method ; Drug Therapy, Combination ; Methotrexate/adverse effects* ; Treatment Outcome ; Sulfonamides

Objective: To explore the feasibility of synthetic magnetic resonance imaging (syMRI) combined with clinicopathological characteristics for the pre-treatment prediction of chemoradiotherapy (CRT) response in advanced nasopharyngeal carcinoma (ANPC). Materials and Methods: Patients with ANPC treated with CRT between September 2020 and June 2022 were retrospectively enrolled and categorized into response group (RG, n = 95) and non RGs (NRG, n = 32) based on the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1. The quantitative parameters from pre-treatment syMRI (longitudinal [T1] and transverse [T2] relaxation times and proton density [PD]), diffusion-weighted imaging (apparent diffusion coefficient [ADC]), and clinicopathological characteristics were compared between RG and NRG. Logistic regression analysis was applied to identify parameters independently associated with CRT response and to construct a multivariable model. The areas under the receiveroperating characteristic curve (AUC) for various diagnostic approaches were compared using the DeLong test. Results: The T1, T2, and PD values in the NRG were significantly lower than those in the RG (all P < 0.05), whereas no significant difference was observed in the ADC values between these two groups. Clinicopathological characteristics (Epstein–Barr virus [EBV]-DNA level, lymph node extranodal extension, clinical stage, and Ki-67 expression) exhibited significant differences between the two groups. Logistic regression analysis showed that T1, PD, EBV-DNA level, clinical stage, and Ki-67 expression had significant independent relationships with CRT response (all P < 0.05). The multivariable model incorporating these five variables yielded AUC, sensitivity, and specificity values of 0.974, 93.8% (30/32), and 91.6% (87/95), respectively. Conclusion SyMRI may be used for the pretreatment prediction of CRT response in ANPC. The multivariable model incorporating syMRI quantitative parameters and clinicopathological characteristics, which were independently associated with CRT response, may be a new tool for the pretreatment prediction of CRT response.

Objective: To explore the feasibility of synthetic magnetic resonance imaging (syMRI) combined with clinicopathological characteristics for the pre-treatment prediction of chemoradiotherapy (CRT) response in advanced nasopharyngeal carcinoma (ANPC). Materials and Methods: Patients with ANPC treated with CRT between September 2020 and June 2022 were retrospectively enrolled and categorized into response group (RG, n = 95) and non RGs (NRG, n = 32) based on the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1. The quantitative parameters from pre-treatment syMRI (longitudinal [T1] and transverse [T2] relaxation times and proton density [PD]), diffusion-weighted imaging (apparent diffusion coefficient [ADC]), and clinicopathological characteristics were compared between RG and NRG. Logistic regression analysis was applied to identify parameters independently associated with CRT response and to construct a multivariable model. The areas under the receiveroperating characteristic curve (AUC) for various diagnostic approaches were compared using the DeLong test. Results: The T1, T2, and PD values in the NRG were significantly lower than those in the RG (all P < 0.05), whereas no significant difference was observed in the ADC values between these two groups. Clinicopathological characteristics (Epstein–Barr virus [EBV]-DNA level, lymph node extranodal extension, clinical stage, and Ki-67 expression) exhibited significant differences between the two groups. Logistic regression analysis showed that T1, PD, EBV-DNA level, clinical stage, and Ki-67 expression had significant independent relationships with CRT response (all P < 0.05). The multivariable model incorporating these five variables yielded AUC, sensitivity, and specificity values of 0.974, 93.8% (30/32), and 91.6% (87/95), respectively. Conclusion SyMRI may be used for the pretreatment prediction of CRT response in ANPC. The multivariable model incorporating syMRI quantitative parameters and clinicopathological characteristics, which were independently associated with CRT response, may be a new tool for the pretreatment prediction of CRT response.

Objective: To explore the feasibility of synthetic magnetic resonance imaging (syMRI) combined with clinicopathological characteristics for the pre-treatment prediction of chemoradiotherapy (CRT) response in advanced nasopharyngeal carcinoma (ANPC). Materials and Methods: Patients with ANPC treated with CRT between September 2020 and June 2022 were retrospectively enrolled and categorized into response group (RG, n = 95) and non RGs (NRG, n = 32) based on the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1. The quantitative parameters from pre-treatment syMRI (longitudinal [T1] and transverse [T2] relaxation times and proton density [PD]), diffusion-weighted imaging (apparent diffusion coefficient [ADC]), and clinicopathological characteristics were compared between RG and NRG. Logistic regression analysis was applied to identify parameters independently associated with CRT response and to construct a multivariable model. The areas under the receiveroperating characteristic curve (AUC) for various diagnostic approaches were compared using the DeLong test. Results: The T1, T2, and PD values in the NRG were significantly lower than those in the RG (all P < 0.05), whereas no significant difference was observed in the ADC values between these two groups. Clinicopathological characteristics (Epstein–Barr virus [EBV]-DNA level, lymph node extranodal extension, clinical stage, and Ki-67 expression) exhibited significant differences between the two groups. Logistic regression analysis showed that T1, PD, EBV-DNA level, clinical stage, and Ki-67 expression had significant independent relationships with CRT response (all P < 0.05). The multivariable model incorporating these five variables yielded AUC, sensitivity, and specificity values of 0.974, 93.8% (30/32), and 91.6% (87/95), respectively. Conclusion SyMRI may be used for the pretreatment prediction of CRT response in ANPC. The multivariable model incorporating syMRI quantitative parameters and clinicopathological characteristics, which were independently associated with CRT response, may be a new tool for the pretreatment prediction of CRT response.

Objective: To explore the feasibility of synthetic magnetic resonance imaging (syMRI) combined with clinicopathological characteristics for the pre-treatment prediction of chemoradiotherapy (CRT) response in advanced nasopharyngeal carcinoma (ANPC). Materials and Methods: Patients with ANPC treated with CRT between September 2020 and June 2022 were retrospectively enrolled and categorized into response group (RG, n = 95) and non RGs (NRG, n = 32) based on the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1. The quantitative parameters from pre-treatment syMRI (longitudinal [T1] and transverse [T2] relaxation times and proton density [PD]), diffusion-weighted imaging (apparent diffusion coefficient [ADC]), and clinicopathological characteristics were compared between RG and NRG. Logistic regression analysis was applied to identify parameters independently associated with CRT response and to construct a multivariable model. The areas under the receiveroperating characteristic curve (AUC) for various diagnostic approaches were compared using the DeLong test. Results: The T1, T2, and PD values in the NRG were significantly lower than those in the RG (all P < 0.05), whereas no significant difference was observed in the ADC values between these two groups. Clinicopathological characteristics (Epstein–Barr virus [EBV]-DNA level, lymph node extranodal extension, clinical stage, and Ki-67 expression) exhibited significant differences between the two groups. Logistic regression analysis showed that T1, PD, EBV-DNA level, clinical stage, and Ki-67 expression had significant independent relationships with CRT response (all P < 0.05). The multivariable model incorporating these five variables yielded AUC, sensitivity, and specificity values of 0.974, 93.8% (30/32), and 91.6% (87/95), respectively. Conclusion SyMRI may be used for the pretreatment prediction of CRT response in ANPC. The multivariable model incorporating syMRI quantitative parameters and clinicopathological characteristics, which were independently associated with CRT response, may be a new tool for the pretreatment prediction of CRT response.

Objective:To construct a risk prediction model for early post-injury respiratory failure in patients with traumatic cervical spinal cord injury (TCSCI) and validate its efficacy.Methods:A retrospective cohort study was conducted to analyze the clinical data of 393 TCSCI patients admitted to Zhengzhou Central Hospital Affiliated to Zhengzhou University from January 2020 to October 2024, including 294 males and 99 females, aged 18-82 years [59(45, 72)years]. Among them, 76 patients had respiratory failure (19.3%). The patients were randomly divided into the training set ( n=275) and validation set ( n=118) at a ratio of 7∶3. According to the presence of respiratory failure within one week after admission, 275 patients in the training set were divided into respiratory failure group ( n=53) and non-respiratory failure group ( n=222). The demographic data, injury characteristics, laboratory test results, and imaging findings of the patients were collected. Risk factors were determined through univariate analysis and multivariate Logistic regression analysis and a nomogram prediction model was constructed. The area under the receiver operating characteristic (ROC) curve (AUC) and Hosmer-Lemeshow test were used to evaluate the discrimination and calibration of the model. Decision curve analysis (DCA) was plotted to evaluate the clinical effectiveness of the prediction model. Results:The results of the univariate analysis showed that there were significant differences in history of respiratory diseases, causes of injury, Glasgow coma scale (GCS), American Spinal Injury Association (ASIA) classification, ASIA-motor score (AMS), injury severity score (ISS), clinical pulmonary infection score (CPIS), hypoproteinemia and cervical vertebra fracture and dislocation between the respiratory failure group and non-respiratory failure group in the training set ( P<0.05). The results of multivariate Logistic regression analysis indicated that GCS, ASIA classification, CPIS, and hypoproteinemia were independent risk factors for early post-injury respiratory failure in TCSCI patients ( P<0.05). Based on the above four variables, a Logistic regression equation was constructed: Logit( P)=2.361-0.675×ASIA classification+0.419×CPIS-0.358×GCS+0.854×hypoproteinemia. In the prediction model established based on this equation, the AUC was 0.96 (95% CI 0.94, 0.99) in the training set and 0.89 (95% CI 0.82, 0.96) in the validation set. In the calibration curves of the training set and validation set, the prediction curve and reference curve were approximately overlapping, with the average absolute errors of 0.04 and 0.03. DCA results demonstrated that both the training and validation sets exhibited positive net benefits when threshold probabilities fell within ranges of 0%-78% and 0%-87%, respectively. Conclusion:The risk prediction model for early post-injury respiratory failure in TCSCI patients based on GCS, ASIA classification, CPIS and hypoproteinemia has good predictive efficacy and clinical practicability.

Objective: To explore the feasibility of synthetic magnetic resonance imaging (syMRI) combined with clinicopathological characteristics for the pre-treatment prediction of chemoradiotherapy (CRT) response in advanced nasopharyngeal carcinoma (ANPC). Materials and Methods: Patients with ANPC treated with CRT between September 2020 and June 2022 were retrospectively enrolled and categorized into response group (RG, n = 95) and non RGs (NRG, n = 32) based on the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1. The quantitative parameters from pre-treatment syMRI (longitudinal [T1] and transverse [T2] relaxation times and proton density [PD]), diffusion-weighted imaging (apparent diffusion coefficient [ADC]), and clinicopathological characteristics were compared between RG and NRG. Logistic regression analysis was applied to identify parameters independently associated with CRT response and to construct a multivariable model. The areas under the receiveroperating characteristic curve (AUC) for various diagnostic approaches were compared using the DeLong test. Results: The T1, T2, and PD values in the NRG were significantly lower than those in the RG (all P < 0.05), whereas no significant difference was observed in the ADC values between these two groups. Clinicopathological characteristics (Epstein–Barr virus [EBV]-DNA level, lymph node extranodal extension, clinical stage, and Ki-67 expression) exhibited significant differences between the two groups. Logistic regression analysis showed that T1, PD, EBV-DNA level, clinical stage, and Ki-67 expression had significant independent relationships with CRT response (all P < 0.05). The multivariable model incorporating these five variables yielded AUC, sensitivity, and specificity values of 0.974, 93.8% (30/32), and 91.6% (87/95), respectively. Conclusion SyMRI may be used for the pretreatment prediction of CRT response in ANPC. The multivariable model incorporating syMRI quantitative parameters and clinicopathological characteristics, which were independently associated with CRT response, may be a new tool for the pretreatment prediction of CRT response.