Objective​ To evaluate the clinical characteristics and influencing factors of fatigue in patients with rheumatoid arthritis （RA）， with the aim of providing guidance for clinical treatment. Methods​ Based on the multicenter real-world cohort of the China Registry of Traditional Chinese Medicine for Rheumatism （CERTAIN） platform， patients with RA enrolled from 2019 to 2025 were included. Demographic data， disease assessment indicators， laboratory indices， and traditional Chinese medicine （TCM） syndrome patterns were collected to analyze the TCM syndromes and clinical characteristics of RA patients with fatigue. Spearman correlation analysis and logistic regression analysis were used to identify factors associated with fatigue in RA. Results​ A total of 3 021 patients with RA were included， among whom 2 007 （66.43%） had fatigue. Compared with the non-fatigue group， the fatigue group was older and had a longer disease duration， with significantly higher scores for the 28-joint Disease Activity Score （DAS28）， swollen joint count （SJC）， tender joint count （TJC）， Health Assessment Questionnaire （HAQ）， pain visual analog scale （VAS）， and patient global assessment （PGA） （P<0.01）. Among TCM syndromes， fatigue was more common in patients with dampness-heat obstruction， cold-dampness obstruction， and liver-kidney deficiency syndromes （P<0.05）. Multivariate analysis revealed that morning stiffness duration exhibited a stepwise association with fatigue， while poor appetite， insomnia with frequent dreaming， restlessness， high HAQ scores， and high pain VAS scores were identified as risk factors. ConclusionFatigue is a prominent symptom in patients with RA and is more common among those with dampness-heat obstruction， cold-dampness obstruction， and liver-kidney deficiency syndromes. It is closely associated with disease activity， pain， functional limitation， sleep， and emotional status.

ObjectiveTo evaluate the effects of Qingre Huoxue prescription combined with methotrexate （MTX） and folic acid （FA） on homocysteine （Hcy） levels and disease activity in patients with rheumatoid arthritis （RA） complicated by hyperhomocysteinemia （HHcy）. MethodsOn the basis of a multicenter real-world cohort from the China Registry of Traditional Chinese Medicine for Rheumatism （CERTAIN） platform，408 patients with RA complicated by HHcy were selected and included in this study. Treatment with Qingre Huoxue prescription was used as the exposure factor. According to whether Qingre Huoxue prescription was combined with MTX and FA，patients were assigned into an exposure group of 281 cases and a control group of 127 cases. Follow-ups were conducted every three months，with the primary outcome indicator being the achievement rate of target Hcy level. A generalized estimating equation model was adopted to analyze the dynamic changes in Hcy level under different medication regimens. Kaplan-Meier analysis was performed to evaluate the cumulative achievement rate of target Hcy level in the two groups，and Cox regression analysis was conducted to explore the predictive factors affecting the achievement rate of target Hcy level. Changes in erythrocyte sedimentation rate （ESR），C-reactive protein （CRP），28-joint disease activity score （DAS 28），and Health Assessment Questionnaire-Disability Index （HAQ-DI） scores before and after the first combined treatment with Qingre Huoxue prescription were compared between the two groups. ResultsThe Hcy level in the exposure group showed a gradual decreasing trend over time，while the decrease in Hcy level was not significant in the control group. At the 12-month follow-up，the achievement rate of target Hcy level in the exposure group （124/281，44.13%） was higher than that in the control group （23/127，18.11%，P<0.01）. Multivariable Cox regression analysis showed that treatment with Qingre Huoxue prescription ［hazard ratio（HR）=3.013，95% confidence interval （CI） 2.188-4.149， P<0.001］， absence of comorbidities （HR=2.035， 95%CI 1.352-3.061， P<0.001）， and baseline Hcy <15 μmol·L^-1 （HR=1.810， 95%CI 1.390-2.357， P<0.001） were significantly associated with an increased likelihood of achieving target Hcy levels within 6 months. In contrast， higher PGA scores were associated with a reduced likelihood of achieving target Hcy levels （HR=0.991， 95% CI 0.986-0.997， P=0.003）. After treatment，the exposure group demonstrated reductions in ESR，CRP，and DAS 28 scores （P<0.05） and had lower ESR，CRP and DAS 28 scores than the control group （P<0.05）. ConclusionEven after taking FA supplements，some RA patients undergoing MTX treatment still have high Hcy levels. When being used in conjunction with MTX and FA，Qingre Huoxue prescription can effectively lower the Hcy level and disease activity in RA patients with HHcy，outperforming Western treatment alone.

ObjectiveTo evaluate the effects of Qingre Huoxue prescription combined with methotrexate （MTX） and folic acid （FA） on homocysteine （Hcy） levels and disease activity in patients with rheumatoid arthritis （RA） complicated by hyperhomocysteinemia （HHcy）. MethodsOn the basis of a multicenter real-world cohort from the China Registry of Traditional Chinese Medicine for Rheumatism （CERTAIN） platform，408 patients with RA complicated by HHcy were selected and included in this study. Treatment with Qingre Huoxue prescription was used as the exposure factor. According to whether Qingre Huoxue prescription was combined with MTX and FA，patients were assigned into an exposure group of 281 cases and a control group of 127 cases. Follow-ups were conducted every three months，with the primary outcome indicator being the achievement rate of target Hcy level. A generalized estimating equation model was adopted to analyze the dynamic changes in Hcy level under different medication regimens. Kaplan-Meier analysis was performed to evaluate the cumulative achievement rate of target Hcy level in the two groups，and Cox regression analysis was conducted to explore the predictive factors affecting the achievement rate of target Hcy level. Changes in erythrocyte sedimentation rate （ESR），C-reactive protein （CRP），28-joint disease activity score （DAS 28），and Health Assessment Questionnaire-Disability Index （HAQ-DI） scores before and after the first combined treatment with Qingre Huoxue prescription were compared between the two groups. ResultsThe Hcy level in the exposure group showed a gradual decreasing trend over time，while the decrease in Hcy level was not significant in the control group. At the 12-month follow-up，the achievement rate of target Hcy level in the exposure group （124/281，44.13%） was higher than that in the control group （23/127，18.11%，P<0.01）. Multivariable Cox regression analysis showed that treatment with Qingre Huoxue prescription ［hazard ratio（HR）=3.013，95% confidence interval （CI） 2.188-4.149， P<0.001］， absence of comorbidities （HR=2.035， 95%CI 1.352-3.061， P<0.001）， and baseline Hcy <15 μmol·L^-1 （HR=1.810， 95%CI 1.390-2.357， P<0.001） were significantly associated with an increased likelihood of achieving target Hcy levels within 6 months. In contrast， higher PGA scores were associated with a reduced likelihood of achieving target Hcy levels （HR=0.991， 95% CI 0.986-0.997， P=0.003）. After treatment，the exposure group demonstrated reductions in ESR，CRP，and DAS 28 scores （P<0.05） and had lower ESR，CRP and DAS 28 scores than the control group （P<0.05）. ConclusionEven after taking FA supplements，some RA patients undergoing MTX treatment still have high Hcy levels. When being used in conjunction with MTX and FA，Qingre Huoxue prescription can effectively lower the Hcy level and disease activity in RA patients with HHcy，outperforming Western treatment alone.

BACKGROUND:In recent years,improving the health of skeletal muscles through exercise has become an important research concern for scholars.Appropriate exercise has a positive effect on skeletal muscles.Among them,how to activate the sphingosine kinase1(SphK1)/sphingosine-1-phase(S1P)/sphingosine-1-phase receptor2(S1PR2)signaling pathway during exercise so as to improve the health of skeletal muscles is receiving attention from researchers. OBJECTIVE:To investigate how exercise improves the health of skeletal muscles through the SphK1/S1P/S1PR2 signaling pathway,and to explore new methods for treating related muscle diseases in order to improve human skeletal muscle health. METHODS:The first author searched for relevant literature from the establishment of the database to the present in the Web of Science,PubMed,CNKI,WanFang,and VIP databases.The search terms were"signaling pathway,SphK1,S1P,S1PR2,skeletal muscle,satellite cell,myogenesis,exercise"in Chinese and English.Finally,69 articles were included for review and analysis. RESULTS AND CONCLUSION:The SphK1/S1P/S1PR2 signaling pathway is a complex regulatory network that triggers downstream signal transduction processes by SphK1 to catalyze the interaction between S1P and receptors such as S1PR2,thereby regulating multiple biological functions of cells,tissues,organs,and systems.The SphK1/S1P/S1PR2 signaling pathway can regulate satellite cell proliferation and myoblast differentiation,improving myogenesis.The physiological basis of the SphK1/S1P/S1PR2 signaling pathway and the potential impact of exercise on it were analyzed through literature research.Acute aerobic exercise can increase the expression of SphK1 in skeletal muscle.Both human and animal studies have confirmed that acute and long-term exercise can increase the expression of S1P in skeletal muscle.In addition,studies have shown that long-term resistance exercise can increase the expression of S1PR2 in skeletal muscle.Some experimental results indicate that acute and long-term exercise have no significant effect on muscle or blood S1P levels,and the reason for different results may be due to different research subjects,methods,intensities,and frequencies selected,while the specific mechanism is not yet clear.Research suggests that exercise can promote the expression of the SphK1/S1P/S1PR2 signaling pathway in skeletal muscle and regulate downstream related signaling pathways.Research on this signaling pathway may provide new strategies and methods for the treatment of skeletal muscle diseases,thereby improving skeletal muscle health.In the future,we should deepen the research on the association between SphK1/S1P/S1PR2 signaling pathway and skeletal muscle health,further reveal its regulatory relationship with satellite cells and myoblasts as well as its interactions with the upstream and downstream pathways,explore its clinical application value,take into account the changes of this pathway when formulating the rehabilitation program,explore the specific mechanisms by which different types of exercise affect the SphK1/S1P/S1PR2 signaling pathway in skeletal muscles,and use the SphK1/S1P/S1PR2 signaling pathway as a potential therapeutic target for diseases.Further development and application of human muscle models should be developed to improve research depth and accuracy.

Objective: To establish a method for determining the molecular weight and molecular weight distribution of Poly(Lactide-co-Glycolide Acid) (PLGA) using Size Exclusion Chromatography-Refractive Index-Multiangle Laser Light Scattering (SEC-RI-MALLS) and Size Exclusion Chromatography-Refractive Index (SEC-RID), and to compare the results obtained from these two methods.
Methods: For SEC-RI-MALLS, tetrahydrofuran was used as the mobile phase, Shodex GPC KF-803L was employed as the chromatographic column with a flow rate of 1 mL·min^-1, column temperature at 30 ℃, and an injection volume of 100 μL. For SEC-RID, tetrahydrofuran was also used as the mobile phase, Agilent PLgel 5 μm MIXD-D was used as the chromatographic column with a flow rate of 1 mL·min^-1, column temperature at 30 ℃, differential detector temperature at 35 ℃, and an injection volume of 20 μL. The molecular weight and molecular weight distribution were calculated using Agilent’s GPC software. The newly established methods were validated methodologically, and the molecular weight and molecular weight distribution of 13 batches of samples were determined.
Results: The precision, accuracy, stability, and repeatability tests for SEC-RI-MALLS showed RSD values of 1.35%, 1.58%, 1.53%, and 1.26%, respectively. The SEC-RID method exhibited good linearity (r=0.999 9), with RSD values for precision, accuracy, stability, and repeatability tests (n=6) of 2.05%, 1.62%, 1.30%, and 2.97%, respectively. The results obtained from SEC-RI-MALLS were lower than those from SEC-RID, and the molecular weight distribution coefficient was smaller, but the results from the paired T-test performed with the value measured by SEC-RID method and the value measured by SEC-RI-MALLS method multiplied a conversion coefficient of 1.5 showed no significant difference between the two methods.
Conclusion: Both methods are stable and reliable, and can be used for the determination of PLGA molecular weight and molecular weight distribution based on the specific situations.

OBJECTIVE To construct and evaluate nomogram prediction model for refractory chemotherapy-induced nausea and vomiting （CINV）. METHODS The data of malignant tumor patients who received chemotherapy at the Third People’s Hospital of Zhengzhou from January 2017 to December 2023 were collected. These patients were categorized into the occurrence group and the non-occurrence group according to the occurrence of refractory CINV. Multivariate Logistic regression analysis was employed to screen predictive factors for refractory CINV and constructing a nomogram prediction model. Model performance was assessed via receiver operating characteristic curve analysis. Model calibration was evaluated using Bootstrap resampling. Decision curve analysis （DCA） was used to determine the clinical net benefit of three strategies under different risk thresholds. Clinical impact curves were utilized to assess the clinical value of the model at different risk thresholds. Shapley additive explanations （SHAP） analysis was performed to evaluate individual factor contributions to the predictive model. RESULTS A total of 388 patients were included， with 219 experiencing refractory CINV. Multivariate Logistic regression identified 11 predictive factors for refractory CINV， including gastrointestinal disease history， anticipated nausea and vomiting， chemotherapy-induced emetic risk classification， and electrolyte levels， etc. The model’s area under the curve was 0.80 [95% confidence interval （0.76， 0.84）]， with a mean error of 0.036. DCA demonstrated the prediction model had higher clinical net benefit when the risk threshold was between 0.05 and 0.85. SHAP analysis revealed the top three predictive factors as gastrointestinal disease history （0.924）， chemotherapy- induced emetic risk classification （0.866）， and electrolyte levels （0.581）. CONCLUSIONS Eleven factors， including gastrointestinal disease history， anticipated nausea and vomiting， chemotherapy-induced emetic risk classification， and electrolyte levels， are identified as predictors of refractory CINV. The model based on these factors has good predictive ability， which can be used to predict the risk of refractory CINV.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.