ObjectiveTo identify the primary hemostatic active components in Moutan Cortex Carbonisata（MCC） based on the spectrum-effect relationship between the fingerprint and hemostatic efficacy， thereby providing a basis for characterizing its active constituents. MethodsUltra-performance liquid chromatography-quadrupole-electrostatic field orbitrap high-resolution mass spectrometry（UPLC-Q-Orbitrap MS/MS） was employed to establish the fingerprint profiles of 16 batches of MCC aqueous extracts and identify the common peaks. Activated partial thromboplastin time（APTT）， an in vitro coagulation activity indicator， was measured for the 16 batches of samples using a semi-automated coagulometer. Grey relational analysis（GRA）， Pearson correlation analysis， and partial least squares regression（PLSR） were comprehensively applied to screen potential hemostatic active components. For the identified active components， multi-dimensional pharmacological validation was conducted through in vitro coagulation assays measuring APTT， prothrombin time（PT）， and thrombin time（TT）， evaluation of hemostasis rate using a zebrafish cerebral hemorrhage model， and real-time quantitative polymerase chain reaction（Real-time PCR） detection of coagulation factor X（FⅩ） mRNA expression level. ResultsThe UPLC fingerprint of the aqueous extract of MCC was successfully established， identifying 12 common peaks. Among these， 9 chemical components were subsequently characterized using UPLC-Q-Orbitrap MS. Comprehensive application of GRA， Pearson correlation analysis， and PLSR analysis identified 5-hydroxymethylfurfural（5-HMF）， gallic acid， 1-O-galloylglucose， and p-hydroxybenzoic acid as key hemostatic active constituents in MCC. In vitro coagulation assays confirmed that all four active components significantly shortened APTT and PT（P<0.05， P<0.01）. The zebrafish cerebral hemorrhage model further validated their in vivo hemostatic efficacy， with each component significantly reducing hemorrhage area（P<0.05， P<0.01）， yielding hemostasis rates of 31.20% for 5-HMF， 68.85% for gallic acid， 45.45% for 1-O-galloylglucose， and 45.60% for p-hydroxybenzoic acid， and demonstrating overall concentration-dependent effects. Real-time PCR analysis demonstrated that all active components significantly upregulated FⅩ mRNA expression（P<0.05， P<0.01）， synergistically enhancing hemostasis. ConclusionBy integrating spectrum-effect relationship analysis and multi-dimensional efficacy validation， this study identified four hemostatic constituents from MCC， providing a scientific basis for elucidating its hemostatic material basis.

ObjectiveTo systematically evaluate the application of narrative education in undergraduate nursing teaching， to understand the current application status of narrative education， and to provide a theoretical basis for the subsequent establishment of a sound narrative education system. MethodsA systematic search was conducted for studies published in Chinese and English databases on applying narrative education to undergraduate nursing teaching， with the search period ranging from database inception to February 23， 2025. Literature was screened， and relevant information was extracted. A rigorous quality evaluation was conducted on the included studies， and a descriptive analysis was performed on their content. ResultsA total of 20 papers were included， involving 3，180 research subjects， all of whom were undergraduate nursing students. The results of descriptive analysis showed that the teaching model of narrative education primarily encompassed reading narrative works， watching films and videos， performing narrative scenarios， and writing reflective journals. The course setting and content covered pre-teaching preparation and in-teaching implementation. The evaluation of teaching effectiveness included the evaluation of teachers’ teaching methods （student evaluation/self-evaluation） and the evaluation of students’ learning effectiveness （course grade evaluation/humanistic care scale/empathy scale assessment， and others）. ConclusionNarrative education combines abstract concepts with concrete clinical situations， which not only enriches students’ learning experiences but also enhances their humanistic literacy. Meanwhile， it provides teachers with opportunities to develop their narrative teaching skills， which requires them to possess profound professional knowledge and employ narrative techniques to guide students in reflection and critical thinking， thereby improving teaching quality and learning outcomes. Future efforts should consistently deepen the connotation research of narrative education and build a systematic nursing education system.

The Medical Cases of WU Jutong （《吴鞠通医案》） proposes the principle of "treating all Bi （痹） diseases through taiyin"， which forms the basis for analyzing WU Jutong's understanding of the causes， mechanisms， and treatments of Bi （痹） diseases， providing a reference for clinical diagnosis and treatment. Through an interpretation of the phrase "treating all Bi （痹） diseases through taiyin"， it is suggested that Bi （痹） diseases is primarily caused by dampness， necessitating a focus on spleen and lung in treatment. WU emphasized four main causes of Bi （痹） diseases （wind， cold， dampness， and heat）， with dampness being the predominant factor. The disease location is initially in lung， for which external dampness invades lung first， and internal dampness obstructs the source of water metabolism， impeding lung qi and qi failing to disperse， then dampness further accumulates in the joints， leading to Bi （痹） diseases. WU Jutong proposed the modified Mufangji Decoction （木防己汤） as the foundational prescription for treating Bi （痹） diseases. By comparing the similarities and differences between the modified and original Mufangji Decoction， and analyzing the adjustments in herbal prescriptions， the clinical characteristic of "treating all Bi （痹） diseases through taiyin" is further substantiated.

Two-dimensional nuclear magnetic resonance (2D NMR) is a widely used technique for structural analysis of small molecular compounds. It can obtain information about the hydrogen-hydrogen correlation, hydrogen-carbon single bond correlation, hydrogen-carbon remote correlation, and hydrogen-hydrogen spatial arrangement of compounds. Thus, 2D NMR has an irreplaceable role in the structure elucidation of small molecular products. However, the sample amount of trace components in phytochemical research is very low, and the traditional sampling method (uniform sampling) has problems of poor spectral quality and too long measure time. Increasing the number of scans results in several hours of the acquisition time for a single two-dimensional spectrum, which in turn causes strain on the NMR machine. The non-uniform sampling (NUS) technique can shorten the acquisition time to a large extent and not affect the quality of 2D NMR data, which greatly improves the efficiency of 2D NMR acquisition. In this paper, fuziline, a small molecular compound in the lateral roots of Aconitum carmichaelii was selected as the research object. Its ¹H-¹³C HSQC, ¹H-¹H COSY, HMBC, and NOESY spectra were acquired by US and NUS methods, respectively. By comparing the integral values of NMR signals of three chemical groups in fuziline, it is confirmed that the NUS technique has the advantages of improving the quality of 2D NMR spectra and shortening the acquisition time in structure elucidation of small molecule compounds. In HMBC spectrum, it was further confirmed that NUS technology can improve the quality of the 2D spectra and the signal resolution. This indicates that NUS technology can improve the efficiency and reliability of the structure elucidation of small molecule compounds.

ObjectiveTo retrospectively analyze the epidemiological trends of birth defects in perinatal infants in Fengxian District, Shanghai from 2018 to 2022, so as to provide a scientific evidence for the formulation of related prevention and control strategies. MethodsBased on the data from the National Birth Defects Surveillance System, statistical analysis was conducted on the perinatal birth defects from monitored hospitals within the region from 2018 to 2022. ResultsFrom 2018 to 2022, a total of 20 870 perinatal infants delivered in the monitored hospitals in Fengxian District, with 472 cases with birth defects, showing a significant increase in the prevalence of birth defects (PRR=1.49, 95%CI: 1.39‒1.59). The risk of birth defects increased with maternal age, especially for advanced maternal age (PRR=1.58, 95%CI: 1.12‒2.25). Infants born to mothers with gestational diabetes had a higher prevalence of birth defects compared to those without gestational diabetes (PRR=1.99, 95%CI: 1.46‒2.70). Infants with birth defects were more likely to be born prematurely (PRR=2.07, 95%CI:1.56‒2.76). The top three types of birth defects were congenital heart disease (CHD), other anomalies of the external ear, and polydactyly. ConclusionThe prevalence of birth defects in Fengxian District monitored hospitals showed an upward trend from 2018 to 2022. Advanced maternal age and gestational diabetes were identified as risk factors for birth defects. CHD is the leading type of birth defect in Fengxian District over the five-year period. To reduce the prevalence of birth defects, it is crucial to implement comprehensive prevention and treatment measures for CHD.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Hypercoagulable state (HCS) after kidney transplantation is one of the common and serious complications in kidney transplant recipients, which has attracted increasing attention in recent years. HCS refers to the abnormal and excessive activation of blood coagulation function, leading to the increased risk of thrombosis. After kidney transplantation, the combined effects of hemodynamic changes, surgical trauma and severe rejection increase the incidence of HCS, not only raising the risk of thrombosis but also potentially causing graft failure and affecting the postoperative survival rate of patients. This article reviews the influencing factors, clinical manifestations, diagnostic methods and preventive strategies of HCS after kidney transplantation, aiming to provide a theoretical basis for optimizing perioperative management and improving the prognosis of patients.

Chronic heart failure （CHF）， as the terminal stage of various cardiovascular diseases， is characterized by a prolonged clinical course and recurrent exacerbations. The coexistence of CHF with anxiety and depression falls under the category of psycho-cardiological diseases. Studies have demonstrated that anxiety and depression are closely associated with adverse outcomes including elevated risks of cardiovascular events and increased mortality in CHF patients. The complex pathogenesis poses challenges to modern medical treatments， which often face limited efficacy and concurrent side effects. According to the theory of Shaoyang Pivot in traditional Chinese medicine （TCM）， this paper elucidates that obstructed Shaoyang Pivot—manifested as Qi transformation disorder， dysregulated fluid metabolism， and abnormal distribution of ministerial fire-serves as a critical pathological basis for CHF with anxiety and depression. Bupleuri Radix-based Formulas， such as Xiao Chaihu Tang， Chaihu Guizhi Tang， and Chaihu Jia Longgu Muli Tang， aim to harmonize lesser Yang to restore the Qi transformation， activate Yang to promote water excretion， and redistribute ministerial fire， thus effectively alleviating pathological states such as Qi stagnation， blood stasis， water retention， and phlegm-fire disturbing the heart in CHF patients with anxiety and depression. Consequently， they mitigate symptoms of this psycho-cardiological disease. Mechanism studies have revealed that Bupleuri Radix-based formulas exhibit multi-target effects， including modulation of neurotransmitters， suppression of inflammatory responses， regulation of lipid metabolism， protection of cardiomyocytes， and improvement of the endothelial function. By interpreting the TCM pathogenesis of CHF with anxiety and depression from the theory of Shaoyang Pivot， this paper delves into the therapeutic principles and mechanisms of Bupleuri Radix-based formulas， providing a theoretical foundation for optimizing TCM diagnosis and treatment strategies for psycho-cardiological diseases.