The prescription of Qidong Yixin oral liquid is derived from the experience of national medical master Ren Jixue in treating viral myocarditis （VMC）. It has the functions of tonifying Qi， nourishing the heart，calming the mind， and relieving palpitations. It is used to treat VMC and angina pectoris of coronary heart disease caused by deficiency of both Qi and Yin. However，the understanding of its efficacy evidence， advantageous aspects， dosage and administration， and medication safety remains insufficient in clinical practice. Therefore，the development of the Expert Consensus on the Clinical Application of Qidong Yixin Oral Liquid （hereinafter referred to as consensus） was initiated. Consensus strictly followed the process and methods of the expert consensus on the clinical application of Chinese patent medicines of the China Association of Chinese Medicine，successively completing multiple tasks such as the consensus project initiation，determination of clinical problems，evidence search and evaluation，formation of recommendation opinions and consensus suggestions，solicitation of opinions，peer review， submission for review and release， and so on. Consensus formed a total of 10 recommendation opinions and 12 consensus suggestions，clarifying the clinical positioning，efficacy advantages，syndrome differentiation，dosage and administration，combination therapy，timing of medication，adverse reactions，contraindications， and precautions of Qidong Yixin oral liquid，indicating that it has good clinical advantages and safety in the treatment of VMC and angina pectoris of coronary heart disease，providing norms and references for physicians to safely and rationally apply Qidong Yixin oral liquid. Consensus was reviewed and approved for release by the Standardization Office of the China Association of Chinese Medicine on December 23， 2024. Standard number：GSCACM-376-2024.

ObjectiveTo investigate the therapeutic mechanism of Xuefu Zhuyutang （XFZYT） for metabolic-associated fatty liver disease （MAFLD） through integrated network pharmacology and animal experiments. MethodsNetwork pharmacology was utilized to predict the core components， key therapeutic targets， and signaling pathways of XFZYT in the treatment of MAFLD. For animal experiments， a rat model of MAFLD was established by feeding a high-cholesterol diet for 4 weeks. Intervention was then administered with low-dose （2 g·kg^-1） and high-dose （4 g·kg^-1） XFZYT for 2 weeks. Biochemical assays were performed to measure the serum levels of aspartate aminotransferase （AST）， alanine aminotransferase （ALT）， total cholesterol （TC）， triglycerides （TG）， high-density lipoprotein （HDL）， and low-density lipoprotein （LDL）. In addition， the activities of superoxide dismutase （SOD） and catalase （CAT） and levels of malondialdehyde （MDA） and glutathione （GSH） in the serum were measured. The same way was adopted to measure the levels of TC and TG in the liver tissue. Enzyme-linked immunosorbent assay （ELISA） was employed to quantify the serum levels of interleukin （IL）-6， IL-1β， and tumor necrosis factor-alpha （TNF-α）. Histopathological evaluations included hematoxylin and eosin （HE） staining for liver tissue morphology， Oil Red O staining for lipid deposition， and dihydroethidium （DHE） probe staining for reactive oxygen species （ROS） levels. Western blot analysis was conducted to assess the protein levels of AMP-activated protein kinase （AMPK）， phosphorylated （p）-AMPK， nuclear factor erythroid 2-related factor 2 （Nrf2）， heme oxygenase-1 （HO-1）， nuclear factor-kappa B （NF-κB）， and p-NF-κB in the liver tissue. Untargeted metabolomics analysis of the serum was performed by liquid chromatography-tandem mass spectrometry （LC-MS/MS）. ResultsNetwork pharmacology analysis predicted 155 potential targets of XFZYT for MAFLD treatment， with core targets including signal transducer and activator of transcription 3 （STAT3）， protein kinase B1 （Akt1）， TNF， and IL-6. Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment primarily implicated the AMPK signaling pathway. Animal experiments demonstrated that compared with the normal group， the model group exhibited dyslipidemia， hepatic function impairment， pronounced hepatic lipid deposition， and inflammatory manifestations， with elevated serum levels of AST， ALT， TC， TG， LDL， and MDA （P<0.05）， reduced HDL and GSH levels plus decreased SOD and CAT activities （P<0.05）， downregulated protein levels of Nrf2， HO-1， and p-AMPK （P<0.05）， and upregulated protein level of p-NF-κB （P<0.05） in the liver tissue. Compared with the model group， XFZYT intervention groups showed significant amelioration of dyslipidemia and hepatic function impairment， markedly reduced hepatic lipid deposition and inflammatory cell infiltration， decreased serum levels of AST， ALT， TC， TG， LDL， and MDA （P<0.05）， increased HDL and GSH levels plus enhanced SOD and CAT activities （P<0.05）， upregulated protein levels of Nrf2， HO-1， and p-AMPK （P<0.05）， and downregulated protein level of p-NF-κB （P<0.05）. Serum metabolomics revealed 511 differentially expressed metabolites （231 upregulated and 280 downregulated） between normal and model groups， while XFZYT groups versus model group showed 94 differential metabolites （51 upregulated and 43 downregulated）. Among them， 11 metabolites displayed the most significant alterations， with enriched pathways including glycerolipid metabolism， cholesterol metabolism， and insulin resistance， multiple of which demonstrated AMPK association. ConclusionXFZYT alleviates MAFLD by regulating the AMPK signaling pathway and associated metabolic networks.

ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

Background: The hypotension prediction index (HPI) is an algorithm designed to predict hypotension. Some studies have reported that HPI-guided hemodynamic management strategies decrease intraoperative hypotension and complications; however, the effect of HPI on reducing perioperative complications is controversial. This meta-analysis aimed to assess the efficacy of the HPI in reducing major complications and intraoperative hypotension. Methods: We conducted this meta-analysis according to the PRISMA statement and Cochrane Handbook guidelines. A comprehensive literature review was conducted to identify studies focusing on the efficacy of HPI-guided management in reducing intraoperative hypotension and postoperative complications. The PubMed, Embase, Scopus, and Web of Science databases were searched, and the resulting data were combined to calculate the pooled mean differences or risk ratios (RRs) with 95% CIs of both randomized controlled trials (RCTs) and retrospective studies, as appropriate. Heterogeneity and potential publication bias were also assessed. Results: Nineteen articles (12 RCTs and 7 retrospective studies) with 2570 recruited patients were included in this meta-analysis. The critical evaluation of the study quality revealed a low risk of bias in the included RCTs. Among the non-randomized trials, one was rated 7, two were rated 8, and the remaining four were rated 9 on the Newcastle-Ottawa Scale, indicating high quality and a low risk of bias. HPI-guided management significantly reduced intraoperative hypotension and associated major complications (RR = 0.79, 95% CI [0.69–0.90], I2 = 0, P < 0.001). Blood loss and length of hospital stay were comparable between the groups. Conclusions HPI-guided management significantly reduced intraoperative hypotension and major complications.

Sinusoidal obstruction syndrome/veno-occlusive disease （SOS/VOD） after hematopoietic stem cell transplantation （HSCT） in children has high incidence and mortality rates， and missed diagnosis of jaundice-free cases is common. In addition， there are still controversies over the efficacy of prophylactic defibrotide （DF） use， and the European Medicines Agency does not recommend the prophylactic use of DF， whereas clinical needs remain urgent. In 2026， by integrating controversial research evidence and focusing on specific prophylaxis for high-risk children， the European Society for Blood and Marrow Transplantation established a weighted cumulative scoring system to quantify risks and accurately identify the populations who may benefit from DF prophylaxis， in order to provide evidence-based support for the prophylactic use of DF， reduce the incidence and mortality rates of SOS/VOD in children， and improve the prognosis of patients. This article gives an excerpt of the key points in the consensus guidelines.

Objective To explore the factors predicting the reliability of platelet-impedance(PLT-I)re-sults through a retrospective analysis of non-aggregated samples with abnormal platelet histograms.Methods A total of 322 samples with abnormal platelet histograms were collected from the Sysmex XN9000 automatic hematology analyzer,all of which showed no platelet aggregation as determined by the DI-60 auto-matic digital image analysis system.Using the platelet count fluorescent(PLT-F)results as a standard,the absolute and relative deviations of PLT-I results were calculated,and the parameters of samples with devia-tions within and outside the allowable range were analyzed.Logistic regression analysis was used to identify potential factors associated with deviations of PLT-I from PLT-F beyond the allowable range.The receiver op-erating characteristic(ROC)curve was used to evaluate the predictive value of these potential factors for devi-ations beyond the allowable range.Results The deviations of PLT-I from PLT-F were within the allowable range in 279 cases(86.65％)and outside the allowable range in 43 cases(13.35％).Comparisons between the two groups revealed statistically significant differences in mean red blood cell valume(MCV),red blood cell distribution width-cuefficient of variation(RDW-SD),DI-60 red cell fragments,platelet distribution width(PDW),and DI-60 large platelet ratio(P＜0.05).Logistic regression indicated that DI-60 red cell fragments and DI-60 large platelet ratio were independent potential factors for deviations of PLT-I from PLT-F beyond the allowable range(P＜0.05).The cut off values for predicting deviations beyond the allowable range were 1.75 for DI-60 red cell fragments and 66％for DI-60 large platelet ratio.The area under the curve(AUC)for the combined diagnosis of the two factors was 0.813,with a sensitivity of 88.4％and a specificity of 66.3％,indicating a higher predictive value than individual factors(P＜0.05).Conclusion When platelet histograms are abnormal,DI-60 large platelet ratio and DI-60 red cell fragments are independent potential factors predic-ting the reliability of PLT-I results,and their combination has a high predictive value.

Objective To explore the risk factors for 28-day mortality of sepsis-associated acute kidney injury(SA-AKI)patients and to develop a nomogram risk prediction model.Methods A retrospective cohort study was conducted,involving 184 patients with SA-AKI admitted to the intensive care unit(ICU)of the 940th Hospital of Joint Logistic Support Force of PLA between January 2017 and December 2022.Patients were categorized into survival(n=135)and non-survival(n=49)groups based on 28-day mortality.Clinical data were collected,and statistically significant risk factors were preliminarily screened.Multivariate stepwise logistic regression analysis was performed to identify independent risk factors for 28-day mortality of SA-AKI patients.A nomogram predictive model was constructed using these factors,and internally validated with the Bootstrap method.The receiver operating characteristic curve(ROC curve)was drawn,and the area under the ROC curve(AUC)was calculated to verify the predictive value and accuracy of the model.Results The 28-day mortality rate among 184 SA-AKI patients was 26.6％(49/184).Multivariate stepwise logistic regression analysis identified multiple organ dysfunction syndrome(MODS)(OR=16.393,95％CI 4.317-62.254,P＜0.001),high acute physiology and chronic health evaluation Ⅱ(APACHE Ⅱ)score(OR=1.097,95％CI 1.036-1.161,P=0.002),low oxygenation index(OR=0.992,95％CI 0.986-0.998,P=0.015),low neutrophil count(OR=0.912,95％CI 0.860-0.968,P=0.002)and low fibrinogen concentration(OR=0.733,95％CI 0.549-0.978,P=0.034)as independent risk factors.The prediction model equation was P=1/1+e-logit(P),logit(P)=-1.626+2.797×MODS+0.092×AP ACHE Ⅱ+(-0.311)×fibrinogen+(-0.092)×neutrophil count+(-0.008)×oxygenation index.Internal validation with 1000 Bootstrap resamples showed high consistency between predicted and actual values.ROC analysis showed an AUC of 0.911(95％CI 0.868-0.955,P＜0.05)for the model,with 93.9％sensitivity and 78.5％specificity at a cut-off of 0.194.The Hosmer-Lemeshow test confirmed good calibration(P=0.62),and decision-making curve analysis demonstrated clinical utility within the high-risk threshold range(0.1-0.9).Conclusions MODS,high APACHE Ⅱ score,low oxygenation index,low neutrophil count,and low fibrinogen concentration are independent risk factors for 28-day mortality in SA-AKI patients.The developed nomogram risk prediction model may provide important guidance for predicting 28-day mortality in SA-AKI patients.

Mitophagy is a specific type of autophagy that selectively eliminates damaged mitochondria to maintain mitochondrial activity and cellular homeostasis.In recent years,regulating mitophagy to preserve normal cellular functions has gradually become an important preventive and therapeutic strategy for many diseases.Macrophages are key participants in the formation of atherosclerosis(AS)plaques.Studies have shown that mitophagy may be involved in the development of AS by regulating macrophage homeostasis and physiological functions.This review summarizes the mechanisms by which mitophagy regulates macrophage lipid metabolism,inflammation,senescence,apoptosis and pyroptosis in AS,aiming to provide a new theoretical basis for mitophagy-mediated regulation in AS.

Objective To explore the effectiveness of drawing-based method in medical courses and their impact on students' learning habits,academic performance,and comprehensive competencies,in order to meet the demand for high-quality,interdisciplinary,and innovative talent,and provide theoretical support for integrating aesthetic education into medical training.Methods A questionnaire survey was conducted among medical students(n=310)at Dalian Medical University,covering the frequency of using drawing method and their effects on learning outcomes,innovation ability,and humanistic qualities.Data were analyzed using the Chi-square test and Fisher's exact test(P＜0.05).Results Totally 93.6％of students approved of using drawing method for learning medical courses,with 70.8％having developed a habit of drawing-based learning.Students with stronger drawing skills were more inclined to use drawing method and supported their application in teaching.The frequency of drawing-based learning was positively correlated with anatomy scores(P＜0.05).Students generally agreed that drawing method enhanced knowledge comprehension,learning interest,long-term memory,innovation ability,critical thinking,and humanistic qualities.However,students with weaker drawing skills perceived drawing method as potentially increasing learning burdens and being less efficient,but this perception significantly decreased with increased drawing frequency(P＜0.05).Conclusion Drawing methods are widely used in medical courses and effectively improve learning outcomes and comprehensive competencies.Drawing proficiency and frequency are key factors influencing students' acceptance and learning effectiveness.Future efforts should focus on promoting drawing method,strengthening students' drawing skills,and optimizing learning processes to deepen the integration of aesthetic education in medical training.