To explore the advantages of traditional Chinese medicine （TCM） and integrative TCM-Western medicine approaches in the treatment of diabetic microvascular complications （DMC）， refine key pathophysiological insights and treatment principles， and promote academic innovation and strategic research planning in the prevention and treatment of DMC. The 38th session of the Expert Salon on Diseases Responding Specifically to Traditional Chinese Medicine， hosted by the China Association of Chinese Medicine， was held in Beijing， 2024. Experts in TCM， Western medicine， and interdisciplinary fields convened to conduct a systematic discussion on the pathogenesis， diagnostic and treatment challenges， and mechanism research related to DMC， ultimately forming a consensus on key directions. Four major research recommendations were proposed. The first is addressing clinical bottlenecks in the prevention and control of DMC by optimizing TCM-based evidence evaluation systems. The second is refining TCM core pathogenesis across DMC stages and establishing corresponding "disease-pattern-time" framework. The third is innovating mechanism research strategies to facilitate a shift from holistic regulation to targeted intervention in TCM. The fourth is advancing interdisciplinary collaboration to enhance the role of TCM in new drug development， research prioritization， and guideline formulation. TCM and integrative approaches offer distinct advantages in managing DMC. With a focus on the diseases responding specifically to TCM， strengthening evidence-based support and mechanism interpretation and promoting the integration of clinical care and research innovation will provide strong momentum for the modernization of TCM and the advancement of national health strategies.

ObjectiveTo observe the clinical efficacy of the Yiqi Yangyin Huoxue prescription （YYHP） in the treatment of cathartic colon （CC） and its effects on fecal short-chain fatty acids （SCFAs）， and to explore the correlations among CC severity indicators and between these indicators and patient history. MethodsAccording to the inclusion and exclusion criteria， 98 patients meeting the diagnostic criteria of both traditional Chinese and Western medicine for CC with the syndrome of Qi-Yin deficiency complicated by blood stasis were randomly assigned to an observation group and a control group. The observation group received YYHP granules， while the control group received lactulose. Both medications were administered twice daily， one sachet each time， half an hour after breakfast and dinner， with a treatment course of 8 weeks. The primary constipation symptom score， Patient Assessment of Constipation Quality of Life （PAC-QOL） score， and TCM syndrome score were assessed before and after treatment and at the 8^th week after the end of treatment. The overall clinical effective rate， as well as the efficacy attenuation index and degree， were evaluated. Fecal SCFA levels were measured using gas chromatography-mass spectrometry （GC-MS）. Spearman correlation analysis was performed to explore the correlations among CC severity indicators and between these indicators and patient history. ResultsThe overall clinical effective rate in the observation group （95.83%） was higher than that in the control group （78.72%） （P<0.05）. After treatment， the total scores for primary constipation symptoms， PAC-QOL， and TCM syndromes decreased in both groups （P<0.05）， with more significant reductions in the observation group （P<0.05）. The severity of all primary constipation symptoms was alleviated in both groups （P<0.05）. In terms of "excessive straining and difficult defecation"， "anal heaviness， incomplete evacuation， and bloating sensation"， "abdominal distension"， and "defecation frequency"， the observation group showed better efficacy than the control group （P<0.05）. Scores of the four PAC-QOL dimensions and the scores and severity of primary and secondary TCM symptoms were reduced in both groups （P<0.05）， with more significant reductions in the observation group （P<0.05）. After treatment， acetic acid， propionic acid， butyric acid， and total SCFAs in the observation group increased significantly （P<0.05）. The efficacy attenuation index and degree in the observation group were lower than those in the control group （P<0.05）. No severe adverse reactions occurred in either group， and there was no statistically significant difference in the incidence of adverse reactions between the two groups. Positive correlations of varying degrees were observed among the total scores of primary constipation symptoms， PAC-QOL， and TCM syndromes， as well as between these scores and the history of stimulant laxative use， disease duration， and age. ConclusionYYHP can effectively alleviate the primary constipation symptoms in CC patients， improve quality of life， and ameliorate TCM syndromes， with good safety. It also has the advantage of a lower rebound degree after drug withdrawal， and its mechanism may be related to increasing fecal SCFA levels. Long-term abuse of stimulant laxatives may aggravate the severity of CC and prolong the disease course.

Diabetic Nephropathy (DN) is the leading cause of end-stage renal disease (ESRD) globally, representing a major global health burden with limited disease-modifying therapies. Podocyte injury serves as the core pathological hallmark of DN, and conventional treatments targeting metabolic disorders or hemodynamic abnormalities fail to reverse the progressive decline of renal function. Accumulating evidence over the past decade has established that high glucose-induced podocyte pyroptosis—a pro-inflammatory form of programmed cell death—is a key driving force in DN progression. Its core molecular mechanism hinges on the activation of the TXNIP-NLRP3 inflammasome axis. Under sustained hyperglycemic conditions, excessive reactive oxygen species (ROS) are generated via pathways including the polyol pathway, advanced glycation end products (AGEs) accumulation, and mitochondrial dysfunction. Concurrently, methylglyoxal (a glucose metabolite) mediates post-translational modification of thioredoxin-interacting protein (TXNIP). These events collectively trigger the dissociation of TXNIP from thioredoxin (TRX), a redox-regulating protein. The free TXNIP then translocates to the mitochondria, where it binds to The NACHT, LRR, and PYD domain-containing protein 3 (NLRP3) and promotes inflammasome assembly. This assembly activates cysteine-aspartic acid protease 1 (caspase-1), which cleaves Gasdermin D (GSDMD) to generate its N-terminal fragment (GSDMD-NT). GSDMD-NT oligomerizes to form membrane pores, leading to podocyte swelling, rupture, and the release of pro-inflammatory cytokines interleukin-1β (IL-1β) and interleukin-18 (IL-18). These cytokines amplify local inflammatory responses, induce mesangial cell proliferation, and accelerate extracellular matrix deposition, ultimately exacerbating glomerulosclerosis. MCC950, a highly selective NLRP3 inhibitor, exerts its therapeutic effects through a multi-layered mechanism: it binds to the NACHT domain (NAIP, CIITA, HET-E and TP1 domain) of NLRP3 with nanomolar affinity, forming hydrogen bonds with key residues (Lys-42 and Asp-166) within the ATP-hydrolysis pocket to block ATP hydrolysis, thereby locking NLRP3 in an inactive conformational state. Additionally, MCC950 interferes with the protein-protein interaction between TXNIP and NLRP3 and regulates mitochondrial homeostasis to reduce ROS production. Preclinical studies have demonstrated that MCC950 dose-dependently reduces proteinuria, restores the expression of podocyte-specific markers (nephrin and Wilms tumor 1 protein, WT1), and alleviates podocyte foot process fusion and glomerulosclerosis in both streptozotocin (STZ)-induced type 1 diabetic models (characterized by absolute insulin deficiency) and db/db type 2 diabetic models (driven by insulin resistance). However, discrepancies in therapeutic outcomes exist across different models—some studies report exacerbated renal inflammation and fibrosis in STZ-induced models—which may stem from differences in disease pathogenesis, intervention timing (early vs. mid-stage disease), and dosing duration. Despite its promising preclinical efficacy, MCC950 faces significant translational challenges, including low oral bioavailability, insufficient podocyte targeting, potential hepatotoxicity, and drug-drug interactions with statins (commonly prescribed to diabetic patients for cardiovascular risk management). Furthermore, off-target effects such as the inhibition of carbonic anhydrase 2 have been identified, raising concerns about its safety profile. Nevertheless, its unique mechanism of action—directly blocking podocyte pyroptosis by targeting the TXNIP-NLRP3 axis—endows it with substantial translational value. In the future, strategies to overcome these barriers are expected to advance its clinical application: targeted delivery via nanocarriers (e.g., PLGA-PEG nanoparticles or nephrin antibody-conjugated systems) to enhance renal accumulation and podocyte specificity; precise patient stratification based on biomarkers such as serum IL-18 and renal TXNIP/NLRP3 expression to identify “inflammatory-phenotype” DN patients most likely to benefit; and combination therapy with sodium-glucose cotransporter 2 (SGLT2) inhibitors—whose metabolic benefits synergize with MCC950’s anti-inflammatory effects. These approaches hold great potential to break through clinical translation bottlenecks, offering a novel, precise anti-inflammatory treatment option for DN and addressing an unmet clinical need for therapies targeting the inflammatory underpinnings of the disease.

Diabetic Nephropathy (DN) is the leading cause of end-stage renal disease (ESRD) globally, representing a major global health burden with limited disease-modifying therapies. Podocyte injury serves as the core pathological hallmark of DN, and conventional treatments targeting metabolic disorders or hemodynamic abnormalities fail to reverse the progressive decline of renal function. Accumulating evidence over the past decade has established that high glucose-induced podocyte pyroptosis—a pro-inflammatory form of programmed cell death—is a key driving force in DN progression. Its core molecular mechanism hinges on the activation of the TXNIP-NLRP3 inflammasome axis. Under sustained hyperglycemic conditions, excessive reactive oxygen species (ROS) are generated via pathways including the polyol pathway, advanced glycation end products (AGEs) accumulation, and mitochondrial dysfunction. Concurrently, methylglyoxal (a glucose metabolite) mediates post-translational modification of thioredoxin-interacting protein (TXNIP). These events collectively trigger the dissociation of TXNIP from thioredoxin (TRX), a redox-regulating protein. The free TXNIP then translocates to the mitochondria, where it binds to The NACHT, LRR, and PYD domain-containing protein 3 (NLRP3) and promotes inflammasome assembly. This assembly activates cysteine-aspartic acid protease 1 (caspase-1), which cleaves Gasdermin D (GSDMD) to generate its N-terminal fragment (GSDMD-NT). GSDMD-NT oligomerizes to form membrane pores, leading to podocyte swelling, rupture, and the release of pro-inflammatory cytokines interleukin-1β (IL-1β) and interleukin-18 (IL-18). These cytokines amplify local inflammatory responses, induce mesangial cell proliferation, and accelerate extracellular matrix deposition, ultimately exacerbating glomerulosclerosis. MCC950, a highly selective NLRP3 inhibitor, exerts its therapeutic effects through a multi-layered mechanism: it binds to the NACHT domain (NAIP, CIITA, HET-E and TP1 domain) of NLRP3 with nanomolar affinity, forming hydrogen bonds with key residues (Lys-42 and Asp-166) within the ATP-hydrolysis pocket to block ATP hydrolysis, thereby locking NLRP3 in an inactive conformational state. Additionally, MCC950 interferes with the protein-protein interaction between TXNIP and NLRP3 and regulates mitochondrial homeostasis to reduce ROS production. Preclinical studies have demonstrated that MCC950 dose-dependently reduces proteinuria, restores the expression of podocyte-specific markers (nephrin and Wilms tumor 1 protein, WT1), and alleviates podocyte foot process fusion and glomerulosclerosis in both streptozotocin (STZ)-induced type 1 diabetic models (characterized by absolute insulin deficiency) and db/db type 2 diabetic models (driven by insulin resistance). However, discrepancies in therapeutic outcomes exist across different models—some studies report exacerbated renal inflammation and fibrosis in STZ-induced models—which may stem from differences in disease pathogenesis, intervention timing (early vs. mid-stage disease), and dosing duration. Despite its promising preclinical efficacy, MCC950 faces significant translational challenges, including low oral bioavailability, insufficient podocyte targeting, potential hepatotoxicity, and drug-drug interactions with statins (commonly prescribed to diabetic patients for cardiovascular risk management). Furthermore, off-target effects such as the inhibition of carbonic anhydrase 2 have been identified, raising concerns about its safety profile. Nevertheless, its unique mechanism of action—directly blocking podocyte pyroptosis by targeting the TXNIP-NLRP3 axis—endows it with substantial translational value. In the future, strategies to overcome these barriers are expected to advance its clinical application: targeted delivery via nanocarriers (e.g., PLGA-PEG nanoparticles or nephrin antibody-conjugated systems) to enhance renal accumulation and podocyte specificity; precise patient stratification based on biomarkers such as serum IL-18 and renal TXNIP/NLRP3 expression to identify “inflammatory-phenotype” DN patients most likely to benefit; and combination therapy with sodium-glucose cotransporter 2 (SGLT2) inhibitors—whose metabolic benefits synergize with MCC950’s anti-inflammatory effects. These approaches hold great potential to break through clinical translation bottlenecks, offering a novel, precise anti-inflammatory treatment option for DN and addressing an unmet clinical need for therapies targeting the inflammatory underpinnings of the disease.

ObjectiveTo address the challenges of unstructured classical Chinese expressions， nested entity relationships， and limited annotated data in famous traditional Chinese medicine（TCM） case records， this study proposes a joint relation extraction framework that integrates data augmentation and entity mapping， aiming to support the construction of TCM diagnostic knowledge graphs and clinical pattern mining. MethodsWe developed an annotation structure for entities and their relationships in TCM case texts and applied a data augmentation strategy by incorporating multiple ancient texts to expand the relation extraction dataset. A cascade binary tagging framework for relation triple extraction（CasRel） model for TCM semantics was designed， integrating a pre-trained bidirectional encoder representations from transformers（BERT） layer for classical TCM texts to enhance semantic representation， and using a head entity-relation-tail entity mapping mechanism to address entity nesting and relation overlapping issues. ResultsExperimental results showed that the CasRel model， combining data augmentation and entity mapping， outperformed the pipeline-based Bert-Radical-Lexicon（BRL）-bidirectional long short-term memory（BiLSTM）-Attention model. The overall precision， recall， and F₁-score across 12 relation types reached 65.73%， 64.03%， and 64.87%， which represent improvements of 14.26%， 7.98%， and 11.21% compared to the BRL-BiLSTM-Attention model， respectively. Notably， the F₁-score for tongue syndrome relations increased by 22.68%（69.32%）， and the prescription-syndrome relations performed the best with the F₁-score of 70.10%. ConclusionThe proposed framework significantly improves the semantic representation and complex dependencies in TCM texts， offering a reusable technical framework for structured mining of TCM case records. The constructed knowledge graph can support clinical syndrome differentiation， prescription optimization， and drug compatibility， providing a methodological reference for TCM artificial intelligence research.

ObjectiveThe frequency difference limen (FDL) serves as a fundamental metric utilized for effectively quantifying the precise perceptual capabilities of the central auditory system. However, traditional measurement methods rely heavily on the active behavioral responses of subjects and are consequently highly susceptible to the negative influence of confounding subjective factors. Furthermore, existing research paradigms frequently employ uniform stimulus configurations that overlook critical individual perceptual differences. Based on brain-computer interface (BCI) technology, this comprehensive study aims to establish an objective and quantitative evaluation method for auditory frequency discrimination by systematically analyzing and decoding the specific neural responses elicited at the exact threshold state. MethodsWe designed a personalized rapid serial auditory presentation (RSAP) paradigm customized based on each individual’s precise FDL. A cohort of eleven healthy participants was recruited to evaluate the paradigm using pure-tone sequences at a baseline frequency of 4 000 Hz. This experimental paradigm simulates a realistic auditory perception environment through the continuous presentation of acoustic stimuli, thereby allowing for an in-depth investigation into the specific neural representations evoked by weak frequency deviations at the threshold state. Given that auditory stimulus-evoked response features exhibit complex and differentiated spatiotemporal distribution patterns across multiple frequency domains, this study further deeply integrates the cross-scale feature interaction module with the dynamic spatiotemporal attention allocation strategy, innovatively proposing the Multi-Scale Spatial-Temporal Dual Attention Network (MS-STAMNet). Specifically, the network constructs parallel processing branches with multiple receptive fields and introduces a dynamic adaptive weighting strategy to precisely localize core neural activity signals, further deeply integrating multi-scale information through cross-branch feature information interaction to achieve robust single-trial decoding of weak auditory evoked responses. ResultsThe comprehensive electrophysiological data analysis demonstrated that subtle auditory frequency deviation stimuli presented at the threshold level successfully elicited pronounced N2 and P3 event-related potential features, reflecting pre-attentive mismatch detection and subsequent cognitive evaluation, which were prominently distributed over the frontal, central, and temporal regions of the scalp. In the complex time-frequency domain, the extracted neural response characteristics exhibited distinct, statistically significant event-related synchronization within both the low-frequency δ and θ frequency bands, which was simultaneously accompanied by a widespread, prominent event-related desynchronization within the higher α band. A comparative analysis of model performance demonstrated that MS-STAMNet achieved an average unweighted average recall (UAR) of (69.67±6.12)% and area under the curve (AUC) of 0.761 8±0.07, significantly outperforming the established baseline models such as EEGNet and PLNet. Furthermore, a distinct dissociation phenomenon was verified between neural decoding and behavioral performance through regression analysis (R²=0.016, P=0.709), indicating that this model can effectively capture the implicit features of subtle frequency deviations, even when they fail to trigger explicit conscious responses. Additionally, attention weight visualization analysis further reveals the highly accurate focus of the network on key features concentrated over the bilateral temporal and fronto-parietal regions. ConclusionThis study systematically and comprehensively uncovers the multi-dimensional spatiotemporal evolutionary patterns of complex neural responses processing subtle acoustic variations under long-sequence threshold auditory stimulation. Concurrently, it verifies the efficacy and robustness of the proposed MS-STAMNet architecture in accurately deciphering weak, single-trial electroencephalogram signals amidst complex background noise. Ultimately, these neurophysiological and algorithmic findings lay a solid theoretical and methodological foundation for the objective and quantitative evaluation of individual auditory cognitive capabilities in clinical applications, transcending the fundamental limitations of traditional behavioral paradigms and providing robust technical support for future auditory research and related clinical assessments.

Objective To analyze the risk factors for increased drainage volume after open transforaminal lumbar interbody fusion(TLIF),and to establish a predictive model and then validate it.Methods The clinical data of 680 patients who underwent open TLIF at the General Hospital of Northern Theater Command from January 2016 to December 2019 were collected and the patients were randomly divided into the training group(n=476)and the validation group(n=204).Taking the predictive factors screened out by LASSO regression analysis as independent variables,a multivariate Logistic regression predictive model was constructed.The model was internally validated through the receiver operating characteristic(ROC)curve,Hosmer-Lemeshow goodness-of-fit test,and calibration curve,and its clinical utility was assessed via decision curve analysis(DCA).Results LASSO regression analysis screened out four predictive variables:age,number of surgical segments,operative duration,and intraoperative blood loss.The multivariate Logistic regression predictive model demonstrated that age≥60 years,number of surgical segments≥4,operative duration≥2 hours,and intraoperative blood loss≥200 mL were independent influencing factors for the increased postoperative drainage volume in patients undergoing TLIF(P<0.05).ROC curve analysis revealed an area under the curve(AUC)of 0.816(95%CI:0.798 to 0.867)in the training group and 0.783(95%CI:0.685 to 0.823)in the validation group,indicating that the predictive model had good discriminatory ability.Additionally,the Hosmer-Lemeshow goodness-of-fit test and calibration curve indicated that the predictive model had a good degree of fit,and the predicted probability was basically consistent with the actual probability,demonstrating a good calibration.The DCA results confirmed that this predictive model could be applied in clinical practice.Conclusion The risk factors for increased drainage volume after open TLIF include age,number of surgical segments,operative duration,and intraoperative blood loss.The predictive model established based on these factors demonstrates good performance,and it can be applied in clinical guidance for the selection of drainage tube removal time after TLIF.

Lyase acylation is a post-translational modification of proteins that plays a key role in cellular function,gene transcription and cellular metabolism.Meanwhile,lysine acylation is also involved in mul-tiple biological processes in life forms,and its abnormality may be associated with the occurrence and de-velopment of many diseases.Therefore,prediction of lysine acylation sites is important for the diagnosis and treatment of diseases.Although biomedical experiments can detect lysine acylation sites with high precision,they are costly and time-consuming.To address this problem,researchers have developed more convenient and efficient computational methods as an alternative to traditional biomedical experi-mental techniques.In this study,we developed a prediction model iKcr-RG based on a deep learning ap-proach,which employs a two-branching strategy using both ResNet and BiGRU to extract both local and global feature information from the original sequence encoding.To further improve the performance of the model,we innovatively designed a feature fusion method.After these optimizations,this study demon-strates stronger robustness and stability in unbalanced data.In the independent dataset results,specificity(Sp),sensitivity(Sn),accuracy(Acc)and Matthews correlation coefficient(MCC)were 0.8109,0.7902,0.7940,and 0.4978 respectively.The iKcr-RG model was better than existing prediction mod-els in predicting lysine acylation sites,and this study provides new ideas and methods for the application of deep learning in bioinformatics.

Objective To explore the relationship between serum thioredoxin 1(Trx1),programmed cell death factor 4(PDCD4),aquaporin 4(AQP4)expression and cognitive function in patients with Parkinson's disease(PD).Methods A total of 145 PD patients(PD group)were selected as the study subjects,and patients were divided into the cognition impairment(CI)group 43 cases and the no CI group(102 cases)according to the mini-mental state examination(MMSE).Another 105 healthy subjects in the same period were taken as the control group.General patient data were collected and analyzed.The serum expression of Trx1,PDCD4 and AQP4 were detected by ELISA.The correlation between serum levels of Trx1,PDCD4 and AQP4 in PD patients and CI score were analyzed by Pearson method.Multivariate Logistic regression was used to analyze influencing factors of CI in PD patients.The predictive values of serum Trx1,PDCD4 and AQP4 levels for the occurrence of CI in PD patients were analyzed by receiver operating characteristic(ROC)curve.Results Serum levels of Trx1 and AQP4 were lower in the PD group than those of the control group,and PDCD4 was higher in the PD group than that of the control group(P＜0.05).In the CI group,PD duration and PDCD4 levels were higher than those of the no CI group(P＜0.05),and BMI,years of education,MMSE score,MoCA score,Trx1 and AQP4 were lower than those in the no CI group(P＜0.05).In the PD group,serum Trx1 and AQP4 levels were positively correlated with MMSE and MoCA scores,and serum PDCD4 levels were negatively correlated with MMSE and MoCA scores(P＜0.05).The long course of disease and increased PDCD4 levels were risk factors for CI in PD patients,while increased Trx1 and AQP4 levels were protective factors for CI in PD patients(P＜0.05).Serum Trx1,PDCD4,AQP4 levels and the combined AUC for predicting CI in PD patients were 0.820,0.741,0.831 and 0.932,respectively,and the combined prediction was better than the respective prediction alone.Conclusion Serum Trx1,AQP4 and PDCD4 are closely related to cognitive function,and the combination of the three has high predictive value for CI in PD patients.

Objective:To explore the correlation between serum ferritin(SF)levels and the efficacy of platelet transfusion in patients with malignant hematological diseases.Methods:Patients with malignant hematological diseases who received repeated transfusions of apheresis platelets in Department of Hematology of Aerospace Center Hospital in 2023 were selected.The platelet corrected count increment(CCI)was used to evaluate the efficacy of platelet transfusion.The correlations between sex,age,disease type,transplantation history,red blood cell transfusion history,and SF level and the efficacy of platelet transfusion were analyzed.Results:A total of 87 patients were included,with a cumulative 326 person-times platelet transfusions.As suggested by one-way analysis of variance,compared with the patients in the age groups of 24-45 years old and 46-66 years old,the patients in the age group of 2-23 years old had a better efficacy of platelet transfusion(P=0.004,P=0.004).There was no significant difference in the efficacy of platelet transfusion between the patients in the age group of 24-45 years old and those in the age group of 46-66 years old(P=0.876).Compared with the patients who had a history of red blood cell transfusion within 3 days,the patients without a history of red blood cell transfusion within 3 days had a better efficacy of platelet transfusion(P＜0.001).Compared with the groups with SF levels of 1.44-2.78 ng/L and＞2.78 ng/L,the group with SF levels＜1.44 ng/L had a better efficacy of platelet transfusion(P=0.028,P＜0.001).Compared with the group with SF levels＞2.78 ng/L,the group with SF levels of 1.44-2.78 ng/L had a better efficacy of platelet transfusion(P=0.001).After adjusting for age and the history of red blood cell transfusion,the transfusion efficacy of the group with SF levels＜1.44 ng/L was better than that of the groups with SF levels of 1.44-2.78 ng/L and＞2.78 ng/L(P=0.021,P＜0.001);Compared with the group with SF levels＞2.78 ng/L,the group with SF levels of 1.44-2.78 ng/L had a better efficacy of platelet transfusion(P=0.001).Both univariate and multivariate linear regression models showed that SF levels were negatively correlated with the efficacy of platelet transfusion(P＜0.001).Conclusion:There is a negative correlation between SF levels and the efficacy of platelet transfusion in patients with malignant hematological diseases.Detection of SF levels may provide guidance for predicting the efficacy of platelet transfusion.