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.

Electroencephalogram (EEG) is a non-invasive, high temporal-resolution technique for monitoring brain activity. However, affected by the volume conduction effect, EEG has a low spatial resolution and is difficult to locate brain neuronal activity precisely. The surface Laplacian (SL) technique obtains the Laplacian EEG (LEEG) by estimating the second-order spatial derivative of the scalp potential. LEEG can reflect the radial current activity under the scalp, with positive values indicating current flow from the brain to the scalp (“source”) and negative values indicating current flow from the scalp to the brain (“sink”). It attenuates signals from volume conduction, effectively improving the spatial resolution of EEG, and is expected to contribute to breakthroughs in neural engineering. This paper provides a systematic overview of the principles and development of SL technology. Currently, there are two implementation paths for SL technology: current source density algorithms (CSD) and concentric ring electrodes (CRE). CSD performs the Laplace transform of the EEG signals acquired by conventional disc electrodes to indirectly estimate the LEEG. It can be mainly classified into local methods, global methods, and realistic Laplacian methods. The global method is the most commonly used approach in CSD, which can achieve more accurate estimation compared with the local method, and it does not require additional imaging equipment compared with the realistic Laplacian method. CRE employs new concentric ring electrodes instead of the traditional disc electrodes, and measures the LEEG directly by differential acquisition of the multi-ring signals. Depending on the structure, it can be divided into bipolar CRE, quasi-bipolar CRE, tripolar CRE, and multi-pole CRE. The tripolar CRE is widely used due to its optimal detection performance. While ensuring the quality of signal acquisition, the complexity of its preamplifier is relatively acceptable. Here, this paper introduces the study of the SL technique in resting rhythms, visual-related potentials, movement-related potentials, and sensorimotor rhythms. These studies demonstrate that SL technology can improve signal quality and enhance signal characteristics, confirming its potential applications in neuroscientific research, disease diagnosis, visual pathway detection, and brain-computer interfaces. CSD is frequently utilized in applications such as neuroscientific research and disease detection, where high-precision estimation of LEEG is required. And CRE tends to be used in brain-computer interfaces, that have stringent requirements for real-time data processing. Finally, this paper summarizes the strengths and weaknesses of SL technology and envisages its future development. SL technology boasts advantages such as reference independence, high spatial resolution, high temporal resolution, enhanced source connectivity analysis, and noise suppression. However, it also has shortcomings that can be further improved. Theoretically, simulation experiments should be conducted to investigate the theoretical characteristics of SL technology. For CSD methods, the algorithm needs to be optimized to improve the precision of LEEG estimation, reduce dependence on the number of channels, and decrease computational complexity and time consumption. For CRE methods, the electrodes need to be designed with appropriate structures and sizes, and the low-noise, high common-mode rejection ratio preamplifier should be developed. We hope that this paper can promote the in-depth research and wide application of SL technology.

Objective To compare and find an optimal model for predicting the risk of DKD occurrence in patients with type 2 diabetes mellitus(T2DM).Methods A total of 2005 patients with T2DM were enrolled in this study from The Second Hospital of Shijiazhuang City during December 2017 to December 2022.All the subjects were divided into a training set(n=1403)and a validation set(n=602)according to the ratio of 3∶1 by simple random sampling.With the occurrence of DKD as the outcome variablein the training set,important feature variables were screened by LASSO regression.Six different machine learning models were established according to the feature variables,thenthe optimal model was determined by comparison,and anonlinerisk predictor for DKD occurrence was constructed in patients with T2DM.Results Taking the occurrence of DKD as the outcome variable in the training set,the results of LASSO regression analysis showed that the optimal value of the model was 10-fold cross validation lambda.1se=0.01662473,and 15 characteristic variables with nonzero coefficient were screened out to be related to the occurrence of DKD.The data included sex,age,family history of DM,DM duration,LDL-C,HbA1c,WBC,PDW,Scr,urine α1-microglobulin,urine β2-microglobulin,urine microalbumin,hypertension,hypokalemia,and DR.In the training set and validation set,the prediction performance of XGBoost model was better than that of other models(AUC=0.872,0.893,95%CI 0.853～0.891,0.865～0.921),the sensitivity was 0.779,0.863,and the specificity was 0.721,0.758,respectively.The F1 scores were 0.774 and 0.787.DCA analysis showed that the XGBoost model had a greater net benefit and threshold probability.According to the XGBoost model,the online predictor of DKD risk in T2DM patients was laid out,and two patients were selected for application,the results showed that the predictive value of the model was 0.185 in non-DKD patients,and the predictive value was 0.510 in DKD patients.Conclusions The XGBoost model is the best model for predicting the occurrence of DKD in T2DM patients,and an online predictor was successfully built.

Objective:To explore the effect of social cognition and interaction training (SCIT) combined with transcranial magnetic stimulation (TMS) on intrinsic motivation and social cognition in patients with schizophrenia.Methods:Forty-two stable schizophrenia patients were randomly divided into the SCIT + TMS group( n=22) and the SCIT group( n=20). All the subjects received 20 sessions of SCIT treatment, and the SCIT+ TMS group simultaneously received 15 sessions of intermittent theta burst stimulation(iTBS) over the left dorsolateral prefrontal cortex(DLPFC). All the subjects were assessed by intrinsic motivation inventory for schizophrenia research(IMI-SR), Chinese version of the ambiguous intentions hostility questionnaire(AIHQ-C), theory of mind-picture sequencing task(ToM-PST), mentalization scale (MentS), Chinese version of interpersonal reactivity index (IRI-C) and positive and negative syndrome scale (PANSS) before and after intervention. SPSS 26.0 software was used for data analysis.Wilcoxon signed-rank test was used for intra-group comparison before and after treatment, while Mann-Whitney U test and covariance analysis were used for inter-group comparison.Spearman correlation analysis and Logistic regression analyses were used to explore the association between the intrinsic motivation and social cognition. Results:There were no significant differences on IMI-SR scores before and after treatment between the two groups(all P>0.05). In the SCIT+ TMS group, the total score of hostility bias (HB), HB scores in ambiguous scenes, HB scores in intentional scenes, and aggressive bias (AB) scores in ambiguous scenes of AIHQ-C scale after treatment were lower than those befor treatment( Z=-2.044--3.112, all P<0.05), while the total score of ToM-PST(18.50(16.00, 21.00) vs 15.50(11.75, 18.00), Z=-2.598, P=0.009) and IRI-C imagination score (12.18±3.79, 14.41±4.73, t=-2.694, P=0.014) were higher than those before treatment.In the SCIT group, the total score of ToM-PST after treatment was higher than that before treatment(21.00(20.00, 22.00) vs 17.00(14.50, 20.75), Z=-2.518, P=0.012).There was no significant statistical difference in MentS scores between after treatment and before treatment ( P>0.05). The difference in AIHQ-C intentional scenario AB score before and after treatment was higher in the SCIT+ TMS group than in the SCIT group ( Z=-1.996, P=0.046), while there was no statistically significant difference in the difference before and after treatment in social cognitive scores between the two groups (all P>0.05).In the combined two samples, Spearman correlation analysis showed that the total score of IMI-SR before treatment was positively correlated with the primary belief score of ToM-PST understanding, reciprocity score, MentS total score, other person mentalization score, motivation mentalization score, IRI-C total score, viewpoint taking score, and empathy concern score after treatment( r=0.341-0.509, all P<0.05), while negatively correlated with AIHQ-C total score and factor scores ( r=-0.434--0.645, P<0.05).Logistic regression analysis showed that the total score of IMI-SR had negative impact on AIHQ-C total HB score( B=-0.047, OR=0.954, 95% CI=0.917-0.993).The value score had a positive impact on the total score of MentS ( B=0.143, OR=1.154, 95% CI=1.043-1.277), other person mentalization score( B=0.166, OR=1.181, 95% CI=1.058-1.318), motivation mentalization score( B=0.111, OR=1.117, 95% CI=1.021-1.223), IRI-C total score ( B=0.138, OR=1.148, 95% CI=1.038-1.270), and viewpoint taking score( B=0.194, OR=1.214, 95% CI=1.076-1.369). Interest score had a positive impact on IRI-C empathy concern score ( B=0.098, OR=1.103, 95% CI=0.998-1.218) and ToM-PST understanding primary belief score( B=0.130, OR=1.138, 95% CI=1.010-1.283) and reciprocity score( B=0.189, OR=1.208, 95% CI=1.057-1.380). Conclusion:The research results did not confirm the effect of TMS over the DLPFC on enhancing intrinsic motivation, as well as the synergistic effect of SCIT treatment on social cognition. But the correlation results indicates that improving schizophrenia patients' intrinsic motivation level in cognitive training is meaningful for promoting social cognition.

Objective To compare and find an optimal model for predicting the risk of DKD occurrence in patients with type 2 diabetes mellitus(T2DM).Methods A total of 2005 patients with T2DM were enrolled in this study from The Second Hospital of Shijiazhuang City during December 2017 to December 2022.All the subjects were divided into a training set(n=1403)and a validation set(n=602)according to the ratio of 3∶1 by simple random sampling.With the occurrence of DKD as the outcome variablein the training set,important feature variables were screened by LASSO regression.Six different machine learning models were established according to the feature variables,thenthe optimal model was determined by comparison,and anonlinerisk predictor for DKD occurrence was constructed in patients with T2DM.Results Taking the occurrence of DKD as the outcome variable in the training set,the results of LASSO regression analysis showed that the optimal value of the model was 10-fold cross validation lambda.1se=0.01662473,and 15 characteristic variables with nonzero coefficient were screened out to be related to the occurrence of DKD.The data included sex,age,family history of DM,DM duration,LDL-C,HbA1c,WBC,PDW,Scr,urine α1-microglobulin,urine β2-microglobulin,urine microalbumin,hypertension,hypokalemia,and DR.In the training set and validation set,the prediction performance of XGBoost model was better than that of other models(AUC=0.872,0.893,95%CI 0.853～0.891,0.865～0.921),the sensitivity was 0.779,0.863,and the specificity was 0.721,0.758,respectively.The F1 scores were 0.774 and 0.787.DCA analysis showed that the XGBoost model had a greater net benefit and threshold probability.According to the XGBoost model,the online predictor of DKD risk in T2DM patients was laid out,and two patients were selected for application,the results showed that the predictive value of the model was 0.185 in non-DKD patients,and the predictive value was 0.510 in DKD patients.Conclusions The XGBoost model is the best model for predicting the occurrence of DKD in T2DM patients,and an online predictor was successfully built.

Objective:To observe the early clinical efficacy of 3D-printed modular supporting prosthesis for reconstruction of lacunar bone defect caused by giant cell tumor of the distal femur.Methods:From May 2018 to July 2023, a total of 9 patients with giant cell tumor of the distal femur were treated with 3D-printed modular supporting prosthesis to reconstruct lacunar bone defects in the Department of Orthopedics, West China Hospital, Sichuan University. There were 4 males and 5 females, aged 30.8±6.1 years (range, 24-44 years), 5 cases on the left side, 4 cases on the right side, 2 cases of Campanacci grade I, 7 cases of Campanacci grade II. The anteroposterior and lateral X-ray films and T-SMART tomosynthesis imaging of the knee joint were taken to observe the bone graft healing and osseointegration after operation. Musculoskeletal Tumor Society (MSTS)-93 was used to evaluate knee function, and visual analogue scale (VAS) was used to evaluate knee pain.Results:All patients were successfully operated and followed up for an average of 30.8±7.5 months (range, 18-42 months). The operation time was 124.2±23.6 min, and the intraoperative blood loss was 105.6±17.4 ml. All autografts showed bony union at the graft-host junction, and the healing time was 3.3±0.4 months (range, 3.0-4.0 months). At 6 months after surgery, T-SMART tomosynthesis imaging showed that the gap between the prosthesis-bone interface was less than 1 mm in all patients. At the last follow-up, the thickness of residual subchondral bone was 5.7±1.3 mm, which was greater than that before operation 2.2±0.8 mm, and the difference was statistically significant ( t=10.823, P<0.001). At the last follow-up, the score of MSTS-93 was 26.7±2.4, which was higher than that before operation 18.8±3.7, and the difference was statistically significant ( t=5.367, P<0.001). At the last follow-up, the range of motion of the knee joint was 122.8°±9.1°, which was higher than that before operation 108.3°±6.1°, and the difference was statistically significant ( t=3.970, P<0.001). All patients were able to walk normally, go up and down stairs and other daily activities, and 7 patients were able to complete squats. At the last follow-up, there was no local tumor recurrence, distant metastasis, death, joint infection, pain (VAS score was 0), delayed wound healing, joint degeneration, prosthesis loosening or articular surface collapse. Conclusion:Reconstruction of lacunar bone defect caused by giant cell tumor of distal femur with 3D-printed modular supporting prosthesis can effectively improve knee joint function and osseointegration, and the short-term clinical results are satisfactory.

The medulla oblongata,situated at the caudal portion of the brainstem,serves as a critical regulatory center responsible for maintaining fundamental vital functions including respiratory and cardiovascular homeostasis.As a pivotal hub within the autonomic nervous system,it orchestrates the coordinated control of afferent and efferent neural pathways.Dysfunction of this region may precipitate life-threatening cardiorespiratory arrest,associated with substantial mortality rates.This case report presents a patient who developed acute extensive anterior myocardial infarction during treatment with dual antiplatelet therapy and moderate-intensity statins following acute medullary infarction.It is hypothesized that the pathogenesis may involve the acceleration of plaque erosion by the stroke-heart syndrome.This clinical case provides valuable insights into the complex neurocardiac interplay,particularly highlighting the imperative for enhanced recognition of brain-heart axis interactions in cerebrovascular pathology.

Objective To explore its application value of LNM in patients with gastric adenocarcinoma based on the construction of a radiomic nomogram prediction model for preoperative lymph node metastasis in gastric adenocarcinoma using enhanced CT imaging features and parameters.Methods 131 patients with gastric adenocarcinoma who underwent radical gastric cancer surgery(Billroth Ⅱ)+lymph node dissection in our hospital from August 2019 to October 2023 were retrospectively analysed,and the preoperative enhancement CT extracted lesions,histological features of lymph node images,and pathological examination of LNM were recorded respectively,and the statistically significant Enhanced CT image histological features and parameters,multifactorial logistic regression to analyse the independent risk factors of gastric adenocarcinoma LNM(+)and construct a column-line diagram,and evaluate its performance.The performance and clinical value of the prediction model were evaluated using subject work characteristic(ROC)curves,and the column-line diagram was internally validated.Results The results of univariate analysis showed that the maximum diameter of the tumour,the lymph node status,the short-axis length and volume of the largest lymph node in the lymph node group and the sum of the short-axis lengths of all the lymph nodes were associated with the occurrence of LNM,and the difference was statistically significant(P＜0.05);multifactorial logistic regression analysis suggested that the maximum diameter of the tumour was ≥15 mm and the lymph node status was positive in the enhanced CT imaging examination,maximum lymph node short-axis length ≥ 7 mm in the lymph node group,the sum of short-axis lengths of all lymph nodes ≥ 11 mm,and the maximum lymph node short-axis volume ≥ 300 mm3 in the lymph node group were the independent risk factors for gastric adenocarcinoma patients with LNM(+)(P＜0.05);the area under the curve of the model was plotted using a ROC curve with an AUC=0.816(95％ CI 0.810-0.939),with the sensitivity of 0.91 and the specificity of 0.86.Model validation was performed using the BOOTSTRAP method containing 500 resamples,and the results suggested that the differences between the fitted curves and the ideal curves of the constructed column-line graphical model were not significant,and the validity and reliability were good.Conclusion The radiomic nomogram prediction model based on enhanced CT imaging features and parameters can effectively predict preoperative lymph node metastasis in gastric adenocarcinoma,providing strong support for clinical decision-making in gastric adenocarcinoma patients.

In the field of substance detection,ion dissociation techniques have become crucial for enhancing qualitative accuracy.By applying external energy to induce dissociation of ions in the substance being analyzed,the internal structural information can be obtained,thereby improving qualitative capabilities.Current research on ion dissociation techniques primarily focuses on tandem mass spectrometry,which typically requires a vacuum environment.However,research on ambient ion dissociation techniques is less developed,with some progress made in the field of tandem ion mobility spectrometry.Recently,the development of field-induced dissociation(FID)in this area has enabled ambient dissociation of various explosive and volatile alcohol ions.Nevertheless,the limitation imposed by the maximum breakdown field of air restricts the energy of the electric field,making it challenging to dissociate ions with high energy requirements,such as those of drugs.To address this issue,in this work,an ambient heat-induced dissociation(HID)technique based on high temperatures was proposed,in which an ambient ion heat-induced dissociation unit was developed and integrated into a home-made ion trap mass spectrometer.Experiments were conducted on four representative drug samples,e.g.methamphetamine,heroin,cocaine,and ketamine.The parent ions mass spectra,low vacuum collision-induced dissociation(CID)mass spectra and ambient HID mass spectra for each sample were obtained.By analyzing and comparing the fragmentation products from ambient and low vacuum dissociation,the feasibility of the ambient HID technique was verified.This technique provided a method for ion dissociation in single mass analyzers without tandem mass spectrometry capability and offered a new research direction for the future development of tandem ion mobility spectrometry.

Objective To target at the NKG2A-HLA-E inhibitory axis,a pluripotent stem cell(iPSC)-derived geneti-cally engineered natural killer cells(NK cells)with NKG2A knockout(NKG2A KO-iNK)were prepared and then their tumor-killing efficacy was evaluated in vitro.Methods NKG2A was knocked out in iPSCs using gene-editing technology.These cells were then differentiated into NKG2A KO-iNK cells.Surface markers at each differentiation stage were analyzed by flow cytometry.Western blot confirmed NKG2A knockout,and flow cytometry assessed expres-sion of activating receptors(NKG2D)and natural cytotoxicity receptors(NKp30,NKp44,NKp46)in NKG2A KO-iNK cells.Cytotoxic activity against tumor cell lines with varying human leukocyte antigen E(HLA-E)expression level was evaluated via lactate dehydrogenase(LDH)release assay.Results Co-transfection of iPSCs with Cas9 pro-tein and three small-guide RNAs(sgRNAs)targeting at exons 1 and 2 of the KLRC1 gene(encoding NKG2A)suc-cessfully generated monoclonal NKG2A-knockout iPSCs(NKG2A KO-iPSCs)with a single T-base insertion in exon 1.During iPSC differentiation into NK cells,CD34 expression reached 30％-50％at the embryoid body(EB)stage(day 8),while CD56 and CD 16 expression exceeded 80％by day 28.Western blot confirmed complete NKG2A knockout in NKG2A KO-iNK cells.Flow cytometry revealed comparable expression level of activating receptor NKG2D and cytotox-icity receptors(NKp30,NKp44,NKp46)between NKG2A KO-iNK and wild-type iNK(WT-iNK)cells.The LDH assay results indicated that the cytotoxic activity of NKG2A KO-iNK cells against the HLA-E highly-expressed B-cell precursor leukemia cell line Nalm6 cells was significantly higher than that of WT-iNK cells,while there was no signif-icant difference between them and human myeloma cell line H929 cells with low HLA-E expression and human hepa-tocellular carcinoma cell line HepG2 cells with almost no HLA-E expression.Interferon-γ(IFN-γ)pretreatment up regulated HLA-E expression in Nalm6 cells,further amplifying NKG2A KO-iNK-mediated cytotoxicity.Conclusions By disrupting the NKG2A-HLA-E inhibitory axis,NKG2A KO-iNK cells exhibit markedly enhanced in vitro cytotoxic-ity against HLA-E-high tumor cells.This result highlights their potential function as a novel adoptive cell therapy strategy for cancers reliant on HLA-E-mediated immune evasion.