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 explore the mechanism by which Buyang Huanwutang regulates the glutathione peroxidase 4 （GPX4）-acyl-CoA synthetase long-chain family member 4 （ACSL4） axis to inhibit ferroptosis and promote neurological functional recovery after spinal cord injury （SCI）. MethodsNinety rats were randomly divided into five groups： sham operation group， model group， low-dose Buyang Huanwutang group （12.5 g·kg^-1）， high-dose Buyang Huanwutang group （25 g·kg^-1）， and Buyang Huanwutang + inhibitor group （25 g·kg^-1 + 5 g·kg^-1 RSL3）. The SCI model was established by using the allen method. Tissue was collected on the 7th and 28th days after operation. Motor function was assessed by using the Basso-Beattie-Bresnahan （BBB） scale. Hematoxylin-eosin （HE）， Nissl， and Luxol fast blue （LFB） staining were performed to observe spinal cord histopathology. Transmission electron microscopy was used to examine mitochondrial ultrastructure. Immunofluorescence staining was used to detect the number of NeuN-positive cells and the fluorescence intensity of myelin basic protein （MBP）， GPX4， and ACSL4. Real-time fluorescent quantitative polymerase chain reaction （Real-time PCR） was used to analyze the mRNA expression of GPX4 and ACSL4. Enzyme linked immunosorbent assay （ELISA） was performed to measure the levels of reactive oxygen species （ROS）， malondialdehyde （MDA）， glutathione （GSH）， and superoxide dismutase （SOD）. Colorimetric assays were used to determine the iron content in spinal cord tissue. ResultsCompared to the sham operation group， the model group exhibited significantly reduced BBB scores （P<0.01）， severe pathological damage in spinal cord tissue， and marked mitochondrial ultrastructural disruption. In addition， the model group showed a decrease in the number of NeuN-positive cells （P<0.01）， reduced fluorescence intensity of MBP and GPX4 （P<0.01）， lower levels of GSH and SOD （P<0.01）， and downregulated mRNA expression of GPX4 （P<0.01）. Moreover， compared to the sham operation group， the model group had elevated levels of ROS， MDA， and tissue iron content （P<0.01）， along with increased fluorescence intensity and mRNA expression of ACSL4 （P<0.01）. Compared with the model group and Buyang Huanwutang + inhibitor group， the Buyang Huanwutang group showed significantly improved BBB scores （P<0.05， P<0.01） and exhibited less severe spinal cord tissue damage， reduced edema and inflammatory cell infiltration， increased neuronal survival， and more intact myelin structures. Additionally， mitochondrial ultrastructure was significantly improved in the Buyang Huanwutang group. Compared to the model group and Buyang Huanwutang + inhibitor group， the Buyang Huanwutang group significantly increased the number of NeuN-positive cells and the fluorescence intensity of MBP （P<0.05， P<0.01）. Furthermore， Buyang Huanwutang significantly increased the fluorescence intensity and mRNA expression of GPX4 （P<0.01） and decreased the fluorescence intensity and mRNA expression of ACSL4 （P<0.01） compared to the model group and Buyang Huanwutang + inhibitor group. Finally， the Buyang Huanwutang group significantly decreased ROS， MDA， and tissue iron content （P<0.01） and significantly increased GSH and SOD levels （P<0.01） compared to the model group and Buyang Huanwutang + inhibitor group. ConclusionBuyang Huanwutang inhibits ferroptosis through the GPX4/ACSL4 axis， reduces secondary neuronal and myelin injury and oxidative stress， and ultimately promotes the recovery of neurological function.

Background/Aims: Early detection and effective prognosis prediction in patients with hepatocellular carcinoma (HCC) provide an avenue for survival improvement, yet more effective approaches are greatly needed. We sought to develop the detection and prognosis models with ultra-sensitivity and low cost based on fragmentomic features of circulating cell free mtDNA (ccf-mtDNA). Methods: Capture-based mtDNA sequencing was carried out in plasma cell-free DNA samples from 1168 participants, including 571 patients with HCC, 301 patients with chronic hepatitis B or liver cirrhosis (CHB/LC) and 296 healthy controls (HC). Results: The systematic analysis revealed significantly aberrant fragmentomic features of ccf-mtDNA in HCC group when compared with CHB/LC and HC groups. Moreover, we constructed a random forest algorithm-based HCC detection model by utilizing ccf-mtDNA fragmentomic features. Both internal and two external validation cohorts demonstrated the excellent capacity of our model in distinguishing early HCC patients from HC and highrisk population with CHB/LC, with AUC exceeding 0.983 and 0.981, sensitivity over 89.6% and 89.61%, and specificity over 98.20% and 95.00%, respectively, greatly surpassing the performance of alpha-fetoprotein (AFP) and mtDNA copy number. We also developed an HCC prognosis prediction model by LASSO-Cox regression to select 20 fragmentomic features, which exhibited exceptional ability in predicting 1-year, 2-year and 3-year survival (AUC=0.8333, 0.8145 and 0.7958 for validation cohort, respectively). Conclusions We have developed and validated a high-performing and low-cost approach in a large clinical cohort based on aberrant ccf-mtDNA fragmentomic features with promising clinical translational application for the early detection and prognosis prediction of HCC patients.

Pulmonary sarcoidosis is an immune system disease with an unclear etiology. Guided by the yang-reinforcing method， it is believed that the fundamental pathogenesis of pulmonary sarcoidosis lies in the disharmony between water and fire and the reckless movement of the ministerial fire. The failure of the spleen and stomach to maintain warmth， leading to the production of phlegm and blood stasis， is an important pathogenesis. The invasion of external pathogenic toxins， deeply penetrating into the interior， is considered a triggering factor for the disease. The treatment focuses on supplementing the yang， consolidating the kidney， drawing fire back to its source， warming the yang， benefiting the kidney， and nourishing the spleen to generate metal. It also emphasizes unblocking the yang， transforming turbidity， and eliminating phlegm and blood stasis.

Background/Aims: Early detection and effective prognosis prediction in patients with hepatocellular carcinoma (HCC) provide an avenue for survival improvement, yet more effective approaches are greatly needed. We sought to develop the detection and prognosis models with ultra-sensitivity and low cost based on fragmentomic features of circulating cell free mtDNA (ccf-mtDNA). Methods: Capture-based mtDNA sequencing was carried out in plasma cell-free DNA samples from 1168 participants, including 571 patients with HCC, 301 patients with chronic hepatitis B or liver cirrhosis (CHB/LC) and 296 healthy controls (HC). Results: The systematic analysis revealed significantly aberrant fragmentomic features of ccf-mtDNA in HCC group when compared with CHB/LC and HC groups. Moreover, we constructed a random forest algorithm-based HCC detection model by utilizing ccf-mtDNA fragmentomic features. Both internal and two external validation cohorts demonstrated the excellent capacity of our model in distinguishing early HCC patients from HC and highrisk population with CHB/LC, with AUC exceeding 0.983 and 0.981, sensitivity over 89.6% and 89.61%, and specificity over 98.20% and 95.00%, respectively, greatly surpassing the performance of alpha-fetoprotein (AFP) and mtDNA copy number. We also developed an HCC prognosis prediction model by LASSO-Cox regression to select 20 fragmentomic features, which exhibited exceptional ability in predicting 1-year, 2-year and 3-year survival (AUC=0.8333, 0.8145 and 0.7958 for validation cohort, respectively). Conclusions We have developed and validated a high-performing and low-cost approach in a large clinical cohort based on aberrant ccf-mtDNA fragmentomic features with promising clinical translational application for the early detection and prognosis prediction of HCC patients.

Background/Aims: Early detection and effective prognosis prediction in patients with hepatocellular carcinoma (HCC) provide an avenue for survival improvement, yet more effective approaches are greatly needed. We sought to develop the detection and prognosis models with ultra-sensitivity and low cost based on fragmentomic features of circulating cell free mtDNA (ccf-mtDNA). Methods: Capture-based mtDNA sequencing was carried out in plasma cell-free DNA samples from 1168 participants, including 571 patients with HCC, 301 patients with chronic hepatitis B or liver cirrhosis (CHB/LC) and 296 healthy controls (HC). Results: The systematic analysis revealed significantly aberrant fragmentomic features of ccf-mtDNA in HCC group when compared with CHB/LC and HC groups. Moreover, we constructed a random forest algorithm-based HCC detection model by utilizing ccf-mtDNA fragmentomic features. Both internal and two external validation cohorts demonstrated the excellent capacity of our model in distinguishing early HCC patients from HC and highrisk population with CHB/LC, with AUC exceeding 0.983 and 0.981, sensitivity over 89.6% and 89.61%, and specificity over 98.20% and 95.00%, respectively, greatly surpassing the performance of alpha-fetoprotein (AFP) and mtDNA copy number. We also developed an HCC prognosis prediction model by LASSO-Cox regression to select 20 fragmentomic features, which exhibited exceptional ability in predicting 1-year, 2-year and 3-year survival (AUC=0.8333, 0.8145 and 0.7958 for validation cohort, respectively). Conclusions We have developed and validated a high-performing and low-cost approach in a large clinical cohort based on aberrant ccf-mtDNA fragmentomic features with promising clinical translational application for the early detection and prognosis prediction of HCC patients.