ObjectiveBased on whole-animal mass spectrometry imaging technology， spatial metabolomics was used to characterize in situ the metabolic alteration patterns in the lungs and brain of a rat model of lung heat-induced cough and asthma， as well as after treatment with Xiebai San. MethodsNine Sprague-Dawley （SD） rats were randomly divided into a blank group （physiological saline）， a model group （physiological saline）， and a Xiebai San group （9 g·kg^-1）， with three rats in each group. The model group and the Xiebai San group were both induced using lipopolysaccharide-ovalbumin （LPS-OVA） to establish an asthma rat model. After treatment with Xiebai San， the animals were euthanized on day 21 and rapidly frozen in liquid nitrogen to preserve morphology. Whole-animal tissue sections were prepared using a cryomicrotome， and imaging was performed using the Air-flow-assisted Desorption Electrospray Ionization Mass Spectrometry Imaging （AFADESI-MSI） platform. Based on the corresponding optical images， ion data of metabolites from the lung and brain tissues of each group were extracted. Differential metabolites were analyzed using SIMCA and GraphPad Prism 9.0 software. Metabolites were identified using the HMDB （https：//hmdb.ca/） and LipidMAPS^® （https：//www.lipidmaps.org/） databases， and metabolic changes in the lungs and brain were analyzed. ResultsMass spectrometry imaging showed that， after Xiebai San intervention， components such as neoglycyrrhizin and glycyrrhizin from Glycyrrhizae Radix et Rhizoma， as well as palmitamide from Lycii Cortex， were significantly distributed in the lung and brain tissues of rats. Lung analysis indicated that substances with anti-inflammatory effects， such as citric acid， were significantly decreased （P0.01）， while lipid metabolites such as lysophosphatidylethanolamine （LPE 17：1）， LPE （22：4）， and LPE （19：0） （P0.01） were significantly increased， showing a marked inflammatory response in the model group. After Xiebai San intervention， these conditions were notably improved. Analysis of metabolic changes in brain tissue showed that， compared with the blank group， amino acid and fatty acid metabolic pathways in the model group exhibited restricted alterations. Among them， levels of aspartic acid， glutamic acid， fatty acid （FA 18：5）， hydroxy fatty acids （FAHFA 36：0；O）， FA （6：1；O6）， and LPE （18：1） increased， whereas FA （16：0） and FA （20：4） significantly decreased. Administration of Xiebai San improved these metabolic abnormalities in the brain. Systematic analysis of lung and brain metabolic changes in rats with lung heat-induced cough and asthma showed that antioxidant unsaturated phospholipid substances were significantly decreased in the model group， suggesting oxidative stress and inflammation-related lung-brain axis responses after the onset of lung heat-induced cough and asthma. ConclusionUsing whole-animal mass spectrometry imaging combined with spatial metabolomics revealed the in vivo distribution of Xiebai San constituents， characterized the metabolic alterations in the lungs and brain caused by lung heat-induced cough and asthma， and systematically demonstrated the lung-brain axis inflammatory responses and the regulatory effects of Xiebai San. These findings provide valuable information for the study of Chinese medicine in lung heat-induced cough and asthma.

ObjectiveBased on whole-animal mass spectrometry imaging technology， spatial metabolomics was used to characterize in situ the metabolic alteration patterns in the lungs and brain of a rat model of lung heat-induced cough and asthma， as well as after treatment with Xiebai San. MethodsNine Sprague-Dawley （SD） rats were randomly divided into a blank group （physiological saline）， a model group （physiological saline）， and a Xiebai San group （9 g·kg^-1）， with three rats in each group. The model group and the Xiebai San group were both induced using lipopolysaccharide-ovalbumin （LPS-OVA） to establish an asthma rat model. After treatment with Xiebai San， the animals were euthanized on day 21 and rapidly frozen in liquid nitrogen to preserve morphology. Whole-animal tissue sections were prepared using a cryomicrotome， and imaging was performed using the Air-flow-assisted Desorption Electrospray Ionization Mass Spectrometry Imaging （AFADESI-MSI） platform. Based on the corresponding optical images， ion data of metabolites from the lung and brain tissues of each group were extracted. Differential metabolites were analyzed using SIMCA and GraphPad Prism 9.0 software. Metabolites were identified using the HMDB （https：//hmdb.ca/） and LipidMAPS^® （https：//www.lipidmaps.org/） databases， and metabolic changes in the lungs and brain were analyzed. ResultsMass spectrometry imaging showed that， after Xiebai San intervention， components such as neoglycyrrhizin and glycyrrhizin from Glycyrrhizae Radix et Rhizoma， as well as palmitamide from Lycii Cortex， were significantly distributed in the lung and brain tissues of rats. Lung analysis indicated that substances with anti-inflammatory effects， such as citric acid， were significantly decreased （P0.01）， while lipid metabolites such as lysophosphatidylethanolamine （LPE 17：1）， LPE （22：4）， and LPE （19：0） （P0.01） were significantly increased， showing a marked inflammatory response in the model group. After Xiebai San intervention， these conditions were notably improved. Analysis of metabolic changes in brain tissue showed that， compared with the blank group， amino acid and fatty acid metabolic pathways in the model group exhibited restricted alterations. Among them， levels of aspartic acid， glutamic acid， fatty acid （FA 18：5）， hydroxy fatty acids （FAHFA 36：0；O）， FA （6：1；O6）， and LPE （18：1） increased， whereas FA （16：0） and FA （20：4） significantly decreased. Administration of Xiebai San improved these metabolic abnormalities in the brain. Systematic analysis of lung and brain metabolic changes in rats with lung heat-induced cough and asthma showed that antioxidant unsaturated phospholipid substances were significantly decreased in the model group， suggesting oxidative stress and inflammation-related lung-brain axis responses after the onset of lung heat-induced cough and asthma. ConclusionUsing whole-animal mass spectrometry imaging combined with spatial metabolomics revealed the in vivo distribution of Xiebai San constituents， characterized the metabolic alterations in the lungs and brain caused by lung heat-induced cough and asthma， and systematically demonstrated the lung-brain axis inflammatory responses and the regulatory effects of Xiebai San. These findings provide valuable information for the study of Chinese medicine in lung heat-induced cough and asthma.

Objective: To explore the management of blood donors tested reactive to HCV in blood screening based on confirmation of HCV infection. Methods: Multiple HCV antibody assays, repeating HCV RNA testing, follow-up of blood donors and retesting of archive samples were performed to confirm HCV infection, identify infection status, and exclude false positives in blood donors reactive to HCV in blood screening. Results: From 2011 to 2024, the unqualified rate of HCV detection in blood screening was 2.45‰(2 751/1 122 026). Among these, anti-HCV+-&NAT-accounted for 1.85‰, followed by anti-HCV++ at 0.60‰. The proportion of anti-HCV+-&NAT-and HCV RNA yields was extremely low (0.007‰). The positive rate of anti-HCV+-&NAT-samples tested by electrochemiluminescence method (ELCIA) was approximately 7.5%, differing among reagents (P<0.05). The follow-up of anti-HCV+-&NAT-donors showed that 96.2% (202/210) were false positives, but 51.4% of donors remained anti-HCV+-&NAT-during follow-up. Among them, 8 donors (3.8%) could not be ruled out from HCV infection due to positive retesting by ELCIA. Of the anti-HCV+-&NAT-donors who were reactive at the first follow-up, 86.8% remained anti-HCV+-&NAT-at the second follow-up. The sampling confirmation data showed that all of 260 anti-HCV++ donors were confirmed as anti-HCV positive, and the proportion of false positives or missed detections by NAT was very low. Two occult HBV infections (OBIs) and one HBsAg carrier were identified among the 3 anti-HCV +-&NAT+ donors, and no HCV infection was confirmed in 5 anti-HCV--&HCV RNA + donors. Conclusion: The prevalence of HCV among blood donors in Dalian was about 0.06%, with extremely low proportion of window-period infection and slightly higher proportion of resolved infections than that of current infections. The majority of anti-HCV+-&NAT-were false positive. Blood donors confirmed as false positive should be qualified in blood screening 3 months later before next donation. In order to reduce the false positive results, it was advisable to avoid the same type of supplementary reagents as the initial reagents when performing confirmation.

Objective: To address systemic challenges in the blood system, such as supply-demand imbalance, inefficient allocation, and inappropriate clinical use, while bridging gaps in current theories regarding the integration of social mobilization, institutional practice, and policy coordination. It sought to construct a system dynamics model spanning from macro to micro levels to analyze the blood management system holistically. Methods: Key variables were identified by a systematic literature search in both Chinese and English databases. An improved Delphi method was then employed to conduct expert consultations across different fields, leading to the selection and determination of core variable sets for each sub-model. Furthermore, by defining their logical relationships, a system dynamics model was constructed to systematically analyze the operation mechanism of the blood management system. Results: Four core sub-models were developed: 1) A macro "Dynamic Balance" model quantifying regional supply-demand equilibrium and inventory control; 2) a mobilization "Three-Layer Funnel" model analyzing how socio-cultural factors, service channels, and policy incentives influence donation behavior; 3) an institutional "Dual-Cycle Regulation" model revealing hospital blood usage is driven by both disease burden (demand cycle) and management practices (regulation cycle); and 4) an individual "Three-Layer Filter" model standardizing clinical transfusion decisions based on necessity, risk-benefit, and context. These were integrated into a "Multi-Layer Linkage and Feedback" model, elucidating bidirectional interactions among five levels: policy environment, regional supply, blood station mobilization, hospital application, and clinical decision-making. Conclusion: This study constructed a system dynamics model for blood management. By defining key variables and their logical relationships, it systematically analyzes the system′s operational mechanism. The integrated framework connects multiple levels—regional supply, voluntary donation, hospital blood use, and clinical decision-making—revealing their intrinsic linkages. Future efforts should employ systems thinking to synergistically enhance supply-side mobilization, demand-side management, systemic regulation, and decision standardization to build a safe, efficient, and sustainable blood security system.

OBJECTIVE To establish a quality control method for Jinbei oral liquid based on multi-wavelength switching high performance liquid chromatography （HPLC） fingerprint， chemical pattern recognition and multi-index content determination. METHODS A total of 15 batches of Jinbei oral liquid were used as test samples. The Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine （ Version 2012 ） was adopted to establish multi-wavelength switching HPLC fingerprints， followed by chromatographic peak identification and similarity evaluation. Cluster analysis， principal component analysis and orthogonal partial least squares-discriminant analysis were applied to conduct chemical pattern recognition on the 15 batches of samples. The multi-wavelength switching HPLC method was used to simultaneously determine the contents of neochlorogenic acid， chlorogenic acid， cryptochlorogenic acid， forsythoside A， baicalin， salvianoli c acid B and wogonoside in samples. RESULTS A total of 25 common peaks were calibrated in the fingerprints of 15 batches of Jinbei oral liquid， among which 7 common peaks were unambiguously identified. The similarity of all samples was higher than 0.960. Chemical pattern recognition results showed that samples S1-S8 were clustered into group 1， and samples S9-S15 were clustered into group 2. Baicalin， wogonoside， neochlorogenic acid， chlorogenic acid and salvianolic acid B were identified as the differential quality markers. The average contents of neochlorogenic acid， chlorogenic acid， cryptochlorogenic acid， forsythoside A， baicalin， salvianolic acid B and wogonoside in 15 batches of Jinbei oral liquid were 0.213 7， 0.085 3， 0.104 9， 0.287 3， 0.420 1， 0.062 1， 0.176 0 mg/mL， respectively. CONCLUSIONS The established quality control method for Jinbei oral liquid combining multi-wavelength switching HPLC fingerprint， chemical pattern recognition and multi-index content determination is stable and reliable， which can provide a reference for the formulation of quality standards of this preparation.

OBJECTIVE To establish a quality control method for Jinbei oral liquid based on multi-wavelength switching high performance liquid chromatography （HPLC） fingerprint， chemical pattern recognition and multi-index content determination. METHODS A total of 15 batches of Jinbei oral liquid were used as test samples. The Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine （ Version 2012 ） was adopted to establish multi-wavelength switching HPLC fingerprints， followed by chromatographic peak identification and similarity evaluation. Cluster analysis， principal component analysis and orthogonal partial least squares-discriminant analysis were applied to conduct chemical pattern recognition on the 15 batches of samples. The multi-wavelength switching HPLC method was used to simultaneously determine the contents of neochlorogenic acid， chlorogenic acid， cryptochlorogenic acid， forsythoside A， baicalin， salvianoli c acid B and wogonoside in samples. RESULTS A total of 25 common peaks were calibrated in the fingerprints of 15 batches of Jinbei oral liquid， among which 7 common peaks were unambiguously identified. The similarity of all samples was higher than 0.960. Chemical pattern recognition results showed that samples S1-S8 were clustered into group 1， and samples S9-S15 were clustered into group 2. Baicalin， wogonoside， neochlorogenic acid， chlorogenic acid and salvianolic acid B were identified as the differential quality markers. The average contents of neochlorogenic acid， chlorogenic acid， cryptochlorogenic acid， forsythoside A， baicalin， salvianolic acid B and wogonoside in 15 batches of Jinbei oral liquid were 0.213 7， 0.085 3， 0.104 9， 0.287 3， 0.420 1， 0.062 1， 0.176 0 mg/mL， respectively. CONCLUSIONS The established quality control method for Jinbei oral liquid combining multi-wavelength switching HPLC fingerprint， chemical pattern recognition and multi-index content determination is stable and reliable， which can provide a reference for the formulation of quality standards of this preparation.

Type 2 diabetes mellitus (T2DM) is a highly prevalent chronic metabolic disease with an increasing incidence worldwide, that poses a significant risk to public health. In many current clinical practices for diabetes management, conventional Western treatments, including oral or injectable hypoglycemic agents, have serious side effects. Given that traditional Chinese medicine (TCM) is characterized by a multi-component, multi-target and multi-pathway approach, its combination with Western medicine could enhance efficacy and reduce adverse effects. Consequently, the use of TCM as a potential auxiliary or alternative treatment for the prevention and/or management of T2DM has emerged as a research hotspot. This article reviews existing reports on TCM in the treatment of T2DM and provides a detailed discussion of its applications. By integrating relevant clinical evidence, this review summarizes the clinical data on 23 TCM formulas and Chinese patent medicines, comprehensively describing their efficacy and potential pharmacological mechanisms in the treatment of T2DM. This includes an exploration of the impacts of TCM-based therapeutic interventions on T2DM-related microRNAs and their target genes. We hope this review not only offers new insights for future research directions but also enhances the understanding of the scientific value of TCM. Please cite this article as: Ni HX, Cao LH, Gong XX, Zang ZY, Chang H. Traditional Chinese medicine for treatment of type 2 diabetes mellitus: Clinical evidence and pharmacological mechanisms. J Integr Med. 2025; 23(6):605-622.
Humans ; Diabetes Mellitus, Type 2/drug therapy* ; Medicine, Chinese Traditional/methods* ; Drugs, Chinese Herbal/pharmacology* ; Hypoglycemic Agents/pharmacology*

Objective:To compare the impact of the AlignRT-based optical guidance method with the traditional marker line method on the accuracy of positioning, and explore the effect of patient′s different thoracic characteristic parameters on the precision of optical guidance positioning.Methods:A total of sixty breast cancer patients who received post breast-conserving radiotherapy at Anhui Cancer Hospital from July 2022 to September 2023 were retrospectively selected. Then these patients were equally divided into traditional cross hairs set-up (marker line group) and surface-guided set-up (SGRT group). The cone-beam CT scanning results were used as the gold standard, the three-dimensional set-up errors and the CTV-PTV target area external radiotherapy boundaries of two groups were studied comparatively. Multiple patient′s thoracic characteristic parameters were defined and the correction between each parameter and set-up error of SGRT was analyzed.Results:The mean value of three-dimensional set-up errors in the SGRT group and the marker line group was within 0.2 cm and 0.5 cm, respectively. The differences in three-dimensional set-up errors and total displacements between two groups were statistically significant ( z=-2.93, -3.21, -2.59, -4.76, P<0.05). The SGRT group reduced the CTV-PTV boundary from 0.5 cm of conventional marker line group to 0.3 cm. The thoracic aspect ratio H/W, the affected side pinch angle α1, and the healthy side pinch angle α2 were positively correlated with the x-direction posing error ( r=0.49, 0.59, 0.71, P<0.05); whereas, the affected side and the healthy side mammary gland heights D1 and D2 were negatively correlated with the z-direction posing error ( r=-0.46, -0.49, P<0.05). Conclusions:For breast-conserving postoperative radiotherapy patients, SGRT can obtain a more accurate radiotherapy set-up than the traditional marker line method, and can effectively reduce the target area externally expanded range. Meanwhile, the monitoring accuracy of SGRT is affected by the patient′s thoracic characteristic parameters, and clinical attention should be paid to breast-conserving radiotherapy patients with thick body shape, narrow body width, and small breast glands.

Nonunion of osteoporotic vertebral fractures (OVF), predominantly affecting the elderly, can lead to intractable pain, vertebral collapse, progressive kyphotic deformity, and neurological impairment, significantly compromising patients′ quality of life. There exists considerable debate on diagnosis and management of OVF, encompassing key issues such as clinical diagnosis and staging criteria for nonunion, surgical indications and procedure selection, and postoperative rehabilitation planning. Currently, there lacks standardized clinical guideline and expert consensus on the diagnosis and management of OVF nonunion in China. To address this gap, Minimally Invasive Surgery Group of Chinese Orthopedic Association, Osteoporosis Committee of Chinese Association of Orthopedic Surgeons, Prevention and Rehabilitation Committee for Osteoporosis of Chinese Association of Rehabilitation Medicine and Minimally Invasive Orthopedic Surgery Branch of China Association for Geriatric Care jointly organized domestic experts in spinal surgery, endocrinology, and rehabilitation to formulate the Clinical guideline for the diagnosis and treatment for nonunion of osteoporotic vertebral fractures ( version 2025), based on existing literature and clinical experience and adhering to principles of scientific rigor and practicality. The guideline provided 13 evidence-based recommendations encompassing diagnosis and treatment of OVF nonunion, aiming to standardize its clinical management.

Objective:To apply artificial intelligence（AI）in classifying ovarian tumors on ultrasound images，and compare the diagnostic results of several sonographers with varying seniority levels.Methods:A total of 645 patients diagnosed with adnexal masses via gynecological ultrasound examination at Qilu Hospital of Shandong University from January 2021 to December 2024 were enrolled. Three deep learning architectures，i.e.，Alexnet，Densenet121，and Resnet50 were developed and used to internally test the classification effectiveness of ovarian tumors，while the optimal model was selected for external testing. Two junior sonographers and two senior sonographers were recruited to independently diagnose ovarian tumors in the external test dataset. Subsequently，the benign and malignant results of the model's predictions were disclosed to each sonographer，and their revised diagnoses on the same external test data in combination with the best AI model were recorded.Results:The optimal model achieved an accuracy of 0.941，sensitivity of 0.936，and specificity of 0.944 on the internal test dataset，and maintained robust performance on the external test dataset with accuracy of 0.891，sensitivity of 0.880，and specificity of 0.907. Compared to junior sonographers，the optimal model demonstrated significantly higher sensitivity in discriminating benign from malignant ovarian tumors（0.880 vs. 0.723，0.602；all P<0.05）. No statistically significant difference was observed in diagnostic accuracy between the optimal model and senior sonographer 1（ P=0.05）. With assistance from the optimal model，junior sonographers achieved significant improvements in both sensitivity and specificity（sensitivity：0.723 vs. 0.843，0.602 vs. 0.819；specificity：0.778 vs. 0.833，0.685 vs. 0.741；all P<0.05）. Conclusions:The optimal model achieves comparable performance to that of senior sonographers in ovarian tumor classification. With model assistance，the diagnostic performance of junior sonographers is significantly improved.