Fluid shear stress-mediated Piezo1 alleviates osteocyte apoptosis by activating the PI3K/Akt pathway.

Glucocorticoid-induced osteoporosis serves as a primary cause for secondary osteoporosis and fragility fractures, representing the most prevalent adverse reaction associated with prolonged glucocorticoid use. In this study, to elucidate the impact and underlying mechanisms of fluid shear stress (FSS)-mediated Piezo1 on dexamethasone (Dex)-induced apoptosis, we respectively applied Dex treatment for 6 h, FSS at 9 dyne/cm2 for 30 min, Yoda1 treatment for 2 h, and Piezo1 siRNA transfection to intervene in MLO-Y4 osteocytes. Western blot analysis was used to assess the expression of Cleaved Caspase-3, Bax, Bcl-2, and proteins associated with the PI3K/Akt pathway. Additionally, qRT-PCR was utilized to quantify the mRNA expression levels of these molecules. Hoechst 33258 staining and flow cytometry were utilized to evaluate the apoptosis levels. The results indicate that FSS at 9 dyne/cm2 for 30 min significantly upregulates Piezo1 in osteocytes. Following Dex-induced apoptosis, the phosphorylation levels of PI3K and Akt are markedly suppressed. FSS-mediated Piezo1 exerts a protective effect against Dex-induced apoptosis by activating the PI3K/Akt pathway. Additionally, downregulating the expression of Piezo1 in osteocytes using siRNA exacerbates Dex-induced apoptosis. To further demonstrate the role of the PI3K/Akt signaling pathway, after intervention with the PI3K pathway inhibitor, the activation of the PI3K/Akt pathway by FSS-mediated Piezo1 in osteocytes was significantly inhibited, reversing the anti-apoptotic effect. This study indicates that under FSS, Piezo1 in MLO-Y4 osteocytes is significantly upregulated, providing protection against Dex-induced apoptosis through the activation of the PI3K/Akt pathway.

Flexible Self-Powered Energy Systems Based on H2 O/Ni2+ Intercalated Nix V2 O5 ⋠nH2 O.

The development of portable electronic devices has created greater demands for multifunctional energy integration systems. Self-powered systems have gained widespread interest because they can collect and storage renewable environmental energy and provide stable electricity to electronic devices. Herein, we developed a flexible self-charging energy system, involving textile-based zinc-ion hybrid (ZIHC) and triboelectric nanogenerator (TENG), which demonstrates wearable, compatibility, lightweight and can quickly harvest and store energy. Nix V2 O5 ⋅ nH2 O (NVO) loaded on carbon cloth (CC) with Ni2+ /H2 O ions intercalated as the cathode was assembled with activated CC to form a ZIHC, which has a voltage range of 2.0 V and capacitance value of 267.1 mF cm-2 as well as good charge and discharge rates and excellent cycling stability. At the same time, the NVO/CC can be assembled with PDMS to form a TENG achieving a maximum instantaneous power of 18.5 mW cm-2 . The device can be flexibly worn over the body to continuously harvest and store biomechanical energy and charge the electronic wristwatch successfully. This work demonstrates great convenience and promising practical applications as sustainable flexible energy system for portable electronic devices.

A deep learning model based on contrast-enhanced computed tomography for differential diagnosis of gallbladder carcinoma.

BACKGROUND: Gallbladder carcinoma (GBC) is highly malignant, and its early diagnosis remains difficult. This study aimed to develop a deep learning model based on contrast-enhanced computed tomography (CT) images to assist radiologists in identifying GBC. METHODS: We retrospectively enrolled 278 patients with gallbladder lesions (> 10 mm) who underwent contrast-enhanced CT and cholecystectomy and divided them into the training (n = 194) and validation (n = 84) datasets. The deep learning model was developed based on ResNet50 network. Radiomics and clinical models were built based on support vector machine (SVM) method. We comprehensively compared the performance of deep learning, radiomics, clinical models, and three radiologists. RESULTS: Three radiomics features including LoG_3.0 gray-level size zone matrix zone variance, HHL first-order kurtosis, and LHL gray-level co-occurrence matrix dependence variance were significantly different between benign gallbladder lesions and GBC, and were selected for developing radiomics model. Multivariate regression analysis revealed that age ≥ 65 years [odds ratios (OR) = 4.4, 95% confidence interval (CI): 2.1-9.1, P < 0.001], lesion size (OR = 2.6, 95% CI: 1.6-4.1, P < 0.001), and CA-19-9 > 37 U/mL (OR = 4.0, 95% CI: 1.6-10.0, P = 0.003) were significant clinical risk factors of GBC. The deep learning model achieved the area under the receiver operating characteristic curve (AUC) values of 0.864 (95% CI: 0.814-0.915) and 0.857 (95% CI: 0.773-0.942) in the training and validation datasets, which were comparable with radiomics, clinical models and three radiologists. The sensitivity of deep learning model was the highest both in the training [90% (95% CI: 82%-96%)] and validation [85% (95% CI: 68%-95%)] datasets. CONCLUSIONS: The deep learning model may be a useful tool for radiologists to distinguish between GBC and benign gallbladder lesions.

The Association Between Bone Bruises and Concomitant Ligaments Injuries in Anterior Cruciate Ligament Injuries: A Systematic Review and Meta-analysis.

Background: Bone bruises and concomitant ligament injuries after anterior cruciate ligament (ACL) injuries have attracted attention, but their correlation and potential clinical significance remain unclear. Purpose: To assess the relationship between bone bruises and concomitant ligamentous injuries in ACL injuries. Study design: Systematic review. Methods: A comprehensive search of PubMed, Embase, Web of Science, and Cochrane Library was completed from inception to October 20, 2021. All articles that evaluated the relationship between bone bruises and related ligaments injuries were included. Methodological Index for Non-Randomized Studies (MINORS) was used for quality assessment as well as Review Manager 5.3 was used for data analysis. Results: A total of 19 studies evaluating 3292 patients were included. After meta-analysis, anterolateral ligament (ALL) injuries were associated with bone bruising on the lateral tibial plateau (LTP) (RR = 2.33; 95% CI 1.44-3.77; p = 0.0006), lateral femoral condyle (LFC) (RR = 1.97; 95% CI 1.37-2.85; p = 0.0003) and medial tibial plateau (MTP) (RR = 1.62; 95% CI 1.24-2.11; p = 0.0004); Moreover, medial collateral ligament (MCL) injuries were associated with bone bruising on the femur (RR = 1.49; 95% CI 1.17-1.90; p = 0.001), and no statistical significance was found between bone bruising on the MTP and Kaplan fiber (KF) injuries (RR = 1.58; 95% CI 1.00-2.49; p = 0.05). Nonetheless, the current evidence did not conclude that bone bruises were associated with lateral collateral ligament (LCL) injuries. Conclusion: For individuals with an ACL injury, bone bruises of the LTP, LFC, and MTP can assist in the diagnosis of ALL injuries. Furthermore, femoral bruising has potential diagnostic value for MCL injuries. Knowing these associations allows surgeons to be alert to ACL-related ligament injuries on MRI and during operations in future clinical practice.

Contrast-enhanced CT radiomics for prediction of recurrence-free survival in gallbladder carcinoma after surgical resection.

OBJECTIVES: Gallbladder carcinoma (GBC) is the most common and aggressive biliary tract malignancy with high postoperative recurrence rates. This single-center study aimed to develop and validate a radiomics signature to estimate GBC recurrence-free survival (RFS). METHODS: This study retrospectively included 204 consecutive patients with pathologically diagnosed GBC and were randomly divided into development (n = 142) and validation (n = 62) cohorts (7:3). The radiomics features of tumor were extracted from preoperative contrast-enhanced CT imaging for each patient. In the development cohort, the least absolute shrinkage and selection operator (LASSO) Cox regression was employed to develop a radiomics signature for RFS prediction. The patients were stratified into high-score or low-score groups according to their median value of radiomics score. A nomogram was established using multivariable Cox regression by incorporating significant pathological predictors and radiomics signatures. RESULTS: The radiomics signature based on 12 features could discriminate high-risk patients with poor RFS. Multivariate Cox analysis revealed that pT3/4 stage (hazard ratio, [HR] = 2.691), pN2 stage (HR = 3.60), poor differentiation grade (HR = 2.651), and high radiomics score (HR = 1.482) were independent risk variables associated with worse RFS and were incorporated to construct a nomogram. The nomogram displayed good prediction performance in estimating RFS with AUC values of 0.895, 0.935, and 0.907 at 1, 3, and 5 years, respectively. CONCLUSIONS: The radiomics signature and combined nomogram may assist in predicting RFS in GBC patients. KEY POINTS: • A radiomics signature extracted from preoperative contrast-enhanced CT can be a useful tool to preoperatively predict RFS of GBC. • T3/T4 stage, N2, poor tumor differentiation, and high radiomics score were positively associated with postoperative recurrence.

Radiomics Analysis of Contrast-Enhanced CT for the Preoperative Prediction of Microvascular Invasion in Mass-Forming Intrahepatic Cholangiocarcinoma.

BACKGROUND: Microvascular invasion (MVI) has been shown to be closely associated with postoperative recurrence and metastasis in patients with intrahepatic cholangiocarcinoma (ICC). We aimed to develop a radiomics prediction model based on contrast-enhanced CT (CECT) to distinguish MVI in patients with mass-forming ICC. METHODS: 157 patients were included and randomly divided into training (n=110) and test (n=47) datasets. Radiomic signatures were built based on the recursive feature elimination support vector machine (Rfe-SVM) algorithm. Significant clinical-radiologic factors were screened, and a clinical model was built by multivariate logistic regression. A nomogram was developed by integrating radiomics signature and the significant clinical risk factors. RESULTS: The portal phase image radiomics signature with 6 features was constructed and provided an area under the receiver operating characteristic curve (AUC) of 0.804 in the training and 0.769 in the test datasets. Three significant predictors, including satellite nodules (odds ratio [OR]=13.73), arterial hypo-enhancement (OR=4.31), and tumor contour (OR=4.99), were identified by multivariate analysis. The clinical model using these predictors exhibited an AUC of 0.822 in the training and 0.756 in the test datasets. The nomogram combining significant clinical factors and radiomics signature achieved satisfactory prediction efficacy, showing an AUC of 0.886 in the training and 0.80 in the test datasets. CONCLUSIONS: Both CECT radiomics analysis and radiologic factors have the potential for MVI prediction in mass-forming ICC patients. The nomogram can further improve the prediction efficacy.

CT radiomics nomogram for the preoperative prediction of severe post-hepatectomy liver failure in patients with huge (≥ 10 cm) hepatocellular carcinoma.

BACKGROUND: This study aimed to establish a radiomics-based nomogram for predicting severe (grade B or C) post-hepatectomy liver failure (PHLF) in patients with huge (≥ 10 cm) hepatocellular carcinoma (HCC). METHODS: One hundred eighty-six patients with huge HCC (training dataset, n = 131 and test dataset, n = 55) that underwent curative hepatic resection were included in this study. The least absolute shrinkage and selection operator (LASSO) approach was applied to develop a radiomics signature for grade B or C PHLF prediction using the training dataset. A multivariable logistic regression model was used by incorporating radiomics signature and other clinical predictors to establish a radiomics nomogram. Decision tree analysis was performed to stratify the risk for severe PHLF. RESULTS: The radiomics signature consisting of nine features predicted severe PHLF with AUCs of 0.766 and 0.745 for the training and test datasets. The radiomics nomogram was generated by integrating the radiomics signature, the extent of resection and the model for end-stage liver disease (MELD) score. The nomogram exhibited satisfactory discrimination ability, with AUCs of 0.842 and 0.863 for the training and test datasets, respectively. Based on decision tree analysis, patients were divided into three risk classes: low-risk patients with radiomics score < -0.247 and MELD score < 10 or radiomics score ≥ - 0.247 but underwent partial resections; intermediate-risk patients with radiomics score < - 0.247 but MELD score ≥10; high-risk patients with radiomics score ≥ - 0.247 and underwent extended resections. CONCLUSIONS: The radiomics nomogram could predict severe PHLF in huge HCC patients. A decision tree may be useful in surgical decision-making for huge HCC hepatectomy.

A Clinical-Radiomics Nomogram for Preoperative Prediction of Lymph Node Metastasis in Gallbladder Cancer.

OBJECTIVES: The aim of the current study was to develop and validate a nomogram based on CT radiomics features and clinical variables for predicting lymph node metastasis (LNM) in gallbladder cancer (GBC). METHODS: A total of 353 GBC patients from two hospitals were enrolled in this study. A Radscore was developed using least absolute shrinkage and selection operator (LASSO) logistic model based on the radiomics features extracted from the portal venous-phase computed tomography (CT). Four prediction models were constructed based on the training cohort and were validated using internal and external validation cohorts. The most effective model was then selected to build a nomogram. RESULTS: The clinical-radiomics nomogram, which comprised Radscore and three clinical variables, showed the best diagnostic efficiency in the training cohort (AUC = 0.851), internal validation cohort (AUC = 0.819), and external validation cohort (AUC = 0.824). Calibration curves showed good discrimination ability of the nomogram using the validation cohorts. Decision curve analysis (DCA) showed that the nomogram had a high clinical utility. CONCLUSION: The findings showed that the clinical-radiomics nomogram based on radiomics features and clinical parameters is a promising tool for preoperative prediction of LN status in patients with GBC.

A radiomics model that predicts lymph node status in pancreatic cancer to guide clinical decision making: A retrospective study.

Purpose: To construct a radiomics-based model for predicting lymph node (LN) metastasis status in pancreatic ductal adenocarcinoma (PDAC) before therapy and to evaluate its prognostic clinical value. Materials and Methods: We retrospectively collected preoperative CT scans of 130 PDAC patients who underwent original tumor resection and LN dissection in the entire cohort between January 2014 and December 2017. Radiomics features were systematically extracted and analyzed from CT scans of 89 patients in the primary cohort. To construct a radiomics signature, the least absolute shrinkage and selection operator methods were employed with LN metastasis status as classification labels. Pathological analysis of LN status which were assessed by experienced pathologists was used as the evaluation label. We subjected the clinical nomogram to multivariable logistic regression analysis and conducted performance evaluation based on its discrimination, calibration, and clinical value. The model was tested and validated in 41 patients with PDAC in a separate validation cohort. Results: Four radiomics features closely associated with LN metastasis were selected in the primary and validation cohorts (P < 0.01). Following the integration of CT-reported results and radiomics signatures into the radiomics nomogram, we reported better performance in the primary (area under the curve, 0.80) and validation (area under the curve, 0.78) cohorts. Conclusion: The noninvasive tool constructed from the portal venous phase CT based on radiomics showed better performance for LN metastasis prediction than traditional approaches in pancreatic cancer. It may assist surgeons in crafting detailed procedures before treatment, this subsequently improves tumor staging and resection of patients.

Physiological and developmental traits associated with the grain yield of winter wheat as affected by phosphorus fertilizer management.

Although researchers have determined that attaining high grain yields of winter wheat depends on the spike number and the shoot biomass, a quantitative understanding of how phosphorus (P) nutrition affects spike formation, leaf expansion and photosynthesis is still lacking. A 3-year field experiment with wheat with six P application rates (0, 25, 50, 100, 200, and 400 kg P ha-1) was conducted to investigate this issue. Stem development and mortality, photosynthetic parameters, dry matter accumulation, and P concentration in whole shoots and in single tillers were studied at key growth stages for this purpose. The results indicated that spike number contributed the most to grain yield of all the yield components in a high-yielding (>8 t/ha) winter wheat system. The main stem (MS) contributed 79% to the spike number and tiller 1 (T1) contributed 21%. The 2.7 g kg-1 tiller P concentration associated with 15 mg kg-1 soil Olsen-P at anthesis stage led to the maximal rate of productive T1s (64%). The critical shoot P concentration that resulted in an adequate product of Pn and LAI was identified as 2.1 g kg-1. The thresholds of shoot P concentration that led to the maximum productive ability of T1 and optimal canopy photosynthetic capacity at anthesis were very similar. In conclusion, the thresholds of soil available P and shoot P concentration in whole plants and in single organs (individual tillers) were established for optimal spike formation, canopy photosynthetic capacity, and dry matter accumulation. These thresholds could be useful in achieving high grain yields while avoiding excessive P fertilization.

Targeting carbon nanotubes based on IGF-1R for photothermal therapy of orthotopic pancreatic cancer guided by optical imaging.

Pancreatic cancer is one of the most lethal malignancies worldwide. The existing therapeutic regimen in the clinic for advanced inoperable carcinomas are far from satisfactory, thus it is urgent to seek more effective anticancer strategies. In the pursuit of novel, more effective interventions, photothermal therapy (PTT) based on nanomaterials has attracted increased attention. Recent advances in related fields have catalyzed the generation of novel nanoprobes, such as organic dyes, metal nanoparticles. However, organic dyes are poorly stable and easy to quench while metal nanoparticles with potential metal toxicity are difficult to degrade, both of which have low light-to-heat conversion efficiency, broad spectrum of anti-tumor effects, and lack of tumor targeting specificity. Single-walled carbon nanotubes (SWNTs) can remedy the above inadequacies. Herein, we report our water-soluble, bio-stable and low-toxicity SWNTs with excellent photothermal conversion efficiency. Specific modifications can enable visualization of the aggregate characteristics of SWNTs at the macroscopic or microscopic level in tumors. The dye-conjugated SWNTs bound with targeting antibodies that can induce them specifically targeting to pancreatic tumors for purposes of performing dyes imaging-guided cytotoxic PTT. PTT using this method achieves precise and excellent curative effects with minimal adverse effects, thus providing a promising strategy for anticancer therapy.

An Innovation for Treating Orthotopic Pancreatic Cancer by Preoperative Screening and Imaging-Guided Surgery.

PURPOSE: Pancreatic cancer is still associated with a poor outcome and low patient quality of life, which are mainly attributed to the late detection and requirement of distal pancreatectomy with extended resection of pancreatic tumors. Therefore, novel strategies for early screening and precise tumor resection are urgently needed. In this study, we evaluated the feasibility of a low-density lipoprotein receptor (LDLR)-targeted small-molecule contrast agent (peptide-22-Cy7) for early screening with photoacoustic tomography and near-infrared (NIR) imaging as guided surgical navigation to achieve precise resection. PROCEDURE: Normal pancreatic cells (HPDE6-C7) and cancer cells (PANC-1) were respectively used in the in vitro targeting evaluations. The ability of peptide-22-Cy7 for preoperative in vivo pancreatic tumor detection was investigated in a mouse orthotopic pancreatic cancer model (n = 10) using photoacoustic tomography; 18 tumor-bearing mice were further divided into three groups for different treatments. After intravenous injection of peptide-22-Cy7, surgical navigation was conducted through laparotomy. Histopathological analysis was used to further confirm the tumor area and the state of surgical margins. RESULTS: Flow cytometry demonstrated that peptide-22 is highly specific to pancreatic cancer cells, with a fluorescence intensity of approximately 87.3 %. Orthotopic pancreatic tumors with a size of 4 mm could be accurately detected by photoacoustic tomography. Surgical navigation effectively achieved R0 resection and minimized the range of resection, which led to increased body weight of the mice following surgery. CONCLUSION: Overall, our newly developed targeted contrast agent facilitated the accurate positioning and resection of pancreatic tumors. Photoacoustic tomography and optical imaging-guided surgical navigation may be a novel direction for improving the survival, quality of life, and disease management of pancreatic cancer patients.

The diagnosis of hepatic fibrosis by magnetic resonance and near-infrared imaging using dual-modality nanoparticles.

Hepatic fibrosis (HF), as the only reversible process of chronic liver disease, remains a big diagnostic challenge. Development of noninvasive and effective methods to assess quantitatively early-stage HF is of great clinical importance. Compared with conventional diagnostic methods, near-infrared fluorescence imaging (NIR) and magnetic resonance imaging (MRI) could offer highly sensitive and spatial resolution signals for HF detection. However, precise detection using contrast agents is not possible. Superparamagnetic iron oxide (SPIO) nanoparticles have low toxicity, high sensitivity and excellent biocompatibility. Integration of Fe3O4 nanoparticles and indocyanine green (ICG), coupled with targeting ligand of integrin αvß3, arginine-glycine-aspartic acid (RGD) expressed on hepatic stellate cells (HSCs), were used to detect HF. Both in vivo and in vitro results showed that the SPIO@SiO2-ICG-RGD had high stability and low cytotoxicity. The biodistribution of SPIO@SiO2-ICG-RGD was significantly different between mice with HF and healthy controls. SPIO@SiO2-ICG-RGD was characterized and the results of imaging in vitro and in vivo demonstrated the expression of integrin αvß3 on activated HSCs. These data suggest that our SPIO@SiO2-ICG-RGD probe could be used for the diagnosis of early-stage HF. This new nanoprobe with a dual-modality imaging approach holds great potential for the diagnosis and classification of HF.

Theranostic imaging of liver cancer using targeted optical/MRI dual-modal probes.

The accurate preoperative detection and intraoperative navigation afforded by imaging techniques have had significant impact on the success of liver cancer surgeries. However, it is difficult to achieve satisfactory performance in both diagnosis and surgical treatment processes using any single modality imaging method. Here, we report the synthesis and characteristics of a novel dual-modality magnetic resonance imaging (MRI) and near-infrared fluorescence (NIRF) probe and verify its feasibility in nude mouse models with liver cancer. The probes are comprised of superparamagnetic iron oxide (SPIO) nanoparticles coated with liposomes to which a tumor-targeted agent, Arg-Gly-Asp peptides (RGD), and a NIRF dye (indocyanine green, ICG) have been conjugated. Specific targeting, biodistribution, and the imaging ability of the probes for MRI-NIRF were examined. Furthermore, we applied the dual-modality methodology toward the preoperative diagnosis and intraoperative guidance of radical resection in mouse models with both orthotopic liver tumors and intrahepatic tumor metastasis. The study demonstrated that both MRI and fluorescent images showed clear tumor delineation after probe injection (SPIO@Liposome-ICG-RGD). The contrast-to-noise ratio obtained from MRI was 31.9 ± 25.4 at post-injection for the preoperative diagnosis, which is helpful for detecting small tumors (0.9 ± 0.5 mm). The maximum tumor to background ratio of NIRF imaging was 2.5 ± 0.3 at 72 h post-injection for effectively capturing miniscule tumor lesions (0.6 ± 0.3 mm) intraoperatively. The novel MRI-NIRF dual modality probes are promising for the achievement of more accurate liver tumor detection and resection.

Dye-conjugated single-walled carbon nanotubes induce photothermal therapy under the guidance of near-infrared imaging.

Recently, photothermal therapy (PTT) has become viewed as an ideal auxiliary therapeutic treatment for cancers. However, the development of safe, convenient, and highly effective photothermal agents remains a great challenge. In this study, we prepared single-walled carbon nanotubes (SWNTs) for PTT against breast tumors under the guidance of infrared fluorescent cyanines. Tumors were accurately located using near-infrared imaging (NIR) and then exposed to laser irradiation. Both the in vivo and in vitro results showed that the SWNTs have high stability and low cytotoxicity. Introducing polyethylene glycol into our nanoparticles increased the blood-circulation time. Our in vivo results further showed that Cy5.5-conjugated SWNTs mediated PTT, resulting in efficient tumor suppression in mice under the guidance of near-infrared imaging. Due to the small amount of absorption at 808-nm, Cy5.5 increased the efficiency of PTT. Breast tumors significantly shrunk after irradiation under the 808-nm near-infrared laser. The treated mice developed scabs, but otherwise recovered after 15 days, and their physical conditions restored gradually. These data indicate that our unique photothermal-responsive SWNT-Cy5.5-based theranostic agent can serve as a promising candidate for PTT.

Cancer Diagnosis and Imaging-Guided Photothermal Therapy Using a Dual-Modality Nanoparticle.

To improve patient outcome and decrease overall health-care costs, highly sensitive and precise detection of a tumor is required for its accurate diagnosis and efficient therapy; however, this remains a challenge when using conventional single mode imaging. Here, we successfully designed a near-infrared (NIR)-response photothermal therapy (PTT) platform (Au@MSNs-ICG) for the location, diagnosis, and NIR/computer tomography (CT) bimodal imaging-guided PTT of tumor tissues, using gold (Au) nanospheres coated with indocyanine green (ICG)-loaded mesoporous silica nanoparticles (MSNs), which would have high sensitivity and precision. The nanoparticles (NPs) exhibited good monodispersity, fluorescence stability, biocompatibility, and NIR/CT signaling and had a preferable temperature response under NIR laser irradiation in vitro or in vivo. Using a combination of NIR/CT imaging and PTT treatment, the tumor could be accurately positioned and thoroughly eradicated in vivo by Au@MSNs-ICG injection. Hence, the multifunctional NPs could play an important role in facilitating the accurate treatment of tumors in future clinical applications.

[Medicinal resources of Salvia yunnanensis].

Salvia yunnanensis is a habitually used medicinal plant in Yunnan. It distributed widely over the southwest China, and its contents of tanshinone II-A and protocatechuic aldehyde are higher than those of Salvia miltiorrhiza. Therefore, S. yunnanensis is one of the best resources of the medicinal plant.