Ultrahigh Piezocatalytic Performance of Perovskite Ferroelectric Powder via Oxygen Vacancy Engineering.

Piezocatalysis has increasingly gained prominence due to its enormous potential for addressing energy shortages and environmental pollution issues. Nonetheless, the low piezocatalytic activity of state-of-the-art materials seriously inhibits the practical applications of piezocatalysis. Here, it is proposed to greatly enhance the piezocatalytic activity for a perovskite ferroelectric, i.e., Sm-doped 0.68Pb(Mg1/3 Nb2/3 )-0.32PbTiO3 (Sm-PMN-PT, a solid solution with ultrahigh piezoelectricity), by introducing oxygen vacancies (OVs). The results show that the presence of OVs promotes the production of reactive oxygen species while enhancing the adsorption and activation of organic pollutants to improve piezocatalytic performance. The OV-Sm-PMN-PT is found to possess a superior piezocatalytic degradation rate constant of 0.073 min-1 under ultrasonic vibration, which is ≈4.9 times higher than that of pristine Sm-PMN-PT. Furthermore, the OV-Sm-PMN-PT can efficiently remove RhB under 400 rpm stirring, making it a promising candidate for water purification using low-frequency mechanical energy from nature. This research sheds light on the design of piezocatalytic materials via defect engineering.

Superselective arterial microcoil embolization for delayed bleeding after peroral endoscopic myotomy.

Peroral endoscopic myotomy (POEM) has been shown to be an effective treatment for achalasia and with few adverse events. Only a few cases of delayed bleeding have been described. This current case report describes a patient with delayed bleeding in the submucosal tunnel on the eighth day after POEM. The patient was a 21-year-old woman with a 4-month history of dysphagia, vomiting and excessive weight loss. Achalasia was diagnosed according to her symptoms, barium oesophagogram, oesophageal manometry and endoscopy examination. POEM was performed by an experienced operator. On the eighth day after POEM, the patient suddenly developed continuous haematemesis presented with vomiting of fresh blood and melena. An emergency exploratory esophagogastroduodenoscopy was performed. A large number of blood clots were found at the wound and a long haematoma was found along the lining of the submucosal tunnel. Re-entry into the submucosal tunnel and exposure of the haemorrhagic site was attempted but failed because of severe submucosal tissue adhesion. An emergency angiography was undertaken and haemostasis was achieved with superselective arterial microcoil embolization.

The structural, mechanical and electronic properties of Ti-Al-based compounds by first-principles calculations.

The first-principles calculations with density functional theory were performed to investigate the effects of transition metal elements (Mo, Cu, Fe, Ni and Nb) on the physical properties of the Ti-Al-based compounds. Our optimized crystal parameters are in good agreement with the previous theoretical and experimental values. The mechanical stability is verified by the independent elastic constants. The B/G and Poisson's ratio ν both show that Al6TiMo is brittle, while other compounds exhibit ductility. The values of compression anisotropy of the compounds are small, but the shear anisotropy of AlCu2Ti and AlNi2Ti is much more intense than that of other compounds. The anisotropy in elastic properties of AlFe2Ti and AlNbTi2 is smaller than that of the others. It can be seen that the capacity to compress along c-axis is smaller than that along a-axis and b-axis for AlNbTi2. For AlNbTi2, the anisotropy of the bulk modulus along a-axis relative to b-axis is more insignificant than that along c-axis relative to b-axis. The hardness and Debye temperature verify that AlFe2Ti has the greatest resistance to the plastic deformation and more intense inter-atomic bonding force, respectively. Band structures and DOS are used to investigate the electronic properties. The band structures without band gaps show that these ternary Ti-Al-based compounds are conductors. DOS shows the interactions between elements and gives the bond properties. Density of states and charge density both show the strong covalent properties of AlFe2Ti by the hybridization between Fe-3d and Ti-3d states.

DigestPath: A benchmark dataset with challenge review for the pathological detection and segmentation of digestive-system.

Examination of pathological images is the golden standard for diagnosing and screening many kinds of cancers. Multiple datasets, benchmarks, and challenges have been released in recent years, resulting in significant improvements in computer-aided diagnosis (CAD) of related diseases. However, few existing works focus on the digestive system. We released two well-annotated benchmark datasets and organized challenges for the digestive-system pathological cell detection and tissue segmentation, in conjunction with the International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI). This paper first introduces the two released datasets, i.e., signet ring cell detection and colonoscopy tissue segmentation, with the descriptions of data collection, annotation, and potential uses. We also report the set-up, evaluation metrics, and top-performing methods and results of two challenge tasks for cell detection and tissue segmentation. In particular, the challenge received 234 effective submissions from 32 participating teams, where top-performing teams developed advancing approaches and tools for the CAD of digestive pathology. To the best of our knowledge, these are the first released publicly available datasets with corresponding challenges for the digestive-system pathological detection and segmentation. The related datasets and results provide new opportunities for the research and application of digestive pathology.

Qualitative Distribution of Endogenous Cholesteryl Esters in Plasma of Humans and Three Rodent Species Using Stepwise UPLC-Q-Exactive-MS.

OBJECTIVE: Cholesteryl esters (CEs) are composed of various fatty acyl chains attached to the hydroxyl groups of cholesterol, and abnormalities in their metabolism are related to many diseases. This study aimed to develop an ultrahigh-performance liquid chromatography-quadrupole exactive mass spectrometry (UPLC-Q-Exactive MS) method to identify the CEs in plasma. METHODS: First, the MS fragmentation patterns were investigated using seven commercial CE standards. Then, the CEs in plasma were characterized through the accurate mass data of precursor ions and characteristic product ions. A strategy of step-by-step m/z scans in a narrow range was proposed to identify more trace CEs by the full-scan data-dependent MS/MS (ddMS2) mode. RESULTS: A total of 50 CE species consisting of 55 regioisomers were identified in human plasma. Among them, two species were reported for the first time. CONCLUSION: This study is the most comprehensive identification of CE species in human plasma to date. These results will contribute to the in-depth profiling of CEs in human plasma and provide guidance for animal model selection when studying lipid-related diseases.

A retrospective cohort study of intensive gastric variceal ligation versus endoscopic gastric variceal obturation in the management of gastric variceal bleeding.

BACKGROUND: Gastric variceal bleeding is often more serious and can be fatal. Currently, international consensus recommendations for the treatment of gastric variceal bleeding vary according to endoscopic classification. Few studies have investigated ligation versus gastric variceal obturation (GVO) for the treatment of gastric varices. METHODS: The study included 79 patients with cirrhosis-induced bleeding from esophageal and fundal varices who were treated at the Second Hospital of Hebei Medical University between January 2016 and December 2020 and who met the inclusion criteria. Among them, 42 patients were included in the intensive gastric varices ligation (IGVL) group, and 37 were included in the GVO group. We conducted a retrospective cohort study to analyze the effectiveness and safety of these 2 treatments. RESULTS: The rebleeding rate after initial treatment was significantly lower in the IGVL group than in the GVO group (23.8% vs. 48.6%, P<0.05). No significant between-group difference was observed in overall mortality (14.3% vs. 32.4%), 6-week mortality (0.0% vs. 2.7%), or 1-year mortality (11.9% vs. 13.5%, all P>0.05). The >1-year mortality and bleeding-related mortality rates were significantly higher in the GVO group than in the IGVL group (23.3% vs. 2.7%, P<0.05; 27.0% vs. 9.5%, P<0.05). The incidence of adverse events was 57.1% in the IGVL group and 48.6% in the GVO group, with no significant difference (P>0.05). Independent predictors for rebleeding after initial treatment were the use of GVO as endoscopic treatment, total bilirubin >17.1 µmol/L, liver cancer, and diabetes. For mortality, the independent predictors were male sex, liver cancer, ascites, and rebleeding after initial treatment. CONCLUSIONS: Rebleeding after initial treatment was lower after IGVL than GVO. Independent predictors for rebleeding after initial treatment were endoscopic treatment method, total bilirubin >17.1 µmol/L, liver cancer, and diabetes. For mortality, the independent predictors were male sex, liver cancer, ascites, and rebleeding after initial treatment.

Discriminative Cervical Lesion Detection in Colposcopic Images With Global Class Activation and Local Bin Excitation.

Accurate cervical lesion detection (CLD) methods using colposcopic images are highly demanded in computer-aided diagnosis (CAD) for automatic diagnosis of High-grade Squamous Intraepithelial Lesions (HSIL). However, compared to natural scene images, the specific characteristics of colposcopic images, such as low contrast, visual similarity, and ambiguous lesion boundaries, pose difficulties to accurately locating HSIL regions and also significantly impede the performance improvement of existing CLD approaches. To tackle these difficulties and better capture cervical lesions, we develop novel feature enhancing mechanisms from both global and local perspectives, and propose a new discriminative CLD framework, called CervixNet, with a Global Class Activation (GCA) module and a Local Bin Excitation (LBE) module. Specifically, the GCA module learns discriminative features by introducing an auxiliary classifier, and guides our model to focus on HSIL regions while ignoring noisy regions. It globally facilitates the feature extraction process and helps boost feature discriminability. Further, our LBE module excites lesion features in a local manner, and allows the lesion regions to be more fine-grained enhanced by explicitly modelling the inter-dependencies among bins of proposal feature. Extensive experiments on a number of 9888 clinical colposcopic images verify the superiority of our method (AP .75 = 20.45) over state-of-the-art models on four widely used metrics.

Double plastic stent implantation for recurrent acute pancreatitis with incomplete pancreas divisum: a case report and literature review.

Pancreas divisum (PD) is a common pancreatic malformation caused by the failure of fusion between ventral and dorsal pancreatic ducts. There is a small branch of communication between the two systems in incomplete PD, and this variation has an incidence of 15%. A 43-year-old female patient presented to our department with recurrent abdominal pain. Magnetic resonance cholangiopancreatography (MRCP) showed that the ventral pancreatic duct was curved, with a local pouchlike dilatation. Endoscopic ultrasonography supported the diagnosis of incomplete PD and showed a thin branch of communication between ventral and dorsal pancreatic ducts. Endoscopic retrograde cholangiopancreatography (ERCP) and papillotomy of the minor papilla with double plastic stent implantation were performed. One pancreatic plastic stent was inserted across the minor and major papilla over the guide wire, creating a U-shape. The other wire-guided plastic stent was inserted through the minor papilla into the dorsal pancreatic duct. The pancreatic fluid drained smoothly after stent placement. During the 6-month follow-up, the patient remained well, without recurrence of pancreatitis.

Improved structural annotation of triterpene metabolites of traditional Chinese medicine in vivo based on quantitative structure-retention relationships combined with characteristic ions: Alismatis Rhizoma as an example.

As a fast, sensitive and selective method, liquid chromatography-tandem high-resolution mass spectrometry (LC-HRMS) has been used for studying the in vivo metabolism of traditional Chinese medicine (TCM). However, the rapid discovery and characterization of metabolites, especially isomers, remain challenging due to their complexity and low concentration in vivo. This study proposed a strategy to improve the structural annotation of prototypes and metabolites through characteristic ions and a quantitative structure-retention relationship (QSRR) model, and Alismatis Rhizoma (AR) triterpenes were used as an example. This strategy consists of four steps. First, based on an in-house database reported previously, prototypes and metabolites in biosamples were preliminarily identified. Second, the candidate structures of prototype compounds and metabolites were determined by characteristic ions, databases or potential metabolic pathways. Then, a QSRR model was established to predict the retention times of the proposed structure. Finally, the structures of unknown prototypes and metabolites were determined by matching experimental retention times with the predicted values. The QSRR model built by the genetic algorithm-multiple linear regression (GA-MLR) has excellent regression correlation (R2 = 0.9966). Based on this strategy, a total of 118 compounds were identified, including 47 prototypes and 71 metabolites, among which 61 unknown compounds were reasonably characterized. The typical compound identified by this strategy was successfully validated using a triterpene standard. This strategy can improve the annotation confidence of in vivo metabolites of TCM and facilitate further pharmacological research.

Correction: Unexpected formation of 1,2- and 1,4-bismethoxyl Sc3N@I h-C80 derivatives via regioselective anion addition: an unambiguous structural identification and mechanism study.

[This corrects the article DOI: 10.1039/D1SC01178B.].

Unexpected formation of 1,2- and 1,4-bismethoxyl Sc3N@I h-C80 derivatives via regioselective anion addition: an unambiguous structural identification and mechanism study.

An attempt to achieve heterocyclic cycloadducts of Sc3N@I h-C80 via reaction with Ph2C[double bond, length as m-dash]O, PhC[triple bond, length as m-dash]CPh or PhC[triple bond, length as m-dash]N in the presence of tetrabutylammonium hydroxide (TBAOH) stored in CH3OH led to the formation of the unexpected bismethoxyl adducts of Sc3N@I h-C80 (1 and 2). Further studies reveal that TBAOH in CH3OH can boost the CH3O- addition efficiently, regardless of the presence of other reagents. Single-crystal X-ray diffraction results firmly assign the molecular structures of 1 and 2 as respective 1,4- and 1,2-bismethoxyl adducts, and reveal unusual relationships between the internal Sc3N cluster and the addition modes, in addition to the unusual packing mode in view of the orientation of the methoxyl groups. Electrochemical results demonstrate smaller electrochemical gaps for 1 and 2, relative to that of Sc3N@I h-C80, confirming their better electroactive properties. Finally, a plausible reaction mechanism involving anion addition and a radical reaction was proposed, presenting new insights into the highly selective reactions between the methoxyl anion and metallofullerenes. 1 and 2 represent the first examples of methoxyl derivatives of metallofullerenes. This work not only presents a novel and facile strategy for the controllable synthesis of alkoxylated metallofullerene derivatives, but also provides new non-cycloadducts for the potential applications of EMFs.

Identification of a five-gene signature in association with overall survival for hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is considered to be a malignant tumor with a high incidence and a high mortality. Accurate prognostic models are urgently needed. The present study was aimed at screening the critical genes for prognosis of HCC. METHODS: The GSE25097, GSE14520, GSE36376 and GSE76427 datasets were obtained from Gene Expression Omnibus (GEO). We used GEO2R to screen differentially expressed genes (DEGs). A protein-protein interaction network of the DEGs was constructed by Cytoscape in order to find hub genes by module analysis. The Metascape was performed to discover biological functions and pathway enrichment of DEGs. MCODE components were calculated to construct a module complex of DEGs. Then, gene set enrichment analysis (GSEA) was used for gene enrichment analysis. ONCOMINE was employed to assess the mRNA expression levels of key genes in HCC, and the survival analysis was conducted using the array from The Cancer Genome Atlas (TCGA) of HCC. Then, the LASSO Cox regression model was performed to establish and identify the prognostic gene signature. We validated the prognostic value of the gene signature in the TCGA cohort. RESULTS: We screened out 10 hub genes which were all up-regulated in HCC tissue. They mainly enrich in mitotic cell cycle process. The GSEA results showed that these data sets had good enrichment score and significance in the cell cycle pathway. Each candidate gene may be an indicator of prognostic factors in the development of HCC. However, hub genes expression was weekly associated with overall survival in HCC patients. LASSO Cox regression analysis validated a five-gene signature (including CDC20, CCNB2, NCAPG, ASPM and NUSAP1). These results suggest that five-gene signature model may provide clues for clinical prognostic biomarker of HCC.

Qualitative distribution of endogenous sphingolipids in plasma of human and rodent species by UPLC-Q-Exactive-MS.

Sphingolipids (SLs) are endogenously bioactive molecules with diverse structures, and its metabolic disorders are involved in the progression of many diseases. In this study, an ultra-performance liquid chromatography quadrupole exactive mass spectrometry (UPLC-Q-Exactive-MS) method was established to comprehensively profile SLs in plasma. First, the fragment patterns of SL standards of each subclass were investigated. Then, the SL species in plasma were characterized based on the fragmentation rules. Finally, a total of 144 endogenous SL species consisting of 216 regioisomers were identified in plasma of human, golden hamster and C57BL/6 mice, which was the most comprehensive identification for SLs in plasma. In addition to the known species, 19 SL species that have never been reported were also identified. The profile of SLs in plasma of human and two rodent species was compared subsequently. It was worth noting that a total of 9 SL molecular species consisting of 11 regioisomers with low abundance were successfully identified in human plasma through comparison among species. Those findings contribute to a deeper understanding of SLs in human plasma and provide scientific basis for the selection of animal model. The established profile of SLs in plasma could be used for screening of lipid biomarkers of various diseases.

A Transfer Learning Based Super-Resolution Microscopy for Biopsy Slice Images: The Joint Methods Perspective.

Higher-resolution biopsy slice images reveal many details, which are widely used in medical practice. However, taking high-resolution slice images is more costly than taking low-resolution ones. In this paper, we propose a joint framework containing a novel transfer learning strategy and a deep super-resolution framework to generate high-resolution slice images from low-resolution ones. The super-resolution framework called SRFBN+ is proposed by modifying a state-of-the-art framework SRFBN. Specifically, the structure of the feedback block of SRFBN was modified to be more flexible. Besides, it is challenging to use typical transfer learning strategies directly for the tasks on slice images, as the patterns on different types of biopsy slice images are varying. To this end, we propose a novel transfer learning strategy, called Channel Fusion Transfer Learning (CF-Trans). CF-Trans builds a middle domain by fusing the data manifolds of the source domain and the target domain, serving as a springboard for knowledge transfer. Thus, in the transfer learning setting, SRFBN+ can be trained on the source domain and then the middle domain and finally the target domain. Experiments on biopsy slice images validate SRFBN+ works well in generating super-resolution slice images, and CF-Trans is an efficient transfer learning strategy.

A Deep Learning Approach for Colonoscopy Pathology WSI Analysis: Accurate Segmentation and Classification.

Colorectal cancer (CRC) is one of the most life-threatening malignancies. Colonoscopy pathology examination can identify cells of early-stage colon tumors in small tissue image slices. But, such examination is time-consuming and exhausting on high resolution images. In this paper, we present a new framework for colonoscopy pathology whole slide image (WSI) analysis, including lesion segmentation and tissue diagnosis. Our framework contains an improved U-shape network with a VGG net as backbone, and two schemes for training and inference, respectively (the training scheme and inference scheme). Based on the characteristics of colonoscopy pathology WSI, we introduce a specific sampling strategy for sample selection and a transfer learning strategy for model training in our training scheme. Besides, we propose a specific loss function, class-wise DSC loss, to train the segmentation network. In our inference scheme, we apply a sliding-window based sampling strategy for patch generation and diploid ensemble (data ensemble and model ensemble) for the final prediction. We use the predicted segmentation mask to generate the classification probability for the likelihood of WSI being malignant. To our best knowledge, DigestPath 2019 is the first challenge and the first public dataset available on colonoscopy tissue screening and segmentation, and our proposed framework yields good performance on this dataset. Our new framework achieved a DSC of 0.7789 and AUC of 1 on the online test dataset, and we won the [Formula: see text] place in the DigestPath 2019 Challenge (task 2). Our code is available at https://github.com/bhfs9999/colonoscopy_tissue_screen_and_segmentation.

N­linoleyltyrosine protects PC12 cells against oxidative damage via autophagy: Possible involvement of CB1 receptor regulation.

Oxidative stress is one of the main pathogenic factors of neurodegenerative diseases. As the ligand of cannabinoid type 1 (CB1) and 2 (CB2) receptors, anandamide (AEA) exerts benign antioxidant activities. However, the instability of AEA results in low levels in vivo, which limit its further application. Based on the structure of AEA, N­linoleyltyrosine (NITyr) was synthesized in our laboratory and was hypothesized to possess a similar function to that of AEA. To the best of our knowledge, the present study demonstrates for the first time, the activities and mechanisms of NITyr. NITyr treatment attenuated hydrogen peroxide (H2O2)­induced cytotoxicity, with the most promiment effect observed at 1 µmol/l. Treatment with NITyr also suppressed the H2O2­induced elevation of reactive oxygen species (ROS) and enhanced the expression of the autophagy­related proteins, LC3­II, beclin­1, ATG 5 and ATG13. The autophagic inhibitor, 3­methyladenine, reversed the effects of NITyr on ROS levels and cellular viability. Furthermore, AM251, a CB1 receptor antagonist, but not AM630 (a CB2 receptor antagonist), diminished the effects of NITyr on cell viability, ROS generation and autophagy­related protein expression. However, NITyr increased the protein expression of both the CB1 and CB2 receptors. Therefore, NITyr was concluded to protect PC12 cells against H2O2­induced oxidative injury by inducing autophagy, a process which may involve the CB1 receptor.

An alternative method for analyzing dimensional interactions of urban carrying capacity: Case study of Guangdong-Hong Kong-Macao Greater Bay Area.

Most previous studies on comprehensive urban carrying capacity (UCC) have estimated UCC levels and comparatively analyzed the heterogeneity of the sample cities. Very few researchers have focused on the interaction effects between different categories of UCC based on synergetic theory. To fill this gap, we constructed a panel vector autoregressive (PVAR) model to study 11 cities in the Guangdong-Hong Kong-Macao Greater Bay Area from 2000 to 2016. The ultimate goal of this study is to improve comprehensive UCC levels by forming a virtuous circle of mutual reinforcement between the four types of carrying capacity. To do so, the interaction mechanisms of the four subsystems are examined. Results show that (a) only transportation and social carrying capacity had causality between them as per the Granger causality test; (b) all four carrying capacities can support themselves (i.e., the development of economic conditions helps to improve social carrying capacity and the improvement of social carrying capacity helps to improve environmental carrying capacity); and (c) both the four carrying capacities are mostly affected by their own fluctuations. Overall transportation carrying capacity is the most important driving force among the four subsystems that interact with each other; followed by economic carrying capacity, which has promotion effect on the social and environmental aspects; social carrying capacity poses impact on the environmental dimension but not vice versa. Policy suggestions and future research directions are highlighted in the final section.

The application of deep learning based diagnostic system to cervical squamous intraepithelial lesions recognition in colposcopy images.

Background Deep learning has presented considerable potential and is gaining more importance in computer assisted diagnosis. As the gold standard for pathologically diagnosing cervical intraepithelial lesions and invasive cervical cancer, colposcopy-guided biopsy faces challenges in improving accuracy and efficiency worldwide, especially in developing countries. To ease the heavy burden of cervical cancer screening, it is urgent to establish a scientific, accurate and efficient method for assisting diagnosis and biopsy. Methods The data were collected to establish three deep-learning-based models. For every case, one saline image, one acetic image, one iodine image and the corresponding clinical information, including age, the results of human papillomavirus testing and cytology, type of transformation zone, and pathologic diagnosis, were collected. The dataset was proportionally divided into three subsets including the training set, the test set and the validation set, at a ratio of 8:1:1. The validation set was used to evaluate model performance. After model establishment, an independent dataset of high-definition images was collected to further evaluate the model performance. In addition, the comparison of diagnostic accuracy between colposcopists and models weas performed. Results The sensitivity, specificity and accuracy of the classification model to differentiate negative cases from positive cases were 85.38%, 82.62% and 84.10% respectively, with an AUC of 0.93. The recall and DICE of the segmentation model to segment suspicious lesions in acetic images were 84.73% and 61.64%, with an average accuracy of 95.59%. Furthermore, 84.67% of high-grade lesions were detected by the acetic detection model. Compared to colposcopists, the diagnostic system performed better in ordinary colposcopy images but slightly unsatisfactory in high-definition images. Implications The deep learning-based diagnostic system could help assist colposcopy diagnosis and biopsy for HSILs.

Chemical Reactions of Cationic Metallofullerenes: An Alternative Route for Exohedral Functionalization.

The chemistry of cationic forms of clusterfullerenes remain less explored than that of the corresponding neutral or anionic species. In the present work, M3 N@Ih -C80 (M=Sc or Lu) cations were generated by both electrochemical and chemical oxidation methods. The as-obtained cations successfully underwent the typical Bingel-Hirsch reaction that fails with neutral Sc3 N@Ih -C80 . Two isomeric Sc3 N@Ih -C80 cation derivatives, [5,6]-open and [6,6]-open adducts, were synthesized, and the former has never been prepared by means of a Bingel-Hirsch reaction with neutral clusterfullerenes. In the case of the Lu3 N@Ih -C80 cation, however, only a [6,6]-open adduct was obtained. Density functional theory (DFT) calculations indicated that the oxidized M3 N@Ih -C80 was much more reactive than the neutral compound upon addition of the diethyl bromomalonate anion. The Bingel-Hirsch reaction of M3 N@Ih -C80 cations occurred by means of an unusual outer-sphere single-electron transfer (SET) process from the diethyl bromomalonate anion to the stable intermediate [M3 N@C80 (C2 H5 COO)2 CBr]. . Remarkably, the diethyl bromomalonate anion was found to act as both a nucleophile and an electron donor.

Spectrum-effect relationship for anti-tumor activity of shikonins and shikonofurans in medicinal Zicao by UHPLC-MS/MS and chemometric approaches.

Shikonin, shikonofuran and their derivatives are the main bioactive components of Zicao, a traditional Chinese medicine prepared with the dried roots of Lithospermum erythrorhizon, Arnebia euchroma or Arnebia guttata. To establish an efficient and sensitive method for studying material basis of Zicao, different scan modes of ultra-high performance liquid chromatography quadrupole time of flight tandem mass spectrometry (UHPLC-QTOF-MS/MS) and UHPLC triple quadrupole linear ion trap mass spectrometry (QTRAP-MS/MS) were incorporated to make full use of the sensitivity of multiple reaction monitoring (MRM) and overcome its disadvantages. A total of 73 shikonins and shikonofurans compounds were detected in Zicao utilizing various scanning modes. Thereafter the characteristic chemical profile for shikonins and shikonofurans was established based on UHPLC-QTRAP-MS/MS, which was subsequently used to study the spectrum-effect relationship by correlating the relative quantity of compounds and the anti-tumor activity. As a result, 27 compounds were screened as the main active components inhibiting HeLa cells by othogonal partial least square (OPLS). Among them, shikonin, acetylshikonin have been reported to inhibit HeLa cells previously, and ß, ß-dimethylacrylshikonin has been reported to be active component by other method. Those results showed that chemical characteristic profile combined with chemometric methods was efficient and reliable for discovery of material basis in TCM, especially trace active compounds.