Erosion Life Prediction of Metal Mesh Screen Pipes in Oil Wells Based on Numerical Simulation of Discrete Particle Flow.

High-speed fluid-carried sand particles pose a significant challenge to oil well screen pipes, leading to sand control failure and adversely affecting the well's production and recovery rates. This research targets the commonly used metal mesh screen pipe in oil well sand production and establishes a full-sized three-dimensional structure model. A fluid-solid coupling of discrete particle flow numerical simulation algorithm is incorporated to formulate a novel method for predicting the screen pipe's erosion life. This method provides a solution to the complex task of predicting the pipe's lifespan under oil sand fluid erosion. The analysis elucidates the impact of sand particles on the velocity distribution and erosion rate of the metal mesh at varying velocities, facilitating the prediction of the mesh screen pipe's erosion life. Key findings reveal that the velocity and erosion rate vary across the different layers. The first layer screen experiences velocity and erosion rates that are 3.6-3.76 times and 2.45-2.50 times, respectively, higher than those at the inlet. The second layer screen undergoes velocity and erosion rates 2.32-2.43 times and 1.04-1.06 times, respectively, higher than those at the inlet. Erosion failure primarily occurs in the first layer screen due to velocity expansion instigated by the screen tube's structure. The discrete flow numerical simulation method proves valuable in predicting the mesh screen's erosion life at different flow rates, with a maximum error of 6.38% when compared with field monitoring life values. This method introduces a new technical approach to predicting the life span of metal mesh screens in oil wells. The study concludes by suggesting measures to extend the screen pipe's lifespan, thereby enhancing oil recovery.

Network pharmacology-based prediction and verification of the active ingredients and potential targets of Huagan Decoction for reflux esophagitis.

ETHNOPHARMACOLOGICAL RELEVANCE: Huagan Decoction (HGD), a famous traditional Chinese medicine (TCM) formula, has been widely used in the treatment of reflux esophagitis (RE). However, its effective compounds, potential targets and molecular mechanism remain unclear. AIM OF THE STUDY: To investigate effective compounds, potential targets and molecular mechanism of HGD against RE by using network pharmacology combined with in vitro validation, with the aims of observing the action of HGD and exploring new therapeutic strategies for RE treatment. MATERIALS AND METHODS: Effective compounds and potential targets of HGD, as well as related genes of RE, were collected from public databases. Pharmacological clustering and Gene Ontology (GO) enrichment analysis were applied to find targets that involving in the anti-inflammatory module. The pathways were drawn using Cytoscape 3.8.0. Important ingredients, potential targets, and signaling pathways were determined through the construction of protein-protein interaction (PPI), GO and Kyoto Encyclopedia of Genes and Genomes (KEGG). Subsequently, cell experiments were carried out. RESULTS: A total of 54 active ingredients and 240 RE-related gene targets of HGD were identified. The active compound-target network was visualized and pharmacological clustering further sorted 53 proteins that involve in the regulation of inflammatory responses. GO analysis confirmed the classification was statistically significant. Analysis of compound-target network revealed that quercetin and geniposide may be key ingredients for the anti-inflammatory effect of HGD against RE. The potential targets regulated by HGD are IL-6, IL-1ß, PTGS2, AKT1, TNF-α, MAPK1, IL-8, IL-10, CCL2 and MAPK3. In vitro experiment showed that quercetin and geniposide could inhibit the inflammatory response of HET-1A cells through p38MAPK/NF-κB signaling pathway, which was consistent with the prediction by the network pharmacology approach. CONCLUSIONS: Geniposide and quercetin could be effective therapeutic ingredients for the HGD against RE. They play anti-inflammatory effects via down-regulating the pro-inflammatory cytokines and the conduction of p38MAPK/NF-κB signal. This research provides a comprehensive study on the active components, potential targets, and molecular mechanisms of HGD against RE. Moreover, the study supplies a feasible approach to reveal the mechanisms of TCM formula.

Near-field engineering for boosting the photoelectrochemical activity to a modal strong coupling structure.

Near-field engineering is considered a significant strategy in constructing plasmonic nanostructures for efficient plasmonic chemistry. We demonstrate interfacial near-field engineering on a Au-NP/TiO2/Au-film (ATA) photoanode to improve the water oxidation efficiency. To tailor the near-field distribution, postdeposited Au on an ATA electrode (Au@ATA) is implemented using a facile constant potential electrolysis technique. As a result, the average photocurrent conversion efficiency of Au@ATA is approximately 1.3-fold higher than that of ATA.

[Characteristics of Stable Isotopes and Moisture Sources of Two Typical Precipitation Events in Lanzhou City].

To better understand the isotope variations on a short time scale, this study focused on a long-term rainfall event with light precipitation (June 26-27) and a short-term one with heavy precipitation (July 28) in Lanzhou City in the summer of 2019. Combined with HYSPLIT model, samples collected during a continuous precipitation event every 10 min and 30 min were analyzed to explore the characteristics and mechanism of stable hydrogen and oxygen isotopes in precipitation. The results indicate that the effect of sub-cloud secondary evaporation makes the slope of the sequential meteoric water line (SMWL) smaller at the beginning of the rainfall event. Most of the continuous sampling points are distributed above the global meteoric water line (GMWL) and local meteoric water line (LMWL). Moreover, the deuterium excess is larger than the local average annual deuterium (8.13), indicating that the samples have experienced moisture recycling to a certain extent. During two consecutive days (June 26-27) of rainfall, the variations in oxygen isotope δ18O did not follow the effect of precipitation amount; the precipitation δ18O of the first day was "L" shaped, and it fluctuated the next day. On July 28, δ18O steadily decreased, and the range of δ18O exceeded 9‰. On June 26, the moisture transport path was short at the height of 500 m and on June 27 local evaporation was the main pathway. On July 28, with a relatively stable air mass, the moisture source of the entire precipitation event did not change significantly, neither did the isotope value. Therefore, for a single precipitation event on a short time scale, the difference in moisture sources is one of the reasons for isotope variations.

A Novel Discovery: Holistic Efficacy at the Special Organ Level of Pungent Flavored Compounds from Pungent Traditional Chinese Medicine.

Pungent traditional Chinese medicines (TCMs) play a vital role in the clinical treatment of hepatobiliary disease, gastrointestinal diseases, cardiovascular diseases, diabetes, skin diseases and so on. Pungent TCMs have a vastness of pungent flavored (with pungent taste or smell) compounds. To elucidate the molecular mechanism of pungent flavored compounds in treating cardiovascular diseases (CVDs) and liver diseases, five pungent TCMs with the action of blood-activating and stasis-resolving (BASR) were selected. Here, an integrated systems pharmacology approach is presented for illustrating the molecular correlations between pungent flavored compounds and their holistic efficacy at the special organ level. First, we identified target proteins that are associated with pungent flavored compounds and found that these targets were functionally related to CVDs and liver diseases. Then, based on the phenotype that directly links human genes to the body parts they affect, we clustered target modules associated with pungent flavored compounds into liver and heart organs. We applied systems-based analysis to introduce a pungent flavored compound-target-pathway-organ network that clarifies mechanisms of pungent substances treating cardiovascular diseases and liver diseases by acting on the heart/liver organ. The systems pharmacology also suggests a novel systematic strategy for rational drug development from pungent TCMs in treating cardiovascular disease and associated liver diseases.

Danshen: a phytochemical and pharmacological overview.

Danshen, the dried root or rhizome of Salvia miltiorrhiza Bge., is a traditional and folk medicine in Asian countries, especially in China and Japan. In this review, we summarized the recent researches of Danshen in traditional uses and preparations, chemical constituents, pharmacological activities and side effects. A total of 201 compounds from Danshen have been reported, including lipophilic diterpenoids, water-soluble phenolic acids, and other constituents, which have showed various pharmacological activities, such as anti-inflammation, anti-oxidation, anti-tumor, anti-atherogenesis, and anti-diabetes. This article intends to provide novel insight information for further development of Danshen, which could be of great value to its improvement of utilization.

The anticancer mechanism investigation of Tanshinone IIA by pharmacological clustering in protein network.

BACKGROUND: Cancer is the second most common cause of death globally. The anticancer effects of Tanshinone IIA (Tan IIA) has been confirmed by numerous researches. However, the underlying mechanism remained to be integrated in systematic format. Systems biology embraced the complexity of cancer; therefore, a system study approach was proposed in the present study to explore the anticancer mechanism of Tan IIA based on network pharmacology. METHOD: Agilent Literature Search (ALS), a text-mining tool, was used to pull protein targets of Tan IIA. Then, pharmacological clustering was applied to classify obtained hits, the anticancer module was analysed further. The top ten essential nodes in the anticancer module were obtained by ClusterONE. Functional units in the anticancer module were catalogued and validated by Gene Ontology (GO) analysis. Meanwhile, KEGG and Cell Signalling Technology Pathway were employed to provide pathway data for potential anticancer pathways construction. Finally, the pathways were plotted using Cytoscape 3.5.1. Furthermore, in vitro experiments with five carcinoma cell lines were conducted. RESULTS: A total of 258 proteins regulated by Tan IIA were identified through ALS and were visualized by protein network. Pharmacological clustering further sorted 68 proteins that intimately involved in cancer pathogenesis based on Gene Ontology. Subsequently, pathways on anticancer effect of Tan IIA were delineated. Five functional units were clarified according to literature: including regulation on apoptosis, proliferation, sustained angiogenesis, autophagic cell death, and cell cycle. The GO analysis confirmed the classification was statistically significant. The inhibiting influence of Tan IIA on p70 S6K/mTOR pathway was revealed for the first time. The in vitro experiments displayed the selectivity of Tan IIA on HeLa, MDA-MB-231, HepG2, A549, and ACHN cell lines, the IC50 values were 0.54 µM, 4.63 µM, 1.42 µM, 17.30 µM and 204.00 µM, respectively. This result further reinforced the anticancer effect of Tan IIA treatment. CONCLUSIONS: The current study provides a systematic methodology for discovering the coordination of the anticancer pathways regulated by Tan IIA via protein network. And it also offers a valuable guidance for systematic study on the therapeutic values of other herbs and their active compounds.

Development of models for classification of action between heat-clearing herbs and blood-activating stasis-resolving herbs based on theory of traditional Chinese medicine.

BACKGROUND: Action ("gongxiao" in Chinese) of traditional Chinese medicine (TCM) is the high recapitulation for therapeutic and health-preserving effects under the guidance of TCM theory. TCM-defined herbal properties ("yaoxing" in Chinese) had been used in this research. TCM herbal property (TCM-HP) is the high generalization and summary for actions, both of which come from long-term effective clinical practice in two thousands of years in China. However, the specific relationship between TCM-HP and action of TCM is complex and unclear from a scientific perspective. The research about this is conducive to expound the connotation of TCM-HP theory and is of important significance for the development of the TCM-HP theory. METHODS: One hundred and thirty-three herbs including 88 heat-clearing herbs (HCHs) and 45 blood-activating stasis-resolving herbs (BAHRHs) were collected from reputable TCM literatures, and their corresponding TCM-HPs/actions information were collected from Chinese pharmacopoeia (2015 edition). The Kennard-Stone (K-S) algorithm was used to split 133 herbs into 100 calibration samples and 33 validation samples. Then, machine learning methods including supported vector machine (SVM), k-nearest neighbor (kNN) and deep learning methods including deep belief network (DBN), convolutional neutral network (CNN) were adopted to develop action classification models based on TCM-HP theory, respectively. In order to ensure robustness, these four classification methods were evaluated by using the method of tenfold cross validation and 20 external validation samples for prediction. RESULTS: As results, 72.7-100% of 33 validation samples including 17 HCHs and 16 BASRHs were correctly predicted by these four types of methods. Both of the DBN and CNN methods gave out the best results and their sensitivity, specificity, precision, accuracy were all 100.00%. Especially, the predicted results of external validation set showed that the performance of deep learning methods (DBN, CNN) were better than traditional machine learning methods (kNN, SVM) in terms of their sensitivity, specificity, precision, accuracy. Moreover, the distribution patterns of TCM-HPs of HCHs and BASRHs were also analyzed to detect the featured TCM-HPs of these two types of herbs. The result showed that the featured TCM-HPs of HCHs were cold, bitter, liver and stomach meridians entered, while those of BASRHs were warm, bitter and pungent, liver meridian entered. CONCLUSIONS: The performance on validation set and external validation set of deep learning methods (DBN, CNN) were better than machine learning models (kNN, SVM) in sensitivity, specificity, precision, accuracy when predicting the actions of heat-clearing and blood-activating stasis-resolving based on TCM-HP theory. The deep learning classification methods owned better generalization ability and accuracy when predicting the actions of heat-clearing and blood-activating stasis-resolving based on TCM-HP theory. Besides, the methods of deep learning would help us to improve our understanding about the relationship between herbal property and action, as well as to enrich and develop the theory of TCM-HP scientifically.

An integrated strategy for rapid discovery and identification of the sequential piperine metabolites in rats using ultra high-performance liquid chromatography/high resolution mass spectrometery.

Piperine, one of the major bioactive constituents isolated from natural flavorings and medicinal-culinary herbs, possesses various biological activities. In the present study, an integrated strategy based on ultra high-performance liquid chromatography/high resolution mass spectrometry was established to reveal piperine metabolism in rats. First of all, post-acquisition data-mining methods, including high resolution extracted ion chromatograms (HREICs) and multiple mass defect filtering (MMDF), were used to screen piperine metabolite candidates in a full-scan HRMS1 level. Then, parent ion list-dynamic exclusion coupled with data-dependent data-acquisition method was utilized to acquire MSn datasets. In addition, the established reverse molecular assembly (RMA) approach based on paired diagnostic product ions (pDPIs) coupled with neutral loss fragments (NLFs) was used to ascertain and identify the major-to-trace piperine metabolites efficiently. And then, the calculated ClogP values were utilized to distinguish the positional isomers. As a result, a total of 148 piperine metabolites were detected and characterized tentatively. The results demonstrated that piperine mainly underwent hydrogenation, dehydrogenation, hydroxylation, glucuronide conjugation, sulfate conjugation, ring-cleavage, and their composite reactions. Our results not only provided novel and useful data to better understand the safety, toxicity and efficacy of this potential therapeutic agent, but also indicated that the proposed strategy was reliable for a rapid discovery and identification drug-related constituents in vivo.

Novelty application of multi-omics correlation in the discrimination of sulfur-fumigation and non-sulfur-fumigation Ophiopogonis Radix.

A rapid and sensitive approach to differentiate sulfur-fumigated (SF) Ophiopogonis Radix based on Multi-Omics Correlation Analysis (MOCA) strategy was first established. It was characterized by multiple data-acquisition methods (NIR, HPLC, and UHPLC-HRMS) based metabonomics and multivariate statistical analysis methods. As a result, SF and non-sulfur fumigated (NSF) Ophiopogonis Radix samples were efficaciously discriminated. Moreover, based on the acquired HRMS data, 38 sulfur-containing discriminatory markers were eventually characterized, whose NIR absorption could be in close correlation with the discriminatory NIR wavebands (5000-5200 cm-1) screened by NIR metabonomics coupled with SiPLS and 2D-COS methods. This results were also validated from multiple perspectives, including metabonomics analysis based on the discriminatory markers and the simulation of SF ophiopogonin D and Ophiopogonis Radix sample. In conclusion, our results first revealed the intrinsic mechanism of discriminatory NIR wavebands by means of UHPLC-HRMS analysis. Meanwhile, the established MOCA strategy also provided a promising NIR based differential method for SF Ophiopogonis Radix, which could be exemplary for future researches on rapid discrimination of other SF Chinese herbal medicines.

An Indoor Continuous Positioning Algorithm on the Move by Fusing Sensors and Wi-Fi on Smartphones.

Wi-Fi indoor positioning algorithms experience large positioning error and low stability when continuously positioning terminals that are on the move. This paper proposes a novel indoor continuous positioning algorithm that is on the move, fusing sensors and Wi-Fi on smartphones. The main innovative points include an improved Wi-Fi positioning algorithm and a novel positioning fusion algorithm named the Trust Chain Positioning Fusion (TCPF) algorithm. The improved Wi-Fi positioning algorithm was designed based on the properties of Wi-Fi signals on the move, which are found in a novel "quasi-dynamic" Wi-Fi signal experiment. The TCPF algorithm is proposed to realize the "process-level" fusion of Wi-Fi and Pedestrians Dead Reckoning (PDR) positioning, including three parts: trusted point determination, trust state and positioning fusion algorithm. An experiment is carried out for verification in a typical indoor environment, and the average positioning error on the move is 1.36 m, a decrease of 28.8% compared to an existing algorithm. The results show that the proposed algorithm can effectively reduce the influence caused by the unstable Wi-Fi signals, and improve the accuracy and stability of indoor continuous positioning on the move.

The effect of stroke and other components in Xing-Nao-Jing on the pharmacokinetics of geniposide.

ETHNOPHARMACOLOGICAL RELEVANCE: Geniposide is a bioactive substance derived from gardenia, which has been used in traditional Chinese preparation, such as "Xing-Nao-Jing" (XNJ) for stroke treatment. Stroke and the ingredients of herbal preparation affect the pharmacokinetics of geniposide. A comparative pharmacokinetic study of geniposide in stroke and sham-operated rats after administration of XNJ and geniposide was proceeded to evaluate the effect of stroke on pharmacokinetics of geniposide, while the influence of other components in XNJ was determined by using gardenia extract and geniposide-borneol compounds in rats with stroke to compare. MATERIALS AND METHODS: Stroke was induced by middle cerebral artery occlusion followed by reperfusion 2h later. Plasma concentration of geniposide was determined by HPLC. Various pharmacokinetic parameters were estimated from the plasma concentration versus time data using non-compartmental methods. RESULTS: The maximum plasma concentration (Cmax) and area under the curve (AUC0-t) in stroke after administration of XNJ were 5.97±3.82 µg/mL, and 570.06±274.32 µg·min/mL, respectively, which were 5 times compared with sham-operated rats or the stroke-afflicted rats given geniposide. In stroke, the Cmax and AUC(0-t) of geniposide-borneol group and gardenia extraction group were close to XNJ group and geniposide group, respectively. The geniposide-borneol group had a higher value. CONCLUSION: Stroke improved the absorption of geniposide in XNJ. Borneol may be the key ingredient in XNJ improving the absorption of geniposide.