Reducing toxicity and increasing efficiency: aconitine with liquiritin and glycyrrhetinic acid regulate calcium regulatory proteins in rat myocardial cell

Background: Compatibility of Radix Aconiti Carmichaeli and Liquorice is known to treat heart diseases such as heart failure and cardiac arrhythmias. This work answers the question that whether the active components (Aconitine, Liquiritin and Glycyrrhetinic Acid) of Radix Aconiti Carmichaeli and Liquorice could result in regulating intracellular calcium homeostasis and calcium cycling, and thereby verifies the therapeutic material basis.Materials and Methods: The myocardial cells were divided into twelve groups randomly as control group, Aconitine group, nine different dose groups that orthogonal combined with Aconitine, Liquiritin and Glycyrrhetinic Acid, and Verapamil group. The myocardial cellular survival rate and morphology were assessed. The expression of calcium regulation protein(RyR2、NCX1、DHPR-a1) in the myocardial cell by Western-blotting.Results: The results exhibited that Aconitine (120 uM) significantly damaged on myocardial cell, decreased the survival rate and expression of Na+/Ca2+ exchangers (NCX1) and dihydropteridine reducta-α1 (DHPR-a1), and increased the expression of ryanodine receptor type2 (RyR2) obviously. The compatibility groups (Aconitine, Liquiritin and Glycyrrhetinic Acid) all could against the damage on the myocardial cell by Aconitine at different levels.Conclusion: Aconitine with Liquiritin and Glycyrrhetinic Acid may regulate the expression of calcium-regulated proteins to protect myocardial cells from damage.Keywords: Aconitine, Liquiritin, Glycyrrhetinic Acid, myocardial cell, calcium regulator

Effects of Active Components of Fuzi and Gancao Compatibility on Bax, Bcl-2, and Caspase-3 in Chronic Heart Failure Rats

Hypaconitine (HA) and glycyrrhetinic acid (GA) are active components of Fuzi (Aconitum carmichaelii) and Gancao (Glycyrrhiza uralensis Fisch); they have been used in compatibility for chronic heart failure (CHF) from ancient times. The purpose of the present research was to explore whether apoptosis pathways were related with the protective effects of HA + GA against CHF rats or not. The rats were progressed with transverse-aortic constriction (TAC) operation for 4 weeks to build the CHF state, and then the Digoxin (1 mg/kg), HA (2.07 mg/kg), GA (25 mg/kg), and HA (2.07 mg/kg) + GA (25 mg/kg) were orally administrated to rats for 1 week. The levels of BNP and cTnI in the plasma were decreased in the HA + GA group, and the heart/body weight ratio (H/B) and left ventricular (LV) parameters of transthoracic echocardiography were also declined; moreover, the expressions of Bax, Bcl-2, and caspase-3 were all improved in the HA + GA group than other groups in the immunohistochemistry and western blot methods. In general, the data suggested that Fuzi and Gancao compatibility could protect the CHF rats from apoptosis, which provided a strong evidence for further searching for mechanisms of them

Re-ID done right: towards good practices for person re-identification

Training a deep architecture using a ranking loss has become standard for the person re-identification task. Increasingly, these deep architectures include additional components that leverage part detections, attribute predictions, pose estimators and other auxiliary information, in order to more effectively localize and align discriminative image regions. In this paper we adopt a different approach and carefully design each component of a simple deep architecture and, critically, the strategy for training it effectively for person re-identification. We extensively evaluate each design choice, leading to a list of good practices for person re-identification. By following these practices, our approach outperforms the state of the art, including more complex methods with auxiliary components, by large margins on four benchmark datasets. We also provide a qualitative analysis of our trained representation which indicates that, while compact, it is able to capture information from localized and discriminative regions, in a manner akin to an implicit attention mechanism

Developing New Oligo Probes to Distinguish Specific Chromosomal Segments and the A, B, D Genomes of Wheat (Triticum aestivum L.) Using ND-FISH

Non-denaturing FISH (ND-FISH) technology has been widely used to study the chromosomes of Triticeae species because of its convenience. The oligo probes for ND-FISH analysis of wheat (Triticum aestivum L.) chromosomes are still limited. In this study, the whole genome shotgun assembly sequences (IWGSC WGA v0.4) and the first version of the reference sequences (IWGSC RefSeq v1.0) of Chinese Spring (T. aestivum L.) were used to find new tandem repeats. One hundred and twenty oligo probes were designed according to the new tandem repeats and used for ND-FISH analysis of chromosomes of wheat Chinese Spring. Twenty nine of the 120 oligo probes produce clear or strong signals on wheat chromosomes. Two of the 29 oligo probes can be used to conveniently distinguish wheat A-, B-, and D-genome chromosomes. Sixteen of the 29 oligo probes only produce clear or strong signals on the subtelomeric regions of 1AS, 5AS, 7AL, 4BS, 5BS, and 3DS arms, on the telomeric regions of 1AL, 5AL, 2BS, 3BL, 6DS, and 7DL arms, on the intercalary regions of 4AL and 2DL arms, and on the pericentromeric regions of 3DL and 6DS arms. Eleven of the 29 oligo probes generate distinct signal bands on several chromosomes and they are different from those previously reported. In addition, the short and long arms of 6D chromosome have been confirmed. The new oligo probes developed in this study are useful and convenient for distinguishing wheat chromosomes or specific segments of wheat chromosomes

Machine Learning for Hydropower Scheduling: State of the Art and Future Research Directions

This paper investigates and discusses the current and future role of machine learning (ML) within the hydropower sector. An overview of the main applications of ML in the field of hydropower operations is presented to show the most common topics that have been addressed in the scientific literature in the last years. The objective is to provide recommendations for novel research directions that can be taken in the near future to cover those areas that have not been studied so far. The key contribution of this paper lies in a critical investigation of the state of the art of ML applications in hydropower scheduling. In light of the established literature available in the last years, this study identifies and discusses new roles that can be covered by ML, coupled with cyber-physical systems (CPSs), with a particular focus on short-term hydropower scheduling (STHS) challenges.publishedVersio

Machine Learning for Hydropower Scheduling: State of the Art and Future Research Directions

This paper investigates and discusses the current and future role of machine learning (ML) within the hydropower sector. An overview of the main applications of ML in the field of hydropower operations is presented to show the most common topics that have been addressed in the scientific literature in the last years. The objective is to provide recommendations for novel research directions that can be taken in the near future to cover those areas that have not been studied so far. The key contribution of this paper lies in a critical investigation of the state of the art of ML applications in hydropower scheduling. In light of the established literature available in the last years, this study identifies and discusses new roles that can be covered by ML, coupled with cyber-physical systems (CPSs), with a particular focus on short-term hydropower scheduling (STHS) challenges

Machine Learning for Hydropower Scheduling: State of the Art and Future Research Directions

This paper investigates and discusses the current and future role of machine learning (ML) within the hydropower sector. An overview of the main applications of ML in the field of hydropower operations is presented to show the most common topics that have been addressed in the scientific literature in the last years. The objective is to provide recommendations for novel research directions that can be taken in the near future to cover those areas that have not been studied so far. The key contribution of this paper lies in a critical investigation of the state of the art of ML applications in hydropower scheduling. In light of the established literature available in the last years, this study identifies and discusses new roles that can be covered by ML, coupled with cyber-physical systems (CPSs), with a particular focus on short-term hydropower scheduling (STHS) challenges

Combination of Radix Astragali and Safflower Promotes Angiogenesis in Rats with Ischemic Stroke via Silencing PTGS2

Promotion of angiogenesis and restoration of the blood flow in the ischemic penumbra is an effective treatment for patients with ischemic stroke (IS). Radix astragali-safflower (AS), a classic herbal pair for accelerating blood circulation and dispersing blood stasis, has been used for thousands of years to treat patients with IS in China. Even so, the mechanism of the treatment of IS by AS is still undecipherable. In the current study, network pharmacology was firstly employed to unveil the mechanism of AS in treating IS, which showed that AS might promote angiogenesis associated with PTGS2 silence. Middle cerebral artery occlusion/reperfusion (MCAO/R) model rats were then used as the experimental animals to verify the prediction result. The experimental results revealed that treatment with AS improved the cerebral infarct volume, neurological damage, and cerebral histopathological damage; inhibited cell apoptosis; increased the contents of PDGF-BB, EPO, and TGF-β1; and reduced the levels of PF4, Ang-2, and TIMP-1 in serum. Immunohistochemical staining demonstrated that the expression of PTGS2 was dramatically increased in the hippocampus and cerebral cortex of rats with MCAO/R, and this trend was reversed by the treatment of AS. Immunofluorescent staining expressed that AS reversed the down-regulation of VEGF and further promoted the expression of CD31, which indicated that AS promoted angiogenesis in MCAO/R rats. The abnormal protein or mRNA expression of PTGS2, PGI2, bFGF, TSP-1, and VEGF in the penumbra were transposed by AS or Celecoxib (an inhibitor of PTGS2). In conclusion, the protective mechanism of AS for IS promoted angiogenesis and was involved with PTGS2 silence

Combination of Radix Astragali and Safflower Promotes Angiogenesis in Rats with Ischemic Stroke via Silencing PTGS2

Promotion of angiogenesis and restoration of the blood flow in the ischemic penumbra is an effective treatment for patients with ischemic stroke (IS). Radix astragali-safflower (AS), a classic herbal pair for accelerating blood circulation and dispersing blood stasis, has been used for thousands of years to treat patients with IS in China. Even so, the mechanism of the treatment of IS by AS is still undecipherable. In the current study, network pharmacology was firstly employed to unveil the mechanism of AS in treating IS, which showed that AS might promote angiogenesis associated with PTGS2 silence. Middle cerebral artery occlusion/reperfusion (MCAO/R) model rats were then used as the experimental animals to verify the prediction result. The experimental results revealed that treatment with AS improved the cerebral infarct volume, neurological damage, and cerebral histopathological damage; inhibited cell apoptosis; increased the contents of PDGF-BB, EPO, and TGF-β1; and reduced the levels of PF4, Ang-2, and TIMP-1 in serum. Immunohistochemical staining demonstrated that the expression of PTGS2 was dramatically increased in the hippocampus and cerebral cortex of rats with MCAO/R, and this trend was reversed by the treatment of AS. Immunofluorescent staining expressed that AS reversed the down-regulation of VEGF and further promoted the expression of CD31, which indicated that AS promoted angiogenesis in MCAO/R rats. The abnormal protein or mRNA expression of PTGS2, PGI2, bFGF, TSP-1, and VEGF in the penumbra were transposed by AS or Celecoxib (an inhibitor of PTGS2). In conclusion, the protective mechanism of AS for IS promoted angiogenesis and was involved with PTGS2 silence

A Tightly Integrated Navigation Method of SINS, DVL, and PS Based on RIMM in the Complex Underwater Environment

Navigation and positioning of autonomous underwater vehicles (AUVs) in the complex and changeable marine environment are crucial and challenging. For the positioning of AUVs, the integrated navigation of the strap-down inertial navigation system (SINS), Doppler velocity log (DVL), and pressure sensor (PS) has a common application. Nevertheless, in the complex underwater environment, the DVL performance is affected by the current and complex terrain environments. The outliers in sensor observations also have a substantial adverse effect on the AUV positioning accuracy. To address these issues, in this paper, a novel tightly integrated navigation model of the SINS, DVL, and PS is established. In contrast to the traditional SINS, DVL, and PS tightly integrated navigation methods, the proposed method in this paper is based on the velocity variation of the DVL beam by applying the DVL bottom-track and water-track models. Furthermore, a new robust interacting multiple models (RIMM) information fusion algorithm is proposed. In this algorithm, DVL beam anomaly is detected, and the Markov transfer probability matrix is accordingly updated to enable quick model matching. By simulating the motion of the AUV in a complex underwater environment, we also compare the performance of the traditional loosely integrated navigation (TLIN) model, the tightly integrated navigation (TTIN) model, and the IMM algorithm. The simulation results show that because of the PS, the velocity and height in the up-change amplitude of the four algorithms are small. Compared with the TLIN algorithm in terms of maximum deviation of latitude and longitude, the RIMM algorithm also improves the accuracy by 39.1243 m and 26.4364 m, respectively. Furthermore, compared with the TTIN algorithm, the RIMM algorithm improves latitude and longitude accuracy by 1.8913 m and 11.8274 m, respectively. A comparison with IMM also shows that RIMM improves the accuracy of latitude and longitude by 1.1506 m and 7.2301 m, respectively. The results confirm that the proposed algorithm suppresses the observed noise and outliers of DVL and further achieves quick conversion between different DVL models while making full use of the effective information of the DVL beams. The proposed method also improves the navigation accuracy of AUVs in complex underwater environments