Coronary heart disease prediction method fusing domain-adaptive transfer learning with graph convolutional networks (GCN).

Graph convolutional networks (GCNs) have achieved impressive results in many medical scenarios involving graph node classification tasks. However, there are difficulties in transfer learning for graph representation learning and graph network models. Most GNNs work only in a single domain and cannot transfer the learned knowledge to other domains. Coronary Heart Disease (CHD) is a high-mortality disease, and there are non-public and significant differences in CHD datasets for current research, which makes it difficult to perform unified transfer learning. Therefore, in this paper, we propose a novel adversarial domain-adaptive multichannel graph convolutional network (DAMGCN) that can perform graph transfer learning on cross-domain tasks to achieve cross-domain medical knowledge transfer on different CHD datasets. First, we use a two-channel GCN model for feature aggregation using local consistency and global consistency. Then, a uniform node representation is generated for different graphs using an attention mechanism. Finally, we provide a domain adversarial module to decrease the discrepancies between the source and target domain classifiers and optimize the three loss functions in order to accomplish source and target domain knowledge transfer. The experimental findings demonstrate that our model performs best on three CHD datasets, and its performance is greatly enhanced by graph transfer learning.

Acute coronary syndrome risk prediction based on gradient boosted tree feature selection and recursive feature elimination: A dataset-specific modeling study.

Acute coronary syndrome (ACS) is a serious cardiovascular disease that can lead to cardiac arrest if not diagnosed promptly. However, in the actual diagnosis and treatment of ACS, there will be a large number of redundant related features that interfere with the judgment of professionals. Further, existing methods have difficulty identifying high-quality ACS features from these data, and the interpretability work is insufficient. In response to this problem, this paper uses a hybrid feature selection method based on gradient boosting trees and recursive feature elimination with cross-validation (RFECV) to reduce ACS feature redundancy and uses interpretable feature learning for feature selection to retain the most discriminative features. While reducing the feature set search space, this method can balance model simplicity and learning performance to select the best feature subset. We leverage the interpretability of gradient boosting trees to aid in understanding key features of ACS, linking the eigenvalue meaning of instances to model risk predictions to provide interpretability for the classifier. The data set used in this paper is patient records after percutaneous coronary intervention (PCI) in a tertiary hospital in Fujian Province, China from 2016 to 2021. In this paper, we experimentally explored the impact of our method on ACS risk prediction. We extracted 25 key variables from 430 complex ACS medical features, with a feature reduction rate of 94.19%, and identified 5 key ACS factors. Compared with different baseline methods (Logistic Regression, Random Forest, Gradient Boosting, Extreme Gradient Boosting, Multilayer Perceptron, and 1D Convolutional Networks), the results show that our method achieves the highest Accuracy of 98.8%.

All-Cause Death Prediction Method for CHD Based on Graph Convolutional Networks.

Coronary heart disease (CHD) has become one of the most serious public health issues due to its high morbidity and mortality rates. Most of the existing coronary heart disease risk prediction models manually extract features based on shallow machine learning methods. It only focuses on the differences between local patient features and ignores the interaction modeling between global patients. Its accuracy is still insufficient for individualized patient management strategies. In this paper, we propose CHD prediction as a graph node classification task for the first time, where nodes can represent individuals in potentially diseased populations and graphs intuitively represent associations between populations. We used an adaptive multi-channel graph convolutional neural network (AM-GCN) model to extract graph embeddings from topology, node features, and their combinations through graph convolution. Then, the adaptive importance weights of the extracted embeddings are learned by using an attention mechanism. For different situations, we model the relationship of the CHD population with the population graph and the K-nearest neighbor graph method. Our experimental evaluation explored the impact of the independent components of the model on the CHD disease prediction performance and compared it to different baselines. The experimental results show that our new model exhibits the best experimental results on the CHD dataset, with a 1.3% improvement in accuracy, a 5.1% improvement in AUC, and a 4.6% improvement in F1-score compared to the nongraph model.

Morphology-Dependent Electrocatalytic Performance of a Two-Dimensional Nickel-Iron MOF for Oxygen Evolution Reaction.

Developing highly efficient, low-cost, and durable oxygen evolution reaction (OER) electrocatalysts is extraordinarily desirable for achieving clean and sustainable hydrogen energy. Metal-organic frameworks (MOFs) are emerging as attractive candidates for OER electrocatalysts. Herein, a two-dimensional Fe-Ni MOF of Fe(py)2Ni(CN)4 (py = pyridine) is synthesized controllably to generate various nanostructures, including nanoboxes, nanocubes, nanoplates, and nanosheets. Since different morphologies expose different active crystal planes and generate disparate intrinsic active sites, these nanostructures exhibit obviously different electrocatalytic activities. Particularly, the nanoboxes with a hollow structure display superior electrocatalytic activity and stability for OER due to greater active surface area and higher intrinsic activity of the exposed crystal planes, delivering a low overpotential of 285 mV at 10 mA cm-2 and a small Tafel value of 50.9 mV dec-1 in a 1.0 M KOH solution. The morphology-dependent electrocatalytic properties demonstrated in this work provide an efficient strategy to optimize MOF precatalysts for electrochemical energy storage and conversion.

Pharmacokinetic Study of Hypaphorine, a Potential Agent for Treating Osteoclast-based Bone Loss, on Rats Using LC-MS/MS.

AIMS AND OBJECTIVES: A high-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for determining hypaphorine, a potential agent for treating osteoclast- based bone loss, was developed and validated in rat plasma. MATERIALS AND METHODS: Plasma samples were pretreated by the protein precipitation. Chromatographic separation was performed using an Inertsil ODS-3 column (50 mm × 4.6 mm, 5 µm). The mobile phase consisted of water (containing 0.1% formic acid) and acetonitrile in a gradient mode at a flow rate of 0.5 mL/min. The transitions from protonated precursor ion [M + H]+ to the particular daughter ion were acquired using selected reaction monitoring (SRM). The mass transitions of hypaphorine and IS were found to be 247 → 188 and m/z 219 → 188, respectively. The method was validated in terms of selectivity, linearity, accuracy and precision, extraction recovery and matrix effect, stability, and carryover. RESULTS: It showed good linearity over the range of 1-2000 ng/mL (R2 = 0.9978). The intra-batch accuracy was within 93.95-105.81%, and the precision was within 4.92-11.53%. The inter-batch accuracy was within 96.18-100.39% with a precision of 6.22-11.23%. The extraction recovery and matrix factors were acceptable. CONCLUSION: The simple and rapid method was successfully applied to the pharmacokinetic study in rats following oral administration of hypaphorine at the doses of 0.5, 1.5, and 4.5 mg/kg.

Decoration of nickel hexacyanoferrate nanocubes onto reduced graphene oxide sheets as high-performance cathode material for rechargeable aqueous zinc-ion batteries.

Prussian blue analogues (PBA) have attracted much attention in energy research due to their unique three-dimensional open framework structure, adjustable metal ions, and facile synthesis. However, the application of PBA as a cathode material for aqueous zinc-ion batteries (ZIBs) is restricted by its poor cycling performance and lower capacity. In this paper, we develop a new PBA-based hybrid cathode material for aqueous ZIBs by loading uniform nickel hexacyanoferrate (NiHCF) nanocubes onto reduced graphene oxide (RGO) sheets. In the NiHCF/RGO hybrid, NiHCF nanoparticles are well anchored on the RGO layers, forming a conductive network. The strong synergy between NiHCF and highly conductive RGO effectively increases the specific surface area, accelerates the electron and ion transport, and inhibits the structural collapse of the NiHCF/RGO electrode during the Zn2+ insertion/extraction process. Benefiting from the above advantages, the NiHCF/RGO hybrid exhibits a remarkable reversible capacity of 94.5 mAh g-1 at a current density of 5 mA g-1, excellent rate performance of 50.1 mAh g-1 at 200 mA g-1, and enhanced cycling stability with a capacity retention of 80.3% after 1000 cycles at 200 mA g-1. This work provides a simple and effective way to improve the electrochemical performance of PBA-based cathodes for aqueous ZIBs application.

Pharmaceutical excipient salts effect on micellization and drug solubilization of PEO-PPO-ph-PPO-PEO block copolymer.

Hydrophobic modification PEO-PPO copolymer BP123 was synthesized, with two aromatic rings in the centre linked to PEO-PPO blocks, and the identical PEO and PPO block numbers were possessed with commercial copolymer P123. The influence of three common pharmaceutical excipient salts sodium chloride (NaCl), sodium citrate (NaCA) and sodium benzoate (NaBZ) on self-assembly behaviors of BP123 and P123 was investigated via cloud point, surface tension, pyrene fluorescence and dynamic light scattering. Solubilization for hydrophobic drug simvastatin (SV) and in vitro drug release behavior were assessed accordingly. In the presence of NaCl or NaCA, cloud point and critical micellization concentration (CMC) decreased, micelles became more hydrophobic, micellar size and drug solubilization increased, drug release rate slowed, and the impact of NaCA was more significant than NaCl. Oppositely, cloud point and CMC increased with the addition of NaBZ. NaBZ could participate in the formation of micelles by hydrophobic aromatic ring, which greatly raised solubilization of SV. Moreover, a different performance occurred when NaBZ was added to BP123 or P123, due to the hydrophobic benzene rings in BP123, which prominently enhanced the interaction with hydrophobic drug, leading to obvious delay of drug release for BP123. This work is conducive to turning copolymer property in diverse pharmaceutical applications and in drug delivery systems as drug carriers.

[Analysis on quality value transmitting of substance benchmarks of Linggui Zhugan Decoction].

By preparing 10 batches of the material reference of Linggui Zhugan Decoction,the methodology of the characteristic spectrum of the material reference was created. The creaming rate range,the contents and the transfer rate range of cinnamaldehyde,glycyrrhizin and glycyrrhizic acid,the characteristic peaks and the similarity range of the characteristic spectrum of Linggui Zhugan Decoction were determined to clarify key quality attributes of the material reference of Linggui Zhugan Decoction. In the 10 batches of the material reference of Linggui Zhugan Decoction,the similarity of characteristic spectrum was higher than 0. 9. Furthermore,after summarizing the characteristic peak information,we knew that Fuling had two characteristic peaks,Guizhi had six characteristic peaks,Baizhu had two characteristic peaks and Gancao had 11 characteristic peaks. The average creaming rate of the material reference of the ten batches was( 12. 13 ± 0. 35) %. The average content of cinnamaldehyde was 0. 32%,the average transfer rate was 10. 69%,the content of cinnamaldehyde in the different batches was between 0. 22% and 0. 42%,and the transfer rate was between 7. 48% and13. 90%. The average content of glycyrrhizin was 0. 84%,the average transfer rate was 50. 39%,the content of glycyrrhizin in the different batches was between 0. 42% and 1. 26%,and the transfer rate was between 35. 27% and 65. 51%. The average content of glycyrrhizic was 1. 88%,the average transfer rate was 40. 74%,the content of glycyrrhizic in the different batches was between 0. 94% and2. 82%,and the transfer rate was between 28. 52% and 52. 96%. In this paper,the quality value transmitting of substance benchmarks of Linggui Zhugan Decoction was analyzed by the combination of characteristic spectrum,creaming rate and the content of index component. A scientific and stable method was preliminarily established,which provided scientific basis for the quality control and formulation development of Linggui Zhugan Decoction.

Microneedle-Assisted Percutaneous Delivery of Paeoniflorin-Loaded Ethosomes.

Paeoniflorin, the main component of total glucosides of paeony (TGP), shows good therapeutic effects in arthritis, but has low bioavailability when administered orally. Avoiding such a deficiency for topical administration would expand its clinical application. This study aimed to avoid these limitations by using nanotechnology (ethosomes) and a physical approach (microneedles). Paeoniflorin-loaded ethosomal formulation (TGP-E) was optimized and evaluated in terms of entrapment efficiency (EE), particle size (PS), zeta potential (ZP), polydispersity index (PDI) and morphology. TGP-E was prepared by the hot injection method and optimized by single-factor tests and an orthogonal experimental design. The optimized paeoniflorin-loaded ethosomes had EE of 27.82 ± 1.56%, PS of 137.9 ± 7.57 nm with PDI of 0.120 ± 0.005, ZP of -0.74 ± 0.43 mV. Ethosomes showed a nearly spherical shape under the transmission electron microscope (TEM). The optimal microneedle-assisted (MN-assisted) conditions were obtained at a microneedle length of 500 µm, a pressure of 3 N and an action time of 3 min. The cumulative penetration amounts (Qn) of TGP solution transdermal (ST) and MN-assisted TGP solution transdermal (MST) were 24.42 ± 8.35 µg/cm² and 548.11 ± 10.49 µg/cm², respectively. Qn of TGP-E transdermal (PT) and MN-assisted TGP-E transdermal (MPT) were 54.97 ± 4.72 µg/cm² and 307.17 ± 26.36 µg/cm², respectively. These findings indicate that use of ethosomes and microneedles can both enhance the penetration ofpaeoniflorin, but for the water-soluble drug, there is no obvious synergism between nanotechnology and microneedles for enhancing penetration in a transdermal drug delivery system.

Effect of Red Ginseng Extract on the Pharmacokinetics of Aspirin Metabolite in Sprague Dawley Rats.

Objective To investigate whether red ginseng extract can affect the pharmacokinetics of aspirin in Sprague Dawley (SD) rats.Methods Totally, 12 male SD rats were randomly and uniformly divided into the aspirin group (aspirin 10.42 mg·kg -1) and the combined group (red ginseng extraction 0.5 mg·g -1 + aspirin 10.42 mg·kg -1). After intragastric administration of drugs, blood samples (0.5 ml once) were drawn from orbit at 0.083, 0.25, 0.5, 1, 2, 4, 6, 8, 10 and 12 hours after dosing. Plasma concentration of salicylic acid (metabolite of aspirin) was detected with ultraviolet-visible high performance liquid chromatography (HPLC). The reliability of the procedure was verified with respect to specificity, linearity, accuracy, precision, extraction recovery and matrix effect, and stability. Pharmacokinetics of salicylic acid was evaluated by using non-compartmental model. Results The method was proved to be validated. Compared with the aspirin group, area under the curve (AUC 0-t) and maximum concentration of salicylic acid in rats of the combined group increased obviously (P<0.01), while clearance rate (CLz/F) decreased clearly (P<0.05).Conclusion The in vivo study showed that red ginseng extract can help the internal absorption of aspirin, and delay the in vivo metabolism of aspirin.

[Effect of paeoniflorin and menthol on membrane fluidity, Na⁺-K⁺-ATPase activity and Ca²âº-ATPase activity during transport of puerarin in Calu-3 cell].

The aim of this research is to investigate the effects of paeoniflorin and menthol on the physiological function of Calu-3 cell membrane during the transport of puerarin. Calu-3 cell was used as the in vitro cell model to simulate nasal mucosa tissues, and the cell membrane fluidity, Na⁺-K⁺-ATPase activity and Ca²âº-ATPase activity were detected by fluorescence recovery after photobleaching(FRAP) and ultramicro enzyme activity testing, in order to explore the mechanism of compatible drugs on promoting puerarin transport. The results showed that when puerarin associated with low, middle and high concentration of menthol or both paeoniflorin and menthol, the fluorescence recovery rate was increased significantly, while Na⁺-K⁺-ATPase activity had no significant change and Ca²âº-ATPase activity was enhanced significantly as compared with puerarin alone. Therefore, it was concluded that menthol had the abilit of promoting the transport and the mechanism might be related to increasing membrane fluidity and activating Ca²âº-ATPase.

[The molecular identification of licorice species and the quality evaluation of licorice slices].

Licorice is one of the most common herbs in traditional Chinese medicine, and classified as top grade in Shen Nong Ben Cao Jing. There are three different original plants of licorice stipulated in Chinese Pharmacopeia, Glycyrrhiza uralensis Fisch., Glycyrrhiza glabra L., and Glycyrrhiza inflata Bat. However, previous investigation showed that the pharmacodynamic effects of the three licorices were quite different. It is very difficult to identify them by the classical identification methods. In order to establish a fast and effective identification method, we collected 240 licorice plants from 21 populations of 7 provinces, and amplified their ITS and psbA-trnH sequences. ITS sequences with a full length of 616 bp and psbA-trnH sequences with a full length of 389 bp were obtained separately. Using DNAMAN to analyze these sequences, 4 variable sites were found in ITS sequences and 2 ITS haplotypes were determined, and 3 variable sites were found in psbA-trnH sequences and 4 psbA-trnH haplotypes were determined. With the combination analysis of ITS and psbA-trnH sequences, the molecular identification method of original licorice was established. Using this method, 40 samples of licorice slices collected from 4 main herbal material markets in China were identified successfully. Furthermore, the contents of 2 triterpenes, 18α-glycyrrhizic acid and 18ß-glycyrrhizic acid, and 4 flavonoids, liquiritin, isoliquiritin, liquiritigenin, and isoliquiritigenin in these licorice pieces were examined by HPLC and the results were analyzed using SPSS 21.0. This study provides a new method in identification of licorice, which may serve as a guideline for quality control of licorice slices.