Prediction of key quality attributes in Salvia miltiorrhiza standard decoction using a Gaussian process regression model.

INTRODUCTION: Nonstationary, nonlinear mass transfer in traditional Chinese medicine (TCM) extraction poses challenges to correlating process characteristics with quality parameters, particularly in defining clear parameter ranges for the process. OBJECTIVES: The aim of the study was to provide a solution for quality consistency analysis in TCM preparation processes. MATERIALS AND METHODS: Salvia miltiorrhiza was taken as an example for 15 batches of standard decoction. Using aqueous extract, alcoholic extract, and the content of salvianolic acid B as herb material key quality attributes, multiple nonlinear regression, Gaussian process regression, and artificial neural network models were employed to predict the key quality attributes including the paste yield, the content of salvianolic acid B, and the transfer rate. The evaluation criteria were root mean square error, mean absolute percentage error, and R2. RESULTS: The Gaussian process regression model had the best prediction effect on the paste yield, the content of salvianolic acid B, and the transfer rate, with R2 being 0.918, 0.934, and 0.919, respectively. Utilizing Gaussian process regression model confidence intervals, along with Shewhart control and intervals optimized through process capability index analysis, the quality control range of the standard decoction was determined as follows: paste yield, 25.14%-33.19%; salvianolic acid B content, 2.62%-4.78%; and transfer rate, 56.88%-64.80%. CONCLUSION: This study combined the preparation process of standard decoction with the Gaussian process regression model, accurately predicted the key quality attributes, and determined the quality parameter range by using process analysis tools, providing a new idea for the quality consistency standard of TCM processes.

Detection of trace components in Xiangdan injection of Dalbergia odorifera based on microextraction and back-extraction along with bar-form-diagram strategy.

Xiangdan Injection are commonly used traditional Chinese medicine formulations for the clinical treatment of cardiovascular diseases. However, the trace components of Dalbergia odorifera in Xiangdan Injection pose a challenge for evaluating its quality due to the difficulty of detection. This study proposes a technology combining dispersive liquid-liquid microextraction and back-extraction (DLLME-BE) along with Bar-Form-Diagram (BFD) to address this issue. The proposed combination method involves vortex-mixing tetradecane, which has a lower density than water, with the sample solution to facilitate the transfer of the target components. Subsequently, a new vortex-assisted liquid-liquid extraction step is performed to enrich the components of Dalbergia odorifera in acetonitrile. The sample analysis was performed on HPLC-DAD, and a clear overview of the chemical composition was obtained by integrating spectral and chromatographic information using BFD. The combination of BFD and CRITIC-TOPSIS strategies was used to optimize the process parameters of DLLME-BE. The determined optimal sample pre-treatment process parameters were as follows: 200 µL extraction solvent, 60 s extraction time, 50 µL back-extraction solvent, and 90 s back-extraction time. Based on the above strategy, a total of 29 trace components, including trans-nerolidol, were detected in the Xiangdan Injection. This combination technology provides valuable guidance for the enrichment analysis of trace components in traditional Chinese medicines.

Improving the geographical origin classification of Radix glycyrrhizae (licorice) through hyperspectral imaging assisted by U-Net fine structure recognition.

Radix glycyrrhizae (licorice) is extensively employed in traditional Chinese medicine, and serves as a crucial raw material in industries such as food and cosmetics. The quality of licorice from different origins varies greatly, so classification of its geographical origin is particularly important. This study proposes a technique for fine structure recognition and segmentation of hyperspectral images of licorice using deep learning U-Net neural networks to segment the tissue structure patterns (phloem, xylem, and pith). Firstly, the three partitions were separately labeled using the Labelme tool, which was utilized to train the U-Net model. Secondly, the obtained optimal U-Net model was applied to predict three partitions of all samples. Lastly, various machine learning models (LDA, SVM, and PLS-DA) were trained based on segmented hyperspectral data. In addition, a threshold method and a circumcircle method were applied to segment licorice hyperspectral images for comparison. The results revealed that compared with the threshold segmentation method (which yielded SVM classifier accuracies of 99.17%, 91.15%, and 92.50% on the training set, validation set, and test set, respectively), the U-Net segmentation method significantly enhanced the accuracy of origin classification (99.06%, 94.72% and 96.07%). Conversely, the circumcircle segmentation method did not effectively improve the accuracy of origin classification (99.65%, 91.16% and 92.13%). By integrating Raman imaging of licorice, it can be inferred that the U-Net model, designed for region segmentation based on the inherent tissue structure of licorice, can effectively improve the accuracy origin classification, which has positive significance in the development of intelligence and information technology of Chinese medicine quality control.

Study on Mechanical Properties and Degradation Behavior of Magnesium Alloy Vascular Clip.

The Mg alloy vascular clip has biodegradability and good biocompatibility, which can improve the convenience and safety of clinical application. However, the Mg alloy vascular clip also has some disadvantages, such as an unreasonable structure design and a degradation rate which is too fast. In this study, the process of clamping blood vessels with a biodegradable Mg alloy (Mg-Zn-Nd-Zr and Mg-Zn-Nd) general V-type vascular clip was simulated by finite element simulation software (Abaqus). A new type of vascular clip, the P-type vascular clip, was analyzed and investigated through simulation. The differences between Mg alloy vascular clips of V-type and P-type were analyzed by finite element simulation. In addition, the effects of Zr element on the mechanical properties and corrosion resistance of P-type vascular clips were also investigated to improve the mechanical stability. The results show that during the V-type vascular clip closure of Mg-Zn-Nd-Zr alloy, this clip has some problems, such as uneven distribution of blood vessel stress, crevices in blood vessels and stress concentration. The improved P-type vascular clip has uniform closure, and there is no gap in the blood vessel, which can effectively avoid stress concentration. The improved P-type vascular clip is well closed and can effectively avoid stress concentration. The corrosion resistance of the Mg-Zn-Nd-Zr alloy P-type clip was better than that of the Mg-Zn-Nd alloy P-type clip (degradation rate of 2.02 mm/y and 2.61 mm/y on the 7th day, respectively). Mg-Zn-Nd-Zr alloy The P-type vascular clip remained closed even on the 7th day, which could meet the requirements of clinical application.

Efficient macrocyclization facilitated by skeleton preorganization.

Reported here is the efficient macrocyclization facilitated by skeleton preorganization. A pyridylcarbazole macrocycle and a phenylpyridylcarbazole macrocycle was synthesized in yield up to 75%. Single-crystal structures and theoretic computation uncovered that the skeleton preorganization promoted the formation of cyclization-favorable conformation of noncyclic precursors via π⋯π interactions. This result provided a new approach for the efficient syntheses of macrocycles.

Network pharmacology and molecular docking to explore the mechanism of Sheng Xue Bao mixture against iron deficiency anemia.

Based on network pharmacology and molecular docking, we investigated the mechanism of action of Sheng Xue Bao mixture (SXBM) in treating iron deficiency anemia (IDA). We screened the HERB and traditional Chinese medicine systems pharmacology database and analysis platform databases to identify the active ingredients and targets of SXBM. The targets associated with "iron deficiency anemia" were collected from GeneCards, TTD, and OMIM databases. A component-target interaction network was constructed using Cytoscape 3.8.2. The protein-protein interaction network of candidate targets was generated using the STRING database and visualized with Cytoscape 3.8.2 software. Core modules obtained from clustering analysis were subjected to Gene Ontology and Kyoto encyclopedia of genes and genomes enrichment analysis. Finally, molecular docking validation of key targets and active components was performed using Autodock Vina software. A total of 174 active components and 111 genes were identified as potential active components and targets for IDA treatment, including quercetin, kaempferol, luteolin, beta-sitosterol, and other flavonoids as main active components. Gene Ontology enrichment analysis show that interleaved genes are enriched in 2328 biological processes, 71 cellular component expression processes, and 157 molecular function processes. Kyoto encyclopedia of genes and genomes analysis mainly envolved Prostate cancer, Hepatitis B, Kaposi sarcoma-associated herpesvirus infection, Endocrine resistance, Lipid and atherosclerosis, Central carbon metabolism in cancer, Human cytomegalovirus infection and HIF-1 signaling pathway. STAT3, SRC, PIK3R1, and GRB2 were selected as core targets. The molecular docking results demonstrated strong interactions between key components and their respective target proteins. Network pharmacological analysis suggested that SXBM could treat IDA by regulating various biological processes and related signaling pathways. It laid the foundation for further elucidating the molecular mechanism of SXBM treatment of IDA.

Applications of Hyperspectral Imaging Technology Combined with Machine Learning in Quality Control of Traditional Chinese Medicine from the Perspective of Artificial Intelligence: A Review.

Traditional Chinese medicine (TCM) is the treasure of China, and the quality control of TCM is of crucial importance. In recent years, with the quick rise of artificial intelligence (AI) and the rapid development of hyperspectral imaging (HSI) technology, the combination of the two has been widely used in the quality evaluation of TCM. Machine learning (ML) is the core wisdom of AI, and its progress in rapid analysis and higher accuracy improves the potential of applying HSI to the field of TCM. This article reviewed five aspects of ML applied to hyperspectral data analysis of TCM: partition of data set, data preprocessing, data dimension reduction, qualitative or quantitative models, and model performance measurement. The different algorithms proposed by researchers for quality assessment of TCM were also compared. Finally, the challenges in the analysis of hyperspectral images for TCM were summarized, and the future works were prospected.

An intelligent extraction approach of feature information from three-dimensional DAD chromatogram for integrated quality control of traditional Chinese medicines: Gardenia jasminoides root as an example.

Traditional Chinese medicine (TCM) fingerprinting, which has the characteristics of holism and ambiguity, is a conventional strategy for the holistic quality control of TCMs. However, the fingerprinting of TCMs at the current stage generally adopts a single wavelength or few wavelengths, lacking the effective utilization of diode-array detector (DAD) chromatogram data. This study proposes an intelligent extraction approach of feature information from a three-dimensional DAD chromatogram to establish a novel bar-form-diagram (BFD) for integrated quality control of TCMs. The BFD was automatically established by the chromatographic and spectral information of a complex hybrid system in a DAD chromatogram. This covered the peak areas of target compositions at the optimal absorption wavelength. Taking 27 batches of Gardenia jasminoides root as samples, the BFD combined with chemometrics was applied for assessing the quality of samples completely, which improved the accuracy of origin classification using hierarchical cluster analysis, principal component analysis, soft independent modeling of class analogy and orthogonal partial least squares discriminant analysis. Single-wavelength fingerprinting and BFD used 23 and 38 common peaks as variables respectively, and the adjusted rand index results of the single wavelength and BFD were 0.559 and 0.819, respectively. Compared with the ergodic methods of each single wavelength, the peak recognition method in this study improved the operation speed from 180 s to 4 s and the computational complexity. The established BFD approach performed more abundant characteristic information of chemical components of TCMs and more accurate origin classification ability, and it had great advantages in the overall quality control of TCMs.

Recognition of the rhizome of red ginseng based on spectral-image dual-scale digital information combined with intelligent algorithms.

Red ginseng is a widely used and extensively researched food and medicinal product with high nutritional value, derived from steamed fresh ginseng. The components in various parts of red ginseng differ significantly, resulting in distinct pharmacological activities and efficacies. This study proposed to establish a hyperspectral imaging technology combined with intelligent algorithms for the recognition of different parts of red ginseng based on the dual-scale of spectrum and image information. Firstly, the spectral information was processed by the best combination of first derivative as pre-processing method and partial least squares discriminant analysis (PLS-DA) as classification model. The recognition accuracy of the rhizome and the main root of red ginseng is 96.79% and 95.94% respectively. Then, the image information was processed by the You Only Look Once version 5 small (YOLO v5s) model. The best parameter combination is epoch = 30, learning rate = 0.01, and activation function is leaky ReLU. In the red ginseng dataset, the highest accuracy, recall and mean Average Precision at IoU (Intersection over Union) threshold 0.5 (mAP@0.5) were 99.01%, 98.51% and 99.07% respectively. The application of spectrum-image dual-scale digital information combined with intelligent algorithms in the recognition of red ginseng is successful, which provides a positive significance for the online and on-site quality control and authenticity identification of crude drugs or fruits.

PCSK-9 inhibitors: a new direction for the future treatment of ischemic stroke.

Ischemic stroke, the most prevalent and serious manifestation of cerebrovascular disease, is the main cause of neurological problems that require hospitalization, resulting in disability and death worldwide. Currently, clinical practice focuses on the effective management of blood lipids as a crucial approach to preventing and treating ischemic stroke. In recent years, a great breakthrough in ischemic stroke treatment has been witnessed with the emergence and use of a novel lipid-lowering medication, Proprotein convertase subtilisin kexin type 9 (PCSK9) inhibitor. And its remarkable potential for reducing the occurrence of ischemic stroke is being acknowledged. This article aims to provide a comprehensive review, encompassing the association between PCSK9 and the heightened risk of ischemic stroke, the mechanisms, and the extensive evidence supporting the proven efficacy of PCSK9 inhibitors in clinical practice. Through this present study, we can gain deeper insights into the utilization and impact of PCSK9 inhibitors in treating ischemic stroke.

MiR-135a-5p suppresses breast cancer cell proliferation, migration, and invasion by regulating BAG3.

BACKGROUND: MicroRNAs (miRNAs) are involved in the progression of diverse human cancers. This work aimed to delve into how microRNA-135a-5p (miR-135a-5p) affects the biological behaviors of Breast Cancer (BC) cells. METHODS: Gene Expression Omnibus (GEO) datasets were used to analyze the expression differences of miR-135a-5p in cancer tissues of BC patients. Quantitative real-time PCR and western blot were conducted to detect miR-135a-5p and Bcl-2 Associated Athanogene (BAG3) expression levels in BC tissues and cells, respectively. The proliferation, migration, invasion, and cell cycle of BC cells were detected by cell counting kit-8 assay, BrdU assay, wound healing assay, transwell assay, and flow cytometry. The targeted relationship between miR-135a-5p and BAG3 mRNA 3'UTR predicted by bioinformatics was further testified by a dual-luciferase reporter gene assay. Pearson's correlation analysis was adopted to analyze the correlation between miR-135a-5p expression and BAG3 expression. The downstream pathways of BAG3 were analyzed by the LinkedOmics database. RESULTS: MiR-135a-5p was significantly down-regulated and BAG3 expression was significantly raised in BC tissues. MiR-135a-5p overexpression repressed the viability, migration and invasion of BC cells, and blocked cell cycle progression in G0/G1 phase while inhibiting miR-135a-5p worked oppositely. BAG3 was verified as a target of miR-135a-5p. Overexpression of BAG3 reversed the impacts of miR-135a-5p on the malignant biological behaviors of BC cells. The high expression of BAG3 was associated with the activation of the cell cycle, mTOR and TGF-ß signaling pathways. CONCLUSION: MiR-135a-5p regulates BAG3 to repress the growth, migration, invasion, and cell cycle progression of BC cells.

Antibacterial activity of guanidinium-based ionic covalent organic framework anchoring Ag nanoparticles.

In this paper, the antibacterial 2D covalent organic framework (COFTGTp) containing guanidyl cation was synthesized and used as a carrier to deposit AgNPs on N and O groups to form nanocomposites to avoid AgNPs aggregation and achieve excellent antibacterial effect. The Ag content in Ag/COFTGTp was 10.3% determined by ICP. TEM can clearly observe that AgNPs were uniformly dispersed in COFTGTp. Ag/COFTGTp was stable after being evenly dispersed in water with low cytotoxicity and hemolysis rate to erythrocytes. In bacteriostatic study, the minimum inhibitory concentration of Ag/COFTGTp for E. coli and S. aureus were 100 µg/mL and 50 µg/mL, respectively. Finally, the morphology of the bacteria was observed by SEM, confirmed the main sterilization by Ag/COFTGTp was destroying the cell wall of the bacteria.

Multi-wavelength fusion column fingerprint technology combined with chemometric analysis to evaluate the overall quality of the Gardenia jasminoides root.

Chromatographic fingerprinting provides effective technical means for quality evaluation of traditional Chinese medicine. In this work, a novel multi-wavelength fusion column fingerprint was obtained by intelligent selection of chromatographic peaks from different wavelengths, which displayed the maximum peak area information under the optimal wavelength at the same retention time. Here, the Gardenia jasminoides root was selected as a sample. The multi-wavelength fusion column fingerprint graph of the Gardenia jasminoides root was constructed from five wavelengths (203 nm, 210 nm, 238 nm, 250 nm and 330 nm). The peak capacity, peak resolution, the number of common peaks and similarity were used to evaluate the performance. The 19 batches of Gardenia jasminoides root were classified into three categories with clear distinction between origin categories based on the multi-wavelength fusion column fingerprint combined with chemometrics, including hierarchical cluster analysis and principal component analysis. Nine markers of variation that led to differences between batches were screened by orthogonal partial least squares discriminant analysis. This study demonstrated that the classification model based on the multi-wavelength fusion column fingerprint was better than that on a single-wavelength, and the fusion fingerprint was suitable for the identification and quality control of traditional Chinese medicine with more comprehensive chemical composition information and more accurate prediction ability.

lncRNA H19 promotes glioblastoma multiforme development by activating autophagy by sponging miR-491-5p.

Glioblastoma multiforme (GBM) is a malignant cancer with severely poor survival, and the cells continue to thrive during hypoxia and toxic stress through autophagy. To validate the oncogenic role of long noncoding RNA H19 in GBM progression and examine whether autophagy and/or miR-491-5p participate in the process. The expression of H19 and autophagy-related genes in GBM and healthy control tissues was assessed via quantitative polymerase chain reaction. In addition, cell viability, proliferation, apoptosis and autophagy were respectively determined via cell counting kit-8 assay, clone formation assay, flow cytometry, western blotting and green fluorescent protein-microtubule-associated protein 1 light chain 3 alpha fluorescence analysis in vitro. Furthermore, a rescue assay was performed using rapamycin or miR-491-5p antagomir to examine the role of autophagy or miR-491-5p in H19-mediated regulation of proliferation and apoptosis. RNA pull-down and dual-luciferase reporter assays were employed to analyze the interaction between H19 and miR-491-5p. Additionally, tumor growth in a xenograft-bearing mouse model and autophagy in tumor mass were analyzed in vivo. The expression H19 was increased in GBM and was positively correlated with LC3 or Beclin-1. Silencing H19 inhibited growth and promoted apoptosis in GBM cells both in vitro and in vivo, and miR-491-5p was identified as one of the important mediators. H19 regulated the autophagy signaling pathway at least partly via miR-491-5p. Increased H19 expression in GBM exerts oncogenic effects by sponging miR-491-5p and enhancing autophagy. Therefore, H19 may be explored as a target for GBM therapy.

Sofosbuvir-based therapy for late pregnant women and infants with severe chronic hepatitis C: A case series study.

Data on sofosbuvir-based therapy for pregnant women and infants with severe chronic hepatitis C (CHC) are lacking. Two late pregnant women and one female infant with severe CHC were enrolled for treatment. Pregnant Women 1 and 2 and Infant 3 were 30, 33, and 1.2 years old, respectively; the gestational ages of pregnant Women 1 and 2 were 31 and 26 weeks, respectively. Notably, pregnant Women 1 and 2 and Infant 3 had hepatitis C virus (HCV) RNA levels of 139 000, 198 000, and 8 450 000 IU/ml; alanine aminotransferase levels of 420, 781, and 220 U/L; and received sofosbuvir/ledipasvir, sofosbuvir/velpatasvir, and sofosbuvir/ledipasvir for 12 weeks, respectively. All three patients were safely cured with favorable tolerance, and two newborns were both breastfeeding and were consistently negative for the anti-HCV antibody during the 1-year follow-up after birth. Additionally, two newborns and Infant 3 had normal growth parameters during the follow-up year one. In conclusion, this case series study found that sofosbuvir-based therapy for pregnant women and infants with severe CHC is safe and effective. The data may fill the gap and provide evidence of the use of sofosbuvir-based therapy as a reference when similar severe CHC situations are encountered during clinical practice.

Process optimization for the synthesis of functionalized Au@AgNPs for specific detection of Hg2+ based on quality by design (QbD).

The current study highlights the advantages of using the quality by design (QbD) approach to synthesise and optimize SERS substrates for the detection of Hg2+. Considering that the performance of Au@AgNPs is affected by many factors, Plackett-Burman (PB) experimental design was used to determine the critical process parameters (CPPs) for evaluating the performance of Au@AgNPs. The quantitative relationships between the CPPs and the critical quality attributes (CQAs) were assessed by Box-Behnken Design (BBD). The optimal design space for Au@AgNPs was calculated via a Monte Carlo algorithm. Finally, detection of Hg2+ in the range of 1 ∼ 100 ng mL-1 (R 2 = 0.9891) was achieved by SERS in combination with 4,4-bipyridine (Dpy) as signal molecules. The recoveries for licorice ranged from 83.53% to 92.96%. Specificity and practicality studies indicated that the method based on the QbD concept and design space not only met the optimal performance of Au@AgNPs but also improved the rapid detection of Hg2+ in Chinese medicine samples.

Enhancing the drug sensitivity of antibiotics on drug-resistant bacteria via the photothermal effect of FeTGNPs.

The growing problem of bacterial resistance caused by the abuse of antibiotics is a serious challenge for the world. In order to make the clinically available antibiotics regain their bactericidal effect, our study introduced photothermal therapy (PTT) to assist antibiotics to annihilate drug-resistant bacteria. To achieve the synergistic effect, nanoparticles (FeTGNPs) with an antibiotic core (gatifloxacin complexing with tannins) and a photothermal shell (ferric iron coordinating with tannins) were prepared directly in aqueous solution by a convenient yet efficient one-pot synthesis. The excellent photothermal properties of the shell of FeTGNPs were used to break the mechanism of bacterial resistance, and the sustained-release of gatifloxacin from the core regained the killing effect against drug-resistant bacteria. From the results of antibacterial experiments, with the synergistic effect of APTT and antibiotics, FeTGNPs (400 µg/mL) could effectively kill methicillin-resistant Staphylococcus aureus (sterilizing rate up to 96.5 %) and gatifloxacin-resistant Staphylococcus aureus (sterilizing rate up to 98.7 %) than equivalent antibiotics. Moreover, under slightly acidic microenvironment, such as infection area, gatifloxacin could accelerate its release from the core of FeTGNPs. Therefore, FeTGNPs would be a highly effective antibacterial agent against drug-resistant bacterial infections in the future.

Tenofovir Alafenamide for Pregnant Chinese Women With Active Chronic Hepatitis B: A Multicenter Prospective Study.

BACKGROUND & AIMS: Data on long-term tenofovir alafenamide (TAF) therapy for pregnant women with active chronic hepatitis B (CHB) (immune clearance and reactivation phases, currently and previously diagnosed) and their infants are lacking. METHODS: Pregnant women with active CHB treated with TAF and tenofovir disoproxil fumarate (TDF) were enrolled in this multicenter prospective study, and infants received immunoprophylaxis. The primary outcomes were rates of adverse (safety) events in pregnant women and defects in infants and fetuses. The secondary outcomes were virologic responses in pregnant women, infants' safety, hepatitis B surface antigen (HBsAg) status, and growth conditions. RESULTS: One hundred three and 104 pregnant women were enrolled and 102 and 104 infants were born in the TAF and TDF groups, respectively. In the TAF group, the mean age, gestational age, alanine aminotransferase level, and viral loads at treatment initiation were 29.3 years, 1.3 weeks, 122.2 U/L, and 5.1 log10 IU/mL, respectively. TAF was well-tolerated, and the most common adverse event was nausea (29.1%) during a mean of 2 years of treatment. Notably, 1 (1.0%) TAF-treated pregnant woman underwent induced abortion due to noncausal fetal cleft lip and palate. No infants in either group had birth defects. In the TAF group, the hepatitis B e antigen seroconversion rate was 20.7% at postpartum month 6, infants had normal growth parameters, and no infants were positive for HBsAg at 7 months. The TDF group had comparable safety and effectiveness profiles. CONCLUSIONS: TAF administered throughout or beginning in early pregnancy is generally safe and effective for pregnant women with active CHB and their infants.