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Qilong capsule (QLC) is a well-known Traditional Chinese Medicine, and it has a long history for the treatment of ischemic stroke. Its major ingredients are saponins, such as paeoniflorin, amygdalin and calycosin-7-glucoside, contributing to vasodilation function. In this study, a simple, rapid and sensitive high-performance liquid chromatography-tandem mass spectrometry method was developed to determine three bioactive ingredients in rat plasma after oral administration of QLC. A simple acetonitrile precipitation method was introduced during the sample preparation. Chromatographic separation was performed on a Shiseido CAPCELL PAC MGIII-C18 column using a gradient elution with acetonitrile and water (0.1% formic acid) as a mobile phase, and the chromatographic separation was 5 min. The methodological evaluation showed that this method had a high sensitivity (the lower limit of quantification was 1 ng/mL for calycosin-7-glucoside, 5 ng/mL for paeoniflorin, 5 ng/mL for amygdalin), satisfactory accuracy (relative error ≤ ±15%) and precision (relative standard deviation ≤15%). Then, the analytical method was applied to the pharmacokinetic study in rats following oral administration of the extracts in QLC. Meanwhile, the pharmacokinetic parameters of complex system in QLC were analyzed and the potential interaction between ingredients was explored. The present quantification method and pharmacokinetic study will provide a meaningful reference for the formulas research of QLC in the treatment of ischemic stroke. Highlight A simple, rapid and sensitive HPLC–MS/MS analytical method was developed for the simultaneous determination of three ingredients in rat plasma after oral administration of QLC. A simple acetonitrile precipitation method was introduced to extract three biomedical ingredients during the plasma sample preparation. The pharmacokinetic results revealed the pharmacological active substances, identified internal variation rules and provided a meaningful reference for the formulas research of QLC in the treatment of ischemic stroke. [ABSTRACT FROM AUTHOR]

The usage of traditional Chinese medicines has expanded globally, but the data about authentication, efficacy, and safety is far from sufficient to meet the criteria supporting their use worldwide due to complexity in the composition. Fingerprinting describes integral characterization and reflects interactive aspects of complex components; therefore, it can offer the possibility of evaluating quality of traditional Chinese medicines following the overall principle. Chemometric techniques introduce multivariate analytical methods into fingerprinting to obtain more information that is useful, which is consistent with the holistic thought and plays an important role in research on the substantial basis. In this review, we will start with three aspects to expound the quality evaluation of traditional Chinese medicines based on fingerprints. The analytical techniques used in developing fingerprints including chromatographic methods, spectroscopic methods, and capillary electrophoresis are introduced. Strategies for fingerprints analysis usually based on chemometric methods including unsupervised and supervised pattern recognition are described. Applications of fingerprints for multi‐component quantification, quality control, screening of bioactive components, and fingerprint‐efficacy relationship study are also outlined. Finally, we propose challenges and future perspectives of fingerprints in quality evaluation to promote the development of modernization and internationalization of traditional Chinese medicines. [ABSTRACT FROM AUTHOR]

At present, Tradition Chinese Medicine (TCM) industry in China is in the stage from the empirical development to industrial production. Near infrared (NIR) spectroscopy has been widely used in the quality control of TCM's modernization with its characteristics including rapidness, nondestruction, simplicity, economy, and so on. In this study, as one type of a portable micro NIR spectrometer, Micro NIR 1700 was used to establish the qualitative models for identification of geographical region and authenticity of Radix codonopsis based on discriminant analysis (DA) method. Both of the DA models had better predictive ability with 100% accuracy. In addition, a method for rapid quantitative analysis of polysaccharide in Radix codonopsis was also developed based on Micro NIR 1700 spectrometer with partial least-squares (PLS) algorithm. In the PLS calibration model, the NIR spectra of samples were pretreated with different preprocessing methods and the spectral region was selected with different variable selection methods as well. The performance of the final PLS model was evaluated according to correlation coefficient of calibration (), correlation coefficient of prediction (), root mean squared error of cross validation (RMSECV), and root mean squared of prediction (RMSEP). The values of , , RMSECV, and RMSEP were 0.9775, 0.9602, 2.496, and 2.734g/mL, respectively. This work demonstrated that micro infrared spectrometer could be more convenient and rapid for quality control of Radix codonopsis, and the presented models would be a useful reference for quality control of other similar raw materials of TCM. [ABSTRACT FROM AUTHOR]

A simple and accurate capillary electrophoresis (CE) method was developed to simultaneously separate and quantify heparin, chondroitin sulfate and hyaluronic acid. The relative standard deviations (intra-day) of migration time, peak height and peak area for heparin, chondroitin sulfate and hyaluronic acid were lower than 1.11, 5.45 and 2.82%, respectively. The limits of detection of heparin, chondroitin sulfate and hyaluronic acid were 0.91, 0.12 and 9.04 × 10−3 mg/mL, respectively. The developed electrophoretic method was successfully applied to the analysis of commercial drug products and biological samples containing chondroitin sulfate and/or hyaluronic acid. The recoveries for chondroitin sulfate and hyaluronic acid were in the range of 95.9 ∼107.0%. This was the first time the content of hyaluronic acid in the synovial fluids from osteoarthritic rabbits was investigated by CE. The results suggested that hyaluronic acid in the synovial fluids from osteoarthritic rabbits may be further metabolized and the administration of chondroitin sulfate or hyaluronic acid could affect the content and metabolism of hyaluronic acid in the synovial fluids. The developed CE method was simple to implement without sample pretreatment such as depolymerisation, very repeatable and easily transferred from lab to lab. [ABSTRACT FROM PUBLISHER]

[Display omitted] To prepare a PLGA microsphere loaded with the antipsychotic Blonanserin without release leg period and released in a near-zero model for long time, in this study, 15 kDa and 75 kDa PLGA were chosen to be mixed with different ratios, and Blonanserin microspheres (Bn-MS) without significant differences in the particle size, drug loading capacity, and encapsulation rate were prepared by microfluidics. The release kinetic model was fitted to the release behavior by monitoring the changes in particle size and morphology during the Bn-MS release to investigate microspheres' in vitro release pattern. The results showed that the addition of appropriate ratios of mixed molecular weights to Bn-MS could eliminate the release hysteresis period. When the ratio of 15 kDa and 75 kDa was 1:9 (F3), the Bn-MS had a low burst release rate, moderate release rate, no release hysteresis period, a long release period of up to 35 days, and a stable release pattern close to the zero level. The results of the release mechanism study indicated that the hybrid PLGA improved the release behavior of the microspheres by adjusting the dissolution degradation rate of Bn-MS, which in turn affected the release mechanism of the microspheres. [ABSTRACT FROM AUTHOR]

[Display omitted] • The first time using CBAM-CNN to predict particle size distribution during fluidized bed granulation. • The CBAM-CNN model was optimized by introducing Bayesian optimization and C-Mixup algorithms. • The performance of CBAM-CNN was compared to other classic models. • The modeling convenience of CBAM-CNN was evaluated. Monitoring the particle size distribution (PSD) is crucial for controlling product quality during fluidized bed granulation. This paper proposed a rapid analytical method that quantifies the D10, D50, and D90 values using a Convolutional Block Attention Module-Convolutional Neural Network (CBAM-CNN) framework tailored for deep learning with near-infrared (NIR) spectroscopy. This innovative framework, which fuses CBAM with CNN, excels at extracting intricate features while prioritizing crucial ones, thereby facilitating the creation of a robust multi-output regression model. To expand the training dataset, we incorporated the C-Mixup algorithm, ensuring that the deep learning model was trained comprehensively. Additionally, the Bayesian optimization algorithm was introduced to optimize the hyperparameters, improving the prediction performance of the deep learning model. Compared with the commonly used Partial Least Squares (PLS), Support Vector Machine (SVM), and Artificial Neural Network (ANN) models, the CBAM-CNN model yielded higher prediction accuracy. Furthermore, the CBAM-CNN model avoided spectral preprocessing, preserved the spectral information to the maximum extent, and returned multiple predicted values at one time without degrading the prediction accuracy. Therefore, the CBAM-CNN model showed better prediction performance and modeling convenience for analyzing PSD values in fluidized bed granulation. [ABSTRACT FROM AUTHOR]

Swertia mussotii Franch. (SMF), a traditional Tibetan medicine, which has miraculous effect on treating hepatitis diseases. However, there is no research on its entire production process, and invisible production process has seriously hindered the SMF modern development. In this study, principal component analysis (PCA), subtractive spectroscopy, and two-dimensional correlation spectroscopy (2D-COS) were used to explain changes of characteristic groups in the extraction process. Four main characteristic peaks at 1884 nm, 1944 nm, 2246 nm and 2308 nm were identified to describe the changes of molecular structure information of total active components in SMF extraction process. In addition, multi critical quality attributes (CQAs) models were established by near-infrared spectroscopy (NIRS) combined with the total quantum statistical moment (TQSM). The coefficients of determination (R 2 eval and R 2 ival ) were both greater than 0.99. The ratios of the standard deviation of validation to the standard error of the prediction (RPD e and RPD i ) were greater than five. The quantitative model of AUC T could save time on primary data measurement by not requiring determination of indicator components compared with others. In conclusion, these results demonstrated that it was feasible to understand the SMF extraction process through AUC T and characteristic groups. These could realize the visual digital characterization and quality stability of the SMF extraction process., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Background: This study aims to evaluate the efficacy and therapeutic mechanism of bufalin on lung adenocarcinoma (LUAD) through a comprehensive strategy integrating network pharmacology, metabolomics and molecular biology verification., Methods: The putative targets of bufalin were discerned from PharmMapper and Swiss Target Prediction database. LUAD-related targets were obtained by target filtering of GeneCard database and data mining of GEO database. PPI network was constructed to screen the core targets, and their clinical significance was assessed through several public databases. GO and KEGG pathway analyses were performed to identify possible enrichment of genes with specific biological themes. Molecular docking and molecular dynamics (MD) simulation were employed to determine the correlation and binding pattern between bufalin and core targets. The potential mechanisms of bufalin acting on LUAD, as predicted by network pharmacology analyses, were experimentally validated using in-vitro and in-vivo models. Finally, the effects of bufalin intervention on metabolite profile and metabolic pathway in LUAD nude mice were investigated by non-targeted metabolomics., Results: 209 bufalin targets and 1082 LUAD-associated targets were harvested, of which 51 intersection targets were identified. 10 core targets including Akt1, STAT3, EGFR, CASP3 and SRC were picked out through network topology analysis, and they had a potent binding activity with bufalin as indicated by molecular docking and MD simulation. Hub module of PPI network was closely related to cell proliferation and apoptosis. GO and KEGG enrichment analyses suggested that bufalin exerted therapeutic effects on LUAD possibly by inhibiting proliferation and promoting apoptosis via PI3K/Akt, FoxO1 and MAPK/ERK pathways, which were confirmed by a series of in-vitro studies as well as HE, TUNEL and Ki-67 staining of tumor tissues. Further metabolomics analysis revealed that bufalin mainly regulated ABC transporter and remodeled AA metabolism, thereby contributing to the treatment of LUAD., Conclusion: From molecular and metabolic perspective, the present study not only provided a unique insight into the possible mechanisms of bufalin against LUAD after successfully filtering out associated key target genes, differential endogenous metabolites, and signaling pathways, but also proposed a novel promising therapeutic strategy for LUAD., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

As an important pharmaceutical process, crystallization greatly impacts the final product. In recent years, the continuous crystallization process has attracted more attention from researchers, with the promotion of continuous manufacturing (CM) by the Food and Drug Administration (FDA). The continuous crystallization process has the advantages of high economic benefit, stable and uniform quality, a short production cycle, and personalization. To carry out continuous crystallization, some related process analytical technology (PAT) tools have become the focus of breakthroughs. Infrared (IR) spectroscopy, Raman spectroscopy, and focused beam reflection measurement (FBRM) tools have gradually become research hotspots due to their fast, non-destructive, and real-time monitoring characteristics. This review compared the advantages and disadvantages of the three technologies. Their applications in the upstream mixed continuous crystallization process, the middle reaches of crystal nucleation and growth, and the process of the downstream refining were discussed to provide corresponding guidance for the practice and further development of these three technologies in the continuous crystallization process and promote the development of CM in the pharmaceutical industry., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

The traditional Chinese medicine (TCM) extraction process is a complicated dynamic system with many variables and disturbance. Therefore, multi critical quality attributes (CQAs) monitoring is of great significance to understand the whole process. Spectroscopy is a powerful process analytical tool used for process understanding. However, single senor sometimes could not provide comprehensive information. Sensor fusion is a very practical method to overcome this deficiency. In this study, the extraction process of Xiao'er Xiaoji Zhike Oral Liquid (XXZOL) was carried out in pilot scale, where near infrared (NIR) spectroscopy and mid infrared (MIR) spectroscopy were collected to determine the concentrations of seven CQAs (synephrine, arecoline, chlorogenic acid, forsythoside A, naringin, hesperidin and neohesperidin) during extraction process. Based on fused data blocks, fusion partial least squares (PLS) models were established. Two fusion data blocks are obtained from the concatenation of original spectra (low-level data fusion) and the concatenation of characteristic variables based on band selection (mid-level data fusion) respectively. The results indicated that for all seven analytes, the mid-level data fusion models were superior to the single spectral models, with the prediction performance significantly improved. Specifically, the coefficients of determination (R p 2 and R t 2 ) of NIR, MIR and fusion quantitative models were all higher than 0.95. The relative standard errors of prediction (RSEP) values were all within 10%, except for models of neohesperidin, which were 10.76%, 12.39%, 12.05%, 10.03% for NIR, MIR, low-level and mid-level models respectively. These results demonstrate that it is feasible to monitor the extraction process of Xiao'er Xiaoji Zhike Oral Liquid more accurately and rapidly by fusing NIR and MIR spectroscopy, and the proposed approach also has vital and valuable reference value for the rapid monitoring of the mixed decoction process of other TCM., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Osteoarthritis (OA), as an "undead cancer", causes a serious burden for both individuals and society. In this study, a glycosaminoglycan-based injectable hydrogel was prepared with hyaluronic acid (HA), chondroitin sulfate E disaccharide (ΔUA-diSE) and thermosensitive Pluronic F127 (PF127) to provide a new strategy for OA alleviation. Both in vitro and in vivo biological evaluations were introduced to investigate the slow-release capacity, related mechanisms, and effectiveness of PF-HA-diSE on OA. The results demonstrated that PF-HA-diSE could alleviate OA effectively by regulating the complement system, especially the formation of C5b-9, and its downstream signals. Interestingly, we also found that PF127 was not only a drug carrier, but may have the potential on inhibiting C5b-9 formation. Altogether, these findings provided a more effective local drug delivery system for glycosaminoglycans in better treatment of OA and related diseases., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Some chemotherapy can damage tumor cells, releasing damage-related molecular patterns including ATP to improve immunological recognition against the tumor by immunogenic cell death (ICD). However, the immune-stimulating ATP may be rapidly degraded into immunosuppressive adenosine by highly expressed CD39 and CD73 in the tumor microenvironment, which leads to immune escape. Based on the above paradox, a liposome nanoplatform combined with ICD inducer (oxaliplatin) and CD39 inhibitor (POM-1) is designed for immunochemotherapy. The liposomes efficiently load the phospholipid-like oxaliplatin prodrug, and the cationic charged surface could adsorb POM-1. Rationally designed DSPE-PEG n -pep, on the one hand, could cover and hide POM-1 to avoid systematic toxicity and, on the other, achieve a response and charge reversal to favor POM-1 shedding and tumor deep penetration. This combination maximizes the ICD effect, and takes two-pronged advantage of stimulating the immune response and relieving immune suppression. The designed POL can effectively inhibit the growth of in situ, lung metastasis and postoperative recurrence melanoma model and form long-term immune memory. With the powerful clinical transformation potential of nanoliposome platforms, this new synergistic strategy is expected to enhance anticancer effects safely and effectively., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Near-infrared spectroscopy (NIRS) is an excellent process analytical technology (PAT) tool for active pharmaceutical ingredient (API) quantification during fluidized granulation. Therefore, a portable near-infrared spectrometer combined with a new innovative method of extended iterative optimization technique (EIOT) was used to in-line monitor the API content uniformity during fluidized bed granulation. The principal component analysis (PCA) and partial least squares regression (PLSR) were also used to characterize and predict API concentration with changes from 75% to 125% of the label claim to prove the superiority of EIOT. The API content prediction accuracy of the EIOT method was verified through offline High Performance Liquid Chromatography (HPLC) measurement. Also, the spatial distribution of API in granules was visualized by Raman imaging technology. The results showed that the established NIRS method was suitable for the prediction of API content in fluidized bed granulation, which provides a new idea for the determination of API content during granulation., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

The stability of biological drugs with protein as an active substance depends heavily on the retention of natural protein structure during freeze-drying. Stabilizers have become important substances in the process of protein freeze-drying. In order to further understand the mechanism of the interaction between protein and stabilizers, human serum albumin (HSA) and simple hydroxyl compound ethanol were used as models. Infrared (IR) spectroscopy combined with chemometrics was implemented to investigate the changes of secondary structure and hydration of HSA when different concentrations of ethanol were considered as interference. Through the analysis of the protein secondary structure and hydrated layer, we found that the addition of ethanol-d6 increased the α-helix of HSA and reduced the disordered structure. The hydrogen bond structure around HSA was enhanced and intermolecular aggregation was reduced through the action of the water molecules. The hypothesis was verified by circular dichroism (CD) and transmission electron microscopy (TEM) observation by adding different concentrations of ethanol-d6. It was found that a small amount of ethanol could protect the native conformation of HSA. In conclusion, this study revealed the mechanism of ethanol as a protein protector, provided a new idea for protein purification process and a theoretical basis for biomolecular interaction., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)