Current Issue

Vol. 15, Issue 1, 2025

Table of Contents

ISSN2095-1779

CN61-1484/R

Editor-in-Chief: Langchong He

Impact Factor 2023: 6.1
CiteScore 2023: 16.2
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Label-free electrochemical aptasensing of cardiac cell secretomes in cell culture media for the evaluation of drug-induced myocardial injury
Zelin Yang, Xilin Chen, Mingang Liao, Feng Liao, Wen Chen, Qian Shao, Bing Liu, Duanping Sun
 doi: 10.1016/j.jpha.2025.101234
[Abstract](0) [PDF 0KB](0)
Abstract:
Cardiac troponin I (cTnI), a widely used biomarker for assessing cardiovascular risk, can provide a window for the evaluation of drug-induced myocardial injury. Label-free biosensors are promising candidates for detecting cell secretomes, since they do not require labor-intensive processes. In this work, a label-free electrochemical aptasensor is developed for in situ monitoring of cardiac cell secretomes in cell culture media based on target-induced strand displacement. The aptasensing system contains an aptamer-functionalized signal nanoprobe facing trimetallic metal-organic framework nanosheets and a gold nanoparticle-based detection working electrode modified with DNA nanotetrahedron-based complementary DNA for indirect target detection. The signal nanoprobes (termed CAHA) consisted of copper-based metal-organic frameworks, AuPt nanoparticles, horseradish peroxidase, and an aptamer. When the aptasensor is exposed to cardiac cell secretomes, cTnI competitively binds to the aptamer, resulting in the release of signal nanoprobes from the biorecognition interface and electrochemical signal changes. The aptasensor exhibited rapid response times, a low detection limit of 0.31 pg mL-1, and a wide linear range of 0.001-100 ng mL-1. We successfully used this aptasensor to measure cTnI concentrations among secreted cardiac markers during antitumor drug treatment. In general, aptasensors can be used to monitor a variety of cardiac biomarkers in the evaluation of cardiotoxicity.
The latest progress of personalized drug screening and therapy research for clinical highly lethal tumors through the PDX model platform
Yitong Yuan, Hongling Gao, Yanhong Li, Xiangying Jiao
 doi: 10.1016/j.jpha.2025.101225
[Abstract](14) [PDF 7535KB](0)
Abstract:
The establishment of mouse models is critical for discovering the biological targets of tumorigenesis and cancer development, preclinical trials of targeted drugs, and formulation of personalized therapeutic regimens. Currently, the patient-derived xenograft (PDX) model is considered a reliable animal tumor model because of its ability to retain the characteristics of the primary tumor at the histopathological, molecular, and genetic levels, and to preserve the tumor microenvironment. The application of the PDX model has promoted in-depth research on tumors in recent years, focusing on drug development, tumor target discovery, and precise treatment of patients. However, there are still some common questions. This review introduces the latest research progress and common questions regarding tumors with high mortality rates, focusing on their application in targeted drug screening and the formulation of personalized medical strategies. The challenges faced, improvement methods, and future development of the PDX model in tumor treatment applications are also discussed. This article provides technical guidance and comprehensive expectations for anti-cancer drug screening and clinical personalized therapy.
Artificial intelligence-aided endoscopic in-line particle size analysis during the pellet layering process
Orsolya Péterfi, Nikolett Kállai-Szabó, Kincső Renáta Demeter, Ádám Tibor Barna, István Antal, Edina Szabó, Emese Sipos, Zsombor Kristóf Nagy, Dorián László Galata
 doi: 10.1016/j.jpha.2025.101227
[Abstract](10) [PDF 2634KB](0)
Abstract:
In this study, an artificial intelligence-based machine vision system was developed for in-line particle size analysis during the pellet layering process. Drug-layered pellets were produced by coating microcrystalline cellulose cores with an ibuprofen-containing layering liquid until the target drug content was achieved. Drug content increases with pellet size; therefore, particle size monitoring can ensure product safety and quality. The direct imaging system, consisting of a rigid endoscope, a light source, and a high-speed camera, provides real-time information about pellet size and layer uniformity, enabling timely intervention in the case of out-of-spec products. A convolutional neural network-based instance segmentation algorithm was employed to detect particles in focus, ensuring that pellet size could be accurately determined despite the dense flow of the particles. After training the model, the performance of the developed system was assessed by analysing the particle size distribution of pellet cores with variable sizes within the 250–850 μm size range. The endoscopic system was tested in-line at a larger scale during the drug layering of inert pellet cores. The particle size data acquired in real time with the endoscopic imaging system corresponded with the reference methods, demonstrating the feasibility of the proposed machine vision-based method as a process analytical technology tool for in-line process monitoring.
Generation of SARS-CoV-2 dual-target candidate inhibitors through 3D equivariant conditional generative neural networks
Zhong-Xing Zhou, Hong-Xing Zhang, Qingchuan Zheng
 doi: 10.1016/j.jpha.2025.101229
[Abstract](49) [PDF 8635KB](3)
Abstract:
SARS-CoV-2 mutations are influenced by random and uncontrollable factors, and the risk of the next 3 widespread epidemic remains. Dual-target drugs that synergistically act on two targets exhibit strong 4 therapeutic effects and advantages against mutations. In this study, a novel computational workflow was 5 developed to design dual-target SARS-CoV-2 candidate inhibitors with the Envelope protein and Main 6 protease selected as the two target proteins. The drug-like molecules of our self-constructed 3D scaffold 7 database were used as high-throughput molecular docking probes for feature extraction of two target protein 8 pockets. A multi-layer perceptron (MLP) was employed to embed the binding affinities into a latent space as 9 conditional vectors to control conditional distribution. Utilizing a conditional generative neural network, cG- 10 SchNet, with 3D Euclidean group (E3) symmetries, the conditional probability distributions of molecular 3D 11 structures were acquired and a set of novel SARS-CoV-2 dual-target candidate inhibitors were generated. 12 The 1D probability, 2D joint probability, and 2D cumulative probability distribution results indicate that the 13 generated sets are significantly enhanced compared to the training set in the high binding affinity area. 14 Among the 201 generated molecules, 42 molecules exhibited a sum binding affinity exceeding 17.0 kcal/mol 15 while 9 of them having a sum binding affinity exceeding 19.0 kcal/mol, demonstrating structure diversity 16 along with strong dual-target affinities, good ADMET properties, and ease of synthesis. Dual-target drugs 17 are rare and difficult to find, and our “High-Throughput Docking - Multi-Conditional Generation” workflow 18 offers a wide range of options for designing or optimizing potent dual-target SARS-CoV-2 inhibitors.
A cascade reaction nanoplatform with magnetic resonance imaging capability for combined photothermal/chemodynamic/gas cancer therapy
Jinyu Wang, Yuhao Guo, Xiaomei Wu, Yiming Ma, Qianqian Qiao, Linwei Li, Tao Liao, Ying Kuang, Cao Li
 doi: 10.1016/j.jpha.2025.101223
[Abstract](15) [PDF 39516KB](0)
Abstract:
To effectively exploit the tumor microenvironment (TME), TME-responsive nanocarriers based on cascade reactions have received much attention. In this study, we designed a novel nanoparticle PB@SiO2@MnO2@P-Arg (PMP) to construct a cascade reaction nanoplatform. While using biosafety Prussian blue (PB) for photothermal therapy (PTT), this nanoplatform uses silica (SiO2) as an intermediate layer to assemble Prussian blue and manganese dioxide (MnO2) into a core-shell structure, which effectively enhances the response of the nanoplatform to TME and promotes the effect of chemodynamic therapy (CDT) resulting from glutathione (GSH) depletion and Fenton-like reaction. The released Mn2+ can also be used for magnetic resonance imaging (MRI). Through the cascade reaction, poly-L-arginine (P-Arg) coated on the surface of the nanoparticles can react with hydroxyl radical (·OH) obtained from the Fenton-like reaction to release nitric oxide (NO), which further reacts with O2·- to produce the more toxic peroxynitrite anion (ONOO-). The photothermal effect of PB further enhances the effect of the cascade reaction while reducing the amount of heat required for treatment. In vitro and in vivo studies confirmed the antitumor effects of cascade reaction-based nanoplatforms in combined photothermal/chemodynamic/gas cancer therapies, providing new strategies for the design and fabrication of multifunctional nanoplatforms that integrate diagnostic and therapeutic functions, as well as the application of cascade reactions in multimodal synergistic therapy.
Integrating biogravimetric analysis and machine learning for systematic studies of botanical materials: From bioactive constituent identification to production area prediction
Sinan Wang, Huiru Xiang, Xinyuan Pan, Jianyang Pan, Lu Zhao, Yi Wang, Shaoqing Cui, Yu Tang
 doi: 10.1016/j.jpha.2025.101222
[Abstract](12) [PDF 10551KB](0)
Abstract:
In general, bioassay-guided fractionation and isolation of bioactive constituents from botanical materials frequently ended up with the reward of a single compound. However, botanical materials typically exert their therapeutic actions through multi- pathway effects due to the intrinsic complex nature of chemical constituents. In addition, the content of bioactive compounds in botanical materials is largely dependent on humidity, temperature, soil, especially geographical origins, from which rapid and accurate identification of plant materials is pressingly needed. These long-standing obstacles collectively impede the deep exploitation and application of these versatile natural sources. To address the challenges, a new paradigm integrating biogravimetric analyses and machine learning-driven origin classification (BAMLOC) was developed. The biogravimetric analyses are based on absolute qHNMR quantification and in vivo zebrafish model-assisted activity index calculation, by which bioactive substance groups jointly responsible for the bioactivities in all fractions are pinpointed before any isolation effort. To differentiate origin-different botanical materials varying in the content of bioactive substance groups, principal component analysis, linear discriminant analysis, and hierarchical cluster analysis in conjunction with supervised support vector machine are employed to classify and predict production areas based on the detection of volatile organic compounds by E-nose and GC-MS. Expanding BAMLOC to Codonopsis Radix enables the identification of polyacetylenes and pyrrolidine alkaloids as the bioactive substance group for immune restoration effect and accurately determines the origins of plants. This study advances the toolbox for the discovery of bioactive compounds from complex mixtures and lays a more definitive foundation for the in-depth utilization of botanical materials.
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Perspective
Review paper
Application of artificial intelligence to quantitative structure-retention relationship calculations in chromatography
Jingru Xie, Si Chen, Liang Zhao, Xin Dong
2025, 15(1): 101155.   doi: 10.1016/j.jpha.2024.101155
Abstract(59) HTML Full Text PDF(6)
Abstract:

Quantitative structure-retention relationship (QSRR) is an important tool in chromatography. QSRR examines the correlation between molecular structures and their retention behaviors during chromatographic separation. This approach involves developing models for predicting the retention time (RT) of analytes, thereby accelerating method development and facilitating compound identification. In addition, QSRR can be used to study compound retention mechanisms and support drug screening efforts. This review provides a comprehensive analysis of QSRR workflows and applications, with a special focus on the role of artificial intelligence—an area not thoroughly explored in previous reviews. Moreover, we discuss current limitations in RT prediction and propose promising solutions. Overall, this review offers a fresh perspective on future QSRR research, encouraging the development of innovative strategies that enable the diverse applications of QSRR models in chromatographic analysis.

Advanced bioanalytical techniques for pharmacokinetic studies of nanocarrier drug delivery systems
Xiangjun Meng, Jiayi Yao, Jingkai Gu
2025, 15(1): 101070.   doi: 10.1016/j.jpha.2024.101070
Abstract(110) HTML Full Text PDF(7)
Abstract:

Significant investment in nanocarrier drug delivery systems (Nano-DDSs) has yielded only a limited number of successfully marketed nanomedicines, highlighting a low rate of clinical translation. A primary contributing factor is the lack of foundational understanding of in vivo processes. Comprehensive knowledge of the pharmacokinetics of Nano-DDSs is essential for developing more efficacious nanomedicines and accurately evaluating their safety and associated risks. However, the complexity of Nano-DDSs has impeded thorough and systematic pharmacokinetic studies. Key components of pharmacokinetic investigations on Nano-DDSs include the analysis of the released drug, the encapsulated drug, and the nanomaterial, which present a higher level of complexity compared to traditional small-molecule drugs. Establishing an appropriate approach for monitoring the pharmacokinetics of Nano-DDSs is crucial for facilitating the clinical translation of nanomedicines. This review provides an overview of advanced bioanalytical methodologies employed in studying the pharmacokinetics of anticancer organic Nano-DDSs over the past five years. We hope that this review will enhance the understanding of the pharmacokinetics of Nano-DDSs and support the advancement of nanomedicines.

Targeting AMPK related signaling pathways: A feasible approach for natural herbal medicines to intervene non-alcoholic fatty liver disease
Yongqing Cai, Lu Fang, Fei Chen, Peiling Zhong, Xiangru Zheng, Haiyan Xing, Rongrong Fan, Lie Yuan, Wei Peng, Xiaoli Li
2025, 15(1): 101052.   doi: 10.1016/j.jpha.2024.101052
Abstract(91) HTML Full Text PDF(4)
Abstract:

Non-alcoholic fatty liver disease (NAFLD) is a metabolic disease characterized by abnormal deposition of lipid in hepatocytes. If not intervened in time, NAFLD may develop into liver fibrosis or liver cancer, and ultimately threatening life. NAFLD has complicated etiology and pathogenesis, and there are no effective therapeutic means and specific drugs. Currently, insulin sensitizers, lipid-lowering agents and hepatoprotective agents are often used for clinical intervention, but these drugs have obvious side effects, and their effectiveness and safety need to be further confirmed. Adenosine monophosphate (AMP)-activated protein kinase (AMPK) plays a central role in maintaining energy homeostasis. Activated AMPK can enhance lipid degradation, alleviate insulin resistance (IR), suppress oxidative stress and inflammatory response, and regulate autophagy, thereby alleviating NAFLD. Natural herbal medicines have received extensive attention recently because of their regulatory effects on AMPK and low side effects. In this article, we reviewed the biologically active natural herbal medicines (such as natural herbal medicine formulas, extracts, polysaccharides, and monomers) that reported in recent years to treat NAFLD via regulating AMPK, which can serve as a foundation for subsequent development of candidate drugs for NAFLD.

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Molecular immune pathogenesis and diagnosis of COVID-19
Xiaowei Li, Manman Geng, Yizhao Peng, Liesu Meng, Shemin Lu
2020, 10(2): 102-108.  
[Abstract](1718) [PDF 2284KB](23)
摘要:
Coronavirus disease 2019 (COVID-19) is a kind of viral pneumonia which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The emergence of SARS-CoV-2 has been marked as the third introduction of a highly pathogenic coronavirus into the human population after the severe acute respiratory syndrome coronavirus (SARS-CoV) and the Middle East respiratory syndrome coro-navirus (MERS-CoV) in the twenty-first century. In this minireview, we provide a brief introduction of the general features of SARS-CoV-2 and discuss current knowledge of molecular immune pathogenesis, diagnosis and treatment of COVID-19 on the base of the present understanding of SARS-CoV and MERS-CoV infections, which may be helpful in offering novel insights and potential therapeutic targets for combating the SARS-CoV-2 infection.
Structural basis of SARS-CoV-23CLpro and anti-COVID-19 drug discovery from medicinal plants
Muhammad Tahir ul Qamar, Safar M.Alqahtani, Mubarak A.Alamri, Ling-Ling Chen
2020, 10(4): 313-319.  
[Abstract](4043) [PDF 5841KB](50)
摘要:
The recent pandemic of coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 has raised global health concerns. The viral 3-chymotrypsin-like cysteine protease (3CLpro) enzyme controls coronavirus replication and is essential for its life cycle. 3CLpro is a proven drug discovery target in the case of severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV). Recent studies revealed that the genome sequence of SARS-CoV-2 is very similar to that of SARS-CoV. Therefore, herein, we analysed the 3CLpro sequence, constructed its 3D homology model, and screened it against a medicinal plant library containing 32,297 potential anti-viral phytochemicals/traditional Chinese medicinal compounds. Our analyses revealed that the top nine hits might serve as potential anti- SARS-CoV-2 lead molecules for further optimisation and drug development process to combat COVID-19.
Recent advances and perspectives of nucleic acid detection for coronavirus
Minzhe Shen, Ying Zhou, Jiawei Ye, Abdu Ahmed Abdullah AL-maskri, Yu Kang, Su Zeng, Sheng Cai
2020, 10(2): 97-101.  
[Abstract](1688) [PDF 2697KB](19)
摘要:
The recent pneumonia outbreak caused by a novel coronavirus (SARS-CoV-2) is posing a great threat to global public health. Therefore, rapid and accurate identification of pathogenic viruses plays a vital role in selecting appropriate treatments, saving people's lives and preventing epidemics. It is important to establish a quick standard diagnostic test for the detection of the infectious disease (COVID-19) to prevent subsequent secondary spread. Polymerase chain reaction (PCR) is regarded as a gold standard test for the molecular diagnosis of viral and bacterial infections with high sensitivity and specificity. Isothermal nucleic acid amplification is considered to be a highly promising candidate method due to its fundamental advantage in quick procedure time at constant temperature without thermocycler opera-tion. A variety of improved or new approaches also have been developed. This review summarizes the currently available detection methods for coronavirus nucleic acid. It is anticipated that this will assist researchers and clinicians in developing better techniques for timely and effective detection of coro-navirus infection.
Application of microfluidic chip technology in pharmaceutical analysis:A review
Ping Cui, Sicen Wang
2019, 9(4): 238-247.  
[Abstract](389) [PDF 5845KB](19)
摘要:
The development of pharmaceutical analytical methods represents one of the most significant aspects of drug development. Recent advances in microfabrication and microfluidics could provide new approaches for drug analysis, including drug screening, active testing and the study of metabolism. Microfluidic chip technologies, such as lab-on-a-chip technology, three-dimensional (3D) cell culture, organs-on-chip and droplet techniques, have all been developed rapidly. Microfluidic chips coupled with various kinds of detection techniques are suitable for the high-throughput screening, detection and mechanistic study of drugs. This review highlights the latest (2010–2018) microfluidic technology for drug analysis and dis-cusses the potential future development in this field.
Research advances in the detection of miRNA
Jiawei Ye, Mingcheng Xu, Xueke Tian, Sheng Cai, Su Zeng
2019, 9(4): 217-226.  
[Abstract](685) [PDF 6429KB](19)
摘要:
MicroRNAs (miRNAs) are a family of endogenous, small (approximately 22 nucleotides in length), noncoding, functional RNAs. With the development of molecular biology, the research of miRNA bio-logical function has attracted significant interest, as abnormal miRNA expression is identified to contribute to serious human diseases such as cancers. Traditional methods for miRNA detection do not meet current demands. In particular, nanomaterial-based methods, nucleic acid amplification-based methods such as rolling circle amplification (RCA), loop-mediated isothermal amplification (LAMP), strand-displacement amplification (SDA) and some enzyme-free amplifications have been employed widely for the highly sensitive detection of miRNA. MiRNA functional research and clinical diagnostics have been accelerated by these new techniques. Herein, we summarize and discuss the recent progress in the development of miRNA detection methods and new applications. This review will provide guidelines for the development of follow-up miRNA detection methods with high sensitivity and spec-ificity, and applicability to disease diagnosis and therapy.
Carbon nanotubes:Evaluation of toxicity at biointerfaces
Debashish Mohanta, Soma Patnaik, Sanchit Sood, Nilanjan Das
2019, 9(5): 293-300.  
[Abstract](534) [PDF 3216KB](14)
摘要:
Carbon nanotubes (CNTs) are a class of carbon allotropes with interesting properties that make them productive materials for usage in various disciplines of nanotechnology such as in electronics equip-ments, optics and therapeutics. They exhibit distinguished properties viz., strength, and high electrical and heat conductivity. Their uniqueness can be attributed due to the bonding pattern present between the atoms which are very strong and also exhibit high extreme aspect ratios. CNTs are classified as single-walled carbon nanotubes (SWCNTs) and multi-walled carbon nanotubes (MWCNTs) on the basis of number of sidewalls present and the way they are arranged spatially. Application of CNTs to improve the performance of many products, especially in healthcare, has led to an occupational and public exposure to these nanomaterials. Hence, it becomes a major concern to analyze the issues pertaining to the toxicity of CNTs and find the best suitable ways to counter those challenges. This review summarizes the toxicity issues of CNTs in vitro and in vivo in different organ systems (bio interphases) of the body that result in cellular toxicity.
Structural elucidation of SARS-CoV-2 vital proteins: Computational methods reveal potential drug candidates against main protease, Nsp12 polymerase and Nsp13 helicase
Muhammad Usman Mirza, Matheus Froeyen
2020, 10(4): 320-328.  
[Abstract](535) [PDF 19436KB](12)
摘要:
Recently emerged SARS-CoV-2 caused a major outbreak of coronavirus disease 2019 (COVID-19) and instigated a widespread fear, threatening global health safety. To date, no licensed antiviral drugs or vaccines are available against COVID-19 although several clinical trials are under way to test possible therapies. During this urgent situation, computational drug discovery methods provide an alternative to tiresome high-throughput screening, particularly in the hit-to-lead-optimization stage. Identification of small molecules that specifically target viral replication apparatus has indicated the highest potential towards antiviral drug discovery. In this work, we present potential compounds that specifically target SARS-CoV-2 vital proteins, including the main protease, Nsp12 RNA polymerase and Nsp13 helicase. An integrative virtual screening and molecular dynamics simulations approach has facilitated the identifi-cation of potential binding modes and favourable molecular interaction profile of corresponding com-pounds. Moreover, the identification of structurally important binding site residues in conserved motifs located inside the active site highlights relative importance of ligand binding based on residual energy decomposition analysis. Although the current study lacks experimental validation, the structural infor-mation obtained from this computational study has paved way for the design of targeted inhibitors to combat COVID-19 outbreak.
Nanodiamonds with powerful ability for drug delivery and biomedical applications: Recent updates on in vivo study and patents
Swati Chauhan, Neha Jain, Upendra Nagaich
2020, 10(1): 1-12.  
[Abstract](301) [PDF 2643KB](7)
摘要:
Nanodiamonds are novel nanosized carbon building blocks possessing varied fascinating mechanical, chemical, optical and biological properties, making them significant active moiety carriers for biomedical application. These are known as the most'captivating' crystals attributed to their chemical inertness and unique properties posing them useful for variety of applications in biomedical era. Alongside, it becomes increasingly important to find, ascertain and circumvent the negative aspects associated with nano-diamonds. Surface modification or functionalization with biological molecules plays a significant role in managing the toxic behavior since nanodiamonds have tailorable surface chemistry. To take advantage of nanodiamond potential in drug delivery, focus has to be laid on its purity, surface chemistry and other considerations which may directly or indirectly affect drug adsorption on nanodiamond and drug release in biological environment. This review emphasizes on the basic properties, synthesis techniques, surface modification techniques, toxicity issues and biomedical applications of nanodiamonds. For the devel-opment of nanodiamonds as an effective dosage form, researchers are still engaged in the in-depth study of nanodiamonds and their effect on life interfaces.
Identification and characterization of phenolics and terpenoids from ethanolic extracts of Phyllanthus species by HPLC-ESI-QTOF-MS/MS
Sunil Kumar, Awantika Singh, Brijesh Kumar
2017, 7(4): 214-222.  
[Abstract](791) [PDF 3923KB](391)
Abstract:
Phyllanthus species plants are a rich source of phenolics and widely used due to their medicinal properties. A liquid chromatography–tandem mass spectrometry (LC–MS/MS) method was developed using high-pressure liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry (HPLC-ESI-QTOF-MS/MS) for the identification and characterization of quercetin, kaempferol, ellagic acid and their derivatives in ethanolic extracts of Phyllanthus species. The chromatographic separation was carried out on Thermo Betasil C8 column (250 mm×4.5 mm, 5 μm) using 0.1% formic acid in water and 0.1% formic acid in methanol as the mobile phase. The identification of diagnostic fragment ions and optimization of collision energies were carried out using 21 reference standards. Totally 51 compounds were identified which include 21 compounds identified and characterized unambiguously by comparison with their authentic standards and the remaining 30 were tentatively identified and characterized in ethanolic extracts of P. emblica, P. fraternus, P. amarus and P. niruri.
Progress and prediction of multicomponent quantification in complex systems with practical LC-UV methods
Xi Chen, Zhao Yang, Yang Xu, Zhe Liu, Yanfang Liu, Yuntao Dai, Shilin Chen
2023, 13(2): 142-155.   doi: 10.1016/j.jpha.2022.11.011
[Abstract](2370) [PDF 1336KB](1176)
Abstract:
Complex systems exist widely, including medicines from natural products, functional foods, and biological samples. The biological activity of complex systems is often the result of the synergistic effect of multiple components. In the quality evaluation of complex samples, multicomponent quantitative analysis (MCQA) is usually needed. To overcome the difficulty in obtaining standard products, scholars have proposed achieving MCQA through the “single standard to determine multiple components (SSDMC)” approach. This method has been used in the determination of multicomponent content in natural source drugs and the analysis of impurities in chemical drugs and has been included in the Chinese Pharmacopoeia. Depending on a convenient (ultra) high-performance liquid chromatography method, how can the repeatability and robustness of the MCQA method be improved? How can the chromatography conditions be optimized to improve the number of quantitative components? How can computer software technology be introduced to improve the efficiency of multicomponent analysis (MCA)? These are the key problems that remain to be solved in practical MCQA. First, this review article summarizes the calculation methods of relative correction factors in the SSDMC approach in the past five years, as well as the method robustness and accuracy evaluation. Second, it also summarizes methods to improve peak capacity and quantitative accuracy in MCA, including column selection and two-dimensional chromatographic analysis technology. Finally, computer software technologies for predicting chromatographic conditions and analytical parameters are introduced, which provides an idea for intelligent method development in MCA. This paper aims to provide methodological ideas for the improvement of complex system analysis, especially MCQA.
Preface for Special Issue: Single-Cell and Spatially Resolved Omics
2023, 13(7): 689-690.   doi: 10.1016/j.jpha.2023.07.005
[Abstract](200) [PDF 229KB](101)
Abstract:
Potential of RP-UHPLC-DAD-MS for the qualitative and quantitative analysis of sofosbuvir in film coated tablets and profiling degradants
María del Mar Contreras, Aránzazu Morales-Soto, Antonio Segura-Carretero, Javier Valverde
2017, 7(4): 208-213.  
[Abstract](175) [PDF 2055KB](84)
Abstract:
Sofosbuvir is one of the new direct-acting antiviral drugs against hepatitis C virus (HCV) infection. This drug has recently been launched into the market, and generic versions of the medication are expected to be produced by local drug producers in some countries. Therefore, new methods are required to control sofosbuvir in pharmaceuticals. In the present study, a new method based on reversed phase (RP)-ultra-high performance liquid chromatography (UHPLC) coupled to diode array detection (DAD) and mass spectrometry (MS) was developed to facilitate the qualitative and quantitative analysis of sofosbuvir in film coated tablets. A wavelength of 260 nm was selected to perform a cost-effective quantification and the method showed adequate linearity, with an R2 value of 0.9998, and acceptable values of accuracy (75%–102%) and precision (residual standard deviation < 5%). The detection and quantification limits were 0.07 μg/mL and 0.36 μg/mL, respectively. Furthermore, the use of high-resolution MS enabled us to ensure the specificity, check impurities and better sensitivity. Therefore, this methodology promises to be suitable not only for the routine analysis of sofosbuvir in pharmaceutical dosage forms, but also for potential degradants.
Natural Product Virtual-Interact-Phenotypic Target Characterization: A Novel Approach Demonstrated with Salvia Miltiorrhiza Extract
Rui Xu, Hengyuan Yu, Yichen Wang, Boyu Li, Yong Chen, Xuesong Liu, Tengfei Xu
doi: 10.1016/j.jpha.2024.101101
[Abstract](510) [PDF 4176KB](241)
Abstract:
Natural products (NPs) have historically been a fundamental source for drug discovery. Yet the complex nature of NPs presents substantial challenges in pinpointing bioactive constituents, and corresponding targets. In the present study, an innovative Natural Product Virtual screening-Interaction-Phenotype (NP-VIP) strategy that integrates virtual screening, chemical proteomics, and metabolomics to identify and validate the bioactive targets of NPs. This approach reduces false positive results and enhances the efficiency of target identification. Salvia miltiorrhiza (SM), a herb with recognized therapeutic potential against ischemic stroke (IS), was used to illustrate the workflow. Utilizing virtual screening, chemical proteomics, and metabolomics, potential therapeutic targets for SM in the IS treatment were identified, totaling 29, 100, and 78, respectively. Further analysis via the NP-VIP strategy highlighted five high- confidence targets, including Poly [ADP-ribose] polymerase 1 (PARP1), signal transducer and activator of transcription 3 (STAT3), amyloid precursor protein (APP), glutamate-ammonia ligase (GLUL), and glutamate decarboxylase 67 (GAD67). These targets were subsequently validated and found to play critical roles in the neuroprotective effects of SM. The study not only underscores the importance of SM in treating IS but also sets a precedent for NP research, proposing a comprehensive approach that could be adapted for broader pharmacological explorations.
Editorial Board
2021, 11(6).  
[Abstract](269) [PDF 64KB](130)
Abstract:
Single-cell RNA-sequencing and subcellular spatial transcriptomics facilitate the translation of liver microphysiological systems for regulatory application
Dan Li, Zhou Fang, Qiang Shi, Nicholas Zhang, Binsheng Gong, Weida Tong, Ahmet F. Coskun, Joshua Xu
2023, 13(7): 691-693.   doi: 10.1016/j.jpha.2023.06.013
[Abstract](721) [PDF 707KB](349)
Abstract:
Single-cell analyses reveal cannabidiol rewires tumor microenvironment via inhibiting alternative activation of macrophage and synergizes with anti-PD-1 in colon cancer
Xiaofan Sun, Lisha Zhou, Yi Wang, Guoliang Deng, Xinran Cao, Bowen Ke, Xiaoqi Wu, Yanhong Gu, Haibo Cheng, Qiang Xu, Qianming Du, Hongqi Chen, Yang Sun
2023, 13(7): 726-744.   doi: 10.1016/j.jpha.2023.04.013
[Abstract](590) [PDF 9014KB](291)
Abstract:
Colorectal tumors often create an immunosuppressive microenvironment that prevents them from responding to immunotherapy. Cannabidiol (CBD) is a non-psychoactive natural active ingredient from the cannabis plant that has various pharmacological effects, including neuroprotective, antiemetic, anti-inflammatory, and antineoplastic activities. This study aimed to elucidate the specific anticancer mechanism of CBD by single-cell RNA sequencing (scRNA-seq) and single-cell ATAC sequencing (scATAC-seq) technologies. Here, we report that CBD inhibits colorectal cancer progression by modulating the suppressive tumor microenvironment (TME). Our single-cell transcriptome and ATAC sequencing results showed that CBD suppressed M2-like macrophages and promoted M1-like macrophages in tumors both in strength and quantity. Furthermore, CBD significantly enhanced the interaction between M1-like macrophages and tumor cells and restored the intrinsic anti-tumor properties of macrophages, thereby preventing tumor progression. Mechanistically, CBD altered the metabolic pattern of macrophages and related anti-tumor signaling pathways. We found that CBD inhibited the alternative activation of macrophages and shifted the metabolic process from oxidative phosphorylation and fatty acid oxidation to glycolysis by inhibiting the phosphatidylinositol 3-kinase-protein kinase B signaling pathway and related downstream target genes. Furthermore, CBD-mediated macrophage plasticity enhanced the response to anti-programmed cell death protein-1 (PD-1) immunotherapy in xenografted mice. Taken together, we provide new insights into the anti-tumor effects of CBD.