Journal of pharmaceutical analysis最新文献

{"title":"Enhancements of symbiotic adhesion and antibiotic efficacy observed by the metabolic crosstalk within cell-bacteria cocultured on a microfluidic gut chip.","authors":"Jingyang Li, Yuxuan Li, Shulang Chen, Gaowa Xing, Yingrui Zhang, Xianli Meng, Yi Zhang, Yukmi Cai, Jin-Ming Lin","doi":"10.1016/j.jpha.2026.101641","DOIUrl":"10.1016/j.jpha.2026.101641","url":null,"abstract":"<p><p>The gut cells and symbiotic bacteria play a critical role in maintaining gut health and influencing disease development, with metabolic interactions among its constituents warranting further investigation. In this study, we developed a cell-bacteria coculture system on a microfluidic gut chip to simulate the human gut microenvironment and performed multi-omics analyses to elucidate the metabolic crosstalk within the system. The results revealed that the coculture significantly enhances the adhesion and biofilm formation of symbiotic bacteria to gut epithelial cells through activation of the glucose-pyruvate-acetate metabolic cycle. This coculture promotes glucose consumption and acetate secretion while remaining resilient to antibiotics. Moreover, the coculture protected symbiotic bacterial biofilms from antibiotic-induced disruption, thereby enhancing colonization resistance and improving the efficacy of antibiotics against pathogens. Our findings highlight the importance of cell-bacteria interactions in driving the glucose-pyruvate-acetate metabolic cycle, enhancing symbiotic adhesion, and optimizing antibiotic efficacy.</p>","PeriodicalId":94338,"journal":{"name":"Journal of pharmaceutical analysis","volume":"16 5","pages":"101641"},"PeriodicalIF":8.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13217494/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148140512","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Authentication of Linderae Radix through plant metabolomics coupled with a machine learning-enhanced <i>in situ</i> hyperspectral imaging approach.","authors":"Yangbin Lv, Hongwei Sun, Qiaoling Ding, Bangxu Chen, Hongwei Ye, Ning Xu, Chu Chu","doi":"10.1016/j.jpha.2025.101476","DOIUrl":"10.1016/j.jpha.2025.101476","url":null,"abstract":"<p><p>Linderae Radix, a medicinally significant herb with a history of over 2000 years, is highly esteemed for its potential to promote longevity. Derived from the tuberous roots of <i>Lindera aggregata</i> (<i>L. aggregata</i>), it encounters difficulties in being distinguished from non-medicinal parts, such as non-fusiform taproots and old roots in the herbal drug market. To address the problem, this study developed a new strategy that integrates non-targeted plant metabolomics with a machine learning-enhanced hyperspectral imaging (HSI) approach for <i>in situ</i> quality assessment. Firstly, a comprehensive metabolomics analysis was conducted using ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) and gas chromatography-mass spectrometry (GC-MS) to identify 25 and 48 differential metabolites, respectively. Then, combined with machine learning algorithms, HSI in the 400-1000 nm band achieved visual <i>in situ</i> assessment of different types of <i>L. aggregata</i> roots. Second derivative (2^ndD)-Savitzky-Golay (SG) smoothing-logistic regression (LR) models achieved 93.33% accuracy of the test set in spectral classification. Moreover, spectral pre-processing and characteristic wavelength selection led to high prediction accuracies for the content of significant components in <i>L. aggregata</i> using standard normal variate (SNV)-competitive adaptive reweighted sampling (CARS)-least squares support vector machine (LSSVM) and SNV-CARS-extreme learning machine (ELM) ( <math> <mrow><msubsup><mi>R</mi> <mi>P</mi> <mn>2</mn></msubsup> </mrow> </math> > 0.87 for the test set). This is the first study to provide a visual representation of the content of marker compounds in <i>L. aggregata</i> roots, offering a rapid, non-destructive method for assessing the quality of Linderae Radix. It scientifically justifies the medicinal use of tuberous roots and illuminates rapid quality evaluation through morphological identification.</p>","PeriodicalId":94338,"journal":{"name":"Journal of pharmaceutical analysis","volume":"16 5","pages":"101476"},"PeriodicalIF":8.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13213644/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148059323","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SMPD1-mediated sphingolipid metabolism dysregulation in predicting and preventing in-stent restenosis of coronary heart disease patients.","authors":"Weiyu Meng, Yuyang Sha, Ci-Ren Zhong-Ga, Hongxin Pan, Xiaobing Zhai, Pu Zhen, Henry H Y Tong, Edmundo Patricio Lopes Lao, Hongjia Zhang, Wenzhi Yang, Song Cui, Xiantao Song, Kefeng Li","doi":"10.1016/j.jpha.2026.101553","DOIUrl":"10.1016/j.jpha.2026.101553","url":null,"abstract":"<p><p>Image 1.</p>","PeriodicalId":94338,"journal":{"name":"Journal of pharmaceutical analysis","volume":"16 5","pages":"101553"},"PeriodicalIF":8.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13141952/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147848433","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing ginsenoside isomers annotation by integrated analysis of electron-activated dissociation and collision-induced dissociation tandem mass spectrometry.","authors":"Wenxiang Fan, Ziwei Li, Longchan Liu, Rufeng Wang, ChenChun Zhong, Kaixian Chen, Zhengtao Wang, Li Yang","doi":"10.1016/j.jpha.2025.101495","DOIUrl":"10.1016/j.jpha.2025.101495","url":null,"abstract":"<p><p>Natural products, with their diverse structures and biological activities, are a critical source for new drug development. Advances in mass spectrometry have significantly enhanced the accurate and rapid identification of natural products. However, differentiating isomers remains a challenge. This study establishes a complementary approach combining collision-induced dissociation (CID) and electron-activated dissociation (EAD) to effectively distinguish isomers, exemplified by ginsenoside isomers. The CID mode clearly distinguishes the structural types of ginsenosides, while EAD mode identifies the substitution sites (e.g., C-3, C-6, C-20) of the glycosyl groups. Mass spectrometry molecular network (MN) analysis showed that, compared to CID-MN, the EAD-MN demonstrated more robust clustering of ginsenosides and more accurately reflected structural similarities of ginsenosides. The developed method enables precise characterization of unknown ginsenoside isomers in <i>Panax</i> species including <i>Panax ginseng</i>, <i>Panax notoginseng</i>, and <i>Panax quinquefolius</i>, and reveals species-specific features, thereby facilitating improved quality control. The proposed strategy effectively addresses the challenge of distinguishing ginsenoside isomers by integrated analysis of CID and EAD tandem mass spectrometry to identify diagnostic ions specific to each isomer. This approach enhances the accuracy of natural product annotation.</p>","PeriodicalId":94338,"journal":{"name":"Journal of pharmaceutical analysis","volume":"16 5","pages":"101495"},"PeriodicalIF":8.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13224131/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148152733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unveiling the multifaceted potential of <i>Artemisia</i>: Cutting-edge insights into nutritional benefits and emerging therapeutic applications.","authors":"Samy Selim, Mohammad Harun-Ur-Rashid, Soad K Al Jaouni","doi":"10.1016/j.jpha.2025.101531","DOIUrl":"10.1016/j.jpha.2025.101531","url":null,"abstract":"<p><p>The <i>Artemisia</i> genus, comprising over 500 species, is a cornerstone of traditional and modern medicine due to its extensive phytochemical diversity and remarkable therapeutic properties. As highlighted in this review, <i>Artemisia</i> demonstrates exceptional potential across nutritional, therapeutic, and industrial domains. The genus is rich in bioactive compounds, including flavonoids, sesquiterpene lactones, and terpenoids, which exhibit potent antioxidant, anti-inflammatory, and antimicrobial effects. Its nutritional benefits are equally notable, with species like <i>Artemisia annua</i> and <i>Artemisia absinthium</i> providing macronutrients, essential minerals, and vitamins critical for metabolic health and immune support. This review systematically explores <i>Artemisia</i>'s role in addressing chronic diseases, including its neuroprotective potential against Alzheimer's desease (AD) and Parkinson's disease (PD) through oxidative stress reduction and inflammatory pathway modulation. Furthermore, <i>Artemisia</i>'s contributions to sustainable agriculture, functional foods, and cosmeceuticals underline its adaptability and economic significance. However, gaps in clinical validation, sustainable cultivation, and regulatory frameworks remain barriers to fully harnessing its potential. Future multidisciplinary research and ethical policies are essential to integrate <i>Artemisia</i> more effectively into global health and industry. The insights provided here aim to inspire innovation in the utilization of <i>Artemisia</i> as a transformative botanical resource for health, industry, and sustainability.</p>","PeriodicalId":94338,"journal":{"name":"Journal of pharmaceutical analysis","volume":"16 5","pages":"101531"},"PeriodicalIF":8.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13199817/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148038835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"BER-Ago: A simultaneous detection and inhibitor screening platform for multiple base excision repair proteins.","authors":"Sheng Ding, Ju Chen, Jing Li, Ting Zhu, Wenyue Jia, Shiqi Xiao, Jin Yang, Dianxiang Lu","doi":"10.1016/j.jpha.2025.101507","DOIUrl":"10.1016/j.jpha.2025.101507","url":null,"abstract":"<p><p>Image 1.</p>","PeriodicalId":94338,"journal":{"name":"Journal of pharmaceutical analysis","volume":"16 5","pages":"101507"},"PeriodicalIF":8.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13199826/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148038818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Protein <i>S</i>-palmitoylation: Potential strategy for inflammation-related diseases.","authors":"Sunan Li, Xinyue Dou, Jiamei Sun, Yongyuan Xiao, Tianyang Wang, Qiyuan Shan, Xin Han, Gang Cao","doi":"10.1016/j.jpha.2025.101490","DOIUrl":"10.1016/j.jpha.2025.101490","url":null,"abstract":"<p><p><i>S</i>-palmitoylation represents a dynamic and reversible modification wherein palmitate forms covalent bonds with cysteine residues in proteins, thereby modifying their localization, stability, signaling pathways, and protein-protein interactions. Aberrations in <i>S</i>-palmitoylation are associated with the progression of various diseases, particularly inflammatory conditions. This association can be attributed to its regulation of pattern recognition receptors (PRRs) and its influence on immune cell functions, including macrophages, T cells, neutrophils, and natural killer cells (NK cells). This review synthesizes current knowledge regarding the impact of <i>S-</i>palmitoylation on inflammation-related diseases through examination of its regulatory roles in PRRs and immune cell functions. The objective is to illuminate the underlying mechanisms and regulatory networks involved in inflammation-related diseases.</p>","PeriodicalId":94338,"journal":{"name":"Journal of pharmaceutical analysis","volume":"16 5","pages":"101490"},"PeriodicalIF":8.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13202024/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148045283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Techniques for the determination of dipeptidyl peptidase IV and screening of its inhibitors.","authors":"Hong-Hong Ma, Xiao-Dong Li, Xing-Kai Qian, Li-Wei Zou","doi":"10.1016/j.jpha.2025.101499","DOIUrl":"10.1016/j.jpha.2025.101499","url":null,"abstract":"<p><p>Dipeptidyl peptidase IV (DPP-IV), an important member of the serine hydrolase family, plays a core regulatory role in various physiological and pathological processes because of its unique broad-spectrum substrate specificity. DPP-IV-mediated proteolytic processing of endogenous peptide substrates serves as a fundamental regulatory mechanism governing physiological processes. An in-depth exploration of the enzymatic characteristics and mechanisms regulating DPP-IV activity will not only provide a theoretical basis for revealing the molecular pathogenesis of related diseases but also contribute to the construction of a complete disease regulatory network map. Furthermore, the development of specific DPP-IV inhibitors constitutes a key strategy for innovative therapy, holding significant promise for clinical translation. This review provides a comprehensive comparison of the applications, merits, and limitations of DPP-IV detection at the messenger RNA (mRNA), protein, and functional levels, along with an in-depth analysis of how DPP-IV enzymatic activity assessment profoundly impacts disease pathogenesis, progression, and therapeutic interventions. Particular emphasis is placed on the superior performance of probes based on drugs and optical substrates (e.g., for fluorescence and bioluminescence) in the functional determination of DPP-IV. Through metabolic phenotyping, we further summarize drug screening systems that target DPP-IV across multiple biological levels, including recombinant proteins (e.g., proteins derived from humans, animals, and <i>gut bacteria</i>), tissues, cells, human organ-on-a-chip models, and whole-animal studies. Furthermore, this review comprehensively evaluates both synthetic and natural DPP-IV inhibitors. Additionally, systematic investigations of their structure-activity relationships (SARs) provide a rational foundation for developing novel inhibitors with enhanced efficacy and safety.</p>","PeriodicalId":94338,"journal":{"name":"Journal of pharmaceutical analysis","volume":"16 5","pages":"101499"},"PeriodicalIF":8.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13199831/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148038794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"UGP system: A deep learning-driven platform for automated identification of ultrafine granular powders using chromatographic fingerprinting.","authors":"Fei Huang, Ya-Ling An, Li-Jie Zhang, Jia-Wei Wang, Ming-Jin Zhang, Zhen-Wei Li, Xiao-Kang Liu, Dai-di Zhang, Qian-Liang Zhang, Li-Hua Peng, Wei-Lin Qiao, De-An Guo","doi":"10.1016/j.jpha.2025.101474","DOIUrl":"10.1016/j.jpha.2025.101474","url":null,"abstract":"<p><p>This study developed an intelligent identification system for ultrafine granular powder (UGP) by integrating high performance liquid chromatography (HPLC) fingerprinting with deep learning algorithms. A comprehensive HPLC fingerprint database encompassing 530 batches from 53 UGP varieties across 29 botanical families was established using a standardized 60-min, six-wavelength detection protocol (210, 230, 254, 280, 327, and 380 nm). Chromatographic reproducibility was ensured with quality control (QC) sample retention time relative standard deviations (RSDs) below 2%. A three-layer one-dimensional convolutional neural network (1D-CNN) was designed with 32, 64, and 128 filters in successive layers for species classification. Data augmentation techniques including noise interference, baseline drift, and retention time shifts (3.5-60 min) expanded the dataset sixfold and enhanced model generalization capabilities. The optimized model achieved excellent performance on test data with 97.62% accuracy, 97.97% precision, and 97.16% recall, demonstrating consistent reproducibility with mean accuracy of 97.2% ± 0.65% across ten independent training runs. External validation using 63 commercial samples yielded 95.24% identification accuracy, confirming practical applicability. The Flask-based web system enables automated workflows from data upload to species identification and is accessible to users without specialized expertise. This work establishes a standardized approach for intelligent authentication of food-medicine homologous Chinese medicinal UGPs, addressing regulatory and consumer requirements for product authenticity and safety in pharmaceutical and functional food industries.</p>","PeriodicalId":94338,"journal":{"name":"Journal of pharmaceutical analysis","volume":"16 5","pages":"101474"},"PeriodicalIF":8.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13217488/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148140532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"DNA-encoded library screening identifies CDK2-targeting lead compounds with favorable drug-like properties for anticancer development.","authors":"Li Zhou, Yong Ju, Zhijuan Cao, Sheng Cai, Jiayuan Su, Jianzhong Lu","doi":"10.1016/j.jpha.2025.101498","DOIUrl":"10.1016/j.jpha.2025.101498","url":null,"abstract":"<p><p>Image 1.</p>","PeriodicalId":94338,"journal":{"name":"Journal of pharmaceutical analysis","volume":"16 5","pages":"101498"},"PeriodicalIF":8.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13217489/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148140529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}