The excipient processing is an essential part of traditional Chinese medicine processing, and understanding its scientific connotations is a critical scientific issue that urgently needs resolution. Building upon a foundation where the composition of traditional Chinese medicine substances is fundamentally clear, this paper applies the techniques and methods of chemoinformatics to the study of the excipient processing mechanism. Relevant information on traditional Chinese medicines processed with four kinds of excipients (wine, vinegar, salt and honey) was collected, including properties, taste, meridian tropism, chemical components, etc. Molecular descritors and skeletons corresponding to each chemical component were calculated using chemoinformatics to characterize the properties and structural features of the components. Characteristic components associated with the four excipients (wine, vinegar, salt and honey) were explored through multivariate statistical analysis and Murcko skeleton analysis. Further analysis, taking honey-processed Astragali Radix as an example, the focus was on the impact of the processing excipient honey on the solubility and permeability of its characteristic pharmacologically active components (isoflavones). It was discovered that the excipient honey can increase their solubility and permeability, emphasizing that the impact of processing excipients on the pharmacological classification properties is a key breakthrough in elucidating the mechanism of excipient processing. In summary, this study analyzed the characteristic components associated with the processing excipients "wine, vinegar, salt and honey" based on their composition characteristics, providing data support for the research on the mechanism of excipient processing from a biopharmaceutical perspective.

ObjectiveTemporal heterogeneity in lung cancer presents as fluctuations in the biological characteristics, genomic mutations, proliferation rates, and chemotherapeutic responses of tumor cells over time, posing a significant barrier to effective treatment. The complexity of this temporal variance, coupled with the spatial diversity of lung cancer, presents formidable challenges for research. This article will pave the way for new avenues in lung cancer research, aiding in a deeper understanding of the temporal heterogeneity of lung cancer, thereby enhancing the cure rate for lung cancer. MethodsRaman spectroscopy emerges as a powerful tool for real-time surveillance of biomolecular composition changes in lung cancer at the cellular scale, thus shedding light on the disease’s temporal heterogeneity. In our investigation, we harnessed Raman spectroscopic microscopy alongside multivariate statistical analysis to scrutinize the biomolecular alterations in human lung epithelial cells across various timeframes after benzo(a)pyrene exposure. ResultsOur findings indicated a temporal reduction in nucleic acids, lipids, proteins, and carotenoids, coinciding with a rise in glucose concentration. These patterns suggest that benzo(a)pyrene induces structural damage to the genetic material, accelerates lipid peroxidation, disrupts protein metabolism, curtails carotenoid production, and alters glucose metabolic pathways. Employing Raman spectroscopy enabled us to monitor the biomolecular dynamics within lung cancer cells in a real-time, non-invasive, and non-destructive manner, facilitating the elucidation of pivotal molecular features. ConclusionThis research enhances the comprehension of lung cancer progression and supports the development of personalized therapeutic approaches, which may improve the clinical outcomes for patients.

Chemical cleaning and disinfection are crucial steps for eliminating infection in root canal treatment.However,irrigant selection or irrigation procedures are far from clear.The vapor lock effect in the apical region has yet to be solved,impeding irrigation efficacy and resulting in residual infections and compromised treatment outcomes.Additionally,ambiguous clinical indications for root canal medication and non-standardized dressing protocols must be clarified.Inappropriate intracanal medication may present side effects and jeopardize the therapeutic outcomes.Indeed,clinicians have been aware of these concerns for years.Based on the current evidence of studies,this article reviews the properties of various irrigants and intracanal medicaments and elucidates their effectiveness and interactions.The evolution of different kinetic irrigation methods,their effects,limitations,the paradigm shift,current indications,and effective operational procedures regarding intracanal medication are also discussed.This expert consensus aims to establish the clinical operation guidelines for root canal irrigation and a position statement on intracanal medication,thus facilitating a better understanding of infection control,standardizing clinical practice,and ultimately improving the success of endodontic therapy.

Objective To quantitatively analyze the impact of environmental hygiene on the occurrence of health-care-associated infections(HAI).Methods Monitoring data of HAI and environmental hygiene from a tertiary first-class hospital from January 2018 to December 2022 were collected,and the impact of environmental bacterial colony forming unit(CFU)on the occurrence of HAI was analyzed by a time-series generalized additive model.Results The single-contamination model showed a significant positive correlation between HAI and staff's hand bacterial CFU(β1=0.009,P=0.012).For an increase of 1 interquartile range(IQR)in the monthly mean CFU per dish(MCFU/Dish)of staffs'hand,the incidence of HAI increased by 13.28％(95％CI:2.82％-24.81％).Subgroup and lag effect analysis showed that when the monthly MCFU/Dish(after hand disinfection)of staffs'hand in-creased by one IQR,the excess risk(ER)of HAI for the month(lag0)was 16.26％(95％CI:15.45％-17.09％).In the multi-contamination model,the correlation between surface contamination and HAI was also statistically sig-nificant.Conclusion There is a significant correlation between hospital environmental hygiene and the occurrence of HAI.

Perihilar cholangiocarcinoma(PHC)is a common malignancy of biliary tract,for which surgery is the most effective treatment.However,its prognosis is not satisfactory even after surgical resection.In recent years,there have been some new advances in the surgical treatment of PHC.In this paper,we reviewed the existing literatures,demonstrated the current situation of preoperative biliary drainage,liver hyperplasia,hepatic resection,liver transplantation and minimally invasive surgery in the treatment of PHC,and prospected the future research direction.

Aim To explore the mechanism and mate-rial basis of Shenkang injection(SKI)in the treatment of renal fibrosis(RF)by bioinformatics and in vitro experiments.Methods The differentially expressed genes of RF were screened by GEO database.With the help of CMAP database,based on the similarity princi-ple of gene expression profile,the drugs that regulated RF were repositioned,and then the components of SKI potential treatment RF were screened by molecular fin-gerprint similarity analysis.At the same time,the core targets and pathways of SKI regulating RF were predic-ted based on network pharmacology.Finally,it was verified by molecular docking and cell experiments.Results Based on the GEO database,two RF-related data sets were screened,and CMAP was relocated to three common RF therapeutic drugs(saracatinib,da-satinib,pp-2).Molecular fingerprint similarity analysis showed that RF therapeutic drugs had high structural similarity with five SKI components such as salvianolic acid B and hydroxysafflor yellow A.Molecular docking results showed that salvianolic acid B,hydroxysafflor yellow A and other components had good binding abili-ty with MMP1 and MMP13,which were the core targets of SKI-regulated potential treatment of RF.Network pharmacology analysis suggested that the core targets of SKI were mainly enriched in signaling pathways such as Relaxin and AGE-RAGE.Cell experiments showed that SKI could significantly reduce the mRNA expres-sion levels of AGER,NFKB1,COL1A1,SERPINE1,VEGFC in AGE-RAGE signaling pathway and MMP1 and MMP13 in Relaxin signaling pathway in RF model cells,and significantly increase the mRNA expression level of RXFP1.Conclusions SKI can play a role in the treatment of RF by regulating Relaxin and AGE-RAGE signaling pathways,and its material basis may be salvianolic acid B,hydroxysafflor yellow A and other components.

Objective:To establish a set of artificial intelligence (AI) verification rules for blood routine analysis.Methods:Blood routine analysis data of 18 474 hospitalized patients from the First Hospital of Jilin University during August 1st to 31st, 2019, were collected as training group for establishment of the AI verification rules,and the corresponding patient age, microscopic examination results, and clinical diagnosis information were collected. 92 laboratory parameters, including blood analysis report parameters, research parameters and alarm information, were used as candidate conditions for AI audit rules; manual verification combining microscopy was considered as standard, marked whether it was passed or blocked. Using decision tree algorithm, AI audit rules are initially established through high-intensity, multi-round and five-fold cross-validation and AI verification rules were optimized by setting important mandatory cases. The performance of AI verification rules was evaluated by comparing the false negative rate, precision rate, recall rate, F1 score, and pass rate with that of the current autoverification rules using Chi-square test. Another cohort of blood routine analysis data of 12 475 hospitalized patients in the First Hospital of Jilin University during November 1sr to 31st, 2023, were collected as validation group for validation of AI verification rules, which underwent simulated verification via the preliminary AI rules, thus performance of AI rules were analyzed by the above indicators. Results:AI verification rules consist of 15 rules and 17 parameters and do distinguish numeric and morphological abnormalities. Compared with auto-verification rules, the true positive rate, the false positive rate, the true negative rate, the false negative rate, the pass rate, the accuracy, the precision rate, the recall rate and F1 score of AI rules in training group were 22.7%, 1.6%, 74.5%, 1.3%, 75.7%, 97.2%, 93.5%, 94.7%, 94.1, respectively.All of them were better than auto-verification rules, and the difference was statistically significant ( P<0.001), and with no important case missed. In validation group, the true positive rate, the false positive rate, the true negative rate, the false negative rate, the pass rate, the accuracy, the precision rate, the recall rate and F1 score were 19.2%, 8.2%, 70.1%, 2.5%, 72.6%, 89.2%, 70.0%, 88.3%, 78.1, respectively, Compared with the auto-verification rules, The false negative rate was lower, the false positive rate and the recall rate were slightly higher, and the difference was statistically significant ( P<0.001). Conclusion:A set of the AI verification rules are established and verified by using decision tree algorithm of machine learning, which can identify, intercept and prompt abnormal results stably, and is moresimple, highly efficient and more accurate in the report of blood analysis test results compared with auto-vefication.

The study aims to investigate and compare the effects of probiotics and docosahexaenoic acid (DHA) with the Alzheimer's disease (AD) therapeutic drug donepezil on the learning cognition and brain damage related indexes in AD mice, and to provide experimental basis for its treatment of AD. All animal experiments were approved by the Ethics Committee of the Henan University of Chinese Medicine (ethics number DWLL2018080003). Fifty male C57BL/6J mice were randomly assigned to one of five groups: sham-operated, model, donepezil (10 mg·kg^-1), probiotic (2.7×10⁹ CFU·d^-1), and DHA (0.104 g·kg^-1). Except for the sham-operated group, the AD animal model was established by injecting Aβ_25-35 (200 μmol·L^-1) in the lateral ventricle, followed by gavage administration for 4 weeks. In all mouse groups, learning memory ability, neuronal morphology in the hippocampus, apoptosis of primary hippocampal cells, and immune cell levels were detected. The levels of Aβ_1-42, Aβ_1-40, p-Tau, AchE, Ach, oxidative stress, glial cell activation, and the inflammatory factors IL-1β, IL-10, and TNF-α in the brain tissue of mice were also detected. 16S rDNA sequencing was used to further investigate the effects of donepezil and probiotics on AD. Donepezil, probiotics and DHA improved cognitive deficits and enhanced learning memory in Aβ_25-35-induced mice by increasing locomotion time, locomotion distance, autonomic alternation rate, and shortening the time to reach the plateau; it significantly attenuated Aβ_25-35-induced brain injury and neuroinflammation in mice by decreasing Aβ_1-42, Aβ_1-40, p-Tau, AchE, IL-1β, TNF-α, and MDA and increasing the levels of Ach, IL-10, GSH-Px, and T-SOD in brain tissues, as well as decreasing the activation of glial cells, and had a modulatory effect on immune cells. 16S rDNA sequencing shows that both donepezil and probiotics restore flora homeostasis and that differential bacteria are strongly associated with cognition, AD pathology, and neuroinflammation. Combining all indicators, donepezil and probiotics were more effective than DHA. All in all, donepezil, probiotics and DHA ameliorate Aβ_25-35-induced cognitive dysfunction and brain damage in mice by modulating immune cells, reducing the number of apoptotic cells and glial cell activation in the brain, and decreasing the levels of oxidative stress and inflammatory factor expression, among which the effects of donepezil and probiotics were better than those of DHA, and the therapeutic effects of donepezil and probiotics on AD were closely related to the modulation of gut microbiome.

Thirteen isoflavones were separated and purified from an ethanol extract of the rhizome of Dalbergia benthamii Prain by using silica gel, Sephadex LH-20, recrystallization et al. Their structures were identified by physicochemical properties and spectral analysis such as MS, 1D/2D-NMR as dalbergibenthamin (1), butesuperin A (2), xanthocercin A (3), butesuperin B (4), di-O-methylalpinum isoflavone (5), 2′-deoxgisoaunculutin (6), robustone (7), 4′-hydroxy-5,7-dimethoxy-6-(3-methyl-2-butenyl)-isoflavone (8), formononetin (9), 6″-O-rhamnosyldaidzin (10), 3′,4′-di-O-methylene-5-hydroxy-7-methoxy-6-isopentenyl isoflavone (11), derrubone dimethyl enter (12), and derrubone (13). Compound 1 is a pair of new isoflavonoid enantiomers, compound 12 is a new natural product and compounds 1-7 and 10-13 were obtained from D. benthamii Prain for the first time. In vitro cytotoxic activities of the compounds were explored by MTS testing with HL-60, A-549, SMMC-7721, MCF-7 and SW480 cell lines. Results show that compound 8 significantly inhibited cellular proliferation. The IC₅₀ of compound 8 in A-549 and SW480 cells was 16.68 ± 0.19 and 15.21 ± 0.60 μmol·L^-1.

In the new stage for intelligent manufacturing of traditional Chinese medicine(TCM) from pilot demonstration to in-depth application and comprehensive promotion, how to raise the degree of intelligence for the process quality control system has become the bottleneck of the development of TCM production process control technology. This article has sorted out 226 TCM intelligent manufacturing projects that have been approved by the national and provincial governments since the implementation of the "Made in China 2025" plan and 145 related pharmaceutical enterprises. Then, the patents applied by these pharmaceutical enterprises were thoroughly retrieved, and 135 patents in terms of intelligent quality control technology in the production process were found. The technical details about intelligent quality control at both the unit levels such as cultivation, processing of crude herbs, preparation pretreatment, pharmaceutical preparations, and the production workshop level were reviewed from three aspects, i.e., intelligent quality sensing, intelligent process cognition, and intelligent process control. The results showed that intelligent quality control technologies have been preliminarily applied to the whole process of TCM production. The intelligence control of the extraction and concentration processes and the intelligent sensing of critical quality attributes are currently the focus of pharmaceutical enterprises. However, there is a lack of process cognitive patent technology for the TCM manufacturing process, which fails to meet the requirements of closed-loop integration of intelligent sensing and intelligent control technologies. It is suggested that in the future, with the help of artificial intelligence and machine learning methods, the process cognitive bottleneck of TCM production can be overcome, and the holistic quality formation mechanisms of TCM products can be elucidated. Moreover, key technologies for system integration and intelligent equipment are expected to be innovated and accelerated to enhance the quality uniformity and manufacturing reliability of TCM.
Artificial Intelligence ; Medicine, Chinese Traditional ; Reproducibility of Results ; Quality Control ; Intelligence ; Pharmaceutical Preparations