The use of wastewater analysis, or wastewater-based epidemiology, to assess and monitor the situation of drug abuse is now widely used at home and abroad. However, there is currently a lack of effective evaluation methods and effective ways of comparison, supervision and standardization, which is not conducive to the analysis and comparisons of data in different countries and regions. Quality control techniques can control the laboratory's analytical errors, safeguard the consistency and comparability of identification conclusions, and promote the further improvement of the level and capacity of urban drug governance, thus playing significant roles. This paper provides an overview of sample collection, sample preservation and transportation, laboratory analysis, back-calculation of drug use and external laboratory quality control in the process of wastewater analysis, with a view to exploring more comprehensive scientific and objective methods and approaches suitable for examining and evaluating qualitative and quantitative analysis of drugs in wastewater among laboratories.

ObjectiveTraditional Chinese medicine (TCM) constitutes a valuable cultural heritage and an important source of antitumor compounds. Poria (Poria cocos (Schw.) Wolf), the dried sclerotium of a polyporaceae fungus, was first documented in Shennong’s Classic of Materia Medica and has been used therapeutically and dietarily in China for millennia. Traditionally recognized for its diuretic, spleen-tonifying, and sedative properties, modern pharmacological studies confirm that Poria exhibits antioxidant, anti-inflammatory, antibacterial, and antitumor activities. Pachymic acid (PA; a triterpenoid with the chemical structure 3β-acetyloxy-16α-hydroxy-lanosta-8,24(31)-dien-21-oic acid), isolated from Poria, is a principal bioactive constituent. Emerging evidence indicates PA exerts antitumor effects through multiple mechanisms, though these remain incompletely characterized. Neuroblastoma (NB), a highly malignant pediatric extracranial solid tumor accounting for 15% of childhood cancer deaths, urgently requires safer therapeutics due to the limitations of current treatments. Although PA shows multi-mechanistic antitumor potential, its efficacy against NB remains uncharacterized. This study systematically investigated the potential molecular targets and mechanisms underlying the anti-NB effects of PA by integrating network pharmacology-based target prediction with experimental validation of multi-target interactions through molecular docking, dynamic simulations, and in vitro assays, aimed to establish a novel perspective on PA’s antitumor activity and explore its potential clinical implications for NB treatment by integrating computational predictions with biological assays. MethodsThis study employed network pharmacology to identify potential targets of PA in NB, followed by validation using molecular docking, molecular dynamics (MD) simulations, MM/PBSA free energy analysis, RT-qPCR and Western blot experiments. Network pharmacology analysis included target screening via TCMSP, GeneCards, DisGeNET, SwissTargetPrediction, SuperPred, and PharmMapper. Subsequently, potential targets were predicted by intersecting the results from these databases via Venn analysis. Following target prediction, topological analysis was performed to identify key targets using Cytoscape software. Molecular docking was conducted using AutoDock Vina, with the binding pocket defined based on crystal structures. MD simulations were performed for 100 ns using GROMACS, and RMSD, RMSF, SASA, and hydrogen bonding dynamics were analyzed. MM/PBSA calculations were carried out to estimate the binding free energy of each protein-ligand complex. In vitro validation included RT-qPCR and Western blot, with GAPDH used as an internal control. ResultsThe CCK-8 assay demonstrated a concentration-dependent inhibitory effect of PA on NB cell viability. GO analysis suggested that the anti-NB activity of PA might involve cellular response to chemical stress, vesicle lumen, and protein tyrosine kinase activity. KEGG pathway enrichment analysis suggested that the anti-NB activity of PA might involve the PI3K/AKT, MAPK, and Ras signaling pathways. Molecular docking and MD simulations revealed stable binding interactions between PA and the core target proteins AKT1, EGFR, SRC, and HSP90AA1. RT-qPCR and Western blot analyses further confirmed that PA treatment significantly decreased the mRNA and protein expression of AKT1, EGFR, and SRC while increasing the HSP90AA1 mRNA and protein levels. ConclusionIt was suggested that PA may exert its anti-NB effects by inhibiting AKT1, EGFR, and SRC expression, potentially modulating the PI3K/AKT signaling pathway. These findings provide crucial evidence supporting PA’s development as a therapeutic candidate for NB.

Elemene, derived from Curcuma wenyujin, one of the "8 famous genuine medicinal materials of Zhejiang province," exhibits remarkable antitumor activity. It has gained wide recognition in clinical practice for effectiveness on tumors. Dr. XIE Tian, introduced the innovative concept of "molecular compatibility theory" by combining Chinese medicine principles, specifically the "monarch, minister, assistant, and envoy" theory, with modern biomedical technology. This groundbreaking approach, along with a systematic analysis of Chinese medicine and modern biomedical knowledge, led to the development of elemene nanoliposome formulations. These novel formulations offer numerous advantages, including low toxicity, well-defined composition, synergistic effects on multiple targets, and excellent biocompatibility. Following the principles of the "molecular compatibility theory", further exploration of cancer treatment strategies and methods based on elemene was undertaken. This comprehensive review consolidates the current understanding of elemene's potential antitumor mechanisms, recent clinical investigations, advancements in drug delivery systems, and structural modifications. The ultimate goal of this review is to establish a solid theoretical foundation for researchers, empowering them to develop more effective antitumor drugs based on the principles of "molecular compatibility theory".
Humans ; Retrospective Studies ; Antineoplastic Agents/therapeutic use* ; Neoplasms/drug therapy* ; Drugs, Chinese Herbal/therapeutic use* ; Sesquiterpenes/therapeutic use*

Natural products are important sources of drug discovery. However, the traditional methods of extraction and isolation, as well as chemical synthesis for obtaining natural products are associated with issues such as operational complexity, high costs, low efficiency, and environmental pollution. Constructing microbial cell factories through synthetic biology methods to produce medicinal natural products has the advantages of high efficiency, low cost, and environmental protection. Nevertheless, the scope and yield improvement of the products are limited by the limitations of enzymes in microbial cell factories. Protein engineering is considered one of the most effective approaches to overcome these limitations. This article introduces commonly used methods of protein engineering technology and summarizes its specific applications in improving enzyme performance, modifying the enzymatic environment, and promoting the development of synthetic biology tools in the field of pharmaceutical natural product synthesis. Furthermore, it analyzes the current bottlenecks and challenges in protein engineering and looks forward to its future application prospects, offering insights for the development and practical use of protein engineering technology.

In recent years, polysaccharides have received much attention because of their high safety and good immunological activity. The study of polysaccharide in vivo process is a key scientific problem that needs to be solved for polysaccharide drug development. Some progress has been made in the field of polysaccharide pharmacokinetics and immunomodulation. However, due to the lack of both chromogenic and light-absorbing groups and the complex molecular structure of polysaccharides, the in vivo processes and immunomodulatory mechanisms of polysaccharides have been slow to be investigated. The effective combination of multiple techniques can break the bottleneck of difficult tracing and unknown immunomodulatory mechanism of polysaccharides in vivo, and promote the development and utilization of polysaccharides. In this paper, we systematically summarize the key techniques in the study of polysaccharide in vivo processes and immunomodulatory mechanisms in order to provide technical references and research ideas for the study of polysaccharide in vivo processes and immunomodulatory mechanisms.

Objective To investigate the diagnostic efficiency of artificial intelligence(AI)in rib frac-ture under the computed tomography(CT)images with different reconstruction slice thickness.Methods The first CT images of 100 patients with rib fractures were selected,and the interval-free recon-struction was carried out with the thickness of 0.625 mm,1.250 mm,2.500 mm and 5.000 mm,respectively.The rib fracture screening function of AI was used to automatically detect the CT images of four groups,and the diagnostic efficiency of AI for rib fracture under different reconstruction thickness conditions was com-pared.Results The sensitivity of AI in the diagnosis of rib fracture at 0.625 mm,1.250 mm,2.500 mm and 5.000 mm thickness was 99.32%(436/439),98.41%(432/439),89.52%(393/439)and 83.60%(367/439),respectively.The false positive rate was 4.80%(22/458),0.92%(4/436),0.76%(3/396)and 0.27%(1/368).The diagnostic sensitivity of AI in 0.625 mm and 1.250 mm thickness was higher than that in 2.500 mm and 5.000 mm,and the difference was statistically significant(P<0.05),while there was no significant difference in the thickness of 0.625 mm and 1.250 mm.The false positive rate of AI in the diagnosis of 0.625 mm slice thickness was higher than that of 1.250 mm,2.500 mm and 5.000 mm,and the difference was sta-tistically significant(P<0.05),while there was no significant difference in the thickness of 1.250 mm,2.500 mm and 5.000 mm(P>0.05).Conclusion The diagnostic efficiency of AI in 1.250 mm CT images is better than that in 0.625 mm,2.500 mm and 5.000 mm CT images.

ObjectiveGastric cancer (GC) seriously affects human health and life, and research has shown that it is closely related to the serine/glycine metabolism. The proliferation ability of tumor cells is greatly influenced by the metabolism of serine and glycine. The aim of this study was to investigate the molecular mechanism of serine/glycine metabolism can affect the proliferation of gastric cancer cells. MethodsIn this work, a stable metabolic dynamic model of gastric cancer cells was established via a large-scale metabolic network dynamic modeling method in terms of a potential landscape description of stochastic and non-gradient systems. Based on the regulation of the model, a quantitative analysis was conducted to investigate the dynamic mechanism of serine/glycine metabolism affecting the proliferation of gastric cancer cells. We introduced random noise to the kinetic equations of the general metabolic network, and applied stochastic kinetic decomposition to obtain the Lyapunov function of the metabolic network parameter space. A stable metabolic network was achieved by further reducing the change in the Lyapunov function tied to the stochastic fluctuations. ResultsDespite the unavailability of a large number of dynamic parameters, we were able to successfully construct a dynamic model for the metabolic network in gastric cancer cells. When extracellular serine is available, the model preferentially consumes serine. In addition, when the conversion rate of glycine to serine increases, the model significantly upregulates the steady-state fluxes of S-adenosylmethionine (SAM) and S-adenosyl homocysteine (SAH). ConclusionIn this paper, we provide evidence supporting the preferential uptake of serine by gastric cancer cells and the important role of serine/glycine conversion rate in SAM generation, which may affect the proliferation ability of gastric cancer cells by regulating the cellular methylation process. This provides a new idea and direction for targeted cancer therapy based on serine/glycine metabolism.

BACKGROUND:Bibliometrics and visual analyses based on thematic literature are particularly important for understanding the foundation and frontiers of postmenopausal osteoporosis research. OBJECTIVE:To perform bibliometric,citation,and visualization analyses of highly cited SCI papers in postmenopausal osteoporosis research over the last 20 years. METHODS:The top 100 highly cited papers on postmenopausal osteoporosis published between 2003 and 2022 included in SCI-EXPANDED catalog of the Web of Science database were obtained for bibliometric measure and visual analysis using CiteSpace software. RESULTS AND CONCLUSION:The top 100 highly cited papers have a total of 67 377 citations in the Web of Science Core Collection,with an annual average of 49.17 citations per paper.Postmenopausal osteoporosis research primarily involves medical,engineering,biological,and multidisciplinary fields.The subcategories are dominated by endocrinology and metabolism,and medicine:internal medicine.Stable and close cooperative network relationships have been formed globally.United States,University of California System,Cummings,and Steven R are the country,research institution,and author,respectively,with the most highly-cited publications.The frontiers of postmenopausal osteoporosis research mainly include calcium and vitamin D supplementation and fracture risk,clinical studies of bisphosphonates in the treatment of postmenopausal osteoporosis,atypical femur fracture,clinical studies of new drugs and sequential treatment of postmenopausal osteoporosis,predictors of fracture risk,mid-and long-term follow-up of osteoporotic vertebral compression fractures,genetic polymorphisms and hereditary factors,formulation and updating of clinical practice guidelines for postmenopausal osteoporosis.Large cohort studies,high-quality randomized controlled trials,systematic reviews,meta-analyses,and clinical practice guidelines are the great engines that drive the development of clinical research in postmenopausal osteoporosis.We should make efforts in the above areas to improve China's international influence in the field of osteoporosis.

Cervical cancer is the leading cause of cancer death in women in the developing countries.The treatment based on surgery,radiotherapy and chemotherapy is often accompanied by intolerable complications.Clinical practice has proved that TCM therapy has a positive effect on the complications related to the treatment of cervical cancer,but there is still a lack of scientific and standardized application reference opinions.Based on Delphi method,our research group constructed and formulated an expert consensus study on the complications related to the treatment of cervical cancer with TCM therapies,so as to provide a reference for clinical treatment of such diseases.

With the development of more and more multi-center and cross-field cooperative medical research,the establishment of high-quality and efficient ethical collaborative review and mutual recognition systems is an inevitable demand for multi-institutional research,and an inevitable move to implement relevant national policies.Based on the work practice of ethical collaborative review and mutual recognition in Shenzhen,by analyzing the practical challenges of ethical collaborative review and mutual recognition in China,this paper proposed that to ensure the homogeneity and efficiency of review.Government departments need to take the lead,establish an ethical review alliance,and clarify responsibilities and rights.Based on actual needs,system first,and effective communication,ethical collaborative review and mutual recognition of results could be jointly promoted,aiming to provide a reference for our counterparts in China to promote ethical collaborative review and mutual recognition of cross-institutional research.