The Pharmacopeia of the People’s Republic of China 2025 Edition (referred to as the Chinese Pharmacopoeia 2025 Edition, ChP 2025) will be promulgated and implemented. This article introduces the process of development of ChP 2025 Edition (Volume Ⅱ), including the selection, the revision of general notices,the addition and revision of drug monographs, etc., and provides some analysis and examples to illustrate,which can facilitate the readers to understand and implement the ChP 2025 Edition (Volume Ⅱ).

Wilson disease is a copper metabolism disorder caused by mutations in the ATP7B gene， which encodes a copper-transporting ATPase β， and can result in multisystem damage. The kidneys are the third most commonly affected organs after the liver and brain. In recent years， numerous diagnostic and treatment guidelines for Wilson disease have emerged. However， most of these focus primarily on hepatic and neurological manifestations and their management， with limited coverage of renal involvement. The high incidence， low awareness， and lack of clinical specificity of Wilson disease-related renal damage （WDRD） have made early detection and intervention particularly challenging in clinical practice. To further optimize the treatment of patients with WDRD， improve clinical diagnosis and management， and enhance patients' quality of life， the Neurology Committee of the Chinese Association of Integrative Medicine， in April 2024， initiated a revision of the first expert consensus on the integrated diagnosis， treatment， and management of WDRD. This effort brought together experts in hepatology， encephalopathy （neurology）， and nephrology from many tertiary-level grade A hospitals and research institutions across China. Through comprehensive literature review and integration of frontline clinical experience， the expert group jointly developed Chinese Expert Consensus on Integrated Chinese and Western Medicine Management of Wilson Disease-related Renal Damage （hereinafter referred to as the "Consensus"）. This article provides a detailed interpretation of the Consensus in terms of diagnostic criteria， traditional Chinese medicine （TCM） syndrome differentiation and treatment classification， and comprehensive disease management， aiming to better guide clinical application. Regarding diagnostic criteria， the Consensus integrates the latest standards in China and abroad， highlights the importance of biochemical diagnosis， and compensates for the limitations of genetic testing. In the area of TCM syndrome differentiation and treatment， the Consensus refines four major syndrome types， introduces a newly defined syndrome， i.e.， phlegm， blood stasis， and heat accumulation， and elaborates on treatment principles， prescriptions， and clinical modification rules for each syndrome. For comprehensive disease management， the Consensus emphasizes multi-dimensional intervention strategies， including diet， exercise， emotional regulation， medication， and medical care， with the goal of maximally controlling the progression of renal dysfunction and helping patients achieve a better quality of life.

ObjectiveTransfer RNA-derived fragments (tRFs) are a recently characterized and rapidly expanding class of small non-coding RNAs, typically ranging from 13 to 50 nucleotides in length. They are derived from mature or precursor tRNA molecules through specific cleavage events and have been implicated in a wide range of cellular processes. Increasing evidence indicates that tRFs play important regulatory roles in gene expression, primarily by interacting with target messenger RNAs (mRNAs) to induce transcript degradation, in a manner partially analogous to microRNAs (miRNAs). However, despite their emerging biological relevance and potential roles in disease mechanisms, there remains a significant lack of computational tools capable of systematically predicting the interaction landscape between tRFs and their target mRNAs. Existing databases often rely on limited interaction features and lack the flexibility to accommodate novel or user-defined tRF sequences. The primary goal of this study was to develop a machine learning based prediction algorithm that enables high-throughput, accurate identification of tRF:mRNA binding events, thereby facilitating the functional analysis of tRF regulatory networks. MethodsWe began by assembling a manually curated dataset of 38 687 experimentally verified tRF:mRNA interaction pairs and extracting seven biologically informed features for each pair: (1) AU content of the binding site, (2) site pairing status, (3) binding region location, (4) number of binding sites per mRNA, (5) length of the longest consecutive complementary stretch, (6) total binding region length, and (7) seed sequence complementarity. Using this dataset and feature set, we trained 4 distinct machine learning classifiers—logistic regression, random forest, decision tree, and a multilayer perceptron (MLP)—to compare their ability to discriminate true interactions from non-interactions. Each model’s performance was evaluated using overall accuracy, receiver operating characteristic (ROC) curves, and the corresponding area under the ROC curve (AUC). The MLP consistently achieved the highest AUC among the four, and was therefore selected as the backbone of our prediction framework, which we named tRF Prospect. For biological validation, we retrieved 3 high-throughput RNA-seq datasets from the gene expression omnibus (GEO) in which individual tRFs were overexpressed: AS-tDR-007333 (GSE184690), tRF-3004b (GSE197091), and tRF-20-S998LO9D (GSE208381). Differential expression analysis of each dataset identified genes downregulated upon tRF overexpression, which we designated as putative targets. We then compared the predictions generated by tRF Prospect against those from three established tools—tRFTar, tRForest, and tRFTarget—by quantifying the number of predicted targets for each tRF and assessing concordance with the experimentally derived gene sets. ResultsThe proposed algorithm achieved high predictive accuracy, with an AUC of 0.934. Functional validation was conducted using transcriptome-wide RNA-seq datasets from cells overexpressing specific tRFs, confirming the model’s ability to accurately predict biologically relevant downregulation of mRNA targets. When benchmarked against established tools such as tRFTar, tRForest, and tRFTarget, tRF Prospect consistently demonstrated superior performance, both in terms of predictive precision and sensitivity, as well as in identifying a higher number of true-positive interactions. Moreover, unlike static databases that are limited to precomputed results, tRF Prospect supports real-time prediction for any user-defined tRF sequence, enhancing its applicability in exploratory and hypothesis-driven research. ConclusionThis study introduces tRF Prospect as a powerful and flexible computational tool for investigating tRF:mRNA interactions. By leveraging the predictive strength of deep learning and incorporating a broad spectrum of interaction-relevant features, it addresses key limitations of existing platforms. Specifically, tRF Prospect: (1) expands the range of detectable tRF and target types; (2) improves prediction accuracy through multilayer perceptron model; and (3) allows for dynamic, user-driven analysis beyond database constraints. Although the current version emphasizes miRNA-like repression mechanisms and faces challenges in accurately capturing 5'UTR-associated binding events, it nonetheless provides a critical foundation for future studies aiming to unravel the complex roles of tRFs in gene regulation, cellular function, and disease pathogenesis.

With the widespread adoption of low-dose CT screening and the extensive application of high-resolution CT, the detection rate of sub-centimeter lung nodules has significantly increased. How to scientifically manage these nodules while avoiding overtreatment and diagnostic delays has become an important clinical issue. Among them, lung nodules with a consolidation tumor ratio less than 0.25, dominated by ground-glass shadows, are particularly worthy of attention. The therapeutic challenge for this group is how to achieve precise and complete resection of nodules during surgery while maximizing the preservation of the patient's lung function. The "watershed topography map" is a new technology based on big data and artificial intelligence algorithms. This method uses Dicom data from conventional dose CT scans, combined with microscopic (22-24 levels) capillary network anatomical watershed features, to generate high-precision simulated natural segmentation planes of lung sub-segments through specific textures and forms. This technology forms fluorescent watershed boundaries on the lung surface, which highly fit the actual lung anatomical structure. By analyzing the adjacent relationship between the nodule and the watershed boundary, real-time, visually accurate positioning of the nodule can be achieved. This innovative technology provides a new solution for the intraoperative positioning and resection of lung nodules. This consensus was led by four major domestic societies, jointly with expert teams in related fields, oriented to clinical practical needs, referring to domestic and foreign guidelines and consensus, and finally formed after multiple rounds of consultation, discussion, and voting. The main content covers the theoretical basis of the "watershed topography map" technology, indications, operation procedures, surgical planning details, and postoperative evaluation standards, aiming to provide scientific guidance and exploration directions for clinical peers who are currently or plan to carry out lung nodule resection using the fluorescent microscope watershed analysis method.

Objective: To systematically evaluate the influencing factors for autism spectrum disorder (ASD) in Chinese children, so as to provide the evidence for risk prediction and intervention of ASD. Methods: The publications pertaining to the influencing factors for ASD in Chinese children were retrieved from CNKI, Wanfang Data, VIP, PubMed and Embase database from inception to August 2024. A meta-analysis was performed using R package version 4.4.1. Sensitivity analysis was performed using the "leave-one-out" evaluation procedure. Publication bias was assessed using Egger regression test. Results: A total of 38 high-quality articles out of 9 015 articles were finally included, covering 149 607 individuals, with 5 974 cases of ASD. The meta-analysis showed that demographic factors including family history of related diseases (OR=14.958), maternal age of ≥35 years (OR=2.287) and parental history of hazardous occupations (OR=3.511); pregnancy-related factors including history of abortion (OR=5.832), no folate supplementation before and during pregnancy (OR=4.566), tobacco exposure before and during pregnancy (OR=2.596), history of other adverse exposures before and during pregnancy (OR=3.533), history of infectious diseases during pregnancy (OR=3.753), history of non-infectious diseases during pregnancy (OR=2.563), psychological problems during pregnancy (OR=3.864), history of medication during pregnancy (OR=6.651), adverse environmental exposures during pregnancy (OR=3.754), severe pregnancy reactions (OR=5.082), abnormal perinatal period (OR=2.987), cesarean delivery (OR=1.659), other perinatal adverse factors (OR=3.856), history of neonatal asphyxia (OR=2.792) and neonatal jaundice (OR=3.687); parenting factors including non-exclusive breastfeeding (OR=2.510), early/excessive screen exposure (OR=3.589) and feeding problems (OR=3.113); and individual factors including being male (OR=3.333) and history of convulsions/epilepsy (OR=7.035) were influencing factors for ASD in Chinese children. Conclusions The prevalence of ASD in Chinese children is primarily associated with 23 influencing factors, including family history of related diseases, history of abortion, no folate supplementation before and during pregnancy, medication during pregnancy, early/excessive screen exposure and history of convulsions/epilepsy.

This paper summarizes Professor Gao Jiansheng's clinical experience in treating herpes simplex keratitis （HSK） based on the theory of hidden pathogens. It is believed that the core pathogenesis of HSK involves deficiency of vital qi and the internal presence of pathogenic factors. In the early stage， the pathogenesis is characterized by lung and spleen qi deficiency and invasion of external pathogens. In the middle stage， pathogenesis worsens due to latent pathogens damaging the vital qi and spleen deficiency with dampness. In the late stage， kidney yang deficiency and lingering pathogenic toxins are the root cause of recurrent attacks. In clinical practice， it is recommended to strengthen and protect the vital qi. In the early stage， the Modified Yupingfeng Powder （玉屏风散） is used. In the middle stage， the Modified Linggui Zhugan Decoction （苓桂术甘汤） is used. In the late stage， a self-formulated Modified Bushen Tuodu Fomulation （补肾托毒方） is applied. Additionally， herbs of tonifying qi and strengthening the exterior are used throughout the treatment to reduce recurrence.

Andrographolide sulfonate (AS) is a sulfonated derivative of andrographolide extracted from Andrographis paniculata (Burm.f.) Nees, and has been approved for several decades in China. The present study aimed to investigate the novel therapeutic application and possible mechanisms of AS in the treatment of rheumatoid arthritis. Results indicated that administration of AS by injection or gavage significantly reduced the paw swelling, improved body weights, and attenuated pathological changes in joints of rats with adjuvant-induced arthritis. Additionally, the levels of tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), and IL-1β in the serum and ankle joints were reduced. Bioinformatics analysis, along with the spleen index and measurements of IL-17 and IL-10 levels, suggested a potential relationship between AS and Th17 cells under arthritic conditions. In vitro, AS was shown to block Th17 cell differentiation, as evidenced by the reduced percentages of CD4⁺ IL-17A⁺ T cells and decreased expression levels of RORγt, IL-17A, IL-17F, IL-21, and IL-22, without affecting the cell viability and apoptosis. This effect was attributed to the limited glycolysis, as indicated by metabolomics analysis, reduced glucose uptake, and pH measurements. Further investigation revealed that AS might bind to hexokinase2 (HK2) to down-regulate the protein levels of HK2 but not glyceraldehyde-3-phosphate dehydrogenase (GAPDH) or pyruvate kinase M2 (PKM2), and overexpression of HK2 reversed the inhibition of AS on Th17 cell differentiation. Furthermore, AS impaired the activation of phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT) signals in vivo and in vitro, which was abolished by the addition of lactate. In conclusion, AS significantly improved adjuvant-induced arthritis (AIA) in rats by inhibiting glycolysis-mediated activation of PI3K/AKT to restrain Th17 cell differentiation.
Animals ; Th17 Cells/immunology* ; Diterpenes/pharmacology* ; Arthritis, Rheumatoid/metabolism* ; Proto-Oncogene Proteins c-akt/immunology* ; Glycolysis/drug effects* ; Cell Differentiation/drug effects* ; Phosphatidylinositol 3-Kinases/genetics* ; Rats ; Male ; Rats, Sprague-Dawley ; Humans ; Andrographis paniculata/chemistry* ; Arthritis, Experimental/drug therapy* ; Interleukin-17/immunology* ; Signal Transduction/drug effects*

ObjectiveTo investigate the incidence rate of sarcopenia in patients with Wilson’s disease （WD）-related liver cirrhosis， as well as the risk factors for sarcopenia and their impact on clinical outcomes. MethodsA total of 140 patients with WD-related liver cirrhosis who were treated in The First Affiliated Hospital of Anhui University of Chinese Medicine from January 2019 to June 2020， and according to the third lumbar skeletal muscle mass index （L3 SMI）， the patients were divided into sarcopenia group and non-sarcopenia group. Nutritional risk screening， anthropometric measurements， and blood biochemical tests were performed for the patients to identify the influencing factors for sarcopenia. The patients were followed up for 36 — 48 months， and survival status and complications were compared between the two groups. The independent-samples t test was used for comparison of normally distributed continuous data between two groups， and the chi-square test and the Mann-Whitney U rank sum test were used for comparison of categorical data between two groups. A binary Logistic regression analysis was used to investigate the influencing factors for sarcopenia， and univariate and multivariate Cox regression analyses were used to investigate the risk factors for the prognosis of patients with WD-related liver cirrhosis. The Kaplan-Meier survival curve was plotted， and the Log-rank test was used for comparison between groups. ResultsAmong the 140 patients with WD-related liver cirrhosis， 53 （37.9%） developed sarcopenia， with significantly lower body mass index （BMI） and L3 SMI than the patients without sarcopenia （t=10.550 and 3.982， both P<0.001）. The multivariate Logistic regression analysis showed that age （odds ratio ［OR］=2.243， 95% confidence interval ［CI］： 1.196 — 4.208， P=0.012）， sex （OR=0.450， 95%CI： 0.232 — 0.872， P=0.018）， BMI （OR=0.126， 95%CI： 0.089 — 0.294， P<0.001）， and hepatic encephalopathy （OR=8.367， 95%CI： 2.423 — 28.897， P<0.001） were the main influencing factors for sarcopenia in patients with WD-related liver cirrhosis. Compared with the non-sarcopenia group， the sarcopenia group had significantly higher mortality rate （χ²=6.158， P=0.019） and significantly higher incidence rates of infection （χ²=8.008， P=0.040）， recurrent abdominal/pleural efflux （χ²=17.742， P<0.001）， and hepatic encephalopathy （χ²=4.338， P=0.039）. The multivariate Cox regression analysis showed that sarcopenia （hazard ratio ［HR］=4.685， P=0.002） and hepatic encephalopathy （HR=19.156， P<0.001） were independent risk factors for death in patients with WD-related liver cirrhosis. The Kaplan-Meier survival curve analysis showed a significant reduction in survival rate in the patients with sarcopenia （P=0.003）. ConclusionSarcopenia is one of the manifestations of malnutrition in patients with WD-related liver cirrhosis， which increases the risk of mortality and other complications and has an adverse effect on prognosis. There is an increased risk of sarcopenia in male patients or patients with hepatic encephalopathy， a lower level of BMI or an older age.

Abstract In recent years, the prevalence of overweight and obesity among children and adolescents has risen rapidly, posing a serious threat to their physical and mental health. To provide scientific, systematic, and standardized weight management guidance for overweight and obese children and adolescents, the study focuses on the core concept of healthy lifestyle intervention, integrates multidisciplinary expert opinions and research findings,and proposes a comprehensive multidisciplinary intervention framework covering scientific exercise intervention, precise nutrition and diet, optimized sleep management, and standardized psychological support. It calls for the establishment of a multi agent collaborative management mechanism led by the government, implemented by families, fostered by schools, initiated by individuals, optimized by communities, reinforced by healthcare, and coordinated by multiple stakeholders. Emphasizing a child and adolescent centered approach, the consensus advocates for comprehensive, multi level, and personalized guidance strategies to promote the internalization and maintenance of a healthy lifestyle. It serves as a reference and provides recommendations for the effective prevention and control of overweight and obesity, and enhancing the health level of children and adolescents.