Functional dyspepsia （FD） is a prioritized disease category where traditional Chinese medicine （TCM） demonstrates distinct therapeutic advantages. The current western medicine treatment for FD is mainly based on proton pump inhibitors and prokinetic agents， with digestive enzymes， probiotics and antidepressants serving as adjuvant medication， yet such therapies still have certain limitations. TCM treatment for FD includes oral administration of Chinese herbal formulas and Chinese patent medicines， as well as external TCM therapies such as acupuncture and moxibustion， acupoint application， hot medicinal compress therapy， rubbing with ointment， medicinal iontophoresis， auricular acupoint therapy and tui na （Chinese medical massage）. The combined treatment of FD with integrated TCM and western medicine can significantly improve clinical effectiveness and reduce adverse reactions. The common mechanisms underlying the therapeutic effects of both TCM and western medicine revolve around the core pathological processes of FD， mainly focusing on restoring gastrointestinal motility， regulating the levels of brain-gut peptides， modulating intestinal microecology， and ameliorating inflammatory status. The differential mechanisms lie in the precise targeting feature of western medicine versus the holistic-regulating and multi-target characteristics of TCM， and the two approaches exert a synergistic effect to enhance efficacy. This paper proposes to leverage the advantages of TCM in holistic regulation and the strengths of western medicine in targeted treatment， so as to provide personalized and comprehensive treatment regimens for FD patients.

The chapter Zhouyu in Guoyu says "Qi of the heaven and the earth moves without losing its order." With lucidity ascending and turbidity descending， Qi moves in a normal state， and Yin and Yang consolidate the foundation of the body. The mutual interference between lucidity and turbidity leads to the disorder of Qi movement， thus causing diseases. It is a pathological state of disorder between ascending and descending， as well as between entering and exiting， gradually evolving into a state of turbidity affecting lucidity and transforming into pathogen， which can be used to interpret and analyze the core of disease pathogenesis. The theory of lucidity and turbidity is connected with the harmony of nutrient and defensive aspects， Qi circulation， and sweat pore associating with Qi movement， and it has common implications with immune responses and nutrient metabolism system， intestinal mucosal barrier function， and mitochondrial energy synthesis. Modern studies have shown that intestinal flora imbalance， bile acid receptor inactivation， macrophage polarization imbalance， epithelial-mesenchymal transition， ferroptosis and other related microscopic pathological mechanisms are involved in the development and progression of ulcerative colitis. By delving into the common meaning of the classic theory of mutual interference between lucidity and turbidity in traditional Chinese medicine and modern medical pathological mechanisms， this paper summarizes the correspondence between the micropathological mechanism and the theory of mutual interference between lucidity and turbidity in the regulation and mamagement of ulcerative colitis. The combined use of sweet and warm medicinal materials consolidates the middle Qi and activates Qi circulation， thus ascending lucidity and descending turbidity. The combined use of pungent medicinal materials for dispersing and bitter medicinal materials for descending simultaneously raises warm and clear Qi. Wind-extinguishing medicinal materials facilitate the ascending of Qi and the opening of sweat pores. Accordingly， turbidity descends and lucidity ascends. The prescriptions incorporating these medication principles are in agreement with the therapeutic approach of following the normal flow of lucidity and turbidity. This paper clarifies the scientific connotation and micropathologic mechanism of ulcerative colitis from the perspective of mutual interference between lucidity and turbidity， providing new theories and prescriptions for the clinical diagnosis， treatment， and prevention of ulcerative colitis.

OBJECTIVE To develope a predictive model for medication deviation risks during the hospital-to-home transition period in coronary heart disease （CHD） patients with initial treatment， aiming to assist medical staff in rapidly identifying high-risk groups for medication deviation. METHODS A total of 462 CHD patients with initial treatment from the Affiliated Hospital of North China University of Science and Technology （hereinafter referred to as “our hospital”） between January and July 2024 were enrolled. The patients were randomly divided into a modeling group and an internal validation group. The modeling group was further categorized into a medication deviation group and a non-medication deviation group based on whether medication deviations occurred. Similarly， 57 CHD patients with initial treatment from the cardiology department of our hospital between June and September 2025 were collected as an external validation group. Univariate analysis was used to screen predictive factors， followed by multivariate Logistic regression to construct the predictive model. Internal validation methods were employed to evaluate model performance， while external validation methods were used to test the model’s generalizability. RESULTS The 462 patients were divided into a modeling group （319 cases） and an internal validation group （143 cases）. In the modeling group， the medication deviation group （192 cases， 60.19%） and the non-medication deviation group （127 cases， 39.81%） were identified. Multivariate Logistic regression analysis revealed that age， medication type， medication adherence， and self-efficacy in rational medication use were predictive factors for medication deviations in CHD patients with initial treatment （ P ＜0.05）. The predictive model equation was logit P ＝ln[ P /（1－ P ） ] ＝1.321+1.732×age+4.091×medication type －4.360×medication adherence －3.081×self-efficacy in rational medication use. The model demonstrated good discrimination， with a Hosmer-Lemeshow goodness-of-fit test P -value of 0.439， an area under the receiver operating characteristic curve （AUC） of 0.870， sensitivity of 0.970， and specificity of 0.607. A risk nomogram with a total score of 350 points and a cutoff value of 110 points was plotted. The internal validation group showed an AUC o f 0.787 and a prediction accuracy of 77.6%， while the external validation group exhibited an AUC of 0.802 and a prediction accuracy of 73.7%. CONCLUSIONS This study successfully developed a predictive model for medication deviation risks during the hospital-to-home transition period in CHD patients with initial treatment. The model demonstrates excellent discrimination and predictive accuracy， effectively identifying high-risk populations for medication deviations. Age （＞70 years）， number of drug types≥5， poor medication adherence， and poor self-efficacy in rational medication use are independent risk factors for medication deviations.

: To analyze the prevalence of anemia and iron deficiency among primary and secondary school students in Rural Nutrition Improvement Program areas of Guizhou Province in 2023, and to explore the related factors, so as to provide evidence for Rural Nutrition Improvement Program optimization. Methods: In September 2023, a stratified random cluster sampling strategy was used to select 40 rural compulsory education schools with rural nutrition improvement program in five counties of Guizhou Province. School level questionnaire was employed to collect information of basic characteristics and school meal implementation. A total of 7 826 primary and secondary school students aged 6-16 underwent anthropometry and hemoglobin (Hb) determination; serum ferritin (SF) was additionally measured in a random subsample of 1 795 pupils. Students in Grade 3 and above also completed a questionnaire covering demographic characteristics, dietary behaviours and nutrition knowledge. Group comparisons were conducted by Chi square test or Fisher s exact test, and multivariable Logistic regression models were constructed to identify factors associated with anemia and iron deficiency. Results: The overall Hb level was (133.21±12.95)g/L, with an anemia prevalence of 7.17%. The overall SF level was (69.58±59.01)μg/L, with an iron deficiency prevalence of 2.73%. Multivariable analysis showed that stunting ( OR =1.88), school menus without nutrient calculation ( OR =1.61) and absence of menu planning software in the current semester ( OR =2.34) independently increased anemia risk, whereas obesity reduced it ( OR =0.54) (all P <0.05). Girls ( OR =4.16) and Grades 7-9 ( OR =5.93) increased iron deficiency risk (both P <0.05). Compared with rarely eating fresh vegetables, students with consuming <3 kinds per day ( OR =0.08) or exactly 3 kinds per day ( OR =0.06) had lower iron deficiency risks (both P <0.05). Conclusions Anemia and iron deficiency are prevalent among primary and secondary school students in Guizhou. Targeted intervention measures should be implemented for key populations to enhance the effectiveness of nutrition improvement program.

Objective: To develop a dual-branch deep learning framework for accurate multi-label classification of fundus diseases, addressing the key limitations of insufficient complementary feature extraction and inadequate cross-modal feature fusion in existing automated diagnostic methods. Methods: The fundus multi-label classification dataset with 12 disease categories (FMLC-12) dataset was constructed by integrating complementary samples from Ocular Disease Intelligent Recognition (ODIR) and Retinal Fundus Multi-Disease Image Dataset (RFMiD), yielding 6 936 fundus images across 12 retinal pathology categories, and the framework was validated on both FMLC-12 and ODIR. Inspired by the holistic multi-regional assessment principle of the Five Wheels theory in traditional Chinese medicine (TCM) ophthalmology, the dual-branch multi-label network (DBMNet) was developed as a novel framework integrating complementary visual feature extraction with pathological correlation modeling. The architecture employed a TransNeXt backbone within a dual-branch design: one branch processed red-green-blue (RGB) images to capture color-dependent features, such as vascular patterns and lesion morphology, while the other processed grayscale-converted images to enhance subtle textural details and contrast variations. A feature interaction module (FIM) effectively integrated the multi-scale features from both branches. Comprehensive ablation studies were conducted to evaluate the contributions of the dual-branch architecture and the FIM. The performance of DBMNet was compared against four state-of-the-art methods, including EfficientNet Ensemble, transfer learning-based convolutional neural network (CNN), BFENet, and EyeDeep-Net, using mean average precision (mAP), F1-score, and Cohen's kappa coefficient. Results: The dual-branch architecture improved mAP by 15.44 percentage points over the single-branch TransNeXt baseline, increasing from 34.41% to 44.24%, and the addition of FIM further boosted mAP to 49.85%. On FMLC-12, DBMNet achieved an mAP of 49.85%, a Cohen’s kappa coefficient of 62.14%, and an F1-score of 70.21%. Compared with BFENet (mAP: 45.42%, kappa: 46.64%, F1-score: 71.34%), DBMNet outperformed it by 4.43 percentage points in mAP and 15.50 percentage points in kappa, while BFENet achieved a marginally higher F1-score. On ODIR, DBMNet achieved an F1-score of 85.50%, comparable to state-of-the-art methods. Conclusion DBMNet effectively integrates RGB and grayscale visual modalities through a dual-branch architecture, significantly improving multi-label fundus disease classification. The framework not only addresses the issue of insufficient feature fusion in existing methods but also demonstrates outstanding performance in balancing detection across both common and rare diseases, providing a promising and clinically applicable pathway for standardized, intelligent fundus disease classification.

The Chinese Pharmacopoeia is the legal technical standard which should be followed during the research, production, use, and administration of drugs. At present, the new edition of the Chinese Pharmacopoeia is planned to be promulgated and implemented. This article summarizes and analyzes the main characteristics and the content of updates and amendments of the Chinese Pharmacopoeia 2025 Edition(Volume Ⅰ), to provide a reference for the correct understanding and accurate implementation the new edition of the pharmacopoeia.

To reduce the dependency on high-carbon-load chromatographic columns,a new method has been established for the determination of the content of docusate sodium using ion-pair high-performance liquid chromatography (IP-HPLC). Tetrapropylammonium chloride was used as the ion-pair reagent with a mobile phase, composition of acetonitrile:10 mmol/L tetrapropylammonium chloride solution = 66∶34, adjusting pH to 6.5 with 0.1% phosphoric acid solution,flow rate of 1.5 mL/min, detection wavelength of 214 nm,column temperature of 35 °C, and an injection volume of 25 μL,and quantified by an external standard method. The main peak of docusate sodium exhibited a tailing factor of 1.34. The method showed good linearity within the range of 0.02 mg/mL to 0.40 mg/mL, with a correlation coefficient (r) of 0.999 9. It also demonstrated good repeatability, with recovery ranging from 97.0% to 98.2% (n=6). The quantification limit was 3.31 μg/mL, and the detection limit was 2.76 μg/mL.In summary,the new method shows good durability, a wide linear range, and high sensitivity, it is suitable for the determination of docusate sodium.

Self-face is a unique and highly distinctive stimulus, not shared with others, and serves as a reliable marker of self-awareness. Compared to other faces, self-face processing exhibits several advantages, including the self-face recognition advantage, self-face attention advantage, and self-face positive processing advantage. The self-face recognition advantage manifests as faster and more accurate identification across different orientations and spatial frequency components, supported by enhanced early event-related potential (ERP) components, such as N170. Attentional biases toward self-face are evident in target detection during spatial tasks and the attentional blink effect in temporal paradigms. However, measurement sensitivity, perceptual load, and task demands contribute to some mixed findings. Positive biases further characterize the self-face processing advantage, with individuals perceiving their faces as more attractive or trustworthy than objective representations. These biases even extend to self-similar others, influencing social behaviors such as trust and voting preferences. Self-face processing advantages have been observed at an unconscious level and are regulated by several factors, including self-esteem, cultural differences, and multisensory integration. Cultural and individual differences play a crucial role in shaping self-face advantages. Individuals from Western cultures, which emphasize independent self-construal, exhibit stronger self-face biases compared to those from East Asian collectivist contexts. Self-esteem also modulates self-face advantages: high-self-esteem individuals generally maintain their self-face recognition advantage despite interference, exhibit attentional prioritization of self-faces, and demonstrate enhanced positive associations with subliminal self-faces. In contrast, low-self-esteem individuals display recognition vulnerabilities to social cues, show context-dependent attentional divergence (prioritizing others’ faces in task-oriented settings while prioritizing self-face in free-viewing tasks), and exhibit reversed positive associations with subliminal self-faces. Multisensory integration, such as synchronized visual-tactile cues, enhances self-face advantages and induces perceptual plasticity. This phenomenon is exemplified by the enfacement illusion, in which synchronous visual and tactile inputs update the mental representation of the self-face, leading to assimilation with another face. Neuroanatomically, self-face processing is predominantly lateralized to the right hemisphere and involves a network of brain regions, including the occipital lobe, temporal lobe, frontal lobe, insula, and cingulate gyrus. Disruptions in these networks are linked to self-face processing deficits in socio-cognitive disorders. For instance, autism spectrum disorder (ASD) and schizophrenia are associated with attenuated self-face advantages and abnormal neural activity in regions such as the right inferior frontal gyrus, insula, and posterior cingulate cortex. These findings suggest that self-face processing could serve as a potential biomarker for the early diagnosis and intervention of such disorders. In recent years, researchers have proposed various theoretical explanations for self-face processing and its advantage effects. However, some studies have reported no significant behavioral or neural advantages of self-faces over familiar faces, leaving the specificity of self-face a subject of debate. Further elucidation of self-face specificity requires the adoption of a face association paradigm, which controls for facial familiarity and helps determine whether qualitative differences exist between self-faces and familiar faces. Given the close relationship between self-face processing advantages and socio-cognitive disorders (e.g., ASD, schizophrenia), a deeper understanding of self-face specificity has the potential to provide critical insights into the early identification, classification, and intervention of these disorders. This research holds both theoretical significance and substantial social value.

Continuous manufacturing, as an innovative pharmaceutical production model, offers advantages such as high production efficiency and ease of control compared to traditional batch production, aligning with the future trend of drug production moving toward greater efficiency and intelligence. However, the development of continuous manufacturing technology in wet granulation has been slow. On one hand, this is closely related to its high technical complexity, substantial equipment investment costs, and stringent process control requirements. On the other hand, the long-term use of the traditional batch production model has created strong path dependence, and the lack of mature standardized processes further increases the difficulty of technological transformation. To promote the deep integration of wet granulation technology with continuous manufacturing, this review systematically outlines the current application of wet granulation in continuous manufacturing. It focuses on the development of key technologies such as online detection, process modeling, and process scale-up, with the aim of providing a reference for process innovation and application in wet granulation.
Drug Compounding/instrumentation* ; Technology, Pharmaceutical/methods* ; Drugs, Chinese Herbal/chemistry* ; Models, Theoretical

This study aims to explore the impact of host plants on the quality of Taxilli Herba and provide a theoretical basis for the quality control of Taxilli Herba. The components of Taxilli Herba from three different host plants(Morus alba, Salix babylonica, and Cinnamomum cassia) and its 3 hosts(mulberry branch, willow branch, and cinnamon branch) were detected by widely targeted metabolomics based on ultra-high performance liquid chromatography-tandem mass spectrometry(UPLC-MS/MS). Principal component analysis(PCA), orthogonal partial least squares discriminant analysis(OPLS-DA), and Venn diagram were employed for analysis. A total of 717 metabolites were detected in Taxilli Herba from the three host plants and the branches of these host plants by UPLC-MS/MS. The results of PCA and OPLS-DA of Taxilli Herba from the three different host plants showed an obvious separation trend due to the different effects of host plants. The Venn diagram showed that there were 32, 8, and 26 characteristic metabolites in samples of Taxilli Herba from M. alba host, S. babylonica host, and C. cassia host, respectively. It was found by comparing the characteristic metabolites of Taxilli Herba and its hosts that each host transmits its characteristic components to Taxilli Herba, so that the Taxilli Herba contains the characteristic components of the host. The Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway analysis showed that the differential metabolites of Taxilli Herba from the three hosts were mainly enriched in flavonoid biosynthesis, arginine and proline metabolism, and glycolysis/gluconeogenesis pathways. Furthermore, the differential metabolites enriching pathways of Taxilli Herba from the three hosts were different depending on the host. In a word, host plants have a significant impact on the metabolites of Taxilli Herba, and it may be an important factor for the quality of Taxilli Herba.
Metabolomics/methods* ; Drugs, Chinese Herbal/chemistry* ; Chromatography, High Pressure Liquid ; Tandem Mass Spectrometry ; Quality Control ; Salix/chemistry* ; Cinnamomum aromaticum/metabolism* ; Principal Component Analysis