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.

Objective Patients with chronic liver diseases often exhibit unique hemodynamic abnormalities and metabolic disorders.Postoperative fluid management presents numerous challenges,especially for critically ill patients admitted to the intensive care unit(ICU)after surgery.This study aimed at exploring the relationship between postoperative fluid therapy and prognosis.Methods Based on 2 414 patients with chronic liver diseases who underwent surgical treatment and were subsequently transferred to the ICU in the MIMIC-IV database,a retrospective cohort study was conducted on the final 2 143 patients after our inclusion and exclusion criteria.Multivariate adjusted logistic regression model was used to analyze the association between fluid therapeutic regimens on the first day after ICU admission and the risk of 7-day death after surgery.Restricted cubic spline(RCS)was applied to analyze the dose-response relationship.Results Multivariate analysis indicated that restrictive fluid resuscitation was an independent protective factor.Compared with the non-restrictive fluid resuscitation group,restrictive fluid resuscitation significantly reduced the 7-day postoperative mortality rate(6.4％vs 12.4％,OR=0.44,95％CI:0.22～0.88,P=0.021),decreased the use of mechanical ventilation(42.9％vs 72.3％,OR=0.29,95％CI:0.24～0.35,P<0.001),and shortened the ICU stay(1.86 vs 3.47 d,OR=0.81,95％CI:0.78～0.84,P<0.001).RCS curve showed that the fluid intake on the first postoperative day and the 7-day postoperative mortality risk presented a J-shaped curve relationship,with an inflection point at 1 850 mL.Beyond this threshold,the 7-day postoperative mortality risk was increased.Subgroup analysis results indicated that the protective effect of restrictive fluid resuscitation was consistent across different age and comorbidity groups.Conclusion For patients with chronic liver diseases,adopting a restrictive fluid therapy on the first day after surgery can effectively reduce the risk of short-term death.Moreover,there is a non-linear dose-effect relationship between the fluid intake and the 7-day mortality risk.When the fluid intake exceeds 1 850 mL,the risk of death significantly increases.

With the increasing demand for dynamic,real-time and rapid qualitative analysis of chemical composition in areas such as emergency response and space exploration,chip-scale mass spectrometers have attracted significant attention.These devices are expected to drive the integration of mass spectrometry with micro/nano-fabrication and intelligent sensing technologies,fostering profound innovation and breakthroughs in analytical chemistry.As an excellent mass analyzer,the ion trap exhibits numerous advantages,and its miniaturization creates favorable conditions for the high-density integration of miniature mass spectrometers.However,the reduction in ion storage capacity may compromise its sensitivity and dynamic range,rendering the study of ion unidirectional ejection in highly miniaturized ion traps of significant practical importance.In this work,a research was conducted on achieving efficient ion unidirectional ejection while maintaining high mass resolution in the extremely miniature hyperbolic linear ion trap(M-HLIT)with a field radius of 1 mm,and an electric field compensation method was proposed,which combined asymmetric electrode stretching and unbalanced RF voltage to achieve high-precision optimization of the electric field composition.Simulations showed that in an ideal structure,this method achieved 100％unidirectional ejection efficiency with the mass resolution of 518,significantly outperforming traditional asymmetric structure method(365)and unbalanced voltage method(321).Following the introduction of ion ejection slots,further optimization through bidirectional stretching and electrical parameters improved the resolution to 790 while maintaining a unidirectional ejection efficiency of 93％.This method eliminated the requirement for additional excitation voltage,offering an ideal solution for the miniature mass analyzer with high detection performance of chip-level mass spectrometers.

Objective: To investigate the iodine nutrition status of children aged 8-10 in Guangming, Longhua and Yantian District of Shenzhen in 2023, and to explore the influencing factors of thyroid volume. To evaluate prevention strategies and to provide a scientific basis for the elimination of iodine deficiency disorders. Methods: Urine and household salt samples were randomly collected from 580 non-boarding students aged 8-10 years foriodine content detection. Thyroid volume was measured using a fully digital ultrasound imaging system, and goiter prevalence was calculated. Results: A total of 580 samples was tested. The median salt iodine concentration was 23.86 mg/kg, with 93.62% qualified iodized salt and 94.48% coverage rate. The median of urinary iodine was 265.00 μg/L, mainly distributed between 200 - < 300 μg/L and ≥300 μg/L. The proportion of children with ap⁃ propriate iodine was 20. 86% , and the proportion of children with insufficient or excessive urinary iodine levels was 10. 86% and 68. 28% of the total surveyed population , respectively. The median thyroid volume was 3. 27 mL , and the goiter rate was 1. 72% . Multiple linear regression analysis showed that age was the risk factor for thyroid volume (8=0 328, P<0.05). while urinary iodine was the protective factor for thyroid volume(B=-4.134x10-4,P<0.05). Conclusion The qualified iodized salt rate, median of urinary iodine,and goiter prevalence of 580 children aged 8 - 10 meet the elimination criteria for iodine deficiency disorders. Age and urinary iodine are closely related to thyroid volume change. The urinary iodine level of children is generally high and requires serious attention.

Objective To investigate the five-circuit and six-qi features at conception and at birth in the patients with endometrial cancer.Methods From June 2020 to August 2024,the information about the conception time and birth time of 1 099 patients with endometrial cancer admitted to Guang'anmen Hospital of China Academy of Chinese Medical Sciences was collected from the electronic medical record system.The circuit-qi information at conception and at birth of the patients was statistically analyzed,and then the congenital endowment characteristics of the patients were explored.Results The results showed that most of the patients suffering endometrial cancer were born in winter,and the dominant qi at birth of the patients was predominated by taiyang cold-water,and the differences of the distribution of dominant qi at birth were statistically significant(P＜0.05).There were no significant differences in the distribution of yearly circuit,guest qi,and sitian-zaiquan at birth,and in the distribution of seasons,yearly circuit,dominant qi,guest qi,and sitian-zaiquan at conception(P＞0.05),and only an obvious trend of differences was presented.Conclusion There is a certain correlation between the prevalence of endometrial cancer and the five-circuit and six-qi features at conception and at birth.The congenital endowment of patients with endometrial cancer is characterized by yang deficiency with predominant coldness,and the prevalence is related to jueyin wind wood.

Objective To investigate traditional Chinese medicine(TCM)syndrome characteristics associated with immunotherapy efficacy in cervical cancer using propensity score matching(PSM),aiming to identify the population benefiting from immunotherapy.Methods A retrospective analysis was conducted in 253 cervical cancer patients,who received the treatment with programmed death receptor 1(PD-1)inhibitors at Guang'anmen Hospital,China Academy of Chinese Medical Sciences from January 2020 to October 2024.Clinical data and TCM four-examination data were collected.After balancing the confounders via PSM(1∶1 matching)and with therapeutic efficacy as the dependent variable,multivariate logistic regression was performed to analyze the characteristics of TCM syndrome in the immunotherapy-response group and then a predictive model was constructed.Results(1)After matching with PSM,198 cases were included,99 cases in response group and 99 cases in non-response group.(2)Analysis of the distribution of TCM syndrome elements showed that the differences in the pathogenic syndrome elements of qi deficiency,qi stagnation,blood stasis,heat and phlegm between the two groups were statistically significant(P＜0.05 or P＜0.01),while there were no statistically significant differences in the disease-location syndrome elements of uterus,kidneys,lungs,spleen,liver,and heart,as well as in the pathogenic syndrome elements of blood deficiency,yin deficiency,yang deficiency,cold,and dampness(P＞0.05).The main pathogenic syndrome elements in the response group were qi deficiency,blood deficiency and heat,while those in the non-response group were qi stagnation,heat and phlegm.(3)The results of univariate regression analysis showed that targeted therapy(P=0.040),programmed cell death-ligand 1(PD-L1)expression level(P＜0.001),qi deficiency(P=0.009),blood deficiency(P＜0.001),yang deficiency(P＜0.001),yin deficiency(P＜0.001),qi stagnation(P=0.003),blood stasis(P＜0.001),cold(P＜0.001),cold(P＜0.001),heat(P＜0.001),phlegm(P＜0.001),and dampness(P＜0.001)were the factors associated with the efficacy of PD-1 inhibitors.(4)The results of multivariate logistic regression analysis showed that previous targeted therapy(OR=0.36,95%CI:0.16-0.83)and pathogenic syndrome elements of qi stagnation(OR=0.23,95%CI:0.10-0.49),phlegm(OR=0.28,95%CI:0.13-0.61)were the risk factors of associated with the efficacy of PD-1 inhibitors,while PD-L1 expression level(OR=15.27,95%CI:2.60-89.63),and pathogenic syndrome element qi deficiency(OR=2.90,95%CI:1.42-5.89)were the protective factors associated with the efficacy of PD-1 inhibitors in cervical cancer.(5)Receiver operating characteristic(ROC)curve analysis demonstrated that the area under the ROC curve(AUC)of the predictive model for evaluating PD-1 inhibitor efficacy in cervical cancer was 0.78(95%CI:0.71-0.84),indicating certain predictive value.Conclusion PD-L1 expression level and TCM pathogenic syndrome elements such as qi deficiency,qi stagnation,and phlegm are the independent factors influencing PD-1 inhibitor efficacy in cervical cancer,providing insights for optimizing integrated TCM-western medicine treatment strategies.

The mechanism of L-perilla alcohol(L-POH) in intervening hypoxic pulmonary hypertension(HPAH) was discussed based on network pharmacology, and experimental verification. The active components and potential targets of the volatile oil of Rhodiola tangutica(VORA) in the intervention of HPAH were screened by network pharmacology. The biological process of Gene Ontology(GO) and the signaling pathway enrichment of Kyoto Encyclopedia of Genes and Genomes(KEGG) were analyzed for the core targets, and a "component-common target-disease" network was constructed. Four active components were screened from VORA: L-POH, linalool, geraniol, and(-)-myrtenol. The core targets for treating HPAH were HSP90AA1, AKT1, ESR1, PIK3CA, EP300, EGFR, and JAK2. GO enrichment analysis mainly involved biological processes such as reaction to hypoxia, heme binding, and steroid binding. KEGG enrichment analysis mainly involved hypoxia-inducing factor 1(HIF-1) signaling pathway, phosphatidylinositol 3-kinase/protein kinase B(PI3K/AKT) signaling pathway, and Janus kinase/activator of signal transduction and transcription(JAK/STAT) signaling pathway. The vasodilation effects of the four active components were screened by perfusion experiment of extracorporeal vascular rings, and the mechanism of the main active component L-POH was studied by channel blockers. The inhibitory effects of the four active components on the proliferation of pulmonary artery smooth muscle cells(PASMCs) induced by hypoxia were screened by cell proliferation experiment, and the mechanism of the main active component L-POH was studied by flow cytometry, cell cycle experiment, and Western blot. The results showed that L-POH could directly act on vascular smooth muscle to relax pulmonary arterioles, induce ATP-sensitive potassium channels to open, and inhibit extracellular Ca~(2+) influx through voltage-gated calcium channels to relax blood vessels. In addition, L-POH could inhibit the abnormal proliferation of PASMCs induced by hypoxia and promote its apoptosis, and its mechanism may be related to the increase in Bax protein expression and the decrease in p-JAK2, p-STAT3, Bcl-2, and cyclinA2 protein expression. In summary, L-POH can interfere with HPAH by relaxing pulmonary arterioles and inhibiting the proliferation of smooth muscle cells.
Network Pharmacology ; Animals ; Hypertension, Pulmonary/physiopathology* ; Drugs, Chinese Herbal/administration & dosage* ; Rats ; Hypoxia/metabolism* ; Rhodiola/chemistry* ; Signal Transduction/drug effects* ; Humans ; Monoterpenes/chemistry* ; Male ; Cell Proliferation/drug effects* ; Rats, Sprague-Dawley

This study employs ultra-performance liquid chromatography(UPLC) to analyze the differences in alkaloid content of Commelina communis from various geographical origins, exploring its feasibility as a quality evaluation indicator. A total of 57 batches of C. communis samples from 23 provinces, autonomous regions, and municipalities in China were selected. The MicroPulite HSS T3(2.1 mm×50 mm, 1.8 μm)column was used with a mobile phase of acetonitrile-0.2% phosphoric acid aqueous solution(20∶80), detection wavelength at 254 nm, and a flow rate of 0.3 mL·min~(-1) to measure the content of 1-deoxynojirimycin(DNJ) and deoxymannojirimycin(DMJ). The MicroPulite XP tC_(18)(2.1 mm×100 mm, 1.7 μm)column was employed with a mobile phase of acetonitrile-0.2% phosphoric acid aqueous solution(4∶96), detection wavelength at 254 nm, and a flow rate of 0.4 mL·min~(-1) to measure the content of norharmine(NHM) and harmanme(HM). Chemometric methods were applied to study the relationships and differences among the 57 batches of C. communis. Significant differences in alkaloid content were observed among C. communis from different regions, with the average total content decreasing in the order of North China, Northeast China, Northwest China, East China, Southwest China, Central China, and South China. Cluster analysis(CA) and principal component analysis(PCA) further revealed the quality differences of C. communis from various origins, and partial least squares discriminant analysis(PLS-DA) identified DNJ as a marker compound to distinguish the quality differences between different geographical sources of C. communis. It is recommended that the content limit of DNJ be set at no less than 0.055 9%, providing a reference for the quality evaluation and clinical application of C. communis medicinal materials.
Alkaloids/analysis* ; Drugs, Chinese Herbal/chemistry* ; China ; Chromatography, High Pressure Liquid ; Chemometrics/methods* ; Quality Control

In recent years, the application of artificial intelligence (AI) in the field of biology has witnessed remarkable advancements. Among these, the most notable achievements have emerged in the domain of protein structure prediction and design, with AlphaFold and related innovations earning the 2024 Nobel Prize in Chemistry. These breakthroughs have transformed our ability to understand protein folding and molecular interactions, marking a pivotal milestone in computational biology. Looking ahead, it is foreseeable that the accurate prediction of various physicochemical properties of proteins—beyond static structure—will become the next critical frontier in this rapidly evolving field. One of the most important protein properties is thermodynamic stability, which refers to a protein’s ability to maintain its native conformation under physiological or stress conditions. Accurate prediction of protein stability, especially upon single-point mutations, plays a vital role in numerous scientific and industrial domains. These include understanding the molecular basis of disease, rational drug design, development of therapeutic proteins, design of more robust industrial enzymes, and engineering of biosensors. Consequently, the ability to reliably forecast the stability changes caused by mutations has broad and transformative implications across biomedical and biotechnological applications. Historically, protein stability was assessed via experimental methods such as differential scanning calorimetry (DSC) and circular dichroism (CD), which, while precise, are time-consuming and resource-intensive. This prompted the development of computational approaches, including empirical energy functions and physics-based simulations. However, these traditional models often fall short in capturing the complex, high-dimensional nature of protein conformational landscapes and mutational effects. Recent advances in machine learning (ML) have significantly improved predictive performance in this area. Early ML models used handcrafted features derived from sequence and structure, whereas modern deep learning models leverage massive datasets and learn representations directly from data. Deep neural networks (DNNs), graph neural networks (GNNs), and attention-based architectures such as transformers have shown particular promise. GNNs, in particular, excel at modeling spatial and topological relationships in molecular structures, making them well-suited for protein modeling tasks. Furthermore, attention mechanisms enable models to dynamically weigh the contribution of specific residues or regions, capturing long-range interactions and allosteric effects. Nevertheless, several key challenges remain. These include the imbalance and scarcity of high-quality experimental datasets, particularly for rare or functionally significant mutations, which can lead to biased or overfitted models. Additionally, the inherently dynamic nature of proteins—their conformational flexibility and context-dependent behavior—is difficult to encode in static structural representations. Current models often rely on a single structure or average conformation, which may overlook important aspects of stability modulation. Efforts are ongoing to incorporate multi-conformational ensembles, molecular dynamics simulations, and physics-informed learning frameworks into predictive models. This paper presents a comprehensive review of the evolution of protein thermodynamic stability prediction techniques, with emphasis on the recent progress enabled by machine learning. It highlights representative datasets, modeling strategies, evaluation benchmarks, and the integration of structural and biochemical features. The aim is to provide researchers with a structured and up-to-date reference, guiding the development of more robust, generalizable, and interpretable models for predicting protein stability changes upon mutation. As the field moves forward, the synergy between data-driven AI methods and domain-specific biological knowledge will be key to unlocking deeper understanding and broader applications of protein engineering.

OBJECTIVE To summarize the implementation experiences of the China Hospital Association’s Clinical Pharmacist Instructor Training Program Reform， and to evaluate the effectiveness of the reform， thus continuously enhancing the quality and standards of clinical pharmacist instructor training. METHODS The study drew on project evaluation methodologies to summarize the main characteristics of the comprehensive system and new model for clinical pharmacist instructor training established through the reform by literature review. The “learning assessment” and “reaction assessment” were conducted by using Kirkpatrick’s four-level model of evaluation in order to evaluate the effectiveness of the clinical pharmacist instructor training reform through statistically processing and analyzing the performance data and teaching evaluation data of the instructor participants. Based on problem and trend analysis， the future development directions were anticipated for the reform of clinical pharmacist instructor training. RESULTS & CONCLUSIONS The latest round of clinical pharmacist instructor training reform initiated by the Chinese Hospital Association had initially established a four-pronged training system encompassing “recruitment， training， assessment， and management”. It had also forged a training 。 model “oriented towards enhancing clinical teaching competency， with practical learning and skill-based assessment conducted on clinical teaching sites as its core”. Following a period of over three years of gradual reform， the new training system and model became increasingly mature. In both 2023 and 2024， the participants achieved relatively high average total scores in their initial completion assessments [with scores of （84.05± 5.83） and （85.82±4.35） points， respectively]. They also reported a strong sense of gain from the training reform [with self- perceived gain scores of （4.80±0.44） and （4.85±0.39） points， respectively]. The operation and implementation effects of the reform were generally satisfactory. In the future， clinical pharmacist instructor training reforms should continue to address the issues remaining from the current phase， while aligning with global trends in pharmacy education and industry development. Additionally， sustained exploration and practice will be carried out around the core objective of “enhancing clinical teaching competence”.