Objective: To investigate the correlation between the color parameters (L^*, a^*, b^*, Eab^* values) of Polygoni Multiflori Radix Praeparata powder prepared by different processing techniques and the contents of 2,3,5,4’-tetrahydroxystilbene-2-O-β-D-glucopyranoside, emodin, physcion, emodin-8-O-β-D-glucopyranoside, physcion-8-O-β-D-glucopyranoside.
Methods: The L^*, a^*, b^* and Eab^* values of Polygoni Multiflori Radix Praeparata powder prepared by different processing techniques were determined by spectrophotometer, and the contents of the five components were determined by high performance liquid chromatography. Secondly, SPSS 26.0 software and Simca 14.1 software were used to analyze the correlation.
Results: Through the hierarchical cluster analysis (HCA), it was found that the steamed samples and black bean steamed samples could be obviously divided into two categories: raw products and processed products. The processed products could be further divided into 2-8 h and 12-48 h. Pearson correlation analysis showed that the content of stilbene glycoside was significantly positively correlated with L^*, a^* and b^* values (P<0.01). The a^* value was significantly positively correlated with the content of emodin and physcion (P<0.01). Emodin-8-O-β-D-glucoside was positively correlated with L^* value and b^* value, while physcion-8-O-β-D-glucoside was negatively correlated with a^* value. Partial least squares discriminant analysis (PLS) showed that 2,3,5,4’-tetrahydroxystilbene-2-O-β-D-glucoside (VIP=1.69) and emodin-8-O-β-D-glucoside (VIP=1.06) were the key variables affecting chromaticity characteristics (P<0.01).
Conclusion: The three processes of steaming, black bean steaming and black bean stewing are consistent in composition transformation and chromaticity variation, and stilbene glycoside can be used as a specific index component to characterize the processed color. Chromatic parameters can effectively reflect the processing progression and serve as quality monitoring indicators during production.

Organoid-on-a-chip technology represents a promising interdisciplinary advancement that merges two cutting-edge biomedical platforms: stem cell-derived organoids and microfluidics-based organ-on-a-chip systems. Organoids are self-organizing three-dimensional (3D) cell cultures that mimic the key structural and functional features of in vivo organs. However, traditional organoid culture systems are often static, lacking dynamic environmental cues and suffering from limitations such as batch-to-batch variability, low stability, and low throughput. Organ-on-a-chip platforms, by contrast, utilize microfluidic technologies to simulate the dynamic physiological microenvironment of human tissues and organs, enabling more controlled cell growth and differentiation. By integrating the advantages of organoids and organ-on-a-chip technologies, organoid-on-a-chip systems transcend the limitations of conventional 3D culture models, offering a more physiologically relevant and controllable in vitro platform. In organoid-on-a-chip systems, stem cells or pre-formed organoids are cultured in micro-engineered environments that mimic in vivo conditions, enabling precise control over fluid flow, mechanical forces, and biochemical cues. Specifically, these platforms employ advanced strategies including bio-inspired 3D scaffolds for structural support, precise spatial cell patterning via 3D bioprinting, and integrated biosensors for real-time monitoring of metabolic activities. These synergistic elements recreate complex extracellular matrix signals and ensure high structural fidelity. Based on structural complexity, organoid-on-a-chip systems are classified into single-organoid and multi-organoid types, forming a trajectory from unit biomimicry to systemic simulation. Single-organoid chips focus on highly biomimetic units by integrating vascular, immune, or neural functions. Multi-organoid chips simulate inter-organ crosstalk and systemic homeostasis, advancing complex disease modeling and PK/PD evaluation. This emerging technology has demonstrated broad application potential in multiple fields of biomedicine. Organoid-on-a-chip systems can recapitulate organ developmentin vitro, facilitating research in developmental biology. They mimic organ-specific physiological activities and mechanisms, showing promising applications in regenerative medicine for tissue repair or replacement. In disease modeling, they support the reconstruction of models for neurodegenerative, inflammatory, infectious, metabolic diseases, and cancers. These platforms also enable in vitro drug testing and pharmacokinetic studies (ADME). Patient-derived chips preserve genetic and pathological features, offering potential for precision medicine. Additionally, they reduce species differences in toxicology, providing human-relevant data for environmental, food, cosmetic, and drug safety assessments. Despite progress, organoid-on-a-chip systems face challenges in dynamic simulation, extracellular matrix (ECM) variability, and limited real-time 3D imaging, requiring improved materials and the integration of developmental signals. Current bottlenecks also include the high technical threshold for automation and the lack of standardized validation frameworks for regulatory adoption. Meanwhile, the concept of a “human-on-a-chip” has been proposed to mimic whole-body physiology by integrating multiple organoid modules. This approach enables systemic modeling of drug responses and toxicity, with the potential to reduce animal testing and revolutionize drug development. Future advancements in bio-responsive hydrogels and flexible biosensors will further empower these platforms to bridge the gap between bench-side research and personalized clinical interventions. In conclusion, organoid-on-a-chip technology offers a transformative in vitro model that closely recapitulates the complexity of human tissues and organ systems. It provides an unprecedented platform for advancing biomedical research, clinical translation, and pharmaceutical innovation. Continued development in biomaterials, microengineering, and analytical technologies will be essential to unlocking the full potential of this powerful tool.

Organoid-on-a-chip technology represents a promising interdisciplinary advancement that merges two cutting-edge biomedical platforms: stem cell-derived organoids and microfluidics-based organ-on-a-chip systems. Organoids are self-organizing three-dimensional (3D) cell cultures that mimic the key structural and functional features of in vivo organs. However, traditional organoid culture systems are often static, lacking dynamic environmental cues and suffering from limitations such as batch-to-batch variability, low stability, and low throughput. Organ-on-a-chip platforms, by contrast, utilize microfluidic technologies to simulate the dynamic physiological microenvironment of human tissues and organs, enabling more controlled cell growth and differentiation. By integrating the advantages of organoids and organ-on-a-chip technologies, organoid-on-a-chip systems transcend the limitations of conventional 3D culture models, offering a more physiologically relevant and controllable in vitro platform. In organoid-on-a-chip systems, stem cells or pre-formed organoids are cultured in micro-engineered environments that mimic in vivo conditions, enabling precise control over fluid flow, mechanical forces, and biochemical cues. Specifically, these platforms employ advanced strategies including bio-inspired 3D scaffolds for structural support, precise spatial cell patterning via 3D bioprinting, and integrated biosensors for real-time monitoring of metabolic activities. These synergistic elements recreate complex extracellular matrix signals and ensure high structural fidelity. Based on structural complexity, organoid-on-a-chip systems are classified into single-organoid and multi-organoid types, forming a trajectory from unit biomimicry to systemic simulation. Single-organoid chips focus on highly biomimetic units by integrating vascular, immune, or neural functions. Multi-organoid chips simulate inter-organ crosstalk and systemic homeostasis, advancing complex disease modeling and PK/PD evaluation. This emerging technology has demonstrated broad application potential in multiple fields of biomedicine. Organoid-on-a-chip systems can recapitulate organ developmentin vitro, facilitating research in developmental biology. They mimic organ-specific physiological activities and mechanisms, showing promising applications in regenerative medicine for tissue repair or replacement. In disease modeling, they support the reconstruction of models for neurodegenerative, inflammatory, infectious, metabolic diseases, and cancers. These platforms also enable in vitro drug testing and pharmacokinetic studies (ADME). Patient-derived chips preserve genetic and pathological features, offering potential for precision medicine. Additionally, they reduce species differences in toxicology, providing human-relevant data for environmental, food, cosmetic, and drug safety assessments. Despite progress, organoid-on-a-chip systems face challenges in dynamic simulation, extracellular matrix (ECM) variability, and limited real-time 3D imaging, requiring improved materials and the integration of developmental signals. Current bottlenecks also include the high technical threshold for automation and the lack of standardized validation frameworks for regulatory adoption. Meanwhile, the concept of a “human-on-a-chip” has been proposed to mimic whole-body physiology by integrating multiple organoid modules. This approach enables systemic modeling of drug responses and toxicity, with the potential to reduce animal testing and revolutionize drug development. Future advancements in bio-responsive hydrogels and flexible biosensors will further empower these platforms to bridge the gap between bench-side research and personalized clinical interventions. In conclusion, organoid-on-a-chip technology offers a transformative in vitro model that closely recapitulates the complexity of human tissues and organ systems. It provides an unprecedented platform for advancing biomedical research, clinical translation, and pharmaceutical innovation. Continued development in biomaterials, microengineering, and analytical technologies will be essential to unlocking the full potential of this powerful tool.

Hepatocellular carcinoma (HCC) is a lethal cancer with high morbidity rates worldwide. It is a major threat to public health in China, due to the combination of known and new risk factors, such as endemic hepatitis B virus (HBV), dietary aflatoxin exposure, and the occurrence of metabolic dysfunction-associated steatotic liver disease (MASLD). Although many methods for surveillance and multimodal therapies, such as surgery, local ablation, transarterial therapy, and new systemic agents, have been available, the survival rates of HCC remains poor. They have very limited durable responses, long post-treatment recurrence rates, and high resistance to treatment. This reflects an imperfect picture of the biological cause of the disease and a need for new mechanistic or targeted techniques. A significant characteristic of HCC, in common with other aggressive cancers, is the presence of reprogrammed, hyperactive cell metabolism. Tumor cells hijack metabolic pathways to promote their uncontrolled growth, stress survival, invasion and metastasis. While classical mechanisms such as the Warburg effect, lipid metabolism and glutamine utilization have been understood, the lysosome, which was once viewed as a static “waste disposal unit” to remove old organelles and proteins, is instead a dynamic signaling and metabolic core. The lysosomes incorporate nutrients, energy and stress signals by master regulators such as mTORC1 (activated on its surface) that balance anabolic growth and catabolic recycling to the cellular demands. In HCC, lysosomes are not passive, but are highly active and dysregulated. HCC cells upregulate lysosomes, which scavenge intracellular components via enhanced autophagy and engulf extracellular proteins via macropinocytosis, crucial for survival in the nutrient-poor, hypoxic tumor microenvironment. In addition to metabolism, lysosomes exhibit pro-invasive functions by secreting hydrolases to remodel the extracellular matrix, promote angiogenesis, and suppress stromal immune cells to foster a pro-tumor microenvironment. In a clinical context, lysosomes play an important role in therapeutic resistance: they sequester and inactivate chemotherapeutics via lysosomal sequestration, and enhanced autophagic flux protects the cell from therapy-induced damage, contributing to relapse, as lysosomal dysfunction is a key cause of treatment failure. This makes lysosomes promising yet challenging therapeutic targets in HCC. Recent preclinical and early clinical studies investigate multiple strategies to exploit the susceptibility of lysosomes: lysosome-specific agents, alkalinizing the lysosome lumen or inducing membrane permeabilization and lysosome-dependent cell death; pharmacological inhibition of key lysosomal enzymes or autophagy to impair nutrient recycling and stress adaptation; smart nanotherapeutic agents or antibody-drug conjugates, specifically activated in the acidic lysosomal environment or utilizing lysosomal pathways for efficient intracellular drug release; and combination strategies of lysosome-targeting agents with tyrosine kinase inhibitors or immunotherapy to overcome resistance and achieve synergistic antitumor effects. In summary, our review systematically presents the role of lysosomes in HCC, from metabolic reprogramming and microenvironmental adaptation to therapeutic resistance. By synthesizing the latest mechanistic insights and preclinical advances, this review highlights the indispensable role of lysosomes in the complex HCC biological network, emphasizing that an in-depth understanding of this dynamic organelle holds great promise for developing innovative, targeted therapies, offering new hope for improving the poor prognosis of global HCC patients.

Objective To analyze the predictive value of different obesity indicators on acute cerebral infarction in patients with transient ischemic attack (TIA). Methods A total of 310 patients with TIA admitted to Tangdu Hospital of Air Force Medical University from March 2022 to September 2025 were selected and classified into non-event group (276 cases) and cerebral infarction group (34 cases) based on acute cerebral infarction within 90 days. The basic data and obesity-related indicators [body mass index (BMI), waist-to-hip ratio, body adiposity index (BAI), conicity index (C-index) and a body shape index (ABSI were compared. Multivariate logistic regression analysis was utilized to screen the independent influencing factors. Receiver operating characteristic (ROC) curve was drawn to analyze the predictive efficiency. Results The age, proportions of concurrent hypertension and concurrent diabetes mellitus, ABCD2 score, waist-to-hip ratio, ABSI, C-index, BMI and BAI in the cerebral infarction group were older or higher than those in the non-event group, and the symptoms duration was longer (P<0.05). The above indicators were all related factors for acute cerebral infarction in patients with TIA within 90 days (P<0.05), and ABSI and ABCD² score were independent influencing factors (P<0.05). The prediction model was manifested as Logit (P)=− 4.205 + 0.482 × ABCD² score + 1.120 × ABSI × 100. ABSI and ABCD2 score had predictive value on the occurrence of acute cerebral infarction (P<0.05), and the predictive efficiency of combined model was higher than that of single indicator (P<0.05). Conclusion Among different obesity indicators, ABSI has the highest value on predicting recent acute cerebral infarction in TIA. The prediction model based on ABSI and ABCD2 score exhibits the best predictive efficiency.

BackgroundObstructive sleep apnea （OSA） represents a prevalent sleep disordered breathing condition characterized by complex pathophysiology. The arousal threshold （ArTH）， a core non-anatomical contributor to OSA pathogenesis， is intimately tied to the disease severity and clinical phenotypes. To date， research regarding factors associated with ArTH has yielded inconsistent findings， and ArTH profiles and disparities across populations with different genetic backgrounds are not fully elucidated. ObjectiveTo explore the differences of ArTH in OSA patients with different genetic backgrounds and analyze the key factors affecting ArTH， thereby providing evidence for understanding OSA pathophysiology and formulating targeted treatment regimens. MethodsA total of 285 patients who met the diagnostic criteria for OSA， as defined by the Multidisciplinary Diagnosis and Treatment Guidelines for Adult Obstructive Sleep Apnea， were retrospectively enrolled in this study. All participants underwent overnight polysomnography （PSG） at the Sleep Medicine Center of Inner Mongolia Mental Health Center from December 2022 to May 2024. Based on the study design， the cohort was stratified into two distinct genetic background subgroups （group A and group B）. Demographic and clinical characteristics， the Epworth Sleepiness Scale （ESS） score， and overnight PSG data were collected. The apnea hypopnea index （AHI）， the lowest pulse oxygen saturation （LSpO₂）， and fraction of hypopneas （F_Hypopneas） were utilized as surrogate indicators to estimate ArTH in OSA patients. The influencing factors of low ArTH were tested by binary Logistic regression analysis. ResultsAmong the 285 OSA patients， there were 227 cases （79.65%） in group A and 58 cases （20.35%） in group B. Comparisons between the two genetic background subgroups revealed no statistically significant differences in the proportion of low ArTH， ESS score， PSG parameters， and the three markers for low ArTH （AHI<30 events/h， LSpO₂>82.5%， F_Hypopneas>58.3%） （P>0.05）. Binary Logistic regression analysis identified sex （OR=2.421， 95% CI： 1.070–5.478）， BMI （OR=0.847， 95% CI： 0.770–0.932）， N1 sleep duration （OR=0.974， 95% CI： 0.963–0.985）， and hypertension （OR=0.348， 95% CI： 0.143–0.848） as independent factors associated with low ArTH in the total cohort. Stratified analysis by genetic backgrounds revealed that sex（OR=3.799， 95% CI： 1.389–10.392）， BMI（OR=0.819， 95% CI：0.723–0.929）， and N1 sleep duration（OR=0.973， 95% CI： 0.961–0.986） were independent factors of low ArTH in group A. In contrast， only N1 sleep duration （OR=0.951， 95% CI： 0.911–0.993） remained a significant factor in group B. ConclusionArthur may have conservative characteristics in patients with OSA with different genetic backgrounds， but the pathophysiological mechanism of OSA may have population heterogeneity. ［Funded by Inner Mongolia Autonomous Region Natural Science Fundation Project （number， 2024QN08050）； Intra-institutional Scientific Research Project of Inner Mongolia Mental Health Center （number， 2022QNWN0010）］

Objective:This study aimed to analyze the expression of B-cell maturation antigen (CD269) on myeloma cells in patients with newly diagnosed multiple myeloma (NDMM) and evaluate its prognostic value.Methods:The retrospective analysis was conducted on the clinical data of 154 NDMM patients admitted to the outpatient clinics and wards of Beijing Chaoyang Hospital, Capital Medical University from October 23, 2018 to December 25, 2023, including 90 males and 64 females, aged 60(55,66) years old. CD269 phenotype was analyzed using flow cytometry (FCM). Specifically, patients were divided into CD269 positive group (expression>20%, n=103) and CD269 negative group (expression≤20%, n=51) based on the flow cytometry prior to treatment. Initially, we assessed the effect of CD269 expression on progression-free survival (PFS) in patients with NDMM and compared the two groups. Through a cross-sectional analysis, we examined the basic clinical characteristics, 32 laboratory indicators, and 5 cytogenetic indicators. We identified differences between the two groups and analyzed the impact of various indicators on the PFS of patients in both the CD269 positive and negative groups. Furthermore, we employed the Cox proportional hazards regression model to evaluate the influence of CD269 expression and other disease-related indicators on patients′ PFS. Results:Among 154 NDMM patients, 103 were identified as CD269 positive (66.9%), while 51 were CD269 negative (33.1%). No statistically significant differences in clinical indicators were observed between the two groups. The PFS for CD269 positive group was significantly lower than it in the CD269 negative group [28.0(18.0,41.0) months vs 35.0 (27.0, -) months, HR=2.012, 95% CI 1.059-3.824, χ 2=4.554, P=0.033]. Cox proportional hazards regression analysis indicated that CD269 positivity and non-IgG subtypes were independent risk factors influencing PFS in NDMM patients( HR=2.395,95% CI 1.152-4.979, P=0.019; HR=0.425,95% CI 0.223-0.810, P=0.009). In the CD269 positive group, progression-free survival (PFS) was significantly shortened in patients with>65 years, non-IgG subtypes, International Staging System (ISS) stage Ⅲ, β2-microglobulin (β2-MG) levels≥5.5 mg/L, abnormal t(11;14) or ≥3 cytogenetic abnormalities. Conclusion:CD269 positivity serves as an independent risk factor influencing PFS in NDMM patients. Among the factors examined, older age, non-IgG subtype, ISS stage Ⅲ, elevated serum β2-MG, the presence of an abnormal t(11;14) translocation and≥3cytogenetic abnormalities, significantly impact the PFS of CD269 positive patients.

Objective:To analyze the influencing factors of China′s DRG payment system reform(DRG reform) and its hierarchical relationship, for references for the in-depth promotion of China′s medical insurance payment reform.Methods:Relevant literature on DRG reform in China from databases such as CNKI, Wanfang Database, Pubmed, etc, were obtained. Content analysis method was used to extract the influencing factors of DRG reform. The correlation between each influencing factor was determined through expert discussion. An interpretive structural model(ISM) was constructed to analyze the hierarchical relationship of factors influencing DRG reform.Results:After analysis, the influencing factors(12) of DRG reform in China were included such as medical level, hospital management, and medical staff′s cognition and behavior. Among them, the local situation was the deep-level factor affecting DRG reform, 9 factors such as data quality assurance and policy design/implementation were the middle-level factors, and patients′ interests/needs and disease grouping were the surface-level factors.Conclusions:There were many influencing factors on the reform of China′s DRG payment system. It was suggested that relevant management departments in various regions should focus on the actual situation of the locality, take data quality and policy design and implementation as the key points of reform, formulate a scientific and reasonable DRG grouping scheme, safeguard the interests of patients, so as to promote the deepening of DRG reform.

AIM To explore the relieving effect of Er Miao Wan on atopic dermatitis in mice.METHODS In vivo experiment:BALB/c mice were randomly divided into normal group,model group,dexamethasone group(2 mg/kg)and high,medium and low dose groups of Er Miao Wan(4.68,2.34 and 1.17 g/kg).The mouse model of atopic dermatitis was established by repeatedly smearing DNCB solution,and the model was given orally for 21 days.The skin lesion condition on the back of mice,ear swelling degree,and the weight difference between ear lobes were observed and recorded.HE staining was used to observe the histopathological changes in the skin lesion tissues of mice.Toluidine blue(TB)staining was used to observe the infiltration of mast cells in skin lesions.The expression of macrophage marker F4/80 in skin lesions was detected by IHC.The serum levels of TSLP,IL-4,IL-5 and total IgE were detected by ELISA.In vitro experiment:RAW264.7 cells in logarithmic growth period were given 400,200 and 100 μg/mL Er Miao Wan for intervention.Cell proliferation was detected by CCK-8 method.NO level in cell supernatant was detected by Griess method.TNF-α,IL-1 β and IL-6 levels in cell supernatant were detected by ELISA method.The expressions of proteins related to the MAPK/NF-κB signaling pathway in cells was detected by Western blot.RESULTS In vivo experiment:Compared with the model group,the scores of back skin lesions,the swelling degree of right ear and the weight difference between left and right ear pieces in the high-dose group of Er Miao Wan decreased(P＜0.05,P＜0.01),the thickness of skin lesions decreased,the infiltration of mast cells and macrophages decreased(P＜0.05,P＜0.01),and the inflammatory factors TSLP,IL-4,IL-5 and total IgE levels in serum decreased(P＜0.05,P＜0.01),and the expression of F4/80 in the skin lesions decreased(P＜0.01).In vitro experiment:Compared with the model group,the levels of NO,TNF-α,IL-1 β and IL-6 in Er Miao Wan 400 and 200 μg/mL groups decreased(P＜0.05,P＜0.01),and the phosphorylation levels of P38,JNK and P65 proteins decreased(P＜0.05,P＜0.01).CONCLUSION Er Miao Wan can alleviate skin lesion inflammation in DNCB-induced atopic dermatitis mice,and its mechanism may be related to inhibiting the activation of MAPK/NF-κB signaling pathway of macrophage,reducing macrophage infiltration and reducing Th2 cytokines.

Objective:To explore and analyze the system development, application and evaluation of virtual simulation (VS) based clinical thinking system in midwifery education, and to provide reference for the research in this area.Methods:The scoping review guidelines published by the Joanna Briggs Institute was used as the methodological framework. Literature was searched from the domestic and international databases such as CNKI, Wanfang, PubMed, and Web of Science Core Collection, from the date of database construction to September 1, 2023. The literature was screened according to the inclusion and exclusion criteria, and the included literature was statistically and analytically reviewed.Results:A total of 314 articles were retrieved, and 13 articles were finally included. The VS based clinical thinking system is in its infancy in midwifery education at home and abroad. In China, there is a lack of theoretical framework underpinned the system development. The content was limited to the care during labor and delivery and family planning, and virtual woman and multiply operation paths have not been adopted in the system development. Besides, research design of the studies was less rigid and the indicators were not specifically selected for clinical thinking.Conclusions:Current studies have preliminarily proved some positive effects of VS on midwifery clinical thinking. However, it is suggested that development of VS system needs to be underpinned by theoretical framework related to clinical thinking. Types of VS and its operation path need to be adopted according to learning contents and objectives, whilst learning content should be extended to the wider midwifery scope of practice. Improve intervention plans in application and evaluation, select specific high evaluation tools, and further explore the impact of virtual simulation technology on students′ clinical thinking ability in midwifery.