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.

Objective To analyze the monitoring data of ¹³¹I internal exposure in Guangdong Province over the past 3 years, study the thyroid ¹³¹I contamination levels among nuclear medicine staff, and provide a basis for optimizing the monitoring plan. Methods Using a convenience sampling method, 574 detections of nuclear medicine staff from 28 hospitals in Guangdong Province were included in the study. The thyroid ¹³¹I activity was measured directly in vivo. Differences in detection rates were analyzed, and committed effective doses were estimated. Results Over the past 3 years in Guangdong Province, ¹³¹I accumulation was found in the thyroids of staff from 14 hospitals for 62 (10.8%) detections, with an average activity of 154.8 (13.2-8730.6) Bq. The adjusted annual intake was 50.7 (4.5-820.6) kBq. The committed effective dose was 0.56 (0.05-9.03) mSv/a, and the values were ≥ 2 mSv for 8 persons. Among different positions, nurses showed the highest detection rate (19.6%), followed by cleaners (14.7%), with significant differences (P<0.05). Among different exposure types, the detection rate was highest for loading medication into automatic dispenser (23.3%), and the mean activity was highest for entering thyroid cancer patient ward (495.4 Bq), with significant differences (P<0.05). Conclusion Monitoring of ¹³¹I internal exposure in Guangdong Province found that the radiation doses of some staff members had exceeded the threshold specified in other investigations. Routine personal ¹³¹I internal exposure monitoring should be conducted, with increased monitoring frequency. Priority should be given to nurses and cleaners, with monitoring extended to cleaners and outsourced dispensing staff.

Objective:To observe the clinical efficacy of Chinese materia medica soaking therapy combined with cervical rotation-traction manipulation in the treatment of cervical spondylotic radiculopathy (CSR).Methods:A randomized controlled trial was conducted. Totally 84 CSR patients from the Orthopedics Department of Shunyi Hospital, Beijing Traditional Chinese Medicine Hospital from April 2023 to May 2024 were selected as the observation subjects. They were divided into two groups using a random number table method, with 42 patients in each group. The treatment for both groups lasted for 14 d. VAS scale was used to assess pain levels before and after treatment, OASTCSR was used to evaluate cervical function, and NDI was used to assess cervical functional status; adverse reactions during treatment were observed and recorded, and clinical efficacy was evaluated.Results:The total effective rate was 95.24% (40/42) in the treatment group and 80.95% (34/42) in the control group, with statistical significance ( χ2=4.36, P=0.029). After treatment, the VAS score (1.60±1.21 vs. 2.91±1.12, t=-1.89), the OASTCSR score (5.17±2.14 vs. 9.31±3.82, t=-11.57), and the NDI score (9.17±2.13 vs. 13.36±3.45, t=-10.82) in the treatment group were lower than those in the control group ( P<0.001 or P<0.05). During the treatment period, neither group experienced any adverse reactions. Conclusion:The combination of Chinese materia medica soaking therapy and cervical rotation-traction manipulation can significantly improve the clinical symptoms and quality of life of patients with CSR, and its efficacy is superior to the use of cervical rotation-traction manipulation alone.

Objective This research was performed to identify rodent-borne pathogens in Hekou Port,Yunnan Province.Methods Rodents were captured using cages and dissected to collect their lungs,liver,spleen,and other viscera.Eight pathogens,including Yersinia pestis,Leptospira,Bartonella,and Anaplasmataceae,were identified using polymerase chain reaction amplification.Amplified pathogen sequences from positive samples were sequenced,and BLAST homology searches were conducted using GenBank to confirm pathogen identities.A phylogenetic tree of the identified pathogens was constructed using the neighbor joining method.Results The total of 31 rodents,identified as Rattus tanezumi,R.norvegicus,and Mus musculus,were captured.Among these,R.tanezumi was the dominant species,accounting for 64.52％of the total.Two pathogens,Leptospira interrogans and Neoehrlichia mikurensis,were detected,with positivity rates of 9.68％and 29.03％,respectively.No other pathogens were detected.The overall positivity rate for rodent-borne pathogens was 35.48％.Conclusions The single 16S rRNA gene fragment is insufficient for the molecular identification of all Neoehrlichia species.Accurate species identification should be based on a combined analysis of multiple genes.The prevalence of rodent-borne pathogens in Hekou Port indicates the necessity for enhanced surveillance of rodent-borne diseases and implementation of additional prevention and control measures in border ports.

This paper reported the clinical manifestations, pathological features, immunophenotype and follow-up of two patients with superficial CD34-positive fibroblastic tumor (SCPFT), who were admitted to Shandong Provincial Hospital in 2022 and 2023, and discussed the relevant literatures. The two patients, aged 43 and 20 years old, were both male. Their tumors were located in the perineum and the back of left shoulder, respectively. Both presented as single slow-growing subcutaneous masses with a course typically measured in years, accompanied by mild tenderness but without pain or pruritus. Microscopically, spindled to epithelioid cells and pleomorphous nuclear cells arranged in cellular fascicles and solid sheets were the main findings. Immunophenotypically, positive expression of CD34 was found in both cases. Extended resection ensured negative marginal and basal margins for both cases. No recurrence was observed after 22 and 12 months of follow-up, respectively. Clinical features, pathology, and differential diagnosis were discussed and summarized through a review of relevant literature. SCPFT is a novel type of fibroblastic tumor categorized as a low-grade malignant soft tissue tumor with unique pathological and biological characteristics that is relatively rare clinically. Routine resection may lead to recurrence; therefore, long-term follow-up is necessary. The combination of morphological characteristics and immunohistochemistry is helpful to diagnosis. It is important to differentiate this disease from other tumors to avoid misdiagnosis or mistreatment.

Guidelines for Digital Ancient Books of TCM Indexing(T/CIATCM 119-2024)is based on the theoretical knowledge,disciplinary methods,and practical applications of TCM classical cataloging.Taking digital ancient books of TCM as the object,it systematically reveals the content of TCM knowledge,which is an essential indexing processing standard for building an intelligent retrieval system for TCM ancient books,and can provide support for the deep development and innovative utilization of TCM knowledge.It can not only promote the co-construction and sharing of ancient book resources in the TCM industry,but also promote the standardization construction and application of TCM information.This standard specifies the principles,methods,and examples of free indexing of digital ancient books of TCM based on their original content.It is applicable to the indexing and processing of digital ancient books of TCM for TCM professional libraries and related institutions,and to the data processing and construction of various types of TCM ancient book databases.

BACKGROUND:Lipophagy is closely related to a variety of chronic metabolic diseases.Exercise can delay the pathological process of non-alcoholic fatty liver by regulating lipophagy,which has become one of the most popular studies in the field of sports medicine.OBJECTIVE:To summarize the regulatory role of lipophagy in non-alcoholic fatty liver disease and the mechanism of exercise-mediated lipophagy in non-alcoholic fatty liver disease.METHODS:CNKI,PubMed,and Web of Science databases were searched for relevant literature published from 1980 to 2025,using the search terms of"lipophagy,lipid metabolism,non-alcoholic fatty liver disease,aerobic exercise,resistance training,combined aerobic resistance exercise"in Chinese and English.Totally 98 documents were included according to inclusion and exclusion criteria.RESULTS AND CONCLUSION:(1)Lipophagy plays an important regulatory role in the prevention and treatment of non-alcoholic fatty liver disease.(2)Different types of exercises affect lipophagy:Aerobic exercise can play a beneficial role can regulate the expression of lipophagy related factors,enhance autophagy flow,improve lysosome biosynthesis and promote the decomposition of lipase.Resistance training can increase the expression of autophagy related factors in adipose tissue.Combined aerobic resistance exercise can increase fat oxidation rate and improve insulin sensitivity.(3)Exercise can treat non-alcoholic fatty liver disease by improving liver inflammation,insulin resistance,and liver function.(4)Exercise plays a key role in the prevention and treatment of non-alcoholic fatty liver by regulating lipophagy,reducing lipid accumulation,inhibiting steatosis,alleviating liver inflammation and fibrosis and improving insulin resistance.

Objective:To analyze the current situation of health-related quality of life (HRQOL) and its influencing factors among community-dwelling elderly with mild cognitive impairment (MCI) based on the health ecology model (HEM).Methods:From December 2023 to September 2024, a cross-sectional survey was conducted among 997 community-dwelling elderly in Beijing, Shandong, Chongqing and other regions. The EuroQol five-dimensional questionnaire 5 level (EQ-5D-5L), the Montreal cognitive assessment (MoCA), and the Pittsburgh sleep quality index (PSQI) were used to assess the subjects.Descriptive analysis, Mann-Whitney U test, Kruskal-Wallis test, and Tobit regression analysis were performed using Stata 18.0 software. Results:A total of 324 valid samples were finally obtained, and the health utility value of MCI elderly was 0.842(0.815, 0.951). Tobit regression analysis showed that ≥80 years old( β=-0.121, 95% CI=-0.193--0.050) in individual traits level, don't exercise( β=-0.196, 95% CI=-0.255--0.137) and poor quality of sleep ( β=-0.064, 95% CI=-0.116--0.013) in behavior characteristics level, and poor subjective economic status( β=-0.153, 95% CI=-0.261--0.045) in living and working conditions level were risk factors for the health utility value of the elderly with MCI. Drinking( β=0.096, 95% CI=0.022-0.171) in behavior characteristics level and participating in social activities( β=0.126, 95% CI=0.062-0.190) in interpersonal network level were protective factors for the health utility value of the elderly with MCI. Conclusions:The HRQOL of the community-dwelling elderly with MCI in China is low, and its influencing factors are multi-level. HEM should be combined to strengthen the intervention and management of the elderly with MCI from personal constitution to policy environment to improve their HRQOL.

Accurate prediction of drug-target interactions (DTIs) plays a pivotal role in drug discovery, facilitating optimization of lead compounds, drug repurposing and elucidation of drug side effects. However, traditional DTI prediction methods are often limited by incomplete biological data and insufficient representation of protein features. In this study, we proposed KG-CNNDTI, a novel knowledge graph-enhanced framework for DTI prediction, which integrates heterogeneous biological information to improve model generalizability and predictive performance. The proposed model utilized protein embeddings derived from a biomedical knowledge graph via the Node2Vec algorithm, which were further enriched with contextualized sequence representations obtained from ProteinBERT. For compound representation, multiple molecular fingerprint schemes alongside the Uni-Mol pre-trained model were evaluated. The fused representations served as inputs to both classical machine learning models and a convolutional neural network-based predictor. Experimental evaluations across benchmark datasets demonstrated that KG-CNNDTI achieved superior performance compared to state-of-the-art methods, particularly in terms of Precision, Recall, F1-Score and area under the precision-recall curve (AUPR). Ablation analysis highlighted the substantial contribution of knowledge graph-derived features. Moreover, KG-CNNDTI was employed for virtual screening of natural products against Alzheimer's disease, resulting in 40 candidate compounds. 5 were supported by literature evidence, among which 3 were further validated in vitro assays.
Alzheimer Disease/drug therapy* ; Biological Products/therapeutic use* ; Humans ; Neural Networks, Computer ; Machine Learning ; Drug Discovery/methods* ; Algorithms ; Drug Evaluation, Preclinical/methods*