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.

A 20-year-old male patient presented to the Department of Dermatology of Peking Union Medical College Hospital with complaints of an 8-year history of facial scarring, swelling of the lower limbs, and a 4-year history of scalp thickening. Physical examination showed thickening furrowing wrinkling of the skin on the face and behind the ears, ciliary body hirsutism, blepharoptosis, and cutis verticis gyrate. Both lower limbs were swollen, especially the knees and ankles. The skin of the palms and soles of the feet was keratinized and thickened. Laboratory examination using bone and joint X-ray showed periostosis of the proximal middle phalanges and metacarpals of both hands, distal ulna and radius, tibia and fibula, distal femurs, and metatarsals.Genetic testing revealed two variants in SLCO2A1, c.1658T > A and c.96+4A > C.Through multidisciplinary consultation, we confirmed the diagnosis of pachydermoperiostosis.

To explore the common irritant components in different base sources of Polygonati Rhizoma(PR). A rabbit eye irritation experiment was conducted to compare the irritant effects of raw products of Polygonatum kingianum, P. officinale, and P. multiflorum. The irritant effects of different solvent extraction parts and needle crystals of PR were compared, and the irritant components were screened. The morphology and structure of the purified needle crystal of PR were observed by microscope and scanning electron microscope and characterized by X-ray diffraction. Rabbit eye irritation and mouse abdominal inflammation model were used to evaluate rabbit eye irritation scores, inflammatory mediators, inflammatory factors levels in the peritoneal exudate of mice, with the peritoneal pathological section used as indicators. The inflammatory effect of needle crystals of PR was studied, and the content of calcium oxalate in three kinds of PR was determined by HPLC. The common protein in three kinds of PR was screened and compared by double enzymatic hydrolysis in solution combined with mass spectrometry. The results showed that three kinds of PR raw products had certain irritant effects on rabbit eyes, among which P. kingianum had the strongest irritant effect. There were no obvious irritant effects in the different solvent extraction parts of P. kingianum. Compared with the blank group, the needle crystal of PR had a significant irritant effect on rabbit eyes, and the inflammatory mediators and inflammatory factors in the peritoneal exudate were significantly increased(P<0.05) in a dose-dependent manner. Meanwhile, the peritoneal tissue of mice was damaged with significant inflammatory cell infiltration after intraperitoneal injection of needle crystal, indicating that needle crystal had an inflammatory effect. Microscope and scanning electron microscope observations showed that the needle crystals of PR were slender, with a length of about 100-200 μm and sharp ends. X-ray diffraction analysis showed that the needle crystals of PR were calcium oxalate monohydrate crystals. The results of HPLC showed that the content of calcium oxalate in P. kingianum was the highest among the three kinds of PR. It was speculated that the content of needle crystal in P. kingianum was higher than that in P. officinale and P. multiflorum, which was consistent with the results of the rabbit eye irritation experiment. The results of mass spectrometry showed that ribosome inactivating protein and mannose/sialic acid binding lectin were related to inflammation and cell metabolism in all three kinds of PR. There was no obvious irritant effect in different solvent extracts of PR. The calcium oxalate needle crystal contained was the main irritant component of PR, and three kinds of PR contained common ribosome inactivating protein and mannose/sialic acid binding lectin, which may be related to the inflammatory irritant effect of PR.
Animals ; Rabbits ; Mice ; Polygonatum/chemistry* ; Drugs, Chinese Herbal/toxicity* ; Rhizome/chemistry* ; Male ; Eye/drug effects* ; Female ; Humans

This study aimed to characterize and identify the non-volatile components in aqueous and ethanolic extracts of the stems and leaves of Rhododendron tomentosum by using sensitive and efficient ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry(UHPLC-Q-TOF-MS) combined with a self-built information database. By comparing with reference compounds, analyzing fragment ion information, searching relevant literature, and using a self-built information database, 118 compounds were identified from the aqueous and ethanolic extracts of R. tomentosum, including 35 flavonoid glycosides, 15 phenolic glycosides, 12 flavonoids, 7 phenolic acids, 7 phenylethanol glycosides, 6 tannins, 6 phospholipids, 5 coumarins, 5 monoterpene glycosides, 6 triterpenes, 3 fatty acids, and 11 other types of compounds. Among them, 102 compounds were reported in R. tomentosum for the first time, and 36 compounds were identified by comparing them with reference compounds. The chemical components in the ethanolic and aqueous extracts of R. tomentosum leaves and stems showed slight differences, with 84 common chemical components accounting for 71.2% of the total 118 compounds. This study systematically characterized and identified the non-volatile chemical components in the ethanolic and aqueous extracts of R. tomentosum for the first time. The findings provide a reference for active ingredient research, quality control, and product development of R. tomentosum.
Rhododendron/chemistry* ; Chromatography, High Pressure Liquid/methods* ; Drugs, Chinese Herbal/chemistry* ; Mass Spectrometry/methods* ; Plant Leaves/chemistry*

From the perspective of competitive endogenous RNA(ceRNA) constructed by metastasy-associated lung adenocarcinoma transcript 1(Malat1) and microRNA 16-5p(miR-16-5p), the improvement mechanism of Tonggu Xiaotong Capsules(TGXTC) on the imbalance and disorder of "cholesterol-iron" metabolism in chondrocytes of osteoarthritis(OA) was explored. In vivo experiments, 60 8-week-old C57BL/6 mice were acclimatized and fed for 1 week and then randomly divided into two groups: blank group(12 mice) and modeling group(48 mice). The animals in modeling group were anesthetized by 5% isoflurane inhalation, which was followed by the construction of OA model. They were then randomly divided into model group, TGXTC group, Malat1 overexpression group, and TGXTC+Malat1 overexpression(TGXTC+Malat1-OE) group, with 12 mice in each group. The structural changes of mouse cartilage tissues were observed by Masson staining after the intervention in each group. RT-PCR was employed to detect the mRNA levels of Malat1 and miR-16-5p in cartilage tissues. Western blot was used to analyze the protein expression of ATP-binding cassette transporter A1(ABCA1), sterol regulatory element-binding protein(SREBP), cytochrome P450 family 7 subfamily B member 1(CYP7B1), CCAAT/enhancer-binding protein homologous protein(CHOP), acyl-CoA synthetase long-chain family member 4(ACSL4), and glutathione peroxidase 4(GPX4) in cartilage tissues. In vitro experiments, mouse chondrocytes were induced by thapsigargin(TG), and the combination of Malat1 and miR-16-5p was detected by double luciferase assay. The fluorescence intensity of Malat1 in chondrocytes was determined by fluorescence in situ hybridization. The miR-16-5p inhibitory chondrocyte model was constructed. RT-PCR was used to analyze the levels of Malat1 and miR-16-5p in chondrocytes under the inhibition of miR-16-5p. Western blot was adopted to analyze the regulation of TG-induced chondrocyte proteins ABCA1, SREBP, CYP7B1, CHOP, ACSL4, and GPX4 by TGXTC under the inhibition of miR-16-5p. The results of in vivo experiments showed that,(1) compared with model group, TGXTC group exhibited a relatively complete cartilage layer structure. Compared with Malat1-OE group, TGXTC+Malat1-OE group showed alleviated cartilage surface damage.(2) Compared with model group, TGXTC group had a significantly decreased Malat1 mRNA level and an increased miR-16-5p mRNA level in mouse cartilage tissues(P<0.01).(3) Compared with the model group, the protein levels of ABCA1 and GPX4 in the cartilage tissue of mice in the TGXTC group increased, while the protein levels of SREBP, CYP7B1, CHOP and ACSL4 decreased(P<0.01). The results of in vitro experiments show that,(1) dual-luciferase was used to evaluate that miR-16-5p has a targeting effect on the Malat1 gene.(2)Compared with TG+miR-16-5p inhibition group, TG+miR-16-5p inhibition+TGXTC group had an increased mRNA level of miR-16-5p and an decreased mRNA level of Malat1(P<0.01).(3) Compared with TG+miR-16-5p inhibition group, TG+miR-16-5p inhibition+TGXTC group exhibited increased expression of ABCA1 and GPX4 proteins and decreased expression of SREBP, CYP7B1, CHOP, and ACSL4 proteins(P<0.01). The reasults showed that TGXTC can regulate the ceRNA of Malat1 and miR-16-5p to alleviate the "cholesterol-iron" metabolism disorder of osteoarthritis chondrocytes.
Animals ; MicroRNAs/metabolism* ; RNA, Long Noncoding/metabolism* ; Chondrocytes/drug effects* ; Drugs, Chinese Herbal/pharmacology* ; Mice, Inbred C57BL ; Mice ; Osteoarthritis/drug therapy* ; Iron/metabolism* ; Male ; Cholesterol/metabolism* ; Humans ; Capsules ; RNA, Competitive Endogenous

OBJECTIVE: To construct a prediction model for fracture reduction fixator therapy using the multi-modal multi-label classification (MMC) method. METHODS: Medical record data of 818 orthopedic patients from 2019 to 2023 were collected. Medical image features were extracted using the VGG19 network, text features of TCM four diagnostic methods (Inspection, Auscultation & Olfaction, Inquiry, Palpation) were extracted via the MiniLM model, and clinical case features were extracted through a fully connected neural network. After fusing the multi-modal information, multi-label therapy prediction was achieved using a linear layer. RESULTS: Experimental results on the clinical multi-modal dataset showed that the MMC method performed excellently in terms of subset accuracy(SA), accuracy(Acc), precision, and F₁-score, reaching 0.661, 0.856, 0.897, and 0.899 respectively. When the image modality and text modality were removed, the model performance decreased by an average of 8.1% and 2.4% respectively, while the hamming loss(HL) increased by 21.1% and 5.6% respectively. CONCLUSION The fracture reduction fixator therapy prediction model constructed in this study can effectively fuse multi-modal data, accurately predict personalized treatment plans for patients, and significantly improve the accuracy and reliability of treatment decisions. It provides a new solution for the digitalization and intellectualization of Traditional Chinese Medicine(TCM) in fracture treatment and has important clinical application prospects.
Humans ; Female ; Male ; Middle Aged ; Fracture Fixation/methods* ; Adult ; Fractures, Bone/surgery* ; Neural Networks, Computer ; Medicine, Chinese Traditional ; Aged

Case 1: A 19-day-old male infant presented with poor feeding and decreased activity for 2 weeks, worsening with poor responsiveness for 3 days. At 5 days old, he developed poor feeding and poor responsiveness, was hospitalized, and was found to have elevated blood ammonia and thrombocytopenia. Whole-genome genetic analysis revealed a pathogenic homozygous mutation in the PCCA gene, NM-000282.4: c.1834-1835del (p.Arg612AspfsTer44), leading to a diagnosis of propionic acidemia. Case 2: A 4-day-old male infant presented with poor responsiveness and feeding difficulties since birth, with elevated blood ammonia for 1 day. He showed weak sucking and deteriorating responsiveness, with blood ammonia >200 µmol/L. Genetic testing identified two heterozygous mutations in the MMUT gene: NM_000255.4: c.1677-1G>A and NM_000255.4: ex.5del, confirming methylmalonic acidemia. Case 3: A 20-day-old male infant presented with poor feeding for 15 days and skin petechiae for 8 days. He developed feeding difficulties at 5 days old and lower limb petechiae at 12 days old, with blood ammonia measured at 551.6 µmol/L. Genetic analysis found two heterozygous mutations in the PCCA gene: NM_000282.4: c.1118T>A (p.Met373Lys) and NM_000282.4: ex.16-18del, confirming propionic acidemia. In the first two cases, continuous hemodiafiltration was performed for 30 hours and 20 hours, respectively, before administering carglumic acid. In the third case, carglumic acid was administered orally without continuous hemodiafiltration, resulting in a decrease in blood ammonia from 551.6 µmol/L to 72.0 µmol/L within 6 hours, with a reduction rate of approximately 20-25 µmol/(kg·h), similar to the first two cases. Carglumic acid was effective in all three cases, suggesting it may help optimize future treatment protocols for organic acidemia.
Humans ; Male ; Infant, Newborn ; Propionic Acidemia/drug therapy* ; Amino Acid Metabolism, Inborn Errors/genetics* ; Mutation ; Methylmalonyl-CoA Decarboxylase/genetics* ; Citrates/administration & dosage* ; Carbon-Carbon Ligases/genetics* ; Glutamates

BACKGROUND: Blood glucose and serum albumin have been associated with cardiovascular disease prognosis, but the impact of admission-blood-glucose-to-albumin ratio (AAR) on adverse outcomes in critical ill coronary artery disease (CAD) patients was not investigated. METHODS: Patients diagnosed with CAD were non-consecutively selected from the MIMIC-IV database and categorized into quartiles based on their AAR. The primary outcome was 1-year mortality, and secondary endpoints were in-hospital mortality, acute kidney injury (AKI), and renal replacement therapy (RRT). A restricted cubic splines model and Cox proportional hazard models assessed the association between AAR and adverse outcomes in CAD patients. Kaplan-Meier survival analysis determined differences in endpoints across subgroups. RESULTS: A total of 8360 patients were included. There were 726 patients (8.7%) died in the hospital and 1944 patients (23%) died at 1 year. The incidence of AKI and RRT was 63% and 4.3%, respectively. High AAR was markedly associated with in-hospital mortality (HR = 1.587, P = 0.003), 1-year mortality (HR = 1.502, P < 0.001), AKI incidence (HR = 1.579, P < 0.001), and RRT (HR = 1.640, P < 0.016) in CAD patients in the completely adjusted Cox proportional hazard model. Kaplan-Meier survival analysis noted substantial differences in all endpoints based on AAR quartiles. Stratified analysis and interaction test demonstrated stable correlations between AAR and outcomes. CONCLUSIONS The results highlight that AAR may be a potential indicator for assessing in-hospital mortality, 1-year mortality, and adverse renal prognosis in critical CAD patients.

BACKGROUND: Biomarkers-based prediction of long-term risk of acute coronary syndrome (ACS) is scarce. We aim to develop a risk score integrating clinical routine information (C) and plasma biomarkers (B) for predicting long-term risk of ACS patients. METHODS: We included 2729 ACS patients from the OCEA (Observation of cardiovascular events in ACS patients). The earlier admitted 1910 patients were enrolled as development cohort; and the subsequently admitted 819 subjects were treated as validation cohort. We investigated 10-year risk of cardiovascular (CV) death, myocardial infarction (MI) and all cause death in these patients. Potential variables contributing to risk of clinical events were assessed using Cox regression models and a score was derived using main part of these variables. RESULTS: During 16,110 person-years of follow-up, there were 238 CV death/MI in the development cohort. The 7 most important predictors including in the final model were NT-proBNP, D-dimer, GDF-15, peripheral artery disease (PAD), Fibrinogen, ST-segment elevated MI (STEMI), left ventricular ejection fraction (LVEF), termed as CB-ACS score. C-index of the score for predication of cardiovascular events was 0.79 (95% CI: 0.76-0.82) in development cohort and 0.77 (95% CI: 0.76-0.78) in the validation cohort (5832 person-years of follow-up), which outperformed GRACE 2.0 and ABC-ACS risk score. The CB-ACS score was also well calibrated in development and validation cohort (Greenwood-Nam-D'Agostino: P = 0.70 and P = 0.07, respectively). CONCLUSIONS CB-ACS risk score provides a useful tool for long-term prediction of CV events in patients with ACS. This model outperforms GRACE 2.0 and ABC-ACS ischemic risk score.