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.

Chinese hamster ovary (CHO) cells are the most established and versatile mammalian expression system for the large-scale production of recombinant therapeutic proteins, owing to their genetic stability, adaptability to serum-free suspension culture, and ability to perform human-like post-translational modifications. More than 70% of biologics approved by the U.S. Food and Drug Administration rely on CHO-based production platforms, underscoring their central role in modern biopharmaceutical manufacturing. Despite these advantages, CHO systems continue to face three persistent bottlenecks that limit their potential for high-yield, reproducible, and cost-efficient production: excessive metabolic burden during high-density culture, heterogeneity of glycosylation patterns, and progressive loss of long-term expression stability. This review provides an integrated analysis of recent advances addressing these challenges and proposes a forward-looking framework for constructing intelligent and sustainable CHO cell factories. In terms of metabolic regulation, excessive lactate and ammonia accumulation disrupts energy balance and reduces recombinant protein synthesis efficiency. Optimization of culture parameters such as temperature, pH, dissolved oxygen, osmolarity, and glucose feeding can effectively alleviate metabolic stress, while supplementation with modulators including sodium butyrate, baicalein, and S-adenosylmethionine promotes specific productivity (qP) by modulating apoptosis and chromatin structure. Furthermore, genetic engineering strategies—such as overexpression of MPC1/2, HSP27, and SIRT6 or knockout of Bax, Apaf1, and IGF-1R—have demonstrated significant improvements in cell viability and product yield. The combination of multi-omics metabolic modeling with artificial intelligence (AI)-based prediction offers new opportunities for building self-regulating CHO systems capable of dynamic adaptation to environmental stress. Regarding glycosylation uniformity, which determines therapeutic efficacy and immunogenicity, gene editing-based glycoengineering (e.g., FUT8 knockdown or ST6Gal1 overexpression) has enabled the humanization of CHO glycan profiles, minimizing non-human sugar residues and enhancing drug stability. Process-level strategies such as galactose or manganese co-feeding and fine control of temperature or osmolarity further allow rational regulation of glycosyltransferase activity. Additionally, in vitro chemoenzymatic remodeling provides a complementary route to construct human-type glycans with defined structures, though industrial applications remain constrained by cost and scalability. The integration of model-driven process design and AI feedback control is expected to enable real-time prediction and correction of glycosylation deviations, ensuring batch-to-batch consistency in continuous biomanufacturing. Long-term expression stability, another critical challenge, is often impaired by promoter silencing, chromatin condensation, and random genomic integration. Molecular optimization—such as the use of improved promoters (CMV, EF-1α, or CHO endogenous promoters), Kozak and signal peptide refinement, and incorporation of chromatin-opening elements (UCOE, MAR, STAR)—helps maintain durable transcriptional activity, while site-specific integration systems including Cre/loxP, Flp/FRT, φC31, and CRISPR/Cas9 can enable single-copy, position-independent gene insertion at genomic safe-harbor loci, ensuring stable, predictable expression. Collectively, this review highlights a paradigm shift in CHO system optimization driven by the convergence of genome editing, synthetic biology, and artificial intelligence. The transition from empirical optimization to rational, data-driven design will facilitate the development of programmable CHO platforms capable of autonomous regulation of metabolic flux, glycosylation fidelity, and transcriptional activity. Such intelligent cell factories are expected to accelerate the transformation from laboratory-scale research to industrial-scale, high-consistency, and economically sustainable biopharmaceutical manufacturing, thereby supporting the next generation of efficient and customizable biologics manufacturing.

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.

Chinese hamster ovary (CHO) cells are the most established and versatile mammalian expression system for the large-scale production of recombinant therapeutic proteins, owing to their genetic stability, adaptability to serum-free suspension culture, and ability to perform human-like post-translational modifications. More than 70% of biologics approved by the U.S. Food and Drug Administration rely on CHO-based production platforms, underscoring their central role in modern biopharmaceutical manufacturing. Despite these advantages, CHO systems continue to face three persistent bottlenecks that limit their potential for high-yield, reproducible, and cost-efficient production: excessive metabolic burden during high-density culture, heterogeneity of glycosylation patterns, and progressive loss of long-term expression stability. This review provides an integrated analysis of recent advances addressing these challenges and proposes a forward-looking framework for constructing intelligent and sustainable CHO cell factories. In terms of metabolic regulation, excessive lactate and ammonia accumulation disrupts energy balance and reduces recombinant protein synthesis efficiency. Optimization of culture parameters such as temperature, pH, dissolved oxygen, osmolarity, and glucose feeding can effectively alleviate metabolic stress, while supplementation with modulators including sodium butyrate, baicalein, and S-adenosylmethionine promotes specific productivity (qP) by modulating apoptosis and chromatin structure. Furthermore, genetic engineering strategies—such as overexpression of MPC1/2, HSP27, and SIRT6 or knockout of Bax, Apaf1, and IGF-1R—have demonstrated significant improvements in cell viability and product yield. The combination of multi-omics metabolic modeling with artificial intelligence (AI)-based prediction offers new opportunities for building self-regulating CHO systems capable of dynamic adaptation to environmental stress. Regarding glycosylation uniformity, which determines therapeutic efficacy and immunogenicity, gene editing-based glycoengineering (e.g., FUT8 knockdown or ST6Gal1 overexpression) has enabled the humanization of CHO glycan profiles, minimizing non-human sugar residues and enhancing drug stability. Process-level strategies such as galactose or manganese co-feeding and fine control of temperature or osmolarity further allow rational regulation of glycosyltransferase activity. Additionally, in vitro chemoenzymatic remodeling provides a complementary route to construct human-type glycans with defined structures, though industrial applications remain constrained by cost and scalability. The integration of model-driven process design and AI feedback control is expected to enable real-time prediction and correction of glycosylation deviations, ensuring batch-to-batch consistency in continuous biomanufacturing. Long-term expression stability, another critical challenge, is often impaired by promoter silencing, chromatin condensation, and random genomic integration. Molecular optimization—such as the use of improved promoters (CMV, EF-1α, or CHO endogenous promoters), Kozak and signal peptide refinement, and incorporation of chromatin-opening elements (UCOE, MAR, STAR)—helps maintain durable transcriptional activity, while site-specific integration systems including Cre/loxP, Flp/FRT, φC31, and CRISPR/Cas9 can enable single-copy, position-independent gene insertion at genomic safe-harbor loci, ensuring stable, predictable expression. Collectively, this review highlights a paradigm shift in CHO system optimization driven by the convergence of genome editing, synthetic biology, and artificial intelligence. The transition from empirical optimization to rational, data-driven design will facilitate the development of programmable CHO platforms capable of autonomous regulation of metabolic flux, glycosylation fidelity, and transcriptional activity. Such intelligent cell factories are expected to accelerate the transformation from laboratory-scale research to industrial-scale, high-consistency, and economically sustainable biopharmaceutical manufacturing, thereby supporting the next generation of efficient and customizable biologics manufacturing.

Based on the theory of "yang governs and yin follows"， it is believed that pediatric obesity is primarily involves the key pathogenesis of constraint and stagnation due to yang deficiency， and the excessive accumulation of yin turbid. The root cause lies in the spleen-stomach yang deficiency and impaired digestion and transformation， while the branch manifestation is characterized by constraint and stagnation in sanjiao （三焦） and excessive accumulation of yin turbid. This emphasizes the imbalance between the governing function of yang qi and the transformation mechanism of yin essence in the overall pathological process. Accordingly， the treatment approach of reinforcing yang and unblocking stagnation， inhibiting yin and resolving turbid has been proposed. And a comprehensive treatment plan is suggested， including abdominal tuina combined with spinal manipulation， timed acupuncture according to the the eightfold method of the sacred tortoise， syndrome differentiation-based acupuncture， and mild moxibustion. This approach aims to provide an integrated approach for the prevention and treatment of pediatric obesity.

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.

Objective:To investigate the correlation of combined detection of p16 and Rb with high-risk human papilloma virus (HR-HPV) infection in non-oropharyngeal squamous cell carcinoma (NOPSCC) of the head and neck.Methods:A total of 68 NOPSCC cases of the head and neck (23 cases of the nasal cavity and paranasal sinuses and 45 cases of larynx) with complete clinical and pathological data, diagnosed at the Beijing Tongren Hospital, Capital Medical University, Beijing, China from November 2013 to December 2023, were collected. The expression of p16 and Rb was detected using immunohistochemistry of the EnVision two-step method, while the HR-HPV mRNA expression was detected using in situ hybridization. The concordance, sensitivity, and specificity of p16 alone and the combined detection of p16 and Rb for detecting HR-HPV infection were analyzed.Results:Among the 68 patients with NOPSCC, 53 were male and 15 were female, with a median age of 63.5 (range, 57.3 to 66.8) years. 41 patients had a smoking history and 27 did not. 33 patients had an early T stage (T1/T2) and 35 had advanced T stage (T3/T4). 14 patients had lymph node metastasis and 2 had distant metastasis. Histological types included 62 cases of keratinized squamous cell carcinoma, 5 cases of non-keratinized squamous cell carcinoma, and 1 case of basal-like squamous cell carcinoma. 25 cases were positive for p16. Among the 25 cases, 16 cases were positive for Rb, and 6 cases were positive for HR-HPV mRNA. 43 cases were negative for p16, including 38 cases positive for Rb and no cases positive for HR-HPV mRNA. The concordance between p16 and HR-HPV mRNA expression was poor ( Kappa=0.285, P=0.001), with a sensitivity of 100.0% and specificity of 69.4%. In contrast, the combined detection of p16+/Rb- showed high concordance with HR-HPV mRNA expression ( Kappa=0.719, P<0.001), with a sensitivity of 100.0% and specificity of 95.2%. Conclusions:In NOPSCC of the head and neck, the combined detection of p16 and Rb may be used as a marker for assessing HR-HPV infection. Recognizing the p16+/Rb- expression pattern in NOPSCC can improve the specificity of HR-HPV detection.

Objective:To analyze the effect of continuous positive airway pressure (CPAP) on maternal and neonatal outcomes in pregnant women with obstructive sleep apnea syndrome (OSAS), especially on the incidence of hypertensive disorder in pregnancy (HDP) in women with moderate to severe OSAS.Methods:A total of 180 pregnant women with OSAS who were diagnosed through sleep monitoring during pregnancy due to high-risk factors of OSAS and registered in Peking University People′s Hospital from January 2021 to May 2024 were selected as the study subjects. Clinical data were collected from medical records for retrospective analysis. According to whether they received standardized treatment with CPAP, they were divided into the CPAP treatment group (42 cases) and the control group (138 cases). The CPAP treatment group consisted of 9 pregnant women with moderate to severe OSAS, while the control group consisted of 34 pregnant women with moderate to severe OSAS. The maternal and neonatal outcomes, the incidence of HDP, placental weight after delivery and placental weight/neonatal birth weight ratio were compared between the two groups.Results:(1) The average gestational age of pregnant women in the CPAP treatment group was higher than that in the control group [(38.7±1.0) vs (38.0±1.4) weeks], the proportion of infants small for gestational age (SGA) in the CPAP treatment group was lower [0 (0/42) vs 12.3% (17/138)], and the birth weight of infants in the CPAP treatment group was bigger [(3 396±475) vs (3 082±710) g); the differences between the two groups were statistically significant (all P<0.05). There were no significant differences between the CPAP treatment group and the control group in terms of delivery mode, rates of postpartum hemorrhage and preterm birth, umbilical artery blood gas analysis pH<7.1, lactate≥6.0 mmol/L, base excess<-12.0 mmol/L and the incidence of gestational diabetes mellitus and HDP (all P>0.05). (2) The placental weight of the CPAP treatment group was significantly lower than that of the control group [(554.0±70.6) vs (615.7±119.1) g], the placental weight/newborn birth weight ratio of the CPAP treatment group was significantly lower than that of the control group (median: 0.17 vs 0.19), and the differences were statistically significant (all P<0.05). (3) The incidence of HDP in pregnant women with moderate to severe OSAS in the CPAP treatment group was lower than that in the control group [1/9 vs 61.8% (21/34)], and the difference was statistically significant ( P<0.05). Conclusions:CPAP treatment could prolong the gestational age in pregnant women with OSAS, reduce the incidence of SGA, increase the birth weight of infants, and reduce the incidence of HDP in pregnant women with moderate to severe OSAS, and is worth promoting in clinical practice. The improvement of neonatal outcomes by CPAP treatment is closely related to the placenta, which is worthy of further exploration.

Peritoneal metastasis represents the most aggressive form of gastric cancer metastasis and serves as a primary contributor to poor prognosis. Conventional therapeutic approaches offer limited survival benefits, making the development of novel treatment strategies an urgent medical priority. With advancements in molecular medicine and sociomedical sciences, contemporary cancer management is evolving towards individualized precision medicine. This transition has given rise to a plethora of innovative therapeutic strategies, including molecular typing-driven targeted therapy, immunotherapy, and locally targeted technology. These strategies emphasize the construction of a precise and individualized therapeutic framework through the integration of genomics, imaging genomics, and artificial intelligence-assisted decision-making, which promotes the continuous improvement of treatment strategies for peritoneal metastasis of gastric cancer. This article provides a comprehensive analysis of the prevailing individualized treatment modalities from the standpoint of precision medicine, offering novel perspectives on the management of peritoneal metastasis in gastric cancer.

The incidence of non-alcoholic fatty liver disease(NAFLD)has been increasing annually.Current primary treatment strategies involve dietary modifications and increased physical activity to allevi-ate symptoms,yet there is a notable lack of targeted pharmacological interventions.Members of the micro RNA-29(miR-29)family(miR-29a,miR-29b,miR-29c)are known to play a critical regulatory role in lipid metabolism within hepatocytes;however,the underlying mechanisms remain to be elucidated.This study aims to identify the target genes and associated signaling pathways of the miR-29 family,thereby providing potential therapeutic targets for the development of NAFLD treatments.Firstly,the human liver cell line HepG2 was utilized as a model for adipogenic induction,and miR-29a/b/c-3p mimics were indi-vidually transfected.Through methods such as Oil Red O staining and triglyceride(TG)quantification,it was observed that the miR-29 family members significantly inhibited lipid accumulation in hepatocytes(P＜0.05).Subsequently,qRT-PCR and Western blot were utilized to detect the expression levels of ad-ipogenic marker genes(fatty acid synthase(FAS),acetyl coa carboxylase(ACACA),stearoyl-coen-zyme a desaturase 1(Scd 1))and autophagy marker genes(sequestosome 1(SQSTM1,also known as p62),autophagy related gene 5(Atg5)),and the results indicated that the members of the miR-29 fam-ily could significantly suppress the expression of FAS,ACACA,Scd1,and p62 genes in hepatocytes,while significantly enhancing the level of the Atg5 gene.Further investigations using signaling pathway activity analysis and dual luciferase reporter assays confirmed that the miR-29a/b/c could suppress the mTOR signaling pathway activity and directly interact with the ten-eleven translocation 2(TET2)gene.Finally,co-transfection experiments were performed to examine the potential synergistic effects among the miR-29-3p family members,and the results demonstrated that co-transfection of miR-29 family members more effectively inhibited lipid droplet accumulation in HepG2 cells and further suppressed the expression of the target gene TET2 compared to individual transfection.In summary,the miR-29 family members may reduce lipid accumulation in hepatocytes by inhibiting the mTOR signaling pathway via the TET2 gene,and they exhibit a positive synergistic effect.