Objective: To prepare the erythrocyte-liposome drug delivery system to enhance the therapeutic effect of drugs on tumors and inhibit tumor metastasis. Methods: This study prepared and characterized paclitaxel (PTX)-plerixafor (AMD3100) liposomes (Lips), developed the erythrocyte-liposome drug delivery system, and evaluated its targeting efficiency and therapeutic efficacy through a series of in vitro cellular and in vivo animal experiments. Results: The particle size of PTX-AMD-Lips was (186.4±0.83) nm. Drug encapsulation efficiency of PTX-AMD-Lips was (75.50±5.27)% for PTX and (88.31±2.45)% for AMD. The Binding efficiency between RBC and liposomes in the drug delivery system was (69.93±2.55)%. Vitro cellular experiments revealed that PTX-AMD-Lips significantly inhibited tumor cell migration. In vivo animal experiments, the erythrocyte-liposome drug delivery system significantly increased drug accumulation in the lungs. At the experimental endpoint, the quantitative fluorescence signal of tumor size measured (4.04±0.44)×10 for the PTX-Lips group, and (5.14±3.40)×10 for the RBC-PTX-AMD-Lips group. Conclusion: The erythrocyte-liposome drug delivery system could enhance the lung-specific targeting capability of liposomes, kill tumor cells and suppress further metastasis effectively.

To develop the Pharmacovigilance Guidelines for Clinical Application of Chinese Patent Medicines for Mucosal Administration in response to common problems， including insufficient safety information in package inserts， amplified medication risks in special populations， and non-standard clinical practices， thus establishing a risk management system tailored to the characteristics of Chinese patent medicines for mucosal administration. An approach combining qualitative and quantitative methods was adopted. In accordance with the Drug Administration Law of the People's Republic of China （2019 revision） and the GB/T 1.1—2020 standard， a systematic search was performed in the Chinese Pharmacopoeia （2020 edition）， the Catalog of Medicines Covered by Medical Insurance （2022 edition）， Chinese databases ［China Network of Knowledge Infrastructure （CNKI）， Wanfang Data （Wanfang）， and VIP journal resource integration service platform （VIP）］， and international databases （Cochrane Library， PubMed， and EMbase）. Guideline outlines were developed through questionnaire surveys， expert interviews， and the nominal group technique. The content of each item was formulated with full consideration of traditional Chinese medicine （TCM） incompatibility， as well as the conceptual connotations and extensions of pharmacovigilance. The results included 54 Chinese patent medicines for mucosal administration from the Chinese Pharmacopoeia （2020 edition） and 58 from the Catalog of Medicines Covered by Medical Insurance （2022 edition）. Safety-related items in the corresponding package inserts were collected， and 27 relevant publications were retrieved. Thirty experts from 24 institutions were mobilized for the drafting， and opinions from 61 external experts were solicited. A pharmacovigilance framework was established， covering the full chain of "monitoring， identification， assessment， and control". Based on seven anatomical sites， including nasal， ocular， and oral mucosa， a stratified monitoring system was constructed. The guideline proposed key recommendations on improving package insert sections such as "Adverse Reactions"， "Contraindications"， and "Precautions"， clinical procedure standardization in healthcare institutions， risk control， and dynamic pharmacovigilance. The Guideline provides evidence-based support tailored to the risk profile of Chinese patent medicines for mucosal administration， filling the current gap in international pharmacovigilance standards in this field， while offering technical support for safety management across the full life cycle of medicines for mucosal administration.

To develop the Pharmacovigilance Guidelines for Clinical Application of Chinese Patent Medicines for Mucosal Administration in response to common problems， including insufficient safety information in package inserts， amplified medication risks in special populations， and non-standard clinical practices， thus establishing a risk management system tailored to the characteristics of Chinese patent medicines for mucosal administration. An approach combining qualitative and quantitative methods was adopted. In accordance with the Drug Administration Law of the People's Republic of China （2019 revision） and the GB/T 1.1—2020 standard， a systematic search was performed in the Chinese Pharmacopoeia （2020 edition）， the Catalog of Medicines Covered by Medical Insurance （2022 edition）， Chinese databases ［China Network of Knowledge Infrastructure （CNKI）， Wanfang Data （Wanfang）， and VIP journal resource integration service platform （VIP）］， and international databases （Cochrane Library， PubMed， and EMbase）. Guideline outlines were developed through questionnaire surveys， expert interviews， and the nominal group technique. The content of each item was formulated with full consideration of traditional Chinese medicine （TCM） incompatibility， as well as the conceptual connotations and extensions of pharmacovigilance. The results included 54 Chinese patent medicines for mucosal administration from the Chinese Pharmacopoeia （2020 edition） and 58 from the Catalog of Medicines Covered by Medical Insurance （2022 edition）. Safety-related items in the corresponding package inserts were collected， and 27 relevant publications were retrieved. Thirty experts from 24 institutions were mobilized for the drafting， and opinions from 61 external experts were solicited. A pharmacovigilance framework was established， covering the full chain of "monitoring， identification， assessment， and control". Based on seven anatomical sites， including nasal， ocular， and oral mucosa， a stratified monitoring system was constructed. The guideline proposed key recommendations on improving package insert sections such as "Adverse Reactions"， "Contraindications"， and "Precautions"， clinical procedure standardization in healthcare institutions， risk control， and dynamic pharmacovigilance. The Guideline provides evidence-based support tailored to the risk profile of Chinese patent medicines for mucosal administration， filling the current gap in international pharmacovigilance standards in this field， while offering technical support for safety management across the full life cycle of medicines for mucosal administration.

Objective To quantitatively assess the exposure-response association between exposure to heatwave and sudden death, estimate the attributable excess deaths, and identify potential vulnerable subgroups. Methods A time-stratified case-crossover study was conducted among residents who died from sudden death in Jiangsu Province, China between 2015 and 2021. Heatwave events in Jiangsu Province, defined using varying relative temperature thresholds and durations, were identified using temperature data from the China Meteorological Administration Land Data Assimilation System (CLDAS V2.0). Individual heatwave exposure was assessed based on each subject's residential address. The exposure-response association between heatwave and sudden death was evaluated using conditional logistic regression model combined with a Distributed Lag Nonlinear Model(DLNM). Heatwave-attributable excess deaths were estimated. Stratified analyses by sex and age were performed to assess potential effect modifications. Results Under all definitions, exposure to heatwave was significantly associated with an increased risk of sudden death, and the risk increased with the intensity of heatwave. Using the P95_3d definition (temperature exceeding the 95th percentile for ≥3 consecutive days), heatwave was significantlyassociated with a 56% increased risk of sudden death (95% CI: 31%, 86%). The population-attributable fraction of sudden death due to heatwave exposure was 1.45% (95% CI: 0.97%, 1.90%). Stratified analyses indicated no statistically significant differences in the association between heatwave exposure and sudden death across age or sex subgroups. Conclusion Heatwave exposure was associated with an increased risk of sudden death. Reducing heatwave exposure during summer may help lower the occurrence of sudden death.

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.

Objective: To verify the inhibitory effect of a carbon monoxide hemoglobin-based oxygen carrier (CO-HBOC) on the fibrotic process in mice with idiopathic pulmonary fibrosis (IPF), clarify its efficacy difference compared with hemoglobin-based oxygen carriers (HBOCs), and elucidate its mechanism of action via proteomic analysis. Methods: CO-HBOC was prepared using gas loading technology. An IPF mouse model was established and the mice were randomly divided into a normal saline control group, an HBOC treatment group, and a CO-HBOC treatment group. The fibrotic area percentage was analyzed using Micro-CT; the degree of inflammatory infiltration and fibrosis in lung tissue was assessed by pathological section staining (e.g., HE and Masson staining); and differentially expressed proteins in lung tissue of IPF mice after CO-HBOC treatment were screened using proteomic technology. Results: Micro-CT results showed that the mean fibrotic area percentage in the CO-HBOC treatment group on day 21 was (8.89±0.98)%, which was better than that of the HBOC group (16.5±1.732)% and the normal saline group (30.75±6.45)% (P<0.05). HE and Masson staining results showed that the CO-HBOC group had reduced inflammatory cell infiltration and significantly decreased collagen fiber deposition in lung tissue, with a mean pathological score of 3.33±0.58, which was lower than that of the normal saline control group (8.33±1.53)(P<0.05); the mean collagen-positive area percentage was (3.33±1.53)%, significantly lower than that of the normal saline control group (14.00±3.61)% (P<0.05). Proteomic analysis identified 330 differentially expressed proteins, which were mainly enriched in inflammatory response regulatory pathways (such as the complement and coagulation cascades), and the expression changes of complement proteins may be the core target of CO-HBOC's anti-fibrotic effects. Conclusion: CO-HBOC can inhibit inflammatory responses and regulate fibrosis-related signaling pathways, there-by effectively inhibiting the fibrotic process in IPF mice, with superior efficacy to HBOC. Its mechanism of action involves the regulation of complement cascade-related signaling pathways and complement protein expression, providing an experimental and theoretical basis for targeted therapy of IPF.

Objective: To enhance the ability of nanoparticles to target and bind tumor cells by constructing a neutrophil hitchhiking system based on hyaluronic acid (HA)-modified dual-drug loaded lipid nanoparticles. Methods: Lipid nanoparticles (LNPs) were prepared using microfluidic technology, and the nitrogen/phosphate (N/P) ratio, flow rate ratio, and drug-to-lipid ratio were optimized. HA-modified LNPs (HA-LNPs) were prepared and characterized. The interaction between the nanoparticles and tumor cells was evaluated through in vitro cell experiments. Results: The optimal preparation conditions for LNPs are N/P=8, flow rate ratio=5, and drug-to-lipid ratio=1∶30 (w∶w). HA-LNPs has a particle size of (177.28±2.41) nm, a polydispersity index (PDI) of 0.198±0.10, and an siRNA encapsulation efficiency of (91.37±0.47)%. The optimal binding rate with neutrophils was (98.64±2.34)%. Conclusion: An HA-modified dual-drug loaded lipid nanoparticle-neutrophil hitchhiking system was successfully constructed, enhancing the synergistic anti-tumor activity of the nanomedicine and the uptake of nanoparticles by tumor cells, providing a novel delivery strategy for targeted therapy of bone marrow tumors.