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.

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.

To explore the advantages of traditional Chinese medicine （TCM） and integrative TCM-Western medicine approaches in the treatment of diabetic microvascular complications （DMC）， refine key pathophysiological insights and treatment principles， and promote academic innovation and strategic research planning in the prevention and treatment of DMC. The 38th session of the Expert Salon on Diseases Responding Specifically to Traditional Chinese Medicine， hosted by the China Association of Chinese Medicine， was held in Beijing， 2024. Experts in TCM， Western medicine， and interdisciplinary fields convened to conduct a systematic discussion on the pathogenesis， diagnostic and treatment challenges， and mechanism research related to DMC， ultimately forming a consensus on key directions. Four major research recommendations were proposed. The first is addressing clinical bottlenecks in the prevention and control of DMC by optimizing TCM-based evidence evaluation systems. The second is refining TCM core pathogenesis across DMC stages and establishing corresponding "disease-pattern-time" framework. The third is innovating mechanism research strategies to facilitate a shift from holistic regulation to targeted intervention in TCM. The fourth is advancing interdisciplinary collaboration to enhance the role of TCM in new drug development， research prioritization， and guideline formulation. TCM and integrative approaches offer distinct advantages in managing DMC. With a focus on the diseases responding specifically to TCM， strengthening evidence-based support and mechanism interpretation and promoting the integration of clinical care and research innovation will provide strong momentum for the modernization of TCM and the advancement of national health strategies.

Background: Chinese herbal pieces are an essential component of traditional Chinese medicine. Accurate identification and classification of these materials are crucial in clinical practice. Objective: This study aims to enhance the recognition efficiency of Chinese herbal pieces using deep learning technology, while addressing the limitations of traditional manual classification methods in terms of both quality and efficiency. Methods: A comprehensive dataset containing 201 types of Chinese herbal pieces was established. Based on Real-time Detection Transformer (RT-DETR), we designed and integrated a Feature-focused Diffusion Network (FDN), resulting in an improved model termed RT-DETR-FDN. The proposed FDN includes a Feature-focus Module and a feature diffusion mechanism, enabling the model to capture more extensive feature information from Chinese herbal pieces and diffuse it across multiple detection scales. Results: Experimental results show that RT-DETR-FDN achieved a precision of 0.925, a recall of 0.943, and an mAP50-95 of 0.851. In addition, the model was compared with representative You Only Look Once series models commonly used in object detection. Compared with these models, RT-DETR-FDN achieved higher recognition accuracy while maintaining a lightweight architecture. Conclusion: This study integrates deep learning with traditional Chinese medicine, providing a more effective solution for the recognition of Chinese herbal pieces.

ObjectiveTo investigate the effects of Trpc6 knockout on chronic lipopolysaccharide （LPS）-induced myocardial inflammation and fibrosis in mice and its potential mechanisms. MethodsMale C57BL/6 wild-type （WT） mice and Trpc6 knockout （Trpc6^-/-） mice of the same background were randomly divided into four groups： WT control， WT+LPS （200 μg/kg）， Trpc6^-/- control， and Trpc6^-/-+LPS （200 μg/kg）. Group with LPS received intraperitoneal LPS injections for 21 consecutive days to induce chronic myocardial inflammatory injury. Cardiac ultrasound assessed changes in left ventricular ejection fraction （EF）， left ventricular shortening fraction （FS）， and cardiac output （CO）. Hematoxylin and eosin （HE） staining and periodic acid-Schiff （PAS） staining were used to examine morphological alterations in myocardial tissue. Masson’s trichrome staining was used to assess myocardial fiber alterations； Western blot analysis was used to measure myocardial tissue expression of transient receptor potential calcium channel 6 （TRPC6）， NOD-like receptor family pyrin domain-containing 3 inflammasome （NLRP3），absent in melanoma 2 inflammasome （AIM2）， Caspase-1， interleukin （IL）-6， and IL-1β in mouse myocardial tissue. ResultsCompared with the WT control group， the WT+LPS group exhibited decreased cardiac EF （P<0.01）， FS （P<0.01）， and CO （P<0.05）， along with significantly increased myocardial tissue damage， glycoprotein deposition， and fibrosis （P<0.01）. Further analysis revealed that compared with the WT control group， the WT+LPS group exhibited markedly increased myocardial tissue expression of TRPC6， NLRP3， AIM2， Caspase-1， IL-6， and IL-1β （P<0.01）. Compared with the WT+LPS group， mice in the Trpc6^-/- +LPS group exhibited elevated EF （P<0.01） and FS （P<0.05）， along with reduced myocardial tissue injury， glycoprotein deposition， and fibrosis （P<0.05）. ConclusionChronic LPS treatment can activate NLRP3/AIM2 inflammasomes through the up-regulation of TRPC6 expression， and then lead to chronic myocardial inflammatory injury and fibrosis， while Trpc6 knockdown can reduce myocardial inflammatory injury and fibrosis， and the mechanism is related to inhibiting the activation of NLRP3/AIM2 inflammasomes.

OBJECTIVE To evaluate the efficacy and safety of cadonilimab plus chemotherapy in patients with advanced gastric adenocarcinoma or adenocarcinoma of gastroesophageal junction （AEG） with intermediate， low， or no human epidermal growth factor receptor 2 （HER2） expression. METHODS Patients with advanced gastric adenocarcinoma or AEG with intermediate， low， or no HER2 expression who were treated at Liaoning Cancer Hospital between October 1， 2024 and June 30， 2025 were retrospectively included. According to the treatment regimen received， the patients were divided into group A [cadonilimab plus oxaliplatin and capecitabine （XELOX）， n ＝54 ] ， group B （sintilimab plus XELOX， n ＝68）， and group C （tislelizumab plus XELOX， n ＝49）. Short-term efficacy after 4 cycles of treatment， survival outcomes， and adverse events were compared among the three groups. Cox regression and Logistic regression analyses were further performed to evaluate the effects of the treatment regimen and baseline data on survival outcomes and the risk of grade 3-4 treatment related adverse events （TRAEs）. RESULTS No statistically significant differences in objective response rate or disease control rate were observed among the three groups （ P ＞0.05）. The median progression-free survival was 7.56 （5.62， 8.11） months in group A， 7.23 （5.33， 8.23） months in group B， and 7.33 （5.42， 8.19） months in group C， with no statistically significant difference among the three groups （ P ＞0.05）. The median overall survival （mOS） was 11.67 （8.82， 13.88） months in group A， 9.78 （6.82， 12.73） months in group B， and 9.69 （6.78， 12.66） months in group C. The mOS was significantly longer in group A than in group B and group C （ P ＜0.05）， whereas no statistically significant difference was observed between group B and group C （ P ＞0.05）. The correlation analysis indicated that treatment regimen， Eastern Cooperative Oncology Group performance status （ECOG PS）， number of metastatic organs， and peritoneal metastasis may be associated with overall survival （OS）. No significant association was observed between treatment regimen and the risk of grade 3-4 TRAEs. The incidences of grade 1-2 or grade 3-4 TRAEs did not differ significantly among the three groups （ P ＞0.05）. CONCLUSIONS In patients with advanced gastric adenocarcinoma or AEG with intermediate， low， or no HER2 expression， cadonilimab plus XELOX may provide a more significant OS benefit with a safety profile comparable to that of sintilimab or tislelizumab plus XELOX. Further studies with larger sample sizes are required to validate these findings.

ObjectiveTo understand the infection characteristics of multidrug-resistant organisms (MDROs) in hospitalized patients in a tertiary sentinel hospital in Shanghai, so as to provide an evidence for the development of targeted prevention and control measures. MethodsData of MDROs strains and corresponding medical records of some hospitalized patients in a hospital in Shanghai from 2021 to 2023 were collected, together with an analysis of the basic information, clinical treatment, underlying diseases and sources of sample collection. ResultsA total of 134 strains of MDROs isolated from hospitalized patients in this hospital were collected from 2021 to 2023 , including 63 strains of methicillin-resistant Staphylococcus aureus (MRSA), 57 strains of carbapenem-resistant Acinetobacter baumannii (CRAB), and 14 strains of carbapenem-resistant Klebsiella pneumoniae (CRKP). Of the 134 strains, 30 strains were found in 2021, 47 strains in 2022 and 57 strains in 2023. The male-to-female ratio of patients was 2.05∶1, with the highest percentage (70.90%) in the age group of 60‒<90 years. The primary diagnosis was mainly respiratory disease, with lung and respiratory tract as the cheif infection sites. There was no statistically significant difference in the distribution of strains between different genders and infection sites (P>0.05). However, the differences in the distribution of strains between different ages and primary diagnosis were statistically significant (P<0.05). Patients who were admitted to the intensive care unit (ICU), had urinary tract intubation, were not artery or vein intubated, were not on a ventilator, were not using immunosuppresants or hormones, and were not applying radiotherapy or chemotherapy were in the majority. There was no statistically significant difference in the distribution of strains for whether received radiotherapy or chemotherapy or not (P>0.05), while the differences in the distribution of strains with ICU admission history, urinary tract intubation, artery or vein intubation, ventilator use, and immunosuppresants or hormones use or not were statistically significant (all P<0.05). The type of specimen was mainly sputum, the hospitalized ward was mainly comprehensive ICU, the sampling time was mainly in the first quarter throughout the year, the number of underlying diseases was mainly between 1 to 2 kinds, the application of antibiotics ≥4 kinds, and those who didn’t receive any surgery recently accounted for the most. There were statistically significant differences in the distribution of strains between different specimen types, wards occupied and history of ICU stay (P<0.05), but no statistically significant difference in the distribution of strains between different sampling times, number of underlying diseases and types of antibiotics applied (P>0.05). ConclusionThe situation of prevention and control on MDROs in this hospital is still serious. Focus should be placed on high-risk factors’ and infection monitoring and preventive measures should be strengthened to reduce the incidence rate of MDROs infection.

Objective To design a multi-terminal collaborative medical equipment acceptance management system to enhance the informatized management of medical equipment acceptance.Methods The multi-terminal collaborative medical equipment acceptance management system was designed with the front-end and back-end separation mode.The front end was developed with Flutter framework and Dart language,the back end was implemented with Tornado 6.1 architecture and Python language,the communication between the front-end and the back-end service followed the RESTful design principle and the interaction was carried out through the hypertext transfer protocol(HTTP)request.There were three functional modules involved in the system for user management,basic information management and acceptance management.Results The system developed realized informatized management for medical equipment acceptance process,supported cross-platform management of acceptance reports,related attachments and medical device registration certificates and improved the quality and efficiency of medical equipment acceptance.Conclusion The system developed facilitates multi-terminal collaborative management for medical equipment acceptance,and lays a foundation for the digital and intelligent transformation of hospital medical equipment management.[Chinese Medical Equipment Journal,2025,46(7):39-44]

Patients with severe periodontal disease often involve multidisciplinary therapy.This paper reports a case of adult patients with severe periodontitis who was treated by orthodontics,restoration,and periodontics.The space between upper central incisors was closed,aesthetics and periodontal conditions were significantly improved.

Objective:To investigate the effects of toosendanin(TSN)on the proliferation,apoptosis,migration and invasion of esophageal squamous cell carcinoma(ESCC)KYSE150 cells,and to elucidate its underlying molecular mechanisms.Methods:CCK-8 assay,colony formation assay,and EdU assay were used to assess the effects of varying TSN concentrations(0.062 5,0.125,and 0.25 μmol/L)on KYSE150 cell proliferation.The impacts of TSN on the apoptosis,migration,and invasion of KYSE150 cells were evaluated using flow cytometry,wound healing assay,and Transwell chamber assay,respectively.The expression of hypoxia-inducible factor 1 alpha(HIF1A)in esophageal cancer tissues was analyzed using the GEPIA database.qPCR was used to detect the expression level of HIF1A mRNA in human esophageal epithelial Het-1A and KYSE150 cells,and in TSN-treated KYSE150 cells.Western blot(WB)was performed to detect the effects of TSN on the upstream signaling pathway AKT/mTOR of HIF1A and the expression of downstream proteins related to cell migration,invasion,and apoptosis.Results:TSN of varying concentrations significantly inhibited proliferation,migration,and invasion of KYSE150 cells and promoted apoptosis in a dose-dependent manner(P<0.05 or P<0.01).HIF1A mRNA was highly expressed in KYSE150 cells,and its expression was significantly downregulated after TSN treatment(P<0.05 or P<0.01).TSN markedly downregulated the expression of HIF1A and key upstream signaling proteins p-AKT and p-mTOR.In addition,TSN significantly suppressed the expression of downstream proteins associated with cell migration,invasion,and apoptosis,including N-cadherin,vimentin,Bcl-2,and caspase-3,while upregulating the expression of E-cadherin(P<0.05 or P<0.01).Conclusion:TSN inhibits the proliferation,migration,and invasion,and induces apoptosis in ESCC KYSE150 cells by down-regulating HIF1A expression through suppression of the AKT/mTOR signaling pathway.