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.

Health economics evidence plays an important role in linking clinical value evidence with health resource allocation decisions in the development of clinical practice guidelines. It can not only effectively balance clinical effectiveness and economic feasibility but also avoid forming "idealized" recommendations that are detached from the affordability of the healthcare system or the burden-bearing capacity of patients. To promote guideline developers to use health economics evidence more standardizedly and fully, this paper conducts an in-depth analysis of the current application status, existing challenges, access channels, and application processes of health economics evidence in current guidelines, and on this basis, puts forward considerations and suggestions for strengthening and standardizing the application of health economics evidence in China's clinical practice guidelines.

Background: Problems related to sleep affect approximately 23-56% of the world’s population. In Mongolia, the prevalence of non-organic sleep disorders is estimated at 27.9%, among which 42.2% of the population have poor sleep quality. Long-term insomnia can have a negative impact on an individual’s normal work and life, increasing the risk of various health problems. Severe insomnia can reduce work efficiency and concentration, thereby causing serious harm. Traditional medicine has a long history of treating insomnia. However, there are currently no systematic studies on insomnia based on ancient traditional medical books. Goal: Based on the ancient medical literature of traditional medicine, identify the underlying diseases that cause insomnia and compare their symptoms. Materials and Methods: We adopted the checklist method to list the relevant information of insomnia from the literature, providing a prerequisite for further analysis and the issue of syndrome differentiation of insomnia was analyzed by using comparison methods.
The research protocol was reviewed and approved by the Medical Ethics Committee of the Mongolian National University of Medical Sciences at its meeting on June 24, 2025 (No. 04), and ethical clearance was granted for the conduct of this study. Results: The research materials we selected did not describe insomnia as a dedicated chapter, but mentioned the content related to insomnia in the form of disease symptoms, such as terms like ”sleeplessness”, ”reduced sleep” and ”light sleep”. We explore the underlying diseases of insomnia based on the above symptoms related to insomnia and analyze the syndrome differentiation of insomnia. Exploring the underlying disease of insomnia:
1. Insomnia caused by diseases resulting from Wind include Wind delirium, palpitations, bone marrow Wind, heart Wind, lung Wind, Wind-induced diabetes, Wind tsbs.
2. Insomnia caused by diseases resulting from Bile include heat Bile, heart Bile, liver sdembu, deficiency heat, Invisible heat and epidemic heat.
3. Other diseases include mugpo spreads to the heart, heart chuser, trichomoniasis and childhood evil spirit disease.
We also compared the symptoms of the underlying diseases that cause insomnia and listed their similarities and differences. Conclusion The underlying etiologies of insomnia were categorized into Wind, Bile, Mugpo, yellow fluid, parasitic and evil spirit disorders. Accordingly, effective management of insomnia requires differentiation based on the primary disease and an individualized treatment approach that integrates both etiological and symptomatic therapies.

ObjectiveTo investigate the inhibitory effect of gingerol， an active component of ginger， on Staphylococcus aureus （S. aureus） infection， and to preliminarily explore its mechanism related to extracellular vesicles （EVs）. MethodsS.aureus infection models were established in human umbilical vein endothelial cell （HUVECs）， Vero E6 cells， and C57BL/6 mice. Experimental groups included control， infection， and gingerol-treated groups. Bacterial load and VE-cadherin protein expression were detected using immunofluorescence and Western blot. EVs were isolated by size exclusion chromatography and characterized by transmission electron microscopy and nanoparticle tracking analysis. miRNA sequencing was performed on EVs. ResultsGingerol treatment significantly reduced the bacterial load in both in vitro and in vivo infection models and upregulated VE-cadherin expression. miRNA sequencing of EVs revealed that S. aureus infection upregulated the expression of hsa-miR-320c， while gingerol treatment reversed this abnormal expression. Bioinformatic analysis further predicted that the target genes of hsa-miR-320c were significantly enriched in cell junction-related pathways. ConclusionGingerol exhibits clear antibacterial and host-protective effects， by regulating hsa-miR-320c in EVs to maintain endothelial barrier integrity.

Background and aims Alcohol-associated liver disease (ALD) is a leading cause of liver-related morbidity and mortality worldwide, with no currently effective treatment. ALD is caused by excessive lipid buildup, which eventually triggers inflammation and fibrosis in the liver. Activation of hepatic Kupffer cells (KCs) and macrophages drives liver inflammation, which can worsen alcohol-induced liver injury. The autophagy-lysosome system is crucial for macrophages to support their innate immune functions. Transcription factor EB (TFEB) is a key regulator of autophagy and lysosomal biogenesis, but the role of macrophage TFEB in ALD development is unknown. The aim of this study was to evaluate the effects of Gao-binge alcohol consumption on myeloid cell TFEB and elucidate the role of myeloid TFEB in ALD. Methods Two-to-three-month-old male and female LysM Cre− (WT) and LysM Cre+ Tfeb Flox/Flox (f/f) (myeloid-Tfeb KO) mice were subjected to chronic alcohol feeding plus an acute binge following the Gao-binge model. Serum alanine aminotransferase, aspartate aminotransferase, triglycerides, and cholesterol content were determined using biochemical assays. Total hepatic protein content and messenger RNA (mRNA) levels of autophagy-related proteins and inflammatory markers were determined using immunoblotting, immunohistochemistry, and real-time quantitative polymerase chain reaction (RT-qPCR). Isolated hepatic infiltrating macrophages and KCs from mice given intragastric ethanol infusions were analyzed by Western blot for TFEB and autophagy-related protein content. Raw 264.7 macrophages were treated with ethanol, lipopolysaccharide (LPS), and LPS plus ethanol to examine nuclear TFEB translocation using immunofluorescence. Results We found that TFEB levels were higher in macrophage/KC cells than in hepatocytes and cholangiocytes. While ethanol feeding increased serum alanine aminotransferase and aspartate aminotransferase levels, as well as hepatic triglyceride levels, no significant differences were observed between WT and myeloid-Tfeb KO mice. The number of F4/80-positive KCs/macrophages was similar in all four experimental groups, but hepatic neutrophil infiltration increased in alcohol-fed myeloid-Tfeb KO mice. LPS or ethanol alone induced nuclear TFEB translocation only moderately in Raw 264.7 macrophages. Conclusions Our findings suggest that myeloid TFEB is dispensable for alcohol-induced liver injury in mice.

Immobilized enzyme-based enzyme electrode biosensors, characterized by high sensitivity and efficiency, strong specificity, and compact size, demonstrate broad application prospects in life science research, disease diagnosis and monitoring, etc. Immobilization of enzyme is a critical step in determining the performance (stability, sensitivity, and reproducibility) of the biosensors. Random immobilization (physical adsorption, covalent cross-linking, etc.) can easily bring about problems, such as decreased enzyme activity and relatively unstable immobilization. Whereas, directional immobilization utilizing amino acid residue mutation, affinity peptide fusion, or nucleotide-specific binding to restrict the orientation of the enzymes provides new possibilities to solve the problems caused by random immobilization. In this paper, the principles, advantages and disadvantages and the application progress of enzyme electrode biosensors of different directional immobilization strategies for enzyme molecular sensing elements by specific amino acids (lysine, histidine, cysteine, unnatural amino acid) with functional groups introduced based on site-specific mutation, affinity peptides (gold binding peptides, carbon binding peptides, carbohydrate binding domains) fused through genetic engineering, and specific binding between nucleotides and target enzymes (proteins) were reviewed, and the application fields, advantages and limitations of various immobilized enzyme interface characterization techniques were discussed, hoping to provide theoretical and technical guidance for the creation of high-performance enzyme sensing elements and the manufacture of enzyme electrode sensors.

With the rapid development of sequencing technologies, the detection of alternative polyadenylation (APA) in mammals has become more precise. APA precisely regulates gene expression by altering the length and position of the poly(A) tail, and is involved in various biological processes such as disease occurrence and embryonic development. The research on APA in mammals mainly focuses on the following aspects:(1) identifying APA based on transcriptome data and elucidating their characteristics; (2) investigating the relationship between APA and gene expression regulation to reveal its important role in life regulation;(3) exploring the intrinsic connections between APA and disease occurrence, embryonic development, differentiation, and other life processes to provide new perspectives and methods for disease diagnosis and treatment, as well as uncovering embryonic development regulatory mechanisms. In this review, the classification, mechanisms and functions of APA were elaborated in detail and the methods for APA identifying and APA data resources based on various transcriptome data were systematically summarized. Moreover, we epitomized and provided an outlook on research on APA, emphasizing the role of sequencing technologies in driving studies on APA in mammals. In the future, with the further development of sequencing technology, the regulatory mechanisms of APA in mammals will become clearer.

Objective:To analyze the potential risk factors for early relapse/progression in patients with multiple myeloma(MM)and develop a risk prediction model based on these factors.Methods:A retrospective analysis was conducted on 187 newly diagnosed multiple myeloma(NDMM)patients who treated at the Affiliated Hospital of North Sichuan Medical College from February 2014 to December 2020.The clinical,laboratory examination,and follow-up data of patients experiencing relapse/progression within 24 months after treatment(ER/EP24)were analyzed using univariate and multivariate analyses,and a nomogram prediction model was established.Results:Among the 187 patients,58(31.0％)experienced ER/EP24,with a median survival time of only 24 months.The results of multivariate logistic regression analysis showed that failure to achieve partial response(PR)or better after 3-4 cycles of chemotherapy and albumin(ALB)levels＜35 g/L were independent risk factors for ER/EP24(P＜0.05).These factors,along with other clinically relevant variables,were further incorporated into the nomogram prediction model.The model demonstrated a concordance index(C-index)of 0.784,indicating strong predictive accuracy.Conclusion:MM patients experiencing ER/EP24 exhibit poor outcome,and the nomogram model developed in this study effectively predicts the risk of ER/EP24 in NDMM patients,providing a valuable tool for clinical risk assessment.

Objective:To explore the clinical characteristics and prognosis risk factors of aggressive NK-cell leukemia(ANKL).Methods:The clinical and laboratory data of 34 patients with ANKL and 15 patients with chronic lymphoproliferative disorders of NK cells(CLPD-NK)admitted to the First Affiliated Hospital of Zhengzhou University from September 2019 to December 2024 were retrospectively analyzed.The Kaplan-Meier method was used to calculate survival rates,and the Cox proportional hazards regression model was used to analyze prognostic factors.Results:Compared with CLPD-NK patients,ANKL patients had a younger median age of onset,a higher proportion patients with EBV-DNA≥500 copies/ml,hepatosplenomegaly and hemophagocytic syndrome.They also presented with a higher peak of fever,a shorter median survival time,lower WBC count,PLT count,ALB and Fib values,while having higher LDH,AST,TG,ferritin,CRP and PCT levels.There were statistically significant differences in the morphology and expression of HLA-DR,CD56,CD57,CD16 and CD158 on abnormall cells between ANKL patients and CLPD-NK patients.Multivariate survival analysis revealed that combined with asparaginase treatment could improve patients' survival,and CRP≥ 15 mg/L and Fib＜2.0 g/L were independent risk factors affecting the overall survival of patients with ANKL.Conclusion:The differences in clinical features and laboratory tests between patients with ANKL and CLPD-NK aid in the diagnosis of ANKL.CRP and Fib levels can be used to predict the prognosis of patients,and combined asparaginase therapy can enhance the overall survival of patients.