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.

ObjectiveZheng’s San Qi San (ZSQS) power, a classic traditional Chinese medicine (TCM) formula, is used for treating soft tissue injuries involving muscles, tendons, and ligaments. However, its underlying therapeutic mechanisms remain unclear. This study aimed to screen and identify pharmaceutically active ingredients and their candidate biomolecule targets, and further elucidate the molecular mechanism of ZSQS in the treatment of skeletal muscle injury. MethodsNetwork pharmacology was employed to construct “ZSQS-component-target”, “protein-protein interaction (PPI)” and “active ingredient-core protein-pathway” networks to predict the key active ingredients and potential core targets of ZSQS for skeletal muscle injury. The predicted results were then validated via microarray data from the GEO database. Molecular docking was then performed to assess the binding ability between the screened active ingredients of ZSQS and the candidate core targets. Moreover, liquid chromatography-mass spectrometry (LC-MS) was used for qualitative and quantitative analysis to verify the active components of the drug and ZSQS serum. Finally, an animal model of eccentric exercise-induced skeletal muscle injury and a myotube cell model of oxidative stress-induced injury were established to validate the effects of ZSQS and its interventional effects on the biological functions of critical targets, thereby demonstrating the potential therapeutic mechanism of ZSQS. ResultsAmong the 111 active components identified in ZSQS and their corresponding 204 targets related to the skeletal muscle injury repair process, 14 core targets (including AKT1) and 4 core active components (quercetin, luteolin, kaempferol, and β‑sitosterol) were screened out, while the corresponding metabolites of quercetin, luteolin and kaempferol were detected in the ZSQS serum. Among these targets, 5 candidate genes (IL-6, CASP3, HIF1A, STAT3, and JUN) overlapped with the differential expression screening results with GEO data, and IL-6 was confirmed to be enriched in the PI3K/AKT pathway. Combined with the prediction results of the AKT expression levels, these findings suggest that the phosphorylation level of AKT1 plays a core role in the therapeutic mechanism of ZSQS. Molecular docking analysis further revealed that the PH domain of AKT1 had high binding energy with all 4 core active components, as verified by LC-MS. Finally, animal model studies have shown the promoting effect of ZSQS administration on skeletal muscle injury repair and its possible antioxidant damage mechanism. Cell model studies further demonstrated that ZSQS-containing serum, core active ingredient combination therapy, and quercetin monomer could increase the phosphorylation level of AKT, promote the nuclear translocation of Nrf2, upregulate the expression of downstream antioxidant enzymes (SOD, GPx, and GR), and inhibit the expression of inflammatory factors (IL-6 and TNF-α), thereby alleviating oxidative stress and the inflammatory response. ConclusionZSQS alleviates skeletal muscle injury mainly by activating the AKT/Nrf2 signaling pathway, enhancing cellular antioxidant and anti-inflammatory capabilities. The results of this study provide a scientific basis for the clinical application and modernized development of ZSQS.

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.

ObjectiveTo investigate the association between insulin resistance （IR） and cardiovascular metabolic indicators， including blood pressure， blood lipids， and serum uric acid， in a middle-aged population. MethodsBased on the baseline survey of the Hong Sifang cohort of China National Salt Industry Group， a total of 575 participants were included. According to the homeostasis model assessment of insulin resistance， the participants were divided into an IR group （n=116） and a non-IR group （n=459）. Differences between the two groups were compared using the t-test and chi-square test. Multivariate logistic regression analysis was performed to evaluate the associations between IR and abnormalities in metabolic indicators. ResultsA total of 575 participants were included， including 390 men and 185 women， with a mean age of （48.58 ± 5.14） years and a mean body mass index （BMI） of （24.16 ± 2.97） kg/m². Blood pressure， serum uric acid， and blood lipid levels were significantly higher in the IR group than in the non-IR group （P<0.001）. After adjusting for potential confounders including age， sex， and BMI， IR was independently associated with hypertension， dyslipidemia， and hyperuricemia， with odds ratios （OR） and 95% confidence intervals （CI） of 2.57 （1.61-4.09）， 3.81 （2.36-6.17）， and 2.68 （1.53-4.71）， respectively （all P<0.001）. ConclusionInsulin resistance is significantly associated with multiple cardiovascular metabolic risk factors in the middle-aged population. Monitoring IR may contribute to the early prevention and control of cardiovascular diseases.

Under the current upsurge of cross-disciplinary research between artificial intelligence （AI） and traditional Chinese medicine （TCM）， the inheritance of academic thought in TCM is confronted with the deep-seated predicament of cognitive paradigm dislocation. The existing AI model is based on the classical reasoning mode of formal logic and statistical probability， which is difficult to adapt to the nonlinear and holistic cognitive logic of TCM with image-based thinking and syndrome-differentiated treatment as the core， resulting in systematic misreading and loss of the core essence in digital inheritance. Based on this， this paper proposes to construct a new cognitive model oriented towards the context of TCM. Its essence is not to have AI imitate the thinking of TCM， but to establish an auxiliary understanding framework based on semantic mapping and relational reasoning. It is advocated that the role of AI should be reconstructed from a knowledge substitute to a clinical interactor， and its application boundary in the inheritance of TCM wisdom should be clarified. By establishing the theoretical framework and practical path of human-computer collaboration， this paper aims to provide a scientific basis for realizing the deep integration of AI technology and the academic thought in TCM.

Under the current upsurge of cross-disciplinary research between artificial intelligence （AI） and traditional Chinese medicine （TCM）， the inheritance of academic thought in TCM is confronted with the deep-seated predicament of cognitive paradigm dislocation. The existing AI model is based on the classical reasoning mode of formal logic and statistical probability， which is difficult to adapt to the nonlinear and holistic cognitive logic of TCM with image-based thinking and syndrome-differentiated treatment as the core， resulting in systematic misreading and loss of the core essence in digital inheritance. Based on this， this paper proposes to construct a new cognitive model oriented towards the context of TCM. Its essence is not to have AI imitate the thinking of TCM， but to establish an auxiliary understanding framework based on semantic mapping and relational reasoning. It is advocated that the role of AI should be reconstructed from a knowledge substitute to a clinical interactor， and its application boundary in the inheritance of TCM wisdom should be clarified. By establishing the theoretical framework and practical path of human-computer collaboration， this paper aims to provide a scientific basis for realizing the deep integration of AI technology and the academic thought in TCM.

Ulcerative colitis （UC） is a chronic inflammatory bowel disease primarily affecting the colon and rectum. With a rising incidence， UC has aroused an increasingly serious public health concern. The etiology and pathogenesis of UC are complex， involving genetic susceptibility， intestinal barrier dysfunction， immune dysregulation， and environmental factors such as diet， smoking， and infection. Current UC therapies face limitations including persistent drug resistance， multiple side effects， and compromised immune function， necessitating the exploration of novel intervention strategies. In recent years， with the continuous advancement of research into UC mechanisms， the Toll-like receptor 4 （TLR4）/nuclear factor-κB （NF-κB） signaling pathway has been revealved as one of the classical pathways involved in inflammation. Being crucial for maintaining intestinal homeostasis， this pathway regulates inflammatory and immune responses by controlling gene transcription， thereby playing a significant role in the occurrence and progression of UC. However， systematic summarization within this field remains lacking. Traditional Chinese medicine （TCM） possesses unique advantages through its multi-target， multi-pathway， and multi-mechanism approaches， being capable of curbing the pathological progression of UC by targeting key molecules in the TLR4/NF-κB signaling pathway. This paper systematically summarizes the mechanisms by which TLR4/NF-κB-related pathways regulate UC， primarily encompassing inflammatory responses， oxidative stress， immune balance， and gut microbiota. It reviews single herbs （e.g.， Rosa roxburghii root and Saposhnikoviae Radix）， active components （e.g.， resveratrol， Tripterygium glycosides， and gypenosides）， herbal extracts （e.g.， Zingiberis Rhizoma extract and Taraxaci Herba extract）， and compound formulas for clearing heat and removing dampness， invigorating the spleen and warming the kidneys， clearing heat and detoxifying， harmonizing the liver and spleen， and treating cold and heat in complexity （e.g.， Huaihua Powder， Shenling Baizhu Powder， and Jiedu Huayu Formula）. The aim is to fully leverage the advantages of TCM in UC treatment and provide novel insights for clinical and pharmacological research on UC.

Ulcerative colitis （UC） is a chronic inflammatory bowel disease primarily affecting the colon and rectum. With a rising incidence， UC has aroused an increasingly serious public health concern. The etiology and pathogenesis of UC are complex， involving genetic susceptibility， intestinal barrier dysfunction， immune dysregulation， and environmental factors such as diet， smoking， and infection. Current UC therapies face limitations including persistent drug resistance， multiple side effects， and compromised immune function， necessitating the exploration of novel intervention strategies. In recent years， with the continuous advancement of research into UC mechanisms， the Toll-like receptor 4 （TLR4）/nuclear factor-κB （NF-κB） signaling pathway has been revealved as one of the classical pathways involved in inflammation. Being crucial for maintaining intestinal homeostasis， this pathway regulates inflammatory and immune responses by controlling gene transcription， thereby playing a significant role in the occurrence and progression of UC. However， systematic summarization within this field remains lacking. Traditional Chinese medicine （TCM） possesses unique advantages through its multi-target， multi-pathway， and multi-mechanism approaches， being capable of curbing the pathological progression of UC by targeting key molecules in the TLR4/NF-κB signaling pathway. This paper systematically summarizes the mechanisms by which TLR4/NF-κB-related pathways regulate UC， primarily encompassing inflammatory responses， oxidative stress， immune balance， and gut microbiota. It reviews single herbs （e.g.， Rosa roxburghii root and Saposhnikoviae Radix）， active components （e.g.， resveratrol， Tripterygium glycosides， and gypenosides）， herbal extracts （e.g.， Zingiberis Rhizoma extract and Taraxaci Herba extract）， and compound formulas for clearing heat and removing dampness， invigorating the spleen and warming the kidneys， clearing heat and detoxifying， harmonizing the liver and spleen， and treating cold and heat in complexity （e.g.， Huaihua Powder， Shenling Baizhu Powder， and Jiedu Huayu Formula）. The aim is to fully leverage the advantages of TCM in UC treatment and provide novel insights for clinical and pharmacological research on UC.

In this experiment, self-assembled nanoparticles(SANs) were prepared by the pH-driven method, and Her-HCP SAN was constructed by using herpetrione(Her) and Herpetospermum caudigerum polysaccharides(HCPs). The average particle size and polydispersity index(PDI) were used as evaluation indexes for process optimization, and the quality of the final formulation was evaluated in terms of particle size, PDI, Zeta potential, and microstructure. The proposed Her-HCP SAN showed a spheroid structure and uniform morphology, with an average particle size of(244.58±16.84) nm, a PDI of 0.147 1±0.014 8, and a Zeta potential of(-38.52±2.11) mV. Her-HCP SAN significantly increased the saturation solubility of Her by 2.69 times, with a cumulative release of 90.18% within eight hours. The results of in vivo unidirectional intestinal perfusion reveal that Her active pharmaceutical ingredient(API) is most effectively absorbed in the jejunum, where both K_a and P_(app) are significantly higher compared to the ileum(P<0.001). However, the addition of HCP leads to a significant reduction in the P_(app) of Her in the jejunum(P<0.05). Furthermore, the formation of the Her-HCP SAN results in a notably lower P_(app) in the jejunum compared to Her API alone(P<0.001), while both K_a and P_(app) in the ileum are significantly increased(P<0.001, P<0.05). The absorption of Her-HCP SAN at different concentrations in the ileum shows no significant differences, and the pH has no significant effect on the absorption of Her-HCP SAN in the ileum. The addition of the transporter protein inhibitors(indomethacin and rifampicin) significantly increases the absorption parameters K_a and P_(app) of Her-HCP SAN in the ileum(P<0.05,P<0.01), whereas the addition of verapamil has no significant effect on the intestinal absorption parameters of Her-HCP SAN, suggesting that Her may be a substrate for multidrug resistance-associated protein 2 and breast cancer resistance proteins but not a substrate of P-glycoprotein.
Nanoparticles/metabolism* ; Polysaccharides/pharmacokinetics* ; Intestinal Absorption/drug effects* ; Animals ; Rats ; Particle Size ; Drugs, Chinese Herbal/pharmacokinetics* ; Male ; Rats, Sprague-Dawley ; Drug Carriers/chemistry* ; Drug Compounding ; Cucurbitaceae/chemistry*

This study aims to explore the mechanism of Huanglian Jiedu Decoction(HJD) in treating acute liver injury(ALI) in the mouse model of sepsis induced by lipopolysaccharide(LPS). Fifty-four male C57BL/6 mice were randomized into six groups: blank group, model group, low-, medium-, and high-dose group HJD, and dexamethasone group. The mouse model of sepsis was established by intraperitoneal injection of LPS after 7 days of gavage with HJD, and dexamethasone(0.2 mL) was injected intraperitoneally 1.5 h after modeling. The murine sepsis score(MSS) was recorded 12 h after modeling. The levels of alanine aminotransferase(ALT) and aspartate aminotransferase(AST) in the liver tissue and tumor necrosis factor-α(TNF-α) and interleukin-6(IL-6) in the serum were measured by ELISA. Hematoxylin-eosin(HE) staining was used to observe the pathological changes of the mouse liver. The content of light chain 3 of microtubule-associated protein 1(LC3) was detected by immunofluorescence, and that of sirtuin 1(SIRT1) was detected by immunohistochemistry. The mRNA levels of adenosine 5'-monophosphate-activated protein kinase(AMPK), LC3, and P62 were detected by RT-PCR. Western blot was employed to determine the protein levels of AMPK, p-AMPK, and SIRT1 in the liver tissue. The results showed that compared with model group, drug interventions decreased the MSS and liver injury indicators, lowered the levels of inflammatory cytokines, improved the liver tissue structure, upregulated the protein levels of of p-AMPK/AMPK and SIRT1 and the mRNA levels of AMPK and LC3, and downregulated the mRNA level of P62. To sum up, HJD can regulate the autophagy level and reduce inflammation to ameliorate acute liver injury in septic mice by activating the AMPK/SIRT1 autophagy pathway.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Sirtuin 1/genetics* ; Male ; Mice ; Sepsis/metabolism* ; Mice, Inbred C57BL ; Autophagy/drug effects* ; AMP-Activated Protein Kinases/genetics* ; Liver/metabolism* ; Humans ; Signal Transduction/drug effects* ; Disease Models, Animal ; Tumor Necrosis Factor-alpha/genetics*