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.

Objective To explore the influencing factors of postoperative pancreatitis in elderly patients with common bile duct stones undergoing endoscopic retrograde cholangiopancreatography(ERCP).Methods 304 elderly patients with common bile duct stones treated with ERCP in our hospital from February 2021 to June 2023 were selected as the study subjects.They were divided into a group with concurrent pancreatitis(n=22)and a group without concurrent pancreatitis(n=282)based on whether postoperative pancreatitis occurred.And the levels of serum lipase,whole blood PLR,and serum CRP were measured before surgery and 3,6,and 24 hours after surgery,respectively.At the same time,the differences in other relevant clinical data between the two groups of patients were compared.Binary Logistic regression was used to analyze the risk factors of pancreatitis after ERCP.Results The serum lipase levels in the concurrent pancreatitis group at 3,6,and 24 hours after the operation were(1060.48±131.23)U/L,(1137.45±126.34)U/L,and(1152.87±135.05)U/L,respectively.The levels of PLR in whole blood were 192.24±29.26,216.45±30.24,and 243.62±38.22 respectively,all of which were higher than those in the group without concurrent pancreatitis during the same period.There was a statistically significant difference between the two groups(P＜0.05).The serum CRP level in the group with pancreatitis was significantly higher than that in the group without pancreatitis at 6 and 24 h after operation(P＜0.05).Body mass index,Oddi sphincter dysfunction,difficulty in intubation,pancreatic development,ERCP operation time＞60 min,multiple entry of the catheter into the pancreatic duct were associated with postoperative pancreatitis after ERCP in elderly patients(P＜0.05).Multivariate Logistic regression analysis showed that after adjusting for confounding factors such as gender,age,BMI,course of disease,and number of stones,Serum lipase at 3 h after surgery,whole blood PLR at 3 h after surgery,serum CRP level at 6 h after surgery,difficulty in intubation and pancreatic development were independent risk factors for pancreatitis after ERCP in elderly patients(P＜0.05).Conclusion Serum lipase,whole blood PLR levels 3 hours after surgery,and serum CRP levels 6 hours after surgery are independent risk factors for pancreatitis after ERCP in the elderly with common bile duct stones.

Aim Mouse model of myocardial hypertro-phy was established via intraperitoneal injection of iso-proterenol(ISO)in mice.This approach allows for an in-depth investigation into the pharmacological effects and mechanisms of action of emodin,offering novel in-sights and directions for the improvement of myocardial hypertrophy.Methods The mice were randomly di-vided into the following groups:control group(CON),emodin group(EMO),MAPK activator control group(EMO+Ani),model group(ISO),treatment group(ISO+EMO),and activator intervention group(ISO+EMO+Ani).After treatment with emodin and inter-vention with MAPK activator,the heart weight ratio and cardiac size of each group were observed.Hematoxy-lin-eosin(HE)staining was used to observe the patho-logical changes in cardiac tissue,and kits were utilized to measure the levels of GSH,LDH,and MDA in the serum.Western blot was employed to detect the protein expression levels of inflammatory and oxidative factors,as well as p-p38,p-ERK,p38,and ERK in cardiac tis-sue.Results Emodin can significantly inhibit the production of myocardial inflammatory and oxidative factors induced by ISO,thereby effectively alleviating the degree of myocardial hypertrophy and fibrosis.Af-ter the p38/ERK signaling pathway was specifically ac-tivated by farnesol,the improvement effect of emodin on myocardial hypertrophy was weakened.Further comparison revealed that,compared with the myocardi-al hypertrophy pathological model group,the pathologi-cal protein expression levels in the farnesol-treated group showed no significant difference,and were even higher in some indicators.Conclusion Emodin can effectively inhibit the release of inflammatory factors and improve the state of oxidative stress by modulating the p38/ERK signaling pathway,thereby exerting an ameliorative effect on myocardial hypertrophy.

Objective·To explore the relationship between abdominal fat area and the first-phase insulin secretion function of pancreatic β-cells in patients with type 2 diabetes,and to establish predictive models of nomogram.Methods·From October 2020 to February 2024,a total of 120 patients with type 2 diabetes,who were hospitalized in the Department of Endocrinology,Zhongshan Hospital,Fudan University,and underwent the arginine stimulation test,were recruited for the study.Patients were categorized into an insulin secretion function-preserved group(i.e.preserved group)and a depleted group according to the results of the arginine stimulation test.General information and laboratory parameters were collected.Subcutaneous fat area(SFA)and visceral fat area(VFA)were non-invasively measured by abdominal fat detector.The variables were screened by univariate analysis,and multivariate Logistic regression was used to identify the influencing factors,followed by the establishment of predictive models of nomogram.The area under the receiver operating characteristic curve(ROC curve)and concordance index(C-index)were used to evaluate the predictive performance of the models.Results·Seventy-four patients(61.7%)were assigned to the preserved group,and 46 patients(38.3%)to the depleted group.Patients in the depleted group had a longer diabetes duration,lower waist circumference,hip circumference,body mass index(BMI),uric acid,free triiodothyronine(FT3),adipose tissue insulin resistance(Adipo-IR),ankle brachial index(ABI),SFA and VFA,and higher brachial ankle pulse wave velocity(baPWV).Multivariate Logistic regression showed that SFA,VFA,FT3,baPWV,and ABI were independent risk factors for the depleted insulin secretion function.Nomogram models were constructed based on the above risk factors.Among them,the model comprising VFA,FT3,ABI,and baPWV showed the best predictive performance with a C-index of 0.81.Conclusion·SFA and VFA are lower in patients with depleted first-phase insulin secretion function of pancreatic β-cells.The nomogram model,including SFA or VFA,can be used to predict first-phase insulin secretion function of pancreatic β-cells in patients with type 2 diabetes.

Objective To analyze the association between lifestyle and the risk of type 2 diabetes(T2D)among adult residents.Methods The data was sourced from the Shanghai Suburban Adult Cohort and Biobank.A total of 42 096 adult residents who had not developed T2D were recruited from four districts of Shanghai(Songjiang,Jiading,Minhang,and Xuhui)between 2016 and 2019.The follow-up ended on Feb 28,2023.A structured questionnaire was used to collect information on six lifestyle-related items,including smoking,alcohol consumption,BMI,waist circumference(WC),physical activity,and diet.The unhealthy lifestyle scores(UHLS)were calculated by counting the number of all the unhealthy lifestyle items,with a range of 0-6.New-onset T2D events diagnosed by physicians were obtained through the medical information system.Cox proportional hazards regression model and restricted cubic spline model were utilized to evaluate the association between unhealthy lifestyles and the risk of T2D incidence.Results About 28.1%of the participants led 4-6 unhealthy lifestyles.A total of 1 752 new T2D cases were identified during 218 513.4 person-years of follow-up.Analysis of single unhealthy lifestyle showed that abnormal WC(HR=1.5,95%CI:1.4-1.7)and abnormal BMI(HR=1.3,95%CI:1.2-1.5)were associated with an increased risk of T2D.Compared with individuals with a UHLS of 0-1,those with a UHLS of 3 and 4-6 had 30%(95%CI:1.1-1.6)and 50%(95%CI:1.2-1.8)higher risks of T2D,respectively.Each additional unhealthy lifestyle was associated with a 10%increase in T2D incidence risk(HR=1.1,95%CI:1.1-1.2).Conclusion The risk of T2D in adult residents increases with the cumulative number of unhealthy lifestyles.Adult residents with abnormal WC or BMI,or have three or more unhealthy lifestyles accumulated,will increase the risk of new-onset T2D.

AIM To study the chemical constituents from salt-processed Litchi Semen and their antioxidant activities.METHODS The 85％ethanol extract from salt-processed Litchi Semen was isolated and purified by silica gel,Sephadex LH-20,MCI,ODS and semi-preparative HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.DPPH and ABTS+free radical scavenging method were used to evaluate their antioxidant activities.RESULTS Fifteen compounds were isolated and identified as dehydrocostuslactone(1),ananosmoside A(2),funingensin A(3),(2S)-pinocembrin-7-O-(6-O-α-L-rhamnopyranosyl-β-D-glucopyranoside)(4),liquiritienin(5),quercetin(6),rutin(7),isorhamnetin-3-O-β-rutinoside(8),procyanidin A2(9),procyanidin A1(10),ethyl protocatechuate(11),5-hydroxymethylfurfural(12),di(2-ethyl-hexyl)phthalate(13),nicotinamide(14),(10E,15Z)-9,12,13-trihydroxyoctadeca-10,15-dienoic acid(15).Compounds 6-7,9-10 exhibited scavenging activities against DPPH radicals with IC50 values of(12.929±1.232),(14.104±0.946),(10.417±1.736),(6.944±0.030)μmol/L,respectively.Compounds 6-10 exhibited scavenging activities against ABTS+radicals with IC50 values of(21.952±0.577),(25.683±0.625),(22.970±1.336),(20.210±1.435),(18.725±0.324)μmol/L,respectively.CONCLUSION Compounds 1,5,14-15 are isolated from Litchi genus for the first time.Compounds 6-7,9-10 have strong in vitro antioxidant activities.

AIM To investigate the effects of Gan Jiang-Huang Qin-Huang Lian-Ren Shen Decoction(GJHQHLRSD)on the pyroptosis,pathway of colonic epithelial cells in mouse models of ulcerative colitis(UC).METHODS Among the 63 C57BL/6J mice,13 were randomly selected and assigned to the model group,and the others were divided into the control group,the positive Sulfasalazine Enteric-Coated Tablets group(0.6 g/kg),and low,medium,and high dose GJHQHLRSD groups(3.9,7.8,15.6 g/kg),with 10 mice in each group.The UC mouse model was established using DSS,and the corresponding drugs were administered by gavage.The mice had their general condition observed;their disease activity index(DAI)score assessed;their colon length measured;their histopathological damage of the colon analyzed using HE staining;their colonic IL-1β,IL-8,and TNF-α levels measured by ELISA method;their colonic NLRP3,GSDMD,pro-IL-1β,pro-caspase-1,and IL-1βprotein expression detected by Western blot method;and their cell pyroptosis detected by TUNEL and GSDMD fluorescence double staining.RESULTS Compared with the control group,the model group exhibited significant decrease in body weight and a shortened colon length(P＜0.01);increases in DAI score,levels of IL-1β,IL-8,TNF-α,as well as the protein expressions of NLRP3,GSDMD,and active-caspase-1(P＜0.05,P＜0.01);significant increase of colonic GSDMD and TUNEL positivity;indicating increased tissue damage and inflammatory response.Compared with the model group,the groups intervened with GJHQHLRSD showed a significant increase in body weight and colonic elongation(P＜0.05,P＜0.01);decreases in DAI score,levels of IL-1β,IL-8,TNF-α,as well as the protein expressions of NLRP3,GSDMD,and active-caspase-1(P＜0.05,P＜0.01);a gradient decrease in positivity of GSDMD and TUNEL;indicating a significantly reduced colonic pathological damage.CONCLUSION GJHQHLRSD can improve the DSS-induced inflammatory reaction of colonic mucosa in UC mice,and its mechanism mainly involves the NLRP3/caspase-1,thereby the regulation of the cell pyroptosis process.

Objective To propose a liver ultraound image classification model based on bimodal fusion and deep residual network to enhance the diagnosis accuracy of space-occupying lesions(SOLs)of liver.Methods Firstly,a liver ultrasound dataset containing 164 lesions from 100 patients was constructed,including the ultrasound and ultrasonography videos of the patients.Secondly,the parallel residual block was introduced to improve the ResNet-18 network,and the simple attention module and coordinate attention mechanism were used to extract the image features of ultrasound and echography videos,respectively.Finally,a bimodal fusion network was developed with the image features of ultrasound and sonography videos,which was combined with the improved ResNet-18 network to form an ultrasound image classification model.The ultrasound image classification model proposed underwent performance verification by ablation experiment,application evaluation,diagnosis efficacy evaluation,significance evaluation for assisting surgical operation and comparison with the existing classification models in terms of image classification ability.Results The ablation experiment results showed that the proposed model performed the best in classification speed and accuracy when compared with the existing classification models,with a floating-point operation speed of 5.328×109/s,an average accuracy of 0.941 and a calculation speed of 245.266 frames/s.The application evaluation results indicated when compared with the existing classification models the proposed model had the best convergence performance of the loss function curve and the lowest misdiagnosis rate of 7.03%.The diagnosis efficacy evaluation results proved the proposed model gained advantages over other models in diagnostic efficacy,with a sensitivity of 89.38%,a specificity of 94.12%,an accuracy of 90.85%,a positive predictive value of 97.12%and a negative predictive value of 80.00%.The significance evaluation for assisting surgical operation found when compared with the existing classification models the proposed model had the shortest end-to-end delay of 723 ms;laparoscopic hepatectomy assisted with the proposed model had the blood loss reduced by 109.832 mL when compared with the traditional laparoscopic procedure,with the difference being statistically significant(P<0.05).Conclusion The proposed model enhances the diagnosis efficiency and accuracy of ultrasond SOLs of liver,providing support for clinical diagnosis and surgical assistance.[Chinese Medical Equipment Journal,2025,46(10):9-16]

Objective To analyze the association between lifestyle and the risk of type 2 diabetes(T2D)among adult residents.Methods The data was sourced from the Shanghai Suburban Adult Cohort and Biobank.A total of 42 096 adult residents who had not developed T2D were recruited from four districts of Shanghai(Songjiang,Jiading,Minhang,and Xuhui)between 2016 and 2019.The follow-up ended on Feb 28,2023.A structured questionnaire was used to collect information on six lifestyle-related items,including smoking,alcohol consumption,BMI,waist circumference(WC),physical activity,and diet.The unhealthy lifestyle scores(UHLS)were calculated by counting the number of all the unhealthy lifestyle items,with a range of 0-6.New-onset T2D events diagnosed by physicians were obtained through the medical information system.Cox proportional hazards regression model and restricted cubic spline model were utilized to evaluate the association between unhealthy lifestyles and the risk of T2D incidence.Results About 28.1%of the participants led 4-6 unhealthy lifestyles.A total of 1 752 new T2D cases were identified during 218 513.4 person-years of follow-up.Analysis of single unhealthy lifestyle showed that abnormal WC(HR=1.5,95%CI:1.4-1.7)and abnormal BMI(HR=1.3,95%CI:1.2-1.5)were associated with an increased risk of T2D.Compared with individuals with a UHLS of 0-1,those with a UHLS of 3 and 4-6 had 30%(95%CI:1.1-1.6)and 50%(95%CI:1.2-1.8)higher risks of T2D,respectively.Each additional unhealthy lifestyle was associated with a 10%increase in T2D incidence risk(HR=1.1,95%CI:1.1-1.2).Conclusion The risk of T2D in adult residents increases with the cumulative number of unhealthy lifestyles.Adult residents with abnormal WC or BMI,or have three or more unhealthy lifestyles accumulated,will increase the risk of new-onset T2D.