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 investigate the status of electronic cigarette use and its influencing factors among residents aged ≥15 years in Chengdu City in 2021 and 2024, so as to provide the evidence for optimizing electronic cigarette control strategies. Methods: Two rounds of cross-sectional surveys were conducted in 2021 and 2024. Multi-stage cluster random sampling method was used to select permanent residents aged ≥15 years in Chengdu City as survey subjects. The Chinese Adult Tobacco Survey Questionnaire was used to collect information on gender, age, and electronic cigarette use. Complex sampling weighting was used to calculate the rate of electronic cigarette use and the proportion of reasons for electronic cigarette use. A complex sampling multivariable logistic regression model was used to analyze the influencing factors for electronic cigarette use. Results: A total of 7 950 and 6 920 people were surveyed in 2021 and 2024, respectively, including 3 868 and 3 653 males (48.65% and 52.79%), and 4 082 and 3 267 females (51.35% and 47.21%), respectively. The rate of electronic cigarette use in 2024 was lower than in 2021 (2.29% vs. 3.15%, P<0.05). In 2024, the rates of electronic cigarette use were lower in males, rural areas, people aged 15-<45 years, educational level of bachelor' s degree or above, occupation in government/public institutions or occupation in enterprises/commercial/service industries, and current smokers compared with 2021, while the rate of electronic cigarette use was higher in residents aged ≥65 years compared with 2021 (all P<0.05). In 2021 and 2024, the main reasons for electronic cigarette use were smoking cessation and the belief that electronic cigarettes are less harmful. Smoking cessation accounted for 27.78% and 23.28%, and the belief that electronic cigarettes are less harmful accounted for 24.26% and 22.10%, respectively. Complex sampling multivariable logistic regression analysis showed that age (15-<25 years, OR=15.682, 95%CI: 5.660-43.450; 25-<45 years, OR=7.463, 95%CI: 2.987-18.647; 45-<65 years, OR=3.425, 95%CI: 1.562-7.510), educational level (bachelor' s degree or above, OR=2.916, 95%CI: 1.444-5.891), and smoking (current, OR=23.992, 95%CI: 8.182-70.353; former, OR=20.393, 95%CI: 6.150-67.624) were influencing factors for electronic cigarette use in 2021. Gender (male, OR=2.279, 95%CI: 1.074-4.832), age (25-<45 years, OR=2.114, 95%CI: 1.148-3.892), educational level (high school/vocational high school/technical secondary school, OR=2.792, 95%CI: 1.414-5.514; bachelor' s degree or above, OR=3.321, 95%CI: 1.567-7.039), occupation (unemployed, retired, and retired, OR=0.449, 95%CI: 0.226-0.892), and smoking (current, OR=10.547, 95%CI: 5.563-19.994; former, OR=8.998, 95%CI: 3.833-21.125) were influencing factors for electronic cigarette use in 2024. Conclusions Compared with 2021, the rate of electronic cigarette use among residents in Chengdu City decreased in 2024. Young people, males, bachelor' s degree or above, and current smokers are the key populations for electronic cigarette control. The cognitive bias held by residents that electronic cigarette can aid in smoking cessation and pose minimal harm needs to be corrected.

As global greenhouse gases continue rising, the urgency of more ambitious action is clearer than ever before. China is the world's biggest emitter of greenhouse gases and one of the countries affected most by climate change. The evidence about the impacts of climate change on the environment and human health may encourage China to take more decisive action to mitigate greenhouse gas emissions and adapt to climate impacts. This article aimed to review the evidence of environmental damages and health risks posed by climate change and to provide a new science-based perspective for the delivery of sustainable development goals. Over recent decades, China has experienced a strong warming pattern with a growing frequency of extreme weather events, and the impacts of climate change on China's environment and human health have been consistently observed, with increasing O ₃ air pollution, decreases in water resources and availability, land degradation, and increased risks for both communicable and non-communicable diseases. Therefore, China's climate policy should target the key factors driving climate change and scale up strategic measures to curb carbon emissions and adapt to inevitable increasing climate impacts. It provides new insights for not only China but also other countries, particularly developing and emerging economies, to ensure climate and environmental sustainability whilst pursuing economic growth.
Climate Change ; China ; Humans ; Greenhouse Gases ; Air Pollution ; Sustainable Development ; Environment

BACKGROUND: The clinical impact of post-percutaneous coronary intervention (PCI) quantitative flow ratio (QFR) in patients treated with PCI for chronic total occlusion (CTO) was still undetermined. METHODS: All CTO vessels treated with successful anatomical PCI in patients from PANDA III trial were retrospectively measured for post-PCI QFR. The primary outcome was 2-year vessel-oriented composite endpoints (VOCEs, composite of target vessel-related cardiac death, target vessel-related myocardial infarction, and ischemia-driven target vessel revascularization). Receiver operator characteristic curve analysis was conducted to identify optimal cutoff value of post-PCI QFR for predicting the 2-year VOCEs, and all vessels were stratified by this optimal cutoff value. Cox proportional hazards models were employed to calculate the hazard ratio (HR) with 95% CI. RESULTS: Among 428 CTO vessels treated with PCI, 353 vessels (82.5%) were analyzable for post-PCI QFR. 31 VOCEs (8.7%) occurred at 2 years. Mean value of post-PCI QFR was 0.92 ± 0.13. Receiver operator characteristic curve analysis shown the optimal cutoff value of post-PCI QFR for predicting 2-year VOCEs was 0.91. The incidence of 2-year VOCEs in the vessel with post-PCI QFR < 0.91 (n = 91) was significantly higher compared with the vessels with post-PCI QFR ≥ 0.91 (n = 262) (22.0% vs. 4.2%, HR = 4.98, 95% CI: 2.32-10.70). CONCLUSIONS Higher post-PCI QFR values were associated with improved prognosis in the PCI practice for coronary CTO. Achieving functionally optimal PCI results (post-PCI QFR value ≥ 0.91) tends to get better prognosis for patients with CTO lesions.

The intelligent development of the medical field is burgeoning,and smart healthcare has become a crucial driver for enhancing medical service efficiency and improving patient experience.However,the specific pathways through which smart healthcare improves patient experience have not been fully explained.To address this gap,this study utilizes micro-level individual data collected by the Beijing Hospitals Authority in 2023 from patients in municipal hospitals,employing the Technology Acceptance Model(TAM)to investigate the impact mechanisms of smart service construction on patient experience.The results indicate that smart services significantly improve patient experience by enhancing perceived ease of use,with this effect being particularly prominent during the treatment stage.Additionally,smart services demonstrate potential advantages in alleviating the"digital divide,"with a more pronounced optimization effect on the healthcare experience of elderly populations.Highly educated groups exhibit greater satisfaction and perceived benefits from smart services.

An assay was established for detection of toxigenic Clostridioides difficile by combining microfluidic chip analysis with immunochromatography,and its performance was evaluated and compared with those of the Xpert C.difficile/Epi and VIDAS CD AB tests.Primer pairs were designed according to the tcdB and tpi genes in C.difficile.The specificity,limit of detection,reproducibility,and stability were evaluated.A total of 215 stool samples from patients with diarrhea were collected and tested in parallel with the Xpert C.difficile/Epi,VIDAS CDAB,and our assay.C.difficile was isolated from samples,and the tcdB gene was identified when discrepant results were obtained from the three above assays.Our assay showed no cross-reaction with other diarrhea-associated pathogens.Its reproducibility was 100％in testing of two standard plasmids containing tcdB and tpi genes at two concentrations(105 and 102 copies/μL).Two standard plasmids were detected after the PCR and immunochromatography reagents had been stored for 3,6,9,and 12 months,and all the results were posi-tive.The limit of detection was 10 copies/μL for toxigenic C.difficile.Testing of 33 samples positive for C.difficile with our assay(33/215,15.3％)yielded findings statistically coherent with those of the Xpert C.difficile/Epi test(kappa value=0.965).The sensitivity,specificity,positive predictive value,and negative predictive value of our assay,with respect to Xpert C.difficile/Epi as the standard,were 94.3％,100.0％,100.0％,and 98.9％;these values were significantly higher than those of VIDAS CDAB(60.0％,98.9％,91.3％,and 92.7％)(Kappa=0.714,OR=157.50,95％CI:62.03-847.28,P=0.013).In conclusion,our newly developed assay is specific,stable,and reproducible,and may be used for rapid and accu-rate detection of toxigenic C.difficile.The assay could be used for C.difficile infection screening in outpatient and emergen-cy,community medical service center,and epidemiological settings.

Objective To explore the relationship between the degree of compression and shape grading of the cerebral cistern ambiens in hypertensive cerebral hemorrhage(HCH)patients after neural endoscopic intracranial hematoma evacuation(NEIHE)and prognosis.Methods 246 HCH patients who underwent NEIHE surgery from January 2020 to June 2023 were selected as the research subjects.According to the postoperative 6 month Glasgow outcome score(GOS),the patients were divided into good prognosis group(n=158)and poor prognosis group(n=88).Hierarchical regression model was used to analyze the relationship between clinical pathological features and the degree of compression and shape grading of the cerebral cistern ambiens.Multivariate logistic regression model was used to analyze the independent risk factors affecting the poor prognosis of patients with HCH after NEIHE,and a prediction model was constructed.Receiver operating characteristic curve(ROC curve)was drawn with poor prognosis as the outcome variable.Area under the curve(AUC),integrated discrimination improvement(IDI)and net reclassification improvement(NRI)of different prediction models were compared.Hosmer-Lemeshow was used to test the goodness of fit.Generalized additive model(GAM)was used to analyze the relationship between GOS and related factors.Results Compared with the good prognosis group,the poor prognosis group had more preoperative blood loss,lower preoperative Glasgow coma score(GCS),and higher proportion of patients with midline deviation,hypertension history ≥10 years,hemorrhage breaking into the brain ventricle,and operation time in the late stage,the differences were statistically significant(P＜0.05).Compared with the good prognosis group,the proportions of patients with ipsilateral and contralateral cerebral cistern ambiens compression of 3 to 4 points and the morphological classification of cerebral cistern ambiens of grade V in the poor prognosis group were higher,and the differences were statistically significant(P＜0.05).The location of bleeding,midline deviation,and intracranial pressure all had an impact on the degree of compression and morphological grading of the cerebral cistern ambiens,and the differences were statistically significant(P＜0.05).Multivariate Logistic regression analysis(model 2:including the degree of compression and shape grading of the cerebral cistern ambiens)showed that midline deviation,history of hypertension ≥10 years,preoperative bleeding volume＞37 mL,bleeding into the brain ventricles,preoperative GCS＜7 points,late surgical timing,degree of compression of the cerebral cistern ambiens(3 to 4 points on the same side of hematoma,3 to 4 points on the opposite side of hematoma),and grade V morphology were all risk factors influencing the poor prognosis of patients with HCH after NEIHE(P＜0.05).After incorporating the degree of compression and morphological grading of the cerebral cistern ambiens into model 1(excluding the degree of compression and shape grading of the cerebral cistern ambiens),the AUC increased to 0.812(95％CI:0.763～0.872),and both the IDI(0.081,95％CI:0.049～0.095)and NRI(0.611,95％CI:0.510～0.674)of the model improved,with statistically significant differences(P＜0.05).Compared with model 1,model 2 showed an increase in AUC(0.826,95％CI:0.771～0.863),IDI(0.085,95％CI:0.052～0.110),and NRI(0.628,95％CI:0.510～0.709),with statistically significant differences(P＜0.05).The Hosmer-Lemeshow test showed that model 2(P=0.878)had a better fit for predicting poor prognosis than model 1(P=0.691).GAM analysis showed that the higher the degree of compression and morphological grading of the cerebral cistern ambiens,the lower the GOS,and the difference was statistically significant(P＜0.05).ROC curve analysis showed that the combined application of degree of compression and morphological grading of the cerebral cistern ambiens had a high predictive value for poor prognosis,with AUC of 0.935(95％CI:0.890～0.971),sensitivity of 70.26％,and specificity of 93.84％.Conclusion The degree of compression and shape changes of the cerebral cistern ambiens in HCH patients after NEIHE are closely related to prognosis,and the combined application has certain predictive value for poor prognosis.The location of bleeding,midline deviation,intracranial pressure,and other factors significantly affect the compression degree and shape change of the cerebral cistern ambiens.

Objective To comprehensively analyze the clinical characteristics and risk factors of children with refractory mycoplasma pneumonia(RMPP),precisely identify the joint predictors in these children,and construct a prediction model.This aims to offer a scientific foundation for the early identification of RMPP and the formulation of accurate treatment and medication strategies.Methods A retrospective analysis was performed on the clinical data of 282 children diagnosed with mycoplasma pneumoniae pneumonia(MPP)who were admitted to the Pediatric Department of the Seventh Medical Center of the Chinese People's Liberation Army General Hospital between August 1,2023,and February 29,2024.Among these children,119 with RMPP were classified into the RMPP group,while the remaining 163 with general MPP(GMPP)were assigned to the GMPP group.The clinical data of both groups,encompassing age,gender,duration of fever,symptoms,laboratory test indices,chest imaging data,complications,etc.,were compared.A logistic probability model(LogP model)for joint application was constructed.The discriminatory ability of the model was evaluated using the area under the receiver operating characteristic(ROC)curve,and the calibration of the model was assessed by means of a calibration curve.Results In comparison with the GMPP group,children in the RMPP group exhibited a significantly longer duration of fever(P=0.002).Moreover,they had a higher incidence of complications,including myocardial damage and coagulation dysfunction(P<0.05).Regarding inflammatory markers,the levels of C-reactive protein(CRP),procalcitonin(PCT),and lactate dehydrogenase(LDH)were notably elevated in the RMPP group(P<0.05),whereas the level of albumin(Alb)was lower(P=0.001).In the RMPP group,the levels of interleukin-2(IL-2),interleukin-5(IL-5),interleukin-8(IL-8),interleukin-1β(IL-1β),and D-Dimer were increased,while the levels of interleukin-6(IL-6)and interleukin-17(IL-17)were decreased(P<0.05).Chest computed tomography(CT)scans revealed a higher proportion of lung consolidation,pleural effusion,and atelectasis in the RMPP group(P<0.05).Multivariate logistic regression analysis demonstrated that CRP,total bilirubin(T-BIL),LDH,IL-17,and prothrombin time(PT)were independent risk factors for RMPP(P<0.05).The receiver operating characteristic(ROC)predictive model established based on these factors had an area under the curve(AUC)of 0.787(95%confidence interval[CI]:0.693～0.880),with a cutoff value of 0.421,a sensitivity of 0.786,and a specificity of 0.660.The calibration curve indicated that the predicted probability matched well with the reference probability,and there was no statistical difference in the results of the Hosmer-Lemeshow test(P>0.05).Conclusions The clinical features of children with RMPP are predominantly characterized by prolonged fever,moderate lung lesions,other organ injuries,and high inflammatory markers.CRP,T-BIL,LDH,IL-17,and PT can act as independent risk factors for RMPP.

Objective To explore value of peritumoral radiomics models for predicting lymphovascular invasion(LVI)of gastric adenocarcinoma based on portal-venous phase enhanced CT images.Methods Totally 351 patients with gastric adenocarcinoma were collected and randomly divided into training set(n=246)and test set(n=105)at a ratio of 7∶3.ROI of tumors were manually delineated on portal-venous phase enhanced CT images,then radiomics features of tumoral areas and peritumoral areas(1,3 and 5 mm expanded from lesions)were extracted,respectively.Clinical-CT,tumoral and peritumoral(1 mm,3 mm,5 mm)radiomics and comprehensive model nomograms were established,and their predictive performances for LVI were compared.Calibration curve was used to evaluate the consistency between the predicted and actual LVI of gastric adenocarcinoma,while decision curve analysis(DCA)was used to assess the net clinical benefit of each model.Results The area under the curve of clinical-CT,tumoral,peritumoral(1 mm,3 mm,5 mm)radiomics models and the comprehensive model for predicting LVI in training set was 0.741,0.732,0.713,0.728,0.708 and 0.755,respectively,which in test set was 0.748,0.725,0.759,0.724,0.704 and 0.764,respectively.The comprehensive model demonstrated the highest prediction efficiency,also good calibration and clinical practicability.Conclusion Portal-venous phase CT peritumoral radiomics models could be used to predict LVI of gastric adenocarcinoma.Combining with CT features,tumoral and optimal peritumoral radiomics features could further improve predictive efficiency.