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 distribution of IgM anti-A/B titers among group O whole blood donors in Jiangsu, establish a low-titer threshold, and analyze the demographic characteristics of low-titer donors, so as to provide data for recruiting low-titer group O whole blood (LTOWB) donors. Methods: Plasma samples from 1 009 group O whole blood donors were tested for IgM anti-A and anti-B titers using the microplate technique. The distribution of antibody titers was analyzed to establish a low-titer threshold. The distribution trends of titers across different demographic groups were also analyzed. Results: The peak titer for anti-A, anti-B were 64 (31.5%), 4 (23.8%), respectively, The proportion of donors with both anti-A and anti-B titers below 64 was 97.3% (982/1 009). The mean anti-A titer was higher than anti-B titer. Anti-A titers were higher in female donors than in male donors (P<0.05). The anti-A titers differed significantly among different age groups (P<0.05). However, no significant difference in titers was observed based on the number of donations (P>0.05). Conclusion: A titer of 64 can be used as the reference threshold of LTOWB in Jiangsu. Male donors of appropriate age are more suitable than female donors for establishing an emergency panel of LTOWB mobile donors.

This study aimed to explore the therapeutic mechanisms of Colquhounia Root Tablets(CRT) in treating diabetic kidney disease(DKD) by integrating biomolecular network mining with animal model verification. By analyzing clinical transcriptomics data, an interaction network was constructed between candidate targets of CRT and DKD-related genes. Based on the topological eigenvalues of network nodes, 101 core network targets of CRT against DKD were identified. These targets were found to be closely related to multiple pathways associated with type 2 diabetes, immune response, and metabolic reprogramming. Given that immune-inflammatory imbalance driven by metabolic reprogramming is one of the key pathogenic mechanisms of DKD, and that many core network targets of CRT are involved in this pathological process, receptor for advanced glycation end products(RAGE)-reactive oxygen species(ROS)-phosphatidylinositol 3-kinase(PI3K)-protein kinase B(AKT)-nuclear factor-κB(NF-κB)-NOD-like receptor family pyrin domain containing 3(NLRP3) signaling axis was selected as a candidate target for in-depth research. Further, a rat model of DKD induced by a high-sugar, high-fat diet and streptozotocin was established to evaluate the pharmacological effects of CRT and verify the expression of related targets. The experimental results showed that CRT could effectively correct metabolic disturbances in DKD, restore immune-inflammatory balance, and improve renal function and its pathological changes by inhibiting the activation of the RAGE-ROS-PI3K-AKT-NF-κB-NLRP3 signaling axis. In conclusion, this study reveals that CRT alleviates the progression of DKD through dual regulation of metabolic reprogramming and immune-inflammatory responses, providing strong experimental evidence for its clinical application in DKD.
Animals ; Diabetic Nephropathies/metabolism* ; Receptor for Advanced Glycation End Products/genetics* ; NF-kappa B/genetics* ; Signal Transduction/drug effects* ; Rats ; NLR Family, Pyrin Domain-Containing 3 Protein/genetics* ; Proto-Oncogene Proteins c-akt/genetics* ; Drugs, Chinese Herbal/administration & dosage* ; Male ; Phosphatidylinositol 3-Kinases/genetics* ; Reactive Oxygen Species/metabolism* ; Humans ; Plant Roots/chemistry* ; Rats, Sprague-Dawley ; Tablets/administration & dosage*

High-performance liquid chromatography(HPLC) was used to determine the content of three major components in Citri Reticulatae Semen(CRS), including limonin, nomilin, and obacunone. The chromaticity of the CRS sample during salt processing and stir-frying was measured using a color difference meter. Next, the relationship between the color and content of the salt-processed CRS sample was investigated through correlation analysis. By integrating the oil bath technique for processing simulation with HPLC, the changes in the relative content of nomilin and its transformation products were analyzed, with its structural transformation pattern during processing identified. Additionally, RAW264.7 cells were induced with lipopolysaccharides(LPSs) to establish an inflammatory model, and the anti-inflammatory activity of nomilin and its transformation product, namely obacunone was evaluated. The results indicated that as processing progressed, E~*ab and L~* values showed a downward trend; a~* values exhibited a slow increase over a certain period, followed by no significant changes, and b~* values remained stable with no significant changes over a certain period and then started to decrease. The limonin content remained barely unchanged; the nomilin content decreased, and the obacunone increased significantly. The changing trends in content and color parameters during salt-processing and stir-frying were basically consistent. The content of nomilin and obacunone was significantly correlated with the colorimetric values(L~*, a~*, b~*, and E~*ab), while limonin content showed no significant correlation with these values. By analyzing HPLC patterns of nomylin at different heating temperatures and time, it was found that under conditions of 200-250 ℃ for heating of 5-60 min, the content of nomilin significantly decreased, while the obacunone content increased pronouncedly. The in vitro anti-inflammatory activity results indicated that compared to the model group, the group with a high concentration of nomilin and the groups with varying concentrations of obacunone showed significantly reduced release of nitric oxide(NO)(P<0.01). When both were at the same concentration, obacunone showed better performance in inhibiting NO release. In this study, the obvious correlation between the color and content of major components during the processing of CRS samples was identified, and the dynamic patterns of quality change in CRS samples during processing were revealed. Additionally, the study revealed and confirmed the transformation of nomilin into obacunone during processing, with the in vitro anti-inflammatory activity of obacunone significantly greater than that of nomilin. These findings provided a scientific basis for CRS processing optimization, tablet quality control, and its clinical application.
Mice ; Animals ; Drugs, Chinese Herbal/pharmacology* ; RAW 264.7 Cells ; Limonins/chemistry* ; Chromatography, High Pressure Liquid ; Citrus/chemistry* ; Color ; Benzoxepins/chemistry* ; Anti-Inflammatory Agents/chemistry*

Objective To mine and analyze the routine blood test data of children with allergic rhinitis (AR), identify routine blood parameters related to childhood allergic rhinitis, establish an effective diagnostic model, and evaluate the performance of the model. Methods This study was a retrospective study of clinical cases. The experimental group comprised a total of 1110 children diagnosed with AR at the First Affiliated Hospital of Air Force Medical University during the period from December 12, 2020 to December 12, 2021, while the control group included 1109 children without a history of allergic rhinitis or other allergic diseases who underwent routine physical examinations during the same period. Information such as age, sex and routine blood test results was collected for all subjects. The levels of routine blood test indicators were compared between AR children and healthy children using comprehensive intelligent baseline analysis, with indicators of P≥0.05 excluded; variables were screened by Lasso regression. Binary Logistic regression was used to further evaluate the influence of multiple routine blood indexes on the results. Five kinds of machine model algorithms were used, namely extreme value gradient lift (XGBoost), logistic regression (LR), gradient lift decision tree (LGBMC), Random forest (RF) and adaptive lift algorithm (AdaBoost), to establish the diagnostic models. The receiver operating characteristic (ROC) curve was used to screen the optimal model. The best LightGBM algorithm was used to build an online patient risk assessment tool for clinical application. Results Statistically significant differences were observed between the AR group and the control group in the following routine blood test indicators: mean cellular hemoglobin concentration (MCHC), hemoglobin (HGB), absolute value of basophils (BASO), absolute value of eosinophils (EOS), large platelet ratio (P-LCR), mean platelet volume (MPV), platelet distribution width (PDW), platelet count (PLT), absolute values of leukocyte neutrophil (W-LCC), leukocyte monocyte (W-MCC), leukocyte lymphocyte (W-SCC), and age. Lasso regression identified these variables as important predictors, and binary Logistic regression further analyzed the significant influence of these variables on the results. The optimal machine learning algorithm LightGBM was used to establish a multi-index joint detection model. The model showed robust prediction performance in the training set, with AUC values of 0.8512 and 0.8103 in the internal validation set. Conclusion The identified routine blood parameters can be used as potential biomarkers for early diagnosis and risk assessment of AR, which can improve the accuracy and efficiency of diagnosis. The established model provides scientific basis for more accurate diagnostic tools and personalized prevention strategies. Future studies should prospectively validate these findings and explore their applicability in other related diseases.
Humans ; Male ; Female ; Rhinitis, Allergic/blood* ; Child ; Biomarkers/blood* ; Retrospective Studies ; Early Diagnosis ; Child, Preschool ; ROC Curve ; Logistic Models ; Hematologic Tests ; Algorithms ; Adolescent ; Machine Learning

Recent studies have shown that shorter periods of ejaculatory abstinence may enhance certain sperm parameters, but the molecular mechanisms underlying these improvements are still unclear. This study explored whether reduced abstinence periods could improve semen quality, particularly for use in assisted reproductive technologies (ART). We analyzed semen samples from men with normal sperm counts ( n = 101) and those with low sperm motility or concentration ( n = 53) after 3-7 days of abstinence and then after 1-3 h of abstinence, obtained from the Reproductive & Genetic Hospital of CITIC-Xiangya (Changsha, China). Physiological and biochemical sperm parameters were evaluated, and the dynamics of transfer RNA (tRNA)-derived fragments (tRFs) were analyzed using deep RNA sequencing in five consecutive samples from men with normal sperm counts. Our results revealed significant improvement in sperm motility and a decrease in the DNA fragmentation index after the 1- to 3-h abstinence period. Additionally, we identified 245 differentially expressed tRFs, and the mitogen-activated protein kinase (MAPK) signaling pathway was the most enriched. Further investigations showed significant changes in tRF-Lys-TTT and its target gene mitogen-activated protein kinase kinase 2 ( MAP2K2 ), which indicates a role of tRFs in improving sperm function. These findings provide new insights into how shorter abstinence periods influence sperm quality and suggest that tRFs may serve as biomarkers for male fertility. This research highlights the potential for optimizing ART protocols and improving reproductive outcomes through molecular approaches that target sperm function.
Male ; Humans ; Spermatozoa/metabolism* ; RNA, Transfer/genetics* ; Sperm Motility/genetics* ; Adult ; Semen Analysis ; Sexual Abstinence/physiology* ; Sperm Count ; DNA Fragmentation

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.

Cemental tear is a rare and indetectable condition unless obvious clinical signs present with the involvement of surrounding periodontal and periapical tissues. Due to its clinical manifestations similar to common dental issues, such as vertical root fracture, primary endodontic diseases, and periodontal diseases, as well as the low awareness of cemental tear for clinicians, misdiagnosis often occurs. The critical principle for cemental tear treatment is to remove torn fragments, and overlooking fragments leads to futile therapy, which could deteriorate the conditions of the affected teeth. Therefore, accurate diagnosis and subsequent appropriate interventions are vital for managing cemental tear. Novel diagnostic tools, including cone-beam computed tomography (CBCT), microscopes, and enamel matrix derivatives, have improved early detection and management, enhancing tooth retention. The implementation of standardized diagnostic criteria and treatment protocols, combined with improved clinical awareness among dental professionals, serves to mitigate risks of diagnostic errors and suboptimal therapeutic interventions. This expert consensus reviewed the epidemiology, pathogenesis, potential predisposing factors, clinical manifestations, diagnosis, differential diagnosis, treatment, and prognosis of cemental tear, aiming to provide a clinical guideline and facilitate clinicians to have a better understanding of cemental tear.
Humans ; Dental Cementum/injuries* ; Consensus ; Diagnosis, Differential ; Cone-Beam Computed Tomography ; Tooth Fractures/therapy*

A method for simultaneous determination of 21 kinds of Aconitum alkaloids(ATS)in biological specimens and infused liquor using ultra-performance liquid chromatography-tandem mass spectrometry(UPLC-MS/MS)was developed.The biological samples were pretreated with methanol-acetonitrile(1∶2,V/V)for protein precipitation,while infused liquors were diluted 100-fold with acetonitrile,followed by centrifugation,and filtration by a 0.22-μm membrane.Chromatographic separation was carried out on an EC-C18 column using gradient elution with the mixture of 10 mmol/L ammonium acetate and 0.2%formic acid as mobile phase A and acetonitrile as mobile phase B.With this method,all the analytes were separated within 9.5 min.The samples were detected in positive ESI mode with dynamic multiple reaction monitoring(MRM)and quantified via external standard calibration.The results showed that the concentrations of the analytes in the range of 2-1000 ng/mL had excellent linearity(R2>0.9992)with the peak area.The developed method was successfully used for detection of 21 kinds of aconitum alkaloids,with limits of detection of 0.5-2 ng/mL,quantification limits of 2-6 ng/mL,intra/inter-day precision≤6.0%,spiked recoveries of 89.4%-100.9%,extraction recoveries of 74.2%-104.4%,and matrix effects ranging from-11.1%to 9.2%in blood/urine.The method was applied to detection of 12 samples from 4 fatal aconite poisoning cases,and all 21 kinds of ATS with total alkaloid concentrations of 0.04-4.18 μg/mL in blood and 154.96-422.83 μg/mL in medicinal liquors were detected.Tissue distribution revealed that the order of concentrations from highest to lowest is as follows:urine(157.22 μg/mL)>gastric contents(51.37 μg/mL)>kidney(21.6 μg/g)>whole blood(4.18 μg/mL)>liver(0.03 μg/g).This method showed many advantages such as simple pretreatment,low detection limits,accurate quantification,broad analyte coverage,and superior anti-interference capability in complex matrices,proving ideal for forensic and toxicological analysis of aconitum alkaloids.