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.

"Sinew prescription correspondence" is the principle of selecting prescriptions for channel sinew diseases. On the basis of the theory of syndrome differentiation and treatment， the pulse manifestation corresponds to the channel sinew syndrome， which can improve the flexibility and standardization of clinical prescriptions. From the perspective of systematic dialectical sphygmology， this paper explains the dialectical relationship between channel sinew theory and pulse body elements， pulse wall elements， pulse elements and blood flow elements， and clarifies the internal relationship between pulse manifestation and prescriptions at the level of channel sinew disease. The prescription is derived from the method， while the method is established with the syndrome， and the prescription is unified by the method. According to the theory of "sinew prescription correspondence"， the treatment ideas of channel sinew diseases were analyzed from the perspective of channel sinew distribution， functional characteristics and structural changes. On this basis， the diagnosis of channel sinew disease and the application of prescriptions are expanded， and the research on the internal treatment and diagnosis mode of "pulse manifestation-channel sinew-zang fu （脏腑）" is prospected， so as to expand the differentiation and treatment methods of channel sinew theory.

Objective: This prospective study evaluated the feasibility of chemical exchange saturation transfer (CEST) MRI for assessing disease activity in thyroid-associated ophthalmopathy (TAO). Materials and Methods: A total of 88 patients with active TAO, 76 with inactive TAO, and 30 healthy controls were enrolled. CEST MRI-derived magnetization transfer ratio (MTR) and MTR asymmetry (MTRasym) at 1 ppm, 2 ppm, and 3.5 ppm were calculated. Clinical data, MTR, and MTRasym values for the extraocular muscles (one representative muscle per eye, yielding two measurements per participant) were compared among the groups. Spearman’s correlation was used to examine associations between imaging parameters and the clinical activity score (CAS) in patients with TAO. Logistic regression analysis was used to identify independent associations between imaging parameters and disease activity in patients with TAO (active vs. inactive). Receiver operating characteristic (ROC) analysis was conducted to evaluate the diagnostic performance for discriminating active from inactive TAO. Results: Patients with active TAO showed lower MTR values (P < 0.001) and higher MTRasym (1 ppm), MTRasym (2 ppm), and MTRasym (3.5 ppm) (all P < 0.001) compared with those with inactive TAO. MTR was negatively correlated with CAS (r = -0.402; P < 0.001), while MTRasym (1 ppm), MTRasym (2 ppm), and MTRasym (3.5 ppm) were positively correlated with CAS (r = 0.369, 0.350, and 0.349, respectively;all P < 0.001). MTR and MTRasym (1 ppm) were independently associated with TAO activity. The areas under the ROC curve (AUCs) for MTR and MTRasym (1 ppm) in discriminating active from inactive TAO were 0.772 and 0.730, respectively. Combining MTR with MTRasym (1 ppm) significantly improved diagnostic performance compared with either parameter alone, achieving an AUC of 0.805 (P = 0.029 and 0.001). Conclusion MTR and MTRasym (1 ppm) were independently associated with TAO activity. Their combination further enhanced diagnostic performance in distinguishing active from inactive TAO, suggesting their potential as quantitative imaging biomarkers to guide treatment in patients with TAO.

ObjectiveThe frequency difference limen (FDL) serves as a fundamental metric utilized for effectively quantifying the precise perceptual capabilities of the central auditory system. However, traditional measurement methods rely heavily on the active behavioral responses of subjects and are consequently highly susceptible to the negative influence of confounding subjective factors. Furthermore, existing research paradigms frequently employ uniform stimulus configurations that overlook critical individual perceptual differences. Based on brain-computer interface (BCI) technology, this comprehensive study aims to establish an objective and quantitative evaluation method for auditory frequency discrimination by systematically analyzing and decoding the specific neural responses elicited at the exact threshold state. MethodsWe designed a personalized rapid serial auditory presentation (RSAP) paradigm customized based on each individual’s precise FDL. A cohort of eleven healthy participants was recruited to evaluate the paradigm using pure-tone sequences at a baseline frequency of 4 000 Hz. This experimental paradigm simulates a realistic auditory perception environment through the continuous presentation of acoustic stimuli, thereby allowing for an in-depth investigation into the specific neural representations evoked by weak frequency deviations at the threshold state. Given that auditory stimulus-evoked response features exhibit complex and differentiated spatiotemporal distribution patterns across multiple frequency domains, this study further deeply integrates the cross-scale feature interaction module with the dynamic spatiotemporal attention allocation strategy, innovatively proposing the Multi-Scale Spatial-Temporal Dual Attention Network (MS-STAMNet). Specifically, the network constructs parallel processing branches with multiple receptive fields and introduces a dynamic adaptive weighting strategy to precisely localize core neural activity signals, further deeply integrating multi-scale information through cross-branch feature information interaction to achieve robust single-trial decoding of weak auditory evoked responses. ResultsThe comprehensive electrophysiological data analysis demonstrated that subtle auditory frequency deviation stimuli presented at the threshold level successfully elicited pronounced N2 and P3 event-related potential features, reflecting pre-attentive mismatch detection and subsequent cognitive evaluation, which were prominently distributed over the frontal, central, and temporal regions of the scalp. In the complex time-frequency domain, the extracted neural response characteristics exhibited distinct, statistically significant event-related synchronization within both the low-frequency δ and θ frequency bands, which was simultaneously accompanied by a widespread, prominent event-related desynchronization within the higher α band. A comparative analysis of model performance demonstrated that MS-STAMNet achieved an average unweighted average recall (UAR) of (69.67±6.12)% and area under the curve (AUC) of 0.761 8±0.07, significantly outperforming the established baseline models such as EEGNet and PLNet. Furthermore, a distinct dissociation phenomenon was verified between neural decoding and behavioral performance through regression analysis (R²=0.016, P=0.709), indicating that this model can effectively capture the implicit features of subtle frequency deviations, even when they fail to trigger explicit conscious responses. Additionally, attention weight visualization analysis further reveals the highly accurate focus of the network on key features concentrated over the bilateral temporal and fronto-parietal regions. ConclusionThis study systematically and comprehensively uncovers the multi-dimensional spatiotemporal evolutionary patterns of complex neural responses processing subtle acoustic variations under long-sequence threshold auditory stimulation. Concurrently, it verifies the efficacy and robustness of the proposed MS-STAMNet architecture in accurately deciphering weak, single-trial electroencephalogram signals amidst complex background noise. Ultimately, these neurophysiological and algorithmic findings lay a solid theoretical and methodological foundation for the objective and quantitative evaluation of individual auditory cognitive capabilities in clinical applications, transcending the fundamental limitations of traditional behavioral paradigms and providing robust technical support for future auditory research and related clinical assessments.

Liver transplantation is a radical treatment for progressive and irreversible end-stage liver disease. However, its clinical application has always been restricted by the core bottleneck of donor liver shortage. Living donor liver transplantation can alleviate the shortage of donor livers to a certain extent, but it requires simultaneous assurance of sufficient residual liver volume in donors to avoid liver insufficiency, as well as an adequate graft-to-recipient weight ratio to prevent small-for-size syndrome, which limits its clinical application. Dual-donor liver transplantation utilizes partial liver tissues from two donors as grafts. While ensuring donor safety, avoiding small-for-size syndrome in recipients, and expanding the donor pool, this technique significantly improves the utilization rate of donor livers and effectively eases the clinical contradiction of donor liver shortage. Based on recent domestic and international clinical practices and the latest diagnosis and treatment guidelines, this article systematically reviews the developmental background, donor and recipient evaluation and selection, surgical procedures and postoperative complications of dual-donor liver transplantation, aiming to provide references for the standardized promotion and clinical optimization of this technique.

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

Objective : To investigate the effects and underlying mechanisms of high mobility group nucleosome-binding domain protein 2(HMGN2) on lung adenocarcinoma cells. Methods : This work first analyzed the association between HMGN2 and lung adenocarcinoma tissues using The Cancer Genome Atlas(TCGA) database. Lung adenocarcinoma tissues and adjacent normal tissues were collected to compare the differential expression levels of HMGN2. The expression of HMGN2 mRNA in lung adenocarcinoma cell lines A549 and NC-H1299 were detected by qRT-PCR and Western blot. HMGN2 expression was knocked down using si-RNA technology, with the control group transfected with an equivalent amount of NC-siRNA, and the si-RNA group transfected with si-HMGN2. Stable transfected cell lines were established based on si-RNA knockdown efficiency. The effects of HMGN2 knockdown on the growth, movement, and spread of lung adenocarcinoma cells were assessed using CCK-8, Transwell assays, scratch assays, colony formation assays, and EdU assays. Transcriptome sequencing analysis revealed pathways related to tumorigenesis associated with HMGN2. The relative expression levels of MAPK pathway proteins after HMGN2 knockdown were detected by Western blot. Results : HMGN2 mRNA expression was significantly elevated in lung cancer tissues and lung adenocarcinoma cell lines(P<0.05). After HMGN2 knockdown, cell proliferation, migration, and invasion were significantly reduced(P<0.05), and the phosphorylation levels of the MAPK signaling pathway markedly decreased(P<0.05). Conclusion HMGN2 enhances the proliferation, migration, and invasion of lung adenocarcinoma cells, and its mechanism may be closely related to the activation of the MAPK signaling pathwayviaphosphorylation.

Objective:To investigate the patterns of mutation evolution in patients with acute myeloid leukemia (AML) during treatment and the possible clinical significances.Methods:A retrospective case series study was conducted. A total of 103 AML patients who were hospitalized at the Affiliated Yuebei People's Hospital of Medical College of Shantou University from November 2019 to August 2021 and underwent high-throughput next-generation sequencing (NGS) technology to detect the mutations of 128 AML-related genes in bone marrow samples were selected. Based on the NGS results, the somatic gene mutations in samples of patients collected at initial diagnosis (73 cases), complete remission (CR) (30 cases), non-remission (NR) (23 cases), and recurrence (12 cases) were analyzed, and the targeted drugs involved in the gene mutations detected in NR and recurrence samples were summarized.Results:The median age [ M ( Q1, Q3)] of onset for 103 patients was 58 (48, 66) years, including 64 males (61%) and 39 females (39%); 86 cases (83%) were primary AML, and 17 cases (17%) were secondary AML; at the initial diagnosis, 51 cases (50%) had normal karyotypes, 34 cases (33%) had abnormalities, and 18 cases (17.5%) were unknown. Compared with the CR samples, the mutation frequencies of FLT3 [29% (21/73) vs. 3% (1/30)], NPM1 [27% (20/73) vs. 3% (1/30)], NRAS [22% (16/73) vs. 3% (1/30)], and IDH2 [14% (10/73) vs. 0 (0/30)] were all higher in the initial diagnosis samples, and the differences were statistically significant (all P < 0.05); compared with the initial diagnosis sample, the median number of gene mutations in each CR sample was lower [4 (2, 5) vs. 7 (5, 9)], and the difference was statistically significant ( P < 0.001). However, there was no statistically significant difference in the median number of gene mutations in each patient between the initial diagnosis samples and the NR samples, the initial diagnosis samples and the recurrence samples, and the NR samples and the recurrence samples (all P > 0.05). Analysis of 14 patients with NGS data at initial diagnosis and CR showed that the same gene mutations could be detected at initial diagnosis and CR, such as DNAH23 (3 cases), USH2A (3 cases), etc; partial gene mutations were detected at initial diagnosis but were not detected at CR, including NRAS (5 cases), FLT3 (3 cases), ANKRD26 (3 cases), NPM1 (3 cases), ETV6 (3 cases), etc; ARID1B (1 case) and DNMT3A (1 case) were negative for mutations at initial diagnosis but positive upon reaching CR. Analysis of 14 patients with NGS data at initial diagnosis and NR showed that most gene mutations persisted at initial diagnosis and NR, such as DNMT3A (5 cases), NRAS (5 cases), KRAS (3 cases), RUNX1 (3 cases), etc; the mutant genes detected at initial diagnosis but not detected at NR included USH2A (2 cases), PCLO (2 cases), ATM (2 cases), FAT1 (2 cases), etc; partial gene mutations were not detected at initial diagnosis but were detected at NR, such as FAT1 (2 cases), TCF3 (2 cases), etc. Analysis of 5 patients with NGS data at CR and recurrence showed that some gene mutations were detected at both CR and recurrence, such as BCORL1 (1 case), ARID2 (1 case), SETD2 (1 case), VEGFC (1 case), etc; FLT1 (1 case) and GNAS (1 case) gene mutations were detected at CR but not detected at recurrence; at recurrence, some gene mutations that were not detected at CR were also detected, such as ANKRD26 (1 case), WT1 (1 case), etc. Among the 23 NR samples and 12 recurrence samples, the targets of drugs approved by US Food and Drug Administration or in clinical trials were detected in 14 (61%) and 5 (42%) samples respectively, including IDH1, IDH2, FLT3, KIT, KRAS, NRAS, SF3B1, U2AF1, and SRSF2. Conclusions:The number of gene mutations in AML patients during CR is significantly less than that at initial diagnosis, some gene mutations disappear when CR is achieved through treatment, but the majority of gene mutations persist during the treatment period, including NR and recurrence, suggesting that monitoring through NGS technology can help understand the evolution of gene mutations during AML treatment and discover the potential therapeutic targets.

Plutonium isotopes(238Pu,239Pu,240Pu and 241Pu)in the environment are important"fingerprint"nuclides in the study of nuclear activity traceability.The content of plutonium isotopes in the environmental metrics is usually very low,and the measurement of these isotopes,especially 238Pu,using mass spectrometry is seriously interfered with by the coexisting 238U.The analysis of several plutonium isotopes in soil usually requires combination of multiple measurement techniques,which leads to a long analysis time and large uncertainty in the isotope ratio.In this work,the hydrous titanium oxide(HTiO)precipitated by the hydrolysis of titanium oxydichloride(TiOCl2)under near-neutral condition was used to preconcentrate plutonium from the soil digestion solution,and the highly efficient decontamination of 238U in the sample was achieved by TK200 resin column chromatography with a decontamination factor of 108.Simulation resuts of density functional theory(DFT)showed that NH3 was considered as a promising reaction gas to eliminate the interference of 238U from 238Pu measurement using mass spectrometry due to the significant discrepancy of the chemical reactivity of U+and Pu+with the reactive gas NH3.Experiments confirmed that by optimizing the flow rates of collision gas(He)and reaction gas(NH3),the interference of 238U could be effectively suppressed,and the decontamination factor of 238U was 104.Combined with chemical separation,the overall decontamination factor of 238U could reach 1012 by using the developed method.By combining chemical separation and tandem quadrupole inductively coupled plasmon-mass spectrometry(ICP-MS/MS)measurement,the simultaneous determination of four ultra-trace plutonium isotopes in soil was realized,and the detection limit of plutonium isotopes was at the femtogram level.Analysis of the international standard reference materials(NIST-SRM-4357 and IAEA-384)showed that the established method could be successfully used for the accurate analysis of ultra-trace four plutonium isotopes(238Pu,239Pu,240Pu and 241Pu)in soil samples.