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.

Electroencephalogram (EEG) is a non-invasive, high temporal-resolution technique for monitoring brain activity. However, affected by the volume conduction effect, EEG has a low spatial resolution and is difficult to locate brain neuronal activity precisely. The surface Laplacian (SL) technique obtains the Laplacian EEG (LEEG) by estimating the second-order spatial derivative of the scalp potential. LEEG can reflect the radial current activity under the scalp, with positive values indicating current flow from the brain to the scalp (“source”) and negative values indicating current flow from the scalp to the brain (“sink”). It attenuates signals from volume conduction, effectively improving the spatial resolution of EEG, and is expected to contribute to breakthroughs in neural engineering. This paper provides a systematic overview of the principles and development of SL technology. Currently, there are two implementation paths for SL technology: current source density algorithms (CSD) and concentric ring electrodes (CRE). CSD performs the Laplace transform of the EEG signals acquired by conventional disc electrodes to indirectly estimate the LEEG. It can be mainly classified into local methods, global methods, and realistic Laplacian methods. The global method is the most commonly used approach in CSD, which can achieve more accurate estimation compared with the local method, and it does not require additional imaging equipment compared with the realistic Laplacian method. CRE employs new concentric ring electrodes instead of the traditional disc electrodes, and measures the LEEG directly by differential acquisition of the multi-ring signals. Depending on the structure, it can be divided into bipolar CRE, quasi-bipolar CRE, tripolar CRE, and multi-pole CRE. The tripolar CRE is widely used due to its optimal detection performance. While ensuring the quality of signal acquisition, the complexity of its preamplifier is relatively acceptable. Here, this paper introduces the study of the SL technique in resting rhythms, visual-related potentials, movement-related potentials, and sensorimotor rhythms. These studies demonstrate that SL technology can improve signal quality and enhance signal characteristics, confirming its potential applications in neuroscientific research, disease diagnosis, visual pathway detection, and brain-computer interfaces. CSD is frequently utilized in applications such as neuroscientific research and disease detection, where high-precision estimation of LEEG is required. And CRE tends to be used in brain-computer interfaces, that have stringent requirements for real-time data processing. Finally, this paper summarizes the strengths and weaknesses of SL technology and envisages its future development. SL technology boasts advantages such as reference independence, high spatial resolution, high temporal resolution, enhanced source connectivity analysis, and noise suppression. However, it also has shortcomings that can be further improved. Theoretically, simulation experiments should be conducted to investigate the theoretical characteristics of SL technology. For CSD methods, the algorithm needs to be optimized to improve the precision of LEEG estimation, reduce dependence on the number of channels, and decrease computational complexity and time consumption. For CRE methods, the electrodes need to be designed with appropriate structures and sizes, and the low-noise, high common-mode rejection ratio preamplifier should be developed. We hope that this paper can promote the in-depth research and wide application of SL technology.

Post-stroke depression(PSD),a common stroke complication characterized by depressed mood and diminished interest,severely affects patients'recovery and quality of life.Microglial abnormal activation and polarization play key roles in PSD pathogenesis,closely associated with neuroinflammation and imbalance in neu-rotransmitter metabolism.In contrast,traditional Chinese medicine(TCM)demonstrates unique multi-target and multi-level mechanisms:regulating microglial function,ameliorating post-stroke neuroinflammatory environments,and promoting neuroplasticity,thereby potentially alleviating PSD symptoms.This review summarizes TCM's effects on microglial activation/polarization states and its therapeutic advances in PSD,providing novel perspectives and strategies for clinical management.

Aortic regurgitation and mitral regurgitation are more common in elderly heart valve disease,and both may be present in some patients.Severe aortic regurgitation complicated with severe mitral regurgitation often requires surgical valve replacement,but in patients at high risk of surgery,the risk of perioperative mortality is significantly increased.Therefore,for such patients,minimally invasive interventions can significantly improve long-term patient outcomes while reducing surgical risk.This article report a case of transcatheter aortic valve replacement combined with transcatheter edge-to-edge repair in the treatment of severe aortic regurgitation combined with mitral valve prolapse,in order to explore new treatment ideas for similar cases.

Aim To investigate the effect of N6-methy-ladenosine(m6A)demethylase ALKBH5 on the prolif-eration and migration of cardiac fibroblasts(CFs)in-duced by high glucose.Methods Primary CFs were isolated from neonatal mouse hearts and identified u-sing optical and confocal microscopy.Cell activation was induced using a high-glucose medium(33 mmol·L-1 glucose).An ALKBH5 overexpression model was established by transfecting CFs with an ALKBH5 ex-pression vector in a high-glucose medium.The expres-sion of ALKBH5 in CFs was assessed through immuno-fluorescence staining,Western blot and RT-qPCR.Changes in m6A levels were evaluated using Dot blot a-nalysis.Additionally,Alterations in the expression of proliferating cell nuclear antigen(PCNA)and collagenⅠ,a pivotal fibrosis indicator,were measured using Western blot.The proliferation and migration ability of CFs were assessed through EdU staining and Transwell migration assay,respectively.Results Following treatment with high glucose,the expression of ALKBH5 in CFs notably decreased,while m6A level increased.This was accompanied by a significant increase in the expression of the proliferation marker PCNA and the fi-brosis marker collagen Ⅰ.Additionally,there was a sig-nificant improvement in the ability of proliferation and migration.Overexpression of ALKBH5 resulted in a significant decrease in the expressions of PCNA and collagen Ⅰ,leading to the inhibition of both proliferation and migration in CFs.Conclusion Overexpression of ALKBH5 suppresses the expression of PCNA and colla-gen Ⅰ,consequently reducing the proliferation and mi-gration of CFs,potentially through m6A methylation modification.

Objective To explore the effect of endoscopic surgery via trans-axilloareolar sternocleidomastoid intermuscular approach for unilateral thyroid cancer.Methods A total of 116 patients with unilateral thyroid cancer admitted to our hospital from January 2020 to March 2023 were selected,and all of them underwent unilateral thyroidectomy+isthmus resection+central lymph node dissection under endoscopy.The patients were divided into the observation group and the control group according to random number table method,with 58 cases in each group.Patients in the observation group received the trans-axilloareolar sternocleidomastoid intermuscular approach,and patients in the control group received subclavian approach.The surgical-related indicators,stress indicators[adrenocorticotropic hormone(ACTH),norepinephrine(NE),cortisol(Cor)]before and after surgery,parathyroid hormone(PTH),blood calcium level,postoperative incision aesthetics satisfaction,and occurrence of complications were compared between the two groups.Results There was no statistically significant difference in the operation time,intraoperative blood loss,or postoperative drainage volume of patients between the two groups(P>0.05).The dissection number of lymph nodes in the central region of patients in the observation group was greater than that in the control group(P<0.05).In the two groups,the levels of NE,Cor,and ACTH 1 day and 3 days after surgery were higher than those before surgery(P<0.05),and the levels of NE,Cor and ACTH 1 day after surgery were higher than those 3 days after surgery(P<0.05);the levels of NE,Cor and ACTH 1 day and 3 days after surgery of patients in the observation group were lower than those in the control group(P<0.05).In the two groups,the levels of PTH and serum calcium 1 day and 3 days after surgery were lower than those before surgery(P<0.05),and the levels of PTH and serum calcium 3 days after surgery were lower than those 1 day after surgery(P<0.05),while there were no significant differences in the levels of PTH or serum calcium 1 day and 3 days after surgery between the two groups(P>0.05).The satisfaction of postoperative incision aesthetics in the observation group(100%)was higher than that in the control group(72.41%),with statistically significant difference(P<0.05).No statistically significant difference was found in the incidence of complications between the two groups(P>0.05).Conclusion Endoscopic surgery via trans-axilloareolar sternocleidomastoid intermuscular approach is safe and feasible for unilateral thyroid cancer,which has a mild stress response and inconspicuous incisions,with high satisfaction of incision aesthetics for patients.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective:To explore the potential causal relationships between major depressive disorder(MDD),anxiety disorder(AD)and various highly prevalent cancers from the genetic perspective.Methods:Sum-mary statistics from large-scale genome-wide association studies(GW AS)were analyzed using a bidirectional two-sample Mendelian randomization(MR)approach.The inverse variance weighting method(IVW)was usedas the main analytical approach.The intercept term of MR-Egger regression and the MR-PRESSO method were adopted for the pleiotropy test.Results:The IVW analysis revealed potential causal relationships between MDD and breast cancer[OR(95％CI):1.11(1.01-1.22),P＜0.05],AD and lung cancer[OR(95％CI):1.30(1.02-1.65),P＜0.05],and between colon cancer and MDD[OR(95％CI):1.05(1.00-1.11),P＜0.05].The results of the pleiotropy test showed that the intercept terms of the MR-Egger regression were not statistically significant,indica-ting the absence of pleiotropy.The MR-PRESSO method detected outliers only in the relationship between MDD and breast cancer.The association between MDD and breast cancer remained significant after correction for outliers[OR(95％CI):1.10(1.03-1.17),P＜0.05].Conclusion:The study suggests that MDD may be a risk factor for breast cancer,AD may increase the risk factor for lung cancer,and colon cancer may elevate the risk factor of MDD.Moreover,the possibility of reverse causal relationships has been excluded in all these cases.

Objective To carry out a dynamic simulation analysis on the surgical process of the surgical robot for pedicle screw placement so as to enhance the safety of the procedure.Methods Firstly,the process of pedicle screw placement were analyzed to determine the three typical force conditions during pedicle screw track drilling including no-load condition,bone layer switching condition and spine dynamic displacement condition.Secondly,a virtual protype model of the surgical robot for pedicle screw placement was constructed with the automated dynamic analysis of mechanical systems(ADAMS).Finally,the dynamic characteristics of the surgical robot were simulated and analyzed with considerations on the three typical force conditions.Results The driving torque of the robot joints was sensitive to the load applied to the end of the opener mechanism under a wide range of operating conditions.Conclusion The surgical robot meets the requirements for pedicle screw placment,and a new idea is provided for enhancing the accuracy of pedicle screw placement.[Chinese Medical Equipment Journal,2025,46(8):32-37]