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 understand mosquito density, species composition, and seasonal variations around the Beijing Capital International Airport(BCIA)and provide scientific evidence for mosquito-borne disease prevention and control. Methods Meteorological data were collected from 2016 to 2022, and mosquito density was monitored at seven surveillance sites around the BCIA from May to October each year using CO2-baited mosquito traps to analyze the relationship between mosquito density and meteorological factors. Results In total,68 518 female mosquitoes were captured, with a mosquito density of 10.20 per light · hour. The dominant species was Culex pipiens pallens(73.90%), followed by Aedes albopictus(9.71%)and Ae. vexans(9.29%);the mosquito density was highest in 2016(14.8 per light·hour)and lowest in 2022(4.46 per light·hour). Significant statistical differences were observed in mosquito density among different species(F=18.118, P<0.05). The density of Cx. pipiens pallens and other mosquito species showed a mutually exclusive trend; the peak of mosquito density varied based on years and habitats, with significant statistical differences in mosquito density among different habitats(F=8.504, P<0.05). The highest mosquito density was observed near the Wenyu River(21.50 per light·hour), whereas the lowest was recorded at the BCIA construction site(2.44 per light· hour). The monthly average temperature(r=0.595), monthly average highest temperature(r=0.575), and monthly average lowest temperature(r=0.624)showed moderate positive correlations, whereas the monthly average air pressure(r=-0.484)showed a moderate negative correlation. The monthly average minimum temperature was included in the regression model(F=25.575, P<0.000), and the equation Y=1.029X4-8.181 was used. The monthly average air pressure 2 months prior(b=-2.418, β=-1.619, P<0.05)and the monthly average relative humidity(b=-0.739, β=-1.201, P<0.05)significantly negatively predicted the mosquito density. Notably, the regression equation used was y=2526.170+(-2.418)X9+(-0.739)X13. The exposure-response analysis revealed that the density of mosquitoes was not linearly related to the average monthly air pressure, rainfall, and duration of sunshine. Conclusions The dominant mosquito species around the BCIA was Cx. pipiens pallens, Ae. albopictus, and Ae. vexans. During the control of Cx. pipiens pallens, the impact on other mosquito species must also be considered. Environmental management, breeding sites, and scientific use of pesticides should be prioritized based on the activity periods of mosquitoes. Further studies on mosquitoes and meteorological factors should be conducted to provide references and novel avenues for mosquito control.

Owing to its inherent advantages—such as being non-destructive, rapid, highly molecule-specific, and minimally interfered with by moisture—Raman spectroscopy has been widely adopted in the fields of skin barrier function assessment, monitoring the transdermal penetration of active cosmetic ingredients, and the identification and quality control of cosmetic products. Despite these strengths, the practical application of this technique faces a significant bottleneck: the strong fluorescence background generated by endogenous skin components and exogenous cosmetic additives. Endogenous skin substances, such as structural proteins (e.g., collagen and elastin), metabolic coenzymes (e.g., nicotinamide adenine dinucleotide), and pigments (e.g., melanin), together with exogenous cosmetic constituents like organic colorants, chemical sunscreens, and fragrances, often possess strong absorption and emission characteristics. When excited by lasers, these components produce a fluorescence background that can be 10⁶ to 10⁸ times stronger than the Raman scattering signals, effectively masking the inherently weak vibrational fingerprint information. In recent years, driven by the rapid development of optoelectronic hardware and artificial intelligence algorithms, fluorescence suppression strategies have evolved from isolated, single-method approaches into comprehensive, multi-level synergistic systems. These systems are categorized into three distinct tiers: sample preparation, signal acquisition, and data processing. At the sample preparation level, techniques such as photobleaching and surface-enhanced Raman spectroscopy (SERS) are employed to eliminate or bypass the generation of fluorescence at the source. At the signal acquisition level, instrumental improvements—including the use of long-wavelength near-infrared excitation (typically 785 nm or 1 064 nm), confocal spatial filtering, and shifted excitation Raman difference spectroscopy (SERDS)— are utilized to physically isolate Raman signals from the fluorescence background. Furthermore, at the data processing level, numerical baseline correction methods such as polynomial fitting, penalized least squares (e.g., airPLS, arPLS), wavelet transform, and derivative algorithms are increasingly integrated into the analytical pipeline to extract Raman spectral features from mixed signals without increasing hardware costs or acquisition time. This review provides a systematic categorization and critical evaluation of these fluorescence suppression methods, detailing their underlying principles, technical advantages, and inherent limitations in diverse experimental setups. By focusing on critical application scenarios—including skin barrier assessment, percutaneous absorption monitoring, the routine quality control of cosmetics, and the emerging field of portable on-site detection—this paper explores the current state of technique selection and optimization. Finally, the article discusses future development trends, emphasizing the necessity of constructing adaptive, tiered suppression strategies, developing intelligent and automated data processing algorithms, and promoting the integration of portable, multi-modal diagnostic devices. The objective of this review is to provide a comprehensive technical reference to facilitate the transition of Raman spectroscopy from a specialized laboratory tool into a routine, robust analytical platform for advancements in skin science and cosmetic research.

In recent years, with the improvement of people's awareness of physical examination and the more accurate detection equipment, the detection rate of pulmonary nodules is getting higher and higher. Surgical resection is the first choice for the treatment of malignant pulmonary nodules, but multiple pulmonary nodules, nodules in complex areas and those with surgical contraindications are not suitable for surgery. As an effective, less invasive and low-cost treatment, ablation has developed rapidly in the treatment of multiple pulmonary nodules. This article introduces the progress of several common ablation techniques (radiofrequency ablation, microwave ablation, cryoablation) in the treatment of multiple pulmonary nodules, the indications and contraindications of ablation techniques, the efficacy evaluation and complications after ablation therapy, and the prospects of ablation techniques in the treatment of multiple pulmonary nodules.

Readiness for Hospital Discharge(RHD)refers to a multidimensional assessment of a patient's ability to transition safely from hospital to home,encompassing physiological stability,psychological preparedness,and social support adequacy.For patients requiring Home Nutrition Support(HNS),discharge readiness is particularly critical due to their heightened need for post-discharge specialized care,which significantly influences long-term recovery and quality of life.This paper reviews the concept,influencing factors,and unmet needs of RHD in patients with HNS and proposes targeted strategies to enhance discharge preparedness.By addressing gaps in current practices,we aim to optimize RHD in this vulnerable population and provide clinicians with evidence-based guidance for developing effective discharge plans.

OBJECTIVES: To investigate the expression of soluble factor-related apoptosis ligand (sFasL) in peripheral blood and microRNA-147b (miR-147b) in monocytes in children with sepsis and their value in assessing prognosis. METHODS: A prospective study was conducted on 124 children with sepsis (sepsis group), 60 children with common infections (infection group), and 60 healthy children undergoing physical examinations (healthy control group). The independent risk factors for poor prognosis in children with sepsis were analyzed, and the value of serum sFasL and monocyte miR-147b in predicting poor prognosis in children with sepsis was assessed. RESULTS: The serum level of sFasL and the relative expression of miR-147b in monocytes were highest in the sepsis group, followed by the infection group and the healthy control group (P<0.05). The multivariate logistic regression analysis showed that the serum level of sFasL and the relative expression of miR-147b in monocytes were closely associated with the poor prognosis of children with sepsis (P<0.05). The receiver operating characteristic curve analysis showed that the combination of serum sFasL level and relative expression of miR-147b in monocytes had a larger area under the curve compared to each indicator alone in predicting the prognosis of children with sepsis (P<0.05). CONCLUSIONS There are significant increases in the level of sFasL in peripheral blood and the relative expression of miR-147b in monocytes in children with sepsis. The combined use of these two indicators has relatively high clinical value in assessing the prognosis of children with sepsis.
Humans ; Sepsis/diagnosis* ; MicroRNAs/blood* ; Male ; Female ; Monocytes/metabolism* ; Prognosis ; Child, Preschool ; Prospective Studies ; Child ; Infant ; TNF-Related Apoptosis-Inducing Ligand/blood* ; Logistic Models

OBJECTIVES: To summarize the clinical and genetic characteristics of end-stage renal disease caused by PLCE1 gene mutations. METHODS: A retrospective analysis of the clinical and genetic features of three children from a family with PLCE1 gene mutations was conducted, along with a literature review of hereditary kidney disease cases caused by PLCE1 gene mutations. RESULTS: The proband was an 8-year-old male presenting with nephrotic syndrome stage 4 chronic kidney disease. Renal biopsy showed focal segmental glomerulosclerosis. Two years and five months after kidney transplantation, the patient had persistent negative proteinuria and normal renal function. Whole-exome sequencing identified two pathogenic heterozygous variants: c.961C>T and c.3255_3256delinsT, with c.3255_3256delinsT being a novel mutation. Family screening revealed no renal involvement in the parents, but among five siblings, one brother died at age of 4 years from end-stage renal disease. A 7-year-old sister presented with proteinuria and bilateral medullary sponge kidney, with proteinuria resolving after one year of follow-up. A 3-year-old brother died after kidney transplantation due to severe pneumonia. The literature review included 45 patients with hereditary kidney disease caused by PLCE1 gene mutations. The main clinical phenotype was nephrotic syndrome (87%, 39/45), and renal pathology predominantly showed focal segmental glomerulosclerosis (57%, 16/28). No mutation hotspots were identified. CONCLUSIONS Compound heterozygous mutations in the PLCE1 gene can lead to rapid progression of the disease to end-stage renal disease, with favorable outcomes following kidney transplantation. Family screening is crucial for early diagnosis, and medullary sponge kidney may be a novel phenotype associated with these gene mutations.
Humans ; Male ; Proteinuria/genetics* ; Kidney Failure, Chronic/etiology* ; Child ; Mutation ; Female ; Child, Preschool ; Retrospective Studies ; Phosphoinositide Phospholipase C

OBJECTIVES: To evaluate the application value of genetic newborn screening (gNBS) in the Yunnan region. METHODS: A prospective study was conducted with a random selection of 3 001 newborns born in the Yunnan region from February to December 2021. Traditional newborn screening (tNBS) was used to test biochemical indicators, and targeted next-generation sequencing was employed to screen 159 genes related to 156 diseases. Positive-screened newborns underwent validation and confirmation tests, and confirmed cases received standardized treatment and long-term follow-up. RESULTS: Among the 3 001 newborns, 166 (5.53%) were initially positive for genetic screening, and 1 435 (47.82%) were genetic carriers. The top ten genes with the highest variation frequency were GJB2 (21.29%), DUOX2 (7.27%), HBA (6.14%), GALC (3.63%), SLC12A3 (3.33%), HBB (3.03%), G6PD (2.94%), SLC25A13 (2.90%), PAH (2.73%), and UNC13D (2.68%). Among the initially positive newborns from tNBS and gNBS, 33 (1.10%) and 47 (1.57%) cases were confirmed, respectively. A total of 48 (1.60%) cases were confirmed using gNBS+tNBS. The receiver operating characteristic curve analysis demonstrated that the areas under the curve for tNBS, gNBS, and gNBS+tNBS in diagnosing diseases were 0.866, 0.982, and 0.968, respectively (P<0.05). DeLong's test showed that the area under the curve for gNBS and gNBS+tNBS was higher than that for tNBS (P<0.05). CONCLUSIONS gNBS can expand the range of disease detection, and its combined use with tNBS can significantly shorten diagnosis time, enabling early intervention and treatment.
Humans ; Infant, Newborn ; Neonatal Screening ; Genetic Testing ; Female ; Male ; Follow-Up Studies ; Prospective Studies ; China

OBJECTIVE: To prepare clinical-grade human umbilical cord-derived mesenchymal stem cells (hUC-MSC) with high expression of hematopoietic supporting factors and evaluate their stem cell characteristics. METHODS: Fetal umbilical cord tissues were collected from healthy postpartum women during full-term cesarean section. Wharton's jelly was mechanically separated and hUC-MSCs were obtained by explant culture method and enzyme digestion method in an animal serum-free culture system with addition of human platelet lysate. The phenotypic characteristics of hUC-MSCs obtained by two methods were detected by flow cytometry. The differences in proliferation ability between the two groups of hUC-MSCs were identified through CCK-8 assay and colony forming unit-fibroblast (CFU-F) assay. The differences in multilineage differentiation potential between the two groups of hUC-MSCs were identified through induction of adipogenic, osteogenic, and chondrogenic differentiation. The mRNA expression levels of hematopoietic supporting factors such as SCF, IL-3, CXCL12, VCAM1 and ANGPT1 in the two groups of hUC-MSCs were identified by real-time fluorescence quantiative PCR(RT-qPCR). RESULTS: The results of flow cytometry showed that hUC-MSCs obtained by the two methods both expressed high levels of CD73, CD90 and CD105, while lowly expressed CD31, CD45 and HLA-DR. The results of CCK-8 and CFU-F assay showed that the proliferation ability of hUC-MSCs obtained by explant culture method was better than those obtained by enzyme digestion method. The results of the triple lineage differentiation experiment showed that there was no significant difference in multilineage differentiation potential between the two grous of hUC-MSCs. The results of RT-qPCR showed that the mRNA expression levels of hematopoietic supporting factors SCF, IL-3, CXCL12, VCAM1 and ANGPT1 in hUC-MSCs obtained by explant cultrue method were higher than those obtained by enzyme digestion method. CONCLUSION Clinical-grade hUC-MSCs with high expression levels of hematopoietic supporting factors were successfully cultured in an animal serum-free culture system.
Humans ; Mesenchymal Stem Cells/metabolism* ; Umbilical Cord/cytology* ; Cell Differentiation ; Female ; Cell Proliferation ; Cells, Cultured ; Chemokine CXCL12/metabolism* ; Angiopoietin-1/metabolism* ; Vascular Cell Adhesion Molecule-1/metabolism* ; Stem Cell Factor/metabolism* ; Flow Cytometry ; Pregnancy