Objective: To investigate the ability of different concentrations of piceatannol (PIC) solution to biomodify decalcified dentin matrices in primary teeth, thereby providing a theoretical basis for improving the durability of resin-dentin bonding. Methods: This study was approved by the Medical Ethics Committee of the institution. Molecular docking was performed to predict the interaction effects of PIC with type I collagen and matrix metalloproteinases (MMPs) in dentin. A total of 124 clinically extracted intact primary molars were selected due to retention; of these, 76 were prepared into 60 completely decalcified dentin beams and 24 dentin slices. The 60 beams were equally allocated for dry mass loss and swelling ratio testing (30 beams each). For both experiments, the beams were randomly divided into five groups (n = 6): a control group, 5% glutaraldehyde group, and 2.5, 5, and 10 mg/mL PIC solution groups. This was to evaluate the anti-enzymatic hydrolytic properties and mechanical performance of type I collagen. Of the 24 slices, 15 were assigned to the aforementioned five groups (n = 3) for Fourier-transform infrared spectroscopy (FTIR) to explore the cross-linking mechanism. The remaining nine slices were randomly divided into three groups (n = 3): distilled water group A (SEM examination prior to enzymatic hydrolysis), distilled water group B (SEM examination after enzymatic hydrolysis), and a 10 mg/mL PIC solution group (SEM examination after treatment with 10 mg/mL PIC and subsequent enzymatic hydrolysis). This was to evaluate the cross-linking effect on demineralized dentin collagen. The remaining 48 molars were fabricated into bonding specimens and randomly divided into four groups (n = 12): a control group (distilled water group) and 2.5, 5, and 10 mg/mL PIC groups. Immediate and aged shear bond strength (SBS) were measured, and failure modes were observed under a stereomicroscope to investigate the impact of different PIC concentrations on the bonding durability of primary tooth dentin. Results: Molecular docking revealed strong binding activity between PIC and type I collagen/MMPs via hydrogen bonds, electrostatic potential, and hydrophobic forces; the FTIR results confirmed hydrogen bond formation. In the dry mass loss test, mass loss rates in the 2.5, 5, and 10 mg/mL PIC groups were significantly lower than that in the control group (P < 0.05), with the 10 mg/mL PIC group showing the most optimized cross-linking effect. Swelling tests indicated that all three PIC concentrations reduced the swelling ratio of the demineralized matrix, effectively improving its mechanical properties. SEM showed that collagen from the 10 mg/mL PIC group retained its natural three-dimensional network post-enzymolysis, contrasting sharply with the disintegrated collagen in the enzymolyzed distilled water group B but resembling the morphology of the non-enzymolyzed distilled water group A. SBS results demonstrated that the 10 mg/mL PIC group exhibited significantly higher bond strengths than the control group in both the immediate and aged tests (P < 0.05); immediate SBS in the 10 mg/mL PIC group was also significantly greater than that in the 2.5 mg/mL PIC group (P < 0.05), while no other intergroup differences were found (P > 0.05). Failure mode analysis indicated predominantly mixed fractures, with the proportion of interfacial fractures decreasing as PIC concentration increased compared with the control group. Conclusion A 10 mg/mL PIC solution can effectively cross-link decalcified dentin matrices in primary teeth, enhancing the anti-enzymatic hydrolytic capacity and mechanical properties during clinical operation, thereby promoting bond strength and interface stability, which promises to improve the long-term durability of resin-dentin bonding.

Hyperthyroidism （HT） is frequently complicated by atrial fibrillation （AF） in clinical practice. Based on traditional Chinese medicine （TCM） zang-xiang （藏象） theory and clinical experience， both HT and AF are closely associated with dysfunction of the liver. The pathogenesis is initiated by the liver failing to govern the free flow of qi， and liver constraint and qi stagnation， with the key turning points being liver constraint transforming into fire and the internal stirring of liver wind， ultimately leading to liver blood depletion and insufficient nourishment of the heart spirit. Thus， it is proposed to treat the disease from the liver， with stage-specific therapeutic approaches according to the evolution of the disease. In the early stage， the treatment should focus on soothing the liver and relieving constraint to reduce goiter and calm the heart， while in the progressive stage， the method of clearing liver and draining fire is suggested to subdue yang and stabilize palpitations. In the acute stage， the strategy is calming the liver and nourishing yin to subdue yang and extinguish wind. In the later stage， it is suggested to soften the liver and benefit qi， so as to nourish yin and restore pulse. These methods are sequentially applied to synergistically reduce goiter and stabilize palpitations， providing a therapeutic approach for HT complicated by AF.

ObjectiveTo investigate the effects of Trpc6 knockout on chronic lipopolysaccharide （LPS）-induced myocardial inflammation and fibrosis in mice and its potential mechanisms. MethodsMale C57BL/6 wild-type （WT） mice and Trpc6 knockout （Trpc6^-/-） mice of the same background were randomly divided into four groups： WT control， WT+LPS （200 μg/kg）， Trpc6^-/- control， and Trpc6^-/-+LPS （200 μg/kg）. Group with LPS received intraperitoneal LPS injections for 21 consecutive days to induce chronic myocardial inflammatory injury. Cardiac ultrasound assessed changes in left ventricular ejection fraction （EF）， left ventricular shortening fraction （FS）， and cardiac output （CO）. Hematoxylin and eosin （HE） staining and periodic acid-Schiff （PAS） staining were used to examine morphological alterations in myocardial tissue. Masson’s trichrome staining was used to assess myocardial fiber alterations； Western blot analysis was used to measure myocardial tissue expression of transient receptor potential calcium channel 6 （TRPC6）， NOD-like receptor family pyrin domain-containing 3 inflammasome （NLRP3），absent in melanoma 2 inflammasome （AIM2）， Caspase-1， interleukin （IL）-6， and IL-1β in mouse myocardial tissue. ResultsCompared with the WT control group， the WT+LPS group exhibited decreased cardiac EF （P<0.01）， FS （P<0.01）， and CO （P<0.05）， along with significantly increased myocardial tissue damage， glycoprotein deposition， and fibrosis （P<0.01）. Further analysis revealed that compared with the WT control group， the WT+LPS group exhibited markedly increased myocardial tissue expression of TRPC6， NLRP3， AIM2， Caspase-1， IL-6， and IL-1β （P<0.01）. Compared with the WT+LPS group， mice in the Trpc6^-/- +LPS group exhibited elevated EF （P<0.01） and FS （P<0.05）， along with reduced myocardial tissue injury， glycoprotein deposition， and fibrosis （P<0.05）. ConclusionChronic LPS treatment can activate NLRP3/AIM2 inflammasomes through the up-regulation of TRPC6 expression， and then lead to chronic myocardial inflammatory injury and fibrosis， while Trpc6 knockdown can reduce myocardial inflammatory injury and fibrosis， and the mechanism is related to inhibiting the activation of NLRP3/AIM2 inflammasomes.

ObjectiveTo evaluate the feasibility of various strength levels of deep learning image reconstruction （DLIR） algorithms for improving non-contrast abdominal CT image quality at ultra-low radiation doses， by comparing ultra-low-dose DLIR images with low-dose filtered back projection （FBP） images. MethodsA prospective collection of 85 patients undergoing non-contrast abdominal CT scans was performed， and a self-controlled study method was employed to conduct low-dose （LD） group and ultra-low-dose （ULD） group scans. The LD group used a noise index of 10 and employed FBP for image reconstruction （LD-FBP group）. The ULD group used a noise index of 30 and employed DLIR at different levels （low， medium， high）， resulting in three subgroups of reconstructed images： ULD-DLIR-L， ULD-DLIR-M， and ULD-DLIR-H. For each group， CT values， standard devia-tion （SD）， signal-to-noise ratio （SNR）， and contrast-to-noise ratio （CNR） were measured and calculated for the liver， spleen， kidneys， aorta， psoas major， and subcutaneous fat. Effective dose （ED） was also recorded. Two radiologists independently performed subjective evaluations of image quality using a 5-point scale. ResultsCompared with the LD-FBP group， the ULD-DLIR-L group showed significantly lower SNR and CNR values in the liver， spleen， kidneys， aorta， and psoas major （P<0.001）， while the ULD-DLIR-H group exhibited significantly higher values （P<0.001）. The difference of SNR and CNR values for the ULD-DLIR-M group showed no statistically significant difference. For subjective evaluation， the scores of the ULD-DLIR-L and ULD-DLIR-M groups were lower than those of the LD-FBP group， while there was no statistically significant difference in scores between the ULD-DLIR-H group and the LD-FBP group. The ED value of the ULD group was approximately 88% lower than that of the LD group. ConclusionCompared with the LD-FBP group， the ULD-DLIR-H group significantly reduces SD values while increasing SNR and CNR values， effectively improving the image quality of non-contrast abdominal CT scans.

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.

Hepatic fibrosis is a reversible pathological process in various chronic liver diseases and is closely associated with the development and progression of severe liver diseases such as liver cirrhosis and hepatocellular carcinoma， and it has emerged as a significant global health challenge. In recent years， studies have shown that histone lactylation， a newly discovered epigenetic modification， actively participates in regulating the progression of hepatic fibrosis. This article systematically reviews the core regulatory effect of histone lactylation modification in the interaction between inflammatory microenvironment and hepatic fibrosis， in order to clarify the cascade regulatory mechanism of “inflammation-hepatic fibrosis” and provide new insights for early diagnosis， targeted intervention， and prevention of malignant transformation in hepatic fibrosis.

Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection. Septic shock is the primary cause of mortality in sepsis, with its core pathophysiological mechanism being severe ischemia and hypoxia in critical units—composed of microcirculation and the mitochondria of functional cells—resulting from disruptions in blood flow and oxygen flow following a dysregulated host response. Due to the systemically convergent yet clinically heterogeneous nature of the host response, current understanding and management strategies for hemodynamics remain inconsistent, often leading to inadequate resuscitation or overtreatment. To improve the quality of care, based on a systematic review of the "blood flow-oxygen flow" theory, an expert panel emphasizes reevaluating septic shock from an integrated perspective of blood flow and oxygen flow, and has formulated the Expert Consensus on Blood Flow and Oxygen Delivery Phenotyping and Clinical Management of Septic Shock (2025). The consensus proposes that clinical typing of blood flow-oxygen flow should comprehensively consider cardiac function, vascular tone, oxygen flow utilization status in critical units, and disease trajectory, while optimizing subtype identification by integrating host response phenotypes and artificial intelligence technologies. It advocates establishing a continuous assessment system through multi-site oxygen flow monitoring for organ perfusion, peripheral perfusion monitoring, and critical care ultrasound. Under the framework of the "critical care triangle", the consensus promotes the implementation of individualized, bundled management strategies, providing guidance for multiple management points to restore blood flow-oxygen flow matching, reduce the risk of organ failure, and decrease patient mortality.

ObjectiveTo investigate the effects of jatrorrhizine on endogenous metabolites and metabolic pathways in the mouse model of ulcerative colitis. MethodsThirty male C57BL/6J mice were randomly divided into the normal group， the model group， the low-dose and high-dose jatrorrhizine groups （0.04， 0.16 g·kg^-1）， and the mesalazine group （0.52 g·kg^-1）The mouse model of ulcerative colitis was established with 3% dextran sulfate sodium （DSS） and treated with different doses of jatrorrhizine by gavage. The changes in body weight， colon length， disease activity index （DAI）， and colonic histopathology were analyzed to evaluate the therapeutic effects of jatrorrhizine. UPLC-Q-TOF/MS was employed to determine the serum and fecal levels of metabolites in mice. Metabolomics methods were used to screen the differential metabolites， on the basis of which the potential therapeutic mechanism of jatrorrhizine on DSS-induced ulcerative colitis in mice was investigated. ResultsAfter intervention with jatrorrhizine， the model mice showed significantly decreased DAI（P<0.05，P<0.01）， recovered colon length，（P<0.05，P<0.01） and alleviated histopathology of the colon. The metabolomics study screened out 13 differential metabolites in the serum and 8 differential metabolites in the feces. The pathway enrichment analysis predicted three potential metabolic pathways： Biosynthesis of unsaturated fatty acids， phenylalanine， tyrosine and tryptophan biosynthesis， and phenylalanine metabolism. ConclusionJatrorrhizine may treat ulcerative colitis by regulating the biosynthesis and metabolism of amino acids and the synthesis of unsaturated fatty acids.

ObjectiveTo systematically evaluate the application of narrative education in undergraduate nursing teaching， to understand the current application status of narrative education， and to provide a theoretical basis for the subsequent establishment of a sound narrative education system. MethodsA systematic search was conducted for studies published in Chinese and English databases on applying narrative education to undergraduate nursing teaching， with the search period ranging from database inception to February 23， 2025. Literature was screened， and relevant information was extracted. A rigorous quality evaluation was conducted on the included studies， and a descriptive analysis was performed on their content. ResultsA total of 20 papers were included， involving 3，180 research subjects， all of whom were undergraduate nursing students. The results of descriptive analysis showed that the teaching model of narrative education primarily encompassed reading narrative works， watching films and videos， performing narrative scenarios， and writing reflective journals. The course setting and content covered pre-teaching preparation and in-teaching implementation. The evaluation of teaching effectiveness included the evaluation of teachers’ teaching methods （student evaluation/self-evaluation） and the evaluation of students’ learning effectiveness （course grade evaluation/humanistic care scale/empathy scale assessment， and others）. ConclusionNarrative education combines abstract concepts with concrete clinical situations， which not only enriches students’ learning experiences but also enhances their humanistic literacy. Meanwhile， it provides teachers with opportunities to develop their narrative teaching skills， which requires them to possess profound professional knowledge and employ narrative techniques to guide students in reflection and critical thinking， thereby improving teaching quality and learning outcomes. Future efforts should consistently deepen the connotation research of narrative education and build a systematic nursing education system.