Organoid-on-a-chip technology represents a promising interdisciplinary advancement that merges two cutting-edge biomedical platforms: stem cell-derived organoids and microfluidics-based organ-on-a-chip systems. Organoids are self-organizing three-dimensional (3D) cell cultures that mimic the key structural and functional features of in vivo organs. However, traditional organoid culture systems are often static, lacking dynamic environmental cues and suffering from limitations such as batch-to-batch variability, low stability, and low throughput. Organ-on-a-chip platforms, by contrast, utilize microfluidic technologies to simulate the dynamic physiological microenvironment of human tissues and organs, enabling more controlled cell growth and differentiation. By integrating the advantages of organoids and organ-on-a-chip technologies, organoid-on-a-chip systems transcend the limitations of conventional 3D culture models, offering a more physiologically relevant and controllable in vitro platform. In organoid-on-a-chip systems, stem cells or pre-formed organoids are cultured in micro-engineered environments that mimic in vivo conditions, enabling precise control over fluid flow, mechanical forces, and biochemical cues. Specifically, these platforms employ advanced strategies including bio-inspired 3D scaffolds for structural support, precise spatial cell patterning via 3D bioprinting, and integrated biosensors for real-time monitoring of metabolic activities. These synergistic elements recreate complex extracellular matrix signals and ensure high structural fidelity. Based on structural complexity, organoid-on-a-chip systems are classified into single-organoid and multi-organoid types, forming a trajectory from unit biomimicry to systemic simulation. Single-organoid chips focus on highly biomimetic units by integrating vascular, immune, or neural functions. Multi-organoid chips simulate inter-organ crosstalk and systemic homeostasis, advancing complex disease modeling and PK/PD evaluation. This emerging technology has demonstrated broad application potential in multiple fields of biomedicine. Organoid-on-a-chip systems can recapitulate organ developmentin vitro, facilitating research in developmental biology. They mimic organ-specific physiological activities and mechanisms, showing promising applications in regenerative medicine for tissue repair or replacement. In disease modeling, they support the reconstruction of models for neurodegenerative, inflammatory, infectious, metabolic diseases, and cancers. These platforms also enable in vitro drug testing and pharmacokinetic studies (ADME). Patient-derived chips preserve genetic and pathological features, offering potential for precision medicine. Additionally, they reduce species differences in toxicology, providing human-relevant data for environmental, food, cosmetic, and drug safety assessments. Despite progress, organoid-on-a-chip systems face challenges in dynamic simulation, extracellular matrix (ECM) variability, and limited real-time 3D imaging, requiring improved materials and the integration of developmental signals. Current bottlenecks also include the high technical threshold for automation and the lack of standardized validation frameworks for regulatory adoption. Meanwhile, the concept of a “human-on-a-chip” has been proposed to mimic whole-body physiology by integrating multiple organoid modules. This approach enables systemic modeling of drug responses and toxicity, with the potential to reduce animal testing and revolutionize drug development. Future advancements in bio-responsive hydrogels and flexible biosensors will further empower these platforms to bridge the gap between bench-side research and personalized clinical interventions. In conclusion, organoid-on-a-chip technology offers a transformative in vitro model that closely recapitulates the complexity of human tissues and organ systems. It provides an unprecedented platform for advancing biomedical research, clinical translation, and pharmaceutical innovation. Continued development in biomaterials, microengineering, and analytical technologies will be essential to unlocking the full potential of this powerful tool.

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.

Organoid-on-a-chip technology represents a promising interdisciplinary advancement that merges two cutting-edge biomedical platforms: stem cell-derived organoids and microfluidics-based organ-on-a-chip systems. Organoids are self-organizing three-dimensional (3D) cell cultures that mimic the key structural and functional features of in vivo organs. However, traditional organoid culture systems are often static, lacking dynamic environmental cues and suffering from limitations such as batch-to-batch variability, low stability, and low throughput. Organ-on-a-chip platforms, by contrast, utilize microfluidic technologies to simulate the dynamic physiological microenvironment of human tissues and organs, enabling more controlled cell growth and differentiation. By integrating the advantages of organoids and organ-on-a-chip technologies, organoid-on-a-chip systems transcend the limitations of conventional 3D culture models, offering a more physiologically relevant and controllable in vitro platform. In organoid-on-a-chip systems, stem cells or pre-formed organoids are cultured in micro-engineered environments that mimic in vivo conditions, enabling precise control over fluid flow, mechanical forces, and biochemical cues. Specifically, these platforms employ advanced strategies including bio-inspired 3D scaffolds for structural support, precise spatial cell patterning via 3D bioprinting, and integrated biosensors for real-time monitoring of metabolic activities. These synergistic elements recreate complex extracellular matrix signals and ensure high structural fidelity. Based on structural complexity, organoid-on-a-chip systems are classified into single-organoid and multi-organoid types, forming a trajectory from unit biomimicry to systemic simulation. Single-organoid chips focus on highly biomimetic units by integrating vascular, immune, or neural functions. Multi-organoid chips simulate inter-organ crosstalk and systemic homeostasis, advancing complex disease modeling and PK/PD evaluation. This emerging technology has demonstrated broad application potential in multiple fields of biomedicine. Organoid-on-a-chip systems can recapitulate organ developmentin vitro, facilitating research in developmental biology. They mimic organ-specific physiological activities and mechanisms, showing promising applications in regenerative medicine for tissue repair or replacement. In disease modeling, they support the reconstruction of models for neurodegenerative, inflammatory, infectious, metabolic diseases, and cancers. These platforms also enable in vitro drug testing and pharmacokinetic studies (ADME). Patient-derived chips preserve genetic and pathological features, offering potential for precision medicine. Additionally, they reduce species differences in toxicology, providing human-relevant data for environmental, food, cosmetic, and drug safety assessments. Despite progress, organoid-on-a-chip systems face challenges in dynamic simulation, extracellular matrix (ECM) variability, and limited real-time 3D imaging, requiring improved materials and the integration of developmental signals. Current bottlenecks also include the high technical threshold for automation and the lack of standardized validation frameworks for regulatory adoption. Meanwhile, the concept of a “human-on-a-chip” has been proposed to mimic whole-body physiology by integrating multiple organoid modules. This approach enables systemic modeling of drug responses and toxicity, with the potential to reduce animal testing and revolutionize drug development. Future advancements in bio-responsive hydrogels and flexible biosensors will further empower these platforms to bridge the gap between bench-side research and personalized clinical interventions. In conclusion, organoid-on-a-chip technology offers a transformative in vitro model that closely recapitulates the complexity of human tissues and organ systems. It provides an unprecedented platform for advancing biomedical research, clinical translation, and pharmaceutical innovation. Continued development in biomaterials, microengineering, and analytical technologies will be essential to unlocking the full potential of this powerful tool.

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.

Since its emergence in the 1980s, the human immunodeficiency virus (HIV) has caused a global pandemic, posing a severe threat to human life and health as well as social development. Although pre-exposure prophylaxis (PrEP) effectively curbs HIV transmission and antiretroviral therapy (ART) significantly extends the lifespan of patients, vaccines remain a pivotal tool for blocking transmission and ending the pandemic. The high genetic variability of HIV-1, the glycan shield of its envelope glycoproteins, and the long-term persistence of latent reservoirs have repeatedly led to bottlenecks in traditional vaccine strategies. In recent years, mRNA technology has offered a novel approach to addressing these challenges, leveraging advantages such as sequence programmability, short production cycles, native conformational expression of antigens, and self-adjuvant effects. In recent years, mRNA vaccine technology has emerged as a transformative solution to longstanding vaccinology challenges, characterized by its sequence programmability, rapid production cycles, native conformational antigen expression, and intrinsic self-adjuvanting properties. Unlike traditional platforms reliant on pathogen culture or recombinant proteins, mRNA vaccines can be expeditiously designed and updated based solely on viral genomic sequences. Lipid nanoparticle (LNP)-encapsulated mRNA facilitates endogenous antigen expression and presentation, simultaneously eliciting potent humoral and cellular immune responses. Within this landscape, self-amplifying mRNA (saRNA) further extends in vivo antigen expression to enhance the persistence of immune responses. Moreover, the LNP delivery system not only protects mRNA from degradation and mediates endosomal escape but also synergizes with mRNA to optimize immune activation via self-adjuvant effects. Importantly, mRNA platforms circumvent the pre-existing immunity associated with viral vectors and the genomic integration risks of DNA vaccines, positioning them as a cornerstone for global pandemic preparedness. This review systematically delineates recent advances in mRNA technology for HIV-1 vaccine development, focusing on four pivotal research frontiers. First, mRNA innovations building upon the RV144 trial optimize antigens through codon modification and multivalent designs to induce more durable and broad-spectrum immunity. Second, particulate mRNA vaccine strategies, utilizing virus-like particles (VLPs) and ferritin nanoparticles, achieve in situ antigen self-assembly, significantly enhancing B cell activation and reducing infection risks in non-human primate models. Third, germline-targeting mRNA vaccines address the low-affinity barrier of broadly neutralizing antibody (bNAp) precursors, efficiently activating rare precursor B cells and promoting affinity maturation. Fourth, therapeutic mRNA vaccines offer unique advantages for an HIV functional cure; combining immunogens with mRNA-encoded adjuvants potentiates cellular immunity, while LNP-mediated “shock-and-kill” strategies specifically activate latent reservoirs to guide immune clearance. Comparative analyses with traditional platforms reveal that mRNA technology redefines antigen production and presentation, simulating chronic infection through sustained expression and enabling dual-pathway presentation via endogenous synthesis. Furthermore, we explore the mechanistic innovations of mRNA vaccines in inducing bNAps: sustained in vivo production prolongs the activation window for precursor B cells and maintains germinal center (GC) reactions; endogenously expressed antigens adopt native conformations to expose conserved epitopes; and self-adjuvanting effects modulate the functions of antigen-presenting cells (APCs) and follicular helper T cells (Tfh), driving somatic hypermutation and affinity maturation. We also address critical clinical translation challenges, including immune durability, adaptability to special populations, and large-scale LNP manufacturing, while proposing targeted optimization strategies. In conclusion, this review establishes a theoretical framework for utilizing mRNA technology to overcome HIV-1 immune escape, transitioning from a descriptive paradigm to a problem-solving-based synthesis of evidence. By integrating preclinical and early clinical data, we bridge the gap between basic design and translational verification. mRNA technology is poised to become a central pillar inHIV-1 prevention and therapy, providing a robust toolset to achieve the global goal of ending the AIDS pandemic and offering a blueprint for vaccine development against other recalcitrant infectious diseases.

ObjectiveThe exacerbating trend of global population aging poses profound socioeconomic and public health challenges, making the comprehensive elucidation of biological aging mechanisms and the discovery of effective anti-aging interventions an urgent priority in the life sciences. Based on our previous serum metabolomics findings that dimethylglycine, an intermediate metabolite of amino acid metabolism naturally present in the human body, was significantly enriched in the serum of longevity families, this study aimed to systematically investigate the anti-aging effects of dimethylglycine both in living organisms and in controlled laboratory environments, and to preliminarily elucidate its underlying molecular mechanisms. While existing literature indicates that dimethylglycine possesses antioxidant and immunomodulatory properties, its direct anti-aging efficacy and the specific molecular pathways through which it operates remain largely unexplored. MethodsTo comprehensively evaluate the anti-aging properties of dimethylglycine, we utilized replicative senescent human embryonic lung fibroblasts, specifically the WI-38 cell line, as an experimental model in a controlled laboratory environment. Cell viability and safety were thoroughly assessed using Cell Counting Kit-8 and lactate dehydrogenase release assays across various concentrations of dimethylglycine. The impact of dimethylglycine on cellular senescence phenotypes, oxidative stress, and proliferative capacity was evaluated via senescence-associated beta-galactosidase staining, reactive oxygen species fluorescence detection, and 5-ethynyl-2'-deoxyuridine incorporation assays. Furthermore, the molecular alterations of senescence-associated secretory phenotype factors and core senescence signaling pathways were quantified using quantitative reverse transcription polymerase chain reaction for the messenger RNA levels of interleukin-6, interleukin-8, p21, and matrix metalloproteinase-1, and enzyme-linked immunosorbent assay for the measurement of p16 and p21 protein expression levels. For the living organism model, the wild-type nematode Caenorhabditis elegans was used to evaluate systemic physiological effects. We conducted a comprehensive lifespan analysis at 20°C, heat stress resistance survival assays at 35℃, senescence-associated beta-galactosidase staining, lipofuscin accumulation tracking, intracellular reactive oxygen species measurement, and Oil Red O staining to ascertain systemic lipid accumulation. Additionally, network pharmacology bioinformatics tools, including PharmMapper and STRING databases, and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were utilized to predict target pathways, alongside highly detailed molecular docking simulations utilizing SwissDock and Protein-Ligand Interaction Profiler to examine interactions with the cytochrome P450 family 2 subfamily C member 9 protein. ResultsThe experimental outcomes robustly demonstrate the potent anti-aging capabilities of dimethylglycine. At the cellular level, toxicity analyses firmly confirmed that dimethylglycine is highly safe; continuous treatment with 50 mol/L and 70 mol/L of dimethylglycine for 5 d did not induce any cellular membrane damage or cytotoxicity, but rather actively promoted cellular proliferation. Utilizing the optimal standardized concentration of 50 mol/L, dimethylglycine treatment significantly ameliorated senescent phenotypic markers in human embryonic lung fibroblasts, which was evidenced by a drastic and highly significant reduction in the senescence-associated beta-galactosidase positive cell percentage (P<0.000 1) and intracellular reactive oxygen species levels (P<0.000 1), alongside a marked increase in the 5-ethynyl-2'-deoxyuridine-positive proliferation rate (P=0.003 5). On a molecular expression scale, dimethylglycine significantly downregulated the messenger RNA expression of multiple core senescence-associated secretory phenotype inflammatory factors, including interleukin-6, interleukin-8, p21, and matrix metalloproteinase-1. Concurrently, it effectively suppressed the protein expression of critical cell cycle arrest markers, diminishing p16 protein levels by 57.3% (P=0.000 4) and p21 protein levels by 27.2% (P=0.000 7). In the nematode Caenorhabditis elegans animal model, dimethylglycine significantly extended the mean lifespan from 20.402 d to an impressive 23.066 d (P<0.000 1) and notably enhanced overall survival rates under severe heat stress environmental conditions (P=0.017). Furthermore, systemic dimethylglycine intervention significantly mitigated age-related physiological decline by decreasing bodily lipofuscin accumulation (P<0.000 1), significantly reducing senescence-associated beta-galactosidase activity, lowering systemic reactive oxygen species fluorescence (P=0.008), and effectively alleviating overall fat accumulation (P<0.000 1). Mechanistically, extensive network pharmacology and Kyoto Encyclopedia of Genes and Genomes analyses strongly revealed that the potential targets of dimethylglycine are significantly enriched in fundamental drug metabolism and oxidative stress response pathways. Precision molecular docking simulations conclusively demonstrated that dimethylglycine forms highly stable structural interactions with the cytochrome P450 family 2 subfamily C member 9 protein, specifically highlighting the definitive formation of 5 stable hydrogen bonds involving serine 365, leucine 366, and serine 429 residues, as well as two critical salt bridge formations with arginine 97 and histidine 368 residues. It is additionally predicted to interact favorably with glutathione S-transferase family proteins. ConclusionDimethylglycine exhibits a profoundly significant and multifaceted anti-aging activity at both the cellular and entire living animal levels. By powerfully alleviating oxidative stress, heavily suppressing the core p16 and p21-dependent cellular senescence signaling pathways, and substantially mitigating the detrimental senescence-associated secretory phenotype, dimethylglycine effectively delays fundamental cellular senescence processes and drastically extends whole-organism lifespan. The biological mechanisms driving these robust protective effects are highly likely closely associated with its direct stable interactions with crucial metabolic and detoxifying enzyme systems, such as cytochrome P450 family 2 subfamily C member 9 and glutathione S-transferase family proteins, thereby systemically improving metabolic dysregulation and restoring critical redox homeostasis. This comprehensive study provides highly solid experimental evidence supporting dimethylglycine as a highly potent and safe potential anti-aging intervention agent, while simultaneously offering a clear molecular mechanistic explanation for the previously documented high abundance of dimethylglycine observed within exceptionally long-lived human populations.

ObjectiveGastric hemorrhage is one of the most common and life-threatening emergencies of the upper digestive tract. Early identification and continuous monitoring are essential for reducing rebleeding rates and mortality, particularly within the critical early hours after onset. Although endoscopy and radiological imaging can accurately localize bleeding sites, these approaches are invasive, resource-intensive, and unsuitable for continuous bedside monitoring. Electrical impedance tomography (EIT), as a noninvasive and radiation-free functional imaging technique, offers real-time visualization of conductivity distribution and has the potential for detecting intragastric bleeding based on the electrical contrast between blood and surrounding gastric tissues. In this study, a three-dimensional gastric EIT (3D-gEIT) framework is proposed to achieve noninvasive, real-time, and dynamic monitoring of gastric hemorrhage, with emphasis on spatial localization and quantitative volume assessment. MethodsA three-dimensional upper-abdominal simulation model incorporating the stomach, gastric wall, gastric contents, and surrounding tissues was established. Three electrode configurations, namely the dual layer ring, the four layer staggered ring, and the opposed dual plane array, were designed and systematically compared to evaluate their influence on depth sensitivity and spatial resolution. Based on the Tikhonov-Noser hybrid regularization scheme, a region-clustering constraint was introduced to develop the TK-Noser-RCC algorithm. This approach aggregates spatially adjacent elements with similar conductivity variations, thereby enhancing structural continuity and suppressing isolated noise artifacts. To validate the proposed framework, an upper-abdominal physical phantom was constructed using agar to simulate background tissue conductivity. Hemispherical high-conductivity inclusions with volumes ranging from 10 ml to 50 ml were attached to the inner gastric wall to mimic localized bleeding under different gastric filling states. Boundary voltages were acquired under a 120 kHz excitation current and reconstructed using the TK-Noser-RCC algorithm. Furthermore, an in vivo animal experiment was performed using a porcine model with adult-scale abdominal dimensions. A total of 100 ml of autologous blood was injected incrementally into the stomach to simulate progressive gastric hemorrhage, and time-difference EIT reconstruction was conducted at each injection stage to assess the dynamic system response under physiological conditions. ResultsSimulation results demonstrated that the opposed dual-plane electrode array achieved superior depth sensitivity distribution and spatial resolution. For a 40 ml hemorrhage model, the average ICC and SSIM improved by 55.9% and 38.8% compared with the dual-layer ring configuration, and by 64.0% and 39.5% compared with the four-layer staggered configuration. The proposed region-clustering constraint significantly enhanced reconstruction stability. Under added Gaussian noise of 40 dB and 30 dB, ICC values remained approximately 0.85, indicating effective artifact suppression and preservation of boundary integrity. In physical phantom experiments, reconstructed hemorrhage volumes increased approximately linearly with the preset hemispherical volumes, and the reconstructed high-conductivity regions closely matched the actual bleeding locations. Both empty-stomach and full-stomach conditions were evaluated, demonstrating that the opposed dual-plane configuration maintained stable imaging performance across varying gastric contents. In the animal experiment, reconstructed low-impedance regions expanded progressively with increasing injected blood volume. The spatial localization of the hemorrhage remained stable throughout the procedure, and no significant artifacts were observed. Quantitative analysis showed that reconstructed volume and average conductivity variation exhibited an approximately linear growth trend with injected blood volume, confirming the sensitivity of the system to dynamic intragastric conductivity changes. ConclusionThe proposed 3D-gEIT framework enables quantitative reconstruction of gastric hemorrhage volume and spatial distribution with improved depth sensitivity, structural continuity, and noise robustness compared with conventional EIT approaches. By integrating optimized electrode configuration and a region-clustering-constrained reconstruction algorithm, the system provides stable dynamic monitoring under both controlled phantom conditions and in vivo physiological environments. This method offers a noninvasive, real-time, and low-cost imaging strategy for early diagnosis, postoperative monitoring, and bedside surveillance of gastric bleeding.

ObjectiveTo explore the effect of oral sodium butyrate on skeletal muscle atrophy in CT26 tumor mice through the gut microbiota-skeletal muscle axis and its potential mechanism. MethodsSixty SPF BALB/c male mice aged 8 weeks were randomly divided into a normal control group (NC, n=18) and a ABX-depleted group (ABX, n=42). The ABX mice were pretreated with a quadruple antibiotic cocktail via oral gavage (0.2 ml per administration, once daily, 6 d per week, for 2 weeks), whereas NC received an equal volume of sterile water. The quadruple antibiotic cocktail consisted of metronidazole (1 g/L), vancomycin (0.5 g/L), ampicillin (1 g/L), and gentamicin (1 g/L). Following successful pretreatment, six mice from each group were randomly selected for gut microbiota sequencing analysis and designated as the Abx group and the NC0 group, respectively. Theremaining mice in ABX were subcutaneously inoculated in the dorsum with 0.2 ml of CT26 cell suspension (at a cell density of 1×10⁷/ml). Then these mice were randomly allocated into three subgroups: a control tumor bearing model group (0_NaB, n=12), a tumor-bearing model group receiving low-dose oral sodium butyrate (L_NaB, n=12), a tumor-bearing model group receiving high-dose oral sodium butyrate (H_NaB, n=12). And mice in NC were inoculated at the same site with 0.2 ml of normal saline. The administration dose for L_NaB was 0.3 g/(kg·d), that for H_NaB was 0.5 g/(kg·d), while NC and 0_NaB were given the same volume of normal saline (0.2ml per time, once daily, 6 d per week, for 4 weeks). The general condition of mice was monitored, and forelimb grip strength gastrocnemius muscle mass and its muscle fiber cross-sectional area were measured for each group. The structural changes in gut microbiota were assessed by 16S rRNA sequencing of cecal contents. Pathological alterations in the intestinal wall were examined via HE staining. Serum and gastrocnemius muscle levels of TNF‑α, IL-6, IL-1β, and LPS were quantified using ELISA. The protein expression of ZO-1 and occludin in the small intestine, as well as proteins associated with the TLR4/MyD88/NF-κB signaling pathway in the gastrocnemius muscle, were detected by Western blot analysis. Results(1) The alpha-diversity in Abx was significantly lower than that in NC0 (P<0.01), a significant decrease of the mass and muscle fiber cross-sectional area of the gastrocnemius (P<0.01), with the majority of gut microbiota being effectively depleted. (2) Compared with NC, the subcutaneous tumors of mice in 0_NaB were prominent, a significant increase of the mass and muscle fiber cross-sectional area of the gastrocnemius, accompanied by a significant decrease in body weight at the end of the 3th and 4th week (P<0.05), and a significant weakening of the forelimb grasping strength at the 5th and 6th week (P<0.01). Compared with 0_NaB, the tumor mass of mice in L_NaB and H_NaB showed a significant decreasing trend, and the grip strength of the forelimbs significantly increased at the 5th and 6th week (P<0.05, P<0.01). (3) Compared with 0_NaB, the Shannon and Observed species indices in α diversity of L_NaB and H_NaB were significantly increased (P<0.05). At the genus level, compared with 0_NaB, L_NaB exhibited a significant decrease in the relative abundance of Parasutterella (P< 0.01), while H_NaB showed significant reductions in the relative abundances of both Escherichia-Shigella and Parasutterella (P < 0.01). (4) Compared with 0_NaB, the small intestinal tissue structure in L_NaB and H_NaB was more intact, the infiltration of inflammatory cells was significantly reduced, and the capillaries were slightly dilated. The expression levels of ZO-1 and occludin proteins in L_NaB were significantly increased (P<0.01). (5) The LPS concentration in the gastrocnemius muscle and the protein expression levels of TLR4, MyD88, p-IκBα, and p-NF‑κB p65 in L_NaB and H_NaB were significantly lower than those in 0_NaB (P<0.05). The serum TNF‑α concentration in H_NaB and TNF-α concentration in the gastrocnemius muscle of the L_NaB and H_NaB were significantly lower than those in 0_NaB (P<0.05, P<0.01, P<0.01). ConclusionOral administration of NaB can improve gut microbiota α diversity, adjusting its composition, improving intestinal mucosal barrier function, reducing the LPS-induced pro-inflammatory response, and delaying skeletal muscle atrophy. The underlying mechanism may involve down regulation of TLR4/MyD88/NF-κB signaling in skeletal muscle.

ObjectiveDonkey hide is the sole legally designated raw material for the preparation of the traditional Chinese medicine Ejiao. The quality stability of donkey hide during preservation directly determines the efficacy and safety of Ejiao. This study focuses on the dynamic succession of microbial communities during the preservation of donkey hides from different origins, aiming to clarify the correlation between microbial biodiversity difference and the degradation profiles of hide collagen and critical biochemical components, thereby providing a theoretical foundation for developing targeted preservation strategies based on microbial regulation. MethodsDonkey hides originating from four different regions were subjected to an accelerated microbial aging assay to simulate the spoilage process. The microbial community succession was analyzed using high-throughput sequencing. Microstructure changes and pore structure characteristics were assessed by scanning electron microscopy and mercury intrusion porosimetry, respectively. Additionally, the content of major components, including lipids, proteins, and sugars were determined by biochemical methods. ResultsAfter 96 h of aging, the collagen fiber structure in Africa donkey hides (ADH) exhibited significant degradation and collapse, followed by Xinjiang donkey hides (XDH). Instead, the microstructure of Dong’e black donkey hides (DDH) and Peru donkey hides (PDH) remained relatively intact. The porosities of DDH, XDH, PDH, and ADH increased from 27.9%, 15.7%, 30.3%, and 46.2% to 36.5%, 52.6%, 42.8%, and 57.7%, respectively, during the aging process, which suggested that the originally compact fiber structure was disrupted by microbial aging. Fourier transform infrared spectrometer analysis revealed the amide bands in XDH exhibited relatively weak intensity, and no collagen amide I band was observed in ADH. Meanwhile, the lipid and protein contents decreased in all four types of donkey hides, indicating that these components served as the primary nutrient sources for the growth of microorganism. Notably, the most severe collagen degradation was observed in XDH and ADH. A substantial increase was detected in the total soluble sugar in PDH aging solution and hydroxyproline in the ADH aging solution, respectively. These results indicated that donkey hides exhibit distinct patterns of structural degradation and nutrient utilization. Furthermore, the viable cells number of donkey hides increased sharply after 48 h of aging. Metagenomic analysis revealed that the relative abundance of Euryarchaeota in ADH, PDH and XDH declining from initial 93.19%, 97.73% and 30.08% to 0.79%, 1.43% and 0.02% after 96 h, respectively. Conversely, a significantly increase was observed in the abundance of Bacillota, with a marked increase in ADH, peaking at 92.75%. Additionally, the abundance of Pseudomonadota in PDH increased from 0.10% to 87.84%, suggesting that Bacillota and Pseudomonadota may be key factors exacerbating donkey hide spoilage. Unlike the other three types of donkey hides, the dominant bacterial phylum in DDH shifted from Pseudomonadota to Bacteroidota, characterized by a substantial abundance increase of Bacteroidota from 0.13% to 44.22%. ConclusionRegional variation in origin significantly influence the microbial aging of donkey hides, leading to distinct patterns of structural deterioration and differential nutrient utilization. Therefore, implementing origin-specific preservation strategies, through the precisely controlling environmental factors to suppress harmful phyla such as Bacillota and Pseudomonadota, is crucial for enhancing the storage quality of donkey hides.

Objective: To explore a simple, effective, and safe method for excluding false positives and identifying infections by comprehensively evaluating blood donors with reactive HIV screening results, thereby providing a basis for developing management strategies for such donors. Methods: HIV testing data of blood donors from our laboratory from January 2022 to December 2024 were collected. The results of ELISA and nucleic acid testing (NAT) were combined with confirmatory results from the CDC and analyzed. Results: A total of 605 929 samples were tested for HIV over the three-year period, with 682 reactive samples (reactive rate: 11.25 per 10 000). All were sent to the CDC for Western blot (WB) confirmation, resulting in 53 confirmed positives ((confirmed positive rate: 7.77%). Among these, 619 samples showed isolated HIV Ag&Ab reactivity with non-reactive NAT (HIV Ag&Ab+-&HIV RNA or NAT NR), with a confirmed infection rate of 0%; 9 samples showed dual HIV Ag&Ab reactivity with non-reactive NAT (HIV Ag&Ab++&HIV RNA NR or NAT NR), also with 0% confirmed infection; 52 samples showed dual HIV Ag&Ab reactivity and reactive NAT (HIV Ag&Ab++&HIV RNA R or NAT R), all confirmed as positive (100% infection rate); and 2 HIV Ag&Ab dual-reactive samples without NAT detection were also confirmed infected (100%). For all four HIV Ag&Ab assays, the S/CO values in the true positive group with dual reactivity were significantly higher than those in the false-positive groups (P<0.05). The S/CO distributions for both single-reactive false positives and dual-reactive false positives were narrow, with the upper box (Q3, 75th percentile) below optimal cutoff values in all cases (The optimal cutoff values for the four reagents were 5.00, 11.67, 8.50, and 20.90, respectively). Conclusion: Blood donors with positive NAT results in HIV blood screening are permanently deferred. Donors with dual positive HIV Ag&Ab but negative NAT results are classified and managed based on the S/CO values of HIV Ag&Ab and the optimal screening thresholds. Donors with single positive HIV Ag&Ab but negative NAT results are placed under evaluation status and retain their eligibility to donate blood. Optimizing the management measures for blood donors and establishing a scientific stratified management and assessment mechanism can effectively maintain the stability of the blood donor team.