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.

Renal ischemia-reperfusion injury （RIRI） is a major cause of acute kidney injury during kidney transplantation and peri-operative settings， and there is still a lack of safe and effective targeted preventive and therapeutic drugs in clinical practice. Specifically， xanthohumol， luteolin， dracorhodin C， naringin， senkyunolide Ⅰ， verbascoside， and shikonin enhance antioxidant defenses， and inhibit lipid peroxidation and ferroptosis via the nuclear factor-erythroid 2-related factor 2/heme oxygenase-1 pathway. Apigenin， nobiletin， tanshinone Ⅱ A ， and salidroside activate the phosphatidylinositol 3-kinase/protein kinase B pathway to inhibit mitochondria- dependent apoptosis and facilitate renal repair. Quercetin， methyleugenol， cyanidin-3-glucoside， and platycodin D promote autophagy and improve mitochondrial homeostasis through the adenosine monophosphate-activated protein kinase（AMPK）/mTOR or AMPK/phosphatase and tensin homolog-induced kinase 1/Parkin pathways. In addition， hesperidin， curcumin， ganoderic acid， pulsatilla saponin B4， capsaicin， and diosgenin mitigate inflammatory responses and decrease renal tubular injury markers by inhibiting the Toll-like receptor 4/nuclear factor κB， high mobility group box 1， Janus kinase/signal transducer and activator of transcription pathways， thereby exerting multi-target， multi-stage renoprotective effects.

OBJECTIVE To construct a preoperative medication reconciliation model assisted by a localized large language model （LLM） for gastric cancer and evaluate its clinical efficacy. METHODS A total of 249 gastric cancer patients with a history of continuous medication before admission in the Gastric Surgery Department of Jiangsu Cancer Hospital were retrospectively enrolled. Patients were divided into training set （154 cases） and validation set （95 cases） based on the order of time. Based on guidelines， drug package inserts， and other evidence， a standardized medication reconcili ation process and a structured knowledge base were constructed. DeepSeek-V3 LLM was deployed privately in the hospital， combined with retrieval-augmented generation technology， to achieve automated integration of medication information， risk screening， and generation of personalized recommendations. The quality of LLM-generated recommendations was evaluated using automatic metrics （BERT Score and ROUGE-1， 2， L） and manual scoring [seven-dimensional index （7DI） ] . Spearman correlation analysis was performed to explore the correlation between automatic scores and manual scores. Cronbach’s α coefficient was used to test the internal consistency of manual scoring results. The time consumed by manual and LLM-assisted medication reconciliation was compared across tasks of different difficulty levels （simple， moderate， and high）. RESULTS A structured knowledge base covering 8 major drug categories was finally established， covering common and high-risk preoperative medication scenarios and providing structured retrieval support for the LLM. For automatic evaluation， the precision， recall， and F1-score of BERT Score were 0.783±0.033， 0.811±0.038， and 0.796±0.028， respectively. The F1-scores of ROUGE-1， ROUGE-2 and ROUGE-L were 0.566±0.067， 0.338±0.076 and 0.468±0.082， respectively. The 7DI scores from three manual raters ranged from 32.06 to 33.45. The F1-score of automatic scoring was significantly positively correlated with the 7DI score of manual scoring （maximum coefficient of determination＝0.611， P ＜0.001）， and the internal consistency of manual scoring was good （Cronbach’s α ＝ 0.876）. In terms of efficiency， LLM-assisted medication reconciliation reduced time consumption by more than 90% compared with manual reconciliation in the simple， moderate， and high-difficulty groups （ P ＜0.001）. CONCLUSIONS The medication reconciliation model constructed based on a localized LLM and structured knowledge base shows high accuracy， consistency， and clinical applicability in complex preoperative medication scenarios for gastric cancer. It can improve the efficiency of medication reconciliation and reduce potential medication risks.

Objective: To explore the association between problematic short video use (PSVU) and executive function among students in grades 3 to 6 of primary school, so as to provide references for intervening in primary school students PSVU. Methods: In September 2024 (T1), using a convenience sampling method, 520 students in grades 3 to 6 from a primary school in Xi an City of Shaanxi Province were selected as research subjects. They were followed up at three time points: T1, T2 (January 2025), and T3 (May 2025) using an adapted version of the Internet Addiction Test and Questionnaire of Executive Functioning of Chinese. Pearson correlation and cross lagged model were used to analyze the correlation between PSVU and executive function among primary school students at each time point. Results: The mean PSVU scores of primary school students at T1-T3 were (35.51±12.46, 34.86± 12.64 , 35.16±13.37) respectively, and the mean executive function scores were (68.31±12.95, 64.92±12.99, 66.58±14.13) respectively. Correlation analysis results indicated that PSVU scores and executive function scores were positively correlated in all three measurements ( r =0.26~0.62, all P <0.01). Cross lagged analysis results showed that executive function scores at T1 could positively predict PSVU scores at T2 ( β =0.21), and executive function scores at T2 could positively predict PSVU scores at T3 ( β = 0.20) (both P <0.01). Conclusion The level of executive function in students from grades 3 to 6 of primary school can unidirectionally predict the severity of their PSVU.

Background In 2021, chronic obstructive pulmonary disease (COPD) emerged as the forth leading cause of death in the world. However, the impact of air pollutants on COPD is still inconsistent across current studies. Objective To analyze the relationship between ambient sulfur dioxide (SO₂) exposure and hospital admissions for COPD in Lanzhou, and to examine the modified effects of SO₂ across different genders, age groups, and seasons. Methods A total of 20718 hospital admission records for COPD were collected from Lanzhou between 2016 and 2020, alongside synchronized data on SO₂ concentration and meteorological variables. A generalized additive model integrated with a distributed lag nonlinear model was used to assess the relationship and the lag effects between SO₂ exposure and COPD admissions. Potential confounders, including meteorological factors, day-of-the-week effect, and holidays, were controlled for, with a maximum lag period set at 7 d. Two-pollutant models and sensitivity analyses were conducted to ensure robustness. Results are expressed as relative risks (RR) with 95% confidence intervals (95%CI). Results During the study period, the average daily number of COPD admissions was 11.34±7.03. The average mass concentration of SO₂ was (23.72±12.35) μg·m⁻³. SO₂ exposure was positively correlated with COPD admissions; specifically, each 10 μg·m⁻³ increase in SO₂ concentration was associated with an RR of 1.440 (95%CI: 1.317, 1.573). Stratified analyses found that at a cumulative lag of 7 d, the RRs were higher among females, individuals aged ≥65 years, and during the cold season. Conversely, no significant increase in COPD admission risk related to SO₂ was observed during the warm season. For every 10 μg·m⁻³ increase in SO₂ concentration, the RR was 1.483 (95%CI: 1.311, 1.678) for females, 1.441 (95%CI: 1.311, 1.583) for those aged > 65 years， and 1.595 (95%CI: 1.313, 1.937) during the cold season. Conclusion Short-term exposure to ambient SO₂ exposure in Lanzhou is associated with an increased risk of COPD admission. The association is more pronounced among females, the elderly (aged> 65 years) and during the cold season.

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.

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.

ObjectiveTo investigate the inhibitory effect of Biejiajian Pills （BJJW） on the growth of liver cancer， as well as its potential mechanism in mediating the AMP-activated protein kinase （AMPK）/mammalian target of rapamycin （mTOR） pathway through mitochondrial energy metabolism. MethodsHuman hepatoma Huh7 cells were used to establish a nude mouse model of subcutaneous xenograft tumor. A total of 18 tumor-bearing nude mice were randomly divided into model group， BJJW group （2.2 g/kg）， and metformin group （250 mg/kg）， and the corresponding drug was given by gavage for 14 consecutive days. Tumor volume and weight were monitored during the experiment； HE staining was used to observe histopathological changes； the levels of reactive oxygen species （ROS） and adenosine triphosphate （ATP） in tumor tissue were measured； immunohistochemistry and Western blotting were used to measure the expression levels of proteins associated with the AMPK/mTOR pathway. A one-way analysis of variance was used for comparison of normally distributed continuous data between multiple groups， and the Tukey’s test was used for further comparison between two groups； the Kruskal-Wallis H test was used for comparison of non-normally distributed continuous data between multiple groups， and the Dunn’s test was used for further comparison between two groups. ResultsCompared with the model group， the BJJW group had a tumor inhibition rate of 45.73%， with significant reductions in both tumor volume and weight （P<0.01）. Pathological examination showed that compared with the model group， the BJJW group had a significant reduction in the number of tumor cells and the presence of extensive necrosis. Mechanistic studies showed that compared with the model group， the BJJW group had a significant increase in ROS level （P<0.001） and a significant reduction in ATP level （P<0.001）， as well as significant increases in p-AMPK/AMPK ratio （0.81±0.20 vs 0.13±0.04， P<0.01） and p-ULK1/ULK1 ratio （0.69±0.17 vs 0.18±0.13， P<0.01） and a significant reduction in p-mTOR/mTOR ratio （1.34±0.16 vs 3.20±0.62， P<0.01）. ConclusionBJJW may inhibit the growth of liver cancer by inducing mitochondrial energy metabolism dysfunction， increasing the level of ROS， reducing the level of ATP， and activating the AMPK/mTOR signaling pathway.

BACKGROUND:The mechanism of programmed death receptor-1(PD-1)effect on osteogenic differentiation of bone marrow mesenchymal stem cells in high glucose environment remains unclear. OBJECTIVE:To explore the effect of PD-1 on osteogenic differentiation of rat bone marrow mesenchymal stem cells in high glucose environment and its regulatory mechanism. METHODS:Rat bone marrow mesenchymal stem cells were randomly divided into normal glucose group(5.6 mmol/L),high glucose group(30 mmol/L),PD-1 overexpression group,PD-1 overexpression no-load group,PD-1 knockdown group,PD-1 knockdown no-load group,and PI3K/AKT pathway inhibitor group(PD-1 knockdown+5 μmol/L LY294002).Rat bone marrow mesenchymal stem cells were cultured in high glucose to simulate the diabetic environment in vitro.The mRNA expression of PD-1 and ligand PD-L1 and the mRNA expression of osteogenic markers Runx2 and OSX in rat bone marrow mesenchymal stem cells were detected by qRT-PCR.The osteogenic differentiation ability was observed by alkaline phosphatase staining and alizarin red staining.Cell proliferation was detected by CCK-8 assay.The protein expressions of PD-1,PD-L1,p-PI3K,and p-AKT were detected by western blot assay. RESULTS AND CONCLUSION:(1)The levels of PD-1 and PD-L1 were significantly increased in the high glucose environment in vitro,and the osteogenic differentiation ability of bone marrow mesenchymal stem cells was inhibited in the high glucose environment.(2)Knockdown of PD-1 expression could promote osteogenic differentiation of bone marrow mesenchymal stem cells,increase cell proliferation activity,and activate the PI3K/AKT pathway.(3)After addition of PI3K/AKT pathway inhibitor LY294002,the ability of bone marrow mesenchymal stem cells to differentiate into osteoblasts decreased.The results show that PD-1 is dependent on the PI3K/AKT signaling pathway to inhibit osteogenic differentiation of rat bone marrow mesenchymal stem cells under high glucose environment.

BACKGROUND:U937 cells can be used as a cell model for studying the biological characteristics,signaling pathways,and therapeutic targets of acute myeloid leukemia.Although it has been reported that long non-coding RNA KIAA0125 is highly expressed in acute myeloid leukemia,its biological function in U937 cells remains unclear,and its mechanism of action in the occurrence and development of acute myeloid leukemia needs to be further clarified. OBJECTIVE:To investigate the expression level of long non-coding RNA KIAA0125 in peripheral blood of patients with acute myeloid leukemia and its effect on the proliferation and apoptosis of U937 cells. METHODS:RNA-sequencing was used to analyze the bone marrow monocyte samples from acute myeloid leukemia patients,and the differentially expressed gene long non-coding RNA KIAA0125 was screened.The expression of long non-coding RNA KIAA0125 in peripheral blood of patients with acute myeloid leukemia was detected by qRT-PCR.The relationship between long non-coding RNA KIAA0125 mRNA expression and prognosis in bone marrow cells of 173 acute myeloid leukemia patients and 70 healthy people was statistically analyzed by GEPIA database.Subsequently,recombinant lentivirus technology and CRISPR/Cas9-SAM technology were used to construct U937 cell lines with knockdown/overexpression of long non-coding RNA KIAA0125.qRT-PCR was used to detect the knockdown/overexpression efficiency of long non-coding RNA KIAA0125.Next,CCK-8 assay,flow cytometry,and western blot assay were used to detect the effects of knockdown/overexpression of long non-coding RNA KIAA0125 on the proliferation and apoptosis of U937 cells.Finally,western blot assay was used to detect the effect of knockdown/overexpressed long non-coding RNA KIAA0125 on Wnt/β-catenin signaling pathway-related proteins. RESULTS AND CONCLUSION:(1)The results of qRT-PCR showed that long non-coding RNA KIAA0125 was highly expressed in peripheral blood of acute myeloid leukemia patients.The results of GEPIA database showed that long non-coding RNA KIAA0125 was highly expressed in bone marrow cells of acute myeloid leukemia patients,and the high expression group had worse overall survival.(2)The knockdown efficiency of long non-coding RNA KIAA0125 in knockdown group was 70%,and the U937 cells that stably down-regulated long non-coding RNA KIAA0125 expression were successfully constructed.The expression of long non-coding RNA KIAA0125 in overexpression group was four times that of vector group,and stable U937 cells were successfully constructed.(3)Knockdown of long non-coding RNA KIAA0125 inhibited the proliferation of U937 cells and promoted their apoptosis.Overexpression of long non-coding RNA KIAA0125 promoted the proliferation of U937 cells but had no significant effect on the apoptosis of U937 cells.(4)Knockdown of long non-coding RNA KIAA0125 inhibited the activity of Wnt/β-catenin signaling pathway,while overexpression of long non-coding RNA KIAA0125 activated Wnt/β-catenin signaling pathway.These results confirm that long non-coding RNA KIAA0125 is highly expressed in acute myeloid leukemia peripheral blood.Long non-coding RNA KIAA0125 may affect the proliferation and apoptosis of U937 cells by regulating the Wnt/β-catenin signaling pathway,and may be a potential prognostic marker for acute myeloid leukemia.