Genetic polymorphism of IL-18 influences susceptibility to lung cancer in population of eastern China.

The association of Interleukin-18 (IL-18) genetic polymorphism with lung cancer risk has yielded inconsistent findings in previous studies. The current research aims to clarify the relationship of IL-18 gene polymorphism with lung cancer susceptibility through experimental investigation and meta-analysis, providing insights for lung cancer prevention and treatment. We conducted a thorough search of major databases from their inception until March 2024. OR and 95%CI were calculated to know the results of meta-analysis. The IL-18 gene polymorphism was detected using the PCR-RFLP method. Significant associations were detected across all genetic models in allele contrast (A vs. C: Odds Ratio [OR] = 1.29, 95% Confidence Interval [CI] = 1.07-1.55, p = 0.006), homozygote comparison (AA vs. CC: OR = 1.87, 95%CI = 1.34-2.62, p < 0.001), recessive genetic model (AA vs. CT/CC: OR = 1.54, 95%CI = 1.08-2.20, p = 0.018), and dominant genetic model (AA/AC vs. CC: OR = 1.41, 95%CI = 1.12-1.78, p = 0.003). Three genotypes (AA, AC, and CC) were identified for the IL-18 -607 C/A polymorphism, with significant associations noted for the AA genotype and A allele (p = 0.018 and 0.005, respectively). This is the first study which investigates this polymorphism with lung cancer in population of eastern China. The IL-18 -607 C/A polymorphism appears to significantly increase the risk of lung cancer in the population of Eastern China. Further research is imperative to validate these findings.

Machine learning-based prediction of clinical outcomes after traumatic brain injury: Hidden information of early physiological time series.

AIMS: To assess the predictive value of early-stage physiological time-series (PTS) data and non-interrogative electronic health record (EHR) signals, collected within 24 h of ICU admission, for traumatic brain injury (TBI) patient outcomes. METHODS: Using data from TBI patients in the multi-center eICU database, we focused on in-hospital mortality, neurological status based on the Glasgow Coma Score (mGCS) motor subscore at discharge, and prolonged ICU stay (PLOS). Three machine learning (ML) models were developed, utilizing EHR features, PTS signals collected 24 h after ICU admission, and their combination. External validation was performed using the MIMIC III dataset, and interpretability was enhanced using the Shapley Additive Explanations (SHAP) algorithm. RESULTS: The analysis included 1085 TBI patients. Compared to individual models and existing scoring systems, the combination of EHR and PTS features demonstrated comparable or even superior performance in predicting in-hospital mortality (AUROC = 0.878), neurological outcomes (AUROC = 0.877), and PLOS (AUROC = 0.835). The model's performance was validated in the MIMIC III dataset, and SHAP algorithms identified six key intervention points for EHR features related to prognostic outcomes. Moreover, the EHR results (All AUROC >0.8) were translated into online tools for clinical use. CONCLUSION: Our study highlights the importance of early-stage PTS signals in predicting TBI patient outcomes. The integration of interpretable algorithms and simplified prediction tools can support treatment decision-making, contributing to the development of accurate prediction models and timely clinical intervention.

Dilemmas and prospects of artificial intelligence technology in the data management of medical informatization in China: A new perspective on SPRAY-type AI applications.

Objectives: This study aims to address the critical challenges of data integrity, accuracy, consistency, and precision in the application of electronic medical record (EMR) data within the healthcare sector, particularly within the context of Chinese medical information data management. The research seeks to propose a solution in the form of a medical metadata governance framework that is efficient and suitable for clinical research and transformation. Methods: The article begins by outlining the background of medical information data management and reviews the advancements in artificial intelligence (AI) technology relevant to the field. It then introduces the "Service, Patient, Regression, base/Away, Yeast" (SPRAY)-type AI application as a case study to illustrate the potential of AI in EMR data management. Results: The research identifies the scarcity of scientific research on the transformation of EMR data in Chinese hospitals and proposes a medical metadata governance framework as a solution. This framework is designed to achieve scientific governance of clinical data by integrating metadata management and master data management, grounded in clinical practices, medical disciplines, and scientific exploration. Furthermore, it incorporates an information privacy security architecture to ensure data protection. Conclusion: The proposed medical metadata governance framework, supported by AI technology, offers a structured approach to managing and transforming EMR data into valuable scientific research outcomes. This framework provides guidance for the identification, cleaning, mining, and deep application of EMR data, thereby addressing the bottlenecks currently faced in the healthcare scenario and paving the way for more effective clinical research and data-driven decision-making.

Charge Oscillations in Bilayer Graphene Quantum Confinement Devices.

Quantum confinement structures are building blocks of quantum devices in fundamental physics exploration and technological applications. In this work, we fabricate dual-gated bilayer graphene Fabry-Pérot quantum Hall interferometers employing two different gating strategies and conduct finite element simulations to understand the electrostatics of the confinement structures and to guide device design and fabrication. We observe two types of resistance oscillations arising from the charging of quantum dots formed inside the interferometers. We obtain the size, location, and charging energy of the dots by measuring the dependence of the oscillations on the magnetic field, gate voltages, and dc bias. We analyze and discuss the origin of the quantum dots and their impact on quantum Hall edge state backscattering and interference. Insights gained in these studies shed light on the construction of van der Waals quantum confinement devices.

Machine Learning-Based Screening of Risk Factors and Prediction of Deep Vein Thrombosis and Pulmonary Embolism After Hip Arthroplasty.

Prophylactic anticoagulation is a standard strategy for patients undergoing total hip arthroplasty (THA) to prevent deep venous thromboembolism (DVT) and pulmonary embolism (PE). Nevertheless, some patients still experience these complications during their hospital stay. Current risk assessment methods like the Caprini and Geneva scores are not specifically designed for THA and may not accurately predict DVT or PE postoperatively. This study used machine learning techniques to establish models for early diagnosis of DVT and PE in patients undergoing THA. Data were collected from 1481 patients who received perioperative prophylactic anticoagulation. Model establishment and parameter tuning were performed using a training set and evaluated using a test set. Among the models, extreme gradient boosting (XGBoost) performed the best, with an area under the receiver operating characteristic curve (AUC) of 0.982, sensitivity of 0.913, and specificity of 0.998. The main features used in the XGBoost model were direct and indirect bilirubin, partial activation prothrombin time, prealbumin, creatinine, D-dimer, and C-reactive protein. Shapley Additive Explanations analysis was conducted to further analyze these features. This study presents a model for early diagnosis DVT or PE after THA and demonstrates bilirubin could be a potential predictor in the assessment of DVT or PE. Compared to traditional risk assessment, XGBoost has a high sensitivity and specificity to predict DVT and PE in the clinical setting. Furthermore, the results of this study were converted into a web calculator that can be used in clinical practice.

Fibroblast growth factor 21 attenuates ventilator-induced lung injury by inhibiting the NLRP3/caspase-1/GSDMD pyroptotic pathway.

BACKGROUND: Ventilator-induced lung injury (VILI) is caused by overdistension of the alveoli by the repetitive recruitment and derecruitment of alveolar units. This study aims to investigate the potential role and mechanism of fibroblast growth factor 21 (FGF21), a metabolic regulator secreted by the liver, in VILI development. METHODS: Serum FGF21 concentrations were determined in patients undergoing mechanical ventilation during general anesthesia and in a mouse VILI model. Lung injury was compared between FGF21-knockout (KO) mice and wild-type (WT) mice. Recombinant FGF21 was administrated in vivo and in vitro to determine its therapeutic effect. RESULTS: Serum FGF21 levels in patients and mice with VILI were significantly higher than in those without VILI. Additionally, the increment of serum FGF21 in anesthesia patients was positively correlated with the duration of ventilation. VILI was aggravated in FGF21-KO mice compared with WT mice. Conversely, the administration of FGF21 alleviated VILI in both mouse and cell models. FGF21 reduced Caspase-1 activity, suppressed the mRNA levels of Nlrp3, Asc, Il-1ß, Il-18, Hmgb1 and Nf-κb, and decreased the protein levels of NLRP3, ASC, IL-1ß, IL-18, HMGB1 and the cleaved form of GSDMD. CONCLUSIONS: Our findings reveal that endogenous FGF21 signaling is triggered in response to VILI, which protects against VILI by inhibiting the NLRP3/Caspase-1/GSDMD pyroptosis pathway. These results suggest that boosting endogenous FGF21 or the administration of recombinant FGF21 could be promising therapeutic strategies for the treatment of VILI during anesthesia or critical care.

A Review on the Progress of Optoelectronic Devices Based on TiO2 Thin Films and Nanomaterials.

Titanium dioxide (TiO2) is a kind of wide-bandgap semiconductor. Nano-TiO2 devices exhibit size-dependent and novel photoelectric performance due to their quantum limiting effect, high absorption coefficient, high surface-volume ratio, adjustable band gap, etc. Due to their excellent electronic performance, abundant presence, and high cost performance, they are widely used in various application fields such as memory, sensors, and photodiodes. This article provides an overview of the most recent developments in the application of nanostructured TiO2-based optoelectronic devices. Various complex devices are considered, such as sensors, photodetectors, light-emitting diodes (LEDs), storage applications, and field-effect transistors (FETs). This review of recent discoveries in TiO2-based optoelectronic devices, along with summary reviews and predictions, has important implications for the development of transitional metal oxides in optoelectronic applications for researchers.

Utilizing Metagenomic Next-Generation Sequencing (mNGS) for Rapid Pathogen Identification and to Inform Clinical Decision-Making: Results from a Large Real-World Cohort.

INTRODUCTION: Clinical metagenomic next-generation sequencing (mNGS) has proven to be a powerful diagnostic tool in pathogen detection. However, its clinical utility has not been thoroughly evaluated. METHODS: In this single-center prospective study at the First Affiliated Hospital of Soochow University, a total of 228 samples from 215 patients suspected of having acute or chronic infections between June 2018 and December 2018 were studied. Samples that met the mNGS quality control (QC) criteria (N = 201) were simultaneously analyzed using conventional tests (CTs), including multiple clinical microbiological tests and real-time PCR (if applicable). RESULTS: Pathogen detection results of mNGS in the 201 QC-passed samples were compared to CTs and exhibited a sensitivity of 98.8%, specificity of 38.5%, and accuracy of 87.1%. Specifically, 109 out of 160 (68.1%) CT+/mNGS+ samples exhibited concordant results at the species/genus level, 25 samples (15.6%) showed overlapping results, while the remaining 26 samples (16.3%) had discordant results between the CT and mNGS assays. In addition, mNGS could identify pathogens at the species level, whereas only the genera of some pathogens could be identified by CT. In this cohort, mNGS results were used to guide treatment plans in 24 out of 41 cases that had available follow-up information, and the symptoms were improved in over 70% (17/24) of them. CONCLUSION: Our data demonstrated the analytic performance of our mNGS pipeline for pathogen detection using a large clinical cohort and strongly supports the notion that in clinical practice, mNGS represents a valuable supplementary tool to CTs to rapidly determine etiological factors of various types of infection and to guide treatment decision-making.

Anomalous quantized plateaus in two-dimensional electron gas with gate confinement.

Quantum information can be coded by the topologically protected edges of fractional quantum Hall (FQH) states. Investigation on FQH edges in the hope of searching and utilizing non-Abelian statistics has been a focused challenge for years. Manipulating the edges, e.g. to bring edges close to each other or to separate edges spatially, is a common and essential step for such studies. The FQH edge structures in a confined region are typically presupposed to be the same as that in the open region in analysis of experimental results, but whether they remain unchanged with extra confinement is obscure. In this work, we present a series of unexpected plateaus in a confined single-layer two-dimensional electron gas (2DEG), which are quantized at anomalous fractions such as 9/4, 17/11, 16/13 and the reported 3/2. We explain all the plateaus by assuming surprisingly larger filling factors in the confined region. Our findings enrich the understanding of edge states in the confined region and in the applications of gate manipulation, which is crucial for the experiments with quantum point contact and interferometer.

Aharonov-Bohm Oscillations in Bilayer Graphene Quantum Hall Edge State Fabry-Pérot Interferometers.

Bernal-stacked bilayer graphene exhibits a wealth of interaction-driven phenomena, including robust even-denominator fractional quantum Hall states. We construct Fabry-Pérot interferometers using a split-gate design and present measurements of the Aharonov-Bohm oscillations. The edge state velocity is found to be approximately 6 × 104 m/s at filling factor ν = 2 and decreases with increasing filling factor. The dc bias and temperature dependence of the interference point to electron-electron interaction induced decoherence mechanisms. These results pave the way for the quest of fractional and non-Abelian braiding statistics in this promising device platform.

Huc-MSCs-derived exosomes attenuate inflammatory pain by regulating microglia pyroptosis and autophagy via the miR-146a-5p/TRAF6 axis.

BACKGROUND: Chronic inflammatory pain significantly reduces the quality of life and lacks effective interventions. In recent years, human umbilical cord mesenchymal stem cells (huc-MSCs)-derived exosomes have been used to relieve neuropathic pain and other inflammatory diseases as a promising cell-free therapeutic strategy. However, the therapeutic value of huc-MSCs-derived exosomes in complete Freund's adjuvant (CFA)-induced inflammatory pain remains to be confirmed. In this study, we investigated the therapeutic effect and related mechanisms of huc-MSCs-derived exosomes in a chronic inflammatory pain model. METHODS: C57BL/6J male mice were used to establish a CFA-induced inflammatory pain model, and huc-MSCs-derived exosomes were intrathecally injected for 4 consecutive days. BV2 microglia cells were stimulated with lipopolysaccharide (LPS) plus adenosine triphosphate (ATP) to investigate the effect of huc-MSCs-derived exosomes on pyroptosis and autophagy. Bioinformatic analysis and rescue experiments were used to demonstrate the role of miR-146a-5p/ TRAF6 in regulating pyroptosis and autophagy. Western blotting, RT-qPCR, small interfering RNA and Yo-Pro-1 dye staining were performed to investigate the related mechanisms. RESULTS: Huc-MSCs-derived exosomes alleviated mechanical allodynia and thermal hyperalgesia in CFA-induced inflammatory pain. Furthermore, huc-MSCs-derived exosomes attenuated neuroinflammation by increasing the expression of autophagy-related proteins (LC3-II and beclin1) and inhibiting the activation of NLRP3 inflammasomes in the spinal cord dorsal horn. In vitro, NLRP3 inflammasome components (NLRP3, caspase1-p20, ASC) and gasdermin D (GSDMD-F, GSDMD-N) were inhibited in BV2 cells pretreated with huc-MSCs-derived exosomes. Western blot and Yo-Pro-1 dye staining demonstrated that 3-MA, an autophagy inhibitor, weakened the protective effect of huc-MSCs-derived exosomes on BV2 cell pyroptosis. Importantly, huc-MSCs-derived exosomes transfected with miR-146a-5p mimic promoted autophagy and inhibited BV2 cell pyroptosis. TRAF6, as a target gene of miR-146a-5p, was knocked down via small-interfering RNA, which increased pyroptosis and inhibited autophagy. CONCLUSION: Huc-MSCs-derived exosomes attenuated inflammatory pain via miR-146a-5p/TRAF6, which increased the level of autophagy and inhibited pyroptosis.

The impact of COVID-19 on Emergency Department length of stay for urgent and life-threatening patients.

OBJECTIVES: To determine the impact of the Coronavirus disease-2019 (COVID-19) pandemic on the length of stay (LOS) and prognosis of patients in the resuscitation area. METHODS: A retrospective analysis of case data of patients in the resuscitation area during the early stages of the COVID-19 pandemic (January 15, 2020- January 14, 2021) was performed and compared with the pre-COVID-19 period (January 15, 2019 - January 14, 2020) in the First Affiliated Hospital of Soochow University. The patients' information, including age, sex, length of stay, and death, was collected. The Wilcoxon Rank sum test was performed to compare the LOS difference between the two periods. Fisher's Exact test and Chi-Squared test were used to analyze the prognosis of patients. The LOS and prognosis in different departments of the resuscitation area (emergency internal medicine, emergency surgery, emergency neurology, and other departments) were further analyzed. RESULTS: Of the total 8278 patients, 4159 (50.24%) were enrolled in the COVID-19 pandemic period group, and 4119 (49.76%) were enrolled pre-COVID-19 period group. The length of stay was prolonged significantly in the COVID-19 period compared with the pre-COVID-19 period (13h VS 9.8h, p < 0.001). The LOS in the COVID-19 period was prolonged in both emergency internal medicine (15.3h VS 11.3h, p < 0.001) and emergency surgery (8.7h VS 4.9h, p < 0.001) but not in emergency neurology or other emergency departments. There was no significant difference in mortality between the two cohorts (4.8% VS 5.3%, p = 0.341). CONCLUSION: The COVID-19 pandemic was associated with a significant increase in the length of resuscitation area stay, which may lead to resuscitation area crowding. The influence of the COVID-19 pandemic on patients of different departments was variable. There was no significant impact on the LOS of emergency neurology. According to different departments of the resuscitation area, the COVID-19 pandemic didn't significantly impact the prognosis of patients.

Implementation of multi-mode nursing insulation program for patients receiving surgery for spine tumor: a propensity score-matched analysis.

BACKGROUND: Spinal tumor surgery usually involved long operation time, large area of soft tissue resection and long wound, and was prone to hypothermia during the operation. Therefore, actively promoting insulation and optimizing the intraoperative insulation program have great potential in reducing the incidence of hypothermia and reducing the incidence of postoperative complications. In this study, we compared patients who did not implement multi-mode nursing insulation program (MNIP) with those who implemented MNIP, observing and comparing clinical outcomes, and complications in both groups, with the aim of developing an optimal management plan for the preoperative, intraoperative, and postoperative periods, respectively. METHODS: We selected 2 periods of 1 year, before (n = 120 patients) and after MINP implementation (n = 120 patients). Data were collected on patient demographics, operative, perioperative details, temperature changes, anesthesia recovery effect, incidence of postoperative wound infection, length of hospital stay and complications. PS analyses were used for dealing with confounding bias in this retrospective observational study. RESULTS: After PS matching, the outcomes of 120 well-balanced pairs of patients were compared (No-MNIP vs MNIP). There was no significant difference concerning the satisfaction survey. The results indicated that the MNIP had better insulation effect at 90 min, 120 min, 150 min after anesthesia induction and after surgery. There were 16 cases of complications in the No-MNIP group and 5 cases in the MNIP group postoperative, which have significant statistical difference. CONCLUSION: In this study, the incidence of intraoperative hypothermia was effectively reduced by adopting the multi-mode insulation scheme, thus reducing the incidence of incision infection and shortening the length of hospital stay of patients.

Attenuation of hepatic ischemia­reperfusion injury by adipose stem cell­derived exosome treatment via ERK1/2 and GSK­3ß signaling pathways.

Exosomes are an emerging therapeutic tool for the treatment of tissue injuries. In the present study, the protective effect of isolated exosomes from adipose­derived stem cells (ADSCs­exo) against hepatic ischemia­reperfusion (I/R) injury was explored. Hepatic I/R injury was achieved by inducing ischemia for 60 min followed by reperfusion for 2 and 6 h. Pre­treatment with ADSCs­exo revealed a significant reduction in necrosis and apoptosis in liver tissue induced by I/R injury. Hypoxic oxidative stress was managed by exosome­mediated reduced reactive oxygen species and increased superoxide dismutase that in turn protected mitochondrial damage and apoptosis. Reduction in inflammatory mediators such as IL­1ß and TNF­α was also observed and protection of hepatocytes from I/R injury was evidenced by a significant decrease in biochemical markers of liver damage (alanine transaminase, aspartate transaminase and lactate dehydrogenase). Exosomal prostaglandin E2 (PGE2)­mediated ERK1/2 and GSK­3ß phosphorylation were revealed to increase Bcl­2 and decrease Bax expression with mitochondrial permeability transition pore­inhibition which may be considered a prime mechanism of exosome­mediated hepatoprotection. In conclusion, our results indicated that ADSCs­exo pre­treatment is effective in protecting liver I/R injury.

Olfactory ecto-mesenchymal stem cell-derived exosomes ameliorate murine Sjögren's syndrome by modulating the function of myeloid-derived suppressor cells.

Sjögren's syndrome (SS) is a systemic autoimmune disease characterized by progressive inflammation and tissue damage in salivary glands and lacrimal glands. Our previous studies showed that myeloid-derived suppressor cells (MDSCs) exhibited impaired immunosuppressive function during disease progression in patients with SS and mice with experimental Sjögren's syndrome (ESS), but it remains unclear whether restoring the function of MDSCs can effectively ameliorate the development of ESS. In this study, we found that murine olfactory ecto-mesenchymal stem cell-derived exosomes (OE-MSC-Exos) significantly enhanced the suppressive function of MDSCs by upregulating arginase expression and increasing ROS and NO levels. Moreover, treatment with OE-MSC-Exos via intravenous injection markedly attenuated disease progression and restored MDSC function in ESS mice. Mechanistically, OE-MSC-Exo-secreted IL-6 activated the Jak2/Stat3 pathway in MDSCs. In addition, the abundant S100A4 in OE-MSC-Exos acted as a key factor in mediating the endogenous production of IL-6 by MDSCs via TLR4 signaling, indicating an autocrine pathway of MDSC functional modulation by IL-6. Taken together, our results demonstrated that OE-MSC-Exos possess therapeutic potential to attenuate ESS progression by enhancing the immunosuppressive function of MDSCs, possibly constituting a new strategy for the treatment of Sjögren's syndrome and other autoimmune diseases.

[Breakpoints of balanced chromosome 1 translocation is related to routine semen parameters].

Objective: To explore the influence of the breakpoints of balanced chromosome 1 translocation on routine semen parameters. METHODS: This study included 44,239 patients with male reproductive abnormalities from the outpatient department of Shandong University Hospital of Reproduction between January 2017 and December 2020. Through chromosome G banding karyotype analysis of peripheral blood, 57 of the patients were diagnosed as balanced chromosome 1 translocation carriers and underwent routine semen examination. RESULTS: Normal semen were found in 24.56% and abnormal semen in 75.44% of the 57 balanced chromosome 1 translocation carriers. The most common breakpoints were p36.2, p21, q31 and q32 for normal semen, q21, p13, p10, p21, p11, q24 and q32 for abnormal semen in the 11 cases of azoospermia, q21, p13, p32, p22 and p12 in the 5 patients with severe semen abnormalities such as oligospermia and asthenospermia, and q21, p13 and p10 in azoospermia and severe semen abnormalities. CONCLUSIONS: Balanced chromosome 1 translocation is closely related to routine semen parameters, and so is the breakpoint of chromosome 1 to the severity of semen abnormalities.

Risk factors and socio-economic burden in pancreatic ductal adenocarcinoma operation: a machine learning based analysis.

BACKGROUND: Surgical resection is the major way to cure pancreatic ductal adenocarcinoma (PDAC). However, this operation is complex, and the peri-operative risk is high, making patients more likely to be admitted to the intensive care unit (ICU). Therefore, establishing a risk model that predicts admission to ICU is meaningful in preventing patients from post-operation deterioration and potentially reducing socio-economic burden. METHODS: We retrospectively collected 120 clinical features from 1242 PDAC patients, including demographic data, pre-operative and intra-operative blood tests, in-hospital duration, and ICU status. Machine learning pipelines, including Supporting Vector Machine (SVM), Logistic Regression, and Lasso Regression, were employed to choose an optimal model in predicting ICU admission. Ordinary least-squares regression (OLS) and Lasso Regression were adopted in the correlation analysis of post-operative bleeding, total in-hospital duration, and discharge costs. RESULTS: SVM model achieved higher performance than the other two models, resulted in an AU-ROC of 0.80. The features, such as age, duration of operation, monocyte count, and intra-operative partial arterial pressure of oxygen (PaO2), are risk factors in the ICU admission. The protective factors include RBC count, analgesic pump dexmedetomidine (DEX), and intra-operative maintenance of DEX. Basophil percentage, duration of the operation, and total infusion volume were risk variables for staying in ICU. The bilirubin, CA125, and pre-operative albumin were associated with the post-operative bleeding volume. The operation duration was the most important factor for discharge costs, while pre-lymphocyte percentage and the absolute count are responsible for less cost. CONCLUSIONS: We observed that several new indicators such as DEX, monocyte count, basophil percentage, and intra-operative PaO2 showed a good predictive effect on the possibility of admission to ICU and duration of stay in ICU. This work provided an essential reference for indication in advance to PDAC operation.

EP4 activation ameliorates liver ischemia/reperfusion injury via ERK1/2­GSK3ß­dependent MPTP inhibition.

Prostaglandin E receptor subtype 4 (EP4) is widely distributed in the heart, but its role in hepatic ischemia/reperfusion (I/R), particularly in mitochondrial permeability transition pore (MPTP) modulation, is yet to be elucidated. In the present study, an EP4 agonist (CAY10598) was used in a rat model to evaluate the effects of EP4 activation on liver I/R and the mechanisms underlying this. I/R insult upregulated hepatic EP4 expression during early reperfusion. In addition, subcutaneous CAY10598 injection prior to the onset of reperfusion significantly increased hepatocyte cAMP concentrations and decreased serum ALT and AST levels and necrotic and apoptotic cell percentages, after 6 h of reperfusion. Moreover, CAY10598 protected mitochondrial morphology, markedly inhibited mitochondrial permeability transition pore (MPTP) opening and decreased liver reactive oxygen species levels. This occurred via activation of the ERK1/2­GSK3ß pathway rather than the janus kinase (JAK)2­signal transducers and activators of transcription (STAT)3 pathway, and resulted in prevention of mitochondria­associated cell injury. The MPTP opener carboxyatractyloside (CATR) and the ERK1/2 inhibitor PD98059 also partially reversed the protective effects of CAY10598 on the liver and mitochondria. The current findings indicate that EP4 activation induces ERK1/2­GSK3ß signaling and subsequent MPTP inhibition to provide hepatoprotection, and these observations are informative for developing new molecular targets and preventative therapies for I/R in a clinical setting.