Aim. To investigate whether hyperglycemia will aggravate hepatic ischemia reperfusion injury (HIRI) and the underlying mechanisms. Methods. Control and streptozotocin‐induced diabetic Sprague‐Dawley rats were subjected to partial hepatic ischemia reperfusion. Liver histology, transferase, inflammatory cytokines, and oxidative stress were assessed accordingly. Similarly, BRL‐3A hepatocytes were subjected to hypoxia/reoxygenation (H/R) after high (25 mM) or low (5.5 mM) glucose culture. Cell viability, reactive oxygen species (ROS), and activation of nuclear factor‐erythroid 2‐related factor 2 (Nrf2) and nuclear factor of kappa light polypeptide gene enhancer in B‐cells (NF‐κB) were determined. Results. Compared with control, diabetic rats presented more severe hepatic injury and increased hepatic inflammatory cytokines and oxidative stress. HIRI in diabetic rats could be ameliorated by pretreatment of N‐acetyl‐L‐cysteine (NAC) or apocynin. Excessive ROS generation and consequent Nrf2 and NF‐κB translocation were determined after high glucose exposure. NF‐κB translocation and its downstream cytokines were further increased in high glucose cultured group after H/R. While proper regulation of Nrf2 to its downstream antioxidases was observed in low glucose cultured group, no further induction of Nrf2 pathway by H/R after high glucose culture was identified. Conclusion. Hyperglycemia aggravates HIRI, which might be attributed to chronic oxidative stress and inflammation and potential malfunction of antioxidative system.

Background: Patients undergoing liver transplantation (LT) are at risk of perioperative neurocognitive dysfunction (PND), which significantly affects the patients’ prognosis. Objective: This study used machine learning (ML) algorithms with an aim to extract critical predictors and develop an ML model to predict PND among LT recipients. Methods: In this retrospective study, data from 958 patients who underwent LT between January 2015 and January 2020 were extracted from the Third Affiliated Hospital of Sun Yat-sen University. Six ML algorithms were used to predict post-LT PND, and model performance was evaluated using area under the receiver operating curve (AUC), accuracy, sensitivity, specificity, and F1-scores. The best-performing model was additionally validated using a temporal external dataset including 309 LT cases from February 2020 to August 2022, and an independent external dataset extracted from the Medical Information Mart for Intensive Care Ⅳ (MIMIC-Ⅳ) database including 325 patients. Results: In the development cohort, 201 out of 751 (33.5%) patients were diagnosed with PND. The logistic regression model achieved the highest AUC (0.799) in the internal validation set, with comparable AUC in the temporal external (0.826) and MIMIC-Ⅳ validation sets (0.72). The top 3 features contributing to post-LT PND diagnosis were the preoperative overt hepatic encephalopathy, platelet level, and postoperative sequential organ failure assessment score, as revealed by the Shapley additive explanations method. Conclusions: A real-time logistic regression model-based online predictor of post-LT PND was developed, providing a highly interoperable tool for use across medical institutions to support early risk stratification and decision making for the LT recipients.

Background. Liver transplantation leads to liver ischemia/reperfusion (I/R) injury, resulting in early graft dysfunction and failure. Exacerbations of oxidative stress and inflammatory response are key processes in the development of liver I/R injury. Intravenous anesthetic propofol potent effects on free radical scavenging and protects livers against I/R injury. However, the role and mechanism of propofol‐mediated hepatic protection in liver transplantation is poorly understood. The aim of this study was to evaluate the role of propofol postconditioning in the liver I/R injury after liver transplantation. Methods. Forty‐eight rats were randomly divided into six groups: rats receiving either sham operation or orthotopic autologous liver transplantation (OALT) in the absence or presence of propofol (high dose and low dose) postconditioning or intralipid control or VAS2870 (Nox2 special inhibitor). Eight hours after OALT or sham operation, parameters of organ injury, oxidative stress, inflammation, and NADPH‐associated proteins were assessed. Results. After OALT, severe liver pathological injury was observed that was associated with increases of serum AST and ALT, which were attenuated by propofol postconditioning. In addition, especially high dose of propofol postconditioning reduced TNF‐α, IL‐1β, IL‐6, TLR4, and NF‐κB inflammatory pathway, accompanied with decrease of neutrophil elastase activity, MPO activity, 8‐isoprotane, p47^phox and gp91^phox protein expressions, and increase of SOD activity. Inhibition of Nox2 by VAS2870 conferred similar protective effects in liver transplantation. Conclusion. Liver transplantation leads to severe inflammation and oxidative stress with NADPH oxidase activation. Propofol postconditioning reduces liver I/R injury after liver transplantation partly via inhibiting NADPH oxidase Nox2 and the subsequent inflammation and oxidative stress.

Background: Misplacement of double-lumen endobronchial tubes (DLTs) during bronchial intubation, especially when bronchoscopy guidance is not applicable, threatens effective lung isolation and brings about airway injury during reposition. We aimed to examine whether a novel maneuver called right tracheal displacement (RTD) can reduce left-sided DLT misplacement during first-attempt intubation without bronchoscopy guidance. Methods: Patients that underwent thoracic surgeries requiring one-lung ventilation during November 2020 to January 2021 were recruited and randomized into control and RTD group, with 54 cases in each group. The primary outcomes included the incidence of DLT misplacement and the time to complete desired bronchial intubation. The secondary outcomes included mucosal injury, sore throat and hoarseness upon emergence and at 24 h post-operatively. Result: The incidence of DLT misplacement in RTD group was significantly lower compared to control group (0% vs. 16.7%) The time to complete bronchial intubation was also significantly shortened in RTD group compared to control (52.88 ± 9.36 s vs. 63.04 ± 20.02 s). The incidence of mucosal injury, sore throat and hoarseness were comparable between two groups. Conclusion: RTD maneuver can effectively improve the success rate of first-attempt proper DLT positioning and shorten the time required by bronchial intubation. Trial registration: This prospective, double-blind, randomized study has completed the registration of the Chinese Clinical Trial Center at 2/11/2020 with the registration number ChiCTR2000040212. It was conducted from 26/11/2020 to 31/7/2021 in third affiliated hospital of Sun Yat-sen university.

DXM is widely used as an antifibrotic agent due to its protection of the lungs against fibrosis by inhibiting the production of inflammatory mediators. Many studies clearly indicated that the time point at which DXM treatment started, the dose and the duration of intervention are critical for exerting its antifibrotic effect. Exploring the role of DXM in the occurrence and development of PF at different stages is the fundamental purpose of this article. Lung fibrosis was persuaded in Sprague-Dawley rats by a single intratracheal BLM (5 mg/kg) injection. This experiment was divided into two animal experiments and treated with DXM following or after bleomycin administration respectively. The biochemical, histopathological and molecular alterations were studied in the lung tissues. A long course of low-dose DXM had the ability to ameliorate PF induced by BLM via decreasing inflammation and improving oxidative stress through modulation of TGF-β/Smad, PI3K/Akt/mTOR and NF-κB signaling pathway. Long course of low-dose DXM intake following or after bleomycin administration both had therapeutic effects on pulmonary fibrosis.

Background: Systemic inflammatory response syndrome (SIRS) is a serious postoperative complication among older adult surgical patients that frequently develops into sepsis or even death. Notably, the incidences of SIRS and sepsis steadily increase with age. It is important to identify the risk of postoperative SIRS for older adult patients at a sufficiently early stage, which would allow preemptive individualized enhanced therapy to be conducted to improve the prognosis of older adult patients. In recent years, machine learning (ML) models have been deployed by researchers for many tasks, including disease prediction and risk stratification, exhibiting good application potential. Objective: We aimed to develop and validate an individualized predictive model to identify susceptible and high-risk populations for SIRS in older adult patients to instruct appropriate early interventions. Methods: Data for surgical patients aged ≥65 years from September 2015 to September 2020 in 3 independent medical centers were retrieved and analyzed. The eligible patient cohort in the Third Affiliated Hospital of Sun Yat-sen University was randomly separated into an 80% training set (2882 patients) and a 20% internal validation set (720 patients). We developed 4 ML models to predict postoperative SIRS. The area under the receiver operating curve (AUC), F1 score, Brier score, and calibration curve were used to evaluate the model performance. The model with the best performance was further validated in the other 2 independent data sets involving 844 and 307 cases, respectively. Results: The incidences of SIRS in the 3 medical centers were 24.3% (876/3602), 29.6% (250/844), and 6.5% (20/307), respectively. We identified 15 variables that were significantly associated with postoperative SIRS and used in 4 ML models to predict postoperative SIRS. A balanced cutoff between sensitivity and specificity was chosen to ensure as high a true positive as possible. The random forest classifier (RF) model showed the best overall performance to predict postoperative SIRS, with an AUC of 0.751 (95% CI 0.709-0.793), sensitivity of 0.682, specificity of 0.681, and F1 score of 0.508 in the internal validation set and higher AUCs in the external validation-1 set (0.759, 95% CI 0.723-0.795) and external validation-2 set (0.804, 95% CI 0.746-0.863). Conclusions: We developed and validated a generalizable RF model to predict postoperative SIRS in older adult patients, enabling clinicians to screen susceptible and high-risk patients and implement early individualized interventions. An online risk calculator to make the RF model accessible to anesthesiologists and peers around the world was developed.