The innate immune system can be boosted in response to subsequent triggers by pre-exposure to microbes or microbial products, known as “trained immunity”. Compared to classical immune memory, innate trained immunity has several different features. Firstly, the molecules involved in trained immunity differ from those involved in classical immune memory. Innate trained immunity mainly involves innate immune cells (e.g., myeloid immune cells, natural killer cells, innate lymphoid cells) and their effector molecules (e.g., pattern recognition receptor (PRR), various cytokines), as well as some kinds of non-immune cells (e.g., microglial cells). Secondly, the increased responsiveness to secondary stimuli during innate trained immunity is not specific to a particular pathogen, but influences epigenetic reprogramming in the cell through signaling pathways, leading to the sustained changes in genes transcriptional process, which ultimately affects cellular physiology without permanent genetic changes (e.g., mutations or recombination). Finally, innate trained immunity relies on an altered functional state of innate immune cells that could persist for weeks to months after initial stimulus removal. An appropriate inducer could induce trained immunity in innate lymphocytes, such as exogenous stimulants (including vaccines) and endogenous stimulants, which was firstly discovered in bone marrow derived immune cells. However, mature bone marrow derived immune cells are short-lived cells, that may not be able to transmit memory phenotypes to their offspring and provide long-term protection. Therefore, trained immunity is more likely to be relied on long-lived cells, such as epithelial stem cells, mesenchymal stromal cells and non-immune cells such as fibroblasts. Epigenetic reprogramming is one of the key molecular mechanisms that induces trained immunity, including DNA modifications, non-coding RNAs, histone modifications and chromatin remodeling. In addition to epigenetic reprogramming, different cellular metabolic pathways are involved in the regulation of innate trained immunity, including aerobic glycolysis, glutamine catabolism, cholesterol metabolism and fatty acid synthesis, through a series of intracellular cascade responses triggered by the recognition of PRR specific ligands. In the view of evolutionary, trained immunity is beneficial in enhancing protection against secondary infections with an induction in the evolutionary protective process against infections. Therefore, innate trained immunity plays an important role in therapy against diseases such as tumors and infections, which has signature therapeutic effects in these diseases. In organ transplantation, trained immunity has been associated with acute rejection, which prolongs the survival of allografts. However, trained immunity is not always protective but pathological in some cases, and dysregulated trained immunity contributes to the development of inflammatory and autoimmune diseases. Trained immunity provides a novel form of immune memory, but when inappropriately activated, may lead to an attack on tissues, causing autoinflammation. In autoimmune diseases such as rheumatoid arthritis and atherosclerosis, trained immunity may lead to enhance inflammation and tissue lesion in diseased regions. In Alzheimer’s disease and Parkinson’s disease, trained immunity may lead to over-activation of microglial cells, triggering neuroinflammation even nerve injury. This paper summarizes the basis and mechanisms of innate trained immunity, including the different cell types involved, the impacts on diseases and the effects as a therapeutic strategy to provide novel ideas for different diseases.

Objective To establish a stable,reliable,and clinically relevant porcine model of endotoxin-induced acute respiratory distress syndrome(ARDS).Methods Ten 8-month-old male Bama minipigs were deeply sedated,followed by invasive mechanical ventilation and electrocardiographic monitoring.Lipopolysaccharide(LPS)was intravenously pumped at 600 μg/(kg·h)for 3 hours,then maintained at 15 μg/(kg·h)thereafter.Dynamic monitoring was performed at five time points after LPS injection(LPS 0,1,3,5,and 8 h),including arterial blood gas analysis and chest computed tomography(CT)scans.Pathological examination of lung tissues obtained via bronchoscopic biopsy(HE staining and transmission electron microscopy)was conducted.These indicators were comprehensively used to evaluate the success of the animal model.Results At 5 hours after LPS administration,8 minipigs developed symptoms such as skin cyanosis,elevated body temperature,and respiratory distress.The oxygenation index decreased to<300 mmHg.Chest CT scans showed diffuse pulmonary infiltrates.Histopathology revealed alveolar edema and hyaline membrane formation.Transmission electron microscopy demonstrated disruption of pulmonary blood-air barrier,depletion of lamellar bodies in type Ⅱ pneumocytes,inflammatory cell infiltration,and exudation of plasma proteins and fibrin.Compared with LPS 0 h,at LPS 8 h,the oxygenation index and arterial blood pH were significantly decreased(P<0.001),while blood lactic acid and serum potassium were significantly increased(P<0.05);serum calcium and base excess were significantly decreased(P<0.05),and the lung injury score based on HE-stained lung sections was significantly increased(P<0.01).Conclusion The porcine ARDS model established by continuous LPS injection can dynamically simulate the pathophysiological characteristics and typical pathological manifestations of clinical septic ARDS,making it an effective tool to study the pathogenesis,prevention,and treatment strategies of septic ARDS.

There are huge differences between tumor cells and normal cells in material metabolism, and tumor cells mainly show increased anabolism, decreased catabolism, and imbalance in substance metabolism. These differences provide the necessary material basis for the growth and reproduction of tumor cells, and also provide important targets for the treatment of tumors. Ferroptosis is an iron-dependent form of cell death characterized by an imbalance of iron-dependent lipid peroxidation and lipid membrane antioxidant systems in cells, resulting in excessive accumulation of lipid peroxide, causing damage to lipid membrane structure and loss of function, and ultimately cell death. The regulation of ferroptosis involves a variety of metabolic pathways, including glucose metabolism, lipid metabolism, amino acid metabolism, nucleotide metabolism and iron metabolism. In order for tumor cells to grow rapidly, their metabolic needs are more vigorous than those of normal cells. Tumor cells are metabolically reprogrammed to meet their rapidly proliferating material and energy needs. Metabolic reprogramming is mainly manifested in glycolysis and enhancement of pentose phosphate pathway, enhanced glutamine metabolism, increased nucleic acid synthesis, and iron metabolism tends to retain more intracellular iron. Metabolic reprogramming is accompanied by the production of reactive oxygen species and the activation of the antioxidant system. The state of high oxidative stress makes tumor cells more susceptible to redox imbalances, causing intracellular lipid peroxidation, which ultimately leads to ferroptosis. Therefore, in-depth study of the molecular mechanism and metabolic basis of ferroptosis is conducive to the development of new therapies to induce ferroptosis in cancer treatment. Ferroptosis, as a regulated form of cell death, can induce ferroptosis in tumor cells by pharmacologically or genetically targeting the metabolism of substances in tumor cells, which has great potential value in tumor treatment. This article summarizes the effects of cellular metabolism on ferroptosis in order to find new targets for tumor treatment and provide new ideas for clinical treatment.

Objective:To establish a predictive risk model for acute kidney injury (AKI) in acute myocardial infarction (AMI) patients based on machine learning algorithm and compare with a traditional logistic regression model.Methods:It was a retrospective study. The demographic data, laboratory examination, treatment regimen and medication of AMI patients from July 2011 to December 2016 in Beijing Anzhen Hospital, Capital Medical University were collected. The diagnostic criteria of AKI were based on the AKI diagnosis and treatment guidelines published by Kidney Diseases: Improving Global Outcomes in 2012. The selected AMI patients were randomly divided into training set (70%) and internal test set (30%) by simple random sampling. SelectFromModel and Lasso regression models were used to extract clinical parameters as predictors of AKI in AMI patients. Logistic regression model (model A) and machine learning algorithm (model B) were used to establish the risk prediction model of AKI in AMI patients. DeLong method was used to compare the area under the receiver-operating characteristic (ROC) curve ( AUC) between model A and model B for selecting the best model. Results:A total of 6 014 AMI patients were included in the study, with age of (58.4±11.7) years old and 3 414 males (80.5%). There were 674 patients (11.2%) with AKI. There were 4 252 patients (70.7%) in the training set and 1 762 patients (29.3%) in the test set. The selected twelve clinical parameters by the SelectFromModel and Lasso regression models included the number of myocardial infarctions, ST-segment elevation myocardial infarction, ventricular tachycardia, third degree atrioventricular block, decompensated heart failure at admission, admission serum creatinine, admission blood urea nitrogen, admission peak creatine kinase isoenzyme, diuretics, maximum daily dose of diuretics, days of diuretic use and statins. Logistic regression prediction model showed that AUC for the test set was 0.80 (95% CI 0.76-0.84). The machine learning algorithm model obtained AUC in the test set with 0.82 (95% CI 0.78-0.85).There was no significant difference in AUC between the two models ( Z=0.858, P=0.363), and AUC of the machine learning algorithm predictive model was slightly higher than that of the traditional logistic regression model. Conclusions:The prediction effect of AKI risk in AMI patients based on machine learning algorithm is similar to that of traditional logistic regression model, and the prediction accuracy of machine learning algorithm is better. The introduction of machine learning algorithm model may improve the ability to predict AKI risk.

Fluorescent surgical navigation has been widely used in liver and biliary surgery, including imaging of tumors, bile ducts, blood vessels, and other small lesions that cannot be identified by traditional methods. This helps surgeons obtain visual information during surgery and facilitates intraoperative decision-making. However, there are still many controversies in pancreatic tumor surgery, which is also the reason for the limited application of this technology in the pancreas at present. This article first summarizes the current status of the application of this technology in pancreatic tumor surgery. Based on our own experiences, we summarize the current problems of fluorescence imaging technology and propose corresponding optimization strategies. Finally, we look forward to its application prospects, hoping to provide a reference for the future application of fluorescence imaging technology in pancreatic tumors.

Objective To provide a theoretical basis for radiation health supervision through an analysis of the situation of computed tomography (CT) equipment quality control and CT room radiological protection in Guangdong Province, China in recent years. Methods We collected the data of 392 times of CT quality control and radiological protection testing by a third-party radiological health technical service institution in Guangdong Province from 2019 to 2021. We analyzed the levels of CT-owning hospitals, CT manufacturers, CT quality control test results, and the pass rate of radiation protection tests. Results The examined CT scanners were from different levels of hospitals in Guangdong Province, and were manufactured by nine major CT equipment manufacturers at home and abroad. The pass rate of CT room radiological protection was 99.88%, and the ambient dose equivalent rates of five monitoring points exceeded the limit, with four at the control room door and one at the shield wall of the room. The overall pass rate of CT equipment quality control was 99.49%, and the non-conforming parameters were the accuracy of positioning light and the deviation of reconstructed slice thickness. Conclusion In recent years, CT equipment quality control and room radiation protection in Guangdong Province have been at a high level.

This video presents a case of L4–5 unstable spondylolisthesis treated with full-endoscopic transforaminal lumbar interbody fusion (Endo-TLIF), emphasizing the GUARD (Glider Used as a Rotary Device) technique for nerve root protection. This innovative approach involves controlled rotation of the cage glider before cage insertion to minimize the risk of nerve root injury, a significant complication in Endo-TLIF procedures. The GUARD technique, validated in previous cadaveric studies, provides enhanced safety during cage insertion by protecting the nerve root. A 48-year-old woman with a 3-year history of progressive low back pain and bilateral lower extremity radiculopathy (right-sided predominance) was diagnosed with L4–5 unstable spondylolisthesis and spinal stenosis. After failure of conservative management, she underwent uniportal full-endoscopic facet-resecting transforaminal lumbar interbody fusion using the GUARD technique. Postoperatively, the patient experienced significant symptomatic improvement and resolution of radiculopathy, without any intraoperative nerve root injury or postoperative neurological deficits. This case demonstrates the effectiveness of the GUARD technique in reducing neurological complications and improving patient outcomes.

Objective: Uniportal full-endoscopic transforaminal lumbar interbody fusion (FE-TLIF) carries a unique risk of nerve traction and abrasion injury during cage insertion. This study aims to evaluate the clinical efficacy of the GUARD technique and delayed ligamentum flavectomy in reducing postoperative radicular pain and neurapraxia in patients undergoing uniportal FE-TLIF. Methods: A retrospective analysis was conducted on 45 patients with an average age of 53.9±12.4 years who underwent either FE facet-sparing TLIF (FE fs-TLIF) or FE facet-resecting TLIF (FE fr-TLIF). Patients were divided into 2 groups: the sentinel group (21 patients) using traditional sentinel pin techniques, and the GUARD group (24 patients) using the GUARD technique with delayed ligamentum flavectomy. Patient-reported outcomes included the visual analogue scale (VAS) for leg and back pain, and Oswestry Disability Index. Complication rates, including incidental durotomy, postoperative neurapraxia, and hematoma, were also documented. Results: Postoperative radicular pain in the legs was significantly reduced at 6 weeks in the GUARD group compared to the sentinel group (VAS: 2.201 vs. 3.267, p=0.021). The incidence of postoperative neurapraxia was markedly lower in the GUARD group (0% vs. 19%, p=0.047). Both groups showed similar improvements in disc height, segmental lordosis, and lumbar lordosis at the 1-year follow-up, with no significant differences in endplate injury or fusion rates. Conclusion The GUARD technique and delayed ligamentum flavectomy significantly enhance patient safety by reducing postoperative radicular pain and neurapraxia without incurring additional costs. These techniques are easy to learn and integrate into existing surgical workflows, offering a valuable improvement for surgeons performing FE-TLIF procedures.

Objective To establish an animal model of dampness-syndrome in mice (single model) and evaluate its characteristics of dampness-syndrome. The above-mentioned mice with dampness syndrome were used to construct mice model of ischemic stroke (double model) and observe the effect of dampness-pathogenic on the outcome of stroke. Methods Healthy C57BL/6J male mice were randomly divided into dampness-syndrome (including sham-surgery group and ischemic stroke group,with 10 mice in each group) and non dampness-syndrome groups (including sham-surgery group and ischemic stroke group,with 10 mice in each group). The dampness-syndrome group was fed with high-fat diet and the non dampness-syndrome group was fed with normal diet for 12 weeks. After the mice model of dampness-syndrome was successfully established,transient middle cerebral artery occlusion/reperfusion (tMCAO/R) surgery was used to replicate an ischemic stroke mice model. Evaluation indicators for dampness-syndrome mice model:the general status including body weight,morphology,posture,activity status,and physical characteristics,the histopathological observation of the aorta (oil red O staining,Masson-trichrome staining) and liver (HE staining,oil red O staining),electron microscopic observation of the tongue tissue (scanning electron microscopy,electron microscopy),blood lipid levels[total cholesterol(TC),triglycerides(TG)]and liver coefficient. Evaluation indicators for ischemic stroke mice model:neurological function score and the cerebral infarction volume ratio. Results Compared with the non dampness-syndrome group,the mice in the dampness-syndrome group showed an increased in body weight,poor hair color,sparse hair,fatigue and laziness,mental atrophy,anorexia and lethargy. It was observed that the aortic lumen was narrowed,the intima was significantly thickened,lipid plaque deposition was increased,and foam cells were visible. A large amount of red lipid droplets appeared in liver cells. There were obvious lipid infiltration and diffuse steatosis. Increased keratosis of the mucosal layer of tongue tissue,the thicker stratum corneum,lipofuscin,and bacteria on the tongue surface were found. Serum TG and TC levels significantly increased(P<0.01),and the liver coefficient significantly decreased (P<0.001). Compared with non dampness-syndrome group (sham-surgery group),neurological function score and the cerebral infarction volume ratio in dampness-syndrome ischemic stroke group obviously increased (P<0.001). Conclusion High-fat feeding for 12 weeks combined with tMCAO/R modeling can successfully establish a mice model with dampness-syndrome ischemic stroke,and the neurological function score and cerebral infarction volume in the dampness-syndrome ischemic stroke group was more severe than that in the non dampness-syndrome ischemic stroke group.

Traditional acute kidney injury (AKI) classifications, which are centered around semi-anatomical lines, can no longer capture the complexity of AKI. By employing strategies to identify predictive and prognostic enrichment targets, experts could gain a deeper comprehension of AKI’s pathophysiology, allowing for the development of treatment-specific targets and enhancing individualized care. Subphenotyping, which is enriched with AKI biomarkers, holds insights into distinct risk profiles and tailored treatment strategies that redefine AKI and contribute to improved clinical management. The utilization of biomarkers such as N-acetyl-β-D-glucosaminidase, tissue inhibitor of metalloprotease-2·insulin-like growth factor-binding protein 7, kidney injury molecule-1, and liver fatty acid-binding protein garnered significant attention as a means to predict subclinical AKI. Novel biomarkers offer promise in predicting persistent AKI, with urinary motif chemokine ligand 14 displaying significant sensitivity and specificity. Furthermore, they serve as predictive markers for weaning patients from acute dialysis and offer valuable insights into distinct AKI subgroups. The proposed management of AKI, which is encapsulated in a structured flowchart, bridges the gap between research and clinical practice. It streamlines the utilization of biomarkers and subphenotyping, promising a future in which AKI is swiftly identified and managed with unprecedented precision. Incorporating kidney biomarkers into strategies for early AKI detection and the initiation of AKI care bundles has proven to be more effective than using care bundles without these novel biomarkers. This comprehensive approach represents a significant stride toward precision medicine, enabling the identification of high-risk subphenotypes in patients with AKI.