The high incidence and mortality of acute kidney injury (AKI) have brought great challenges to global health. In recent years, China has made some achievements in the epidemiology, risk factors and treatment of AKI. However, further prevention and treatment are still facing difficulties. Based on current new ideas and research progress, this paper summarized and analyzed the management throughout the whole course of AKI, including AKI risk assessment, early prevention, early identification, treatment and follow-up. The aim is to make Chinese nephrologists realize the focus of AKI prevention and treatment, standardize the management of AKI, and explore the prevention and treatment strategy suitable for AKI in China.
Objective The management of pulmonary nodules is a common clinical problem, and this study constructed a nomogram model based on FUT7 methylation combined with CT imaging features to predict the risk of adenocarcinoma in patients with pulmonary nodules. Methods The clinical data of 219 patients with pulmonary nodules diagnosed by histopathology at the First Affiliated Hospital of Zhengzhou University from 2021 to 2022 were retrospectively analyzed. The FUT7 methylation level in peripheral blood were detected, and the patients were randomly divided into training set (n=154) and validation set (n=65) according to proportion of 7:3. They were divided into a lung adenocarcinoma group and a benign nodule group according to pathological results. Single-factor analysis and multi-factor logistic regression analysis were used to construct a prediction model in the training set and verified in the validation set. The receiver operating characteristic (ROC) curve was used to evaluate the discrimination of the model, the calibration curve was used to evaluate the consistency of the model, and the clinical decision curve analysis (DCA) was used to evaluate the clinical application value of the model. The applicability of the model was further evaluated in the subgroup of high-risk CT signs (located in the upper lobe, vascular sign, and pleural sign). Results Multivariate logistic regression analysis showed that female, age, FUT7_CpG_4, FUT7_CpG_6, sub-solid nodules, lobular sign and burr sign were independent risk factors for lung adenocarcinoma (P<0.05). A column-line graph prediction model was constructed based on the results of the multifactorial analysis, and the area under the ROC curve was 0.925 (95%CI 0.877 - 0.972 ), and the maximum approximate entry index corresponded to a critical value of 0.562, at which time the sensitivity was 89.25%, the specificity was 86.89%, the positive predictive value was 91.21%, and the negative predictive value was 84.13%. The calibration plot predicted the risk of adenocarcinoma of pulmonary nodules was highly consistent with the risk of actual occurrence. The DCA curve showed a good clinical net benefit value when the threshold probability of the model was 0.02 - 0.80, which showed a good clinical net benefit value. In the upper lobe, vascular sign and pleural sign groups, the area under the ROC curve was 0.903 (95%CI 0.847 - 0.959), 0.897 (95%CI 0.848 - 0.945), and 0.894 (95%CI 0.831 - 0.956). Conclusions This study developed a nomogram model to predict the risk of lung adenocarcinoma in patients with pulmonary nodules. The nomogram has high predictive performance and clinical application value, and can provide a theoretical basis for the diagnosis and subsequent clinical management of pulmonary nodules.
Unhealthy diet, habits and drug abuse cause a variety of liver diseases, including steatohepatitis, liver fibrosis, liver cirrhosis and liver cancer, which seriously affect human health. The fabrication of highly simulated cell models in vitro is important in the treatment of liver diseases and drug development. This article summarized the common strategies for the construction of liver pathology models in vitro. It introduced four typical cell models in vitro related to liver disease and provided a reference for the study of liver disease models.
Objective To explore key genes and mechanisms of depression aggravating Crohn disease. Methods In March 2023, the Public Health Genomics and Precision Health Knowledge Base and Gene Expression Omnibus database were used to identify the overlapping differentially expressed genes between Crohn disease and depression and the key genes were screened by Metascape, STRING, Cytoscape, and protein interaction network analysis. The Gene Expression Omnibus database was used to analyze the correlations between key genes and clinical pathologies such as Crohn Disease Endoscopic Index of Severity and intestinal microvilli length. Results There were 137 overlapping differentially expressed genes between Crohn disease and depression, and 25 key genes were further screened out. Among them, CREB1, FKBP5, MAPT, NTSR1, OXTR, PROK2, POMC, HTR2B, and PPARGC1A genes were significantly correlated with multiple clinical parameters. The functions of PROK2 and PROK2-related genes were mainly enriched in neutrophil and granulocyte migration, neutrophil and granulocyte chemotaxis, etc. Conclusions There are 25 key genes, especially CREB1, FKBP5, MAPT, NTSR1, OXTR, PROK2, POMC, HTR2B, and PPARGC1A, that possibly contribute to the establishment and deterioration of Crohn disease caused by depressive disorder. Among these genes, PROK2 showes the possibility of regulating immune cell (neutrophils and CD8+ T cells) infiltration.
Non-invasive biomarkers, due to their non-invasive and safe characteristics, hold significant potential for the diagnosis and prognosis of epilepsy. This review summarizes the research progress and future directions of non-invasive biomarkers for epilepsy, encompassing electrophysiological, imaging, biochemical, and genetic markers, and discusses biomarkers for specific types of epilepsy, such as structural lesion-related epilepsy, infection and inflammation-related epilepsy, autoimmune epilepsy, endocrine hormone-related epilepsy, and metabolic epilepsy, to facilitate their clinical application.
Breast cancer is a malignant tumor with the highest morbidity and mortality in female in recent years, and it is a complex disease that affects human health. Studies have shown that dynamic network biomarkers (DNB) can effectively identify critical states at which complex diseases such as breast cancer change from a normal state to a disease state. However, the traditional DNB method requires data from multiple samples in the same disease state, which is usually unachievable in clinical diagnosis. This paper quantitatively analyzes the time series data of MCF-7 breast cancer cells and finds the DNB module of a single sample in the time series based on landscape DNB (L-DNB) method. Then, a comprehensive index is constructed to detect its early warning signals to determine the critical state of breast cancer cell differentiation. The results of this study may be of great significance for the prevention and early diagnosis of breast cancer. It is expected that this paper can provide references for the related research of breast cancer.
ObjectiveTo analyze the current development of researches on biomarkers for predicting the efficacy of immunotherapy in non-small cell lung cancer and to provide reference for subsequent studies. MethodsStudies on biomarkers for predicting the efficacy of immunotherapy for non-small cell lung cancer indexed in the Web of Science Core Collection from 2017 to 2021 were searched by computer. The annual distribution, journals, authors, countries, institutions, and keywords of studies were visualized and analyzed by CiteSpace. ResultsA total of 426 studies were collected, including 298 articles and 128 reviews. The average number of published studies was about 85, and increased year by year. PD-L1 expression, tumor mutational burden, tumor microenvironment and liquid biopsy were hot keywords in this field. ConclusionIn the future, combination of biomarkers in the liquid biopsy and tumor microenvironment with radiomics analysis will be the research hotspot and frontier in this field for more accurate assessment with tumor-related signatures such as lymphocytic immune status and characteristics of tumor lesions in non-small cell lung cancer patients.
The human gut microbiota regulates many host pathophysiological processes including metabolic, inflammatory, immune and cellular responses. In recent years, the incidence and mortality of lung cancer have increased rapidly, which is one of the biggest challenges in the field of cancer treatment today, especially in non-small cell lung cancer. Animal models and clinical studies have found that the gut microbiota of non-small cell lung cancer patients is significantly changed compared with the healthy people. The gut microbiota and metabolites can not only play a pro-cancer or tumor suppressor role by regulating immune, inflammatory responses and so on, but also be related with radiotherapy and chemotherapy of non-small cell lung cancer and the resistance of immunotherapy. Therefore, gut microbiota and related metabolites can be both potential markers for early diagnosis and prognosis in patients with non-small cell lung cancer and novel therapeutic targets for targeted drugs. This study will review the latest research progress of effect of gut microbiota on non-small cell lung cancer, and provide a new diagnosis and treatment ideas for non-small cell lung cancer.
Objective To investigate the impact and mechanisms of periostin (POSTN), Krebs von den Lungen-6 (KL-6), pulmonary surfactant protein A (SP-A), and pulmonary surfactant protein D (SP-D) on the diagnosis and disease assessment of idiopathic pulmonary fibrosis (IPF), and conduct a comparative analysis. Methods From October 2022 to October 2023, a total of 55 patients diagnosed with IPF and treated at the Third Affiliated Hospital of Anhui Medical University were enrolled as an IPF group. Additionally, 30 patients with bacterial pneumonia and 30 healthy individuals undergoing concurrent health examinations during the same period were selected as a pneumonia control group and a healthy control group, respectively. All participants underwent enzyme-linked immunosorbent assay to measure serum levels of POSTN, KL-6, SP-A, and SP-D, along with pulmonary function tests. The IPF patients also underwent high-resolution computed tomography (HRCT) and echocardiography to quantify HRCT scores and pulmonary artery systolic pressure (PASP). Receiver operating characteristic (ROC) curves were plotted to analyze the significance of serum POSTN, KL-6, SP-A, and SP-D levels in IPF diagnosis. Pearson and Spearman correlation tests were used to analyze the relationships between these biomarkers and pulmonary function, PASP, and HRCT scores. Results Serum concentrations of POSTN, KL-6, SP-A, and SP-D were significantly elevated in the IPF group compared with the pneumonia group and the healthy controls (P<0.05), while serum levels of SP-A and SP-D were notably higher in the pneumonia group compared with the healthy control group (P<0.05). Within the IPF group, serum POSTN levels were negatively correlated with forced expiratory volume in the first second as a percentage of predicted value (FEV1%pred) and diffusion capacity of the lung for carbon monoxide as a percentage of predicted value (DLCO%pred) (P<0.05); KL-6 and SP-D levels were also negatively correlated with FEV1%pred, forced vital capacity as a percentage of predicted value (FVC%pred), and DLCO%pred (P<0.05); and the concentration of SP-A was negatively correlated with DLCO%pred and positively correlated with PASP (P<0.05). Additionally, serum levels of POSTN, KL-6, and SP-A in the IPF group showed significant positive associations with HRCT scores (P<0.01). Conclusions POSTN is a valuable serum biomarker for IPF, exhibiting the highest sensitivity and specificity among the four serum markers, with diagnostic performance superior to KL-6, SP-A, and SP-D. POSTN, KL-6, SP-A, and SP-D can all be used for the diagnosis and assessment of IPF.
Objective To investigate the serum level of surfactant protein D ( SP-D) in patients with chronic obstructive pulmonary disease ( COPD) and its clinical significance. Methods Serumlevels of SP-D in patients with acute exacerbations of COPD ( n = 29) , stable COPD ( n = 26) , and control subjects ( n = 19 ) were measured by ELISA. Multiple regression modeling was performed to determine the independent relationship between SP-D and lung function variables. Results The serum SP-D levels were significantly increased in the patients who experienced an acute exacerbation [ ( 70. 6 ±20. 7) ng/mL] compared with the patients with stable COPD and the control subjects [ ( 47. 9 ±13. 3) ng/mL and ( 31. 2 ±11. 4) ng/mL] ( both P lt; 0. 01) . The serum SP-D levels in the patients with stable COPD increased significantly than the control subjects ( P lt; 0. 01) . Smoking index and staging of COPD were positively related to SP-D level. Serum SP-D levels were also found to be inversely related to FEV1% pred in stable COPD. Conclusion Serum SP-D may be a potential diagnostic and staging biomarker for COPD.