Polymyxin is an essential antibiotic for treating multidrug-resistant Gram-negative bacterial infections； however， its significant nephrotoxicity greatly limits its clinical application. To enhance its safety and improve patient outcomes， the study of novel biomarkers for the early prediction of polymyxin-associated acute kidney injury is critically important. Novel biomarkers， such as cystatin C， kidney injury molecule-1， neutrophil gelatinase-associated lipocalin， N-acetyl-β-glucosaminidase， β2- microglobulin， have shown obvious advantages in the early prediction of polymyxin-associated acute kidney injury. Compared to traditional biomarkers， these biomarkers can provide sensitive and specific diagnostic information in the early stages of kidney injury， helping to optimize individualized treatment plans and reduce clinical risks. However， the high cost of detection and complex operation still limit their clinical promotion. Future research should focus on optimizing the detection technology of new biomarkers， simplifying the operation process and reducing costs， while conducting multi-center， large-scale randomized controlled trials to systematically evaluate the sensitivity and specificity of various novel biomarkers， in order to promote their application in the field of prediction of renal injury in clinical practice.

OBJECTIVE To investigate the mechanism of gossypol acetic acid （GAA） in the treatment of uterine fibroids. METHODS Human leiomyoma cells SK-UT-1 were selected as objects to investigate the effects of different concentrations （5， 10， 20， 40， 80， 160 μmol/L） of GAA on the activities of cell proliferation. 4D-DIA proteomic detection and bioinformatics analysis were carried out to screen differential proteins. Gene ontology （GO） analysis and Kyoto Encyclopedia of Genes and Genomes （KEGG） signaling pathway analysis were performed. The expressions of top 3 proteins [N-myc downstream regulated gene 1 （NDRG1）， epidermal growth factor receptor feedback inhibitor 1 （ERRFI1）， CXC chemokine ligand 3 （CXCL3）] with differential fold changes in SK-UT-1 cells were determined. RESULTS 10-160 μmol/L GAA could significantly reduce the survival rate of SK- UT-1 cells （P＜0.05）. Proteomics results showed that a total of 921 differentially expressed proteins were obtained， including 254 up-regulated proteins and 667 down-regulated proteins. The differentially expressed proteins were mainly distributed in mitochondria， nucleus， extracellular matrix， etc. Bioinformatics results showed that differentially expressed proteins were mainly involved in signaling pathways such as PI3K/AKT （phosphoinositide 3-kinase/protein kinase B）， MAPK （mitogen-activated protein kinase）， TNF （tumor necrosis factor）， etc.， which mainly involved cell apoptosis， aging， and movement. GAA significantly decreased protein expressions of NDRG1 and CXCL3 （P＜0.05）， but increased protein expression of ERRFI1 （P＜0.05）. CONCLUSIONS The improvement effect of GAA on uterine fibroids may involve signaling pathways such as PI3K/AKT， MAPK， TNF， etc. It can improve the occurrence and development of uterine fibroids by downregulating the expressions of NDRG1 and CXCL3 proteins， upregulating the expression of ERRFI1 protein， and affecting the proliferation and apoptosis of uterine fibroid cells.

Polymyxin is an essential antibiotic for treating multidrug-resistant Gram-negative bacterial infections； however， its significant nephrotoxicity greatly limits its clinical application. To enhance its safety and improve patient outcomes， the study of novel biomarkers for the early prediction of polymyxin-associated acute kidney injury is critically important. Novel biomarkers， such as cystatin C， kidney injury molecule-1， neutrophil gelatinase-associated lipocalin， N-acetyl-β-glucosaminidase， β2- microglobulin， have shown obvious advantages in the early prediction of polymyxin-associated acute kidney injury. Compared to traditional biomarkers， these biomarkers can provide sensitive and specific diagnostic information in the early stages of kidney injury， helping to optimize individualized treatment plans and reduce clinical risks. However， the high cost of detection and complex operation still limit their clinical promotion. Future research should focus on optimizing the detection technology of new biomarkers， simplifying the operation process and reducing costs， while conducting multi-center， large-scale randomized controlled trials to systematically evaluate the sensitivity and specificity of various novel biomarkers， in order to promote their application in the field of prediction of renal injury in clinical practice.

ObjectiveTo explore the therapeutic effect of Xuebijing injection （XBJ） on severe acute pancreatitis induced acute lung injury （SAP-ALI） by regulating formyl peptide receptors （FPRs）/nucleotide-binding oligomerization domain-like receptor 3 （NLRP3） inflammatory pathway. MethodsSixty rats were randomly divided into a sham group， a SAP-ALI model group， low-， medium-， and high-dose XBJ groups （4， 8， and 12 mL·kg^-1）， and a positive drug （BOC2， 0.2 mg·kg^-1） group. For the sham group， the pancreas of rats was only gently flipped after laparotomy， and then the abdomen was closed， while for the remaining five groups， SAP-ALI rat models were established by retrograde injection of 5% sodium taurocholate （Na-Tc） via the biliopancreatic duct. XBJ and BOC2 were administered via intraperitoneal injection once daily for 3 d prior to modeling and 0.5 h after modeling. Blood was collected from the abdominal aorta 6 h after the completion of modeling， and the expression of interleukin （IL）-1β， IL-6， and tumor necrosis factor-α （TNF-α） in plasma was measured by enzyme-linked immunosorbent assay （ELISA）. The amount of ascites was measured， and the dry-wet weight ratios of pancreatic and lung tissue were determined. Pancreatic and lung tissue was taken for hematoxylin-eosin （HE） staining to observe pathological changes and then scored. The protein expression levels of FPR1， FPR2， and NLRP3 in lung tissue were detected by the immunohistochemical method. Western blot was used to detect the expression of FPR1， FPR2， and NLRP3 in lung tissue. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） was used to detect the mRNA expression of FPR1， FPR2， and NLRP3 in lung tissue. ResultsCompared with the sham group， the SAP-ALI model group showed significantly decreased dry-wet weight ratio of lung tissue （P<0.01）， serious pathological changes of lung tissue， a significantly increased pathological score （P<0.01）， and significantly increased protein and mRNA expression levels of FPR1， FPR2， and NLRP3 in lung tissue （P<0.01）. After BOC2 intervention， the above detection indicators were significantly reversed （P<0.01）. After treatment with XBJ， the groups of different XBJ doses achieved results consistent with BOC2 intervention. ConclusionXBJ can effectively improve the inflammatory response of the lungs in SAP-ALI rats and reduce damage. The mechanism may be related to inhibiting the expression of FPRs and NLRP3 in lung tissue， which thereby reduces IL-1β and simultaneously antagonize the release of inflammatory factors IL-6 and TNF-α.

ObjectiveTo establish the fingerprints of 15 batches of Hengzhi Kechuan capsules， to quantitatively analyze 10 index components， and to evaluate the quality uniformity of samples from different batches. MethodsThe fingerprints and quantitative analysis of Hengzhi Kechuan capsules were established by a combination method of high performance liquid chromatography coupled with diode array detector and charged aerosol detector（HPLC-DAD-CAD）， adenosine， guanosine， vanillic acid， safflomin A， agarotetrol， naringin， hesperidin， militarine， ginsenoside Rb₁， and glycyrrhizic acid were selected as quality attribute indexes. A total of 15 batches of Hengzhi Kechuan capsules from 2022 to 2024（3 boxes per batch） were qualitatively and quantitatively analyzed， and the quality uniformity level of the manufacturers was characterized by parameters of intra-batch consistency（P_A） and inter-batch consistency（P_B）. The homogeneity and difference of quality attribute indexes of samples from different years were analyzed by heatmap clustering analysis. ResultsHPLC fingerprints and quantitative method of Hengzhi Kechuan capsules were established， and the methods could be used for qualitative and quantitative analysis of this preparation， which was found to be stable and reliable by method validation. The similarity of fingerprints of 15 batches of samples was 0.887-0.975， a total of 13 common peaks were calibrated， and 10 common peaks were designated， all of which were quality attribute index components. The results of quantitative analysis showed that the contents of the above 10 ingredients in the samples were 0.038-0.078， 0.115-0.251， 0.007-0.018， 0.291-0.673， 0.122-0.257， 0.887-1.905， 1.841-3.364， 1.412-2.450， 2.207-3.112， 0.650-1.161， respectively. And the contents of ginsenoside Rb₁ and glycyrrhizic acid met the limit requirements in the 2020 edition of Chinese Pharmacopoeia. For the samples from 15 batches， the P_A values of the 10 index components were all <10%， indicating good intra-batch homogeneity， and the P_B values ranged from 33.86% to 92.97%， suggesting that the inter-batch homogeneity was poor. Heatmap clustering analysis showed that the samples from different years were clustered into separate categories， and adenosine， guanosine， safflomin A， naringin， hesperidin and agarotetrol were the main differential components. ConclusionThe intra-annual quality uniformity of Hengzhi Kechuan capsules is good and the inter-annual quality uniformity is insufficient， which may be related to the quality difference of Pinellinae Rhizoma Praeparatum， Carthami Flos， Citri Sarcodactylis Fructus， Citri Reticulatae Pericarpium， Aquilariae Lignum Resinatum， Citri Fructus， etc. In this study， the fingerprint and multi-indicator determination method of Hengzhi Kechuan capsules was established， which can be used for more accurate and efficient quality control and standardization enhancement.

Houpo Qiwutang originated from the Synopsis of the Golden Chamber， and it consists of seven medicines： Magnoliae Officinalis Cortex， Rhei Radix et Rhizoma， Aurantii Fructus Immaturus， Cinnamomi Ramulus， Zingiberis Rhizoma Recens， Glycyrrhizae Radix et Rhizoma， and Jujubae Fructus. It is a basic formula for the treatment of abdominal fullness. Through the bibliometric method， the historical history， drug base， preparation and dosage， decoction method， and ancient and modern applications of Houpu Qiwu Tang were analyzed by means of textual research. The research finds that Houpu Qiwu Tang has been passed down through the generations in an orderly manner with fewer changes. The drug base of this formula is basically clear， and the base of Magnoliae Officinalis Cortex， Rhei Radix et Rhizoma， Cinnamomi Ramulus， Zingiberis Rhizoma Recens， and Jujubae Fructus is consistent with the 2020 edition of Chinese Pharmacopoeia. The mainstream base of Aurantii Fructus Immaturus is the dried young fruit of Citrus aurantium of Rutaceae family， and the historical mainstream base of Glycyrrhizae Radix et Rhizoma is the dried root of Glycyrrhiza uralensis of Leguminosae family. The modern dosage of this formula is 110.40 g of Magnoliae Officinalis Cortex， 41.40 g of Rhei Radix et Rhizoma， 69 g of Aurantii Fructus Immaturus， 27.60 g of Cinnamomi Ramulus， 69 g of Zingiberis Rhizoma Recens， 41.40 g of Glycyrrhizae Radix et Rhizoma， and 30 g of Jujubae Fructus. In addition， the decoction method is to add 2 000 mL of water with the above seven flavors of the medicine， boil it to 800 mL， and then take 160 mL in a warm state each time. The amount of the medicine taken for each time is 22.08 g of Magnoliae Officinalis Cortex， 8.28 g of Rhei Radix et Rhizoma， 13.80 g of Aurantii Fructus Immaturus， 5.52 g of Cinnamomi Ramulus， 13.80 g of Zingiberis Rhizoma Recens， 8.28 g of Glycyrrhizae Radix et Rhizoma， and 6 g of Jujubae Fructus. The modern application of this formula involves the digestive system， respiratory system， and urinary system. It is more advantageous in digestive system diseases such as early postoperative inflammatory bowel obstruction， functional dyspepsia， gastric pain， functional abdominal distension， and gastric reflux esophagitis. By comprehensively examining the key information of Houpu Qiwu Tang， this paper aims to provide literature support for the development and clinical application of this formula.

Objective: To analyze the spatio-temporal distribution of pulmonary tuberculosis (PTB) among students in Suzhou City, Jiangsu Province from 2015 to 2023, so as to provide the evidence for the prevention and control of PTB in schools. Methods: Data of PTB cases among students in Suzhou City from 2015 to 2023 were collected from Chinese Disease Prevention and Control Information System and Suzhou Report of Investigation and Disposal of Tuberculosis in Schools. The seasonal incidence of PTB among students was analyzed using seasonal index (SI). The spatio-temporal clustering characteristics of PTB among students were analyzed using spatial autocorrelation and retrospective spatio-temporal permutation scanning. Results: Totally 1 374 PTB cases among students were reported in Suzhou City from 2015 to 2023. PTB cases were reported in each month, and the SIs were 100.69%, 124.38%, 108.98%, 135.04%, 106.61% and 106.61% in April, May, July, September, October and November, respectively, indicating the prevalence of PTB among students. Spatial autocorrelation analysis showed there was a positive spatial correlation of PTB among students in 2019 and 2020 (Moran's I=0.053 and 0.089, both P<0.05). From 2015 to 2023, there were high-high clustering sites mainly in Hengtang Street and Shishan Street. Retrospective spatio-temporal permutation scanning showed a primary cluster in Hengtang Street, with aggregation time in 2017, and 6 secondary clusters covering 25 towns (streets). Conclusion From 2015 to 2023, the PTB cases among students in Suzhou City were mainly concentrated in summer and autumn, and were predominantly clustered in Hengtang Street and Shishan Street.

Obstructive sleep apnea (OSA) is an increasingly widespread sleep-breathing disordered disease, and is an independent risk factor for many high-risk chronic diseases such as hypertension, coronary heart disease, stroke, arrhythmias and diabetes, which is potentially fatal. The key to the prevention and treatment of OSA is early diagnosis and treatment, so the assessment and diagnostic technologies of OSA have become a research hotspot. This paper reviews the research progresses of severity assessment parameters and diagnostic technologies of OSA, and discusses their future development trends. In terms of severity assessment parameters of OSA, apnea hypopnea index (AHI), as the gold standard, together with the percentage of duration of apnea hypopnea (AH%), lowest oxygen saturation (LSpO₂), heart rate variability (HRV), oxygen desaturation index (ODI) and the emerging biomarkers, constitute a multi-dimensional evaluation system. Specifically, the AHI, which measures the frequency of sleep respiratory events per hour, does not fully reflect the patients’ overall sleep quality or the extent of their daytime functional impairments. To address this limitation, the AH%, which measures the proportion of the entire sleep cycle affected by apneas and hypopneas, deepens our understanding of the impact on sleep quality. The LSpO₂ plays a critical role in highlighting the potential severe hypoxic episodes during sleep, while the HRV offers a different perspective by analyzing the fluctuations in heart rate thereby revealing the activity of the autonomic nervous system. The ODI provides a direct and objective measure of patients’ nocturnal oxygenation stability by calculating the number of desaturation events per hour, and the biomarkers offers novel insights into the diagnosis and management of OSA, and fosters the development of more precise and tailored OSA therapeutic strategies. In terms of diagnostic techniques of OSA, the standardized questionnaire and Epworth sleepiness scale (ESS) is a simple and effective method for preliminary screening of OSA, and the polysomnography (PSG) which is based on recording multiple physiological signals stands for gold standard, but it has limitations of complex operations, high costs and inconvenience. As a convenient alternative, the home sleep apnea testing (HSAT) allows patients to monitor their sleep with simplified equipment in the comfort of their own homes, and the cardiopulmonary coupling (CPC) offers a minimal version that simply analyzes the electrocardiogram (ECG) signals. As an emerging diagnostic technology of OSA, machine learning (ML) and artificial intelligence (AI) adeptly pinpoint respiratory incidents and expose delicate physiological changes, thus casting new light on the diagnostic approach to OSA. In addition, imaging examination utilizes detailed visual representations of the airway’s structure and assists in recognizing structural abnormalities that may result in obstructed airways, while sound monitoring technology records and analyzes snoring and breathing sounds to detect the condition subtly, and thus further expands our medical diagnostic toolkit. As for the future development directions, it can be predicted that interdisciplinary integrated researches, the construction of personalized diagnosis and treatment models, and the popularization of high-tech in clinical applications will become the development trends in the field of OSA evaluation and diagnosis.

Objective By combining biological detection and imaging evaluation, a clinical prediction model is constructed based on a large cohort to improve the accuracy of distinguishing between benign and malignant pulmonary nodules. Methods A retrospective analysis was conducted on the clinical data of the 32 627 patients with pulmonary nodules who underwent chest CT and testing for 7 types of lung cancer-related serum autoantibodies (7-AABs) at our hospital from January 2020 to April 2024. The univariate and multivariate logistic regression models were performed to screen independent risk factors for benign and malignant pulmonary nodules, based on which a nomogram model was established. The performance of the model was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Results A total of 1 017 patients with pulmonary nodules were included in the study. The training set consisted of 712 patients, including 291 males and 421 females, with a mean age of (58±12) years. The validation set included 305 patients, comprising 129 males and 176 females, with a mean age of (58±13) years. Univariate ROC curve analysis indicated that the combination of CT and 7-AABs testing achieved the highest area under the curve (AUC) value (0.794), surpassing the diagnostic efficacy of CT alone (AUC=0.667) or 7-AABs alone (AUC=0.514). Multivariate logistic regression analysis showed that radiological nodule diameter, nodule nature, and CT combined with 7-AABs detection were independent predictors, which were used to construct a nomogram prediction model. The AUC values for this model were 0.826 and 0.862 in the training and validation sets, respectively, demonstrating excellent performance in DCA. Conclusion The combination of 7-AABs with CT significantly enhances the accuracy of distinguishing between benign and malignant pulmonary nodules. The developed predictive model provides strong support for clinical decision-making and contributes to achieving precise diagnosis and treatment of pulmonary nodules.

Objective To explore and verify the prognostic value of endothelial cells in glioblastoma. Methods Through bioinformatics analysis of the TCGA and CGGA databases, we screened endothelial cell-related markers in GBM single-cell data according to a series of criteria. Moreover, univariate Cox regression analysis was performed to obtain and screen endothelial cell prognosis-related markers and construct endothelial cell-related prognostic risk score. qPCR experiments was used to verify the differences in the expression of prognostic markers in GBM tissues and peritumoral normal brain tissues. Kaplan-Meier method was used to construct the survival curve to identify the prognostic efficacy of the prognostic risk score. Results A total of 2 115 prognostic genes of glioblastoma (GBM) were screened. Among them, 1 494 was upregulated and 621 was downregulated. Seven groups of cells were obtained after GBM single-cell sequencing analysis, including AC-like tumor cells, endothelial cells, monocytes/macrophages, NB-like tumor cells, neurons, OC-like tumor cells, and OPC-like tumor cells. According to the differential genes of endothelial cells and the corresponding screening criteria, four genes (DUSP6, STC1, VWA1, and TM4SF1) were screened for risk-score construction. The expression of the target gene in GBM tissues and normal brain tissues around the tumor was significantly up-regulated detected by qPCR. The risk score=0.171*DUSP6+0.144*STC1+0.041*VWA1−0.004*TM4SF1. Conclusion The glioblastoma endothelial cells’ risk score determined in this study can preferably predict the prognosis of patients.