ObjectiveTo investigate the value of preoperative dual-layer spectral detector CT （DLCT） parameters in predicting lymph node metastasis （LNM） of non-functional pancreatic neuroendocrine neoplasms （NF-pNENs）. MethodsA retrospective study was conducted on patients with pathologically confirmed NF-pNENs who underwent preoperative contrast-enhanced DLCT examination between September 2019 and July 2024. Regions of interest （ROIs） were manually delineated on three representative slices of the solid component of the lesion， and the mean values were recorded. Conventional CT parameters， monochromatic energy images （40 keV， 70 keV， 100 keV）， iodine concentration maps， and effective atomic number （Z_eff） maps in the pancreatic parenchymal phase and portal venous phase were acquired. A total of 34 parameters， including clinical characteristics， imaging features， conventional CT and DLCT quantitative parameters， were analyzed. Intergroup differences were compared between the LNM and non-LNM groups. Independent predictive factors were screened using logistic regression and least absolute shrinkage and selection operator （LASSO） regression. Receiver operating characteristic （ROC） curves were generated for each predictive model， and the area under the curve （AUC） was calculated to evaluate the predictive efficacy. ResultsA total of 82 patients with NF-pNENs were enrolled， including 37 males and 45 females， with a mean age of 49.7±14.7 years. Thirty patients were performed with LNM and 52 were with non-LNM. After univariate logistic regression， LASSO regression and multivariate stepwise logistic regression analyses， body mass index （BMI）， organ invasion， normalized CT value in the portal venous phase （nCTv） and normalized iodine concentration in the portal venous phase （nICv） were identified as independent predictive factors. The AUCs of the clinical-radiological qualitative model （BMI+organ invasion）， conventional CT model （nCTv）， DLCT model （nICv） and comprehensive model （organ invasion+nICv） were 0.815 （0.719， 0.910）， 0.750 （0.642， 0.858）， 0.829 （0.733， 0.925） and 0.865 （0.879， 0.953）， respectively. The comprehensive model combining clinical-radiological and DLCT characteristics exhibited superior predictive performance. ConclusionDLCT parameters are more effective than conventional CT parameters in predicting LNM in NF-pNENs， enabling non-invasive preoperative prediction and assisting clinical decision-making.

ObjectiveTo investigate the value of preoperative dual-layer spectral detector CT （DLCT） parameters in predicting lymph node metastasis （LNM） of non-functional pancreatic neuroendocrine neoplasms （NF-pNENs）. MethodsA retrospective study was conducted on patients with pathologically confirmed NF-pNENs who underwent preoperative contrast-enhanced DLCT examination between September 2019 and July 2024. Regions of interest （ROIs） were manually delineated on three representative slices of the solid component of the lesion， and the mean values were recorded. Conventional CT parameters， monochromatic energy images （40 keV， 70 keV， 100 keV）， iodine concentration maps， and effective atomic number （Z_eff） maps in the pancreatic parenchymal phase and portal venous phase were acquired. A total of 34 parameters， including clinical characteristics， imaging features， conventional CT and DLCT quantitative parameters， were analyzed. Intergroup differences were compared between the LNM and non-LNM groups. Independent predictive factors were screened using logistic regression and least absolute shrinkage and selection operator （LASSO） regression. Receiver operating characteristic （ROC） curves were generated for each predictive model， and the area under the curve （AUC） was calculated to evaluate the predictive efficacy. ResultsA total of 82 patients with NF-pNENs were enrolled， including 37 males and 45 females， with a mean age of 49.7±14.7 years. Thirty patients were performed with LNM and 52 were with non-LNM. After univariate logistic regression， LASSO regression and multivariate stepwise logistic regression analyses， body mass index （BMI）， organ invasion， normalized CT value in the portal venous phase （nCTv） and normalized iodine concentration in the portal venous phase （nICv） were identified as independent predictive factors. The AUCs of the clinical-radiological qualitative model （BMI+organ invasion）， conventional CT model （nCTv）， DLCT model （nICv） and comprehensive model （organ invasion+nICv） were 0.815 （0.719， 0.910）， 0.750 （0.642， 0.858）， 0.829 （0.733， 0.925） and 0.865 （0.879， 0.953）， respectively. The comprehensive model combining clinical-radiological and DLCT characteristics exhibited superior predictive performance. ConclusionDLCT parameters are more effective than conventional CT parameters in predicting LNM in NF-pNENs， enabling non-invasive preoperative prediction and assisting clinical decision-making.

With the widespread use of antibiotics, drug-resistant bacterial infections have become a significant threat to human health. Finding new antibacterial strategies that can effectively control drug-resistant bacterial infections has become an urgent task. Unlike small molecule drugs that target bacterial proteins, antisense oligonucleotide (ASO) can target genes related to bacterial resistance, pathogenesis, growth, reproduction and biofilm formation. By regulating the expression of these genes, ASO can inhibit or kill bacteria, providing a novel approach for the development of antibacterial drugs. To overcome the challenge of delivering antisense oligonucleotide into bacterial cells, various drug delivery systems have been applied in this field, including cell-penetrating peptides, lipid nanoparticles and inorganic nanoparticles, which have injected new momentum into the development of antisense oligonucleotide in the antibacterial realm. This review summarizes the current development of small nucleic acid drugs, the antibacterial mechanisms, targets, sequences and delivery vectors of antisense oligonucleotide, providing a reference for the research and development of antisense oligonucleotide in the treatment of bacterial infections.

Objective To investigate the potential factors influencing the occurrence of major adverse cardiovascular events (MACE) in patients with acute myocardial infarction (AMI) after percutaneous coronary intervention (PCI) and develop an efficient and accurate predictive model. Methods Clinical data of AMI patients treated in the emergency department of Jining Medical University Affiliated Hospital between January and December 2020 were retrospectively collected. Patients were divided into two groups based on the occurrence of in-hospital MACE,the MACE group and the non-MACE group. Clinical indicators of the two groups were compared,and statistically significant variables were selected for inclusion in a multivariate logistic regression analysis. Based on this analysis,a nomogram model was constructed to predict the risk of in-hospital MACE in AMI patients after PCI. The model's predictive accuracy was evaluated using the receiver operating characteristic (ROC) curve,and the goodness of fit was assessed using the Hosmer-Lemeshow test. Results A total of 583 patients were included after screening based on inclusion and exclusion criteria,of whom 85 (14.58％) experienced in-hospital MACE. Univariate analysis showed that compared to the non-MACE group,the MACE group had higher values for age,Killip classification,myoglobin (MYO),brain natriuretic peptide (BNP),white blood cell count (WBC),prothrombin time (PT),T-wave changes on electrocardiogram (ECG),abnormal wall motion on echocardiography,ischemia duration greater than 6 hours,the number of MACE before PCI,and left anterior descending artery stenosis. In contrast,the number of patients with a history of oral antiplatelet medication use,coronary artery disease (CAD),family history of CAD,admission systolic blood pressure,and left ventricular ejection fraction (LVEF) were lower in the MACE group. Multivariate analysis indicated that Killip classification,BNP,ischemia duration greater than 6 hours,and MACE before PCI were independent risk factors for in-hospital MACE in AMI patients after PCI,while pre-onset use of antiplatelet medications and LVEF were independent protective factors. The nomogram model constructed based on independent risk factors demonstrated good predictive ability,with an area under the ROC curve (AUC) of 0.817,a sensitivity of 81.48％,and a specificity of 67.66％. The Hosmer-Lemeshow test confirmed the model's good fit (x2=1.937,P=0.983). Conclusion The nomogram model developed in this study effectively assesses the risk of in-hospital MACE in AMI patients after PCI,providing a valuable tool for predicting patient outcomes post-PCI.

The nucleotide-binding oligomerization domain-like receptor protein 3(NLRP3)inflammasome is an inflammatory protein complex, and can participate into the inflammatory response. Upon activation, these inflammasomes can lead to Caspase-1 activation, thereby inducing a cascade of inflammatory factor activation and further cell pyroptosis. Excessive activation of inflammasomes will induce the overexpression of inflammatory factors, persistently triggering immune dysregulation and inflammatory chain reactions, even causing severe damage. The recent studies have confirmed a close association between retinal diseases, such as diabetic retinopathy(DR), retinal ischemia-reperfusion injury(RIRI), and proliferative vitreoretinopathy(PVR)with immune dysregulation and inflammatory responses, which is serving as crucial factors in the progression of retinal diseases. This article reviews the NLRP3 inflammasome signaling pathway and its role in the occurrence and development of retinal diseases, in order to provide new ideas for the pathogenesis and prevention of retinal diseases.

Objective To investigate the potential factors influencing the occurrence of major adverse cardiovascular events (MACE) in patients with acute myocardial infarction (AMI) after percutaneous coronary intervention (PCI) and develop an efficient and accurate predictive model. Methods Clinical data of AMI patients treated in the emergency department of Jining Medical University Affiliated Hospital between January and December 2020 were retrospectively collected. Patients were divided into two groups based on the occurrence of in-hospital MACE,the MACE group and the non-MACE group. Clinical indicators of the two groups were compared,and statistically significant variables were selected for inclusion in a multivariate logistic regression analysis. Based on this analysis,a nomogram model was constructed to predict the risk of in-hospital MACE in AMI patients after PCI. The model's predictive accuracy was evaluated using the receiver operating characteristic (ROC) curve,and the goodness of fit was assessed using the Hosmer-Lemeshow test. Results A total of 583 patients were included after screening based on inclusion and exclusion criteria,of whom 85 (14.58％) experienced in-hospital MACE. Univariate analysis showed that compared to the non-MACE group,the MACE group had higher values for age,Killip classification,myoglobin (MYO),brain natriuretic peptide (BNP),white blood cell count (WBC),prothrombin time (PT),T-wave changes on electrocardiogram (ECG),abnormal wall motion on echocardiography,ischemia duration greater than 6 hours,the number of MACE before PCI,and left anterior descending artery stenosis. In contrast,the number of patients with a history of oral antiplatelet medication use,coronary artery disease (CAD),family history of CAD,admission systolic blood pressure,and left ventricular ejection fraction (LVEF) were lower in the MACE group. Multivariate analysis indicated that Killip classification,BNP,ischemia duration greater than 6 hours,and MACE before PCI were independent risk factors for in-hospital MACE in AMI patients after PCI,while pre-onset use of antiplatelet medications and LVEF were independent protective factors. The nomogram model constructed based on independent risk factors demonstrated good predictive ability,with an area under the ROC curve (AUC) of 0.817,a sensitivity of 81.48％,and a specificity of 67.66％. The Hosmer-Lemeshow test confirmed the model's good fit (x2=1.937,P=0.983). Conclusion The nomogram model developed in this study effectively assesses the risk of in-hospital MACE in AMI patients after PCI,providing a valuable tool for predicting patient outcomes post-PCI.

Objective:To summarize the characteristics of the participants (P), interventions (I), control measures (C), outcomes (O) and study design (S) of the clinical study of chronic back pain (CBP) in recent years; To further systematically organize the outcomes of the clinical study of CBP and their corresponding measurement tools.Methods:Clinical studies of CBP were retrieved from various databases including CNKI, Wanfang Database, VIP, SinoMed, Cochrane Library, Pubmed, Embase, Web of Science, etc. The search period was from January 1, 2015 to December 31, 2019. The retrieved literature was extracted and analyzed.The retrieved literatures will be extracted and analyzed. The retrieved literature was subjected to data extraction and analysis, and the quality of outcome indicators was evaluated according to 6 items. The Newcastle-Ottawa Scale ( NOS ) was used to evaluate the quality of cohort studies and case-control studies. Analyze the relationship between outcome indicators and interventions.Results:A total of 3 028 articles were finally included after examination and screening. The top 7 diagnoses of CBP were low back pain, lumbar disc protrusion, lumbar vertebral stenosis, lumbar vertebral slip, lumbar disc degression, non-specific chronic low back pain and post-operative pain syndrome. The top 7 intervention measures in clinical studies of CBP were surgery, acupuncture, physiotherapy, Tuina, exercise therapy, Western medicine painkillers and oral Chinese patent medicines. A total of 47 outcomes and 348 outcome measurement tools were reported in the literature included.Conclusion:In the clinical study of CBP in the recent years, there are problems such as incomplete and low quality of reporting, a wide variety of outcome measurement tools and lack of uniform reporting standards. The characteristics of patients determine the common characteristics of outcomes selection and it is also necessary to consider the specific outcomes related to interventions.

Hydrogels/therapeutic use* ; Tissue Engineering ; Gelatin ; Intervertebral Disc/surgery* ; Methacrylates ; Tissue Scaffolds

ObjectiveTo study the possible molecular mechanism of baicalein （BAI）-mediated focal adhesion kinase （FAK） in the regulation of phosphatidylinositol 3-kinase/protein kinase B （PI3K/Akt） signaling pathway to inhibit the proliferation and migration of gastric cancer HGC-27 cells. MethodThe gastric epithelial GES-1 cells and gastric cancer HGC-27 cells were respectively treated with BAI （0， 5， 15， 25， and 50 μmol·L^-1） for 48 h， and then methyl thiazolyl tetrazolium （MTT） assay was adopted to detect effect of BAI on cell proliferation. Western blot （WB） was employed to detect the expression of FAK and the proteins related to epithelial-mesenchymal transition （EMT） and PI3K signaling pathway after intervention with different concentrations of BAI. The HGC-27 cells stably overexpressing FAK were constructed with lentivirus-mediated transfection technique， and the transfection of FAK was detected through WB and green fluorescent protein （GFP）. The cells were divided into empty vector （NC） group， BAI group， FAK overexpression group， and BAI-treated FAK overexpression group， and cell proliferation activity was detected by MTT assay. The colony formation and cell migration were observed via colony formation assay and Transwell migration assay， respectively. The expression of proteins involved in EMT and PI3K signaling pathways were detected by Western blot. ResultCompared with the NC group， BAI （15， 25 and 50 μmol·L^-1） inhibited the proliferation of HGC-27 cells in a dose-dependent manner （P<0.05， P<0.01） while did not affect that of GES-1 cells. BAI （5， 15 and 25 μmol·L^-1） down-regulated the expression level of p-FAK （P<0.05， P<0.01）. Compared with NC group， FAK overexpression group showed up-regulated expression level of FAK in HGC-27 cells. The HGC-27 cells in both NC group and FAK overexpression group had green fluorescence. Compared with NC group， BAI inhibited the growth， colony formation， and migration， while FAK overexpression promoted those of HGC-27 cells. The treatment of FAK overexpression group with BAI inhibited the enhancement of cell proliferation and migration （P<0.05）. WB showed that compared with NC group， BAI （15， 25 μmol·L^-1） significantly up-regulated the expression of E-cadherin protein and down-regulated that of Vimentin， Snail， p-PI3K， and p-Akt protein in HGC-27 cells （P<0.05， P<0.01）. Compared with NC group， FAK overexpression group showed down-regulated expression of E-cadherin， up-regulated expression of p-FAK， Vimentin， and Snail， and increased ratios of p-FAK/FAK， p-PI3K/PI3K and p-Akt/Akt （P<0.05）. This phenomenon would be reversed after BAI treatment. ConclusionBAI can affect the proliferation and migration of gastric cancer HGC-27 cells by mediating FAK to regulate PI3K/Akt signaling pathway.

Objective: To investigate the effect of taraxerol on autophagy of breast cancer MCF-7 cells in vitro, and explore the related mechanisms. Method: The effect of various doses of taraxerol (12.5, 25, 50, 100, 200 μmol·L^-1) on proliferation of MCF-7 cells was detected by methye thiazolye telrazlium (MTT) assay. The autophagy-inducing effect of taraxerol was observed by acridine orange staining, transmission electron microscope (TEM) and immunofluorescence. The expressions of autophagy-related proteins and the changes of mammalian target of rapamycin (mTOR) signaling pathway were determined by Western blot analysis. Result: The viability of MCF-7 cells was significantly inhibited by taraxerol. Acridine orange staining indicated that the acidic lysosomes increased significantly after treatment with taraxerol in MCF-7 cells. The autophagic structure in the treated group was observed by TEM. Immunofluorescence showed that the expression of microtubule-associated protein 1 light chain 3 (LC3) in the cells of the drug group was increased. Western blot demonstrated that the protein expressions of LC3-Ⅱ and Beclin-1 were increased in taraxerol-treated MCF-7 cells (P<0.05,P<0.01), respectively. Compared with 100 μmol·L^-1 taraxerol group, combination group (taraxerol + 3-methyladenine, 3-MA) showed the down-regulation of LC3-Ⅱ in the MCF-7 cells (P<0.05).And expressions of phosphorylated mammal target of rapamycin (p-mTOR) and phosphorylated eukaryotic initiation factor 4E binding protein 1 (p-4EBP1) were decreased in MCF-7 cells after treatment with taraxerol (P<0.05, P<0.01). Conclusion: Taraxerol can induce autophagy in MCF-7 cells, which may be related to the inhibition of mTOR signaling pathway.