ObjectiveAs a second messenger in intracellular signal transduction, Ca²⁺ plays an important role in cell migration. Previous studies have demonstrated that extracellular Ca²⁺ influx can promote electric field-guided cell migration, known as electrotaxis. However, the effect of intracellular Ca²⁺ flow on electrotaxis is unclear. Therefore, in this study, we investigate the effect of Ca²⁺ flux on the electrotaxis of Dictyostelium discoideum. MethodsThe electrotaxis of Dictyostelium discoideum was investigated by applying a direct current (DC) electric field. Cell migration was recorded using a real-time imaging system. Calcium channel inhibitors, the extracellular Ca²⁺ chelator EGTA, Ca²⁺-free DB buffer, and caffeine were applied to investigate the impact of intra- and extracellular Ca²⁺ flow on electrotaxis. The involvement of G proteins and ERK2 in directed cell migration mediated by endoplasmic reticulum Ca²⁺ release was explored using mutants. ResultsDictyostelium discoideum migrated toward the cathode in the electric field in a voltage-dependent manner. The intracellular Ca²⁺ concentration of the cells was significantly increased in the electric field. Inhibition of both extracellular Ca²⁺ influx and intracellular Ca²⁺ release suppressed cell electrotaxis migration. Inhibition of endoplasmic reticulum Ca²⁺ release induced by caffeine significantly impaired the electrotaxis of Dictyostelium discoideum. Deletion of Gα2, Gβ, Gγ, and Erk2 notably reduced the electrotaxis of the cells. Enhancing Ca²⁺ release mediated by caffeine restored the electrotaxis of the Gα2^-, Gβ ^-, and Erk2^- mutant cells partially or completely, but did not restore electrotaxis in the Gγ^- mutant cells. ConclusionCa²⁺ release from the endoplasmic reticulum regulates electrotaxis migration in Dictyostelium discoideum and is involved in the regulation of cell electrotaxis by G proteins and ERK2.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

The early response of plant auxin gene family Aux/IAA (auxin/indole-3-acetic acid) and its interaction with auxin response factor (ARF) are important pattern to regulate plant growth and development. This work identified 28 StoIAA and 24 StoARF members based on the whole genome data of the medicinal plant Senna tora L., which were classified into 10 and 8 subfamilies, respectively. Phylogenetic tree and collinearity analysis showed that S. tora has close evolutionary relationship with the IAA and ARF homologous genes of Glycine max, Medicago truncatula, and the segment duplication events dominate the expansion of StoIAA and StoARF. Gene structure analysis showed that the vast majority of StoIAA and StoARF contain characteristic conserved domain. Transcriptome data showed that StoIAAs and StoARFs were expressed in leaves, roots and seeds, some members had tissue specific expression. The StoIAA and StoARF promoter region most contain functional elements related to stress response, growth and development, hormone induction and secondary metabolism. In addition, gene expression analysis showed that many StoIAAs and StoARFs can quickly respond to drought and salt stress and exhibited same expression patterns under both stress condition. The yeast two-hybrid experiment confirmed that StoARF8 and StoARF10 exhibit varying degrees of interaction with multiple StoIAA proteins, respectively. The above results provide a basis for further biological functional analysis of the Aux/IAA and ARF gene family of S. tora.

Bacterial biofilms gave rise to persistent infections and multi-organ failure, thereby posing a serious threat to human health. Biofilms were formed by cross-linking of hydrophobic extracellular polymeric substances (EPS), such as proteins, polysaccharides, and eDNA, which were synthesized by bacteria themselves after adhesion and colonization on biological surfaces. They had the characteristics of dense structure, high adhesiveness and low drug permeability, and had been found in many human organs or tissues, such as the brain, heart, liver, spleen, lungs, kidneys, gastrointestinal tract, and skeleton. By releasing pro-inflammatory bacterial metabolites including endotoxins, exotoxins and interleukin, biofilms stimulated the body’s immune system to secrete inflammatory factors. These factors triggered local inflammation and chronic infections. Those were the key reason for the failure of traditional clinical drug therapy for infectious diseases.In order to cope with the increasingly severe drug-resistant infections, it was urgent to develop new therapeutic strategies for bacterial-biofilm eradication and anti-bacterial infections. Based on the nanoscale structure and biocompatible activity, nanobiomaterials had the advantages of specific targeting, intelligent delivery, high drug loading and low toxicity, which could realize efficient intervention and precise treatment of drug-resistant bacterial biofilms. This paper highlighted multiple strategies of biofilms eradication based on nanobiomaterials. For example, nanobiomaterials combined with EPS degrading enzymes could be used for targeted hydrolysis of bacterial biofilms, and effectively increased the drug enrichment within biofilms. By loading quorum sensing inhibitors, nanotechnology was also an effective strategy for eradicating bacterial biofilms and recovering the infectious symptoms. Nanobiomaterials could intervene the bacterial metabolism and break the bacterial survival homeostasis by blocking the uptake of nutrients. Moreover, energy-driven micro-nano robotics had shown excellent performance in active delivery and biofilm eradication. Micro-nano robots could penetrate physiological barriers by exogenous or endogenous driving modes such as by biological or chemical methods, ultrasound, and magnetic field, and deliver drugs to the infection sites accurately. Achieving this using conventional drugs was difficult. Overall, the paper described the biological properties and drug-resistant molecular mechanisms of bacterial biofilms, and highlighted therapeutic strategies from different perspectives by nanobiomaterials, such as dispersing bacterial mature biofilms, blocking quorum sensing, inhibiting bacterial metabolism, and energy driving penetration. In addition, we presented the key challenges still faced by nanobiomaterials in combating bacterial biofilm infections. Firstly, the dense structure of EPS caused biofilms spatial heterogeneity and metabolic heterogeneity, which created exacting requirements for the design, construction and preparation process of nanobiomaterials. Secondly, biofilm disruption carried the risk of spread and infection the pathogenic bacteria, which might lead to other infections. Finally, we emphasized the role of nanobiomaterials in the development trends and translational prospects in biofilm treatment.

AIM To establish a GC-MS method for the simultaneous content determination of sixteen pesticide residues in Lycii Fructus and perform safety assessment.METHODS The analysis was performed on DB-5MS chromatographic column(30 m×0.25 mm,0.25 μm)subjected to the programmed heating,with splitless injection of 1.0 μL dissolved sample at a flowing rate of 1.0 mL/min.Other parameters were as follows:injection port temperature of 250℃,electron impact ionization(EI),electron energy of 70 eV;ion source temperature of 230℃,multi-reaction monitoring mode,and collision gas.of high-purity N2.Pesticide residues with relatively high dietary risk were analyzed and discussed with regard to residue levels,dietary intake risk,risk ranking and cumulative exposure assessment.RESULTS Sixteen pesticides showed good linear relationships within their own ranges(r≥0.994 4),whose average recoveries were 70%-114%,with the RSDs of less than 2%.The highest average cyfluthrin residue of 0.999 2 mg/kg in Lycii Fructus of production regions and the highest average cypermethrin residue of 0.088 4 mg/kg in Lycii Fructus commodities were both detected.In Lycii Fructus of production regions with chronic hazard index(HI)value of 0.012 9 and acute HI value of 0.065 5 and their commodities with chronic HI of 0.001 2 and acute HI of 0.005 4,the pesticide residue of cypermethrin was the leading cause of chronic and acute dietary risk,and additionally,pyridaben within maximum residue limit(MRL)was the only detectectable highly toxic pesticide among the other most concerning pestcides of deltamethrin,pyridaben,chlorpyrifos,dichlorvos and methidathion.CONCLUSION There exist pesticide residues within MRL values in some samples of Lycii Fructus and the use of cypermethrin should be well-controlled.

Objective To study the apoptosis and mechanism of lung epithelial cells induced by exposure to ozone oxidized black carbon(OBC)and explore the therapeutic effect of dexamethasone.Methods A549 cells were divided into seven groups:control group,dexamethasone group and 0,6.5,12.5,25.0,50.0 μg·mL-1OBC treatment groups.All cells were cultured for 24 h.Cell counting kit-8(CCK-8)was used to detect the survival rate of cells.Immunofluorescence was used to detect the activity of reactive oxygen species.Annexin V-FITC/PI two-color fluorescent dye Notation was used to detect apoptotic cells.Real-time quantitative polymerase chain reaction(PCR)was used to detect the expression level of P53,B-cell lymphoma-2(Bcl-2),cysteinyl aspartate specific proteinase-3(caspase-3)mRNA.Western blot was used to detect the expression level of P53,Bcl-2,caspase-3 protein.Results The cell survival rates of 50.0 μg·mL-1 OBC treatment group,control group and dexamethasone group were(12.64±2.45)％,(100.00±0.00)％and(42.39±2.50)％;the reactive oxygen species were(147.00±5.65),(42.82±2.50)and(94.40±4.30)MFI;the apoptosis rates of epithelial cells were(40.50±3.52)％,(5.02±1.15)％and(21.58±2.35)％;the expression of P53 mRNA were 3.81±0.22,1.04±0.02 and 2.03±0.08;the equivalent expression levels of P53 protein were 0.54±0.06,0.14±0.02 and 0.33±0.03.The above indicators in 50.0 μg·mL-1 OBC treatment group showed statistically significant differences compared with control group and dexamethasone group(all P＜0.05).Conclusion OBC exposure leads to oxidative damage of lung epithelial cells and activates their apoptosis related pathways,while dexamethasone has shown good therapeutic effects in vitro experiments.