Anionic Ultrasmall Gold Nanoparticles Bind to Coagulation Factors and Disturb Normal Hemostatic Balance

Stealth and Biocompatible Gold Nanoparticles through Surface Coating with a Zwitterionic Derivative of Glutathione

Gold nanoparticles (AuNPs) hold promise in biomedicine, but challenges like aggregation, protein corona formation, and insufficient biocompatibility must be thoroughly addressed before advancing their clinical applications. Designing AuNPs with specific protein corona compositions is challenging, and strategies for corona elimination, such as coating with polyethylene glycol (PEG), have limitations. In this study, we introduce a commercially available zwitterionic derivative of glutathione, glutathione monoethyl ester (GSHzwt), for the surface coating of colloidal AuNPs. Particles coated with GSHzwt were investigated alongside four other AuNPs coated with various ligands, including citrate ions, tiopronin, glutathione, cysteine, and PEG. We then undertook a head-to-head comparison of these AuNPs to assess their behavior in biological fluid. GSHzwt-coated AuNPs exhibited exceptional resistance to aggregation and protein adsorption. The particles could also be readily functionalized with biotin and interact with streptavidin receptors in human plasma. Additionally, they exhibited significant blood compatibility and noncytotoxicity. In conclusion, GSHzwt provides a practical and easy method for the surface passivation of AuNPs, creating "stealth" particles for potential clinical applications.

Clinical value of coagulation parameters in predicting the severity of severe fever with thrombocytopenia syndrome

Introduction

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease caused by a novel bunyavirus infection with a high lethality rate. The purpose of this study was to investigate the changes in coagulation parameters in patients with SFTS, aiming to provide clinical evidence for early diagnosis, treatment, and disease analysis.

Methods

A total of 40 patients with SFTS attended from April 1, 2020 to May 21, 2022 in Nanjing Drum Tower Hospital were selected and grouped according to the duration of the disease, mild and severe disease, cure and death, with 50 healthy physical examiners as controls, and the risk of severe and death disease was predicted using ROC curves.

Results

Comparison between the healthy, mild and severe groups revealed that PT, INR, APTT, TT, D-D and vWF levels were higher than those in the healthy control group, and FII, FIX, FX, FXI, FXII, PC and PS levels were lower than those in the healthy control group, the differences were statistically significant (p < 0.05). Comparing the results of SFTS patients with different course times, the results of Fib, FV, FVII, FVIII, FIX, FX, FXI were statistically significant (p < 0.05). Among the survived and deceased patients, the PT, INR, DD and PS results of the deceased patients were higher than those of the survived patients, and the FVIII, FIX, FXI, FXII and PC were lower than those of the survived patients. The area under the ROC curve showed that D-D had higher predictive ability for the risk of severe disease (AUROC 0.93, sensitivity and specificity at a Cut-off value of 1.50 mg/L were 90.0 and 86.5%, respectively) and the risk of death occurring (AUROC 0.84, sensitivity and specificity at a Cut-off value of 3.39 mg/L were 87.5 and 80.0%, respectively).

Discussion

The monitoring of the coagulation parameters in patients with SFTS is great significance for identifying the severity and death of the patient's condition, and it is of great clinical value to provide early attention, timely intervention and maximum reduction of the mortality rate for patients at risk of severe disease.

Time Evolution of Ultrasmall Gold Nanoparticle-Protein Interactions

To date, much effort has been devoted toward the study of protein corona formation onto large gold nanoparticles (GNPs). However, the protein corona concept breaks down for GNPs in the ultrasmall size regime (<3 nm), and, as a result, our understanding of ultrasmall GNP (usGNP)-protein interactions remains incomplete. Herein, we used anionic usGNPs and six different proteins as model systems to systematically investigate usGNP-protein interactions, with particular focus on the time evolution and long-term behavior of complex formation. The different proteins comprised chymotrypsin (Cht), trypsin (Try), thrombin (Thr), serum albumin (HSA), cytochrome c (Cyt c), and factor XII (FXII). We used a range of biochemical and biophysical methods to estimate binding affinities, determine the effects of usGNPs on protein structure and function, assess the reversibility of any protein structural and functional changes, and evaluate usGNP-protein complex stability. Among the main findings, we observed that prolonged (24 h)─but not short-term (10 min)─interactions between proteins and usGNPs permanently altered protein function, including enzyme activities (Try, Thr, and FXIIa), peroxidase-like activity (Cyt c), and ligand-binding properties (HSA). Remarkably, this occurred without any large-scale loss of the native global conformation, implying time-dependent effects of usGNPs on local protein conformation or dynamics. We also found that both short-(10 min) and long-term (24 h) interactions between proteins and usGNPs yielded short-lived complexes, i.e., there was no time-dependent "hardening" of the interactions at the binding interface as usually seen with large GNPs. The present study increases our fundamental understanding of nano-bio interactions in the ultrasmall size regime, which may assist the safe and effective translation of usGNPs into the clinic.

Context Aware Convolutional Neural Network for Children Caries Diagnosis on Dental Panoramic Radiographs

The objective of this study is to improve traditional convolutional neural networks for more accurate children dental caries diagnosis on panoramic radiographs. A context aware convolutional neural network (CNN) is proposed by considering information among adjacent teeth, based on the fact that caries of teeth often affects each other due to the same growing environment. Specifically, when performing caries diagnosis on a tooth, information from its adjacent teeth will be collected and adaptively fused for final classification. Children panoramic radiographs of 210 patients with one or more caries and 94 patients without caries are utilized, among which there are a total of 6028 teeth with 3039 to be caries. The proposed context aware CNN outperforms typical CNN baseline with the accuracy, precision, recall, F1 score, and area-under-the-curve (AUC) being 0.8272, 0.8538, 0.8770, 0.8652, and 0.9005, respectively, showing potential to improve typical CNN instead of just copying them in previous works. Specially, the proposed method performs better than two five-year attending doctors for the second primary molar caries diagnosis. Considering the results obtained, it is beneficial to promote CNN based deep learning methods for assisting dentists for caries diagnosis in hospitals.