Metal-Folded Single-Chain Nanoparticle: Nanoclusters and Self-Assembled Reduction-Responsive Sub-5-nm Discrete Subdomains.

Easy access to discrete nanoclusters in metal-folded single-chain nanoparticles (metal-SCNPs) and independent ultrafine sudomains in the assemblies via coordination-driven self-assembly of hydrophilic copolymer containing 9% imidazole groups is reported herein. 1 H NMR, dynamic light scattering, and NMR diffusion-ordered spectroscopy results demonstrate self-assembly into metal-SCNPs (>70% imidazole-units folded) by neutralization in the presence of Cu(II) in water to pH 4.6. Further neutralization induces self-assembly of metal-SCNPs (pH 4.6-5.0) and shrinkage (pH 5.0-5.6), with concurrent restraining residual imidazole motifs and hydrophilic segment, which organized into constant nanoparticles over pH 5.6-7.5. Atomic force microscopy results evidence discrete 1.2 nm nanoclusters and sub-5-nm subdomains in metal-SCNP and assembled nanoparticle. Reduction of metal center using sodium ascorbate induces structural rearrangement to one order lower than the precursor. Enzyme mimic catalysis required media-tunable discrete ultrafine interiors in metal-SCNPs and assemblies have hence been achieved.

Chelation-Induced Polymer Structural Hierarchy/Complexity in Water.

Understanding nanoscale structural hierarchy/complexity of hydrophilic flexible polymers is imperative because it can be viewed as an analogue to protein-alike superstructures. However, current understanding is still in infancy. Herein the first demonstration of nanoscale structural hierarchy/complexity via copper chelation-induced self-assembly (CCISA) is presented. Hierarchically-ordered colloidal networks and disks can be achieved by deliberate control of spacer length and solution pH. Dynamic light scattering, transmission electron microscopy, and atomic force microscopy demonstrate that CCISA underwent supramolecular-to-supracolloidal stepwise-growth mechanism, and underline amazing prospects to the hierarchically-ordered superstructures of hydrophilic flexible polymers in water.

Intratumoral and Peritumoral Multiparametric MRI-Based Radiomics Signature for Preoperative Prediction of Ki-67 Proliferation Status in Glioblastoma: A Two-Center Study.

RATIONALE AND OBJECTIVES: To assess the predictive ability of intratumoral and peritumoral multiparametric magnetic resonance imaging (MRI)-based radiomics signature (RS) for preoperative prediction of Ki-67 proliferation status in glioblastoma. MATERIALS AND METHODS: A total of 205 patients with glioblastoma at two institutions were retrospectively analyzed. Data from institution 1 (n = 158) were used to develop the predictive model, and as an internal test dataset, data from institution 2 (n = 47) constitute the external test dataset. Feature selection was performed using spearman correlation coefficient, univariate ranking method, and the least absolute shrinkage and selection operator algorithm. RSs were established using a logistic regression algorithm. The predictive performance of the RSs was assessed using calibration curve, decision curve analysis (DCA), and area under the curve (AUC). RESULTS: In the RSs based on single-parametric (contrast-enhanced T1-weighted image, T2-weighted image, or apparent diffusion coefficient maps), the AUCs of intratumoral, peritumoral, and combined area (intratumoral and peritumoral) were 0.60-0.67, with no significant difference among them. The RSs that using multiparametric features (integrating the previously mentioned three sequences) showed improved AUC compared to the single-parametric RSs; AUC reached 0.75-0.89. Among them, the multiparametric RS based on radiomics features of the combined area (Multi-Com) exhibited the highest performance, with an internal test dataset AUC of 0.89 (95% confidence interval (CI) 0.75-1.00) and an external test dataset AUC of 0.88 (95% CI 0.78-0.97). The calibration curve and DCA display RS (Multi-Com) have good calibration ability and clinical applicability. CONCLUSION: The multiparametric MRI-based RS combining intratumoral and peritumoral features can serve as a noninvasive and effective tool for preoperative assessment of Ki-67 proliferation status in glioblastoma.

Radiomics Based on Dynamic Contrast-Enhanced MRI to Early Predict Pathologic Complete Response in Breast Cancer Patients Treated with Neoadjuvant Therapy.

RATIONALE AND OBJECTIVES: To investigate the value of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI)-based radiomics at baseline and after two cycles of neoadjuvant therapy (NAT) and associated longitudinal changes for early prediction of the NAT response in patients with breast cancer. MATERIALS AND METHODS: One hundred seventeen patients with breast cancer who underwent DCE-MRI before NAT and after two cycles of NAT from April 2019 to November 2021 were enrolled retrospectively. Patients were randomly divided into a training set (n = 81) and a test set (n = 36) at a ratio of 7:3. Clinical-pathological data and the relative tumor maximum diameter regression value (diameter%) were also collected. A total of 851 radiomic features were extracted from the phase with the most pronounced tumor enhancement on DCE-MRI T1 imaging acquired both pre- and post-treatment. Delta and delta% radiomics features were also calculated. The Least Absolute Shrinkage and Selection Operator (LASSO) method was applied to select features, and a logistic regression model was used to calculate pre-NAT, early-NAT, delta, and delta% radscores and then select among four radscores to build a Fusion radiomics model. The final clinical-radiomics model was constructed by combining fusion radscores and clinical-pathological variables. The discrimination and clinical utility of the models were further evaluated and compared. RESULTS: The area under the curve (AUC) values of the fusion radiomics model based on pre-NAT, Delta, and Delta% radscores were 0.868 of 0.825. The clinical-radiomics model integrating Fusion radscores and clinical-pathological variables achieved AUC values of 0.920 of 0.884, which were higher than those of the clinical model constructed by AUC values (0.858/0.831), although no significant improvement was observed in the test set (Delong test, p = 0.196). Decision curve analysis (DCA) showed that the clinical-radiomics model demonstrated more clinical utility than the clinical model. CONCLUSION: DCE-MRI-based radiomics features may have potential for pathological complete response (pCR) prediction in the early phase of NAT. By combining radiomics features and clinical-pathological characteristics, higher diagnostic performance can be achieved.

Dynamic local metrics changes in patients with toothache: A resting-state functional magnetic resonance imaging study.

Objective: To study the dynamic changes of local metrics in patients with toothache (TA, Toothache) in the resting state, in order to further understand the changes of central neural mechanism in patients with dental pain and its effect on cognition and emotion. Methods: Thirty patients with TA and thirty matched healthy (HC) control volunteers were recruited, and resting-state functional magnetic resonance (rs-MRI) scans were performed on all subjects, and data were analyzed to compare group differences in three dynamic local indices: dynamic regional homogeneity (dReHO), dynamic low-frequency fluctuation amplitude (dALFF) and dynamic fractional low-frequency fluctuation amplitude (dfALFF). In addition, the association between dynamic local metrics in different brain regions of TA patients and scores on the Visual Analog Scale (VAS) and the Hospital Anxiety and Depression Scale (HADS) was investigated by Pearson correlation analysis. Results: In this study, we found that The local metrics of TA patients changed with time Compared with the HC group, TA patients showed increased dReHo values in the left superior temporal gyrus, middle frontal gyrus, precentral gyrus, precuneus, angular gyrus, right superior frontal gyrus, middle temporal gyrus, postcentral gyrus and middle frontal gyrus, increased dALFF values in the right superior frontal gyrus, and increased dfALFF values in the right middle temporal gyrus, middle frontal gyrus and right superior occipital gyrus (p < 0.01, cluster level P < 0.05). Pearson correlation analysis showed that dReHo values of left precuneus and left angular gyrus were positively correlated with VAS scores in TA group. dReHo value of right posterior central gyrus was positively correlated with HADS score (P < 0.05). Conclusion: There are differences in the patterns of neural activity changes in resting-state brain areas of TA patients, and the brain areas that undergo abnormal changes are mainly pain processing brain areas, emotion processing brain areas and pain cognitive modulation brain areas, which help to reveal their underlying neuropathological mechanisms. In the hope of further understanding its effects on cognition and emotion.

Compartmentalization and Unidirectional Cross-Domain Molecule Shuttling of Organometallic Single-Chain Nanoparticles.

Compartmentalization and unidirectional cross-domain molecule shuttling are omnipresent in proteins, and play key roles in molecular recognition, enzymatic reaction, and other living functions. Nanomachinery design emulating these biological functions is being considered as one of the most ambitious and challenging tasks in modern chemistry and nanoscience. Here, we present a biomimetic nanomachinery design using single-chain technology. Stepwise complex of the outer blocks of water-soluble linear ABC triblock terpolymer to copper ions yields dumbbell-shaped single-chain nanoparticle. A novel nanomachine capable of compartmentalization and unidirectional cross-domain molecule shuttling has been achieved upon ascorbic acid reduction, leading to synergistically donating/accepting copper centers between discrete double heads, overall dumbbell-to-tadpole configurational transition, and intake of oxidized ascorbic acid into reconstructed head. Subsequent air oxidation results in the inverse molecule shuttling and configurational transition processes. This is the first demonstration of biomimetic nanomachinery design that is capable of compartmentalization and unidirectional cross-domain molecule shuttling, exemplified simply using a new single-chain technology.

Drop-Weight Impact Test on U-Shape Concrete Specimens with Statistical and Regression Analyses.

According to the principle and method of drop-weight impact test, the impact resistance of concrete was measured using self-designed U-shape specimens and a newly designed drop-weight impact test apparatus. A series of drop-weight impact tests were carried out with four different masses of drop hammers (0.875, 0.8, 0.675 and 0.5 kg). The test results show that the impact resistance results fail to follow a normal distribution. As expected, U-shaped specimens can predetermine the location of the cracks very well. It is also easy to record the cracks propagation during the test. The maximum of coefficient of variation in this study is 31.2%; it is lower than the values obtained from the American Concrete Institute (ACI) impact tests in the literature. By regression analysis, the linear relationship between the first-crack and ultimate failure impact resistance is good. It can suggested that a minimum number of specimens is required to reliably measure the properties of the material based on the observed levels of variation.