Unusual Designated-Tailoring on Zone-Axis Preferential Growth of Surfactant-Free ZnO Mesocrystals

An unusual designated-tailoring on zone-axis preferential growth of surfactant-free ZnO mesocrystals with different features (shapes and sizes) was successfully achieved via an additive-free complex-precursor solution method. The formation of ZnO mesocrystals here is essentially determined by the characteristic of [Zn­(OH)4]2– precursors, and an oriented nanoparicle aggregation with tailoring sizes and shapes can occur in different concentration of reactants at higher reaction temperature. Spindle-like ZnO mesocrystals with tunable sizes (along the c-axis direction) were synthesized by adjusting the concentration of hydroxyl ions, and peanut-like ZnO mesocrystals with controllable sizes (along the c-axis direction) and shapes (perpendicular c-axis direction) were prepared by tailoring the concentration of zinc ions. Structural and morphological evolutions were investigated by X-ray diffraction (XRD), transmission electron microscopy (TEM), high-resolution transmission electron microscopy (HRTEM), and field-emission scanning electron microscopy (FESEM). The study is of great significance in bottom-up assembly of controllable ordering architectures, and provides a good opportunity to understand the formation mechanism and fundamental significance of zone-axis preferential growth of ZnO mesocrystals. Significantly, it is believed that the precursor driven assembly of mesostructures reported here would provide a green way to design more and more surfactant-free metal oxide architectures with well-defined shapes

Viscoelastic-Sorting Integrated Deformability Cytometer for High-Throughput Sorting and High-Precision Mechanical Phenotyping of Tumor Cells

The counts and phenotypes of circulating tumor cells (CTCs) in whole blood are useful for disease monitoring and prognostic assessment of cancer. However, phenotyping CTCs in the blood is difficult due to the presence of a large number of background blood cells, especially some blood cells with features similar to those of tumor cells. Herein, we presented a viscoelastic-sorting integrated deformability cytometer (VSDC) for high-throughput label-free sorting and high-precision mechanical phenotyping of tumor cells. A sorting chip for removing large background blood cells and a detection chip for detecting multiple cellular mechanical properties were integrated into our VSDC. Our VSDC has a sorting efficiency and a purity of over 95% and over 81% for tumor cells, respectively. Furthermore, multiple mechanical parameters were used to distinguish tumor cells from white blood cells using machine learning. An accuracy of over 97% for identifying tumor cells was successfully achieved with the highest identification accuracy of 99.4% for MCF-7 cells. It is envisioned that our VSDC will open up new avenues for high-throughput and label-free single-cell analysis in various biomedical applications

Pyrylium-Based Derivatization for Rapid Labeling and Enhanced Detection of Cholesterol in Mass Spectrometry Imaging

Cholesterol in the central nervous system has been increasingly found to be closely related to neurodegenerative diseases. Defects in cholesterol metabolism can cause structural and functional disorders of the central nervous system. The detection of abnormal cholesterol is of great significance for the cognition of physiological and pathological states of organisms, and the spatial distribution of cholesterol can also provide more clues for our understanding of the complex mechanism of disease. Here, we developed a novel pyrylium-based derivatization reagent combined with matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) to visualize cholesterol in biological tissues. A new class of charged hydroxyl derivatization reagents was designed and synthesized, and finally 1-(carboxymethyl)-2,4,6-trimethylpyridinium (CTMP) was screened for tissue derivatization of cholesterol. Different from the shortcomings of traditional hydroxyl labeling methods such as harsh reaction conditions and long reaction time, in our study, we combined the advantages of CTMP itself and the EDCl/HOBt reaction system to achieve instant labeling of cholesterol on tissues through two-step activation. In addition, we also reported changes in cholesterol content in different stages and different brain regions during disease development in SOD1 mutant mouse model. The cholesterol derivatization method we developed provides an efficient way to explore the distribution and spatial metabolic network of cholesterol in biological tissues

Simultaneous Mapping of Amino Neurotransmitters and Nucleoside Neuromodulators on Brain Tissue Sections by On-Tissue Chemoselective Derivatization and MALDI-MSI

Neurotransmitters (NTs) and neuromodulators (NMs) are two of the most important neurochemicals in the brain, and their imbalances in specific brain regions are thought to underlie certain neurological disorders. We present an on-tissue chemoselective derivatization mass spectrometry imaging (OTCD-MSI) method for the simultaneous mapping of NTs and NMs. Our derivatization system consists of a pyridiniumyl-benzylboronic acid based derivatization reagent and pyrylium salt, which facilitate covalent charge labeling of molecules containing cis-diol and primary amino, respectively. These derivatization systems improved the detection sensitivity of matrix-assisted laser desorption/ionization (MALDI)-MSI and simplified the identification of amino NTs and nucleoside NMs by the innate chemoselectivity of derivatization reagents and the unique isotopic pattern of boron-derivative reagents. We demonstrated the ability of the developed method on brain sections from a hypoxia mouse model and control. The simultaneous imaging of NTs and NMs provided a method for exploring how hypoxic stress and drugs affect specific brain regions through neurotransmitter modulation

Table_3_Performance of Multiparametric Functional Imaging and Texture Analysis in Predicting Synchronous Metastatic Disease in Pancreatic Ductal Adenocarcinoma Patients by Hybrid PET/MR: Initial Experience.docx

Objectives: To assess the imaging biomarkers of glucose metabolic activity and diffusion-weighted imaging (DWI) derived from pretreatment integrated 18F-fluorodeoxyglucose positron emission tomography-magnetic resonance (18F-FDG PET/MR) imaging as potential predictive factors of metastasis in patients with pancreatic ductal adenocarcinoma (PDAC).Patients and Methods: We retrospectively included 17 consecutive patients with pathologically confirmed PDAC by pretreatment 18F-FDG PET/MR. The study subjects were divided into a non-metastatic group (M0, six cases) and a metastatic group (M1, 11 cases). The 18F-FDG PET/MR images were reviewed independently by two board certificated nuclear medicine physicians and one radiologist. Conventional characteristics and quantitative parameters from both PET and apparent diffusion coefficient (ADC) were assessed. The texture features were extracted from LIFEx packages (www.lifexsoft.org), and a 3D tumor volume of interest was manually drawn on fused PET/ADC images. Chi-square tests, independent-samples t-tests and Mann–Whitney U-tests were used to compare the differences in single parameters between the two groups. A logistic regression analysis was performed to determine independent predictors. A receiver operating characteristic (ROC) curve analysis was performed to assess the discriminatory power of the selected parameters. Correlations between metabolic parameters and ADC features were calculated with Spearman's rank correlation coefficient test.Results: For conventional parameters, univariable analysis demonstrated that the M1 group had a significantly larger size and a higher peak of standardized uptake value (SUVpeak), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) than those of the M0 group (p 0.05 for all). For the texture features, there were four features from the PET image and 13 from the ADC map that showed significant differences between the two groups. Multivariate analysis indicated that one feature from PET and three from the ADC were significant predictors. TLG was associated with ADC-GLRLM_GLNU (r = 0.659), ADC-GLRLM_LRHGE (r = 0.762), and PET-GLRLM_LRHGE (r = 0.806).Conclusions: Multiple parameters and texture features of primary tumors from 18F-FDG PET/MR images maybe reliable biomarkers to predict synchronous metastatic disease for the pretreatment PDAC.</p

Table_1_Performance of Multiparametric Functional Imaging and Texture Analysis in Predicting Synchronous Metastatic Disease in Pancreatic Ductal Adenocarcinoma Patients by Hybrid PET/MR: Initial Experience.DOCX

Objectives: To assess the imaging biomarkers of glucose metabolic activity and diffusion-weighted imaging (DWI) derived from pretreatment integrated 18F-fluorodeoxyglucose positron emission tomography-magnetic resonance (18F-FDG PET/MR) imaging as potential predictive factors of metastasis in patients with pancreatic ductal adenocarcinoma (PDAC).Patients and Methods: We retrospectively included 17 consecutive patients with pathologically confirmed PDAC by pretreatment 18F-FDG PET/MR. The study subjects were divided into a non-metastatic group (M0, six cases) and a metastatic group (M1, 11 cases). The 18F-FDG PET/MR images were reviewed independently by two board certificated nuclear medicine physicians and one radiologist. Conventional characteristics and quantitative parameters from both PET and apparent diffusion coefficient (ADC) were assessed. The texture features were extracted from LIFEx packages (www.lifexsoft.org), and a 3D tumor volume of interest was manually drawn on fused PET/ADC images. Chi-square tests, independent-samples t-tests and Mann–Whitney U-tests were used to compare the differences in single parameters between the two groups. A logistic regression analysis was performed to determine independent predictors. A receiver operating characteristic (ROC) curve analysis was performed to assess the discriminatory power of the selected parameters. Correlations between metabolic parameters and ADC features were calculated with Spearman's rank correlation coefficient test.Results: For conventional parameters, univariable analysis demonstrated that the M1 group had a significantly larger size and a higher peak of standardized uptake value (SUVpeak), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) than those of the M0 group (p 0.05 for all). For the texture features, there were four features from the PET image and 13 from the ADC map that showed significant differences between the two groups. Multivariate analysis indicated that one feature from PET and three from the ADC were significant predictors. TLG was associated with ADC-GLRLM_GLNU (r = 0.659), ADC-GLRLM_LRHGE (r = 0.762), and PET-GLRLM_LRHGE (r = 0.806).Conclusions: Multiple parameters and texture features of primary tumors from 18F-FDG PET/MR images maybe reliable biomarkers to predict synchronous metastatic disease for the pretreatment PDAC.</p

Table_2_Performance of Multiparametric Functional Imaging and Texture Analysis in Predicting Synchronous Metastatic Disease in Pancreatic Ductal Adenocarcinoma Patients by Hybrid PET/MR: Initial Experience.DOCX

Objectives: To assess the imaging biomarkers of glucose metabolic activity and diffusion-weighted imaging (DWI) derived from pretreatment integrated 18F-fluorodeoxyglucose positron emission tomography-magnetic resonance (18F-FDG PET/MR) imaging as potential predictive factors of metastasis in patients with pancreatic ductal adenocarcinoma (PDAC).Patients and Methods: We retrospectively included 17 consecutive patients with pathologically confirmed PDAC by pretreatment 18F-FDG PET/MR. The study subjects were divided into a non-metastatic group (M0, six cases) and a metastatic group (M1, 11 cases). The 18F-FDG PET/MR images were reviewed independently by two board certificated nuclear medicine physicians and one radiologist. Conventional characteristics and quantitative parameters from both PET and apparent diffusion coefficient (ADC) were assessed. The texture features were extracted from LIFEx packages (www.lifexsoft.org), and a 3D tumor volume of interest was manually drawn on fused PET/ADC images. Chi-square tests, independent-samples t-tests and Mann–Whitney U-tests were used to compare the differences in single parameters between the two groups. A logistic regression analysis was performed to determine independent predictors. A receiver operating characteristic (ROC) curve analysis was performed to assess the discriminatory power of the selected parameters. Correlations between metabolic parameters and ADC features were calculated with Spearman's rank correlation coefficient test.Results: For conventional parameters, univariable analysis demonstrated that the M1 group had a significantly larger size and a higher peak of standardized uptake value (SUVpeak), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) than those of the M0 group (p 0.05 for all). For the texture features, there were four features from the PET image and 13 from the ADC map that showed significant differences between the two groups. Multivariate analysis indicated that one feature from PET and three from the ADC were significant predictors. TLG was associated with ADC-GLRLM_GLNU (r = 0.659), ADC-GLRLM_LRHGE (r = 0.762), and PET-GLRLM_LRHGE (r = 0.806).Conclusions: Multiple parameters and texture features of primary tumors from 18F-FDG PET/MR images maybe reliable biomarkers to predict synchronous metastatic disease for the pretreatment PDAC.</p

Facile Water-Assisted Synthesis of Cupric Oxide Nanourchins and Their Application as Nonenzymatic Glucose Biosensor

We have demonstrated an interesting approach for the one-pot synthesis of cupric oxide (CuO) nanourchins with sub-100 nm through a sequential dissolution–precipitation process in a water/ethanol system. The first stage produces a precursory crystal [Cu₇Cl₄(OH)₁₀H₂O] that is transformed into monoclinic CuO nanourchins during the following stage. Water is a required reactant for the morphology-controlled growth of different CuO nanostructures. When evaluated for their nonenzymatic glucose-sensing properties, these CuO nanourchins manifest higher sensitivity. Significantly, this water-dependent precursor transformation method may be widely used to effectively control the growth of other metal oxide nanostructures

High-Efficiency Recognition and Identification of Disulfide Bonded Peptides in Rat Neuropeptidome Using Targeted Electron Transfer Dissociation Tandem Mass Spectrometry

The main goal of the present study is to develop a method to recognize and identify endogenous intrachain disulfide bonded peptide, which are rarely sequenced in current peptidomics studies. In order to achieve highly efficient detection of these peptides in a neuropeptidome analysis, we alkylated the peptides, mined the raw mass spectrometry data, and then recognized the candidates of untreated disulfide bonded peptides from unalkylated peptide extracts. After removing more than 90% features, targeted electron transfer dissociation fragmentation was performed for detecting and fragmenting disulfide bonded peptides, and even most of them were present in low abundance in the original sample. Diverse endogenous disulfide bonded peptides were then detected and sequenced, opening up new perspectives for comprehensively understanding the response of a neuropeptidome