<i>In vivo</i> magnetic resonance imaging of iron oxide-labeled, intravenous-injected mesenchymal stem cells in kidneys of rabbits with acute ischemic kidney injury: detection and monitoring at 1.5 T

<div><p></p><p><i>Background</i>: Acute kidney injury (AKI) is one of the most important causes of mortality and morbidity worldwide. Mesenchymal stem cells (MSCs) can be used for stem cell-based therapy containing AKI. Magnetic resonance imaging (MRI) is an ideal mean for stem cells tracking by labeling with superparamagnetic iron oxide (SPIO). Therefore, using the iron oxide-labeled mesenchymal stem cells (MSC) to treat the AKI and evaluating migration, distribution, and homing of cells by MRI is an ideal method for cell therapy and cell tracking <i>in vivo. Methods</i>: <i>In vitro</i>, the MSCs were labeled with 25 μg/mL for 24 h, and test the labeled efficiency and cells viability. <i>In vitro</i> experiments, magnetic resonance imaging (MRI) measurement of non-labeled and SPIO-labeled MSCs (SPIO-MSCs) was performed in correlation to detectable cells concentrations and detectable time windows. <i>In vivo</i> experiments, MRI evaluation was performed before and after ischemic/reperfusion AKI (<i>N</i> = 14) and intravenous injection of 5 × 10⁵ SPIO-MSCs (<i>N</i> = 10), PBS (<i>N = </i>6) up to 8 days using a clinical 1.5 T scanner. Signal intensity of kidneys were measured and tested for statistical significance (unpaired Student’s <i>t</i>-test, <i>p < </i>0.05) in comparison histology (hematoxylin and eosin [H&E], Prussian blue). <i>Results</i>: <i>In vitro</i>, MSCs can be labeled with the SPIO without affecting the viability and labeling efficiency. SPIO-MSCs showed a reduction of signal intensity at T2WI and T2*WI, 5 × 10⁴cells/mL, SPIO-MSCs were the minimum imaging cells concentration using a 1.5 T MR <i>in vitro. In vivo</i>, SPIO-MSCs administration resulted in a T2*WI signal intensity decrease in renal medulla caused by SPIO-MSCs accumulation in contrast to control groups (<i>p < </i>0.05) up to day 3 after transplantation, but T2*WI low signal intensity region of the renal medulla revealed an decrease at day 5, and no significant differences between SPIO-MSCs and control animals at day 8. <i>Conclusion</i>: Our data demonstrate that <i>in vitro</i> and <i>in vivo</i>, cell-tracking and monitoring of kidney distribution of intravenous injected SPIO-MSCs after AKI is feasible in MRI at 1.5 T.</p></div

Data-Driven Deciphering of Latent Lesions in Heterogeneous Tissue Using Function-Directed <i>t</i>‑SNE of Mass Spectrometry Imaging Data

Mass spectrometry imaging (MSI), which quantifies the underlying chemistry with molecular spatial information in tissue, represents an emerging tool for the functional exploration of pathological progression. Unsupervised machine learning of MSI datasets usually gives an overall interpretation of the metabolic features derived from the abundant ions. However, the features related to the latent lesions are always concealed by the abundant ion features, which hinders precise delineation of the lesions. Herein, we report a data-driven MSI data segmentation approach for recognizing the hidden lesions in the heterogeneous tissue without prior knowledge, which utilizes one-step prediction for feature selection to generate function-specific segmentation maps of the tissue. The performance and robustness of this approach are demonstrated on the MSI datasets of the ischemic rat brain tissues and the human glioma tissue, both possessing different structural complexity and metabolic heterogeneity. Application of the approach to the MSI datasets of the ischemic rat brain tissues reveals the location of the ischemic penumbra, a hidden zone between the ischemic core and the healthy tissue, and instantly discovers the metabolic signatures related to the penumbra. In view of the precise demarcation of latent lesions and the screening of lesion-specific metabolic signatures in tissues, this approach has great potential for in-depth exploration of the metabolic organization of complex tissue

Data-Driven Deciphering of Latent Lesions in Heterogeneous Tissue Using Function-Directed <i>t</i>‑SNE of Mass Spectrometry Imaging Data

Mass spectrometry imaging (MSI), which quantifies the underlying chemistry with molecular spatial information in tissue, represents an emerging tool for the functional exploration of pathological progression. Unsupervised machine learning of MSI datasets usually gives an overall interpretation of the metabolic features derived from the abundant ions. However, the features related to the latent lesions are always concealed by the abundant ion features, which hinders precise delineation of the lesions. Herein, we report a data-driven MSI data segmentation approach for recognizing the hidden lesions in the heterogeneous tissue without prior knowledge, which utilizes one-step prediction for feature selection to generate function-specific segmentation maps of the tissue. The performance and robustness of this approach are demonstrated on the MSI datasets of the ischemic rat brain tissues and the human glioma tissue, both possessing different structural complexity and metabolic heterogeneity. Application of the approach to the MSI datasets of the ischemic rat brain tissues reveals the location of the ischemic penumbra, a hidden zone between the ischemic core and the healthy tissue, and instantly discovers the metabolic signatures related to the penumbra. In view of the precise demarcation of latent lesions and the screening of lesion-specific metabolic signatures in tissues, this approach has great potential for in-depth exploration of the metabolic organization of complex tissue

Hybrid Nanotrimers for Dual <i>T</i>₁ and <i>T</i>₂‑Weighted Magnetic Resonance Imaging

Development of multifunctional nanoparticle-based probes for dual <i>T</i>₁- and <i>T</i>₂-weighted magnetic resonance imaging (MRI) could allow us to image and diagnose the tumors or other abnormalities in an exceptionally accurate and reliable manner. In this study, by fusing distinct nanocrystals <i>via</i> solid-state interfaces, we built hybrid heteronanostructures to combine both <i>T</i>₁ and <i>T</i>₂- weighted contrast agents together for MRI with high accuracy and reliability. The resultant hybrid heterotrimers showed high stability in physiological conditions and could induce both simultaneous positive and negative contrast enhancements in MR images. Small animal positron emission tomography imaging study revealed that the hybrid heterostructures displayed favorable biodistribution and were suitable for <i>in vivo</i> imaging. Their potential as dual contrast agents for <i>T</i>₁ and <i>T</i>₂-weighted MRI was further demonstrated by <i>in vitro</i> and <i>in vivo</i> imaging and relaxivity measurements

Bovine Omasum-Inspired Interfacial Carbon-Based Nanocomposite for Saliva Metabolic Screening of Gastric Cancer

Gastric cancer is one of the most common malignant digestive cancers, and its diagnostic has still faced challenges based on metabolic analysis due to complex sample pretreatment and low metabolite abundance. In this study, inspired by the structure of bovine omasum, we in situ synthesized a novel interfacial carbon-based nanocomposite of graphene supported nickel nanoparticles-encapsulated in the nitrogen-doped carbon nanotube (Ni/N-CNT/rGO), which was served as a novel matrix with enhanced ionization efficiency for the matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS) saliva metabolic analysis of gastric cancer. Benefiting from its high sp2 graphitic degree, large surface area, strong UV absorption, and rich active sites, Ni/N-CNT/rGO matrix exhibited excellent performances of reproducibility, coverage, salt-tolerance, sensitivity, and adsorption ability in MALDI-TOF MS. The differential scanning calorimetry (DSC) and thermal conversion behaviors explained the highly efficient LDI mechanism. Based on saliva metabolic fingerprints, Ni/N-CNT/rGO assisted LDI MS with cross-validation analysis could successfully distinguish gastric cancer patients from healthy controls through the screening of four potential biomarkers with an accuracy of 92.50%, specificity of 88.03%, and sensitivity of 97.12%. This work provided a fast and sensitive MS sensing platform for the metabolomics characterization of gastric cancer and might have potential value for precision medicine in the future

Combination of Droplet Extraction and Pico-ESI-MS Allows the Identification of Metabolites from Single Cancer Cells

We have combined droplet extraction and a pulsed direct current electrospray ionization mass spectrometry method (Pico-ESI-MS) to obtain information-rich metabolite profiling from single cells. We studied normal human astrocyte cells and glioblastoma cancer cells. Over 600 tandem mass spectra (MS²) of metabolites from a single cell were recorded, allowing the successful identification of more than 300 phospholipids. We found the ratios of unsaturated phosphatidylcholines (PCs) to saturated PCs were significantly higher in glioblastoma cells compared to normal cells. In addition, both isomeric PC (17:1) and (phosphatidylethanolamine) PE (20:1) were found in glioblastoma cells, whereas only PC (17:1) was observed in astrocyte cells. Our method paves the way to characterize the chemical contents of single cells, providing rich metabolome information. We suggest that this technique is general and can be applied to other life science studies such as differentiation and drug resistance of individual cells

Liquid Chromatography–Tandem Mass Spectrometry-Based Plasma Metabonomics Delineate the Effect of Metabolites’ Stability on Reliability of Potential Biomarkers

Metabonomics is an important platform for investigating the metabolites of integrated living systems and their dynamic responses to changes caused by both endogenous and exogenous factors. A metabonomics strategy based on liquid chromatography–mass spectrometry/mass spectrometry in both positive and negative ion modes was applied to investigate the short-term and long-term stability of metabolites in plasma. Principal components analysis and ten types of identified metabolites were used to summarize the time-dependent change rules in metabolites systematically at different temperatures. The long-term stability of metabolites in plasma specimens stored at −80 °C for five years was also studied. Analysis of these subjects identified 36 metabolites with statistically significant changes in expression (<i>p</i> < 0.05) and found a kind of metabolite with a hundred-fold change. The stability of metabolites in blood at 4 °C for 24 h was also investigated. These studies show that a thorough understanding of the effects of metabolite stability are necessary for improving the reliability of potential biomarkers

Additional file 1 of Hypoxia-induced TMTC3 expression in esophageal squamous cell carcinoma potentiates tumor angiogenesis through Rho GTPase/STAT3/VEGFA pathway

Supplementary Material

Additional file 2 of Hypoxia-induced TMTC3 expression in esophageal squamous cell carcinoma potentiates tumor angiogenesis through Rho GTPase/STAT3/VEGFA pathway

Supplementary Material

Ligand Engineering of Gold Nanoclusters for NIR-II Imaging

Near-infrared-II (NIR-II) imaging has shown great potential in medical diagnosis and surgical navigation, but developing safe, photostable, high-brightness molecular probes remains a great challenge. Due to their ultrasmall size resulting in highly efficient renal clearance, gold nanoclusters have shown great clinical potential. In this work, we systematically explored the effect of different ligands on the luminescence and bioactivity of gold nanoclusters. Our results show that gold nanoclusters protected by thioglycolic acid (TGA) and 6-mercaptohexanoic acid (MHA) exhibit the strongest fluorescence, while 3-mercaptopropionic acid (MPA)- and sodium sulfide (Na2S)-protected gold nanoclusters show the weakest NIR-II signal. Further doping showed that the Cd-doped MPA and MHA-protected gold nanoclusters exhibited enhanced fluorescence, but the cysteine (Cys)-, glutathione (GSH)-, and Na2S-protected gold nanoclusters showed fluorescence quenching after doping, indicating significant ligand selectivity. Because of the unique multi-energy structure and the large number of electronic states at the highest occupied molecular orbital energy level, MPA- and MHA-protected gold nanoclusters exhibit high stability and photostability. In addition, gold nanoclusters with different ligands exhibited different selective enzyme-mimicking activities of peroxidase (POD), superoxide dismutase (SOD), and catalase (CAT). Imaging in vivo showed that gold nanoclusters could accomplish reliable imaging of cerebral vasculature, hindlimb vessels, and spine as well as monitor renal clearance. The stable nanoclusters allow the time window of imaging to reach 125 min for hindlimb imaging and 270 min for spinal imaging. The gold nanoclusters exhibit a high signal-to-noise ratio of up to 11 for whole-body imaging and show efficient renal clearance and low toxicity at an injected dose of 50 mg/kg