DOTA-Branched Organic Frameworks as Giant and Potent Metal Chelators.

Multinuclear complexes as metallo-agents for clinical use have caught extensive attention. In this paper, using 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA) as both a functioning unit and a constructing junction, we build a series of DOTA-branched organic frameworks with multiple chelating holes by organizing DOTA layer by layer. These giant chelators are well characterized, which reveals their nanosized and soft structures. Further experiments demonstrate that they could efficiently hold abundant metal ions with much higher kinetic stabilities than the conventional small DOTA chelator. Their corresponding polynuclear complexes containing Gd3+, Tb3+, or both show superior imaging properties, excellent feasibility for peripheral modification, and unusual kinetic stability. This work can be easily extended to the fabrication of diverse homomultinuclear complexes and core/shell heteromultinuclear complexes with multifunctional properties. We expect that this new type of giant molecules and the ligand-branching strategy would open up a new avenue for the design and construction of next-generation polymetallic agents with high performance and stabilities for biomedical applications.

A Self-Assembled Biocompatible Nanoplatform for Multimodal MR/Fluorescence Imaging Assisted Photothermal Therapy and Prognosis Analysis.

The need for better imaging assisted cancer therapy calls for new biocompatible agents with excellent imaging and therapeutic capabilities. This study successfully fabricates albumin-cooperated human serum albumin (HSA)-GGD-ICG nanoparticles (NPs), which are comprised of a magnetic resonance (MR) contrast agent, glycyrrhetinic-acid-modified gadolinium (III)-1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetate (GGD), and a fluorescence (FL) dye, indocyanine green (ICG), for multimodal MR/FL imaging assisted cancer therapy. These HSA-GGD-ICG NPs with excellent biocompatibility are stable under physiological conditions, and exhibit enhanced T1 contrast capability and improved fluorescence imaging capacity. In vitro experiments reveal an apparent effect of the NPs in killing tumor cells under low laser irradiation, due to the enhanced photothermal conversion efficiency (≈85.1%). Importantly, multimodal MR/FL imaging clearly shows the in vivo behaviors and the efficiency of tumor accumulation of HSA-GGD-ICG NPs, as confirmed by a pharmacokinetic study. With the guidance of multimodal imaging, photothermal therapy is subsequently conducted, which demonstrates again high photothermal conversion capability for eliminating tumors without relapse. Notably, real-time monitoring of tumor ablation for prognosis and therapy evaluation is also achieved by MR imaging. This strategy of constructing nanoplatforms through albumin-mediated methods is both convenient and efficient, which would enlighten the design of multimodal imaging assisted cancer therapy for potential clinical translation.

Facile Chemoselective Modification of Thio-Ethers Generates Chiral Center-Induced Helical Peptides.

A precisely positioned sulfimide chiral center on-tether of a thio-ether tethered peptide determines the peptide secondary structure by chemoselective oxaziridine modification. This method provides a facile way to tune peptides' secondary structures and biophysical properties.

Reversible and Versatile On-Tether Modification of Chiral-Center-Induced Helical Peptides.

Modification of the cross-linker of constrained peptides has recently received considerable attention. Here, we present a versatile approach to modifing the cross-linking tether of chiral-center-induced helical (CIH) peptides via the S-alkylation reaction. The alkylation process displayed high conversion efficiency, selectivity, and substrate tolerance. Notably, although on-tether S-alkylation could lead to a pair of peptide epimers, the major alkylated product retained the helical structure of its helical precursor peptide. This S-alkylation was readily reversible under reductive conditions, which provides a simple method for traceless modification. In addition to expanding the chemical space of CIH peptides, this strategy is the first on-tether modification platform with known retention of the peptides' original helicity.

Dual In-Tether Chiral Centers Modulate Peptide Helicity.

The facile chemical modification on the peptide cross-linking moiety is an important strategy for improving the physicochemical properties of a peptide. Herein, peptides were constrained into helical conformations via the synergistic effects of dual in-tether chiral centers. A pentapeptide minimalistic model was used to determine the correlation between the absolute configurations of the dual in-tether chiral centers and the secondary structures of the peptides. This strategy provides an on-tether modification site that does not interrupt the secondary structure of the peptide.

Investigation of Cellular Uptakes of the In-Tether Chiral-Center-Induced Helical Pentapeptides.

We recently reported that a precisely positioned in-tether chiral center can modulate backbone peptides' secondary structures, which provides an unbiased platform to evaluate peptides' biophysical properties solely imposed by secondary structure differences. In this work, we studied the cellular uptake efficiency and mechanism of epimer pairs of a panel of chirality-induced helical peptides (CIH peptides). Although the peptides' cellular uptake is a synergetic result of various factors, our results unambiguously indicate that helical content is an important factor for the cellular uptake of CIH peptides.

An In-tether Chiral Center Modulates the Helicity, Cell Permeability, and Target Binding Affinity of a Peptide.

The addition of a precisely positioned chiral center in the tether of a constrained peptide is reported, yielding two separable peptide diastereomers with significantly different helicity, as supported by circular dichroism (CD) and NMR spectroscopy. Single crystal X-ray diffraction analysis suggests that the absolute configuration of the in-tether chiral center in helical form is R, which is in agreement with theoretical simulations. The relationship between the secondary structure of the short peptides and their biochemical/biophysical properties remains elusive, largely because of the lack of proper controls. The present strategy provides the only method for investigating the influence of solely conformational differences upon the biochemical/biophysical properties of peptides. The significant differences in permeability and target binding affinity between the peptide diastereomers demonstrate the importance of helical conformation.

Combining convolutional neural networks and self-attention for fundus diseases identification.

Early detection of lesions is of great significance for treating fundus diseases. Fundus photography is an effective and convenient screening technique by which common fundus diseases can be detected. In this study, we use color fundus images to distinguish among multiple fundus diseases. Existing research on fundus disease classification has achieved some success through deep learning techniques, but there is still much room for improvement in model evaluation metrics using only deep convolutional neural network (CNN) architectures with limited global modeling ability; the simultaneous diagnosis of multiple fundus diseases still faces great challenges. Therefore, given that the self-attention (SA) model with a global receptive field may have robust global-level feature modeling ability, we propose a multistage fundus image classification model MBSaNet which combines CNN and SA mechanism. The convolution block extracts the local information of the fundus image, and the SA module further captures the complex relationships between different spatial positions, thereby directly detecting one or more fundus diseases in retinal fundus image. In the initial stage of feature extraction, we propose a multiscale feature fusion stem, which uses convolutional kernels of different scales to extract low-level features of the input image and fuse them to improve recognition accuracy. The training and testing were performed based on the ODIR-5k dataset. The experimental results show that MBSaNet achieves state-of-the-art performance with fewer parameters. The wide range of diseases and different fundus image collection conditions confirmed the applicability of MBSaNet.

A high-performance fluorescent and ratiometric colorimetric detection of Cu2+ in practice.

To monitor Cu2+ efficiently, a kind of D-π-A-π-D conjugated 3,5-di-(2-hydroxyl naphthaldehyde)-iminyl triazole (HNIT) was developed, using triazole as the electron acceptor, 2-hydroxyl naphthaline as the electron donor, and -CN- as the bridging group. The proposed HNIT possessed superior UV-vis and fluorescent spectral property with high molar absorption coefficient of 2.313 × 104 L mol-1 cm-1 and fluorescence quantum yield of 36.2%. Trace Cu2+ could exclusively alter its UV-vis and fluorescent property with clear color change. Under the optimized conditions, a high-performance fluorescent and ratiometric colorimetric detection of Cu2+ based on HNIT was efficient, with low detection limits of 3.3 × 10-8 mol L-1 (S/N = 3) and 9.6 × 10-8 mol L-1 (S/N = 3), respectively. It well satisfied with the safe value of 31.5 µM Cu2+ in drinking water recommended by World Health Organization (WHO). When applied for detection of Cu2+ in real environmental samples, the recovery was in the range of 97.5-105.2%. The recognition mechanism for HNIT to Cu2+ realized quite stable 6-membered rings between electron-deficient Cu2+ and electron-rich N and O atoms in HNIT with 1 : 2 chemical stoichiometry of HNIT to Cu2+.

Convenient colorimetric-fluorescent dual-mode recognition of I- in agricultural products and visual determination of Hg2+ in drinking beverages using Ag-Pt bimetal quantum dot nanozyme.

Conveniently and efficiently monitoring I- and Hg2+ in agricultural products or drinking beverages for the protection of human health is currently a great challenge. With this aim, a Ag-Pt bimetal quantum-dot nanozyme boosted by bioactive folic acid (FA@Ag-Pt QDs) was first developed for multichannel monitoring of I- and Hg2+ in this work using a two-step liquid-phase reduction method. Not only did the present FA@Ag-Pt QDs possess superior peroxidase-like activity with Michaelis constant (Km) and maximal reaction rate (Vmax) of 0.01 mM/2.95 × 10-8 M·s-1 and 1.15 mM/3.88 × 10-8 M·s-1, respectively, trace Hg2+ or I- could exclusively alter their enzyme-mimic performance with obvious color changes from blue to colorless or dark blue. I- could also strengthen the inherent fluorescence property of FA@Ag-Pt QDs. When applied for visual monitoring of I- and Hg2+ in real beverages or iodine-containing agricultural products, the detection recoveries were 93.9 %-105.3 % and 96.8-104.3 % with low detection limits of 6.56 × 10-8 mol/L and 4.00 × 10-10 mol/L (S/N = 3), respectively. The recovery and detection limit for fluorescent detection of I- were 95.8 %-104.1 % and 1.75 × 10-8 mol/L (S/N = 3), respectively. The mechanisms driving the improved peroxidase-like activity of FA@Ag-Pt QDs and their selective monitoring of Hg2+ and I- were illustrated in detail. The proposed FA@Ag-Pt QDs will act as an efficient sensor for the practical multichannel monitoring of Hg2+ and I-, with superior catalytic signal amplification.

Metabolic fluorine labeling and hotspot imaging of dynamic gut microbiota in mice.

Real-time localization and microbial activity information of indigenous gut microbiota over an extended period of time remains a challenge with existing visualizing methods. Here, we report a metabolic fluorine labeling (MEFLA)-based strategy for monitoring the dynamic gut microbiota via 19F magnetic resonance imaging (19F MRI). In situ labeling of different microbiota subgroups is achieved by using a panel of peptidoglycan-targeting MEFLA probes containing 19F atoms of different chemical shifts, and subsequent real-time in vivo imaging is accomplished by multiplexed hotspot 19F MRI with high sensitivity and unlimited penetration. Using this method, we realize extended visualization (>24 hours) of native gut microbes located at different intestinal sections and semiquantitative analysis of their metabolic dynamics modulated by various conditions, such as the host death and different ß-lactam antibiotics. Our strategy holds great potential for noninvasive and real-time assessing of the metabolic activities and locations of the highly dynamic gut microbiota.

Augmentation and heterogeneous graph neural network for AAAI2021-COVID-19 fake news detection.

Misinformation has become a frightening specter of society, especially fake news that concerning Covid-19. It massively spreads on the Internet, and then induces misunderstandings of information to the national and global communities during the pandemic. Detecting massive misinformation on the Internet is crucial and challenging because humans have struggled against this phenomenon for a long time. Our research concerns detecting fake news related to covid-19 using augmentation [random deletion (RD), random insertion (RI), random swap (RS), synonym replacement (SR)] and several graph neural network [graph convolutional network (GCN), graph attention network (GAT), and GraphSAGE (SAmple and aggreGatE)] model. We constructed nodes and edges in the graph, word-word node, and word-document node to graph neural network. Then, we tested those models in different amounts of sample training data to obtain accuracy for each model and compared them. For our fake news detection task, we found training accuracy steadily increasing for GCN, GAT, and SAGE models from the beginning to the end of the epochs. This result proved that the performance of GNN, whether GCN, GAT, or SAGE gained an entirely insignificant difference precision result.

Cervical Cell/Clumps Detection in Cytology Images Using Transfer Learning.

Cervical cancer is one of the most common and deadliest cancers among women and poses a serious health risk. Automated screening and diagnosis of cervical cancer will help improve the accuracy of cervical cell screening. In recent years, there have been many studies conducted using deep learning methods for automatic cervical cancer screening and diagnosis. Deep-learning-based Convolutional Neural Network (CNN) models require large amounts of data for training, but large cervical cell datasets with annotations are difficult to obtain. Some studies have used transfer learning approaches to handle this problem. However, such studies used the same transfer learning method that is the backbone network initialization by the ImageNet pre-trained model in two different types of tasks, the detection and classification of cervical cell/clumps. Considering the differences between detection and classification tasks, this study proposes the use of COCO pre-trained models when using deep learning methods for cervical cell/clumps detection tasks to better handle limited data set problem at training time. To further improve the model detection performance, based on transfer learning, we conducted multi-scale training according to the actual situation of the dataset. Considering the effect of bounding box loss on the precision of cervical cell/clumps detection, we analyzed the effects of different bounding box losses on the detection performance of the model and demonstrated that using a loss function consistent with the type of pre-trained model can help improve the model performance. We analyzed the effect of mean and std of different datasets on the performance of the model. It was demonstrated that the detection performance was optimal when using the mean and std of the cervical cell dataset used in the current study. Ultimately, based on backbone Resnet50, the mean Average Precision (mAP) of the network model is 61.6% and Average Recall (AR) is 87.7%. Compared to the current values of 48.8% and 64.0% in the used dataset, the model detection performance is significantly improved by 12.8% and 23.7%, respectively.

Redox-Activated Contrast-Enhanced T1-Weighted Imaging Visualizes Glutathione-Mediated Biotransformation Dynamics in the Liver.

GSH-mediated liver biotransformation is a crucial physiological process demanding efficient research tools. Here, we report a type of amorphous FexMnyO nanoparticles (AFMO-ZDS NPs) as redox-activated probes for in vivo visualization of the dynamics of GSH-mediated biotransformation in liver with T1-weighted magnetic resonance imaging (MRI). This imaging technique reveals the periodic variations in GSH concentration during the degradation of AFMO-ZDS NPs due to the limited transportation capacity of GSH carriers in the course of GSH efflux from hepatocytes to perisinusoidal space, providing direct imaging evidence for this important carrier-mediated process during GSH-mediated biotransformation. Therefore, this technique offers an effective method for in-depth investigations of GSH-related biological processes in liver under various conditions as well as a feasible means for the real-time assessment of liver functions, which is highly desirable for early diagnosis of liver diseases and prompt a toxicity evaluation of pharmaceuticals.

Reversible redox-responsive 1H/19F MRI molecular probes.

Herein we report a pair of redox-responsive manganese complexes Mn(iii)/(ii)-N,N'-bis(2-hydroxy-4-trifluoromethylbenzyl)ethylenediamine-N,N'-diacetate (HTFBED, L1), which are water soluble and biologically interconvertible, as reversible redox-responsive probes in 1H/19F MRI for detecting and imaging biological redox species, offering a means to access valuable redox information associated with various diseases.

A gadolinium-complex-based theranostic prodrug for in vivo tumour-targeted magnetic resonance imaging and therapy.

Here we report a target-specific theranostic prodrug (1a) containing Gd-DOTA, biotin, and camptothecin (CPT) along with a disulfide self-immolative linker. This prodrug exhibits selective targeting towards tumour cells and tissues, stimuli-responsive controlled release, enhanced anticancer efficacy, and accurate diagnosis and real-time monitoring via contrast-enhanced magnetic resonance imaging (MRI).

Directional assembly of a stapled α-helical peptide.

The de novo design of stapled peptide-based self-assemblies attracts vast interest, yet still remains challenging. The development of an oxidation trigger for peptide stapling and subsequent self-assembly is described here. A self-assembling sequence, Fmoc-R(RCEX)2-NH2, transformed from a random coil to an α-helical structure upon disulphide bonding of the flanking cysteine residues positioning at the i/i + 4 locations. The stapling form of this peptide enforces a conformational restraint that affords the driving force for self-assembly into nanorod/nanovesicle structures. Moreover, these assembled materials can transport siRNA into cancer cells and immediately release the cargo in a reductive environment.

Iron-oxide-based twin nanoplates with strong T2 relaxation shortening for contrast-enhanced magnetic resonance imaging.

Iron oxide nanomaterials have been intensively investigated over the past few decades as magnetic resonance imaging (MRI) contrast agents (CAs) due to their favorable magnetism and excellent biocompatibility. However, commercial iron-oxide-nanoparticle-based CAs suffer from low T2 relaxivity, which significantly limits their applications in the biomedical field. Herein, we report a new type of iron oxide nanoplate (IOP) with an interesting twinning plane, which is fabricated via seed growth. Compared with the conventional iron oxide (IO) spherical nanoparticles, iron oxide twin nanoplates (IOP-13) have a larger effective radius, higher saturation magnetization, and greater anisotropy, resulting in their superior T2 relaxivity of 571.21 mM-1 s-1 at 0.5 T, which is about six times higher than that of commercial IO nanoparticles. In vivo MR imaging demonstrated that IOP-13 could be used for liver imaging and liver tumor diagnosis with high sensitivity and accuracy, revealing the great potential of IOP-13 as a next-generation CA. This work provides a novel strategy of structure tuning to devise high-performance T2 contrast agents, which expands the applications of iron oxide nanoparticles in biology and materials.

Surface manganese substitution in magnetite nanocrystals enhances T1 contrast ability by increasing electron spin relaxation.

Magnetite nanoparticles, with good biocompatibility and favorable magnetic properties, have the potential to be the best candidate for non-gadolinium MRI contrast agents. However, they usually show low T1 contrast ability, largely because Fe(ii) ions have a short electronic relaxation time and also have a small number of unpaired electrons with inefficient proton relaxation enhancement. Herein, we report a novel strategy to increase the T1 contrast ability of magnetite nanoparticles, through substituting the undesirable Fe(ii) ions with Mn(ii) ions. Mn(ii) ions have a longer electronic relaxation time (10-8 s) and more unpaired electrons (5 unpaired electrons). We successfully construct diverse-shaped manganese ferrite nanoparticles with abundant magnetic ions, Mn(ii) and Fe(iii), exposed on the surface. These manganese ferrite nanoparticles exhibit remarkably higher longitudinal relaxivity than their parent iron oxide nanoparticles. We demonstrate that the increase in T1 relaxivity is attributed to the extended electronic relaxation time and the increased number of unpaired electrons on the surface of the nanoparticles by controlling surface features, particularly by adjusting the substitution degree of Mn(ii) ions and in situ coating. This study provides an insightful strategy to improve the T1 contrast ability of iron oxide nanoparticles, which is urgently needed for developing high-performance non-gadolinium T1 contrast agents for imaging and diagnosis of disease.

Erratum: In-Tether Chiral Center Induced Helical Peptide Modulators Target p53-MDM2/MDMX and Inhibit Tumor Growth in Stem-Like Cancer Cell: Erratum.

[This corrects the article DOI: 10.7150/thno.19840.].