S-Doping Regulated Iron Spin States in Fe-N-C Single-Atom Material for Enhanced Peroxidase-Mimicking Activity at Neutral pH.

Designing biomimetic nanomaterials with peroxidase (POD)-like activity at neutral pH remains a significant challenge. An S-doping strategy is developed to afford an iron single-atom nanomaterial (Fe1@CN-S) with high POD-like activity under neutral conditions. To the best of knowledge, there is the first example on the achievement of excellent POD-like activity under neutral conditions by regulating the active site structure. S-doping not only promotes the dissociation of the N─H bond in 3,3″,5,5″-tetramethylbenzidine (TMB), but also facilitates the desorption of OH* by the transformation of iron species' spin states from middle-spin (MS FeII) to low-spin (LS FeII). Meanwhile, LS FeII sites typically have more unfilled d orbitals, thereby exhibiting stronger interactions with H2O2 than MS FeII, which can enhance POD-like activity. Finally, a one-pot visual detection of glucose at pH 7 is performed, demonstrating the best selectivity and sensitivity than previous reports.

Nanozyme sensor array based on Fe, Se co-doped carbon material for the discrimination of Sulfur-containing compounds.

Developing methods for the accurate identification and analysis of sulfur-containing compounds (SCCs) is of great significance because of their essential roles in living organisms and the diagnosis of diseases. Herein, Se-doping improved oxidase-like activity of iron-based carbon material (Fe-Se/NC) was prepared and applied to construct a four-channel colorimetric sensor array for the detection and identification of SCCs (including biothiols and sulfur-containing metal salts). Fe-Se/NC can realize the chromogenic oxidation of 3,3',5,5'-tetramethylbenzidine (TMB) by activating O2 without relying on H2O2, which can be inhibited by different SCCs to diverse degrees to produce different colorimetric response changes as "fingerprints" on the sensor array. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) revealed that nine kinds of SCCs could be well discriminated. The sensor array was also applied for the detection of SCCs with a linear range of 1-50 µM and a limit of detection of 0.07-0.2 µM. Moreover, colorimetric sensor array inspired by the different levels of SCCs in real samples were used to discriminate cancer cells and food samples, demonstrating its potential application in the field of disease diagnosis and food monitoring. ENVIRONMENTAL IMPLICATIONS: In this work, a four-channel colorimetric sensor array for accurate SCCs identification and detection was successfully constructed. The colorimetric sensor array inspired by the different levels of SCCs in real samples were also used to discriminate cancer cells and food samples. Therefore, this Fe-Se/NC based sensor array is expected to be applied in the field of environmental monitoring and environment related disease diagnosis.

CuFe Layered Double Hydroxide as Self-Cascade Nanoreactor for Efficient Antibacterial Therapy.

Nanozyme-induced reactive oxygen species (ROS)-dependent catalytic therapy has been developed into a powerful strategy against bacterial wound infections. However, the limited endogenous supply or instability of H2O2, the reliance on external stimuli for the generation of ROS, and the highly expressed glutathione (GSH) level make it a challenge to achieve high-performance therapeutic efficiency. In this work, a facile therapeutic strategy against bacterial infections with pristine CuFe layered double hydroxide (LDH) as the self-cascade nanoreactor is proposed without modification or additional energy input. CuFe LDH with an oxidase-like feature can catalyze the generation of multiple ROS, such as 1O2, ·O2-, and H2O2. And the self-generated H2O2 in the cascade nanoreactor could be further in situ transformed to ·OH owing to the peroxidase-like activity. As a result, the cell membrane of bacteria is destroyed, leading to death. Furthermore, its ultrahigh enzyme-like activity of CuFe LDH could effectively promote the breakdown of the biofilm structure. Additionally, the Cu2+-mediated GSH exhaustion of CuFe LDH further avoids the consumption of oxidized ROS and thereby significantly improves the sterilization effect. Finally, the as-prepared CuFe LDH with negligible side effects on normal tissues can be successfully used to eliminate the methicillin-resistant Staphylococcus aureus-infected wounds and accelerate their healing in the mouse model, which paves a new avenue as an antibacterial agent for clinical anti-infective treatment.

Size transformation of Au nanoclusters for enhanced photocatalytic hydrogen generation: Interaction behavior at nanocluster/semiconductor interface.

Recently, atomically precise metal nanoclusters (NCs) become a new class of photosensitizer for light energy conversion in metal-cluster-sensitized semiconductor (MCSS) system. However, fundamental understanding for the suitable combination of NCs and semiconductor is still unclear. Aside from aspects of light harvesting, energy level alignment and catalytic activity, interfacial interaction behavior at NCs/semiconductor interface is also crucial due to its important influence in charge transportation. In this work, the interface interaction between Au NCs and TiO2 is examined by precise transformation of Au NCs from Au22(SG)18 to Au18(SG)14, as well as its effect on photocatalytic hydrogen production activity. From the optical, charge transport and solid-states spectroscopy analyses, it is able to display that precisely tuning the number of core atoms from Au22(SG)18 to Au18(SG)14 results in the strong interface interaction between Au NCs and TiO2, reflecting in high difference of work function and modified surface band bending of TiO2, therefore promoting the injection of electrons from NCs to TiO2 and reducing interfacial charges recombination. As a result, Au18(SG)14/TiO2 shows higher hydrogen generation rate than Au22(SG)18/TiO2 under light irradiation. This work would provide new insights into rational combination of metal NCs with semiconductor and highlights the overlooked effect of interfacial interaction behavior on light energy conversion.

NoiseMol: A noise-robusted data augmentation via perturbing noise for molecular property prediction.

Simplified Molecular-Input Line-Entry System (SMILES) is one of a widely used molecular representation methods for molecular property prediction. We conjecture that all the characters in the SMILES string of a molecule are essential for making up the molecules, but most of them make little contribution to determining a particular property of the molecule. Therefore, we verified the conjecture in the pre-experiment. Motivated by the result, we propose to inject proper noisy information into the SMILES to augment the training data by increasing the diversity of the labeled molecules. To this end, we explore injecting perturbing noise into the original labeled SMILES strings to construct augmented data for alleviating the limitation of the labeled compound data and enhancing the model to extract more useful molecular representation for molecular property prediction. Specifically, we directly adopt mask, swap, deletion, and fusion operations on SMILES strings to randomly mask, swap, and delete atoms in SMILES strings. Then, the augmented data is used by two strategies: each epoch alternately feeds the original and perturbing noisy molecules, or each batch alternately feeds the original and perturbing noisy molecules. We conduct experiments on both Transformer and BiGRU models to validate the effectiveness by adopting widely used datasets from MoleculeNet and ZINC. Experimental results demonstrate that the proposed method outperforms strong baselines on all the datasets. NoiseMol obtains the best performance on BBBP and FDA when compared with state-of-the-art methods. Besides, NoiseMol achieves the best accuracy on LogP. Therefore, injecting perturbing noise into the labeled SMILES strings is an effective and efficient method, which improves the prediction performance, generalization, and robustness of the deep learning models.

A New Fluorescent Probe Tool: ERNathG.

ß-d-Glucuronidase (GUS) plays a pivotal role in both clinical treatment assessment and environmental monitoring. Existing tools for GUS detection suffer from (1) poor continuity due to a gap between the optimal pH of the probes and the enzyme and (2) diffusion from the detection site due to lack of an anchoring structure. Here we report a novel GUS pH-matching and endoplasmic reticulum-anchoring strategy for GUS recognition. The new fluorescent probe tool was termed ERNathG, which was designed and synthesized with ß-d-glucuronic acid as the GUS-specific recognition site and 4-hydroxy-1,8-naphthalimide as a fluorescence reporting group, with a p-toluene sulfonyl as an anchoring group. This probe enabled the continuous and anchored detection of GUS without pH-adjustment for the related assessment of common cancer cell lines and gut bacteria. The probe's properties are far superior to those of commonly used commercial molecules.

HUMBI: A Large Multiview Dataset of Human Body Expressions and Benchmark Challenge.

This paper presents a new large multiview dataset called HUMBI for human body expressions with natural clothing. The goal of HUMBI is to facilitate modeling view-specific appearance and geometry of five primary body signals including gaze, face, hand, body, and garment from assorted people. 107 synchronized HD cameras are used to capture 772 distinctive subjects across gender, ethnicity, age, and style. With the multiview image streams, we reconstruct the geometry of body expressions using 3D mesh models, which allows representing view-specific appearance. We demonstrate that HUMBI is highly effective in learning and reconstructing a complete human model and is complementary to the existing datasets of human body expressions with limited views and subjects such as MPII-Gaze, Multi-PIE, Human3.6M, and Panoptic Studio datasets. Based on HUMBI, we formulate a new benchmark challenge of a pose-guided appearance rendering task that aims to substantially extend photorealism in modeling diverse human expressions in 3D, which is the key enabling factor of authentic social tele-presence. HUMBI is publicly available at http://humbi-data.net.

MRI Assessment of the Relationship Between Cortical Morphological Features and Hemiparetic Motor-Related Outcomes in Chronic Subcortical Stroke Patients.

BACKGROUND: It is unclear which cortical regions are specific to or commonly associated with the impairments of the upper/lower limbs and the activities of daily life (ADL) in stroke patients. PURPOSE: To investigate the relationships between MRI-assessed surface-based morphometry (SBM) features and motor function as well as ADL in participants with chronic stroke. STUDY TYPE: Prospective. SUBJECTS: Thirty-five participants with subcortical stroke more than 3 months from the first-onset (age: 56.44 ± 9.56 years; 32 male). FIELD STRENGTH/SEQUENCE: T1 -weighted images, 3.0 T, three-dimensional fast field-echo sequence. ASSESSMENT: FreeSurfer (6.0) was used to parcellate each hemisphere into 34 regions based on the Desikan-Killiany atlas and to extract the surface area, volume, thickness, and curvature. The motor function and ADL were assessed by the Fugl-Meyer Assessment for the Upper/Lower Extremity (FMA-UE/FMA-LE) and the Chinese version of the Modified Barthel Index (MBI-C), respectively. STATISTICAL TESTS: A linear mixed-effect model was applied to evaluate the relationship between the morphological features and the FMA-UE, FMA-LE, and MBI-C. A false discovery rate corrected P value < 0.05 was considered statistically significant. RESULTS: Correlations between the size of stroke lesion and MRI measurements did not pass the FDR correction (adjusted P > 0.05). SBM features in motor-related and high-order cognitive cortical regions showed significant correlations with FMA-UE and FMA-LE, respectively. Moreover, the thickness in the prefrontal cortex significantly positively correlated, while the surface area in the right supramarginal gyrus significantly negatively correlated, with both FMA-UE, FMA-LE, and MBI-C. The thickness in the left frontal lobe significantly positively correlated with both FMA-UE and MBI-C. DATA CONCLUSION: This study's findings suggest that different hemiparetic motor-related outcomes in participants with subcortical stroke which suffered a corticospinal tract-related injury show specific, but also share common, associations with several cortical regions. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.

Specific Nanodrug for Diabetic Chronic Wounds Based on Antioxidase-Mimicking MOF-818 Nanozymes.

Chronic wound is a common complication for diabetic patients, which entails substantial inconvenience, persistent pain, and significant economic burden to patients. However, current clinical treatments for diabetic chronic wounds remain unsatisfactory. A prolonged but ineffective inflammation phase in chronic wounds is the primary difference between diabetic chronic wounds and normal wounds. Herein, we present an effective antioxidative system (MOF/Gel) for chronic wound healing of diabetic rats through integrating a metal organic framework (MOF) nanozyme with antioxidant enzyme-like activity with a hydrogel (Gel). MOF/Gel can continuously scavenge reactive oxygen species to modulate the oxidative stress microenvironment in diabetic chronic wounds, which leads to a natural transition from the inflammation phase to the proliferation phase. Impressively, the efficacy of one-time-applied MOF/Gel was comparable to that of the human epidermal growth factor Gel, a widely used clinical drug for various wound treatments. Such an effective, safe, and convenient MOF/Gel system can meet complex clinical demands.

Altered cerebellar functional connectivity in chronic subcortical stroke patients.

Background: Previous studies demonstrated that cerebellar subregions are involved in different functions. Especially the cerebellar anterior lobe (CAL) and cerebellar posterior lobe (CPL) have been postulated to primarily account for sensorimotor and cognitive function, respectively. However, the functional connectivity (FC) alterations of CAL and CPL, and their relationships with behavior performance in chronic stroke participants are unclear so far. Materials and methods: The present study collected resting-state fMRI data from thirty-six subcortical chronic stroke participants and thirty-eight well-matched healthy controls (HCs). We performed the FC analysis with bilateral CAL and CPL as seeds for each participant. Then, we detected the FC difference between the two groups by using a two-sample t-test and evaluated the relationship between the FC and scores of motor and cognitive assessments across all post-stroke participants by using partial correlation analysis. Results: The CAL showed increased FCs in the prefrontal cortex, superior/inferior temporal gyrus, and lingual gyrus, while the CPL showed increased FCs in the inferior parietal lobule, precuneus, and cingulum gyrus in the stroke participants compared with HCs. Moreover, the FC alteration in the right CAL and the right CPL were negatively correlated with executive and memory functions across stroke participants, respectively. Conclusion: These findings shed light on the different increased FC alteration patterns of CAL and CPL that help understand the neuro-mechanisms underlying behavior performance in chronic stroke survivors.

Platinum-Gold Alloy Catalyzes the Aerobic Oxidation of Formic Acid for Hydrogen Peroxide Synthesis.

On-site hydrogen peroxide production through electrocatalytic and photocatalytic oxygen reduction reactions has recently attracted broad research interest. However, practical applications have thus far been plagued by the low activity and the requirement of complex equipment. Here, inspired by the process of biological hydrogen peroxide synthesis catalyzed by enzymes, we report a Pt-Au alloy to mimic the catalytic function of natural formate oxidase for hydrogen peroxide synthesis through aerobic oxidation of formic acid. The mass activity of the Pt-Au alloy is three times higher than that of formate oxidase. Density functional theory calculations revealed that the efficient dehydrogenation of formic acid and the high selectivity of the subsequent reduction of oxygen to hydrogen peroxide account for the high hydrogen peroxide productivity. In addition, the formic acid aqueous solution provides an acidic environment, which is conducive to the utilization of the in situ generated hydrogen peroxide for oxidation reactions, including C-H bond oxidation and sterilization.

Early Expression of Tet1 and Tet2 in Mouse Zygotes Altered DNA Methylation Status and Affected Embryonic Development.

Ten-eleven translocation (Tet) dioxygenases can induce DNA demethylation by catalyzing 5-methylcytosine(5mC) to 5-hydroxymethylcytosine(5hmC), and play important roles during mammalian development. In mouse, Tet1 and Tet2 are not expressed in pronucleus-staged embryos and are not involved in the genomic demethylation of early zygotes. Here, we investigated the influence of Tet1 and Tet2 on methylation of parental genomes by ectopically expressing Tet1 and Tet2 in zygotes. Immunofluorescence staining showed a marked 5hmC increase in the maternal pronucleus after injection of Tet1 or Tet2 mRNA into zygotes. Whole-genome bisulfite sequencing further revealed that Tet2 greatly enhanced the global demethylation of both parental genomes, while Tet1 only promoted the paternal demethylation. Tet1 and Tet2 overexpression altered the DNA methylation across genomes, including various genic elements and germline-specific differently methylated regions. Tet2 exhibited overall stronger demethylation activity than Tet1. Either Tet1 or Tet2 overexpression impaired preimplantation embryonic development. These results demonstrated that early expression of Tet1 and Tet2 could substantially alter the zygotic methylation landscape and damage embryonic development. These findings provide new insights into understanding the function of Tet dioxygenases and the mechanism of DNA methylation in relation to embryogenesis.

Automated segmentation of liver segment on portal venous phase MR images using a 3D convolutional neural network.

OBJECTIVE: We aim to develop and validate a three-dimensional convolutional neural network (3D-CNN) model for automatic liver segment segmentation on MRI images. METHODS: This retrospective study evaluated an automated method using a deep neural network that was trained, validated, and tested with 367, 157, and 158 portal venous phase MR images, respectively. The Dice similarity coefficient (DSC), mean surface distance (MSD), Hausdorff distance (HD), and volume ratio (RV) were used to quantitatively measure the accuracy of segmentation. The time consumed for model and manual segmentation was also compared. In addition, the model was applied to 100 consecutive cases from real clinical scenario for a qualitative evaluation and indirect evaluation. RESULTS: In quantitative evaluation, the model achieved high accuracy for DSC, MSD, HD and RV (0.920, 3.34, 3.61 and 1.01, respectively). Compared to manual segmentation, the automated method reduced the segmentation time from 26 min to 8 s. In qualitative evaluation, the segmentation quality was rated as good in 79% of the cases, moderate in 15% and poor in 6%. In indirect evaluation, 93.4% (99/106) of lesions could be assigned to the correct segment by only referring to the results from automated segmentation. CONCLUSION: The proposed model may serve as an effective tool for automated anatomical region annotation of the liver on MRI images.

Sewage sludge application enhances soil properties and rice growth in a salt-affected mudflat soil.

The most important measures for salt-affected mudflat soil reclamation are to reduce salinity and to increase soil organic carbon (OC) content and thus soil fertility. Salinity reduction is often accomplished through costly freshwater irrigation by special engineering measures. Whether fertility enhancement only through one-off application of a great amount of OC can improve soil properties and promote plant growth in salt-affected mudflat soil remains unclear. Therefore, the objective of our indoor pot experiment was to study the effects of OC amendment at 0, 0.5%, 1.0%, 1.5%, and 2.5%, calculated from carbon content, by one-off application of sewage sludge on soil properties, rice yield, and root growth in salt-affected mudflat soil under waterlogged conditions. The results showed that the application of sewage sludge promoted soil fertility by reducing soil pH and increasing content of OC, nitrogen and phosphorus in salt-affected mudflat soil, while soil electric conductivity (EC) increased with increasing sewage sludge (SS) application rates under waterlogged conditions. In this study, the rice growth was not inhibited by the highest EC of 4.43 dS m-1 even at high doses of SS application. The SS application increased yield of rice, promoted root growth, enhanced root activity and root flux activity, and increased the soluble sugar and amino acid content in the bleeding sap of rice plants at the tillering, jointing, and maturity stages. In conclusion, fertility enhancement through organic carbon amendment can "offset" the adverse effects of increased salinity and promote plant growth in salt-affected mudflat soil under waterlogged conditions.