Geminal-atom catalysis for cross-coupling.

Single-atom catalysts (SACs) have well-defined active sites, making them of potential interest for organic synthesis1-4. However, the architecture of these mononuclear metal species stabilized on solid supports may not be optimal for catalysing complex molecular transformations owing to restricted spatial environment and electronic quantum states5,6. Here we report a class of heterogeneous geminal-atom catalysts (GACs), which pair single-atom sites in specific coordination and spatial proximity. Regularly separated nitrogen anchoring groups with delocalized π-bonding nature in a polymeric carbon nitride (PCN) host7 permit the coordination of Cu geminal sites with a ground-state separation of about 4 Å at high metal density8. The adaptable coordination of individual Cu sites in GACs enables a cooperative bridge-coupling pathway through dynamic Cu-Cu bonding for diverse C-X (X = C, N, O, S) cross-couplings with a low activation barrier. In situ characterization and quantum-theoretical studies show that such a dynamic process for cross-coupling is triggered by the adsorption of two different reactants at geminal metal sites, rendering homo-coupling unfeasible. These intrinsic advantages of GACs enable the assembly of heterocycles with several coordination sites, sterically congested scaffolds and pharmaceuticals with highly specific and stable activity. Scale-up experiments and translation to continuous flow suggest broad applicability for the manufacturing of fine chemicals.

Constructing molecule-metal relay catalysis over heterophase metallene for high-performance rechargeable zinc-nitrate/ethanol batteries.

Zinc-nitrate batteries can integrate energy supply, ammonia electrosynthesis, and sewage disposal into one electrochemical device. However, current zinc-nitrate batteries still severely suffer from the limited energy density and poor rechargeability. Here, we report the synthesis of tetraphenylporphyrin (tpp)-modified heterophase (amorphous/crystalline) rhodium-copper alloy metallenes (RhCu M-tpp). Using RhCu M-tpp as a bifunctional catalyst for nitrate reduction reaction (NO3RR) and ethanol oxidation reaction in neutral solution, a highly rechargeable and low-overpotential zinc-nitrate/ethanol battery is successfully constructed, which exhibits outstanding energy density of 117364.6 Wh kg-1cat, superior rate capability, excellent cycling stability of ~400 cycles, and potential ammonium acetate production. Ex/in situ experimental studies and theoretical calculations reveal that there is a molecule-metal relay catalysis in NO3RR over RhCu M-tpp that significantly facilitates the ammonia selectivity and reaction kinetics via a low energy barrier pathway. This work provides an effective design strategy of multifunctional metal-based catalysts toward the high-performance zinc-based hybrid energy systems.

1T'-transition metal dichalcogenide monolayers stabilized on 4H-Au nanowires for ultrasensitive SERS detection.

Unconventional 1T'-phase transition metal dichalcogenides (TMDs) have aroused tremendous research interest due to their unique phase-dependent physicochemical properties and applications. However, due to the metastable nature of 1T'-TMDs, the controlled synthesis of 1T'-TMD monolayers (MLs) with high phase purity and stability still remains a challenge. Here we report that 4H-Au nanowires (NWs), when used as templates, can induce the quasi-epitaxial growth of high-phase-purity and stable 1T'-TMD MLs, including WS2, WSe2, MoS2 and MoSe2, via a facile and rapid wet-chemical method. The as-synthesized 4H-Au@1T'-TMD core-shell NWs can be used for ultrasensitive surface-enhanced Raman scattering (SERS) detection. For instance, the 4H-Au@1T'-WS2 NWs have achieved attomole-level SERS detections of Rhodamine 6G and a variety of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike proteins. This work provides insights into the preparation of high-phase-purity and stable 1T'-TMD MLs on metal substrates or templates, showing great potential in various promising applications.

Smaller total and subregional cerebellar volumes in posttraumatic stress disorder: a mega-analysis by the ENIGMA-PGC PTSD workgroup.

Although the cerebellum contributes to higher-order cognitive and emotional functions relevant to posttraumatic stress disorder (PTSD), prior research on cerebellar volume in PTSD is scant, particularly when considering subregions that differentially map on to motor, cognitive, and affective functions. In a sample of 4215 adults (PTSD n = 1642; Control n = 2573) across 40 sites from the ENIGMA-PGC PTSD working group, we employed a new state-of-the-art deep-learning based approach for automatic cerebellar parcellation to obtain volumetric estimates for the total cerebellum and 28 subregions. Linear mixed effects models controlling for age, gender, intracranial volume, and site were used to compare cerebellum volumes in PTSD compared to healthy controls (88% trauma-exposed). PTSD was associated with significant grey and white matter reductions of the cerebellum. Compared to controls, people with PTSD demonstrated smaller total cerebellum volume, as well as reduced volume in subregions primarily within the posterior lobe (lobule VIIB, crus II), vermis (VI, VIII), flocculonodular lobe (lobule X), and corpus medullare (all p-FDR < 0.05). Effects of PTSD on volume were consistent, and generally more robust, when examining symptom severity rather than diagnostic status. These findings implicate regionally specific cerebellar volumetric differences in the pathophysiology of PTSD. The cerebellum appears to play an important role in higher-order cognitive and emotional processes, far beyond its historical association with vestibulomotor function. Further examination of the cerebellum in trauma-related psychopathology will help to clarify how cerebellar structure and function may disrupt cognitive and affective processes at the center of translational models for PTSD.

Individualized prediction of anxiety and depressive symptoms using gray matter volume in a non-clinical population.

Machine learning is an emerging tool in clinical psychology and neuroscience for the individualized prediction of psychiatric symptoms. However, its application in non-clinical populations is still in its infancy. Given the widespread morphological changes observed in psychiatric disorders, our study applies five supervised machine learning regression algorithms-ridge regression, support vector regression, partial least squares regression, least absolute shrinkage and selection operator regression, and Elastic-Net regression-to predict anxiety and depressive symptom scores. We base these predictions on the whole-brain gray matter volume in a large non-clinical sample (n = 425). Our results demonstrate that machine learning algorithms can effectively predict individual variability in anxiety and depressive symptoms, as measured by the Mood and Anxiety Symptoms Questionnaire. The most discriminative features contributing to the prediction models were primarily located in the prefrontal-parietal, temporal, visual, and sub-cortical regions (e.g. amygdala, hippocampus, and putamen). These regions showed distinct patterns for anxious arousal and high positive affect in three of the five models (partial least squares regression, support vector regression, and ridge regression). Importantly, these predictions were consistent across genders and robust to demographic variability (e.g. age, parental education, etc.). Our findings offer critical insights into the distinct brain morphological patterns underlying specific components of anxiety and depressive symptoms, supporting the existing tripartite theory from a neuroimaging perspective.

Characteristic Plasmon Energies for 2D In2Se3 Phase Identification at Nanoscale.

Two-dimensional (2D) materials with competing polymorphs offer remarkable potential to switch the associated 2D functionalities for novel device applications. Probing their phase transition and competition mechanisms requires nanoscale characterization techniques that can sensitively detect the nucleation of secondary phases down to single-layer thickness. Here we demonstrate nanoscale phase identification on 2D In2Se3 polymorphs, utilizing their distinct plasmon energies that can be distinguished by electron energy-loss spectroscopy (EELS). The characteristic plasmon energies of In2Se3 polymorphs have been validated by first-principles calculations, and also been successfully applied to reveal phase transitions using in situ EELS. Correlating with in situ X-ray diffraction, we further derive a subtle difference in the valence electron density of In2Se3 polymorphs, consistent with their disparate electronic properties. The nanometer resolution and independence of orientation make plasmon-energy mapping a versatile technique for nanoscale phase identification on 2D materials.

Orbital-Selectivity-Induced Robust Quantum Anomalous Hall Effect in Hund's Metals MgFeP.

Ferromagnetic (FM) states with high Curie temperatures (Tc) and strong spin-orbit coupling (SOC) are indispensable for the long-sought room-temperature quantum anomalous Hall (QAH) effects. Here, we propose a two-dimensional (2D) iron-based monolayer MgFeP that exhibits a notably high FM Tc (about 1525 K) along with exceptional structural stabilities. The unique multiorbital nature in MgFeP, where localized dx2-y2 and dxz/yz orbitals coexist with itinerant dxy and dz2 orbitals, renders the monolayer a Hund's metal and in an orbital-selective Mott phase (OSMP). This OSMP triggers an FM double exchange mechanism, rationalizing the high Tc in the Hund's metal. This material transitions to a QAH insulator upon consideration of the SOC effect. By leveraging orbital selectivity, the QAH band gap can be enlarged by more than two times (to 137 meV). Our findings showcase Hund's metals as a promising material platform for realizing high-performance quantum topological electronic devices.

Imaging Anisotropic Proton Intercalation in Photochromic MoO3.

Protonation represents a fundamental chemical process with promising applications in the fields of energy, environment, and memory devices. Probing the protonation mechanism, however, presents a formidable challenge owing to the elusiveness of intercalated protons. In this work, we utilize the atomic and electronic structure changes associated with protonation to directly image the proton intercalation pathways in α-MoO3 induced by UV illumination. We reveal the anisotropic intercalation behavior which is initiated by photocatalyzed water dissociation preferentially at the (001) edges and then propagates along the c axis, transforming α-MoO3 into HxMoO3 to realize photochromism. This photochromic process can be reversed via heating in air, leading to anisotropic proton deintercalation, also preferentially along the c axis. The observed anisotropic behavior can be attributed to the intrinsically low energy barriers for both proton migration along the c axis and water dissociation/formation at (001) edges.

Characterization of lncRNA and mRNA profiles in the process of repairing peripheral nerve defects with cell-matrixed nerve grafts.

BACKGROUND: Decellularized extracellular matrix (dECM) is an intriguing natural biomaterial that has garnered significant attention due to its remarkable biological properties. In our study, we employed a cell-matrixed nerve graft for the repair of sciatic nerve defects in rats. The efficacy of this approach was assessed, and concurrently, the underlying molecular regulatory mechanisms were explored to elucidate how such grafts facilitate nerve regeneration. Long noncoding RNAs (lncRNAs) regulate mRNA expression via multiple mechanisms, including post-transcriptional regulation, transcription factor effects, and competitive binding with miRNAs. These interactions between lncRNAs and mRNAs facilitate precise control of gene expression, allowing organisms to adapt to varying biological environments and physiological states. By investigating the expression profiles and interaction dynamics of mRNAs and lncRNAs, we can enhance our understanding of the molecular mechanisms through which cell-matrixed nerve grafts influence neural repair. Such studies are pivotal in uncovering the intricate networks of gene regulation that underpin this process. RESULTS: Weighted gene co-expression network analysis (WGCNA) utilizes clustering algorithms, such as hierarchical clustering, to aggregate genes with similar expression profiles into modules. These modules, which potentially correspond to distinct biological functions or processes, can subsequently be analyzed for their association with external sample traits. By correlating gene modules with specific conditions, such as disease states or responses to treatments, WGCNA enables a deeper understanding of the genetic architecture underlying various phenotypic traits and their functional implications. We identified seven mRNA modules and five lncRNA modules that exhibited associations with treatment or time-related events by WGCNA. We found the blue (mRNAs) module which displayed a remarkable enrichment in "axonal guidance" and "metabolic pathways", exhibited strong co-expression with multiple lncRNA modules, including blue (related to "GnRH secretion" and "pyrimidine metabolism"), green (related to "arginine and proline metabolism"), black (related to "nitrogen metabolism"), grey60 (related to "PPAR signaling pathway"), and greenyellow (related to "steroid hormone biosynthesis"). All of the top 50 mRNAs and lncRNAs exhibiting the strongest correlation were derived from the blue module. Validation of key molecules were performed using immunohistochemistry and qRT-PCR. CONCLUSION: Revealing the principles and molecular regulatory mechanisms of the interaction between materials and biological entities, such as cells and tissues, is a direction for the development of biomimetic tissue engineering technologies and clinically effective products.

Happy people are always similar: The evidence from brain morphological and functional inter-subject correlations.

A fundamental question in the study of happiness is whether there is neural evidence to support a well-known hypothesis that happy people are always similar while unfortunate people have their own misfortunes. To investigate this, we employed several happiness-related questionnaires to identify potential components of happiness, and further investigated and confirmed their associations with personality, mood, aggressive behaviors, and amygdala reactivity to fearful faces within a substantial sample size of college students (n = 570). Additionally, we examined the functional and morphological similarities and differences among happy individuals using the inter-subject representational similarity analysis (IS-RSA). IS-RSA emphasizes the geometric properties in a high-dimensional space constructed by brain or behavioral patterns and focuses on individual subjects. Our behavioral findings unveiled two factors of happiness: individual and social, both of which mediated the effect of personality traits on individual aggression. Subsequently, mood mediated the impact of happiness on aggressive behaviors across two subgroup splits. Functional imaging data revealed that individuals with higher levels of happiness exhibited reduced amygdala reactivity to fearful faces, as evidenced by a conventional face-matching task (n = 104). Moreover, IS-RSA demonstrated that these participants manifested similar neural activation patterns when processing fearful faces within the visual pathway, but not within the emotional network (e.g., amygdala). Morphological observations (n = 425) indicated that individuals with similar high happiness levels exhibited comparable gray matter volume patterns within several networks, including the default mode network, fronto-parietal network, visual network, and attention network. Collectively, these findings offer early neural evidence supporting the proposition that happy individuals may share common neural characteristics.

Facet-Dependent Surface Restructuring on Nickel (Oxy)hydroxides: A Self-Activation Process for Enhanced Oxygen Evolution Reaction.

Unraveling the catalyst surface structure and behavior during reactions is essential for both mechanistic understanding and performance optimization. Here we report a phenomenon of facet-dependent surface restructuring intrinsic to ß-Ni(OH)2 catalysts during oxygen evolution reaction (OER), discovered by the correlative ex situ and operando characterization. The ex situ study after OER reveals ß-Ni(OH)2 restructuring at the edge facets to form nanoporous Ni1-xO, which is Ni deficient containing Ni3+ species. Operando liquid transmission electron microscopy (TEM) and Raman spectroscopy further identify the active role of the intermediate ß-NiOOH phase in both the OER catalysis and Ni1-xO formation, pinpointing the complete surface restructuring pathway. Such surface restructuring is shown to effectively increase the exposed active sites, accelerate Ni oxidation kinetics, and optimize *OH intermediate bonding energy toward fast OER kinetics, which leads to an extraordinary activity enhancement of ∼16-fold. Facilitated by such a self-activation process, the specially prepared ß-Ni(OH)2 with larger edge facets exhibits a 470-fold current enhancement than that of the benchmark IrO2, demonstrating a promising way to optimize metal-(oxy)hydroxide-based catalysts.

Facet-Controlled Synthesis of Unconventional-Phase Metal Alloys for Highly Efficient Hydrogen Oxidation.

Facet control and phase engineering of metal nanomaterials are both important strategies to regulate their physicochemical properties and improve their applications. However, it is still a challenge to tune the exposed facets of metal nanomaterials with unconventional crystal phases, hindering the exploration of the facet effects on their properties and functions. In this work, by using Pd nanoparticles with unconventional hexagonal close-packed (hcp, 2H type) phase, referred to as 2H-Pd, as seeds, a selective epitaxial growth method is developed to tune the predominant growth directions of secondary materials on 2H-Pd, forming Pd@NiRh nanoplates (NPLs) and nanorods (NRs) with 2H phase, referred to as 2H-Pd@2H-NiRh NPLs and NRs, respectively. The 2H-Pd@2H-NiRh NRs expose more (100)h and (101)h facets on the 2H-NiRh shells compared to the 2H-Pd@2H-NiRh NPLs. Impressively, when used as electrocatalysts toward hydrogen oxidation reaction (HOR), the 2H-Pd@2H-NiRh NRs show superior activity compared to the NiRh alloy with conventional face-centered cubic (fcc) phase (fcc-NiRh) and the 2H-Pd@2H-NiRh NPLs, revealing the crucial role of facet control in enhancing the catalytic performance of unconventional-phase metal nanomaterials. Density functional theory (DFT) calculations further unravel that the excellent HOR activity of 2H-Pd@2H-NiRh NRs can be attributed to the more exposed (100)h and (101)h facets on the 2H-NiRh shells, which possess high electron transfer efficiency, optimized H* binding energy, enhanced OH* binding energy, and a low energy barrier for the rate-determining step during the HOR process.

The computational and neural substrates of individual differences in impulsivity under loss framework.

Numerous neuroimaging studies have identified significant individual variability in intertemporal choice, often attributed to three neural mechanisms: (1) increased reward circuit activity, (2) decreased cognitive control, and (3) prospection ability. These mechanisms that explain impulsivity, however, have been primarily studied in the gain domain. This study extends this investigation to the loss domain. We employed a hierarchical Bayesian drift-diffusion model (DDM) and the inter-subject representational similarity approach (IS-RSA) to investigate the potential computational neural substrates underlying impulsivity in loss domain across two experiments (n = 155). These experiments utilized a revised intertemporal task that independently manipulated the amounts of immediate and delayed-loss options. Behavioral results demonstrated positive correlations between the drift rate, measured by the DDM, and the impulsivity index K in Exp. 1 (n = 97) and were replicated in Exp. 2 (n = 58). Imaging analyses further revealed that the drift rate significantly mediated the relations between brain properties (e.g., prefrontal cortex activations and gray matter volume in the orbitofrontal cortex and precuneus) and K in Exp. 1. IS-RSA analyses indicated that variability in the drift rate also mediated the associations between inter-subject variations in activation patterns and individual differences in K. These findings suggest that individuals with similar impulsivity levels are likely to exhibit similar value processing patterns, providing a potential explanation for individual differences in impulsivity within a loss framework.

Engineered bone marrow mesenchymal stem cell-derived exosomes loaded with miR302 through the cardiomyocyte specific peptide can reduce myocardial ischemia and reperfusion (I/R) injury.

BACKGROUND: MicroRNA (miRNA)-based therapies have shown great potential in myocardial repair following myocardial infarction (MI). MicroRNA-302 (miR302) has been reported to exert a protective effect on MI. However, miRNAs are easily degraded and ineffective in penetrating cells, which limit their clinical applications. Exosomes, which are small bioactive molecules, have been considered as an ideal vehicle for miRNAs delivery due to their cell penetration, low immunogenicity and excellent stability potential. Herein, we explored cardiomyocyte-targeting exosomes as vehicles for delivery of miR302 into cardiomyocyte to potentially treat MI. METHODS: To generate an efficient exosomal delivery system that can target cardiomyocytes, we engineered exosomes with cardiomyocyte specific peptide (CMP, WLSEAGPVVTVRALRGTGSW). Afterwards, the engineered exosomes were characterized and identified using transmission electron microscope (TEM) and Nanoparticle Tracking Analysis (NTA). Later on, the miR302 mimics were loaded into the engineered exosomes via electroporation technique. Subsequently, the effect of the engineered exosomes on myocardial ischemia and reperfusion (I/R) injury was evaluated in vitro and in vivo, including MTT, ELISA, real-time quantitative polymerase chain reaction (PCR), western blot, TUNNEL staining, echocardiogram and hematoxylin and eosin (HE) staining. RESULTS: Results of in vitro experimentation showed that DSPE-PEG-CMP-EXO could be more efficiently internalized by H9C2 cells than unmodified exosomes (blank-exosomes). Importantly, compared with the DSPE-PEG-CMP-EXO group, DSPE-PEG-CMP-miR302-EXO significantly upregulated the expression of miR302, while exosomes loaded with miR302 could enhance proliferation of H9C2 cells. Western blot results showed that the DSPE-PEG-CMP-miR302-EXO significantly increased the protein level of Ki67 and Yap, which suggests that DSPE-PEG-CMP-miR302-EXO enhanced the activity of Yap, the principal downstream effector of Hippo pathway. In vivo, DSPE-PEG-CMP-miR302-EXO improved cardiac function, attenuated myocardial apoptosis and inflammatory response, as well as reduced infarct size significantly. CONCLUSION: In conclusion, our findings suggest that CMP-engineered exosomes loaded with miR302 was internalized by H9C2 cells, an in vitro model for cardiomyocytes coupled with potential enhancement of the therapeutic effects on myocardial I/R injury.

FURION: modeling of FEL pulses propagation in dispersive soft X-ray beamline systems.

Modern X-ray free-electron lasers (XFELs) can generate pulses with durations ranging from femtoseconds to attoseconds. The numerical evaluation of ultra-short XFEL pulses through beamline systems is a critical process of beamline system design. However, the bandwidth of such ultra-short XFEL pulses is often non-negligible, and the propagation cannot be simply approximated using the central wavelength, especially in dispersive beamline systems. We developed a numerical model which is called Fourier optics based Ultrashort x-Ray pulse propagatION tool (FURION). This model can not only be used to simulate dispersive beamline systems but also to evaluate non-dispersive beamline systems. The FURION model utilizes Fresnel integral and angular spectrum integral to perform ultra-short XFEL pulse propagation in free space. We also present the method for XFEL pulse propagation through different types of dispersive gratings, which are commonly used in soft X-ray beamline systems. By using FURION, a start-to-end simulation of the FEL-1 beamline system at Shenzhen superconducting soft X-ray free electron laser (S3FEL) is carried out. This model can also be used to evaluate gratings-based spectrometers, beam splitters, pulse compressors, and pulse stretchers. This work provides valuable insights into the start-to-end simulation of X-ray beamline systems.

The novel peptide PFAP1 promotes primordial follicle activation by binding to MCM5.

Premature ovarian failure (POF) is a complication of ovarian dysfunction resulting from the depletion or dysfunction of primordial follicles (PFs) in the ovaries. However, residual follicles that have the potential to be activated are present in POF or aged women. Little is known about the mechanisms by which the remaining dormant PFs in POF patients are activated. Using mass spectrometry, we screened differentially generated peptides extracted from the ovarian cortical tissue biopsies of patients with or without POF, during which we identified PFAP1, a peptide that significantly promoted the activation of PFs in the ovaries of 3 dpp mice in vitro. PFAP1 reversed age-related fertility damage in vivo to a certain extent, promoted estrogen (E2) and anti-mullerian hormone (AMH) production (p < .05), and decreased the levels of follicle-stimulating hormone (FSH) (p < .05). In newborn mouse ovaries, PFAP1 could bind to the protein minichromosome maintenance protein 5 (MCM5) and inhibit its ubiquitination and degradation. In addition, PFAP1 promoted the proliferation of GCs, probably by regulating the function and production of MCM5. In conclusion, PFAP1 could promote the activation of PFs in the ovaries of newborn mice, partially restore the ovarian function of aged mice, and increase the proliferation of primary granulosa cells (GCs) by regulating the function of MCM5. PFAP1 is a promising novel peptide that may be developed into a new therapeutic agent for POF and other ovarian diseases.

Electroacupuncture Alleviates Obesity and Insulin Resistance via the GLP-1-VTADA Reward Circuit.

INTRODUCTION: We investigated the effects of electroacupuncture (EA) on improving obesity and insulin resistance (IR) in high-fat diet-induced (HFDI) obese rats by modulating the nucleus tractus solitarius (NTS) glucagon-like peptide-1 (GLP-1)-ventral tegmental area (VTA) dopamine (DA) neural reward circuit, thereby uncovering a possible central mechanism underlying EA's actions in improving obesity and IR. METHODS: We randomly allocated 45 Wistar male rats to five groups (normal, model, EA, chemogenetic activation, chemogenetic suppression + EA), with 9 rats in each group. All interventions were conducted within 8 weeks after the model was established. We tested rats for obesity phenotypes included body mass, Lee's index, 24-h food intake, and glucose-metabolism parameters. We observed protein and gene expression for GLP-1 in the NTS and tyrosine hydroxylase in the VTA by Western blotting and real-time polymerase chain reaction, as well as their localization by immunofluorescence. We also determined the DA content in the VTA using high-performance liquid chromatography. RESULTS: Obese rats exhibited marked hyperphagia, accompanied by increased excitability of DA neurons in the VTA region and reduced insulin sensitivity. After EA treatment, obese rats showed augmented excitability of NTS GLP-1 and suppression of VTADA neurons with a diminution in food intake, showing results similar to those in the chemogenetic activation group. After EA treatment and while inhibiting GLP-1 neurons by chemogenetics, the effect of EA on activating GLP-1 neurons and inhibiting VTADA was partially abrogated. The effects of improving obesity and insulin sensitivity were likewise also suppressed. CONCLUSION: EA effectively activated GLP-1 neurons in the NTS, thereby inhibited the expression of DA in the VTA and improved obesity and insulin sensitivity in HFDI-obese rats.

Solvent-regulated self-assembled carbon nitride for photocatalytic reduction of U(VI) in water.

Manufacturing high-performance and reusable materials from radioactive uranium-containing wastewater remains a significant challenge. Herein, a supramolecular self-assembly strategy was proposed, using melamine and cyanuric acid as precursors and using intermolecular hydrogen bond force to form carbon nitride (CN-D) in different solvents through a single thermal polymerization strategy. Supramolecular self-assembly method is a promising strategy to synthesize a novel carbon nitride with molecular regulatory properties. In addition, 98% of U(VI) in wastewater can be removed by using CN-D for 60 min under visible light. After five cycles of recycling, more than 95% of U(VI) can still be reduced, indicating that it has good recyclability and reusability. This study not only provides an efficient photocatalytic method of uranium reduction, but also provides a new method for self-assembly synthesis.

Convolutional autoencoder based on latent subspace projection for anomaly detection.

Image anomaly detection (AD) is widely researched on many occasions in computer vision tasks. High-dimensional data, such as image data, with noise and complex background is still challenging to detect anomalies under the situation that imbalanced or incomplete data are available. Some deep learning methods can be trained in an unsupervised way and map the original input into low-dimensional manifolds to predict larger differences in anomalies according to normal ones by dimension reduction. However, training a single low-dimension latent space is limited to present the low-dimensional features due to the fact that the noise and irreverent features are mapped into this space, resulting in that the manifolds are not discriminative for detecting anomalies. To address this problem, a new autoencoder framework is proposed in this study with two trainable mutually orthogonal complementary subspaces in the latent space, by latent subspace projection (LSP) mechanism, which is named as LSP-CAE. Specifically, latent subspace projection is used to train the latent image subspace (LIS) and the latent kernel subspace (LKS) in the latent space of the autoencoder-like model respectively, which can enhance learning power of different features from the input instance. The features of normal data are projected into the latent image subspace, while the latent kernel subspace is trained to extract the irrelevant information according to normal features by end-to-end training. To verify the generality and effectiveness of the proposed method, we replace the convolutional network with the fully-connected network contucted in the real-world medical datasets. The anomaly score based on projection norms in two subspace is used to evaluate the anomalies in the testing. Consequently, our proposed method can achieve the best performance according to four public datasets in comparison of the state-of-the-art methods.

Alda-1 Ameliorates Oxidative Stress-Induced Cardiomyocyte Damage by Inhibiting the Mitochondrial ROS/TXNIP/NLRP3 Pathway.

Alda-1 functions as an agonist of aldehyde dehydrogenase (ALDH2) within the mitochondria, contributing to the preservation of mitochondrial structure and function. This study aimed to determine whether Alda-1 inhibited the accumulation of mitochondrial reactive oxygen species (mtROS) and improved cardiomyocyte damage under oxidative stress. Cardiomyocytes derived from human induced pluripotent embryonic stem cells (iPSC-CMs) and human AC16 cardiomyocytes were chosen for the experiments. Oxidative stress was induced in both cardiomyocyte types using hydrogen peroxide (H2O2), a commonly employed agent. The mtROS accumulation and mitochondrial functional status were assessed by measuring the ROS content, mitochondrial membrane potential, and mitochondrial respiratory chain function. Co-IP experiments were used to analyze whether mtROS promoted protein interactions between TXNIP and NLRP3 and induced NLRP3 inflammasome activation. The results showed that Alda-1 mitigated damage to mitochondrial structure and function under oxidative stress, concurrently reducing the accumulation of mtROS. Co-IP experiments revealed that elevated mtROS levels attenuated the protein interaction between TXNIP and TRX while intensifying the interaction between TXNIP and NLRP3. Consequently, this triggers activation of the NLRP3 inflammasome, leading to cardiomyocyte damage. In contrast, TXNIP knockdown inhibited H2O2-induced myocardial injury and enhanced the therapeutic effects of Alda-1. Collectively, the results show that, in an H2O2 environment, Alda-1 increased the production of ALDH2 activity in cardiomyocytes, hindered the production of mtROS, disrupted the interaction between TXNIP and NLRP3, and alleviated myocardial damage during oxidative stress.