Holographic multiplexing metasurface with twisted diffractive neural network.

As the cornerstone of AI generated content, data drives human-machine interaction and is essential for developing sophisticated deep learning agents. Nevertheless, the associated data storage poses a formidable challenge from conventional energy-intensive planar storage, high maintenance cost, and the susceptibility to electromagnetic interference. In this work, we introduce the concept of metasurface disk, meta-disk, to expand the capacity limits of optical holographic storage by leveraging uncorrelated structural twist. We develop a physical twisted neural network to describe the optical behavior of the meta-disk and conduct a comprehensive lateral error analysis, where the meta-disk stores large volumes of information through internal structural multiplexing. Two-layer 640 µm x 640 µm meta-disk is sufficient to store over hundreds of high-fidelity images with SSIM of 0.8. By harnessing advanced three-dimensional (3D) printing technology, optical holographic storage is experimentally demonstrated with Pancharatnam-Berry metasurfaces. Our technology provides essential backing for the next generation of optical storage, display, encryption, and multifunctional optical analog computing.

A Universal Framework for General Prediction of Physicochemical Properties: The Natural Growth Model.

To precisely and reasonably describe the contribution of interatomic and intermolecular interactions to the physicochemical properties of complex systems, a chemical message passing strategy as driven by graph neural network is proposed. Thus, by distinguishing inherent and environmental features of atoms, as well as proper delivering of these messages upon growth of systems from atoms to bulk level, the evolution of system features affords eventually the target properties like the adsorption wavelength, emission wavelength, solubility, photoluminescence quantum yield, ionization energy, and lipophilicity. Considering that such a model combines chemical principles and natural behavior of atom aggregation crossing multiple scales, most likely, it will be proven to be rational and efficient for more general aims in dealing with complex systems.

Group Contribution Method Supervised Neural Network for Precise Design of Organic Nonlinear Optical Materials.

To rationalize the design of D-π-A type organic small-molecule nonlinear optical materials, a theory guided machine learning framework is constructed. Such an approach is based on the recognition that the optical property of the molecule is predictable upon accumulating the contribution of each component, which is in line with the concept of group contribution method in thermodynamics. To realize this, a Lewis-mode group contribution method (LGC) has been developed in this work, which is combined with the multistage Bayesian neural network and the evolutionary algorithm to constitute an interactive framework (LGC-msBNN-EA). Thus, different optical properties of molecules are afforded accurately and efficiently-by using only a small data set for training. Moreover, by employing the EA model designed specifically for LGC, structural search is well achievable. The origins of the satisfying performance of the framework are discussed in detail. Considering that such a framework combines chemical principles and data-driven tools, most likely, it will be proven to be rational and efficient to complete mission regarding structure design in related fields.

The Role of Contrast-enhanced Ultrasound in the Femoral Head Perfusion Evaluation: A Pilot Study.

OBJECTIVES: We explored the value of contrast-enhanced ultrasound (CEUS) in evaluating femoral head (FH) perfusion, guiding interventions and follow-up for infants with developmental dysplasia of the hip (DDH) and septic arthritis of the hip (SAH). The aim was to provide robust evidence for clinical assessment. METHODS: Ten infants, including 7 with DDH and 3 with SAH, were prospectively enrolled, with their bilateral hips alternately scanned during the CEUS exams. Twenty hips were classified into the case group (n = 11) and the control group (n = 9). Pre- and post-interventional studies were performed in DDH infants requiring interventions. FH perfusion was assessed by the perfusion area ratio (PAR) and quadrant location of microbubble-defect regions. RESULTS: In the case group, 25 CEUS studies were conducted, including 11 baseline, 7 follow-up and 7 post-intervention studies. The PAR significantly decreased in the case group (49.79% vs. 100.00%, p < 0.05). The microbubble-defect regions averagely affected 2 quadrants, primarily quadrat No. 3 (30%) and No. 4 (32%). Seven hip abduction angle adjustments were made based on pre-interventional studies, resulting in a significant increase in PAR in post-interventional studies (37.63% vs. 60.24%, p < 0.05). PAR increased in follow-up studies compared to baseline values (45.61% vs. 76.07%, p < 0.05). The inter- and intra-observer reproducibility of PAR measurements were excellent (intraclass correlation coefficient, both 0.97). CONCLUSION: CEUS proves to be a promising technique for quantitatively detecting FH perfusion in DDH and SAH infants with high reproducibility. It is valuable for baseline, intra-intervention and follow-up studies, aiming in clinical conditions and therapeutic effect evaluation.

One-pot, Solvent Free Synthesis of 2,5-Furandicarboxylic Acid from Deep Eutectic Mixtures of Sugars as Mediated by Bifunctional Catalyst.

Currently one-pot conversion of sugars to 2,5-furandicarboxylic acid (FDCA) is of significant interest due to the attainability of sugars as a feedstock and the enormous potential of FDCA as a bioplastic monomer. However, it remains challenging to construct efficient catalysts for this process. In this study, Co3O4 species were anchored to a sulfonated covalent organic framework thus affording a bifunctional catalyst (Co3O4@COF-SO3H). The sulfonic acid sites dehydrate sugars to 5-hydroxymethylfurfural (HMF), which is next oxidized to FDCA as catalyzed by the Co3O4 species. Such a process was applied in the conversion of various binary and ternary deep eutectic mixtures involving choline chloride and sugars without additional solvent. The maximum FDCA yield of 84% was obtained using glucose-fructose eutectic mixture as the substrates. Moreover, the catalyst was recyclable and stable under the applied reaction conditions. Our process eliminates the employment of organic solvents and expensive noble metal catalysts, resulting in green and economic biomass conversions.

Negative Conductivity Induced Reconfigurable Gain Metasurfaces and Their Nonlinearity.

The past decades have witnessed the rapid development of metamaterials and metasurfaces. However, loss is still a challenging problem limiting numerous practical applications, including long-range wireless communications, superscattering, and non-Hermitian physics. Recently, great effort has been made to minimize the loss, however, they are too complicated for practical implementation and still restricted by the theoretical limit. Here, we propose and experimentally realize a tunable gain metasurface induced by negative conductivity, with deep theoretical analysis from scattering theory and equivalent circuits. In the experiment, we create metasurface samples embedded with tunable negative (or positive) conductivity to achieve adjustable gain (or loss). By varying the control bias voltages, the metasurfaces can reflect incident waves with additional controllable gain. Interestingly, we find the gain metasurfaces inherently pose nonlinearities, which are beneficial for nonlinear optics and microwave applications, particularly for the nonlinear activation of wave-based neural networks.

The First-In-Class Deubiquitinase-Targeting Chimera Stabilizes and Activates cGAS.

Deubiquitinase-targeting chimera (DUBTAC) is a promising technology for inducing targeted protein stabilization (TPS). Despite its therapeutic potential, very few proteins have been stabilized by DUBTACs to date. The limited applicability of this technology is likely due to the modest DUBTAC-induced protein stabilization effect, and the scarcity of effective deubiquitinase ligands that can be harnessed for DUBTAC development. Here, we report the discovery of MS7829 and MS8588, the first-in-class DUBTACs of cGAS, a key component of the cGAS-STING pathway. While these DUBTACs are based on a cGAS inhibitor, they effectively stabilized cGAS and activated the cGAS/STING/IRF3 signaling. To develop these cGAS DUBTACs, we optimized EN523, an OTUB1 covalent ligand, into an improved ligand, MS5105. We validated MS5105 by generating a MS5105-based CFTR DUBTAC, which was approximately 10-fold more effective in stabilizing the ΔF508-CFTR mutant protein than the previously reported EN523-based CFTR DUBTAC. Overall, this work advances the DUBTAC technology for TPS.

Zirconia specimens printed by vat photopolymerization: Mechanical properties, fatigue properties, and fractography analysis.

PURPOSE: The mechanical and fatigue properties of zirconia specimens printed by vat photopolymerization (VPP) were evaluated and compared with those of zirconia specimens milled by computer numerical control (CNC). MATERIALS AND METHODS: Bar-shaped specimens were printed by stereolithography (SL) and digital light processing (DLP). CNC-milled specimens were used as control samples. The fracture toughness, hardness, and flexural strength properties of the zirconia specimens were evaluated via single edge V-notch beam tests, Vickers hardness tests, and 3-point bending tests. Dynamic fatigue tests were carried out in distilled water using a step-stress test. After static bending and dynamic step-stress testing, fractography analysis was performed. Statistical analysis was carried out to compare the fracture toughness, hardness, flexural strength, and fatigue cycle results of each group (α = 0.05). RESULTS: The fracture toughness values did not significantly differ among the groups (p > 0.05). The flexural strength was 894.10 MPa for SL, 831.46 MPa for DLP, and 1140.39 MPa for CNC. The flexural strength of CNC was greater than that of SL and DLP (p < 0.01). The mean fatigue cycles were 23498.07 for SL, 19858.60 for DLP, and 31566.80 for CNC. The mean fatigue failure strength was 643.13 MPa for SL, 530.63 MPa for DLP, and 903.75 MPa for CNC. The fatigue failure strength of CNC was greater than that of SL and DLP (p < 0.05). Fractography analysis revealed material defects at the fracture origin for each group. A partially fused structure of the incompletely debonded resin could be observed in SL, and a porous region of incompletely sintered zirconia grains could be observed in CNC. CONCLUSIONS: The fracture toughness and hardness of zirconia printed by VPP are comparable to those of zirconia milled by CNC. However, zirconia milled by CNC has superior static flexural strength and dynamic fatigue resistance. Further studies are needed to explore the clinical applications of VPP-printed zirconia.

Reducing the uncertainty in estimating soil microbial-derived carbon storage.

Soil organic carbon (SOC) is the largest carbon pool in terrestrial ecosystems and plays a crucial role in mitigating climate change and enhancing soil productivity. Microbial-derived carbon (MDC) is the main component of the persistent SOC pool. However, current formulas used to estimate the proportional contribution of MDC are plagued by uncertainties due to limited sample sizes and the neglect of bacterial group composition effects. Here, we compiled the comprehensive global dataset and employed machine learning approaches to refine our quantitative understanding of MDC contributions to total carbon storage. Our efforts resulted in a reduction in the relative standard errors in prevailing estimations by an average of 71% and minimized the effect of global variations in bacterial group compositions on estimating MDC. Our estimation indicates that MDC contributes approximately 758 Pg, representing approximately 40% of the global soil carbon stock. Our study updated the formulas of MDC estimation with improving the accuracy and preserving simplicity and practicality. Given the unique biochemistry and functioning of the MDC pool, our study has direct implications for modeling efforts and predicting the land-atmosphere carbon balance under current and future climate scenarios.

Harnessing the Missing Spectral Correlation for Metasurface Inverse Design.

A long-held tenet in computer science asserts that the training of deep learning is analogous to an alchemical furnace, and its "black box" signature brings forth inexplicability. For electromagnetic metasurfaces, the related intelligent applications also get stuck into such a dilemma. Although the past 5 years have witnessed a proliferation of deep learning-based works across complex photonic scenarios, they neglect the already existing but untapped physical laws. Here, the intrinsic correlation between the real and imaginary parts of the spectra are revealed using Kramers-Kronig relations, which is then mimicked by bidirectional information flow in neural network space. Such consideration harnesses the missing spectral connection to extract crucial features effectively. The bidirectional recurrent neural network is benchmarked in metasurface inverse design and compare it with a fully-connected neural network, unidirectional recurrent neural network, and attention-based transformer. Beyond the improved accuracy, the study examines the intermediate information products and physically explains why different network structures yield different performances. The work offers explicable perspectives to utilize physical information in the deep learning field and facilitates many data-intensive research endeavors.

Non-Invasive Self-Adaptive Information States' Acquisition inside Dynamic Scattering Spaces.

Pushing the information states' acquisition efficiency has been a long-held goal to reach the measurement precision limit inside scattering spaces. Recent studies have indicated that maximal information states can be attained through engineered modes; however, partial intrusion is generally required. While non-invasive designs have been substantially explored across diverse physical scenarios, the non-invasive acquisition of information states inside dynamic scattering spaces remains challenging due to the intractable non-unique mapping problem, particularly in the context of multi-target scenarios. Here, we establish the feasibility of non-invasive information states' acquisition experimentally for the first time by introducing a tandem-generated adversarial network framework inside dynamic scattering spaces. To illustrate the framework's efficacy, we demonstrate that efficient information states' acquisition for multi-target scenarios can achieve the Fisher information limit solely through the utilization of the external scattering matrix of the system. Our work provides insightful perspectives for precise measurements inside dynamic complex systems.

Tumor microenvironment-regulated drug delivery system combined with sonodynamic therapy for the synergistic treatment of breast cancer.

Co-loading of sonosensitizers and chemotherapeutic drugs into nanocarriers can improve the biocompatibilities, stabilities, and targeting of drugs and reduce the adverse reactions of drugs, providing a robust platform to orchestrate the synergistic interplay between chemotherapy and sonodynamic therapy (SDT) in cancer treatment. In this regard, biodegradable manganese dioxide (MnO2) has attracted widespread attention because of its unique properties in the tumor microenvironment (TME). Accordingly, herein, MnO2 nanoshells with hollow mesoporous structures (H-MnO2) were etched to co-load hematoporphyrin monomethyl ether (HMME) and doxorubicin (DOX), and DOX/HMME-HMnO2@bovine serum albumin (BSA) obtained after simple BSA modification of DOX/HMME-HMnO2 exhibited excellent hydrophilicity and dispersibility. H-MnO2 rapidly degraded in the weakly acidic TME, releasing loaded HMME and DOX, and catalysed the decomposition of H2O2 abundantly present in TME, producing oxygen (O2) in situ, significantly increasing O2 concentration and downregulating the hypoxia-inducible factor 1α (HIF-1α). After irradiation of the tumor area with low-frequency ultrasound, the drug delivery efficiency of DOX/HMME-HMnO2@BSA substantially increased, and the excited HMME generated a large amount of reactive oxygen species (ROS), which caused irreversible damage to tumor cells. Moreover, the cell death rate exceeded 60% after synergistic SDT-chemotherapy. Therefore, the pH-responsive nanoshells designed in this study can realize drug accumulation in tumor regions by responding to TME and augment SDT-chemotherapy potency for breast cancer treatment by improving hypoxia in tumors. Thus, this study provides theoretical support for the development of multifunctional nanocarriers and scientific evidence for further exploration of safer and more efficient breast cancer treatments.

Protein Profiles and Novel Molecular Biomarkers of Schizophrenia Based on 4D-DIA Proteomics.

Schizophrenia is a severe psychological disorder. The current diagnosis mainly relies on clinical symptoms and lacks laboratory evidence, which makes it very difficult to make an accurate diagnosis especially at an early stage. Plasma protein profiles of schizophrenia patients were obtained and compared with healthy controls using 4D-DIA proteomics technology. Furthermore, 79 DEPs were identified between schizophrenia and healthy controls. GO functional analysis indicated that DEPs were predominantly associated with responses to toxic substances and platelet aggregation, suggesting the presence of metabolic and immune dysregulation in patients with schizophrenia. KEGG pathway enrichment analysis revealed that DEPs were primarily enriched in the chemokine signaling pathway and cytokine receptor interactions. A diagnostic model was ultimately established, comprising three proteins, namely, PFN1, GAPDH and ACTBL2. This model demonstrated an AUC value of 0.972, indicating its effectiveness in accurately identifying schizophrenia. PFN1, GAPDH and ACTBL2 exhibit potential as biomarkers for the early detection of schizophrenia. The findings of our studies provide novel insights into the laboratory-based diagnosis of schizophrenia.

Preparation of VC nanoliposomes by high pressure homogenization: Process optimization and evaluation of efficacy, transdermal absorption, and stability.

Vitamin C (VC) possesses antioxidant and whitening effects. However, its effectiveness is hindered by challenges such as instability, impaired solubility, and limited bioavailability hinder. In this study, VC was encapsulated in nanoliposomes by primary emulsification and high-pressure homogenization. The VC nanoliposomes were comprehensively characterized for their microscopic morphology, particle size, polydispersity index (PDI), and encapsulation efficiency (EE). Orthogonal experiments were designed to optimize the optimal preparation process, and the antioxidant activity, whitening efficacy, transdermal absorption, and stability of VC nanoliposomes were evaluated based on this optimized process. The findings demonstrated the high reproducibility of the optimal process, with particle size, PDI, and EE values of 113.502 ± 4.360 nm, 0.104 ± 0.010, and 56.09 ± 1.01 %, respectively. Differential scanning calorimetry analysis showed effective encapsulation of VC nanoliposomes with better thermal stability than aqueous VC solution. Besides, the VC nanoliposomes demonstrated excellent antioxidant and whitening effects in efficacy experiments, stronger skin permeability in transdermal experiments and fluorescence tracking. Furthermore, storage stability tests indicated that the VC in nanoliposomes remained relatively stable after 60 days of storage. These findings highlighted the potential use of VC nanoliposomes in a wide range of applications for the cosmetic market, especially in the development of ingredients for skin care products.

Myricetin Acts as an Inhibitor of Type II NADH Dehydrogenase from Staphylococcus aureus.

BACKGROUND: Staphylococcus aureus is a common pathogenic microorganism in humans and animals. Type II NADH oxidoreductase (NDH-2) is the only NADH:quinone oxidoreductase present in this organism and represents a promising target for the development of anti-staphylococcal drugs. Recently, myricetin, a natural flavonoid from vegetables and fruits, was found to be a potential inhibitor of NDH-2 of S. aureus. The objective of this study was to evaluate the inhibitory properties of myricetin against NDH-2 and its impact on the growth and expression of virulence factors in S. aureus. RESULTS: A screening method was established to identify effective inhibitors of NDH-2, based on heterologously expressed S. aureus NDH-2. Myricetin was found to be an effective inhibitor of NDH-2 with a half maximal inhibitory concentration (IC50) of 2 µM. In silico predictions and enzyme inhibition kinetics further characterized myricetin as a competitive inhibitor of NDH-2 with respect to the substrate menadione (MK). The minimum inhibitory concentrations (MICs) of myricetin against S. aureus strains ranged from 64 to 128 µg/mL. Time-kill assays showed that myricetin was a bactericidal agent against S. aureus. In line with being a competitive inhibitor of the NDH-2 substrate MK, the anti-staphylococcal activity of myricetin was antagonized by MK-4. In addition, myricetin was found to inhibit the gene expression of enterotoxin SeA and reduce the hemolytic activity induced by S. aureus culture on rabbit erythrocytes in a dose-dependent manner. CONCLUSIONS: Myricetin was newly discovered to be a competitive inhibitor of S. aureus NDH-2 in relation to the substrate MK. This discovery offers a fresh perspective on the anti-staphylococcal activity of myricetin.

3D Intelligent Cloaked Vehicle Equipped with Thousand-Level Reconfigurable Full-Polarization Metasurfaces.

A crucial aspect in shielding a variety of advanced electronic devices from electromagnetic detection involves controlling the flow of electromagnetic waves, akin to invisibility cloaks. Decades ago, the exploration of transformation optics heralded the dawn of modern invisibility cloaks, which has stimulated immense interest across various physical scenarios. However, most prior research is simplified to low-dimensional and stationary hidden objects, limiting their practical applicability in a dynamically changing world. This study develops a 3D large-scale intelligent cloak capable of remaining undetectable even in non-stationary conditions. By employing thousand-level reconfigurable full-polarization metasurfaces, this work has achieved an exceptionally high degree of freedom in sculpting the scattering waves as desired. Serving as the core computational unit, a hybrid inverse design enables the cloaked vehicle to respond in real-time, with a rapid reaction time of just 70 ms. These experiments integrate the cloaked vehicle with a perception-decision-control-execution system and evaluate its performance under random static positions and dynamic travelling trajectories, achieving a background scattering matching degree of up to 93.3%. These findings establish a general paradigm for the next generation of intelligent meta-devices in real-world settings, potentially paving the way for an era of "Electromagnetic Internet of Things."

USP7-Based Deubiquitinase-Targeting Chimeras Stabilize AMPK.

Deubiquitinase-targeting chimeras (DUBTACs) have been recently developed to stabilize proteins of interest, which is in contrast to targeted protein degradation (TPD) approaches that degrade disease-causing proteins. However, to date, only the OTUB1 deubiquitinase has been utilized to develop DUBTACs via an OTUB1 covalent ligand, which could unexpectedly compromise the endogenous function of OTUB1 owing to its covalent nature. Here, we show for the first time that deubiquitinase USP7 can be harnessed for DUBTAC development. Based on a noncovalent ligand of USP7, we developed USP7-based DUBTACs that stabilized the ΔF508-CFTR mutant protein as effectively as the previously reported OTUB1-based DUBTAC. Importantly, using two different noncovalent ligands of USP7, we developed the first AMPK DUBTACs that appear to selectively stabilize different isoforms of AMPKß, leading to elevated AMPK signaling. Overall, these results highlight that, in addition to OTUB1, USP7 can be leveraged to develop DUBTACs, thus significantly expanding the limited toolbox for targeted protein stabilization and the development of novel AMPK DUBTACs as potential therapeutics.

Suitability and Trueness of the Removable Partial Denture Framework Fabricating by Polyether Ether Ketone with CAD-CAM Technology.

The object of the study was to evaluate the suitability and trueness of the removable partial denture (RPD) framework fabricated by polyether ether ketone (PEEK) with the CAD-CAM technology in vitro. Four different types of dentition defects were selected. In each type, five PEEK RPD frameworks were fabricated by the CAD-CAM technology, while five Co-Cr RPD frameworks were made by traditional casting. The suitability of the framework was evaluated by silicone rubber film slice measurement and the three-dimensional image overlay method. The trueness of the PEEK framework was detected by the three-dimensional image overlay method. Data were statistically analyzed with the use of an independent samples t-test (α = 0.05). The suitability values by silicone rubber film slice measurement of the PEEK group were lower than those of the Co-Cr group in four types, with the differences indicating statistical significance (p < 0.05) in type one, type two, and type four. The suitability values using the three-dimensional image overlay method showed no statistical differences (p > 0.05) between the two groups in four types. The trueness values of the PEEK group were within the allowable range of clinical error. The suitability and trueness of the PEEK RPD framework fabricated by CAD-CAM technology met the requirements of the clinical prosthesis.

Preoperative single-dose camrelizumab and/or microwave ablation in women with early-stage breast cancer: A window-of-opportunity trial.

BACKGROUND: Immune checkpoint blockade has shown low response rates for advanced breast cancer, and combination strategies are needed. Microwave ablation (MWA) may be a trigger of antitumor immunity. This window-of-opportunity trial (ClinicalTrials.gov: NCT04805736) was conducted to determine the safety and feasibility of preoperative camrelizumab (an anti-PD-1 antibody) combined with MWA in the treatment of early-stage breast cancer. METHODS: Sixty participants were randomized to preoperatively receive single-dose camrelizumab alone (n = 20), MWA alone (n = 20), or camrelizumab+MWA (n = 20). A random number table was used to allocate interventions. The primary outcome was the safety and feasibility of MWA combined with camrelizumab. FINDINGS: Camrelizumab and MWA were well tolerated alone and in combination without delays in prescheduled surgery. No treatment-related grade III/IV adverse events were observed. Different from in the single-dose camrelizumab or MWA group, participants showed stable counts of blood cells after combination therapy. After combination therapy, peripheral CD8+ T cells showed enhanced cytotoxic and effect-memory functions. Clonal expansional CD8+ T cells showed higher cytotoxic activity and effector memory- and tumor-specific signatures than emergent clones after combination therapy. Enhanced interactions between clonal expansional CD8+ T cells and monocytes were observed, suggesting that monocytes contributed to the enhanced functions of clonal expansional CD8+ T cells. Major histocompatibility complex (MHC) class I-related pathways and interferon signaling pathways were activated in monocytes by combination therapy. CONCLUSIONS: Camrelizumab combined with MWA was feasible for early-stage breast cancer. Peripheral CD8+ T cells were activated after combination therapy, dependent on monocytes with activated MHC class I pathways. FUNDING: This study was supported by the Natural Science Foundation of Jiangsu Province (BK20230017).

Carbon-Atom Exchange between [MC2]+ (M = Os and Ir) and Methane: on the Thermodynamic and Dynamic Aspects.

Gas-phase reactions of [OsC2]+ and [IrC2]+ with methane at ambient temperature have been studied using quadrupole-ion trap mass spectrometry combined with quantum chemical calculations. Both [OsC2]+ and [IrC2]+ undergo carbon-atom exchange reactions with methane. The associated mechanisms for the two systems are found to be similar. The differences in the rates of carbon isotope exchange reactions of methane with [MC2]+ (M = Os and Ir) are explained by several factors like the energy barrier for the initial H3C-H bond breaking processes, the molecular dynamics, orbital interactions, and the H-binding energies of the pivotal steps. Besides, the number of participating valence orbitals might be one of the keys to regulate the rate in the key step. The present findings may provide useful ideas and inspiration for designing similar processes.