Machine-Learning-Assisted Nanozyme Design: Lessons from Materials and Engineered Enzymes.

Nanozymes are nanomaterials that exhibit enzyme-like biomimicry. In combination with intrinsic characteristics of nanomaterials, nanozymes have broad applicability in materials science, chemical engineering, bioengineering, biochemistry, and disease theranostics. Recently, the heterogeneity of published results has highlighted the complexity and diversity of nanozymes in terms of consistency of catalytic capacity. Machine learning (ML) shows promising potential for discovering new materials, yet it remains challenging for the design of new nanozymes based on ML approaches. Alternatively, ML is employed to promote optimization of intelligent design and application of catalytic materials and engineered enzymes. Incorporation of the successful ML algorithms used in the intelligent design of catalytic materials and engineered enzymes can concomitantly facilitate the guided development of next-generation nanozymes with desirable properties. Here, recent progress in ML, its utilization in the design of catalytic materials and enzymes, and how emergent ML applications serve as promising strategies to circumvent challenges associated with time-expensive and laborious testing in nanozyme research and development are summarized. The potential applications of successful examples of ML-aided catalytic materials and engineered enzymes in nanozyme design are also highlighted, with special focus on the unified aims in enhancing design and recapitulation of substrate selectivity and catalytic activity.

Thermal-Responsive MXene-DNA Hydrogel for Near-Infrared Light Triggered Localized Photothermal-Chemo Synergistic Cancer Therapy.

Stimuli-responsive DNA hydrogels are promising candidates for cancer treatment, as they not only possess biocompatible and biodegradable 3D network structures as highly efficient carriers for therapeutic agents but also are capable of undergoing programmable gel-to-solution transition upon external stimuli to achieve controlled delivery. Herein, a promising platform for highly efficient photothermal-chemo synergistic cancer therapy is established by integrating DNA hydrogels with Ti3 C2 TX -based MXene as a photothermal agent and doxorubicin (DOX) as a loaded chemotherapeutic agent. Upon the irradiation of near-infrared light (NIR), temperature rise caused by photothermal MXene nanosheets triggers the reversible gel-to-solution transition of the DOX-loaded MXene-DNA hydrogel, during which the DNA duplex crosslinking structures unwind to release therapeutic agents for efficient localized cancer therapy. Removal of the NIR irradiation results in the re-formation of DNA duplex structures and the hydrogel matrix, and the recombination of free DOX and adaptive hydrogel transformations can also be achieved. As demonstrated by both in vitro and in vivo models, the MXene-DNA hydrogel system, with excellent biocompatibility and injectability, dynamically NIR-triggered drug delivery, and enhanced drug uptake under mild hyperthermia conditions, exhibits efficient localized cancer treatment with fewer side effects to the organisms.

Screening of Protein-Based Ultrasmall Nanozymes for Building Cell-Mimicking Catalytic Vesicles.

Enzymes are an important component for bottom-up building of synthetic/artificial cells. Nanozymes are nanomaterials with intrinsic enzyme-like properties, however, the construction of synthetic cells using nanozymes is difficult owing to their high surface energy or large size. Herein, the authors show a protein-based general platform that biomimetically integrates various ultrasmall metal nanozymes into protein shells. Specifically, eight metal-based ultrasmall nano-particles/clusters are in situ incorporated into ferritin nanocages that are self-assembled by 24 subunits of ferritin heavy chain. As a nanozyme generator, such a platform is suitable for screening the desired enzyme-like activities, including peroxidase (POD), oxidase (OXD), catalase (CAT) and superoxide dismutase (SOD). After screening, it is found that Ru intrinsically possesses the highest POD-like and CAT-like activities, while Mn and Pt show the highest OXD-like and SOD-like activities, respectively. Additionally, the inducers/inhibitors of various nanozymes are screened from more than 50 compounds to improve or inhibit their enzyme-like activities. Based on the screened nanozymes and their inhibitors, a proof-of-conceptually constructs cell-mimicking catalytic vesicles to mimic or modulate the events of redox homeostasis in living cells. This study offers a type of artificial metalloenzyme based on nanotechnology and shows a choice for bottom-up enzyme-based synthetic cell systems in a fully synthetic manner.

A Novel Antihypertensive Pentapeptide Identified in Quinoa Bran Globulin Hydrolysates: Purification, In Silico Characterization, Molecular Docking with ACE and Stability against Different Food-Processing Conditions.

The addition of food derived antihypertensive peptides to the diet is considered a reasonable way to prevent and lower blood pressure. However, data about stability of antihypertensive peptides against different food-processing conditions are limited. In this study, through Sephadex G-15 gel chromatography and RP-HPLC separation, UPLC-ESI-MS/MS analysis and in silico screening, a novel ACE-inhibitory pentapeptide Ser-Ala-Pro-Pro-Pro (IC50: 915.03 µmol/L) was identified in quinoa bran globulin hydrolysate. The inhibition patterns on angiotensin-I-converting enzyme and safety of SAPPP were studied using molecular docking and in silico predication, respectively. Results demonstrated that SAPPP could noncompetitively bind to active sites PRO519 and SER461 of ACE through short hydrogen bonds. SAPPP was resistant to different pH values (2.0-10.0), pasteurization conditions, addition of Na+, Mg2+, Fe3+ or K+, and the simulated gastrointestinal digestion. In contrast, SAPPP was unstable against heating at 100 °C for more than 50 min and the treatment of Zn2+ (5 mmol/L). These results indicated that peptides derived from quinoa globulin hydrolysates can be added into foods for antihypertension.

Prediction and Design of Nanozymes using Explainable Machine Learning.

An abundant number of nanomaterials have been discovered to possess enzyme-like catalytic activity, termed nanozymes. It is identified that a variety of internal and external factors influence the catalytic activity of nanozymes. However, there is a lack of essential methodologies to uncover the hidden mechanisms between nanozyme features and enzyme-like activity. Here, a data-driven approach is demonstrated that utilizes machine-learning algorithms to understand particle-property relationships, allowing for classification and quantitative predictions of enzyme-like activity exhibited by nanozymes. High consistency between predicted outputs and the observations is confirmed by accuracy (90.6%) and R2 (up to 0.80). Furthermore, sensitive analysis of the models reveals the central roles of transition metals in determining nanozyme activity. As an example, the models are successfully applied to predict or design desirable nanozymes by uncovering the hidden relationship between different periods of transition metals and their enzyme-like performance. This study offers a promising strategy to develop nanozymes with desirable catalytic activity and demonstrates the potential of machine learning within the field of material science.

Isolation and Characterization of Bacteriocin-Producing Lacticaseibacillus rhamnosus XN2 from Yak Yoghurt and Its Bacteriocin.

Lactic acid bacteria (LAB) produce antimicrobial substances that could potentially inhibit the growth of pathogenic and food spoilage microorganisms. Lacticaseibacillus rhamnosus XN2, isolated from yak yoghurt, demonstrated antibacterial activity against Bacillus subtilis, B. cereus, Micrococcus luteus, Brochothrix thermosphacta, Clostridium butyricum, S. aureus, Listeria innocua CICC 10416, L. monocytogenes, and Escherichia coli. The antibacterial activity was estimated to be 3200 AU/mL after 30 h cultivation. Time-kill kinetics curve showed that the semi-purified cell-free supernatants (CFS) of strain XN2 possessed bactericidal activity. Flow cytometry analysis indicated disruption of the sensitive bacteria membrane by semi-purified CFS, which ultimately caused cell death. Interestingly, sub-lethal concentrations of semi-purified CFS were observed to reduce the production of α-haemolysin and biofilm formation. We further investigated the changes in the transcriptional level of luxS gene, which encodes signal molecule synthase (Al-2) induced by semi-purified CFS from strain XN2. In conclusion, L. rhamnosus XN2 and its bacteriocin showed antagonistic activity at both cellular and quorum sensing (QS) levels. Finally, bacteriocin was further purified by reversed-phase high-performance liquid chromatography (RP-HPLC), named bacteriocin XN2. The amino acid sequence was Met-Lue-Lys-Lys-Phe-Ser-Thr-Ala-Tyr-Val.

Bioorthogonal catalytic nanozyme-mediated lysosomal membrane leakage for targeted drug delivery.

Rationale: Employing in situ bioorthogonal catalysis within subcellular organelles, such as lysosomes, remains a challenge. Lysosomal membranes pose an intracellular barrier for drug sequestration, thereby greatly limiting drug accumulation and concentrations at intended targets. Here, we provide a proof-of-concept report of a nanozyme-based strategy that mediates in situ bioorthogonal uncaging reactions within lysosomes, followed by lysosomal escape and the release of uncaged drugs into the cytoplasm. Methods: A model system composed of a protein-based nanozyme platform (based on the transition metals Co, Fe, Mn, Rh, Ir, Pt, Au, Ru and Pd) and caged compound fluorophores was designed to screen for nanozyme/protecting group pairings. The optimized nanozyme/protecting group pairing was then selected for utilization in the design of anti-cancer pro-drugs and drug delivery systems. Results: Our screening system identified Pd nanozymes that mimic mutant P450BM3 activity and specifically cleave propargylic ether groups. We found that the intrinsic peroxidase-like activity of Pd nanozymes induced the production of free radicals under acid conditions, resulting in lysosomal membrane leakage of uncaged molecules into the cytoplasm. Using a multienzyme synergistic approach, our Pd nanozymes achieved in situ bioorthogonal catalysis and nanozyme-mediated lysosomal membrane leakage, which were successfully applied to the design of model pro-drugs for anti-cancer therapy. The extension of our nanozyme system to the construction of a liposome-based "all-in-one" delivery system offers promise for realizing efficacious in vivo tumor-targeted therapies. Conclusions: This strategy shows a promising new direction by utilizing nanotechnology for drug development through in situ catalyzing bioorthogonal chemistry within specific subcellular organelles.

A Novel Model System for Understanding Anticancer Activity of Hypoxia-Activated Prodrugs.

Reports on the comprehensive factors for design considerations of hypoxia-activated prodrugs (HAPs) are rare. We introduced a new model system composed of a series of highly water-soluble HAPs, providing a platform to comprehensively understand the interaction between HAPs and hypoxic biosystems. Specifically, four kinds of new HAPs were designed and synthesized, containing the same biologically active moiety but masked by different bioreductive groups. Our results demonstrated that the activity of the prodrugs was strongly dependent on not only the molecular structure but also the hypoxic tumor microenvironment. We found the presence of a direct linear relationship between cytotoxicity of the HAPs and the reduction potential of whole molecule/oxygen concentration/reductase expression. Moreover, limited blood vasculature in hypoxic regions was also a critical barrier for effective activation of the HAPs. This study offers a comprehensive insight into understanding the design factors required for HAPs.

Organocatalytic, Enantioselective Reductive Bis-functionalization of Secondary Amides: One-Pot Construction of Chiral 2,2-Disubstituted 3-Iminoindoline.

We report the first catalytic, enantioselective reductive bis-functionalization of common amides, which provides a facile access to a variety of 2,2-disubstituted 3-iminoindolines in good yields and with excellent enantioselectivities. The reaction conditions are quite mild and can be run on a gram scale. In this one-pot reaction, three C-C bonds, one ring, and one nitrogen-containing tetrasubstituted carbon stereocenter are created in a catalytic enantioselective manner.

Comparative analysis of salt-tolerant gene HOG1 in a Zygosaccharomyces rouxii mutant strain and its parent strain.

BACKGROUND: A higher-salt-tolerant mutant strain Zygosaccharomyces rouxii 3-2 (strain S3-2) that could be used for improving the flavour of high-salt liquid state soy sauce was previously constructed from parent strain Z. rouxii (strain S) by genome shuffling. However, whether the mutations in this strain affect HOG1 encoding MAPK Hog1p and improve intracellular glycerol production remains to be elucidated. RESULTS: Although two mutations in the ORF and one in the promoter of the HOG1 gene sequence of strain S3-2 occurred compared with that of strain S, there was no significant difference in secondary and tertiary structures between S3-2Hog1p and SHog1p. It was found that the expression level of S3-2HOG1 was higher than that of SHOG1 in YPDN medium with high salt concentration. Furthermore, overexpression of S3-2HOG1 in Saccharomyces cerevisiae W303-1A could improve the salt tolerance and osmotolerance of engineered yeast compared with that of SHOG1. CONCLUSION: Enhancement of the transcription level of HOG1 induced by mutation in the promoter region may be one of the main reasons for the improved salt tolerance of strain S3-2 compared with that of strain S. Considering food security, the conservation of S3-2HOG1 would be beneficial for application of strain S3-2 in the fermentation of soy sauce.

SimTB, a simulation toolbox for fMRI data under a model of spatiotemporal separability.

We introduce SimTB, a MATLAB toolbox designed to simulate functional magnetic resonance imaging (fMRI) datasets under a model of spatiotemporal separability. The toolbox meets the increasing need of the fMRI community to more comprehensively understand the effects of complex processing strategies by providing a ground truth that estimation methods may be compared against. SimTB captures the fundamental structure of real data, but data generation is fully parameterized and fully controlled by the user, allowing for accurate and precise comparisons. The toolbox offers a wealth of options regarding the number and configuration of spatial sources, implementation of experimental paradigms, inclusion of tissue-specific properties, addition of noise and head movement, and much more. A straightforward data generation method and short computation time (3-10 seconds for each dataset) allow a practitioner to simulate and analyze many datasets to potentially understand a problem from many angles. Beginning MATLAB users can use the SimTB graphical user interface (GUI) to design and execute simulations while experienced users can write batch scripts to automate and customize this process. The toolbox is freely available at http://mialab.mrn.org/software together with sample scripts and tutorials.

Capturing inter-subject variability with group independent component analysis of fMRI data: a simulation study.

A key challenge in functional neuroimaging is the meaningful combination of results across subjects. Even in a sample of healthy participants, brain morphology and functional organization exhibit considerable variability, such that no two individuals have the same neural activation at the same location in response to the same stimulus. This inter-subject variability limits inferences at the group-level as average activation patterns may fail to represent the patterns seen in individuals. A promising approach to multi-subject analysis is group independent component analysis (GICA), which identifies group components and reconstructs activations at the individual level. GICA has gained considerable popularity, particularly in studies where temporal response models cannot be specified. However, a comprehensive understanding of the performance of GICA under realistic conditions of inter-subject variability is lacking. In this study we use simulated functional magnetic resonance imaging (fMRI) data to determine the capabilities and limitations of GICA under conditions of spatial, temporal, and amplitude variability. Simulations, generated with the SimTB toolbox, address questions that commonly arise in GICA studies, such as: (1) How well can individual subject activations be estimated and when will spatial variability preclude estimation? (2) Why does component splitting occur and how is it affected by model order? (3) How should we analyze component features to maximize sensitivity to intersubject differences? Overall, our results indicate an excellent capability of GICA to capture between-subject differences and we make a number of recommendations regarding analytic choices for application to functional imaging data.

[Cephalometry study of craniofacial and upper airway in boys with OSAS].

OBJECTIVE: The purpose of the study was to find out craniofacial and upper airway characteristics of boys with OSAS. METHODS: Craniofacial and upper airway morphology was studied by computerized cephalometric analysis in 7 mixed dentition boys with OSAS and 29 healthy boys. RESULTS: The main differences of OSAS patients were shown as follows: longer dimension of cranial base with clockwise rotation of palate plane and mandibular plane, increased height of the tongue, inferiorly displaced hyoid bone, decreased sagittal dimension of upper airway in soft palate level and tongue base level. In addition, the tongue and soft palate occupied a larger portion of the oropharyngeal area. CONCLUSION: Patients with OSAS presented multiple abnormalities in craniofacial and upper airway. Cephalometry can be useful in diagnosis and determining the appropriate treatment for OSAS patients.