Facile engineering of interactive double network hydrogels for heart valve regeneration.

Regenerative heart valve prostheses are essential for treating valvular heart disease, which requested interactive materials that can adapt to the tissue remodeling process. Such materials typically involves intricate designs with multiple active components, limiting their translational potential. This study introduces a facile method to engineer interactive materials for heart valve regeneration using 1,1'-thiocarbonyldiimidazole (TCDI) chemistry. TCDI crosslinking forms cleavable thiourea and thiocarbamate linkages which could gradually release H2S during degradation, therefore regulates the immune microenvironment and accelerates tissue remodeling. By employing this approach, a double network hydrogel was formed on decellularized heart valves (DHVs), showcasing robust anti-calcification and anti-thrombosis properties post fatigue testing. Post-implantation, the DHVs could adaptively degrade during recellularization, releasing H2S to further support tissue regeneration. Therefore, the comprehensive endothelial cell coverage and notable extracellular matrix remodeling could be clearly observed. This accessible and integrated strategy effectively overcomes various limitations of bioprosthetic valves, showing promise as an attractive approach for immune modulation of biomaterials.

Chemogenetic Evolution of Diversified Photoenzymes for Enantioselective [2 + 2] Cycloadditions in Whole Cells.

Artificial photoenzymes with novel catalytic modes not found in nature are in high demand; yet, they also present significant challenges in the field of biocatalysis. In this study, a chemogenetic modification strategy is developed to facilitate the rapid diversification of photoenzymes. This strategy integrates site-specific chemical conjugation of various artificial photosensitizers into natural protein cavities and the iterative mutagenesis in cell lysates. Through rounds of directed evolution, prominent visible-light-activatable photoenzyme variants were developed, featuring a thioxanthone chromophore. They successfully enabled the enantioselective [2 + 2] photocycloaddition of 2-carboxamide indoles, a class of UV-sensitive substrates that are traditionally challenging for known photoenzymes. Furthermore, the versatility of this photoenzyme is demonstrated in enantioselective whole-cell photobiocatalysis, enabling the efficient synthesis of enantioenriched cyclobutane-fused indoline tetracycles. These findings significantly expand the photophysical properties of artificial photoenzymes, a critical factor in enhancing their potential for harnessing excited-state reactivity in stereoselective transformations.

Development and validation of competing risk nomograms for predicting cancer­specific mortality in non-metastatic patients with non­muscle invasive urothelial bladder cancer.

We aimed to assess the cumulative incidences of cancer-specific mortality (CSM) in non-metastatic patients with non­muscle invasive urothelial bladder cancer (NMIUBC) and establish competing risk nomograms to predict CSM. Patient data was sourced from the Surveillance, Epidemiology, and End Results database, as well as the electronic medical record system in our institution to form the external validation cohort. Sub-distribution proportional hazards model was utilized to determine independent risk factors influencing CSM in non-metastatic NMIUBC patients. Competitive risk nomograms were constructed to predict 3-year, 5-year, and 8-year cancer-specific survival (CSS) in all patients group, TURBT group and cystectomy group, respectively. The discrimination and accuracy of the model were validated through the concordance index (C-index), the area under the receiver operating characteristic curve (AUC), and calibration curves. Decision curve analysis (DCA) and a risk stratification system was employed to evaluate the clinical utility of the model. Race, age, marital status, surgery in other sites, tumor size, histological type, histological grade, T stage and N stage were identified as independent risk factors to predict CSS in all patients group. The C-index for 3-year CSS was 0.771, 0.770 and 0.846 in the training, testing and external validation sets, respectively. The ROC curves showed well discrimination and the calibration plots were well fitted and consistent. Moreover, DCA demonstrated well clinical effectiveness. Altogether, the competing risk nomogram displayed excellent discrimination and accuracy for predicting CSS in non-metastatic NMIUBC patients, which can be applied in clinical practice to help tailor treatment plans and make clinical decisions.

Identification and functional analysis of a deduced geraniol synthase from Camphora officinarum.

The market demand for essential oil containing citral is increasing. Our research group identified a rare chemotype of Camphora officinarum whose leaves are high in citral content by examining over 1000 wild trees across the entire native distribution area of C. officinarum in China. Because C. officinarum is suitable for large-scale cultivation, it is therefore seen as a promising source of natural citral. However, the molecular mechanism of citral biosynthesis in C. officinarum is poorly understood. In this study, transcriptomic analyses of C. officinarum with different citral contents revealed a strong positive correlation between the expression of a putative geraniol synthase gene (CoGES) and citral content. The CoGES cDNA was cloned, and the CoGES protein shared high similarity with other monoterpene synthases. Enzymatic assays of CoGES with geranyl diphosphate (GPP) as substrate yielded geraniol as the single product, which is the precursor of citral. Further transient expression of CoGES in Nicotiana benthamiana resulted in a higher relative content of geranial and the appearance of a new substance, neral. These findings indicate that CoGES is a geraniol synthase-encoding gene, and the encoded protein can catalyze the transformation of GPP into geraniol, which is further converted into geranial and neral through an unknown mechanism in vivo. These findings expand our understanding of citral biosynthesis in Lauraceae plants. Supplementary Information: The online version contains supplementary material available at 10.1007/s12298-024-01463-4.

Exploring the association between multiple factors and urolithiasis: A retrospective study and Mendelian randomization analysis.

To investigate the relationship between several factors and urinary stone as well as different stone compositions. To guide the diagnosis, treatment, and prevention of urinary stone recurrence. We used bidirectional Mendelian randomization to analyze the causal relationship between hypertension and urinary stones, diabetes and urinary stones, and body mass index (BMI) and urinary stones. We retrospectively analyzed the medical records of patients with urinary stones admitted to a tertiary care hospital in Chongqing, China, from July 2015 to October 2022. Patients were included when they were first diagnosed with urinary stones. The odds ratio of calculi on hypertension estimated by inverse variance weighted was 8.46 (95%CI: 4.00-17.90, P = 2.25 × 10-8). The stone composition analysis showed that there were 3101 (67.02%) mixed, 1322 (28.57%) calcium oxalate monohydrate, 148 (3.20%) anhydrous uric acid, 16 (0.35%) magnesium ammonium phosphate hexahydrate, 11 (0.24%) dicalcium phosphate dihydrate, 10 (0.22%) carbonate apatite, 8 (0.17%) L-cystine, 4 ammonium uric acid (0.09%), and 7 other stone types (0.15%). Mendelian randomization studies have proven that urinary stones may be a potential risk factor for hypertension, while there is no causal relationship between diabetes and stones, BMI, and stones. Our retrospective study has shown that urinary stone components are closely associated with sex, age, hypertension, diabetes, and BMI. It is reasonable to suspect that treating a single stone component is ineffective in preventing recurrence. We also found that the peak incidence of urinary stones was at the most active stage of most people's working lives.

Establishment and validation of nomograms to predict the overall survival and cancer-specific survival for non-metastatic bladder cancer patients: A large population-based cohort study and external validation.

This study aimed to develop nomograms to accurately predict the overall survival (OS) and cancer-specific survival (CSS) of non-metastatic bladder cancer (BC) patients. Clinicopathological information of 260,412 non-metastatic BC patients was downloaded from the Surveillance, Epidemiology, and End Results (SEER) database from 2000 to 2020. LASSO method and Cox proportional hazard regression analysis were utilized to discover the independent risk factors, which were used to develop nomograms. The accuracy and discrimination of models were tested by the consistency index (C-index), the area under the subject operating characteristic curve (AUC) and the calibration curve. Decision curve analysis (DCA) was used to test the clinical value of nomograms compared with the TNM staging system. Nomograms predicting OS and CSS were constructed after identifying independent prognostic factors. The C-index of the training, internal validation and external validation cohort for OS was 0.722 (95%CI: 0.720-0.724), 0.723 (95%CI: 0.721-0.725) and 0.744 (95%CI: 0.677-0.811). The C-index of the training, internal validation and external validation cohort for CSS was 0.794 (95%CI: 0.792-0.796), 0.793 (95%CI: 0.789-0.797) and 0.879 (95%CI: 0.814-0.944). The AUC and the calibration curves showed good accuracy and discriminability. The DCA showed favorable clinical potential value of nomograms. Kaplan-Meier curve and log-rank test uncovered statistically significance survival difference between high- and low-risk groups. We developed nomograms to predict OS and CSS for non-metastatic BC patients. The models have been internally and externally validated with accuracy and discrimination and can assist clinicians to make better clinical decisions.

Spatiotemporally Controlled Photolabeling of Genetically Unmodified Proteins in Live Cells.

Selective labeling of the protein of interest (POI) in genetically unmodified live cells is crucial for understanding protein functions and kinetics in their natural habitat. In particular, spatiotemporally controlled installation of the labels on a POI under light control without affecting their original activity is in high demand but is a tremendous challenge. Here, we describe a novel ligand-directed photoclick strategy for spatiotemporally controlled labeling of endogenous proteins in live cells. It was realized with a designer labeling reagent skillfully integrating the photochemistries of 2-nitrophenylpropyloxycarbonyl and 3-hydroxymethyl-2-naphthol with an affinity ligand. Highly electrophilic ortho-naphthoquinone methide was photochemically released and underwent a proximity coupling reaction with nucleophilic amino acid residues on the POI in live cells. With fluorescein as a marker, this photoclick strategy enables time-resolved labeling of carbonic anhydrase subtypes localized either on the cell membrane or in the cytoplasm and a discriminable visualization of their metabolic kinetics. Given the versatility underlined by facilely tethering other functional entities (e.g., biotin, a peptide short chain) via acylation or (in cell) Huisgen cycloaddition, this affinity-driven photoclick chemistry opens up enormous opportunities for discovering dynamic functions and mechanistic interrogation of endogenous proteins in live cells.

Hyperbolic graph convolutional neural network with contrastive learning for automated ICD coding.

The International Classification of Diseases (ICD) is a widely used criterion for disease classification, health monitoring, and medical data analysis. Deep learning-based automated ICD coding has gained attention due to the time-consuming and costly nature of manual coding. The main challenges of automated ICD coding include imbalanced label distribution, code hierarchy and noisy texts. Recent works have considered using code hierarchy or description for better label representation to solve the problem of imbalanced label distribution. However, these methods are still ineffective and redundant since they only interact with a constant label representation. In this work, we introduce a novel Hyperbolic Graph Convolutional Network with Contrastive Learning (HGCN-CL) to solve the above problems and the shortcomings of the previous methods. We adopt a Hyperbolic graph convolutional network on ICD coding to capture the hierarchical structure of codes, which can solve the problem of large distortions when embedding hierarchical structure with graph convolutional network. Besides, we introduce contrastive learning for automatic ICD coding by injecting code features into text encoder to generate hierarchical-aware positive samples to solve the problem of interacting with constant code features. We conduct experiments on the public MIMIC-III and MIMIC-II datasets. The results on MIMIC III show that HGCN-CL outperforms previous state-of-art methods for automatic ICD coding, which achieves a 2.7% and 3.6% improvement respectively compared to previous best results (Hypercore). We also provide ablation experiments and hierarchy visualization to verify the effectiveness of components in our model.

Design, Synthesis, and Biological Evaluation of Thioglucoside Analogues of Gliflozin as Potent New Gliflozin Drugs.

In this study, we have investigated the potential of two classes of thioglucoside analogues of gliflozins as antidiabetic drugs, one with substitutions of S-atoms in meta-positions (similar to C-glucoside SGLT2 inhibitors, TAGs A, B, and C) and the other with substitutions of S-atoms in ortho-positions (similar to O-glucoside SGLT2 inhibitors, TAGs D, E, F, and G). These TAGs were confirmed to show good stability against ß-glucosidase and to have no acute toxicity to cultured cells. Most importantly, TAGs D, E, F, and G all showed high inhibitory activity against SGLT2 (IC50: 2.0-5.9 nM) and thus have great potential to be developed as new gliflozin drugs. Compared with the synthesis of C-glucoside gliflozins, the synthesis of TAGs is simple, efficient, and associated with low costs, high yields, and very mild reaction conditions.

Fluorescent Turn-On Probes for Visualizing GPx4 Levels in Live Cells and Predicting Drug Sensitivity.

Glutathione peroxidase 4 (GPx4) is the membrane peroxidase in mammals that is essential for protecting cells against oxidative damage and critical for ferroptosis. However, no live cell probe is currently available to specifically label GPx4. Herein, we report both inhibitory and noninhibitory fluorescent turn-on probes for specific labeling of GPx4 in live cells. With these probes, the GPx4 expression levels and degradation kinetics in live cells could be visualized, and their real-time responses to the cellular selenium availability were revealed. These probes could also potentially serve as staining reagents to predict the sensitivity of GPx4-related ferroptosis drugs. In view of these features, these GPx4-selective probes will offer opportunities for a deeper understanding of GPx4 function in natural habitats and hold great promise for biomedical applications.

Expanding the Promiscuity of a Copper-Dependent Oxidase for Enantioselective Cross-Coupling of Indoles.

Herein, we disclose the highly enantioselective oxidative cross-coupling of 3-hydroxyindole esters with various nucleophilic partners as catalyzed by copper efflux oxidase. The biocatalytic transformation delivers functionalized 2,2-disubstituted indolin-3-ones with excellent optical purity (90-99 % ee), which exhibited anticancer activity against MCF-7 cell lines, as shown by preliminary biological evaluation. Mechanistic studies and molecular docking results suggest the formation of a phenoxyl radical and enantiocontrol facilitated by a suited enzyme chiral pocket. This study is significant with regard to expanding the catalytic repertoire of natural multicopper oxidases as well as enlarging the synthetic toolbox for sustainable asymmetric oxidative coupling.

Light-Controlled Traceless Protein Labeling via Decaging Thio-o-naphthoquinone Methide Chemistry.

We report the molecular design of a novel multifunctional reagent and its application for light-controlled selective protein labeling. This molecule integrates functions of protein-ligand recognition, bioconjugation, ligand cleavage, and photoactivation by merging the photochemistries of 2-nitrophenylpropyloxycarbonyl and 3-hydroxymethyl-2-naphthol with an affinity ligand and fluorescein. Highly electrophilic o-naphthoquinone methide was photochemically released and underwent proximity-driven selective labeling with the protein of interest (e.g., carbonic anhydrases), which retains its native function after labeling.

Biomineralized Manganese Oxide Nanoparticles Synergistically Relieve Tumor Hypoxia and Activate Immune Response with Radiotherapy in Non-Small Cell Lung Cancer.

Radiotherapy (RT) is currently considered as an essential treatment for non-small cell lung cancer (NSCLC); it can induce cell death directly and indirectly via promoting systemic immune responses. However, there still exist obstacles that affect the efficacy of RT such as tumor hypoxia and immunosuppressive tumor microenvironment (TME). Herein, we report that the biomineralized manganese oxide nanoparticles (Bio-MnO2 NPs) prepared by mild enzymatic reaction could be a promising candidate to synergistically enhance RT and RT-induced immune responses by relieving tumor hypoxia and activating cGAS-STING pathway. Bio-MnO2 NPs could convert endogenic H2O2 to O2 and catalyze the generation of reactive oxygen species so as to sensitize the radiosensitivity of NSCLC cells. Meanwhile, the release of Mn2+ into the TME significantly enhanced the cGAS-STING activity to activate radio-immune responses, boosting immunogenic cell death and increasing cytotoxic T cell infiltration. Collectively, this work presents the great promise of TME reversal with Bio-MnO2 NPs to collaborate RT-induced antitumor immune responses in NSCLC.

Enantioselective [2+2]-cycloadditions with triplet photoenzymes.

Naturally evolved enzymes, despite their astonishingly large variety and functional diversity, operate predominantly through thermochemical activation. Integrating prominent photocatalysis modes into proteins, such as triplet energy transfer, could create artificial photoenzymes that expand the scope of natural biocatalysis1-3. Here, we exploit genetically reprogrammed, chemically evolved photoenzymes embedded with a synthetic triplet photosensitizer that are capable of excited-state enantio-induction4-6. Structural optimization through four rounds of directed evolution afforded proficient variants for the enantioselective intramolecular [2+2]-photocycloaddition of indole derivatives with good substrate generality and excellent enantioselectivities (up to 99% enantiomeric excess). A crystal structure of the photoenzyme-substrate complex elucidated the non-covalent interactions that mediate the reaction stereochemistry. This study expands the energy transfer reactivity7-10 of artificial triplet photoenzymes in a supramolecular protein cavity and unlocks an integrated approach to valuable enantioselective photochemical synthesis that is not accessible with either the synthetic or the biological world alone.

Nanoscale Zeolitic Imidazolate Framework (ZIF)-8 in Cancer Theranostics: Current Challenges and Prospects.

Cancer severely threatens human health and has remained the leading cause of disease-related death for decades. With the rapid advancement of nanomedicine, nanoscale metal-organic frameworks are believed to be potentially applied in the treatment and biomedical imaging for various tumors. Zeolite imidazole framework (ZIF)-8 attracts increasing attention due to its high porosity, large specific surface area, and pH-responsiveness. The designs and modifications of ZIF-8 nanoparticles, as well as the strategy of drug loading, demand a multifaceted and comprehensive understanding of nanomaterial features and tumor characteristics. We searched for studies on ZIF-8-based nanoplatforms in tumor theranostics on Web of Science from 2015 to 2022, mainly focused on the research published in the past 3 years, summarized the progress of their applications in tumor imaging and treatment, and discussed the favorable aspects of ZIF-8 nanoparticles for tumor theranostics as well as the future opportunities and potential challenges. As a kind of metal-organic framework material full of potential, ZIF-8 can be expected to be combined with more therapeutic systems in the future and continue to contribute to all aspects of tumor therapy and diagnosis.

JAN: Joint Attention Networks for Automatic ICD Coding.

The International Classification of Diseases (ICD) code is a disease classification method formulated by the World Health Organization(WHO). ICD coding usually requires clinicians to manually allocate ICD codes to clinical documents, which is labor-intensive, expensive, and error-prone. Therefore, many methods have been introduced for automatic ICD coding. However, most of the methods have ignored or cannot combine two essential features well: long-tailed label distribution and label correlation. In this paper, we propose a novel end-to-end Joint Attention Network (JAN) to solve these two problems. JAN includes Document-based attention and Label-based attention to capture semantic information from clinical document text and label description, respectively, which helps solve the classification of dense and sparse data in long-tailed label distribution. Besides, an Adaptive fusion layer and CorNet block are presented to adaptively adjust the weight of these two attentions and exploit label co-occurrence relations, respectively. Experiments on the MIMIC-III and MIMIC-II datasets demonstrate that our proposed JAN outperformed previous state-of-art methods achieving Micro-F1 of 0.553, Micro-AUC of 0.989 and precision at top 8(P@8) of 0.735. Finally, we also provide attention and label correlation visualization to verify the effectiveness of our model and improve the interpretation of our deep learning-based method.

Defined positive charge patterns created on DNA nanostructures determine cellular uptake efficiency.

We provide an effective method to create DNA nanostructures below 100 nm with defined charge patterns and explore whether the density and location of charges affect the cellular uptake efficiency of nanoparticles (NPs). To avoid spontaneous charge neutralization, the negatively charged polymer nanopatterns were first created by in situ polymerization using photoresponsive monomers on DNA origami. Subsequent irradiation generated positive charges on the immobilized polymers, achieving precise positively charged patterns on the negatively charged DNA surface. Via this method, we have discovered that the positive charges located on the edges of nanostructures facilitate more efficient cellular uptake in comparison to the central counterparts. In addition, the high-density positive charge decoration could also enhance particle penetration into 3D multicellular spheroids. This strategy paves a new way to construct elaborate charge-separated substructures on NP surfaces and holds great promise for a deeper understanding of the influence between the surface charge distribution and nano-bio interactions.

QM/MM Calculations Suggest Concerted O-O Bond Cleavage and Substrate Oxidation by Nonheme Diiron Toluene/o-Xylene Monooxygenase.

The nonheme diiron toluene/o-xylene monooxygenase (ToMO) is the most studied toluene monooxygenase that mediates an aromatic hydroxylation reaction. In this work, QM/MM calculations were performed to understand the reaction mechanism. It is revealed that the µ-η2 :η2 peroxodiferric species is the reactive intermediate after the binding of the O2 molecule to the reduced diferrous center. Subsequently, both a stepwise and a concerted mechanism involving the critical O-O bond cleavage and C-O bond formation were considered. The latter was calculated to be more favorable, suggesting that the formation of a high-valent diferryl Q intermediate is not needed. The isomeric formation of the phenol product was found very facile. The first step was calculated to be rate-limiting, with a barrier of 17.6 kcal/mol for the ortho-hydroxylation.

Catalytic Atroposelective Electrophilic Amination of Indoles.

Reported here is the first catalytic atroposelective electrophilic amination of indoles, which delivers functionalized atropochiral N-sulfonyl-3-arylaminoindoles with excellent optical purity. This reaction was furnished by 1,6-nucleophilic addition to p-quinone diimines. Control experiments suggest an ionic mechanism that differs from the radical addition pathway commonly proposed for 1,6-addition to quinones. The origin of 1,6-addition selectivity was investigated through computational studies. Preliminary studies show that the obtained 3-aminoindoles atropisomers exhibit anticancer activities. This method is valuable with respect to enlarging the toolbox for atropochiral amine derivatives.

Chemical Modification for the "Off-/On" Regulation of Enzyme Activity.

Enzymes with excellent catalytic performance play important roles in living organisms. Advances in strategies for enzyme chemical modification have enabled powerful strategies for exploring and manipulating enzyme functions and activities. Based on the development of chemical enzyme modifications, incorporating external stimuli-responsive features-for example, responsivity to light, voltage, magnetic force, pH, temperature, redox activity, and small molecules-into a target enzyme to turn "on" and "off" its activity has attracted much attention. The ability to precisely control enzyme activity using different approaches will greatly expand the chemical biology toolbox for clarification and detection of signal transduction and in vivo enzyme function and significantly promote enzyme-based disease therapy. This review summarizes the methods available for chemical enzyme modification mainly for the off-/on control of enzyme activity and particularly highlights the recent progress regarding the applications of this strategy.