Revolutionizing breast cancer Ki-67 diagnosis: ultrasound radiomics and fully connected neural networks (FCNN) combination method.

PURPOSE: This study aims to assess the diagnostic value of ultrasound habitat sub-region radiomics feature parameters using a fully connected neural networks (FCNN) combination method L2,1-norm in relation to breast cancer Ki-67 status. METHODS: Ultrasound images from 528 cases of female breast cancer at the Affiliated Hospital of Xiangnan University and 232 cases of female breast cancer at the Affiliated Rehabilitation Hospital of Xiangnan University were selected for this study. We utilized deep learning methods to automatically outline the gross tumor volume and perform habitat clustering. Subsequently, habitat sub-regions were extracted to identify radiomics features and underwent feature engineering using the L1,2-norm. A prediction model for the Ki-67 status of breast cancer patients was then developed using a FCNN. The model's performance was evaluated using accuracy, area under the curve (AUC), specificity (Spe), positive predictive value (PPV), negative predictive value (NPV), Recall, and F1. In addition, calibration curves and clinical decision curves were plotted for the test set to visually assess the predictive accuracy and clinical benefit of the models. RESULT: Based on the feature engineering using the L1,2-norm, a total of 9 core features were identified. The predictive model, constructed by the FCNN model based on these 9 features, achieved the following scores: ACC 0.856, AUC 0.915, Spe 0.843, PPV 0.920, NPV 0.747, Recall 0.974, and F1 0.890. Furthermore, calibration curves and clinical decision curves of the validation set demonstrated a high level of confidence in the model's performance and its clinical benefit. CONCLUSION: Habitat clustering of ultrasound images of breast cancer is effectively supported by the combined implementation of the L1,2-norm and FCNN algorithms, allowing for the accurate classification of the Ki-67 status in breast cancer patients.

Autonomic self-regulating systems based on polyelectrolyte microcapsules and microgel particles.

Biological systems possess unique non-equilibrium functions, maintaining tight manipulation of their surroundings through inter-communication of multiple components and self-regulatory capability organized over different length scales. However, most artificial materials are incapable of communicating and self-regulating behavior due to their limited number of component and direct responsive modes. Herein, a new integrated self-regulation system is developed utilizing stimuli-responsive polyelectrolyte capsules as building blocks. The combination of stimuli-responsive capsules and enzyme immobilized microgels is designed to mimic life systems and its programmable interactive communications and self-regulation behavior is demonstrated through communication-feedback mechanism. Polyelectrolyte capsules can sense changes of their surrounding, then start the internal communication by releasing energy-rich cargo mimicking the behavior of the cells. The microgel particles subsequently complete closed-loop communication through providing negative feedback on capsules by enzymatic reaction and actuating pH-regulation of the whole system. Different communication modes and pH-regulation behaviors could be achieved by adjusting spatial and kinetic conditions. Proposed intelligent system is highly customizable due to the wide selection of encapsulated cargos, stimuli-responsive blocks and reaction networks, and would have broad influences in areas ranging from medical implants that assist in stabilizing body functions to microreactor system that regulate catalytic reactions.

Communicating assemblies of biomimetic nanocapsules.

Communication assemblies between biomimetic nanocapsules in a 3D closed system with self-regulating and self-organization functionalities were demonstrated for the first time. Two types of biomimetic nanocapsules, TiO2/polydopamine capsules and SiO2/polyelectrolytes capsules with different stimuli-responsive properties were prepared and leveraged to sense the external stimulus, transmit chemical signaling, and autonomic communication-controlled release of active cargos. The capsules have clear core-shell structures with average diameters of 30 nm and 25 nm, respectively. The nitrogen adsorption-desorption isotherms and thermogravimetric analysis displayed their massive pore structures and encapsulation capacity of 32% of glycine pH buffer and 68% of benzotriazole, respectively. Different from the direct release mode of the single capsule, the communication assemblies show an autonomic three-stage release process with a "jet lag" feature, showing the internal modulation ability of self-controlled release efficiency. The control overweight ratios of capsules influences on communication-release interaction between capsules. The highest communication-release efficiency (89.6% of benzotriazole) was achieved when the weight ratio of TiO2/polydopamine/SiO2/polyelectrolytes capsules was 5 : 1 or 10 : 1. Communication assemblies containing various types of nanocapsules can autonomically perform complex tasks in a biomimetic fashion, such as cascaded amplification and multidirectional communication platforms in bioreactors.

Helping Roles of Artificial Intelligence (AI) in the Screening and Evaluation of COVID-19 Based on the CT Images.

OBJECTIVE: The aim of this study was to explore the role of the AI system which was designed and developed based on the characteristics of COVID-19 CT images in the screening and evaluation of COVID-19. METHODS: The research team adopted an improved U-shaped neural network to segment lungs and pneumonia lesions in CT images through multilayer convolution iterations. Then the appropriate 159 cases were selected to establish and train the model, and Dice loss function and Adam optimizer were used for network training with the initial learning rate of 0.001. Finally, 39 cases (29 positive and 10 negative) were selected for the comparative test. Experimental group: an attending physician a and an associate chief physician a read the CT images to diagnose COVID-19 with the help of the AI system. Control group: an attending physician b and an associate chief physician b did the diagnosis only by their experience, without the help of the AI system. The time spent by each doctor in the diagnosis and their diagnostic results were recorded. Paired t-test, univariate ANOVA, chi-squared test, receiver operating characteristic curves, and logistic regression analysis were used for the statistical analysis. RESULTS: There was statistical significance in the time spent in the diagnosis of different groups (P<0.05). For the group with the optimal diagnostic results, univariate and multivariate analyses both suggested no significant correlation for all variables, and thus it might be the assistance of the AI system, the epidemiological history and other factors that played an important role. CONCLUSION: The AI system developed by us, which was created due to COVID-19, had certain clinical practicability and was worth popularizing.

UL36 Encoded by Marek's Disease Virus Exhibits Linkage-Specific Deubiquitinase Activity.

(1) Background: Deubiquitinase (DUB) regulates various important cellular processes via reversing the protein ubiquitination. The N-terminal fragment of a giant tegument protein, UL36, encoded by the Marek's disease (MD) virus (MDV), encompasses a putative DUB (UL36-DUB) and shares no homology with any known DUBs. The N-terminus 75 kDa fragment of UL36 exists in MD T lymphoma cells at a high level and participates in MDV pathogenicity. (2) Methods: To characterize deubiquitinating activity and substrate specificity of UL36-DUB, the UL36 N-terminal fragments, UL36(323), UL36(480), and mutants were prepared using the Bac-to-Bac system. The deubiquitinating activity and substrate specificity of these recombinant UL36-DUBs were analyzed using various ubiquitin (Ub) or ubiquitin-like (UbL) substrates and activity-based deubiquitinating enzyme probes. (3) Results: The results indicated that wild type UL36-DUBs show a different hydrolysis ability against varied types of ubiquitin chains. These wild type UL36-DUBs presented the highest activity to K11, K48, and K63 linkage Ub chains, weak activity to K6, K29, and K33 Ub chains, and no activity to K27 linkage Ub chain. UL36 has higher cleavage efficiency for K48 and K63 poly-ubiquitin than linear ubiquitin chain (M1-Ub4), but no activity on various ubiquitin-like modifiers. The mutation of C98 and H234 residues eliminated the deubiquitinating activity of UL36-DUB. D232A mutation impacted, but did not eliminated UL36(480) activity. The Ub-Br probe can bind to wild type UL36-DUB and mutants UL36(480)H234A and UL36(480)D232A, but not C98 mutants. These in vitro results suggested that the C98 and H234 are essential catalytic residues of UL36-DUB. UL36-DUB exhibited a strict substrate specificity. Inhibition assay revealed that UL36-DUB exhibits resistance to the Roche protease inhibitor cocktail and serine protease inhibitor, but not to the Solarbio protease inhibitor cocktail. (4) Conclusions: UL36-DUB exhibited a strict substrate preference, and the protocol developed in the current study for obtaining active UL36-DUB protein should promote the high-throughput screening of UL36 inhibitors and the study on the function of MDV-encoded UL36.

Four Cysteine Residues Contribute to Homodimerization of Chicken Interleukin-2.

Interleukin-2 (IL-2) is a pleiotropic cytokine regulating the immune and nervous systems. Mammalian and bird IL-2s have different protein sequences, but perform similar functions. In the current study, two bands were detected by immunoblotting using an antibody against freshly purified chicken IL-2 (chIL-2). The molecular weight of the larger band was approximately twice as much of the chIL-2 monomer, although a chIL-2 complex or homodimer has never been reported. To explain this intriguing result, several dissociation reagents were used to examine the intermolecular forces between components of the proposed chIL-2 complex. It was found that intermolecular disulphide bond promotes homodimerization of chIL-2. Subsequently, mutation of Cys residues of chIL-2 revealed that mutation of all four Cys residues disrupted homodimerization, but a single, dual, or triple Cys mutation failed to disrupt homodimerization, suggesting that all four Cys residues on chIL-2 contribute to this dimerization. Functional analysis showed that both monomeric and dimeric chIL-2 consisting of either wild type or mutant chIL-2 were able to stimulate the expansion of CD4+ T cell in vivo or in vitro, and effectively bind to chIL-2 receptor. Overall, this study revealed that the recombinant chIL-2 purified from either Escherichia coli (E. coli) or Spodoptera frugiperda (Sf9) cells could homodimerize in vitro, with all four Cys residues on each chIL-2 protein contributing to this homodimerization, and dimerization and Cys mutation not impacting chIL-2 induced stimulation of chicken CD4+ T cells.

Marek's Disease Virus Regulates the Ubiquitylome of Chicken CD4+ T Cells to Promote Tumorigenesis.

Ubiquitination and deubiquitination of cellular proteins are reciprocal reactions catalyzed by ubiquitination-related enzymes and deubiquitinase (DUB) which regulate almost all cellular processes. Marek's disease virus (MDV) encodes a viral DUB that plays an important role in the MDV pathogenicity. Chicken CD4+ T-cell lymphoma induced by MDV is a key contributor to multiple visceral tumors and immunosuppression of chickens with Marek's disease (MD). However, alterations in the ubiquitylome of MDV-induced T lymphoma cells are still unclear. In this study, a specific antibody against K-ε-GG was used to isolate ubiquitinated peptides from CD4+ T cells and MD T lymphoma cells. Mass spectrometry was used to compare and analyze alterations in the ubiquitylome. Our results showed that the ubiquitination of 717 and 778 proteins was significantly up- and downregulated, respectively, in T lymphoma cells. MDV up- and downregulated ubiquitination of a similar percentage of proteins. The ubiquitination of transferases, especially serine/threonine kinases, was the main regulatory target of MDV. Compared with CD4+ T cells of the control group, MDV mainly altered the ubiquitylome associated with the signal transduction, immune system, cancer, and infectious disease pathways in T lymphoma cells. In these pathways, the ubiquitination of CDK1, IL-18, PRKCB, ETV6, and EST1 proteins was significantly up- or downregulated as shown by immunoblotting. The current study revealed that the MDV infection could exert a significant influence on the ubiquitylome of CD4+ T cells.

A Study on Preparation and Stabilizing Mechanism of Hydrophobic Silica Nanofluids.

Nanofluids have increasingly drawn interest in recent years with their various applications in a number of fields. The method for the preparation of stable nanofluids is a key concern for extending the application of nanofluids. This study focuses on the effect of pH, dosage of surfactant (TX-100), and nanofluid concentration on the stability of a silica nanofluid. Particle size and zeta potential are two important factors to consider in evaluating the stability of the silica nanofluid. Results indicate that the stability of the silica nanofluid highly depends on pH, dosage of surfactant (TX-100), and nanofluid concentration. On the basis of these experiments, the best conditions for the preparation of a silica nanofluid are 0.1 wt. % for the concentration of silica nanoparticles and TX-100 and 10 for pH. A transparent and stable silica nanofluid can thus be obtained.