Universal Features Research Articles

Abstract B141: Evaluation of antigen-agnostic anti-tumor activity and immunological memory induced by CBX-15 (alphalexTM-MMAE) in the rat syngeneic breast cancer model

Abstract CBX-15 is a peptide-drug conjugate consisting of alphalexTM-monomethyl auristatin E (MMAE). The alphalexTM is a unique variant of pH-Low Insertion Peptide1 (pHLIP®) designed to target the low pH microenvironment of cancer cells, a universal feature of all rapidly growing tumors. The peptide of CBX-15 forms an alpha helix only in low pH conditions, resulting in unidirectional insertion of the peptide and delivery of MMAE across the cancer cell membrane, and avoidance of delivery to healthy tissues, including immune cells. Efficacy and anti-tumor immunological memory induced by CBX-15 was evaluated in Fischer 344 rats bearing syngeneic 13762 mammary adenocarcinoma tumors. The development of anti-tumor immunological memory was examined in CBX-15-cured animals by in vivo/ex vivo rechallenge with live tumor cells and subsequent assessment of tumor rejection, cytokine release by T cells, tumor immune cell infiltration, and memory T cell composition of the bone marrow. CBX-15 rapidly regressed rat tumors, resulting in complete responses while sparing healthy tissues such as bone marrow. Cured rats rejected live tumor rechallenge and exhibited a doubling of bone marrow-resident CD4 memory T cells 50 days post-dose. Splenocytes and lymph node suspensions derived from cured rats demonstrated formation of a Th1-mediated IFNƳ response when exposed ex vivo to tumor cells. The ability of CBX-15 to induce immunogenic cell death was established by vaccinating syngeneic animals with CBX-15 treated tumor cells and subsequent tumor rechallenge, which demonstrated anti-tumor immunity induced by CBX-15. These preclinical data demonstrate the anti-tumor efficacy of CBX-15 in the rat as well as the ability of CBX-15 to enhance tumor immunogenicity through immunogenic cell death by utilizing a universal pH-based tumor targeting mechanism.1 Wyatt LC et al. 2017. Applications of pHLIP Technology for Cancer Imaging and Therapy. Trends Biotech. Citation Format: Sophia Gayle, Timothy Paradis, Qing Zhang, Laurie Tylaska, Connor Hagen, Theresa Pasqualini, Vishwas Paralkar. Evaluation of antigen-agnostic anti-tumor activity and immunological memory induced by CBX-15 (alphalexTM-MMAE) in the rat syngeneic breast cancer model [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr B141.

THE «WEALTH - POVERTY» OPPOSITION IN THE LINGUISTIC PICTURE OF THE WORLD (BASED ON THE MATERIAL OF KAZAKH AND TATAR PAREMIAS)

Background. This article examines the opposition of the concepts “baylyk-baylyk”, “kedeilik-yarlylyk” in the paremiological units of the Kazakh and Tatar languages. It is well known that proverbs are mostly closely related to the external factors of human life. Paremias react realistically to phenomena, reflect an ethnic worldview, and express philosophical, aesthetic, and religiously pragmatic folk views.
 Purpose. The aim of the study is to determine the features of the expression of the oppositional concepts “baylyk-baylyk”, “kedeilik-yarlylyk” in Kazakh and Tatar paroemias.
 Materials and methods. In the research work, a detailed analysis of proverbs and sayings of the Kazakh and Tatar languages containing units of lexical and semantic groups “baylyk-baylyk”, “kedeilik-yarlylyk” was carried out. The following research methods are used in the work: conceptual, diachronic analyses, methods of comparative linguoculturological analysis.
 Results. The concepts “baylyk-baylyk”, “kedeilik-yarlylyk” in the Kazakh and Tatar paremiological system represent both universal and specific features of the linguistic world pictures of the two peoples through various ethnospecific images. As a result of the study, it was revealed that these concepts in the paremias serve as a reflection not only of the material situation, but also of the spiritual state of a person. A brief dialogue with the use of paremias is instructive in nature and often asserts the priority of moral values over material goods.
 Practical implications. The results of the research can be used both in the main course of teaching Kazakh and Tatar languages, and in elective courses of cognitive linguistics, conceptology, literary studies, folklore, and can also be useful for research in the field of linguistic worldviews of the Kazakh and Tatar peoples.

Expanding the Enzymatic Polymerization Landscape by Lipid Mesophase Soft Nanoconfinement.

Soft nanoconfinement can increase chemical reactivity in nature and has therefore led to considerable interest in transferring this universal feature to artificial biological systems. However, little is known about the underlying principles of soft nanoconfinement responsible for the enhancement of biochemical reactions. Herein we demonstrate how enzymatic polymerization can be expanded, optimized, and engineered when carried out under soft nanoconfinement mediated by lipidic mesophases. By systematically varying the water content in the mesophase and thus the diameter of the confined water nanochannels, we show higher efficiency, turnover rate, and degrees of polymerization as compared to the bulk aqueous solution, all controlled by soft nanoconfinement effects. Furthermore, we exploit the unique properties of unfreezing soft nanoconfined water to perform the first enzymatic polymerization at -20 °C in pure aqueous media. These results underpin lipidic mesophases as a versatile host system for chemical reactions and promote them as an original and unexplored platform for enzymatic polymerization.

Expanding the Enzymatic Polymerization Landscape by Lipid Mesophase Soft Nanoconfinement

AbstractSoft nanoconfinement can increase chemical reactivity in nature and has therefore led to considerable interest in transferring this universal feature to artificial biological systems. However, little is known about the underlying principles of soft nanoconfinement responsible for the enhancement of biochemical reactions. Herein we demonstrate how enzymatic polymerization can be expanded, optimized, and engineered when carried out under soft nanoconfinement mediated by lipidic mesophases. By systematically varying the water content in the mesophase and thus the diameter of the confined water nanochannels, we show higher efficiency, turnover rate, and degrees of polymerization as compared to the bulk aqueous solution, all controlled by soft nanoconfinement effects. Furthermore, we exploit the unique properties of unfreezing soft nanoconfined water to perform the first enzymatic polymerization at −20 °C in pure aqueous media. These results underpin lipidic mesophases as a versatile host system for chemical reactions and promote them as an original and unexplored platform for enzymatic polymerization.

TSE-ARF: An adaptive prediction method of effectors across secretion system types

Bacterial effector proteins are secreted by a variety of protein secretion systems and play an important role in the interaction between the host and pathogenic bacteria. Therefore, it is important to find a fast and inexpensive method to discover bacterial effectors. In this study, we propose a multi-type secretion effector adaptive random forest (TSE-ARF) to adaptively identify secretion effectors across T1SE-T4SE and T6SE based only on protein sequences. First, we proposed two new feature descriptors by considering some characteristic protein information and fused them with some universal features to form a 290-dimensional feature vector with good versatility. Then, the TSE-ARF model was used to make classification predictions by parameter adaptation of different secretion effectors integrating Shuffled Frog Leaping Algorithm and random forest. The perfect performance in TSE-ARF under different data sets and settings shows its considerable generalization ability, with which more candidate effectors were screened in the whole genome. Source code is available at https://github.com/AIMOVE/TSE-ARF.

Sars-Cov-2 Spike Protein Triggers Inflammasome-Mediated Tissue Factor Activity

Introduction: An exaggerated inflammatory response both locally and systemically mediated by innate immune signaling is a near universal feature of severe COVID-19 illness and has been associated with multi-organ damage and thrombosis. As part of an antiviral response, activation and formation of the intracellular NLRP3 inflammasome leads to expression of proinflammatory IL-1 family cytokines. In macrophages, the NLRP3 inflammasome is linked to the release of tissue factor (TF) bearing microvesicles. Multiple studies provide evidence of NLRP3 inflammasome activation in COVID-19 including increased IL-1β in monocytes, sera, and bronchoalveolar lavage fluid from COVID-19 patients. Patient monocytes bear features of inflammasome activation, which correlate with disease severity (Potere et al. Cardiovascular Research 2023). Given the central role of thromboinflammation in COVID-19, we explored the ability of various coronavirus spike proteins to increase TF activity in a monocytic cell line. Mechanistically, we sought to explore the role of the NLRP3 inflammasome in SARS-CoV-2 spike protein triggered tissue factor generation. Methods: The SARS-CoV-2 α variant S1 subunit (S1α) and Omicron variant BA.1.1.529 S1 (S1O) recombinant proteins were obtained from Raybiotech and OC43, a non-COVID respiratory human coronavirus, recombinant spike protein (OC43 S) from Sino Biological. THP-1 cells at a concentration of 2x10 6/mL were incubated with spike proteins at 37°C in RPMI, supplemented with 10% fetal bovine serum. A specific NLRP3 inflammasome inhibitor (MCC950) was incubated with select samples for 1 hour following addition of the spike protein. The cells were harvested, subjected to RNA extraction and cDNA synthesis by reverse transcription. TF, NLRP3, caspase (CASP)-1, and IL-1β relative mRNA expression was quantified using RT-PCR and normalized to GADPH expression. For quantifying microparticle TF activity, cells were incubated with the spike proteins for 6 hours then microparticles were isolated from the supernatant after centrifugation at 20,000 g for 30 minutes at 4°C, washed and TF activity was measured using a two-stage chromogenic assay kit (Abcam). A monoclonal anti-TF antibody (Santa Cruz) was used to confirm specificity for TF generation. Experiments were performed in triplicate. Data is presented as mean ± standard deviation. The student t test was used to assess the difference between unpaired groups with a value of p <.05 considered statistically significant. Results: Our previous data showed that S1α, but not S1O or OC43 S, leads to increased TF mRNA expression in THP-1 cells in a dose dependent manner. Here we show TF microparticle activity was increased with S1α (20 µg/mL) as compared to incubation of THP-1 cells with S1O or OC43 spike proteins (20 µg/mL), which were comparable to the activity of cells alone ( Figure 1). After treatment with S1α (20 µg/mL) for 1 hour, we found increased expression of TF (10-fold), NLRP3 (2-fold), CASP-1 (3-fold), and IL-1β (3.5-fold). Treatment with S1O and OC43 S did not lead to a significant change in relative mRNA expression of TF, NLRP3, CASP-1, and IL-1β. Following incubation with the S1α spike protein for 1 hour, cells were re-plated in fresh media containing 10 µM MCC950. Treatment with MCC950 significantly reduced expression of TF, NLRP3, CASP-1, and IL-1β ( Figure 2). Conclusion: We confirmed that TF expression induced by the S1α spike protein leads to an increase in TF activity, as assessed by microparticle generation. The NLRP3 inflammasome is a mediator of coagulopathy induced by the spike protein, and TF, CASP-1, and IL-1β expression are abrogated after specific NLRP3 inflammasome inhibition. TF activity and inflammation induced by the coronavirus spike proteins in vitro correlates with the respective clinical phenotype and disease severity of the variants. This suggests that the effects of SARS-CoV-2 on TF and inflammasome activation derive in part from the spike protein, and these assays may be useful in predicting the effects of spike protein variants.

Harnessing TCR/CAR Antagonism to Enhance Immunotherapeutic Precision

Chimeric Antigen Receptor (CAR) T cell immunotherapy represents a conceptual breakthrough in the treatment of hematological malignancies. However, the rarity of cell surface protein targets specific to cancerous but not vital tissue has hindered its broad application to solid tumor treatment. While new logic-gated CAR designs have shown reduced toxicity against healthy tissues, the generalizability of such approaches across tumors remains unclear. Here, we harness a universal characteristic of endogenous T cell receptors (TCRs), their ability to discriminate between self and non-self ligands through inhibition of response against self (weak) antigens, to develop a broadly applicable method of enhancing immunotherapeutic precision. We hypothesized that this discriminatory mechanism, known as antagonism, would apply across receptors, allowing for a transfer of specificityfrom TCRs onto CARs. We therefore systematically mapped out the responses of CAR T cells to joint TCR and CAR stimulations. We transduced ovalbumin-specific TCR T cells with mouse CD19 CAR to produce T cells expressing both TCR and CAR and evaluated the response of TCR/CAR T cells using in vivo and in vitro leukemia models ( Figure 1A). We discovered that strong TCR antigen enhanced CAR T killing of CD19 + leukemia, while weak TCR antigen antagonized CAR T responses as assessed in vivo cytotoxicity and in vitro multiplexed dynamic profiling ( Figure 1B). We developed a mathematical model based on cross-receptor inhibitory coupling that accurately predicted the extent of TCR/CAR antagonism across a wide range of immunological settings. This model was validated in a CD19 + B16 mouse melanoma model showing that TCR/CAR antagonism decreased the infiltration of a tumor-reactive T cell cluster (cluster 1), while TCR/CAR agonism enhanced infiltration of this cluster1 ( Figure 1C). We then applied our quantitative knowledge of TCR/CAR crosstalk to design an Antagonism-Enforced Braking System (AEBS) for CAR T cell therapy. This was assessed in a model system using a CAR targeting the tyrosine-protein kinase erbB-2 (HER2), expressed on a subset of patients with both B-ALL and AML together with a hedgehog acyltransferase (HHAT) specific TCR, which responds strongly to mutated peptides presented on tumor cells and weakly to wild-type peptides presented on healthy tissue. Consistent with our discovery of the TCR/CAR antagonism, TCR signals against healthy cells expressing wild-type HHAT peptide antigen antagonized HER2 CAR T cell responses, minimizing on-target/off-tumor cytotoxicity against healthy cells. Notably though, AEBS-CAR T cells exhibited high anti-tumor cytotoxicity against tumor cells expressing HER2 and mutated HHAT peptides ( Figure 1D). AEBS CAR T cells sharpen the discriminatory power of synthetic anti-tumor lymphocytes, laying the groundwork for future studies to engineer complex logic into cells with minimal numbers of receptors ( Figure 1E). Our work highlights a novel mechanism by which TCRs can enforce CAR T cell specificity, with practical implications for the rational design of future anti-leukemia immunotherapies.

Topological data analysis assisted automated sleep stage scoring using airflow signals

Objective:Breathing pattern variability (BPV), as a universal physiological feature, encodes rich health information. We aim to show that, a high-quality automatic sleep stage scoring based on a proper quantification of BPV extracting from the single airflow signal can be achieved. Methods:Topological data analysis (TDA) is applied to characterize BPV from the intrinsically nonstationary airflow signal. The extracted features from TDA are utilized to train an automatic sleep stage scoring model using the XGBoost learner. Additionally, the noise and artifacts that are typically present in the air flow signal are leveraged to improve the performance of the trained system. To evaluate the effectiveness of the proposed approach, a state-of-the-art method is implemented for comparison purposes. Results:A leave-one-subject-out cross-validation was conducted on a dataset comprising 30 whole-night polysomnogram signals with standard annotations. The results show that the proposed features outperform those considered in the state-of-the-art work in terms of overall accuracy (78.8% ± 8.7% vs. 75.0% ± 9.6%) and Cohen’s kappa (0.56 ± 0.15 vs. 0.50 ± 0.15) for automatically scoring wake, rapid eye movement (REM), and non-REM (NREM) stages. An external validation conducted on a dataset comprising 80 whole-night polysomnogram signals with standard annotations shows a result of overall accuracy 74.1%±11.6% and Cohen’s kappa 0.42±0.15, which again outperforms the state-of-the-art work. Furthermore, the analysis of feature importance reveals that the TDA features provide complementary information to the traditional features commonly used in the literature, and the respiratory quality index is identified as an essential component. Conclusion:The proposed TDA-assisted automatic annotation system can accurately distinguish wake, REM and NREM from the airflow signal. Significance:The utilization of a single air flow channel and the universality of BPV suggest the potential of TDA-assisted signal processing in addressing various biomedical signals and homecare issues beyond sleep stage annotation.

Epoxyeicosatrienoic acids alleviate alveolar epithelial cell senescence by inhibiting mitophagy through NOX4/Nrf2 pathway

Alveolar epithelial cell (AEC) senescence is considered to be a universal pathological feature of many chronic pulmonary diseases. Our previous study found that epoxyeicosatrienoic acids (EETs), produced from arachidonic acid (ARA) through the cytochrome P450 cyclooxygenase (CYP) pathway, have significant negative regulatory effects on cellular senescence in AECs. However, the exact mechanisms by which EETs alleviate the senescence of AECs still need to be further explored. In the present study, we observed that bleomycin (BLM) induced enhanced mitophagy accompanied by increased mitochondrial ROS (mito-ROS) content in the murine alveolar epithelial cell line MLE12. While EETs reduced BLM-induced mitophagy and mito-ROS content in MLE12 cells, and the mechanism was related to the regulation of NOX4/Nrf2-mediated redox imbalance. Furthermore, we found that inhibition of EETs degradation could significantly inhibit mitophagy and regulate NOX4/Nrf2 balance to exert anti-oxidant effects in D-galactose-induced premature aging mice. Collectively, these findings may provide new ideas for treating age-related pulmonary diseases by targeting EETs to improve mitochondrial dysfunction and reduce oxidative stress.

HILPS, a long noncoding RNA essential for global oxygen sensing in humans.

Adaptation to low levels of oxygen (hypoxia) is a universal biological feature across metazoans. However, the unique mechanisms how different species sense oxygen deprivation remain unresolved. Here, we functionally characterize a novel long noncoding RNA (lncRNA), LOC105369301, which we termed hypoxia-induced lncRNA for polo-like kinase 1 (PLK1) stabilization (HILPS). HILPS exhibits appreciable basal expression exclusively in a wide variety of human normal and cancer cells and is robustly induced by hypoxia-inducible factor 1α (HIF1α). HILPS binds to PLK1 and sequesters it from proteasomal degradation. Stabilized PLK1 directly phosphorylates HIF1α and enhances its stability, constituting a positive feed-forward circuit that reinforces oxygen sensing by HIF1α. HILPS depletion triggers catastrophic adaptation defect during hypoxia in both normal and cancer cells. These findings introduce a mechanism that underlies the HIF1α identity deeply interconnected with PLK1 integrity and identify the HILPS-PLK1-HIF1α pathway as a unique oxygen-sensing axis in the regulation of human physiological and pathogenic processes.

Geometry of commutes in the universality of percolating traffic flows.

Traffic congestion is a major problem in megacities which increases vehicle emissions and degrades ambient air quality. Various models have been developed to address the universal features of traffic jams. These models range from microscopic car-following models to macroscopic collective dynamic models. Here, we study the macrostructure of congested traffic influenced by the complex geometry of the commute. Our main focus is on the dynamics of traffic patterns in Paris and Los Angeles, each with distinct urban structures. We analyze the complexity of the giant traffic clusters based on a percolation framework during rush hours in the mornings, evenings, and holidays. We uncover that the universality described by several critical exponents of traffic patterns is highly correlated with the geometry of commute and the underlying urban structure. Our findings might have broad implications for developing a greener, healthier, and more sustainable future city.

Collective Emotion: A Framework for Experimental Research

Research on collective emotion spans social sciences, psychology and philosophy. There are detailed case studies and diverse theories of collective emotion. However, experimental evidence regarding the universal characteristics, antecedents and consequences of collective emotion remains sparse. Moreover, current research mainly relies on emotion self-reports, accounting for the subjective experience of collective emotion and ignoring their cognitive and physiological bases. In response to these challenges, we argue for experimental research on collective emotion. We start with an overview of theoretical frameworks to identify a set of three characteristics of collective emotion. Based on research in cognitive and affective sciences, we then examine the corresponding candidate mechanisms. Finally, we highlight outstanding questions, review experimental evidence, and suggest ideas for future experimental research.

Reviving trace: photographic image within the treatment of pain experiences

Recognition the importance of other people’s experiences is one of the urgent philosophical problems. If by the middle of the 19th century people encountered painful experiences of others directly or through witnesses, since then after the advent of media technologies, the role of the witness was replaced by the anonymous visual. Visual images are formations whose structure avoids ambiguity and creates a field for multiple interpretations. This duality is well reflected by the nature of the photographic image. It is characterized by a dialectical tension: on the one hand, capturing someone’s painful experience the photograph represents the mental state of a person, but on the other hand, it raises the question of an unambiguous attitude towards it. The ambiguity of the photographic image yields a dilemma: either to accept what we see on faith and base our moral discussion of events on it alone, or to analyze the action of the forces hidden in the work of the photographic image. To talk about photographing suffering means to declare a certain ethical and political position. The case of the photograph problematizes the requirement of ethical involvement, because the photograph can simply be ignored. The article shows how the photographic image communicates the criteria, using which a perceiver is able to fit what he sees into the context of his own political and social world. Having performed the act of recognition, a perceiver is able to politicize human life as an irreplaceable value. In such acts, he actualizes his own subjectivity through the recognition of the photographic image as a part of common shared reality. He perceives the signs of someone else’s pain in the photo as a reason to reflect on human vulnerability. For this, the perceiver must carry out a complex procedure of image interpretation, stripping it off anonymous universal features.

Targeting acidic pre-metastatic niche in lungs by pH low insertion peptide and its utility for anti-metastatic therapy.

Dysregulated extracellular pH, the universal feature of tumor, works as an evolutional force to drive dissemination of tumor cells. It is well-established that tumor acidity is associated with tumor growth and metastasis. However, the pH of pre-metastatic niche remains unclear. We hypothesized that primary tumor cells remotely prime acidity in secondary organ to achieve metastatic colonization. Herein, we demonstrated that the pH responsive probe pH Low Insertion Peptide (pHLIP) was notably accumulated in pre-metastatic lungs of 4T1.2 breast tumor-bearing mice. The pHLIP-targeted lungs showed high amounts of lactate and overexpressed glycolysis-related proteins. Pharmacological inhibition of glycolysis suppressed the lung acidification induced by 4T1.2 cancer cell culture supernatant and delayed subsequent metastatic burden of disseminated tumor cells. In the acidic lungs, pHLIP was primarily localized in alveolar type 2 cells which strongly expressed glycolysis-related proteins. 4T1.2-derived extracellular vesicles expressed some of the glycolysis-related proteins, and their administration increased pHLIP accumulation and glycolytic enhancement in lungs. pHLIP-conjugated dexamethasone effectively attenuated lung metastatic burden by disrupting pro-inflammatory response in the acidic lungs. From these results, targeting the metastasis-supporting microenvironment by pHLIP technology creates possibility to identify pre-metastatic organ and prevent metastatic recurrence.

Covariant description of the colloidal dynamics on curved manifolds

Brownian motion is a universal characteristic of colloidal particles embedded in a host medium, and it is the fingerprint of molecular transport or diffusion, a generic feature of relevance not only in physics but also in several branches of science and engineering. Since its discovery, Brownian motion, also known as colloidal dynamics, has been important in elucidating the connection between the molecular details of the diffusing macromolecule and the macroscopic information on the host medium. However, colloidal dynamics is far from being completely understood. For instance, the diffusion of non-spherical colloids and the effects of the underlying geometry of the host medium on the dynamics of either passive or active particles are a few representative cases that are part of the current challenges in soft matter physics. In this contribution, we take a step forward to introduce a covariant description of the colloidal dynamics in curved spaces. Without the loss of generality, we consider the case where hydrodynamic interactions are neglected. This formalism will allow us to understand several phenomena, for instance, the curvature effects on the kinetics during spinodal decomposition and the thermodynamic properties of colloidal dispersion, to mention a few examples. This theoretical framework will also serve as the starting point to highlight the role of geometry on colloidal dynamics, an aspect that is of paramount importance to understanding more complex transport phenomena, such as the diffusive mechanisms of proteins embedded in cell membranes.

Electrocardiogram-Based Biometric Identification Using Mixed Feature Extraction and Sparse Representation.

(1) Background: The ability to recognize identities is an essential component of security. Electrocardiogram (ECG) signals have gained popularity for identity recognition because of their universal, unique, stable, and measurable characteristics. To ensure accurate identification of ECG signals, this paper proposes an approach which involves mixed feature sampling, sparse representation, and recognition. (2) Methods: This paper introduces a new method of identifying individuals through their ECG signals. This technique combines the extraction of fixed ECG features and specific frequency features to improve accuracy in ECG identity recognition. This approach uses the wavelet transform to extract frequency bands which contain personal information features from the ECG signals. These bands are reconstructed, and the single R-peak localization determines the ECG window. The signals are segmented and standardized based on the located windows. A sparse dictionary is created using the standardized ECG signals, and the KSVD (K-Orthogonal Matching Pursuit) algorithm is employed to project ECG target signals into a sparse vector-matrix representation. To extract the final representation of the target signals for identification, the sparse coefficient vectors in the signals are maximally pooled. For recognition, the co-dimensional bundle search method is used in this paper. (3) Results: This paper utilizes the publicly available European ST-T database for our study. Specifically, this paper selects ECG signals from 20, 50 and 70 subjects, each with 30 testing segments. The method proposed in this paper achieved recognition rates of 99.14%, 99.09%, and 99.05%, respectively. (4) Conclusion: The experiments indicate that the method proposed in this paper can accurately capture, represent and identify ECG signals.

UniG-Encoder: A universal feature encoder for graph and hypergraph node classification

Despite the decent performance and fruitful applications of Graph Neural Networks (GNNs), Hypergraph Neural Networks (HGNNs), and their well-designed variants, on some commonly used benchmark graphs and hypergraphs, they are outperformed by even a simple Multi-Layer Perceptron. This observation motivates a reexamination of the design paradigm of the current GNNs and HGNNs and poses challenges of extracting graph features effectively. In this work, a universal feature encoder for both graph and hypergraph representation learning is designed, called UniG-Encoder. The architecture starts with a forward transformation of the topological relationships of connected nodes into edge or hyperedge features via a normalized projection matrix. The resulting edge/hyperedge features, together with the original node features, are fed into a neural network. The encoded node embeddings are then derived from the reversed transformation, described by the transpose of the projection matrix, of the network’s output, which can be further used for tasks such as node classification. The designed projection matrix, encoding the graph features, is intuitive and interpretable. The proposed architecture, in contrast to the traditional spectral-based and/or message passing approaches, simultaneously and comprehensively exploits the node features and graph/hypergraph topologies in an efficient and unified manner, covering both heterophilic and homophilic graphs. Furthermore, a variant version, UniG-Encoder II, is devised to leverage multi-hop node information. Extensive experiments are conducted and demonstrate the superior performance of the proposed framework on twelve representative hypergraph datasets and six real-world graph datasets, compared to the state-of-the-art methods. Our implementation is available online at https://github.com/MinhZou/UniG-Encoder.

Structure of a heteropolymeric type 4 pilus from a monoderm bacterium

Type 4 pili (T4P) are important virulence factors, which belong to a superfamily of nanomachines ubiquitous in prokaryotes, called type 4 filaments (T4F). T4F are defined as helical polymers of type 4 pilins. Recent advances in cryo-electron microscopy (cryo-EM) led to structures of several T4F, revealing that the long N-terminal α-helix (α1) – the trademark of pilins – packs in the centre of the filaments to form a hydrophobic core. In diderm bacteria – all available bacterial T4F structures are from diderm species – a portion of α1 is melted (unfolded). Here we report that this architecture is conserved in phylogenetically distant monoderm species by determining the structure of Streptococcus sanguinis T4P. Our 3.7 Å resolution cryo-EM structure of S. sanguinis heteropolymeric T4P and the resulting full atomic model including all minor pilins highlight universal features of bacterial T4F and have widespread implications in understanding T4F biology.

Репрезентация концепта «ангел» в романах Ф.М. Достоевского

The paper analyzes the representation of the concept ‘angel’ in the novels of F.M. Dostoevsky. The content of the concept ‘angel’, which is an important component of Dostoevsky’s conceptosphere, is also described. Universal content of the concept ‘angel’ in Dostoevsky’s works is represented in the context of philosophical problems of his works, which are expressed in the foundation of the human’s contradictory spiritual choice in the situation of chaos; in the necessity of a personal path to the divine truth and meaning of existence. Especially noted the inconsistency of human perception of the concept ‘angel’, which combines an exalted adoration of the deity with a desire to destroy it. The concept of ‘angel’ in Dostoevsky’s interpretation has universal features descending from the biblical interpretation of the image, but it is also included in the philosophical issues outlined. ‘Angel’ appears both in its absolute, universal meaning and also as the embodiment of human reflection — as an internally contradictory narrative, a message about the simultaneous greatness and falling of man. The intrinsic conflict of the conceptual content of the ‘angelic’ manifests through both profane and noble perception and usage of it by the protagonists. However, there is no conflict in the true destiny of the hero, who realizes the mission of an angel in the world. The concept passes from the verbal level to the event level, and at this level it loses its inner conflict and is embodied in the basic meaning of the concept of angel, losing its subjectivity and contradictory human interpretations.

Raising Awareness About Language- and Culture-Specific Considerations in the Management of Dysarthria Associated With Parkinson's Disease Within the United States.

The purpose of this article is to raise awareness about the importance of diverting from English-centric approaches in the management of dysarthria associated with Parkinson's disease (PD) in the United States, and embracing a language- and culture-specific perspective when working with linguistically and culturally diverse populations within the context of culturally responsive, precision medicine. This tutorial is divided into two primary components: a critical review of language universal and language-specific characteristics of dysarthria associated with PD and their relationship with speech intelligibility, and a practical guide to culturally responsive evidence-based practice for speech-language pathologists. We offer a framework for linguistically and culturally appropriate considerations when working with clients with dysarthria associated with PD. While "universal" representations of dysarthria may be part of the big picture, language-specific contributions to speakers' intelligibility should be carefully examined to maximize treatment outcomes. Additionally, an evidence-based model that fully embraces clients' wishes and values within the context of culturally responsive, precision medicine should be prioritized, a practice that may include the use of interpreters.