Multiple Modes Of Interaction Research Articles

The pseudogene GBP1P1 suppresses influenza A virus replication by acting as a protein decoy for DHX9.

Recently, substantial evidence has demonstrated that pseudogene-derived long noncoding RNAs (lncRNAs) as regulatory RNAs have been implicated in basic physiological processes and disease development through multiple modes of functional interaction with DNA, RNA, and proteins. Here, we report an important role for GBP1P1, the pseudogene of guanylate-binding protein 1, in regulating influenza A virus (IAV) replication in A549 cells. GBP1P1 was dramatically upregulated after IAV infection, which is controlled by JAK/STAT signaling. Functionally, ectopic expression of GBP1P1 in A549 cells resulted in significant suppression of IAV replication. Conversely, silencing GBP1P1 facilitated IAV replication and virus production, suggesting that GBP1P1 is one of the interferon-inducible antiviral effectors. Mechanistically, GBP1P1 is localized in the cytoplasm and functions as a sponge to trap DHX9 (DExH-box helicase 9), which subsequently restricts IAV replication. Together, these studies demonstrate that GBP1P1 plays an important role in antagonizing IAV replication.IMPORTANCELong noncoding RNAs (lncRNAs) are extensively expressed in mammalian cells and play a crucial role as regulators in various biological processes. A growing body of evidence suggests that host-encoded lncRNAs are important regulators involved in host-virus interactions. Here, we define a novel function of GBP1P1 as a decoy to compete with viral mRNAs for DHX9 binding. We demonstrate that GBP1P1 induction by IAV is mediated by JAK/STAT activation. In addition, GBP1P1 has the ability to inhibit IAV replication. Importantly, we reveal that GBP1P1 acts as a decoy to bind and titrate DHX9 away from viral mRNAs, thereby attenuating virus production. This study provides new insight into the role of a previously uncharacterized GBP1P1, a pseudogene-derived lncRNA, in the host antiviral process and a further understanding of the complex GBP network.

High-efficiency and economical uranium extraction from seawater with easily prepared supramolecular complexes

Developing effective adsorbents for uranium extraction from natural seawater is strategically significant for the sustainable fuel supply of nuclear energy. Herein, stable and low-cost supramolecular complexes (PA-bPEI complexes) were facilely constructed through the assembly of phytic acid and hyperbranched polyethyleneimine based on the multiple modes of electrostatic interaction and hydrogen bonding. The PA-bPEI complexes exhibited not only high uptake (841.7 mg g−1) and selectivity (uranium/vanadium selectivity = 84.1) toward uranium but also good antibacterial ability against biofouling. Mechanism analysis revealed that phosphate chelating groups and amine assistant groups coordinated the uranyl ions together with a high affinity. To be more suitable for practical applications, powdery PA-bPEI complexes were compounded with sodium alginate to fabricate various macroscopic adsorbents with engineered forms, which achieved an extraction capacity of 9.0 mg g−1 in natural seawater after 50 days of testing. Impressively, the estimated economic cost of the macroscopic adsorbent for uranium extraction from seawater ($96.5 ∼ 138.1 kg−1 uranium) was lower than that of all currently available uranium adsorbents. Due to their good uranium extraction performance and low economic cost, supramolecular complex-based adsorbents show great potential for industrial uranium extraction from seawater.

Research on a new cable-driven lower limb rehabilitation robot with bilateral coordination control

In this paper, a new type of cable-driven lower limb rehabilitation robot (CDLLRR) based on bilateral control is proposed. Compared with the traditional rehabilitation robot, it has multiple cooperative remote rehabilitation modes of patient-therapist interaction with better safety, mechanical compliance and adaptability. Firstly, according to the characteristics of gait movement of human lower limbs and the performance requirements of the robot in therapy and rehabilitation, the overall structure, main components and assembly arrangement of the robot are designed in detail. Secondly, in order to ensure that the rehabilitation robot has excellent force transparency and system stability while still maintaining a certain position tracking, according to the performance measurement index based on the introduced bilateral control strategy, this paper proposes an improved PD controller based on Anderson method (IPDAM). Finally, the feasibility of the proposed CDLLRR and the effectiveness of the IPDAM are verified by simulation experiments.

Exploring multi-relational spatial interaction imputation with distance-decay effects

ABSTRACT Spatial interaction imputation aims to compensate for missing stable connections in geographical space, bolstering interaction network integrity and accuracy. Graph neural networks excel in graph-structured interaction data. However, existing research often focuses on homogeneous networks, neglecting the impact of heterogeneous interaction relationships influenced by distance decay on interaction imputation. Neglecting edge heterogeneity constrains the ability to effectively model the network structure, consequently leading to suboptimal performance in interaction imputation. This study introduces an interaction imputation graph convolutional network model. It constructs a heterogeneous interaction network with multi-distance relationships, considering distance decay. The model performs graph embedding based on interaction relationships between nodes. It comprehensively incorporates multiple interaction modes, topological structures, and node attributes to enhance spatial interaction imputation accuracy. Empirically validated using Beijing taxi travel data, our model outperforms existing models, improving imputation accuracy by approximately 8.70%. Our model consistently maintains superior accuracy in interaction networks of various sizes, demonstrating the stable superiority of our model. We also demonstrated that the variation in the number of interaction relationships affects imputation accuracy. A reasonable number of relationships and a larger feature dimension of geographical units yield better interaction imputation results.

A novel multifunctional intelligent bed integrated with multimodal human–robot interaction approach and safe nursing methods

AbstractThe authors propose a multifunctional intelligent bed (MIB) that integrates multiple modes of interaction to improve the welfare of mobility‐impaired users and reduce the workload of medical personnel. The MIB features independent autonomous omnidirectional movement, position adjustment, multi‐degree‐of‐freedom (DOF) movement regulation and posture memory functions to facilitate comfortable and convenient interaction for mobility‐impaired users. In particular, an integrated “MIB‐state perception‐interaction interfaces” system is established, and a bed fall risk detection algorithm and assisted get‐up‐transfer algorithm is proposed. By recognising and sharing human body state characteristics, nursing collaboration can be achieved with caregivers or other nursing robots. Comprehensive experiments demonstrate that the MIB is a novel MIB that is highly adaptable to the environment, convenient to interact with and safe. By integrating the proposed algorithms, daily safety monitoring, assisted get‐up and defecation tasks can be effectively accomplished. This technology demonstrates excellent applicability and promising prospects for implementation in hospitals, nursing centres and homes catering to elderly and disabled individuals with mobility impairments.

Docking Study, Synthesis, Characterization and Preliminary Cytotoxic Evaluation of New 1,3,4- Thiadiazole Derivatives

Objectives: This study has determined that these newly synthesized analogs hold promise as potential sources of novel anticancer agents for combating breast cancer.
 Methods: We initiated our research by obtaining the crystal structure of Histone deacetylases (HDACs-8) bound with Vorinostat (SAHA) from the Protein Data Bank (PDB code 4QA0). Subsequently, we conducted docking experiments, which revealed that compounds (V c,s, V d,s, V c,t, and V d,t) exhibited favorable docking scores when compared to the standard. These compounds, synthesized through multi-step procedures involving the reaction of intermediate derivatives (IV c,d) with thiosemicarbazide or semicarbazide, were subjected to confirmation of their chemical structures using FT-IR and 1H NMR analysis.
 Results: The results of our in-vitro cytotoxicity assay (MTT assay) highlighted that compounds V c,t and V d,t exhibited notable inhibition ratios in the breast cancer cell line (MCF-7), while V c,t displayed similar efficacy in human colon adenocarcinoma (HRT-18) compared to the control drug, Vorinostat (SAHA).
 Conclusion: Our docking analysis led us to conclude that the C=S moiety demonstrated exceptional binding affinity to the zinc binding group of the HDAC enzyme, establishing multiple interaction modes. This finding suggests the potential of these compounds as valuable candidates in the development of anticancer treatments.

A unified inferring framework of multiplex epidemic networks under multiple interlayer interaction modes

Different epidemic transmissions on multiplex networks may interact and display intertwined effects, leading to a challenge and urgently needed problem of the inference of multiplex epidemic network structures under multiple interlayer interaction modes (IIMs). However, in reality, few existing studies have focused on multiplex epidemic network inference responding to the intertwined IIMs, much less the corresponding consistency analysis. To fill these two gaps, we first propose an inference framework of multiplex epidemic networks under a unified form of IIMs. In particular, we develop a Hamming distance-based two-step estimator for an intricate IIM called infection-probability-dependent interaction (IPDI). The proposed two-step estimator overcomes the problems of unobservable and time-varying variable inference in the IPDI mode. Second, we solve the theoretical difficulty of consistency analysis for the network inference under multiple IIMs and obtain sufficient conditions for exponentially decaying inferring error. Under the guarantee of consistently sufficient conditions, the sample size scale enables our framework's high-dimensional inferring ability. The synthetic network simulations show the validity of the proposed algorithm and consistency analysis. In addition, the analysis of real data of Twitter and Foursquare indicates the effectiveness and practicality of the proposed inferring framework.

Protein interactions: anything new?

How do proteins interact in the cellular environment? Which interactions stabilize liquid-liquid phase separated condensates? Are the concepts, which have been developed for specific protein complexes also applicable to higher-order assemblies? Recent discoveries prompt for a universal framework for protein interactions, which can be applied across the scales of protein communities. Here, we discuss how our views on protein interactions have evolved from rigid structures to conformational ensembles of proteins and discuss the open problems, in particular related to biomolecular condensates. Protein interactions have evolved to follow changes in the cellular environment, which manifests in multiple modes of interactions between the same partners. Such cellular context-dependence requires multiplicity of binding modes (MBM) by sampling multiple minima of the interaction energy landscape. We demonstrate that the energy landscape framework of protein folding can be applied to explain this phenomenon, opening a perspective toward a physics-based, universal model for cellular protein behaviors.

Sequence-Dependent Backbone Dynamics of Intrinsically Disordered Proteins.

For intrinsically disordered proteins (IDPs), a pressing question is how sequence codes for function. Dynamics serves as a crucial link, reminiscent of the role of structure in sequence-function relations of structured proteins. To define general rules governing sequence-dependent backbone dynamics, we carried out long molecular dynamics simulations of eight IDPs. Blocks of residues exhibiting large amplitudes in slow dynamics are rigidified by local inter-residue interactions or secondary structures. A long region or an entire IDP can be slowed down by long-range contacts or secondary-structure packing. On the other hand, glycines promote fast dynamics and either demarcate rigid blocks or facilitate multiple modes of local and long-range inter-residue interactions. The sequence-dependent backbone dynamics endows IDPs with versatile response to binding partners, with some blocks recalcitrant while others readily adapting to intermolecular interactions.

SEM/EDX analysis of stomach contents of a sea slug snacking on a polluted seafloor reveal microplastics as a component of its diet

Understanding the impacts of microplastics on living organisms in aquatic habitats is one of the hottest research topics worldwide. Despite increased attention, investigating microplastics in underwater environments remains a problematic task, due to the ubiquitous occurrence of microplastic, its multiple modes of interactions with the biota, and to the diversity of the synthetic organic polymers composing microplastics in the field. Several studies on microplastics focused on marine invertebrates, but to date, the benthic sea slugs (Mollusca, Gastropoda, Heterobranchia) were not yet investigated. Sea slugs are known to live on the organisms on which they feed on or to snack while gliding over the sea floor, but also as users of exogenous molecules or materials not only for nutrition. Therefore, they may represent a potential biological model to explore new modes of transformation and/or management of plastic, so far considered to be a non-biodegradable polymer. In this study we analysed the stomachal content of Bursatella leachii, an aplysiid heterobranch living in the Mar Piccolo, a highly polluted coastal basin near Taranto, in the northern part of the Ionian Sea. Microplastics were found in the stomachs of all the six sampled specimens, and SEM/EDX analyses were carried out to characterize the plastic debris. The SEM images and EDX spectra gathered here should be regarded as a baseline reference database for future investigations on marine Heterobranchia and their interactions with microplastics.

Utilising the triboelectricity of the human body for human-computer interactions

Human-computer interaction (HCI) strategies communicate the human mind and machine intelligence based on different devices and technologies. The majority of HCI strategies assume normal physical conditions that limit accessibility for users with disabilities. Certain products, such as Braille keyboards, work fine for people with specific disabilities. However, a more general HCI strategy that can neglect users’ physical conditions would enhance the accessibility of these tools for disabled persons. Here, we report an HCI strategy that utilises triboelectricity of the human body (TEHB) for HCI. The TEHB can be generated by many parts of the human body, eliminating the obstacles imposed by physical function disabilities. Such an HCI approach has been used for text inputs, graphical inputs, and mimicked mouse functions. With the assistance of deep learning, an accuracy of approximately 98.4 % is achieved for text inputs obtained directly from handwriting. Our findings provide a new approach for HCI and demonstrate the feasibility of multiple interaction modes.

Finite-Time Interactive Control of Robots with Multiple Interaction Modes.

This paper proposes a finite-time multi-modal robotic control strategy for physical human–robot interaction. The proposed multi-modal controller consists of a modified super-twisting-based finite-time control term that is designed in each interaction mode and a continuity-guaranteed control term. The finite-time control term guarantees finite-time achievement of the desired impedance dynamics in active interaction mode (AIM), makes the tracking error of the reference trajectory converge to zero in finite time in passive interaction mode (PIM), and also guarantees robotic motion stop in finite time in safety-stop mode (SSM). Meanwhile, the continuity-guaranteed control term guarantees control input continuity and steady interaction modes transition. The finite-time closed-loop control stability and the control effectiveness is validated by Lyapunov-based theoretical analysis and simulations on a robot manipulator.

A conformational switch in the SCF-D3/MAX2 ubiquitin ligase facilitates strigolactone signalling.

Strigolactones (SLs) are a class of plant hormones that regulate numerous processes of growth and development. SL perception and signal activation involves interaction between F-box E3 ubiquitin ligase D3/MAX2 and DWARF14 (D14) α/β-hydrolase in a SL-dependent manner and targeting of D53/SMXL6/7/8 transcriptional repressors (SMXLs) for proteasome-mediated degradation. D3/MAX2 has been shown to exist in multiple conformational states in which the C-terminal helix (CTH) undergoes a closed-to-open dynamics and regulates D14 binding and SL perception. Despite the multiple modes of D3-D14 interactions found in vitro, the residues that regulate the conformational switch of D3/MAX2 CTH in targeting D53/SMXLs and the subsequent effect on SL signalling remain unclear. Here we elucidate the functional dynamics of ASK1-D3/MAX2 in SL signalling by leveraging conformational switch mutants in vitro and in plants. We report the crystal structure of a dislodged CTH of the ASK1-D3 mutant and demonstrate that disruptions in CTH plasticity via either CRISPR-Cas9 genome editing or expression of point mutation mutants result in impairment of SL signalling. We show that the conformational switch in ASK1-D3/MAX2 CTH directly regulates ubiquitin-mediated protein degradation. A dislodged conformation involved in D53/SMXLs SL-dependent recruitment and ubiquitination and an engaged conformation are required for the release of polyubiquitinated D53/SMXLs and subsequently D14 for proteasomal degradation. Finally, we uncovered an organic acid metabolite that can directly trigger the D3/MAX2 CTH conformational switch. Our findings unravel a new regulatory function of a SKP1-CUL1-F-box ubiquitin ligase in plant signalling.

How human-robot collaboration impacts construction productivity: An agent-based multi-fidelity modeling approach

Though construction robots have drawn attention in research and practice for decades, human-robot collaboration (HRC) remains important to conduct complex construction tasks. Considering its complexity and uniqueness, it is still unclear how HRC process will impact construction productivity, which is difficult to handle with conventional methods such as field tests, mathematical modeling and physical simulation approaches. To this end, an agent-based (AB) multi-fidelity modeling approach is introduced to simulate and evaluate how HRC influences construction productivity. A high-fidelity model is first proposed for a scenario with one robot. Then, a low-fidelity model is established to extract key parameters that capture the inner relationship among scenarios. The multi-fidelity models work together to simulate complex scenarios. Based on the simulation model, the twofold influence of HRC on productivity, namely the supplement strategy on the worker side, and the design for proactive interaction on the robot side, are fully investigated. Experimental results show that: 1) the proposed approach is feasible and flexible for simulation of complex HRC processes, and can cover multiple collaboration and interaction modes; 2) the influence of the supplement strategy is simple when there is only one robot, where lower Check Interval (CI) and higher Supplement Limit (SL) will improve productivity. But the influence becomes much more complicated when there are more robots due to the internal competition among robots for the limited time of workers; 3) HRC has a scale effect on productivity per robot, which means the productivity improves if there are more robots and workers, even if the human-robot ratio remains the same; 4) introducing proactive interaction between robots and workers could improve productivity significantly, up to 22% in our experiments, which further depends on the supplement strategy and the human-robot ratio. Overall, this research contributes an integrated approach to simulate and evaluate HRC’s impacts on productivity as well as valuable insights on how to optimize HRC for better performance and occupational health. The proposed approach is also useful for the evaluation and development of new robots.

Identification of a Long Noncoding RNA (lncPRDM16) Inhibiting Preadipocyte Proliferation in the Chicken.

Long noncoding RNAs are vital to a variety of biological and physiological processes through multiple modes of functional interaction with DNA, RNA, and proteins. In chickens, numerous lncRNAs were discovered to be important to growth or disease progression. However, the detailed molecular function and role of lncRNAs remain less explored. Here, we performed lncRNA sequencing on abdominal adipose tissues from broiler lines divergently selected for abdominal fat content, and significantly differentially expressed lncRNAs were found, including lncPRDM16, a divergently transcribed and conserved lncRNA near PRDM16. Full lengths of two transcripts of lncPRDM16 were obtained, and their genomic structures were compared. Expression dynamics of lncPRDM16 in different tissues and during preadipocyte proliferation and differentiation were profiled. Moreover, a 250-nucleotide sequence at 5'-end was found to be inevitable to the function of lncPRDM16 in inhibiting preadipocyte proliferation and regulating the promoter activities of both lncPRDM16 and PRDM16. Taken together, we identified the 5'-end functional elements of lncPRDM16 and their potential importance in inhibiting preadipocyte proliferation. Our findings provide the foundation for further exploration of lncPRDM16 function and potential improvement of chicken muscle quality.

Organizing an “organizationless” protest campaign in the WeChatsphere

The introduction of digital technologies in collective actions seems to have transformed the dynamics of movement organizing and enabled divergent forms of protest organizing. While some studies emphasize “organizationless” organizing in which traditional organizational forms—social movements organizations and formal-bureaucratic structures—have been pushed into the margins, other studies showcase how traditional forms have assumed alternative features, for example, connective leadership and organizations with fluid boundaries. While existing research correctly points out the evolving organizing dynamics and forms in digital activism, few studies have accounted for why digitally enabled protests take certain organizing forms over others among multiple modes of interaction between protesters and digital technologies. Using a case study of a protest campaign organized by Chinese American immigrants, this study illustrates why immigrant activists struggled to keep the campaign “organizationless” on WeChat, a China-based digital platform that afforded other forms of organizing over such an organizing mode. Building on the mechanism-based approach in social movement studies, the findings show that immigrant activists’ emotional–cognitive responses to the changing digital environments became the driving force behind the relational choices to maintain the protest “organizationless.” The study, therefore, may not only inform future studies to explore why certain structures of protest networks emerge and develop but also contribute to the mechanism-based approach by foregrounding emotional–cognitive mechanisms, which mediate environmental and relational mechanisms.

Community Detection in Fully-Connected Multi-layer Networks Through Joint Nonnegative Matrix Factorization

Modern data analysis and processing tasks typically involve large sets of structured data. Graphs provide a powerful tool to describe the structure of such data, where the entities and the relationships between them are modeled as the nodes and edges of the graph. Traditional single layer network models are insufficient for describing the multiple entity types and modes of interaction encountered in real-world applications. Recently, multi-layer network models, which consider the different types of interactions both within and across layers, have emerged to model these systems. One of the important tools in understanding the topology of these high-dimensional networks is community detection. In this paper, a joint nonnegative matrix factorization approach is proposed to detect the community structure in multi-layer networks. The proposed approach models the multi-layer network as the union of a multiplex and bipartite network and formulates community detection as a regularized optimization problem. This optimization problem simultaneously finds the nonnegative low-rank embedding of the intra- and inter-layer adjacency matrices while minimizing the distance between the two to guarantee pair-wise similarity across embeddings. The proposed approach can detect the community structure for both homogeneous and heterogeneous multi-layer networks and is robust to noise and sparsity. The performance of the proposed approach is evaluated for both simulated and real networks and compared to state-of-the-art methods.

Multiple interaction modes between saccharin and sweet taste receptors determine a species-dependent response to saccharin.

Saccharin is a commonly used artificial sweetener that exhibits both sweetening and sweet inhibition activities. The species‐dependent response towards saccharin and the interaction between saccharin and the sweet taste receptor T1R2/T1R3 remain elusive. In this study we used mismatched chimeras of T1R2 and T1R3 and calcium mobilization functional analysis to reveal a detailed species‐dependent response towards saccharin of human, squirrel monkey, and mouse sweet taste receptors. Our findings, combined with previous results by others, suggest multiple and complex interaction modes between saccharin and the sweet taste receptor, which are helpful guidelines for effective modulation of the sweet taste by sweetener/sweet inhibitors.

The Determinants of States' Interactions with China in the Belt and Road Initiative (BRI): Spatial Gravity Interaction

The Belt and Road Initiative (BRI) is a far‐reaching initiative of China's active engagement in global affairs and is seen to determine the future fate of Eurasia. Previous studies about states' interactions with China in the BRI either give suggestions on further actions or selectively depict how participants interact with China in a non‐comparative way. With the BRI event data collected that covers multiple modes of BRI interactions, this paper takes the initiative to explore the determinants of states' interactions with China in the BRI. With the spatial gravity model, this paper finds that economic size, market quality, geographic proximity, and political and economic amity are closely associated with states' interactions with China in the BRI, which further contributes to the broad literature of the application of the gravity model as well as the interaction of states with China under the new era of China's more active, confidential, and assertive foreign policy.

Vesicle encapsulation stabilizes intermolecular association and structure formation of functional RNA and DNA

During the origin of life, encapsulation of RNA inside vesicles is believed to have been a defining feature of the earliest cells (protocells). The confined biophysical environment provided by membrane encapsulation differs from that of bulk solution and has been shown to increase activity as well as evolutionary rate for functional RNA. However, the structural basis of the effect on RNA has not been clear. Here, we studied how encapsulation of the hairpin ribozyme inside model protocells affects ribozyme kinetics, ribozyme folding into the active conformation, and cleavage and ligation activities. We further examined the effect of encapsulation on the folding of a stem-loop RNA structure and on the formation of a triplex structure in a pH-sensitive DNA switch. The results indicate that encapsulation promotes RNA-RNA association, both intermolecular and intramolecular, and also stabilizes tertiary folding, including the docked conformation characteristic of the active hairpin ribozyme and the triplex structure. The effects of encapsulation were sufficient to rescue the activity of folding-deficient mutants of the hairpin ribozyme. Stabilization of multiple modes of nucleic acid folding and interaction thus enhanced the activity of encapsulated nucleic acids. Increased association between RNA molecules may facilitate the formation of more complex structures and cooperative interactions. These effects could promote the emergence of biological functions in an "RNA world" and may have utility in the construction of minimal synthetic cells.