Bidirectional Interactions Research Articles

Macrophage polarization in rheumatoid arthritis: signaling pathways, metabolic reprogramming, and crosstalk with synovial fibroblasts

Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by persistent synovial inflammation and progressive joint destruction. Macrophages are key effector cells that play a central role in RA pathogenesis through their ability to polarize into distinct functional phenotypes. An imbalance favoring pro-inflammatory M1 macrophages over anti-inflammatory M2 macrophages disrupts immune homeostasis and exacerbates joint inflammation. Multiple signaling pathways, including Notch, JAK/STAT, NF-κb, and MAPK, regulate macrophage polarization towards the M1 phenotype in RA. Metabolic reprogramming also contributes to this process, with M1 macrophages prioritizing glycolysis while M2 macrophages utilize oxidative phosphorylation. Redressing this imbalance by modulating macrophage polarization and metabolic state represents a promising therapeutic strategy. Furthermore, complex bidirectional interactions exist between synovial macrophages and fibroblast-like synoviocytes (FLS), forming a self-perpetuating inflammatory loop. Macrophage-derived factors promote aggressive phenotypes in FLS, while FLS-secreted mediators contribute to aberrant macrophage activation. Elucidating the signaling networks governing macrophage polarization, metabolic adaptations, and crosstalk with FLS is crucial to developing targeted therapies that can restore immune homeostasis and mitigate joint pathology in RA.

Modal-aware prompt tuning with deep adaptive feature enhancement

Prompt learning has recently emerged as a promising method for fine-tuning vision-language models. By introducing prompts in the text encoder or image encoder, the pre-trained model can quickly adapt to downstream tasks without updating the pre-trained weights. However, prior multi-modal prompt tuning works do not consider the difference in feature distributions between text and images, and adopt the same prompts for both encoders, thus achieving sub-optimal performance in the downstream few-shot learning. In this paper, we propose Modal-Aware Prompt (MAP) to alleviate this issue. Specifically, considering the stability of text features, we design text-specific prompts, which can acquire text class-related information from a general template (i.e., “a photo of a <category>”) by unidirectional attention-based interaction. Additionally, considering the diversity of image features, we design visual-specific prompts to acquire image class-related information and adjust the image features by bidirectional attention-based interaction. To learn hierarchical prompt representations and reinforce the prompt features, we further propose a Deep Adaptive Feature Enhancement (DAFE) module to adaptively utilize the prompt output of the former layer, which can combine instance-level and task-level information simultaneously. Combining the above two designs, our method MAP-DAFE obtains state-of-the-art results on 11 image recognition datasets and has the fastest convergence rate. This proves our MAP-DAFE is effective and efficient.

Task-order control in dual-tasks: Only marginal interactions between conflict at lower levels and higher processes of task organization.

When simultaneously performing two tasks that share response properties, interference can occur. Besides general performance decrements, performance in the first task is worse when the second task requires a spatially incompatible response, known as the backward crosstalk effect (BCE). The size of this BCE, similar to congruency effects in conflict tasks, is subject to a sequential modulation, with a smaller BCE after incompatible compared to compatible trials. In the present study, we focus on a potential bidirectional interaction between crosstalk (and its resolution) at a lower level of task performance and higher-order processes of task organization. Two questions were of particular interest: First, do participants switch task order more frequently after a conflict-prone incompatible trial than after a compatible trial? Second, does changing task order influence the efficiency of conflict resolution, as indexed by the size of the sequential modulation of the BCE. Across four experiments, we only found marginal evidence for an influence of lower-level conflict on higher-order processes of task organization, with only one experiment revealing a tendency to repeat task order following conflict. Our results thus suggest practical independence between conflict and task-order control. When separating processes of task selection and task performance, the sequential modulation was generally diminished, suggesting that conflict resolution in dual-tasks can be disrupted by a deliberate decision about task order, or, alternatively, by a longer inter-trial interval. Finally, the study found a strong bias towards repeating the same task order across trials, suggesting that task-order sets not only impact task performance but also guide task selection.

Friend or Foe: Exploring the Relationship between the Gut Microbiota and the Pathogenesis and Treatment of Digestive Cancers

Digestive cancers are among the leading causes of cancer death in the world. However, the mechanisms of cancer development and progression are not fully understood. Accumulating evidence in recent years pointing to the bidirectional interactions between gut dysbiosis and the development of a specific type of gastrointestinal cancer is shedding light on the importance of this “unseen organ”—the microbiota. This review focuses on the local role of the gut microbiota imbalance in different digestive tract organs and annexes related to the carcinogenic mechanisms. Microbiota modulation, either by probiotic administration or by dietary changes, plays an important role in the future therapies of various digestive cancers.

Synergistic Effects of Matrix Biophysical Properties on Gastric Cancer Cell Behavior via Integrin-Mediated Cell-ECM Interactions.

The biophysical properties of the extracellular matrix (ECM) play a pivotal role in modulating cancer progression via cell-ECM interactions. However, the biophysical properties specific to gastric cancer (GC) remain largely unexplored. Pertinently, GC ECM shows significantly heterogeneous metamorphoses, such as matrix stiffening and intricate restructuring. By combining collagen I and alginate, this study designs an in vitro biomimetic hydrogel platform to independently modulate matrix stiffness and structure across a physiological stiffness spectrum while preserving consistent collagen concentration and fiber topography. With this platform, this study assesses the impacts of matrix biophysical properties on cell proliferation, migration, invasion, and other pivotal dynamics of AGS. The findings spotlight a compelling interplay between matrix stiffness and structure, influencing both cellular responses and ECM remodeling. Furthermore, this investigation into the integrin/actin-collagen interplay reinforces the central role of integrins in mediating cell-ECM interactions, reciprocally sculpting cell conduct, and ECM adaptation. Collectively, this study reveals a previously unidentified role of ECM biophysical properties in GC malignant potential and provides insight into the bidirectional mechanical cell-ECM interactions, which may facilitate the development of novel therapeutic horizons.

Prediction of erosion defects and buckling pressure of pipe bend based on bidirectional fluid-structure interaction method

In this study, a bidirectional fluid-structure interaction (FSI) method was proposed based on dynamic mesh technology to calculate the erosion defects of pipe bends under high pressure. In calculating the erosion rate of pipe bends, a stress erosion model was adopted, and the displacement and stress of the inner wall of pipe bend under high external pressure were considered. The influence of different parameters on the calculation results of erosion depth was discussed, and the buckling pressure and collapse mode of pipe bend under the erosion defect of liquid-solid flow were also studied. The proposed method can be used for predicting pipeline erosion defects under high pressure and evaluating the remaining limit load of pipelines with such erosion defects.

Gut-liver Axis: Recent concepts in pathophysiology in alcohol-associated liver disease.

The growing recognition of the role of the gut microbiome's impact on alcohol-related diseases, especially in alcohol-associated liver disease, emphasizes the need to understand molecular mechanisms involved in governing organ-organ communication to identify novel avenues to combat alcohol-related diseases. The gut-liver axis refers to the bidirectional communication and interaction between gut and liver. Intestinal microbiota play a pivotal role in maintaining homeostasis within the gut-liver axis and this axis plays a significant role in alcohol-associated liver disease. The intricate communication between intestine and liver involves communication between multiple cellular components in each organ that enable them to carry out their physiological functions. In this review, we focus on novel approaches to understanding how chronic alcohol exposure impacts the microbiome, and individual cells within the liver and intestine, as well as the impact of ethanol on the molecular machinery required for intra- and inter-organ communication.

Impact of the gut microbiome composition on social decision-making.

There is increasing evidence for the role of the gut microbiome in the regulation of socio-affective behavior in animals and clinical conditions. However, whether and how the composition of the gut microbiome may influence social decision-making in health remains unknown. Here, we tested the causal effects of a 7-week synbiotic (vs. placebo) dietary intervention on altruistic social punishment behavior in an ultimatum game. Results showed that the intervention increased participants' willingness to forgo a monetary payoff when treated unfairly. This change in social decision-making was related to changes in fasting-state serum levels of the dopamine-precursor tyrosine proposing a potential mechanistic link along the gut-microbiota-brain-behavior axis. These results improve our understanding of the bidirectional role body-brain interactions play in social decision-making and why humans at times act "irrationally" according to standard economic theory.

Electric vehicle-based distant energy sharing between zero-emission coastal office and hotel buildings

With the rapid growth of distributed renewable energy systems, energy sharing brings a practical solution to mitigate mismatching between intermittent electricity generation and building demand. In past research, energy sharing was designed mostly for onshore energy integrated systems and is commonly realised with the assistance of microgrids, distributed battery storage, or peer-to-peer energy trading. This research innovatively proposed a distant energy sharing between the ocean energy-supported coastal office building and hotel building by ten electric vehicles, enabling the circulation of ocean renewable energy between two buildings. This project aims to accomplish maximum technical, environmental and economic benefits for the stakeholder. Using bidirectional vehicle-building interaction, advanced control algorithms, including shifting vehicle batches, sizing renewable capacity, and involving stationary batteries, are implemented successively in the TRNSYS simulation as analysis groups to enhance the current system's performance. According to the results, the vehicle-based bidirectional energy sharing between these two buildings can attain a relative net present value of 49.18 million HKD and a weighted matching index of 0.63. After implementing advanced controls with stationary batteries, the system achieved a relative net present value of 62.15 million HKD with an improved matching index of 0.70. Both batteries contributed to increase the matching performance of the system, but the increase in battery capacity reduces the benefit due to their replacement cost. This research developed an energy management system for effectively utilising electric vehicles and coastal renewable energy for distant energy sharing. It elucidated the technological, environmental, and economic benefits to the stakeholders for effective decision-making.

Epidemiology of Disorders of the Gut-Brain Interaction: An Appraisal of the Rome IV Criteria and Beyond.

Disorders of the gut-brain interaction (DGBIs) are presently classified into mutually exclusive anatomical area-related symptom-based categories according to the Rome IV criteria. The pathophysiology of visceral nociception, which contributes to the wide range of symptoms of DGBIs, involves complex psychobiological processes arising from the bidirectional interactions of multiple systems at the gut and brain levels, which affect symptom expression and illness behaviors. The attitude toward an illness and expression of pain and bowel habit vary across cultures with variable interpretation based on sociocultural beliefs, which may not tally with the medical definitions. Thus, psychological factors impact DGBI definitions, their severity and health care utilization. Due to the poor localization and multisegment referral of visceral pain, the anatomical site of pain may not correspond to the affected segment, and there may be a variable degree of overlap among symptoms. The somewhat restrictively defined Rome IV criteria assume one-to-one correlation of symptoms with underlying pathophysiology and ignore overlapping DGBIs, nonstandardized symptom categories, and change or shift in category over time. The microorganic nature of DGBIs resulting from systemic, metabolic or motility disorders, gut dysbiosis and inflammation are not addressed in the Rome IV criteria. Although there is a multidimensional clinical profile that does address these factors, it is not followed rigorously in practice. Threshold changes for diagnostic criteria or addition/deletion of symptoms leads to wide variation among different DGBI criteria resulting in uncertain comparability of results. Although the Rome IV criteria are excellent for research studies and therapeutic trials in homogenous populations, further improvement is needed for their wider applicability in clinical practice.

Bidirectional correlation-driven inter-frame interaction Transformer for referring video object segmentation

Referring video object segmentation (RVOS) aims to segment the target object in a video sequence described by a language expression. Typical multimodal Transformer based RVOS approaches process video sequence in a frame-independent manner to reduce the high computational cost, which however restricts the performance due to the lack of inter-frame interaction for temporal coherence modeling and spatio-temporal representation learning of the referred object. Besides, the absence of sufficient cross-modal interactions results in weak correlation between the visual and linguistic features, which increases the difficulty of decoding the target information and limits the performance of the model. In this paper, we propose a bidirectional correlation-driven inter-frame interaction Transformer, dubbed BIFIT, to address these issues in RVOS. Specifically, we design a lightweight and plug-and-play inter-frame interaction module in the Transformer decoder to efficiently learn the spatio-temporal features of the referred object, so as to decode the object information in the video sequence more precisely and generate more accurate segmentation results. Moreover, a bidirectional multi-level vision-language interaction module is implemented before the multimodal Transformer to enhance the correlation between the linguistic and multi-level visual features, thus facilitating the language queries to decode more precise object information from visual features and ultimately improving the segmentation performance. Extensive experimental results on four benchmarks validate the superiority of our BIFIT over state-of-the-art methods and the effectiveness of our proposed modules. The code is available in https://github.com/LANMNG/BIFIT.

Exploring the Causal Role of Immune Cells in Cerebral Aneurysm Through Single-Cell Transcriptomics and Mendelian Randomization Analysis.

Cerebral aneurysm (CA) represent a significant clinical challenge, characterized by pathological dilation of cerebral arteries. Recent evidence underscores the crucial involvement of immune cells in CA pathogenesis. This study aims to explore the complex interplay between immune cells and CA formation. We analyzed single-cell RNA sequencing data from the GSE193533 dataset, focusing on unruptured CA and their controls. Comprehensive cell-type identification and pseudotime trajectory analyses were conducted to delineate the dynamic shifts in immune cell populations. Additionally, a two-sample Mendelian Randomization (MR) approach was employed to investigate the causal influence of various immunophenotypes on CA susceptibility and the reciprocal effect of CA formation on immune phenotypes. Single-cell transcriptomic analysis revealed a progressive loss of vascular smooth muscle cells (VSMCs) and an increase in monocytes/macrophages (Mo/MΦ) and other immune cells, signifying a shift from a structural to an inflammatory milieu in CA evolution. MR analysis identified some vital immunophenotypes, such as CD64 on CD14+ CD16+ monocytes (OR: 1.236, 95% CI: 1.064 to 1.435, p=0.006), as potential risk factors for CA development, while others, like CD28- CD8br %CD8br (OR: 0.883, 95% CI: 0.789 to 0.988, p=0.030), appeared protective. Reverse MR analysis demonstrated that CA formation could modulate specific immunophenotypic expressions, highlighting a complex bidirectional interaction between CA pathology and immune response. This study underscores the pivotal role of immune cells in this process through the integration of single-cell transcriptomics with MR analysis, offering a comprehensive perspective on CA pathogenesis, potentially guiding future therapeutic strategies targeting specific immune pathways.

A CCP-based distributed cooperative operation strategy for multi-agent energy systems integrated with wind, solar, and buildings

To explore the bidirectional interaction between renewable energy and buildings in multi-agent energy systems, this paper proposes a distributed cooperative operation strategy for multi-agent energy systems integrated with wind, solar, and buildings based on chance-constrained programming (CCP). First, the multi-agent energy system integrated with wind, solar, and buildings is comprehensively modeled with detailed electric and thermal characteristics for flexibility enhancement. Then for maximizing the profits of the cooperative energy system and each engaged agent, a Nash bargaining model is presented and is divided into two subproblems: the coalition income and the power payment. To preserve the privacy of agents, the adaptive alternating direction method of multipliers (ADMM) is exploited to solve both subproblems. Meanwhile, the CCP method is applied to address diverse uncertainties from wind and solar power generation as well as outdoor temperature. Finally, the effectiveness of the proposed strategy is validated. The simulation results show that, besides the privacy of information among all agents being well preserved, our strategy enhances the profits not only for the energy system but also for all engaged agents.

A Mouth and Tongue Interactive Device to Control Wearable Robotic Limbs in Tasks where Human Limbs Are Occupied

The Wearable Robotic Limb (WRL) is a type of robotic arm worn on the human body, aiming to enhance the wearer’s operational capabilities. However, proposing additional methods to control and perceive the WRL when human limbs are heavily occupied with primary tasks presents a challenge. Existing interactive methods, such as voice, gaze, and electromyography (EMG), have limitations in control precision and convenience. To address this, we have developed an interactive device that utilizes the mouth and tongue. This device is lightweight and compact, allowing wearers to achieve continuous motion and contact force control of the WRL. By using a tongue controller and mouth gas pressure sensor, wearers can control the WRL while also receiving sensitive contact feedback through changes in mouth pressure. To facilitate bidirectional interaction between the wearer and the WRL, we have devised an algorithm that divides WRL control into motion and force-position hybrid modes. In order to evaluate the performance of the device, we conducted an experiment with ten participants tasked with completing a pin-hole assembly task with the assistance of the WRL system. The results show that the device enables continuous control of the position and contact force of the WRL, with users perceiving feedback through mouth airflow resistance. However, the experiment also revealed some shortcomings of the device, including user fatigue and its impact on breathing. After experimental investigation, it was observed that fatigue levels can decrease with training. Experimental studies have revealed that fatigue levels can decrease with training. Furthermore, the limitations of the device have shown potential for improvement through structural enhancements. Overall, our mouth and tongue interactive device shows promising potential in controlling the WRL during tasks where human limbs are occupied.

Strategi Alih Tutur pada Gelar Wicara Mata Najwa Episode “Beres-Beres Kursi Menteri Kesehatan”: Kajian Analisis Percakapan

This research investigates the dynamics of turn-taking within a talk show context, specifically focusing on the "Beres-Beres Kursi Menkes" episode of Indonesia's Mata Najwa. Utilizing a qualitative content analysis methodology involving recording and note-taking, the study examines turn-taking behaviors based on Stenström's (1994) theoretical framework. The analysis reveals three primary strategies: Taking the Floor, Holding the Floor, and Yielding the Floor. The conversation unfolds through bidirectional interactions, characterized by initial greetings, instances of overlapping speech, intermittent interruptions, and a concluding prompt. The study underscores the significance of mastering the Taking the Floor strategy, which involves seizing speaking opportunities, initiating or responding to turns, and rectifying errors. Proficiency in this aspect facilitates meaningful dialogues and ensures a coherent exchange of ideas within the context of talk shows.

Berberine alleviates Alzheimer's disease by regulating the gut microenvironment, restoring the gut barrier and brain-gut axis balance

BackgroundAlzheimer's disease (AD) is the most common neurodegenerative disease. Intestinal flora and its metabolism play a significant role in ameliorating central nervous system disorders, including AD, through bidirectional interactions between the gut-brain axis. A naturally occurring alkaloid compound called berberine (BBR) has neuroprotective properties and prevents Aβ-induced microglial activation. Additionally, BBR can suppress the synthesis of Aβ and decrease BACE1 expression. However, it is still unclear if BBR therapy can alleviate AD by changing the gut flora. PurposeIn this study, we examined whether a partial alleviation of AD could be achieved with BBR treatment and the molecular mechanisms involved. MethodsWe did this by analyzing alterations in Aβ plaques, neurons, and related neuroinflammation-related markers in the brain and the transcriptome of the mouse brain. The relationship between the intestinal flora of 5xFAD model mice and BBR treatment was investigated using high-throughput sequencing analysis of 16S rRNA from mouse feces. ResultsThe findings demonstrated that treatment with BBR cleared Aβ plaques, alleviated neuroinflammation, and ameliorated spatial memory dysfunction in AD. BBR significantly alleviated intestinal inflammation, decreased intestinal permeability, and could improve intestinal microbiota composition in 5xFAD mice.

Multi-resolution sequence and structure feature extraction for binding site prediction

Circular ribonucleic acids (circRNAs) are single-stranded RNA molecules that form loops and are widely expressed in various cells and tissues. They interact with RNA-binding proteins (RBPs) and play a vital regulatory role in the onset and development of several diseases. Researchers have proposed various hybrid architecture prediction methods based on convolutional neural networks and recurrent neural networks to recognize the interactions and sites between circRNAs and RBPs and thus reveal the biological functions of circRNAs. However, existing methods usually ignore the structural information of circRNA, which may affect the modeling of circRNA and RBP binding modes. To address these problems, we propose a prediction model based on multi-resolution feature extraction. First, it generates sequence features using unsupervised word embedding and nucleotide density. Then, it uses implicit and explicit pseudo-secondary structure hybrid encoding to fuse sequence and structural information and better simulate circRNA-RBP binding patterns. Second, it uses an enhanced bidirectional sample convolution and interaction network encoder to capture and integrate high-order features of distinct resolutions from the multi-scale convolution module. This provides rich semantic input to the downstream bidirectional long short-term memory network to improve prediction accuracy. Experimental results on 37 circRNA and 31 linear RNA datasets show that our method has significant advantages in identifying RNA-RBP interactions. Furthermore, the four motifs learned by our method are verified against existing motif databases, indicating that it can discover biologically meaningful circRNA-RBP binding patterns.

Estimating structural response to bidirectional seismic excitation using spectrum compatible motions: Performance of a pair of companion spectra

AbstractBidirectional analyses covering a range of incidence angles for several records are essential yet challenging for routine design. Recent studies have shown that the response to bidirectional shaking may be estimated per straightforward unidirectional analysis in the most preferred orientation in conjunction with the orthogonal combination rules, and this can also remove the need for various incidence angles. Further, it is well known that the mean response can be estimated with reduced dispersion using fewer spectrum‐compatible records. Combining the advantages of both, a pair of companion spectra independent of period and orientation has recently been developed. While the basis of the companion spectra is established therein from a sound mathematical perspective, the applicability of the proposed spectra to real structures may be revisited, especially to structures sensitive to bidirectional interaction, before recommending the companion spectra for practical design. To achieve this end, following a brief scrutiny of the companion spectra, the performance of the same is critically examined for idealized SDoF analogues and real structures such as bridge piers representative of SDoF systems and buildings with asymmetry using single storey and multistorey models (MDoF systems). The results show that the response of the real structures to bidirectional seismic loading can be reasonably estimated with reduced dispersion using fewer records compatible with the pair of the companion spectra. As such, the critical response parameters may be computed by actual bidirectional analyses or by combining responses to unidirectional analyses under fewer spectrum compatible records. Hence, the pair of companion spectra that can be used as “target” to independently match two components of a chosen record is useful for practical design.

The virtual drum circle: polyrhythmic music interactions in mixed reality

Emerging technologies in the domain of mixed reality offer rich, new possibilities for the study and practice of joint music performance. Apart from the technological challenges, bringing music players together in mixed reality raises important questions on their performance and embodied coordination. In this study, we designed a mixed reality platform to assess a remote, bidirectional polyrhythmic interaction between two players, mediated in real time by their three-dimensional embodied avatars and a shared, virtual ‘drum circle’. We leveraged a multi-layered analysis framework to assess their performance quality, embodied coregulation and first-person interaction experience, using statistical techniques for timeseries analysis and mixed-effect regression and focusing on contrasts of visual coupling (not seeing / seeing as avatars / seeing as real) and auditory context (metronome / music). Results reveal that an auditory context with music improved the performance output as measured by a prediction error, increased movement energy and levels of experienced agency. Visual coupling impacted experiential qualities and induced prosocial effects with increased levels of partner realism resulting in increased levels of shared agency and self-other merging. Embodied coregulation between players was impacted by auditory context and visual coupling, suggesting prediction-based compensatory mechanisms to deal with the novelty, difficulty, and expressivity in the musical interaction. This study contributes to the understanding of music performance in mixed reality by using a methodological approach to demonstrate how coregulation between players is impacted by visual coupling and auditory context and provides a basis and future directions for further action-oriented research.

Association of adipokine levels with obesity in periodontal health and disease: A systematic review with meta-analysis and meta-regression.

This study aimed to investigate the levels of serum, gingival crevicular fluid (GCF), and salivary adipokines and their possible relationship with periodontitis and obesity. An electronic search was conducted in the following databases: PubMed/ Medline, Scopus, and EBSCOhost through February 2023. Two independent reviewers screened the titles, abstracts, and full text of all the studies. Studies comparing the levels of adipokines in GCF, serum, and/or saliva in subjects with obesity and periodontitis (group 1), subjects with normal weight and periodontitis (group 2), and subjects with obesity and gingival health (group 3) were included. Meta-analyses and meta-regression were performed on the data from included studies. Seventeen studies with study participants ranging from 30 to 120 were included with subjects in each group ranging from 10 to 40. There was a significant increase in levels of serum TNF-α, leptin, IL-6, and CRP between groups 1 and 2 (p < .05). In GCF, TNF-α and resistin levels were significantly higher (p < .05) in Group 1 vs. 2. Serum level of leptin was higher for group 1 vs. 3 (p < .05). Meta-regression analysis revealed that the obesity definition (body mass index (BMI) cut-off value >25 or >30) was significant for serum resistin (p < .05) and GCF resistin (p < .05) between group 1 and 2. The current analysis indicates that both periodontitis and obesity can modulate the pro-inflammatory cytokines at systemic and local levels. This bidirectional interaction of periodontitis and obesity via the inflammation pathway seems likely plausible. Further studies are required to elucidate this mechanism in more detail.