Signaling Complex Research Articles

MSEI-ENet: A Multi-scale EEG-Inception Integrated Encoder Network for Motor Imagery EEG Decoding

Background: Due to complex signal characteristics and distinct individual differences, the decoding of a motor imagery electroencephalogram (MI-EEG) is limited by the unsatisfactory performance of suboptimal traditional models. Methods: A subject-independent model named MSEI-ENet is proposed for multiple-task MI-EEG decoding. It employs a specially designed multi-scale structure EEG-inception module (MSEI) for comprehensive feature learning. The encoder module further helps to detect discriminative information by its multi-head self-attention layer with a larger receptive field, which enhances feature representation and improves recognition efficacy. Results: The experimental results on Competition IV dataset 2a showed that our proposed model yielded an overall accuracy of 94.30%, MF1 score of 94.31%, and Kappa of 0.92. Conclusions: A performance comparison with state-of-the-art methods demonstrated the effectiveness and generalizability of the proposed model on challenging multi-task MI-EEG decoding.

YAP/TAZ-associated cell signaling – at the crossroads of cancer and neurodevelopmental disorders

YAP/TAZ (Yes-associated protein/paralog transcriptional co-activator with PDZ-binding domain) are transcriptional cofactors that are the key and major downstream effectors of the Hippo signaling pathway. Both are known to play a crucial role in defining cellular outcomes, including cell differentiation, cell proliferation, and apoptosis. Aside from the canonical Hippo signaling cascade with the key components MST1/2 (mammalian STE20-like kinase 1/2), SAV1 (Salvador homologue 1), MOB1A/B (Mps one binder kinase activator 1A/B) and LATS1/2 (large tumor suppressor kinase 1/2) upstream of YAP/TAZ, YAP/TAZ activation is also influenced by numerous other signaling pathways. Such non-canonical regulation of YAP/TAZ includes well-known growth factor signaling pathways such as the epidermal growth factor receptor (EGFR)/ErbB family, Notch, and Wnt signaling as well as cell-cell adhesion, cell-matrix interactions and mechanical cues from a cell’s microenvironment. This puts YAP/TAZ at the center of a complex signaling network capable of regulating developmental processes and tissue regeneration. On the other hand, dysregulation of YAP/TAZ signaling has been implicated in numerous diseases including various cancers and neurodevelopmental disorders. Indeed, in recent years, parallels between cancer development and neurodevelopmental disorders have become apparent with YAP/TAZ signaling being one of these pathways. This review discusses the role of YAP/TAZ in brain development, cancer and neurodevelopmental disorders with a special focus on the interconnection in the role of YAP/TAZ in these different conditions.

Comparative Analysis of Machine Learning Algorithms Used for Translating Aptamer-Antigen Binding Kinetic Profiles to Diagnostic Decisions.

Current approaches for classifying biosensor data in diagnostics rely on fixed decision thresholds based on receiver operating characteristic (ROC) curves, which can be limited in accuracy for complex and variable signals. To address these limitations, we developed a framework that facilitates the application of machine learning (ML) to diagnostic data for the binary classification of clinical samples, when using real-time electrochemical measurements. The framework was applied to a real-time multimeric aptamer assay (RT-MAp) that captures single-frequency (12.6 Hz) impedance data during the binding of viral protein targets to trimeric aptamers. The impedance data collected from 172 COVID-19 saliva samples were processed through multiple nonlinear regression models to extract nine key features from the transient signals. These features were then used to train three supervised ML algorithms─support vector machine (SVM), artificial neural network (ANN), and random forest (RF)─using a 75:25 training-testing ratio. Traditional ROC-based classification achieved an accuracy of 83.6%, while ML-based models significantly improved performance, with SVM, ANN, and RF achieving accuracies of 86.0%, 100%, and 100%, respectively. The ANN model demonstrated superior performance in handling complex and high-variance biosensor data, providing a robust and scalable solution for improving diagnostic accuracy in point-of-care settings.

Novel mapping techniques for ablation of non-pulmonary vein foci using complex signal identification.

The complex signal identification function of CARTO version 8 enables quantitative evaluation of local potential fractionation. We present a case where this advanced technology successfully identified non-pulmonary vein foci associated with fractionated potentials during sinus rhythm.

The role of canopy family proteins: biological mechanism and disease function.

Canopy family proteins are highly sequence-conserved proteins with an N-terminal hydrophobic signal sequence, a unique pattern of six cysteine residues characteristic of the saposin-like proteins, and a C-terminal putative endoplasmic reticulum retention signal sequence. At present, the known canopy family proteins are canopy fibroblast growth factor signaling regulator 1 (CNPY1), CNPY2, CNPY3, and CNPY4. Despite similar structures, canopy family proteins regulate complex signal networks to participate in various biological processes. They are involved in a wide range of diseases, including angiogenesis, abnormal immune responses, neurodevelopmental disorders, and the development of tumors. Here, we summarized the biological processes and influence on the disease of every CNPY family protein to elucidate potential biomarkers and point out the direction for future in-depth research.

Ouabain Counteracts Retinal Ganglion Cell Death Through Modulation of BDNF and IL-1 Signaling Pathways

Background: Ouabain is a steroid hormone that binds to the sodium pump (Na+, K+-ATPase) at physiological (nanomolar) concentrations, activating different signaling pathways. This interaction has been shown to prevent the axotomy-induced death of retinal ganglion cells (RGCs), although the underlying mechanisms remain unclear. Objective: In this study, we investigated potential mechanisms by which ouabain promotes RGC survival using primary cultures of rat neural retina. Results: Our findings indicate that ouabain regulates brain-derived neurotrophic factor (BDNF) signaling in retinal cells via matrix metalloproteinase-9-mediated processing of proBDNF to mature BDNF (mBDNF) and by increasing the phosphorylation of the mBDNF receptor, tropomyosin-related receptor kinase B. Ouabain also enhances the maturation of interleukin (IL)-1β through the increased activation of caspase-1, which mediates the processing of proIL-1β into IL-1β, and transiently upregulates both IL-1 receptor and IL-1 receptor antagonist (IL-1Ra). Treatment using either IL-1β or IL-1Ra alone is sufficient to enhance RGC survival similarly to that achieved with ouabain. Finally, we further show that ouabain prevents RGC death through a complex signaling mechanism shared by BDNF and IL-1β, which includes the activation of the Src and protein kinase C pathways. Conclusions: Collectively, these results suggest that ouabain stimulates the maturation and signaling of both BDNF and IL-1β, which act as key mediators of RGC survival.

Potential roles of mitochondrial carrier proteins in plant responses to abiotic stress.

The transport of metabolites across the inner mitochondrial membrane (IMM) is crucial for maintaining energy balance and efficient distribution of metabolic intermediates between cellular compartments. Under abiotic stress, mitochondrial function becomes particularly critical, activating complex signaling pathways essential for plant stress responses. These pathways modulate stress-responsive gene expression, influencing key physiological processes such as cell respiration and senescence, helping plants adapt to stress. Recent studies have emphasized the importance of finely tuned regulation of mitochondrial metabolite transport through the IMM, particularly under stress conditions, to optimize plant survival and resilience. This review summarizes the current knowledge on the possible roles of mitochondrial transport proteins and their contributions to plant adaptation under abiotic stress.

ANALYSIS OF THE CORRELATION BETWEEN BRAIN AND MUSCLE REACTION IN REST AND LIMB MOVEMENTS

The study of correlations between different organs under various conditions is a prominent field in biomedical science and engineering. This paper explores the relationship between brain and muscle activities during rest and various limb movements including plantar flexion and knee flexion. We employed complexity measures, calculating the fractal dimension (FD) and sample entropy (SampEn) of electroencephalogram (EEG) and electromyogram (EMG) signals, which serve as indicators of brain and muscle activities, respectively. Our analysis focused on how the complexity variations in these signals correlate across different tasks. The results revealed opposite trends in the complexity of EEG and EMG signals. Specifically, the complexity of EEG signals increased from initial rest to final rest, plantar flexion, and knee flexion, suggesting heightened neural activity likely due to motor planning and execution. Conversely, the complexity of EMG signals decreased, indicating more synchronized and consistent muscle contractions during these movements, reflecting coordinated motor control and reduced variability in muscular activity. This analytical approach can be applied to study the correlations between different organs’ reactions and brain activity across various tasks.

Dietary dopamine supplementation has no effect on ovary activity in queen-less or queen-right honeybee (Apis mellifera) workers

Eusociality in honeybees (Apis mellifera) is characterised by a reproductive division of labour, where the queen monopolises reproduction while worker reproduction is constrained. This constraint is mediated by queen mandibular pheromone (QMP), which inhibits worker ovary development through Notch signalling and possibly oocyte apoptosis. Dopamine has been implicated in regulating reproduction in worker honeybees, with prior studies suggesting that dietary dopamine enhances ovary activity in queen-less workers. This study aimed to test whether dopamine supplementation could overcome QMP-mediated reproductive constraint in worker honeybees. Using caged honeybee experiments, we administered dopamine and its precursor L-dopa at a range of concentrations, both in the presence and absence of QMP. Results showed that neither dopamine nor L-dopa supplementation affected ovary development, survival rates, or food intake, which contrasts with a previous study. These findings suggest that dopamine may not be a major factor in QMP-mediated reproductive inhibition. Instead, we suggest that the multifaceted nature of QMP’s components together with the complexity of neuroendocrine signalling makes it likely that multiple redundant mechanisms regulate worker reproduction. Future research should investigate the interplay between nutrition, dopamine and QMP components to fully understand the regulation of ovary activation in honeybee workers.

Computational design of highly signalling-active membrane receptors through solvent-mediated allosteric networks.

Protein catalysis and allostery require the atomic-level orchestration and motion of residues and ligand, solvent and protein effector molecules. However, the ability to design protein activity through precise protein-solvent cooperative interactions has not yet been demonstrated. Here we report the design of 14 membrane receptors that catalyse G protein nucleotide exchange through diverse engineered allosteric pathways mediated by cooperative networks of intraprotein, protein-ligand and -solvent molecule interactions. Consistent with predictions, the designed protein activities correlated well with the level of plasticity of the networks at flexible transmembrane helical interfaces. Several designs displayed considerably enhanced thermostability and activity compared with related natural receptors. The most stable and active variant crystallized in an unforeseen signalling-active conformation, in excellent agreement with the design models. The allosteric network topologies of the best designs bear limited similarity to those of natural receptors and reveal an allosteric interaction space larger than previously inferred from natural proteins. The approach should prove useful for engineering proteins with novel complex protein binding, catalytic and signalling activities.

Frequency-Modulated Antipodal Chaos Shift Keying Chaotic Communication on Field Program Gate Array: Prototype Design and Performance Insights

Using chaos for communication can provide more robust channel security, covert transmission, and inherent support for spread-spectrum modulation. Although numerous studies have explored this technology, its practical deployment remains limited due to substantial hardware demands, complex signal processing, and a lack of efficient modulation methods for chaotic signals. In this study, a novel chaotic digital communication system is proposed and studied. A prototype of a frequency-modulated antipodal chaos shift keying (FM-ACSK) system is implemented on an Intel Cyclone V field-programmable gate array (FPGA) along with a complete mathematical model using Matlab R2022a Simulink software. Using FPGAs to implement chaotic oscillators avoids analog system problems such as component drift and high thermal instability while providing determined system parameters, rapid prototyping, and high throughput. The employment of FM over a chaotic modulation layer provides a passband operation (currently at an intermediate frequency of 10.7 MHz) while adding the benefits of carrier frequency offset robustness and constant signal envelope. Within this study, the robustness of FM-ACSK to white noise in the channel was evaluated using bit error rate, which was tested through hardware experiments and simulations. The results show the feasibility and potential performance limitations of this approach to chaotic communication system design.

Deep learning-based image classification reveals heterogeneous execution of cell death fates during viral infection.

Cell fate decisions, such as proliferation, differentiation, and death, are driven by complex molecular interactions and signaling cascades. While significant progress has been made in understanding the molecular determinants of these processes, historically, cell fate transitions were identified through light microscopy that focused on changes in cell morphology and function. Modern techniques have shifted towards probing molecular effectors to quantify these transitions, offering more precise quantification and mechanistic understanding. However, challenges remain in cases where the molecular signals are ambiguous, complicating the assignment of cell fate. During viral infection, programmed cell death (PCD) pathways, including apoptosis, necroptosis, and pyroptosis, exhibit complex signaling and molecular crosstalk. This can lead to simultaneous activation of multiple PCD pathways, which confounds assignment of cell fate based on molecular information alone. To address this challenge, we employed deep learning-based image classification of dying cells to analyze PCD in single Herpes Simplex Virus-1 (HSV-1)-infected cells. Our approach reveals that despite heterogeneous activation of signaling, individual cells adopt predominantly prototypical death morphologies. Nevertheless, PCD is executed heterogeneously within a uniform population of virus-infected cells and varies over time. These findings demonstrate that image-based phenotyping can provide valuable insights into cell fate decisions, complementing molecular assays. [Media: see text] [Media: see text] [Media: see text] [Media: see text].

Multimodal approach to public health interventions using EGG and mobile health technologies.

Public health interventions increasingly integrate multimodal data sources, such as Electroencephalogram (EEG) data, to enhance monitoring and predictive capabilities for mental health conditions. However, traditional models often face challenges with the complexity and high dimensionality of EEG signals. While recent advancements like Contrastive Language-lmage Pre-training(CLIP) models excel in cross-modal understanding, their application to EEG-based tasks remains limited due to the unique characteristics of EEG data. In response, we introduce PH-CLIP (Public Health Contrastive Language-lmage Pretraining), a novel framework that combines CLIP's representational power with a multi-scale fusion mechanism designed specifically for EEG data within mobile health technologies. PH-CLIP employs hierarchical feature extraction to capture the temporal dynamics of EEG signals, aligning them with contextually relevant textual descriptions for improved public health insights. Through a multi-scale fusion layer, PH-CLIP enhances interpretability and robustness in EEG embeddings, thereby supporting more accurate and scalable interventions across diverse public health applications. Experimental results indicate that PH-CLIP achieves significant improvements in EEG classification accuracy and mental health prediction efficiency compared to leading EEG analysis models. This framework positions PH-CLIP as a transformative tool in public health monitoring, with the potential to advance large-scale mental health interventions through integrative mobile health technologies.

Apoptosis antagonizing transcription factor expression and its validation as a potential diagnostic and prognostic biomarker in oral squamous cell carcinoma.

Oral squamous cell carcinoma (OSCC) is characterized by a high degree of malignancy and poor prognosis. This study aimed to investigate the expression of apoptosis antagonizing transcription factor (AATF) in OSCC, examine its correlation with clinicopathological features, assess its prognostic implications, and explore its potential role in OSCC progression. Expression profiles and clinical data of OSCC patients were obtained from The Cancer Genome Atlas (TCGA). Immunohistochemical analysis on tissue microarrays was performed to assess AATF expression in OSCC. Functional enrichment analyses were conducted to identify potential signaling pathways and biological functions associated with AATF. Logistic regression analyses were employed to evaluate the relationship between AATF expression and clinicopathological features. Immune cell infiltration was assessed using single-sample gene set enrichment analysis (ssGSEA). The prognostic value of AATF was determined using Kaplan-Meier and Cox regression analyses. A nomogram was developed to predict overall survival (OS) rates at one, three-, and five years post-cancer diagnosis. Validation of AATF expression was performed using quantitative real-time PCR (qRT-PCR). AATF was significantly overexpressed in OSCC, and high AATF expression correlated with adverse clinicopathological features, including histologic grade and lymph node metastasis. Functional enrichment analysis revealed several enriched pathways, including epidermis development, immunoglobulin complex, antigen binding and IL-17 signaling pathway. Notably, AATF overexpression was negatively correlated with the infiltration levels of mast cells, interdigitating dendritic cells and Th 17 cells. High AATF expression significantly predicted poorer overall survival (OS) and disease-specific survival (DSS). Multivariate Cox analysis confirmed AATF as an independent negative prognostic marker of OS. Validation via qRT-PCR confirmed the overexpression of AATF in OSCC tissues. Elevated expression of AATF in OSCC correlates with adverse clinicopathological features and negatively impacts immune cell infiltration. High AATF levels serve as an independent marker of poor OS and DSS. These findings support AATF as a valuable prognostic biomarker and a potential therapeutic target in OSCC, warranting further investigation.

TRAF2 and RIPK1 redundantly mediate classical NFκB signaling by TNFR1 and CD95-type death receptors

This study suggests a modified model of TNFR1-induced complex I-mediated NFκB signaling. Evaluation of a panel of five tumor cell lines (HCT116-PIK3CAmut, SK-MEL-23, HeLa-RIPK3, HT29, D10) with TRAF2 knockout revealed in two cell lines (HT29, HeLa-RIPK3) a sensitizing effect for death receptor-induced necroptosis and in one cell line (D10) a mild sensitization for TNFR1-induced apoptosis. TRAF2 deficiency inhibited death receptor-induced classical NFκB-mediated production of IL-8 only in a subset of cell lines and only partly. TRAF5, furthermore, failed to improve DR-induced NFκB signaling in HCT116-PIK3CAmut and HCT116-PIK3CAmut-TRAF2KO cells. These findings argue for a non-obligatory role of TRAF2 in death receptor-induced classical NFκB signaling. Similar as in TRAF2-deficient cells, TNF- and CD95L-induced NFκB signaling was found to be only poorly affected in RIPK1KO cells and in cells treated with the RIPK1-specific PROTAC LD4172. Intriguingly, however, death receptor-induced NFκB signaling was completely inhibited in HCT116-PIK3CAmut cells double deficient for TRAF2 and RIPK1 and in TRAF2-deficient cells treated with LD4172. Moreover, with exception of recruitment of TRADD, acting upstream to TRAF2 and parallel to RIPK1, TNFR1 signaling complex formation was abrogated in TRAF2-RIPK1 DKO cells. Based on our findings, two distinguishable types of TNFR1-interacting complexes promote TNF-induced NFκB signaling: First, a TRADD-TRAF2/cIAP utilizing complex Ia which becomes evident in RIPK1-deficient cells. Second, a non-modified RIPK1 utilizing complex Ib which acts in TRADD- or TRAF2-deficient cells. Complex Ia and Ib may furthermore interact and cooperate to ubiquitinate RIPK1 resulting in a modified complex Ia/b preventing complex Ia and Ib to convert to the established TNFR1-induced cytotoxic complexes IIa and IIb.

On Oscillations in the External Electrical Potential of Sea Urchins.

Sea urchins display complex bioelectric activity patterns, even with their decentralized nervous system. Electrophysiological recordings showed distinct spiking patterns. The baseline potential was about 8.80 mV. It had transient spikes with amplitudes up to 21.05 mV. We observed many types of depolarization events. They included burst-like activity and prolonged state fluctuations lasting several seconds. Frequency domain analysis showed a power-law behavior. It had a scaling exponent of 6.21 ± 0.06, indicating critical dynamics. The analysis showed potential variations between 3.69 and 21.05 mV. The oscillation periods ranged from 4 to 3102 s. The varied timing of bioelectric signals suggests that these organisms can process information. This challenges traditional views of neural computation in simpler animals. These findings provide quantitative insights into the complex signaling mechanisms of the sea urchin's distributed nervous system.

Design Principles From Natural Olfaction for Electronic Noses.

Natural olfactory systems possess remarkable sensitivity and precision beyond what is currently achievable by engineered gas sensors. Unlike their artificial counterparts, noses are capable of distinguishing scents associated with mixtures of volatile molecules in complex, typically fluctuating environments and can adapt to changes. This perspective examines the multifaceted biological principles that provide olfactory systems their discriminatory prowess, and how these ideas can be ported to the design of electronic noses for substantial improvements in performance across metrics such as sensitivity and ability to speciate chemical mixtures. The topics examined herein include the fluid dynamics of odorants in natural channels; specificity and kinetics of odorant interactions with olfactory receptors and mucus linings; complex signal processing that spatiotemporally encodes physicochemical properties of odorants; active sampling techniques, like biological sniffing and nose repositioning; biological priming; and molecular chaperoning. Each of these components of natural olfactory systems are systmatically investigated, as to how they have been or can be applied to electronic noses. While not all artificial sensors can employ these strategies simultaneously, integrating a subset of bioinspired principles can address issues like sensitivity, drift, and poor selectivity, offering advancements in many sectors such as environmental monitoring, industrial safety, and disease diagnostics.

Recent advances in the role of gasotransmitters in necroptosis.

Necroptosis is a finely regulated programmed cell death process involving complex molecular mechanisms and signal transduction networks. Among them, receptor-interacting protein kinase 1 (RIPK1), receptor-interacting protein kinase 3 (RIPK3) and mixed lineage kinase domain-like protein are the key molecules regulating this process. In recent years, gasotransmitters such as nitric oxide, carbon monoxide and hydrogen sulfide have been suggested to play a regulatory role in necroptosis. This paper reviews the evidence that these gasotransmitters are involved in the regulation of necroptosis by influencing the production of reactive oxygen species, regulating the modification of S subunits of RIPK1 and RIPK3, regulating inflammatory mediators, and signal transduction. In addition, this review explores the potential therapeutic applications of these gasotransmitters in pathological conditions such as cardiovascular disease and ischemia-reperfusion injury. Although some studies have revealed the important role of gasotransmitters in necroptosis, the specific mechanism of action is still not fully understood. Future research is needed to further elucidate the molecular mechanisms of gasotransmitters in precisely regulating necroptosis, which will help develop new therapeutic strategies to prevent and treat related diseases.

Arabidopsis thaliana DNA Damage Response Mutants Challenged with Genotoxic Agents-A Different Experimental Approach to Investigate the TDP1α and TDP1β Genes.

Background/Objectives: DNA damage response (DDR) is a highly conserved and complex signal transduction network required for preserving genome integrity. DNA repair pathways downstream of DDR include the tyrosyl-DNA phosphodiesterase1 (TDP1) enzyme that hydrolyses the phosphodiester bond between the tyrosine residue of topoisomerase I (TopI) and 3'-phosphate end of DNA. A small TDP1 subfamily, composed of TDP1α and TDP1β, is present in plants. The aim of this work was to investigate the role of the two TDP1 genes in the DDR context. Methods: A series of Arabidopsis thaliana DDR single and double mutants defective in the sog1, e2fb, pol2A, atm, and atr genes, treated with the genotoxic agents camptothecin (CPT, inhibitor of TopI) and NSC120686 (NSC, inhibitor of TDP1), were used. These compounds were specifically used due to their known impact on the TDP1 function. The effect of the treatments was assessed via phenotypic analyses that included germination percentage, speed, and seedling growth. Subsequently, the expression of the TDP1α and TDP1β genes was monitored through qRT-PCR. Results: Overall, the gathered data indicate that the atm mutant was highly sensitive to NSC120686, both phenotypically and concerning the TDP1α gene expression profiles. Alternatively, the upregulation of TDP1β in e2fb, pol2a, and atr supports its implication in the replication stress response. Conclusions: The current study demonstrates that genotoxic stress induced by CPT and NSC has a genotype-dependent effect reflected by a differential expression of TDP1 genes and early phenotypic development.

Wireless power transfer empowered by reconfigurable intelligent surfaces

ABSTRACT Reconfigurable Intelligent Surfaces (RIS) represent a significant advancement in hardware technology, enhancing both wireless energy and spectral efficiency within wireless communication systems. Comprising a programmable metasurface, RIS can adeptly manipulate the wavefronts of incident signals – encompassing parameters such as phase, amplitude, frequency, and polarisation – without necessitating complex signal processing techniques. The integration of RIS into wireless communication networks enables the strategic manipulation of radio waves, thereby mitigating the adverse effects associated with natural wireless propagation. This study examines a multi-user (MU) multiple-input multiple-output (MIMO) wireless power transfer (WPT) system augmented by multiple RISs, wherein the transmitter is equipped with a constant-envelope beamformer. The optimisation of the phase shifts of the RIS and the beamformer of the transmitter is conducted jointly to maximise the total power received by users. An alternating optimisation approach is proposed, utilising the semidefinite relaxation (SDR) method. Additionally, a problem is formulated to maximise the total received power while adhering to constraints on the minimum power received by users, thereby addressing issues of user fairness. To resolve this problem, an iterative algorithm based on the Alternating Direction Method of Multipliers (ADMM) is introduced. Analysis and simulation results indicate a significant enhancement in total received power when employing the proposed methodology compared to existing algorithms documented in the literature. Furthermore, in scenarios involving multiple users, a detailed analysis of the system’s transmission performance, facilitated by RIS, is conducted. The numerical results substantiate the validity of the analysis and demonstrate the efficacy of the proposed algorithms.