Complex Actions Research Articles

Complex Actions of FKBP12 on RyR1 Ion Channel Activity Consistent with Negative Co-Operativity in FKBP12 Binding to the RyR1 Tetramer

The association of the 12 KDa FK506 binding protein (FKBP12) with ryanodine receptor type 1 (RyR1) in skeletal muscle is thought to suppress RyR1 channel opening and contribute to healthy muscle function. The strongest evidence for this role is increased RyR1 channel activity following FKBP12 dissociation. However, the corollary that channel activity will decrease when FKBP12 is added back to FKBP12-depleted RyR1 is not well established, and when reported, the time- and concentration-dependence of inhibition vary over orders of magnitude. Here, we address this problem with an investigation of the molecular mechanisms of the FKBP12 regulation of RyR1. Muscle processing to obtain sarcoplasmic reticulum (SR) vesicle preparations enriched in RyR1 resulted in substantial FKBP12 dissociation from RyR1, indicating low-affinity binding. Conversely, high-affinity binding was indicated by some FKBP12 remaining bound to RyR1 after solubilization. We report, for the first time, an increase in the activity of FKBP12-depleted channels after the addition of exogenous FKBP12 (5 nM to 5 µM), followed by a reduction in activity consistent with inhibition after 20–30 min exposure to higher [FKBP12]s. Both the increase and later decline in activity were time- and concentration-dependent. The results suggest a high-affinity activation when FKBP12 binding sites on the RyR1 tetramer are partially occupied by FKBP12 and lower affinity inhibition as more RyR1 monomers become occupied. These novel results imply negative cooperativity in FKBP12 binding to RyR1 and a dynamic role for FKBP12/RyR1 interactions in intact muscle fibers.

Modulation of the mechanism of action of antibacterial silver N-heterocyclic carbene complexes by variation of the halide ligand.

The antimicrobial properties of silver and silver complexes have been known in medicine since ancient times. However, limitations in stability and solubility have impaired medicinal chemistry and drug development research. With the advent of N-heterocyclic carbenes (NHC) as ligands, the development of synthesis methods for organometallic silver species of the type (NHC)AgX (where X = halide) has brought significant improvements, and the class of antimicrobial silver NHC complexes has emerged. However, reports studying structure-activity relationships and the mechanism of action of this compound type are still rare. This paper explores the activity of silver NHC complexes with halide (chloride, iodide) ligands and attempts to elucidate their mechanism of antibacterial action in Gram-negative E. coli bacteria in comparison to non-organometallic silver nitrate. In particular, the complexes with an iodide ligand were confirmed to cause stronger antibacterial effects in E. coli than silver nitrate. Moreover, iodide complexes exhibit an enhanced cellular uptake, show signs of DNA condensation, strongly inhibit TrxR in E. coli and cause a strong depolarization of the membrane potential and permeability of the inner cell membrane. In contrast, chloride silver NHC complexes and silver nitrate caused permeability of the outer membranes and also showed a different activity pattern in most of the studied mechanisms. In conclusion, by variation of the halide ligand of silver NHC complexes the mechanism of action and strength of antibacterial activity can be fine-tuned.

SYNTHESIS, ANTIMICROBIAL AND ANTIFUNGAL ACTIVITY OF PLATINUM (II) AND PALLADIUM (II) COMPLEXES

The aim of the work is the synthesis of mono- and binuclear complexes of platinum (II) and palladium (II) containing terminal and bridging atoms of chlorine and sulfur as ligands and the study of their biological activity in relation to test cultures of Bacillus subtilis B4647, Aspergillus brasiliensis (niger) F679, Pseudomonas aeruginosa B8243, Escherichia coli. The composition and structure of the synthesized platinum (II) and palladium (II) complexes were established by methods of elemental analysis, X-ray photoelectron spectroscopy (XPS), IR spectroscopy, and X-ray diffraction (XRD) technique, which correspond to our results on the X-ray structural analysis of these complexes. Antimicrobial and antifungicidal properties were assessed by the ability of the synthesized complexes to suppress the vital activity of bacteria and fungi using the agar diffusion method and the in vitro dilution method. The results obtained showed high activity of the binuclear complex of palladium (II) (μ-S)[Pd2(SCH2CH2NH+ 3)2Cl4] and platinum (II) (μ-Cl)[Pt2(SCH2CH2NH2)2Cl2]∙3H2O of non-electrolyte type. Binuclear complexes of palladium and platinum, in contrast to mononuclear trans-[Pd(SCH2CH2NH2)2] and cis-[Pt(SCH2CH2NH2)2], exhibit higher antibacterial activity. The effectiveness of the antibacterial action of the non-electrolyte palladium complex against the bacteria Bacillus subtilis, Escherichia coli and fungi Aspergillus niger was more pronounced. The results of our study showed that by changing the structure of the complex, the composition and charge of the inner sphere, the number of coordination centers, the nature and dentacy of the ligands, it is possible to achieve a higher toxic effect of the complexes (μ-S [Pd2(SCH2CH2NH+ 3)2Cl4], μ-Cl [Pt2(SCH2CH2NH2)2Cl2]∙3H2O) in relation to bacteria and fungi.

Functional anatomy of zinc finger antiviral protein complexes.

ZAP is an antiviral protein that binds to and depletes viral RNA, which is often distinguished from vertebrate host RNA by its elevated CpG content. Two ZAP cofactors, TRIM25 and KHNYN, have activities that are poorly understood. Here, we show that functional interactions between ZAP, TRIM25 and KHNYN involve multiple domains of each protein, and that the ability of TRIM25 to multimerize via its RING domain augments ZAP activity and specificity. We show that KHNYN is an active nuclease that acts in apartly redundant manner with its homolog N4BP1. The ZAP N-terminal RNA binding domain constitutes a minimal core that is essential for antiviral complex activity, and we present a crystal structure of this domain that reveals contacts with the functionally required KHNYN C-terminal domain. These contacts are remote from the ZAP CpG binding site and would not interfere with RNA binding. Based on our dissection of ZAP, TRIM25 and KHNYN functional anatomy, we could design artificial chimeric antiviral proteins that reconstitute the antiviral function of the intact authentic proteins, but in the absence of protein domains that are otherwise required for activity. Together, these results suggest a model for the RNA recognition and action of ZAP-containing antiviral protein complexes.

AN EXPERIMENTAL MODEL FOR STUDYING THE RESPONSE OF CELLS TO THE EFFECTS OF PERIODONTAL GEL COMPOSITIONS AND BRACES POTENTIATED BY ELECTROPHORESIS

Aim: Іnvestigation of the effectiveness of penetration of a dental gel composition based on a flavonoid complex and benzydamine hydrochloride (patented periodontal gel composition Benzidaflaziverdin (GCB)) into the simulated environment of periodontal tissues consisting of three types of mammalian and human cells in semi-solid agar using an electrophoresis procedure. Research methods. The penetration of GCB and comparison drugs (Сholisal, Gengigel®) into the microenvironment of periodontal tissues was explored in vitro, consisting of three types of cells grown in semi-solid agar. These are murine BALB-3T3 fibroblasts, murine J774.2 macrophages, and pseudo-normal human HaCaT keratinocytes. Electrophoresis was conducted using the Potik-1 device (SMEP). Unused and used orthodontic braces were applied in the oral cavity to assess the influence of metal elements in the cellular microenvironment. Cell viability was quantified using an MTT test. The reactive oxygen species (ROS) level was determined after cell staining with fluorescent dye dihydroethidium (DHE). Results: GCB showed a higher ability to promote the proliferation of all studied cells compared with Cholisal and Gengigel® drugs. Electrophoresis potentiated cytostimulatory and protective effects of GCB when applied to + electrode. This evidences that the duration of electrophoresis conducted in clinics can be reduced from 15–20 min per jaw to 15–50 sec. In comparison, the prolongation of GCB action and local delivery of flavonoid complex and benzydamine hydrochloride into the microenvironment were maintained. Unused braces were shown to lose metal cations more intensively in the culture microenvironment, thus increasing oxidative stress. It is suggested that GCB modulates the ability of cells to withstand oxidative stress. Conclusions: GCB may be recommended as a new product for periodontal dressing in clinical periodontics and orthodontics.

Optimization method of task uninstallation in mobile edge computing environment combining improved deep Q-learning and transmission learning

Traditional task uninstallation methods are difficult to cope with the continuous changes in network environment and device status, therefore a more intelligent solution is urgently needed. This article studied the optimization method of task uninstallation in mobile edge computing (MEC) environment, and studied the optimization method of task uninstallation in combination with improved deep Q-learning and transmission learning (TL). Firstly, it provided an overview of the basic concepts and optimization problems of task uninstallation in MEC environments, and then delved into the application of improved deep Q-learning in task uninstallation optimization, namely the application of deep Q-network (DQN) in task uninstallation optimization. Next, this article designed the TL-DQN method by combining DQN and TL. This method utilizes the DQN algorithm to construct a model that can handle complex states and action spaces. Meanwhile, by introducing TL, the model can quickly transfer knowledge and achieve adaptive optimization of tasks in new environments, thereby improving the generalization ability and efficiency of the decision-making process. Experiments have shown that TL-DQN performs better in convergence speed compared to other algorithms. For delay sensitive users, the delay growth of TL-DQN algorithm is relatively slow. When the task volume reached 10, the delay of TL-DQN was 7.97 s, which was 1.99 s lower than reinforcement learning. When the number of unloading tasks increased to 500, the energy consumption of TL-DQN was 554 J, which was 282 J lower than the energy consumption required by the task uninstallation method constructed by reinforcement learning algorithms. The task uninstallation method studied in this article has achieved significant results in reducing latency, improving energy efficiency, and adapting to network dynamic changes, bringing users a more stable and reliable service experience.

An Action Evaluation Method for Virtual Reality Simulation Power Training Based on an Improved Dynamic Time Warping Algorithm

To address the shortcomings in action evaluation within VR simulation power training, this paper introduces a novel action recognition and evaluation method based on dynamic recognition of finger keypoints combined with an improved Dynamic Time Warping (DTW) algorithm. By constructing an action recognition model centered on hand keypoints, the proposed method integrates distance similarity and cosine similarity to account comprehensively for both numerical differences and directional consistency of action features. This approach effectively tackles the challenges of feature extraction and recognition for complex actions in VR power training. Furthermore, a scoring mechanism based on the improved DTW algorithm is proposed, which employs Gaussian-weighted feature-derivative Euclidean distance combined with cosine similarity. This method significantly reduces computational complexity while improving scoring accuracy and consistency. Experimental results indicated that the improved DTW algorithm outperformed traditional methods in terms of classification accuracy and robustness. In particular, cosine similarity demonstrated superior performance in capturing dynamic variations and assessing the consistency of fine hand movements. This study provides an essential technical reference for action evaluation in VR simulation power training and offers a scientific basis for advancing the intelligence and digitalization of power VR training environments.

A hybrid approach to context based human activity recognition in smart environment using ResBi-LSTM

ABSTRACT Human Activity Recognition (HAR) is essential for allowing assistive services in automated residential environments. Existing methods still have limitations, including handling complex action sequences, processing costs from high-dimensional sensor data, and collecting long-term connections. To address these issues, this paper presents a hybrid Deep Residual Bi-LSTM Network (ResBi-LSTM). This approach efficiently extracts deep features and captures temporal context by combining the advantages of residual networks, Bidirectional LSTM architectures, and one-dimensional convolution layers. Enhanced Deep Residual blocks for feature extraction, repeated residual network blocks with skip connections for improved learning, and Bi-LSTM layers for capturing long-term patterns are all included in the ResBi-LSTM model. In the present research, the efficacy of the suggested network has been assessed with an accuracy of 95.07%, precision of 95.27%, recall of 94.99%, and F1-score of 99.83% on HAR tasks in smart homes. Based on experimental results, the ResBi-LSTM model is an appropriate choice for assistive technology and smart home systems in real-life situations since it can effectively identify human behaviors while reducing computational complexity.

Two observations of rescue behavior in wild Asian elephants

AbstractWe report two instances of rescue behavior in wild Asian elephants (Elephas maximus) in Northeast India. Adult males assisted adult females sedated during GPS‐collaring efforts, pushing them away from perceived threats. These behaviors meet the criteria for rescue behavior, providing evidence of prosocial and cognitively complex actions in elephants.Abstract in Assamese is available with online material.

Mechanistic Insights into Chloride-Dependent Uncaging Reaction of Propargyl and Allene-Protected Substrates by Pd-Complexes.

This study investigates the effect of chloride levels on the mode of action of palladium complexes for the activation of propargyl- and allene-protected fluorophores and chemotherapeutic drugs through uncaging reactions. Four Pd(II) complexes were synthesized and characterized using various spectroscopic techniques to confirm their structure and electronic properties. Kinetic studies and density functional theory calculations revealed that chloride ions in phosphate buffered saline (PBS) significantly enhance catalytic efficiency, particularly for allenyl-protected substrates compared to propargylic counterparts. This enhancement is attributed to the neutral charge nature of the Pd complex. The data suggest that neutral complexes are less prone to chloride exchange by water molecules. Additionally, chloride ligands counterbalance the unusually high stability of the key σ-bound η1-Pd intermediates in the aquo complexes in PB, leading to an overall higher reactivity. These results highlight the impact of fine-tuning the electronic properties of the metal center through both designed ligands and environmental factors. Bench evaluations and tests with living breast cancer cells demonstrated that a Pd catalyst complex with a bidentate ligand effectively activates the prodrugs propargyl-5-fluorouracil (Prop-5FU) and allene-5-Fluorouracil (Alle-5FU), the latter being a novel prodrug. The Pd catalyst successfully released the active drug, inducing significant cytotoxicity, especially with Alle-5FU, which operates at lower catalyst concentrations than Pro-5FU.

Fundamentals for very long term planning

After the economy, education, health system, culture, society in general were almost completely destroyed in the last decades, the Romanian civilization must be rebuilt, on new foundations, considering top trends. Being a complex action, the reconstruction and relaunching of the country on the way to development could be planned and carried out on the basis of very long-term strategies from which the plans for more and more detailed terms can later be extracted. The strategies must start from fundamental strategic principles that target the major objectives of the national interest, as well as the objectives of interest in the international arena in which the country is involved. From many possible principles, we comment only a few, less discussed, for exemplification.

Magnetochrome-catalyzed oxidation of ferrous iron by MamP enables magnetite crystal growth in the magnetotactic bacterium AMB-1

Magnetotactic bacteria have evolved the remarkable capacity to biomineralize chains of magnetite [Fe(II)Fe(III)2O4] nanoparticles that align along the geomagnetic field and optimize their navigation in the environment. Mechanisms enabling magnetite formation require the complex action of numerous proteins for iron acquisition, sequestration in dedicated magnetosome organelles, and precipitation into magnetite. The MamP protein contains c-type cytochromes called magnetochrome domains that are found exclusively in magnetotactic bacteria. Ablation of magnetochromes in MamP prevents bacteria from aligning with external magnetic fields, showing their importance to maintain this biological function. MamP has been proposed, mostly from in vitro experimentations, to regulate iron redox state and maintain an Fe(II)/Fe(III) balance compatible with magnetite formation via the iron oxidase activity of magnetochromes. To test the proposed function for MamP in vivo in the magnetotactic strain Magnetospirillum magneticum (AMB)-1, we characterized the iron species in chemical MamP-mediated magnetite syntheses as well as in bacteria unable to produce MamP using a combination of physicochemical methodologies. We show that MamP has no apparent control on the speciation and oxidation state of intracellular iron or on the Fe(II)/Fe(III) balance in magnetite. We propose that MamP promotes magnetite growth by incorporating Fe(III) into preexisting magnetite seeds and that magnetite structure and stoichiometry is maintained by further equilibration with dissolved Fe(II) in magnetosome organelles.

No need to execute: Omitted responses still yield response-response binding effects.

In the literature on human action control, the binding and retrieval of responses are assumed to shape the coordination of more complex actions. Specifically, the consecutive execution of two responses is assumed to result in their integration into cognitive representations (so-called event files) and can be retrieved from that upon later response repetition, thereby influencing behavior. Against the background of ideomotor theory and more recent theorizing in the binding and retrieval in action control framework (Frings et al., 2020), we investigated whether response execution is necessary for binding and retrieval of responses. We manipulated whether the retrieving response (Experiment 1), as well as the to-be-bound response (Experiment 2), is executed or omitted. The results showed that responses do not need to be executed to retrieve other responses or to be bound to other responses. Apparently, activating the cognitive representation of a response sufficed for this response to trigger event file binding and retrieval. Our results are the first to show that response-response binding is not dependent on executing responses. Together, the results support the core assumptions of ideomotor theory and the binding and retrieval in action control framework, namely a common coding of action and perception. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Process tomography of structured optical gates with convolutional neural networks

Abstract Efficient and accurate characterization of an experimental setup is a critical requirement in any physical setting. In the quantum realm, the characterization of an unknown operator is experimentally accomplished via Quantum Process Tomography (QPT). This technique combines the outcomes of different projective measurements to reconstruct the underlying process matrix, typically extracted from maximum-likelihood estimation. Here, we exploit the logical correspondence between optical polarization and two-level quantum systems to retrieve the complex action of structured metasurfaces within a QPT-inspired context. In particular, we investigate a deep-learning approach that allows for fast and accurate reconstructions of space-dependent SU(2) operators by only processing a minimal set of measurements. We train a convolutional neural network based on a scalable U-Net architecture to process entire experimental images in parallel. Synthetic processes are reconstructed with average fidelity above 90%. The performance of our routine is experimentally validated in the case of space-dependent polarization transformations acting on a classical laser beam. Our approach further expands the toolbox of data-driven approaches to QPT and shows promise in the real-time characterization of complex optical gates.

Cultural heritage as a field for EU’s action in external relations: the evolution of strategy and the Ukrainian check

The European Union’s systemic engagement in the field of cultural heritage in the external relations is a relatively new and still emerging area. This is a complex action field that requires the Union to find systemic solutions that will enable it to act effectively and make full use of cultural heritage as an instrument of its foreign policy. The process of conceptualising and adopting political decisions in order to introduce the protection, preservation and promotion of cultural heritage as a field of EU action in external relations lasted from 2016 to 2022. Influenced by internal and external factors, the concept on EU Approach to Cultural Heritage in External Action evolved. A few months before the outbreak of full-scale war in Ukraine in 2022, the Council of the European Union adopted Conclusions on EU Approach to Cultural Heritage in Conflicts and Crises. The war in Ukraine and Russia's destruction and threat to Ukrainian tangible and intangible cultural heritage has become a significant test of the EU's capabilities in this field. The text is divided into two parts. The first is an analysis of the process of integrating cultural heritage into the EU's strategy in external relations, while the second attempts to answer the question of how the EU has activated the mechanisms and instruments adopted to protect Ukraine's endangered cultural heritage in the face of Russia's systemic destructive measures.

The DLEU2-miR-15a-16-1 Cluster Is a Determinant of Bone Microarchitecture and Strength in Postmenopausal Women and Mice.

This study explores how select microRNAs (miRNAs) influence bone structure in humans and in transgenic mice. In trabecular bone biopsies from 84 postmenopausal women (healthy, osteopenic, and osteoporotic), we demonstrate that DLEU2 (deleted in lymphocytic leukemia 2)-encoded miR-15a-5p is strongly positively associated with bone mineral density (BMD) at different skeletal sites. In bone transcriptome analyses, miR-15a-5p levels correlated positively with the osteocyte characteristic transcripts SOST (encoding sclerostin) and MEPE (Matrix Extracellular Phosphoglycoprotein), while the related miR-15b-5p showed a negative association with BMD and osteoblast markers. The data imply that these miRNAs have opposite roles in bone remodeling with distinct actions on bone cells. Expression quantitative trait loci (eQTL) variants confirmed earlier DLEU2 associations. Furthermore, a novel variant (rs12585295) showed high localization with transcriptionally active chromatin states in osteoblast primary cell cultures. The supposition that DLEU2-encoded miRNAs have an important regulatory role in bone remodeling was further confirmed in a transgenic mice model showing that miR-15a/16-1-deleted mice had significantly higher percentage bone volume and trabecular number than the wild type, possibly due to prenatal actions. However, the three-point mechanical break force test of mice femurs showed a positive correlation between strength and miR-15a-5p/miR-16-5p levels, indicating differential effects on cortical and trabecular bone. Moreover, these miRNAs appear to have distinct and complex actions in mice prenatally and in adult humans, impacting BMD and microstructure by regulating bone cell transcription. However, detailed interactions between these miRNAs and their downstream mechanisms in health and disease need further clarification.

Enhancing human behavior recognition with dynamic graph convolutional networks and multi-scale position attention

PurposeHuman behavior recognition poses a pivotal challenge in intelligent computing and cybernetics, significantly impacting engineering and management systems. With the rapid advancement of autonomous systems and intelligent manufacturing, there is an increasing demand for precise and efficient human behavior recognition technologies. However, traditional methods often suffer from insufficient accuracy and limited generalization ability when dealing with complex and diverse human actions. Therefore, this study aims to enhance the precision of human behavior recognition by proposing an innovative framework, dynamic graph convolutional networks with multi-scale position attention (DGCN-MPA) to sup.Design/methodology/approachThe primary applications are in autonomous systems and intelligent manufacturing. The main objective of this study is to develop an efficient human behavior recognition framework that leverages advanced techniques to improve the prediction and interpretation of human actions. This framework aims to address the shortcomings of existing methods in handling the complexity and variability of human actions, providing more reliable and precise solutions for practical applications. The proposed DGCN-MPA framework integrates the strengths of convolutional neural networks and graph-based models. It innovatively incorporates wavelet packet transform to extract time-frequency characteristics and a MPA module to enhance the representation of skeletal node positions. The core innovation lies in the fusion of dynamic graph convolution with hierarchical attention mechanisms, which selectively attend to relevant features and spatial relationships, adjusting their importance across scales to address the variability in human actions.FindingsTo validate the effectiveness of the DGCN-MPA framework, rigorous evaluations were conducted on benchmark datasets such as NTU-RGB + D and Kinetics-Skeleton. The results demonstrate that the framework achieves an F1 score of 62.18% and an accuracy of 75.93% on NTU-RGB + D and an F1 score of 69.34% and an accuracy of 76.86% on Kinetics-Skeleton, outperforming existing models. These findings underscore the framework’s capability to capture complex behavior patterns with high precision.Originality/valueBy introducing a dynamic graph convolutional approach combined with multi-scale position attention mechanisms, this study represents a significant advancement in human behavior recognition technologies. The innovative design and superior performance of the DGCN-MPA framework contribute to its potential for real-world applications, particularly in integrating behavior recognition into engineering and autonomous systems. In the future, this framework has the potential to further propel the development of intelligent computing, cybernetics and related fields.

Design of an epidemic prevention and control bracelet system integrated with convolutional neural networks: Promote real-time physiological feedback and adaptive training in remote physical education

This study aims to design an epidemic prevention and control bracelet system that integrates convolutional neural network (CNN). This system can collect and process the user’s physiological index data in real time, especially in the remote physical education scene, and provide learners with immediate physiological index feedback and personalized adaptive training suggestions through accurate human action recognition (HAR) technology. One-dimensional acceleration signal is converted into two-dimensional image, and CNN’s powerful feature extraction and classification ability is used to effectively solve the problem that manual feature extraction is complex and nonlinear features are difficult to capture. By considering the joint action trajectory in the time window, a dynamic Recurrence Plot (RP) is constructed to capture the dynamic changes among joints. To input recursive graph data into CNN, it needs to be converted into image form. In the task of HAR, CNN can automatically learn useful features from images without manually designing features. It can not only effectively extract features from images, but also be directly used in classification tasks. Experimental results show that compared with other algorithms, the proposed RP + CNN model has the best performance in action recognition, with an accuracy of 96.89% and a F1 value of 86.76%. RP captures the dynamic patterns and periodic behaviors in time series by visualizing the repeated appearance of system states over time. The RP + CNN model is used to extract and classify human action features, which significantly improves the accuracy and efficiency of HAR. This innovative method not only simplifies the complex process of traditional manual feature extraction, but also enhances the system’s ability to identify nonlinear and complex action patterns, which provides strong technical support for remote physical education.

Electrophysiological indexes of the cognitive-motor trade-off associated with motor response complexity in a cognitive task

Complex actions require more cognitive and motor control than simple ones. Literature shows that to face complexity, the brain must make a compromise between available resources usually giving priority to motor control. However, literature has minimally explored the effect of the motor response complexity on brain processing associated with cognitive tasks. Consequently, it is unknown whether carrying out a cognitive task requiring motor responses of increasing complexity could reduce cognitive processing keeping stable motor control. Therefore, this study aims to investigate possible modulations exerted by increasing motor response complexity in a cognitive task on brain processing. To this aim, we analyzed the event-related potentials and behavioral responses during a cognitive task with increasing complexity of the required motor response (keypress, reaching and stepping). Results showed the increasing motor complexity enhances early visual and attentional processing (P1 and N1 components) but reduces the late post-perceptual cognitive control (P3 component). Additionally, we found a component following the P3 which was specific for stimuli requiring a response. This component, labeled N750, increased amplitude along with the response motor complexity. Behaviorally, response accuracy was not affected by complexity. Results indicated that in cognitive tasks stimulus processing is affected by the complexity of the motor response. Complex responses require a greater investment of early perceptual and attentional resources, but at late phases of processing, cognitive resources are less available in favor of motor resources. This confirms the idea of the motor-priority cognitive-motor trade-off of the brain.

SERCA Modulators Reveal Distinct Signaling and Functional Roles of T Lymphocyte Ca2+ Stores.

The allosteric SERCA (Sarcoplasmic/Endoplasmic Reticulum Ca2+-ATPase) activator CDN1163 has been recently added to the group of pharmacological tools for probing SERCA function. We chose to investigate the effects of the compound on T lymphocyte Ca2+ stores, using the well-described Jurkat T lymphocyte as a reliable cell system for Ca2+ signaling pathways. Our study identified the lowest concentrations of the SERCA inhibitors thapsigargin (TG) and 2,5-di-(tert butyl)-1,4-benzohydroquinone (tBHQ) capable of releasing Ca2+, permitting the differentiation of the TG-sensitive SERCA 2b Ca2+ store from the tBHQ-sensitive SERCA 3 Ca2+ store. We proceeded to test the effects of CDN1163 on Ca2+ stores, examining specific actions on the SERCA 2b and SERCA 3 Ca2+ pools using our low-dose SERCA blocker regimen. In contrast to previous work, we find CDN1163 exerts complex time-sensitive and SERCA isoform-specific actions on Ca2+ stores. Surprisingly, short-term exposure (0-30 min) to CDN1163 perturbs T cell Ca2+ stores by suppressing Ca2+ uptake with diminished Ca2+ release from the SERCA 2b-controlled store. Concomitantly, we find evidence for a SERCA-activating effect of CDN1163 on the SERCA-3 regulated store, given the observation of increased Ca2+ release inducible by low-dose tBHQ. Intriguingly, longer-term (>12 h) CDN1163 exposure reversed this pattern, with increased Ca2+ release from SERCA 2b-regulated pools yet decreased Ca2+ release responses from the tBHQ-sensitive SERCA 3 pool. Indeed, this remodeling of SERCA 2b Ca2+ stores with longer-term CDN1163 exposure also translated into the compound's ability to protect Jurkat T lymphocytes from TG but not tBHQ-induced growth suppression.