Significant Stimuli Research Articles

The effects of preceding sound on three measures related to gain reduction

The medial olivocochlear reflex (MOCR) decreases the gain of the cochlear active process in response to sound. We have used psychoacoustic techniques to show behavioral effects of gain reduction, which could be consistent with the MOCR. We have used forward masking paradigms understood to measure frequency selectivity and the input/output function at the level of the cochlea using stimuli (masker and signal) that should be too short to evoke the MOCR. A precursor sound is then presented before these stimuli to evoke the MOCR. In previous studies, we have shown that a precursor: (1) increases signal threshold more after an off-frequency masker than the on-frequency one for forward maskers matched in effectiveness to increase signal threshold to 5 dB SL, (2) may increase on-frequency masker threshold required to mask a signal of 15-20 dB SL, and (3) may decrease suppression in forward masking. All of these effects would be consistent with a reduction in gain by the precursor, possibly by the MOCR. In the current study, these effects are all measured within the same listeners, using a more effective precursor than has been used in previous studies. The relationship between the measures will be discussed.

Thermal-Response Proton Conduction in Schiff Base-Incorporated Metal-Organic Framework Hybrid Membranes under Low Humidity Based on the Excited-State Intramolecular Proton Transfer Mechanism.

Stimulus-responsive proton conduction materials have attracted enormous interest as a new kind of "smart material". It is desirable to develop the appropriate stimulus signal and high proton-conducting materials with an excellent proton-conducting switch ratio (γ), but it remains a great challenge. Here, it can be found for the first time that 4-((2-hydroxybenzylidene)amino)benzenesulfonic acid (HBABSA) has obvious thermal isomerization when porous solids act as matrixes at the ambient temperatures, which is different from that in the crystalline state at 77 K. Therefore, we proposed a host-guest metal-organic framework (MOF) composite, namely, MOF-808 incorporated with HBABSA (HBABSA@MOF-808), which has a proton-conducting switch ratio (γ) of 16 between 338 and 343 K due to the thermally induced isomerization of HBABSA molecules in the MOF pores. The strong binding between the keto-type HBABSA and MOF at the relatively low temperatures can efficiently suppress the proton conduction, while the enol-type one provides more mobile protons for conduction at the high temperatures due to the excited-state intramolecular proton transfer mechanism. Further, the HBABSA@MOF-808 as a filler is blended into polyvinyl alcohol and poly(2-acrylamide-2-methyl-1-propane sulfonic acid) to form hybrid membranes. The hybrid membrane with the highest content of the MOF composite displays a high proton conductivity of 5.57 × 10-3 S·cm-1 under 353 K and 57% RH along with a good switch ratio of 5.4. The development of thermal-response proton-conducting MOF materials is opening up a unique pathway for remote control, thermal sensing, intelligent batteries, and other fields.

A DNA Finite-State Machine Based on the Programmable Allosteric Strategy of DNAzyme.

Living organisms can produce corresponding functions by responding to external and internal stimuli, and this irritability plays a pivotal role in nature. Inspired by such natural temporal responses, the development and design of nanodevices with the ability to process time-related information could facilitate the development of molecular information processing systems. Here, we proposed a DNA finite-state machine that can dynamically respond to sequential stimuli signals. To build this state machine, a programmable allosteric strategy of DNAzyme was developed. This strategy performs the programmable control of DNAzyme conformation using a reconfigurable DNA hairpin. Based on this strategy, we first implemented a finite-state machine with two states. Through the modular design of the strategy, we further realized the finite-state machine with five states. The DNA finite-state machine endows molecular information systems with the ability of reversible logic control and order detection, which can be extended to more complex DNA computing and nanomachines to promote the development of dynamic nanotechnology.

Dynamic immune response in the spleens of rainbow trout (Oncorhynchus mykiss) to infectious hematopoietic necrosis virus revealed by transcriptome and immune-related genes expression analysis

Rainbow trout (Oncorhynchus mykiss) is, economically, one of the most important cultured fish in the world. Infectious hematopoietic necrosis virus (IHNV) is a serious pathogen causing high morbidity and mortality in rainbow trout. To gain more insight into the immune response of rainbow trout to the virus, RNA sequencing technology was used to examine the transcriptome profiles in spleens of trout infected and uninfected with IHNV. A total of 9144 differentially expressed genes (DEGs) were identified, of which 3274 were upregulated and 5870 were downregulated. The expression levels of 13 DEGs were validated by quantitative real-time PCR. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis showed that most DEGs were significantly enriched in major immune terms such as immune system process, immune effector process, response to stimulus and key immune signaling pathways. Moreover, we detected the expression levels of six key immune-related genes based on transcriptomic data and protein–protein interaction analysis in four important immune signaling pathways at 0, 6, 12, 24, 48, 72, 96, 120, and 144 h post-infection, including Toll-like receptor signaling pathway (TLR2 and TLR5M), RIG-I-like receptor signaling pathway (TRIM25), NOD-like receptor signaling pathway (RIPK2 and A20) and JAK-STAT signaling pathway (SOCS2). Results revealed that the immune-related genes in these pathways were involved in the antiviral immune response. Altogether, this study provides a better understanding of the dynamic immune response of rainbow trout infected with IHNV, which will lay a foundation for further study of molecular mechanisms of anti-IHNV innate immunity.

Savory Signaling: T1R Umami Receptor Modulates Endoplasmic Reticulum Calcium Store Content and Release Dynamics in Airway Epithelial Cells.

T1Rs are expressed in solitary chemosensory cells of the upper airway where they detect apical glucose levels and repress bitter taste receptor Ca2+ signaling pathways. Microbial growth leads to a decrease in apical glucose levels. T1Rs detect this change and liberate bitter taste receptor signaling, initiating an innate immune response to both kill and expel pathogens through releasing antimicrobial peptides and increasing nitric oxide production and ciliary beat frequency. However, chronic inflammation due to disease, smoking, or viral infections causes a remodeling of the epithelial airway. The resulting squamous metaplasia causes a loss of multi-ciliated cells and solitary chemosensory cells, replaced by basal epithelial cells. To understand how T1R function is altered during disease, we used basal epithelial cells as a model to study the function of T1R3 on Ca2+ signaling dynamics. We found that both T1R1 and T1R3 detect amino acids and signal via cAMP, increasing the responsiveness of the cells to Ca2+ signaling stimuli. Either knocking down T1R1/3 or treating wild-type cells with MEM amino acids caused a reduction in ER Ca2+ content through a non-cAMP signaled pathway. Treatment with amino acids led to a reduction in downstream denatonium-induced Ca2+-signaled caspase activity. Thus, amino acids may be used to reduce unwanted apoptosis signaling in treatments containing bitter compounds.

CsPbBr3/graphene nanowall artificial optoelectronic synapses for controllable perceptual learning

The rapid development of neuromorphic computing has stimulated extensive research interest in artificial synapses. Optoelectronic artificial synapses using laser beams as stimulus signals have the advantages of broadband, fast response, and low crosstalk. However, the optoelectronic synapses usually exhibit short memory duration due to the low lifetime of the photo-generated carriers. It greatly limits the mimicking of human perceptual learning, which is a common phenomenon in sensory interactions with the environment and practices of specific sensory tasks. Herein, a heterostructure optoelectronic synapse based on graphene nanowalls and CsPbBr3 quantum dots was fabricated. The graphene/CsPbBr3 heterojunction and the natural middle energy band in graphene nanowalls extend the carrier lifetime. Therefore, a long half-life period of photocurrent decay - 35.59 s has been achieved. Moreover, the long-term optoelectronic response can be controlled by the adjustment of numbers, powers, wavelengths, and frequencies of the laser pulses. Next, an artificial neural network consisting of a 28 × 28 synaptic array was established. It can be used to mimic a typical characteristic of human perceptual learning that the ability of sensory systems is enhanced through a learning experience. The learning behavior of image recognition can be tuned based on the photocurrent response control. The accuracy of image recognition keeps above 80% even under a low-frequency learning process. We also verify that less time is required to regain the lost sensory ability that has been previously learned. This approach paves the way toward high-performance intelligent devices with controllable learning of visual perception.

DNA-decorated multilamellar cholesterol assemblies for nucleic acid detection in the micrometer-scale solid-state nanopore

The large-sized glass nanopipette (GN) allows for an access of large targets and show the benefits of excellent mechanical stability and reproducibility. The nanoscale DNA-decorated multilamellar cholesterol assemblies are introduced into the GN with several nanometers, and could in situ grow into a micrometer-scale aggregates under DNA signal stimulus, developing a simple and sensitive strategy for DNA detection in the micrometer-scale GN. The detection limit of target DNA reaches 2.69 fM in a GN with a diameter of up to ca. 4.76 μm.

EFEITOS DO TREINAMENTO COM ESCADA NA MOBILIDADE DOS ATLETAS DE VOLEIBOL

ABSTRACT Introduction: The step movement in volleyball is a fundamental skill that volleyball players must master, being the basis of the support of all other techniques of this sport. Objective: Explore the effect of ladder training on the mobility of high school volleyball players. Methods: Twenty high school male volleyball players aged 16-17 were selected as experimental volunteers. Randomly divided into experimental and control groups, 10 individuals in each group received a training intervention for 8 weeks, with ladder training added to the experimental group. Results: Both pieces of training resulted showed positive effects on the improvement of movement ability and speed and could effectively improve the athletes’ movement speed ability. Conclusion: Through systematic ladder training, the excitatory conduction time in the reflex arc of athletes was significantly reduced, leading to a faster response to various signal stimuli, bringing the athletes’ central nervous system to a state more prepared for sports practice. Level of evidence II; Therapeutic studies - investigation of treatment outcomes.

Role of necroptosis in spinal cord injury and its therapeutic implications

Spinal cord injury (SCI), a complex neurological disorder, triggers a series of devastating neuropathological events such as ischemia, oxidative stress, inflammatory events, neuronal apoptosis, and motor dysfunction. However, the classical necrosome, which consists of receptor-interacting protein (RIP)1, RIP3, and mixed-lineage kinase domain-like protein, is believed to control a novel type of programmed cell death called necroptosis, through tumour necrosis factor-alpha/tumour necrosis factor receptor-1 signalling or other stimuli. Several studies reported that necroptosis plays an important role in neural cell damage, release of intracellular pro-inflammatory factors, lysosomal dysfunction and endoplasmic reticulum stress. Recent research indicates that necroptosis is crucial to the pathophysiology of a number of neurological disorders and SCIs. In our review, we summarize the potential role of programmed cell death regulated by necroptosis in SCI based on its molecular and pathophysiological mechanisms. We also summarize the targets of several necroptosis pathways, which provide a more reliable reference for the treatment of SCI.

An ultrasensitive flexible pressure, temperature, and humidity sensor based on structurally adjustable nano-through-hole array films

A pressure, temperature and humidity flexible multiresponsive sensor was fabricated, which has independent responses to triple stimulus signals without crosstalk.

Recent advances in responsive antibacterial materials: design and application scenarios.

Bacterial infection is one of the leading causes of death globally, although modern medicine has made considerable strides in the past century. As traditional antibiotics are suffering from the emergence of drug resistance, new antibacterial strategies are of great interest. Responsive materials are appealing alternatives that have shown great potential in combating resistant bacteria and avoiding the side effects of traditional antibiotics. In this review, the responsive antibacterial materials are introduced in terms of stimulus signals including intrinsic (pH, enzyme, ROS, etc.) and extrinsic (light, temperature, magnetic fields, etc.) stimuli. Their biomedical applications in therapeutics and medical devices are then discussed. Finally, the author's perspective of the challenge and the future of such a system is provided.

Development of a Wearable Haptic Glove Presenting Haptic Sensation by Electrical Stimulation

Most haptic devices generate haptic sensation using mechanical actuators. However, the workload and limited workspace handicap the operator from operating freely. Electrical stimulation is an alternative approach to generate haptic sensations without using mechanical actuators. The light weight of the electrodes adhering to the body brings no limitations to free motion. Because a real haptic sensation consists of feelings from several areas, mounting the electrodes to several different body areas can make the sensations more realistic. However, simultaneously stimulating multiple electrodes may result in "noise" sensations. Moreover, the operators may feel tingling because of unstable stimulus signals when using the dry electrodes to help develop an easily mounted haptic device using electrical stimulation. In this study, we first determine the appropriate stimulation areas and stimulus signals to generate a real touch sensation on the forearm. Then, we propose a circuit design guideline for generating stable electrical stimulus signals using a voltage divider resistor. Finally, based on the aforementioned results, we develop a wearable haptic glove prototype. This haptic glove allows the user to experience the haptic sensations of touching objects with five different degrees of stiffness.

Dynamic Pathway Selection Mechanisms of Brain Networks

Based on the dynamic reorganization mechanism of brain science and the fact that synaptic adaptability is affected by synaptic type, synaptic number and ion concentration, a bionic dynamic synaptic model is proposed and applied to a motif model and brain-like network model. By extracting the phase synchronization characteristics of the neural signals of node pairs in time sequence, and then deeply studying the regulation and control effect of synchronous discharge activities on effective links under the action of stimulating information, the path selection strategy is designed with the goal of maximizing the information transmission capacity between nodes. Four indicators are proposed: (1) pathway-synchronization-facilitation; (2) pathway-activation; (3) pathway-phase-selectivity; (4) pathway-switching-selectivity, which are used as the main basis for path selection in the network. The results show that the in-phase and anti-phase transition of neuron nodes under the action of time delay is an important way to form an effective link, and, in addition to the influence of synaptic strength and the number of central nodes on synchronization characteristics, the phase information carried by the stimulus signal also regulates the path selection. Furthermore, the paths between the pairs of stimulus nodes in the network have different phase preferences. In the brain-like network with twenty nodes, it is found that nearly 42% of the stimulus nodes have a strong phase preference; that is, the path can be selected and switched through the phase information carried by the information flow, and then the path with better representation information can be found. It also provides a new idea for how brain-like intelligences might better represent information.

The causal role of the prefrontal and superior medial frontal cortices in the incidental manipulation of decision strategies

A key strategic decision one must make in virtually every task context concerns the speed accuracy trade-off (SAT). Experimentally, this ubiquitous phenomenon, whereby response speed and task accuracy are inversely related, is typically studied by explicitly instructing participants to adjust their strategy: by either focusing on speed, or on accuracy. Computational modelling has been applied to deconvolve the latent decision processes involved in the SAT, with considerable evidence suggesting that response caution (the amount of evidence needed for a decision to be reached) is a key variable in the setting of SAT strategy. Neuroimaging has implicated the prefrontal cortex, the pre-supplementary motor area (preSMA), and the striatum in the setting of response caution. In addition, brain stimulation has provided causal evidence for the involvement of the left prefrontal cortex and superior medial frontal cortex (SMFC, which includes the preSMA) in adjustments of response caution following explicit instructions, although stimulation of the two regions has dissociable effects. Here, in a double-blind and preregistered study we investigated the role of these two regions using an incidental manipulation of SAT strategy – via stimulus signal variability – which has previously been shown to influence decision confidence. We again found tDCS applied to both regions modulated response caution, and there was a dissociation: stimulating prefrontal cortex increased, and stimulating SMFC decreased, response caution. These findings provide further support for key, but dissociable, roles of these brain regions in decision strategies whether they are implemented explicitly or incidentally.

A self-powered wearable seizure-monitoring/brain-stimulating system for potential epilepsy treatment

A new self-powered wearable body-detecting/brain-stimulating system for monitoring and restraining epilepsy has been fabricated. The system can monitor body motion in real time and transmit the stimulus signals to brain for restraining the epileptic seizures. The system is composed of energy harvesting module, the body motion detection sensor, the data processing center, and neural stimulator. An arch-shaped device made of piezoelectric ceramic transducer (lead zirconate titanate; PZT) as energy harvesting module can convert the mechanical energy generated by body movement into electricity power. The motion detection sensor is made of polyvinylidene fluoride (PVDF) doped with zinc oxide (ZnO) nanostructures, which can detect the tiny movements of the human body and transmit sensing signals to the data processing center. The data processing center can determine the epileptic seizure and generate neural stimulating signals. By stimulating the dentate gyrus/hilus brain region of mice, the total duration of epileptic seizures in mice is significantly reduced by 40–50%. This new self-powered strategy demonstrates the potential of brain-machine-interface system for personalized treatment of brain disease.

Comprehensive investigation and regulatory function of lncRNAs engaged in western honey bee larval immune response to Ascosphaera apis invasion.

Ascosphaera apis is a fungal pathogen that exclusively infects bee larvae, causing chalkbrood disease, which results in severe damage for beekeeping industry. Long non-coding RNAs (lncRNAs) are versatile regulators in various biological processes such as immune defense and host-pathogen interaction. However, expression pattern and regulatory role of lncRNAs involved in immune response of bee host to A. apis invasion is still very limited. Here, the gut tissues of Apis mellifera ligustica 4-, 5-, and 6-day-old larvae inoculated by A. apis spores (AmT1, AmT2, and AmT3 groups) and corresponding un-inoculated larval guts (AmCK1, AmCK2, and AmCK3 groups) were prepared and subjected to deep sequencing, followed by identification of lncRNAs, analysis of differentially expressed lncRNAs (DElncRNAs), and investigation of competing endogenous RNA (ceRNA) network. In total, 3,746 A. m. ligustica lncRNAs were identified, including 78 sense lncRNAs, 891 antisense lncRNAs, 1,893 intergenic lncRNAs, 346 bidirectional lncRNAs, and 210 intronic lncRNAs. In the 4-, 5-, and 6- comparison groups, 357, 236, and 505 DElncRNAs were discovered. Additionally, 217, 129, and 272 DElncRNAs were respectively predicted to regulate neighboring genes via cis-acting manner, and these targets were associated with a series of GO terms and KEGG pathways of great importance, such as response to stimulus and Jak-STAT signaling pathway. Moreover, 197, 95, and 356 DElncRNAs were observed to target 10, eight, and 21 DEmiRNAs and further target 147, 79, and 315 DEmRNAs, forming complex regulatory networks. Further investigation suggested that these targets were engaged in several key cellular and humoral immune pathways, such as phagosome and MAPK signaling pathway. Ultimately, the expression trends of nine randomly selected DElncRNAs were verified by RT-qPCR, confirming the authenticity and reliability of our transcriptome data. Findings in this current work not only provide candidate DElncRNAs for functional study, but also lay a foundation for unclosing the mechanism underlying DElncRNA-regulated larval immune responses to A. apis invasion.

Signal generation and regulation of implantable nerve stimulator

In the treatment of nervous system diseases, implantable nerve stimulators have attracted more and more attention because of their obvious therapeutic efficacy and high safety. The generation and regulation of stimulus signals are the most important step in the design of an implantable nerve stimulator. The stimulation signals from the implanted nerve stimulator act directly on nerve cells. If the stimulus signal is not delivered accurately according to the set parameters, it will not only affect the therapeutic effect but also cause unpredictable malignant consequences. To generate stimulus signals that meet certain requirements, the different circuit structures need to be designed to be applied to the stimulators with different function types. In this paper, five types of stimulator circuits are introduced, and their strengths and weaknesses are analyzed based on the detailed introduction of the working principles of the different stimulator circuits, which might provide a theoretical and practical reference for future research.

Very low frequency waves as selective probe for Cysticercus tenuicollis, Hydatid cyst and Coenurus cerebralis bio-analysis using single cell-signal recording

Comparative electric behavior of Cysticercus tenuicollis, Hydatid cyst and Coenurus cerebralis at the Very Low Frequency (VLF) region has been studied in detail. This investigation could be significant, because of the economic and public health importance of these parasitic infections in domestic animals. In this report, a single cell signal recording technique has been adopted for comparison using a stainless steel (type: 316, diameter: ~ 300 µm, height: 2.00 cm) two identical electrode system, implanted on the surface of the tested cysts with inter electrode distance of 0.50 cm at a ~ 6.0 giga ohm (GΩ) sealed condition (based on the situation of the implanted electrode system). This process was achieved based on applying electrical interaction between the cysts and the VLF electrical signal. Relative to the measured time domain signal (Current–time diagram), the frequency domain (Current-frequency diagram) was estimated via applying a “Discrete Fast Fourier Transform” (DFFT) algorithm at a fixed time interval (5.0 min). Factors, having important influence on the sensitivity of the detection system including the type (waveform) of different alternating-current (AC) triggering stimulus signals (such as direct current, square wave, triangular, sin (t), etc.), the amplitude, as well as the frequency were optimized automatically through a written “Visual Basic 6” program by one-factor-at-a-time method. Direct applying this AC triggering VLF voltage to the cysts resulted in tracing an AC electrical current vs. time that considered as the time domain wave. However, this electrical current was decayed rapidly versus time during maximum 30.0 s time scale. Applying the DFFT algorithm to the measured time domain, resulted in accessing to the frequency domain at the selected frequency range between 2 and 5 kHz that was considered as the selected frequency for the selective differentiation of C. tenuicollis, Hydatid cyst and C. cerebralis. The related probable mechanism of this process may be attributed to the correlation between the triggering potential and the cyst’s electrical surface charge (Zeta potential) as the current source under similar conditions. The results of this study may help to introduce a new detection system for in vivo recognition of the cysts in future.

Forgetting memristor based STDP learning circuit for neural networks

The circuit implementation of STDP based on memristor is of great significance for the application of neural network. However, recent research shows that the research on the pure circuit implementation of forgetting memristor and STDP is still rare. This paper proposes a new STDP learning rule implementation circuit based on the forgetting memristor. This kind of forgetting memory resistance synapse makes the neural network have the function of time-division multiplexing, but the instability of short-term memory will affect the learning ability of the neural network. This paper analyzes and discusses the influence of synapses with long-term and short-term memory on the learning characteristics of neural network STDP, which lays a foundation for the construction of time-division multiplexing neural network with long-term and short-term memory synapses. Through this circuit, it is found that the volatile memristor has different behaviors to the stimulus signal in different initial states, and the resulting LTP phenomenon is more in line with the forgetting effect in biology. This circuit has multiple adjustable parameters, which can fit the STDP learning rules under different conditions. The application of neural network proves the availability of this circuit.

Operant conditioning of stochastic chemical reaction networks.

Adapting one's behavior to environmental conditions and past experience is a key trait of living systems. In the biological world, there is evidence for adaptive behaviors such as learning even in naturally occurring, non-neural, single-celled organisms. In the bioengineered world, advances in synthetic cell engineering and biorobotics have created the possibility of implementing lifelike systems engineered from the bottom up. This will require the development of programmable control circuitry for such biomimetic systems that is capable of realizing such non-trivial and adaptive behavior, including modification of subsequent behavior in response to environmental feedback. To this end, we report the design of novel stochastic chemical reaction networks capable of probabilistic decision-making in response to stimuli. We show that a simple chemical reaction network motif can be tuned to produce arbitrary decision probabilities when choosing between two or more responses to a stimulus signal. We further show that simple feedback mechanisms from the environment can modify these probabilities over time, enabling the system to adapt its behavior dynamically in response to positive or negative reinforcement based on its decisions. This system thus acts as a form of operant conditioning of the chemical circuit, in the sense that feedback provided based on decisions taken by the circuit form the basis of the learning process. Our work thus demonstrates that simple chemical systems can be used to implement lifelike behavior in engineered biomimetic systems.