Innate Receptors Expression by Lung Nociceptors: Impact on COVID-19 and Aging

The lungs are constantly exposed to non-sterile air which carries harmful threats, such as particles and pathogens. Nonetheless, this organ is equipped with fast and efficient mechanisms to eliminate these threats from the airways as well as prevent pathogen invasion. The respiratory tract is densely innervated by sensory neurons, also known as nociceptors, which are responsible for the detection of external stimuli and initiation of physiological and immunological responses. Furthermore, expression of functional innate receptors by nociceptors have been reported; however, the influence of these receptors to the lung function and local immune response is poorly described. The COVID-19 pandemic has shown the importance of coordinated and competent pulmonary immunity for the prevention of pathogen spread as well as prevention of excessive tissue injury. New findings suggest that lung nociceptors can be a target of SARS-CoV-2 infection; what remains unclear is whether innate receptor trigger sensory neuron activation during SARS-CoV-2 infection and what is the relevance for the outcomes. Moreover, elderly individuals often present with respiratory, neurological and immunological dysfunction. Whether aging in the context of sensory nerve function and innate receptors contributes to the disorders of these systems is currently unknown. Here we discuss the expression of innate receptors by nociceptors, particularly in the lungs, and the possible impact of their activation on pulmonary immunity. We then demonstrate recent evidence that suggests lung sensory neurons as reservoirs for SARS-CoV-2 and possible viral recognition via innate receptors. Lastly, we explore the mechanisms by which lung nociceptors might contribute to disturbance in respiratory and immunological responses during the aging process.

Changes in the Orexin System in Rats Exhibiting Learned Helplessness Behaviors

Orexin-A (OX-A) and orexin-B (OX-B) are neuropeptides produced in the hypothalamus. Preclinical and clinical studies suggest that depression and anxiety are associated with the orexin system. In the current study, we used the learned helplessness (LH) animal model of depression to identify rats displaying LH behaviors (LH rats) and those that did not (No-LH rats). We compared the number of orexin-containing neurons in the hypothalamus of LH, No-LH, and control rats. Orexin peptides, orexin receptor 1 (OXR1) and 2 (OXR2) in brain areas involved in major depression and serum OX-A and corticosterone (CORT) concentrations were quantified and compared between rat groups. We found that LH and No-LH rats displayed higher serum OX-A concentrations compared with control rats. Comparison between LH and No-LH rats revealed that No-LH rats had significantly higher OX-A levels in the brain, more OX-A neurons, and more OX-A neuron activation. LH rats had more OX-B neurons and more OX-B neuron activation. Orexin peptides and receptors in the brain areas involved in major depression exhibited different patterns in LH and NoLH rats. Our findings revealed that activation of OX-A neurons could promote resilient behaviors under stressful situations and OX-A and OX-B neuropeptides exhibit dissimilar functions in LH behaviors.

Effect of Visualization on Muscular Activation for Stability in Adolescent Ballet Students

The purpose of this study is to determine whether commonly used visualization techniques, whose results have been solely anecdotal, produce tangible, scientific results in muscular activation and improvement to ballet balances. Ballet training methods include imagery techniques however, much of this practice is solely based on the experience of the instructor and its results are anecdotal so that there are many gaps between research on imagery and dance instruction. Few published studies focus on the effect of the imagery training for dance students on either motor and nonmotor outcomes (Abraham, 2019). A survey will be administered to ballet instructors to determine the most used visualization cues for stability. Three adolescent female ballet students studying under said instructors will be asked to perform three balances. Surface electromyography data will be taken on the gluteus maximus, hip adductors, and abdominal oblique. The length of balance will also be taken. The dancers will then be exposed to a short visualization session or stimulus of anatomical images with arrows showing bodily adjustments and targeted muscles accompanied by verbal cues developed based on the instructor techniques from the survey. The same balances and data will be taken following the session. Results will be compared to the control data taken prior to the session to reveal whether the visualization training had significant results by determining statistically significant changes in balance times and changes in neuron spikes following spike analysis. Dancers will also be asked for qualitative feedback. Subject 2 yielded a significant increase in length of balance in all three types and the most consistent increase in neuron spikes in all of their muscles. This suggests a positive correlation between an increase in the degree of neuron activation or recruitment of those stability muscles and the ability for an individual to balance. This was also supported by increased confidence they felt in their balances after the visualization session. Subject 1 yielded no significant change in balance time before and after the visualization stimulus and the number of neuron spikes decreased after the session. This suggests that decreased activity in the tested muscles for stability resulted in lower balance times. This lack of muscular activation could be attributed to fatigue as reported by the dancer. The rest of the balances yielded significant increases in lengths of balance which were accompanied by increases in neuron spikes in the gluteus maximus and hip adductors for Degage a la Seconde and in the gluteus maximus for Releve en Retire. Subject 3 yielded insignificant changes in balance times for the first two types of balances but produced increases in the number of neuron spikes in most of the tested muscles in all of the balances. Reports from the dancer of being “less wobbly” the unexpected data to be attributed to an allocation to quality of the balance. The results on length of balances, number of neuron spikes, and confidence/reflection feedback obtained by this study supports the scientific validity of commonly-used visualization techniques in ballet by showcasing a higher degree of activation in the targeted stability muscles and longer average balance lengths should ensue following visualization training. Results also suggest that visualization techniques and stimuli for stability are the most effective when applied to learning unfamiliar movements. Further research could apply such visualization techniques to other movements, and even outside of dance.

Blocking HMGB1/RAGE Signaling by Berberine Alleviates A1 Astrocyte and Attenuates Sepsis-Associated Encephalopathy

As a life-threatening multiple organ dysfunction attributable to maladjusted host immune responses to infection, sepsis is usually the common pathway to serious prognosis and death for numerous infectious diseases all over the world. Sepsis-associated encephalopathy (SAE) is frequently complicated by septic conditions, and is one of the most important reasons for increased mortality and poor outcomes in septic patients which is still an urgent clinical problem need to be solved. In this research, a conspicuously discovery of treatment-related translational use for berberine was elaborated. The results revealed that berberine treatment significantly restored cognitive impairment in sepsis mice. Reduced expression levels of TNF-α, IL-1α, and C1qA were exhibited in the hippocampus of the berberine treatment group, and attenuated effect of declining neo-neuron, activation of microglia and astrocytes in the hippocampus of mice with sepsis were also found. Moreover, berberine inhibits microglia-stressed A1 astrocytes by inhibiting HMGB1 signaling was revealed, then the molecular mechanism of HMGB1/RAGE signaling inhibition leads to the better outcome of SAE was elucidated. To summarize, this research indicated that berberine targets HMGB1/RAGE signaling to inhibit microglia-stressed A1 astrocyte and neo-neuron decline, which consequently alleviates sepsis-induced cognitive impairment. Collectively, berberine may serve as potential therapeutic drug and HMGB1/RAGE signaling would be a novel target for medicine development for treating SAE.

A conserved neuropeptide system links head and body motor circuits to enable adaptive behavior

Neuromodulators promote adaptive behaviors that are often complex and involve concerted activity changes across circuits that are often not physically connected. It is not well understood how neuromodulatory systems accomplish these tasks. Here we show that the C. elegans NLP-12 neuropeptide system shapes responses to food availability by modulating the activity of head and body wall motor neurons through alternate G-protein coupled receptor (GPCR) targets, CKR-1 and CKR-2. We show ckr-2 deletion reduces body bend depth during movement under basal conditions. We demonstrate CKR-1 is a functional NLP-12 receptor and define its expression in the nervous system. In contrast to basal locomotion, biased CKR-1 GPCR stimulation of head motor neurons promotes turning during local searching. Deletion of ckr-1 reduces head neuron activity and diminishes turning while specific ckr-1 overexpression or head neuron activation promote turning. Thus, our studies suggest locomotor responses to changing food availability are regulated through conditional NLP-12 stimulation of head or body wall motor circuits.

Stimulation of hypothalamic oxytocin neurons suppresses colorectal cancer progression in mice

Emerging evidence suggests that the nervous system is involved in tumor development in the periphery, however, the role of central nervous system remains largely unknown. Here, by combining genetic, chemogenetic, pharmacological and electrophysiological approaches, we show that hypothalamic oxytocin (Oxt)-producing neurons modulate colitis-associated cancer (CAC) progression in mice. Depletion or activation of Oxt neurons could augment or suppress CAC progression. Importantly, brain treatment with celastrol, a pentacyclic triterpenoid, excites Oxt neurons and inhibits CAC progression, and this anti-tumor effect was significantly attenuated in Oxt neuron-lesioned mice. Furthermore, brain treatment with celastrol suppresses sympathetic neuronal activity in the celiac-superior mesenteric ganglion (CG-SMG), and activation of β2 adrenergic receptor abolishes the anti-tumor effect of Oxt neuron activation or centrally administered celastrol. Taken together, these findings demonstrate that hypothalamic Oxt neurons regulate CAC progression by modulating the neuronal activity in the CG-SMG. Stimulation of Oxt neurons using chemicals, eg. celastrol, might be a novel strategy for colorectal cancer treatment.

NTS Prlh overcomes orexigenic stimuli and ameliorates dietary and genetic forms of obesity

Calcitonin receptor (Calcr)-expressing neurons of the nucleus tractus solitarius (NTS; CalcrNTS cells) contribute to the long-term control of food intake and body weight. Here, we show that Prlh-expressing NTS (PrlhNTS) neurons represent a subset of CalcrNTS cells and that Prlh expression in these cells restrains body weight gain in the face of high fat diet challenge in mice. To understand the relationship of PrlhNTS cells to hypothalamic feeding circuits, we determined the ability of PrlhNTS-mediated signals to overcome enforced activation of AgRP neurons. We found that PrlhNTS neuron activation and Prlh overexpression in PrlhNTS cells abrogates AgRP neuron-driven hyperphagia and ameliorates the obesity of mice deficient in melanocortin signaling or leptin. Thus, enhancing Prlh-mediated neurotransmission from the NTS dampens hypothalamically-driven hyperphagia and obesity, demonstrating that NTS-mediated signals can override the effects of orexigenic hypothalamic signals on long-term energy balance.

Non-genetic photoacoustic stimulation of single neurons by a tapered fiber optoacoustic emitter

Neuromodulation at high spatial resolution poses great significance in advancing fundamental knowledge in the field of neuroscience and offering novel clinical treatments. Here, we developed a tapered fiber optoacoustic emitter (TFOE) generating an ultrasound field with a high spatial precision of 39.6 µm, enabling optoacoustic activation of single neurons or subcellular structures, such as axons and dendrites. Temporally, a single acoustic pulse of sub-microsecond converted by the TFOE from a single laser pulse of 3 ns is shown as the shortest acoustic stimuli so far for successful neuron activation. The precise ultrasound generated by the TFOE enabled the integration of the optoacoustic stimulation with highly stable patch-clamp recording on single neurons. Direct measurements of the electrical response of single neurons to acoustic stimulation, which is difficult for conventional ultrasound stimulation, have been demonstrated. By coupling TFOE with ex vivo brain slice electrophysiology, we unveil cell-type-specific responses of excitatory and inhibitory neurons to acoustic stimulation. These results demonstrate that TFOE is a non-genetic single-cell and sub-cellular modulation technology, which could shed new insights into the mechanism of ultrasound neurostimulation.

Fixed-Time Synchronization of Delayed Memristive Neural Networks with Discontinuous Activations

In this paper, the fixed-time synchronization problem for a class of memristive neural networks with discontinuous neuron activation functions and mixed time-varying delays is investigated. With the help of the fixed-time stability theory, under the framework of Filippov solution and differential inclusion theory, several new and useful sufficient criteria for fixed-time synchronization are obtained by designing two types of energy-saving and simple controllers for the considered systems. Compared with the traditional fixed-time synchronization controller, the controllers used in this paper only have one power exponent term, which is a function of the system state error rather than a constant. Moreover, some previous relevant works are especially improved. Finally, two numerical examples are given to show the correctness and the effectiveness of the obtained theoretical results.

Communication Signal Modulation Mechanism Based on Artificial Feature Engineering Deep Neural Network Modulation Identifier

Based on the characteristics of time domain and frequency domain recognition theory, a recognition scheme is designed to complete the modulation identification of communication signals including 16 analog and digital modulations, involving 10 different eigenvalues in total. In the in-class recognition of FSK signal, feature extraction in frequency domain is carried out, and a statistical algorithm of spectral peak number is proposed. This paper presents a method to calculate the rotation degree of constellation image. By calculating the rotation degree and modifying the clustering radius, the recognition rate of QAM signal is improved significantly. Another commonly used method for calculating the rotation of constellations is based on Radon transform. Compared with the proposed algorithm, the proposed algorithm has lower computational complexity and higher accuracy under certain SNR conditions. In the modulation discriminator of the deep neural network, the spectral features and cumulative features are extracted as inputs, the modified linear elements are used as neuron activation functions, and the cross-entropy is used as loss functions. In the modulation recognitor of deep neural network, deep neural network and cyclic neural network are constructed for modulation recognition of communication signals. The neural network automatic modulation recognizer is implemented on CPU and GPU, which verifies the recognition accuracy of communication signal modulation recognizer based on neural network. The experimental results show that the communication signal modulation recognizer based on artificial neural network has good classification accuracy in both the training set and the test set.