Novel Cellular Stress Models with Implications in Understanding and Treating ENT Pathologies

Interaction with the world around us requires extracting meaningful signals to guide behaviour. The mammalian senses of olfaction, vision, somatosensation, hearing, balance and taste facilitate extraction of sense-specific information. Most sensory organs in the vertebrate head originate from cranial placodes (CPs). CPs are formed embryonically through a series of differentiation steps arising at the boundary between neural and non-neural ectoderm, and they can be divided into anterior, posterior and intermediate groups depending on their place of origin in the developing embryonic head. Anterior CPs include adenohypophyseal, olfactory and lens placodes;intermediate CPs include the trigeminal placode, which gives rise to the sensory neurons of the ophthalmic and maxilla-mandibular divisions of the trigeminal ganglion;posterior CPs are comprised of the otic, lateral line placode and the epibranchial placodes that give rise to the inner ear, lateral line organs (in fish and amphibian) and sensory neurons of the geniculate, petrosal and nodose ganglia, respectively. The complexity of neural plate border specification in vitro poses a major limitation to gain deeper mechanistic insights into the developmental cues driving efficient placodal differentiation;hence generation and establishment of in vitro cellular models with improved cranial placode differentiation are challenging. Our group is interested in the establishment of cranial/sensory placodes in vitro using novel cellular stress stem cell reprogramming models with translational implications in sensorineural hearing loss regeneration and modelling COVID-19-associated anosmia. We are primarily interested in building the otic placodes that can form viable otic vesicles in vitro, which can be further directed to generate cochlear/vestibular systems of inner ear and the sensory neurons of its associated vestibulocochlear ganglion. Given the copious involvement of serine proteases in COVID-19 pathogenesis, we are also encouraged to leverage our proteolytic stress cellular models towards establishment and characterization of novel olfactory epithelial neurospheres housing supporting cells, progenitor cells and sensory neurons for investigating cellular and molecular targets of COVID-19-associated anosmia. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022.

A Case Report on Heart Rate Variability Biofeedback and Postconcussion Syndrome: Healing the Autonomic Nervous System

Postconcussion syndrome is a devastating condition of the mind, body, and even personality. Mounting research demonstrates that heart rate variability biofeedback can help the concussed individual in three critical ways: (a) eliciting high amplitude oscillations in cardiovascular functions and thereby strengthening self-regulatory control mechanisms;(b) restoring autonomic balance;and (c) increasing the afferent impulse stream from the baroreceptors to restore balance between inhibitory and excitatory processes in the brain.

Neuropathogenesis and Neurological Manifestations of SARS-CoV-2

Neurological complications of COVID-19 contribute significantly to mortality in the intensive care unit (ICU). Preventive therapy, though discussed in literature, is limited for COVID-19 neurological manifestations and treatment algorithms continue to rely on evidence from previous pandemics. Thus, in this chapter we evaluate current in vitro, in vitro, histopathological studies to ascertain the most likely mechanisms of SARS-CoV-2 central nervous system entry. From this understanding, we determine probable mechanisms for neurological compilations observed in COVID-19 as relevant to the clinician. SARS-CoV-2 infection of nasal epithelium and the respiratory tract may allow for a systemic inflammatory response that results in neuroinflammation. While most neurological complications are inflammatory in etiology, rarely, SARS-CoV-2 may enter into the central nervous system and mediate neuronal damage. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

Angiotensin and pain

The role of the renin-angiotensin system in human pain is a complicated and controversial field, partly due to the complexities of the system itself, but also because of the diverse ways in which pain functions. Here, we focus on what is known about the angiotensins in pathological pain and describe the ongoing attempts to identify candidate modulators of clinical significance. Systemic angiotensin agonists and antagonists have effects in a number of neuropathic ailments, including some of the most medically intractable conditions, such as endocrine disorders, cancer, myopathies, and viral infections (such as COVID-19), apart from direct damage to the nervous system. These arise due to multiple physiological processes involving both neural and nonneural pathways that could be overcome with future research. In summary, it is clear that the angiotensins acting through their different receptors exercise both algesic and analgesic effects, but less clear how this diversity of responses arises. © 2023 Elsevier Inc. All rights reserved.

DESIGN OF NEURAL PREDICTORS FOR PREDICTING AND ANALYSING COVID-19 CASES IN DIFFERENT REGIONS

Nowadays, some unexpected viruses are affecting people with many troubles. COVID-19 virus is spread in the world very rapidly. However, it seems that predicting cases and death fatalities is not easy. Artificial neural networks are employed in many areas for predicting the system's parameters in simulation or real-time approaches. This paper presents the design of neural predictors for analysing the cases of COVID-19 in three countries. Three countries were selected because of their different regions. Especially, these major countries' cases were selected for predicting future effects. Furthermore, three types of neural network predictors were employed to analyse COVID-19 cases. NAR-NN is one of the proposed neural networks that have three layers with one input layer neurons, hidden layer neurons and an output layer with fifteen neurons. Each neuron consisted of the activation functions of the tan-sigmoid. The other proposed neural network, ANFIS, consists of five layers with two inputs and one output and ARIMA uses four iterative steps to predict. The proposed neural network types have been selected from many other types of neural network types. These neural network structures are feed-forward types rather than recurrent neural networks. Learning time is better and faster than other types of networks. Finally, three types of neural predictors were used to predict the cases. The R2 and MSE results improved that three types of neural networks have good performance to predict and analyse three region cases of countries. © CTU FTS 2022.

Assessment of SARS-CoV-2 infection in astrocytes

Discovered in late 2019 in a market in the city of Wuhan, Hubei Province, China, SARS-CoV-2 is an important member of the Coronaviridae family, responsible for bringing the whole world into a state of alert causing a global pandemic. The virus has been identified as causing a characteristic clinical condition known as "Corona-virus disease 2019" (COVID-19), causing an Acute Respiratory Syndrome. Being a respiratory virus, transmitted by direct contact with an infected person and by touching contaminated surfaces, SARS-CoV-2 quickly spread throughout the world, causing a pandemic, having today more than 535 million people infected and causing more than million deaths. In addition to the respiratory system, the virus is present in other cells in the body. Findings show the presence of SARS-CoV-2 in cerebrospinal fluid associated with changes in the expression of neuronal inflammation markers, as well as an increased expression of cytokines released by astrocytes, indicating an alteration in the Central Nervous System (CNS). In this project, we analyzed the effects of SARS-CoV-2 infection directly on astrocytes, glial cells that are extremely important for the maintenance of homeostasis and CNS defense. Therefore, we produced astrocytes from three human iPSC strains to verify aspects of cell morphology and physiology, as well as gene and protein expression, after infection with the virus. We found that SARS-CoV-2 is capable of infecting astrocytes, but some studies are still needed to better elucidate its role in the interaction with this cell type in the CNS.

Design of neural predictors for predicting and analysing COVID-19 cases in different regions: International Journal on Neural and Mass - Parallel Computing and Information Systems

Nowadays, some unexpected viruses are affecting people with many troubles. COVID-19 virus is spread in the world very rapidly. However, it seems that predicting cases and death fatalities is not easy. Artificial neural networks are employed in many areas for predicting the system’s parameters in simulation or real-time approaches. This paper presents the design of neural predictors for analysing the cases of COVID-19 in three countries. Three countries were selected because of their different regions. Especially, these major countries’ cases were selected for predicting future effects. Furthermore, three types of neural network predictors were employed to analyse COVID-19 cases. NAR-NN is one of the proposed neural networks that have three layers with one input layer neurons, hidden layer neurons and an output layer with fifteen neurons. Each neuron consisted of the activation functions of the tan-sigmoid. The other proposed neural network, ANFIS, consists of five layers with two inputs and one output and ARIMA uses four iterative steps to predict. The proposed neural network types have been selected from many other types of neural network types. These neural network structures are feed-forward types rather than recurrent neural networks. Learning time is better and faster than other types of networks. Finally, three types of neural predictors were used to predict the cases. The R2 and MSE results improved that three types of neural networks have good performance to predict and analyse three region cases of countries.

[An electron microscopic study of neocortex of Syrian hamsters (Mesocricetus auratus) infected with SARS-CoV-2 (Coronaviridae: Coronavirinae: Betacoronavirus: Sarbecovirus)].

INTRODUCTION: Convalescent COVID-19 patients have various signs of central nervous system damage, including those directly associated with SARS-CoV-2. Hence, studies of SARS-COV-2 related morphological changes in neocortex are particularly relevant for understanding the mechanisms of their formation and development of approaches to preclinical evaluation of the effectiveness of antiviral drugs. The purpose of the research is a longitudinal study of the ultrastructural alterations in Syrian hamsters neocortex after experimental SARS-CoV-2 infection. MATERIALS AND METHODS: Male Syrian hamsters weighing 80100 g, aged 4 to 6 weeks, were infected with 26 l SARS-CoV-2 intranasally with 4104 TCD50/ml of viral particles. The animals were euthanized on days 3, 7 or 28 post-infection, the brain was extracted with the cortex excision. The material analysis was performed using transmission electron microscopy. RESULTS AND DISCUSSION: On day 3 post-infection, the number of moderately hyperchromic neurons in neocortex increased, while by the day 7 the number of apoptotic cells significantly increased. Simultaneously, an increased signs of neuronophagy and representation of atypical glia were observed. Increased number of altered oligodendrocytes was observed on day 28 post-infection. Viral invasion was accompanied by changes in neocortical cells since day 3 post-infection, such as transformation of their nucleus, the rough endoplasmic reticulum and the Golgi vesicles as well as microvascular spasm with perivascular edema. CONCLUSION: As a result of electron microscopic study, the ultrastructural alterations in neocortex were described in an experimental model of SARS-CoV-2 infection. The findings can be used to identify the mechanisms of infection pathogenesis and to search for the new directions in development of medicines.

Dendritic Deep Residual Learning for COVID‐19 Prediction

Deep residual network (ResNet), one of the mainstream deep learning models, has achieved groundbreaking results in various fields. However, all neurons used in ResNet are based on the McCulloch‐Pitts model which has long been criticized for its oversimplified structure. Accordingly, this paper for the first time proposes a novel dendritic residual network by considering the powerful information processing capacity of dendrites in neurons. Experimental results based on the challenging COVID‐19 prediction problem show the superiority of the proposed method in comparison with other state‐of‐the‐art ones. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

Using Neuroscience-informed Group Work with Children and Adolescents Affected by the Pandemic

The COVID-19 pandemic has resulted in many types of disruptions from mild inconveniences to deaths. These disruptions have resulted in a host of stress responses among children and adolescents. Small group work is one way that helpers in schools and agencies can address developmental and diagnostic issues that arise. Neuroscience informs counselors understanding of stress responses and reactions in children and adolescents, as well as aids in generating activities and activating group therapeutic factors. This article describes the ways the neuroscience of pandemic stress and therapeutic factors can be used in group work with children and adolescents.

A Novel Approach of Using Neural Circuit Policies for COVID-19 Classification on CT-Images

Fully connected (FC) layers as a classifier to categorize data have been practiced widely by the deep learning community. The dense wiring topology might lead to redundant complexity and overfitting during training. To overcome the disadvantages, we investigate neural circuit policies (NCP) to alternate the FC layers in this paper. NCP networks enable sparse and polarized connections between layers. Neurons within one layer can interact with themselves as well. However, NCP can handle only sequential data. To be compatible with the image classification task, we use sequence modeling techniques to simulate sequential data within the images. The ultimate comparison between NCP and FC models relies on the performance in classifying COVID-19 CT-slides. With our novel modeling technique, Z-NCP, the NCP models obtain the most stable scores. The FC models are comparably good and less resource-demanding. However, they are much less efficient considering the accuracy-complexity trade-off. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

SARS-CoV-2 Induces Epithelial-Enteric Neuronal Crosstalk Stimulating VIP Release.

BACKGROUND: Diarrhea is present in up to 30-50% of patients with COVID-19. The mechanism of SARS-CoV-2-induced diarrhea remains unclear. We hypothesized that enterocyte-enteric neuron interactions were important in SARS-CoV-2-induced diarrhea. SARS-CoV-2 induces endoplasmic reticulum (ER) stress in enterocytes causing the release of damage associated molecular patterns (DAMPs). The DAMPs then stimulate the release of enteric neurotransmitters that disrupt gut electrolyte homeostasis. METHODS: Primary mouse enteric neurons (EN) were exposed to a conditioned medium from ACE2-expressing Caco-2 colonic epithelial cells infected with SARS-CoV-2 or treated with tunicamycin (ER stress inducer). Vasoactive intestinal peptides (VIP) expression and secretion by EN were assessed by RT-PCR and ELISA, respectively. Membrane expression of NHE3 was determined by surface biotinylation. RESULTS: SARS-CoV-2 infection led to increased expression of BiP/GRP78, a marker and key regulator for ER stress in Caco-2 cells. Infected cells secreted the DAMP protein, heat shock protein 70 (HSP70), into the culture media, as revealed by proteomic and Western analyses. The expression of VIP mRNA in EN was up-regulated after treatment with a conditioned medium of SARS-CoV-2-infected Caco-2 cells. CD91, a receptor for HSP70, is abundantly expressed in the cultured mouse EN. Tunicamycin, an inducer of ER stress, also induced the release of HSP70 and Xbp1s, mimicking SARS-CoV-2 infection. Co-treatment of Caco-2 with tunicamycin (apical) and VIP (basolateral) induced a synergistic decrease in membrane expression of Na+/H+ exchanger (NHE3), an important transporter that mediates intestinal Na+/fluid absorption. CONCLUSIONS: Our findings demonstrate that SARS-CoV-2 enterocyte infection leads to ER stress and the release of DAMPs that up-regulates the expression and release of VIP by EN. VIP in turn inhibits fluid absorption through the downregulation of brush-border membrane expression of NHE3 in enterocytes. These data highlight the role of epithelial-enteric neuronal crosstalk in COVID-19-related diarrhea.

Corrigendum: TDP-43 and NEAT long non-coding RNA: Roles in neurodegenerative disease.

[This corrects the article DOI: 10.3389/fncel.2022.954912.].

Substance P and Prokineticin-2 are overexpressed in olfactory neurons and play differential roles in persons with persistent post-COVID-19 olfactory dysfunction.

Persistent olfactory dysfunction (OD) is one of the most complaining and worrying complications of long COVID-19 because of the potential long-term neurological consequences. While causes of OD in the acute phases of the SARS-CoV-2 infection have been figured out, reasons for persistent OD are still unclear. Here we investigated the activity of two inflammatory pathways tightly linked with olfaction pathophysiology, namely Substance P (SP) and Prokineticin-2 (PK2), directly within the olfactory neurons (ONs) of patients to understand mechanisms of persistent post-COVID-19 OD. ONs were collected by non-invasive brushing from ten patients with persistent post-COVID-19 OD and ten healthy controls. Gene expression levels of SP, Neurokinin receptor 1, Interleukin-1ß (IL-1ß), PK2, PK2 receptors type 1 and 2, and Prokineticin-2-long peptide were measured in ONs by Real Time-PCR in both the groups, and correlated with residual olfaction. Immunofluorescence staining was also performed to quantify SP and PK2 proteins. OD patients, compared to controls, exhibited increased levels of both SP and PK2 in ONs, the latter proportional to residual olfaction. This work provided unprecedented, preliminary evidence that both SP and PK2 pathways may have a role in persistent post-COVID-19 OD. Namely, if the sustained activation of SP, lasting months after infection's resolution, might foster chronic inflammation and contribute to hyposmia, the PK2 expression could instead support the smell recovery.

Emerging Roles of Type-I Interferons in Neuroinflammation, Neurological Diseases, and Long-Haul COVID.

Interferons (IFNs) are pleiotropic cytokines originally identified for their antiviral activity. IFN-α and IFN-ß are both type I IFNs that have been used to treat neurological diseases such as multiple sclerosis. Microglia, astrocytes, as well as neurons in the central and peripheral nervous systems, including spinal cord neurons and dorsal root ganglion neurons, express type I IFN receptors (IFNARs). Type I IFNs play an active role in regulating cognition, aging, depression, and neurodegenerative diseases. Notably, by suppressing neuronal activity and synaptic transmission, IFN-α and IFN-ß produced potent analgesia. In this article, we discuss the role of type I IFNs in cognition, neurodegenerative diseases, and pain with a focus on neuroinflammation and neuro-glial interactions and their effects on cognition, neurodegenerative diseases, and pain. The role of type I IFNs in long-haul COVID-associated neurological disorders is also discussed. Insights into type I IFN signaling in neurons and non-neuronal cells will improve our treatments of neurological disorders in various disease conditions.

Central Effects of Ivermectin in Alleviation of Covid-19-induced Dysauto-nomia.

Covid-19 may be associated with various neurological disorders, including dysautonomia, a dysfunction of the autonomic nervous system (ANS). In Covid-19, hypoxia, immunoinflammatory abnormality, and deregulation of the renin-angiotensin system (RAS) may increase sympathetic discharge with dysautonomia development. Direct SARS-CoV-2 cytopathic effects and associated inflammatory reaction may lead to neuroinflammation, affecting different parts of the central nervous system (CNS), including the autonomic center in the hypothalamus, causing dysautonomia. High circulating AngII, hypoxia, oxidative stress, high pro-inflammatory cytokines, and emotional stress can also provoke autonomic deregulation and high sympathetic outflow with the development of the sympathetic storm. During SARS-CoV-2 infection with neuro-invasion, GABA-ergic neurons and nicotinic acetylcholine receptor (nAChR) are inhibited in the hypothalamic pre-sympathetic neurons leading to sympathetic storm and dysautonomia. Different therapeutic modalities are applied to treat SARS-CoV-2 infection, like antiviral and anti-inflammatory drugs. Ivermectin (IVM) is a robust repurposed drug widely used to prevent and manage mild-moderate Covid-19. IVM activates both GABA-ergic neurons and nAChRs to mitigate SARS-CoV-2 infection- induced dysautonomia. Therefore, in this brief report, we try to identify the potential role of IVM in managing Covid-19-induced dysautonomia.

Spurring competitiveness, social and economic performance of family-owned SMEs through social entrepreneurship;a multi-analytical SEM & ANN perspective

Social enterprises have become a nascent concept in academia and have grabbed the attention of research scholars. They are deemed as an important predictor of economic growth, poverty alleviation, and solving social and economic issues. In the COVID-19 pandemic, many developed and developing economies accounted for a negative change in unemployment, health, education, and other social issues. Consequently, researchers realized that social enterprises are an important predictor to overcome many issues during the pandemic. Hence, the current study contributes to the body of knowledge by investigating the influence of social entrepreneurial orientation on social and economic performance through a mediating role of competitive advantage. The data were collected from the top management of family-owned manufacturing firms operating in Pakistan. The current study executed a dual-stage analysis involving Smart-PLS and artificial intelligence (AI) named Artificial Neurons Networks (ANN). The SEM model shows that social entrepreneurial orientation has a negative impact on economic performance (profit maximization) but a positive effect on social performance. ANN architecture explains the 78 % accuracy of the proposed model. Considering the results, we recommend firms emphasize social entrepreneurial orientation to configure their competitive advantage and performance in the pandemic.

Rapidly progressing idiopathic intracranial hypertension after a Covid-19 infection

AimsTo present a case of a previously well child with rapidly progressing idiopathic intracranial hypertension (IIH) requiring a lumboperitoneal shunt after a Covid-19 infection.MethodsA fifteen-year-old girl presented to the Children’s Emergency Department on 23th October 2021 with a history of headaches (temporal, periorbital and occipital) and reduced visual acuity. These started following a Covid-19 infection on 30th September. She was reviewed by ophthalmology in view of deteriorating visual acuity (right eye>left eye). Bilateral papilloedema and haemorrhages were noted on examination. Her visual acuity was 6/24 unaided in the right eye and 6/7.5 unaided in the left eye. During the admission her visual acuity deteriorated to 6/36 pinhole in the right eye and 6/12 pinhole in the left eye. In the right eye she lost colour vision and developed a relative afferent pupillary defect. She received acetazolamide and intravenous methylprednisolone before being transferred to Birmingham Children’s Hospital neurosurgical ward for a lumboperitoneal shunt.There has been a significant improvement since surgery. On 22nd November there was resolving papilloedema and haemorrhages. She had normalised colour vision and resolution of the afferent pupillary reflex. Her visual acuity was 0.275 in the right eye and 0.100 in the left eye (LogMAR). However, persistent deficits could have significant consequences such as the ability to obtain a driving licence.ResultsAn MRI showed bilateral papilloedema of the optic discs. An MRV showed narrowing of the bilateral traverse sinuses with gradual tapering suggestive of high intracranial pressure. Raised intracranial pressures were confirmed by lumbar puncture on two separate occasions. The pressures were beyond the limit of the manometer used (34cm H2O).ConclusionShe had two well recognised risk factors;female gender and increased BMI so is within the high-risk group. However, she had no pathognomonic signs/symptoms of IIH or Ophthalmic complaints before COVID-19, meaning this was a rapidly progressing case that coincided with a Covid-19 infection.It is not possible to declare a cause and effect relationship in this case, but there is some emerging reports of Covid-19 positive patients with refractory headaches having isolated raised intracranial pressures within the adult population.1 2The Covid-19 pandemic has also precipitated indirect consequences. Weight gain as a result of lockdown was reported, which increased her risk of IIH.ReferencesSilva MTT, Lima MA, Torezani G, et al. Isolated intracranial hypertension associated with COVID-19. Cephalalgia. 2020;40(13):1452-1458. doi:10.1177/0333102420965963Ilhan B, Cokal BG, Mungan Y. Intracranial hypertension and visual loss following COVID-19: A case report. Indian J Ophthalmol. 2021;69(6):1625-1627. doi:10.4103/ijo.IJO_342_21

COVID-19 and Respiratory Diseases Classification using Deep Convolution Neuron Network

This study proposes COVID-19 and Respiratory Diseases Classification using Deep Convolution Neuron Network. ICBHI 2017 Respiratory Sound Database including COVID-19 from Coswara databased were used in our experiments. The potential results show that the left side model performances are 0.85 accuracy, 0.76 sensitivity, and 0.90 specificity. The right side model performances are 0.86 accuracy, 0.76 sensitivity, and 0.93 specificity. No side set model performances are 0.83 accuracy, 0.71 sensitivity, and 0.93 specificity. In addition, the lung characteristics and lung functions are different among left and right. Therefore, the breathing sound from left and right lung are difference. For this reason, the cross-model performances were evaluated to test this assumption. The cross-model performance results show that the left data is consistent with the left model. As same as the right data is consistent with the right model. Furthermore, the experiment found that mixing training data built the no side set model is the lowest performance. In addition, the proposed framework tends to achieve high performance when compared with a recent study. © 2022 IEEE.