The spinal dorsal horn is a major site for the induction and maintenance of mechanical allodynia, but the circuitry that underlies this clinically important form of pain remains unclear. The studies ...presented here provide strong evidence that the neural circuits conveying mechanical allodynia in the dorsal horn differ by the nature of the injury. Calretinin (CR) neurons in lamina II inner convey mechanical allodynia induced by inflammatory injuries, while protein kinase C gamma (PKCγ) neurons at the lamina II/III border convey mechanical allodynia induced by neuropathic injuries. Cholecystokinin (CCK) neurons located deeper within the dorsal horn (laminae III–IV) are important for both types of injuries. Interestingly, the Maf+ subset of CCK neurons is composed of transient vesicular glutamate transporter 3 (tVGLUT3) neurons, which convey primarily dynamic allodynia. Identification of an etiology-based circuitry for mechanical allodynia in the dorsal horn has important implications for the mechanistic and clinical understanding of this condition.
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•CR neurons are important for mechanical allodynia in inflammatory injuries•PKCγ neurons are important for mechanical allodynia in neuropathic injuries•CCK and tVGLUT3 neurons in deeper laminae convey both types of injuries•The Maf+ subset of CCK neurons encompasses tVGLUT3 and conveys dynamic allodynia
Peirs et al. identified distinct spinal cord microcircuits that underlie mechanical allodynia, depending on the injury type. The neurons engaged after neuropathic or inflammatory injuries include populations that express CCK, tVGLUT3, CR, and PKCγ.
In a general computational context for biomedical data analysis, DNA sequence classification is a crucial challenge. Several machine learning techniques have used to complete this task in recent ...years successfully. Identification and classification of viruses are essential to avoid an outbreak like COVID-19. Regardless, the feature selection process remains the most challenging aspect of the issue. The most commonly used representations worsen the case of high dimensionality, and sequences lack explicit features. It also helps in detecting the effect of viruses and drug design. In recent days, deep learning (DL) models can automatically extract the features from the input. In this work, we employed CNN, CNN-LSTM, and CNN-Bidirectional LSTM architectures using Label and K-mer encoding for DNA sequence classification. The models are evaluated on different classification metrics. From the experimental results, the CNN and CNN-Bidirectional LSTM with K-mer encoding offers high accuracy with 93.16% and 93.13%, respectively, on testing data.
Ellis-Van Creveld syndrome or chondroectodermal dysplasia is a rare autosomal recessive disorder presenting several skeletal manifestations and congenital heart malformations. Ellis-Van Creveld ...syndrome comprises of a tetrad of clinical manifestations of chondrodysplasia, polydactyly, ectodermal dysplasia, and cardiac defects. Here, we are presenting a very rare case of Ellis-Van Creveld syndrome in siblings.
Delivering genes to and across the brain vasculature efficiently and specifically across species remains a critical challenge for addressing neurological diseases. We have evolved adeno-associated ...virus (AAV9) capsids into vectors that transduce brain endothelial cells specifically and efficiently following systemic administration in wild-type mice with diverse genetic backgrounds, and in rats. These AAVs also exhibit superior transduction of the CNS across non-human primates (marmosets and rhesus macaques), and in ex vivo human brain slices, although the endothelial tropism is not conserved across species. The capsid modifications translate from AAV9 to other serotypes such as AAV1 and AAV-DJ, enabling serotype switching for sequential AAV administration in mice. We demonstrate that the endothelial-specific mouse capsids can be used to genetically engineer the blood-brain barrier by transforming the mouse brain vasculature into a functional biofactory. We apply this approach to Hevin knockout mice, where AAV-X1-mediated ectopic expression of the synaptogenic protein Sparcl1/Hevin in brain endothelial cells rescued synaptic deficits.
Gene therapy offers great promise in addressing neuropathologies associated with the central and peripheral nervous systems (CNS and PNS). However, genetic access remains difficult, reflecting the ...critical need for the development of effective and non-invasive gene delivery vectors across species. To that end, we evolved adeno-associated virus serotype 9 (AAV9) capsid in mice and validated two capsids, AAV-MaCPNS1 and AAV-MaCPNS2, across rodent species (mice and rats) and non-human primate (NHP) species (marmosets and rhesus macaques). Intravenous administration of either AAV efficiently transduced the PNS in rodents and both the PNS and CNS in NHPs. Furthermore, we used AAV-MaCPNS1 in mice to systemically deliver the following: (1) the neuronal sensor jGCaMP8s to record calcium signal dynamics in nodose ganglia and (2) the neuronal actuator DREADD to dorsal root ganglia to mediate pain. This conclusively demonstrates the translatability of these two systemic AAVs across four species and their functional utility through proof-of-concept studies in mice.
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•Directed evolution in rodents identified AAV vectors targeting the PNS•Systemically administered MaCPNS1 and MaCPNS2 efficiently target the PNS in rodents•Systemic MaCPNS1 is used for functional readout and non-invasive modulation of the PNS•Systemic MaCPNS1 and MaCPNS2 transduce both the PNS and CNS in macaque and marmoset
Chen et al. evolved a family of AAV capsid variants, including MaCPNS1 and MaCPNS2, that efficiently transduced the PNS in rodents following systemic administration, enabling functional readout and non-invasive modulation of PNS. Both vectors could also enable efficient gene delivery to both PNS and CNS in macaque and marmoset.
Mechanical allodynia is a major symptom of neuropathic pain whereby innocuous touch evokes severe pain. Here we identify a population of peripheral sensory neurons expressing TrkB that are both ...necessary and sufficient for producing pain from light touch after nerve injury in mice. Mice in which TrkB-Cre-expressing neurons are ablated are less sensitive to the lightest touch under basal conditions, and fail to develop mechanical allodynia in a model of neuropathic pain. Moreover, selective optogenetic activation of these neurons after nerve injury evokes marked nociceptive behavior. Using a phototherapeutic approach based upon BDNF, the ligand for TrkB, we perform molecule-guided laser ablation of these neurons and achieve long-term retraction of TrkB-positive neurons from the skin and pronounced reversal of mechanical allodynia across multiple types of neuropathic pain. Thus we identify the peripheral neurons which transmit pain from light touch and uncover a novel pharmacological strategy for its treatment.
A game based virtual campus tour Razia Sulthana, A; Arokiaraj Jovith, A; Saveetha, D ...
Journal of physics. Conference series,
04/2018, Letnik:
1000, Številka:
1
Journal Article
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Odprti dostop
The aim of the application is to create a virtual reality game, whose purpose is to showcase the facilities of SRM University, while doing so in an entertaining manner. The virtual prototype of the ...institution is deployed in a game engine which eases the students to look over the infrastructure, thereby reducing the resources utilization. Time and money are the resources in concern today. The virtual campus application assists the end user even from a remote location. The virtual world simulates the exact location and hence the effect is created. Thus, it virtually transports the user to the university, with the help of a VR Headset. This is a dynamic application wherein the user can move in any direction. The VR headset provides an interface to get gyro input and this is used to start and stop the movement. Virtual Campus is size efficient and occupies minimal space. It is scalable against mobile gadgets. This gaming application helps the end user to explore the campus, while having fun too. It is a user friendly application that supports users worldwide.
Presently, a green Internet of Things (IoT) based energy aware network plays a significant part in the sensing technology. The development of IoT has a major impact on several application areas such ...as healthcare, smart city, transportation, etc. The exponential rise in the sensor nodes might result in enhanced energy dissipation. So, the minimization of environmental impact in green media networks is a challenging issue for both researchers and business people. Energy efficiency and security remain crucial in the design of IoT applications. This paper presents a new green energy-efficient routing with DL based anomaly detection (GEER-DLAD) technique for IoT applications. The presented model enables IoT devices to utilize energy effectively in such a way as to increase the network span. The GEER-DLAD technique performs error lossy compression (ELC) technique to lessen the quantity of data communication over the network. In addition, the moth flame swarm optimization (MSO) algorithm is applied for the optimal selection of routes in the network. Besides, DLAD process takes place via the recurrent neural network-long short term memory (RNN-LSTM) model to detect anomalies in the IoT communication networks. A detailed experimental validation process is carried out and the results ensured the betterment of the GEER-DLAD model in terms of energy efficiency and detection performance.
In recent times, Internet of Things (IoT) has become a hot research topic and it aims at interlinking several sensor-enabled devices mainly for data gathering and tracking applications. Wireless ...Sensor Network (WSN) is an important component in IoT paradigm since its inception and has become the most preferred platform to deploy several smart city application areas like home automation, smart buildings, intelligent transportation, disaster management, and other such IoT-based applications. Clustering methods are widely-employed energy efficient techniques with a primary purpose i.e., to balance the energy among sensor nodes. Clustering and routing processes are considered as Non-Polynomial (NP) hard problems whereas bio-inspired techniques have been employed for a known time to resolve such problems. The current research paper designs an Energy Efficient Two-Tier Clustering with Multi-hop Routing Protocol (EETTC-MRP) for IoT networks. The presented EETTC-MRP technique operates on different stages namely, tentative Cluster Head (CH) selection, final CH selection, and routing. In first stage of the proposed EETTC-MRP technique, a type II fuzzy logic-based tentative CH (T2FL-TCH) selection is used. Subsequently, Quantum Group Teaching Optimization Algorithm-based Final CH selection (QGTOA-FCH) technique is deployed to derive an optimum group of CHs in the network. Besides, Political Optimizer based Multihop Routing (PO-MHR) technique is also employed to derive an optimal selection of routes between CHs in the network. In order to validate the efficacy of EETTC-MRP method, a series of experiments was conducted and the outcomes were examined under distinct measures. The experimental analysis infers that the proposed EETTC-MRP technique is superior to other methods under different measures.
General Electronics for TPCs (GET) is a generic, reconfigurable and comprehensive electronics and data-acquisition system for nuclear physics instrumentation of up to 33792 channels. The system ...consists of a custom-designed ASIC for signal processing, front-end cards that each house 4 ASIC chips and digitize the data in parallel through 12-bit ADCs, concentration boards to read and process the digital data from up to 16 ASICs, a 3-level trigger and master clock module to trigger the system and synchronize the data, as well as all of the associated firmware, communication and data-acquisition software. An overview of the system including its specifications and measured performances are presented.
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