Characterization of optical fibers doped with nanoparticles for distributed displacement sensing.

High-scattering optical fibers have emerged as a key component in distributed sensing systems, primarily due to their capacity to enhance signal-to-noise ratio. This paper presents an experimental characterization of optical fibers doped with oxide nanoparticles for displacement sensing. They were manufactured using the phase-separation technique and different doping compounds, including calcium, strontium, lanthanum and magnesium. The Rayleigh backscattering (RBS) signatures in time and frequency domains were acquired using an Optical Backscatter Reflectometer (OBR). The maximum representative length, backscattering gain and strain sensitivity were evaluated. The results indicate that the fiber co-doped with magnesium and erbium chlorides offered the best compromise between strain sensitivity (0.96 pm/µ ϵ) and maximum length (17 m). For conditions of single and multiple perturbations, strain saturation was reached at ≥7000 µm and <1500 µm, respectively. In addition, the results reveal that, under a condition of variable temperature (30-60 °C), the sensor response becomes significantly nonlinear over length, requiring a technique for temperature cross-sensitivity mitigation that accounts for nonlinearities in sensitivity and hysteresis.

The Gap Junction Inhibitor Octanol Decreases Proliferation and Increases Glial Differentiation of Postnatal Neural Progenitor Cells.

Neural precursor cells (NPCs) that persist in the postnatal/adult subventricular zone (SVZ) express connexins that form hemichannels and gap junctions. Gap junctional communication plays a role in NPC proliferation and differentiation during development, but its relevance on postnatal age remains to be elucidated. In this work we aimed to evaluate the effect of the blockade of gap junctional communication on proliferation and cell fate of NPCs obtained from the SVZ of postnatal rats. NPCs were isolated and expanded in culture as neurospheres. Electron microscopy revealed the existence of gap junctions among neurosphere cells. Treatment of cultures with octanol, a broad-spectrum gap junction blocker, or with Gap27, a specific blocker for gap junctions formed by connexin43, produced a significant decrease in bromodeoxyuridine incorporation. Octanol treatment also exerted a dose-dependent antiproliferative effect on glioblastoma cells. To analyze possible actions on NPC fate, cells were seeded in the absence of mitogens. Treatment with octanol led to an increase in the percentage of astrocytes and oligodendrocyte precursors, whereas the percentage of neurons remained unchanged. Gap27 treatment, in contrast, did not modify the differentiation pattern of SVZ NPCs. Our results indicate that general blockade of gap junctions with octanol induces significant effects on the behavior of postnatal SVZ NPCs, by reducing proliferation and promoting glial differentiation.

Soft-Sensor System for Grasp Type Recognition in Underactuated Hand Prostheses.

This paper presents the development of an intelligent soft-sensor system to add haptic perception to the underactuated hand prosthesis PrHand. Two sensors based on optical fiber were constructed, one for finger joint angles and the other for fingertips' contact force. Three sensor fabrications were tested for the angle sensor by axially rotating the sensors in four positions. The configuration with the most similar response in the four rotations was chosen. The chosen sensors presented a polynomial response with R2 higher than 92%. The tactile force sensors tracked the force made over the objects. Almost all sensors presented a polynomial response with R2 higher than 94%. The system monitored the prosthesis activity by recognizing grasp types. Six machine learning algorithms were tested: linear regression, k-nearest neighbor, support vector machine, decision tree, k-means clustering, and hierarchical clustering. To validate the algorithms, a k-fold test was used with a k = 10, and the accuracy result for k-nearest neighbor was 98.5%, while that for decision tree was 93.3%, enabling the classification of the eight grip types.

Data-Driven Approach for Upper Limb Fatigue Estimation Based on Wearable Sensors.

Muscle fatigue is defined as a reduced ability to maintain maximal strength during voluntary contraction. It is associated with musculoskeletal disorders that affect workers performing repetitive activities, affecting their performance and well-being. Although electromyography remains the gold standard for measuring muscle fatigue, its limitations in long-term work motivate the use of wearable devices. This article proposes a computational model for estimating muscle fatigue using wearable and non-invasive devices, such as Optical Fiber Sensors (OFSs) and Inertial Measurement Units (IMUs) along the subjective Borg scale. Electromyography (EMG) sensors are used to observe their importance in estimating muscle fatigue and comparing performance in different sensor combinations. This study involves 30 subjects performing a repetitive lifting activity with their dominant arm until reaching muscle fatigue. Muscle activity, elbow angles, and angular and linear velocities, among others, are measured to extract multiple features. Different machine learning algorithms obtain a model that estimates three fatigue states (low, moderate and high). Results showed that between the machine learning classifiers, the LightGBM presented an accuracy of 96.2% in the classification task using all of the sensors with 33 features and 95.4% using only OFS and IMU sensors with 13 features. This demonstrates that elbow angles, wrist velocities, acceleration variations, and compensatory neck movements are essential for estimating muscle fatigue. In conclusion, the resulting model can be used to estimate fatigue during heavy lifting in work environments, having the potential to monitor and prevent muscle fatigue during long working shifts.

Fiber-Optic Hydrophone Based on Michelson's Interferometer with Active Stabilization for Liquid Volume Measurement.

Sensing technologies using optical fibers have been studied and applied since the 1970s in oil and gas, industrial, medical, aerospace, and civil areas. Detecting ultrasound acoustic waves through fiber-optic hydrophone (FOH) sensors can be one solution for continuous measurement of volumes inside production tanks used by these industries. This work presents an FOH system composed of two optical fiber coils made with commercial single mode fiber (SMF) working in the sensor head of a Michelson's interferometer (MI) supported by an active stabilization mechanism that drives another optical coil wound around a piezoelectric actuator (PZT) in the reference arm to mitigate external mechanical and thermal noise from the environment. A 1000 mL glass graduated cylinder filled with water is used as a test tank, inside which the sensor head and an ultrasound source are placed. For detection, amplitudes and phases are measured, and machine learning algorithms predict their respective liquid volumes. The acoustic waves create patterns electronically detected with resolution of 1 mL and sensitivity of 340 mrad/mL and 70 mvolts/mL. The nonlinear behavior of both measurands requires classification, distance metrics, and regression algorithms to define an adequate model. The results show the system can determine liquid volumes with an accuracy of 99.4% using a k-nearest neighbors (k-NN) classification with one neighbor and Manhattan's distance. Moreover, Gaussian process regression using rational quadratic metrics presented a root mean squared error (RMSE) of 0.211 mL.

Towards Multimodal Equipment to Help in the Diagnosis of COVID-19 Using Machine Learning Algorithms.

COVID-19 occurs due to infection through respiratory droplets containing the SARS-CoV-2 virus, which are released when someone sneezes, coughs, or talks. The gold-standard exam to detect the virus is Real-Time Polymerase Chain Reaction (RT-PCR); however, this is an expensive test and may require up to 3 days after infection for a reliable result, and if there is high demand, the labs could be overwhelmed, which can cause significant delays in providing results. Biomedical data (oxygen saturation level-SpO2, body temperature, heart rate, and cough) are acquired from individuals and are used to help infer infection by COVID-19, using machine learning algorithms. The goal of this study is to introduce the Integrated Portable Medical Assistant (IPMA), which is a multimodal piece of equipment that can collect biomedical data, such as oxygen saturation level, body temperature, heart rate, and cough sound, and helps infer the diagnosis of COVID-19 through machine learning algorithms. The IPMA has the capacity to store the biomedical data for continuous studies and can be used to infer other respiratory diseases. Quadratic kernel-free non-linear Support Vector Machine (QSVM) and Decision Tree (DT) were applied on three datasets with data of cough, speech, body temperature, heart rate, and SpO2, obtaining an Accuracy rate (ACC) and Area Under the Curve (AUC) of approximately up to 88.0% and 0.85, respectively, as well as an ACC up to 99% and AUC = 0.94, respectively, for COVID-19 infection inference. When applied to the data acquired with the IMPA, these algorithms achieved 100% accuracy. Regarding the easiness of using the equipment, 36 volunteers reported that the IPMA has a high usability, according to results from two metrics used for evaluation: System Usability Scale (SUS) and Post Study System Usability Questionnaire (PSSUQ), with scores of 85.5 and 1.41, respectively. In light of the worldwide needs for smart equipment to help fight the COVID-19 pandemic, this new equipment may help with the screening of COVID-19 through data collected from biomedical signals and cough sounds, as well as the use of machine learning algorithms.

Machine Learning Approach for Fatigue Estimation in Sit-to-Stand Exercise.

Physical exercise (PE) has become an essential tool for different rehabilitation programs. High-intensity exercises (HIEs) have been demonstrated to provide better results in general health conditions, compared with low and moderate-intensity exercises. In this context, monitoring of a patients' condition is essential to avoid extreme fatigue conditions, which may cause physical and physiological complications. Different methods have been proposed for fatigue estimation, such as: monitoring the subject's physiological parameters and subjective scales. However, there is still a need for practical procedures that provide an objective estimation, especially for HIEs. In this work, considering that the sit-to-stand (STS) exercise is one of the most implemented in physical rehabilitation, a computational model for estimating fatigue during this exercise is proposed. A study with 60 healthy volunteers was carried out to obtain a data set to develop and evaluate the proposed model. According to the literature, this model estimates three fatigue conditions (low, moderate, and high) by monitoring 32 STS kinematic features and the heart rate from a set of ambulatory sensors (Kinect and Zephyr sensors). Results show that a random forest model composed of 60 sub-classifiers presented an accuracy of 82.5% in the classification task. Moreover, results suggest that the movement of the upper body part is the most relevant feature for fatigue estimation. Movements of the lower body and the heart rate also contribute to essential information for identifying the fatigue condition. This work presents a promising tool for physical rehabilitation.

BCI-Based Control for Ankle Exoskeleton T-FLEX: Comparison of Visual and Haptic Stimuli with Stroke Survivors.

Brain-computer interface (BCI) remains an emerging tool that seeks to improve the patient interaction with the therapeutic mechanisms and to generate neuroplasticity progressively through neuromotor abilities. Motor imagery (MI) analysis is the most used paradigm based on the motor cortex's electrical activity to detect movement intention. It has been shown that motor imagery mental practice with movement-associated stimuli may offer an effective strategy to facilitate motor recovery in brain injury patients. In this sense, this study aims to present the BCI associated with visual and haptic stimuli to facilitate MI generation and control the T-FLEX ankle exoskeleton. To achieve this, five post-stroke patients (55-63 years) were subjected to three different strategies using T-FLEX: stationary therapy (ST) without motor imagination, motor imagination with visual stimulation (MIV), and motor imagination with visual-haptic inducement (MIVH). The quantitative characterization of both BCI stimuli strategies was made through the motor imagery accuracy rate, the electroencephalographic (EEG) analysis during the MI active periods, the statistical analysis, and a subjective patient's perception. The preliminary results demonstrated the viability of the BCI-controlled ankle exoskeleton system with the beta rebound, in terms of patient's performance during MI active periods and satisfaction outcomes. Accuracy differences employing haptic stimulus were detected with an average of 68% compared with the 50.7% over only visual stimulus. However, the power spectral density (PSD) did not present changes in prominent activation of the MI band but presented significant variations in terms of laterality. In this way, visual and haptic stimuli improved the subject's MI accuracy but did not generate differential brain activity over the affected hemisphere. Hence, long-term sessions with a more extensive sample and a more robust algorithm should be carried out to evaluate the impact of the proposed system on neuronal and motor evolution after stroke.

An Optimized Self-Compensated Solution for Temperature and Strain Cross-Sensitivity in FBG Interrogators Based on Edge Filter.

Optical fiber sensors based on fiber Bragg gratings (FBGs) are prone to measurement errors if the cross-sensitivity between temperature and strain is not properly considered. This paper describes a self-compensated technique for canceling the undesired influence of temperature in strain measurement. An edge-filter-based interrogator is proposed and the central peaks of two FBGs (sensor and reference) are matched with the positive and negative slopes of a Fabry-Perot interferometer that acts as an optical filter. A tuning process performed by the grey wolf optimizer (GWO) algorithm is required to determine the optimal spectral characteristics of each FBG. The interrogation range is not compromised by the proposed technique, being determined by the spectral characteristics of the optical filter in accordance with the traditional edge-filtering interrogation. Simulations show that, by employing FBGs with optimal characteristics, temperature variations of 30 °C led to an average relative error of 3.4% for strain measurements up to 700µÏµ. The proposed technique was experimentally tested under non-ideal conditions: two FBGs with spectral characteristics different from the optimized results were used. The temperature sensibility decreased by 50.8% as compared to a temperature uncompensated interrogation system based on an edge filter. The non-ideal experimental conditions were simulated and the maximum error between theoretical and experimental data was 5.79%, proving that the results from simulation and experimentation are compatible.

Primary cutaneous osteosarcoma of the scalp in an immunosuppressed individual: A case report and review of the literature.

We report a case of a 76-year-old man presenting with a 12-month history of a solitary lesion on his scalp. The histopathology was consistent with a grade 2/3 osteosarcoma extending to the subcutis. Full-body imaging excluded any involvement of the underlying bony tissue or solid organ malignancy, thus a diagnosis of primary cutaneous osteosarcoma (PCO) was made. Given the exceedingly rare nature of PCO, we discuss the clinico-pathological features of this case and those previously reported in the literature.

Polymer Optical Fiber-Based Integrated Instrumentation in a Robot-Assisted Rehabilitation Smart Environment: A Proof of Concept.

Advances in robotic systems for rehabilitation purposes have led to the development of specialized robot-assisted rehabilitation clinics. In addition, advantageous features of polymer optical fiber (POF) sensors such as light weight, multiplexing capabilities, electromagnetic field immunity and flexibility have resulted in the widespread use of POF sensors in many areas. Considering this background, this paper presents an integrated POF intensity variation-based sensor system for the instrumentation of different devices. We consider different scenarios for physical rehabilitation, resembling a clinic for robot-assisted rehabilitation. Thus, a multiplexing technique for POF intensity variation-based sensors was applied in which an orthosis for flexion/extension movement, a modular exoskeleton for gait assistance and a treadmill were instrumented with POF angle and force sensors, where all the sensors were integrated in the same POF system. In addition, wearable sensors for gait analysis and physiological parameter monitoring were also proposed and applied in gait exercises. The results show the feasibility of the sensors and methods proposed, where, after the characterization of each sensor, the system was implemented with three volunteers: one for the orthosis on the flexion/extension movements, one for the exoskeleton for gait assistance and the other for the free gait analysis using the proposed wearable POF sensors. To the authors' best knowledge, this is the first time that optical fiber sensors have been used as a multiplexed and integrated solution for the simultaneous assessment of different robotic devices and rehabilitation protocols, where such an approach results in a compact, fully integrated and low-cost system, which can be readily employed in any clinical environment.

3D-Printing Techniques on the Development of Multiparameter Sensors Using One FBG.

We report the development of a fiber Bragg grating (FBG) sensor for multiparameter sensing using only one FBG. The FBG was half-embedded in a 3D-printed structure, which resulted in a division of the grating spectrum creating two peaks with different sensitivities with respect to different physical parameters. A numerical analysis of the proposed technique was performed using the coupled-mode theory with modified transfer matrix formulation. Then, experimental analyses were performed as function of temperature, strain and force, where the peaks showed different sensitivities in all analyzed cases. Such results enable the application of a technique for simultaneous measurement of multiple physical parameters using both peaks and the full width half maximum of the FBG embedded in a 3D structure. In the simultaneous multiparameter assessment, the proposed sensor system was able to estimate the three tested parameters (strain, temperature and force) with relative errors as low as 4%.

POF Smart Carpet: A Multiplexed Polymer Optical Fiber-Embedded Smart Carpet for Gait Analysis.

This paper presents the development of a smart carpet based on polymer optical fiber (POF) for ground reaction force (GRF) and spatio-temporal gait parameter assessment. The proposed carpet has 20 intensity variation-based sensors on one fiber with two photodetectors for acquisition, each one for the response of 10 closer sensors. The used multiplexing technique is based on side-coupling between the light sources and POF lateral sections in which one light-emitting diode (LED) is activated at a time, sequentially. Three tests were performed, two for sensor characterization and one for validation of the smart carpet, where the first test consisted of the application of calibrated weights on the top of each sensor for force characterization. In the second test, the foot was positioned on predefined points distributed on the carpet, where a mean relative error of 2.9% was obtained. Results of the walking tests on the proposed POF-embedded smart carpet showed the possibility of estimating the GRF and spatio-temporal gait parameters (step and stride lengths, cadence, and stance duration). The obtained results make possible the identification of gait events (stance and swing phases) as well as the stance duration and double support periods. The proposed carpet is a low-cost and reliable tool for gait analysis in different applications.

Polymer Optical Fiber Sensors in Healthcare Applications: A Comprehensive Review.

Advances in medicine and improvements in life quality has led to an increase in the life expectancy of the general population. An ageing world population have placed demands on the use of assistive technology and, in particular, towards novel healthcare devices and sensors. Besides the electromagnetic field immunity, polymer optical fiber (POF) sensors have additional advantages due to their material features such as high flexibility, lower Young's modulus (enabling high sensitivity for mechanical parameters), higher elastic limits, and impact resistance. Such advantages are well-aligned with the instrumentation requirements of many healthcare devices and in movement analysis. Aiming at these advantages, this review paper presents the state-of-the-art developments of POF sensors for healthcare applications. A plethora of healthcare applications are discussed, which include movement analysis, physiological parameters monitoring, instrumented insoles, as well as instrumentation of healthcare robotic devices such as exoskeletons, smart walkers, actuators, prostheses, and orthosis. This review paper shows the feasibility of using POF sensors in healthcare applications and, due to the aforementioned advantages, it is possible to envisage a further widespread use of such sensors in this research field in the next few years.

Perrogator: A Portable Energy-Efficient Interrogator for Dynamic Monitoring of Wavelength-Based Sensors in Wearable Applications.

In this paper, we report the development of a portable energy-efficient interrogator (Perrogator) for wavelength-based optical sensors. The interrogator is based on a compact solution encompassing a white light source and the spectral convolution between the sensor and a tunable filter, which is acquired by a photodetector, where a microcontroller has two functions: (i) To control the filter tuning and to (ii) acquire the photodetector signal. Then, the data is sent to a single-board computer for further signal processing. Furthermore, the employed single-board computer has a Wi-Fi module, which can be used to send the sensors data to the cloud. The proposed approach resulted in an interrogator with a resolution as high as 3.82 pm (for 15.64 nm sweeping range) and maximum acquisition frequency of about 210 Hz (with lower resolution ~15.30 pm). Perrogator was compared with a commercial fiber Bragg grating (FBG) interrogator for strain measurements and good agreement between both devices was found (1.226 pm/µÎµ for the commercial interrogator and 1.201 pm/µÎµ for the proposed approach with root mean square error of 0.0144 and 0.0153, respectively), where the Perrogator has the additional advantages of lower cost, higher portability and lower energy consumption. In order to demonstrate such advantages in conjunction with the high acquisition frequency allowed us to demonstrate two wearable applications using the proposed interrogation device over FBG and Fabry-Perot interferometer (FPI) sensors. In the first application, an FBG-embedded smart textile for knee angle assessment was used to analyze the gait of a healthy person. Due to the capability of reconstructing the FBG spectra, it was possible to employ a technique based on the FBG wavelength shift and reflectivity to decouple the effects of the bending angle and axial strain on the FBG response. The measurement of the knee angle as well as the estimation of the angular and axial displacements on the grating that can be correlated to the variations of the knee center of rotation were performed. In the second application, a FPI was embedded in a chest band for simultaneous measurement of breath and heart rates, where good agreement (error below 5%) was found with the reference sensors in all analyzed cases.

Effects of Selective Deafferentation on the Discharge Characteristics of Medial Rectus Motoneurons.

Medial rectus motoneurons receive two main pontine inputs: abducens internuclear neurons, whose axons course through the medial longitudinal fasciculus (MLF), and neurons in the lateral vestibular nucleus, whose axons project through the ascending tract of Deiters (ATD). Abducens internuclear neurons are responsible for conjugate gaze in the horizontal plane, whereas ATD neurons provide medial rectus motoneurons with a vestibular input comprising mainly head velocity. To reveal the relative contribution of each input to the oculomotor physiology, single-unit recordings from medial rectus motoneurons were obtained in the control situation and after selective deafferentation from cats with unilateral transection of either the MLF or the ATD. Both MLF and ATD transection produced similar short-term alterations in medial rectus motoneuron firing pattern, which were more drastic in MLF of animals. However, long-term recordings revealed important differences between the two types of lesion. Thus, while the effects of the MLF section were permanent, 2 months after ATD lesioning all motoneuronal firing parameters were similar to the control. These findings indicated a more relevant role of the MLF pathway in driving motoneuronal firing and evidenced compensatory mechanisms following the ATD lesion. Confocal immunocytochemistry revealed that MLF transection produced also a higher loss of synaptic boutons, mainly at the dendritic level. Moreover, 2 months after ATD transection, we observed an increase in synaptic coverage around motoneuron cell bodies compared with short-term data, which is indicative of a synaptogenic compensatory mechanism of the abducens internuclear pathway that could lead to the observed firing and morphological recovery.SIGNIFICANCE STATEMENT Eye movements rely on multiple neuronal circuits for appropriate performance. The abducens internuclear pathway through the medial longitudinal fascicle (MLF) and the vestibular neurons through the ascending tract of Deiters (ATD) are a dual system that supports the firing of medial rectus motoneurons. We report the effect of sectioning the MLF or the ATD pathway on the firing of medial rectus motoneurons, as well as the plastic mechanisms by which one input compensates for the lack of the other. This work shows that while the effects of MLF transection are permanent, the ATD section produces transitory effects. A mechanism based on axonal sprouting and occupancy of the vacant synaptic space due to deafferentation is the base for the mechanism of compensation on the medial rectus motoneuron.

Material features based compensation technique for the temperature effects in a polymer diaphragm-based FBG pressure sensor.

Fiber Bragg grating (FBG) based sensors have been applied to measure several parameters, such as pressure, vibration, liquid level, humidity, the concentration of chemical compounds, among others. An approach to measure parameters like liquid level, pressure and vibration are to embed the FBG on a diaphragm, which is generally made of a polymeric material. Nevertheless, the mechanical properties of polymers depend on temperature variation. For this reason, a polymer diaphragm can enhance the cross-sensitivity between the strain and temperature on an FBG sensor. In order to overcome this limitation, this paper presents a compensation technique for the temperature effects on an oblong polymer diaphragm-based FBG pressure sensor. The presented technique is based on the analytical model of the sensor, which takes into account the variation of the diaphragm properties with temperature obtained through a dynamic mechanical analysis of the diaphragm material. Results show that the developed technique reduces the sensor cross-sensitivity to about 1.74 Pa/°C. Furthermore, the presented technique is compared with the direct difference between the FBG strain and temperature responses presented in reference works. The comparison shows a better performance of the technique presented in this paper with respect to the cross-sensitivity and the root mean squared error.

Low-Cost Interrogation Technique for Dynamic Measurements with FBG-Based Devices.

Fiber Bragg gratings are widely used optical fiber sensors for measuring temperature and/or mechanical strain. Nevertheless, the high cost of the interrogation systems is the most important drawback for their large commercial application. In this work, an in-line Fabry-Perot interferometer based edge filter is explored in the interrogation of fiber Bragg grating dynamic measurements up to 5 kHz. Two devices an accelerometer and an arterial pulse wave probe were interrogated with the developed approach and the results were compared with a commercial interrogation monitor. The data obtained with the edge filter are in agreement with the commercial device, with a maximum RMSE of 0.05 being able to meet the requirements of the measurements. Resolutions of 3.6 pm and 2.4 pm were obtained, using the optical accelerometer and the arterial pulse wave probe, respectively.

Neural progenitor cell implants in the lesioned medial longitudinal fascicle of adult cats regulate synaptic composition and firing properties of abducens internuclear neurons.

Transplants of neural progenitor cells (NPCs) into the injured CNS have been proposed as a powerful tool for brain repair, but, to date, few studies on the physiological response of host neurons have been reported. Therefore, we explored the effects of NPC implants on the discharge characteristics and synaptology of axotomized abducens internuclear neurons, which mediate gaze conjugacy for horizontal eye movements. NPCs were isolated from the subventricular zone of neonatal cats and implanted at the site of transection in the medial longitudinal fascicle of adult cats. Abducens internuclear neurons of host animals showed a complete restoration of axotomy-induced alterations in eye position sensitivity, but eye velocity sensitivity was only partially regained. Analysis of the inhibitory and excitatory components of the discharge revealed a normal re-establishment of inhibitory inputs, but only partial re-establishment of excitatory inputs. Moreover, their inhibitory terminal coverage was similar to that in controls, indicating that there was ultimately no loss of inhibitory synaptic inputs. Somatic coverage by synaptophysin-positive contacts, however, showed intermediate values between control animals and animals that had undergone axotomy, likely due to partial loss of excitatory inputs. We also demonstrated that severed axons synaptically contacted NPCs, most of which were VEGF immunopositive, and that abducens internuclear neurons expressed the VEGF receptor Flk1. Together, our results suggest that VEGF neurotrophic support might underlie the increased inhibitory-to-excitatory balance observed in the postimplant cells. The noteworthy improvement of firing properties of injured neurons following NPC implants indicates that these cells might provide a promising therapeutic strategy after neuronal lesions.

Axons giving rise to the palisade endings of feline extraocular muscles display motor features.

Palisade endings are nerve specializations found in the extraocular muscles (EOMs) of mammals, including primates. They have long been postulated to be proprioceptors. It was recently demonstrated that palisade endings are cholinergic and that in monkeys they originate from the EOM motor nuclei. Nevertheless, there is considerable difference of opinion concerning the nature of palisade ending function. Palisade endings in EOMs were examined in cats to test whether they display motor or sensory characteristics. We injected an anterograde tracer into the oculomotor or abducens nuclei and combined tracer visualization with immunohistochemistry and α-bungarotoxin staining. Employing immunohistochemistry, we performed molecular analyses of palisade endings and trigeminal ganglia to determine whether cat palisade endings are a cholinergic trigeminal projection. We confirmed that palisade endings are cholinergic and showed, for the first time, that they, like extraocular motoneurons, are also immunoreactive for calcitonin gene-related peptide. Following tracer injection into the EOM nuclei, we observed tracer-positive palisade endings that exhibited choline acetyl transferase immunoreactivity. The tracer-positive nerve fibers supplying palisade endings also established motor terminals along the muscle fibers, as demonstrated by α-bungarotoxin. Neither the trigeminal ganglion nor the ophthalmic branch of the trigeminal nerve contained cholinergic elements. This study confirms that palisade endings originate in the EOM motor nuclei and further indicates that they are extensions of the axons supplying the muscle fiber related to the palisade. The present work excludes the possibility that they receive cholinergic trigeminal projections. These findings call into doubt the proposed proprioceptive function of palisade endings.