Potential of combined red and near-infrared photobiomodulation to mitigate pro-osteoclastic and inflammatory gene expression in human mandibular osteogenic cells.

Appropriate regeneration of jawbone after dental or surgical procedures relies on the recruitment of osteoprogenitor cells able to differentiate into matrix-producing osteoblasts. In this context, photobiomodulation (PBM) has emerged as promising therapy to improve tissue regeneration and to facilitate wound healing processes. The aim of this study was to determine the effect of PBM on human osteoprogenitor cells isolated from mandibular trabecular bone.Bone marrow stromal cell cultures were established from 4 donors and induced toward osteogenic differentiation for 14 days in a standard osteogenic assay. Cells were irradiated with a combined red/near-infrared (NIR) laser following different schedules and expression of osteogenic, matrix-related, osteoclastogenic and inflammatory genes was analyzed by quantitative PCR.Gene expression analysis revealed no overall effects of PBM on osteogenic differentiation. However, a statistically significant reduction was observed in the transcripts of COL1A1 and MMP13, two important genes involved in the bone matrix homeostasis. Most important, PBM significantly downregulated the expression of RANKL, IL6 and IL1B, three genes that are involved in both osteoclastogenesis and inflammation.In conclusion, PBM with a red/NIR laser did not modulate the osteogenic phenotype of mandibular osteoprogenitors but markedly reduced their expression of matrix-related genes and their pro-osteoclastogenic and pro-inflammatory profile.

Non-invasive estimation of muscle fibre size from high-density electromyography.

Because of the biophysical relation between muscle fibre diameter and the propagation velocity of action potentials along the muscle fibres, motor unit conduction velocity could be a non-invasive index of muscle fibre size in humans. However, the relation between motor unit conduction velocity and fibre size has been only assessed indirectly in animal models and in human patients with invasive intramuscular EMG recordings, or it has been mathematically derived from computer simulations. By combining advanced non-invasive techniques to record motor unit activity in vivo, i.e. high-density surface EMG, with the gold standard technique for muscle tissue sampling, i.e. muscle biopsy, here we investigated the relation between the conduction velocity of populations of motor units identified from the biceps brachii muscle, and muscle fibre diameter. We demonstrate the possibility of predicting muscle fibre diameter (R2  = 0.66) and cross-sectional area (R2  = 0.65) from conduction velocity estimates with low systematic bias (∼2% and ∼4% respectively) and a relatively low margin of individual error (∼8% and ∼16%, respectively). The proposed neuromuscular interface opens new perspectives in the use of high-density EMG as a non-invasive tool to estimate muscle fibre size without the need of surgical biopsy sampling. The non-invasive nature of high-density surface EMG for the assessment of muscle fibre size may be useful in studies monitoring child development, ageing, space and exercise physiology, although the applicability and validity of the proposed methodology need to be more directly assessed in these specific populations by future studies. KEY POINTS: Because of the biophysical relation between muscle fibre size and the propagation velocity of action potentials along the sarcolemma, motor unit conduction velocity could represent a potential non-invasive candidate for estimating muscle fibre size in vivo. This relation has been previously assessed in animal models and humans with invasive techniques, or it has been mathematically derived from simulations. By combining high-density surface EMG with muscle biopsy, here we explored the relation between the conduction velocity of populations of motor units and muscle fibre size in healthy individuals. Our results confirmed that motor unit conduction velocity can be considered as a novel biomarker of fibre size, which can be adopted to predict muscle fibre diameter and cross-sectional area with low systematic bias and margin of individual error. The proposed neuromuscular interface opens new perspectives in the use of high-density EMG as a non-invasive tool to estimate muscle fibre size without the need of surgical biopsy sampling.

Identification of Spared and Proportionally Controllable Hand Motor Dimensions in Motor Complete Spinal Cord Injuries Using Latent Manifold Analysis.

The loss of bilateral hand function is a debilitating challenge for millions of individuals that suffered a motor-complete spinal cord injury (SCI). We have recently demonstrated in eight tetraplegic individuals the presence of highly functional spared spinal motor neurons in the extrinsic muscles of the hand that are still capable of generating proportional flexion and extension signals. In this work, we hypothesized that an artificial intelligence (AI) system could automatically learn the spared electromyographic (EMG) patterns that encode the attempted movements of the paralyzed digits. We constrained the AI to continuously output the attempted movements in the form of a digital hand so that this signal could be used to control any assistive system (e.g. exoskeletons, electrical stimulation). We trained a convolutional neural network using data from 13 uninjured (control) participants and 8 tetraplegic participants (7 motor-complete, 1 incomplete) to study the latent space learned by the AI. Our model can automatically differentiate between eight different hand movements, including individual finger flexions, grasps, and pinches, achieving a mean accuracy of 98.3% within the SCI group. Analysis of the latent space of the model revealed that proportionally controllable movements exhibited an elliptical path, while movements lacking proportional control followed a chaotic trajectory. We found that proportional control of a movement can only be correctly estimated if the latent space embedding of the movement follows an elliptical path (correlation = 0.73; p < 0.001). These findings emphasize the reliability of the proposed system for closed-loop applications that require an accurate estimate of spinal cord motor output.

Simultaneous Estimation of Digit Tip Forces and Hand Postures in a Simulated Real-Life Condition With High-Density Electromyography and Deep Learning.

In myoelectric control, continuous estimation of multiple degrees of freedom has an important role. Most studies have focused on estimating discrete postures or forces of the human hand but for a practical prosthetic system, both should be considered. In daily life activities, hand postures vary for grasping different objects and the amount of force exerted on each fingertip depends on the shape and weight of the object. This study aims to investigate the feasibility of continuous estimation of multiple degrees of freedom. We proposed a reach and grasp framework to study both absolute fingertip forces and hand movement types using deep learning techniques applied to high-density surface electromyography (HD-sEMG). Four daily life grasp types were examined and absolute fingertip forces were simultaneously estimated while grasping various objects, along with the grasp types. We showed that combining a 3-dimensional Convolutional Neural Network (3DCNN) with a Long Short-term Memory (LSTM) can reliably and continuously estimate the digit tip forces and classify different hand postures in human individuals. The mean absolute error (MAE) and Pearson correlation coefficient (PCC) results of the force estimation problem across all fingers and subjects were 0.46 ± 0.23 and 0.90 ± 0.03% respectively and for the classification problem, they were 0.04 ± 0.01 and 0.97 ± 0.02%. The results demonstrated that both absolute digit tip forces and hand postures can be successfully estimated through deep learning and HD-sEMG.

Low-frequency Motor Cortex EEG Predicts Four Rates of Force Development.

The movement-related cortical potential (MRCP) is a low-frequency component of the electroencephalography (EEG) signal that originates from the motor cortex and surrounding cortical regions. As the MRCP reflects both the intention and execution of motor control, it has the potential to serve as a communication interface between patients and neurorehabilitation robots. In this study, we investigated the EEG signal recorded centered at the Cz electrode with the aim of decoding four rates of force development (RFD) during isometric contractions of the tibialis anterior muscle. The four levels of RFD were defined with respect to the maximum voluntary contraction (MVC) of the muscle as follows: Slow (20% MVC/s), Medium (30% MVC/s), Fast (60% MVC/s), and Ballistic (120% MVC/s). Three feature sets were assessed for describing the EEG traces in the classification process. These included: (i) MRCP Morphological Characteristics in the δ-band, such as timing and amplitude; (ii) MRCP Statistical Characteristics in the δ-band, such as standard deviation, mean, and kurtosis; and (iii) Wideband Time-frequency Features in the 0.1-90 Hz range. The four levels of RFD were accurately classified using a support vector machine. When utilizing the Wideband Time-frequency Features, the accuracy was 83% ± 9% (mean ± SD). Meanwhile, when using the MRCP Statistical Characteristics, the accuracy was 78% ± 12% (mean ± SD). The analysis of the MRCP waveform revealed that it contains highly informative data on the planning, execution, completion, and duration of the isometric dorsiflexion task. The temporal analysis emphasized the importance of the δ-band in translating to motor command, and this has promising implications for the field of neural engineering systems.

Learning a Hand Model from Dynamic Movements Using High-Density EMG and Convolutional Neural Networks.

OBJECTIVE: Surface electromyography (sEMG) can sense the motor commands transmitted to the muscles. This work presents a deep learning method that can decode the electrophysiological activity of the forearm muscles into the movements of the human hand. METHODS: We have recorded the kinematics and kinetics of the hand during a wide range of grasps and individual digit movements that cover 22 degrees of freedom of the hand at slow (0.5 Hz) and comfortable (1.5 Hz) movement speeds in 13 healthy participants. The input of the model consists of 320 non-invasive EMG sensors placed on the extrinsic hand muscles. RESULTS: Our network achieves accurate continuous estimation of both kinematics and kinetics, surpassing the performance of comparable networks reported in the literature. By examining the latent space of the network, we find evidence that it mapped EMG activity into the anatomy of the hand at the individual digit level. In contrast to what is observed from the low-pass filtered EMG and linear decoding approaches, we found that the full-bandwidth EMG (monopolar unfiltered) signals during synergistic and individual digit movements contain distinct neural embeddings that encode each movement of the human hand. These manifolds consistently represent the anatomy of the hand and are generalized across participants. Moreover, we found a task-specific distribution of the embeddings without any presence of correlated activations during multi- and individual-digit tasks. CONCLUSION/SIGNIFICANCE: The proposed method could advance the control of assistive hand devices by providing a robust and intuitive interface between muscle signals and hand movements.

Deep Learning for Robust Decomposition of High-Density Surface EMG Signals.

Blind source separation (BSS) algorithms, such as gradient convolution kernel compensation (gCKC), can efficiently and accurately decompose high-density surface electromyography (HD-sEMG) signals into constituent motor unit (MU) action potential trains. Once the separation matrix is blindly estimated on a signal interval, it is also possible to apply the same matrix to subsequent signal segments. Nonetheless, the trained separation matrices are sub-optimal in noisy conditions and require that incoming data undergo computationally expensive whitening. One unexplored alternative is to instead use the paired HD-sEMG signal and BSS output to train a model to predict MU activations within a supervised learning framework. A gated recurrent unit (GRU) network was trained to decompose both simulated and experimental unwhitened HD-sEMG signal using the output of the gCKC algorithm. The results on the experimental data were validated by comparison with the decomposition of concurrently recorded intramuscular EMG signals. The GRU network outperformed gCKC at low signal-to-noise ratios, proving superior performance in generalising to new data. Using 12 seconds of experimental data per recording, the GRU performed similarly to gCKC, at rates of agreement of 92.5% (84.5%-97.5%) and 94.9% (88.8%-100.0%) respectively for GRU and gCKC against matched intramuscular sources.

Laser dentistry in daily practice during the COVID-19 pandemic: Benefits, risks and recommendations for safe treatments.

The COVID-19 pandemic forced dental professionals to cope with an unexpected challenge and caused an abrupt cessation of conventional care practices. The high degree of contagiousness as well as the diffusion of the virus through the air and droplets via respiratory transmission placed dental professionals at top-level risk of contracting and spreading the disease. General recommendations were announced in different countries, including patient distancing, air ventilation, surface and instrument sanitization, and the wearing of suitable masks and shields. However, many dental treatments are performed using lasers, and some specific precautions must be added to conventional procedures to ensure the advantages of this technology to patients because of the particular tissue­matter interaction effects of laser wavelengths. Based on the literature, the authors evaluated all of using laser wavelengths to analyze the risk and the benefits of using lasers in daily dental practice, and to provide safety recommendations during pandemic. An unrestricted search of indexed databases was performed. Laser use effects were categorized into: 1) explosive processes that produce tissue ablation and aerosol formation; 2) thermal actions that create vaporization and smoke plume; 3) photobiomodulation of the cells; and 4) enhanced chemical activity. Knowledge of the device functions and choice of adequate parameters will reduce aerosol and plume formation, and the application of suction systems with high flow volume and good filtration close to the surgical site will avoid virus dissemination during laser use. In the categories that involve low energy, the beneficial effects of lasers are available and sometimes preferable during this pandemic because only conventional precautions are required. Lasers maintain the potential to add benefits to dental practice even in the COVID-19 era, but it is necessary to know how lasers work to utilize these advantages. The great potential of laser light, with undiscovered limits, may provide a different path to face the severe health challenges of this pandemic.

Improvement in the Synthesis Conditions and Studying the Physicochemical Properties of the Zeolite Li-A(BW) Obtained from a Kaolinitic Rock.

Crystallization of zeolite Li-A(BW) from kaolinite (Standard Porcelain by the IMERYS Minerals Ltd) through a conventional hydrothermal treatment is here achieved for the first time with no additives as reported in the literature. Moreover lower kaolin calcination temperatures and lower synthesis temperatures are tested and verified in this work. The synthesis process is rather simple as the reaction of kaolinite with alkali occurs very readily after calcination of at 650 °C. Metakaolin is mixed with calculated amount of aluminum hydroxide and lithium hydroxide and the experiment is performed at ambient pressure and 180 ± 0.1 °C. Li-A(BW) is characterized by powder X-ray diffraction, high temperature X-ray diffraction, scanning electron microscopy, inductively coupled plasma optical emission spectrometry, thermal analysis and infrared spectroscopy. Calculation of cell parameters (through Rietveld Refinement) and density, specific surface and pore size are also achieved. The amount of amorphous phase in the synthesis powders is estimated with quantitative phase analysis using the combined Rietveld and reference intensity ratio methods. The results become notably attractive in view of a possible industrial transfer of the synthesis protocol.

Focal epithelial hyperplasia in a human immuno-deficiency virus patient treated with laser surgery.

Focal epithelial hyperplasia (FEH), or Heck's disease, is a rare disease of the oral mucosa; it is mostly found in children or young adults who are immunosuppressed and who live in regions with low socioeconomic status. It is characterized by asymptomatic papules on the oral mucosa, gingiva, tongue, and lips. Healing can be spontaneous, and treatment is indicated if there are aesthetic or functional complications. Human papillomavirus, especially genotypes 13 and 32, has been associated with FEH and is detected in the majority of lesions. Histopathologically, FEH is characterized by parakeratosis, epithelial hyperplasia, focal acanthosis, and fusion and horizontal outgrowth of epithelial ridges. A 37-year-old male patient was referred to the Department of Oral and Maxillofacial Sciences at the Sapienza University of Rome, complaining of numerous exophytic lesions in his mouth. He stated that the lesions were not painful but he had experienced occasional bleeding after incidental masticatory trauma. He had received no previous treatment for the oral lesions. His medical history revealed that he was human immuno-deficiency virus positive and was a smoker with numerous, asymptomatic oral papules clinically and histologically corresponding to FEH. The labial and buccal mucosa were especially affected by lesions. Surgical treatment was performed using a 532-nm potassium titanyl phosphate laser (SmartLite, Deka, Florence, Italy) in continuous mode with a 300 µm fiber and power of 1.4 W (power density 1980.22 W/cm(2)). After anesthesia without vasoconstrictors, the lesions were tractioned with sutures or an Allis clamp and then completely excised. The lesions were preserved in 10% formalin for histological examination, which confirmed the clinical diagnosis of FEH. In this case, the laser allowed excellent control of bleeding, without postoperative sutures, and optimal wound healing.

Observation of pain control in patients with bisphosphonate-induced osteonecrosis using low level laser therapy: preliminary results.

BACKGROUND: Bisphosphonate-related osteonecrosis of the jaw (BRONJ) is an adverse side effect associated with bisphosphonate (BP) therapy, especially when parenteral BP administration is used. Patients affected by BRONJ present wide areas of exposed necrotic bone, particularly after surgical oral procedures. The main symptom is pain that is poorly controlled by common analgesic drugs. Recently, many studies have pointed to the beneficial effect of low-level laser therapy (LLLT) in pain reduction for many pathological conditions. The purpose of this study is to investigate whether LLLT could be helpful in managing BRONJ by reducing the problems associated with this condition and the use of analgesic drugs. METHODS: Twelve patients affected by BRONJ were monitored at the Complex Operative Unit of Oral Pathology. Among these patients, only seven referred to pain in necrotic areas and were recruited for LLLT. Laser applications were performed with a double diode laser simultaneously emitting at two different wavelengths (λ = 650 nm and λ = 904-910 nm, spot size = 8 mm). All of the patients were irradiated with a fluence of 0.053 J/cm(2) for 15 min five times over a period of 2 weeks, in a non-contact mode, ∼1 mm from the pathologic area. The patient's maximum and minimum pain was recorded using a numeric rating scale (NRS) evaluation before and after the treatment. Statistical analysis was performed using the Kruskal-Wallis test. RESULTS: Six patients showed significant pain reduction, and only one patient indicated a worsening of the symptoms, which was probably related to a reinfection of the BRONJ site, which occurred during the study. A statistically significant difference (p < 0.05) was found between the NRS rates before and after the protocol. CONCLUSIONS: This pilot study suggests that LLLT may be a valid technique to support the treatment of BRONJ-related pain, even though the low number of cases in this study does not permit any conclusive consideration.