A Residual U-Net Neural Network for Seismocardiogram Denoising and Analysis During Physical Activity.

Seismocardiogram (SCG) signals are noninvasively obtained cardiomechanical signals containing important features for cardiovascular health monitoring. However, these signals are prone to contamination by motion noise, which can significantly impact accuracy and robustness of the measurements. A deep learning model based on the U-Net architecture is proposed to recover SCG signals contaminated by motion noise induced by walking. The model performance was evaluated through qualitative visualization, as well as quantitative analyses. Quantitative analyses included distance-based comparisons before and after applying our model. Analyses also included assessments of the model's efficacy in improving the performance of downstream tasks related to health parameter estimation during walking. Experimental findings revealed that the denoising model improved similarity to clean signals by approximately 90%. The performance of the model in enhancing heart rate estimation demonstrated a mean absolute error of 1.21 BPM and a root-mean-squared error (RMSE) of 1.97 BPM during walking after denoising with 9.16 BPM and 10.38 BPM improvements, respectively, compared to without denoising. Furthermore, the RMSEs of aortic opening and aortic closing time estimation after denoising for one dataset with catheter ground truth were 7.29 ms and 19.71 ms during walking, respectively, with 50.33 ms and 51.91 ms RMSE improvements compared to without denoising. And for another dataset with ICG-derived PEP ground truth, the RMSE of aortic opening time estimation after denoising was 10.21 ms during walking, with 38.74 ms RMSE improvement compared to without denoising. The proposed model attenuates motion noise from corrupted SCG signals while preserving cardiac information. This development paves the way for improved ambulatory cardiac health monitoring using wearable accelerometers during daily activities.

Relationship Between Diabetes Mellitus and Periodontal/Peri-Implant Disease: A Contemporaneous Review.

The prevalence of diabetes mellitus (DM), a major chronic disease and a leading cause of death and disability around the world, is rising. According to the latest data, the global prevalence of DM has increased to 463 million (9.3% of adults) in 2019 and is estimated to reach 700 million by 2045. Periodontal disease, result of periodontium inflammation, is a common, chronic disease and has long been considered one of the complications of DM. Moreover, literature reflects a spectrum of conflicting viewpoints on the effect of diabetic conditions on the implant treatment strategies. The current review aims to update the recent epidemiologic evidence regarding the relationship between DM and periodontal/peri-implant disease, emphasising the effects of glycaemic control on the severity of these diseases and describing the pathobiological mechanisms underlying this association. This review's findings indicate a bidirectional relationship between DM and periodontal/peri-implant disease and that this relationship seems causal, implying that controlling these two diseases might help prevent each other's incidence. Additionally, the severity of periodontal/peri-implant disease is directly related to metabolic control. Although patients with diabetes can obtain implant success similar to those in systemically healthy individuals, an increased risk of peri-implantitis has been reported in DM patients. Therefore, the importance of glycaemic control and maintaining proper oral hygiene cannot be overstated.

ITC-net-audio-5: an audio streaming dataset for application identification in network traffic classification.

OBJECTIVES: An essential aspect of network traffic classification is application identification. This involves capturing and analyzing the traffic patterns of applications. There are a few publicly available datasets that specifically capture streaming data from network-based applications. Therefore, our objective is to generate an up-to-date dataset with a focus on audio streaming data. This dataset can be a valuable resource for identifying audio streaming applications in the field of network traffic classification. DATA DESCRIPTION: The dataset contains network traffic captured during audio streaming communications on five trending applications: Google Meet, Skype, Telegram, WhatsApp, and SoundCloud. It includes 500 files in PCAP format captured by Wireshark and PCAPdroid tools during voice calls and online music playback. The concurrent utilization of these tools facilitates the avoidance of capturing background traffic.

A Comparison of Normalization Techniques for Individual Baseline-Free Estimation of Absolute Hypovolemic Status Using a Porcine Model.

Hypovolemic shock is one of the leading causes of death in the military. The current methods of assessing hypovolemia in field settings rely on a clinician assessment of vital signs, which is an unreliable assessment of hypovolemia severity. These methods often detect hypovolemia when interventional methods are ineffective. Therefore, there is a need to develop real-time sensing methods for the early detection of hypovolemia. Previously, our group developed a random-forest model that successfully estimated absolute blood-volume status (ABVS) from noninvasive wearable sensor data for a porcine model (n = 6). However, this model required normalizing ABVS data using individual baseline data, which may not be present in crisis situations where a wearable sensor might be placed on a patient by the attending clinician. We address this barrier by examining seven individual baseline-free normalization techniques. Using a feature-specific global mean from the ABVS and an external dataset for normalization demonstrated similar performance metrics compared to no normalization (normalization: R2 = 0.82 ± 0.025|0.80 ± 0.032, AUC = 0.86 ± 5.5 × 10-3|0.86 ± 0.013, RMSE = 28.30 ± 0.63%|27.68 ± 0.80%; no normalization: R2 = 0.81 ± 0.045, AUC = 0.86 ± 8.9 × 10-3, RMSE = 28.89 ± 0.84%). This demonstrates that normalization may not be required and develops a foundation for individual baseline-free ABVS prediction.

Leveraging Physiological Markers to Quantify the Transient Effects of Traumatic Stress and Non-Invasive Neuromodulation.

Millions around the world suffer from traumatic stress (stress caused by traumatic memories). Transcutaneous cervical vagus nerve stimulation (tcVNS) has been shown to counteract physiological changes associated with traumatic stress. However, little is known regarding the approximate timecourse of tcVNS effects. This knowledge of how quickly tcVNS takes effect is needed to optimize closed-loop tcVNS systems that can mitigate traumatic stress in a timely manner. To address this gap, we studied N=26 participants with history of prior trauma. Participants wore electrocardiogram, photoplethysmogram, seismocardiogram, and respiratory effort sensors throughout a double-blind protocol involving traumatic stress and active tcVNS (n=12) or sham stimulation (n=14). From the physiological signals, we extracted cardiovascular and respiratory markers and studied their dynamics during the traumatic stress and stimulation conditions. We decoupled the short-term transient responses from longer-term cumulative changes by centering each condition's response with respect to data immediately prior to the condition. We thereby elucidate a diverse set of transient physiological responses to tcVNS and traumatic stress. These responses demonstrate that tcVNS-induced changes occur within seconds and have the potential to reduce acute physiological manifestations of traumatic stress.Clinical relevance- Traumatic stress can overpower an individual within seconds and often occurs outside the clinic. This analysis focuses on transient physiological responses to traumatic memories and tcVNS captured using multimodal physiological sensing. We demonstrate that tcVNS-induced changes occur within seconds and have the potential to mitigate some of the short-term effects of traumatic stress.

Clinical Trials of Mesenchymal Stem Cells for the Treatment of COVID 19.

Mesenchymal Stem Cells (MSCs) are being investigated as a treatment for a novel viral disease owing to their immunomodulatory, anti-inflammatory, tissue repair and regeneration characteristics, however, the exact processes are unknown. MSC therapy was found to be effective in lowering immune system overactivation and increasing endogenous healing after SARS-CoV-2 infection by improving the pulmonary microenvironment. Many studies on mesenchymal stem cells have been undertaken concurrently, and we may help speed up the effectiveness of these studies by collecting and statistically analyzing data from them. Based on clinical trial information found on clinicaltrials. gov and on 16 November 2020, which includes 63 clinical trials in the field of patient treatment with COVID-19 using MSCs, according to the trend of increasing studies in this field, and with the help of meta-analysis studies, it is possible to hope that the promise of MSCs will one day be realized. The potential therapeutic applications of MSCs for COVID-19 are investigated in this study.

Scaling and root planing for a patient with perforated palate caused by mucormycosis: A case report.

Some diseases like mucormycosis can lead to palatal perforation which can cause limitations for dental and oral care for the patients. Nasal septal buttons may be an effective solution according to the literature.

Application of Platelet-Rich Fibrin and Bone Morphogenetic Protein for Full-Mouth Implant-Based Oral Rehabilitation in a Case of Mandibular Osteoradionecrosis.

Osteoradionecrosis (ORN) is a debilitating complication following radiation therapy, which in the head and neck region, occurs most frequently in the mandible. Although ORN is rare, it is complex and multifactorial and requires appropriate management. Manipulation of bone in patients with head and neck cancers before radiotherapy can cause ORN. In this report, we aim to present successful insertion of four dental implants in the interforaminal segment combined with application of platelet-rich fibrin and bone morphogenetic protein in a 60-year-old male with stable ORN in the posterior regions of the mandible.

Real-Time Seismocardiogram Feature Extraction Using Adaptive Gaussian Mixture Models.

Wearable systems can provide accurate cardiovascular evaluations by estimating hemodynamic indices in real-time. Key hemodynamic parameters can be non-invasively estimated using the seismocardiogram (SCG), a cardiomechanical signal whose features link to cardiac events like aortic valve opening (AO) and closing (AC). However, tracking a single SCG feature is unreliable due to physiological changes, motion artifacts, and external vibrations. This work proposes an adaptable Gaussian Mixture Model (GMM) to track multiple AO/AC correlated features in quasi-real-time from the SCG. The GMM calculates the likelihood of an extremum being an AO/AC feature for each SCG beat. The Dijkstra algorithm selects heartbeat-related extrema, and a Kalman filter updates the GMM parameters while filtering features. Tracking accuracy is tested on a porcine hypovolemia dataset with varying noise levels. Blood volume loss estimation accuracy is also evaluated using the tracked features on a previously developed model. Experimental results show a 4.5 ms tracking latency and average root mean square errors (RMSE) of 1.47 ms for AO and 7.67 ms for AC at 10 dB noise, and 6.18 ms for AO and 15.3 ms for AC at -10 dB noise. When considering all AO/AC correlated features, the combined RMSE remains in similar ranges, specifically 2.70 ms for AO and 11.91 ms for AC at 10 dB noise, and 7.50 ms for AO and 16.35 ms for AC at -10 dB noise. The proposed algorithm offers low latency and RMSE for all tracked features, making it suitable for real-time processing. These systems enable accurate, timely extraction of hemodynamic indices for many cardiovascular monitoring applications, including trauma care in field settings.

Relationship between Anger Expression in Mothers and Acceptance of Behavior Management Techniques in Pediatric Dentistry.

Statement of the Problem: The parental acceptance rate of the behavior management methods used in pediatric dentistry is influenced by various factors. Purpose: This study was aimed to investigate the relationship between mothers' anger expression and their acceptance of behavior management methods. Materials and Method: In this cross-sectional study, 110 mothers of children who had less than 12 years of age were recruited. They completed Spielberg's state-trait anger expression inventory (STAXI). The respondents watched an educational video that included explanations of seven behavior management methods. Then, they reported their acceptance of each of these methods using the visual analog scale (VAS). Results: The acceptance rates of behavior management methods from the highest to lowest included tell-show-do, pre-appointment behavior shaping, mouthpiece, voice control, general anesthesia, active restraint, and passive restraint, respectively. There was only a significant inverse relationship between the acceptance of the tell-show-do method and the anger expression (p< 0.05). There was no significant relationship between the acceptance of behavioral management methods and the previous history of a pediatric dental visit, age, and mothers' education. Conclusion: There was a significant inverse relationship between acceptance of the tell-show-do behavioral management method and mothers' anger expression. However, there is no significant relationship between other methods and mothers' anger expression. According to this study, there was a relation between mothers' ages and their acceptance of using a mouthpiece.

Synthetic seismocardiogram generation using a transformer-based neural network.

OBJECTIVE: To design and validate a novel deep generative model for seismocardiogram (SCG) dataset augmentation. SCG is a noninvasively acquired cardiomechanical signal used in a wide range of cardivascular monitoring tasks; however, these approaches are limited due to the scarcity of SCG data. METHODS: A deep generative model based on transformer neural networks is proposed to enable SCG dataset augmentation with control over features such as aortic opening (AO), aortic closing (AC), and participant-specific morphology. We compared the generated SCG beats to real human beats using various distribution distance metrics, notably Sliced-Wasserstein Distance (SWD). The benefits of dataset augmentation using the proposed model for other machine learning tasks were also explored. RESULTS: Experimental results showed smaller distribution distances for all metrics between the synthetically generated set of SCG and a test set of human SCG, compared to distances from an animal dataset (1.14× SWD), Gaussian noise (2.5× SWD), or other comparison sets of data. The input and output features also showed minimal error (95% limits of agreement for pre-ejection period [PEP] and left ventricular ejection time [LVET] timings are 0.03 ± 3.81 ms and -0.28 ± 6.08 ms, respectively). Experimental results for data augmentation for a PEP estimation task showed 3.3% accuracy improvement on an average for every 10% augmentation (ratio of synthetic data to real data). CONCLUSION: The model is thus able to generate physiologically diverse, realistic SCG signals with precise control over AO and AC features. This will uniquely enable dataset augmentation for SCG processing and machine learning to overcome data scarcity.

The Effect of External Cold and Vibration on Infiltration-Induced Pain in Children: A Randomized Clinical Trial.

Introduction: Children's fear of and anxiety about dental treatments are important problems in maintaining health. The anesthetic injection is the main cause of dental fear. One of the methods to reduce the infiltration-induced pain is to use external cold or vibration using the gate control system. Various devices have been used to apply cold and vibration, including the BUZZY device (BUZZY Company, Arizona). Studies have shown contradictory results for the effectiveness of cold and vibration. This study aimed to investigate the effect of cold and vibration versus cold alone on maxillary infiltration-induced pain and stress. Methods: Thirty children aged 6-12 years who required profound restoration of deciduous or permanent first molars were recruited in this randomized double-blind clinical trial. The anesthetic gel and BUZZY device were used in half of the children's jaws, and the anesthetic gel and the cold alone were used in the other half of the jaws. To measure stress from the heart rate, the Wong-Baker scale was used as the subjective scale, and the face, legs, activity, cry, consolability (FLACC) scale was used as the objective scale. Results: The FLACC score was significantly lower in the BUZZY group than in the cold-alone group, but the Wong-Baker scale and heart rate did not show a significant difference between the two groups. Conclusions: The BUZZY device can be effective in reducing infiltration-induced dental pain.

Comparison of Clinical and Radiographic Success between MTA and Biodentine in Pulpotomy of Primary Mandibular Second Molars with Irreversible Pulpitis: A Randomized Double-Blind Clinical Trial.

Introduction: Among the new therapeutic materials, MTA and Biodentine are recommended for pulpotomy and sealing the pulp. Considering the similar characteristics of these two materials and considering that their effects on the treatment of primary second molars with irreversible pulpitis have not been compared properly, this study aimed to compare clinical and radiographic success between MTA and Biodentine in pulpotomy of primary mandibular second molars with irreversible pulpitis. Materials and Methods: This study was conducted as a randomized double-blind clinical trial. Participants were selected according to inclusion criteria and 52 samples were randomly selected using random numbers table in group A. Then, patients in the next group B were matched with the first group in terms of age range and sex. In group A, the remaining pulp was covered with 2 mm MTA+ and in group B with 3 mm Biodentine. Participants were called for clinical evaluation every three months for 12 months (long-term follow-up). Radiographic evaluations were in the sixth and twelfth months. Results: Fischer's exact test showed that there was no significant difference between MTA and Biodentine in terms of clinical and radiographic success rates (P value = 1). According to the results of the Kaplan-Meier test, the survival rate in both pulp treatment methods was similar in symptomatic teeth. Conclusions: The results of this study showed that Biodentine properties are similar to MTA, and both materials show high clinical and radiographic success rates in long-term follow-up.

Granular cell odontogenic tumor: report of a rare case and a review of literature.

BACKGROUND: Granular cell odontogenic tumor (GCOT) is a rare neoplasm with about 45 cases reported in the literature. It usually occurs in the posterior mandible of middle-aged women. CASE PRESENTATION: We report a case of asymptomatic GCOT in the posterior mandible of a 28 years old female and provide a literature review of GCOT cases. Some unusual features such as root resorption, displacement of inferior tooth canal, and multilocular appearance were considerable in this case. CONCLUSIONS: Complete surgical excision of the lesion was beneficial for the patient.

Encapsulation of Satureja khuzistanica jamzad essential oil in chitosan nanoparticles with enhanced antibacterial and anticancer activities.

Satureja khuzistanica jamzad (SKJ), which is a member of Lamiaceae, has various proven effects such as antispasmodic and anti-inflammatory, anti-diabetic, antioxidant, and antifungal properties. However, the use of essential oil of plants is limited due to their inherent instability in the environment. Encapsulation with nanoparticles in the nanogel forms is one of their stabilization methods. The aim of this study was to synthesize nano-gel based on chitosan (CS) and extracts of SKJ essential oil, and to evaluate the antibacterial and anticancer activities. SKJ essential oil was extracted using water distillation method. Then, it was loaded on CS particles using two-step process as following: droplets formation and freezing. The Dynamic Light Scattering (DLS), Fourier transform infrared spectroscopy (FTIR), Scanning electron microscopy (SEM), and Zeta potential determination were used to evaluate the physical and chemical properties of CS-SKJ nanogel, which its result was acceptable. After confirmation of the loaded essential oil rate and releasing amount, the antibacterial effects were evaluated on five Gram-positive bacteria and five Gram-negative bacteria using microbroth dilution method. The encapsulation efficiency, size, polydispersity index, and zeta potential of nanoparticles were characterized were 30.74%, 571.00 nm, 0.451 and -67.2 mV, respectively. The results were significant not only on Gram-positive bacteria, but also on Gram-negative bacteria. The MIC range was between 7.8 and 500 µg/ml. The CS-SKJ nanogel has acceptable anticancer activities on KB and A549 tumor cell lines. the IC50 range was between 5.6 and 6.71 µg/ml. The results indicate that both CS particles and SKJ alone, and CS-SKJ nanogel could be considered as the outlook to produce new antimicrobial and anticancer drugs.

Sophisticated polycaprolactone/gelatin nanofibrous nerve guided conduit containing platelet-rich plasma and citicoline for peripheral nerve regeneration: In vitro and in vivo study.

Peripheral nerve injury (PNI) is a devastating condition that may result in loss of sensory function, motor function, or both. In the present study, we construct an electrospun nerve guide conduit (NGC) based on polycaprolactone (PCL) and gelatin filled with citicoline bearing platelet-rich plasma (PRP) gel as a treatment for PNI. The NGCs fabricated from PCL/Gel polymeric blend using the electrospinning technique. The characterizations demonstrated that the fabricated nanofibers were straight with the diameter of 708 ±â€¯476 nm, the water contact angle of 78.30 ±â€¯2.52°, the weight loss of 41.60 ±â€¯6.94% during 60 days, the tensile strength of 5.31 ±â€¯0.97 MPa, and the young's modulus of 3.47 ±â€¯0.10 GPa. The in vitro studies revealed that the PCL/Gel/PRP/Citi NGC was biocompatible and hemocompatible. The in vivo studies conducted on sciatic nerve injury in rats showed that the implantation of PCL/Gel/PRP/Citi NGC induced regeneration of nerve tissue, demonstrated with histopathological assessments. Moreover, the sciatic function index (SFI) value of -30.3 ±â€¯3.5 and hot plate latency time of 6.10 ±â€¯1.10 s revealed that the PCL/Gel/PRP/Citi NGCs recovered motor and sensory functions. Our findings implied that the fabricated NGC exhibited promising physicochemical and biological activates favorable for PNI treatment.

Formulation and Physicochemical Characterization of Cyclosporine Microfiber by Electrospinning.

Purpose: The objective of this study was to improve the permeability and water solubility rate of a poor water soluble drug, cyclosporine A (CsA). Methods: In order to improve the drug dissolution rate and oral bioavailability, electrospinning method was used as an approach to prepare. The fibers were evaluated for surface morphology, thermal characterizations, drug crystallinity, in vitro drug release and in vivo bioavailability studies. Results: Scanning electron microscope (SEM) results confirmed that the fibers were in microsize range and the size of the fibers was in the rang of 0.2 to 2 micron. Differential scanning calorimetry (DSC) and powder X-ray diffractometry (XRPD) analysis ensured that the crystalline lattice of drug were weakened or destroyed in the fibers. The drug release was 15.28%, 20.67%, and 32.84% from pure drug, fibers of formulation B, and formulation A, respectively. In vivo study results indicated that the bioavailability parameters of the optimized fiber formulation were improved and the maximum concentration (Cmax) were significantly higher for fibers (3001 ng/mL) than for pure drug (2550 ng/mL). The dissolution rate of the formulations was dependent on the nature and ratio of drug to carriers. Conclusion: The physicochemical properties showed that the optimized mixture of polyethylene glycol (PEG) and povidone (PVP) fibers could be an effective carrier for CsA delivery. PEG and PVP fibers improved the absolute bioavailability and drug dissolution rate with appropriate physicochemical properties.

Evaluation of a new lymphocyte proliferation assay based on cyclic voltammetry; an alternative method.

Lymphocyte proliferation assays are widely used to assess the cell-mediated immunity. Current in vitro testing methods that are being used have extensive applications but still more problematic, due to the technical complexity and the needs for specialized equipment and reagents. Electrochemical methods such as cyclic voltammetry represent a very promising tool for the development of label-free in vitro assays of cell proliferation and viability. Here, a novel procedure based on voltammetric behaviours of proliferating cells was fabricated. Results indicated that proliferation in cell cultures and whole blood can be monitored electrochemically using cyclic voltammetry. In the comparison with colorimetric (MTT) assay, cyclic voltammetry gave the best correlation with cell count data over a range of 1200-300,000 cells/well of a microplate. Besides the advantages of short assay duration (4 hours) and the rapidness, the possibility use of fresh blood without further processing, would give more accurate results because cells are monitoring in an intact environment. Cyclic voltammetry assay is an efficient analytical method, which can provide a simple platform for the electrochemical study of lymphocyte proliferation.

Molecular and Cellular Interactions of Allogenic and Autologus Mesenchymal Stem Cells with Innate and Acquired Immunity and Their Role in Regenerative Medicine.

Mesenchymal stem cells (MSCs), as major stem cells for cell therapy, have been studied from different aspects in preclinical and clinical settings for more than a decade. These cells modulate the immune system (humoral and cellular immune responses) in vitro by producing soluble factors (anti-inflammatory molecules) and/or making cell-cell contacts. Hence, they could be used in regenerative medicine, tissue engineering and immune therapy. MSCs-based therapy have been recently used for treatment of cancer regarding the migratory potential of these cells towards tumor cells which makes them considerable candidates, also for cell therapy in both allogeneic and autologous settings. So, this review attempts to focus on the factors secreted by MSCs such as cytokines, their functional role in mounting and controlling immune responses mediated by different immune cell subpopulations and their significance in regenerative medicine in clinical trials. Although, further studies remain to be done to increase our knowledge of regulating development mechanisms, homeostasis and tissue repair in order to provide new tools to implement the efficacy of cell therapy trials. Although MSCs have been proved safe and effective for cell therapy, there are still challenges to overcome before widely applying MSCs in clinic.

Tobacco Use and its Relationship with Health Complaints Among Employees of Kermanshah Province, Iran.

BACKGROUND: Identifying the pattern of tobacco use and its related factors in employees is crucial. This study aimed to investigate the pattern of tobacco use and its related factors in employees of Kermanshah Province, Iran. METHODS: In 2012, 7129 employees were investigated in a cross-sectional study using the census method. Data on tobacco use and on several chronic diseases obtained using a standardized questionnaire on noncommunicable diseases risk factors of the World Health Organization through face-to-face interviews. Statistical analysis was performed based on the Chi-square test and multivariate logistic regression. RESULTS: In general, the prevalence of tobacco use, smoking cigarettes, and smoking waterpipe was 9.9%, 8.9%, and 1.2% among the employees, respectively. Tobacco use was significantly higher in the age group over 40 (14.0%), in male gender (13.3%), in married individuals (10.8%) and in those with diploma and lower degree (16.4%), (P < 0.001). At the individual level, the odds ratio of tobacco use was 1.5 (95% confidence interval [CI]: 1.2-1.8) in hypertensive, 1.8 (95% CI: 1.2-2.6) in diabetic employees and 1.7 (95% CI: 1.3-2.3) in those with heart diseases, compared to healthy individuals. After adjusting for age, gender, marital status and educational level, there was not any significant relationship between tobacco use and health complaints and only the demographic variables remained significant. CONCLUSIONS: Preventive public health policies are mandatory especially in younger ages and male employees to promote their knowledge on disadvantages of tobacco use.