Silymarin Encapsulated Liposomal Formulation: An Effective Treatment Modality against Copper Toxicity Associated Liver Dysfunction and Neurobehavioral Abnormalities in Wistar Rats.

Wilson's disease causes copper accumulation in the liver and extrahepatic organs. The available therapies aim to lower copper levels by various means. However, a potent drug that can repair the damaged liver and brain tissue is needed. Silymarin has hepatoprotective, antioxidant, and cytoprotective properties. However, poor oral bioavailability reduces its efficacy. In this study, a "thin film hydration method" was used for synthesizing silymarin-encapsulated liposome nanoparticles (SLNPs) and evaluated them against copper toxicity, associated liver dysfunction and neurobehavioral abnormalities in Wistar rats. After copper toxicity induction, serological and behavioral assays were conducted to evaluate treatment approaches. Histological examination of the diseased rats revealed severe hepatocyte necrosis and neuronal vacuolation. These cellular degenerations were mild in rats treated with SLNPs and a combination of zinc and SLNPs (ZSLNPs). SLNPs also decreased liver enzymes and enhanced rats' spatial memory significantly (p = 0.006) in the diseased rats. During forced swim tests, SLNPs treated rats exhibited a 60-s reduction in the immobility period, indicating reduced depression. ZSLNPs were significantly more effective than traditional zinc therapy in decreasing the immobility period (p = 0.0008) and reducing liver enzymes, but not in improving spatial memory. Overall, SLNPs enhanced oral silymarin administration and managed copper toxicity symptoms.

The effects of surface inclination on gastrocnemius, soleus and tibialis anterior muscle activation during gait.

BACKGROUND: Inclined walking is associated with multiple musculoskeletal benefits and is considered a therapeutic exercise. Various patterns of increased and decreased muscle activation with inclined surfaces have been observed in normal muscles, with more focus on the proximal lower limb musculature. OBJECTIVE: The aim of this study was to assess the differences in electromyographic activation of gastrocnemius, soleus, and tibialis anterior at various inclined surfaces during gait. METHODS: Fourteen healthy male participants aged between 17-30 years walked at a self-selected speed at motor driven treadmill on 0, 2 and 4 degrees of inclination. EMG activity of the muscles was recorded using the Delsys Trigno surface EMG system. RESULTS: Results showed that muscular activation of tibialis anterior significantly decreased with increase in the level of inclination (p< 0.05). However, soleus, gastrocnemius medialis and gastrocnemius lateralis showed no significant differences (p> 0.05) in their muscular activation, and no noticeable trends were found. Furthermore, no significant difference was found between all the muscles at ground level and inclined level 2 and 4. CONCLUSION: These differences in activation patterns found in distal extremity can be useful for designing rehabilitation protocols in sports training and for patients with neurological and musculoskeletal pathologies.

DEAE-Dextran Coated AgNPs: A Highly Blendable Nanofiller Enhances Compressive Strength of Dental Resin Composites.

Micro-crack formation and resultant bacterial infiltration are major causes of secondary caries formation in dental resin-based composite restorations. Improving dental resin composites' mechanical and biological properties using highly bendable nanoparticles (NPs) can resolve this issue. This study aims to develop novel Diethylaminoethyl (DEAE)-Dextran silver nanoparticles (AgNPs) and subsequently modify composite resins with these NPs to enhance their mechanical and antibacterial properties. DEAE-Dextran AgNPs were successfully synthesized using a chemical reduction method that was confirmed with the help of ultraviolet-visible (UV-Vis) spectroscopy, scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), Zeta potential, and energy-dispersive X-ray spectroscopy (EDS). Antibacterial activity of a composite disc with DEAE-Dextran AgNPs was tested against Streptococcus mutans, Enterococcus faecalis, and oral microcosm. The composite discs prepared with DEAE-Dextran AgNPs exhibited excellent antibacterial activity compared with composite resin reinforced by simple AgNPs (p < 0.05). Mechanical properties were significantly enhanced by adding DEAE-Dextran into composite resin (p < 0.05). Moreover, unlike AgNPs, DEAE-Dextran AgNPs were found to be less hemolytic. The results establish strong ground applications for DEAE-Dextran-modified dental composite resins in restorative dental applications.

Decoding of Ankle Joint Movements in Stroke Patients Using Surface Electromyography.

Stroke is a cerebrovascular disease (CVD), which results in hemiplegia, paralysis, or death. Conventionally, a stroke patient requires prolonged sessions with physical therapists for the recovery of motor function. Various home-based rehabilitative devices are also available for upper limbs and require minimal or no assistance from a physiotherapist. However, there is no clinically proven device available for functional recovery of a lower limb. In this study, we explored the potential use of surface electromyography (sEMG) as a controlling mechanism for the development of a home-based lower limb rehabilitative device for stroke patients. In this experiment, three channels of sEMG were used to record data from 11 stroke patients while performing ankle joint movements. The movements were then decoded from the sEMG data and their correlation with the level of motor impairment was investigated. The impairment level was quantified using the Fugl-Meyer Assessment (FMA) scale. During the analysis, Hudgins time-domain features were extracted and classified using linear discriminant analysis (LDA) and artificial neural network (ANN). On average, 63.86% ± 4.3% and 67.1% ± 7.9% of the movements were accurately classified in an offline analysis by LDA and ANN, respectively. We found that in both classifiers, some motions outperformed others (p < 0.001 for LDA and p = 0.014 for ANN). The Spearman correlation (ρ) was calculated between the FMA scores and classification accuracies. The results indicate that there is a moderately positive correlation (ρ = 0.75 for LDA and ρ = 0.55 for ANN) between the two of them. The findings of this study suggest that a home-based EMG system can be developed to provide customized therapy for the improvement of functional lower limb motion in stroke patients.

Evaluation of windowing techniques for intramuscular EMG-based diagnostic, rehabilitative and assistive devices.

Objective.Intramuscular electromyography (iEMG) signals, invasively recorded, directly from the muscles are used to diagnose various neuromuscular disorders/diseases and to control rehabilitative and assistive robotic devices. iEMG signals are potentially being used in neurology, kinesiology, rehabilitation and ergonomics, to detect/diagnose various diseases/disorders. Electromyography-based classification and analysis systems are being designed and tested for the classification of various neuromuscular disorders and to control rehabilitative and assistive robotic devices. Many studies have explored parameters such as the pre-processing, feature extraction and selection of classifiers that can affect the performance and efficacy of iEMG-based classification systems. The pre-processing stage includes the removal of any unwanted noise from the original signal and windowing of the signal.Approach.This study investigated and presented the optimum windowing configurations for robust control and better performance results of an iEMG-based analysis system based on the stationarity rate (SR) and classification accuracy. Both disjoint and overlap, windowing techniques with varying window and overlap sizes have been investigated using a machine learning-based classification algorithm called linear discriminant analysis.Main results.The optimum window size ranges are from 200-300 ms for the disjoint and 225-300 ms for the overlap windowing technique, respectively. The inferred results show that for the overlap windowing technique the optimum range of overlap size is from 10%-30% of the length of window size. The mean classification accuracy (MCA) and mean stationarity rate (MSR) were found to be lower in the disjoint windowing technique compared to overlap windowing at all investigated overlap sizes. Statistical analysis (two-way analysis of variance test) showed that the MSR and MCA of the overlap windowing technique was significantly different at overlap sizes of 10%-30% (p-values < 0.05).Significance.The presented results can be used to achieve the best possible classification results and SR for any iEMG-based real-time diagnosis, detection and control system, which can enhance the performance of the system significantly.