To Study the Effectiveness of Laser Therapy and G.D Maitland Mobilization in Adhesive Capsulitis Among 40-50 Years Age Group Male Patients

Background:Thestudy focused to make a comparative evaluation regarding the efficacy of laser therapy treatment with that of the Maitland mobilization technique in patients with adhesive capsulitis. Objective: Study to show the effectiveness of laser therapy and G.D Maitland mobilization in adhesive capsulitis. Methods:In this randomized controlled study, total subject 30participants were equally divided using random method in to two different treatment groups with each group having 15 patients each in each of the group namely GD Maitland Mobilization and the LASER therapy group. All the subjects were treated for 3 sessions per week for six weeks (total 18 sessions). The variable of the study include assessments of pain severity on Visual Analogue Scale (VAS), shoulder active ROM (flexion, extension, abduction), associated disability SPADI scores for pain and disability scales.nbsp The variable score were taken in the beginning of the study (day 0) and after 30 days and 90 days for both the group. Goniometric assessment of active ranges of shoulder movements were made for the range documentation of the study. Data of 30 subjects (only men) enrolled subjects were used for analysis. Results:In the study there are improvement in all shoulder parameters after treatment and in the follow up period compared to before treatment in both groups. Conclusion: though both treatment are effective in reducing the symptoms associated with adhesive capsulitis, the study concludes that G.D Maitland is more effective than Laser therapy at the 30 days documentation.nbs

Phenolic compound and fatty acid properties of some microalgae species isolated from Erbil City

The total phenolic compound and fatty acid profiles of lipids from microalgae are unique. The present study was designed to investigate aqueous, ethanolic and acetone extracts of several algae (Spirogyra sp., Spirulina sp.,Chlorella sp and Chara sp.) for their antioxidant capacities of the crude extracts and fractions by radical scavenging activity against the stable radical 1,1-diphenyl-2-picrylhydrazyl DPPH as well; total phenolic content. The results showed that Spirulina sp. indicated significantly higher total phenolic compound and antioxidant activities compared to the other species (P < 0.05) and acetone extracts showed higher quantity among three extracts. The fatty acids analysis using High performance liquid chromatography –HPLC showed the presence of palmitic acid, stearic acid, oleic acid, and linoleic acid, palmitic acid showed high quantity than other fatty acid classes in all studied algae. This study concluded that high antioxidant capacity of microalgae could be inspected for different industrial applications

Social media for cardiac imagers: a review.

Cardiac imaging plays a pivotal role in the diagnosis and management of cardiovascular diseases. In the burgeoning landscape of digital technology and social media platforms, it becomes essential for cardiac imagers to know how to effectively increase the visibility and the impact of their activity. With the availability of social sites like X (formerly Twitter), Instagram and Facebook, cardiac imagers can now reach a wider audience and engage with peers, sharing their findings, insights, and discussions. The integration of persistent identifiers, such as Digital Object Identifiers (DOIs), facilitates traceability and citation of cardiac imaging publications across various digital platforms, further enhancing their discoverability. To maximize visibility, practical advice is provided, including the use of visually engaging infographics and videos, as well as the strategic implementation of relevant hashtags and keywords. These techniques can significantly improve the discoverability of cardiac imaging research through search engine optimization and social media algorithms. Tracking impact and engagement is crucial in the digital age, and this review discusses various metrics and tools to gauge the reach and influence of cardiac imaging publications. This includes traditional citation-based metrics and altmetrics. Moreover, this review underscores the importance of creating and updating professional profiles on social platforms and participating in relevant scientific communities online. The adoption of digital technology, social platforms, and a strategic approach to publication sharing can empower cardiac imaging professionals to enhance the visibility and impact of their research, ultimately advancing the field and improving patient care

Effect of gender on strength gains after isometric exercise coupled with electromyographic biofeedback in knee osteoarthritis: A preliminary study

AbstractObjectiveThe objective of this trial was to evaluate the effect of gender on strength gains after five week training programme that consisted of isometric exercise coupled with electromyographic biofeedback to the quadriceps muscle.Materials and methodsForty-three (20 men and 23 women) patients with knee osteoarthritis (OA), were placed into two groups based on their gender. Both groups performed isometric exercise coupled with electromyographic biofeedback for five days a week for five weeks.ResultsBoth groups reported gains in muscle strength after five week training. However, the difference was found to be statistically insignificant between the two groups (P=0.224).ConclusionThe results suggest that gender did not affect gains in muscle strength by isometric exercise coupled with electromyographic biofeedback in patients with knee OA

Post-Acute Sequelae of COVID-19 (PASC): Association with Inflammation and Autoimmunity

It has become increasingly evident that a high percentage of patients that recover from acute COVID-19 infection continue to suffer from a variety of persistent symptoms even months after viral clearance, the most common ones being fatigue, dyspnea, anosmia, dysgeusia, cognitive dysfunction, and psychological problems, including anxiety and depression. This syndrome, known as Post-acute sequelae of COVID-19 (PASC), can severely affect the life quality and represents an important health care concern. The exact causes for the symptoms observed in patients with PASC remain to be adequately characterized, but are likely to be associated with multiple factors, including residual disease and/or inflammation, organ damage, effects of hospitalization and/or prolonged ventilation, as well as effects of social isolation and stress. This mini-review discusses evidence that may link both inflammatory and auto-immune processes in the pathophysiology of PASC

Compressed Machine Learning Models for the Uncertainty Quantification of Power Distribution Networks

Today’s spread of power distribution networks, with the installation of a significant number of renewable generators that depend on environmental conditions and on users’ consumption profiles, requires sophisticated models for monitoring the power flow, regulating the electricity market, and assessing the reliability of power grids. Such models cannot avoid taking into account the variability that is inherent to the electrical system and users’ behavior. In this paper, we present a solution for the generation of a compressed surrogate model of the electrical state of a realistic power network that is subject to a large number (on the order of a few hundreds) of uncertain parameters representing the power injected by distributed renewable sources or absorbed by users with different consumption profiles. Specifically, principal component analysis is combined with two state-of-the-art surrogate modeling strategies for uncertainty quantification, namely, the least-squares support vector machine, which is a nonparametric regression belonging to the class of machine learning methods, and the widely adopted polynomial chaos expansion. Such methods allow providing compact and efficient surrogate models capable of predicting the statistical behavior of all nodal voltages within the network as functions of its stochastic parameters. The IEEE 8500-node test feeder benchmark with 450 and 900 uncertain parameters is considered as a validation example in this study. The feasibility and strength of the proposed method are verified through a systematic assessment of its performance in terms of accuracy, efficiency, and convergence, based on reference simulations obtained via classical Monte Carlo analysis