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Development of a novel direct compressible co-processed excipient and its application for formulation of Mirtazapine orally disintegrating tablets
No full textIntroduction
Orally disintegrating tablets (ODTs) are designed to dissolve in the oral cavity within 3 min, providing a convenient option for patients as they can be taken without water. Direct compression is the most common method used for ODTs formulations. However, the availability of single composite excipients with desirable characteristics such as good compressibility, fast disintegration, and a good mouthfeel suitable for direct compression is limited.
Objective
This research was proposed to develop a co-processed excipient composed of xylitol, mannitol, and microcrystalline cellulose for the formulation of ODTs.
Methods
A total of 11 formulations of co-processed excipients with different ratios of ingredients were prepared, which were then compressed into ODTs, and their characteristics were thoroughly examined. The primary focus was on evaluating the disintegration time and hardness of the tablets, as these factors are important in ensuring the ODTs meet the desired criteria. The model drug, Mirtazapine was then incorporated into the chosen optimized formulation.
Results
The results showed that the formulation comprised of 10% xylitol, 10% mannitol and 80% microcrystalline cellulose demonstrated the fastest disintegration time (1.77 ± 0.119 min) and sufficient hardness (3.521 ± 0.143 kg) compared to the other formulations. Furthermore, the drug was uniformly distributed within the tablets and fully released within 15 min.
Conclusion
Therefore, the developed co-processed excipients show great potential in enhancing the functionalities of ODTs, offering a promising solution to improve the overall performance and usability of ODTs in various therapeutic applications
The impact of student computer competency on e-learning outcomes: A path analysis model of virtual learning infrastructure, collaboration, and access to electronic facilities
No full textAim
This study explored the influence of student computer competency on e-learning outcomes among Iranian nursing students and examined its mediating role in the relationship between virtual learning infrastructure, student collaboration, access to electronic facilities, and e-learning outcomes.
Design
A cross sectional study.
Method
A self-administered online survey was used from August to October 2022, with a sample size of 417 nursing students selected through convenience sampling. Descriptive statistics, correlation analyses, and PROCESS macro v4.1 (Model 4) were used for data analysis.
Results
The results revealed that virtual learning infrastructure, access to electronic facilities, and student collaboration, significantly predict student computer competency and e-learning outcomes. Virtual learning infrastructure and access to electronic facilities were found to be the strongest predictors of student computer competency, while student collaboration had a smaller but still significant effect. Student computer competency was found to mediate the relationship between virtual learning infrastructure, access to electronic facilities, student collaboration, and e-learning outcomes
Movement magic: how sports can help empower kids with intellectual disabilities.
No full textHaving a child with intellectual disability (ID) is, more often than not, viewed negatively. It comes with a sense of dread, hopelessness and even helplessness.
The narrative that having a child with ID is pitiful and to some people, disastrous, is often the single psychological barrier that prevents the child and his or her family from living a more fulfilling life.
While it is undeniable that life becomes more difficult when a child is diagnosed with ID, living under the cloud of pity doesn’t help. What is important is to understand that there are many things parents can do to facilitate their child’s development into a healthy and valuable member of the community.
Such efforts should also be carried out together, in collaboration with professionals, industries and the community
Effectiveness of digital tools for smoking cessation in Asian countries: a systematic review
Get PDFAim: The use of tobacco is responsible for many preventable diseases and deaths worldwide. Digital interventions have greatly improved patient health and clinical care and have proven to be effective for quitting smoking in the general population due to their flexibility and potential for personalization. However, there is limited evidence on the effectiveness of digital interventions for smoking cessation in Asian countries.
Methods: Three major databases - Web of Science (WOS), Scopus, and PubMed - for relevant studies published between 1 January 2010 and 12 February 2023 were searched for studies evaluating the effectiveness of digital intervention for smoking cessation in Asian countries.
Results: A total of 25 studies of varying designs were eligible for this study collectively involving a total of n = 22,005 participants from 9 countries. Among different digital tools for smoking cessation, the highest abstinence rate (70%) was reported with cognitive behavioural theory (CBT)-based smoking cessation intervention via Facebook followed by smartphone app (60%), WhatsApp (59.9%), and Pharmacist counselling with Quit US smartphone app (58.4%). However, WhatsApp was preferred over Facebook intervention due to lower rates of relapse. WeChat was responsible for 15.6% and 41.8% 7-day point prevalence abstinence. For telephone/text messaging abstinence rate ranged from 8-44.3% and quit rates from 6.3% to 16.8%. Whereas, no significant impact of media/multimedia messages and web-based learning on smoking cessation was observed in this study.
Conclusion: Based on the study findings the use of digital tools can be considered an alternative and cost-effective smoking cessation intervention as compared to traditional smoking cessation interventions
Health benefits, pharmacological properties, and metabolism of cannabinol: A comprehensive review
No full textCannabinol (CBN) is a non-psychoactive phytocannabinoid found in Cannabis sativa. Although overshadowed by its more well-known counterparts, such as delta-9-tetrahydrocannabinol (THC) and cannabidiol (CBD), CBN has been gaining attention due to its potential therapeutic properties. This review aims to provide insight into the molecular mechanisms underlying the pharmacological actions of CBN. CBN interacts with the endocannabinoid system (ECS), primarily targeting the CB2 and CB1 cannabinoid receptors. It acts as a partial agonist for both receptors, modulating their activity and downstream signaling pathways. Through these interactions, CBN exhibits diverse effects on various physiological processes, including pain perception, inflammation, immune response, and neuroprotection. Moreover, CBN has been shown to affect non-cannabinoid receptors, including transient receptor potential (TRP) channels, peroxisome proliferator-activated receptors (PPARs), and serotonin receptors. These interactions contribute to the modulation of pain, inflammation, and mood regulation. The molecular mechanisms of CBN also involve its antioxidant and anti-inflammatory properties. CBN has been found to reduce oxidative stress by scavenging reactive oxygen species (ROS) and inhibiting inflammatory mediators. This antioxidant activity potentially contributes to its neuroprotective effects and may have implications for the treatment of neurodegenerative disorders. Furthermore, CBN exhibits potential antimicrobial activity, acting against various bacteria, fungi, and methicillin-resistant Staphylococcus aureus (MRSA) strains. The underlying mechanisms of this antimicrobial effect are still being elucidated, but may involve disruption of microbial cell membranes and interference with microbial biofilm formation. The molecular mechanisms underlying CBN's pharmacological actions involve its interactions with the ECS, modulation of non-cannabinoid receptors, antioxidant and anti-inflammatory properties, and potential antimicrobial activity. Further research is needed to fully understand the therapeutic potential of CBN and its role in various disease states, paving the way for the development of novel therapeutic interventions. Due to its multiple interests, the isolation and synthesis of CBN has been investigated by several approaches. CBN synthesis involves various approaches, including oxidative conversions, isomerization reactions, enzymatic transformations, and biotransformation techniques. Advancements in synthetic methodologies and innovative strategies continue to contribute to the efficient production of CBN. Further research and optimization are necessary to enhance yields, purity, and scalability of the synthesis processes
Unraveling the genetic variations underlying virulence disparities among SARS-CoV-2 strains across global regions: insights from Pakistan
No full textOver the course of the COVID-19 pandemic, several SARS-CoV-2 variants have emerged that may exhibit different etiological effects such as enhanced transmissibility and infectivity. However, genetic variations that reduce virulence and deteriorate viral fitness have not yet been thoroughly investigated. The present study sought to evaluate the effects of viral genetic makeup on COVID-19 epidemiology in Pakistan, where the infectivity and mortality rate was comparatively lower than other countries during the first pandemic wave. For this purpose, we focused on the comparative analyses of 7096 amino-acid long polyprotein pp1ab. Comparative sequence analysis of 203 SARS-CoV-2 genomes, sampled from Pakistan during the first wave of the pandemic revealed 179 amino acid substitutions in pp1ab. Within this set, 38 substitutions were identified within the Nsp3 region of the pp1ab polyprotein. Structural and biophysical analysis of proteins revealed that amino acid variations within Nsp3's macrodomains induced conformational changes and modified protein-ligand interactions, consequently diminishing the virulence and fitness of SARS-CoV-2. Additionally, the epistatic effects resulting from evolutionary substitutions in SARS-CoV-2 proteins may have unnoticed implications for reducing disease burden. In light of these findings, further characterization of such deleterious SARS-CoV-2 mutations will not only aid in identifying potential therapeutic targets but will also provide a roadmap for maintaining vigilance against the genetic variability of diverse SARS-CoV-2 strains circulating globally. Furthermore, these insights empower us to more effectively manage and respond to potential viral-based pandemic outbreaks of a similar nature in the future
Antibacterial Evaluation of Gallic Acid and its Derivatives against a Panel of Multi-drug Resistant Bacteria
No full textBackground: Infectious diseases are the second leading cause of deaths worldwide. Pathogenic bacteria have been developing tremendous resistance against antibiotics which has placed an additional burden on healthcare systems. Gallic acid belongs to a naturally occurring phenolic class of compounds and is known to possess a wide spectrum of antimicrobial activities.
Aims & objectives: In this study, we synthesized thirteen derivatives of gallic acid and evaluated their antibacterial potential against seven multi-drug resistant bacteria, as well as cytotoxic effects against human embryonic kidney cell line in vitro. Methods: 13 compounds were successfully synthesized with moderate to good yield and evaluated. Synthesized derivatives were characterized by using nuclear magnetic resonance spectroscopy, mass spectrometry, and Fourier transformation infrared spectroscopy. Antibacterial activity was determined using microdilution while cytotoxicyt was assessed using MTT assay.
Results: The results of antibacterial assay showed that seven out of thirteen compounds exhibited antibacterial effects with compound 6 and 13 being most potent against Staphylococcus aureus (MIC 56 μg/mL) and Salmonella enterica (MIC 475 μg/mL) respectively. On the other hand, most of these compounds showed lower cytotoxicity against human embryonic kidney cells (HEK 293), with IC50 values ranging from over 700 μg/mL.
Conclusion: Notably, compound 13 was found to be non-toxic at concentrations as high as 5000 μg/mL. These findings suggest that the present synthetic derivatives of gallic acid hold potential for further studies in the development of potent antibacterial agents
Born this way or formed this way? Distal personality traits and proximal self-efficacy of Malaysian students and their academic performance
Get PDFIt has been acknowledged that academic performance has important consequences in one’s career, thus, a better understanding of both distal and proximal predictors deserves consideration. Based on social cognitive theory, this study contributes to the limited research investigating the academic performance of university students in Malaysia using the trait model which considers the mediation of self-efficacy (proximal characteristic) in the relationship between student personality (distal trait) and academic performance (outcomes). In a sample of 264 participants, self-efficacy positively relates to academic performance and positively mediated effects of all traits (except neuroticism) on academic performance. Contrary to past research, conscientiousness, extraversion, and agreeableness do not exert direct effects on academic achievement but instead through self-efficacy. Openness to experience turned out to be the strongest predictor pointing to a need for in-depth investigations into this dimension and for more complex model incorporating other proximal attributes in predicting academic performance in future research
Taking Care Of Our Health Care Workers
No full textDespite potential challenges of the health care system, it is important for organisations to focus on work-life balance. This could include options for flexible work hours, better staff to decrease the chances of overworking, and encouraging vacations
Machine learning based hybrid trust management scheme for authentication and authorization in IoT
Get PDFWith the ongoing efforts for widespread adoption of the Internet of Things (IoT), security is one critical factor hindering the wide acceptance of IoT. To address the security issue of IoT, several studies have been carried out that involve the use of, but are not limited to, Blockchain, Artificial Intelligence (AI), and edge/fog/cloud computing. Authentication and Authorization (AA) are crucial aspects of the information security policy of the CIA triad that protect the network from malicious parties. However, existing authorization and authentication schemes are insufficient for handling security due to the IoT network’s scalability issue and the devices’ resource-constrained nature. To overcome challenges due to various constraints of IoT networks and nodes, there is a significant interest in trust management (TM) techniques to assist in the AA process for IoT. TM eliminates the requirement to determine "identities" while facilitating the authorization process. Instead, they represent security rights and constraints. This permits more flexibility and expressiveness, and standardizing current, scalable security measures. Hence, TM has received significant attention in enhancing the system’s security by defining policies and providing users with specific access rights. The current TM model in IoT is still under development, and the centralized characteristics of the IoT AA scheme are not enough to solve the heterogeneity and scalability problems. Generic TM for AA depends solely on direct inputs such as user ID and password, MAC, key, digital certificates, etc. Most common security attacks occur in the physical layer by MAC impersonation (spoofing attack), which may jeopardize the whole network. Furthermore, malicious nodes are increasingly intelligent and can change their attack approaches dynamically depending on the ambient inputs to avoid being detected. This makes attack pattern identification for the defending system difficult. Therefore, this thesis attempts to resolve this situation by proposing a holistic multilevel distributed TM scheme for trust and reputation in IoT and privacy control. Zigbee Zolertia Z1 is a popular communication node that offers coverage in a wide-area network with minimal implementation cost and power consumption. Our data-collection testbed consists of 3 client nodes and an edge or gateway node. Here, we used Zolertia Z1 low-power wireless modules compliant with IEEE 802.15.4 and Zigbee protocols. Firstly, a dataset was created from a wireless sensor network testbed comprising the node’s history of (RSSI), (LQI), MAC address, device Temperature, and battery level. Second, a multilevel TM model is designed and implemented to determine the suitable trust level for each node. The proposed scheme trained a feed-forward network and shared the weights between multi-layer perceptrons to the federated machine learning (FML) of the proposed distributed TM model to classify 4-trust levels. Once the trust level is determined, authentication and authorization access rights are intelligently determined using FML. Here, the Local trust manager, such as the edge node or gateway node, will manage the device’s access rights learning model in a distributed fashion. The Global trust manager in the cloud, on the other hand, will aggregate the device’s or edge node’s (e.g., gateway node) learning model in a centralized manner. Furthermore, intelligent attacks can be determined by the probability and frequency of the attack. The proposed TM scheme for AA in IoT allows for spoofing and impersonation attacks to be consistently detected autonomously to remove or isolate a malicious node seeking unauthorized access. Performance evaluation and benchmarking results indicate a high accuracy level compared to the currently available schemes in the literature. The proposed AA scheme’s results were achieved for the four different trust levels, with an overall accuracy of 99.7925% for different AA classes