Analyzing the Prebiotic Potential of Glucosamine for Targeting the Gut Microbiome Health

Recognizing the composition and modulation of the microbiome, a viable therapeutic tool for multi-targeted therapy is a new strategy that has recently been explored. Glucosamine (GS) is being studied for its prebiotic potential in addition to being the most abundant and naturally occurring amino monosaccharide. The current study focuses on glucosamine’s prebiotic potential by assessing the stability of various GS concentrations (1% - 5%) in the gastrointestinal tract (GIT) and its ability to be fermented by the gut microbiota. The results showed that GS stimulated the most growth in L. acidophilus even after a longer incubation time than B. bifidum and L. acidophilus growth was concentration-dependent, with maximum growth at 3% with a simultaneous decrease in pH (5.6 - 1.7). The decrease in GS concentration with time also represented the growth of bacterial species, demonstrating the species’ utilization of GS. Furthermore, at 3%, GS also represented the prebiotic index of 1.9. In addition, the concentration of GS in various simulated GIT fluids was estimated in both fast and fed conditions to examine GS stability at various levels in the gut. The results showed that GS remained unaffected and non-digestible in all of the simulated GIT fluids (salivary, gastric, intestinal, and colonic), but there was a slight decrease in GS concentration (2.8%) in the fasted state of gastric fluid due to low pH levels (1.6). As a result, the findings are conclusive and suggest that GS possesses prebiotic properties.

<i>In-Silico</i>Validation and Development of Chlorogenic Acid (CGA) Loaded Polymeric Nanoparticle for Targeting Neurodegenerative Disorders

Background: Recent decades witnessed a significant growth in terms of phytocompounds based therapeutics, extensively explored for almost all types of existing disorders. They have also been widely investigated in Neurodegenerative disorders (NDDs) and Chlorogenic acid (CGA), a polyphenolic compound having potential anti-inflammatory and anti-oxidative properties, emerged as a promising compound in ameliorating NDDs. Owing to its poor stability, bioavailability and release kinetics, CGA needed a suitable nanocarrier based pharmaceutical design for targeting NDDs. Objective: The current study is aimed at the in-silico validation of CGA as an effective therapeutic agent targeting various NDDs followed by the fabrication of polymeric nanoparticles-based carrier system to overcome its pharmacological limitations and improve its stability. Methods: A successful in-silico validation using molecular docking techniques along with synthesis of CGA loaded polymeric nanoparticles (CGA-NPs) by ionic gelation method was performed. The statistical optimisation of the developed CGA-NPs was done by Box Behnken method and then the optimized formulation of CGA-NPs was characterised using particle size analysis (PSA), Transmission electron microscopy (TEM), Fourier Transform Infrared spectroscopy (FTIR) along with in-vitro release kinetics analysis. Results & Conclusion: The results attained exhibited average particle size of 101.9 ± 1.5 nm, Polydispersibility (PDI) score of 0.065 and a ZP of −17.4 mV. On a similar note, TEM results showed a size range of CGA-NPs between 90 - 110 nm with a spherical shape of NPs. Also, the data from in-vitro release kinetics showed a sustained release of CGA from the NPs following the first-order kinetics suggesting the appropriate designing of nanoformulation.

Synthesis and Characterization of <i>Citrus limonum</i>Essential Oil Based Nanoemulsion and Its Enhanced Antioxidant Activity with Stability for Transdermal Application

Lemon oil (LO), also known as Citrus limonum is a highly volatile essential oil (EO) with potential therapeutic properties like anti-oxidative, anti-proliferative, anti-fungal and anti-cancerous. However, the efficacy of LO is limited due to its physiological factors such as high volatility, poor stability (particularly sensitive to sunlight) and quick degradability upon exposure. To overcome these challenges, we formulated lemon oil loaded nanoemulsion system (LO-NE) (oil-in-water), using aqueous titration method. The formulation comprised of lemon oil (LO), Tween 80 and ethanol as oil, surfactant and co-surfactant phases respectively. The existence zone of NE was established by constructing pseudo-ternary phase diagrams using different concentrations of LO, surfactant and co-surfactant (Smix). The quantitative estimation of LO was performed using a high throughput gas chromatography, revealing the presence of various compounds like Limonene, Alpha-Pinene and Linalyl acetate followed by the estimation of total phenolics and flavonoid content. The characterization of LO-NE indicated the particle size of 60 ± 2.5 nm along with the polydispersity index of 0.125 and zeta potential of −14.9 mV. The size range of the NE particles dispersed in the colloidal system was further verified by TEM micrograph which shows size range between 46.2 - 104.7 nm. All the anti-oxidant assays outcomes exhibited the higher activity of LO-NE in comparison to LO alone with lower IC50 values. The release kinetics statistical data showed that LO-NE had a sustained release and followed the Higuchi’s model in comparison to burst release of LO alone. Lastly, the stability analysis of the optimised formulation (LO-NE) and LO was estimated through antioxidant assay and subjecting them for thermodynamic stability after 6 months. The results attained, showed higher stability and anti-oxidant capability of LO-NE than LO alone. The study suggested that formulated nanoemulsion can be effectively used as a highly efficacious biologically active alternative nanoformulation against many transdermal disorders.

Automated Time Based Multi-Criteria Bug Triage Approach:Developer Working Efficiency and Social Network Based Developer Recommendation

In software development projects,bugs are common phenomena.Developers report bugs in open source repositories.There is a need to develop high quality developer prediction model that considers developer work satisfaction,keep within limited development cost,and improve bug resolution time.To address and resolve bug report as soon as possible is the main focus of triager when a new bug is reported.Thus,developer work efficiency is an important factor in bug-fixing.To address these issues,a proposed approach recommends a set of developers that could potentially share their knowledge with each other to fix new bug reports.The proposed approach is called developer working efficiency and social network based developer recommendation(DweSn).It is a composite model that builds developers'profile by using developer average bug fixing time,work efficiency to fix variety of bugs,as well as the developer's social interactions with other developers.A similarity measure is applied between new bug and bugs in corpus to extract the list of capable developers from the corpus.The proposed approach only selects those developers who are active and less loaded with work.The developer with the highest profile score is assigned the bugs.We evaluated our approach on the subset of five large open-source projects including Mozilla,Netbeans,Eclipse,Firefox and OpenOffice,and compared it with the state-of-the-art.The results demonstrate that combination of developers'efficiency with their average bug fixing time and interactions in their social network gives good accuracy and efficiently reduces bug tossing length.This approach shows an improvement in prediction accuracy,precision,recall,F-score and reduced bug tossing length up to 93.89%,93.12%,93.46%,93.27%and 93.25%,respectively.The proposed approach achieved a 93%hit ratio and 93.34%mean reciprocal rank,indicating that our proposed triager is able to efficiently assign bugs to correct developers.