Evaluation of Nootropic Potential of Aerva persica Roots against D-galactose-induced Memory Impairment.

BACKGROUND: The primary phytoconstituents reported to have neuroprotective effects are flavonoids and phenolic compounds. Aerva persica roots are reported to be rich in flavonoids and phenolic compounds. Therefore, this study aimed to explore the nootropic potential of Aerva persica roots. OBJECTIVE: The objective of this study was to evaluate the nootropic potential of Aerva persica roots against D-galactose-induced memory impairment. METHODS: In this study, the roots of Aerva persica were extracted with 70% ethanol. The obtained extract was evaluated for total phenolic content using the Folin-Ciocalteu method and total flavonoid content using the aluminium chloride colorimetric assay. Afterward, the acute oral toxicity of the extract was determined following the Organisation for Economic Co-operation and Development (OECD) guideline 423. Additionally, two doses of Aerva persica (100 and 200 mg/kg body weight (BW)) were evaluated for their nootropic potential against D-galactose-induced memory impairment. The nootropic potential of the crude extract was assessed through a behavioural study and brain neurochemical analysis. Behavioural studies involved the evaluation of spatial reference- working memory using the radial arm maze test and the Y-maze test. Neurochemical analysis was performed to determine the brain's acetylcholine, acetylcholinesterase, glutathione (GSH), and malondialdehyde (MDA) levels. RESULTS: The total phenolic content and total flavonoid content were found to be 179.14 ± 2.08 µg GAE/mg and 273.72 ± 3.94 µg QE/mg, respectively. The Aerva persica extract was found to be safe up to 2000 mg/kg BW. Following the safety assessment, the experimental mice received various treatments for 14 days. The behavioural analysis using the radial maze test showed that the extract at both doses significantly improved spatial reference-working memory and reduced the number of total errors compared to disease control groups. Similarly, in the Y-maze test, both doses significantly increased the alteration percentage and the percentage of novel arm entry (both indicative of intact spatial memory) compared to disease control. In neurochemical analysis, Aerva persica at 200 mg/kg significantly normalised the acetylcholine level (p<0.0001) and GSH level (p<0.01) compared to disease control. However, the same effect was not observed with Aerva persica at 100 mg/kg. Additionally, Aerva persica at 200mg/kg BW significantly decreased the acetylcholinesterase level (p<0.0001) and decreased the brain's MDA level (p<0.01) compared to the disease control, whereas the effect of Aerva persica at 100 mg/kg BW in reducing acetylcholinesterase was non-significant. CONCLUSION: Based on the results, it can be concluded that the nootropic potential of Aerva persica was comparable to that of the standard drug, Donepezil, and the effect might be attributed to the higher content of flavonoids and phenolic compounds.

Maximum entropy based common spatial patterns for motor imagery classification.

The common spatial pattern (CSP) is extensively used to extract discriminative feature from raw Electroencephalography (EEG) signals for motor imagery classification. The CSP is a statistical signal processing technique, which relies on sample based covariance matrix estimation to give discriminative information from raw EEG signals. The sample based estimation of covariance matrix becomes a problem when the number of training samples is limited, which causes the performance of CSP based brain computer interface (BCI) to degrade significantly. In this paper, we present a maximum entropy based CSP algorithm that incorporates principle of maximum entropy while estimating the sample based covariance matrix. The proposed algorithm is evaluated on publicly available data set samples. The classification results indicate that the proposed algorithm outperforms the traditional CSP algorithm by 13.38% on average.

Phytofabrication of bioinduced silver nanoparticles for biomedical applications.

Synthesis of nanomaterials holds infinite possibilities as nanotechnology is revolutionizing the field of medicine by its myriad applications. Green synthesis of nanoparticles has become the need of the hour because of its eco-friendly, nontoxic, and economic nature. In this study, leaf extract of Rosa damascena was used as a bioreductant to reduce silver nitrate, leading to synthesis of silver nanoparticles (AgNPs) in a single step, without the use of any additional reducing or capping agents. The synthesized nanoparticles were characterized by the use of UV-visible spectroscopy, fourier transform infrared spectroscopy, dynamic light scattering, transmission electron microscopy, and field emission scanning electron microscopy. Time-dependent synthesis of AgNPs was studied spectrophotometrically. Synthesized AgNPs were found to possess flower-like spherical structure where individual nanoparticles were of 16 nm in diameter, whereas the agglomerated AgNPs were in the range of 60-80 nm. These biologically synthesized AgNPs exhibited significant antibacterial activity against Gram-negative bacterial species but not against Gram-positive ones (Escherichia coli and Bacillus cereus). Anti-inflammatory and analgesic activities were studied on a Wistar rat model to gauge the impact of AgNPs for a probable role in these applications. AgNPs tested positive for both these activities, although the potency was less as compared to the standard drugs.