Asparagus recemosus enhances memory and protects against amnesia in rodent models
Authors: Sairam Krishnamurthy
Gireesh Kumar Singh
Alakh N Sahu
Rakesh Ojha
A V Muruganandam
Journal: Brain and cognition (2010)
Discipline: NEUROSCIENCE & BEHAVIOR
Keywords: Asparagus Racemosus; neuropharmacological activities; adaptogenic; antidepressant; nootropic
Affiliations: Department of Pharmaceutics, Institute of Technology, Banaras Hindu University, UP, India.

Abstract:  Asparagus Racemosus (AR) is an Ayurvedic rasayana possessing multiple neuropharmacological activities. The adpatogenic and antidepressant activity of AR is well documented. The present study was undertaken to assess nootropic and anti-amnesic activities of MAR in rats. The Morris water maze (MWM) and elevated plus maze (EPM) models were employed to evaluate learning and memory activity. Subsequently, the anti-amnestic activity was evaluated in scopolamine and sodium nitrite (NaNO(2))-induced amnestic models in rats. Rats pre-treated with MAR (50, 100 and 200mg/kg, p.o) for 7 days showed significant decrease in escape latency in the MWM test indicating nootropic activity. MAR also significantly reversed scopolamine and sodium nitrite-induced increase in transfer latency on EPM indicating anti-amnesic activity. Further, MAR dose-dependently inhibited acetylcholinesterase enzyme in specific brain regions (prefrontal cortex, hippocampus and hypothalamus). Thus, MAR showed nootropic and anti-amnesic activities in the models tested and these effects may probably be mediated through augmentation of cholinergic system due to its anti-cholinesterase activity. 

Retracted: No

PubPeer comments:
 Table 3 shows  transfer latency in an elevated plus maze, presumably in seconds, for 5 rats per group. Amazeingly the authors report identical SEMs for many values, with a preference for 0.71 (red boxes), 0.93 (blue boxes) and some other numbers. Could the authors clarify if there was something in their calculation that resulted in so many identical values? ![file] , 
 Another remark that might be of note, in particular for people who are doing keyword searches. The topic of this paper, a medicinal plant called *Asparagus racemosus* is sometimes - but not always - misspelled as *Asparagus recemosus* in the title, the keywords, several times in the text, and four times in the references. The citations all have the correct species names, but the authors of this paper misspelled the plant name in these article titles. ![file] , 
 #1  or 0.71 (red boxes), 0.93 (blue boxes) and some other numbers If I may steal the core concept of SPRITE from James Heathers, Jordan Anaya and Nick Brown: Rows like Mean=52, std.err = 0.71 correspond to distributions of this form: {50, 51, 52, 53, 54}. In general, if mean = X, the values have to be {X-2, X-1, X, X+1, X+2}. Evidently there were four occurrences of this very flat distribution within Table 1. Distributions like 67.6 (or more generally, X.6), std.err = 0.93 correspond to distributions of the form {65, 66, 68, 69, 70} (or more generally, {X-2, X-1, X+1, X+2, X+3}). Similarly, the entries in Table 1 like mean=X.4 , std.err = 0.93 correspond to distributions {X-2, X-1, X, X+2, X+3}. I have no idea why Table 1 should contain so many cases of distributions where the raw data avoided duplicated numbers. But to be fair, the entry  Mean = 39.6, std.err = 0.51 means that the raw data were {38, 39, 40, 40, 41} - which **does** have a duplicated measurement. The entry  Mean = 63.4, std.err = 0.51 corresponds to raw data {62, 63, 63, 64, 65}. ,