Assessing the potential of <i>Psidium guajava</i> derived phytoconstituents as anticholinesterase inhibitor to combat Alzheimer’s disease: an <i>in-silico</i> and <i>in-vitro</i> approach

Acetylcholinesterase (AChE) inhibitors play a crucial role in the treatment of Alzheimer’s disease. These drugs increase acetylcholine levels by inhibiting the enzyme responsible for its degradation, which is a vital neurotransmitter involved in memory and cognition. This intervention intermittently improves cognitive symptoms and augments neurotransmission. This study investigates the potential of Psidium guajava fruit extract as an acetylcholinesterase (AChE) inhibitor for Alzheimer’s disease treatment. Molecular characteristics and drug-likeness were analyzed after HR-LCMS revealed phytocompounds in an ethanolic extract of Psidium guajava fruit. Selected phytocompounds were subjected to molecular docking against AChE, with the best-docked compound then undergoing MD simulation, MMGBSA, DCCM, FEL, and PCA investigations to evaluate the complex stability. The hit compound’s potential toxicity and further pharmacokinetic features were also predicted. Anticholinesterase activity was also studied using in vitro assay. The HR-LCMS uncovered 68 compounds. Based on computational analysis, Fluspirilene was determined to have the highest potential to inhibit AChE. It was discovered that the Fluspirilene-AChE complex is stable and that Fluspirilene has a high binding affinity for AChE. Extract of Psidium guajava fruit significantly inhibits AChE (88.37% at 200 μg/ml). It is comparable to the standard AChE inhibitor Galantamine. Fluspirilene exhibited remarkable binding to AChE. Psidium guajava fruit extract demonstrated substantial AChE inhibitory activity, indicating its potential for Alzheimer’s treatment. The study underscores natural sources’ significance in drug discovery. Communicated by Ramaswamy H. Sarma</p

Egocentric_File_RSOS

The file Egocentric_File_RSOS.csv contains data corresponding to egocentric networks of 3,106,293 individuals derived from anonymized call detail records for a single month in the year 2007 from a mobile phone service provider in a European country

MOESM1 of Absence makes the heart grow fonder: social compensation when failure to interact risks weakening a relationship

Supplementary material. (pdf

Time progression of the onset and termination of the calling activity along the geographical longitude.

<p>Temporal progression of the onset and termination of the calling activity for cities lying at different geographical longitude. The time shift <i>n</i>*Δ that minimizes the divergence between the probability distribution of the first call <i>P</i>_<i>F</i> in a reference city and the corresponding distributions of the other different cities lying at the same latitude. 4 different bands are analyzed, centred at 37.5°N, 39.5°N, 41.5°N, and +43.1°N. For each city inside each band, the time shifts <i>n</i>*Δ for the 7 days of the week are shown, as the set of 7 points with the same color located at the corresponding time difference between the local meridians of each city and that of the reference. The dashed line represents the time shift between the sun transit time at the reference city and a hypothetical point located at each corresponding longitude. The error bars represent the standard deviation from the average value for each day of the week. From the plot it can be seen that, for cities lying further away from the reference city, a bigger time shift is required to collapse the distributions.</p

Temporal shift of the onset and termination times of the calling activity along geographical longitude.

<p>Probability distributions of the time of the last call <i>P</i>_<i>L</i>(<i>t</i>, <i>d</i>) and that of the first call <i>P</i>_<i>F</i>(<i>t</i>, <i>d</i>) for 5 different cities lying at the same latitude but at different relative longitudes from a reference point located at the second city from east to west within the band for two consecutive days during the year. The relative longitudes of the cities are -7.8°, -4.7°, -3.7°, 0°, and +3°. (Upper panel) Probability distributions for (A) the time of the last call, and (B) the time of first call. (Lower panel) Probability distributions for (C) the time of the last call, and (D) the time of first call, shifted by a time corresponding to the difference between their local sun transit times (31.2, 18.8, 14.8, and -12 minutes for the cities located at -7.8°, -4.7°, -3.7°, and +3° from the reference city, respectively). The collapse of the distributions onto the reference city’s distribution is evident when the longitudinal time shift is added. This collapse implies that the 5 cities begin (or cease) their calling activity in a way that is synchronized with a temporal phase corresponding to the difference between their sun transit times.</p

Probability distribution for finding a call at time t, for a particular in 2007.

<p>(green) Distribution when all the calls are included. (red) Distribution when only the last call at night is included (between 5:00 pm and 4:00 am next day). (blue) Distribution when only the first call of the day is included (between 5:00 am and 4:00 pm). The distribution of the last and first calls are sharper and have well-defined maxima.</p

The yearly evolution of the time of the first call and that of the last call compared against the yearly shift of the solar midnight.

<p>(Top sets) —average of the mean time of the first call of 3 sets of cities located at latitudinal bands centred at <i>ϕ</i> = 37°30′N (blue), 40°20′N (green), and 43°0′N (red). (bottom sets) —average of the mean time of the last call for the same sets of cities. In the middle of the panels, the solar midnight time in one of the cities within the band. The shape of resembles to some extent the graph of the solar midnight, coinciding with the two minima (for days 130 and 302) and one of the maxima (for day 210). For the case of , the graph shows some correspondence with the sunrise although to a lesser extent. The discontinuities introduced by the daylight saving shows in the graphs, suggesting that the period of low calling activity is not solely influenced by the socially-driven time, but is synchronized with an external (astronomical) event. The number of cities inside the bands <i>ϕ</i> = 37°30′N (blue), 40°20′N (green), and 43°0′N (red), are 7, 6, and 8, respectively.</p

Livogrit prevents Amiodarone-induced toxicity in experimental model of human liver (HepG2) cells and <i>Caenorhabditis elegans</i> by regulating redox homeostasis

Treatment with cationic amphiphilic drugs like Amiodarone leads to development of phospholipidosis, a type of lysosomal storage disorder characterized by excessive deposition of phospholipids. Such disorder in liver enhances accumulation of drugs and its metabolites, and dysregulates lipid profiles, which subsequently leads to hepatotoxicity. In the present study, we assessed pharmacological effects of herbal medicine, Livogrit, against hepatic phospholipidosis-induced toxicity. Human liver (HepG2) cells and in vivo model of Caenorhabditis elegans (N2 and CF1553 strains) were used to study effect of Livogrit on Amiodarone-induced phospholipidosis. In HepG2 cells, Livogrit treatment displayed enhanced uptake of acidic pH-based stains and reduced phospholipid accumulation, oxidative stress, AST, ALT, cholesterol levels, and gene expression of SCD-1 and LSS. Protein levels of LPLA2 were also normalized. Livogrit treatment restored Pgp functionality which led to decreased cellular accumulation of Amiodarone as observed by UHPLC analysis. In C. elegans, Livogrit prevented ROS generation, fat-6/7 gene overexpression, and lysosomal trapping of Amiodarone in N2 strain. SOD-3::GFP expression in CF1553 strain normalized by Livogrit treatment. Livogrit regulates phospholipidosis by regulation of redox homeostasis, phospholipid anabolism, and Pgp functionality hindered by lysosomal trapping of Amiodarone. Livogrit could be a potential therapeutic intervention for amelioration of drug-induced phospholipidosis and prevent hepatotoxicity.</p

Period of low calling activity and mid-sleep times for different age and gender cohorts.

<p>(a) Period of low calling activity <i>T</i>_<i>LCA</i>. The <i>T</i>_<i>LCA</i> is calculated as the elapsed time between the mean time of the last call and that of the first call, as a function of the age and gender of different cohorts, for the most populated city in the dataset in 2007. (b) mid-sleep time <i>t</i>_<i>mid</i>, calculated as the time in the middle of the interval between the mean time of the last call and that of the first call, as a function of the age and gender of different cohorts of the same city. For each age cohort, <i>T</i>_<i>LCA</i> and <i>t</i>_<i>mid</i> are calculated for females (circles) and males (triangles) separately. Both quantities are different for different days of the week, and the corresponding plots are shown for (green) Tuesdays, (red) Fridays, (blue) Saturdays, and (violet) Sundays. As Mondays to Thursdays have similar values, therefore only the data for Tuesdays is shown.</p

MOESM3 of Network of families in a contemporary population: regional and cultural assortativity

Types of triangles. The two different types of triangles that could be found in the network are shown in the figure (details in the caption). (PDF 167 kB