Response times to probes.

<p>Response times to probes following word pair presentations that either included a threat word (Threat) or did not include a threat word (Neutral). Graphs illustrate response times to probes in the attended (A) and unattended (B) locations following worry inductions or following mental arithmetic. Bars represent 95% confidence intervals <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0013411#pone.0013411-Cumming1" target="_blank">[73]</a> around the means after adjusting for between-subject variance <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0013411#pone.0013411-Loftus1" target="_blank">[74]</a>. *<i>p</i><0.05.</p

Identification of Amides as Carboxylic Acid Surrogates for Quinolizidinone-Based M₁ Positive Allosteric Modulators

Selective activation of the M₁ muscarinic receptor via positive allosteric modulation represents an approach to treat the cognitive decline in patients with Alzheimer's disease. A series of amides were examined as a replacement for the carboxylic acid moiety in a class of quinolizidinone carboxylic acid M₁ muscarinic receptor positive allosteric modulators, and leading pyran <b>4o</b> and cyclohexane <b>5c</b> were found to possess good potency and in vivo efficacy

Pathway/process context matters.

<p>Not all pathways/processes that contain genes with extreme values are significant suggesting that the approach may be resistant to to outliers. For example, ITGB3 and APP are clear outliers with Z* scores of 7.18 and -7.1, respectively but not all of their corresponding pathways/processes were found to be significant regulators of Aβ42. Each circle corresponds to pathway/process and the size corresponds to the number of genes in that pathway/process. Y-axis represents the likelihood of a pathway of a given size to have the corresponding net or absolute PI score by chance. Black dotted line corresponds to p-value = 0.01 or -log₁₀(p-value) = 2 and the x-axis corresponds to the either Net or ABS PI score based on the Aβ42 readout.</p

Identification of pathways that regulate APP processing (Aβ42).

<p>A. By combining the <i>P</i>-value and PI score, we identified pathways/processes that, when knocked down, significantly affect the readout in question. Depicted here are the results for Aβ42 readout. Each circle represents a process/pathway set and the size of the circle corresponds to the number of genes, measured in the screen, that comprise each pathway. Colors correspond to the database from which the pathway/process set was derived. Y-axis represents the likelihood of a pathway of a given size to have the corresponding net or absolute PI score by chance. Black dotted line corresponds to p-value = 0.01 or -log₁₀(p-value) = 2. One of the most significant sets was the AD pathway as defined by KEGG (red arrow). This pathway contains γ-secretase, β secretase, and other enzymes known to either cleave APP or degrade Aβ42. B. Clustering of candidate pathways/processes based on gene overlap. The overlap between two pathways/processes is determined by the ratio of the overlap of the smaller with the larger set to the size of the smaller set (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0115369#sec008" target="_blank">materials and methods</a>). Clusters (black boxes) of highly overlapping pathways/processes were identified using hierarchical clustering. Cluster 4 contains the AD pathway. This type of representation also allows for the identification of interplay across the different pathways/processes. For example, the red-dashed squares indicate overlap between sets in Cluster 3 (inflammation and cell adhesion) with genes in Cluster 6 (mRNA processing, translation, and transcription). The table captures each cluster which consists of pathways/processes that share similar overlapping patterns. Several of these pathways/processes have been implicated in modulating γ-secretase activity, have been implicated in AD pathogenesis, and/or are under consideration as strategies for the treatment and prevention of AD [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0115369#pone.0115369.ref001" target="_blank">1</a>,<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0115369#pone.0115369.ref003" target="_blank">3</a>,<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0115369#pone.0115369.ref007" target="_blank">7</a>,<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0115369#pone.0115369.ref024" target="_blank">24</a>].</p

Pathways/processes that differentially regulate Aβ42 vs. Aβ40 production.

<p>A. Scatter plot of -log(-<i>P</i>-values) for Net PI scores of pathways/processes for Aβ42 against that for Aβ40. Each circle represents a pathway/process. The size of the circle corresponds to the number of genes in the set. The color corresponds to the database source from which the pathway/process was derived. As expected, most pathways and processes that regulate Aβ40 also regulate Aβ42 production. However, there are some “modulator” pathways that are significant for one readout but not the other. Red square: Aβ42-regulating pathways. Blue square: Aβ40-specific pathways.</p

MK-7622: A First-in-Class M₁ Positive Allosteric Modulator Development Candidate

Identification of ligands that selectively activate the M₁ muscarinic signaling pathway has been sought for decades to treat a range of neurological and cognitive disorders. Herein, we describe the optimization efforts focused on addressing key physicochemical and safety properties, ultimately leading to the clinical candidate MK-7622, a highly selective positive allosteric modulator of the M₁ muscarinic receptor that has entered Phase II studies in patients with Alzheimer’s disease