Based on a high throughput screening hit, pyrrolopyrimidine inhibitors of the Akt kinase are explored. X-ray co-crystal structures of two lead series results in the understanding of key binding interactions, the design of new lead series, and enhanced potency. The syntheses of these series and their biological activities are described. Spiroindoline 13j is found to have an Akt1 kinase IC(50) of 2.4+/-0.6 nM, Akt cell potency of 50+/-19 nM, and provides 68% inhibition of tumor growth in a mouse xenograft model (50 mg/kg, qd, po).
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http://dx.doi.org/10.1016/j.bmcl.2008.04.034 | DOI Listing |
Anal Chim Acta
February 2025
Institute of Basic and Translational Medicine & Shaanxi Key Laboratory of Brain Disorders, Xi'an Medical University, Xi'an, 710021, Shaanxi Province, PR China; Engineering Research Center of Brain Diseases Drug Development, Universities of Shaanxi Province, Xi'an Medical University, Xi'an, 710021, Shaanxi Province, PR China. Electronic address:
Background: Accurate quantification of microRNA (miRNA) is of great significance because it provides opportunities for the accurate early diagnosis of a series of human diseases including cancers. Currently, complicated nucleic acid amplification technologies are always required for the highly sensitive miRNA detection. The introduction of nucleic acid signal amplification coupled with various enzymes will inevitably lead to tedious work and increase the complexity of the analysis process.
View Article and Find Full Text PDFBrain Res
January 2025
Department of Computing Science, University of Alberta Edmonton Alberta Canada; Alberta Machine Intelligence Institute Edmonton Alberta Canada; Canada Institute for Advanced Research (CIFAR) AI Chair, Canada.
Humans are excellent at modifying our behaviour depending on context. For example, humans will change how they explore when losses are possible compared to when they are not possible. However, it remains unclear what specific cognitive and neural processes are modulated when exploring in different contexts.
View Article and Find Full Text PDFBioorg Med Chem Lett
January 2025
Calibr-Skaggs Institute for Innovative Medicines, a division of Scripps Research, La Jolla, CA 92037, United States. Electronic address:
Screening of the ChemDiv molecular library in cholesterol media against Mycobacterium tuberculosis (Mtb) H37Rv strain identified a novel isoxazole thiophene hit as a putative Rv1625c/Cya activator with a promising in vitro activity and good pharmacokinetic properties. Twenty-nine analogs were synthesized to assess the structure-activity relationships (SAR) to further improve potency. The most notable analog was P15, which showed an intramacrophage EC = 1.
View Article and Find Full Text PDFViruses
January 2025
Antiguo Hospital Civil de Guadalajara, "Fray Antonio Alcalde", Guadalajara 44280, Mexico.
This study investigates the relationship between SARS-CoV-2 RT-PCR cycle threshold (Ct) values and key COVID-19 transmission and outcome metrics across five years of the pandemic in Jalisco, Mexico. Utilizing a comprehensive time-series analysis, we evaluated weekly median Ct values as proxies for viral load and their temporal associations with positivity rates, reproduction numbers (Rt), hospitalizations, and mortality. Cross-correlation and lagged regression analyses revealed significant lead-lag relationships, with declining Ct values consistently preceding surges in positivity rates and hospitalizations, particularly during the early phases of the pandemic.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China.
Predicting the time series energy consumption data of manufacturing processes can optimize energy management efficiency and reduce maintenance costs for enterprises. Using deep learning algorithms to establish prediction models for sensor data is an effective approach; however, the performance of these models is significantly influenced by the quantity and quality of the training data. In real production environments, the amount of time series data that can be collected during the manufacturing process is limited, which can lead to a decline in model performance.
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