Synthesis of Thiazolo[5,4-f]quinazolin-9(8H)-ones as Multi-Target Directed Ligands of Ser/Thr Kinases

International audienceA library of thirty novel thiazolo[5,4-f]quinazolin-9(8H)-one derivatives belonging to four series designated as 12, 13, 14 and 15 was efficiently prepared, helped by microwave-assisted technology when required. The efficient multistep synthesis of methyl 6-amino-2-cyano- benzo[d]thiazole-7-carboxylate (1) has been reinvestigated and performed on a multigram scale. The inhibitory potency of the final products against five kinases involved in Alzheimer’s disease was evaluated. This study demonstrates that some molecules of the 12 and 13 series described in this paper are particularly promising for the development of new multi-target inhibitors of kinase

Hypothalamic circuitry underlying stress-induced insomnia and peripheral immunosuppression.

The neural substrates of insomnia/hyperarousal induced by stress remain unknown. Here, we show that restraint stress leads to hyperarousal associated with strong activation of corticotropin-releasing hormone neurons in the paraventricular nucleus of hypothalamus (CRHPVN) and hypocretin neurons in the lateral hypothalamus (HcrtLH). CRHPVN neurons directly innervate HcrtLH neurons, and optogenetic stimulation of LH-projecting CRHPVN neurons elicits hyperarousal. CRISPR-Cas9-mediated knockdown of the crh gene in CRHPVN neurons abolishes hyperarousal induced by stimulating LH-projecting CRHPVN neurons. Genetic ablation of Hcrt neurons or crh gene knockdown significantly counteracts restraint stress-induced hyperarousal. Single-cell mass cytometry by time of flight (CyTOF) revealed extensive changes to immune cell distribution and functional responses in peripheral blood during hyperarousal upon optogenetic stimulation of CRHPVN neurons simulating stress-induced insomnia. Our findings suggest both central and peripheral systems are synergistically engaged in the response to stress via CRHPVN circuitry

Integrated trajectories of the maternal metabolome, proteome, and immunome predict labor onset

Estimating the time of delivery is of high clinical importance because pre- and postterm deviations are associated with complications for the mother and her offspring. However, current estimations are inaccurate. As pregnancy progresses toward labor, major transitions occur in fetomaternal immune, metabolic, and endocrine systems that culminate in birth. The comprehensive characterization of maternal biology that precedes labor is key to understanding these physiological transitions and identifying predictive biomarkers of delivery. Here, a longitudinal study was conducted in 63 women who went into labor spontaneously. More than 7000 plasma analytes and peripheral immune cell responses were analyzed using untargeted mass spectrometry, aptamer-based proteomic technology, and single-cell mass cytometry in serial blood samples collected during the last 100 days of pregnancy. The high-dimensional dataset was integrated into a multiomic model that predicted the time to spontaneous labor [R = 0.85, 95% confidence interval (CI) [0.79 to 0.89], P = 1.2 × 10−40, N = 53, training set; R = 0.81, 95% CI [0.61 to 0.91], P = 3.9 × 10−7, N = 10, independent test set]. Coordinated alterations in maternal metabolome, proteome, and immunome marked a molecular shift from pregnancy maintenance to prelabor biology 2 to 4 weeks before delivery. A surge in steroid hormone metabolites and interleukin-1 receptor type 4 that preceded labor coincided with a switch from immune activation to regulation of inflammatory responses. Our study lays the groundwork for developing blood-based methods for predicting the day of labor, anchored in mechanisms shared in preterm and term pregnancies

Discovery of sparse, reliable omic biomarkers with Stabl

<p><span>Adoption of high-content omic technologies in clinical studies, coupled with computational </span><span>methods, have yielded an abundance of candidate biomarkers. However, translating such find</span><span>ings into bona fide clinical biomarkers remains challenging.</span> <span>To facilitate this process, we </span><span>introduce Stabl, a general machine learning framework that identifies a sparse, reliable set </span><span>of biomarkers by integrating noise injection and a data-driven signal-to-noise threshold into </span><span>multivariable predictive modeling.</span> <span>Evaluation of Stabl on synthetic datasets and five inde</span><span>pendent clinical studies demonstrates improved biomarker sparsity and reliability compared to </span><span>commonly used sparsity-promoting regularization methods while maintaining predictive per</span><span>formance; it distills datasets containing 1,400 to 35,000 features down to 4 to 34 candidate </span><span>biomarkers. Stabl extends to multi-omic integration tasks, enabling biological interpretation of </span><span>complex predictive models, as it hones in on a shortlist of proteomic, metabolomic, and cyto</span><span>metric events predicting labor onset, microbial biomarkers of preterm birth, and a pre-operative </span><span>immune signature of post-surgical infections.</span></p><p>Funding provided by: Stanford University<br>Crossref Funder Registry ID: http://dx.doi.org/10.13039/100005492<br>Award Number: </p&gt

Synthesis of polyfunctionalized benzo[d]thiazoles as novel anthranilic acid derivatives

International audienceA small library of valuable novel polyfunctionalized benzo[d]thiazole derivatives was prepared in a straightforward and convenient manner. Here again, 4,5-dichloro-1,2,3-dithiazolium chloride (Appel salt) proved to be an efficient agent for merging a 2-cyanothiazole ring to an arene counterpart

Synthesis of Thiazolo[5,4-f]quinazolin-9(8H)-ones as Multi-Target Directed Ligands of Ser/Thr Kinases

A library of thirty novel thiazolo[5,4-f]quinazolin-9(8H)-one derivatives belonging to four series designated as 12, 13, 14 and 15 was efficiently prepared, helped by microwave-assisted technology when required. The efficient multistep synthesis of methyl 6-amino-2-cyano- benzo[d]thiazole-7-carboxylate (1) has been reinvestigated and performed on a multigram scale. The inhibitory potency of the final products against five kinases involved in Alzheimer’s disease was evaluated. This study demonstrates that some molecules of the 12 and 13 series described in this paper are particularly promising for the development of new multi-target inhibitors of kinases

Proteomic Biomarkers of the Apnea Hypopnea Index and Obstructive Sleep Apnea:Insights into the Pathophysiology of Presence, Severity, and Treatment Response

Obstructive sleep apnea (OSA), a disease associated with excessive sleepiness and increased cardiovascular risk, affects an estimated 1 billion people worldwide. The present study examined proteomic biomarkers indicative of presence, severity, and treatment response in OSA. Participants (n = 1391) of the Stanford Technology Analytics and Genomics in Sleep study had blood collected and completed an overnight polysomnography for scoring the apnea–hypopnea index (AHI). A highly multiplexed aptamer-based array (SomaScan) was used to quantify 5000 proteins in all plasma samples. Two separate intervention-based cohorts with sleep apnea (n = 41) provided samples pre- and post-continuous/positive airway pressure (CPAP/PAP). Multivariate analyses identified 84 proteins (47 positively, 37 negatively) associated with AHI after correction for multiple testing. Of the top 15 features from a machine learning classifier for AHI ≥ 15 vs. AHI < 15 (Area Under the Curve (AUC) = 0.74), 8 were significant markers of both AHI and OSA from multivariate analyses. Exploration of pre- and post-intervention analysis identified 5 of the 84 proteins to be significantly decreased following CPAP/PAP treatment, with pathways involving endothelial function, blood coagulation, and inflammatory response. The present study identified PAI-1, tPA, and sE-Selectin as key biomarkers and suggests that endothelial dysfunction and increased coagulopathy are important consequences of OSA, which may explain the association with cardiovascular disease and stroke

Integrated trajectories of the maternal metabolome, proteome, and immunome predict labor onset.

Estimating the time of delivery is of high clinical importance because pre- and postterm deviations are associated with complications for the mother and her offspring. However, current estimations are inaccurate. As pregnancy progresses toward labor, major transitions occur in fetomaternal immune, metabolic, and endocrine systems that culminate in birth. The comprehensive characterization of maternal biology that precedes labor is key to understanding these physiological transitions and identifying predictive biomarkers of delivery. Here, a longitudinal study was conducted in 63 women who went into labor spontaneously. More than 7000 plasma analytes and peripheral immune cell responses were analyzed using untargeted mass spectrometry, aptamer-based proteomic technology, and single-cell mass cytometry in serial blood samples collected during the last 100 days of pregnancy. The high-dimensional dataset was integrated into a multiomic model that predicted the time to spontaneous labor [R = 0.85, 95% confidence interval (CI) [0.79 to 0.89], P = 1.2 × 10-40, N = 53, training set; R = 0.81, 95% CI [0.61 to 0.91], P = 3.9 × 10-7, N = 10, independent test set]. Coordinated alterations in maternal metabolome, proteome, and immunome marked a molecular shift from pregnancy maintenance to prelabor biology 2 to 4 weeks before delivery. A surge in steroid hormone metabolites and interleukin-1 receptor type 4 that preceded labor coincided with a switch from immune activation to regulation of inflammatory responses. Our study lays the groundwork for developing blood-based methods for predicting the day of labor, anchored in mechanisms shared in preterm and term pregnancies