Lipophilic efficiency (LipE) is an important metric that has been increasingly applied in drug discovery medicinal chemistry lead optimization programs. In this Perspective, using literature drug ...discovery examples, we discuss the concept of rigorously applying LipE to guide medicinal chemistry lead optimization toward drug candidates with potential for superior in vivo efficacy and safety, especially when guided by physiochemical property-based optimization (PPBO). Also highlighted are examples of small structural modifications such as addition of single atoms, small functional groups, and cyclization that produce large increases in LipE. Understanding the factors that may contribute to LipE changes through analysis of ligand–protein crystal structures and using structure-based drug design (SBDD) to increase LipE by design is also discussed. Herein we advocate for use of LipE analysis coupled with PPBO and SBDD as an efficient mechanism for drug design.
For many complex traits, gene regulation is likely to play a crucial mechanistic role. How the genetic architectures of complex traits vary between populations and subsequent effects on genetic ...prediction are not well understood, in part due to the historical paucity of GWAS in populations of non-European ancestry. We used data from the MESA (Multi-Ethnic Study of Atherosclerosis) cohort to characterize the genetic architecture of gene expression within and between diverse populations. Genotype and monocyte gene expression were available in individuals with African American (AFA, n = 233), Hispanic (HIS, n = 352), and European (CAU, n = 578) ancestry. We performed expression quantitative trait loci (eQTL) mapping in each population and show genetic correlation of gene expression depends on shared ancestry proportions. Using elastic net modeling with cross validation to optimize genotypic predictors of gene expression in each population, we show the genetic architecture of gene expression for most predictable genes is sparse. We found the best predicted gene in each population, TACSTD2 in AFA and CHURC1 in CAU and HIS, had similar prediction performance across populations with R2 > 0.8 in each population. However, we identified a subset of genes that are well-predicted in one population, but poorly predicted in another. We show these differences in predictive performance are due to allele frequency differences between populations. Using genotype weights trained in MESA to predict gene expression in independent populations showed that a training set with ancestry similar to the test set is better at predicting gene expression in test populations, demonstrating an urgent need for diverse population sampling in genomics. Our predictive models and performance statistics in diverse cohorts are made publicly available for use in transcriptome mapping methods at https://github.com/WheelerLab/DivPop.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Applying machine learning to continuous acoustic emissions, signals previously deemed noise, from laboratory faults and slowly slipping subduction‐zone faults, demonstrates hidden signatures are ...emitted that describe physical details, including fault displacement and friction. However, no evidence currently exists to demonstrate that similar hidden signals occur during seismogenic stick‐slip on earthquake faults—the damaging earthquakes of most societal interest. We show that continuous seismic emissions emitted during the 2018 multi‐month caldera collapse sequence at the Kı̄lauea volcano in Hawai'i contain hidden signatures characterizing the earthquake cycle. Multi‐spectral data features extracted from 30 s intervals of the continuous seismic emission are used to train a gradient boosted tree regression model to predict the GNSS‐derived contemporaneous surface displacement and time‐to‐failure of the upcoming collapse event. This striking result suggests that at least some faults emit such signals and provide a potential path to characterizing the instantaneous and future behavior of earthquake faults.
Plain Language Summary
Applications of machine learning have revealed that continuous acoustic emissions from laboratory earthquake experiments contain continuous, hidden signatures that describe the fault slip. In these laboratory studies, the acoustic emissions signals that were previously deemed to be dominantly noise, are found to be rich with details that can describe physical properties such as the fault displacement, friction, and fault thickness. By applying similar machine learning approaches, it was discovered that signatures of surface displacement exist in the seismic emissions from slowly slipping subduction zone faults. However, there has yet to be similar evidence observed during seismogenic stick‐slip on earthquake faults–the damaging earthquakes of most societal interest. Here we study a repeating caldera collapse sequence with short enough repeat times to mimic the experiments performed in the laboratory. We find that seismic emissions from seismogenic fault slip associated with the 2018 caldera collapse at the Kı̄lauea volcano in Hawai'i, also contain hidden signatures informing of instantaneous surface displacement associated with fault slip at depth, as well as time‐to‐failure of the upcoming slip event. These observations suggest that at least some seismogenic faults emit such signals, and provide a potential path to characterizing the instantaneous and future behavior of earthquake faults.
Key Points
Features extracted from 30 s of continuous seismic waveforms contain information about contemporaneous GNSS ground displacements
A gradient boosted tree model predicts GNSS ground displacements and timing of the next caldera collapse event
The observations suggest some seismogenic faults emit precursory signals, providing a potential path to characterize behavior of faults
The widespread and increasing use of cooperative learning is one of the great success stories of social and educational psychology. Its success largely rests on the relationships among theory, ...research, and practice. Social interdependence theory provides a foundation on which cooperative learning is built. More than 1,200 research studies have been conducted in the past 11 decades on cooperative, competitive, and individualistic efforts. Findings from these studies have validated, modified, refined, and extended the theory. From the theory, procedures for the teacher's role in using formal and informal cooperative learning and cooperative base groups have been operationalized. Those procedures are widely used by educators throughout the world. The applications have resulted in revisions of the theory and the generation of new research.
The value of big old fat fecund female fish (BOFFFFs) in fostering stock productivity and stability has long been underappreciated by conventional fisheries science and management, although Hjort ...(1914) indirectly alluded to the importance of maternal effects. Compared with smaller mature females, BOFFFFs in a broad variety of marine and freshwater teleosts produce far more and often larger eggs that may develop into larvae that grow faster and withstand starvation better. As (if not more) importantly, BOFFFFs in batch-spawning species tend to have earlier and longer spawning seasons and may spawn in different locations than smaller females. Such features indicate that BOFFFFs are major agents of bet-hedging strategies that help to ensure individual reproductive success in environments that vary tremendously in time and space. Even if all else were equal, BOFFFFs can outlive periods that are unfavourable for successful reproduction and be ready to spawn profusely and enhance recruitment when favourable conditions return (the storage effect). Fishing differentially removes BOFFFFs, typically resulting in severe truncation of the size and age structure of the population. In the worst cases, fishing mortality acts as a powerful selective agent that inhibits reversal of size and age truncation, even if fishing intensity is later reduced. Age truncation is now known to destabilize fished populations, increasing their susceptibility to collapse. Although some fisheries models are beginning to incorporate maternal and other old-growth effects, most continue to treat all spawning-stock biomass as identical: many small young females are assumed to contribute the same to stock productivity as an equivalent mass of BOFFFFs. A growing body of knowledge dictates that fisheries productivity and stability would be enhanced if management conserved old-growth age structure in fished stocks, be it by limiting exploitation rates, by implementing slot limits, or by establishing marine reserves, which are now known to seed surrounding fished areas via larval dispersal. Networks of marine reserves are likely to be the most effective means of ensuring that pockets of old-growth age structure survive throughout the geographic range of demersal species.
Non-biological experimental variation or "batch effects" are commonly observed across multiple batches of microarray experiments, often rendering the task of combining data from these batches ...difficult. The ability to combine microarray data sets is advantageous to researchers to increase statistical power to detect biological phenomena from studies where logistical considerations restrict sample size or in studies that require the sequential hybridization of arrays. In general, it is inappropriate to combine data sets without adjusting for batch effects. Methods have been proposed to filter batch effects from data, but these are often complicated and require large batch sizes ( > 25) to implement. Because the majority of microarray studies are conducted using much smaller sample sizes, existing methods are not sufficient. We propose parametric and non-parametric empirical Bayes frameworks for adjusting data for batch effects that is robust to outliers in small sample sizes and performs comparable to existing methods for large samples. We illustrate our methods using two example data sets and show that our methods are justifiable, easy to apply, and useful in practice. Software for our method is freely available at: http://biosun1.harvard.edu/complab/batch/.
ABSTRACT
We investigate the impact of bursts in star formation on the predictions of one-zone chemical evolution models, adopting oxygen (O), iron (Fe), and strontium (Sr), as representative α, ...iron-peak, and s-process elements, respectively. To this end, we develop and make use of the Versatile Integrator for Chemical Evolution (VICE), a python package designed to handle flexible user-specified evolutionary parameters. Starbursts driven by a temporary boost of gas accretion rate create loops in O/Fe–Fe/H evolutionary tracks and a peak in the stellar O/Fe distribution at intermediate values. Bursts driven by a temporary boost of star formation efficiency have similar effects, and they also produce a population of α-deficient stars during the depressed star formation phase following the burst. This α-deficient population is more prominent if the outflow rate is tied to a time-averaged star formation rate (SFR) instead of the instantaneous SFR. Theoretical models of Sr production predict a strong metallicity dependence of supernova and asymptotic giant branch star yields, though comparison to data suggests an additional, nearly metallicity-independent source. Evolution of Sr/Fe and Sr/O during a starburst is complex because of this metallicity dependence and the multiple time-scales at play. Moderate amplitude (10–20 per cent) sinusoidal oscillations in SFR produce loops in O/Fe–Fe/H tracks and multiple peaks in O/Fe distributions, a potential source of intrinsic scatter in observed sequences. We investigate the impact of a factor ∼2 enhancement of Galactic star formation ∼2 Gyr ago, as suggested by some recent observations. VICE is publicly available at <http://pypi.org/project/vice/>.
Objective
The goal of this narrative review is to provide an overview of migraine pathophysiology, with an emphasis on the role of calcitonin gene‐related peptide (CGRP) within the context of the ...trigeminovascular system.
Background
Migraine is a prevalent and disabling neurological disease that is characterized in part by intense, throbbing, and unilateral headaches. Despite recent advances in understanding its pathophysiology, migraine still represents an unmet medical need, as it is often underrecognized and undertreated. Although CGRP has been known to play a pivotal role in migraine for the last 2 decades, this has now received more interest spurred by the early clinical successes of drugs that block CGRP signaling in the trigeminovascular system.
Design
This narrative review presents an update on the role of CGRP within the trigeminovascular system. PubMed searches were used to find recent (ie, 2016 to November 2018) published articles presenting new study results. Review articles are also included not as primary references but to bring these to the attention of the reader. Original research is referenced in describing the core of the narrative, and review articles are used to support ancillary points.
Results
The trigeminal ganglion neurons provide the connection between the periphery, stemming from the interface between the primary afferent fibers of the trigeminal ganglion and the meningeal vasculature and the central terminals in the trigeminal nucleus caudalis. The neuropeptide CGRP is abundant in trigeminal ganglion neurons, and is released from the peripheral nerve and central nerve terminals as well as being secreted within the trigeminal ganglion. Release of CGRP from the peripheral terminals initiates a cascade of events that include increased synthesis of nitric oxide and sensitization of the trigeminal nerves. Secreted CGRP in the trigeminal ganglion interacts with adjacent neurons and satellite glial cells to perpetuate peripheral sensitization, and can drive central sensitization of the second‐order neurons. A shift in central sensitization from activity‐dependent to activity‐independent central sensitization may indicate a mechanism driving the progression of episodic migraine to chronic migraine. The pathophysiology of cluster headache is much more obscure than that of migraine, but emerging evidence suggests that it may also involve hypersensitivity of the trigeminovascular system. Ongoing clinical studies with therapies targeted at CGRP will provide additional, valuable insights into the pathophysiology of this disorder.
Conclusions
CGRP plays an essential role in the pathophysiology of migraine. Treatments that interfere with the functioning of CGRP in the peripheral trigeminal system are effective against migraine. Blocking sensitization of the trigeminal nerve by attenuating CGRP activity in the periphery may be sufficient to block a migraine attack. Additionally, the potential exists that this therapeutic strategy may also alleviate cluster headache as well.
The catalytic activity of the ribosome is mediated by RNA, yet proteins are essential for the function of the peptidyl transferase center (PTC). In eukaryotes, final assembly of the PTC occurs in the ...cytoplasm by insertion of the ribosomal protein Rpl10 (uL16). We determine structures of six intermediates in late nuclear and cytoplasmic maturation of the large subunit that reveal a tightly-choreographed sequence of protein and RNA rearrangements controlling the insertion of Rpl10. We also determine the structure of the biogenesis factor Yvh1 and show how it promotes assembly of the P stalk, a critical element for recruitment of GTPases that drive translation. Together, our structures provide a blueprint for final assembly of a functional ribosome.
Recent studies suggest that activation of the peripheral immune system elicits a discordant central (i.e., in the brain) inflammatory response in aged but otherwise healthy subjects compared with ...younger cohorts. A fundamental difference in the reactive state of microglial cells in the aged brain has been suggested as the basis for this discordant inflammatory response. Thus, the aging process appears to serve as a “priming” stimulus for microglia, and upon secondary stimulation with a triggering stimulus (i.e., peripheral signals communicating infection), these primed microglia release excessive quantities of proinflammatory cytokines. Subsequently, this exaggerated cytokine release elicits exaggerated behavioral changes including anorexia, hypersomnia, lethargy, decreased social interaction, and deficits in cognitive and motor function (collectively known as the sickness behavior syndrome). Whereas this reorganization of host priorities is normally adaptive in young subjects, there is a propensity for this response to be maladaptive in aged subjects, resulting in greater severity and duration of the sickness behavior syndrome. Consequently, acute bouts of cognitive impairment in elderly subjects increase the likelihood of poor self‐care behaviors (i.e., anorexia, weight loss, noncompliance), which ultimately leads to higher rates of hospitalization and mortality.
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