Translation fidelity relies on accurate aminoacylation of transfer RNAs (tRNAs) by aminoacyl-tRNA synthetases (AARSs). AARSs specific for alanine (Ala), leucine (Leu), serine, and pyrrolysine do not recognize the anticodon bases. Single nucleotide anticodon variants in their cognate tRNAs can lead to mistranslation. Human genomes include both rare and more common mistranslating tRNA variants. We investigated three rare human tRNALeu variants that mis-incorporate Leu at phenylalanine or tryptophan codons. Expression of each tRNALeu anticodon variant in neuroblastoma cells caused defects in fluorescent protein production without significantly increased cytotoxicity under normal conditions or in the context of proteasome inhibition. Using tRNA sequencing and mass spectrometry we confirmed that each tRNALeu variant was expressed and generated mistranslation with Leu. To probe the flexibility of the entire genetic code towards Leu mis-incorporation, we created 64 yeast strains to express all possible tRNALeu anticodon variants in a doxycycline-inducible system. While some variants showed mild or no growth defects, many anticodon variants, enriched with G/C at positions 35 and 36, including those replacing Leu for proline, arginine, alanine, or glycine, caused dramatic reductions in growth. Differential phenotypic defects were observed for tRNALeu mutants with synonymous anticodons and for different tRNALeu isoacceptors with the same anticodon. A comparison to tRNAAla anticodon variants demonstrates that Ala mis-incorporation is more tolerable than Leu at nearly every codon. The data show that the nature of the amino acid substitution, the tRNA gene, and the anticodon are each important factors that influence the ability of cells to tolerate mistranslating tRNAs.
Abstract: The need for large-scale production of highly accurate simulated event samples for the extensive physics programme of the ATLAS experiment at the Large Hadron Collider motivates the development of new simulation techniques. Building on the recent success of deep learning algorithms, variational autoencoders and generative adversarial networks are investigated for modelling the response of the central region of the ATLAS electromagnetic calorimeter to photons of various energies. The properties of synthesised showers are compared with showers from a full detector simulation using geant4. Both variational autoencoders and generative adversarial networks are capable of quickly simulating electromagnetic showers with correct total energies and stochasticity, though the modelling of some shower shape distributions requires more refinement. This feasibility study demonstrates the potential of using such algorithms for ATLAS fast calorimeter simulation in the future and shows a possible way to complement current simulation techniques.
Charged particle reconstruction in the presence of many simultaneous proton–proton (pp) collisions in the LHC is a challenging task for the ATLAS experiment’s reconstruction software due to the combinatorial complexity. This paper describes the major changes made to adapt the software to reconstruct high-activity collisions with an average of 50 or more simultaneous pp interactions per bunch crossing (pile-up) promptly using the available computing resources. The performance of the key components of the track reconstruction chain and its dependence on pile-up are evaluated, and the improvement achieved compared to the previous software version is quantified. For events with an average of 60pp collisions per bunch crossing, the updated track reconstruction is twice as fast as the previous version, without significant reduction in reconstruction efficiency and while reducing the rate of combinatorial fake tracks by more than a factor two.
Hoarding disorder (HD) is marked by difficulty discarding possessions. Many refuse treatment or drop out, which may be due to treatment's incorporation of in-home decluttering, which is feared and avoided. Thus, strategies to prepare patients for decluttering/discarding are needed. Imaginal exposure (IE), or imagining one's worst fears about discarding, could be one such strategy. This pilot preliminarily tested a short-duration IE intervention compared with a control intervention. Over 3 days, adults diagnosed with HD (n = 32) were randomly assigned to either write about and imagine their worst fears about discarding (IE condition) or a neutral topic (control writing [CW] condition). The IE condition showed significant improvements in HD symptoms from preintervention to 1-week follow-up, with medium to large effects; however, the CW condition did as well. Comparing change scores between conditions, the IE condition's improvements were not significantly different than the CW condition's. Overall, IE was helpful in improving HD symptoms, but this pilot did not indicate that it was more helpful than CW. This raises important questions about possible demand characteristics, placebo effects, or regression to the mean, and it has implications for the design and methodology of other studies assessing IE's utility.
Genetic diversity is a fundamental component of biodiversity. Examination of global patterns of genetic diversity can help highlight mechanisms underlying species diversity, though a recurring challenge has been that patterns may vary by molecular marker. Here, we compiled 6862 observations of genetic diversity from 492 species of marine fish and tested among hypotheses for diversity gradients: the founder effect hypothesis, the kinetic energy hypothesis, and the productivity-diversity hypothesis. We fit generalized linear mixed effect models (GLMMs) and explored the extent to which various macroecological drivers (latitude, longitude, temperature (SST), and chlorophyll-a concentration) explained variation in genetic diversity. We found that mitochondrial genetic diversity followed geographic gradients similar to those of species diversity, being highest near the Equator, particularly in the Coral Triangle, while nuclear genetic diversity did not follow clear geographic patterns. Despite these differences, all genetic diversity metrics were correlated with chlorophyll-a concentration, while mitochondrial diversity was also positively associated with SST. Our results provide support for the kinetic energy hypothesis, which predicts that elevated mutation rates at higher temperatures increase mitochondrial but not necessarily nuclear diversity, and the productivity-diversity hypothesis, which posits that resource-rich regions support larger populations with greater genetic diversity. Overall, these findings reveal how environmental variables can influence mutation rates and genetic drift in the ocean, caution against using mitochondrial macrogenetic patterns as proxies for whole-genome diversity, and aid in defining global gradients of genetic diversity.
Many animals and plants have species-typical annual cycles, but individuals vary in their timing of life-history events. Individual variation in fur replacement (moult) timing is poorly understood in mammals due to the challenge of repeated observations and longitudinal sampling. We examined factors that influence variation in moult duration and timing among elephant seals (Mirounga angustirostris). We quantified the onset and progression of fur loss in 1178 individuals. We found that an exceptionally rapid visible moult (7 days, the shortest of any mammals or birds), and a wide range of moult start dates (spanning 6-10× the event duration) facilitated high asynchrony across individuals (only 20% of individuals in the population moulting at the same time). Some of the variation was due to reproductive state, as reproductively mature females that skipped a breeding season moulted a week earlier than reproductive females. Moreover, individual variation in timing and duration within age-sex categories far outweighed (76-80%) variation among age-sex categories. Individuals arriving at the end of the moult season spent 50% less time on the beach, which allowed them to catch up in their annual cycles and reduce population-level variance during breeding. These findings underscore the importance of individual variation in annual cycles.
Wayfinding systems using inertial data recorded from a smartphone carried by the walker have great potential for increasing mobility independence of blind pedestrians. Pedestrian dead-reckoning (PDR) algorithms for localization require estimation of the step length of the walker. Prior work has shown that step length can be reliably predicted by processing the inertial data recorded by the smartphone with a simple machine learning algorithm. However, this prior work only considered sighted walkers, whose gait may be different from that of blind walkers using a long cane or a dog guide. In this work, we show that a step length estimation network trained on data from sighted walkers performs poorly when tested on blind walkers, and that retraining with data from blind walkers can dramatically increase the accuracy of step length prediction.
