bluuebunny/crossref_metadata_2025 huggingface dataset:
Routes of importation and spatial dynamics of SARS-CoV-2 variants during localised interventions in Chile
Authors: Gutierrez Bernardo , Tsui Joseph L.-H. , Pullano Giulia , Mazzoli Mattia , Gangavarapu Karthik , Inward Rhys P.D. , Bajaj Sumali , Evans Pena Rosario , Busch-Moreno Simon , Suchard Marc A. , Pybus Oliver G. , Dunner Alejandra , Puentes Rodrigo , Ayala Salvador , Fernandez Jorge , Araos Rafael , Ferres Leo , Colizza Vittoria , Kraemer Moritz U.G.
Published: January 2024

South America suffered large SARS-CoV-2 epidemics between 2020 and 2022 caused by multiple variants of interest and concern, some causing substantial morbidity and mortality. However, their transmission dynamics are poorly characterised. The epidemic situation in Chile enables us to investigate differences in the distribution and spread of variants Alpha, Gamma, Lambda, Mu and Delta. Chile implemented non-pharmaceutical interventions and an integrated genomic and epidemiological surveillance system that included airport and community surveillance to track SARS-CoV-2 variants. Here we combine viral genomic data and anonymised human mobility data from mobile phones to characterise the routes of importation of different variants into Chile, the relative contributions of airport-based importations to viral diversity versus land border crossings and test the impact of the mobility network on the diffusion of viral lineages within the country. We find that Alpha, Lambda and Mu were identified in Chile via airport surveillance six, four and five weeks ahead of their detection via community surveillance, respectively. Further, some variants that originated in South America were imported into Chile via land rather than international air travel, most notably Gamma. Different variants exhibited similar trends of viral dissemination throughout the country following their importation, and we show that the mobility network predicts the time of arrival of imported lineages to different Chilean comunas. Higher stringency of local NPIs was also associated with fewer domestic viral importations. Our results show how genomic surveillance combined with high resolution mobility data can help predict the multi-scale geographic expansion of emerging infectious diseases.

Significance statement

Global preparedness for pandemic threats requires an understanding of the global variations of spatiotemporal transmission dynamics. Regional differences are important because the local context sets the conditions for the unfolding of local epidemics, which in turn affect transmission dynamics at a broader scale. Knowledge gaps from the SARS-CoV-2 pandemic remain for regions like South America, where distinct sets of viral variants emerged and spread from late 2020 onwards, and where changes in human behaviour resulted in epidemics which differed from those observed in other regions. Our interdisciplinary analysis of the SARS-CoV-2 epidemic in Chile provides insights into the spatiotemporal trends of viral diffusion in the region which shed light on the drivers that can influence future epidemic waves and pandemics.
Speedy benthi: Elongated photoperiods reduce generation times of the model plant speciesNicotiana benthamiana
Authors: Castle Matthew , Lüdke Daniel
Published: January 2024

Nicotiana benthamianais increasingly gaining prominence as a model plant species with recently published high-quality genome assemblies, which will further enable forward and reverse genetic approaches (Bally et al., 2018; Derevnina et al., 2019; Kourelis et al., 2019; Ranawaka et al., 2023; Vollheyde et al., 2023). However, the generation time ofN. benthamianaposes a bottleneck in the creation of mutant and transgenic plant lines. Speed breeding (SB), by extended photoperiods and adjustments to growth parameters, is an efficient way to reduce generation times for many crop and model plant species (Ghosh et al., 2018; Watson et al., 2018; Hickey et al., 2019; Varshney et al., 2021). We hypothesized that an extended photoperiod could reduce the seed to seed generation time ofN. benthamiana. We tested this hypothesis by comparing generation times under SB conditions to traditionally used photoperiods in growth chambers and green house settings. We found that a 22h photoperiod reduced the generation time ofN. benthamianaby approximately 2 weeks (16-22%). Fertilization in combination with a far-red light spectrum did not yield a further reduction in generation time when combined with SB conditions. Our findings further contribute to the establishment ofN. benthamianaas an important model organism for plant research.
Statistical inference with a manifold-constrained RNA velocity model uncovers cell cycle speed modulations
Authors: Lederer Alex R. , Leonardi Maxine , Talamanca Lorenzo , Herrera Antonio , Droin Colas , Khven Irina , Carvalho Hugo J.F. , Valente Alessandro , Mantes Albert Dominguez , Arabí Pau Mulet , Pinello Luca , Naef Felix , Manno Gioele La
Published: January 2024

Across a range of biological processes, cells undergo coordinated changes in gene expression, resulting in transcriptome dynamics that unfold within a low-dimensional manifold. Single-cell RNA-sequencing (scRNA-seq) only measures temporal snapshots of gene expression. However, information on the underlying low-dimensional dynamics can be extracted using RNA velocity, which models unspliced and spliced RNA abundances to estimate the rate of change of gene expression. Available RNA velocity algorithms can be fragile and rely on heuristics that lack statistical control. Moreover, the estimated vector field is not dynamically consistent with the traversed gene expression manifold. Here, we develop a generative model of RNA velocity and a Bayesian inference approach that solves these problems. Our model couples velocity field and manifold estimation in a reformulated, unified framework, so as to coherently identify the parameters of an autonomous dynamical system. Focusing on the cell cycle, we implementedVeloCycleto study gene regulation dynamics on one-dimensional periodic manifolds and validated using live-imaging its ability to infer actual cell cycle periods. We benchmarked RNA velocity inference with sensitivity analyses and demonstrated one- and multiple-sample testing. We also conducted Markov chain Monte Carlo inference on the model, uncovering key relationships between gene-specific kinetics and our gene-independent velocity estimate. Finally, we appliedVeloCycletoin vivosamples andin vitrogenome-wide Perturb-seq, revealing regionally-defined proliferation modes in neural progenitors and the effect of gene knockdowns on cell cycle speed. Ultimately,VeloCycleexpands the scRNA-seq analysis toolkit with a modular and statistically rigorous RNA velocity inference framework.
Development of a metabolic engineering technology to simultaneously suppress the expression of multiple genes in yeast and application in carotenoid production
Authors: Yamada Ryosuke , Yamamoto Chihiro , Sakaguchi Rumi , Matsumoto Takuya , Ogino Hiroyasu
Published: January 2024

In yeast metabolic engineering, there is a need for technologies that simultaneously suppress and regulate the expression of multiple genes and improve the production of target chemicals. In this study, we aimed to develop a novel technology that simultaneously suppresses the expression of multiple genes by combining RNA interference with global metabolic engineering technology (GMES). Furthermore, using β-carotene as the target chemical, we attempted to improve its production by using the technology. First, we developed a technology to suppress the expression of the target genes with various strengths using RNA interference. Using this technology, total carotenoid production was successfully improved by suppressing the expression of a single gene out of 10 candidate genes. Then, using this technology, RNA interference strain targeting 10 candidate genes for simultaneous suppression was constructed. The total carotenoid production of the constructed RNA interference strain was 1.7 times compared with the parental strain. In the constructed strain, the expression of eight out of the 10 candidate genes was suppressed. We developed a novel technology that can simultaneously suppress the expression of multiple genes at various intensities and succeeded in improving carotenoid production in yeast. Because this technology can suppress the expression of any gene, even essential genes, using only gene sequence information, it is considered a useful technology that can suppress the formation of by-products during the production of various target chemicals by yeast.
Dissecting the membrane association mechanism of aerolysin pore at femtomolar concentrations using water as a probe
Authors: Roesel Tereza , Cao Chan , Juarez Juan F. Bada , Dal Peraro Matteo , Roke Sylvie
Published: January 2024

Aerolysin is a bacterial pore-forming toxin able to form transmembrane pores at the host plasma membrane of narrow internal diameter and great stability. These assets make it a highly promising nanopore for the detection of biopolymers such as nucleic acids and peptides. While much is known about aerolysin from a microbiological and structural side, its membrane association and pore-formation mechanism are not yet fully disclosed. Here, we studied the interaction of femtomolar concentrations of aerolysin and its mutants with liposomes in aqueous solution using angle-resolved second harmonic scattering (AR-SHS), in combination with single-channel current measurements. The measurements were so sensitive to detect electrostatic changes on the membrane-bound aerolysin induced by pH variation induced by the changes in the hydration shell of aerolysin. We reported for the first time the membrane binding affinity of aerolysin at different stages of the pore formation mechanism: while wt aerolysin has a binding affinity as high as 20 fM, the quasi-pore state and the prepore state show gradually decreasing membrane affinities, incomplete insertion and pore opening signature. Moreover, we quantitatively characterized the membrane affinity of mutants relevant for applications to nanopore sensing. This approach opens new possibilities to efficiently screen biological pores suitable for conducting molecular sensing and sequencing measurements, as well as to probe pore forming processes.
Pre-trained Maldi Transformers improve MALDI-TOF MS-based prediction
Authors: De Waele Gaetan , Menschaert Gerben , Vandamme Peter , Waegeman Willem
Published: January 2024

For the last decade, matrix-assisted laser desportion/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has been the reference method for species identification in clinical microbiology. Hampered by a historical lack of open data, machine learning research towards models specifically adapted to MALDI-TOF MS remains in its infancy. Given the growing complexity of available datasets (such as large-scale antimicrobial resistance prediction), a need for models that (1) are specifically designed for MALDI-TOF MS data, and (2) have high representational capacity, presents itself.

Here, we introduce Maldi Transformer, an adaptation of the state-of-the-art transformer architecture to the MALDI-TOF mass spectral domain. We propose the first self-supervised pre-training technique specifically designed for mass spectra. The technique is based on shuffling peaks across spectra, and pre-training the transformer as a peak discriminator. Extensive benchmarks confirm the efficacy of this novel design. The final result is a model exhibiting state-of-the-art (or competitive) performance on downstream prediction tasks. In addition, we show that Maldi Transformer’s identification of noisy spectra may be leveraged towards higher predictive performance.

All code supporting this study is distributed on PyPI and is packaged under:https://github.com/gdewael/maldi-nn
Metabolic responses to cold: thermal physiology of native common waxbills (Estrilda astrild)
Authors: Pacioni Cesare , Sentís Marina , Kerimov Anvar , Bushuev Andrey , Downs Colleen T. , Lens Luc , Strubbe Diederik
Published: January 2024

Ecophysiological studies of invasive species tend to focus on captive individuals and their invasive range. However, the importance of gaining a thorough understanding of their physiology in their native range, where autecological knowledge is limited, has played a crucial role in assessing species ecophysiological responses to the often novel environmental conditions encountered in their invasive range. Here, we investigated the ecophysiological characteristics of a population of the wild-caught common waxbill (Estrilda astrild), a successful global invader, in part of its native range (South Africa). We investigated how this species adjusts its resting metabolic rate over a range of temperatures to identify its thermoneutral zone (TNZ) as an indicator of a species’ thermal tolerance. The observed TNZ curve predominantly followed the classic Scholander-Irving model, with metabolic rates increasing linearly at temperatures outside the TNZ. However, we found an inflection point at moderately cold temperatures (16°C) where the common waxbill began to decrease its metabolic rate. This finding highlights the potential use of an energy-saving strategy as an adaptive response to cold, such as facultative hypothermic responses through a reduction in body temperature, which may explain their success as an invasive species. We argue that although metabolic infection points have been repeatedly identified in studies of TNZ, the specific mechanisms behind metabolic down-regulation at low temperatures remain underexplored in the literature. We therefore suggest that future research should focus on investigating body temperature variation, with particular emphasis on its potential contribution to metabolic adaptation in colder environments.
Identification of motor unit discharges from ultrasound images: Analysis of in silico and in vivo experiments
Authors: Rohlén Robin , Lubel Emma , Farina Dario
Published: January 2024

Objective

Ultrasound (US) images during a muscle contraction can be decoded into individual motor unit (MU) activity, i.e., trains of neural discharges from the spinal cord. However, current decoding algorithms assume a stationary mixing matrix, i.e. equal mechanical twitches at each discharge. This study aimed to investigate the accuracy of these approaches in non-ideal conditions when the mechanical twitches in response to neural discharges vary over time and are partially fused in tetanic contractions.

Methods

We performed an in silico experiment to study the decomposition accuracy for changes in simulation parameters, including the twitch waveforms, spatial territories, and motoneuron-driven activity. Then, we explored the consistency of the in silico findings with an in vivo experiment on the tibialis anterior muscle at varying contraction forces.

Results

A large population of MU spike trains across different excitatory drives, and noise levels could be identified. The identified MUs with varying twitch waveforms resulted in varying amplitudes of the estimated sources correlated with the ground truth twitch amplitudes. The identified spike trains had a wide range of firing rates, and the later recruited MUs with larger twitch amplitudes were easier to identify than those with small amplitudes. Finally, the in silico and in vivo results were consistent, and the method could identify MU spike trains in US images at least up to 40% of the maximal voluntary contraction force.

Conclusion

The decoding method was accurate irrespective of the varying twitch-like shapes or the degree of twitch fusion, indicating robustness, important for neural interfacing applications.
Identification of CK2α’ selective inhibitors by the screening of an allosteric-kinase-inhibitor-like compound library
Authors: Mudaliar Deepti , Mansky Rachel H. , White Angel , Baudhuin Grace , Hawkinson Jon , Wong Henry , Walters Michael A. , Gomez-Pastor Rocio
Published: January 2024

Protein Kinase CK2 is a holoenzyme composed of two regulatory subunits (CK2β) and two catalytic subunits (CK2α and CK2α’). CK2 controls several cellular processes including proliferation, inflammation, and cell death. However, CK2α and CK2α’ possess different expression patterns and substrates and therefore impact each of these processes differently. Elevated CK2α participates in the development of cancer, while increased CK2α’ has been associated with neurodegeneration, especially Huntington’s disease (HD). HD is a fatal disease for which no effective therapies are available. Genetic deletion of CK2α’ in HD mouse models has ameliorated neurodegeneration. Therefore, pharmacological inhibition of CK2α’ presents a promising therapeutic strategy for treating HD. However, current CK2 inhibitors are unable to discriminate between CK2α and CK2α’ due to their high structural homology, especially in the targeted ATP binding site. Using computational analyses, we found a potential Type IV (“D” pocket) allosteric site on CK2α’ that contained different residues than CK2α and was distal from the ATP binding pocket featured in both kinases. With this potential allosteric site in mind, we screened a commercial library containing ∼29,000 allosteric-kinase-inhibitor-like compounds using a CK2α’ activity-dependent ADP-GloTMKinase assay. Obtained hits were counter-screened against CK2α revealing two CK2α’ selective compounds. These two compounds might serve as the basis for further medicinal chemistry optimization for the potential treatment of HD.
The transcriptional and translational landscape of HCoV-OC43 infection
Authors: Bresson Stefan , Sani Emanuela , Armatowska Alicja , Dixon Charles , Tollervey David
Published: January 2024

The coronavirus HCoV-OC43 circulates continuously in the human population and is a frequent cause of the common cold. Here, we generated a high-resolution atlas of the transcriptional and translational landscape of OC43 during a time course following infection of human lung fibroblasts. Using ribosome profiling, we quantified the relative expression of the canonical open reading frames (ORFs) and identified previously unannotated ORFs. These included several short upstream ORFs and a putative ORF nested inside the M gene. In parallel, we analyzed the cellular response to infection. Endoplasmic reticulum (ER) stress response genes were transcriptionally and translationally induced beginning 12 and 18 hours post infection, respectively. By contrast, conventional antiviral genes mostly remained quiescent. At the same time points, we observed accumulation and increased translation of noncoding transcripts normally targeted by nonsense mediated decay (NMD), suggesting NMD is suppressed during the course of infection. This work provides resources for deeper understanding of OC43 gene expression and the cellular responses during infection.
Aggregation ofrecount3RNA-seq data improves inference of consensus and tissue-specific gene co-expression networks
Authors: Ravichandran Prashanthi , Parsana Princy , Keener Rebecca , Hansen Kaspar D. , Battle Alexis
Published: January 2024

Background

Gene co-expression networks (GCNs) describe relationships among expressed genes key to maintaining cellular identity and homeostasis. However, the small sample size of typical RNA-seq experiments which is several orders of magnitude fewer than the number of genes is too low to infer GCNs reliably.recount3, a publicly available dataset comprised of 316,443 uniformly processed human RNA-seq samples, provides an opportunity to improve power for accurate network reconstruction and obtain biological insight from the resulting networks.

Results

We compared alternate aggregation strategies to identify an optimal workflow for GCN inference by data aggregation and inferred three consensus networks: a universal network, a non-cancer network, and a cancer network in addition to 27 tissue context-specific networks. Central network genes from our consensus networks were enriched for evolutionarily constrained genes and ubiquitous biological pathways, whereas central context-specific network genes included tissue-specific transcription factors and factorization based on the hubs led to clustering of related tissue contexts. We discovered that annotations corresponding to context-specific networks inferred from aggregated data were enriched for trait heritability beyond known functional genomic annotations and were significantly more enriched when we aggregated over a larger number of samples.

Conclusion

This study outlines best practices for network GCN inference and evaluation by data aggregation. We recommend estimating and regressing confounders in each data set before aggregation and prioritizing large sample size studies for GCN reconstruction. Increased statistical power in inferring context-specific networks enabled the derivation of variant annotations that were enriched for concordant trait heritability independent of functional genomic annotations that are context-agnostic. While we observed strictly increasing held-out log-likelihood with data aggregation, we noted diminishing marginal improvements. Future directions aimed at alternate methods for estimating confounders and integrating orthogonal information from modalities such as Hi-C and ChIP-seq can further improve GCN inference.
Exploring the Impact of Probiotic Route of Administration on Its Protective Effects against Pathogenic Infection inGalleria mellonella
Authors: Menta Lakshmi Naga Kavya , Law Soffi Kei Kei , Tan Hock Siew
Published: January 2024

In probiotic research, identifying promising candidates for further development remains challenging. Traditional mammalian models are invaluable for assessing efficacy, but limitations such as high cost, ethical considerations, and lengthy reproductive cycles can slow the preliminary screening process. TheGalleria mellonellalarvae have emerged as a powerfulin vivo-like screening model. Most studies onG. mellonellaoften use intra-hemocelic injection, bypassing the natural gut entry point for probiotics, which is analogous to introducing probiotics into the mammalian blood. Despite their advantages, discrepancies exist betweenG. mellonellaand mammalian models, particularly regarding the route of probiotic administration. This study bridges this gap by investigating the differential effects of oral and intra-hemocelic administration of a probiotic,Escherichia coliNissle 1917 (EcN1917), on its protective efficacy against a gastrointestinal pathogen,SalmonellaTyphimurium ATCC 14028 (ST14028). The larvae were challenged with varying doses of EcN1917 and ST14028 through both routes. Survivability, health index, and bacterial burden in the gut and hemolymph were assessed. This study demonstrated that oral EcN1917 pre-treatment significantly increased survivability against ST14028 infection compared to the control group and alleviated the pathogen gut burden. Notably, injection pre-treatment decreased survivability. This discrepancy is attributed to the dual nature of probiotics, exhibiting beneficial effects in the gut but acting as pathogens in non-native locations like the hemolymph. This study concludes that the route of probiotic administration inG. mellonellasignificantly impacts the protective effects of probiotics.
Facilitating clinical trials in Polycythemia vera (PV) by identifying patient cohorts at high near-term risk of thrombosis using rich data and machine learning
Authors: Abu-Zeinah Ghaith , Krichevsky Spencer , Erdos Katie , Silver Richard T. , Scandura Joseph M.
Published: January 2024

Thrombosis remains the leading cause of morbidity and mortality for patients (pts) with polycythemia vera (PV), yet PV clinical trials are not powered to identify interventions that improve thrombosis-free survival (TFS). Such trials are infeasible in a contemporary PV cohort, even when selecting “high-risk” pts based on Age >60 and thrombosis history, because thousands of patients would be required for a short-term study to meet TFS endpoint. To address this problem, we used artificial intelligence and machine learning (ML) to dynamically predict near-term (1-year) thrombosis risk in PV pts with high sensitivity and positive predictive value (PPV) to enhance pts selection. Our automation-driven data extraction methods yielded more than 16 million data elements across 1,448 unique variables (parameters) from 11,123 clinical visits for 470 pts. Using the AutoGluon framework, the Random Forest ML classification algorithm was selected as the top performer. The full (309-parameter) model performed very well (F1=0.91, AUC=0.84) when compared with the current ELN gold-standard for thrombosis risk stratification in PV (F1=0.1, AUC=0.39). Parameter engineering, guided by Gini feature importance identified the 21 parameters (top-21) most important for accurate prediction. The top-21 parameters included known, suspected and previously unappreciated thrombosis risk factors. To identify the minimum number of parameters required for the accurate ML prediction, we tested the performance of every possible combination of 3-9 parameters from top-21 (>1.6M combinations). High-performing models (F1> 0.8) most frequently included age (continuous), time since dx, time since thrombosis, complete blood count parameters, blood type, body mass index, and JAK2 mutant allele frequency. Having trained at tested over 1.6M practical ML models with a feasible number of parameters (3-9 parameters in top-21 most predictive), it is clear that study cohorts of patients with PV at high near-term thrombosis risk can be identified with high enough sensitivity and PPV to power a clinical trial for TFS. Further validation with external, multicenter cohorts is ongoing to establish a universal ML model for PV thrombosis that would facilitate clinical trials aimed at improving TFS.
Plasma proteomic associates of infection mortality in UK Biobank
Authors: Drozd Michael , Hamilton Fergus , Cheng Chew W , Lillie Patrick J , Brown Oliver I , Chaddock Natalie , Savic Sinisa , Naseem Khalid , Iles Mark M , Morgan Ann W , Kearney Mark T , Cubbon Richard M
Published: January 2024

Background

Infectious diseases are a major cause of mortality in spite of existing public health, anti-microbial and vaccine interventions. We aimed to define plasma proteomic associates of infection mortality and then apply Mendelian randomisation (MR) to yield biomarkers that may be causally associated.

Methods

We used UK Biobank plasma proteomic data to associate 2,923 plasma proteins with infection mortality before 31stDecember 2019 (240 events in 52,520 participants). Since many plasma proteins also predict non-infection mortality, we focussed on those associated with >1.5-fold risk of infection mortality in an analysis excluding survivors. Protein quantitative trait scores (pQTS) were then used to identify whether genetically predicted protein levels also associated with infection mortality. To conduct Two Sample MR, we performed a genome-wide association study (GWAS) of infection mortality using UK Biobank participants without plasma proteomic data (n=363,953 including 984 infection deaths).

Findings

After adjusting for clinical risk factors, 1,142 plasma proteins were associated with risk of infection mortality (false discovery rate <0.05). 259 proteins were associated with >1.5-fold increased risk of infection versus non-infection mortality. Of these, we identified genetically predicted increasing MERTK concentration was associated with increased risk of infection mortality. GWAS for infection mortality revealed no SNPs achieving genome-wide statistical significance (p<5×10-8). However, MR supported a causal association between increasing plasma MERTK protein and infection mortality (odds ratio 1.46 per unit; 95% CI 1.15-1.85; p=0.002).

Interpretation

Plasma proteomics demonstrates many proteins are associated with infection mortality. MERTK warrants exploration as a potential therapeutic target.
Diagnosis in children with prolonged or recurrent cough: findings from the Swiss Paediatric Airway Cohort
Authors: Mallet Maria Christina , Elmiger Annina , Glick Sarah , Krasnova Tayisiya , de Jong Carmen CM , Kern Barbara , Moeller Alexander , Regamey Nicolas , Sutter Oliver , Usemann Jakob ,   SPAC Study Team, Pedersen Eva SL , Kuehni Claudia E
Published: January 2024

Introduction

Prolonged or recurrent cough is a common reason for referral to pediatric pulmonologists, yet few studies have assessed its causes. We examined records of children visiting respiratory outpatient clinics in Switzerland and assessed how diagnoses vary by age.

Methods

We analyzed data from the multicenter Swiss Paediatric Airway Cohort study. We included 363 children (median age 6 years, range 0–16) referred for prolonged or recurrent cough. From outpatient records, we extracted information on diagnostic investigations, final diagnoses proposed by pediatric pulmonologists, and treatments prescribed.

Results

Asthma and asthma-like conditions (cough variant asthma, episodic viral wheeze, and recurrent obstructive bronchitis) was diagnosed in 132 (36%) of 363 children, respiratory tract infections (RTI) including protracted bacterial bronchitis (PBB) in 51 (14%), upper airway cough syndrome (UACS) in 48 (13%), postinfectious cough in 36 (10%); other diagnoses including gastroesophageal reflux disease (GERD) and somatic cough syndrome or tic cough were found in 23 (6%). No etiology was found in 73 children (20%). Asthma was diagnosed 3.5 times more often in schoolchildren while RTI including PBB was diagnosed 3 times more often in preschoolers. Inhaled corticosteroids were prescribed for 84% of children diagnosed with asthma and asthma-like conditions, antibiotics for 43% of children with RTI, and nasal corticosteroids for 83% of those with UACS.

Conclusion

Coughing children received a wide spectrum of diagnoses that differed between preschool and schoolchildren. Asthma accounted for 36% of diagnoses, which emphasizes the importance of comprehensive investigation beyond asthma in children with prolonged or recurrent cough.
Constraints on the Emergence of RNA through Non-Templated Primer Extension with Mixtures of Potentially Prebiotic Nucleotides
Authors: Jia Xiwen , Zhang Stephanie J. , Zhou Lijun , Szostak Jack W.
Published: January 2024

The emergence of RNA on the early Earth is likely to have been influenced by a series of chemical and physical processes that acted to filter out various alternative nucleic acids. For example, UV photostability is thought to have favored the survival of the canonical nucleotides. In a recent proposal for the prebiotic synthesis of the building blocks of RNA, ribonucleotides share a common pathway with arabino- and threo-nucleotides. We have therefore investigated non-templated primer extension with 2-aminoimidazole-activated forms of these alternative nucleotides to see if the synthesis of the first oligonucleotides might have been biased in favor of RNA. We show that non-templated primer extension occurs predominantly through 5ʹ-5ʹ imidazolium bridged dinucleotides, echoing the mechanism of template-directed primer extension. Ribo- and arabino-nucleotides exhibited comparable rates and yields of non-templated primer extension, whereas threo-nucleotides showed lower reactivity. Competition experiments with mixtures of nucleotides confirmed the bias against the incorporation of threo-nucleotides into oligonucleotides. This bias, coupled with selective prebiotic synthesis and templated copying favoring ribonucleotides, provides a plausible model for the exclusion of threo-nucleotides from primordial oligonucleotides. In contrast, the exclusion of arabino-nucleotides may have resulted primarily from biases in synthesis and in template-directed primer extension.
MagIC-Cryo-EM: Structural determination on magnetic beads for scarce macromolecules in heterogeneous samples
Authors: Arimura Yasuhiro , Konishi Hide A. , Funabiki Hironori
Published: January 2024

Cryo-EM single-particle analyses typically require target macromolecule concentration at 0.05∼5.0 mg/ml, which is often difficult to achieve. Here, we deviseMagnetic Isolation andConcentration (MagIC)-cryo-EM, a technique enabling direct structural analysis of targets captured on magnetic beads, thereby reducing the targets’ concentration requirement to < 0.0005 mg/ml. Adapting MagIC-cryo-EM to a Chromatin Immunoprecipitation protocol, we characterized structural variations of the linker histone H1.8-associated nucleosomes that were isolated from interphase and metaphase chromosomes inXenopusegg extract. CombiningDuplicatedSelectionToExcludeRubbish particles (DuSTER), a particle curation method that excludes low signal-to-noise ratio particles, we also resolved the 3D cryo-EM structures of nucleoplasmin NPM2 co-isolated with the linker histone H1.8 and revealed distinct open and closed structural variants. Our study demonstrates the utility of MagIC-cryo-EM for structural analysis of scarce macromolecules in heterogeneous samples and provides structural insights into the cell cycle-regulation of H1.8 association to nucleosomes.
Cryo-EM structure of a blue-shifted channelrhodopsin fromKlebsormidium nitens
Authors: Wang Yuzhu Z. , Natsume Koki , Tanaka Tatsuki , Hososhima Shoko , Tashiro Rintaro , Sano Fumiya K. , Akasaka Hiroaki , Tsunoda Satoshi P. , Shihoya Wataru , Kandori Hideki , Nureki Osamu
Published: January 2024

Channelrhodopsins (ChRs) are light-gated ion channels and invaluable tools for optogenetic applications. Recent developments in multicolor optogenetics, in which different neurons are controlled by multiple colors of light simultaneously, have increased the demand for ChR mutants with more distant absorption wavelengths. Here we report the 2.9 Å-resolution cryo-electron microscopy structure of a ChR fromKlebsormidium nitens(KnChR), which is one of the most blue-shifted ChRs. The structure elucidates the 6-s-cisconfiguration of the retinal chromophore, indicating its contribution to a distinctive blue shift in action spectra. The unique architecture of the C-terminal region reveals its role in the allosteric modulation of channel kinetics, enhancing our understanding of its functional dynamics. Based on the structure-guided design, we developed mutants with blue-shifted action spectra. Finally, we confirm that UV or deep-blue light can activate KnChR-transfected precultured neurons, expanding its utility in optogenetic applications. Our findings contribute valuable insights to advance optogenetic tools and enable refined capabilities in neuroscience experiments.
Multipoles from Majorana constellations
Authors: Romero J. L. , Klimov A. B. , Goldberg A. Z. , Leuchs G. , Sánchez-Soto L. L.
Published: January 2024

Majorana stars, the 2S spin coherent states that are orthogonal to a spin-S state, offer an elegant method to visualize quantum states, disclosing their intrinsic symmetries. These states are naturally described by the corresponding multipoles. These quantities can be experimentally determined and allow for an SU(2)-invariant analysis. We investigate the relationship between Majorana constellations and state multipoles, thus providing insights into the underlying symmetries of the system. We illustrate our approach with some relevant and informative examples.

Published by the American Physical Society
2024
Superexchange coupling of donor qubits in silicon
Authors: Munia Mushita M. , Monir Serajum , Osika Edyta N. , Simmons Michelle Y. , Rahman Rajib
Published: January 2024

Atomic engineering in a solid-state material has the potential to functionalize the host with novel phenomena. STM-based lithographic techniques have enabled the placement of individual phosphorus atoms at selective lattice sites of silicon with atomic precision. Here we show that by placing four phosphorus donors spaced 10–15 nm apart from their neighbors in a linear chain, one can realize coherent spin coupling between the end dopants of the chain, analogous to the superexchange interaction in magnetic materials. Since phosphorus atoms are a promising building block of a silicon quantum computer, this enables spin coupling between their bound electrons beyond nearest neighbors, allowing the qubits to be separated by 30–45 nm. The added flexibility in architecture brought about by this long-range coupling not only reduces gate densities but can also reduce correlated noise between qubits from local noise sources that are detrimental to error-correction codes. We base our calculations on a full-configuration-interaction technique in the atomistic tight-binding basis, solving the four-electron problem exactly, over a domain of a million silicon atoms. Our calculations show that superexchange can be tuned electrically through gate voltages where it is less sensitive to charge noise and donor-placement errors.

Published by the American Physical Society
2024
Heavy quark diffusion coefficient in heavy-ion collisions via kinetic theory
Authors: Boguslavski K. , Kurkela A. , Lappi T. , Lindenbauer F. , Peuron J.
Published: January 2024

We compute the heavy quark momentum diffusion coefficient κ using QCD kinetic theory for a system going through bottom-up isotropization in the initial stages of a heavy ion collision. We find that the values of κ are within 30% from a thermal system at the same energy density. When matching for other quantities we observe considerably larger deviations. We also observe that the diffusion coefficient in the transverse direction is larger at high occupation numbers, whereas for an underoccupied system the longitudinal diffusion coefficient dominates. The behavior of the diffusion coefficient can be understood on a qualitative level based on the Debye mass mD and the effective temperature of soft modes T*. Our findings for the kinetic evolution of κ in different directions can be used in phenomenological descriptions of heavy quark diffusion and quarkonium dynamics to include the impact of preequilibrium stages.

Published by the American Physical Society
2024
Long-lived particles and the quiet Sun
Authors: Gustafson R. Andrew , Plestid Ryan , Shoemaker Ian M. , Zhou Albert
Published: January 2024

The nuclear reaction network within the interior of the Sun is an efficient MeV physics factory and can produce long-lived particles generic to dark sector models. In this work we consider the sensitivity of satellite instruments, primarily the RHESSI spectrometer, that observe the quiet Sun in the MeV regime where backgrounds are low. We find that quiet Sun observations offer a powerful and complementary probe in regions of parameter space, where the long-lived particle decay length is longer than the radius of the Sun and shorter than the distance between the Sun and Earth. We comment on connections to recent model-building work on heavy neutral leptons coupled to neutrinos and high-quality axions from mirror symmetries.

Published by the American Physical Society
2024
Gravitational wave probes on self-interacting dark matter surrounding an intermediate mass black hole
Authors: Kadota Kenji , Kim Jeong Han , Ko Pyungwon , Yang Xing-Yu
Published: January 2024

The presence of dark matter overdensities surrounding a black hole can influence the evolution of a binary system. The gravitational wave signals emitted by a black hole binary offer a promising means to probe the dark matter environments near a black hole. The dense region of dark matter can lead to the dephasing of gravitational waveforms, which can be detected by upcoming experiments such as the Laser Interferometer Space Antenna (LISA). The dark matter density profile around the black hole can vary for different dark matter models. Our study specifically investigates the impact of the ultralight self-interacting scalar dark matter (SIDM) on the gravitational wave signals emitted by black hole binaries. A distinctive characteristic of SIDM surrounding a black hole, as opposed to collisionless dark matter, is the formation of a soliton core. We perform a Fisher matrix analysis to estimate the size of the soliton and the corresponding SIDM parameter space that future LISA-like gravitational wave experiments can explore.

Published by the American Physical Society
2024
Early release of the expanded atlas of the sky in continuous gravitational waves
Authors: Dergachev Vladimir , Papa Maria Alessandra
Published: January 2024

We present the early release of the atlas of continuous gravitational waves covering frequencies from 20 Hz to 1500 Hz and spindowns from −5×10−10 to 5×10−10  Hz/s. Compared to the previous atlas release we have greatly expanded the parameter space, and we now also provide polarization-specific data—both for signal-to-noise ratios and for the upper limits. Continuous wave searches are computationally difficult and take a long time to complete. The atlas enables new searches to be performed using modest computing power. To allow new searches to start sooner, we are releasing this data early, before our followup stages have completed.

Published by the American Physical Society
2024
Trade-offs between precision and fluctuations in charging finite-dimensional quantum batteries
Authors: Bakhshinezhad Pharnam , Jablonski Beniamin R. , Binder Felix C. , Friis Nicolai
Published: January 2024

Within quantum thermodynamics, many tasks are modeled by processes that require work sources represented by out-of-equilibrium quantum systems, often dubbed quantum batteries, in which work can be deposited or from which work can be extracted. Here we consider quantum batteries modeled as finite-dimensional quantum systems initially in thermal equilibrium that are charged via cyclic Hamiltonian processes. We present optimal or near-optimal protocols for N identical two-level systems and individual d-level systems with equally spaced energy gaps in terms of the charging precision and work fluctuations during the charging process. We analyze the trade-off between these figures of merit as well as the performance of local and global operations.

Published by the American Physical Society
2024
Mitigated barren plateaus in the time-nonlocal optimization of analog quantum-algorithm protocols
Authors: Broers Lukas , Mathey Ludwig
Published: January 2024

Quantum machine learning has emerged as a promising utilization of near-term quantum computation devices. However, algorithmic classes such as variational quantum algorithms have been shown to suffer from barren plateaus due to vanishing gradients in their parameters spaces. We present an approach to quantum algorithm optimization that is based on trainable Fourier coefficients of Hamiltonian system parameters. Our is exclusive to the extension of discrete quantum variational algorithms to analog quantum optimal control schemes and is nonlocal in time. We demonstrate the viability of our on the objectives of compiling the quantum Fourier transform and preparing ground states of random problem Hamiltonians. In comparison to the temporally local discretization in quantum optimal control and parametrized circuits, our exhibits faster and more consistent convergence. We uniformly sample objective gradients across the parameter space and find that in our the variance decays at a nonexponential rate with the number of qubits, while it decays at an exponential rate in the temporally local benchmark . This indicates the mitigation of barren plateaus in our . We propose our as a viable candidate for near-term quantum machine learning.

Published by the American Physical Society
2024
Understanding random-walk dynamical phase coexistence through waiting times
Authors: Stuhrmann David C. , Coghi Francesco
Published: January 2024

We study the appearance of first-order dynamical phase transitions (DPTs) as “intermittent” coexisting phases in the fluctuations of random walks on graphs. We show that the diverging timescale leading to critical behavior is the waiting time to jump from one phase to another. This timescale is crucial for observing the system's relaxation to stationarity and demonstrate ergodicity of the system at criticality. We illustrate these results through three analytical examples which provide insights into random walks exploring random graphs.

Published by the American Physical Society
2024
Propagation of light in cold emitter ensembles with quantum position correlations due to static long-range dipolar interactions
Authors: Bean G. J. , Drummond N. D. , Ruostekoski J.
Published: January 2024

We analyze the scattering of light from dipolar emitters whose disordered positions exhibit correlations induced by static, long-range dipole-dipole interactions. The quantum-mechanical position correlations are calculated for zero-temperature bosonic atoms or molecules using variational and diffusion quantum Monte Carlo methods. For stationary atoms in dense ensembles in the limit of low light intensity, the simulations yield solutions for the optical responses to all orders of position correlation functions that involve electronic ground and excited states. We calculate how coherent and incoherent scattering, collective linewidths, line shifts, and eigenmodes, and disorder-induced excitation localization are influenced by the static interactions and the density. We find that dominantly repulsive static interactions in strongly confined oblate and prolate traps introduce short-range ordering among the dipoles, which curtails large fluctuations in the light-mediated resonant dipole-dipole interactions. This typically results in an increase in coherent reflection and optical depth, accompanied by reduced incoherent scattering. The presence of static dipolar interactions permits the highly selective excitation of subradiant eigenmodes in dense clouds. This effect becomes even more pronounced in a prolate trap, where the resonances narrow below the natural linewidth. When the static dipolar interactions affect the optical transition frequencies, the ensemble exhibits inhomogeneous broadening due to the nonuniformly experienced static dipolar interactions that suppress cooperative effects, but we argue that, e.g., for Dy atoms such inhomogeneous broadening is negligible.

Published by the American Physical Society
2024
Stick-slip in a stack: How slip dissonance reveals aging
Authors: Poincloux Samuel , Reis Pedro M. , de Geus Tom W. J.
Published: January 2024

We perform physical and numerical experiments to study the stick-slip response of a stack of slabs in contact through dry frictional interfaces driven in quasistatic shear. The ratio between the drive's stiffness and the slab's shear stiffness controls the presence or absence of slip synchronization. A sufficiently high stiffness ratio leads to synchronization, comprising periodic slip events in which all interfaces slip simultaneously. A lower stiffness ratio leads to asynchronous slips and, experimentally, to the stick-slip amplitude becoming broadly distributed as the number of layers in the stack increases. We interpret this broadening in light of the combined effect of complex loading paths, due to the asynchronous slips, and interface aging. Consequently, the aging rate of the interfaces can be readily extracted from the stick-slip cycles, and it is found to be of the same order of magnitude as existing experimental results on a similar material. Finally, we discuss the emergence of slow slips and an increase in aging-rate variations when more slabs are added to the stack.

Published by the American Physical Society
2024