bluuebunny/crossref_metadata_2025 huggingface dataset:
Artificial age-independent seismic anisotropy, slab thickening and shallowing due to limited resolving power of (an)isotropic tomography
Authors: Rappisi F , Witek M , Faccenda M , Ferreira A M G , Chang S - J
Published: January 2024

Seismic anisotropy is key to constrain mantle flow, but it is challenging to image and interpret it. Existing large-scale tomography models of seismic anisotropy typically show large discrepancies, which can lead to completely distinct geodynamical interpretations. To better quantify the robustness of anisotropy tomography, we create a 2-D ridge-to-slab geodynamic model and compute the associated fabrics. Using the resulting 21 elastic constants, we compute seismic full waveforms, which are inverted for isotropic and radially anisotropic structure. We test the effects of different data coverage and levels of regularization on the resulting images and on their geodynamical interpretation. Within the context of our specific imposed conditions and source–receiver configuration, the retrieved isotropic images exhibit substantial artificial slab thickening and loss of the slab’s high-velocity signature below ∼100 km depth. Our results also show that the first-order features of radial anisotropy are well retrieved despite strong azimuthal anisotropy (up to 2.7 per cent) in the input model. On the other hand, regularization and data coverage strongly control the detailed characteristics of the retrieved anisotropy, notably the depth–age dependency of anisotropy, leading to an artificial flat depth–age trend shown in existing anisotropy tomography models. Greater data coverage and additional complementary data types are needed to improve the resolution of (an)isotropic tomography models.
VapC10 toxin of the legume symbiont Sinorhizobium meliloti targets tRNASer and controls intracellular lifestyle
Authors: Syska Camille , Kiers Aurélie , Rancurel Corinne , Bailly-Bechet Marc , Lipuma Justine , Alloing Geneviève , Garcia Isabelle , Dupont Laurence
Published: January 2024

The soil bacterium Sinorhizobium meliloti can establish a nitrogen-fixing symbiosis with the model legume Medicago truncatula. The rhizobia induce the formation of a specialized root organ called nodule, where they differentiate into bacteroids and reduce atmospheric nitrogen into ammonia. Little is known on the mechanisms involved in nodule senescence onset and in bacteroid survival inside the infected plant cells. Although toxin-antitoxin (TA) systems have been shown to promote intracellular survival within host cells in human pathogenic bacteria, their role in symbiotic bacteria was rarely investigated. S. meliloti encodes several TA systems, mainly of the VapBC family. Here we present the functional characterization, through a multidisciplinary approach, of the VapBC10 TA system of S. meliloti. Following a mapping by overexpression of an RNase in Escherichia coli (MORE) RNA-seq analysis, we demonstrated that the VapC10 toxin is an RNase that cleaves the anticodon loop of two tRNASer. Thereafter, a bioinformatics approach was used to predict VapC10 targets in bacteroids. This analysis suggests that toxin activation triggers a specific proteome reprogramming that could limit nitrogen fixation capability and viability of bacteroids. Accordingly, a vapC10 mutant induces a delayed senescence in nodules, associated to an enhanced bacteroid survival. VapBC10 TA system could contribute to S. meliloti adaptation to symbiotic lifestyle, in response to plant nitrogen status.
Improving large language models for clinical named entity recognition via prompt engineering
Authors: Hu Yan , Chen Qingyu , Du Jingcheng , Peng Xueqing , Keloth Vipina Kuttichi , Zuo Xu , Zhou Yujia , Li Zehan , Jiang Xiaoqian , Lu Zhiyong , Roberts Kirk , Xu Hua
Published: January 2024

Importance

The study highlights the potential of large language models, specifically GPT-3.5 and GPT-4, in processing complex clinical data and extracting meaningful information with minimal training data. By developing and refining prompt-based strategies, we can significantly enhance the models’ performance, making them viable tools for clinical NER tasks and possibly reducing the reliance on extensive annotated datasets.

Objectives

This study quantifies the capabilities of GPT-3.5 and GPT-4 for clinical named entity recognition (NER) tasks and proposes task-specific prompts to improve their performance.

Materials and Methods

We evaluated these models on 2 clinical NER tasks: (1) to extract medical problems, treatments, and tests from clinical notes in the MTSamples corpus, following the 2010 i2b2 concept extraction shared task, and (2) to identify nervous system disorder-related adverse events from safety reports in the vaccine adverse event reporting system (VAERS). To improve the GPT models' performance, we developed a clinical task-specific prompt framework that includes (1) baseline prompts with task description and format specification, (2) annotation guideline-based prompts, (3) error analysis-based instructions, and (4) annotated samples for few-shot learning. We assessed each prompt's effectiveness and compared the models to BioClinicalBERT.

Results

Using baseline prompts, GPT-3.5 and GPT-4 achieved relaxed F1 scores of 0.634, 0.804 for MTSamples and 0.301, 0.593 for VAERS. Additional prompt components consistently improved model performance. When all 4 components were used, GPT-3.5 and GPT-4 achieved relaxed F1 socres of 0.794, 0.861 for MTSamples and 0.676, 0.736 for VAERS, demonstrating the effectiveness of our prompt framework. Although these results trail BioClinicalBERT (F1 of 0.901 for the MTSamples dataset and 0.802 for the VAERS), it is very promising considering few training samples are needed.

Discussion

The study’s findings suggest a promising direction in leveraging LLMs for clinical NER tasks. However, while the performance of GPT models improved with task-specific prompts, there's a need for further development and refinement. LLMs like GPT-4 show potential in achieving close performance to state-of-the-art models like BioClinicalBERT, but they still require careful prompt engineering and understanding of task-specific knowledge. The study also underscores the importance of evaluation schemas that accurately reflect the capabilities and performance of LLMs in clinical settings.

Conclusion

While direct application of GPT models to clinical NER tasks falls short of optimal performance, our task-specific prompt framework, incorporating medical knowledge and training samples, significantly enhances GPT models' feasibility for potential clinical applications.
Assessing the use of HL7 FHIR for implementing the FAIR guiding principles: a case study of the MIMIC-IV Emergency Department module
Authors: van Damme Philip , Löbe Matthias , Benis Nirupama , de Keizer Nicolette F , Cornet Ronald
Published: January 2024

Objectives

To provide a real-world example on how and to what extent Health Level Seven Fast Healthcare Interoperability Resources (FHIR) implements the Findable, Accessible, Interoperable, and Reusable (FAIR) guiding principles for scientific data. Additionally, presents a list of FAIR implementation choices for supporting future FAIR implementations that use FHIR.

Materials and methods

A case study was conducted on the Medical Information Mart for Intensive Care-IV Emergency Department (MIMIC-ED) dataset, a deidentified clinical dataset converted into FHIR. The FAIRness of this dataset was assessed using a set of common FAIR assessment indicators.

Results

The FHIR distribution of MIMIC-ED, comprising an implementation guide and demo data, was more FAIR compared to the non-FHIR distribution. The FAIRness score increased from 60 to 82 out of 95 points, a relative improvement of 37%. The most notable improvements were observed in interoperability, with a score increase from 5 to 19 out of 19 points, and reusability, with a score increase from 8 to 14 out of 24 points. A total of 14 FAIR implementation choices were identified.

Discussion

Our work examined how and to what extent the FHIR standard contributes to FAIR data. Challenges arose from interpreting the FAIR assessment indicators. This study stands out for providing a real-world example of a dataset that was made more FAIR using FHIR.

Conclusion

To the best of our knowledge, this is the first study that formally assessed the conformance of a FHIR dataset to the FAIR principles. FHIR improved the accessibility, interoperability, and reusability of MIMIC-ED. Future research should focus on implementing FHIR in research data infrastructures.
Design and evaluation of an electronic prospective medication order review system for medication orders in the inpatient setting
Authors: Ojha Pooja , Anderson Benjamin J , Draper Evan W , Flaker Susan M , Siska Mark H , Mara Kristin C , Kennedy Brian D , Schreier Diana J
Published: January 2024

Objectives

Since the 1970s, a plethora of tools have been introduced to support the medication use process. However, automation initiatives to assist pharmacists in prospectively reviewing medication orders are lacking. The review of many medications may be protocolized and implemented in an algorithmic fashion utilizing discrete data from the electronic health record (EHR). This research serves as a proof of concept to evaluate the capability and effectiveness of an electronic prospective medication order review (EPMOR) system compared to pharmacists’ review.

Materials and methods

A subset of the most frequently verified medication orders were identified for inclusion. A team of clinical pharmacist experts developed best-practice EPMOR criteria. The established criteria were incorporated into conditional logic built within the EHR. Verification outcomes from the pharmacist (human) and EPMOR (automation) were compared.

Results

Overall, 13 404 medication orders were included. Of those orders, 13 133 passed pharmacist review, 7388 of which passed EPMOR. A total of 271 medication orders failed pharmacist review due to order modification or discontinuation, 105 of which passed EPMOR. Of the 105 orders, 19 were duplicate orders correctly caught by both EPMOR and pharmacists, but the opposite duplicate order was rejected, 51 orders failed due to scheduling changes.

Discussion

This simulation was capable of effectively discriminating and triaging orders. Protocolization and automation of the prospective medication order review process in the EHR appear possible using clinically driven algorithms.

Conclusion

Further research is necessary to refine such algorithms to maximize value, improve efficiency, and minimize safety risks in preparation for the implementation of fully automated systems.
Decline in muscle strength and physical function after fracture in men – the prospective STRAMBO study
Authors: Szulc Paweł , Lewis Joshua R , Chapurlat Roland
Published: January 2024

Studies on muscle strength and physical function after fracture are focused on short follow-ups and adjacent anatomical region. We compared loss of muscle strength and physical function in men after fracture with normal ageing-related decline. In 823 men aged 60–87, measurements of grip strength and clinical tests (chair stands, balance) were performed every 4 years for 12 years. In 155 men with incident fracture, we compared the status after vs. before the fracture. In men without fracture (controls), we compared the status on the first follow-up (4 years) vs. baseline. In men with fracture, grip strength decreased more than in the controls (41%, 0.28SD, P < .01). Men with fracture had higher risk of incident deterioration on the five chair-stand test vs. the controls (OR = 2.45, P < .001). They had higher risk of incident inability to stand for 10s with closed eyes vs. the controls (OR = 4.80, P < .01). They also had higher risk of deterioration on the tandem walk than the controls: forwards (OR = 2.04, P < .01), backwards (OR = 2.25, P < .005). The rapid physical decline was not limited to the region of the fracture site. In men who had incident non-upper limb fractures, grip strength decreased more (32%, P < .05) vs. the controls. In men who had incident non-lower limb fractures, the risk of decline in the tests of the lower limbs was higher vs. controls (chair stands, OR = 2.73, P < .001). The risk of decline was higher in men with clinical fractures which occurred >1 year before the next visit vs. controls (tandem walk forwards, OR = 2.98, P < .005). Overall, in older men, fractures were associated with greater loss of muscle strength and physical function vs. normal ageing. This accelerated decline was also found in the anatomical regions remote from the fracture site. Thus, programs to decrease or reverse the post-fracture decline could have beneficial effects on subsequent fracture risk.
An effective Q extraction method via deep learning
Authors: Li Fang , Yu Zhenzhen , Ma Jianwei
Published: January 2024

The quality factor (Q) is a parameter reflecting the physical properties of reservoirs. Accurate estimation of the quality factor plays an important role in improving the resolution of seismic data. Spectral-ratio method is a widely used traditional method based on the linear least-squares fitting to extract the quality factor, but is sensitive to noise. This is the main reason preventing this method from being widely used. Some supervised deep-learning methods are proposed to extract Q in which the construction of training labels is a key link. The proposed method is based on the spectral-ratio method to create training labels, avoiding errors in generating them. In contrast to the least-squares method, this paper proposes to use a nonlinear regression algorithm based on a fully connected network to fit the spectral logarithmic ratio and frequency. Meanwhile, the empirical equation is applied to constrain prediction results. The proposed method can effectively overcome the influence of noise and improve the accuracy of prediction results. Tests on the synthesized data of vertical seismic profile and common middle profile show that the proposed method has better generalization ability than the spectral-ratio method. Applying the method to the field vertical seismic profile data successfully extracts the quality factor, which can provide effective information for dividing stratigraphic layers.
Effect of temperature and fluid on rock microstructure based on an effective-medium theory
Authors: Zhu Hesong , Ba Jing , Zhang Lin , Carcione José M , Yan Xinfei
Published: January 2024

Temperature and pressure variations during the geologic diagenesis process can lead to complex pore structures in tight rocks. The effective-medium theory, based on the stress–strain relationship in combination with pore structure parameters, can be used to describe the elastic-wave responses of rocks. In this work, the differential effective medium (DEM) and self-consistent approximation (SCA) models are combined to invert the pore-crack spectrum. The Voigt–Reuss–Hill average is used to estimate the elastic moduli of the minerals. Then, based on SCA, the pore structures are incorporated into the rock matrix to create a new host phase. Subsequently, the DEM theory is used to add cracks with different volume fractions and aspect ratios to the host phase. To predict the structure of pores and cracks (crack density and aspect ratio), an objective function is defined as the sum of variances between experimentally measured and predicted wave velocities. The results show that the modeling predictions of P- and S-wave velocities at different temperatures and pressure ratios agree well with the experimental measurements. Variations in pore structure are determined at a zero effective pressure and different temperatures. We analyze the characteristics of how cracks change with variations in temperature and confining pressure, providing a theoretical basis for characterizing the structure of tight rocks.
Sound absorption mechanism of underwater anechoic coating with spherical cavities
Authors: Hu Ningdong , Jin Jun , Zou Wentao , Peng Weicai , Hu Hongping
Published: January 2024

An axisymmetric theoretical model is simplified to investigate sound absorption in the underwater anechoic coating with spherical cavities. An empirical equation is put forward to predict the frequency at the first absorption peak. The sound absorption mechanism of viscoelastic solid with cavity is clarified by the power analysis method. The quantitative analysis of viscoelastic power dissipation on sound energy provides a new idea for the structural topology optimization of anechoic coatings. These formulas are given to calculate the dissipation power of viscoelastic solid. The dependence of sound absorption performance of the anechoic coating upon radius and position of single or two spherical cavities of the unit cell is analyzed in detail. The study provides guidance for the design of anechoic coatings with cavities.
Returning to sport after injury: the influence of injury appraisals and post-traumatic stress symptoms on adolescent risk-taking intentions post-injury
Authors: Seasons Mackenzie , Morrongiello Barbara A
Published: January 2024

Objective

How youth think about injury risk can affect their decisions about whether to engage in behaviors that can lead to injury. Appraisals also influence the development of post-traumatic stress symptoms (PTSS), which occur in approximately 20% of children after a medically treated injury. The current study examined how the injury appraisals of youth are associated with the development of PTSS post-skateboarding injury, and if PTSS or perceived benefits of the sport are also associated with youths’ intentions to return to the sport.

Method

One hundred three youth who had a medically treated skateboarding injury within the last year provided survey data on injury appraisals, PTSS, the benefits of skateboarding, and intentions to return to the sport.

Results

A two-stage moderated statistical mediation path model was specified. In the first stage, there was a positive relationship between pain at injury and PTSS, which was attenuated by the moderator, perceived bad luck. PTSS fully mediated the association between perceived pain at the time of injury and intentions to return to skateboarding. In the second stage of the mediation model, the moderator perceived benefits of skateboarding, reversed the negative relationship between PTSS and intentions to return to skateboarding.

Conclusions

Skateboarders are a group at risk for injury that can lead to PTSS, and they also are likely to return to the sport despite PTSS. This research identifies factors that impact the decision to return to skateboarding after injury. Limitations of the study and implications for mental health support and injury prevention are provided.
A case of rare lumbar intradural tumor: paraganglioma
Authors: Sevin Ismail Ertan , Dağ Onur Davut , Kahraman Aslı , Sucu Hasan Kamil
Published: January 2024

Lumbar paragangliomas are rare neuroendocrine neoplasms arising from specialized neural crest cells in the cauda equina/filum terminale region. They are difficult to diagnose radiologically and can be difficult to treat surgically if they secrete catecholamines. A 38-year-old woman presented with three and a half years of increasing lower back and sacrum discomfort. Her neurological examination was normal. The MRI revealed an L4 intradural lesion that was compressing the cauda equina. A total tumor resection was conducted. The paraganglioma was diagnosed by the pathology report. Paragangliomas should be considered in the differential diagnosis of intradural masses of the lumbar spine.
Modeling in Sample Surveys: Discussion of Professor Valliant’s Hansen Lecture 2022
Authors: Raghunathan Trivellore
Published: January 2024

Statistical modeling has been, and continues to be, at the core of statistical inferential activity. No good can come off of sophisticated modeling of data from a badly designed study, and hence, the design principles have been at the core of our field. However, use of models in sample surveys has been controversial and has been limited to certain applications, such as small-area estimation. It is clear, however, from Professor Valliant’s paper that almost every practical problem in sample surveys requires modeling. In my view, the distrust of modeling strategy, limited to a certain period, is largely due to a misconstrued threat to probability sample designs. The historical account and contributions of Hansen have deeper implications for future development in sample survey research and in training, ultimately integrating modeling and design principles for survey inferences.
Deep learning approach for identification of H ii regions during reionization in 21-cm observations – II. Foreground contamination
Authors: Bianco Michele , Giri Sambit K , Prelogović David , Chen Tianyue , Mertens Florent G , Tolley Emma , Mesinger Andrei , Kneib Jean-Paul
Published: January 2024

The upcoming Square Kilometre Array Observatory will produce images of neutral hydrogen distribution during the epoch of reionization by observing the corresponding 21-cm signal. However, the 21-cm signal will be subject to instrumental limitations such as noise and galactic foreground contamination that pose a challenge for accurate detection. In this study, we present the SegU-Net v2 framework, an enhanced version of our convolutional neural network, built to identify neutral and ionized regions in the 21-cm signal contaminated with foreground emission. We trained our neural network on 21-cm image data processed by a foreground removal method based on Principal Component Analysis achieving an average classification accuracy of 71 per cent between redshift z = 7 and 11. We tested SegU-Net v2 against various foreground removal methods, including Gaussian Process Regression, Polynomial Fitting, and Foreground-Wedge Removal. Results show comparable performance, highlighting SegU-Net v2’s independence on these pre-processing methods. Statistical analysis shows that a perfect classification score with ${\rm AUC}=95~{{\ \rm per\ cent}}$ is possible for 8 < z < 10. While the network prediction lacks the ability to correctly identify ionized regions at higher redshift and differentiate well the few remaining neutral regions at lower redshift due to low contrast between 21-cm signal, noise, and foreground residual in images. Moreover, as the photon sources driving reionization are expected to be located inside ionized regions, we show that SegU-Net v2 can be used to correctly identify and measure the volume of isolated bubbles with $V_{\rm ion}\gt (10\, {\rm cMpc})^3$ at z > 9, for follow-up studies with infrared/optical telescopes to detect these sources.
Determining the baryon impact on the matter power spectrum with galaxy clusters
Authors: Grandis Sebastian , Aricò Giovanni , Schneider Aurel , Linke Laila
Published: January 2024

The redistribution of baryonic matter in massive haloes through processes like active galactic nuclei feedback and star formation leads to a suppression of the matter power spectrum on small scales. This redistribution can be measured empirically via the gas and stellar mass fractions in galaxy clusters, and leaves imprints on their electron density profiles. We constrain two semi-analytical baryon correction models with a compilation of recent Bayesian population studies of galaxy groups and clusters sampling a mass range above ∼3 × 1013 M⊙, and with cluster gas density profiles derived from deep, high-resolution X-ray observations. We are able to fit all the considered observational data, but highlight some anomalies in the observations. The constraints allow us to place precise, physically informed priors on the matter power spectrum suppression. At a scale of k = 1 h Mpc−1 we find a suppression of $0.042^{+0.012}_{-0.014}$ ($0.049^{+0.016}_{-0.012}$), while at k = 3 h Mpc−1 we find $0.184^{+0.026}_{-0.031}$ ($0.179^{+0.018}_{-0.020}$), depending on the model used. In our fiducial setting, we also predict at 97.5 per cent credibility, that at scales k < 0.37 h Mpc−1 baryon feedback impacts the matter power less than 1 per cent. This puts into question if baryon feedback is the driving factor for the discrepancy between cosmic shear and primary CMB results. We independently confirm results on this suppression from small-scale cosmic shear studies, while we exclude some hydro-dynamical simulations with too strong and too weak baryonic feedback. Our empirical prediction of the power spectrum suppression shows that studies of galaxy groups and clusters will be instrumental in unlocking the cosmological constraining power of future cosmic shear experiments like Euclid and Rubin-LSST, and invites further investigation of the baryon correction models.
Effect of variable crustal density on the surface magnetic field of radio pulsars
Authors: Sellick Kathleen , Ray Subharthi
Published: January 2024

We study the surface magnetic field fluctuations due to radial oscillations as a viable cause for the microstructures of the radio pulsar pulse patterns. The electrical conductivity of matter in the outer layer of the crust of a neutron star (NS) plays a crucial role in the resulting surface magnetic field if we assume that the magnetic field is confined to this layer. This outer layer has a rapidly varying matter density that changes the microphysics of the material, affecting the electrical conductivity at every stage of the density change. In this study, the varying electrical conductivity in this rapidly varying density regime of the outer layer of the NS crust – from ∼1011 to about 104 g cm−3 – has been used to calculate the surface magnetic field using the induction equation. A finite effect of the strong gravitational field at the NS surface has also been taken into account. The equations have been solved in MATLAB using the method of lines. Any minor radial fluctuation due to stellar oscillation, in particular the radial oscillations, leads to a fluctuation of the electrical conductivity in the outer layer of the crust. This leads to fluctuations in the surface magnetic field with a frequency equal to the frequency of the stellar oscillation. We find that not only is the variation of the surface magnetic field substantial, but also it does not remain constant throughout the lifetime of the NS.
Measuring M31 globular cluster ages and metallicities using both photometry and spectroscopy
Authors: Usher Christopher , Caldwell Nelson , Cabrera-Ziri Ivan
Published: January 2024

The ages and metallicities of globular clusters play an important role not just in testing models for their formation and evolution but also in understanding the assembly history of their host galaxies. Here, we use a combination of imaging and spectroscopy to measure the ages and metallicities of globular clusters in M31, the closest massive galaxy to our own. We use the strength of the near-infrared calcium triplet spectral feature to provide a relatively age-insensitive prior on the metallicity when fitting stellar population models to the observed photometry. While the age–extinction degeneracy is an issue for globular clusters projected on to the disc of M31, we find generally old ages for globular clusters in the halo of M31 and in its satellite galaxy NGC 205 in line with previous studies. We measure ages for a number of outer halo globular clusters for the first time, finding that globular clusters associated with halo substructure extend to younger ages and higher metallicities than those associated with the smooth halo. This is in line with the expectation that the smooth halo was accreted earlier than the substructured halo.
Joint gravitational wave-short GRB detection of binary neutron star mergers with existing and future facilities
Authors: Bhattacharjee Soumyadeep , Banerjee Smaranika , Bhalerao Varun , Beniamini Paz , Bose Sukanta , Hotokezaka Kenta , Pai Archana , Saleem Muhammed , Waratkar Gaurav
Published: January 2024

We explore the joint detection prospects of short gamma-ray bursts (sGRBs) and their gravitational wave (GW) counterparts by the current and upcoming high-energy GRB and GW facilities from binary neutron star (BNS) mergers. We consider two GW detector networks: (1) a four-detector network comprising LIGO Hanford, Livingston, Virgo, and Kagra (IGWN4) and (2) a future five-detector network including the same four detectors and LIGO India (IGWN5). For the sGRB detection, we consider existing satellites Fermi and Swift and the proposed all-sky satellite Daksha. Most of the events for the joint detection will be off-axis, hence, we consider a broad range of sGRB jet models predicting the off-axis emission. Also, to test the effect of the assumed sGRB luminosity function, we consider two different functions for one of the emission models. We find that for the different jet models, the joint sGRB and GW detection rates for Fermi and Swift with IGWN4 (IGWN5) lie within 0.07–0.62  yr−1 0.8–4.0 yr−1) and 0.02–0.14 yr−1 (0.15–1.0 yr−1), respectively, when the BNS merger rate is taken to be 320 Gpc−3 yr−1. With Daksha, the rates increase to 0.2–1.3 yr−1 (1.3–8.3 yr−1), which is 2–9 times higher than the existing satellites. We show that such a mission with higher sensitivity will be ideal for detecting a higher number of fainter events observed off-axis or at a larger distance. Thus, Daksha will boost the joint detections of sGRB and GW, especially for the off-axis events. Finally, we find that our detection rates with optimal SNRs are conservative, and noise in GW detectors can increase the rates further.
Origin of reduced dynamical friction by dark matter haloes with net prograde rotation
Authors: Chiba Rimpei , Kataria Sandeep Kumar
Published: January 2024

We provide an explanation for the reduced dynamical friction on galactic bars in spinning dark matter haloes. Earlier work based on linear theory predicted an increase in dynamical friction when dark haloes have a net forward rotation because prograde orbits couple to bars with greater strength than retrograde orbits. Subsequent numerical studies, however, found the opposite trend: dynamical friction weakens with increasing spin of the halo. We revisit this problem and demonstrate that linear theory in fact correctly predicts a reduced torque in forward-rotating haloes. We show that shifting the halo mass from retrograde to prograde phase space generates a positive gradient in the distribution function near the origin of the z-angular momentum (Lz = 0), which results in a resonant transfer of Lz to the bar, making the net dynamical friction weaker. While this effect is subdominant for the major resonances, including the corotation resonance, it leads to a significant positive torque on the bar for the series of direct radial resonances as these resonances are strongest at Lz = 0. The overall dynamical friction from spinning haloes is shown to decrease with the halo’s spin in agreement with the secular behaviour of N-body simulations. We validate our linear calculation by computing the non-linear torque from individual resonances using the angle-averaged Hamiltonian.
Multiple mechanisms activate GCN2 eIF2 kinase in response to diverse stress conditions
Authors: Misra Jagannath , Carlson Kenneth R , Spandau Dan F , Wek Ronald C
Published: January 2024

Diverse environmental insults induce the integrated stress response (ISR), which features eIF2 phosphorylation and translational control that serves to restore protein homeostasis. The eIF2 kinase GCN2 is a first responder in the ISR that is activated by amino acid depletion and other stresses not directly related to nutrients. Two mechanisms are suggested to trigger an ordered process of GCN2 activation during stress: GCN2 monitoring stress via accumulating uncharged tRNAs or by stalled and colliding ribosomes. Our results suggest that while ribosomal collisions are indeed essential for GCN2 activation in response to translational elongation inhibitors, conditions that trigger deacylation of tRNAs activate GCN2 via its direct association with affected tRNAs. Both mechanisms require the GCN2 regulatory domain related to histidyl tRNA synthetases. GCN2 activation by UV irradiation features lowered amino acids and increased uncharged tRNAs and UV-induced ribosome collisions are suggested to be dispensable. We conclude that there are multiple mechanisms that activate GCN2 during diverse stresses.
Smoother: on-the-fly processing of interactome data using prefix sums
Authors: Schmidt Markus R , Barcons-Simon Anna , Rabuffo Claudia , Siegel T Nicolai
Published: January 2024

Nucleic acid interactome data, such as chromosome conformation capture data and RNA–DNA interactome data, are currently analyzed via pipelines that must be rerun for each new parameter set. A more dynamic approach is desirable since the optimal parameter set is commonly unknown ahead of time and rerunning pipelines is a time-consuming process. We have developed an approach fast enough to process interactome data on-the-fly using a sparse prefix sum index. With this index, we created Smoother, a flexible, multifeatured visualization and analysis tool that allows interactive filtering, e.g. by mapping quality, almost instant comparisons between different normalization approaches, e.g. iterative correction, and ploidy correction. Further, Smoother can overlay other sequencing data or genomic annotations, compare different samples, and perform virtual 4C analysis. Smoother permits a novel way to interact with and explore interactome data, fostering comprehensive, high-quality data analysis. Smoother is available at https://github.com/Siegel-Lab/BioSmoother under the MIT license.
Decoding the universal human chromatin landscape through teratoma-based profiling
Authors: Kidder Benjamin L
Published: January 2024

Teratoma formation is key for evaluating differentiation of human pluripotent stem cells into embryonic germ layers and serves as a model for understanding stem cell differentiation and developmental processes. Its potential for insights into epigenome and transcriptome profiling is significant. This study integrates the analysis of the epigenome and transcriptome of hESC-generated teratomas, comparing transcriptomes between hESCs and teratomas. It employs cell type-specific expression patterns from single-cell data to deconvolve RNA-Seq data and identify cell types within teratomas. Our results provide a catalog of activating and repressive histone modifications, while also elucidating distinctive features of chromatin states. Construction of an epigenetic signature matrix enabled the quantification of diverse cell populations in teratomas and enhanced the ability to unravel the epigenetic landscape in heterogeneous tissue contexts. This study also includes a single cell multiome atlas of expression (scRNA-Seq) and chromatin accessibility (scATAC-Seq) of human teratomas, further revealing the complexity of these tissues. A histology-based digital staining tool further complemented the annotation of cell types in teratomas, enhancing our understanding of their cellular composition. This research is a valuable resource for examining teratoma epigenomic and transcriptomic landscapes and serves as a model for epigenetic data comparison.
Genomic transcription factor binding site selection is edited by the chromatin remodeling factor CHD4
Authors: Saotome Mika , Poduval Deepak B , Grimm Sara A , Nagornyuk Aerica , Gunarathna Sakuntha , Shimbo Takashi , Wade Paul A , Takaku Motoki
Published: January 2024

Biologically precise enhancer licensing by lineage-determining transcription factors enables activation of transcripts appropriate to biological demand and prevents deleterious gene activation. This essential process is challenged by the millions of matches to most transcription factor binding motifs present in many eukaryotic genomes, leading to questions about how transcription factors achieve the exquisite specificity required. The importance of chromatin remodeling factors to enhancer activation is highlighted by their frequent mutation in developmental disorders and in cancer. Here, we determine the roles of CHD4 in enhancer licensing and maintenance in breast cancer cells and during cellular reprogramming. In unchallenged basal breast cancer cells, CHD4 modulates chromatin accessibility. Its depletion leads to redistribution of transcription factors to previously unoccupied sites. During cellular reprogramming induced by the pioneer factor GATA3, CHD4 activity is necessary to prevent inappropriate chromatin opening. Mechanistically, CHD4 promotes nucleosome positioning over GATA3 binding motifs to compete with transcription factor–DNA interaction. We propose that CHD4 acts as a chromatin proof-reading enzyme that prevents unnecessary gene expression by editing chromatin binding activities of transcription factors.
NMR measurements of transient low-populated tautomeric and anionic Watson–Crick-like G·T/U in RNA:DNA hybrids: implications for the fidelity of transcription and CRISPR/Cas9 gene editing
Authors: Szekely Or , Rangadurai Atul Kaushik , Gu Stephanie , Manghrani Akanksha , Guseva Serafima , Al-Hashimi Hashim M
Published: January 2024

Many biochemical processes use the Watson–Crick geometry to distinguish correct from incorrect base pairing. However, on rare occasions, mismatches such as G·T/U can transiently adopt Watson–Crick-like conformations through tautomerization or ionization of the bases, giving rise to replicative and translational errors. The propensities to form Watson–Crick-like mismatches in RNA:DNA hybrids remain unknown, making it unclear whether they can also contribute to errors during processes such as transcription and CRISPR/Cas editing. Here, using NMR R1ρ experiments, we show that dG·rU and dT·rG mismatches in two RNA:DNA hybrids transiently form tautomeric (Genol·T/U $ \mathbin{\lower.3ex\hbox{$\buildrel\textstyle\rightarrow\over {\smash{\leftarrow}\vphantom{_{\vbox to.5ex{\vss}}}}$}}$ G·Tenol/Uenol) and anionic (G·T−/U−) Watson–Crick-like conformations. The tautomerization dynamics were like those measured in A-RNA and B-DNA duplexes. However, anionic dG·rU− formed with a ten-fold higher propensity relative to dT−·rG and dG·dT− and this could be attributed to the lower pKa (ΔpKa ∼0.4–0.9) of U versus T. Our findings suggest plausible roles for Watson–Crick-like G·T/U mismatches in transcriptional errors and CRISPR/Cas9 off-target gene editing, uncover a crucial difference between the chemical dynamics of G·U versus G·T, and indicate that anionic Watson–Crick-like G·U− could play a significant role evading Watson–Crick fidelity checkpoints in RNA:DNA hybrids and RNA duplexes.
MMCT-Loop: a mix model-based pipeline for calling targeted 3D chromatin loops
Authors: Tang Li , Liao Jiaqi , Hill Matthew C , Hu Jiaxin , Zhao Yichao , Ellinor Patrick T , Li Min
Published: January 2024

Protein-specific Chromatin Conformation Capture (3C)-based technologies have become essential for identifying distal genomic interactions with critical roles in gene regulation. The standard techniques include Chromatin Interaction Analysis by Paired-End Tag (ChIA-PET), in situ Hi-C followed by chromatin immunoprecipitation (HiChIP) also known as PLAC-seq. To identify chromatin interactions from these data, a variety of computational methods have emerged. Although these state-of-art methods address many issues with loop calling, only few methods can fit different data types simultaneously, and the accuracy as well as the efficiency these approaches remains limited. Here we have generated a pipeline, MMCT-Loop, which ensures the accurate identification of strong loops as well as dynamic or weak loops through a mixed model. MMCT-Loop outperforms existing methods in accuracy, and the detected loops show higher activation functionality. To highlight the utility of MMCT-Loop, we applied it to conformational data derived from neural stem cell (NSCs) and uncovered several previously unidentified regulatory regions for key master regulators of stem cell identity. MMCT-Loop is an accurate and efficient loop caller for targeted conformation capture data, which supports raw data or pre-processed valid pairs as input, the output interactions are formatted and easily uploaded to a genome browser for visualization.
Rat1 promotes premature transcription termination at R-loops
Authors: Mérida-Cerro José Antonio , Maraver-Cárdenas Pablo , Rondón Ana G , Aguilera Andrés
Published: January 2024

Certain DNA sequences can adopt a non-B form in the genome that interfere with DNA-templated processes, including transcription. Among the sequences that are intrinsically difficult to transcribe are those that tend to form R-loops, three-stranded nucleic acid structures formed by a DNA-RNA hybrid and the displaced ssDNA. Here we compared the transcription of an endogenous gene with and without an R-loop-forming sequence inserted. We show that, in agreement with previous in vivo and in vitro analyses, transcription elongation is delayed by R-loops in yeast. Importantly, we demonstrate that the Rat1 transcription terminator factor facilitates transcription throughout such structures by inducing premature termination of arrested RNAPIIs. We propose that RNase H degrades the RNA moiety of the hybrid, providing an entry site for Rat1. Thus, we have uncovered an unanticipated function of Rat1 as a transcription restoring factor opening up the possibility that it may also promote transcription through other genomic DNA structures intrinsically difficult to transcribe. If R-loop-mediated transcriptional stress is not relieved by Rat1, it will cause genomic instability, probably through the increase of transcription-replication conflicts, a deleterious situation that could lead to cancer.
Ribosomal frameshifting at normal codon repeats recodes functional chimeric proteins in human
Authors: Ren Guiping , Gu Xiaoqian , Zhang Lu , Gong Shimin , Song Shuang , Chen Shunkai , Chen Zhenjing , Wang Xiaoyan , Li Zhanbiao , Zhou Yingshui , Li Longxi , Yang Jiao , Lai Fan , Dang Yunkun
Published: January 2024

Ribosomal frameshifting refers to the process that ribosomes slip into +1 or −1 reading frame, thus produce chimeric trans-frame proteins. In viruses and bacteria, programmed ribosomal frameshifting can produce essential trans-frame proteins for viral replication or regulation of other biological processes. In humans, however, functional trans-frame protein derived from ribosomal frameshifting is scarcely documented. Combining multiple assays, we show that short codon repeats could act as cis-acting elements that stimulate ribosomal frameshifting in humans, abbreviated as CRFS hereafter. Using proteomic analyses, we identified many putative CRFS events from 32 normal human tissues supported by trans-frame peptides positioned at codon repeats. Finally, we show a CRFS-derived trans-frame protein (HDAC1-FS) functions by antagonizing the activities of HDAC1, thus affecting cell migration and apoptosis. These data suggest a novel type of translational recoding associated with codon repeats, which may expand the coding capacity of mRNA and diversify the regulation in human.
SHIFTR enables the unbiased identification of proteins bound to specific RNA regions in live cells
Authors: Aydin Jens , Gabel Alexander , Zielinski Sebastian , Ganskih Sabina , Schmidt Nora , Hartigan Christina R , Schenone Monica , Carr Steven A , Munschauer Mathias
Published: January 2024

RNA-protein interactions determine the cellular fate of RNA and are central to regulating gene expression outcomes in health and disease. To date, no method exists that is able to identify proteins that interact with specific regions within endogenous RNAs in live cells. Here, we develop SHIFTR (Selective RNase H-mediated interactome framing for target RNA regions), an efficient and scalable approach to identify proteins bound to selected regions within endogenous RNAs using mass spectrometry. Compared to state-of-the-art techniques, SHIFTR is superior in accuracy, captures minimal background interactions and requires orders of magnitude lower input material. We establish SHIFTR workflows for targeting RNA classes of different length and abundance, including short and long non-coding RNAs, as well as mRNAs and demonstrate that SHIFTR is compatible with sequentially mapping interactomes for multiple target RNAs in a single experiment. Using SHIFTR, we comprehensively identify interactions of cis-regulatory elements located at the 5′ and 3′-terminal regions of authentic SARS-CoV-2 RNAs in infected cells and accurately recover known and novel interactions linked to the function of these viral RNA elements. SHIFTR enables the systematic mapping of region-resolved RNA interactomes for any RNA in any cell type and has the potential to revolutionize our understanding of transcriptomes and their regulation.
EquiPNAS: improved protein–nucleic acid binding site prediction using protein-language-model-informed equivariant deep graph neural networks
Authors: Roche Rahmatullah , Moussad Bernard , Shuvo Md Hossain , Tarafder Sumit , Bhattacharya Debswapna
Published: January 2024

Protein language models (pLMs) trained on a large corpus of protein sequences have shown unprecedented scalability and broad generalizability in a wide range of predictive modeling tasks, but their power has not yet been harnessed for predicting protein–nucleic acid binding sites, critical for characterizing the interactions between proteins and nucleic acids. Here, we present EquiPNAS, a new pLM-informed E(3) equivariant deep graph neural network framework for improved protein–nucleic acid binding site prediction. By combining the strengths of pLM and symmetry-aware deep graph learning, EquiPNAS consistently outperforms the state-of-the-art methods for both protein–DNA and protein–RNA binding site prediction on multiple datasets across a diverse set of predictive modeling scenarios ranging from using experimental input to AlphaFold2 predictions. Our ablation study reveals that the pLM embeddings used in EquiPNAS are sufficiently powerful to dramatically reduce the dependence on the availability of evolutionary information without compromising on accuracy, and that the symmetry-aware nature of the E(3) equivariant graph-based neural architecture offers remarkable robustness and performance resilience. EquiPNAS is freely available at https://github.com/Bhattacharya-Lab/EquiPNAS.
Ultrafast micro/nano-manufacturing of metastable materials for energy
Authors: Cui Xiaoya , Liu Yanchang , Chen Yanan
Published: January 2024

The structural engineering of metastable nanomaterials with abundant defects has attracted much attention in energy-related fields. The high-temperature shock (HTS) technique, as a rapidly developing and advanced synthesis strategy, offers significant potential for the rational design and fabrication of high-quality nanocatalysts in an ultrafast, scalable, controllable and eco-friendly way. In this review, we provide an overview of various metastable micro- and nanomaterials synthesized via HTS, including single metallic and bimetallic nanostructures, high entropy alloys, metal compounds (e.g. metal oxides) and carbon nanomaterials. Note that HTS provides a new research dimension for nanostructures, i.e. kinetic modulation. Furthermore, we summarize the application of HTS—as supporting films for transmission electron microscopy grids—in the structural engineering of 2D materials, which is vital for the direct imaging of metastable materials. Finally, we discuss the potential future applications of high-throughput and liquid-phase HTS strategies for non-equilibrium micro/nano-manufacturing beyond energy-related fields. It is believed that this emerging research field will bring new opportunities to the development of nanoscience and nanotechnology in both fundamental and practical aspects.