bluuebunny/crossref_metadata_2025_split huggingface dataset:
Recombination smooths the time signal disrupted by latency in within-host HIV phylogenies
Authors: Castro Lauren A , Leitner Thomas , Romero-Severson Ethan 
Published: May 2023

Abstract
Within-host Human immunodeficiency virus (HIV) evolution involves several features that may disrupt standard phylogenetic reconstruction. One important feature is reactivation of latently integrated provirus, which has the potential to disrupt the temporal signal, leading to variation in the branch lengths and apparent evolutionary rates in a tree. Yet, real within-host HIV phylogenies tend to show clear, ladder-like trees structured by the time of sampling. Another important feature is recombination, which violates the fundamental assumption that evolutionary history can be represented by a single bifurcating tree. Thus, recombination complicates the within-host HIV dynamic by mixing genomes and creating evolutionary loop structures that cannot be represented in a bifurcating tree. In this paper, we develop a coalescent-based simulator of within-host HIV evolution that includes latency, recombination, and effective population size dynamics that allows us to study the relationship between the true, complex genealogy of within-host HIV evolution, encoded as an ancestral recombination graph (ARG), and the observed phylogenetic tree. To compare our ARG results to the familiar phylogeny format, we calculate the expected bifurcating tree after decomposing the ARG into all unique site trees, their combined distance matrix, and the overall corresponding bifurcating tree. While latency and recombination separately disrupt the phylogenetic signal, remarkably, we find that recombination recovers the temporal signal of within-host HIV evolution caused by latency by mixing fragments of old, latent genomes into the contemporary population. In effect, recombination averages over extant heterogeneity, whether it stems from mixed time signals or population bottlenecks. Furthermore, we establish that the signals of latency and recombination can be observed in phylogenetic trees despite being an incorrect representation of the true evolutionary history. Using an approximate Bayesian computation method, we develop a set of statistical probes to tune our simulation model to nine longitudinally sampled within-host HIV phylogenies. Because ARGs are exceedingly difficult to infer from real HIV data, our simulation system allows investigating effects of latency, recombination, and population size bottlenecks by matching decomposed ARGs to real data as observed in standard phylogenies.
Mutation rate, selection, and epistasis inferred from RNA virus haplotypes via neural posterior estimation
Authors: Caspi Itamar , Meir Moran , Ben Nun Nadav , Abu Rass Reem , Yakhini Uri , Stern Adi , Ram Yoav 
Published: May 2023

Abstract
RNA viruses are particularly notorious for their high levels of genetic diversity, which is generated through the forces of mutation and natural selection. However, disentangling these two forces is a considerable challenge, and this may lead to widely divergent estimates of viral mutation rates, as well as difficulties in inferring the fitness effects of mutations. Here, we develop, test, and apply an approach aimed at inferring the mutation rate and key parameters that govern natural selection, from haplotype sequences covering full-length genomes of an evolving virus population. Our approach employs neural posterior estimation, a computational technique that applies simulation-based inference with neural networks to jointly infer multiple model parameters. We first tested our approach on synthetic data simulated using different mutation rates and selection parameters while accounting for sequencing errors. Reassuringly, the inferred parameter estimates were accurate and unbiased. We then applied our approach to haplotype sequencing data from a serial passaging experiment with the MS2 bacteriophage, a virus that parasites Escherichia coli. We estimated that the mutation rate of this phage is around 0.2 mutations per genome per replication cycle (95% highest density interval: 0.051–0.56). We validated this finding with two different approaches based on single-locus models that gave similar estimates but with much broader posterior distributions. Furthermore, we found evidence for reciprocal sign epistasis between four strongly beneficial mutations that all reside in an RNA stem loop that controls the expression of the viral lysis protein, responsible for lysing host cells and viral egress. We surmise that there is a fine balance between over- and underexpression of lysis that leads to this pattern of epistasis. To recap, we have developed an approach for joint inference of the mutation rate and selection parameters from full haplotype data with sequencing errors and used it to reveal features governing MS2 evolution.
Computational infrared and Raman spectra by hybrid QM/MM techniques: a study on molecular and catalytic material systems
Authors: Guan Jingcheng , Lu You , Sen Kakali , Abdul Nasir Jamal , Desmoutier Alec W. , Hou Qing , Zhang Xingfan , Logsdail Andrew J. , Dutta Gargi , Beale Andrew M. , Strange Richard W. , Yong Chin , Sherwood Paul , Senn Hans M. , Catlow C. Richard A. , Keal Thomas W. , Sokol Alexey A. 
Published: May 2023

Vibrational spectroscopy is one of the most well-established and important techniques for characterizing chemical systems. To aid the interpretation of experimental infrared and Raman spectra, we report on recent theoretical developments in the ChemShell computational chemistry environment for modelling vibrational signatures. The hybrid quantum mechanical and molecular mechanical approach is employed, using density functional theory for the electronic structure calculations and classical forcefields for the environment. Computational vibrational intensities at chemical active sites are reported using electrostatic and fully polarizable embedding environments to achieve more realistic vibrational signatures for materials and molecular systems, including solvated molecules, proteins, zeolites and metal oxide surfaces, providing useful insight into the effect of the chemical environment on the signatures obtained from experiment. This work has been enabled by the efficient task-farming parallelism implemented in ChemShell for high-performance computing platforms.
This article is part of a discussion meeting issue ‘Supercomputing simulations of advanced materials’.
Exact distributed kinetic Monte Carlo simulations for on-lattice chemical kinetics: lessons learnt from medium- and large-scale benchmarks
Authors: Savva Giannis D. , Benson Raz L. , Christidi Ilektra-Athanasia , Stamatakis Michail 
Published: May 2023

Kinetic Monte Carlo (KMC) simulations have been instrumental in multiscale catalysis studies, enabling the elucidation of the complex dynamics of heterogeneous catalysts and the prediction of macroscopic performance metrics, such as activity and selectivity. However, the accessible length- and time-scales have been a limiting factor in such simulations. For instance, handling lattices containing millions of sites with ‘traditional’ sequential KMC implementations is prohibitive owing to large memory requirements and long simulation times. We have recently established an approach for exact, distributed, lattice-based simulations of catalytic kinetics which couples the Time-Warp algorithm with the Graph-Theoretical KMC framework, enabling the handling of complex adsorbate lateral interactions and reaction events within large lattices. In this work, we develop a lattice-based variant of the Brusselator system, a prototype chemical oscillator pioneered by Prigogine and Lefever in the late 60s, to benchmark and demonstrate our approach. This system can form spiral wave patterns, which would be computationally intractable with sequential KMC, while our distributed KMC approach can simulate such patterns 15 and 36 times faster with 625 and 1600 processors, respectively. The medium- and large-scale benchmarks thus conducted, demonstrate the robustness of the approach, and reveal computational bottlenecks that could be targeted in further development efforts.
This article is part of a discussion meeting issue ‘Supercomputing simulations of advanced materials’.
Challenges in modelling dynamic processes in realistic nanostructured materials at operating conditions
Authors: Van Speybroeck Veronique 
Published: May 2023

The question is addressed in how far current modelling strategies are capable of modelling dynamic phenomena in realistic nanostructured materials at operating conditions. Nanostructured materials used in applications are far from perfect; they possess a broad range of heterogeneities in space and time extending over several orders of magnitude. Spatial heterogeneities from the subnanometre to the micrometre scale in crystal particles with a finite size and specific morphology, impact the material's dynamics. Furthermore, the material's functional behaviour is largely determined by the operating conditions. Currently, there exists a huge length–time scale gap between attainable theoretical length–time scales and experimentally relevant scales. Within this perspective, three key challenges are highlighted within the molecular modelling chain to bridge this length–time scale gap. Methods are needed that enable (i) building structural models for realistic crystal particles having mesoscale dimensions with isolated defects, correlated nanoregions, mesoporosity, internal and external surfaces; (ii) the evaluation of interatomic forces with quantum mechanical accuracy albeit at much lower computational cost than the currently used density functional theory methods and (iii) derivation of the kinetics of phenomena taking place in a multi-length–time scale window to obtain an overall view of the dynamics of the process.
This article is part of a discussion meeting issue ‘Supercomputing simulations of advanced materials’.
Analysing ill-conditioned Markov chains
Authors: Woods Esmae J. , Kannan Deepti , Sharpe Daniel J. , Swinburne Thomas D. , Wales David J. 
Published: May 2023

Discrete state Markov chains in discrete or continuous time are widely used to model phenomena in the social, physical and life sciences. In many cases, the model can feature a large state space, with extreme differences between the fastest and slowest transition timescales. Analysis of such ill-conditioned models is often intractable with finite precision linear algebra techniques. In this contribution, we propose a solution to this problem, namely partial graph transformation, to iteratively eliminate and renormalize states, producing a low-rank Markov chain from an ill-conditioned initial model. We show that the error induced by this procedure can be minimized by retaining both the renormalized nodes that represent metastable superbasins, and those through which reactive pathways concentrate, i.e. the dividing surface in the discrete state space. This procedure typically returns a much lower rank model, where trajectories can be efficiently generated with kinetic path sampling. We apply this approach to an ill-conditioned Markov chain for a model multi-community system, measuring the accuracy by direct comparison with trajectories and transition statistics.This article is part of a discussion meeting issue ‘Supercomputing simulations of advanced materials’.
Structure prediction in low dimensions: concepts, issues and examples
Authors: Schön J. Christian 
Published: May 2023

Structure prediction of stable and metastable polymorphs of chemical systems in low dimensions has become an important field, since materials that are patterned on the nano-scale are of increasing importance in modern technological applications. While many techniques for the prediction of crystalline structures in three dimensions or of small clusters of atoms have been developed over the past three decades, dealing with low-dimensional systems—ideal one-dimensional and two-dimensional systems, quasi-one-dimensional and quasi-two-dimensional systems, as well as low-dimensional composite systems—poses its own challenges that need to be addressed when developing a systematic methodology for the determination of low-dimensional polymorphs that are suitable for practical applications. Quite generally, the search algorithms that had been developed for three-dimensional systems need to be adjusted when being applied to low-dimensional systems with their own specific constraints; in particular, the embedding of the (quasi-)one-dimensional/two-dimensional system in three dimensions and the influence of stabilizing substrates need to be taken into account, both on a technical and a conceptual level.
This article is part of a discussion meeting issue ‘Supercomputing simulations of advanced materials’.
Solubility-consistent force field simulations for aqueous metal carbonate systems using graphical processing units
Authors: Armstrong Blake , Silvestri Alessandro , Demichelis Raffaella , Raiteri Paolo , Gale Julian D. 
Published: May 2023

Crystallization of alkaline earth metal carbonates from water is important for biomineralization and environmental geochemistry. Here, large-scale computer simulations are a useful approach to complement experimental studies by providing atomistic insights and even by quantitatively determining the thermodynamics of individual steps. However, this is dependent on the existence of force field models that are sufficiently accurate while being computationally efficient enough to sample complex systems. Here, we introduce a revised force field for aqueous alkaline earth metal carbonates that reproduces both the solubilities of the crystalline anhydrous minerals, as well as the hydration free energies of the ions. The model is also designed to run efficiently on graphical processing units thereby reducing the cost of such simulations. The performance of the revised force field is compared against previous results for important properties relevant to crystallization, including ion-pairing and mineral–water interfacial structure and dynamics.
This article is part of a discussion meeting issue ‘Supercomputing simulations of advanced materials’.
Review: understanding the properties of amorphous materials with high-performance computing methods
Authors: Christie J. K. 
Published: May 2023

Amorphous materials have no long-range order in their atomic structure. This makes much of the formalism for the study of crystalline materials irrelevant, and so elucidating their structure and properties is challenging. The use of computational methods is a powerful complement to experimental studies, and in this paper we review the use of high-performance computing methods in the simulation of amorphous materials. Five case studies are presented to showcase the wide range of materials and computational methods available to practitioners in this field.
This article is part of a discussion meeting issue ‘Supercomputing simulations of advanced materials’.
The structural and functional modularity of ovarian follicle epithelium in the pill-millipedeHyleoglomeris japonica(Myriapoda: Diplopoda: Pentazonia: Glomerida) and the morphological reconsideration of somatic tissues around oocytes in Myriapoda
Authors: Chikami Yasuhiko , Yahata Kensuke 
Published: May 2023

AbstractOvarian somatic tissues around oocytes are essential for oogenesis in many metazoans. The functional ovarian somatic tissues sometimes have structural properties specific to their roles. In contrast, there is no evidence of such structural modularity of the follicle epithelium in Myriapoda, suggesting that myriapod ovarian soma may not participate in oogenesis. The ultrastructural nature of follicle cells also supports solitary oogenesis in most myriapods investigated. In contrast, here, we report two structurally and developmentally distinct domains of the follicle epithelium in the Japanese pill millipede,Hyleoglomeris japonica. The follicle epithelium ofH. japonicahas a thick cell mass on the apex of the follicle. These thick cells contain the rich rough endoplasmic reticulum, mitochondria, and Goldi bodies and possess many microvilli, indicating synthetic/secretory activities, and become thicker along with the oogenetic progress. Another region of epithelium does not exhibit these features. These results show the structural and functional modularity specific to some functions of the follicle epithelium ofH. japonica. Therefore, the follicle epithelium of Myriapoda is divided into 3 types: physiologically functional uniformly, nonfunctional only, and those with both. We suggest the need to reconsider the nature and roles of ovarian somatic tissues of Myriapoda and Arthropoda.
Establishment of hairy root culture and its genetic transformation ofStephania tetrandraS. Moore for production of BIAs
Authors: Zhang Xiuhua , Bu Junling , Zhao Yujun , Li Qishuang , Li Xinyi , Ma Ying , Tang Jinfu , Wang Jian , Lai Changjiangsheng , Cui Guanghong , Guo Juan , Huang Luqi 
Published: May 2023

AbstractMetabolic engineering improvement of plants will play an essential role in future agriculture, but this largely depends on the establishment of genetic transformation.Stephania tetrandraS. Moore is a traditional Chinese medicine used for rheumatalgia that accumulates benzylisoquinoline alkaloids as its main active ingredients. Wild or farmed plants have remained the main source of these essential medicines, resulting in supply pressure due to the scarcity of wild plant resources and the slow growth rate in cultivation. Here, we constructedAgrobacterium rhizogenes(C58C1)-mediated hairy root culture and a co-transformation system inS. tetrandrato obtain a new source of bisbenzylisoquinoline alkaloids production. We show that the biomass of the hairy roots increased by 10-fold, and the content of tetrandrine reached 8.382 ± 0.160 mg/g DW after 50 days of cultivation. In addition, overexpression of (R, S)-norcoclaurine 6-O-methyltransferase (6OMT) gene or treatment of hairy roots with methyl jasmonate (MJ) increased protoberberine alkaloid content. This work provides a method of obtaining hairy roots and a genetic transformation system forS. tetrandra, not only broadening the access toS. tetrandraresources, but also laying a foundation for further elucidation of the biosynthesis of tetrandrine and related alkaloids.
On-farm hatching and contact with adult hen post hatch induce sex-dependent effects on performance, health and robustness in broiler chickens
Authors: Guilloteau L. A. , Bertin A. , Crochet S. , Bagnard C. , Hondelatte A. , Ravon L. , Schouler C. , Germain K. , Collin A. 
Published: May 2023

AbstractTo improve the early perinatal conditions of broiler chicks, alternative hatching systems have been developed. On-farm hatching (OFH) with an enriched microbial and stimulating environment by the presence of an adult hen is a promising solution. Day-old chicks were allotted within five hatching and rearing conditions: OFH, conventional hatchery (CH), CH and post-hatching treatment with antibiotics (CH + AB), as well as both hatching systems with an adult hen at hatching (OFH + H, CH + H). To challenge the robustness of chickens, they were exposed on D27 to suboptimal rearing conditions by combining for 4 h transport in boxes in a new room at a lower temperature and fasting. On their return to the original room, the chicken density was increased, and birds were orally vaccinated with the Gumboro vaccine. The impacts of these conditions on hatchability, chick quality score, performance, health and robustness were determined. The OFH chick body weights (BWs) were significantly greater than those of CH chicks at hatching. Whereas there was no effect of hatching conditions, the presence of hens decreased the hatchability rate, the quality score of OFH chicks and increased mortality at hatching. Treatment of CH chicks with antibiotics (CH + AB) temporarily decreased chicken BW at D19, but the feed conversion ratio (FCR) was not modified. At D19, OFH chicks had the highest BW compared to the other groups, and the presence of hens at hatching harmed chicken BW regardless of the hatching condition and FCR. An interaction between the effect of experimental rearing conditions and chicken sex was observed later for BW. In males, the OFH chickens were the heaviest compared to the other groups at D34 but not at D56. The presence of hens negatively impacted CH chicken BW at D56. In females, there was no effect of hatching condition on the BWs at D34 and D56, and the presence of hens had a positive impact on OFH chicken BW. There was no effect of hatching conditions on health parameters. In conclusion, the OFH system was a hatching system at least equivalent to the CH system. The presence of the hen at hatching and during the chick start-up phase on performance interacted with the hatching condition and the sex of the chickens.
Enhancing anti-gastrointestinal cancer activities of CLDN18.2 CAR-T armored with novel synthetic NKG2D receptors Containing DAP10 and DAP12 signaling domains
Authors: Sun Minmin , Wang Hongye , Hao Ruidong , Wang Youtao , Li Yantao , Zhong Yunpeng , Zhang Shuangshuang , Zhai Bo , Cheng Yuanguo 
Published: May 2023

AbstractChimeric antigen receptor (CAR) T therapies have shown remarkable efficacy in hematopoietic malignancies, but their therapeutic benefits in solid tumors have been limited due to heterogeneities in both antigen types and their expression levels on tumor cells. NK group 2 member D ligands (NKG2DLs) are extensively expressed on various tumors and absent on normal tissues, making them a promising target for cellular immunotherapy. DAP10 and DAP12 function as adaptor proteins in NK cells to transduce activating signals, and recent studies have revealed DAP10 and DAP12’s additional role as a co-stimulatory signal in T cells. Our pre-clinical data showed that CAR-T targeting CLDN18.2 is highly effective in gastrointestinal (GI) cancers, but the heterogeneous expression of CLDN18.2 poses a treatment challenge. To complement this antigen deficiency, we demonstrated that NKG2DLs were extensively expressed in GI tumor tissues and formed an ideal dual target. Here, we reported a CLDN18.2 CAR design armored with synthetic NKG2D receptors (SNR) containing DAP10 and DAP12 signaling domains. This novel CAR-T showed improved cytotoxicity against tumor cells with heterogeneous expression of CLDN18.2. The possible underlined mechanism is that SNR promotes CAR-T memory formation and reduces their exhaustion, while also enhancing their expansion and ability to infiltrate immune-excluded tumors in vivo. Taken together, SNR with DAP10/12 signaling and their synergistic involvement, increased CAR-T function and overcame the antigen deficiency, providing a novel treatment modality for solid GI tumor.