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Abstract Embedding a collective of tumor cells, i.e. a tumor spheroid, in a fibrous environment, such as a collagen network, provides an essentialin vitroplatform to investigate the biophysical mechanisms of tumor invasion. To predict new mechanisms, we develop a three-dimensional computational model of an embedded spheroid using a vertex model, with cells represented as deformable polyhedrons, mechanically coupled to a fiber network via active linker springs. As the linker springs actively contract, the fiber network remodels. As we tune the rheology of the spheroid and the fiber network stiffness, we find that both factors affect the remodeling of the fiber network with fluid-like spheroids densifying and radially realigning the fiber network more on average than solid-like spheroids but only for a range of intermediate fiber network stiffnesses. Our predictions are supported by experimental studies comparing non-tumorigenic MCF10A spheroids and malignant MDA-MB-231 spheroids embedded in collagen networks. The spheroid rheology-dependent effects are the result of cellular motility generating spheroid shape fluctuations. These shape fluctuations lead to emergent feedback between the spheroid and the fiber network to further remodel the fiber network. This emergent feedback occurs only at intermediate fiber network stiffness since at low fiber network stiffness, the mechanical response of the coupled system is dominated by the spheroid and for high fiber network stiffness, the mechanical response is dominated by the fiber network. We are therefore able to quantify the regime of optimal spheroid-fiber network mechanical reciprocity. Our results uncover intricate morphological-mechanical interplay between an embedded spheroid and its surrounding fiber network with both spheroid contractile strengthandspheroid shape fluctuations playing important roles in the pre-invasion stages of tumor invasion. 

Increasing studies have shown bugs in multi-language software as a critical loophole in modern software quality assurance, especially those induced by language interactions (i.e., multilingual bugs). Yet existing tool support for bug detection/localization remains largely limited to single-language software, despite the long-standing prevalence of multi-language systems in various real-world software domains. Extant static/dynamic analysis and deep learning (DL) based approaches all face major challenges in addressing multilingual bugs. In this paper, we present xLoc, a DL-based technique/tool for detecting and localizing multilingual bugs. Motivated by results of our bug-characteristics study on top locations of multilingual bugs, xLoc first learns the general knowledge relevant to differentiating various multilingual control-flow structures. This is achieved by pre-training a Transformer model with customized position encoding against novel objectives. Then, xLoc learns task-specific knowledge for the task of multilingual bug detection/localization, through another new position encoding scheme (based on cross-language API vicinity) that allows for the model to attend particularly to control-flow constructs that bear most multilingual bugs during fine-tuning. We have implemented xLoc for Python-C software and curated a dataset of 3,770 buggy and 15,884 non-buggy Python-C samples, which enabled our extensive evaluation of xLoc against two state-of-the-art baselines: fine-tuned CodeT5 and zero-shot ChatGPT. Our results show that xLoc achieved 94.98% F1 and 87.24%@Top-1 accuracy, which are significantly (up to 162.88% and 511.75%) higher than the baselines. Ablation studies further confirmed significant contributions of each of the novel design elements in xLoc. With respective bug-location characteristics and labeled bug datasets for fine-tuning, our design may be applied to other language combinations beyond Python-C. 

Multi-axial real-time hybrid simulation (maRTHS) uses multiple hydraulic actuators to apply loads and deform experimental substructures, enacting bothtranslationalandrotationalmotion. This allows for an increased level of realism in seismic testing. However, this also demands the implementation of multiple-input, multiple-output control strategies with complex nonlinear behaviors. To realize true real-time hybrid simulation at the necessary sub-millisecond timescales, computational platforms will need to support these complexities at scale, while still providing deadline assurance. This paper presents initial work towards supporting (and is influenced by the need for) envisioned larger-scale future experiments based on the current maRTHS benchmark: it discusses aspects of hardware, operating system kernels, runtime middleware, and scheduling theory that may be leveraged or developed to meet those goals. This work aims to create new concurrency platforms capable of managing task scheduling and adaptive event handling for computationally intensive numerical simulation and control models like those for the maRTHS benchmark problem. These should support real-time behavior at millisecond timescales, even for large complex structures with thousands of degrees of freedom. Temporal guarantees should be maintained across behavioral and computational mode changes, e.g., linear to nonlinear control. Pursuant to this goal, preliminary scalability analysis is conducted towards designing future maRTHS experiments. The results demonstrate that the increased capabilities of modern hardware architectures are able to handle larger finite element models compared to prior work, while imposing the same latency constraints. However, the results also illustrate a subtle challenge: with larger numbers of CPU cores, thread coordination incurs more overhead. These results provide insight into the computational requirements to support envisioned future experiments that will take the maRTHS benchmark problem to nine stories and beyond in scale. In particular, this paper (1) re-evaluates scalability of prior work on current platform hardware, and (2) assesses the resource demands of a basic smaller scale model from which to gauge the projected scalability of the new maRTHS benchmark as ever larger and more complex models are integrated within it. 

Abstract Cytosine base editors (CBEs) and adenine base editors (ABEs) enable precise C-to-T and A-to-G edits. Recently, ABE8e, derived from TadA-8e, enhances A-to-G edits in mammalian cells and plants. Interestingly, TadA-8e can also be evolved to confer C-to-T editing. This study compares engineered CBEs derived from TadA-8e in rice and tomato cells, identifying TadCBEa, TadCBEd, and TadCBEd_V106W as efficient CBEs with high purity and a narrow editing window. A dual base editor, TadDE, promotes simultaneous C-to-T and A-to-G editing. Multiplexed base editing with TadCBEa and TadDE is demonstrated in transgenic rice, with no off-target effects detected by whole genome and transcriptome sequencing, indicating high specificity. Finally, two crop engineering applications using TadDE are shown: introducing herbicide resistance alleles inOsALSand creating synonymous mutations inOsSPL14to resistOsMIR156-mediated degradation. Together, this study presents TadA-8e derived CBEs and a dual base editor as valuable additions to the plant editing toolbox. 

Abstract Centromeres in most multicellular eukaryotes are composed of long arrays of repetitive DNA sequences. Interestingly, several transposable elements, including the well-known long terminal repeat centromeric retrotransposon of maize (CRM), were found to be enriched in functional centromeres marked by the centromeric histone H3 (CENH3). Here, we report a centromeric long interspersed nuclear element (LINE), Celine, in Populus species. Celine has colonized preferentially in the CENH3-associated chromatin of every poplar chromosome, with 84% of the Celine elements localized in the CENH3-binding domains. In contrast, only 51% of the CRM elements were bound to CENH3 domains in Populus trichocarpa. These results suggest different centromere targeting mechanisms employed by Celine and CRM elements. Nevertheless, the high target specificity seems to be detrimental to further amplification of the Celine elements, leading to a shorter life span and patchy distribution among plant species compared with the CRM elements. Using a phylogenetically guided approach, we were able to identify Celine-like LINE elements in tea plant (Camellia sinensis) and green ash tree (Fraxinus pennsylvanica). The centromeric localization of these Celine-like LINEs was confirmed in both species. We demonstrate that the centromere targeting property of Celine-like LINEs is of primitive origin and has been conserved among distantly related plant species. 

Summary CRISPR‐Cas9 is widely used for genome editing, but its PAM sequence requirements limit its efficiency. In this study, we exploreFaecalibaculum rodentiumCas9 (FrCas9) for plant genome editing, especially in rice. FrCas9 recognizes a concise 5′‐NNTA‐3′ PAM, targeting more abundant palindromic TA sites in plant genomes than the 5′‐NGG‐3′ PAM sites of the most popular SpCas9. FrCas9 shows cleavage activities at all tested 5′‐NNTA‐3′ PAM sites with editing outcomes sharing the same characteristics of a typical CRISPR‐Cas9 system. FrCas9 induces high‐efficiency targeted mutagenesis in stable rice lines, readily generating biallelic mutants with expected phenotypes. We augment FrCas9's ability to generate larger deletions through fusion with the exonuclease, TREX2. TREX2‐FrCas9 generates much larger deletions than FrCas9 without compromise in editing efficiency. We demonstrate TREX2‐FrCas9 as an efficient tool for genetic knockout of a microRNA gene. Furthermore, FrCas9‐derived cytosine base editors (CBEs) and adenine base editors (ABE) are developed to produce targeted C‐to‐T and A‐to‐G base edits in rice plants. Whole‐genome sequencing‐based off‐target analysis suggests that FrCas9 is a highly specific nuclease. Expression of TREX2‐FrCas9 in plants, however, causes detectable guide RNA‐independent off‐target mutations, mostly as single nucleotide variants (SNVs). Together, we have established an efficient CRISPR‐FrCas9 system for targeted mutagenesis, large deletions, C‐to‐T base editing, and A‐to‐G base editing in plants. The simple palindromic TA motif in the PAM makes the CRISPR‐FrCas9 system a promising tool for genome editing in plants with an expanded targeting scope.