Genome editing methods have commonly relied on the initial introduction of double-stranded DNA breaks (DSBs), resulting in stochastic insertions, deletions, and translocations at the target genomic locus. To achieve gene correction, these methods typically require the introduction of exogenous DNA repair templates and low-efficiency homologous recombination processes. In this review, we describe alternative, mechanistically motivated strategies to perform chemistry on the genome of unmodified cells without introducing DSBs. One such strategy, base editing, uses chemical and biological insights to directly and permanently convert one target base pair to another. Despite its recent introduction, base editing has already enabled a number of new capabilities and applications in the genome editing community. We summarize these advances here and discuss the new possibilities that this method has unveiled, concluding with a brief analysis of future prospects for genome and transcriptome editing without double-stranded DNA cleavage.

We propose a system for dynamic triangle mesh processing entirely on the GPU. Our system offers an efficient data structure that allows fast updates of the underlying mesh connectivity and attributes. Our data structure partitions the mesh into small patches which allows processing all dynamic updates for each patch within the GPU's fast shared memory. This allows us to rely on speculative processing for conflict handling, which has low rollback cost while maximizing parallelism and reducing the cost of locking. Our system also introduces a new programming model for dynamic mesh processing. The programming model offers concise semantics for dynamic updates, relieving the user from having to worry about conflicting updates in the context of parallel execution. Our programming model relies on the cavity operator, which is a general mesh update operator that formulates any dynamic operation as an element reinsertion by removing a set of mesh elements and inserting others in the created void. We used our system to implement Delaunay edge flips and isotropic remeshing applications on the GPU. Our system achieves a 3—18x speedup on large models compared to multithreaded CPU solutions. Despite our additional dynamic features, our data structure also outperforms state-of-the-art GPU static data structures in terms of speed and memory requirements.

We propose a new static high-performance mesh data structure for triangle surface meshes on the GPU. Our data structure is carefully designed for parallel execution while capturing mesh locality and confining data access, as much as possible, within the GPU's fast shared memory. We achieve this by subdividing the mesh into patches and representing these patches compactly using a matrix-based representation. Our patching technique is decorated with ribbons, thin mesh strips around patches that eliminate the need to communicate between different computation thread blocks, resulting in consistent high throughput. We call our data structure RXMesh: Ribbon-matriX Mesh. We hide the complexity of our data structure behind a flexible but powerful programming model that helps deliver high performance by inducing load balance even in highly irregular input meshes. We show the efficacy of our programming model on common geometry processing applications—mesh smoothing and filtering, geodesic distance, and vertex normal computation. For evaluation, we benchmark our data structure against well-optimized GPU and (single and multi-core) CPU data structures and show significant speedups.

In many geometry processing applications, it is required to improve an initial mesh in terms of multiple quality objectives. Despite the availability of several mesh generation algorithms with provable guarantees, such generated meshes may only satisfy a subset of the objectives. The conflicting nature of such objectives makes it challenging to establish similar guarantees for each combination, e.g., angle bounds and vertex count. In this paper, we describe a versatile strategy for mesh improvement by interpreting quality objectives as spatial constraints on resampling and develop a toolbox of local operators to improve the mesh while preserving desirable properties. Our strategy judiciously combines smoothing and transformation techniques allowing increased flexibility to practically achieve multiple objectives simultaneously.  We apply our strategy to both planar and surface meshes demonstrating how to simplify Delaunay meshes while preserving element quality, eliminate all obtuse angles in a complex mesh, and maximize the shortest edge length in a Voronoi tessellation far better than the state-of-the-art.

Kommerell diverticulum is the aneurysmal dilatation of the proximal descending aorta at the origin of an aberrant subclavian artery and may occur in either the left-sided or right-sided aortic arch. We report an unusual case of right-sided aortic arch with Kommerell diverticulum and concurrent agenesis of the left common carotid artery in a patient with progressive dysphagia to solid food. A brief overview of embryology, relevant anatomy, radiographic findings, and treatment options of Kommerell diverticulum are presented.

Acute generalized exanthematous pustulosis (AGEP) is an abrupt cutaneous adverse reaction usually in response to medications. It is generally a self-limiting disease if diagnosed promptly and the offending agent discontinued. Cetirizine, a commonly used anti-histamine medication for the treatment of allergic diseases has few reported side effects and is normally well-tolerated and effective. Herein, the first reported case of cetirizine induced AGEP is presented, followed by a discussion of the clinical and pathological aspects of this adverse cutaneous reaction to a widely used drug. Awareness of this reaction is vital owing to the extensive use of cetirizine and the importance of drug cessation once the reaction is identified. Lastly, other pustular cutaneous reactions may present similarly and therefore accurate identification of this disease can prevent unnecessary diagnostic testing.