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Sequential membrane- and protein-bound organelles compartmentalize genomes during phage infection
Many eukaryotic viruses require membrane-bound compartments for replication, but no such organelles are known to be formed by prokaryotic viruses. Bacteriophages of the Chimalliviridae family sequester their genomes within a phage-generated organelle, the phage nucleus, which is enclosed by a lattice of the viral protein ChmA. We show that inhibiting phage nucleus formation arrests infections at an early stage in which the injected phage genome is enclosed within a membrane-bound early phage infection (EPI) vesicle. Early phage genes are expressed from the EPI vesicle, demonstrating its functionality as a prokaryotic, transcriptionally active, membrane-bound organelle. We also show that the phage nucleus is essential, with genome replication beginning after the injected DNA is transferred from the EPI vesicle to the phage nucleus. Our results show that Chimalliviridae require two sophisticated subcellular compartments of distinct compositions and functions that facilitate successive stages of the viral life cycle.
Deep Sequential Feature Learning in Clinical Image Classification of Infectious Keratitis
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Sequential Bayesian parameter estimation of stochastic dynamic load models
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Intensity Modulated Radiation Therapy (IMRT) With Simultaneously Integrated Boost Shortens Treatment Time and Is Noninferior to Conventional Radiation Therapy Followed by Sequential Boost in Adjuvant Breast Cancer Treatment: Results of a Large Randomized Phase III Trial (IMRT-MC2 Trial)
In the modern era, improvements in radiation therapy techniques have paved the way for simultaneous integrated boost irradiation in adjuvant breast radiation therapy after breast conservation surgery. Nevertheless, randomized trials supporting the noninferiority of this treatment to historical standards of care approach are lacking.
New insights in the fractionation of Pinus pinaster wood: sequential autohydrolysis, soda ethanol organosolv and acidic precipitation
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Unsupervised probabilistic models for sequential Electronic Health Records
We develop an unsupervised probabilistic model for heterogeneous Electronic Health Record (EHR) data. Utilizing a mixture model formulation, our approach directly models sequences of arbitrary length, such as medications and laboratory results. This allows for subgrouping and incorporation of the dynamics underlying heterogeneous data types. The model consists of a layered set of latent variables that encode underlying structure in the data. These variables represent subject subgroups at the top layer, and unobserved states for sequences in the second layer. We train this model on episodic data from subjects receiving medical care in the Kaiser Permanente Northern California integrated healthcare delivery system. The resulting properties of the trained model generate novel insight from these complex and multifaceted data. In addition, we show how the model can be used to analyze sequences that contribute to assessment of mortality likelihood.
One-pot ternary sequential reactions for photopatterned gradient multimaterials
Seamless multimaterial construction is a common motif in animal physiology. Such continuous mechanical gradients remain challenging to reproduce in engineered systems, as current resin chemistries typically result in a single fixed set of properties. As an alternative to single-property materials, we introduce a thiol-ene-epoxy-based photothermal reaction scheme that produces multimaterials by altering the polymer microstructure within a single resin. In this system, the photodosage during the first stage of processing dictates the extent of conversion for each subsequent reaction. As a result, our photochemistry can exhibit a diverse range of soft (Young’s modulus, E ~ 400 kPa; elongation, dL/L0 ~ 300%) and stiff (E ~ 1.6 GPa; dL/L 0 ~ 3%) mechanical properties. Furthermore, we pattern photostable and mechanically robust modulus gradients (d[E r, stiff /E r , soft] /dx > 1,000 mm -1 ) that exceed those found in squid beaks and human knee entheses. We demonstrate the ability to build intricate multimaterial architectures including a soft, wearable braille display.
Sequential Shape Heritability during Confined Comminution
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An empirical study of the added value of the sequential learning of model parameters to industrial system health monitoring
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