Complex unit lattice cell for low-emittance storage ring light source

To achieve the true diffraction-limited emittance of a storage ring light source, such as ~10 pm.rad for medium-energy electron beams, within a limited circumference, it is generally necessary to increase the number of bending magnets in a multi-bend achromat (MBA) lattice, as in the future upgrade plan of MAX IV with a 19BA replacing the current 7BA. However, this comes with extremely strong quadrupole and sextupole magnets and very limited space. The former can result in very small vacuum chambers, increasing the coupling impedance and thus enhancing the beam instabilities, and the latter can pose significant challenges in accommodating the necessary diagnostics and vacuum components. Inspired by the hybrid MBA lattice concept, in this paper we propose a new unit lattice concept called the complex unit lattice cell, which can reduce the magnet strengths and also save space. The complex unit cell is numerically studied using a simplified model. Then as an example, a 17BA lattice based on the complex unit cell concept is designed for a 3 GeV storage ring light source with a circumference of 537.6 m, which has a natural emittance of 19.3 pm.rad. This 17BA lattice is also compared with the 17BA lattice designed with conventional unit cells to showcase the benefits of the complex unit cell concept. This 17BA lattice also suggests a new type of MBA lattice, which we call the MBA lattice with semi-distributed chromatic correction

Minimizing the fluctuation of resonance driving terms in dynamic aperture optimization

Dynamic aperture (DA) is an important nonlinear property of a storage ring lattice, which has a dominant effect on beam injection efficiency and beam lifetime. Generally, minimizing both resonance driving terms (RDTs) and amplitude dependent tune shifts is an essential condition for enlarging the DA. In this paper, we study the correlation between the fluctuation of RDTs along the ring and the DA area with double- and multi-bend achromat lattices. It is found that minimizing the RDT fluctuations is more effective than minimizing RDTs themselves in enlarging the DA, and thus can serve as a very powerful indicator in the DA optimization. Besides, it is found that minimizing lower-order RDT fluctuations can also reduce higher-order RDTs, which are not only more computationally complicated but also more numerous. The effectiveness of controlling the RDT fluctuations in enlarging the DA confirms that the local cancellation of nonlinear effects used in some diffraction-limited storage ring lattices is more effective than the global cancellation

EMITTANCE OPTIMIZATION USING PARTICLE SWARM ALGORITHM*

Abstract In this paper we use a swarm intelligence algorithm, Particle Swarm Optimization (PSO), to optimize the emittance directly. Some constraint conditions such as beta functions, fractional tunes and dispersion function, are considered in the emittance optimization. We optimize the strengths of quadrupoles to search for low emittances. Here an FBA lattice studied in the design of the Hefei Advanced Light Source storage ring is used as the test lattice. The PSO is shown to be beneficial in the optimization

Frequent mutation of receptor protein tyrosine phosphatases provides a mechanism for STAT3 hyperactivation in head and neck cancer

The underpinnings of STAT3 hyperphosphorylation resulting in enhanced signaling and cancer progression are incompletely understood. Loss-of-function mutations of enzymes that dephosphorylate STAT3, such as receptor protein tyrosine phosphatases, which are encoded by the PTPR gene family, represent a plausible mechanism of STAT3 hyperactivation. We analyzed whole exome sequencing (n = 374) and reverse-phase protein array data (n = 212) from head and neck squamous cell carcinomas (HNSCCs). PTPR mutations are most common and are associated with significantly increased phospho-STAT3 expression in HNSCC tumors. Expression of receptor-like protein tyrosine phosphatase T (PTPRT) mutant proteins induces STAT3 phosphorylation and cell survival, consistent with a “driver” phenotype. Computational modeling reveals functional consequences of PTPRT mutations on phospho-tyrosine–substrate interactions. A high mutation rate (30%) of PTPRs was found in HNSCC and 14 other solid tumors, suggesting that PTPR alterations, in particular PTPRT mutations, may define a subset of patients where STAT3 pathway inhibitors hold particular promise as effective therapeutic agents.Fil: Lui, Vivian Wai Yan. University of Pittsburgh; Estados UnidosFil: Peyser, Noah D.. University of Pittsburgh; Estados UnidosFil: Ng, Patrick Kwok-Shing. University Of Texas Md Anderson Cancer Center;Fil: Hritz, Jozef. University of Pittsburgh at Johnstown; Estados Unidos. University of Pittsburgh; Estados Unidos. Masaryk University; República ChecaFil: Zeng, Yan. University of Pittsburgh at Johnstown; Estados Unidos. University of Pittsburgh; Estados UnidosFil: Lu, Yiling. University Of Texas Md Anderson Cancer Center;Fil: Li, Hua. University of Pittsburgh; Estados Unidos. University of Pittsburgh at Johnstown; Estados UnidosFil: Wang, Lin. University of Pittsburgh; Estados Unidos. University of Pittsburgh at Johnstown; Estados UnidosFil: Gilbert, Breean R.. University of Pittsburgh; Estados Unidos. University of Pittsburgh at Johnstown; Estados UnidosFil: General, Ignacio. University of Pittsburgh; Estados Unidos. University of Pittsburgh at Johnstown; Estados UnidosFil: Bahar, Ivet. University of Pittsburgh at Johnstown; Estados Unidos. University of Pittsburgh; Estados UnidosFil: Ju, Zhenlin. University Of Texas Md Anderson Cancer Center;Fil: Wang, Zhenghe. Case Western Reserve University; Estados UnidosFil: Pendleton, Kelsey P.. University of Pittsburgh; Estados Unidos. University of Pittsburgh at Johnstown; Estados UnidosFil: Xiao, Xiao. University of Pittsburgh at Johnstown; Estados Unidos. University of Pittsburgh; Estados UnidosFil: Du, Yu. University of Pittsburgh at Johnstown; Estados Unidos. University of Pittsburgh; Estados UnidosFil: Vries, John K.. University of Pittsburgh; Estados Unidos. University of Pittsburgh at Johnstown; Estados UnidosFil: Hammerman, Peter S.. Harvard Medical School; Estados UnidosFil: Garraway, Levi A.. Harvard Medical School; Estados UnidosFil: Mills, Gordon B.. University Of Texas Md Anderson Cancer Center;Fil: Johnson, Daniel E.. University of Pittsburgh at Johnstown; Estados Unidos. University of Pittsburgh; Estados UnidosFil: Grandis, Jennifer R.. University of Pittsburgh; Estados Unidos. University of Pittsburgh at Johnstown; Estados Unido

Studying bubble-particle interactions by zeta potential distribution analysis

Over a decade ago, Xu and Masliyah pioneered an approach to characterize the interactions between particles in dynamic environments of multicomponent systems by measuring zeta potential distributions of individual components and their mixtures. Using a Zetaphoremeter, the measured zeta potential distributions of individual components and their mixtures were used to determine the conditions of preferential attachment in multicomponent particle suspensions. The technique has been applied to study the attachment of nano-sized silica and alumina particles to sub-micron size bubbles in solutions with and without the addition of surface active agents (SDS, DAH and DF250). The degree of attachment between gas bubbles and particles is shown to be a function of the interaction energy governed by the dispersion, electrostatic double layer and hydrophobic forces. Under certain chemical conditions, the attachment of nano-particles to sub-micron size bubbles is shown to be enhanced by in-situ gas nucleation induced by hydrodynamic cavitation for the weakly interacting systems, where mixing of the two individual components results in negligible attachment. Preferential interaction in complex tertiary particle systems demonstrated strong attachment between micron-sized alumina and gas bubbles, with little attachment between micron-sized alumina and silica, possibly due to instability of the aggregates in the shear flow environment

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Dewetting Dynamics of a Solid Microsphere by Emulsion Drops

A novel micropipet technique was developed to quantify the dewetting dynamics of individual microsphere particles by emulsified viscous crude oil drops in aqueous media. This technique allowed dynamic microscale receding contact angles of water to be measured in situ for solid–oil–water systems. System parameters, including modification of glass microspheres and characteristics of oil drops, were varied to study their effect on dewetting dynamics of the systems. Increasing solvent dosage in viscous oil was found to decrease static receding contact angle of water for clean and bitumen-treated glass surfaces, but showed a negligible effect on static receding contact angle for ethyl cellulose (EC)-treated glass surface. Interestingly, dynamic dewetting behavior exhibited a strong dependence on surface modification and the addition of solvent to viscous oil. No dewetting dynamics was observed for clean hydrophilic glass surface. For bitumen- or EC-treated glass surfaces, more rapid dewetting dynamics of water were determined with increasing addition of solvent to viscous oil. Both de Gennes viscous dissipation hydrodynamic and the Blake/Haynes molecular-kinetic models were developed for the current system to understand the observed dynamic dewetting characteristics

Matrix‐glycoprotein interactions required for budding of a plant nucleorhabdovirus and induction of inner nuclear membrane invagination

Nucleorhabdoviruses such as Sonchus yellow net virus (SYNV) replicate in the nuclei and undergo morphogenesis at the inner nuclear membrane (IM) in plant cells. Mature particles are presumed to form by budding of the Matrix (M) protein-nucleocapsid complexes through host IMs to acquire host phospholipids and the surface glycoproteins (G). To address mechanisms underlying nucleorhabdovirus budding, we generated recombinant SYNV G mutants containing a truncated amino-terminal (NT) or carboxyl-terminal (CT) domain. Electron microscopy and sucrose gradient centrifugation analyses showed that the CT domain is essential for virion morphogenesis whereas the NT domain is also required for efficient budding. SYNV infection induces IM invaginations that are thought to provide membrane sites for virus budding. We found that in the context of viral infections, interactions of the M protein with the CT domain of the membrane-anchored G protein mediate M protein translocation and IM invagination. Interestingly, tethering the M protein to endomembranes, either by co-expression with a transmembrane G protein CT domain or by artificial fusion with the G protein membrane targeting sequence, induces IM invagination in uninfected cells. Further evidence to support functions of G-M interactions in virus budding came from dominant negative effects on SYNV-induced IM invagination and viral infections that were elicited by expression of a soluble version of the G protein CT domain. Based on these data, we propose that cooperative G-M interactions promote efficient SYNV budding

De Novo Sequencing of a Sparassis latifolia Genome and Its Associated Comparative Analyses

Known to be rich in β-glucan, Sparassis latifolia (S. latifolia) is a valuable edible fungus cultivated in East Asia. A few studies have suggested that S. latifolia is effective on antidiabetic, antihypertension, antitumor, and antiallergen medications. However, it is still unclear genetically why the fungus has these medical effects, which has become a key bottleneck for its further applications. To provide a better understanding of this fungus, we sequenced its whole genome, which has a total size of 48.13 megabases (Mb) and contains 12,471 predicted gene models. We then performed comparative and phylogenetic analyses, which indicate that S. latifolia is closely related to a few species in the antrodia clade including Fomitopsis pinicola, Wolfiporia cocos, Postia placenta, and Antrodia sinuosa. Finally, we annotated the predicted genes. Interestingly, the S. latifolia genome encodes most enzymes involved in carbohydrate and glycoconjugate metabolism and is also enriched in genes encoding enzymes critical to secondary metabolite biosynthesis and involved in indole, terpene, and type I polyketide pathways. As a conclusion, the genome content of S. latifolia sheds light on its genetic basis of the reported medicinal properties and could also be used as a reference genome for comparative studies on fungi