Higher-order interactions of Bcr-Abl can broaden chronic myeloid leukemia (CML) drug repertoire

Bcr-Abl, a nonreceptor tyrosine kinase, is associated with leukemias, especially chronic myeloid leukemia (CML). Deletion of Abl's N-terminal region, to which myristoyl is linked, renders the Bcr-Abl fusion oncoprotein constitutively active. The substitution of Abl's N-terminal region by Bcr enables Bcr-Abl oligomerization. Oligomerization is critical: it promotes clustering on the membrane, which is essential for potent MAPK signaling and cell proliferation. Here we decipher the Bcr-Abl specific, step-by-step oligomerization process, identify a specific packing surface, determine exactly how the process is structured and identify its key elements. Bcr's coiled coil (CC) domain at the N-terminal controls Bcr-Abl oligomerization. Crystallography validated oligomerization via Bcr-Abl dimerization between two Bcr CC domains, with tetramerization via tight packing between two binary assemblies. However, the structural principles guiding Bcr CC domain oligomerization are unknown, hindering mechanistic understanding and drugs exploiting it. Using molecular dynamics (MD) simulations, we determine that the binary complex of the Bcr CC domain serves as a basic unit in the quaternary complex providing a specific surface for dimer–dimer packing and higher-order oligomerization. We discover that the small α1-helix is the key. In the binary assembly, the helix forms interchain aromatic dimeric packing, and in the quaternary assembly, it contributes to the specific dimer–dimer packing. Our mechanism is supported by the experimental literature. It offers the key elements controlling this process which can expand the drug discovery strategy, including by Bcr CC-derived peptides, and candidate residues for small covalent drugs, toward quenching oligomerization, supplementing competitive and allosteric tyrosine kinase inhibitors.     

Semiparametric estimation of the transformation model by leveraging external aggregate data in the presence of population heterogeneity

Leveraging information in aggregate data from external sources to improve estimation efficiency and prediction accuracy with smaller scale studies has drawn a great deal of attention in recent years. Yet, conventional methods often either ignore uncertainty in the external information or fail to account for the heterogeneity between internal and external studies. This article proposes an empirical likelihood-based framework to improve the estimation of the semiparametric transformation models by incorporating information about the t-year subgroup survival probability from external sources. The proposed estimation procedure incorporates an additional likelihood component to account for uncertainty in the external information and employs a density ratio model to characterize population heterogeneity. We establish the consistency and asymptotic normality of the proposed estimator and show that it is more efficient than the conventional pseudopartial likelihood estimator without combining information. Simulation studies show that the proposed estimator yields little bias and outperforms the conventional approach even in the presence of information uncertainty and heterogeneity. The proposed methodologies are illustrated with an analysis of a pancreatic cancer study.     

Integrating sample similarities into latent class analysis: a tree-structured shrinkage approach

This paper is concerned with using multivariate binary observations to estimate the probabilities of unobserved classes with scientific meanings. We focus on the setting where additional information about sample similarities is available and represented by a rooted weighted tree. Every leaf in the given tree contains multiple samples. Shorter distances over the tree between the leaves indicate a priori higher similarity in class probability vectors. We propose a novel data integrative extension to classical latent class models with tree-structured shrinkage. The proposed approach enables (1) borrowing of information across leaves, (2) estimating data-driven leaf groups with distinct vectors of class probabilities, and (3) individual-level probabilistic class assignment given the observed multivariate binary measurements. We derive and implement a scalable posterior inference algorithm in a variational Bayes framework. Extensive simulations show more accurate estimation of class probabilities than alternatives that suboptimally use the additional sample similarity information. A zoonotic infectious disease application is used to illustrate the proposed approach. The paper concludes by a brief discussion on model limitations and extensions.     

Extraction,Antioxidant Activity and Identification of Flavonoids from Root Tubers of <i>Kosteletzkya virginica</i>

Kosteletzkya virginica (K. virginica) is used for revegetation of salt-affected coastal tidal flats and as a raw material of biodiesel. K. virginica root tuber, a biowaste with low economic value, is rich in bioactive compounds. This study aimed to extract and identify flavonoids from K. virginica root tubers. The optimal extraction conditions were 1/25 (w/v) solid/liquid ratio, 40% ethanol concentration at 40°C for 60 min. Under these conditions, 65.2 ± 3.7 mg/g total flavonoid content was extracted from the roots, which were collected from salinized soil in late autumn of the third year. Antioxidant activity was evaluated through 1,1-diphenyl-2-picrylhydrazyl, hydroxyl radical, and superoxide anion scavenging assays. The extracted flavonoids exhibited antioxidant activity in a dose-dependent manner. Five flavonoids, glucoliquiritin apioside, licoisoflavone B, 5-methoxy-7,8-diprenyl- flavone, 7,2′-dihydroxy-6,8-dimethyl-4′,5′-methylenedioxyflavan, and 5,7,4′-trihydroxy-3′-methoxy-6,8-di-Cmethylflavanone, were identified by ultra-performance liquid chromatography–tandem mass spectrometry. Our results suggest that the flavonoids of K. virginica root tubers might be potent antioxidants and can be effectively applied as an ingredient in food and natural medicine.     

Genome constitutions of Thinopyrum curvifolium, T. scirpeum, T. distichum, and T. junceum (Triticeae: Gramineae).

The objective of this study is to elucidate genome constitutions of Thinopyrum curvifolium (Lange) D.R. Dewey, T. scirpeum (K. Presl) D.R. Dewey, T. distichum (Thunb.) A. L?ve, and T. junceum (L.) A. L?ve. Hybrids of T. sartorii (Boiss. &Heidr.) A. L?ve with T. scirpeum and T. junceum, as well as the hybrid between T. curvifolium and Pseudoroegneria geniculata ssp. scythica (Nevski) A. L?ve, were made and chromosome pairing at metaphase I was studied. The karyotype analyses of mitotic cells stained by aceto-orcein were conducted for both hybrids and the four target species. The Giemsa C-banding following acetocarmine staining was carried out for the above species and the triploid hybrid T. curvifolium x T. bessarabicum (Savul &Rayss) A. L?ve. Meiotic data indicate that all target species have two sets of the basic genome J, but they behave like true allopolyploids because of bivalentization. Karyotypes of T. curvifolium and its triploid hybrid with T. bessarabicum indicate that T. curvifolium contains two different versions of the Jb genome, designated as Jb3 and Jb4, rather than two Je genomes as previously believed. Thinopyrum scirpeum and T. elongatum (4x) have similar karyotypes. Both are segmental allotetraploids carrying two forms of the Je genome. Their genome formulae are Je2 Je3 and Je1 Je3, respectively. Thinopyrum distichum has a karyotype similar to T. junceiforme, which has the Jb2 Je2 genome formula. However, the two species differ in C-banding patterns, reflecting their geographical separation. Thinopyrum junceum is a hexaploid with two pairs of Jb2 genomes and one pair of the Je2 genome, and it has a C-banding pattern similar to that of T. junceiforme, which has one pair each of the Jb2 and Je2 genomes.     

Sub-Cellular Distribution of Zinc in Different Vegetative Organs and Their Contribution to Grains Zinc Accumulation in Rice Under Different Nitrogen and Zinc Supply

Journal of Plant Growth Regulation - Zinc is an important micronutrient for the growth and development of human body and plants. Proper use of nitrogen fertilizer and foliar application of Zn have...     

Regulation of Nitrogen Metabolism,Photosynthetic Activity,and Yield Attributes of Spring Wheat by Nitrogen Fertilizer in the Semi-arid Loess Plateau Region

It is critical for spring wheat (Triticum aestivum L.) production in the semi-arid Loess Plateau to understand the impact of nitrogen (N) fertilizer on changes in N metabolism, photosynthetic parameters, and their relationship with grain yield and quality. The photosynthetic capacity of flag leaves, dry matter accumulation, and N metabolite enzyme activities from anthesis to maturity were studied on a long-term fertilization trial under different N rates [0 kg ha^?1(N1), 52.5 kg ha^?1 (N2), 105 kg ha^?1 (N3), 157.5 kg ha^?1 (N4), and 210 kg ha^?1 (N5)]. It was observed that N3 produced optimum total dry matter (5407 kg ha^?1), 1000 grain weight (39.7 g), grain yield (2.64 t ha^?1), and protein content (13.97%). Our results showed that N fertilization significantly increased photosynthetic parameters and N metabolite enzymes at all growth stages. Nitrogen harvest index, partial productivity factor, agronomic recovery efficiency, and nitrogen agronomic efficiency were decreased with increased N. Higher N rates (N3–N5) maintained higher photosynthetic capacity and dry matter accumulation and lower intercellular CO₂ content. The N supply influenced NUE by improving photosynthetic properties. The N3 produced highest chlorophyll content, photosynthetic rate, stomatal conductance and transpiration rate, grain yield, grain protein, dry matter, grains weight, and N metabolite enzyme activities compared to the other rates (N1, N2, N4, and N5). Therefore, increasing N rates beyond the optimum quantity only promotes vegetative development and results in lower yields.

     

Fulvic Acid,Brassinolide, and Uniconazole Mediated Regulation of Morphological and Physiological Traits in Maize Seedlings Under Water Stress

Water stress is one of the most important factors limiting sustainable crop production. Therefore, the effects of the plant growth regulators (PGRs) fulvic acid (FA), brassinolide (BR), and uniconazole (Uni) on seedling growth and physiology of two maize (Zea mays L.) varieties were evaluated under???0.7 MPa water stress induced by polyethylene glycol-6000. Under drought stress, the PGRs promoted seedling growth, altered the root-to-shoot ratio, and significantly increased root biomass, length, surface area, diameter, and volume. In addition, depending on the PGR, net photosynthesis rate, SPAD value (indicating chlorophyll content), and water use efficiency increased significantly, under drought stress, whereas transpiration rate decreased. The PGRs also significantly increased antioxidant enzyme activities and significantly decreased malondialdehyde accumulation in leaves and roots under drought stress. Zhengdan958 showed greater variation in physiological responses and stronger drought resistance than Xundan20. In alleviating drought stress in maize seedlings, FA had the greatest effects on shoot growth and leaf physiology; Uni exerted its effects by regulating root structure, and BR effects were intermediate. Under drought stress, the three PGRs increased maize seedling growth, which reduced drought stress-induced damage and improved plant ability to resist the adversity. Based on a comprehensive analysis of physiological indices of drought resistance, Uni is recommended as the best PGR to improve maize seedlings resistance to drought.

     

乌云伞的解剖学及花粉形态学研究

八角莲属(Dysosma)是小檗科(Berberidaceae)一个重要属,全国共有7个种,大约分布于北纬23—32°,东经94—122°之间。湖北八角莲属有4个种,其中乌云伞(Dysosma lichuanensis Z. Cheng, sp. nev., ined.)为内定种,是多年生草本,它的形态特征与八角莲(Dysosma