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provides coniferyl ferulate(CAS#:51803-68-0) MSDS, density, melting point, boiling point, structure, formula, molecular weight etc. Articles of coniferyl ferulate are included as well.>> amp version: coniferyl ferulate
The Mongolian gerbil (Meriones unguiculatus) has historically been used as a model organism for the auditory and visual systems, stroke/ischemia, epilepsy and aging related research since 1935 when laboratory gerbils were separated from their wild counterparts. In this study we report genome sequencing, assembly, and annotation further supported by transcriptome sequencing and assembly from 27 different tissues samples.
The genome was sequenced using Illumina HiSeq 2000 and after assembly resulted in a final genome size of 2.54 Gbp with contig and scaffold N50 values of 31.4 Kbp and 500.0 Kbp, respectively. Based on the k-mer estimated genome size of 2.48 Gbp, the assembly appears to be complete. The genome annotation was supported by transcriptome data that identified 31,769 (> 2000 bp) predicted protein-coding genes across 27 tissue samples. A BUSCO search of 3023 mammalian groups resulted in 86% of curated single copy orthologs present among predicted genes, indicating a high level of completeness of the genome.
We report the first de novo assembly of the Mongolian gerbil genome enhanced by assembly of transcriptome data from several tissues. Sequencing of this genome and transcriptome increases the utility of the gerbil as a model organism, opening the availability of now widely used genetic tools.
Gerbil genome, Meriones unguiculatus, Transcriptome, Model organism
Enhancement of de novo sequencing, assembly and annotation of the Mongolian gerbil genome with transcriptome sequencing and assembly from several different tissues
Shifeng Cheng,#1,2 Yuan Fu,#1,3 Yaolei Zhang,1,3 Wenfei Xian,1,2 Hongli Wang,1,3 Benedikt Grothe,4 Xin Liu,1,3 Xun Xu,1,3 Achim Klug,5 and Elizabeth A. McCullaghcorresponding author5,6
In the title complex, [CuCl2(C24H24N2O2)], the CuII cation is N,N′,O-chelated by a 2,2′-(1,1′-binaphthyl-2,2′-diyldiimino)diethanol ligand and coordinated by two chloride anions in a distorted square-pyramidal geometry. In the diethanol ligand, the two naphthalene ring systems are twisted with respect to each other at a dihedral angle of 68.30 (9)°. The uncoordinated hydroxy group links with a coordinated chloride anion via an intramolecular O—H⋯Cl hydrogen bond. Intermolecular N—H⋯O and N—H⋯Cl hydrogen bonds occur in the crystal structure.
Wan-Yun Huang,a Dong-Cheng Liu,a Han-Chang Wei,a and Fu-Pei Lianga,*
2011 Dec 1;
To assess the ability of the patient main problem to predict acuity in adults admitted to hospital wards and step‐down units.
Acuity refers to the categorization of patients based on their required nursing intensity. The relationship between acuity and nurses’ clinical judgment on the patient problems, including their prioritization, is an underexplored issue.
Cross‐sectional, multi‐centre study in a sample of 200,000 adults. Multivariate analysis of main problems potentially associated with acuity levels higher than acute was performed. Distribution of patients and outcome differences among acuity clusters were evaluated.
The main problems identified are strongly associated with patient acuity. The model exhibits remarkable ability to predict acuity (AUC, 0.814; 95% CI, 0.81-0.816). Most patients (64.8%) match higher than acute categories. Significant differences in terms of mortality, hospital readmission and other outcomes are observed (p < .005). Conclusion The patient main problem predicts acuity. Most inpatients require more intensive than acute nursing care and their outcomes are adversely affected. Implications for nursing management Prospective measurement of acuity, considering nurses' clinical judgments on the patient main problem, is feasible and may contribute to support nurse management workforce planning and staffing decision‐making, and to optimize patients, nurses and organizational outcomes.
acuity, clinical judgment, nursing intensity, patient classification systems, priority setting
Predicting patient acuity according to their main problem
Maria‐Eulàlia Juve‐Udina, PhD, MSN, BSN, RN,corresponding author 1 , 2 , 3 Jordi Adamuz, PhD, MSN, BSN, RN, 2 , 3 , 4 Maria‐Magdalena Lopez‐Jimenez, BSN, RN, 2 , 3 Marta Tapia‐Perez, BSN, RN, 4 Núria Fabrellas, PhD, MSN, BSN, RN, 3 , 5 Cristina Matud‐Calvo, BSN, RN, 2 , 4 and Maribel Gonzalez‐Samartino, PhD, MSN, BSN, RN 2 , 3 , 4