The crystallization problem is an outstanding challenge in the chemistry of porous covalent organic frameworks (COFs). Their structural characterization has been limited to modeling and solutions based on powder x-ray or electron diffraction data. Single crystals of COFs amenable to x-ray diffraction characterization have not been reported. Here, we developed a general procedure to grow large single crystals of three-dimensional imine-based COFs (COF-300, hydrated form of COF-300, COF-303, LZU-79, and LZU-111). The high quality of the crystals allowed collection of single-crystal x-ray diffraction data of up to 0.83-angstrom resolution, leading to unambiguous solution and precise anisotropic refinement. Characteristics such as degree of interpenetration, arrangement of water guests, the reversed imine connectivity, linker disorder, and uncommon topology were deciphered with atomic precision-aspects impossible to determine without single crystals.

Genome‐, transcriptome‐ and proteome‐wide measurements provide insights into how biological systems are regulated. However, fundamental aspects relating to which human proteins exist, where they are expressed and in which quantities are not fully understood. Therefore, we generated a quantitative proteome and transcriptome abundance atlas of 29 paired healthy human tissues from the Human Protein Atlas project representing human genes by 18,072 transcripts and 13,640 proteins including 37 without prior protein‐level evidence. The analysis revealed that hundreds of proteins, particularly in testis, could not be detected even for highly expressed mRNA s, that few proteins show tissue‐specific expression, that strong differences between mRNA and protein quantities within and across tissues exist and that protein expression is often more stable across tissues than that of transcripts. Only 238 of 9,848 amino acid variants found by exome sequencing could be confidently detected at the protein level showing that proteogenomics remains challenging, needs better computational methods and requires rigorous validation. Many uses of this resource can be envisaged including the study of gene/protein expression regulation and biomarker specificity evaluation.

Genome-, transcriptome- and proteome-wide measurements provide valuable insights into how biological systems are regulated. However, even fundamental aspects relating to which human proteins exist, where they are expressed and in which quantities are not fully understood. Therefore, we have generated a systematic, quantitative and deep proteome and transcriptome abundance atlas from 29 paired healthy human tissues from the Human Protein Atlas Project and representing human genes by 17,615 transcripts and 13,664 proteins. The analysis revealed that few proteins show truly tissue-specific expression, that vast differences between mRNA and protein quantities within and across tissues exist and that the expression levels of proteins are often more stable across tissues than those of transcripts. In addition, only ~2% of all exome and ~7% of all mRNA variants could be confidently detected at the protein level showing that proteogenomics remains challenging, requires rigorous validation using synthetic peptides and needs more sophisticated computational methods. Many uses of this resource can be envisaged ranging from the study of gene/protein expression regulation to protein biomarker specificity evaluation to name a few.

The transcription factor EGR1 is a tumor suppressor gene that is downregulated in many cancer types. Clinically, loss of EGR1 translates to increased tumor transformation and subsequent patient morbidity and mortality. In synovial sarcoma, the SS18-SSX fusion protein represses EGR1 expression through a direct association with the EGR1 promoter. However, the mechanism through which EGR1 becomes downregulated in other tumor types is unclear. Here, we report that EGR1 is regulated by microRNA (miR)-183 in multiple tumor types including synovial sarcoma, rhabdomyosarcoma (RMS), and colon cancer. Using an integrative network analysis, we identified that miR-183 is significantly overexpressed in these tumor types as well as in corresponding tumor cell lines. Bioinformatic analyses suggested that miR-183 could target EGR1 mRNA and this specific interaction was validated in vitro. miR-183 knockdown in synovial sarcoma, RMS, and colon cancer cell lines revealed deregulation of a miRNA network composed of miR-183-EGR1-PTEN in these tumors. Integrated miRNA-and mRNA-based genomic analyses indicated that miR-183 is an important contributor to cell migration in these tumor types and this result was functionally validated to be occurring via an EGR1-based mechanism. In conclusion, our findings have significant implications in the mechanisms underlying EGR1 regulation in cancers. miR-183 has a potential oncogenic role through the regulation of 2 tumor suppressor genes, EGR1 and PTEN, and the deregulation of this fundamental miRNA regulatory network may be central to many tumor types. Cancer Res; 70(23); 9570-80. Ó2010 AACR.

A supramolecular hydrogel based on D-amino acids, which resists hydrolysis catalyzed by proteinase K and offers long-term biostability, exhibits controlled release in vivo, as proved by the pharmacokinetics of encapsulated 125I tracers and the SPECT imaging of the hydrogel-encapsulated 131I tracers. As the first in vivo imaging investigation of the drug release properties of the supramolecular hydrogel, isotope encapsulation serves as a valid, useful assay for characterizing the controlled release properties of supramolecular hydrogels in vivo. Our results indicate that supramolecular hydrogels promise new biomaterials for controlled drug release.

This paper presents observations of deep convection characteristics in the tropics and subtropics that have been classified into four categories: tropical cyclone, oceanic, land, and sea breeze. Vertical velocities in the convection were derived from Doppler radar measurements collected during several NASA field experiments from the nadir-viewing high-altitude ER-2 Doppler radar (EDOP). Emphasis is placed on the vertical structure of the convection from the surface to cloud top (sometimes reaching 18-km altitude). This unique look at convection is not possible from other approaches such as ground-based or lower-altitude airborne scanning radars. The vertical motions from the radar measurements are derived using new relationships between radar reflectivity and hydrometeor fall speed. Various convective properties, such as the peak updraft and downdraft velocities and their corresponding altitude, heights of reflectivity levels, and widths of reflectivity cores, are estimated. The most significant findings are the following: 1) strong updrafts that mostly exceed 15 m s 21 , with a few exceeding 30 m s 21 , are found in all the deep convection cases, whether over land or ocean; 2) peak updrafts were almost always above the 10-km level and, in the case of tropical cyclones, were closer to the 12-km level; and 3) land-based and sea-breeze convection had higher reflectivities and wider convective cores than oceanic and tropical cyclone convection. In addition, the high-resolution EDOP data were used to examine the connection between reflectivity and vertical velocity, for which only weak linear relationships were found. The results are discussed in terms of dynamical and microphysical implications for numerical models and future remote sensors.

MotivationAnnotation of enzyme function has a broad range of applications, such as metagenomics, industrial biotechnology, and diagnosis of enzyme deficiency-caused diseases. However, the time and resource required make it prohibitively expensive to experimentally determine the function of every enzyme. Therefore, computational enzyme function prediction has become increasingly important. In this paper, we develop such an approach, determining the enzyme function by predicting the Enzyme Commission number.ResultsWe propose an end-to-end feature selection and classification model training approach, as well as an automatic and robust feature dimensionality uniformization method, DEEPre, in the field of enzyme function prediction. Instead of extracting manually crafted features from enzyme sequences, our model takes the raw sequence encoding as inputs, extracting convolutional and sequential features from the raw encoding based on the classification result to directly improve the prediction performance. The thorough cross-fold validation experiments conducted on two large-scale datasets show that DEEPre improves the prediction performance over the previous state-of-the-art methods. In addition, our server outperforms five other servers in determining the main class of enzymes on a separate low-homology dataset. Two case studies demonstrate DEEPre’s ability to capture the functional difference of enzyme isoforms.Availability and implementationThe server could be accessed freely at http://www.cbrc.kaust.edu.sa/DEEPre.Supplementary information Supplementary data are available at Bioinformatics online.

Monolayer graphene exhibits extraordinary properties owing to the unique, regular arrangement of atoms in it. However, graphene is usually modified for specific applications, which introduces disorder. This article presents details of graphene structure, including sp2 hybridization, critical parameters of the unit cell, formation of σ and π bonds, electronic band structure, edge orientations, and the number and stacking order of graphene layers. We also discuss topics related to the creation and configuration of disorders in graphene, such as corrugations, topological defects, vacancies, adatoms and sp3-defects. The effects of these disorders on the electrical, thermal, chemical and mechanical properties of graphene are analyzed subsequently. Finally, we review previous work on the modulation of structural defects in graphene for specific applications.