Molecular cloning of the hydrogen oxidizing genes of Alcaligenes eutrophus strain H1

Hydrogen evolution by the enzyme nitrogenase during nitrogen fixation is considered to cause higher energy requirements for nitrogen fixation. This loss of energy may indirectly inhibit plant growth during symbiotic nitrogen fixation between leguminous plants and Rhizobium. The loss could conceivably be reversed by introduction of a hydrogenase enzyme into hydrogen-evolving Rhizobium to recycle the lost energy. The unique physiological and biochemical characteristics of the hydrogenase system of Alcaligenes eutrophus provides a potential source of hydrogen oxidizing genes for introduction into Rhizobium. The genes for hydrogen oxidation have been identified to be coded on a 200 Mdal plasmid in several A. eutrophus strains. The goal of this study was to map and isolate plasmid-encoded genes involved in hydrogen oxidation in A. eutrophus and also to determine if these hydrogen-oxidizing genes will function in other bacteria;The identification and isolation of hydrogen-oxidizing genes was achieved by Tn5-mutagenesis and genetic complementation by using a total genomic DNA library constructed in a broad-host-range vector. The cloned fragment of DNA carrying the hydrogenase genes was identified, but this fragment alone was not functional in Rhizobium;During the search for the hydrogenase gene clone, several unique phenomena were observed. These include (1) transposition of endogenous insertion element during Tn5 mutagenesis, (2) high frequency of plasmid curing during Tn5 mutagenesis, and (3) a plasmid region that seemed to be highly sensitive to mutagenesis treatment and consequently resulted in plasmid deletion. In addition, the 200 Mdal plasmid also demonstrated a high degree of homology with its chromosomal counterpart

GeneAlign: a coding exon prediction tool based on phylogenetical comparisons

GeneAlign is a coding exon prediction tool for predicting protein coding genes by measuring the homologies between a sequence of a genome and related sequences, which have been annotated, of other genomes. Identifying protein coding genes is one of most important tasks in newly sequenced genomes. With increasing numbers of gene annotations verified by experiments, it is feasible to identify genes in the newly sequenced genomes by comparing to annotated genes of phylogenetically close organisms. GeneAlign applies CORAL, a heuristic linear time alignment tool, to determine if regions flanked by the candidate signals (initiation codon-GT, AG-GT and AG-STOP codon) are similar to annotated coding exons. Employing the conservation of gene structures and sequence homologies between protein coding regions increases the prediction accuracy. GeneAlign was tested on Projector dataset of 491 human–mouse homologous sequence pairs. At the gene level, both the average sensitivity and the average specificity of GeneAlign are 81%, and they are larger than 96% at the exon level. The rates of missing exons and wrong exons are smaller than 1%. GeneAlign is a free tool available at

Improved label noise identification by exploiting unlabeled data

© 2017 IEEE. In machine learning, the available training samples are not always perfect and some labels can be corrupted which are called label noises. This may cause the reduction of accuracy. Meanwhile it will also increase the complexity of model. To mitigate the detrimental effect of label noises, noise filtering has been widely used which tries to identify label noises and remove them prior to learning. Almost all existing works only focus on the mislabeled training dataset and ignore the existence of unlabeled data. In fact, unlabeled data are easily accessible in many applications. In this work, we explore how to utilize these unlabeled data to increase the noise filtering effect. To this end, we have proposed a method named MFUDCM (Multiple Filtering with the aid of Unlabeled Data using Confidence Measurement). This method applies the novel multiple soft majority voting idea to make use unlabeled data. In addition, MFUDCM is expected to have a higher accuracy of identifying mislabeled data by using the concept of multiple voting. Finally, the validity of the proposed method MFUDCM is confirmed by experiments and the comparison results with other methods

Important photosynthetic contribution from the non-foliar green organs in cotton at the late growth stage

Non-foliar green organs are recognized as important carbon sources after leaves. However, the contribution of each organ to total yield has not been comprehensively studied in relation to the time-course of changes in surface area and photosynthetic activity of different organs at different growth stages. We studied the contribution of leaves, main stem, bracts and capsule walls in cotton by measuring their time-course of surface area development, O2 evolution capacity and photosynthetic enzyme activity. Because of the early senescence of leaves, non-foliar organs increased their surface area up to 38.2% of total at late growth stage. Bracts and capsule wall showed less ontogenetic decrease in O2 evolution capacity per area and photosynthetic enzyme activity than leaves at the late growth stage. The total capacity for O2 evolution of stalks and bolls (bracts plus capsule wall) was 12.7% and 23.7% (total ca. 36.4%), respectively, as estimated by m! ultiplying their surface area by their O2 evolution capacity per area. We also kept the bolls (from 15 days after anthesis) or main stem (at the early full bolling stage) in darkness for comparison with non-darkened controls. Darkening the bolls and main stem reduced the boll weight by 24.1% and 9%, respectively, and the seed weight by 35.9% and 16.3%, respectively. We conclude that non-foliar organs significantly contribute to the yield at the late growth stage

Anti–SARS-CoV Immunoglobulin G in Healthcare Workers, Guangzhou, China

Low level of immunity for SARS-CoV among well healthcare workers reinforces the need for infection control measures in hospitals to prevent epidemics

Transcriptional activation of the Axl and PDGFR-α by c-Met through a ras- and Src-independent mechanism in human bladder cancer

<p>Abstract</p> <p>Background</p> <p>A cross-talk between different receptor tyrosine kinases (RTKs) plays an important role in the pathogenesis of human cancers.</p> <p>Methods</p> <p>Both NIH-Met5 and T24-Met3 cell lines harboring an inducible human c-Met gene were established. C-Met-related RTKs were screened by RTK microarray analysis. The cross-talk of RTKs was demonstrated by Western blotting and confirmed by small interfering RNA (siRNA) silencing, followed by elucidation of the underlying mechanism. The impact of this cross-talk on biological function was demonstrated by Trans-well migration assay. Finally, the potential clinical importance was examined in a cohort of 65 cases of locally advanced and metastatic bladder cancer patients.</p> <p>Results</p> <p>A positive association of Axl or platelet-derived growth factor receptor-alpha (PDGFR-α) with c-Met expression was demonstrated at translational level, and confirmed by specific siRNA knock-down. The transactivation of c-Met on Axl or PDGFR-α <it>in vitro </it>was through a <it>ras</it>- and Src-independent activation of mitogen-activated protein kinase/extracellular signal-regulated kinase (MEK/ERK) pathway. In human bladder cancer, co-expression of these RTKs was associated with poor patient survival (<it>p </it>< 0.05), and overexpression of c-Met/Axl/PDGFR-α or c-Met alone showed the most significant correlation with poor survival (<it>p </it>< 0.01).</p> <p>Conclusions</p> <p>In addition to c-Met, the cross-talk with Axl and/or PDGFR-α also contributes to the progression of human bladder cancer. Evaluation of Axl and PDGFR-α expression status may identify a subset of c-Met-positive bladder cancer patients who may require co-targeting therapy.</p