Non-pathogenic Staphylococcus strains augmented the maize growth through oxidative stress management and nutrient supply under induced salt stress

The present study was conducted to elucidate the role of phytobeneficial bacteria to control the cellular oxidative damage in maize (Zea mays L.) plants caused by salinity. Bacteria were isolated from the rhizosphere of kallar grass (Leptochloa fusca L.) through serial dilution method and taxonomically identified on the basis of their 16S ribosomal RNA gene sequencing. In vitro phosphate solubilization, indole-3-acetic acid (IAA) synthesis, and 1-aminocyclopropane-1-carboxylic acid (ACC) deaminase activity were evaluated by solubilization index measurement, colorimetric method, and turbidity assay, respectively. In the pot experiment, the impact of single and mixed inoculation of these strains at four levels (0, 50, 100, and 200 mM) of salt stress was evaluated in terms of growth and physiological response of maize plants to salinity. The bacterial strains (STN-1, STN-5, and STN-14) were taxonomically classified as Staphylococcus spp. At 5% NaCl level, the strains demonstrated substantial potential for phosphate solubilization, ACC deaminase activity, and IAA production both with and without tryptophan. The inoculation of strains STN-1, STN-5, and mixed inoculation resulted in substantial growth improvement of maize plants along with increased antioxidant enzyme activity and decreased levels of reactive oxygen species. In addition, single inoculation of STN-1 and STN-5 along with mixed inoculation augmented the uptake of N, P, K, and Ca+2 and reduced Na+ uptake. Current results demonstrated that the strains STN-1 and STN-5 modulated stress-responsive mechanisms and regulated ion balance in induced salinity to promote maize growth.     

Assessments of 226Ra and 222Rn concentration in well and tap water from Sik,Malaysia, and consequent dose estimates

Abstract

The ingestion of ²²⁶Ra, inhalation, and ingestion of ²²²Rn in water is considered the primary health risk for lungs and stomach. This study presents the concentrations of ²²⁶Ra and ²²²Rn in well and tap water collected from Sik, Malaysia, using HPGe and RAD7 detectors. Maximum average concentrations of ²²⁶Ra and ²²²Rn were found 47.6?±?3.6 mBq/l and 9.3?±?1.4?Bq/l in well water, respectively, and minimum were found 17.1?±?3.6 mBq/l and 1.6?±?1.0?Bq/l in tap water, respectively. A positive correlation (R=.88) was found between ²²⁶Ra and ²²²Rn determined by HPGe and RAD7 detectors, respectively. Infants in the age group of 0–1 y appeared to be at risk with respect to the annual effective doses from ²²⁶Ra and ²²²Rn as compared to the other age groups. However, annual effective doses for all three age groups from intake of ²²⁶Ra and ²²²Rn in well and tap drinking water were found below the World Health Organization (WHO) recommended level of .1 mSv/y_.     

Blockchain based secure,efficient and coordinated energy trading and data sharing between electric vehicles

Cluster Computing - In this study, a secure and coordinated blockchain based energy trading system for Electric Vehicles (EVs) is presented. The major goals of this study are to provide secure and...     

Predicting subcellular localization of multi-label proteins by incorporating the sequence features into Chou's PseAAC

The emergence of numerous genome projects has made the experimental classification of the protein localization almost impossible due to the exponential increase in the number of protein samples. However, most of the applications are merely developed for single-plex and completely ignored the presence of one protein at two or more locations in a cell. In this regard, few attempts were carried out to target Multi-label protein localizations; consequently, undesirable accuracies are achieved. This paper presents a novel approach, in which a discrete feature extraction method is fused with physicochemical properties of amino acids by using Chou's general form of Pseudo Amino Acid Composition. The technique is tested on two benchmark datasets namely: Gpos-mploc and Virus-mPLoc. The empirical results demonstrated that the proposed method yields better results via two examined classifiers i.e. ML-KNN and Rank-SVM. It is established that the proposed model has improved values in all performance measures considered for the comparison.     

Characterization of a new Pseudomonas aeruginosa strain NJ-15 as a potential biocontrol agent

Phylogenetic characterization of soil isolate NJ-15, based on sequence homology of a partial 746-bp fragment of 16SrDNA amplicon, with the ribosomal database sequences (http://www.msu.edu/RDP/cgis/phylip.cgi), validated the strain as Pseudomonas aeruginosa. The strain NJ-15 produced a substantial amount of indole acetic acid (IAA) in tryptophan-supplemented medium. Besides, the strain also exhibited significant production of both the siderophore and hydrogen cyanide (HCN) on chrome azurol S and King's B media, respectively. The data revealed lower HCN production under iron-limiting conditions vis-à-vis higher HCN release with iron stimulation. Significant growth inhibition of phytopathogenic fungi occurred in the order as Fusarium oxysporum > Trichoderma herizum > Alternaria alternata > Macrophomina phasiolina upon incubation with strain NJ-15 cells. Thus, the secondary metabolites producing new Pseudomonas aeruginosa strain NJ-15 exhibited innate potential of plant growth promotion and biocontrol activities in vitro.     

Tetracycline-Cu(II) photo-induced fragmentation of serum albumin

The protein-damaging potential of photosensitized tetracycline hydrochloride alone and in combination with the metal ion Cu(II) was assessed using serum albumin as a model protein. Exposure of tetracycline to white light in an aqueous solution triggered the generation of significant amounts of reactive oxygen species (ROS) and engendered substantial protein damage. The appearance of distinct low-molecular-mass protein bands on 10% SDS-polyacrylamide gel ascertained the tetracycline concentration-dependent fragmentation of albumin. Photoexcited tetracycline in combination with 100 microM Cu(II) enhanced the protein fragmentation process with concurrent increase in free radical production. The significant release of acid-soluble amino groups and carbonyl groups from treated albumin provided quantitative estimation of protein fragmentation at 0-1.0 mM concentrations of tetracycline. Cu(II) ions per se did not cause any perceptible protein damage. The results with free radical quenchers suggested the role of hydroxyl radicals (*OH) in tetracycline-Cu(II)-induced protein fragmentation, as no superoxide dismutase (SOD)-mediated quenching effect was noted. The generation of free radicals upon tetracycline photoexcitation and consequent protein fragmentation may be considered as important factors in augmentation of tetracycline-induced phototoxic responses.     

An intelligent biological information management system

MOTIVATION: As biomedical researchers are amassing a plethora of information in a variety of forms resulting from the advancements in biomedical research, there is a critical need for innovative information management and knowledge discovery tools to sift through these vast volumes of heterogeneous data and analysis tools. In this paper we present a general model for an information management system that is adaptable and scalable, followed by a detailed design and implementation of one component of the model. The prototype, called BioSifter, was applied to problems in the bioinformatics area. RESULTS: BioSifter was tested using 500 documents obtained from PubMed database on two biological problems related to genetic polymorphism and extracorporal shockwave lithotripsy. The results indicate that BioSifter is a powerful tool for biological researchers to automatically retrieve relevant text documents from biological literature based on their interest profile. The results also indicate that the first stage of information management process, i.e. data to information transformation, significantly reduces the size of the information space. The filtered data obtained through BioSifter is relevant as well as much smaller in dimension compared to all the retrieved data. This would in turn significantly reduce the complexity associated with the next level transformation, i.e. information to knowledge.