Metal and drought tolerant biochar based biofertilizer for enhanced growth of Raphanus sativus

Majority of applied agrochemicals remain persistent in soil for long time, causing deleterious effect on soil and its micro-flora, resulting in unproductive use of agricultural lands further causes land scarcity for future use. Application of biochar (BC) and plant growth promoting rhizobacteria (PGPR) plays a vital role in improved growth of crops. The present study involves preparation of biofertilizer using BC derived from hardwood forest tree of birch as carrier material. For this purpose, plant growth promoting, metal and drought tolerant bacterial strains were selected as test inoculants. The efficacy of these inoculated carriers was observed on the seedling growth of Raphanus sativus. The isolated bacterial inoculums showed indole-3-acetic acid and siderophore production, phosphate solubilization, and 1-aminocyclopropane- 1-carboxylic acid (ACC) deaminase activity, which help in plant growth promotion. Application of 2.5% of BC along with Bacillus sp. 16a significantly increased the rate of seed germination, root and shoot length, and fresh biomass of roots and shoots of R. sativus plant. Results suggest both BC and PGPR could together produce much higher biomass than the single amendment. © 2021 Author(s).Department of Science and Technology, Ministry of Science and Technology, India, डीएसटी, (INT/ RUS/RFBR/363)Government Council on Grants, Russian FederationUral Federal University, UrFUThe authors acknowledge the work support by RFBR, Russia (Project No. 19-516-45006) and DST, India (INT/ RUS/RFBR/363) and the Ural Federal University Competitiveness Enhancement Program, Act 211 Government of the Russian Federation (ɫontract ʋ 02.A03.21.0006)

Tissue Thermometry during Ultrasound Exposure

In order to quantify ultrasound therapy it is important to measure the tissue temperature during the treatment. Invasive probes induce several artifacts in ultrasound fields. The magnitude of these artifacts is probe dependent. Several different probes were evaluated for hyperthermia purposes in this study. An alternative noninvasive method to evaluate the temperature elevations and tissue damage is to use magnetic resonance imaging. The fast imaging sequences used in this study are marginally useful for monitoring hyperthermia. However, these imaging sequences can be utilized to guide and monitor ultrasound surgery

Tissue thermometry during ultrasound exposure

In order to quantify ultrasound therapy it is important to measure the tissue temperature during the treatment. Invasive probes induce several artifacts in ultrasound fields. The magnitude of these artifacts is probe dependent. Several different probes were evaluated for hyperthermia purposes in this study. An alternative noninvasive method to evaluate the temperature elevations and tissue damage is to use magnetic resonance imaging. The fast imaging sequences used in this study are marginally useful for monitoring hyperthermia. However, these imaging sequences can be utilized to guide and monitor ultrasound surgery

Mapping of Brain Metabolite Distributions by Volumetric Proton MR Spectroscopic Imaging (MRSI)

Distributions of proton MR-detected metabolites have been mapped throughout the brain in a group of normal subjects using a volumetric MR spectroscopic imaging (MRSI) acquisition with an interleaved water reference. Data were processed with intensity and spatial normalization to enable voxel-based analysis methods to be applied across a group of subjects. Results demonstrate significant regional, tissue, and gender-dependent variations of brain metabolite concentrations, and variations of these distributions with normal aging. The greatest alteration of metabolites with age was observed for white-matter choline and creatine. An example of the utility of the normative metabolic information is then demonstrated for analysis of data acquired from a subject who suffered a traumatic brain injury. This study demonstrates the ability to obtain proton spectra from a wide region of the brain and to apply fully automated processing methods. The resultant data provide a normative reference for subsequent utilization for studies of brain injury and disease

The usefulness of a contrast agent and gradient-recalled acquisition in a steady-state imaging sequence for magnetic resonance imaging-guided noninvasive ultrasound surgery

Rationale and Objectives. The ability of magnetic resonance imaging to detect small temperature elevations from focused ultrasound surgery beams was studied. In addition, the value of a contrast agent in delineating the necrosed tissue volume was investigated. materials and methods. Gradient-recalled acquisition in a steady state (GRASS) T1-weighted images were used to follow the temperature elevation and tissue changes during 2-minute sonications in the thigh muscles of 10 rabbits. The effects of the treatment on the vascular network was investigated by injecting a contrast agent bolus before or after the son-ication. Results. The signal intensity decreased during the sonica-tion, and the reduction was directly proportional to the applied power and increase in temperature. The signal intensity returned gradually back to baseline after the ultrasound was turned off. Injection of the contrast agent increased the signal intensity in muscle, but not in the necrosed tissue. The dimensions of the delineated tissue volume were the same as mca-sured from the T2-weightcd fast-spin-echo images and postmortem tissue examination. Conclusions. These results indicate that magnetic resonance imaging can be used to detect temperature elevations that do not cause tissue damage and that contrast agent can be used to delineate the necrosed tissue volume. © 1994. J.B. Lippincott Company

A Scalable Framework For Segmenting Magnetic Resonance Images

A fast, accurate and fully automatic method of segmenting magnetic resonance images of the human brain is introduced. The approach scales well allowing fast segmentations of fine resolution images. The approach is based on modifications of the soft clustering algorithm, fuzzy c-means, that enable it to scale to large data sets. Two types of modifications to create incremental versions of fuzzy c-means are discussed. They are much faster when compared to fuzzy c-means for medium to extremely large data sets because they work on just parts of the data. They are comparable in quality to application of fuzzy c-means to all of the data. The clustering algorithms coupled with inhomogeneity correction and smoothing are used to create a framework for automatically segmenting magnetic resonance images of the human brain. The framework is applied to a set of normal human brain volumes acquired from different magnetic resonance scanners using different head coils, acquisition parameters and field strengths. Results are compared to those from two widely used magnetic resonance image segmentation programs, SPM and FSL. The results are comparable to FSL while providing significant speed-up and better scalability to larger volumes of data.

Comprehensive processing, display and analysis for in vivo MR spectroscopic imaging

Image reconstruction for magnetic resonance spectroscopic imaging (MRSI) requires specialized spatial and spectral data processing methods and benefits from the use of several sources of prior information that are not commonly available, including MRI-derived tissue segmentation, morphological analysis and spectral characteristics of the observed metabolites. In addition, incorporating information obtained from MRI data can enhance the display of low-resolution metabolite images and multiparametric and regional statistical analysis methods can improve detection of altered metabolite distributions. As a result, full MRSI processing and analysis can involve multiple processing steps and several different data types. In this paper, a processing environment is described that integrates and automates these data processing and analysis functions for imaging of proton metabolite distributions in the normal human brain. The capabilities include normalization of metabolite signal intensities and transformation into a common spatial reference frame, thereby allowing the formation of a database of MR-measured human metabolite values as a function of acquisition, spatial and subject parameters. This development is carried out under the MIDAS project (Metabolite Imaging and Data Analysis System), which provides an integrated set of MRI and MRSI processing functions. It is anticipated that further development and distribution of these capabilities will facilitate more widespread use of MRSI for diagnostic imaging, encourage the development of standardized MRSI acquisition, processing and analysis methods and enable improved mapping of metabolite distributions in the human brain