Integration of Biochemical Processes in the Physiology of Water Stressed Plants

1983 ◽  
pp. 35-44 ◽  
Author(s):  
D. W. Lawlor
Keyword(s):  
Biochemical Processes

3-D imaging of cells using a confocal laser scanning microscope and digital image processing

1988 ◽  
Vol 46 ◽  
pp. 96-97
Author(s):  
Thomas M. Jovin ◽  
Michel Robert-Nicoud ◽  
Donna J. Arndt-Jovin ◽  
Thorsten Schormann
Keyword(s):  
Laser Scanning ◽  
Confocal Laser Scanning Microscope ◽  
Laser Scanning Microscopy ◽  
Confocal Laser Scanning ◽  
Confocal Laser ◽  
Scanning Microscope ◽  
Laser Scanning Microscope ◽  
Biochemical Processes ◽  
Adjacent Structures

Light microscopic techniques for visualizing biomolecules and biochemical processes in situ have become indispensable in studies concerning the structural organization of supramolecular assemblies in cells and of processes during the cell cycle, transformation, differentiation, and development. Confocal laser scanning microscopy offers a number of advantages for the in situ localization and quantitation of fluorescence labeled targets and probes: (i) rejection of interfering signals emanating from out-of-focus and adjacent structures, allowing the “optical sectioning” of the specimen and 3-D reconstruction without time consuming deconvolution; (ii) increased spatial resolution; (iii) electronic control of contrast and magnification; (iv) simultanous imaging of the specimen by optical phenomena based on incident, scattered, emitted, and transmitted light; and (v) simultanous use of different fluorescent probes and types of detectors.We currently use a confocal laser scanning microscope CLSM (Zeiss, Oberkochen) equipped with 3-laser excitation (u.v - visible) and confocal optics in the fluorescence mode, as well as a computer-controlled X-Y-Z scanning stage with 0.1 μ resolution.

Germination and initial growth of triticale seeds under stationary magnetic fields

2014 ◽  
Vol 2 (2) ◽  
pp. 72-79 ◽  
Author(s):  
Mercedes Florez ◽  
Elvira Martinez ◽  
Victoria Carbonell
Keyword(s):  
Magnetic Field ◽  
Magnetic Fields ◽  
Seed Vigor ◽  
Initial Growth ◽  
Practical Application ◽  
Biochemical Processes ◽  
Mean Germination Time ◽  
Nutrition Value ◽  
The Mean ◽  
Growth Of Seedlings

The main objective of this study is to determine the effects of 125 mT and 250mT magnetic treatment on the germination and initial growth of triticale seeds. This objective has a practical application in agriculture science: early growth of triticale. An increase in the percentage and rate of germination of seeds and a stimulation of growth of seedlings as positive response to magnetic field treatment in rice, wheat, maize and barley seeds have been found in previous studies. Germination tests were carried out under laboratory conditions by exposing triticale seeds to magnetic field for different times. The effect was studied by exposure of seeds prior sowing. The mean germination time were reduced for all the magnetic treatments applied. Most significant differences were obtained for time of exposure of 1 and 24 hours and maximum reductions was 12%. Furthermore, seedlings from magnetically treated seeds grew taller than control. The longest mean total length was obtained from seedlings exposed to 125 and 250 mT for 24 hours. External magnetic fields are assumed to enhance seed vigor by influencing the biochemical processes by stimulating activity of proteins and enzymes. Numerous studies suggested that magnetic field increases ions uptake and consequently improves nutrition value.

To the item of biochemical processes at reservation and storage of milk

2018 ◽  
pp. 22-25
Author(s):  
A.D. Koval’ ◽  
◽  
A.V. Mironova ◽  
V.A. Pushkarev ◽  
K.E. Shevchenko ◽  
...  
Keyword(s):  
Biochemical Processes ◽  
And Storage

A Survey for Predicting Enzyme Family Classes Using Machine Learning Methods

2019 ◽  
Vol 20 (5) ◽  
pp. 540-550 ◽  
Author(s):  
Jiu-Xin Tan ◽  
Hao Lv ◽  
Fang Wang ◽  
Fu-Ying Dao ◽  
Wei Chen ◽  
...  
Keyword(s):  
Machine Learning ◽  
Catalytic Mechanism ◽  
Biological Function ◽  
Learning Methods ◽  
Biochemical Processes ◽  
Machine Learning Methods ◽  
Enzyme Family ◽  
The Family ◽  
Speed Up ◽  
Family Classification

Enzymes are proteins that act as biological catalysts to speed up cellular biochemical processes. According to their main Enzyme Commission (EC) numbers, enzymes are divided into six categories: EC-1: oxidoreductase; EC-2: transferase; EC-3: hydrolase; EC-4: lyase; EC-5: isomerase and EC-6: synthetase. Different enzymes have different biological functions and acting objects. Therefore, knowing which family an enzyme belongs to can help infer its catalytic mechanism and provide information about the relevant biological function. With the large amount of protein sequences influxing into databanks in the post-genomics age, the annotation of the family for an enzyme is very important. Since the experimental methods are cost ineffective, bioinformatics tool will be a great help for accurately classifying the family of the enzymes. In this review, we summarized the application of machine learning methods in the prediction of enzyme family from different aspects. We hope that this review will provide insights and inspirations for the researches on enzyme family classification.

Microbial Biofilms and Biotechnology – Some Perceptions

2020 ◽  
Vol 09 ◽  
Author(s):  
Subba Rao Toleti
Keyword(s):  
Tissue Culture ◽  
Synthetic Biology ◽  
Industrial Effluents ◽  
Aquatic Environments ◽  
Biochemical Processes ◽  
Microbial Biofilms ◽  
Biofilm Bacteria ◽  
Prophylactic Vaccines ◽  
Design Construction

: The review is an attempt to introduce the readers in brief about biofilms and their implications as well as some new perceptions in biotechnology. Biofilms are adherent microbial communities, which are developed on submerged surfaces in aquatic environments. Biofilms play a significant role in exopolymer production, material deterioration and also cause harmful infections. Further, the role of corrosion causing biofilm bacteria in deterioration of different materials, microbial biofilms and their enzymatic processes in reducing the toxicity of pollutants in industrial effluents are elaborated, along with clean technologies for wastewater treatment. Biotechnology is defined as any technological application that uses biological systems to synthesize or modify products or processes. The applications include biochemical processes, medical care, cell and tissue culture as well as synthetic biology and others. Synthetic biology details about the design, construction of new biological components and systems for useful purposes. Finally, to overcome the limitations that are inherent to the use of cellular host’s, cell-free systems as critical platforms for synthetic biology applications. This mini-review also mentions about new diagnostic products based on enzymes, monoclonal antibodies and engineered proteins as well as novel prophylactic vaccines.

scholarly journals Neural network aided approximation and parameter inference of non-Markovian models of gene expression

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Qingchao Jiang ◽  
Xiaoming Fu ◽  
Shifu Yan ◽  
Runlai Li ◽  
Wenli Du ◽  
...  
Keyword(s):  
Neural Network ◽  
Stochastic Dynamics ◽  
Stochastic Simulations ◽  
Parameter Inference ◽  
Biochemical Processes ◽  
Markovian Models ◽  
The Neural Network ◽  
Large Numbers ◽  
Small Set ◽  
Noisy Measurements

AbstractNon-Markovian models of stochastic biochemical kinetics often incorporate explicit time delays to effectively model large numbers of intermediate biochemical processes. Analysis and simulation of these models, as well as the inference of their parameters from data, are fraught with difficulties because the dynamics depends on the system’s history. Here we use an artificial neural network to approximate the time-dependent distributions of non-Markovian models by the solutions of much simpler time-inhomogeneous Markovian models; the approximation does not increase the dimensionality of the model and simultaneously leads to inference of the kinetic parameters. The training of the neural network uses a relatively small set of noisy measurements generated by experimental data or stochastic simulations of the non-Markovian model. We show using a variety of models, where the delays stem from transcriptional processes and feedback control, that the Markovian models learnt by the neural network accurately reflect the stochastic dynamics across parameter space.

scholarly journals Exogenous Putrescine Enhances Salt Tolerance and Ginsenosides Content in Korean Ginseng (Panax ginseng Meyer) Sprouts

Plants ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 1313
Author(s):  
Md. Jahirul Islam ◽  
Byeong Ryeol Ryu ◽  
Md. Obyedul Kalam Azad ◽  
Md. Hafizur Rahman ◽  
Md. Soyel Rana ◽  
...  
Keyword(s):  
Panax Ginseng ◽  
Salinity Stress ◽  
Soluble Sugar ◽  
Principal Component ◽  
Total Soluble Protein ◽  
Soluble Carbohydrate ◽  
Guaiacol Peroxidase ◽  
Salinity Treatment ◽  
Total Soluble Sugar ◽  
Biochemical Processes

The effect of exogenously applied putrescine (Put) on salt stress tolerance was investigated in Panax ginseng. Thirty-day-old ginseng sprouts were grown in salinized nutrient solution (150 mM NaCl) for five days, while the control sprouts were grown in nutrients solution. Putrescine (0.3, 0.6, and 0.9 mM) was sprayed on the plants once at the onset of salinity treatment, whereas control plants were sprayed with water only. Ginseng seedlings tested under salinity exhibited reduced plant growth and biomass production, which was directly interlinked with reduced chlorophyll and chlorophyll fluorescence due to higher reactive oxygen species (hydrogen peroxide; H2O2) and lipid peroxidation (malondialdehyde; MDA) production. Application of Put enhanced accumulation of proline, total soluble carbohydrate, total soluble sugar and total soluble protein. At the same time, activities of antioxidant enzymes like superoxide dismutase, catalase, ascorbate peroxidase, guaiacol peroxidase in leaves, stems, and roots of ginseng seedlings were increased. Such modulation of physio-biochemical processes reduced the level of H2O2 and MDA, which indicates a successful adaptation of ginseng seedlings to salinity stress. Moreover, protopanaxadiol (PPD) ginsenosides enhanced by both salinity stress and exogenous Put treatment. On the other hand, protopanaxatriol (PPT) ginsenosides enhanced in roots and reduced in leaves and stems under salinity stress condition. In contrast, they enhanced by exogenous Put application in all parts of the plants for most cases, also evidenced by principal component analysis. Collectively, our findings provide an important prospect for the use of Put in modulating salinity tolerance and ginsenosides content in ginseng sprouts.

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