TL;DR: In a wide variety of excitable cells the transmembrane exchange of the monovalent marine cations Na and K can be considered the substantial basis of bioelectric membrane activity, whereas Ca ions are required as mediators when, by this superfi cial process, intracellular reactions such as muscular contraction, glandular secre tion, or liberation of transmitter substances are initiated.
Abstract: The essential connection of the basic physiological processes of excitation and contraction with transmembrane movements of Na, K, and Ca ions probably origi nates from an early stage of cellular evolution. Despite innumerable modifications the fundamental processes that developed in the ocean have not undergone major changes during the course of development of higher forms of animal life. Thus in a wide variety of excitable cells the transmembrane exchange of the monovalent marine cations Na and K can be considered the substantial basis of bioelectric membrane activity, whereas Ca ions are required as mediators when, by this superfi cial process, intracellular reactions such as muscular contraction, glandular secre tion, or liberation of transmitter substances are initiated ( 1, 2). Ca ions can exert this messenger function either in a primitive way, by penetrating into the intracellu lar space across the depolarized cell membrane or, at a more advanced stage of evolution, by being released from intracellulariy located endoplasmic stores. As to contractile tissues, the development of large endoplasmic Ca pools is most obvious in skeletal muscle, whereas myocardial fibers and, particularly, smooth muscle cells are less specialized in this respect. The natural consequences are as follows:
TL;DR: This work focuses on the development of models for Surface EMG Signal Generation based on the principles of Structure--Based SEMG models, which were developed in the context of motor control and Muscle Contraction.
Abstract: Introduction. Contributors. 1 BASIC PHYSIOLOGY AND BIOPHYSICS OF EMG SIGNAL GENERATION (T. Moritani, D. Stegeman, R. Merletti). 1.1 Introduction. 1.2 Basic Physiology of Motor Control and Muscle Contraction. 1.3 Basic Electrophysiology of the Muscle Cell Membrane. References. 2 NEEDLE AND WIRE DETECTION TECHNIQUES (J. V. Trontelj, J. Jabre, M. Mihelin). 2.1 Anatomical and Physiological Background of Intramuscular Recording. 2.2 Recording Characteristics of Needle Electrodes. 2.3 Conventional Needle EMG. 2.4 Special Needle Recording Techniques. 2.5 Physical Characteristics of Needle EMG Signals. 2.6 Recording Equipment. References. 3 DECOMPOSITION OF INTRAMUSCULAR EMG SIGNALS (D. W. Stashuk, D. Farina, K. Sogaard). 3.1 Introduction. 3.2 Basic Steps for EMG Signal Decomposition. 3.3 Evaluation of Performance of EMG Signal Decomposition Algorithms. 3.4 Applications of Results of the Decomposition of an Intramuscular EMG Signal. 3.5 Conclusions. References. 4 BIOPHYSICS OF THE GENERATION OF EMG SIGNALS (D. Farina, R. Merletti, D. F. Stegeman). 4.1 Introduction. 4.2 EMG Signal Generation. 4.3 Crosstalk. 4.4 Relationships between Surface EMG Features and Developed Force. 4.5 Conclusions. References. 5 DETECTION AND CONDITIONING OF THE SURFACE EMG SIGNAL (R. Merletti, H. Hermens). 5.1 Introduction. 5.2 Electrodes: Their Transfer Function. 5.3 Electrodes: Their Impedance, Noise, and dc Voltages. 5.4 Electrode Configuration, Distance, Location. 5.5 EMG Front--End Amplifiers. 5.6 EMG Filters: Specifications. 5.7 Sampling and A/D Conversion. 5.8 European Recommendations on Electrodes and Electrode Locations. References. 6 SINGLE--CHANNEL TECHNIQUES FOR INFORMATION EXTRACTION FROM THE SURFACE EMG SIGNAL (E. A. Clancy, D. Farina, G. Filligoi). 6.1 Introduction. 6.2 Spectral Estimation of Deterministic Signals and Stochastic Processes. 6.3 Basic Surface EMG Signal Models. 6.4 Surface EMG Amplitude Estimation. 6.5 Extraction of Information in Frequency Domain from Surface EMG Signals. 6.6 Joint Analysis of EMG Spectrum and Amplitude (JASA). 6.7 Recurrence Quantification Analysis of Surface EMG Signals. 6.8 Conclusions. References. 7 MULTI--CHANNEL TECHNIQUES FOR INFORMATION EXTRACTION FROM THE SURFACE EMG (D. Farina, R. Merletti, C. Disselhorst--Klug). 7.1 Introduction. 7.2 Spatial Filtering. 7.3 Spatial Sampling. 7.4 Estimation of Muscle--Fiber Conduction Velocity. 7.5 Conclusions. References. 8 EMG MODELING AND SIMULATION (D. F. Stegeman, R. Merletti, H. J. Hermens). 8.1 Introduction. 8.2 Phenomenological Models of EMG. 8.3 Elements of Structure--Based SEMG Models. 8.4 Basic Assumptions. 8.5 Elementary Sources of Bioelectric Muscle Activity. 8.6 Fiber Membrane Activity Profiles, Their Generation, Propagation, and Extinction. 8.7 Structure of the Motor Unit. 8.8 Volume Conduction. 8.9 Modeling EMG Detection Systems. 8.10 Modeling Motor Unit Recruitment and Firing Behavior. 8.11 Inverse Modeling. 8.12 Modeling of Muscle Fatigue. 8.13 Other Applications of Modeling. 8.14 Conclusions. References. 9 MYOELECTRIC MANIFESTATIONS OF MUSCLE FATIGUE (R. Merletti, A. Rainoldi, D. Farina). 9.1 Introduction. 9.2 Definitions and Sites of Neuromuscular Fatigue. 9.3 Assessment of Muscle Fatigue. 9.4 How Fatigue Is Reflected in Surface EMG Variables. 9.5 Myoelectric Manifestations of Muscle Fatigue in Isometric Voluntary Contractions. 9.6 Fiber Typing and Myoelectric Manifestations of Muscle Fatigue. 9.7 Factors Affecting Surface EMG Variable. 9.8 Repeatability of Estimates of EMG Variables and Fatigue Indexes. 9.9 Conclusions. References. 10 ADVANCED SIGNAL PROCESSING TECHNIQUES (D. Zazula, S. Karlsson, C. Doncarli). 10.1 Introduction. 10.2 Theoretical Background. 10.3 Decomposition of EMG Signals. 10.4 Applications to Monitoring Myoelectric Manifestations of Muscle Fatigue. 10.5 Conclusions. Acknowledgment. References. 11 SURFACE MECHANOMYOGRAM (C. Orizio). 11.1 The Mechanomyogram (MMG): General Aspects during Stimulated and Voluntary Contraction. 11.2 Detection Techniques and Sensors Comparison. 11.3 Comparison between Different Detectors. 11.4 Simulation. 11.5 MMG Versus Force: Joint and Adjunct Information Content. 11.6 MMG Versus EMG: Joint and Adjunct Information Content. 11.7 Area of Application. References. 12 SURFACE EMG APPLICATIONS IN NEUROLOGY (M. J. Zwarts, D. F. Stegeman, J. G. van Dijk). 12.1 Introduction. 12.2 Central Nervous System Disorders and SEMG. 12.3 Compound Muscle Action Potential and Motor Nerve Conduction. 12.4 CMAP Generation. 12.5 Clinical Applications. 12.6 Pathological Fatigue. 12.7 New Avenues: High--Density Multichannel Recording. 12.8 Conclusion. References. 13 APPLICATIONS IN ERGONOMICS (G. M. Hagg, B. Melin, R. Kadefors). 13.1 Historic Perspective. 13.2 Basic Workload Concepts in Ergonomics. 13.3 Basic Surface EMG Signal Processing. 13.4 Load Estimation and SEMG Normalization and Calibration. 13.5 Amplitude Data Reduction over Time. 13.6 Electromyographic Signal Alterations Indicating Muscle Fatigue in Ergonomics. 13.7 SEMG Biofeedback in Ergonomics. 13.8 Surface EMG and Musculoskeletal Disorders. 13.9 Psychological Effects on EMG. References. 14 APPLICATIONS IN EXERCISE PHYSIOLOGY (F. Felici). 14.1 Introduction. 14.2 A Few "Tips and Tricks". 14.3 Time and Frequency Domain Analysis of sEMG: What Are We Looking For? 14.4 Application of sEMG to the Study of Exercise. 14.5 Strength and Power Training. 14.6 Muscle Damage Studied by Means of sEMG. References. 15 APPLICATIONS IN MOVEMENT AND GAIT ANALYSIS (C. Frigo, R. Shiavi). 15.1 Relevance of Electromyography in Kinesiology. 15.2 Typical Acquisition Settings. 15.3 Study of Motor Control Strategies. 15.4 Investigation on the Mechanical Effect of Muscle Contraction. 15.5 Gait Analysis. 15.6 Identification of Pathophysiologic Factors. 15.7 Workload Assessment in Occupational Biomechanics. 15.8 Biofeedback. 15.9 The Linear Envelope. 15.10 Information Enhancement through Multifactorial Analysis. References. 16 APPLICATIONS IN REHABILITATION MEDICINE AND RELATED FIELDS (A. Rainoldi, R. Casale, P. Hodges, G. Jull). 16.1 Introduction. 16.2 Electromyography as a Tool in Back and Neck Pain. 16.3 EMG of the Pelvic Floor: A New Challenge in Neurological Rehabilitation. 16.4 Age--Related Effects on EMG Assessment of Muscle Physiology. 16.5 Surface EMG and Hypobaric Hipoxia. 16.6 Microgravity Effects on Neuromuscular System. References. 17 BIOFEEDBACK APPLICATIONS (J. R. Cram). 17.1 Introduction. 17.2 Biofeedback Application to Impairment Syndromes. 17.3 SEMG Biofeedback Techniques. 17.4 Summary. References. 18 CONTROL OF POWERED UPPER LIMB PROSTHESES (P. A. Parker, K. B. Englehart, B. S. Hudgins). 18.1 Introduction. 18.2 Myoelectric Signal as a Control Input. 18.3 Conventional Myoelectric Control. 18.4 Emerging MEC Strategies. 18.5 Summary. References. Index.
TL;DR: This review proposes the “Multiple Mechanisms Theory,” based on the assumption that there is no single mechanism involved in promotion of plant growth by Azospirillum, but a combination of a few or many mechanisms in each case of inoculation.
Abstract: During the last 35 years of studies of Azospirillum–plant interaction, over 20 proposals were suggested for the mechanism of action by which Azospirillum spp., the most intensively studied plant growth-promoting bacteria, enhances plant growth. The proposals include a single phytohormone activity, multiple phytohormones, nitrogen fixation, assortments of small-sized molecules and enzymes, enhanced membrane activity, proliferation of the root system, enhanced water and mineral uptake, mobilization of minerals, mitigation of environmental stressors of plants, and direct and indirect biological control of numerous phytopathogens. By volume, the largest number of published information involves hormonal activities, nitrogen fixation, and root proliferation. After analyzing the accumulated knowledge, it was concluded that this versatile genus possesses a large array of potential mechanisms by which it can effect plant growth. Consequently, this review proposes the “Multiple Mechanisms Theory,” based on the assumption that there is no single mechanism involved in promotion of plant growth by Azospirillum, but a combination of a few or many mechanisms in each case of inoculation. These may vary according to the plant species, the Azospirillum strain, and environmental conditions when the interaction occurred. The effect can be cumulative, an “additive hypothesis” (proposed before), where the effects of small mechanisms operating at the same time or consecutively create a larger final effect on plant. Additionally, the observed effect on plant growth can be the result of a tandem or a cascade of mechanisms in which one mechanism stimulates another, yielding enhanced plant growth, such as the plausible relations among phytohormones, nitric oxide, membrane activities, and proliferation of roots. Finally, the growth promotion can also be a combination of unrelated mechanisms that operate under environmental or agricultural conditions needed by the crop at particular locations, such as mitigating stress (salt, drought, toxic compounds, adverse environment), and the need for biological control of or reducing pathogenic microflora.
TL;DR: In contrast to the mammalian gp91(phox), the plant homolog can produce O(2)(-) in the absence of additional cytosolic components and is stimulated directly by Ca(2+), indicating that the formazan precipitates were due to reduction by O( 2)(-) radicals catalyzed by an NADPH-dependent flavin containing enzyme.
Abstract: Genes encoding homologs of the gp91(phox) subunit of the plasma membrane NADPH oxidase complex have been identified in plants and are hypothesized to be a source of reactive oxygen species during defense responses. However, the direct involvement of the gene products in superoxide (O(2)(-)) production has yet to be shown. A novel activity gel assay based on protein fractionation in native or sodium dodecyl sulfate (SDS)-denaturing polyacrylamide gels was developed. In native polyacrylamide gel electrophoresis, one or two major O(2)(-)-producing formazan bands were detected in tomato (Lycopersicum esculentum Mill. cv Moneymaker) and tobacco (Nicotiana tabacum var. Samsun, NN) plasma membranes, respectively. Denaturing fractionation of tomato and tobacco plasma membrane in SDS-polyacrylamide gel electrophoresis, followed by regeneration of the in-gel activity, revealed NADPH-dependent O(2)(-)-producing formazan bands of 106-, 103-, and 80- to 75-kD molecular masses. The SDS and native activity bands were dependent on NADPH and completely inhibited by diphenylene iodonium or CuZn- O(2)(-) dismutase, indicating that the formazan precipitates were due to reduction by O(2)(-) radicals catalyzed by an NADPH-dependent flavin containing enzyme. The source of the plasma membrane activity bands was confirmed by their cross-reaction with antibody prepared from the C terminus of the tomato gp91(phox) homolog. Membrane extracts as well as the in-gel NADPH oxidase activities were stimulated in the presence of Ca(2+). In addition, the relative activity of the gp91(phox) homolog was enhanced in the plasma membrane of tobacco mosaic virus-infected leaves. Thus, in contrast to the mammalian gp91(phox), the plant homolog can produce O(2)(-) in the absence of additional cytosolic components and is stimulated directly by Ca(2+).
TL;DR: Investigation of magainin II amide analogs with cationic charges showed that enhancement of the peptide charge up to a threshold value of +5 and conservation of appropriate hydrophobic properties optimized the antimicrobial activity and selectivity.