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Background: Propagated sensation along channels occurs because of stimulations during acupuncture therapies and tends to transmit the stimulating signals along the meridians. From the Western medicine aspect, researchers consider the phenomena as neurotransmissions initiated by nerves, and various ions regulate the physiological functions of the nervous systems. Objective: This research investigates the critical characteristics of ions at acupoints and the mechanism of propagated sensation along channels, crossing meridians in traditional Chinese medicine (TCM). Methods: This research first conducts experiments by applying intense pulse light beams, which replace the traditional acupuncture treatments, on designated acupoints of studied human subjects, and employs a thermal infrared imager to monitor the temperature responses, which are induced by post sensation, in adjacent regions of the acupoints. Meanwhile, the research applies a synchrotron radiation technique on adult SD (Sprague Dawley) rats. The study analyzes the output responses with an X-ray Absorption Fine Spectroscopy (XAFS) to investigate the ion distributions in the relevant acupoints, which trigger the propagated sensation crossing meridians. Results: Experimental results demonstrate significant temperature increases simultaneously at the stimulated acupoints and specific other acupoints, whether in the same meridians. Moreover, XAFS experimental results indicate significantly high calcium, potassium, and sulfide ions at the stimulated acupoint regions. On the contrary, the measured chloride ions level at the regions is correspondingly lower. Conclusions: The thermal infrared imager monitoring shows significant temperature variations of crossing-meridian acupoints after implementing the intense pulse light beams on designated acupoints, and it implies the occurring of prolonged sensation along channels using acupuncture therapies. The X-ray absorption spectrum demonstrates significant differences in ion amounts and distributions between the acupoints and non-acupoints, and acupuncture therapies result in ion concentrations in the correlated regions inducing propagated sensation crossing meridians in TCM. Hence, the stimulated acupoints operate as ion reservoirs to provide high-concentration of specific ions to trigger the crossing-meridian post sensation.

Based upon the CANopen communication protocol and the LabVIEW graphic programing procedures, this paper develops a closed-loop control architecture for a parallel three-axis (Delta) robotic arm mechanism. The accomplishments include prototyping a parallel three-axis robotic arm mechanism, assembling servomotors with associated encoders and gearsets, coding CANopen communication scripts for servomotor controllers and a host supervision GUI, coding forward/inverse kinematics scripts to compute the required servomotor rotations and the coordinates of a movable platform or the mechanism, coding tracking error compensation scripts for effective closed-loop griper control, and coding integration scripts to command and supervise the mechanism motion on the LabVIEW-based host GUI. During the development stage, this research designed and prototyped the parallel three-axis robotic arm mechanism based upon basic Delta robot kinematics. To control the mechanism effectively and accurately, this study implemented the CANopen communication protocol, which characterizes high speed and stable transmission. The protocol applies to the CANopen communication channels among the controllers and the host supervision GUI. On the LabVIEW development platform, the coded supervision GUI performs issuing/receiving messages to the CANopen-based controllers. The controllers excite the servomotors and actuate the parallel mechanism to track prescribed trajectories in a closed-loop control fashion. Meanwhile, an electromagnet attached to the movable platform of the robotic mechanism performs satisfactory picking/placing object actions.

This paper suggests an optimization strategy to train a CNN deep-learning network, which successfully recognizing working status on the HMI panels of CNC machines. To verify the developed strategy, the research experiments using a prototype that consists of a CNC milling machine and an industrial robot. In the optimization strategy, the research first defines a length-varying hyperparameter list for the deep-learning network, and the entities in the list adjust themselves to optimize the model scales. During the optimization process, this paper adopts a two-stage training scheme that gradually augments image datasets to improve HMI control-panel recognition performances, such as recognition accuracy and recognition speed to identify the CNC machine working status. Using an open-source PyTorch platform, this research establishes a cloud-based distributed architecture to build training codes for the deep-learning network, in which an applicable optimization model is deployed to recognize the CNC control-panel working status. The optimization strategy employs minimal codes to rebuild the architecture and the least efforts to reform the manufacturing system. The optimally trained model provides up to a 99.34% CNC panel-message recognition accuracy and a high-speed recognition of 100 images in 0.6 s. Moreover, the developed optimization strategy enables the prediction of necessitated dataset augmentation to training a practically implemented CNN network.

Manufacturing industries nowadays need to reconfigure their production lines promptly as to acclimate to rapid changing markets. Meanwhile, exercising system reconfigurations also needs to manage innumerous types of manufacturing apparatus involved. Nevertheless, traditional incompatible manufacturing systems delivered by exclusive vendors usually increase manufacture costs and prolong development time. This paper presents a novel RMS framework, which is intended to implement a Redis master/slave server mechanism to integrate various CNC manufacturing apparatus, hardware control means, and data exchange protocols through developed configurating codes. In the RMS framework each manufacturing apparatus or accessory stands for an object, and information of recognized CNC control panel image features, associated apparatus tuned parameters, communication formats, operation procedures, and control APIs, are stored into the Redis master cloud server database. Through implementation of machine vision techniques to acquire CNC controller panel images, the system effectively identifies instantaneous CNC machining states and response messages once the embedded image features are recognized. Upon demanding system reconfigurations for the manufacturing resources, the system issues commands from Redis local client servers to retrieve the stored information in the Redis master cloud servers, in which the resources for registered CNC machines, robots, and built-in accessories are maintained securely. The system then exploits the collected information locally to reconfigure involved manufacturing resources and starts manufacturing immediately, and thus is capable to promptly response to fast revised orders in a comitative market. In a prototyped RMS architecture, the proposed approach takes advantage of recognized feedback visual information, which is obtained using an invariant image feature extraction algorithm, and effectively commands an industrial robot to accomplish demanded actions on a CNC control panel, as a regular operator does daily in front of the CNC machine for manufacturing.

The novelty of this research is that the study utilizes Lagrangian multipliers for an articulated close-chain robot mechanism as time-varying states to augment an energy-based Lagrangian dynamic model, and the strategy facilitates the system computations while satisfying the forward/inverse dynamics and mechanism constraints simultaneously for the close-chained robot. Then, this article develops a controller based upon the augmented dynamics model for the Delta robot mechanism and drives its moving platform to track prescribed trajectories in space. As a result, the simulation results validate the effectiveness of the augmented system model in undertaking complex dynamics of close-chained robot mechanisms.

The research prototypes an optical fiber-scanning mechanism for capturing fiber-acquired multiple images. First, the study develops an image processing firmware embedded in high-speed hardware for image cropping, rotation, sharpening, and stitching, especially synchronizing with the moving mechanism. Then, the embedded firmware successively builds panoramic images while iteratively acquiring images as the mechanism in motion. This research applies a 3D printing technology to prototype the mechanism components and employs servomotors for mechanism motions during the prototyping stage. Next, the mechanism guides the scanning motions to follow prescribed trajectories while capturing images of specified regions. Finally, the research embeds the firmware developed on a Linux OS platform into a high-speed controller board. The resolution tests verify that the best image resolution for the prototyped optical mechanism reaches 14.30 line pairs per millimeter, and the achievable image resolution for an inspected object is 35 μm. Through acquiring and synthesizing images simultaneously by the embedded firmware while the optical fiber-scanning mechanism is in motion, this research demonstrates that the developed system effectively constructs panoramic images for an endoscope device at a lower cost.

Pain perception and its EEG wave have been used to describe the body's neural systemic response with respect to a given stimulation. Pain artificially induced by non-coherent intensive light (wavelength of 500nm-1200nm) impulse has not been studied yet. In this study this technique was applied to statistically correlate the brain activity under induced pain while particular acupuncture points (yanlingchuan of both feet, GB34) were stimulated by intensive light impulses. The brain electrophysiological signals or electroencephalogram (EEG) at F(p1), F(p2) were recorded. The data of brain waves showed a distinguishable raising slope in this study. Intensive light beam impulse with beam diameter of 10 mm and intensity of 14 joule/cm2 was applied to the acupuncture points. In order to quantify the pain effects, a pain intensity function was defined based on the induced pain activities related to the collected data. The pain intensity function and its equations were used to analyze the changing rate of pain with respect to stimulated intensity and pain momentum transport activity. The results showed that the area of the brain wave evoked by pain could be used as pain perception indicator. The raising slope at one brain side was relatively higher when the acupuncture point GB34 at the contralateral side was stimulated.

This paper presents the application of a model-based iterative learning control technique to position tracking of a piezoelectric system. Identification of the closed-loop piezoelectric system was undertaken first, and then an iterative learning control methodology based on the identified model was implemented for dynamic tracking control of the actuator. The methodology differs from the conventional iterative learning scheme in that it takes into account the difference of the one-step-ahead predictive input between two successive iterations. The methodology compensates for the predictive input difference as well as the causal error in the previous iteration. The results of the experiments prove the excellence of this technique for precision tracking control of the piezoelectric actuator.

This research proposes a novel scheme of state-compensated iterative learning control (SCILC) for trajectory tracking of piezoelectric systems. The new ILC scheme adds a state compensation term to the conventional Arimoto-type ILC formula. The state compensation term is based on the difference in tracking error between current and previous iterations. With the aid of this state compensation, ILC can therefore take effect more precisely as desired. Further, the addition of the current error in the compensation term can also serve the role of feedback control to stabilize the system. The new ILC scheme keeps the simplicity feature of conventional ILC that no model is required for the control purpose. Experimental results demonstrate that a piezoelectric actuator using the proposed learning scheme can achieve error convergence in about three to five iterations, and keep steady-state tracking errors close to the system noise level.

For trajectory tracking of a piezoelectric actuator system, an enhanced iterative learning control (ILC) scheme based on wavelet transform filtering (WTF) is proposed in this research. The enhanced ILC scheme incorporates a state compensation in the ILC formula. Combining state compensation with iterative learning, the scheme enhances tracking accuracies substantially, in comparison to the conventional D-type ILC and a proportional control-aided D-type ILC. The wavelet transform is adopted to filter learnable tracking errors without phase shift. Based on both a time–frequency analysis of tracking errors and a convergence bandwidth analysis of ILC, a two-level WTF is chosen for ILC in this study. The enhanced ILC scheme using WTF was applied to track two desired trajectories, one with a single frequency and the other with multiple frequencies, respectively. Experimental results validate the efficacy of the enhanced ILC in terms of the speed of convergence and the level of long-term tracking errors.

The main objective of this study is to establish a virtual prototyping model of a flexible four-bar mechanism and perform co-simulations using both mechanism model construction and control strategy development tools for the structure. Taking the four-bar mechanism as an example, a co-simulation control approach is introduced to study multi-body flexible dynamics. Lagrange approach is first implemented to study the dynamics model of a rigid four-bar mechanism, and co-simulations are conducted to investigate the responses of its flexible form made of various materials. Then, controller strategies are exercised to demand the four-bar mechanism to response as requested. The study verifies the feasibility to control of flexible multi-body mechanisms' traces.

Extended Bond Graph (EBG) reticulations for general and linear piezoelectric continua are developed in this paper. The EBG formulation is especially advantageous for modeling the distributed coupled electromechanical effects of these materials and for combining this representation with other discrete models. The electromechanical coupling effects are represented by a multiport C-element for the general piezoelectric material. For linear constitutive properties, the coupling effects are represented by two multiport C-elements; one for the strain energy and the other for the capacitance storage, and a transformer that converts the power flows between the two energy domains. Details of the developments of the general formulation and of the specific models are provided. This work represents the first application of EBGs to electric fields.

Capacitive-micro-ultrasonic transducers (CMUT) are considered as prospective probes to replace traditional piezoelectric transducers for high frequency ultrasonic imaging. DC bias voltages are commonly employed to improve their signal/noise ratios and sensitivities. Since expansion limits of CMUT membranes are confined by the bias voltages, bias effects for CMUT devices are investigated and modeled in this research. Also, this research carries out fabrications based upon MEMS processes to prototype the CMUT devices, and describes the manufacturing procedures systematically.

The extended bond graph (EBG) method is used to model the distributed coupled magnetoelastic effects of general magnetostrictive continua. The mechanical and magnetic fields are described in terms of defined displacement and momentum states, and Galerkin’s discretization technique is applied to reticulate the dynamics of the fields into power flows which are defined as the inner products of extended efforts and flows. The power‐based EBG descriptions are consistently used to represent the discretized inertia, compliance, reluctance, coupled fields, and external sources of the magnetostrictive continua. The power bonds associated with the multienergetic fields are directed separately to the magnetic and mechanical energetic domains to enforce energy conservation laws. Details of the development of the general formulation for the model are provided. The EBG network model provides a unified way to analyze the coupling effects and dynamics of complex systems using general magnetostrictive continua.

The Extended Bond Graph (EBG) method is used to develop a network model for distributed electromechanical systems. The mechanical and magnetoquasistatic fields are written in terms of the defined displacement and momentum states, and Galerkin's method is used to reticulate the distributed systems into discrete power-based representations. Using these EBG descriptions, the energy storage, dissipation and external sources for the distributed systems are reticulated as multiport elements with associated power bonds. The EBG junction structures connecting the power bonds to these multiport elements are established for the mechanical and magnetoquasistatic energy modes by enforcing power balance principles. The coupling effects of the distributed electromechanical systems are also consistently reticulated into a power-based multi-energetic, multiport IC element to connect the two junction structures. The energy stored in this IC element is contributed to simultaneously by the electromechanically-induced distributed forces and currents. The power flows associated with these forces and currents are directed to each energetic domain to satisfy the power balance relations. The overall EBG network reticulation provides a unified way to model nonuniform mechanical and magnetoquasistatic fields in distributed electromechanical systems.

DC bias voltages are commonly employed in using capacitive micro-ultrasonic transducers (CMUT) for their signal/noise ratio and sensitivity improvements. On the other hand, deformations of CMUT membranes are usually limited by the applied biasing voltages. Bias effects for CMUTs are investigated and modeled in this research, whether the transducers are operating in their transmitting or receiving modes. As to model a multi-energetically coupled CMUT device, the DC bias voltage effects are first examined based upon conversion from electrical energetic domain into mechanical energetic domain. The bias is represented as mechanical impedance, which is integrated with a modified CMUT mechanical equivalent circuit model, and subsequently interfaced with an acoustic equivalent model. This innovative model is implemented to derive physical relations and transfer functions for CMUT transducers, when they work in transmitting or receiving modes through gas or fluid media.

The object of this research is to build an optical servo inspection system by integrating optical acquisition mechanisms and controlling algorithm to perform auto biomedical specimen inspections. The system applies a fuzzy control algorithm to exercise optical zooming, focusing, and sectioning functions on the inspected specimens. The paper also utilizes the MATLAB/SIMULINK platform to implement the fuzzy logic controller, and a NI multi-function data acquisition board to deliver control signals, which minutely displace the optical lenses system to execute prescribed functions. The optical system consists of an image focusing subsystem, which receives processed sharpness values of captured images, a con-focal pinhole aperture subsystem, which holds a pinhole to allow only light beams from in-focus plane specimen images to pass through, and a piezoactuator, which serves to minutely displace a plate with the pinhole to perform the optical biopsy function. As to accomplish the optical biopsy goal, the biomedical sample images on slightly differentiated focus depth planes are therefore acquired separately according to calculated image sharpness values.Copyright © 2010 by ASME

In this study, optical-mechatronical techniques are integrated to develop an embedded controller for BioCD image sample inspections. The Linux-based OS is loaded on an ARM platform to code the mandatory embedded controller functions, including image sharpness evaluations for feedback calculations, lenses-carried motor activations for magnifications or autofocusing, piezoactuator displacements for transected sample imaging, human-machine interfacing (graphic user interface, GUI) for accepting user instructions, and touch panel LCD displays for instant image realizations. The developed embedded controller has verified its performances in an experimental BioCD setup.

An optical inspection apparatus was prototyped for examining BioCD samples, and an automatic focusing mechanism using an embedded bio-image feedback mechanism was built in to control the focusing lenses system as to obtain adequate images on the image sensing chip, where sharpness of the captured images are evaluated and compared for subsequent motor movements. Over the motor course motion intervals, piezoactuator minute adjustments are henceforth triggered in fine movements to obtain clear images of the designated layer within inspected BioCD samples. The prototype is featured in its Linux OS based application on an ARM platform, which can execute a variety of servo-motions, including fine motions through implementing piezo-actuations, once the assistances of processed bio images are employed.

The object of this research is to develop a fully automatic computation algorithm for quality control purposes during inspecting color filters. The hardware setup can analyze dyed pixels on the color filters upon acquiring the transmiting-through light waves ranging from 350 nm to 850 nm and a light wavelength resolution up to 3.49 nm, once a micro-spectrometer is employed. With the acquitted information this research builds a quality inspection algorithm to analyze the color properties of the dyed pixels, and performs dedicated statistics computations of the color filters automatically. With the analysis results of the typical color filter, its color quality can be justified using the developed quality computation algorithm, and any defects of the pixels on a sampled filter can also be detected. Hence, the automatic inspection system can evaluate the statistics of the acquired information and identify the grade of the inspected ones in order to assure the quality of each fabricated color filer. .

The object of this research is to prototype a hybrid driving circuit (AC+DC) for nano-manipulation mechanisms employing piezoelectric actuators. The experimented analog driver is triggered by digital signals and commanded by a PC which is loaded with a graphic user interface code (GUI). The developed hybrid circuit can therefore precisely drive the piezoelectric actuators as to fulfill high resolution as well as high accuracy promises for nano-manipulation applications.

The object of this research is to prototype a precision system, which mainly consists of a piezoelectrically actuated cantilever beam structure as powered by an AC + DC hybrid driving circuit. Pulse width modulation (PWM) control algorithm as well as nonlinear tabulation are developed to capture characteristics of the specific hybrid driver and actuator, while dedicated driving techniques are elaborately explored for achieving fine motions of the beam. Enhanced apparatus such as a Doppler interferometer, a laser interferometer, and a conventional accelerometer are employed to quantify the dynamic as well as static deflections of the piezoactuator-driven structure. The experimental results validate the efficacy of the hybrid driver circuit as it is powering the piezoactuator-driven structure, and finite element method (FEM) approach also confirms the resonance frequency of the assembled mechanism.

The object of this paper is to establish a theoretic model for four-edge-clamped micro-pump membranes locally excited by electromagnetic forces. The studied membrane is to be fabricated as a 25 mum thick polyimide (PI) film, which includes a central portion of Ni-Fe metal layer. Its deflection distributions are formulated through ingenious modification and manipulations through available models, and theoretical solutions for the PI membrane with the prescribed particular boundary and load conditions are finally reached. Furthermore, coupled-field finite element (FEM) simulations for the membrane deflection distributions caused by the external electromagnetic field are also practiced. It is inspirational that errors between simulation results obtained from the FEM simulations and calculation outcomes from the novel approach are within 2%, which applies the same to the well-known ANSYS and COMSOL models.

This paper proposes a novel scheme of state compensated iterative learning control (ILC) for trajectory tracking of piezoelectric systems. The new ILC scheme adds a state compensation term to the conventional Arimoto-type ILC formula. The state compensation term is based on the difference of tracking error between the current and previous iterations. With the aid of this state compensation, iterative learning control can therefore take effect more precisely as desired. Further, the addition of the current error in the compensation term can also serve the role of feedback control to stabilize the system. The new ILC scheme keeps the simplicity feature of conventional iterative learning control that no model is required for control purpose. Experimental results demonstrate that a piezoelectric actuator using the proposed learning scheme can achieve error convergence in about three to five iterations, and keep steady-state tracking errors reaching the system noise level.

This paper presents the trajectory tracking approach of a piezoelectric actuator using an iterative learning control (ILC) scheme based on B-spline network (BSN) filtering. The ILC scheme adopts a state compensated iterative learning formula, which compensates for the state difference between two consecutive iterations so that the iterative learning can learn from the tracking errors of the previous iteration effectively. The BSN is used to attenuate the noises and retrieve the signals of the tracking errors for ILC. The BSN serves as a unique filter which generally does not have zero-phase responses. Design details on the ILC scheme using the BSN filtering are discussed in the paper. Experiments of tracking two desired trajectories on a piezoelectric actuator are presented. Experimental results show that the state compensated ILC scheme using the BSN filtering can achieve fast error convergence and keep small steady-state tracking errors close to the system noise level. This research relaxes the restriction of the zero-phase criterion commonly applied to ILC filtering in the literature.

The object of this research is to design and prototype a linear/rotary ultrasonic motor based upon multi-mode resonance behaviors for a piezoelectrically excited driver structure system. The whole ultrasonic motor system includes a pair of piezoactuator-equipped driver rods, a linear/rotary driven shaft, and a set of high-voltage power stages for energizing the piezoelectric stacks. The linear/rotary ultrasonic motor operating principle basically employs excited resonant modes of the driver structure as applying selected AC frequencies on the equipped piezostacks. Therefore, the prescribed combinational resonant modes of the driver structure result in the driven shaft operating in linear or rotary motions

A 2DOF ultrasonic motor structure is designed and simulated using finite element method (FEM) in this study. The ultrasonic motor structure is consist of two resonant driver rods and one driven shaft between. Each driver rod is equipped with four stacked piezoelectric actuators to perform resonant functions. Different resonant modes of the driver rods, the driven shaft, and the overall assembly would be excited to conduct different motion characteristics. Preload and non-preload conditions for the driver rods are studied as well, and assembly of a half portion or an overall ultrasonic motor structure are simulated considering contact and constraint boundaries as well. The adequate resonant modes to perform the driven shaft's liner and rotary motion, respectively, arc calculated and tabulated in this study.

This paper presents an application of system identification technique to tracking control of a piezoelectric system. An iterative scheme of identification and control design is introduced, and its corresponding application is described. Based on the estimated model of the system, a fine-tuning co-controller was built and adjusted in an iterative approach. The experiment results prove the excellence of this technique for delicate tracking control of the piezoelectric actuator.

An engine dynamic model is established in this research based upon theoretic approach and supplement of acquired engine experiment data using a dynamometer setup. Experiment data are employed to obtain relations among throttle valve opening, inject fuel amount, ignition timing, air/fuel ratio, engine speed and generated torque using curve-fitting techniques. Consequently, air intake and generated engine torque subsystem models are developed for simulations using MATLAB/SimuLink tool. Hence, the developed model could be excised to investigate steady state as well as transient performances of certain engines. The long-term object of this research is to prototype motorcycle engine fuel injection systems and to improve the control strategy for the engines developed in Taiwan.

A general model for fuel injection valves using multilayer electrostrictive materials actuators is established. Based upon finite element approach, the model describes the dynamic behaviors of the multilayer electrostrictive actuators and correlates with dynamics of other lumped-parameter components to form overall system state equations for the fuel injector. Simulations are performed for the system using LiF, RbI, and NaF electrostrictive materials with different number of layers to form the actuators.

A novel approach is developed to study a film-overlapped membrane structure. Meanwhile, the established model is employed to design the micro-pump membrane structure and to evaluate its pumping efficiency. Two-dimensional coupling effects between the overlapping actuator films and the deformable membrane are thoroughly investigated, including the influences on the membrane from the overlapping films' elongation effects, Poisson's ratio effects and shear strain effects. Overall deformations and interactions for the three-layer membrane structures are accurately calculated through exercising the developed model, in contrast to what difficulties are usually encountered in carrying out FEM methods with very thin elements meshed for the actuator films. Furthermore, this study demonstrates that the high stiffness of the actuating metal films needs to be reflected in the equivalent stiffness of the membrane structures, especially when the sizes of the actuator films become compatible with the sizes of the membranes. Hence, the optimal micro-pumping efficiency of a membrane structure is acquired upon exercising the developed model, and larger sizes of the actuating films do not definitely obtain larger pumping efficiencies for the electromagnetically actuated micro-pumps.

The amino acid sequence of human lecithin:cholesterol acyltransferase has been determined by degradation and alignment of peptides obtained from tryptic and staphylococcal digestions and the cleavage with cyanogen bromide and consisted of 416 amino acid residues. All of the tryptic peptides of lecithin:cholesterol acyltransferase were isolated and sequenced. Peptides resulting from digestion by staphylococcal protease, cyanogen bromide cleavage, or the combination of the two methods were employed to find overlapping segments. The N terminus of human lecithin:cholesterol acyltransferase was determined to be phenylalanine by sequencing the whole protein up to 40 residues while the C terminus was identified as glutamic acid through carboxypeptidase Y cleavage. Cys50 and Cys74 and Cys313 and Cys356 were identified as the two disulfide bridges while the free sulfhydryl groups were located at positions 31 and 184. The N-glycosylated sites of the protein were assigned to asparagines at positions 20, 84, 272, and 384. The active site of lecithin:cholesterol acyltransferase was identified as serine on position 181 according to its homology with other serine-type esterases which have a common structure of glycine-variable amino acid-active serine-variable amino acid-glycine (Gly-X-Ser-X-Gly) with the variable amino acids disrupting the homology. No long internal repeats or homologies with apolipoproteins were found. The secondary structure is consistent with the results of predictive algorithms. A simple model of the enzyme is proposed on the basis of available chemical data and predictive methods.

Apolipoprotein (apo) B-100, the major protein component in low density lipoprotein (LDL), is the ligand that binds to the LDL receptor. It is important in the metabolism of LDL and elevated plasma levels of LDL-apo B are strongly associated with increased risk of coronary artery disease. Although apo B-100 is of great clinical and biological importance its primary structure has defied chemical elucidation, mainly because of its enormous size, insolubility, and tendency to aggregate. Less than 5% of the apo B-100 sequence has been reported, despite the efforts of many laboratories over the past twenty years. Here we report the complete amino acid sequence of human apo B-100 as deducted by sequence analysis of complementary DNA clones; 2,366 of the 4,536 residues were also confirmed by direct sequencing of apo B-100 tryptic peptides. The distribution of trypsin-accessible and -inaccessible peptides of the protein on LDL is non-random and they can be grouped into 5 hypothetical domains. Of 20 potential N-glycosylation sites identified in the sequence, 13 were found by direct peptide sequencing to be glycosylated, and 4 unglycosylated. Examination of the primary structure of apo B-100 reveals that it contains a large number of long (greater than 70 residues) internal repeats and an even larger number of shorter ones, suggesting that the apo B-100 sequence was derived largely from internal duplications. Finally, using synthetic peptides of a specific region of apo B-100, we have identified a potential LDL receptor-binding domain (residues 3,345-3,381) which can bind to the LDL receptor and suppress 3-hydroxy-3-methyl-glutaryl coenzyme A (HMG-CoA) reductase activities in cultured human fibroblasts.