Threshold learning algorithm for memristive neural network with binary switching behavior.

On-chip learning is an effective method for adjusting artificial neural networks in neuromorphic computing systems by considering hardware intrinsic properties. However, it faces challenges due to hardware nonidealities, such as the nonlinearity of potentiation and depression and limitations on fine weight adjustment. In this study, we propose a threshold learning algorithm for a variation-tolerant ternary neural network in a memristor crossbar array. This algorithm utilizes two tightly separated resistance states in memristive devices to represent weight values. The high-resistance state (HRS) and low-resistance state (LRS) defined as read current of < 0.1 µA and > 1 µA, respectively, were successfully programmed in a 32 × 32 crossbar array, and exhibited half-normal distributions due to the programming method. To validate our approach experimentally, a 64 × 10 single-layer fully connected network were trained in the fabricated crossbar for an 8 × 8 MNIST dataset using the threshold learning algorithm, where the weight value is updated when a gradient determined by backpropagation exceeds a threshold value. Thanks to the large margin between the two states of the memristor, we observed only a 0.42 % drop in classification accuracy compared to the baseline network results. The threshold learning algorithm is expected to alleviate the programming burden and be utilized in variation-tolerant neuromorphic architectures.

Realization of Multiple Synapse Plasticity by Coexistence of Volatile and Nonvolatile Characteristics of Interface Type Memristor.

Studies on neuromorphic computing systems are becoming increasingly important in the big-data-processing era as these systems are capable of energy-efficient parallel data processing and can overcome the present limitations owing to the von Neumann bottleneck. The Pt/WOx/ITO resistive random-access memory device can be used to implement versatile synapse functions because it possesses both volatile and nonvolatile characteristics. The gradual increase and decrease in the current of the Pt/WOx/ITO device with its uniform resistance state for endurance and retention enables additional synaptic applications that can be controlled using electric pulses. If the volatile and nonvolatile device properties are set through rehearsal and forgetting processes, the device can emulate various synaptic behaviors, such as potentiation and depression, paired-pulse facilitation, post-tetanic potentiation, image training, Hebbian learning rules, excitatory postsynaptic current, and Pavlov's test. Furthermore, reservoir computing can be implemented for applications such as pattern generation and recognition. This emphasizes the various applications of future neuromorphic devices, demonstrating the various favorable characteristics of pulse-enhanced Pt/WOx/ITO devices.

Programmable Threshold Logic Implementations in a Memristor Crossbar Array.

In this study, we demonstrate the implementation of programmable threshold logics using a 32 × 32 memristor crossbar array. Thanks to forming-free characteristics obtained by the annealing process, its accurate programming characteristics are presented by a 256-level grayscale image. By simultaneous subtraction between weighted sum and threshold values with a differential pair in an opposite way, 3-input and 4-input Boolean logics are implemented in the crossbar without additional reference bias. Also, we verify a full-adder circuit and analyze its fidelity, depending on the device programming accuracy. Lastly, we successfully implement a 4-bit ripple carry adder in the crossbar and achieve reliable operations by read-based logic operations. Compared to stateful logic driven by device switching, a 4-bit ripple carry adder on a memristor crossbar array can perform more reliably in fewer steps thanks to its read-based parallel logic operation.

Implementation of Convolutional Neural Networks in Memristor Crossbar Arrays with Binary Activation and Weight Quantization.

We propose a hardware-friendly architecture of a convolutional neural network using a 32 × 32 memristor crossbar array having an overshoot suppression layer. The gradual switching characteristics in both set and reset operations enable the implementation of a 3-bit multilevel operation in a whole array that can be utilized as 16 kernels. Moreover, a binary activation function mapped to the read voltage and ground is introduced to evaluate the result of training with a boundary of 0.5 and its estimated gradient. Additionally, we adopt a fixed kernel method, where inputs are sequentially applied to a crossbar array with a differential memristor pair scheme, reducing unused cell waste. The binary activation has robust characteristics against device state variations, and a neuron circuit is experimentally demonstrated on a customized breadboard. Thanks to the analogue switching characteristics of the memristor device, the accurate vector-matrix multiplication (VMM) operations can be experimentally demonstrated by combining sequential inputs and the weights obtained through tuning operations in the crossbar array. In addition, the feature images extracted by VMM during the hardware inference operations on 100 test samples are classified, and the classification performance by off-chip training is compared with the software results. Finally, inference results depending on the tolerance are statistically verified through several tuning cycles.

Discovery of Orally Bioavailable Phthalazinone Analogues as an ENPP1 Inhibitor for STING-Mediated Cancer Immunotherapy.

A lack of the T cell-inflamed tumor microenvironment limits the efficacy of immune checkpoint inhibitors (ICIs). Activation of stimulator of interferon genes (STING)-mediated innate immunity has emerged as a novel therapeutic approach in cancer therapy. 2',3'-Cyclic GMP-AMP (cGAMP) is a natural STING agonist; however, cGAMP is subjected to endogenous degradation by ecto-nucleotide pyrophosphatase phosphodiesterase 1 (ENPP1). To improve the ICI response rate, we developed 29f, a novel ENPP1 inhibitor with phthalazin-1(2H)-one as the core scaffold. 29f inhibited the cGAMP hydrolysis by ENPP1 in vitro (IC50 = 68 nM) and enhanced the STING-mediated type I interferon response in both immune and tumor cells. 29f demonstrated excellent metabolic stability and bioavailability (F = 65%). Orally administered 29f promoted tumor growth inhibition in a CT26 syngeneic model and increased the anti-PD-L1 response. Furthermore, 29f-induced immunological memory prevented the tumor relapse against tumor rechallenge, suggesting the promising therapeutic potential of 29f.

Correction: Synaptic plasticity and non-volatile memory characteristics in TiN-nanocrystal-embedded 3D vertical memristor-based synapses for neuromorphic systems.

Correction for 'Synaptic plasticity and non-volatile memory characteristics in TiN-nanocrystal-embedded 3D vertical memristor-based synapses for neuromorphic systems' by Seyeong Yang et al., Nanoscale, 2023, https://doi.org/10.1039/D3NR01930F.

Synaptic plasticity and non-volatile memory characteristics in TiN-nanocrystal-embedded 3D vertical memristor-based synapses for neuromorphic systems.

Although vertical configurations for high-density storage require challenging process steps, such as etching high aspect ratios and atomic layer deposition (ALD), they are more affordable with a relatively simple lithography process and have been employed in many studies. Herein, the potential of memristors with CMOS-compatible 3D vertical stacked structures of Pt/Ti/HfOx/TiN-NCs/HfOx/TiN is examined for use in neuromorphic systems. The electrical characteristics (including I-V properties, retention, and endurance) were investigated for both planar single cells and vertical resistive random-access memory (VRRAM) cells at each layer, demonstrating their outstanding non-volatile memory capabilities. In addition, various synaptic functions (including potentiation and depression) under different pulse schemes, excitatory postsynaptic current (EPSC), and spike-timing-dependent plasticity (STDP) were investigated. In pattern recognition simulations, an improved recognition rate was achieved by the linearly changing conductance, which was enhanced by the incremental pulse scheme. The achieved results demonstrated the feasibility of employing VRRAM with TiN nanocrystals in neuromorphic systems that resemble the human brain.

Thermodynamics and Kinetics in Anisotropic Growth of One-Dimensional Midentropy Nanoribbons.

One-dimensional (1D) materials demonstrate anisotropic in-plane physical properties that enable a wide range of functionalities in electronics, photonics, valleytronics, optoelectronics, and catalysis. Here, we undertake an in-depth study of the growth mechanism for equimolar midentropy alloy of (NbTaTi)0.33S3 nanoribbons as a model system for 1D transition metal trichalcogenide structures. To understand the thermodynamic and kinetic effects in the growth process, the energetically preferred phases at different synthesis temperatures and times are investigated, and the phase evolution is inspected at a sequence of growth steps. It is uncovered that the dynamics of the growth process occurs at four different stages via preferential incorporation of chemical species at high-surface-energy facets. Also, a sequence of temperature and time dependent nonuniform to uniform phase evolutions has emerged in the composition and structure of (NbTaTi)0.33S3 which is described based on an anisotropic vapor-solid (V-S) mechanism. Furthermore, direct evidence for the 3D structure of the charge density wave (CDW) phase (width less than 100 nm) is provided by three-dimensional electron diffraction (3DED) in individual nanoribbons at cryogenic temperature, and detailed comparisons are made between the phases obtained before and after CDW transformation. This study provides important fundamental information for the design and synthesis of future 1D alloy structures.

Intrinsic variation effect in memristive neural network with weight quantization.

To analyze the effect of the intrinsic variations of the memristor device on the neuromorphic system, we fabricated 32 × 32 Al2O3/TiOx-based memristor crossbar array and implemented 3 bit multilevel conductance as weight quantization by utilizing the switching characteristics to minimize the performance degradation of the neural network. The tuning operation for 8 weight levels was confirmed with a tolerance of ±4µA (±40µS). The endurance and retention characteristics were also verified, and the random telegraph noise (RTN) characteristics were measured according to the weight range to evaluate the internal stochastic variation effect. Subsequently, a memristive neural network was constructed by off-chip training with differential memristor pairs for the Modified National Institute of Standards and Technology (MNIST) handwritten dataset. The pre-trained weights were quantized, and the classification accuracy was evaluated by applying the intrinsic variations to each quantized weight. The intrinsic variations were applied using the measured weight inaccuracy given by the tuning tolerance, RTN characteristics, and the fault device yield. We believe these results should be considered when the pre-trained weights are transferred to a memristive neural network by off-chip training.

Analytically and empirically consistent characterization of the resistive switching mechanism in a Ag conducting-bridge random-access memory device through a pseudo-liquid interpretation approach.

A new physical analysis of the filament formation in a Ag conducting-bridge random-access memory (CBRAM) device in consideration of the existence of inter-atomic attractions caused by metal bonding is suggested. The movement of Ag atoms inside the switching layer is characterized hydrodynamically using the Young-Laplace equation during set and reset operations. Both meridional and azimuthal curvatures of the Ag filament protruding from the Ag electrode are accurately calculated to track down the exact shape of the Ag filament with change in the applied voltage. The second-order partial differential equation for the Ag filament geometry is derived from the equation of equilibrium between the electrostatic pressure and the Laplace one. The solution to the equation is numerically obtained, and furthermore, the abrupt set operation in the forming process, bipolar resistive-switching, and the threshold switching operation in the reset operations are successfully simulated in accordance with the numerical solutions. Also, it is demonstrated that the currents extracted from the suggested model show good agreement with the I-V characteristics measured from the fabricated Ag CBRAM device.

Improving Generation of Cardiac Organoids from Human Pluripotent Stem Cells Using the Aurora Kinase Inhibitor ZM447439.

Drug-induced cardiotoxicity reduces the success rates of drug development. Thus, the limitations of current evaluation methods must be addressed. Human cardiac organoids (hCOs) derived from induced pluripotent stem cells (hiPSCs) are useful as an advanced drug-testing model; they demonstrate similar electrophysiological functionality and drug reactivity as the heart. How-ever, similar to other organoid models, they have immature characteristics compared to adult hearts, and exhibit batch-to-batch variation. As the cell cycle is important for the mesodermal differentiation of stem cells, we examined the effect of ZM447439, an aurora kinase inhibitor that regulates the cell cycle, on cardiogenic differentiation. We determined the optimal concentration and timing of ZM447439 for the differentiation of hCOs from hiPSCs and developed a novel protocol for efficiently and reproducibly generating beating hCOs with improved electrophysiological functionality, contractility, and yield. We validated their maturity through electro-physiological- and image-based functional assays and gene profiling with next-generation sequencing, and then applied these cells to multi-electrode array platforms to monitor the cardio-toxicity of drugs related to cardiac arrhythmia; the results confirmed the drug reactivity of hCOs. These findings may enable determination of the regulatory mechanism of cell cycles underlying the generation of iPSC-derived hCOs, providing a valuable drug testing platform.

Effects of mobile phone usage on sperm quality - No time-dependent relationship on usage: A systematic review and updated meta-analysis.

BACKGROUND: Mobile phones emit radiofrequency (RF) electromagnetic waves (EMWs), a low-level RF that can be absorbed by the human body and exert potential adverse effects on the brain, heart, endocrine system, and reproductive function. Owing to the novel findings of numerous studies published since 2012 regarding the effect of mobile phone use on sperm quality, we conducted a systematic review and updated meta-analysis to determine whether the exposure to RF-EMWs affects human sperm quality. METHODS: This study was conducted in accordance with the PRISMA guidelines. The outcome measures depicting sperm quality were motility, viability, and concentration, which are the most frequently used parameters in clinical settings to assess fertility. RESULTS: We evaluated 18 studies that included 4280 samples. Exposure to mobile phones is associated with reduced sperm motility, viability, and concentration. The decrease in sperm quality after RF-EMW exposure was not significant, even when the mobile phone usage increased. This finding was consistent across experimental in vitro and observational in vivo studies. DISCUSSION: Accumulated data from in vivo studies show that mobile phone usage is harmful to sperm quality. Additional studies are needed to determine the effect of the exposure to EMWs from new mobile phone models used in the present digital environment.

Dual Mechanisms of Cardiac Action Potential Prolongation by 4-Oxo-Nonenal Increasing the Risk of Arrhythmia; Late Na+ Current Induction and hERG K+ Channel Inhibition.

4-Oxo-nonenal (4-ONE) is an endogenous lipid peroxidation product that is more reactive than 4-hydroxy-nonenal (4-HNE). We previously reported the arrhythmic potential of 4-HNE by suppression of cardiac human Ether-a-go-go Related Gene (hERG) K+ channels with prolonged action potential duration (APD) in cardiomyocytes. Here, we illustrate the higher arrhythmic risk of 4-ONE by modulating the cardiac hNaV1.5 channel currents (INaV). Although the peak amplitude of INaV was not significantly changed by 4-ONE up to 10 µM, the rate of INaV inactivation was slowed, and the late Na+ current (INaL) became larger by 10 µM 4-ONE. The chemical modification of specific residues in hNaV1.5 by 4-ONE was identified using MS-fingerprinting analysis. In addition to the changes in INaV, 4-ONE decreased the delayed rectifier K+ channel currents including the hERG current. The L-type Ca2+ channel current was decreased, whereas its inactivation was slowed by 4-ONE. The APD prolongation by 10 µM of 4-ONE was more prominent than that by 100 µM of 4-HNE. In the computational in silico cardiomyocyte simulation analysis, the changes of INaL by 4-ONE significantly exacerbated the risk of arrhythmia exhibited by the TdP marker, qNet. Our study suggests an arrhythmogenic effect of 4-ONE on cardiac ion channels, especially hNaV1.5.

Visual Field Inference From Optical Coherence Tomography Using Deep Learning Algorithms: A Comparison Between Devices.

Purpose: To develop a deep learning model to estimate the visual field (VF) from spectral-domain optical coherence tomography (SD-OCT) and swept-source OCT (SS-OCT) and to compare the performance between them. Methods: Two deep learning models based on Inception-ResNet-v2 were trained to estimate 24-2 VF from SS-OCT and SD-OCT images. The estimation performance of the two models was evaluated by using the root mean square error between the actual and estimated VF. The performance was also compared among different glaucoma severities, Garway-Heath sectorizations, and central/peripheral regions. Results: The training dataset comprised images of 4391 eyes from 2350 subjects, and the test dataset was obtained from another 243 subjects (243 eyes). In all subjects, the global estimation errors were 5.29 ± 2.68 dB (SD-OCT) and 4.51 ± 2.54 dB (SS-OCT), and the estimation error of SS-OCT was significantly lower than that of SD-OCT (P < 0.001). In the analysis of sectors, SS-OCT showed better performance in all sectors except for the inferonasal sector in normal vision and early glaucoma. In advanced glaucoma, the estimation error of the central region was worsened in both OCTs, but SS-OCT was still significantly better in the peripheral region. Conclusions: Our deep learning model estimated the VF 24-2 better with a wide field image of SS-OCT than did with retinal nerve fiber layer and ganglion cell-inner plexiform layer images of SD-OCT. Translational Relevance: This deep learning method can help clinicians to determine the VF from OCT images. OCT manufacturers can equip this system to provide additional VF data.

COVID-19 Spike Protein Induced Phononic Modification in Antibody-Coupled Graphene for Viral Detection Application.

With an incubation time of about 5 days, early diagnosis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is critical to control the spread of the coronavirus disease 2019 (COVID-19) that killed more than 3 million people in its first 1.5 years. Here, we report on the modification of the dopant density and the phononic energy of antibody-coupled graphene when it interfaces with SARS-CoV-2 spike protein. This graphene chemeo-phononic system was able to detect SARS-CoV-2 spike protein at the limit of detection of ∼3.75 and ∼1 fg/mL in artificial saliva and phosphate-buffered saline, respectively. It also exhibited selectivity over proteins in saliva and MERS-CoV spike protein. Since the change in graphene phononics is monitored instead of the phononic signature of the analyte, this optical platform can be replicated for other COVID variants and specific-binding-based biodetection applications.

3-bit multilevel operation with accurate programming scheme in TiOx/Al2O3memristor crossbar array for quantized neuromorphic system.

As interest in artificial intelligence (AI) and relevant hardware technologies has been developed rapidly, algorithms and network structures have become significantly complicated, causing serious power consumption issues because an enormous amount of computation is required. Neuromorphic computing, a hardware AI technology with memory devices, has emerged to solve this problem. For this application, multilevel operations of synaptic devices are important to imitate floating point weight values in software AI technologies. Furthermore, weight transfer methods to desired weight targets must be arranged for off-chip training. From this point of view, we fabricate 32 × 32 memristor crossbar array and verify the 3-bit multilevel operations. The programming accuracy is verified for 3-bit quantized levels by applying a reset-voltage-control programming scheme to the fabricated TiOx/Al2O3-based memristor array. After that, a synapse composed of two differential memristors and a fully-connected neural network for modified national institute of standards and technology (MNIST) pattern recognition are constructed. The trained weights are post-training quantized in consideration of the 3-bit characteristics of the memristor. Finally, the effect of programming error on classification accuracy is verified based on the measured data, and we obtained 98.12% classification accuracy for MNIST data with the programming accuracy of 1.79% root-mean-square-error. These results imply that the proposed reset-voltage-control programming scheme can be utilized for a precise tuning, and expected to contribute for the development of a neuromorphic system capable of highly precise weight transfer.

Efficiency of magnetic resonance imaging for diagnosing unstable ligament injuries around the thumb metacarpophalangeal joint: A comparison to arthroscopy.

PURPOSE: This study aimed to assess the accuracy of MRI in identifying ulnar collateral ligament (UCL), radial collateral ligament (RCL), and volar plate (VP) injuries of the metacarpophalangeal joint (MCPJ) of the thumb by comparing with diagnostic arthroscopy. METHODS: A total of 56 consecutive patients (56 thumbs) who underwent arthroscopy of MCPJ of thumb were enrolled. MRI findings reviewed by consensus reading of two blinded radiologists were compared with arthroscopic examination. Statistical data, including sensitivity, specificity, accuracy, were analyzed. Additionally, the performance characteristics between 3.0-tesla (39 thumbs) and 1.5-tesla (17 thumbs) MRI and acute (≤4 weeks after injury) and chronic (>4 weeks) injuries were compared. RESULTS: Of the 56 thumbs, 38 thumbs (67.9%) showed complete correspondence between MRI and arthroscopic findings. The sensitivity, specificity and accuracy of MRI for detecting UCL injuries were 78.8%, 87.0%, and 82.1%, respectively. The sensitivity, specificity and accuracy of MRI for detecting RCL injuries were 85.7%, 91.4%, and 85.7%, respectively. The sensitivity, specificity, and accuracy of MRI for detecting VP injuries were 89.5%, 89.2%, and 81.0%, respectively. 3.0-tesla MRI showed higher correspondence with arthroscopic observation (76.9%) than 1.5-tesla MRI (47.1%) (p = 0.028). For acute injuries, 78.4% showed complete correspondence between MRI and arthroscopic findings, whereas 47.4% with chronic injuries revealed complete agreement (p = 0.019). CONCLUSION: Overall, MRI is moderately effective in evaluating ligamentous lesions around MCPJ of thumb, but MRI is more sensitive in diagnosing acute injuries. Furthermore, 3.0-tesla MRI can provide results with better accuracy for diagnosing ligamentous lesions around MCPJ of thumb. However, the sensitivity and the specificity are not applicable to all ligament injuries, but only the severe one which would agree for surgical options.

Performance Validation of a Planar Hall Resistance Biosensor through Beta-Amyloid Biomarker.

Magnetic sensors have great potential for biomedical applications, particularly, detection of magnetically-labeled biomolecules and cells. On the basis of the advantage of the planar Hall effect sensor, which consists of improved thermal stability as compared with other magnetic sensors, we have designed a portable biosensor platform that can detect magnetic labels without applying any external magnetic field. The trilayer sensor, with a composition of Ta (5 nm)/NiFe (10 nm)/Cu (x = 0 nm~1.2 nm)/IrMn (10 nm)/Ta (5 nm), was deposited on a silicon wafer using photolithography and a sputtering system, where the optimized sensor sensitivity was 6 µV/(Oe∙mA). The detection of the magnetic label was done by comparing the signals obtained in first harmonic AC mode (1f mode) using an external magnetic field and in the second harmonic AC mode (2f mode) with a self-field generated by current passing through the sensor. In addition, a technique for the ß-amyloid biomarker-based antibody-antigen sandwich model was demonstrated for the detection of a series of concentrations of magnetic labels using the self-field mode method, where the signal-to-noise ratio (SNR) was high. The generated self-field was enough to detect an immobilized magnetic tag without an additional external magnetic field. Hence, it could be possible to reduce the device size to use the point-of-care testing using a portable circuit system.

New predictors for subscapularis tear: Coraco-lesser tuberosity angle, lesser tuberosity angle, and lesser tuberosity height.

BACKGROUND: The pathogenesis of degenerative subscapularis (SC) tear is not clear, several mechanisms are involved: intrinsic tendon degeneration or subcoracoid impingement. The aim of this study was to propose new radiographic markers, the coraco-lesser tuberosity angle (CLA), lesser tuberosity angle (LTA) and lesser tuberosity height (LTH). The hypothesis was that higher values of CLA, LTA, and LTH would be associated with a higher likelihood in detecting a SC tear. METHOD: A total of 114 patients who classified as SC tears through arthroscopic evaluation were retrospectively enrolled in the study from 2016 to 2018. Fifty-seven patients with impingement syndrome were also enrolled as the control group for normal-population comparison. The CLA was measured on an anteroposterior shoulder x-ray image with the arm in neutral rotation, the LTA and LTH were measured on magnetic resonance imaging. Multivariable analyses were used to clarify the potential risks for SC tears. All measurements were calculated by two shoulder surgeons independently measured at 2 different times, 1 month apart. RESULTS: The intra- and inter-observer reliabilities for radiologic measurements and the interobserver reliability of SC tear classification were almost perfect. The mean CLA value of SC tear group (41.4±4.2°) was significantly larger than that of the control group (38.7±4.0°, p<0.001). The mean LTA value of SC tear group (33.4±4.3°) was significantly larger than that of the control group (31.0±3.9°, p=0.001). Mean LTH value was 9.5±1.9mm in patients and 8.9±1.5mm for controls, there was no statistically significant difference (p=0.054). Multivariable analysis showed that larger CLAs significantly increased the risk of SC tears, with odds ratios of 1.17 per degree. Moreover, larger LTAs also significantly increased the risk of SC tears, with odds ratios of 1.14 per degree. CONCLUSION: Our findings confirmed associations between new predictors (CLA and LTA) and SC tears. CLA and LTA values were greater in patients with SC tears than in controls, suggesting that they may be independent risk factors for SC tear onset. LEVEL OF EVIDENCE: IV, retrospective study.

Color changes of ceramic veneers following glazing with respect to their composition.

PURPOSE: The purpose of this study was to compare the translucency and color changes of ceramic laminate veneers of different composition following glazing process. MATERIALS AND METHODS: 10 mm × 10 mm square specimens of 0.6 mm and 1.0 mm thicknesses were fabricated with IPS e.max Press (EM) and IPS e.max ZirPress (ZP) (n=10 per group). The color coordinates (CIE L* a* b*) of the specimens were recorded with a colorimeter before and after glazing. The color changes and translucency parameter (TP) were calculated. For the comparisons with the composition and thicknesses between the 'not glazed' and 'glazed' groups, statistical analyses were done through paired T-test, independent two-sample T-test, and multiple regression analysis using SPSS 18.0 (P<.05). RESULTS: The TP of 0.6 mm EM was higher than that of 0.6 mm ZP. Total color difference (ΔE*) between bare and glazed specimens of 1.0 mm EM was greater than that of 1.0 mm ZP with statistical significance. Following glazing, specimens from all groups showed statistically significant amount of decrease in L* and a*, and statistically significant increase in b*. The result of multiple regression analysis of EM and ZP showed that ΔL* improved ΔE*. CONCLUSION: Within the limitations of present study, we conclude that translucency and color of ceramic laminate veneers change significantly after glazing process, and the nature and amount of changes vary with different compositions.