Fasting State Research Articles

The optimization, design and performance of the FBCM23 ASIC for the upgraded CMS beam monitoring system

We present the development of the FBCM23 ASIC designed for the Phase-II upgrade of the Fast Beam Condition Monitoring (FBCM) system built at the CMS experiment which will replace the present luminometer based on the BCM1F ASIC [1]. The FBCM system should provide reliable luminosity measurement with 1 ns time resolution enabling the detection of beam-induced background. The FBCM23 ASIC comprises 6 channels of the fast front-end amplifier working in transimpedance configuration, booster amplifier, and leading edge discriminator. The complete processing chain provides an overall shaping function equivalent to the CR-RC3 filter. The paper will show the optimization of the design, overall architecture, and the detailed implementation in a CMOS 65 nm process as well as preliminary electrical performance.

Differences between repeated lipid profile measurements in a tertiary hospital over a short time period

BackgroundMeasurement of the plasma lipid profile, mainly low-density lipoprotein cholesterol (LDL-C), is widely used in the management of hospitalized patients as part of their cardiometabolic risk assessment. In common practice, LDL-C is calculated indirectly by the Friedewald equation. For many years, fasting of 8–14 h is needed to obtain an accurate lipid profile measurement, although recent guidelines do not necessitate it. The aim of this study was to find patients with two consecutive LDL-C measurements taken over a short time period on the same admission to see if a significant difference exists and to suggest reasons that may explain it. We also aim to define whether the difference between LDL-C calculated by the Friedewald equation is diminished while using the newer Martin/Hopkins, de Cordova or Sampson/NIH equations.MethodsThis was a retrospective cohort study performed in one medical center in Israel. In a five-year time period, 772 patients with two repeated LDL-C measurements taken on the same admission were found. The median time gap between tests was 2 days. Correlations between laboratory results and LDL-C measurements were determined.ResultsA total of 414 patients (53.6%) had a difference greater than the acceptable total error of 8.9% in LDL-C calculation using the Friedewald equation, with a mean 25.8% difference between the two tests. Newer LDL-C calculations showed less diversity. Non-HDL-C was found as the only variable with a major correlation with LDL-C results in all equations. A weaker correlation was found with HDL-C. Triglycerides showed an even weaker correlation, and glucose differences had no correlation with LDL-C differences.ConclusionsRepeated LDL-C measurements can vary widely, even during a short period of hospitalization. In this study, more than half of the patients had a significant difference between their consecutive LDL-C results. This wide difference between two consecutive tests was diminished using newer calculations, yet not well explained. The fasting state likely has no effect on LDL-C levels. The results of this study might emphasize that many factors influence LDL-C calculation, especially in the disease state. Further research is needed, especially in looking for a more accurate LDL-C calculation from existing formulas.

Trajectory Data-Driven Network Representation for Traffic State Prediction using Deep Learning

In this study, we propose a trajectory data-driven network representation method, specifically leveraging directional statistics. This approach allows us to extract major intersections and define links from observed trajectories, thereby mitigating the reliance on existing network data and map matching. We apply Graph Convolutional Networks and Long-Short Term Memory models to the trajectory data-driven network representation, suggesting the potential for fast and accurate traffic state prediction. The results imply significant reduction in computational complexity while demonstrating promising prediction accuracy. Our proposed method offers a valuable approach for analyzing and modeling transportation networks using real-world trajectory data, providing insights into traffic patterns and facilitating the exploration of more efficient traffic management strategies.

Lipid-based Nutritional Supplement Impact on Energy Intake, Appetite, Glucose and Insulin Levels in Under-Weight Pregnant and Lactating Women with Preeclampsia.

To investigate the response of nutritional supplement (LNS-PLW) on appetite score, energy intake, insulin and glucose levels in preeclamptic women. Sixty under-weight preeclamptic primigravida were divided into two groups randomly and provided LNS-PLW/Placebo in the fasted state. Blood samples were collected at fasting state, after 30mins of supplementation, "ad libitum buffet" breakfast and lunch for glucose and insulin levels. Total energy intake was higher significantly in the LNS-PLW group, although during breakfast it was significantly reduced. The insulin and glucose concentration was significantly increased after 30min of supplementation in the LNS-PLW group. Intake of the LNS-PLW by pre-eclamptic women had short-term suppression on subsequent meal but improved total energy intake during trial.

An auditory perspective on phonological development in infancy.

The auditory system encodes the phonetic features of languages by processing spectro-temporal modulations in speech, which can be described at two time scales: relatively slow amplitude variations over time (AM, further distinguished into the slowest <8-16 Hz and faster components 16-500 Hz), and frequency modulations (FM, oscillating at higher rates about 600-10 kHz). While adults require only the slowest AM cues to identify and discriminate speech sounds, infants have been shown to also require faster AM cues (>8-16 Hz) for similar tasks. Using an observer-based psychophysical method, this study measured the ability of typical-hearing 6-month-olds, 10-month-olds, and adults to detect a change in the vowel or consonant features of consonant-vowel syllables when temporal modulations are selectively degraded. Two acoustically degraded conditions were designed, replacing FM cues with pure tones in 32 frequency bands, and then extracting AM cues in each frequency band with two different low-pass cut- off frequencies: (1) half the bandwidth (Fast AM condition), (2) <8 Hz (Slow AM condition). In the Fast AM condition, results show that with reduced FM cues, 85% of 6-month-olds, 72.5% of 10-month-olds, and 100% of adults successfully categorize phonemes. Among participants who passed the Fast AM condition, 67% of 6-month-olds, 75% of 10-month-olds, and 95% of adults passed the Slow AM condition. Furthermore, across the three age groups, the proportion of participants able to detect phonetic category change did not differ between the vowel and consonant conditions. However, age-related differences were observed for vowel categorization: while the 6- and 10-month-old groups did not differ from one another, they both independently differed from adults. Moreover, for consonant categorization, 10-month-olds were more impacted by acoustic temporal degradation compared to 6-month-olds, and showed a greater decline in detection success rates between the Fast AM and Slow AM conditions. The degradation of FM and faster AM cues (>8 Hz) appears to strongly affect consonant processing at 10 months of age. These findings suggest that between 6 and 10 months, infants show different developmental trajectories in the perceptual weight of speech temporal acoustic cues for vowel and consonant processing, possibly linked to phonological attunement.

Intelligent electric vehicle charging optimization and horse herd-inspired power generation for enhanced energy management

This article focuses on optimizing electric vehicle charging in distribution networks, emphasizing technical and economic considerations. Unlike traditional methods, the proposed intelligent approach tailors each EV's charging based on specific daily trip energy requirements. Vehicle owners provide trip data to the charge management system, enabling precise charging calculations considering factors such as energy tariffs, distribution network limits, and charging levels. The paper introduces the horse herd optimization algorithm, inspired by horse herd behavior, offering advantages like reduced computational time and improved convergence in maximizing power generation, especially under shading conditions. The comparative analysis of smart EV charging under normal and fast conditions, considering various constraints and load response programs, demonstrates the proposed method's effectiveness. Numerical results reveal a 46.02 % average load reduction and a 20.53 % peak load decrease with a Load Response Program. Charging costs are optimized, with Case 2 exhibiting a 2.61 % cost reduction compared to Case 3. The study delves into charging frequencies, discharge frequencies, total unsupplied energy, and unloaded energy for each case, providing crucial insights into algorithmic performance. The horse herd optimization algorithm-based approach proves superior, offering a promising solution for efficient and cost-effective electric vehicle charging in distribution networks. Furthermore, graphical representations illustrate the algorithm's impact on charging power, energy allocation, power passing through distribution posts, and megavolt-ampere flow through network lines. These numerical and graphical analyses provide a comprehensive understanding of the horse herd optimization algorithm capabilities, emphasizing its potential to optimize power distribution, reduce costs, and enhance the resilience of residential distribution networks.

An autonomous UAV system based on adaptive LiDAR inertial odometry for practical exploration in complex environments

AbstractUnmanned aerial vehicles (UAVs) offer many advantages over ground vehicles, including quadruped robots, based on high maneuverability when performing exploration in complex and unknown environments. However, due to their limited computational capability, UAVs require lightweight but accurate state estimation algorithms for reliable exploration. In this paper, we propose a segmented map‐based exploration system based on light detection and ranging (LiDAR)‐based state estimation for UAVs. The proposed system includes capabilities such as exploration, obstacle avoidance, and object detection with localization using three‐dimensional (3D) dense maps generated by tightly coupled LiDAR Inertial Odometry (LIO). Our proposed system is a hybrid system that can switch between guided and exploration modes, making it practical for search and rescue missions in disaster scenarios. The proposed LIO algorithm adapts to its surroundings, allowing for fast and accurate state estimation in complex environments. The proposed exploration algorithm is designed to cover specific regions in the 3D dense map generated by the proposed LIO, with the UAV determining if map points are included within the coverage area. We tested the proposed system in both simulation and real‐world environments and validated that the proposed system outperforms state‐of‐the‐art algorithms in various aspects such as localization accuracy and exploration efficiency in complex environments.

Fast and noise-robust quantum state tomography based on ELM

This paper proposed a quantum state tomography approach based on the extreme learning machine (ELM), which is available in the reconstruction of quantum states via a lightweight neural network. The key step of the proposed tomography approach is to employ the ELM to approximate the complex mapping between the measurement values sequence and the real density matrix. After obtaining the output of the ELM-based estimator, a matrix transformation technique is used to make the network outputs satisfy quantum state constraints. Compared with deep learning-based tomography approaches, our proposed ELM-based approach enables both high-fidelity and high-efficiency quantum state tomography with only one training process under the condition of very few numbers of training samples, network layers and hidden layer nodes. In addition, the proposed tomography approach is robust to noisy measurement values, since the ELM-based estimator is quite lightweight. Simulations on the tomography of eigenstates, superposition states and mixed states are presented to verify our theoretical findings. Also, the superiority of the ELM-based tomography approach is demonstrated in comparison with that based on the radial basis function network, convolutional neural network and maximum likelihood estimation approach.

Survey on the Most Current Image Processing Methods in Huntington's Disease Diagnostics and Progression Assessment

Huntington's disease (HD) is a rare, incurable neurodegenerative disorder where fast and non-invasive diagnosis targeting patients' condition plays a crucial role. In modern medicine, various scientific areas are being combined, such as computing, medicine and biomedical engineering. This survey is focused on the most recent image processing methods applied not only for the purpose of diagnosing HD but also for the assessment of its progression severity, in order to contribute to the effort to prolong life of and to improve its quality.

ATF4 expression in thermogenic adipocytes is required for cold-induced thermogenesis in mice via FGF21-independent mechanisms

In brown adipose tissue (BAT), short-term cold exposure induces the activating transcription factor 4 (ATF4), and its downstream target fibroblast growth factor 21 (FGF21). Induction of ATF4 in BAT in response to mitochondrial stress is required for thermoregulation, partially by increasing FGF21 expression. In the present study, we tested the hypothesis that Atf4 and Fgf21 induction in BAT are both required for BAT thermogenesis under physiological stress by generating mice selectively lacking either Atf4 (ATF4 BKO) or Fgf21 (FGF21 BKO) in UCP1-expressing adipocytes. After 3 days of cold exposure, core body temperature was significantly reduced in ad-libitum-fed ATF4 BKO mice, which correlated with Fgf21 downregulation in brown and beige adipocytes, and impaired browning of white adipose tissue. Conversely, despite having reduced browning, FGF21 BKO mice had preserved core body temperature after cold exposure. Mechanistically, ATF4, but not FGF21, regulates amino acid import and metabolism in response to cold, likely contributing to BAT thermogenic capacity under ad libitum-fed conditions. Importantly, under fasting conditions, both ATF4 and FGF21 were required for thermogenesis in cold-exposed mice. Thus, ATF4 regulates BAT thermogenesis under fed conditions likely in a FGF21-independent manner, in part via increased amino acid uptake and metabolism.

Metformin treatment of juvenile mice alters aging-related developmental and metabolic phenotypes in sex-dependent and sex-independent manners.

Metformin has attracted increasing interest for its potential benefits in extending healthspan and longevity. This study examined the effects of early-life metformin treatment on the development and metabolism of C57BL/6J (B6) mice, with metformin administered to juvenile mice from 15 to 56days of age. Metformin treatment led to decreased body weight in both sexes (P < 0.05, t-test). At 9weeks of age, mice were euthanized and organ weights were recorded. The relative weight of retroperitoneal fat was decreased in females, while relative weights of perigonadal and retroperitoneal fat were decreased, and relative liver weight was increased in males (P < 0.05, t-test). Glucose and insulin tolerance tests (GTT and ITT) were conducted at the age of 7weeks. ANOVA revealed a significant impairment in insulin sensitivity by the treatment, and a significantly interactive effect on glucose tolerance between sex and treatment, underscoring a disparity in GTT between sexes in response to the treatment. Metformin treatment reduced circulating insulin levels in fasting and non-fasting conditions for male mice, with no significant alterations observed in female mice. qRT-PCR analysis of glucose metabolism-related genes (Akt2, Glut2, Glut4, Irs1, Nrip1, Pi3k, Pi3kca, Pkca) in the liver and skeletal muscle reveals metformin-induced sex- and organ-specific effects on gene expression. Comparison with previous studies in heterogeneous UM-HET3 mice receiving the same treatment suggests that genetic differences may contribute to variability in the effects of metformin treatment on development and metabolism. These findings indicate that early-life metformin treatment affects development and metabolism in both sex- and genetics-dependent manners.

Inhibition of resurgent Na+ currents by rufinamide

Na+ channels are essential for the genesis of action potentials in most neurons. After opening by membrane depolarization, Na+ channels enter a series of inactivated states (e.g. the fast, intermediate, and slow inactivated states; or If, Ii, and Is). The inactivated Na+ channel may recover via the open state upon membrane repolarization, giving rise to “resurgent” Na+ currents which could be critical for densely repetitive or burst discharges. We incubated CHO–K1 cells transfected with human NaV1.7 cDNA and measured resurgent currents with whole-cell patch recordings. We found Ii is the major inactivated state responsible for the genesis of resurgent currents. Rufinamide, in therapeutic concentrations, could selectively bind to Ii to slow the recovery process and dose-dependently inhibit resurgent currents. The other Na+ channel-inhibiting antiseizure medications (ASM), such as phenytoin and lacosamide (selectively binds to If and Is, separately), fail to show a similar inhibitory effect in clinically relevant concentrations. Resurgent currents are decreased with lengthening of the prepulse, presumably because of redistribution of the channel from Ii to If. Rufinamide could accentuate the decrease to mimic a use-dependent inhibitory effect. The molecular action of slowing of recovery from inactivation by binding to Ii also explains the highly correlative inhibitory effect of rufinamide on both transient and resurgent Na+ currents. The modest but correlative inhibition of both currents may make a novel synergistic effect and thus strong-enough suppression of pathological repetitive and especially burst discharges. Rufinamide may thus have a unique spectrum of therapeutic applications for disorders with excessive neural excitabilities.

Changes in Isoleucine, Sarcosine, and Dimethylglycine During OGTT as Risk Factors for Diabetes.

Current metabolomics studies in diabetes have focused on the fasting state, while only a few have addressed the satiated state. We combined the oral glucose tolerance test (OGTT) and metabolomics to examine metabolite-level changes in populations with different glucose tolerance statuses and to evaluate the potential risk of these changes for diabetes. We grouped participants into those with normal glucose tolerance (NGT), impaired glucose regulation (IGR), and newly diagnosed type 2 diabetes (NDM). During the OGTT, serum was collected at 0, 30, 60, 120, and 180 minutes. We evaluated the changes in metabolite levels during the OGTT and compared metabolic profiles among the 3 groups. The relationship between metabolite levels during the OGTT and risk of diabetes and prediabetes was analyzed using a generalized estimating equation (GEE). The regression results were adjusted for sex, body mass index, fasting insulin levels, heart rate, smoking status, and blood pressure. Glucose intake altered metabolic profile and induced an increase in glycolytic intermediates and a decrease in amino acids, glycerol, ketone bodies, and triglycerides. Isoleucine levels differed between the NGT and NDM groups and between the NGT and IGR groups. Changes in sarcosine levels during the OGTT in the diabetes groups were opposite to those in glycine levels. GEE analysis revealed that during OGTT, isoleucine, sarcosine, and acetic acid levels were associated with NDM risks, and isoleucine and acetate levels with IGR risks. Metabolic profiles differ after glucose induction in individuals with different glucose tolerance statuses. Changes in metabolite levels during OGTT are potential risk factors for diabetes development.

Surface fluorinated graphite suppressing the lithium dendrite formation for fast chargeable lithium ion batteries

Developing lithium-ion batteries with high power and fast charging features has been highlighted as an essential research area to address growing energy demands for portable electronics and long-range electric vehicles. The commercial graphite anode has been recognized as a competent material owing to its benefits, including a long cycle life, high columbic efficiency, and low volume expansion. However, the intrinsic features of their intercalation kinetics render them highly susceptible to lithium deposition, resulting in poor cycle stability at fast charging conditions. In this study, we propose a simple thermal fluorine treatment of flake-type graphite to produce fluorine-doped-flake graphite. We observed the fluorine treatment improves the Li+ ion intercalation kinetics and reduces the lithium deposition and dendrite growth upon fast charging conditions. As a result, enhanced lithiation behavior was observed, with a high specific capacity of 348.3 mAh g−1 and a good rate capability of 66 % at 2C-rate in half-cell conditions. Furthermore, a full cell demonstrated outstanding cycle stability with 83.5 % capacity retention at 2C even after 950 cycles. Our findings emphasize that fluorine doping in graphite could be a straightforward and practical approach to mitigate Li deposition issues and enhance the fast charge kinetics of graphite-based commercial Li-ion batteries.

Low-cost MPPT for triple-junction solar cells used in nanosatellites: A comparative study between P&O and INC algorithms

This paper presents a study of solar panels composed of triple-junction solar cells used in CubeSats; in particular, it focuses on optimizing the power supplied by these panels using the maximum power point tracking technique (MPPT). Optimizing this power is a challenge that is not easily overcome, due to the constraints associated with CubeSats applications, especially in terms of weight, area, budget, as well as the low power generated by these panels which do not exceed 2.4 W at the maximum power point. For all these considerations, both P&O and INC techniques were chosen, since P&O is relatively easy to implement and does not require complex equipment, while INC is known for its high tracking accuracy in difficult environments under fast changing solar conditions, plus the low cost characterizing both techniques, which makes them suitable for CubeSats applications. To select the most appropriate technique for CubeSats applications, a comparative study between both P&O and INC algorithms is performed theoretically using a MATLAB/SIMULINK simulation, followed by a hardware implementation to transfer ideas from theory to practice for realizing the CubeSats power system electronic board since the present study is carried out in the context of a CubeSat application, it focuses on the nanosatellite power system, making it distinct compared to ordinary photovoltaic systems, which have been widely used and studied in previous research in the field of photovoltaics.

Maternal Serum Polyols and Its Link to Gestational Diabetes Mellitus: A Population-Based Nested Case-Control Study.

Sugar alcohols (also called polyols) are regarded as a "healthy" sugar substitute. One of the possible reasons for their safe use in pregnant women is their natural origin and the presence of polyols in maternal and fetal samples during normal human gestation. But little is known about the association between circulating sugar alcohols levels and maternal metabolic disorders during pregnancy. We aimed to detect the concentration of the polyols in participants with and without gestational diabetes mellitus (GDM), and to investigate the association between maternal serum levels of polyols and GDM, as well as newborn outcomes. A nested population-based case-control study was conducted in 109 women with and without GDM. Maternal concentrations of serum erythritol, sorbitol, and xylitol in the fasting state were quantified using a time of flight mass spectrometry system. In women with GDM, serum concentrations of erythritol and sorbitol were higher, but serum concentrations of xylitol were lower than those in women without GDM. Per 1-SD increment of Box-Cox-transformed concentrations of erythritol and sorbitol were associated with the increased odds of GDM by 43% and 155% (95% CI 1.07-1.92 and 95% CI 1.77-3.69), while decreased odds were found for xylitol by 25% (95% CI 0.57-1.00). Additionally, per 1-SD increase of Box-Cox-transformed concentrations of serum sorbitol was associated with a 52% increased odds of large for gestational age newborns controlling for possible confounders (95% CI 1.00-2.30). Maternal circulating sugar alcohols levels during pregnancy were significantly associated with GDM. These findings provide the potential roles of polyols on maternal metabolic health during pregnancy.

Examining the Effects of Communication Features of Educational Robots on Students’ Cognitive Load, Attitudes, and Learning Performance

Educational robots represent a unique form of teacher presence. Exploring how the communication features of robot instructors affect student learning experience could contribute to the advancement of educational robots. This study examined the impact of speech rate, voice type, and emotional tone of robots on students’ cognitive load, attitudes toward robot-assisted teaching, and learning performance. We recruited 477 Chinese primary school students assigned to either the speech rate, voice type, or emotional tone experiment. The results indicate that speech rate significantly influenced students’ cognitive load, with the medium speed condition resulting in higher germane load compared to both fast and slow speed conditions. Moreover, students had a lower preference for adult male voices over adult female, boy, or girl voices. However, voice type did not significantly impact attitudes toward robot-assisted teaching or learning outcomes. Emotional tone did not affect students’ cognitive load, attitudes, or learning performance. These findings provide valuable insights for instructors and designers when configuring the communication features of educational robots in classroom environments. Additionally, students generally prioritized the intelligence of the robot over its communication features, and they did not perceive the teaching content as difficult in all experiments. This study has methodological and practical significance.

The effect of background information and motion speed on the performance of TTC estimation

BackgroundIn previous studies, most research on motion perception have been conducted under background-free condition when the stimulus moved in a plane parallel to the observer. In real-life situations, people’s perception of the motion state of objects is usually done under different visual noise. Based on the occlusion paradigm, this study aimed to investigate whether different background information and motion speed affect the trend and accuracy of time-to-collision (TTC) estimation when stimuli move in a plane parallel to the observer.MethodsThirty five college students (mean age = 20.94, SD = 2.95, range = 18-28 years) participated in experiment 1, and used a 2 (background orientation: horizontal, vertical) × 3 (motion speed: slow, medium, fast) design to explore the effect of different line segment orientations and motion speed on TTC estimation performance; 36 college students (mean age = 20.81, SD = 2.82, range = 18-28 years) participated in experiment 2, and used a 2 (background dimension: two-dimensional background, three-dimensional background) × 3 (motion speed: slow, medium, fast) design to explore the effect of different background dimensions and motion speed on the performance of TTC estimation. The data were analyzed using SPSS 25.0.ResultsThe results revealed that: (1) The TTC was underestimated for the slow speed condition and overestimated for the medium and fast speed conditions. (2) The highest accuracy of TTC estimation was obtained for the fast condition. (3) The TTC were overestimated for the vertical background condition and underestimated for the horizontal background condition. (4) Compared to the two-dimensional background, the TTC was overestimated in the three-dimensional background.ConclusionsObject motion speed affected the TTC estimation performance, and different background information affected the TTC estimation performance when the object moved in a plane parallel to the observer. Meanwhile, the impact of background orientation and motion speed showed significant interactions.

Low-Temperature Molten Salt Electrochemical CO2 Upcycling for Advanced Energy Materials.

One strategy for addressing the climate crisis caused by CO2 emissions is to efficiently convert CO2 to advanced materials suited for green and clean energy technology applications. Porous carbon is widely used as an advanced energy storage material because of its enhanced energy storage capabilities as an anode. Herein, we report electrochemical CO2 upcycling to solid carbon with a controlled microstructure and porosity in a ternary molten carbonate melt at 450 °C. Controlling the electrochemical parameters (voltage, temperature, cathode material) enabled the conversion of CO2 to porous carbon with a tunable morphology and porosity for the first time at such a low temperature. Additionally, a well-controlled morphology and porosity are beneficial for reversible energy storage. In fact, these carbon materials delivered high specific capacity, stable cycling performances, and exceptional rate capability even under extremely fast charging conditions when integrated as an anode in lithium-ion batteries (LIBs). The present approach not only demonstrated efficient upcycling of CO2 into porous carbon suitable for enhanced energy storage but can also contribute to a clean and green energy technology that can reduce carbon emissions to achieve sustainable energy goals.

Pharmacokinetics and Bioequivalence of Apremilast Tablets in Chinese Healthy Subjects Under Fasting and Postprandial States.

This study compared the pharmacokinetics, safety and bioequivalence (BE) of generic and original apremilast tablets in healthy Chinese subjects under fasting and postprandial conditions, providing sufficient evidence for abbreviated new drug application. A randomized, open-label, two-formulation, single-dose, two-period crossover pharmacokinetic study was performed. Thirty-two eligible healthy Chinese subjects were enrolled in fasting and postprandial studies, respectively. In each trial, subjects received a single 30-mg dose of the test or reference apremilast tablet, followed by a 7-day washout interval between periods. Serial blood samples were obtained for up to 48 h post-intake in each period, and the plasma concentrations of apremilast were determined by a validated method. The primary pharmacokinetic (PK) parameters, including the maximum plasma concentration (Cmax), the areas under the plasma concentration-time curve (AUC0-t, AUC0-∞), were calculated using the non-compartmental method. The geometric mean ratios of the two formulations and the corresponding 90% confidence intervals (CIs) were acquired for bioequivalence analysis. The safety of both formulations was also evaluated. Under fasting and postprandial states, the PK parameters of the test drug were similar to those of the reference drug. The 90% CIs of the geometric mean ratios of the test to reference formulations were 94.09-103.44% for Cmax, 94.05-103.51% for AUC0-t, and 94.56-103.86% for AUC0-∞ under fasting conditions, and 99.18-112.48% for Cmax, 98.79-106.02% for AUC0-t, and 98.95-105.89% for AUC0-∞ under postprandial conditions, all of which were within the bioequivalence range of 80.00-125.00%. Both formulations were well tolerated, and no serious adverse events occurred during the study. The trial confirmed that the PK parameters of the generic and original apremilast tablets were bioequivalent in healthy Chinese subjects under fasting and postprandial states, which met the predetermined regulatory standards. Both formulations were safe and well tolerated. chinaDrugtrials.org.cn, identifier CTR20191056 (July 30, 2019); chictr.org.cn, identifier ChiCTR2300076806 (October 19, 2023).