REDD1 knockdown ameliorates endothelial cell senescence through repressing TXNIP-mediated oxidative stress.

Endothelial cell senescence characterized by reactive oxygen species (ROS) accumulation and chronic inflammation is widely recognized as a key contributor to atherosclerosis (AS). Regulated in development and DNA damage response 1 (REDD1), a conserved stress-response protein that regulates ROS production, is involved in the pathogenesis of various age-related diseases. However, the role of REDD1 in endothelial cell senescence is still unclear. Here, we screened REDD1 as a differentially expressed senescence-related gene in the AS progression using bioinformatics methods, and validated the upregulation of REDD1 expression in AS plaques, senescent endothelial cells, and aging aorta by constructing AS mice, D-galactose (DG)-induced senescent endothelial cells and DG-induced accelerated aging mice, respectively. siRNA against REDD1 could improve DG-induced premature senescence of endothelial cells and inhibit ROS accumulation, similar to antioxidant N-Acetylcysteine (NAC) treatment. Meanwhile, NAC reduced the upregulation of REDD1 induced by DG, supporting the positive feedback loop between REDD1 and ROS contributes to endothelial cell senescence. Mechanistically, the regulatory effect of REDD1 on ROS might be related to the TXNIP-REDD1 interaction in DG-induced endothelial cell senescence. Collectively, experiments above provide evidence that REDD1 participates in endothelial cell senescence through repressing TXNIP-mediated oxidative stress, which may be involved in the progression of atherosclerosis.

Perivascular fat tissue and vascular aging: A sword and a shield.

The understanding of the function of perivascular adipose tissue (PVAT) in vascular aging has significantly changed due to the increasing amount of information regarding its biology. Adipose tissue surrounding blood vessels is increasingly recognized as a key regulator of vascular disorders. It has significant endocrine and paracrine effects on the vasculature and is mediated by the production of a variety of bioactive chemicals. It also participates in a number of pathological regulatory processes, including oxidative stress, immunological inflammation, lipid metabolism, vasoconstriction, and dilation. Mechanisms of homeostasis and interactions between cells at the local level tightly regulate the function and secretory repertoire of PVAT, which can become dysregulated during vascular aging. The PVAT secretion group changes from being reducing inflammation and lowering cholesterol to increasing inflammation and increasing cholesterol in response to systemic or local inflammation and insulin resistance. In addition, the interaction between the PVAT and the vasculature is reciprocal, and the biological processes of PVAT are directly influenced by the pertinent indicators of vascular aging. The architectural and biological traits of PVAT, the molecular mechanism of crosstalk between PVAT and vascular aging, and the clinical correlation of vascular age-related disorders are all summarized in this review. In addition, this paper aims to elucidate and evaluate the potential benefits of therapeutically targeting PVAT in the context of mitigating vascular aging. Furthermore, it will discuss the latest advancements in technology used for targeting PVAT.

N-acetylneuraminic acid modulates SQSTM1/p62 sialyation-mediated ubiquitination degradation contributing to vascular endothelium dysfunction in experimental atherosclerosis mice.

Sialic acid (SIA) has been reported to be a risk factor for atherosclerosis (AS) due to its high plasma levels in such patients. However, the effect of increasing SIA in circulation on endothelial function during AS progression remains unclear. In the present study, ApoE-/- mice and endothelial cells line (HUVEC cells) were applied to investigate the effect of SIA on AS progression and its potential molecular mechanism. In vivo, mice were injected intraperitoneally with Neu5Ac (main form of SIA) to keep high-level SIA in circulation. ORO, H&E, and Masson staining were applied to detect the plaque progression. In vitro, HUVECs were treated with Neu5Ac at different times, CCK-8, RT-PCR, western blot, and immunoprecipitation methods were used to analyze its effects on endothelial function and the potential involved mechanism. Results from the present study showed that high plasma levels of Neu5Ac in ApoE-/- mice could aggravate the plaque areas as well as increase necrotic core areas and collagen fiber contents. Remarkably, Neu5Ac levels in circulation displayed a positive correlation with AS plaque areas. Furthermore, results from HUVECs showed that Neu5Ac inhibited cells viability in a time/dose-dependent manner, by then induced the activation of inflammation makers such as ICAM-1 and IL-1ß. Mechanism study showed that the activation of excessive autophagy medicated by SQSTM1/p62 displayed an important role in endothelium inflammatory injury. Neu5Ac could modify SQSTM1/p62 as a sialylation protein, and then increase its level with ubiquitin binding, further inducing ubiquitination degradation and being involved in the excessive autophagy pathway. Inhibition of sialylation by P-3Fax-Neu5Ac, a sialyltransferase inhibitor, reduced the binding of SQSTM1/p62 to ubiquitin. Together, these findings indicated that Neu5Ac increased SQSTM1/p62-ubiquitin binding through sialylation modification, thereby inducing excessive autophagy and subsequent endothelial injury. Inhibition of SQSTM1/p62 sialylation might be a potential strategy for preventing such disease with high levels of Neu5Ac in circulation.

Metabolite Neu5Ac triggers SLC3A2 degradation promoting vascular endothelial ferroptosis and aggravates atherosclerosis progression in ApoE-/-mice.

Background: Atherosclerosis (AS) is still the major cause of cardiovascular disease (CVD) as well as stroke. Endothelial metabolic disorder has been found to be activated and then promote endothelial cells (ECs) injury, which is regarded to initiate AS progression. N-acetylneuraminic acid (Neu5Ac), a metabolite produced by hexosamine-sialic acid pathway branching from glucose metabolism, was presented as a notable biomarker of CVD and is positively correlated with ECs function. However, few studies explain whether Neu5Ac regulate AS progression by affecting EC function as well as its involved mechanisms are still unknown. Methods: Here, we mimicked an animal model in ApoE-/- mice which displaying similar plasma Neu5Ac levels with AS model to investigate its effect on AS progression. Results: We found that Neu5Ac exacerbated plaques area and increased lipids in plasma in absence of HFD feeding, and ECs inflammatory injury was supposed as the triggering factor upon Neu5Ac treatment with increasing expression of IL-1ß, ICAM-1, and promoting ability of monocyte adhesion to ECs. Mechanistic studies showed that Neu5Ac facilitated SLC3A2 binding to ubiquitin and then triggered P62 mediated degradation, further leading to accumulation of lipid peroxidation in ECs. Fer-1 could inhibit ECs injury and reverse AS progression induced by Neu5Ac in ApoE-/- mice. Interestingly, mitochondrial dysfunction was also partly participated in ECs injury after Neu5Ac treatment and been reversed by Fer-1. Conclusions: Together, our study unveils a new mechanism by which evaluated metabolite Neu5Ac could promote SLC3A2 associated endothelial ferroptosis to activate ECs injury and AS plaque progression, thus providing a new insight into the role of Neu5Ac-ferroptosis pathway in AS. Also, our research revealed that pharmacological inhibition of ferroptosis may provide a novel therapeutic strategy for premature AS.

Infant Alstrom syndrome diagnosed by a new gene mutation: a case report.

Alstrom syndrome is a rare autosomal recessive disorder resulting from an ALMS1 gene mutation. Here, we present the clinical data of a case of an infant diagnosed with Alstrom syndrome through whole-exome sequencing. A 2-month-old male infant was admitted to Sichuan Provincial Maternity and Child Health Care Hospital on 30 May 2019 after "coughing for half a day and dyspnea for 2 hours". He was diagnosed with severe pneumonia, acute congestive heart failure, Grade III cardiac function, acute respiratory failure, and myocarditis. After treatment, he was discharged with a prescription for oral medication. After a 4-month follow-up, the patient's left ventricle exhibited spherical enlargement and a decrease in left ventricular function. The infant's whole-exome sequencing results revealed compound heterozygous mutations in the ALMS1 gene: c.2179dup (p. Y727Lfs*12), a frameshift mutation, that was heterozygous and originated from the mother, while c.11140C>T (p. Q3714*) was a heterozygous nonsense mutation that originated from the father. Both mutations are classified as "category 1-pathogenic mutations" according to the American College of Medical Genetics and Genomics (ACMG) assessment. A novel ALMS1 mutation was identified in this case report, highlighting the importance of genetic testing for the early diagnosis of Alstrom syndrome.

The role of prophylactic antibiotics in elective inguinal tension-free hernia repair: A systematic review and meta-analysis.

Whether to use antibiotics to prevent surgical site infection in elective inguinal tension-free hernia repair has been controversial. To systematically evaluate the effect of prophylactic antibiotic application in elective inguinal tension-free hernia repair, we identified all published randomised controlled trials of the effect of prophylactic antibiotic application on elective inguinal tension-free hernia repair were collected by computer retrieval from the China National Knowledge Infrastructure; VIP Database; Wanfang Database; China Biomedical Literature Database; and PubMed, EMBASE and Cochrane Library databases. Meta-analysis was performed by RevMan 5.3 software. The meta-analysis showed that the total incidence of surgical site infections [P = 0.003] and the incidence of superficial surgical site infections [P = 0.004] in the antibiotic group (AG) were lower than those in the non-antibiotic group (NAG). There was no significant difference in the total incidence of postoperative infections [P = 0.06], deep surgical site infections [P = 0.26] and seroma [P = 0.52] between the AG and the NAG. Based on current evidence, the application of prophylactic antibiotics in elective inguinal tension-free hernia repair can prevent the total incidence of surgical site infections and that of superficial surgical site infections but cannot prevent the total incidence of postoperative infection events, incidence of deep surgical site infections and incidence of seroma.

Blind identification of active landslides in urban areas: a new set of comprehensive criteria.

More than 70% of catastrophic landslides were previously unknown and brought tremendous losses to human life and property in urban regions; therefore, there is an urgent need for early identification of active landslides to eliminate landslide risk at the early stage. However, early identification of landslides has always been a worldwide challenge due to high concealment, steep topography, inaccessible location, and sudden onset. This work suggests a new set of comprehensive criteria for the early identification of landslides by integrating surface deformation, geological, topographic, geomorphological, and disaster-failure features. This set of criteria is universally applicable with no use of the prior knowledge of landslide locations (blind identification) and is successfully validated by a field survey. This work selects the Xuecheng region, a hard-hit area of landslides, as the study area and employs multisource data (seismic, geological, topographic, meteorological, SAR, and optical remote sensing data) and time-series InSAR technology to identify active landslides and reveal their deformation rules. Some new viewpoints are suggested. (1) The new comprehensive criteria synthesize the surface deformation, disaster-controlling, and disaster-inducing characteristics and achieve relatively high accuracy by field validation. (2) Forty-seven active landslides are identified in Xuecheng with no use of the prior knowledge of landslides. The soft rocks or soft-hard interbeddings, tectonic movement, fluvial undercutting and eroding, precipitation, earthquakes, and human engineering activity control or induce the development of these active landslides. (3) Two giant landslides that significantly threaten human lives and properties and exhibit different movement modes are selected to highlight the deformation rules of active landslides under the coupled action of poor lithologic condition, tectonic movement, river erosion, precipitation, and human engineering activity. The suggested new criteria can be applied to other landslide hard-hit urban regions and contribute to the timely and effective prevention and control of catastrophic landslides, reduction of enormous disaster losses, and rational management of the environment.

Landslide Susceptibility Evaluation Based on Potential Disaster Identification and Ensemble Learning.

Catastrophic landslides have much more frequently occurred worldwide due to increasing extreme rainfall events and intensified human engineering activity. Landslide susceptibility evaluation (LSE) is a vital and effective technique for the prevention and control of disastrous landslides. Moreover, about 80% of disastrous landslides had not been discovered ahead and significantly impeded social and economic sustainability development. However, the present studies on LSE mainly focus on the known landslides, neglect the great threat posed by the potential landslides, and thus to some degree constrain the precision and rationality of LSE maps. Moreover, at present, potential landslides are generally identified by the characteristics of surface deformation, terrain, and/or geomorphology. The essential disaster-inducing mechanism is neglected, which has caused relatively low accuracies and relatively high false alarms. Therefore, this work suggests new synthetic criteria of potential landslide identification. The criteria involve surface deformation, disaster-controlling features, and disaster-triggering characteristics and improve the recognition accuracy and lower the false alarm. Furthermore, this work combines the known landslides and discovered potential landslides to improve the precision and rationality of LSE. This work selects Chaya County, a representative region significantly threatened by landslides, as the study area and employs multisource data (geological, topographical, geographical, hydrological, meteorological, seismic, and remote sensing data) to identify potential landslides and realize LSE based on the time-series InSAR technique and XGBoost algorithm. The LSE precision indices of AUC, Accuracy, TPR, F1-score, and Kappa coefficient reach 0.996, 97.98%, 98.77%, 0.98, and 0.96, respectively, and 16 potential landslides are newly discovered. Moreover, the development characteristics of potential landslides and the cause of high landslide susceptibility are illuminated. The proposed synthetic criteria of potential landslide identification and the LSE idea of combining known and potential landslides can be utilized to other disaster-serious regions in the world.

Tribological Behavior of 3D-Printed Nanometer SiC and SiO2 Particle-Reinforced Polyamide 12 Composites by Selective Laser Sintering under Seawater Lubrication Condition.

Polymeric matrix composites have been widely used in the marine field. In this study, the tribological behavior under seawater-lubricated conditions of pure Polyamide 12 (PA12), micron-SiC and nanometer SiC and SiO2 particle-reinforced PA12 composites, which are prepared by selective laser sintering (SLS), were studied. The seawater absorption, hardness, contact angle and tribology performance were investigated. The results show that the addition of micron- and nano-SiC particles and nano-SiO2 particles could decrease the seawater adsorption and contact angle, and increase the hardness. Under seawater conditions, the addition of micro SiC particles can reduce the friction coefficient and wear loss, whereas the addition of nano-SiC and -SiO2 particles increases the corresponding values. The specimen printed with recycled powder has a higher friction coefficient, while having a better wear resistance. However, it increases the width and depth of the wear track in some locations. The wear mechanisms of the composite specimens are also analyzed. This was the result of the combined effects of fatigue wear and abrasive wear under seawater conditions. The latter plays a dominant role under seawater conditions. This study may provide a valuable reference for the further research and application of polymeric matrix composites in marine engineering equipment.

A Universal Detection Method for Adversarial Examples and Fake Images.

Deep-learning technologies have shown impressive performance on many tasks in recent years. However, there are multiple serious security risks when using deep-learning technologies. For examples, state-of-the-art deep-learning technologies are vulnerable to adversarial examples that make the model's predictions wrong due to some specific subtle perturbation, and these technologies can be abused for the tampering with and forgery of multimedia, i.e., deep forgery. In this paper, we propose a universal detection framework for adversarial examples and fake images. We observe some differences in the distribution of model outputs for normal and adversarial examples (fake images) and train the detector to learn the differences. We perform extensive experiments on the CIFAR10 and CIFAR100 datasets. Experimental results show that the proposed framework has good feasibility and effectiveness in detecting adversarial examples or fake images. Moreover, the proposed framework has good generalizability for the different datasets and model structures.

Generative Adversarial Training for Supervised and Semi-supervised Learning.

Neural networks have played critical roles in many research fields. The recently proposed adversarial training (AT) can improve the generalization ability of neural networks by adding intentional perturbations in the training process, but sometimes still fail to generate worst-case perturbations, thus resulting in limited improvement. Instead of designing a specific smoothness function and seeking an approximate solution used in existing AT methods, we propose a new training methodology, named Generative AT (GAT) in this article, for supervised and semi-supervised learning. The key idea of GAT is to formulate the learning task as a minimax game, in which the perturbation generator aims to yield the worst-case perturbations that maximize the deviation of output distribution, while the target classifier is to minimize the impact of this perturbation and prediction error. To solve this minimax optimization problem, a new adversarial loss function is constructed based on the cross-entropy measure. As a result, the smoothness and confidence of the model are both greatly improved. Moreover, we develop a trajectory-preserving-based alternating update strategy to enable the stable training of GAT. Numerous experiments conducted on benchmark datasets clearly demonstrate that the proposed GAT significantly outperforms the state-of-the-art AT methods in terms of supervised and semi-supervised learning tasks, especially when the number of labeled examples is rather small in semi-supervised learning.

Xpert MTB/RIF Improves the Prognosis of Multidrug-Resistant Tuberculosis Patients Through Faster Diagnosis and Earlier Targeted Treatment: A Prospective Cohort Study.

Objective: To evaluate the effectiveness of Xpert MTB/RIF in patients with multidrug-resistant tuberculosis (MDR-TB). Methods: Seventy-five patients with MDR-TB were enrolled in this prospective cohort study and were divided into two groups. The observation group were given standardized anti-MDR-TB treatment regimen (6ZAmLfxPtoCs/18ZLfxPtoCs) immediately when they had two positive sputum Xpert MTB/RIF results of RIF resistance. The control group were not given standardized anti-MDR-TB regimen until culture-based drug-susceptibility testing suggested MDR-TB. Treatment effect index, foci absorption, conversion of sputum, treatment outcomes, and adverse reactions were observed. Fisher's exact test and chi-square test were used to compare the differences between groups. Results: Treatment effect index of the observation group significantly out-performed the control group (24/34, 70.6% vs. 17/38, 44.7%, p = 0.027). At the 6th month of treatment course, observation group achieved significantly higher conversion (28/34, 82.3% vs. 23/38, 60.5%, p = 0.042). The foci absorption, cavity change, conversion at the 24th month of course, or treatment outcome between two groups were not statistically different. Conclusion: Xpert MTB/RIF helps MDR-TB patients to start rational treatment regimen earlier and reach earlier sputum conversion.

Identification of Fuzzy Rule-Based Models With Collaborative Fuzzy Clustering.

Fuzzy rule-based models (FRBMs) are sound constructs to describe complex systems. However, in reality, we may encounter situations, where the user or owner of a system only owns either the input or output data of that system (the other part could be owned by another user); and due to the consideration of data privacy, he/she could not obtain all the needed data to build the FRBMs. Since this type of situation has not been fully realized (noticed) and studied before, our objective is to come up with some strategy to address this challenge to meet the specific privacy consideration during the modeling process. In this study, the concept and algorithm of the collaborative fuzzy clustering (CFC) are applied to the identification of FRBMs, describing either multiple-input-single-output (MISO) or multiple-input-multiple-output (MIMO) systems. The collaboration between input and output spaces based on their structural information (conveyed in terms of the corresponding partition matrices) makes it possible to build FRBMs when input and output data could not be collected and used in unison. Surprisingly, on top of this primary pursuit, with the collaboration mechanism the input and output spaces of a system are endowed with an innovative way to comprehensively share, exchange, and utilize the structural information between each other, which results in their more relevant structures that guarantee better model performance compared with performance produced by some state-of-the-art modeling strategies. The effectiveness of the proposed approach is demonstrated by experiments on a series of synthetic and publicly available datasets.

Spatio-temporal evolution of post-seismic landslides and debris flows: 2017 Ms 7.0 Jiuzhaigou earthquake.

Spatio-temporal evolution of post-seismic landslides and debris flows provides a new perspective to understand post-earthquake evolution of geological environments and landscapes, and to instruct cascaded catastrophic hazard mitigation and post-disaster reconstruction. However, limited earthquake events have been investigated for post-earthquake geohazard evolution. This work reports the geohazard evolution after the 2017 Ms 7.0 Jiuzhaigou earthquake considering the effects of the earthquake, geology, terrain, meteorology, hydrology, and human engineering activity. Some new viewpoints are suggested. (1) Landslide and debris flow activity intensified in the first year following the earthquake under the effects of the antecedent earthquake, precipitation, fault tectonics, human engineering activity, and fluvial networks. (2) Landslide and debris flow activity declined rapidly in the second year as a result of dramatically reduced sediments, declined rainfall, and self-healed slopes. (3) The significant decay of landslide and debris flow activity and the prominent reduction of loose deposits indicate that the geological environment was gradually restoring. (4) Although the hazard effect mitigation and geological environment restoration were ongoing (in the absence of rainstorm events) to attain a new balance, the geoenvironment has not returned to the pre-earthquake level because of widespread unrecovered geohazards and the remaining loose deposits on hillslopes or in channels. (5) The geological environment after the Jiuzhaigou earthquake may re-equilibrate and return to the pre-earthquake level more quickly than after the Kashmir, Chi-Chi, Gorkha, Wenchuan, and Murchison earthquakes. This work provides new knowledge pertaining to geohazard evolution after a strong earthquake and to profound impacts of a catastrophic earthquake on geological environment and landscape.

Predictive value of brachial artery flow-mediated dilation on coronary artery abnormality in acute stage of Kawasaki disease.

Coronary artery abnormalities (CAAs) are a severe complication of Kawasaki disease (KD) that may lead to cardiovascular events. Given the evidence that brachial artery flow-mediated dilation (FMD) decreases in children after the onset of KD, we hypothesized that it could be an early marker of CAA development in the acute stage and investigated its relationship with variation in the coronary artery diameter. A total of 326 sex- and age-matched children were enrolled, including 120 with KD, 109 febrile children and 97 healthy controls. In this study, FMD was significantly decreased in the KD group compared with the febrile and healthy groups. FMD was lower in the CAA group than in the no coronary artery abnormality group. The comparison of FMD showed an obvious difference among the CAA subgroups. The FMD in the coronary aneurysm (CA) group showed a strong negative correlation with the pretreatment maximum coronary artery Z-score (preZmax). While preZmax was 2.5, the receiver operating characteristic curve indicated an optimal cutoff point of 3.44% for FMD. FMD ≤ 3.44% could be considered as a signal of coronary lesions in acute stage of KD.

Phase unwrapping in ICF target interferometric measurement via deep learning.

This paper proposes an unwrapping algorithm based on deep learning for inertial confinement fusion (ICF) target interferograms. With a deep convolutional neural network (CNN), the task of phase unwrapping is transferred into a problem of semantic segmentation. A method for producing the data set for the ICF target measurement system is demonstrated. The noisy wrapped phase is preprocessed using a guided filter. Postprocessing is introduced to refine the final result, ensuring the proposed method can still accurately unwrap the phase even when the segmentation result of the CNN is not perfect. Simulations and actual interferograms show that our method has better accuracy and antinoise ability than some classical unwrapping approaches. In addition, the generalization capability of our method is verified by successfully applying it to an aspheric nonnull test system. By adjusting the data set, the proposed method may be transferred to other systems.

Low-dose aspirin use and cancer-specific mortality: a meta-analysis of cohort studies.

BACKGROUND: Considering the increased risk of bleeding caused by aspirin, and the observed benefit in all-cause mortality may be due to an improvement in cardiovascular-related mortality. We carried out this meta-analysis to estimate the association of low-dose aspirin use and risk of cancer-specific mortality. METHODS: We searched the PubMed and China National Knowledge Infrastructure (CNKI) databases for all articles within a range of published years from 1980 to 2018. RESULTS: Finally, 13 published cohort studies with 65 768 patients were available for estimating overall risk of cancer-specific mortality associating with post-diagnosis low-dose aspirin use, and 4 cohort studies were available for pre-diagnosis low-dose aspirin use with 16 654 patients. Overall, statistical evidence of significantly decreased cancer-specific mortality was found to be associated with post-diagnosis low-dose aspirin use (OR = 0.84, 95% CI = 0.75-0.93), but not with pre-diagnosis low-dose aspirin use. In terms of subgroup analyses by cancer type, post-diagnosis low-dose aspirin use was significantly with decreased cancer-specific mortality for digestive tract cancer including colorectal cancer, esophageal cancer and gastric cancer. CONCLUSION: Our meta-analysis indicated that post-diagnosis but not pre-diagnosis low-dose aspirin use may reduce cancer-specific mortality.

Predictive value of heart rate deceleration capacity on coronary artery lesion in acute phase of Kawasaki disease.

This study was to investigate the correlation of vagal activity with coronary artery lesion (CAL) in Kawasaki disease (KD) children, and assess the predictive value of heart rate deceleration capacity (DC) for CAL in acute phase of KD.50 KD children with CAL, 130 KD children without CAL, 30 children with acute upper respiratory infection and 100 healthy children were recruited and indicators reflecting vagal activity including DC were measstuogram. KD children with CAL showed decreased vagal activity with significantly lower values of DC. DC was negatively correlated with levels of N-terminal pro-brain natriuretic peptide (NT-proBNP) and C-reactive protein (CRP) in KD children. DC was a usable cardiac electrophysiological index to predict CAL in children with KD, with an area under the receiver operating characteristic curve (AUC) of 0.741. The cut-off value of DC for predicting CAL in KD children was 4.37 ms. DC was an independent predictor of CAL in children with KD, evaluated by multiple logistic regression analysis, KD children with DC ≤ 4.37 ms had an increased risk of CAL, with odds ratios (OR) of 5.94. Our study illustrates DC could be used to predict CAL in acute phase of KD.

Approximation of Fuzzy Sets by Interval Type-2 Trapezoidal Fuzzy Sets.

In this paper, we propose a gradient-based method to approximate a fuzzy set through a trapezoidal fuzzy set (TFS). By adding some constraints in the formulated optimization problem, the major characteristics of the fuzzy set such as the core, the major part of the support, and the shape of the membership function could be preserved; also the form of the optimized result as a TFS is guaranteed. We regard the optimized TFS as the "skeleton" (blueprint) of the original fuzzy set. Based on this skeleton, we further extend the TFS to a higher type, that is, an interval type-2 TFS (IT2 TFS), so that more information about the original fuzzy set could be captured but the number of the parameters used to describe the original fuzzy set is still maintained low (nine parameters are required for an IT2 TFS). The principle of justifiable granularity is used to ensure that the formed type-2 information granule exhibits a sound interpretation. Both synthetic fuzzy sets and those constructed by the fuzzy C -means algorithm applied to the publicly available data have been used to demonstrate the usefulness of the proposed approximation methods.