Differential Gradient Research Articles

Race/ethnic differences in educational gradients in sleep duration and quality among U.S. adults.

At the population level, those with more education tend to report better sleep, mirroring the education gradient found in other health outcomes. But research has shown that higher educational attainment does not always confer the same health benefits for Non-Hispanic Black (Black) and Hispanic adults as it does for Non-Hispanic White (White) adults. It is therefore possible that the educational gradient in sleep varies across racial/ethnic groups in the United States. Using the 2004–2018 National Health Interview Survey (N = 356,048), we examined differences in self-reported sleep duration and sleep quality by level of educational attainment and race/ethnicity. Utilizing multinomial (sleep duration) and negative binomial (times in the past week with difficulty falling asleep and staying asleep) regression models, we found that, compared to their less educated counterparts, college or more educated Whites were more likely to report ideal sleep compared to short or long sleep, and also reported fewer times with difficulty falling or staying asleep. The education-sleep association was generally reversed for Black and Hispanic adults, with the worst sleep being reported by those with college-level education. These patterns remained after adjusting for health behaviors, health outcomes, and socioeconomic status. Our study suggests that education does not yield the same protective benefit for sleep among Black and Hispanic adults as it does for White adults, and that highly educated Black and Hispanic adults in particular experience a sleep disadvantage. The differential education gradient in sleep may, therefore, be an important factor underlying current racial and ethnic health disparities.

Small extracellular vesicles from epicardial fat of patients with atrial fibrillation induce inflammation, fibrosis and re-entrant arrhythmias

Abstract Background and aim Epicardial fat (eFat) has been linked to atrial remodeling and fibrillation (AF). Small extracellular vesicles (sEVs) are heterogeneous membrane vesicles released by all cell types. They can both protect and damage tissues by the delivery of multiple different messengers. Surprisingly, the role of sEVs in the pathogenesis of AF has not been studied. Thus, we aimed to determine whether sEVs derived from eFat play a role in the pathogenesis of AF. Methods and results We collected eFat specimens from patients with and without chronic or paroxysmal AF undergoing open-heart surgery. Isolated eFat specimens were cut into small pieces and incubated as organ cultures. We isolated sEVs from the medium of the explant by differential ultra-centrifugation, high-density gradient or size exclusion chromatography (SEC), and characterized vesicle size distribution, morphology, specific markers, histology and molecular cargo. Immunostaining for macrophage accumulation, fibrosis and apoptosis confirmed the pro-inflammatory and pro-fibrotic properties of eFat sEVs from patients with AF (Fig. 1). eFat sEVs labeled with PKH26 were massively up taken by endothelial cells (Fig. 2). Real-time PCR showed an increased level of oxidative stress genes in endothelial cells. eFat sEVs from patients with AF caused more fibrosis after injection into rat hearts than those without AF. (Fig. 3). Finally, while eFat sEVs from patients with and without AF induced shorter action potential duration, only eFat sEVs from patients with AF induced sustained re-entry (rotor) in human induced pluripotent stem cell (iPS)-derived cardiomyocytes (Fig. 4) Conclusion We show, for the first time, that sEVs from eFat of patients with AF demonstrate unique pro-inflammatory, pro-fibrotic and pro-arrhythmic properties. Our findings suggest that eFat sEVs can induce cellular, molecular and electrophysiological remodeling that can subsequently lead to the development of AF. Funding Acknowledgement Type of funding source: None

Differential privacy distributed learning under chaotic quantum particle swarm optimization

Differential privacy has been a common framework that provides an effective method of establishing privacy-guaranteed machine learning. Extensive research work has focused on differential privacy stochastic gradient descent (SGD-DP) and its variants under distributed machine learning to improve training efficiency and protect privacy. However, SGD-DP relies on the premise of convex optimization. In large-scale distributed machine learning, the objective function may be more a non-convex objective function, which not only makes the gradient calculation difficult and easy to fall into local optimization. It’s difficult to achieve truly global optimization. To address this issue, we propose a novel differential privacy optimization algorithm based on quantum particle swarm theory that suitable for both convex optimization and non-convex optimization. We further comprehensively apply adaptive contraction–expansion and chaotic search to overcome the premature problem, and provide theoretical analysis in terms of convergence and privacy protection. Also, we verify through experiments that the actual application performance of the algorithm is consistent with the theoretical analysis.

Numerical investigation of transient phase-change transpiration cooling based on variable properties of coolant

Aimed at promoting the practical application of transpiration cooling technology in the field of active thermal protective system of hypersonic vehicles, this study presents a comprehensive numerical approach combining two-phase mixture model (TPMM), local thermal non-equilibrium (LTNE) assumption and variable properties of coolant to investigate the transient transpiration cooling problems with phase change. The real variable physical properties of coolant as functions of temperature and pressure are taken into consideration based on the data from the National Institute of Standards and Technology (NIST). The model is verified by comparing with the numerical and experimental data in previous researches. Results suggest that a new phenomenon of “reverse temperature distribution” in two-phase region is observed in the transient simulation considering variable properties. Comparison between the constant-property model and variable-property model indicates the necessity of the real variable physical properties, especially at low-pressure conditions with large differential pressure gradient. Meanwhile, the simulation with a non-uniform heat flux boundary condition reveals the mechanism of heat transfer deterioration. A gap of liquid outflow is formed after vapor generation, next moves along the outlet, then disappears and finally regenerates. The non-uniform heat flux will certainly lead to an uneven pressure distribution, resulting in the deterioration of local heat transfer in the porous matrix.

A WOX/Auxin Biosynthesis Module Controls Growth to Shape Leaf Form

A key challenge in biology is to understand how the regional control of cell growth gives rise to final organ forms. Plant leaves must coordinate growth along both the proximodistal and mediolateral axes to produce their final shape. However, the cell-level mechanisms controlling this coordination remain largely unclear. Here, we show that, in A.thaliana, WOX5, one of the WUSCHEL-RELATED HOMEOBOX (WOX) family of homeobox genes, acts redundantly with WOX1 and WOX3 (PRESSED FLOWER [PRS]) to control leaf shape. Through genetics and hormone measurements, we find that these WOXs act in part through the regional control of YUCCA (YUC) auxin biosynthetic gene expression along the leaf margin. The requirement for WOX-mediated YUC expression in patterning of leaf shape cannot be bypassed by the epidermal expression of YUC, indicating that the precise domain of auxin biosynthesis is important for leaf form. Using time-lapse growth analysis, we demonstrate that WOX-mediated auxin biosynthesis organizes a proximodistal growth gradient that promotes lateral growth and consequently the characteristic ellipsoid A.thaliana leaf shape. We also provide evidence that WOX proteins shape the proximodistal gradient of differentiation by inhibiting differentiation proximally in the leaf blade and promoting it distally. This regulation allows sustained growth of the blade and enables a leaf to attain its final form. In conclusion, we show that the WOX/auxin regulatory module shapes leaf form by coordinating growth along the proximodistal and mediolateral leaf axes.

Footprints of local adaptation span hundreds of linked genes in the Atlantic silverside genome.

The study of local adaptation in the presence of ongoing gene flow is the study of natural selection in action, revealing the functional genetic diversity most relevant to contemporary pressures. In addition to individual genes, genome‐wide architecture can itself evolve to enable adaptation. Distributed across a steep thermal gradient along the east coast of North America, Atlantic silversides (Menidia menidia) exhibit an extraordinary degree of local adaptation in a suite of traits, and the capacity for rapid adaptation from standing genetic variation, but we know little about the patterns of genomic variation across the species range that enable this remarkable adaptability. Here, we use low‐coverage, whole‐transcriptome sequencing of Atlantic silversides sampled along an environmental cline to show marked signatures of divergent selection across a gradient of neutral differentiation. Atlantic silversides sampled across 1371 km of the southern section of its distribution have very low genome‐wide differentiation (median F ST = 0.006 across 1.9 million variants), consistent with historical connectivity and observations of recent migrants. Yet almost 14,000 single nucleotide polymorphisms (SNPs) are nearly fixed (F ST > 0.95) for alternate alleles. Highly differentiated SNPs cluster into four tight linkage disequilibrium (LD) blocks that span hundreds of genes and several megabases. Variants in these LD blocks are disproportionately nonsynonymous and concentrated in genes enriched for multiple functions related to known adaptations in silversides, including variation in lipid storage, metabolic rate, and spawning behavior. Elevated levels of absolute divergence and demographic modeling suggest selection maintaining divergence across these blocks under gene flow. These findings represent an extreme case of heterogeneity in levels of differentiation across the genome, and highlight how gene flow shapes genomic architecture in continuous populations. Locally adapted alleles may be common features of populations distributed along environmental gradients, and will likely be key to conserving variation to enable future responses to environmental change.

Discordance between human sperm quality and telomere length following differential gradient separation/swim-up.

Strong evidence has suggested an important role of telomeres in meiosis, fertilization, and embryo development. To determine if sperm telomere length (STL) in sperm purified by differential gradient centrifugation followed by swim-up (selected STL) is correlated with sperm quality and clinical outcomes. Relative selected STL was assessed by quantitative polymerase chain reaction (Q-PCR) in 78 consecutive assisted reproductive technology (ART) treatments during 2017. Statistical analyses were performed in the totality of patients, and in normozoospermic and non-normozoospermic patients. These included correlations between selected STL and sperm quality parameters, embryological parameters (multivariable linear regression), and clinical parameters (multivariable logistic regression). No significant correlations were found between selected STL and sperm quality in the total population. However, selected STL was significantly correlated with total sperm count (r = 0.361; P = 0.039) and sperm DNA fragmentation-post-acrosomal region pattern (r = - 0.464; P = 0.030) in normozoospermic patients. No relation was observed between selected STL and clinical outcomes in any clinical group. As the correlations observed in normozoospermic patients were not representative of the whole heterogeneous population, differences in the sperm characteristics of the study population may lead to discrepant results when evaluating the association of STL with sperm quality. Since the total population selected STL was not related with sperm quality and with clinical outcomes, results do not support the use of selected STL measurement to evaluate the reproductive potential of the male patient or to predict the success rates of ART treatments.

Bone marrow mesenchymal stem cell-derived exosomes attenuate cardiac hypertrophy and fibrosis in pressure overload induced remodeling.

The multiple therapeutic effects of bone marrow mesenchymal stem cells (BM-MSCs) have been verified in ischemic and reperfusion diseases. Exosomes are thought to play vital roles in MSCs-related cardioprotective effects. Recently, more and more evidences indicated that apoptosis and fibrosis were crucial pathological mechanisms in cardiac remodeling. Whether MSCs-derived exosomes could regulate cardiac hypertrophy and remodeling need to be explored. Murine BM-MSCs-derived exosomes were isolated by differential gradient centrifugation method. The transverse aortic constriction (TAC) mice model was established to promote cardiac remodeling. Cardiac function and remodeling were assessed via echocardiography and histology analysis. Myocytes apoptosis was determined by TUNEL fluorescence staining. Meanwhile, premature senescence was detected by β-galactosidase (SA-β-gal) staining. Related proteins and mRNA alternation were assessed via western blotting and quantitative reverse transcription polymerase chain reaction, respectively. MSCs-derived exosomes significantly protected myocardium against cardiac hypertrophy, attenuated myocardial apoptosis, and fibrosis and preserved heart function when pressure overload. In cultured myocytes, MSCs-derived exosomes also prevented cell hypertrophy stimulated with angiotensin II. One the other hand, exosomes promoted premature senescence of myofibroblasts vitro, indicating its anti-fibrosis effect in cardiac remodeling. Exosomes protected cardiomyocytes against pathological hypertrophy. It may provide a promising future treatment for heart failure.

Stability of Vibrating Functionally Graded Nanoplates with Axial Motion Based on the Nonlocal Strain Gradient Theory

Considering both the nonlocal scale and material length scale effects, we investigate vibration and stability behaviors of functionally graded nanoplates with axial motion in order to model the two-dimensional nanobelt in nanoengineering. The nonlocal strain gradient theory is applied and the differential nonlocal strain gradient constitutive relation is adopted. Using the physical neutral plane of a functionally graded thin plate, we derive the governing equation of motion for the functionally graded nanoplate with axial motion via Hamilton’s principle, where the kinematic characteristics are introduced into the dynamic behaviors. The governing equation is numerically solved using the Galerkin method. Effects of the nonlocal scale and material length scale parameters, axial velocity, gradient index, biaxial pre-tensions and aspect ratio are discussed. The results demonstrate that complex frequencies of the functionally graded nanoplate with axial motion decrease with an increase of axial velocity in the subcritical region, while the moving nanoplate experiences a divergent instability or flutter instability in the supercritical region. Natural frequency and critical speed decrease with the increase of the nonlocal scale parameter while increase with the increase of the material length scale parameter, reflecting the nonlocal softening and strain gradient hardening mechanisms, respectively. Besides, natural frequency and critical speed increase with the increase of the biaxial pre-tensions and aspect ratio, but decrease with the increase of the gradient index. In particular, the influences of the gradient index and size or weight of functionally graded nanoplates on the critical speed are explored.

Learning to predict pain: differences in people with persistent neck pain and pain-free controls.

BackgroundLearning to predict threatening events enables an organism to engage in protective behavior and prevent harm. Failure to differentiate between cues that truly predict danger and those that do not, however, may lead to indiscriminate fear and avoidance behaviors, which in turn may contribute to disability in people with persistent pain. We aimed to test whether people with persistent neck pain exhibit contingency learning deficits in predicting pain relative to pain-free, gender-and age-matched controls.MethodWe developed a differential predictive learning task with a neck pain-relevant scenario. During the acquisition phase, images displaying two distinct neck positions were presented and participants were asked to predict whether these neck positions would lead to pain in a fictive patient with persistent neck pain (see fictive patient scenario details in Appendix A). After participants gave their pain-expectancy judgment in the hypothetical scenario, the verbal outcome (PAIN or NO PAIN) was shown on the screen. One image (CS+) was followed by the outcome “PAIN”, while another image (CS−) was followed by the outcome “NO PAIN”. During the generalization phase, novel but related images depicting neck positions along a continuum between the CS+ and CS− images (generalization stimuli; GSs) were introduced to assess the generalization of acquired predictive learning to the novel images; the GSs were always followed by the verbal outcome “NOTES UNREADABLE” to prevent extinction learning. Finally, an extinction phase was included in which all images were followed by “NO PAIN” assessing the persistence of pain-expectancy judgments following disconfirming information.ResultsDifferential pain-expectancy learning was reduced in people with neck pain relative to controls, resulting from patients giving significantly lower pain-expectancy judgments for the CS+, and significantly higher pain-expectancy judgments for the CS−. People with neck pain also demonstrated flatter generalization gradients relative to controls. No differences in extinction were noted.DiscussionThe results support the hypothesis that people with persistent neck pain exhibit reduced differential pain-expectancy learning and flatter generalization gradients, reflecting deficits in predictive learning. Contrary to our hypothesis, no differences in extinction were found. These findings may be relevant to understanding behavioral aspects of chronic pain.

Identification of Podocyte Cargo Proteins by Proteomic Analysis of Clathrin-Coated Vesicles.

Clathrin-mediated endocytosis (CME) plays a fundamental role in podocyte health. Genetic ablation of genes implicated in CME has been shown to cause severe proteinuria and foot process effacement in mice. However, little is known about the cargo of clathrin-coated vesicles (CCVs) in podocytes. The goal of this study was to isolate CCVs from podocytes and identify their cargo by proteomic analysis. Glomeruli isolated from Podocin-Cre Rosa-DTRflox mouse kidneys were seeded and treated with diphtheria toxin to obtain pure primary podocyte cultures. CCVs were isolated by differential gradient ultracentrifugation, and enrichment of CCVs was assessed by immunoblotting and electron microscopy (EM). Liquid chromatography-mass spectrometry (LC-MS) was performed for proteomic analysis. Proteins with higher abundance than transferrin receptor protein 1 were evaluated for CCV cargo potential against previously published literature. Immunofluorescence staining of identified cargo proteins and CCVs was performed in podocytes for further verification. Immunoblotting for multiple protein markers of CME revealed enrichment in the CCV fraction. Enrichment of CCVs among other small vesicles was observed via EM. Proteomics yielded a total of >1200 significant proteins. Multiple-step data analysis revealed 36 CCV-associated proteins, of which 10 represent novel, highly abundant cargo proteins in podocytes. Colocalization of cargo proteins and CCVs on immunostaining was observed. Our identification of podocyte CCV cargo proteins helps to elucidate the importance of endocytic trafficking for podocyte health and maintenance of the glomerular environment.

Isolation and Characterization of Extracellular Vesicles from Cell Culture Conditioned Medium for Immunological Studies.

Extracellular vesicles (EVs) are small, membranous particles that have recently emerged as one the most important mediators of intercellular communication. They can contain a variety of proteins, lipids, and nucleic acids and thus are responsible for modulation of multiple biological processes, including immune response and regulation of immune cells. Immunomodulatory activity of different EVs can be reliably assessed using EVs isolated from cell culture conditioned medium and added to in vitro or ex vivo cultures of immune cells. This article describes protocols for isolation of EVs from cell culture supernatants by differential ultracentrifugation and density gradient centrifugation. It also provides tools and protocols that enable characterization and validation of isolated particles, as well as analysis of interactions between EVs of interest and different subpopulations of human immune cells. © 2020 Wiley Periodicals LLC. Basic Protocol 1: Isolation of extracellular vesicles by differential ultracentrifugation Basic Protocol 2: Isolation of extracellular vesicles by density gradient centrifugation Support Protocol 1: Imaging of extracellular vesicles using transmission electron microscopy Support Protocol 2: Detection of extracellular vesicle protein markers by Western blotting Support Protocol 3: Measurement and counting of extracellular vesicles by nanoparticle tracking analysis Basic Protocol 3: Analysis of extracellular vesicle uptake or association by different subpopulations of lymphocytes in vitro.

Isolation of large dense-core vesicles from bovine adrenal medulla for functional studies

Large dense-core vesicles (LDCVs) contain a variety of neurotransmitters, proteins, and hormones such as biogenic amines and peptides, together with microRNAs (miRNAs). Isolation of LDCVs is essential for functional studies including vesicle fusion, vesicle acidification, monoamine transport, and the miRNAs stored in LDCVs. Although several methods were reported for purifying LDCVs, the final fractions are significantly contaminated by other organelles, compromising biochemical characterization. Here we isolated LDCVs (chromaffin granules) with high yield and purity from bovine adrenal medulla. The fractionation protocol combines differential and continuous sucrose gradient centrifugation, allowing for reducing major contaminants such as mitochondria. Purified LDCVs show robust acidification by the endogenous V-ATPase and undergo SNARE-mediated fusion with artificial membranes. Interestingly, LDCVs contain specific miRNAs such as miR-375 and miR-375 is stabilized by protein complex against RNase A. This protocol can be useful in research on the biological functions of LDCVs.

Description method of Illumination invariant image features

Image feature extraction technology is one of main topics in the field of computer vision, which has been widely applied in biological recognition, image retrieval, target detection and other fields. To overcome the drawbacks of WLD under complex illumination condition, we propose a novel illumination–insensitive feature descriptor named as anisotropic Weber synergy gradient descriptor (AWSGD). The proposed algorithm contains two parts:differential excitation component and gradient direction component. Firstly, by introducing the differential synergy excitation pattern (DSEP) and anisotropic LOG operator with variable scales and angles, we propose the anisotropic differential synergy excitation pattern (ADSEP) as the differential excitation component. Next, focused on the shortage that local gradient pattern (LGP) lacks detailed description of local features with single-layer model, we propose weighted local synergy gradient pattern (WLSGP) as the gradient direction component based on two-layer structure model and weight coefficient distribution model. Finally, ADSEP and WLSGP are fused to form AWSGD histogram. Meanwhile, we adopt XGBoost classifier to conduct related experiments on face databases CMUPIE, Yale B and texture databases PhoTex, RawFooT. The experimental results indicate that the proposed algorithm has stronger robustness to illumination variation and achieves the best performance compared with state-of-the-art methods, which has a certain theoretical significance and practical value in image recognition field under complex illumination condition.

Geographical Gradients of Genetic Diversity and Differentiation among the Southernmost Marginal Populations of Abies sachalinensis Revealed by EST-SSR Polymorphism

Research Highlights: We detected the longitudinal gradients of genetic diversity parameters, such as the number of alleles, effective number of alleles, heterozygosity, and inbreeding coefficient, and found that these might be attributable to climatic conditions, such as temperature and snow depth. Background and Objectives: Genetic diversity among local populations of a plant species at its distributional margin has long been of interest in ecological genetics. Populations at the distribution center grow well in favorable conditions, but those at the range margins are exposed to unfavorable environments, and the environmental conditions at establishment sites might reflect the genetic diversity of local populations. This is known as the central-marginal hypothesis in which marginal populations show lower genetic variation and higher differentiation than in central populations. In addition, genetic variation in a local population is influenced by phylogenetic constraints and the population history of selection under environmental constraints. In this study, we investigated this hypothesis in relation to Abies sachalinensis, a major conifer species in Hokkaido. Materials and Methods: A total of 1189 trees from 25 natural populations were analyzed using 19 EST-SSR loci. Results: The eastern populations, namely, those in the species distribution center, showed greater genetic diversity than did the western peripheral populations. Another important finding is that the southwestern marginal populations were genetically differentiated from the other populations. Conclusions: These differences might be due to genetic drift in the small and isolated populations at the range margin. Therefore, our results indicated that the central-marginal hypothesis held true for the southernmost A. sachalinensis populations in Hokkaido.

Trans-right ventricle and transpulmonary metabolite gradients in human pulmonary arterial hypertension

ObjectiveWhile metabolic dysfunction occurs in several pulmonary arterial hypertension (PAH) animal models, its role in the human hypertensive right ventricle (RV) and lung is not well characterised. We investigated whether...

Fusion of visible and infrared images based on multiple differential gradients

ABSTRACTThe ideal fusion of infrared and visible images is to preserve the details of the visible image as much as possible and superimpose important highlights of the infrared image on the visible image. Therefore, this paper proposes a multiple differential gradient method (MDG) that fuses the infrared image with the difference image of the visible light image and the gradient image of the infrared image. First, an image with comprehensive information is obtained through the difference between the infrared image and the visible image, and it is fused with the suppressed visible image. The new image obtained is then fused with the divergent image of the infrared gradient. Finally, the gray value of the visible image is compared with the new image, and the point with the larger gray value is selected to be fused into the new image. The result is better than most classical algorithms.

Simulations of Active Transport Across the Blood-Brain Barrier

The blood-brain barrier (BBB) is responsible for maintaining homeostasis of the brain by regulating the chemical environment, immune cell transport, and the entry of toxins and pathogens, and misregulation of the BBB has been shown to be implicated in numerous CNS disorders. One of the challenges in studying the BBB include the bioavailability of therapies, as well as rising multidrug resistance of pathogens. A major contributor to drug resistance and lacking bioavailability of therapies is the over-expression of the broad-specificity P-glycoprotein (P-gp) efflux pump in the endothelial cells of the BBB. However, despite the role of P-gp in affecting the bioavailability, pharmacokinetics and efficacy of therapeutic drugs, the mechanism of the efflux of substrates via P-gp, as well as the inhibition of P-gp activity, are not well understood. To address the mechanisms of P-gp-mediated substrate efflux and P-gp inhibition, we performed multimicrosecond unbiased atomic detail molecular dynamics (MD) simulations of the P-glycoprotein from novel human cryo-EM models as well as X-ray crystal structures in the presence of substrates (doxorubicin, rhodamine-123) and an inhibitor (tariquidar). We compare the differential transport gradient of P-gp substrates and inhibitors between the inward-facing (IF) and outward-facing (OF) conformations of P-gp to propose a model of P-gp turnover. We compare this model of active transport to our model of passive transport across the BBB.

A Privacy-Preserving Multi-Task Learning Framework for Face Detection, Landmark Localization, Pose Estimation, and Gender Recognition.

Recently, multi-task learning (MTL) has been extensively studied for various face processing tasks, including face detection, landmark localization, pose estimation, and gender recognition. This approach endeavors to train a better model by exploiting the synergy among the related tasks. However, the raw face dataset used for training often contains sensitive and private information, which can be maliciously recovered by carefully analyzing the model and outputs. To address this problem, we propose a novel privacy-preserving multi-task learning approach that utilizes the differential private stochastic gradient descent algorithm to optimize the end-to-end multi-task model and weighs the loss functions of multiple tasks to improve learning efficiency and prediction accuracy. Specifically, calibrated noise is added to the gradient of loss functions to preserve the privacy of the training data during model training. Furthermore, we exploit the homoscedastic uncertainty to balance different learning tasks. The experiments demonstrate that the proposed approach yields differential privacy guarantees without decreasing the accuracy of HyperFace under a desirable privacy budget.

Design and optimization of sensor array for magnetic gradient tensor system

PurposeThe differential magnetic gradient tensor system is usually constructed from the three-axis magnetic sensor array. While the effects of measurement error, sensor performance and baseline distance on localization performance of such systems have been widely reported, the research about the effect of spatial design of sensor array is less presented. This paper aims to provide a spatial design method of sensor array and corresponding optimization strategy to localization based on magnetic tensor gradient to get the optimum design of the sensor array. Based on the results of simulation, magnetic localization systems constructed from the proposed array and the traditional array have been built to carry out a localization experiment. The results of experiment have verified the effectiveness of magnetic localization based on the proposed array.Design/methodology/approachThe authors focus on the localization of the magnetic target based on magnetic gradient by using three-axis magnetic sensor array and combine a design method with corresponding optimization strategy to get the optimum design of the sensor array.FindingsThis paper provides an array design and optimization method for magnetic target localization based on magnetic gradient to improve the localization performance.Originality/valueIn this paper, the authors focus on the magnetic localization based on magnetic gradient by using three-axis magnetic sensors and study the effect of the spatial design of sensor array on localization performance.