Retroviruses selectively incorporate a specific subset of host cell proteins and lipids into their outer membrane when they bud out from the host plasma membrane. This specialized viral membrane composition is critical for both viral survivability and infectivity. Here, we review recent findings from live cell imaging of single virus assembly demonstrating that proteins and lipids sort into the HIV retroviral membrane by a mechanism of lipid-based phase partitioning. The findings showed that multimerizing HIV Gag at the assembly site creates a liquid-ordered lipid phase enriched in cholesterol and sphingolipids. Proteins with affinity for this specialized lipid environment partition into it, resulting in the selective incorporation of proteins into the nascent viral membrane. Building on this and other work in the field, we propose a model describing how HIV Gag induces phase separation of the viral assembly site through a mechanism involving transbilayer coupling of lipid acyl chains and membrane curvature changes. Similar phase-partitioning pathways in response to multimerizing structural proteins likely help sort proteins into the membranes of other budding structures within cells. Protein sorting is ubiquitous in biological membranes, involved in such diverse physiological phenomena as formation of transport carriers, biogenesis of extracellular vesicles, and receptor-mediated signaling ,2,3. TheRetroviruses, such as HIV, assemble at the plasma membrane (PM) of host cells and subsequently bud out as spherical viral particles. During this process, the assembly site membrane patch attached to oligomerized HIV structural protein, Gag, is transformed into the outer membrane of the released virus particle. This transformation is crucial for the virus to survive, infect other cells, and exhibit tropism ,24. SurpThe assembly of HIV involves the expansion of a protein lattice at the cytoplasmic face of the PM by progressive oligomerization of HIV Gag ,36, a prIn the above study , the proThis real-time evaluation of assembly site remodeling suggests an important distinction between Gag-induced phase separation at the HIV assembly site and lipid-based phase separation in model systems. Lipid-based phase separation processes in model membrane systems are characterized by switch-like, first-order phase transitions ,43. HIV A novel concept emerging from the real-time analysis of single virus assembly is the temporal structuring of the assembly process into distinct windows of protein sorting. The sequential sorting of different proteins between assembly site domain and bulk PM contributes to the continuously changing composition of the assembly site. These temporally distinct sorting events can be utilized for controlling the concentration of proteins in the HIV membrane by confining their recruitment to specific time windows. For example, early-recruited proteins might be expected to become more numerous in the virion membrane compared to late-recruited proteins. Consistent with this possibility, the envelope protein of the gammaretrovirus MLV (MLV-Env), recruited early, has a high number of proteins in the HIV membrane . In contThe envelope proteins of lentiviruses such as HIV have a significantly longer cytoplasmic tail compared to gammaretroviruses like MLV . As a neHIV Gag uses two specific structural elements to bind to PM: an N-terminus myristoyl lipid anchor and a stretch of basic amino acids within the highly basic region (HBR) of its matrix domain. Gag is anchored to the PM by the insertion of the myristoyl chain into the inner leaflet ,58,59 anAn appealing possibility for how Gag multimerization at the inner PM leaflet could impact events on the outer PM leaflet could be through Gag’s interactions with PIP2 and PS. High-affinity interactions between HIV Gag and PIP2 are expected to cluster PIP2 at the viral assembly site. This is supported by recent studies in model membranes and mammalian cells showing that PIP2 is concentrated at sites of Gag multimerization ,64. AcidThe above transbilayer coupling model invokes the involvement of outer leaflet lipids and lipid-anchored proteins in initiating the transition of the assembly site into an increasingly ordered lipid domain, which is supported by the early recruitment of GPI-anchored proteins and other order-preferring lipids to the assembly site . A diffeAs viral assembly progresses, the assembly site membrane juxtaposed to the expanding Gag platform increases its curvature ,71. InitOne possible mechanism involves the curvature of the assembly site membrane facilitating protein sorting by imposing geometrical constraints to the partitioning of proteins and lipids. The two adjacent membrane areas, bulk PM and assembly site, present contrasting curvatures to the membrane proteins, which can sort between the two environments based on their molecular shapes ,74. AddiThe curving of the assembly site domain can also contribute to protein sorting by a second mechanism that involves modulation of the energy at the interface of assembly site and bulk PM. The mismatch in physical properties between the assembly site and the bulk PM would give rise to an interfacial energy, called line tension, at the boundary between the two membrane regions ,79. The The above results and ideas suggest a new way of thinking about protein sorting during retroviral budding that is based on active-phase partitioning of proteins between bulk PM and an assembly site membrane domain. In this scheme, the multimerization of an extrinsic membrane element, HIV Gag, at the inner leaflet of the bilayer initiates phase partitioning by ordering the inner leaflet lipids it contacts . Inner lA major challenge in studying protein sorting in biological membranes is that the spatiotemporal scales and location of the sorting events often make them inaccessible for direct visualization. Two features of the HIV assembly process make it a convenient platform for clarifying the mechanisms underlying the sorting of membrane proteins. First is the relatively slow kinetics of the HIV assembly process (~10–15 min), and second is the clear spatial demarcation of the assembly site by the oligomerizing Gag lattice. Results from real-time analyses of HIV assembly, as discussed in this review, have helped identify lipid-based partitioning as a major driving force for protein sorting during HIV assembly. We propose that phase partitioning and protein sorting at the HIV assembly require both transbilayer coupling and curvature changes in the membrane.We anticipate that specific features of the proposed transbilayer model are likely shared by protein sorting events at other locations within mammalian cells. Transbilayer coupling can be initiated if the following two criteria are satisfied: (i) immobilization and local ordering of lipids in one of the leaflets across a significant spatial scale and (ii) presence of lipids and lipid-anchored proteins in the opposite leaflet that can interdigitate with the immobilized lipids. Once transbilayer coupling is established, the transmission of lipid ordering across the two leaflets can facilitate local phase separation to drive protein sorting by a partitioning mechanism. The immobilization of lipids for transbilayer coupling can occur by asymmetric interaction of coat proteins with one of the leaflets of the bilayer ,5,8,85, The contribution of membrane curvature to the HIV sorting process is also significant. The assembly site membrane acquires high curvature as the underlying Gag lattice curves to form a spherical particle. Consequently, the viral assembly process is coupled to membrane mechanics and provides a platform for studying how membrane shape collaborates with specific protein-lipid interactions to drive membrane compartmentalization. As described in this review, bilayer coupling working in conjunction with membrane curvature is likely to be essential for the final differentiation of the viral particle membrane. Membrane curvature can help to amplify the assembly site protein sorting by inducing shape-based sorting of molecules and by reducing the boundary energy. Additionally, high membrane curvature could create a kinetic trap for retaining proteins sorted into the viral membrane.The two mechanisms for assembly site phase separation and protein sorting proposed in this review, viz. transbilayer coupling and membrane curvature, are certainly not exhaustive of the possible biophysical principles involved in membrane remodeling and protein sorting during viral assembly. Rather, we anticipate that the concepts emerging from our study and the proposed mechanisms will serve as a starting point for more in-depth investigation that will reveal how additional mechanisms collaborate to drive sorting during viral assembly. For example, electrostatic interactions, as indicated in a recent study , could pIn conclusion, given the role of phase separation in protein sorting into the HIV membrane, it will be interesting to see if this process is involved in other sorting steps within cells, such as the coat-dependent sorting of proteins into intracellular transport carriers. Indeed, phase partitioning could well be working in conjunction with coat proteins for specifying the unique cargo delivered into vesicular transport intermediates ,85,95.


The axon has been considered as a high-fidelity digital cable that reliably conducts action potentials toward the presynaptic terminals  neurons, a relay of the ascending auditory pathway, during development and aging. It was shown that AIS length and distance from the soma change with age and auditory experience, and that these structural changes account for the modifications in the excitability of MNTB neurons, as supported by modeling. The paper by Zhang et al. examined the roles of purinergic signaling in the development and maintenance of AIS. Using mouse cultured hippocampal neurons, they demonstrated that P2Y1 purinergic receptors determine the initial development of AIS structure and function. On the other hand, P2X7 receptors are involved in the maintenance of AIS maturation. The study by Alpizar et al. explored the roles of the cell adhesion molecule neurofascin-186 (NF-186) in the arrangement of ankyrin G and sodium channels in the AIS. Ablation of NF-186 perturbed ankyrin G accumulation at the AIS and altered expression of sodium channels and therefore suggested the possible contribution of this cell adhesion molecule in AIS-specific molecular organization. Schlüter et al. reported the maturation of AIS in retinal ganglion cells with a focus on the cisternal organelle, a presumed Ca2+-store of the AIS, using the marker synaptopodin. Since retinal development, as well as visual deprivation, alter the AIS and synaptopodin distribution, the authors suggested the activity-dependent structural plasticity occur in both retinal ganglion cells and pyramidal cells in the visual cortex.Action potentials are generated at the AIS or in the proximal axon near the soma, and therefore the excitability of the AIS is the critical determinant of encoding output trains of the action potential. In a series of papers, this Research Topic gained insight into our understanding of the AIS structure and function. Alcami and El Hady offered a comprehensive review of the computational abilities of axons and the dynamic control of generation and propagation of action potentials. This paper also lights up the issues to be investigated in future studies with cutting-edge technologies. The authors suggested the importance of “hybrid computation” of analog and digital signals and their interplay. Burke and Bender reviewed the mechanisms as well as the functional significance of modulation of ionic channels in axons. Action potential generation and propagation, as well as neurotransmitter release and its short-term plasticity, are critically and dynamically regulated by modulation of ion channels in axonal membranes. The future perspective of looking for the functional consequence of modulation of axonal excitability in vivo is of extreme interest. Liu and Rasband provided a nice overview of the axonal spectrin, a key cytoskeletal molecule determining the microstructure of the axons. Thanks to the recent development of super-resolution microscopy, the periodic spatial organization of ring-like structures of actin and subcellular arrangement of spectrin implicate the pivotal role of actin-spectrin cytoskeletons in determining axonal excitable domains such as AIS and nodes of Ranvier. Bonetto et al. reported the early steps of compartmentalization of Kv1 channels and associated molecules preceding myelination of axons in cultured hippocampal GABAergic neurons. Although K+ channels are well-known to localized at nodes and juxtaparanodes to secure spike propagation along myelinated axons, they demonstrated that Kv1.2 channels are highly expressed all along the axons and the AIS before myelination, in contrast with “pre-nodes” localization of NaV1 channels. Rozov et al. provided an overview of the current understanding of the underlying mechanisms for asynchronous transmitter release from the axon terminals. Ca2+ sensors, Ca2+ sources, and Ca2+ extrusion mechanisms may coordinate to limit the prolonged time course of the asynchronous release. Although high-affinity Ca2+ sensor Syt7 has been suggested to play key roles in the asynchronous release, the contribution of other synaptotagmins as well as the Na+/Ca2+ exchanger (NCX) which determine the rate of Ca2+ extrusion is needed to be determined in future investigation. Goaillard et al. summarized the roles of dendrite geometry in the output of action potentials and transmitter release. The authors overviewed the examples of “non-canonical polarity neurons” and even axon-less neurons. They also discussed the case of dorsal root ganglion neurons as an example of unipolar neurons. The diversity of axonal and dendritic roles in shaping neuronal output is of importance for the understanding of neuronal functions.This Research Topic puts special emphasis on the understanding of basic mechanisms underlying fine-tuning of the excitability of the axons. In this line, a few articles nicely reviewed and summarized the current understandings of the functional significance of the excitability tuning of the axons as well as the underlying molecular identities. In combination with the historical views as well as the recent updates on the biophysical properties of axons, Emmenegger et al. provided a nice and concise overview of the methods for studying the propagation of action potential along the axons, i.e., subcellular patch-clamping from the axon, genetically encoded voltage imaging, and CMOS technology-based high-density microelectrode arrays (HD-MEAs). With high temporal resolution and spatial information obtained by recordings with HD-MEAs covering the entire course of axon arbors of cultured hippocampal neurons, the authors focused on fundamental studies on action potential propagation. Bullmann et al. introduced a novel approach for high-throughput scanning of axonal arbors and mapping of axonal delays using cultured cortex neurons grown on HD-MEAs. With a high temporal and spatial resolution of HD-MEA recordings of axonal spikes, they provided the evaluation of axon segmentation and enabled high-throughput functional mapping of axon arbors. Rama et al. adopted simultaneous imaging of presynaptic Ca2+ entry and glutamate release at the hippocampal mossy fiber boutons using biolistic transfection of glutamate sensor SF-iGluSnFR and introduction of Ca2+ indicator Cal-590 in granule cells from organotypic hippocampal cultures. This technique offers a unique opportunity to evaluate the relationship between presynaptic Ca2+ and glutamate release across multiple release sites within the individual presynaptic terminals. With this multiplexed imaging, they demonstrated the evidence for the existence of distinct release sites of glutamate at the mossy fiber synapse. Nagendran and Taylor investigated the intrinsic injury mechanisms following axotomy. Using cultured hippocampal neurons grown on microfluidic chambers, they revealed that Na+ influx and reversal of NCX induce dendritic spine loss. The authors also report that Ca2+ release from the axonal endoplasmic reticulum (ER) plays a critical role in trans-synaptic hyperexcitability following axotomy.Several studies also illustrate novel experimental methods to overcome the limitation of previous approaches. Zbili and Debanne addressed the contribution of myelination on length constant of analog-digital facilitations (ADFs), a graded modulation of transmitter release due to subthreshold depolarization of axonal membranes. This study demonstrated that myelination enhances the axonal length constant thus suggesting a possible functional significance of ADFs in myelinated axons. An important notion is that the enhanced spatial extent of ADFs with myelination may enhance the contribution of ADFs in fine-tuning of neuronal information processing. An advantage of the modeling approach was further highlighted by the review by Kamiya which focused on the mechanism underlying afterdepolarization that follows axonal action potentials. Using a realistic model of hippocampal mossy fibers in combination with a direct recording from the axon terminals, the author clearly shows the substantial contribution of a capacitive component in axonal afterdepolarization. This study also suggests that voltage-dependent K+ and Na+ conductance play a critical role in shaping time course of afterdepolarization lasting for several tens of ms. Holland et al. discussed alternative solutions for the famous Hodgkin-Huxley (HH) model of the action potential that entirely lies on the electrical nature of the nerve impulse propagating along the axon. Non-electrical factors such as the mechanical and/or thermal changes are taking into account for an attempt to propose a unified model that takes into account the mechanical wave by the pressure pulse of axoplasm and represents the process of nerve impulse propagation accurately. This paper gave insight into the fundamental understanding of the neve impulse propagating axon. Daur et al. addressed the interaction of different spike initiation sites of proximal and distal axons of the unmyelinated motor axon of the lobster with the simultaneous recordings from the two sites of the same axons. The author points to the fact that centrally generated bursts occurring in the proximal axons and peripheral “ectopic” spike initiation from distal axon show mutually suppressive influence. Although the functional significance of ectopically generated action potentials is not fully understood, this implies that they play an important role in shaping the output of the neuronal network. It is also noteworthy that these rules can be generalized to understanding axonal information processing in the mammalian central nervous system.This Research Topic also highlighted the advantage of modeling approach due to the limitation of the experimental approach in axon physiology. Since the information based on the experimental findings is limited for quantitative evaluation, a simulation approach based on a simple assumption might help in testing the quantitative validity of the hypothesis. Using computer modeling, As overviewed above, this Research Topics illustrated the current state of knowledge on axon neurobiology, of fundamental importance for the bottom-up approach in the understanding of brain functions. It is also obvious that our continuing efforts to understand axon function will require a combination of cutting edge optical techniques for imaging fine structures with super-resolution technologies (Chéreau et al., All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Interferometric phase filtering is a crucial step in multibaseline interferometric synthetic aperture radar (InSAR). Current multibaseline interferometric phase filtering methods mostly follow methods of single-baseline InSAR and do not bring its data superiority into full play. The joint filtering of multibaseline InSAR based on statistics is proposed in this paper. We study and analyze the fourth-order statistical quantity of interferometric phase: kurtosis. An empirical assumption that the kurtosis of interferograms with different baselines keeps constant is proposed and is named as the baseline-invariant property of kurtosis in this paper. Some numerical experiments and rational analyses confirm its validity and universality. The noise level estimation of nature images is extended to multibaseline InSAR by dint of the baseline-invariant property of kurtosis. A filtering method based on the non-subsampled shearlet transform (NSST) and Wiener filter with estimated noise variance is proposed then. Firstly, multi-scaled and multi-directional coefficients of interferograms are obtained by NSST. Secondly, the noise variance is represented as the solution of a constrained non-convex optimization problem. A pre-thresholded Wiener filtering with estimated noise variance is employed for shrinking or zeroing NSST coefficients. Finally, the inverse NSST is utilized to obtain the filtered interferograms. Experiments on simulated and real data show that the proposed method has excellent comprehensive performance and is superior to conventional single-baseline filtering methods. Interferometric synthetic aperture radar is an important extension of synthetic aperture radar (SAR), which is extensively adopted to topography surveying , surfaceAs matters stand, the filtering methods of multibaseline InSAR are mainly divided into two categories. One applies the filtering method of single-baseline InSAR to denoise multiple interferograms separately. The filtering method of single-baseline InSAR is divided into two parts: the method in spatial domain and the method in transform domain. Some spatial filters, such as boxcar filter , Lee filAnother category is the multibaseline joint filtering method. The strategy of multibaseline InSAR filtering methods is divided into two parts. One works on the SAR data stacks. NL-InSAR can be regarded as a special case of this part, and the number of SAR images is two. The filtered interferogram is extracted from the covariance matrix. And the covariance matrix is estimated with help of the average effect of statistically homogeneous pixels which have a similar statistical distribution with the central pixel ,18,19,20This paper is an exploration of multibaseline interferometric phase filter based on the statistical characteristic. We propose a new filter on the basis of the NSST filter which is a part of the wavelet filter. The interferogram contains a large number of edges, fringes and other high-dimensional anisotropies. The NSST produces a multi-scaled and multi-directional sparse representation to images optimally and drives a more meticulous depiction of the high-dimensional anisotropies. The interferogram is decomposed into coefficient components with various scales and directions. the coefficient component involves little significant information with large amplitude and noise spreading in whole frequency domain. Coefficients, which are considered as noise are removed immediately, while the significant information is retained or shrinked. A pre-thresholded Wiener filter  is appliThe noise variance, which decides whether the coefficient is zeroed or retained, is a critical parameter of the Wiener filter. The accuracy of noise variance determines whether the performance of the wiener filter is optimal. A noise level estimation framework which is conceptually similar to the method in Reference  is propox is the ideal phase deduced by the natural topography. y is the observed phase disturbed by the zero mean noise n, which is assumed to be independent of x. The phase jump ranged from In the case of single-look, the probability density function of interferometric phase can be represented as . The intThe real part and the imaginary part can be expressed asS is the anisotropic dilation matrix related to scale transformation. j denotes the scale parameter in particular, which dominates the refinement of frequency and the redundancy of basis elements. G is the shear matrix related to geometrical transformation. l denotes the shear parameter which restricts the orientation of each shearlet element. Moreover, k indicates the shift parameter to locate distributed discontinuities in spatial domain. Calculating the Fourier transform to elements Wavelet is prone to deal with 1-D signals existing pointwise singularities. Nevertheless, it is weak to handle multidimensional data dominated by distributed discontinuities, such as edges and fringes. In an effort to solve this problem, the wavelet basis with much higher directional sensitivity and more flexible shapes is encouraged for effectively capturing the singularity features of multidimensional data, involving composite wavelets , contourIt has frequency support as . The freThe asymptotic approximation error of the shearlet transform is when N→∞ . So it pof −l2−j . The corIn practice, the shearlet is shift-variant. The shearlet transform adopts the shift operation of the window function to realize the directional filtering. It involves a subsampling operation, which causes spectral aliasing in frequency domain. Thereby the Gibbs distortion occurs in the reconstructed image. To solve this problem, Easley and Labate proposed the nonsubsampled shearlet transform (NSST) which is enlightened by the great performance of the nonsubsampled contourlet transform. The NSST replaces the subsampled operation with convolution in the directional filtering. It is shift-invariant and efficiently eliminates the pseudo-Gibbs phenomenon in reconstructed images. Hereby the reconstructed image is more effective and intuitive. The decomposition procedure primarily contains two steps as shown in j scales.The image is decomposed into a high-frequency component and a low-frequency component by means of non-subsampled pyramid (NSP). Then iteratively execute this step till image is decomposed into the The core of direction localization is non-subsampled shearing filter banks (NSSFB), which impose the 2-D convolution of the shearing filter and the high-frequency component on the cartesian domain. The convolution averts subsampled operation, thereby the NSST is shift-invariant.On account of the shift-invariant property, the NSST displays great performance in image denoising, particularly for the texture image. It is also desirable that the NSST filter exploits the coefficient shrinkage method which is consistent with the wavelet filter. Shearlet gives a sparse expression to images. That is to say, the intrinsical information of image is concentrated on few coefficients spreading over each scale with a considerable large amplitude. By contrast, shearlet coefficients generated by noise widely distribute in shearlet domain and its amplitude is small. Owing to this feature, a more accurate pre-thresholded Wiener filtering method with known noise variance is employed to remove the noise component. It consists of two steps:the pre-thresholded operation and Wiener filter. The pre-thresholded operation ensures the smaller local expected square error (LESE) of linear approximation, which is represented asThen the Wiener filter obtains the best linear estimation of clean images. It is represented asThe noise variance is the crux of the Wiener filter. The robust noise level estimator  designedIn this section, the kurtosis of the interferometric phase is introduced. And a special property of the kurtosis is proposed in multibaseline InSAR and is named as the baseline-invariant property. Along with the idea in Reference , the basY is defined asThe image is decomposed into various coefficient components at different scales and directions by NSST. The research on the distribution of NSST coefficient components is conducive to the further analysis of images and is a significant topic in image processing. Among them, the research on its statistics is of great potential. The low-order statistic is weak, even invalid in interferograms which involve a large amount of textures and detail informations. Consequently, the scholar begins with the study of its higher-order statistic, such as kurtosis and skewness. In this section, we study and analyse the kurtosis of interferograms and NSST coefficient components. The kurtosis of a random variable Y.The proposed method takes advantage of two vital properties of the kurtosis of interferograms. One is the scale-invariant property, which works well on all natural images, that is, the kurtosis of coefficient components in the Linear Transform Domain should be held constant at different scales. It is verified and revised by some work in References ,32,33. AAnother property, which is particular to interferograms and can be yielded from an empirical summary, is proposed in this paper. The kurtosis of images with similar structure or statistical behavior is assumed to be a constant . Along thttp://www.gscloud.cn). The elevation data and typical interferograms of them are shown in Some simulated analyses prove the baseline-invariant property. In order to verify the validity of that property for various types of interferograms (generated by various topographies), we select the DEM of five common topography, including Cone, Building, the Northeast plain, China , the Sichuan Basin, China, Mangkang Mountain, Tibet, China . All primordial elevation data are derived from simulated data and Shuttle Radar Topography Mission DEM (SRTM-DEM) elevation data which is provided by Geospatial Data Cloud site, Computer Network Information Center, Chinese Academy of Sciences =C4Since the assumption that ced from  and 21)ni obeys ced from .(22)κ23).(24)model in . Then thThe aforementioned optimization function is constrained and non-convex optimization problem with two variables: the vector A is a diagonal matrix of B is a symmetric matrixthe vector Ignoring the second item which is independent with Then the optimization function can be simplified asBecause Similarly, fix shown in .(27) algorithm, optimal integration-based adaptive direction filter (OADF), iterative NL-InSAR and InSAR-BM3D. Finally, the proposed method on real interferograms will be tested. For simplicity, the proposed method is termed as NSST in the following sections.The parameters of various filters are set asThe key of the proposed method is noise variance estimation. In this section, we verify the accuracy of the estimated noise variance on simulated data. The original elevation model is a cone, as shown in The comparison between the estimation and the mean implies the accuracy and stability of the proposed method. The maximum error rate is calculated to evaluate the estimation accuracy and is defined asIn this section, we simulate three interferograms of cone and mountain to assess the performance of the proposed method. The noise environment comprises two situations: constant and variable noise variance in spatial domain. It is necessary for comparative experiments within each section. The experiments in interferograms with unitary noise variance are conducted to inspect the reconstructed performance for phase jump and phase gradient mutation. We select interferograms with Intuitively, the result of the Goldstein method is incorrect. There are obvious errors in OADF and LFE. NL-InSAR, InSAR-BM3D and the proposed method all obtain appreciable results. The mean square error (MSE) between the clean interferogram and the filtered interferogram confirms above statements. What is more, The second row of Considering a more complex noise level model in the second experiment, in which the coherence ranges from 0.1 to 0.9 and increases from left to right at regular intervals. o and f. The gradient magnitudes is derived from  ,35 betweved from  and 32)(30)GMS(ived from .(33)hx=It should be noted that the larger the GMS value is, the higher the quality of the restored image is. When MSE: NSST>InSAR-BM3D>NL-InSAR>OADF>LFE>GoldsteinGMSM: NSST>InSAR-BM3D>NL-InSAR≥LFE>OADF>GoldsteinComputation efficiency: Goldstein>NSST>InSAR-BM3D>OADF>LFE>NL-InSARAs a whole, our method is superior to other methods.We consider a more complex topography to test the performance of various methods. The elevation data of a steep mountain in Shaanxi Province, China is selected to generate three interferograms. Coherence is consistent with last experiment. The size of interferograms is The original data set is three repeat-orbit InSAR data at Colorado Grand Canyon, USA, which is obtained by Alos-1 satellite. Results are shown in In order to further compare various methods, the low-coherence region in the upper right corner  is cropped to further analysis. Eight phase profiles along the phase gradient direction, which involve intact phase period and satisfy local stationarity, are extracted for contrast. White lines in An attempt to the joint filtering method in multibaseline InSAR based on the statistical property of interferometric phase is proposed in this paper. This paper analyses the high-order statistical property of interferograms with different baseline and proposes an empirical assumption: the kurtosis of interferograms with different baseline keeps invariant. Simulated experiments give numerical support to it. The filtering process of the proposed method involves four parts: the NSST decomposition, the noise level estimation, pre-thresholded Wiener filter and inverse NSST. NSST gives an optimal sparse representation of distributed discontinuities, such as fringes of interferograms. We obtain a series of NSST coefficients at different scales and directions after NSST decomposition. Based on the kurtosis model in NSST domain and baseline-invariant property of interferograms, the noise variance of interferograms is represented as the solution of a constrained non-convex optimization problem. The clean NSST coefficient is estimated by the Wiener filter with the local noise variance derived by block estimation. The noise estimation experiments prove the validity of the noise level estimator. Experiments on simulated data and real data prove the edge-preservation performance and excellent filtering performance of the proposed method. Many coefficient components with the same kurtosis are obtained by NSST. Sufficient data means that the filtering performance of the proposed method is not affected by the number of interferograms. The great performance can be acquired when the number of interferograms is small. However, a large amount of memory is occupied by a large number of coefficient components. The algorithm has some requirements for memory performance. But this problem can be alleviated by adjusting the scale of NSST decomposition according to the actual computer performance.


We showed a decrease in glutathione peroxidase and superoxide dismutase activity and an increase in catalase activity in the hypothalamus of HSD rats compared to controls. The activity of xanthine oxidase and NADPH oxidase and the contents of oxidation (protein carbonyls), glycoxidation  and protein glycation products (advanced glycation end products and Amadori products) were significantly higher only in the hypothalamus of the study group. The HSD was also responsible for the disruption of antioxidant systems and oxidative damage to blood proteins, but we did not show any correlation between systemic redox homeostasis and the brain levels. In summary, HSD is responsible for disorders of enzymatic antioxidant defenses only at the central (plasma/serum) and hypothalamic levels but does not affect the cerebral cortex. The hypothalamus is much more sensitive to oxidative damage caused by an HSD than the cerebral cortex.Despite several reports on the relationship between metabolic and neurodegenerative diseases, the effect of a high-sugar diet (HSD) on brain function is still unknown. Given the crucial role of oxidative stress in the pathogenesis of these disorders, this study was the first to compare the effect of an HSD on the activity of prooxidative enzymes, enzymatic and non-enzymatic antioxidants, and protein oxidative damage in the brain structures regulating energy metabolism  and cognitive functions . Male Wistar rats were randomly divided into two groups ( The 21st century is defined as an epidemic of metabolic diseases that not only significantly reduce the quality of life of patients but are also the main cause of death worldwide. The decreased sensitivity of peripheral cells and tissues to insulin, which is called insulin resistance (IR), contributes to the metabolic disorders in the course of obesity, type 2 diabetes and metabolic syndrome . The binIn our previous studies, we demonstrated that a high-sugar diet (HSD) both interferes with systemic redox homeostasis (plasma/serum) and induces oxidative stress at the salivary gland level . Interesn = 20) were randomly divided into two groups. The control group was fed a control diet  consisting of 70 kcal% carbohydrates , 20 kcal% protein and 10 kcal% fat. The HSD group was fed a high-sucrose diet  composed of 70 kcal% carbohydrates , 20 kcal% protein and 10 kcal% fat . The calorie content of both diets was the same and amounted to 3.85 kcal/g. The body weights of the animals and food intake were monitored weekly. The body mass index (BMI) was calculated with the formula BMI = body weight (g)/length2 (cm2)   . The thi2/[GSSG] . The totAll the assays were performed with duplicate samples both of the brain samples and of the plasma. The results were standardized to one mg of total protein.+)  ratio and the total glutathione levels remained unchanged after 8 weeks of the diet experiment compared to those in the control rats  in the plasma of HSD rats, whereas CAT activity remained unchanged and the SOD level was even lower (−29%) compared to that in the control group . The urirol rats . Only throl rats . All of rol rats .The activity of xanthine oxidase in the hypothalamus was significantly higher (+17%) in HSD rats than in CD animals, whereas in the cerebral cortex, it remained unchanged . FurtherGPx and SOD-1 activities in the hypothalamus were lower in HSD-fed animals than in the controls , whereas in the cerebral cortex, their values remained unchanged by the diet . SOD-1 a2/[GSSG] ratio did not differ in both the cerebral cortex and hypothalamus in any of the studied groups , Amadori products (+31%), PCs (+173%), dityrosine (+29%) and kynurenine (+29%) . The conNO and CAS-3 were higher only in the hypothalamus  of HSD rats when compared to the controls . Moreover = 0.698, p = 0.05; r = 0.754, p = 0.029). NOX and XO were also positively correlated with AGE content . We did not demonstrate such relationships in the cerebral cortex of HSD animals or in either of the studied brain structures of the control animals.In the hypothalamus of HSD rats, a high positive correlation between the activity of prooxidative enzymes (NOX and XO) and CAT activity was shown  as well as PC  content only in the hypothalamus of HSD rats.We demonstrated a positive correlation between CAT activity and AGE  as well as higher oxidative damage to proteins  compared to in rats fed a standard diet . These o2O2 concentration), increased CAT activity may suggest an enhanced production of free radicals in the hypothalamus of the rats from the study group. Indeed, both CAT and GPx are involved in the cytotoxic decomposition of hydrogen peroxide, but CAT is active at high and GPx at low intracellular H2O2 concentrations [Aerobic organisms have developed both enzymatic and non-enzymatic antioxidant systems in order to protect against ROS overproduction. However, the activity of brain antioxidant enzymes (compared to those in other tissues) is relatively low . Our stutrations ,51.Interestingly, we did not observe any changes in the total antioxidant capacity and total oxidant status or differences in glutathione metabolism between the studied brain structures. However, in the hypothalamus of HSD rats, we noted a significantly higher oxidative stress index (compared to in the controls), which indicates a shift in brain redox homeostasis towards oxidation reactions. Indeed, this parameter (OSI = TOS/TAC) predisposes the biological system to oxidative stress . MoreoveThe consequence of the disruption of antioxidant systems as well as increased activity of prooxidant enzymes is the increased oxidation of hypothalamic proteins . This hypothesis is confirmed by a positive correlation between the activity of antioxidant enzymes (CAT) and the products of oxidation (PCs) and glycation of proteins (Amadori products and AGEs) in the hypothalamus of HSD rats, and a positive correlation between the activity of prooxidant enzymes and AGEs. However, such changes were not observed in the cerebral cortex of rats from the study group.The main cell components that undergo oxidation and glycation processes are proteins ,55. InteWe did not observe increased carbonyl stress or apoptosis in the cerebral cortex of HSD rats. Moreover, the efficiency of the antioxidant barrier and the activity of prooxidant enzymes in the cerebral cortex did not differ significantly between the study and control groups. Therefore, we conclude that the hypothalamus is much more sensitive to HSD-induced oxidative damage. This organ, due to the synthesis and secretion of numerous hormones, regulates lipid and carbohydrate metabolism. Indeed, the hypothalamus is characterized by a high density of insulin receptors, which are involved in the central control of the metabolism of peripheral tissues as well as regulation of appetite and satiety ,68. HoweOur work, despite its undoubted advantages, also had certain limitations. We evaluated only the most commonly used redox and apoptosis biomarkers, so we cannot fully compare the effect of the HSD on redox homeostasis in the brain as well as plasma/serum. Furthermore, our study did not include the assessment of cognitive functions in rats, so we were unable to determine whether OS in the hypothalamus results from hyperglycemia or other metabolic disorders caused by the HSD. Therefore, this work is a starting point for further research, both experimental and clinical.(i) A high-sugar diet disrupts redox homeostasis, not only at the systemic but also local  level.(ii) Disorders of the enzymatic antioxidant defense caused by an HSD were observed only at the central (plasma/serum) and hypothalamic levels. However, it is necessary to assess cognitive function in order to confirm or exclude the neuropathological disturbances caused by a high sugar intake.(iii) The hypothalamus is much more sensitive to oxidative damage caused by an HSD than the cerebral cortex.


The absolute positioning accuracy of a robot is an important specification that determines its performance, but it is affected by several error sources. Typical calibration methods only consider kinematic errors and neglect complex non-kinematic errors, thus limiting the absolute positioning accuracy. To further improve the absolute positioning accuracy, we propose an artificial neural network optimized by the differential evolution algorithm. Specifically, the structure and parameters of the network are iteratively updated by differential evolution to improve both accuracy and efficiency. Then, the absolute positioning deviation caused by kinematic and non-kinematic errors is compensated using the trained network. To verify the performance of the proposed network, the simulations and experiments are conducted using a six-degree-of-freedom robot and a laser tracker. The robot average positioning accuracy improved from 0.8497 mm before calibration to 0.0490 mm. The results demonstrate the substantial improvement in the absolute positioning accuracy achieved by the proposed network on an industrial robot. Although industrial robots are flexible platforms and provide high repeatability for the automation of a variety of manufacturing tasks, a low absolute positioning accuracy may limit their applicability . Error sExtensive reports have shown that kinematic errors account for about 90% of the total positioning error . TherefoRobot calibration aims to optimize an objective function and obtain accurate kinematic parameters . The mosGiven the difficulty to model non-kinematic errors, artificial neural networks have been used as an alternative to compensate the absolute positioning error . Neural The performance of neural networks is influenced by their structure and parameters. To optimize neural networks, Rouhani et al. introduced one-pass heuristic rules to determine the center, number, and spread of hidden neurons in the network . Feng etThe main contributions of this work can be summarized as follows. (1) The influence of kinematic and non-kinematic errors on the absolute positioning accuracy is analyzed, and the limitations of kinematic calibration are addressed. (2) A neural network optimized using differential evolution is proposed to enhance the absolute positioning accuracy. Thresholds, initial weights, and the number of hidden neurons in the neural network are optimized using differential evolution to improve the performance of the neural network. The proposed network mitigates the effects of kinematic and non-kinematic errors and thus improves the absolute positioning accuracy of a robot. (3) The experiment and simulation are completed with the six-DOF robot as the research object and the laser tracker as the measuring instrument. The theoretical correctness and effectiveness of the proposed neural network are verified by simulations and experiments.The remainder of this paper is organized as follows: The influences of kinematic and non-kinematic errors on robot positioning accuracy are analyzed in The accuracy of a robot kinematic model depends on robot calibration. We use the POE model to describe the robot kinematics , consideThe pose of end-effector frame For a rotational joint, the exponential matrix of the motion screw can be represented asThe forward kinematics of a six-DOF serial robot is given byThe kinematic parameters of the robot generally deviate from their designed values due to different kinematic errors such as mechanical deformation, assembly and machining errors etc., as shown in When the kinematic errors are only considered, the actual robot position However, non-kinematic errors undermine accuracy, but they are generally neglected due to their modeling difficulty and complexity. All error sources whose contributions to positioning errors cannot be characterized by kinematic parameters are herein described as non-kinematic errors . The nonConsidering non-kinematic errors, the actual robot joint variable can be expressed asm denotes the order of the Chebyshev polynomial and We can use Chebyshev polynomials to calculate Ci(θ^i) :(9)CiEncoding solution population;(2)Fitness function to evaluate solution optimality;(3)Evolutionary operation comprising selection, crossover and mutation.The differential evolution algorithm typically consists of three elements: Individual g is the number of iterations, For differential evolution, mutation is expressed asTest individuals Thus, for each parameter of the particle, crossover can be expressed asSelection is based on a greedy search strategy expressed asi and The optimized parameters during pre-training are applied to the proposed neural network. If the predicted values after pre-training do not reach the expected deviation, the number of hidden layers of each particle is updated using Equation (22). This procedure is repeated until the desired values are obtained.We validated the performance of the proposed neural network through simulations and experiments of error compensation on a six-DOF robot manipulator. For comparison, the robot kinematic parameters were calibrated using the POE model  and LM aAs described in standard ISO 9283 [n times, j-th attained pose along the respective axes.Thus, the positioning accuracy can be calculated asAnalogously, the distance accuracy expresses the deviation in positioning and orientation between the command distance and mean of the attained distances, as illustrated in The distance accuracy can be calculated asWe use both the distance accuracy and positioning accuracy to quantify error compensation.To perform simulations, we added random parameter errors to the theoretical robot kinematic parameters as actual parameters and non-kinematic errors as the compensation of the nominal joint variables of the robot. The actual and theoretical end-effector position coordinates of the robot were calculated using the POE model.We applied 1000 pairs of joint variables and position coordinates to optimize the thresholds, initial weights, and number of hidden neurons in the proposed network using differential evolution. The same 1000 samples were applied to train the optimized neural network, and 100 command points were employed for verification of the prediction accuracy of the trained neural network. In addition, the robot kinematic parameters were calibrated using the POE model and LM algorithm for comparison by applying the same samples. The compensation results are shown in Compared to the calibration method, the proposed neural network optimized using differential evolution provides better compensation. The maximum distance accuracy is improved from 3.1760 mm to 0.7743 mm, and the average distance accuracy is improved from 1.1118 mm to 0.1564 mm by using the proposed network. The maximum positioning accuracy is improved from 3.1760 mm to 0.7743 mm and the average positioning accuracy is improved from 0.7411 mm to 0.1007 mm by using the proposed algorithm.As summarized in The calibration system, as shown in We measured 600 samples in the workspace of the robot for optimization and training of the proposed network. The same samples were used for calibration of kinematic parameters using the POE model and LM algorithm. The samples were selected such that the corresponding joint variables covered the robot joint working ranges, as shown in The absolute positioning accuracy of robots has become increasingly important to support their widespread applications, particularly when offline programming is required. Error sources in robots can be classified into kinematic and non-kinematic errors. Conventional calibration can reduce the influence of kinematic errors on positioning accuracy, but the complexity of non-kinematic error sources and modeling hinders the compensation of such errors.We applied a neural network to compensate both kinematic and non-kinematic errors with the aim of improving the absolute positioning accuracy of robot manipulators. The proposed network can avoid complex modeling while comprehensively considering the influence of all error sources. As the performance of a neural network is influenced by its structure and parameters, we optimized the proposed network using differential evolution. The thresholds, initial weights, and number of hidden neurons in the network are optimized using differential evolution to improve efficiency and performance. Using the proposed network, the effects of kinematic, and non-kinematic errors decreased, thus improving the absolute positioning accuracy of an industrial robot.The theoretical correctness and effectiveness of the proposed method are verified by simulations and experiments on a six-DOF serial robot and compared with calibration using the POE model and LM algorithm. The absolute positioning accuracy improves using the proposed network, and the experimental results verify the correctness and effectiveness of the network. After calibration, the robot average distance accuracy improved from 0.8497 mm before calibration to 0.04933 mm. Likewise, the robot average positioning accuracy improved from 3.176 mm before calibration to 0.7743 mm.


Enzyme-responsive polymers and theirassemblies offer great potentialto serve as key materials for the design of drug delivery systemsand other biomedical applications. However, the utilization of enzymesto trigger the disassembly of polymeric amphiphiles, such as micelles,also suffers from the limited accessibility of the enzyme to moietiesthat are hidden inside the assembled structures. In this Perspective,we will discuss examples for the utilization of high molecular precisionthat dendritic structures offer to study the enzymatic degradationof polymeric amphiphiles with high resolution. Up to date, severaldifferent amphiphilic systems based on dendritic blocks have all shownthat small changes in the hydrophobicity and amphiphilicity stronglyaffected the degree and rate of enzymatic degradation. The abilityto observe the huge effects due to relatively small variations inthe molecular structure of polymers can explain the limited enzymaticdegradation that is often observed for many reported polymeric assemblies.The observed trends imply that the enzymes cannot reach the hydrophobiccore of the micelles, and instead, they gain access to the amphiphilesby the unimer–micelle equilibrium, making the unimer exchangerate a key parameter in tuning the enzymatic degradation rate. Severalapproaches that are aimed at overcoming the stability–responsivenesschallenge are discussed as they open the way to the design of stableand yet enzymatically responsive polymeric nanocarriers. It is clear that for a micelle to serve as a drug deliveryplatform it must be extremely stable against dilution and degradationbefore it reaches its target. At the same time, a drug release mechanismis needed to allow the delivery of the drug to the target site. Manyrelease mechanisms have been explored, ranging from simple diffusionof the drugs from the carrier to more sophisticated stimuli-responsivepolymeric micellesTogether with the great potentialof enzymes to trigger the releaseof hydrophobic drugs, enzymatic activation holds one key differencefrom other types of stimuli—the accessibility of the enzymeto the enzyme-responsive moieties. In comparison with dimensionlessstimuli such as light and temperature, or low molecular weight speciessuch as protons (or hydronium ions) in the case of pH-responsive assemblies,the significantly larger dimensions of enzymes can drastically limittheir accessibility to the responsive groups.41 Taking advantage of the high molecular precision that emerges fromusing a dendron as the hydrophobic block, we studied how fine-tuningof the amphiphilicity, mostly by altering the structure of the hydrophobicdendron, affects the self-assembly and enzymatic degradation of ourPEG-dendron amphiphiles. In this Perspective we will share our understandingof the enzymatic degradation mechanism by discussing our results togetherwith key examples of enzyme-responsive polymeric assemblies that haveinspired our own research. We will focus only on highly precise dendriticsystems and their utilization to study the effect of fine structuralchanges on the enzymatic activation/degradation and cargo releasewith high resolution. In our opinion, the study of such systems, whichbenefit from the well-defined and precise dendron-based structureof the amphiphile, can shed more light on the limitations and challengesthat need to be addressed to gain a better understanding of the designprinciples of enzymatically degradable polymeric nanocarriers andenzyme-responsive materials in general.In the past fewyears, we have been studying polymeric amphiphilesbased on linear PEG as the hydrophilic block and dendron containingenzymatically cleavable lipophilic end-groups as the hydrophobic block.42 In that work, monofunctional PEG was used to polymerize protectedphosphate bearing styrenic monomers, which after the deprotectionof the phosphate group yielded a double hydrophilic block copolymer.The polymers were designed to be soluble in aqueous solution and toself-assemble upon enzymatic cleavage of the phosphate side groupsfrom the styrenic block as its hydrophobicity increased due to theremoval of the charged solubilizing moieties. This enzymatic activationtransformed the diblock copolymers to become amphiphilic, leadingto their self-assembly into spherical colloidal nanostructures. Interestingly,when following the degree of dephosphorylation directly by 31P NMR, a substantial amount of phosphate groups (∼40% forthe shorter block with degree of polymerization (DP) of 13 and ∼10%for a longer block with DP of 30) remained on the styrenic block.Further evidence for the residual phosphate groups was revealed ina fluorescent assay using pyrene, which indicated greater polarityof the enzymatically assembled structures in comparison with the fullydephosphorylated amphiphilic block copolymer, which was used as acontrol. These results demonstrate that once the polymers become amphiphilicand start to self-assemble, the residual phosphate groups, which arelinked to the core-forming block, become inaccessible to the enzyme,and their cleavage rate becomes negligible. Similar trends in enzymaticdegradation of phosphorylated polypeptides due to limited accessibilityof the enzyme to the phosphate side groups were recently reportedby Gupta and co-workers.43Striking evidence for the limitedaccessibility of an enzyme toits substrates when they are attached to a polymeric backbone wasreported by the Hawker group in 2009.n-butyl acrylate) as the hydrophobic block.34 In their paper, Heise and co-workers hypothesized thatthe limited degradation of the amphiphiles based on PS was due tothe higher Tg of the PS chains and theresulting limited exchange and escape from the micelles. The highstability of self-assembled DNA-based nanoparticles, as reported bythe Mirkin group,44 further supports thelimited access of degrading enzymes even to the outer shell of nanosizedassemblies. However, reading through the literature, it is clear thatthere are also numerous papers and reviews that describe the enzymaticallyinduced disassembly of different polymeric amphiphiles.51 Do these reports stand in contradiction to the hypothesis of limitedaccess of the enzyme to the polymeric chains, which result in higherstability and poor responsiveness of polymeric assemblies toward enzymaticdegradation? Or is there another mechanism that can still allow accessof the enzyme to its hydrophobic substrates  or poly. Enzymatic cleavageof the hydrophobic moieties by porcine liver esterase (PLE) shouldresult in increased hydrophilicity of the degraded dendrons, leadingto their disassembly.52 a clear trend could beobserved from dye release experiments—a zero-generation (G0)dendron bearing a single hydrophilic chain and a single enzymaticallycleavable aliphatic ester dissembled much faster than higher molecularweight dendrons (first- to third-generation dendrons), which showedsignificantly slower dye release and disassembly rates as the generationof the dendrons increased ,54 respectively. These studies included also theimpressive capability to precisely label the focal, middle layer,or periphery of first- and second-generation dendrons with biotinand the use of molecular dynamics to gain a deeper insight into thestructural parameters that govern the protein–ligand interactions.55 The results showed that the interaction of thedendrons with the protein, through ligand–protein binding,significantly change the amphiphilicity of the dendron–proteincomplexes leading to disassembly of the micellar assemblies. On thebasis of the trends in disassembly and cargo release, it seems thatthe protein-responsive amphiphiles interact with the protein at theirunimer state.54 This hypothesis was a key findingthat was later suggested also for enzyme-responsive amphiphiles, whichjust like their protein-responsive analogues, need be accessible tothe enzyme to allow the enzymatic reaction to take place.In parallel to theirreports on enzyme-triggered disassembly ofdendrimer-based assemblies, the Thayumanavan group also studied theability of protein–ligand interaction to induce disassembly3. Dendro56 Conjugating these dendrons to well-definedoligoethylene imine with specific numbers of repeat units (2–5)yielded oligomeric amphiphiles with distinct molecular weights  as the PEG chains gotlonger. In addition, we found that the increase in length of the PEGchain resulted also in higher critical micelle concentration (CMC)values . The utilization of a dendron to presentthe cleavable end-groups allowed all of the cleavable end-groups tobe terminal and highly symmetrical, which was found to be highly advantageousfor the detailed characterization of the enzymatic degradation. Furthermore,the monodispersity of the dendritic block allowed us to use HPLC todirectly follow the cleavage of the end-groups by the activating enzymeand track the formation of both partially and fully cleaved amphiphiles. However, the size of the micelles was strongly influencedby the increase in hydrophobicity as the diameter of the micellesincreased by 8 nm going from the hexanoic-based amphiphiles to thenonanoic ones and another 8 nm increase for the undecanoate. Thisincrease in size cannot be rationalized when considering only thelonger length of the end-groups, which got elongated by only a fewmethylene units and hence can contribute to an increase of a few angstroms.Using small-angle X-ray scattering (SAXS), we could estimate thatthe aggregation number nearly doubled upon the increase in hydrophobicityof the end-groups, leading to the significant increase in diameter.Strikingly, the differences in the degradation and disassembly rateswere even more significant, and while the hexanoate-containing amphiphileswere readily degraded upon addition of the enzyme, the nonanoate-containingPEG-dendrons were fully cleaved only after 24 h when incubated withsignificantly higher concentration of the enzyme . The uniqueness of the system is the fast responsethat is achieved by the ability to present the hydrophilic enzyme-cleavablegroups on the surface of the polymeric assemblies, which make themhighly accessible to the enzyme. This elegant approach, which placesthe enzymatic cleavage sites on the surface of the polymeric assembliesand hence significantly enhances their availability to the activatingenzyme, overcomes the need to balance between stability and responsiveness.However, it comes with two significant price tags: release of electrophilicspecies that are being formed during the self-degradation processand might have some toxicity and the need for custom synthesis usinga relatively limited number of backbones.Both above-described approaches of dual responsiveamphiphilesare based on enhancing the enzymatic responsiveness of the amphiphilesby reducing their hydrophobicity or molecular weight and hence acceleratingthe unimer–micelle exchange, which is critical for the enzymaticactivation. A very different approach was very recently reported byThayumanavan and co-workers that utilized an elegant molecular designthat allows the translation of an enzymatic cleavage on the surfaceof polymeric assemblies into complete degradation of the assembledstructures 9.77 The There is no doubt thatenzyme-responsive polymers and their assemblieshold great potential as key materials for the design of smart drugdelivery systems and other biomedical applications. However, usingenzymes to trigger the disassembly of polymeric amphiphiles bringsalso a significant challenge due to the comparable dimensions of enzymesand micelles, which limit the accessibility of the enzyme. Takingadvantage of the high molecular precision that dendritic structuresoffer, we can study the enzymatic degradation of polymeric amphiphileswith high resolution. Up to date, several different amphiphilic systemscontaining dendritic blocks have all shown that small changes in thehydrophobicity and amphiphilicity strongly affected the degree andrate of enzymatic degradation. In all the systems that were describedabove, increasing the degree hydrophobicity by altering the type ornumber of lipophilic side/end-groups led to rapid increase in stabilityagainst the enzymatic degradation. In addition, increasing the molecularweight of the amphiphiles, while keeping the hydrophilic-to-hydrophobicratio constant, also led to a significant increase in stability.The observed trends imply that the enzymes cannot reach the hydrophobiccore of the micelles and have limited access also to the hydrophilicchains in the shell. Instead, amphiphiles can become significantlymore accessible in their unimer form, making the unimer–micelleequilibrium and exchange rates key parameters in tuning the enzymaticdegradation rate. Although the observed stability-responsiveness trendshave been mostly studied for esterase (PLE)-responsive systems, similarbehaviors were also reported for penicillin G amidase- and elastase-responsiveamphiphiles, demonstrating that the unimer–assembly equilibrium-basedactivation is indeed general and not specific only to esterase. Atthe same time, it is clear that the repertoire of activating enzymesneeds to be extended to include disease-associated enzymes and thatthese enzyme-responsive systems should be studied in more complexenvironments such as serum and blood to evaluate their performanceunder more relevant conditions to the final biomedical applicationof delivering drugs in a selective manner in the body.The abilityto observe how relatively small variations in eitherthe molecular weight of the hydrophobic block or the hydrophilic/hydrophobicratio of well-defined dendritic amphiphiles strongly affected theirdegradation, implies that for most types of polymers, small changesin their molecular weight due to their inherited polydispersity canresult in a broad range of enzymatic responsiveness. Hence, polymerswith a relatively small hydrophobic block will be readily degradedwhile polymers with a higher degree of hydrophobicity might degradevery slow or become nondegradable because of their greater thermodynamicand/or kinetic stabilities. This deeper understanding of the finebalance between stability and responsiveness of amphiphiles can explainthe partial enzymatic degradation that is observed for many reportedpolymeric assemblies. The risk of poor degradability due to smallvariations in the degree of hydrophobicity can be extremely importantin the field of polymer therapeutics when using hydrophilic polymersfor preparing polymer–drug conjugates. These polymeric carriersare often prepared by the postpolymerization step of conjugating thelipophilic drugs to the side groups of the polymer. As the exact numberof drugs per polymer chain cannot be precisely controlled beyond theaverage number of drugs per chain, these procedures will result inensembles composed of polymers with different number of conjugatedhydrophobic drugs. Such polymers are expected to self-assemble intomicelles or other types of assemblies bearing the hydrophobic drugsin their core. The variation in the hydrophobicity may lead to rapidenzymatic degradation of the polymers carrying a smaller number ofdrugs, while polymers with a larger number of drugs might become poorlydegradable or nondegradable because of their higher thermodynamicand kinetic stabilities. This wide range in responsiveness means thatthe more hydrophobic polymers, which carry more drug molecules andhence contain the major part of the loaded drugs, might not be ableto release the conjugated drugs, leading to an overall poor drug releaseprofile.By highlighting the need to balance between the stabilityof theassemblies and their responsiveness to the enzyme, the reported studiesof high molecular precision systems further support the need to overcomethe stability-responsiveness barrier. To date, several approachesincluding multiresponsive systems and self-immolative amphiphilescapable of self-destructing upon cleavage of its end-groups have beendeveloped. While there is no doubt that these approaches open theway toward highly stable and yet enzymatically responsive polymericassemblies, further research and development are needed to addressthe synthetic challenges that are associated with these more complexplatforms. Furthermore, in the next steps, the design of enzyme-responsivenanocarrier systems should take into account not only the types ofstimuli in the biological environment but also the sequence at whichbiological cues are encountered by the drug delivery systems. Lastbut not least, while the high molecular precision of polymeric systemshas not been translated into the clinic, there is no doubt that suchsystems provide a highly valuable and essential tool for studyingthe how small changes in the polymeric structures affects their function.