Intrinsic Capability Research Articles

Multiband dual- and cross-LFM waveform generation using a dual-drive Mach–Zehnder​ modulator

Linear frequency modulation (LFM) signals are widely used in modern radar systems owing to their intrinsic pulse compression capability but are restricted due to a limited range-Doppler resolution. On the other hand, dual- or cross-LFM signals have complementary LFM waveforms at the same time instant that reduces the range-Doppler coupling and thus improving range-Doppler resolution. We propose a simple microwave-photonic-based approach to generate multiband dual- and cross-LFM waveforms using only a single dual-drive Mach–Zehnder modulator (DDMZM). A theoretical analysis is carried out, which is modeled and verified through experiments. Dual- and cross-LFM waveforms at a carrier frequency of 6 GHz and 18 GHz with a bandwidth of 2 GHz is generated by controlling the DC and RF bias of the DDMZM. The tunability of the carrier frequency from 3 GHz to 9 GHz is also verified. A range resolution of 6.3 cm for dual- and cross-LFM waveforms, is obtained with a time-bandwidth-product (TBWP) of 20,000. The proposed technique is a promising solution for dual- and cross-LFM waveform generation in two-band multipurpose radar systems.

Extracellular vesicle-derived miRNAs improve stem cell-based therapeutic approaches in muscle wasting conditions.

Skeletal muscle holds an intrinsic capability of growth and regeneration both in physiological conditions and in case of injury. Chronic muscle illnesses, generally caused by genetic and acquired factors, lead to deconditioning of the skeletal muscle structure and function, and are associated with a significant loss in muscle mass. At the same time, progressive muscle wasting is a hallmark of aging. Given the paracrine properties of myogenic stem cells, extracellular vesicle-derived signals have been studied for their potential implication in both the pathogenesis of degenerative neuromuscular diseases and as a possible therapeutic target. In this study, we screened the content of extracellular vesicles from animal models of muscle hypertrophy and muscle wasting associated with chronic disease and aging. Analysis of the transcriptome, protein cargo, and microRNAs (miRNAs) allowed us to identify a hypertrophic miRNA signature amenable for targeting muscle wasting, consisting of miR-1 and miR-208a. We tested this signature among others in vitro on mesoangioblasts (MABs), vessel-associated adult stem cells, and we observed an increase in the efficiency of myogenic differentiation. Furthermore, injections of miRNA-treated MABs in aged mice resulted in an improvement in skeletal muscle features, such as muscle weight, strength, cross-sectional area, and fibrosis compared to controls. Overall, we provide evidence that the extracellular vesicle-derived miRNA signature we identified enhances the myogenic potential of myogenic stem cells.

Modeling Human Gonad Development in Organoids.

Our learning about human reproductive development is greatly hampered due to the absence of an adequate model. Animal studies cannot truthfully recapitulate human developmental processes, and studies of human fetal tissues are limited by their availability and ethical restrictions. Innovative three-dimensional (3D) organoid technology utilizing human pluripotent stem cells (hPSCs) offered a new approach to study tissue and organ development in vitro. However, a system for modeling human gonad development has not been established, thus, limiting our ability to study causes of infertility. In our study we utilized the 3D hPSC organoid culture in mini-spin bioreactors. Relying on intrinsic self-organizing and differentiation capabilities of stem cells, we explored whether organoids could mimic the development of human embryonic and fetal gonad. We have developed a simple, bioreactor-based organoid system for modeling early human gonad development. Male hPSC-derived organoids follow the embryonic gonad developmental trajectory and differentiate into multipotent progenitors, which further specialize into testicular supporting and interstitial cells. We demonstrated functional activity of the generated cell types by analyzing the expression of cell type-specific markers. Furthermore, the specification of gonadal progenitors in organoid culture was accompanied by the characteristic architectural tissue organization. This organoid system opens the opportunity for detailed studies of human gonad and germ cell development that can advance our understanding of sex development disorders. Implementation of human gonad organoid technology could be extended to modeling causes of infertility and regenerative medicine applications.

Polyimide Films Impregnated with Epoxy Resin Demonstrating Superior Self-Healing Properties for Thermally Stable Energy Storage Capacitors.

Metallized polymer films (MPFs) with superior self-healing properties are extremely attractive for application in energy storage capacitors. Self-healing behaviors allow MPFs to keep insulating between the local electrical breakdown region and the electrode, thereby reserving long-term operational viability of the capacitors. Polyimide (PI) is a type of well-developed polymer material with excellent mechanical and thermal stabilities, but it is deficient in intrinsic self-healing capabilities. This work reports a facile surface engineering strategy to endow metalized PI films with self-healing capabilities. By simple immersion of bare PI films in the solution of epoxy resin (ER) accompanied by curing of ER, PI films impregnated with ER (P-E films) not only show enhanced dielectric characteristics but also obtain excellent self-healing abilities upon multiple cycles of electrical breakdowns, even at a high temperature. For example, in comparison to bare PI films, PI films impregnated in ER solution with a solid content of 1 wt % (P-1%E) display improved initial Weibull breakdown strength (αb1 of 353.0 versus 310.9 kV/mm), maximum discharging energy density (Ud of 2.1836 versus 0.8254 J/cm3), and charging/discharging efficiency (η of 95.72 versus 55.19%) at 150 °C. After 5 breakdown cycles, P-1%E films could maintain a much higher breakdown strength (αb5 of 338.1 versus 21.3 kV/mm). When subjected to a constant electrical strength of 350 kV/mm at 150 °C, P-1%E films show merely <6% decline in both Ud and η values after 5 breakdown cycles. On the contrary, bare PI films would undergo dramatic performance decay after 1 or 2 breakdowns under similar conditions. In view of their outstanding self-healing properties at a high temperature, P-E films can serve as a promising candidate to fabricate thermally stable MPF capacitors for long-term operation.

Capability Analysis of Drift-Inherent Processes: Case of Nail Wire Drawing

Purpose: The central purpose of the study is to model the process capability of drift-inherent manufacturing processes by testing the efficacy of a novel approach that filters trend from raw process data before applying statistical process control tools. A secondary aim was to ascertain the intrinsic capability of the process following the filtering.&#x0D; Design/Methodology/Approach: Specifically, the study focused on processes in a nail-wire drawing and tested a method for analysing data from naturally-drifting processes that involves filtering trends from data before applying appropriate tools to verify the state of statistical control and capability of the process. The physical foundation for this work is based on data collected from a nail-wire drawing process A total of 250 data points were gathered over 50 days in two successive instances of 125 points, each spanning 25 days. Data were checked for normality followed by mathematical conditioning to filter out the wear trend before analysis by normal statistical process capability and control chart procedures.&#x0D; Findings: Results show that the proposed method is effective for tracking hidden effects in steadily drifting processes such as those associated with wear. After filtering, the data is found to fall within product specifications, though robust statistical control was still required through appropriate measures.&#x0D; Research Limitation: To investigate the intrinsic nature of the process outside of the process, material wear is assumed to be the sole source of the inherent drift. In processes where several sources of inherent drift are present, this may pose a problem. Additionally, the study focused on just one plant; however, data from other similar plants will be needed to buttress the findings and widen the scope of applicability of the findings.&#x0D; Practical implication: The competitive pressures of today’s marketplace are increasingly forcing companies to place premium emphasis on product quality while aiming at the lowest costs possible. The study recommends continuous and sustained efforts to reduce variation in manufacturing processes to brighten firms’ competitive survival.&#x0D; Social implication: The study will bring new knowledge to metal product manufacturers that can help them deliver high-quality products and value for money to consumers. &#x0D; Originality / Value: New insights afforded by the study’s approach include revelations of otherwise hidden measurement errors as well as undersized finishing-die. Any other out-of-control occurrences can then be more easily tracked and identified and root-cause analysis applied to eliminate them. This is a practical study that seeks to develop an innovative way to monitor the quality of processes whose tracking is made difficult by inherent drift. The easy-to-adopt methodology can be implemented by metal product manufacturers grappling with drift-inherent processes.

GaN on Engineered Bulk Silicon Power Integration Platform With Avalanche Capability Enabled by Built-in Si PN Junctions

A GaN on engineered bulk silicon (GaN-on-EBUS) power IC platform featuring an industry-standard 200-V GaN power HEMT epi-structure has been recently demonstrated, showing effective isolation and crosstalk suppression between the high-side (HS) and low-side (LS) GaN transistors in half-bridge configuration. In this work, we scale up the vertical breakdown voltage (BV) of the GaN film on the EBUS substrate to be over 600 V. Meanwhile, the built-in back-to-back PN junctions along the trench created in the Si substrate are employed to provide an overvoltage-protection scheme through their intrinsic avalanche capability for the overlaying GaN half-bridge circuit.

Analysis and validation of a planar parallel continuum manipulator with variable Cartesian stiffness

Manipulators with variable stiffness provide more flexibility between safety and performance when executing delicate tasks. In this paper, a novel planar parallel continuum manipulator (PPCM) with variable Cartesian stiffness is presented. The proposed manipulator consists of three flexible parallel limbs, with each limb made up with one PR drive and one slender flexible link, while the moving platform connects the links together. Except for the PR drive, there is no other rigid joint in this manipulator. An efficient kinetostatics analysis method is used based on previous research, and the stiffness model is built to compute the Cartesian stiffness. The advantage of the proposed PPCM is its intrinsic stiffness variation capability, which is achieved by the coupled large deflections of the flexible links and redundant actuation. An iterative algorithm is developed to calculate the actuator input under prescribed pose and required stiffness. A prototype of the manipulator is fabricated and its characteristics are validated by experiments. The measured results show that the studied PPCM has high position accuracy and its stiffness can be changed under different postures.

Evolutionary Algorithm-Based Iterated Local Search Hyper-Heuristic for Combinatorial Optimization Problems

Hyper-heuristics are widely used for solving numerous complex computational search problems because of their intrinsic capability to generalize across problem domains. The fair-share iterated local search is one of the most successful hyper-heuristics for cross-domain search with outstanding performances on six problem domains. However, it has recorded low performances on three supplementary problems, namely knapsack, quadratic assignment, and maximum-cut problems, which undermines its credibility across problem domains. The purpose of this study was to design an evolutionary algorithm-based iterated local search (EA-ILS) hyper-heuristic that applies a novel mutation operator to control the selection of perturbative low-level heuristics in searching for optimal sequences for performance improvement. The algorithm was compared to existing ones in the hyper-heuristics flexible (HyFlex) framework to demonstrate its performance across the problem domains of knapsack, quadratic assignment, and maximum cut. The comparative results have shown that the EA-ILS hyper-heuristic can obtain the best median objective function values on 22 out of 30 instances in the HyFlex framework. Moreover, it has achieved superiority in its generalization capability when compared to the reported top-performing hyper-heuristic algorithms.

A 0.00426 mm2 77.6-dB Dynamic Range VCO-Based CTDSM for Multi-Channel Neural Recording

Driven by needs in neuroscientific research, future neural interface technologies demand integrated circuits that can record a large number of channels of neural signals in parallel while maintaining a miniaturized physical form factor. Using conventional methods, it is challenging to reduce circuit area while maintaining the high dynamic range, low noise, and low power consumption required in the neural application. This paper proposes to address this challenge using a VCO-based continuous-time delta-sigma modulator (CTDSM) circuit, which can record and digitize neural signals directly without the need for front-end instrumentation amplifiers and anti-aliasing filters, which are limited by the abovementioned circuit-area performance tradeoff. Thanks to the multi-level quantization and intrinsic mismatch-shaping capabilities of the VCO-based approach, the proposed first-order CTDSM can achieve comparable electrical performance to a higher-order CTDSM while offering further area and power reductions. We prototyped the circuit in a 22-channel test chip and demonstrate, based on the chip measurement results, that the proposed modulator occupies an area of 0.00426 mm2 while achieving input-referred noise levels of 6.26 and 3.54 µVrms in the action potential (AP) and local field potential (LFP) bands, respectively. With a 77.6 dB wide-dynamic range, the noise and total harmonic distortion meet the requirements of a neural interface with up to 149 mVpp input AC amplitude or up to ±68 mV DC offsets. We also validated the feasibility of the circuit for multi-channel recording applications by examining the impact of cross-channel VCO oscillation interferences on the circuit noise performance. The experimental results demonstrate the proposed architecture is an excellent candidate to implement future multi-channel neural-recording interfaces.

Quantification of area-selective deposition on nanometer-scale patterns using Rutherford backscattering spectrometry

We present a site-specific elemental analysis of nano-scale patterns whereby the data acquisition is based on Rutherford backscattering spectrometry (RBS). The analysis builds on probing a large ensemble of identical nanostructures. This ensures that a very good limit of detection can be achieved. In addition, the analysis exploits the energy loss effects of the backscattered ions within the nanostructures to distinguish signals coming from different locations of the nanostructures. The spectrum deconvolution is based on ion-trajectory calculations. With this approach, we analyse the Ru area-selective deposition on SiO2-TiN line-space patterns with a linewidth of 35 nm and a pitch of 90 nm. We quantify the selectivity and the Ru local areal density on the top versus on the sidewall of the SiO2 lines. The sensitivity to probe ruthenium deposited on the various surfaces is as low as 1013 atoms/cm2. The analysis is quantitative, traceable, and highly accurate thanks to the intrinsic capabilities of RBS.

Accurate Quantum-Mechanically Derived Force-Fields through a Fragment-Based Approach: Balancing Specificity and Transferability in the Prediction of Self-Assembly in Soft Matter.

The wide range of time/length scales covered by self-assembly in soft matter makes molecular dynamics (MD) the ideal candidate for simulating such a supramolecular phenomenon at an atomistic level. However, the reliability of MD outcomes heavily relies on the accuracy of the adopted force-field (FF). The spontaneous re-ordering in liquid crystalline materials stands as a clear example of such collective self-assembling processes, driven by a subtle and delicate balance between supramolecular interactions and single-molecule flexibility. General-purpose transferable FFs often dramatically fail to reproduce such complex phenomena, for example, the error on the transition temperatures being larger than 100 K. Conversely, quantum-mechanically derived force-fields (QMD-FFs), specifically tailored for the target system, were recently shown (J. Phys. Chem. Lett.2022,13, 243) to allow for the required accuracy as they not only well reproduced transition temperatures but also yielded a quantitative agreement with the experiment on a wealth of structural, dynamic, and thermodynamic properties. The main drawback of this strategy stands in the computational burden connected to the numerous quantum mechanical (QM) calculations usually required for a target-specific parameterization, which has undoubtedly hampered the routine application of QMD-FFs. In this work, we propose a fragment-based strategy to extend the applicability of QMD-FFs, in which the amount of QM calculations is significantly reduced, being a single-molecule-optimized geometry and its Hessian matrix the only QM information required. To validate this route, a new FF is assembled for a large mesogen, exploiting the parameters obtained for two smaller liquid crystalline molecules, in this and previous work. Lengthy MD simulations are carried out with the new transferred QMD-FF, observing again a spontaneous re-orientation in the correct range of temperatures, with good agreement with the available experimental measures. The present results strongly suggest that a partial transfer of QMD-FF parameters can be invoked without a significant loss of accuracy, thus paving the way to exploit the method's intrinsic predictive capabilities in the simulation of novel soft materials.

Increasing strengths of liquid crystalline polymers while minimizing anisotropy via topological rearrangement assisted bi-directional stretching of reversibly interlocked macromolecular networks

To prepare oriented crosslinked liquid crystalline polymers (LCPs) while preventing the unwanted anisotropy, the authors fabricated interlocked networks from liquid crystalline epoxy and amorphous polyurethane, which are crosslinked by reversible Diels-Alder (DA) bonds and Schiff base, respectively. By making use of dynamicity of the reversible bonds as well as relative mobility of the parent networks of the interlocked networks, the material is subjected to stepwise solid-state bi-directional drawing. Owing to the directional alignment of the mesogens and molecular chains and the increased crosslinking density during stretching caused by the networks reshuffling, the strengths of the material in orthogonal directions are simultaneously improved and gradually converged to the values comparable to the reported highest level of unidirectionally orientated crosslinked LCPs. Furthermore, the biaxially oriented interlocked networks have inherited the intrinsic self-healing capability from the included reversible bonds. The proposed method is easy to use and expected to contribute to the practical applications of crosslinked LCPs, which is becoming more and more important in modern microelectronics and communication technology.

Engineered Protein Nanocages for Concurrent RNA and Protein Packaging In Vivo.

Protein nanocages have emerged as an important engineering platform for biotechnological and biomedical applications. Among naturally occurring protein cages, encapsulin nanocompartments have recently gained prominence due to their favorable physico-chemical properties, ease of shell modification, and highly efficient and selective intrinsic protein packaging capabilities. Here, we expand encapsulin function by designing and characterizing encapsulins for concurrent RNA and protein encapsulation in vivo. Our strategy is based on modifying encapsulin shells with nucleic acid-binding peptides without disrupting the native protein packaging mechanism. We show that our engineered encapsulins reliably self-assemble in vivo, are capable of efficient size-selective in vivo RNA packaging, can simultaneously load multiple functional RNAs, and can be used for concurrent in vivo packaging of RNA and protein. Our engineered encapsulation platform has potential for codelivery of therapeutic RNAs and proteins to elicit synergistic effects and as a modular tool for other biotechnological applications.

Deep learning and multiwavelength fluorescence imaging for cleanliness assessment and disinfection in Food Services

Precise, reliable, and speedy contamination detection and disinfection is an ongoing challenge for the food-service industry. Contamination in food-related services can cause foodborne illness, endangering customers and jeopardizing provider reputations. Fluorescence imaging has been shown to be capable of identifying organic residues and biofilms that can host pathogens. We use new fluorescence imaging technology, applying Xception and DeepLabv3+ deep learning algorithms to identify and segment contaminated areas in images of equipment and surfaces. Deep learning models demonstrated a 98.78% accuracy for differentiation between clean and contaminated frames on various surfaces and resulted in an intersection over union (IoU) score of 95.13% for the segmentation of contamination. The portable imaging system’s intrinsic disinfection capability was evaluated on S. enterica, E. coli, and L. monocytogenes, resulting in up to 8-log reductions in under 5 s. Results showed that fluorescence imaging with deep learning algorithms could help assure safety and cleanliness in the food-service industry.

Discovering Noncritical Organization: Statistical Mechanical, Information Theoretic, and Computational Views of Patterns in One-Dimensional Spin Systems.

We compare and contrast three different, but complementary views of “structure” and “pattern” in spatial processes. For definiteness and analytical clarity, we apply all three approaches to the simplest class of spatial processes: one-dimensional Ising spin systems with finite-range interactions. These noncritical systems are well-suited for this study since the change in structure as a function of system parameters is more subtle than that found in critical systems where, at a phase transition, many observables diverge, thereby making the detection of change in structure obvious. This survey demonstrates that the measures of pattern from information theory and computational mechanics differ from known thermodynamic and statistical mechanical functions. Moreover, they capture important structural features that are otherwise missed. In particular, a type of mutual information called the excess entropy—an information theoretic measure of memory—serves to detect ordered, low entropy density patterns. It is superior in several respects to other functions used to probe structure, such as magnetization and structure factors. -Machines—the main objects of computational mechanics—are seen to be the most direct approach to revealing the (group and semigroup) symmetries possessed by the spatial patterns and to estimating the minimum amount of memory required to reproduce the configuration ensemble, a quantity known as the statistical complexity. Finally, we argue that the information theoretic and computational mechanical analyses of spatial patterns capture the intrinsic computational capabilities embedded in spin systems—how they store, transmit, and manipulate configurational information to produce spatial structure.

Identification of aging-associated immunotypes and immune stability as indicators of post-vaccination immune activation.

Immunosenescence describes immune dysfunction observed in older individuals. To identify individuals at‐risk for immune dysfunction, it is crucial to understand the diverse immune phenotypes and their intrinsic functional capabilities. We investigated immune cell subsets and variation in the aging population. We observed that inter‐individual immune variation was associated with age and cytomegalovirus seropositivity. Based on the similarities of immune subset composition among individuals, we identified nine immunotypes that displayed different aging‐associated immune signatures, which explained inter‐individual variation better than age. Additionally, we correlated the immune subset composition of individuals over approximately a year as a measure of stability of immune parameters. Immune stability was significantly lower in immunotypes that contained aging‐associated immune subsets and correlated with a circulating CD38 + CD4+ T follicular helper cell increase 7 days after influenza vaccination. In conclusion, immune stability is a feature of immunotypes and could be a potential indicator of post‐vaccination cellular kinetics.

Republication de : Central nystagmus and alterations in vestibular tests due to an inadvertent gentamicin administration into spinal space: A CARE case report

Gentamicin has a well-known potential for damaging the peripheral vestibular organs. However, it is considered to be innocuous to the CNS as it crosses the blood-brain barrier poorly. Here, we describe central neuro-otological abnormalities developed by a patient after deployment of gentamicin into his spinal space. A 61-year-old male unintentionally received gentamicin during spinal locoregional anesthesia for a urological procedure. During the first 48 hours the patient presented upper extremity dysmetria, dysarthria, and bilateral abducens nerve paralysis from which he recovered completely. He remained asymptomatic from day 3 to 10 after the incident. On day 11 he presented an acute vestibular syndrome. Severe bilateral vestibulopathy was confirmed by means of video head impulse testing. From day 14 onwards, he presented a persistent horizontal left-beating nystagmus, showing no variation or signs of compensation after 14 months, not responding to intensive vestibular rehabilitation or vestibular suppressant drugs. During follow-up, intercurrent gaze-evoked/direction-changing nystagmus has been recorded in various opportunities. We interpreted these findings as signs of both severe peripheral bilateral vestibulopathy and cerebellar and/or midbrain late-onset neurotoxicity, which can be explained by the intrinsic neurotoxic capability of high doses of gentamicin in the CNS.

Flower-shaped and sea urchin-shaped structures coexisting in cobalt-based phosphate and oxides achieve efficient electrochemical overall water electrolysis

Active site engineering for electrocatalysts is an essential strategy to improve their intrinsic electrocatalytic capability for practical applications and it is of great significance to develop a new excellent electrocatalyst for overall water splitting. Here, Co3O4/nickel foam (NF) and Co2(P4O12)/NF electrocatalysts with flower-shaped and sea urchin-shaped structures are synthesized by a simple hydrothermal process and followed by a post-treatment method. Among them, Co2(P4O12)/NF shows good catalytic activity for hydrogen evolution reaction (HER), and at the current density of 10 mA cm−2, the overpotential is only 113 mV Co3O4/NF exhibits good catalytic activity for oxygen evolution reaction (OER), and the overpotential is 327 mV at 20 mA cm−2. An alkaline electrolyzer with Co3O4/NF and Co2(P4O12)/NF catalysts respectively as anode and cathode displays a current density of 10 mA cm−2 at a cell voltage of 1.59 V. This work provides a simple way to prepare high efficient, low cost and rich in content promising electrocatalysts for overall water splitting.

Rapid adaptation of predictive models during language comprehension: Aperiodic EEG slope, individual alpha frequency and idea density modulate individual differences in real-time model updating.

Predictive coding provides a compelling, unified theory of neural information processing, including for language. However, there is insufficient understanding of how predictive models adapt to changing contextual and environmental demands and the extent to which such adaptive processes differ between individuals. Here, we used electroencephalography (EEG) to track prediction error responses during a naturalistic language processing paradigm. In Experiment 1, 45 native speakers of English listened to a series of short passages. Via a speaker manipulation, we introduced changing intra-experimental adjective order probabilities for two-adjective noun phrases embedded within the passages and investigated whether prediction error responses adapt to reflect these intra-experimental predictive contingencies. To this end, we calculated a novel measure of speaker-based, intra-experimental surprisal (“speaker-based surprisal”) as defined on a trial-by-trial basis and by clustering together adjectives with a similar meaning. N400 amplitude at the position of the critical second adjective was used as an outcome measure of prediction error. Results showed that N400 responses attuned to speaker-based surprisal over the course of the experiment, thus indicating that listeners rapidly adapt their predictive models to reflect local environmental contingencies (here: the probability of one type of adjective following another when uttered by a particular speaker). Strikingly, this occurs in spite of the wealth of prior linguistic experience that participants bring to the laboratory. Model adaptation effects were strongest for participants with a steep aperiodic (1/f) slope in resting EEG and low individual alpha frequency (IAF), with idea density (ID) showing a more complex pattern. These results were replicated in a separate sample of 40 participants in Experiment 2, which employed a highly similar design to Experiment 1. Overall, our results suggest that individuals with a steep aperiodic slope adapt their predictive models most strongly to context-specific probabilistic information. Steep aperiodic slope is thought to reflect low neural noise, which in turn may be associated with higher neural gain control and better cognitive control. Individuals with a steep aperiodic slope may thus be able to more effectively and dynamically reconfigure their prediction-related neural networks to meet current task demands. We conclude that predictive mechanisms in language are highly malleable and dynamic, reflecting both the affordances of the present environment as well as intrinsic information processing capabilities of the individual.

The immune microenvironment and tissue engineering strategies for spinal cord regeneration.

Regeneration of neural tissue is limited following spinal cord injury (SCI). Successful regeneration of injured nerves requires the intrinsic regenerative capability of the neurons and a suitable microenvironment. However, the local microenvironment is damaged, including insufficient intraneural vascularization, prolonged immune responses, overactive immune responses, dysregulated bioenergetic metabolism and terminated bioelectrical conduction. Among them, the immune microenvironment formed by immune cells and cytokines plays a dual role in inflammation and regeneration. Few studies have focused on the role of the immune microenvironment in spinal cord regeneration. Here, we summarize those findings involving various immune cells (neutrophils, monocytes, microglia and T lymphocytes) after SCI. The pathological changes that occur in the local microenvironment and the function of immune cells are described. We also summarize and discuss the current strategies for treating SCI with tissue-engineered biomaterials from the perspective of the immune microenvironment.