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The high-resolution and nondestructive co-reference measurement of the inner and outer three-dimensional (3D) surface profiles of laser fusion targets is difficult to achieve. In this study, we propose a laser differential confocal (LDC)–atomic force probe (AFP) method to measure the inner and outer 3D surface profiles of laser fusion targets at a high resolution. This method utilizes the LDC method to detect the deflection of the AFP and exploits the high spatial resolution of the AFP to enhance the spatial resolution of the outer profile measurement. Nondestructive and co-reference measurements of the inner profile of a target were achieved using the tomographic characteristics of the LDC method. Furthermore, by combining multiple repositionings of the target using a horizontal slewing shaft, the inner and outer 3D surface profiles of the target were obtained, along with a power spectrum assessment of the entire surface. The experimental results revealed that the respective axial and lateral resolutions of the outer profile measurement were 0.5 and 1.3 nm, while the respective axial and lateral resolutions of the inner profile measurement were 2.0 nm and approximately 400.0 nm. The repeatabilities of the root-mean-square deviation measurements for the outer and inner profiles of the target were 2.6 and 2.4 nm, respectively. We believe our study provides a promising method for the high-resolution and nondestructive co-reference measurement of the inner and outer 3D profiles of laser fusion targets.

Metabolic reprogramming and cellular senescence greatly contribute to cancer relapse and recurrence. In aging and treated prostate, persistent accumulating senescence-associated secretory phenotype (SASP) of cancer cells often limits the overall survival of patients. Novel strategic therapy with monoacylglycerol lipase (MGLL) upregulation that counters the cellular and docetaxel induced SASP might overcome this clinical challenge in prostate cancer (PCa). With primary comparative expression and survival analysis screening of fatty acid (FA) metabolism signature genes in the TCGA PCa dataset and our single center cohort, MGLL was detected to be downregulated in malignancy prostate tissues and its low expression predicted worse progression-free and overall survival. Functionally, overexpression of MGLL mainly suppresses NF-κB-driven SASP (N-SASP) which mostly restricts the cancer cell paracrine and autocrine tumorigenic manners and the corresponding cellular senescence. Further investigating metabolites, we determined that MGLL constitutive expression prevents lipid accumulation, decreases metabolites preferably, and consequently downregulates ATP levels. Overexpressed MGLL inhibited IκBα phosphorylation, NF-κB p65 phosphorylation, and NF-κB nuclear translocation to deactivate NF-κB transcriptional activities, and be responsible for the repressed N-SASP, partially through reducing ATP levels. Preclinically, combinational treatment with MGLL overexpression and docetaxel chemotherapy dramatically delays tumor progression in mouse models. Taken together, our findings identify MGLL as a switch for lipase-related N-SASP suppression and provide a potential drug candidate for promoting docetaxel efficacy in PCa.

In this letter, we report the fabrication of Uni-travelling-carrier photodiode (UTC-PDs) for mm-wave applications. For the fabricated PDs, the area of the p electrode is smaller than that of the absorption area. Though this leads to a response roll off when the frequency is below 3.5 GHz, a higher impedance of the PD can be obtained, which leads to a higher RF power output for a $50~\Omega $ load resistance. For the PD having $50\times 4~\mu $ m2 absorption area and $46\times 2.5~\mu $ m2 p electrode area, the measured RF output power at 6 mA photocurrent, −2V bias and 15 GHz is 0.2 dBm. The ideal RF output power for a PD at this current is 0.35 dBm, which is only 0.15 dB higher than the measured RF power, indicating a high RF power output efficiency.

This article presents a wideband sub-terahertz (sub-THz) inline transition from microstrip line (MSL) to rectangular waveguide (RWG). The transition employs the bow-tie antenna to achieve a compact inline transition and wideband impedance matching with the RWG, resulting in bigger bandwidths than the transitions using dipoles. In order to overcome the substrate width limitations of conventional probes, the perfect magnetic conductor (PMC) packaging concept is used in this article, resulting in a better integration ability with large-sized monolithic microwave integrated circuits (MMICs). Two back-to-back transition prototypes related to different angles of the bow-tie antenna have been fabricated to evaluate the transition performances in the sub-THz band. The tested large-sized substrates have a large width of 10.826 mm and a length of 10.8 mm, and the length of the MSL is 9.28 mm. According to the experimental results, in the 110–170-GHz band, prototype I has a reflection coefficient of less than -11 dB and an insertion loss of 1.79–2.6 dB, while prototype II has a reflection coefficient of less than -8.5 dB and an insertion loss of 1.52–2.5 dB.

Scaffold materials, seed cells and growth factors are referred to as the three elements of bone tissue engineering (BTE). However, the physical properties and biocompatibility of these scaffolds and the safety and cost of their growth factors limit their clinical application. Therefore, it is critical to develop a novel scaffold modified with efficient growth factors that meets the requirements of BTE. Herein, 3D-printed poly (lactic-co-glycolic acid)/hydroxyapatite (PLGA/HA) composite scaffolds modified with new fusion peptides, which can effectively promote the regeneration and repair of bone defects, were developed. 3D-printed PLGA/HA composite scaffolds with appropriate HA contents were prepared and had appropriate mechanical properties. In addition, the surface of the 3D-printed PLGA/HA composite scaffold was modified with new fusion peptides to provide osteogenic, antimicrobial, and angiogenesis-promoting effects. In vitro experiments showed that the fusion peptide-modified scaffolds had good biocompatibility and a certain degree of antibacterial activity. Moreover, the fusion peptide-modified scaffolds significantly improved the migration ability of BMSCs and Ea.hy926 cells, promoted the expression of osteogenesis-related factors (BMP2, RUNX2, ALP, OPN) in BMSCs, and promoted the expression of angiogenesis-related factors (VEGF and HIF-1α) in Ea.hy926 cells. In vivo experiments showed that the fusion peptide-modified scaffolds had good osteogenic ability. This study reveals considerable application potential for bone defect repair and provides a new option of scaffold material for BTE.

•PCV 13 still key for children IPD prevention in Shenzhen.•Meningitis isolates exhibit higher penicillin and ceftriaxone resistance.•81.3% of erythromycin-resistant pneumococcus possess dual ermB and mefA genotypes.•Elevated β-lactam and macrolide resistance link to 19F-CC271, 19A-CC271, and 14-CC876.

High levels of cell-free DNA (cfDNA) induce psoriasis. Currently, the treatment of psoriasis has the disadvantages of penetration difficulty, suppression of normal immunity, and skin irritation. In this study, biguanide chitosan microneedles (BGC-MNs) were prepared to treat psoriasis by removing cfDNA from the dermis through the skin barrier. The effects of chitosan with different bisguanidine contents on DNA-binding capacity, biocompatibility, and inflammation inhibition were compared, revealing that chitosan containing 20% bisguanidine (BGC2) was found to have the best overall performance. In vitro,BGC2 effectively cleared cfDNA and inhibited the production of inflammatory factors. BGC-MN made from BGC2 had good mechanical and solubility properties. In vivo,BGC-MNs cleared cfDNA, reduced the level of inflammatory factors in the dermis, and exerted a good therapeutic effect on mice with psoriasis. These results suggested that BGC-MNs provided a new approach to treating psoriasis in terms of scavenging cfDNA and exerting anti-inflammatory effects.

3D printing technology offers extensive applications in tissue engineering and regenerative medicine (TERM) because it can create a three-dimensional porous structure with acceptable porosity and fine mechanical qualities that can mimic natural bone. Hydroxyapatite (HA) is commonly used as a bone repair material due to its excellent biocompatibility and osteoconductivity. Small extracellular vesicles (sEVs) derived from bone marrow mesenchymal stem cells (BMSCs) can regulate bone metabolism and stimulate the osteogenic differentiation of stem cells. This study has designed a functionalized bone regeneration scaffold (3D H-P-sEVs) by combining the biological activity of BMSCs-sEVs and the 3D-HA scaffold to improve bone regeneration. The scaffold utilizes the targeting of fusion peptides to increase the loading efficiency of sEVs. The composition, structure, mechanical properties, and in vitro degradation performance of the 3D H-P-sEVs scaffolds were examined. The composite scaffold demonstrated good biocompatibility, substantially increased the expression of osteogenic-related genes and proteins, and had a satisfactory bone integration effect in the critical skull defect model of rats. In conclusion, the combination of EVs and 3D-HA scaffold via fusion peptide provides an innovative composite scaffold for bone regeneration and repair, improving osteogenic performance.

This paper proposes a novel hierarchical reinforcement learning (HRL) framework of complex manipulation tasks which integrates the human prior knowledge. The framework involves the following steps: 1) The manipulation process is divided into several stages based on human prior knowledge. 2) Transition conditions between stages are determined in the form of “if-then” rules. 3) The key features of each stage are selected, and the corresponding control policies are designed via human knowledge. 4) The policy gradient with parameter-based exploration (PGPE) method is employed to optimize the policy parameters because it does not require the policy to be derivable for the parameters. To increase the convergence speed of this framework, importance sampling and adaptive adjustment of exploration variance are employed to improve it. 5) On this basis, to facilitate the transfer of simulation results to practical experiments, half sim-to-real method is presented, which fully utilizes the simulation results, and the differences between simulation and experimental environments are considered. Simulation and experimental studies show that our framework can deal with the peg-hole-insertion task with a high quality in less than 1600 episodes and can safely adapt the skill into the practical scene with little iterations, which verify the efficiency of the presented method. Note to Practitioners—Intelligent robots will become the right assistants of human beings in the future, especially in various areas of complex manipulation occasions. The important premise is that the robots should have certain ability of complex manipulation skill learning. Complex manipulation tasks can be decomposed into multiple stages, and HRL is a suitable and efficient method for solving this kind of problems. This paper proposes a novel HRL framework which can better integrate the human prior knowledge. In addition, improved PGPE method is proposed to obtain the optimized policy parameters more quickly. More importantly, a novel half sim-to-real transfer method is presented to better integrate the simulation and experiment results. This provides a common paradigm, which leverages the simulation results to reduce the interaction between robot and practical environment and then utilizes the experiment results to further optimize the policy parameters.

Purpose: This study aimed to evaluate the performance of 18F-MD-PSMA PET/CT in patients previously treated for prostate cancer by either surgery or therapy, but later relapsed biochemically.Methods: This retrospective study enrolled 213 patients in sequence previously treated for prostate cancer by either surgery or therapy, but later PSA relapsed. A total of 191 of these 213 patients were included in this analysis. All patients were biochemically relapsed after radical prostatectomy or therapy, had 18F-MD-PSMA PET/CT scan within 1 week, and were off hormonal therapy at the time of the scans. The new tracer was compared directly with 11C-choline in sensitivity.Results: In 3 patients, a side-by-side comparison between 18F-MD-PSMA and 11C-choline was performed, and it was found that the former was about 3 times more sensitive than the latter. The analysis of PET imaging using 18F-MD-PSMA in 191 relapsed patients showed that less than 10% of patients showed the disease limited in the prostate. Among the remote lesions, the number in decreasing order was bone, followed by lymph nodes and other organs. The maximal SUV in lesions in each patient followed an exponential decay, with SUV inclined to the lower end. The Gleason score measured at the diagnosis showed no correlation with the average number of lesions in each patient, the average maximal SUV values among this cohort of patients, and the PSA values measured at the time of PET imaging. The number of lesions observed in each patient has no correlation with the PSA value measured at the time of PET imaging. When PSA value was measured as an independent biomarker at the time of PET imaging, the positivity of PET imaging using 18F-MD-PSMA increased along with an increase in PSA value, but with exceptions where PSMA expression was low or negative. From the PET imaging of this radioligand, the majority of patients showed oligo-metastasis, favoring using local therapy to manage the disease.Conclusion: An 18F-MD-PSMA as a radioligand was found to be superior to 11C-choline in the setting of patients with biochemical relapse after previous treatment. Its PET imaging results matched those of established PSMA radioligands, but its chemical structure was found to have added features to conjugate with other functional molecules, such as those with therapeutic properties. This radioligand lays the foundation for our further work.

This letter re-investigates the difficult statistical sum-rate maximization for two-user multiple-input single-output (MISO) broadcast beamforming (BF). The identified linear structure of the Pareto-optimal (PO) BF vectors interprets the optimal statistical channel state information (SCSI) aided two-user MISO broadcast BF vectors as the linear combinations of the statistical maximum-ratio transmission (MRT) and the statistical zero-forcing (ZF) BF. Inspired by this knowledge, a SCSI enabled BF neural network “MRT-ZF-BNN” is constructed for fast determining optimal two-user MISO statistical BF. The simulation results confirm the improved sum-rate and computational efficiency of the devised MRT-ZF-BNN over the existing baselines.

The aim of the violent recognition task is to determine whether a video contains violent behaviors. Given that violent behavior often comes with visual and audio anomalies, multimodal approaches have always played an important role in this field. However, existing methods have been limited by the insufficient utilization of audio-visual self-supervised semantic cues and correlation, resulting in a restricted representational capacity of the network and low generalization due to the scarcity of available violent video datasets. To address this issue, we propose a violent action recognition model based on global-local visual and audio contrastive learning. Our model introduces global and local contrastive objectives to achieve audio-visual multi-grained semantic alignment and leverage the correlation for violent video recognition. Experimental results demonstrate that our proposed model improves state-of-the-art by 2.31% on the VSD dataset, 0.71% on the Violent-Flows dataset, and 1.43% on the VCD dataset.

Solar-driven atmospheric water harvesting technology has the advantage of not being limited by geography and has great potential in solving the freshwater crisis. Here, we first propose a purely natural and degradable superhydrophilic composite macroporous hygroscopic material by applying guar gum (GG) to atmospheric water harvesting. The material consists of GG-cellulose nanofibers (CNFs) as a porous substrate material, limiting the hygroscopic factor lithium chloride (LiCl) in its three-dimensional (3D) network structure, and carbon nanotubes (CNTs) play a photothermal conversion role. The composite material has a high light absorption rate of more than 95%, and the macroporous structure (20–60 μm) allows for rapid adsorption/desorption kinetics. At 35 °C and 90% relative humidity (RH), the moisture absorption capacity is as high as 1.94 g/g. Under 100 mW/cm2irradiation, the absorbed water is almost completely desorbed within 3 h, and the water harvesting performance is stable in 10 cycles. Moreover, liquid water was successfully collected in an actual outdoor experiment. This work demonstrates the great potential of biomass materials in the field of atmospheric water collection and provides more opportunities for various energy and sustainable applications in the future.

The interrupted sampling repeater jamming (ISRJ) produces multiple false targets after pulse compression, making it difficult for radar to detect real targets. In this article, an anti-ISRJ algorithm is developed based on the joint design of the waveform and the mismatched filter with an expanded mainlobe. First, to prevent false alarms when the range sidelobes and jamming peaks of the filter output are too high, the sum of the peak sidelobe level of the waveform compressed with the mismatched filter and the peak level of the ISRJ signal compressed with the mismatched filter is taken as an optimization criterion for minimization. Meanwhile, a penalty function is used to control the mainlobe shape of the correlation function between the waveform and the mismatched filter to approximate the desired mainlobe. To maximize the transmitted power efficiency of the radar and control the signal-to-noise ratio loss caused by the mismatched filter, a constant modular constraint for the waveform and an energy constraint for the filter are adopted. Then, an iterative algorithm based on the majorization–minimization framework is proposed to solve the joint design problem. In each iteration, an analytical expression is derived to realize the simultaneous updating of the waveform and filter. The convergence of the proposed algorithm is proven, and its computational complexity is analyzed. Finally, simulations are provided to demonstrate the effectiveness of the proposed algorithm. Compared with existing algorithms, the waveform and filter designed in this article exhibit better pulse compression performance and antijamming ability.

By modifying the mass and stiffness parameters of a structure, a subset of its natural frequencies can be assigned. However, such an assignment is usually accompanied with changes of the remaining frequencies, known as ‘spillover’. Eigenvalue or frequency spillover often needs to be avoided in engineering.In this paper, a new and general method is proposed for assigning a subset of the natural frequencies of a structure with a low level of spillover through structural modifications. The method combines a multi-population genetic algorithm and a radial basis function neural network and is implemented in a MATLAB-PYTHON-ABAQUS data interaction system. It is suitable for theoretical models (for example, finite element models) of general structures.By means of three numerical examples, the ability of the method to assign subsets of frequencies to discrete and discretised continuous structures while maintaining low spillover is demonstrated.

Sensors and communication capabilities of connected vehicles provide look-ahead information that can be exploited by vehicle controllers. This work demonstrates the benefits of look-ahead information combined with hierarchical economic model predictive control for the airpath management of compression ignition engines. This work exploits road information predicted with a 0.1- and 2-s horizon to simultaneously control fast and slow engine dynamics, respectively. It controls the variable nozzle turbocharger and dual-loop exhaust gas recirculation, at a 0.01-s rate, to simultaneously optimize NOx, soot, and fuel economy. Simulation studies and hardware-in-loop implementation on an ARM Cortex-A15 processor demonstrate improved NOx, soot, and torque tracking without compromising fuel economy, and a worst case computation time of 8.92 ms.

In this paper, a MoS2/MXene/N-doped carbon (NC) porous composite microsphere with a wrinkled surface was designed and constructed. Lithium fluoride exfoliation and lithium-ion etching fabricated two types of 2D assembly elements, MXene (Ti3C2Tx) and MoS2nanosheets. The two nanosheets were self-assembled by an ultrasonic spray technique with high-temperature reduction, and MoS2/MXene microspheres with 3Dwrinkled shapes were obtained. The coating of the surface NC layer was achieved by the carbonization of a polydopamine (PDA) precursor formed by the self-polymerization of dopamine. The amount of PDA coating and raw material ratio significantly affect the microstructure and electromagnetic wave absorption performance. The optimal MXene to MoS2mass ratio is 5:1, and the optimal coating time and filler amount are 8 h and 40%. MoS2/MXene/NC composite microspheres exhibit excellent absorption performance with low reflection losses (RLmin) of −52.9 dB at 6.4 GHz and high adequate absorption bandwidths of 5.2 GHz. By adjusting the thickness of the absorber, the full coverage of the C–Ku band (4–18 GHz) can be achieved. As a new composite absorber, it has significant potential applications.

Digital detector emulators (DDEs) are important tools for developing particle flux monitoring systems in the laboratory. However, as the dynamic range of modern particle flux monitoring systems, particularly neutron flux monitoring (NFM) systems, continues to rapidly increase, DDEs must also increase their maximum count rate to keep up. The pulse array generating module is the core of the DDE, which utilizes pseudorandom numbers generated by linear-feedback shift registers (LFSRs) to control the intensity and amount of simulated neutrons emitted in each clock cycle. However, the defects or limitations associated with pseudorandom number generators (PRNGs) can cause deviations from the ideal situation, which affects the quality of the output waveform. We propose a novel design that achieves the optimal quality of simulated pulse signals with the same computational cost compared to existing methods, along with a customized algorithm based on the property of linear transformation that can automatically generate the desired LFSR structure. We evaluate the simulated results of the PRNG and pulse array generator from multiple aspects to avoid any systemic errors in the design. In addition, we collect and analyze measured Campbell value data of the DDE. This study aims to contribute to the development of more accurate particle flux monitoring systems by improving the capabilities and reliability of DDEs, addressing the issue of PRNGs, and proposing a novel design that achieves optimal quality of simulated pulse signals.

Exosome-based liquid biopsies highlight potential utility in diagnosis and determining the prognosis of patients with cancer and other diseases. However, the existing techniques are severely limited for practical applications due to the complications of high cost, low sensitivity, tedious procedures, and large sample consumption. Herein, we report a microstructured optical fiber sensor for fast, sensitive, and accurate quantification of exosomes in blood samples of breast cancer patients. Numerical simulations are applied to demonstrate that hollow-core microstructured antiresonant fibers (HARFs) can stringently confine light in the fiber core, ensuring strong light–matter interaction and thus maximumly amplifying the signal. Taking this advantage, a AuNPs–dsDNA assembly containing gold nanoparticles, a recognizing DNA aptamer, and a fluorescent reporter DNA sequence is fabricated followed by immobilization on the fiber wall to form a AuNPs–dsDNA–HARF sensor. Cancer-derived exosomes can be recognized and captured in the fiber channel and generate dose-dependent fluorescent signals for quantification. The microfiber sensor demonstrates enhanced sensitivity and specificity, enabling the detection of single digits of exosome particles at the nanoliter sample level. In addition, by tracking exosome phenotypic changes, the proposed fiber sensor can facilitate precise drug treatment monitoring. This work provides a robust platform for exosome-based biopsy for cancer diagnosis and prediction of therapeutic outcomes.

Abstract:To establish The Texture of Time as a notable philosophical achievement, this essay puts it in the context of transcendental phenomenology and elucidates "Veen's Time" by way of comparison to Husserl's theory of time-consciousness. Despite Nabokov's apparent disinterest in phenomenology, the monist stance, descriptive method and de facto epoché in The Texture of Time all point to it being a piece of phenomenological analysis. Veen's conception of the Present as a hollow is analogous to Husserl's notion of the absolute flow of time-constituting consciousness; by emphasizing the stillness of the Present, Veen even irons out a couple of rough edges in Husserl's account. The Past is not a mere extension of the Present, but an equally important panel of "Veen's Time" with its own structure that centers on the subject and the object as two identity poles. Finally, drawing on the concept of "protention," the future-facing element of the Present, Veen's dismissal of the Future as "a quack at the court of Chronos" is interpreted as attacking the conventional tripartite image of Time instead of the Future per se.

The lesion recognition of dermoscopy images is significant for automated skin cancer diagnosis. Most of the existing methods ignore the medical perspective, which is crucial since this task requires a large amount of medical knowledge. A few methods are designed according to medical knowledge, but they ignore to be fully in line with doctors’ entire learning and diagnosis process, since certain strategies and steps of those are conducted in practice for doctors. Thus, we put forward Clinical-Inspired Network (CI-Net) to involve the learning strategy and diagnosis process of doctors, as for a better analysis. The diagnostic process contains three main steps: the zoom step, the observe step and the compare step. To simulate these, we introduce three corresponding modules: a lesion area attention module, a feature extraction module and a lesion feature attention module. To simulate the distinguish strategy, which is commonly used by doctors, we introduce a distinguish module. We evaluate our proposed CI-Net on six challenging datasets, including ISIC 2016, ISIC 2017, ISIC 2018, ISIC 2019, ISIC 2020 and PH2 datasets, and the results indicate that CI-Net outperforms existing work. The code is publicly available at https://github.com/lzh19961031/Dermoscopy_classification.

With the large-scale application of 5G technology in smart distribution networks, the operation effects of distribution networks are not clear. Herein, we propose a comprehensive evaluation model of a 5G+ smart distribution network based on the combination weighting and cloud model of the improved Fuzzy Analytic Hierarchy-Entropy Weight Method (FAHP- EWM). First, we establish comprehensive evaluation indexes of a 5G+ smart distribution network from five dimensions: reliable operation, economic operation, efficient interaction, technological intelligence, and green emission reduction. Second, by introducing the principle of variance minimization, we propose a combined weighting method based on the improved FAHP-EWM to calculate the comprehensive weight, so as to reduce the defects of subjective arbitrariness and promote objectivity. Finally, a comprehensive evaluation model of 5G+ smart distribution network based on cloud model is proposed by considering the uncertainty of distribution network node information and equipment status information. The example analysis indicates that the overall operation of the 5G+ smart distribution network project is decent, and the weight value calculated by the combined weighting method is more reasonable and accurate than that calculated by the single weighting method, which verifies the effectiveness and rationality of the proposed evaluation method. Moreover, the proposed evaluation method has a certain guiding role for the large-scale application of 5G communication technology in smart distribution networks.

Amyotrophic lateral sclerosis (ALS) is a devastating neurodegenerative disease characterized by the progressive loss of motor neurons in the brain and spinal cord, and there are no effective drug treatments. Low-intensity pulsed ultrasound (LIPUS) has garnered attention as a promising noninvasive neuromodulation method. In this study, we investigate its effects on the motor cortex and underlying mechanisms using the SOD1G93Amouse model of ALS. Our results show that LIPUS treatment delays disease onset and prolongs lifespan in ALS mice. LIPUS significantly increases cerebral blood flow in the motor cortex by preserving vascular endothelial cell integrity and increasing microvascular density, which may be mediated via the ion channel TRPV4. RNA sequencing analysis reveals that LIPUS substantially reduces the expression of genes associated with neuroinflammation. These findings suggest that LIPUS applied to the motor cortex may represent a potentially effective therapeutic tool for the treatment of ALS.

Bacterial networks became less connected with soil development along primary succession.Community composition was initially governed by stochasticity, but as succession proceeded, there was a progressive increase in deterministic selection correlated with decreasing pH.Most natural microorganisms in extreme habitats exist as consortia that provide robustness and extensive metabolic capabilities in structuring bacterial communities.

Dysfunctional CD8+T cells, which have defective production of antitumor effectors, represent a major mediator of immunosuppression in the tumor microenvironment. Here, we show that SUSD2 is a negative regulator of CD8+T cell antitumor function. Susd2−/−effector CD8+T cells showed enhanced production of antitumor molecules, which consequently blunted tumor growth in multiple syngeneic mouse tumor models. Through a quantitative mass spectrometry assay, we found that SUSD2 interacted with interleukin (IL)-2 receptor α through sushi domain-dependent protein interactions and that this interaction suppressed the binding of IL-2, an essential cytokine for the effector functions of CD8+T cells, to IL-2 receptor α. SUSD2 was not expressed on regulatory CD4+T cells and did not affect the inhibitory function of these cells. Adoptive transfer of Susd2−/−chimeric antigen receptor T cells induced a robust antitumor response in mice, highlighting the potential of SUSD2 as an immunotherapy target for cancer.

Various types of biomaterials have been widely used to treat complex bone defects. However, potential infection risks and inappropriate host immune responses induced by biomaterials can adversely affect the final bone repair outcome. Therefore, the development of novel bone biomaterials with antibacterial and immunomodulatory capabilities is conducive to achieving a good interaction between the host and material, thereby creating a local microenvironment favorable for osteogenesis and ultimately accelerating bone regeneration. In this study, we fabricated a porcine small intestinal submucosa (SIS) hydrogel containing LL37 peptides and polylactic-glycolic acid (PLGA) microspheres encapsulated with WP9QY(W9) peptide (LL37-W9/PLGA-SIS), which can fill irregular bone defects and exhibits excellent mechanical properties. In vitro experiments showed that the microsphere–gel composite system had sequential drug release characteristics. The LL37 peptide released first had good antibacterial performance and BMSC recruitment ability, which could prevent infection at an early stage and increase the number of BMSCs at the injured site. In addition, it also has immunomodulatory properties, showing both pro-inflammatory and anti-inflammatory activities, but its early pro-inflammatory properties are more inclined to activate the M1 phenotype of macrophages. Moreover, the subsequently released W9 peptide not only reduced the expression of pro-inflammatory genes to alleviate inflammation and induced more macrophages to convert to M2 phenotypes but also promoted the osteogenic differentiation of BMSCs. This finely regulated immune response is considered to be more closely related to the physiological bone healing process. When studying the interaction between macrophages and BMSCs mediated by the material, it was found that the immunomodulatory and osteogenic effects were enhanced. In vivo experiments, we constructed rat skull defect models, which further proved that LL37-W9/PLGA-SIS gel can properly regulate the immune response, and has a good ability to promote osteogenesis in situ. In conclusion, the LL37-W9/PLGA-SIS hydrogel has great application prospects in immune regulation and bone therapy.

Exosomes derived from mesenchymal stem cells (MSCs) have been proven to exhibit great potentials in spinal cord injury (SCI) therapy. However, conventional two-dimensional (2D) culture will inevitably lead to the loss of stemness of MSCs, which substantially limits the therapeutic potency of MSCs exosomes (2D-Exo). Exosomes derived from three-dimensional culture (3D-Exo) possess higher therapeutic efficiency which have wide applications in spinal cord therapy. Typically, conventional exosome therapy that relies on local repeated injection results in secondary injury and low efficiency. It is urgent to develop a more reliable, convenient, and effective exosome delivery method to achieve constant in situexosomes release. Herein, we proposed a controlled 3D-exohydrogel hybrid microneedle array patch to achieve SCI repair in situ. Our studies suggested that MSCs with 3D-culturing could maintain their stemness, and consequently, 3D-Exo effectively reduced SCI-induced inflammation and glial scarring. Thus, it is a promising therapeutic strategy for the treatment of SCI.

The early-age cracking of concrete is one of the most critical parameters affecting the performance of concrete structures. It is attributed to both the internal and external influences such as early age restrained shrinkage, thermal deformation as well as the applied load. In this paper, a detailed review of the causes of early-age cracking is first presented, followed by the factors affecting the concrete cracking including raw materials quality problems, improper construction measures, external environmental influences and structural design flaws. Then the preventive measures for concrete cracking are summarized. The potential for the application and development of structural health monitoring and artificial intelligence techniques for early-age cracking of concrete is also discussed. Through the comprehensive review of the early-age cracking of concrete, the research direction for the subsequent research on early-age cracking of concrete is pointed out. The current problems and concerns of concrete cracking are also prospected.

Acoustic metasurfaces have shown great promise for applications in many acoustic wave modulation fields, while the use of intelligent optimization algorithms has facilitated the design of acoustic metasurfaces. In this paper, we utilize the stop band properties of phononic crystals to design a metasurface that can achieve both transmission focusing and reflection focusing, as well as a metasurface that utilizes acoustic focusing to filter the incident acoustic wave. In order to achieve the best effect, this paper uses the taboo genetic algorithm to optimize the arrangement order of the structural units controlling different focuses in the acoustic metasurface, and the optimization achieves a good focusing effect, which expands the design of acoustic metasurfaces as well as the application scenarios of acoustic focusing.

Conventional defect detection and recognition algorithms for integrated circuit (IC) components, used in printed circuit boards (PCBs), are primarily based on automated optical inspection (AOI). These techniques typically extract image features using image processing models, which are heavily dependent on visual cues and can thus be inaccurate. To address these issues, we propose the use of a deep convolutional neural network, an improved LeNet-5 structure called ICChaNet with a deeper structure and more complex parameters. First, the algorithm for character extraction is implemented and used to generate character samples from IC component images. This process includes grayscaling, binarization, and contour extraction, applied to a set of IC component images to establish 53 categories of characters (letters and number with similar symbols removed). Three critical hyperparameters, including learning rate, pooling strategy, and optimization strategy, are then optimized through a comparative analysis. The effect of different network architectures on model efficiency is also investigated by varying the layer depth. A combination classifier strategy is subsequently added to the fully connected layers to strengthen the feature expression in the corresponding classes. Finally, the performance of the proposed ICChaNet model is verified through a comparison with popular CNNs. Experimental results demonstrate that ICChaNet has achieved a classification accuracy of 98.5% and a test average accuracy precision of 97.73%. These results suggest the proposed ICChaNet model is a promising approach for automated character identification.