The existence of micro cracks inside rocks influences the rock strength and deformation significantly and controls the presence of crack closure stage under compression. However typical discrete ...element method (DEM) fails to model the gradual crack closure behavior of rock due to insufficient consideration for pre-existing micro-cracks. The stress-strain curves simulated in previous DEM are usually linear in initial stage until numerous cracks are induced under stress. Thus a new method implemented in Discrete Element Method is proposed to model the crack closure behavior of rocks under uniaxial compression. The pre-existing micro-cracks inside the rock sample are created and opened by introducing two notional contact surfaces and giving a negative reference gap. These opened cracks are gradually closed under stress as the adjacent discs sustain sufficient relative movement (re-contact). Thus the gradual crack closure behavior of rock under compression is reproduced. The crack distribution respect to the crack orientation is described with the crack tensor analysis to consider the effect of crack density and anisotropy. Three factors including crack intensity, crack orientation and crack gap are discussed with parametric study to study their influence on the crack closure behavior. The effects of pre-existing cracks on the properties of rocks (such as rock strength, Young's modulus, crack closure stress levels) are also analyzed, and are in well agreement with observations by experiment. A little modification is made to previous calibration process to consider the crack closure stage of rock. Finally two types of rocks including limestone and granite are calibrated and compared to the experiment results. The simulated stress-strain curves match the curves of experiment, especially the initial crack closure segment perfectly, which validates the proposed method.
Microfluidic paper chip combined with ion imprinting technology and ZnSe quantum dots for the detection of cadmium and lead ions in oceans and lakes.
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•A novel ZnSe quantum dots-based ...MIP paper microfluidic devices (μPADs) was developed.•ZnSe quantum dots are less toxic to the environment.•The rotary μPADs gave a flexible convenient way to multiplexed detection of Cd2+ and Pb2+.
In this study, a newly fluorescent ZnSe quantum dots (QDs) with ion imprinting technology was firstly realized on the three-dimensional (3D) rotary paper–based microfluidic chip platform which can be used to realize specific and multiplexed detection of Cadmium ions (Cd2+) and Lead ions (Pb2+). Compared to CdTe quantum dots, ZnSe quantum dots are less toxic and more environmental friendly. In addition, this design improved the portability of the device by transferred the liquid phase of ZnSe QDs@ion imprinted polymers to solid glass fiber paper. Moreover, the 3D rotary microfluidic chip (μPADs) showed great advantages including low cost, simple and fast facile operation, multiplexed detection, and showed good sensitivity and selectivity. Under optimal experiment conditions, our proposed method was enabled to realize specific and multi-channel determination of Cd2+ and Pb2+ ions. The developed sensor of Cd2+μPADs provided a linear response from 1 to 70 μg/L with a lower detection limit of 0.245 μg/L, and Pb2+μPADs provided a linear response from 1 to 60 μg/L with a lower detection limit of 0.335 μg/L, respectively. Excitingly, this newly designed 3D rotary μPADs exhibited quantitative information conveniently, which showed the promising application prospects to rapid testing target metal ions in environmental in the future.
Immunotherapy has received tremendous attention for tumor treatment, but the efficacy is greatly hindered by insufficient tumor‐infiltration of immune cells and immunosuppressive tumor ...microenvironment. The strategy that can efficiently activate cytotoxic T lymphocytes and inhibit negative immune regulators will greatly amplify immunotherapy outcome, which is however very rare. Herein, a new kind of semiconducting polymer (SP) nanoparticles is developed, featured with surface‐mimicking protein secondary structure (SPSS NPs) for self‐synergistic cancer immunotherapy by combining immunogenic cell death (ICD) and immune checkpoint blockade therapy. The SPs with excellent photodynamic property are synthesized by rational fluorination, which can massively induce ICD. Additionally, the peptide antagonists are introduced and self‐assembled into β‐sheet protein secondary structures on the photodynamic NP surface via preparation process optimization, which function as efficient lysosome‐targeting chimaeras (LYTACs) to mediate the degradation of programmed cell death ligand‐1 (PD‐L1) in lysosome. In vivo experiments demonstrate that SPSS NPs can not only elicit strong antitumor immunity to suppress both primary tumor and distant tumor, but also evoke long‐term immunological memory against tumor rechallenge. This work introduces a new kind of robust immunotherapy agents by combining well‐designed photosensitizer‐based ICD induction and protein secondary structures‐mediated LYTAC‐like multivalence PD‐L1 blockade, rendering great promise for synergistic immunotherapy.
A new kind of photodynamic semiconducting polymer nanoparticles with surface mimicking protein secondary structure (SPSS NPs) is developed to achieve self‐synergistic cancer immunotherapy by combining excellent immunogenic cell death and lysosome‐targeting chimaera‐like multivalent programmed cell death ligand‐1 blockade. SPSS NPs can not only effectively suppress both primary tumor and distant tumor, but also evoke long‐term immunological memory against tumor rechallenge.
Polarization is a fundamental property of light and a powerful sensing tool that has been applied to many areas. A Mueller matrix is a complete mathematical description of the polarization ...characteristics of objects that interact with light, and is known as a transfer function of Stokes vectors which characterise the state of polarization of light. Mueller polarimetric imaging measures Mueller matrices over a field of view and thus allows for visualising the polarization characteristics of the objects. It has emerged as a promising technique in recent years for tissue imaging, improving image contrast and providing a unique perspective to reveal additional information that cannot be resolved by other optical imaging modalities. This review introduces the basis of the Stokes‐Mueller formulism, interpretation methods of Mueller matrices into fundamental polarization properties, polarization properties of biological tissues, and considerations in the construction of Mueller polarimetric imaging devices for surgical and diagnostic applications, including primary configurations, optimization procedures, calibration methods as well as the instrument polarization properties of several widely‐used biomedical optical devices. The paper also reviews recent progress in Mueller polarimetric endoscopes and fibre Mueller polarimeters, followed by the future outlook in applying the technique to surgery and diagnostics. Tissue polarization properties convey morphological, micro‐structural and compositional information of tissue with great potential for label free characterization of tissue pathological changes. Recent progress in tissue polarimetric imaging and polarization resolved endoscopy paved the way for translation of polarimetric imaging to surgery and tissue diagnosis.
Polarization is a fundamental property of light that is able to provide an interesting and unique insight into tissue. Tissue polarization properties convey morphological, micro‐structural and compositional information of tissue with great potential for label free characterization of tissue pathological changes. Recent progress in tissue polarimetric imaging and polarization resolved endoscopy paved the way for translation of polarimetric imaging to surgery and tissue diagnosis.
With the development of deep learning, supervised learning methods perform well in remote sensing image (RSI) scene classification. However, supervised learning requires a huge number of annotated ...data for training. When labeled samples are not sufficient, the most common solution is to fine-tune the pretraining models using a large natural image data set (e.g., ImageNet). However, this learning paradigm is not a panacea, especially when the target RSIs (e.g., multispectral and hyperspectral data) have different imaging mechanisms from RGB natural images. To solve this problem, we introduce a new self-supervised learning (SSL) mechanism to obtain the high-performance pretraining model for RSI scene classification from large unlabeled data. Experiments on three commonly used RSI scene classification data sets demonstrated that this new learning paradigm outperforms the traditional dominant ImageNet pretrained model. Moreover, we analyze the impacts of several factors in SSL on RSI scene classification, including the choice of self-supervised signals, the domain difference between the source and target data sets, and the amount of pretraining data. The insights distilled from this work can help to foster the development of SSL in the remote sensing community. Since SSL could learn from unlabeled massive RSIs, which are extremely easy to obtain, it will be a promising way to alleviate dependence on labeled samples and thus efficiently solve many problems, such as global mapping.
As a monumental breakthrough in cancer treatment, immunotherapy has attracted tremendous attention in recent years. However, one challenge faced by immunotherapy is the low response rate and the ...immune‐related adverse events (irAEs). Therefore, it is important to explore new therapeutic strategies and platforms for boosting therapeutic benefits and decreasing the side effects of immunotherapy. In recent years, semiconducting polymer (SP), a category of organic materials with π‐conjugated aromatic backbone, has been attracting considerable attention because of their outstanding characteristics such as excellent photophysical features, good biosafety, adjustable chemical flexibility, easy fabrication, and high stability. With these distinct advantages, SP is extensively explored for bioimaging and photo‐ or ultrasound‐activated tumor therapy. Here, the recent advancements in SP‐based nanomedicines are summarized for enhanced tumor immunotherapy. According to the photophysical properties of SPs, the cancer immunotherapies enabled by SPs with the photothermal, photodynamic, or sonodynamic functions are highlighted in detail, with a particular focus on the construction of combination immunotherapy and activatable nanoplatforms to maximize the benefits of cancer immunotherapy. Herein, new guidance and comprehensive insights are provided for the design of SPs with desired photophysical properties to realize maximized effectiveness of required biomedical applications.
Herein, the recent advancements in semiconducting polymer‐based nanomedicines are summarized for enhanced tumor immunotherapy. The cancer immunotherapies enabled by semiconducting polymers with the photothermal, photodynamic, or sonodynamic functions are highlighted in detail, with a particular focus on the construction of combination immunotherapy and activatable nanoplatforms to boost the outcomes of cancer immunotherapy.
Semiconducting Polymers for Cancer Immunotherapy Li, Wen; Liang, Mengyun; Qi, Ji ...
Macromolecular rapid communications.,
December 2023, 2023-12-00, 20231201, Letnik:
44, Številka:
23
Journal Article
Recenzirano
Odprti dostop
Inside Front Cover: In article 2300496, Ji Qi, Dan Ding, and co‐workers summarize the recent advancements in semiconducting polymer (SP)‐based nanomedicines for enhanced tumor immunotherapy. The ...cancer immunotherapies enabled by SPs with the photothermal, photodynamic, or sonodynamic functions are highlighted in detail, which can not only kill tumors directly but also evoke immunogenic cell death of cancer cells for immunotherapy. Additionally, the constructions of combination immunotherapeutic nanoplatforms, in which immunomodulatory agents can further be released from SP NPs to boost immunotherapeutic action, are also introduced.
Modular-spoke-type permanent-magnet (MSTPM) machines are novel in-wheel traction machines for electric vehicles (EVs). Considering the strict constraints including the mass and volume of electric ...machines in EVs, which are heavily dependent on the dissipation condition, an accurate thermal model and resultant temperature distribution analysis are key challenges. Therefore, in this paper, a lumped parameter thermal network (LPTN) model for thermal analysis of MSTPM machines is proposed, where the heat transfer coefficients are determined theoretically instead of empirically, which means that the proposed LPTN model can be applicable for the MSTPM machines with different specifications and parameters. Both the steady-state and transient-state temperature rises are analyzed by the LPTN model, and the results are verified by both 3-D finite element analysis (FEA) predictions and experiments, indicating that the proposed method has advantages in both computational efficiency and accuracy.
The progressive debilitating nature of rheumatoid arthritis (RA) combined with its unknown etiology and initial similarity to other inflammatory diseases makes early diagnosis a significant ...challenge. Early recognition and treatment of RA is essential for achieving effective therapeutic outcome. NIR‐II photoacoustic (PA) molecular imaging (PMI) is emerging as a promising new strategy for effective diagnosis and treatment guidance of RA, owing to its high sensitivity and specificity at large penetration depth. Herein, an antirheumatic targeted drug tocilizumab (TCZ) is conjugated to polymer nanoparticles (PNPs) to develop the first NIR‐II theranostic nanoplatform, named TCZ‐PNPs, for PA‐imaging‐guided therapy of RA. The TCZ‐PNPs are demonstrated to have strong NIR‐II extinction coefficient, high photostability and excellent biocompatibility. NIR‐II PMI results reveal the excellent targeting abilities of TCZ‐PNPs for the effective noninvasive diagnosis of RA joint tissue with a high signal‐to noise ratio (SNR) of 35.8 dB in 3D PA tomography images. Remarkably, one‐month treatment and PA monitoring using TCZ‐PNPs shows RA is significantly suppressed. In addition, the therapeutic evaluation of RA mice by NIR‐II PMI is shown to be consistent with clinical micro‐CT and histological analysis. The TCZ‐PNPs‐assisted NIR‐II PMI provides a new strategy for RA theranostics, therapeutic monitoring and the beyond.
The US Food and Drug Administration approved antirheumatic targeted drug tocilizumab (TCZ) is conjugated to polymer nanoparticles (PNPs) to develop TCZ‐PNPs for near‐infrared (NIR)‐II photoacoustic (PA) imaging‐guided therapy of rheumatoid arthritis (RA). TCZ‐PNPs‐assisted NIR‐II PA molecular imaging shows that the TCZ‐PNPs have excellent RA specificity and a significant suppression effect, which provides a new strategy for RA theranostics and therapeutic monitoring.
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