Sepsis is a life‐threatening disease resulted from a dysregulated host immune response to bacterial infections, continuing to cause high morbidity and mortality worldwide. Despite discoveries of many ...potential therapeutic targets, effective treatments of sepsis are lacking. Here, a strategy is reported to target infectious microenvironments (IMEs) via bioresponsive nanoparticles that simultaneously eliminate bacteria and alleviate the host inflammation response, thus managing sepsis in mice. The nanoparticle is made of copolymers sensitive to pH and bacterial enzymes to self‐assemble into a micelle loaded with both an antibiotic (ciprofloxacin) and an anti‐inflammatory agent ((2‐(aminocarbonyl)amino‐5‐(4‐fluorophenyl)‐3‐thiophenecarboxamide). In addition, the nanoparticle is conjugated with intercellular adhesion molecule‐1 antibodies to target IMEs. Nanoparticle targeting to IMEs and local cues as triggers to deliver therapeutics in on‐demand manners is demonstrated using an acute lung bacterial infection mouse model. In the sepsis mouse model induced by peritonitis at a lethal dose of bacterial invasion, it is shown that concurrently targeting pathogens and excessive inflammation pathways is valuable to manage the sepsis. The study illustrates not only the development of a new delivery system but also the mechanism‐based therapy of nanomedicine for infectious diseases.
Stimuli‐responsive nanoparticles loaded with antibiotic and anti‐inflammatory agents can specifically target infection sites via binding to intercellular adhesion molecule‐1 (ICAM‐1) expressed on inflamed endothelium. The nanoparticles are composed of pH/enzyme‐responsive copolymers and anti‐mouse ICAM‐1 antibody, and drug release is triggered by infectious microenvironments. The studies show concurrently eliminating pathogens and mitigating host inflammation responses are valuable to manage sepsis.
Object detection is a fundamental step for automated video analysis in many vision applications. Object detection in a video is usually performed by object detectors or background subtraction ...techniques. Often, an object detector requires manually labeled examples to train a binary classifier, while background subtraction needs a training sequence that contains no objects to build a background model. To automate the analysis, object detection without a separate training phase becomes a critical task. People have tried to tackle this task by using motion information. But existing motion-based methods are usually limited when coping with complex scenarios such as nonrigid motion and dynamic background. In this paper, we show that the above challenges can be addressed in a unified framework named DEtecting Contiguous Outliers in the LOw-rank Representation (DECOLOR). This formulation integrates object detection and background learning into a single process of optimization, which can be solved by an alternating algorithm efficiently. We explain the relations between DECOLOR and other sparsity-based methods. Experiments on both simulated data and real sequences demonstrate that DECOLOR outperforms the state-of-the-art approaches and it can work effectively on a wide range of complex scenarios.
2D carbon nitride nanosheets have attracted ever‐increasing interest in photocatalysis due to their unique structural advantages. However, the nanosheets synthesized by the traditional methods, such ...as post oxidation and liquid exfoliation, have suffered from in‐plane disorder with abundant structural defects, which seriously counteracts their structural benefits for photocatalysis. Herein, it is demonstrated that polymer carbon nitride nanosheets with in‐plane highly ordered structure (PCNNs‐IHO) can be successfully prepared by on‐surface polymerization of melamine on NaCl crystal surface at elevated temperatures. The NaCl crystals with relative high surface energy not only facilitate the adsorption and activation of melamine to undergo condensation reaction, but also function as unique substrates to orientate the assembly of 2D nanosheet structure. In addition, NaCl also acts as a reactant to provide Na+ doping into carbon nitride matrix, affording PCNNs‐IHO with robust structural base sites. Benefiting from this structural basicity, PCNNs‐IHO exhibits superior photocatalytic performance toward CH3SH mineralization under visible light irradiation.
In‐plane highly ordered carbon nitride nanosheets with low structural defects synthesized by on‐surface polymerization are endowed with strong sulfation‐resistant ability and good reusability for complete photocatalytic mineralization of mercaptans. This study highlights the on‐surface polymerization technique which opens up the prospect of the construction of an atomically controlled nanostructure with potentially advantageous properties that cannot otherwise be synthesized.
Photodynamic therapy (PDT) is a treatment by combining light and a photosensitizer to generate reactive oxygen species (ROS) for cellular damage, and is used to treat cancer and infectious diseases. ...In this review, we focus on recent advances in design of new photosensitizers for increased production of ROS and in genetic engineering of biological photosensitizers to study cellular signaling pathways. A new concept has been proposed that PDT‐induced acute inflammation can mediate neutrophil infiltration to deliver therapeutics in deep tumor tissues. Combination of PDT and immunotherapies (neutrophil‐mediated therapeutic delivery) has shown the promising translation of PDT for cancer therapies. Furthermore, a new area in PDT is to treat bacterial infections to overcome the antimicrobial resistance. Finally, we have discussed the new directions of PDT for therapies of cancer and infectious diseases. In summary, we believe that rational design and innovations in nanomaterials may have a great impact on translation of PDT in cancer and infectious diseases.
This article is categorized under:
Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease
Therapeutic Approaches and Drug Discovery > Nanomedicine for Infectious Disease
Nanotechnology Approaches to Biology > Nanoscale Systems in Biology
Schematic illustration of the photochemical reactions in photodynamic therapy.
•Waste heat recovery behavior of the RCS during driving cycle was investigated.•Four operating modes were defined to describe the operating process of the RCS under driving cycle.•The operating mode ...switching is the crucial reason for on-road inefficiency.•The dry and isentropic fluids are superior to the wet ones on the adaptability to unsteady ExGE.•The effects of the vapor parameters on RCT-E and power mode percentage are opposite.
The RCS (Rankine cycle system) used to recover the WHE (waste heat energy) from engines has been regarded as one of the most potential ways of achieving higher efficiency. However, it is of great challenge to keep the RCS still in good performance under driving cycle. This paper tries to reveal and explain its on-road inefficiency.
The operating process of the RCS under driving cycle was analyzed in advance. Afterwards, four basic operating modes were defined, including startup mode, turbine turning mode, power mode and protection mode. Then, a RCS model was established and operating performances of the RCS under an actual driving cycle were discussed based on this model. The results indicate that the on-road RCS-E (Rankine cycle system efficiency) is as low as 3.63%, which is less than half of the design RCS-E (7.77%) at the rated operating point. Despite the inevitable vapor state fluctuation, it is the operating mode switching during the driving cycle that leads to the on-road inefficiency. Further investigations indicate that the expander safety temperature and its safety margin affected by the working fluids, designed superheat degree and evaporating pressure are the main factors determining the operating mode switching. Finally, the effects of the working fluids, designed superheat degree and evaporating pressure on the operating mode switching and RC (Rankine cycle) efficiencies were profoundly investigated. The study shows that the dry and isentropic fluids are superior to the wet ones due to their less probabilities of droplets formation as a consequence of their saturated vapor characteristics. The effects of the vapor parameters on the RCT-E (Rankine cycle thermal efficiency) and operating mode switching are opposite. Therefore, in order to optimize the RCS, it would be better to take full consideration in reducing the operating mode switching, while pursuing the maximum RCT-E.
Low-rank modeling generally refers to a class of methods that solves problems by representing variables of interest as low-rank matrices. It has achieved great success in various fields including ...computer vision, data mining, signal processing, and bioinformatics. Recently, much progress has been made in theories, algorithms, and applications of low-rank modeling, such as exact low-rank matrix recovery via convex programming and matrix completion applied to collaborative filtering. These advances have brought more and more attention to this topic. In this article, we review the recent advances of low-rank modeling, the state-of-the-art algorithms, and the related applications in image analysis. We first give an overview of the concept of low-rank modeling and the challenging problems in this area. Then, we summarize the models and algorithms for low-rank matrix recovery and illustrate their advantages and limitations with numerical experiments. Next, we introduce a few applications of low-rank modeling in the context of image analysis. Finally, we conclude this article with some discussions.
Polymeric carbon nitride modified with selected heteroatom dopants was prepared and used as a model photocatalyst to identify and understand the key mechanisms required for efficient photoproduction ...of H2O2 via selective oxygen reduction reaction (ORR). The photochemical production of H2O2 was achieved at a millimolar level per hour under visible‐light irradiation along with 100 % apparent quantum yield (in 360–450 nm region) and 96 % selectivity in an electrochemical system (0.1 V vs. RHE). Spectroscopic analysis in spatiotemporal resolution and theoretical calculations revealed that the synergistic association of alkali and sulfur dopants in the polymeric matrix promoted the interlayer charge separation and polarization of trapped electrons for preferable oxygen capture and reduction in ORR kinetics. This work highlights the key features that are responsible for controlling the photocatalytic activity and selectivity toward the two‐electron ORR, which should be the basis of further development of solar H2O2 production.
Heptazine‐based C3N4 photocatalysts with heteroatom dopants exhibit potassium‐induced interlayer charge separation and local charge polarization on sulfur sites. This facilitates O2 adsorption and the subsequent two‐electron reduction of dioxygen to achieve highly efficient and selective production of H2O2 up to a millimolar level per hour and 100 % apparent quantum yield at 420 nm.
Glioblastoma (GBM) is the most malignant and highly aggressive brain tumor. In this study, four types of typical GBM cell lines (LN229, SNB19, U87, U251) were cultured in a microfabricated 3-D model ...to study their in vitro behaviors. The 3-D in vitro model provides hollow micro-chamber arrays containing a natural collagen interface and thus allows the GBM cells to grow in the 3-D chambers. The GBM cells in this model showed specific properties on the aspects of cell morphology, proliferation, migration, and invasion, some of which were rarely observed before. Furthermore, how the cells invaded into the surrounding ECM and the corresponding specific invasion patterns were observed in details, implying that the four types of cells have different features during their development in cancer. This complex in vitro model, if applied to patient derived cells, possesses the potential of becoming a clinically relevant predictive model.
Construction of organic semiconducting materials with in-plane π-conjugated structures and robustness through carbon-carbon bond linkages, alternatively as organic graphene analogs, is extremely ...desired for powerfully optoelectrical conversion. However, the poor reversibility for sp
carbon bond forming reactions makes them unavailable for building high crystalline well-defined organic structures through a self-healing process, such as covalent organic frameworks (COFs). Here we report a scalable solution-processing approach to synthesize a family of two-dimensional (2D) COFs with trans-disubstituted C = C linkages via condensation reaction at arylmethyl carbon atoms on the basis of 3,5-dicyano-2,4,6-trimethylpyridine and linear/trigonal aldehyde (i.e., 4,4″-diformyl-p-terphenyl, 4,4'-diformyl-1,1'-biphenyl, or 1,3,5-tris(4-formylphenyl)benzene) monomers. Such sp
carbon-jointed-pyridinyl frameworks, featuring crystalline honeycomb-like structures with high surface areas, enable driving two half-reactions of water splitting separately under visible light irradiation, comparable to graphitic carbon nitride (g-C
N
) derivatives.
The development of polygenic risk scores (PRSs) has proved useful to stratify the general European population into different risk groups. However, PRSs are less accurate in non-European populations ...due to genetic differences across different populations. To improve the prediction accuracy in non-European populations, we propose a cross-population analysis framework for PRS construction with both individual-level (XPA) and summary-level (XPASS) GWAS data. By leveraging trans-ancestry genetic correlation, our methods can borrow information from the Biobank-scale European population data to improve risk prediction in the non-European populations. Our framework can also incorporate population-specific effects to further improve construction of PRS. With innovations in data structure and algorithm design, our methods provide a substantial saving in computational time and memory usage. Through comprehensive simulation studies, we show that our framework provides accurate, efficient, and robust PRS construction across a range of genetic architectures. In a Chinese cohort, our methods achieved 7.3%–198.0% accuracy gain for height and 19.5%–313.3% accuracy gain for body mass index (BMI) in terms of predictive R2 compared to existing PRS approaches. We also show that XPA and XPASS can achieve substantial improvement for construction of height PRSs in the African population, suggesting the generality of our framework across global populations.
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