Search

The photocatalytic nitrogen reduction reaction (NRR) in aqueous solution is a green and sustainable strategy for ammonia production. Nonetheless, the efficiency of the process still has a wide gap compared to that of the Haber–Bosch one due to the difficulty of N2 activation and the quick recombination of photo-generated carriers. Herein, a core-shell Bi@Bi2MoO6 microsphere through constructing Schottky junctions has been explored as a robust photocatalyst toward N2 reduction to NH3. Metal Bi self-reduced onto Bi2MoO6 not only spurs the photo-generated electron and hole separation owing to the Schottky junction at the interface of Bi and Bi2MoO6 but also promotes N2 adsorption and activation at Bi active sites synchronously. As a result, the yield of the photocatalytic N2-to-ammonia conversion reaches up to 173.40 μmol g−1 on core-shell Bi@Bi2MoO6 photocatalysts, as much as two times of that of bare Bi2MoO6. This work provides a new design for the decarbonization of the nitrogen reduction reaction by the utilization of renewable energy sources.

To address China’s small coal power units facing shutdown and retirement, which urgently need life cycle extension and renovation, a complete solar thermal storage simulation power generation system based on the original site of a decommissioned thermal power unit is developed using Ebsilon software in this study. The operational characteristics of the simulated system are studied in depth to build a system with integrity and stability that can carry out economic and stable power production. The results of simulation tests on the solar collector system and the thermal storage subsystem show that the energy storage rate of the energy storage subsystem is affected by light intensity and significantly increases at approximately 8:00 a.m. The annual power generation capacity of the system is influenced by the energy storage hours set by the energy storage subsystem, and the annual power generation capacity increases more significantly when the energy storage hours are controlled within the range of 5–8 h. The operating efficiency of the corresponding subsystem can be improved by selecting a suitable location for the light intensity required and controlling the effective reflectivity of the mirror field and the energy storage hours, which can ensure the system’s stable operation. The research results provide theoretical guidance for reusing and transforming retired thermal power units.

In order to explore the law of gas–solid countercurrent cooling heat transfer in a vertical sinter cooling furnace at a high temperature, based on the Euler model and the local non-thermodynamic equilibrium theory, an exergy efficiency model was built to evaluate the heat transfer process in the vertical sinter cooling furnace with different parameter changes. It was found that the inlet temperature of cooling air and sinter inlet temperature are the main factors affecting the temperature field and gas–solid heat transfer characteristics in the furnace. Under the conditions of each parameter, the cooling air temperature presents a radial “M” shape distribution. The axial cooling section is the most intense area of gas–solid heat transfer, and this part has the best heat transfer effect. When the inlet temperature of cooling air and the inlet temperature of sinter increase, the outlet temperature of sinter and the outlet temperature of cooling air increase. When the sinter equivalent diameter increases, the cooling air outlet temperature decreases gradually, while the sinter outlet temperature increases gradually. When the diameter and height of the cooling section increase, respectively, the outlet temperature of the sinter decreases and the outlet temperature of the cooling air increases. Based on dimensional analysis, the heat transfer correlation formula suitable for certain test conditions is obtained.

We study a new technique for solving the fundamental challenge in nanophotonic design: fast and accurate characterization of nanoscale photonic devices with minimal human intervention. Much like the fusion between Artificial Intelligence and Electronic Design Automation (EDA), many efforts have been made to apply deep neural networks (DNN) such as convolutional neural networks to prototype and characterize next-gen optoelectronic devices commonly found in Photonic Integrated Circuits. However, state-of-the-art DNN models are still far from being directly applicable in the real world: e.g., DNN-produced correlation coefficients between target and predicted physical quantities are about 80%, which is much lower than what it takes to generate reliable and reproducible nanophotonic designs. Recently, attention-based transformer models have attracted extensive interests and been widely used in Computer Vision and Natural Language Processing. In this work, we for the first time propose a Transformer model (POViT) to efficiently design and simulate photonic crystal nanocavities with multiple objectives under consideration. Unlike the standard Vision Transformer, our model takes photonic crystals as input data and changes the activation layer from GELU to an absolute-value function. Extensive experiments show that POViT significantly improves results reported by previous models: correlation coefficients are increased by over 12% (i.e., to 92.0%) and prediction errors are reduced by an order of magnitude, among several key metric improvements. Our work has the potential to drive the expansion of EDA to fully automated photonic design (i.e., PDA). The complete dataset and code will be released to promote research in the interdisciplinary field of materials science/physics and computer science.

In this study, a strategy was developed for in situ, non-intrusive, and quantitative measurement of the oxides of nitrogen (NO and NO2) to describe emission characteristics in gas turbines. The linear calibration-free wavelength modulation spectroscopy (LCF-WMS) approach combined with the temperature profile-fitting strategy was utilized for trace NO and NO2 concentration detection with broad spectral interference from gaseous water (H2O). Transition lines near 1308 nm, 5238 nm, and 6250 nm were selected to investigate the H2O, NO, and NO2 generated from combustion. Experiments were performed under different equivalence ratios in a combustion exhaust tube, which was heated at 450–700 K, with an effective optical length of 1.57 m. Ultra-low NOx emissions were captured by optical measurements under different equivalence ratios. The mole fractions of H2O were in agreement with the theoretical values calculated using Chemkin. Herein, the uncertainty of the TDLAS measurements and the limitation of improving the relative precision are discussed in detail. The proposed strategy proved to be a promising combustion diagnostic technique for the quantitative measurement of low-absorbance trace NO and NO2 with strong H2O interference in real combustion gases.

The design of nanophotonic structures based on deep learning is emerging rapidly in the research community. Design methods using Deep Neural Networks (DNN) are outperforming conventional physics-based simulations performed iteratively by human experts. Here, a self-adaptive and regularized DNN based on Convolutional Neural Networks (CNNs) for the smart and fast characterization of nanophotonic structures in high-dimensional design parameter space is presented. This proposed CNN model, named LRS-RCNN, utilizes dynamic learning rate scheduling and L2 regularization techniques to overcome overfitting and speed up training convergence and is shown to surpass the performance of all previous algorithms, with the exception of two metrics where it achieves a comparable level relative to prior works. We applied the model to two challenging types of photonic structures: 2D photonic crystals (e.g., L3 nanocavity) and 1D photonic crystals (e.g., nanobeam) and results show that LRS-RCNN achieves record-high prediction accuracies, strong generalizibility, and substantially faster convergence speed compared to prior works. Although still a proof-of-concept model, the proposed smart LRS-RCNN has been proven to greatly accelerate the design of photonic crystal structures as a state-of-the-art predictor for both Q-factor and V. It can also be modified and generalized to predict any type of optical properties for designing a wide range of different nanophotonic structures. The complete dataset and code will be released to aid the development of related research endeavors.

As an effective optical diagnosis method, tunable diode-laser absorption spectroscopy (TDLAS) has increasingly moved to examine nonuniform flows, such as two-dimensional combustion diagnosis. To investigate the effect of nonuniformity along the line of sight in a measurement using TDLAS, the integrated absorbance (IA, the key intermediate quantity in TDLAS) error was quantified. The error distribution is obtained from the line-shape parameters through the comprehensive analysis of the line-shape function and the fitting method. The effects of the fitting function and the absorption line overlap are also considered. A general method for estimating the error is given. The work illustrates the applicability of TDLAS technology in nonuniform flow fields and provides input parameters for the evaluation of tunable diode laser absorption tomography error.

UV-B illumination facilitates aggregation of alpha-lactalbumin (α-LA) by intramolecular disulfide bond cleavage followed by intermolecular thiol-disulfide exchange reactions. However, long term exposure to UV-B illumination may induce undesired oxidative modifications of amino acid residues in the protein. The purpose of this study was to examine the effect of UV-induced aggregation of apo-α-LA (a calcium-depleted form of α-LA) under aerobic and anaerobic conditions and by addition of tryptophan (Trp) as a photosensitizer. The addition of Trp to apo-α-LA illuminated under anaerobic conditions facilitated the highest level of free thiol release and disulfide-mediated aggregation as compared to without addition of Trp under both anaerobic and aerobic conditions. Addition of Trp under aerobic condition resulted in the lowest level of free thiols and disulfide-mediated aggregation and the aerobic conditions caused oxidation of the free Trp with formation of kynurenine and 5-hydroxy-Trp. Minor levels of the Trp oxidation product, 3-hydroxy-kynurenine (2% converted from Trp), was formed in apo-α-LA with added Trp under both aerobic and anaerobic conditions after UV-B treatment.

We adopted a weight of evidence approach to establish a causal analysis of an impaired land ecosystem on a regional scale; namely, Daye, a traditional mining city in China. Working processes, including problem statements, a list of candidate causes, and a conceptual model were developed to represent a causal hypothesis for describing land degradation. Causal criteria were applied to integrate multiple lines of evidence. Then, various pieces of evidence were scored to either strengthen or weaken our causal assumptions. Results showed that habitat alteration, heavy metal accumulation, organic pollutants, water eutrophication, and nutrient runoff were the probable causes of land ecosystem impairment in Daye. Meanwhile, noxious gas, toxicants, altered underground runoff, atmospheric deposition, and acid rain were identified as possible causes. The most unlikely causes were altered hydrology, altered earth surface runoff, and soil erosion. Soil salinization, soluble inorganic salts, biological species invasion, and pathogens were deferred as delayed causes due to lack of adequate information. The causal analysis approach was applied to identify the primary causes of land degradation and implement accurate protective measures in an impaired land ecosystem.

Bradykinin-related peptides (BRPs) are significant components of the defensive skin secretions of many anuran amphibians, and these secretions represent the source of the most diverse spectrum of such peptides so far encountered in nature. Of the many families of bioactive peptides that have been identified from this source, the BRPs uniquely appear to represent homologues of counterparts that have specific distributions and receptor targets within discrete vertebrate taxa, ranging from fishes through mammals. Their broad spectra of actions, including pain and inflammation induction and smooth muscle effects, make these peptides ideal weapons in predator deterrence. Here, we describe a novel 12-mer BRP (RVALPPGFTPLR-RVAL-(L1, T6, L8)-bradykinin) from the skin secretion of the Fujian large-headed frog (Limnonectes fujianensis). The C-terminal 9 residues of this BRP (-LPPGFTPLR) exhibit three amino acid substitutions (L/R at Position 1, T/S at Position 6 and L/F at Position 8) when compared to canonical mammalian bradykinin (BK), but are identical to the kinin sequence present within the cloned kininogen-2 from the Chinese soft-shelled turtle (Pelodiscus sinensis) and differ from that encoded by kininogen-2 of the Tibetan ground tit (Pseudopodoces humilis) at just a single site (F/L at Position 8). These data would imply that the novel BRP is an amphibian defensive agent against predation by sympatric turtles and also that the primary structure of the avian BK, ornithokinin (RPPGFTPLR), is not invariant within this taxon. Synthetic RVAL-(L1, T6, L8)-bradykinin was found to be an antagonist of BK-induced rat tail artery smooth muscle relaxation acting via the B2-receptor.

This paper presents a drowsiness on-line detection system for monitoring driver fatigue level under real driving conditions, based on the data of steering wheel angles (SWA) collected from sensors mounted on the steering lever. The proposed system firstly extracts approximate entropy (ApEn)featuresfromfixedslidingwindowsonreal-timesteeringwheelanglestimeseries. Afterthat, this system linearizes the ApEn features series through an adaptive piecewise linear fitting using a given deviation. Then, the detection system calculates the warping distance between the linear features series of the sample data. Finally, this system uses the warping distance to determine the drowsiness state of the driver according to a designed binary decision classifier. The experimental data were collected from 14.68 h driving under real road conditions, including two fatigue levels: “wake” and “drowsy”. The results show that the proposed system is capable of working online with an average 78.01% accuracy, 29.35% false detections of the “awake” state, and 15.15% false detections of the “drowsy” state. The results also confirm that the proposed method based on SWA signal is valuable for applications in preventing traffic accidents caused by driver fatigue.

Glycosaminoglycans (GAGs) are valuable bioactive polysaccharides with promising biomedical and pharmaceutical applications. In this study, we analyzed GAGs using HPLC-MS/MS from the bone (B), muscle (M), skin (S), and viscera (V) of Scophthalmus maximus (SM), Paralichthysi (P), Limanda ferruginea (LF), Cleisthenes herzensteini (G), Platichthys bicoloratus (PB), Pleuronichthys cornutus (PC), and Cleisthenes herzensteini (CH). Unsaturated disaccharide products were obtained by enzymatic hydrolysis of the GAGs and subjected to compositional analysis of chondroitin sulfate (CS), heparin sulfate (HS), and hyaluronic acid (HA), including the sulfation degree of CS and HS, as well as the content of each GAG. The contents of GAGs in the tissues and the sulfation degree differed significantly among the fish. The bone of S. maximus contained more than 12 μg of CS per mg of dry tissue. Although the fish typically contained high levels of CSA (CS-4S), some fish bone tissue exhibited elevated levels of CSC (CS-6S). The HS content was found to range from 10–150 ug/g, primarily distributed in viscera, with a predominant non-sulfated structure (HS-0S). The structure of HA is well-defined without sulfation modification. These analytical results are independent of biological classification. We provide a high-throughput rapid detection method for tissue samples using HPLC-MS/MS to rapidly screen ideal sources of GAG. On this basis, four kinds of CS were prepared and purified from flounder bone, and their molecular weight was determined to be 23–28 kDa by HPGPC-MALLS, and the disaccharide component unit was dominated by CS-6S, which is a potential substitute for CSC derived from shark cartilage.

Due to the size limitations of shaking tables, dynamic scale models of large-span space structures for engineering have small cross-sections and thin wall thicknesses. It is difficult to use the structural steels commonly used in prototypes to make dynamic scale models. In this paper, 304 stainless steel is proposed for making the scale model, and the similarity relationship between the structural-steel prototype and the 304-stainless-steel dynamic scale model was studied. Firstly, a uniaxial test was conducted to study the elastic modulus similarity and the yielding stress similarity. The test results demonstrated that the elastic modulus similarity ratio was 1:1, and the stress similarity ratios of the 304 stainless steel and the three typical structural steels were 1:1 (Q235 steel), 1:1.5 (Q355 steel) and 1:1.8 (Q420 steel). Then, the similarities of other variables were derived using the dimensional analysis method. In the end, a numerical analysis was conducted to verify the similarity relationship between the structural-steel prototype and the 304-stainless-steel dynamic scale model. In the numerical analysis, a single-layer spherical reticulated shell structure and a dynamic scale model with a length similarity ratio of 1:20 were established by using the ABAQUS 2021 software, and the node displacement, the element internal force and natural vibration characteristics were analyzed. The results show that standard deviations of the displacements, the internal forces and the natural vibration frequencies between the prototype and the scale model were within 5%. It turns out that the proposed similarity between the structural-steel prototype and the 304-stainless-steel dynamic scale model was applicable in the elastic stage. The findings provide a reference for designing a dynamic scale model of large-span space structures for engineering by using 304 stainless steel.

Crosstalk is the primary source of noise in quantum computing equipment. The parallel execution of multiple instructions in quantum computation causes crosstalk, which causes coupling between signal lines and mutual inductance and capacitance between signal lines, destroying the quantum state and causing the program to fail to execute correctly. Overcoming crosstalk is a critical prerequisite for quantum error correction and large-scale fault-tolerant quantum computing. This paper provides an approach for suppressing crosstalk in quantum computers based on multiple instruction exchange rules and duration. Firstly, for the majority of the quantum gates that can be executed on quantum computing devices, a multiple instruction exchange rule is proposed. The multiple instruction exchange rule reorders quantum gates in quantum circuits and separates double quantum gates with high crosstalk on quantum circuits. Then, time stakes are inserted based on the duration of different quantum gates, and quantum gates with high crosstalk are carefully separated in the process of quantum circuit execution by quantum computing equipment to reduce the influence of crosstalk on circuit fidelity. Several benchmark experiments verify the proposed method’s effectiveness. In comparison to previous techniques, the proposed method improves fidelity by 15.97% on average.

The loop-free single-layer hyperbolic cable net structure (LSHCS) is a new tensile cable structure for buildings, and it can overcome the disadvantages of key elements and the high tension in tensile cable structures with loop cables. The imperfection of the LSHCS is that cable clamps near the inside boundary are redundant. In this paper, the static behavior and dynamic characteristics of thirty-one schemes in five levels of deleting cable clamps are carried out with ANSYS software and Midas/Gen software. The results show that SE1/1, SE2/1, SE3/1, and SE4/1 are the best cable clamp deleting schemes for their respective levels. Displacements are the most sensitive to deleting cable clamps, the natural vibration period comes in second, and tensions are not sensitive with the growth rates of 6.09%, 5.11%, 15.97%, and 19.28% in the best scheme of each level. It is concluded that schemes involving the virtual rings of cable clamps closest to the inside boundary cause the smallest effect on static behavior and dynamic characteristics. Deleting the cable clamps affects the structural stiffness significantly, but the bearing capacity is not seriously affected. It turns out that removing redundant cable clamps in the dense part of the LSHCS is feasible.

A double-sided thin steel plate shear wall filled with rigid polyurethane foam (SWR) is proposed. A quasi-static monotonic loading test and quasi-static cycling loading test on shear behavior and the energy dissipation capacity of the SWR were carried out. Four kinds of test specimens, including the pure steel frames, the steel frame with double-sided thin steel plates, the SWR, and the SWR with an open hole, were tested. The results showed that compared with the pure steel frame, the erection of thin steel plates on both sides enhances the shear bearing capacity, initial shear stiffness, and energy consumption capacity. It turns out that the rigid foam polyurethane (RPUF) significantly increases the shear performance of the thin steel plate shear wall. The main reason for this is that the bond effect and support effect of the RPUF delay the out-of-plane buckling of thin steel plates and improve shear performance and energy dissipation capacity.

Space truss structures are commonly used in long-span roof structures. Recently, middle-hung scoreboards (MHS), a kind of large-scale display device flexibly suspended in the center of the roof, have been widely used in gymnasiums. However, the effect of the MHS on dynamic characteristics and earthquake response of space truss structures needs to be investigated. In this paper, the effect on the MHS under horizontal earthquake motion is studied. The simplified model, where the MHS is simplified to four fixed masses on a structure, and the flexibly suspended model are established with Abaqus software, and the earthquake response is analyzed by the time-history method with the dynamic explicit method. The influence laws of the wire extent and the MHS weight are discussed. Compared with the simplified model, the nodal acceleration and the axial force rise up to 2.123 times and 1.575 times, respectively, in the flexibly suspended model, indicating that the amplification effect of the MHS acts significantly under horizontal earthquake motion. It turns out that the earthquake response of a space truss structure could be underestimated if a simplified model is used. The crest acceleration of both top chord nodes and bottom chords nodes are greatly influenced by the MHS weight but little affected by the wire extent. The influence laws of the MHS weight and the wire extent on crest axial forces of structural members are very complicated. The central regions of both the top chords and the bottom chords are the most affected regions, and the boundary regions parallel to the direction of the earthquake motion are the least affected regions. It is suggested that the envelope value under the conditions of different wire extent and MHS weight are used for structural design.

To explore new approaches to severe plastic deformation and the ductility of a multicomponent magnesium–lithium alloy, an ultralight microduplex Mg-9.55Li-2.92Al-0.027Y-0.026Mn alloy was made by novel multidirectional forging and asymmetrical rolling, and the superplasticity behavior was investigated by optical microscope, hot tensile test, and modeling. The average grain size is 1.9 μm in this alloy after multidirectional forging and asymmetrical rolling. Remarkable grain refinement caused by such a forming, which turns the as-cast grain size of 144.68 μm into the as-rolled grain size of 1.9 μm, is achieved. The elongation to failure of 228.05% is obtained at 523 K and 1 × 10−2 s−1, which demonstrates the high strain rate quasi-superplasticity. The maximum elongation to failure of 287.12% was achieved in this alloy at 573 K and 5 × 10−4 s−1. It was found that strain-induced grain coarsening at 523 K is much weaker than the strain-induced grain coarsening at 573 K. Thus, the ductility of 228.05% is suitable for application in high strain rate superplastic forming. The stress exponent of 3 and the average activation energy for deformation of 50.06 kJ/mol indicate that the rate-controlling deformation mechanism is dislocation-glide controlled by pipe diffusion.

The center-hung scoreboard is a large electronic display device, that usually has a significant weight and is flexibly suspended from the roof of the gymnasium. The suspen-dome structure is one of the common roof structures of gymnasiums. In order to investigate the effect of the center-hung scoreboard on the natural vibration characteristics and seismic response, including acceleration, displacement, and strain, of the suspen-dome structure and considering that the dynamic behavior of the structure under seismic action can be realistically reflected, a shaking table test was carried out based on the suspen-dome structure of the Gymnasium of the Lanzhou Olympic Sports Center. Firstly, according to the size of the shaking table, a dynamic scale model with a geometric similarity ratio of 1:20 was established. After that, the white noise excitation test and numerical modal analysis were conducted on the models with and without the center-hung scoreboard to compare the two modes’ natural vibration characteristics. Furthermore, the earthquake simulation test was carried out on the models with and without a center-hung scoreboard, and their various seismic responses, including acceleration, displacement, and strain, were compared and analyzed. Finally, the acceleration response and displacement response of the center-hung scoreboard were investigated. The results show that the higher-order natural frequencies of the suspen-dome structure will increase when the center-hung scoreboard is suspended from the roof, and the swing of the center-hung scoreboard will be excited first in the low-order mode. In addition, the various seismic responses, including acceleration, displacement, and strain, of the model with the center-hung scoreboard are all increased compared to the model without the center-hung scoreboard. Meanwhile, the influence of the center-hung scoreboard on the seismic response of the suspen-dome structure decreases from the inner ring to the outer ring of the structure. Moreover, under the action of an earthquake, the acceleration response and displacement response of the center-hung scoreboard are both extremely high. Considering the center-hung scoreboard in the analysis and design stage of the suspen-dome structure is necessary.

Understanding the composition, function and regulation of complex cellular systems requires tools that quantify the expression of multiple proteins at their native cellular context. Here, we report a highly sensitive and accurate protein in situ profiling approach using off-the-shelf antibodies and cleavable fluorescent tyramide (CFT). In each cycle of this method, protein targets are stained with horseradish peroxidase (HRP) conjugated antibodies and CFT. Subsequently, the fluorophores are efficiently cleaved by mild chemical reagents, which simultaneously deactivate HRP. Through reiterative cycles of protein staining, fluorescence imaging, fluorophore cleavage, and HRP deactivation, multiplexed protein quantification in single cells in situ can be achieved. We designed and synthesized the high-performance CFT, and demonstrated that over 95% of the staining signals can be erased by mild chemical reagents while preserving the integrity of the epitopes on protein targets. Applying this method, we explored the protein expression heterogeneity and correlation in a group of genetically identical cells. With the high signal removal efficiency, this approach also enables us to accurately profile proteins in formalin-fixed paraffin-embedded (FFPE) tissues in the order of low to high and also high to low expression levels.

The ability to comprehensively profile nucleic acids in individual cells in their natural spatial contexts is essential to advance our understanding of biology and medicine. Here, we report a novel method for spatial transcriptomics and genomics analysis. In this method, every nucleic acid molecule is detected as a fluorescent spot at its natural cellular location throughout the cycles of consecutive fluorescence in situ hybridization (C-FISH). In each C-FISH cycle, fluorescent oligonucleotide probes hybridize to the probes applied in the previous cycle, and also introduce the binding sites for the next cycle probes. With reiterative cycles of hybridization, imaging and photobleaching, the identities of the varied nucleic acids are determined by their unique color sequences. To demonstrate the feasibility of this method, we show that transcripts or genomic loci in single cells can be unambiguously quantified with 2 fluorophores and 16 C-FISH cycles or with 3 fluorophores and 9 C-FISH cycles. Without any error correction, the error rates obtained using the raw data are close to zero. These results indicate that C-FISH potentially enables tens of thousands (216 = 65,536 or 39 = 19,683) of different transcripts or genomic loci to be precisely profiled in individual cells in situ.

A cut-edge detection method based on machine vision was developed for obtaining the navigation path of a combine harvester. First, the Cr component in the YCbCr color model was selected as the grayscale feature factor. Then, by detecting the end of the crop row, judging the target demarcation and getting the feature points, the region of interest (ROI) was automatically gained. Subsequently, the vertical projection was applied to reduce the noise. All the points in the ROI were calculated, and a dividing point was found in each row. The hierarchical clustering method was used to extract the outliers. At last, the polynomial fitting method was used to acquire the straight or curved cut-edge. The results gained from the samples showed that the average error for locating the cut-edge was 2.84 cm. The method was capable of providing support for the automatic navigation of a combine harvester.

The ability to perform highly sensitive and multiplexed in-situ protein analysis is crucial to advance our understanding of normal physiology and disease pathogenesis. To achieve this goal, we here develop an approach using cleavable biotin-conjugated antibodies and cleavable fluorescent streptavidin (CFS). In this approach, protein targets are first recognized by the cleavable biotin-labeled antibodies. Subsequently, CFS is applied to stain the protein targets. Though layer-by-layer signal amplification using cleavable biotin-conjugated orthogonal antibodies and CSF, the protein detection sensitivity can be enhanced at least 10-fold, compared with the current in-situ proteomics methods. After imaging, the fluorophore and the biotin unbound to streptavidin are removed by chemical cleavage. The leftover streptavidin is blocked by biotin. Upon reiterative analysis cycles, a large number of different proteins with a wide range of expression levels can be profiled in individual cells at the optical resolution. Applying this approach, we have demonstrated that multiple proteins are unambiguously detected in the same set of cells, regardless of the protein analysis order. We have also shown that this method can be successfully applied to quantify proteins in formalin-fixed paraffin-embedded (FFPE) tissues.

Owing to its unique structure and properties, the glucose dendrimer phytoglycogen is gaining interest for medical and biotechnology applications. Although many maize variants are available from commercial and academic breeding programs, most applications rely on phytoglycogen extracted from the common maize variant, sugary1. Here we characterized the solubility, hydrodynamic diameter, water-binding properties, protein contaminant concentration, and cytotoxicity of phytoglycogens from different maize sources, A632su1, A619su1, Wesu7, and Ia453su1, harboring various sugary1 mutants. A619su1-SW phytoglycogen was cytotoxic while A632su1-SW phytoglycogen was not. A632su1-Pu phytoglycogen promoted cell growth, whereas extracts from A632su1-NE, A632su1-NC, and A632su1-CM were cytotoxic. Phytoglycogen extracted from Wesu7su1-NE using ethanol precipitation was cytotoxic. Acid-treatment improved Wesu7 phytoglycogen cytocompatibility. Protease-treated Wesu7 extracts promoted cell growth. Phytoglycogen extracted from Ia453su1 21 days after pollination (“Ia435su1 21DAP”) was cytotoxic, whereas phytoglycogen extracted at 40 days (“Ia435su1 40DAP”) was not. In general, size and solubility had no correlation with cytocompatibility, whereas protein contaminant concentration and water-binding properties did. A632su1-CM had the highest protein contamination among A632 mutants, consistent with its higher cytotoxicity. Likewise, Ia435su1 21DAP phytoglycogen had higher protein contamination than Ia435su1 40DAP. Conversely, protease-treated Wesu7 extracts had lower protein contamination than the other Wesu7 extracts. A632su1-NE, A632su1-NC, and A632su1-CM had similar water-binding properties which differed from those of A632su1-Pu and A632su1-SW. Likewise, water binding differed between Ia435su1 21DAP and Ia435su1 40DAP. Collectively, these data demonstrate that maize phytoglycogen extracts are not uniformly cytocompatible. Rather, maize variant, plant genotype, protein contaminants, and water-binding properties are determinants of phytoglycogen cytotoxicity.

Throughout nature, self-assembly gives rise to functional supramolecular biomaterials that can perform complex tasks with extraordinary efficiency and specificity. Inspired by these examples, self-assembly is increasingly used to fabricate synthetic supramolecular biomaterials for diverse applications in biomedicine and biotechnology. Peptides are particularly attractive as building blocks for these materials because they are based on naturally derived amino acids that are biocompatible and biodegradable; they can be synthesized using scalable and cost-effective methods, and their sequence can be tailored to encode formation of diverse architectures. To endow synthetic supramolecular biomaterials with functional capabilities, it is now commonplace to conjugate self-assembling building blocks to molecules having a desired functional property, such as selective recognition of a cell surface receptor or soluble protein, antigenicity, or enzymatic activity. This review surveys recent advances in using self-assembling peptides as handles to incorporate biologically active molecules into supramolecular biomaterials. Particular emphasis is placed on examples of functional nanofibers, nanovesicles, and other nano-scale structures that are fabricated by linking self-assembling peptides to proteins and carbohydrates. Collectively, this review highlights the enormous potential of these approaches to create supramolecular biomaterials with sophisticated functional capabilities that can be finely tuned to meet the needs of downstream applications.