SPICER: Self-supervised learning for MRI with automatic coil sensitivity estimation and reconstruction.

PURPOSE: To introduce a novel deep model-based architecture (DMBA), SPICER, that uses pairs of noisy and undersampled k-space measurements of the same object to jointly train a model for MRI reconstruction and automatic coil sensitivity estimation. METHODS: SPICER consists of two modules to simultaneously reconstructs accurate MR images and estimates high-quality coil sensitivity maps (CSMs). The first module, CSM estimation module, uses a convolutional neural network (CNN) to estimate CSMs from the raw measurements. The second module, DMBA-based MRI reconstruction module, forms reconstructed images from the input measurements and the estimated CSMs using both the physical measurement model and learned CNN prior. With the benefit of our self-supervised learning strategy, SPICER can be efficiently trained without any fully sampled reference data. RESULTS: We validate SPICER on both open-access datasets and experimentally collected data, showing that it can achieve state-of-the-art performance in highly accelerated data acquisition settings (up to 10 × $$ 10\times $$ ). Our results also highlight the importance of different modules of SPICER-including the DMBA, the CSM estimation, and the SPICER training loss-on the final performance of the method. Moreover, SPICER can estimate better CSMs than pre-estimation methods especially when the ACS data is limited. CONCLUSION: Despite being trained on noisy undersampled data, SPICER can reconstruct high-quality images and CSMs in highly undersampled settings, which outperforms other self-supervised learning methods and matches the performance of the well-known E2E-VarNet trained on fully sampled ground-truth data.

Phosphorescent acyclic cucurbituril solid supramolecular multicolour delayed fluorescence behaviour.

Organic photoluminescent macrocyclic hosts have been widely advanced in many fields. Phosphorescent hosts with the ability to bind organic guests have rarely been reported. Herein, acyclic cucurbituril modified with four carboxylic acids (ACB-COOH) is mined to present uncommon purely organic room-temperature phosphorescence (RTP) at 510 nm with a lifetime of 1.86 µs. Its RTP properties are significantly promoted with an extended lifetime up to 2.12 s and considerable quantum yield of 6.29% after assembly with a polyvinyl alcohol (PVA) matrix. By virtue of the intrinsic self-crimping configuration of ACB-COOH, organic guests, including fluorescence dyes (Rhodamine B (RhB) and Pyronin Y (PyY)) and a drug molecule (morphine (Mor)), could be fully encapsulated by ACB-COOH to attain energy transfer involving phosphorescent acyclic cucurbituril. Ultimately, as-prepared systems are successfully exploited to establish multicolor afterglow materials and visible sensing of morphine. As an expansion of phosphorescent acyclic cucurbituril, the host afterglow color can be readily regulated by attaching different aromatic sidewalls. This study develops the fabrication strategies and application scope of a supramolecular phosphorescent host and opens up a new direction for the manufacture of intelligent long-lived luminescent materials.

Intra-nanoparticle plasmonic nanogap based spatial-confinement SERS analysis of polypeptides.

Sensing and characterizing water-soluble polypeptides are essential in various biological applications. However, detecting polypeptides using Surface-Enhanced Raman Scattering (SERS) remains a challenge due to the dominance of aromatic amino acid residues and backbones in the signal, which hinders the detection of non-aromatic amino acid residues. Herein, intra-nanoparticle plasmonic nanogap were designed by etching the Ag shell in Au@AgNPs (i.e., obtaining AuAg cores) with chlorauric acid under mild conditions, at the same time forming the outermost Au shell and the void between the AuAg cores and the Au shell (AuAg@void@Au). By varying the Ag to added chloroauric acid molar ratios, we pioneered a simple, controllable, and general synthetic strategy to form interlayer-free nanoparticles with tunable Au shell thickness, achieving precise regulation of electric field enhancement within the intra-nanogap. As validation, two polypeptide molecules, bacitracin and insulin B, were successfully synchronously encapsulated and spatial-confined in the intra-nanogap for sensing. Compared with concentrated 50 nm AuNPs and Au@AgNPs as SERS substrates, our simultaneous detection method improved the sensitivity of the assay while benefiting to obtain more comprehensive characteristic peaks of polypeptides. The synthetic strategy of confining analytes while fabricating plasmonic nanostructures enables the diffusion of target molecules into the nanogap in a highly specific and sensitive manner, providing the majority of the functionality required to achieve peptide detection or sequencing without the hassle of labeling.

Machine learning-driven 3D plasmonic cellulose sensor for in situ rapid SERS detection of bisphenol compounds in water sample.

Rapid component separation and accurate identification of bisphenols compounds (BPs) in real water sample remain an attractive challenge due to the trace amounts and structural similarities of BPs, and complexity of real samples. Here, we designed and synthesized chemically modified cellulose p-toluenesulfonate (CTSA) to encapsulate octadecylamine-modified gold nanoparticles (Au-ODA), obtaining 3D plasmonic cellulose (Au@CTSA). Simultaneously, by virtue of the high surface area in the 3D network of CTSA and the solvent volatile deposition, BPs in water were in situ extracted and concentrated in Au@CTSA microspheres. Since the 3D network of Au@CTSA supports the formation of "hotspots", the number of "hotspots" available is greatly improved, enabling excellent SERS detection of BPs. Based on the collected SERS spectra, machine learning was utilized to analyze the overall profile of BPs, which eliminated the subjective judgment of the concentration by the Au@CTSA sensor using a single characteristic peak. In this way, the accuracy of identification of BPs was significantly improved. The machine learning-driven Au@CTSA sensor realized the detection of traces bisphenol A (BPA), bisphenol S (BPS), and bisphenol F (BPF) in water sample, pushing quantitative detection of different concentrations of BPs and contributing facile indicators for water quality monitoring.

Quinine-Fabricated Surface-Enhanced Raman Spectroscopy Chiral Sensing Platform Enables Simultaneous Enantioselective Discrimination and Identification of Aliphatic Amino Acids.

Due to low optical activity and structural simplicity, synchronous chiral discrimination and identification of aliphatic amino acids (AAs) are still challenging yet demanding. Herein, we developed a novel surface-enhanced Raman spectroscopy (SERS)-based chiral discrimination-sensing platform for aliphatic AAs, in which l- and d-enantiomers are able to discriminately bind with quinine to generate distinct differences in the SERS vibrational modes. Meanwhile, the plasmonic sub-nanometer gaps supported by the rigid quinine enable the maximization of SERS signal enhancement to reveal feeble signals, allowing for simultaneously acquiring the structural specificity and enantioselectivity of aliphatic amino acid enantiomers in a single SERS spectrum. Different kinds of chiral aliphatic AAs were successfully identified by using this sensing platform, demonstrating its potential and practicality in recognizing chiral aliphatic molecules.

Deep Learning-Based Multicapturer SERS Platform on Plasmonic Nanocube Metasurfaces for Multiplex Detection of Organophosphorus Pesticides in Environmental Water.

In situ rapid detection of contaminants in environmental water is crucial for protecting the ecological environment and human health; however, it is always hindered by the complexity of sample matrices, trace content, and unknown species. Herein, we demonstrate a deep learning-based multicapturer surface-enhanced Raman scattering (SERS) platform on plasmonic nanocube metasurfaces for multiplex determination of organophosphorus pesticides (OPPs) residues. Poly(vinylpyrrolidone), 4-mercaptobenzoic acid, and l-cysteine are assembled on Ag nanocubes (AgNCs) and act as capturers to chemically define OPPs. Meanwhile, the OPPs-captured AgNCs efficiently close the interparticle distance and generate plasmonic metasurfaces, guaranteeing ultrasensitive and reproducible SERS analysis. Furthermore, by strategically combining all capturer-OPP SERS spectra, comprehensive "combined-SERS spectra" are reconstructed to enhance spectral variations of each OPP. Based on the combined-SERS spectra, a deep learning model is trained to predict OPPs, which significantly improve the qualitative and quantitative analysis accuracy. We successfully identified multiple OPPs in farmland, river, and fishpond water using this strategy. The whole detection procedure requires only 30 min, including sampling, SERS measurements, and deep learning analyses. This combination of a multicapturer SERS platform with the deep learning algorithm creates a rapid and reliable analytical strategy for multiplex detection of target molecules, providing a potential paradigm shift for environment-related research.

Generation of Tunable Ultrastrong White-Light Emission by Activation of a Solid Supramolecule through Bromonaphthylpyridinium Polymerization.

Herein, we reported solid supramolecular bromonaphthylpyridinium polymers (P-BrNp), which exhibit tunable phosphorescence emission in the amorphous state enabled by sulfobutylether-ß-cyclodextrin (SBE-ß-CD) and diarylethene derivatives. The monomer BrNp gave single fluorescence emission at 490 nm, while an apparent room-temperature phosphorescence (RTP) at 550 nm emerged for P-BrNp copolymers with various feed ratios. Through fluorescence-phosphorescence dual emission, P-BrNp-0.1 displayed an ultrahigh white-light emission quantum yield of 83.9 %. Moreover, the subsequent assembly with SBE-ß-CD further enhanced the phosphorescent quantum yield of P-BrNp-0.1 from 64.1 % to 71.3 %, accompanied by the conversion of photoluminescence emission from white to yellow. Diarylethene monomers were introduced as photoswitches to realize reversible RTP emission, which can be used in switchable data encryption and multifunctional writing ink.

A dual-channel probe based on copper ion-mediated metal organic framework composite for colorimetric and ratiometric fluorescence monitoring of glyphosate degradation in soil and water.

A dual-channel probe was developed, based on a novel composite metal organic frameworks (ZnMOF-74@Al-MOF) for glyphosate determination through ratio fluorescence and colorimetric methods. The prepared probe can not only recognize and combine glyphosate by introducing copper ion into the MOF, but also possess peroxidase-like catalytic activity. The recognition of target glyphosate brought about changes relative to its concentration on fluorescence intensity and ultraviolet absorption. And, the high specific surface area and porosity of porphyrin MOF provides the developed probe with more response opportunities to afford a better detection performance for glyphosate. Under optimum conditions, the copper ion-mediated method exhibited good detection performance for glyphosate with low detection limits (0.070 and 0.092 µg mL-1 for fluorescence and colorimetric techniques, respectively). Furthermore, the possible mechanisms of the fluorescence quenching and the peroxidase-like catalytic of the probe were also explored. This dual-channel method was applied to monitor glyphosate degradation in environmental samples and satisfactory results were obtained.

Noncovalent Polymerization-Activated Ultrastrong Near-Infrared Room-Temperature Phosphorescence Energy Transfer Assembly in Aqueous Solution.

Noncovalent macrocycle-confined supramolecular purely organic room-temperature phosphorescence (RTP) is a current research hotspot. Herein, a high-efficiency noncovalent polymerization-activated near-infrared (NIR)-emissive RTP-harvesting system in aqueous solution based on the stepwise confinement of cucurbit[7]uril (CB[7]) and ß-cyclodextrin-grafted hyaluronic acid (HACD), is reported. Compared with the dodecyl-chain-bridged 6-bromoisoquinoline derivative (G), the dumbbell-shaped assembly G⊂CB[7] presents an appeared complexation-induced RTP signal at 540 nm via the first confinement of CB[7]. Subsequently, benefitting from the stepwise confinement encapsulation of the ß-cyclodextrin cavity, the subsequent noncovalent polymerization of the binary G⊂CB[7] assembly enabled by HACD can contribute to the further-enhanced RTP emission intensity approximately eight times in addition to an increased lifetime from 59.0 µs to 0.581 ms. Moreover, upon doping a small amount of two types of organic dyes, Nile blue or tetrakis(4-sulfophenyl)porphyrin as an acceptor into the supramolecular confinement assembly G⊂CB[7] @ HACD, efficient RTP energy transfer occurs accompanied by a long-lived NIR-emitting performance (680 and 710 nm) with a high donor/acceptor ratio. Intriguingly, the prepared RTP-harvesting system is successfully applied for targeted NIR imaging of living tumor cells by utilizing the targeting ability of hyaluronic acid, which provides a new strategy to create advanced water-soluble NIR phosphorescent materials.

Peridynamic Simulation of Dynamic Fracture Process of Engineered Cementitious Composites (ECC) with Different Curing Ages.

The mechanical properties of engineered cementitious composites (ECC) are time-dependent due to the cement hydration process. The mechanical behavior of ECC is not only related to the matrix material properties, but also to the fiber/matrix interface properties. In this study, the modeling of fiber and fiber/matrix interactions is accomplished by using a semi-discrete model in the framework of peridynamics (PD), and the time-varying laws of cement matrix and fiber/matrix interface bonding properties with curing age are also considered. The strain-softening behavior of the cement matrix is represented by introducing a correction factor to modify the pairwise force function in PD theory. The fracture damage of ECC plate from 3 to 28 days was numerically simulated by using the improved PD model to visualize the process of damage fracture under dynamic loading. The shorter the hydration time, the lower the corresponding elastic modulus, and the smaller the number of cracks generated. The dynamic fracture process of early-age ECC is analyzed to understand the crack development pattern, which provides reference for guiding structural design and engineering practice.

A Highly Efficient Phosphorescence/Fluorescence Supramolecular Switch Based on a Bromoisoquinoline Cascaded Assembly in Aqueous Solution.

Despite ongoing research into photocontrolled supramolecular switches, reversible photoswitching between room-temperature phosphorescence (RTP) and delayed fluorescence is rare in the aqueous phase. Herein, an efficient RTP-fluorescence switch based on a cascaded supramolecular assembly is reported, which is constructed using a 6-bromoisoquinoline derivative (G3 ), cucurbit[7]uril (CB[7]), sulfonatocalix[4]arene (SC4A4), and a photochromic spiropyran (SP) derivative. Benefiting from the confinement effect of CB[7], initial complexation with CB[7] arouses an emerging RTP signal at 540 nm for G3 . This structure subsequently coassembles with amphiphilic SC4A4 to form tight spherical nanoparticles, thereby further facilitating RTP emission (≈12 times) in addition to a prolonged lifetime (i.e., 1.80 ms c.f., 50.1 µs). Interestingly, following cascaded assembly with a photocontrolled energy acceptor (i.e., SP), the efficient light-driven RTP energy transfer occurs when SP is transformed to its fluorescent merocyanine (MC) state. Ultimately, this endows the final system with an excellent RTP-fluorescence photoswitching property accompanied by multicolor tunable long-lived emission. Moreover, this switching process can be reversibly modulated over multiple cycles under alternating UV and visible photoirradiation. Finally, the prepared switch is successfully applied to photocontrolled multicolor cell labeling to offer a new approach for the design and fabrication of novel advanced light-responsive RTP materials in aqueous environments.

A Dual-Modal Imaging Method Combining Ultrasound and Electromagnetism for Simultaneous Measurement of Tissue Elasticity and Electrical Conductivity.

The mechanical and electrical properties of soft tissues are relative to soft tissues' pathological state. Modern medical imaging devices have shown a trend to multi-modal imaging, which will provide complementary functional information to improve the accuracy of disease diagnosis. However, no method or system can simultaneously measure the mechanical and electrical properties of the soft tissue. In this study, we proposed a novel dual-modal imaging method integrated by shear wave elasticity imaging (SWEI) and Magneto-acousto-electrical tomography (MAET) to measure soft tissue's elasticity and conductivity simultaneously. A dual-modal imaging system based on a linear array transducer is built, and the imaging performances of MAET and SWEI were respectively evaluated by phantoms experiment and in vitro experiment. Conductivity phantom experiments show that the MAET in this dual-modal system can image conductivity gradient as low as 0.4 S/m. The phantom experiments show that the reconstructed 2-D elasticity maps of the phantoms with inclusions with a diameter larger than 5 mm are relatively accurate. In vitro experiments show that the elasticity parameter can significantly distinguish the changes in tissue before and after heating. This study first proposes a method that can simultaneously obtain tissue elasticity and electrical conductivity to the best of our knowledge. Although this paper just carried out the proof of concept experiments of the new method, it demonstrates great potential for disease diagnosis in the future.

Simultaneous In Situ Extraction and Self-Assembly of Plasmonic Colloidal Gold Superparticles for SERS Detection of Organochlorine Pesticides in Water.

Rapid component separation and reliable surface-enhanced Raman scattering (SERS) detection of organochlorine pesticide (OCP) residues in real water samples remain major challenges because of sample complexity, trace content, and low molecular affinity for a metal surface. Here, we report a novel strategy of simultaneous in situ extraction and fabrication of plasmonic colloidal gold superparticles (AuSPs) to perform rapid SERS detection of OCPs in environmental water. In this protocol, multiple components of OCPs in complex water were facilely diffused into dichloromethane (DCM) microdroplets and specifically bound to octadecylamine-modified gold nanoparticles (Au-ODAs), affording the SERS substrate through self-assembly of the OCP-trapped Au-ODA into AuSPs with the evaporation of DCM. SERS signals of the specifically prepared Au-ODA could be used as an internal standard to calibrate the absolute signal of OCPs, and multiplex detection could be achieved depending on their molecularly narrow Raman peaks. As for simultaneously sensing four kinds of OCPs (4,4'-DDT, α-endosulfan, tetradifon, and chlordane) in water, the established method showed strong anti-interference ability and comparable quantification ranges with a low limit of detection (LOD). The recoveries ranged from 90.20 to 109.4% for OCPs in farmland, river, and fishpond water, indicating that the established AuSP-based platform is reliable and applicable to the detection of OCPs in real water samples.

Human neutralizing Fab molecules against severe acute respiratory syndrome coronavirus generated by phage display.

Human recombinant Fab fragments specific for the spike protein of severe acute respiratory syndrome coronavirus (SARS-CoV) were screened from a human Fab library, which was generated from RNAs from peripheral lymphocytes of convalescent SARS patients. Among 50 randomly picked clones, 12 Fabs specially reacted with S protein by an enzyme-linked immunosorbent assay. The microneutralizing test showed that one clone, designated M1A, had neutralizing activity on Vero E6 cells against SARS-CoV. DNA sequence analysis indicated that the light- and heavy-chain genes of M1A Fab belong to the kappa2a and 4f families, respectively. A neutralizing test on purified M1A demonstrated that 0.5 mg/ml of M1A completely inhibited SARS-CoV activity, with an absence of cytopathic effect for 7 days. Real-time fluorescence reverse transcription-PCR also proved the neutralizing capacity of M1A. These data showed that the number of virus copies was significantly reduced in the M1A-treated group, suggesting an important role for M1A in passive immunoprophylaxis against the SARS virus.