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Resolving the spatial distribution of RNA and protein in tissues at subcellular resolution is a challenge in the field of spatial biology. We describe spatial molecular imaging, a system that measures RNAs and proteins in intact biological samples at subcellular resolution by performing multiple cycles of nucleic acid hybridization of fluorescent molecular barcodes. We demonstrate that spatial molecular imaging has high sensitivity (one or two copies per cell) and very low error rate (0.0092 false calls per cell) and background (~0.04 counts per cell). The imaging system generates three-dimensional, super-resolution localization of analytes at ~2 million cells per sample. Cell segmentation is morphology based using antibodies, compatible with formalin-fixed, paraffin-embedded samples. We measured multiomic data (980 RNAs and 108 proteins) at subcellular resolution in formalin-fixed, paraffin-embedded tissues (nonsmall cell lung and breast cancer) and identified18 distinct cell types, ten unique tumor microenvironments and 100 pairwise ligand-receptor interactions. Data on800,000 single cells and ~260 million transcripts can be accessed at http://nanostring.com/CosMx-dataset .

Recent technological advancements have enabled spatially resolved transcriptomic profiling but at multi-cellular resolution. The task of cell type deconvolution has been introduced to disentangle discrete cell types from such multi-cellular spots. However, existing datasets for cell type deconvolution are limited in scale, predominantly encompassing data on mice, and are not designed for human immuno-oncology. In order to overcome these limitations and promote comprehensive investigation of cell type deconvolution for human immuno-oncology, we introduce a large-scale spatial transcriptomic dataset named SpatialCTD, encompassing 1.8 million cells from the human tumor microenvironment across the lung, kidney, and liver. Distinct from existing approaches that primarily depend on single-cell RNA sequencing data as a reference without incorporating spatial information, we introduce Graph Neural Network-based method (i.e., GNNDeconvolver) that effectively utilize the spatial information from reference samples, and extensive experiments show that GNNDeconvolveroften outperforms existing state-of-the-art methods by a substantial margin, without requiring single-cell RNA-seq data. To enable comprehensive evaluations on spatial transcriptomics data from flexible protocols, we provide an online tool capable of converting spatial transcriptomic data from other platforms (e.g., 10x Visium, MERFISH and sci-Space) into pseudo spots, featuring adjustable spot size. The SpatialCTD dataset and GNNDeconvolverimplementation are available athttps://github.com/OmicsML/SpatialCTD, and the online converter tool can be accessed athttps://omicsml.github.io/SpatialCTD/.

Cancer research across drug development, molecular biomarkers, and patient response depends on understanding biology that is dependent on complex interactions between malignant, immune, and stromal cells. To survive clearance mechanisms, a tumor can rely on a myriad of escape strategies, and the microenvironment is architected around the current path of escape. To enable a more comprehensive picture of tumor biology, we have developed the CosMx™ Spatial Molecular Imager (SMI) technology to capture a snapshot of thousands of RNA species resolved subcellularly from a single, standard histopathology slide. Building upon the previously released panels, this study tests a new 6,000-plex panel, the highest RNA plex measured in situ within human tissue, allowing the imputation of a spatial whole transcriptome in the tissue. We performed an ultra-high-plex RNA assay to detect 6,000 targets simultaneously in situ on an FFPE human liver cancer tissue (~1 cm2 area) using the CosMx SMI. This RNA panel covers broad biological areas with special emphasis on oncology, immunology, and signal transduction, such that all cancer researchers can benefit from the direct detection of targets of interest (sans imputation) in intact tissue. Analysis algorithms were developed to allow robust assessments of cell types, cell states, cell-cell interactions, and pathway activation. Imputation based on reference profiles from HCA, TCGA, and other public repositories allows estimation of non-measured transcripts at a ratio of approximately 1:3, compared to the approximate 1:20-1:70 imputations performed previously for spatial data.Thousands of transcripts were simultaneously detected with high sensitivity and specificity on the FFPE liver cancer tissue section at single-cell subcellular resolution. We were able to accurately map known reference profiles from scRNA-seq into this sample while identifying cancer-specific malignant, immune, and stromal cells in this tissue sample using this ultra-high plex RNA panel. In addition, we constructed sample-specific spatial neighborhoods, defined by cell types, cell states, and nearly unlimited sets of biological pathways through the imputed whole transcriptome. Finally, we measured >1,000 ligand-receptor interactions between key cell types of adjacent cells in the tissue, identifying mechanisms for tumor-mediated escape as well as reactive re-architecting of the native stroma which defines the trajectory of cancer’s evolution. Single-cell spatial measurements of gene expression at 6,000 plex from a single FFPE slide has the potential to transform our understanding of tumor biology and facilitate the next advances in cancer research by extracting the highest data density possible from rare specimens collected during patient treatment. Citation Format: Shanshan He, Michael Patrick, Jason W. Reeves, Patrick Danaher, Julian Preciado, Joseph Phan, Erin Piazza, Zachary Reitz, Lidan Wu, Rustem Khafizov, Haiyan Zhai, Michael Rhodes, David Ruff, Joseph Beechem. Path to the holy grail of spatial biology: Spatial single-cell whole transcriptomes using 6000-plex spatial molecular imaging on FFPE tissue. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5637.

In the present work, a kind of efficient heterogeneous catalyst was synthesized from amine-functionalized hypercrosslinked bottlebrush copolymers of microporous network nanotubes (amine-MNNs) and Na2WO4. The synthesized tungstate-supported microporous network nanotubes (TMNNs) catalyst was shown to be highly active in the selective H2O2 oxidation of sulfides to sulfoxides or sulfones under mild conditions due to the high specific surface area (800 m2 g−1) and firm structure of the nanotubes. The catalyst was found to be very stable and could be recycled at least 8 times without any significant loss of activity. These results present a new opportunity for the development of efficient green organic catalytic materials with high activity.

Amyloid-β (Aβ) deposition and neurotoxicity play an important role in Alzheimer's disease (AD). Notably, the nonnegligible role of endogenous heparan sulfate (HS) in the release, uptake and misfolding of Aβ sheds light on the discovery of HS as an effective drug for AD. In this work, the effects of HS from porcine mucosa (PMHS) on Aβ

The Spatial Molecular Imaging platform (CosMxTM SMI, NanoString Technologies, Seattle, WA) utilizes high-plex in-situ imaging chemistry for both RNA and protein detection. This automated instrument provides 1000’s of plex, at high sensitivity (1 to 2 copies/cell), very low error rate (0.0092 false calls/cell) and background (∼0.04 counts/cell). The imaging system generates three-dimensional super-resolution localization of analytes at ∼2 million cells per sample, four samples per run. Cell segmentation is morphology-based using antibodies, compatible with FFPE samples. Multiomic data (980 RNAs, 108 proteins) were measured at subcellular resolution using FFPE tissues (non-small cell lung (NSCLC) and breast cancer) and allowed identification of over 18 distinct cell types, 10 unique tumor microenvironments, and 100 pairwise ligand-receptor interactions. Over 800,000 single cells and ∼260 million transcripts data are released into the public domain allowing extended data analysis by the entire spatial biology research community.

Multidrug resistant organisms are a serious threat to human health1,2. Fast, accurate antibiotic susceptibility testing (AST) is a critical need in addressing escalating antibiotic resistance, since delays in identifying multidrug resistant organisms increase mortality3,4 and use of broad-spectrum antibiotics, further selecting for resistant organisms. Yet current growth-based AST assays, such as broth microdilution5, require several days before informing key clinical decisions. Rapid AST would transform the care of patients with infection while ensuring that our antibiotic arsenal is deployed as efficiently as possible. Growth-based assays are fundamentally constrained in speed by doubling time of the pathogen, and genotypic assays are limited by the ever-growing diversity and complexity of bacterial antibiotic resistance mechanisms. Here we describe a rapid assay for combined genotypic and phenotypic AST through RNA detection, GoPhAST-R, that classifies strains with 94–99% accuracy by coupling machine learning analysis of early antibiotic-induced transcriptional changes with simultaneous detection of key genetic resistance determinants to increase accuracy of resistance detection, facilitate molecular epidemiology and enable early detection of emerging resistance mechanisms. This two-pronged approach provides phenotypic AST 24–36 h faster than standard workflows, with

Rapid bacterial identification remains a critical challenge in infectious disease diagnostics. We developed a novel molecular approach to detect and identify a wide diversity of bacterial pathogens in a single, simple assay, exploiting the conservation, abundance, and rich phylogenetic content of ribosomal RNA in a rapid fluorescent hybridization assay that requires no amplification or enzymology. Of 117 isolates from 64 species across 4 phyla, this assay identified bacteria with >89% accuracy at the species level and 100% accuracy at the family level, enabling all critical clinical distinctions. In pilot studies on primary clinical specimens, including sputum, blood cultures, and pus, bacteria from 5 different phyla were identified.

Dysarthria is a manifestation of disruption in the neuromuscular physiology resulting in uneven, slow, slurred, harsh, or quiet speech. Despite the remarkable progress of automatic speech recognition (ASR), it poses great challenges in developing stable ASR for dysarthric individuals due to the high intra- and inter-speaker variations and data deficiency. In this paper, we propose a contrastive learning framework for robust dysarthric speech recognition (DSR) by capturing the dysarthric speech variability. Several speech data augmentation strategies are explored to form two branches of the framework, meanwhile alleviating the scarcity of dysarthria data. We also develop an efficient projection head acting on a sequence of learned hidden representations for defining contrastive loss. Experiment results on DSR demonstrate that the model is better than or comparable to the supervised baseline.

Alzheimer's disease (AD) is a neurodegenerative disease characterized by memory loss and cognitive impairments. Amyloid-β (Aβ) deposition and neurotoxicity play important roles in AD. It has been widely reported that heparan sulfate (HS) proteoglycans play a nonnegligible role in the release, uptake and misfolding of Aβ, resulting in the discovery of HS as a therapeutic drug for AD. In this manuscript, HS from porcine mucosa could promote Aβ fibrosis and improve the cognitive defects of APPswe/PS1ΔE9 mice. Furthermore, HS enhanced the phagocytosis of neutrophils to clear Aβ

Our previous study found that low molecular weight chondroitin sulfate (LMWCS) had neuroprotective effects against the toxicity of amyloid-β (Aβ) peptides both in vitro and in vivo, and we speculated that the effects might be related with its anti-oxidative activities. In this study, the anti-Alzheimer's disease (AD) activity of LMWCS was further studied in 5XFAD transgenic mice. After 4-month gavage, the levels of Aβ1-42 level, amyloid precursor protein (APP) and presenilin 1 (PS1) were significantly decreased in the brains of 5XFAD mice, indicating the alteration of APP metabolism by LMWCS. Besides, LMWCS inhibited the secretions of pro-inflammatory cytokines, including interleukin-1β (IL-1β), tumor necrosis factor-α (TNF-α) and IL-6. Furthermore, the suppression of neuroinflammation by LMWCS was supported by the decreased expressions of glial fibrillary acidic protein (GFAP) and toll-like receptor 2 (TLR2) in the brains. LMWCS also reduced the production of reactive oxygen species (ROS) and the level of phospho-tau (Ser404) in the brains. Nevertheless, the changes in the behavior tests were moderate. In conclusion, LMWCS administration ameliorated APP metabolism, neuroinflammation, ROS production and tau protein abnormality in the brains of 5XFAD mice, displaying the potential to improve the pathological changes of AD mouse brain. LMWCS could be considered as a promising anti-AD drug candidate, nonetheless, the therapy regimen need to be optimized to improve its pharmacotherapy efficacy.

In the present paper, the authors investigated the adsorption of cadmium on magnetic Levextrel resin containing about 352 mg g−1 Cyanex 272 (C272) as adsorbent. Magnetic Levextrel resin (mPst-DVB-C272) was synthesized through adding Cyanex 272 and oleic acid-coated magnetite nanoparticles directly to the mixture of styrene (st) and divinylbenzene (DVB) monomers during the bead polymerization. It is a new method for preparing magnetic Levextrel resins with less organic solvents and less steps MPst-DVB-C272 was characterized with scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FT-IR), thermal gravity (TG) and differential thermal gravity (DTG), and vibrating sample magnetometry (VSM). Then mPst-DVB-C272 was applied to remove cadmium. The effects of pH, initial Cd(II) concentration, and contact time on Cd(II) removal were investigated in batch experiments. The optimized pH value for the Cd(II) adsorption was 6.5. The maximum adsorption capacity was 18.77 mg g−1 for mPst-DVB-C272. The adsorption reached equilibrium within 90 min and the experimental data fit the pseudo-second-order model.

Electrical lysis of mammalian cells has been a preferred method in microfluidic platforms because of its simple implementation and rapid recovery of lysates without additional reagents. However, bacterial lysis typically requires at least a 10-fold higher electric field (∼10 kV/cm), resulting in various technical difficulties. Here, we present a novel, low-field-enabled electromechanical lysis mechanism of bacterial cells using electroconvective vortices near ion selective materials. The vortex-assisted lysis only requires a field strength of ∼100 V/cm, yet it efficiently recovers proteins and nucleic acids from a variety of pathogenic bacteria and operates in a continuous and ultrahigh-throughput (1 mL/min) manner. Therefore, we believe that the electromechanical lysis will not only facilitate microfluidic bacterial sensing and analysis but also various high-volume applications such as the energy-efficient recovery of valuable metabolites in biorefinery pharmaceutical industries and the disinfection of large-volume fluid for the water and food industries.

P-vinylphenol (pVP) is a common building block of a large number of fluorescent protein chromophores. Theoretical investigation employed TD-DFT calculation has been carried out on pVP molecule to reveal the structural properties that influence the absorption and fluorescence. The molecular structures of the first excited state (S 1 ) as well as the ground state (S 0 ) have been optimized. Based on these structures, the absorption spectra are simulated using the Franck-Condon factors and displaced-distorted harmonic oscillator model. The result agrees well with the reported experiment data. It’s also found that the S 0 → S 1 transition is a significant π → π ∗ transition. Besides the π electrons on the benzene ring, the π electron together with the lone pair electron on hydroxyl group takes parts in the transition. Therefore the absorption of pVP would be modulated not only by the isomerization but also by the intermolecular hydrogen bond.

In multiview settings, observations from different views are assumed to share the same subspace. The abundance of views can be utilized to better explore the subspace. In this chapter, we consider two different kinds of multiview subspace learning problems. The first one contains the general unsupervised multiview subspace learning problems. We focus on canonical correlation analysis as well as some of its extensions. The second one contains the supervised multiview subspace learning problems, i.e., there exists available label information. In this case, representations more suitable for the on-hand task can be obtained by utilizing the label information. We also briefly introduce some other methods at the end of this chapter.

Transfer learning is proposed to transfer the learned knowledge from source domains to target domains where the target ones own fewer training data. Multitask learning learns multiple tasks simultaneously and makes use of the relationship among these tasks. Both of these learning methods can combine with the multiview learning, which exploits the information from the consistency of diverse views. In this chapter, we introduce four multiview transfer learning methods and three multiview multitask learning methods. We review research on multiview transfer learning under the large margin framework, discuss multiview discriminant transfer learning in detail, and introduce how to adapt Adaboost into multiview transfer learning. Three multiview multitask learning methods concentrate on the shared structures between tasks and views. The most natural way is to represent the relationships based on the bipartite graph and use an iterative algorithm to optimize its objective function. Another method constructs additional regularization function to ensure the view consistency. In general, convex shared structure learning algorithm provides structure parameters to share information. Besides, we introduce other methods; as supplements, where multi-transfer, multitask multiview discriminant analysis, and clustering are briefly mentioned.

Active learning is proposed based on the fact that manually labeled examples are expensive, thus it picks the most informative points to label so as to improve the learning efficiency. Combined with multiview learning algorithm, it constructs multiple learners to select contention points among different views. In this chapter, we introduce five multiview active learning algorithms as examples. At first, we introduce co-testing, the first algorithm applying active learning to multiview learning, and discuss how to process the contradiction between multiple learners. Bayesian co-training is proposed under the mutual information framework, which considers the unobserved labels as latent variables and marginalizes them out. We focus on multiview multi-learner learning active learning, which introduces the ambiguity of an example to measure its confidence. In the situation that active learning with extremely sparse labeled examples, there is a detailed derivation of CCA in two view. At last, we retell a practical active learning algorithm combined with semi-supervised learning. Besides, there are other methods briefly mentioned at the end of this chapter.

Semi-supervised learning is concerned with such learning scenarios where only a small portion of training data are labeled. In multiview settings, unlabeled data can be used to regularize the prediction functions, and thus to reduce the search space. In this chapter, we introduce two categories of multiview semi-supervised learning methods. The first one contains the co-training style methods, where the prediction functions from different views are trained through their own objective, and each prediction function is improved by the others. The second one contains the co-regularization style methods, where a single objective function exists for the prediction functions from different views to be trained simultaneously.

Multiview supervised learning algorithm can exploit the multiview nature of the data by the consensus of the views, that is, to seek predictors from different views that agree on the same example. In this chapter, we introduce three categories of multiview supervised learning methods. The first one contains the multiview large margin-based classifiers, which regularize the classifiers from different views with their agreements on classification margins to enforce view consensus. The second one contains multiple kernel learning, where the feature mappings underlying multiple kernels will map the views to new feature spaces where the classifiers are more likely to agree on the views. The third one contains some Gaussian process related models, in which case the predict functions themselves are taken as random variables. We also briefly introduce some other methods at the end of this chapter.

The multiview deep learning described in this chapter deals with multiview data or simulates constructing its intrinsic structure by using deep learning methods. We highlight three major categories of multiview deep learning methods through three different thoughts. The first category of approaches focuses on obtaining a shared joint representation from different views by building a hierarchical structure. The second category of approaches focuses on constructing structured spaces with different representations of multiple views which gives some constraints between representations on a different view. The third major category approaches focuses on explicitly constructing connections or relationships between different views or representations, which allows different views to be translated or mapped to each other.

Accumulation of amyloid beta (Aβ) peptide and hyperphosphorylated tau protein has been proposed to play roles in neural destruction which induce Alzheimer's disease (AD) progresses, glutamate transporter type 1 (GLT-1) and Glycogen synthase kinase3β (GSK3β) may be the pathological links between Aβ and tau pathology. Schisantherin B (STB) is one bioactive of lignans isolated from Schisandra chinensis (Turcz.) Baill which has been commonly used as a traditional herbal medicine for thousands of years. This paper was designed to investigate the effects of STB on improving the cognitive function and neurodegeneration in the mouse model of Alzheimer's disease induced by Aβ1-42, and its possible mechanism were Glutamate transporter GLT-1, tau and GSK3β. It was found that successive intracerebroventricular (ICV) administration of STB (0.15mg/kg) for 5days significantly attenuated Aβ1-42-induced learning and memory impairment as measured by the Locomotor activity test, Y-maze test and Morris water maze test. Furthermore, STB at a dose of 0.15mg/kg restored the activities of GLT-1 and GSK3β while decreasing the levels of hyperphosphorylated tau protein in the hippocampus and cerebral cortex. The results suggested that STB might protect against cognitive deficits and neurodegeneration induced by Aβ1-42 in mice by regulating the GLT-1 restoration as well as the capacity of GSK3β.

Leukocytes are the essential cells of the immune system that protect the human body against bacteria, viruses, and other foreign invaders. Secretory products of individual leukocytes, such as matrix metalloproteinases (MMPs) and a disintegrin and metalloproteinase (ADAMs), are critical for regulating the inflammatory response and mediating host defense. Conventional single cell analytical methods, such as flow cytometry for cellular surface biomarker studies, are insufficient for performing functional assays of the protease activity of individual leukocytes. Here, an integrated continuous-flow microfluidic assay is developed to effectively detect secretory protease activity of individual viable leukocytes. Leukocytes in blood are first washed on-chip with defined buffer to remove background activity, followed by encapsulating individual leukocytes with protease sensors in water-in-oil droplets and incubating for 1 h to measure protease secretion. With this design, single leukocyte protease profiles under naive and phorbol 12-myristate 13-acetate (PMA)-stimulated conditions are reliably measured. It is found that PMA treatment not only elevates the average protease activity level but also reduces the cellular heterogeneity in protease secretion, which is important in understanding immune capability and the disease condition of individual patients.

Sepsis represents a systemic inflammatory response caused by microbial infection in blood. Herein, we present a novel comprehensive approach to mitigate inflammatory responses through broad spectrum removal of pathogens, leukocytes and cytokines based on biomimetic cell margination. Using a murine model of polymicrobial sepsis induced by cecal ligation and puncture (CLP), we performed extracorporeal blood filtration with the developed microfluidic blood margination (μBM) device. Circulating bacteremia, leukocytes and cytokines in blood decreased post-filtration and significant attenuation of immune cell and cytokine responses were observed 3–5 days after intervention, indicating successful long-term immunomodulation. A dose-dependent effect on long-term immune cell count was also achieved by varying filtration time. As proof of concept for human therapy, the μBM device was scaled up to achieve ∼100-fold higher throughput (∼150 mL h⁻¹). With further multiplexing, the μBM technique could be applied in clinical settings as an adjunctive treatment for sepsis and other inflammatory diseases., United States. Defense Advanced Research Projects Agency (N66001-11-1-4182)

Blue organic emissive materials are still the most important bottlenecks for the development of organic light-emitting diodes (OLEDs). To enrich the material library, herin, three bipolar phenanthroimidazole derivatives, namely MePPIM-TPA, ClPPIM- TPA and BuPPIM-TPA, are synthesized using triphenylamine as electron-donor and phenanthroimidazole as the electron-acceptor. The photophysical, thermal and electrochemical properties of three compounds are investigated with high decomposition temperature up to 350 °C, and strong blue emission. Single-carrier devices are fabricated to show that three compounds have good bipolar carrier transport characteristic. The non-doped fluorescent OLEDs devices using three compounds as emitting layers are fabricated among which the devices based on MePPIM-TPA achieved the maximum luminance of 1743 cd/m2, the maximum external quantum efficiency (EQE) of 2.99% which is relatively comparable to commonly used blue emitters.

Circulating tumor cells (CTCs) are rare cancer cells that are shed from primary or metastatic tumors into the peripheral blood circulation. Phenotypic and genetic characterization of these rare cells can provide important information to guide cancer staging and treatment, and thus further research into their characteristics and properties is an area of considerable interest. In this protocol, we describe detailed procedures for the production and use of a label-free spiral microfluidic device to allow size-based isolation of viable CTCs using hydrodynamic forces that are present in curvilinear microchannels. This spiral system enables us to achieve ≥ 85% recovery of spiked cells across multiple cancer cell lines and 99.99% depletion of white blood cells in whole blood. The described spiral microfluidic devices can be produced at an extremely low cost using standard microfabrication and soft lithography techniques (2-3 d), and they can be operated using two syringe pumps for lysed blood samples (7.5 ml in 12.5 min for a three-layered multiplexed chip). The fast processing time and the ability to collect CTCs from a large patient blood volume allows this technique to be used experimentally in a broad range of potential genomic and transcriptomic applications.

In this paper, [NaGd1-xNdx](MoO4)2 crystals with x = 0.005–0.05 were grown by Czochralski method at 950 ℃ for 10 hours and subsequently characterized by absorption spectroscopy and fluorescence spectroscopy. The intensity parameters of Nd3+ were calculated by Judd-Ofelt theory, and the relationship between the parameters and Nd3+ concentration was analyzed. The results show that with the increasing Nd3+ concentration, the oscillator strength, stimulated emission cross-section, Ωt and spontaneous transition probability decrease slightly, while the fluorescence lifetime decreases significantly. However, the fluorescence branching ratio is almost unchanged with the increasing Nd3+concentration. The [NaGd1-xNdx](MoO4)2 crystal with (x = 0.01) possesses the highest quantum efficiency of 88.98%, a good fluorescence line-width of 23 nm, a large value of σem·τf up to 0.55 × 10−22 cm2·s and a stimulated emission cross-section up to 3.747 × 10−19 cm2 for the transition from 4F3/2 to4I11/2 at 1064 nm. Test results indicate that [NaGd1-xNdx](MoO4)2 crystals are an excellent gain media for the solid state laser system.

The key radical ion-pair transient in DNA guanine oxidation is directly observed at low temperature by time-resolved spectroscopy., Although the radical ion pair has been frequently invoked as a key intermediate in DNA oxidative damage reactions and photoinduced electron transfer processes, the unambiguous detection and characterization of this species remain formidable and unresolved due to its extremely unstable nature and low concentration. We use the strategy that, at cryogenic temperatures, the transient species could be sufficiently stabilized to be detectable spectroscopically. By coupling the two techniques (the cryogenic stabilization and the time-resolved laser flash photolysis spectroscopy) together, we are able to capture the ion-pair transient G+•⋯Cl− in the chlorine radical–initiated DNA guanine (G) oxidation reaction, and provide direct evidence to ascertain the intricate type of addition/charge separation mechanism underlying guanine oxidation. The unique spectral signature of the radical ion-pair G+•⋯Cl− is identified, revealing a markedly intense absorption feature peaking at 570 nm that is distinctive from G+• alone. Moreover, the ion-pair spectrum is found to be highly sensitive to the protonation equilibria within guanine-cytosine base pair (G:C), which splits into two resolved bands at 480 and 610 nm as the acidic proton transfers along the central hydrogen bond from G+• to C. We thus use this exquisite sensitivity to track the intrabase-pair proton transfer dynamics in the double-stranded DNA oligonucleotides, which is of critical importance for the description of the proton-coupled charge transfer mechanisms in DNA.

We report a new transient spectral method utilizing triplet excited state as sensitive reporters to monitor and differentiate the multiplex G- quadruplex/ligand interactions in a single assay, which is a difficult task and usually requires a combination of several techniques. From a systematic study on the interactions of porphyrin (TMPyP4) with each telomeric G-quadruplex: AG3(T2AG3)3 ,G 2T2G2TGTG2T2G2 ,( G4T4G4)2, and (TG4T)4, it is convinc- ingly shown that the ligand triplet decay lifetimes are sensitive to the local bound microenvironment within G-quadruplexes, from which the coexisting binding modes of end-stacking, intercalation, and sandwich are distinguished and their respective contribution are determined. The complete scenario of mixed interaction modes is thus revealed, shedding light on the past controversial issues. Additional control experiments demonstrate the sensitivity of this triplet reporter method, which can even capture the binding behavior change as the G-quadruplex structures are adjusted by Na + or K + .

In this paper, we evaluate the strategy of using self-assembled microbeads to build a robust and tunable membrane for free-flow zone electrophoresis in a PDMS microfluidic chip. To fabricate a porous membrane as a salt bridge for free-flow zone electrophoresis, we used silica or polystyrene microbeads between 3-6 μm in diameter and packed them inside a microchannel. After complete evaporation, we infiltrated the porous microbead structure with a positively or negatively charged hydrogel to modify its surface charge polarity. Using this device, we demonstrated binary sorting (separation of positive and negative species at a given pH) of peptides and dyes in standard buffer systems without using sheath flows. The sample loss during sorting could be minimized by using ion selectivity of hydrogel-infiltrated microbead membranes. Our fabrication method enables building a robust membrane for pressure-driven free-flow zone electrophoresis with tunable pore size as well as surface charge polarity.

The o-hydroxycinnamic derivatives represent efficient caged compounds that can realize quantification of delivery upon uncaging, but there has been lack of time-resolved and mechanistic studies. We used time-resolved infrared (TRIR) spectroscopy to investigate the photochemical uncaging dynamics of the prototype o-hydroxycinnamic compound, (E)-3-(2-hydroxyphenyl)-acrylic acid ethyl ester (HAAEE), leading to coumarin and ethanol upon uncaging. Taking advantage of the specific vibrational marker bands and the IR discerning capability, we have identified and distinguished two key intermediate species, the cis-isomers of HAAEE and the tetrahedral intermediate, in the transient infrared spectra, thus providing clear spectral evidence to support the intramolecular nucleophilic addition mechanism following the trans-cis photoisomerization. Moreover, the product yields of coumarin upon uncaging were observed to be greatly affected by the solvent polarity, suppressed in CH2Cl2 but enhanced in D2O/CH3CN with the increasing volume ratio of D2O. The highly solvent-dependent behavior indicates E1 elimination of the tetrahedral intermediate to give rise to the final uncaging product coumarin. The photorelease rate of coumarin was directly characterized from TRIR (3.6 × 10(6) s(-1)), revealing the promising application of such o-hydroxycinnamic compound in producing fast alcohol jumps. The TRIR results provide the first time-resolved detection and thus offer direct dynamical information about this photochemical uncaging reaction.

Seasonal variations of baroclinic tides for K1 and M2 constituents were separately studied using two-dimensional numerical simulations along the 21°N section of the northern South China Sea (SCS). Results show that the continental slope of the northern SCS and the west ridge of the Luzon Strait are supercritical to K1 internal tides, which may be trapped in the deep basin of the SCS and form standing or partial standing waves. Meanwhile, these areas are sub-critical to M2 internal tides, which can transmit onto the shelf and are seldom reflected back into the basin. The trapped K1 internal tides are dominated by mode-2 and mode-3 in summer and by mode-1 and mode-3 in winter. Moreover, high mode K1 internal tides account for nearly 20–40 % of the total energy density in winter and 15–20 % in summer. The pattern of K1 internal tides in the basin is mainly determined by the percentage of reflected energy from the continental slope. The phase difference between the incoming mode-1 and mode-2 K1 internal tides near the continental slope are nearly out of phase in winter, which means that the percentage of reflection of the K1 internal tide is larger than that in summer. Both the convergence and high mode K1 internal tides can enhance the vertical shear. The above results indicate that, in the deep basin of the SCS, water mixing potentially induced by internal tides in winter is stronger than in summer.

Puerarin is a major isoflavone glycoside from the root of Pueraria lobata. It has been reported that puerarin can protect neurons from oxidative stress-induced apoptosis. Emerging evidence suggests that oxidative damage is associated with Aβ-induced neuronal death. In the current study, we evaluated the effect of puerarin on Alzheimerʼs disease induced by Aβ and explored the potential mechanisms underlying this effect. We found that the escape latency of the Morris water maze was decreased in groups treated with puerarin compared to the model group (p

Accumulation of amyloid beta (Aβ) peptide and hyperphosphorylated tau protein has been proposed to play roles in neural destruction which induce Alzheimer's disease (AD) progresses, glutamate transporter type 1 (GLT-1) and Glycogen synthase kinase3β (GSK3β) may be the pathological links between Aβ and tau pathology. Schisantherin B (STB) is one bioactive of lignans isolated from Schisandra chinensis (Turcz.) Baill which has been commonly used as a traditional herbal medicine for thousands of years. This paper was designed to investigate the effects of STB on improving the cognitive function and neurodegeneration in the mouse model of Alzheimer's disease induced by Aβ

Pentachlorophenol, a widespread environmental pollutant that is possibly carcinogenic to humans, is metabolically oxidized to tetrachloroquinone (TCBQ) which can result in DNA damage. We have investigated the photochemical reaction dynamics of TCBQ with two pyrimidine type nucleobases (thymine and uracil) upon UVA (355 nm) excitation using the technique of nanosecond time-resolved laser flash photolysis. It has been found that 355 nm excitation populates TCBQ molecules to their triplet state 3TCBQ*, which are highly reactive towards thymine or uracil and undergo two parallel reactions, the hydrogen abstraction and electron transfer, leading to the observed photoproducts of TCBQH· and TCBQ·− in transient absorption spectra. The concomitantly produced nucleobase radicals and radical cations are expected to induce a series of oxidative or strand cleavage damage to DNA afterwards. By characterizing the photochemical hydrogen abstraction and electron transfer reactions, our results provide potentially important molecular reaction mechanisms for understanding the carcinogenic effects of pentachlorophenol and its metabolites TCBQ.

As key components of autocrine signaling, pericellular proteases, a disintegrin and metalloproteinases (ADAMs) in particular, are known to impact the microenvironment of individual cells and have significant implications in various pathological situations including cancer, inflammatory and vascular diseases. There is great incentive to develop a high-throughput platform for single-cell measurement of pericellular protease activity, as it is essential for studying the heterogeneity of protease response and the corresponding cell behavioral consequences. In this work, we developed a microfluidic platform to simultaneously monitor protease activity of many single cells in a time-dependent manner. This platform isolates individual microwells rapidly on demand and thus allows single-cell activity measurement of both cell-surface and secreted proteases by confining individual cells with diffusive FRET-based substrates. With this platform, we observed dose-dependent heterogeneous protease activation of HepG2 cells treated with phorbol 12-myristate 13-acetate (PMA). To study the temporal behavior of PMA-induced protease response, we monitored the pericellular protease activity of the same single cells during three different time periods and revealed the diversity in the dynamic patterns of single-cell protease activity profile upon PMA stimulation. The unique temporal information of single-cell protease response can help unveil the complicated functional role of pericellular proteases., National Institutes of Health (U.S.) (Grant R01-CA096504), Singapore-MIT Alliance for Research and Technology (SMART)