A SURF4-to-proteoglycan relay mechanism that mediates the sorting and secretion of a tagged variant of sonic hedgehog

SignificanceSonic Hedgehog (Shh) is a key signaling molecule that plays important roles in embryonic patterning, cell differentiation, and organ development. Although fundamentally important, the molecular mechanisms that regulate secretion of newly synthesized Shh are still unclear. Our study reveals a role for the cargo receptor, SURF4, in facilitating export of Shh from the endoplasmic reticulum (ER) via a ER export signal. In addition, our study provides evidence suggesting that proteoglycans promote the dissociation of SURF4 from Shh at the Golgi, suggesting a SURF4-to-proteoglycan relay mechanism. These analyses provide insight into an important question in cell biology: how do cargo receptors capture their clients in one compartment, then disengage at their destination?</p

Dynamic conformational changes of a tardigrade group-3 late embryogenesis abundant protein modulate membrane biophysical properties

A number of intrinsically disordered proteins (IDPs) encoded in stress-tolerant organisms, such as tardigrade, can confer fitness advantage and abiotic stress tolerance when heterologously expressed. Tardigrade-specific disordered proteins including the cytosolic-abundant heat-soluble proteins are proposed to confer stress tolerance through vitrification or gelation, whereas evolutionarily conserved IDPs in tardigrades may contribute to stress tolerance through other biophysical mechanisms. In this study, we characterized the mechanism of action of an evolutionarily conserved, tardigrade IDP, HeLEA1, which belongs to the group-3 late embryogenesis abundant (LEA) protein family. HeLEA1 homologs are found across different kingdoms of life. HeLEA1 is intrinsically disordered in solution but shows a propensity for helical structure across its entire sequence. HeLEA1 interacts with negatively charged membranes via dynamic disorder-to-helical transition, mainly driven by electrostatic interactions. Membrane interaction of HeLEA1 is shown to ameliorate excess surface tension and lipid packing defects. HeLEA1 localizes to the mitochondrial matrix when expressed in yeast and interacts with model membranes mimicking inner mitochondrial membrane. Yeast expressing HeLEA1 shows enhanced tolerance to hyperosmotic stress under nonfermentative growth and increased mitochondrial membrane potential. Evolutionary analysis suggests that although HeLEA1 homologs have diverged their sequences to localize to different subcellular organelles, all homologs maintain a weak hydrophobic moment that is characteristic of weak and reversible membrane interaction. We suggest that such dynamic and weak protein-membrane interaction buffering alterations in lipid packing could be a conserved strategy for regulating membrane properties and represent a general biophysical solution for stress tolerance across the domains of life.</p

Fluorescent core-shell silica nanoparticles as tunable precursors: towards encoding and multifunctional nano-probes

Core-shell silica nanoparticles comprised of a RuBpy doped silica core and a Pas-DTPA doped silica shell were synthesized and post-functionalized with an encoding fluorescence combination and multiplex imaging function

Comprehensive Bibliometric Analysis of the Kynurenine Pathway in Mood Disorders: Focus on Gut Microbiota Research

Background: Emerging evidence implicates the dysregulated kynurenine pathway (KP), an immune-inflammatory pathway, in the pathophysiology of mood disorders (MD), including depression and bipolar disorder characterized by a low-grade chronic pro-inflammatory state. The metabolites of the KP, an important part of the microbiota-gut-brain axis, serve as immune system modulators linking the gut microbiota (GM) with the host central nervous system.Aim: This bibliometric analysis aimed to provide a first glimpse into the KP in MD, with a focus on GM research in this field, to guide future research and promote the development of this field.Methods: Publications relating to the KP in MD between the years 2000 and 2020 were retrieved from the Scopus and Web of Science Core Collection (WoSCC), and analyzed in CiteSpace (5.7 R5W), biblioshiny (using R-Studio), and VOSviewer (1.6.16).Results: In total, 1,064 and 948 documents were extracted from the Scopus and WoSCC databases, respectively. The publications have shown rapid growth since 2006, partly owing to the largest research hotspot appearing since then, “quinolinic acid.” All the top five most relevant journals were in the neuropsychiatry field, such as Brain Behavior and Immunity. The United States and Innsbruck Medical University were the most influential country and institute, respectively. Journal co-citation analysis showed a strong tendency toward co-citation of research in the psychiatry field. Reference co-citation analysis revealed that the top four most important research focuses were “kynurenine pathway,” “psychoneuroimmunology,” “indoleamine 2,3-dioxygenase,” and “proinflammatory cytokines,” and the most recent focus was “gut-brain axis,” thus indicating the role of the KP in bridging the GM and the host immune system, and together reflecting the field’s research foundations. Overlap analysis between the thematic map of keywords and the keyword burst analysis revealed that the topics “Alzheimer’s disease,” “prefrontal cortex,” and “acid,” were research frontiers.Conclusion: This comprehensive bibliometric study provides an updated perspective on research associated with the KP in MD, with a focus on the current status of GM research in this field. This perspective may benefit researchers in choosing suitable journals and collaborators, and aid in the further understanding of the field’s hotspots and frontiers, thus facilitating future research

A study of the reaction mechanisms and reactive intermediates involved in halogenated compounds : trichloroethylene oxide, halogenated benzophenones, and halogenated quinoline-based phototriggers

UV/Vis absorption spectroscopy (UV/Vis), femtosecond transient absorption spectroscopy (fs-TA), nanosecond transient absorption spectroscopy (ns-TA), and nanosecond time-resolved resonance Raman spectroscopy (ns-TR3), as well as density functional theory (DFT) computations were employed to study the mechanisms and the intermediates in reactions of selected halogenated compounds, including trichloroethylene oxide (TCE oxide), halogenated benzophenones (4-FBP, 4-ClBP, 4-BrBP, 3-FBP, 33’-DFBP, 3-ClBP, 3-BrBP, 2-FBP, 2-ClBP, and 2-BrBP), and halogenated quinoline-based phototriggers (BHQ-OPh and BHQ-OAc). This study investigated the halogen substituent effect on the mechanisms of various water-involved reactions and the influences from the number of halogens present, the type of halogen and the substituent position of the halogen in the molecules of interest. The general mechanisms for the reactions of these halogenated compounds were summarized along with discussion of the driving forces from the substituted halogen. First, TCE oxide was hydrolyzed to release chloride ions one by one which led to a complicated water-catalyzed decomposition. To account for the dehalogenation and the formation of CO with three kinds of carboxylic acids (formic acid, glyoxylic acid, and dichloroacetic acid), the predominant decomposition pathways were examined by comparing the computed activation energies for the formation of different products. From these comparisons, the ring-opening reaction was identified as the rate-determining step, which is also supported by previous experimental observations reported in the literature. Based on all of these analyses, the mechanisms of the water-catalyzed decomposition reactions were determined and a water-assisted HCl elimination model has been proposed. Second, some halogen-substituted benzophenones demonstrated an efficiency for a photosubstitution reaction and the related photohydration reactions. Interestingly, the efficient photosubstitution reactions of 3-FBP and 33’-DFBP were dependent on the solution acidity and reached a maximum in 1 M HClO4 CH3CN/H2O (1/1) solution. Only the photohydration reaction took place for the 3-ClBP, 3-BrBP, 4-FBP, 4-ClBP, and 4-BrBP molecules. Nevertheless, no special photochemical reaction occurred for 2-FBP, 2-ClBP, and 2-BrBP. The mechanisms and intermediates were directly characterized by spectroscopic observations and rationalized by results from DFT computations. According to these results, the general mechanisms for the photosubstitution reaction and the related photohydration reactions of halogenated benzophenone derivatives were summarized. These results reveal that the efficiency in forming the corresponding hydroxy benzophenone is influenced by the solution acidity, substituent positions, and the character of the substituted halogens. The substituted halogen is the driving force of this photosubstitution reaction. This conclusion provides insight into several possible applications that are also briefly discussed in this thesis. Lastly, the BHQ-OPh system was found to undergo an extraordinary efficient excited-state proton transfer (ESPT) to initiate a dehalogenation reaction. The fs-TA and ns-TA spectra indicate clearly the interactions between four prototropic forms of BHQ-OPh, which were characterized by UV-Vis spectra under different pH values. These prototropic forms play important roles in inducing further dehalogenation, thus their structural configurations were also investigated by DFT computations. Besides, competing with the dehalogenation reaction, BHQ-OAc underwent another photodeprotection to release the OAc group. The comparison between BHQ-OPh and BHQ-OAc provides further information in understanding the mechanisms of dehalogenation reactions and photodeprotection reactions of these quinoline-based phototriggers.published_or_final_versionChemistryDoctoralDoctor of Philosoph

Object-oriented polarimetric SAR image classification via the combination of a pixel-based classifier and a region growing technique

ABSTRACTLand-cover type interpretation by the use of remote sensing image classification techniques is always a hot topic. In this paper, an object-oriented method is presented for fully polarimetric synthetic aperture radar (SAR) image classification. Differing from most of the traditional object-oriented classification algorithms, the proposed method employs an innovative classification strategy that combines a pixel-based classifier and a region growing technique. Firstly, taking each individual pixel as a seed pixel, the homogeneous areas are extracted by a region growing technique. Then, using the information of the pixel-based classification result, the pixels located in each homogeneous area are all assigned to a certain class. Finally, the majority voting strategy is deployed to determine the final class label of each pixel. The experiments conducted on two fully polarimetric SAR images reveal that the proposed classification scheme can obtain pleasing classification accuracy and can provide the classification maps with more homogeneous regions than pixel-based classification

DNA-Pt complex interactions investigated by single-molecule force spectroscopy and surface-enhanced Raman spectroscopy

Biomacromolecules have dynamic three-dimensional structures that are selective for interacting with other biological components in cellular function. For example, DNA is the major target of anti-cancer drugs in chemotherapy medications. Despite the broad clinical successes in cancer treatment, Platinum complexes exhibit severe side effects and acquired/intrinsic drug resistance due to off-target binding. Thus, an in-depth mechanistic understanding of DNA-Platinum complex interactions is required to support the rational design of new chemotherapy drugs that selectively bind to target DNA.Published versio

Sensor Distribution Optimization for Composite Impact Monitoring Based on AR Model and LPP

The aim of this article is to provide a sensor distribution optimization method for the effective impact monitoring of composite plates with fewer sensors. In this research, the number of sensors and the minimum difference between categories are used as objective functions I and II, respectively, where the minimum difference is the Euclidean distance between different influence categories. The dual objective functions are defined by means of finite element analysis, the autoregressive (AR) model, and locality&minus;preserving projection (LPP). The sensor distribution is optimized based on Multi&minus;Objective Particle Swarm Optimization (MOPSO). Finally, an impact monitoring method is provided, and an experimental platform is built to verify the method. According to the optimization results, different grid sizes have a certain impact on the identification results, with the smaller the grid size, the smaller the minimum difference between categories. Within a given grid size, the minimum difference between categories increases with the increasing number of sensors. Experiments show that the higher the number of sensors, the higher the recognition rate of the system. Comparing the experimental results with the energy analysis of wavelet bands and PCA methods, it is found that the method used in this study has a higher recognition rate. This research provides an impact monitoring method based on sensor distribution optimization. And the effectiveness of the method is verified by experiments. It provides a useful reference and choice for the structure condition monitoring of composite material plates

Sensor Distribution Optimization for Composite Impact Monitoring Based on AR Model and LPP

The aim of this article is to provide a sensor distribution optimization method for the effective impact monitoring of composite plates with fewer sensors. In this research, the number of sensors and the minimum difference between categories are used as objective functions I and II, respectively, where the minimum difference is the Euclidean distance between different influence categories. The dual objective functions are defined by means of finite element analysis, the autoregressive (AR) model, and locality−preserving projection (LPP). The sensor distribution is optimized based on Multi−Objective Particle Swarm Optimization (MOPSO). Finally, an impact monitoring method is provided, and an experimental platform is built to verify the method. According to the optimization results, different grid sizes have a certain impact on the identification results, with the smaller the grid size, the smaller the minimum difference between categories. Within a given grid size, the minimum difference between categories increases with the increasing number of sensors. Experiments show that the higher the number of sensors, the higher the recognition rate of the system. Comparing the experimental results with the energy analysis of wavelet bands and PCA methods, it is found that the method used in this study has a higher recognition rate. This research provides an impact monitoring method based on sensor distribution optimization. And the effectiveness of the method is verified by experiments. It provides a useful reference and choice for the structure condition monitoring of composite material plates