Development of high-efficiency superparamagnetic drug delivery system with MPI imaging capability

In this study, a high-efficiency superparamagnetic drug delivery system was developed for preclinical treatment of bladder cancer in small animals. Two types of nanoparticles with magnetic particle imaging (MPI) capability, i.e., single- and multi-core superparamagnetic iron oxide nanoparticles (SPIONs), were selected and coupled with bladder anti-tumor drugs by a covalent coupling scheme. Owing to the minimal particle size, magnetic field strengths of 270 mT with a gradient of 3.2 T/m and 260 mT with a gradient of 3.7 T/m were found to be necessary to reach an average velocity of 2 mm/s for single- and multi-core SPIONs, respectively. To achieve this, a method of constructing an in vitro magnetic field for drug delivery was developed based on hollow multi-coils arranged coaxially in close rows, and magnetic field simulation was used to study the laws of the influence of the coil structure and parameters on the magnetic field. Using this method, a magnetic drug delivery system of single-core SPIONs was developed for rabbit bladder therapy. The delivery system consisted of three coaxially and equidistantly arranged coils with an inner diameter of Φ50 mm, radial height of 85 mm, and width of 15 mm that were positioned in close proximity to each other. CCK8 experimental results showed that the three types of drug-coupled SPION killed tumor cells effectively. By adjusting the axial and radial positions of the rabbit bladder within the inner hole of the delivery coil structure, the magnetic drugs injected could undergo two-dimensional delivery motions and were delivered and aggregated to the specified target location within 12 s, with an aggregation range of about 5 mm × 5 mm. In addition, the SPION distribution before and after delivery was imaged using a home-made open-bore MPI system that could realistically reflect the physical state. This study contributes to the development of local, rapid, and precise drug delivery and the visualization of this process during cancer therapy, and further research on MPI/delivery synchronization technology is planned for the future.

Effective synthesis of high-content fructooligosaccharides in engineered Aspergillus niger

BACKGROUND

Aspergillus niger ATCC 20611 is an industrially important fructooligosaccharides (FOS) producer since it produces the β-fructofuranosidase with superior transglycosylation activity, which is responsible for the conversion of sucrose to FOS accompanied by the by-product (glucose) generation. This study aims to consume glucose to enhance the content of FOS by heterologously expressing glucose oxidase and peroxidase in engineered A. niger.

RESULTS

Glucose oxidase was successfully expressed and co-localized with β-fructofuranosidase in mycelia. These mycelia were applied to synthesis of FOS, which possessed an increased purity of 60.63% from 52.07%. Furthermore, peroxidase was expressed in A. niger and reached 7.70 U/g, which could remove the potential inhibitor of glucose oxidase to facilitate the FOS synthesis. Finally, the glucose oxidase-expressing strain and the peroxidase-expressing strain were jointly used to synthesize FOS, which content achieved 71.00%.

CONCLUSIONS

This strategy allows for obtaining high-content FOS by the multiple enzymes expressed in the industrial fungus, avoiding additional purification processes used in the production of oligosaccharides. This study not only facilitated the high-purity FOS synthesis, but also demonstrated the potential of A. niger ATCC 20611 as an enzyme-producing cell factory.

Expectations for employing Escherichia coli Nissle 1917 in food science and nutrition

As a promising probiotic strain, Escherichia coli Nissle 1917 (EcN) has been demonstrated to confer beneficial effects on intestinal health, immune function, and pathogen prevention. Additionally, EcN has also been widely studied due to its clear genomic information, tractable gene regulation, and simple growth conditions. This review summarizes the various applications potential of EcN in food science and nutrition, including inflammation prevention, tumor-targeting therapy, antibacterial agents for food, and nutrient production with a focus on specific case studies. Moreover, we highlight the major challenges of employing EcN in food science and nutrition, including regulatory approval, stability during food processing, and consumer acceptance. Finally, we conclude with a discussion on perspectives related to employing EcN in food science and nutrition.

Human milk oligosaccharide lacto-N-tetraose: Physiological functions and synthesis methods

Human milk oligosaccharides (HMOs) have attracted considerable attention due to their unique role in boosting infant health. Among the HMOs, lacto-N-tetraose (LNT) is a significant constituent associated with various health benefits, such as prebiotic effects, antiadhesive antimicrobials, antiviral protection, and immune modulators. LNT has received a "Generally Recognized as Safe" status by the American Food and Drug Administration and was approved as a food ingredient for infant formula. However, the limited availability of LNT poses a major challenge for its application in food and medicine. In this review, we first explored the physiological functions of LNT. Next, we describe several synthesis methods for production of LNT, including chemical, enzymatic, and cell factory approaches, and summarize the pivotal research results. Finally, challenges and opportunities for the large-scale synthesis of LNT were discussed.

Correction: Sheng et al. Antibacterial and Angiogenic Poly(ionic liquid) Hydrogels. Gels 2022, 8, 476

In the original publication [...].

Adaptive NN Optimal Consensus Fault-Tolerant Control for Stochastic Nonlinear Multiagent Systems

This article investigates the problem of adaptive neural network (NN) optimal consensus tracking control for nonlinear multiagent systems (MASs) with stochastic disturbances and actuator bias faults. In control design, NN is adopted to approximate the unknown nonlinear dynamic, and a state identifier is constructed. The fault estimator is designed to solve the problem raised by time-varying actuator bias fault. By utilizing adaptive dynamic programming (ADP) in identifier-critic-actor construction, an adaptive NN optimal consensus fault-tolerant control algorithm is presented. It is proven that all signals of the controlled system are uniformly ultimately bounded (UUB) in probability, and all states of the follower agents can remain consensus with the leader's state. Finally, simulation results are given to illustrate the effectiveness of the developed optimal consensus control scheme and theorem.

Grey Wolf Optimization algorithm based on Cauchy-Gaussian mutation and improved search strategy

The traditional Grey Wolf Optimization algorithm (GWO) has received widespread attention due to features of strong convergence performance, few parameters, and easy implementation. However, in actual optimization projects, there are problems of slow convergence speed and easy to fall into local optimal solution. The paper proposed a Grey Wolf Optimization algorithm based on Cauchy-Gaussian mutation and improved search strategy (CG-GWO) in response to the above problems. The Cauchy-Gaussian mutation operator is introduced to increase the population diversity of the leader wolves and improve the global search ability of the algorithm. This work retains outstanding grey wolf individuals through the greedy selection mechanism to ensure the convergence speed of the algorithm. An improved search strategy was proposed to expand the optimization space of the algorithm and improve the convergence accuracy. Experiments are performed with 16 benchmark functions covering unimodal functions, multimodal functions, and fixed-dimension multimodal functions to verify the effectiveness of the algorithm. Experimental results show that compared with four classic optimization algorithms, particle swarm optimization algorithm (PSO), whale optimization algorithm (WOA), sparrow optimization algorithm (SSA), and farmland fertility algorithm (FFA), the CG-GWO algorithm shows better convergence accuracy, convergence speed, and global search ability. The proposed algorithm shows the same better performance compared with a series of improved algorithms such as the improved grey wolf algorithm (IGWO), modified Grey Wolf Optimization algorithm (mGWO), and the Grey Wolf Optimization algorithm inspired by enhanced leadership (GLF-GWO).

Removal of starch granule-associated surface and channel lipids alters the properties of sodium trimetaphosphate crosslinked maize starch

Starch granule-associated surface and channel lipids (SGALs) were effectively removed from waxy maize starch (WMS) and normal maize starch (NMS), then the starches were crosslinked by different levels of sodium trimetaphosphate (STMP) (0.25 %, 0.5 %, 1 % and 2 %). The effective removal of SGALs and successful crosslinking, were evidenced by the disappearance of surface-fluorescence and channel-fluorescence of Pro-Q Diamond-stained granules, and the increased phosphorus content respectively. STMP crosslinking increased peak and final viscosity for WMS and NMS. Crosslinking at high STMP levels (0.5 %, 1 % and 2 %) transformed the starch pastes from thixotropic to anti-thixotropic. STMP crosslinking significantly decreased the tan δ values of maize starches, enhancing the elastic structure of the gel. Crosslinked maize starches without SGALs had lower breakdown than crosslinked starches at same STMP level, indicating higher tightened crosslinked starch granules after SGALs removal. Removal of SGALs increased the anti-thixotropy of crosslinked starches, facilitating the reorientation of crosslinked amylopectin/amylose molecules during shearing. Removal of SGALs increased the tan δ values from frequency sweep of WMS and NMS during STMP crosslinking, indicating the presence of surface-lipids and channel-lipids could enhance the elastic gel network structure of crosslinked maize starch.

Adaptive Optimized Backstepping Control-Based RL Algorithm for Stochastic Nonlinear Systems With State Constraints and Its Application

This article investigates the adaptive neural-network (NN) tracking optimal control problem for stochastic nonlinear systems, which contain state constraints and uncertain dynamics. First, to avoid the violation of state constraints in achieving optimal control, the novel barrier optimal performance index functions for subsystems are developed. Second, under the framework of the identifier-actor-critic, the virtual and actual optimal controllers are presented based on the backstepping technique, in which the unknown nonlinear dynamics are learned by the NN approximators. Moreover, the quartic barrier Lyapunov functions are constructed instead of square ones to cope with the Hessian term to ensure the stability of the systems with stochastic disturbance. The proposed optimal control strategy can guarantee the boundedness of closed-loop signals, and the output can follow the given reference signal. Meanwhile, the system states are restricted within some preselected compact sets all the while. Finally, both numerical and practical systems are carried out to further illustrate the validity of the proposed optimal control approach.

A survey of adaptive optimal control theory

This paper makes a survey about the recent development of optimal control based on adaptive dynamic programming (ADP). First of all, based on DP algorithm and reinforcement learning (RL) algorithm, the origin and development of the optimization idea and its application in the control field are introduced. The second part introduces achievements in the optimal control direction, then we classify and summarize the research results of optimization method, constraint problem, structure design in control algorithm and practical engineering process based on optimal control. Finally, the possible future research topics are discussed. Through a comprehensive and complete investigation of its application in many existing fields, this survey fully demonstrates that the optimal control algorithms via ADP with critic-actor neural network (NN) structure, which also have a broad application prospect, and some developed optimal control design algorithms have been applied to practical engineering fields.

Adaptive Neural Network Finite-Time Dynamic Surface Control for Nonlinear Systems

This article addresses the problem of finite-time neural network (NN) adaptive dynamic surface control (DSC) design for a class of single-input single-output (SISO) nonlinear systems. Such designs adopt NNs to approximate unknown continuous system functions. To avoid the "explosion of complexity" problem, a novel nonlinear filter is developed in control design. Under the framework of adaptive backstepping control, an NN adaptive finite-time DSC design algorithm is proposed by adopting a smooth projection operator and finite-time Lyapunov stable theory. The developed control algorithm means that the tracking error converges to a small neighborhood of origin within finite time, which further verifies that all the signals of the controlled system possess globally finite-time stability (GFTS). Finally, both numerical and practical simulation examples and comparing results are provided to elucidate the superiority and effectiveness of the proposed control algorithm.

An Enhanced Scheme for Multiscale Modeling of Thermomechanical Properties of Polymer Bulks

While multiscale modeling significantly enhances the capability of molecular simulations of polymer systems, it is well realized that the systematically derived coarse-grained (CG) models generally underestimate the thermomechanical properties. In this work, a charge-based mapping scheme has been adopted to include explicit electrostatic interactions and benchmarked against two typical polymers, atactic poly(methyl methacrylate) (PMMA) and polystyrene (PS). The CG potentials are parameterized against the oligomer bulks of nine monomers per chain to match the essential structural features and the two basic pressure-volume-temperature (PVT) properties, which are obtained from the all-atomistic (AA) molecular dynamics (MD) simulations at a single elevated temperature. The so-parameterized CG potentials are extended with the MD method to simulate the two polymer bulks of one hundred monomers per chain over a wide temperature range. Without any scaling, all the simulated results, including mass densities and bulk moduli at room temperature, thermal expansion coefficients at rubbery and glassy states, and glass transition temperatures (T_g), compare well with the corresponding experimental data. The proposed scheme not only contributes to realistically simulating various thermomechanical properties of both apolar and polar polymers but also allows for directly simulating their electrical properties.

Modeling the Effects of Module Size and Material Property on Thermoelectric Generator Power

It is known that thermoelectric power generators (TEGs) can utilize geothermal resources and recycle waste heat. It is vital to improve the thermoelectric power generation efficiency to economically and efficiently use these thermal resources. In this paper, ANSYS was used to build a three-dimensional model of a very simple TEG with only one pair of p- and n-legs (1-PN-TEG) to find the optimal design. The thickness of the semiconductor elements, the cross-sectional area of p- and n-type semiconductor elements, the heat insulation material, the thickness of copper sheet, and other factors were analyzed to study their effects on the power output of 1-PN-TEG. The results show that the power of TEG increases first and then decreases with the thickness of p- and n-legs (H); the maximum power existed at a specific value of H. The power increases when the cross-sectional areas of p- and n-type semiconductor elements become more extensive, but the power per area decreases. Furthermore, the power increases with the volume of p- and n-type semiconductor elements and tends to be stabilized finally. This observation may be used to estimate how much thermoelectric material is required to generate a specific value of TEG power. The gaps between p- and n-type semiconductor elements were filled with different heat insulation materials. The heat insulation material with lower thermal conductivity had a greater power output. The thickness of the copper sheet, as a conductor between p- and n-type semiconductor elements, was also investigated. The maximum power value was reached when the thickness of the copper sheet was equal to about 1.0 mm. All of the results obtained in this paper might provide a theoretical basis for the configuration and design optimization of a thermoelectric generator, making more efficient use of geothermal resources and the waste heat.

Adaptive Neural Network Finite-Time Control for Multi-Input and Multi-Output Nonlinear Systems With Positive Powers of Odd Rational Numbers

This article investigates the adaptive neural network (NN) finite-time output tracking control problem for a class of multi-input and multi-output (MIMO) uncertain nonlinear systems whose powers are positive odd rational numbers. Such designs adopt NNs to approximate unknown continuous system functions, and a controller is constructed by combining backstepping design and adding a power integrator technique. By constructing new iterative Lyapunov functions and using finite-time stability theory, the closed-loop stability has been achieved, which further verifies that the entire system possesses semiglobal practical finite-time stability (SGPFS), and the tracking errors converge to a small neighborhood of the origin within finite time. Finally, a simulation example is given to elaborate the effectiveness and superiority of the developed.

Long non‑coding RNA RP1‑163G9.1 is downregulated in gastric adenocarcinoma and is associated with a poor prognosis

The aim of the present study was to investigate the expression, function and underlying molecular mechanism of the long non‑coding (lnc) RNA RP1‑163G9.1 in patients with gastric adenocarcinoma (GA). The expression levels of lncRNA RP1‑163G9.1 were determined in 112 paired clinical GA tissues by reverse transcription‑quantitative polymerase chain reaction analysis. Subsequently, the potential clinical values of lncRNA RP1‑163G9.1 were analyzed with statistical methods. Additionally, the function of lncRNA RP1‑163G9.1 was explored at the cellular level using the Cell Counting Kit‑8 proliferation assay, Transwell experiments, fluorescence in situ hybridization (FISH), colony formation assay and flow cytometry. Furthermore, the function of lncRNA RP1‑163G9.1 was assessed in vivo using subcutaneous tumorigenesis experiments in nude mice. lncRNA RP1‑163G9.1 expression in GA tissues and cells was significantly decreased when compared with that in control gastric tissues (P<0.001) or gastric epithelial cells GES‑1 (P<0.05). This finding was associated with the depth of invasion (P=0.001), lymph node metastasis (P=0.009), tumor size (P=0.037) and immunocytochemistry marker Ki‑67 (P=0.010). FISH detection demonstrated that lncRNA RP1‑163G9.1 was primarily located in the cytoplasm. Notably, overexpression of lncRNA RP1‑163G9.1 significantly decreased cell proliferation (P<0.01), colony formation (P<0.01), invasion (P<0.01) and the number of cells at the S‑phase of the cell cycle (P<0.05); However, it did not exert a significant effect on apoptosis (P>0.05). Furthermore, tumor formation experiments revealed that overexpression of lncRNA RP1‑163G9.1 inhibited cancer cell proliferation in nude mice. The present research indicated that low expression of lncRNA RP1‑163G9.1 may be associated with enhanced tumor proliferation and invasion in GA.

Improved PSO_AdaBoost Ensemble Algorithm for Imbalanced Data

The Adaptive Boosting (AdaBoost) algorithm is a widely used ensemble learning framework, and it can get good classification results on general datasets. However, it is challenging to apply the AdaBoost algorithm directly to imbalanced data since it is designed mainly for processing misclassified samples rather than samples of minority classes. To better process imbalanced data, this paper introduces the indicator Area Under Curve (AUC) which can reflect the comprehensive performance of the model, and proposes an improved AdaBoost algorithm based on AUC (AdaBoost-A) which improves the error calculation performance of the AdaBoost algorithm by comprehensively considering the effects of misclassification probability and AUC. To prevent redundant or useless weak classifiers the traditional AdaBoost algorithm generated from consuming too much system resources, this paper proposes an ensemble algorithm, PSOPD-AdaBoost-A, which can re-initialize parameters to avoid falling into local optimum, and optimize the coefficients of AdaBoost weak classifiers. Experiment results show that the proposed algorithm is effective for processing imbalanced data, especially the data with relatively high imbalances.

The Arabidopsis GORK K+-channel is phosphorylated by calcium-dependent protein kinase 21 (CPK21), which in turn is activated by 14-3-3 proteins

Potassium (K⁺) is a vital ion for many processes in the plant and fine-tuned ion channels control the K⁺-fluxes across the plasma membrane. GORK is an outward-rectifying K⁺-channel with important functions in stomatal closure and in root K⁺-homeostasis. In this study, post-translational modification of the Arabidopsis GORK ion channel and its regulation by 14-3-3 proteins was investigated. To investigate the possible interaction between GORK and 14-3-3s an in vivo pull-down from an Arabidopsis protein extract with recombinant GORK C-terminus (GORK-C) indeed identified endogenous 14-3-3s (LAMBDA, CHI, NU) as binding partners in a phosphorylation dependent manner. However, a direct interaction between 14-3-3's and GORK-C could not be demonstrated. Since the pull-down of 14-3-3s was phosphorylation dependent, we determined GORK-C as substrate for CPK21 phosphorylation and identified three CPK21 phospho-sites in the GORK protein (T³⁴⁴, S⁵¹⁸ and S⁶⁴⁹). Moreover, interaction of 14-3-3 to CPK21 strongly stimulates its kinase activity; an effect that can result in increased GORK phosphorylation and change in activity. Using the non-invasive vibrating probe technique, we measured the predominantly GORK mediated salt induced K⁺-efflux from wild-type, gork, cpk21, aha2 and 14-3-3 mutant roots. The mutants cpk21 and aha2 did not show statistical significant differences compared to WT. However, two (out of six) 14-3-3 isoforms, CHI and PHI, have a clear function in the salt induced K⁺-efflux. In conclusion, our results show that GORK can be phosphorylated by CPK21 and suggest that 14-3-3 proteins control GORK activity through binding with and activation of CPK21.

Graphene coating on the surface of CoCrMo alloy enhances the adhesion and proliferation of bone marrow mesenchymal stem cells

The objective was to investigate whether a graphene coating could improve the surface bioactivity of a cobalt-chromium-molybdenum-based alloy (CoCrMo). Graphene was produced by chemical vapor deposition and transferred to the surface of the CoCrMo alloy using an improved wet transfer approach. The morphology of the samples was observed, and the adhesion force and stabilization of graphene coating were analyzed by a nanoscratch test and ultrasonication test. In an in vitro study, the adhesion and proliferation of bone marrow mesenchymal stem cells (BMSCs) cultured on the samples were quantified via an Alamar Blue assay and cell counting kit-8 (CCK-8) assay. The results showed that it is feasible to apply graphene to modify the surface of a CoCrMo alloy, and the enhancement of the adhesion and proliferation of BMSCs was also shown in the present study. In conclusion, graphene exhibits considerable potential for enhancing the surface bioactivity of CoCrMo alloy.

Evaluation of the osteogenesis and osseointegration of titanium alloys coated with graphene: an in vivo study

The aim of this study was to investigate whether a surface coating with graphene could enhance the surface bioactivation of titanium alloys (Ti6Al4V) to further accelerate in vivo osteogenesis and osseointegration at the implant surface. In this study, a New Zealand white rabbit femoral condyle defect model was established. After 4, 12 and 24 weeks, biomechanical testing, micro-computed tomography (Micro-CT) analyses and histological observations were performed. At the highest push-out forces during the test, microstructure parameters, such as the bone volume/total volume fraction (BV/TV) and mineral apposition rate (MAR), of the new bone were significantly higher in the graphene-coated Ti6Al4V group (G-Ti6Al4V) than in the Ti6Al4V group (P < 0.05). Van Gieson (VG) staining showed that the G-Ti6Al4V group had more new bone formation than the Ti6Al4V group, and the G-Ti6Al4V group showed a closer fit between the bone and implant. In conclusion, graphene might be a novel type of nano-coating material for enhancing the surface biological activity of Ti-based alloy materials and may further promote in vivo osteogenesis and osseointegration.

Thermal stability control system of photo-elastic interferometer in the PEM-FTs

A drifting model for the resonant frequency and retardation amplitude of a photo-elastic modulator (PEM) in the photo-elastic modulated Fourier transform spectrometer (PEM-FTs) is presented. A multi-parameter broadband-matching driving control method is proposed to improve the thermal stability of the PEM interferometer. The automatically frequency-modulated technology of the driving signal based on digital phase-locked technology is used to track the PEM's changing resonant frequency. Simultaneously the maximum optical-path-difference of a laser's interferogram is measured to adjust the amplitude of the PEM's driving signal so that the spectral resolution is stable. In the experiment, the multi-parameter broadband-matching control method is applied to the driving control system of the PEM-FTs. Control of resonant frequency and retardation amplitude stabilizes the maximum optical-path-difference to approximately 236 μm and results in a spectral resolution of 42 cm^-1. This corresponds to a relative error smaller than 2.16% (4.28 standard deviation). The experiment shows that the method can effectively stabilize the spectral resolution of the PEM-FTs.

Lanthanide ions-induced formation of hierarchical and transparent polysaccharide hybrid films

Nacre-like hybrid films based on N-succinyl chitosan (NSC), sodium alginate (SA) and lanthanide ions were fabricated via coordination interactions. In this work, the binary building blocks (NSC and SA) were self-assembled into aligned hydrogel films by coordination with lanthanide ions, and hierarchical NSC-SA hybrid films were obtained upon drying. Two species of lanthanide ions (Gd³⁺ and Yb³⁺) were used to fabricate the hierarchical NSC-SA hybrid films. The as-prepared NSC-SA hybrid films exhibit high tensile strength and stability. The tensile strength and toughness of as-prepared hybrid films reach 122.10MPa and 3.89MJm^-3, respectively. Meanwhile, the well-aligned lamellar microstructures also exhibit a good light transmittance. The highest light transmittance reaches 92% for NSC-SA hybrid films at 760nm. This fabrication method for hierarchical NSC-SA hybrid films is innovative due to the utilization of rare earth coordination bonding, and can serve as the basic strategy for the construction of high-performance composites in the near future.

Modulation axis performs circular motion in a 45° dual-drive symmetric photoelastic modulator

A 45° dual-drive symmetric photoelastic modulator is demonstrated. Two piezoelectric actuators are connected to a symmetric photoelastic crystal at an angle of 45°. When the amplitudes of the stress standing waves induced by the two piezoelectric actuators are equal and the phase difference between the two stress standing waves is π2, the modulation axis performs circular motion with a frequency of half of the photoelastic modulator's resonant frequency, while the retardation remains a constant that is determined at the driving voltage amplitudes. This reveals a new polarization modulation method. We have theoretically analyzed and experimentally observed the new polarization modulation, and the retardation calibration is also reported.

Well-defined and biocompatible hydrogels with toughening and reversible photoresponsive properties

In the present study, novel hydrogels with extremely high strength, reversible photoresponsive and excellent biocompatible properties were prepared. The functional hydrogels were synthesized from a well-defined poly (ethylene glycol) polymer with spiropyran groups at a given position (PEG-SP) via a Cu(i)-catalyst Azide-Alkyne Cycloaddition (CuAAC) reaction. The molecular structures of the sequential intermediates for PEG-SP hydrogel preparation were verified by (1)HNMR and FT-IR. The mechanical property, swelling ratio, compression strength, surface hydrophilicity, and biocompatibility of the resulting hydrogel were characterized. Since spiropyran is pivotal to the switch in hydrophilicity on the hydrogel surface, the swelling ratio of PEG-SP hydrogel under Vis irradiation has a major decrease (155%). Before and after UV light irradiation, the contact angle of the hydrogel has a change of 13.8°. The photoresponsive property of this hydrogel was thus demonstrated, and such a property was also shown to be reversible. The well-defined PEG-SP hydrogel can also sustain a compressive stress of 49.8 MPa without any macro- or micro-damage, indicating its outstanding mechanical performance. Furthermore, it possessed excellent biocompatibility as demonstrated by its performance in an in vivo porcine subcutaneous implantation environment. No inflammation was observed and it got along well with the adjacent tissue. The above features indicate that PEG-SP hydrogels are promising as an implantable matrix for potential applications in biomaterial.

Hierarchical alginate biopolymer papers produced via lanthanide ion coordination

A layered alginate-based biopolymer paper with a hierarchical structure and excellent mechanical properties was prepared via lanthanide ions coordination.

HCN channels are a novel therapeutic target for cognitive dysfunction in Neurofibromatosis type 1

Cognitive impairments are a major clinical feature of the common neurogenetic disease neurofibromatosis type 1 (NF1). Previous studies have demonstrated that increased neuronal inhibition underlies the learning deficits in NF1, however, the molecular mechanism underlying this cell-type specificity has remained unknown. Here, we identify an interneuron-specific attenuation of hyperpolarization-activated cyclic nucleotide-gated (HCN) current as the cause for increased inhibition in Nf1 mutants. Mechanistically, we demonstrate that HCN1 is a novel NF1-interacting protein for which loss of NF1 results in a concomitant increase of interneuron excitability. Furthermore, the HCN channel agonist lamotrigine rescued the electrophysiological and cognitive deficits in two independent Nf1 mouse models, thereby establishing the importance of HCN channel dysfunction in NF1. Together, our results provide detailed mechanistic insights into the pathophysiology of NF1-associated cognitive defects, and identify a novel target for clinical drug development.

Criteria for Applying the Lucas-Washburn Law

Spontaneous imbibition happens in many natural and chemical engineering processes in which the mean advancing front usually follows Lucas-Washburn’s law. However it has been found that the scaling law does not apply in many cases. There have been few criteria to determine under what conditions the Washburn law works. The effect of gravity on spontaneous imbibition in porous media was investigated both theoretically and experimentally. The mathematical model derived analytically was used to calculate the imbibition rates in porous media with different permeabilities. The results demonstrated that the effect of gravity on spontaneous imbibition was governed by the hydraulic conductivity of the porous media (permeability of the imbibition systems). The criteria for applying the Lucas-Washburn law have been proposed. The effect of gravity becomes more apparent with the increase in permeability or with the decrease in CGR number (the ratio of capillary pressure to gravity forces) and may be ignored when the CGR number is less than a specific value  ≅ 3.0. The effect of gravity on imbibition in porous media can be modeled theoretically. It may not be necessary to conduct spontaneous imbibition experiments horizontally in order to exclude the effect of gravity, as has been done previously.

Dynamic Proteomics: In Vivo Proteome-Wide Measurement of Protein Kinetics Using Metabolic Labeling

Control of biosynthetic and catabolic rates of polymers, including proteins, stands at the center of phenotype, physiologic adaptation, and disease pathogenesis. Advances in stable isotope-labeling concepts and mass spectrometric instrumentation now allow accurate in vivo measurement of protein synthesis and turnover rates, both for targeted proteins and for unbiased screening across the proteome. We describe here the underlying principles and operational protocols for measuring protein dynamics, focusing on metabolic labeling with (2)H2O (heavy water) combined with tandem mass spectrometric analysis of mass isotopomer abundances in trypsin-generated peptides. The core principles of combinatorial analysis (mass isotopomer distribution analysis or MIDA) are reviewed in detail, including practical advantages, limitations, and technical procedures to ensure optimal kinetic results. Technical factors include heavy water labeling protocols, optimal duration of labeling, clean up and simplification of sample matrices, accurate quantitation of mass isotopomer abundances in peptides, criteria for adequacy of mass spectrometric abundance measurements, and calculation algorithms. Some applications are described, including the noninvasive "virtual biopsy" strategy for measuring molecular flux rates in tissues through measurements in body fluids. In addition, application of heavy water labeling to measure flux lipidomics is noted. In summary, the combination of stable isotope labeling, particularly from (2)H2O, with tandem mass spectrometric analysis of mass isotopomer abundances in peptides, provides a powerful approach for characterizing the dynamics of proteins across the global proteome. Many applications in research and clinical medicine have been achieved and many others can be envisioned.

Functional characterization of the PCLO p.Ser4814Ala variant associated with major depressive disorder reveals cellular but not behavioral differences

Genome-wide association studies have suggested a role for a genetic variation in the presynaptic gene PCLO in major depressive disorder (MDD). As with many complex traits, the PCLO variant has a small contribution to the overall heritability and the association does not always replicate. One variant (rs2522833, p.Ser4814Ala) is of particular interest given that it is a common, nonsynonymous exon variant near a calcium-sensing part of PCLO. It has been suggested that the molecular effects of such variations penetrate to a variable extent in the population due to phenotypic and genotypic heterogeneity at the population level. More robust effects may be exposed by studying such variations in isolation, in a more homogeneous context. We tested this idea by modeling PCLO variation in a mouse knock-in model expressing the Pclo(SA)(/)(SA) variant. In the highly homogeneous background of inbred mice, two functional effects of the SA-variation were observed at the cellular level: increased synaptic Piccolo levels, and 30% increased excitatory synaptic transmission in cultured neurons. Other aspects of Piccolo function were unaltered: calcium-dependent phospholipid binding, synapse formation in vitro, and synaptic accumulation of synaptic vesicles. Moreover, anxiety, cognition and depressive-like behavior were normal in Pclo(SA)(/)(SA) mice. We conclude that the PCLO p.Ser4814Ala missense variant produces mild cellular phenotypes, which do not translate into behavioral phenotypes. We propose a model explaining how (subtle) cellular phenotypes do not penetrate to the mouse behavioral level but, due to genetic and phenotypic heterogeneity and non-linearity, can produce association signals in human population studies.

Higher order Arabidopsis 14-3-3 mutants show 14-3-3 involvement in primary root growth both under control and abiotic stress conditions

Arabidopsis 14-3-3 proteins are a family of conserved proteins that interact with numerous partner proteins in a phospho-specific manner, and can affect the target proteins in a number of ways; e.g. modification of enzymatic activity. We isolated T-DNA insertion lines in six 14-3-3 genes within the non-epsilon group that phylogenetically group in three closely related gene pairs. In total, 6 single, 3 double, 12 triple, and 3 quadruple mutants were generated. The mutants were phenotyped for primary root growth on control plates: single and double mutants were indistinguishable from WT, whereas six triples and all quadruples showed a shorter primary root. In addition, length of the first epidermal cell with a visible root hair bulge (LEH) was used to determine primary root elongation on medium containing mannitol and 1-aminocyclopropane-1-carboxylic acid (ACC). This analysis showed clear differences depending on the stress and 14-3-3 gene combinations. Next to the phenotypic growth analyses, a 14-3-3 pull-down assay on roots treated with and without mannitol showed that mannitol stress strongly affects the 14-3-3 interactome. In conclusion, we show gene specificity and functional redundancy among 14-3-3 proteins in primary root elongation under control and under abiotic stress conditions and changes in the 14-3-3 interactome during the onset of stress adaptation.

Application of carbon nanocatalysts in upgrading heavy crude oil assisted with microwave heating

Heavy crude oil can be upgraded to lighter oil using several techniques. However, current methods usually require high temperatures, long reaction duration, and cause serious environmental pollution. This study shows that by using carbon nanocatalysts, heavy crude oil can be efficiently upgraded to lighter oil at a relatively low temperature of about 150 °C. The temperature of crude oil was increased by microwave heating. The technique proposed in this study has the following advantages: (1) great viscosity reduction ratio over 96%, (2) short reaction time (less than 1 h), (3) low required temperature, and (4) long viscosity regression time. Because of these advantages, upgrading heavy crude oil to light oil can be cheaper and more environment-friendly.

Frequency of developmental dysplasia of the hip in breech-presented Chinese neonates in Hong Kong

OBJECTIVES. To clarify the use of ultrasonography by determining the frequency of developmental dysplasia of the hip among breech-presented Chinese neonates in Hong Kong. DESIGN. Prospective case series. SETTING. Regional hospital, Hong Kong. PATIENTS. All breech-presented Chinese neonates born during January 2008 to June 2009 were included (except premature neonates). They were examined clinically from birth till the age of 1 year. Ultrasound of the hips was performed at the age of 2 weeks, and X-ray of the pelvis at the age of 1 year. RESULTS. A total of 209 breech-presented neonates were born during the study period; 110 neonates completed all necessary investigations and follow-up. Among the latter, there were three neonates with developmental dysplasia of the hip warranting treatment, which amounted to a frequency of 2.7%. CONCLUSION. Developmental dysplasia of the hip among breech-presented Chinese babies is only slightly less common than in corresponding populations in other regions in the world. Since early diagnosis is important, ultrasonography screening in high-risk cases such as those with breech presentation may be useful.

Association between the rs1050450 glutathione peroxidase-1 (C > T) gene variant and peripheral neuropathy in two independent samples of subjects with diabetes mellitus

Glutathione peroxidase-1 (GPx-1) is an endogenous anti-oxidant enzyme. The T allele of the GPx-1 rs1050450 (C > T) gene variant is associated with reduced enzyme activity. Our aim was to examine the association between this gene variant and peripheral neuropathy in two cross-sectional samples of subjects with diabetes: (i) 773 Caucasian subjects were genotyped from the UCL Diabetes and Cardiovascular disease Study (UDACS) and (ii) 382 Caucasian subjects from the Ealing Diabetes Study (EDS). Peripheral neuropathy status (and oxidised-LDL [Ox-LDL:LDL] and plasma Total Ant-ioxidant Status [TAOS] in UDACS), were analysed in relation to genotype. We observed that: (i) In UDACS, the odds ratio (OR) for peripheral neuropathy in the T allele carriers compared to the CC genotype was 1.61 [1.10-2.28], p = 0.01. This remained significant after adjustment for other risk factors. Ox-LDL:LDL ratio was significantly elevated in T allele carriers (CC vs. CT/TT: 16.3 ± 2.4 v 18.0 ± 2.9 U/mmol LDL, p = 0.02). (ii) In EDS, the OR for peripheral neuropathy in the T allele carriers compared to the CC genotype was 1.95 [1.11-3.42], p = 0.02. This remained significant after adjustment for other risk factors. In conclusion, we observed a significant association between the T allele and peripheral neuropathy and LDL oxidation. This is the first paper to examine the rs1050450 variant in two samples of Caucasian subjects with diabetes. Prospective analysis of the gene variant is required in diabetic and healthy cohorts with measured plasma markers of oxidative stress to investigate the described association further.

More general capillary pressure and relative permeability models from fractal geometry

More general capillary pressure and relative permeability models were derived theoretically from fractal modeling of a porous medium. It was found that the new capillary pressure model could be reduced to the frequently-used Brooks-Corey capillary pressure model and the Li-Horne imbibition model when the fractal dimension of a porous medium takes specific values. This also demonstrates that the Brooks-Corey model and the Li-Horne model have a further confirmed theoretical basis. Capillary pressure data measured using mercury intrusion techinque were used to verify the model. The results demonstrated that the new capillary pressure model could represent the capillary pressure curves in those rocks with fracures or with great heterogeneity while the existing models cannot. The new relative permeability models can be reduced to the Brooks-Corey relative permeability model in a specific case. It has been proved theoretically that the relative permeability of each phase in a smooth fracture is only a linear function of its own saturation. Relative permeability data were calculated using the new models and the model results were compared with experimental data measured using a steady-state technique. The comparison demonstrated that the relative permeability models and experimental results were consistent with each other.

Proteomics analysis of immuno-precipitated synaptic protein complexes

Synapses are key neuronal elements of the brain. They are responsible for transmission, integration, and storage of information between nerve cells. A synapse is considered as the most complex cellular organelle consisting of approximately 1500 of proteins that are interacting in an activity dependent manner. We have initiated a series of immuno-precipitation experiments in conjunction with LC-MS/MS analysis in order to gain better insight into the organization of the synapse. In particular, we focused on proteins that have been implicated previously in the process of neuroplasticity, i.e., the glutamate receptor (GluR2), scaffolding proteins (PSD-95 and CASK), voltage gated potassium (KCNQ2 and Kv4.2) and calcium (CaV beta4) channel subunits, the signalling protein (GIT1) and synaptic vesicle protein (synaptophysin). This study confirms the previous reported protein-protein interactions and furthermore detects novel interactors. In conjunction with the literature reported protein-protein interaction a simple synaptic protein interactome was constructed. This model implicates the potential interaction of distinct protein complexes, and the engagement of single proteins, especially the scaffolding proteins, in multiple protein complexes.

Magnetic resonance whole body imaging at 3 Tesla: feasibility and findings in a cohort of asymptomatic medical doctors

OBJECTIVES

To evaluate the feasibility of whole body imaging using a 3 Tesla magnetic resonance scanner without a contrast agent, and to study the prevalence of abnormal findings among a cohort of asymptomatic doctors.

DESIGN

Prospective study.

SETTING

Private hospital, Hong Kong.

PARTICIPANTS

A total of 132 asymptomatic medical doctors (111 men, 21 women), with a mean age of 56 (range, 38-82) years, volunteered for the study. They underwent corresponding whole body imaging at our hospital between October 2005 and February 2006. Imaging involved a 3 Tesla magnetic resonance scanner with 32 channels, parallel imaging, Total Imaging Matrix technology, a maximum gradient amplitude of 40 mT/m and a slew rate of 200 mT/m/ms (Magnetom Tim Trio, Siemens Medical Solution, Erlangen, Germany). The use of matrix coils enabled coverage of the whole body. No contrast agent was used.

MAIN OUTCOME MEASURES

Detection of abnormalities in asymptomatic, apparently healthy adults.

RESULTS

All examinations were completed successfully. The mean scan time per subject was 33 (standard deviation, 4) minutes. All subjects tolerated the examination well and overall imaging quality was satisfactory. A total of 124 (94%) subjects had positive findings, of whom 24 (18%) had further workup. Five (4%) subjects were found to have tumours, of which two (1.5%) were proven malignant. Our cancer detection rate was comparable to that of other reported whole body screening studies using contrast magnetic resonance imaging and positron emission tomography.

CONCLUSION

We demonstrated the feasibility of performing whole body imaging in 30 minutes, using 32-channel magnetic resonance imaging at 3 Tesla without a contrast agent or any ionising radiation.