Multitype Perception Method for Drug-Target Interaction Prediction.

With the growing popularity of artificial intelligence in drug discovery, many deep-learning technologies have been used to automatically predict unknown drug-target interactions (DTIs). A unique challenge in using these technologies to predict DTI is fully exploiting the knowledge diversity across different interaction types, such as drug-drug, drug-target, drug-enzyme, drug-path, and drug-structure types. Unfortunately, existing methods tend to learn the specifical knowledge on each interaction type and they usually ignore the knowledge diversity across different interaction types. Therefore, we propose a multitype perception method (MPM) for DTI prediction by exploiting knowledge diversity across different link types. The method consists of two main components: a type perceptor and a multitype predictor. The type perceptor learns distinguished edge representations by retaining the specifical features across different interaction types; this maximizes the prediction performance for each interaction type. The multitype predictor calculates the type similarity between the type perceptor and predicted interactions, and the domain gate module is reconstructed to assign an adaptive weight to each type perceptor. Extensive experiments demonstrate that our proposed MPM outperforms the state-of-the-art methods in DTI prediction.

Real-time imaging of traumatic brain injury using magnetic induction tomography.

Objective. Early diagnosis of traumatic brain injury (TBI) is crucial for its prognosis; however, traditional computed tomography diagnostic methods rely on large medical devices with an associated lag time to receive results. Therefore, an imaging modality is needed that provides real-time monitoring, can easily be carried out to assess the extent of TBI damage, and thus guides treatment.Approach. In the present study, an improved magnetic induction tomography (MIT) data acquisition system was used to monitor TBI in an animal model and distinguish the injury level. A pneumatically controlled cortical impactor was used to strike the parietal lobe of anesthetized rabbits two or three times under the same parameter mode to establish two different rabbit models of TBI. The MIT data acquisition system was used to record data and continuously monitor the brain for one hour without intervention.Main results. A target with increased conductivity was clearly observed in the reconstructed image. The position was relatively fixed and accurate, and the average positioning error of the image was 0.013 72 m. The normalized mean reconstruction value of all images increased with time. The slope of the regression line of the normalized mean reconstruction value differed significantly between the two models (p< 0.0001).Significance. This indicates that in the animal model, the unique features of MIT may facilitate the early monitoring of TBI and distinguish different degrees of injuries, thereby reducing the risk and mortality of associated complications.

Advances of deep learning in electrical impedance tomography image reconstruction.

Electrical impedance tomography (EIT) has been widely used in biomedical research because of its advantages of real-time imaging and nature of being non-invasive and radiation-free. Additionally, it can reconstruct the distribution or changes in electrical properties in the sensing area. Recently, with the significant advancements in the use of deep learning in intelligent medical imaging, EIT image reconstruction based on deep learning has received considerable attention. This study introduces the basic principles of EIT and summarizes the application progress of deep learning in EIT image reconstruction with regards to three aspects: a single network reconstruction, deep learning combined with traditional algorithm reconstruction, and multiple network hybrid reconstruction. In future, optimizing the datasets may be the main challenge in applying deep learning for EIT image reconstruction. Adopting a better network structure, focusing on the joint reconstruction of EIT and traditional algorithms, and using multimodal deep learning-based EIT may be the solution to existing problems. In general, deep learning offers a fresh approach for improving the performance of EIT image reconstruction and could be the foundation for building an intelligent integrated EIT diagnostic system in the future.

Adaptive threshold split Bregman algorithm based on magnetic induction tomography for brain injury monitoring imaging.

Objective. Traditional magnetic induction tomography (MIT) algorithms have problems in reconstruction, such as large area error (AE), blurred boundaries of reconstructed targets, and considerable image noise (IN). As the size and boundary of a lesion greatly affect the treatment plan, more accurate algorithms are necessary to meet clinical needs.Approach. In this study, adaptive threshold split Bregman (ATSB) is proposed for brain injury monitoring imaging in MIT. We established a 3D brain MIT simulation model with the actual anatomical structure and a phantom model and obtained the reconstructed images of single targets in different positions and multiple targets, using the Tikhonov, eigenvalue threshold regularisation (ETR), split Bregman (SB), and ATSB algorithms.Main results. Compared with the Tikhonov and ETR algorithms, the ATSB algorithm reduced the AE by 95% and the IN by 17% in a simulation and reduced the AE by 87% and IN by 6% in phantom experiments. Compared with the SB algorithm, the ATSB algorithm can reduce the difficulty of adjusting parameters and is easier to use in clinical practice. The simulation and phantom experiments results showed that the ATSB algorithm could reconstruct the target size more accurately and could distinguish multiple targets more effectively than the other three algorithms.Significance. The ATSB algorithm could improve the image quality of MIT and better meet the needs of clinical applications and is expected to promote brain injury monitoring imaging via MIT.

[A multifrequency time-difference electrical impedance tomography algorithm using spectral constraints].

This study aims to propose a multifrequency time-difference algorithm using spectral constraints. Based on the knowledge of tissue spectrum in the imaging domain, the fraction model was used in conjunction with the finite element method (FEM) to approximate a conductivity distribution. Then a frequency independent parameter (volume or area fraction change) was reconstructed which made it possible to simultaneously employ multifrequency time-difference boundary voltage data and then reduce the degrees of freedom of the reconstruction problem. Furthermore, this will alleviate the illness of the EIT inverse problem and lead to a better reconstruction result. The numerical validation results suggested that the proposed time-difference fraction reconstruction algorithm behaved better than traditional damped least squares algorithm (DLS) especially in the noise suppression capability. Moreover, under the condition of low signal-to-noise ratio, the proposed algorithm had a more obvious advantage in reconstructions of targets shape and position. This algorithm provides an efficient way to simultaneously utilize multifrequency measurement data for time-difference EIT, and leads to a more accurate reconstruction result. It may show us a new direction for the development of time-difference EIT algorithms in the case that the tissue spectrums are known.

Preparation and characterization of reinforced starch-based composites with compatibilizer by simple extrusion.

Because of the poor performance of starch-based composites, we prepared the starch-based composites with good mechanical properties by a simple two-step melt-blending extrusion. Glycerol and nano-SiO2 were firstly introduced into starch to prepare the TPS/nano-SiO2 composite by the first extrusion, and poly(butylene adipate-co-terephthalate) (PBAT) and the compatibilizers were then incorporated to obtain the improved composites by the second extrusion. The mechanical properties, thermal properties, morphology, and structure of the composites were characterized. The results showed that the strength dramatically increased after the addition of nano-SiO2 into starch, and the elongation at break was significantly improved by the incorporation of PBAT. The tensile strength was increased distinctly after the addition of the compatibilizers. All the composites exhibited good mechanical properties. The melting transition, the thermal stability, and the crystalline structure did not change with the additives, whereas the glass transition of the starch-rich phase shifted to a lower temperature. The results indicated that the combined compatibilizers had better compatibilization than each one alone.

Super-strong and tough poly(vinyl alcohol)/poly(acrylic acid) hydrogels reinforced by hydrogen bonding.

Synthetic hydrogels or water-containing polymeric materials are much inferior to biological tissues and solid plastics in many aspects of mechanical properties; it is a great challenge to develop hydrogels with mechanical properties comparable with or even superior to those of biological tissues and plastics. Here, we report a type of super-strong and tough hydrogen-bonded poly(vinyl alcohol)/poly(acrylic acid) (PVA/PAA) hydrogel by immersing as-prepared PVA hydrogels in aqueous PAA solutions and then cold-drawing the hydrogels to different strains. The immersing process introduces PAA chains into the PVA hydrogels, which increases the cross-linking density by hydrogen bonding and hence, much improved mechanical properties and low water contents (35.9-40.2 wt%) are observed. The cold-drawing orients the polymer chains, which enables the formation of more and stronger hydrogen bonds. The mechanical properties of cold-drawn gels are dramatically enhanced, with tensile strength and elastic modulus up to 140 and 100 MPa, respectively; also, super-high toughness (117 MJ m-3) and fracture energy (101 kJ m-2) are obtained. Very impressively, the ultra-high tensile strengths of the cold-drawn hydrogels are superior to those of biological tissues and most solid engineered plastics. Characterizations and comparative studies prove that the enhancement of mechanical properties is mainly due to the formation of more hydrogen bonding rather than the loss of water or the change in crystallinity. This study provides a new strategy for preparing super-strong physically cross-linked hydrogels and other polymeric materials. This super-strong and tough hydrogel may find potential applications in biomedical and load-bearing fields.

Gelation of Na-alginate aqueous solution: A study of sodium ion dynamics via NMR relaxometry.

Sodium alginate (SA) hydrogels have a wide range of applications including tissue engineering, drug delivery and formulations for preventing gastric reflux. The dynamics of sodium ions during the gelation process of SA solution is critical for clarification of the gelation procedure. In this work, nuclear magnetic resonance (NMR) relaxometry and pulsed-field-gradient (PFG) NMR diffusometry were used to investigate the dynamics of the sodium ions during the gelation of SA alginate. We find that sodium ions are in two different states with the addition of divalent calcium ions, corresponding to Ca2+ crosslinked and un-crosslinked regions in the hydrogels. The sodium ions within the un-crosslinked regions are those released from the alginate chains without Ca2+ crosslinking. The relative content of sodium ions within the Ca2+ crosslinked regions decreased with the increase in the content of calcium ions in the system. The relaxation time T2 of sodium ions within the Ca2+ crosslinked and un-crosslinked regions shift to shorter and longer relaxation time with the increase in concentration of calcium ion, which indicates the closer package of SA chains and the larger space for the diffusion of free sodium ions. This work clarifies the dynamics of 23Na+ in a calcium alginate gel at the equilibrium state.

Dissolution and Metastable Solution of Cellulose in NaOH/Thiourea at 8 °C for Construction of Nanofibers.

To develop a facile approach for the dissolution of cellulose, a novel solvent (9.3 wt % NaOH/7.4 wt % thiourea aqueous solution) was used, for the first time, to dissolve cellulose within 5 min at 8 °C. The results of NMR and Raman spectra demonstrated that stable thiourea···OH- complexes were formed through strong hydrogen bonds in NaOH/thiourea at room temperature. Moreover, the strength of the hydrogen bonds in thiourea···OH- complexes was much higher than that in urea···OH- complexes, and the number of thiourea···OH- complexes increased significantly in 9.3 wt % NaOH/7.4 wt % thiourea compared to that in 9.5 wt % NaOH/4.5 wt % thiourea, which dissolved cellulose at -5 °C, leading to the dissolution of cellulose at a relatively high temperature (8 °C). The cellulose that dissolved at such a high temperature was metastable. The results of dynamic light scattering and transmission electron microscope experiments confirmed that the extended cellulose chains and their aggregates coexisted in the dilute cellulose solution. Interestingly, stiff cellulose chains could be self-assembled in parallel to form nanofibers in the metastable cellulose solution, from which cellulose microspheres consisting of nanofibers could be easily produced by inducing heating. This work not only proposed a novel method for the dissolution of cellulose in aqueous system at temperatures over 0 °C but also opened up a new pathway for the construction of nanofibrous cellulose materials.

Thermal sensitivity and protein anti-adsorption of hydroxypropyl cellulose-g- poly(2-(methacryloyloxy) ethyl phosphorylcholine).

Zwitterionic graft copolymers, hydroxypropyl cellulose graft poly(2-(methacryloyloxy) ethyl phosphorylcholine) (HPC-g-PMPC) with well-defined architecture were synthesized by atom transfer radical polymerization (ATRP). The self-assembly behaviors and thermal sensitivity of HPC-g-PMPC copolymers and their correlations with graft density and side chain length were investigated in details. HPC-g-PMPC copolymers can self-assemble into spherical aggregate structure above the critical aggregation concentration (CAC) at room temperature. Meanwhile, the size of the aggregates mainly depended on the graft density. The obtained aggregates were thermal sensitive and their low critical solution temperature (LCST) was efficiently regulated by varying the graft density. Above the LCST, the aggregates were transferred into aggregates with core-shell structure, in which the HPC rich core was stabilized by the PMPC rich shell. The interaction between the HPC-g-PMPC aggregates and BSA was investigated. The results indicated that the anti-adsorption of BSA on the aggregates surface depended on the length and graft density of the PMPC zwitterionic side chains.

Reversible redox activity of ferrocene functionalized hydroxypropyl cellulose and its application to detect H2O2.

Novel ferrocene functionalized hydroxypropyl cellulose (HPC-Fc) were prepared by azide-alkyne cycloaddition and characterized. HPC-Fc exhibits an excellent reversible redox activity and could establish amazing electron transfer ability between enzyme and electrode. HPC-Fc and horseradish peroxidase (HRP) were coated on a platinized carbon electrode to prepare an amperometric biosensor for hydrogen peroxide (H2O2) detection. The amperometric response was measured as a function of H2O2 concentration at a fixed potential of 0.35V in 100mM phosphate buffer solution (pH 7.0). The novel biosensor exhibits a fast linear response toward H2O2 in the range of 0.1-8µM with sensitivity of 4.21nA/µM. Moreover, the enzyme assays measured by the spectrophotometer method confirm that abundant hydroxyl groups of HPC backbones are conductive for HRP to maintaining or even enhancing their activity. The redox active HPC-Fc with the unique properties of both ferrocene and cellulose is a good candidate for biosensor applications.

Bacterial Cellulose Supported Gold Nanoparticles with Excellent Catalytic Properties.

Amidoxime surface functionalized bacterial cellulose (AOBC) has been successfully prepared by a simple two-step method without obviously changing the morphology of bacterial cellulose. AOBC has been used as the reducing agent and carrier for the synthesis of gold nanoparticles (AuNPs) that distributed homogeneously on bacterial cellulose surface. Higher content in amidoxime groups in AOBC is beneficial for the synthesis of AuNPs with smaller and more uniform size. The AuNPs/AOBC nanohybrids have excellent catalytic activity for reduction of 4-nitrophenol (4-NP) by using NaBH4. It was found that catalytic activity of AuNPs/AOBC first increases with increasing NaBH4 concentration and temperature, and then leveled off at NaBH4 concentration above 238 mM and temperature above 50 °C. Moreover, AuNPs with smaller size have higher catalytic activity. The highest apparent turnover frequency of AuNPs/AOBC is 1190 h(-1). The high catalytic activity is due to the high affinity of 4-NP with AuNPs/AOBC and the reduced product 4-aminophenol has good solubility in water in the presence of AuNPs/AOBC. The catalytic stability of the AuNPs/AOBC was estimated by filling a fluid column contained AuNPs/AOBC and used for continuously catalysis of the reduction of 4-NP by using NaBH4. The column works well without detection of 4-NP in the eluent after running for more than two months, and it is still running. This work provides an excellent catalyst based on bacterial cellulose stabilized AuNPs and has promising applications in industry.

Static imaging of the electrical impedance tomography on cylinder physical phantom.

Static imaging of the electrical impedance tomography can obtain the absolute electrical conductivity distribution at one section of the subject. The test is performed on a cylinder physical phantom in which slim rectangle, hollow cylinder, small rectangle or three cylinders are selected to simulate complex conductivity perturbation objects. The measurement data is obtained by a data acquisition system with 32 compound electrodes. A group of static images of conductivity distribution in the cylinder phantom are reconstructed by the modified Newton-Raphson algorithm with two kinds of regularization methods. The results show correct position, size, conductivity difference, and similar shape of the perturbation objects in the images.

Ultrathin core-sheath fibers for liposome stabilization.

Ultrathin core-sheath fibers with small unilamellar vesicles (SUVs) in the core were prepared by coaxial electrospinning. SUVs/sodium hyaluranate (HA-Na)/water and polyvinylpyrrolidone (PVP)/ethanol solutions were used as core and sheath fluid in electrospinning, respectively. The ultrathin fibers were characterized by scanning and transmission electron microscopy (SEM and TEM) and laser scanning confocal microscopy (LSCM). The SUVs were successfully encapsulated in the core HA-Na matrix of the ultrathin fibers and are in the elliptic shape. The SUVs encapsulated in the core matrix of the ultrathin fibers have an excellent stability. The SUVs embedded in the ultrathin fibers are stable. When the ultrathin fibers were re-dissolved in water after one-month storage at room temperature, the rehydrated SUVs have the similar size and size distribution as the as-prepared SUVs. The liposome-loaded ultrathin fiber mats have the promising applications in wound healing materials.

Intermolecular interactions and 3D structure in cellulose-NaOH-urea aqueous system.

The dissolution of cellulose in NaOH/urea aqueous solution at low temperature is a key finding in cellulose science and technology. In this paper, (15)N and (23)Na NMR experiments were carried out to clarify the intermolecular interactions in cellulose/NaOH/urea aqueous solution. It was found that there are direct interactions between OH(-) anions and amino groups of urea through hydrogen bonds and no direct interaction between urea and cellulose. Moreover, Na(+) ions can interact with both cellulose and urea in an aqueous system. These interactions lead to the formation of cellulose-NaOH-urea-H2O inclusion complexes (ICs). (23)Na relaxation results confirmed that the formation of urea-OH(-) clusters can effectively enhance the stability of Na(+) ions that attracted to cellulose chains. Low temperature can enhance the hydrogen bonding interaction between OH(-) ions and urea and improve the binding ability of the NaOH/urea/H2O clusters that attached to cellulose chains. Cryo-TEM observation confirmed the formation of cellulose-NaOH-urea-H2O ICs, which is in extended conformation with mean diameter of about 3.6 nm and mean length of about 300 nm. Possible 3D structure of the ICs was proposed by the M06-2X/6-31+G(d) theoretical calculation, revealing the O3H···O5 intramolecular hydrogen bonds could remain in the ICs. This work clarified the interactions in cellulose/NaOH/urea aqueous solution and the 3D structure of the cellulose chain in dilute cellulose/NaOH/urea aqueous solution.

Controlled release of liposome-encapsulated Naproxen from core-sheath electrospun nanofibers.

Naproxen (NAP) loaded nanofibers of different structures have been successfully prepared by electrospinning. The structures of the nanofibers are NAP and cellulose acetate (CA) mixed nanofibers (NF-1), nanofibers with NAP/CA mixed core and CA sheath (NF-2), and NAP loaded liposomes and sodium hyaluronate (HA-Na) mixed core with CA sheath (NF-3). The structure and morphology of the nanofibers were characterized and the drug release behaviors were investigated. It was found that NAP can disperse in the HA-Na or CA matrix in molecular level without formation of NAP crystals and dimers. The drug release behaviors of NF-1 and NF-2 show a non-Fickian diffusion mechanism, while the NF-3 shows a specific drug release behavior with a burst release within 8h followed by a sustained drug release for 12 days. The particular two-stage drug release behavior of NF-3 nanofibers offers the materials promising applications as wound dressing materials.

Dissolution mechanism of cellulose in N,N-dimethylacetamide/lithium chloride: revisiting through molecular interactions.

Understanding the interactions between solvent molecules and cellulose at a molecular level is still not fully achieved in cellulose/N,N-dimethylacetamide (DMAc)/LiCl system. In this paper, cellobiose was used as the model compound of cellulose to investigate the interactions in cellulose/DMAc/LiCl solution by using Fourier transform infrared spectroscopy (FTIR), (13)C, (35)Cl, and (7)Li nuclear magnetic resonance (NMR) spectroscopy and conductivity measurements. It was found that when cellulose is dissolved in DMAc/LiCl cosolvent system, the hydroxyl protons of cellulose form strong hydrogen bonds with the Cl(-), during which the intermolecular hydrogen bonding networks of cellulose is broken with simultaneous splitting of the Li(+)-Cl(-) ion pairs. Simultaneously, the Li(+) cations are further solvated by free DMAc molecules, which accompany the hydrogen-bonded Cl(-) to meet electric balance. Thereafter, the cellulose chains are dispersed in molecular level in the solvent system to form homogeneous solution. This work clarifies the interactions in the cellulose/DMAc/LiCl solution at molecular level and the dissolution mechanism of cellulose in DMAc/LiCl, which is important for understanding the principle for selecting and designing new cellulose solvent systems.

An effect of alginate on the stability of LDH nanosheets in aqueous solution and preparation of alginate/LDH nanocomposites.

Nanosheets under 10nm in thickness are obtained by exfoliating layered double hydroxide (LDH) in formamide. The LDH nanosheets are dispersed and stabilized in an alginate aqueous solution after removing formamide by water washing and ultracentrifugation. During the water washing stage LDH nanosheets can be prevented from restacking by electrostatic stabilization of the surface of LDH sheets through the adsorption of alginate. Alginate/LDH nanocomposites can be prepared by drying the dispersion, and sandwich-like structures in the nanocomposites are formed with two alginate layers contained between two LDH sheets. LDH nanosheets in the dried alginate/LDH nanocomposites can be re-dispersed in water. The thermal stability of alginate in the nanocomposite is increased by LDH. Alginate membranes containing this layered nanocomposite can be prepared. The addition of LDH into the alginate matrix leads to an increase in the mechanical properties of the nanocomposite.

Design and optimization of multi-class series-parallel linear electromagnetic array artificial muscle.

Skeletal muscle exhibiting complex and excellent precision has evolved for millions of years. Skeletal muscle has better performance and simpler structure compared with existing driving modes. Artificial muscle may be designed by analyzing and imitating properties and structure of skeletal muscle based on bionics, which has been focused on by bionic researchers, and a structure mode of linear electromagnetic array artificial muscle has been designed in this paper. Half sarcomere is the minimum unit of artificial muscle and electromagnetic model has been built. The structural parameters of artificial half sarcomere actuator were optimized to achieve better movement performance. Experimental results show that artificial half sarcomere actuator possesses great motion performance such as high response speed, great acceleration, small weight and size, robustness, etc., which presents a promising application prospect of artificial half sarcomere actuator.

Real-time imaging of cerebral infarction in rabbits using electrical impedance tomography.

OBJECTIVE: To investigate the possible use of electrical impedance tomography (EIT) in monitoring focal cerebral infarction in a rabbit model. METHODS: A model of focal cerebral infarction was established in eight New Zealand rabbits using a photochemical method without craniectomy. Focal cerebral infarction was confirmed by histopathological examination. Intracranial impedance variation was measured using 16 electrodes placed in a circle on the scalp. EIT images were obtained using a damped least-squares reconstruction algorithm. The average resistivity value (ARV) of the infarct region on EIT images was calculated to quantify relative resistivity changes. A symmetry index was calculated to evaluate the relative difference in resistivity between the two sides of the cerebrum. RESULTS: EIT images and ARV curves showed that impedance changes caused by cerebral infarction increased linearly with irradiation time. A difference in ARV was found between measurements taken before and after infarct induction. CONCLUSIONS: Focal cerebral infarction can be monitored by EIT in the proposed animal model. The results are sufficiently encouraging that the authors plan to extend this study to humans, after further technical improvements.