Mechanical Field Guiding Structure Design Strategy for Meta-Fiber Reinforced Hydrogel Composites by Deep Learning.

Fiber-reinforced hydrogel composites are widely employed in many engineering applications, such as drug release, and flexible electronics, with more flexible mechanical properties than pure hydrogel materials. Comparing to the hydrogel strengthened by continuous fiber, the meta-fiber reinforced hydrogel provides stronger individualized design ability of deformation patterns and tunable stiffness, especially for the elaborate applications in joint, cartilage, and organ. In this paper, a novel structure design strategy based on deep learning algorithm is proposed for hydrogel reinforced by meta-fiber to achieve targeted mechanical properties, such as stress and displacement fields. A solid mechanic model for meta-fiber reinforced hydrogel is first developed to construct the dataset of fiber distribution and the corresponding mechanical properties of the composite. Generative adversarial network (GAN) is then trained to characterize the relationship between stress or displacement field, and meta-fiber distribution. The well-trained GAN is implemented to design meta-fiber reinforced hydrogel composite structure under specific operation conditions. The results show that the deep learning method may efficiently predict the structure of the hydrogel composite with satisfied confidence, and has great potential for applications in drug delivery and flexible electronics.

Reinforcement hybridization in staggered composites enhances wave attenuation performance.

Advanced composites with superior wave attenuation or vibration isolation capacity are in high demand in engineering practice. In this study, we develop the hybrid dynamic shear-lag model with Bloch's theorem to investigate the hybrid effect of reinforcement on wave attenuation in bioinspired staggered composites. We present for the first time the relationship between macroscopic wave filtering and hybridization of building blocks in staggered composites. Viscoelasticity was taken into account for both reinforcement and matrix to reflect the damping effect on wave transmission. Our findings indicate that reinforcement hybridization significantly enhances wave attenuation performance through two critical parameters: the linear stiffness and linear density of reinforcements. For purely elastic constituents, reinforcement hybridization consistently improves wave attenuation by reducing the initial frequency of the first bandgap and broadening it. For viscoelastic constituents, increasing the heterogeneity of reinforcements can benefit wave attenuation, particularly in ultralow frequency regimes, due to the strengthening of the damping effect. Our case study demonstrates that controlling the difference in linear density can result in up to a 59 % reduction in energy transmission. Our analysis suggests that hybridizing reinforcements could provide a new approach to designing and synthesizing advanced composites with exceptional wave attenuation performance.

Efficient characterization of double-cross-linked networks in hydrogels using data-inspired coarse-grained molecular dynamics model.

The network structure within polymers significantly influences their mechanical properties, including their strength, toughness, and fatigue resistance. All-atom molecular dynamics (AAMD) simulations offer a method to investigate the energy dissipation mechanism within polymers during deformation and fracture; Such an approach is, however, computationally inefficient when used to analyze polymers with complex network structures, such as the common chemically double-networked hydrogels. Alternatively, coarse-grained molecular dynamics (CGMD) models, which reduce the computational degrees of freedom by concentrating a set of adjacent atoms into a coarse-grained bead, can be employed. In CGMD simulations, a coarse-grained force field (CGFF) is a critical factor affecting the simulation accuracy. In this paper, we proposed a data-based method for predicting the CGFF parameters to improve the simulation efficiency of complex cross-linked network in polymers. Here, we utilized a typical chemically double-networked hydrogel as an example. An artificial neural network was selected, and it was trained with the tensile stress-strain data from the CGMD simulations using different CGFF parameters. The CGMD simulations using the predicted CGFF parameters show good agreement with the AAMD simulations and are almost fifty times faster. The data-inspired CGMD model presented here broadens the applicability of molecular dynamics simulations to cross-linked polymers and has the potential to provide insights that will aid the design of polymers with desirable mechanical properties.

Stress softening of nanoparticle-crosslinked hydrogels described using a physics-based damage model.

Despite the promising applications of hydrogels, their poor mechanical properties still greatly limit their further applications. To improve the mechanical properties of hydrogels, various strategies have been proposed. Hydrogels with nanoparticle-crosslinked polymer networks show excellent toughness, self-recovery, and other advantages, and thus have great prospects for use in tissue engineering, artificial muscles, flexible electronics, and other fields. There have been experimental and theoretical studies of its damage. However, the underlying microscale physical mechanisms have not been fully elucidated. Herein, we established a physics-based constitutive model to describe the mechanical behavior of nanoparticle-crosslinked hydrogels under cyclic loading. The deformation-induced damage and the rate-dependent damage were explained by the network alteration and kinetics of chain dissociation/association, respectively. The kinetics dissociation/association theory was modified considering the polymer chains that wind around nanoparticles. The Mullins stress softening and recovery during cyclic loading were described. Cyclic loading tests on nanoparticle-crosslinked hydrogels were carried out to verify the proposed constitutive model. It is demonstrated that the model can well describe the mechanical behavior of nanoparticle-crosslinked hydrogels during cyclic loading.

Direct Targeting of CREB1 with Imperatorin Inhibits TGFß2-ERK Signaling to Suppress Esophageal Cancer Metastasis.

Metastasis accounts for 90% of cancer death worldwide, and effective therapeutic strategies are lacking. The aim of this work is to identify the key drivers in tumor metastasis and screen therapeutics for treatment of esophageal squamous cell carcinoma (ESCC). Gene Ontology analysis of The Cancer Genome Atlas (TCGA) gene expression datasets of ESCC patients with or without lympy metastasis identifies that TGFß2 is highly enriched in the pathways essential for tumor metastasis and upregulates in the metastatic ESCC tumors. High TGFß2 expression in ESCC correlates with metastasis and patient survival, and functionally contributes to tumor metastasis via activating extracellular signal-regulated kinases (ERK) signaling. By screening of a library consisting of 429 bioactive compounds, imperatorin is verified as a novel TGFß2 inhibitor, with robustly suppressive effect on tumor metastasis in multiple mice models. Mechanistically, direct binding of imperatorin and CREB1 inhibits phosphorylation, nuclear translocation of CREB1, and its interaction with TGFß2 promoter, represses TGFß2 expression and fibroblasts-secreted CCL2, and then inactivates ERK signaling to block cancer invasion and abrogates the paracrine effects of fibroblasts on tumor angiogenesis and metastasis. Overall, the findings suggest the use of TGFß2 as a diagnostic and prognostic biomarker and therapeutic target in ESCC, and supports the potential of imperatorin as a novel therapeutic strategy for cancer metastasis.

Identification of miR-29c and its Target FBXO31 as a Key Regulatory Mechanism in Esophageal Cancer Chemoresistance: Functional Validation and Clinical Significance.

Rationale: Dysregulated microRNA (miRNA) expressions in cancer can contribute to chemoresistance. This study aims to identify miRNAs that are associated with fluorouracil (5-FU) chemoresistance in esophageal squamous cell carcinoma (ESCC). The potential of miR-29c as a novel diagnostic, prognostic and treatment-predictive marker in ESCC, and its mechanisms and therapeutic implication in overcoming 5-FU chemoresistance were explored. Methods: The miRNA profiles of an ESCC cell model with acquired chemoresistance to 5-FU were analyzed using a Taqman miRNA microarray to identify novel miRNAs associated with 5-FU chemoresistance. Quantitative real-time PCR was used to determine miR-29c expression in tissue and serum samples of patients. Bioinformatics, gain- and loss-of-function experiments, and luciferase reporter assay were performed to validate F-box only protein 31 (FBXO31) as a direct target of miR-29c, and to identify potential transcription factor binding events that control miR-29c expression. The potential of systemic miR-29c oligonucleotide-based therapy in overcoming 5-FU chemoresistance was evaluated in tumor xenograft model. Results: MiR-29c, under the regulatory control of STAT5A, was frequently downregulated in tumor and serum samples of patients with ESCC, and the expression level was correlated with overall survival. Functional studies showed that miR-29c could override 5-FU chemoresistance in vitro and in vivo by directly interacting with the 3'UTR of FBXO31, leading to repression of FBXO31 expression and downstream activation of p38 MAPK. Systemically administered miR-29c dramatically improved response of 5-FU chemoresistant ESCC xenografts in vivo. Conclusions: MiR-29c modulates chemoresistance by interacting with FBXO31, and is a promising non-invasive biomarker and therapeutic target in ESCC.

Optimal modified performance of MIMO networked control systems with multi-parameter constraints.

The optimal modified performance of the multi-input multi-output (MIMO) networked control systems (NCSs) with encoding-decoding, channel noise in the forward channel and packet dropouts, quantization in the feedback channel is investigated in this paper. A new and efficient tracking performance index for the NCSs is presented which prevents variations in the tracking error where there is no integrator in the plant. The optimal modified performance is obtained by the method of coprime factorization and partial fraction. The results demonstrate that the optimal modified performance is related to the locations of the non-minimum phase (NMP) zeros, unstable poles of the given plant as well as their directions. In addition, the modified factor, packet dropouts probability, channel noise and encoding-decoding are also closely related to optimal modified performance of the NCSs. Finally, we present some particular examples to illustrate the theoretical results.

Micro-Mechanism of Interfacial Separation and Slippage of Graphene/Aluminum Nanolaminated Composites.

Due to their excellent properties and two-dimensional geometry, graphenes (Grs) have been widely used as reinforced fillers in graphene/aluminum nanolaminated composite (GANC). The separation and slippage behavior of the GANC is highly dependent on the interfacial properties between Gr and aluminum (Al). In this study, two interfacial failures of GANCs, i.e., pull-up failure and pull-out failure, were investigated using a molecular dynamics (MD) method. The effects of the crystal orientation of single-crystal Al component and the geometry of the Gr component on the normal and shear interfacial properties of the GANC were examined. It was evident that the interfacial pull-up resistance resulted from the atomic forces of all the atoms at the interface, whereas the interfacial shear force during pull-out stems from the atomic forces of the atoms at the crack tip. In addition, the studies revealed that the interface bonding strength between the Gr and Al was sensitive to both the crystal orientation of the Al and the environmental temperature. Finally, the cohesive law was used to describe the interfacial behavior of the Gr and Al, providing the interfacial data for the finite element modeling of composites with Gr and Al interface.

Synephrine Hydrochloride Suppresses Esophageal Cancer Tumor Growth and Metastatic Potential through Inhibition of Galectin-3-AKT/ERK Signaling.

A library consisting of 429 food-source compounds was used to screen the natural products with anticancer properties in esophageal squamous cell carcinoma (ESCC). We demonstrated for the first time that synephrine, an active compound isolated from leaves of citrus trees, markedly suppressed cell proliferation (inhibition rate with 20 µM synephrine at day 5:71.1 ± 5.8% and 75.7 ± 6.2% for KYSE30 and KYSE270, respectively) and colony formation (inhibition rate with 10 µM synephrine: 86.5 ± 5.9% and 82.3 ± 4.5% for KYSE30 and KYSE270, respectively), as well as migration (inhibition rate with 10 µM synephrine: 76.9 ± 4.4% and 62.2 ± 5.8% for KYSE30 and KYSE270, respectively) and invasion abilities (inhibition rate with 10 µM synephrine: 73.3 ± 7.5% and 75.3 ± 3.4% for KYSE30 and KYSE270, respectively) of ESCC cells in a dose-dependent manner, without significant toxic effect on normal esophageal epithelial cells. Mechanistically, quantitative proteomics and bioinformatics analyses were performed to explore the synephrine-regulated proteins. Western blot and qRT-PCR data indicated that synephrine may downregulate Galectin-3 to inactivate AKT and ERK pathways. In addition, we found that the sensitivity of ESCC to fluorouracil (5-FU) could be enhanced by synephrine. Furthermore, in vivo experiments showed that synephrine had significant antitumor effect on ESCC tumor xenografts in nude mice (inhibition rate with 20 mg/kg synephrine is 61.3 ± 20.5%) without observed side effects on the animals. Taken together, synephrine, a food-source natural product, may be a potential therapeutic strategy in ESCC.

New Coarse-Grained Model and Its Implementation in Simulations of Graphene Assemblies.

Graphene is a one-atom thick layer of carbon atoms arranged in a hexagonal pattern, which makes it the strongest material in the world. The Tersoff potential is a suitable potential for simulating the mechanical behavior of the complex covalently bonded system of graphene. In this paper, we describe a new coarse-grained (CG) potential, TersoffCG, which is based on the function form of the Tersoff potential. The TersoffCG applies to a CG model of graphene that uses the same hexagonal pattern as the atomistic model. The parameters of the TersoffCG potential are determined using structural feature and potential-energy fitting between the CG model and the atomic model. The modeling process of graphene is highly simplified using the present CG model as it avoids the necessity to define bonds/angles/dihedrals connectivity. What is more, the present CG model provides a new perspective of coarse-graining scheme for crystal structures of nanomaterials. The structural changes and mechanical properties of multilayer graphene were calculated using the new potential. Furthermore, a CG model of a graphene aerogel was built in a specific form of assembly. The chemical bonding in the joints of graphene-aerogel forms automatically during the energy relaxation process. The compressive and recover test of the graphene aerogel was reproduced to study its high elasticity. Our computational examples show that the TersoffCG potential can be used for simulations of graphene and its assemblies, which have many applications in areas of environmental protection, aerospace engineering, and others.

Preparation and partial structural characterization of the exopolysaccharide from Bacillus mucilaginosus SM-01.

In this study, an acidic hetero-exopolysaccharide, designated as BMPS, was isolated from the culture supernatant of bacteria Bacillus mucilaginosus SM-01 by ion-exchange and size-exclusion chromatography. The molecular weight of BMPS was measured to be 2.67×10(6)Da. To analyze the structure of the polysaccharide, the low-molecular weight fragment (BMPS-H) of BMPS was obtained under mild hydrolysis. BMPS-H was determined to be a liner neutral fraction with an average molecular weight of 1621Da. Monosaccharide analysis indicated that BMPS-H contained glucose and mannose in a molar ratio of 1.5:1. Based on methylation analysis and NMR spectroscopy data, the following structure of BMPS-H was established: In addition, MALDI-TOF-MS analysis showed the hydroxyl group on C-2 of 1,4-linked-glucosyl residues was partially acetylated.

Ionic Adsorption and Desorption of CNT Nanoropes.

A nanorope is comprised of several carbon nanotubes (CNTs) with different chiralities. A molecular dynamic model is built to investigate the ionic adsorption and desorption of the CNT nanoropes. The charge distribution on the nanorope is obtained by using a modified gradient method based on classical electrostatic theory. The electrostatic interactions among charged carbon atoms are calculated by using the Coulomb law. It was found here that the charged nanorope can adsorb heavy metal ions, and the adsorption and desorption can be realized by controlling the strength of applied electric field. The distance between the ions and the nanorope as well as the amount of ions have an effect on the adsorption capacity of the nanorope. The desorption process takes less time than that of adsorption. The study indicates that the CNT nanorope can be used as a core element of devices for sewage treatment.

Incorporating geographical factors with artificial neural networks to predict reference values of erythrocyte sedimentation rate.

BACKGROUND: The measurement of the Erythrocyte Sedimentation Rate (ESR) value is a standard procedure performed during a typical blood test. In order to formulate a unified standard of establishing reference ESR values, this paper presents a novel prediction model in which local normal ESR values and corresponding geographical factors are used to predict reference ESR values using multi-layer feed-forward artificial neural networks (ANN). METHODS AND FINDINGS: Local normal ESR values were obtained from hospital data, while geographical factors that include altitude, sunshine hours, relative humidity, temperature and precipitation were obtained from the National Geographical Data Information Centre in China.The results show that predicted values are statistically in agreement with measured values. Model results exhibit significant agreement between training data and test data. Consequently, the model is used to predict the unseen local reference ESR values. CONCLUSIONS: Reference ESR values can be established with geographical factors by using artificial intelligence techniques. ANN is an effective method for simulating and predicting reference ESR values because of its ability to model nonlinear and complex relationships.

Microstructural evolution of carbon nanotube fibers: deformation and strength mechanism.

A comprehensive investigation of the mechanical behavior and microstructural evolution of carbon nanotube (CNT) continuous fibers under twisting and tension is conducted using coarse-grained molecular dynamics simulations. The tensile strength of CNT fibers with random CNT stacking is found to be higher than that of fibers with regular CNT stacking. The factor dominating the mechanical response of CNT fibers is identified as individual CNT stretching. A simplified twisted CNT fiber model is studied to illustrate the structural evolution mechanisms of CNT fibers under tension. Moreover, it is demonstrated that CNT fibers can be reinforced by enhancing intertube interactions. This study would be helpful not only in the general understanding of the nano- and micro-scale factors affecting CNT fibers' mechanical behavior, but also in the optimal design of CNT fibers' architecture and performance.

[Simulation of urban ecological security pattern based on cellular automata: a case of Dongguan City, Guangdong Province of South China].

Taking the Dongguan City with rapid urbanization as a case, and selecting landscape ecological security level as evaluation criterion, the urbanization cellular number of 1 km x 1 km ecological security cells was obtained, and imbedded into the transition rules of cellular automata (CA) as the restraint term to control urban development, establish ecological security urban CA, and simulate ecological security urban development pattern. The results showed the integrated landscape ecological security index of the City decreased from 0.497 in 1998 to 0.395 in 2005, indicating that the ecological security at landscape scale was decreased. The CA-simulated integrated ecological security index of the City in 2005 was increased from the measured 0.395 to 0.479, showing that the simulated urban landscape ecological pressure from human became lesser, ecological security became better, and integrated landscape ecological security became higher. CA could be used as an effective tool in researching urban ecological security.

Effect of Wuye Decoction on lymphocyte phenotype in patients with non-small cell lung cancer.

OBJECTIVE: To investigate the effect of Chinese recipe, Wuye Decoction (WYD), on immune function in patients with non-small cell lung cancer (NSCLC). METHODS: Eighty-two patients of NSCLC with pathologically confirmed diagnosis, who had received operative treatment and completed the post-operational chemotherapy, were randomly assigned into 2 groups. Group A (42 cases) received WYD and Group B (40 cases) received no specific medicine. Positive rate of various peripheral lymphocyte subsets, including CD3, CD4, CD8, CD16, CD19 and CD25, in both groups was observed immediately after chemotherapy (T(0)) and 3 months later (T(1)), the same indexes of 20 healthy volunteers allocated in Group C were also determined at T(0) for control. RESULTS: The positive rates of CD4, CD4/CD8, CD16, CD19 and CD25 were significantly lower (P < 0.05) while that of CD8 was significantly higher (P < 0.05) in Group A and B at T(0) than those in Group C; at T(1), these indexes, except CD25, got significantly restored in Group A with the level approaching normal range (P > 0.05), and showed significant difference from those in Group B (P < 0.05), since these indexes in that group remained unchanged at the corresponding period. As for CD25, it was insignificantly changed in Group A after WYD treatment, and thus, at T(1), it was still lower than that in Group C (P < 0.05) and showed insignificant difference as compared with that in Group B (P > 0.05). Comparison of CD3 among the 3 groups showed no significant difference (P > 0.05). CONCLUSION: WYD could activate the immune function of NSCLC patients, and so it is recommended to be used in the treatment of NSCLC in clinical practice.