Data-Driven Framework toward Accurate Prediction of Interfacial Thermal Resistance in Particulate-Filled Composites.

The interfacial thermal resistance (ITR) inside the particulate-filled polymer composite is a bottleneck for improving the thermal conductivity (TC) of the material. Getting full knowledge of the ITR is crucial to the material design as well as to a faithful prediction of TC of the composite. However, a method fully taking into account the local circumstances inside the composite is yet to be developed to precisely characterize the ITR. Here, we propose a comprehensive framework combining high-throughput numerical simulations, machine learning and optimization algorithms, and experiments, which is demonstrated to be robust for the accurate determination of ITRs inside the particulate-filled composites. The strategy extracts as much information as possible about the structure and heat transfer characteristics of the composite based on simple experiments, which lays the foundation for the method to be effective. We show that the polymer-filler ITRs and the effective filler-filler contact ITRs predicted with the method faithfully represent the true characteristics inside the composite materials; they also provide the exact effective parameters, which cannot be obtained from experiments, for accurate numerical prediction of TCs of composite materials with high efficiency. As a result, the framework not only provides a robust tool for accurate characterization of ITRs inside composites but also paves the way for virtual high-throughput formula screening of thermally conductive composite materials that could be used in industrial product design.

Methyltransferase-like 3 facilitates lung cancer progression by accelerating m6A methylation-mediated primary miR-663 processing and impeding SOCS6 expression.

OBJECTIVE: Lung cancer (LC) remains a threatening health issue worldwide. Methyltransferase-like protein 3 (METTL3) is imperative in carcinogenesis via m6A modification of microRNAs (miRNAs). This study estimated the effect of METTL3 in LC by regulating m6A methylation-mediated pri-miR-663 processing. METHODS: miR-663 expression in 4 LC cell lines and normal HBE cells was determined using RT-qPCR. A549 and PC9 LC cells selected for in vitro studies were transfected with miR-663 mimics or inhibitor. Cell viability, migration, invasion, proliferation, and apoptosis were detected by CCK-8, Transwell, EdU, and flow cytometry assays. The downstream target genes and binding sites of miR-663 were predicted via Starbase database and validated by dual-luciferase assay. LC cells were delivered with oe-METTL3/sh-METTL3. Crosslinking between METTL3 and DGCR8 was verified by co-immunoprecipitation. Levels of m6A, miR-663, and pri-miR-663 were measured by m6A dot blot assay and RT-qPCR. m6A modification of pri-miR-663 was verified by Me-RIP assay. Finally, the effects of METTL3 in vivo were ascertained by tumor xenograft in nude mice. RESULTS: miR-663 was upregulated in LC cells, and miR-663 overexpression promoted cell proliferation, migration, invasion, and inhibited apoptosis, but miR-663 knockdown exerted the opposite effects. miR-663 repressed SOCS6 expression. SOCS6 overexpression annulled the promotion of miR-663 on LC cell growth. METTL3 bound to DGCR8, and METTL3 silencing elevated the levels of pri-miR-663 and m6A methylation-modified pri-miR-663, and suppressed miR-663 maturation and miR-663 expression. METTL3 facilitated tumor growth in mice through the miR-663/SOCS6 axis. CONCLUSION: METTL3 promotes LC progression by accelerating m6A methylation-mediated pri-miR-663 processing and repressing SOCS6.

Fabrication and characterization of oil-in-water pickering emulsions stabilized by ZEIN-HTCC nanoparticles as a composite layer.

In this work, the ZEIN-HTCC nanoparticles formed by zein and N-(2-hydroxy)propyl-3-trimethylammonium chitosan chloride (HTCC) were used as stabilizers to prepare oil-in-water (O/W) Pickering emulsions. The preparation conditions including shearing time, volume fraction of corn oil, mass ratio of ZEIN:HTCC and total concentration of ZEIN-HTCC of emulsions were optimized by measuring the droplet size, zeta potential, PDI and surface tension of emulsions. The ZEIN-HTCC emulsions are stable at the pH range of 4-9 and in the low salt ion concentrations up to 0.2 mol L-1, and can keep stable up to 21 d during low temperature storage. Fourier transform infrared spectroscopy (FTIR), the confocal laser scanning microscope (CLSM) and scanning electron microscopy (SEM) were used to analyze the interaction between emulsion components, revealing that zein and HTCC form a composite layer by flocculation to adsorb on the surface of oil droplets, thus preventing emulsion droplets from aggregation. This novel, long-term stable, surfactant-free, and edible zein-based Pickering emulsion could be used as potential carriers for lipophilic nutrients delivery.

A Stochastic FE2 Data-Driven Method for Nonlinear Multiscale Modeling.

A stochastic data-driven multilevel finite-element (FE2) method is introduced for random nonlinear multiscale calculations. A hybrid neural-network-interpolation (NN-I) scheme is proposed to construct a surrogate model of the macroscopic nonlinear constitutive law from representative-volume-element calculations, whose results are used as input data. Then, a FE2 method replacing the nonlinear multiscale calculations by the NN-I is developed. The NN-I scheme improved the accuracy of the neural-network surrogate model when insufficient data were available. Due to the achieved reduction in computational time, which was several orders of magnitude less than that to direct FE2, the use of such a machine-learning method is demonstrated for performing Monte Carlo simulations in nonlinear heterogeneous structures and propagating uncertainties in this context, and the identification of probabilistic models at the macroscale on some quantities of interest. Applications to nonlinear electric conduction in graphene-polymer composites are presented.

Ultrahigh-Aspect-Ratio Boron Nitride Nanosheets Leading to Superhigh In-Plane Thermal Conductivity of Foldable Heat Spreader.

The rapid development of integrated circuits and electronic devices creates a strong demand for highly thermally conductive yet electrically insulating composites to efficiently solve "hot spot" problems during device operation. On the basis of these considerations, hexagonal boron nitride nanosheets (BNNS) have been regarded as promising fillers to fabricate polymer matrix composites. However, so far an efficient approach to prepare ultrahigh-aspect-ratio BNNS with large lateral size while maintaining an atomically thin nature is still lacking, seriously restricting further improvement of the thermal conductivity for BNNS/polymer composites. Here, a rapid and high-yield method based on a microfluidization technique is developed to obtain exfoliated BNNS with a record high aspect ratio of ≈1500 and a low degree of defects. A foldable and electrically insulating film made of such a BNNS and poly(vinyl alcohol) (PVA) matrix through filtration exhibits an in-plane thermal conductivity of 67.6 W m-1 K-1 at a BNNS loading of 83 wt %, leading to a record high value of thermal conductivity enhancement (≈35 500). The composite film then acts as a heat spreader for heat dissipation of high-power LED modules and shows superior cooling efficiency compared to commercial flexible copper clad laminate. Our findings provide a practical route to produce electrically insulating polymer composites with high thermal conductivity for thermal management applications in modern electronic devices.

Numerical homogenization of thermal conductivity of particle-filled thermal interface material by fast Fourier transform method.

Thermal interface material (TIM) is pivotal for the heat dissipation between layers of high-density electronic packaging. The most widely used TIMs are particle-filled composite materials, in which highly conductive particulate fillers are added into the polymer matrix to promote heat conduction. The numerical simulation of heat transfer in the composites is essential for the design of TIMs; however, the widely used finite element method (FEM) requires large memory and presents limited computational time for the composites with dense particles. In this work, a numerical homogenization algorithm based on fast Fourier transform was adopted to estimate the thermal conductivity of composites with randomly dispersed particles in 3D space. The unit cell problem is solved by means of a polarization-based iterative scheme, which can accelerate the convergence procedure regardless of the contrast between various components. The algorithm shows good precision and requires dramatically reduced computation time and cost compared with FEM. Moreover, the effect of the particle volume fraction, interface thermal resistance between particles (R-PP), interface thermal resistance between particle and matrix (R-PM), and particle size have been estimated. It turns out that the effective conductivity of the particulate composites increases sharply at a critical filler volume fraction, after which it is sensitive to the variation of filler loading. We can observe that the effective thermal conductivity of the composites with low filler volume fraction is sensitive to R-PM, whereas the it is governed by R-PP for the composites with high filler content. The algorithm presents excellent efficiency and accuracy, showing potential for the future design of highly thermally conductive TIMs.

A meta-analysis of the safety and effectiveness of pemetrexed compared with gefitinib for pre-treated advanced or metastatic NSCLC.

BACKGROUND: The purpose of the current meta-analysis was to compare the oncological outcomes of pemetrexed versus gefitinib in pre-treated advanced or metastatic non-small cell lung cancer (NSCLC) patients. METHODS: Search the online electronic databases on comparison the effectiveness and adverse effects of pemetrexed versus gefitinib in therapy outcomes of pre-treated NSCLC to September 2019. All studies analyzed the summary odds ratios (ORs) of the main outcomes, including survival efficacy and toxicity complications. RESULTS: In all, 5 trials involving 676 subjects were included, with 332 receiving pemetrexed and 344 using gefitinib. The pooled analysis of overall survival (OS) (OR = 0.97, 95%CI = 0.77-1.21, P = .76) and progression-free survival (PFS) (OR = 1.17, 95%CI = 0.60-2.30, P = .65) showed that pemetrexed did not achieve benefit when compared with gefitinib. In the results of subgroup analysis among the EGFR mutation-positive patients, the comparison of gefitinib therapy versus pemetrexed did show PFS benefit 0.35 (95%CI 0.12-1.01; P = .05). In terms of grade 3 or 4 side effects, a similar toxicity profile of both pemetrexed and gefitinib was shown in the incidence rate of rash (P = .045), fatigue (P = .97), thrombocytopenia (P = .68) and anemia (P = .21) between the 2 groups. CONCLUSION: Pemetrexed was not associated with survival benefit than gefitinib therapy among pre-treated NSCLC patients. While, gefitinib showed superior PFS efficacy than pemetrexed for patients with EGFR mutation-type. Future investigations are required to identify relevant biomarkers in selected patients that would most likely benefit from pemetrexed or gefitinib treatment in pre-treated advanced NSCLC patients.

Design of Electrically Conductive Structural Composites by Modulating Aligned CVD-Grown Carbon Nanotube Length on Glass Fibers.

Function-integration in glass fiber (GF) reinforced polymer composites is highly desired for developing lightweight structures and devices with improved performance and structural health monitoring. In this study, homogeneously aligned carbon nanotube (CNT) shell was in situ grafted on GF by chemical vapor deposition (CVD). It was demonstrated that the CNT shell thickness and weight fraction can be modulated by controlling the CVD conditions. The obtained hierarchical CNTs-GF/epoxy composites show highly improved electrical conductivity and thermo-mechanical and flexural properties. The composite through-plane and in-plane electrical conductivities increase from a quasi-isolator value to ∼3.5 and 100 S/m, respectively, when the weight fraction of CNTs grafted on GF fabric varies from 0% to 7%, respectively. Meanwhile, the composite storage modulus and flexural modulus and strength improve as high as 12%, 21%, and 26%, respectively, with 100% retention of the glass transition temperature. The reinforcing mechanisms are investigated by analyzing the composite microstructure and the interfacial adhesion and wetting properties of CNTs-GF hybrids. Moreover, the specific damage-related resistance variation characteristics could be employed to in situ monitor the structural health state of the composites. The outstanding electrical and structural properties of the CNTs-GF composites were due to the specific interfacial and interphase structures created by homogeneously grafting aligned CNTs on each GF of the fabric.

Hyperbaric oxygen therapy in acute ischemic stroke: a review.

Stroke, also known as cerebrovascular disease, is a common and serious neurological disease, which is also the fourth leading cause of death in the United States so far. Hyperbaric medicine, as an emerging interdisciplinary subject, has been applied in the treatment of cerebral vascular diseases since the 1960s. Now it is widely used to treat a variety of clinical disorders, especially hypoxia-induced disorders. However, owing to the complex mechanisms of hyperbaric oxygen (HBO) treatment, the therapeutic time window and the undefined dose as well as some common clinical side effects (such as middle ear barotrauma), the widespread promotion and application of HBO was hindered, slowing down the hyperbaric medicine development. In August 2013, the US Food and Drug Administration declared artery occlusion as one of the 13 specific indications for HBO therapy. This provides opportunities, to some extent, for the further development of hyperbaric medicine. Currently, the mechanisms of HBO therapy for ischemic stroke are still not very clear. This review focuses on the potential mechanisms of HBO therapy in acute ischemic stroke as well as the time window.

[Clinical characterization and treatment of acute decompression sickness after group repeated dives].

OBJECTIVE: To clinically characterize the divers who suffer from decompression sickness in group after diving, optimize therapeutic treatment settings for grouped patients where the conventional individualized treatment cannot be implemented. METHODS: Clinical parameters of patients such as age, professional seniority in dive, labor intensity, diving depth and their symptoms were statistically categorized to identify the factors that correlate with treatment efficacy and recurrence rate. In accordance with the symptoms and the reactions to pressure, 4 treatment programs were applied: Program A, Program B, Program C, Program D. RESULTS: (1) age, professional seniority, diving depth, length of service, dive frequency were positively correlated with the treatment efficacy (P<0.05, P<0.01), and these parameters together with pain intensity were also positively correlated with recurrence risk (P<0.05, P<0.01), while long latency time of the disease often related with poor therapeutic outcome and high recurrence rate (P<0.01), (2) pain intensity were positively affected by age, diving depth and dive frequency (P<0.05, P<0.01), whereas negatively affected by disease latency time (P<0.01), (3) Four elements in this clinic project, selection of treatment program, length of service, diving depth and disease latency time of patient, were responsible for (or: could account for) 48.0% change of treatment efficacy, (4) Among Programs using different therapeutic pressure, Program D, C and B had better outcomes than Program A (P<0.01, P<0.05). Also, less patients in Program D, C and B suffered from recurrence with relative to Program A (P<0.01, P<0.05), (5) Between Programs adopting same hyperbaric pressure and treatment duration time, Program D was more efficient and fewer recurrent cases were found in it if compared to Program B (P<0.05), (6) In programs with same pressure and duration time settings, Program D was remarkably superior to program C in regard of its treatment efficacy. CONCLUSIONS: In condition with only limited clinic supplies, Program D could be the first choice to provide the hyperbaric oxygen as an ideal group treatment, and it is not very necessary for the clinician to provide individualized therapy. An appropriate extension of stay in hyperbaric chamber may apply to some patients but depending on the clinical symptoms, however, no longer time than 120 min is recommended.

[Design of automatic monitoring for hyperbaric oxygen-cabins by using microcomputer].

This paper introduces a kind of union of hyperbaric oxygen-cabins and a microcomputer through which, the temperature measurement, the monitoring of oxygen concentration and air exchange are realized automatically with uniformly ascending voltage and static constant voltage.