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This study delves into the characterization of IGZO/ZnO bilayer memristors, examining the impact of ZnO thickness and voltage scan rate on device performance. Bilayer memristors with varying ZnO thicknesses were prepared using magnetron sputtering, and their electrical properties were evaluated. The results indicate that a ZnO thickness of 17.3 nm yields optimal device performance, characterized by lower Forming and RESET voltages, reduced operating voltage volatility, higher switching ratios, and excellent cycling endurance and state retention. As the ZnO thickness increases, the Forming and RESET voltages of the devices also increase, the high resistance state volatility increases, and the switching ratio improves, although this is accompanied by greater operating voltage volatility. I–V characteristic measurements conducted at different scan rates revealed that the devices are insensitive to voltage scan rates, exhibiting stable resistive behavior within the range of 0.125–1.0 V/s. Furthermore, the study explores the multi-value storage capability of the bilayer device. To understand the resistive switching mechanism, current conduction mechanism fitting and resistive switching modeling were performed. The findings demonstrate that the device’s current conduction mechanism primarily involves the space-charge-limited current mechanism and Schottky emission mechanism. This research presents a novel approach to developing high-performance memristors, paving the way for their applications in nonvolatile storage and neuromorphic computing.

A nanoparticle-based drug delivery technology could develop combination cancer therapy more effectively. However, because of inadequate drug delivery into tumor cells, the cancer therapeutic efficiency of nanomedicines is diminished. PEGylated poly(α-lipoic acid) copolymers with (mPEG-PLA) were fabricated and used as pH/reductive responsive nanovesicles to administer Gefitinib (GFT) and doxorubicin (DOX) for the treatment of ovarian cancer. The amphiphilic polymers mPEG-PLA may be efficiently incorporated on DOX and GFT to fabricate DOX and GFT coloaded nanoparticles (DOX@GFT-NPs) and self-assembled into an aqueous solution. The DOX@GFT-NPs released more DOX and GFT after being prepared to respond to pH and reduction stimuli. The outcomes of confocal laser scanning microscopy and flow cytometry findings, the SKOV3 ovarian cancer cells quickly fascinated the dual drugs-coloaded nanoparticles and drugs released intracellularly accumulated. DOX@GFT-NPs triggered cell death and demonstrated synergistic therapeutic benefits in SKOV3 cells. Results showed that the nanoparticles efficiently trigger apoptosis in SKOV3 ovarian cancer cells using morphological staining (acridine orange/ethidium bromide (AO/EB) and HOECHST 33342 nuclear staining). These outcomes show that using pH and reduction stimuli on mPEG-PLA copolymer to treat ovarian cancer is a promising approach.

AXL is overexpressed and has been investigated as a therapeutic target in several cancer types, including lung cancer. Here the authors design AXLdirected CAR-T cells and show that their anti-tumor activity can be improved in combination with microwave ablation in preclinical lung cancer models.

Abstract Although chimeric antigen receptor (CAR)-engineered T cells have shown great success in the treatment of B cell malignancies, this strategy has limited efficacy in patients with solid tumors. In mouse CAR-T cells, IL-7 and CCL19 expression have been demonstrated to improve T cell infiltration and CAR-T cell survival in mouse tumors. Therefore, in the current study, we engineered human CAR-T cells to secrete human IL-7 and CCL19 (7 × 19) and found that these 7 × 19 CAR-T cells showed enhanced capacities of expansion and migration in vitro. Furthermore, 7 × 19 CAR-T cells showed superior tumor suppression ability compared to conventional CAR-T cells in xenografts of hepatocellular carcinoma (HCC) cell lines, primary HCC tissue samples and pancreatic carcinoma (PC) cell lines. We then initiated a phase 1 clinical trial in advanced HCC/PC/ovarian carcinoma (OC) patients with glypican-3 (GPC3) or mesothelin (MSLN) expression. In a patient with advanced HCC, anti-GPC3-7 × 19 CAR-T treatment resulted in complete tumor disappearance 30 days post intratumor injection. In a patient with advanced PC, anti-MSLN-7 × 19 CAR-T treatment resulted in almost complete tumor disappearance 240 days post-intravenous infusion. Our results demonstrated that the incorporation of 7 × 19 into CAR-T cells significantly enhanced the antitumor activity against human solid tumor. Trial registration: NCT03198546. Registered 26 June 2017, https://clinicaltrials.gov/ct2/show/NCT03198546?term=NCT03198546&draw=2&rank=1

Abstract Cucurbitacin B (CuB) is a widely available triterpenoid molecule that exhibits various biological activities. Previous studies on the anti-tumour mechanism of CuB have mostly focused on cell apoptosis, and research on the ferroptosis-inducing effect has rarely been reported. Herein, we first discovered the excellent cytotoxicity of CuB towards human nasopharyngeal carcinoma cells and elucidated its potential ferroptosis-inducing mechanisms. Morphology alterations of mitochondrial ultrastructure, as observed via transmission electron microscopy, showed that CuB-treated cells undergo ferroptosis. CuB caused intracellular accumulation of iron ions and depletion of glutathione. Detailed molecular mechanism investigation confirmed that CuB both induced widespread lipid peroxidation and downregulated the expression of GPX4, ultimately initiating a multipronged mechanism of ferroptosis. Furthermore, CuB exhibited anti-tumour effects in vitro by inhibiting cellular microtubule polymerization, arresting cell cycle and suppressing migration and invasion. Finally, CuB significantly inhibited tumour progression without causing obvious side effects in vivo. Altogether, our study highlighted the therapeutic potential of CuB as a ferroptosis-inducing agent for nasopharyngeal cancer, and it provided valuable insights for developing effective anti-tumour agents with novel molecular mechanisms derived from natural products.

Diabetes mellitus is a group of complex metabolic disorders which has affected hundreds of millions of patients world-widely. The underlying pathogenesis of various types of diabetes is still unclear, which hinders the way of developing more efficient therapies. Although many genes have been found associated with diabetes mellitus, more novel genes are still needed to be discovered towards a complete picture of the underlying mechanism. With the development of complex molecular networks, network-based disease-gene prediction methods have been widely proposed. However, most existing methods are based on the hypothesis of guilt-by-association and often handcraft node features based on local topological structures. Advances in graph embedding techniques have enabled automatically global feature extraction from molecular networks. Inspired by the successful applications of cutting-edge graph embedding methods on complex diseases, we proposed a computational framework to investigate novel genes associated with diabetes mellitus. There are three main steps in the framework: network feature extraction based on graph embedding methods; feature denoising and regeneration using stacked autoencoder; and disease-gene prediction based on machine learning classifiers. We compared the performance by using different graph embedding methods and machine learning classifiers and designed the best workflow for predicting genes associated with diabetes mellitus. Functional enrichment analysis based on Human Phenotype Ontology (HPO), KEGG, and GO biological process and publication search further evaluated the predicted novel genes.

Poverty is a critical issue in sustainable development, and the study of poverty has gradually shifted from absolute to relative poverty. This paper measures three types of relative poverty—strongly relative poverty (50% of median income), strongly relative poverty (50% of mean income), and weakly relative poverty. Then this paper decomposes the change of relative poverty into the growth component, redistribution component, and poverty line change component. Further, the intra- and inter-group decompositions of relative poverty change are carried out by considering the urban and rural population mobility components. We apply the China Health and Nutrition Survey (CHNS) data from 1989 to 2015 for an empirical study. The results show that: (1) In recent years, the change in relative poverty in China has shown a trend of low fluctuation (1989–1997), rising fluctuation (1997–2006), and high fluctuation (2006–2015). (2) In the decomposition of relative poverty change, the growth component has the most excellent effect on alleviating relative poverty, the redistribution component exacerbates the occurrence of relative poverty in most years and reduces it in a few years, and the poverty line change component offsets the poverty reduction effect of the growth component. (3) The change in relative poverty is decomposed by urban and rural sub-groups, and it is found that the population mobility from rural to urban can reduce the national relative poverty.

A facile and efficient protocol for palladium-catalyzed C8-selective acylation of quinoline N-oxides with α-oxocarboxylic acids has been developed. In this approach, N-oxide was utilized as a stepping stone for the remote C-H functionalization. The reactions proceeded efficiently under mild reaction conditions with excellent regioselectivity and broad functional group tolerance. [ABSTRACT FROM AUTHOR]

A "one-pot" facile and efficient protocol for 8-acylated 2-quinolinones has been developed through palladium-catalyzed acylation of quinoline N-oxides, which proceeds with high selectivity at the C8-position. The desired products were isolated in up to 95% yield and good functional group tolerance. A palladacycle was isolated from the catalytic process and proposed as a key intermediate. [ABSTRACT FROM AUTHOR]

An efficient cross-dehydrogenativecoupling of quinoline N-oxides and 1,3-azoles hasbeen developed under externaloxidant and metal free conditions. The desired products were isolatedin good to excellent yields for 26 examples. This methodology providesa practical pathway to biheteroaryls and features high practicality,high efficiency, and environmental friendliness. [ABSTRACT FROM AUTHOR]

This paper presents a microgap multicavity Fabry-Perot interferometric sensor fabricated by wet etching and fusion splicing of single-mode optical fibers. The temperature dependence of the optical thickness measurement of self-assembled thin films can be compensated by extracting the temperature information from the multiplexed temperature sensor. Experimental results demonstrate that thin-film characteristics under temperature variations can be examined accurately. The high-temperature sensitivity of the temperature sensor also enables biosensing under temperature variations. This greatly improves the flexibility in sample handling and provides the opportunity to investigate temperature effects in biological applications. [ABSTRACT FROM PUBLISHER]

In this paper, experimental design techniques are utilized to understand sources of variation in an optical fiber sensor design and development project in a university research setting. Application of the Taguchi method of robust design assisted fiber optic sensor development in a cost-effective and timely manner. According to the analysis, compensation of the source of the variation identified in the experimental design results was achieved on a new design concept of a multiplexed optical fiber sensor. The experimental results and conclusions not only are suitable for this sensor structure, but also are useful for other fiber optic sensors based on the technique of Fabry-Perot interferometry. [ABSTRACT FROM AUTHOR]

This letter presents an intrinsic Fabry-Pe´rot interferometric sensor fabricated by splicing a section of multimode fiber in between two single-mode fibers. The fabrication process only involves fusion splicing and cleaving. The sensor is analyzed and the issues in sensor fabrication are discussed. The sensor temperature and strain measurement performance is evaluated. The sensor may find its application in quasi-distributed sensing due to its low insertion loss. [ABSTRACT FROM PUBLISHER]

In this work, the reason for the difference between the simulated and experimental breakdown voltage is confirmed in power MOSFETs. Theoretical study predicts two factors. One is that the recombination phenomenon is ignored in the simulation. Another problem is that the accuracies of commonly used impact ionization models are not qualified. The widely used impact ionization models, which are the key factor to influence the breakdown voltage, are analyzed theoretically and numerically. Meanwhile, the validities of these models are verified experimentally. It is proved that the Lackner model is more precise. With the help of qualifying and with the recombination phenomenon considered, the conventional ionization integral is modified. The relations between the breakdown voltage, the specific on-resistance, the thickness and the doping concentration of the epitaxial layer are then simulated and fitted to the non-punch-through (NPT) structure. While the breakdown voltage of the NPT structure using the Lackner model varies from 182 V to 1471 V, the value using the Chynoweth model, which is in common use in simulation, is underestimated by 6.0%(171 V) to 9.5%(1332 V). Based on these improvements, an expression set is presented for the epitaxial layer parameters selection. The re-established formula set has more accuracy and obvious difference from the results obtained with the conventional Chynoweth models. For optimum designed punch-though (PT) structures, the analytical results indicate that the specific on-resistance can be reduced by about 12.0% compared with the NPT structure. The PT structure also allows the epitaxial layer to be decreased by about 25.3% in thickness and 8.3% in doping concentration. [ABSTRACT FROM AUTHOR]