miR-638 is a new biomarker for outcome prediction of non-small cell lung cancer patients receiving chemotherapy.

MicroRNAs (miRNAs), a class of small non-coding RNAs, mediate gene expression by either cleaving target mRNAs or inhibiting their translation. They have key roles in the tumorigenesis of several cancers, including non-small cell lung cancer (NSCLC). The aim of this study was to investigate the clinical significance of miR-638 in the evaluation of NSCLC patient prognosis in response to chemotherapy. First, we detected miR-638 expression levels in vitro in the culture supernatants of the NSCLC cell line SPC-A1 treated with cisplatin, as well as the apoptosis rates of SPC-A1. Second, serum miR-638 expression levels were detected in vivo by using nude mice xenograft models bearing SPC-A1 with and without cisplatin treatment. In the clinic, the serum miR-638 levels of 200 cases of NSCLC patients before and after chemotherapy were determined by quantitative real-time PCR, and the associations of clinicopathological features with miR-638 expression patterns after chemotherapy were analyzed. Our data helped in demonstrating that cisplatin induced apoptosis of the SPC-A1 cells in a dose- and time-dependent manner accompanied by increased miR-638 expression levels in the culture supernatants. In vivo data further revealed that cisplatin induced miR-638 upregulation in the serum derived from mice xenograft models, and in NSCLC patient sera, miR-638 expression patterns after chemotherapy significantly correlated with lymph node metastasis. Moreover, survival analyses revealed that patients who had increased miR-638 levels after chemotherapy showed significantly longer survival time than those who had decreased miR-638 levels. Our findings suggest that serum miR-638 levels are associated with the survival of NSCLC patients and may be considered a potential independent predictor for NSCLC prognosis

A novel recyclable magnetic nanostructure for highly sensitive, selective and reversible detection of zinc ions in aqueous solutions

The synthesis and characterisation of a novel dansylated magnetic nanostructure, namely Fe3O4@SiO2-PEG-DnS, is reported here. Investigations of its fluorescent properties showed that the presence of the PEG moiety significantly enhanced the fluorescent intensity of the nanostructure when compared to both the free dansyl fluorophore and a nanostructure that contained no PEG spacer between the core and the attached dansyl group. The addition of zinc (Zn2+) ions to the aqueous suspension of Fe3O4@SiO2-PEG-DnS led to a 12.5-fold decrease in intensity. The quenching was selective to only Zn2+. No interference was observed by other examined metal cations, including cadmium (Cd2+). A very low detection limit of 6.00 nM in relation to zinc ions was demonstrated. In addition, the newly developed magnetic nanostructured chemosensor was found to be highly stable, reusable and recoverable

Disordered structure for long-range charge density wave order in annealed crystals of magnetic kagome FeGe

Recently, charge density wave (CDW) has been observed well below the order of antiferromagnetism (AFM) in kagome FeGe in which magnetism and CDW are intertwined to form an emergent quantum ground state. The mechanism of CDW precipitating from an A-type AFM of Fe kagome sublattice is intensively debated. The structural distortion originating from the CDW has yet to be accurately determined in FeGe. Here we resolved the structure model of the CDW in annealed FeGe crystals through single crystal x-ray diffraction via a synchrotron radiation source. The annealed crystals exhibit strong CDW transition signals exemplified by sharp magnetic susceptibility drop and specific heat jump, as well as intense superlattice reflections from 2 $\times$ 2 $\times$ 2 CDW order. Occupational disorder of Ge atoms resulting from short-range CDW correlations above $T_\mathrm{CDW}$ has also been identified from the structure refinements. The dimerization of Ge atoms along c axis has been demonstrated to be the dominant distortion for CDW. The Fe kagome and Ge honeycomb sublattices only undergo subtle distortions. Occupational disorder of Ge atoms is also proved to exist in the CDW phase due to the random selection of partial Ge sites to be dimerized to realize the structural distortion. Our work paves the way to understanding the unconventional nature of CDW in FeGe not only by solving the structural distortion below $T_\mathrm{CDW}$ and identifying fluctuations above it but also by rationalizing the synthesis of high-quality crystals for in-depth investigations in the future.Comment: 18 pages, 4 figures. Comments are welcom

Synergistic synthesis of quasi-monocrystal CdS nanoboxes with high-energy facets

Hollow nanostructures with a highly oriented lattice structure and active facets are promising for catalytic applications, while their preparation via traditional approaches contains multiple steps and is time and energy consuming. Here, we demonstrate a new one-step strategy involving two complementary reactions which promote each other; it is capable of producing unique hollow nanoparticles. Specifically, we apply synergic cooperation of cation exchange and chemical etching to attack PbS nanosized cubes (NCs) and produce CdS quasi-monocrystal nanoboxes (QMNBs) which possess the smallest dimensions reported so far, a metastable zinc-blende phase, a large specific surface area, and particularly high-energy {100} facets directly visualized by aberration-corrected scanning transmission electron microscopy. These properties in combination allow the nanoboxes to acquire exceptional photocatalytic activities. As an extension of the approach, we use the same strategy to prepare Co9S8 and Cu7.2S4 single-crystal hollow nanooctahedrons (SCHNOs) successfully. Hence, the synergic reaction synthesis strategy exhibits great potential in engineering unique nanostructures with superior properties

Colossal band renormalization and stoner ferromagnetism induced by electron-antiferromagnetic-magnon coupling

The interactions between electrons and antiferromagnetic magnons (AFMMs) are important for a large class of correlated materials. For example, they are the most plausible pairing glues in high-temperature superconductors, such as cuprates and iron pnictides. However, unlike electron-phonon interactions (EPIs), clear-cut observations regarding how electron-AFMM interactions (EAIs) affect the band structure are still lacking. Consequently, critical information on the EAIs, such as its strength and doping dependence, remains elusive. Here we directly observe that EAIs induces a kink structure in the band dispersion in Ba$_{1-x}$K$_x$Mn$_2$As$_2$, and subsequently unveil several key characteristics of EAIs. We found that the coupling constant of EAIs can be as large as 6, and it shows huge doping dependence and temperature dependence, all in stark contrast to the behaviors of EPI and beyond our current understanding of EAIs. Such a colossal renormalization of electronic bands by EAIs drives the system to the Stoner criteria, giving the intriguing ferromagnetic state in Ba$_{1-x}$K$_x$Mn$_2$As$_2$. Our results expand the current knowledge of EAIs, which may facilitate the further understanding of many correlated materials where EAIs play a critical role, such as high-temperature superconductors

Enhanced electrochemical reduction of hydrogen peroxide by Co3O4 nanowire electrode

Crystalline Co3O4 nanowire arrays with different morphologies grown on Ni foam were investigated by varying the reaction temperature, the concentration of precursors, and reaction time. The Co3O4 nanowires synthesized under typical reaction condition had a diameter range of approximately 500–900 nm with a length of 17 µm. Electrochemical reduction of hydrogen peroxide (H2O2) of the optimized Co3O4 nanowire electrode was studied by cyclic voltammetry. A high current density of 101.8 mA cm−2 was obtained at −0.4 V in a solution of 0.4 M H2O2 and 3.0 M NaOH at room temperature compared to 85.8 mA cm−2 at −0.35 V of the Co3O4 nanoparticle electrode. Results clearly indicated that the Ni foam supported Co3O4 nanowire electrode exhibited superior catalytic activity and mass transport kinetics for H2O2 electrochemical reduction

Automatic Recognition of Laryngoscopic Images Using a Deep-Learning Technique

Objectives/Hypothesis: To develop a deep-learning–based computer-aided diagnosis system for distinguishing laryngeal neoplasms (benign, precancerous lesions, and cancer) and improve the clinician-based accuracy of diagnostic assessments of laryngoscopy findings. Study Design: Retrospective study. Methods: A total of 24,667 laryngoscopy images (normal, vocal nodule, polyps, leukoplakia and malignancy) were collected to develop and test a convolutional neural network (CNN)-based classifier. A comparison between the proposed CNN-based classifier and the clinical visual assessments (CVAs) by 12 otolaryngologists was conducted. Results: In the independent testing dataset, an overall accuracy of 96.24% was achieved; for leukoplakia, benign, malignancy, normal, and vocal nodule, the sensitivity and specificity were 92.8% vs. 98.9%, 97% vs. 99.7%, 89% vs. 99.3%, 99.0% vs. 99.4%, and 97.2% vs. 99.1%, respectively. Furthermore, when compared with CVAs on the randomly selected test dataset, the CNN-based classifier outperformed physicians for most laryngeal conditions, with striking improvements in the ability to distinguish nodules (98% vs. 45%, P <.001), polyps (91% vs. 86%, P <.001), leukoplakia (91% vs. 65%, P <.001), and malignancy (90% vs. 54%, P <.001). Conclusions: The CNN-based classifier can provide a valuable reference for the diagnosis of laryngeal neoplasms during laryngoscopy, especially for distinguishing benign, precancerous, and cancer lesions. Level of Evidence: NA Laryngoscope, 130:E686–E693, 2020

All inkjet-printed graphene-based conductive patterns for wearable e-textile applications

© 2017 The Royal Society of Chemistry. Inkjet printing of graphene inks is considered to be very promising for wearable e-textile applications as benefits of both inkjet printing and extra-ordinary electronic, optical and mechanical properties of graphene can be exploited. However, the common problem associated with inkjet printing of conductive inks on textiles is the difficulty to print a continuous conductive path on a rough and porous textile surface. Here we report inkjet printing of an organic nanoparticle based surface pre-treatment onto textiles to enable all inkjet-printed graphene e-textiles for the first time. The functionalized organic nanoparticles present a hydrophobic breathable coating on textiles. Subsequent inkjet printing of a continuous conductive electrical path onto the pre-treated coating reduced the sheet resistance of graphene-based printed e-textiles by three orders of magnitude from 1.09 × 106 Ω sq-1 to 2.14 × 103 Ω sq-1 compared with untreated textiles. We present several examples of how this finding opens up opportunities for real world applications of printed, low cost and environmentally friendly graphene wearable e-textiles