Multiplex metal-detection based assay (MMDA) for COVID-19 diagnosis and identification of disease severity biomarkers

The ongoing COVID-19 pandemic caused by SARS-CoV-2 highlights the urgent need to develop sensitive methods for diagnosis and prognosis. To achieve this, multidimensional detection of SARS-CoV-2 related parameters including virus loads, immune response, and inflammation factors is crucial. Herein, by using metal-tagged antibodies as reporting probes, we developed a multiplex metal-detection based assay (MMDA) method as a general multiplex assay strategy for biofluids. This strategy provides extremely high multiplexing capability (theoretically over 100) compared with other reported biofluid assay methods. As a proof-of-concept, MMDA was used for serologic profiling of anti-SARS-CoV-2 antibodies. The MMDA exhibits significantly higher sensitivity and specificity than ELISA for the detection of anti-SARS-CoV-2 antibodies. By integrating the high dimensional data exploration/visualization tool (tSNE) and machine learning algorithms with in-depth analysis of multiplex data, we classified COVID-19 patients into different subgroups based on their distinct antibody landscape. We unbiasedly identified anti-SARS-CoV-2-nucleocapsid IgG and IgA as the most potently induced types of antibodies for COVID-19 diagnosis, and anti-SARS-CoV-2-spike IgA as a biomarker for disease severity stratification. MMDA represents a more accurate method for the diagnosis and disease severity stratification of the ongoing COVID-19 pandemic, as well as for biomarker discovery of other diseases.

A MMDA platform is developed by using metal-tagged antibodies as reporting probes combined with machine learning algorithms, as a general strategy for highly multiplexed biofluid assay.     

Regioselective Arylation and Alkynylation of 2,3‐Dibromo‐1H‐inden‐1‐one by Suzuki?Miyaura and Sonogashira Cross‐Coupling Reactions

Suzuki? Miyaura reactions of 2,3‐dibromo‐1H‐inden‐1‐one afforded a wide range of arylated 1H‐inden‐1‐ones. Sonogashira cross‐coupling reactions gave alkynylated indenones. The reactions proceeded with very good regioselectivity in the less sterically hindered and more electron‐deficient position 3.     

On the development of a triple‐preserving Maxwell's equations solver in non‐staggered grids

We present in this paper a finite difference solver for Maxwell's equations in non‐staggered grids. The scheme formulated in time domain theoretically preserves the properties of zero‐divergence, symplecticity, and dispersion relation. The mathematically inherent Hamiltonian can be also retained all the time. Moreover, both spatial and temporal terms are approximated to yield the equal fourth‐order spatial and temporal accuracies. Through the computational exercises, modified equation analysis and Fourier analysis, it can be clearly demonstrated that the proposed triple‐preserving solver is computationally accurate and efficient for use to predict the Maxwell's solutions. Copyright © 2009 John Wiley & Sons, Ltd.     

Inducing anisotropy in bulk Nd-Fe-Co-Al-B nanocrystalline alloys by quenching in magnetic field

We have observed magnetic anisotropy in bulk Nd_55−xCo_xFe₃₀Al₁₀B₅ (x=10, 15 and 20) alloys prepared by copper mold suction casting method with a presence of external magnetic field (quenching field) μ₀H=0.25 T. By changing direction of the measuring field from perpendicular to parallel one in comparison with that of the quenching field, coercive force of the alloys slightly decreases while remanent magnetization and squareness of hysteresis loop increase more clearly. It is also found that the higher Co-concentration in the alloys the larger magnetic anisotropy is induced. The structure analyses manifest nanocrystalline particles embedded in residual amorphous matrix of the alloys. The size of the particles is in range of 10-30 nm and their crystalline phases consist of Nd₂(Fe,Co)₁₄B, Nd₃Co, Nd₃Al, NdAl₂ and Nd.     

Determination of neutron temperature in irradiation channels of reactor

The neutron temperature is a characteristic parameter in irradiation channels of reactor. For nuclides which have resonances in the thermal neutron energy range, their Westcott g-factors are different from unity. The values of g-factors and cross-sections of (n, γ) reaction of these nuclides are temperature dependence. The standard energy for tabulation of thermal neutron cross-section (σ₀) is that of room temperature (293.59 K or 20.43 °C), corresponding to a neutron energy 0.0253 eV or to a neutron velocity of 2200 m/s. However, in the irradiation channels of reactor, the temperature is not exact at 20.43 °C. Thus, the temperature at the irradiation position must be known to convert σ₀ to σ(T). A method for determination of the neutron temperature in irradiation channels of Dalat reactor is presented by fitting the thermal neutron spectrum obtained from the calculation using MCNP code.     

A multinomial tree model for pricing credit default swap options

Among the traded credit derivatives, the market interest in credit default swap options (CDSwaptions) is enormous. We propose a multinomial tree model to price Bermudan CDSwaptions. Our basic rationale is that we distribute the occurring probability for each node in a branch proportional to the probability density function of the assumed (normal) distribution. Through this approach, without the need of solving a large number of equations simultaneously, only the first four moments are required to build an arbitrarily large N-branches tree. We also demonstrate the detailed model implementation procedure including the valuation and the estimation of critical prices through an empirical example in Tucker and Wei (J Fixed Income 15(1):88–95, 2005). Numerical results show that, in the valuation, the proposed multinomial tree model is accurate and can significantly save pricing time under the same degree of accuracy as the binomial tree model. In the estimation of critical prices, the results are less accurate than those in the valuation, but the relative errors are acceptable.