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At the stroke of the New Year 2020, COVID-19, a zoonotic disease that would turn into a global pandemic, was identified in the Chinese city of Wuhan. Although unique in its transmission and virulence, COVID-19 is similar to zoonotic diseases, including other SARS variants (e.g., SARS-CoV) and MERS, in exhibiting severe flu-like symptoms and acute respiratory distress. Even at the molecular level, many parallels have been identified between SARS and COVID-19 so much so that the COVID-19 virus has been named SARS-CoV-2. These similarities have provided several opportunities to treat COVID-19 patients using clinical approaches that were proven to be effective against SARS. Importantly, the identification of similarities in how SARS-CoV and SARS-CoV-2 access the host, replicate, and trigger life-threatening pathological conditions have revealed opportunities to repurpose drugs that were proven to be effective against SARS. In this article, we first provided an overview of COVID-19 etiology vis-a-vis other zoonotic diseases, particularly SARS and MERS. Then, we summarized the characteristics of droplets/aerosols emitted by COVID-19 patients and how they aid in the transmission of the virus among people. Moreover, we discussed the molecular mechanisms that enable SARS-CoV-2 to access the host and become more contagious than other betacoronaviruses such as SARS-CoV. Further, we outlined various approaches that are currently being employed to diagnose and symptomatically treat COVID-19 in the clinic. Finally, we reviewed various approaches and technologies employed to develop vaccines against COVID-19 and summarized the attempts to repurpose various classes of drugs and novel therapeutic approaches.

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This paper proposes a widely applicable method of approximate maximum-likelihood estimation for multivariate diffusion process from discretely sampled data. A closed-form asymptotic expansion for transition density is proposed and accompanied by an algorithm containing only basic and explicit calculations for delivering any arbitrary order of the expansion. The likelihood function is thus approximated explicitly and employed in statistical estimation. The performance of our method is demonstrated by Monte Carlo simulations from implementing several examples, which represent a wide range of commonly used diffusion models. The convergence related to the expansion and the estimation method are theoretically justified using the theory of Watanabe [Ann. Probab. 15 (1987) 1-39] and Yoshida [J. Japan Statist. Soc. 22 (1992) 139-159] on analysis of the generalized random variables under some standard sufficient conditions. This is an electronic reprint of the original article published by the Institute of Mathematical Statistics in The Annals of Statistics, 2013, Vol. 41, No. 3, 1350-1380. This reprint differs from the original in pagination and typographic detail. 1 2 C. LI and the references given in Sørensen [59]. Taking the efficiency, feasibility and generality into account, maximum-likelihood estimation (hereafter MLE) can be a choice among others. However, for the increasingly complex real-world dynamics, likelihood functions (transition densities) are generally not known in closed-form and thus involve significant challenges in valuation. This leads to various methods of approximation and the resulting approximate MLE. The focus of this paper is to propose a widely applicable closed-form asymptotic expansion for transition density and thus to apply it in approximate MLE for multivariate diffusion process. 1.1. Background. To approximate likelihood functions, Yoshida [69] proposed to discretize continuous likelihood functions (see, e.g., Basawa and Prakasa Rao [13]); many others focused on direct approximation of likelihood functions (transition densities) for discretely monitored data, see surveys in, for example, Phillips and Yu [56], Jensen and Poulsen [36], Hurn, Jeisman and Lindsay [34] and the references therein. In particular, among various numerical methods, Lo [46] proposed to employ a numerical solution of Kolmogorov equation for transition density; Pedersen [55], Brandt and Santa-Clara [21], Durham and Gallant [25], Stramer and Yan [60], Beskos and Roberts [17], Beskos et al. [16], Beskos, Papaspiliopoulos and Roberts [15] and Elerian, Chib and Shephard [28] advocated the application of various Monte Carlo simulation methods; Yu and Phillips [73] developed an exact Gaussian method for models with a linear drift function; Jensen and Poulsen [36] resorted to the techniques of binomial trees. Since all these numerical methods are computationally demanding, real-world implementation has necessitated the development of analytical methods for efficiently approximating transition density. An adhoc approach is...

The mechanical property of extracellular matrix and cell-supporting substrates is known to modulate neuronal growth, differentiation, extension and branching. Here we show that substrate stiffness is an important microenvironmental cue, to which mouse hippocampal neurons respond and integrate into synapse formation and transmission in cultured neuronal network. Hippocampal neurons were cultured on polydimethylsiloxane substrates fabricated to have similar surface properties but a 10-fold difference in Young's modulus. Voltage-gated Ca2+ channel currents determined by patch-clamp recording were greater in neurons on stiff substrates than on soft substrates. Ca2+ oscillations in cultured neuronal network monitored using time-lapse single cell imaging increased in both amplitude and frequency among neurons on stiff substrates. Consistently, synaptic connectivity recorded by paired recording was enhanced between neurons on stiff substrates. Furthermore, spontaneous excitatory postsynaptic activity became greater and more frequent in neurons on stiff substrates. Evoked excitatory transmitter release and excitatory postsynaptic currents also were heightened at synapses between neurons on stiff substrates. Taken together, our results provide compelling evidence to show that substrate stiffness is an important biophysical factor modulating synapse connectivity and transmission in cultured hippocampal neuronal network. Such information is useful in designing instructive scaffolds or supporting substrates for neural tissue engineering.

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Based on multielectron conversion reactions, layered transition metal dichalcogenides are considered promising electrode materials for sodium‐ion batteries, but suffer from poor cycling performance and rate capability due to their low intrinsic conductivity and severe volume variations. Here, interlayer‐expanded MoSe2/phosphorus‐doped carbon hybrid nanospheres coated by anatase TiO2 (denoted as MoSe2/P‐C@TiO2) are prepared by a facile hydrolysis reaction, in which TiO2 coating polypyrrole‐phosphomolybdic acid is utilized as a novel precursor followed by a selenization process. Benefiting from synergistic effects of MoSe2, phosphorus‐doped carbon, and TiO2, the hybrid nanospheres manifest unprecedented cycling stability and ultrafast pseudocapacitive sodium storage capability. The MoSe2/P‐C@TiO2 delivers decent reversible capacities of 214 mAh g−1 at 5.0 A g−1 for 8000 cycles, 154 mAh g−1 at 10.0 A g−1 for 10000 cycles, and an exceptional rate capability up to 20.0 A g−1 with a capacity of ≈175 mAh g−1 in a voltage range of 0.5–3.0 V. Coupled with a Na3V2(PO4)3@C cathode, a full cell successfully confirms a reversible capacity of 242.2 mAh g−1 at 0.5 A g−1 for 100 cycles with a coulombic efficiency over 99%.

In this study, the mechanism of ammonium bisulfate (ABS) formation and decomposition over V/WTi for the NH-selective catalytic reduction (SCR) at various temperatures was deeply investigated. Bridged bidentate, chelating bidentate, and tridentate sulfates bound to TiO were formed as dominant intermediates at 200, 250, and 300 °C, respectively. These sulfates reacted with affinitive ammonium species to form ammonium (bi)sulfate species and also covered the active sites and embedded the VOSO intermediates, which resulted in an inferior intrinsic NH-SCR conversion rate at 200 °C and 250 °C. At 300 °C, trace amounts of ABS on TiO presented no influence on the NH-SCR performance. The electrons deviating towards sulfates through the bond between ABS and metal oxides (WO and TiO) weakened the stability of ABS and lowered its decomposition temperature, whereas the vanadia species played the opposite role due to the sulfur species existing in an electron saturation state with the formation of the VOSO intermediate. The presence of NO + O could break the bonds inside ABS and it could react with the ammonium species originating from ABS, which pulls NH out of the ABS formation equilibrium and accelerates its decomposition and competitively inhibits its formation. Correspondingly, the faster NH-SCR conversion rate and higher N selectivity improve the ABS poisoning resistance of the V/WTi catalyst at low temperatures.