Frozen Natural Orbitals for the State-Averaged Driven Similarity Renormalization Group.

We present a reduced-cost implementation of the state-averaged driven similarity renormalization group (SA-DSRG) based on the frozen natural orbital (FNO) approach. The natural orbitals (NOs) are obtained by diagonalizing the one-body reduced density matrix from SA-DSRG second-order perturbation theory (SA-DSRG-PT2). We consider three criteria to truncate the virtual NOs for the subsequent electron correlation treatment beyond SA-DSRG-PT2. An additive second-order correction is applied to the SA-DSRG Hamiltonian to reintroduce correlation effects from the discarded orbitals. The FNO SA-DSRG method is benchmarked on 35 small organic molecules in the QUEST database. When keeping 98-99% of the cumulative occupation numbers, the mean absolute error in the vertical transition energies due to FNO is less than 0.01 eV. Using the same FNO threshold, we observe a speedup of 9 times compared to the conventional SA-DSRG implementation for nickel carbonyl with a quadruple-ζ basis set. The FNO approach enables nonperturbative SA-DSRG computations on chloroiron corrole [FeCl(C19H11N4)] with more than 1000 basis functions, surpassing the current limit of a conventional implementation.

Traditional Chinese medicine combined with Moxibustion in the treatment of "long-COVID": A protocol for systematic review and meta-analysis.

BACKGROUND: From the end of 2019 to now, COVID-19 is still prevalent, which poses a great threat to international public health. With the increasing number of people infected, the number of patients with COVID-19 sequelae is also increasing, but there is no specific drug for COVID-19 sequelae. In China, traditional Chinese medicine combined with acupuncture has been widely used in COVID-19 sequelae, but there is still a lack of evidence-based medicine evaluation. The purpose of this study was to evaluate the efficacy and safety of traditional Chinese medicine combined with moxibustion in the treatment of COVID-19 sequelae. METHODS: According to the retrieval strategy, the "long COVID" randomized controlled trial of traditional Chinese medicine combined with moxibustion will be search in eight databases composed of PubMed, Embase, Web of Science, China National knowledge Infrastructure Database, China Biomedical Database and China Science and Technology Journal Database, regardless of publication date or language. The study was screened according to the inclusion and exclusion criteria, and the Cochrane risk bias assessment tool was used to evaluate the quality of the study. Meta-analysis was carried out using RevMan5.3 and STATA12.0 software. Finally, the level of evidence of the results will be evaluated. RESULTS: This study will evaluate whether traditional Chinese medicine combined with moxibustion can effectively treat the symptoms of COVID-19 sequelae. CONCLUSION: This study will provide evidence whether there is benefit of traditional Chinese medicine combined with moxibustion in the treatment of COVID-19 sequelae. At the same time, our research results will provide a reference for clinical decision-making and guiding development in the future.

Core-shell structured Ag@C for direct electrochemistry and hydrogen peroxide biosensor applications.

Ag@C core-shell nano-composites have been prepared by a simple one-step hydrothermal method and are further explored for protein immobilization and bio-sensing. The electrochemical behavior of immobilized horseradish peroxidase (HRP) on Ag@C modified indium-tin-oxide (ITO) electrode and its application as H2O2 sensor are investigated. Electrochemical and UV-vis spectroscopic measurements demonstrated that Ag@C nano-composites provide excellent matrixes for the adsorption of HRP and the entrapped HRP retains its bioactivities. It is found that on the HRP-Ag@C/ITO electrode, HRP exhibited a fast electron transfer process and good electrocatalytic reduction toward H2O2. Under optimum experimental conditions the biosensor linearly responds to H2O2 concentration in the range of 5.0×10⁻7-1.4×10⁻4 M with a detection limit of 2.0×10⁻7 M (S/N=3). The apparent Michaelis-Menten constant (K(app)(M)) of the biosensor is calculated to be 3.75×10⁻5 M, suggesting high enzymatic activity and affinity toward H2O2. In addition, the HRP-Ag@C/ITO bio-electrode shows good reproducibility and long-term stability. Thus, the core-shell structured Ag@C is an attractive material for application in the fabrication of biosensors due to its direct electrochemistry and functionalized surface for efficient immobilization of bio-molecules.

Sensitive electrochemical sensor of tryptophan based on Ag@C core-shell nanocomposite modified glassy carbon electrode.

We here reported a simple electrochemical method for the detection of tryptophan (Trp) based on the Ag@C modified glassy carbon (Ag@C/GC) electrode. The Ag@C core-shell structured nanoparticles were synthesized using one-pot hydrothermal method and characterized by scanning electron microscope (SEM), transmission electron microscope (TEM), and Fourier transform-infrared spectroscopy (FTIR). The electrochemical behaviors of Trp on Ag@C/GC electrode were investigated and exhibited a direct electrochemical process. The favorable electrochemical properties of Ag@C/GC electrode were attributed to the synergistic effect of the Ag core and carbon shell. The carbon shell cannot only protect Ag core but also contribute to the enhanced substrate accessibility and Trp-substrate interactions, while nano-Ag core can display good electrocatalytic activity to Trp at the same time. Under the optimum experimental conditions the oxidation peak current was linearly dependent on the Trp concentration in the range of 1.0×10(-7) to 1.0×10(-4) M with a detection limit of 4.0×10(-8) M (S/N=3). In addition, the proposed electrode was applied for the determination of Trp concentration in real samples and satisfactory results were obtained. The technique offers enhanced sensitivity and may trigger the possibilities of the Ag@C nanocomposite towards diverse applications in biosensor and electroanalysis.