Development of a quadruple qRT-PCR assay for simultaneous identification of hypervirulent and carbapenem-resistant Klebsiella pneumoniae.

IMPORTANCE: Globally, the increasing number of hypervirulent Klebsiella pneumoniae (hvKp) and carbapenem-resistant Kp (CR-Kp) infections poses a huge public health challenge with high morbidity and mortality. Worrisomely, due to the mobility of elements carrying virulence and drug-resistance genes, the increasing prevalence of CR-hvKp has also been found with an overwhelming mortality rate in recent years. However, the current detection methods for hvKp and CR-Kp have many disadvantages, such as long turnaround time, complex operation, low sensitivity, and specificity. Herein, a more sensitive, rapid, single-reaction, and multiplex quantitative real-time PCR was developed and validated to differentiate the circulating lineages of Kp with excellent performance in sensitivity and specificity, providing a useful tool for the differential diagnosis and the surveillance of the circulating Kp.

Experimental and Modeling Study on the Ignition Kinetics of Nitromethane behind Reflected Shock Waves.

Nitromethane (NM) is the simplest nitroalkane fuel and has demonstrated potential usage as propellant and fuel additive. Thus, understanding the combustion characteristics and chemistry of NM is critical to the development of hierarchical detailed kinetic models of nitro-containing energetic materials. Herein, to further investigate the ignition kinetics of NM and supplement the experimental database for kinetic mechanism development, an experimental and kinetic modeling analysis of the ignition delay times (IDTs) of NM behind reflected shock waves at high fuel concentrations is reported against previous studies. Specifically, the IDTs of NM are measured via a high-pressure shock tube within the temperature from 900 to 1150 K at pressures of 5 and 10 bar and equivalence ratios of 0.5, 1.0, and 2.0. Brute-force sensitivity analysis and chemical explosive mode analysis in combination with reaction path analysis are employed to reveal the fundamental ignition kinetics of NM. Finally, a skeletal mechanism for NM is derived via the combination of directed relation graph-based methods, which demonstrates good prediction accuracy of NM ignition and flame speeds. The present work should be valuable for understanding the combustion chemistry of NM and the development of the fundamental reaction mechanism of nitroalkane fuels.

Clinical features and transmission risk analysis of dengue virus infections in Shenzhen, During 2014-2019.

Dengue fever (DF) and dengue hemorrhagic fever (DHF) are among the most common tropical diseases affecting humans. To analyze the risk of clinical and transmission of DF/DHF in Shenzhen, the surveillance on patients of all-age patients with dengue virus (DENV) infections was conducted. Our findings revealed that the majority of DENV-infected patients are young to middle-aged males, and the development of the disease is accompanied by abnormal changes in the percentages of neutrophils, lymphocytes, and basophils. Demographic analysis revealed that these patients is concentrated in areas such as Futian District, which may be due to the higher mosquito density and temperature than that in other area. Subsequent, mosquito infection experiments confirmed that the effect of temperature shift on DENV proliferation and transmission. Not only that, constant temperatures can enhance the spread of DENV, even increase the risk of epidemic. Thus, the role of innate immune response should be highlighted in the prediction of severe severity of DENV-infected patients, and temperature should be taken into account in the prevention and control of DENV. Introduction: Dengue fever (DF) and dengue hemorrhagic fever (DHF) are among the most common tropical diseases affecting humans, and which caused by the four dengue virus serotypes (DENV 1-4). Objectives: To analyze the risk of clinical and transmission of DF/DHF in Shenzhen. Methods: The surveillance on patients of all-age patients with dengue virus (DENV) infections was conducted. Results: Our findings revealed that the majority of DENV-infected patients are young to middle-aged males, and the development of the disease is accompanied by abnormal changes in the percentages of neutrophils, lymphocytes, and basophils. Demographic analysis revealed that these patients is concentrated in areas such as Futian District, which may be due to the higher mosquito density and temperature than that in other area. Subsequent, mosquito infection experiments confirmed that the effect of temperature shift on DENV proliferation and transmission. Not only that, constant temperatures can enhance the spread of DENV, even increase the risk of epidemic. Conclusion: 1. Elevated levels of neutrophils, lymphocytes, basophils, and temperature are all significant risk factors for dengue transmission and pathogenesis; 2. Temperature increasing is associated with a higher risk of dengue transmission; 3. Fluctuations in temperature around 28 °C (28 ± 5 °C) would increase dengue transmission.

Viral and antibody dynamics of acute infection with SARS-CoV-2 omicron variant (B.1.1.529): a prospective cohort study from Shenzhen, China.

BACKGROUND: Elucidating viral dynamics within the host is important for designing public health measures against SARS-CoV-2, particularly during the early stages of infection when transmission potential rapidly increases. We aimed to analyse the viral and antibody dynamics of the omicron variant in relation to symptom onset or laboratory confirmation and replication dynamics throughout the infection course. METHODS: In this prospective cohort study, patients with laboratory-confirmed SARS-CoV-2 infection who were admitted to Shenzhen Third People's Hospital (Shenzhen, China) between Jan 11, 2020, and April 24, 2022, were screened for eligibility. We included immunocompetent individuals with acute SARS-CoV-2 infection without antiviral agents targeting SARS-CoV-2. Serial nasopharyngeal swabs and plasma samples were analysed for viral RNAs and specific IgG antibodies of SARS-CoV-2. The comparative viral and antibody kinetics in association with symptom onset or laboratory confirmation and replication dynamics throughout the infection course were calculated by the locally estimated scatterplot smoothing curve fitting polynomial regression. The associations between viral and antibody dynamics and vaccination, age, sex, disease severity, and underlying health conditions were analysed using the Mann-Whitney U test and the Gehan-Breslow-Wilcoxon method. FINDINGS: 15 406 serial nasopharyngeal swabs and 2324 plasma samples were taken from 2043 individuals with acute SARS-CoV-2 infection (n=217 prototype [A.1] and D614G [B.1] variant [wild-type]; n=105 delta variant [B.1.617.2]; n=1721 omicron variant [B.1.1.529]) and were included for the analyses. The mean Ct value of omicron variant on the first day post symptom onset (dpo; defined as the first day post laboratory confirmation in asymptomatic participants) was 22·65 (95% CI 22·05-23·26). Peak viral load was reached with a mean Ct value of 17·63 (17·47-17·79) at a mean of 3·19 dpo (95% CI 3·09-3·28), and viral clearance (Ct values ≥35) was reached at a mean of 13·50 dpo (95% CI 13·32-13·67). Omicron variant showed faster viral replication and clearance than wild-type SARS-CoV-2 and delta variant, and the viral load at the first dpo and the peak viral load was lower than delta variant but higher than wild-type SARS-CoV-2. Age, sex, disease severity, and underlying health conditions were associated with the viral dynamics of omicron variant, with faster viral clearance found in young (aged 0-14 years), male, and asymptomatic participants, and those without underlying health conditions. Replication dynamics thoughout the infection course showed that peak viral load was reached at a mean of 5·06 dpo (4·76-5·36) and viral clearance took a mean of 14·27 days (13·6-14·93) for omicron variant. SARS-CoV-2-specific IgG increased earlier and faster to significantly higher concentrations in breakthrough infection than naive infection with omicron variant, despite long intervals (≥7 months) between the last dose of vaccination and infection. INTERPRETATION: Our data provide a comprehensive overview of the longitudinal viral and antibody dynamics of omicron variant in people with acute SARS-CoV-2 infection, with important implications for public health strategies, including population screening, antiviral treatment, isolation periods, and vaccination. FUNDING: National Natural Science Foundation of China and Emergency Key Program of Guangzhou Laboratory. TRANSLATION: For the Chinese translation of the abstract see Supplementary Materials section.

Rational Design and Characterization of Trispecific Antibodies Targeting the HIV-1 Receptor and Envelope Glycoprotein.

Multitudinous broadly neutralizing antibodies (bNAbs) against HIV-1 have been developed as novel antiviral prophylactic and therapeutic agents. Combinations of bNAbs are generally even more effective than when they are applied individually, showing excellent neutralization coverage and limiting the emergence of escape mutants. In this study, we investigated the design and characterization of three trispecific antibodies that allow a single molecule to interact with independent HIV-1 envelope determinants-(1) the host receptor CD4, (2) the host co-receptor CCR5 and (3) distinct domains in the envelope glycoprotein of HIV-1-using an ELISA, an HIV-1 pseudovirus neutralization assay and in vivo antiviral experiments in humanized mice. We found that trispecific bNAbs and monovalent ones all had satisfactory binding activities against the corresponding antigens in the ELISA, exhibited higher potency and breadth than any previously described single bnAb in the HIV-1 pseudovirus neutralization assay and showed an excellent antiviral effect in vivo. The trispecific antibodies simultaneously recognize the host receptor CD4, host co-receptor CCR5 and HIV-1 envelope glycoprotein, which could mean they have promise as prophylactic and therapeutic agents against HIV-1.

Experimental and Kinetic Modeling Study on High-Temperature Autoignition of Cyclohexene.

Cyclohexene is an important intermediate during the oxidation of cycloalkanes, which comprise a significant portion of real fuels. Thus, experimental data sets and kinetic models of cyclohexene play an important role in the understanding of the combustion of cycloalkanes and real fuels. In this work, an experimental and kinetic modeling study of the high-temperature ignition of cyclohexene is performed. Ignition delay time (IDT) measurements are carried out in a high-pressure shock tube (HPST). The studied pressures are 5, 10, and 20 bar; the equivalence ratios are 0.5, 1.0, and 2.0; and the temperatures range from 980 to 1400 K for IDT in HPST. It is shown that the IDTs of cyclohexene exhibit Arrhenius behaviors as a function of temperature, and the IDTs decrease as the equivalence ratio and pressure increase. The experimental results are simulated using three previous detailed kinetic mechanisms and an updated detailed mechanism in this work. The updated detailed kinetic mechanism exhibits good agreement with experimental results. Reaction path analysis and sensitivity analysis are performed to provide insights into the chemical kinetics controlling the ignition of cyclohexene. The results demonstrate that different detailed kinetic mechanisms are significantly different, and there are still no unified conclusions about the major reaction path for cyclohexene oxidation. However, it is worth noting that the abstraction reaction by oxygen at the allylic site and the submechanism of cyclopentene are of significant importance for the accurate prediction of IDTs of cyclohexene. The present experimental data set and kinetic model should be valuable to improve our understanding of the combustion chemistry of cycloalkanes.

A Hierarchical Theoretical Study of the Hydrogen Abstraction Reactions of H2/C1-C4 Molecules by the Methyl Peroxy Radical and Implications for Kinetic Modeling.

The hydrogen atom abstraction by the methyl peroxy radical (CH3O2) is an important reaction class in detailed chemical kinetic modeling of the autoignition properties of hydrocarbon fuels. Systematic theoretical studies are performed on this reaction class for H2/C1-C4 fuels, which is critical in the development of a base model for large fuels. The molecules include hydrogen, alkanes, alkenes, and alkynes with a carbon number from 1 to 4. The B2PLYP-D3/cc-pVTZ level of theory is employed to optimize the geometries of all of the reactants, transition states, and products and also the treatments of hindered rotation for lower frequency modes. Accurate benchmark calculations for abstraction reactions of hydrogen, methane, and ethylene with CH3O2 are performed by using the coupled cluster method with explicit inclusion of single and double electron excitations and perturbative inclusion of triple electron excitations (CCSD(T)), the domain-based local pair-natural orbital coupled cluster method (DLPNO-CCSD(T)), and the explicitly correlated CCSD(T)-F12 method with large basis sets. Reaction rate constants are computed via conventional transition state theory with quantum tunneling corrections. The computed rate constants are compared with literature values and those employed in detailed chemical kinetic mechanisms. The calculated rate constants are implemented into the recently developed NUIGMECH1.1 base model for kinetic modeling of ignition properties.

Simultaneous detection of Zika, chikungunya, dengue, yellow fever, West Nile, and Japanese encephalitis viruses by a two-tube multiplex real-time RT-PCR assay.

Due to the concurrent prevalence and increasing risk of coinfection of the clinically important Arboviruses, timely and accurate differential diagnosis is important for clinical management and the epidemiological investigation. A two-tube multiplex real-time reverse transcription-polymerase chain reaction (RT-PCR) assay for the simultaneous detection of Zika virus (ZIKV), chikungunya virus (CHIKV), dengue virus (DENV), yellow fever virus (YFV), West Nile virus (WNV), and Japanese encephalitis virus (JEV) was developed and optimized with high specificity and sensitivity. The detection limit for all the six viruses could reach as low as five genome equivalent copies and 2.8 × 10-3 tissue culture infectious doses (TCID50 ) for ZIKV, YFV, CHIKV and 2.8 × 10-2 TCID50  for JEV per reaction, with high accuracy and precision (R2 > 0.99). The coefficient of variation of intra-assay and inter-assay for our quantitative reverse transcription-polymerase chain reaction (qRT-PCR) assay was low, and the obtained positive rates ad Ct values of this assay were comparable with singleplex commercial kits. Moreover, the multiplex qRT-PCR assay was able to detect possible co-infections without competitive inhibition of target viral genomes. In conclusion, our rapid, sensitive, cost-effective multiplex qRT-PCR will be of great use for differential diagnosis in a clinical setting and epidemiological investigation during surveillance.

Data-driven machine learning model for the prediction of oxygen vacancy formation energy of metal oxide materials.

Metal oxides are widely used in the fields of chemistry, physics and materials science. Oxygen vacancy formation energy is a key parameter to describe the chemical, mechanical, and thermodynamic properties of metal oxides. How to acquire quickly and accurately oxygen vacancy formation energy remains a challenge for both experimental and theoretical researchers. Herein, we propose a machine learning model for the prediction of oxygen vacancy formation energy via data-driven analysis and the definition of simple descriptors. Starting with the database containing oxygen vacancy formation energies for 1750 metal oxides with enough structural diversity, new descriptors that effectively avoid the defects of molecular fingerprints, molecular graphic descriptors and site descriptors are defined. The descriptors have obvious physical meanings and wide practicability. Multiple linear regression analysis is then used to screen important features for machine learning model development, and two strongly associated features are obtained. The selected descriptors are used as input for the training of 21 machine learning models to select and develop the most accurate machine learning model. Finally, it is shown that the least squares support vector regression method exhibits the best performance for accurate prediction of the targeted oxygen vacancy formation energy through systematic error analysis, and the prediction accuracy is also verified by the external dataset. Our work establishes a novel and simple computational approach for accurate prediction of the oxygen vacancy formation energy of metal oxides and highlights the availability of data-driven analysis for metal oxide material research.

Single-Pulse Shock Tube Experimental and Kinetic Modeling Study on Pyrolysis of a Direct Coal Liquefaction-Derived Jet Fuel and Its Blends with the Traditional RP-3 Jet Fuel.

A basic understanding of the high-temperature pyrolysis process of jet fuels is not only valuable for the development of combustion kinetic models but also critical to the design of advanced aeroengines. The development and utilization of alternative jet fuels are of crucial importance in both military and civil aviation. A direct coal liquefaction (DCL) derived liquid fuel is an important alternative jet fuel, yet fundamental pyrolysis studies on this category of jet fuels are lacking. In the present work, high-temperature pyrolysis studies on a DCL-derived jet fuel and its blend with the traditional RP-3 jet fuel are carried out by using a single-pulse shock tube (SPST) facility. The SPST experiments are performed at averaged pressures of 5.0 and 10.0 bar in the temperature range around 900-1800 K for 0.05% fuel diluted by argon. Major intermediates are obtained and quantified using gas chromatography analysis. A flame-ionization detector and a thermal conductivity detector are used for species identification and quantification. Ethylene is the most abundant product for the two fuels in the pyrolysis process. Other important intermediates such as methane, ethane, propyne, acetylene, and 1,3-butadiene are also identified and quantified. The pyrolysis product distributions of the pure RP-3 jet fuel are also performed. Kinetic modeling is performed by using a modern detailed mechanism for the DCL-derived jet fuel and its blends with the RP-3 jet fuel. Rate-of-production analysis and sensitivity analysis are conducted to compare the differences of the chemical kinetics of the pyrolysis process of the two jet fuels. The present work is not only valuable for the validation and development of detailed combustion mechanisms for alternative jet fuels but also improves our understanding of the pyrolysis characteristics of alternative jet fuels.

Accelerating the optimization of enzyme-catalyzed synthesis conditions via machine learning and reactivity descriptors.

Enzyme-catalyzed synthesis reactions are of crucial importance for a wide range of applications. An accurate and rapid selection of optimal synthesis conditions is crucial and challenging for both human knowledge and computer predictions. In this work, a new scenario, which combines a data-driven machine learning (ML) model with reactivity descriptors, is developed to predict the optimal enzyme-catalyzed synthesis conditions and the reaction yield. Fourteen reactivity descriptors in total are constructed to describe 125 reactions (classified into five categories) included in different reaction mechanisms. Nineteen ML models are developed to train the dataset and the Quadratic support vector machine (SVM) model is found to exhibit the best performance. The Quadratic SVM model is then used to predict the optimal reaction conditions, which are subsequently used to obtain the highest yield among 109 200 reaction conditions with different molar ratios of substrates, solvents, water contents, enzyme concentrations and temperatures for each reaction. The proposed protocol should be generally applicable to a diverse range of chemical reactions and provides a black-box evaluation for optimizing the reaction conditions of organic synthesis reactions.

Single-Pulse Shock Tube Pyrolysis Study of RP-3 Jet Fuel and Kinetic Modeling.

A single-pulse shock tube study of the pyrolysis of two different concentrations of Chinese RP-3 jet fuel at 5 bar in the temperature range of 900-1800 K has been performed in this work. Major intermediates are obtained and quantified using gas chromatography analysis. A flame-ionization detector and a thermal conductivity detector are used for species identification and quantification. Ethylene is the most abundant product in the pyrolysis process. Other important intermediates such as methane, ethane, propyne, acetylene, butene, and benzene are also identified and quantified. Kinetic modeling is performed using several detailed, semidetailed, and lumped mechanisms. It is found that the predictions for the major species such as ethylene, propene, and methane are acceptable. However, current kinetic mechanisms still need refinement for some important species. Different kinetic mechanisms exhibit very different performance in the prediction of certain species during the pyrolysis process. The rate of production (ROP) is carried out to compare the differences among these mechanisms and to identify major reaction pathways to the formation and consumption of the important species, and the results indicate that further studies on the thermal decomposition of 1,3-butadiene are needed to optimize kinetic models. The experimental data are expected to contribute to a database for the validation of mechanisms under pyrolytic conditions for RP-3 jet fuel and should also be valuable to a better understanding of the combustion behavior of RP-3 jet fuel.

Benchmark calculations for bond dissociation energies and enthalpy of formation of chlorinated and brominated polycyclic aromatic hydrocarbons.

Thermodynamic properties, i.e., bond dissociation energies and enthalpy of formation, of chlorinated and brominated polycyclic aromatic hydrocarbons play a fundamental role in understanding their formation mechanisms and reactivity. Computational electronic structure calculations routinely used to predict thermodynamic properties of various species are limited for these compounds due to large computational cost to obtain accurate results by employing high-level wave function theory methods. In this work, a number of composite model chemistry methods (CBS-QB3, G3MP2, G3, and G4) are used to compute bond dissociation energies and enthalpies of formation of small to medium-size chlorinated and brominated polycyclic aromatic hydrocarbon compounds. The enthalpy of formation is derived via the atomization method and compared against the recommended values. Statistical analysis indicates that G4 is the best method. For comparison, three commonly used density functional theory (DFT) methods (M06-2X, ωB97X-D and B2PLYP-D3) with various basis sets including 6-311++G(d, p), cc-pVTZ, and cc-pVQZ in the prediction of bond dissociation energies and enthalpies of formation have been tested using the optimized geometries at the same M06-2X/6-311++G(d, p) level of theory. It is found that ωB97X-D/6-311++G(d, p) shows the best performance in computing the bond dissociation energies, while ωB97X-D/cc-pVTZ exhibits the best prediction in enthalpy of formation of the studied reaction systems. The structural effect on the bond dissociation energies and enthalpy of formation of chlorinated and brominated polycyclic aromatic hydrocarbons are then systematically analyzed. Based on comparisons of the various methods, reliable DFT methods are recommended for future theoretical studies on large chlorinated and brominated polycyclic aromatic hydrocarbons considering both accuracy and computational cost. This work, to the authors' knowledge, is the first to systematically benchmark theoretical methods for the accurate prediction of thermodynamic properties for chlorinated and brominated polycyclic aromatic hydrocarbons.

Au/SBA-15 catalyst prepared by ozone treatment and importance of negatively charged gold in CO oxidation by DRIFTS.

There is a lack of consensus on the charge state of active gold species in catalytic CO oxidation reaction. Herein, Au/SBA-15 catalyst was prepared by room temperature ozone treatment. Through diffuse reflectance Fourier-transform infrared spectroscopy (DRIFTS), two different gold species, Au0 and Auδ- with CO adsorption at about 2112 cm-1 and 2077 cm-1, were observed on Au/SBA-15. In CO oxidation mixture, the 2077 cm-1 band is completely attenuated while the 2112 cm-1 band retains some intensity. CO-Auδ- bonding is weaker than that of CO-Au0, but CO-Auδ- exhibits higher reactivity towards oxygen. Ozone treatment produces AuOx nanoparticles that is not stable and decomposes to metallic Au gradually. To our best knowledge, this is the first time to identify the presence and importance of Auδ- species for "inert" SiO2 supported gold catalyst.

Chemical Kinetics of Hydrogen Atom Abstraction from Propargyl Sites by Hydrogen and Hydroxy Radicals.

Hydrogen atom abstraction from propargyl C-H sites of alkynes plays a critical role in determining the reactivity of alkyne molecules and understanding the formation of soot precursors. This work reports a systematic theoretical study on the reaction mechanisms and rate constants for hydrogen abstraction reactions by hydrogen and hydroxy radicals from a series of alkyne molecules with different structural propargyl C-H atoms. Geometry optimizations and frequency calculations for all species are performed at M06-2X/cc-pVTZ level of theory and the hindered internal rotations are also treated at this level. The high-level W1BD and CCSD(T)/CBS theoretical calculations are used as a benchmark for a series of DFT calculations toward the selection of accurate DFT functionals for large reaction systems in this work. Based on the quantum chemistry calculations, rate constants are computed using the canonical transition state theory with tunneling correction and the treatment of internal rotations. The effects of the structure and reaction site on the energy barriers and rate constants are examined systematically. To the best of our knowledge, this work provides the first systematic study for one of the key initiation abstraction reactions for compounds containing propargyl hydrogen atoms.

Reaction Mechanisms and Kinetics of the Hydrogen Abstraction Reactions of C4⁻C6 Alkenes with Hydroxyl Radical: A Theoretical Exploration.

The reaction of alkenes with hydroxyl (OH) radical is of great importance to atmospheric and combustion chemistry. This work used a combined ab initio/transition state theory (TST) method to study the reaction mechanisms and kinetics for hydrogen abstraction reactions by OH radical on C4⁻C6 alkenes. The elementary abstraction reactions involved were divided into 10 reaction classes depending upon the type of carbon atoms in the reaction center. Geometry optimization was performed by using DFT M06-2X functional with the 6-311+G(d,p) basis set. The energies were computed at the high-level CCSD(T)/CBS level of theory. Linear correlation for the computed reaction barriers and enthalpies between M06-2X/6-311+G(d,p) and CCSD(T)/CBS methods were found. It was shown that the C=C double bond in long alkenes not only affected the related allylic reaction site, but also exhibited a large influence on the reaction sites nearby the allylic site due to steric effects. TST in conjunction with tunneling effects were employed to determine high-pressure limit rate constants of these abstraction reactions and the computed overall rate constants were compared with the available literature data.