COVID-19 Traumatic Disaster Appraisal and Stress Symptoms Among Health Care Workers: Insights From the Yale Stress Self-assessment.

OBJECTIVE: To determine to what extent did health care workers experience the pandemic as a severe stress event. METHODS: This cross-sectional evaluation of 8299 health care workers, representing a 22% response rate, utilized machine learning to predict high levels of escalating stress based on demographics and known predictors for adverse psychological outcomes after trauma. RESULTS: A third of health care workers experienced the pandemic as a potentially traumatic stress event; a greater proportion of health care workers experienced high levels of escalating stress. Predictive factors included sense of control, ability to manage work-life demands, guilt or shame, age, and level of education. Gender was no longer predictive after controlling for other factors. Escalating stress was especially high among nonclinical academics and clinical private practitioners. CONCLUSION: Findings suggest adverse effects on total worker health, care quality, professionalism, retention, and acute and chronic mental health.

Mobilizing an institutional supportive response for healthcare workers and other staff in the context of COVID-19: The Yale experience.

The burden of the COVID-19 pandemic upon healthcare workers necessitates a systematic effort to support their resilience. This article describes the Yale University and Yale New Haven Health System effort to unite several independent initiatives into a coherent integrated model for institutional support for healthcare workers. Here, we highlight both opportunities and challenges faced in attempting to support healthcare workers during this pandemic.

Mechanism by which Tungsten Oxide Promotes the Activity of Supported V2 O5 /TiO2 Catalysts for NOX Abatement: Structural Effects Revealed by 51 V MAS NMR Spectroscopy.

The selective catalytic reduction (SCR) of NOx with NH3 to N2 with supported V2 O5 (-WO3 )/TiO2 catalysts is an industrial technology used to mitigate toxic emissions. Long-standing uncertainties in the molecular structures of surface vanadia are clarified, whereby progressive addition of vanadia to TiO2 forms oligomeric vanadia structures and reveals a proportional relationship of SCR reaction rate to [surface VOx concentration]2 , implying a 2-site mechanism. Unreactive surface tungsta (WO3 ) also promote the formation of oligomeric vanadia (V2 O5 ) sites, showing that promoter incorporation enhances the SCR reaction by a structural effect generating adjacent surface sites and not from electronic effects as previously proposed. The findings outline a method to assess structural effects of promoter incorporation on catalysts and reveal both the dual-site requirement for the SCR reaction and the important structural promotional effect that tungsten oxide offers for the SCR reaction by V2 O5 /TiO2 catalysts.

In situ and ex situ NMR for battery research.

A rechargeable battery stores readily convertible chemical energy to operate a variety of devices such as mobile phones, laptop computers, electric automobiles, etc. A battery generally consists of four components: a cathode, an anode, a separator and electrolytes. The properties of these components jointly determine the safety, the lifetime, and the electrochemical performance. They also include, but are not limited to, the power density and the charge as well as the recharge time/rate associated with a battery system. An extensive amount of research is dedicated to understanding the physical and chemical properties associated with each of the four components aimed at developing new generations of battery systems with greatly enhanced safety and electrochemical performance at a significantly reduced cost for large scale applications. Advanced characterization tools are a prerequisite to fundamentally understanding battery materials. Considering that some of the key electrochemical processes can only exist under in situ conditions, which can only be captured under working battery conditions when electric wires are attached and current and voltage are applied, make in situ detection critical. Nuclear magnetic resonance (NMR), a non-invasive and atomic specific tool, is capable of detecting all phases, including crystalline, amorphous, liquid and gaseous phases simultaneously and is ideal for in situ detection on a working battery system. Ex situ NMR on the other hand can provide more detailed molecular or structural information on stable species with better spectral resolution and sensitivity. The combination of in situ and ex situ NMR, thus, offers a powerful tool for investigating the detailed electrochemistry in batteries.

Mechanism of Phenol Alkylation in Zeolite H-BEA Using In Situ Solid-State NMR Spectroscopy.

The reaction mechanism of solid-acid-catalyzed phenol alkylation with cyclohexanol and cyclohexene in the apolar solvent decalin has been studied using in situ 13C MAS NMR spectroscopy. Phenol alkylation with cyclohexanol sets in only after a majority of cyclohexanol is dehydrated to cyclohexene. As phenol and cyclohexanol show similar adsorption strength, this strict reaction sequence is not caused by the limited access of phenol to cyclohexanol, but is due to the absence of a reactive electrophile as long as a significant fraction of cyclohexanol is present. 13C isotope labeling demonstrates that the reactive electrophile, the cyclohexyl carbenium ion, is directly formed in a protonation step when cyclohexene is the coreactant. In the presence of cyclohexanol, its protonated dimers at Brønsted acid sites hinder the adsorption of cyclohexene and the formation of a carbenium ion. Thus, it is demonstrated that protonated cyclohexanol dimers dehydrate without the formation of a carbenium ion, which would otherwise have contributed to the alkylation in the kinetically relevant step. Isotope scrambling shows that intramolecular rearrangement of cyclohexyl phenyl ether does not significantly contribute to alkylation at the aromatic ring.

NMR-based Metabolomics Analysis of Liver from C57BL/6 Mouse Exposed to Ionizing Radiation.

The effects of ionizing radiation to human health are of great concern in the field of space exploration and for patients considering radiotherapy. However, to date, the effect of high-dose radiation on metabolism in the liver has not been clearly defined. In this study, 1H nuclear magnetic resonance (NMR)-based metabolomics combined with multivariate data analysis was applied to study the changes of metabolism in the liver of C57BL/6 mouse after whole-body gamma (3.0 and 7.8 Gy) or proton (3.0 Gy) irradiation. Principal component analysis (PCA) and orthogonal projection to latent structures analysis (OPLS) were used for classification and identification of potential biomarkers associated with exposure to gamma and proton radiation. The results show that the radiation exposed groups can be well separated from the control group. Where the same dose was received, the proton exposed group was nevertheless well separated from the gamma-exposed group, indicating that different radiation sources induce different alterations in the metabolic profile. Common among all high-dose gamma and proton exposed groups were the statistically decreased concentrations of choline, O-phosphocholine and trimethylamine N-oxide, while the concentrations of glutamine, glutathione, malate, creatinine, phosphate, betaine and 4-hydroxyphenylacetate were statistically and significantly elevated. Since these altered metabolites are associated with multiple biological pathways, the results suggest that radiation induces abnormality in multiple biological pathways. In particular, metabolites such as 4-hydroxyphenylacetate, betaine, glutamine, choline and trimethylamine N-oxide may be prediagnostic biomarkers candidates for ionizing exposure of the liver.

Multinuclear NMR Study of the Solid Electrolyte Interface Formed in Lithium Metal Batteries.

The composition of the solid electrolyte interphase (SEI) layers formed in Cu|Li cells using lithium bis(fluorosulfonyi)imide (LiFSI) and lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) in 1,2-dimethoxyethane (DME) electrolytes is determined by a multinuclear solid-state MAS NMR study at high magnetic field. It is found that the "dead" metallic Li is largely reduced in the SEI layers formed in a 4 M LiFSI-DME electrolyte system compared with those formed in a 1 M LiFSI-DME electrolyte system. This finding relates directly to the safety of Li metal batteries, as one of the main safety concerns for these batteries is associated with the "dead" metallic Li formed after long-term cycling. It is also found that a large amount of LiF, which exhibits superior mechanical strength and good Li+ ionic conductivity, is observed in the SEI layer formed in the concentrated 4 M LiFSI-DME and 3 M LiTFSI-DME systems but not in the diluted 1 M LiFSI-DME system. Quantitative 6Li MAS NMR results indicate that the SEI associated with the 4 M LiFSI-DME electrolyte is denser than those formed in the 1 M LiFSI-DME and 3 M LiTFSI-DME systems. These studies reveal the fundamental mechanisms behind the excellent electrochemical performance associated with higher concentration LiFSI-DME electrolyte systems.

In Situ Natural Abundance 17O and 25Mg NMR Investigation of Aqueous Mg(OH)2 Dissolution in the Presence of Supercritical CO2.

We report an in situ high-pressure NMR capability that permits natural abundance 17O and 25Mg NMR characterization of dissolved species in aqueous solution and in the presence of supercritical CO2 fluid (scCO2). The dissolution of Mg(OH)2 (brucite) in a multiphase water/scCO2 fluid at 90 atm pressure and 50 °C was studied in situ, with relevance to geological carbon sequestration. 17O NMR spectra allowed identification and distinction of various fluid species including dissolved CO2 in the H2O-rich phase, scCO2, aqueous H2O, and HCO3-. The widely separated spectral peaks for various species can all be observed both dynamically and quantitatively at concentrations as low as 20 mM. Measurement of the concentrations of these individual species also allows an in situ estimate of the hydrogen ion concentration, or pCH+ values, of the reacting solutions. The concentration of Mg2+ can be observed by natural abundance 25Mg NMR at a concentration as low as 10 mM. Quantum chemistry calculations of the NMR chemical shifts on cluster models aided in the interpretation of the experimental results. Evidence for the formation of polymeric Mg2+ clusters at high concentrations in the H2O-rich phase, a possible critical step needed for magnesium carbonate formation, was found.

Sealed rotors for in situ high temperature high pressure MAS NMR.

Here we present the design of reusable and perfectly sealed all-zirconia MAS rotors. The rotors are used to study AlPO4-5 molecular sieve crystallization under hydrothermal conditions, high temperature high pressure cyclohexanol dehydration reaction, and low temperature metabolomics of intact biological tissue.

A Multi-Center Prospective Derivation and Validation of a Clinical Prediction Tool for Severe Clostridium difficile Infection.

BACKGROUND AND AIMS: Prediction of severe clinical outcomes in Clostridium difficile infection (CDI) is important to inform management decisions for optimum patient care. Currently, treatment recommendations for CDI vary based on disease severity but validated methods to predict severe disease are lacking. The aim of the study was to derive and validate a clinical prediction tool for severe outcomes in CDI. METHODS: A cohort totaling 638 patients with CDI was prospectively studied at three tertiary care clinical sites (Boston, Dublin and Houston). The clinical prediction rule (CPR) was developed by multivariate logistic regression analysis using the Boston cohort and the performance of this model was then evaluated in the combined Houston and Dublin cohorts. RESULTS: The CPR included the following three binary variables: age ≥ 65 years, peak serum creatinine ≥ 2 mg/dL and peak peripheral blood leukocyte count of ≥ 20,000 cells/µL. The Clostridium difficile severity score (CDSS) correctly classified 76.5% (95% CI: 70.87-81.31) and 72.5% (95% CI: 67.52-76.91) of patients in the derivation and validation cohorts, respectively. In the validation cohort, CDSS scores of 0, 1, 2 or 3 were associated with severe clinical outcomes of CDI in 4.7%, 13.8%, 33.3% and 40.0% of cases respectively. CONCLUSIONS: We prospectively derived and validated a clinical prediction rule for severe CDI that is simple, reliable and accurate and can be used to identify high-risk patients most likely to benefit from measures to prevent complications of CDI.

Following the transient reactions in lithium-sulfur batteries using an in situ nuclear magnetic resonance technique.

A fundamental understanding of electrochemical reaction pathways is critical to improving the performance of Li-S batteries, but few techniques can be used to directly identify and quantify the reaction species during disharge/charge cycling processes in real time. Here, an in situ (7)Li NMR technique employing a specially designed cylindrical microbattery was used to probe the transient electrochemical and chemical reactions occurring during the cycling of a Li-S system. In situ NMR provides real time, semiquantitative information related to the temporal evolution of lithium polysulfide allotropes during both discharge/charge processes. This technique uniquely reveals that the polysulfide redox reactions involve charged free radicals as intermediate species that are difficult to detect in ex situ NMR studies. Additionally, it also uncovers vital information about the (7)Li chemical environments during the electrochemical and parasitic reactions on the Li metal anode. These new molecular-level insights about transient species and the associated anode failure mechanism are crucial to delineating effective strategies to accelerate the development of Li-S battery technologies.

Probing lithium germanide phase evolution and structural change in a germanium-in-carbon nanotube energy storage system.

Lithium alloys of group IV elements such as silicon and germanium are attractive candidates for use as anodes in high-energy-density lithium-ion batteries. However, the poor capacity retention arising from volume swing during lithium cycling restricts their widespread application. Herein, we report high reversible capacity and superior rate capability from core-shell structure consisting of germanium nanorods embedded in multiwall carbon nanotubes. To understand how the core-shell structure helps to mitigate volume swings and buffer against mechanical instability, transmission electron microscopy, X-ray diffraction, and in situ (7)Li nuclear magnetic resonance were used to probe the structural rearrangements and phase evolution of various Li-Ge alloy phases during (de)alloying reactions with lithium. The results provide insights into amorphous-to-crystalline transition and lithium germanide alloy phase transformation, which are important reactions controlling performance in this system.

A fundamental study on the [(µ-Cl)3Mg2(THF)6]+ dimer electrolytes for rechargeable Mg batteries.

The long sought solvated [MgCl](+) species in the Mg-dimer electrolytes was characterized by soft mass spectrometry. The presented study provides an insightful understanding on the electrolyte chemistry of rechargeable Mg batteries.

1H NMR Metabolomics Study of Metastatic Melanoma in C57BL/6J Mouse Spleen.

Melanoma is a malignant tumor of melanocytes. Although extensive investigations have been done to study metabolic changes in primary melanoma in vivo and in vitro, little effort has been devoted to metabolic profiling of metastatic tumors in organs other than lymph nodes. In this work, NMR-based metabolomics combined with multivariate data analysis is used to study metastatic B16-F10 melanoma in C57BL/6J mouse spleen. Principal Component Analysis (PCA), an unsupervised multivariate data analysis method, is used to detect possible outliers, while Orthogonal Projection to Latent Structure (OPLS), a supervised multivariate data analysis method, is employed to find important metabolites responsible for discriminating the control and the melanoma groups. Two different strategies, i.e. spectral binning and spectral deconvolution, are used to reduce the original spectral data before statistical analysis. Spectral deconvolution is found to be superior for identifying a set of discriminatory metabolites between the control and the melanoma groups, especially when the sample size is small. OPLS results show that the melanoma group can be well separated from its control group. It is found that taurine, glutamate, aspartate, O-Phosphoethanolamine, niacinamide,ATP, lipids and glycerol derivatives are decreased statistically and significantly while alanine, malate, xanthine, histamine, dCTP, GTP, thymidine, 2'-Deoxyguanosine are statistically and significantly elevated. These significantly changed metabolites are associated with multiple biological pathways and may be potential biomarkers for metastatic melanoma in spleen.

Reduction mechanism of fluoroethylene carbonate for stable solid­electrolyte interphase film on silicon anode.

Fluoroethylene carbonate (FEC) is an effective electrolyte additive that can significantly improve the cycling ability of silicon and other anode materials. However, the fundamental mechanism of this improvement is still not well understood. Based on the results obtained from (6)Li NMR and X-ray photoelectron spectroscopy studies, we propose a molecular-level mechanism for how FEC affects the formation of solid electrolyte interphase (SEI) film: 1) FEC is reduced through the opening of the five-membered ring leading to the formation of lithium poly(vinyl carbonate), LiF, and some dimers; 2) the FEC-derived lithium poly(vinyl carbonate) enhances the stability of the SEI film. The proposed reduction mechanism opens a new path to explore new electrolyte additives that can improve the cycling stability of silicon-based electrodes.

Energetics of defects on graphene through fluorination.

Functionalized graphene sheets (FGSs) comprise a unique member of the carbon family, demonstrating excellent electrical conductivity and mechanical strength. However, the detailed chemical composition of this material is still unclear. Herein, we take advantage of the fluorination process to semiquantitatively probe the defects and functional groups on graphene surface. Functionalized graphene sheets are used as substrate for low-temperature (<150 °C) direct fluorination. The fluorine content has been modified to investigate the formation mechanism of different functional groups such as C-F, CF2, O-CF2 and (C=O)F during fluorination. The detailed structure and chemical bonds are simulated by density functional theory (DFT) and quantified experimentally by nuclear magnetic resonance (NMR). The electrochemical properties of fluorinated graphene are also discussed extending the use of graphene from fundamental research to practical applications.

Following solid-acid-catalyzed reactions by MAS NMR spectroscopy in liquid phase--zeolite-catalyzed conversion of cyclohexanol in water.

A microautoclave magic angle spinning NMR rotor is developed enabling in situ monitoring of solid-liquid-gas reactions at high temperatures and pressures. It is used in a kinetic and mechanistic study of the reactions of cyclohexanol on zeolite HBEA in 130 °C water. The (13) C spectra show that dehydration of 1-(13) C-cyclohexanol occurs with significant migration of the hydroxy group in cyclohexanol and the double bond in cyclohexene with respect to the (13) C label. A simplified kinetic model shows the E1-type elimination fully accounts for the initial rates of 1-(13) C-cyclohexanol disappearance and the appearance of the differently labeled products, thus suggesting that the cyclohexyl cation undergoes a 1,2-hydride shift competitive with rehydration and deprotonation. Concurrent with the dehydration, trace amounts of dicyclohexyl ether are observed, and in approaching equilibrium, a secondary product, cyclohexyl-1-cyclohexene is formed. Compared to phosphoric acid, HBEA is shown to be a more active catalyst exhibiting a dehydration rate that is 100-fold faster per proton.

Clostridium difficile strain NAP-1 is not associated with severe disease in a nonepidemic setting.

BACKGROUND & AIMS: Recent outbreaks of Clostridium difficile infection (CDI) in North America and in Europe with very high case-fatality rates have been associated with infection by North American Pulsed Field Type I (NAP-1) isolates. This study examined whether NAP-1 strains are associated with worse outcomes of CDI in a nonepidemic, nosocomial setting. METHODS: All cases of CDI that occurred over a 13-month period at a tertiary medical center were examined for risk factors associated with increased severity of CDI and other outcomes. Stool samples from each patient were cultured for C difficile and the resulting isolates were strain-typed by pulsed-field gel electrophoresis. RESULTS: Strain types were obtained from 236 of 272 CDI samples; the NAP-1 strain was identified in 59 (25%). In this inpatient cohort of patients with CDI, the incidence of in hospital death was 12.1% and of death caused by CDI was 4.0%. Of the patients with CDI, 22.1% met the combined outcome end point of severe CDI. In both univariate and multivariate analyses, patients infected with the NAP-1 strain did not have worse outcomes compared with those infected with non-NAP-1 strains. Infection with the NAP-1 strain was correlated with admission from outside health care facilities regardless of whether symptoms of CDI began before or after admission to the study hospital. CONCLUSIONS: The NAP-1 strain of C difficile was found to cause 25% of cases of CDI in the hospital where the study was performed. However, compared with non-NAP-1 strains, CDI was not associated with increased severity of disease in this nonepidemic setting.

Prospective derivation and validation of a clinical prediction rule for recurrent Clostridium difficile infection.

BACKGROUND & AIMS: Prevention of recurrent Clostridium difficile infection (CDI) is a substantial therapeutic challenge. A previous prospective study of 63 patients with CDI identified risk factors associated with recurrence. This study aimed to develop a prediction rule for recurrent CDI using the above derivation cohort and prospectively evaluate the performance of this rule in an independent validation cohort. METHODS: The clinical prediction rule was developed by multivariate logistic regression analysis and included the following variables: age>65 years, severe or fulminant illness (by the Horn index), and additional antibiotic use after CDI therapy. A second rule combined data on serum concentrations of immunoglobulin G (IgG) against toxin A with the clinical predictors. Both rules were then evaluated prospectively in an independent cohort of 89 patients with CDI. RESULTS: The clinical prediction rule discriminated between patients with and without recurrent CDI, with an area under the curve of the receiver-operating-characteristic curve of 0.83 (95% confidence interval [CI]: 0.70-0.95) in the derivation cohort and 0.80 (95% CI: 0.67-0.92) in the validation cohort. The rule correctly classified 77.3% (95% CI: 62.2%-88.5%) and 71.9% (95% CI: 59.2%-82.4%) of patients in the derivation and validation cohorts, respectively. The combined rule performed well in the derivation cohort but not in the validation cohort (area under the curve of the receiver-operating-characteristic curve, 0.89 vs 0.62; diagnostic accuracy, 93.8% vs 69.2%, respectively). CONCLUSIONS: We prospectively derived and validated a clinical prediction rule for recurrent CDI that is simple, reliable, and accurate and can be used to identify high-risk patients most likely to benefit from measures to prevent recurrence.