Differential impact of COVID-19 on mental health and burnout

BACKGROUND

There may be differential impact of the COVID-19 pandemic on mental health and burnout rates of healthcare professionals (HCPs) performing different roles.

AIMS

To examine mental health and burnout rates, and possible drivers for any disparities between professional roles.

METHODS

In this cohort study, online surveys were distributed to HCPs in July-September 2020 (baseline) and re-sent 4 months later (follow-up; December 2020) assessing for probable major depressive disorder (MDD), generalized anxiety disorder (GAD), insomnia, mental well-being and burnout (emotional exhaustion and depersonalization). Separate logistic regression models (at both phases) compared the risk of outcomes between roles: healthcare assistants (HCAs), nurses and midwives (nurses), allied health professionals (AHPs) and doctors (reference group). Separate linear regression models were also developed relating the change in scores to professional role.

RESULTS

At baseline (n = 1537), nurses had a 1.9-fold and 2.5-fold increased risk of MDD and insomnia, respectively. AHPs had a 1.7-fold and 1.4-fold increased risk of MDD and emotional exhaustion, respectively. At follow-up (n = 736), the disproportionate risk between doctors and others worsened: nurses and HCAs were at 3.7-fold and 3.6-fold increased risk of insomnia, respectively. Nurses also had a significantly increased risk of MDD, GAD, poor mental well-being and burnout. Nurses also had significantly worsened anxiety, mental well-being and burnout scores over time, relative to doctors.

CONCLUSIONS

Nurses and AHPs had excess risk of adverse mental health and burnout during the pandemic, and this difference worsened over time (in nurses especially). Our findings support adoption of targeted strategies accounting for different HCP roles.

First-principles spectroscopy of aqueous interfaces using machine-learned electronic and quantum nuclear effects

Vibrational spectroscopy is a powerful approach to visualising interfacial phenomena. However, extracting structural and dynamical information from vibrational spectra is a challenge that requires first-principles simulations, including non-Condon and quantum nuclear effects. We address this challenge by developing a machine-learning enhanced first-principles framework to speed up predictive modelling of infrared, Raman, and sum-frequency generation spectra. Our approach uses machine learning potentials that encode quantum nuclear effects to generate quantum trajectories using simple molecular dynamics efficiently. In addition, we reformulate bulk and interfacial selection rules to express them unambiguously in terms of the derivatives of polarisation and polarisabilities of the whole system and predict these derivatives efficiently using fully-differentiable machine learning models of dielectric response tensors. We demonstrate our framework's performance by predicting the IR, Raman, and sum-frequency generation spectra of liquid water, ice and the water-air interface by achieving near quantitative agreement with experiments at nearly the same computational efficiency as pure classical methods. Finally, to aid the experimental discovery of new phases of nanoconfined water, we predict the temperature-dependent vibrational spectra of monolayer water across the solid-hexatic-liquid phases transition.

Many-Body Methods for Surface Chemistry Come of Age: Achieving Consensus with Experiments

The adsorption energy of a molecule onto the surface of a material underpins a wide array of applications, spanning heterogeneous catalysis, gas storage, and many more. It is the key quantity where experimental measurements and theoretical calculations meet, with agreement being necessary for reliable predictions of chemical reaction rates and mechanisms. The prototypical molecule-surface system is CO adsorbed on MgO, but despite intense scrutiny from theory and experiment, there is still no consensus on its adsorption energy. In particular, the large cost of accurate many-body methods makes reaching converged theoretical estimates difficult, generating a wide range of values. In this work, we address this challenge, leveraging the latest advances in diffusion Monte Carlo (DMC) and coupled cluster with single, double, and perturbative triple excitations [CCSD(T)] to obtain accurate predictions for CO on MgO. These reliable theoretical estimates allow us to evaluate the inconsistencies in published temperature-programed desorption experiments, revealing that they arise from variations in employed pre-exponential factors. Utilizing this insight, we derive new experimental estimates of the (electronic) adsorption energy with a (more) precise pre-exponential factor. As a culmination of all of this effort, we are able to reach a consensus between multiple theoretical calculations and multiple experiments for the first time. In addition, we show that our recently developed cluster-based CCSD(T) approach provides a low-cost route toward achieving accurate adsorption energies. This sets the stage for affordable and reliable theoretical predictions of chemical reactions on surfaces to guide the realization of new catalysts and gas storage materials.

Quantum dynamics using path integral coarse-graining

Vibrational spectra of condensed and gas-phase systems containing light nuclei are influenced by their quantum-mechanical behaviour. The quantum dynamics of light nuclei can be approximated by the imaginary time path integral (PI) formulation, but still at a large computational cost that increases sharply with decreasing temperature. By leveraging advances in machine-learned coarse-graining, we develop a PI method with the reduced computational cost of a classical simulation. We also propose a simple temperature elevation scheme to significantly attenuate the artefacts of standard PI approaches and also eliminate the unfavourable temperature scaling of the computational cost. We illustrate the approach, by calculating vibrational spectra using standard models of water molecules and bulk water, demonstrating significant computational savings and dramatically improved accuracy compared to more expensive reference approaches. We believe that our simple, efficient and accurate method could enable routine calculations of vibrational spectra including nuclear quantum effects for a wide range of molecular systems.

General embedded cluster protocol for accurate modeling of oxygen vacancies in metal-oxides

The O vacancy (Ov) formation energy, EOv, is an important property of a metal-oxide, governing its performance in applications such as fuel cells or heterogeneous catalysis. These defects are routinely studied with density functional theory (DFT). However, it is well-recognized that standard DFT formulations (e.g., the generalized gradient approximation) are insufficient for modeling the Ov, requiring higher levels of theory. The embedded cluster method offers a promising approach to compute EOv accurately, giving access to all electronic structure methods. Central to this approach is the construction of quantum(-mechanically treated) clusters placed within suitable embedding environments. Unfortunately, current approaches to constructing the quantum clusters either require large system sizes, preventing application of high-level methods, or require significant manual input, preventing investigations of multiple systems simultaneously. In this work, we present a systematic and general quantum cluster design protocol that can determine small converged quantum clusters for studying the Ov in metal-oxides with accurate methods, such as local coupled cluster with single, double, and perturbative triple excitations. We apply this protocol to study the Ov in the bulk and surface planes of rutile TiO2 and rock salt MgO, producing the first accurate and well-converged determinations of EOv with this method. These reference values are used to benchmark exchange–correlation functionals in DFT, and we find that all the studied functionals underestimate EOv, with the average error decreasing along the rungs of Jacob’s ladder. This protocol is automatable for high-throughput calculations and can be generalized to study other point defects or adsorbates.

Inorganic nitrate attenuates endothelial dysfunction consequent to systemic inflammation

Introduction

Chronic cardiovascular diseases are characterised by low-grade systemic inflammation and attenuated nitric oxide (NO) bioavailability resulting in endothelial dysfunction. Inorganic nitrate augments NO bioavailability and improves markers of vascular dysfunction in patients with cardiovascular risk factors. However, the exact mechanism of this effect is uncertain.

Purpose

To determine whether inorganic nitrate supplementation alters systemic inflammation-induced endothelial dysfunction.

Methods

62 healthy male volunteers were randomised 1:1 to receive ∼8–10 mmol of dietary inorganic nitrate in beetroot juice or nitrate-free beetroot juice (placebo) once daily for 6 days. Measures of brachial artery flow-mediated dilatation (FMD), brachial blood pressure (BP), pulse wave analysis and carotid-femoral pulse wave velocity (PWV) by Vicorder were taken prior to and at 8 hours after a typhoid vaccine (to induce mild systemic inflammation). Plasma, urine and saliva samples were also collected. Clinicaltrials.gov: NCT02715635.

Results

Baseline characteristics were similar between the two groups. Inorganic nitrate significantly elevated plasma nitrite (placebo = Δ0.02±0.5 μM, inorganic nitrate = Δ0.63±1.2 μM; p=0.01) and nitrate levels (p<0.0001) compared to placebo. There were significant increases in urine nitrite (p<0.0001) and nitrate (p<0.0001) in addition to salivary nitrite (p<0.0001) and nitrate (p<0.0001) compared to placebo. After 8 hours, typhoid vaccine induced an increase in circulating white cells (placebo = Δ3.34±3.37x109/L, inorganic nitrate = Δ2.9±2.78x109/L; p=0.58) that was similar in in both arms. However, there was a significant reduction in the FMD response in the placebo group at 8-hours post vaccine; an effect that was absent in volunteers treated with inorganic nitrate (placebo = Δ−1.33±1.53%, inorganic nitrate = Δ−0.07±1.84%, p=0.005). Importantly, there were no statistically significant differences in baseline vessel diameter (p=0.78), time to peak diameter in response to flow (p=0.87) and peak shear rate (p=0.57) between the groups. When comparing change from baseline to 8 hours after the vaccine, there were no significant differences in brachial systolic BP (p=0.12), central systolic BP (p=0.12) and PWV (p=0.60) between groups, but a significant reduction in brachial diastolic BP in the inorganic nitrate group (p=0.048).

Conclusions

Inflammation-induced endothelial dysfunction was prevented in those receiving dietary inorganic nitrate suggesting that elevating circulating nitrite and delivering NO to the blood vessel wall, through dietary approaches may offer potential therapeutic benefit in those cardiovascular diseases which typically exhibit low grade inflammation and deficiencies in bioavailable NO.

Funding Acknowledgement

Type of funding sources: Public Institution(s). Main funding source(s): British Heart Foundation

A pro-resolving phenotype underpins the anti-inflammatory effects of inorganic nitrate

Introduction

Increasing evidence highlights the critical role of chronic inflammation in cardiovascular disease (CVD). Targeting inflammatory pathways in patients with CVD has been associated with improved CV function in pre-clinical (Gee, 2017), early clinical (Yndestad, 2006; Velmurugan 2013; Jones, 2016) and large phase III studies (Ridker, 2017).

The resolution of inflammation is an active process and its failure has also been proposed to contribute to CVD progression. At least one mechanism thought to underlie this failure is dysfunction of the canonical pathway for anti-inflammatory nitric oxide (NO) production. Restoring NO through provision of inorganic nitrate (NO3-) and subsequent bioactivation via the non-canonical pathway may offer therapeutic benefit.

Aim

To test whether dietary NO3–derived NO accelerates resolution of inflammation.

Methods

Randomised, double-blind, placebo-controlled, parallel limb study of 8–10mmol dietary NO3- supplementation versus NO3–deplete placebo beetroot juice in 36 healthy male volunteers (NCT03183830). Using a cantharadin-induced skin blister model (Day, 2001), acute (24h) and chronic (72h)-phase blisters were harvested pre- and post-treatment. Blister exudate was analysed for leucocyte activation state (CD11b, CD62L, CD162) by flow cytometry and cytokine/chemokine composition by ELISA. Ozone chemiluminescence established NO3-/NO2- levels in key biological matrices: plasma, urine and saliva.

Results

9.3mmol inorganic NO3- led to a significant rise (versus placebo, p<0.001) of NO3-/NO2- in plasma, saliva and urine NO2- (p<0.02). No differences were seen in blister volumes, cell counts or markers of systemic inflammation. Whilst no differences were seen in the proportions of cellular infiltrate in 24h blisters, there were significant reductions of neutrophil (p=0.017) and intermediate monocyte proportions (p=0.001) and cellular adhesion molecules across inflammatory, intermediate and resolving monocytes at 72h (Figure 1). Generally, no differences in blister cytokine/chemokine profile was evident except for borderline significant suppression of TNFα at 24hrs with dietary NO3- treatment (P=0.057).

Conclusion

Whilst dietary inorganic NO3- does not impair the essential host defence response it does accelerate resolution: enhanced pro- to anti-inflammatory monocyte subtype switching and curtailed neutrophil recruitment, likely via attenuated TNFα production. These actions offer a novel, easy to administer, approach to influence inflammatory responses without impairing host defence.

Funding Acknowledgement

Type of funding sources: Public Institution(s). Main funding source(s): Derek Willoughby Trust and British Heart Foundation

Inorganic nitrate attenuates the systemic inflammatory response in typhoid vaccine-induced endothelial dysfunction in healthy volunteers

Background

Inflammatory responses underlie the development of endothelial dysfunction in CVD, however, therapeutics that might target this pathway have not been forthcoming. A key pathogenic mechanism mediating endothelial dysfunction is a reduction in bioavailable (eNOS-derived) nitric oxide (NO). Activation of the non-canonical pathway for in-vivo NO generation might offer an approach to improve NO levels and recover vascular function in pre-clinical models of CVD. Whether this might occur in humans is unknown.

Purpose

We hypothesize that consumption of inorganic nitrate will lead to increases in bioavailable NO and thus attenuate the inflammatory pathways leading to typhoid vaccine-induced endothelial dysfunction in healthy volunteers.

Methods

Healthy male volunteers were recruited (n=78) and randomized to receive either beetroot juice containing 8–10mmol nitrate or placebo (nitrate-deplete) juice once daily for 6 days. Participants underwent serial measurements of BP, FMD and GTN-induced brachial artery dilatation, and haematology and biochemistry, before and after typhoid vaccination. Blood, urine and saliva nitrite and nitrate were quantified using ozone chemiluminescence, and leukocyte flow cytometry analysis was conducted.

Results

8-hours post-vaccine endothelial function was depressed in placebo-treated volunteers, however this was prevented in nitrate-treated volunteers. This dysfunction was due to impaired endothelial function since responses to GTN were unaffected either by vaccination or dietary intervention (p=0.981). Dietary nitrate resulted in an increase in plasma (p<0.0001), urine (p=0.0006) and saliva (p<0.0001) nitrate, and urine (p=0.0354) and saliva (p<0.0001) nitrite levels. There was a reduction in the proportions of CD14++/CD16+intermediate monocytes in nitrate-treated participants after vaccine (p=0.016, change from baseline between groups). In the nitrate-treated group, less CD14++/CD16+ intermediate monocyte CD62L expression was identified post-vaccine (p=0.0122), compared to placebo, with no difference in soluble plasma CD62L between groups (p=0.875). CD11b median fluorescence intensity was increased in CD3+/CD4+ T-lymphocytes in nitrate-treated volunteers (p=0.0095).

Conclusions

Dietary nitrate reduced BP, as previously shown, indicating efficacy of the intervention. Importantly, we also now show for the first time that inorganic nitrate suppresses the systemic inflammatory response, specifically by reducing the numbers and activation state of CD14++/CD16+ intermediate monocytes. Furthermore, an increased expression of CD3+/CD4+ T-cell CD11b and preserved FMD in healthy volunteers treated with nitrate, suggests an anti-inflammatory phenotype, induced by the intervention, leading to improved endothelial function. Inorganic dietary nitrate modulates endothelial function through the attenuation of inflammatory responses and may be of potential therapeutic benefit in patients with established CAD.

Funding Acknowledgement

Type of funding sources: None.

Efficient Quantum Vibrational Spectroscopy of Water with High-Order Path Integrals: From Bulk to Interfaces

Vibrational spectroscopy is key in probing the interplay between the structure and dynamics of aqueous systems. To map different regions of experimental spectra to the microscopic structure of a system, it is important to combine them with first-principles atomistic simulations that incorporate the quantum nature of nuclei. Here we show that the large cost of calculating the quantum vibrational spectra of aqueous systems can be dramatically reduced compared with standard path integral methods by using approximate quantum dynamics based on high-order path integrals. Together with state-of-the-art machine-learned electronic properties, our approach gives an excellent description not only of the infrared and Raman spectra of bulk water but also of the 2D correlation and the more challenging sum-frequency generation spectra of the water-air interface. This paves the way for understanding complex interfaces such as water encapsulated between or in contact with hydrophobic and hydrophilic materials through robust and inexpensive surface-sensitive and multidimensional spectra with first-principles accuracy.

Importance of Nuclear Quantum Effects for NMR Crystallography

The resolving power of solid-state nuclear magnetic resonance (NMR) crystallography depends heavily on the accuracy of computational predictions of NMR chemical shieldings of candidate structures, which are usually taken to be local minima in the potential energy. To test the limits of this approximation, we systematically study the importance of finite-temperature and quantum nuclear fluctuations for ¹H, ¹³C, and ¹⁵N shieldings in polymorphs of three paradigmatic molecular crystals: benzene, glycine, and succinic acid. The effect of quantum fluctuations is comparable to the typical errors of shielding predictions for static nuclei with respect to experiments, and their inclusion improves the agreement with measurements, translating to more reliable assignment of the NMR spectra to the correct candidate structure. The use of integrated machine-learning models, trained on first-principles energies and shieldings, renders rigorous sampling of nuclear fluctuations affordable, setting a new standard for the calculations underlying NMR structure determinations.

The Barts Health NHS Trust COVID-19 cohort: characteristics, outcomes and risk scoring of patients in East London

BACKGROUND: Barts Health National Health Service Trust (BHNHST) serves a diverse population of 2.5 million people in London, UK. We undertook a health services assessment of factors used to evaluate the risk of severe acute respiratory coronavirus 2 (SARS-CoV-2) infection.METHODS: Patients with confirmed polymerase chain reaction (PCR) test results admitted between 1 March and 1 August 2020 were included, alongwith clinician-diagnosed suspected cases. Prognostic factors from the 4C Mortality score and 4C Deterioration scores were extracted from electronic health records and logistic regression was used to quantify the strength of association with 28-day mortality and clinical deterioration using national death registry linkage.RESULTS: Of 2783 patients, 1621 had a confirmed diagnosis, of whom 61% were male and 54% were from Black and Minority Ethnic groups; 26% died within 28 days of admission. Mortality was strongly associated with older age. The 4C mortality score had good stratification of risk with a calibration slope of 1.14 (95% CI 1.01-1.27). It may have under-estimated mortality risk in those with a high respiratory rate or requiring oxygen.CONCLUSION: Patients in this diverse patient cohort had similar mortality associated with prognostic factors to the 4C score derivation sample, but survival might be poorer in those with respiratory failure.

Simulating the ghost: quantum dynamics of the solvated electron

The nature of the bulk hydrated electron has been a challenge for both experiment and theory due to its short lifetime and high reactivity, and the need for a high-level of electronic structure theory to achieve predictive accuracy. The lack of a classical atomistic structural formula makes it exceedingly difficult to model the solvated electron using conventional empirical force fields, which describe the system in terms of interactions between point particles associated with atomic nuclei. Here we overcome this problem using a machine-learning model, that is sufficiently flexible to describe the effect of the excess electron on the structure of the surrounding water, without including the electron in the model explicitly. The resulting potential is not only able to reproduce the stable cavity structure but also recovers the correct localization dynamics that follow the injection of an electron in neat water. The machine learning model achieves the accuracy of the state-of-the-art correlated wave function method it is trained on. It is sufficiently inexpensive to afford a full quantum statistical and dynamical description and allows us to achieve accurate determination of the structure, diffusion mechanisms, and vibrational spectroscopy of the solvated electron.

Barely porous organic cages for hydrogen isotope separation

The separation of hydrogen isotopes for applications such as nuclear fusion is a major challenge. Current technologies are energy intensive and inefficient. Nanoporous materials have the potential to separate hydrogen isotopes by kinetic quantum sieving, but high separation selectivity tends to correlate with low adsorption capacity, which can prohibit process scale-up. In this study, we use organic synthesis to modify the internal cavities of cage molecules to produce hybrid materials that are excellent quantum sieves. By combining small-pore and large-pore cages together in a single solid, we produce a material with optimal separation performance that combines an excellent deuterium/hydrogen selectivity (8.0) with a high deuterium uptake (4.7 millimoles per gram).

Inexpensive modeling of quantum dynamics using path integral generalized Langevin equation thermostats

The properties of molecules and materials containing light nuclei are affected by their quantum mechanical nature. Accurate modeling of these quantum nuclear effects requires computationally demanding path integral techniques. Considerable success has been achieved in reducing the cost of such simulations by using generalized Langevin dynamics to induce frequency-dependent fluctuations. Path integral generalized Langevin equation methods, however, have this far been limited to the study of static, thermodynamic properties due to the large perturbation to the system's dynamics induced by the aggressive thermostatting. Here, we introduce a post-processing scheme, based on analytical estimates of the dynamical perturbation induced by the generalized Langevin dynamics, which makes it possible to recover meaningful time correlation properties from a thermostatted trajectory. We show that this approach yields spectroscopic observables for model and realistic systems that have an accuracy comparable to much more demanding approximate quantum dynamics techniques based on full path integral simulations.

Accurate Description of Nuclear Quantum Effects with High-Order Perturbed Path Integrals (HOPPI)

Imaginary time path-integral (PI) simulations that account for nuclear quantum effects (NQE) beyond the harmonic approximation are increasingly employed together with modern electronic-structure calculations. Existing PI methods are applicable to molecules, liquids, and solids; however, the computational cost of such simulations increases dramatically with decreasing temperature. To address this challenge, here, we propose to combine high-order PI factorization with perturbation theory (PT). Already for conventional second-order PI simulations, the PT ansatz increases the accuracy 2-fold compared to fourth-order schemes with the same settings. In turn, applying PT to high-order path integrals (HOPI) further improves the efficiency of simulations for molecular and condensed matter systems especially at low temperatures. We present results for bulk liquid water, the aspirin molecule, and the CH₅⁺ molecule. Perturbed HOPI simulations remain both efficient and accurate down to 20 K and provide a convenient method to estimate the convergence of quantum-mechanical observables.

Thermal Engineering of Metal-Organic Frameworks for Adsorption Applications: A Molecular Simulation Perspective

Thermal engineering of metal-organic frameworks for adsorption-based applications is very topical in view of their industrial potential, in particular, since heat management and thermal stability have been identified as important obstacles. Hence, a fundamental understanding of the structural and chemical features underpinning their intrinsic thermal properties is highly sought-after. Herein, we investigate the nanoscale behavior of a diverse set of frameworks using molecular simulation techniques and critically compare properties such as thermal conductivity, heat capacity, and thermal expansion with other classes of materials. Furthermore, we propose a hypothetical thermodynamic cycle to estimate the temperature rise associated with adsorption for the most important greenhouse and energy-related gases (CO₂ and CH₄). This macroscopic response on the heat of adsorption connects the intrinsic thermal properties with the adsorption properties and allows us to evaluate their importance.

Misuse of benzodiazepines and Z-drugs in the UK

Benzodiazepines and Z-drugs are commonly prescribed for insomnia and anxiety syndromes and there is increasing concern regarding their misuse. Using an internet-based questionnaire we found that of 1500 respondents 7.7% (n = 116) had misused one or more of these medications. Almost 15% of those misusing at least one of these drugs did so once weekly or more often. The main reasons reported for their use were to help sleep (66.4%), to cope with stress (37.1%) and/or to get high (31.0%). A total of 31% obtained the medications from multiple sources; healthcare professionals (55.2%) and friends/family (39.7%) most commonly. Our study can be used to inform prevention measures for their misuse.

Inorganic nitrate and the cardiovascular system

Fruit and vegetable-rich diets reduce blood pressure and risk of ischaemic stroke and ischaemic heart disease. While the cardioprotective effects of a fruit and vegetable-rich diet are unequivocal, the exact mechanisms of this effect remain uncertain. Recent evidence has highlighted the possibility that dietary nitrate, an inorganic anion found in large quantities in vegetables (particularly green leafy vegetables), may have a part to play. This beneficial activity lies in the processing in vivo of nitrate to nitrite and thence to the pleiotropic molecule nitric oxide. In this review, recent preclinical and clinical evidence identifying the mechanisms involved in nitrate bioactivity, and the evidence supporting the potential utility of exploitation of this pathway for the prevention and/or treatment of cardiovascular diseases are discussed.

RAS gene activation in acute myelogenous leukemia: analysis by in vitro amplification and DNA base sequence determination

RAS protooncogene activation has been repeatedly demonstrated in neoplastic cell DNA from patients with AML. Despite the convincing demonstration that activating RAS gene point mutations are critical in model systems, their precise prevalence and importance in human cancers such as AML remain speculative. The technology for identifying RAS mutations has changed considerably in recent years. We examined a prospective cohort of 43 acute myeloid leukemia (AML) patients admitted to the University of Maryland Cancer Center for first and second exon mutations of NRAS and KRAS using PCR and DNA sequence analysis. Six (14%) 1st exon NRAS mutations were identified. No clinical or biologic parameter has yet been observed to segregate with RAS activation, although a larger study may be needed to demonstrate this.

Ras gene product expression in blood and marrow smears of patients with acute leukemia: importance of fixation

Activation of ras protooncogenes by any of several possible mutations in codons 12, 13 or 61 has been demonstrated in a variety of human malignancies, including acute non-lymphoblastic leukemia (ANLL). In situ staining for the ras gene product, p21, has been demonstrated in carcinomas of several sites. High levels of p21 expression have been associated with histologic anaplasia in prostate cancer and regional lymph node metastasis in breast cancer. We examined 16 marrow aspirates and blood smears from patients with acute leukemia, predominantly ANLL, and eight controls. Marrow aspirates or blood were smeared on glass slides and fixed immediately in 10% buffered formalin. p21 was examined with avidin-biotin linked immunoperoxidase visualization. Particular attention must be paid to antibody selection and fixation protocol to demonstrate p21, owing to its rapid degradation ex vivo. Three of 16 patients exhibited occasional high p21 expression primarily in leukemic blasts, but in no case were more than 10% of blast cells positive. Normal reticuloendothelial and myeloid cells occasionally exhibited mild to moderately heavy staining, but megakaryocytes, erythroid precursors, lymphocytes and plasma cells were consistently negative. Most patients, 5 normal volunteers and 3 patients with non-malignant disease, exhibited no reactivity, or only a faint blush. These data suggest that while point mutation and concomitant activation of c-N-ras occurs regularly in ANLL, high levels of ras p21 expression are rarely found with this technique.

Immunoprecipitation of cell lysates with RAP-5 does not specifically detect ras oncogene product p21

In the process of developing accurate quantitation of the ras protein (p21), we have screened available anti-ras antibodies for their utility in immunoprecipitation. Immunoprecipitation with the anti-ras antibody RAP-5 consistently failed to precipitate p21 present in two different cell lines (HSIC-5 and MCF-7), but did precipitate numerous other proteins present in these cell lines. Specificity in immunoprecipitation could not be achieved by varying the concentration of RAP-5. In addition, immunohistochemical staining of the nuclei of occasional polymorphonuclear leukocytes is seen, further supporting the contention that RAP-5 is binding to proteins other than ras p21. We conclude that while RAP-5 may recognize an epitope present on the ras protein, this epitope also appears to be present on a wide variety of other cellular proteins and, as such, RAP-5 is of no use in the immunoprecipitation of p21.

Infrequent ras activation in chronic myelogenous leukemia (CML): activating 61st codon mutation in the CML-derived cell line, IM-9

The proto-oncogene c-N-ras frequently bears point mutations in ANLL cell DNA which endow it with the capacity to transform NIH/3T3 cells in vitro. Chronic myelogenous leukemia (CML) is a neoplasm highly related to ANLL since it involves the same hematopoietic progenitor cells and ultimately transforms to a neoplasm virtually indistinguishable from acute nonlymphoblastic leukemia (ANLL). Thus, we and others have examined ras genes in CML. This report confirms that ras gene activation is a very infrequent event in CML. However, a lymphoblastic cell line derived from a patient with CML did exhibit a novel second exon 61st codon activating mutation of c-N-ras.