Overcoming the Chemical Complexity Bottleneck in on-the-Fly Machine Learned Molecular Dynamics Simulations.

We develop a framework for on-the-fly machine learned force field molecular dynamics simulations based on the multipole featurization scheme that overcomes the bottleneck with the number of chemical elements. Considering bulk systems with up to 6 elements, we demonstrate that the number of density functional theory calls remains approximately independent of the number of chemical elements, in contrast to the increase in the smooth overlap of the atomic positions scheme.

Electrocatalysts for Inorganic and Organic Waste Nitrogen Conversion.

Anthropogenic activities have disrupted the natural nitrogen cycle, increasing the level of nitrogen contaminants in water. Nitrogen contaminants are harmful to humans and the environment. This motivates research on advanced and decarbonized treatment technologies that are capable of removing or valorizing nitrogen waste found in water. In this context, the electrocatalytic conversion of inorganic- and organic-based nitrogen compounds has emerged as an important approach that is capable of upconverting waste nitrogen into valuable compounds. This approach differs from state-of-the-art wastewater treatment, which primarily converts inorganic nitrogen to dinitrogen, and organic nitrogen is sent to landfills. Here, we review recent efforts related to electrocatalytic conversion of inorganic- and organic-based nitrogen waste. Specifically, we detail the role that electrocatalyst design (alloys, defects, morphology, and faceting) plays in the promotion of high-activity and high-selectivity electrocatalysts. We also discuss the impact of wastewater constituents. Finally, we discuss the critical product analyses required to ensure that the reported performance is accurate.

The Open DAC 2023 Dataset and Challenges for Sorbent Discovery in Direct Air Capture.

Direct air capture (DAC) of CO2 with porous adsorbents such as metal-organic frameworks (MOFs) has the potential to aid large-scale decarbonization. Previous screening of MOFs for DAC relied on empirical force fields and ignored adsorbed H2O and MOF deformation. We performed quantum chemistry calculations overcoming these restrictions for thousands of MOFs. The resulting data enable efficient descriptions using machine learning.

Model-Based Design of Experiments for Temporal Analysis of Products (TAP): A Simulated Case Study in Oxidative Propane Dehydrogenation.

Temporal analysis of products (TAP) reactors enable experiments that probe numerous kinetic processes within a single set of experimental data through variations in pulse intensity, delay, or temperature. Selecting additional TAP experiments often involves an arbitrary selection of reaction conditions or the use of chemical intuition. To make experiment selection in TAP more robust, we explore the efficacy of model-based design of experiments (MBDoE) for precision in TAP reactor kinetic modeling. We successfully applied this approach to a case study of synthetic oxidative propane dehydrogenation (OPDH) that involves pulses of propane and oxygen. We found that experiments identified as optimal through the MBDoE for precision generally reduce parameter uncertainties to a higher degree than alternative experiments. The performance of MBDoE for model divergence was also explored for OPDH, with the relevant active sites (catalyst structure) being unknown. An experiment that maximized the divergence between the three proposed mechanisms was identified and provided evidence that improved the mechanism discrimination. However, reoptimization of kinetic parameters eliminated the ability to discriminate between models. The findings yield insight into the prospects and limitations of MBDoE for TAP and transient kinetic experiments.

A Retrospective Analysis of 2-Year Follow-Up of Patients with Incidental Findings of Sarcoidosis.

INTRODUCTION: Sarcoidosis is a multi-system granulomatous disease most commonly involving the lungs. It may be incidentally diagnosed during imaging studies for other conditions or non-specific symptoms. The appropriate follow-up of incidentally diagnosed asymptomatic stage 1 disease has not been well defined. OBJECTIVE: To define the clinical course of incidentally diagnosed asymptomatic stage 1 sarcoidosis and propose an algorithm for the follow-up of these patients. METHODOLOGY: A retrospective case note analysis was performed of all EBUS-TBNA (endobronchial ultrasound-guided transbronchial needle aspiration)-confirmed cases of stage 1 sarcoidosis presenting incidentally to Bristol and Liverpool Interstitial Lung Disease services. Clinical history, serology results, imaging scans, and lung function parameters were examined at baseline, 12, and 24 months. A cost analysis was performed comparing the cost of the current 2-year follow-up guidance to a 1 year follow-up period. RESULTS: Sixty-seven patients were identified as the final cohort. There was no significant change in the pulmonary function tests over the two-year follow-up period. Radiological disease stability was observed in the majority of patients (58%, n = 29), and disease regression was evidenced in 40% (n = 20) at 1 year. Where imaging was performed at 2 years, the majority (69.8%, n = 37) had radiological evidence of disease regression, and 30.2% (n = 16) showed radiological evidence of stability. All patients remained asymptomatic and did not require therapeutic intervention over the study period. CONCLUSIONS: Our results show that asymptomatic patients with incidental findings of thoracic lymph nodal non-caseating granulomas do not progress over a 2-year period. Our results suggest that the prolonged secondary-care follow-up of such patients may not be necessary. We propose that these patients are followed up for 1 year with a further year of patient-initiated follow-up (PIFU) prior to discharge.

Self-Consistent Convolutional Density Functional Approximations: Application to Adsorption at Metal Surfaces.

The exchange-correlation (XC) functional in density functional theory is used to approximate multi-electron interactions. A plethora of different functionals are available, but nearly all are based on the hierarchy of inputs commonly referred to as "Jacob's ladder." This paper introduces an approach to construct XC functionals with inputs from convolutions of arbitrary kernels with the electron density, providing a route to move beyond Jacob's ladder. We derive the variational derivative of these functionals, showing consistency with the generalized gradient approximation (GGA), and provide equations for variational derivatives based on multipole features from convolutional kernels. A proof-of-concept functional, PBEq, which generalizes the PBE α ${\alpha }$ framework with α ${\alpha }$ being a spatially-resolved function of the monopole of the electron density, is presented and implemented. It allows a single functional to use different GGAs at different spatial points in a system, while obeying PBE constraints. Analysis of the results underlines the importance of error cancellation and the XC potential in data-driven functional design. After testing on small molecules, bulk metals, and surface catalysts, the results indicate that this approach is a promising route to simultaneously optimize multiple properties of interest.

ANCA-negative ANCA-associated vasculitis: pitfalls of the 'vasculitis screen'.

Despite its recognition as an 'ANCA-associated vasculitis' (AAV), eosinophilic granulomatosis with polyangiitis (EGPA) is ANCA negative in up to 60% of cases. Herein, we report the case of a young man with a clinical syndrome highly suggestive of EGPA but with repeated negative ANCA serology, ultimately presenting with cardiac arrest before recognition of the primary systemic vasculitis, whereupon he received successful induction therapy with high dose glucocorticoids and cyclophosphamide. The case illustrates the importance of awareness of ANCA negative AAV among general physicians in order to minimise morbidity and mortality.

Formation of Carbon-Induced Nitrogen-Centered Radicals on Titanium Dioxide under Illumination.

Titanium dioxide is the most studied photocatalytic material and has been reported to be active for a wide range of reactions, including the oxidation of hydrocarbons and the reduction of nitrogen. However, the molecular-scale interactions between the titania photocatalyst and dinitrogen are still debated, particularly in the presence of hydrocarbons. Here, we used several spectroscopic and computational techniques to identify interactions among nitrogen, methanol, and titania under illumination. Electron paramagnetic resonance spectroscopy (EPR) allowed us to observe the formation of carbon radicals upon exposure to ultraviolet radiation. These carbon radicals are observed to transform into diazo- and nitrogen-centered radicals (e.g., CHxN2• and CHxNHy•) during photoreaction in nitrogen environment. In situ infrared (IR) spectroscopy under the same conditions revealed C-N stretching on titania. Furthermore, density functional theory (DFT) calculations revealed that nitrogen adsorption and the thermodynamic barrier to photocatalytic nitrogen fixation are significantly more favorable in the presence of hydroxymethyl or surface carbon. These results provide compelling evidence that carbon radicals formed from the photooxidation of hydrocarbons interact with dinitrogen and suggest that the role of carbon-based "hole scavengers" and the inertness of nitrogen atmospheres should be reevaluated in the field of photocatalysis.

Kohn-Sham accuracy from orbital-free density functional theory via Δ-machine learning.

We present a Δ-machine learning model for obtaining Kohn-Sham accuracy from orbital-free density functional theory (DFT) calculations. In particular, we employ a machine-learned force field (MLFF) scheme based on the kernel method to capture the difference between Kohn-Sham and orbital-free DFT energies/forces. We implement this model in the context of on-the-fly molecular dynamics simulations and study its accuracy, performance, and sensitivity to parameters for representative systems. We find that the formalism not only improves the accuracy of Thomas-Fermi-von Weizsäcker orbital-free energies and forces by more than two orders of magnitude but is also more accurate than MLFFs based solely on Kohn-Sham DFT while being more efficient and less sensitive to model parameters. We apply the framework to study the structure of molten Al0.88Si0.12, the results suggesting no aggregation of Si atoms, in agreement with a previous Kohn-Sham study performed at an order of magnitude smaller length and time scales.

Screening and Discovery of Metal Compound Active Sites for Strong and Selective Adsorption of N2 in Air.

Photocatalytic nitrogen fixation has the potential to provide a greener route for producing nitrogen-based fertilizers under ambient conditions. Computational screening is a promising route to discover new materials for the nitrogen fixation process, but requires identifying "descriptors" that can be efficiently computed. In this work, we argue that selectivity toward the adsorption of molecular nitrogen and oxygen can act as a key descriptor. A catalyst that can selectively adsorb nitrogen and resist poisoning of oxygen and other molecules present in air has the potential to facilitate the nitrogen fixation process under ambient conditions. We provide a framework for active site screening based on multifidelity density functional theory (DFT) calculations for a range of metal oxides, oxyborides, and oxyphosphides. The screening methodology consists of initial low-fidelity fixed geometry calculations and a second screening in which more expensive geometry optimizations were performed. The approach identifies promising active sites on several TiO2 polymorph surfaces and a VBO4 surface, and the full nitrogen reduction pathway is studied with the BEEF-vdW and HSE06 functionals on two active sites. The findings suggest that metastable TiO2 polymorphs may play a role in photocatalytic nitrogen fixation, and that VBO4 may be an interesting material for further studies.

Automated Generation of Microkinetics for Heterogeneously Catalyzed Reactions Considering Correlated Uncertainties.

The study presents an ab-initio based framework for the automated construction of microkinetic mechanisms considering correlated uncertainties in all energetic parameters and estimation routines. 2000 unique microkinetic models were generated within the uncertainty space of the BEEF-vdW functional for the oxidation reactions of representative exhaust gas emissions from stoichiometric combustion engines over Pt(111) and compared to experiments through multiscale modeling. The ensemble of simulations stresses the importance of considering uncertainties. Within this set of first-principles-based models, it is possible to identify a microkinetic mechanism that agrees with experimental data. This mechanism can be traced back to a single exchange-correlation functional, and it suggests that Pt(111) could be the active site for the oxidation of light hydrocarbons. The study provides a universal framework for the automated construction of reaction mechanisms with correlated uncertainty quantification, enabling a DFT-constrained microkinetic model optimization for other heterogeneously catalyzed systems.

A Universal Framework for Featurization of Atomistic Systems.

Machine-learning force fields have become increasingly popular because of their balance of accuracy and speed. However, a significant limitation is the use of element-specific features, leading to poor scalability with the number of elements. This work introduces the Gaussian multipole (GMP) featurization scheme that utilizes physically relevant multipole expansions of the electron density around atoms to yield feature vectors that interpolate between element types and have a fixed dimension regardless of the number of elements present. We combine GMP with neural networks and apply these models to the MD17 and QM9 data sets, revealing high computational efficiency, systematically improvable accuracy, and the ability to make reasonable predictions on elements not included in the training set. Finally, we test GMP-based models for the OCP data set, demonstrating comparable performance to graph-convolutional models. The results indicate that this featurization scheme fills a critical gap in the construction of efficient and transferable machine-learned force fields.

Gaussian approximation of dispersion potentials for efficient featurization and machine-learning predictions of metal-organic frameworks.

Energy-related descriptors in machine learning are a promising strategy to predict adsorption properties of metal-organic frameworks (MOFs) in the low-pressure regime. Interactions between hosts and guests in these systems are typically expressed as a sum of dispersion and electrostatic potentials. The energy landscape of dispersion potentials plays a crucial role in defining Henry's constants for simple probe molecules in MOFs. To incorporate more information about this energy landscape, we introduce the Gaussian-approximated Lennard-Jones (GALJ) potential, which fits pairwise Lennard-Jones potentials with multiple Gaussians by varying their heights and widths. The GALJ approach is capable of replicating information that can be obtained from the original LJ potentials and enables efficient development of Gaussian integral (GI) descriptors that account for spatial correlations in the dispersion energy environment. GI descriptors would be computationally inconvenient to compute using the usual direct evaluation of the dispersion potential energy surface. We show that these new GI descriptors lead to improvement in ML predictions of Henry's constants for a diverse set of adsorbates in MOFs compared to previous approaches to this task.

Perspectives on the Competition between the Electrochemical Water and N2 Oxidation on a TiO2(110) Electrode.

The electrochemical nitrogen oxidation reaction (NOR) has recently drawn attention due to promising experimental and theoretical results. It provides an alternative, environmentally friendly route to directly synthesize nitrate from N2(g). There is to date a limited number of investigations focused on the electrochemical NOR. Herein, we present a detailed computational study on the kinetics of both the NOR and the competing oxygen evolution reaction (OER) on the TiO2(110) electrode under ambient conditions. The use of grand canonical density functional theory in combination with the linearized Poisson-Boltzmann equation allows a continuous tuning of the explicitly applied electrical potential. We find that the OER may either promote or suppress the NOR on TiO2(110) depending on reaction conditions. The detailed atomistic insights provided on the mechanisms of these competing processes make possible further developments toward a direct electrochemical NOR process.

Suitability of endobronchial ultrasound-guided transbronchial needle aspiration samples for programmed death ligand-1 testing in non-small cell lung cancer, the Bristol experience.

Treatment for non-small cell lung cancer (NSCLC) is now personalised using molecular mutation testing. Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) biopsy suitability for anaplastic lymphoma kinase (ALK) and epidermal growth factor receptor (EGFR) mutation testing is established. Less is currently known about EBUS-TBNA suitability for PD-L1 (programmed death ligand-1) testing. To assess EBUS-TBNA biopsy adequacy for ALK, EGFR and PD-L1 testing, we conducted a prospective study of 279 consecutive NSCLC patients referred to a tertiary EBUS-TBNA centre in South West England. One hundred eight-four (62.6%) patients were found to have adenocarcinoma, 83 (28.2%) had squamous cell carcinoma, and 27 (9.2%) were identified as NSCLC-not otherwise specified. EGFR testing was successful in 166 of 168 patients (98.8%), ALK testing in all 115 and PD-L1 testing in 43 of 49 patients (88.2%). Previous EGFR and ALK testing did not affect biopsy PD-L1 testing success. PD-L1 testing failures occurred in three of five (60.0%) of 22G needle biopsies, one of five (20.0%) of 21G needle biopsies and two of 39 (5.1%) of 19G needle biopsies, P = .016. EBUS-TBNA biopsies are mostly suitable for PD-L1 testing. Larger needle size may improve PD-L1 (but not EGFR and ALK) testing success but requires further study in a controlled trial.

Long-term nitrofurantoin: an analysis of complication awareness, monitoring, and pulmonary injury cases.

BACKGROUND: Long-term nitrofurantoin (NF) treatment can result in pulmonary and hepatic injury. Current guidelines do not outline the type or frequency of monitoring required for detection of these injuries. AIM: To assess 1) awareness of NF complications among prescribers; 2) monitoring practice; and 3) to describe the pulmonary sequelae of NF-related complications. DESIGN & SETTING: Evaluation of prescribing habits by questionnaires and review of GP databases, and case-note review in secondary care. METHOD: The following study procedures were undertaken: 1) an electronic questionnaire was distributed to prescribers, interrogating prescribing and monitoring practices, and awareness of complications; 2) an analysis was undertaken (June-July 2020) of NF monitoring among GPs in the local clinical commissioning group (CCG); and 3) a case review was carried out of patients diagnosed with NF-induced interstitial lung disease (NFILD) at the interstitial lung disease (ILD) centre (2014-2020). RESULTS: A total of 125 prescribers of long-term NF responded to the questionnaire (82.4% GPs; 12.0% urologists). Many were unaware of the potential for liver (42.4%) and lung (28.0%) complications; 40.8% and 52.8% never monitored for these, respectively. Only 53.3% of urologists believed themselves responsible for arranging monitoring, while nearly all GPs believed this to be the prescriber's responsibility (94.2%). One-third of all responders considered current British National Formulary (BNF) guidelines 'not at all sufficient/clear', with mean clarity scoring of 2.2/5. Among patients with NFILD (n = 46), NF had been prescribed most often (69.6%) for treatment of recurrent UTI and 58.6% (n = 27) were prescribed for >6 months. On withdrawal of the medication 61.4% displayed resolution (completely or minimal fibrosis), while 15.9% of patients had progressive lung fibrosis. CONCLUSION: NF can cause marked or irreversible lung complications and there is currently a shortfall in awareness and monitoring. Existing monitoring guidelines should be augmented.

Heterogeneity in susceptibility dictates the order of epidemic models.

The fundamental models of epidemiology describe the progression of an infectious disease through a population using compartmentalized differential equations, but typically do not incorporate population-level heterogeneity in infection susceptibility. Here we combine a generalized analytical framework of contagion with computational models of epidemic dynamics to show that variation strongly influences the rate of infection, while the infection process simultaneously sculpts the susceptibility distribution. These joint dynamics influence the force of infection and are, in turn, influenced by the shape of the initial variability. We find that certain susceptibility distributions (the exponential and the gamma) are unchanged through the course of the outbreak, and lead naturally to power-law behavior in the force of infection; other distributions are often sculpted towards these "eigen-distributions" through the process of contagion. The power-law behavior fundamentally alters predictions of the long-term infection rate, and suggests that first-order epidemic models that are parameterized in the exponential-like phase may systematically and significantly over-estimate the final severity of the outbreak. In summary, our study suggests the need to examine the shape of susceptibility in natural populations as part of efforts to improve prediction models and to prioritize interventions that leverage heterogeneity to mitigate against spread.

Is Systemic Anticancer Therapy Associated With Higher Rates of Malignant Pleural Effusion Control in People With Pharmacologically Sensitive Tumors?: A Retrospective Analysis of Prospectively Collected Data.

BACKGROUND: Malignant pleural effusions (MPEs) often cause symptoms, and guidelines recommend early definitive intervention. However, observational data suggest that systemic anticancer treatment (SACT) may control MPE caused by certain pharmacologically sensitive tumors. RESEARCH QUESTION: Is SACT associated with higher rates of MPE resolution in people with pharmacologically sensitive tumors? STUDY DESIGN AND METHODS: This was a retrospective analysis of prospectively collected data from an observational cohort study of people diagnosed with MPE from lung, breast, ovarian, and hematologic malignancy between May 11, 2008, and August 6, 2017. MPE resolution (defined as radiologic resolution with removal of drain or catheter and cessation of interventions) was compared in pharmacologically sensitive (high-grade lymphoma, small cell or target-mutation-positive lung cancer, and hormone-receptor-positive breast or ovarian cancer) and nonsensitive (remainder of cohort) tumors, with and without SACT. Secondary outcomes included time to resolution, 3-month resolution rates, and total pleural interventions. RESULTS: Of 280 patients, 127 had sensitive and 153 had nonsensitive tumors. One hundred seventy-one received SACT, and 109 did not. More patients with sensitive tumors achieved MPE resolution than those with nonsensitive tumors (53/127 [41.7%] vs 42/153 [27.5%]; P = .01), and this occurred predominantly after receipt of SACT. However, hematologic malignancies were overrepresented in the sensitive group, with high rates of SACT use and MPE resolution. After adjustment for this and other confounders, no relationship was found among pharmacologic sensitivity, SACT, and MPE resolution (adjusted OR, 1.4; 95% CI, 0.5-4.1). The strongest predictor of MPE resolution was administration of chemical pleurodesis (adjusted OR, 6.2; 95% CI, 3.3-11.7). In sensitive tumors, MPE resolution occurred without chemical pleurodesis in 14 of 52 patients (26.9%; 95% CI, 15.6%-41.1%) after SACT and in 5 of 22 patients (22.7%; 95% CI, 8.2%-47.2%) without SACT. INTERPRETATION: In this observational study, SACT was not associated independently on MPE resolution in pharmacologically sensitive tumors. Randomized trials are required, but with current data, patients with symptomatic MPE should receive early definitive pleural intervention regardless of underlying tumor or intended treatment.

Lessons of the month: ANCA-associated vasculitis - granulomatosis with polyangiitis: 'the great mimic'.

We describe the case of a 61-year-old woman who presented with progressive respiratory symptoms and imaging demonstrating multiple opacities in the right lung with hilar and mediastinal lymphadenopathy suggestive of multifocal adenocarcinoma. Subsequent biopsies were consistent with focal changes of organising pneumonia (OP) and no evidence of malignancy. She was treated with steroids for cryptogenic OP with limited response. There was clinical and radiological progression with new lung nodules, mediastinal and thoracic spinal canal infiltration. There was ongoing concern that clinical findings represented disseminated malignancy. Following further investigation and multidisciplinary respiratory and rheumatology review, a diagnosis of anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) - granulomatosis with polyangiitis (GPA) was confirmed. The case highlighted the multisystem nature of GPA with unusual dural and large vessel aortic and pulmonary trunk involvement.

Epidemiology of pleural empyema in English hospitals and the impact of influenza.

Pleural empyema represents a significant healthcare burden due to extended hospital admissions and potential requirement for surgical intervention. This study aimed to assess changes in incidence and management of pleural empyema in England over the past 10 years and the potential impact of influenza on rates.Hospital Episode Statistics data were used to identify patients admitted to English hospitals with pleural empyema between 2008 and 2018. Linear regression was used to analyse the relationship between empyema rates and influenza incidence recorded by Public Health England. The relationship between influenza and empyema was further explored using serological data from a prospective cohort study of patients presenting with pleural empyema.Between April 2008 and March 2018 there were 55 530 patients admitted with pleural empyema. There was male predominance (67% versus 33%), which increased with age. Cases have increased significantly from 4447 in 2008 to 7268 in 2017. Peaks of incidence correlated moderately with rates of laboratory-confirmed influenza in children and young adults (r=0.30). For nine of the 10 years studied, the highest annual point incidence of influenza coincided with the highest admission rate for empyema (with a 2-week lag). In a cohort study of patients presenting to a single UK hospital with pleural empyema/infection, 24% (17 out of 72) had serological evidence of recent influenza infection, compared to 7% in seasonally matched controls with simple parapneumonic or cardiogenic effusions (p<0.001).Rates of empyema admissions in England have increased steadily with a seasonal variation that is temporally related to influenza incidence. Patient-level serological data from a prospective study support the hypothesis that influenza may play a pathogenic role in empyema development.