The Impact of Health Care Algorithms on Racial and Ethnic Disparities : A Systematic Review.

BACKGROUND: There is increasing concern for the potential impact of health care algorithms on racial and ethnic disparities. PURPOSE: To examine the evidence on how health care algorithms and associated mitigation strategies affect racial and ethnic disparities. DATA SOURCES: Several databases were searched for relevant studies published from 1 January 2011 to 30 September 2023. STUDY SELECTION: Using predefined criteria and dual review, studies were screened and selected to determine: 1) the effect of algorithms on racial and ethnic disparities in health and health care outcomes and 2) the effect of strategies or approaches to mitigate racial and ethnic bias in the development, validation, dissemination, and implementation of algorithms. DATA EXTRACTION: Outcomes of interest (that is, access to health care, quality of care, and health outcomes) were extracted with risk-of-bias assessment using the ROBINS-I (Risk Of Bias In Non-randomised Studies - of Interventions) tool and adapted CARE-CPM (Critical Appraisal for Racial and Ethnic Equity in Clinical Prediction Models) equity extension. DATA SYNTHESIS: Sixty-three studies (51 modeling, 4 retrospective, 2 prospective, 5 prepost studies, and 1 randomized controlled trial) were included. Heterogenous evidence on algorithms was found to: a) reduce disparities (for example, the revised kidney allocation system), b) perpetuate or exacerbate disparities (for example, severity-of-illness scores applied to critical care resource allocation), and/or c) have no statistically significant effect on select outcomes (for example, the HEART Pathway [history, electrocardiogram, age, risk factors, and troponin]). To mitigate disparities, 7 strategies were identified: removing an input variable, replacing a variable, adding race, adding a non-race-based variable, changing the racial and ethnic composition of the population used in model development, creating separate thresholds for subpopulations, and modifying algorithmic analytic techniques. LIMITATION: Results are mostly based on modeling studies and may be highly context-specific. CONCLUSION: Algorithms can mitigate, perpetuate, and exacerbate racial and ethnic disparities, regardless of the explicit use of race and ethnicity, but evidence is heterogeneous. Intentionality and implementation of the algorithm can impact the effect on disparities, and there may be tradeoffs in outcomes. PRIMARY FUNDING SOURCE: Agency for Healthcare Quality and Research.

Transplant recipient, care partner, and clinician perceptions of medication adherence monitoring technology: A mixed methods study.

Medication nonadherence is a leading cause of graft loss. Adherence monitoring technologies-reminder texts, smart bottles, video-observed ingestion, and digestion-activated signaling pills-may support adherence. However, patient, care partner, and clinician perceptions of these tools are not well studied. We conducted qualitative individual semistructured interviews and focus groups among 97 participants at a single center: kidney and liver transplant recipients 2 weeks to 18 months posttransplant, their care partners, and transplant clinicians. We assessed adherence practices, reactions to monitoring technologies, and opportunities for care integration. One-size-fits-all approaches were deemed infeasible. Interviewees considered text messages the most acceptable approach; live video checks were the least acceptable and raised the most concerns for inconvenience and invasiveness. Digestion-activated signaling technology produced both excitement and apprehension. Patients and care partners generally aligned in perceptions of adherence monitoring integration into clinical care. Key themes were importance of routine, ease of use, leveraging technology for actionable medication changes, and aversion to surveillance. Transplant clinicians similarly considered text messages most acceptable and video checks least acceptable. Clinicians reported that early posttransplant use and real-time adherence tracking with patient feedback may facilitate successful implementation. The study provides initial insights that may inform future adherence technology implementation.

Cancer driver drug interaction explorer.

Cancer is a heterogeneous disease characterized by unregulated cell growth and promoted by mutations in cancer driver genes some of which encode suitable drug targets. Since the distinct set of cancer driver genes can vary between and within cancer types, evidence-based selection of drugs is crucial for targeted therapy following the precision medicine paradigm. However, many putative cancer driver genes can not be targeted directly, suggesting an indirect approach that considers alternative functionally related targets in the gene interaction network. Once potential drug targets have been identified, it is essential to consider all available drugs. Since tools that offer support for systematic discovery of drug repurposing candidates in oncology are lacking, we developed CADDIE, a web application integrating six human gene-gene and four drug-gene interaction databases, information regarding cancer driver genes, cancer-type specific mutation frequencies, gene expression information, genetically related diseases, and anticancer drugs. CADDIE offers access to various network algorithms for identifying drug targets and drug repurposing candidates. It guides users from the selection of seed genes to the identification of therapeutic targets or drug candidates, making network medicine algorithms accessible for clinical research. CADDIE is available at https://exbio.wzw.tum.de/caddie/ and programmatically via a python package at https://pypi.org/project/caddiepy/.

NOX5-induced uncoupling of endothelial NO synthase is a causal mechanism and theragnostic target of an age-related hypertension endotype.

Hypertension is the most important cause of death and disability in the elderly. In 9 out of 10 cases, the molecular cause, however, is unknown. One mechanistic hypothesis involves impaired endothelium-dependent vasodilation through reactive oxygen species (ROS) formation. Indeed, ROS forming NADPH oxidase (Nox) genes associate with hypertension, yet target validation has been negative. We re-investigate this association by molecular network analysis and identify NOX5, not present in rodents, as a sole neighbor to human vasodilatory endothelial nitric oxide (NO) signaling. In hypertensive patients, endothelial microparticles indeed contained higher levels of NOX5-but not NOX1, NOX2, or NOX4-with a bimodal distribution correlating with disease severity. Mechanistically, mice expressing human Nox5 in endothelial cells developed-upon aging-severe systolic hypertension and impaired endothelium-dependent vasodilation due to uncoupled NO synthase (NOS). We conclude that NOX5-induced uncoupling of endothelial NOS is a causal mechanism and theragnostic target of an age-related hypertension endotype. Nox5 knock-in (KI) mice represent the first mechanism-based animal model of hypertension.

The FeatureCloud Platform for Federated Learning in Biomedicine: Unified Approach.

BACKGROUND: Machine learning and artificial intelligence have shown promising results in many areas and are driven by the increasing amount of available data. However, these data are often distributed across different institutions and cannot be easily shared owing to strict privacy regulations. Federated learning (FL) allows the training of distributed machine learning models without sharing sensitive data. In addition, the implementation is time-consuming and requires advanced programming skills and complex technical infrastructures. OBJECTIVE: Various tools and frameworks have been developed to simplify the development of FL algorithms and provide the necessary technical infrastructure. Although there are many high-quality frameworks, most focus only on a single application case or method. To our knowledge, there are no generic frameworks, meaning that the existing solutions are restricted to a particular type of algorithm or application field. Furthermore, most of these frameworks provide an application programming interface that needs programming knowledge. There is no collection of ready-to-use FL algorithms that are extendable and allow users (eg, researchers) without programming knowledge to apply FL. A central FL platform for both FL algorithm developers and users does not exist. This study aimed to address this gap and make FL available to everyone by developing FeatureCloud, an all-in-one platform for FL in biomedicine and beyond. METHODS: The FeatureCloud platform consists of 3 main components: a global frontend, a global backend, and a local controller. Our platform uses a Docker to separate the local acting components of the platform from the sensitive data systems. We evaluated our platform using 4 different algorithms on 5 data sets for both accuracy and runtime. RESULTS: FeatureCloud removes the complexity of distributed systems for developers and end users by providing a comprehensive platform for executing multi-institutional FL analyses and implementing FL algorithms. Through its integrated artificial intelligence store, federated algorithms can easily be published and reused by the community. To secure sensitive raw data, FeatureCloud supports privacy-enhancing technologies to secure the shared local models and assures high standards in data privacy to comply with the strict General Data Protection Regulation. Our evaluation shows that applications developed in FeatureCloud can produce highly similar results compared with centralized approaches and scale well for an increasing number of participating sites. CONCLUSIONS: FeatureCloud provides a ready-to-use platform that integrates the development and execution of FL algorithms while reducing the complexity to a minimum and removing the hurdles of federated infrastructure. Thus, we believe that it has the potential to greatly increase the accessibility of privacy-preserving and distributed data analyses in biomedicine and beyond.

On the Clinical Pharmacology of Reactive Oxygen Species.

Reactive oxygen species (ROS) have been correlated with almost every human disease. Yet clinical exploitation of these hypotheses by pharmacological modulation of ROS has been scarce to nonexistent. Are ROS, thus, irrelevant for disease? No. One key misconception in the ROS field has been its consideration as a rather detrimental metabolic by-product of cell metabolism, and thus, any approach eliminating ROS to a certain tolerable level would be beneficial. We now know, instead, that ROS at every concentration, low or high, can serve many essential signaling and metabolic functions. This likely explains why systemic, nonspecific antioxidants have failed in the clinic, often with neutral and sometimes even detrimental outcomes. Recently, drug development has focused, instead, on identifying and selectively modulating ROS enzymatic sources that in a given constellation cause disease while leaving ROS physiologic signaling and metabolic functions intact. As sources, the family of NADPH oxidases stands out as the only enzyme family solely dedicated to ROS formation. Selectively targeting disease-relevant ROS-related proteins is already quite advanced, as evidenced by several phase II/III clinical trials and the first drugs having passed registration. The ROS field is expanding by including target enzymes and maturing to resemble more and more modern, big data-enhanced drug discovery and development, including network pharmacology. By defining a disease based on a distinct mechanism, in this case ROS dysregulation, and not by a symptom or phenotype anymore, ROS pharmacology is leaping forward from a clinical underperformer to a proof of concept within the new era of mechanism-based precision medicine. SIGNIFICANCE STATEMENT: Despite being correlated to almost every human disease, nearly no ROS modulator has been translated to the clinics yet. Here, we move far beyond the old-fashioned misconception of ROS as detrimental metabolic by-products and suggest 1) novel pharmacological targeting focused on selective modulation of ROS enzymatic sources, 2) mechanism-based redefinition of diseases, and 3) network pharmacology within the ROS field, altogether toward the new era of ROS pharmacology in precision medicine.

Reactive Oxygen-Forming Nox5 Links Vascular Smooth Muscle Cell Phenotypic Switching and Extracellular Vesicle-Mediated Vascular Calcification.

RATIONALE: Vascular calcification, the formation of calcium phosphate crystals in the vessel wall, is mediated by vascular smooth muscle cells (VSMCs). However, the underlying molecular mechanisms remain elusive, precluding mechanism-based therapies. OBJECTIVE: Phenotypic switching denotes a loss of contractile proteins and an increase in migration and proliferation, whereby VSMCs are termed synthetic. We examined how VSMC phenotypic switching influences vascular calcification and the possible role of the uniquely calcium-dependent reactive oxygen species (ROS)-forming Nox5 (NADPH oxidase 5). METHODS AND RESULTS: In vitro cultures of synthetic VSMCs showed decreased expression of contractile markers CNN-1 (calponin 1), α-SMA (α-smooth muscle actin), and SM22-α (smooth muscle protein 22α) and an increase in synthetic marker S100A4 (S100 calcium binding protein A4) compared with contractile VSMCs. This was associated with increased calcification of synthetic cells in response to high extracellular Ca2+. Phenotypic switching was accompanied by increased levels of ROS and Ca2+-dependent Nox5 in synthetic VSMCs. Nox5 itself regulated VSMC phenotype as siRNA knockdown of Nox5 increased contractile marker expression and decreased calcification, while overexpression of Nox5 decreased contractile marker expression. ROS production in synthetic VSMCs was cytosolic Ca2+-dependent, in line with it being mediated by Nox5. Treatment of VSMCs with Ca2+ loaded extracellular vesicles (EVs) lead to an increase in cytosolic Ca2+. Inhibiting EV endocytosis with dynasore blocked the increase in cytosolic Ca2+ and VSMC calcification. Increased ROS production resulted in increased EV release and decreased phagocytosis by VSMCs. CONCLUSIONS: We show here that contractile VSMCs are resistant to calcification and identify Nox5 as a key regulator of VSMC phenotypic switching. Additionally, we describe a new mechanism of Ca2+ uptake via EVs and show that Ca2+ induces ROS production in VSMCs via Nox5. ROS production is required for release of EVs, which promote calcification. Identifying molecular pathways that control Nox5 and VSMC-derived EVs provides potential targets to modulate vascular remodeling and calcification in the context of mineral imbalance. Graphic Abstract: A graphic abstract is available for this article.

Associations of 4 Geographic Social Vulnerability Indices With US COVID-19 Incidence and Mortality.

Objectives. To examine and compare how 4 indices of population-level social disadvantage-the Social Vulnerability Index (SVI), the Area Deprivation Index (ADI), the COVID-19 Community Vulnerability Index (CCVI), and the Minority Health-Social Vulnerability Index (MH-SVI)-are associated with COVID-19 outcomes. Methods. Spatial autoregressive models adjusted for population density, urbanicity, and state fixed effects were used to estimate associations of county-level SVI, MH-SVI, CCVI, and ADI values with COVID-19 incidence and mortality. Results. All 4 disadvantage indices had similar positive associations with COVID-19 incidence. Each index was also significantly associated with COVID-19 mortality, but the ADI had a stronger association than the CCVI, MH-SVI, and SVI. Conclusions. Despite differences in component measures and weighting, all 4 of the indices we assessed demonstrated associations between greater disadvantage and COVID-19 incidence and mortality. Public Health Implications. Our findings suggest that each of the 4 disadvantage indices can be used to assist public health leaders in targeting ongoing first-dose and booster or third-dose vaccines as well as new vaccines or other resources to regions most vulnerable to negative COVID-19 outcomes, weighing potential tradeoffs in their political and practical acceptability. (Am J Public Health. 2022;112(11):1584-1588. https://doi.org/10.2105/AJPH.2022.307018).

Tracer diffusion in proton-exchanged congruent LiNbO3 crystals as a function of hydrogen content.

The proton-exchange process is an effective method of fabricating low-loss waveguides based on LiNbO3 crystals. During proton-exchange, lithium is replaced by hydrogen and Li1-xHxNbO3 is formed. Currently, mechanisms and kinetics of the proton-exchange process are unclear, primarily due to a lack in reliable tracer diffusion data. We studied lithium and hydrogen tracer diffusion in proton-exchanged congruent LiNbO3 single crystals in the temperature range between 130-230 °C. Proton-exchange was done in benzoic acid with 0, 1, 2, or 3.6 mol% lithium benzoate added, resulting in micrometre thick surface layers where Li is substituted by H with relative fractions between x = 0.45 and 0.85 as determined by Nuclear Reaction Analysis. For the diffusion experiments, ion-beam sputtered isotope enriched 6LiNbO3 was used as a Li tracer source and deuterated benzoic acid as a H tracer source. Isotope depth profile analysis was carried out by secondary ion mass spectrometry. From the experimental results, effective diffusivities governing the lithium/hydrogen exchange as well as individual hydrogen and lithium tracer diffusivities are extracted. All three types of diffusivities can be described by the Arrhenius law with an activation enthalpy of about 1.0-1.2 eV and increase as a function of hydrogen content nearly independent of temperature. The effective diffusivities and the lithium tracer diffusivities are identical within a factor of two to five, while the hydrogen diffusivities are higher by three orders of magnitude. The results show that the diffusion of Li is the rate determining step governing the proton-exchange process. Exponential dependencies between diffusivities and hydrogen concentrations are determined. The observed increase of Li tracer diffusivities and effective diffusivities as a function of hydrogen concentration is attributed to a continuous reduction of the migration enthalpy of diffusion by a maximum factor of about 0.2 eV. Simulations based on the determined diffusivities can reproduce the step-like profile of hydrogen penetration during proton-exchange.

Rationing, racism and justice: advancing the debate around 'colourblind' COVID-19 ventilator allocation.

Withholding or withdrawing life-saving ventilators can become necessary when resources are insufficient. In the USA, such rationing has unique social justice dimensions. Structural elements of dominant allocation frameworks simultaneously advantage white communities, and disadvantage Black communities-who already experience a disproportionate burden of COVID-19-related job losses, hospitalisations and mortality. Using the example of New Jersey's Crisis Standard of Care policy, we describe how dominant rationing guidance compounds for many Black patients prior unfair structural disadvantage, chiefly due to the way creatinine and life expectancy are typically considered.We outline six possible policy options towards a more just approach: improving diversity in decision processes, adjusting creatinine scores, replacing creatinine, dropping creatinine, finding alternative measures, adding equity weights and rejecting the dominant model altogether. We also contrast these options with making no changes, which is not a neutral default, but in separate need of justification, despite a prominent claim that it is simply based on 'objective medical knowledge'. In the regrettable absence of fair federal guidance, hospital and state-level policymakers should reflect on which of these, or further options, seem feasible and justifiable.Irrespective of which approach is taken, all guidance should be supplemented with a monitoring and reporting requirement on possible disparate impacts. The hope that we will be able to continue to avoid rationing ventilators must not stand in the way of revising guidance in a way that better promotes health equity and racial justice, both to be prepared, and given the significant expressive value of ventilator guidance.

Sequential organ failure assessment, ventilator rationing and evolving triage guidance: new evidence underlines the need to recognise and revise, unjust allocation frameworks.

We respond to recent comments on our proposal to improve justice in ventilator triage, in which we used as an example New Jersey's (NJ) publicly available and legally binding Directive Number 2020-03. We agree with Bernard Lo and Doug White that equity implications of triage frameworks should be continually reassessed, which is why we offered six concrete options for improvement, and called for monitoring the consequences of adopted triage models. We disagree with their assessment that we mis-characterised their Model Guidance, as included in the NJ Directive, in ways that undermine our conclusions. They suggest we erroneously described their model as a two-criterion allocation framework; that recognising other operant criterion reveals it 'likely mitigate[s] rather than exacerbate[s] racial disparities during triage', and allege that concerns about inequitable outcomes are 'without evidence'. We highlight two major studies robustly demonstrating why concerns about disparate outcomes are justified. We also show that White and Lo seek to retrospectively-and counterfactually-correct the version of the Model Guideline included in the NJ Directive. However, as our facsimile reproductions show, neither the alleged four-criteria form, nor other key changes, such as dropping the Sequential Organ Failure Assessment score, are found in the Directive. These points matter because (1) our conclusions hence stand, (2) because the public version of the Model Guidance had not been updated to reduce the risk of inequitable outcomes until June 2021 and (3) NJ's Directive still does not reflect these revisions, and, hence, represents a less equitable version, as acknowledged by its authors. We comment on broader policy implications and call for ways of ensuring accurate, transparent and timely updates for users of high-stakes guidelines.

US adults' preferences for race-based and place-based prioritisation for COVID-19 vaccines.

Implementing equity principles in resource allocation is challenging. In one approach, some US states implemented race-based prioritisation of COVID-19 vaccines in response to vast racial inequities in COVID-19 outcomes, while others used place-based allocation. In a nationally representative survey of n=2067 US residents, fielded in mid-April 2021 (before the entire US population became eligible for vaccines), we explored the public acceptability of race-based prioritisation compared with place-based prioritisation, by offering vaccines to harder hit zip codes before residents of other zip codes. We found that in general, a majority of respondents supported the place-based approach, and a substantial proportion supported the race-based plan. Support was higher among Democrats compared with Republicans. All US residents became eligible for vaccines on 19 April 2021 but as of this writing, equitable uptake of vaccines remains urgent not only for first doses for adults but also for boosters and for children. Our findings also provide a benchmark for future pandemic planning that racial and social justice in vaccine allocation are salient considerations for the public. The findings may furthermore be of interest to policy makers designing vaccine allocation frameworks in countries with comparable health disparities across social, ethnic and racial groups, and more broadly, for those exploring ways of promoting equity in resource allocation outside of a pandemic setting.

Public attitudes about equitable COVID-19 vaccine allocation: a randomised experiment of race-based versus novel place-based frames.

Equity was-and is-central in the US policy response to COVID-19, given its disproportionate impact on disadvantaged communities of colour. In an unprecedented turn, the majority of US states used place-based disadvantage indices to promote equity in vaccine allocation (eg, through larger vaccine shares for more disadvantaged areas and people of colour).We conducted a nationally representative survey experiment (n=2003) in April 2021 (before all US residents had become vaccine eligible), that examined respondents' perceptions of the acceptability of disadvantage indices relative to two ways of prioritising racial and ethnic groups more directly, and assessed the role of framing and expert anchors in shaping perceptions.A majority of respondents supported the use of disadvantage indices, and one-fifth opposed any of the three equity-promoting plans. Differences in support and opposition were identified by respondents' political party affiliation. Providing a numerical anchor (that indicated expert recommendations and states' actual practices in reserving a proportion of allocations for prioritised groups) led respondents to prefer a lower distribution of reserved vaccine allocations compared with the randomised condition without this anchor, and the effect of the anchor differed across the frames.Our findings support ongoing uses of disadvantage indices in vaccine allocation, and, by extension, in allocating tests, masks or treatments, especially when supply cannot meet demand. The findings can also inform US allocation frameworks in future pandemic planning, and could provide lessons on how to promote equity in clinical and public health outside of the pandemic setting.

From single drug targets to synergistic network pharmacology in ischemic stroke.

Drug discovery faces an efficacy crisis to which ineffective mainly single-target and symptom-based rather than mechanistic approaches have contributed. We here explore a mechanism-based disease definition for network pharmacology. Beginning with a primary causal target, we extend this to a second using guilt-by-association analysis. We then validate our prediction and explore synergy using both cellular in vitro and mouse in vivo models. As a disease model we chose ischemic stroke, one of the highest unmet medical need indications in medicine, and reactive oxygen species forming NADPH oxidase type 4 (Nox4) as a primary causal therapeutic target. For network analysis, we use classical protein-protein interactions but also metabolite-dependent interactions. Based on this protein-metabolite network, we conduct a gene ontology-based semantic similarity ranking to find suitable synergistic cotargets for network pharmacology. We identify the nitric oxide synthase (Nos1 to 3) gene family as the closest target to Nox4 Indeed, when combining a NOS and a NOX inhibitor at subthreshold concentrations, we observe pharmacological synergy as evidenced by reduced cell death, reduced infarct size, stabilized blood-brain barrier, reduced reoxygenation-induced leakage, and preserved neuromotor function, all in a supraadditive manner. Thus, protein-metabolite network analysis, for example guilt by association, can predict and pair synergistic mechanistic disease targets for systems medicine-driven network pharmacology. Such approaches may in the future reduce the risk of failure in single-target and symptom-based drug discovery and therapy.

Community effort endorsing multiscale modelling, multiscale data science and multiscale computing for systems medicine.

Systems medicine holds many promises, but has so far provided only a limited number of proofs of principle. To address this road block, possible barriers and challenges of translating systems medicine into clinical practice need to be identified and addressed. The members of the European Cooperation in Science and Technology (COST) Action CA15120 Open Multiscale Systems Medicine (OpenMultiMed) wish to engage the scientific community of systems medicine and multiscale modelling, data science and computing, to provide their feedback in a structured manner. This will result in follow-up white papers and open access resources to accelerate the clinical translation of systems medicine.

Is it ethical to incentivize mammography screening in medicaid populations?- A policy review and conceptual analysis.

Mammography screening is controversial, as screening decisions are preference-sensitive: equally well-informed women do not universally get mammograms. Offering financial incentives for screening risks unduly influencing the decision-making process and may undermine voluntariness-yet incentives are being used in 4 US states (Arizona, Indiana, Kentucky, Michigan) under Section 1115 waivers. These initiatives are especially problematic in Medicaid populations who typically have lower health literacy and face the potential threat of disenrollment if they opt out. From June 2018 to January 2019, we analyzed publicly-available information on mammography incentives from the Centers for Medicare and Medicaid Services (CMS) and identified criteria (i.e. starting age and frequency of mammography) for incentive eligibility; income brackets of the affected beneficiaries; whether incentives were financial rewards or penalties; and evaluation arrangements. Several ethically relevant differences emerged: all states except Michigan incentivize screening at starting ages and frequencies that conflict with the US Preventive Services Task Force guidelines. Some incentives are rewards (e.g. reduced cost-sharing), and some penalties (e.g. disenrollment). Across states, rewards range from the equivalent of <1 min of work at state minimum wage to 9 days, and penalties range from 2 to 8 h. Political objectives, rather than evidence and ethics, appear to drive mammography incentive design. Programs risk harming vulnerable low-income populations. CMS and US states should therefore review variations and prevent unjustifiable practices, such as incentivizing 35-year-old women. Large incentives should be offered only if accompanied by robust studies. Incentives for using evidence-based mammography decision-aids, instead of mammography completion, better realize the intended goals.

Lithium tracer diffusion in LiNi0.33Mn0.33Co0.33O2 cathode material for lithium-ion batteries.

The LiNi0.33Mn0.33Co0.33O2 compound is one of the most interesting cathode materials for Li-ion batteries. Li diffusion in this material directly influences charging/discharging times (and consequently power densities), maximum capacities, stress formation and possible side reactions. In the present study Li tracer self-diffusion is investigated in polycrystalline sintered bulk samples with an average grain size of about 50 nm in the temperature range between 110 and 350 °C. For analysis, stable 6Li tracers are used in combination with Secondary Ion Mass Spectrometry (SIMS). The diffusivities can be described by the Arrhenius law with an activation enthalpy of (0.85 ± 0.03) eV, which is interpreted as the migration energy of a single Li vacancy. Lithium diffuses via structural vacancies whose concentration is fixed by a Li deficiency of about 10%. An extrapolation of the diffusivities to room temperature gives significantly lower values than the diffusivities obtained by electrochemical measurements in literature.

NOX Inhibitors: From Bench to Naxibs to Bedside.

Reactive oxygen species (ROS) are ubiquitous metabolic products and important cellular signaling molecules that contribute to several biological functions. Pathophysiology arises when ROS are generated either in excess or in cell types or subcellular locations that normally do not produce ROS or when non-physiological types of ROS (e.g., superoxide instead of hydrogen peroxide) are formed. In the latter scenario, antioxidants were considered as the apparent remedy but, clinically, have consistently failed and even sometimes induced harm. The obvious reason for that is the non-selective ROS scavenging effects of antioxidants which interfere with both qualities of ROS, physiological and pathological. Therefore, it is essential to overcome this "antidote or neutralizer" strategy. We here review the most promising alternative approach by identifying the disease-relevant enzymatic sources of ROS, target these selectively, but leave physiological ROS signaling through other sources intact. Among all ROS sources, NADPH oxidases (NOX1-5 and DUOX1-2) stand out as their sole function is to produce ROS, whereas most other enzymatic sources only produce ROS as a by-product or upon biochemical uncoupling or damage. This qualifies NOXs as the main potential drug-target candidates in diseases associated with dysfunction in ROS signaling. As a reflection of this, the development of several NOX inhibitors has taken place. Recently, the WHO approved a new stem, "naxib," which refers to NADPH oxidase inhibitors, and thereby recognized NOX inhibitors as a new therapeutic class. This has been announced while clinical trials with the first-in-class compound, setanaxib (initially known as GKT137831) had been initiated. We also review the differences between the seven NOX family members in terms of structure and function in health and disease and then focus on the most advanced NOX inhibitors with an exclusive focus on clinically relevant validations and applications. Therapeutically relevant NADPH oxidase isoforms type 1, 2, 4, and 5 (NOX1, NOX2, NOX4, NOX5). Of note, NOX5 is not present in mice and rats and thus pre-clinically less studied. NOX2, formerly termed gp91phox, has been correlated with many, too many, diseases and is rather relevant as genetic deficiency in chronic granulomatous disease (CGD), treated by gene therapy. Overproduction of ROS through NOX1, NOX4, and NOX5 leads to the indicated diseases states including atherosclerosis (red), a condition where NOX4 is surprisingly protective.

Network Medicine-Based Unbiased Disease Modules for Drug and Diagnostic Target Identification in ROSopathies.

Most diseases are defined by a symptom, not a mechanism. Consequently, therapies remain symptomatic. In reverse, many potential disease mechanisms remain in arbitrary search for clinical relevance. Reactive oxygen species (ROS) are such an example. It is an attractive hypothesis that dysregulation of ROS can become a disease trigger. Indeed, elevated ROS levels of various biomarkers have been correlated with almost every disease, yet after decades of research without any therapeutic application. We here present a first systematic, non-hypothesis-based approach to transform this field as a proof of concept for biomedical research in general. We selected as seed proteins 9 families with 42 members of clinically researched ROS-generating enzymes, ROS-metabolizing enzymes or ROS targets. Applying an unbiased network medicine approach, their first neighbours were connected, and, based on a stringent subnet participation degree (SPD) of 0.4, hub nodes excluded. This resulted in 12 distinct human interactome-based ROS signalling modules, while 8 proteins remaining unconnected. This ROSome is in sharp contrast to commonly used highly curated and integrated KEGG, HMDB or WikiPathways. These latter serve more as mind maps of possible ROS signalling events but may lack important interactions and often do not take different cellular and subcellular localization into account. Moreover, novel non-ROS-related proteins were part of these forming functional hybrids, such as the NOX5/sGC, NOX1,2/NOS2, NRF2/ENC-1 and MPO/SP-A modules. Thus, ROS sources are not interchangeable but associated with distinct disease processes or not at all. Module members represent leads for precision diagnostics to stratify patients with specific ROSopathies for precision intervention. The upper panel shows the classical approach to generate hypotheses for a role of ROS in a given disease by focusing on ROS levels and to some degree the ROS type or metabolite. Low levels are considered physiological; higher amounts are thought to cause a redox imbalance, oxidative stress and eventually disease. The source of ROS is less relevant; there is also ROS-induced ROS formation, i.e. by secondary sources (see upwards arrow). The non-hypothesis-based network medicine approach uses genetically or otherwise validated risk genes to construct disease-relevant signalling modules, which will contain also ROS targets. Not all ROS sources will be relevant for a given disease; some may not be disease relevant at all. The three examples show (from left to right) the disease-relevant appearance of an unphysiological ROS modifier/toxifier protein, ROS target or ROS source.

Nitric Oxide Synthase Inhibitors into the Clinic at Last.

The 1998 Nobel Prize in Medicine and Physiology for the discovery of nitric oxide, a nitrogen containing reactive oxygen species (also termed reactive nitrogen or reactive nitrogen/oxygen species) stirred great hopes. Clinical applications, however, have so far pertained exclusively to the downstream signaling of cGMP enhancing drugs such as phosphodiesterase inhibitors and soluble guanylate cyclase stimulators. All clinical attempts, so far, to inhibit NOS have failed even though preclinical models were strikingly positive and clinical biomarkers correlated perfectly. This rather casts doubt on our current way of target identification in drug discovery in general and our way of patient stratification based on correlating but not causal biomarkers or symptoms. The opposite, NO donors, nitrite and enhancing NO synthesis by eNOS/NOS3 recoupling in situations of NO deficiency, are rapidly declining in clinical relevance or hold promise but need yet to enter formal therapeutic guidelines, respectively. Nevertheless, NOS inhibition in situations of NO overproduction often jointly with enhanced superoxide (or hydrogen peroxide production) still holds promise, but most likely only in acute conditions such as neurotrauma (Stover et al., J Neurotrauma 31(19):1599-1606, 2014) and stroke (Kleinschnitz et al., J Cereb Blood Flow Metab 1508-1512, 2016; Casas et al., Proc Natl Acad Sci U S A 116(14):7129-7136, 2019). Conversely, in chronic conditions, long-term inhibition of NOS might be too risky because of off-target effects on eNOS/NOS3 in particular for patients with cardiovascular risks or metabolic and renal diseases. Nitric oxide synthases (NOS) and their role in health (green) and disease (red). Only neuronal/type 1 NOS (NOS1) has a high degree of clinical validation and is in late stage development for traumatic brain injury, followed by a phase II safety/efficacy trial in ischemic stroke. The pathophysiology of NOS1 (Kleinschnitz et al., J Cereb Blood Flow Metab 1508-1512, 2016) is likely to be related to parallel superoxide or hydrogen peroxide formation (Kleinschnitz et al., J Cereb Blood Flow Metab 1508-1512, 2016; Casas et al., Proc Natl Acad Sci U S A 114(46):12315-12320, 2017; Casas et al., Proc Natl Acad Sci U S A 116(14):7129-7136, 2019) leading to peroxynitrite and protein nitration, etc. Endothelial/type 3 NOS (NOS3) is considered protective only and its inhibition should be avoided. The preclinical evidence for a role of high-output inducible/type 2 NOS (NOS2) isoform in sepsis, asthma, rheumatic arthritis, etc. was high, but all clinical development trials in these indications were neutral despite target engagement being validated. This casts doubt on the role of NOS2 in humans in health and disease (hence the neutral, black coloring).