Heme induced loss of renovascular endothelial protein C receptor promotes chronic kidney disease in sickle mice.

Chronic kidney disease (CKD) is a major contributor to morbidity and mortality in sickle cell disease (SCD). Anemia, induced by chronic persistent hemolysis, is associated with progressive deterioration of renal health resulting in CKD. Moreover, patients with SCD experience acute kidney injury (AKI), a risk factor for CKD, often during vasoocclusive crisis associated with acute intravascular hemolysis. However, the mechanisms of the hemolysis-driven pathogenesis of the AKI-to-CKD transition in SCD remain elusive. Here, we investigated the role of increased renovascular rarefaction and the resulting substantial loss of vascular endothelial protein C receptor (EPCR) on the progressive deterioration of renal function in transgenic SCD mice. Multiple hemolytic events raised circulating levels of soluble EPCR (sEPCR) indicating loss of EPCR from the cell surface. Using bone marrow transplantation and super-resolution ultrasound imaging, we demonstrated that SCD mice overexpressing EPCR were protective against heme-induced CKD development. In a cohort of SCD patients, plasma sEPCR was significantly higher in individuals with CKD than in those without CKD. This study concludes that multiple hemolytic events may trigger CKD in SCD through the gradual loss of renovascular EPCR. Thus, restoration of EPCR may be a therapeutic target, and plasma sEPCR can be developed as a prognostic marker for sickle CKD.

Investigation on explainable machine learning models to predict chronic kidney diseases.

Chronic kidney disease (CKD) is a major worldwide health problem, affecting a large proportion of the world's population and leading to higher morbidity and death rates. The early stages of CKD sometimes present without visible symptoms, causing patients to be unaware. Early detection and treatments are critical in reducing complications and improving the overall quality of life for people afflicted. In this work, we investigate the use of an explainable artificial intelligence (XAI)-based strategy, leveraging clinical characteristics, to predict CKD. This study collected clinical data from 491 patients, comprising 56 with CKD and 435 without CKD, encompassing clinical, laboratory, and demographic variables. To develop the predictive model, five machine learning (ML) methods, namely logistic regression (LR), random forest (RF), decision tree (DT), Naïve Bayes (NB), and extreme gradient boosting (XGBoost), were employed. The optimal model was selected based on accuracy and area under the curve (AUC). Additionally, the SHAP (SHapley Additive exPlanations) and LIME (Local Interpretable Model-agnostic Explanations) algorithms were utilized to demonstrate the influence of the features on the optimal model. Among the five models developed, the XGBoost model achieved the best performance with an AUC of 0.9689 and an accuracy of 93.29%. The analysis of feature importance revealed that creatinine, glycosylated hemoglobin type A1C (HgbA1C), and age were the three most influential features in the XGBoost model. The SHAP force analysis further illustrated the model's visualization of individualized CKD predictions. For further insights into individual predictions, we also utilized the LIME algorithm. This study presents an interpretable ML-based approach for the early prediction of CKD. The SHAP and LIME methods enhance the interpretability of ML models and help clinicians better understand the rationale behind the predicted outcomes more effectively.

The post-operative tonsillectomy (POPT) study: A multi-centre prospective paediatric cohort study.

OBJECTIVES: Tonsillectomy is the most common operation performed by otolaryngologists in the UK, despite this we have a poor understanding of the post-operative recovery. We aimed to investigate post-operative bleeding and pain following paediatric tonsillectomy using a patient diary. DESIGN: Prospective observational cohort study. SETTING: Multi-centre study involving 12 secondary and tertiary otolaryngology units across the North of England. Patients were recruited from 1st March 2020 to 30th June 2022. Multilevel ordered logistic regression model statistics were performed. PARTICIPANTS: Children (≥4 years, ≤16 years) undergoing tonsillectomy (with or without adenoidectomy) for benign pathology. MAIN OUTCOME MEASURES: Frequency and severity of post-operative bleeding. Intensity and pattern of post-operative pain. RESULTS: In total 297 children were recruited, with 91 (30.6%) diaries eligible for analysis. Post-operative bleeding occurred in 44% of children. Most frequently blood in the saliva was reported (82.9%). Increasing age significantly increased bleeding odds by 17% per year (p = .001). Bleeding frequency decreased with higher surgeon grade (p = .003) and when performing intracapsular coblation tonsillectomy (p = .02) compared with other techniques. Lower age and intracapsular coblation tonsillectomy, against other techniques, significantly reduced rates of pain post-operatively (p < .0001 and p = .0008). CONCLUSION: A high level of low-level post-operative bleeding was observed. Pain scores remained high for 5 days post-operatively then gradually reduce to normal by day 13. Intracapsular coblation tonsillectomy appears to be superior to all other techniques in terms of reducing post-operative bleeding and pain. These findings should be used to guide patients in the consent process to inform them of the expected nature of post-surgical recovery.

A machine learning driven monogram for predicting chronic kidney disease stages 3-5.

Chronic kidney disease (CKD) remains one of the most prominent global causes of mortality worldwide, necessitating accurate prediction models for early detection and prevention. In recent years, machine learning (ML) techniques have exhibited promising outcomes across various medical applications. This study introduces a novel ML-driven monogram approach for early identification of individuals at risk for developing CKD stages 3-5. This retrospective study employed a comprehensive dataset comprised of clinical and laboratory variables from a large cohort of diagnosed CKD patients. Advanced ML algorithms, including feature selection and regression models, were applied to build a predictive model. Among 467 participants, 11.56% developed CKD stages 3-5 over a 9-year follow-up. Several factors, such as age, gender, medical history, and laboratory results, independently exhibited significant associations with CKD (p < 0.05) and were utilized to create a risk function. The Linear regression (LR)-based model achieved an impressive R-score (coefficient of determination) of 0.954079, while the support vector machine (SVM) achieved a slightly lower value. An LR-based monogram was developed to facilitate the process of risk identification and management. The ML-driven nomogram demonstrated superior performance when compared to traditional prediction models, showcasing its potential as a valuable clinical tool for the early detection and prevention of CKD. Further studies should focus on refining the model and validating its performance in diverse populations.

White-matter abnormalities and cognitive dysfunction are linked to astrocyte activation in sickle mice.

White-matter injury in sickle-cell disease (SCD) includes silent cerebral infarction diagnosed by diffusion tensor imaging (DTI), a complication associated with cognitive dysfunction in children with SCD. The link between white-matter injury and cognitive dysfunction has not been fully elucidated. The goal of this study was to define whether cerebrovascular lesions and cognitive function in SCD are linked to neuroaxonal damage and astrocyte activation in humanized Townes' SCD mice homozygous for human sickle hemoglobin S (SS) and control mice homozygous for human normal hemoglobin A (AA). Mice underwent MRI with DTI and cognitive testing, and histology sections from their brains were stained to assess microstructural tissue damage, neuroaxonal damage, and astrocyte activation. Fractional anisotropy, showing microstructural cerebrovascular abnormalities identified by DTI in the white matter, was significantly associated with neuronal demyelination in the SS mouse brain. SS mice had reduced learning and memory function with a significantly lower discrimination index compared with AA control mice in the novel object recognition tests. Neuroaxonal damage in the SS mice was synchronously correlated with impaired neurocognitive function and activation of astrocytes. The interplay between astrocyte function and neurons may modulate cognitive performance in SCD.

Insulin-like Growth Factor-1 Prevents Hypoxia/Reoxygenation-Induced White Matter Injury in Sickle Cell Mice.

Occlusion of cerebral blood vessels causes acute cerebral hypoxia-an important trigger of ischemic white matter injury and stroke in sickle cell disease (SCD). While chronic hypoxia triggers compensatory neuroprotection via insulin-like growth factor-1 (IGF-1) and hypoxia inducible factor-1α (HIF-1α), severe bouts of acute hypoxia and subsequent restoration of blood flow (hypoxia/reoxygenation, H/R) overwhelm compensatory mechanisms and cause neuroaxonal damage-identified as white matter lesions-in the brain. The neuroprotective role of IGF-1 in the pathogenesis of white matter injury in SCD has not been investigated; however, it is known that systemic IGF-1 is reduced in individuals with SCD. We hypothesized that IGF-1 supplementation may prevent H/R-induced white matter injury in SCD. Transgenic sickle mice homozygous for human hemoglobin S and exposed to H/R developed white matter injury identified by elevated expression of non-phosphorylated neurofilament H (SMI32) with a concomitant decrease in myelin basic protein (MBP) resulting in an increased SMI32/MBP ratio. H/R-challenge also lowered plasma and brain IGF-1 expression. Human recombinant IGF-1 prophylaxis significantly induced HIF-1α and averted H/R-induced white matter injury in the sickle mice compared to vehicle-treated mice. The expression of the IGF-1 binding proteins IGFBP-1 and IGFBP-3 was elevated in the IGF-1-treated brain tissue indicating their potential role in mediating neuroprotective HIF-1α signaling. This study provides proof-of-concept for IGF-1-mediated neuroprotection in SCD.

Immunomodulatory actions of a kynurenine-derived endogenous electrophile.

The up-regulation of kynurenine metabolism induces immunomodulatory responses via incompletely understood mechanisms. We report that increases in cellular and systemic kynurenine levels yield the electrophilic derivative kynurenine-carboxyketoalkene (Kyn-CKA), as evidenced by the accumulation of thiol conjugates and saturated metabolites. Kyn-CKA induces NFE2 like bZIP transcription factor 2- and aryl hydrocarbon receptor-regulated genes and inhibits nuclear factor κB- and NLR family pyrin domain containing 3-dependent proinflammatory signaling. Sickle cell disease (SCD) is a hereditary hemolytic condition characterized by basal inflammation and recurrent vaso-occlusive crises. Both transgenic SCD mice and patients with SCD exhibit increased kynurenine and Kyn-CKA metabolite levels. Plasma hemin and kynurenine concentrations are positively correlated, indicating that Kyn-CKA synthesis in SCD is up-regulated during pathogenic vascular stress. Administration of Kyn-CKA abrogated pulmonary microvasculature occlusion in SCD mice, an important factor in lung injury development. These findings demonstrate that the up-regulation of kynurenine synthesis and its metabolism to Kyn-CKA is an adaptive response that attenuates inflammation and protects tissues.

Nrf2 Activation With CDDO-Methyl Promotes Beneficial and Deleterious Clinical Effects in Transgenic Mice With Sickle Cell Anemia.

Activation of Nrf2, a major transcription factor that drives the antioxidant defense system, is an emerging therapeutic strategy in Sickle Cell Disease (SCD). In this study, transgenic Sickle Cell Anemia mice (SS mice) treated with CDDO-Methyl (CDDO-Me), a potent Nrf2 activator, showed reduced progression of hemolytic anemia with aging, but surprisingly also showed reduced endothelial function. Pulmonary vessels isolated from SS mice treated for 4 months with CDDO-Me displayed a diminished response to nitric oxide (NO)-induced vasodilation compared to littermates given vehicle. It is unclear what molecular mechanism underly the vascular impairment, however, our in vitro assays revealed that CDDO-Me induced the expression of the endothelin receptor (ETA and ETB) in vascular smooth muscle cells. Endothelin signaling is associated with increased vascular tone and vasoconstriction. This study underscores the importance of pre-clinical benefit-risk investigations of Nrf2 activating compounds which may be used to treat patients with SCD.

VEGF Receptor 1 Promotes Hypoxia-Induced Hematopoietic Progenitor Proliferation and Differentiation.

Although it is well known that hypoxia incites unleashed cellular inflammation, the mechanisms of exaggerated cellular inflammation in hypoxic conditions are not known. We observed augmented proliferation of hematopoietic stem and progenitor cells (HSPC), precursors of inflammatory leukocytes, in mice under hypoxia. Consistently, a transcriptomic analysis of human HSPC exposed to hypoxic conditions revealed elevated expression of genes involved in progenitor proliferation and differentiation. Additionally, bone marrow cells in mice expressed high amount of vascular endothelial growth factor (VEGF), and HSPC elevated VEGF receptor 1 (VEGFr1) and its target genes in hypoxic conditions. In line with this, VEGFr1 blockade in vivo and in vitro decreased HSPC proliferation and attenuated inflammation. In silico and ChIP experiments demonstrated that HIF-1α binds to the promoter region of VEGFR1. Correspondingly, HIF1a silencing decreased VEGFr1 expression in HSPC and diminished their proliferation. These results indicate that VEGF signaling in HSPC is an important mediator of their proliferation and differentiation in hypoxia-induced inflammation and represents a potential therapeutic target to prevent aberrant inflammation in hypoxia-associated diseases.

Acute otitis externa: Consensus definition, diagnostic criteria and core outcome set development.

OBJECTIVE: Evidence for the management of acute otitis externa (AOE) is limited, with unclear diagnostic criteria and variably reported outcome measures that may not reflect key stakeholder priorities. We aimed to develop 1) a definition, 2) diagnostic criteria and 3) a core outcome set (COS) for AOE. STUDY DESIGN: COS development according to Core Outcome Measures in Effectiveness Trials (COMET) methodology and parallel consensus selection of diagnostic criteria/definition. SETTING: Stakeholders from the United Kingdom. SUBJECTS AND METHODS: Comprehensive literature review identified candidate items for the COS, definition and diagnostic criteria. Nine individuals with past AOE generated further patient-centred candidate items. Candidate items were rated for importance by patient and professional (ENT doctors, general practitioners, microbiologists, nurses, audiologists) stakeholders in a three-round online Delphi exercise. Consensus items were grouped to form the COS, diagnostic criteria, and definition. RESULTS: Candidate COS items from patients (n = 28) and literature (n = 25) were deduplicated and amalgamated to a final candidate list (n = 46). Patients emphasised quality-of-life and the impact on daily activities/work. Via the Delphi process, stakeholders agreed on 31 candidate items. The final COS covered six outcomes: pain; disease severity; impact on quality-of-life and daily activities; patient satisfaction; treatment-related outcome; and microbiology. 14 candidate diagnostic criteria were identified, 8 reaching inclusion consensus. The final definition for AOE was 'diffuse inflammation of the ear canal skin of less than 6 weeks duration'. CONCLUSION: The development and adoption of a consensus definition, diagnostic criteria and a COS will help to standardise future research in AOE, facilitating meta-analysis. Consulting former patients throughout development highlighted deficiencies in the outcomes adopted previously, in particular concerning the impact of AOE on daily life.

Xanthine Oxidase Drives Hemolysis and Vascular Malfunction in Sickle Cell Disease.

OBJECTIVE: Chronic hemolysis is a hallmark of sickle cell disease (SCD) and a driver of vasculopathy; however, the mechanisms contributing to hemolysis remain incompletely understood. Although XO (xanthine oxidase) activity has been shown to be elevated in SCD, its role remains unknown. XO binds endothelium and generates oxidants as a byproduct of hypoxanthine and xanthine catabolism. We hypothesized that XO inhibition decreases oxidant production leading to less hemolysis. Approach and Results: Wild-type mice were bone marrow transplanted with control (AA) or sickle (SS) Townes bone marrow. After 12 weeks, mice were treated with 10 mg/kg per day of febuxostat (Uloric), Food and Drug Administration-approved XO inhibitor, for 10 weeks. Hematologic analysis demonstrated increased hematocrit, cellular hemoglobin, and red blood cells, with no change in reticulocyte percentage. Significant decreases in cell-free hemoglobin and increases in haptoglobin suggest XO inhibition decreased hemolysis. Myographic studies demonstrated improved pulmonary vascular dilation and blunted constriction, indicating improved pulmonary vasoreactivity, whereas pulmonary pressure and cardiac function were unaffected. The role of hepatic XO in SCD was evaluated by bone marrow transplanting hepatocyte-specific XO knockout mice with SS Townes bone marrow. However, hepatocyte-specific XO knockout, which results in >50% diminution in circulating XO, did not affect hemolysis levels or vascular function, suggesting hepatocyte-derived elevation of circulating XO is not the driver of hemolysis in SCD. CONCLUSIONS: Ten weeks of febuxostat treatment significantly decreased hemolysis and improved pulmonary vasoreactivity in a mouse model of SCD. Although hepatic XO accounts for >50% of circulating XO, it is not the source of XO driving hemolysis in SCD.

National, Virtual Otolaryngology Training Day in the United Kingdom During the COVID-19 Pandemic: Results of a Pilot Survey.

The COVID-19 pandemic has forced an unprecedented worldwide change in our daily lives, particularly in healthcare. In response to the lockdown measure it has brought on, some deaneries cancelled planned teaching days, while others had delivered remote smaller scale teaching sessions electronically. Due to significant regional variation, the National Association of Program Directors in ENT (NAPDENT) set up a national educational program, matched to the Intercollegiate Surgical Curriculum Program. This is delivered virtually and for free. This pilot survey evaluates participants' learning experience of the first NAPDENT National Otology Training Day, which was held on 20 April 2020 via Zoom. This is a pilot survey evaluating the first online, national educational program delivered by the NAPDENT in the United Kingdom. In the times of the COVID-19 pandemic, our program has rapidly learnt from this initial experience and continues to build on lessons learnt for future editions. It is feasible to augment the national ENT curriculum with a collaborative, online teaching program. Regional buy-in is required to make this work. This modality allows for access to subject experts across the country. Synchronous delivery allows for participant interaction, while an online repository allows for asynchronous viewing when work or personal commitments do not allow live attendance. The key to participant engagement is adequate structure, appropriate breaks and opportunities for interaction. Even once the COVID-19 pandemic has passed, this teaching modality will remain as an opportunity to educate ENT surgeons of the future.

Development of Automated Sleep Stage Classification System Using Multivariate Projection-Based Fixed Boundary Empirical Wavelet Transform and Entropy Features Extracted from Multichannel EEG Signals.

The categorization of sleep stages helps to diagnose different sleep-related ailments. In this paper, an entropy-based information-theoretic approach is introduced for the automated categorization of sleep stages using multi-channel electroencephalogram (EEG) signals. This approach comprises of three stages. First, the decomposition of multi-channel EEG signals into sub-band signals or modes is performed using a novel multivariate projection-based fixed boundary empirical wavelet transform (MPFBEWT) filter bank. Second, entropy features such as bubble and dispersion entropies are computed from the modes of multi-channel EEG signals. Third, a hybrid learning classifier based on class-specific residuals using sparse representation and distances from nearest neighbors is used to categorize sleep stages automatically using entropy-based features computed from MPFBEWT domain modes of multi-channel EEG signals. The proposed approach is evaluated using the multi-channel EEG signals obtained from the cyclic alternating pattern (CAP) sleep database. Our results reveal that the proposed sleep staging approach has obtained accuracies of 91.77%, 88.14%, 80.13%, and 73.88% for the automated categorization of wake vs. sleep, wake vs. rapid eye movement (REM) vs. Non-REM, wake vs. light sleep vs. deep sleep vs. REM sleep, and wake vs. S1-sleep vs. S2-sleep vs. S3-sleep vs. REM sleep schemes, respectively. The developed method has obtained the highest overall accuracy compared to the state-of-art approaches and is ready to be tested with more subjects before clinical application.

Heme Induces IL-6 and Cardiac Hypertrophy Genes Transcripts in Sickle Cell Mice.

Emerging data indicate that free heme promotes inflammation in many different disease settings, including in sickle cell disease (SCD). Although free heme, proinflammatory cytokines, and cardiac hypertrophy are co-existing features of SCD, no mechanistic links between these features have been demonstrated. We now report significantly higher levels of IL-6 mRNA and protein in hearts of the Townes sickle cell disease (SS) mice (2.9-fold, p ≤ 0.05) than control mice expressing normal human hemoglobin (AA). We find that experimental administration of heme 50 µmoles/kg body weight induces IL-6 expression directly in vivo and induces gene expression markers of cardiac hypertrophy in SS mice. We administered heme intravenously and found that within three hours plasma IL-6 protein significantly increased in SS mice compared to AA mice (3248 ± 275 vs. 2384 ± 255 pg/ml, p ≤ 0.05). In the heart, heme induced a 15-fold increase in IL-6 transcript in SS mice heart compared to controls. Heme simultaneously induced other markers of cardiac stress and hypertrophy, including atrial natriuretic factor (Nppa; 14-fold, p ≤ 0.05) and beta myosin heavy chain (Myh7; 8-fold, p ≤ 0.05) in SS mice. Our experiments in Nrf2-deficient mice indicate that the cardiac IL-6 response to heme does not require Nrf2, the usual mediator of transcriptional response to heme for heme detoxification by heme oxygenase-1. These data are the first to show heme-induced IL-6 expression in vivo, suggesting that hemolysis may play a role in the elevated IL-6 and cardiac hypertrophy seen in patients and mice with SCD. Our results align with published evidence from rodents and humans without SCD that suggest a causal relationship between IL-6 and cardiac hypertrophy.

Performance anxiety amongst trauma and orthopaedic surgical trainees.

BACKGROUND: This study aims to assess performance anxiety amongst orthopaedic trainees. Operating is equivalent in its skill level, both dexterous and mental, to that of elite sport. This study uses a slightly altered version of the validated Sports Competition Anxiety Test (SCAT), making it relevant to operating, rather than to sport, to evaluate peri-operative stress and anxiety in orthopaedic surgeons. METHODS: The SCAT questionnaire was sent to trainees across 3 UK. deaneries via email. A score of <17 suggests low-levels of anxiety, 17-24 suggests medium-levels of anxiety and >24 suggest high-levels of anxiety. Data was anonymised except from training grade and sex. RESULTS: 109 of 273 (40%) responded to the survey, 71% of respondents were male (n = 77). The mean SCAT score amongst Core Surgical Trainees was 16.9 (n = 21, range 12-23), Specialist Trainees years 3-5 was 18.7 (n = 51, range 12-28), Specialist Trainees years 6-8 was 16.8 (n = 26, range 11-24) and consultants was 16 (n = 11, range 11-28). Across all groups, when sub-divided by sex, females had higher mean scores, this was statistically significant for Specialist Trainees years 3-5 (p = 0.029) and Specialist Trainees years 6-8 (p = 0.042) groups. DISCUSSION: Surgical performance anxiety exists amongst orthopaedic surgeons, with females scoring higher than males. Five respondents scored "high-levels of anxiety" including 2 consultants level surgeons, suggesting experience does not entirely eliminate anxiety. Stress and anxiety are known to lead to surgical mistakes and "burnout" amongst surgeons which is highly topical at present. It is important to highlight this significant issue and it could be taken forward as a national survey to evaluate further.

Automated detection of heart valve diseases using chirplet transform and multiclass composite classifier with PCG signals.

Heart valve diseases (HVDs) are a group of cardiovascular abnormalities, and the causes of HVDs are blood clots, congestive heart failure, stroke, and sudden cardiac death, if not treated timely. Hence, the detection of HVDs at the initial stage is very important in cardiovascular engineering to reduce the mortality rate. In this article, we propose a new approach for the detection of HVDs using phonocardiogram (PCG) signals. The approach uses the Chirplet transform (CT) for the time-frequency (TF) based analysis of the PCG signal. The local energy (LEN) and local entropy (LENT) features are evaluated from the TF matrix of the PCG signal. The multiclass composite classifier formulated based on the sparse representation of the test PCG instance for each class and the distances from the nearest neighbor PCG instances are used for the classification of HVDs such as mitral regurgitation (MR), mitral stenosis (MS), aortic stenosis (AS), and healthy classes (HC). The experimental results show that the proposed approach has sensitivity values of 99.44%, 98.66%, and 96.22% respectively for AS, MS and MR classes. The classification results of the proposed CT based features are compared with existing approaches for the automated classification of HVDs. The proposed approach has obtained the highest overall accuracy as compared to existing methods using the same database. The approach can be considered for the automated detection of HVDs with the Internet of Medical Things (IOMT) applications.

Nrf2 deficiency in mice attenuates erythropoietic stress-related macrophage hypercellularity.

Erythropoiesis in the bone marrow and spleen depends on intricate interactions between the resident macrophages and erythroblasts. Our study focuses on identifying the role of nuclear factor erythroid 2-related factor 2 (Nrf2) during recovery from stress erythropoiesis. To that end, we induced stress erythropoiesis in Nrf2+/+ and Nrf2-null mice and evaluated macrophage subsets known to support erythropoiesis and erythroid cell populations. Our results confirm macrophage and erythroid hypercellularity after acute blood loss. Importantly, Nrf2 depletion results in a marked numerical reduction of F4/80+/CD169+/CD11b+ macrophages, which is more prominent under the induction of stress erythropoiesis. The observed macrophage deficiency is concomitant to a significantly impaired erythroid response to acute stress erythropoiesis in both murine bone marrow and murine spleen. Additionally, peripheral blood reticulocyte count as a response to acute blood loss is delayed in Nrf2-deficient mice compared with age-matched controls (11.0 ± 0.6% vs. 14.8 ± 0.6%, p ≤ 0.001). Interestingly, we observe macrophage hypercellularity in conjunction with erythroid hyperplasia in the bone marrow during stress erythropoiesis in Nrf2+/+ controls, with both impaired in Nrf2-/- mice. We further confirm the finding of macrophage hypercellularity in another model of erythroid hyperplasia, the transgenic sickle cell mouse, characterized by hemolytic anemia and chronic stress erythropoiesis. Our results revealed the role of Nrf2 in stress erythropoiesis in the bone marrow and that macrophage hypercellularity occurs concurrently with erythroid expansion during stress erythropoiesis. Macrophage hypercellularity is a previously underappreciated feature of stress erythropoiesis in sickle cell disease and recovery from blood loss.

Hemopexin deficiency promotes acute kidney injury in sickle cell disease.

Acute kidney injury (AKI) is a major clinical concern in sickle cell disease (SCD). Clinical evidence suggests that red cell alarmins may cause AKI in SCD, however, the sterile inflammatory process involved has hitherto not been defined. We discovered that hemopexin deficiency in SCD is associated with a compensatory increase in α-1-microglobulin (A1M), resulting in an up to 10-fold higher A1M-to-hemopexin ratio in SCD compared with healthy controls. The A1M-to-hemopexin ratio is associated with markers of hemolysis and AKI in both humans and mice with SCD. Studies in mice showed that excess heme is directed to the kidneys in SCD in a process involving A1M causing AKI, whereas excess heme in controls is transported to the liver as expected. Using genetic and bone marrow chimeric tools, we confirmed that hemopexin deficiency promotes AKI in sickle mice under hemolytic stress. However, AKI was blocked when hemopexin deficiency in sickle mice was corrected with infusions of purified hemopexin prior to the induction of hemolytic stress. This study identifies acquired hemopexin deficiency as a risk factor of AKI in SCD and hemopexin replacement as a potential therapy.