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Abstract. This paper describes the rationale and the protocol of the first component of the third simulation round of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3a, http://www.isimip.org, last access: 2 November 2023) and the associated set of climate-related and direct human forcing data (CRF and DHF, respectively). The observation-based climate-related forcings for the first time include high-resolution observational climate forcings derived by orographic downscaling, monthly to hourly coastal water levels, and wind fields associated with historical tropical cyclones. The DHFs include land use patterns, population densities, information about water and agricultural management, and fishing intensities. The ISIMIP3a impact model simulations driven by these observation-based climate-related and direct human forcings are designed to test to what degree the impact models can explain observed changes in natural and human systems. In a second set of ISIMIP3a experiments the participating impact models are forced by the same DHFs but a counterfactual set of atmospheric forcings and coastal water levels where observed trends have been removed. These experiments are designed to allow for the attribution of observed changes in natural, human, and managed systems to climate change, rising CH4 and CO2 concentrations, and sea level rise according to the definition of the Working Group II contribution to the IPCC AR6.

Achieving climate targets requires mitigation against climate change but also understanding of the response of land and ocean carbon systems. In this context, global soil carbon stocks and their response to environmental changes are key. This paper quantifies the global soil carbon feedbacks due to changes in atmospheric CO2, and the associated climate changes, for Earth system models (ESMs) in CMIP6. A standard approach is used to calculate carbon cycle feedbacks, defined here as soil carbon-concentration (βs) and carbon-climate (γs) feedback parameters, which are also broken down into processes which drive soil carbon change. The sensitivity to CO2 is shown to dominate soil carbon changes at least up to a doubling of atmospheric CO2. However, the sensitivity of soil carbon to climate change is found to become an increasingly important source of uncertainty under higher atmospheric CO2 concentrations.

Abstract Despite regulating overlapping gene enhancers and pathways, CREBBP and KMT2D mutations recurrently co-occur in germinal center (GC) B cell-derived lymphomas, suggesting potential oncogenic cooperation. Herein, we report that combined haploinsufficiency of Crebbp and Kmt2d induces a more severe mouse lymphoma phenotype (vs either allele alone) and unexpectedly confers an immune evasive microenvironment manifesting as CD8+ T-cell exhaustion and reduced infiltration. This is linked to profound repression of immune synapse genes that mediate crosstalk with T-cells, resulting in aberrant GC B cell fate decisions. From the epigenetic perspective, we observe interaction and mutually dependent binding and function of CREBBP and KMT2D on chromatin. Their combined deficiency preferentially impairs activation of immune synapse-responsive super-enhancers, pointing to a particular dependency for both co-activators at these specialized regulatory elements. Together, our data provide an example where chromatin modifier mutations cooperatively shape and induce an immune-evasive microenvironment to facilitate lymphomagenesis.

Multicellular life requires altruistic cooperation between cells. The adaptive immune system is a notable exception, wherein germinal center B cells compete vigorously for limiting positive selection signals. Studying primary human lymphomas and developing new mouse models, we found that mutations affecting BTG1 disrupt a critical immune gatekeeper mechanism that strictly limits B cell fitness during antibody affinity maturation. This mechanism converted germinal center B cells into supercompetitors that rapidly outstrip their normal counterparts. This effect was conferred by a small shift in MYC protein induction kinetics but resulted in aggressive invasive lymphomas, which in humans are linked to dire clinical outcomes. Our findings reveal a delicate evolutionary trade-off between natural selection of B cells to provide immunity and potentially dangerous features that recall the more competitive nature of unicellular organisms.

This paper describes the rationale and the protocol of the first component of the third simulation round of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3a, http://www.isimip.org, last access: 2 November 2023) and the associated set of climate-related and direct human forcing data (CRF and DHF, respectively). The observation-based climate-related forcings for the first time include high-resolution observational climate forcings derived by orographic downscaling, monthly to hourly coastal water levels, and wind fields associated with historical tropical cyclones. The DHFs include land use patterns, population densities, information about water and agricultural management, and fishing intensities. The ISIMIP3a impact model simulations driven by these observation-based climate-related and direct human forcings are designed to test to what degree the impact models can explain observed changes in natural and human systems. In a second set of ISIMIP3a experiments the participating impact models are forced by the same DHFs but a counterfactual set of atmospheric forcings and coastal water levels where observed trends have been removed. These experiments are designed to allow for the attribution of observed changes in natural, human, and managed systems to climate change, rising CH4 and CO2 concentrations, and sea level rise according to the definition of the Working Group II contribution to the IPCC AR6.

We herein present an overview of the upcoming 5th edition of the World Health Organization Classification of Haematolymphoid Tumours focussing on lymphoid neoplasms. Myeloid and histiocytic neoplasms will be presented in a separate accompanying article. Besides listing the entities of the classification, we highlight and explain changes from the revised 4th edition. These include reorganization of entities by a hierarchical system as is adopted throughout the 5th edition of the WHO classification of tumours of all organ systems, modification of nomenclature for some entities, revision of diagnostic criteria or subtypes, deletion of certain entities, and introduction of new entities, as well as inclusion of tumour-like lesions, mesenchymal lesions specific to lymph node and spleen, and germline predisposition syndromes associated with the lymphoid neoplasms.

Background Renin–angiotensin system inhibitors, both angiotensin-converting enzyme inhibitors and angiotensin receptor blockers, slow progression of mild and moderate chronic kidney disease. However, some evidence suggests that discontinuation of renin–angiotensin system inhibitors in patients with advanced chronic kidney disease might increase estimated glomerular filtration rate or slow its decline. Objective To test the hypothesis that stopping angiotensin-converting enzyme inhibitors or angiotensin receptor blockers, or a combination of both, compared with continuing these treatments, improves or stabilises kidney function in patients with progressive stages 4 or 5 chronic kidney disease based on assessment of kidney function using the modification of diet in renal disease four-variable estimated glomerular filtration rate at 3 years, follow-up. Setting Thirty-seven UK hospitals with kidney services. Design An investigator-led multicentre open-label, randomised controlled trial of 411 participants with advanced (stage 4 or 5) progressive chronic kidney disease. Participants Adult patients with advanced (estimated glomerular filtration rate < 30 ml/minute/1.73 m2) and progressive chronic kidney disease who were receiving either angiotensin-converting enzyme inhibitors or angiotensin receptor blockers, or a combination of both. Interventions Participants were randomised in a 1 : 1 ratio using a centralised internet-based system to either discontinue renin–angiotensin system inhibitors (n = 206) or continue renin–angiotensin system inhibitors (n = 205). Main outcome measures The primary outcome was the estimated glomerular filtration rate at 3 years; measurements of estimated glomerular filtration rate made after commencing kidney replacement therapy were excluded. Secondary outcomes included development of end-stage kidney disease or starting kidney replacement therapy, a composite of either a > 50% decline in estimated glomerular filtration rate or commencement of kidney replacement therapy (including end-stage kidney disease), cystatin C, hospitalisations, blood pressure, exercise capacity and quality of life. Cardiovascular events, death and safety were recorded. Results At 3 years, the least-squares mean (± standard error) estimated glomerular filtration rate was 12.6 ± 0.7 ml/minute/1.73 m2 in the discontinuation group and 13.3 ± 0.6 ml/minute/1.73 m2 in the continuation group [difference −0.7, 95% confidence interval (−2.5 to 1.0; p = 0.42)] with a negative value favouring the continuation group. The treatment effect did not differ (heterogeneity) when data were analysed by the pre-specified subgroups. End-stage kidney disease or kidney replacement therapy occurred in 128 (62%) and 115 (56%) participants randomised to the discontinue and continue renin–angiotensin system inhibitor groups, respectively (hazard ratio 1.28, 95% confidence interval 0.99 to 1.65). The numbers of cardiovascular events and deaths observed were similar for those randomised to discontinue (108 events and 20 deaths) or continue (88 events and 22 deaths) renin–angiotensin system inhibitors. Limitations Non-white ethnic backgrounds were poorly represented, limiting the generalisability of our findings. The open-label nature of the trial may have affected clinical care and subjective end points, such as quality of life and exercise capacity. We only included patients who were receiving renin–angiotensin system inhibitors at the time of randomisation, thus excluding those who had already discontinued these agents. Conclusions Discontinuing renin–angiotensin system inhibitors in advanced and progressive chronic kidney disease does not cause a clinically relevant change in estimated glomerular filtration rate or difference in its long-term decline. Future work Future work should focus on updating clinical guidelines. Further analyses, in addition to the prespecified analyses, may be undertaken if new estimated glomerular filtration rate equations are introduced into clinical practice. Subgroup analysis by kidney disease aetiology and gender may be undertaken to look for potential differences in outcome in specific groups. Trial registration This trial is registered as STOP ACEi EudraCT Number, 2013-003798-82; ISRCTN62869767. Funding This award was funded by the Efficacy and Mechanism Evaluation (EME) programme (NIHR award ref: 11/30/07), a Medical Research Council (MRC) and National Institute for Health and Care Research (NIHR) partnership. This is published in full in Efficacy and Mechanism Evaluation; Vol. 11, No. 5. See the NIHR Funding and Awards website for further award information. Plain language summary Drugs called angiotensin-converting enzyme inhibitors or angiotensin receptor blockers, together known as renin–angiotensin system inhibitors, are used to treat high blood pressure, slow worsening kidney function and lower the risk of kidney failure (known as end-stage kidney disease which requires treatment with dialysis or kidney transplantation) in patients with early chronic kidney disease. However, we did not know if patients treated with renin–angiotensin system inhibitors and who have progressed to more advanced chronic kidney disease (stage 4 or 5) should stop or continue renin–angiotensin system inhibitors. To determine whether stopping renin–angiotensin system inhibitors in people with advanced chronic kidney disease leads to an improvement or stabilisation of kidney function required a study comparing the outcomes of people who had had these drugs stopped with a group who continued these drugs (the STOP-angiotensin-converting enzyme inhibitors trial). We recruited 411 participants with advanced chronic kidney disease who were receiving renin–angiotensin system inhibitors from 37 kidney units in the UK, and randomly (like flipping a coin) allocated them to either stop or continue renin–angiotensin system inhibitors. We then compared kidney function between the two groups at 3 years. We also assessed whether stopping or continuing renin–angiotensin system inhibitors had an influence on the development of end-stage kidney disease or need for kidney replacement therapy, the number of hospitalisations, blood pressure, quality of life and physical function. We collected data on safety outcomes including death and heart-related events (such as heart attacks). The results of the trial showed no difference in kidney function at 3 years. The number of participants requiring dialysis, or a kidney transplant was also similar, as was the quality of life and physical function between the groups. Deaths and the number of heart events were similar in both groups. This research suggests that there is no benefit in stopping renin–angiotensin system inhibitors in patients with advanced chronic kidney disease. Scientific summary Background Renin–angiotensin system (RAS) inhibitors, both angiotensin-converting enzyme inhibitors (ACEi) and angiotensin receptor blockers (ARB), slow the progression of mild and moderate chronic kidney disease (CKD). However, some evidence suggests that discontinuation of RAS inhibitors in patients with advanced CKD might increase estimated glomerular filtration rate (eGFR) or slow its decline. Primary objective To test the hypothesis that discontinuing ACEi or ARB treatment, or a combination of both, compared with continuing on these treatments, improves or stabilises kidney function in patients with progressive stage 4 or stage 5 CKD based on assessment of kidney function using the modification of diet in renal disease (MDRD) four-variable eGFR at 3 years follow-up. Secondary objectives To test whether in each of the randomised groups. Clinical outcomes The number of participants starting kidney replacement therapy (KRT) (dialysis or transplantation) or sustaining a > 50% decline in eGFR differs. There is a difference in the time taken to reach end-stage kidney disease (ESKD) or need for KRT. Hospitalisation rates from any cause are different. Participant quality of life and well-being [measured using the kidney disease quality of life (KDQoL)-SF™ v1.3 questionnaire] differs. Participant physical function (measured using the 6-minute walk test) differs. Withdrawal of these treatments does not cause excess harm [e.g. increased cardiovascular (CV) events such as heart failure, hypertension, myocardial infarction, stroke] and is not associated with an increase in adverse effects. Participant survival in each group is similar. Blood pressure (BP) control is the same. Cystatin-C levels differ. Mechanistic outcomes There is a change in urine protein excretion [urinary protein-to-creatinine ratio (uPCR)]. Discontinuation of ACEi/ARB affects haemoglobin concentration. Discontinuation of ACEi/ARB affects the requirement for erythropoietin stimulating agents. Methods An investigator-initiated, multicentre, open-label randomised trial where people with advanced and progressive CKD (eGFR < 30 ml/minute/1.73 m2) were randomised to either discontinue or continue RAS inhibitors, and then followed up every 3 months for 3 years. Patients underwent screening at 39 centres in the UK. Adults (≥ 18 years of age) with stage 4 or stage 5 CKD (eGFR, < 30 ml/minute/1.73 m2 of body-surface area) were eligible to participate in the trial if they were not receiving dialysis and had not undergone kidney transplantation. All eligible patients were required to have had a decrease of more than 2 ml/minute/1.73 m2 per year in the eGFR during the previous 2 years and to have been receiving treatment with an ACEi, an ARB, or both for more than 6 months. We calculated the eGFR using the four-variable equation used in the MDRD study, as updated in 2005 (MDRD175). Exclusion criteria included uncontrolled hypertension or a history of myocardial infarction or stroke within the previous 3 months. All the patients provided written informed consent. Patients were randomly assigned in a 1 : 1 ratio to either discontinue or continue RAS inhibitors. Randomisation used a centralised internet-based system with minimisation to ensure balance between groups for the following variables: age (< 65 or ≥ 65 years), eGFR (< 15 or ≥ 15 ml/minute/1.73 m2), diabetes (type 1, type 2, or none), mean arterial pressure (< 100 or ≥ 100 mmHg) and proteinuria [protein-to-creatinine ratio (PCR), < 100 or ≥ 100 mg/mmol]. In the group that discontinued RAS inhibitor, any guideline-recommended antihypertensive agent other than a RAS inhibitor could be used to control BP. In the group that continued RAS inhibitors, the responsible clinician chose the agent and dose of the RAS inhibitor and could combine it with any other guideline-recommended antihypertensive agent. The primary outcome was the eGFR at 3 years as calculated according to the MDRD175 four-variable equation. Secondary outcome measures included the time until the development of ESKD or initiation of KRT; a composite of a decrease of more than 50% in the eGFR, the development of ESKD, or the initiation of KRT; hospitalisation for any cause; measures of cystatin C and BP; quality of life (as measured on the KDQoL 36-Item Short Form Survey, version 1.3); exercise capacity (as assessed by the 6-minute walk test); and CV events and death. At the time of this report, the transfer and processing of samples for cystatin C measurement had not yet occurred, so the results are not provided here. Secondary mechanistic outcomes included measures of haemoglobin and urinary protein excretion (PCR). The trial aimed to recruit 410 patients (205 patients in each trial group) which would provide 80% power to determine a minimum relevant between-group difference in the eGFR of 5 ml/minute/1.73 m2 (alpha level of 0.05), assuming an attrition rate of 20%. This difference represents an effect size of 0.31, with a standard deviation of 16 ml/minute/1.73 m2. The analyses were based on the intention-to-treat principle and were adjusted for the minimisation variables and baseline values. A repeated-measures, mixed-effects linear regression model was used to estimate the between-group difference in eGFR at 3 years. Any measurements of eGFR that were made after patients had initiated dialysis or undergone kidney transplantation were excluded from the primary analysis. To examine the effect of data that were not missing at random, we performed sensitivity analyses by fitting pattern-mixture and joint models for the primary outcome. We also repeated analyses for the primary outcome with the use of two other four-variable equations for the eGFR calculation: the Chronic Kidney Disease Epidemiology Collaboration 2009 equation and the MDRD186 equation. Continuously distributed secondary outcomes, such as BP, were analysed using the same methods as per the primary analysis, but data were not censored at the time of initiation of KRT. Categorical (dichotomous) secondary outcomes were analysed with the use of a Poisson regression model with robust standard errors (SEs) to estimate the relative risk (RR) and 95% confidence interval (CI). A Cox proportional-hazards model was used to calculate hazard ratios (HRs) and 95% CIs for time-to-event outcomes, such as the development of ESKD or the initiation of KRT. Categorical safety outcome measures (i.e. hospitalisation and serious adverse events) were summarised as the percentage of patients with these events. Data collection for kidney outcomes did not distinguish between ESKD and kidney-replacement outcomes (i.e. both outcomes used the same end-point code), although investigators could note the specific outcome. Prespecified subgroup analyses were performed only for the primary outcome according to the minimisation variables. Time and subgroup were included in the model to allow for the possibility of differential changes over time within subgroups, time according to subgroup and the three-way interaction among the variables of treatment, time and subgroup. Although all data were included in the regression models for the subgroup analyses, only estimates of differences at 3 years are presented. All analyses were performed with the use of SAS software, version 9.4 (SAS Institute), and Stata software, version 17 (StataCorp). Results At 3 years, among the 411 patients who underwent randomisation, the least-squares mean (LS-Mean) (±SE) eGFR was 12.6 ± 0.7 ml/minute/1.73 m2 in the discontinuation group and 13.3 ± 0.6 ml/minute/1.73 m2 in the continuation group (difference −0.7, 95% (CI −2.5 to 1.0; p = 0.42) with a negative value favouring the continuation group. End-stage kidney disease or the initiation of KRT occurred in 128 patients (62%) in the discontinuation group and in 115 patients (56%) in the continuation group (HR 1.28, 95% CI 0.99 to 1.65). The number of patients with > 50% decline in eGFR or need to start KRT (including ESKD) was 140/206 (68%) in the discontinue RAS inhibitor group compared to 127/202 (63%) in the continue RAS inhibitor group; RR 1.07, 95% CI 0.94 to 1.22. The number of hospitalisations were similar between the groups; 414 in the stop RAS inhibitor group versus 413 in the continue RAS inhibitor group. The difference in LS-Mean at 3 years for systolic BP was 0 mmHg, 95% CI −4 to 5 mmHg. The results were similar for diastolic BP; 0 mmHg, 95% CI −2 to 3 mmHg. Adverse events were similar in both the discontinuation group and continuation group with respect to CV events (108 vs. 88) and deaths (20 vs. 22). Conclusions Our STOP-ACEi trial showed that discontinuing RAS inhibitors for patients with advanced and progressive CKD does not lead to a clinically relevant change in eGFR or difference in the rate of long-term decline in eGFR, overall or in pre-specified subgroups by age, severity of CKD, diabetes, proteinuria or BP. Numerically more patients who discontinued RAS inhibitors had progression to ESKD or need for KRT, so a larger trial might have shown an advantage to continuing with RAS inhibition. The rate of CV events and death was similar. Systolic and diastolic BP and proteinuria were greater over the first year of follow-up in those randomised to discontinue RAS inhibitors but there was little difference, thereafter, reflecting initiation of antihypertensive agents other than RAS inhibitors. No differences in quality of life or exercise capacity were observed for those who discontinued or continued RAS inhibitors. Our trial lacked sufficient power to investigate the effect of withdrawing RAS inhibitors on CV events or mortality. However, because our trial suggests that there is no advantage in discontinuing RAS inhibitors from the perspective of kidney function, there is little rationale to conduct a larger randomised trial to investigate CV safety. Future work Future work should initially focus on updating clinical guidelines in the UK and potentially worldwide. Further analyses, in addition to the prespecified analyses, may be undertaken if new eGFR equations are introduced into routine clinical practice such as the National Institute for Health and Care Excellence recommended removal of black ethnicity correction factor from the eGFR equation. Consideration of subgroup analysis by aetiology of kidney disease and gender will be considered to look for any potential differences in outcome in specific groups which might warrant future studies. Trial registration This trial is registered as STOP ACEi EudraCT Number, 2013-003798-82; ISTRCTN62869767. Funding This award was funded by the Efficacy and Mechanism Evaluation (EME) programme (NIHR award ref: 11/30/07), a Medical Research Council (MRC) and National Institute for Health and Care Research (NIHR) partnership. This is published in full in Efficacy and Mechanism Evaluation; Vol. 11, No. 5. See the NIHR Funding and Awards website for further award information.

* Context.--Machine learning (ML) allows for the analysis of massive quantities of high-dimensional clinical laboratory data, thereby revealing complex patterns and trends. Thus, ML can potentially improve the efficiency of clinical data interpretation and the practice of laboratory medicine. However, the risks of generating biased or unrepresentative models, which can lead to misleading clinical conclusions or overestimation of the model performance, should be recognized. Objectives.--To discuss the major components for creating ML models, including data collection, data preprocessing, model development, and model evaluation. We also highlight many of the challenges and pitfalls in developing ML models, which could result in misleading clinical impressions or inaccurate model performance, and provide suggestions and guidance on how to circumvent these challenges. Data Sources.--The references for this review were identified through searches of the PubMed database, US Food and Drug Administration white papers and guidelines, conference abstracts, and online preprints. Conclusions.--With the growing interest in developing and implementing ML models in clinical practice, laboratorians and clinicians need to be educated in order to collect sufficiently large and high-quality data, properly report the data set characteristics, and combine data from multiple institutions with proper normalization. They will also need to assess the reasons for missing values, determine the inclusion or exclusion of outliers, and evaluate the completeness of a data set. In addition, they require the necessary knowledge to select a suitable ML model for a specific clinical question and accurately evaluate the performance of the ML model, based on objective criteria. Domain-specific knowledge is critical in the entire workflow of developing ML models. (Arch Pathol Lab Med. 2023;147:826-836; doi: 10.5858/ arpa.2021-0635-RA), Machine learning (ML) (1) has emerged as a powerful tool for analyzing and interpreting laboratory test results as well as integrating clinical findings with laboratory data. (2) In recent years, [...]

Abstract Lymphoid cancers are among the most frequent cancers diagnosed in adolescents and young adults (AYA), ranging from approximately 30%–35% of cancer diagnoses in adolescent patients (age 10–19) to approximately 10% in patients aged 30–39 years. Moreover, the specific distribution of lymphoid cancer types varies by age with substantial shifts in the subtype distributions between pediatric, AYA, adult, and older adult patients. Currently, biology studies specific to AYA lymphomas are rare and therefore insight into age‐related pathogenesis is incomplete. This review focuses on the paradigmatic epidemiology and pathogenesis of select lymphomas, occurring in the AYA patient population. With the example of posttransplant lymphoproliferative disorders, nodular lymphocyte‐predominant Hodgkin lymphoma, follicular lymphoma (incl. pediatric‐type follicular lymphoma), and mediastinal lymphomas (incl. classic Hodgkin lymphoma, primary mediastinal large B cell lymphoma and mediastinal gray zone lymphoma), we here illustrate the current state‐of‐the‐art in lymphoma classification, recent molecular insights including genomics, and translational opportunities. To improve outcome and quality of life, international collaboration in consortia dedicated to AYA lymphoma is needed to overcome challenges related to siloed biospecimens and data collections as well as to develop studies designed specifically for this unique population.

Reliable estimates of soil carbon change are required to determine the carbon budgets consistent with the Paris Agreement climate targets. This study evaluates projections of soil carbon during the 21st century in Coupled Model Intercomparison Project Phase 6 (CMIP6) Earth system models (ESMs) under a range of atmospheric composition scenarios. In general, we find a reduced spread of changes in global soil carbon (ΔCs) in CMIP6 compared to the previous CMIP5 model generation. However, similar reductions were not seen in the derived contributions to ΔCs due to both increases in plant net primary productivity (NPP, named ΔCs,NPP) and reductions in the effective soil carbon turnover time (τs, named ΔCs,τ). Instead, we find a strong relationship across the CMIP6 models between these NPP and τs components of ΔCs, with more positive values of ΔCs,NPP being correlated with more negative values of ΔCs,τ. We show that the concept of “false priming” is likely to be contributing to this emergent relationship, which leads to a decrease in the effective soil carbon turnover time as a direct result of NPP increase and occurs when the rate of increase in NPP is relatively fast compared to the slower timescales of a multi-pool soil carbon model. This finding suggests that the structure of soil carbon models within ESMs in CMIP6 has likely contributed towards the reduction in the overall model spread in future soil carbon projections since CMIP5.

Idiopathic sudden sensorineural hearing loss (ISSNHL) is the rapid onset of reduced hearing due to loss of function of the inner ear or hearing nerve of unknown aetiology. Evidence supports improved hearing recovery with early steroid treatment, via oral, intravenous, intratympanic or a combination of routes. The STARFISH trial aims to identify the most clinically and cost-effective route of administration of steroids as first-line treatment for ISSNHL. STARFISH is a pragmatic, multicentre, assessor-blinded, three-arm intervention, superiority randomised controlled trial (1:1:1) with an internal pilot (ISRCTN10535105, IRAS 1004878). 525 participants with ISSNHL will be recruited from approximately 75 UK Ear, Nose and Throat units. STARFISH will recruit adults with sensorineural hearing loss averaging 30dBHL or greater across three contiguous frequencies (confirmed via pure tone audiogram), with onset over a ≤3-day period, within four weeks of randomisation. Participants will be randomised to 1) oral prednisolone 1mg/Kg/day up to 60mg/day for 7 days; 2) intratympanic dexamethasone: three intratympanic injections 3.3mg/ml or 3.8mg/ml spaced 7±2 days apart; or 3) combined oral and intratympanic steroids. The primary outcome will be absolute improvement in pure tone audiogram average at 12-weeks following randomisation (0.5, 1.0, 2.0 and 4.0kHz). Secondary outcomes at 6 and 12 weeks will include: Speech, Spatial and Qualities of hearing scale, high frequency pure tone average thresholds (4.0, 6.0 and 8.0kHz), Arthur Boothroyd speech test, Vestibular Rehabilitation Benefit Questionnaire, Tinnitus Functional Index, adverse events and optional weekly online speech and pure tone hearing tests. A health economic assessment will be performed, and presented in terms of incremental cost effectiveness ratios, and cost per quality-adjusted life-year. Primary analyses will be by intention-to-treat. Oral prednisolone will be the reference. For the primary outcome, the difference between group means and 97.5% confidence intervals at each time-point will be estimated via a repeated measures mixed-effects linear regression model.

Follicular lymphoma (FL) is an indolent B-cell neoplasm of germinal center origin. Standard treatment regimens consist of anti-CD20 therapy with or without chemotherapy. While high response rates to initial therapy are common, patients ultimately relapse or have progressive disease. Clinical risk factors such as the Follicular Lymphoma International Prognostic Index (FLIPI) have been identified, but there is a need for prognostic and predictive biomarkers. We studied markers of lymphoma cells and tumor microenvironment by immunohistochemistry in tissue samples from patients enrolled in 1 of 4 phase 2 trials of anti-CD20-based biological therapy for previously untreated grades 1 to 2 or 3A FL. Results were correlated with progression-free survival (PFS) and PFS status at 24 months. The 4 trials included 238 patients (51.1% male, median age: 55 y) with stage III, IV, or bulky stage II disease. By FLIPI, 24.6% had low-risk, 56.8% had intermediate-risk, and 18.6% had high-risk disease. The outcome differed significantly for patients treated with lenalidomide and rituximab (CALGB 50803) compared with the other 3 trials (median: PFS not reached vs. 3.0 y, hazard ratio=3.47, 95% confidence interval: 2.11-5.72); therefore, data were stratified by clinical trial (CALGB 50803 vs. all others) and adjusted for FLIPI risk group. Among 154 patients with available tissue, interfollicular BCL6 positivity, interfollicular CD10 positivity, and elevated Ki67 proliferation index ≥30% within neoplastic follicles were each associated with inferior PFS and a high risk of the early event by PFS status at 24 months. We identify promising biomarkers for FL risk stratification that warrant further validation in phase 3 trials.

Carbon cycle feedbacks represent large uncertainties in climate change projections, and the response of soil carbon to climate change contributes the greatest uncertainty to this. Future changes in soil carbon depend on changes in litter and root inputs from plants and especially on reductions in the turnover time of soil carbon (τs) with warming. An approximation to the latter term for the top one metre of soil (ΔCs,τ) can be diagnosed from projections made with the CMIP6 and CMIP5 Earth System Models (ESMs), and is found to span a large range even at 2 °C of global warming (-196 ± 117 PgC). Here, we present a constraint on ΔCs,τ, which makes use of current heterotrophic respiration and the spatial variability of τs inferred from observations. This spatial emergent constraint allows us to halve the uncertainty in ΔCs,τ at 2 °C to -232 ± 52 PgC.

This study investigates and compares soil moisture and hydrology projections of broadly used land models with permafrost processes and highlights the causes and impacts of permafrost zone soil moisture projections. Climate models project warmer temperatures and increases in precipitation (P) which will intensify evapotranspiration (ET) and runoff in land models. However, this study shows that most models project a long-term drying of the surface soil (0-20 cm) for the permafrost region despite increases in the net air-surface water flux (P-ET). Drying is generally explained by infiltration of moisture to deeper soil layers as the active layer deepens or permafrost thaws completely. Although most models agree on drying, the projections vary strongly in magnitude and spatial pattern. Land models tend to agree with decadal runoff trends but underestimate runoff volume when compared to gauge data across the major Arctic river basins, potentially indicating model structural limitations. Coordinated efforts to address the ongoing challenges presented in this study will help reduce uncertainty in our capability to predict the future Arctic hydrological state and associated land-atmosphere biogeochemical processes across spatial and temporal scales.

New insights from genomic studies have had an impact on the definition and the diagnosis of several lymphoid tumors including follicular B-cell lymphomas, aggressive diffuse large B-cell lymphomas, and lymphoproliferations associated with acquired and posttransplant immunodeficiencies. Follicular lymphoma (FL) includes tumors whose behavior varies widely from indolent/early lesions to aggressive/transformed lymphomas. Although some large B-cell lymphomas can be subclassified as specific entities, the majority lack the characteristics necessary for subclassification and, thus, are termed diffuse large B-cell lymphoma, NOS. There have been, however, some changes in the classification of specific subtypes of large B-cell lymphoma as well as the addition of new entities, a few of which are highlighted in this article. The immunodeficiency-related lymphoproliferative disorders are currently divided into four major categories based on the clinical setting in which they arose: primary immune deficiency, post-transplant, HIV infection, and iatrogenic immunosuppression. In the two upcoming classifications systems for hematolymphoid neoplasms, International Consensus Classification (ICC) and WHO-HAEM-5, there is a divergence in the approach to categorize these lesions. Furthermore, whereas the WHO-HAEM-5 confirms the ability to classify a spectrum of EBV+ lesions as EBV+ DLBCL, NOS, the ICC has separated out lesions that are composed of a heterogenous cellular infiltrate into a new separate category, “EBV-positive polymorphic B cell lymphoproliferative disorder, NOS”. Both WHO-HAEM-5 and ICC recognize a number of KSHV/HHV8-associated lymphoid lesions and acknowledge that there is significant overlap among the different lesions. In the future, translation of these innovations in general practice requires further validation.

Infiltration in soils is a key process that partitions precipitation at the land surface into surface runoff and water that enters the soil profile. We reviewed the basic principles of water infiltration in soils and we analyzed approaches commonly used in land surface models (LSMs) to quantify infiltration as well as its numerical implementation and sensitivity to model parameters. We reviewed methods to upscale infiltration from the point to the field, hillslope, and grid cell scales of LSMs. Despite the progress that has been made, upscaling of local-scale infiltration processes to the grid scale used in LSMs is still far from being treated rigorously. We still lack a consistent theoretical framework to predict effective fluxes and parameters that control infiltration in LSMs. Our analysis shows that there is a large variety of approaches used to estimate soil hydraulic properties. Novel, highly resolved soil information at higher resolutions than the grid scale of LSMs may help in better quantifying subgrid variability of key infiltration parameters. Currently, only a few LSMs consider the impact of soil structure on soil hydraulic properties. Finally, we identified several processes not yet considered in LSMs that are known to strongly influence infiltration. Especially, the impact of soil structure on infiltration requires further research. To tackle these challenges and integrate current knowledge on soil processes affecting infiltration processes into LSMs, we advocate a stronger exchange and scientific interaction between the soil and the land surface modeling communities.

Most land surface models (LSMs), i.e. the land components of Earth system models (ESMs), include representation of nitrogen (N) limitation on ecosystem productivity. However, only a few of these models have incorporated phosphorus (P) cycling. In tropical ecosystems, this is likely to be important as N tends to be abundant, whereas the availability of rock-derived elements, such as P, can be very low. Thus, without a representation of P cycling, tropical forest response in areas such as Amazonia to rising atmospheric CO2 conditions remain highly uncertain. In this study, we introduced P dynamics and its interactions with the N and carbon (C) cycles into the Joint UK Land Environment Simulator (JULES). The new model (JULES-CNP) includes the representation of P stocks in vegetation and soil pools, as well as key processes controlling fluxes between these pools. We develop and evaluate JULES-CNP using in situ data collected at a low-fertility site in the central Amazon, with a soil P content representative of 60 % of soils across the Amazon basin, to parameterize, calibrate, and evaluate JULES-CNP. Novel soil and plant P pool observations are used for parameterization and calibration, and the model is evaluated against C fluxes and stocks and those soil P pools not used for parameterization or calibration. We then evaluate the model at additional P-limited test sites across the Amazon and in Panama and Hawaii, showing a significant improvement over the C- and CN-only versions of the model. The model is then applied under elevated CO2 (600 ppm) at our study site in the central Amazon to quantify the impact of P limitation on CO2 fertilization. We compare our results against the current state-of-the-art CNP models using the same methodology that was used in the AmazonFACE model intercomparison study. The model is able to reproduce the observed plant and soil P pools and fluxes used for evaluation under ambient CO2. We estimate P to limit net primary productivity (NPP) by 24 % under current CO2 and by 46 % under elevated CO2. Under elevated CO2, biomass in simulations accounting for CNP increase by 10 % relative to contemporary CO2 conditions, although it is 5 % lower compared to CN- and C-only simulations. Our results highlight the potential for high P limitation and therefore lower CO2 fertilization capacity in the Amazon rainforest with low-fertility soils.

Studies for the northern high latitudes suggest that, in the near term, increased vegetation uptake may offset permafrost carbon losses, but over longer time periods, permafrost carbon decomposition causes a net loss of carbon. Here, we assess the impact of a coupled carbon and nitrogen cycle on the simulations of these carbon fluxes. We present results from JULES-IMOGEN—a global land surface model coupled to an intermediate complexity climate model with vertically resolved soil biogeochemistry. We quantify the impact of nitrogen fertilisation from thawing permafrost on the carbon cycle and compare it with the loss of permafrost carbon. Projections show that the additional fertilisation reduces the high latitude vegetation nitrogen limitation and causes an overall increase in vegetation carbon uptake. This is a few Petagrams of carbon (Pg C) by year 2100, increasing to up to 40 Pg C by year 2300 for the RCP8.5 concentration scenario and adds around 50% to the projected overall increase in vegetation carbon in that region. This nitrogen fertilisation results in a negative (stabilising) feedback on the global mean temperature, which could be equivalent in magnitude to the positive (destabilising) temperature feedback from the loss of permafrost carbon. This balance depends on the future scenario and initial permafrost carbon. JULES-IMOGEN describes one representation of the changes in Arctic carbon and nitrogen cycling in response to climate change. However there are uncertainties in the modelling framework, model parameterisation and missing processes which, when assessed, will provide a more complete picture of the balance between stabilising and destabilising feedbacks.

Several experimental studies have shown that climate-warming-induced permafrost thaw releases previously unavailable nitrogen which can lower nitrogen limitation, increase plant productivity, and counteract some of the carbon released from thawing permafrost. The net effect of this belowground fertilisation effect remains debated and is yet to be included in Earth System models. Here, we included the impact of thaw-related nitrogen fertilisation on vegetation in the Joint UK Land Environment Simulator (JULES) land surface model for the first time. We evaluated its ability to replicate a three-year belowground fertilisation experiment in which JULES was generally able to simulate belowground fertilisation in accordance with the observations. We also ran simulations under future climate to investigate how belowground nitrogen fertilisation affects the carbon cycle. These simulations indicate an increase in plant-available inorganic nitrogen at the thaw front by the end of the century with only the productivity of deep-rooting plants increasing in response. This suggests that deep-rooting species will have a competitive advantage under future climate warming. Our results also illustrate the capacity to simulate belowground nitrogen fertilisation at the thaw front in a global land surface model, leading towards a more complete representation of coupled carbon and nitrogen dynamics in the northern high latitudes.

Climate change is destabilizing permafrost landscapes, affecting infrastructure, ecosystems, and human livelihoods. The rate of permafrost thaw is controlled by surface and subsurface properties and processes, all of which are potentially linked with each other. However, no standardized protocol exists for measuring permafrost thaw and related processes and properties in a linked manner. The permafrost thaw action group of the Terrestrial Multidisciplinary distributed Observatories for the Study of the Arctic Connections (T-MOSAiC) project has developed a protocol, for use by non-specialist scientists and technicians, citizen scientists, and indigenous groups, to collect standardized metadata and data on permafrost thaw. The protocol introduced here addresses the need to jointly measure permafrost thaw and the associated surface and subsurface environmental conditions. The parameters measured along transects include: snow depth, thaw depth, vegetation height, soil texture, and water level. The metadata collection includes data on timing of data collection, geographical coordinates, land surface characteristics (vegetation, ground surface, water conditions), as well as photographs. Our hope is that this openly available dataset will also be highly valuable for validation and parameterization of numerical and conceptual models, and thus to the broad community represented by the T-MOSAiC project.

Peatlands have often been neglected in Earth system models (ESMs). Where they are included, they are usually represented via a separate, prescribed grid cell fraction that is given the physical characteristics of a peat (highly organic) soil. However, in reality soils vary on a spectrum between purely mineral soil (no organic material) and purely organic soil, typically with an organic layer of variable thickness overlying mineral soil below. They are also dynamic, with organic layer thickness and its properties changing over time. Neither the spectrum of soil types nor their dynamic nature can be captured by current ESMs. Here we present a new version of an ESM land surface scheme (Joint UK Land Environment Simulator, JULES) where soil organic matter accumulation – and thus peatland formation, degradation and stability – is integrated in the vertically resolved soil carbon scheme. We also introduce the capacity to track soil carbon age as a function of depth in JULES and compare this to measured peat age–depth profiles. The new scheme is tested and evaluated at northern and temperate sites. This scheme simulates dynamic feedbacks between the soil organic material and its thermal and hydraulic characteristics. We show that draining the peatlands can lead to significant carbon loss, soil compaction and changes in peat properties. However, negative feedbacks can lead to the potential for peatlands to rewet themselves following drainage. These ecohydrological feedbacks can also lead to peatlands maintaining themselves in climates where peat formation would not otherwise initiate in the model, i.e. displaying some degree of resilience. The new model produces similar results to the original model for mineral soils and realistic profiles of soil organic carbon for peatlands. We evaluate the model against typical peat profiles based on 216 northern and temperate sites from a global dataset of peat cores. The root-mean-squared error (RMSE) in the soil carbon profile is reduced by 35 %–80 % in the best-performing JULES-Peat simulations compared with the standard JULES configuration. The RMSE in these JULES-Peat simulations is 7.7–16.7 kg C m−3 depending on climate zone, which is considerably smaller than the soil carbon itself (around 30–60 kg C m−3). The RMSE at mineral soil sites is also reduced in JULES-Peat compared with the original JULES configuration (reduced by ∼ 30 %–50 %). Thus, JULES-Peat can be used as a complete scheme that simulates both organic and mineral soils. It does not require any additional input data and introduces minimal additional variables to the model. This provides a new approach for improving the simulation of organic and peatland soils and associated carbon-cycle feedbacks in ESMs.

In the version of this Article originally published, a parallelization coding problem, which meant that a subset of model grid cells were subjected to erroneous updating of atmospheric gas concentrations, resulted in incorrect calculation of atmospheric CO2 for these grid cells, and therefore underestimation of the carbon uptake by land through vegetation growth and eventual increases to soil carbon stocks. Having re-run the simulations using the corrected code, the authors found that the original estimates of the impact of the natural wetland methane feedback were overestimated. The permafrost and natural wetland methane feedback requires lower permissible emissions of 9–15% to achieve climate stabilization at 1.5 °C, compared with the original published estimate of 17–23%. The Article text, Table 1 and Fig. 3 have been updated online to reflect the revised numerical estimates. The Supplementary Information file has also been amended, with Supplementary Figs 6, 7, 8 and 9 replaced with revised versions produced using the corrected model output. As the strength of feedbacks remain significant, still require inclusion in climate policy and are nonlinear with global warming, the overall conclusions of the Article remain unchanged.

In the version of this Article originally published, a parallelization coding problem, which meant that a subset of model grid cells were subjected to erroneous updating of atmospheric gas concentrations, resulted in incorrect calculation of atmospheric CO2 for these grid cells, and therefore underestimation of the carbon uptake by land through vegetation growth and eventual increases to soil carbon stocks. Having re-run the simulations using the corrected code, the authors found that the original estimates of the impact of the natural wetland methane feedback were overestimated. The permafrost and natural wetland methane feedback requires lower permissible emissions of 9–15% to achieve climate stabilization at 1.5 °C, compared with the original published estimate of 17–23%. The Article text, Table 1 and Fig. 3 have been updated online to reflect the revised numerical estimates. The Supplementary Information file has also been amended, with Supplementary Figs 6, 7, 8 and 9 replaced with revised versions produced using the corrected model output. As the strength of feedbacks remain significant, still require inclusion in climate policy and are nonlinear with global warming, the overall conclusions of the Article remain unchanged.

Scenarios that limit global warming to below 2 °C by 2100 assume significant land-use change to support large-scale carbon dioxide (CO2) removal from the atmosphere by afforestation/reforestation, avoided deforestation, and Biomass Energy with Carbon Capture and Storage (BECCS). The more ambitious mitigation scenarios require even greater land area for mitigation and/or earlier adoption of CO2 removal strategies. Here we show that additional land-use change to meet a 1.5 °C climate change target could result in net losses of carbon from the land. The effectiveness of BECCS strongly depends on several assumptions related to the choice of biomass, the fate of initial above ground biomass, and the fossil-fuel emissions offset in the energy system. Depending on these factors, carbon removed from the atmosphere through BECCS could easily be offset by losses due to land-use change. If BECCS involves replacing high-carbon content ecosystems with crops, then forest-based mitigation could be more efficient for atmospheric CO2 removal than BECCS.

Global methane emissions from natural wetlands and carbon release from permafrost thaw have a positive feedback on climate, yet are not represented in most state-of-the-art climate models. Furthermore, a fraction of the thawed permafrost carbon is released as methane, enhancing the combined feedback strength. We present simulations with an inverted intermediate complexity climate model, which follows prescribed global warming pathways to stabilization at 1.5 or 2.0 °C above pre-industrial levels by the year 2100, and which incorporates a state-of-the-art global land surface model with updated descriptions of wetland and permafrost carbon release. We demonstrate that the climate feedbacks from those two processes are substantial. Specifically, permissible anthropogenic fossil fuel CO2 emission budgets are reduced by 17–23% (47–56 GtC) for stabilization at 1.5 °C, and 9–13% (52–57 GtC) for 2.0 °C stabilization. In our simulations these feedback processes respond more quickly at temperatures below 1.5 °C, and the differences between the 1.5 and 2 °C targets are disproportionately small. This key finding holds for transient emission pathways to 2100 and does not account for longer-term implications of these feedback processes. We conclude that natural feedback processes from wetlands and permafrost must be considered in assessments of transient emission pathways to limit global warming.

To understand the importance of methane on the levels of carbon emission reductions required to achieve temperature goals, a processed-based approach is necessary rather than reliance on the transient climate response to emissions. We show that plausible levels of methane (CH4) mitigation can make a substantial difference to the feasibility of achieving the Paris climate targets through increasing the allowable carbon emissions. This benefit is enhanced by the indirect effects of CH4 on ozone (O3). Here the differing effects of CH4 and CO2 on land carbon storage, including the effects of surface O3, lead to an additional increase in the allowable carbon emissions with CH4 mitigation. We find a simple robust relationship between the change in the 2100 CH4 concentration and the extra allowable cumulative carbon emissions between now and 2100 (0.27 ± 0.05 GtC per ppb CH4). This relationship is independent of modelled climate sensitivity and precise temperature target, although later mitigation of CH4 reduces its value and thus methane reduction effectiveness. Up to 12% of this increase in allowable emissions is due to the effect of surface ozone. We conclude early mitigation of CH4 emissions would significantly increase the feasibility of stabilising global warming below 1.5 °C, alongside having co-benefits for human and ecosystem health.

NASA has launched the decade-long Arctic-Boreal Vulnerability Experiment (ABoVE). While the initial phases focus on field and airborne data collection, early integration with modeling activities is important to benefit future modeling syntheses. We compiled feedback from ecosystem modeling teams on key data needs, which encompass carbon biogeochemistry, vegetation, permafrost, hydrology, and disturbance dynamics. A suite of variables was identified as part of this activity with a critical requirement that they are collected concurrently and representatively over space and time. Individual projects in ABoVE may not capture all these needs, and thus there is both demand and opportunity for the augmentation of field observations, and synthesis of the observations that are collected, to ensure that science questions and integrated modeling activities are successfully implemented.

Abstract Systemic anaplastic large cell lymphoma (ALCL) is a rare CD30-expressing T-cell non-Hodgkin lymphoma. Risk of systemic ALCL is highly increased among immunosuppressed individuals. Because risk of cancers associated with viruses is increased with immunosuppression, we conducted a metagenomic analysis of systemic ALCL to determine whether a known or novel pathogen is associated with this malignancy. Total RNA was extracted and sequenced from formalin-fixed paraffin-embedded tumor specimens from 19 systemic ALCL cases (including one case from an immunosuppressed individual with human immunodeficiency virus infection), 3 Epstein-Barr virus positive diffuse large B-cell lymphomas (DLBCLs) occurring in solid organ transplant recipients (positive controls), and 3 breast cancers (negative controls). We used a pipeline based on the Genome Analysis Toolkit (GATK)-PathSeq algorithm to subtract out human RNA reads and map the remaining RNA reads to microbes. No microbial association with ALCL was identified, but we found Epstein-Barr virus in the DLBCL positive controls and determined the breast cancers to be negative. In conclusion, we did not find a pathogen associated with systemic ALCL, but because we analyzed only one ALCL tumor from an immunosuppressed person, we cannot exclude the possibility that a pathogen is associated with some cases that arise in the setting of immunosuppression.