Defining the optimal biological monotherapy in rheumatoid arthritis: a systematic review and meta-analysis of randomised trials

Objectives To summarize and compare the benefits and harms of biological agents used as monotherapy for rheumatoid arthritis (RA) in order to inform decisions for patients who are intolerant to conventional DMARD therapy. Methods We searched MEDLINE, EMBASE, CENTRAL, and other sources for randomised trials that compared biological monotherapy with methotrexate, placebo, or other biological monotherapies. Primary outcomes were ACR50 and the number of patients who discontinued due to adverse events. Our network meta-analysis was based on mixed-effects logistic regression, including both direct and indirect comparisons of the treatment effects, while preserving the randomised comparisons within each trial. PROSPERO identifier: CRD42012002800. Results The analysis comprises 28 trials (8602 patients), including all nine biological agents approved for RA. Eight trials included “DMARD-naïve”, and 20 “DMARD-Inadequate responder” (DMARD-IR) patients. All agents except anakinra and infliximab were superior (p 0.52). However, because rituximab was evaluated in just 40 patients, our confidence in the estimates is limited. When including only DMARD-IR trials, the same statistical pattern emerged; in addition etanercept and tocilizumab were superior to abatacept. At recommended doses, both etanercept and tocilizumab were superior to adalimumab and certolizumab. No statistically significant differences among biological agents were found with respect to discontinuation due to adverse events (p > 0.068). Conclusions Evidence from randomised trials suggests that most biological agents are effective as monotherapy. Although our confidence in the estimates is limited, etanercept or tocilizumab may be the optimal choice for most patients who need treatment with biological monotherapy. However, given our limited confidence in the estimates including possibility of bias, it is appropriate to strongly weight patients׳ preferences and values in the final treatment choice

A complete representation of uncertainties in layer-counted paleoclimatic archives

Accurate time series representation of paleoclimatic proxy records is challenging because such records involve dating errors in addition to proxy measurement errors. Rigorous attention is rarely given to age uncertainties in paleoclimatic research, although the latter can severely bias the results of proxy record analysis. Here, we introduce a Bayesian approach to represent layer-counted proxy records – such as ice cores, sediments, corals, or tree rings – as sequences of probability distributions on absolute, error-free time axes. The method accounts for both proxy measurement errors and uncertainties arising from layer-counting-based dating of the records. An application to oxygen isotope ratios from the North Greenland Ice Core Project (NGRIP) record reveals that the counting errors, although seemingly small, lead to substantial uncertainties in the final representation of the oxygen isotope ratios. In particular, for the older parts of the NGRIP record, our results show that the total uncertainty originating from dating errors has been seriously underestimated. Our method is next applied to deriving the overall uncertainties of the Suigetsu radiocarbon comparison curve, which was recently obtained from varved sediment cores at Lake Suigetsu, Japan. This curve provides the only terrestrial radiocarbon comparison for the time interval 12.5–52.8 kyr BP. The uncertainties derived here can be readily employed to obtain complete error estimates for arbitrary radiometrically dated proxy records of this recent part of the last glacial interval

Theoretical and paleoclimatic evidence for abrupt transitions in the Earth system

Specific components of the Earth system may abruptly change their state in response to gradual changes in forcing. This possibility has attracted great scientific interest in recent years, and has been recognized as one of the greatest threats associated with anthropogenic climate change. Examples of such components, called tipping elements, include the Atlantic Meridional Overturning Circulation, the polar ice sheets, the Amazon rainforest, as well as the tropical monsoon systems. The mathematical language to describe abrupt climatic transitions is mainly based on the theory of nonlinear dynamical systems and, in particular, on their bifurcations. Applications of this theory to nonautonomous and stochastically forced systems are a very active field of climate research. The empirical evidence that abrupt transitions have indeed occurred in the past stems exclusively from paleoclimate proxy records. In this review, we explain the basic theory needed to describe critical transitions, summarize the proxy evidence for past abrupt climate transitions in different parts of the Earth system, and examine some candidates for future abrupt transitions in response to ongoing anthropogenic forcing. Predicting such transitions remains difficult and is subject to large uncertainties. Substantial improvements in our understanding of the nonlinear mechanisms underlying abrupt transitions of Earth system components are needed. We argue that such an improved understanding requires combining insights from (a) paleoclimatic records; (b) simulations using a hierarchy of models, from conceptual to comprehensive ones; and (c) time series analysis of recent observation-based data that encode the dynamics of the present-day Earth system components that are potentially prone to tipping

Hypermethylation of DNA Methylation Markers in Non-Cirrhotic Hepatocellular Carcinoma

Aberrant DNA methylation changes have been reported to be associated with carcinogenesis in cirrhotic HCC, but DNA methylation patterns for these non-cirrhotic HCC cases were not examined. Therefore, we sought to investigate DNA methylation changes on non-cirrhotic HCC using reported promising DNA methylation markers (DMMs), including HOXA1, CLEC11A, AK055957, and TSPYL5, on 146 liver tissues using quantitative methylation-specific PCR and methylated DNA sequencing. We observed a high frequency of aberrant methylation changes in the four DMMs through both techniques in non-cirrhotic HCC compared to cirrhosis, hepatitis, and benign lesions (p &lt; 0.05), suggesting that hypermethylation of these DMMs is specific to non-cirrhotic HCC development. Also, the combination of the four DMMs exhibited 78% sensitivity at 80% specificity with an AUC of 0.85 in discriminating non-cirrhotic HCC from hepatitis and benign lesions. In addition, HOXA1 showed a higher aberrant methylation percentage in non-cirrhotic HCC compared to cirrhotic HCC (43.3% versus 13.3%, p = 0.039), which was confirmed using multivariate linear regression (p &lt; 0.05). In summary, we identified aberrant hypermethylation changes in HOXA1, CLEC11A, AK055957, and TSPYL5 in non-cirrhotic HCC tissues compared to cirrhosis, hepatitis, and benign lesions, providing information that could be used as potentially detectable biomarkers for these unusual HCC cases in clinical practice.</p

Conditional diffusion models for downscaling & bias correction of Earth system model precipitation

Climate change exacerbates extreme weather events like heavy rainfall and flooding. As these events cause severe losses of property and lives, accurate high-resolution simulation of precipitation is imperative. However, existing Earth System Models (ESMs) struggle with resolving small-scale dynamics and suffer from biases, especially for extreme events. Traditional statistical bias correction and downscaling methods fall short in improving spatial structure, while recent deep learning methods lack controllability over the output and suffer from unstable training. Here, we propose a novel machine learning framework for simultaneous bias correction and downscaling. We train a generative diffusion model in a supervised way purely on observational data. We map observational and ESM data to a shared embedding space, where both are unbiased towards each other and train a conditional diffusion model to reverse the mapping. Our method can be used to correct any ESM field, as the training is independent of the ESM. Our approach ensures statistical fidelity, preserves large-scale spatial patterns and outperforms existing methods especially regarding extreme events and small-scale spatial features that are crucial for impact assessments

A complete representation of uncertainties in layer-counted paleoclimatic archives

Abstract. Accurate time series representation of paleoclimatic proxy records is challenging because such records involve dating errors in addition to proxy measurement errors. Rigorous attention is rarely given to age uncertainties in paleoclimatic research, although the latter can severely bias the results of proxy record analysis. Here, we introduce a Bayesian approach to represent layer-counted proxy records – such as ice cores, sediments, corals or tree rings – as sequences of probability distributions on absolute, error-free time axes. The method accounts for both proxy measurement errors and uncertainties arising from layer-counting–based dating of the records. An application to oxygen isotope ratios from the North Greenland Ice Core Project (NGRIP) record reveals that the counting errors, although seemingly small, lead to substantial uncertainties in the final representation of the oxygen isotope ratios. In particular, for the older parts of the NGRIP record, our results show that the total uncertainty originating from dating errors has been seriously underestimated. Our method is next applied to deriving the overall uncertainties of the Suigetsu radiocarbon calibration curve, which was recently obtained from varved sediment cores at Lake Suigetsu, Japan. This curve provides the only terrestrial radiocarbon calibration for the time interval 12.5–52.8 kyr BP. The uncertainties derived here can be readily employed to obtain complete error estimates for arbitrary radiometrically dated proxy records of this recent part of the last glacial interval. </jats:p

Core Outcomes for Colorectal Cancer Surgery: A Consensus Study

Background: Colorectal cancer (CRC) is a major cause of worldwide morbidity and mortality. Surgical treatment is common, and there is a great need to improve the delivery of such care. The gold standard for evaluating surgery is within well-designed randomized controlled trials (RCTs); however, the impact of RCTs is diminished by a lack of coordinated outcome measurement and reporting. A solution to these issues is to develop an agreed standard “core” set of outcomes to be measured in all trials to facilitate cross-study comparisons, meta-analysis, and minimize outcome reporting bias. This study defines a core outcome set for CRC surgery. Methods and Findings: The scope of this COS includes clinical effectiveness trials of surgical interventions for colorectal cancer. Excluded were nonsurgical oncological interventions. Potential outcomes of importance to patients and professionals were identified through systematic literature reviews and patient interviews. All outcomes were transcribed verbatim and categorized into domains by two independent researchers. This informed a questionnaire survey that asked stakeholders (patients and professionals) from United Kingdom CRC centers to rate the importance of each domain. Respondents were resurveyed following group feedback (Delphi methods). Outcomes rated as less important were discarded after each survey round according to predefined criteria, and remaining outcomes were considered at three consensus meetings; two involving international professionals and a separate one with patients. A modified nominal group technique was used to gain the final consensus. Data sources identified 1,216 outcomes of CRC surgery that informed a 91 domain questionnaire. First round questionnaires were returned from 63 out of 81 (78%) centers, including 90 professionals, and 97 out of 267 (35%) patients. Second round response rates were high for all stakeholders (>80%). Analysis of responses lead to 45 and 23 outcome domains being retained after the first and second surveys, respectively. Consensus meetings generated agreement on a 12 domain COS. This constituted five perioperative outcome domains (including anastomotic leak), four quality of life outcome domains (including fecal urgency and incontinence), and three oncological outcome domains (including long-term survival). Conclusion: This study used robust consensus methodology to develop a core outcome set for use in colorectal cancer surgical trials. It is now necessary to validate the use of this set in research practice

Inverse stochastic-dynamic models for high-resolution Greenland ice core records

Proxy records from Greenland ice cores have been studied for several decades, yet many open questions remain regarding the climate variability encoded therein. Here, we use a Bayesian framework for inferring inverse, stochastic–dynamic models from δ¹⁸O and dust records of unprecedented, subdecadal temporal resolution. The records stem from the North Greenland Ice Core Project (NGRIP), and we focus on the time interval 59–22 ka b2k. Our model reproduces the dynamical characteristics of both the δ¹⁸O and dust proxy records, including the millennial-scale Dansgaard–Oeschger variability, as well as statistical properties such as probability density functions, waiting times and power spectra, with no need for any external forcing. The crucial ingredients for capturing these properties are (i) high-resolution training data, (ii) cubic drift terms, (iii) nonlinear coupling terms between the δ¹⁸O and dust time series, and (iv) non-Markovian contributions that represent short-term memory effects

Better governance starts with better words: why responsible human tissue research demands a change of language

The rise of precision medicine has led to an unprecedented focus on human biological material in biomedical research. In addition, rapid advances in stem cell technology, regenerative medicine and synthetic biology are leading to more complex human tissue structures and new applications with tremendous potential for medicine. While promising, these developments also raise several ethical and practical challenges which have been the subject of extensive academic debate. These debates have led to increasing calls for longitudinal governance arrangements between tissue providers and biobanks that go beyond the initial moment of obtaining consent, such as closer involvement of tissue providers in what happens to their tissue, and more active participatory approaches to the governance of biobanks. However, in spite of these calls, such measures are being adopted slowly in practice, and there remains a strong tendency to focus on the consent procedure as the tool for addressing the ethical challenges of contemporary biobanking. In this paper, we argue that one of the barriers to this transition is the dominant language pervading the field of human tissue research, in which the provision of tissue is phrased as a ‘donation’ or ‘gift’, and tissue providers are referred to as ‘donors’. Because of the performative qualities of language, the effect of using ‘donation’ and ‘donor’ shapes a professional culture in which biobank participants are perceived as passive providers of tissue free from further considerations or entitlements. This hampers the kind of participatory approaches to governance that are deemed necessary to adequately address the ethical challenges currently faced in human tissue research. Rather than reinforcing this idea through language, we need to pave the way for the kind of participatory approaches to governance that are being extensively argued for by starting with the appropriate terminology

Dansgaard–Oeschger-like events of the penultimate climate cycle: the loess point of view

The global character of the millennial-scale climate variability associated with the Dansgaard–Oeschger (DO) events in Greenland has been well-established for the last glacial cycle. Mainly due to the sparsity of reliable data, however, the spatial coherence of corresponding variability during the penultimate cycle is less clear. New investigations of European loess records from Marine Isotope Stage (MIS) 6 reveal the occurrence of alternating loess intervals and paleosols (incipient soil horizons), similar to those from the last climatic cycle. These paleosols are correlated, based on their stratigraphical position and numbers as well as available optically stimulated luminescence (OSL) dates, with interstadials described in various Northern Hemisphere records and in GLt_syn, the synthetic 800 kyr record of Greenland ice core δ18O. Therefore, referring to the interstadials described in the record of the last climate cycle in European loess sequences, the four MIS 6 interstadials can confidently be interpreted as DO-like events of the penultimate climate cycle. Six more interstadials are identified from proxy measurements performed on the same interval, leading to a total of 10 interstadials with a DO-like event status. The statistical similarity between the millennial-scale loess–paleosol oscillations during the last and penultimate climate cycle provides direct empirical evidence that the cycles of the penultimate cycle are indeed of the same nature as the DO cycles originally discovered for the last glacial cycle. Our results thus imply that their underlying cause and global imprint were characteristic of at least the last two climate cycles