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Abstract This study uses complex network analysis to investigate global stock market co-movement during the black swan event of the Coronavirus Disease 2019 (COVID-19) pandemic. We propose a novel method for calculating stock price index correlations based on open-high-low-close (OHLC) data. More intraday information can be utilized compared with the widely used return-based method. Hypothesis testing was used to select the edges incorporated in the network to avoid a rigid setting of the artificial threshold. The topologies of the global stock market complex network constructed using 70 important global stock price indices before (2017–2019) and after (2020–2022) the COVID-19 outbreak were examined. The evidence shows that the degree centrality of the OHLC data-based global stock price index complex network has better power-law distribution characteristics than a return-based network. The global stock market co-movement characteristics are revealed, and the financial centers of the developed, emerging, and frontier markets are identified. Using centrality indicators, we also illustrate changes in the importance of individual stock price indices during the COVID-19 pandemic. Based on these findings, we provide suggestions for investors and policy regulators to improve their international portfolios and strengthen their national financial risk preparedness.

Observation-based data reconstructions of global surface ocean carbonate system variables play an essential role in monitoring the recent status of ocean carbon uptake and ocean acidification, as well as their impacts on marine organisms and ecosystems. So far, ongoing efforts are directed towards exploring new approaches to describe the complete marine carbonate system and to better recover its fine-scale features. In this respect, our research activities within the Copernicus Marine Environment Monitoring Service (CMEMS) aim to develop a sustainable production chain of observation-derived global ocean carbonate system datasets at high space–time resolutions. As the start of the long-term objective, this study introduces a new global 0.25∘ monthly reconstruction, namely CMEMS-LSCE (Laboratoire des Sciences du Climat et de l'Environnement) for the period 1985–2021. The CMEMS-LSCE reconstruction derives datasets of six carbonate system variables, including surface ocean partial pressure of CO2 (pCO2), total alkalinity (AT), total dissolved inorganic carbon (CT), surface ocean pH, and saturation states with respect to aragonite (Ωar) and calcite (Ωca). Reconstructing pCO2 relies on an ensemble of neural network models mapping gridded observation-based data provided by the Surface Ocean CO2 ATlas (SOCAT). Surface ocean AT is estimated with a multiple-linear-regression approach, and the remaining carbonate variables are resolved by CO2 system speciation given the reconstructed pCO2 and AT; 1σ uncertainty associated with these estimates is also provided. Here, σ stands for either the ensemble standard deviation of pCO2 estimates or the total uncertainty for each of the five other variables propagated through the processing chain with input data uncertainty. We demonstrate that the 0.25∘ resolution pCO2 product outperforms a coarser spatial resolution (1∘) thanks to higher data coverage nearshore and a better description of horizontal and temporal variations in pCO2 across diverse ocean basins, particularly in the coastal–open-ocean continuum. Product qualification with observation-based data confirms reliable reconstructions with root-mean-square deviation from observations of less than 8 %, 4 %, and 1 % relative to the global mean of pCO2, AT (CT), and pH. The global average 1σ uncertainty is below 5 % and 8 % for pCO2 and Ωar (Ωca), 2 % for AT and CT, and 0.4 % for pH relative to their global mean values. Both model–observation misfit and model uncertainty indicate that coastal data reproduction still needs further improvement, wherein high temporal and horizontal gradients of carbonate variables and representative uncertainty from data sampling would be taken into account as a priority. This study also presents a potential use case of the CMEMS-LSCE carbonate data product in tracking the recent state of ocean acidification. The data associated with this study are available at https://doi.org/10.14768/a2f0891b-763a-49e9-af1b-78ed78b16982 (Chau et al., 2023).

Abstract The use of peripheral blood (PB) or bone marrow (BM) stem cells graft in haploidentical hematopoietic stem cell transplantation with post-transplant cyclophosphamide (PTCy) for graft-versus-host disease (GVHD) prophylaxis remains controversial. Moreover, the value of adding anti-thymoglobulin (ATG) to PTCy is unknown. A total of 1344 adult patients received an unmanipulated haploidentical transplant at 37 centers from 2012 to 2019 for hematologic malignancy. We compared the outcomes of patients according to the type of graft, using a propensity score analysis. In total population, grade II–IV and III–IV acute GVHD (aGVHD) were lower with BM than with PB. Grade III–IV aGVHD was lower with BM than with PB + ATG. All outcomes were similar in PB and PB + ATG groups. Then, in total population, adding ATG does not benefit the procedure. In acute leukemia, myelodysplastic syndrome and myeloproliferative syndrome (AL-MDS-MPS) subgroup receiving non-myeloablative conditioning, risk of relapse was twice greater with BM than with PB (51 vs. 22%, respectively). Conversely, risk of aGVHD was greater with PB (38% for aGVHD II–IV; 16% for aGVHD III–IV) than with BM (28% for aGVHD II–IV; 8% for aGVHD III–IV). In this subgroup with intensified conditioning regimen, risk of relapse became similar with PB and BM but risk of aGVHD III–IV remained higher with PB than with BM graft (HR = 2.0; range [1.17–3.43], p = 0.012).

Abstract Emissions from fossil fuel exploitation are a leading contributor to global anthropogenic methane emissions, but are highly uncertain. The lack of reliable estimates hinders monitoring of the progress on pledges towards methane reductions. Here we analyze methane emissions from exploitation of coal, oil and gas for major producing nations across a suite of bottom-up inventories and global inversions. Larger disagreement in emissions exists for the oil/gas sector across the inventories compared to coal, arising mostly from disparate data sources for emission factors. Moreover, emissions reported to the United Nations Framework Convention on Climate Change are lower than other bottom-up and inversion estimates, with many countries lacking reporting in the past decades. Finally, comparison with previous global inversions, revealed a strong influence of the prior inventory on the inferred sub-sectoral emissions magnitude. This study highlights the need to improve consensus on the methodological inputs among the bottom-up inventories in order to obtain more consistent inverse modelling results at the sub-sectoral level.

Quantifying both soil organic carbon (SOC) and soil inorganic carbon (SIC) is essential to understand carbon (C) dynamics and to assess the atmospheric C sequestration potential in calcareous soils. The procedures usually used to quantify SOC and SIC involve pretreatments (decarbonation, carbonate removal) and calculations of the difference between C contents estimated by elemental analysis on raw and pretreated aliquots. These procedures lead to analytical bias associated with pretreatments, measurement deviations associated with sample heterogeneity, and cumulative errors associated with calculations. The Rock-Eval® analysis is a ramped thermal analysis that has been used in soil sciences since the 2000s, consisting of pyrolysis of the sample followed by oxidation of the residue. A single Rock-Eval® analysis on non-pretreated aliquots provides two parameters estimating the organic (TOC) and inorganic (MinC) C contents of the samples. Nevertheless, the Rock-Eval® protocol was standardised in the 1970s by IFP Energies Nouvelles for studying oil-bearing rocks and is thus not perfectly suited for soil study. Previous studies have suggested statistical corrections of the standard parameters to improve their estimations of C contents assessed by elemental analysis, but only a few of them have focused on the estimation of inorganic C content using the MinC parameter. Moreover, none of them have suggested adjustments to the standard Rock-Eval® protocol. This study proposes to adapt this protocol to optimise SOC and SIC quantifications in soil samples. Comparisons between SOC and SIC quantifications by elemental analysis and by Rock-Eval®, with and without statistical corrections of the standard TOC and MinC parameters, were carried out on 30 agricultural topsoils with a wide range of SOC and SIC contents. The results show that the standard Rock-Eval® protocol can properly estimate SOC contents once the TOC parameter is corrected. However, it cannot achieve a complete thermal breakdown of SIC amounts > 4 mg, leading to an underestimation of high SIC contents by the MinC parameter, even after correcting for this. Thus, the final oxidation isotherm is extended to 7 min to complete the thermal breakdown of SIC before the end of the analysis. This work is a methodological step to measure SOC and SIC contents in a single analytical run on a non-pretreated aliquot. More work is needed (i) on a wider range of soil samples with differing land use and other forms of carbonate mineral and sampling depths and (ii) to avoid the use of statistical corrections of the TOC and MinC parameters.

In this paper, we conducted an empirical investigation of the realized volatility of cryptocurrencies using an econometric approach. This work’s two main characteristics are: (i) the realized volatility to be forecast filters jumps, and (ii) the benefit of using various historical/implied volatility indices from brokers as exogenous variables was explicitly considered. We feature a jump-robust extension of the REGARCH-MIDAS-X model incorporating realized beta GARCH processes and MIDAS filters with monthly, daily, and hourly components. First, we estimated six jump-robust estimators of realized volatility for Bitcoin and Ethereum that were retained as the dependent variable. Second, we inserted ten Bitcoin and Ethereum volatility indices gathered from various exchanges as an exogenous variable, each at a time. Third, we explored their forecasting ability based on the MSE and QLIKE statistics. Our sample spanned the period from May 2018 to January 2023. The main result featured the best predictors among the volatility indices for Bitcoin and Ethereum derived from 30-day implied volatility. The significance of the findings could mostly be attributable to the ability of our new model to incorporate financial and technological variables directly into the specification of the Bitcoin and Ethereum volatility dynamics.

Sea turtles are an iconic group of marine megafauna that have been exposed to multiple anthropogenic threats across their different life stages, especially in the past decades. This has resulted in population declines, and consequently many sea turtle populations are now classified as threatened or endangered globally. Although some populations of sea turtles worldwide are showing early signs of recovery, many still face fundamental threats. This is problematic since sea turtles have important ecological roles. To encourage informed conservation planning and direct future research, we surveyed experts to identify the key contemporary threats (climate change, direct take, fisheries, pollution, disease, predation, and coastal and marine development) faced by sea turtles. Using the survey results and current literature, we also outline knowledge gaps in our understanding of the impact of these threats and how targeted future research, often involving emerging technologies, could close those gaps.

Abstract In this monocentric prospective study, the influence on long‐term outcomes of peripheral blood levels of monocytic‐myeloid‐derived suppressive cells (M‐MDSC) was investigated in 56 patients with acute leukemia (myeloid n = 47; lymphoid n = 9) before and after (Days+60/+90) allogeneic hematopoietic stem cell transplantation (Allo‐HSCT). A risk of relapse was found to be associated with a level of pregraft M‐MDSC above 1.4% by ROC curve analysis. In multivariate analysis, this threshold retained a strong statistical significance (HR: 5.94 [2.09–16.87], p = 0.001). Considering only the group of patients who were in complete remission prior to Allo‐HSCT (n = 44), a significant prediction of relapse was found to be associated, in multivariate analysis, with a level of pregraft M‐MDSC above 1.4% (HR: 55.01 [14.95–202.37], p

A 66-year-old man with a history of catheter ablation for atrial fibrillation presented with purulent cardiac tamponade, revealing an atrio-oesophageal fistula. He underwent successful endoscopic management. A few days later, the patient fell into a sudden coma due to multiple cerebral air embolisms, resulting from a fistula between the esophagus and the right superior pulmonary vein.

This research consolidates our group’s advances in developing a therapeutic dressing with innovative enzymatic debridement, focusing on the physicochemical and in vitro biological properties of papain immobilized in wet oxidized bacterial cellulose (OxBC–Papain) dressing. OxBC membranes were produced with Komagataeibacter hansenii oxidized with NaIO4, and papain was immobilized on them. They were characterized in terms of enzyme stability (over 100 days), absorption capacity, water vapor transmission (WVT), hemocompatibility, cytotoxicity, and cell adhesion. The OxBC–Papain membrane showed 68.5% proteolytic activity after 100 days, demonstrating the benefit of using the OxBC wet membrane for papain stability. It had a WVT rate of 678 g/m2·24 h and cell viability of 99% and 86% for L929 and HaCat cells, respectively. The membranes exhibited non-hemolytic behavior and maintained 26% clotting capacity after 1 h. The wet OxBC–Papain membrane shows significant potential as a natural biomolecule-based therapeutic dressing for wound care, offering efficient debridement, moisture maintenance, exudate absorption, gas exchange, and hemostasis without cytotoxic effects or cell adhesion to the dressing. Further research, especially using in vivo models, is needed to assess its efficacy in inducing epithelialization. This study advances stomatherapy knowledge, providing a cost-effective solution for enzymatic debridement in healthcare.

Abstract The Surface Ocean CO2 Atlas (SOCAT) of CO2 fugacity (fCO2) observations is a key resource supporting annual assessments of CO2 uptake by the ocean and its side effects on the marine ecosystem. SOCAT data are usually released with a lag of up to 1.5 years which hampers timely quantification of recent variations of carbon fluxes between the Earth System components, not only with the ocean. This study uses a statistical ensemble approach to analyze fCO2 with a latency of one month only based on the previous SOCAT release and a series of predictors. Results indicate a modest degradation in a retrospective prediction test for 2021–2022. The generated fCO2 and fluxes for January–August 2023 show a progressive reduction in the Equatorial Pacific source following the La Niña retreat. A breaking‐record decrease in the northeastern Atlantic CO2 sink has been diagnosed on account of the marine heatwave event in June 2023.

Abstract Congenital erythropoietic porphyria (CEP), or Gunther disease, is a rare genetic disease responsible for severe dermatologic, hepatic and/or haematological damages related to the deficient activity of the uroporphyrinogen III synthase. Allogeneic stem cell transplantation (Allo‐SCT) represents the only curative treatment and few allotransplanted cases have been reported in children but not in adults. Here we report for the first time the successful cure of a 46‐year old man with CEP with a 5‐year follow‐up after Allo‐SCT.

Particle size fractionation enables a better understanding of soil organic carbon (C) dynamics since it separates fractions that differ in composition, residence time and function. However, this method is time-consuming and tedious; thus, its use has been greatly limited. Our objective was to evaluate the ability of an existing soil spectral library (SSL) from different regions of West Africa to predict the C amount in the fractions (gC kg−1 soil) of the samples in a new target set from Benin.The SSL included 181 samples from five countries, and the target set included 94 samples (depth ≤ 40 cm), most of which were coarse-textured; near-infrared reflectance (NIR) spectra were collected for 2 mm sieved samples (non-fractionated samples). The predicted variables were the C amounts in the non-fractionated soil and in the < 20, 20–50, and > 50 µm fractions (F50, respectively). Different methods were tested to optimize the predictions: (i) SSL enrichment with 10 or 15 samples selected from the target set (spiking) and replicated six times (i.e. extra-weighted); (ii) locally weighted (local) partial least squares regression (PLSR), which is calibration by the spectral neighbours with the highest weights attributed to closest neighbours, and was compared to “global” (i.e., common) PLSR, where all calibration samples equally contribute; and (iii) spectrum pretreatments (e.g., smoothing, centring, derivatization). In addition, the intermediate precision of the conventional data (standard error of laboratory; SELint) was estimated through triplicate fractionation of three samples carried out by three operators (one per replicate).When the SSL alone was used for calibration, the predictions were inaccurate for the C amounts in the non-fractionated soil and in F50, with minimal benefit from the local PLSR over the global PLSR in general. For the non-fractionated soil, F50, the ratios of performance to the interquartile range in the validation set, RPIQVAL, were 1.6–1.8, 1.6–1.7, 1.9 and 1.9–2.1, respectively. Calibration with SSL spiked (i.e., completed with spiking samples) yielded an increase in RPIQVAL from 33 to 56% for the C amount in the non-fractionated soil and F50 (RPIQVAL reached 2.4–2.5, 2.2–2.3, 1.9–2.0 and 2.1–2.3, respectively), and the benefit of local PLSR was still limited. The SELint was based on a few samples and thus only provided a rough estimation; this estimate represented at least 65% of the prediction error for the C amounts in the fractions. Therefore, the SELint needs to be determined more extensively to both improve the model accuracy and refine the interpretation of the predictions based on NIR spectra. This library should be enriched with samples from other sites to represent other soil types.

Endocarditis of cardiac implanted electronic devices is a complex and serious disease. Commensal bacteria of the skin are commonly considered as contamination of blood culture. Herein, the authors report the case of a pacemaker endocarditis with cultures positive for Cutibacterium acnes. These were already found 3 and 6 years ago but not observed during hospitalisation. The PET-scan was of great help in guiding the diagnosis. The management was particularly difficult with 9 leads to extract. A sequential approach in the operating room from endovascular procedure to surgery under cardio-pulmonary bypass was used. A second procedure was necessary to extract a small forgotten foreign body already visible on the preoperative chest X-ray. This experience shows the importance of having a high level of suspicion in case of culture positive for Cutibacterium with intracardiac devices, and of looking for foreign bodies on the preoperative chest X-ray in case of a history of multiple rhythmological procedures.