Search

Abstract Currently in NW Europe little is known about the human response to the extensive cold reversal at the end of the Pleistocene, the Younger Dryas (ca. 12,850 till ca. 11,650 cal BP), mainly due to the poor chronological resolution of the archaeological sites belonging to the Ahrensburgian Culture. Here we present a series of 33 radiocarbon dates performed on the seminal cave site of Remouchamps, situated in the Belgian Meuse basin. Combined with a revision of the available radiocarbon evidence along the southern North Sea basin (Belgium, southern Netherlands, western Germany), it is suggested that the first half of the Younger Dryas, characterized as extremely cold and wet, faced a significant population reduction. Repopulation started around the middle of the Younger Dryas, from ca. 12,200 cal BP onward, probably in response to a slight climatic improvement leading to somewhat warmer summers. This might be considered a prelude to the subsequent population boost of the Early Holocene (Mesolithic).

Abstract Our objective was to capture subgroups of soft-tissue sarcoma (STS) using handcraft and deep radiomics approaches to understand their relationship with histopathology, gene-expression profiles, and metastatic relapse-free survival (MFS). We included all consecutive adults with newly diagnosed locally advanced STS (N = 225, 120 men, median age: 62 years) managed at our sarcoma reference center between 2008 and 2020, with contrast-enhanced baseline MRI. After MRI postprocessing, segmentation, and reproducibility assessment, 175 handcrafted radiomics features (h-RFs) were calculated. Convolutional autoencoder neural network (CAE) and half-supervised CAE (HSCAE) were trained in repeated cross-validation on representative contrast-enhanced slices to extract 1024 deep radiomics features (d-RFs). Gene-expression levels were calculated following RNA sequencing (RNAseq) of 110 untreated samples from the same cohort. Unsupervised classifications based on h-RFs, CAE, HSCAE, and RNAseq were built. The h-RFs, CAE, and HSCAE grouping were not associated with the transcriptomics groups but with prognostic radiological features known to correlate with lower survivals and higher grade and SARCULATOR groups (a validated prognostic clinical-histological nomogram). HSCAE and h-RF groups were also associated with MFS in multivariable Cox regressions. Combining HSCAE and transcriptomics groups significantly improved the prognostic performances compared to each group alone, according to the concordance index. The combined radiomic-transcriptomic group with worse MFS was characterized by the up-regulation of 707 genes and 292 genesets related to inflammation, hypoxia, apoptosis, and cell differentiation. Overall, subgroups of STS identified on pre-treatment MRI using handcrafted and deep radiomics were associated with meaningful clinical, histological, and radiological characteristics, and could strengthen the prognostic value of transcriptomics signatures.

This study presents a multiproxy palaeodemographic perspective by combining radiocarbon dates with counts of archaeological site phases in the western Scheldt basin, spanning from the beginning of the Neolithic to the Early Bronze Age. The results were assessed critically, accounting for differences in research methodology, soil conditions and changes in building traditions. The results indicate a dynamic region characterized by almost continual growth. Moreover, two distinct sub-regions of the basin could be compared, thereby elucidating the sub-regional differences. It is clear that palaeodemographic studies are only feasible when a multiproxy analysis is used on a detailed, highly scrutinized dataset.

Abstract Background Biological studies suggested that the COVID-19 outbreak in France occurred before the first official diagnosis on January 24, 2020. We investigated this controversial topic using a large collection of chest CTs performed throughout French emergency departments within 6 months before the 1st lockdown. Results Overall, 49,311 consecutive patients (median age: 60 years, 23,636/49,311 [47.9%] women) with available chest CT images and reports from 61 emergency departments between September 1, 2020, and March 16, 2020 (day before the 1st French lockdown), were retrospectively included in this multicentre study. In the macroscopic analysis of reports automatically (labelled for presence of ground glass opacities [GGOs], reticulations, and bilateral and subpleural abnormalities), we found a significant breakpoint on February 17, 2020, for the weekly time series with 1, 2 and ≥ 3 of these 4 radiological features, with 146/49,311 (0.3%) patients showing bilateral abnormalities and ground glass opacities (GGOs) from that day. According to radiologists, 22/146 (15.1%) CT images showed typical characteristics of COVID-19, including 4/146 (2.7%) before February 2020. According to hospital records, one patient remained without microbial diagnosis, two patients had proven influenza A and one patient had concomitant influenza A and mycoplasma infection. Conclusion These results suggest that SARS-CoV-2 was not circulating in the areas covered by the 61 emergency departments involved in our study before the official beginning of the COVID-19 outbreak in France. In emergency patients, the strong resemblance among mycoplasma, influenza A and SARS-CoV-2 lung infections on chest CT and the nonspecificity of CT patterns in low prevalence periods is stressed. Critical relevance statement We proposed here an innovative approach to revisit a controversial ‘real’ start of the COVID-19 pandemic in France based on (1) a population-level approach combining text mining, time series analysis and an epidemiological dataset and (2) a patient-level approach with careful retrospective reading of chest CT scans complemented by analysis of samples performed contemporarily to the chest CT. We showed no evidence that SARS-CoV-2 was actively circulating in France before February 2020. Graphical Abstract

Abstract Metabolic elevation in soft-tissue sarcomas (STS), as documented with 18F-Fluorodeoxyglucose positron emission tomography (18F-FDG-PET/CT) has been linked with cell proliferation, higher grade, and lower survivals. However, the recent diagnostic innovations (CINSARC gene-expression signature and tertiary lymphoid structure [TLS]) and therapeutic innovations (immune checkpoint inhibitors [ICIs]) for STS patients underscore the need to re-assess the role of 18F-FDG-PET/CT. Thus, in this correspondence, our objective was to investigate the correlations between STS metabolism as assessed by nuclear imaging, and the immune landscape as estimated by transcriptomics analysis, immunohistochemistry panels, and TLS assessment. Based on a prospective cohort of 85 adult patients with high-grade STS recruited in the NEOSARCOMICS trial (NCT02789384), we identified 3 metabolic groups according to 18F-FDG-PET/CT metrics (metabolic-low [60%], -intermediate [15.3%] and high [24.7%]). We found that T-cells CD8 pathway was significantly enriched in metabolic-high STS. Conversely, several pathways involved in antitumor immune response, cell differentiation and cell cycle, were downregulated in extreme metabolic-low STS. Next, multiplex immunofluorescence showed that densities of CD8+, CD14+, CD45+, CD68+, and c-MAF cells were significantly higher in the metabolic-high group compared to the metabolic-low group. Lastly, no association was found between metabolic group and TLS status. Overall, these results suggest that (i) rapidly proliferating and metabolically active STS can instigate a more robust immune response, thereby attracting immune cells such as T cells and macrophages, and (ii) metabolic activity and TLS could independently influence immune responses.

The grey wolf (Canis lupus) was the first species to give rise to a domestic population, and they remained widespread throughout the last Ice Age when many other large mammal species went extinct. Little is known, however, about the history and possible extinction of past wolf populations or when and where the wolf progenitors of the present-day dog lineage (Canis familiaris) lived1-8. Here we analysed 72 ancient wolf genomes spanning the last 100,000 years from Europe, Siberia and North America. We found that wolf populations were highly connected throughout the Late Pleistocene, with levels of differentiation an order of magnitude lower than they are today. This population connectivity allowed us to detect natural selection across the time series, including rapid fixation of mutations in the gene IFT88 40,000-30,000 years ago. We show that dogs are overall more closely related to ancient wolves from eastern Eurasia than to those from western Eurasia, suggesting a domestication process in the east. However, we also found that dogs in the Near East and Africa derive up to half of their ancestry from a distinct population related to modern southwest Eurasian wolves, reflecting either an independent domestication process or admixture from local wolves. None of the analysed ancient wolf genomes is a direct match for either of these dog ancestries, meaning that the exact progenitor populations remain to be located.

Alveolar soft part sarcoma (ASPS) is an extremely rare and aggressive soft-tissue sarcoma (STS) subtype with poor prognosis and limited response to radiation therapy and chemotherapy. Prompt recognition and referral to sarcoma centers for appropriate management are crucial for patients’ survival. The purpose of this study was to report ASPS pre-treatment imaging features and to examine the existing literature on this topic. Twelve patients (7 women, 5 men—mean age 27.1 ± 10.7 years) were included from our single-center experience. Ultrasonography (US), computed tomography (CT), and magnetic resonance imaging (MRI) available were reviewed according to an analysis grid incorporating features from the latest research on STS. Clinical, histological, and outcome data were collected. MRI was available in 10 patients (83.3%), US in 7 patients (58.3%), and CT in 3 patients (25%). Mean longest tumor diameter was 7.6 ± 2.9 cm, and all tumors were deeply seated. Large peritumoral feeding vessels were systematically found and identified on ultrasonography (7/7), MRI (10/10), and CT (3/3). US revealed a well-defined heterogeneous hypoechoic pattern, with abundant flow signals in all patients (7/7). In all patients, MRI showed mildly high signal intensity (SI) on T1-WI and high SI on T2-WI and peritumoral edema. Moreover, flow-voids (due to arteriosus high-flow) into the peritumoral/intratumoral feeding vessels were detected in the MRI fluid-sensitive sequences of all patients. At baseline, whole-body contrast-enhanced CT revealed metastases in 8/12 (66.7%) patients. A pre-treatment longest diameter > 5 cm was significantly associated with distant metastases at diagnosis (p = 0.01). A maximum diameter > 5 cm represents a risk of metastatic disease at diagnosis (odds ratio = 45.0000 (95% CI: 1.4908—1358.3585), p = 0.0285). In the comprehensive literature review, we found 14 articles (case series or original research) focusing on ASPS imaging, with a total of 151 patients included. Merging our experience with the data from the existing literature, we conclude that the hallmark of ASPS imaging at presentation are the following characteristics: deep location, a slight hyperintense MRI SI on T1-WI and a hyperintense SI on T2-WI, numerous MRI flow voids, high internal vascularization, and large peritumoral feeding vessels.

Abstract Comparative macro-archaeological investigations of the human deep past rely on the availability of unified, quality-checked datasets integrating different layers of observation. Information on the durable and ubiquitous record of Paleolithic stone artefacts and technological choices are especially pertinent to this endeavour. We here present a large expert-sourced collaborative dataset for the study of stone tool technology and artefact shape evolution across Europe between ~15.000 and 11.000 years before present. The dataset contains a compendium of key sites from the study period, and data on lithic technology and toolkit composition at the level of the cultural taxa represented by those sites. The dataset further encompasses 2D shapes of selected lithic artefact groups (armatures, endscrapers, and borers/perforators) shared between cultural taxa. These data offer novel possibilities to explore between-regional patterns of material culture change to reveal scale-dependent processes of long-term technological evolution in mobile hunter-gatherer societies at the end of the Pleistocene. Our dataset facilitates state-of-the-art quantitative analyses and showcases the benefits of collaborative data collation and synthesis.

Archaeological systematics, together with spatial and chronological information, are commonly used to infer cultural evolutionary dynamics in the past. For the study of the Palaeolithic, and particularly the European Final Palaeolithic and earliest Mesolithic, proposed changes in material culture are often interpreted as reflecting historical processes, migration, or cultural adaptation to climate change and resource availability. Yet, cultural taxonomic practice is known to be variable across research history and academic traditions, and few large-scale replicable analyses across such traditions have been undertaken. Drawing on recent developments in computational archaeology, we here present a data-driven assessment of the existing Final Palaeolithic/earliest Mesolithic cultural taxonomy in Europe. Our dataset consists of a large expert-sourced compendium of key sites, lithic toolkit composition, blade and bladelet production technology, as well as lithic armatures. The dataset comprises 16 regions and 86 individually named archaeological taxa ('cultures'), covering the period between ca. 15,000 and 11,000 years ago (cal BP). Using these data, we use geometric morphometric and multivariate statistical techniques to explore to what extent the dynamics observed in different lithic data domains (toolkits, technologies, armature shapes) correspond to each other and to the culture-historical relations of taxonomic units implied by traditional naming practice. Our analyses support the widespread conception that some dimensions of material culture became more diverse towards the end of the Pleistocene and the very beginning of the Holocene. At the same time, cultural taxonomic unit coherence and efficacy appear variable, leading us to explore potential biases introduced by regional research traditions, inter-analyst variation, and the role of disjunct macroevolutionary processes. In discussing the implications of these findings for narratives of cultural change and diversification across the Pleistocene-Holocene transition, we emphasize the increasing need for cooperative research and systematic archaeological analyses that reach across research traditions.

Spondylodiscitis is defined by infectious conditions involving the vertebral column. The incidence of the disease has constantly increased over the last decades. Imaging plays a key role in each phase of the disease. Indeed, radiological tools are fundamental in (i) the initial diagnostic recognition of spondylodiscitis, (ii) the differentiation against inflammatory, degenerative, or calcific etiologies, (iii) the disease staging, as well as (iv) to provide clues to orient towards the microorganisms involved. This latter aim can be achieved with a mini-invasive procedure (e.g., CT-guided biopsy) or can be non-invasively supposed by the analysis of the CT, positron emission tomography (PET) CT, or MRI features displayed. Hence, this comprehensive review aims to summarize all the multimodality imaging features of spondylodiscitis. This, with the goal of serving as a reference for Physicians (infectious disease specialists, spine surgeons, radiologists) involved in the care of these patients. Nonetheless, this review article may offer starting points for future research articles.

E. coli O157:H7 is a known Shiga toxin-producing Escherichia coli (STEC), causing foodborne disease globally. Cattle are the main reservoir and consumption of beef and beef products contaminated with E. coli O157:H7 is an important source of STEC infections in humans. To emphasize the cattle-to-human transmission through the consumption of contaminated beef in Bishoftu, Ethiopia, whole-genome sequencing (WGS) was performed on E. coli O157 strains isolated from three sources (cattle, beef, and humans). Forty-four E. coli O157:H7 isolates originating from 23 cattle rectal contents, three cattle hides, five beef carcasses, seven beef cuts at retail shops, and six human stools in Bishoftu between June 2017 and May 2019 were included. This study identified six clusters of closely related E. coli O157:H7 isolates based on core genome multilocus sequence typing (cgMLST) by targeting 2513 loci. A genetic linkage was observed among the isolate genomes from the cattle rectal contents, cattle hides, beef carcasses at slaughterhouses, beef at retail shops, and human stool within a time frame of 20 months. All the strains carried practically the same repertoire of virulence genes except for the stx2 gene, which was present in all but eight of the closely related isolates. All the strains carried the mdfA gene, encoding for the MdfA multi-drug efflux pump. CgMLST analysis revealed genetically linked E. coli O157:H7 isolates circulating in the area, with a potential transmission from cattle to humans through the consumption of contaminated beef and beef products.

A 68-year-old man with a medical history of hypertension was admitted to the emergency department for diffuse abdominal pain preceded by bloody diarrhea. Upon admission, neurological examination was normal, but he suddenly developed a left-sided hemiparesis. After a normal brain computed tomography, intravenous thrombolysis was administered for a suspicion of ischemic stroke. In the first laboratory investigations, hemoglobin was 16.9 g/dL, platelets 121 × 109/L (150–450), and serum creatinine 1.17 mg/dL. By the second hospital day, the platelet level dropped to 79 × 109/L, with haptoglobin at 0.12 g/L, 3% schistocytes, and normal ADAMTS13 activity (57%). Serum creatinine increased to 1.84 mg/dL with oliguria. The suspicion of thrombotic microangiopathy was supported by the identification of Shiga toxin genes stx1 and stx2 on a rectal swab and the isolation of an eaeA-negative Shiga toxin-producing E. coli O113:H4. The patient presented a generalized tonic-clonic seizure, and orotracheal intubation was required for decreased consciousness. Plasma exchange therapy was started, and eculizumab was given 6 days after symptoms onset. Brain magnetic resonance imaging (MRI) on day 13 showed symmetric hyperintensities within basal ganglia that disappeared on a second MRI on day 37. At 2-month follow-up, the patient had made a complete neurological and renal recovery and eculizumab therapy was stopped.

Abstract Whole genome sequencing (WGS) enables detailed characterization of bacteria at single nucleotide resolution. It provides data about acquired resistance genes and mutations leading to resistance. Although WGS is becoming an essential tool to predict resistance patterns accurately, comparing genotype to phenotype with WGS is still in its infancy. Additional data and validation are needed. In this retrospective study, we analysed 234 E. coli isolates from positive blood cultures using WGS as well as microdilution for 11 clinically relevant antibiotics, to compare the two techniques. We performed whole genome sequencing analyses on 234 blood culture isolates (genotype) to detect acquired antibiotic resistance. Minimal inhibitory concentrations (MIC) for E. coli were performed for amoxicillin, cefepime, cefotaxime, ceftazidime, meropenem, amoxicillin/clavulanic acid, piperacillin/tazobactam, amikacin, gentamicin, tobramycin, and ciprofloxacin, using the ISO 20776-1 standard broth microdilution method as recommended by EUCAST (phenotype). We then compared the two methods for statistical ‘agreement’. A perfect (100%) categorical agreement between genotype and phenotype was observed for gentamicin and meropenem. However, no resistance to meropenem was observed. A high categorical agreement (> 95%) was observed for amoxicillin, cefepime, cefotaxime, ceftazidime, amikacin, and tobramycin. A categorical agreement lower than 95% was observed for amoxicillin/clavulanic acid, piperacillin/tazobactam, and ciprofloxacin. Most discrepancies occurred in isolates with MICs within ± 1 doubling dilution of the breakpoint and 22.73% of the major errors were samples that tested phenotypically susceptible at higher antibiotic exposure and were therefore considered as ‘not resistant’. This study shows that WGS can be used as a valuable tool to predict phenotypic resistance against most of the clinically relevant antibiotics used for the treatment of E. coli bloodstream infections.

Abstract Soft‐tissue sarcomas (STS) represent a group of rare and heterogeneous tumors associated with several challenges, including incorrect or late diagnosis, the lack of clinical expertise, and limited therapeutic options. Digital pathology and radiomics represent transformative technologies that appear promising for improving the accuracy of cancer diagnosis, characterization and monitoring. Herein, we review the potential role of the application of digital pathology and radiomics in managing patients with STS. We have particularly described the main results and the limits of the studies using radiomics to refine diagnosis or predict the outcome of patients with soft‐tissue sarcomas. We also discussed the current limitation of implementing radiomics in routine settings. Standard management approaches for STS have not improved since the early 1970s. Immunotherapy has revolutionized cancer treatment; nonetheless, immuno‐oncology agents have not yet been approved for patients with STS. However, several lines of evidence indicate that immunotherapy may represent an efficient therapeutic strategy for this group of diseases. Thus, we emphasized the remarkable potential of immunotherapy in sarcoma treatment by focusing on recent data regarding the immune landscape of these tumors. We have particularly emphasized the fact that the development of immunotherapy for sarcomas is not an aspect of histology (except for alveolar soft‐part sarcoma) but rather that of the tumor microenvironment. Future studies investigating immunotherapy strategies in sarcomas should incorporate at least the presence of tertiary lymphoid structures as a stratification factor in their design, besides including a strong translational program that will allow for a better understanding of the determinants involved in sensitivity and treatment resistance to immune‐oncology agents.

Pathogenic E. coli strains can be classified into two major groups, based on the presence of specific virulence factors: extraintestinal pathogenic E. coli (ExPEC) and diarrheagenic E. coli (DEC). Several case reports describe that DEC can cause bloodstream infections in some rare cases. This mainly concerns a few specific sequence types that express virulence factors from both ExPEC and DEC. In this study, we retrospectively analysed 234 E. coli blood isolates with whole genome sequencing (WGS). WGS was performed on an Illumina NovaSeq6000. Genotyping was performed using BioNumerics software. The presence of genes was determined with a minimum percentage sequence identity (ID) threshold of 95% and a minimum length for sequence coverage of 95%. Three of the 234 (1.28%) isolates were defined as DEC, 182 (77.78%) as ExPEC, and 49 (20.94%) did not carry pathotype-associated virulence genes. We identified 112 different virulence genes, 48 O-antigens, and 28 H-antigens 82 STs, among the 234 analyzed isolates. ST131 and ST88 were related to healthcare-associated infections. This study provides insight into the prevalence of virulence factors in a large set of E. coli blood isolates from the UZ Brussel. It illustrates high diversity in virulence profiles and highlights the potential of DEC to carry virulence factors associated with extraintestinal infections, making it possible for unusual pathotypes to invade and survive in the bloodstream causing bacteraemia. Diarrheagenic strains causing bacteremia are rare and presently underreported, but modern sequencing techniques will better underscore their importance.

IntroductionShiga toxin-producing Escherichia coli (STEC) is a gastrointestinal pathogen causing foodborne outbreaks. Whole Genome Sequencing (WGS) in STEC surveillance holds promise in outbreak prevention and confinement, in broadening STEC epidemiology and in contributing to risk assessment and source attribution. However, despite international recommendations, WGS is often restricted to assist outbreak investigation and is not yet fully implemented in food safety surveillance across all European countries, in contrast to for example in the United States.MethodsIn this study, WGS was retrospectively applied to isolates collected within the context of Belgian food safety surveillance and combined with data from clinical isolates to evaluate its benefits. A cross-sector WGS-based collection of 754 strains from 1998 to 2020 was analyzed.ResultsWe confirmed that WGS in food safety surveillance allows accurate detection of genomic relationships between human cases and strains isolated from food samples, including those dispersed over time and geographical locations. Identifying these links can reveal new insights into outbreaks and direct epidemiological investigations to facilitate outbreak management. Complete WGS-based isolate characterization enabled expanding epidemiological insights related to circulating serotypes, virulence genes and antimicrobial resistance across different reservoirs. Moreover, associations between virulence genes and severe disease were determined by incorporating human metadata into the data analysis. Gaps in the surveillance system were identified and suggestions for optimization related to sample centralization, harmonizing isolation methods, and expanding sampling strategies were formulated.DiscussionThis study contributes to developing a representative WGS-based collection of circulating STEC strains and by illustrating its benefits, it aims to incite policymakers to support WGS uptake in food safety surveillance.

In 2021 JET exploited its unique capabilities to operate with T and D–T fuel with an ITER-like Be/W wall (JET-ILW). This second major JET D–T campaign (DTE2), after DTE1 in 1997, represented the culmination of a series of JET enhancements—new fusion diagnostics, new T injection capabilities, refurbishment of the T plant, increased auxiliary heating, in-vessel calibration of 14 MeV neutron yield monitors—as well as significant advances in plasma theory and modelling in the fusion community. DTE2 was complemented by a sequence of isotope physics campaigns encompassing operation in pure tritium at high T-NBI power. Carefully conducted for safe operation with tritium, the new T and D–T experiments used 1 kg of T (vs 100 g in DTE1), yielding the most fusion reactor relevant D–T plasmas to date and expanding our understanding of isotopes and D–T mixture physics. Furthermore, since the JET T and DTE2 campaigns occurred almost 25 years after the last major D–T tokamak experiment, it was also a strategic goal of the European fusion programme to refresh operational experience of a nuclear tokamak to prepare staff for ITER operation. The key physics results of the JET T and DTE2 experiments, carried out within the EUROfusion JET1 work package, are reported in this paper. Progress in the technological exploitation of JET D–T operations, development and validation of nuclear codes, neutronic tools and techniques for ITER operations carried out by EUROfusion (started within the Horizon 2020 Framework Programme and continuing under the Horizon Europe FP) are reported in (Litaudon et al Nucl. Fusion accepted), while JET experience on T and D–T operations is presented in (King et al Nucl. Fusion submitted).

Abstract Several studies have highlighted the value of diffusion tensor imaging (DTI) with strong diffusion weighting to reveal white matter microstructural lesions, but data in gray matter (GM) remains scarce. Herein, the effects of b-values combined with different numbers of diffusion-encoding directions (NDIRs) on DTI metrics to capture the normal hippocampal microstructure and its early alterations were investigated in a mouse model of multiple sclerosis (experimental autoimmune encephalomyelitis [EAE]). Two initial DTI datasets (B2700-43Dir acquired with b = 2700 s.mm−2 and NDIR = 43; B1000-22Dir acquired with b = 1000 s.mm−2 and NDIR = 22) were collected from 18 normal and 18 EAE mice at 4.7 T. Three additional datasets (B2700-22Dir, B2700-12Dir and B1000-12Dir) were extracted from the initial datasets. In healthy mice, we found a significant influence of b-values and NDIR on all DTI metrics. Confronting unsupervised hippocampal layers classification to the true anatomical classification highlighted the remarkable discrimination of the molecular layer with B2700-43Dir compared with the other datasets. Only DTI from the B2700 datasets captured the dendritic loss occurring in the molecular layer of EAE mice. Our findings stress the needs for both high b-values and sufficient NDIR to achieve a GM DTI with more biologically meaningful correlations, though DTI-metrics should be interpreted with caution in these settings.

In the TOMAS device, a triple Langmuir probe is used to measure the electron temperature and density. The accuracy of this measurement depends on correct determination of the effective collecting area of the probe, which depends on complex plasma transport processes. The probe can be calibrated by electron cyclotron resonance heating experiments using the cut-off density of the ordinary wave (O-wave). This threshold only depends on the frequency of the injected wave, and the occurrence of this phenomenon is clearly visible in the temperature evolution. The value of density is consequently known at this point and can be used to calibrate the density measurements of the triple Langmuir probe.

Elevated phosphate (PO4) concentrations can harm the ecological status in water by eutrophication. In the majority of surface waters in lowland regions such as Flanders (Belgium), the local PO4 levels exceed the limits defined by environmental policy and fail to decrease, despite decreasing total phosphorus (P) emissions. In order to underpin the definition of current limits, this study was set up to identify the pre-industrial background PO4 concentration in surface water of the Scheldt River, a tidal river in Flanders. We used the sedimentary records preserved in tidal marsh sediment cores as an archive for reconstructing historical changes in surface water PO4. For sediment samples at sequential depths below the sediment surface, we dated the time of sediment deposition and analysed the extractable sediment P. The resulting time series of sediment P was linked to the time series of measured surface water-PO4 concentrations (data 1967–present). By combining those datasets, the sorption characteristics of the sediment could be described using a Langmuir-type sorption model. The calibrated sorption model allowed us to estimate a pre-industrial background surface water PO4 levels, based on deeper sediment P that stabilized at concentrations smaller than the modern. In three out of the four cores, the sediment P peaked around 1980, coinciding with the surface water PO4. The estimated pre-industrial (∼1800) background PO4 concentration in the Scheldt River water was 62 [57; 66 (95 % CI)] µg PO4-P L−1. That concentration exceeds the previously estimated natural background values in Flanders (15–35 µg TP L−1) and is about half of the prevailing limit in the Scheldt River (120 µg PO4-P L−1). In the 1930s, river water concentrations were estimated at 140 [128; 148] µg PO4-P L−1, already exceeding the current limit. The method developed here proved useful for reconstructing historical background PO4 concentrations of a lowland tidal river. A similar approach can apply to other lowland tidal rivers to provide a scientific basis for local catchment-specific PO4 backgrounds.

Abstract Background COVID-19 pandemic highlighted the need for real-time monitoring of diseases evolution to rapidly adapt restrictive measures. This prospective multicentric study aimed at investigating radiological markers of COVID-19-related emergency activity as global estimators of pandemic evolution in France. We incorporated two sources of data from March to November 2020: an open-source epidemiological dataset, collecting daily hospitalisations, intensive care unit admissions, hospital deaths and discharges, and a teleradiology dataset corresponding to the weekly number of CT-scans performed in 65 emergency centres and interpreted remotely. CT-scans specifically requested for COVID-19 suspicion were monitored. Teleradiological and epidemiological time series were aligned. Their relationships were estimated through a cross-correlation function, and their extremes and breakpoints were compared. Dynamic linear models were trained to forecast the weekly hospitalisations based on teleradiological activity predictors. Results A total of 100,018 CT-scans were included over 36 weeks, and 19,133 (19%) performed within the COVID-19 workflow. Concomitantly, 227,677 hospitalisations were reported. Teleradiological and epidemiological time series were almost perfectly superimposed (cross-correlation coefficients at lag 0: 0.90–0.92). Maximal number of COVID-19 CT-scans was reached the week of 2020-03-23 (1 086 CT-scans), 1 week before the highest hospitalisations (23,542 patients). The best valid forecasting model combined the number of COVID-19 CT-scans and the number of hospitalisations during the prior two weeks and provided the lowest mean absolute percentage (5.09%, testing period: 2020-11-02 to 2020-11-29). Conclusion Monitoring COVID-19 CT-scan activity in emergencies accurately and instantly predicts hospitalisations and helps adjust medical resources, paving the way for complementary public health indicators.

Abstract Our aim was to develop practical models built with simple clinical and radiological features to help diagnosing Coronavirus disease 2019 [COVID-19] in a real-life emergency cohort. To do so, 513 consecutive adult patients suspected of having COVID-19 from 15 emergency departments from 2020-03-13 to 2020-04-14 were included as long as chest CT-scans and real-time polymerase chain reaction (RT-PCR) results were available (244 [47.6%] with a positive RT-PCR). Immediately after their acquisition, the chest CTs were prospectively interpreted by on-call teleradiologists (OCTRs) and systematically reviewed within one week by another senior teleradiologist. Each OCTR reading was concluded using a 5-point scale: normal, non-infectious, infectious non-COVID-19, indeterminate and highly suspicious of COVID-19. The senior reading reported the lesions’ semiology, distribution, extent and differential diagnoses. After pre-filtering clinical and radiological features through univariate Chi-2, Fisher or Student t-tests (as appropriate), multivariate stepwise logistic regression (Step-LR) and classification tree (CART) models to predict a positive RT-PCR were trained on 412 patients, validated on an independent cohort of 101 patients and compared with the OCTR performances (295 and 71 with available clinical data, respectively) through area under the receiver operating characteristics curves (AUC). Regarding models elaborated on radiological variables alone, best performances were reached with the CART model (i.e., AUC = 0.92 [versus 0.88 for OCTR], sensitivity = 0.77, specificity = 0.94) while step-LR provided the highest AUC with clinical-radiological variables (AUC = 0.93 [versus 0.86 for OCTR], sensitivity = 0.82, specificity = 0.91). Hence, these two simple models, depending on the availability of clinical data, provided high performances to diagnose positive RT-PCR and could be used by any radiologist to support, modulate and communicate their conclusion in case of COVID-19 suspicion. Practically, using clinical and radiological variables (GGO, fever, presence of fibrotic bands, presence of diffuse lesions, predominant peripheral distribution) can accurately predict RT-PCR status.

It is generally accepted that microorganisms can colonize a non-pathological endometrium. However, in a clinical setting, endometrial samples are always collected by passing through the vaginal–cervical route. As such, the vaginal and cervical microbiomes can easily cross-contaminate endometrial samples, resulting in a biased representation of the endometrial microbiome. This makes it difficult to demonstrate that the endometrial microbiome is not merely a reflection of contamination originating from sampling. Therefore, we investigated to what extent the endometrial microbiome corresponds to that of the vagina, applying culturomics on paired vaginal and endometrial samples. Culturomics could give novel insights into the microbiome of the female genital tract, as it overcomes sequencing-related bias. Ten subfertile women undergoing diagnostic hysteroscopy and endometrial biopsy were included. An additional vaginal swab was taken from each participant right before hysteroscopy. Both endometrial biopsies and vaginal swabs were analyzed using our previously described WASPLab-assisted culturomics protocol. In total, 101 bacterial and two fungal species were identified among these 10 patients. Fifty-six species were found in endometrial biopsies and 90 were found in vaginal swabs. On average, 28 % of species were found in both the endometrial biopsy and vaginal swab of a given patient. Of the 56 species found in the endometrial biopsies, 13 were not found in the vaginal swabs. Of the 90 species found in vaginal swabs, 47 were not found in the endometrium. Our culturomics-based approach sheds a different light on the current understanding of the endometrial microbiome. The data suggest the potential existence of a unique endometrial microbiome that is not merely a presentation of cross-contamination derived from sampling. However, we cannot exclude cross-contamination completely. In addition, we observe that the microbiome of the vagina is richer in species than that of the endometrium, which contradicts the current sequence-based literature.