dataesr/scientific-paragraphs-categorization huggingface dataset:
Results The study took place at the PCU of the Clermont-Ferrand Teaching Hospital. The inclusion period was from January 2021 to June 2021. 30 patients were included: 15 in the FR group, 15 in the MTgroup. Concerning the health status of the included patients, 24 (80%) had cancer (11 (73. 3%) in the FR group, 13 (86. 7%) in the MT group). Detail data are reported in Table  1. The cancers included 9 lung, 4 colonic, 3 pancreatic, 2 ovarian, 2 gastric, 2 renal, 1 breast, and 1 bone. The metastatic lesions were in lymph nodes in 11 of the included patients. 11 patients had bone metastases, 9 had lung or pleural metastases, 7 had liver metastases, and 7 had peritoneal metastases. 6 patients had brain metastases. 2 patients had adrenal metastases. For the non-neoplastic diseases, 4 patients (13.
1s energy level reaching the negative energy continuum Figure  3  shows the 1s energy level as a function of nuclear charge for hydrogen-like systems in the FNC variant, computed using the relativistic atomic program package GRASP  [148]. The calculations predict a critical charge of Zc(1s) = 170. 161 (170. 017 including QED effects) before diving into the negative energy continuum  [31]. Using different models of nuclear charge distribution, the predictions for the critical nuclear charge can vary widely between Zc = 164 to 174 for the 1s level  [149, 150] , but more realistically between 168 to 172 using the uniform nuclear charge distribution and neutron numbers varying between N = Z and N = 3Z. This is demonstrated in Fig. 8 , which shows the relation between the rms nuclear charge radius R ch and the proton number Z.
The critical charge as a function of nuclear radius obtained with the analytical expression of Ref. [151]  is shown by a dash-dotted line. The Zc (R ch ) Numerical values (black square) have been obtained using the MDFGME code  [14, 154]  with a Fermi nuclear charge model. In the context of the above discussion, it is interesting to notice that because of the mass scaling √ m of the Dirac equation (  4 ) the critical charge for muonic atoms (mµ/me = 206. 7682830  (46)  [155]) for a point nucleus is more than an order of magnitude larger Z µ cp (1s) ≈ 1966 compared to the electronic case. Taking into consideration the finite nuclear radius, the critical value shifts to Z µ c (1s) ≈ 2200  [156]. As in the free-particle case, the small component becomes large and takes over for E → -mec 2.
Numerical program packages, such as MCHF for the nonrelativistic [297] case or GRASP and MDFGME for the relativistic case, apply the finite difference method (FDM)  [298]. Alternatively, the finite element method (FEM) employing, for example, B-splines (piecewise polynomials)  [186, [299] [300] [301] ] can be used, as implemented for example in the program AMBiT  [302]. The use of B-splines has certain advantages in relativistic atomic structure calculations  [300]. As the radial wave functions are restricted to an interval [0, Rc], the atoms are spherically confined within a radius Rc set large enough (usually around 40 a u ) to achieve accurate numerical results. This discretizes the positive and negative real-energy continuum. It thus allows for an easy implementation of projection operators  [76].
Effective QED Hamiltonians To bring the self-energy term into a useful effective Hamiltonian form, h SE , is the most challenging part as this operator is inherently non-local. Nevertheless, many attempts were made to estimate the self-energy shift in atomic spectra by approximations. Earlier ones were summarized in  [411]. Approximations based on effective Z values to account for electron screening were introduced in the early versions of GRASP  [412]. The  Welton approximation [413]  was introduced in the MDFGME code in 1987  [65]  for s-states and generalized to ≥ 0 in  [66]. Effective operators directly based on BSQED have been introduced more recently  [68, 340].
074 + 0. 35Zα is a coefficient adjusted to reproduce the radiative shifts for the high Coulomb p-levels  [67] , and a B is the Bohr radius. This expression of the self-energy operator was implemented into the program GRASP  [280]  by simply replacing the Coulomb potential -Z/r by its extension to the finite nucleus case  [321]. Later, this has been correctly folded into the self-energy potential leading to more complicated expressions, which slightly improves the self-energy shifts  [414]. To improve the SE corrections for the s-levels, and especially for the 1s 1/2 level, in multi-electron systems the prefactor A(Z) in (  61 ) was chosen to be dependent on the principal quantum number n  [321]. More recently, both coefficients A(Z) and B(Z) were refitted and made dependent on the angular momentum  [414].
24  Energy levels for the dominant configurations of the Group 10 elements Ni, Pd, Pt, and Ds. The values for Ni, Pd, and Pt are from the NIST database  [419]. The Ds levels are from Ref. [42]. Different colors are used to distinguish between the three different configurations: green [(n -1)d 8 ns 2 ], blue [(n -1)d 9 ns] and black [3d 10 ]. For Pd, there are intruder states (not shown here) arising from the [(n -1)d 9 np] configuration (for Pt from the [(n -1)d 9 np] and [(n -1)d 8 ns np] configurations), which mix with several of the low energy states shown. Thus, some configuration assignments (especially for the 3 P 0 level) are approximate at best. For Ds, a dense spectrum arising from the [6d 7 7s 2 7p] configuration intrudes into the normal spectrum and only few predicted lines of even parity are shown  [42].
They showed that for He-like Ds (Z = 110) the correlation energy changes from -2. 019 eV to -1. 391 eV due to the NEC inclusion. The use of projection operators using a B-spline basis set build with direct Dirac-Fock potentials and their effect on the correlation energy were studied in  [76]  for the ground state of He-like ions. The larger impact on the relativistic correlation energy was shown to be due to the magnetic and retardation interaction. To illustrate the effect near Zc we have used the MDFGME code (2022 version) to calculate more precisely the correlation energy for the 1s 2 1 S 0 , with a fully relaxed wave function including 44 configurations, from 1s 2 to 7i 2 and projection operators. The Breit interaction was included in the self-consistent process. The relativistic Coulomb contribution changes sign around Z = 90.
Acknowledgements We acknowledge financial support by the  Program Hubert Curien Dumont d'Urville New Zealand -France Science & Technology Support Program  number  43245QC , and the  Marsden Fund of the Royal Society of New Zealand. We thank  Profs. Trond Saue  ( Toulouse ),  Ephraim Eliav  ( Tel Aviv ),  W. H. Eugen Schwarz  ( Siegen ),  James Avery  ( Copenhagen ) and  Vladimir Shabaev  ( St. Petersburg ) for many stimulating and critical discussions. This material is also based upon work supported by the  U. S. Department of Energy, Office of Science, Office of Nuclear Physics  under award number  DE-SC0013365. P. I. is a member of the  Allianz Program   of the Helmholtz Association , contract no  EMMI HA-216  " Extremes of Density and Temperature: Cosmic Matter in the Laboratory ".
org/10. 5281/zenodo. 6669875). Peak calling was done on Med17, Rsc8 and Sth1 experiments using MACS2 (v2. 2. 7. 1). The peaks were filtered (fold-change >2. 5 and P-value < 1e-10), and as we wanted to focus on protein-coding gene promoters, we kept those that were found on intergenic regions associated to protein-coding genes and <1 kb away from TSSs. We excluded intergenic regions related to replication origins, centromeres, long-terminal repeats, Pol III and Pol I-transcribed genes, retrotransposons, small nucleolar RNAs, small nuclear RNAs and telomeres. For some analysis, peaks were sorted using bedtools (v2. 30. 0) to define those that overlap (shared) or not (unique) between two data sets. All correlations were calculated with Spearman method  (Hollander, 1973). All figures were prepared using R packages (v3.
Acknowledgements We thank  Charles Boone ,  Jenny Wu ,  Claes Gustafsson  and  Vincent Geli  for strains, the  Highthroughput sequencing facility of I2BC  for its sequencing and bioinformatics expertise, the  SPI (CEA/Saclay)  for monoclonal antibodies,  Matthieu Gérard ,  Pascale Lesage  and  Adriana Alberti  for fruitful discussions. This work was supported by  Fondation ARC  [ PGA1 RF20170205342 ];  Comité Ile-de-France -La Ligue Nationale Contre le Cancer. K. A. was supported by a PhD training contact from the  French Ministry of Higher Education and Research. L. Z. was supported by a PhD training contract from the  CEA NUMERICS program , which has received.
Participants and dates All participants were invited to respond to two electronic self-administered questionnaires. Questionnaires were sent as of April 1, 2020 and returned before May 27, 2020, thus they covered the lockdown and post lockdown period (in France, the first lockdown occurred between  March 17, 2020 and May 11, 2020). These data were combined with serological results from the SAPRIS-SERO study, in which a random sample of SAPRIS participants were invited to provide self-sampling dried-blood spot (DBS) aimed at serology testing  [8]. Overall, 279,478 participants were invited to respond to SAPRIS questionnaires, 102,001 (37%) completed both questionnaires, and among them, 93,610 were invited to perform the serology, 86,913 (93%) returned dried blood spot and a serology could be performed and interpretable in 82,787.
Data sources/measurement Symptoms were reported if they had been present at least once within 14 days prior to each questionnaire. Smoking status, alcohol consumption and body mass index (BMI) were extracted from the original cohort databases and updated in 2020 with self-reported questionnaires. The ELISA test (Anti-SARS-CoV-2 ELISA, Euroimmun ® , Lübeck, Germany) was used to detect anti-SARS-CoV-2 antibodies (IgG) directed against the S1 domain of the spike protein of the virus (ELISA-S). Following the manufacturer's instructions, an ELISA-S test was considered to be positive with an optical density ratio ≥ 1. 1, indeterminate between 0. 8 and 1. 1, and negative < 0. 8. The sensitivity and specificity of the ELISA-S test at the 1. 1 threshold (considering indeterminate results as negative) were reported to be 87% and 97.
Symptoms Analyses regarding the association of TSD with other symptoms included 3,247 participants with PE-S and no missing data for symptoms. Table  3  reports results of the hierarchical clustering analysis, using only reported symptoms in PE-S participants. Four clusters were identified: cluster #1 groups all asymptomatic participants; cluster #2 groups participants with various associations of symptoms; cluster #3 groups participants with TSD, mostly isolated or associated with rhinorrhea; whereas cluster #4 groups patients with digestive symptoms, mostly isolated or associated with fatigue. Table  3  also presents the distribution of age, sex and serological titers in these clusters. These characteristics were not used to identify clusters. Results are also presented using two upset plots (Supplementary Fig.
Conclusions In conclusion, our study shows that among patients with a positive serology ELISA-S test, women, smokers and people drinking more than 2 drinks a day were more likely to develop TSD. We also found a strong association between antibody response and TSD. Regarding symptoms associations, the overwhelming majority of participants with TSD experienced a wide variety of acute symptoms, while a few of them only developed TSD either isolated or associated with only rhinorrhea. the data used for this study and to ensure continuing communication with the cohort participants. We thank the CEPH-Biobank staff for their adaptability and the quality of their work. In the virology department, Dr Nadege Brisbarre and the technical staff for impeccable management of samples and serological assays.
, 2005; Bouzier-Sore et al. , 2006; Cloutier et al. , 2009; Jolivet et al. , 2015) , a few simulations predicted lactate flow in the opposite direction, neuronalastrocytic-lactate-shuttle (NALS)  (Simpson et al. , 2007; Mangia et al. , 2009; Occhipinti et al. , 2009)  or concluded that results are highly sensitive to parameters selection  (Jolivet et al. , 2010; Somersalo et al. , 2012; Massucci et al. , 2013). In this work, we proposed a new mathematical model at the mesoscopic level based on the recent physiological data comprising neuronal, extracellular space, astrocytic and capillary compartments with a simplified version of lactate consumption/production within each of those, as depicted in Fig. 1. The goal of this paper is to assess lactate repartition and transfer across compartments under physiological conditions.
As a result, we will have a subset of optimized parameters (Θ s ∈ Θ) that satisfy all the conditions and could be a candidate for the system. The whole procedure is summarized in Fig. S1  in the supplementary materials. Finally, the whole model with fixed and optimized parameters is simulated and analyzed in MATLAB (The MathWorks, Natick MA, USA). during steady-state and activation. We used the MATLAB built-in function ode15s, to numerically solve ODEs.
A growing number of studies compare predicted habitat suitability generated by ENMs from different species to test hypotheses on historical processes that might be responsible for current distributions and also to forecast evolutionary responses of species under predicted future climates (Soberon et al 2017). Species distribution models (SDMs) and ecological niche models are constructed by correlating observations of occurrence with data on environmental conditions at occupied sites (Bradie and Leung 2017). Increasingly, conservation biologists are using species distribution models (SDMs) to assess the environmental parameters that shape species' distributions today and project these species-environment relationships into past and future conditions  (Phillips et al. 2006; Elith and Leathwick 2009).
Species Occurrence Data Set We compiled our eld georeferenced observations (stored in BOLD: Barcode of Life Data Systems http://v4. boldsystems. org/ ) of focal species' with online available occurrence sources: GBIF repository (12,970 records, GBIF. org, Occurrence Download https://doi. org/10. 15468/dl. wjr69h), and herbaria: Darwinion (http://www. darwin. edu. ar/proyectos/ oraargentina/fa. htm), USA_MOBOT (https://www. missouribotanicalgarden. org/) USA_ARIZ (https://cals. arizona. edu/herbarium/node/1), USA_NYBG (https://www. nybg. org/ ), and USA_COLO (https://www. colorado. edu/cumuseum/researchcollections/botany-section-university-herbarium-colo ). We use these occurrence records across the range of each species to develop suitability models in the present , and projected them into past (LGM: 21,000 BP; and Mid Holocene) and future (2050 and 2070) climatic scenarios.
4. 0  (Phillips et al. 2017 ). To estimate bioclimatic variable's relevance in each model, we run a jackknife procedure. We cross validate each model with 10 replicates, 500 iterations, 10 percentile training presence, and regularization multiplier of 1. Once we obtained each species' general model in MaxEnt, we applied dimension-reduction techniques to minimize strong covariance among environmental variables and to avoid over tted models that reduce accuracy (Synes and Bsborne 2011; Boria et al. 2014). We performed Pearson's correlations among 15 bioclimatic variables (BIO8, 9, 18 and 19 were excluded as they are considered mathematically arti cial  (Booth 2022). We then eliminated highly correlated variables using the function cor in the package stats in Rv3. 5, with a threshold of r ≤ 0.
70. For each species, we tested several models and sets of variables considering (1) statistical signi cance, (2) predictive power, and (3) model complexity. We used jackkni ng procedures in MaxEnt and bioclimatic variables correlation matrixes to build alternative models for each species selecting different sets of variables that contributed the most to each model. Then, we applied model calibration, which is a Bayesian procedure that nds the combination of parameters that best represents the phenomenon of interest tting with the data. For each species, we compared alternative models using KuENM R-script  (Cobos et al. 2019) , that automates important calibration and evaluation steps in ENMs. Each comparison included different sets of variables, multipliers (0. 1 to 1, with 0. 1 steps, and 1 to 5, with 1 steps) and features (lineal, quadratic, product, and their combinations).
Niche overlap We estimated present niche overlap, to test shared environmental constrains between pairs of species. For each pairwise comparison we run the function nicheOverlap in the package Dismo using R v3. 5, including each particular set of bioclimatic variables selected in the reduced models, and both species occurrences were pooled and randomly split into two datasets, maintaining the number of occurrences as in the original dataset. Then niche overlap similarity statistics Schoener's D and 'I' were calculated, which show values that range from 0 (no overlap) to 1 (complete overlap) (Schoener 1968).
Objectives: To describe the epidemiology, characteristics, response to initial treatment, and outcomes of Adult-Onset Still's disease (AOSD) in the Afro-Caribbean population of Martinique with free and easy access to specialised care. Methods: We conducted a retrospective study from 2004 to 2022 in the island of Martinique, French West-Indies which total population was 354 800 in 2021. Patients were identified from multiple sources including standardised databases. To be included, patients had to be residents of the island and fulfilled Yamaguchi and/or Fautrel's criteria for AOSD, or have a compatible disease course, without a diagnosis of cancer, auto-immune disease or another auto-inflammatory disorder. Date of diagnosis, clinical and biological characteristics, treatments, and outcomes were collected.
However, all available data on AOSD originate from Caucasian and Asian populations, and the characteristics of AOSD in patients of African origin are unknown  [6]. In fact, differences in epidemiology, severity and treatment efficacy between ethnic groups have been described in other rheumatic diseases (e. g. systemic lupus erythematosus and rheumatoid arthritis), with people of African descent experiencing a worse prognosis  [7, 8]. It can therefore be argued that such disparities may exist in AOSD. The lack of data in the Afro-descendant population is concerning and represents an unmet medical need for hundreds of millions of people in developed and developing countries. Martinique is a French Caribbean island with an estimated population of 354 800 in 2021. The island has a unique university hospital and tertiary care center, designated as a reference center for autoimmune, systemic and rare diseases by the French government and the National Rare Diseases Health Network (Filière de santé des maladies Auto-Immunes et Auto-Inflammatoires Rares, FAI 2 R).
Patients and methods We conducted a retrospective longitudinal study between January 1, 2004 and July 31, 2022 in Martinique. Patients were identified from several sources: the local version of the standardised National Rare diseases database (Base des Maladies Rares, BaMaRa) where each patient treated in the island's only tertiary care center is registered in since 2014, the ICD-10 code for AOSD in the hospital-wide database, and the three office-based rheumatologists on the island. There is no officebased internal medicine practitioner in Martinique. A total of 43 patients were identified and their medical records were reviewed for inclusion. Patients were included if they were residents of Martinique, were over 16 years of age at the diagnosis, met the Yamaguchi and/or Fautrel criteria for AOSD, or had a condition consistent with the diagnosis if the criteria were not met  [9, 10].
Cardiac involvement consisted of myocarditis, pericarditis, the presence of suggestive electrocardiogram (ECG) findings or abnormal cardiac function on transthoracic echocardiography or cardiac magnetic resonance imaging (MRI)  [12]. Pericarditis was assessed by echocardiography or cardiac MRI. Severe cardiac involvement was defined if patient suffered from life-threatening rhythmic disorder, transfer to intensive care unit, or heart failure. HLH diagnosis was retained if diagnosis guidelines of HLH-2004 trial were met  [13]. Systemic activity was assessed using a modified Pouchot score  [14]. Each patient's vital status was verified through contact with the patient's physician or through consultation of the French government's national database (matchID from Institut National de la Statistique et des Etudes Economiques (INSEE)).
Results Epidemiological data regarding the population of Martinique were available from 2006 to 2021 (Table  1 ). During this period, the mean annual incidence was 0. 4/100 000 inhabitants and the prevalence ranged from 1. 2 to 7. 6/100 000 inhabitants in total population. Nearly half of the patients were 35 years old or younger at diagnosis (Fig. 1 ). Thirty-three patients (70. 6% females) with a median follow-up of 35 months  [7. 5; 119]  were included (Fig. 2 ). Baseline characteristics are given in Table  2. Seven patients (21%) were lost to follow-up after a median time of 5 months [2; 34]. Three patients (9%) did not meet the Yamaguchi's and/or Fautrel's criteria but their disease course was still consistent with AOSD after a median follow-up of 104 months [2; 184]. Twenty-six patients (78.
Epidemiological results may therefore be underestimated. The study has some strengths. AOSD requires a tertiary-care center evaluation at first flare, and severe systemic manifestations lead to conventional hospitalisation or intensive care unit. Thus, the unique    University Hospital and Tertiary-care center of the island of Martinique aggregates all those patients, whatever their medical department of origin. More, whatever AOSD patients' initial medical condition and manifestation, rheumatology and/or internal medicine departments ensure their follow-up and have them registered in the National Database of Rare Diseases. Also, retrieving potential patients from officebased rheumatologists was simple given that they are only 3 of them on the island, and none of them ensure the follow-up of AOSD patients.
Strong verbal encouragements were delivered throughout the effort. Furthermore, MVIC was assessed at least 30 s after the end of the experimental condition. Thus, the last electrical stimulation was timed 2 30 after the end of the condition. Maximum torque was determined as the highest peak on the curve. The onset of contraction was determined as the time when the participant reached 2% of maximum torque, and the rate of torque development (RTD) was the level of torque (T 50 ) developed 50 ms after the onset of contraction. We have not reported the RTD from 0 to 50 ms because the value is numerically equivalent to the torque value at a specific time from 0  [28]. All the data were recorded in the same file as the EMG data through an analog-to-digital conversion system (MP150; Biopac Systems Inc.
Data were stored and analyzed with commercially available software (Acqknowledge MP150). From the raw EMG data, the RMS was calculated to quantify the activity of the quadriceps using the following formula: RMS = ∑ n 1 X 2 n n Computing the RMS during MVIC was realized in a 25 ms window (n = 50 points) with an overlap of 49 points. The same procedure was used to compute the RMS signal during the experimental conditions (i. e. , LV or CONT) for each muscle with a time window of 60 s (n = 120. 000 points) and no overlap. RMS MVIC refers to the average RMS signal recorded from 100 ms to 0 ms before peak force (window shifted if too close to DT 100 S ), and RMS COND refers to the average RMS signal recorded over 1, 3, or 6 min. Thus, the RMS values were then normalized based on the peak-to-peak values from the M-wave evaluation (RMS MVIC.