dataesr/scientific-paragraphs-categorization huggingface dataset:
Efficacy endpoints The primary endpoint was the proportion of participants with HIV-1 RNA <50 copies/ml at week 24, defined using the US Food and Drug Administration (FDA)'s Snapshot algorithm. 23 Secondary endpoints included the proportion of participants with HIV-1 RNA <50 copies/ml at weeks 48, 72 and 96; the proportion of participants with HIV-1 RNA <50 copies/ml where missing data were treated as HIV-1 RNA ≥50 copies/ml (missing = failure); the proportion of participants with HIV-1 RNA <50 copies/ml where missing data were excluded from percentage calculations (missing = excluded); the change from baseline in CD4 cell count and percentage at weeks 24, 48, 72 and 96; and the safety and tolerability of B/F/TAF. Additional supportive endpoints included the proportion of participants with HIV-1 RNA <20 copies/ml and medication adherence assessed using a visual analogue scale (VAS) adherence questionnaire at day 1 and weeks 4, 12, 24, 36, 48, 60, 72, 84 and 96.
Statistical analyses Methods for statistical analyses and sample size calculation were reported in detail previously. 18 In brief, efficacy was evaluated using the full analysis set, which included all participants who had received at least one dose of study drug and had no major protocol violations. The safety analysis set included all enrolled participants who had received study drug. The Clopper-Pearson exact method was used to calculate 95% confidence intervals (CIs) for virologic data. Descriptive statistics were used to summarize changes from baseline in CD4 cell counts and percentage CD4, VAS adherence questionnaire results, AEs and clinical laboratory data. Changes from baseline in laboratory data were analysed using the two-sided Wilcoxon signed-rank test. Statistical analyses were performed using SAS ® version 9.
While the events of abnormal faeces and increased GGT were considered related to the study drug, hepatocellular injury was not; none led to study drug discontinuation. No participants discontinued the study because of renal or urinary TEAEs, and no participants had proximal tubulopathy, including Fanconi syndrome. Small initial variations from baseline in median values for urine RBP:Cr, urine β 2 m:Cr and eGFR CG were previously reported,  18  but these values remained stable between weeks 48 and 96 (Figures  S1  and 3a ). Of the eight participants with clinically significant proteinuria (UPCR >200 mg/g) at baseline, data were obtained from five participants at week 96. Of these, one shifted to the classification of urine protein <4. 0 mg/dl; the rest remained unchanged. Of the 39 participants with UPCR ≤200 mg/g at baseline, 28 had data after 96 weeks.
ACKNOWLEDGEMENTS The authors thank all participants and their families, participating sites, investigators and study staff involved in the study. Medical writing support including development of drafts, fact checking and referencing was provided by  Josh Lilly, PhD , at  Aspire Scientific (Bollington, UK ) and funded by  Gilead Sciences, Inc. (Foster City, CA, USA). The study sponsor,  Gilead Sciences, Inc. , played a role in the study design, data collection and analysis, decision to publish and preparation of the manuscript. All authors had full access to all study data and had final responsibility for the decision to submit for publication.
Membranes were incubated overnight at 4 °C with the appropriate primary antibody (Cf above for anti-chemerin, anti-CMKLR1, and anti-GPR1 antibodies; anti-vinculin antibody  26  ; anti-CCRL2 antibody  27  ). Then, membranes were incubated for 90 min at room temperature with a Horse Radish Peroxidase-conjugated anti-rabbit or anti-mouse IgG. Proteins of interest were detected by enhanced chemiluminescence (ECL, Western Lightning Plus-ECL, Perkin Elmer, Villebon-sur-Yvette, France) with a G-box SynGene (Ozyme, St Quentin en Yvelines, France) and the GeneSnap software (Ozyme, St Quentin en Yvelines, France) and subsequently quantified with the GeneTools software. The results were expressed as the intensity signal in arbitrary units after normalisation of target proteins signals with housekeeping protein signals (vinculin) or the total protein amount (Ponceau).
Statistical analysis. The GraphPad Prism ® software (version 8) was used for all analyses. Data were tested for homogeneity of variance by Bartlett's test, and for normal distribution by the Shapiro-Wilk test. A one-way ANOVA was performed with Tukey-Kramer multiple comparisons tests, or with Dunnett's to compare controls, as appropriate. Mann-Whitney tests were performed where variances were unequal. Culture data included replicates as a random variable. Chemerin amounts in blood plasma compared to albumen were analysed by the unpaired t-test. Data are presented as means ± SEM, with p < 0. 05 considered significant.
Results Expression of chemerin within the egg. As shown in Fig. 1A , chemerin protein as determined by immunoblot is highly abundant in the perivitelline membranes and the white (albumen) as compared to the egg yolk. Samples of the hens' blood plasma and albumen were also analysed. As shown in Fig. 1B , the amount of chemerin was about 10 times higher in the albumen compared to the plasma. Similar data were obtained by the ELISA assay (data not shown). However, the chemerin protein level was similar in thin and thick albumen but more abundant in the chalaza (Fig. 1C ). By immunofluorescence, we confirmed the presence of chemerin inside the perivitelline membrane, with a significant staining of this structure when incubated with an anti-chemerin Chemerin in egg white comes from magnum. Since the albumen is produced and secreted during egg formation by the oviduct in hens, we investigated the expression of chemerin and its three receptors within the five parts of the hen oviduct (infundibulum, magnum, isthmus, shell gland and vagina, Fig.
3A-C ). Chicken chemerin antibacterial activity. The antibacterial activity of recombinant chicken chemerin was investigated through the determination of its minimal inhibitory concentrations (MIC), using a standardised broth microdilution assay procedure (CASFM/EUCAST 2019). The MICs of recombinant chicken chemerin obtained after 24 h at 37 °C were 125 µg/mL for each tested bacterial strain of Escherichia coli, Staphylococcus aureus and Pseudomonas aeruginosa. A partial inhibition of bacterial growth, which resulted in a delayed growth, was still observed at the concentration of 62. 5 µg/mL of recombinant chicken chemerin (data not shown). The effect of buffer salts alone, diluted in the same way as the recombinant chemerin, was checked. Buffer salts slightly reduced the bacterial growth by 19.
Chemerin system expression in embryo annexes and fluids. Since chemerin is present in the egg white, we determined whether this hormone could be involved in embryogenesis. First, we collected samples of embryonic annexes (allantoic and amniotic membranes) and amniotic fluids from eggs artificially incubated for 7 days (Fig. 4B ). Western blot data showed that chemerin is found in the albumen and the perivitelline membranes of the eggs, as previously shown in unincubated eggs, but also expressed by the allantoic and amniotic membranes (Fig. 4A ). We measured the expression of chemerin and its receptors by the allantoic and amniotic membranes at different embryonic days (ED): ED 7, 9, 11, 14, 16 and 18. In the allantoic membranes, the amount of chemerin (Fig. 4C ), GPR1 (Fig. 4E ) and CCRL2 (Fig.
The causality of alcohol intoxication was retained when consumption was estimated to exceed 60 g/day. Clinical and biological data were collected at the time of admission to the department and before starting treatment. Most of the patients were unaware of their conditions and did not receive any antiviral therapy before the diagnosis of already severe disease. The criteria for exclusion were the lack of clinical and/or biological data and the detection of liver nodules concomitant to an extra-hepatic primary tumor. Due to the retrospective nature of the study, no informed consent was obtained for the patients before 2019, while patients recruited in 2019 gave their informed consent to participate in the study. The institutional review board approved the study. The study was conducted in accordance with the recommendations of the Convention of Helsinki.
Statistical analyses Statistical analysis was performed using the Prism 8. 0. 2 statistical package (GraphPad, USA) and, in case of very small p values (p < 1. 0 E-04), with the BiostaTGV online software (https:// biostatgv. sentiweb. fr/?module=tests) to improve the appraisal of significance by readers. Numerical variables were compared for analyses of two groups either by a Student's t-test, by a Mann-Whitney U test as appropriate. When more than two groups were examined, ANOVA or Kruskal-Wallis test were used. Categorical variables were summarized as frequencies that were compared by Fisher's exact test when two groups were compared or by c 2 in presence of more than two groups. All tests were univariate and two-sided. The level of significance was set at p < 0. 05. Principal component analysis was performed as well with the Prism 9.
Methods A systematic database search (Embase, Medline, Cochrane Library and Google Scholar) of the literature was performed using both free-text and Medical Subject Headings (MeSH) terms (cholangiocarcinoma and chemotherapy, surgery or radiotherapy, cholangiocarcinoma, perihilar cancer, Klatskin tumor) during the past decade (2010-2020). Both types of CC (i. e. , intra-and extrahepatic) were included for evaluation because of the low number of available RCTs. Articles were selected for inclusion in the analysis of the evidence based on the following criteria:  Population: Patients with advanced CC, including patients after surgery or who are no longer candidates for surgical or liver-directed therapies.  Intervention: First-line or greater-line (due to progression or toxicity) systemic therapy or stenting.
Calculation of SIFI The SIFI was calculated from Kaplan-Meier (KM) curves, reconstructed using Digitizelt software (http:// www. digitizeit. de/), by the iterative redesignation of the best survivors from the experimental to the control arm until statistical significance (defined as P<0. 05) was lost. For trials with non-significant outcomes, negative SIFI was calculated similarly, but the direction was oppositeredesignation of the best survivors from the control to the experimental arm, until statistical significance was gained. Thus, the SIFI reflects statistical robustness, by denoting the minimal number of redesignations required to lose or gain significance in survival analysis. P values were calculated with the 2-sided log-rank test. The follow-up time distribution was calculated using the 'prodlim' package in R.
 Comparison: Interventions listed or placebo control.  Outcomes: Primary outcomes were those explicitly reported as such in the Methods section of the published study or the registered trial in www. ClinicalTrials. gov. If none were explicitly reported, we considered the outcome used to calculate the sample size; if outcomes were not stated in the sample size calculation, the outcome defined in the primary study objective was retained. If the primary outcome was still not clearly identified, the article was excluded. Secondary outcomes were excluded from this study.
Best (BILCAP) Both supportive care Ebata (10) UMIN000000820 (BCAT) 2018, British Journal of Adjuvant Treatment, 225 Gemcitabine vs. Best Surgery PH and distal CC supportive care Edeline (11) EudraCT2008-004560-39 2019, Journal of Clinical Adjuvant Treatment, 196 GEMOX vs. Best (PRODIGE 12-ACCORD) Oncology Both supportive care Sasaki (19) UMIN000001703 2013, Cancer Locally Advanced 62 GEM-S-1 vs. GEM Chemotherapy and Disease, Both Pharmacology Park (17) NCT00869635 2014, European Journal of Locally Advanced 43 PDT + S-1 vs. PDT Cancer Disease, PHCC Lee (13) NCT02166970 2017, Gastrointestinal Locally Advanced 133 Bilateral vs. Unilateral Endoscopy Disease, PHCC Stent GEMOX, gemcitabine and oxaliplatin; PDT, photodynamic therapy; PH, peri-hilar; CC, cholangiocarcinoma. Both CC intra-and extrahepatic CC.
AFM data analysis Data analysis software IGOR (WaveMetrics, Lake Oswego, OR, USA) was used to evaluate the mechanical properties of cells in terms of apparent Young's modulus (E). The Hertzian model for parabolic tips was used to calculate apparent Young's modulus for each force curve within a force map  [21]. The median and 25/75 percentiles and logarithmic histogram of apparent Young's modulus were considered representative modulus of each force map. Sweep frequency data were fitted with the power law structural damping model  [22, 23]  and corrected for the hydrodynamic viscous drag  [24]. E* data are separated into real (in phase) and imaginary (out of phase) parts. The real part represents the storage modulus, and it is a measure of the elastic energy stored and recovered per cycle of oscillation.
4 Oil) was used to observe cells and collect fluorescent images (Photometrics Prime95B Scientific CMOS Camera) through appropriate filters (emission: 450/50; 525/50; 595/50; and 700/75). Three-dimensional-view representation videos were created using IMARIS software (Bitplane, Oxford Instruments). The super-resolution images were taken using a stimulated emission depletion (STED) microscope (Abberior Instruments GmbH, Germany) with the ×100 objective lens (Plan Apo, NA 1. 4 Oil), with an excitation at 640 nm followed by a depletion at 775 nm. SiR-actin (Cytoskeleton, Inc. , 1:1,000) was used to label F-actin in live cells. The cell culture medium was replaced, and SiR-actin was directly added to the cells. The cells were then placed in the incubator at 37 °C and 5% CO 2 for 1-2 h prior to image acquisition.
We measured the complex elastic modulus using AFM over three frequency decades (1 Hz-1 kHz); however, the data were analyzed until 130 Hz due to piezo limitation of our instrument. The cell culture medium exhibits a pure viscous behavior; therefore, the hydrodynamic viscous drag force on the cantilever overestimates the loss modulus. For that reason, viscous drag was corrected calculating the b factor at a distance zero (b (0)) from the sample. The estimation of b (0) was performed following the  [24]  procedure. The cantilever was oscillated at low amplitude (50 nm) at different frequencies (1 Hz-1 kHz) and at different tip-sample distances (0-5 µm). Frequency dependence of storage and loss moduli showed an increase in the storage modulus over frequency in all cases (Supplementary Figure  S4 ); the loss modulus also increased over frequency, even after viscous drag correction; nonetheless, it increases with a more marked frequency dependence at higher frequencies.
Acknowledgments The authors thank  Prof. Dr. Ursula Mirastschijski  for kindly providing tissue samples and  Prof. Dr. Gazanfer Belge  for establishing cell lines from primary cells. The authors thank the members of the  Institute Pasteur Lille  for making their facilities available and for their help and support during the visit. The authors thank  Dr. Lorena Redondo ,  Dr. Fabio Perissinotto , and  Javier Lopez-Alonso  for their help and support. The authors acknowledge the support of the  European Union 's  Horizon 2020 Research and Innovation Programme  under the  Marie Sklodowska-Curie  grant agreement no. 812772 , Project Phys2BioMed.
Introduction Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in December 2019 in Wuhan, China, and is the seventh coronavirus known to infect humans  [1]. In early 2020, this virus quickly spread around the world and was declared a pandemic in mid-March 2020  [2]. As of 2 October 2022, it was estimated to have caused 617,879,854 cases and be involved in 6,546,448 deaths worldwide (https://coronavirus. jhu. edu/map. html (accessed on 3 October 2022)). SARS-CoV-2 is an enveloped single stranded positive RNA virus and belongs to the genus Betacoronavirus. Its genome is 29,903 nucleotide-long (based on the genome of the Wuhan-Hu-1 isolate, GenBank Accession NC_045512. 2) and harbors 14 open reading frames (ORFs) that encode 31 structural, non-structural, or regulatory/accessories proteins.
In our dataset, intra-sample diversity was >4% in a single sample, from which an Alpha variant was identified. Therefore, the overall level of intra-sample genetic diversity was low, the mean (± standard deviation) diversity at the six positions being 0. 31 ± 1. 96% (range, 0. 00-38. 80%) and ranging between 0. 17 ± 0. 63% (range, 0. 00-5. 10%) and 0. 57 ± 1. 62% (0. 00-13. 20%) according to the position. Considering any level of diversity, between 8. 2 and 30. 9% of the genomes, and 27 of the 110 genomes overall, exhibited a genetic diversity at any of these six positions. The variants Marseille-2 (one genome), Marseille-5 (two genomes), and Alpha (two genomes) exhibited an intra-sample genetic diversity at position 22813 corresponding to mutation G22813U, which leads to amino acid substitution K417N where the U corresponds to the minority nucleotide compared to the consensus.
Discussion We investigated here the SARS-CoV-2 quasispecies recovered by NGS directly from nasopharyngeal samples for 110 genomes covering all major lineages that circulated in France during the first year after first detection of SARS-CoV-2 in our geographical area. For this, only genomes with a coverage greater than 99% of the genome GenBank Accession no. NC_045512. 2 and a mean NGS depth greater than 50 reads/nucleotide position were selected for the present analyses. These genomes were classified in lineages 20A, 20B, and 20C that circulated during early 2020 as well as in several variants that were detected in our clinical virology laboratory during summer 2020, among which were the Marseille-1 variant that had a limited spread and was reported to originate from Northern Africa  [39] , the Marseille-2 variant that predominated in Spain  [40] , and the Marseille-4 variant that predominated in France  [41].
Here, NGS of SARS-CoV-2 genomes had been performed in absence of prior multiplex PCR amplification, which limited the sequencing biases of viral quasispecies and may have contributed to their more accurate assessment. In return, this led to far lower sequencing depths than those obtained when using the ARTIC procedure, which may have impaired the detection of very minority viral quasispecies and is a limit of the present study. We identified in this study that approximately one-fifth of nucleotide positions in the SARS-CoV-2 genomes showed intra-sample genetic diversity including in at least two viral genomes in about one-third of these cases, and in a single genome in two-thirds of the cases. This revealed the presence of substantial amounts of SARS-CoV-2 quasispecies in our dataset and delineated pan and core sets of nucleotide positions with intra-sample genetic diversity at the genome level.
Additionally, Vellas et al. reported the emergence of spike mutations E484K or Q493K among viral quasispecies in 5 of 23 patients treated with the combination of monoclonal antibodies Bamlanivimab/Etesevimab  [54]. Here, the comparison of intra-sample genetic diversity according to viral genomes classification did not show sharp variant-specific signatures, neither at the level of intrasample diversity at the gene level for whole genomes nor at spike gene nucleotide positions. This contrasts with a previous study that reported the specific detection of intra-host diversity at some positions in some lineages  [49]. Beyond, we did not observe an increasing trend over time of the mean proportions of nucleotide positions exhibiting significant diversity in our dataset as, regarding these proportions, samples collected during the early pandemic from which lineages 20A, 20B, and 20C were retrieved were intermixed with samples collected since summer 2020 and from which various variants were retrieved.
This could suggest that the increase of the number of mutations accumulated in SARS-CoV-2 genome over time, which is approximately two mutations per month  [9] , was not combined with a greater intra-sample diversity, but this deserves to be further assessed in several other studies with larger datasets. We have been attentive in the present study to the intra-sample diversity at spike nucleotide positions where mutations have been reported to occur that are hallmarks of SARS-CoV-2 variants of concern, and that are critical for immune escape and were reported to emerge during prolonged infection of immunocompromised patients, at codons 417, 452, 484, 501, 614, and 681  [38]. Amino acid substitution K417N is a hallmark of the Omicron variants, occurs in a neutralizing epitope, and has been suspected to be associated with escape from neutralization by some classes of monoclonal antibodies and convalescent patients' serum samples, and to contribute to escape from neutralization by antibodies elicited by mRNA vaccines  [55].
In our dataset, we observed a diversity at ≥1 of these positions in one quarter of the 110 genomes, although most often at a low level, below the threshold of 4% that was used for significance. Finally, it is worthy to note that it was reported that the SARS-CoV-2 quasispecies differed in the same patient according to the clinical samples in which they were investigated, which is another hint of the existence of significant bottlenecks and selection processes for these viral quasispecies  [9, 60]. Moreover, the quasispecies complexity of sputum samples was reported to be significantly lower than that of nasopharyngeal swabs  [50]. Therefore, the spectrum of viral quasispecies present in a given patient will differ according to the sample and to time of sampling. In summary, the present study revealed a pan set and a core set of nucleotide positions exhibiting intra-sample genetic diversity among studied nasopharyngeal samples that were found to be infected with members of the SARS-CoV-2 lineages that predominated during the first year of the pandemic.
Next-Generation SARS-CoV-2 Genome Sequencing Methods and Data The data generated by NGS of SARS-CoV-2 genomes analyzed here had been obtained in the framework of SARS-CoV-2 genotyping performed since the first diagnosis of SARS-CoV-2 performed by real-time reverse transcription-PCR (qPCR) during late February 2020 in our clinical microbiology-virology laboratory at university hospital institute (IHU) Méditerranée Infection in university hospitals of Marseille, southeastern France, as previously reported  [20]. These SARS-CoV-2 genomes are available from the NCBI GenBank nucleotide sequence database (https://www. ncbi. nlm. nih. gov/genbank/ (accessed on 30 September 2022)) [61] with no. OP646492-OP646601, and from the GISAID sequence database (https://www. gisaid. org/ (accessed on 30 September 2022))  [62]  using the GI-SAID online search tool with "IHU" and "France" as keywords or the correspondence table between GenBank and GISAID identifiers provided as Supplementary Table  S2.
Raw NGS data used in the present analyses were those generated from a total of 310 nasopharyngeal samples collected from SARS-CoV-2-positive patients between March 2020 and February 2021 and directly sequenced without prior PCR amplification by the Illumina technology with the Nextera XT paired-end strategy on a MiSeq instrument (Illumina Inc. , San Diego, CA, USA), as previously reported  [20]. Reads obtained had been mapped on the SARS-CoV-2 complete genome of the Wuhan-Hu-1 isolate (Gen-Bank Accession no. NC_045512. 2) with the CLC genomics workbench software v7 using the following thresholds: 0. 8 for sequence coverage and 0. 9 for nucleotide similarity (https://digitalinsights. qiagen. com/ (accessed on 30 September 2022)). Only the files corresponding to complete genomes with a coverage of at least 99% of the genome no.