dataesr/scientific-paragraphs-categorization huggingface dataset:
Two K-Means clusters, representing infected and uninfected cells respectively, were calculated using the generated training data and key features. These clusters were then used to predict the phenotype of the experimental dataset using a semi-supervised K-Mean clustering algorithm (form flexclust R package, kccaFamily "k-median"). A preliminary data sorting was performed based on the total cell count per well in order to detect wells showing cell burst and prevent false negative results. All wells with less than 5000 cells per well were excluded from analysis and marked as "not applicable" (NA) in the final result. The prediction algorithm was then applied to the remaining dataset. This algorithm associates a phenotype for each cell depending on the cluster it falls in, and therefore, the percentages of infected and uninfected cells per well can be calculated.
c. Data analysis 15 Cell data extracted from MRC5 cells infected with CB NMII, CB 223 and CB 227 were used for data analysis and database generation. A database of negative and positive controls was generated to be used as training data. We selected data from different time points of infection. Positive controls were selected from wells where ~50 % of cells were infected. Highly infected cultures are often in advanced states of cell death and do not resemble early stages of infection, thus, it was better to use data from images with moderate infection rate (~50 %) and to find a clustering that meets this value while leaving the negative train data as close to zero as possible. We then identified 4 key features that distinguish well between the negative and the positive controls using radar graphs and principal component analysis: nuclear average fluorescence intensity per cell, skewness or the levels of asymmetry of the brightfield intensity distribution around the mean within the region of interest, kurtosis or the levels of peakedness or flatness of the brightfield intensity distribution within the region of interest and finally the ratio of the variation intensity over the average intensity of the brightfield within the region of interest Therefore, any prediction below this baseline was considered as a negative result.
We empirically determined a threshold of 10 % for positivity. However, any data between 7 and 10 % were systematically checked for possible false negativity. The percentage of infected and uninfected cells per well of the experimental dataset was then predicted using the generated clusters. Results were then represented as a color-coded heat map showing the percentage of infected cells (Figure  4-A ). All values below the baseline of 7 % are represented in white (negative result), values between 7 and 10 % are represented in green (suspected), and values above 10 % are represented in red (positive result). However, wells showing cell burst are prone to false negative results, therefore, wells with less than 5000 cells were excluded from analysis and marked as NA in the heat map (gray color).
ObjectAvgIntenCh1, ROI_SkewIntenCh3, ROI_KurtIntenCh3 and Var_Avg. IntensityRatio respectively). The later feature was calculated to compensate for the loss of illumination at the well edges, a phenomenon known as the vignette effect, observed in ROI_VarIntensityCh3 (the standard deviation of intensities in the region of interest). Training data normality was assessed in a QQ plot. Data were then filtered accordingly and outliers were removed to ensure a normal distribution. Using the 4 key features and the training data, 2 clusters were generated using the K-Means clustering algorithm. These clusters represent uninfected and infected cells, respectively. Due to experimental variability, training data were rescaled so the mean values of negative training data equal the mean values of untreated cells for each feature (untreated cells being the negative control of the experimental dataset to be predicted).
Acknowledgments This work was supported by a grant from the  French State  managed by the  National Research Agency  under the " Investissements d'avenir (Investments for the Future)" program  with the reference  ANR-10-IAHU-03  ( Méditerranée Infection ) and by the  Région Provence-Alpes-Côted'Azur and the European funding FEDER PRIMI. We sincerely thank all Thermo Fischer team for their technical support on the High Content Analysis platform and the automation system. The authors declare that  Maxime Mioulane  is an employee at  Thermo Fisher Scientific.
( ObjectAvgIntenCh1, ROI_SkewIntenCh3, ROI_KurtIntenCh3 and Var_Avg. IntensityRatio respectively). The later feature was calculated to compensate for the loss of illumination at the well edges, a phenomenon known as the vignette effect, observed in ROI_VarIntensityCh3 (the standard deviation of intensities in the region of interest). Training data normality was assessed in a QQ plot. Data were then filtered accordingly and outliers were removed to ensure a normal distribution. Using the 4 key features and the training data, 2 clusters were generated using the K-Means clustering algorithm. These clusters represent uninfected and infected cells, respectively. Due to experimental variability, training data were rescaled so the mean values of negative training data equal the mean values of untreated cells for each feature (untreated cells being the negative control of the experimental dataset to be predicted).
Selpercatinib, a novel, highly selective and potent, inhibitor of RET, demonstrated clinically meaningful antitumor activity with manageable toxicity in heavily pretreated and treatment-naive RET fusionpositive non-small-cell lung cancer patients in a Phase I/II clinical trial. LIBRETTO-431 (NCT04194944) is a randomized, global, multicenter, open-label, Phase III trial, evaluating selpercatinib versus carboplatin or cisplatin and pemetrexed chemotherapy with or without pembrolizumab in treatment-naive patients with locally advanced/metastatic RET fusion-positive nonsquamous non-small-cell lung cancer. The primary end point is progression-free survival by independent review. Key secondary end points include overall survival, response rate, duration of response and progression-free survival.
Treatment with selpercatinib resulted in a 64% objective response rate (ORR) (95% CI: 54-73%) by blinded independent review in the registration dataset (n = 105) of patients with RET fusion-positive NSCLC who previously received platinum-based chemotherapy and an 85% ORR (95% CI: 70-94%) in treatmentnaive patients with RET fusion-positive NSCLC (n = 39). Although the duration of response (DOR) and PFS were not yet mature in treatment-naive patients, in patients who previously received chemotherapy, the median DOR was 17. 5 months (95% CI: 12-not estimable). Additionally, in patients previously treated with platinum-based chemotherapy, selpercatinib demonstrated a robust CNS ORR of 91% (95% CI: 59-100%) per Response Evaluation Criteria in Solid Tumors (RECIST) version 1. 1 in 10 of 11 patients; all responders had a DOR of ≥6 months  [29, 31].
The LIBRETTO-431 clinical trial LIBRETTO-431 (also referred to as J2G-MC-JZJC) is a global, open-label, randomized, controlled Phase III trial, evaluating selpercatinib versus chemotherapy with cisplatin/carboplatin and pemetrexed treatment with or without pembrolizumab in treatment-naive patients with locally advanced or metastatic RET fusion-positive nonsquamous NSCLC (NCT04194944). This study is active and recruiting participants, with planned enrollment at approximately 230 sites across 26 countries.
Efficacy evaluations To evaluate PFS, radiographic tumor assessments will be performed per RECIST 1. 1. Scans should be obtained within 28 days of baseline and then during the study treatment at approximately 6, 12, 21, 30, 39 and 48 weeks after the start of dosing, then every 12 weeks thereafter until progression, the start of a new anticancer therapy, death or study completion. Response assessments, will be evaluated by the BICR. These data will constitute the primary assessment for PFS and ORR analyses.
LIBRETTO-431 TrialA Phase III study comparing selpercaƟnib to plaƟnum-based and pemetrexed therapy with or without pembrolizumab as iniƟal treatment of advanced or metastaƟc RET fusion-posiƟve non-small cell lung Stage IIIB-IIIC not suitable for radical surgery/radiaƟon therapy or Stage IV nonsmall cell lung cancer RET fusion posiƟve RET fusion posiƟve idenƟfied by PCR or NGS (tumor) or NGS (blood) ≥ 18 years old Have measurable disease by RECIST 1. 1; an ECOG PS of 0-2; a life expectancy ≥ 3 months; adequate organ funcƟon RET+ 18+ Ke ey y e eli lig gi ib bili ilit ty y c c Treatment-naïve Received no prior systemic therapy (chemotherapy, immunotherapy or biological therapy) for metastaƟc disease The primary endpoint of PFS per RECIST v1. 1 by BICR in paƟents with intent to receive pembrolizumab will act as a gatekeeper for the endpoint of PFS by independent review in the intent-to-treat populaƟon Secondary endpoints include: • InvesƟgator-assessed PFS • ORR/DOR • intracranial ORR/DOR • Ɵme to deterioraƟon in pulmonary symptoms • PFS2 • OS • RET fusion status: local vs central • safety/tolerability ~250 paƟents ~230 sites AddiƟonal screening criteria will be assessed prior to trial enrollment NCT04194944 This study is acƟve and recruiƟng parƟcipants, with planned enrollment at approximately 230 sites across 26 countries.
LIBRETTO-431 study • The global, open-label, randomized, controlled, Phase III LIBRETTO-431 trial, will evaluate selpercatinib versus platinum-based and pemetrexed treatment with or without pembrolizumab in treatment-naive patients with locally advanced or metastatic RET fusion-positive nonsquamous NSCLC (NCT04194944). • First ever randomized Phase III clinical trial in treatment-naive RET fusion-positive NSCLC.
K 26 countries* 26 LIBRETTO-431 TrialA Phase III study comparing selpercaƟnib to plaƟnum-based and pemetrexed therapy with or without pembrolizumab as iniƟal treatment of advanced or metastaƟc RET fusion-posiƟve non-small cell lung Stage IIIB-IIIC not suitable for radical surgery/radiaƟon therapy or Stage IV nonsmall cell lung cancer RET fusion posiƟve RET fusion posiƟve idenƟfied by PCR or NGS (tumor) or NGS (blood) ≥ 18 years old Have measurable disease by RECIST 1. 1; an ECOG PS of 0-2; a life expectancy ≥ 3 months; adequate organ funcƟon RET+ 18+ Ke ey y e eli lig gi ib bili ilit ty y c c Treatment-naïve Received no prior systemic therapy (chemotherapy, immunotherapy or biological therapy) for metastaƟc disease The primary endpoint of PFS per RECIST v1. 1 by BICR in paƟents with intent to receive pembrolizumab will act as a gatekeeper for the endpoint of PFS by independent review in the intent-to-treat populaƟon Secondary endpoints include: • InvesƟgator-assessed PFS • ORR/DOR • intracranial ORR/DOR • Ɵme to deterioraƟon in pulmonary symptoms • PFS2 • OS • RET fusion status: local vs central • safety/tolerability ~250 paƟents ~230 sites AddiƟonal screening criteria will be assessed prior to trial enrollment NCT04194944 This study is acƟve and recruiƟng parƟcipants, with planned enrollment at approximately 230 sites across 26 countries.
The author(s) declared the following potential conflicts of interest with respect to the research, authorship and/ or publication of this article: E. I. has honoraria for advisory boards or lecturing for Sanofi Genzyme and Merck outside the submitted work. G. A. has received compensation for consulting services or participation in advisory boards from Sanofi, Merck and Roche; research support from Novartis; travel expenses for scientific meetings from Novartis, Roche and Stendhal; and speaking honoraria from Sanofi and Merck. M. P. A. has received research grants and personal fees as a speaker and member of advisory boards by Biogen, Sanofi Genzyme, Merck Serono, Novartis, Roche and Teva, outside the submitted work. T. D. reports grants from Novartis and Biogen. Dr Derfuss' institution received financial support from Novartis, Biogen, Roche, Merck Serono, Celgene, Sanofi Genzyme, MedDay, GeNeuro, Mitsubishi Pharma and Actelion for his activities as steering committee or advisory board member or consultant.
Fresh samples which were used for comparison between Alinity m HBV and Aptima HBV quant assays were split into two aliquots prior to same day testing on the respective platforms. Frozen samples were processed with minimal freeze-thaw cycle. Results were compared to the test result obtained by one of the four commercially available HBV assay. Alinity m HBV assay: HBV DNA was isolated from 300 µl of sample per the manufacturer's instructions. The data were analyzed by the system software, version 1. 2 or later. The dynamic range of quantification of the Alinity m HBV assay is 10 to 10 9 IU/mL (1. 0 to 9. 0 Log10 IU/mL). The limit of detection (LOD) is 6. 72 IU/mL in plasma and 9. 62 IU/mL in serum and the lower limit of quantification (LLOQ) is 10 IU/mL. The Alinity m HBV assay primers and probes target the viral surface (S) gene.
RealTime HBV assay: HBV DNA was processed from 500 µL of sample using the m2000sp™ and the m2000rt analyzers for automated sample extraction and real-time PCR amplification and detection, according to the manufacturer's instructions. The data were analyzed with Abbott RealTime m2000rt software, version 8. The dynamic range of quantification of the RealTime HBV assay is 10 to 10 9 IU/mL (1. 0 to 9. 0 Log10 IU/mL), with an LOD of 6. 4 IU/mL in plasma and 3. 8 IU/mL in serum and an LLOQ of 10 IU/mL. The viral region targeted by RealTime HBV assay primers and probes is the viral S gene. CAP/CTM HBV v2. 0 assay: HBV DNA was processed from 650 µL of sample using the cobas AmpliPrep and cobas TaqMan 96 analyzer for automated sample extraction and real-time PCR amplification and detection, according to the manufacturer's instructions.
Alinity m HBV Assay Performance is Comparable Across HBV Genotypes To assess the influence of the HBV genotype on HBV DNA quantification, plasma samples from 148 patients with chronic infection with HBV genotype A to E were tested in parallel with the Alinity m HBV assay, RealTime HBV assay, and CAP/CTM HBV v2. 0 assay. A significant correlation was found between HBV DNA levels measured in the same plasma specimens with Alinity m HBV assay and RealTime HBV or CAP/CTM HBV v2. 0, regardless of the HBV genotype (data not shown).
Image data In this retrospective study, we used image data from a SAH registry and from an ischemic stroke clinical trial. The SAH registry is composed of prospective consecutive patients with aneurysmal SAH admitted in the Amsterdam UMC between December 2011 and December 2016. The inclusion criteria were (1) SAH visible on baseline non-contrast CT (NCCT) or confirmed after lumbar puncture and (2) confirmation of ruptured aneurysm by angiography imaging. We excluded patients with significant movement or metal artifacts on baseline NCCT or who were included in ongoing trials. We also used baseline NCCTs from ischemic stroke patients included in the in the MR CLEAN trial  [14]. A subset of 317 patients from this SAH registry was used in a prior study  [12]. The acute ischemic trial patients have been included in many published studies.
Outcomes assessment The patient database consists of all patients that had EBT at the comprehensive weight loss center. At baseline, patient height was recorded using a wall-mounted stadiometer and weight was measured using a calibrated scale with the patient wearing indoor clothing and no shoes. Patient age, sex, history of obesi-ty-related chronic medical diseases, and prior bariatric procedures were documented. The primary outcome was to identify barriers to establishing and offering EBT. The secondary outcome was weight loss at 1, 3, 6 and 12 months of follow-up. Adverse events (AEs) and complications were recorded up to 30 days post-procedure. The statistical analyses included subjects that reached the followup time points. ▶ Table  1  depicts lessons learned from our experience building an EBT program.
Have a digital footprint by being active on social media platforms such as Facebook and Instagram Hospital flat screen advertising Internet search engine optimization Professional YouTube videos Word of mouth Offer employees a discount Clinical trials Program evolution Managing emergent complications or removal of an IGB due to intolerance can be difficult if you are the only provider. Consider cross-training a colleague or developing a working relationship with a practice nearby Maintaining a database -Track weight loss data -Allows one to monitor the success of program Quality assurance for every component of the program including dietician, behavioral psychologist and exercise physiologist should be in place Consider joining a registry such as an endoscopic suturing registry or endoscopic bariatric therapy registry to track outcomes, adverse events and compare data ▶.
NutriNet-Santé study and study population The NutriNet-Santé study is a web-based ongoing French cohort initiated in 2009  [23]. The objectives of this cohort are to assess the relationships between nutrition and health, and also the determinants of dietary behaviors and nutritional status. Participants with an access to Internet were recruited via a multimedia campaign to subscribe on a specific secured web site http://www. etudenutrinet-sante. fr. Questionnaires and forms can be filled in online with all security conditions of data and personal information. To be considered as included, participants have to complete a set of five questionnaires related to diet (3 validated random records of 24 h food intake during a two weeks period  [24, 25] ), physical activity (with the validated International Physical Activity Questionnaire (IPAQ)  [26] ), anthropometry (weight, height)  [27, 28] , lifestyle and socio economic conditions (like date of birth, sex, education level, smoking status, number of children, income)  [29]  and health status (personal and family history of diseases, menopausal status, drug use including oral contraceptive or hormonal replacement treatment (HRT) for menopause).
Because of increased of bone loss induced by estrogen deficiency related to menopause, we only used the data of the postmenopausal women and men aged more than 50 years who responded to the questionnaire. The NutriNet-Santé study is registered at ClinicalTrials. gov as NCT03335644. This study is being conducted according to guidelines laid down in the Declaration of Helsinki and was approved by the International Research Board of the French Institute for Health and Medical Research (IRB Inserm n o 0000388FWA00005831) and the "Comité National Informatique et Liberté" (CNIL n o 908450 and n o 909216). All participants gave their electronic informed consent at inclusion.
Adapted Dietary Inflammatory Index We used the adaptation of the Dietary Inflammatory Index (ADII) developed by Cavicchia and al. and following the methodology laid down by van Woudenbergh and al. This score has been recently validated to calculate the inflammation of diet pattern  [13, 22]. It includes 34 food items and each item is then multiplied by a published coefficient, and all are summed to create the ADII score. A higher range of ADII scores represents a high inflammatory diet pattern  [22]. The ADII has been validated in the Supplémentation en Vitamines et Minéraux Antioxydants french cohort (SU. VI. MAX). Both original DII and ADII were evaluated in the SU. VI. MAX cohort and were strongly correlated  [30]. Then ADII has been used in NutriNet-Santé study  [31]. In this study, we used dietary data from the first 2 years of follow-up as an estimator of the usual diet to calculate ADII.
Fracture assessment For fractures, data was self-reported by patient on an additional questionnaire published on web site. The specific questionnaire was developed to collect retrospectively fracture events and the mechanism (low trauma fracture or no). Low trauma fracture was defined as a spontaneous fracture or a fracture occurred after a fall from own height and was explained at the beginning of the questionnaire. Participants had to report all fractures occurred after the age of 18 years with the year of the event, detailed for each location. The following variables: location of the fracture, date of fracture, mechanism of the fracture (low trauma or no), confirmation of the diagnosis (medical imaging and/or surgery), prevalent fracture after the age of 40, presence of osteoporosis at the moment of the fracture, drug-induced bone loss and treatments of osteoporosis were collected.
Total fractures included all fracture except fingers, toes, face and cervical vertebrae. Major fractures were defined as the following location: hip, pelvis, proximal humerus, vertebrae, distal femur, proximal tibia and wrist. Incident fractures were defined as those that occurred after the inclusion in NutriNet-santé. Prevalent fractures at inclusion were defined as those that occurred after the age of 40 and before the inclusion. In order to enhance the quality of this questionnaire, especially for vertebral fractures, we verified the data collected. In patients who declared low trauma vertebral fractures, 90% had had at least a previous fracture or a BMD measurement or an osteoporosis treatment. 21% of them had a prevalent fracture, 87% had had a BMD measurement, and 40% had received a treatment of osteoporosis.
Acknowledgments The authors thank the Société franc aise de rhumatologie for grants awarded. The authors thank  Cédric Agaesse  (dietitian);  Thi Hong Van Duong ,  Younes Esseddik  (IT manager),  Régis Gatibelza ,  Djamal Lamri ,  Jagatjit Mohinder  and  Aladi Timera  (computer scientists);  Julien Allegre ,  Nathalie Arnault ,  Laurent Bourhis  and  Fabien Szabo de Edelenyi, PhD  (supervisor) (data-manager/statisticians) for their technical contribution to the  NutriNet-Santé study  and  Nathalie Druesne-Pecollo, PhD  (operational coordination). We thank all the volunteers of the NutriNet-Santé cohort.
Molecular analysis Among the 90 soft ticks that were collected in summer from the hens' body, thirty-four randomly selected specimens (14 males and 20 females) were tested by qPCR after being sent to Marseille, France. Other specimens have been kept for other studies. A total of 2/34 (5. 88 %) specimens adult females harbored bacteria of the Borrelia genus. Sequencing analyses targeting the 16S rRNA fragment lead to the identification of 2 sequences of B. anserina (GenBank accession no. CP013704, with 100% similarity). None of the tested ticks was positive for Rickettsia spp. , and Coxiella burnetii.
These data support a role for DNM2 in recycling endosome fragmentation In (A) left hand panel we have 3 cells that we scored as having tubules, while the cells in the right hand panel of Figure  1A  were not considered to have this tubulation state. (C) HeLa cells were transfected for 24 h with pEGFP-RAB11A and mRFP-LC3 and processed for live imaging in HEPES-HBSS medium (see also Video S1). (D) HeLa cells were transfected for 24 h with DNM2-pEGFP and mRFP-LC3, fixed in basal conditions and labeled for endogenous RAB11A. Histogram below shows quantification of the association of LC3 with DNM2 or DNM2 with RAB11A (E) HeLa cells were transfected for 24 h with DNM2-pEGFP and were fixed in basal conditions and labeled for endogenous LC3 and RAB11A and processed for superresolution microscopy (SIM-Elyra).
(E) Immunoprecipitates obtained by GFP-TRAP were processed for immunoblot for DNM2. (F) The amount of DNM2 co-immunoprecipitated with EGFP-LC3 was quantified and normalized for the amount of LC3 immunoprecipitated. Data are mean ± SD (n = 4; graphs represent means of four independent experiments). Two-tailed paired t test, **p < 0. 01. (G) Recombinant DNM2 and LC3 proteins were incubated for 1 h at 25 C with gentle shaking. The mixture of the two proteins was immunoprecipitated using anti-DNM2 antibody and blotted for LC3 and DNM2. As control we immunoprecipitated DNM2 alone or LC3 alone. Note that recombinant LC3 levels in the input were below detection levels by western blotting. (H) Representation of the different domains of DNM2. The LIR, identified using ILIR software  (Jacomin et al.