dataesr/scientific-paragraphs-categorization huggingface dataset:
Human Cerebral Microvascular Endothelial Cell (hCMEC)/D3 cells were obtained from Cedarlane. Cells are cultured in the medium cell biologics add with supplements for endothelial cells H1168 as described above. HEK293/CVCL_0045 cells were transfected with pcDNA6. 2™-EmGFP or cotransfected with PiggyBac® transposon expression vectors bearing wt ITM2A and variants cDNAs and transposase plasmids 6209 (10:1) by using Lipofectamine 2000®, following manufacturer instructions. Transfections were performed at 50% con uence in 24 wells plate with 500 ng of plasmids. For stable transfections, clones are obtained by limit dilution in 96 well plates with blasticidin selection for pcDNA 6. 2 or in glutamine free media corresponding to the glutamine synthase selection marker of pBH 6450. Each individual cell is ampli ed in a 6 wells plate, then ITM2A expression is checked rst with uorescent microscope for GFP tag, second by Western Blot for all ITM2A constructions.
After incubation, plates were washed three times with PBS-Tween 0. 05% (Calbiochem, 524653) and blocked for 1 h at RT with 0. 1% BSA solution (A7030, Sigma). After blocking the plates, collected samples in transport assay and standards were incubated on plates for 2 h at RT. After incubation, plates were washed three times with PBS-Tween 0. 05%, and bound antibody was detected with SULFO-TAG conjugated goat anti-mouse antibody (R32AC-1, Meso Scale Discovery) or goat anti-human antibody (R32AJ-1, Meso Scale Discovery) using Tripropylamine containing read buffer (R92TC-2, Meso Scale Discovery). Concentrations were determined from the standard curve using a fourparameter non-linear regression program (Discovery Workbench version 4. 0 software).
Analysis of the Next Generation Sequencing (NGS) data from human brain, liver and lung endothelial cells, selection of the genes with the highest expression in brain, differential expression versus peripheral tissues, annotation of human tissue, cell type and membrane localization using several public databases, led to few genes, some of them previously reported as brain delivery receptors such as LRP8  (54)  or Basigin(12) (54). Among them, ITM2A stood out with the highest differential expression. This protein has been reported as brain endothelial speci c and identi ed from other omics efforts on rat(31) (32) and pig(33) BEC's. However, the function of this protein remains largely unknown, and it was never reported as a brain transporter. To validate a putative transport mechanism for ITM2A along with potential for delivering drugs to the brain, we rst developed cells overexpressing the protein with the aim to validate the protein membrane localization and look at binding and uptake of anti-ITM2A antibodies.
Our next objective was to demonstrate that this uptake could lead to transcytosis in endothelial polarized cells. For this we needed a transcytosis model expressing the protein. It could be rodent or human as our anti ITM2A antibodies were cross reactive. From the COMPACT IMI consortium studies, it had been shown that the protein could no longer be found after an additional cell passage. We showed that ITM2A expression is strongly downregulated upon culture of either non-human primate  (34)  or mouse primary BEC's (Fig. 9 ) as is the case for several BBB genes after cell line establishment or culture (60, 61) and has already been shown speci cally with ITM2A  (33). Most expression studies reported in the literature about ITM2A are transcript-based. In human, a good amount of the ITM2A transcript can be found in the brain as detailed in databases such as Gtex, Stanford, GenCard or open target platform (Fig.
Acknowledgements We are grateful to  Axel Meyer  for his strong involvement in the COMPACT IMI consortium data analyses and his active reading of the manuscript. We are thankful to  Martin Lenter ,  Klaus Fuchs  and  Simon Plythe  for bringing Yumab to the project and active reading of the manuscript. We warmly thank  Anne-Céline Le-Fevre  for colocalization images,  Corinne Célinain  for mass spectrometry experiments and  Patricia Senneville  for the copyright requests.
Participants The participants were part of the MEMENTO Cohort (registration: NCT01926249), a 5-year longitudinal clinic-based study whose principal objective was to identify new phenotypes of participants who will develop dementia over time. The study design of the MEMENTO cohort has been extensively described elsewhere  10   different behavioral and psychological disorders, scored whether they are absent (score=0) or based on their frequency (score ranged 1-4) and severity (score ranged 1-3). Total score for a given disorder is calculated as frequencyXseverity for a total score ranging between 0 and 12. Implementation of the NPI in the MEMENTO cohort was limited to a systematic assessment of depression, anxiety and apathy, whereas assessments of other disorders, such as sleep disorder, were optional.
MRI evaluation Brain magnetic resonance images were acquired after a standardization of the imaging pro ss s by t n uro m n sp l z t m ( TI for " ntr pour l' qu s t on t l Tr t m nt s Im s" http://cati-neuroimaging. com/) 1314. MRI machines of 1. 5 and 3 Tesla were used for this study (the complete list of machines is provided in Supplementary 2 Appendix A). All MRI scans were centralized, quality checked, and postprocessed by the CATI to obtain standardized measurements for each participant. The datasets underwent two steps of quality check in the process to yield HV. MRI raw data were first quality checked to evaluate if no artefact (system or patient related) could endanger the reliability of subsequent image processing pipelines. Then the result of the segmentation tool was quality checked to ensure that no major segmentation failure could make the estimated volume unreliable.
Both steps of the quality check rely on systematic visual evaluation of trained raters. Segmentation results are graded on a 0-4 range, with 0 meaning completely wrong segmentation, 2 borderline segmentation (segmentation mistakes may have an influence on the resulting volume) and 4 perfect segmentation; volumes for grades lesser than 2 were not included in the analyses. The MRI protocol included 3D-T1 1 mm isometric sequences that were used to assess the total intracranial volume (TIV) with Statistical Parametric Mapping  15  and hippocampal volumes with the SACHA software  16. The principal MRI outcome was the hippocampal volume (HV -calculated as the sum of the right and left hippocampi in each participant) divided by TIV as a control for head size inter-subject variability. 2,171 participants with hippocampus volumes were included in the MRI analyses, as HV was not available for 152 participants, because no MRI was available or exclusion after CATI quality check.
The method for images processing with partial volume effect correction on untransformed PET images has been extensively described elsewhere  17. Briefly, a quality check was performed by the CATI team: frames were realigned, averaged and visually inspected for possible artefacts, including subject motion, mismatch between CT and emission scans and attenuation correction artefacts. The Rachel software, developed by the CATI, was used for  18  F Florbetapir PET image processing. Structural MRI images were coregistered to  18  F Florbetapir-PET images using SPM12 with visual inspection to detect any coregistration errors. Parametric PET images were then created for every individual, by dividing each voxel with the mean activity extracted from a combination of the whole cerebellum and pons as the reference region.
Additional limitations regarding dose and/or duration of BZD use include that we used the approximation of a daily use for pro re nata BZD prescription, and that these variables were calculated based on the immediate period prior to study enrollment, whereas lifetime exposure of BZD was not available in our study. These approximations in our data may explain why we could not identify the critical time period of BZD exposure that impacts amyloid deposition or hippocampal cell loss. Longitudinal well-controlled studies for dose and duration of BZD use may be more informative as to whether dose and/or duration of use influence the effect of BZD on amyloid accumulation and hippocampal volume and may ultimately reveal potential mechanisms involved in the BZD effect. Finally, we cannot exclude that other factors not included in our study may have confounded our results, such as history of anxiety disorders (which were not systematically assessed in the MEMENTO cohort, in contrast to depression) or sleep disturbance for which there was too much missing data since this dimension was not systematically asked and only rarely informed in the NPI.
NPI allows assessments for 12 head trauma with neurological sequelae, stroke occurring in the past three months, history of schizophrenia, or illiteracy. Baseline data collection included clinical examinations, neuropsychological testing, blood sampling and brain MRI. In addition, we included participants with 18 F Florbetapir PET scans (n=289) 11,12 , so as to replicate the previous findings on amyloid load and benzodiazepine use, from 2 ancillary studies (Insight-PreAD, AMYGING, NCT02164643). All participants signed an informed consent to participate in the study that was approved by the ethics omm tt " om t Prot t on s P rsonn s Su -Ou st t Outr M r III. " Benzodiazepine use and clinical assessments Participants were identified as chronic BZD users if they had used any type of BZD or Z- drug for at least 3 months in the immediate period prior to study enrollment.
Methods This systematic review and meta-analysis of individual participant data (IPD) will be conducted in interventional, prospective, double-blind, randomized, placebo-controlled trials with an independent duloxetine arm. According to a protocol registered on PROSPERO (systematic review registration-2019 CRD42019130488), we conducted a systematic literature review of relevant trials performed on adult participants aged < and ≥ 65 years old in a population suffering from a condition having EMA or FDA approval for duloxetine. In this report, we describe all eligible studies and present the outcomes that will be extracted for the IPD and the methods that will be used for data synthesis following the PRISMA-P recommendations (Additional le 1). The anticipated end date of the study is November 2022.
Information sources Searches were conducted in PubMed (to identify individual studies from published systematic reviews and meta-analyses of duloxetine), ClinicalTrials. gov, Clinicaltrialsregister. eu, data sharing platforms (ClinicalStudyDataRequest. com, YODA and Vivli), FDA drug approval packages and European public assessment reports and withdrawn applications from the EMA website. The review was performed on studies available in electronic databases from their date of inception to 31 May 2019.
Search strategy identi cation was systematic with different search strategies depending on the source. First, we searched PubMed for all systematic reviews and meta-analyses involving duloxetine for an approved indication. Then, individual trials were identi ed from these systematic reviews and meta-analyses. The search terms were as follows: "(Duloxetine AND Meta-Analysis[ptyp])". In ClinicalTrials. gov, the search was restricted to all interventional studies with adults and older adults, using "duloxetine" as the search term. In Clinicaltrialsregister. eu and in data sharing platforms, the search term was "duloxetine" with no lter applied. On the FDA website, FDA drug approval packages were downloaded from the FDA approved drug product, entering "duloxetine" as the search term. On the EMA website, European public assessment reports and withdrawn applications were selected, which were limited to reports on humans with no restriction on the authorization status and using "duloxetine" as the search term.
Collecting IPD A data sharing request was sent to all sponsors for which trials were spontaneously available on data sharing platforms. For the remaining studies, the request was sent to all corresponding authors, and if possible, a research proposal was addressed to each pharmaceutical sponsor on data sharing platforms (for Eli Lilly, Shionogi, P zer and AbbVie trials) or on the sponsor website (for Lundbeck, Takeda and Merck Sharp & Dohme trials). For willing collaborators, the terms of the collaboration will be speci ed in a data transfer agreement, signed by representatives of the data provider and of the recipients (Clinical Investigation Center, Department of Clinical Pharmacology, Rennes University Hospital, France). The collection of IPD is ongoing. The requested participant characteristics are baseline age, gender, intervention arm, duloxetine dose, duration of treatment, number of SAEs from baseline to endpoint, number of nsAEs from baseline to endpoint, study primary outcome and its values at baseline and at endpoint, type of quality of life scale used and its values at baseline and at endpoint.
Data items For each study, information will be extracted on: Characteristics of the study: year, country, number of arms with duloxetine and placebo, funding sources, con ict of interest, and condition; Characteristics of trial participants: mean age (and its standard deviation), gender, number of patients included in the analysis, and population of analysis used in the identi ed report (intention to treat, per protocol, other); Type of administration, dose and duration; Outcome measures as stated above (including the exact de nition of outcome (e. g. , MedDRA or other)).
In a randomized placebo-controlled setting, this outcome provides a global estimate of treatment safety, without the severity feature of the SAE. The e cacy on the clinical scale for each indication (i. e. , depression, anxiety, pain, and urinary incontinence): different scales with the same indication will be standardized by z-scores. This outcome will evaluate the clinical bene t in patients. The quality of life scores for each indication: the different scales will be standardized by z-scores. In studies multiple quality of life scales were used, a hierarchy was established by selecting scales that both resume health data in one unique total score and were the most used among the duloxetine trials. If the only available instrument in a trial did not permit us to resume data into one score (e.
Ethical Standards The study was conducted from May 2016 to February 2018 and approved by an institutional review board (IRB) from the University Hospital of Rennes (ref. 17. 12). All participants gave written informed consent. The study protocol conforms to the ethical guidelines of the 1975 Declaration of Helsinki. The Exercise Peripheral Artery Disease (PAD) study was registered with the American National Institutes of Health database under reference n • NCT03186391.
We define Total DROP as the lowest DROP value between proximal and distal electrodes on each limb. DROP was recorded in real-time by the in-house Oxymonitor (version 2019. 01. 05) free Software (https://imagemed. univ-rennes1. fr/ en/oxymonitor/download. php) as previously described  (15). As defined in a previous study, we considered a Total DROP ≤-15 mmHg accurate to diagnose arterial stenoses of ≥50% assessed by computed tomography angiography (CTA) as a gold standard  (7).
CTA data were transferred to a computer workstation (Advantage Workstation, AW 4. 6; GE Medical Systems) for analysis. The reformatted 1. 25-mm axial images, multiplanar reformats and Vessel Analysis© software (GE Healthcare, Milwaukee, WI, USA) were used to determine the grade of stenosis. The referring doctor of the patient ordered CTA at his or her discretion. CTA, used as gold standard, was performed to detect luminal arterial stenoses in each patient in our facility. Significant stenoses (≥50% of the diameter) at each artery level (aorta, common iliac artery, external iliac artery, internal iliac artery, common femoral artery, superficial femoral artery, popliteal artery on both sides) were reported by two blinded radiologists (AP and DB) who were unaware of the results of the exercise tests appointment.
Data Analysis Post-exercise pressure decrease, post-exercise ABI were calculated and results of exercise-TcPO2 were analyzed without knowing the results of CTA. Right Total DROP allows the detection of flow-reducing lesions in the following arteries: the aorta, the right common iliac artery, the right external iliac artery, the right common femoral artery, the right superficial femoral artery, and the right popliteal artery. Left Total DROP allows the detection of flow-reducing lesions in the following arteries: the aorta, the left common iliac artery, the left external iliac artery, the left common femoral artery, the left superficial femoral artery, and the left popliteal artery  (14).
Statistical Analyses Results are expressed as mean ± standard deviation. Continuous variables were expressed as mean and 95% confidence interval (CI), and categorical variables as numbers (percentages). Then, sensitivity, specificity, positive predictive value, and negative predictive value were calculated with their respective 95% CI. For the different combinations of exercise testing criteria, sensitivity, or specificity or accuracies were compared with McNemar's test. Statistical analyses were performed with SAS software, v. 9. 4 R (SAS Institute, Cary, NC, USA). For all statistical tests, a two-tailed probability level of p ≤ 0. 05 was used to indicate statistical significance.
The 13 C chemical shifts are referenced to adamantane. The contact time was set to 3. 5 ms, the recycle delay was set at 5 s, the initial 90 • pulse on 1 H to 3 µs with a radio frequency (RF) field of 83 kHz. 1 H SPINAL-64 decoupling was applied during the 13 C acquisition. The NMR spectra were acquired using TopSpin 3. 5 Bruker Software and processed with DM fit program  [42].
Acknowledgments: We are grateful to  K. Salim  ( Seqens, Longjumeau, France ) for kindly donating the Expansorb ® polymer samples. We thank  F. Laurent  and  J. Josse  from the  International Center for Research on Infectious diseases (Lyon, France)  for the VCM samples. We acknowledge  Institut de Chimie et des Matériaux de Paris Est (Thiais, France ) for providing access to the SEM-EDX and STEM-EDX facility,  E. Leroy  for technical assistance and  C. Jain-Beuguel  for her kind help. We also thank  P. Roger  and  L. Costa  for their help with the SEC experiments. MP thanks the  Région Centre-Val de Loire  for a PhD fellowship.
Funding: This research was funded by the  Paris Ile-de-France Region-DIM Respore  and by public grants by the  French National Research Agency (ANR)   ANR-16-CE18-0018 ,  ANR-10-LABX-0035 ,  80-Prime MITI CNRS  and IR-RMN-THC Fr3050 CNRS. Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable.
Such an identification can be achieved by comparison with some reference database(s)  [7] ; however, the databases at hand are largely incomplete  [2, 8, 9]. This is why de novo interpretation of the fragments, directly from the spectra, is a promising alternative. Determining the chemical formula of metabolites is generally used as a first step in the identification of their molecular structure. In  [1] , Böcker et al. initiated such study, where the problem of de novo identifying the chemical formulas of metabolites from tandem mass spectrometry spectra was formally modeled by the Maximum Colorful Subtree (or MCS) problem. Let µ be an unknown metabolite and s µ a tandem mass spectrum of µ. Intuitively, a solution of MCS represents the best possible "fragmentation scenario", called a fragmentation tree, of µ.
High-throughput methods for multi-temporal phenotyping based on remote sensing technologies are described. Tools for higherthroughput post-harvest phenotyping of seeds are presented. A guideline for approaching quinoa field trials including the collection of environmental data and designing layouts with statistical robustness is suggested. To move towards developing resources for quinoa in line with major cereal crops, a database was created. The Quinoa Germinate Platform will serve as a central repository of data for quinoa researchers globally.
To achieve this aim, insights into the broad performance spectrum of different varieties grown in a range of environments as well as an improved understanding of the genes underlying traits of agronomic importance are needed. Recently, genomic tools have emerged to support the development of quinoa germplasm for novel environments. Several novel genomic resources have been developed in the past decade, including bacterial artificial chromosome (BAC), expressed sequence tag (EST) libraries, and DNA-based molecular markers (see  [14] ), as well as, more recently, a chromosome-scale reference genome sequence of a coastal (or "lowland") quinoa accession (BioSample Accession Code QQ74)  [15]  and the resequencing of several wild and cultivated quinoas. Together, these are helping develop genomics-informed breeding programs and genetic studies to accelerate crop improvement  [14].
Quinoa Database The establishment of an international consensus for our methods in phenotyping quinoa field trials is the first important step in driving international quinoa research forward through allowing comparisons among field trials and facilitating collaborations. An important component of the phenotyping operation is the recording of all information needed for further exploitation of the data. These records need to be complemented with a platform that allows sharing of data generated with the herein described methodologies and facilitates access to the available datasets. Contribution of data to this database is of great value to (a) breeders and other people who want to start working with quinoa, (b) other researchers, and (c) to the team that shares their data. Considering the monetary and time cost of field trials, in addition to the phenotypic plasticity of quinoa, access to information on how quinoa varieties perform in different locations is highly valuable in providing decision-making support to growers and individuals who want to start working with quinoa.
Access to data from trials in a similar environment would help them to make informed decisions on what varieties might be performing best in their region. For other researchers, as well as the team that contributes the data, the importance of data shared in a database lies in the opportunities for collaborations that it creates. Many analyses require datasets from multiple locations and years. It is through collaborations that the speed of discoveries is accelerated. If a team has not published their data yet and wants to keep it private, it can still be uploaded to the database under a privacy setting through which the data remains accessible only to the person who uploaded it and optionally a defined list of other individuals (i. e. , the research team). In addition to these privacy settings, license terms can optionally be assigned to datasets before access to the data is granted.
In this case, data would only be accessed after the license has been accepted. Here, we present a central repository Quinoa Germinate Database. Available online: http://germinate. quinoadb. org (accessed on 15 August 2021), which was created using the Germinate platform  [42, 43]. The Germinate platform is used by many international organizations, including CIMMYT and data uploaded to Germinate will also become available through the BreedingAPI. This database allows storing phenotypic and genotypic data as well as germplasm passport data and environmental information. To upload a dataset, users need to first register to the database and data can only be uploaded through the use of standard data templates (https://github. com/germinateplatform/germinate/tree/master/datatemplates accessed on 15 August 2021) to ensure consistency between datasets.