dataesr/scientific-paragraphs-categorization huggingface dataset:
The selected compounds are: ampicillin (negative control), carbamazepine, iopanoic acid, perchlorate, propylthiouracil and tetrabromobisphenol A. Each compound is tested and compared across all test systems, with different vertebrate classes and life stages. B/E are being assessed according to the AOP concept, ranging from the molecular, over morphological, up to the physiological level. Special emphasis is put on the identification of new THD-related B/E in fish, preferably in embryonic stages to comply with the 3R principle. Current focus of the experimental work in WP5 is on THD-induced disturbance of the development of eyes and swim bladder in fish. The data basis for the latter is very broad, and a putative AOP network has already been developed (see Figure  2 ). A similar data set on the effects THDs on eye development is currently being collected from literature and experiments performed by different ERGO partners.
Outreach and Implementation During the course of the project, ERGO will ensure close collaboration and harmonization with other European projects and initiatives on ED testing, e. g. , the ongoing JRC work on THD in vitro testing or different EU Tender projects on optimization of existing OECD TGs. Based on the outcomes of the knowledge management and transfer activities, ERGO will organize three focused workshops that will aim to transfer project knowledge to priority target users. The first workshop will be targeted at end users of OECD TGs, including contract laboratories and larger enterprises, intended to share the results of ERGO and feed them into policy and regulatory processes. A second workshop will be opened up to a broader range of actors involved in the regulatory process across Europe, sharing ERGO knowledge outputs such as scientific findings, recommendations, and datasets, that could be taken up and applied by others.
Figure1. ERGO (acronym for EndocRine Guideline Optimization) approach for testing and crossclass extrapolation of THD (thyroid hormone disruption) effects between mammalian and nonmammalian test guidelines. Based on existing information, chemicals with known molecular initiating events (MIE), key event (KE), endocrine activity (EA) and adverse effect (AE) in mammals will be investigated in silico, in vitro and in vivo, in fish and amphibians. A battery of biomarkers and endpoints (B/E) will be tested for EA and AE confirmation in the in vivo studies. Biotransformation data will be obtained when EA and/or AE cannot be confirmed. All existing and new data will be used for AOP (adverse outcome pathway) network development. Chemicals with unknown effects in mammals but known EA and AE in non-mammalian vertebrates will be investigated in silico, in vitro and for differences in biotransformation among mammals and non-mammalian vertebrates.
Figure1. ERGO (acronym for EndocRine Guideline Optimization) approach for testing and cross-class extrapolation of THD (thyroid hormone disruption) effects between mammalian and non-mammalian test guidelines. Based on existing information, chemicals with known molecular initiating events (MIE), key event (KE), endocrine activity (EA) and adverse effect (AE) in mammals will be investigated in silico, in vitro and in vivo, in fish and amphibians. A battery of biomarkers and endpoints (B/E) will be tested for EA and AE confirmation in the in vivo studies. Biotransformation data will be obtained when EA and/or AE cannot be confirmed. All existing and new data will be used for AOP (adverse outcome pathway) network development. Chemicals with unknown effects in mammals but known EA and AE in non-mammalian vertebrates will be investigated in silico, in vitro and for differences in biotransformation among mammals and non-mammalian vertebrates.
21t. J. Mol. Sci. 2020,21, x FOR PEER REVIEW 9 of 17 different vertebrate classes and life stages. B/E are being assessed according to the AOP concept, ranging from the molecular, over morphological, up to the physiological level. Special emphasis is put on the identification of new THD-related B/E in fish, preferably in embryonic stages to comply with the 3R principle. Current focus of the experimental work in WP5 is on THD-induced disturbance of the development of eyes and swim bladder in fish. The data basis for the latter is very broad, and a putative AOP network has already been developed (see Figure 2). A similar data set on the effects THDs on eye development is currently being collected from literature and experiments performed by different ERGO partners. The first results show that the eye development could serve as a meaningful B/E in already existing OECD TGs with fish, including early life stages.
In the Evaluating Nilotinib Efficacy and Safety in Clinical Trials Newly Diagnosed Patients study, adults with newly diagnosed CML-CP had higher rates and faster achievement of molecular response with nilotinib than with imatinib  (10). Nilotinib also demonstrated activity in adults with Ph+ acute lymphoblastic leukemia (ALL) in phase 1 and 2 studies  (11, 12). To evaluate the dosing of nilotinib in pediatric patients, we conducted a multicenter, open-label, phase 1 pharmacokinetic (PK) study (NCT01077544) in pediatric patients with Ph+ CML or Ph+ ALL. The study aimed to evaluate whether a fixed dose of 230 mg/m 2 twice daily achieved a nilotinib exposure similar to that observed in adults receiving the recommended dose of 400 mg twice daily, with the ultimate goal of identifying a dose for use in future pediatric studies.
PK analyses included all patients who received nilotinib on cycle 1 day 1 and had an evaluable PK profile (defined as having completed cycle 1 and/or had PK sampling sufficien 1 evaluable steady-state trough concentration. Single-dose PK parameters following administration of nilotinib on cycle 1 day 1 were estimated using noncompartmental analysis based on individual concentration-time profiles. AUCSS and CL/F were derived from drug-accumulation ratios based on steady-state trough concentrations of nilotinib on cycle 1 days 8, 15, 22, and 28. Geometric means for AUCSS and BSA-adjusted CL/F at steady state were compared with the reference data from adult patients treated with nilotinib 400 mg twice daily. Because the terminal phases of the concentration-time profiles on cycle 1 day 1 were not attainable due to the limitations of 24-hour sampling, some parameters (eg, AUC to infinity) could not be determined.
After cycling, an electrical measurement is performed at room temperature. We find similar resistance values as in the beginning of the cycle: 734 Ohm instead of 744 Ohm (-1. 3%) for R1 and 934 Ohm instead of 938 Ohm (-0. 4%) for R2. These data support the fact that the pressure inside the cavity remains the same. Fig. 7. Nanogauges resistance evolution during one thermal cycle under atmospheric pressure. At atmospheric pressure the two nanogauges are unbalanced as the pressure inside the sensor cavity is vacuum.
Parameters (temperatures, pressures, pH) were recorded and data were summarized in Table  2. Samples were collected every 5 minutes to determine the antiviral drug and antipyrine concentrations in the fetal vein side and in the maternal compartment. The total perfusion duration was 90 minutes. Samples were then stored at -80˚C until analysis. The concentrations were measured using ultraperformance liquid chromatography coupled with tandem mass spectrometry (Waters Xevo UPLC-TQD, Milford, MA, USA). Four different parameters were looked for, all calculated at steady state: mean fetal concentration (FC), mean maternal concentration (MC), fetal transfer rate (FTR) calculated as the ratio of FC to MC, clearance index (CLI ) which calculated as the ratio of the FTR of the study drug to the FTR of the control (= antipyrine).
This work was supported by the  University Paris Descartes. No conflict  -Gilles Peytavin  has received travel grants, consultancy fees, honoraria or study grants from various pharmaceutical companies, including  Bristol-Myers Squibb, Gilead Sciences, Janssen ,  Merck  and  ViiV Healthcare. - Minh Patrick Lê  has received travel grants from  Bristol-Myers Squibb  and  Janssen. -Tiffany Guilleminot: No conflict -Elisabeth Elefant: No conflict -Julien Stirnemann: No conflict - Marianne Leruez-Ville  declares receiving financial support for meeting expenses from BioMerieux outside the submitted work. -Yves Ville: reports non-financial support from  Ferring SAS , non-financial support from  Siemens Health Care , non-financial support from GE medical, outside the submitted work. This does not alter our adherence to PLOS ONE policies on sharing data and materials.
Updates in Global Regulatory Science, Pharmacovigilance, and Data Mining Cases of SJS/TEN and SCAR can be identified from many sources, including postmarketing adverse event reporting systems, disease registries, electronic health records (EHRs), literature, observational studies, and clinical trials. Cross-sectional studies used EHR allergy lists to identify SCAR cases. Causative drugs, including some rarely implicated in SJS/TEN in the literature, and differences in patient demographics, were reported  [23, 24]. An English-language PubMed literature search from 1980-2017 yielded 851 cases categorized as "probable" or "definite" SJS/TEN cases, 80. 6% of which were drug-induced (unpublished data). In FDA regulatory actions involving labeling for SJS/TEN from 2016-2018, products with SJS/TEN labeled in Warnings/Precautions at initial approval or added post-market included 17 hematology/oncology products, 8 antimicrobials, 6 radiocontrast agents, deflazacort, and febuxostat.
Post-market reports were the primary source of information for the labeling actions. The EMA Pharmacovigilance Risk Assessment Committee (PRAC) monitors the Eudravigilance database (>50 million records) and uses disproportionality tools (electronic Reaction Monitoring Report, eRMR) to identify emerging signals. Since July 2012, PRAC has evaluated 21 drugs for SCAR risk  [25]. From the Eudravigilance data, the fatality of SJS, SJS/TEN overlap and TEN is 7. 4%, 12. 1%, and 22. 4%, respectively. Performance and quality of pharmacogenetic tests assessing SJS/TEN drug-associated risks are also regulated by some health authorities; risks to patients with life-threatening diseases of treatment decisions based on erroneous testing are also considered. Health Canada's evaluations are becoming more context-aware, placing more emphasis on patients' needs, real-world evidence issues and collaborative health system models, which will inform evolutions in regulatory science and decisions about pharmacogenetic testing and patient safety.
ACKNOWLEDGEMENTS We gratefully acknowledge all the SJS/TEN patients and their families- Cheryl Barlow ,  Jim Barlow ,  Jacob Bonebreak ,  Allison Brimhall ,  Carolyn Burr ,  Arthur Burr ,  Janice Casebeer ,  Hsing-Chun Chang ,  Carl Chapman ,  Joseph Croasdaile ,  Tricia Eads ,  Jane Fleiss-Brogger ,  Amy Ford ,  Trevor Ford ,  Pawan Gaikwad ,  Katie Grant ,  Jamie Kidwell ,  Coleen Lambert ,  Trent Lowe ,  Grace Lu ,  Alysia MacGrotty ,  Mark Mills ,  Jeff Niemeyer ,  Anastasia Patrignani ,  Deborah Patrignani ,  Christopher Patrignani ,  Amani Saini ,  Keith Stryker , and  Brock Whale , for their participation in the SJS/TEN 2019: From Science to Translation conference. We appreciate all participants not listed as co-authors who attended and provided important insights regarding SJS/TEN at the meeting.
Funding was also supported by the  University of British Columbia Faculty of Medicine; University of British Columbia Faculty of Pharmaceutical Sciences; BC Children's Hospital Research Institute ;  Dr. Hongsheng Wang  ( Institute of Dermatology, Chinese Academy of Medical Sciences & Peking Union Medical College ) and  Dr. Wen-Hung Chung  ( Chang Gung Memorial Hospital); British Columbia Provincial Health Services Authority; Stevens-Johnson Syndrome Consulting Group, Inc; Eli Lilly Canada, Inc; Murdoch Global University, Australia, Dubai, Singapore ; Dynacare; Illumina;  Sandoz Canada, Biopharmaceuticals ;  Tissue Tech /Ocular Surface; Pharmigene,  Inc. Dr. Stuart MacLeod. This publication has emanated in part from research supported in part by a research grant from  Science Foundation Ireland (SFI)  under Grant Number  16/RC/3948  and co-funded under the  European Regional Development Fund and by FutureNeuro industry partners.
T. Bellón 's research was supported in part by grant  PI18/00718  (cofounded by FEDER) from  ISCII, Spain. S. J. Divito  has received funding from  National Institutes of Health  ( NIH DP5OD023091 ). M. E. Lacouture is funded in part through the  NIH/NCI Cancer Center Support  Grant  P30 CA 008748. M. Pirmohamed wishes to thank the  MRC Centre for Drug Safety Science , and the  International Serious Adverse Event Consortium (ISAEC)  for research support. S. I. Hung 's and  W. H. Chung 's research were supported in part by a grant ( MOST 108-2320-B-182A-023 -MY3 ) from the  Ministry of Science and Technology, Taiwan , and research grants ( CIRPG3I0041 ,  CIRPG3I0021 ) from  Chang Gung Memorial Hospital, Linkou Branch, Taoyuan, Taiwan. The  German Registry of Severe Skin Reactions (dZh) , representing the German part of the multinational RegiSCAR-study since 2003, was mainly funded by a research grant from the  European Commission  ( QLRT-2002-01738 ) and by a grant from the  Federal Ministry for Education and Research (Bundesministerium für Bildung und Forschung (BMBF) ; grant no.
The CQAs correspond to the chemical, physical and biological properties of the product. As well as the type of assay, they have to be defined within an appropriate limit, range or distribution to ensure quality and safety of the product. For cell therapy product and for clinical-grade iPSC, the CQAs include identity, microbiological sterility, genetic fidelity and stability, viability, characterization and potency. In the last few years, there was a common effort made on the banking and the quality control of the iPSC lines. After a series of workshop, adaptation to iPSC of the established recommendations and guidance realized by the International Stem Cell Banking Initiative (ISCBI) for human embryonic stem cell banking, has generated initial recommendations on the minimum dataset required to consider an iPSC line of clinical grade  [46].
Data The following datasets were used in our study, all covering the period ranging from 2014 to 2016: 1. The altimeter-derived sea surface currents computed at CLS (the list of undefined abbreviations is available at the end of the manuscript) in the framework of the DUACS project and distributed by the CMEMS Sea Level Thematic Assembly Center: two different products were used, referred to as "2SAT" and "4SAT". Both products are gridded data provided on a regular 1/4 The SST daily observations are the REMSS processing centre: we used the high resolution product based on the combination of microwave (from TMI, AMSR-E, AMSR2, WindSat and GMI) and infrared (Terra MODIS, Aqua MODIS, VIIRS) data. These SST observations are corrected using a diurnal model and represent a foundation SST ( 10 m depth)  [38, 39].
This operation was repeated for each of the SST datasets involved in our study. The only difference with respect to RS18 is that a common 2002-2017 period was chosen for the OSTIA and MUR SST (constrained by MUR SST data availability). As an example, maps of h and σ u/v are provided as Supplementary Materials (Figure  S1 ). Finally, RS18 also pointed out the need of an empirical calibration of h to optimize the OPC reconstruction. Indeed, based on comparisons with in-situ measured currents (see also Equation (  6 )), they obtained the best global performances if h was increased by a factor of three. In our study, we rely on the Piterbarg 2019 equations calibrated as in RS18, while specific calibrations are derived for the OPC based on OSTIA and MUR SST. Our calibration factor (c h ) varies from 1.
Reconstruction Based on REMSS Data In a good agreement with RS18, the OPC computed using the REMSS data exhibit a PI exceeding 20% (up to 24% locally), with better performances for the meridional component of the motion and in the equatorial band. The results indicate that our method is more efficient when applied to low-quality altimetry products, as for the 2SAT case (see also  Pascual et al. 2006 [37] ). However, still in agreement with RS18, Figure  1  shows that even the 4SAT geostrophic currents do benefit from the optimal combination with SST. Indeed, local maximum improvements range from 10% at mid-latitudes to 20% in the equatorial band for both the zonal and the meridional currents. Therefore, combining the altimeter-derived currents with SST data is advantageous for both altimetry products based on information from two altimeters (like in the early altimetry era) and more recent versions combining observations from several altimeters.
Reconstruction Based on OSTIA Data Here we present the OPC derivation based on the use of OSTIA SST. The results are given in Figure  2. The overall performances of the OSTIA OPC are consistent with the reconstructions obtained with the REMSS SST, as shown in Section 3. 1. The regional variability of the PI is analogous, indicating that the optimal reconstruction brings larger benefits for the 2SAT case, particularly for the meridional component of the currents and in the equatorial band. However, the OSTIA SST data are smoothed to fulfill operational requirements in numerical weather prediction (https://data. noaa. gov/dataset/dataset/global-sst-sea-ice-analysis-l4-ostia-uk-met-officeglobal-0-05-daily-2013-present1). According to Equation (2), one may expect average reduced performances than in the REMSS case, mostly due to the smoothing of the spatial SST gradients.
Reconstruction Based on MUR Data The OPC derived from the MUR SST are here presented for the 2SAT case. The 4SAT OPC, except for the averaged lower improvements, exhibit similar regional variability and dependence on the local SST spatial gradient magnitude (|∇SST|). The results of 4SAT OPC are provided as Supplementary Materials (Figures  S3  and S4 ). The MUR OPC showed reduced performances than in the REMSS and OSTIA cases. This is evident from Figures  3  and 4. The zonal degradation area found at high latitudes is even more evident than in the REMSS-based optimal reconstruction. The zonal OPC are degraded compared to the Altimeter currents below 45 • S as well as in the equatorial Pacific and Indian Oceans. On a global average, the zonal OPC degradation is also confirmed by a negative PI, whose minimum value can go down to -4%, as shown by Figure  4.
The optimal combination was tested with three global L4 SST datasets: the REMSS, OSTIA and MUR SSTs. These datasets led to different performances in deriving the global ocean OPC. The regional variability of the optimal reconstruction has been described in Section 3, while the global percentage of improvement is here discussed as a function of the local |∇SST| for the 2SAT OPC (Figure  4 ). The 4SAT case is analogous and is provided as Supplementary Materials (Figure  S4 ). On average, the PI depends on the magnitude of the local spatial SST gradient. For the meridional PI, all the reconstructions indicate a fairly linear increase up to |∇SST| 4×10 -5 • C• m -1. For even larger SST gradients the PI can further increase, as for the REMSS and MUR cases or stabilize as for the OSTIA OPC. For the zonal case, we get similar behavior in terms of the PI linearity, except a decreasing tendency in areas of highest SST gradients.
Indeed, the very high nominal resolution of this product should in principle allow a more accurate description of the surface dynamical processes as also emphasized by  [44, 48]  and references therein. In order to further investigate this point, we performed a spectral analysis of the three SST datasets used in our study (Figure  5 ). Although a thorough quality assessment of the different SST products is out the scope of our paper, this analysis provides a possible explanation for the anomalous behavior of the MUR OPC. The mean spatial spectral content of the REMSS, OSTIA and MUR SST was analyzed in a test case during wintertime, focusing on scales up to 10 km. This was carried out computing the Power Spectral Density (PSD) via wavenumber spectral analysis in a land-free area of the North Atlantic, on January 1st 2016.
Afterward, the OSTIA spectrum begins to separate, indicating a decreased amount of spatial variance at finer scales, eventually flattening around 50 km. On the other hand, the REMSS and MUR SST exhibit lager PSD than the OSTIA SST, with a dominance of MUR until scales of 15 km, where REMSS is instead quite flat. If we consider the different nature of the three SST datasets described in Section 2, this is the expected spectral behavior of the input SSTs for our application. If the same spectral analysis is performed in the Northern box (Figure  5c ,d), i. e. , where the MUR SST looks smoother, the spectral properties of the MUR and REMSS SST are inverted. Indeed, the REMSS spectrum is characterized by larger PSDs at scales lower than 100 km. Therefore, the REMSS SSTs are associated with the finer effective spatial resolution in the Northern Area (36 • N to 40 • N).
This result is indicating that the global scale OPC based on MUR data can be negatively affected by unequal effective SST resolutions in different areas of the ocean. Visual inspection of the MUR SST fields evidenced that this non uniformity can happen throughout the year in different areas of the ocean. This spectral inconsistency can have drawbacks on the computation of the SST spatio-temporal gradients, in which non physical dynamical structures can be recognized. An example is provided in Figure  6 , showing |∇SST| maps on three different dates in the Gulf Stream, Kuroshio Current and Agulhas Current areas. On the other hand, the REMSS and OSTIA SSTs did not evidence non-homogeneities in the effective resolution of the L4 fields, being coherent with the example provided in Figure  5  during the period 2014-2016.
Based on recent works  [33, 47]  we attempted to optimize the surface currents retrieval by combining the altimeter-derived geostrophic currents with satellite SST from Infrared (IR) and Microwave (MW) sensors. Our study was based on three different L4 SST estimates: a dataset provided by Remote Sensing Systems, fully based on the optimal interpolation of satellite observations (IR and MW), and two additional datasets based on the optimal interpolation of satellite and in-situ data, i. e. , the OSTIA and MUR SSTs.
Acknowledgments: The Authors thank the three anonymous Reviewers for providing valuable comments to improve the manuscript. D. Ciani  acknowledges  S. Marullo  and  A. Pisano  for the discussions on the SST data. This paper also benefited from fruitful discussions with  J. Vazquez-Cuervo ,  J. Gomez-Valdes ,  M. T. Chin  and  M. Bouali  during the Ocean Sciences 2020 meeting in San Diego. Finally, the Authors thank the members of the Remote Sensing Editorial Office for taking care of the review process and publication of this manuscript.
P166 Serum irisin in relation to insulin resistance and osteoporosis Ji Eun Jun a , You-Cheol Hwang a , In-Kyung Jeong a , Kyu Jeung Ahn a , Ho Yeon Chung a , Eui-Hyun Kim b a Endocrinology and Metabolism, Kyung Hee Univ Hosp at Gangdong, Seoul, Republic of Korea b Endocrinology and Metabolism, Daegu Fatima Hospital, Daegu, Republic of Korea Irisin is a muscle-secreted protein which has been proposed to regulate energy homeostasis and bone metabolism. Considering the physiological role of irisin, the aim of this study is to evaluate the association of serum irisin with insulin resistance and osteoporosis. We conducted a cross-sectional study including 40 female subjects who had never been treated for osteoporosis. We collected the data of clinical characteristics, glycemic and lipid parameters as well as bone turnover markers.