dataesr/scientific-paragraphs-categorization huggingface dataset:
Materials and methods To estimate changes in the FA composition of the French diet, we compiled and compared a variety of available data sources. For dietary composition, the most recent estimates came from the French Individual and National Study on Food Consumption (INCA), conducted in 1997 (INCA 1), 2006-7 (INCA 2) and 2017 (INCA 3). The CIQUAL database  (Ciqual, 2013)  was used to obtain the FA composition of products in the diet. Consumption of FAs has been estimated only since INCA 2. Estimates over a longer period (e. g. since 1960) were based on estimates of the quantities of raw products supplied and their FA content. To characterize trends in FA consumption, we compared several studies based on raw products supplied but which differed in FA content of the foods. For the FA composition of products in European countries, the FAO used a USDA database, since the FA composition of animal products remained constant during its study period  (Schmidhuber, 2007).
For example the Bleu-Blanc-Coeur ® (BBC) brand guarantees a minimum n-3 PUFA content of animal food products by establishing specifications for feeding practices 2. The practices are based on feeds (e. g. grass, alfalfa, flaxseed) with a high ALA content. Such changes in feeding practices have resulted in the marketing of animal products with a better FA composition than that from conventional production and that comply with nutritional recommendations, such as increased n-3 PUFAs, a decreased n-6:n-3 PUFA ratio and decreased SFAs (e. g. Kouba and Mourot, 2011). This FA composition varies greatly depending on the cut of meat or type of deli meat considered; therefore, we chose the database of the BBC association  (Schmitt et al. , 2018)  to obtain analysis for the same cuts of meat or dairy products from animals fed conventional rations or BBC rations.
The BBC database was chosen instead of the CIQUAL database because the latter does not contain animal products derived from animals fed flaxseedsupplemented feed. We then collected data on estimates of daily FAs consumption to analyze the major trends over the past 50 years:  Schmidhuber (2007)  and  Ailhaud et al. (2006 ) from the 1960s to 2000s, INCA 2 (2006 ) and INCA 3 (2012). Finally, to determine the most important factors, changes in apparent consumption of the FAs were interpreted from (i) changes in agriculture, especially ruminant production (quantities of feed concentrates used, types of roughage and raw products, and estimated changes in consumption of milk, dairy products and meat), and (ii) processing and food choices (quantities of animal products and oils consumed). Based on these findings, we identified the most promising avenues in agriculture and in consumption choices to meet the average dietary recommendations and then estimated their effects.
Conclusion FA intake of the French population since the 1960s was estimated using several methods (dietary composition, raw products supplied) and databases of food composition. Since we found convergent trends, this diversity makes the estimates robust and does not present an obstacle to identifying major drivers of the trends and drawing conclusions. The FA composition of the average French diet changed most mainly before the 2000s. This change was related to the increase in SFA intake up to the 1990s, due more to the increase in the quantity of dairy products (especially cheese) consumed (þ1. 2 g/day) than to that of oil (þ2 g/day). The strong increase in LA intake was due mainly to the increase in the quantities of oils consumed, especially linoleic sunflower oil. At the same time, n-3 PUFA intake increased by 0.
Acknowledgments F. M. and D. C-G. are grateful to the  Austrian Science Fund FWF  ( SFB-LIPOTOX F3007&F3012 ,  W1226 ,  P29203 ,  P29262 ), in particular for the project  P27893  (" Pro-autophagic polyphenols and polyamines for longevity ") and the  Austrian Federal Ministry of Education, Science and Research and the University of Graz  for grants " Unkonventionelle Forschung" and "flysleep"  ( BMWFW-80. 109/0001-WF/V/3b/2015 ). J. T. is funded by the  FWF  (W 1226,  DK Metabolic and Cardiovascular Disease) at the University of Graz. K. K. is a fellow of the  Doctoral College "Metabolic and Cardiovascular Disease"  ( FWF W1226 ) and was funded by the  University of Graz. We acknowledge support from  NAWI Graz  and the  BioTechMed-Graz  flagship project "EPIAge". G. K. is supported by the  Ligue contre le Cancer  (équipe labelisée);  Agence National de la Recherche (ANR) -Projets blancs ;  ANR  under the frame of E-Rare-2, the  ERA-Net for Research on Rare Diseases; Association pour la recherche sur le cancer (ARC) ;  Cancéropôle Ile-de-France ;  Institut National du Cancer (INCa) ;  Inserm (HTE) ;  Institut Universitaire de France ;  Fondation pour la Recherche Médicale (FRM) ; the  European Commission (ArtForce) ; the  European Research Council (ERC) ;  Fondation Carrefour ; the  LeDucq Foundation ; the  LabEx Immuno-Oncology ; the  RHU Torino Lumière , the  Seerave Foundation , the  SIRIC Stratified Oncology Cell DNA Repair and Tumour Immune Elimination (SOCRATE) ; the  SIRIC Cancer Research and Personalised Medicine (CARPEM) ; and the  Paris Alliance of Cancer Research Institutes (PACRI).
G. K. is supported by the  Ligue contre le Cancer  (équipe labelisée);  Agence National de la Recherche (ANR) -Projets blancs ;  ANR  under the frame of E-Rare-2, the  ERA-Net for Research on Rare Diseases; Association pour la recherche sur le cancer (ARC) ;  Cancéropôle Ile-de-France ;  Institut National du Cancer (INCa) ;  Inserm (HTE) ;  Institut Universitaire de France ;  Fondation pour la Recherche Médicale (FRM) ; the  European Commission (ArtForce) ; the  European Research Council (ERC) ;  Fondation Carrefour ; the  LeDucq Foundation ; the  LabEx Immuno-Oncology ; the  RHU Torino Lumière , the  Seerave Foundation , the  SIRIC Stratified Oncology Cell DNA Repair and Tumour Immune Elimination (SOCRATE) ; the  SIRIC Cancer Research and Personalised Medicine (CARPEM) ; and the  Paris Alliance of Cancer Research Institutes (PACRI).
Lee Moffitt Cancer Center and Research Institute DEBOXA for Inoperable NET Liver Metastases NCT03881306 Phase 1 Phase 2 Recruiting Xiangya Hospital of Central South University Stereotactic Body Radiation Therapy (SBRT) for Unresectable Liver Metastases NCT02185443 Phase 2 Recruiting University of Sao Paulo Everolimus After (Chemo)Embolization for Liver Metastases from Digestive Endocrine Tumors (EVACEL) NCT01678664 Phase 2 Active, not recruiting Federation Francophone de Cancerologie Digestive Efficacy and Safety of 177Lu-edotreotide PRRT in GEP-NET Patients (COMPETE) NCT03049189 Phase 3 Recruiting ITM Solucin GmbH Antitumor Efficacy of Peptide Receptor Radionuclide Therapy With 177Lutetium -Octreotate Randomized vs Sunitinib in Unresectable Progressive Well-Differentiated Neuroendocrine Pancreatic Tumor: NCT02230176 Phase 2 Recruiting Gustave Roussy, Cancer Campus, Grand Paris First Randomized Phase II (OCCLURANDOM).
However, studies have also shown that, as with other therapeutic classes, there is a significant gap between results achieved in RCTs and those achieved in real-life studies. A recent comparison of data from RCTs and an administrative claims and medical records database, in which baseline HbA1c ranged from 8. 34-8. 41%, showed that the mean change in HbA1c was -1. 30% in RCTs, but only -0. 52% in real-world data  [14]. Around three-quarters of the discrepancy was attributed to patient adherence rates, which were 29% in the real-world analysis and 95% in the RCTs  [14]. In addition, studies have revealed that patients enrolled in RCTs are often not representative of real-world populations but, instead, tend to be highly selected (fewer comorbidities, more compliant, managed by selected sites to participate in trials), more motivated and better supported (financially and administratively).
In one recent analysis, for instance, only 48. 0% of real-life patients in the US Diabetes Collaborative Registry (n = 182,525) met the main criteria for inclusion in the Liraglutide Effect and Action in Diabetes: Evaluation of Cardiovascular Outcome Results (LEADER) study  [15]. As these criteria were designed to select patients at very high cardiovascular risk, the other 52% of patients were eligible for prescription of liraglutide, but were not at high cardiovascular risk. Furthermore, in clinical care settings in northern Denmark, liraglutide users did not resemble patients included in the LEAD (Lower Educational Attainment Decision Aid) 1-5 trials, with almost three out of four routine clinical care initiators being classified as ineligible for the RCTs  [16]. In yet another study, patients enrolled in T2DM trials registered at ClinicalTrials.
Adherence Treatment adherence quantifies how well the treatment is maintained over time; this combines the notions of treatment observance (which describes how well a patient follows a prescription) and persistence (which describes the duration of time between starting a treatment and its discontinuation despite an ongoing prescription). Although there is no official standard or consensus on optimal levels of adherence, in general, an adherence rate ≥ 80% is considered sufficient for any treatment of T2DM to be effective  [25] , as this is associated with a decreased risk of all-cause mortality and hospitalization in such patients  [26]. In real-life studies, adherence is most often assessed based on prescription or drug-dispensing data from claims databases or electronic medical records and quantified using either the medication possession ratio (MPR) or proportion of days covered (PDC)  [25].
Effectiveness and tolerability Effectiveness and tolerability in real-life settings can be evaluated from studies that include either primary data collection or secondary analyses of data (such as claims databases, electronic medical records and existing registries). Both types of studies have limitations. Nevertheless, such studies can still provide data to evaluate long-term follow-ups (10-15 years) whereas, in RCTs, these typically last only 26-52 weeks  [6, 7, 9]. However, long-term extensions of RCTs are generally not good sources of data, as they are often not controlled and not representative of real-world patient populations  [27]. While insulin has been the gold standard for injectable medication for decades, few comparisons with GLP1-RAs have been performed in real-life settings, and these have mostly been limited to studies with exenatide, the first molecule to come to market  [24, 28].
5%, and the percentage of patients with HbA1c levels < 7. 0% and ≤ 7. 5% increased from 0. 4% at baseline to 31% and from 3. 3% at baseline to 51%, respectively  [36]. In a retrospective analysis of a US electronic medical records database study (2011-2015), roughly 30% of patients reached an HbA1c < 7. 0% after 6 months of treatment with exenatide QW (n = 2133), dulaglutide QW (n = 201) and albiglutide QW (n = 131)  [33]. In the prospective, multicentre Observational Study on Efficacy and Safety of Liraglutide in Subjects with Type 2 Diabetes (EVIDENCE), 3152 patients were treated with liraglutide QD  [23]. At the 2-year endpoint, 29. 5% of patients were still taking liraglutide and had HbA1c levels < 7. 0%  [23]. Taken together, these real-world data underscore the fact that GLP1-RAs are effective in reducing HbA1c and weight, and are also associated with a limited number of hypoglycaemias.
However, when response-defined as HbA1c < 7. 0%-is considered, the overall glycaemic control rates are still low. A couple of retrospective analyses have looked at the impact of treatment on cardiovascular outcomes and all-cause mortality. In a study of 2006-2014 data from The Health Improvement Network (THIN) database in the UK, the 5-year risk of having a major adverse cardiovascular event was significantly lower in the group with an add-on GLP1-RA (n = 419; exenatide BID or QW, liraglutide QD, lixisenatide QD) vs an add-on insulin group (n = 1584): adjusted hazard ratio (HR): 0. 27, 95% confidence interval (CI): 0. 14-0. 53; P < 0. 0001; propensity score matching of baseline characteristics  [37]. In another analysis of the THIN database  (2008) (2009) (2010) (2011) (2012) (2013) (2014) (2015) , the relative risk (RR) of all-cause mortality after a mean follow-up of 32 months was significantly lower in patients treated with a GLP1-RA (n = 8345; exenatide BID or QW, liraglutide QD, lixisenatide QD) vs matched controls receiving standard treatment (n = 16,541): adjusted incidence rate ratio: 0.
Prescription patterns, persistence and adherence Beyond efficacy, examination of prescription patterns, patient persistence and patient adherence may help physicians to better understand what to expect in their everyday practice. Patients' ability or willingness to take a medication, for instance, directly affects their glycaemic control and long-term outcomes  [39, 40]. In real-world settings, patient persistence and adherence to GLP1-RAs have mostly been measured using insurance and prescription databases, which contain no information on either efficacy or safety.
Persistence and prescription patterns The rate of treatment persistence is often defined as the number of patients still taking the prescribed treatment at the end of the evaluation period, and most definitions allow for a gap in treatment, with the length of the gap tending to change with the length of the evaluation period. In insurance and prescription databases, persistence includes discontinuations ordered by a physician as well as discontinuations initiated by the patient. Some definitions also assess treatment switches with the intention to capture this physician-initiated component. Persistence rates vary from one real-world study to the next and decrease with longer study duration (Fig. 1 )  [40] [41] [42] [43] [44]. In a retrospective cohort analysis of electronic medical records and national healthcare databases from six European countries (2010-2012), these data revealed that the proportion of patients undergoing treatment modification within 6 months (defined as treatment discontinuation, switch/change in therapeutic class, dose increases or off-label titration) varied significantly from country to country  [41].
Thus, with the QW regimen, the missed day is essentially invisible whereas, with the BID regimen, all missed doses are counted. In addition, in matched cohorts taking dulaglutide vs liraglutide (n = 2471) and dulaglutide vs exenatide QW (n = 1891), patients initiating dulaglutide had significantly higher proportions of adherence vs liraglutide (51. 2% vs 38. 2%, respectively; P < 0. 001) and exenatide QW (50. 7% vs 31. 9%, respectively; P < 0. 001)  [45]. Testing the impact of delivery system on adherence is more difficult as, currently, every delivery system is associated with a different medication. Thus, adherence data comparing dulaglutide QW, delivered with a prefilled pen or syringe, and exenatide QW, which requires reconstitution (in Europe) and delivery with a pen or syringe, are likely to reflect differences in delivery system as well as differences in efficacy and tolerability.
Indeed, when a US Truven Health MarketScan Research Databases analysis of 2014-2015 data studied the 6-month treatment adherence with dulaglutide QW and exenatide QW in 2415 matched pairs of patients  [43] , the adherence rate (PDC ≥ 80%) was 54. 2% with dulaglutide QW vs 37. 9% with exenatide QW (P < 0. 0001). Altogether, these studies show that adherence rates are low (< 60%) and remain a significant problem with injectable therapies in daily practice. Thus, industry-driven initiatives to develop formulations with less cumbersome schedules and easier delivery systems are ongoing, and include continuous subcutaneous delivery systems to replace daily and weekly injections with miniature subcutaneous pumps that deliver medication continuously for several months  [55] , as well as oral formulations  [56].
Acknowledgements We would like to thank  Hélène Dassule, PhD , for her editorial help in drafting this manuscript. Her contributions were funded by  Les Laboratoires Servier. 20 Invitations to congresses from  AstraZeneca ,  Dinno Santé ,  Eli Lilly ,  MSD ,  Sanofi  and Servier; and other research support from  Abbott ,  Dinno Santé ,  Janssen  and  Novo Nordisk. Hélène Hanaire  participated in advisory boards or symposia for Abbott,  Lilly ,  Medtronic ,  MSD ,  Novo Nordisk ,  Roche Diabetes Care, Sanofi-Aventis, Servier ,  Vitalaire M. Marre  participated in boards for Abbott,  Intarcia ,  MSD ,  Novo Nordisk ,  Sanofi  and Servier; received speaker fees from  Abbott ,  Eli Lilly ,  MSD ,  Novo Nordisk ,  Sanofi  and Servier; and received research support from  MSD ,  Novartis ,  Novo Nordisk ,  Sanofi  and  Servier.
Therefore, it was thought that an alternative differentiation tool that incorporates the full spectrum of lipid parameters and clinical variables would be of greater utility in differentiating FCS from sHTG. To this end, the clinical data from two phase 3 studies that evaluated the efficacy of volanesorsen (a secondgeneration antisense oligonucleotide inhibitor of apolipoprotein C-III production) for reduction of serum TG levels in patients with FCS (APPROACH) and sHTG (COMPASS)  [19, 20]  were analyzed to determine whether clinical data, other than fasting TG levels, can differentiate these two diseases. Clinical variables such as body mass index (BMI), pancreatitis history, and components of the lipid profile were analyzed individually and in groups to develop a predictive diagnostic tool that could provide physicians with a highly accurate preliminary differentiation between FCS and sHTG to assist clinical decision making and patient care.
A. Study Participants: APPROACH and COMPASS Patients included in this analysis were from the phase 3, multicenter, randomized, doubleblind, placebo-controlled APPROACH and COMPASS studies of subcutaneous volanesorsen treatment in adult patients  [19, 20]. In brief, the APPROACH study (NCT02211209)  [21]  (n 5 67) evaluated 300 mg volanesorsen once weekly for 52 weeks in patients with FCS, with 13 weeks of follow-up. Only patients who had genetically confirmed FCS were included in the analysis  [22]. Patients had fasting TG levels $750 mg/dL ($8. 5 mmol/L) at screening and a documented history of acute pancreatitis and were willing to follow a restrictive diet limited to #20 g of fat per day during the study lead-in and treatment periods. The COMPASS study (NCT02300233)  [23]  (n 5 114) evaluated 300 mg volanesorsen once weekly for 26 weeks for patients with polygenic sHTG (non-FCS), with 13 weeks of follow-up.
Acknowledgments The authors thank the patients who participated in the clinical trials and their families. Medical writing assistance was provided by  Complete HealthVizion , which was contracted and compensated by  Akcea Therapeutics, Inc. Financial Support: The APPROACH and COMPASS studies were funded by  Ionis Pharmaceuticals and Akcea Therapeutics Inc. Clinical Trial Information: APPROACH, ClinicalTrials. govno. NCT02211209 (registered 7 August 2014); COMPASS, ClinicalTrials. govno. NCT02300233 (registered 24 November 2014). Author Contributions: The authors meet the criteria for authorship as recommended by the  International Committee of Medical Journal Editors. They take full responsibility for the scope, direction, and content of and editorial decisions relating to the manuscript.
Lupuzor has been evaluated in phase-III clinical trials in the US, Europe, and Mauritius. Patients were given Lupuzor once a month by the subcutaneous route at a dose at 200 µg peptide/patient for 12 months. Across the whole study population, in those patients who had double-stranded (ds) DNA marker autoantibodies, Lupuzor demonstrated a superior response rate over the placebo (61. 5% vs. 47. 3%, p = 0. 0967), although these results were not statistically significant. Further data analysis demonstrated that in the Europe cohort (130 patients in total), Lupuzor plus SOC showed statistically significant reductions (71. 1% vs. 48. 8%, p = 0. 0218) in disease activity, compared to the placebo plus SOC in 79 patients who were anti-dsDNA autoantibody positive. An open label 6-month extension study from this original phase-III trial has been performed in 2019.
Funding: This research received no external funding. Acknowledgments: MR acknowledges the support and the use of resources of the  French Infrastructure for Integrated Structural Biology FRISBI   ANR-10-INBS-05  and of  Instruct-ERIC ,  Vincent Olieric  and the staff of the  Swiss Light Source  synchrotron for help with data collection and  Francois Stricher  for solving the structure of HSPA8. SM thanks the  French Centre National de la Recherche Scientifique , the  Laboratory of Excellence Medalis  ( ANR-10-LABX-0034 ),  Initiative of Excellence (IdEx), Strasbourg University , and the  University of Strasbourg Institute for Advanced Study (USIAS)  and  ImmuPharma France. SM also acknowledges the support of the  TRANSAUTOPHAGY COST Action CA15138  and the  French club of Autophagy (CFATG).
Effects of type 1 diabetes (t1d) on bone That T1D is associated with bone disorders was demonstrated many decades ago. Thus, as early as 1934 several cases of vertebral fracture were reported in patients with diabetes  [1]. Autopsy data confirmed the association a few years later by showing greater severity of osteoporosis in patients with T1D compared to controls without diabetes  [2]. Cohort studies were then carried out. Among them, a study from Israel found that the proportion of patients with diabetes who had at least one vertebral fracture was 20%, which was far higher than expected  [3]. The development of BMD measurement techniques, i. e. , single-energy then dual-energy X-ray absorptiometry, demonstrated that BMD values in patients with T1D were 30% to 50% lower than in non-diabetic controls  [4, 5].
8 mM leucine. mTOR activation was evaluated by measuring phospho-S6 kinase, phospho-4E-BP1 levels by western blot. S6K, 4E-BP1, and ERK2 were used as loading controls. (C) Flow cytometry analysis of cell size of Dram1 flox/flox MEF expressing Cre recombinase (À/À) or a control vector (fl/fl) grown under control or starvation conditions for 3 h. FSC, forward scatter. Boxplot and whiskers: 1-99 percentile. Bar represents median. *p < 0. 05. (D) Cell proliferation of Dram1 flox/flox MEF expressing Cre recombinase (À/À) or a control vector (fl/fl). Equal cell numbers were split on day 0 in complete DMEM. From day 2, cells were harvested daily and counted using Innovatis cell counter. Result shown is representative of 3 independent experiments. Data are mean ± SD. *p < 0. 05. (E) Dram1 flox/flox MEF expressing Cre recombinase enzyme (À/À) or a control vector (fl/fl) were starved for 3 h in EBSS containing glutamine prior to DMEM treatment for the indicated times.
Cells were fixed in 4% paraformaldehyde and stained for SLC1A5(V5-tag) and LAMP2. (F) Colocalization coefficients were determined using Zeiss Zen Black software (average of at least 25 cells). Data are mean ± SEM. (G) SCAMP3 was downregulated using siRNA in Saos TetOn-DRAM1-myc-his cells overexpressing V5-tagged SLC1A5, then, where indicated, treated with Dox for 24 h, and then starved for 3 h in EBSS before treatment with EBSS containing leucine for 20 min. mTORC1 activation was evaluated by measuring phospho-S6 kinase and phospho-S6 levels by western blot. Levels of total S6 kinase, S6, and actin were used as loading controls. DRAM1 expression was detected using an anti-Myc-tag antibody, and SCAMP3 knockdown was measured using an anti-SCAMP3 antibody. levels and phospho-IRS1 levels are significantly decreased in DRAM-1-null mice fed a HFD, when compared to similarly fed wild-type animals (Figures  6G, 6H , and S6H-S6K).