dataesr/scientific-paragraphs-categorization huggingface dataset:
AE reporting has been criticised, with suboptimal detailing of the incidence/type of clinically relevant AEs cited as a common shortcoming of many clinical trial publications [11e15]. These safety data from KAMILLA, together with published results from the previous safety analysis  [9] , provide comprehensive information for health-care practitioners making treatment decisions about T-DM1 in the clinic. The previous safety analysis found that thrombocytopaenia and increased ALT were the most commonly occurring AEs with T-DM1  [9]. To better understand any associations between T-DM1 and AEs of interest, thrombocytopaenia, hepatic events, haemorrhage and cardiac dysfunction were investigated by combining related AE terms (eTable 1). Importantly, as seen in the safety analysis  [9] , grade !3 thrombocytopaenia was rarely associated with grade !3 haemorrhage-related AEs (of 66 patients with grade 3e4 thrombocytopaenia, 38 had no haemorrhage, 22 had grade 1e2 haemorrhage and 6 had grade !3 haemorrhage; see eTable 3).
Acknowledgements The authors are grateful to the patients and families for their participation in the KAMILLA study as well as the KAMILLA study investigators:  Noemia Afonso ,  Kosh Agarwal ,  Rajiv Agrawal ,  Gokmen Aktas ,  Oscar Alabiso ,  Emilio Alba Conejo ,  Joan Albanell Mestres ,  Juan Carlos Alcedo ,  Mehmet Aliustaoglu ,  Giacomo Allegrini ,  Alberto Alvarado Miranda ,  Isabel Alvarez Lopez ,  Michael Andersson ,  Eric-Charles Antoine ,  Silvia Antolin Novoa ,  Antonio Anton Torres ,  Rumen Antonov ,  Rodrigo Araujo ,  Caroline Archer ,  Antonio Ardizzoia ,  Tobias Arkenau ,  Pa ¨ivi Auvinen ,  Antonio Avella Mestre ,  Thomas Bachelot ,  Carlos Henrique Barrios ,  Urmila Barthakur ,  Jean-Francois Baurain ,  Julie Beaudet ,  Martin Becker ,  Mustafa Benekli ,  Nils Olof Bengtsson ,  Chantal Bernard Marty ,  Gianfilippo Bertelli ,  Giulia Bianchi ,  Laura Biganzoli ,  Claudia Bighin ,  Maria Isabel Blancas Lopez-Barajas ,  Jacques Bonneterre ,  Roberto Bordonaro ,  Joan Lluis Borras Balada ,  Simona Borstnar ,  Philippe Bougnoux ,  Sylvie Bourque ,  Frances Boyle ,  Etienne Brain ,  Christine Brezden-Masley ,  Margarida Brito ,  Russell Burcombe ,  Mohammed Butt ,  Antonio Carlos Buzaid ,  Branislav Bystricky ,  David Cameron ,  Mario Campone ,  Jean-Luc HoffmanneLa Roche , Ltd.
Quantification of stained cells To evaluate the IHC staining, the number of stained cells was quantified per area of tissue using entire tissue sections. The area was calcu- lated using the NDPview software (Hamamatsu Photonics, Herrsching am Ammersee, Germany). Gonocytes and oogonia were identified based on OCT4 staining; proliferating cells were identified by BrdU incorporation; apoptotic cells were identified by cPARP staining; meiotic germ cells were identified by γ H2AX staining (detects doublestrand breaks and therefore potentially also apoptotic cells); and Sertoli cells were identified by SOX9 staining. For all quantifications, tissue samples from at least six embryos/fetuses were included.
Acknowledgements The authors wish to thank the staff members at the  Departments of Gynaecology at Rigshospitalet and Hvidovre Hospital  for their help with the collection of the fetal tissue. The excellent technical assistance of the staff at the  Department of Growth and Reproduction , especially  Ana Ricci Nielsen ,  Camilla Tang Thomsen ,  Brian Vendelbo Hansen ,  Betina F. Nielsen  and  Ole Nielsen  is gratefully acknowledged. We appreciate the kind gift of FOXL2 antibody from  Dr D. Wilhelm  ( University of Melbourne ) and MAGE-A4 antibody from  Prof. G. Spagnoli  ( University of Basel ).
Genetically determined targets Genetics is a powerful mechanism for identifying and prioritising new drug targets with confidence. Mutations in BMPR2 (bone morphogenetic protein receptor type 2), the most common susceptibility gene for PAH, have focused attention on the transforming growth factor-β (TGF-β)/BMP signalling pathway  [36]. To date, the only treatment that has been used to target BMPR2 signalling in clinical trials is FK506 (tacrolimus)  [37] , which is currently in phase 2 (ClinicalTrials. gov identifier NCT01647945). FK506 binds its pharmacological target FKBP12 (12-kDa FK506-binding protein) and removes it from all three BMPR type 1 receptors (ALK1, ALK2 and ALK3), including those preferred by BMPR2 (ALK1 and ALK3). It is able to activate BMPR2-mediated signalling even in the absence of exogenous ligand and BMPR2.
DNA damage Inhibition of poly(ADP-ribose) polymerase (PARP) reverses PAH in several animal models  [43]. An open-label early phase 1 study of olaparib, an orally available PARP1 inhibitor approved for the treatment of BRCA (breast cancer gene)-related breast cancer, has been proposed in PAH patients in World Health Organization Functional Class II-III on stable vasoactive therapy (ClinicalTrials. gov identifier NCT03251872).
Inflammation and immune modulation Histological studies of the lung, the presence of circulating autoantibodies and high plasma levels of cytokines in PAH all point to inflammation as a driver of its pathology  [57]. Direct investigation of this currently lies with a clinical trial of the anti-CD20 monoclonal antibody, rituximab, in PAH associated with connective tissue disease (ClinicalTrials. gov identifier NCT01086540), and a trial of tocilizumab, an interleukin-6 receptor antagonist in PAH (ClinicalTrials. gov identifier NCT02676947) (table  3 ). Elafin, an endogenously produced elastase inhibitor, has now progressed to clinical trials  [58]. Elafin is pro-apoptotic and decreases neointimal lesions in lung organ culture  [59].
Oxidative and hypoxic stress Oxidative stress is another mechanism that has been targeted in PAH. In contrast to animal studies  [61] , a phase 2 study of an inhibitor of apoptosis signal-regulating kinase 1 (ASK1) failed to show overall improvement  [62]. A phase 3 study with bardoxolone methyl in scleroderma has been completed, following some signals of efficacy in phase 2 (ClinicalTrials. gov identifier NCT02036970). This drug induces the nuclear factor erythroid 2-related factor 2 (Nrf2), a transcription factor that regulates antioxidant proteins, and suppresses activation of the pro-inflammatory factor NF-κB. Increased expression of hypoxia-inducible factor (HIF), specifically HIF1α and HIF2α, in the PAH lung, genetic manipulation in animals  [63]  and naturally occurring mutations in humans (e.
Moreover, pre-clinical studies do not employ rigours such as sample size determination and randomisation, and they have not traditionally evaluated end-points used in human trials. Finally, it is possible that therapeutic responses result from off-target effects (i. e. enhanced blood flow to skeletal muscle), which are usually not evaluated in animal models  [78, 80]. Overcoming these potential pre-clinical factors will require a more complete understanding of relevant mechanisms in modern day phenotypes through initiatives such as PVDOMICS (ClinicalTrials. gov identifier NCT02980887), and advancement of technologies to improve applicability of ex vivo and in vitro assays. Establishing rigorous standards guiding pre-clinical animal model testing  [80]  will also likely result in improved selection of therapeutic candidates and minimise the impact of bias and false-positive results when tested in the human clinical trial environment.
v. / parameters and 6MWD s. c. prostacyclins) Trimetazidine NCT03273387 Single-centre phase 12 weeks PAH Changes in RV function (MRI) Changes in cardiac fibrosis level (MRI), NYHA 2 and 3 FC and LDH level Glycolysis: dichloroacetate Dichloroacetate NCT01083524 Two-centre 16 weeks PAH on one or more background Safety and tolerability Change in PVR, 6MWD, RV size and function open-label phase 1 oral specific therapies (MRI), NT-proBNP and lung/RV metabolism (FDG-PET) Modulation of Nrf2 pathway/NF-κB pathway: bardoxolone methyl Bardoxolone methyl NCT02036970 Multicentre phase 2 16 weeks PAH, PH-ILD, subset of patients Change in 6MWD Determine recommended dose range (LARIAT) RCT versus placebo with group 3 or 5 PH Bardoxolone methyl NCT02657356 Multicentre phase 3 24 weeks PAH-CTD Change in 6MWD (CATALYST) RCT versus placebo Bardoxolone methyl NCT03068130 Multicentre phase 3 Up to Patients with PH who previously Long-term safety (RANGER) open-label extension 5 years participated in RCTs with bardoxolone Metabolic syndrome: AMPK signalling and metformin Hormonal, metabolic NCT01884051 Observational 5 years PAH and healthy subjects Safety and biomarkers of mechanism and signalling interactions in PAH Metformin NCT03349775 Early phase 1 12 weeks PH and obesity Pulmonary vascular Effect on PA endothelial cell phenotypes haemodynamics at rest and on exercise RCT: randomised controlled trial; PH: pulmonary hypertension; RV: right ventricle; RVEF: right ventricular ejection fraction; MRI: magnetic resonance imaging; iPSC: induced pluripotent stem cell; LV: left ventricle; mPAP: mean pulmonary arterial pressure; PAOP: pulmonary artery occlusion pressure; PVR: pulmonary vascular resistance; RHC: right heart catheterisation; 6MWD: 6-min walk distance; NT-proBNP: N-terminal pro-brain natriuretic peptide; CPET: cardiopulmonary exercise testing; NYHA: New York Heart Association; FC: functional class; LDH: lactate dehydrogenase; FDG: 18 F-2-fluoro-2-deoxy-D-glucose; PET: positron emission tomography; Nrf2: nuclear factor erythroid 2-related factor 2; ILD: interstitial lung disease; AMPK: AMP-activated protein kinase; PA: pulmonary artery.
Objective A retrospective case-control study was conducted to evaluate whether frequent binge drinking between the age of 18 and 25 years was a risk factor for alcohol dependence in adulthood. setting The Department of Addictive Medicine and the Clinical Investigation Center of a university hospital in France. Participants Cases were alcohol-dependent patients between 25 and 45 years and diagnosed by a psychiatrist. Consecutive patients referred to the Department of Addictive Medicine of a university hospital between 1 January 2017 and 31 December 2017 for alcohol dependence were included in the study. Controls were non-alcohol-dependent adults, defined according to an Alcohol Use Disorders Identification Test score of less than 8, and were matched on age and sex with cases. Data on sociodemographics, behaviour and alcohol consumption were retrospectively collected for three life periods: before the age of 18 years; between the age of 18 and 25 years; and between the age of 25 and 45 years.
Patient and public involvement No patients were involved in setting the research question or the outcome measures, nor were they involved in developing plans for the design or implementation Open access of the study. Controls were healthy volunteers participating in medical research protocols and registered in the database of the Clinical Investigation Center with data on their gender, date of birth and contacts. The main results of the study will be displayed on the Clinical Investigation Center website. data collection Data were collected using structured interview with one psychiatrist for the AD cases and using a self-reported online survey for the non-AD controls. Data were retrospectively collected for three life periods: period 1, before the age of 18 years; period 2, between the age of 18 and 25 years; and period 3, between the age of 25 and 45 years.
Period 2 To enhance the accuracy of these retrospective data, two subperiods were defined: between 18 and 21 years and between 22 and 25 years. Data collected were student status, living at parents' home, relationship with parents, living in a couple, doing sport, smoking and cannabis use. A single variable was obtained from the data of the two subperiods: a 'yes' response for one or both subperiods was recorded as 'yes' for the entire period. For smoking, cannabis use and sport, the cumulated month of use for each subperiod was also collected and added to make the total cumulative month of use. Data were collected on alcohol consumption during this period. BD, defined as consumption of five or more alcoholic drinks (four or more for female students),  40  was categorised as frequent if more than twice a month, occasional if once a month or less and never if no BD 8 (table  1 ).
Statistical Analysis Data analysis was performed using Statistical Package for the Social Sciences® software (version 20. 0). The t-test was used to compare the means of marks between the control and SODAR groups. Fisher's exact test was performed to compare the frequency of right answers obtained from both groups in each of the theoretical knowledge questions. Cohen's d test was also utilized to measure effect sizes between both groups. The correlation between marks achieved prior to the study on the dental anatomy module and marks gained in the carving sessions of this study was conducted using the Pearson correlation test. P-value = 0. 05 was considered significant for all analyses.
These data were obtained from observations of producers and collections of fruits in the orchards during the study period. The susceptible period was between October 1 and December 15 for plum and peach, between March 1 and July 31 for citrus, between November 1 and January 10 for 'Eva' apple, between December 1 and January 30 for 'Gala' apple, and between December 15 and March 31 for pear. The months outside this period were considered the non-susceptible period.
Statistical analyses The comparative analysis of the means of the explanatory factors site, plant protection strategy and susceptibility period was performed using the Student-Newman-Keuls (SNK) test, considering the number of fruit flies collected in traps and fruits in all samples, and expressed as the number of flies per sample per day. Analysis of variance (ANOVA) was performed for the three crops whose sampling period was longer than three years: citrus, apple, and peach. The mean number of fruit flies collected per day in traps was compared with that collected in fruits (number of flies per sample per day) for citrus, apple, and peach during a three-year sampling period. The characteristic of each fruit fly community collected in fruits and traps was determined using the Shannon Wiener diversity index (H'), the Margalef index (α), and the Pielou's evenness index (E), according to the equations: H'= -Σpi ln pi, α= S-1/lnN, and E= H'/lnS, using Excel  software.
Thermal Expansion The thermal properties of composites were assessed on the NETZSCH 402 F1 Hyperion device (NERZSCH Group, Selb, Germany), in which the samples, with a dimension of 4 mm × 4 mm × 20 mm, were placed vertically. Samples were cut from dumbbell samples, produced by the injection molding method. Five specimens were used for each group. Dilatometric analysis consists of measuring the length of the sample (L) as a function of temperature (T). The length and temperature data were recorded and analyzed with Proteus software. The samples were cooled from 30 • C temperature to -60 • C, heated to 140 • C, and finally cooled to -60 • C temperature. The heating and cooling rates were kept constant at 10 • C/min. The measurement was carried out in an air atmosphere with a flow rate of 60 mL/min, while the measurement below 20 • C was possible due to the use of nitrogen.
The selected tests, end points and key references are highlighted in Table  1. In order to verify that the parameters of each test were optimal, they (except FERT) were tested in healthy subjects in order to verify that outcome similar to the reference publications (indicated in the text) can be obtained. Two test populations were used for validation (Biotrial data on file): 124 recordings at baseline of a crossover study conducted in 35 healthy male subjects aged 22-46 years (population A) and 21 healthy subjects (9 males and 12 females), aged 24-48 years and recruited later (population B). All were healthy and drug-free. The PRISM study itself is well on its way and is assessing quantitative biomarkers in schizophrenia (N = 72 SZ), Alzheimer's Disease (N = 72 AD) comparatively to healthy matched controls (N = 48).
5-12. 5 Hz], beta 1 [12. 5-18. 5 Hz], beta 2 [18. 5-21 Hz], beta 3 [21-30 Hz] and gamma  [30] [31] [32] [33] [34] [35] [36] [37] [38] [39] [40]. The area under the curve (AUC) of spectra segments will provide an estimation of power in each frequency band of interest. Absolute and relative powers will be analyzed for each band, both in eyes open and eyes closed conditions. For each band, the relative power will be the absolute power divided by the power on the total band. With respect to data quality control, under both test conditions, all recordings will be visually inspected to reject artifact segments such as high frequency noise caused muscular activity, environmental noise, or eye blinks. In case of sleep episodes occurring during the recording period, these will be manually rejected from the analysis.
The artifact free signal from each electrode will then be analyzed using a fast Fourier transform (FFT) to produce a power spectra. EEG flat maps will be created using absolute and relative powers estimated following IPEG definitions for frequency bands. To study resting brain circuitries, several electrode signals will be used simultaneously and additional computations will be conducted to assess potential relationships within or between specific brain regions. The correlations between an electrode and its neighbor (local properties) will be used with the cordance, that will ultimately provide data comparable with that obtained with brain imaging  (Bell et al. , 2012; Leuchter et al. , 1994). Connectivity at the scalp level can be quantified by several methods  (Sakkalis et al. , 2011) , with coherence  (Pascual-Marqui et al.
The epochs amplitudes will be corrected by subtraction of the average value from the pre-stimulus period (average amplitude on the [-500; 0 ms] window). Artefact rejection: epochs with a signal amplitude exceeding 75μV within 500 ms to +500 ms of the trigger will be rejected from the averaging process. Time frequency representations of the ERP will also be analysed: evoked power, induced power and phase locking factor. The power will be averaged on the relevant epochs. As auditory and visual P300 have a very different time and circuit properties, they will be analysed separately  (Katayama and Polich, 1999). The localisation of sources for P3a and P3b will be analysed using LORETA  (Bachiller et al. , 2015)  as well as connectivity  (Fujimoto et al. , 2013). Auditory P300 previously obtained on a large database (n = 124) produced the expected pattern latency and magnitude.
Epochs with a signal amplitude exceeding 75μV within -500 ms to +500 ms of the trigger will be rejected from the averaging process. The analysis processing used for the auditory P300 data can also be used in the visual P300 task, but there may be a need to take into consideration the extended latency of the P300 peak (Biotrial data on file) and therefore the different time windows of interest to quantify P300 occurrence. As expected, the highest P300 amplitude is observed in centro-parietal area of the flat map. This area matches the region of interest commonly used to study P300  (Oribe et al. , 2015).
Subjects will be asked to fixate on a point on the monitor and asked to count the number of rare tones (10% @ 1000 Hz) that will be presented amongst more frequent stimuli (90% @ 1000 Hz modulated by a 40 Hz sinusoid). As we usually generate ASSR using clicks and as amplitude modulation was used instead, in order to limit hearing issues in the elderly the efficacy of this type of sound to generate ASSR was first verified in population B (Biotrial data on file). A total of 110 tones were presented, each tone lasting 2 s  (Tan et al. , 2015). The ISI varied randomly from 3. 3 to 3. 7 s with the sound level of each stimulus set at 78 dB. The duration of this task is approximately 7 min. Artefact rejection will be performed by rejecting epochs for which the signal amplitude exceeds 75μV within the -500 to + 2000 ms of the trigger.
By using this period, the time course of both the evoked and induced power in the gamma band will be estimated on a 35-45 Hz band of interest between a -450 to 1950 ms period. The evoked or induced power will be averaged on a 500-1950 ms period. The 1000 Hz carrier modulated at 40 Hz elicits a robust response in gamma band in healthy subjects (Biotrial data on file). Evoked gamma is more pronounced using click presentations rather than a modulated 1KHz sinusoid. As the clinical population under test will also contain elderly individuals, where hearing loss across high frequencies are common, it is preferred to use narrow spectrum sounds. ASSR will be analysed as inter-trial coherence per hemisphere with a source modelling approach according to a robust model previously developed  (Edgar et al.
General operational aspects An identical EEG acquisition system will be employed for all the testing at the multiple clinical sites. The system includes an EEG amplifier and a computerized stimulation module (for visual and auditory stimuli). Raw data will be recorded using an eego ™ sports system (amplifier and software) from ANT neuro which provides amplification, filtering and sampling of the electrophysiological signal for up to 59 monopolar EEG channels and 2 bipolar EOG used for artefact rejection. The signal will be digitized on 24 bits. The sampling frequency will be set at 2048 Hz. Electromagnetic noise due to main power supply will be removed using a digital narrow 50 Hz centered notch filter. The EEG signal will be collected using Waveguard EEG caps from ANTneuro in which all electrodes are placed according to the International 10-10 electrode placement standard (Waveguard CA-202).
Acknowledgements We would like to express our gratitude to  Gerry Dawson ,  Amy Bilderbeck  and  Philippe Lhostis  for their expert contribution and the  European Innovative Medicine Initiative  for funding. The  PRISM  project (http://www. prism-project. eu)leading to this application has received funding from the  Innovative Medicines Initiative 2 Joint Undertaking  under grant agreement number:  115916. This Joint Undertaking receives support from the  European Union 's  Horizon 2020 research and innovation programme and EFPIA.
The influence of gravity on two-phase heat transfer represents a challenge to the design and development of thermal systems in which the tubes can be oriented at different inclination angles. In this regard, the present study is based on a global analysis of the effect of the channel orientation on the two-phase heat transfer coefficient, which was performed by collecting 5408 data points from independent published works that include flow boiling, flow condensation and heated gas-liquid flows at various orientations with respect to the gravity force. A comparison against existing prediction methods for two-phase heat transfer including the tube orientation effect has shown a very poor agreement, and no general tool is available in the literature to determine whether the effect of gravity is negligible or of major importance for specific applications.
For these reasons, a new prediction tool is proposed. The Inclination effect Ih is defined as the maximum expected variation of the heat transfer coefficient when the tube inclination angle is changed, with respect to the predicted value in a horizontal arrangement. Using an unconstrained nonlinear optimization, the Inclination effect is correlated with the most influencing nondimensional groups of parameters for boiling and condensation heat transfer, providing satisfactory agreement with the experimental data (MAE=17. 6% and 19. 3%, respectively). The Ih is found to be a decreasing function of the vapor quality and mass flux, and it increases with larger diameters and alongside heat flux in flow boiling. This new tool can be employed in the design process of condensing and evaporating units, since it is able to establish whether the heat transfer coefficient might be affected by the channel orientation or, instead, a typical correlation for non-inclined tubes can be used.