dataesr/scientific-paragraphs-categorization huggingface dataset:
Requests for screening kits Requests for new kits were made to the SBSC, which logged both the requests using the tear-off slip and the returned kits. It was not possible to identify email or telephone requests relating to this project due to the high volume received through these means daily. For the purposes of comparison, the SBSC also provided data on total number of requests for a replacement kit made by each of the recruited practices during the intervention period (plus one extra month to allow time for requests to come in) and for equivalent periods at 6 months, 1 year and 2 years before the intervention.
Questionnaire and interview data The feasibility parameters and mechanisms to be investigated are available in online supplementary file 1. Brief end of study questionnaires were developed for primary care and bowel screening staff. The questionnaires comprised closed and open-ended questions and focused on intervention acceptability and potential impact on workload. Semi-structured interviews were carried out with members of the practice team (aiming to interview the practice manager and at least one GP or practice nurse). Interviews sought to ascertain views on the running of the brief intervention, its acceptability and its overall feasibility as part of routine primary care.
Data analysis Templates were created using SPSS V. 19 for Windows  40  to collect data on the practice proforma and the end of study questionnaires. Quantitative data from the SBSC, proformas and end of study questionnaires were analysed using descriptive statistics (summaries, frequencies and cross-tabulations). As we had a purposeful sample of practices and a non-random sample of patients, no inferential statistics were calculated. 41 nd of study interviews were digitally recorded and transcribed verbatim. Qualitative data were analysed using thematic analysis informed by a framework approach including techniques of familiarisation, coding, indexing, charting, mapping and interpretation  42 43  assisted by QSR NVivo V. 7 software. 44 This approach was considered appropriate due to the pre-existing feasibility parameters being tested.
Identified themes were considered in the context of these parameters and interpreted according to existing theory and research. Scrutiny both within and across transcripts ensured that the analysis encompassed all perspectives and used the whole dataset. All transcripts were read by two researchers (DC and NC) and 50% were subject to triple initial coding (DC, NC and CC). The initial coding framework was developed by DC and was reiterated following discussion, with any discrepancies explored and accounted   23  The lower the decile number, the higher the deprivation levels. Pop, population; QOF, Quality and Outcomes Framework; SIMD, Scottish Index of Multiple Deprivation.
Acknowledgements Bowel screening data were obtained from the  Scottish Bowel Screening Centre in Dundee ; we thank all staff for their assistance and for completing the end of study questionnaires. We acknowledge the support and advice from  NHS Lothian , which provided the practice lists used for recruiting practices and the help from  NHS Scotland  which provided the leaflets in Polish. We thank  Dr Robert Scully  for his help with medical acronyms/terms in the intervention proformas and  Dr Ewan Gray  for his advice when revising this manuscript. We also thank the reviewers for their comments and recommendations. We are very grateful to each GP, practice nurse, healthcare assistant and practice manager who agreed to take part in the study, gave up their time to be interviewed and completed the end of study questionnaires.
e. the actual threshold is determined by the detector acceptance and efficiency of the muon trigger). The same trigger logic was used during the pp and PbPb data taking periods. In order to select a sample of purely inelastic hadronic PbPb (pp) collisions, the contributions from ultraperipheral collisions and noncollision beam background are removed offline, as described in Ref. [36]. Events are preselected if they contain a reconstructed primary vertex formed by at least two tracks and at least three (one in the case of pp events) HF towers on each side of the interaction point with an energy of at least 3 GeV deposited in each tower. To further suppress the beam-gas events, the distribution of hits in the pixel detector along the beam direction is required to be compatible with particles originating from the event vertex.
7%), N MB events in PbPb data (3%), and tracking efficiency (0. 6% for pp and 1. 2% for PbPb data) are considered as global uncertainties. The total systematic uncertainty for v 2 is estimated by summing in quadrature the contributions from the yield extraction and efficiency corrections. The range of the final uncertainties on prompt and nonprompt J/ψ v 2 results is between 10 and 57%, and 37 and 100%, respectively.
Acknowledgements We appreciated discussions with  Steffen Glaser  and  Angela Otto. We thank the  Bavarian NMR Centre  for access to the NMR spectrometer and  GE Global Research Europe  for granting access to the hyperpolarizer. We acknowledge support from  EU  Grant No. 294582  (MUMI),  BMBF  ( FKZ 13EZ1114 ), and  DFG  ( SFB 824 ). G. S. is supported by the  Deutsche Forschungsgemeinschaft  ( SFB824/C9 ) and the  DKTK Joint Funding Program.
However, behind this common terminology we need to acknowledge the existence of a heterogeneous reality  (Woolf 1993). While some oppida were occupied only for one or two generations, others have relatively long histories. If some display characteristics that can be described as urban (e. g. , Manching, Bibracte, Corent), others seem to have been nearly empty (e. g. , Zarten/Tarodunum, Finsterlohr). Some were several hundred or even more than 1000 ha in size (e. g. , Kelheim, Heidengraben), whereas others were no larger than 10 ha (e. g. , Otzenhausen, Hrazany) (for a general overview of the data, see Fichtl 2005a, 2012a and the database http://www. oppida. org/). Over and above this diversity, the most important common denominator of the oppida is their impressive fortification systems, which combined a defensive, ostentatious, and symbolic function  (Fichtl 2010a; Ralston 2013).
Dipstick albuminuria greater than 30 mg/dL is independently associated with lower rates of AKI recovery at 30 days in patients with sepsis  [40]. Another promising biomarker for recovery is osteopontin  [41, 42]. In general, trials evaluating biomarkers for prediction of recovery after AKI have been small and focussed predominantly on the differentiation between transient AKI and AKD. Identification and Validation of Biomarkers of Acute Kidney Injury Recovery (ClinicalTrials. gov Identifier: NCT01868724) was a multicentre study to validate biomarkers specifically for major adverse kidney event (MAKE) and major adverse cardiac events (MACE) following an episode of AKI in ICU. The results are still awaited. Hopefully, the increasing insights into the molecular mechanisms of renal recovery will lead to new biomarkers specific to the repair process.
Study design This study used an abbreviated version of the General Inpatient Survey (GIS), a validated instrument designed for use in the NHS  [15, 16]. The GIS questionnaire is designed for elective and emergency patients and was modified for use in the purely emergency setting by removing questions specifically concerning elective patients. Ethical approval was sought from the South East Scotland Research Ethics Service (ref NR/1412AB6), and a waiver obtained to proceed without formal ethical review, as the project was limited to using data obtained as part of usual care relating to the evaluation of service delivery. This study included sequential patients undergoing emergency intra-peritoneal surgery within a four-week study period, including those who had undergone intraperitoneal gynaecological surgery, but excluding caesarean sections.
Data analysis A continuous overall satisfaction score out of 10 for the whole inpatient experience was used in univariable analysis. Questions were structured using a three point Likert scale, with participants asked if they had experienced a particular variable at all times (1), sometimes  (2)  or not at all (3). If the question concerned a negative experience, for example noise at night, participants were asked if the had experienced that variable never (1), sometimes  (2)  or at all times (3). Responses combined into dichotomous categories for analytic purposes using a "top-box" approach, comparing the mean overall satisfaction score of those who had experienced a particular variable at all times (1), to that of those who had not (2-3)  [17] [18] [19]. The statistical significance of the association between experiencing a variable at all times and the mean overall satisfaction score was tested using the Mann Whitney U test.
Acknowledgements M. C. and Ł. K. received financial support from the  NANOSPIN  under Grant  PSPB-045/2010  from  Switzerland  through the Swiss Contribution, W. S. acknowledges  National Science Center, Poland , Grant No. 2015/17/D/ST3/00500 , J. K. acknowledges  DEC-2012/05/E/ST7/00240 , T. S. acknowledges Grant Harmonia No. UMO-2012/04/M/ST7/00799. S. v. D. and L. Y. acknowledge financial support from the  Academy of Finland  (Grant Nos. 12286361  and  13293929 ) and the  European Research Council  ( ERC-2012-StG 307502 ). Microfabrication process was performed at  Academic Center for Materials and Nanotechnology of AGH University. TEM analysis was conducted at the  Aalto University OtaNano -Nanomicroscopy Center (Aalto-NMC ). M. C. acknowledges  AGH University Dean 's Grant No. 15. 11.
Statistical analyses We analyse associations between 4-year low back pain and each of the four activity of daily living outcomes as measured in 2013 (ie climbing stairs, walking 100 metres, bending/kneeling, and getting dressed). Each functional limitation model included the longitudinal 2009-2013 LBP category (never-reverting-incident-chronic) as the independent variable of interest. Multivariate logistic regression was used for analyses reporting Odds Ratios and 95% Confidence Intervals, adjusting for the potential confounders. Individuals with missing data for any given analysis were excluded (<5% for each variable), thus totals could vary slightly due to available information.
ACI data will inform the new Australian and New Zealand Hip Fracture Registry. This 2015 audit assessed pain management in the Emergency department, Peri-operative setting and Rehabilitation. The audit confirmed the elderly population (mean age 86), appropriate assessment of pain scores (hourly upon presentation in 82% of patients). Analgesia prescribing varied across the cohort. Local nerve blocks were used in 35% of patients in Emergency department. Post op analagesia was determined to be reasonable with only 18% of patients reporting severe pain, which may reflect under utilisation of neuropathic analgesia (14%). Inappropriate use of NSAIDS were found in 10% of patients. In response to the audit findings the team are developing a standardised pain pathway during the hospital journey for the patient.
Recruitment Participants were recruited by emailing databases of NGO members, companies and public organizations (with a total of approximately 300 addresses). In the e-mail we asked candidates if they were willing to take part in research, provided they met the criteria for interview, and/or would be willing to forward the email to others who might be interested. We compiled a list of 73 volunteers (42 men and 31 women) for interview, although not all of them met the criteria or confirmed their availability after the initial contacts. After verifying the inclusion and exclusion criteria, we drew up two lists (one for men, the other for women) with names listed in order of their response to our e-mail. The first ten names were interviewed from both lists. Two men dropped out of the list and contact was therefore made with the 11 th and 12 th candidates.
However, the capacity to lose weight and the associated metabolic improvements show significant variability in humans, even under the same controlled dietary regimes. To understand the molecular basis for these differences we screened the plasma expressions of over twelve hundred proteins in 500 overweight and obese subjects to determine whether we could predict at baseline the weight loss outcome of 8 weeks LCD diet (800 kcal per day). As discovery data to construct a weight loss predictive model we used the Pan-European cohort DiOGenes AGING (Albany NY)  (Diet, Obesity and Genes, Larsen et al. , 2010). To select weight loss predictive proteins we deployed elastic net bootstrap estimation of high-dimensional regression (Chatterjee and Lahiri, 2011) adjusting for gender, age and BMI at baseline.
We evaluated the accuracy of our predictive model on the data set of 500 independent subjects from Ottawa Hospital Weight Management Clinic using LCD for weight loss. The accuracy of the predictive model was significantly higher than random in the independent data set. To identify functional relationships and biochemical pathways shared between the predictive proteins we performed network analyses. The results allow us to formulate a first hypothesis on biological processes leading to successful weight loss for overweight and obese subjects on a low-calorie diet. Alexander Kulminski (Duke University) presented "Uncoupling associations of risk alleles with endophenotypes and phenotypes: Insights from the Apolipoprotein B locus, lipids, myocardial infarction, and survival". Traditionally, genome-wide association studies (GWAS) have emphasized the benefits of large samples in the analyses of age-related traits rather than their specific properties.
The number of assays and repeated measurements required to assess Pace of Aging make it impractical for large-scale geroprotector trials. Biological aging measures that can be implemented in a single crosssection of data at baseline and follow-up are needed. We examined Pace of Aging alongside several, more scalable cross-sectional measures of biological aging. These measures were based on clinical biomarker and genomic data, including two recently published clinicalbiomarker algorithms, telomere length, and epigenetic clocks. We asked two questions: (1) Do different measures of biological aging measure the same thing? and (2) Do different measures of biological aging capture different information about healthspan? Findings suggest promise and challenges in research to develop surrogate endpoints for trials of geroprotective interventions.
Joao Pedro de Magalhaes (University of Liverpool) presented on "Gene expression profiling for the discovery of biomarkers of ageing". There is widespread interest in identifying biomarkers of ageing in order to accelerate basic and translational research. Our lab has employed various gene expression profiling approaches to identify molecular signatures that can be used as biomarkers as well provide functional insights on ageing and its manipulation. We performed a metaanalysis of ageing gene expression profiles using microarray datasets from multiple mammalian tissues, which revealed several conserved molecular signatures of ageing. We also applied our network and metaanalysis methods to dietary manipulations of ageing, in particular caloric restriction (CR), and identified candidate genes and processes strongly associated with CR in mammals.
Moreover, we have been employing whole transcriptome profiling (RNA-seq) to study ageing and its manipulation by diet, which has significant advantages when compared to microarrays. Lastly, to catalogue and help understand ageing changes, we developed the Digital Ageing Atlas (http://ageing-map. org/), a one-stop collection of human age-related data covering different biological levels (molecular, cellular, physiological, psychological and pathological). Arnold Mitnitski (Dalhousie University) reported "Indices of biological aging as indicators of heterogeneity of people's health". There is an increasing interest to assessing biological aging -the aging rates are different in individuals of the same chronological AGING (Albany NY) age. Some found attractive an idea that these differences reflect differences in "biological age".
How to estimate biological age is a matter of ongoing debates. The techniques differ also depending on which biomarkers are used to calculate of biological age. We discuss the different approaches to estimation of biological age based on biomarkers of aging of different nature: from the sub-cellular level to the level to the whole organism. We consider this issue from the heterogeneity of people at the same chronological age perspective, from which the index of biological age is only one of possible measures of such heterogeneity. We illustrate some challenges in assessing biological age, by comparing a few measures of heterogeneity: the indices of biological age, defined with and without chronological age, and the frailty indices. By providing head-to-head comparison of these measures we demonstrated that inclusion of chronological age in the measure of biological age is unnecessary, and also (at least in the data sample we present) inferior to the frailty indices.
The latter based on the higher number of biological and clinical data therefore more likely capture the essential characteristics of health and its changes during aging, than a rather restricted set of biomarkers used to calculate biological age score. Also, the items used to calculate the frailty indices are readily available (either from the routine blood tests or/and from clinical assessments), the algorithm of its assessment is simple, in contrast to the obscured statistical techniques of calculating the biological age scores from a relatively restricted number of continuous biomarkers. Extensive comparisons across different databases are required. We discuss the problem of integration of various biological/clinical in a unified index of biological age. Alexander Kulminski (Duke University) reported "Can age-specific genetic effects be relevant to biological age?".
) presented a talk on "Gamification of data collection for deep learning and biomarker development". Since the publication of Horvath's epigenetic aging clock in 2013, the field of aging biomarkers is rapidly evolving with epigenetic and transcriptomic markers developed to accurately predict chronological age of the patient. However, since these tests are reasonably new and expensive, the number of samples with clinical outcomes is still low making it difficult to assess the biological relevance and facilitate for rapid clinical propagation. One data type, medical professionals have a lot of experience with, which is abundant, cost-effective and actionable is clinical blood and urine tests commonly including basic blood biochemistry and cell counts. Millions of clinical profiles with blood biochemistry data are available worldwide providing sufficient number of samples to train deep neural networks.
We obtained a large data set of standard blood tests with 41 parameters linked to age and sex of the patients from Invitro Laboratories, one of the largest providers of laboratory services in Eastern Europe. The data set contained over 60,000 samples coming from routine checkups and excluded sources of patients with diseases like hospitals and medical institutions. We trained 21 single class deep neural networks ensembled using a stacking model to predict the patients' chronological age with 83. 5% epsilon-accuracy r of 0. 91 with R(2) of 0. 82 and mean absolute error (MAE) of 5. 55 years. Following on the footsteps of Microsoft's http://www. how-old. net, we built a website http://www. aging. ai inviting people from all over the world to submit their test results in order to guess their age.
From January 15 to March 31st over 1,500 people participated in the study. In addition to blood tests we AGING (Albany NY) asked to provide height, weight and smoking status, the new parameters that are being evaluated for the future studies. We plan to expand Aging. AI system to work with urine, transcriptomic and imaging data and welcome collaborations in building comprehensive and actionable biomarkers of aging. Ivan V. Ozerov (Senolytics Department, Insilico Medicine, Inc. ) presented "iPANDA identifies the pathway signature in senescent cells: a step forward to development of novel senolytic drugs". Cellular senescence combined with an inability of immune system to effectively eliminate senescent cells leads to persistent accumulation of senescent cells in an aging organism. On the other hand, senescent cells represent a constant danger to the cell population as far as they partly lose their functions and induce malfunctioning of surrounding cells.
As senescent cells accumulate in even greater numbers over the years, the whole tissues gradually loose their specific properties. Such process results in developing of aging phenotype and encourages the risk of malignant transformation in the affected cells. Hence therapies aimed to selectively eliminate senescent cells have a potential slow down age-related changes in tissues and body in whole as well as to reduce the risks of cancer generation. Recently three low-molecular compounds which demonstrate an ability to selectively eliminate senescent cells in various tissues were proposed. This novel class of prospective drugs is referred to as senolytics. In this study, we apply our recently-developed approach to large-scale transcriptomic data analysis in silico Pathway Activation Network Decomposition Analysis (iPANDA) to identify pathway signatures of senescent cells in various tissues and pathway signatures of known senolytic drugs.
Ksenia Lezhnina and colleagues (Insilico Medicine, Inc. ) presented "Signaling pathways signature of sarcopenia identified by iPANDA algorithm. " Sarcopenia is a losing muscle mass and function with aging. Decreased strength and power of muscle function may contribute to higher risks of accidents among older people and affects quality of life. Until recently sarcopenia was not even considered as a pathological condition and as a consequence clinical definition and diagnostic criteria is poorly developed. Mechanism underlying sarcopenia is extensively investigated but still not fully understood. In order to study this we compare transcriptomic profiles of muscle tissues from young and old people, both women and men. We assume that aging process starts from the fourth decade of life. We apply a new algorithm in silico Pathway Activation Network Decomposition Analysis (iPANDA) to transcriptomic data to find signaling pathway signatures of aging in muscle tissues.
Common pathway signatures can be considered as a target for development of new approaches for sarcopenia treatment. Artem Artemov and colleagues (Insilico Medicine, Inc. ) presented "In silico screen for drugs increasing cancer immunotherapy success rates". Cancer immunotherapy has been shown to be extremely efficient. Unlike traditional targeted therapy, it can lead to a complete remission rather than a few months increase in lifespan. Unfortunately, it is beneficial for only a small subset of patients. In this work, we performed in silico screening of compounds which can be administered in combination with anti-PD1 immunotherapy to increase immunotherapy success rate. We collected publicly available transcriptome data for tumours responding and not responding to immunotherapy. Next, we applied iPANDA, Insilico medicine pathway analysis algorithm, and deep-learning based approach to identify a transcriptomic signature predicting the success of immunotherapy in a particular tumour.