dataesr/scientific-paragraphs-categorization huggingface dataset:
In order to select a polyclonal cell subline in which CD44 is absent, cells were detached using Accutase and collected in serumcontaining medium. A total amount of 1 × 10 7 cells was used for sorting. Cells were resuspended in 1 ml (100 µl/10 6 cells) FACS buffer (2% FBS; 2 mM EDTA; PBS) and incubated with human-specific Fc-block (2 µl/10 6 cells) for 45 min on ice. Surface CD44 was labeled with the anti-CD44 antibody IM7 conjugated to PE or APC/Cy7 (IM7-PE; 1:100, IM7-APC-Cy7, 1:100) and incubated for 15 min at RT in the dark. A corresponding isotype control (PE Rat IgG2bκ, Biolegend Cat# 400607, RRID: AB_326551, APC/Cy7 Rat IgG2bκ; Biolegend Cat# 400623. RRID: AB_326565) was used. Cells were washed with FACS buffer and resuspended in 500 µl PBS. Data was analyzed using the FlowJo software (license number M11c3c353YH92SCS).
For the experiment using fixed cells, 0. 6 × 10 5 cells were seeded on a glass slide in a 12-well plate. Wnt pathway activation was induced by Wnt3a CM or CHIR the day after seeding. 24 h after induction, cells were washed with PBS and fixed in 2% PFA (10 min at 4 °C), followed by washing steps. Before mounting with fluorescence mounting medium (Dako), cells were incubated with DAPI (1:10,000 in PBS, 10 min at RT in the dark). Image segmentation and analysis. For quantification (live cell condition), an Incucyte® software mask was applied that differentiates cells from the background (plastic) in order to define the cell area in which the fluorescent intensity for each picture is measured. The fluorescence values were normalized to a respective non-treated control and the mean of the overall fluorescence of each picture was plotted against time.
The qPCR reactions (20 µl) consisted of 10 µl 2× GoTaq® qPCR Master Mix (Promega), 0. 5 mM reverse and forward primers, and 2 µl cDNA. The qPCR was performed according to the manufacturer's protocol on the StepOnePlus™ Real-Time PCR system (Applied Biosystems). Gapdh and β-Actin were used as reference genes for relative quantification according to the Litvak method (ΔΔCt). Primers were designed using the Primer3 open software (http://primer3. ut. ee) upon NCBI-database transcript sequences, and are detailed in Supplementary Table  2. Technology, Institute of Biological and Chemical Systems Functional Molecular Systems, Karlsruhe, Campus North, Postfach 3640, 76021 Karlsruhe, Germany. e-mail: veronique. orian-rousseau@kit. edu.
HEK293T (ATCC Cat# CRL-3216, RRID: CVCL_0063); HeLa (ATCC Cat# CCL-2, RRID: CVCL_0030); L-Wnt-3A cells (ATCC Cat# CRL-2647, RRID: CVCL_0635) and L-Cells (ATCC CRL-2648, RRID: CVCL_4536) were obtained from ATCC (Wesel, Germany) and maintained in Dulbecco's Modified Eagle Medium (DMEM) supplemented with 10% FBS and 1% PenStrep. NCI-H1703 cells.
ACKNOWLEDGEMENTS We are very grateful to  Philipp Haitz ,  Lisa Geiges , and  Dominique Hoch  for providing excellent technical help. We would like to thank  Selma Huber  and  Sabine Müller  of the animal facility of  IBCS-FMS  for their help and professionalism. We thank  Sylvia Robine  for providing the VillinCreER T2 mouse.
6 h. In order to simulate this condition the incoming flow is kept equal to f max , while the outcoming flow is reduced to 0. 3f max. Then, after the considered interval, it becomes again equal to f max. S2) continuous increasing of the traffic congestion: in this scenario, the traffic congestion is continuously increased for all the simulation window by considering a reduction of the outcoming flow to 0. 5f max at location 50 km. All the simulations have been executed using the MATLAB tool for NLP CasADi, with the primal-dual interior point solver IPOPT.
Study Design The Diet and Nutrition in Cancer (DANICA) trial was a pilot randomized controlled trial conducted at the Wilmot Cancer Institute (WCI) from November 2020 to December 2021. This study was preregistered at clinicaltrials. gov (identifier: NCT04534738, registered September 2020). The research protocol was reviewed and approved by the Institutional Review Board. The primary aims of the trial were to evaluate the feasibility of delivering a MedDiet intervention, as measured by adherence at both four weeks and eight weeks, and to evaluate the preliminary efficacy of MedDiet vs. usual care to prevent cancerrelated fatigue among patients with cancer undergoing chemotherapy. Secondary aims were to evaluate the effects of the MedDiet on blood-based metabolic biomarkers (e. g. , fructosamine) and ex vivo mitochondrial function (i.
Procedures Patients were referred to study investigators by clinicians at WCI or responded to flyers advertising the study. Volunteers interested in participating completed a telephone screening to verify eligibility. Participants were provided the choice to consent via a paper consent or eConsent using REDCap software  [31, 32]. For baseline assessments, participants completed questionnaires, a three-day food record, and a blood draw (described in detail in Section 2. 6). Participants were then randomized 2:1, intervention:control, using a computergenerated random numbers table with blocks of 3 or 6 and stratified based on whether their chemotherapy regimen was (1) weekly, biweekly, or every four weeks, or (2) other; stratification occurred to ensure that participants were balanced in regard to whether baseline, 4-week, and 8-week measurements were at the same vs.
We paid special attention to weight loss and extracted body weight from the medical record at baseline, four weeks, and eight weeks. Body mass index (BMI) was calculated as body weight in kg/(height in m) 2. Three-Day food records were completed by participants at baseline, four weeks, and eight weeks. Data were entered into Nutrition Data System for Research (NDSR) software (2021 version; Nutrition Coordinating Center, University of Minnesota, Minneapolis, MN, USA) by a team of two trained registered dietitians (RP and NW). Nutrients from food and supplements were summed to estimate total dietary intake for macro-and micronutrients. The number of servings in each food group was estimated using NDSR's Serving Count Totals analysis. Blood was collected from either the participant's implanted chemotherapy port or venipuncture at baseline, week 4, and week 8 into red-top tubes with no anticoagulant or preservative (for serum) and mint green-top tubes with sodium heparin (for mitochondrial assays).
No interim analyses were planned or performed. Differences between groups at baseline were identified using a t-test for continuous variables and a χ 2 test for categorical variables. To assess adherence, changes in the MedDiet Adherence questionnaire from baseline to week 4 and week 8 were compared using a two-sided t-test. For the effects of the MedDiet intervention on fatigue, food intake, and metabolic measures, as part of an intent-to-treat analysis, a mixed effect model was constructed with the measure at week 4 or 8 as the dependent variable; group, time, and group×time as fixed effects; the measure at baseline as an independent covariate; participant as a random effect; and an autoregressive structure (AR  [1] ) accounting for repeated measures (4, 8 weeks) per participant (JMP Pro 16, SAS Institute, Cary, NC, USA).
Feasibility, Dietary Adherence, and Safety The threshold for study feasibility was set a priori at >70% of participants who consented to complete the study; 100% completed the study and provided fully evaluable data for the primary aim of fatigue. MedDiet adherence was measured using the 14-item Mediterranean Diet Assessment Tool. Scores were similar between groups at baseline (MedDiet 4. 0 ± 2. 7, control 4. 7 ± 1. 9, Table  S1 ; p = 0. 46). At week 4, scores increased from baseline by 2. 7 ± 3. 2 (mean ± SD) points for the MedDiet group and 0. 7 ± 2. 4 points for the control group (p < 0. 001 and p = 0. 44 within-group comparisons, respectively; p = 0. 062, two-sided between-group comparison). Increases from baseline to week 8 were 2. 5 ± 3. 0 points for the MedDiet group and 0. 5 ± 2. 5 points for the control group (p < 0.
147 ± 0. 517, p = 0. 780), maximal respiration (b ± SE = 0. 373 ± 0. 366, p = 0. 324), or spare capacity (b ± SE = 0. 517 ± 0. 302, p = 0. 107). We then assessed associations between mitochondrial function and patient-reported fatigue using a mixed model (independent of the intervention). Greater patient-reported fatigue was consistently associated with lower basal respiration, lower maximal respiration, and lower spare capacity, after adjusting for age (Table  3 ). Specifically, fatigue as measured using the FACIT-F fatigue subscale and the BFI (usual fatigue) was statistically significantly associated with lower basal respiration (p = 0. 044 and p = 0. 006), lower maximal respiratory capacity (p = 0. 021 and p = 0. 014), and lower spare capacity (p = 0. 029 and p = 0. 044). Table  3. Associations between mitochondrial measures and cancer-related fatigue incorporating data from baseline and four weeks.
This study employed patient-reported outcomes and objective metabolic measures at the same time points, allowing us to directly probe underlying metabolic mechanisms of fatigue and how diet affected these measures. This study, however, is not without limitations. Participants were mostly highly educated, non-Hispanic White women with breast cancer, so generalizability to other populations should be done with prudence. Furthermore, fatigue fluctuates over chemotherapy cycles and these data are only from three time points; therefore, these data did not capture a detailed trajectory of fatigue. However, we used multiple instruments that capture multidimensional aspects of fatigue over different time frames. We also stratified our participants based on chemotherapy cycle length so that the timing of our assessments in relation to their chemotherapy was balanced between groups.
Acknowledgments: We thank  Leslie  and  Tim Dougherty of Project Lean Nation  for facilitating the logistics of meal delivery to the participants in our study. We are grateful to  Shijun Zhu  for helpful statistical discussions. We thank  Robin Peck  and  Nellie Wixom  at the  Clinical Research Center  for entering food log data into NDSR software. We also thank  Wojtek Wojciechowski Development Director  of the  URMC Flow Cytometry Core Facilities , for access to the Seahorse instrument. We thank  Gary Morrow , for helpful discussions in the design of this study with considerations to scale it up in the future. The graphical abstract includes a photograph of original art by  Peggy Simmons.
Background: Patients with cancer-associated venous thromboembolism (VTE) are recommended to receive treatment with therapeutic anticoagulation for at least 3-6 months. Little data exist on extended treatment beyond 6 months. Objective: To comprehensively summarize the best available evidence on incidence of recurrent VTE and major bleeding 6-12 months after the index event in patients with cancer-associated VTE. Patients/Methods: We systematically screened biomedical databases (MEDLINE, Embase, CENTRAL) to identify studies reporting recurrent VTE and/or bleeding events between 6 and 12 months after a diagnosis of cancer-associated VTE. Based on the observed heterogeneity in study design, setting, patient cohort characteristics, anticoagulation strategies, and outcome rates, no overall quantitative estimate of outcome rates was calculated.
| ME THODS We conducted a systematic review of the literature to identify studies that report the rate of recurrent VTE and/or bleeding between 6 and 12 months after the index event in patients with cancer-associated VTE. The study was conducted according to the Cochrane Handbook for Systematic Reviews of Interventions and is presented following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA, available as Data S1 in supporting information) guidelines. 16, 17 The study protocol for this systematic review was prepared prior to the initiation of literature research and submitted to the International Prospective Register of Systematic Reviews (PROSPERO, ID: CRD42021209847).
| Literature research and study selection process Three biomedical databases (MEDLINE, Embase, CENTRAL) were systematically screened for potentially eligible publications based on a search algorithm of predefined search terms, available in the Appendix S1 in supporting information. Titles and abstracts of records identified by the search algorithm were screened by two independent researchers (FM, MC) for eligibility based on predefined in-and exclusion criteria. In the second step, the corresponding full texts of studies identified during the abstract-and title screening were reviewed independently by the two researchers (FM, MC). Any disagreement between the two researchers conducting the literature search was resolved by discussing the respective publication with a third independent researcher (CA).
| Data extraction Data were extracted from the identified studies fulfilling the eligibility criteria by two independent researchers (FM, MC). Primary study data of included studies were not sought from the investigators and only data as extractable from published results were included. Descriptive characteristics of selected studies, including baseline demographics, cancer specifics (type, stage), and details on qualifying VTE event and anticoagulation treatment were gathered. Additionally, data on outcome events between 6 and 12 months after the initial index VTE event were obtained. Primary outcome events of this systematic review were predefined and comprise (a) the rate of recurrent VTE, as defined within the respective study, including symptomatic, incidental, or fatal PE, DVT (including CRT), splanchnic vein thrombosis, or cerebral vein thrombosis; and (b) the rate of major bleeding (MB), either defined according to the bleeding scale of the International Society on Thrombosis and Haemostasis (ISTH; i.
| Statistics Planned quantitative synthesis of data from identified studies was omitted due to the observed degree of underlying risk of bias and substantial between-study heterogeneity in design, study cohorts, anticoagulation strategies, and outcome rates. Individual risk of recurrent VTE and MB are presented in Forrest plots, created with the STATA package metaprop, computing individual 95% confidence intervals by the score method. 22 Heterogeneity between included studies is reported by I 2 as a measure of between-study variance beyond expected random variation. Data extracted from included studies and analytic code are available from the corresponding author upon reasonable request. All statistical analyses were conducted in STATA v15. 1 (Stata Corp. ).
| Study selection In total, 2597 studies were identified after screening of the biomedical databases following predefined search algorithms on September 18, 2020 (MEDLINE via PubMed: 1134, Embase: 1068, CENTRAL: 395). After the removal of duplicates, 2210 records underwent primary eligibility screening based on titles and abstracts. Consequently, 332 publications remained for full-text evaluation. Of those, 11 studies were identified that met the predefined eligibility criteria for this systematic review. The process of study selection is displayed in detail in a PRISMA flow diagram in Figure  1.
| Study characteristics The 11 identified eligible studies varied in study design, inclusion and exclusion criteria, and characteristics of included patients. A comprehensive overview summarizing details of study characteristics is presented in Table  1 , and more details on baseline characteristics of study subgroups in Table  S1. Overall, three randomized controlled trials (RCT), two single-arm interventional trials, two prospective cohort studies, two retrospective cohort studies, and two studies reporting registry data were identified. In total, these studies included 3019 patients with cancer-associated thrombosis at 6 months after the index VTE event.
RCT, randomized controlled trial; VTE, venous thromboembolism which reported data from two prospective observational studies (n = 719), described treatment and outcomes of 432 patients (60%) beyond 6 months after index VTE. 29 Using a single-center retrospective cohort, Schmidt et al. reported on the treatment and outcomes of 322 patients 6-12 months post index VTE. 30 Last, two registry studies were included that allow extraction of outcome data 6-12 months after cancer-associated VTE. In the COMMAND VTE registry, outcomes of patients with symptomatic VTE, including a separately reported subgroup of patients with active cancer, are reported between 6 and 12 months (n = 396),  31  and Yhim et al. evaluated the risk of recurrent VTE in patients with recurrent/metastatic solid cancer and VTE, providing the number of patients at risk at 6 months after index VTE (n = 83) and reporting outcome rates between 6 and 12 months.
| Risk of bias A structured assessment of the underlying risk of bias for each study was conducted to judge the generalizability of the respective study findings, and to evaluate the possibility of aggregating the extracted outcome data of identified studies. Importantly, risk of bias assessment represents an evaluation of each included study in the framework of the research questions of the present systematic review and does not evaluate the overall scientific merit or quality of the respective study. Overall, studies varied in respect to their underlying suspected risk of bias, mostly due to the selection of study cohorts based on index VTE characteristics (e. g. , DVT only, symptomatic VTE only), the presence of RVT at 6 months, or cancer-specific restrictions (e. g. , advanced disease only).
Patients with advanced cancer are at a higher baseline risk of a first VTE event than patients with non-metastatic cancer and also risk of VTE recurrence, bleeding, and mortality is increased in patients with more advanced disease. addition, given the efficacy of reduced dose or prophylactic dose anticoagulation at 6 months after index VTE events in selected subsets of patients,  35, 36  comparative studies evaluating the optimal anticoagulation strategy for the long-term secondary prophylaxis in patients after a diagnosis of cancer-associated VTE are needed. F I G U R E 3 In this regard, the ongoing randomized controlled API-CAT study (ClinicalTrials. gov NCT03692065), comparing standard-dose to lowdose apixaban after 6 months post index VTE, may provide important information on net clinical benefit of reducing anticoagulation doses after 6 months.
For example, in academic settings, Ph. D. , economists are not typically moved to the HR department prior to becoming the dean of a department. Using a large employeremployee linked dataset on executives at US corporations, Jin and Waldman (2019)  show that workers with 17 years of education were twice as likely to be laterally moved before promotion than workers with 19 years of education. 5 An occupation is "exposed" to AI if it has a high intensity in skills that AI can perform, see section What Do These Indicators Measure? for details. Again for the US, Fossen and Sorgner (2019) look at the effect of exposure to AI 6 on job stability and wage growth at the individual level. They find that exposure to AI leads to higher employment stability and higher wages, and that this effect is stronger for higher educated and more experienced workers, again indicating that the productivity effect dominates and that it is stronger for highskilled workers.
Indicators Based on AI-Related Job Posting Frequencies The first set of indicators use data on AI-related skill requirements in job postings as a proxy for AI deployment in firms. The main data source for these indicators is Burning Glass Technologies (BGT), which collects detailed informationincluding job title, sector, required skills etc. -on online job postings (see Box 1 for details). Because of the rich and upto-date information BGT data offers, these indicators allow for a timely tracking of the demand for AI skills across the labor market. Squicciarini and Nachtigall (2021) identify AI-related job postings by using keywords extracted from scientific publications, augmented by text mining techniques and expert validation [see Baruffaldi et al. (2020) for details]. These keywords belong to four broad groups: (i) generic AI keywords, e.
g. , "artificial intelligence, " "machine learning;" (ii) AI approaches or methods: e. g. , "decision trees, " "deep learning;" (iii) AI applications: e. g. , "computer vision, " "image recognition;" (iv) AI software and libraries: e. g. , Python or TensorFlow. Since some of these keywords may be used in job postings for non AI-related jobs (e. g. , "Python" or "Bayesian"), the authors only tag a job as AI-related if the posting contains at least two AI keywords from at least two distinct concepts. This indicator is available on an annual basis for Canada, Singapore, the United Kingdom and the United States, for 2012-2018  8. Acemoglu et al. (2020) take a simpler approach by defining vacancies as AI-related if they contain any keyword belonging to a simple list of skills related to AI 9. As this indicator will tag any job posting that contains one of the keywords, it is less precise than the indicator proposed by Squicciarini and  Nachtigall (2021), but also easier to reproduce.
It also means that workers who possess skills that are similar to AI skills may find it easier to work with AI, even if they are not capable of developing the technology themselves. For example, the skill "copy writing" is similar to "journalism, " meaning that a copy writer might transition to journalism at a lower cost than, say, a social worker, and that a copy writer might find it comparatively easier to use databases and other digital tools created for journalists. Skill similarity allows the identification and tracking of emerging skills: using a short list of "seed skills 11 , " the indicator can track similar skills as they appear in job ads over time, keeping the indicator up to date. For example, TensorFlow is a deep learning framework introduced in 2016. Many job postings now list it as a requirement without additionally specifying "deep learning" (Dawson et al.
These codes can be converted to ISCO at the one-digit level. 9 This paper uses the same list of skills to look at AI job-postings, see Footnote 44 for the complete list of skills. 10 To measure importance of skills in job ads, the authors use the Revealed Comparative Advantage (RCA) measure, loaned from trade economics, that weighs the importance of a skill in a job posting up if the number of skills for this specific posting is low, and weighs it down if the skill is ubiquitous in all job adds. That is, the skill "team work" will be generally less important given its ubiquity in all job ads, but its importance in an individual job posting would increase if only few other skills were required for that job. 11 "Artificial Intelligence, " "Machine Learning, " "Data Science, " "Data Mining, " and "Big Data".
Task-Based Indicators Task-based indicators for AI adoption are based on measures of AI capabilities linked to tasks workers perform, often at the occupational level. They identify occupations as exposed to AI if they perform tasks that AI is increasingly capable of performing. The AI occupational exposure measure developed by Felten  et al. (2018, 2019) is based on progress scores in nine AI applications 13 (such as reading comprehension or image recognition) from the AI progress measurement dataset provided by the Electronic Frontier Foundation (EFF). The EFF monitors progress in AI applications using a mixture of academic literature, blog posts and websites focused on AI. Each application may have several progress scores. One example of a progress score would be a recognition error rate for image recognition.