dataesr/scientific-paragraphs-categorization huggingface dataset:
1%). Four cases of atrial fibrillation were detected from the EKG data of ischemic stroke patients. The outcomes are listed in Table  2. Upon discharge, patients with ischemic stroke were taking more antiplatelet drugs and statins than the other patients, but only 132 (88. 0%) of them had antiplatelet. Four patients had anticoagulant on discharge after antiplatelet in the acute phase. The use of an antiplatelet drug differed for others due to the hemorrhagic transformation of the infarction in the acute phase. Surprisingly, one patient with hemorrhagic stroke used one 75 mg aspirin per day on discharge due to the cardiac prescription (he accumulated four vascular risk factors such as hypertension, diabetes, previous myocardial infarction and a minor hemorrhage on brain CT scan). The antihypertensive drugs were prescribed more to patients with intracerebral hemorrhage (ICH).
Deficits in Insight in Different Psychiatric Disorders As an example, in a sample of 421 schizophrenic patients, 32. 1% were found to have a low insight, 25. 3% a fair insight, and 40. 7% a good insight [  (5) ; see also  (66) ]. In a sample of 431 patients with OCD, 25% had a low insight and 5% were unaware of the absurdity of their obsessions  (9). These data invalidated the hypotheses of the clinical model that insight is constitutively impaired in schizophrenia but preserved in other psychiatric disorders. Lack of insight was also reported in patients with alcohol use disorders (AUD). In a sample of 452 AUD patients, nearly 75% had poor insight into their alcohol-related problems  (67). This lack of cognitive insight was reflected in a significant contrast between the patients' evaluation of their own cognitive performance, which was under-estimated, and the standardized neuropsychological evaluation by clinicians [(68) (N = 86); (69) (N = 91); see also  (70, 71) ].
Study Samples De-identified demographic and cortical thickness data from 83 worldwide samples (Figure  1 ) were pooled to create the dataset analysed in this study. The pooled sample comprised 17,075 participants (52% female) aged 3-90 years (Table  1 ). All participants had been screened to exclude psychiatric disorders, medical and neurological morbidity and cognitive impairment. Information on the screening protocols and eligibility criteria is provided in Supplemental Table  S1.
Image acquisition and processing Prior to pooling the data used in this study, researchers at each participating institution (a) used the ENIGMA MRI analysis protocols, which are based on FreeSurfer (http://surfer. nmr. mgh. harvard. edu) (Fischl, 2012; Fischl, et al. , 2002) , to extract cortical thickness of 68 regions from high-resolution T1-weighted MRI brain scans collected at their site; (b) inspected all images by overlaying the cortical parcellations on the participants' anatomical scans; (c) excluded improperly segmented scans and outliers identified using five median absolute deviations (MAD) of that of the median value. Information on scanner vendor, magnetic field strengths, FreeSurfer version and acquisition parameters for each sample provided by the participating institutions is detailed in Supplemental Table  S1.
Analysis of age-related trajectories in cortical thickness We modeled the effect of age on regional cortical thickness using higher order fractional polynomial (FP) regression analyses  (Royston and Altman, 1994; Sauerbrei, et al. , 2006)  implemented in STATA software version 14. 0 (Stata Corp. , College Station, TX). FP regression is one of the most flexible methods to study the effect of continuous variables on a response variable  (Royston and Altman, 1994; Sauerbrei, et al. , 2006). FP allows for testing a broad family of shapes and multiple turning points while simultaneously providing a good fit at the extremes of the covariates  (Royston and Altman, 1994). Prior to FP regression analysis, cortical thickness values were harmonized between sites using the ComBat method in R  (Fortin, et al.
Centile Values of Cortical Thickness We calculated the centiles (0. 4, 1, 2. 5, 5, 10, 25, 50, 75, 90, 95, 97. 5, 99, 99. 6 ) for each regional cortical thickness measure by sex and hemisphere as normalized growth centiles using parametric Lambda (λ), Mu (μ), Sigma (σ) (LMS) method (Cole and Green, 1992) in the Generalised Additive Models for Location, Scale and Shape (GAMLSS) package in R (http://cran. r-project. org/web/packages/gamlss/index. html) (Rigby and Stasinopoulos, 2005; Stasinopoulos and Rigby, 2007). LMS is considered a powerful method for estimating centile curves based on the distribution of a response variable at each covariate value (in this case age). GAMLSS uses a penalized maximum likelihood function to estimate parameters of smoothness (effective degrees of freedom) which are then used to estimate the λ, μ and σ parameters  (Indrayan, 2014).
Discussion In the present study, we provide the most comprehensive characterisation of lifetime trajectories of regional cortical thickness based on multiple analytic methods (i. e. , FP analysis, meta-analysis and centile calculations) and the largest dataset of cortical thickness measures available from healthy individuals aged 3 to 90 years. In addition to sample size, the study benefited from the standardised and validated protocols for data extraction and quality control that are common to all ENIGMA sites and have supported all published ENIGMA structural MRI studies  (Hibar, et al. , 2018; Schmaal, et al. , 2017; Walton, et al. , 2017; Whelan, et al. , 2018). As predicted, most regional cortical thickness measures reached their maximum value between 3-10 years of age, showed a steep decrease during the second and third decades of life and an attenuated or plateaued slope until later life.
The results presented here are based on the largest available brain MRI dataset worldwide covering the human lifespan. However, none of the pooled samples in the current study was longitudinal. We fully appreciate that longitudinal studies are considered preferable to crosssectional designs when aiming to define age-related brain morphometric trajectories. However, a longitudinal study of this size over nine decades of life is not feasible. In addition to problems with participant recruitment and retention, such a lengthy study would have involved changes in scanner types, magnetic field strengths and acquisition protocols in line with necessary upgrades and technological advances. We took several steps to mitigate against site effects. First, we ensured that we used age-overlapping datasets throughout.
Acknowledgments This study presents independent research funded by multiple agencies. The funding sources had no role in the study design, data collection, analysis, and interpretation of the data. The views expressed in the manuscript are those of the authors and do not necessarily represent those of any of the funding agencies. Dr. Dima received funding from the  National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London , the  Psychiatry Research Trust  and 2014  NARSAD Young Investigator Award. Dr. Frangou  received support from the  National Institutes of Health  ( R01 MH104284 ) the  European Community 's  Seventh Framework Programme  ( FP7/2007-2013 ) (grant agreement  n°602450 ). FBIRN data collection and analysis was supported by the  National Center for Research Resources at the National Institutes of Health  (grant numbers:  NIH  1  U24 RR021992  ( Function Biomedical Informatics Research Network ) and  NIH  1  U24 RR025736-01  ( Biomedical Informatics Research Network Coordinating Center ; http://www.
Within ENIGMA, the focus of the Lifespan Working group is to delineate age-related trajectories of brain morphometry extracted from MRI images using standardized protocols and unified quality control procedures harmonized and validated across all participating sites. Moreover, the ENIGMA Lifespan dataset is the largest sample of healthy individuals available worldwide that offers the most comprehensive coverage of the human lifespan. This distinguishes the ENIGMA Lifespan dataset from other imaging samples, such as the UK Biobank (http://www. ukbiobank. ac. uk) which only includes individuals over 40 years of age. In the present study, we used MRI data from 17,075.
which refers to ln(age). Powers can be repeated in FP; each time a power s repeated, it is multiplied by another ln(age). As an example: and the lowest degree model with the smallest P-value was selected as the optimal model. Following permutation, critical alpha value was set at 0. 01 to decrease the probability of over-fitting. The age at maximum cortical thickness for each cortical region was the maximum fitted value of the corresponding optimal FP model. age (3,',')-𝛽 = β 3 + β ' age 3 + β ) age ' + β 8 age ' ln(age) = β 3 + β ' ln(age) + β ) age + β 8 age ln (age) 494 models were trained for each region. Model comparison was performed using a partial F-test Further, we divided the dataset into three age-groups corresponding to early (3-29 years), middle (30-59 years) and late life (60-90 years).
Funding: This research was funded by the following funding schemes: (1) HELLAS- CH  project ( MIS 5002735 ), implemented under the " Action for Strengthening Research and Innovation Infrastructures ," (2) the  Operational Programme "Competitiveness, Entrepreneurship and Innovation " and co-financed by Greece and the  EU (European Regional Development Fund) ,  Nanoscience Foundries  and  Fine Analysis  (NFFA)-Europe  H2020-INFRAIA-2014-2015  (Grant Agreement No. 654360 ), (3)  COST Action TUMIEE  (supported by  COST-European Cooperation in Science and Technology), (4)   MouldTeX  project -H2020-EU. 2. 1. 5. 1  (Grant agreement No  768705 ), (5) Laserlab-Europe  IV  project, transnational access project: ulf-forth-2258 (Grant-Agreement 654148).
Increased expression of ALDH1A1, ALDH1A3, or ALDH3A1 in NSCLC impacts chemotherapeutic responses and patient survival First, we searched for alterations in the expression of genes of the ALDH family in the two major histopathological subtypes of NSCLC, lung adenocarcinoma (ADC) and squamous cell carcinoma (SCC), by analyzing RNA sequencing (RNAseq) data in datasets from The Cancer Genome Atlas (TCGA) (cBioPortal)  [23]. We found that 13% of ADC (N = 515) and 18% of SCC (N = 504) patients carried transcriptional alterations in ALDH1A1, ALDH1A3, or ALDH3A1 with a mutually exclusive tendency, suggesting that these genes confer similar functional effects (Fig. 1a ). Overall, of the 158 NSCLC patients carrying alterations in any of these ALDH isoenzymes, 86% harbored either gene amplification or mRNA upregulation.
The transcriptional alterations observed in these isoenzymes reflect the protein-level differences reported in Human Protein Atlas platform in normal vs. tumor tissue, changing from undetected or low staining in normal pneumocytes to moderate or intense staining in tumor tissues  [24]  (Fig. 1b ). Cytotoxic chemotherapy retains a major role in the management of advanced NSCLC  [25]. Chemotherapy can be used before surgery to reduce the tumor size (neoadjuvant chemotherapy), after surgery in resected stage II and III NSCLCs or in stage III and IV lung cancers that cannot be removed surgically. Given the reported association of high ALDH activity with tumor-initiating cells and chemotherapeutic drug resistance  [11, 13, 15] , we next investigated the influence of ALDH1A1, ALDH1A3, and ALDH3A1 mRNA expression on the survival of patients treated with or without chemotherapy, according to data in public NSCLC datasets from the TCGA and Gene Expression Omnibus (GEO) databases.
Bioinformatic and statistical analyses The following bioinformatic tools were used to analyze the functions of ALDHs in NSCLC biological processes: TCGA, cBioPortal  [23] , Oncomine  [50, 51] ; Human Protein Atlas  [24] ; Kaplan-Meier plotter  [52, 53]  and GEO  [54, 55]. Kaplan-Meier plotter and the R program were used to evaluate the clinical relevance of ALDHs by linking clinical data to gene expression levels. Kaplan-Meier Plotter was used to confirm disease prognosis and OS times. Transcriptome microarray datasets were downloaded from the TCGA and GEO databases under the accession numbers GSE8894 (N = 138), GSE19188 (N = 91), GSE3141 (N = 111), GSE31210 (N = 246), GSE4573 (N = 130), GSE14814 (N = 133), GSE29013 (N = 55), GSE37745 (N = 196), GSE30219 (N = 293), GSE31908 (N = 30), GSE43580 (N = 150), GSE50081 (N = 181), caArray (N = 443), and TCGA (N = 133).
All datasets were transformed to a common scale and precision. Normalized raw transcriptome data were subsequently reanalyzed to evaluate the associations between ALDH1A1, ALDH1A3, and ALDH3A1 expression and clinicopathological variables using the nonparametric Fisher's exact test. Analysis was performed with the R program  [56]. The flow cytometric analysis, cell viability assay, and in vivo tumor growth results were analyzed by a paired t-test. P < 0. 05 was considered statistically significant.
Acknowledgements The authors are grateful to  Dr Gerard Quash , who has been a motivation and inspiration for this work. The authors also thank  Alessandro Ventura  for imaging support,  Dr Alberto Indacochea  for his advice and support in database analysis and  Dr Yokota Jun  for kindly providing the  H441 ,  H23 ,  H2122 ,  Hop62 , and H829 cell lines. This work was partially funded by the  La Marató TV3 Foundation program of Catalonia, Spain  and the  Prometheus program of SENESCYT.
CAFs remodel the ECM by producing, assembling, cross-linking, and degrading ECM components. Tumor cells and infiltrating immune cells are also important proponents of ECM remodeling. The complex crosstalk between tumor and stromal cells leads to a global increase in ECM abundance and stiffness which in turn amplifies CAF activation via a positive feedback loop. Epi, epithelial cells; End, endothelial cells; PV, peri-vascular cells; CSC, cancer stem cells; BMDP, bone marrow derived precursor cells. predicted matrisome corresponds to over 1,000 genes encoding a set of 278 core components and 753 matrisome-associated proteins, of which 86% of the core matrisome proteins and 58% of the matrisome-associated components have been detected in tissues using ECM-focused proteomics strategies [see (6) for the latest Matrisome database].
Following extensive preclinical studies, L19-IL2 immunocytokine has demonstrated therapeutic activity in advanced solid cancer  (221). In combination with darcabazine, it displayed encouraging clinical activity in patients with metastatic melanoma in a phase I and II studies  (222, 223). A randomized Phase IIb study was completed but not yet reported (NCT01055522). L19-IL2 was also tested in combination with radiotherapy. In a preclinical study, that combination enhance the radiotherapyinduced antitumor immune reaction and provided a longlasting antitumor effect dependent on EDB expression and infiltration of cytotoxic T cells  (224). A Phase I clinical study combining L19-IL2 with Stereotactic Ablative Body Radiotherapy (SABR) in oligometastic tumors (NCT02086721) was completed but results are not published.
Additional clinical trials involving L19-derived targeting agents (L19-IL2, L19-TNF) alone or combined with other therapies are ongoing in several tumor types (see the NIH website identifier: https://clinicaltrials. gov). EDA and EDB based vaccines appear to be promising for the treatment and prevention of cancer. Regarding the EDA domain, a fusion protein between streptavidin and the endogenous TLR4 ligand EDA showed the capacity to target biotinylated antigens to dendritic cells and induce T cell responses in vivo  (225). As EDA is known to activate the NF-κB pathway leading to the activation of innate immune system and release of inflammatory cytokines, it has been explored as a cancer vaccine adjuvant in mouse models  (195, 226, 227). Immunological activity of EDA depends upon its local intramolecular context within the FN chain.
ACKNOWLEDGMENTS The pioneering and insightful scientists whose biochemical, molecular, and genetic studies laid the foundation for the enormous corpus of work on FN were gratefully acknowledged. We also extend our apologies to colleagues whose original contributions could not be cited due to space limitations. EV acknowledges funding from the  French National Agency for Research  ( ANR-16-CE93-0005-01 ), the  Fondation ARC  ( PJA20151203207 , fellowship GE), The  Fondation Recherche Médicale (fellowship AS) , the  Ligue National Contre le Cancer  ( LNCC/EVO Programme Priorité Tabac ), the  LabEx SIGNALIFE program  ( ANR-11-LABX-0028-01 ), the  Fédération Hospitalo-Universitaire OncoAge  and the  3IA Côte d'Azur  ( ANR-19-P3IA-0002 ).
4. Ramaswamy S, Ross KN, Lander ES, Golub TR. A molecular signature of metastasis in primary solid tumors. Nat Genet. (2003) 33:49-54. doi: 10. 1038/ng1060 5. Naba A, Clauser KR, Hoersch S, Carr SA, Hynes RO. The matrisome: in silico definition and in vivo characterization by proteomics of normal and tumor extracellular matrices. Mol Cell Proteomics. (2012) 11:M111. 014647. doi: 10. 1074/mcp. M111. 014647 6. Shao X, Taha IN, Clauser KR, Gao Y (Tom), Naba A. MatrisomeDB: the ECM-protein knowledge database. Nucleic Acids Res. (2020) 48:D1136-44. doi: 10. 1093/nar/gkz849 7. Xiong G-F, Xu R. Function of cancer cell-derived extracellular matrix in tumor progression. JCMT. (2016) 2:357. doi: 10. 20517/2394-4722. 2016. 08 8. Karagiannis GS, Poutahidis T, Erdman SE, Kirsch R, Riddell RH, Diamandis EP.
The patient follow-up visit details are updated regularly in the 'DOT DR-TB' by the healthcare workers. Patient data in the health facility 'DOT DR-TB' register are also entered into the DR-TB register which is maintained and updated by DR-TB co-ordinators at district level. As part of pre-treatment evaluation for all patients, laboratory investigations like liver function tests, renal function tests and complete blood count are supposed to be done before initiation of treatment. The district clinical management team initiates treatment based on pretreatment evaluation. Details of the clinical and laboratory examinations are documented in the DR-TB card and also in the clinical notes attached to the DR-TB card. During the study period, the WHO recommended use of a standardised DOTS-Plus regimen for the management of MDR/RR-TB patients.
Data variables, sources of data and data collection. Patient demographic and clinical data were extracted from the health facility DOT register, individual patient clinical notes and the district DR-TB register using a structured proforma. Data extraction was done by District TB coordinators of the respective districts following training by the principal investigator. A data extraction manual was also shared by the principal investigator indicating the source of variables and explaining the standard procedure to be followed while extracting each variable. District Environmental Health Officers (DEHOs) of the respective districts also crosschecked the source registers and validated 10% of the extracted data. Data was extracted from August to December 2018.
Data entry, analysis and reporting Data were double entered and validated using EpiData Entry software (EpiData Association, Odense, Denmark). Data were analysed using EpiData analysis (version 2. 2. 2. 182, EpiData Association, Odense, Denmark) and Stata (version 12. 0 STATA Corp. , College, TX, USA). Study findings were reported in accordance with Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. [16]  Categorical variables such as MDR/RR-TB treatment outcomes were summarized using numbers and percentages while medians (interquartile range (IQR)) were calculated for skewed continuous data such as age and weight at treatment initiation. The TB treatment outcomes were ascertained at completion of treatment unless there was a known outcome such as deaths, LTFUs or treatment failure.
Acknowledgments This research was conducted through the  Structured Operational Research and Training Initiative (SORT IT ), a global partnership led by the  Special Programme for Research and Training in Tropical Diseases at the World Health Organization (WHO/TDR ). The training model is based on a course developed jointly by the  International Union Against Tuberculosis and Lung Disease  ( The Union ) and Medecins sans Frontières (MSF). The specific  SORT IT program  which resulted in this publication was implemented by the  Centre for Operational Research, The Union, Paris, France. Mentorship and the coordination/facilitation of this particular SORT IT workshop was provided through the  Centre for Operational Research, The Union, Paris, France ; the  Department of Tuberculosis and HIV, The Union, Paris, France; the University of Washington, School of Public Health, Department of Global Health, Seattle, Washington, USA; National Institute for Medical Research, Muhimbili Centre, Dar es Salaam, Tanzania ; and  AIDS & TB Department ,  Ministry of Health & Child Care, Harare , Zimbabwe The contribution by the District TB coordinators who collected the data and completed the proforma is well appreciated.
Patients Patients were retrospectively selected from the neuroendocrine neoplasm (NEN) database of the Hospices Civils de Lyon (Lyon, France), a centre of excellence of the European NeuroEndocrine Tumours Society (ENETS). We included all consecutive patients with advanced/metastatic GEP or lung NETs, treated with everolimus that was initiated between July 2006 and May 2019. Patients received everolimus at the dose of 10 mg with the exception of those with comorbidities or side effects requiring dose adjustment. Patients could continue concurrent somatostatin analogs in case of functioning NET, but no other antitumour treatments. NETs were classified using the most recent WHO classification available: GEP-NETs were re-categorized using the last WHO classification if needed; either as NET G1, NET G2, NET G3, or undefined NET (when the diagnosis was made without tumour grade or Ki67 index; often before 2000)  (11) ; the WHO 2015 was used for lung NETs that were defined as typical carcinoid, atypical carcinoid, or undefined carcinoid (if data not available or in the absence of primary tumour specimen)  (12).
For continuous parameters, the threshold was defined as the median value of the population. Multivariate analyses using a Cox proportional hazards regression model were performed to identify factors independently associated with prognosis. All significant factors from the univariate analysis (Log-rank p-value <0. 10) were included in the multivariate analyses; a p-value of <0. 05 was considered statistically significant. The results from the survival analyses are presented with the effect estimates, hazard ratios (HR), and 95% confidence interval (CI). All statistical analyses were performed using IBM-SPSS version 21. Pusceddu et al. found a median PFS of 12 months in the non-metformin group and 44 months in the metformin group, which correspond to HR of 0. 28  (8). However, that the present study would be positive if the HR between groups <0.
Background: Systematically review the evidence describing the impact of anti-vascular endothelial growth factor (anti-VEGF) therapy on neovascular age-related macular degeneration (nAMD) patient outcomes and healthcare resource utilization. Methods: A systematic literature review was completed using Medline and EMBASE for publications prior to July 2018, and proceedings from major ophthalmology conferences (January 2016 to July 2018). The search strategy combined terms for nAMD with terms for anti-VEGF and study design. The review focused on publications describing the impact of anti-VEGF on blindness, visual impairment, vision-related quality of life (VRQoL), mortality, and costs. The search targeted data collected in epidemiological or observational studies to reflect real-world outcomes but also considered modeling-based approaches.