dataesr/scientific-paragraphs-categorization huggingface dataset:
Multivariate analyses of (non-)parallelism and convergence In addition to comparing all lake-stream divergence vectors in a pairwise manner, we performed the recently described eigen analyses of vector correlation matrices (C)  (34). These multivariate analyses allow the quantification of the extent of parallelism/antiparallelism by assessing the percentage of variance explained by the leading eigenvectors of C. These analyses also reveal how many dimensions of shared evolutionary change exist, by inferring how many eigenvalues are significant. For each dataset (phenotype, genotype outlier, and genotype non-outlier), we calculated the eigen decomposition of the respective matrix of vector correlations C described above (C = QVQ -1 ) to extract eigenvectors (Q) and eigenvalues (V) of each dataset.
To construct a null expectation of evolutionary parallelism, we used an identity matrix sampled from the m-dimensional Wishart distribution with n degrees of freedom as suggested by De Lisle and Bolnick  (34) , where m is the number of lake-stream pairs and n is the number of traits/landmarks. To infer which traits/ landmarks/PCs contribute the most to the leading eigenvector of C, we investigated the value of trait loadings in the matrix A, where A = X T Q T-1. Furthermore, we investigated levels of convergence/divergence in multivariate trait space by comparing the among-lineage covariance matrices of trait mean values (D) for each environment  (34). Specifically, for each one of the three datasets (phenotype, genotype outlier, and genotype non-outlier), we calculated D river and D lake and their respective trace, which encompasses the total amonglineage variance per environment.
The position of the laid eggs was used as a measure for female preference (conspecific choice coded as 1 and heterospecific and no choice coded as 0). The binomial data were then analyzed with a generalized linear mixed model, which tested whether the probability of the females spawning with the conspecific male was significantly different from 0. 5. In the second experiment, female spawning decisions were determined in a multisensory setting with free contact between females and males. A single tank was subdivided into three equally sized compartments by plastic grids (fig. S4B ). The middle compartment offered a resting and hiding place for the females, whereas the two outer compartments served as male territories. The grid size was chosen to allow the smaller females to migrate between the three compartments and to prevent direct contact between the larger males to exclude male-male competition.
Acknowledgments: We would like to thank  F. Ronco ,  A. Indermaur , and  G. Pauquet  for help during fieldwork; the crews of the  Kalambo Lodge and the Ndole Bay Lodge  for logistic support in Zambia; and the  Lake Tanganyika Research Unit, Department of Fisheries, Republic of Zambia  and the  University of Burundi , the  Ministère de l'Eau, de l'Environnement, de l'Amenagement du Territoire et de l'Urbanisme, Republic of Burundi  for research permits. We thank  A. El Taher  and  M. Malinsky  for help with data analyses;  M. Conte  for sharing the Chromonomer results;  A. Böhne ,  M. Matschiner , and four anonymous reviewers for valuable comments on the manuscript; and  J. Johnson  for fish illustrations. Last, we are grateful to the support team of  sciCORE (Center for Scientific Computing, University of Basel ; http://scicore.
2015 ; Gago-Ferrero et al. 2018 ; Gago-Ferrero et al. 2015 ; Hug et al. 2014 ; Schymanski et al. 2015 ). A suspect list relevant for drinking water can be created by prioritising compounds based on their physicochemical properties  ( Dürig et al. , 2019 )  and/or exposure indices and usage quantities derived from regulatory databases  ( Gago-Ferrero et al. 2018 ). To build confidence in the identification, mass accuracy, fragmentation and isotopic profiles can be considered, leading to different levels of confidence  ( Schymanski et al. 2014 ). Suspect screening approaches have been applied to search for CECs in surface water and groundwater ( Andres-Costa, Andreu, and Pico 2016 ;  Gago-Ferrero et al. 2015 ) , but there is a lack of suspect screening studies focusing on drinking water quality.
01% of formic acid was added to both the water and acetonitrile phases and 5 mM of ammonium formate were added to the water phase. The same linear gradient was used in both ionisation modes, with a flow rate of 0. 5 mL min -1. The gradient started at 5% acetonitrile and increased to 99% acetonitrile with a total run time of 21 min. The injection volume was set to 10 μL. The main instrument settings were: 350V capillary voltage in positive mode, 400 V in negative mode, 4 V low collision energy and 10 to 45 eV for high collision energy (ramping). Data were collected using MS Emode and the resolution was ~30 0 0 0 at 556. 28 m/z , with leucine enkephalin used as lock spray (for lock mass correction). The software used for both data collection and evaluation was UNIFI v1. 8. 2. More details of the instrumental analysis are given in Tröger et al.
Suspect list creation The suspect list created using SusTool  ( Dürig et al. , 2019 )  included in total 500 compounds. SusTool uses a database comprising of > 30 0 0 0 compounds, which are relevant for human and/or environmental exposure, and a scoring system to prioritise suspects based on physicochemical properties, environmental fate characteristics, endocrine disruption potential, usage quantity and exposure indices. Although SusTool includes a large database, it is not exhaustive and could be complemented with even more compounds (e. g. CEC transformation products and disinfection byproducts) as well as more toxicological parameters. The parameters used to prioritise the compounds were log D (pH adjusted octanol/water partition coefficient), log K oc (organic carbon/water partition coefficient), log S w (water solubility), log BCF (bioconcentration factor), biodegradation, QI (quantity index), EI (exposure index) for water, EI for sewage treatment and EI for consumers.
Each parameter was assigned a weight between 1-5 according to its relevance for a suspect list focused on surface water and drinking water (see Table  2  ). A high final score means high ranking on the suspect list. The database was sorted based on the total score, and only compounds deemed to be LC compatible (log K ow < 5 (octanol/water partition coefficient)) were selected for further consideration. The top 500 compounds were selected for suspect screening. The full list is given in Table  A6  in the Appendix and the full SusTool Excel file, with all details, can be downloaded from the supporting information in  ( Dürig et al. , 2019 ).
Quality assurance and method performance All compounds were identified using accurate mass screening with a 10 ppm mass error data extraction window and retention time using a one-minute time window. Isotope patterns and fragmentation spectra were also considered for the identification. The software (UNIFI) performs an in silico fragmentation of all compounds and searches for matching fragments in the high-collision energy spectra for each identified peak. If a matching fragment is found, it increases the identification certainty. The ±H adduct was used for quantification in all cases, and all target compounds were quantified using an external 8-point calibration curve, in 50:50 methanol:Milli-Q, with concentrations ranging from 0 to 120 ng L -1. The method detection limit (MDL, ng L -1 ) for the 177 target compounds was calculated from the detection limit (DL) as: MDL = DL+ 3 * RS D spiked * DL DL = C spiked * R cutoff / R spiked -R blank C spiked : nominal concentration in the spiked sample (50 ng L -1 ) R cutoff : minimum detector counts (100) used to not discard a peak R spiked : average detector counts in spiked sample R blank : average detector counts (if detected) in blank sample RSD spiked : relative standard deviation in the spiked sample A cut-off value of 100 counts for discarding a peak was applied, based on expert judgment in accordance with normal noise conditions during a typical analytical run.
Suspect screening To investigate a broader set of compounds, suspect screening was performed by searching for 500 suspects in both positive and negative ionisation mode in all raw and drinking water triplicate samples. A database was created in UNIFI with the molecular structures for all 500 compounds prioritised by SusTool (see section 2. 5 ). This database was later used to perform in silico fragmentation of the compounds. To be considered a detected feature to match a suspect, a maximum ±2 mDa mass error was required. To increase confidence in the assigned suspects, only features that had at least one detected in silico fragment with a maximum mass error of ±4 mDa were considered. The next step was to manually check all suggested candidates and judge their peak shapes, in order to classify them as real peak or noise integration.
Conclusions Concentrations of CECs in raw water and drinking water were screened using comparative data on samples obtained from 13 fullscale DWTPs located in different countries and continents. The analyses clearly showed that many known and unknown mobile CECs pass through artificial barriers (DWTP treatment) around the world and are found in treated drinking water, although in generally low concentrations (mostly below statutory threshold levels). This emphasizes the value of employing good analytical methods and extensive detection workflows to detect and identify CECs in DWTPs and to evaluate the efficiency of treatment techniques. The raw water used by the different DWTPs contained a wide range of CECs, including PFASs, pharmaceuticals, pesticides and other compounds. In total, 115 different CECs out of 177 analysed were detected in at least one water sample.
Acknowledgements This work was supported through projects funded by the  Swedish Research Council Formas SafeDrink  (grant numbers  222-2012-2124 ) and LakePOPs (grant number  2016-01173 ). We thank all participating DWTPs for assistance in sampling and sample shipping. We would also like to acknowledge the following participants for coordinating the local sampling:  Juliane Hollender (Eawag ,  Swiss Federal Institute of Aquatic Science and Technology, Switzerland) ,  Tim Boogaerts ,  Adrian Covaci  and  Pieter Joos  ( Toxicological Center, University of Antwerp, Belgium ),  Rita Binetti  ( Researches and Controls Laboratories, Drinking Water Department Società Metropolitana, Italy ) and  Sara Castiglioni  ( Mario Negri Institute for Pharmacological Research, Italy ).
METHODS A monocentric, retrospective and descriptive study was performed on patients treated with ICIs (nivolumab, pembrolizumab, ipilimumab, or cemiplimab) in the Department of Dermatology of the University Hospital of Brest and in the associated Department in the Hospital of Landerneau. The study was approved by the ethics committee of Brest (B2019CE. 19)  and was registered at clinicaltrials. gov (NCT04365244). The inclusion criteria were as follows: age 18 years and older, treated with ICIs (nivolumab, pembrolizumab, ipilimumab, and cemiplimab) for melanoma, squamous cell carcinoma or Merkel cell carcinoma and not having formulated any opposition. The exclusion criteria were as follows: age under 18 years, adults not legally competent, presence of pruritus at inclusion, and participation refusal.
We conducted a descriptive analysis of the data. Quantitative data are described by their size, mean, standard deviation, median, extreme values (minimum and maximum), and number  of missing data. Qualitative data are described by their distributions in terms of numbers and percentages and the number of missing data. We used Excel for descriptive analyses. Overall survival (OS) was analyzed using a multivariable Cox model with a time-dependent covariate to examine the association between pruritus onset and survival. Pruritus onset was considered a dichotomous (present/absent) time-dependent covariate without transition back from a state of present to a state of absent. Pruritus exposure also declined according to its origin: immunotherapy-induced or systemic, leading to two dichotomous time-dependent covariates without transition back from a state of present to a state of absent.
Characteristics of the Population One hundred and eighty-one patients were included (175 melanoma and six squamous cell carcinoma cases). Demographic data are presented in Table  1. In spite of our small numbers of patients when we compared patients without any pruritus to those who experienced pruritus and found significant differences in patient characteristics with regard to vitiligo and dysthyroidism (Table  1 ). Pembrolizumab (44. 7%), nivolumab (35. 9%), ipilimumab (17. 1%), and cemiplimab (2. 3%) were prescribed as first-line treatments. The average number of infusions was 13. 6; the median was 7, and the extreme values were 1-86 infusions. Thirty-six patients (19. 8%) received a second line of ICIs: ipilimumab for 19, nivolumab for 10, pembrolizumab for 7, and cemiplimab for 1. The average number of second-line infusions was 5.
Open access registries with high-quality data on EVT-treated patients may help answering some of these unanswered issues, especially on safety and efficacy of EVT in specific patient subgroups. Future plans This collaborative effort aims at addressing clinically important questions on safety and efficacy of EVT in conditions not covered by RCTs. The TRISP registry generated substantial novel data supporting stroke physicians in their daily decision making considering IVT candidate patients. While providing observational data on EVT in daily clinical practice, our future findings may likewise be hypothesis generating for future research as well as for quality improvement (on EVT). The collaboration welcomes participation of further centres willing to fulfill the commitment and the outlined requirements.
ABSTRACT Purpose The Thrombolysis in Ischemic Stroke Patients (TRISP) collaboration was a concerted effort initiated in 2010 with the purpose to address relevant research questions about the effectiveness and safety of intravenous thrombolysis (IVT). The collaboration also aims to prospectively collect data on patients undergoing endovascular treatment (EVT) and hence the name of the collaboration was changed from TRISP to EVA-TRISP. The methodology of the former TRISP registry for patients treated with IVT has already been published. This paper focuses on describing the EVT part of the registry. Participants All centres committed to collecting predefined variables on consecutive patients prospectively. We aim for accuracy and completeness of the data and to adapt local databases to investigate novel research questions.
The Endovascular Treatment and Thrombolysis for Ischemic Stroke Patients (EVA-TRISP) registry aims at meeting these prerequisites. Using our decade-long experience from the multinational TRISP registry,  20  we are now aiming to build a prospective multinational registry of AIS patients treated with EVT including detailed clinical, laboratory and imaging data for future analyses. We are presenting herein the current versions of the clinical and imaging database items of the EVA-TRISP registry. Additionally, we will discuss a selection of specific related topics.
AIMS OF THE EVA-TRISP REGISTRY The major aim of EVA-TRISP is to address clinically important questions about safety and outcomes in AIS patients treated with IVT and/or EVT that are not covered by RCTs. The idea of EVA-TRISP is that experienced stroke centres with a record and expertise in both: (1) usage of IVT and/or EVT and (2) maintenance of hospital-based stroke databases pool their data. In addition to the characteristics of the EVA-TRISP centres stated previously, an advantage of EVA-TRISP is the availability of more additional variables than in other large-scale registries and the commitment by the collaborators to: (1) submit accurate and complete data and to (2) be.
COHORT DESCRIPTION The TRISP collaboration was a concerted effort initiated in 2010 by 11 European stroke centres with the purpose to address clinically relevant research questions about the effectiveness and safety of IVT, and currently, 20 stroke centres from nine different countries participate in the collaboration (see figure  1  and online supplemental appendix 1 for a list of member sites and investigators). As the collaboration also aims to prospectively collect granular and high-quality data on all consecutive stroke patients undergoing EVT, the name is changed from TRISP to EVA-TRISP. EVA-TRISP (former TRISP) operates as an independent, non-profit, investigator-driven open platform that focuses on generating high-quality data for clinical research purposes. The EVA-TRISP research initiatives are characterised by informal, project-driven and relaxed work processes based on a high level of mutual trust and understanding between participating collaborators, and no formal scientific leadership committees have so far been implemented or deemed necessary.
This paper focuses on describing the EVT part of the registry. The EVA-TRISP registry aims to prospectively collect granular and high-quality data on all consecutive AIS patients undergoing both IVT and/or EVT. The overall purpose is to provide a means to address clinically important research questions on the safety and effectiveness of IVT and/or EVT in AIS patients that are typically not covered by RCTs or single-centre research initiatives. Furthermore, the EVA-TRISP aims at providing a large data source for various stroke care quality improvement initiatives. All EVA-TRISP centres have a proven track record for delivering high-quality and high-volume stroke patient care. Every EVA-TRISP centre offers stroke management that fulfils the criteria of stroke centres or stroke units as proposed by the ESO.
22 The simple idea Open access of the EVT part of the EVA-TRISP registry is that experienced stroke centres with expertise in both EVT implementation and in the maintenance of hospital-based EVT databases pool their data together. An advantage of the EVA-TRISP registry is the availability of substantially more variables than in other large-scale registries. We strive for a commitment by the collaborators to provide data of high accuracy and completeness as well as towards a willingness among collaborators to swiftly adapt the local databases by adding new variables of interest. This enables a potential for explorative insights in the putative prognostic importance of variables with unknown influence on outcome or risk of complications, such as symptomatic intracranial haemorrhage (sICH). Strengths and limitations of the EVA-TRISP registry in general and compared with other existing EVT registries are discussed further (please see Discussion).
The participating centres have all agreed to fulfil the prerequisites that are summarised in box 1. Participation in other registries does not preclude participation in the EVA-TRISP registry. A standard database template has been developed by an international expert group consisting of stroke physicians and scientists in collaboration with all members, leading to the current standard version of the registry (see online supplemental appendix 2 -registry data elements), which has been agreed on by all EVA-TRISP member sites. This comprehensive dataset includes over 110 items and covers a wide range of data elements, including demographics, prestroke health information, acute phase management and longterm outcomes including 3 months and 1 year modified Rankin Scale (mRS) as well as detailed laboratory data and imaging findings.
Data collection and definitions Data on the characteristics of patients are collected prospectively by all participating centres using standardised definitions and a standardised form. Not all centres have to provide data on all variables but have given a commitment to add missing variables retrospectively, if considered relevant to answer a specific research question. The dataset includes patient demographics, history, prehospital information, admission data, details on acute interventions, stroke unit and/or intensive care information, discharge, rehabilitation, outcome data (3 months and 1 year outcomes measured by mRS), as well as detailed laboratory test results, vital signs and imaging findings (see online supplemental appendix 2). Risk factors and stroke aetiology will be determined according to standard approaches across centres.
Open access (NIHSS) score of more than or equal to four points and if the hemorrhage was likely to be the cause of the clinical deterioration'). 24 6] [27]  Functional outcomes at 3 months and 1 year are assessed using the mRS. The mRS is obtained by telephone calls, postal/electronical questionnaires or outpatient visits. If patients cannot be interviewed, close relatives, nurses or family doctors are asked for disability status. We are currently exploring technical, legal and ethical as well as financial backgrounds for establishing an electronic registry to one of the member centres that would allow direct data insertion from each centre and holding the registry compactly in one single file. Otherwise, each centre will maintain their own registry within their own electronic system, and data will always be transferred without personal identifiers for each single analysis looking at one single aspect and leading to one mutual international publication.
Establishing and maintaining such a large database with complete compliance to rules and safety measures is a costly procedure and requires long-term funding. This option is now under exploration. Future plans in the registry include the addition of a neuroradiology imaging bank that will enable detailed image analysis of patients treated with IVT and/or EVT. The imaging bank will provide 'real-world' diagnostic neuroradiology and, used in combination with detailed clinical information from the EVA-TRISP registry, analysis of these imaging data will help to: (1) create standardised imaging protocols in acute stroke (ie, defining optimal threshold for perfusion parameters), (2) identify new (ie, a collateral score for the posterior circulation) and validate published (ie, different collateral scores for the anterior circulation) imaging outcome predictors and imaging-based selection tools for reperfusion therapies, (3) assess the generalisability of RCT results to subgroups of patients who would have been excluded based on imaging criteria (ie, baseline Alberta Stroke Program Early CT score (ASPECTS) under five, extracranial vessel pathologies), (4) improve automated analysing techniques (ie, machine and deep learning algorithms), and (5) enhance the accuracy of outcome prediction of different clinical and imaging parameters by implementing new imaging outcomes (e.
g. infarct volume, recanalisation status). Neuroimages from TRISP/EVA-TRISP patients since 2015 will be pooled centrally. All imaging modalities (non-contrast CT, CT angiography, CT perfusion, MRI, MRA, MR perfusion and digital subtraction angiography) at baseline and follow-up (up to 3 months after stroke onset) will be eligible for analysis. Image analyses will be performed blinded to clinical information and treatment decisions and undergo a central systematic re-evaluation using a specified case report form including all predefined imaging variables. Stroke-specific image analysing software (ie, OSIRIX medical imaging viewer, Quantomo for semiautomated volumetric analysis and Rapid Processing of Perfusion and Diffusion for perfusion analysis) could be used. A detailed case report form for image analysis will be designed in review with all collaborators.