dataesr/scientific-paragraphs-categorization huggingface dataset:
It aims to evaluate clinical presentation, disease course, treatments, outcomes and time trends, and facilitates recruitment of patients for research studies. Participating centres contribute data continuously and additional centres can join. Eligible datasets and collaborating centres were initially identified through the BESTCILIA project and the BEAT-PCD network. For ERN-LUNG PCD CORE members and associated partners, participation in the International PCD Registry is mandatory in order to fulfil EU requirements. The International PCD Registry collects data on diagnostics (high-speed videomicroscopy, transmission electron microscopy, nasal nitrite oxide, immunofluorescence microscopy and genotype), age and health status at diagnosis, family history, clinical manifestations, associated malformations/diseases, progression of the disease, exacerbations, microbiology, lung function, radiological findings, therapeutic measures (inhalation, antibiotics, oxygen, ventilation, ENT and lung surgery), date and cause of death, fertility, and quality of life using PCD-specific instruments[57].
Acknowledgements: We would like to thank the following collaborators for their contribution in setting up and maintaining the PCD registries and cohort studies. Cyprus PCD Registry:  Panayiotis Kouis ,  Respiratory Physiology Laboratory, Medical School, University of Cyprus, Nicosia, Cyprus. English Paediatric PCD Management Service:  Jane Lucas ,  Claire Hogg ,  Chris O'Callaghan ,  Woolf Walker ,  Siobhan B. Carr ,  Anton Page ,  Patricia Goggin ,  Claire Jackson ,  Regan Doughty ,  Janice Coles ,  James Thompson ,  Bruna Rubbo ,  Corine Driessens ,  Samantha Packham ,  Amelia Shoemark ,  Sarah Ollosson ,  Charlotte Richardson ,  Farheen Daudvohra ,  Ranjit Rai ,  Paul Griffen ,  Andrew Rogers ,  Robert Hirst ,  Andrew Rutman. Philip Chetcuti ,  Manjith Narayanan ,  Priti Kenia ,  Eduardo Moya ,  Amanda Harris ,  Amanda Friend ,  Victoria Keenan ,  Hannah Wilkins ,  Hasnaa Ismail-Koch ,  Andrea Burgess ,  Gemma Marsh ,  Laura Baynton ,  Michael Leshen ,  Nicola Collins ,  Peter Rea ,  Ann-Louise McDermott ,  Amanda Parsons ,  Rajinder Kang ,  Nicola Lloyd ,  Alison Truscott  and  Lynne Schofield.
https://doi. org/10. 1183/23120541. 00005-2020 French RaDiCo-PCD Cohort The French RaDiCo-PCD Cohort was founded in 2017 with the Research National Agency as a sponsor, under the authority of the French Minister of Higher Education, Research and Innovation, and sustained by the French National Rare Lung Disease Network. The cohort is hosted at the French National Institute of Health and Medical Research (Institut National de la Santé et de la Recherche Médicale, Inserm, Paris, Standardised retrospective database FOLLOW-PCD prospective database.
For participating centres without access to genetic testing, this is offered within the framework of research projects. iPCD Cohort International PCD Registry Study design Cohort study, collaborative dataset Registry Year founded 2013 2014 Inclusion criteria National, collaborative or single-centre datasets of patients National, collaborative or single-centre datasets of patients (any age) diagnosed and treated for PCD (any age) diagnosed and treated for PCD National legal and ethical requirements met by National legal and ethical requirements met by participating centre participating centre Both cross-sectional and longitudinal datasets accepted (longitudinal encouraged) Patients with probable or confirmed PCD diagnosis who Patients with a confirmed PCD diagnosis fulfilling the are treated as PCD in the participating centres, ranging following diagnostic criteria: clinical presentation from clinical presentation consistent with PCD to consistent with PCD and consistent findings specific for diagnosis established with several PCD diagnostic tests PCD by at least two methods (high-frequency video based on the European Respiratory Society diagnostic microscopy analysis, transmission electron microscopy, recommendations immunofluorescence microscopy and low nasal nitric oxide concentration/production or biallelic disease- causing mutations by genotyping) Written informed consent needed for prospective data, Entering individual patients requires written informed depending on national laws consent by the patient or his/her legal guardian(s) Patients (2019) n 3824 920 Participating Argentina, Australia, Belgium, Canada, Colombia, Cyprus, Austria, Belgium, Canada, Cyprus, Denmark, France, countries Czech Republic, Denmark, France, Germany, Greece, Greece, Germany, Italy, Netherlands, Slovakia, Spain, Israel, Italy, Netherlands, Norway, Poland, Serbia, Spain, Switzerland, Turkey, UK, USA Switzerland, Turkey, UK, USA Prospective/ Retrospective and prospective Prospective (and retrospective) retrospective Type of data Pseudo-anonymised Pseudo-anonymised ClinicalTrials.
gov NCT03517865 NCT02419365 identifier Database REDCap database Internet-based data entry system; will be transferred to REDCap October 2019 Easy data import and export in several formats Easy data import and export in several formats Each collaborator has access to own data Each collaborator has access to own data Basic data set is monitored for completeness, further items are currently checked manually for plausibility by experts Funding EU-funded BESTCILIA project (FP7/2007-2013) under grant EU-funded BESTCILIA project (FP7/2007-2013) under grant agreement 305404, Swiss National Science Foundation agreement 305404, Eva Luise Köhler Research Award, 320030_173044, Pro-Kartagener Foundation Milena Care-for-Rare Science Award, REGISTRY WAREHOUSE Karvajal and institutional funding (Horizon 2020, grant agreement 777295), DFG CRU326 (OM6/11) and institutional funding.
Validation of polyQ polymorphism by sizing the PolyQ repeat of the AR receptor gene In order to validate the results on AR obtained by LASSO logistic regression, we seized the male subset (351 subjects) using the gold standard technique that uses a fluorescent PCR reaction followed by the use of GeneScan Analysis software ® (Applied Biosystems) for sizing the number of triplets  21. Based on the AR polyQ length, male patients were subdivided into two categories, those having a number of PolyQ repeats less than or equal to 22 repeats, and those having a number of PolyQ repeats greater than or equal to 23 repeats, being 23 repeats the reference sequence on genome browsers. We found that PolyQ repeats below 22 are enriched in the asymptomatic cohort of males. The difference was statistically significant in the group of males younger than 60 years of age in which genetic factors are expected to have a major impact (p-value 0,024) (Table  2;  Supplementary Table  S1 ; Supplementary Table  S2 ).
9%) were more frequently reported in subjects with ≥25 repeats, but not osteopenia/osteoporosis (6% vs 7%). These results indicate a trend toward clinical hypogonadism for those with longer repeats. Conversely, in the entire male dataset, 6 cases of prostate cancer were found annotated in the past-medical history, all in the ≤22 glutamines group, suggesting an increased prostate sensitivity to androgens. No difference was found in the prevalence of BPH or 5-alfa-reductase inhibitors use. As the reduced signal transduction of AR might be compensated by higher testosterone levels, as shown in Fig 2a, we tested whether the feedback was sufficient to overcome polyQ repeats. A binomial logistic regression was performed to ascertain the interaction between age, testosterone levels and polyglutamine receptor length on the likelihood that subjects require intensive care during COVID infections.
Binary representation of WES data In this paper, one of several synthetic approaches to genetic data variability representation is used: poly-amino acids repeat polymorphisms (Benetti et al. , Topological   Data Analysis on boolean representation of genome variability as a method for discovering the genetic bases of complex disorders. Paper in preparation). Reads were mapped to the hg19 reference genome by the Burrow-Wheeler aligner BWA. Variants calling was performed according to the GATK4 best practice guidelines. Namely, duplicates were first removed by MarkDuplicates, and base qualities were recalibrated using BaseRecalibration and ApplyBQSR. HaplotypeCaller was used to calculate Genomic VCF files for each sample, which were then used for multi-sample calling by GenomicDBImport and GenotypeGVCF.
Representation of poly-amino acids triple repeats: A set of binary variables was included to correctly describe non-frameshift variants in gene portions with repeated triplets. A total of 43 genes with triplet repeat variability were taken from UniProtKB (https://www. uniprot. org/uniprot/?query=reviewed:yes%20keyword:%22Triplet%20repeat %20expansion%20%5BKW-0818%5D%22). For any of these genes a variant Dij was defined as equal to 1 if the i-th gene presented a deletion in the region characterized by repeated triplets. Non-informative genes, with either all 0 or all 1, are removed from the dataset.
This choice is related to the aim of the work that is to select the most important genes (and not necessarily the entire set of genes contributing to COVID-19 variability). During the fitting procedure, the class slight unbalancing is tackled by penalizing the misclassification of the minority class with a multiplicative factor inversely proportional to the class frequencies. The data preprocessing was coded in Python, whereas for the logistic regression model the scikit-learn module with the liblinear coordinate descent optimization algorithm was used. Performances of the model were evaluated using the cross-validation confusion matrix as well as by computing precision, sensitivity, specificity, and the Receiver Operating Characteristic (ROC) curve.
ACKNOWLEDGMENTS The authors thank  Thomas Iadecola  for fruitful discussions. A. H. and I. V. acknowledge funding provided by the  Institute of Physics Belgrade , through the grant by the  Ministry of Education, Science, and Technological Development of the Republic of Serbia. N. R. was supported by the  Department of Energy  Grant No. de-sc0016239 , the  National Science Foundation  EAGER Grant No. DMR 1643312 , Simons Investigator Grant No. 404513 ,  ONR  Grant No. N00014-14-1-0330 , the  Packard Foundation , the  Schmidt Fund for Innovative Research , and a  Guggenheim Fellowship  from the  John Simon Guggenheim Memorial Foundation. Z. P. acknowledges support by  EPSRC  grant  EP/R020612/1  and the  National Science Foundation  under Grant No. NSF   PHY-1748958. Part of the numerical simulations were performed on the PARADOX-IV supercomputing facility at the  Scientific Computing Laboratory, National Center of Excellence for the Study of Complex Systems, Institute of Physics Belgrade.
Background: Since the onset of the new coronavirus pandemic, the world is facing a public health emergency. Repositioning hydroxychloroquine (HQ) seems to be a promising option. Many emerging evidences have converged on the effectiveness of HQ in the treatment of Covid-19 infection. In a recent paper, Gautret et al. suggested that further works are needed to determine if HQ antiviral prophylaxis is useful, especially for healthcare workers. Methods: The purpose of this paper is to assess the Covid-19 exposure and risks level among caregivers. For this, we performed research on internet and PubMed by crossing the following keywords: healthcare givers, healthcare workers, doctors, nurses, coronavirus, Covid-19, mortality, infection rate, chloroquine, hydroxychloroquine. Results: Data on healthcare worker's infection and mortality by Covid-19 are partial and are not systematically published.
TYPES OF CAPACITY-BUILDING ACTIVITIES FOR TRANSPARENCY BY THE MAIN INTERNATIONAL SUPPORT INITIATIVES 2. 1 Overview of the main international support initiatives to implement the ETF Information about the main international support initiatives to developing countries, including LDCs and SIDS, has been sourced from the 'MRV Group of Friends' database 1 of ongoing support initiatives for monitoring, reporting, verification (MRV) and transparency, as well as the websites of the individual initiatives. The Group is informally coordinated by the UNFCCC Secretariat and includes about 14 international institutions and countries, including UNEP DTU Partnership. An overview of the main support initiatives, and the period over which they are implemented, is provided below in Figure  3. BURs by the UN Environment Programme (UNEP) and the UN Development Programme (UNDP) will finish in 2020, but will transfer into a new GEF-funded programme and will merge with the CBIT Global Coordination Platform (GCP).
2  Further information about which LDCs and SIDS are supported by the initiatives is provided in Appendix 2. Analysis of the data in Appendix 2 gives an overview of the number of all support activities (both project-type and workshop-type) to all LDCs and SIDS, which can be seen in Figure  4  below. Source: Own analysis based on 'MRV Group of Friends' database and the respective initiatives' own websites, 2019 Figure  4  shows that all LDCs and SIDS have received at least two support activities from the main initiatives, and most countries have received three support activities. The countries that have received the most support -the 'donor darlings', receiving six support activities each -are Burkina Faso, Cambodia, Cuba, Dominican Republic, Ethiopia and Rwanda. By ranking the international support initiatives according to the number of countries supported, an overview can be seen of the geographical outreach and size of the initiatives, as shown in Table  1.
3. The average funding of all CBIT projects is USD 1,276,788. The average funding of CBIT projects in LDCs is slightly lower at USD 1,164,807, while the average funding of CBIT projects in SIDS is even lower at USD 1,066,056 (based on own analysis using data from the GEF projects database, as of 20 November 2019). technical and institutional capacities built are likely higher than those through annual workshops or trainings. This is especially the case for the support provided by the GEF Enabling Activities, as countries are supported for the preparation of consecutive NCs and BURs over many years. With regard to project support, Figure  5  provides an overview of the number of countries supported by projects. Source: Own analysis based on 'MRV Group of Friends' database and the respective initiatives' own websites, 2019 As Figure  5  shows, 1 country is supported by 4 projects (Ethiopia), 6 countries are supported by 3 projects, 25 countries are supported by 2 projects, 45 countries are supported by 1 project and 1 country is not supported (Singapore).
Countries supported by 1 project have received support from the GEF Enabling Activities. Appendix 2 provides further information on which countries receive how much support from which initiatives. A ranking of which LDCs and SIDS receive the most and least support through projects is shown in Table  3. Source: Own analysis based on 'MRV Group of Friends' database and the respective initiatives' own websites, 2019 Ethiopia receives support from four projects, while Burkina Faso, Cambodia, Cuba, Dominican Republic, Rwanda and Uganda receive support from three projects for capacity building to implement the ETF. The remaining 70 LDCs and SIDS receive support from one or two projects. Appendix 2 provides further detail on which international initiatives support which countries. With regard to the mode of support through workshops/training/dialogues, Figure  6  shows the number of countries supported by the initiatives CGE, GSP, PATPA and the MRV Hub for the Caribbean.
• The European Environment Information and Observation Network (Eionet) is a partnership network of the European Environment Agency (EEA) and its 39 member and cooperating countries. The countries have an obligation to report to the EU and GHG Monitoring Mechanism Regulation (MMR). The MMR has now been substituted by Governance of the Energy Union and Climate Action and the first report will be in 2021. Data from the three sources is overlapping, as they report the same activities. ODA is an important part of the OECD reporting and is therefore used to make an overview of the projects covering climate financing for LDCs and SIDS, covering the period 2012-2017. Table  6 , below, presents all the LDCs and SIDS that Nordic countries have provided climaterelated ODA support to. 5  Appendix 5 provides a more detailed breakdown of the support, which shows how many climate-related projects each Nordic country has in each LDC and SIDS.
6. Note that support from international initiatives to workshops/training/dialogue is not included in the analysis of CB needs by LDCs and SIDS countries. The workshop-type support typically targets multiple countries to attend regional or global events. As this modality of CB support is not tailored to country specific needs but rather focuses on generic, ETF technical issues and knowledge sharing among many countries, it is not included in this analysis. Source: Own analysis based on 'MRV Group of Friends' database 2019 and the OECD DAC reported information by the Nordic countries between 2012 and 2017. If the Nordic countries are aiming to target support to LDCs and SIDS with a strong history of Nordic country presence, but with a poor presence of transparency-related activities, then countries with green colour coding in Figure  9  should be prioritised, followed by the green ones in Figures  10  and 11.
Source: Own analysis based on 'MRV Group of Friends' database 2019 and the OECD DAC reported information by the Nordic countries between 2012 and 2017 The fading of the colour of the green and orange bars over the three graphs illustrates an increasing number of project-type support received by international transparency initiatives. This represents the declining prioritization of potential countries for further CB support by Nordic countries. Ethiopia, the only country receiving four transparency project-type support, has the faintest colour coding. Assuming that the Nordic countries intend to further support countries with established relationships and prioritize LDCs and SIDS, which have received the least or medium support from international support initiatives (one or two projects only, see Figures 9 and 10), a shortlist for Nordic CB support to transparency is suggested as follows: • LDCs and SIDS with the least capacity for transparency and Nordic ODA support: Nepal, Zambia, Democratic Republic of Congo, Mali, Somalia, Bhutan, Burundi, Niger, Angola, Guyana, South Sudan (Figure  9 ).
Examples of country-specific challenges and needs The following section includes identified transparency needs and gaps from the countries selected according to criteria presented in Annex 7. The information is sourced from a review of the latest NCs and interviews during COP25 in Madrid. Remote interviews have been attempted with the two countries that were not reached during COP, however they did not respond after COP either and are therefore left out. The information included in the NCs predates the ETF and MPG, and tends to be focused on the needs related to GHG inventories, while the interviews provide more insights on the broader aspects of transparency support needed. The interviews were designed to capture the following information: • Key priorities -and the gaps to meet these -for MRV/transparency in relation to the ETF requirements; • Key challenges to meet the ETF requirements; • Lack of complete activity data on solid waste management and wastewater flow from all utilities and industries, pit latrines and incineration.
g. application of IPCC methodology to be able to report GHG inventories. The identification of gaps and challenges depends on the perspective from which these are analysed. Taking an international transparency perspective, challenges and gaps can be framed around the ability to submit timely communications to the UNFCCC, the ability to use high IPCC tier level methodologies for GHG inventory, or the availability of data to respond to both shall and should reporting requirements in BTRs. From a country perspective, challenges and gaps are more related to the ability to assess the effectiveness of national policies, such as capacity to assess sustainable development impacts of climate policies, alignment with national development plans, and availability of priority sectors' activity data for improved planning.
Analysis of CBIT support requests reflecting country needs and gaps for CB Looking at CBIT funds to developing countries can provide some information on the transparency-related needs and priorities expressed. Figure  12 , below, illustrates the percentage of specific types of CB activities included in approved CBIT projects. Focusing on LDCs and SIDS, there is a similar prioritisation, although LDCs and SIDS seem to have more focus on support needed for GHG Inventory Data Collection and Management Tools, and general GHG Inventory improvements (GEF, 2019). Looking beyond approved CBIT projects, and analysing LDCs and SIDS Project Identification Forms (PIF) submitted to the GEF for CBIT funding, a specific set of trends arise. Figure  13  and Figure  14  illustrate the number of outputs LDCs and SIDS have included in their PIFs, as it relates to a specific set of categories.
• The mid-spread dispersion of capacity level in the group, which is a measure of where the middle 50% of countries are -for example, there is more spread in the group of other developing countries than in the groups of LDCs and SIDS (the coloured boxes). This means that the group of other developing countries is less homogeneous. The areas of the GHG inventory where LDCs and SIDS are lagging somewhat behind other developing countries are methodologies and procedures for data collection and management. Figure  17  (left) shows that half of the LDC and SIDS countries in the sample have a capacity level on methodologies for GHG inventory between 44% and 64%, whereas the capacity level in half of other developing countries is within 48% and 81%. There is a more accentuated difference in the levels of capacity on data collection and management procedures for GHG inventory, as shown in Figure  17  (right).
The capacity level on data collection and management procedures in the majority of the other developing countries is within 54% and 81%, whereas in the LDCs this level ranges between 21% and 73%, and in SIDS countries it is within 32% and 61%. Half of the LDCs have a capacity level on data collection and management procedures for GHG inventory below 43%, whereas in half of SIDS countries it is below 50%. For the different groups of countries assessed (LDCs, other developing countries, and SIDS), the box-and-whisker charts of Figure  17  show, on a scale of 0 to 100: • The minimum value of capacity level in the group -the low end of the whiskers  In general, countries' assessment of the capacity level to report information on the implementation and achievement of NDCs is lower than the capacity level to report on national GHG inventory.
Synthesis of categories and types of gaps and needs Summarizing the gaps and needs in capacity-building efforts to LDCs and SIDS to implement the ETF, there are some general observations that can be used to highlight general trends, and to guide formulation of recommendations for Nordic countries' transparency support. In general, there are very low capacities on data collection and management, procedures for reporting on NDC progress and achievement, and procedures for reporting support needed. SIDS also have limited reporting capacities on climate change impacts and adaptation, especially in terms of institutional arrangements, and data collection and management and procedures. Additionally, there appears to be a large gap for SIDS on methodologies for NDC progress and achievement. In terms of priorities, LDCs seem to prioritise capacity building for GHG inventory improvements, followed by NDC progress and achievement, while SIDS seem to priorities building capacities in NDC progress and achievement, followed by climate change impacts and adaptation.