dataesr/scientific-paragraphs-categorization huggingface dataset:
| CON CLUS IONS This study highlights the power of combining ASV-and OTU-level community metabarcoding, enabled by the application of stringent filtering strategies, for the description of spatial biodiversity patterns of complex communities in understudied regions (Cyprus) and environments (soil), overcoming previous limitations of the taxonomic impediment, low-resolution data and noise due to the presence of spurious sequences. The wide implementation of harmonized field, laboratory and bioinformatic protocols for community metabarcoding of unexplored assemblages will increase the comparability of data sets from across the globe  (Arribas, Andújar, Bidartondo, et al. , 2021) , providing the basis for broad-scale analyses of metacommunity patterns that would enable drawing more general conclusions on the consistency or context-dependency of ecological processes across spatial scales and fractions of biodiversity.
ACK N OWLED G EM ENTS This work is a product of the iBioGen project, which has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 810729. We thank two anonymous referees for their constructive and valuable comments on an earlier version of the manuscript. We are grateful to the Department of Forests-Ministry of Agriculture, Rural Development and Environment, Republic of Cyprus-for providing sampling permission and cartography of the forest habitat distributions. We would like to express our gratitude to Savvas Savva and Heriberto López for assistance in designing and building soil processing facilities at the University of Cyprus, Zoe Makridou, Loudmila J. Lagou, Stylianos Mavrianos and Andreas Dimitriou for help during sampling and sample processing, Konstantinos Ntatsopoulos for support with Coleoptera taxonomy, and Angelina Ceballos-Escalera and Elena Lugli (Natural History Museum, London) for advice during metabarcoding library preparation.
We also wish to thank "Centro de Supercomputación de Galicia" (CESGA) for access to computer resources. V. N. was supported by a postdoctoral contract under the iBioGen project (grant agreement No. 810729) and a "Juan de la Cierva-Formación" postdoctoral fellowship (grant FJC2018-035611-I) funded by MCIN/AEI/10. 13039/501100011033. AUTH O R CO NTR I B UTI O N S V. N. and A. P. conceived and led the study. V. N. and E. M. performed fieldwork. V. N. performed laboratory work with help from E. M. A. C-I. generated climatic and topographic information and wrote the respective methodological section. V. N. and A. P. conceived the methodological approach and V. N. performed the analyses. V. N. wrote the manuscript with help from A. P. All authors contributed critically to the draft and gave final approval for publication.
Dysregulation of the Ras MAPK signaling pathway is implicated in the pathogenesis of autism spectrum disorder (ASD). The RASopathies, a group of disorders caused by mutations of the Ras/MAPK pathway genes, share many overlapping clinical features. Studies suggest a high prevalence of ASD in the RASopathies, but detailed characterization of the ASD profile is lacking. The aim of this study was to compare the ASD symptom profile of three distinct RASopathies associated with both gain-of-function and loss-of-function mutations: neurofibromatosis type 1 (NF1), Noonan syndrome (NS), and cardiofaciocutaneous syndrome (CFC). Participants were drawn from existing databases if they had a diagnosis of a RASopathy, met the criteria for ASD, and were able to communicate verbally. We compared the phenotypic profile of NF1 + ASD (n = 48), NS + ASD (n = 11), and CFC + ASD (n = 7) on the Autism Diagnostic Inventory (ADI-R) and the Autism Diagnostic Observation Schedule (ADOS).
Participants Participant data collected on children with NF1, NS, and CFC aged 4-18 years were available from three previously published independent studies  (15, 16, 27). Two studies characterized the ASD prevalence in NF1, NS, and CFC. A further sample was drawn from a randomized controlled trial (RCT) of simvastatin in children with NF1. Participants included as part of the simvastatin RCT were recruited from regional genetic centers and through NF charity advertisements. All participants had detailed ASD assessments. Participants who met the following inclusion criteria were included in this study:  (1)  meeting ASD cut-off on the Autism Diagnostic Interview Revised (ADI-R); (2) scoring above the ASD cut-off on the Autism Diagnostic Observation Schedule-2 (ADOS-2); (3) having a minimal language by sentence, as confirmed by the use of a module 2, 3, or 4 ADOS-2.
Children with "no or few words, " assessed with module 1 ADOS-2, were excluded from this study. Out of 212 children with RASopathies in the datasets, 69 children with RASopathies and ASD met the inclusion criteria. Among these children with RASopathies and ASD, three children were non-verbal and excluded from the overall analyses as their profile are not directly comparable with verbal ASD. Thus, our final population consisted of 66 children with RASopathies and ASD.
Statistical Analysis Data were analyzed in SPSS version 25 (SPSS Inc. , Chicago, USA). Mean (M) and SD (or ratio for categorical variable) of each characteristic of the population were described. As ADOS items, domain and overall scores CS, items of early general skills development, ADI-R algorithm subscores, and ADI-R algorithm domains mean scores were not normally distributed in each of the RASopathies, non-parametric analyses were used. Summary statistics including group means and CIs are presented. Graphs described the current clinical profile with ADOS items, autistic clinical Profile by the "4-5 most abnormal/ever" subscores of ADI-R, and early general skills development. In an exploratory analysis, we compared the clinical profile, currently, the most abnormal at 4-5 years old or "ever" and throughout early development, between the three groups of children with RASopathies using an independent-samples Kruskal-Wallis test.
A significant limitation of this study is the unequal sample sizes across the three disorders and a small simple size for the NS (n = 11) and CFC (n = 7) which may result in a type 2 error, that is, significant differences may be underreported. These may limit the generalizability of these findings, but larger sample sizes may be difficult to recruit given that these are rare genetic disorders. A further limitation may be the sampling frame and recruitment differences between the three groups. The CFC and NS samples were recruited via clinics and self-referrals through charity advertisements  (16). The NF1 sample was recruited as part of two different studies-a population-based study of ASD ascertainment and a clinical trial  (15, 27). However, participants included in this study were chosen across the research databases based on meeting a set of defined ASD criteria thus minimizing any biases related to recruitment differences.
We excluded three non-verbal children as the ADOS non-verbal assessment module is significantly different to the modules for verbal children. Lastly, we did not have the physical phenotypic data for the population which may impact the cognitive phenotype. The field needs larger samples to confirm our results, and future investigations should consider genotype/phenotype correlation in the context of broader ASD risks. Given the difficulty of examining a large sample for any individual investigator, we recommend multisite studies as well as data sharing and integrative data analyses  (38). The strengths of this study include the careful ASD phenotyping based on the detailed parent-rated interviews (ADI-R) for the past behavior and, based on a direct observation, researcher rate (ADOS) for the current behavior allowing a careful examination of the phenotype across the three RASopathies.
Subjects Longitudinally collected clinical datasets and DNA from participants of the Dubbo Infection Outcomes Study (DIOS) were used  (Cvejic et al. , 2019; Hickie et al. , 2006). The DIOS cohort enroled n = 484 adults of Caucasian descent, who were acutely affected by a febrile illness which was provisionally diagnosed in primary care as being EBV, RRV or QF infection on the basis of screening by pathogen-specific IgM enzymelinked immunosorbent assays (Fig. 1 ). These subjects were prospectively followed-up at 2-3 weeks, 4-6 weeks, and then three-monthly until 12 months post-infection. The EBV, RRV, or QF infections were confirmed by acute and convalesecent serological testing for pathogenspecific IgG antibodies. At baseline, a structured medical history interview was recorded to capture pre-morbid (i.
e. pre-infection) physical and mental health status. At each follow-up visit, self-report questionnaires were administered to record the presence and severity of physical and psychological symptoms related to the ASR. For the purposes of the analysis reported here, demographic data was used in addition to that captured by the 34-item Somatic and Psychological Health Report (SPHERE)  (Hickie et al. , 2001)  and the 19-items Physical Symptoms Checklist (PSC)  (Hickie et al. , 2006).
, 2013). These four PCs were labelled on the basis of the dominant theme captured by the items as (Fig. 1a ): 'Fatigue', 'Musculoskeletal pain', 'Mood disturbance', and 'Acute sickness'  (Hickie et al. , 2006). The loading scores for each questionnaire item in these indices were calculated from the baseline dataset and then applied to the data from each of the follow-up assessments (see Supplementary material, Table  1 ).
Persistence of the endophenotypes The SOMA subscale of the SPHERE questionnaire was used in the orginal study to designate the timepoint when the overall acute illness had resolved (with a score < 3 being indicative of illness resolution)  (Piraino et al. , 2012). Using data from the 12 month follow-up timepoint from subjects (n = 327) whose acute illness had resolved within 4 weeks of initial enrolment, a 'threshold' for background in the PC score for each endophenotype was designated as the 99th percentile of the recovered group. This threshold value was then used to identify the timepoint at which each subject first recorded scores below the threshold for each endophenotype. The midpoint in days between the last above-threshold and the first below-threshold timepoint was used to determine the duration of illness within each endophenotype from symptom onset to resolution (i.
Selection of functional SNPs The SNPs within the NLRP3, CASP1, CARD8, IL-1β, and IL-18 genes were selected to test associations with the severity of ASR endophenotypes. Firstly, SNPs listed for each gene in non-Finnish European populations were download from the Genome Aggregation Database of the Broad Institute  (Karczewski et al. , 2020). In the case of NLRP3, 1193 SNPs were found, whereas 789, 1054, 363 and 22 SNPs were available for CASP1, CARD8, IL-1β, and IL-18. Of this list, SNPs with: i) a minor allele frequency (MAF) > 3% were then selected; and ii) published evidence of altered transcript or protein production in vitro; or iii) a reported association with an infectious or immunological disease (Database of Single Nucleotide Polymorphisms (dbSNP), https://www. ncbi. nlm. nih. gov/snp/) were selected.
Statistical analysis Descriptive statistics, comparisons of groups (i. e. mild and severe cases among each endophenotype), generation of endophenotype indices by PCA, and survival analysis, were performed using Stata/IC version 14 (StataCorp, College Station, Texas, USA). Fisher exact and Chi-square were used for comparison of qualitative variables. Mann-Whitney-Wilcoxon was used for comparison of all quantitative variables due to their abnormal distribution. Survival distributions of the mild and severe illness groups were analysed by the logrank test comparing persistence of symptoms among each endophenotype according to baseline severity. These comparisons were adjusted by age, gender, and infecting pathogen by Cox proportional hazards. Right censoring for the complete dataset was defined at 90 days after the initiation of symptoms.
| Design A population-based matched case-control study was designed using the UK Obstetric Surveillance System (UKOSS), a research platform that collects national population-based information on specific severe pregnancy complications. All 194 maternity units in the UK participate in UKOSS and each has designated UKOSS clinician reporters who are sent monthly notification emails containing a list of conditions under surveillance and are asked to report the number of women with these conditions or to confirm zero cases; the UKOSS administration is set within the National Perinatal Epidemiology Unit at the University of Oxford. For the purposes of this study, data on women affected with DKA while pregnant (cases) and on pregnant women with diabetes who did not have DKA (controls) were collected between April 2019 and September 2020.
| Data collection and consent Information about each patient was collected by the local UKOSS reporting team after the episode of DKA meaning that the clinical management of the woman was not influenced by the data collection in any way. Women's demographic details, previous obstetric and medical history, information on the ongoing pregnancy, birth and infant outcomes were collected. Birth outcomes included the mode of birth and the indication for a caesarean section, if applicable. Indications for caesarean sections were classified as (a) 'maternal compromise' when the caesarean was performed for a severe maternal condition that could be related to DKA or another complication in pregnancy; (b) 'fetal compromise' where caesareans were performed for a non-reassuring fetal status necessitating immediate delivery and (c) 'other' when the caesarean had been performed for any other indication.
Neonates were defined as Small or Large for Gestational Age when their birthweight was below the 10 th or above the 90 th centile according to the Intergrowth birthweight references which are adjusted for gestational age of birth and sex. 19 For cases of DKA, the causes or precipitating factor, clinical features, management and outcomes for the mother and baby were collected. Anonymised information was entered on data collection forms and securely transferred from hospitals to the central UKOSS database hosted on secure servers at the University of Oxford. Individual consent was not required for collection of anonymous data.
| Statistical analysis The incidence rate of DKA in pregnancy (number of DKA cases in pregnant women/number of women giving birth over the same time period across the UK) and its 95% confidence interval (CI) were estimated. Denominator data were obtained from routine statistics published by the Office for National Statistics (For England and Wales), National Records Scotland and the Northern Ireland Statistics and Research Agency and the national Diabetes in Pregnancy Audit. A sensitivity analysis was carried out estimating the incidence using the definition of DKA applied to the non-pregnant population: women with an arterial pH <7. 30 and/or a bicarbonate level <15 mmol/l and capillary ketonaemia of >3 mmol/l or ketonuria of >2 pluses on dipstick testing. The incidence of 'euglycaemic DKA', defined as a venous blood glucose level <14mmol/L, was also estimated.
ACKNOWLEDGEMENTS The authors would like to acknowledge the assistance of UKOSS reporting clinicians and the  UKOSS Steering Committee  without whose support this research would not have been possible. This work was funded by the  National Institute for Health Research (NIHR) Research for Patient Benefit Programme  [ PB-PG-0817-20004 ]. The views expressed are those of the authors and not necessarily those of the  NHS , the  NIHR  or the  Department of Health and Social Care. The funders played no part in the study design, data analyses, data interpretation or writing of the manuscript.
Finally, while all ceramides exhibited significant negative curvatures in general, we find pronounced non-additive mixing for C2:0 ceramide. The paper is structured as follows: After the materials and methods section we introduce the concept of non-linear mixing based on shape arguments and detail how this is assessed by compositional SAXS data modelling including an optimization procedure based on Bayesian probability theory. We then test the modelling against all atom MD simulations of H II phases and previously reported C 0 's of DOPE and dipalmitoleoyl phosphatidylethanolamine (16:1 PE). Finally, the remainder of the results section provides details of non-linear and non-additive mixing contributions to intrinsic curvatures of the above mentioned glycerophospholipids and sphingolipids, which are discussed in the subsequent section.
6B. The position of the backbone (orange solid and dashed lines) shifts to higher radii with increasing DPhPC content, but shows identical behavior for DPhPC and DOPE. This verifies our assumption of aligned backbones in SAXS data analysis (see Sec. 3. 2). The center of the backbone position, R 0 , averaged over both lipid types increased from 24 ± 0. 3 Å at x = 0% to 31 ± 0. 3 Å at 40% (Fig. 6C ). The shape of 300 the different lipid molecules can be visualized by first rotating the backbone position of all lipids to the horizontal axis. We then averaged their electron density as a function of r -R 0 and the coordinate w perpendicular to the radial axis, as indicated Fig. 6D. The resulting average electron densities of DOPE and DPhPC signify the larger head group and the 'heavier' tails of DPhPC (Fig.
Acknowledgment This work was performed in part with support by the  NSF  under grants  CCF-1839232 ,  OAC-1740130 ,  PHY-1806372 , and  PHY-1748958 ; and in conjunction with the  QSUM program , which is supported by the  Engineering and Physical Sciences Research Council  grant  EP/P01058X/1. This work has been supported by the  European Research Council  under the  Consolidator Grant COQCOoN  (Grant No. 820079 ). B. S. acknowledges support from. M. W. and V. P. acknowledge support from. The authors acknowledge Colorado School of Mines supercomputing resources [43] made available for conducting the research reported in this paper. We thank  Sabrina Maniscalco  for useful discussions.
For that, we rely on the data collected through Telegram's API and a combination of network analysis and computational text analysis. We find that the Telegram-based network was cohesive ensuring efficient spread of protest-related information. Content spread through Telegram predominantly concerned discussions of future actions and protest-related on-site information (i. e. , police presence in certain areas). We find that the Telegram network was dominated by different actors each month of the observation suggesting the absence of one single leader. Further, traditional protest leaders-those prominent during the 2014 Umbrella Movement,-such as media and civic organisations were less prominent in the network than local communities. Finally, we observe a cooldown in the level of Telegram activity after the enactment of the harsh National Security Law in July 2020.
We collected only public data (i. e. , no private groups/channels/messages data was collected; the only information available to us was that set as public by the channels owners or public group creators (i. e. , channel/public group names that do not allow identifying who the channel creator/administrator is), or by the users (i. e. , their usernames only if set to public; these, however, can be changed by the users at any point in time and do not allow identifying individual users). Thus, no private or personally identifiable information was collected or used in the analysis. If a channel or a group changed a username, we treated the old and the new usernames as two distinct channels: it is plausible to assume that the change of a username at least temporarily decreases a channel's recognition.
Further, our tests running different parts of the analysis showed that the conclusions are not affected regardless of whether we treat channels that changed usernames as distinct vs identical. Hence, we opted for relying on usernames as, in the case of non-sourced channels and groups (those that were mentioned but whose messages were not collected) it was not possible to infer their persistent IDs rather than usernames, and for individual users who were mentioned we did not want to rely on IDs for privacy reasons to minimize the data collected about individuals: while usernames can be changed and are only visible if a user created a username and set it to public, IDs are persistent and exist for all users. The fact that we collected only public data, though, is an important limitation within the context of the present study: it is unclear whether discussions in private group chats unobserved by us were of fundamentally different nature than those in the public ones.
Unlike in traditional sampling, the initial seed was not sampled randomly but chosen by us-a method appropriate to reach hidden populations with specific properties  [41]. As the initial seed we chose the channel @dadfindboy, which at the time of the protests was one of the most prominent channels among Hong Kong activists according to tgstat. com. From that channel, we relied on snowballing as follows: selected the most mentioned channel in the seed's messages, and collected all of its messages; then, we collected the data from the channel most mentioned by the seed, and the channel collected after it; this procedure was repeated many times. In total, we collected full histories of 1806 public channels and groups. By "full" histories we mean all the messages that were available at the point of data collection.
Researchers therefore have to rely on tokenisers to split texts into basic word units to allow for further analysis  [44]. However, the majority of currently available resources were developed for Mandarin, another dialect of the Chinese language, and therefore perform poorly on Cantonese texts. We hope that the methodology description below can serve as a useful reference for future studies that use automated text analysis techniques in application to the texts in Cantonese. To proceed with tokenisation, we employed a method that is commonly adopted for finding multi-word expressions in other languages. We used the phrase (collocation) detector implemented in the Gensim python package to detect the characters that appear frequently together but infrequently when separated  [45, 46]. We then extracted the word list and read manually to determine if they are valid Cantonese words.
The absence of such dominance would indicate that there were no specific organized leaders, with different groups taking over at different times and suggesting that the protest was in fact leaderless-at least in the traditional sense of leadership characteristic for collective movements of the past in the context of protest coordination and information spread-induced mobilization within Telegram. One limitation is that this method does not account for the potential leadership role of specific individual users. For example, if a user or several users administered different Telegram channels which, in turn, were switching in the observed importance, they would be indeed protest leaders. However, as the data on channel administrators is not public, it is not possible to assess the role of individual users on Telegram.