dataesr/scientific-paragraphs-categorization huggingface dataset:
These differences were tested by using PER-MANOVAs (function "adonis" in package "vegan",  [102] ). The three associated Principal Component Analysis (PCAs, package "factoextra", and function "fviz_pca_biplot"  [103] , on log-transformed and auto-scaled data) was performed separately for each litter species on untargeted metabolome datasets taking into account all metabolites (or detected features). We used a general linear model approach to test for the effects of litter species (P. halepensis, Q. ilex, or Q. pubescens), litter types (i. e. , senescent leaves and needles collected from trees in AD and ND plots), precipitation treatments (AD or ND), forest (P. halepensis, Q. ilex or Q. pubescens forests), and time of decomposition (1 or 2 years) on the litter mass remaining. The full model was simplified to determine the most parsimonious model by using an established model selection procedure with both forward and backward selection algorithms, which ranks all candidate models (all possible combinations of initial explanatory variables included in the full model) based on the lowest AICs (function "stepAIC" and "AIC" in package "MASS",  [104] ).
Funding: Funding was provided by the  French Agence Nationale pour la Recherche (ANR)  through the project  SecPriMe2  (no. ANR-12-BSV7-0016-01 ), the  program BioDivMeX (BioDiversity of the Mediterranean eXperiment)  of the meta-program  MISTRALS (Mediterranean Integrated STudies at Regional Additionally, Local Scales ), and partially by the  Ministry of Education , Youth and Sports of the Czech Republicgrant No. LTC20063 , and the  Ministry of Agriculture of the Czech Republic , institutional support MZE-RO0418. This research is also a contribution to the  Labex OT-Med  (no  ANR-11-LABX-0061 ) funded by the " Investissements d'Avenir" program  of the  French National 418 Research Agency  through the  A*MIDEX project  (no  ANR-11-IDEX-0001-02 ). The three experimental sites were annually supported by the research infrastructure  AnaEE-France  ( ANR-11-INBS-0001 ) and by  Allenvi  through the  SOERE F-ORE-T.
Data Availability Statement: Metabolomics data will be archived in the Metabolights platform (https://www. ebi. ac. uk/metabolights/ accessed on 1 January 2017). Data concerning litter decomposition and litter quality will be archived in the SEDOO database from the BioDivMex Mistrals program (https://mistrals. sedoo. fr/BioDivMex/ accessed on 1 January 2017).
Data This study is part of an international research project led by Prof. Jolanda Jetten. The overall sample consisted of 6112 undergraduate students representing the national majority group members. The data was collected between January 2014 and February 2015 from 28 countries in North America (Canada and the US [from Tennessee and North California]), South America (Chile and Brazil), Europe (Netherlands, UK, Spain, Italy, Germany [from former East Germany and former West Germany], France, Denmark, Finland, Switzerland, Belgium, Portugal, Poland, Hungary, and Latvia), Asia (China, Japan, Malaysia, Singapore, Indonesia, India, and Pakistan), the Middle East (Iran), Africa (South Africa), and Australia. The data that was gathered from two different universities in the same country (the US and Germany) were combined to make an overall country variable.
Control variables were age and gender. Objective country-level wealth GDP per capita and The Human Development Index (HDI) were used as objective indicators of a country's wealth. GDP is a measure which solely captures the country's economic situation, HDI, in turn, is a composite of life expectancy, level of education, and income within a country, thus it reflects the overall functioning of the society for the majority of its citizens. Scores of all 28 countries were derived from the Human Development Report ( United Nations Development Programme, 2015 ) and OECD National Accounts data  ( OECD, 2015 )  were included in the multilevel analysis as the country-level variables. The GDP per capita of the countries studied ranged from 5 to 85,4 international dollars. The HDI rankings vary between 0 and 1, thus a high score indicates high human development.
Data analysis First, we tested for measurement invariance to examine our dependent variable's cross-cultural equivalence -perceived realistic threatacross 28 countries by using multi-group confirmatory factor analyses (MGCFA) with Mplus software  (Muthén & Muthén, 2004). The full information maximum likelihood (FIML) approach was used to handle missing data. We started by examining the configural model to test whether the factor structure was similar across countries and obtained a perfect fit (saturated model). Then, we examined the metric model fit of the three-item scale (with all factor loadings constrained to be equal across countries and intercepts released) to explore whether the factor loadings were equivalent across the countries. The model had adequate fit (CFI = 0. 97, TLI = 0. 96, and RMSEA = 0.
09), confirming metric invariance across countries. This level of invariance allowed us to continue examining correlations and regressions between countries. Next, because participants were nested within countries, we used the Statistical Package for the Social Sciences (SPSS 25) mixed model procedure for multilevel modeling. Individual-level (level 1) predictors were perceived country's wealth and perceived and anticipated personal wealth. The country-level (level 2) predictor was either GDP, or HDI. Perceived realistic threat and personal wealth in the present and future were measured at level 1 and were group-centered based on the mean of each country. The level 2 moderators (GDP and HDI) were grand-centered to test the cross-level interactions. In the multilevel analysis, we used the restricted maximum likelihood approach (REML).
[71,72]hoice of test will also depend on equipment availability, resources, space and time available as well as familiarity and training. The Rehabilitation Measures Database provides a useful description of options and their clinimetric properties (www. sralab. org/rehabilitation-measures). •Astructuredassessment of gait by a trained clinician can be helpful in directing investigations for underlying conditions that may increase falls risk by impairing gait[69,70]. •The Floor Transfer Test is a reliable and valid measure for screening for physical disability, frailty and functional mobility[71,72].
Acknowledgements: We would like to thank and acknowledge our central organisation support team composed by  Dr Frederico Faria ,  Dr Yanina Sarquis-Adamson ,  Surim Son ,  Nattasha Clements  and  Jackie Liu. Also , we would like to thank and acknowledge  Maureen Godfrey  for offering her insights as an older adult with lived experience on our protocol paper, our panel of older adults ( Clarke Heidrick ,  Elizabeth Retzer ,  Walter Retzer  and  Gerry Treble ) for commenting and advising on the recommendations that were developed, and all other adults who supported the work of the individual working groups.
[71,72]hoice of test will also depend on equipment availability, resources, space and time available as well as familiarity and training. The Rehabilitation Measures Database provides a useful description of options and their clinimetric properties (www. sralab. org/rehabilitation-measures). •Astructuredassessment of gait by a trained clinician can be helpful in directing investigations for underlying conditions that may increase falls risk by impairing gait[69,70]. •The Floor Transfer Test is a reliable and valid measure for screening for physical disability, frailty and functional mobility[71,72]. Medication assessment Strong recommendation. Assess for fall history and the risk of falls before prescribing potential fall risk increasing drugs (FRIDs) to older adults (Appendix 2, available in Age and Ageing online).
citri GII-3 genome: the fibril gene (SPICI12_006), the mreB1 gene (SPICI13_009) and the locus composed of mreB2, mreB3, a hypothetical protein encoding gene (HP), mreB4 and mreB5 (SPICI01A_045 to SPI-CI01A_049). S. citri DNA cassettes were amplified to conserve the native promoters. The two last plasmids (pMT85PStetM-mreB1 and pMT85PStetM-mreB5), which were derived from plasmids pMT85PStetM-mreB1-fib and pMT85PStetM-mreB5-fib, respectively, were built using the Q5® Site-Directed Mutagenesis Kit Protocol (Supplementary Table  4 ). All oligonucleotides for plasmid construction were supplied by Eurogentec and are described in Supplementary Data 1. Prior to being used for transformation into Mcap, the purified plasmids were verified by restriction analyses and sequencing.
Determination of the transposon insertion site by singleprimer PCR Transposon insertion sites were determined by single-primer PCR. The 25-µL final reaction volume contained 1× PCR Buffer (NEB), 3 mM MgCl 2 , 1 µM SPP2-pMT85-TetM primer, 0. 2 mM dNTPs, 0. 5 U of Taq NEB polymerase (NEB), and 2. 5 µL of the transformant DNA. The PCR amplification cycle was performed as previously described  52. Transposon insertion sites were determined by Sanger sequencing of the PCR products with the nested primer MT85-1 (Supplementary Data 1).
Dark-field microscopy and cell length measurements One volume of cultures of exponentially growing Mcap in SP4 tet5 and of S. citri in SP4 (pH 6. 8-6. 9) was diluted in one volume of fresh medium. Bacterial suspensions were prepared between two microscope slides sealed using nail polish, with a liquid thickness of 15 µm. The morphology of Mcap transformants growing in SP4 media was observed using an Eclipse Ni (Nikon) microscope working in reflection and equipped with a dark field condenser. The Nikon oil immersion microscope objective was 60× with a numerical aperture (N. A. ) of 0. 80. Images were acquired with an Iris 9™ Scientific CMOS camera (2960 × 2960 pixels). Videos were recorded at the maximal frame rate of 10 to 30 frames per second (fps) using the software NIS-Elements Br (Nikon).
The Mycoplasma cell length and helicity parameters were measured from isolated frames using the same software. Cells were considered helical if at least 70% of the total cell length showed helicity; otherwise, they were considered (nonhelical) filamentous cells. Cells were considered branched if at least one branch could be visualized along the main (longest) filament. Helical pitch measurements excluded nonhelical cells. Data are expressed as the mean ± standard deviation (SD). Graphs and statistical analyses were performed using Excel 2019. Statistical significance was estimated using the two-tailed unpaired t test. For each construct, data from 3 independent cultures were collected and mixed, and differences between transformants were considered significant at p < 0. 001. The total number of cells used to draw the graphs is indicated in the corresponding figure captions, and raw data are given in Source data file.
Fragmentation occurred in the linear ion trap analyser with a collision energy of 35. All measurements in the Orbitrap analyser were performed with on-the-fly internal recalibration (lock mass) at m/z 445. 12002 (polydimethylcyclosiloxane). The resulting raw files were analyzed with Proteome Discoverer 1. 4. 1. 14 (Thermo Scientific). A database search was performed with the Mascot (version 2. 8. 0) algorithm against "GCF_000012765. 1_ASM1276v1_protein" (801 entries) retrieved from NCBI and containing the protein sequences encoded in the M. capricolum subsp. capricolum genome and a multifasta containing S. citri GII-3 and plasmid-encoded protein sequences. The following search parameters were used: trypsin was specified as the enzyme allowing for one miscleavage; carbamidomethyl (C) and oxidation (M) were specified as variable modifications; the precursor mass range was set between 350 and 5000 Da, with a precursor mass tolerance and a fragment ion tolerance of 10 ppm and 0.
Acknowledgements We thank  Nicolas Martin ,  Jean-Christophe Baret  ( Univ. Bordeaux ,  CNRS-UMR5031 ,  Bordeaux, France) , the ' Frontiers of Life' network (Univ. Bordeaux, France)  and the  Microbiology Community of Nouvelle-Aquitaine (Microbio-NA)  for helpful discussions. We also thank  Eva Manduchet ,.
Data availability The mass spectrometry data generated in this study have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository  54  under accession code PXD036290 (http://www. ebi. ac. uk/ pride). All Mycoplasma capricolum subsp. capricolum protein sequences can be found at https://www. ncbi. nlm. nih. gov/search/all/? term=GCF_000012765. 1_ASM1276v1_protein. All Spiroplasma citri GII3 protein sequences were previously reported  55. All other data supporting the findings of this study are available within the paper and its supplementary information files. Source data are provided with this paper.
Neurogenetics ] [10]  We did not exclude as adult onset those patients with subtle and non-progressive symptoms before the age of 10 years of age that could go overlooked, such as mild intellectual disability. Subsequently, we undertook a focused search in PubMed for articles in those same languages, using each previously identified adult-onset neurometabolic disease as a search term, with the aim to refine the adult-onset neurometabolic diseases selection and to identify those where a disease-modifying therapy is currently available (figure  1  and online supplemental material 2). We collected all clinical, MRI, biochemical and therapy data concerning these diseases. Although numerous and different classifications exist, these treatable adult-onset neurometabolic diseases were classified and presented in a clinically relevant manner, meaning that disorders with similar clinical characteristics and common biochemical tests were grouped together.
Participants This study was carried out from August 4, 2020, to December 10, 2021. Participants were recruited from the sleep unit of a hospital in A Coruña, Spain. These people were attending the sleep unit to participate in a PSG study, intended to detect possible sleep alterations, independent of this project. All participants had access to a study information sheet and provided written informed consent for their participation. The protocol study was registered with the ClinicalTrials. gov Protocol Registration and Results System (NCT04568408) and published in an international journal, where the design and recruitment process of the study are detailed  [48]. The research group maintained the anonymization of all data recorded and obtained from each participant, following and respecting the European (UE 2018/1725) and Spanish (BOE-A-2018-16673) laws on personal data protection at all times.
Xiaomi Mi Band 5 The Xiaomi Mi Band 5 includes a 3-axis accelerometer, a 3-axis gyroscope, an HR sensor, and a photoplethysmography sensor to measure some biomedical parameters. This device contains updated software that continuously records daily activity (eg, steps, distance, activity time, and calories), sleep (eg, light sleep, deep sleep, REM sleep, wake, TST, start and end of the sleep period, and naps), and HR  [50]. The device also calculates and classifies the stress level (classified using the terms relaxed, mild, moderate, and high) through HR data. In addition, the wristband requires a series of personal data such as age, sex, weight, height, handedness, and wristband location. The Xiaomi Mi Band connects to its app, the Zepp Life app, via Bluetooth, where the recorded data are transferred and displayed  [50].
Processing the PSG and Xiaomi Mi Band 5 Data The Xiaomi Mi Band 5 and PSG source data were originally available in different formats. The Xiaomi Mi Band 5 data were collected from the Zepp Life app manually and exported to an Excel sheet (Microsoft Corp) because it did not allow downloading of the raw data from the wristband. By contrast, PSG data consisted of CSV text files that contained the manually scored sleep stages and the corresponding reports with clinical sleep diagnostic parameters, available in Word format (Microsoft Corp), both exported using the NicoletOne software. Hence, to enable performance analysis, data were converted into a common format using the European Data Format + (EDF+)  [51]. For this purpose, a Python script (version 3. 10. 5; Python Software Foundation) was developed with help of the PyEDFlib library  [52].
Principal Findings The Xiaomi Mi Band 5 is one of the most popular wristbands among consumers around the world  [4, 5]. Its use has increased because it can continuously record different parameters, including sleep  [4, 5]. Nevertheless, it was not developed for clinical or scientific purposes in the diagnosis of SDis or sleep monitoring, a factor that could influence its performance  [11, 28]. Thus, we considered it necessary to determine the quality and accuracy of sleep data obtained from this device by comparing it against PSG performed at a clinical sleep unit. To our knowledge, this is the first study that has validated the ability of the Xiaomi Mi Band 5 to measure sleep parameters in people with SDis as well as those without SDis. This study investigated the agreement in sleep measures from PSG and the Xiaomi Mi Band 5.
Specifically, the Xiaomi Mi Band 5 misidentified more epochs in the SDis group than in the No SDis group. The device misclassified light sleep epochs as awake, deep sleep, and REM sleep epochs in the SDis group and to a lesser extent in the No SDis group. Overall, the outcomes obtained from people without SDis were a bit more accurate in some sleep measures and sleep stages. Consistent with the literature, devices such as the Xiaomi Mi Band 5 may be an alternative for health management in people without SDis because the data are more reliable than in people with SDis  [8, 11, 41, 61]. However, the outcomes of the SDis group could have been influenced by the inclusion of multiple SDis (rather than a single disorder), with OSA being the most prevalent syndrome. Similar to the results of other studies, the performance of this activity wristband can be lower among people diagnosed with OSA.
Limitations There are some limitations that could have negatively influenced the main findings of this study. The first limitation is attrition: only 45 of the 58 participants completed the study. Participants did not complete the study owing to difficulties with the use of the wristband and data collection. Hence, the sample was heterogeneous, and the size of the groups (SDis and No SDis) was small. In addition, how the participants were monitored might have influenced the data because this was not done in the usual context in which people sleep. Moreover, participants should be followed up for more days for better assessment of the performance of the Xiaomi Mi Band 5. This study includes other limitations. Specifically, the Xiaomi Mi Band 5 and other devices only combine movement and HR to classify sleep parameters, whereas PSG includes several sensors; therefore, the accuracy of the data collected by wearable devices could be lower than that of the data collected by PSG.
Acknowledgments The authors would like to express their gratitude to the participants who kindly agreed to be part of this study, as well as to the clinical staff working at the sleep unit with whom they have worked closely. The authors disclose the receipt of the following financial support for the research, authorship, and publication of this paper: all economic costs involved in the study were borne by the research team. This work is supported in part by some grants from the  European Social Fund   2014-2020 :  Centre for Information and Communications Technology Research (CITIC; Research Center of the Galician University System). Grant support for CITIC was provided by the  Xunta de Galicia  through a collaboration agreement between the  Regional Ministry of Culture, Education, and Vocational Training and the Galician Universities  for the work of the  Research Centers of the Galician University System  and the Handytronic chair.
Negative stain microscopy observations Before preparing cryo-EM grids, we first checked the quality and the homogeneity of the AVP-V2R-barr1DCT-ScFv30 samples by negative stain EM (NS-EM). Three microliters of each complex at 0. 04 mg/ml was applied for 2 min on glow-discharged carbon-coated grids and then negatively stained with 0. 75% uranyl formate for 1 min. Observation of EM grids was carried out on a JEOL 2200FS FEG Transmission Electron Microscope (TEM) operating at 200 kV under low-dose conditions (total dose of 20 electrons/Å 2 ) in the zero-energy loss mode with a slit width of 20 eV. Images were recorded on a 4K × 4K slow-scan charge-coupled device camera (Gatan Inc. ) at a nominal magnification of ×50,000 with defocus ranging from 0. 5 to 1. 5 mm. In total, 55 micrographs were recorded, allowing us to pick 97,182 particles using e2boxer from Eman2 package  (65).
Cryo-EM data processing Movie frames were aligned and summed using the MotionCorr Relion own implementation (Relion 3. 1. 2) with seven-by-five patches, a B factor of 150, and a binning factor of 2, resulting in motioncorrected images with a pixel size of 1. 28 Å. The contrast transfer function parameters were estimated using Gctf  (66). The images with a maximal resolution estimation worse than 7 Å were discarded, resulting in 13,566 images (fig. S4A ). A first automatic picking (fig. S5 ) was carried out using boxnet from Warp software package  (67) , allowing us to select and extract 3,610,370 particles, which were transferred into Relion v3. 1. 2. Iterative 2D classifications combined with bad 2D class average exclusion sorted out a total of 1,169,437 particles (fig. S4A ). Those particle coordinates were used as references to train a model with Topaz (68), a positive-unlabeled convolutional neural network for particle picking (fig.
S5 ). It resulted in the picking of 4,595,394 particles. Both datasets of particles were transferred into Relion 3. 1. 2 and subjected separately to iterative 2D classifications. The particles selected from the best 2D class averages (1,806,545 particles from boxnet and 2,660,410 particles from Topaz) were then merged and duplicates were removed, yielding a dataset of 3,721,020 particles. A conventional approach (fig. S4B ) was first performed with two rounds of 2D classification, allowing us to select 2,206,913 particles, and subjected to an initial model reconstruction and diverse iterative 3D classifications. Although playing with multiple different parameters (T value, mask size, number of 3D classes, box size, and Relion vs cryoSPARC), this approach only allowed us to compute a density map at 6.
Raw spectra were processed using the MaxQuant environment v1. 6. 10. 43  (72)  and Andromeda for database search with match between runs and the iBAQ algorithm enabled. The MS/MS spectra were matched against the sequence of the V2R construct (fig. S15 ), the reference proteome (Proteome ID UP000008292, release 2021_01) of Autographa californica nuclear Downloaded from https://www. science. org on September 07, 2022 polyhedrosis virus, the UniProt entries (release 2021_01, www. uniprot. org/) for Spodoptera frugiperda (fall armyworm, taxon identifier 7108), and 250 frequently observed contaminants, as well as reversed sequences of all entries. Enzyme specificity was set to trypsin/P, and the search included cysteine carbamidomethylation as a fixed modification and oxidation of methionine, acetylation (protein N terminus), and phosphorylation of Ser, Thr, and Tyr residues (STY) as variable modifications.
16 × 10 -6 M. Fluorescent signals were measured at 620 nm (fluorescence of the donor) and at 665 nm (FRET signal) on a PHERAstar (BMG LABTECH). Results were expressed as the 665/620 ratio [10,000 × (665/620)]. A specific variation of the FRET ratio was plotted as a function of benzazepine-red concentration (saturation experiments) or competitor concentration (competition experiment). All binding data were analyzed with GraphPad 9. 1. 1 (GraphPad Prism Software Inc. ) using the one site-specific binding equation. All results are expressed as the means ± SEM of at least three independent experiments performed in triplicate (fig. S2 ). K i values were calculated from median inhibitory concentration values with the Cheng-Prusoff equation.