dataesr/scientific-paragraphs-categorization huggingface dataset:
This study including older adults from Ireland aimed to analyze the prospective association between multimorbidity and falls and to identify the mediators in this relationship. The present study used data from two consecutive waves of the Irish Longitudinal Study on Ageing (TILDA) survey. Multimorbidity was assessed at Wave 1 (2009)(2010)(2011) and was defined as the presence of at least two chronic conditions. Falls occurring at Wave 2 (2012-2013) were self-reported. Mediating variables considered were polypharmacy, cognitive impairment, sleep problems, pain, low handgrip strength, difficulty in activities of daily living (ADL), obesity, and underweight. Multivariable binary logistic regression and mediation analysis using the Karlson Holm Breen method were conducted. This study included 6900 adults aged ≥50 years (51.
The Survey Data from two consecutive waves of the Irish Longitudinal Study on Ageing (TILDA) survey were used for this study. The methodology of the survey has been extensively described in the literature  [25, 26]. Briefly, the survey was undertaken by Trinity College Dublin, and included adults aged ≥50 years from private households in Ireland. Nationally representative samples were obtained using clustered random sampling. Wave 1 (i. e. , baseline survey) was conducted in October 2009-February 2011, and Wave 2 in April 2012-January 2013. People living in institutions, those affected by dementia, and those with severe cognitive impairment limiting their ability to provide written informed consent were excluded from Wave 1. The majority of data were obtained through interviews conducted by trained staff using a computer.
Sensitive data (e. g. , alcohol consumption) were obtained using a self-completed questionnaire returned following the interview. The response rate was 62% and 86% for Wave 1 and Wave 2, respectively. Sampling weights were generated based on the statistics of the Quarterly National Household Survey 2010, and the estimation of these weights relied on sex, age, and educational attainment. Finally, ethical approval for the survey was obtained from the Ethics Committee of the Faculty of Health Sciences of Trinity College Dublin, while each participant provided written informed consent.
Chronic Conditions and Multimorbidity (Independent Variables) We considered all chronic conditions for which data were available in the survey. The question "Has a doctor ever told you that you have any of the conditions on this card?" was used to assess the presence of chronic physical conditions at Wave 1. There were 14 conditions listed on the card: arthritis, asthma, cancer, chronic lung disease (i. e. , chronic bronchitis or emphysema), cirrhosis, diabetes, eye disease (i. e. , age-related macular degeneration, cataracts, glaucoma, or other eye disease), heart disease (i. e. , abnormal heart rhythm, angina, congestive heart failure, heart attack, heart murmur, or other heart disease), high cholesterol, hypertension, osteoporosis, stomach ulcer, stroke, and varicose ulcer. In addition, we also included anxiety and depression in the list of chronic conditions.
Strengths and Limitations The strengths of this study include the large sample size and the use of prospective nationally representative data. Nonetheless, the study results should be interpreted in the light of several limitations. First, while the present list of chronic conditions included a variety of conditions, there was a lack of information on diseases such as orthostatic hypotension or neuropathy, which can lead to particularly high risk for falls. Thus, the estimates of this study could have differed with a different set of diseases assessed. Second, most of the data used in our study, including data on chronic conditions and falls, were based on self-report. Thus, it is possible that some level of bias (e. g. , recall bias) was introduced in our findings. Third, baseline data on multimorbidity and other control or mediating variables were used for the analysis.
Models and Satellite Products Used in the Study A suite of models and satellite data products are identified for supporting ACCLIP field operations and for postcampaign data analysis and interpretation. These models and products are listed in Table  1. The results of post-dry-run analysis are derived largely from three global chemistry forecast models: NASA Goddard Earth Observing System Forward Processing (GEOS-FP), NCAR Whole Atmosphere Community Climate Model (WACCM), and European Centre for Medium-Range Weather Forecasts (ECMWF) Copernicus Atmosphere Monitoring Service (CAMS). The transport analysis is also heavily supported by the Lagrangian trajectory model  TRAJ3D and the idealized surface tracer in the Weather Research and Forecasting (WRF) model. In addition, the models are supported by the CO data from multiple satellite instruments.
3125° longitude by 0. 25° latitude and at 72 vertical levels, extending to 0. 01 hPa. The majority of GEOS-FP data products are time-averaged, but some instantaneous products are also available. Hourly data intervals are used for two-dimensional products, while 3-hourly intervals are used for three-dimensional products. For ACCLIP, 3-hourly instantaneous forecast products for CO and its tagged tracers, SO 2 , and aerosols (including dust, sea salt, sulfate, black carbon [BC], and organic matter) are used for dry-run flight planning and science analysis. The tagged CO tracers, SO 2 , and aerosols in the GEOS model simulations are documented in detail by  Bian et al. (2013).
MLS The primary data set contributing to the post-dry-run analysis reported in this paper is CO from the Aura Microwave Limb Sounder. MLS measurements have been used in a number of prior ASM studies (see  Santee et al. , 2017, and references therein). Here, we use version 4. 2 (v4. 2) MLS measurements  (Livesey et al. , 2020). Although an updated MLS data set (v5) was released in June 2020, it was not used for the dry run that summer because reprocessing with the v5 retrieval algorithms of the entire MLS data record (needed to calculate the climatological fields against which the 2020 season's variations were compared) had not been completed at that time. MLS v4 and v5 CO products generally agree closely in the UTLS. MLS v4 H 2 O and O 3 measurements were also analyzed as part of the dry run.
Integrating airborne in situ observations and modeling is essential for in-depth understanding of the chemical evolution within these shedding events and therefore the chemical impact of the ASM transport. In addition to the enhanced BL trace gas species, the role of the ASM in creating a unique and recurring aerosol layer around the tropopause level is an important scientific issue motivating the ACCLIP campaign. This aerosol layer, referred to as the Asian Tropopause Aerosol Layer (ATAL), was initially discovered by satellite data analysis  (Vernier, Thomason, & Kar, 2011; Vernier, Thomason, Pommereau, et al. , 2011; Thomason & Vernier, 2013)  and has been investigated since using satellite, balloon-borne, and ground-based measurements as well as modeling (e. g. ,  Brunamonti et al. , 2018; Vernier et al.
, 2015 Vernier et al. , , 2018;; Yu et al. , 2017; J. Zhang et al. , 2020). The most notable information gap is the chemical composition and particle size distribution of the aerosols, which are critical for diagnosing ATAL formation and maintenance mechanisms and their radiative effects. Information on these parameters is critically needed for improving model representation. The StratoClim campaign obtained the first significant set of airborne in situ and remote-sensing aerosol data in the ATAL  (Höpfner et al. , 2019; Mahnke et al. , 2021; Weigel, Mahnke, Baumgartner, Dragoneas, et al. , 2021; Weigel, Mahnke, Baumgartner, Krämer, et al. , 2021)  from Kathmandu-based research flights. These measurements sampled the South Asian region including Nepal, Pakistan, northern India, and the Bay of Bengal.
Acknowledgments This work is supported by the  National Science Foundation (NSF)  through its funding of the  National Center for Atmospheric Research (NCAR) , under cooperative agreement number  1852977. Q. Liang  and  P. R. Colarco  acknowledge the support of  NASA   Modeling, Analysis, and Prediction Program. M. Chin  acknowledges the support from  NASA   Aura Science Team  project. Work at the  Jet Propulsion Laboratory, California Institute of Technology , was carried out under a contract with the  National Aeronautics and Space Administration  ( 80NM0018D0004 ). O. B. Toon is supported by  NSF  Grant  AGS-1853932. E. L. Atlas is supported by  NSF  Grant  AGS-1853948  and  NASA  Grant  NNX17AE43G. W. P. Smith is supported by  NSF  Grant  AGS-1853929. We thank  M. Barth  for helpful comments on the manuscript, as well as  J.
Data Availability Statement The satellite data and model output used in this work are available in following locations: MLS: https://acdisc. gesdisc. eosdis. nasa. gov/data/Aura_MLS_Level2/ML2CO. 005/2020/ IASI: https://iasi. aeris-data. fr/CO_AC_SAF_IASI_A_data/ GEOS: https://portal. nccs. nasa. gov/datashare/gmao/geos-fp/das/Y2020/ WACCM: https://www. acom. ucar. edu/waccm/DATA/SPECIAL/WACCM_110L_Pan_et_al/ CAMS: https://ads. atmosphere. copernicus. eu/cdsapp#!/dataset/cams-global-atmospheric-composition-forecasts? tab=form.
Similarly, Gou et al. 27   In this work, we present the results of the sequential neutron powder diffraction (NPD) data collection in a powdered and non-deuterated MAPbBr 3 sample in the 2 to 250 K temperature range. An additional measurement was carried out at 300 K using a single crystal. On the one hand, we deepen on the knowledge on the already described cubic Pm -3 m, tetragonal I4/mcm and orthorhombic Pnma phases. Moreover, from additional sequential ND measurements with higher resolution in temperature, we resolved the intermediate structure as a commensurate orthorhombic Imma phase. This model accurately describes the crystallographic structure in the controversial 148-155 K temperature range, completely elucidating the con guration of the MA units.
An additional sequential analysis around critical phase transition was measured from 145 to 157 K with a temperature interval of ≈ 0. 5 K. About 2 g of non-deuterated sample was contained in a 6 mm diameter vanadium can. The coherent scattering lengths for Pb, Br, C, N and H were, 9. 405, 6. 795, 6. 646, 9. 36 and - 3. 739 fm, respectively. NPD diffraction patterns were analysed with the Rietveld method using the FullProf program  30, 31. In order to generate the shape of the diffraction peaks of the patterns collected, a pseudo-Voigt function was selected. The background was interpolated from areas with no re ections. The parameters simultaneously re ned were: scale factor, background coe cients, zero-point error, pseudo-Voigt corrected for asymmetry parameters, positional coordinates, anisotropic displacement factors and occupancy factors.
The high contrast of H scattering lengths allowed the full elucidation of the organic MA cations. Moreover, an additional data collection at room temperature (RT) was carried out in the single-crystal neutron diffractometer D19 (ILL, Grenoble), with a wavelength of 0. 96 Å. For this experiment, a suitable ''neutron-sized'' crystal with dimensions of 1 x 1 x 1 mm 3 , approximately, was mounted on a pin, and the measurements were carried out with a neutron wavelength of 0. 96 Å. The strong peaks were found with the ILL program PFIND, and indexed with the DIRAX  32  program; the orientation matrix, the unit-cell parameters and the χ, ω and detector offsets were post-re ned with the ILL program RAFD19  33, 34. After that, a sequence of approximately 801 ω-scans at a number of positions of φ and χ were collected to obtain high data completeness.
The observations used in this study include 2 seasons of automatic weather station (AWS) data from the Sunderdhunga valley at about 4,700 m altitude in Central Himalaya. Fundamental for the approach is also the previously characterized LAP deposition in glacier snow from the same valley  (Svensson et al. , 2021). To calculate the albedo reduction originating from the LAP in snow, we utilize the parametric relation by  Pedersen et al. (2015). Their formulation is spectrally dependent on 2 parameters: (1) the ECeq concentration (referring to an operationally defined elemental carbon [EC] as proxy for BC, and where eq represents the equivalent absorption including BC and other light-absorbing non-BC constituents) in the surface snow and (2) the equivalent radii, r e , of the snow grains. With neither of these parameters directly measured at our site in the Sunderdhunga valley, they are here derived from other available observations and assumptions.
M. Young). Data were logged every 10 min and screened for inconsistencies, which may arise, for example, from snow covering the sensors. Subsequently, the data were averaged over each day. To reduce the influence from noise and better capture representative values, the daily median values were used for albedo and SD instead of averages. The time series of albedo and SD covering the entire measuring period from September 22, 2015, to October 31, 2017, are presented in Figure  1. The AWS data are presented as time series in Figure  S2. Precipitation was not directly measured but was estimated using the method described in  Svensson et al. (2021)  yielding an estimate of the amount of precipitation in mm SWE. The positive changes in SD (SD þ ) were integrated over Seasons 1 and 2, and the density of the new snow was assumed to be 100 kg m -3  (Helfricht et al.
The effective radii of the snow grains r e were estimated based on the fitted relationship between albedo, SSA, and r e. The AWS data were grouped into 1 temperature bins and a function between air temperature and the maximum observed albedo (expressed as log(SSA)) for each bin was fitted. The derived LAP concentration in surface snow expressed as EC eq and the diagnosed r e are the final variables used as inputs to parameterize the albedo reduction due to LAP. To diagnose r e , the black body surface temperature was tested as an alternative parameter to estimate r e , but it only marginally improved the agreement between observed and estimated albedo. Hence, the only time-dependent variables that are required to estimate snow surface albedo in our simplified model is air temperature and the SD.
Methods Whole Exome Sequencing and Sanger Sequencing Whole exome sequencing (WES) of index and unaffected parents was performed on gDNA using SureSelect Human All Exon V5 kit (Agilent) or Twist Human Core Exome enrichment with additional probes for humane RefSeq transcripts (Twist Bioscience). Paired-end massively parallel sequencing (2 × 150 cycles) was performed on a NovaSeq 6000 (Illumina) (P1 and P2) or SureSelectXT Human All Exon V6 (Agilent) enrichment and HiSeq 3000 sequencing (Illumina) (P3). Data analysis was accomplished with an in-house developed pipeline, in accordance with international guidelines. For mutation detection in P1 and P2, VariantDB was used  [8]. In addition, a genome-wide Human Phenotype Ontology (HPO)-based filtering was executed using the MOON software (Diploid).
SYBR Green primers (Integrated DNA Technologies) were used for qPCR of misprocessed histone RNA analysis. All SYBR Green primer sequences can be retrieved in Table  S8. NanoString ISG Analysis Blood was collected into PAXgene tubes (PreAnalytix) and, after being kept at room temperature for between 2 and 4 h, was frozen at -80 °C until extraction. Total RNA was extracted from whole blood using a PAXgene (PreAnalytix) RNA isolation kit. Analysis of 24 genes and 3 housekeeping genes was conducted using the NanoString customer-designed Code-Sets according to the manufacturer's recommendations (NanoString Technologies). Data were processed with nSolver software (NanoString Technologies). The data were normalized relative to the internal positive and negative calibrators, the three reference probes, and the control samples.
The median of the 24 probes for each of 27 HC samples was calculated. The mean NanoString score of the 27 HCs + 2 SD of the mean was calculated. Scores above this value (> 2. 758) were designated as positive. Cytokine Quantification Serum cytokines IL-1β, IL-1RA, IL-18, CXCL9, CXCL10, TNFα, and MCP-1 (CCL2) were quantified in duplicate by magnetic bead-based multiplex assay using xMAP technology (Luminex Corporation) and Bio-Plex assays, kits, and standards (Human Cytokine Screening Panel #12,007,919; Bio-Rad, and Human Inflammation Panel #171DL0001; Bio-Rad) according to the manufacturer's protocol. Multiplex assay samples were diluted at 1:2. Acquisition and analysis was performed on a Bio-Plex 200 reader and using the Bio-Plex Manager software (Bio-Rad). The S-PLEX human IFN-α2a kit by MSD (Meso Scale Discovery) was used for determining IFN-α2 in serum samples following the manufacturer's instructions.
Compound Heterozygous RNU7-1 Mutations in 3 Patients with an AGS Phenotype We investigated 3 patients with AGS from unrelated nonconsanguineous families of European origin (full clinical descriptions are given in supplemental data S1). All 3 patients presented with classical features of AGS including psychomotor retardation, spastic quadriparesis, and intracranial calcifications (Fig. 1a ). In addition to calcifications, ultrasound imaging revealed lenticulostriatal vasculopathy in P1 (Fig. 1a ). P1 and P2 are in clinical follow-up and currently 2 and 3 years old, respectively. At 19 years of age, P3 developed tonic-clonic convulsions. Laboratory analysis of P3 revealed mild hemolytic anemia and severe renal insufficiency (creatinine of 2. 85 mg/dl, eGFR 30 ml/ min) with arterial hypertension.
40_47del), which has been recently associated with AGS  [7]. In addition, we identified a novel mutation in RNU7-1 absent in the Genome Aggregation Database (gnomAD); P1 and P3 carried a n. 27dup mutation in trans. In P2, we detected a n. 40C > G mutation in trans, which has been reported only once in Gen egnomAD. In conclusion, Sanger sequencing revealed that P1, P2, and P3 (postmortem analysis) were carrying compound heterozygous mutations in RNU7-1 (Fig. 1c, d ).
2c, d ). In line with the autosomal recessive nature of RNU7-1-mediated AGS, the heterozygous RNU7-1 variants reported in gnomAD spanned the whole spectrum, containing both neutral variants and destabilizing mutations (Fig. 2d, e ). Severely destabilizing heterozygous variants (defined as < 2SD of average MFE of homozygous variants or > -10. 81) were rare (Fig. 2e ) with a number of mutant alleles (MFE > -10. 81) in the population database of 205 out of 152,312 sequenced alleles (gnomAD v3. 1) or an estimated 0. 135% mean allele frequency (MAF). Some AGS patients harbored RNU7-1 stem-loop mutations with a MFE < -10. 81 (Fig. 2e ). Notably, these less destabilizing mutations were always compound heterozygous with mutations in the Sm binding site or stem-loop mutations with a MFE > -10. 81 (Fig.
Increased Concentrations of CXCL10 and MCP-1 Cerebrospinal Fluid of RNU7-1 Patients We quantified IFN-I-induced cytokines in serum of AGS patients. Correlating with the high ISG score and serum IFN-α2 levels, we observed pronounced CXCL10 levels in the serum of patients harboring RNASEH2B (2663 pg/mL) and TREX1 (4010 pg/mL) mutations, whereas the concentration in both RNU7-1-mutated patients (P1: 367 pg/mL, P2: 194 pg/mL) was comparable to HCs (median 232 pg/mL, IQR 66-546) (Fig. 3d ). In parallel, we performed cytokine profiling on cerebrospinal fluid (CSF) of RNU7-1 patients (P1, P2). IL-1b, IL-6, and IL-18 could not be detected (data not shown). Low concentrations of IL-1RA (P1: 10 pg/ mL, P2: 19 pg/mL), produced by monocytes upon IFN-I stimulation  [11] , were present in the CSF of patients with RNU7-1 mutations but undetectable in HCs (Fig.
Acknowledgements We gratefully thank the patients and their families for consenting to this research. We thank  Karlien Claes  for the patient-centered support, and  Evelien Dierick ,  Veronique De Backer , and  Katrien Staes  for technical expertise. Figures of secondary U7 snRNA structures were created with BioRender. com. Program for  Undiagnosed Rare Diseases (UD-PrOZA ):  Steven Callens 1,2 , Bart Dermaut 1,3 , Wim Terryn 1,4 , Nika Schuermans 1,3 , Bruce Poppe 1,3 1 The Program for Undiagnosed Rare Diseases (Programma voor Ongediagnosticeerde Zeldzame Aandoeningen-PrOZA ),  Ghent Uni-.
The proportion of the Clostridia class remained similar across the different dietary groups. Within the order Lactobacillales, higher proportions of the Lactobacillaceae family were detected in mice fed the LF and HF diets, while the proportions of Streptococcaceae and Peptostreptococcaceae were higher in mice fed the HF diet. Higher proportions of the genera Lactobacillus and Ligilactobacillus were detected in mice on LF or cyclic HF/LF diets. A higher proportion of the genus Dubosiella was detected in mice on HF and cyclic LF/HF diets. The genus Akkermansia (phylum Verrucomicrobiota) was detected only in fecal samples from mice on the LF diet (data not shown).
[32]  Interestingly, we only identified the Akkermansia genus in microbiota of mice on the LF diet, thereby supporting the hypothesis that this genus is closely linked to the lean phenotype. In order to help establish a functional hypothesis on the changes observed in the fecal bacterial composition, we used the PICRUSt2 software to predict the functional potential of fecal bacterial communities based on marker gene sequencing profiles. [18] In contrast to compositional data where each group of mice had a specific microbiota, we found that predicted functions were similar in mice on high fat/low fat diets or their cyclic counterparts. Indeed, mice on the chronic LF and on cyclic HF/LF diets had a higher proportion of functions dedicated to the biosynthesis of group B vitamins and carbohydrate metabolism.
, VWR, Fontenay sous Bois, France) was added to maximize bacterial lysis. DNA quality was assessed by separation on agarose gel and ethidium bromide staining. The amount of DNA was assessed using a Nanovue spectrophotometer (GE Health care, Uppsala, Sweden). All DNA extracts were stored at -20 °C until analysis. Analysis of Fecal Microbiota using High Throughput Sequencing: The V4 hypervariable region of bacterial 16S rRNA was sequenced in paired-end mode (2 × 300 bp) on the MiSeq platform (Illumina) using primers 351F and 926R. Demultiplexed sequences were obtained, and the Divisive Am-plicon Denoising Algorithm 2 (DADA2) R package was used to remove low quality reads, to de-noise, and remove chimeric sequences. Only forward reads were used for the analysis due to the small amount of overlap between forward and reverse reads following DADA2 trimming and quality filtering.
The outputs from DADA2 Amplicon Sequence Variants (ASVs) were assigned to taxonomies using the Ribosomal Database Project, Naïve Bayesian classifier  [35]  using SILVA 16S rRNA database version 138. 1. [36, 37] Sequences were rarefied at 2535 reads per sample to determine bacterial  and -diversity using the phyloseq R package. [38] ll alpha-diversity metrics (Chao, Abundance-based Coverage Estimators (ACE), Simpson and Shannon) were then plotted and statistically analyzed by ANOVA with a Tukey post-hoc test (p < 0. 05) using GraphPad Prism software (version 9). Beta-diversity metrics (Bray-Curtis dissimilarity, Jaccard, weighted and unweighted Unifrac) were created using phyloseq. Principal coordinate analysis (PCoA) was performed on beta-diversity metrics and statistically confirmed by permutational multivariate analysis of variance using 999 permutations with the Benjamin-Hochberg false discovery rate (FDR, p < 0.