dataesr/scientific-paragraphs-categorization huggingface dataset:
Strengths and Limitations Our review has several strengths. First, we used a rigorous process to search, screen, and select on-topic literature, following best-practice methodologies  [16, 60]. Our search is current and includes papers as recent as February 2022 from multiple databases. Finally, we used several theoretical frameworks to dissect key concepts about technology-enabled diabetes and mental health integrated care including frameworks to understand key concepts such as the intervention, the purpose of the technology, and the intent of the integration. Although our review did not critically appraise the literature or perform a meta-analysis, our methods align with the aims and purpose of a scoping review  [14, 61]. By only including studies written in English, we may have missed important papers written in other languages.
Neutron diffraction For each doping level on CORELLI, a single crystal of 10-30 mg was mounted on an aluminum pin and aligned in the [H,0,L] scattering plane. The crystal was rotated through 360 degrees to cover a large area of reciprocal space. For x = 0. 12, full maps were collected at 6 (Fig. 2a ), 60, and 165 K (Fig. 2b ). For x = 0. 3, full maps of neutron intensities were collected at 6 and 160 K. The data were reduced using MANTID  27  to extract nuclear and magnetic Bragg peak intensities. The nuclear and magnetic structure refinements were then carried out using Jana2006 software  28. Figure  2a, b  shows reciprocal space maps in the [H,0,L] scattering plane for the x = 0. 12 at T = 6 and 165 K obtained on CORELLI. From susceptibility measurements shown in Fig. 1e  and f , we know that the FM component of the magnetization decreases below around 50 K, in addition to changes in FM domain around 120 K.
Elastic neutron scattering Our elastic neutron scattering experiments were carried out at CORELLI at the Spallation Neutron Source (SNS) and WAND 2 at the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL), Oak Ridge, TN, USA  25, 41. For each experiment and sample doping level, a single crystal of 10-50 mg was mounted in the [H,0,L] scattering plane at CORELLI and [H,-H,0] scattering plane at WAND 2. The crystals were put in a closed cycle refrigerator and rotated 360 degrees to collect large reciprocal space maps as a function of temperature. The Mantid package was used for data reduction and analysis. Jana2006 software was used for structure refinement. Nuclear refinements were done using peak intensities from the 165 K, x = 0. 12 and 160 K, x = 0. 3. A total of 304 and 150 reflections, respectively, were used in the refinement and resulted in good fits with R values of 3.
The exponentially modified Gaussian distribution can be written as, σ , with parameters (λ; σ; μ) where λ is a constant, σ is the standard deviation of the Gaussian, and μ is the mean of the Gaussian. For each temperature (See Supplementary Fig. 7a ), this function was fit to the data (See Supplementary Fig. 7b ) and the peak position was extracted as the energy gap (E g ) as summarized in Table  2. f x ð Þ ¼ λ 2 e λ 2 ð2μþλσ Constant energy scans were performed along [0,0,L] and [H,0,3] as a function of temperature. Several scans are shown in Supplementary Fig. 8. For each scan, data were fit to a double Gaussian function including two slightly asymmetric peaks as I ¼ I A e À HÀδ ð Þ 2 =2σ 2 h i þ I B e À Hþδ ð Þ 2 =2σ 2 h i for H-scans and  for L-scans after subtracting a linear background.
ACKNOWLEDGEMENTS We wish to thank  Ursula Bengaard Hansen  and  Paul Steffens  for help and assistance for the Thales experiment. The neutron scattering and single crystal synthesis work at Rice is supported by  US NSF -DMR-2100741  and by the  Robert A. Welch Foundation  under Grant No. C-1839 , respectively (P. D. ). The transport measurements at UW were supported by the  Air Force Office of Scientific Research (AFOSR)  under Award No. FA2386-21-1-4060  and the  David Lucile Packard Foundation  (J. H. C). A portion of this research used resources at the  Spallation Neutron Source  and the  High Flux Isotope Reactor , a  DOE Office of Science User Facility  operated by  ORNL.
DATA AVAILABILITY The data supporting the findings of this study are available within the paper and in the Supplementary Information. The raw data are available from the corresponding authors upon reasonable request. The raw data obtained on IN8 and Thales at ILL are available at https://doi. org/10. 5291/ILL-DATA. 4-01-1630. The raw data from CORELLI and the WAND 2 diffractometers are available upon request.
Study Design and Data Source 7] [18] [19]  For this study in particular, ISAR initially collected data for 5379 patients, using a core set of variables, from 19 countries (Argentina, Australia, Bulgaria, Canada, Colombia, Denmark, Greece, India, Ireland, Italy, Japan, Kuwait, Mexico, Saudi Arabia, South Korea, Spain, Taiwan, United Arab Emirates and the United Kingdom) between January 2015 and February 2021. 18 The ISAR database has ethical approval from the Anonymised Data Ethics Protocols and Transparency (ADEPT) committee (ADEPT0218). This study was designed, implemented, and reported in compliance with the European Network Centres for Pharmacoepidemiology and Pharmacovigilance Code of Conduct (EMA 2014; EUPAS33582) and with all applicable local and international laws and regulations.
Study Cohort This study included patients aged 18 years or older at enrolment and who have SA (ie receiving treatment at GINA 2018 Step 5 or with uncontrolled asthma at GINA Step 4). 20 A summary of how each registry diagnoses asthma and categorizes SA is provided in Supplementary Table  1. In addition, patients in the study cohort were also required to have a history of HOCS exposure use for at least 12 months prior to the index date, defined as either having long-term (maintenance) use of OCS for at least 12 months prior, or using 4 or more courses of rescue steroid bursts for a 12-month period at baseline; a more strict definition than used in previous studies. 7, 8 atients who had received bronchial thermoplasty, any prior history of biologic use, or who had inadequate background data at the date of initiation, were excluded from the analysis.
In addition, there was also potential for confounding by country (eg, the UK was over-represented in the biologic initiator group which may have skewed findings) and, like with other registries, patients may not have been truly representative of the real-life asthma population (albeit more representative than RCT populations). Notwithstanding these limitations, we are confident of the representativeness of the ISAR population as the vast majority of severe asthma patients included in all asthma specialist centres elected to participate in ISAR, or else data were collected directly from EMR embedded registries. A major strength of this study is its size, including a more heterogenous population than that included in randomized controlled trials, with greater generalizability to real life. The global coverage of ISAR, including standardized data from 19 countries, enabled us to explore the clinical characteristics driving initiation of biologics in everyday clinical practice.
Acknowledgments The authors would like to acknowledge  Dr. James Zangrilli  and  Dr. Alex de Giorgio-Miller  for their instrumental contributions to the study concept,  Mr. Joash Tan  ( BSc, Hons ) of the Observational and  Pragmatic Research Institute (OPRI) , for editorial and formatting assistance that supported the development of this publication. The authors also thank the investigators and participating sites in ISAR for making this research possible. ISAR Participating Sites:.
Western blotting Proteins were separated by 10% SDS-PAGE and transferred to PVDF membranes (Amersham, RPN303F) with wet-blotting system (Bio-Rad). After blocking in 100% methanol, membranes were air-dried overnight at room temperature, and then incubated in primary antibodies diluted in 5% skimmed milk, 0. 1% triton X-100, 1× TBS overnight at +4 • C. Horseradish Peroxide (HRP)conjugated anti-rabbit or anti-mouse IgG was used as a secondary antibody (dilution of 1:1000). Proteins were detected using western lightening ECL pro (Ne112200IEA, Perkin Elmer, Netherlands). Signals were obtained with LAS4000 (FujiFilm), saved as 16-bit TIFF files and processed with ImageJ software version 1. 8. 0 (National Institute of Health, USA) and Adobe Photoshop.
1% Tween-20) (= blocking solution) for 1 h. Primary antibodies were diluted in blocking solution (1:100-1:500) and incubation was performed overnight at 4 • C in humidified environment. Acrosome labeling was done with Rhodamine-conjugated peanut agglutinin (PNA, RL-1072). All washes were done in 0. 1% PBST. Alexa Flour 488/546/647 conjugated secondary antibodies (life Technologies) were used in dilution of 1:500 for 1 h at room temperature. Mounting was done using ProLong Diamond Antifade Mountant with DAPI (P36962, Life Technologies). 3i CSU-W1 Spinning disk (objective 40×, 63× or 100×) microscope was used to obtain images. Acquired images were processed with ImageJ 1. 8. 0 software version (National Institute of Health, USA) and Adobe Photoshop.
Antibodies Primary antibodies used in this study were: DDX25 (sc-51271) and Hiwi (sc-22685) from Santa Cruz Biotechnology; DDX4 (ab13840), EIF4A3 (ab32485), and SMG6 (ab87539) from Abcam; PIWIL1 (G82) from Cell Signaling Technology; FYCO1 (HPA035526 and SAB1400697) from Sigma-Aldrich; GAPDH (5G4) from HyTest; ␥ H2AX antibody (05-636) and PIWIL2 clone 13E-3 (MABE363) from Millipore; SMG7 (A302-170A) from Bethyl Laboratories and hVasa (AF2030-SP) from R&D systems. Secondary antibodies conjugated with Alexa Fluor 488, 546, and 647 made in donkey were from Thermo Fisher Scientific (A-21202, A-21206, A-11055, A10036, A10040, A-11056, A-21203, A-21207, A-11058, A-31571, A-31573, A-21447). HRP-linked anti-rabbit IgG (NA934) and HRPlinked anti-mouse IgG (NA031) were from GE Healthcare Life Sciences.
First, raw read counts were filtered in order to keep only genes with 10 or more counts in at least three individual samples among six samples from a given cell type (3 × control and 3 × cKO). For transposable elements, reads were assigned and counted using TEtranscripts in reverse stranded mode (v2. 2. 1) (41) against reference genic and repeats gtf files (Ensembl: Grcm38). For piRNA precursor transcripts, reads were assigned and counted against the gtf file containing the 214 piRNA precursors (20) using featureCounts. Raw count reads were filtered to keep only genes with at least 10 reads across all samples (Smg6-cKO and control). Raw count reads were normalized and differential expression calculated using DE-Seq2 in R (v4. 1. 3). For transcript-level DE analysis, the procedure was similar than for gene-level except raw read counts were filtered in order to keep only transcripts with 20 or more counts in at least three individual samples.
Analysis of NMD-inducing features and stability For analysis of NMD-inducing features, sequences were obtained using the UCSC Table Browser. To identify putative NMD features, we used a custom program developed by the laboratory that was previously published  (42, 43). Only Ensembl-defined transcripts harboring both 5 UTR and 3 UTR regions were considered for analysis. To find downstream exon junctions (dEJs), exon junction positions for each transcript were identified and dEJs were defined as EJs ≥50 nt from the PTC. The 5 UTR sequences identified through the annotation process were used to scan for upstream open reading frames (uORFs) that contained partic-ular nucleotides from the Kozak consensus sequence critical for initiating translation. In particular, we only considered uORFs ≥ 30 nt long that had a purine at the -3 position or a guanine at the +1 position (relative to the A in the AUG initiation codon [+1]).
Analysis of 3 UTRs Transcripts were assembled using Cufflinks v2. 2. 1 for all samples individually. Cuffmerge was used to merge transcripts assemblies for all samples (control + Smg6-cKO). 3 UTR genomic locations were retained from cuffmerge output. A new gtf file was produced containing 3 UTR locations from assembled transcripts. Subsequently, a differential expression analysis was run using Cuffdiff in order to identify lowly expressed 3 UTR transcripts and filter merged transcripts from Smg6-cKO and control in the next step. In parallel, Cuffmerge was used to merge transcripts assemblies from control and Smg6-cKO samples separately. Merged transcripts from Smg6-cKO and control were trimmed to keep only 3 UTR locations and transcripts ≥1 FPKM from the previous step.
Transcriptome comparison between Smg6-cKO and Piwil1-KO The datasets for Piwil1-KO early round spermatids and late spermatocytes (GSE42004), Piwil1-KO pachytene spermatocytes and round spermatids (GSE64138) were downloaded from the NCBI GEO database. Reads were trimmed off adapter contents and low-quality bases were cut using trimmomatic (v0. 39). The clean reads were mapped to the mouse genome (Ensembl: Mus musculus. GRCm38. 101) using STAR (v2. 7. 1a). Then, the reads were assigned and counted using featureCounts in R after mapping. Raw reads were filtered to keep genes with at least 10 reads found in the replicate samples. Raw reads were normalized and differential expression calculated using DE-Seq2. The piRNA targets were predicted using GTBuster without filtering '-distance-from-canonical-cut-site' (https: //github.
com/weng-lab/GTBuster) and NCBI-BLAST. The piRNA species in round spermatids with normalized read counts ≥ 1 were kept. piRNA target sites were predicted at the transcript-level, and the potential piRNA targeted transcripts were then combined to genes according to their locations. The putative piRNA targets were identified based on two rules: (i) perfect pairing with the seed sequence at g2-g7 of the piRNA molecule, and (ii) varying number of additional base pairing (8, 10, 12 or 14 matches) after the seed sequence at g8-g21.
Germ cell small RNA sequencing and analysis The same spermatocyte and round spermatid samples used for RNA sequencing were subjected to small-RNAseq using QIAseq miRNA library preparation kit and HiSeq2500 Rapid run sequencing platform (1 × 75 bp). SPORTS1. 1  (45)  was used to map small RNA reads successively rsRNA, miRNA, and tsRNA sequences extracted from mm10 UCSC genome files originating from rRNAdb, miRBase (v. 22), and GtRNAdb (v. 2. 0) using SPORTS default settings. Using a pre-compiled Perl script from SPORTS1. 1, the original locations of all sequences were identified and analyzed whether they originated from 5 end, 3 end or 3 CCA end of tRNA. Then, reads mapping to rsRNA, miRNA, and tsRNA sequences were extracted from SPORTS output text file using R. Repeats from repeatMasker and piRNA precursor locations  (20)  were mapped to the mouse genome (UCSC: mm10) using HISAT2 (v2.
Using high-throughput sequencing of isolated CBs from Smg6-  cKO and control mice, we identified 844 significantly upregulated and 1242 downregulated genes (log 2 FC ≥ 1. 5 or ≤-1. 5, P adj ≤ 0. 05) in Smg6-cKO CBs (Figure  5I , Supplementary Table  S3C ). Given that the CB is primarily found in round spermatids, we compared mis-regulated genes in the CB and round spermatids. We found that the majority of both the upregulated (63% [532/844]) and the downregulated (79% [981/1242]) genes in the CB were also upor downregulated in round spermatids, respectively (Supplementary Figure  S5F ). Thus, there is a clear overlap between the transcriptome changes in the Smg6-cKO CBs and round spermatids, suggesting that the CB has a central role in the SMG6-dependent transcriptome regulation. Of note, the CB and round spermatid datasets were generated using different library preparation pipelines and thus the overlap detected by our analysis may be an underestimate.
The relatively modest overlap raises the pos-sibility that male germ cells have many novel NMD target mRNAs. Several different 'features' in mRNA are known to target them for decay by NMD  (33). To determine which of these might target mRNAs for decay in male germ cells, we examined the three most well-established NMD-inducing features: (i) an exon-exon junction downstream of the stop codon (dEJ), (ii) a short open reading frame upstream of the main ORF (uORF) and (iii) a long 3 untranslated region (3 UTR)  (33). We did not observe increased frequency of dEJs or uORFs in upregulated transcripts relative to either downregulated or unregulated transcripts in either spermatocytes or round spermatids (Supplementary Figure  S5G , Supplementary Table  S4A , B), suggesting that neither of these features commonly elicits SMG6-dependent NMD in these germ cell stages.
Scale bar: 10 m. (I) Volcano plot to demonstrate differential expression of genes in CBs. See also Supplementary Figure  S5  and Supplementary Tables  S1  and S3. Downloaded from https://academic. oup. com/nar/advance-article/doi/10. 1093/nar/gkac900/6763389 by guest on 02 November 2022   S4. approach, we also analyzed 3 UTR lengths of transcripts assembled from our own datasets using the Cufflinks program, instead of relying on UTR information from other databases (as we did above). This analysis confirmed our finding that the median 3 UTR length is significantly increased in up-versus down-regulated transcripts in both round spermatids and CBs (Figure  6C ). Together, these results strongly suggest that a NMD-inducing feature that commonly elicits RNA decay in round spermatids is a long 3 UTRs.
5, P adj ≤ 0. 05) (Figure  7F , Supplementary Figure  S7D , Supplementary Table  S5 ). We also examined piRNA precursor levels from our long-RNA-seq datasets. While this showed misregulation of some piRNA precursors (Supplementary Figure  S7E , F, Supplementary Table  S6A -C), there was no correlation between the altered expression of precursors vs. mature piRNAs in Smg6-cKO germ cells (Supplementary Figure  S7G, H ). Thus, the changed levels of mature piR-NAs in Smg6-cKO is unlikely to be explained by a piRNA processing defect.
SMG6 and PIWIL1 regulate partially overlapping set of genes Next, we examined whether Smg6 deletion causes misregulation of transcripts known to be targeted by the piRNA pathway. We first determined the expression of transposable elements in Smg6-cKO germ cells. We found some misregulated transposable elements in Smg6-cKO spermatocytes, rounds spermatids and CBs, but no indications of major defects in transposon silencing (Supplementary Table  S6D -F). We next assessed potential shared mRNA targets by comparing the Smg6-cKO and Piwil1-KO round spermatid transcriptomes, the latter of which we reprocessed using available datasets in public repositories. Although it is not clear if piRNAs are involved in the regulation of RNAs that are altered in Piwil1-KO, PIWIL1 is the main piRNA-binding protein in round spermatids  (17, 21) , and the transcriptome defects are likely to reflect the defects in the piRNA pathway.
We focused our analysis on genes that are upregulated as a consequence of either SMG6 or PI-WIL1 deletion. Differential expression analysis identified 997 and 1282 significantly upregulated genes in Piwil1-KO round spermatids (P adj ≤ 0. 05, log 2 FC ≥ 1) in two independent datasets (GSE42004 and GSE64138, respectively). One-fourth of these Piwil1-KO upregulated genes were also upregulated in Smg6-cKO round spermatids (259/997 genes for GSE42004 and 311/1282 genes for GSE64138; Figure  7G  shows the data for GSE42004). The overlap between Piwil1-KO upregulated genes (997) and Smg6-cKO upregulated genes (4812) was statistically significant (p = 4. 9e-05, using Fisher's exact test with genomic background being all 23 024 genes detectably expressed in Smg6-cKO and Piwil1-KO round spermatids).
Error bars represent mean ± SD of three biological replicates. (E) Size distribution of piRNA-mapping reads in round spermatids. Raw counts were normalized in FPM. Error bars represent mean ± SD of three biological replicates. FPM values for (D) and (E) were calculated using a robust median ratio method using DESeq2 v1. 30. 0. (F) Differential expression of piRNA clusters (small-RNA-seq) in round spermatids. piRNA clusters are divided into pre-pachytene (84 clusters), hybrid (30 clusters), and pachytene (100 clusters) according to their abundance in juvenile testes from 10. 5 to 17. 5 dp  (20). (G) Heatmap showing all genes upregulated in Piwil1-KO round spermatids clustered according to their expression pattern in Smg6-cKO germ cells. Piwil1-KO transcriptome data was downloaded from NCBI GEO database (GSE42004).
Genome Annotation and Comparison One urine sample, collected from an adult female E. dupreanum fruit bat in March 2019, yielded a near full-length HNV genome, which we analyzed in greater depth in subsequent analyses and annotated as the novel HNV, AngV (Genbank Accession #: ON613535). Nucleotide BLAST of the AngV genome identified NiV (GenBank Accession #: AF212302) as the top hit for this novel virus and was subsequently chosen as the reference genome for further analysis. We aligned AngV to NiV (GenBank Accession #: AF212302) in the program Geneious Prime (v2020. 2. 4) and annotated all six major HNV structural genes, and the accessory C ORF, within the P gene. We identified the putative mRNA editing site within the P gene sequence (spanning nucleotides 1,225-1,232 of the P gene) and manually added one or two guanine (G) residues to the 3' end of the conserved HNV mRNA editing site to generate V and W ORFs, respectively, and their corresponding proteins.
We furthered queried all identified transcriptional elements against publicly available sequences using NCBI BLAST and BLASTx  (34). Resulting BLAST and BLASTx hits were used in phylogenetic analyses as described below. We used the program pySimPlot to scan the whole genome sequence of AngV for nucleotide sequence identity to the NiV genome (GenBank Accession #: AF212302) and the nucleotide and amino acid sequences of individual Open Reading Frames (ORFs) contained therein. Respectively, window size and scanning were specified as 50 and one for nucleotide pairwise identity and 50 and five for amino acid pairwise identity. Results were visualized using Prism (9. 2. 0).
In accordance with best practices outlined in the RAxML-NG manual, twenty ML inferences were made on each original alignment. Bootstrap replicate trees were inferred using Felsenstein's method  (38). MRE-based bootstopping test was applied after every 200 replicates  (39) , and bootstrapping was terminated once diagnostic statistics dropped below the threshold value. Bootstrap support values were drawn on the best-scoring tree. We additionally computed one Bayesian time-resolved phylogeny, using all 77 full-length HNV nucleotide sequences available in NCBI, including our newly contributed AngV (GenBank Accession #: ON613535). As with ML trees, sequences were first aligned in MUSCLE (v3. 8. 1551)  (35) , and the best fit nucleotide substitution model was subsequently queried in ModelTest-NG  (36).
We then constructed a Bayesian timetree in the program BEAST2  (40, 41) , using the best fit GTR+I+G4 model inferred for the whole genome alignment from ModelTest-NG and assuming a constant population prior. Sampling dates corresponded to collection data as reported in NCBI Virus; we assumed a collection date of 31-July in cases where only year of collection was reported. We computed trees using both an uncorrelated exponentially distributed relaxed molecular clock (UCED) and a strict clock but here report results from the strict clock only as similar results were inferred from both. We ran Markov Chain Monte Carlo (MCMC) sample chains for 1 billion iterations, checked convergence using TRACER v1. 7  (42)  and averaged trees after 10% burn-in using TreeAnnotator v2. 6. 3  (43)  to visualize mean posterior densities at each node.
AngV G Protein Structure Modeling We used the Artificial Intelligence system, AlphaFold, to predict the 3D structure of the AngV glycoprotein (G)  (45). Molecular graphics and analyses of the AngV glycoprotein structure were performed with UCSF ChimeraX  (46). HNV glycoprotein ephrin binding residues were aligned using the program Geneious Prime (v2020. 2. 4).