dataesr/scientific-paragraphs-categorization huggingface dataset:
In the present analysis, few hypoglycaemia events were recorded (iGlarLixi: 2. 7%; BI + RAI: 2. 5%), and the severity of these events is unknown. Because of factors such as impaired awareness, recall bias, incorrect coding, or reticence of participants to report episodes to their physicians, hypoglycaemia tends to be underreported in retrospective RWE studies. 29, 30 Hypoglycaemic events recorded in EMRs are also more likely to be severe, that is, events requiring external assistance for recovery. 31 In comparison, data from a survey-based study specifically designed to assess self-reported hypoglycaemia showed that >50% of 2706 Canadians receiving insulin and/or sulphonylureas reported at least one non-severe event in the last 30 days and/or severe event in the last year. 32 This suggests many hypoglycaemia events are not captured in EMRs, which is a limitation of the study and means that conclusions about the effect of treatment on hypoglycaemia in SoliSimplify cannot be derived because of the low reported incidence of hypoglycaemia.
23 Furthermore, there are additional treatment considerations for older adults because of their higher risk of hypoglycaemia and associated complications,  35  as well as the prevalence of comorbidities, polypharmacy and renal impairment in this population. 34 Consequently, guidelines recommend treatment simplification where possible for older individuals, which may suggest that iGlarLixi could provide a suitable option for older people with T2D who require therapy advancement. Limitations of the present analysis include that the EMR database used is a repository for reimbursement claims and is not designed to support clinical research. Thus, the quality of the data depends on the information provided by the physicians  11  or on correct coding and many potentially-useful data are not available (e.
ACKNOWLEDGMENTS We thank  Ana Merino-Trigo, PhD  ( Sanofi ) for coordinating the development, facilitating author discussions, and for providing a courtesy review of this manuscript. We also thank  Xiaoyu Lin  and  Jing Li  ( IQVIA China ) for analytical support. Editorial assistance was provided by  Katey Glunt, PhD , and  Hannah Brown, PhD , of  Fishawack Communications Ltd , part of Fishawack Health.
Demographic and baseline characteristics for iGlarLixi versus BI + RAI cohort after PSM Variable iGlarLixi (N = 814) BI + RAI (N = 814) STD DIFF Age, years; mean ± SD 61. 5 ± 11. 0 61. 6 ± 11. 1 0. 01 Age group, years; n (%) 18-49 108 (13. 3) 107 (13. 1) 0. 00 50-64 378 (46. 4) 368 (45. 2) 0. 02 65-74 238 (29. 2) 249 (30. 6) 0. 03 ≥75 90 (11. 1) 90 (11. 1) 0. 00 Sex, female; n (%) 392 (48. 2) 400 (49. 1) 0. 02 Race, n (%) Asian 21 (2. 6) 19 (2. 3) 0. 02 African American 94 (11. 6) 103 (12. 7) 0. 03 Caucasian 573 (70. 4) 563 (69. 2) 0. 03 Other/unknown 126 (15. 5) 129 (15. 9) 0. 01 T2D duration identified in database, years; mean 4. 6 ± 3. 1 4. 8 ± 3. 2 0. 03 ± SD a Body weight, kg; mean ± SD b 100. 1 ± 22. 7 99. 0 ± 23. 5 0. 04 HbA1c value b % mean ± SD 9. 2 ± 1. 8 9. 2 ± 1. 7 0. 01 mmol/mol, mean ± SD 77 ± 19 77 ± 19 0.
4) 150 (18. 4) 0. 00 1 July 2016 index date) and between 90 and 210 days post index date. Insulin degludec 131 (16. 1) Identification period 119 (14. 6) 28 February 2021 0. 04 NPH Retrospective, observational, cohort study of 21 (2. 6) 1 January 2017 -31 August 2020 19 (2. 3) 0. 02 anonymized patient data collected from the OADs usage, n (%) 0 OMOP US Ambulatory EMRs database Baseline period: ≥6 months prior to 160 (19. 7) Follow-up period: Starts from index date and continues to the 148 (18. 2) 0. 04 1 index date 342 (42. 0) date of death, health plan disenrollment, end of 6 months (180 days), or last day of 353 (43. 4) 0. 03 2 251 (30. 8) available data, whichever occurs first 258 (31. 7) 0. 02 ≥3 Population 61 (7. 5) 55 (6. 8) 0. 03 • ≥18 years old with T2D OADs categories, n (%) e BI iGlarLixi (QD) Metformin • Prescribed BI for 6 months 540 (66.
Duration of T2D listed in the database was limited by the length of time that participants were enrolled in the health care plan. Variable iGlarLixi (N = 814) BI + RAI (N = 814) STD DIFF Neuropathy 201 (24. 7) 192 (23. 6) 0. 03 Nephropathy 145 (17. 8) 137 (16. 8) 0. 03 Retinopathy 51 (6. 3) 56 (6. 9) 0. 02 Obesity 220 (27. 0) 225 (27. 6) 0. 01 Depression 108 (13. 3) 107 (13. 1) 0. 00 Chronic kidney disease 93 (11. 4) 85 (10. 4) 0. 03 Systolic blood pressure value, mmHg; mean ± SD a,f 130. 78 ± 15. 12 130. 75 ± 15. 64 0. 00 Diastolic blood pressure value, mmHg; mean ± SD a,g 76. 26 ± 9. 13 75. 94 ± 9. 63 0. 03 a b Closest to index date. cHbA1c: 7% = 53 mmol/mol, 8% = 64 mmol/mol, 9% = 75 mmol/mol, 11% = 97 mmol/mol. dParticipants could be prescribed more than one type of BI in the baseline period.
eIt was not possible to identify SGLT2 inhibitor use from the database. fSystolic blood pressure before PSM was calculated on 814 participants on iGlarLixi and 7183 participants on BI + RAI. g Diastolic blood pressure before PSM was calculated on 814 participants on iGlarLixi and 7184 participants on BI + RAI. Abbreviations: BI, basal insulin; CCI, Charleson Comorbidity Index; DPP-4i, dipeptidyl peptidase-4 inhibitor; GLP-1 RA, glucagon-like peptide-1 receptor agonist; HbA1c, glycated haemoglobin; iGlarLixi, insulin glargine 100 U/ml and lixisenatide; NPH, neutral protamine Hagedorn; OAD, oral antihyperglycaemic drug; PSM, propensity score matching; RAI, rapid acting insulin; SD, standard deviation; SGLT2, sodium glucose co-transporter-2; STD DIFF, standardized mean difference; T2D, type-2 diabetes mellitus.
Trio-whole-exome sequencing analysis The 37 Italian patient-parents trios and German patients underwent whole-exome sequencing (WES). Exome library capture and enrichment was performed with BGI kit (BGI Genomics, n = 104) or the NimbleGen SeqCap EZ (Roche, n = 7) and sequenced as paired-end reads with an Illumina system. As previously described,  23  sequencing reads were processed to obtain annotated variant calls and retain for downstream analyses only variants located in coding exons or canonical splice-site junctions. Guidelines for sequence variant interpretation of the American College of Medical Genetics (ACMG)  24  were followed for clinical classification of variants in established epilepsy genes by using the online platform Varsome (https://varsome. com/). We calculated the mean rate of de novo variants (DNVs) in the main variant classes (missense, nonsense, splicing affecting, frame-shift, in-frame indels and synonymous single nucleotide variants) and used for comparison data from a large control cohort of 1911 trios previously published.
25 Although we did not formally account for differences in variant discovery workflows,  25  they have similarities in both enrichment methods and bioinformatic pipelines. To select candidate FE genes, we used the following criteria: (i) the DNV has allele count ≤1 across control samples in the genome aggregation database (gnomAD) data set v2. 1. 1 including counts on 60146 chromosomes; (ii) the DNV has CADD Phred score (v1. 4) ≥ 15; (iii) the gene is expressed in brain according to the Human Protein Atlas and Human Allen Brain Atlas databases; (iv) the encoded protein is important for brain development and function based on NCBI Entrez Gene Summary and UniprotKB databases as well as bibliographic research; and (v) the gene is intolerant to variation according to gnomAD v2. 1. 1 measures for genetic constraints (missense Z score > 3 and/or pLI > 0.
23 ollowing the observation that disease-causing variants in common epilepsies are characterized by allelic counts ≤1 in large-scale data sets of genomic variants representative of the general population,  28  we defined ultra-rare variants (URVs) using criteria (i) and (ii) described above for the selection of candidate FE genes bearing deleterious protein-altering URVs. We used the Depth of Coverage utility in the Genome Analysis Toolkit (GATK v3. 8)  29  to calculate the per-sample percentage of targeted bases covered by >5 unique reads (Depth of Coverage >5X) on each gene (coding exons and flanking canonical splice sites). Candidate variants were validated by Sanger sequencing.
As samples may have been analysed by smMIPs and subsequently included in the Epi25 study, the variants that were identified in the same samples by both approaches were counted only once. CLUMP carries out an unsupervised clustering analysis of amino-acid residues hit by variants, with no prior assumption on annotated protein domains. We also examined the proximity of smURVs relative to the known domains ('domain-proximity' analysis). To do this, we retrieved the protein sequence positions of the amino-acid residues representing the N-terminal (P N ) and C-terminal (P C ) boundaries of the domains annotated in the Uniprot database record for PI3K-C2β (O00750). We calculated the distance (D) between the position of amino-acid residue hit by each variant (P V ) and each domain separately in the following way: (i) D = 0 if P N ≤ P V ≤ P C ; (ii) D = P V -P C if P V > P C ; and (iii) D = P N -P V if P V < P N.
Lysates were cleared by centrifugation at 13 000 rpm at 4°C for 10 min. Protein concentration was determined by the Bradford method. SDS-PAGE and immunoblotting followed standard procedures. Enhanced chemiluminescence (ECL) detection reagents were purchased from Bio-Rad Laboratories. All other chemicals were purchased from Sigma Aldrich. Signal quantification was performed using Image Lab (Bio-Rad Laboratories). One-way ANOVA was used for statistical testing. Generation of the Pik3c2b +/G1501fs*1 mouse model We modelled the loss of the terminal C2 domain of PI3K-C2β using the CRISPR/Cas9 technology. In mice, the terminal C2 domain starts at position 1504 (Uniprot Database), the residue encoded by exon 31. We designed a single guide RNAs (sgRNAs) targeting this region (TCCCCACCGACCTTCCCAACCGG), in order to generate frameshiftderived stop codons.
Confocal imaging of immunostained hippocampal neurons Cultured hippocampal neurons were fixed at DIV 14 using 4% (w/v) paraformaldehyde (PFA) and 4% sucrose in phosphate-buffered saline (PBS) for 15 min at room temperature. Fixed neurons were blocked and permeabilized with PBS containing 10% (v/v) normal goat serum and 0. 3% Triton X-100 for 1 h, followed by incubation with primary antibodies in 0. 3% Triton X-100 in PBS for 1 h. Corresponding secondary antibodies (Alexa Fluor 488, 568 and 647, Life technologies) were then incubated for 30 min in PBS-0. 3% Triton X-100. Coverslips were mounted with DAPI-containing Immumount (Thermo-Fisher). Imaging was performed with a Zeiss Axiovert 200 M equipped with the Perkin-Elmer Ultra View ERS system and a Hamamatsu C9100 EM-CCD camera under the control of Volocity software (Perkin-Elmer).
Fluorescent intensities were semi-automatically quantified using a custom Fiji macro. 34 anual regions of interest of the soma were defined based on the neuronal marker and mean intensities within these regions of interest were extracted based on the p-S6 channel (macro is available at doi:10. 5281/zenodo. 5652147). Camera background was subtracted by the intensity values of a blank image, and small artefacts/uneven background were controlled for using the rolling ball method with a 200-pixel radius. Segmentation was conducted with the MAP2 channel using a median filter of 2-pixel radius followed by the Huang2 automatic threshold.
Coverslips were placed on top, sealed with nail varnish and stored at 4°C. To quantify p62 levels a z-series of 9-11 images (1024 × 1024 pixels/image with zoom factor 1. 3, each averaged twice) chosen to cover the entire region of interest from top to bottom was acquired using a Zeiss LSM780 confocal microscope equipped with a 20× objective. The resulting z-stack was 'flattened' into a single image using maximum projection. All acquisition settings were set equally for sections of all groups within each immunostaining. Average p62 intensities were determined in rectangular areas of 100 × 50 μm in the stratum pyramidale or stratum radiatum of CA1. Images were quantified using Fiji/ImageJ software (NIH).
Paired pulse modulation (PPM) of the amplitudes of the second compared to the first population spike were calculated and expressed in %. Each value measured is an average of three consecutive stimulations repeated every 20 s for stimulus response and every 30 s for paired pulse modulation measurements. To probe if slices in vitro are prone to epileptic seizure-like activity, we induced activity-dependent disinhibition of neuronal networks by delivering 60 pulses at 1 Hz with the supramaximal intensity of 200 µA. Facilitation of the population spike and appearance of polyspikes, induced by activity-dependent disinhibition, were calculated as the sum area changes of population spikes and polyspikes using a custom-written algorithm implemented in IGOR Pro software. SigmaPlot (Systat Software, Inc.
5 MΩ) placed at 50-60 μm distance to the recorded pyramidal cell. The patch electrodes had a resistance of 3-5 MΩ when filled with an internal solution containing (in mM) 140 CsCl, 10 HEPES, 10 EGTA, 2 Mg-ATP and 5 mM QX-314 (pH 7. 35; 295-305 mOsm). IPSCs were pharmacologically isolated using 20 μM CNQX (AMPA/kainate receptor antagonist) and 50 μM APV (NMDA receptor antagonist) for at least 10 min before the recordings. After obtaining a stable whole-cell configuration (to allow intrapipette solution to diffuse into the cell) for 10 min we first recorded spontaneous IPSCs (sIPSCs) for 3 min. The frequency of sIPSCs was analysed using the Mini Analysis Program (Synaptosoft Inc. ). Synaptic events above a threshold of 10 pA were used to calculate spontaneous synaptic activity. To measure evoked inhibitory transmission, we generated stimulus response curves by plotting increasing stimulation intensities from 10 to 80 μA in steps of 10 μA and compared IPSC amplitudes.
Statistical analyses CLUMP analysis incorporates a Wilcoxon signed-rank test. A two-tailed Student's t-test was used to compare the mean rate of DNVs in the main variant classes (missense, nonsense, splicing affecting, synonymous and frameshift/non-frameshift indels) between our cohort and a large control cohort of 1911 trios. 25 In domain-proximity analysis, we used a two-tailed Student's t-test to evaluate the difference in the mean distance (D) between the position of the variant amino acid residue and each domain separately in cases and controls. P-values were adjusted for multiple comparisons over the 6 PI3K-C2β Uniprot domains with Bonferroni correction. Biochemical data were analysed using the GraphPad Prism6 software: significance was calculated with Student's t-test and one-or two-way ANOVA followed by Bonferroni's post hoc analysis, or Mantel Cox log-rank test where appropriate.
Data are reported as mean ± SEM. The number of independent experiments analysed is represented by 'n'. Significance is denoted using asterisks *P < 0. 05, **P < 0. 01, ***P < 0. 001 and P > 0. 05 or not significant (ns). Confocal microscopy data from hippocampal slices and cultured neurons were analysed using GraphPad Prism6. Student's t-test was used for experiments with two genotypes and one-way ANOVA followed by Bonferroni's post hoc analysis for experiments with more than one variable. Data are reported as mean ± SEM. The number of independent experiments analysed is represented by 'n'. Significance levels were *P < 0. 05, **P < 0. 01, ***P < 0. 001 and P > 0. 05 is not significant (ns). Electrophysiological data curves were statistically evaluated using two-way ANOVA with repeated measures (RM, significance depicted over a line encompassing the curve).
The six remaining PIK3C2B variants (Table  2 ) were all heterozygous URVs including three protein-truncating variants and three missense changes affecting the catalytic or C2 domains (Fig. 1A ). Conversely, URVs identified in controls were five missense variants situated mostly distant from domains involved in catalysis, with only one variant (p. E1168V) within the catalytic domain (Supplementary Table  4 ). None of the patients' variants appeared in the whole data sets available in the gnomAD v2. 1. 1 and v3. 1. 1 browsers. In the Epi25 data set, the trend reported for this gene was towards an excess of loss-of-function variants in NAFE cases: 5/3597 samples (0. 01%), including the p. Q1533* variant originally identified by smMIPs, versus 2/8364 controls (0. 002%). As clustering of singleton missense variants provides insights into the molecular mechanisms underlying epileptic disorders, 40 we further explored whether PIK3C2B missense URVs (smURVs) identified in FE patients were preferentially clustered in key regions of the protein.
Significant clustering was detected in cases within or near the catalytic domain as well as the C-terminal lipid-binding autoregulatory domains C2 and PX, although to a lesser extent (Fig. 1C  and Supplementary Table  7 ), suggesting that URVs located within or near the main known functional domains were more likely to be involved in FE. Interestingly, one of the smURVs in Epi25 (p. N1311D) recurred in two genomically unrelated German NAFE cases: this smURV was the closest to the p. E1294Q DNV on the protein sequence, that was present only once in the whole gnomAD data set and was the only variant with population allele frequency <5% shared by these two subjects. To assess familial segregation of other variants than the p. E1294Q DNV, we could access parental samples of two Epi25 NAFE cases carrying URVs of interest.
The first was a familial case in which the proband inherited the missense p. G1345S variant from the affected father. A paternal uncle was also reported to have experienced seizures, but no further information was available. This URV was not present in the whole gnomAD data sets and was situated immediately downstream to the catalytic domain. Another Epi25 NAFE case inherited a loss-of-function URV (p. K584*) from the unaffected father, suggesting incomplete penetrance. None of the NAFE cases with smURVs was found to carry a concomitant pathogenic/likely pathogenic variant in established FE genes or in FE-related genes along the mTOR pathway axis (details presented in Supplementary material). URV-positive patients did not display specific clinicopathological features (Table  2 ) compared to the characteristics of the whole initial cohort (Table  1 ) except for an earlier mean age at epilepsy onset (11.
Patients' mutations impair PI3K-C2β lipid-synthesizing activity and lead to mTORC1 hyperactivation We next asked whether protein-truncating and missense PI3K-C2β URVs result in a loss-of-function mechanism. We therefore used site-directed mutagenesis to generate three missense mutants (p. R1118L, p. E1294Q and p. I1544M) and one mutant inserting a premature stop codon (p. Q1533*) predicted to cause the truncation of the C2 domain, which is known to be a critical determinant for  kinase activity of class II enzymes. 39 We also generated control cDNAs of p. I1212V and p. E1169K variants that have been observed in FE patients but present in the general population. These variants, located within the PI3K catalytic domain are listed in the gnomAD database and reported with allele frequencies 1.
PI3K-C2β isoform, thus supporting their loss-of-function effect. On the other hand, one tested URV, the p. R1118L, retained its catalytic activity and had no significant effect on mTORC1 when transfected in HEK293T cells. The clinical phenotype of the patient carrying the p. R1118L is remarkably mild, which would be consistent either with a less pronounced effect on kinase activity and mTORC1 activation at the molecular level, or with a pathogenic mechanism that is triggered through different molecular pathways. PIK3C2B is a gene highly intolerant to loss-of-function variation in the general population according to gnomAD data, where only 15 loss-of-function variants are observed against an expected number of 82. 8. Moreover, in the Database of Genomic Variants, deletions of PIK3C2B coding regions are rarely reported, i.
Genome Aggregation Database: https://gnomad. broadinstitute. org/ Database of Genomic Variants: http://dgv. tcag. ca/dgv/app/ home Varsome: https://varsome. com/ Epi25: https://epi25. broadinstitute. org/ CADD score: https://cadd. gs. washington. edu/ ClinVar: https://www. ncbi. nlm. nih. gov/clinvar/.
Acknowledgements We are thankful to the patients and their families for their participation in this study. We acknowledge  Elena Bacchelli  ( Dipartimento di Farmacia e Biotecnologie, University of Bologna, Italy ) for providing access to Italian control samples. Whole Exome Sequencing data were generated at  Beijing Genomic Institute, Shenzhen, China. Pik3c2b +/G1501fs*1 genetically modified mice were generated by the  MBC Core Facility for Gene Transfer and Mutagenesis (University of Torino, Italy). Finally, we thank  Dr Chistopher Schmied  [ Cellular Imaging Facility, Leibniz Forschungsinstitut für Molekulare Pharmakologie (FMP), Berlin, Germany ] for generating a Fiji-based macro for semi-automated neuron segmentation (available at:  DOI 10. 5281/zenodo. 5652147 ).
Funding We acknowledge the  Epi25 collaborative  for the use of Epi25 data: this work was part of the  Centers for Common Disease Genomics (CCDG) program , funded by the  National Human Genome Research Institute (NHGRI)  and the  National Heart, Lung, and Blood Institute (NHLBI). CCDG-funded Epi25 research activities at the  Broad Institute , including genomic data generation in the  Broad Genomics Platform , are supported by  NHGRI  grant  UM1 HG008895  (PIs:  Eric Lander ,  Stacey Gabriel ,  Mark Daly ,  Sekar Kathiresan ). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. This study has been partially supported by  Fondazione Telethon  Project  GGP13200  to P. T. and T. P. ,  Fondazione Telethon  Project  GGP19146  to  G.
This multicentric, randomized open-label phase I/II VICTORIA trial (NCT02730923) showed that Vistusertib and Anastrozole combination treatment (V + A, n = 49) improve neoplastic control compared to Anastrozole alone (A, n = 24), with a progression-free rate at 8 weeks of 67% in the V + A arm and of 39% in the A arm. The VICTORIA trial thus reveals that targeting the PI3K/AKT/mTOR pathway is of clinical relevance in metastatic endometrial cancer. Nevertheless, a better selection of patients based on molecular traits of their tumours would improve outcome, by predicting the effectiveness of mTOR inhibitors  [4, 5]. Ribosome, the cellular machinery translating mRNA into protein, appears at the heart of several recent innovative approaches to improve cancer patient management  [6] [7] [8]. It appears that most cancer cells are addicted to ribosome biogenesis (RiBi).
Study design and samples The randomized phase I/II VICTORIA trial (NCT02730923) was conducted in HR+ metastatic or recurrent endometrial cancer patients (n = 73) to evaluate the Vistusertib + Anastrozole combination (V + A) towards Anastrozole alone (A)  [4]. Tumour biopsies at diagnosis and after 8 weeks of treatment were stored as formalin-fixed, paraffin-embedded (FFPE) blocks before processing at Centre L eon B erard. Blood samples were collected in EDTA tubes at pre-treatment, after 8 weeks of treatment and at disease progression. Serum was directly separated by 2000 g centrifugation for 10 min and stored at À20 °C. Biological samples have been prepared by BB-0033-00050, CRB Centre L eon B erard, Lyon France. It has to be noted that our cohort is limited in terms of sample numbers. First, the study was designed as a two steps trial and the optimal (and minimal) cohort size has been defined according to the Simon optimal two-stage design.