dataesr/scientific-paragraphs-categorization huggingface dataset:
To Manuela A. Oestereicher, Janine M. Wotton, Jacqueline K. White and Nadine Spielmann have equal contributions. Extended author information available on the last page of the article our knowledge, there are no published reference ranges for electrocardiography (ECG) in the laboratory mouse. Such reference ranges would provide the research community with the information necessary to evaluate the consequences of pharmacological, environmental, or genetic perturbations, the latter opening up the opportunity to uncover genotype*phenotype associations. We used ECG data collected under the auspices of the International Mouse Phenotyping Consortium (IMPC)  (Dickinson et al. 2016 ) (https:// www. mouse pheno type. org), to generate the first mouse-specific cardiac physiology reference ranges. Here, data were collected from over 26,000 conscious or anesthetized C57BL/6N wildtype control mice stratified by sex and age.
IMPC centers contributing electrocardiography data IMPC data release (DR) 15. 0 was used herein (https:// www. mouse pheno type. org/ data/ previ ous-relea ses/ 15. 0). The following subset of ten IMPC data-contributing centers provided electrocardiography (ECG) data in DR 15. 0 (ethical approval details are included in parenthesis after each contributing center):.
Animals This study includes data collected from inbred wildtype control animals tested as part of the IMPC goals. These mice, both males and females, were on a C57BL/6N genetic background of substrains: C57BL/6NCrl (CCP, HMGU, ICS, TCP and UCD); C57BL/6NJ (JAX and BCM); C57BL/6NJcl (RBRC) and C57BL/6NTac (KMPC, HMGU, ICS and HAR). Non-IMPC mice were from four different studies: (1) The founder strains animals from a study titled "The Collaborative Cross: A Recombinant Inbred Mouse Population for the Systems Genetic Era"  (Threadgill et al. 2011)  with A/J, C57BL/6J, 129S1/SvlmJ, NOD/ShiLtJ, NZO/HlLtJ, CAST/EiJ, PWK/Ph, and WSB/EiJ inbred strains (https:// pheno me. jax. org/ proje cts/ GMC13); (2) The Jaxwest1 project, a multi-system analysis of physiology on seven inbred strains of mice: 129S1/SvImJ, A/J, BALB/cJ, C57BL/6J, DBA/2J, NOD/ShiLtJ and SJL/J (https:// pheno me.
Data collection The IMPC standard operating procedure provides an overview of the conscious and anesthetized ECG procedures used by contributing centers (https:// www. mouse pheno type. org/ impre ss/ Proce dureI nfo? action= list& procID= 1415& pipeID=7). In brief, conscious ECG was collected using ECGenie equipment (Mouse Specifics, Inc. ) as detailed previously by Spielmann  (Spielmann et al. 2022). Based on availability of equipment and local expertise, some contributing centers opted to perform anesthetized ECG using Power Lab recording equipment and LabChart8 software (ADInstruments), configured in the following way. All centers used the "Mouse" preset detection and analysis settings and the "Rodent T-wave" analysis mode. The default values in the LabChart detection and analysis settings were as follows: the typical QRS width was 10 ms; R-waves were at least 60 ms apart; the Pre-P baseline was 10 ms; the maximum PR was 50 ms; the maximum RT was 40 ms; and the ST height was measured at 10 ms from alignment.
Data annotation and quality Standard protocols for ECG signal analysis were used to analyze the data. For each cardiac cycle, the P, Q, R, S and T peaks were defined and used to derive a total of fifteen parameters including intervals, amplitudes, and dispersions (Supplemental Table  1 ). In both, conscious (ECGenie equipment) and anesthetized (LabChart using the preset windows stipulated above) EGC, P, Q, R, S and T peaks were automatically detected by averaging over multiple cardiac cycles. If any peaks were not selected correctly by either software, the position of this marker was corrected manually. Heart rate variability (HRV) was calculated as the mean of the differences between successive heart rates for the entire set of ECG signals. The QT-intervals were frequency corrected (QTc) by applying the following equation derived by  Mitchell (Mitchell et al.
1998 ): QTc = [QT/√(RR/100)]*1000 s. Noise and movement artefacts were automatically eliminated by the software. Some subtle differences in wave marker placement were observed across IMPC contributing centers. P, Q and R marker locations were annotated consistently by all contributing centers. In Fig. 1 , S is annotated at the peak negative inflection point of the QRS complex, which accurately reflects the majority of data reported herein, including all data collected from conscious mice. However, for datasets collected on anesthetized mice, contributing centers variably annotated S at the peak negative inflection point, the isoelectric point, or halfway between peak negative inflection and isoelectric point. In Fig. 1 , T Conscious is annotated as the peak positive inflection following S, which accurately reflects the majority of data reported herein, including all data collected from conscious mice.
Statistical methods Bespoke methods were developed to assess ECG reference ranges and are independent of the methodologies implemented on the IMPC portal. Data analysis was conducted using R [version 4. 0. 4, R Core Team 2022  (Team 2022) ] with figures and tables produced in ggplot2, embedded in RMarkdown HTML files. Variability of all the data were assessed with two metrics (a) coefficient of variation (COV) and (b) "Quartile-based CV" (QCV), defined as interquartile range (IQR) (75-25%) relative to the median (100*IQR/median). Visual methods, as well as formal statistical tests were applied to test whether the scores of the individual parameters were normally distributed. Data were separated by age, sex and anesthesia regime and histograms for each parameter were plotted. Shapiro-Wilks tests were conducted to assess normality.
Results ECG data collected by IMPC contributing centers (data release, DR, 15. 0) were available from 26,706 wildtype control mice, stratified as presented in Table  1  and summarized below. All the mice were from a C57BL/6N-inbred substrain. ECG was performed on conscious mice, or mice anesthetized with either isoflurane or tribromoethanol. The majority of mice (90. 6% or 24,194) were tested at a mean age of 12 weeks (designated as Early Adult or EA), while the remaining 9. 4% (2512) of mice were tested at a mean age of 62 weeks (designated as Late Adult or LA). Sex was evenly distributed at both EA and LA timepoints. Raw data can be downloaded using the following link: https:// www. mouse pheno type. org/ data/ previ ous-relea ses/ 15. 0. The total number of reported parameters varied slightly between mice and can be accessed in Supplemental Table 2.
Variability assessment A panel of 15 output parameters were collected from ECG, namely heart rate (HR), RR-, PR-, PQ-, ST-, and QT-interval, and QT corrected (QTc) using the Mitchell formula 4 , QRS complex, coefficient of variation of R-R intervals (CV), heart rate variability (HRV), pNN5, rMSSD (Root Mean Sum of Squared Distance), mean R-amplitude, mean SRamplitude and QT corrected (QTc) dispersion (parameter definition in Supplemental Table  1 ). In multi-center, large-scale, high-throughput programs such as the IMPC, variability in the measured values was to be expected. However, the extent of this variability dictates the sensitivity and robustness of each parameter. Variability testing was performed on all DR 15. 0 ECG data from the IMPC, independently of anesthetic agent in this analysis.
2 ) however, PQ-interval was excluded from further analysis in this study because data points were only captured in EA and LA mice from one of the ten data-contributing centers. The remaining seven ECG parameters [heart rate (HR), RR-, PR-, ST-and QT-interval, QRS complex, and QT corrected (QTc) using the Mitchell formula  (Mitchell et al. 1998) ] consistently presented with low variability across the whole IMPC dataset thereby giving high confidence to establish robust, generalizable reference ranges for EA and LA populations on the C57BL/6N-inbred genetic background. Despite the exclusion of several parameters, the electrical conduction phases of a cardiac cycle were entirely captured by the robust parameters included herein (Fig. 1 ). The lengths of PR-interval and QRS complex covered the atrial and ventricular depolarization phases (e.
Effect of age on ECG parameters Two different age groups, i. e. , mean of 12-weeks (minimum 8 and maximum 16 weeks) old EA and mean of 62 weeks (minimum 52 and maximum 78 weeks) old LA, have made it possible to explore the effect of age on ECG parameters in conscious and isoflurane anesthetized mice. A two-tailed Data are stratified by sex, age (EA and LA) and conscious state. Note, there were no data for LA mice anesthetized using tribromoethanol  To test the influence of unbalanced group sizes (i. e. , large number of EA and smaller number of LA datasets), we applied a bootstrap analysis, this time stratified by sex (Fig. 5  -Panel c). The proportion of significant t-tests (p < 0. 05), from the 1000 comparisons, indicates the power to find the age difference, for that subsample size. This bootstrap analysis demonstrated that parameters with even small to medium effect sizes required relatively large experimental group sizes to attain a conventional > 80% value for power estimates  (Cohen 1992; Festing and Altman 2002) , e.
Validation of reference ranges using non-IMPC data Mice characterized by the IMPC are all substrains of one commonly used inbred genetic background, C57BL/6N. To test the validity of the reference ranges reported herein beyond C57BL/6N-inbred mice, we used representative control animals from publicly available ECG data including: six founder strains from a collaborative cross study  (Threadgill et al. 2011) ; the Jaxwest1 project (https:// pheno me. jax. org/ proje cts/ Jaxwe st1) with seven inbred strains of mice; and the Xing1: Aging study (https:// pheno me. jax. org/ proje cts/ Xing1)  (Xing et al. 2009 ) with 29 inbred strains of which we have included herein the 26 strains with complete ECG data. An additional dataset Fig. 6  Reference ranges split by anesthetic regimen showing median, and 95% reference ranges (2.
Discussion Reference ranges for the assessment of abnormal electrocardiograms and cardiac conduction disorders in patients have long been established and are regularly adopted by expert bodies, such as the North American Society of  Pacing and Electrophysiology (GURA et al. 2003)  and the European Society of Cardiology  (Blomström-Lundqvist et al. 2003; Camm et al. 2010). For mouse models, however, there are no such reference ranges. In this multicenter study, we have established reference ranges using an exceptionally large ECG dataset comprising more than 26,000 wildtype control mice from the International Mouse Phenotyping Consortium (IMPC). The goal of the IMPC is to extend the functional annotation of the mammalian genome via the large-scale production and phenotypic characterization of single gene knockout mouse strains for all protein-coding genes.
The phenotypic pipeline used to characterize these knockout strains included cardiac electrophysiology assessment using ECG. For each knockout strain characterized, we also assessed wildtype control animals matched for age, sex and genetic background. The ECG data from these C57BL/6N wildtype control mice hold extraordinary value and represent the focus of the current study. Thus, this study represents a large mouse data set and allows the crucial understanding of the effects of sex, age, and anesthesia on electrocardiograms in mice. To this end, we introduced a stepwise refinement of the data analysis and started with an in-depth assessment of the variability of 15 ECG parameters gathered in the IMPC. We identified seven clinically relevant ECG parameters that were highly robust and had low variability.
The majority of data included in this study were collected on conscious mice using the non-invasive, ECGenie methodology. Given the large sample size collected, this approach represented a huge 3Rs benefit  (Hubrecht and Carter 2019; Tannenbaum and Bennett 2015). However, the relatively low-resolution of the ECGenie technique meant that annotation of the J wave, a commonly recognized feature of the mouse ECG, was omitted from this study. The difference in T marker positioning between ECG data from conscious and anesthetized mice was substantive and contributed to the statistically significant differences in time intervals involving T (QT, QTc and ST). However, we are unable to decouple the contribution of the anesthetic agent and the T marker location. Taken together these differences highlight the urgent need for a standardized and agreed annotation schema that accommodates the variable sensitivity of ECG recording methods.
Neuropsychological assessments were conducted at diagnosis, before and after PBT, and 12 months after PBT. Additionally, data on patient outcomes at the last follow-up were collected. This study was approved by the Institutional Review Board (IRB) of Bambino Gesù Children's Hospital and conducted in accordance with the principles outlined in the Helsinki Declaration (RAP-2023-0008). Written informed consent was obtained from all patients or their legal guardians.
Ophthalmologic assessment Visual performance data were gathered during several time points: at the time of diagnosis, after chemotherapy, after PBT, and every six months during follow-up. The assessments conducted encompassed visual acuity (VA), optical coherence tomography (OCT), and visual field (VF) testing. Snellen charts were employed to evaluate VA  (15). The measurement of retinal nerve fiber layer thickness (RNFL) using OCT was utilized to predict visual loss. A reduction of greater than 10% in one or more quadrants or the overall average from the baseline was considered indicative of visual loss  (16). VF testing was conducted using age-appropriate methods and administered by a pediatric ophthalmologist to cooperative patients. The methods employed included a behavioral VF screening test, Humphrey visual field analyzer, semi-automatic static Peritest, or Goldmann kinetic perimetry  (17) (18) (19).
Endocrinological assessment Endocrinological data were obtained at different time points: upon diagnosis, post-chemotherapy, after PBT, and every six months during the follow-up period. Clinical and auxological data were reported. The evaluation of pituitary function involved assessing deficiencies in gonadotropins, thyrotropin, corticotropin, growth hormone (GHD), and diabetes insipidus. Retrospectively, biochemical and hormonal data were collected, including IGF-I, IGFBP-3, FT4, TSH, FSH, LH, testosterone, 17-beta-estradiol, ACTH, cortisol, glucose, serum and urinary electrolyte levels, as well as plasma and urine osmolarity. Hormonal detection was measured using the chemiluminescent immunometric assay (Immulite 2000 XPi, Siemens). The endocrine evaluation encompassed provocative tests to investigate hypothalamicpituitary function, as described previously  (20).
Statistical analysis Data entry and cleaning processes were conducted using Microsoft Excel. Data analyses were performed utilizing SAS 9. 4 version software. Evaluation of lesion volume and stalk diameter took place at diagnosis, during treatments, and during follow-up. Volumetric reduction after chemotherapy, PBT, and at the final follow-up was compared. The Friedman test was employed for analyzing the results. Regarding endocrinological outcomes, patients were categorized into two groups: no hormonal deficits and hormonal deficiency. For ophthalmological outcomes, visual defects were divided into two groups: normal vision and impaired vision. Comparisons of endocrinological and visual outcomes were made at diagnosis, during treatments and follow up. Fisher's exact test, two-sided tailored, was used for the comparison tests, with the alpha risk set at 5%.
In our study, we assessed data related to visual, endocrinological, and neuropsychological aspects for all patients. FIGURE 2 IQ score distribution at diagnosis, pre-and post-PBT and at last follow-up. (57). GH deficiency is the most commonly associated endocrinopathy with radiotherapy, and its incidence is directly proportional to the hypothalamic-pituitary RT dose  (57, 58). Although PBT reduces the risk of endocrine complications, GH deficiency remains the most prevalent new-onset endocrinopathy even after PBT (4). Diabetes insipidus was the most common hormonal abnormality, affecting all children with endocrine abnormalities, and in 9 out of 12 cases, it was accompanied by one or more other endocrinological defects. No new hormonal deficiencies were observed during treatment. GH deficiency was diagnosed in five patients at the last follow-up, consistent with findings in the literature (4).
To decipher this mechanism, we searched for PLS-interacting proteins using a two-hybrid screen. We found that the PLS can interact with p190A itself. Coimmunoprecipitation experiments demonstrated that the PLS interacts with a region in close proximity to the GAP domain. Furthermore, we demonstrated that this interaction is abolished if the PLS harbors cancer-associated mutations: the S866F point mutation and the Δ865-870 deletion. Our results are in favor of defining PLS as an inhibitory domain responsible for masking the p190A functional GAP domain. Thus, p190A could exist in cells under two forms: an inactive closed conformation with a masked GAP domain and an open conformation allowing p190A GAP function. Altogether, our data unveil a new mechanism of p190A regulation. Small GTPases of the Rho family are molecular switches of key signaling pathways involved in cytoskeletal remodeling.
Among the domains tested in the N-terminal part of p190A, only a weak interaction between the PLS with the GBD and the four FF domains (4FF) was observed (Fig. 2C ); no conclusion can be drawn for the two FF domains (2FF) as we were unable to detect 2FF expression. We then generated HA-tagged constructs corresponding to the two regions identified in the two-hybrid Cortactin) or control siRNAs (siCtrl). Cells were plated on glass coverslips, fixed, and stained for F-actin (red), p190A (green), and cortactin (blue). Bar represents 2. 5 μm. E, graphs represent the quantification of the cortactin signal (left-hand) and the ratio of the p190 staining (green) on the F-actin staining (red) (right-hand) at rosettes determined using imageJ software. Values are expressed as the mean ± SD of three independent experiments.
Plasmid constructs The pKH3-p190A-WT containing the rat full-length p190RhoGAP (GenBank under accession no. M94721) was a generous gift from I. Macara (Vanderbilt University). The two truncated p190A constructs (Nter2h and Cter2h) were engineered by PCR using the rat full-length p190RhoGAP as matrix and subcloned into pKH3 expression vector using BamHI and EcoRI restriction sites. Point mutations were generated in the parental vector pKH3-p190A using site-directed mutagenesis with the QuikChange II XL kit according to the manufacturer's protocol (Agilent Technologies). The two mutated PLS constructs (PLS S866F and PLS Δ865-870) were generated by site-directed mutagenesis in the rat GFP-PLS construct. The four mutated Cter constructs (Cter Y1087F, Cter Y1087E, Cter Y1105F, and Cter Y1105E) were generated by site-directed mutagenesis in the rat HA-Cter construct.
Western blot analysis and immunoprecipitation Twenty four hours after transfection, cells were scraped off on ice and homogenized in Tris-HCl lysis buffer (50 mM Tris-HCl, pH 7. 4, 150 mM NaCl, and 0. 1% NP-40) with protease and phosphatase inhibitors. Cell lysates were centrifuged at 10,000g for 10 min to erase cellular debris and nuclei. Lysates were denatured with Laemmli loading buffer containing 2. 5% 2-β-mercaptoethanol for 5 min and analyzed by SDS-PAGE by blotting them onto nitrocellulose membranes. Blots were incubated overnight at 4 C or for 1 h at room temperature with primary antibodies and then incubated with infrared fluorescent dye-conjugated secondary antibodies (Eurobio). Activity was visualized with the Odyssey infrared imaging system (LI-COR Biosciences) and the Chemidoc infrared imaging system (Bio-Rad) and analyzed using ImageJ image analysis software.
Immunofluorescence and confocal imaging Twenty four hours after transfection on glass coverslips, cells were fixed with 4% paraformaldehyde for 10 min at RT and permeabilized with 0. 2% Triton X-100 for 10 min before incubation with various antibodies, as previously described  (30). After staining, coverslips were mounted on slides with Fluoromount G mounting medium. Cells were imaged using an SP5 confocal microscope (Leica Biosystems) using a 63×/ NA 1. 4 Plan Neofluor objective lens and the LAS-AF-Lite 2. 4. 1 acquisition software (Leica Biosystems). To prevent contamination among fluorochromes, each channel was imaged sequentially using the multitrack recording module before merging. Images were processed using LAS-AF-Lite 2. 4. 1 (Leica Biosystems) or ImageJ software (National Institutes of Health).
For the quantification of the invadosome images, signal intensities were measured using imageJ software on images captured with the same laser intensities. Signals of ≥45 invadosome rosettes were quantified for each condition in three independent experiments. For the quantification of the dendritic-like phenotype, around 50 transfected cells in each condition were analyzed through actin staining and their morphology using a Zeiss Axioplan 2 epifluorescence microscope. Scoring was performed, under the microscope, in three independent experiments, by two independent persons, in a blind manner.
Cells were plated on glass coverslips, fixed, and stained for F-actin (red), p190A (green), and cortactin (blue). Bar represents 2. 5 μm. E, graphs represent the quantification of the cortactin signal (left-hand) and the ratio of the p190 staining (green) on the F-actin staining (red) (right-hand) at rosettes determined using imageJ software. Values are expressed as the mean ± SD of three independent experiments. ****p < 0. 0001; ***p < 0. 001 and ns, not significant. GAP, GTPase-activating protein; GBD, GTP-binding domain; p120BD, p120RasGAP-binding domain; PBR, polybasic region; pG1, pseudo-GTPase domain 1; pG2, pseudo-GTPase domain 2; PLS, protrusion localization sequence.
Acknowledgments-We thank  Dr I. G. Macara  ( Vanderbilt University, USA ) for DNA constructs. We are grateful to  Drs C. Perret  ( Cochin Institute, Paris ) and  S. Courtneidge  ( Burham Institute for Medical Research, La Jolla, CA ) for providing us cell lines. We thank  Céline Léon  and  Alexandra Lehmann  ( U1312, Bordeaux, France ) for their help in performing Cortactin silencing experiments. Microscopy was done in the  Bordeaux Imaging Center , a service unit of the  CNRS-INSERM and Bordeaux University , member of the national infrastructure  France BioImaging. This research was funded by  La Fondation pour la Recherche Médicale  (équipe FRM 2018, grant number  DEQ20180839586 ), by  Institut National du Cancer  (grant  PLBIO2014-182 ), and by  La Ligue contre le Cancer (comité de Gironde).
The efficacy and safety of empagliflozin (Jardiance ® ) in HF have been studied in the EMPEROR trials, including two large-scale clinical trials in patients with HF with EF ≤ 40% (EMPEROR-Reduced, NCT03057977)  [11]  and HF with EF > 40% (EMPEROR-Preserved, NCT03057951)  [12]. EMPEROR-Preserved is a phase III, randomized, doubleblind trial including adults with New York Heart Association (NYHA) functional class II-IV chronic heart failure (cHF) and left ventricular ejection fraction (LVEF) of more than 40%. After a screening period, participants from 622 centers in 23 countries were randomly assigned in 1:1 ratio to receive either placebo or empagliflozin (10 mg per day), in addition to SoC. The primary outcome was time to the first event of adjudicated cardiovascular (CV) death or adjudicated hospitalization for heart failure (HHF).