Resultados de investigación

Table S1: Descriptive statistics of included samples. Abbreviations: PANSS (Positive and Negative Symptoms Scale), SAPS (Scale for the Assessment of Positive Symptoms), SANS (Scale for the Assessment of Negative Symptoms). Table S2: Mean and standard deviation BMI for each group, and overall, at each data collection site. Inter-site differences in outcomes based on BMI or other factors were controlled in all models. Table S3: Image acquisition parameters and software versions used at each site Table S4: Number of participants removed from analysis in each region based on poor data quality or unreliable segmentation (cortical thickness) Table S5: Number of participants removed from analysis in each region based on poor data quality or unreliable segmentation (cortical surface area) Table S6: Number of participants removed from analysis in each region based on poor data quality or unreliable segmentation (cortical surface area) Table S7 Interactions between diagnosis effect and BMI in predicting cortical thickness for each region, using FDR-adjusted p-values Table S8 Interactions between diagnosis effect and BMI in predicting cortical surface area for each region, using FDR-adjusted p-values Table S9 Interactions between diagnosis effect and BMI in predicting subcortical volume for each region, using FDR-adjusted p-values Table S10 Significance of the nonlinearity of BMI effects (BMI quartile by within-quartile BMI interaction) in predicting cortical thickness. FDR-adjusted p-values are shown. Table S11 Significance of the nonlinearity of BMI effects (BMI quartile by within-quartile BMI interaction) in predicting cortical surface area. FDR-adjusted p-values are shown. Table S12 Significance of the nonlinearity of BMI effects (BMI quartile by within-quartile BMI interaction) in predicting cortical thickness. FDR-adjusted p-values are shown. Table S13 Among participants with schizophrenia taking atypical antipsychotics at the time of scanning, the effects of BMI on cortical thickness when modeled alone, and the partial effects of BMI and antipsychotic medication dose on cortical thickness (chlorpromazine equivalent, in mg). Effect sizes (part r) are shown with FDR-adjusted p-values. Table S14 Among participants with schizophrenia taking atypical antipsychotics at the time of scanning, the effects of BMI on cortical surface area when modeled alone, and the partial effects of BMI and antipsychotic medication dose on cortical surface area (chlorpromazine equivalent, in mg). Effect sizes (part r) are shown with FDR-adjusted p-values. Table S15 Among participants with schizophrenia taking atypical antipsychotics at the time of scanning, the effects of BMI on subcortical volume when modeled alone, and the partial effects of BMI and antipsychotic medication dose on subcortical volume (chlorpromazine equivalent, in mg). Effect sizes (part r) are shown with FDR-adjusted p-values. Significance is shown with asterisks (*, α=0.05). Figure S1: BMI distribution of all participants Figure S2 The interaction between BMI categories and within-category relative BMI in predicting rostral anterior cingulate gyrus thickness, demonstrating equivalent slopes at all BMI ranges, for an approximately linear relationship. Supplemental Methods: Description of fixed and random effects in each model., Peer reviewed

Supplementary Fig. 1. Adjustment of the pH of the solutions used in Figs. 2 and 3. Supplementary Fig. 2. Pulsed-field gelelectrophoretic analyses of genomic DNA after PA treatment of the permeabilized nuclei. Supplementary Fig 3. Spermidine binding to DNA demonstrated by EBr displacement in agarose embedded nuclear halos. Supplementary Fig 4. Comparison of PA binding of different topological forms of plasmid DNA. Supplementary Figure 5. CellMiner analyses based on the NCI60 cell line panel, using CellMinerCDB. Supplementary Fig 6. CellMiner analyses based on the NCI60 cell line panel, using CellMinerCDB. Supplementary Figure 7. CellMiner analyses based on the NCI60 panel, using CellMinerCDB. Suppl. Figure 8. CellMiner analyses based on the NCI60 panel, using CellMinerCDB. Supplementary Figure 9. CellMiner analyses based on the NCI60 panel, using CellMinerCDB., Peer reviewed

32 pages. -- Supporting Text: A. Reactions mapping; B. Mathematical details of the Expectation Propagation algorithm; 1. Modeling the posterior probabilities of the fluxes given experimental evidence; 2. Pre-process of the fluxes; 3. Determining a and d, fixed c and y; 4. Determining c and , given a and d; 5. Implementation details; C. Projections of the coefficients along individual flux directions; D. Dimensionality reduction; 1. Reconstruction of the coefficients; E. Accessing the most informative fluxes; 1. Compression of the inferred coefficients: mathematical details; F. Fitting averages using HR-based Boltzmann machine learning. -- Supplementary Figures: G. Fitting quality; H. Correlation matrices; I. Probability densities of the non-measured fluxes; J. Notation used for the biomass production rate, Peer reviewed

Supplemental tables (24). Supplemental note 1, 2, 3. Supplemental Figure 1., Peer reviewed

21 pages. -- Table S1-S15 Observed rotational transition frequencies of the FA conformers. -- Table S16-S19 Structural parameters if II from different analyse. -- Table S20 NBO analysis of the detected cis-COOH conformers of FA and THFA. -- Point S1 The equations used for De and D0. -- Table S21-S25 Observed rotational transition frequencies of the FA dimer. -- Figure S1 Geometries of the I-III and II-III binary conformers., Peer reviewed

6 pages. -- Table S1. Measured transition frequencies of 13C1 TFE isotopologue. -- Table S2. Measured transition frequencies of 13C2 TFE isotopologue. -- Table S3. Experimental Kraitchman’s coordinates (in Å) of g CF3CH2OH and PFPTg in their respective principal inertia axis systems. -- Table S4. The r0, rs and re of the C-C distance. The values of gauche conformer of ethanol are added for the comparison. -- Table S5. Measured transition frequencies of PFP-OD isotopologue., Peer reviewed

El presente trabajo ha sido financiado por Chiesi., Peer reviewed

The dataset includes additional data for the journal paper “Shock cooling of a red-supergiant supernova at redshift 3 in lensed images” by W. Chen et al., 2022. As described in the paper, these data include the MMT spectroscopic data, the HST coaddition and image differencing data, the GALFIT scripts and resulting models, the HST photometry of the SN host galaxy, the lens model, the SN light curve fitting script and resulting MCMC data, and plots of distributions of the model parameters and the best-fit light curves., Peer reviewed

Methods to induce analgesia and anesthesia have been used in 71 crustaceans for research pur-poses, handling, transport or stunning. A non-systematic literature search was carried out crus-tacean anesthetic methods. We prepared this on-line tool based on datasette (https://datasette.io/), a no-code open source solution for simple web-based database frontends that allows exploring and publishing data by method, analgesic/anesthetic, species, life stage or sex., as well as other data including environmental conditions (temperature, salinity, light), way of administration, dosage, and induction and recovery times. Use of this tool for selecting anesthetics in crustaceans is free but we ask that you please cite the following publication that explains the tool in any published outputs: Rotllant, G.; Llonch, P.; García del Arco, J.A.; Chic, Ò.; Flecknell, P.; Sneddon, L.U. Methods to Induce Analgesia and Anesthesia in Crustaceans: A Supportive Decision Tool. Biology 2023, 12, 387. https://doi.org/10.3390/biology12030387, With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), Peer reviewed

Table S1. Search strategy. Table S2. AMSTAR-2 Checklist., Peer reviewed