dataesr/scientific-paragraphs-categorization huggingface dataset:
To mitigate recall bias, scholars have argued that phenomena should instead be measured as close to their occurrence as possible. For such purposes, ecological momentary assessment (EMA) methods are particularly valuable  (14) (15) (16). In older forms of research, EMA was either conducted via pen-and-paper diaries or via standalone technical devices. Today, EMA data collection is often facilitated by smartphone-based applications  (17, 18) , which enable patients to provide self-reports on their mental wellbeing or related factors, while in their ecological habitat  (19) (20) (21). Moreover, the use of pop-up notifications on smartphones allows researchers to randomly select the time point of mood reporting during the day  (19) (20) (21). EMA studies have shown that, compared to healthy controls, persons diagnosed with major depressive disorder (MDD) experience, on average, higher variability and higher emotional inertia  (4, 22, 23).
Participants and Procedures For the purposes of this study, data were analyzed from a subsample of the E-COMPARED study. E-COMPARED is a randomized controlled non-inferiority trial that was conducted across eight European countries. The primary aim of the trial was to compare the use of bCBT with to treatment-as-usual for people with MDD, with respect to both clinical benefit and cost-effectiveness. The blended treatment combined individual face-to-face (f-t-f) sessions and web-and smartphone-based components into one treatment protocol  (28). It included a smartphone-based EMA application that enabled the daily monitoring of mood state, cognitions, social interaction, and sleep patterns. Recruitment for the trial took place from February 2015 to December 2017 in routine MHC settings  (26, 27).
In-depth information about recruitment procedures in countries and settings are provided elsewhere  (27). Patients meeting the inclusion criteria (n = 943) were subsequently randomized to either the bCBT (n = 476) or treatment-as-usual (n = 467) condition. For the purposes of this paper, only patients who were randomized to receive bCBT treatment were initially selected, as the treatment-as-usual group was not invited to take part in the smartphone-based EMA. Of this initial group of 476 patients, 152 did not receive bCBT treatment (that is, never attended the first f-t-f session, dropped out after the first f-t-f session, or never logged onto the platform) or did not provide any EMA data. Of the remaining 324 patients, 37 of the patients had insufficient EMA data (data irretrievable or recorded only once or twice during the first week).
This resulted in our final analytic sample of 287 patients. The studies were conducted in accordance with the Declaration of Helsinki and the rules of Good Clinical Practice. Ethical approval for the trial was obtained locally in each country. All the participants provided written informed consent and granted permission to share their anonymized (encrypted and non-identifiable) data across the participating E-COMPARED partners. Detailed descriptions of both the E-COMPARED study design and the web based-platforms can be found elsewhere  (26, 27, 32, 33).
These assess whether a model with K profiles fits the data better than a model with K-1 profiles, whereby a significant p-value supports the more complex model  (44, 45). We then evaluated the classification accuracy of the models that potentially best fitted the data and we compared the prevalence rates of the profiles. Classification accuracy was evaluated in terms of the entropy value of each model  (46)  and the mean posterior probabilities of each profile within the models  (47). Both such values theoretically range from 0 to 1  (46, 47). Although no official cutoff values available, an entropy value of ≥0. 80 and mean posterior probability values of ≥0. 70 for every model within the model are generally considered as being indicative of an adequate classification  (46, 47). The clinical relevance of the models was evaluated by examining the standardized mean scores for the indicators.
DISCUSSION The results of this explorative study in a cross-national sample of MDD patients demonstrated variations in average mood and mood variability, but not in emotional inertia. Assessments were based on data derived from smartphone-based EMA during the first week of bCBT. The analyses revealed four profiles, which we labeled as "very negative and least variable mood", "negative and moderate variable mood", "positive and moderate variable mood", and "negative and high variable mood". The majority of patients fitted the profile "negative and moderate variable mood". In agreement with our previous explorative study  (24) , in which profiles of mood dynamics among a non-clinical sample of depressed persons, profiles emerged here differed in terms of average mood and mood variability, but not in terms of emotional inertia.
Such profile information may also provide therapists with interesting diagnostic information and suggest different treatment pathways, as well as helping to identify psychiatric comorbidity in early stages of treatment. At this juncture, however, further research is needed to provide more robust results before the findings have direct clinical implications. Studies in larger samples and varied settings are needed in order to increase the external validity of our findings. Also, it would be worthwhile to apply machine learning based methods in future studies. For example, artificial intelligence techniques that extract latent variables from a full dataset using autoencoders and subsequently cluster these latent variables. We could compare these findings with our findings and see whether or not the identified profiles of mood dynamics depend on the statistical approach.
Apparatus The apparatus was the same as that in the study of Soret et al. [11]  and is recalled below. An HTC Vive virtual reality headset with an integrated Tobii eye-tracking system was used. The headset has a Dual AMOLED 3. 6 diagonal screen, a resolution of 1080 × 1200 pixels per eye (2160 × 1200 combined), a refresh rate of 90 Hz, and a field of view of 110 • (145 • diagonally). HTC Vive controllers were used for interaction. The eye-tracking system has a gaze data output frequency (binocular) of 120 Hz with an estimated accuracy of 0. 5 •. The eye tracker has a trackable field of view of 110 • (full HTC Vive field of view). The Posner cueing task was developed using the Unity3D game engine supporting C# programming. We also used OpenVR, SteamVR, Tobii eye-tracking plugins, and Tobii Pro SDK.
Data Analysis 2. 5. 1. Dependent Variable We recorded two different eye-response times, Gaze-Initiation and Target-Seen, both starting from the target appearance. Gaze-Initiation corresponds to the moment when the participant leaves the fixation point out of sight, and Target-Seen when the participant gazed at the viewfinder/rearview mirror corresponding to the target position (eye response). We also recorded motor response times, Ammunition-Choice, that corresponds to the moment when the participant presses the grip button after a target's occurrence.
Trials and Analysis The analysis includes 72. 7 ± 9. 3 trials per participant for Gaze-Initiation RTs, 73. 0 ± 10. 0 trials per participant for Target-Seen RTs, and 71. 4 ± 12. 3 trials for Ammunition-Choice. We used the JASP software to perform a three-way repeated-measure analysis of variance (RMANOVA) on the average RTs for each dependent variable (Gaze-Initiation, Target-Seen, and Ammunition-Choice) to observe the effect of our manipulated factors: Predictivity (100%/50%), Modality (visual/auditory), and Target Location (Front/Rear). Another RMANOVA was carried out on the responses' accuracy for Ammunition-Choice with the same experimental factors. Bonferroni correction was used for post hoc comparison.
Data collection was stopped at least 7 months following transplantation and after last possible PET-scan acquisition. Data-points of the locomotor activity acquired on the day of anesthesia for MRI, PET-scan or surgery were excluded from circadian analyses. Presented results include all other data-points, no outliers were excluded. Nine macaque monkeys (Macaca fascicularis, n=9) were used in total for this study. The study was designed such that one third (n=3) were randomly selected as histological controls i. e. never received MPTP injections and, the other two third (n=6) entered the MPTP protocol. Whilst we selected control animals for histological comparison, we designed the study such that each animal would be its own control for clinical, behavioral and functional measures. Figure  1A  displays a schematic representation of the study design and protocol.
Acknowledgments: We acknowledge  Dr. Vincent Leviel  for discussions at different stages of the study. We thank  Frank Lavenne  for PET acquisition;  Didier Le Bars  and  Frédéric Bonnefoi  for radioligand synthesis;  Mélissa Remy ,  Léo Pion  and  Luc Grinand  for histological graft analyses;  Claude Gronfier  for advice during circadian analyses;  Pascale Giroud  for precious help during anesthesia, surgery and perfusion; and  Kenneth Knoblauch  for help in statistical analyses.
Funding: The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Région Rhône-Alpes (C. D, J. V) Fondation de France (E. P, H. M. C, J. V) Fondation Caisse d'Epargne Rhône-Alpes Lyon (C. D, J. V) Rhône-Alpes  cible  11-010869 (H. K ) Fondation Neurodis (C. R. E. W) Cluster Handicap Vieillissement Neurosciences Rhône-Alpes and LabEX CORTEX  :  Agence Nationale de la Recherche   ANR-11 LABX-0042  (H. K, E. P),  P6-2005 IST-1583 (H. K) ,  FP7-2007 ICT-216593 (H. K )  Agence Nationale de la Recherche   ANR-11-BSV4-501  (H. K).
FUNDING This work was funded by  INSERM, CNRS, University of Strasbourg (Unistra)  and  French Ministère Délégué à la Recherche et à l'Enseignement Supérieur (Ph. D. fellowship to FG and VH). We thank the following research programs of excellence for their support:  FHU Neurogenycs ,  French National Research Agency (ANR)  through the  Programme d'Investissement d'Avenir (FG, VH , and A-KB; contract  ANR-17-EURE-0022 , EURIDOL graduate school of pain).
Statistical analysis Flow cytometry data was analysed using FlowJo software (Treestar). Graphs and statistical tests were carried out using Graphpad prism software (Graphpad). Normality of data distribution was analysed by Shapiro-Wilk test. Parametric data were analysed by Welch's t-test, non-parametric data were analysed by Mann-Whitney-U test. Data represent mean ± SEM unless otherwise stated. Statistical significance between groups is indicated as *p<0. 05, **p<0. 01, ***p<0. 001, ****p<0. 0001, n. s = non-significant difference (p>0. 05). Figure Legends.
Neuronal reconstruction and quantitative morphometrical analysis Widefield fluorescent images of MAP2-labeled hiPSC-derived dopaminergic neurons were taken at 20× magnification using a Zeiss Axio Imager Z1 with apotome (Carl Zeiss AG, Germany). The images were stitched using Fiji software and the somatodendritic domains of individual neurons were reconstructed using Neurolucida 360 (Version 2017. 01. 4, Microbrightfield Bioscience, Williston, USA). Only neurons with at least two primary dendrites and at least one dendritic branch point were selected for reconstruction and further analyses. Care was taken to avoid selection of neurons with strong overlap of multiple neurites or neurons present in neuronal clusters for analysis, as these negatively affect the accuracy of tracing in the neurolucida software.
DA Neurons from three individual rounds of differentiation were used for each cell line, and in total 20 neurons per cell line were used for characterization. Sholl analysis  (Sholl, 1953)  was used to determine the dendritic length of the neurons within a series of concentric circles at μm intervals from the soma. All the morphological data were acquired and analyzed blindly to the genotype of the neurons. For the somatodendritic properties and Sholl analysis, the significance was determined by using Wilks' Lambda multivariate analysis of variance (MANOVA) followed by the Bonferroni post-hoc (IBM SPSS Statistics, version 24. 0, IBM, Armonk, USA).
Data was sampled at 10 kHz through either MC-Rack software (6-well MEA) or Multiwell-Screen software (24-well MEA) (MCS GmbH, Reutlingen, Germany). Data analysis from 24-well MEAs was performed off-line by using Multiwell Analyzer (MCS GmbH, Reutlingen, Germany, i. e. software from the 24-well MEA system that allows the extraction of the filtered output data per electrode) and in-house algorithms to average all the data per well as previously described  (Bologna et al. , 2010; Frega et al. , 2017). The extracted parameters encompassed the mean firing rate (MFR, spikes/s) and mean burst rate (MBR, bursts/min). The MFR was computed by averaging the firing rate of each channel, which is averaged for all the active electrodes of the MEA. Spikes were grouped into a burst if at least 4 consecutive spikes were detected with a smaller than 30 milliseconds inter-spike-interval.
All bursts were merged that were less than 65 milliseconds apart. Bursts with a duration of lower than 50 milliseconds were removed from analysis. For 6-well MEA data analysis, spikes and bursts were detected by using the Precise Timing Spike Detection algorithm (PTSD)  (Maccione et al. , 2009)  and the Burst Detection algorithm  (Pasquale et al. , 2010)  embedded in the SpyCode software  (Bologna et al. , 2010). The mean firing rate (spikes/s) of the network was computed by averaging the firing rate of each channel, which is averaged for all the active electrodes (MFR > 0. 1 Hz) of the MEA. The burst was computed as at least 5 spikes in a burst with a maximum inter-spike-interval of 80 milliseconds. The network burst was defined as synchronized bursts that occurs in >50% of the active channels.
The network burst rate (burst/min) was calculated as the amount of network bursts per minute. Statistical analysis was conducted in PRISM (Graphpad PRISM 7. 0, Graphpad Software, San Diego, CA). For drug application on 6-well MEAs, 100 nM Clorgyline (MAOA inhibitor, Sigma) was added to a single well and activity was recorded at 24 h and 6 days post drug application.
The ejection pressure was set to 5 psi/0. 4 bar and injection duration was set to 100 ms. CNQX (5 μM, Tocris, Bristol, United Kingdom) was used to block all AMPAR-mediated currents. Cells were visualized with an Olympus BX51WI upright microscope (Olympus Life Science, PA, USA), equipped with a DAGE-MTI IR-1000E (DAGE-MTI, IN, USA) camera). Activity was recorded using a Digidata 1440A digitizer and a Multiclamp 700B amplifier (Molecular Devices). Sampling rate was set at 20 kHz (voltage measurements) or 10 kHz (current measurements) and a lowpass 1 kHz filter was used during recording. Recordings were not corrected for liquid junction potential (± 10 mV). Series resistance was monitored on-line and cells were discarded if series resistance increased above 1:10 of membrane resistance. Intrinsic electrophysiological properties were analyzed using Clampfit 10.
Statistical analysis Statistical analysis of the data was performed with GraphPad PRISM (GraphPad Software, Inc. , USA). Data is always shown as mean ± SEM. In case data of multiple lines was pooled to increase statistical power, prior to pooling, Student's t-test was performed to confirm that the lines were not significantly different in any of the parameters investigated (P > 0. 05). At least 2 biological replicates (individual clones) and 3 technical replicates (batches of differentiation) were used for all experiments conducted. All data was tested for normality (D'Agostino & Pearson normality test) and the presence of outliers before statistical comparison between genotypes was conducted. A detailed overview of all averaged data can be found in supplementary data tables S4-S9. Mann-Whitney U test, unpaired Student's t-test or one-way ANOVA with Dunnet's correction for multiple-comparisons was used for statistical analysis.
886C > T, p. Q296*  (Brunner et al. , 1993a) ). All patients were known to display either reduced MAOA acitvity or changes in MAOA protein level, and showed elevated serotonin and disturbed monoamine metabolite levels in serum and urine  (Brunner et al. , 1993b; Piton et al. , 2014; Godar et al. , 2016; Palmer et al. , 2016). Recently, reduced MAOA activity in fibroblasts of Brunner syndrome patients, including our patient ME8, has been shown using HPLC  (Peters et al. , 2021). We additionally assessed MAOA and MAOB enzymatic activity in fibroblasts of the control-1 line and all our patient lines. Our data show that MAOA activity is reduced in patient fibroblasts compared to control levels, whilst MAOB activity is similar (Fig. S1A ). All selected clones expressed the pluripotency markers OCT4, TRA-1-81, NANOG, and SSEA4 (Fig.
3b-d ), and control lines showed similar, albeit sparse, activity levels. Since network activity was comparable between Control-1 and Control-2 (Fig. S4a-c ), we pooled these lines for subsequent analysis and statistical quantification. We furthermore detected no difference in neuronal activity between the ME2 and ME8 lines, and our data on synapse density suggest that dysfunction of the FAD domain similarly affects MAOA function in these lines (Fig. S4a-c ). Therefore, we also pooled data from the missense mutation lines ME2 and ME8 for statistical analysis. For each experiment, all lines were measured simultaneously within the same 6-well MEA, and patient line data was normalized to the control values within the same experiment. Control networks mainly showed sporadic random spiking activity (Fig.
Correction of the ME8 missense mutation also resulted in the normalization of the NMDA-induced NMDAR-mediated current transfer (Fig. 5e , f, Fig. S7f ). Finally, we found that restoration of MAOA function normalized activity on the MEA to control values (Fig. 5g , Fig. S5g, h ). For each experiment, all lines were measured simultaneously within the same 24-well MEA, and the ME8 and CRISPR-ME8 data was normalized to the control values within the same experiment. Whereas ME8 DA neurons showed increased network activity, this increase was absent in ME8-CRISPR DA neuronal networks as the mean firing rate (Fig. 5h ) and mean burst rate (Fig. 5i ) were similar to control levels. Therefore, we conclude that rescue of the p. C266F MAOA mutation results in normalization of GRIN2A and GRIN2B expression, which is reflected by a restoration of neuronal network activity to control values.
Discussion Monoamine aberration through mutations that reduce MAOA function results in Brunner syndrome. Although the syndrome has been described almost three decades ago, insight into the molecular mechanisms of the disorder is still lacking. Here, we developed a hiPSC-derived DA neuron model to assess the molecular and cellular phenotypes underlying brain dysfunction in Brunner syndrome. Until now, reports on four families have been published in which individuals have Brunner syndrome  (Brunner et al. , 1993a; Brunner et al. , 1993b; Piton et al. , 2014; Palmer et al. , 2016)  (and more cases are present in the Clinvar database). We were able to include individuals from three of these families into our study. hiPSC-derived DA neurons generated from individuals with Brunner syndrome showed reduced synapse density but increased network activity.
Acknowledgements The authors would like to acknowledge support from the  Netherlands Organization for Scientific Research (NWO) Vici Innovation Program  (grant  016-130-669  to BF), from the  European Community 's  Seventh Framework Programme  ( FP7/2007-2013)  under grant agreement no. 602805  (Aggressotype), and from the  European Community 's  Horizon 2020 Programme  ( H2020/2014-2020 ) under grant agreements no. 667302  (CoCA) and no. 728018  ( Eat2beNICE ). Additional support is received from the  Dutch National Science Agenda  for the  NeurolabNL  project (grant  40017602 ) the  NWO  grant  012. 200. 001  and  91217055  (to N. N. K. ),  SFARI  grant  610264  (to N. N. K),  ERA-NET NEURON DECODE! grant  ( NWO) 013. 18. 001  (to N. N⋅K) and  ERA-NET   NEURON-102 SYNSCHIZ grant (NWO) 013-17-003.
24 Thus, we next tested whether the retention of Whi3 mnem in the mother cells requires the compartmentalization of ER membranes. We treated the cells expressing Whi3 fused to 3 super-folding GFP in tandem (Whi3-3GFP) with pheromone for 5 h and released them in a pheromone-free medium for 1. 5 h to allow the mother cells to produce a bud. The localization of Whi3-3GFP was analyzed in wild-type and barrier-defective cells. Most wild-type, bud6D, sur2D, and bud1D mutant mother cells contained a super-assembly of Whi3 mnem (N > 122 cells). However, while only 24. 00% ± 6. 22% of the wild-type buds had a super-assembly, 62. 24% ± 3. 85% of the bud6D, 64. 01% ± 3. 65% of the sur2D, and 65. 26% ± 4. 15% of the bud1D mutant buds already had at least one (Figures  2A  and 2B ). These data are consistent with a role for diffusion barriers in the retention of Whi3 mnem in the mother cells after escape from pheromone arrest or in the retention of some Whi3 super-assembly regulator.
Conversely, adding a second copy of WHI3 increased the frequency of CE formation 2. 4-fold (Figure  5I , p = 0. 016). However, the CE trait was not solely due to the conversion of Whi3 into a prion because nearly half of the CE clones did not form small cells and did not contain an increased frequency of Whi3 aggregates. In addition, the WHI3-DpQ allele did not fully abolish CE formation (Figure  5B ) and deleting the WHI3 gene in CE did not cure them. Our data suggest that the CE trait is due to the conversion of at least two epigenetic switches, one that involves Whi3 inactivation through its conversion to a propagating form, and a second one, possibly another prion. To test whether the inactivation of Whi3 promotes the formation of the CE trait, we measured the frequency of CE in whi3D mutant strains.
ACKNOWLEDGMENTS We would like to thank the  Thorpe group  for their help with the GFP/GBP experiments and feedback. We would also like to thank the whole  McMurray group  for their constructive feedback posted on Pubpeer. This work was supported by a  Biotechnology and Biological Sciences Research Council  project grant ( BB/S001204/1 ) to F. C. and H. P. O. ; QMUL to F. C. , Y. L. , and H. P. O. ; MUSE funding to F. C. ; the  Academy of Finland  ( 317038 ) and  Sigrid Jus elius Foundation  to J. S. ; and the  European Research Council  ( BarrAge 250278 ) and  ETH Zurich  to D. H. , J. S. , F. C. , and Y. B.
Data Analysis Infants' performance (success/failure in each condition) was coded from the video recordings. All videos were double coded by an independent observer to assess interobserver reliability. Unweighted Cohen's kappa showed excellent agreement between the observers (κ =. 92, p =. 0). All analyses were performed using R Software (version 3. 2. 1) for Mac OS X. Nonparametric analyses with Bonferroni corrections were used to investigate differences in the performance between groups and conditions. A factorial analysis of mixed data (FAMD) was performed on the questionnaire data  (Pagès, 2014) , in order to get an overview of the potential similarities between infants who most succeeded in the experiment. From the eight questions contained in the questionnaire (provided in the Supplementary Material [available online]), we derived the following eight variables: two quantitative variables about the ages (in months) at which infants were first fed with a spoon and first used a spoon for self-feeding; and six qualitative variables about the frequency of use of a spoon at the time of the test (rarely, about 25%, more than 50%, and about 100%), the social context during feeding times (alone, with younger siblings, and with adults/older siblings), the similarity between a spoon at home and the spoon used for the experiment (not similar vs.