Miracle-dz/UniFAR-FTUs huggingface dataset:
Real-world use of orphan medicinal products (OMPs) in rare disease (RD) patients: A population-based registry study

Background: Despite calls for the use of real-world data, the rare diseases (RD) treatment landscape suffers from a scarcity of data referred to orphan medicinal products (OMP) use at the population level. Objectives: We aim to describe the characteristics and patterns of utilization of OMP in a sizable group of RD patients globally monitored by an area-based rare diseases registry located in the Veneto region, Italy, during a 3-year period (1 January 2019 to 31 December 2021). Methods: A list of OMP (n = 60) was assembled for study purposes, according to extensive criteria with regard to the status of orphan designation and of national reimbursement decisions. Results: OMP prescriptions involved 1,010 patients, corresponding to the 2.3% of all the patients monitored by the RD registry. Nearly one out of five (22.8%) was a pediatric patient at the time of the first prescription. OMP use interested a limited proportion (17.5%) of diseases approaching the rarity threshold, having a prevalence of less than five per 10,000, while individuals affected by these more common rare conditions represented 49% of all the patients receiving an OMP prescription. A clustering effect of OMP use was observed in selected groups of diseases, mainly, neurological, hematological, and hereditary metabolic ones. Medication plans including an OMP show in the 45.9% of the cases a high level of complexity, both in terms of nature and number of co-prescribed treatments. Off-label use interested 15.3% (n = 155) of all the RD patients with at least an OMP prescription during the study period. Conclusion: Data collected in a real-world setting through population-based registries globally monitoring RD patients, including related medication plans, have the potential to identify which diseases, and thus patients, have less benefit from the advent of OMP so far. Furthermore, in the rapidly evolving RD therapeutic landscape, they can help understand which therapeutic areas are most in need of investment to address existing unmet care needs.
Impaired ankle inversion proprioception during walking is associated with fear of falling in older adults

Background Ankle proprioception plays a critical role in lower limb movement control. However, the relationship between ankle proprioception and fear of falling (FOF) in older people is still unclear. Objective (1) This study aims to develop a new device for measuring ankle inversion proprioceptive discrimination sensitivity during walking, i.e., the Ankle Inversion Discrimination Apparatus–Walking (AIDAW), and assess the test–retest reliability of the AIDAW in both young and older adults; (2) to evaluate the discriminant validity of the measure by comparing ankle proprioception during walking between the two groups; and (3) to explore convergent validity by determining to what extent the AIDAW proprioceptive scores correlate with Fall Efficacy Scale-International (FES-I) scores. Materials and methods The AIDAW was purpose-built to test ankle inversion proprioceptive discrimination sensitivity during walking. The area under the receiver operating curve (AUC) was calculated as the proprioceptive discrimination score. In total, 54 adults volunteered. Test–retest reliability was evaluated in 12 young and 12 older adults, and another 15 young and 15 older adults completed the comparison study. FOF was assessed by using the FES-I. Results The test–retest reliability intraclass correlation coefficient ICC (3,1) value for the whole group was 0.76 (95% CI: 0.52–0.89). The ICC values of the young and older groups were 0.81 (95% CI: 0.46–0.94) and 0.71 (95% CI: 0.26–0.91), respectively. The Minimal Detectable Change with 90% confidence (MDC90) values for the young and older groups were 0.03 and 0.11, respectively. There was a significant difference between the AIDAW proprioceptive sensitivity scores for the young and older groups (0.78 ± 0.04 vs. 0.72 ± 0.08, F = 5.06, p = 0.033). Spearman’s correlation analysis showed that the FES-I scores were significantly and negatively correlated with the AIDAW scores (rho = −0.61, p = 0.015), with higher FOF associated with worse ankle proprioception. Conclusion The AIDAW is a reliable and valid device for measuring ankle proprioception during walking in both young and older adults. Ankle inversion proprioceptive discrimination sensitivity during walking was found to be impaired in the elderly compared to young adults. This impairment was found to be strongly associated with FOF, suggesting that assessment and intervention for ankle proprioception in this population are needed to reduce the risk of falls.
What constitutes a fulfilled life? A mixed methods study on lay perspectives across the lifespan

Recently, we initiated a new research line on fulfillment in life by developing a conceptual framework and a self-report measure. To enhance conceptual clarity and complement theoretical considerations and empirical findings, we investigated lay conceptions of a fulfilled life in German-speaking participants at different life stages. First, we selected a qualitative approach using an open-ended question asking participants to describe a fulfilled life. Second, for a more comprehensive understanding, quantitative data were collected about the relevance of sources in providing fulfillment and ratings on a fulfilling life in the present and a fulfilled life in retrospect. Qualitative content analysis was used to assess the responses to the open-ended question. One-fifth of the data was double coded, and intercoder reliability was high (Kappa = 0.89). Responses comprised a variety of descriptions, and we grouped them into seven themes, three of which overlapped with the prior conceptualization, namely the core elements of (a) general description, (b) cognitive appraisals, and (c) affective appraisals. Cognitive evaluations related to intrapersonal aspects, particularly having lived life fully, attained personally significant goals, and developed oneself, as well as interpersonal, generative aspects, such as having made a contribution and been able to leave something of value. These categories are mostly in line with what the Fulfilled Life Scale (FLS) measures. Further themes referred to correlates—including (d) sources—and antecedents, including (e) resources, (f) personal characteristics, and (g) quality of life, all considered worthy to be the subject of empirical investigation but which were not included in the conceptual model. Qualitative and quantitative results suggest that individuals derive fulfillment from different sources. Fulfillment from a profession and having a life task was strongly associated with longer-term fulfillment. Only a few age and sex differences were found. The overarching framework developed from the qualitative results can stimulate further investigation. Our findings underscore that a fulfilled life as a distinct construct should be measured directly rather than via a proxy. Insights into the constituents, sources, and antecedents of a fulfilled life can inform practice to promote a life well lived.
Examining racial and ethnic disparities in adult emergency department patient visits for concussion in the United States

Background Racial and ethnic differences in emergency department (ED) visits have been reported among adolescent patients but are unsubstantiated among adults. Therefore, our purpose in this study was to examine the relationship between race/ethnicity and adult ED visits for concussions, their injury mechanisms, and computed tomography (CT) scan use among a nationally representative sample. Methods We used the National Hospital Ambulatory Medical Care Survey database from 2010–2015 to examine 63,725 adult (20–45 years old) patient visits, representing an estimated 310.6 million visits presented to EDs. Of these visits, 884 (4.5 million national estimate) were diagnosed with a concussion. Visit records detailed patient information (age, sex, race/ethnicity, geographic region, primary payment type), ED visit diagnoses, injury mechanism (sport, motor vehicle, fall, struck by or against, “other”), and head CT scan use. The primary independent variable was race/ethnicity (non-Hispanic Asian, non-Hispanic Black or African American, Hispanic/Latinx, non-Hispanic multiracial or another, and non-Hispanic White). We used multivariable logistic and multinomial regression models with complex survey sampling design weighting to examine the relationship between concussion ED visits, injury mechanisms, and CT scan use separately by race/ethnicity while accounting for covariates. Results There were no associations between race/ethnicity and concussion diagnosis among adult ED visits after accounting for covariates. Relative to sports-related injuries, non-Hispanic Black or African American patient visits were associated with a motor vehicle (OR = 2.69, 95% CI: 1.06–6.86) and “other” injury mechanism (OR = 4.58, 95% CI: 1.34–15.69) compared to non-Hispanic White patients. Relative to sports-related injuries, non-Hispanic Asian, multiracial, or patients of another race had decreased odds of falls (OR = 0.20, 95% CI: 0.04–0.91) and “other” injuries (OR = 0.09, 95% CI: 0.01–0.55) compared to non-Hispanic White patients. The odds of a CT scan being performed were significantly lower among Hispanic/Latinx patient visits relative to non-Hispanic White patients (OR = 0.52, 95% CI: 0.30–0.91), while no other race/ethnicity comparisons differed. Conclusion Our findings indicate that the overarching concussion ED visit likelihood may not differ by race/ethnicity in adults, but the underlying mechanism causing the concussion and receiving a CT scan demonstrates considerable differences. Prospective future research is warranted to comprehensively understand and intervene in the complex, multi-level race/ethnicity relationships related to concussion health care to ensure equitable patient treatment.
MicroRNAs with non-additive expression in the ovary of hybrid hens target genes enriched in key reproductive pathways that may influence heterosis for egg laying traits

Heterosis has been extensively exploited in chicken breeding to improve laying traits in commercial hybrid stock. However, the molecular mechanisms underlying it remains elusive. This study characterizes the miRNAome in the pre-hierarchical follicles of purebred and hybrid laying hens, and investigate the functions of miRNAs with non-additive expression in the pre-hierarchical follicles as they modulate heterosis for egg number and clutch size. To achieve that aim, White Leghorn and Rhode Island Red chicken lines were reciprocally crossed to generate hybrids. The crossbreds demonstrated heterosis for egg number and clutch size, and pre-hierarchical follicles from 4 birds of each genotype were collected at 53 weeks of age. Mode of miRNA expression was characterized after miRNA sequencing. A total of 50 miRNAs including 30 novel ones, were found to exhibit non-additive expression. Dominance was the predominant mode of expression exhibited by majority of the miRNAs. Functional analysis of target genes of the known miRNAs with non-additive expression revealed Gene Ontology terms related to regulation of transcription, metabolic processes and gene expression. KEGG and REACTOME pathways including hedgehog, cellular senescence, wnt, TGF-β, progesterone-mediated oocyte maturation, oocyte meiosis, GnRH signaling, signal transduction and generic transcription, which can be linked to primordial follicle activation, growth and ovulation, were significantly enriched by target genes of miRNAs with non-additive expression. Majority of the genes enriched in these biological pathways were targeted by gga-miR-19a, gga-miR-19b, gga-miR-375, gga-miR-135a, and gga-miR-7 and 7b, thus, revealing their synergistic roles in enhancing processes that could influence heterosis for egg number and clutch size in hybrid hens.
Band 3–mediated Plasmodium vivax invasion is associated with transcriptional variation in PvTRAg genes

The Plasmodium vivax reticulocyte invasion process is still poorly understood, with only a few receptor-ligand interactions identified to date. Individuals with the Southeast Asian ovalocytosis (SAO) phenotype have a deletion in the band 3 protein on the surface of erythrocytes, and are reported to have a lower incidence of clinical P. vivax malaria. Based on this observation, band 3 has been put forward as a receptor for P. vivax invasion, although direct proof is still lacking. In this study, we combined functional ex vivo invasion assays and transcriptome sequencing to uncover a band 3–mediated invasion pathway in P. vivax and potential band 3 ligands. Invasion by P. vivax field isolates was 67%-71% lower in SAO reticulocytes compared with non-SAO reticulocytes. Reticulocyte invasion was decreased by 40% and 27%-31% when blocking with an anti-band 3 polyclonal antibody and a PvTRAg38 peptide, respectively. To identify new band 3 receptor candidates, we mRNA-sequenced schizont-stage isolates used in the invasion assays, and observed high transcriptional variability in multigene and invasion-related families. Transcriptomes of isolates with low or high dependency on band 3 for invasion were compared by differential expression analysis, which produced a list of band 3 ligand candidates with high representation of PvTRAg genes. Our ex vivo invasion assays have demonstrated that band 3 is a P. vivax invasion receptor and confirm previous in vitro studies showing binding between PvTRAg38 and band 3, although the lower and variable inhibition levels observed suggest the involvement of other ligands. By coupling transcriptomes and invasion phenotypes from the same isolates, we identified a list of band 3 ligand candidates, of which the overrepresented PvTRAg genes are the most promising for future research.
Introducing EM-FT for Manipuri-English Neural Machine Translation

This paper introduces a pretrained word embedding for Manipuri, a low-resourced Indian language. The pretrained word embedding based on FastText is capable of handling the highly agglutinating language Manipuri (mni). We then perform machine translation (MT) experiments using neural network (NN) models. In this paper, we confirm the following observations. Firstly, the reported BLEU score of the Transformer architecture with FastText word embedding model EM-FT performs better than without in all the NMT experiments. Secondly, we observe that adding more training data from a different domain of the test data negatively impacts translation accuracy. The resources reported in this paper are made available in the ELRA catalogue to help the low-resourced languages community with MT/NLP tasks.
PADDLe: a Platform to Identify Complex Words for Learners of French as a Foreign Language (FFL)

Annotations of word difficulty by readers provide invaluable insights into lexical complexity. Yet, there is currently a paucity of tools allowing researchers to gather such annotations in an adaptable and simple manner. This article presents PADDLe, an online platform aiming to fill that gap and designed to encourage best practices when collecting difficulty judgements. Studies crafted using the tool ask users to provide a selection of demographic information, then to annotate a certain number of texts and answer multiple-choice comprehension questions after each text. Researchers are encouraged to use a multi-level annotation scheme, to avoid the drawbacks of binary complexity annotations. Once a study is launched, its results are summarised in a visual representation accessible both to researchers and teachers, and can be downloaded in . csv format. Some findings of a pilot study designed with the tool are also provided in the article, to give an idea of the types of research questions it allows to answer.
SyntAct: A Synthesized Database of Basic Emotions

Speech emotion recognition is in the focus of research since several decades and has many applications. One problem is sparse data for supervised learning. One way to tackle this problem is the synthesis of data with emotion simulating speech synthesis approaches. We present a synthesized database of five basic emotions and neutral expression based on rule based manipulation for a diphone synthesizer which we release to the public. The database has been validated in several machine learning experiments as a training set to detect emotional expression from natural speech data. The scripts to generate such a database have been made open source and could be used to aid speech emotion recognition for a low resourced language, as MBROLA supports 35 languages
A 408 MHz all-sky continuum survey. II. The atlas of contour maps.

We present an atlas of the radio continuum brightness of the whole sky at a frequency of 408 MHz. A set of both α, δ as well as l, b maps is shown. The angular resolution is 0°. 85. The atlas combines data from four different surveys using the Jodrell Bank MkI, Bonn 100 meter, Parkes 64 meter and Jodrell Bank MkIA telescopes.
Phonetics of Negative Headshake in Russian Sign Language: A Small-Scale Corpus Study

We analyzed negative headshake found in the online corpus of Russian Sign Language. We found that negative headshake can co-occur with negative manual signs, although most of these signs are not accompanied by it. We applied OpenFace, a Computer Vision toolkit, to extract head rotation measurements from video recordings, and analyzed the headshake in terms of the number of peaks (turns), the amplitude of the turns, and their frequency. We find that such basic phonetic measurements of headshake can be extracted using a combination of manual annotation and Computer Vision, and can be further used in comparative research across constructions and sign languages.
The Viability of Best-worst Scaling and Categorical Data Label Annotation Tasks in Detecting Implicit Bias

Annotating workplace bias in text is a noisy and subjective task. In encoding the inherently continuous nature of bias, aggregated binary classifications do not suffice. Best-worst scaling (BWS) offers a framework to obtain real-valued scores through a series of comparative evaluations, but it is often impractical to deploy to traditional annotation pipelines within industry. We present analyses of a small-scale bias dataset, jointly annotated with categorical annotations and BWS annotations. We show that there is a strong correlation between observed agreement and BWS score (Spearman’s r=0.72). We identify several shortcomings of BWS relative to traditional categorical annotation: (1) When compared to categorical annotation, we estimate BWS takes approximately 4.5x longer to complete; (2) BWS does not scale well to large annotation tasks with sparse target phenomena; (3) The high correlation between BWS and the traditional task shows that the benefits of BWS can be recovered from a simple categorically annotated, non-aggregated dataset.
Ara-Women-Hate: An Annotated Corpus Dedicated to Hate Speech Detection against Women in the Arabic Community

In this paper, an approach for hate speech detection against women in the Arabic community on social media (e.g. Youtube) is proposed. In the literature, similar works have been presented for other languages such as English. However, to the best of our knowledge, not much work has been conducted in the Arabic language. A new hate speech corpus (Arabic_fr_en) is developed using three different annotators. For corpus validation, three different machine learning algorithms are used, including deep Convolutional Neural Network (CNN), long short-term memory (LSTM) network and Bi-directional LSTM (Bi-LSTM) network. Simulation results demonstrate the best performa
The other side of Bulge Formation in a Lambda-CDM cosmology: Bulgeless Galaxies in the Local Universe

We study the physical properties, formation histories, and environment of galaxies without a significant "classical" spheroidal component, as predicted by semi-analytical models of galaxy formation and evolution. This work is complementary to the analysis presented in De Lucia et al., (2011), where we focus on the relative contribution of various physical mechanisms responsible for bulge assembly in a Lambda-CDM cosmology. We find that the fraction of bulgeless galaxies is a strong decreasing function of stellar mass: they represent a negligible fraction of the galaxy population with M* > 10^12 Msun, but dominate at M* < 10^10 Msun. We find a clear dichotomy in this galaxy population, between central galaxies of low-mass dark matter haloes, and satellite galaxies in massive groups/clusters. We show that bulgeless galaxies are relatively young systems, that assemble most of their mass at low-redshift, but they can also host very old stellar populations. Since galaxy-galaxy mergers are assumed to lead to the formation of a spheroidal component, in our models these galaxies form preferentially in low-mass haloes that host a small number of satellites galaxies. We show that the adopted modelling for galaxy mergers represents a key ingredient in determining the actual number of bulgeless galaxies. Our results show that these galaxies are not a rare population in theoretical models: at z~0, galaxies with no classical bulge (but often including galaxies with the equivalent of pseudo-bulges) account for up to 14% of the galaxies with 10^11 < M*/Msun < 10^12.
Discovering Financial Hypernyms by Prompting Masked Language Models

With the rising popularity of Transformer-based language models, several studies have tried to exploit their masked language modeling capabilities to automatically extract relational linguistic knowledge, although this kind of research has rarely investigated semantic relations in specialized domains. The present study aims at testing a general-domain and a domain-adapted Transformer models on two datasets of financial term-hypernym pairs using the prompt methodology. Our results show that the differences of prompts impact critically on models’ performance, and that domain adaptation on financial text generally improves the capacity of the models to associate the target terms with the right hypernyms, although the more successful models are those retaining a general-domain vocabulary.
An Analysis of Abusive Language Data Collected through a Game with a Purpose

In this work we present an analysis of abusive language annotations collected through a 3D video game. With this approach, we are able to involve in the annotation teenagers, i.e. typical targets of cyberbullying, whose data are usually not available for research purposes. Using the game in the framework of educational activities to empower teenagers against online abuse we are able to obtain insights into how teenagers communicate, and what kind of messages they consider more offensive. While players produced interesting annotations and the distributions of classes between players and experts are similar, we obtained a significant number of mismatching judgements between experts and players.
The Post-Stroke Speech Transcription (PSST) Challenge

We present the outcome of the Post-Stroke Speech Transcription (PSST) challenge. For the challenge, we prepared a new data resource of responses to two confrontation naming tests found in AphasiaBank, extracting audio and adding new phonemic transcripts for each response. The challenge consisted of two tasks. Task A asked challengers to build an automatic speech recognizer (ASR) for phonemic transcription of the PSST samples, evaluated in terms of phoneme error rate (PER) as well as a finer-grained metric derived from phonological feature theory, feature error rate (FER). The best model had a 9.9% FER / 20.0% PER, improving on our baseline by a relative 18% and 24%, respectively. Task B approximated a downstream assessment task, asking challengers to identify whether each recording contained a correctly pronounced target word. Challengers were unable to improve on the baseline algorithm; however, using this algorithm with the improved transcripts from Task A resulted in 92.8% accuracy / 0.921 F1, a relative improvement of 2.8% and 3.3%, respectively.