Miracle-dz/UniFAR-FTUs huggingface dataset:
The relations between different components of intolerance of uncertainty and symptoms of depression during the COVID-19 pandemic: A network analysis

Background The relations between depression and intolerance of uncertainty (IU) have been extensively investigated during the COVID-19 pandemic. However, there is a lack of understanding on how each component of IU may differentially affect depression symptoms and vice versa. The current study used a network approach to reveal the component-to-symptom interplay between IU and depression and identify intervention targets for depression during the COVID-19 pandemic. Methods A total of 624 college students participated in the current study. An IU-Depression network was estimated using items from the 12-item Intolerance of Uncertainty Scale and the Patient Health Questionnaire-9. We examined the network structure, node centrality, and node bridge centrality to identify component-to-symptom pathways, central nodes, and bridge nodes within the IU-Depression network. Results Several distinct pathways (e.g., “Frustration when facing uncertainty” and “Feelings of worthlessness”) emerged between IU and Depression. “Fatigue” and “Frustration when facing uncertainty” were identified as the central nodes in the estimated network. “Frustration when facing uncertainty,” “Psychomotor agitation/retardation,” and “Depressed or sad mood” were identified as bridging nodes between the IU and Depression communities. Conclusion By delineating specific pathways between IU and depression and highlighting the influential role of “Frustration when facing uncertainty” in maintaining the IU-Depression co-occurrence, current findings may inform targeted prevention and interventions for depression during the COVID-19 pandemic.
Molecular epidemiology of tuberculosis in the Somali region, eastern Ethiopia

Background Tuberculosis (TB) is one of the leading causes of morbidity and mortality in low-income countries like Ethiopia. However, because of the limited laboratory infrastructure there is a shortage of comprehensive data on the genotypes of clinical isolates of Mycobacterium tuberculosis (M. tuberculosis) complex (MTBC) in peripheral regions of Ethiopia. The objective of this study was to characterize MTBC isolates in the Somali region of eastern Ethiopia. Methods A cross-sectional study was conducted in three health institutions between October 2018 and December 2019 in the capital of Somali region. A total of 323 MTBC isolates (249 from pulmonary TB and 74 from extrapulmonary TB) were analyzed using regions of difference 9 (RD 9)-based polymerase chain reaction (PCR) and spoligotyping. Results Of the 323 MTBC isolates, 99.7% (95% CI: 99.1–100%) were M. tuberculosis while the remaining one isolate was M. bovis based on RD 9-based PCR. Spoligotyping identified 71 spoligotype patterns; 61 shared types and 10 orphans. A majority of the isolates were grouped in shared types while the remaining grouped in orphans. The M. tuberculosis lineages identified in this study were lineage 1, 2, 3, 4, and 7 with the percentages of 7.4, 2.2, 28.2, 60.4, and 0.6%, respectively. Most (87.9%) of the isolates were classified in clustered spoligotypes while the remaining 12.1% isolates were singletons. The predominant clustered spoligotypes identified were SIT 149, SIT 21, SIT 26, SIT 53, and SIT 52, each consisting of 17.6, 13.3, 8.4, 7.4, and 5%, respectively. Lineage 3 and lineage 4, as well as the age group (15–24), were associated significantly with clustering. Conclusion The MTBC isolated from TB patients in Somali region were highly diverse, with considerable spoligotype clustering which suggests active TB transmission. In addition, the Beijing spoligotype was isolated in relatively higher frequency than the frequencies of its isolation from the other regions of Ethiopia warranting the attention of the TB Control Program of the Somali region.
The validation of the Norwegian Basic Psychological Need Satisfaction and Frustration Scale: A stratified sampling procedure

This study aimed to validate the Norwegian version of the Basic Psychological Need Satisfaction and Frustration Scale (BPNSFS) and to examine its relations with indicators of well-being and ill-being. Additionally, despite the vast number of studies employing the BPNSFS, norms related to the BPNSFS are currently lacking. Therefore, we also aimed to provide normative data for this scale. Data were collected among a representative sample of 326 participants (M age = 42.90 years, SD = 14.76; range 18–70) in Norway, of which 49.7% was female. Results yielded evidence for a six-factor structure (i.e., combining satisfaction/frustration with the type of need) and showed the subscales to be highly reliable. Subsequent structural equation modeling showed that both need satisfaction and need frustration related strongly to vitality, life satisfaction, and internalizing symptoms, but in opposite ways. Norm scores were provided, thereby differentiating between women and men and different age groups. These findings support the use of the Norwegian BPNSFS and provide researchers and professionals with normative data on the most widely used tool to assess individuals’ satisfaction and frustration of the basic psychological needs for autonomy, competence, and relatedness.
RAISE: Robotics & AI to improve STEM and social skills for elementary school students

The authors present the design and implementation of an exploratory virtual learning environment that assists children with autism (ASD) in learning science, technology, engineering, and mathematics (STEM) skills along with improving social-emotional and communication skills. The primary contribution of this exploratory research is how educational research informs technological advances in triggering a virtual AI companion (AIC) for children in need of social-emotional and communication skills development. The AIC adapts to students’ varying levels of needed support. This project began by using puppetry control (human-in-the-loop) of the AIC, assisting students with ASD in learning basic coding, practicing their social skills with the AIC, and attaining emotional recognition and regulation skills for effective communication and learning. The student is given the challenge to program a robot, Dash™, to move in a square. Based on observed behaviors, the puppeteer controls the virtual agent’s actions to support the student in coding the robot. The virtual agent’s actions that inform the development of the AIC include speech, facial expressions, gestures, respiration, and heart color changes coded to indicate emotional state. The paper provides exploratory findings of the first 2 years of this 5-year scaling-up research study. The outcomes discussed align with a common approach of research design used for students with disabilities, called single case study research. This type of design does not involve random control trial research; instead, the student acts as her or his own control subject. Students with ASD have substantial individual differences in their social skill deficits, behaviors, communications, and learning needs, which vary greatly from the norm and from other individuals identified with this disability. Therefore, findings are reported as changes within subjects instead of across subjects. While these exploratory observations serve as a basis for longer term research on a larger population, this paper focuses less on student learning and more on evolving technology in AIC and supporting students with ASD in STEM environments.
The supergiant fast X-ray transients XTE J1739-302 and IGR J08408-4503 in quiescence with XMM-Newton

Context. Supergiant fast X-ray transients are a subclass of high mass X-ray binaries that host a neutron star accreting mass from the wind of its OB supergiant companion. They are characterized by an extremely pronounced and rapid variability in X-rays, which still lacks an unambiguous interpretation. A number of deep pointed observations with XMM-Newtonhave been carried out to study the quiescent emission of these sources and gain insight into the mechanism that causes their X-ray variability. Aims. We continued this study by using three XMM-Newton observations of the two supergiant fast X-ray transient prototypes XTE J1739-302and IGR J08408-4503in quiescence. Methods. An in-depth timing and spectral analysis of these data have been carried out. Results. We found that the quiescent emission of these sources is characterized by both complex timing and spectral variability, with multiple small flares occurring sporadically after per iods of lower X-ray emission. Some evidence is found in the XMM-Newton spectra of a soft component below �2 keV, similar to that observed in the two supergiant fast X-ray transients AX J1845.0-0433 and IGR J16207-5129 and in many other high mass X-ray binaries. Conclusions. We suggest some possible interpretations of the timing and spectral properties of the quiescent emission of XTE J1739302 and IGR J08408-4503 in the context of the different theoretical models proposed to interpret the behavior of the supergiant fast X-ray transients.
Strain level and comprehensive microbiome analysis in inflammatory bowel disease via multi-technology meta-analysis identifies key bacterial influencers of disease

Objective Inflammatory bowel disease (IBD) is a heterogenous disease in which the microbiome has been shown to play an important role. However, the precise homeostatic or pathological functions played by bacteria remain unclear. Most published studies report taxa-disease associations based on single-technology analysis of a single cohort, potentially biasing results to one clinical protocol, cohort, and molecular analysis technology. To begin to address this key question, precise identification of the bacteria implicated in IBD across cohorts is necessary. Methods We sought to take advantage of the numerous and diverse studies characterizing the microbiome in IBD to develop a multi-technology meta-analysis (MTMA) as a platform for aggregation of independently generated datasets, irrespective of DNA-profiling technique, in order to uncover the consistent microbial modulators of disease. We report the largest strain-level survey of IBD, integrating microbiome profiles from 3,407 samples from 21 datasets spanning 15 cohorts, three of which are presented for the first time in the current study, characterized using three DNA-profiling technologies, mapping all nucleotide data against known, culturable strain reference data. Results We identify several novel IBD associations with culturable strains that have so far remained elusive, including two genome-sequenced but uncharacterized Lachnospiraceae strains consistently decreased in both the gut luminal and mucosal contents of patients with IBD, and demonstrate that these strains are correlated with inflammation-related pathways that are known mechanisms targeted for treatment. Furthermore, comparative MTMA at the species versus strain level reveals that not all significant strain associations resulted in a corresponding species-level significance and conversely significant species associations are not always re-captured at the strain level. Conclusion We propose MTMA for uncovering experimentally testable strain-disease associations that, as demonstrated here, are beneficial in discovering mechanisms underpinning microbiome impact on disease or novel targets for therapeutic interventions.
Re-discussion of servitization strategy and firm performance

Servitization innovation is critical for manufacturing firms to strengthen their sustainable competitive advantage in a dynamic business environment. Current research on the relationship between servitization and firm performance has matured, but many conclusion remain divergent. That cannot only hinder the development of servitization theory, but also make manufacturers lack a scientific basis for deciding whether to develop servitization. Thus, this study aims to systematically analyze the quantitative research results in this field through Meta-analysis methods to reveal the reasons for the disagreement. After collecting 59 independent articles on servitization and firm performance, this study performed statistical analysis using Meta-analysis. Then, the relationship between servitization and firm performance was explored, as well as the effects of different potential moderating variables. The moderate positive relationship between servitization strategies and their different orientations and firm performance is found. For the moderating variables, the servitization strategy has a more significant effect on non-financial performance. And they are more correlated when there are mediator variables. The impact of firm servitization transformation in developing regions is better than in developed areas. A stable market environment is more beneficial to the servitization transformation. The transformation effect of high-tech manufacturing is better than that of traditional manufacturing. And the transformation effect of large companies is better than that of small and medium-sized companies.
Classification of multiple sclerosis clinical profiles using machine learning and grey matter connectome

Purpose: The main goal of this study is to investigate the discrimination power of Grey Matter (GM) thickness connectome data between Multiple Sclerosis (MS) clinical profiles using statistical and Machine Learning (ML) methods. Materials and Methods: A dataset composed of 90 MS patients acquired at the MS clinic of Lyon Neurological Hospital was used for the analysis. Four MS profiles were considered, corresponding to Clinical Isolated Syndrome (CIS), Relapsing-Remitting MS (RRMS), Secondary Progressive MS (SPMS), and Primary Progressive MS (PPMS). Each patient was classified in one of these profiles by our neurologist and underwent longitudinal MRI examinations including T1-weighted image acquisition at each examination, from which the GM tissue was segmented and the cortical GM thickness measured. Following the GM parcellation using two different atlases (FSAverage and Glasser 2016), the morphological connectome was built and six global metrics (Betweenness Centrality (BC), Assortativity (r), Transitivity (T), Efficiency (E g ), Modularity (Q) and Density (D)) were extracted. Based on their connectivity metrics, MS profiles were first statistically compared and second, classified using four different learning machines (Logistic Regression, Random Forest, Support Vector Machine and AdaBoost), combined in a higher level ensemble model by majority voting. Finally, the impact of the GM spatial resolution on the MS clinical profiles classification was analyzed. Results: Using binary comparisons between the four MS clinical profiles, statistical differences and classification performances higher than 0.7 were observed. Good performances were obtained when comparing the two early clinical forms, RRMS and PPMS (F1 score of 0.86), and the two neurodegenerative profiles, PPMS and SPMS (F1 score of 0.72). When comparing the two atlases, slightly better performances were obtained with the Glasser 2016 atlas, especially between RRMS with PPMS (F1 score of 0.83), compared to the FSAverage atlas (F1 score of 0.69). Also, the thresholding value for graph binarization was investigated suggesting more informative graph properties in the percentile range between 0.6 and 0.8. Conclusion: An automated pipeline was proposed for the classification of MS clinical profiles using six global graph metrics extracted from the GM morphological connectome of MS patients. This work demonstrated that GM morphological connectivity data could provide good classification performances by combining four simple ML models, without the cost of long and complex MR techniques, such as MR diffusion, and/or deep learning architectures.
Weak and Strong Field Dynamos: from the Earth to the stars

Observations of magnetism in very low mass stars recently made important progress, revealing characteristics that are now to be understood in the framework of dynamo theory. In parallel, there is growing evidence that dynamo processes in these stars share many similarities with planetary dynamos. We investigate the extent to which the weak \emph{vs} strong field bistability predicted for the geodynamo can apply to recent observations of two groups of very low mass fully-convective stars sharing similar stellar parameters but generating radically different types of magnetic fields. Our analysis is based on previously published spectropolarimetric and spectroscopic data. We argue that these can be interpreted in the framework of weak and strong field dynamos.
Vestibular paroxysmia: Long-term clinical outcome after treatment

Objective To study the long-term treatment outcome of vestibular paroxysmia (VP). Study design Retrospective study. Setting Tertiary referral hospital. Methods We analyzed records of 29 consecutive patients who were diagnosed with VP and who were treated with VP-specific anticonvulsants for at least 3 months. Patients were followed for a minimum of 6 months. We recorded and assessed starting and target dosage of medications, time to achieve adequate therapeutic response, adverse effects, and the rates of short-term and long-term remission without medication. Results All 29 patients were started on oxcarbazepine as first-line treatment, and 93.1% and 100% of patients reported good-to-excellent therapeutic response within 2 and 4 weeks, respectively. Three patients switched to other anticonvulsants at 3 months. At long-term follow-up (8–56 months), most (84.6%) oxcarbazepine-treated patients maintained good therapeutic response at doses between 300 and 600 mg/day. Eleven (37.9%) patients experienced complete remission without medication for more than 1 month, of which six (20.7%) had long-term remission off medication for more than 12 months. Nineteen (65.5%) patients had neurovascular compression (NVC) of vestibulocochlear nerve on MRI, but its presence or absence did not predict treatment response or remission. Conclusion Low-dose oxcarbazepine monotherapy for VP is effective over the long term and is generally well-tolerated. About 20% of patients with VP in our study had long-term remission off medication.
Single-nuclei analysis reveals depot-specific transcriptional heterogeneity and depot-specific cell types in adipose tissue of dairy cows

Adipose tissue (AT) is an endocrine organ with a central role on whole-body energy metabolism and development of metabolic diseases. Single-cell and single-nuclei RNA sequencing (scRNA-seq and snRNA-seq, respectively) analyses in mice and human AT have revealed vast cell heterogeneity and functionally distinct subtypes that are potential therapeutic targets to metabolic disease. In periparturient dairy cows, AT goes through intensive remodeling and its dysfunction is associated with metabolic disease pathogenesis and decreased productive performance. The contributions of depot-specific cells and subtypes to the development of diseases in dairy cows remain to be studied. Our objective was to elucidate differences in cellular diversity of visceral (VAT) and subcutaneous (SAT) AT in dairy cows at the single-nuclei level. We collected matched SAT and VAT samples from three dairy cows and performed snRNA-seq analysis. We identified distinct cell types including four major mature adipocytes (AD) and three stem and progenitor cells (ASPC) subtypes, along with endothelial cells (EC), mesothelial cells (ME), immune cells, and pericytes and smooth muscle cells. All major cell types were present in both SAT and VAT, although a strong VAT-specificity was observed for ME, which were basically absent in SAT. One ASPC subtype was defined as adipogenic (PPARG+) while the other two had a fibro-adipogenic profile (PDGFRA+). We identified vascular and lymphatic EC subtypes, and different immune cell types and subtypes in both SAT and VAT, i.e., macrophages, monocytes, T cells, and natural killer cells. Not only did VAT show a greater proportion of immune cells, but these visceral immune cells had greater activation of pathways related to immune and inflammatory response, and complement cascade in comparison with SAT. There was a substantial contrast between depots for gene expression of complement cascade, which were greatly expressed by VAT cell subtypes compared to SAT, indicating a pro-inflammatory profile in VAT. Unprecedently, our study demonstrated cell-type and depot-specific heterogeneity in VAT and SAT of dairy cows. A better understanding of depot-specific molecular and cellular features of SAT and VAT will aid in the development of AT-targeted strategies to prevent and treat metabolic disease in dairy cows, especially during the periparturient period. Graphical Abstract Graphical summary. Transcriptional profile (differently expressed genes - DEG) of distinct cell types and subtypes obtained through single-nuclei RNA sequencing analysis of matched omental visceral (VAT) and abdominal subcutaneous adipose tissues (SAT) from dairy cows (n = 3). Genes following each cell types (e.g. adipocytes, macrophages) represent signature genes through they were identified. Column on the right includes the depot in which each cell type is more abundant. ‘+’ and ‘−’ represent the expression and lack of expression, respectively, for that specific gene.
Folate vitamers in the Australian green plum: Through growth and ripening and across locations

The green plum is a native fruit of Australia that grows on the tree Buchanania obovata. This study aimed to confirm the high level of folate in green plums by analyzing a large number of ripe samples from multiple locations and to understand how folate vitamers change as the fruit grows through maturity stages. This study analyzed green plums for five vitamers of folate, H4folate, 5-CH3-H4folate, 5-CHO-H4folate, 10-CHO-PteGlu, and PteGlu (folic acid) using a stable isotope dilution assay on a liquid chromatograph mass spectrometer (LC-MS). Green plums were tested from four locations, two harvests and five maturity stages. Another 11 ripe samples, each from different tree clumps from one location, were also tested as were ripe red-colored green plums. The results show the 5-CH3-H4folate in green plum increases and accumulates in the fruit through development, ripening and senescence. The ripe green plums contain between 82.4 ± 5.5 and 149.4 ± 10.7 μg/100 g Fresh Weight (FW). The red-colored green plums are even higher in folate, with total folate measured as 192.5 ± 7.0 and 293.7 ± 27.4 μg/100 g FW, and further analysis of them is suggested. There is some variation in amounts of folate between fruit from different locations and sets of trees, but all ripe green plums tested are considered good dietary sources of folate. Graphical Abstract Green plum total folate results as fresh weight for five maturity stages of green plum growth and by locations and harvest.