Miracle-dz/UniFAR-FTUs huggingface dataset:
Further Delineation of the Spectrum of XMEN Disease in Six Chinese Pediatric Patients

X-linked MAGT1 deficiency with increased susceptibility to EBV-infection and N-linked glycosylation defect (XMEN) disease is a primary immunodeficiency caused by loss-of-function variants in the MAGT1 gene. Only two patients from one family have been diagnosed with XMEN in China. In this study, we retrospectively analyzed the genetic, clinical, and immunological characteristics of six pediatric patients in a Chinese cohort. Medical records were retrieved, immunological phenotypes were assessed, and infectious microbes in patients were detected. Six male patients (mean age, 6.3 years) from five unrelated families were genetically diagnosed as XMEN. Five patients presented with a major complaint of elevated liver enzymes, while one patient was referred for recurrent fever, cough and skin rash. Five patients developed EBV viremia, and one patient developed non-Hodgkin’s lymphoma. Histopathological findings from liver biopsy tissues showed variable hepatic steatosis, fibrosis, inflammatory infiltration, and glycogenosis. Immune phenotypes included CD4 T-cell lymphopenia, elevated B cells, inverted CD4/CD8 ratios, and elevated αβDNTs. No pathogenic microbes other than EBV were identified in these patients. This study reports the clinical and molecular features of Chinese patients with XMEN. For patients with transaminase elevation, chronic EBV infection and EBV-associated lymphoproliferative disease, the possibility of XMEN should be considered in addition to isolated liver diseases.
A SWOT Analysis of Portable and Low-Cost Markerless Motion Capture Systems to Assess Lower-Limb Musculoskeletal Kinematics in Sport

Markerless motion capture systems are promising for the assessment of movement in more real world research and clinical settings. While the technology has come a long way in the last 20 years, it is important for researchers and clinicians to understand the capacities and considerations for implementing these types of systems. The current review provides a SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis related to the successful adoption of markerless motion capture technology for the assessment of lower-limb musculoskeletal kinematics in sport medicine and performance settings. 31 articles met the a priori inclusion criteria of this analysis. Findings from the analysis indicate that the improving accuracy of these systems via the refinement of machine learning algorithms, combined with their cost efficacy and the enhanced ecological validity outweighs the current weaknesses and threats. Further, the analysis makes clear that there is a need for multidisciplinary collaboration between sport scientists and computer vision scientists to develop accurate clinical and research applications that are specific to sport. While work remains to be done for broad application, markerless motion capture technology is currently on a positive trajectory and the data from this analysis provide an efficient roadmap toward widespread adoption.
Self-Worth as a Mediator and Moderator Between Teacher-Student Relationships and Student Engagement in Rural Schools

This study examined how self-worth of students mediated and moderated their perceived positive teacher-student relationships and student engagement among middle-school students from rural China. Eighth graders (N = 838) completed surveys measuring their perceived relationships with teachers, their self-worth, and engagement. Statistical analyses revealed significant correlations among all three variables, with the strongest being between teacher-student relationships and student engagement. The structural equation modeling indicated that self-worth partially mediated the effect of teacher-student relationships on student engagement; however, positive teacher-student relationships were a stronger predictor. Multigroup analyses identified self-worth as a moderator, whereby students with lower self-worth were more reliant on positive teacher-student relationships to enhance their engagement. This study provides insights into how self-worth of students and their perceived positive teacher-student relationships influence their academic engagement in disadvantaged rural areas of China.
Glymphatic Dysfunction in Patients With End-Stage Renal Disease

Background We aimed to compare glymphatic dysfunction between patients with end-stage renal disease (ESRD) and healthy controls and analyze the correlation between the glymphatic function and clinical characteristics using the diffusion tensor image analysis along with the perivascular space (DTI-ALPS) index. Methods We prospectively enrolled neurologically asymptomatic 49 patients with ESRD undergoing dialysis and 38 healthy controls. Diffusion tensor image was conducted using the same 3T scanner, and the DTI-ALPS index was calculated. We compared the DTI-ALPS index between the patients with ESRD and healthy controls. In addition, we conducted a correlation analysis between the clinical characteristics and DTI-ALPS index in patients with ESRD. Results There were significant differences in the DTI-ALPS index between patients with ESRD and healthy controls. The DTI-ALPS index in patients with ESRD was lower than that in healthy controls (1.460 vs. 1.632, p = 0.003). In addition, there was a significant positive correlation between the DTI-ALPS index and serum parathyroid hormone levels (r = 0.357, p = 0.011). Conclusion We demonstrated glymphatic dysfunction in patients with ESRD, as revealed by the DTI-ALPS index. This study also reveals the feasibility of the DTI-ALPS method to determine glymphatic function in patients with ESRD, which could be used in future research studies.
Design and implementation of accessible open-source augmented reality learning authoring tool

The emerging learning technologies have brought new dimensions to the learning process. Particularly in this era, where due to health reasons, online learning is preferred, augmenting reality with digital information is paramount. Unfortunately, most of the existing augmented reality learning applications were not designed for different abilities, apart from having substantial annual licenses. Further, they require advanced digital competence such as programming, which many non-technical educational practitioners lack. This research attempts to fill this gap by designing and implementing an accessible open-source augmented reality learning authoring tool that will empower non-technical educational practitioners of different abilities to develop and use augmented reality applications for teaching and learning purposes.
Lavandula viridis L´Hér. Essential Oil Inhibits the Inflammatory Response in Macrophages Through Blockade of NF-KB Signaling Cascade

Lavandula viridis L´Hér. is an endemic Iberian species with a high essential oil yield and a pleasant lemon scent. Despite these interesting features, this species remains unrecognized and poorly explored by the food and pharmaceutical industries. Nevertheless, it has been valued in traditional medicine being used against flu, circulatory problems and to relieve headaches. Since these disorders trigger inflammatory responses, it is relevant to determine the anti-inflammatory potential of L. viridis L´Hér. essential oil in an attempt to validate its traditional use and concomitantly to increment its industrial exploitation. Therefore, in the present study the chemical composition of this volatile extract as well as the effect on ROS production, inflammatory response and proteasome activity on LPS-stimulated macrophages were disclosed. Also, its safety profile on keratinocytes, hepatocytes and alveolar epithelial cells was depicted, envisioning a future human administration. The essential oil was characterized by high quantities of 1,8-cineole, camphor and α-pinene. From a pharmacological point of view, the essential oil showed a potent antioxidant effect and inhibited nitric oxide production through down-modulation of nuclear factor kappa B-dependent Nos2 transcription and consequently iNOS protein expression as well as a decrease in proteasomal activity. The anti-inflammatory activity was also evidenced by a strong inhibition of LPS-induced Il1b and Il6 transcriptions and downregulation of COX-2 levels. Overall, bioactive safe concentrations of L. viridis L´Hér. essential oil were disclosed, thus corroborating the traditional usage of this species and paving the way for the development of plant-based therapies.
The Sensitivity of Tsunami Impact to Earthquake Source Parameters and Manning Friction in High-Resolution Inundation Simulations

In seismically active regions with variable dominant focal mechanisms, there is considerable tsunami inundation height uncertainty. Basic earthquake source parameters such as dip, strike, and rake affect significantly the tsunamigenic potential and the tsunami directivity. Tsunami inundation is also sensitive to other properties such as bottom friction. Despite their importance, sensitivity to these basic parameters is surprisingly sparsely studied in literature. We perform suites of systematic parameter searches to investigate the sensitivity of inundation at the towns of Catania and Siracusa on Sicily to changes both in the earthquake source parameters and the Manning friction. The inundation is modelled using the Tsunami-HySEA shallow water code on a system of nested topo-bathymetric grids with a finest spatial resolution of 10 m. This GPU-based model, with significant HPC resources, allows us to perform large numbers of high-resolution tsunami simulations. We analyze the variability of different hydrodynamic parameters due to large earthquakes with uniform slip at different locations, focal depth, and different source parameters. We consider sources both near the coastline, in which significant near-shore co-seismic deformation occurs, and offshore, where near-shore co-seismic deformation is negligible. For distant offshore earthquake sources, we see systematic and intuitive changes in the inundation with changes in strike, dip, rake, and depth. For near-shore sources, the dependency is far more complicated and co-determined by both the source mechanisms and the coastal morphology. The sensitivity studies provide directions on how to resolve the source discretization to optimize the number of sources in Probabilistic Tsunami Hazard Analysis, and they demonstrate a need for a far finer discretization of local sources than for more distant sources. For a small number of earthquake sources, we study systematically the inundation as a function of the Manning coefficient. The sensitivity of the inundation to this parameter varies greatly for different earthquake sources and topo-bathymetry at the coastline of interest. The friction greatly affects the velocities and momentum flux and to a lesser but still significant extent the inundation distance from the coastline. An understanding of all these dependencies is needed to better quantify the hazard when source complexity increases.
Mental Health of Staff at Correctional Facilities in the United States During the COVID-19 Pandemic

Background Although United States (US) correctional workers (correctional officers and health care workers at correctional institutions) have experienced unprecedented stress during the COVID-19 pandemic, to date, there are no systematic data on the mental health impact of COVID-19 on correctional workers. Objective To determine the perceived mental health burden of the COVID-19 pandemic on correctional workers and to explore the relationship between workers' mental health, social demographics, and environmental/work factors. In particular, the study sought to examine if occupational role (correctional officers vs. health care workers) or sex were associated with mental health status. Methods This cross-sectional survey was conducted in 78 correctional sites in Pennsylvania, Maryland, West Virginia and New York from November 1 to December 1, 2020. There were 589 participants, including 103 correctional officers and 486 health care workers employed at the correctional facilities. Measurements included the Patient Health Questionnaire-9, Generalized Anxiety Disorder-7, Adult PROMIS Short Form v.1. 0—Sleep Disturbance, Impact of Event Scale-Revised, Maslach Burnout Inventory 2-item, and Connor-Davidson Resilience Scale 2-item. Results Approximately 48% of healthcare workers and 32% of correctional officers reported mild to severe depressive symptoms, 37% reported mild to severe anxiety symptoms, 47% of healthcare workers and 57% of correctional officers reported symptoms of burnout, and 50% of healthcare workers and 45% of correctional officers reported post-traumatic stress symptoms. Approximately 18% of healthcare workers and 11% of correctional officers reports mild to moderate sleep disturbance. Health care workers had significantly higher depression and sleep disturbance scores than did correctional officers, while correctional officers had significantly higher burnout scores. Female correctional workers scored significantly higher on anxiety than their male counterparts. Increased workload, workplace conflict, younger age of employees, trust in institutional isolation practices, and lower work position were associated with increased burnout. Despite experiencing high mental health burden, correctional workers showed high resilience (60%). Conclusion We found a high level of psychological symptoms among health care workers in correctional settings, and this population may experience unique challenges, risks and protective factors relative to other health care workers outside of correctional settings. Understanding these factors is essential for developing effective interventions for correctional workers.
Prescreening-Based Subset Selection for Improving Predictions of Earth System Models With Application to Regional Prediction of Red Tide

We present the ensemble method of prescreening-based subset selection to improve ensemble predictions of Earth system models (ESMs). In the prescreening step, the independent ensemble members are categorized based on their ability to reproduce physically-interpretable features of interest that are regional and problem-specific. The ensemble size is then updated by selecting the subsets that improve the performance of the ensemble prediction using decision relevant metrics. We apply the method to improve the prediction of red tide along the West Florida Shelf in the Gulf of Mexico, which affects coastal water quality and has substantial environmental and socioeconomic impacts on the State of Florida. Red tide is a common name for harmful algal blooms that occur worldwide, which result from large concentrations of aquatic microorganisms, such as dinoflagellate Karenia brevis, a toxic single celled protist. We present ensemble method for improving red tide prediction using the high resolution ESMs of the Coupled Model Intercomparison Project Phase 6 (CMIP6) and reanalysis data. The study results highlight the importance of prescreening-based subset selection with decision relevant metrics in identifying non-representative models, understanding their impact on ensemble prediction, and improving the ensemble prediction. These findings are pertinent to other regional environmental management applications and climate services. Additionally, our analysis follows the FAIR Guiding Principles for scientific data management and stewardship such that data and analysis tools are findable, accessible, interoperable, and reusable. As such, the interactive Colab notebooks developed for data analysis are annotated in the paper. This allows for efficient and transparent testing of the results’ sensitivity to different modeling assumptions. Moreover, this research serves as a starting point to build upon for red tide management, using the publicly available CMIP, Coordinated Regional Downscaling Experiment (CORDEX), and reanalysis data.
Glufosinate-Ammonium Induced Aberrant Histone Modifications in Mouse Sperm Are Concordant With Transcriptome in Preimplantation Embryos

Glufosinate-ammonium (GLA) is a widely used herbicide with emerging concern over its male reproductive toxicity. Abnormalities in sperm histone modification induced by GLA exposure observed in our previous study aroused our interest in whether such alterations could further affect embryonic gene expression. Here we administered adult male mice with 0.2 mg/kg⋅day of GLA for 5 weeks to collect their sperm or 4-cell embryos after copulation. Cleavage Under Targets and Tagmentation (CUT&Tag) sequencing showed alterations of sperm H3 lysine 4 trimethylation (H3K4me3) and histone H3 lysine 27 acetylation (H3K27ac), which are active histone modification marks involved in embryo development, while RNA sequencing identified differentially expressed genes in 4-cell embryos. Differentially H3K4me3 and H3K27ac occupied regions were mainly distributed at the gene promoters and putative enhancers, and were enriched in pathways related to the immune system and nervous system. Integrative analysis of these sequencing data showed that genes such as Mgl2 with increased H3K4me3 and H3K27ac in sperm were up-regulated in embryos, and vice versa for genes such as Dcn. Additionally, differentially occupied H3K4me3 and H3K27ac in sperm were linked to gene expression changes in both paternal and maternal alleles of 4-cell embryos. In conclusion, GLA-induced changes in sperm H3K4me3 and H3K27ac are concordant with gene expression in preimplantation embryos, which might further affect embryo development and offspring health.
Initial Evaluation of the Concept-2 Rowing Ergometer's Accuracy Using a Motorized Test Rig

Introduction The Concept 2 (C2) rowing ergometer is used worldwide for home-based training, official competitions, and performance assessment in sports and science. Previous studies reported a disparate underestimation of mechanical power output positively related to an unclearly defined stroke variability. The aim of this study was to quantify the accuracy of the C2 while controlling for the potentially influencing variables of the rowing stroke by using a test rig for air-braked rowing ergometers and thus excluding biological variability. Methods A unique motorized test rig for rowing ergometers was employed. Accuracy was assessed as the difference in mechanical power output between C2 and a reference system during steady (i.e., minimal variations of stroke power within a series of 50 spacemark, no -strokes) and unsteady simulated rowing (i.e., persistent variations during measurement series) while manipulating the stroke variables shape, force, or rate. Results During steady simulated rowing, differences between C2 and the reference system ranged 2.9–4.3%. Differences were not significantly affected by stroke shapes (P = 0.153), but by stroke rates ranging 22–28 min−1 (P < 0.001). During unsteady simulated rowing with alterations of stroke force and rate, mean differences of 2.5–3.9% were similar as during steady simulated rowing, but the random error increased up to 18-fold. C2 underestimated mechanical power output of the first five strokes by 10–70%. Their exclusion reduced mean differences to 0.2–1.9%. Conclusion Due to the enormous underestimation of the start strokes, the nominal accuracy of the C2 depends on the total number of strokes considered. It ranges 0.2–1.9%, once the flywheel has been sufficiently accelerated. Inaccuracy increases with uneven rowing, but the stroke shape has a marginal impact. Hence, rowers should row as even as possible and prefer higher stroke rates to optimize C2 readings. We recommend external reference systems for scientific and high-performance assessments, especially for short tests designs where the start strokes will have a major impact.
Magnetic Resonance Imaging Markers for Cognitive Impairment in Parkinson’s Disease: Current View

Cognitive impairment (CI) ranging from mild cognitive impairment (MCI) to dementia is a common and disturbing complication in patients with Parkinson’s disease (PD). Numerous studies have focused on neuropathological mechanisms underlying CI in PD, along with the identification of specific biomarkers for CI. Magnetic resonance imaging (MRI), a promising method, has been adopted to examine the changes in the brain and identify the candidate biomarkers associated with CI. In this review, we have summarized the potential biomarkers for CI in PD which have been identified through multi-modal MRI studies. Structural MRI technology is widely used in biomarker research. Specific patterns of gray matter atrophy are promising predictors of the evolution of CI in patients with PD. Moreover, other MRI techniques, such as MRI related to small-vessel disease, neuromelanin-sensitive MRI, quantitative susceptibility mapping, MR diffusion imaging, MRI related to cerebrovascular abnormality, resting-state functional MRI, and proton magnetic resonance spectroscopy, can provide imaging features with a good degree of prediction for CI. In the future, novel combined biomarkers should be developed using the recognized analysis tools and predictive algorithms in both cross-sectional and longitudinal studies.
Feedback Related Potentials for EEG-Based Typing Systems

Error related potentials (ErrP), which are elicited in the EEG in response to a perceived error, have been used for error correction and adaption in the event related potential (ERP)-based brain computer interfaces designed for typing. In these typing interfaces, ERP evidence is collected in response to a sequence of stimuli presented usually in the visual form and the intended user stimulus is probabilistically inferred (stimulus with highest probability) and presented to the user as the decision. If the inferred stimulus is incorrect, ErrP is expected to be elicited in the EEG. Early approaches to use ErrP in the design of typing interfaces attempt to make hard decisions on the perceived error such that the perceived error is corrected and either the sequence of stimuli are repeated to obtain further ERP evidence, or without further repetition the stimulus with the second highest probability is presented to the user as the decision of the system. Moreover, none of the existing approaches use a language model to increase the performance of typing. In this work, unlike the existing approaches, we study the potential benefits of fusing feedback related potentials (FRP), a form of ErrP, with ERP and context information (language model, LM) in a Bayesian fashion to detect the user intent. We present experimental results based on data from 12 healthy participants using RSVP Keyboard™ to complete a copy-phrase-task. Three paradigms are compared: [P1] uses only ERP/LM Bayesian fusion; [P2] each RSVP sequence is appended with the top candidate in the alphabet according to posterior after ERP evidence fusion; corresponding FRP is then incorporated; and [P3] the top candidate is shown as a prospect to generate FRP evidence only if its posterior exceeds a threshold. Analyses indicate that ERP/LM/FRP evidence fusion during decision making yields significant speed-accuracy benefits for the user.