Miracle-dz/UniFAR-FTUs huggingface dataset:
Limited muscle oxygen diffusive transport during exercise in humans

Mitochondrial oxidative phosphorylation, which modulates resynthesis of PCr, depends in part on the availability of O2 for the mitochondria in working muscle. Particularly during intense exercise, the induced lower O2 availability due to hypoxic condition by inadequate blood flow affects mitochondrial oxidative phosphorylation. However, there are few studies which have reported the relationship between mitochondrial stimuli and oxygen diffusion rate from capillary to mitochondria in skeletal muscle (muscle rDO2) during varying-workload exercise including under severe acidosis conditions in humans. The purpose of this study was to investigate the relationship between muscle PCr, rDO2, and muscle deoxygenation in humans during incremental dynamic exercise. Twelve healthy, nonsmoking male subjects participated in this study. The subjects performed incremental dynamic handgrip exercise until exhaustion. Muscle PCr during exercise was evaluated using 31-phosphorus magnetic resonance spectroscopy. Muscle deoxygenation level was monitored using near-infrared spectroscopy, and muscle rDO2 was determined by the rate of muscle deoxygenation during temporary arterial occlusion immediately after the end of each exercise stage. Muscle PCr level subsequently decreased with higher workloads, and muscle rDO2 above 10%MVC significantly increased from the resting, and was constant with higher workloads. Muscle deoxygenation level was also significantly greater above 10%MVC, and gradually increased with higher workloads. These results suggest that muscle rDO2 is limited at higher workloads, although mitochondrial stimuli are increased. The constant muscle rDO2 with higher workloads may be caused by reduced O2 gradient from capillary to mitochondria.
Screening Tea Cultivars for Novel Climates: Plant Growth and Leaf Quality of Camellia sinensis Cultivars Grown in Mississippi, United States

The United States (U.S.) consumed over 80 billion servings of tea, approximately 3.8 billion gallons, in the year of 2018. With the vast majority of tea demand being met by importation, the United States became the third largest tea importer worldwide after Russia and Pakistan. As demand for domestically produced tea increases and growers expressing increasing interest in growing and producing tea, tea production became an emerging industry in the United States. Compared to major tea producing countries with centuries of growing history, tea production in the United States is limited and requires research support in many aspect of tea production including selecting suitable cultivars adapted to local climatic conditions. This study evaluated nine tea cultivars, including ‘BL1,’ ‘BL2,’ ‘Black Sea,’ ‘Christine’s Choice,’ ‘Dave’s Fave,’ ‘Large Leaf,’ ‘Small Leaf,’ ‘Sochi,’ and ‘var. assamica,’ for plant growth, leaf morphological characteristics, cold tolerance, and leaf biochemical compositions when grown in Mississippi United States with a subtropical climate. The nine tested cultivars had varying plant growth indices (PGI) and varying degrees of cold tolerance to freezing temperatures in winter, but resumed healthy growth the following spring. ‘BL2’ showed the highest PGI of 104.53 cm by February 2019, which might be helpful toward suppressing weed and early establishment of tea plantation. The nine cultivars also showed varying leaf characteristics in terms of leaf length, width, area, fresh and dry weights, and new shoot weight. There existed a diversity in leaf biochemical composition including soluble solids, carbohydrates, total polyphenols (TP), free amino acids (AA), L-theanine and caffeine among the nine cultivars and among different harvesting seasons of spring, summer, and fall within a certain cultivar. The nine cultivars in this study generally grow well in local environment. All tea samples collected from nine cultivars and three seasons were considered suitable for green tea processing with low TP/AA ratios ranging from 1.72 to 3.71 in this study.
BYOC: A "Bring Your Own Core" Framework for Heterogeneous-ISA Research

Heterogeneous architectures and heterogeneous-ISA designs are growing areas of computer architecture and system software research. Unfortunately, this line of research is significantly hindered by the lack of experimental systems and modifiable hardware frameworks. This work proposes BYOC, a "Bring Your Own Core" framework that is specifically designed to enable heterogeneous-ISA and heterogeneous system research. BYOC is an open-source hardware framework that provides a scalable cache coherence system, that includes out-of-the-box support for four different ISAs (RISC-V 32-bit, RISC-V 64-bit, x86, and SPARCv9) and has been connected to ten different cores. The framework also supports multiple loosely coupled accelerators and is a fully working system supporting SMP Linux. The Transaction-Response Interface (TRI) introduced with BYOC has been specifically designed to make it easy to add in new cores with new ISAs and memory interfaces. This work demonstrates multiple multi-ISA designs running on FPGA and characterises the communication costs. This work describes many of the architectural design trade-offs for building such a flexible system. BYOC is well suited to be the premiere platform for heterogeneous-ISA architecture, system software, and compiler research.
Demonstrating the Psychological Aspects of Stressors and Abusive Supervision Behavior: Attainment of Sustainability Under the Rubric of Resources Theory

This article builds on the conservation of resources (COR) theory and the challenge–hindrance stressors framework to propose a model for understanding and investigating why and when these two distinct categorized stressors similarly promote the display of abusive supervision behavior. The data from 228 supervisors and subordinates are selected by using the time-lagged method. Prior to hypothesis testing, we first conducted confirmatory factor analyses (CFAs) of the proposed models in Lisrel software. Hierarchical regression analysis revealed why and when two distinct categorized stressors positively relate to ego depletion and thus, in turn, promote the display of abusive supervision behavior. The bootstrap methods confirmed the mediating effect of ego depletion and the moderated-mediation role of emotional intelligence (EI). The findings show that both challenge and hindrance stressors are positively related to ego depletion and that ego depletion is positively associated with abusive supervision behavior. Results suggest that challenge and hindrance stressors have similar positive effects on abusive supervision behavior via the mediating effect of ego depletion. In addition, we find that supervisors’ EI weakens the positive relationship between challenge stressors and ego depletion, and it also weakens the positive relationship between hindrance stressors and ego depletion. This study extends the current literature by directly testing resource depletion as a mediating mechanism and resource replenishment as a boundary condition of the effect of work stressors.
Comparison of two minimally invasive cardiac-output monitoring systems with different algorithms

Objectives: Minimally invasive haemodynamic monitoring is important in goal-directed therapy. The algorithms used by the FloTrac/Vigileo (FV) and lithium dilution cardiac output rapid (LiDCOrapid) (LR) measurement systems for cardiac output (CO) monitoring differ. We examined correlations of FV and LR measurements with thermodilution measurements and determined responsiveness to phenylephrine using both systems.
Electric field tuning of ferroelectric liquid-crystal microlaser

We discuss the electric field tuning of ferroelectric liquid crystal microlasers. The microlasers were made of 90:10 wt % mixture of CE3 and CE14 ferroelectric liquid crystals (FLCs), which was doped with ~0.1% Pyrromethene 580 fluorescent dye. The ferroelectric Sm C* phase was observed between 42°C and 74°C. The droplets were embedded into the CYTOP CTX-809A, a polymer with low electric conductivity and high viscosity. Within the temperature range 42-60°C the droplets obtained good homeotropic structure with the perpendicular anchoring of the molecules to the surface of the droplets. When the droplets were illuminated with a 532 nm pulsed laser light, Whispering Gallery Mode lasing was observed. The application of a low frequency electric field induced a red-shift of the WGM resonance peaks. The shift was reversible and had a quadratic dependency on the electric field. The observed tuning range was 4.5 nm for 2 V/μm applied electric field. The observed behaviour is explained by the soliton-like deformation of the helical ferroelectric Sm C* structure in an external electric field.
MicroRNA-1224-5p Inhibits Metastasis and Epithelial-Mesenchymal Transition in Colorectal Cancer by Targeting SP1-Mediated NF-κB Signaling Pathways

MicroRNAs (miRNAs) are small non-coding RNAs that play pivotal roles in cancer initiation and progression. However, the roles and molecular mechanisms of miRNAs in colorectal cancer (CRC) progression remain unclear. Here, we show that downregulation of miR-1224-5p in CRC is negatively correlated with SP1 expression and metastasis in patients and xenografted mouse models. Gain- and loss-of-function assays reveal that miR-1224-5p suppresses the migration, invasion, and epithelial–mesenchymal transition (EMT) of CRC cells in vitro and in vivo by directly targeting SP1. Moreover, SP1 promotes the phosphorylation of p65, which results in EMT progress in CRC cells. Clinical analysis reveals that miR-1224-5p and SP1 expression are remarkably associated with advanced clinical features and unfavorable prognosis of patients with CRC. Further study confirms that hypoxia accounts for the depletion of miR-1224-5p in CRC. The enhancement of hypoxia during epithelial–mesenchymal transition and metastasis of CRC cells is abolished by miR-1224-5p. Our findings provide the first evidence that miR-1224-5p is a potential therapeutic target and prognostic biomarker for patients with CRC.
The Role of Chemokines in the Pathogenesis of HTLV-1

Human T cell leukemia virus type 1 (HTLV-1) is a human retrovirus that is associated with two main diseases: HTLV-associated myelopathy/tropical spastic paraparesis (HAM/TSP) and adult T cell leukemia/lymphoma (ATL). Chemokines are highly specialized groups of cytokines that play important roles in organizing, trafficking, homing, and in the migration of immune cells to the bone marrow, lymphoid organs and sites of infection and inflammation. Aberrant expression or function of chemokines, or their receptors, has been linked to the protection against or susceptibility to specific infectious diseases, as well as increased the risk of autoimmune diseases and malignancy. Chemokines and their receptors participate in pathogenesis of HTLV-1 associated diseases from inflammation in the central nervous system (CNS) which occurs in cases of HAM/TSP to T cell immortalization and tissue infiltration observed in ATL patients. Chemokines represent viable effective prognostic biomarkers for HTLV-1-associated diseases which provide the early identification of high-risk, treatment possibilities and high-yielding clinical trials. This review focuses on the emerging roles of these molecules in the outcome of HTLV-1-associated diseases.
Combining analytic methods to unlock sequential and temporal patterns of self-regulated learning

The temporal and sequential nature of learning is receiving increasing focus in Learning Analytics circles. The desire to embed studies in recognised theories of self-regulated learning (SRL) has led researchers to conceptualise learning as a process that unfolds and changes over time. To that end, a body of research knowledge is growing which states that traditional frequency-based correlational studies are limited in narrative impact. To further explore this, we analysed trace data collected from online activities of a sample of 239 computer engineering undergraduate students enrolled on a course that followed a flipped class-room pedagogy. We employed SRL categorisation of micro-level processes based on a recognised model of learning, and then analysed the data using: 1) simple frequency measures; 2) epistemic network analysis; 3) temporal process mining; and 4) stochastic process mining. We found that a combination of analyses provided us with a richer insight into SRL behaviours than any one single method. We found that better performing learners employed more optimal behaviours in their navigation through the course's learning management system.
De novo Assembly of Transcriptomes From a B73 Maize Line Introgressed With a QTL for Resistance to Gray Leaf Spot Disease Reveals a Candidate Allele of a Lectin Receptor-Like Kinase

Gray leaf spot (GLS) disease in maize, caused by the fungus Cercospora zeina, is a threat to maize production globally. Understanding the molecular basis for quantitative resistance to GLS is therefore important for food security. We developed a de novo assembly pipeline to identify candidate maize resistance genes. Near-isogenic maize lines with and without a QTL for GLS resistance on chromosome 10 from inbred CML444 were produced in the inbred B73 background. The B73-QTL line showed a 20% reduction in GLS disease symptoms compared to B73 in the field (p = 0.01). B73-QTL leaf samples from this field experiment conducted under GLS disease pressure were RNA sequenced. The reads that did not map to the B73 or C. zeina genomes were expected to contain novel defense genes and were de novo assembled. A total of 141 protein-coding sequences with B73-like or plant annotations were identified from the B73-QTL plants exposed to C. zeina. To determine whether candidate gene expression was induced by C. zeina, the RNAseq reads from C. zeina-challenged and control leaves were mapped to a master assembly of all of the B73-QTL reads, and differential gene expression analysis was conducted. Combining results from both bioinformatics approaches led to the identification of a likely candidate gene, which was a novel allele of a lectin receptor-like kinase named L-RLK-CML that (i) was induced by C. zeina, (ii) was positioned in the QTL region, and (iii) had functional domains for pathogen perception and defense signal transduction. The 817AA L-RLK-CML protein had 53 amino acid differences from its 818AA counterpart in B73. A second “B73-like” allele of L-RLK was expressed at a low level in B73-QTL. Gene copy-specific RT-qPCR confirmed that the l-rlk-cml transcript was the major product induced four-fold by C. zeina. Several other expressed defense-related candidates were identified, including a wall-associated kinase, two glutathione s-transferases, a chitinase, a glucan beta-glucosidase, a plasmodesmata callose-binding protein, several other receptor-like kinases, and components of calcium signaling, vesicular trafficking, and ethylene biosynthesis. This work presents a bioinformatics protocol for gene discovery from de novo assembled transcriptomes and identifies candidate quantitative resistance genes.
Human Chorionic Gonadotrophin: New Pleiotropic Functions for an “Old” Hormone During Pregnancy

Human chorionic gonadotrophin (hCG) is the first specific molecule synthesized by the embryo. hCG RNA is transcribed as early as the eight-cell stage, and the blastocyst produces the protein before its implantation. hCG in the uterine microenvironment binds with its cognate receptor, luteinizing hormone/choriogonadotropin receptor (LHCGR), on the endometrial surface. This binding stimulates leukemia inhibitory factor (LIF) production and inhibits interleukin-6 (IL-6) production by epithelial cells of the endometrium. These effects ensure essential help in the preparation of the endometrium for initial embryo implantation. hCG also effects angiogenic and immunomodulatory actions as reported in many articles by our laboratories and other ones. By stimulating angiogenesis and vasculogenesis, hCG provides the placenta with an adequate maternal blood supply and optimal embryo nutrition during the invasion of the uterine endometrium. The immunomodulatory properties of hCG are numerous and important for programming maternal immune tolerance toward the embryo. The reported effects of hCG on uterine NK, Treg, and B cells, three major cell populations for the maintenance of pregnancy, demonstrate the role of this embryonic signal as a crucial immune regulator in the course of pregnancy. Human embryo rejection for hCG-related immunological reasons has been studied in different ways, and a sufficient dose of hCG seems to be necessary to maintain maternal tolerance. Different teams have studied the addition of hCG in patients suffering from recurrent miscarriages or implantation failures. hCG could also have a beneficial or a negative impact on autoimmune diseases during pregnancy. In this review, we will discuss the immunological impacts of hCG during pregnancy and if this hormone might be used therapeutically.
Self-regulated learning and learning analytics in online learning environments: a review of empirical research

Self-regulated learning (SRL) can predict academic performance. Yet, it is difficult for learners. The ability to self-regulate learning becomes even more important in emerging online learning settings. To support learners in developing their SRL, learning analytics (LA), which can improve learning practice by transforming the ways we support learning, is critical. This scoping review is based on the analysis of 54 papers on LA empirical research for SRL in online learning contexts published between 2011 and 2019. The research question is: What is the current state of the applications of learning analytics to measure and support students' SRL in online learning environments? The focus is on SRL phases, methods, forms of SRL support, evidence for LA and types of online learning settings. Zimmerman's model (2002) was used to examine SRL phases. The evidence about LA was examined in relation to four propositions: whether LA i) improve learning outcomes, ii) improve learning support and teaching, iii) are deployed widely, and iv) used ethically. Results showed most studies focused on SRL parts from the forethought and performance phase but much less focus on reflection. We found little evidence for LA that showed i) improvements in learning outcomes (20%), ii) improvements in learning support and teaching (22%). LA was also found iii) not used widely and iv) few studies (15%) approached research ethically. Overall, the findings show LA research was conducted mainly to measure rather than to support SRL. Thus, there is a critical need to exploit the LA support mechanisms further in order to ultimately use them to foster student SRL in online learning environments.
Exploring the Construct of Relational Values: An Empirical Approach

In recent environmental research, relational values (RVs) have emerged as a new group of values to explain environmental behavior. Although this new concept is attracting attention, empirical studies on the subject are still rare. On this basis, we have conducted three studies to analyze an existing measurement tool for RVs and compared the construct with the concept of connection to nature. In study 1, we confirmed convergent and discriminant validity of the RV scale by comparing it with the Two Factor Model of Environmental Values (2-MEV) model using a sample of n = 350 university students. Additionally, study 1 verified reliability using test–retest reliability on three different groups of students (n1 = 53; n2 = 37; n3 = 48). In study 2, principal component analyses were performed to examine the structure of RVs and to compare it to the concept of connection to nature by reusing the sample 350 university students from study 1. The results show that RVs and connection to nature are not fundamentally distinct constructs, but overlap. However, if the structure of the RV measurement is forced to a single factor, no perfect fit is found, making a multidimensional solution more likely. A third study was conducted to review the results from study 2 using confirmatory factor analysis on a new sample of 878 university and high school students. Study 3 confirmed RVs as a multidimensional construct with three factors: care, community, and connection. It also proved the overlap of the connection to nature and RV concepts to some extent.
Upregulation of RND3 Affects Trophoblast Proliferation, Apoptosis, and Migration at the Maternal-Fetal Interface

Trophoblasts as the particular cells of the placenta play an important role in implantation and formation of the maternal-fetal interface. RND3 (also known as RhoE) is a unique member of the Rnd subfamily of small GTP-binding proteins. However, its function in cytotrophoblasts (CTBs) at the maternal-fetal interface is poorly understood. In the present study, we found that RND3 expression was significantly increased in trophoblasts from the villous tissues of patients with recurrent miscarriage (RM). RND3 inhibited proliferation and migration and promoted apoptosis in HTR-8/SVneo cells. Using dual-luciferase reporter and chromatin immunoprecipitation assays, we found that forkhead box D3 (FOXD3) is a key transcription factor that binds to the RND3 core promoter region and regulates RND3 expression. Here, the level of FOXD3 was upregulated in the first-trimester CTBs of patients with RM, which in turn mediated RND3 function, including inhibition of cell proliferation and migration and promotion of apoptosis. Further, we found that RND3 regulates trophoblast migration and proliferation via the RhoA-ROCK1 signaling pathway and inhibits apoptosis via ERK1/2 signaling. Taken together, our findings suggest that RND3 and FOXD3 may be involved in pathogenesis of RM and may serve as potential therapeutic targets.
Prague: High-Performance Heterogeneity-Aware Asynchronous Decentralized Training

Distributed deep learning training usually adopts All-Reduce as the synchronization mechanism for data parallel algorithms due to its high performance in homogeneous environment. However, its performance is bounded by the slowest worker among all workers. For this reason, it is significantly slower in heterogeneous settings. AD-PSGD, a newly proposed synchronization method which provides numerically fast convergence and heterogeneity tolerance, suffers from deadlock issues and high synchronization overhead. Is it possible to get the best of both worlds --- designing a distributed training method that has both high performance like All-Reduce in homogeneous environment and good heterogeneity tolerance like AD-PSGD? In this paper, we propose Prague, a high-performance heterogeneity-aware asynchronous decentralized training approach. We achieve the above goal with intensive synchronization optimization by exploring the interplay between algorithm and system implementation, or statistical and hardware efficiency. To reduce synchronization cost, we propose a novel communication primitive, Partial All-Reduce, that enables fast synchronization among a group of workers. To reduce serialization cost, we propose static group scheduling in homogeneous environment and simple techniques, i.e., Group Buffer and Group Division, to largely eliminate conflicts with slightly reduced randomness. Our experiments show that in homogeneous environment, Prague is 1.2x faster than the state-of-the-art implementation of All-Reduce, 5.3x faster than Parameter Server and 3.7x faster than AD-PSGD. In a heterogeneous setting, Prague tolerates slowdowns well and achieves 4.4x speedup over All-Reduce.