A multi-dimensional investigation of self-regulated learning in a blended classroom context : a case study on eLDa MOOC

Online systems such as massive open online courses (MOOCs) are new innovative learning technology in education. With the proliferation of MOOC systems, little has been mentioned about blended MOOC system and how it enhances students’ performance. Blended classroom is a form of learning taking place between two different activities of which one is online and the other is traditional teaching method using bricks and mortal classroom settings. This study reveals the effectiveness of blended classroom teaching for an undergraduate course. The module was embedded in an eLDa MOOC platform, which is a platform for delivery computing concepts, and Python programme course. This research aims to investigate students’ perceptions of self-regulated learning (SRL) habits. A multi-dimensional survey was designed to evaluate each aspect of SRL skills, motivation and attaining better grades within the course. This research analysis explores (a) cognitive process of students improving their self-regulated learning skills (b) potential of students’ preparedness and motivation to engage with the course content in a blended context (c) potential difference in addressing the relation among the methods of engagement and achievement in their weekly assessment results. The research applied an online self-regulated learning questionnaire (OSLQ) as the instrument for measuring the self-regulated learning skills of the students in the learning platform environment. In relation to developing a revised OSLQ to address the use of the instrument to measure self-regulated learning in an online blended classroom context. Data collection process was conducted on a sample of first year undergraduate students who took a seminar module via a blended course format. The results indicate the level of self-regulated learning explored from the measure of the self-regulation in the blended learning environment in this study

Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta

Advances in Extracellular Matrix-Associated Diagnostics and Therapeutics

\ua9 2025 by the authors.The extracellular matrix (ECM) is the common denominator of more than 50 chronic diseases. Some of these chronic pathologies lead to enhanced tissue formation and deposition, whereas others are associated with increased tissue degradation, and some exhibit a combination of both, leading to severe tissue alterations. To develop effective therapies for diseases affecting the lung, liver, kidney, skin, intestine, musculoskeletal system, heart, and solid tumors, we need to modulate the ECM’s composition to restore its organization and function. Across diverse organ diseases, there are common denominators and distinguishing factors in this fibroinflammatory axis, which may be used to foster new insights into drug development across disease indications. The 2nd Extracellular Matrix Pharmacology Congress took place in Copenhagen, Denmark, from 17 to 19 June 2024 and was hosted by the International Society of Extracellular Matrix Pharmacology. The event was attended by 450 participants from 35 countries, among whom were prominent scientists who brought together state-of-the-art research on organ diseases and asked important questions to facilitate drug development. We highlight key aspects of the ECM in the liver, kidney, skin, intestine, musculoskeletal system, lungs, and solid tumors to advance our understanding of the ECM and its central targets in drug development. We also highlight key advances in the tools and technology that enable this drug development, thereby supporting the ECM

Relevance of laboratory testing for the diagnosis of primary immunodeficiencies: a review of case-based examples of selected immunodeficiencies

The field of primary immunodeficiencies (PIDs) is one of several in the area of clinical immunology that has not been static, but rather has shown exponential growth due to enhanced physician, scientist and patient education and awareness, leading to identification of new diseases, new molecular diagnoses of existing clinical phenotypes, broadening of the spectrum of clinical and phenotypic presentations associated with a single or related gene defects, increased bioinformatics resources, and utilization of advanced diagnostic technology and methodology for disease diagnosis and management resulting in improved outcomes and survival. There are currently over 200 PIDs with at least 170 associated genetic defects identified, with several of these being reported in recent years. The enormous clinical and immunological heterogeneity in the PIDs makes diagnosis challenging, but there is no doubt that early and accurate diagnosis facilitates prompt intervention leading to decreased morbidity and mortality. Diagnosis of PIDs often requires correlation of data obtained from clinical and radiological findings with laboratory immunological analyses and genetic testing. The field of laboratory diagnostic immunology is also rapidly burgeoning, both in terms of novel technologies and applications, and knowledge of human immunology. Over the years, the classification of PIDs has been primarily based on the immunological defect(s) ("immunophenotype") with the relatively recent addition of genotype, though there are clinical classifications as well. There can be substantial overlap in terms of the broad immunophenotype and clinical features between PIDs, and therefore, it is relevant to refine, at a cellular and molecular level, unique immunological defects that allow for a specific and accurate diagnosis. The diagnostic testing armamentarium for PID includes flow cytometry - phenotyping and functional, cellular and molecular assays, protein analysis, and mutation identification by gene sequencing. The complexity and diversity of the laboratory diagnosis of PIDs necessitates many of the above-mentioned tests being performed in highly specialized reference laboratories. Despite these restrictions, there remains an urgent need for improved standardization and optimization of phenotypic and functional flow cytometry and protein-specific assays. A key component in the interpretation of immunological assays is the comparison of patient data to that obtained in a statistically-robust manner from age and gender-matched healthy donors. This review highlights a few of the laboratory assays available for the diagnostic work-up of broad categories of PIDs, based on immunophenotyping, followed by examples of disease-specific testing

Meta-analysis of shared genetic architecture across ten pediatric autoimmune diseases

Genome-wide association studies (GWASs) have identified hundreds of susceptibility genes, including shared associations across clinically distinct autoimmune diseases. We performed an inverse χ(2) meta-analysis across ten pediatric-age-of-onset autoimmune diseases (pAIDs) in a case-control study including more than 6,035 cases and 10,718 shared population-based controls. We identified 27 genome-wide significant loci associated with one or more pAIDs, mapping to in silico-replicated autoimmune-associated genes (including IL2RA) and new candidate loci with established immunoregulatory functions such as ADGRL2, TENM3, ANKRD30A, ADCY7 and CD40LG. The pAID-associated single-nucleotide polymorphisms (SNPs) were functionally enriched for deoxyribonuclease (DNase)-hypersensitivity sites, expression quantitative trait loci (eQTLs), microRNA (miRNA)-binding sites and coding variants. We also identified biologically correlated, pAID-associated candidate gene sets on the basis of immune cell expression profiling and found evidence of genetic sharing. Network and protein-interaction analyses demonstrated converging roles for the signaling pathways of type 1, 2 and 17 helper T cells (TH1, TH2 and TH17), JAK-STAT, interferon and interleukin in multiple autoimmune diseases