Voices of Students who Quit Studies Amidst the Pandemic

The present study sought to describe and interpret the experiences that became the factor of the students at a selected state university in Cebu City of Bachelor of Special Needs Education to withdraw and quit studies amidst the pandemic. This research used phenomenology research design to achieve in-depth and rich first-person accounts utilizing interpretative phenomenological analysis with four stages in interpreting the data. Given the societal condition, the data gathering was held through personal conversation in Messenger with a sample size of 5. Findings revealed that the majority of the factors experienced by the respondents were about having problems with internet connection and environmental setbacks while being admitted to online learning. Financial difficulty and experiences with mental health issues were also specified from the results that influenced the decision of the respondents to discontinue their studying

Rhomboid family member 2 regulates cytoskeletal stress-associated Keratin 16.

Keratin 16 (K16) is a cytoskeletal scaffolding protein highly expressed at pressure-bearing sites of the mammalian footpad. It can be induced in hyperproliferative states such as wound healing, inflammation and cancer. Here we show that the inactive rhomboid protease RHBDF2 (iRHOM2) regulates thickening of the footpad epidermis through its interaction with K16. K16 expression is absent in the thinned footpads of irhom2-/- mice compared with irhom2+/+mice, due to reduced keratinocyte proliferation. Gain-of-function mutations in iRHOM2 underlie Tylosis with oesophageal cancer (TOC), characterized by palmoplantar thickening, upregulate K16 with robust downregulation of its type II keratin binding partner, K6. By orchestrating the remodelling and turnover of K16, and uncoupling it from K6, iRHOM2 regulates the epithelial response to physical stress. These findings contribute to our understanding of the molecular mechanisms underlying hyperproliferation of the palmoplantar epidermis in both physiological and disease states, and how this 'stress' keratin is regulated

Periodic Emission from the Gamma-ray Binary 1FGL J1018.6-5856

Gamma-ray binaries are stellar systems containing a neutron star or black hole with gamma-ray emission produced by an interaction between the components. These systems are rare, even though binary evolution models predict dozens in our Galaxy. A search for gamma-ray binaries with the Fermi Large Area Telescope (LAT) shows that 1FGL J1018.6-5856 exhibits intensity and spectral modulation with a 16.6 day period. We identified a variable X-ray counterpart, which shows a sharp maximum coinciding with maximum gamma-ray emission, as well as an O6V((f)) star optical counterpart and a radio counterpart that is also apparently modulated on the orbital period. 1FGL J1018.6-5856 is thus a gamma-ray binary, and its detection suggests the presence of other fainter binaries in the Galaxy.Comment: Contact authors: R.H.D. Corbet, M. Kerr, C.C. Cheun

Blogging the Virtual: New Geographies of Domination and Resistance In and Beyond Russia

Russia’s accelerating authoritarian turn has not ignored the internet, and in recent years, the Russian state has clamped down on internet activities that diverge from the statist line, employing a variety of strategies to dominate online spaces. Nevertheless, oppositional voices flourish on the Russian internet, taking shape in independent blogs and videos. This paper explores three political bloggers through surveillant and resistance assemblages, making sense of this contestation through an interpretation of the Deleuzian virtual that underscores the emancipatory potential of online activities for producing more egalitarian configurations, but also taking stock of the ways that these technologies have increased domination. Encompassing the blurriness between digital and corporeal spaces, the paper contributes by revealing new geographies of contestation against state strategies to dominate the Russian internet. Overlapping with but not corresponding to Russian territorial boundaries, these dynamics highlight shifting spaces of power and resistance in the increasingly illiberal world

Graph Regionalization with Clustering and Partitioning: an Application for Daily Commuting Flows in Albania

The paper presents an original application of the recently proposed spatial data mining method named GraphRECAP on daily commuting flows using 2011 Albanian census data. Its aim is to identify several clusters of Albanian municipalities/communes; propose a classification of the Albanian territory based on daily commuting flows among municipalities/communes. Starting from 373 local units, we first applied a spatial clustering technique without imposing any constraining strategy. Based on the input variables, we obtained 16 clusters. In the second step of our analysis, we impose a set of constraining parameters to identify intermediate areas between the local level (municipality/commune) and the national one. We have defined 12 derived regions (same number as the actual Albanian prefectures but with different geographies). These derived regions are quite different from the traditional ones in terms of both geographical dimensions and boundarie

Chronic airflow obstruction and ambient particulate air pollution

Smoking is the most well-established cause of chronic airflow obstruction (CAO) but particulate air pollution and poverty have also been implicated. We regressed sex-specific prevalence of CAO from 41 Burden of Obstructive Lung Disease study sites against smoking prevalence from the same study, the gross national income per capita and the local annual mean level of ambient particulate matter (PM2.5) using negative binomial regression. The prevalence of CAO was not independently associated with PM2.5 but was strongly associated with smoking and was also associated with poverty. Strengthening tobacco control and improved understanding of the link between CAO and poverty should be prioritised

Radionuclide imaging of bone marrow disorders

Noninvasive imaging techniques have been used in the past for visualization the functional activity of the bone marrow compartment. Imaging with radiolabelled compounds may allow different bone marrow disorders to be distinguished. These imaging techniques, almost all of which use radionuclide-labelled tracers, such as 99mTc-nanocolloid, 99mTc-sulphur colloid, 111In-chloride, and radiolabelled white blood cells, have been used in nuclear medicine for several decades. With these techniques three separate compartments can be recognized including the reticuloendothelial system, the erythroid compartment and the myeloid compartment. Recent developments in research and the clinical use of PET tracers have made possible the analysis of additional properties such as cellular metabolism and proliferative activity, using 18F-FDG and 18F-FLT. These tracers may lead to better quantification and targeting of different cell systems in the bone marrow. In this review the imaging of different bone marrow targets with radionuclides including PET tracers in various bone marrow diseases are discussed

Network Compression as a Quality Measure for Protein Interaction Networks

With the advent of large-scale protein interaction studies, there is much debate about data quality. Can different noise levels in the measurements be assessed by analyzing network structure? Because proteomic regulation is inherently co-operative, modular and redundant, it is inherently compressible when represented as a network. Here we propose that network compression can be used to compare false positive and false negative noise levels in protein interaction networks. We validate this hypothesis by first confirming the detrimental effect of false positives and false negatives. Second, we show that gold standard networks are more compressible. Third, we show that compressibility correlates with co-expression, co-localization, and shared function. Fourth, we also observe correlation with better protein tagging methods, physiological expression in contrast to over-expression of tagged proteins, and smart pooling approaches for yeast two-hybrid screens. Overall, this new measure is a proxy for both sensitivity and specificity and gives complementary information to standard measures such as average degree and clustering coefficients

Protein Networks Reveal Detection Bias and Species Consistency When Analysed by Information-Theoretic Methods

We apply our recently developed information-theoretic measures for the characterisation and comparison of protein–protein interaction networks. These measures are used to quantify topological network features via macroscopic statistical properties. Network differences are assessed based on these macroscopic properties as opposed to microscopic overlap, homology information or motif occurrences. We present the results of a large–scale analysis of protein–protein interaction networks. Precise null models are used in our analyses, allowing for reliable interpretation of the results. By quantifying the methodological biases of the experimental data, we can define an information threshold above which networks may be deemed to comprise consistent macroscopic topological properties, despite their small microscopic overlaps. Based on this rationale, data from yeast–two–hybrid methods are sufficiently consistent to allow for intra–species comparisons (between different experiments) and inter–species comparisons, while data from affinity–purification mass–spectrometry methods show large differences even within intra–species comparisons