Search results for: temporal progression

Authors: Sidra Islam, Moin Uddin, Mir A. Rouf

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A wide variety of pathological disorders owing to hyperglycemic conditions involves structural rearrangements and condensations of proteins. The implication of methylglyoxal (MG) modified immunoglobulin G (IgG) in the onset and progression of diabetes type 2 (T2DM) is studied in the present study. Using biophysical and biochemical approaches MG was found to perturb the structure of IgG, effect its microenvironment and leads to aggregate formation. Furthermore, MG-IgG was found to be highly immunogenic inducing high titre antibodies in female rabbits. Clinical studies revealed the presence of circulating anti-MG-IgG antibodies as analyzed by direct binding ELISA. The circulating auto antibodies were highly specific for MG-IgG as revealed by inhibition ELISA. Thus it can be concluded that MG is a powerful agent with a high damaging potential. To IgG. It is highly capable of generating immune response that contributes to the immunopathology associated with diabetes. Dicarbonyl adducts may emerge as potential biomarkers for T2DM.

Keywords: immunogenicity, Immunoglobulin G, methylglyoxal, Type 2 Diabetes Mellitus

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Authors: Nour Charara, Hussein Charara, Omar Abou Khaled, Hani Abdallah, Elena Mugellini

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In this paper, we present a human behavior modeling approach in videos scenes. This approach is used to model the normal behaviors in the conference halls. We exploited the Probabilistic Latent Semantic Analysis technique (PLSA), using the 'Bag-of-Terms' paradigm, as a tool for exploring video data to learn the model by grouping similar activities. Our term vocabulary consists of 3D spatio-temporal patch groups assigned by the direction of motion. Our video representation ensures the spatial information, the object trajectory, and the motion. The main importance of this approach is that it can be adapted to detect abnormal behaviors in order to ensure and enhance human security.

Keywords: activity modeling, clustering, PLSA, video representation

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Authors: Sherly Shelton, Zhaohui Lin

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In recent decades, the inter-annual variability of summer precipitation over the India and Sri Lanka has intensified significantly with an increased frequency of both abnormally dry and wet summers. Therefore prediction of the inter-annual variability of summer precipitation is crucial and urgent for water management and local agriculture scheduling. However, none of the hypotheses put forward so far could understand the relationship to monsoon variability and related factors that affect to the South West Monsoon (SWM) variability in Sri Lanka. This study focused to identify the spatial and temporal variability of SWM rainfall events from June to September (JJAS) over Sri Lanka and associated trend. The monthly rainfall records covering 1980-2013 over the Sri Lanka are used for 19 stations to investigate long-term trends in SWM rainfall over Sri Lanka. The linear trends of atmospheric variables are calculated to understand the drivers behind the changers described based on the observed precipitation, sea surface temperature and atmospheric reanalysis products data for 34 years (1980–2013). Empirical orthogonal function (EOF) analysis was applied to understand the spatial and temporal behaviour of seasonal SWM rainfall variability and also investigate whether the trend pattern is the dominant mode that explains SWM rainfall variability. The spatial and stations based precipitation over the country showed statistically insignificant decreasing trends except few stations. The first two EOFs of seasonal (JJAS) mean of rainfall explained 52% and 23 % of the total variance and first PC showed positive loadings of the SWM rainfall for the whole landmass while strongest positive lording can be seen in western/ southwestern part of the Sri Lanka. There is a negative correlation (r ≤ -0.3) between SMRI and SST in the Arabian Sea and Central Indian Ocean which indicate that lower temperature in the Arabian Sea and Central Indian Ocean are associated with greater rainfall over the country. This study also shows that consistently warming throughout the Indian Ocean. The result shows that the perceptible water over the county is decreasing with the time which the influence to the reduction of precipitation over the area by weakening drawn draft. In addition, evaporation is getting weaker over the Arabian Sea, Bay of Bengal and Sri Lankan landmass which leads to reduction of moisture availability required for the SWM rainfall over Sri Lanka. At the same time, weakening of the SST gradients between Arabian Sea and Bay of Bengal can deteriorate the monsoon circulation, untimely which diminish SWM over Sri Lanka. The decreasing trends of moisture, moisture transport, zonal wind, moisture divergence with weakening evaporation over Arabian Sea, during the past decade having an aggravating influence on decreasing trends of monsoon rainfall over the Sri Lanka.

Keywords: Arabian Sea, moisture flux convergence, South West Monsoon, Sri Lanka, sea surface temperature

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Authors: Miroslava Cuperlovic-Culf, Lipu Wang, Ketty Boyle, Nadine Makley, Ian Burton, Anissa Belkaid, Mohamed Touaibia, Marc E. Surrette

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Metabolic changes are one of the major factors in the development of a variety of diseases in various species. Metabolism of agricultural plants is altered the following infection with pathogens sometimes contributing to resistance. At the same time, pathogens use metabolites for infection and progression. In humans, metabolism is a hallmark of cancer development for example. Quantified metabolomics data combined with other omics or clinical data and analyzed using various unsupervised and supervised methods can lead to better diagnosis and prognosis. It can also provide information about resistance as well as contribute knowledge of compounds significant for disease progression or prevention. In this work, different methods for metabolomics quantification and analysis from Nuclear Magnetic Resonance (NMR) measurements that are used for investigation of disease development in wheat and human cells will be presented. One-dimensional 1H NMR spectra are used extensively for metabolic profiling due to their high reliability, wide range of applicability, speed, trivial sample preparation and low cost. This presentation will describe a new method for metabolite quantification from NMR data that combines alignment of spectra of standards to sample spectra followed by multivariate linear regression optimization of spectra of assigned metabolites to samples’ spectra. Several different alignment methods were tested and multivariate linear regression result has been compared with other quantification methods. Quantified metabolomics data can be analyzed in the variety of ways and we will present different clustering methods used for phenotype determination, network analysis providing knowledge about the relationships between metabolites through metabolic network as well as biomarker selection providing novel markers. These analysis methods have been utilized for the investigation of fusarium head blight resistance in wheat cultivars as well as analysis of the effect of estrogen receptor and carbonic anhydrase activation and inhibition on breast cancer cell metabolism. Metabolic changes in spikelet’s of wheat cultivars FL62R1, Stettler, MuchMore and Sumai3 following fusarium graminearum infection were explored. Extensive 1D 1H and 2D NMR measurements provided information for detailed metabolite assignment and quantification leading to possible metabolic markers discriminating resistance level in wheat subtypes. Quantification data is compared to results obtained using other published methods. Fusarium infection induced metabolic changes in different wheat varieties are discussed in the context of metabolic network and resistance. Quantitative metabolomics has been used for the investigation of the effect of targeted enzyme inhibition in cancer. In this work, the effect of 17 β -estradiol and ferulic acid on metabolism of ER+ breast cancer cells has been compared to their effect on ER- control cells. The effect of the inhibitors of carbonic anhydrase on the observed metabolic changes resulting from ER activation has also been determined. Metabolic profiles were studied using 1D and 2D metabolomic NMR experiments, combined with the identification and quantification of metabolites, and the annotation of the results is provided in the context of biochemical pathways.

Keywords: metabolic biomarkers, metabolic network, metabolomics, multivariate linear regression, NMR quantification, quantified metabolomics, spectral alignment

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Authors: Malika Souada, Juanita Rausch, Benjamin Guinot, Christine Bugajny

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The increase of global commerce and tourism makes the shipping sector an important contributor of atmospheric pollution. Both, airborne particles and gaseous pollutants have negative impact on health and climate. This is especially the case in port cities, due to the proximity of the exposed population to the shipping emissions in addition to other multiple sources of pollution linked to the surrounding urban activity. The objective of this study is to determine the concentrations of fine particles (immission), specifically PM2.5, PM1, PM0.3, BC and sulphates, in a context where maritime passenger traffic plays an important role (port area of Bordeaux centre). The methodology is based on high temporal resolution measurements of pollutants, correlated with meteorological and ship movements data. Particles and gaseous pollutants from seven maritime passenger ships were sampled and analysed during the docking, manoeuvring and berthing phases. The particle mass measurements were supplemented by measurements of the number concentration of ultrafine particles (<300 nm diameter). The different measurement points were chosen by taking into account the local meteorological conditions and by pre-modelling the dispersion of the smoke plumes. The results of the measurement campaign carried out during the summer of 2021 in the port of Bordeaux show that the detection of concentrations of particles emitted by ships proved to be punctual and stealthy. Punctual peaks of ultrafine particle concentration in number (P#/m3) and BC (ng/m3) were measured during the docking phases of the ships, but the concentrations returned to their background level within minutes. However, it appears that the influence of the docking phases does not significantly affect the air quality of Bordeaux centre in terms of mass concentration. Additionally, no clear differences in PM2.5 concentrations between the periods with and without ships at berth were observed. The urban background pollution seems to be mainly dominated by exhaust and non-exhaust road traffic emissions. However, temporal high-resolution measurements suggest a probable emission of gaseous precursors responsible for the formation of secondary aerosols related to the ship activities. This was evidenced by the high values of the PM1/BC and PN/BC ratios, tracers of non-primary particle formation, during periods of ship berthing vs. periods without ships at berth. The research findings from this study provide robust support for port area air quality assessment and source apportionment.

Keywords: characterization, fine particulate matter, harbour air quality, shipping impacts

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Authors: Lavanya Madhuri Bollipo, K. V. Kadambari

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Objective: To discuss key issues in the diagnosis of Parkinson disease (PD), To discuss features influencing PD progression, To discuss importance of brain SPECT data in PD diagnosis, and To discuss the essentiality of machine learning techniques in early diagnosis of PD. An accurate and early diagnosis of PD is nowadays a challenge as clinical symptoms in PD arise only when there is more than 60% loss of dopaminergic neurons. So far there are no laboratory tests for the diagnosis of PD, causing a high rate of misdiagnosis especially when the disease is in the early stages. Recent neuroimaging studies with brain SPECT using 123I-Ioflupane (DaTSCAN) as radiotracer shown to be widely used to assist the diagnosis of PD even in its early stages. Machine learning techniques can be used in combination with image analysis procedures to develop computer-aided diagnosis (CAD) systems for PD. This paper addressed recent studies involving diagnosis of PD in its early stages using brain SPECT data with Machine Learning Techniques.

Keywords: Parkinson disease (PD), dopamine transporter, single-photon emission computed tomography (SPECT), support vector machine (SVM)

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Authors: Christakis Damianou, Christos Christofi, Nicos Mylonas

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The aim of this paper was to conduct a feasibility study using a flat rectangular (3x10 mm2) MRI compatible transducer operating at 5 MHz for destroying atherosclerotic plaque using the thermal effects of ultrasound in in vitro models. A parametric study was performed where the time needed to ablate the plaque was studied as a function of Spatial Average Temporal Average (SATA) intensity, and pulse duration. The time needed to ablate plaque is directly related to intensity, and pulse duration. The temperature measured close to the artery is above safe limits and therefore thermal ultrasound does not have a place in removing plaques in arteries.

Keywords: ultrasound, atherosclerotic, plaque, pulse

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Authors: Shenghu Feng, Jun Cheng

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The molecular mechanism underlying nonalcoholic fatty liver disease (NAFLD) progression to hepatocellular carcinoma (HCC) remains unknown. In this study, immunohistochemistry staining result showed that NS5ABP37 protein expression decreased as with increasing degree of HCC malignancy. In agreement, NS5ABP37 protein overexpression significantly suppressed cell proliferation, caused G1/S cell cycle arrest, and induced apoptosis by increasing caspase-3/7 activity and cleaved caspase-3 levels. In addition, NS5ABP37 overexpression resulted in decreased intracellular TG and TC contents, with level reduction in SREBPs and downstream effectors. Furthermore, NS5ABP37 overexpression decreased SREBP1c and SREBP2 levels by inducing their respective promoters. Finally, ROS levels and ER-stress were both induced by NS5ABP37 overexpression. These findings together demonstrate that NS5ABP37 inhibits cancer cell proliferation and promotes apoptosis, by altering SREBP-dependent lipogenesis and cholesterogenesis in HepG2 cells and inducing oxidative stress and ER stress.

Keywords: NS5ABP37, liver cancer, lipid metabolism, oxidative stress, ER stress

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Authors: Aleksandra Bylinska, Samantha Slight-Webb, Kevin Thomas, Miles Smith, Susan Macwana, Nicolas Dominguez, Eliza Chakravarty, Joan T. Merrill, Judith A. James, Joel M. Guthridge

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Background: Systemic Lupus Erythematosus (SLE) is an interferon-related autoimmune disease characterized by B cell dysfunction. One of the main hallmarks is a loss of tolerance to self-antigens leading to increased levels of autoantibodies against nuclear components (ANAs). However, up to 20% of healthy ANA+ individuals will not develop clinical illness. SLE is more prevalent among women and minority populations (African, Asian American and Hispanics). Moreover, African Americans have a stronger interferon (IFN) signature and develop more severe symptoms. The exact mechanisms involved in ethnicity-dependent B cell dysregulation and the progression of autoimmune disease from ANA+ healthy individuals to clinical disease remains unclear. Methods: Peripheral blood mononuclear cells (PBMCs) from African (AA) and European American (EA) ANA- (n=12), ANA+ (n=12) and SLE (n=12) individuals were assessed by multimodal scRNA-Seq/CITE-Seq methods to examine differential gene signatures in specific B cell subsets. Library preparation was done with a 10X Genomics Chromium according to established protocols and sequenced on Illumina NextSeq. The data were further analyzed for distinct cluster identification and differential gene signatures in the Seurat package in R and pathways analysis was performed using Ingenuity Pathways Analysis (IPA). Results: Comparing all subjects, 14 distinct B cell clusters were identified using a community detection algorithm and visualized with Uniform Manifold Approximation Projection (UMAP). The proportion of each of those clusters varied by disease status and ethnicity. Transitional B cells trended higher in ANA+ healthy individuals, especially in AA. Ribonucleoprotein high population (HNRNPH1 elevated, heterogeneous nuclear ribonucleoprotein, RNP-Hi) of proliferating Naïve B cells were more prevalent in SLE patients, specifically in EA. Interferon-induced protein high population (IFIT-Hi) of Naive B cells are increased in EA ANA- individuals. The proportion of memory B cells and plasma cells clusters tend to be expanded in SLE patients. As anticipated, we observed a higher signature of cytokine-related pathways, especially interferon, in SLE individuals. Pathway analysis among AA individuals revealed an NRF2-mediated Oxidative Stress response signature in the transitional B cell cluster, not seen in EA individuals. TNFR1/2 and Sirtuin Signaling pathway genes were higher in AA IFIT-Hi Naive B cells, whereas they were not detected in EA individuals. Interferon signaling was observed in B cells in both ethnicities. Oxidative phosphorylation was found in age-related B cells (ABCs) for both ethnicities, whereas Death Receptor Signaling was found only in EA patients in these cells. Interferon-related transcription factors were elevated in ABCs and IFIT-Hi Naive B cells in SLE subjects of both ethnicities. Conclusions: ANA+ healthy individuals have altered gene expression pathways in B cells that might drive apoptosis and subsequent clinical autoimmune pathogenesis. Increases in certain regulatory pathways may delay progression to SLE. Further, AA individuals have more elevated activation pathways that may make them more susceptible to SLE.

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Authors: Jasminka Mujic, Karin Milde-Langosch, Volkmar Mueller, Mirza Suljagic, Tea Becirevic, Jozo Coric, Daria Ler

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MACC1 (metastasis associated in colon cancer-1) is a prognostic biomarker for tumor progression, metastasis, and survival of a variety of solid cancers. MACC1 also causes tumor growth in xenograft models and acts as a master regulator of the HGF/MET signaling pathway. In breast cancer, the expression of MACC1 determined by immunohistochemistry was significantly associated with positive lymph node status and advanced clinical stage. The aim of the present study was to further investigate the prognostic or predictive value of MACC1 expression in breast cancer using western blot analysis and immunohistochemistry. The results of our study have shown that high MACC1 expression in breast cancer is associated with shorter disease-free survival, especially in node-negative tumors. The MACC1 might be a suitable biomarker to select patients with a higher probability of recurrence which might benefit from adjuvant chemotherapy. Our results support a biologic role and potentially open the perspective for the use of MACC1 as predictive biomarker for treatment decision in breast cancer patients.

Keywords: breast cancer, biomarker, HGF/MET, MACC1

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Authors: Sini George

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Active learning pedagogies are valued for their success in increasing 21st-century learners’ engagement, developing transferable skills like critical thinking or quantitative reasoning, and creating deeper and more lasting educational gains. 'Blended learning' is an active learning pedagogical approach in which direct instruction moves from the group learning space to the individual learning space, and the resulting group space is transformed into a dynamic, interactive learning environment where the educator guides students as they apply concepts and engage creatively in the subject matter. This project aimed to develop a blended learning instructional approach to teaching concepts around pharmaceutical calculations to year 1 pharmacy students. The wrong dose, strength or frequency of a medication accounts for almost a third of medication errors in the NHS therefore, progression to year 2 requires a 70% pass in this calculation test, in addition to the standard progression requirements. Many students were struggling to achieve this requirement in the past. It was also challenging to teach these concepts to students of a large class (> 130) with mixed mathematical abilities, especially within a traditional didactic lecture format. Therefore, short screencasts with voice-over of the lecturer were provided in advance of a total of four teaching sessions (two hours/session), incorporating core content of each session and talking through how they approached the calculations to model metacognition. Links to the screencasts were posted on the learning management. Viewership counts were used to determine that the students were indeed accessing and watching the screencasts on schedule. In the classroom, students had to apply the knowledge learned beforehand to a series of increasingly difficult set of questions. Students were then asked to create a question in group settings (two students/group) and to discuss the questions created by their peers in their groups to promote deep conceptual learning. Students were also given time for question-and-answer period to seek clarifications on the concepts covered. Student response to this instructional approach and their test grades were collected. After collecting and organizing the data, statistical analysis was carried out to calculate binomial statistics for the two data sets: the test grade for students who received blended learning instruction and the test grades for students who received instruction in a standard lecture format in class, to compare the effectiveness of each type of instruction. Student response and their performance data on the assessment indicate that the learning of content in the blended learning instructional approach led to higher levels of student engagement, satisfaction, and more substantial learning gains. The blended learning approach enabled each student to learn how to do calculations at their own pace freeing class time for interactive application of this knowledge. Although time-consuming for an instructor to implement, the findings of this research demonstrate that the blended learning instructional approach improves student academic outcomes and represents a valuable method to incorporate active learning methodologies while still maintaining broad content coverage. Satisfaction with this approach was high, and we are currently developing more pharmacy content for delivery in this format.

Keywords: active learning, blended learning, deep conceptual learning, instructional approach, metacognition, pharmaceutical calculations

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Authors: Andrew Laming, John Hattie, Mark Wilson

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Nine Queensland Independent high schools provided deidentified student-matched ATAR and NAPLAN data for all 1217 ATAR graduates since 2020 who also sat NAPLAN at the school. Graduating cohorts from the nine schools contained a mean 100 ATAR graduates with previous NAPLAN data from their school. Excluded were vocational students (mean=27) and any ATAR graduates without NAPLAN data (mean=20). Based on Index of Community Socio-Educational Access (ICSEA) prediction, all schools had larger that predicted proportions of their students graduating with ATARs. There were an additional 173 students not releasing their ATARs to their school (14%), requiring this data to be inferred by schools. Gain was established by first converting each student’s strongest NAPLAN domain to a statewide percentile, then subtracting this result from final ATAR. The resulting ‘percentile shift’ was corrected for plausible ATAR participation at each NAPLAN level. Strongest NAPLAN domain had the highest correlation with ATAR (R2=0.58). RESULTS School mean NAPLAN scores fitted ICSEA closely (R2=0.97). Schools achieved a mean cohort gain of two ATAR rankings, but only 66% of students gained. This ranged from 46% of top-NAPLAN decile students gaining, rising to 75% achieving gains outside the top decile. The 54% of top-decile students whose ATAR fell short of prediction lost a mean 4.0 percentiles (or 6.2 percentiles prior to correction for regression to the mean). 71% of students in smaller schools gained, compared to 63% in larger schools. NAPLAN variability in each of the 13 ICSEA1100 cohorts was 17%, with both intra-school and inter-school variation of these values extremely low (0.3% to 1.8%). Mean ATAR change between years in each school was just 1.1 ATAR ranks. This suggests consecutive school cohorts and ICSEA-similar schools share very similar distributions and outcomes over time. Quantile analysis of the NAPLAN/ATAR revealed heteroscedasticity, but splines offered little additional benefit over simple linear regression. The NAPLAN/ATAR R2 was 0.33. DISCUSSION Standardised data like NAPLAN and ATAR offer educators a simple no-cost progression metric to analyse performance in conjunction with their internal test results. Change is expressed in percentiles, or ATAR shift per student, which is layperson intuitive. Findings may also reduce ATAR/vocational stream mismatch, reveal proportions of cohorts meeting or falling short of expectation and demonstrate by how much. Finally, ‘crashed’ ATARs well below expectation are revealed, which schools can reasonably work to minimise. The percentile shift method is neither value-add nor a growth percentile. In the absence of exit NAPLAN testing, this metric is unable to discriminate academic gain from legitimate ATAR-maximizing strategies. But by controlling for ICSEA, ATAR proportion variation and student mobility, it uncovers progression to ATAR metrics which are not currently publicly available. However achieved, ATAR maximisation is a sought-after private good. So long as standardised nationwide data is available, this analysis offers useful analytics for educators and reasonable predictivity when counselling subsequent cohorts about their ATAR prospects.  

Keywords: NAPLAN, ATAR, analytics, measurement, gain, performance, data, percentile, value-added, high school, numeracy, reading comprehension, variability, regression to the mean

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Authors: Salehi Zahabi Saleh, Rajabi Hosaien, Rasaneh Samira

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Yttrium-90 (90Y) radioembolisation(RE) is increasingly used for the treatment of patients with unresectable primary or metastatic liver tumours. Image-based approaches to assess microsphere distribution after RE have gained interest but are mostly hampered by the limited imaging possibilities of the Isotope 90Y. Quantitative 90Y-SPECT imaging has limited spatial resolution because it is based on 90Y Bremsstrahlung whereas 90Y-PET has better spatial resolution but low sensitivity. As a consequence, new alternative methods of visualizing the microspheres have been investigated, such as MR imaging of iron-labelled microspheres. It was also shown that MRI combines high sensitivity with high spatial and temporal resolution and with superior soft tissue contrast and thus can be used to cover a broad range of clinically interesting imaging parameters.The aim of the study in this article was to investigate the capability of MRI to measure the intrahepatic microsphere distribution in order to quantify the absorbed radiation dose in RE.

Keywords: radioembolisation, MRI, imaging, dosimetry

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Authors: Jiao F. Huang, Shi Chen, Shu C. Duan, Gang H. Wang

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Due to its complex spatial structure as well as dynamic temporal evolution, an analytic solution of an X-pinch process is out of question, and numerical simulation becomes an important tool in X-pinch studies. Intrinsically, simulations of X-pinch are three-dimensional (3D) because of the specific structure of its load. Furthermore, in order to resolve both its μm-scales and ns-durations, fine spatial mesh grid and short time steps are usually adopted. The resulting large computational scales make the parallelization of codes a vital problem to be solved if any practical simulations are to be carried out. In this work, we report OpenMP parallelization of our 3D magnetohydrodynamic (MHD) code FOI-PERFECT. Results of test runs confirm that computational efficiency has been improved after parallelization, and both the sequential and parallel versions give the same physical results under the same initial conditions.

Keywords: MHD simulation, OpenMP, parallelization, X-pinch

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Authors: Mohammadjavad Sotoudeheian

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Heart failure (HF) prevalence, as a global cardiovascular problem, is increasing gradually. A variety of molecular mechanisms contribute to HF. Proteins involved in cardiac contractility regulation, such as ion channels and calcium handling proteins, are altered. Additionally, epigenetic modifications and gene expression can lead to altered cardiac function. Moreover, inflammation and oxidative stress contribute to HF. The progression of HF can be attributed to mitochondrial dysfunction that impairs energy production and increases apoptosis. Molecular mechanisms such as these contribute to the development of cardiomyocyte defects and HF and can be therapeutically targeted. The heart's contractile function is controlled by cardiomyocytes. Calpain, and its related molecules, including Bax, VEGF, and AMPK, are among the proteins involved in regulating cardiomyocyte function. Apoptosis is facilitated by Bax. Cardiomyocyte apoptosis is regulated by this protein. Furthermore, cardiomyocyte survival, contractility, wound healing, and proliferation are all regulated by VEGF, which is produced by cardiomyocytes during inflammation and cytokine stress. Cardiomyocyte proliferation and survival are also influenced by AMPK, an enzyme that plays an active role in energy metabolism. They all play key roles in apoptosis, angiogenesis, hypertrophy, and metabolism during myocardial inflammation. The role of calpains has been linked to several molecular pathways. The calpain pathway plays an important role in signal transduction and apoptosis, as well as autophagy, endocytosis, and exocytosis. Cell death and survival are regulated by these calcium-dependent cysteine proteases that cleave proteins. As a result, protein fragments can be used for various cellular functions. By cleaving adhesion and motility proteins, calcium proteins also contribute to cell migration. HF may be brought about by calpain-mediated pathways. Many physiological processes are mediated by the calpain molecular pathways. Signal transduction, cell death, and cell migration are all regulated by these molecular pathways. Calpain is activated by calcium binding to calmodulin. In the presence of calcium, calmodulin activates calpain. Calpains are stimulated by calcium, which increases matrix metalloproteinases (MMPs). In order to develop novel treatments for these diseases, we must understand how this pathway works. A variety of myocardial remodeling processes involve calpains, including remodeling of the extracellular matrix and hypertrophy of cardiomyocytes. Calpains also play a role in maintaining cardiac homeostasis through apoptosis and autophagy. The development of HF may be in part due to calpain-mediated pathways promoting cardiomyocyte death. Numerous studies have suggested the importance of the Ca2+ -dependent protease calpain in cardiac physiology and pathology. Therefore, it is important to consider this pathway to develop and test therapeutic options in humans that targets calpain in HF. Apoptosis, autophagy, endocytosis, exocytosis, signal transduction, and disease progression all involve calpain molecular pathways. Therefore, it is conceivable that calpain inhibitors might have therapeutic potential as they have been investigated in preclinical models of several conditions in which the enzyme has been implicated that might be treated with them. Ca 2+ - dependent proteases and calpains contribute to adverse ventricular remodeling and HF in multiple experimental models. In this manuscript, we will discuss the calpain molecular pathway's important roles in HF development.

Keywords: calpain, heart failure, autophagy, apoptosis, cardiomyocyte

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Authors: Ishrat Jahan Saifi, Sheelu Shafiq Siddiqi, M. R. Ajmal

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Glycation of protein is very important as well as a harmful process, which may lead to develop DM in human body. Human Serum Albumin (HSA) is the most abundant protein in blood and it is highly prone to glycation by the reducing sugars. 2-¬deoxy d-¬Ribose (dRib) is a highly reactive reducing sugar which is produced in cells as a product of the enzyme thymidine phosphorylase. It is generated during the degradation of DNA in human body. It may cause glycation in HSA rapidly and is involved in the development of DM. In present study, we did in¬vitro glycation of HSA with different concentrations of 2-¬deoxy d-¬ribose and found that dRib glycated HSA rapidly within 4h incubation at 37◦C. UV¬ Spectroscopy, Fluorescence spectroscopy, Fourier transform infrared spectroscopy (FTIR) and Circular Dichroism (CD) technique have been done to determine the structural changes in HSA upon glycation. Results of this study suggested that dRib is the potential glycating agent and it causes alteration in protein structure and biophysical properties which may lead to development and progression of Diabetes mellitus.

Keywords: 2-deoxy D-ribose, human serum albumin, glycation, diabetes mellitus

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Authors: Rahul Agarwal, Ashutosh Singh

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Colorectal cancer (CRC) also refers as bowel cancer or colon cancer. It involves the development of abnormal growth of cells in colon or rectum part of the body. This work leads to the development of a miRNA database in colorectal cancer. We named this database- miCoRe. This database comprises of all validated colon-rectal cancer miRNAs information from various published literature with an effectual knowledge based information retrieval system. miRNAs have been collected from various published literature reports. MySQL is used for main-framework of miCoRe while the front-end was developed in PHP script. The aim of developing miCoRe is to create a comprehensive central repository of colorectal carcinoma miRNAs with all germane information of miRNAs and their target genes. The current version of miCoRe consists of 238 miRNAs which are known to be implicated in malignancy of CRC. Alongside with miRNA information, miCoRe also contains the information related to the target genes of these miRNA. miCoRe furnishes the information about the mechanism of incidence and progression of the disease, which would further help the researchers to look for colorectal specific miRNAs therapies and CRC specific targeted drug designing. Moreover, it will also help in development of biomarkers for the better and early detection of CRC and will help in better clinical management of the disease.

Keywords: colorectal cancer, database, miCoRe, miRNAs

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Authors: Shu-Jun Li, Cheng-Cao Sun, De-Jia Li

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Recently, long noncoding RNAs (lncRNAs) have been emerged as crucial regulators of human diseases and prognostic markers in numerous of cancers, including colorectal carcinoma (CRC). Here, we identified an oncogenetic lncRNA HULC, which may promote colorectal tumorigenesis. HULC has been found to be up-regulated and acts as oncogene in gastric cancer and hepatocellular carcinoma, but its expression pattern, biological function and underlying mechanism in CRC is still undetermined. Here, we reported that HULC expression is also over-expressed in CRC, and its increased level is associated with poor prognosis and shorter survival. Knockdown of HULC impaired CRC cells proliferation, migration and invasion, facilitated cell apoptosis in vitro, and inhibited tumorigenicity of CRC cells in vivo. Mechanistically, RNA immunoprecipitation (RIP) and RNA pull-down experiment demonstrated that HULC could simultaneously interact with EZH2 to repress underlying targets NKD2 transcription. In addition, rescue experiments determined that HULC oncogenic function is partly dependent on repressing NKD2. Taken together, our findings expound how HULC over-expression endows an oncogenic function in CRC.

Keywords: long noncoding RNA, HULC, NKD2, colorectal carcinoma, proliferation, apoptosis

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Authors: Aziz Ikhlef

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Most of multi-slices CT scanners are built with detectors composed of scintillator - photodiodes arrays. The photodiodes arrays are mainly based on front-illuminated technology for detectors under 64 slices and on back-illuminated photodiode for systems of 64 slices or more. The designs based on back-illuminated photodiodes were being investigated for CT machines to overcome the challenge of the higher number of runs and connection required in front-illuminated diodes. In backlit diodes, the electronic noise has already been improved because of the reduction of the load capacitance due to the routing reduction. This translated by a better image quality in low signal application, improving low dose imaging in large patient population. With the fast development of multi-detector-rows CT (MDCT) scanners and the increasing number of examinations, the clinical community has raised significant concerns on radiation dose received by the patient in both medical and regulatory community. In order to reduce individual exposure and in response to the recommendations of the International Commission on Radiological Protection (ICRP) which suggests that all exposures should be kept as low as reasonably achievable (ALARA), every manufacturer is trying to implement strategies and solutions to optimize dose efficiency and image quality based on x-ray emission and scanning parameters. The added demands on the CT detector performance also comes from the increased utilization of spectral CT or dual-energy CT in which projection data of two different tube potentials are collected. One of the approaches utilizes a technology called fast-kVp switching in which the tube voltage is switched between 80kVp and 140kVp in fraction of a millisecond. To reduce the cross-contamination of signals, the scintillator based detector temporal response has to be extremely fast to minimize the residual signal from previous samples. In addition, this paper will present an overview of detector technologies and image chain improvement which have been investigated in the last few years to improve the signal-noise ratio and the dose efficiency CT scanners in regular examinations and in energy discrimination techniques. Several parameters of the image chain in general and in the detector technology contribute in the optimization of the final image quality. We will go through the properties of the post-patient collimation to improve the scatter-to-primary ratio, the scintillator material properties such as light output, afterglow, primary speed, crosstalk to improve the spectral imaging, the photodiode design characteristics and the data acquisition system (DAS) to optimize for crosstalk, noise and temporal/spatial resolution.

Keywords: computed tomography, X-ray detector, medical imaging, image quality, artifacts

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Authors: Goh Mingyuan Asher, Nurul Fadiah Johari, Neo Yu Wei, Kim Aryung, Ho Kong Chong, Irene Y. H. N. G.

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The COVID-19 pandemic represents an externally induced force as they face a combination of reduced work, dismissal, and job change for young precarious workers. The paper drew insights from two interview waves of the in-work poverty study in Singapore which were conducted a year apart. By analysing respondents’ job histories before and at the start of the pandemic as well as their job experiences over the two waves of interviews, the study found the presence of what scholars describe as trap and stepping stone trajectories. Trap trajectories refer to how the nature of precarious employment leads respondents to be in dead-end jobs with no room for progression while stepping stone trajectories refer to how poor work provides opportunities for the accumulation of work experiences. We also look at how structure, agency and biographical factors affect job trajectories and discuss the impacts of COVID-19 on work experiences and the implications of the bifurcation of trajectory outcomes on poverty and inequality among the young working poor in Singapore.

Keywords: working poor, precarity, young workers, COVID-19, work trajectories

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Authors: Allagui Mohamed

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The study of the temporal variation of the PM10 and the SO₂ in the area of Sfax during the year of 2008, showed very significant fluctuations of the contents. They depend on the transmitting sources and the weather conditions. The study of the evolutionary behavior of the PM10 and the SO₂ in a situation of the Sirocco revealed the determining influence of the Sahara which was confirmed by its strong enrichment of the atmosphere with particulate matter. The analysis of a situation of breeze of sea highlighted the increase in the contents of the PM10 of agreement with the increase the speed of the marine wind, in particular for the diurnal period, possibly testifying to the enrichment of the aerosol in a considerable maritime component. A situation of anticyclonic winter examined when with it the accumulation of the contents of the PM10 at a rate of 70 μg/m³ showed such concentrations remained weak by comparison with other studies which show contents of about 300 μg/m³.

Keywords: PM10, sea breeze, SO₂, sirocco, anticyclone

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Authors: Shima Mahmoudi, Setareh Mamishi, Babak Pourakbari, Majid Marjani

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In the last years, the potential role of distinct T-cell subsets as biomarkers of active tuberculosis TB and/or latent tuberculosis infection (LTBI) has been studied. The aim of this study was to investigate the potential role of interleukin-2 (IL-2) in whole blood stimulated with M. tuberculosis-specific antigens in the QuantiFERON-TB Gold In Tube (QFT-G-IT) for the discrimination of active and latent tuberculosis. After 72-h of stimulation by antigens from the QFT-G-IT assay, IL-2 secretion was quantitated in supernatants by using ELISA (Mabtech AB, Sweden). Observing the level of IL-2 released after 72-h of incubation, we found that the level of IL-2 were significantly higher in LTBI group than in patients with active TB infection or control group (P value=0.019, Kruskal–Wallis test). The discrimination performance (assessed by the area under ROC curve) between LTBI and patients with active TB was 0.816 (95%CI: 0.72-0.97). Maximum discrimination was reached at a cut-off of 13.9 pg/mL for IL-2 following stimulation with 82% sensitivity and 86% specificity. In conclusion, although cytokine analysis has greatly contributed to the understanding of TB pathogenesis, data on cytokine profiles that might distinguish progression from latency of TB infection are scarce and even controversial. Our data indicate that the concomitant evaluation of IFN- γ and IL-2 could be instrumental in discriminating of active and latent TB infection.

Keywords: interleukin-2, discrimination, active TB, latent TB

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Authors: Abdi Ammar, Ouazir Youcef, Laissaoui Abdelmalek

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In this work, an approach based on transmission lines theory is presented. It is exploited for the calculation of overvoltage created by direct impacts of lightning waves on a guard cable of an overhead high-voltage line. First, we show the theoretical developments leading to the propagation equation, its discretization by finite difference time domain method (FDTD), and the resulting linear algebraic equations, followed by the calculation of the linear parameters of the line. The second step consists of solving the transmission lines system of equations by the FDTD method. This enabled us to determine the spatio-temporal evolution of the induced overvoltage.

Keywords: lightning surge, transient overvoltage, eddy current, FDTD, electromagnetic compatibility, ground wire

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Authors: Kai Zhu, Shanhua He, Yujiao Chang

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This paper explores the virtual linguistic landscape of an emerging virtual language community in TikTok, a language community realizing immediate and non-immediate communication without a precise Spatio-temporal domain or a specific socio-cultural boundary or interpersonal network. This kind of language community generates a large number and various forms of virtual linguistic landscape, with which we conducted a virtual ethnographic survey together with telephone interviews to collect data from coping. We have been following two language communities in TikTok for several months so that we can illustrate the composition of the two language communities and some typical virtual language landscapes in both language communities first. Then we try to explore the reasons why and how they are formed through the organization, transcription, and analysis of the interviews. Our analysis reveals the richness and diversity of the virtual linguistic landscape, and finally, we summarize some of the characteristics of this language community.

Keywords: virtual linguistic landscape, virtual language community, virtual ethnographic survey, TikTok

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Authors: Aziz Ikhlef

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Most of multi-slices Computed Tomography (CT) scanners are built with detectors composed of scintillator - photodiodes arrays. The photodiodes arrays are mainly based on front-illuminated technology for detectors under 64 slices and on back-illuminated photodiode for systems of 64 slices or more. The designs based on back-illuminated photodiodes were being investigated for CT machines to overcome the challenge of the higher number of runs and connection required in front-illuminated diodes. In backlit diodes, the electronic noise has already been improved because of the reduction of the load capacitance due to the routing reduction. This is translated by a better image quality in low signal application, improving low dose imaging in large patient population. With the fast development of multi-detector-rows CT (MDCT) scanners and the increasing number of examinations, the clinical community has raised significant concerns on radiation dose received by the patient in both medical and regulatory community. In order to reduce individual exposure and in response to the recommendations of the International Commission on Radiological Protection (ICRP) which suggests that all exposures should be kept as low as reasonably achievable (ALARA), every manufacturer is trying to implement strategies and solutions to optimize dose efficiency and image quality based on x-ray emission and scanning parameters. The added demands on the CT detector performance also comes from the increased utilization of spectral CT or dual-energy CT in which projection data of two different tube potentials are collected. One of the approaches utilizes a technology called fast-kVp switching in which the tube voltage is switched between 80 kVp and 140 kVp in fraction of a millisecond. To reduce the cross-contamination of signals, the scintillator based detector temporal response has to be extremely fast to minimize the residual signal from previous samples. In addition, this paper will present an overview of detector technologies and image chain improvement which have been investigated in the last few years to improve the signal-noise ratio and the dose efficiency CT scanners in regular examinations and in energy discrimination techniques. Several parameters of the image chain in general and in the detector technology contribute in the optimization of the final image quality. We will go through the properties of the post-patient collimation to improve the scatter-to-primary ratio, the scintillator material properties such as light output, afterglow, primary speed, crosstalk to improve the spectral imaging, the photodiode design characteristics and the data acquisition system (DAS) to optimize for crosstalk, noise and temporal/spatial resolution.

Keywords: computed tomography, X-ray detector, medical imaging, image quality, artifacts

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Authors: Rafal Maciag

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Due to the development of the current civilization, one must create suitable models of its pervasive massive phenomena. Such a phenomenon is the digital transformation, which has a substantial number of disciplined, methodical interpretations forming the diversified reflection. This reflection could be understood pragmatically as the current temporal, a local differential state of knowledge. The model of the discursive space is proposed as a model for the analysis and description of this knowledge. Discursive space is understood as an autonomous multidimensional space where separate discourses traverse specific trajectories of what can be presented in multidimensional parallel coordinate system. Discursive space built on the world of facts preserves the complex character of that world. Digital transformation as a discursive space has a relativistic character that means that at the same time, it is created by the dynamic discourses and these discourses are molded by the shape of this space.

Keywords: complexity, digital transformation, discourse, discursive space, knowledge

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Authors: Pirta Palola, Richard Bailey, Lisa Wedding

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Societies and economies worldwide fundamentally depend on natural capital. Alarmingly, natural capital assets are quickly depreciating, posing an existential challenge for humanity. The development of robust natural capital accounting systems is essential for transitioning towards sustainable economic systems and ensuring sound management of capital assets. However, the accurate, equitable and comprehensive estimation of natural capital asset stocks and their accounting values still faces multiple challenges. In particular, the representation of socio-cultural values held by groups or communities has arguably been limited, as to date, the valuation of natural capital assets has primarily been based on monetary valuation methods and assumptions of individual rationality. People relate to and value the natural environment in multiple ways, and no single valuation method can provide a sufficiently comprehensive image of the range of values associated with the environment. Indeed, calls have been made to improve the representation of multiple types of value (instrumental, intrinsic, and relational) and diverse ontological and epistemological perspectives in environmental valuation. This study addresses this need by establishing a novel valuation framework, Environmental Value Functions (EVF), that allows for the integration of multiple types of value in natural capital accounting systems. The EVF framework is based on the estimation and application of value functions, each of which describes the relationship between the value and quantity (or quality) of an ecosystem component of interest. In this framework, values are estimated in terms of change relative to the current level instead of calculating absolute values. Furthermore, EVF was developed to also support non-marginalist conceptualizations of value: it is likely that some environmental values cannot be conceptualized in terms of marginal changes. For example, ecological resilience value may, in some cases, be best understood as a binary: it either exists (1) or is lost (0). In such cases, a logistic value function may be used as the discriminator. Uncertainty in the value function parameterization can be considered through, for example, Monte Carlo sampling analysis. The use of EVF is illustrated with two conceptual examples. For the first time, EVF offers a clear framework and concrete methodology for the representation of multiple types of value in natural capital accounting systems, simultaneously enabling 1) the complementary use and integration of multiple valuation methods (monetary and non-monetary); 2) the synthesis of information from diverse knowledge systems; 3) the recognition of value incommensurability; 4) marginalist and non-marginalist value analysis. Furthermore, with this advancement, the coupling of EVF and ecosystem modeling can offer novel insights to the study of spatial-temporal dynamics in natural capital asset values. For example, value time series can be produced, allowing for the prediction and analysis of volatility, long-term trends, and temporal trade-offs. This approach can provide essential information to help guide the transition to a sustainable economy.

Keywords: economics of biodiversity, environmental valuation, natural capital, value function

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Authors: Ewedafe Simon Uzezi

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In this paper we presented a method based on Domain Decomposition (DD) for parallelization of 1-D Sugarcane Equation on parallel platform with parallel paradigms on Master-Slave platform using Message Passing Interface (MPI). The 1-D Sugarcane Equation was discretized using explicit method of discretization requiring evaluation nof temporal and spatial distribution of temperature. This platform gives better predictions of the effects of temperature distribution of the sugarcane problem. This work presented parallel overheads with overlapping communication and communication across parallel computers with numerical results across different block sizes with scalability. However, performance improvement strategies from the DD on various mesh sizes were compared experimentally and parallel results show speedup and efficiency for the parallel algorithms design.

Keywords: sugarcane, parallelization, explicit method, domain decomposition, MPI

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Authors: Mazhar B. Tayel, Eslam I. AlSaba

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The heart is the most important part in any body organisms. It effects and affected by any factor in the body. Therefore, it is a good detector of any matter in the body. When the heart signal is non-stationary signal, therefore, it should be study its variability. So, the Heart Rate Variability (HRV) has attracted considerable attention in psychology, medicine and have become important dependent measure in psychophysiology and behavioral medicine. Quantification and interpretation of heart rate variability. However, remain complex issues are fraught with pitfalls. This paper presents one of the non-linear techniques to analyze HRV. It discusses 'What Poincare plot is?', 'How it is work?', 'its usage benefits especially in HRV', 'the limitation of Poincare cause of standard deviation SD1, SD2', and 'How overcome this limitation by using complex correlation measure (CCM)'. The CCM is most sensitive to changes in temporal structure of the Poincaré plot as compared to SD1 and SD2.

Keywords: heart rate variability, chaotic system, poincare, variance, standard deviation, complex correlation measure

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Authors: Laura Bellassen, Idit Shachar

Abstract:

Multiple sclerosis (MS) is a chronic neurological disorder characterized by demyelination of the central nervous system (CNS), leading to a wide range of physical and cognitive impairments. Myeloid cells in the CNS, such microglia and border associated macrophage cells, participate in the neuroinflammation in MS. Activation of those cells in MS contributes to the inflammatory response in the CNS and recruitment of immune cells in the this compartment. SLAMF5 is a cell surface receptor that functions as a homophilic adhesion molecule, whose signaling can activate or inhibit leukocyte function. In the current study we followed the expression and function of SLAMF5 in myeloid cells in the CNS and in the periphery in the murine model for MS, the experimental autoimmune encephalomyelitis model (EAE). Our results show that SLAMF5 deficiency or blocking decreases the expression of activation molecules and costimulatory molecules such as MHCII and CD80, resulting in delayed onset and reduced progression of the disease. Moreover, blocking SLAMF5 in peripheral monocytes derived from MS patients and iPSC-derived microglia cells, controls the expression of HLA-DR and CD80. Thus, SLAMF5 is a regulator of myeloid cells function and can serve as a therapeutic target in autoimmune disorders as Multiple Sclerosis.

Keywords: multiple sclerosis, EAE model, myeloid cells, new antibody, neuroimmunology

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