Miracle-dz/UniFAR-FTUs huggingface dataset:
Feedback Control Through cGMP-Dependent Protein Kinase Contributes to Differential Regulation and Compartmentation of cGMP in Rat Cardiac Myocytes

Rationale: We have shown recently that particulate (pGC) and soluble guanylyl (sGC) cyclases synthesize cGMP in different compartments in adult rat ventricular myocytes (ARVMs). Objective: We hypothesized that cGMP-dependent protein kinase (PKG) exerts a feedback control on cGMP concentration contributing to its intracellular compartmentation. Methods and Results: Global cGMP levels, cGMP-phosphodiesterase (PDE) and pGC enzymatic activities were determined in purified ARVMs. Subsarcolemmal cGMP signals were monitored in single cells by recording the cGMP-gated current (ICNG) in myocytes expressing the wild-type rat olfactory cyclic nucleotide-gated (CNG) channel. Whereas the NO donor S-nitroso-N-acetyl-penicillamine (SNAP) (100 &mgr;mol/L) produced little effect on ICNG, the response increased 2-fold in the presence of the PKG inhibitors KT5823 (50 nmol/L) or DT-2 (2 &mgr;mol/L). The effect of KT5823 was abolished in the presence of the nonselective cyclic nucleotide PDE inhibitor 3-isobutyl-1-methylxantine (IBMX) (100 &mgr;mol/L) or the selective cGMP-PDE5 inhibitor sildenafil (100 nmol/L). PKG inhibition also potentiated the effect of SNAP on global cGMP levels and fully blocked the increase in cGMP-PDE5 activity. In contrast, PKG inhibition decreased by ≈50% the ICNG response to ANP (10 and 100 nmol/L), even in the presence of IBMX. Conversely, PKG activation increased the ICNG response to ANP and amplified the stimulatory effect of ANP on pGC activity. Conclusions: PKG activation in adult cardiomyocytes limits the accumulation of cGMP induced by NO donors via PDE5 stimulation but increases that induced by natriuretic peptides. These findings support the paradigm that cGMP is not uniformly distributed in the cytosol and identifies PKG as a key component in this process.
Genome-wide quantitative assessment of variation in DNA methylation patterns

Genomic DNA methylation contributes substantively to transcriptional regulations that underlie mammalian development and cellular differentiation. Much effort has been made to decipher the molecular mechanisms governing the establishment and maintenance of DNA methylation patterns. However, little is known about genome-wide variation of DNA methylation patterns. In this study, we introduced the concept of methylation entropy, a measure of the randomness of DNA methylation patterns in a cell population, and exploited it to assess the variability in DNA methylation patterns of Alu repeats and promoters. A few interesting observations were made: (i) within a cell population, methylation entropy varies among genomic loci; (ii) among cell populations, the methylation entropies of most genomic loci remain constant; (iii) compared to normal tissue controls, some tumors exhibit greater methylation entropies; (iv) Alu elements with high methylation entropy are associated with high GC content but depletion of CpG dinucleotides and (v) Alu elements in the intronic regions or far from CpG islands are associated with low methylation entropy. We further identified 12 putative allelic-specific methylated genomic loci, including four Alu elements and eight promoters. Lastly, using subcloned normal fibroblast cells, we demonstrated the highly variable methylation patterns are resulted from low fidelity of DNA methylation inheritance.
Reassessing Deep Learning in Time Series: Predicting Time with Foresight

Machine learning relies heavily on time series forecasting, which has a wide range of uses, including although not limited to forecasting air quality, traffic patterns, and power use. Recent developments in deep training and matrix factorization models, however, have shown competitive performance and are emerging as alternatives. However, a fundamental disadvantage of these contemporary models over more established ones is their complexity. The Gradient Boosted Regression Tree, a well-known machine learning baseline, and popular deep learning models are compared in this work. We convert the time series forecast challenge into a window-based prediction issue, which is akin to (DNN) models. In addition, we design the GBRT model's input and output structure. In order to construct a single input instance to simulate a multi-output GBRT model, we concatenate the desired values with additional characteristics for each training window before flattening them. Using nine datasets, we undertake a thorough investigation and evaluate eight cutting-edge deep learning models recently presented at prestigious conferences. The findings show that a simple GBRT model performs much better than the state-of-the-art DNN models evaluated in this research thanks to the window-based input transformation.
Initial replacement stage of primary uranium (UIV) minerals by supergene alteration: association of uranyl-oxide hydroxy-hydrates and “calciolepersonnite” from the Krátka Dolina Valley (Gemerská Poloma, Gemeric Unit, Western Carpathians, Slovakia)

1 Department of Geography and Geology, Faculty of Natural Sciences, Matej Bel University, Tajovského 40, 974 01 Banská Bystrica, Slovak Republic; stefan.ferenc@umb.sk 2 Earth Science Institute of the Slovak Academy of Sciences, Ďumbierska 1, 974 11 Banská Bystrica, Slovak Republic 3 Department of Chemistry, Faculty of Natural Sciences, Matej Bel University, Tajovského 40, 974 01 Banská Bystrica, Slovak Republic * Corresponding author
Probabilistic surveillance with multiple active cameras

In this work we present a consistent probabilistic approach to control multiple, but diverse pan-tilt-zoom cameras concertedly observing a scene. There are disparate goals to this control: the cameras are not only to react to objects moving about, arbitrating conflicting interests of target resolution and trajectory accuracy, they are also to anticipate the appearance of new targets.
Identifying good diagnostic gene groups from gene expression profiles using the concept of emerging patterns

MOTIVATIONS AND RESULTS Gene groups that are significantly related to a disease can be detected by conducting a series of gene expression experiments. This work is aimed at discovering special types of gene groups that satisfy the following property. In each group, its member genes are found to be one-to-one contained in pre-determined intervals of gene expression level with a large frequency in one class of cells but are never found unanimously in these intervals in the other class of cells. We call these gene groups emerging patterns, to emphasize the patterns' frequency changes between two classes of cells. We use effective discretization and gene selection methods to obtain the most discriminatory genes. We also use efficient algorithms to derive the patterns from these genes. According to our studies on the ALL/AML dataset and the colon tumor dataset, some patterns, which consist of one or more genes, can reach a high frequency of 90%, or even 100%. In other words, they nearly or fully dominate one class of cells, even though they rarely occur in the other class. The discovered patterns are used to classify new cells with a higher accuracy than other reported methods. Based on these patterns, we also conjecture the possibility of a personalized treatment plan which converts colon tumor cells into normal cells by modulating the expression levels of a few genes.
Heparin regulates B6FS cell motility through a FAK/actin cytoskeleton axis

Soft tissue sarcomas are rare, heterogeneous tumors of mesenchymal origin with an aggressive behavior. Heparin is a mixture of heavily sulfated, linear glycosaminoglycan (GAG) chains, which participate in the regulation of various cell biological functions. Heparin is considered to have significant anticancer capabilities, although the mechanisms involved have not been fully defined. In the present study, the effects of unfractionated heparin (UFH) and low-molecular-weight heparin (LMWH) on B6FS fibrosarcoma cell motility were examined. Both preparations of heparin were shown to both enhance B6FS cell adhesion (p<0.01 and p<0.05), and migration (p<0.05), the maximal effect being evident at the concentration of 10 µg/ml. The utilization of FAK-deficient cells demonstrated that the participation of FAK was obligatory for heparin-dependent fibrosarcoma cell adhesion (p<0.05). The results of confocal microscopy indicated that heparin was taken up by the B6FS cells, and that UFH and LMWH induced F-actin polymerization. Heparitinase digestion demonstrated that the endogenous heparan sulfate (HS) chains did not affect the motility of the B6FS cells (p>0.05, not significant). In conclusion, both UFH and LMWH, through a FAK/actin cytoskeleton axis, promoted the adhesion and migration of B6FS fibrosarcoma cells. Thus, our findings indicate that the responsiveness of fibrosarcoma cells to the exogenous heparin/HS content of the cancer microenvironment may play a role in their ability to become mobile and metastasize.
Using the Actor-Network Theory to interpret e-government implementation barriers

This paper describes a research approach based on the Actor-Network Theory (ANT) to interpret or understand the implementation barriers as they emerged during the real implementation of large scale project in Palestine for the benefit of Ministry of Local Government and a group of municipalities. The main concepts of ANT such as Actor-Network, Black Boxes, moments of Translation: Problematisation, Interessement, Enrolment and Mobilization are examined to see how much ANT can help in understanding the socio-technical nature of e-Government and information systems in general. Also ANT was used as a tool to understand how change took place in situations where some beliefs such as exercising power by those who think they own the power can exercise it to enforce the adoption of new technology and create a critical mass. Furthermore, this illustrates how after interweaving a relationship between ANT concepts and e-Government the findings might be used to enhance the design of e-government implementation plans.
Bacteria and game theory: the rise and fall of cooperation in spatially heterogeneous environments

One of the predictions of game theory is that cooperative behaviours are vulnerable to exploitation by selfish individuals, but this result seemingly contradicts the survival of cooperation observed in nature. In this review, we will introduce game theoretical concepts that lead to this conclusion and show how the spatial competition dynamics between microorganisms can be used to model the survival and maintenance of cooperation. In particular, we focus on how Escherichia coli bacteria with a growth advantage in stationary phase (GASP) phenotype maintain a proliferative phenotype when faced with overcrowding to gain a fitness advantage over wild-type populations. We review recent experimental approaches studying the growth dynamics of competing GASP and wild-type strains of E. coli inside interconnected microfabricated habitats and use a game theoretical approach to analyse the observed inter-species interactions. We describe how the use of evolutionary game theory and the ideal free distribution accurately models the spatial distribution of cooperative and selfish individuals in spatially heterogeneous environments. Using bacteria as a model system of cooperative and selfish behaviours may lead to a better understanding of the competition dynamics of other organisms—including tumour–host interactions during cancer development and metastasis.
Sensitivity Analysis of HEMT Biosensor for Variation in Alx Ga1-xN Layer Alloy Composition, Bulk Trap and Doping

This work presents comprehensive analysis of a A$l_{\mathrm{x}}Ga_{(1-x)}$N/GaN High Electron Mobility Transistor(HEMT) biosensor for variation in A$l_{\mathrm{x}}Ga_{(1-x)}$N layer alloy composition, bulk trap and doping for sensing a wide set of biomolecule charge. For this study, biomolecular interface charges in the order 1$0^{12}/c\mathrm{m}^{2}$, 1$0^{13}/c\mathrm{m}^{2}$,1$0^{14}/c\mathrm{m}^{2}$ and 1$0^{15}/c\mathrm{m}^{2}$ are preferred which are exhibited by some especially significant and recognized biomarkers like the breast cancer biomarker (c-erbB-2), Kidney injury Molecule (KIM-I), Monokine Induced by Interferon Gamma (MIG) and Prostate Specific Antigen (PSA) at diverse environments. The impact of A$l_{\mathrm{x}}Ga_{(1-x)}$N layer mole fraction, trap and doping are assessed by quantifying changes in energy band, electron concentration in 2D Electron Gas (2DEG), potential distribution, current-voltage characteristics and sensitivity. Multifold changes in sensitivity are noted with change in A$l_{\mathrm{x}}Ga_{(1-x)}$N layer composition benefitting from changing polarization at A$l_{\mathrm{x}}$Ga(1-x)N/GaN surface, whereas, rate of such change differs considerably for each order of biomolecular interface charges. It is further found that presence of acceptor bulk trap and ntype doping in A$l_{\mathrm{x}}Ga_{(1-x)}$N heavily modifies the sensitivity for lower biomolecular interface charges of order 1$0^{12}/c\mathrm{m}^{2}$,1$0^{13}/c\mathrm{m}^{2}$ (induced by c-erbB-2, KIM-I) but yield minor effect on sensitivity for higher biomolecular interface charges of order 1$0^{14}/c\mathrm{m}^{2},10^{15}/c\mathrm{m}^{2}$ (induced by MIG, PSA).
Energy expenditure in men and women during 54 h of exercise and caloric deprivation.

UNLABELLED Fifty U.S. Marine recruits (30 men, 20 women) were studied during a physically intense, energy intake-restricted, winter-time 54-h field training exercise (FEX) at Parris Island Marine Corps Recruit Depot. Men and women completed the same physical tasks. PURPOSE To characterize and compare the total energy expenditure (TEE) and core temperature responses in men and women working almost continuously for 2.25 d in an outdoor environment while developing a substantial energy deficit. METHODS TEE was measured using doubly labeled water (D(2)O(18)). Energy intake was estimated using beverage diaries and collecting ration wrappers saved by each volunteer and adding the known caloric value of each food item consumed. Core temperature was measured using an ingested thermometer pill. Physical activity level (PAL) was calculated by dividing TEE by the calculated basal metabolic rate. RESULTS TEE was higher (P < 0.001) for the men (25.7 MJ.d(-1)) than women (19.8 MJ.d(-1)), but there were no differences between men and women in TEE normalized to body mass (men, 0.35 +/- 0.05 MJ.d(-1). kg(-1); women, 0.34 +/- 0.06 MJ.d(-). kg(-1)), corrected body mass (men, 0.29 +/- 0.04 MJ.d(-1). kg(-1) corrected body mass; women, 0.27 +/- 0.04 MJ.d(-1). kg(-1) corrected body mass), fat-free mass (men, 0.41 +/- 0.07 MJ.d(-1). kg(-1) FFM; women, 0.46 +/- 0.07 MJ.d(-1). kg(-1) FFM), or corrected fat-free mass (men, 0.30 +/- 0.05 MJ.d(-1). kg corrected body mass; women, 0.30 +/- 0.04 0.30 +/- 0.05 MJ.d(-1). kg(-1) corrected body mass). PAL was the same for men (3.4 +/- 0.5) and women (3.3 +/- 0.4). Energy intakes were higher (P < 0.05) in men (6.0 +/- 2.0 MJ.d(-1)) than women (4.8 +/- 1.8 MJ.d(-1)). The average minimum core temperature was 36.0 +/- 0.4 degrees C, and the mean maximum core temperature was 38.5 +/- 0.3 degrees C. CONCLUSIONS For both men and women, total energy expenditures were among the highest observed for a military FEX. TEE, when normalized or corrected to body mass and fat-free mass, and PAL were the same for men and women.
Single-Trace Attack on NTRU Decryption with Machine Learning and Template Profiling

NTRU is a post-quantum public key cryptosystem based on lattices and was a finalist in the 3rd round of the post-quantum standardization process organized by the National Institute of Standards and Technology (NIST). We present a new single-trace attack against the NTRU decryption algorithm, meaning we can obtain the private key only from one power trace, assuming the profiling phase was conducted before the attack. The attack was performed on the submission implementation from the standardization process. We used several machine-learning methods and Template attacks for the profiling and testing phase. Both methods achieve high accuracy reaching almost 100% tested on more than 12 000 traces. We also provide a comparison of their success score with regard to a different number of points of interest.
Type 1 Diabetes Versus Type 2 Diabetes/Metabolic Syndrome, Opposite Extremes of an Immune Spectrum Disorder Induced by Vaccines

There is an epidemic in children of type 2 diabetes and metabolic syndrome including individual diseases that form the components of metabolic syndrome. The epidemic resembles the epidemic of type 1 diabetes in children which has been linked to immunization. The epidemic of obesity in US children has a statistically significant positive correlation with the number of vaccine doses recommended. There is a similar trend with both hypertension and metabolic syndrome. The incidence of type 2 diabetes in Japanese children decreased significantly following the discontinuation of the BCG vaccine, a vaccine which is associated with an increased risk of type 1 diabetes. This paper describes two aberrant re- sponses to immunization. At one extreme immunization leads to progressive autoimmune diseases including type 1 diabe- tes. A second response to immunization, and an opposite extreme to autoimmunity, is for the body to suppress the im- mune system through increased cortisol activity and other counter measures leading to type 2 diabetes and metabolic syn- drome. Some vaccine recipients may have a mixed response, falling between the extremes, such as an incomplete auto- immune disorder or an intermittent autoimmune disorder. The propensity to develop a particular response relates to race. Japanese children produce large amounts of cortisol following immunization and have lower risk of type 1 diabetes but higher risk of type 2 diabetes than White children. Analysis using Austin Bradford-Hill criteria for causation support a causal relation between immunization and metabolic syndrome. Additional studies are needed to further characterize this risk.
Point System in Digital Bank: Is It the Key to Successful Customer Engagement and Loyalty?

This study investigates the transformative impact of digitalization, with a particular focus on emerging digital banking in Indonesia. Amidst a landscape populated by digital banking brands such as Allobank, Blu, Jenius, Neobank, and TMRW, this research reveals distinct differences in their strategies for effectively attracting and retaining customers. Notably, two of the leading digital banks use a spectrum of gamification elements such as badges, levels, challenges, quests, social graphs, and virtual goods. However, a noteworthy aspect, the point system, remains unexplored. Through a quantitative approach involving an online questionnaire distributed to XYZ digital bank users and analyzed with SEM-PLS, this study explores the effect of hedonic, utilitarian, and social aspects of point system gamification on customer engagement and loyalty. The findings indicate a weak but significant positive relationship between the hedonic and social value of XYZ digital bank point system and customer engagement, while the utilitarian value shows a weak and insignificant negative relationship. Most importantly, customer engagement emerged as a powerful and positively significant driver of customer loyalty. Thus, XYZ digital bank is advised to prioritize enhancing the hedonic value, followed by the social value, in their customer engagement strategies, considering alternative avenues beyond the point system gamification to fortify customer loyalty.
Conjugated polyenes as chemical probes of life signature: use of Raman spectroscopy to differentiate polyenic pigments

Polyenes, which are represented by carotenes, carotenoids and conjugated polyenals, are some of the most important targets for astrobiology, because they can provide strong evidence of the presence of organic compounds in the most extreme environments, such as on Mars. Raman spectroscopy has been used as the main analytical tool in the identification of such compounds, for the greatest variety of living species, from microorganisms to animals and plants. However, using only the position of the characteristic Raman bands can lead to errors in tentatively identifying chemicals. In this work, we present a series of observations that can provide a more complete and robust way to analyse the Raman spectrum of a polyenal, in which the position, the intensity, the use of various laser lines for excitation, and the combination of more than one pigment can be considered in the complete analysis.
Traffic matrix estimation on a large IP backbone: a comparison on real data

This paper considers the problem of estimating the point-to-point traffic matrix in an operational IP backbone. Contrary to previous studies, that have used a partial traffic matrix or demands estimated from aggregated Netflow traces, we use a unique data set of complete traffic matrices from a global IP network measured over five-minute intervals. This allows us to do an accurate data analysis on the time-scale of typical link-load measurements and enables us to make a balanced evaluation of different traffic matrix estimation techniques. We describe the data collection infrastructure, present spatial and temporal demand distributions, investigate the stability of fan-out factors, and analyze the mean-variance relationships between demands. We perform a critical evaluation of existing and novel methods for traffic matrix estimation, including recursive fanout estimation, worst-case bounds, regularized estimation techniques, and methods that rely on mean variance relationships. We discuss the weaknesses and strengths of the various methods, and highlight differences in the results for the European and American subnetworks.
Effect of Media Use on HIV-Related Stigma in Sub-Saharan Africa: A Cross-Sectional Study

It is known that HIV-related stigma hinders prevention efforts. Previous studies have documented that HIV-related stigma may be associated with socioeconomic and socioecological factors. Mass media use may moderate this association, but there is limited research addressing that possibility. In this study, based on cross-sectional data pooled from the 2006–2011 Demographic and Health Surveys of 11 sub-Saharan African countries (N = 204,343), we investigated the moderating effects of exposure to mass media on HIV-related stigma. Hierarchical regression analysis indicated that HIV-related stigma tends to be higher among rural residents and individuals with low levels of education and HIV knowledge, as well as those who do not know people living with HIV. Media use was generally associated with low levels of HIV-related stigma, and attenuated the gap between individuals with high and low educational levels. However, the effect of mass media was found to be stronger among urbanites rather than among rural residents, which could lead to a widening gap between the two groups in endorsement of HIV-related stigma. The implication of this study regarding the effect of media use on HIV-related stigma in sub-Saharan Africa is twofold: 1) mass media may have the potential to minimize the gap in HIV-related stigma between individuals with high and low educational levels, and hence future efforts of reducing HIV-related stigma in the region may benefit from utilizing media; 2) due perhaps to low media penetration to rural sub-Saharan Africa, mass media could have the unintended effect of widening the urban-rural gap further unless other more customized and rural-focused communication interventions are put in place.