Miracle-dz/UniFAR-FTUs huggingface dataset:
Prediction of Extracellular Proteases of the Human Pathogen Helicobacter pylori Reveals Proteolytic Activity of the Hp1018/19 Protein HtrA

Exported proteases of Helicobacter pylori (H. pylori) are potentially involved in pathogen-associated disorders leading to gastric inflammation and neoplasia. By comprehensive sequence screening of the H. pylori proteome for predicted secreted proteases, we retrieved several candidate genes. We detected caseinolytic activities of several such proteases, which are released independently from the H. pylori type IV secretion system encoded by the cag pathogenicity island (cagPAI). Among these, we found the predicted serine protease HtrA (Hp1019), which was previously identified in the bacterial secretome of H. pylori. Importantly, we further found that the H. pylori genes hp1018 and hp1019 represent a single gene likely coding for an exported protein. Here, we directly verified proteolytic activity of HtrA in vitro and identified the HtrA protease in zymograms by mass spectrometry. Overexpressed and purified HtrA exhibited pronounced proteolytic activity, which is inactivated after mutation of Ser205 to alanine in the predicted active center of HtrA. These data demonstrate that H. pylori secretes HtrA as an active protease, which might represent a novel candidate target for therapeutic intervention strategies.
Performance bound analysis of analog circuits in frequency- and time-domain considering process variations

In this article, we propose a new performance bound analysis of analog circuits considering process variations. We model the variations of component values as intervals measured from tested chips and manufacture processes. The new method first applies a graph-based analysis approach to generate the symbolic transfer function of a linear(ized) analog circuit. Then the frequency response bounds (maximum and minimum) are obtained by performing nonlinear constrained optimization in which magnitude or phase of the transfer function is the objective function to be optimized subject to the ranges of process variational parameters. The response bounds given by the optimization-based method are very accurate and do not have the over-conservativeness issues of existing methods. Based on the frequency-domain bounds, we further develop a method to calculate the time-domain response bounds for any arbitrary input stimulus. Experimental results from several analog benchmark circuits show that the proposed method gives the correct bounds verified by Monte Carlo analysis while it delivers one order of magnitude speedup over Monte Carlo for both frequency-domain and time-domain bound analyses. We also show analog circuit yield analysis as an application of the frequency-domain variational bound analysis.
A model for local/mobile radio communications with correct packet capture

The performance of a local/mobile radio communications system utilizing the slotted ALOHA multiple random access protocol is analyzed. The probability of correct packet capture is evaluated for a packet radio system using ideal coherent binary phase-shift-keying (BPSK) modulation. Both the near/far effect and the effect of Rayleigh fading on the probability of correct packet capture are taken into account, but the effect of thermal noise is neglected since the interference due to competing packets is dominant in practical systems. Spatial diversity, forward error-correction coding, and hard-decision Viterbi decoding are used to improve the probability of correct packet reception so that system throughput can be increased. The pseudo-Bayesian algorithm that has been developed to stabilize a packet system based on the slotted ALOHA protocol at maximum channel throughput is found to be adaptable to the local/mobile operating environment. For the system considered it is possible to obtain channel throughputs as high as 0.66, provided a spatial diversity of around ten can be implemented. <<ETX>>
Estrogen suppresses melatonin-enhanced hyperactivation of hamster spermatozoa

Hamster sperm hyperactivation is enhanced by progesterone, and this progesterone-enhanced hyperactivation is suppressed by 17β-estradiol (17βE2) and γ-aminobutyric acid (GABA). Although it has been indicated that melatonin also enhances hyperactivation, it is unknown whether melatonin-enhanced hyperactivation is also suppressed by 17βE2 and GABA. In the present study, melatonin-enhanced hyperactivation was significantly suppressed by 17βE2 but not by GABA. Moreover, suppression of melatonin-enhanced hyperactivation by 17βE2 occurred through non-genomic regulation via the estrogen receptor (ER). These results suggest that enhancement of hyperactivation is regulated by melatonin and 17βE2 through non-genomic regulation.
A role for cyclooxygenase-1 in β-amyloid-induced neuroinflammation

Alzheimer's disease (AD) is a chronic neurodegenerative disorder characterized by progressive cognitive decline and memory loss. Accumulation of β-amyloid (Aβ) and tau protein are believed to be important pathological features of AD [1]. Results from a large number of studies suggest that neuroinflammation is a key contributor to neuronal loss in AD. Anti-inflammatory drugs, in particular non-steroidal anti-inflammatory drugs (NSAIDs), seem to be beneficial in terms of slowing the development of AD, as shown by several epidemiological studies [2-4]. Inhibition of cyclooxygenase (COX) activity is the main mechanism of action of NSAIDs. Two COX isoforms, COX-1 and COX-2, have been identified. Clinical studies evaluating the effects of NSAIDs or COX-2 selective inhibitors on AD have failed to show therapeutic efficacy. Some authors have suggested that the main reason for this is that COX-1 and COX-2 are involved in AD neuropathology in a preclinical stage of the disease. This explains the positive reports of the epidemiological studies and the negative findings in clinical trials with COX inhibitors [5,6]. Long-term use of NSAIDs might reduce the risk of AD, if the treatment starts before the onset of AD dementia [7].
National Prevalence and Exposure Risk for Cockroach Allergen in U.S. Households

We characterized the prevalence of cockroach allergen exposure in a nationally representative sample of U.S. homes and assessed risk factors for elevated concentrations. Design We used data from the National Survey of Lead and Allergens in Housing, a population-based cross-sectional survey. Participants Participants were residents of 831 U.S. homes in the survey. Evaluations/Measurements We analyzed allergen, questionnaire, and observational data of 831 U.S. homes. Results Cockroach allergen (Bla g 1) concentrations exceed 2.0 U/g, a level associated with allergic sensitization, in 11% of U.S. living room floors and 13% of kitchen floors. Concentrations exceed 8.0 U/g, a level associated with asthma morbidity, in 3% of living room floors and 10% of kitchen floors. Elevated concentrations were observed in high-rise apartments, urban settings, pre-1940 constructions, and households with incomes < $20,000. Odds of having concentrations > 8.0 U/g were greatest when roach problems were reported or observed and increased with the number of cockroaches observed and with indications of recent cockroach activity. Conclusions Household cockroach allergen exposure is characterized in a nationally representative context. The allergen is prevalent in many settings, at levels that may contribute to allergic sensitization and asthma morbidity. Relevance to Clinical or Professional Practice Likelihood of exposure can be assessed by consideration of demographic and household determinants.
The lamina-associated polypeptide 2 (LAP2) isoforms β, γ andω of zebrafish: developmental expression and behavior during the cell cycle

Zebrafish lamina-associated polypeptides 2 (ZLAP2) β, γ andω have in common an N-terminal region with a LEM domain, and in the C-terminal half of the molecule a lamina binding domain and a membrane spanning sequence. The maternally synthesized ω is the largest isoform and the only LAP2 present in the rapidly dividing embryonic cells up to the gastrula stage. ZLAP2ω levels decrease during development, concomitant with the increase of the somatic isoforms ZLAP2β and γ. In somatic zebrafish cells ZLAP2γ is the predominant isoform, whereas only small amounts of ZLAP2β are present. During early embryonic development, ZLAP2ω becomes associated with mitotic chromosomes before anaphase. The surface of these chromosomes is decorated with vesicles, and each chromosome assembles its own nuclear envelope at the end of mitosis (karyomere formation). Ectopically expressed ZLAP2ω-green fluorescent protein (GFP) fusion protein targets vesicles to mitotic chromosomes in Xenopus A6 cells, suggesting that ZLAP2ω is involved in karyomere formation during early zebrafish development. When ZLAP2β and γ were expressed as GFP fusion proteins in Xenopus A6 cells, the β- but not the γ-isoform was found in association with mitotic chromosomes, and ZLAP2β-containing chromosomes were decorated with vesicles. Further analysis of ZLAP2-GFP fusion proteins containing only distinct domains of the ZLAP2 isoforms revealed that the common N-terminal region in conjunction with β- or ω-specific sequences mediate binding to mitotic chromosomes in vivo.
Impacts of climate change on avian populations

This review focuses on the impacts of climate change on population dynamics. I introduce the MUP (Measuring, Understanding, and Predicting) approach, which provides a general framework where an enhanced understanding of climate‐population processes, along with improved long‐term data, are merged into coherent projections of future population responses to climate change. This approach can be applied to any species, but this review illustrates its benefit using birds as examples.
Evolving Hidden Markov Models For Network Anomaly Detection

This paper reports the results of a system that performs network anomaly detection through the use of Hidden Markov Models (HMMs). The HMMs used to detect anomalies are designed and trained using Genetic Algorithms (GAs). The use of GAs helps automating the use of HMMs, by liberating users from the need of statistical knowledge, assumed by software that trains HMMs from data. The number of states, connections and weights, and probability distributions of states are determined by the GA. Results are compared to those obtained with the Baum-Welch algorithm, proving that in all cases that we tested GA outperforms Baum-Welch. The best of the evolved HMMs was used to perform anomaly detection in network traffic activity with real data.
Cloning and nucleotide sequence of the gene coding for citrate synthase from a thermotolerant Bacillus sp

The structural gene coding for citrate synthase from the gram-positive soil isolate Bacillus sp. strain C4 (ATCC 55182) capable of secreting acetic acid at pH 5.0 to 7.0 in the presence of dolime has been cloned from a genomic library by complementation of an Escherichia coli auxotrophic mutant lacking citrate synthase. The nucleotide sequence of the entire 3.1-kb HindIII fragment has been determined, and one major open reading frame was found coding for citrate synthase (ctsA). Citrate synthase from Bacillus sp. strain C4 was found to be a dimer (Mr, 84,500) with a subunit with an Mr of 42,000. The N-terminal sequence was found to be identical with that predicted from the gene sequence. The kinetics were best fit to a bisubstrate enzyme with an ordered mechanism. Bacillus sp. strain C4 citrate synthase was not activated by potassium chloride and was not inhibited by NADH, ATP, ADP, or AMP at levels up to 1 mM. The predicted amino acid sequence was compared with that of the E. coli, Acinetobacter anitratum, Pseudomonas aeruginosa, Rickettsia prowazekii, porcine heart, and Saccharomyces cerevisiae cytoplasmic and mitochondrial enzymes.
Identification of Cytochrome P450 Isoforms Involved in the Metabolism of Paroxetine and Estimation of Their Importance for Human Paroxetine Metabolism Using a Population-Based Simulator

We identify here for the first time the low-affinity cytochrome P450 (P450) isoforms that metabolize paroxetine, using cDNA-expressed human P450s measuring substrate depletion and paroxetine-catechol (product) formation by liquid chromatography-tandem mass spectrometry. CYP1A2, CYP2C19, CYP2D6, CYP3A4, and CYP3A5 were identified as paroxetine-catechol-forming P450 isoforms, and CYP2C19 and CYP2D6 were identified as metabolizing P450 isoforms by substrate depletion. Michaelis-Menten constants Km and Vmax were determined by product formation and substrate depletion. Using selective inhibitory studies and a relative activity factor approach for pooled and single-donor human liver microsomes, we confirmed involvement of the identified P450 isoforms for paroxetine-catechol formation at 1 and 20 μM paroxetine. In addition, we used the population-based simulator Simcyp to estimate the importance of the identified paroxetine-metabolizing P450 isoforms for human metabolism, taking mechanism-based inhibition into account. The amount of active hepatic CYP2D6 and CYP3A4 (not inactivated by mechanism-based inhibition) was also estimated by Simcyp. For extensive and poor metabolizers of CYP2D6, Simcyp-estimated pharmacokinetic profiles were in good agreement with those reported in published in vivo studies. Considering the kinetic parameters, inhibition results, relative activity factor calculations, and Simcyp simulations, CYP2D6 (high affinity) and CYP3A4 (low affinity) are most likely to be the major contributors to paroxetine metabolism in humans. For some individuals CYP1A2 could be of importance for paroxetine metabolism, whereas the importance of CYP2C19 and CYP3A5 is probably limited.
Conversational homes: a uniform natural language approach for collaboration among humans and devices

As devices proliferate, the ability for us to interact with them in an intuitive and meaningful way becomes increasingly challenging. In this paper we take the typical home as an experimental environment to investigate the challenges and potential solutions arising from ever-increasing device proliferation and complexity. We describe and evaluate a potential solution based on conversational interactions between “things” in the environment where those things can be either machine devices or human users. Our key innovation is the use of a Controlled Natural Language (CNL) technology as the underpinning information representation language for both machine and human agents, enabling humans and machines to trivially “read” the information being exchanged. The core CNL is augmented with a conversational protocol enabling different speech acts to be exchanged within the system. This conversational layer enables key contextual information to be conveyed, as well as providing a mechanism for translation from the core CNL to other forms, such as device specific API (Application Programming Interface) requests, or more easily consumable human representations. Our goal is to show that a single, uniform language can support machine-machine, machine-human, human-machine and humanhuman interaction in a dynamic environment that is able to rapidly evolve to accommodate new devices and capabilities as they are encountered. We also report results from our first formal evaluation of a Conversational Homes prototype and demonstrate users with no previous experience of this environment are able to rapidly and effectively interact with simulated devices in a number of simple scenarios.
Thin Film Evolution over a Thin Porous Layer: Modeling a Tear Film on a Contact Lens

We examine a mathematical model describing the behavior of the precontact lens tear film of a human eye. Our work examines the effect of contact lens thickness and lens permeability on the film dynamics. Also investigated are gravitational effects and the effects of different slip models at the fluid-lens interface. A mathematical model for the evolution of the tear film is derived using a lubrication approximation applied to the hydrodynamic equations of motion in the fluid film and the porous layer. The model is a nonlinear fourth-order partial differential equation subject to boundary conditions and an initial condition for post-blink film evolution. The evolution equation is solved numerically, and the effects of various parameters on the rupture of the thin film are studied. We find that increasing the lens thickness, permeability, and slip all contribute to an increase in the film thinning rate, although for parameter values typical for contact lens wear, these modifications are minor. Gravity plays.
Genetic variants and the risk of gestational diabetes mellitus: a systematic review.

BACKGROUND Several studies have examined associations between genetic variants and the risk of gestational diabetes mellitus (GDM). However, inferences from these studies were often hindered by limited statistical power and conflicting results. We aimed to systematically review and quantitatively summarize the association of commonly studied single nucleotide polymorphisms (SNPs) with GDM risk and to identify important gaps that remain for consideration in future studies. METHODS Genetic association studies of GDM published through 1 October 2012 were searched using the HuGE Navigator and PubMed databases. A SNP was included if the SNP-GDM associations were assessed in three or more independent studies. Two reviewers independently evaluated the eligibility for inclusion and extracted the data. The allele-specific odds ratios (ORs) and 95% confidence intervals (CIs) were pooled using random effects models accounting for heterogeneity. RESULTS Overall, 29 eligible articles capturing associations of 12 SNPs from 10 genes were included for the systematic review. The minor alleles of rs7903146 (TCF7L2), rs12255372 (TCF7L2), rs1799884 (-30G/A, GCK), rs5219 (E23K, KCNJ11), rs7754840 (CDKAL1), rs4402960 (IGF2BP2), rs10830963 (MTNR1B), rs1387153 (MTNR1B) and rs1801278 (Gly972Arg, IRS1) were significantly associated with a higher risk of GDM. Among them, genetic variants in TCF7L2 showed the strongest association with GDM risk, with ORs (95% CIs) of 1.44 (1.29-1.60, P < 0.001) per T allele of rs7903146 and 1.46 (1.15-1.84, P = 0.002) per T allele of rs12255372. CONCLUSIONS In this systematic review, we found significant associations of GDM risk with nine SNPs in seven genes, most of which have been related to the regulation of insulin secretion.
Cerebral atrophy and its relation to cognitive impairment in Parkinson disease

Objective: Voxel-based morphometry was used to compare the amounts of gray matter in the brains of patients with Parkinson disease (PD) and normal control subjects (NCs) and to identify the specific regions responsible for cognitive dysfunction in PD. Methods: Patients were classified into nondemented (ND) and demented (D) groups according to the criteria of the Diagnostic and Statistical Manual of Mental Disorders (4th ed.), and a group comparison was performed. In the ND patients, a correlation was also performed between local gray matter density and the score on Raven Colored Progressive Matrices (RCPM), a test of executive and visuospatial function. Results: In patients with advanced ND-PD vs NCs, atrophic changes were observed in the limbic/paralimbic areas and the prefrontal cortex. In D vs ND patients, atrophic change was observed widely in the limbic/paralimbic system, including the anterior cingulate gyrus and hippocampus as well as the temporal lobe, dorsolateral prefrontal cortex, thalamus, and caudate nucleus. The RCPM score was positively correlated with the gray matter density in the dorsolateral prefrontal cortex and the parahippocampal gyrus. Conclusions: In patients with Parkinson disease (PD), atrophic changes occur mainly in the limbic/paralimbic and prefrontal areas. These atrophic changes may be related to the development of dementia in PD.
A low variance consistent test of relative dependency

We describe a novel non-parametric statistical hypothesis test of relative dependence between a source variable and two candidate target variables. Such a test enables us to determine whether one source variable is significantly more dependent on a first target variable or a second. Dependence is measured via the Hilbert-Schmidt Independence Criterion (HSIC), resulting in a pair of empirical dependence measures (source-target 1, source-target 2). We test whether the first dependence measure is significantly larger than the second. Modeling the covariance between these HSIC statistics leads to a provably more powerful test than the construction of independent HSIC statistics by sub-sampling. The resulting test is consistent and unbiased, and (being based on U-statistics) has favorable convergence properties. The test can be computed in quadratic time, matching the computational complexity of standard empirical HSIC estimators. The effectiveness of the test is demonstrated on several real-world problems: we identify language groups from a multilingual corpus, and we prove that tumor location is more dependent on gene expression than chromosomal imbalances. Source code is available for download at this https URL
Mathematical Proofs in Practice: Revisiting the reliability of published mathematical proofs *

Mathematics seems to have a special status when compared to other areas of human knowledge. This special status is linked with the role of proof. Mathematicians all too often believe that this type of argumentation leaves no room for errors or unclarity. In this paper we take a closer look at mathematical practice, more precisely at the publication process in mathematics. We argue that the apparent view that mathematical literature is also more reliable is too naive. We will discuss several problems in the publication process that threaten this view, and give several suggestions on how this could be countered.
Improved Metabolic Control in Children and Adolescents With Type 1 Diabetes

OBJECTIVE To investigate the temporal trend of metabolic control and potential predictors in German and Austrian children and adolescents with type 1 diabetes. RESEARCH DESIGN AND METHODS This study is based on a large, multicenter database for prospective longitudinal documentation of diabetes care in Germany and Austria. Data from 30,708 patients documented in 305 diabetes centers between 1995 and 2009 were analyzed. Generalized linear mixed regression models were used to adjust trend analysis for relevant confounders. RESULTS Unadjusted mean HbA1c decreased from 8.7 ± 1.8% in 1995 to 8.1 ± 1.5% in 2009. In multiple regression analysis, treatment year, age, sex, diabetes duration, migration background, BMI-SDS, and daily insulin dose were significant predictors of metabolic control (P < 0.001). After multiple adjustment, mean HbA1c decreased significantly by 0.038% per year (95% CI 0.032–0.043%), average odds ratio (OR) per year for HbA1c >7.5% (>9.0%) was 0.969 (95% CI 0.961–0.977) (0.948, 95% CI 0.941–0.956). Intensified insulin regimen was associated with lower frequency of poor metabolic control (HbA1c >9%; P = 0.005) but not with average HbA1c (P = 0.797). Rate of severe hypoglycemia and hypoglycemic coma decreased significantly (relative risk [RR] per year 0.948, 95% CI 0.918–0.979; RR 0.917, 95% CI 0.885–0.950) over the study period. Diabetic ketoacidosis rate showed no significant variation over time. CONCLUSIONS This study showed a significant improvement in metabolic control in children and adolescents with type 1 diabetes during the past decade and a simultaneous decrease in hypoglycemic events. The improvement was not completely explained by changes in the mode of insulin treatment. Other factors such as improved patient education may have accounted for the observed trend.
On the continuous-time Poisson channel with varying dark current known to the transmitter

This paper considers a continuous-time Poisson channel whose dark current varies with time. The actual values of the dark current are revealed to the transmitter as channel-state information (CSI), either causally or noncausally. It is shown that, in the limit where the coherence time of the dark current tends to zero, the improvement on capacity provided by both causal and noncausal CSI vanishes linearly with the coherence time.