Miracle-dz/UniFAR-FTUs huggingface dataset:
Pituitary tumor-transforming gene 1 regulates the patterning of retinal mosaics

Significance The spatial distributions of neuronal populations are frequently patterned, but molecular mechanisms underlying their orderliness have received little attention. We used a genetic screen to identify prospective genes participating in the patterning within a population of retinal amacrine cells. We mapped variation in their patterning, assessed using nearest-neighbor analysis across a panel of 25 recombinant inbred strains, to a genomic locus on chromosome 11. There, we identified pituitary tumor-transforming gene 1 (Pttg1) as a candidate. Critically, Pttg1 expression correlated with regularity across these 25 strains, and a variant in Pttg1 was found to modulate expression. By knocking out Pttg1, patterning was selectively disrupted in two types of retinal neuron. Neurons are commonly organized as regular arrays within a structure, and their patterning is achieved by minimizing the proximity between like-type cells, but molecular mechanisms regulating this process have, until recently, been unexplored. We performed a forward genetic screen using recombinant inbred (RI) strains derived from two parental A/J and C57BL/6J mouse strains to identify genomic loci controlling spacing of cholinergic amacrine cells, which is a subclass of retinal interneuron. We found conspicuous variation in mosaic regularity across these strains and mapped a sizeable proportion of that variation to a locus on chromosome 11 that was subsequently validated with a chromosome substitution strain. Using a bioinformatics approach to narrow the list of potential candidate genes, we identified pituitary tumor-transforming gene 1 (Pttg1) as the most promising. Expression of Pttg1 was significantly different between the two parental strains and correlated with mosaic regularity across the RI strains. We identified a seven-nucleotide deletion in the Pttg1 promoter in the C57BL/6J mouse strain and confirmed a direct role for this motif in modulating Pttg1 expression. Analysis of Pttg1 KO mice revealed a reduction in the mosaic regularity of cholinergic amacrine cells, as well as horizontal cells, but not in two other retinal cell types. Together, these results implicate Pttg1 in the regulation of homotypic spacing between specific types of retinal neurons. The genetic variant identified creates a binding motif for the transcriptional activator protein 1 complex, which may be instrumental in driving differential expression of downstream processes that participate in neuronal spacing.
Prophylactic and Therapeutic Effects of Small Interfering Rna Targeting Sars-Coronavirus

Objectives To identify and characterize the siRNA duplexes that are effective for inhibition of SARS-CoV infection and replication in the non-human primate cells. This in vitro study will serve as the foundation for development of novel anti-SARS therapeutics. Methods 48 siRNA sequences were designed for targeting regions throughout entire SARS-CoV genome RNA including open-reading frames for several key proteins. Chemically synthesized siRNA duplexes were transfected into foetal rhesus kidney (FRhK-4) cells prior to or after SARS-CoV infection. The inhibitory effects of the siRNAs were evaluated for reductions of intracellular viral genome copy number and viral titres in the cell culture medium measured by Q-RT-PCR and CPE-based titration, respectively. Four siRNA duplexes were found to achieve potent inhibition of SARS-CoV infection and replication. A prolonged prophylactic effect of siRNA duplexes with up to 90% inhibition that lasted for at least 72 h was observed. Combination of active siRNA duplexes targeting different regions of the viral genome resulted in therapeutic activity of up to 80% inhibition. Conclusion Chemically synthesized siRNA duplexes targeting SARS-CoV genomic RNA are potent agents for inhibition of the viral infection and replication. The location effects of siRNAs were revealed at both genome sequence and open-reading frame levels. The rapid development of siRNA-based SARS-CoV inhibitors marked a novel approach for combating newly emergent infectious diseases.
Large scale cohort study of the relationship between serum cholesterol concentration and coronary events with low-dose simvastatin therapy in Japanese patients with hypercholesterolemia and coronary heart disease: secondary prevention cohort study of the Japan Lipid Intervention Trial (J-LIT).

Hyperlipidemia is primarily implicated in the progression of coronary heart disease (CHD) and its treatment is essential for patients with a history of CHD. Statins such as simvastatin, the lipid-lowering agents, are well-known for their ability to normalize patient's serum lipid levels. The Japan Lipid Intervention Trial study of simvastatin is the first nationwide investigation of the relationship between serum lipid levels and the development of CHD in Japanese patients with hypercholesterolemia. Of 5,127 patients, exclusively with a history of documented CHD at enrollment, 4,673 were treated with open-labeled simvastatin at an initial dose of 5-10 mg/day and were monitored for 6 years. The risk of coronary events tended to be higher in patients with a serum total cholesterol (TC) > or =240 mg/dl compared with total cholesterol <240 mg/dl. The concentration of low-density lipoprotein cholesterol (LDL-C) positively correlated and that of high-density lipoprotein cholesterol (HDL-C) inversely correlated with the risk of CHD. Each 10 mg/dl decrease in LDL-C and each 10 mg/dl increase in HDL-C concentration reduced the risk of CHD by 8.0% (95% confidence interval 3.8-12.0) and 28.3% (95% CI 13.9-40.3), respectively. A reasonable therapeutic strategy to reduce CHD progression in patients with prior CHD under low-dose statin treatment might be regulating the serum LDL-C concentration to at least <120 mg/dl and HDL-C >40 mg/dl, respectively.
In vitro activity of decaplanin (M86-1410), a new glycopeptide antibiotic

The in vitro activity of decaplanin (formerly M86-1410), a novel glycopeptide antimicrobial agent, was tested against 169 gram-positive bloodstream isolates from patients at the University of Iowa Hospitals and Clinics and 12 selected vancomycin-resistant strains. Enterococcus faecalis, E. faecium, Staphylococcus aureus, streptococci, bacilli, corynebacteria, and listeria were inhibited by decaplanin (MICs for 90% of the strains tested [MIC90s], 0.12 to 4 micrograms/ml). However, some rarely isolated and selected Enterococcus sp. populations had a MIC90 of 16 micrograms/ml, and S. haemolyticus strains had a MIC90 of 8 micrograms/ml. These in vitro results suggest that decaplanin may be useful against most gram-positive strains, even though some Enterococcus species and coagulase-negative staphylococci were potentially resistant (MICs, greater than or equal to 8 micrograms/ml).
Wind speed forecasting in overhead lines for system operation

Wind power has a significant impact on the operation of power grids. As the operation is planned some hours in advance, it is necessary to forecast the wind power. Besides, wind power forecasting techniques can be adapted for the overhead line rating forecasting. This can be useful for defining advanced strategies for grid operation and improve the power integration. This paper describes several works carried out in the forecasting of the wind speed for the overhead line rating. Some of the methods used for the forecasting are implemented in a pilot line and the results are analyzed.
Changing Environmental Influences on Substance Use Across Development

Abstract In contrast to many phenotypes that have been studied using twin designs, substance use shows considerable evidence of environmental influence. Accordingly, specifying the relevant environments and understanding the nature of their effects is an important research priority. Twin studies also have demonstrated that the importance of genetic and environmental influences varies across development for a variety of behavioral outcomes, including substance use. Here, we report analyses exploring moderating effects associated with parenting and peer characteristics on adolescent smoking and drinking, measured at ages 14 and 17. We find significant evidence of moderating effects associated with two dimensions of parenting (parental monitoring and time spent in activities with parents) on adolescent smoking, measured at two time points across development, but no moderating effects on adolescent drinking. Genetic influences on smoking increased, and common environmental effects decreased, as adolescents reported less parental monitoring and spending more time with their parents. Conversely, we find evidence that adolescent drinking is more strongly influenced by peer characteristics. The importance of genetic predispositions was increased among adolescents who reported more friends who used alcohol. These analyses illustrate the importance of incorporating measured aspects of the environment into genetically informative twin models to begin to understand how specific environments are related to various outcomes. Furthermore, they illustrate the importance of using a developmental perspective to understand how specific influences may vary across different ages, and across different phenotypes.
Epithelial NF-κB signaling promotes EGFR-driven lung carcinogenesis via macrophage recruitment

ABSTRACT Several studies have demonstrated that NF-κB activation is common in lung cancer; however, the mechanistic links between NF-κB signaling and tumorigenesis remain to be fully elucidated. We investigated the function of NF-κB signaling in epidermal growth factor receptor (EGFR)-mutant lung tumors using a transgenic mouse model with doxycycline (dox)-inducible expression of oncogenic EGFR in the lung epithelium with or without a dominant inhibitor of NF-κB signaling. NF-κB inhibition resulted in a significant reduction in tumor burden in both EGFR tyrosine kinase inhibitor (TKI)-sensitive and resistant tumors. However, NF-κB inhibition did not alter epithelial cell survival in vitro or in vivo, and no changes were detected in activation of EGFR downstream signaling pathways. Instead, we observed an influx of inflammatory cells (macrophages and neutrophils) in the lungs of mice with oncogenic EGFR expression that was blocked in the setting of NF-κB inhibition. To investigate whether inflammatory cells play a role in promoting EGFR-mutant lung tumors, we depleted macrophages and neutrophils during tumorigenesis and found that neutrophil depletion had no effect on tumor formation, but macrophage depletion caused a significant reduction in tumor burden. Together, these data suggest that epithelial NF-κB signaling supports carcinogenesis in a non-cell autonomous manner in EGFR-mutant tumors through recruitment of pro-tumorigenic macrophages.
Investigation of data-driven optical neuromonitoring approach during general anesthesia with sevoflurane

Abstract. Anesthesia monitoring currently needs a reliable method to evaluate the effects of the anesthetics on its primary target, the brain. This study focuses on investigating the clinical usability of a functional near-infrared spectroscopy (fNIRS)-derived machine learning classifier to perform automated and real-time classification of maintenance and emergence states during sevoflurane anesthesia. For 19 surgical procedures, we examine the entire continuum of the maintenance–transition–emergence phases and evaluate the predictive capability of a support vector machine (SVM) classifier during these phases. We demonstrate the robustness of the predictions made by the SVM classifier and compare its performance with that of minimum alveolar concentration (MAC) and bispectral (BIS) index-based predictions. The fNIRS-SVM investigated in this study provides evidence to the usability of the fNIRS signal for anesthesia monitoring. The method presented enables classification of the signal as maintenance or emergence automatically as well as in real-time with high accuracy, sensitivity, and specificity. The features local mean HbTotal, std HbO2, local min Hb and HbO2, and range Hb and HbO2 were found to be robust biomarkers of this binary classification task. Furthermore, fNIRS-SVM was capable of identifying emergence before movement in a larger number of patients than BIS and MAC.
Mechanical Ventilation in Guillain-Barré Syndrome: Does Age Influence Functional Outcome?

Purpose: To examine the effects of age on differences in the clinical course and functional outcome of mechanically ventilated Guillain-Barré syndrome (GBS) patients. Methods: 32 consecutive patients with GBS in need of mechanical ventilation were divided into two groups: (1) 15 patients <65 years, and (2) 17 patients ≥65 years. Length of ventilation, therapy, incidence of bulbar involvement, dysautonomia, preceding infections, need for tracheostomy, mortality, and functional outcome at 1-year follow-up using the Hughes outcome scale were analyzed. Results: The groups were comparable regarding treatment, lesion type, incidence of bulbar involvement, dysautonomia, preceding infections and duration of ventilation. The majority of patients (75%) received combination therapy (intravenous immunoglobulin and plasma exchange). Tracheostomy was performed in 91% of patients. Mortality was higher in older patients (41 vs. 7%; p = 0.02) and overall outcome worse (p = 0.05). Interestingly, once surviving the early, most critical period, older patients functionally recovered as well as younger patients (80% good outcome vs. 86%; p = 0.71). Conclusions: Despite all the advances in intensive care, mortality in older, ventilated GBS patients is still substantial. However, once they have survived the early, most critical period, older patients may recover as well as younger patients. Special care should therefore be taken to prevent and, if present, to vigorously treat complications commonly associated with intensive care treatment of severe GBS in elderly patients.
Compact coupled graphene and porous polyaryltriazine-derived frameworks as high performance cathodes for lithium-ion batteries.

It is highly desirable to develop electroactive organic materials and their derivatives as green alternatives of cathodes for sustainable and cost-effective lithium-ion batteries (LIBs) in energy storage fields. Herein, compact two-dimensional coupled graphene and porous polyaryltriazine-derived frameworks with tailormade pore structures are fabricated by using various molecular building blocks under ionothermal conditions. The porous nanosheets display nanoscale thickness, high specific surface area, and strong coupling of electroactive polyaryltriazine-derived frameworks with graphene. All these features make it possible to efficiently depress the dissolution of redox moieties in electrolytes and to boost the electrical conductivity of whole electrode. When employed as a cathode in LIBs, the two-dimensional porous nanosheets exhibit outstanding cycle stability of 395 mAh g(-1) at 5 A g(-1) for more than 5100 cycles and excellent rate capability of 135 mAh g(-1) at a high current density of 15 A g(-1).
Using genetic programming for symbolic regression to detect climate change signatures

Most often, climate change signals are slow moving (in human terms), low amplitude changes embedded in high amplitude, noisy data. There are many techniques for extracting such signals. This paper introduces a technique which in contrast with empirical methods produces a decomposition of a time series into a set of equations plus a “residual”. This is referred to as stepwise symbolic secomposition (SSD). The extraction of symbolic equations in lieu of empirical functions assists with characterization of time series. This paper takes two examples of climate data, and applies two different techniques for characterising the low amplitude, slow change embedded therein. The record of CO2 levels at Mauna-Loa since March 1958, is used to demonstrate and contrast empirical mode decomposition (EMD), and SSD. The mean monthly tidal gauge records from the small number of gauges which have more than 120 years of data are analysed in more detail by SSD, then three techniques are used to characterize the residual. The techniques are (a) LOESS smoothing, (b) EMD, and (c) high order polynomial regression. SSD uses a genetic programming system called Eureqa from Cornell Creative Machines Lab guided by an information metric, to extract the most compact informative function it can at each step; the process is repeated on the residuals until no sufficiently informative function is found. EMD and SSD are in stark contrast in the order in which signals are decomposed. EMD extracts high frequency components first. SSD extracts components based on a mixture of parsimonious representation and variance explained. EMD leaves a low frequency filtrate of the signal in its residue, SSD tends to operate as a broad band filter, leaving high frequency noise plus a possible low frequency signal. EMD, LOESS and polynomial fitting all serve to extract low frequency components of the signal from this SSD residual. For the set of tidal gauge data, in the absence of a change in global sea level rise, the SSD procedure should randomize all segments of residual signals equally – the residual should be whitened with respect to the initial signal. It is shown however that late 20th century portions of the residuals show behaviour that is consistent with accelerating sea level rise in keeping with the bulk of the literature.
Stimulating cooperation in the iPeer TV architecture

P2P IPTV systems employ P2P networks due to their scalability and potentiality to efficiently deliver different types of content to users. However, since the viability of these networks can be jeopardized by user's selfish behavior, incentive mechanisms to stimulate cooperation among participants are required. This paper proposes two novel incentive mechanisms to the iPeer TV architecture, which were designed to increase cooperation among peers. Results show that the proposed mechanisms are capable of improving cooperation at a low cost, especially in scenarios involving streams demanding small bandwidth.
Polyamines and Nucleic Acids in Gestational Trophoblastic Tumors

To test the relationship between tumor malignancy and content and distribution of polyamines and nucleic acids, 2 forms of human gestational trophoblastic tumors were examined: the hydatidiform mole (self-limited form) and the human choriocarcinoma (invasive form) xenografted into nude mice. The results indicate that there are 2 significant differences between the choriocarcinoma and the mole: 1) the choriocarcinoma is characterized by increased polyamine and nucleic acid levels, 2) the 2 tissues differ in their putrescine:spermidine and spermidine:spermine ratios. There is an increase in polyamines in the urine of mole-bearing patients over that of normal controls. The correlation between putrescine and spermidine with the chorionic gonadotropin indicates that these 2 polyamines reflect the biological activity of the mole.
Channel Measurements and Models for High-Speed Train Communication Systems: A Survey

The recent development of high-speed trains (HSTs) as an emerging high mobility transportation system, and the growing demands of broadband services for HST users, introduce new challenges to wireless communication systems for HSTs. Accurate and efficient channel models considering both large-scale and non-stationary small-scale fading characteristics are crucial for the design, performance evaluation, and parameter optimization of HST wireless communication systems. However, the characteristics of the underlying HST channels have not yet been sufficiently investigated. This paper first provides a comprehensive review of the measurement campaigns conducted in different HST scenarios and then addresses the recent advances in HST channel models. Finally, key challenges of HST channel measurements and models are discussed and several research directions in this area are outlined.
Spectral Contextual Classification of Hyperspectral Imagery With Probabilistic Relaxation Labeling

In this paper, a spectral-spatial classification framework based on probabilistic relaxation labeling using compatibility coefficients is proposed for hyperspectral images. It is a two-stage classifier that uses maximum a posteriori (MAP) estimation to maximize posterior probabilities of classification map obtained in first stage to incorporate spatial information for better classification accuracy. Two different forms of compatibility coefficients based on correlation and mutual information are used for MAP estimation. The initial probability estimates are obtained from probabilistic support vector machine (SVM) classifier. The combination of SVM with MAP estimation is investigated and compared with benchmark Markov random field and extended morphological profile-based approaches and some other recent methods. The experimental results are presented for three airborne hyperspectral images. The results reveal that incorporation of contextual information with both forms of compatibility coefficients statistically significantly improved SVM results. The compatibility coefficients based on correlation produced the best results among the relaxation methods outperforming many existing methods.
Fast, interactive algorithm for segmentation of a series of related images: Application to volumetric analysis of MR images of the heart

Magnetic resonance (MR) cine images of the beating heart have excellent spatial and temporal resolution. Extracting the boundaries of the heart from MR images for volumetric measurements is of considerable interest; however, since the number of images involved is large, tracing the boundaries by hand is tedious and prohibitively time consuming. The authors have developed an interactive method of boundary detection that uses the correlation between the cardiac boundaries on temporally or spatially adjacent images to increase the speed of the process and reproducibility of the measurement. A simulated cine MR study of a phantom (total of 155 images) and cardiac cine studies of two patients (192 images each) were analyzed by two independent observers. Analysis of the phantom data was completed in 5.6 minutes (2.16 seconds per image) by observer 1 and 6.3 minutes (2.4 seconds per image) by observer 2. The percent measurement errors for 31 phantom volumes (30‐120 mL) were 0.96% and 0.83% for observers 1 and 2, respectively. The observers analyzed the patient studies in 14‐23 minutes (4.4‐7.2 seconds per image), with interobserver variabilities of 5.8% and 3.7% for the two patients, respectively. The authors conclude that their flexible, semiautomatic, interactive algorithm allows rapid and reproducible detection of structural boundaries.