Miracle-dz/UniFAR-FTUs huggingface dataset:
Skipping breakfast leads to weight loss but also elevated cholesterol compared with consuming daily breakfasts of oat porridge or frosted cornflakes in overweight individuals: a randomised controlled trial

Eating breakfast may reduce appetite, body weight and CVD risk factors, but the breakfast type that produces the greatest health benefits remains unclear. We compared the effects of consuming a high-fibre breakfast, a non-fibre breakfast, or no-breakfast control on body weight, CVD risk factors and appetite. A total of thirty-six overweight participants (eighteen men and eighteen women) (mean age 33·9 (sd 7·5) years, mean BMI 32·8 (sd 4·7) kg/m2) were randomly assigned to consume oat porridge (n = 12), frosted cornflakes (n = 12) or a water control (n = 12) breakfast daily for 4 weeks. Appetite ratings were collected on the first day and weekly thereafter. Before and after the intervention, body weight, composition, blood pressure and resting energy expenditure (REE) were measured and a fasting blood sample was collected. Across the 4 weeks, fullness was higher and hunger was lower in the oat porridge group compared with the control group (P < 0·05). Mean weight change over the intervention was significantly different in the control group (−1·18 (sd 1·16) kg) compared with both the cornflakes (−0·12 (sd 1·34) kg) and oat porridge (+0·26 (sd 0·91) kg) groups (P < 0·05). However, the control group also showed elevated total cholesterol concentrations relative to the cornflakes and oat porridge groups (P < 0·05). There were no differences between groups in changes in body composition, blood pressure, REE or other CVD risk factors. In conclusion, although skipping breakfast led to weight loss, it also resulted in increased total cholesterol concentrations compared with eating either oat porridge or frosted cornflakes for breakfast.
Baseline Motivation Type as a Predictor of Dropout in a Healthy Eating Text Messaging Program

Background Growing evidence suggests that text messaging programs are effective in facilitating health behavior change. However, high dropout rates limit the potential effectiveness of these programs. Objective This paper describes patterns of early dropout in the HealthyYou text (HYTxt) program, with a focus on the impact of baseline motivation quality on dropout, as characterized by Self-Determination Theory (SDT). Methods This analysis included 193 users of HYTxt, a diet and physical activity text messaging intervention developed by the US National Cancer Institute. Descriptive statistics were computed, and logistic regression models were run to examine the association between baseline motivation type and early program dropout. Results Overall, 43.0% (83/193) of users dropped out of the program; of these, 65.1% (54/83; 28.0% of all users) did so within the first 2 weeks. Users with higher autonomous motivation had significantly lower odds of dropping out within the first 2 weeks. A one unit increase in autonomous motivation was associated with lower odds (odds ratio 0.44, 95% CI 0.24–0.81) of early dropout, which persisted after adjusting for level of controlled motivation. Conclusions Applying SDT-based strategies to enhance autonomous motivation might reduce early dropout rates, which can improve program exposure and effectiveness.
Predicting Dark Triad Personality Traits from Twitter Usage and a Linguistic Analysis of Tweets

Social media sites are now the most popular destination for Internet users, providing social scientists with a great opportunity to understand online behaviour. There are a growing number of research papers related to social media, a small number of which focus on personality prediction. To date, studies have typically focused on the Big Five traits of personality, but one area which is relatively unexplored is that of the anti-social traits of narcissism, Machiavellians and psychopathy, commonly referred to as the Dark Triad. This study explored the extent to which it is possible to determine anti-social personality traits based on Twitter use. This was performed by comparing the Dark Triad and Big Five personality traits of 2,927 Twitter users with their profile attributes and use of language. Analysis shows that there are some statistically significant relationships between these variables. Through the use of crowd sourced machine learning algorithms, we show that machine learning provides useful prediction rates, but is imperfect in predicting an individual's Dark Triad traits from Twitter activity. While predictive models may be unsuitable for predicting an individual's personality, they may still be of practical importance when models are applied to large groups of people, such as gaining the ability to see whether anti-social traits are increasing or decreasing over a population. Our results raise important questions related to the unregulated use of social media analysis for screening purposes. It is important that the practical and ethical implications of drawing conclusions about personal information embedded in social media sites are better understood.
A Presurgical Study of Lecithin Formulation of Green Tea Extract in Women with Early Breast Cancer

Epidemiologic data support an inverse association between green tea intake and breast cancer risk. Greenselect Phytosome (GSP) is a lecithin formulation of a caffeine-free green tea catechin extract. The purpose of the study was to determine the tissue distribution of epigallocatechin-3-O-gallate (EGCG) and its effect on cell proliferation and circulating biomarkers in breast cancer patients. Twelve early breast cancer patients received GSP 300 mg, equivalent to 44.9 mg of EGCG, daily for 4 weeks prior to surgery. The EGCG levels were measured before (free) and after (total) enzymatic hydrolysis by HPLC-MS/MS in plasma, urine, breast cancer tissue, and surrounding normal breast tissue. Fasting blood samples were taken at baseline, before the last administration, and 2 hours later. Repeated administration of GSP achieved levels of total EGCG ranging from 17 to 121 ng/mL in plasma. Despite a high between-subject variability, total EGCG was detectable in all tumor tissue samples collected up to 8 ng/g. Median total EGCG concentration was higher in the tumor as compared with the adjacent normal tissue (3.18 ng/g vs. 0 ng/g, P = 0.02). Free EGCG concentrations ranged from 8 to 65.8 ng/mL in plasma (P between last administration and 2 hours after <0.001). Free EGCG plasma levels showed a significant positive correlation with the Ki-67 decrease in tumor tissue (P = 0.02). No change in any other biomarkers was noted, except for a slight increase in testosterone levels after treatment. Oral GSP increases bioavailability of EGCG, which is detectable in breast tumor tissue and is associated with antiproliferative effects on breast cancer tissue. Cancer Prev Res; 10(6); 363–9. ©2017 AACR.
The Impact of Air‐Sea Interactions on the Representation of Tropical Precipitation Extremes

The impacts of air‐sea interactions on the representation of tropical precipitation extremes are investigated using an atmosphere‐ocean‐mixed‐layer coupled model. The coupled model is compared to two atmosphere‐only simulations driven by the coupled‐model sea‐surface temperatures (SSTs): one with 31 day running means (31 d), the other with a repeating mean annual cycle. This allows separation of the effects of interannual SST variability from those of coupled feedbacks on shorter timescales. Crucially, all simulations have a consistent mean state with very small SST biases against present‐day climatology. 31d overestimates the frequency, intensity, and persistence of extreme tropical precipitation relative to the coupled model, likely due to excessive SST‐forced precipitation variability. This implies that atmosphere‐only attribution and time‐slice experiments may overestimate the strength and duration of precipitation extremes. In the coupled model, air‐sea feedbacks damp extreme precipitation, through negative local thermodynamic feedbacks between convection, surface fluxes, and SST.
Photoperiodic Influences on Ultradian Rhythms of Male Siberian Hamsters

Seasonal changes in mammalian physiology and behavior are proximately controlled by the annual variation in day length. Long summer and short winter day lengths markedly alter the amplitude of endogenous circadian rhythms and may affect ultradian oscillations, but the threshold photoperiods for inducing these changes are not known. We assessed the effects of short and intermediate day lengths and changes in reproductive physiology on circadian and ultradian rhythms of locomotor activity in Siberian hamsters. Males were maintained in a long photoperiod from birth (15 h light/day; 15 L) and transferred in adulthood to 1 of 7 experimental photoperiods ranging from 14 L to 9 L. Decreases in circadian rhythm (CR) robustness, mesor and amplitude were evident in photoperiods ≤14 L, as were delays in the timing of CR acrophase and expansion of nocturnal activity duration. Nocturnal ultradian rhythms (URs) were comparably prevalent in all day lengths, but 15 L markedly inhibited the expression of light-phase URs. The period (τ’), amplitude and complexity of URs increased in day lengths ≤13 L. Among hamsters that failed to undergo gonadal regression in short day lengths (nonresponders), τ’ of the dark-phase UR was longer than in photoresponsive hamsters; in 13 L the incidence and amplitude of light-phase URs were greater in hamsters that did not undergo testicular regression. Day lengths as long as 14 L were sufficient to trigger changes in the waveform of CRs without affecting UR waveform. The transition from a long- to a short-day ultradian phenotype occurred for most UR components at day lengths of 12 L–13 L, thereby establishing different thresholds for CR and UR responses to day length. At the UR-threshold photoperiod of 13 L, differences in gonadal status were largely without effect on most UR parameters.
Semi-blind student's t source separation for multichannel audio convolutive mixtures

This paper addresses the problem of multichannel audio source separation in under-determined convolutive mixtures. We target a semi-blind scenario assuming that the mixing filters are known. The convolutive mixing process is exactly modeled using the time-domain impulse responses of the mixing filters. We propose a Student's t time-frequency source model based on non-negative matrix factorization (NMF). The Student's t distribution being heavy-tailed with respect to the Gaussian, it provides some flexibility in the modeling of the sources. We also study a simpler Student's t sparse source model within the same general source separation framework. The inference procedure relies on a variational expectation-maximization algorithm. Experiments show the advantage of using an NMF model compared with the sparse source model. While the Student's t NMF source model leads to slightly better results than our previous Gaussian one, we demonstrate the superiority of our method over two other approaches from the literature.
The Role of High Dose Intratympanic Dexamethasone as Salvage Therapy for Idiopathic Sudden Sensorineural Hearing Loss.

OBJECTIVE The aim of this study was to assess the efficacy of a single high dose intratympanic (IT) dexamethasone (DEX) as salvage therapy for idiopathic sudden sensorineural hearing loss (ISSNHL) after unsuccessful treatment with oral corticosteroid (CS). MATERIALS AND METHODS This was a prospective open-label study of 59 patients treated with IT DEX after systemic CS therapy has failed. All patients received high dose (24 mg/mL) IT DEX in a single injection through myringotomy. RESULTS Of the 59 patients, 40.7% showed improvement in their mean pure tone average (PTA) with IT DEX (p=0.005). The difference in the mean PTA after oral CS treatment only from baseline was not statistically significant (p=0.074). The time from onset of hearing loss to the start of therapy was significantly associated with the outcome (p=0.03). CONCLUSION We determined that high dose IT DEX as salvage therapy was beneficial when the primary treatment with oral CS had failed. An early start of the treatment significantly influenced the improvement of hearing.
Discovering Reference Process Models by Mining Process Variants

Recently, a new generation of adaptive Process-Aware Information Systems (PAIS) has emerged, which allows for dynamic process and service changes (e.g., to insert, delete, and move activities and service executions in a running process). This, in turn, has led to a large number of process variants derived from the same model, but differing in structure due to the applied changes. Generally, such process variants are expensive to configure and difficult to maintain. This paper provides a sophisticated approach which fosters learning from past process changes and allows for mining process variants. As a result we obtain a generic process model for which the average distance between this model and the respective process variants becomes minimal. By adopting this generic model in the PAIS, need for future process configuration and adaptation decreases. We have validated the proposed mining method and implemented it in a powerful proof-of-concept prototype.
An ecological approach to preventing human infection: Vaccinating wild mouse reservoirs intervenes in the Lyme disease cycle

Many pathogens, such as the agents of West Nile encephalitis and plague, are maintained in nature by animal reservoirs and transmitted to humans by arthropod vectors. Efforts to reduce disease incidence usually rely on vector control or immunization of humans. Lyme disease, for which no human vaccine is currently available, is a commonly reported vector-borne disease in North America and Europe. In a recently developed, ecological approach to disease prevention, we intervened in the natural cycle of the Lyme disease agent (Borrelia burgdorferi) by immunizing wild white-footed mice (Peromyscus leucopus), a reservoir host species, with either a recombinant antigen of the pathogen, outer surface protein A, or a negative control antigen in a repeated field experiment with paired experimental and control grids stratified by site. Outer surface protein A vaccination significantly reduced the prevalence of B. burgdorferi in nymphal blacklegged ticks (Ixodes scapularis) collected at the sites the following year in both experiments. The magnitude of the vaccine's effect at a given site correlated with the tick infection prevalence found on the control grid, which in turn correlated with mouse density. These data, as well as differences in the population structures of B. burgdorferi in sympatric ticks and mice, indicated that nonmouse hosts contributed more to infecting ticks than previously expected. Thus, where nonmouse hosts play a large role in infection dynamics, vaccination should be directed at additional species.
Probiotic supplementation decreases intestinal transit time: meta-analysis of randomized controlled trials.

AIM To determine the efficacy of probiotic supplementation on intestinal transit time (ITT) and to identify factors that influence these outcomes. METHODS A systematic review of randomized controlled trials (RCTs) of probiotic supplementation that measured ITT in adults was conducted by searching MEDLINE and EMBASE using relevant key word combinations. Main search limits included RCTs of probiotic supplementation in healthy or constipated adults that measured ITT. Study quality was assessed using the Jadad scale. A random effects meta-analysis was performed with standardized mean difference (SMD) of ITT between probiotic and control groups as the primary outcome. Meta-regression and subgroup analyses were conducted to examine the impact of moderator variables on ITT SMD. RESULTS A total of 11 clinical trials with 13 treatment effects representing 464 subjects were included in this analysis. Probiotic supplementation was associated with decreased ITT in relation to controls, with an SMD of 0.40 (95%CI: 0.20-0.59, P < 0.001). Constipation (r (2) = 39%, P = 0.01), higher mean age (r (2) = 27%, P = 0.03), and higher percentage of female subjects (r (2) = 23%, P < 0.05) were predictive of decreased ITT with probiotics in meta-regression. Subgroup analyses demonstrated statistically greater reductions in ITT with probiotics in subjects with vs without constipation and in older vs younger subjects [both SMD: 0.59 (95%CI: 0.39-0.79) vs 0.17 (95%CI: -0.08-0.42), P = 0.01]. Medium to large treatment effects were identified with Bifidobacterium Lactis (B. lactis) HN019 (SMD: 0.72, 95%CI: 0.27-1.18, P < 0.01) and B. lactis DN-173 010 (SMD: 0.54, 95%CI: 0.15-0.94, P < 0.01) while other single strains and combination products yielded small treatment effects. CONCLUSION Overall, short-term probiotic supplementation decreases ITT with consistently greater treatment effects identified in constipated or older adults and with certain probiotic strains.
Researchers’ participation in and motivations for engaging with research information management systems

Researchers’ participation in online RIMSs This article examined how researchers participated in research information management systems (RIMSs), their motivations for participation, and their priorities for those motivations. Profile maintenance, question-answering, and endorsement activities were used to define three cumulatively increasing levels of participation: Readers, Record Managers, and Community Members. Junior researchers were more engaged in RIMSs than were senior researchers. Postdocs had significantly higher odds of endorsing other researchers for skills and being categorized as Community Members than did full and associate professors. Assistant professors were significantly more likely to be Record Managers than were members of any other seniority categories. Finally, researchers from the life sciences showed a significantly higher propensity for being Community Members than Readers and Record Managers when compared with researchers from engineering and the physical sciences, respectively. Researchers’ motivations to participate in RIMSs When performing activities, researchers were motivated by the desire to share scholarship, feel competent, experience a sense of enjoyment, improve their status, and build ties with other members of the community. Moreover, when researchers performed activities that directly benefited other members of a RIMS, they assigned higher priorities to intrinsic motivations, such as perceived self-efficacy, enjoyment, and building community ties. Researchers at different stages of their academic careers and disciplines ranked some of the motivations for engaging with RIMSs differently. The general model of research participation in RIMSs; the relationships among RIMS activities; the motivation scales for activities; and the activity, seniority, and discipline-specific priorities for the motivations developed by this study provide the foundation for a framework for researcher participation in RIMSs. This framework can be used by RIMSs and institutional repositories to develop tools and design mechanisms to increase researchers’ engagement in RIMSs.
Combinatorial interaction network of transcriptomic and phenotypic responses to nitrogen and hormones in the Arabidopsis thaliana root

Multivariate analysis reveals a hormone- and nutrient-regulated network that shapes root architecture. A nitrogen-hormone interaction network in plants Both intrinsic factors, such as hormones, and extrinsic factors, such as water and nutrient availability, shape plant development. Ristova et al. evaluated the short-term transcriptional responses and the long-term developmental responses of Arabidopsis thaliana roots to the nitrogen-containing nutrients nitrate and ammonium and the hormones auxin, cytokinin, and abscisic acid. The authors identified genes that were stimulated or inhibited in response to each single factor and to all possible combinations of these three hormones and two nitrogen sources. By combining these transcriptomic data with quantification of changes in root architecture after each treatment, the authors built a multivariate network model of the interaction between nitrogen and hormones that may predict changes in the architecture response of the Arabidopsis root. These data will be useful for future studies on the molecular mechanisms that mediate these interactions and may help identify combinations of nutrients and hormones that improve plant growth under specific environmental conditions. Plants form the basis of the food webs that sustain animal life. Exogenous factors, such as nutrients and sunlight, and endogenous factors, such as hormones, cooperate to control both the growth and the development of plants. We assessed how Arabidopsis thaliana integrated nutrient and hormone signaling pathways to control root growth and development by investigating the effects of combinatorial treatment with the nutrients nitrate and ammonium; the hormones auxin, cytokinin, and abscisic acid; and all binary combinations of these factors. We monitored and integrated short-term genome-wide changes in gene expression over hours and long-term effects on root development and architecture over several days. Our analysis revealed trends in nutrient and hormonal signal crosstalk and feedback, including responses that exhibited logic gate behavior, which means that they were triggered only when specific combinations of signals were present. From the data, we developed a multivariate network model comprising the signaling molecules, the early gene expression modulation, and the subsequent changes in root phenotypes. This multivariate network model pinpoints several genes that play key roles in the control of root development and may help understand how eukaryotes manage multifactorial signaling inputs.
Experimental Demonstration of Simultaneous Modulation Format/Symbol Rate Identification and Optical Performance Monitoring for Coherent Optical Systems

Transmission systems that use advanced complex modulation schemes and digital coherent receivers, have been driving the growth of optical communication networks for nearly a decade. In this fact, new strategies for network diagnosis and management are developed. In this paper, we propose and experimentally demonstrate a cost-effective technique that not only exhibits optical performance monitoring functionalities but also enables simultaneous symbol rate and modulation format identification. It is implemented for both dual-polarized quadrature phase shift keying and 16-quadrature amplitude modulation at various symbol rates. Our approach is based on artificial neural networks (ANNs) in conjunction with asynchronous amplitude histogram (AAH) evaluation. Our ANN-based pattern recognition algorithm, with all of the features of AAHs, facilitates both symbol rate and modulation format classification at high data rates. Experimental investigation demonstrates accurate classification of advanced modulation formats, in the presence of various link impairments. The latter include chromatic dispersion (CD) varying from 200 to 1600 ps/nm, differential group delay between 10 and 70 ps, phase noise varying from 10 kHz to 10 MHz and amplified spontaneous emission noise. The results of the aforementioned method demonstrate multiimpairment monitoring over wide monitoring ranges. At high symbol rates, after a precise extraction of monitoring parameters (i.e., $F_{\text{CD}}$ and $F_{\text{OSNR}}$), our approach achieved a minimum dispersion parameter close to 0.2 dB and a maximum performance parameter of 6 dB. Our technique is robust and transparent for both the symbol rates and the modulation formats.