Notes

Outcomes of coalescence as well as isospin symmetry about the freezeout regarding nuclei along with their anti-particles.
Depression is a major public health concern in the U.S. and globally. While successful early identification and treatment can lead to many positive health and behavioral outcomes, depression, remains undiagnosed, untreated or undertreated due to several reasons, including denial of the illness as well as cultural and social stigma. With the ubiquity of social media platforms, millions of people are now sharing their online persona by expressing their thoughts, moods, emotions, and even their daily struggles with mental health on social media. Unlike traditional observational cohort studies conducted through questionnaires and self-reported surveys, we explore the reliable detection of depressive symptoms from tweets obtained, unobtrusively. Particularly, we examine and exploit multimodal big (social) data to discern depressive behaviors using a wide variety of features including individual-level demographics. By developing a multimodal framework and employing statistical techniques to fuse heterogeneous sets of features obtained through the processing of visual, textual, and user interaction data, we significantly enhance the current state-of-the-art approaches for identifying depressed individuals on Twitter (improving the average F1-Score by 5 percent) as well as facilitate demographic inferences from social media. Besides providing insights into the relationship between demographics and mental health, our research assists in the design of a new breed of demographic-aware health interventions.Although inspiratory muscle training (IMT) is reported to improve inspiratory muscle strength in humans little has been reported for horses. We tested the hypothesis that IMT would maintain and/or improve inspiratory muscle strength variables measured in Thoroughbreds during detraining. Thoroughbreds from one training yard were placed into a control (Con, n = 3 males n = 7 females; median age 2.2±0.4 years) or treatment group (Tr, n = 5 males, n = 5 females; median age 2.1±0.3 years) as they entered a detraining period at the end of the racing/training season. https://www.selleckchem.com/products/PD-0332991.html The Tr group underwent eight weeks of IMT twice a day, five days per week using custom-made training masks with resistance valves and an incremental threshold of breath-loading protocol. An inspiratory muscle strength test to fatigue using an incremental threshold of breath-loading was performed in duplicate before (T0) and after four (T1) and eight weeks (T2) of IMT/no IMT using a custom-made testing mask and a commercial testing device. Inspiratory measurements included the total number of breaths achieved during the test, average load, peak power, peak volume, peak flow, energy and the mean peak inspiratory muscle strength index (IMSi). link2 Data were analysed using a linear mixed effects model, P≤0.05 significant. There were no differences for inspiratory measurements between groups at T0. Compared to T0, the total number of breaths achieved (P = 0.02), load (P = 0.003) and IMSi (P = 0.01) at T2 had decreased for the Con group while the total number of breaths achieved (P less then 0.001), load (P = 0.03), volume (P = 0.004), flow (P = 0.006), energy (P = 0.01) and IMSi (P = 0.002) had increased for the Tr group. At T2 the total number of breaths achieved (P less then 0.0001), load (P less then 0.0001), volume (P = 0.02), energy (P = 0.03) and IMSi (P less then 0.0001) were greater for the Tr than Con group. In conclusion, our results support that IMT can maintain and/or increase aspects of inspiratory muscle strength for horses in a detraining programme.Convolutional Neural Networks (CNNs) have become a prominent method of AI implementation in medical classification tasks. Grading Diabetic Retinopathy (DR) has been at the forefront of the development of AI for ophthalmology. However, major obstacles remain in the generalization of these CNNs onto real-world DR screening programs. We believe these difficulties are due to use of 1) small training datasets ( less then 5,000 images), 2) private and 'curated' repositories, 3) locally implemented CNN implementation methods, while 4) relying on measured Area Under the Curve (AUC) as the sole measure of CNN performance. To address these issues, the public EyePACS Kaggle Diabetic Retinopathy dataset was uploaded onto Microsoft Azure™ cloud platform. Two CNNs were trained; 1 a "Quality Assurance", and 2. a "Classifier". The Diabetic Retinopathy classifier CNN (DRCNN) performance was then tested both on 'un-curated' as well as the 'curated' test set created by the "Quality Assessment" CNN model. Finally, the sensitivity of the DRCNNs was boosted using two post-training techniques. Our DRCNN proved to be robust, as its performance was similar on 'curated' and 'un-curated' test sets. The implementation of 'cascading thresholds' and 'max margin' techniques led to significant improvements in the DRCNN's sensitivity, while also enhancing the specificity of other grades.Among the genus Actinidia, Actinidia arguta possesses the strongest cold resistance and produces fresh fruit with an intense flavor. link3 To investigate genomic variation that may contribute to variation in phenotypic traits, we performed whole-genome re-sequencing of four A. arguta genotypes originating from different regions in China and identified the polymorphisms using InDel markers. In total, 4,710,650, 4,787,750, 4,646,026, and 4,590,616 SNPs and 1,481,002, 1,534,198, 1,471,304, and 1,425,393 InDels were detected in the 'Ruby-3', 'Yongfeng male', 'Kuilv male', and 'Hongbei male' genomes, respectively, compared with the reference genome sequence of cv 'Hongyang'. A subset of 120 InDels were selected for re-sequencing validation. Additionally, genes related to non-synonymous SNPs and InDels in coding domain sequences were screened for functional analysis. The analysis of GO and KEGG showed that genes involved in cellular responses to water deprivation, sucrose transport, decreased oxygen levels and plant hormone signal transduction were significantly enriched in A. arguta. The results of this study provide insight into the genomic variation of kiwifruit and can inform future research on molecular breeding to improve cold resistance in kiwifruit.BACKGROUND In 2015, there were approximately 40,000 new HIV diagnoses in the United States. Pre-exposure prophylaxis (PrEP) is an effective strategy that reduces the risk of HIV acquisition; however, uptake among those who can benefit from it has lagged. In this study, we 1) compared the characteristics of patients who were prescribed PrEP with individuals newly diagnosed with HIV infection, 2) identified the specialties of practitioners prescribing PrEP, 3) identified metropolitan statistical areas (MSAs) within the US where there is relatively low uptake of PrEP, and 4) reported median amounts paid by patients and third-party payors for PrEP. METHODS AND FINDINGS We analyzed prescription drug claims for individuals prescribed PrEP in the Integrated Dataverse (IDV) from Symphony Health for the period of September 2015 to August 2016 to describe PrEP patients, prescribers, relative uptake, and payment methods in the US. Data were available for 75,839 individuals prescribed PrEP, and findings were extrapolatedor their antiretroviral treatment using publicly sponsored programs. Addressing the affordability of PrEP and otherwise promoting its use among those with indications for PrEP represents an important opportunity to help end the HIV epidemic.Dengue is one of the most important vector-borne diseases, resulting in an estimated hundreds of millions of infections annually throughout the tropics. Control of dengue is heavily dependent upon control of its primary mosquito vector, Aedes aegypti. Innovative interventions that are effective at targeting the adult stage of the mosquito are needed to increase the options for effective control. The use of insecticide-treated curtains (ITCs) has previously been shown to significantly reduce the abundance of Ae. aegypti in and around homes, but the impact of ITCs on dengue virus (DENV) transmission has not been rigorously quantified. A parallel arm cluster-randomized controlled trial was conducted in Iquitos, Peru to quantify the impact of ITCs on DENV seroconversion as measured through plaque-reduction neutralization tests. Seroconversion data showed that individuals living in the clusters that received ITCs were at greater risk to seroconverting to DENV, with an average seroconversion rate of 50.6 per 100 person-years (PY) (CI 29.9-71.9), while those in the control arm had an average seroconversion rate of 37.4 per 100 PY (CI 15.2-51.7). ITCs lost their insecticidal efficacy within 6 months of deployment, necessitating re-treatment with insecticide. Entomological indicators did not show statistically significant differences between ITC and non-ITC clusters. It's unclear how the lack of protective efficacy reported here is attributable to simple failure of the intervention to protect against Ae. aegypti bites, or the presence of a faulty intervention during much of the follow-up period. The higher risk of dengue seroconversion that was detected in the ITC clusters may have arisen due to a false sense of security that inadvertently led to less routine protective behaviors on the part of households that received the ITCs. Our study provides important lessons learned for conducting cluster randomized trials for vector control interventions against Aedes-transmitted virus infections.DNA methylation is a heritable epigenetic modification that plays an essential role in mammalian development. Genomic methylation patterns are dynamically maintained, with DNA methyltransferases mediating inheritance of methyl marks onto nascent DNA over cycles of replication. A recently developed experimental technique employing immunoprecipitation of bromodeoxyuridine labeled nascent DNA followed by bisulfite sequencing (Repli-BS) measures post-replication temporal evolution of cytosine methylation, thus enabling genome-wide monitoring of methylation maintenance. In this work, we combine statistical analysis and stochastic mathematical modeling to analyze Repli-BS data from human embryonic stem cells. We estimate site-specific kinetic rate constants for the restoration of methyl marks on >10 million uniquely mapped cytosines within the CpG (cytosine-phosphate-guanine) dinucleotide context across the genome using Maximum Likelihood Estimation. We find that post-replication remethylation rate constants span approximately two orders of magnitude, with half-lives of per-site recovery of steady-state methylation levels ranging from shorter than ten minutes to five hours and longer. Furthermore, we find that kinetic constants of maintenance methylation are correlated among neighboring CpG sites. Stochastic mathematical modeling provides insight to the biological mechanisms underlying the inference results, suggesting that enzyme processivity and/or collaboration can produce the observed kinetic correlations. Our combined statistical/mathematical modeling approach expands the utility of genomic datasets and disentangles heterogeneity in methylation patterns arising from replication-associated temporal dynamics versus stable cell-to-cell differences.
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