Meteorological and chemical factors controlling ozone formation in Seoul during MAPS-Seoul 2015

To understand the chemical mechanisms of controlling factors in ozone (O3) formation in early summer in Seoul, a comprehensive study encompassing measurement and modeling was conducted under the Megacity Air Pollution Study-Seoul (MAPS-Seoul) campaign. From May 18 to June 12, 2015, O3 and peroxyacetyl nitrate (PAN) were measured, along with their precursors, including NOx and volatile organic compounds (VOCs), at the Korea Institute of Science and Technology, located in northeast Seoul. VOCs were sampled in a canister twice a day (at 09:30 and 15:00) and analyzed via gas chromatography. The meteorological conditions and chemical regimes of the air masses were clearly distinguished during the study period. In May, NOx concentrations were higher with more pronounced diurnal cycles of precursors and O3 under constant westerly winds. By contrast, stagnant conditions developed in June, which reduced the inflow of primary emissions from the downtown area but increased the influence from the neighboring forest under high temperatures. As a result, the ratio of O3 to odd oxygen was higher in June, indicating a less efficient removal of O3 by NOx. In the same context, the air mass was chemically more aged with a higher NO2/NOx ratio and enhanced OH reactivity of oxygenated and biogenic VOCs in June. The overall measurement results suggest that O3 formation is slightly more sensitive to VOCs than to NOx in Seoul during this season, when O3 concentrations are the highest of the year

Encoding of physics concepts: Concreteness and presentation modality reflected by human brain dynamics

Previous research into working memory has focused on activations in different brain areas accompanying either different presentation modalities (verbal vs. non-verbal) or concreteness (abstract vs. concrete) of non-science concepts. Less research has been conducted investigating how scientific concepts are learned and further processed in working memory. To bridge this gap, the present study investigated human brain dynamics associated with encoding of physics concepts, taking both presentation modality and concreteness into account. Results of this study revealed greater theta and low-beta synchronization in the anterior cingulate cortex (ACC) during encoding of concrete pictures as compared to the encoding of both high and low imageable words. In visual brain areas, greater theta activity accompanying stimulus onsets was observed for words as compared to pictures while stronger alpha suppression was observed in responses to pictures as compared to words. In general, the EEG oscillation patterns for encoding words of different levels of abstractness were comparable but differed significantly from encoding of pictures. These results provide insights into the effects of modality of presentation on human encoding of scientific concepts and thus might help in developing new ways to better teach scientific concepts in class. © 2012 Lai et al

A trial for the use of qigong in the treatment of pre and mild essential hypertension: a study protocol for a randomized controlled trial

<p>Abstract</p> <p>Background</p> <p>Hypertension is a risk factor for cardiovascular disease, and the prevalence of hypertension tends to increase with age. Current treatments for hypertension have side effects and poor adherence. Qigong has been studied as an alternative therapy for hypertension; however, the types of qigong used in those studies were diverse, and there have not been many well-designed randomized controlled trials.</p> <p>Our objectives are the following: 1) To evaluate the effects of qigong on blood pressure, health status and hormone levels for pre- or mild hypertension. 2) To test the methodological appropriateness of this clinical trial and calculate a sample size for future randomized trials.</p> <p>Methods</p> <p>Forty subjects with pre- or mild hypertension will be randomized to either the qigong exercise group or the non-treated group. Participants in the qigong group will conduct qigong exercises 5 times per week for 8 weeks, and participants in the non-treated group will maintain their current lifestyle, including diet and exercise. The use of antihypertensive medication is not permitted. The primary endpoint is a change in patient blood pressure. Secondary endpoints are patient health status (as measured by the SF-36 and the MYMOP2 questionnaires) and changes in hormone levels, including norepinephrine, epinephrine, and cortisol.</p> <p>Discussion</p> <p>This study will be the first randomized trial to investigate the effectiveness of qigong exercises for the treatment of pre- and mild hypertension. The results of this study will help to establish the optimal approach for the care of adults with pre- or mild hypertension.</p> <p>Trial registration</p> <p>Clinical Research Information Service KCT0000140</p

A developmental approach to predicting neuronal connectivity from small biological datasets: a gradient-based neuron growth model.

PMCID: PMC3931784 Open Access article: BB/G006652/1 and BB/G006369/1.Relating structure and function of neuronal circuits is a challenging problem. It requires demonstrating how dynamical patterns of spiking activity lead to functions like cognitive behaviour and identifying the neurons and connections that lead to appropriate activity of a circuit. We apply a "developmental approach" to define the connectome of a simple nervous system, where connections between neurons are not prescribed but appear as a result of neuron growth. A gradient based mathematical model of two-dimensional axon growth from rows of undifferentiated neurons is derived for the different types of neurons in the brainstem and spinal cord of young tadpoles of the frog Xenopus. Model parameters define a two-dimensional CNS growth environment with three gradient cues and the specific responsiveness of the axons of each neuron type to these cues. The model is described by a nonlinear system of three difference equations; it includes a random variable, and takes specific neuron characteristics into account. Anatomical measurements are first used to position cell bodies in rows and define axon origins. Then a generalization procedure allows information on the axons of individual neurons from small anatomical datasets to be used to generate larger artificial datasets. To specify parameters in the axon growth model we use a stochastic optimization procedure, derive a cost function and find the optimal parameters for each type of neuron. Our biologically realistic model of axon growth starts from axon outgrowth from the cell body and generates multiple axons for each different neuron type with statistical properties matching those of real axons. We illustrate how the axon growth model works for neurons with axons which grow to the same and the opposite side of the CNS. We then show how, by adding a simple specification for dendrite morphology, our model "developmental approach" allows us to generate biologically-realistic connectomes

Grifonin-1: A Small HIV-1 Entry Inhibitor Derived from the Algal Lectin, Griffithsin

Background: Griffithsin, a 121-residue protein isolated from a red algal Griffithsia sp., binds high mannose N-linked glycans of virus surface glycoproteins with extremely high affinity, a property that allows it to prevent the entry of primary isolates and laboratory strains of T- and M-tropic HIV-1. We used the sequence of a portion of griffithsin's sequence as a design template to create smaller peptides with antiviral and carbohydrate-binding properties. Methodology/Results: The new peptides derived from a trio of homologous β-sheet repeats that comprise the motifs responsible for its biological activity. Our most active antiviral peptide, grifonin-1 (GRFN-1), had an EC50 of 190.8±11.0 nM in in vitro TZM-bl assays and an EC50 of 546.6±66.1 nM in p24gag antigen release assays. GRFN-1 showed considerable structural plasticity, assuming different conformations in solvents that differed in polarity and hydrophobicity. Higher concentrations of GRFN-1 formed oligomers, based on intermolecular β-sheet interactions. Like its parent protein, GRFN-1 bound viral glycoproteins gp41 and gp120 via the N-linked glycans on their surface. Conclusion: Its substantial antiviral activity and low toxicity in vitro suggest that GRFN-1 and/or its derivatives may have therapeutic potential as topical and/or systemic agents directed against HIV-1

Understanding the impact of droughts in the Yarmouk Basin, Jordan: monitoring droughts through meteorological and hydrological drought indices

This article assesses drought status in the Yarmouk Basin (YB), in northern Jordan, using the Standardized Precipitation Index (SPI), the Standardized Water-Level Index (SWI), and the Percent Departure from Normal rainfall (PDNimd) during the years 1993–2014. The results showed that the YB suffers from frequent and irregular periods of drought as variations in drought intensity and frequency have been observed. The SPI results revealed that the highest drought magnitude of − 2.34 appeared at Nuaimeh rainfall station in 1991. This station has also experienced severe drought particularly in years 1995, 1999, 2005, and 2012 with SPI values ranging from − 1.51 to − 1.59. Some other rainfall stations such as Baqura, Ibbin, Khanasiri, Kharja, Mafraq police, Ramtha, Turra, and Umm Qais have also suffered several periods of drought mostly in 1993. The SWI results show the highest extreme drought events in 2001 in Souf well while other extreme drought periods were observed at Wadi Elyabis well in 1994 and at Mafraq well in 1995. As compared to SPI maps, our SWI maps reflect severe and extreme drought events in most years, negatively impacting the groundwater levels in the study area

Change in diet, physical activity, and body weight among young-adults during the transition from high school to college

<p>Abstract</p> <p>Background</p> <p>The freshmen year of college is likely a critical period for risk of weight gain among young-adults.</p> <p>Methods</p> <p>A longitudinal observational study was conducted to examine changes in weight, dietary intake, and other health-related behaviors among first-year college students (n = 186) attending a public University in the western United States. Weight was measured at the beginning and end of fall semester (August – December 2005). Participants completed surveys about dietary intake, physical activity and other health-related behaviors during the last six months of high school (January – June 2005) in August 2005 and during their first semester of college (August – December 2005) in December 2005.</p> <p>Results</p> <p>159 students (n = 102 women, 57 men) completed both assessments. The average BMI at the baseline assessment was 23.0 (standard deviation (SD) 3.8). Although the average amount of weight gained during the 15-week study was modest (1.5 kg), 23% of participants gained ≥ 5% of their baseline body weight. Average weight gain among those who gained ≥ 5% of baseline body weight was 4.5 kg. Those who gained ≥ 5% of body weight reported less physical activity during college than high school, were more likely to eat breakfast, and slept more than were those who did not gain ≥ 5% of body weight.</p> <p>Conclusion</p> <p>Almost one quarter of students gained a significant amount of weight during their first semester of college. This research provides further support for the implementation of education or other strategies aimed at helping young-adults entering college to achieve or maintain a healthy body weight.</p

MiR-122 targets pyruvate kinase M2 and affects metabolism of hepatocellular carcinoma

10.1371/journal.pone.0086872PLoS ONE91-POLN

Distinguishing Asthma Phenotypes Using Machine Learning Approaches.

Asthma is not a single disease, but an umbrella term for a number of distinct diseases, each of which are caused by a distinct underlying pathophysiological mechanism. These discrete disease entities are often labelled as asthma endotypes. The discovery of different asthma subtypes has moved from subjective approaches in which putative phenotypes are assigned by experts to data-driven ones which incorporate machine learning. This review focuses on the methodological developments of one such machine learning technique-latent class analysis-and how it has contributed to distinguishing asthma and wheezing subtypes in childhood. It also gives a clinical perspective, presenting the findings of studies from the past 5 years that used this approach. The identification of true asthma endotypes may be a crucial step towards understanding their distinct pathophysiological mechanisms, which could ultimately lead to more precise prevention strategies, identification of novel therapeutic targets and the development of effective personalized therapies

Protein and lipid MALDI profiles classify breast cancers according to the intrinsic subtype

<p>Abstract</p> <p>Background</p> <p>Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS) has been demonstrated to be useful for molecular profiling of common solid tumors. Using recently developed MALDI matrices for lipid profiling, we evaluated whether direct tissue MALDI MS analysis on proteins and lipids may classify human breast cancer samples according to the intrinsic subtype.</p> <p>Methods</p> <p>Thirty-four pairs of frozen, resected breast cancer and adjacent normal tissue samples were analyzed using histology-directed, MALDI MS analysis. Sinapinic acid and 2,5-dihydroxybenzoic acid/α-cyano-4-hydroxycinnamic acid were manually deposited on areas of each tissue section enriched in epithelial cells to identify lipid profiles, and mass spectra were acquired using a MALDI-time of flight instrument.</p> <p>Results</p> <p>Protein and lipid profiles distinguish cancer from adjacent normal tissue samples with the median prediction accuracy of 94.1%. Luminal, HER2+, and triple-negative tumors demonstrated different protein and lipid profiles, as evidenced by permutation <it>P </it>values less than 0.01 for 0.632+ bootstrap cross-validated misclassification rates with all classifiers tested. Discriminatory proteins and lipids were useful for classifying tumors according to the intrinsic subtype with median prediction accuracies of 80.0-81.3% in random test sets.</p> <p>Conclusions</p> <p>Protein and lipid profiles accurately distinguish tumor from adjacent normal tissue and classify breast cancers according to the intrinsic subtype.</p