Fluorescence, pigment and microscopic characterization of Bering Sea phytoplankton community structure and photosynthetic competency in the presence of a Cold Pool during summer

Spectral fluorescence measurements of phytoplankton chlorophyll a (Chl a), phytoplankton phycobilipigments and variable fluorescence (Fv/Fm), are utilized with High Performance Liquid Chromatography (HPLC) estimates of phytoplankton pigments and microscopic cells counts to construct a comprehensive picture of summer-time phytoplankton communities and their photosynthetic competency in the eastern Bering Sea shelf. Although the Bering Sea was ice-free during our study, the exceptionally cold winter that preceded the summer of 2008 when our cruise took place, facilitated the formation of a “Cold Pool” (<2 °C) and its entrapment at depth in the northern middle shelf. The presence of a strong pycnocline over the entire middle and outer shelves restricted inorganic nutrient fluxes into the surface waters resulting in phytoplankton populations that were photo-physiologically stressed due to nutrient limitation. Elevated Chl a concentrations recorded in the Green Belt along the shelf edge of the Bering Sea, were due to Phaeocystis pouchetii and nano-sized cryptophytes. Although inorganic nutrients were not limiting in the Green Belt, Fv/Fm values were low in all probability due to iron limitation. Phytoplankton communities in the low biomass surface waters of the middle shelf were comprised of prasinophytes, haptophytes, cryptophytes and diatoms. In the northern part of the middle shelf, a sinking bloom made up of the centric diatoms Chaeotoceros socialis, Thalassiosira nordenskioeldii and Porosira glacialis was located above the Cold Pool. The high biomass associated with this senescent bloom and its accretion above the pycnocline, suggests that the Cold Pool acts as a barrier, preventing sinking phytoplankton from reaching the bottom where they can become available to benthic organisms. We further posit that if summer-time storms are not energetic enough and the Cold Pool is not eroded, its presence facilitates the transfer of the large spring phytoplankton bloom to the pelagic ecosystem

Effects of Flow Cytometric Analysis on Morphology and Viability of Fragile Phytoplankton

We assessed damage done to especially delicate marine phytoplankton cells by passage through a Coulter Epics V flow cytometer. The cells did not distort or lyse after exposure to fluidics or to laser light to 1,000 mW. The cells did sustain damage evidenced by temporary growth rate depressions. The four clones tested eventually resumed control growth rates after growth lags to 48 h

School-based physical activity in relation to active travel – a cluster randomized controlled trial among adolescents enrolled in the school in motion study in Norway

Abstract Background Active travel and school settings are considered ideal for promoting physical activity. However, previous research suggests limited effect of school-based interventions on overall physical activity levels among adolescents. The relationship between physical activity in different domains remains inconclusive. In this study, we examined the effects of adding two weekly hours of school-based physical activity on active travel rates. Method We analyzed data from 1370 pupils in the 9th-grade participating in the cluster RCT; the School In Motion (ScIM) project. Intervention schools (n = 19) implemented 120 min of class-scheduled physical activity and physical education, in addition to the normal 2 hours of weekly physical education in the control schools (n = 9), for 9 months. Active travel was defined as pupils who reported walking or cycling to school, while motorized travel was defined as pupils who commuted by bus or car, during the spring/summer half of the year (April–September), or autumn/winter (October–February). The participants were categorized based on their travel mode from pretest to posttest as; maintained active or motorized travel (“No change”), changing to active travel (motorized-active), or changing to motorized travel (active-motorized). Multilevel logistic regression was used to analyze the intervention effect on travel mode. Results During the intervention period, most participants maintained their travel habits. In total, 91% of pupils maintained their travel mode to school. Only 6% of pupils switched to motorized travel and 3% switched to active travel, with small variations according to season and trip direction. The intervention did not seem to influence the likelihood of changing travel mode. The odds ratios for changing travel habits in spring/summer season were from active to motorized travel 1.19 [95%CI: 0.53–2.15] and changing from motorized to active travel 1.18 [0.30–2.62], compared to the “No change” group. These findings were consistent to and from school, and for the autumn/winter season. Conclusion The extra school-based physical activity does not seem to affect rates of active travel among adolescents in the ScIM project. Trial registration Clinicaltrials.gov ID nr: NCT03817047. Registered 01/25/2019′ retrospectively registered’

Characteristics of reproductive hormones according to BMI group, and associations between BMI and serum hormone levels by multiple linear regression.

<p>T, testosterone; FAI, free androgen index; SHBG, sex hormone binding globulin; FSH, follicle stimulating hormone; LH, luteinizing hormone; AMH, anti-Müllerian hormone; B, regression coefficient; CI, confidence interval.</p><p>Associations tested by multiple linear regression were adjusted for age. All variables in the regression analyses were continuous variables.</p><p>^a, log transformed data.</p><p>Characteristics of reproductive hormones according to BMI group, and associations between BMI and serum hormone levels by multiple linear regression.</p

Characteristics of semen parameters according to BMI groups, comparison between group 1 and group 4, and associations between BMI and semen parameters by multiple linear regression.

<p>BMI, body mass index; DFI, DNA fragmentation index; B, regression coefficient; CI, confidence interval.</p><p>P-values for differences between group 1 and group 4 were calculated by Mann-Whitney U test. Associations tested by multiple linear regression were adjusted for age and time of abstinence. All variables in the regression analyses were continuous.</p><p>^a, log transformed data</p><p>^b, square root transformed data</p><p>Characteristics of semen parameters according to BMI groups, comparison between group 1 and group 4, and associations between BMI and semen parameters by multiple linear regression.</p

Characteristics of the participants according to BMI groups.

<p>BMI, body mass index.</p><p>Characteristics of the participants according to BMI groups.</p

Proportions of normal weight and severely obese men with semen parameters below the WHO lower reference limits [38].

<p>χ², Chi-square value; df, degrees of freedom.</p><p>n (%), number (percentage) of participants with sperm characteristics below WHO lower reference limit/ group total.</p><p>Associations were tested by Chi-square test with Yates’ correction for continuity.</p><p>Proportions of normal weight and severely obese men with semen parameters below the WHO lower reference limits [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0130210#pone.0130210.ref038" target="_blank">38</a>].</p

Characteristics of reproductive hormones according to BMI group, and associations between BMI and serum hormone levels by multiple linear regression.

<p>T, testosterone; FAI, free androgen index; SHBG, sex hormone binding globulin; FSH, follicle stimulating hormone; LH, luteinizing hormone; AMH, anti-Müllerian hormone; B, regression coefficient; CI, confidence interval.</p><p>Associations tested by multiple linear regression were adjusted for age. All variables in the regression analyses were continuous variables.</p><p>^a, log transformed data.</p><p>Characteristics of reproductive hormones according to BMI group, and associations between BMI and serum hormone levels by multiple linear regression.</p