Schematic summary of results.

(A) Depicts two distinct microenvironments with overlapping emissions (refer to Fig 5). (B) Spectral breadth decreasing with decreasing level of microenvironment heterogeneity (refer to Figs 3 and 4B). (C) The fluorescence of CoroNa Green indicates available Na+ rather than actual concentration in a given cellular region (refer to Fig 1). N = Nucleus.</p

Spectral analysis of control and serum starved myoblast progenitor cells.

(A) Phasor plot depicting the phasor position of control and serum starved cells in the second quadrant of first harmonic. Four cone shaped cursors were utilised to select four distinct λmax values irrespective of the spectral width. (B) Spectral images were produced by remapping the selected emissions in the (A) phasor plot to the original fluorescence images. Notably, the 532, 536, 540 and 544 nm emissions were apparent in both the nucleus and cytoplasm of cells throughout the first 40-minutes post serum starvation.</p

Sodium microenvironment heat map in myoblast progenitor cells induced to differentiate.

(A) Fluorescence images (photons collected in the range of 413–728 nm) depicting lower levels of fluorescence in the nucleus and cytoplasm of cells at 10 and 20 minutes post induction of differentiation relative to control cells and cells at 30 and 40 minutes. White border indicates nucleus and NL = Nucleolus. Regions of interest were isolated, and fluorescence intensity images and spectral heat maps of (B) a transect from the cytoplasmic membrane into the cytosol and (C) the nuclear membrane region, were produced. ‘F’ indicates fluorescence intensity image, while ‘S’ indicates spectral heat map. The heat map depicts areas within the region of interests that share similar spectral properties via pseudo colouring (B and C–‘S’). Dotted circles within isolated areas provide a comparison of specific fluorescence intensities and spectral heat map ‘microenvironments’. Red arrow indicates region with similar fluorescence intensity but different spectral properties.</p

Spectral emission variations as a function of time post serum starvation.

(A) 3D scatter plot was generated by utilising cursors (size = 0.005) to select wavelengths and widths in the phasor plot corresponding to each time course (control: n = 274, 10 min: n = 471, 20 min: n = 519, 30 min: n = 439, 40 min: n = 370). The number of data points collected (n) depended on the shape of the phasor; a condensed phasor resulted in lower ‘n’ value, conversely a more spread out phasor resulted in a higher n value. (B-i) The phasor shape of emissions corresponding to the cell after the removal of background emissions. (B-ii) The phasor shape of emissions corresponding to the background after the removal of the cell emissions. Relative to the cellular emissions, background emissions were apparent near the centre of the plot and exhibited broader widths. (C) A different coloured cursor was utilised to select the most intense region of the phasor plot for each time course, and the emissions were mapped to the original fluorescence images to generate spectral images.</p

CoroNa Green spectral variations with respect to increasing distance from the cytoplasmic membrane.

A line of transect was drawn from 1 μm outside of the cell to the nucleolus. The location of the transect line was varied to ensure equidistance from the extracellular space to the nucleolus in all the time courses. Spectral emissions were isolated by selecting regions along the line of transect at 1 μm increments. Graphs were created by utilising small cursors (size = 0.005) to select λmax and widths on the phasor plot corresponding to the cellular region. (A) Depicts smaller λmax values in the extracellular space and near the cytoplasmic region compared to intracellular regions. (B) Depicts a decrease in the width of emissions with respect to a decrease in the distance from the nucleolus. EC = 1 μm outside of cell, CM = cytoplasmic membrane, and NL = nucleolus.</p

Annual average weight change according to body mass index transition groups among the 1973–1978 cohort of the Australian Longitudinal Study on Women’s Health from 1996 to 2012.

<p>^a mean±SD</p><p>Annual average weight change according to body mass index transition groups among the 1973–1978 cohort of the Australian Longitudinal Study on Women’s Health from 1996 to 2012.</p

Spectral variation with respect to distance from cytoplasmic membrane.

Regions of the spectral image along the transect line (A) at 1 μm increments were isolated and 50 cursors (size = 0.005) were utilised to select emissions on the phasor plot corresponding to the selected regions of interest. (B) The variance of emissions appeared greater in the background (indicated by the largest circle) than the cytoplasmic membrane which was more variable than emissions found within the cell. (C) Removing the background emissions made apparent the difference in the degree of variability between the cytoplasmic membrane emissions compared to regions within the cell. (D) Within the population of emissions found 1–8 μm within the cell, each region’s emissions appeared to converge in non-overlapping parts of the spectrum; however, these λmax did share similar spectral widths. Note that the colour code for each scatter plot changes for each cell region from (B) to (D) as the background and cytoplasmic membrane emission are removed. White dotted line represents the nucleus and the red dotted line represents the nucleolus.</p

Associations of house characteristics with indoor dampness and measured moisture: Results from three New Zealand House Condition Surveys in 2005, 2010 and 2015

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Univariate and multivariable-adjusted association from GEE analysis between BMI and dysmenorrhea among the 1973–1978 cohort of the Australian Longitudinal Study on Women’s Health from 2000 to 2012.

<p>BMI, body mass index, GEE, generalised estimating equations.</p><p>Multivariable-adjusted analysis estimates the effect of the exposure of interest (body mass index) after controlling for sociodemographics (age, education, employment, marital status, language spoken at home, managing income, and history of abuse), lifestyle factors (smoking, illicit drug use and alcohol consumption), reproductive factors (use of oral contraception, parity, age at menarche, and endometriosis).</p><p>Univariate and multivariable-adjusted association from GEE analysis between BMI and dysmenorrhea among the 1973–1978 cohort of the Australian Longitudinal Study on Women’s Health from 2000 to 2012.</p

Baseline body mass index, other characteristics, and the prevalence of dysmenorrhea among women from the 1973–78 cohort of the Australian Longitudinal Study on Women's Health, aged 22–27 years in 2000.

<p>^a percent may not add up to 100% due to rounding.</p><p>Baseline body mass index, other characteristics, and the prevalence of dysmenorrhea among women from the 1973–78 cohort of the Australian Longitudinal Study on Women's Health, aged 22–27 years in 2000.</p