Monthly Archives: July 2021

Measuring SP-D using the “diameter” function in ImageJ

Methods to assess TEM and AFM images, surfactant proteins A and D

Easy to use, I found this to be the most efficient way to determine the diameter of surfactant protein D dodecamers.  I think it will ultimately be just in between the measurements that correspond to the shorter of the two hexamers, and the longer, which is where it should be.  It is a circle drawn to contact the edge (in this case, the most peripheral part of the carbohydrate domains) of three of the four.  Example below.

One dodecamer (from Arroyo et al), screen print, resampled at 300ppi, image processed in CorelDRAW 19 using the “smart blur”.  This ends up being 136.53nm, very close to what was found for 95 separate measurements of the same image (see mean and sd below)


Deviation, σ: 5.8922403533121
Count, N: 95 (separate processed images, using half a dozen different filters and effects)
Sum, Σx: 12797.82416297
Mean, μ: 134.71393855758
Variance, σ2: 34.7184963812

When the “political wish” becomes a “rosary”

Ultimate order, the cell

Has anyone else noticed a speech pattern from the previous president.  It is like a set of words become a mantra, perhaps a meditative experience, or a soothing mantra, maybe even a prayer list, a mandala, a rosary or prayer beads. The following quote made me think of this.

This is the quote “”The county has, for whatever reason, also refused to produce the network routers. We want the routers, Sonny, Wendy, we got to get those routers, please. The routers. Come on, Kelly, we can get those routers. Those routers. You know what? We’re so beyond the routers, there’s so many fraudulent votes without the routers. But if you got those routers, what that will show, and they don’t want to give up the routers. They don’t want to give them. They are fighting like hell. Why are these commissioners fighting not to give the routers?”

Lycoris squamigera: how fast does the flower spike grow?

Good Grief!, Rants

This lily (which i may wrongly call and august lily, but is well known as a surprise lily, naked lady, resurrection lily, but still confused with an amaryllis belladonna plant) Lycoris squamigera is one of my favorites.  Early spring dense foliage, which dies back (and helps keep weeds out of the flower bed) and then the spike and flower tip come up rapidly at the end of july (at least here in cincinnati it seems to be the end of july).  I was curious about how fast the spike grew (which seemed very fast) and searched but in the many posts did NOT FIND a single reference to any measurements.  So here is a quick and dirty estimate.

Measuring 5 stalks (not a big sample) crudely with a yardstick, at a 14 hour interval (most of it overnight) the plants can grow about one inch in 5 hours.  Also, just a casual observance, the taller the spike the faster the growth, which makes sense, because there are more cells dividing in a larger spike pushing it up faster.

I will post more measurements if i have time… LOL.

Image and signal processing micrographs of SP-D

surfactant proteins A and D

1) The Y axes on these plots are what are generated by ImageJ…. so the y axis apparently depends upon what kind of raster file I have used to get the luminance plots that ImageJ can detect. All y axes can be (should be) normalized either to 0-100 % or to 0-255 grayscale. I don’t know if it matters, but I believe most of the existing hundreds of excel plots have 0-255 (sometimes 300) as their Y axes. THE HEIGHT depends upon all the image factors, including the brightness and ppi of the original image.

2) The X axis is variable as well, SP-D molecules just fall as they may when they are dropped onto the mica grid so there are short arms, twisted arms, touching arms, bent arms, stretched etc etc. Distance of the entire molecule i have measured as a “diameter” defined by any circle that touches three of the four edges of the cross shaped molecule. I would like the x axis to be a composite number (in nanometers) of every arm I have measured (for each microscopic technique). I haven’t gotten that final number yet, but it will be very close to 135nm with a few nm SD. So All the plots need to be adjusted to that X axis.

3) The MAIN goal here is to normalize all the plots that i have and determine mean number of peaks (with some statistical measure of likelihood) from one side of the dodecamer to the other….. and then a) find the width of each set of peaks…. b) the relative height of each set of peaks,

Amerithon challenge: Cantaloupe

Amerithon

Still going, after a couple minor injuries… LOL,  there was one day where i eeked out just 0.2 miles, limping and groaning.  But moving right along, getting close to half way across the USA getting near Cantaloupe Colorado, Rocky Ford region in the southeastern portion of the state.

Verge of a Dream: One candle

Prose and Poems

It kept burning.
One candle that
Held the wish.
Maybe to keep
The others from
The dark.
A shrug unapparent
To most,
for the gift
with your name
on it.
Maybe to build
Humility.
A heart may
Hold me along
With another.
One Anxious child
Amongst the smiling waves
On the gangplank
Shudders, color of
The white life saver.
Maybe it hangs like
Decoration not
To bob in the cold
Ocean.

RLB 07/17/2021

SP-D “fake” model from real micrographs and LUT tables

Methods to assess TEM and AFM images, surfactant proteins A and D

So the process of identifying which filters work well for image processing of AFM and TEMs (shadowed and negative stained) of molecules, it became diverted briefly into an effort to understand the algorithms of signal processing.  (the diversion was short lived, as I will never devote the time to understand them, and am not sure that an in-depth knowledge of them is required for those of us who just want to maximize the basic data that is inherent in our micrographs) I am interested in those filters that present in an unbiased and honest and searchable way (and just for fun, the image above).

The previous post (using an RGB control image to watch the erosion and dilation and alterations in pixels) examined some filters in a simplistic way. This spawned an even more interesting idea which was to use an actual “arm” (trimer) of an actual SP-D molecule as a model.  The choice of this arm is definitely biased, as it is what I have come to think is the mostly likely configuration of the SP-D trimer in terms of LUT plots.  SO while the bias in creating the initial vector illustration is mine, it is based on hundreds and hundreds of LUT plots from images processed in dozens of filters and effects in  more than 10 different image processing programs.  So it is “educated” bias.   The “raster” fill for this vector image (which is created with identical trimers — mirrored and rotated) is an actual AFM image of an SP-D trimer.  That “fake” or “control” SP-D model is below.

The N termini junction is central, beside it are four small peaks (which I am predicting) next is the alleged N-glycosylation peak (4 of them) one per trimer (about which I have not been able to find an answer as to whether this is an all (all three molecules) or none event, or 1+ 2+ or 3+ event, thus producing N glycosylation peaks of various sizes).  Lateral to that are the three predicted peaks cascading in size and width along the greater length of the collagen like domain.  Finally,  the neck (sometimes present as a slope, or small peak, leading to the CRD which definitely can be seen to have “areas of brightness and looks actually lumpy, just like the molecular models would predict”, and can be seen in the raster fill of this vector image.  Round and bell shapes are based on my observations.

The first test of a filter was made in CorelDRAWx5: Bitmap>blur>gaussian blur>10px. Image below.


And just for fun

Image processing programs for microscopy

Methods to assess TEM and AFM images

Image processing programs are so numerous that it is a daunting task to find one that is easy to use, and also provides the basic filters and effects that microscopists (thinking here specifically of those that use TEM, and AFM, the only two with which i am familiar). All the commercial tricks for graphic design are not helpful in enhancing images and data (such as smoothing LUT plots of brightness and contrast, to sharpen edges, and increase the chances of quantifying “real” events.

In a search for affordable (and often free and dedicated) user friendly programs for processing images I have used my own “artificial” image of solid squares and circles (RGB) as well as “real” images from several types of published and original micrographs of two well studied multimers (surfactant protein D and DMBT1 –  from various species).  I do NOT in any way profess to understand the math behind various signal processing libraries used in any of these programs. I only express opinions about how they affect my the images, and enhance retrieval of data that can be otherwise be missed.

What follows is just my opinion but it might provide insight for someone who just wants to find an easy program and use the basic filters and effects,  and it might help someone who wants to use such filters and effects to investigate molecular structure of a particular molecule.

The programs whose filters and effects I studied pretty thoroughly, paid, and free  opensource, and an estimate of how easy it was to process the images and “real” images are to the right. First on the list is CorelDRAW which is a program I have used for almost 3 decades, and Photoshop for almost that long. Both are paid programs that have extensive menus of filters and effects, way beyond what is  practical (and pertinent) for image processing for scientific work. It is difficult to assess the ease of use of those two programs because of their long history and general familarity.  Their effects and filter menus are easy to find and extensive. Their affordability has made them less practical now.

Some institutions provide Adobe licenses for their faculty, staff and students, though a two month personal subscription to Photoshop2021 provided me with enough time to process hundreds of images to compare with earlier Photoshop versions. That said, many of the filters for image processing have not changed in decades either.

Features to look for are those which adjust — the  size, color management (HSL, RGB,  and provide the standard filters and effects, e.g. gaussian blur and median, maximum, minimum, highpass, noise and unsharp mask filters.

CorelDRAW (includes CorelPhotoPaint): There are two ways to process images in Corel. 1) is built into the vector part of the program (CorelDRAW) that has all the most commonly used and relevant filters for image processing.  The separate raster processing portion (CorelPhotoPaint) has a different feel than Photoshop but also has the necessary filters to process images. I have found that CorelDRAW (under current owners) has begun very aggressive popup tactics that are not only annoying but sometimes crash the program.  The current commercial version of Photoshop is really only available on a monthly  subscription.

GAUSSIAN BLUR IS A GREAT FILTER – number of pixels to select depends upon the ppi of your image and your desired effect. All programs above have a blur filter.

This I confirmed when I compared images processed in programs separated in time by at least 10 years. Picking up an old CD of CorelDraw (which includes CorelPhotoPaint) or Photoshop is really pretty sufficient for any processing of TEM or AFM images that one needs and has filters that are similar (or nearly identical) across platforms and time. The algorithms used for these standard filters seem to be part of a library and accessible to programmers creating their own image processing platforms, so there is an underlying uniformity among them all (not withstanding some variations, limits, menu name changes, and the addition of sliders for adjusting levels of filter application.

The order in which filters are applied matters as does the pixel radius relationship of each applied filter and percent applied.  Vector image exported to 300ppi tif (8″ width), imported into CorelDrawx5 and processed –bitmap>sharpen>highpass 50% 10px, then – blur>gaussian blur 3pxr, (left image); or bitmap>blur>gaussian blur 10pxr, then highpass 50% 10px (right image). Bottom image, blur>gaussian blur 3pxr, then highpass 50% 10px.
THE ORDER OF APPLICATION of the filters matters in the cosmetics of the outcome, and may affect outcome.