Hey readers!
This week has been probably filled with the most ups and downs I've ever experienced... as you read last week, I started the week despairing about a complication at ASU: I could not run human blood samples in the particle accelerator. And I was getting frustrated.
However, I got a change in perspective... I owe a big thanks to Mrs. Haag, Dr. Herbots, and a few fellow interns like Grady Day and Ryan van Haren. I had been going into the lab daily, but I was just trying to accomplish tasks, and I would get frustrated if they didn't get done. I had forgotten what really mattered -- that I was doing my own experiment, and that even though things didn't go according to plan, I was lucky in a lot of respects. So, I pivoted and pushed harder to collect data and, of course, learn some amazing stuff about HemaDrop™and biomedical engineering. Now, I feel like my research is finally hitting its stride.
So, I'll take you through the work it took this week to get us there -- and then go in to what my Results section should look like.
Without human blood, we focused on using model liquids (like balanced saline solution and canine blood) to take our RBS measurements and then characterizing how human blood, saline, and canine blood dried on our samples. Armed with this new focus and new equipment (mechanical pipettes which deliver controlled volumes of liquid as small as 5 microliters), I am in a groove.
#1 began with a restating of the purpose and what methods were employed to answer the major research questions. By doing this, Acharya clearly showed what he sought to find out, and then explained how he got the results from the methods he employed.
#3 and #2 showed very clear figures with full explanations, so that the figures basically could stand alone. From my Cancer Bio class with Dr. Scaling, I have found that figures are a really really important part of biomedical research papers, as many in the field are familiar with methods you are using, but want to see the results for themselves. #4 does label parts of the RBS Spectra pretty well, but the figures do not stand alone and little quantitative data is shown apart from the graph. To improve upon what I did in that previous paper, I have devised a more rigorous method of calculation of uniformity apart from just comparing spectra visually -- the subtraction method. With this, I can show a bar graph along with a spectra (scatterplot), which will clearly show elemental composition and error levels. Relating back to error is extremely important, as the impetus of the project started with comparing HemaDrop to previous blood tests and even Theranos.
#2 did a fantastic job restating data from the tables/figures in different ways that allowed for a greater understanding of the paper and "planted the seeds" for its conclusion section. By showing data in percentages (i.e., for me error values for measurements), graphs, and raw values, #3 made sure the readers understood the meaning of the results. #4 was lacking these explanations, since I kind of just spilled out a bunch of numbers and calculations without a lot of explanation, which made the paper esoteric and convoluted.
However, both #4 and #5 did a nice job of showing pictures of the samples along with their quantitative data. This practice really made the plots more digestible. #1 had nice graphical displays with keys on how to read the graphs and why the axes/scale were chosen. Again, the figures and explanations in my paper were lacking.
#1, Acharya's thesis, provides a really interesting model for me to present my qualitative results, as he used a mixed study as well. He separated the qualitative data from the quantitative data a lot though, so I think using the qualitative characteristics as signs of quantitative lack of uniformity will allow me to put those sections of my results in better conversation for my conclusion. He used tables very effectively for observations, which I plan on doing.
One element we discussed in class, which no one used were clear examples of specific qualities (for qualitative) or calculations (for quantitative). Space permitting, I think showing an illustrative example of calculations and images will really allow readers to understand my paper better.
Phew -- that was a lot. So, from that I think I will have 3 parts of my results section. (1) 3LCAA data which characterizes the hydrophilicity of the samples, (2) Qualitative coding data, and (3) Quantitative uniformity calculations. Can't wait to show y'all what I have next week!!
So, that's it for this week. I'll leave you with a sick time lapse gif of blood drying that I took last week in video form with a microscope. You can kind of see the film sucking up the water -- which was our initial hypothesis!! HYPER-HYDROPHILICITY WORKS?!?! Stay tuned for more information next week!
This week has been probably filled with the most ups and downs I've ever experienced... as you read last week, I started the week despairing about a complication at ASU: I could not run human blood samples in the particle accelerator. And I was getting frustrated.
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Early this week, I felt as unprepared as Dunder Mifflin for a Dwight fire drill. |
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Let's goooooooo |
Without human blood, we focused on using model liquids (like balanced saline solution and canine blood) to take our RBS measurements and then characterizing how human blood, saline, and canine blood dried on our samples. Armed with this new focus and new equipment (mechanical pipettes which deliver controlled volumes of liquid as small as 5 microliters), I am in a groove.
I looked at some sources in my discipline to find some key qualities of results sections. Here are the sources I decided to investigate:
- Acharya, Ajjya et al. “HemoClear: A New Thin Fluid Film Device to Control Blood Clot Formation.” American Physical Society Fall Meeting - Four Corners. 59, (2014).
(Biomedical engineering thesis at Barrett Honors College of a fellow intern from the Herbots lab. This results section is very useful, as Ajju Acharya discusses the importance of a new technology called HemoClear, uses spectroscopy to measure elemental composition and qualitative observations to compare samples. Used mixed methods) - Depciuch, Joanna et al. “Phospholipid-Protein Balance in Affective Disorders: Analysis of Human Blood Serum Using Raman and FTIR Spectroscopy. A Pilot Study.” Journal of Pharmaceutical and Biomedical Analysis. 131 (2016): 287–296.
(Paper involving the analysis of blood with spectroscopic techniques similar to RBS. Useful, as it shows the best way of portraying Rutherford Backscattering Spectrometry Spectrometry -- which I have to do. Purely quantitative) - Thomas, A. et al. "On-line desorption of dried blood spots coupled to hydrophilic interaction/reversed- phase LC/MS/MS system for the simultaneous analysis of drugs and their polar metabolites." Journal of Separation Science 33, 873 (2010). (Paper discusses the benefits of a new technology for analyzing blood spots with liquid chromatography... presents specific chromatograms with detailed figures including models of the samples. Employed mixed methods.)
- RELATIVELY HEALTHY 17 YEAR OLD INDIAN MALE et al. “Electrolyte Detection by Ion Beam Analysis, in Continuous Glucose Sensors and in Microliters of Blood Using a Homogeneous Thin Solid Film of Blood, HemaDrop™.” MRS Advances (2016): 1–7.(Paper proposes a new technology and tries to demonstrate uniformity of samples with RBS and PIXE. Purely quantitative)
#1 began with a restating of the purpose and what methods were employed to answer the major research questions. By doing this, Acharya clearly showed what he sought to find out, and then explained how he got the results from the methods he employed.
#3 and #2 showed very clear figures with full explanations, so that the figures basically could stand alone. From my Cancer Bio class with Dr. Scaling, I have found that figures are a really really important part of biomedical research papers, as many in the field are familiar with methods you are using, but want to see the results for themselves. #4 does label parts of the RBS Spectra pretty well, but the figures do not stand alone and little quantitative data is shown apart from the graph. To improve upon what I did in that previous paper, I have devised a more rigorous method of calculation of uniformity apart from just comparing spectra visually -- the subtraction method. With this, I can show a bar graph along with a spectra (scatterplot), which will clearly show elemental composition and error levels. Relating back to error is extremely important, as the impetus of the project started with comparing HemaDrop to previous blood tests and even Theranos.
#2 did a fantastic job restating data from the tables/figures in different ways that allowed for a greater understanding of the paper and "planted the seeds" for its conclusion section. By showing data in percentages (i.e., for me error values for measurements), graphs, and raw values, #3 made sure the readers understood the meaning of the results. #4 was lacking these explanations, since I kind of just spilled out a bunch of numbers and calculations without a lot of explanation, which made the paper esoteric and convoluted.
However, both #4 and #5 did a nice job of showing pictures of the samples along with their quantitative data. This practice really made the plots more digestible. #1 had nice graphical displays with keys on how to read the graphs and why the axes/scale were chosen. Again, the figures and explanations in my paper were lacking.
#1, Acharya's thesis, provides a really interesting model for me to present my qualitative results, as he used a mixed study as well. He separated the qualitative data from the quantitative data a lot though, so I think using the qualitative characteristics as signs of quantitative lack of uniformity will allow me to put those sections of my results in better conversation for my conclusion. He used tables very effectively for observations, which I plan on doing.
One element we discussed in class, which no one used were clear examples of specific qualities (for qualitative) or calculations (for quantitative). Space permitting, I think showing an illustrative example of calculations and images will really allow readers to understand my paper better.
Phew -- that was a lot. So, from that I think I will have 3 parts of my results section. (1) 3LCAA data which characterizes the hydrophilicity of the samples, (2) Qualitative coding data, and (3) Quantitative uniformity calculations. Can't wait to show y'all what I have next week!!
So, that's it for this week. I'll leave you with a sick time lapse gif of blood drying that I took last week in video form with a microscope. You can kind of see the film sucking up the water -- which was our initial hypothesis!! HYPER-HYDROPHILICITY WORKS?!?! Stay tuned for more information next week!
dear Yash, your gif is the coolest demo yet on-line of our research. The high light of the week Definitely watching in real-time a metered blood droplet dry for 20 minutes - in our slow version of drying without our secret sauce - *THANK you so much Grady Day for converting us to using sterile pipetting!!! So much better than sterile needles and Drummon capillaries!!* The most remarkable aspect is the "Table Mesa shape of the droplet" of our blood Homogeneous Thin Solid Films ( HTSF) = rapidly rising sidewalls, and than uniform flat enough film for our purpose. What is remarkable about what you found in thinking of videotaping the absorption of H2O molecules with our Hyper-Hydrophilic coating is the demonstrating how the coating absorbs vertically the H2O molecules WITHOUT phase separation, maintaining good uniformity for the scale of our analysis (1 mm2 ion probe). Can't wait to analyze these samples by RBS, but just the optical microscopy is AMAZING!
ReplyDeleteOne additional comment - this gif demonstrates the difference between HYPER-hydrophilic and SUPER-Hydrophilic properties. If the coating was super hydrophilic, we would see the droplet spread faster and flatter and phase separate a bit (as in the picture I just e-mailed to Yash showing canine blood dried on a super hydrophilic surface). BUT on a HYPER-hydrophilic coating *Patent pending Herbots, Peshad et al.., 2016, 2017 the fact is that the H2O is absorbed vertically with respect to the surface, in a drying mechanism, as opposed to horizontally along the surface, in a wetting mechanism. The regularly space radial lines appearing all along the perimeter of the droplet as in a pleated skirt demonstrate how the water is absorbed at a higher rate away from the center of the droplet, and a slower rate near the periphery. That 1/R**Squared dependency of water molecule absorption by the coating is simply due to the fact that the surface density of micropores decreases as 1/R**squared in a circular drop where obviously more micropores in the coating are available on the spread out "skirt" at the edges compared to the center. Beautiful demo of the concept.
ReplyDelete... and outstanding experimental proof of the mechanism and geometric dependency. This is physics at its best, applied to a bio-physics problem of course :D
ReplyDeleteWhat’s up Yampire (get it because it’s Yash+Vampire, and you’re doing research on human blood...ok bad idea).
ReplyDeleteIf Dr. Herbots hadn't beat me to it, I would have said the same exact thing. But, since I was too slow, let me give you some other advice.
First of all, it is always good to admit your mistakes, but it is even better to learn from them. So I admire you for stepping up and roasting that RELATIVELY HEALTHY 17 YEAR OLD INDIAN MALE. Next, I think it is more important if you show examples for your qualitative coding data. Because qualitative data lacks the same sort of credibility and validity as quantitative data, illustrative examples for your qualitative data will be more effective.
I think your project is bloody interesting (sorry) and all your efforts in making that GIF were not in vein (sorry again), cuz’ that was one cool GIF.
Yash,
ReplyDeleteDAMN MAN. You got a lot of stuff done. I think it's great that you're finally getting your research on track and thinking about your results section.
I still have one or two questions though. First, how do you plan on representing the qualitative data in a way that readers can nicely understand the observations that you made. I know quantitative data can be arranged into tables, but you need to think about the qualitative data too.
Also, how will you nicely synthesize the qualitative data with the quantitative data to arrive at a nice conclusion? I think having side by side visual comparisons would be amazing (I don't know if this is even possible) or maybe including a picture and having a quantitative and qualitative interpretation of it. I'm just spitballing.
Anyways, I think you're doing amazing. Keep up the baller work.
Akash
Hi Yash,
ReplyDeleteHappy to hear that your new pipettes got that blood analysis rolling. 3LCAA seems to be essential to your analysis. I like how you will restate the purpose and the methods employed to answer the major research question. Honestly I'm probably gonna do this too. Including the qualitative data is essential to backing up the quantitative results. It will help the reader envision the results. Dr. Herbots sounded extremely technical there, so fill me in later. Qualitative data is extremely difficult to present to a lay crowd because you have to set up a background to them as well. i think you need to build the readers up with examples and walkthroughs before you talk about qualitative data.
-
Ashwath V.
Yash -- I like that you noticed the features of different results sections (also that you acknowledged that you're the "worst kind of arrogant jerk" -- haha, just kidding). However, my concerned is that your articulation of the features reads as a little scatterbrained to me. As in, I didn't see a clear organization guiding your understanding of the results section. I just want you to make sure that you're starting to think of how to organize it and put it together to construct a clear narrative. You have so many different pieces of your methods and results, that if you aren't meticulous about this, it will undoubtedly lose the reader.
ReplyDelete