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.
![]() |
Early this week, I felt as unprepared as Dunder Mifflin for a Dwight fire drill. |
![]() |
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!