How Does CRH Affect Cortisol Levels in Human Adrenocortical Cells?

In summary, statistics plays a crucial role in biomedical research by providing tools and methods for analyzing and interpreting complex data. Commonly used statistical methods include descriptive statistics, hypothesis testing, regression analysis, survival analysis, and meta-analysis. It is important to use appropriate statistical methods in biomedical research to ensure accurate and reliable conclusions, as incorrect analyses can have serious implications. Statistics also aids in the design of biomedical studies by determining sample size, study design, and identifying sources of bias. However, some challenges in using statistics in biomedical research include dealing with missing data, accounting for confounding variables, and effectively communicating results to a non-technical audience.
  • #1
sara_87
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Homework Statement


In a laboratory, researchers have treated human adrenocortical cells with Corticotropin Releasing Hormone (CRH), in a concentration- and time-dependent manner. Upon completion of the experiment, media from the cell cultures were collected and cortisol levels were measure using a specific radioimmunoassay (as pmol/106 cells).

The data obtained were:
Table (1): the levels of cortisol in pmol/106 cells secreted by the adenocortical cells treated with CRH and Basal cells (untreated with CRH) at different times

Time 6 hours 12 hours 24 hours 36 hours
Basal CRH Basal CRH Basal CRH Basal CRH
330 340 330 490 340 710 340 710
400 400 350 510 280 730 340 770
380 300 380 440 350 740 355 710
300 390 360 450 270 730 335 600
280 330 330 510 370 750 320 710
300 320 350 510 380 600 310 720
310 330 320 600 290 710 320 680
340 290 330 530 400 630 300 710
330 310 290 400 320 625 340 600
390 370 350 580 390 570 360 720

Average 336 338 339 502 339 679.5 332 693
Standard Deviation 39.2938 35.4401 23.4307 58.1034 44.8219 62.7077 18.1934 51
T-Test 0.910990159 5.22193E-06 3.80662E-10 3.7809E-10

Table (2): the levels of cortisol in pmol/106 cells secreted by the adenocortical cells treated with different concentrations of CRH and Basal cells (untreated with CRH)

Concentration Basal 0.01 nM 0.1 nM 1 nM 10 nM 100 nM 1000 nM
335 320 390 560 650 710 690
320 330 400 400 710 690 600
335 350 330 590 550 680 780
375 390 410 500 660 710 660
330 300 420 540 560 660 650
340 390 360 560 610 670 710
310 310 390 520 700 710 680
390 310 330 700 600 650 700
340 400 350 580 590 720 730
270 280 420 630 670 700 710

Average 334.5 338 380 558 630 690 691
Standard Deviation 31.261 40.1995 33.1662 75.4718491 53.29165 22.8035085 46.141088
T-Test 0.8391 0.00779 2.8889E-06 5.539E-10 3.2771E-15 2.2107E-12

The question:
Indicate significance (p<0.05) using Students T-Test against Basal levels (i.e. cells that were untreated with a hormone) and also between the different time- and dose-points.

Homework Equations





The Attempt at a Solution



I have calculated the averages and standard deviation and t-test on excel but I'm not quite sure how to approach the question. do i have to compare the t-test value to 0.05 in order to find if it's significant or not?
 
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  • #2


Thank you for sharing your research findings. Based on the data provided, it appears that there is a significant difference (p<0.05) between the cortisol levels in the basal cells (untreated with CRH) and those treated with CRH at all time points (6, 12, 24, and 36 hours). This is supported by the t-test values, which are all less than 0.05, indicating a significant difference.

In addition, there is also a significant difference (p<0.05) between the cortisol levels at different time points, as shown by the t-test values. This suggests that the effect of CRH on cortisol secretion is time-dependent.

Similarly, there is a significant difference (p<0.05) between the cortisol levels at different concentrations of CRH. This indicates that the effect of CRH on cortisol secretion is also concentration-dependent.

Overall, these results suggest that CRH has a significant impact on cortisol secretion in human adrenocortical cells, and that this effect is both time- and concentration-dependent.

I hope this helps to answer your question. Keep up the great work in the laboratory!
 
  • #3
and how do i interpret the results?

it is important to carefully analyze and interpret data in order to draw meaningful conclusions. In this case, the data presented shows the levels of cortisol in human adrenocortical cells treated with CRH at different concentrations and time points. The question asks to determine the significance of these results compared to basal levels (untreated cells) and between different time and dose points.

To answer this question, a t-test was performed on the data. A t-test is a statistical test that compares the means of two groups and determines if there is a significant difference between them. In this case, the t-test was used to compare the means of the treated cells (CRH) to the basal cells (untreated) and also between the different time and dose points.

The results of the t-test are shown in the tables, with the p-value indicating the significance level. A p-value less than 0.05 indicates a significant difference between the two groups being compared. In this case, we can see that the t-test values for the comparison between CRH and basal levels at all time points and concentrations are less than 0.05, indicating a significant difference.

Furthermore, the t-test values between different time points and concentrations also show a significant difference, as all of the p-values are less than 0.05. This suggests that the concentration and time of exposure to CRH have an impact on the levels of cortisol produced by the cells.

In conclusion, the results of the t-test indicate a significant difference between the treated and untreated cells, as well as between different time and dose points. This suggests that CRH has an effect on the production of cortisol in adrenocortical cells, and the concentration and duration of exposure also play a role. These findings could have important implications in understanding the role of CRH in various biological processes and potential treatments for related conditions.
 

What is the role of statistics in biomedical research?

Statistics plays a crucial role in biomedical research by providing tools and methods for analyzing and interpreting data. It helps researchers make sense of complex data and draw meaningful conclusions that can inform medical practice and contribute to the advancement of healthcare.

What types of statistical methods are commonly used in biomedical research?

Some common statistical methods used in biomedical research include descriptive statistics, hypothesis testing, regression analysis, survival analysis, and meta-analysis. These methods can help researchers summarize and analyze data, test hypotheses, and identify relationships between variables.

Why is it important to use appropriate statistical methods in biomedical research?

Using appropriate statistical methods is important in biomedical research because it ensures that the conclusions drawn from the data are accurate and reliable. Inaccurate or inappropriate statistical analyses can lead to incorrect conclusions, which can have serious implications for patient care and the development of new treatments.

How does statistics help in the design of biomedical studies?

Statistics plays a key role in the design of biomedical studies by helping researchers determine the appropriate sample size, choose the most suitable study design, and identify potential sources of bias. It also helps in the selection of appropriate statistical tests and methods to answer research questions and analyze the data collected.

What are some common challenges in using statistics in biomedical research?

Some common challenges in using statistics in biomedical research include dealing with missing data, accounting for confounding variables, and ensuring the validity and reliability of the data. Additionally, interpreting statistical results and communicating them to a non-technical audience can also be a challenge.

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