A 6-Step Approach to Gain Higher Quality Results From Organotypic Hippocampal Brain Slices in a Traumatic Brain Injury Model

Abstract

Introduction: Organotypic Hippocampal Brain Slices (OHBS) provide an advantageous alternative to in vivo models to scrutinize Traumatic Brain Injury (TBI). We followed a well-established TBI protocol, but noticed that several factors may influence the results in such a setup. Here, we describe a structured approach to generate more comparable results and discuss why specific eligibility criteria should be applied.

Methods: We defined necessary checkpoints and developed inclusion and exclusion criteria that take the observed variation in such a model into consideration. Objective measures include the identification and exclusion of pre-damaged slices and outliers. Six steps were outlined in this study.

Results: A six-step approach to enhance comparability is proposed and summarized in a flowchart. We applied the suggested measures to data derived from our TBI-experiments examining the impact of three different interventions in 1459 OHBS. Our exemplary results show that through equal requirements set for all slices more precise findings are ensured.

Conclusion: Results in a TBI experiment on OHBS should be analyzed critically as inhomogeneities may occur. In order to ensure more precise findings, a structured approach of comparing the results should be followed. Further research is recommended to confirm and further develop this framework.

Keywords: Eligibility; Framework; In vitro model; Organotypic hippocampal brain slices; Propidium Iodide (PI); Traumatic Brain Injury (TBI).

Figure 1:

Flowchart summarizing the six-step approach The flowchart summarizes the six-step approach; we applied the proposed model to the data derived from our experiments on 1459 OHBS, as mentioned above.

Figure 2.

Example images of steps 2.1: Example image of step 1: This picture is taken at the baseline assessment. A: Shows the image generated by ImageJ software via the red channel. B: shows the same slice after having enhanced the contrast; Figure 2.2: Example image of step 2: Picture A shows a slice at baseline assessment. Due the threshold number of pixels at baseline assessment <1000, this pre-damaged slice was restrained from entering the experiment. Thus, it could be avoided that the picture showing the trauma intensity after the incubation period (B) distorted the final results (B); Figure 2.3 Example image of step 3: Picture A shows a margin, which is probably due to errors within the preparation process. Picture B shows damage which probably occurs inevitably; Figure 2.4: Example image of step 4: Morphological peculiarities include what we called “holes”, “frayed margin”, and “emigrated cells”. These peculiarities are often only seen when the contrast is enhanced (A: picture generated by ImageJ; B: contrast additionally enhanced). The slice in the image (picture taken after the incubation time) shows all three peculiarities. The reason for these phenomena are unknown; Figure 2.5: Example image of step 5: As trauma intensities vary, it is important to set a scope of trauma strength. Picture A is an example of a very weak trauma, and picture B shows one of the slices excluded by the established threshold; Figure 2.6: Example image of step 6: Picture A shows a slice at baseline assessment, which was not excluded by the threshold #pixels at baseline assessment <1000. Picture B shows the same slice after the incubation period. Through the performed boxplot analysis, this slice was identified and excluded eventually.

Figure 3.

Results demonstrate that more precise findings are ascertained Figure 3.1: This image shows the trauma intensity of two non-trauma groups without applying a threshold concerning pre-damage compared to when a threshold is used (step 2). The difference in between the two groups is not significant anymore when the threshold concerning pre-damage is applied (P=0.004 vs. P=0.716); Figure 3.2: This image shows the results of two non-trauma groups before and after taking margins possibly caused by errors in the preparatory process into consideration. Our established threshold (step 3) aims to identify those errors and subtract the cell death of those margin areas. The difference in between the two groups is not significant when those margins are considered (P=0.004 vs. P=0.444); Figure 3.3: This image shows that the difference in between the two trauma groups is not significant when outliers are identified and excluded, as described in step 5. The difference in between the two groups seems to be significant at first glance, but it is not (P<0.001 vs. P=0.304); Figure 3.4: This image shows This image shows that also in the non-trauma groups results can differ when outliers are identified and excluded (step 6). The results show that the difference between the two groups is not as striking as expected at first (P= 0.016 vs. P=0.075).