diff --git a/src/collections/programs/lfx-2024/lfx-2024.mdx b/src/collections/programs/lfx-2024/lfx-2024.mdx
index e481e9f1a64df..45b71c8a41eb6 100644
--- a/src/collections/programs/lfx-2024/lfx-2024.mdx
+++ b/src/collections/programs/lfx-2024/lfx-2024.mdx
@@ -185,6 +185,7 @@ Integrate Nighthawk testing with existing CI/CD pipelines for automated performa
 
 ### Service Mesh Performance
 <br/>
+
 #### Service Mesh Performance: Convergence of Network and Graph topologies
 
 - Description: Opens the door to leveraging algorithms in the areas of Centrality, Community Detection, Pathfinding, Topological Link Prediction, etc. Bringing to bear advances made in Machine Learning / AI / recommendation systems, fraud detection could really help to derive meaning and comprehension for future tools. Another example is how ML + graph approaches are used to find and determine the optimal molecular structure of atoms such that desired physical properties are targeted. This approach could be applied to the problem of workload sizing and estimation for service mesh operators and would-be adopters.
@@ -269,6 +270,7 @@ Understand that your challenges will be promoted through CNCF channels, reviewed
 
 ### Meshery
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+
 #### Meshery: End-to-End Testing with Playwright (Round 2)
 
 - Description: Meshery integrates with many other CNCF projects and technologies. Sustaining those integrations is only possible through automation. End-to-end testing with Playwright, GitHub Workflows, and self-documenting test reports is the means to the end of maintaining a healthy state of each of these [Meshery integrations](https://meshery.io/integrations).