Minocycline Increases in-vitro Cortical Neuronal Cell Survival after Laser Induced Axotomy

Burak Yulug1, Mehmet Ozansoy2,3, Merve Alokten2

  • 1Department of Neurology, Faculty of Medicine, Alanya Alaaddin Keykubat University, Antalya/Alanya, Turkey

Abstract

Insights

Minocycline shows significant neuroprotective effects in vitro, increasing neuronal cell survival after laser-induced injury. This finding offers hope for future studies addressing the challenges in translating animal findings to human therapies.

Area of Science:

  • Neuroscience
  • Pharmacology
  • Cell Biology

Background:

  • Antibiotic therapies show potential for neuroprotection but face challenges due to diverse experimental strategies and lack of standardized trials.
  • No successful clinical applications of neuroprotective candidate molecules have been reported in human patients.

Purpose of the Study:

  • To investigate the neuroprotective effects of minocycline on primary cortical neurons using an in vitro laser axotomy model.
  • To evaluate minocycline's efficacy at different concentrations (1 μM, 10 μM, and 100 μM).

Main Methods:

  • Primary cortical neurons were cultured for 24 hours.
  • Minocycline was added at three concentrations (1 μM, 10 μM, 100 μM) 15 minutes prior to laser axotomy.
  • Neuronal survival was assessed to determine the protective effect of minocycline.

Main Results:

  • Minocycline demonstrated a significant neuroprotective effect at 1 μM and 100 μM concentrations.
  • This study confirms minocycline's neuroprotective capabilities in a standardized in vitro trauma model.

Conclusions:

  • Minocycline increases in vitro neuronal cell survival following laser axotomy, a novel finding.
  • These results have implications for overcoming translational blocks in neuroprotection research between animal and human studies.

Related Concept Videos

Survival Curves01:18

Survival Curves

Survival curves are graphical representations that depict the survival experience of a population over time, offering an intuitive way to track the proportion of individuals who remain event-free at each time point. These curves are widely used in fields such as medicine, public health, and reliability engineering to visualize and compare survival probabilities across different groups or conditions.
The Kaplan-Meier estimator is the most common method for constructing survival curves. This...
698
Survival Tree01:19

Survival Tree

Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a...
418
Increasing Function01:18

Increasing Function

An increasing function exhibits a rise in output values as input values increase. This behavior is depicted graphically as a curve or line that slopes upward from left to right. Such a function satisfies the condition that if x1 < x2, then f(x1) < f(x2), indicating that the function values grow with increasing inputs. This concept is fundamental in understanding growth trends across various domains, such as population dynamics, financial investments, or resource consumption.The...
389
Introduction To Survival Analysis01:18

Introduction To Survival Analysis

Survival analysis is a statistical method used to study time-to-event data, where the "event" might represent outcomes like death, disease relapse, system failure, or recovery. A unique feature of survival data is censoring, which occurs when the event of interest has not been observed for some individuals during the study period. This requires specialized techniques to handle incomplete data effectively.
The primary goal of survival analysis is to estimate survival time—the time...
771
Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
583
Truncation in Survival Analysis01:09

Truncation in Survival Analysis

Truncation in survival analysis refers to the exclusion of individuals or events from the dataset based on specific criteria related to the time of the event. This exclusion can happen in two primary forms: left truncation and right truncation.
Left truncation occurs when individuals who experienced the event of interest before a certain time are not included in the study. This is often due to a "delayed entry" into the study where only those who survive until a certain entry point are...
612