Cell death is an essential process where the body gets rid of old or damaged cells. Cell proliferation and death need to be balanced, as an imbalance between the two may lead to cancer or autoimmune diseases.
Cell death was observed in the early 19th century, but there was no experimental evidence to prove it. In 1842, Carl Vogt first discovered cell death in a metamorphic toad; however, it was not termed ‘cell death.’ Scientists discovered different cell death pathways only in the...

Christian de Duve discovered “autophagy,” a process in which cellular components are engulfed by membrane-bound organelles called autophagosomes. The autophagosomes then fuse with lysosomes to digest the enclosed contents. Autophagy is generally activated in cells to prevent cell death. However, cell death is triggered when the damage is beyond repair.
Autophagy and Apoptosis
Autophagy can activate apoptosis. In normal conditions, the autophagy activating protein Beclin-1 and...

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...

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...

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...

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...