Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Search research articles

Related Experiment Video

Updated: Jul 16, 2026

Controlled Microfluidic Environment for Dynamic Investigation of Red Blood Cell Aggregation

Controlled Microfluidic Environment for Dynamic Investigation of Red Blood Cell Aggregation

Published on: June 4, 2015

When Brownian Motion Meets Clinical Laboratory Automation: A DLS-Inspired Autocorrelation Function for Characterizing

Claudia Spoliti¹, Raimondo De Cristofaro^1,2, Enrico Di Stasio^2,3

¹Department of Translational Medicine and Surgery, Catholic University of the Sacred Heart, Largo Francesco Vito 1, 00168 Rome, Italy.

Diagnostics (Basel, Switzerland)

|July 15, 2026

Summary

Related Concept Videos

Drug Concentration Versus Time Correlation

Drug Concentration Versus Time Correlation

The plasma drug concentration-time curve is a crucial tool in pharmacokinetics, representing the drug's concentration in plasma at different time intervals post-administration. This curve illustrates the drug's journey from absorption into the systemic circulation, distribution to body tissues, and eventual elimination through excretion or biotransformation.
Two pivotal parameters are the minimum effective concentration (MEC) and the minimum toxic concentration (MTC). The MEC is the lowest drug...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Bone Mineral Density in Hemophilia and VWD.

Blood advances·2026

Same author

Origin of the High Variability in Sol-Gel Phase Transitions: The Agar Gelation Model.

Gels (Basel, Switzerland)·2026

Same author

Permanent weakness and myopathy in hypokalemic periodic paralysis.

Acta myologica : myopathies and cardiomyopathies : official journal of the Mediterranean Society of Myology·2026

Same author

Dialysis Unit Differences in Post-Dialysis Fatigue Prevalence and Characteristics and Time to Recovery After Dialysis.

Hemodialysis international. International Symposium on Home Hemodialysis·2026

Same author

Association Between Postdialysis Fatigue and Number of Comorbidities and Number and Prevalence of Symptoms.

Hemodialysis international. International Symposium on Home Hemodialysis·2026

Same author

Natural variants of von Willebrand factor R1205 causing von Willebrand disease with accelerated von Willebrand factor clearance: In silico docking models and energetics of the interaction with both LRP1 and GpIb A1 domain.

PLoS computational biology·2025

This study introduces a novel method inspired by Brownian motion to analyze laboratory automation performance. It offers new metrics for real-time monitoring of sample processing and system efficiency beyond traditional turnaround time statistics.

Area of Science:

Laboratory automation
Biomedical engineering
Data analysis

Background:

Laboratory automation enhances productivity and reduces sample turnaround time (TAT).
Conventional TAT statistics like mean and percentiles fail to capture individual sample processing history.
Analyzing sample flow requires advanced methods beyond standard statistical descriptors.

Purpose of the Study:

To develop a novel approach for analyzing sample flow in automated laboratories.
To create metrics for real-time monitoring of automation efficiency.
To provide a tool for evaluating and comparing laboratory automation systems.

Main Methods:

Sample flow was analyzed using an analogy to Brownian motion.
A modified Dynamic Light Scattering (DLS) correlation function was adapted for sample status tracking.

Keywords:

automation chain correlation function dynamic light scattering laboratory efficiency laboratory performance laboratory workflow sample flow turnaround time

Related Experiment Videos

Last Updated: Jul 16, 2026

Controlled Microfluidic Environment for Dynamic Investigation of Red Blood Cell Aggregation

Controlled Microfluidic Environment for Dynamic Investigation of Red Blood Cell Aggregation

Published on: June 4, 2015

Correlation functions were calculated for simulated processing histories.

Main Results:

The DLS-inspired autocorrelation function yielded parameters for system performance and sample status.
These parameters offer quantitative indicators for near-real-time monitoring of automation efficiency.
The method revealed system features not captured by conventional TAT statistics.

Conclusions:

The approach defines measurable metrics for system resilience to operational disruptions.
It allows for evaluation at both global and individual sample levels.
This framework provides a novel tool for assessing and comparing laboratory automation systems.