Multi-laboratory Stroke
Multi-laboratory Stroke - Related Videos
06:38
The Stroke Preclinical Assessment Network Multi-Laboratory Model of Thromboembolic Stroke with Thrombolysis: TE-MCAo
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2025
To simulate thromboembolic stroke, emboli prepared from heterologous rat blood were injected into the middle cerebral artery, followed by administration of systemic thrombolysis for recanalization. This version of the model is optimized for use in a multi-laboratory network and supports testing multiple candidate therapeutics.
08:14
Modeling Stroke in Mice: Permanent Coagulation of the Distal Middle Cerebral Artery
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Cited by 104 •
2014
Various murine models of middle cerebral artery occlusion (MCAO) are widely used in experimental brain research. Here, we demonstrate the model of transcranial permanent distal MCAO which produces consistent cortical infarction of a size corresponding to damage imposed by the majority of human ischemic strokes.
06:19
Decontamination for Laboratory Biosafety
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2023
Robert M. Rioux and Zhifeng Chen, Pennsylvania State University, University Park, PA Decontamination is essential for laboratory biosafety, as the accumulation of microbial contamination in the laboratory can lead to the transmission of disease. The degree of decontamination can be classified as either disinfection or sterilization. Disinfection aims to eliminate all pathogenic microorganisms, with the exception of bacterial spores on lab surfaces or equipment. Sterilization, on the other hand,...
08:00
Measuring Mass in the Laboratory
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2023
The analytical balance is the common piece of equipment in the scientific laboratory. These highly precise instruments can measure down to ten thousandths or even hundred thousandths of a gram. The triple beam balance is a type of scale that uses counterweights on a three rider beams to counterbalance the sample in the pan. On the other hand, modern analytical balances use a complex system of electronic sensors to accurately mass a substance. The analytical balance is so sensitive that it...
04:32
Exertional Heat Stroke Mouse Model: A Protocol to Study Mechanisms Underlying Exertional Heat Stroke
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2025
In this video we describe a step-by-step protocol to study exertional heat stroke (EHS) in a mouse model.
FAQs
Harmonized protocols make experiments more comparable across independent institutions by aligning how models, experimental conditions, and measurements are handled. This reduces uncertainty about whether differing results reflect genuine biological effects or variations in study design. As a result, consistent findings provide stronger support for proposed mechanisms of neuronal injury, recovery, and treatment response.
Biological variability can cause the same intervention or experimental model to produce different outcomes across laboratories. Examining that variation helps distinguish robust effects from findings that depend on a particular setting or population. This perspective improves interpretation of neuronal injury and recovery mechanisms and can identify conditions under which a potential therapy is more or less effective.
Shared outcome measures give participating laboratories a common basis for evaluating tissue injury, functional effects, recovery, or treatment response. Without comparable measurements, results may be difficult to combine or interpret across institutions. Using aligned outcomes therefore supports reproducibility and helps researchers determine whether an observed pattern is consistent across experiments rather than limited to one laboratory.
Treatment timing can influence how researchers interpret both injury and recovery outcomes. A therapy may appear different when evaluated at different stages of the stroke process, so timing must be considered when comparing results between laboratories. Accounting for this variable helps separate effects related to the intervention itself from effects associated with when it was administered or measured.
A collaborative study begins by coordinating independent institutions around comparable models or clinical data, harmonized protocols, and shared outcome measures. Laboratories then conduct their experiments or analyses under the agreed framework and compare the resulting findings. This workflow allows investigators to examine reproducibility while also assessing how experimental conditions and biological variability influence the overall pattern of results.
It can show whether a proposed mechanism, biomarker, or treatment-related effect remains consistent across independent settings. It may also reveal how biological variability, experimental conditions, or treatment timing shape the outcome. These findings help researchers judge the reliability of evidence before using it to guide biomarker discovery, therapy development, or further translational work.
In neuroscience, multi-laboratory studies provide a stronger test of whether preclinical findings are reproducible and clinically relevant. Comparing results across institutions can expose limitations that might otherwise remain hidden in a single setting. That evidence supports more reliable biomarker discovery and therapy development, while helping researchers decide which findings merit progression toward clinically relevant interventions.