Review of Green Microextraction Methods for Hormone Analysis
by Vicente Zurdo, David / e-cienciaDatos Harvested Dataverse·Updated 4mo ago
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Description
This review provides an overview of green and emerging microextraction approaches for determining hormones in biological samples. It critically discusses key techniques like solid-phase microextraction (SPME) and dispersive liquid–liquid microextraction (DLLME), followed by HPLC-DAD or HPLC-MS analysis. The work examines applications across various bioanalytical matrices including urine, plasma, serum, saliva, and tissues.
Use Cases
Compare the sensitivity and selectivity of SPME versus DLLME for steroidal hormone extraction from plasma.
Analyze the use of environmentally friendly solvents like deep eutectic solvents (DESs) across different bioanalytical matrices such as urine and saliva.
Evaluate the performance of advanced sorbents including molecularly imprinted polymers (MIPs) for peptide hormone determination in tissues.
Study validation parameters for hormone determination methods discussed in the review to identify method development gaps.
Strengths
The review critically discusses multiple established microextraction techniques (SPME, DLLME) and analytical methods (HPLC-DAD, HPLC-MS).
It covers a wide range of hormone types including steroidal, thyroid, and peptide hormones.
Examines applications across various complex biological matrices such as urine, plasma, serum, saliva, and tissues.
Limitations
The input is a review article, not a primary dataset, so it contains summarized findings rather than raw experimental data.
Specific quantitative data such as sample sizes, validation metrics, or extraction yields are not provided in the input description.
The scope is methodological, focusing on trends and applications, which limits direct use for statistical modeling or machine learning.
Provenance
Source
e-cienciaDatos Harvested Dataverse
Collection Method
Literature review summarizing research on microextraction techniques for hormone analysis.
Time Range
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Freshness
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Geography
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This is a review article or scholarly work, not a tabular dataset. Users seeking raw data for analysis will need to consult the primary research articles referenced within this review.