Evidence map›Paper›PMID 41416150›Full record

ReviewSichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition2025

[New Technologies and Application Developments in Sample Pretreatment for Public Health Laboratory Testing].

Yu Shen, Yutong Zhu, Huiling Zhou, Jiankun Cao, Huayin Zhang, Min Jin, Lei Li

Abstract readReviewEnglish Abstract
In one paragraph

Review in Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Yu Shen( 211166) School of Public Health, Key Laboratory of Public Health Safety and Emergency Prevention and Control Technology of Higher Education Institutions in Jiangsu Province, Nanjing Medical University, Nanjing 211166, China.ORCID 0009-0009-5992-288X
Yutong Zhu( 211166) School of Public Health, Key Laboratory of Public Health Safety and Emergency Prevention and Control Technology of Higher Education Institutions in Jiangsu Province, Nanjing Medical University, Nanjing 211166, China.
Huiling Zhou( 211166) School of Public Health, Key Laboratory of Public Health Safety and Emergency Prevention and Control Technology of Higher Education Institutions in Jiangsu Province, Nanjing Medical University, Nanjing 211166, China.
Jiankun Cao( 211166) School of Public Health, Key Laboratory of Public Health Safety and Emergency Prevention and Control Technology of Higher Education Institutions in Jiangsu Province, Nanjing Medical University, Nanjing 211166, China.
Huayin Zhang( 211166) School of Public Health, Key Laboratory of Public Health Safety and Emergency Prevention and Control Technology of Higher Education Institutions in Jiangsu Province, Nanjing Medical University, Nanjing 211166, China.
Min Jin( 211166) School of Public Health, Key Laboratory of Public Health Safety and Emergency Prevention and Control Technology of Higher Education Institutions in Jiangsu Province, Nanjing Medical University, Nanjing 211166, China.
Lei Li( 211166) School of Public Health, Key Laboratory of Public Health Safety and Emergency Prevention and Control Technology of Higher Education Institutions in Jiangsu Province, Nanjing Medical University, Nanjing 211166, China.ORCID 0000-0003-1836-186X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Public health laboratory testing involves a wide range of sample types, complex matrices, diverse target analytes with varying concentrations, and multiple application contexts with different analytical requirements. As a critical step in public health laboratory analysis and testing, sample pretreatment plays a decisive role in ensuring the reproducibility and efficiency of the analytical methods. It directly affects the accuracy, sensitivity, and reliability of testing results, as well as the feasibility of downstream analyses. Traditional sample pretreatment techniques face persistent challenges, including low efficiency, limited throughput, restricted universal applicability, high organic solvent consumption, and poor compatibility with downstream analytical procedures. These limitations constrain their capacity to meet the evolving demands of research and practice in public health and preventive medicine. In recent years, technological advances have focused on improving efficiency and automation, enhancing selectivity and sensitivity, facilitating online testing capabilities, and promoting environmental sustainability. Sample pretreatment techniques in public health laboratory testing have been undergoing progressive upgrades, and numerous novel technologies have emerged. The paper provides a comprehensive review of new technologies and applications in the field. We focused on the development of new materials, the application of artificial intelligence, connections for online processing, and the approaches tailored to the demands of specific testing settings. We also discussed sample processing for omics analyses and mass spectrometry imaging methods relevant to public health laboratory testing. These advances are expected to support the development of greener and higher-throughput sample pretreatment and foster innovation in the public health laboratory testing system.

Indexed as

Public HealthSpecimen HandlingArtificial IntelligenceHumansReproducibility of ResultsApplicationArtificial intelligenceNovel technologyPublic health laboratory testingSample pretreatment

Identifiers

PMID41416150
PMCPMC12709072

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.