Evidence map›Paper›PMID 41940150›Full record

ReviewaBIOTECH2026

Advances and applications in sequencing-based pathogen surveillance.

Hao Luo, Yao Wang, Huiyu Hou, Junbo Yang, Yong-Xin Liu

Abstract readReview
In one paragraph

Review in aBIOTECH, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

5 authors.

Hao LuoGenome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China.
Yao WangGenome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China.
Huiyu HouGenome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China.
Junbo YangGenome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China.
Yong-Xin LiuGenome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ongoing emergence of infectious diseases necessitates cutting-edge diagnostic methodologies. Traditional diagnostic methods are constrained by limited range, lengthy processing times, and inadequate sensitivity. High-throughput sequencing technologies, particularly multiplex polymerase chain reaction (PCR)-based targeted sequencing, have emerged as transformative tools for pathogen detection, offering enhanced sensitivity, specificity, and cost efficiency. However, challenges in primer design, such as dimerization and bias, limit the effectiveness of these approaches. This review explores advances in sequencing technologies, emphasizing the roles of culturomics, metagenomics, and metatranscriptomics in pathogen discovery. We spotlight innovative strategies for error-tolerant primer design that address existing limitations by balancing coverage and specificity, thereby optimizing the multiplex PCR process. Furthermore, integration of artificial intelligence enhances the precision and scalability of sequencing, enabling real-time diagnostics. Collectively, these advances offer promising pathways to bolster global health, food security, and ecological resilience through robust and sustainable pathogen-detection systems.

Indexed as

Artificial intelligenceDiagnostic methodologiesHigh-throughput sequencingPathogen detection

Identifiers

PMID41940150
PMCPMC12973409

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.