Evidence map›Paper›PMID 41725607›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2026

Hierarchical Channeled Graphitized Nanoarchitecture as a Diagnostic Platform for Maternal Fever Warning.

Yiwen Lin, Ning Li, Heyuhan Zhang, Xufang Hu, Zhiqiang Liu, Chunhui Deng

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2026. 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

6 authors.

Yiwen LinDepartment of Chemistry, Fudan University, Shanghai, China.
Ning LiShanghai Key Lab of Reproduction and Development, Shanghai Key Lab of Female Reproductive Endocrine Related Diseases, Obstetrics & Gynecology Hospital of Fudan University, Shanghai, China.
Heyuhan ZhangDepartment of Chemistry, Fudan University, Shanghai, China.
Xufang HuSchool of Chemical Science and Technology, National Demonstration Center for Experimental, Chemistry and Chemical Engineering Education, Yunnan University, Kunming, Yunnan, China.
Zhiqiang LiuShanghai Key Lab of Reproduction and Development, Shanghai Key Lab of Female Reproductive Endocrine Related Diseases, Obstetrics & Gynecology Hospital of Fudan University, Shanghai, China.
Chunhui DengCenter for Medical Research and Innovation, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, Department of Chemistry, Institutes of Biomedical Sciences, Fudan University, Shanghai, China.ORCID https://orcid.org/0000-0002-8704-7543

Funding

National Key R&D Program of China 2024YFA1307503National Key R&D Program of China 2024YFC3405402National Natural Science Foundation of China 22264024National Natural Science Foundation of China 22574028
6 · The paper itself

Abstract

The precision and effectiveness of nano-diagnostic platforms rely on the deliberate design of advanced nanomaterials, aiming to address the clinical challenge, such as sensitive diagnosis of infectious chorioamnionitis-associated fever (CAM) versus non-infectious epidural-related maternal fever (ERMF), while also expanding the scope of nano-diagnostic technologies to include bio-detection like glycomics, which are cohesively linked to disease but require complex procedures. Here, we designed a hierarchically channeled graphitized nanoarchitecture (HPGC-Z67) as a novel nano-diagnostic platform. HPGC-Z67 features high graphitization and interconnected multi-scale channeled structures that facilitate N-glycan retention and mass transfer in expanded porous channels. Notably, compared to traditional protocol, this HPGC-Z67 platform reduces processing time by about 25 min and cost by approximately CNY 30 per plasma sample, making it suitable for large-scale clinical diagnostics. The HPGC-Z67 nano-diagnostic platform enables sensitive extraction of N-glycan profiles from 150 plasma samples. Notably, two pivotal N-glycans are identified, one sensitive to infectious fever (IF-sensitive) and the other to non-infectious fever (n-IF-sensitive), which together enable simultaneous differentiation of ERMF, CAM, and healthy controls with area under the curve values of 0.965 in the training set and 0.914 in the validation set, respectively. This HPGC-Z67 nano-diagnostic platform advances glycomics towards precise diagnostics and timely clinical intervention.

Indexed as

ChorioamnionitisFeverGlycomicsNanostructuresFemaleHumansPolysaccharidesPregnancyPolysaccharidesgraphitized carbonhierarchical porous channelsintrapartum maternal fevermachine learningnano‐diagnostic platformN‐glycan extractionprecise diagnosis

Identifiers

PMID41725607
PMCPMC13159115

What Socratic holds

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LicenceCC BY
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 Socratic graph.