Evidence map›Paper›PMID 38845582›Full record

ReviewNanoscale2024

Unveiling brain disorders using liquid biopsy and Raman spectroscopy.

Jeewan C Ranasinghe, Ziyang Wang, Shengxi Huang

Abstract readReview
In one paragraph

Review in Nanoscale, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Review
  6. 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

3 authors.

Jeewan C RanasingheDepartment of Electrical and Computer Engineering, Rice University, Houston, TX 77005, USA. shengxi.huang@rice.edu.
Ziyang WangDepartment of Electrical and Computer Engineering, Rice University, Houston, TX 77005, USA. shengxi.huang@rice.edu.
Shengxi HuangDepartment of Electrical and Computer Engineering, Rice University, Houston, TX 77005, USA. shengxi.huang@rice.edu.ORCID http://orcid.org/0000-0002-3618-9074

Funding

SCH: AI-Enhanced Multimodal Sensor-on-a-chip for Alzheimer's Disease DetectionR01AG077016 · NIA · PENNSYLVANIA STATE UNIVERSITY, THE · PI HU, JUEJUN, MA, FENGLONG · 2022 to 2025
$1.2M
NIA NIH HHS R01 AG077016
6 · The paper itself

Abstract

Brain disorders, including neurodegenerative diseases (NDs) and traumatic brain injury (TBI), present significant challenges in early diagnosis and intervention. Conventional imaging modalities, while valuable, lack the molecular specificity necessary for precise disease characterization. Compared to the study of conventional brain tissues, liquid biopsy, which focuses on blood, tear, saliva, and cerebrospinal fluid (CSF), also unveils a myriad of underlying molecular processes, providing abundant predictive clinical information. In addition, liquid biopsy is minimally- to non-invasive, and highly repeatable, offering the potential for continuous monitoring. Raman spectroscopy (RS), with its ability to provide rich molecular information and cost-effectiveness, holds great potential for transformative advancements in early detection and understanding the biochemical changes associated with NDs and TBI. Recent developments in Raman enhancement technologies and advanced data analysis methods have enhanced the applicability of RS in probing the intricate molecular signatures within biological fluids, offering new insights into disease pathology. This review explores the growing role of RS as a promising and emerging tool for disease diagnosis in brain disorders, particularly through the analysis of liquid biopsy. It discusses the current landscape and future prospects of RS in the diagnosis of brain disorders, highlighting its potential as a non-invasive and molecularly specific diagnostic tool.

Indexed as

Spectrum Analysis, RamanBrainBrain DiseasesBrain Injuries, TraumaticHumansLiquid BiopsyNeurodegenerative Diseases

Identifiers

PMID38845582
PMCPMC11290551

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.