Evidence map›Paper›PMID 38174122›Full record

ReviewJournal of pharmaceutical analysis2023

Development status of novel spectral imaging techniques and application to traditional Chinese medicine.

Qi Wang, Yong Zhang, Baofeng Yang

Abstract readReview
In one paragraph

Review in Journal of pharmaceutical analysis, 2023. 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. Optimal Detecting Part ofSensors (Basel, Switzerland) · 2026
    Article
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  3. Article
  4. Review
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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.

Qi WangDepartment of Medicinal Chemistry and Natural Medicinal Chemistry, College of Pharmacy, Harbin Medical University, Harbin, 150081, China.
Yong ZhangDepartment of Pharmacology (The State-Province Key Laboratories of Biomedicine-Pharmaceutics of China, Key Laboratory of Cardiovascular Research, Ministry of Education), College of Pharmacy, Harbin Medical University, Harbin, 150081, China.
Baofeng YangDepartment of Pharmacology (The State-Province Key Laboratories of Biomedicine-Pharmaceutics of China, Key Laboratory of Cardiovascular Research, Ministry of Education), College of Pharmacy, Harbin Medical University, Harbin, 150081, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Traditional Chinese medicine (TCM) is a treasure of the Chinese nation, providing effective solutions to current medical requisites. Various spectral techniques are undergoing continuous development and provide new and reliable means for evaluating the efficacy and quality of TCM. Because spectral techniques are noninvasive, convenient, and sensitive, they have been widely applied to in vitro and in vivo TCM evaluation systems. In this paper, previous achievements and current progress in the research on spectral technologies (including fluorescence spectroscopy, photoacoustic imaging, infrared thermal imaging, laser-induced breakdown spectroscopy, hyperspectral imaging, and surface enhanced Raman spectroscopy) are discussed. The advantages and disadvantages of each technology are also presented. Moreover, the future applications of spectral imaging to identify the origins, components, and pesticide residues of TCM in vitro are elucidated. Subsequently, the evaluation of the efficacy of TCM in vivo is presented. Identifying future applications of spectral imaging is anticipated to promote medical research as well as scientific and technological explorations.

Indexed as

Chinese medicineFluorescence spectroscopyPhotoacoustic imagingSpectral imaging

Identifiers

PMID38174122
PMCPMC10759257

What Socratic 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 Socratic graph.