Evidence map›Paper›PMID 38515515›Full record

ArticleFrontiers in aging neuroscience2024

Assessing interstitial fluid dynamics in type 2 diabetes mellitus and prediabetes cases through diffusion tensor imaging analysis along the perivascular space.

Rukeye Tuerxun, Koji Kamagata, Yuya Saito, Christina Andica, Kaito Takabayashi, Wataru Uchida, Seina Yoshida, Junko Kikuta, Hiroki Tabata, Hitoshi Naito and 11 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in aging neuroscience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
3.2field-weighted citation impact, top 8% of its field
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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.

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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

21 authors at 4 institutions in 1 country.

Rukeye TuerxunDepartment of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Koji KamagataDepartment of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Yuya SaitoDepartment of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Christina AndicaDepartment of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Kaito TakabayashiDepartment of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Wataru UchidaDepartment of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Seina YoshidaDepartment of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Junko KikutaDepartment of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Hiroki TabataSportology Center, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Hitoshi NaitoDepartment of Metabolism and Endocrinology, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Yuki SomeyaSportology Center, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Hideyoshi KagaDepartment of Metabolism and Endocrinology, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Mari MiyataDepartment of Functional Brain Imaging, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan.
Toshiaki AkashiDepartment of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Akihiko WadaDepartment of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Toshiaki TaokaDepartment of Innovative Biomedical Visualization, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Shinji NaganawaDepartment of Radiology, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Yoshifumi TamuraSportology Center, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Hirotaka WatadaSportology Center, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Ryuzo KawamoriSportology Center, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Shigeki AokiDepartment of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Juntendo University · JPNagoya University · JPNational Institutes for Quantum Science and Technology · JPTokyo Metropolitan University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and purpose: Glymphatic system in type 2 diabetes mellitus (T2DM) but not in the prodrome, prediabetes (Pre-DM) was investigated using diffusion tensor image analysis along the perivascular space (DTI-ALPS). Association between glymphatic system and insulin resistance of prominent characteristic in T2DM and Pre-DM between is yet elucidated. Therefore, this study delves into the interstitial fluid dynamics using the DTI-ALPS in both Pre-DM and T2DM and association with insulin resistance. Materials and methods: In our cross-sectional study, we assessed 70 elderly individuals from the Bunkyo Health Study, which included 22 with Pre-DM, 18 with T2DM, and 33 healthy controls with normal glucose metabolism (NGM). We utilized the general linear model (GLM) to evaluate the ALPS index based on DTI-ALPS across these groups, considering variables like sex, age, intracranial volume, years of education, anamnesis of hypertension and hyperlipidemia, and the total Fazekas scale. Furthermore, we have explored the relationship between the ALPS index and insulin resistance, as measured by the homeostasis model assessment of insulin resistance (HOMA-IR) using GLM and the same set of covariates. Results: In the T2DM group, the ALPS index demonstrated a reduction compared with the NGM group [family-wise error (FWE)-corrected Conclusion: The ALPS index significantly decreased in both the pre-DM and T2DM groups and showed a correlated with insulin resistance. This indicated that changes in interstitial fluid dynamics are associated with insulin resistance.

Indexed as

diffusion-magnetic resonance imagingglymphatic systeminsulin resistanceprediabetestype 2 diabetes mellitus

Identifiers

PMID38515515
PMCPMC10954820
OpenAlexW4392613372

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Registered trials

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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.