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      Tractography in Type 2 Diabetes Mellitus With Subjective Memory Complaints: A Diffusion Tensor Imaging Study

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          Abstract

          The brain white matter (WM) structural injury caused by type 2 diabetes mellitus (T2DM) has been linked to cognitive impairment. However, the focus was mainly on the mild cognitive impairment (MCI) stage in most previous studies, with little attention made to subjective memory complaints (SMC). The main purpose of the current study was to investigate the characteristics of WM injury in T2DM patients and its correlation with SMC symptoms. In a group of 66 participants (33 HC and 33 T2DM-S), pointwise differences along WM tracts were identified using the automated fiber quantification (AFQ) approach. Then we investigated the utility of DTI properties along major WM tracts as features to distinguish patients with T2DM-S from HC via the support vector machine (SVM). Based on AFQ analysis, 10 primary fiber tracts that represent the subtle alterations of WM in T2DM-S were identified. Lower fractional anisotropy (FA) in the right SLF tract ( r = −0.538, p = 0.0013), higher radial diffusivity (RD) in the thalamic radiation (TR) tract ( r = 0.433, p = 0.012), and higher mean diffusivity (MD) in the right inferior fronto-occipital fasciculus (IFOF) tract ( r = 0.385, p = 0.0029) were significantly associated with a long period of disease. Decreased axial diffusivity (AD) in the left arcuate was associated with HbA 1c (r = −0.368, p = 0.049). In addition, we found a significant negative correlation between delayed recall and abnormal MD in the left corticospinal tract ( r = −0.546, p = 0.001). The FA of the right SLF tracts and bilateral arcuate can be used to differentiate the T2DM-S and the HC at a high accuracy up to 88.45 and 87.8%, respectively. In conclusion, WM microstructure injury in T2DM may be associated with SMC, and these abnormalities identified by DTI can be used as an effective biomarker.

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          Most cited references78

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            Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus provisional report of a WHO consultation.

            The classification of diabetes mellitus and the tests used for its diagnosis were brought into order by the National Diabetes Data Group of the USA and the second World Health Organization Expert Committee on Diabetes Mellitus in 1979 and 1980. Apart from minor modifications by WHO in 1985, little has been changed since that time. There is however considerable new knowledge regarding the aetiology of different forms of diabetes as well as more information on the predictive value of different blood glucose values for the complications of diabetes. A WHO Consultation has therefore taken place in parallel with a report by an American Diabetes Association Expert Committee to re-examine diagnostic criteria and classification. The present document includes the conclusions of the former and is intended for wide distribution and discussion before final proposals are submitted to WHO for approval. The main changes proposed are as follows. The diagnostic fasting plasma (blood) glucose value has been lowered to > or =7.0 mmol l(-1) (6.1 mmol l(-1)). Impaired Glucose Tolerance (IGT) is changed to allow for the new fasting level. A new category of Impaired Fasting Glycaemia (IFG) is proposed to encompass values which are above normal but below the diagnostic cut-off for diabetes (plasma > or =6.1 to or =5.6 to <6.1 mmol l(-1)). Gestational Diabetes Mellitus (GDM) now includes gestational impaired glucose tolerance as well as the previous GDM. The classification defines both process and stage of the disease. The processes include Type 1, autoimmune and non-autoimmune, with beta-cell destruction; Type 2 with varying degrees of insulin resistance and insulin hyposecretion; Gestational Diabetes Mellitus; and Other Types where the cause is known (e.g. MODY, endocrinopathies). It is anticipated that this group will expand as causes of Type 2 become known. Stages range from normoglycaemia to insulin required for survival. It is hoped that the new classification will allow better classification of individuals and lead to fewer therapeutic misjudgements.
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              A conceptual framework for research on subjective cognitive decline in preclinical Alzheimer's disease

              There is increasing evidence that subjective cognitive decline (SCD) in individuals with unimpaired performance on cognitive tests may represent the first symptomatic manifestation of Alzheimer's disease (AD). The research on SCD in early AD, however, is limited by the absence of common standards. The working group of the Subjective Cognitive Decline Initiative (SCD-I) addressed this deficiency by reaching consensus on terminology and on a conceptual framework for research on SCD in AD. In this publication, research criteria for SCD in pre-mild cognitive impairment (MCI) are presented. In addition, a list of core features proposed for reporting in SCD studies is provided, which will enable comparability of research across different settings. Finally, a set of features is presented, which in accordance with current knowledge, increases the likelihood of the presence of preclinical AD in individuals with SCD. This list is referred to as SCD plus.
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                Author and article information

                Contributors
                Journal
                Front Neurosci
                Front Neurosci
                Front. Neurosci.
                Frontiers in Neuroscience
                Frontiers Media S.A.
                1662-4548
                1662-453X
                06 April 2022
                2021
                : 15
                : 800420
                Affiliations
                [1] 1Department of Magnetic Resonance, Lanzhou University Second Hospital , Lanzhou, China
                [2] 2Department of Endocrine, Lanzhou University Second Hospital , Lanzhou, China
                [3] 3Department of Clinical Science, Philips Healthcare , Xi’an, China
                Author notes

                Edited by: Hubert Vaudry, Université de Rouen, France

                Reviewed by: Bing Zhang, Nanjing Drum Tower Hospital, China; Kai Yuan, Xidian University, China

                *Correspondence: Jing Zhang, lztong2001@ 123456163.com

                These authors have contributed equally to this work and share first authorship

                This article was submitted to Neuroendocrine Science, a section of the journal Frontiers in Neuroscience

                Article
                10.3389/fnins.2021.800420
                9019711
                35462734
                b20a290f-f2d3-4535-8aa6-8cbd1d8d690d
                Copyright © 2022 Wang, Ma, Liu, Bai, Ai, Zhang, Hu and Zhang.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 23 October 2021
                : 31 December 2021
                Page count
                Figures: 3, Tables: 3, Equations: 0, References: 78, Pages: 11, Words: 8837
                Categories
                Neuroscience
                Original Research

                Neurosciences
                type 2 diabetes,white matter,cognitive function,memory,diffusion tensor imaging
                Neurosciences
                type 2 diabetes, white matter, cognitive function, memory, diffusion tensor imaging

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