Introduction: Cognitive impairment is the main clinical manifestation of cerebral small vessel disease (CSVD). However, the mechanism and structural damage in different domains of cognitive disorders are poorly understood. There is an urgent need to quantify the relation between diffusion tensor imaging (DTI) data and impaired cognitive testing in CSVD, which may help to find biomarkers for early diagnosis or treatment evaluation. We aim to summarise the understanding of association between DTI findings and domain-specific cognitive impairment.
Methods And Analysis: PubMed, EMBASE, Web of science, Cochrane library, Chinese National Knowledge Infrastructure Databases, Wanfang, SinoMed and VIP will be searched, from 1 January 1994 to 1 August 2021. The ClinicalTrials.gov and Chictr.org.cn records will also be searched to identify further potential studies. The included studies should report fractional anisotropy and/or and mean diffusivity/apparent diffusion coefficient data for one or more individual regions of interest in DTI analysis. Meanwhile, cognitive testing scores are also needed. This systematic review will be reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. The quality of cohort or case-control studies will be evaluated by the Newcastle-Ottawa Scale, and the cross-section studies will be evaluated by Agency for Healthcare Research and Quality scale. Meta-analysis, subgroup and sensitivity analyses, and publication bias will be all performed with Stata.
Ethics And Dissemination: Patients and the public will not be involved in this study. The existing data from published studies will be used. The findings from this research will be relevant information regarding the association of DTI metrics with cognitive disorder, which will be published in a peer-reviewed journal. If we need to amend this protocol, we will give the date of each amendment, describe the change and give the rationale. Changes will not be incorporated into the protocol.
Prospero Registration Number: CRD42021226133.
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http://dx.doi.org/10.1136/bmjopen-2021-049203 | DOI Listing |
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Mol Divers
December 2024
Small-Molecule Drug Research Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zu Chong Zhi Road, Shanghai, 201203, People's Republic of China.
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View Article and Find Full Text PDFPsychopharmacology (Berl)
December 2024
Department of Medicinal Chemistry, School of Pharmacy, Medical College of Virginia Campus, Virginia Commonwealth University, 800 E. Leigh St., STE 205, Richmond, VA, 23219-0540, USA.
Rationale α-ET (α-ethyltryptamine), a homolog of the classical hallucinogen α-methyltryptamine, was once prescribed clinically as an antidepressant. Classical psychedelic drugs are currently of interest as potential pharmacotherapy for psychiatric disorders. Objectives Drug discrimination was used to (a) determine if α-ET-like stimulus effects could be engendered by the prototypical phenylalkylamines MDMA ("Ecstasy") or MDA ("Love Drug") and (b) evaluate the α-ET-like stimulus effects of four synthesized aryl-substituted monomethoxy analogs of α-ET (4-OMe-, 5-OMe-, 6-OMe- and 7-OMe-α-ET).
View Article and Find Full Text PDFLangmuir
December 2024
Department of Physics, National Institute of Technology, Jamshedpur-831014, India.
We have conducted a systematic study employing density functional theory (DFT) and quantum theory of atoms in molecules (QTAIM) to explore the gas sensing capabilities of nitrogen-doped single vacancy graphene quantum dots (SV/3N) decorated with transition metals (TM = Mn, Co, Cu). We have studied the interactions between TM@SV/3N and four different target gases (AsH, NH, PH, and HS) through the computation of adsorption energies, charge transfer, noncovalent interaction, density of states, band gap, and work function for 12 distinct adsorption systems. Our comprehensive analysis included an in-depth assessment of sensors' stability, sensitivity, selectivity, and reusability for practical applications.
View Article and Find Full Text PDFStress
December 2025
Technology Transfer and Innovation-Support Office, North-West University, Potchefstroom, South Africa.
Background: Self-reported mental stress is not consistently recognized as a risk factor for stroke. This prompted development of a novel algorithm for stress-phenotype indices to quantify chronic stress prevalence in relation to a modified stroke risk score in a South African cohort. The algorithm is based on biomarkers adrenocorticotrophic hormone, high-density lipoprotein cholesterol, high-sensitive cardiac-troponin-T, and diastolic blood pressure which exemplifies the stress-ischemic-phenotype index.
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