Brain structure alterations and cognitive impairment following repetitive mild head impact: An in vivo MRI and behavioral study in rat

2018 ◽  
Vol 340 ◽  
pp. 41-48 ◽  
Author(s):  
Yang Qin ◽  
Gai-Li Li ◽  
Xian-Hua Xu ◽  
Zhi-Yong Sun ◽  
Jian-Wen Gu ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Brain Structure ◽  
Head Impact ◽  
Behavioral Study

scholarly journals In vivo nucleus basalis of Meynert degeneration in mild cognitive impairment with Lewy bodies

2021 ◽  
Vol 30 ◽  
pp. 102604
Author(s):  
Julia Schumacher ◽  
John-Paul Taylor ◽  
Calum A. Hamilton ◽  
Michael Firbank ◽  
Ruth A. Cromarty ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Lewy Bodies ◽  
Nucleus Basalis ◽  
Nucleus Basalis Of Meynert

In vivo role of BDNF cleavage: Behavioral study of the mutant mice using test battery

2009 ◽  
Vol 65 ◽  
pp. S254
Author(s):  
Haruko Kumanogoh ◽  
Mitsuru Ohtsuka ◽  
Tomoko Hara ◽  
Yoshiko Urbanczyk ◽  
Keizo Takao ◽  
...  
Keyword(s):  
Test Battery ◽  
Mutant Mice ◽  
Behavioral Study

Effects of Gossypium herbaceam Extract Administration on the Learning and Memory Function in the Naturally Aged Rats: Neuronal Niche Improvement1

2012 ◽  
Vol 31 (1) ◽  
pp. 101-111 ◽  
Author(s):  
Yanyong Liu ◽  
Haji Akber Aisa ◽  
Chao Ji ◽  
Nan Yang ◽  
Haibo Zhu ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Learning And Memory ◽  
Memory Impairment ◽  
Neuroprotective Effect ◽  
Memory Function ◽  
Aged Rats

Aging-associated cognitive impairment is an important health care issue since individuals with mild cognitive impairment are more likely to develop Alzheimer’s disease. In the present study, the protective effect of Gossypium herbaceam extracts (GHE) on learning and memory impairment associated with aging were examined in vivo using Morris water maze and step through task. Furthermore, the antioxidant activity and neuroprotective effect of GHE was investigated with methods of histochemistry and biochemistry. These data showed that oral administration with GHE at the doses of 35, 70, and 140 mg/kg exerted an improved effect on the learning and memory impairment in aged rats. Subsequently, GHE afforded a beneficial action on eradication of free radicals without influence on the activity of glutathione peroxidase and superoxide dismutase. GHE treatment enhanced the expression levels of nerve growth factor. Meanwhile, proliferation of neural progenitor cells was elevated in hippocampus after treatment with GHE. Taken together, neurogenic niche improvement could be involved in the mechanism underlying neuroprotection of GHE against aging-associated cognitive impairment. These findings suggested that GHE might be a potential agent as cognitive-enhancing drugs that delay or halt mild cognitive impairment progression to Alzheimer’s disease or treatment of aging-associated cognitive impairment.

scholarly journals Survivors of SARS-CoV-2 Infection Show Neuropsychiatric Sequelae Measured by Surveys, Neurocognitive Testing, and Magnetic Resonance Imaging: Preliminary Results

2021 ◽  
Author(s):  
Laura M. Hack ◽  
Jacob Brawer ◽  
Megan Chesnut ◽  
Xue Zhang ◽  
Max Wintermark ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Functional Connectivity ◽  
Brain Structure ◽  
Functional Neuroimaging ◽  
Structure And Function ◽  
Self Report ◽  
Neurocognitive Testing ◽  
Preliminary Results ◽  
Brain Structure And Function ◽  
And Function

AbstractA significant number of individuals experience physical, cognitive, and mental health symptoms in the months after acute infection with SARS-CoV-2, the virus that causes COVID-19. This study assessed depressive and anxious symptoms, cognition, and brain structure and function in participants with symptomatic COVID-19 confirmed by PCR testing (n=100) approximately three months following infection, leveraging self-report questionnaires, objective neurocognitive testing, and structural and functional neuroimaging data. Preliminary results demonstrated that over 1/5 of our cohort endorsed clinically significant depressive and/or anxious symptoms, and >40% of participants had cognitive impairment on objective testing across multiple domains, consistent with ‘brain-fog’. While depression and one domain of quality of life (physical functioning) were significantly different between hospitalized and non-hospitalized participants, anxiety, cognitive impairment, and most domains of functioning were not, suggesting that the severity of SARS-CoV-2 infection does not necessarily relate to the severity of neuropsychiatric outcomes and impaired functioning in the months after infection. Furthermore, we found that the majority of participants in a subset of our cohort who completed structural and functional neuroimaging (n=15) had smaller olfactory bulbs and sulci in conjunction with anosmia. We also showed that this subset of participants had dysfunction in attention network functional connectivity and ventromedial prefrontal cortex seed-based functional connectivity. These functional imaging dysfunctions have been observed previously in depression and correlated with levels of inflammation. Our results support and extend previous findings in the literature concerning the neuropsychiatric sequelae associated with long COVID. Ongoing data collection and analyses within this cohort will allow for a more comprehensive understanding of the longitudinal relationships between neuropsychiatric symptoms, neurocognitive performance, brain structure and function, and inflammatory and immune profiles.

Structural, Functional, and Molecular Neuroimaging Biomarkers for Alzheimer’s Disease

2013 ◽  
pp. 821-825
Author(s):  
James B. Brewer ◽  
Jorge Sepulcre ◽  
Keith A. Johnson
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Clinical Trials ◽  
Cognitive Impairment ◽  
Neurodegenerative Disorders ◽  
Brain Dysfunction ◽  
Imaging Biomarkers ◽  
Neurocognitive Evaluation ◽  
Neuroimaging Biomarkers

Advances in quantitative structural, functional, and molecular neuroimaging have provided new tools for objective, in vivo, assessment of critical aspects of Alzheimer’s disease and other neurodegenerative disorders. Measures of brain atrophy or brain dysfunction, coupled with measures of disease-linked pathology, might complement the history, physical and neurocognitive evaluation of patients and thereby improve predictive prognosis, especially at early stages of cognitive impairment where neurodegenerative etiology is less certain. Such imaging biomarkers are currently used in nearly all clinical trials of therapeutic agents for Alzheimer’s disease and are increasingly incorporated into clinical practice. In this chapter, imaging biomarkers are introduced and discussed to familiarize the reader with their potential research and clinical uses.

scholarly journals Terpenoids of Ganoderma lucidum reverse cognitive impairment through attenuating neurodegeneration via suppression of PI3K/AKT/mTOR expression in vivo model

2020 ◽  
Vol 73 ◽  
pp. 104142
Author(s):  
Anqi Wang ◽  
Changhao Xiao ◽  
Jianxian Zheng ◽  
Chuansong Ye ◽  
Zhen Dai ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Ganoderma Lucidum ◽  
In Vivo Model

scholarly journals A Deep Learning approach for Diagnosis of Mild Cognitive Impairment Based on MRI Images

2019 ◽  
Vol 9 (9) ◽  
pp. 217 ◽  
Author(s):  
Gorji ◽  
Kaabouch
Keyword(s):  
Deep Learning ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Early Diagnosis ◽  
Brain Structure ◽  
Neurodegenerative Disorder ◽  
Healthy People ◽  
Learning Approach ◽  
Brain Structure And Function ◽  
Percent Accuracy

Mild cognitive impairment (MCI) is an intermediary stage condition between healthy people and Alzheimer’s disease (AD) patients and other dementias. AD is a progressive and irreversible neurodegenerative disorder, which is a significant threat to people, age 65 and older. Although MCI does not always lead to AD, an early diagnosis at the stage of MCI can be very helpful in identifying people who are at risk of AD. Moreover, the early diagnosis of MCI can lead to more effective treatment, or at least, significantly delay the disease’s progress, and can lead to social and financial benefits. Magnetic resonance imaging (MRI), which has become a significant tool for the diagnosis of MCI and AD, can provide neuropsychological data for analyzing the variance in brain structure and function. MCI is divided into early and late MCI (EMCI and LMCI) and sadly, there is no clear differentiation between the brain structure of healthy people and MCI patients, especially in the EMCI stage. This paper aims to use a deep learning approach, which is one of the most powerful branches of machine learning, to discriminate between healthy people and the two types of MCI groups based on MRI results. The convolutional neural network (CNN) with an efficient architecture was used to extract high-quality features from MRIs to classify people into healthy, EMCI, or LMCI groups. The MRIs of 600 individuals used in this study included 200 control normal (CN) people, 200 EMCI patients, and 200 LMCI patients. This study randomly selected 70 percent of the data to train our model and 30 percent for the test set. The results showed the best overall classification between CN and LMCI groups in the sagittal view with an accuracy of 94.54 percent. In addition, 93.96 percent and 93.00 percent accuracy were reached for the pairs of EMCI/LMCI and CN/EMCI, respectively.

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