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Phytochemical composition as well as neurological routines regarding concentrated amounts via ten types of family members Melastomataceae Juss.
lexities involving diabetes patients with infectious disease co-morbidities. It is too early to fully assess the impact of such activities. Conclusion There are a number of ongoing activities across Africa to improve the management of patients with diabetes including co-morbidities. However, more needs to be done considering the high and growing burden of T2DM in Africa. Ongoing research will help further benefit resource allocation and subsequent care. Copyright © 2020 Godman, Basu, Pillay, Mwita, Rwegerera, Anand Paramadhas, Tiroyakgosi, Okwen, Niba, Nonvignon, Sefah, Oluka, Guantai, Kibuule, Kalemeera, Mubita, Fadare, Ogunleye, Distiller, Rampamba, Wing, Mueller, Alfadl, Amu, Matsebula, Kalungia, Zaranyika, Masuka, Wale, Hill, Kurdi, Timoney, Campbell and Meyer.Age-related deterioration in white and gray matter is linked to cognitive deficits. Reduced microstructure of the fornix, the major efferent pathway of the hippocampus, and volume of the dentate gyrus (DG), may cause age-associated memory decline. However, the linkage between these anatomical determinants and memory retrieval in healthy aging are poorly understood. In 30 older adults, we acquired diffusion tensor and T1-weighted images for individual deterministic tractography and volume estimation. A memory task, administered outside of the scanner to assess retrieval of learned associations, required discrimination of previously acquired picture-word pairs. The results showed that fornix fractional anisotropy (FA) and left DG volumes were related to successful retrieval. These brain-behavior associations were observed for correct rejections, but not hits, indicating specificity of memory network functioning for detecting false associations. Mediation analyses showed that left DG volume mediated the effect of fornix FA on memory (48%), but not vice versa. These findings suggest that reduced microstructure induces volume loss and thus negatively affects retrieval of learned associations, complementing evidence of a pivotal role of the fornix in healthy aging. Our study offers a neurobehavioral model to explain variability in memory retrieval in older adults, an important prerequisite for the development of interventions to counteract cognitive decline. Copyright © 2020 Hayek, Thams, Flöel and Antonenko.As the population ages worldwide, the prevalence of cognitive disorders including mild cognitive impairment (MCI) is increasing. MCI appears in 10-20% of adults aged 65 years and older and is generally referred to as an intermediate stage between normal cognitive aging and dementia. To develop timely prevention and early treatment strategies by identifying biological factors, we investigated the relationship between dietary consumption of fish, brain structure, and MCI in cognitively normal subjects. The brain structure was assessed using neuroimaging-derived measures including the "gray-matter brain healthcare quotient (GM-BHQ)" and "fractional-anisotropy brain healthcare quotient (FA-BHQ)," which are approved as the international standard (H.861.1) by the International Telecommunication Union Telecommunication Standardization Sector. Dietary consumption of fish was calculated using the brief self-administered diet history questionnaire (BDHQ), and MCI was assessed using the Memory Performance Index (MPI) of MCI screening method (MCI Screen). This study showed that fish intake was positively associated with both FA-BHQ and MPI, and FA-BHQ was more strongly associated with MPI than fish intake. Our findings are in line with those in previous studies, but our study further indicates that the condition of the whole brain integrity measured by the FA-BHQ may mediate the relationship between fish intake and MCI prevention in healthy people. In other words, FA-BHQ may be used to identify people at high risk of MCI to provide the appropriate intervention. Copyright © 2020 Kokubun, Nemoto and Yamakawa.Currently there are ~6 million Americans who are affected by dementia. Verbal fluency tasks have been commonly and frequently utilized to document the disease progression in many forms of dementia. Verb fluency has been found to display substantial potential to detect and monitor the cognitive declines of individuals with dementia who have fronto-striatal involvement. The neural substrates underlying verb fluency task performance, however, have remained unclear so far, especially in individuals with dementia. Therefore, in the current study, brain activation patterns of seven individuals with dementia and nine healthy older adults were investigated using functional MRI. The participants performed in the scanner an overt, subject-paced verb fluency task, representative of fluency tasks used in clinical settings. The brain activation patterns during the verb fluency task were compared between the two groups, and a correlational analysis was conducted to determine the neural correlates of verb fluency performance. The results suggest that compared to healthy older adults, individuals with dementia demonstrated poorer verb fluency performance and showed higher activation in specific neural regions, such as the bilateral frontal lobe. In addition, the correlational analysis revealed that poorer verb fluency performance lead to increased activation in certain cortical and subcortical areas, including left hippocampus and right supramarginal gyrus. The current findings are consistent with previous neurophysiological findings related to semantic (noun) fluency performance in older adults and individuals with dementia and add to the empirical evidence that supports the role of the frontal lobe and hippocampus in verb retrieval and search. Declines in verb fluency performance cannot only be used as a cognitive marker, but also represent neuropathological changes due to the neurodegenerative disease. Copyright © 2020 Paek, Murray and Newman.The loss of dopaminergic neurons of the nigrostriatal system underlies the onset of the typical motor symptoms of Parkinson's disease (PD). Lewy bodies (LB) and Lewy neurites (LN), proteinaceous inclusions mainly composed of insoluble α-synuclein (α-syn) fibrils are key neuropathological hallmarks of the brain of affected patients. Compelling evidence supports that in the early prodromal phases of PD, synaptic terminal and axonal alterations initiate and drive a retrograde degeneration process culminating with the loss of nigral dopaminergic neurons. This notwithstanding, the molecular triggers remain to be fully elucidated. Although it has been shown that α-syn fibrillary aggregation can induce early synaptic and axonal impairment and cause nigrostriatal degeneration, we still ignore how and why α-syn fibrillation begins. Nuclear factor-κB (NF-κB) transcription factors, key regulators of inflammation and apoptosis, are involved in the brain programming of systemic aging as well as in the pathogenesis of seveupporting a possible interplay between NF-κB dysregulation and α-syn pathology in PD, with the aim to disclose novel potential mechanisms involved in the pathogenesis of this disorder. Copyright © 2020 Bellucci, Bubacco, Longhena, Parrella, Faustini, Porrini, Bono, Missale and Pizzi.Introduction Problems with attention are common in patients with cerebral small vessel disease (CSVD). The normal human brain exhibits functional and structural asymmetry. However, it is unknown whether there is lateralization of attention in patients with CSVD. Objective This study aims to investigate attention separately in both cerebral hemispheres in patients with CSVD using the computer-based Lateralized Attention Network Test-Revised (LANT-R). Methods The total number of subjects included was 58, which includes the CSVD (N = 35) and healthy control (HC, N = 23) groups. All subjects completed the LANT-R paradigm and neuropsychological background tests. Results The results indicate that there is an left hemisphere (LH) lateralization in orienting network efficiency in the HC group. However, this lateralization was not apparent in the CSVD group. Furthermore, the difference between groups was significant (interaction P = 0.02). In addition, the scores of subjects in the CSVD group are lower in several cognitive domains, including attention function, memory function, information processing speed, and executive function, compared with the controls. Conclusion Patients with CSVD change in the lateralization of attention compared with the normal elderly. The decrease in attention in patients with CSVD might be caused by the reduced ability of selecting useful information in the LH. Copyright © 2020 Cao, Zhang, Wang, Pan, Tian, Hu, Wei, Wang, Shi and Wang.Background The detection of large vessel occlusion (LVO) plays a critical role in the diagnosis and treatment of acute ischemic stroke (AIS). SB505124 Identifying LVO in the pre-hospital setting or early stage of hospitalization would increase the patients' chance of receiving appropriate reperfusion therapy and thereby improve neurological recovery. Methods To enable rapid identification of LVO, we established an automated evaluation system based on all recorded AIS patients in Hong Kong Hospital Authority's hospitals in 2016. The 300 study samples were randomly selected based on a disproportionate sampling plan within the integrated electronic health record system, and then separated into a group of 200 patients for model training, and another group of 100 patients for model performance evaluation. The evaluation system contained three hierarchical models based on patients' demographic data, clinical data and non-contrast CT (NCCT) scans. The first two levels of modeling utilized structured demographic and clinical ge, this is the first study combining both structured clinical data with non-structured NCCT imaging data for the diagnosis of LVO in the acute setting, with superior performance compared to previously reported approaches. Our system is capable of automatically providing preliminary evaluations at different pre-hospital stages for potential AIS patients. Copyright © 2020 You, Tsang, Yu, Tsui, Woo, Lui and Leung.In recent years, deep learning (DL) has become more widespread in the fields of cognitive and clinical neuroimaging. Using deep neural network models to process neuroimaging data is an efficient method to classify brain disorders and identify individuals who are at increased risk of age-related cognitive decline and neurodegenerative disease. Here we investigated, for the first time, whether structural brain imaging and DL can be used for predicting a physical trait that is of significant clinical relevance-the body mass index (BMI) of the individual. We show that individual BMI can be accurately predicted using a deep convolutional neural network (CNN) and a single structural magnetic resonance imaging (MRI) brain scan along with information about age and sex. Localization maps computed for the CNN highlighted several brain structures that strongly contributed to BMI prediction, including the caudate nucleus and the amygdala. Comparison to the results obtained via a standard automatic brain segmentation method revealed that the CNN-based visualization approach yielded complementary evidence regarding the relationship between brain structure and BMI. Taken together, our results imply that predicting BMI from structural brain scans using DL represents a promising approach to investigate the relationship between brain morphological variability and individual differences in body weight and provide a new scope for future investigations regarding the potential clinical utility of brain-predicted BMI. Copyright © 2020 Vakli, Deák-Meszlényi, Auer and Vidnyánszky.
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