keyword
MENU ▼
Read by QxMD icon Read
search

Adni

keyword
https://www.readbyqxmd.com/read/28230534/knockdown-of-antiapoptotic-genes-in-breast-cancer-cells-by-sirna-loaded-into-hybrid-nanoparticles
#1
Leônidas Mello Júnior, Gabriela Rosa E Souza, Evelyn Winter, Adny Henrique Silva, Frederico Pittella, Tânia Beatriz Creczynski-Pasa
Tumorigenesis is related to an imbalance in controlling mechanisms of apoptosis. Expression of the genes BCL-2 and BCL-xL results in promotion of cell survival by inhibiting apoptosis. Thus, a novel approach to suppress antiapoptotic genes is the use of small interfering RNA (siRNA) in cancer cells. However, there are some limitations for the application of siRNA such as low bioavailability, requiring vectors as a strategy to achieve the nucleic acid transfection. In this study formulations containing CaP-siRNA-PEG-polyanion hybrid nanoparticles were developed to enhance siRNA delivery to cultured human breast cancer cells (MCF-7) in order to evaluate if the silencing of antiapoptotic genes BCL-2 and BCL-xL by siRNA would succeed in increasing cancer cells death...
February 23, 2017: Nanotechnology
https://www.readbyqxmd.com/read/28227007/identification-of-blood-biomarkers-for-use-in-point-of-care-diagnosis-tool-for-alzheimer-s-disease
#2
E Jammeh, P Zhao, C Carroll, S Pearson, E Ifeachor, E Jammeh, P Zhao, C Carroll, S Pearson, E Ifeachor, C Carroll, E Jammeh, E Ifeachor, S Pearson, P Zhao
Early diagnosis of Alzheimer's Disease (AD) is widely regarded as necessary to allow treatment to be started before irreversible damage to the brain occur and for patients to benefit from new therapies as they become available. Low-cost point-of-care (PoC) diagnostic tools that can be used to routinely diagnose AD in its early stage would facilitate this, but such tools require reliable and accurate biomarkers. However, traditional biomarkers for AD use invasive cerebrospinal fluid (CSF) analysis and/or expensive neuroimaging techniques together with neuropsychological assessments...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28224692/renal-function-affects-hippocampal-volume-and-cognition-the-role-of-vascular-burden-and-amyloid-deposition
#3
Hoyoung An, Booyeol Choi, Sang Joon Son, Eun Young Cho, Seon-Ok Kim, Sooyun Cho, Duk-Hee Kang, Chul Lee, Seong Yoon Kim
AIM: We determined if differences in renal function, even within normal levels, influenced hippocampal volume (HCV) and cognition. METHODS: Cognitively normal (CN) and mild cognitive impairment (MCI) subjects with eGFR ≥ 60 ml/min/1.73m(2) were selected from the ADNI database (N = 1,269) and divided into three groups (eGFR 60-75, 75-90 and ≥90). Associations between eGFR, HCV and cognition scores were examined using regression methods, and random-coefficient models...
February 22, 2017: Geriatrics & Gerontology International
https://www.readbyqxmd.com/read/28222315/allylic-isothiouronium-salts-the-discovery-of-a-novel-class-of-thiourea-analogues-with-antitumor-activity
#4
Misael Ferreira, Laura Sartori Assunção, Adny Henrique Silva, Fabíola Branco Filippin-Monteiro, Tânia Beatriz Creczynski-Pasa, Marcus Mandolesi Sá
A series of 28 aryl- and alkyl-substituted isothiouronium salts were readily synthesized in high yields through the reaction of allylic bromides with thiourea, N-monosubstituted thioureas or thiosemicarbazide. The S-allylic isothiouronium salts substituted with aliphatic groups were found to be the most effective against leukemia cells. These compounds combine high antitumor activity and low toxicity toward non-tumoral cells, with selectivity index higher than 20 in some cases. Furthermore, the selected isothiouronium salts induced G2/M cell cycle arrest and cell death, possibly by apoptosis...
February 12, 2017: European Journal of Medicinal Chemistry
https://www.readbyqxmd.com/read/28220065/prediction-of-mild-cognitive-impairment-conversion-using-a-combination-of-independent-component-analysis-and-the-cox-model
#5
Ke Liu, Kewei Chen, Li Yao, Xiaojuan Guo
Mild cognitive impairment (MCI) represents a transitional stage from normal aging to Alzheimer's disease (AD) and corresponds to a higher risk of developing AD. Thus, it is necessary to explore and predict the onset of AD in MCI stage. In this study, we propose a combination of independent component analysis (ICA) and the multivariate Cox proportional hazards regression model to investigate promising risk factors associated with MCI conversion among 126 MCI converters and 108 MCI non-converters from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database...
2017: Frontiers in Human Neuroscience
https://www.readbyqxmd.com/read/28210220/mri-based-classification-models-in-prediction-of-mild-cognitive-impairment-and-dementia-in-late-life-depression
#6
Aleksandra K Lebedeva, Eric Westman, Tom Borza, Mona K Beyer, Knut Engedal, Dag Aarsland, Geir Selbaek, Asta K Haberg
Objective: Late-life depression (LLD) is associated with development of different types of dementia. Identification of LLD patients, who will develop cognitive decline, i.e., the early stage of dementia would help to implement interventions earlier. The purpose of this study was to assess whether structural brain magnetic resonance imaging (MRI) in LLD patients can predict mild cognitive impairment (MCI) or dementia 1 year prior to the diagnosis. Methods: LLD patients underwent brain MRI at baseline and repeated clinical assessment after 1-year...
2017: Frontiers in Aging Neuroscience
https://www.readbyqxmd.com/read/28205215/multicenter-validation-of-an-mmse-moca-conversion-table
#7
David Bergeron, Kelsey Flynn, Louis Verret, Stéphane Poulin, Rémi W Bouchard, Christian Bocti, Tamàs Fülöp, Guy Lacombe, Serge Gauthier, Ziad Nasreddine, Robert Jr Laforce
BACKGROUND: Accumulating evidence points to the superiority of the MoCA over the MMSE as a cognitive screening tool. To facilitate the transition from the MMSE to the MoCA in clinical and research settings, authors have developed MMSE-MoCA conversion tables. However, it is unknown whether a conversion table generated from Alzheimer's disease (AD) patients would apply to patients with other dementia subtypes like vascular dementia or frontotemporal dementia. Furthermore, the reliability and accuracy of MMSE-MoCA conversion tables has not been properly evaluated...
February 15, 2017: Journal of the American Geriatrics Society
https://www.readbyqxmd.com/read/28202203/female-specific-effect-of-the-bdnf-gene-on-alzheimer-s-disease
#8
Guo-Dong Li, Rui Bi, Deng-Feng Zhang, Min Xu, Rongcan Luo, Dong Wang, Yiru Fang, Tao Li, Chen Zhang, Yong-Gang Yao
Alzheimer's disease (AD) is the most common neurodegenerative disease influenced by genetic and environmental factors. Brain-derived neurotrophic factor (BDNF) plays an important role in the progression of AD, but the genetic association between BDNF and AD remains controversial. In this study, we aimed to explore the potential association between genetic variants in BDNF and AD in Han Chinese and to investigate whether the association is affected by gender. A 3-stage study was conducted to evaluate the genetic association between BDNF and AD...
January 24, 2017: Neurobiology of Aging
https://www.readbyqxmd.com/read/28197591/predicting-brain-network-changes-in-alzheimer-s-disease-with-link-prediction-algorithms
#9
Sadegh Sulaimany, Mohammad Khansari, Peyman Zarrineh, Madelaine Daianu, Neda Jahanshad, Paul M Thompson, Ali Masoudi-Nejad
Link prediction is a promising research area for modeling various types of networks and has mainly focused on predicting missing links. Link prediction methods may be valuable for describing brain connectivity, as it changes in Alzheimer's disease (AD) and its precursor, mild cognitive impairment (MCI). Here, we analyzed 3-tesla whole-brain diffusion-weighted images from 202 participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) - 50 healthy controls, 72 with earlyMCI (eMCI) and 38 with lateMCI (lMCI) and 42 AD patients...
February 15, 2017: Molecular BioSystems
https://www.readbyqxmd.com/read/28191669/adaptive-testing-for-multiple-traits-in-a-proportional-odds-model-with-applications-to-detect-snp-brain-network-associations
#10
Junghi Kim, Wei Pan
There has been increasing interest in developing more powerful and flexible statistical tests to detect genetic associations with multiple traits, as arising from neuroimaging genetic studies. Most of existing methods treat a single trait or multiple traits as response while treating an SNP as a predictor coded under an additive inheritance mode. In this paper, we follow an earlier approach in treating an SNP as an ordinal response while treating traits as predictors in a proportional odds model (POM). In this way, it is not only easier to handle mixed types of traits, e...
February 13, 2017: Genetic Epidemiology
https://www.readbyqxmd.com/read/28188306/left-frontal-cortex-connectivity-underlies-cognitive-reserve-in-prodromal-alzheimer-disease
#11
Nicolai Franzmeier, Marco Duering, Michael Weiner, Martin Dichgans, Michael Ewers
OBJECTIVE: To test whether higher global functional connectivity of the left frontal cortex (LFC) in Alzheimer disease (AD) is associated with more years of education (a proxy of cognitive reserve [CR]) and mitigates the association between AD-related fluorodeoxyglucose (FDG)-PET hypometabolism and episodic memory. METHODS: Forty-four amyloid-PET-positive patients with amnestic mild cognitive impairment (MCI-Aβ+) and 24 amyloid-PET-negative healthy controls (HC) were included...
February 10, 2017: Neurology
https://www.readbyqxmd.com/read/28182655/regional-analysis-of-volumes-and-reproducibilities-of-automatic-and-manual-hippocampal-segmentations
#12
Fabian Bartel, Hugo Vrenken, Fetsje Bijma, Frederik Barkhof, Marcel van Herk, Jan C de Munck
PURPOSE: Precise and reproducible hippocampus outlining is important to quantify hippocampal atrophy caused by neurodegenerative diseases and to spare the hippocampus in whole brain radiation therapy when performing prophylactic cranial irradiation or treating brain metastases. This study aimed to quantify systematic differences between methods by comparing regional volume and outline reproducibility of manual, FSL-FIRST and FreeSurfer hippocampus segmentations. MATERIALS AND METHODS: This study used a dataset from ADNI (Alzheimer's Disease Neuroimaging Initiative), including 20 healthy controls, 40 patients with mild cognitive impairment (MCI), and 20 patients with Alzheimer's disease (AD)...
2017: PloS One
https://www.readbyqxmd.com/read/28180075/independent-value-added-by-diffusion-mri-for-prediction-of-cognitive-function-in-older-adults
#13
Julia A Scott, Duygu Tosun, Meredith N Braskie, Pauline Maillard, Paul M Thompson, Michael Weiner, Charles DeCarli, Owen T Carmichael
The purpose of this study was to determine whether white matter microstructure measured by diffusion magnetic resonance imaging (dMRI) provides independent information about baseline level or change in executive function (EF) or memory (MEM) in older adults with and without cognitive impairment. Longitudinal data was acquired from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study from phases GO and 2 (2009-2015). ADNI participants included were diagnosed as cognitively normal (n = 46), early mild cognitive impairment (MCI) (n = 48), late MCI (n = 29), and dementia (n = 39) at baseline...
2017: NeuroImage: Clinical
https://www.readbyqxmd.com/read/28180074/regional-staging-of-white-matter-signal-abnormalities-in-aging-and-alzheimer-s-disease
#14
Emily R Lindemer, Douglas N Greve, Bruce R Fischl, Jean C Augustinack, David H Salat
White matter lesions, quantified as 'white matter signal abnormalities' (WMSA) on neuroimaging, are common incidental findings on brain images of older adults. This tissue damage is linked to cerebrovascular dysfunction and is associated with cognitive decline. The regional distribution of WMSA throughout the cerebral white matter has been described at a gross scale; however, to date no prior study has described regional patterns relative to cortical gyral landmarks which may be important for understanding functional impact...
2017: NeuroImage: Clinical
https://www.readbyqxmd.com/read/28176662/apoe-%C3%AE%C2%B54-allele-relateted-alterations-in-hippocampal-connectivity-in-early-alzheimer-s-disease-support-memory-performance
#15
Matteo De Marco, Annamaria Vallelunga, Francesca Meneghello, Susheel Varma, Alejandro Frangi, Annalena Venneri
BACKGROUND: Whether the presence of the Apolipoprotein E ε4 allele modulates hippocampal connectivity networks in abnormal ageing has yet to be fully clarified. OBJECTIVE: Allele-dependent differences in this pattern of functional connectivity were investigated in patients with very mild neurodegeneration of the Alzheimer's type, carriers and non-carriers of the ε4 allele. METHOD: A seed-based connectivity approach was used. The two groups were similar in demographics, volumetric measures of brain-structure, and cognitive profiles...
February 6, 2017: Current Alzheimer Research
https://www.readbyqxmd.com/read/28167394/deep-ensemble-learning-of-sparse-regression-models-for-brain-disease-diagnosis
#16
Heung-Il Suk, Seong-Whan Lee, Dinggang Shen
Recent studies on brain imaging analysis witnessed the core roles of machine learning techniques in computer-assisted intervention for brain disease diagnosis. Of various machine-learning techniques, sparse regression models have proved their effectiveness in handling high-dimensional data but with a small number of training samples, especially in medical problems. In the meantime, deep learning methods have been making great successes by outperforming the state-of-the-art performances in various applications...
January 24, 2017: Medical Image Analysis
https://www.readbyqxmd.com/read/28149965/prediction-of-memory-impairment-with-mri-data-a-longitudinal-study-of-alzheimer-s-disease
#17
Xiaoqian Wang, Dinggang Shen, Heng Huang
Alzheimer's Disease (AD), a severe type of neurodegenerative disorder with progressive impairment of learning and memory, has threatened the health of millions of people. How to recognize AD at early stage is crucial. Multiple models have been presented to predict cognitive impairments by means of neuroimaging data. However, traditional models did not employ the valuable longitudinal information along the progression of the disease. In this paper, we proposed a novel longitudinal feature learning model to simultaneously uncover the interrelations among different cognitive measures at different time points and utilize such interrelated structures to enhance the learning of associations between imaging features and prediction tasks...
October 2016: Medical Image Computing and Computer-assisted Intervention: MICCAI ..
https://www.readbyqxmd.com/read/28149964/early-diagnosis-of-alzheimer-s-disease-by-joint-feature-selection-and-classification-on-temporally-structured-support-vector-machine
#18
Yingying Zhu, Xiaofeng Zhu, Minjeong Kim, Dinggang Shen, Guorong Wu
The diagnosis of Alzheimer's disease (AD) from neuroimaging data at the pre-clinical stage has been intensively investigated because of the immense social and economic cost. In the past decade, computational approaches on longitudinal image sequences have been actively investigated with special attention to Mild Cognitive Impairment (MCI), which is an intermediate stage between normal control (NC) and AD. However, current state-of-the-art diagnosis methods have limited power in clinical practice, due to the excessive requirements such as equal and immoderate number of scans in longitudinal imaging data...
October 2016: Medical Image Computing and Computer-assisted Intervention: MICCAI ..
https://www.readbyqxmd.com/read/28143776/predictive-modelling-using-neuroimaging-data-in-the-presence-of-confounds
#19
Anil Rao, Joao M Monteiro, Janaina Mourao-Miranda
When training predictive models from neuroimaging data, we typically have available non-imaging variables such as age and gender that affect the imaging data but which we may be uninterested in from a clinical perspective. Such variables are commonly referred to as 'confounds'. In this work, we firstly give a working definition for confound in the context of training predictive models from samples of neuroimaging data. We define a confound as a variable which affects the imaging data and has an association with the target variable in the sample that differs from that in the population-of-interest, i...
January 29, 2017: NeuroImage
https://www.readbyqxmd.com/read/28123864/diagnostic-performance-of-an-automated-analysis-software-for-the-diagnosis-of-alzheimer-s-dementia-with-18-f-fdg-pet
#20
Sasan Partovi, Roger Yuh, Sara Pirozzi, Ziang Lu, Spencer Couturier, Ulrich Grosse, Mark D Schluchter, Aaron Nelson, Robert Jones, James K O'Donnell, Peter Faulhaber
The objective of this study was to assess the ability of a quantitative software-aided approach to improve the diagnostic accuracy of (18)F FDG PET for Alzheimer's dementia over visual analysis alone. Twenty normal subjects (M:F-12:8; mean age 80.6 years) and twenty mild AD subjects (M:F-12:8; mean age 70.6 years) with (18)F FDG PET scans were obtained from the ADNI database. Three blinded readers interpreted these PET images first using a visual qualitative approach and then using a quantitative software-aided approach...
2017: American Journal of Nuclear Medicine and Molecular Imaging
keyword
keyword
37175
1
2
Fetch more papers »
Fetching more papers... Fetching...
Read by QxMD. Sign in or create an account to discover new knowledge that matter to you.
Remove bar
Read by QxMD icon Read
×

Search Tips

Use Boolean operators: AND/OR

diabetic AND foot
diabetes OR diabetic

Exclude a word using the 'minus' sign

Virchow -triad

Use Parentheses

water AND (cup OR glass)

Add an asterisk (*) at end of a word to include word stems

Neuro* will search for Neurology, Neuroscientist, Neurological, and so on

Use quotes to search for an exact phrase

"primary prevention of cancer"
(heart or cardiac or cardio*) AND arrest -"American Heart Association"