keyword
MENU ▼
Read by QxMD icon Read
search

knowledge network

keyword
https://www.readbyqxmd.com/read/28231395/functional-connectivity-in-amygdalar-sensory-pre-motor-networks-at-rest-new-evidence-from-the-human-connectome-project
#1
Nicola Toschi, Andrea Duggento, Luca Passamonti
The word "e-motion" derives from the Latin word "ex-moveo" which literally means "moving away from something / somebody". Emotions are thus fundamental to prime action and goal-directed behavior with obvious implications for individual's survival. However, the brain mechanisms underlying the interactions between emotional and motor cortical systems remain poorly understood. A recent diffusion tensor imaging study in humans has reported the existence of direct anatomical connections between the amygdala and sensory/(pre)motor cortices, corroborating an initial observation in animal research...
February 23, 2017: European Journal of Neuroscience
https://www.readbyqxmd.com/read/28230725/towards-a-semantic-web-of-things-a-hybrid-semantic-annotation-extraction-and-reasoning-framework-for-cyber-physical-system
#2
Zhenyu Wu, Yuan Xu, Yunong Yang, Chunhong Zhang, Xinning Zhu, Yang Ji
Web of Things (WoT) facilitates the discovery and interoperability of Internet of Things (IoT) devices in a cyber-physical system (CPS). Moreover, a uniform knowledge representation of physical resources is quite necessary for further composition, collaboration, and decision-making process in CPS. Though several efforts have integrated semantics with WoT, such as knowledge engineering methods based on semantic sensor networks (SSN), it still could not represent the complex relationships between devices when dynamic composition and collaboration occur, and it totally depends on manual construction of a knowledge base with low scalability...
February 20, 2017: Sensors
https://www.readbyqxmd.com/read/28229131/discovering-cortical-folding-patterns-in-neonatal-cortical-surfaces-using-large-scale-dataset
#3
Yu Meng, Gang Li, Li Wang, Weili Lin, John H Gilmore, Dinggang Shen
The cortical folding of the human brain is highly complex and variable across individuals. Mining the major patterns of cortical folding from modern large-scale neuroimaging datasets is of great importance in advancing techniques for neuroimaging analysis and understanding the inter-individual variations of cortical folding and its relationship with cognitive function and disorders. As the primary cortical folding is genetically influenced and has been established at term birth, neonates with the minimal exposure to the complicated postnatal environmental influence are the ideal candidates for understanding the major patterns of cortical folding...
October 2016: Medical Image Computing and Computer-assisted Intervention: MICCAI ..
https://www.readbyqxmd.com/read/28228579/network-wide-oscillations-in-the-parkinsonian-state-alterations-in-neuronal-activities-occur-in-the-premotor-cortex-in-parkinsonian-non-human-primates
#4
Jing Wang, Luke A Johnson, Alicia L Jensen, Kenneth B Baker, Jerrold L Vitek
A number of studies suggest that Parkinson's disease (PD) is associated with alterations of neuronal activity patterns in the basal-ganglia-thalamocortical circuit. There are limited electrophysiological data, however, describing how premotor cortex, which is involved in movement and decision making, is likely impacted in PD. In this study, spontaneous local field potential (LFP) and single unit neuronal activity were recorded in the dorsal premotor area of non-human primates in both the naïve and parkinsonian state using the MPTP model of parkinsonism...
February 22, 2017: Journal of Neurophysiology
https://www.readbyqxmd.com/read/28228314/pre-hospital-acute-coronary-syndrome-care-in-kerala-india-a-qualitative-analysis
#5
Amisha Patel, P P Mohanan, Dorairaj Prabhakaran, Mark D Huffman
OBJECTIVE: Ischemic heart disease is the leading cause of death in India. Many of these deaths are due to acute coronary syndromes (ACS), which require prompt symptom recognition, care-seeking behavior, and transport to a treatment facility in the critical pre-hospital period. In India, little is known about pre-hospital management of individuals with ACS. We aim to understand the facilitators, barriers, and context of optimal pre-hospital ACS care to provide opportunities to reduce pre-hospital delays and improve acute cardiovascular care...
January 2017: Indian Heart Journal
https://www.readbyqxmd.com/read/28228108/expression-profiling-and-bioinformatic-analyses-suggest-new-target-genes-and-pathways-for-human-hair-follicle-related-micrornas
#6
Lara M Hochfeld, Thomas Anhalt, Céline S Reinbold, Marisol Herrera-Rivero, Nadine Fricker, Markus M Nöthen, Stefanie Heilmann-Heimbach
BACKGROUND: Human hair follicle (HF) cycling is characterised by the tight orchestration and regulation of signalling cascades. Research shows that micro(mi)RNAs are potent regulators of these pathways. However, knowledge of the expression of miRNAs and their target genes and pathways in the human HF is limited. The objective of this study was to improve understanding of the role of miRNAs and their regulatory interactions in the human HF. METHODS: Expression levels of ten candidate miRNAs with reported functions in hair biology were assessed in HFs from 25 healthy male donors...
February 22, 2017: BMC Dermatology
https://www.readbyqxmd.com/read/28227907/understanding-the-role-of-astrocytic-gaba-in-simulated-neural-networks
#7
Kerstin Lenk, Eero Raisanen, Jari A K Hyttinen, Kerstin Lenk, Eero Raisanen, Jari A K Hyttinen, Kerstin Lenk, Jari Ak Hyttinen, Eero Raisanen
Astrocytes actively influence the behavior of the surrounding neuronal network including changes of the synaptic plasticity and neuronal excitability. These dynamics are altered in diseases like Alzheimer's, where the release of the gliotransmitter GABA is increased by affected, so called reactive astrocytes. In this paper, we aim to simulate a neural network with altered astrocytic GABA release. Therefore, we use our developed neuron-astrocyte model, called INEXA, which includes astrocyte controlled tripartite synapses and the astrocyte-astrocyte interaction...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227870/identifying-disease-network-perturbations-through-regression-on-gene-expression-and-pathway-topology-analysis
#8
Georgios N Dimitrakopoulos, Panos Balomenos, Aristidis G Vrahatis, Kyriakos Sgarbas, Anastasios Bezerianos, Georgios N Dimitrakopoulos, Panos Balomenos, Aristidis G Vrahatis, Kyriakos Sgarbas, Anastasios Bezerianos, Kyriakos Sgarbas, Panos Balomenos, Georgios N Dimitrakopoulos, Anastasios Bezerianos, Aristidis G Vrahatis
In Systems Biology, network-based approaches have been extensively used to effectively study complex diseases. An important challenge is the detection of network perturbations which disrupt regular biological functions as a result of a disease. In this regard, we introduce a network based pathway analysis method which isolates casual interactions with significant regulatory roles within diseased-perturbed pathways. Specifically, we use gene expression data with Random Forest regression models to assess the interactivity strengths of genes within disease-perturbed networks, using KEGG pathway maps as a source of prior-knowledge pertaining to pathway topology...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227700/prediction-of-oral-cancer-recurrence-using-dynamic-bayesian-networks
#9
Konstantina Kourou, George Rigas, Konstantinos P Exarchos, Costas Papaloukas, Dimitrios I Fotiadis, Konstantina Kourou, George Rigas, Konstantinos P Exarchos, Costas Papaloukas, Dimitrios I Fotiadis, George Rigas, Konstantinos P Exarchos, Dimitrios I Fotiadis, Costas Papaloukas, Konstantina Kourou
We propose a methodology for predicting oral cancer recurrence using Dynamic Bayesian Networks. The methodology takes into consideration time series gene expression data collected at the follow-up study of patients that had or had not suffered a disease relapse. Based on that knowledge, our aim is to infer the corresponding dynamic Bayesian networks and subsequently conjecture about the causal relationships among genes within the same time-slice and between consecutive time-slices. Moreover, the proposed methodology aims to (i) assess the prognosis of patients regarding oral cancer recurrence and at the same time, (ii) provide important information about the underlying biological processes of the disease...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227367/statistical-identification-of-stimulus-activated-network-nodes-in-multi-neuron-voltage-sensitive-dye-optical-recordings
#10
Elham Fathiazar, Jorn Anemuller, Jutta Kretzberg, Elham Fathiazar, Jorn Anemuller, Jutta Kretzberg, Elham Fathiazar, Jutta Kretzberg, Jorn Anemuller
Voltage-Sensitive Dye (VSD) imaging is an optical imaging method that allows measuring the graded voltage changes of multiple neurons simultaneously. In neuroscience, this method is used to reveal networks of neurons involved in certain tasks. However, the recorded relative dye fluorescence changes are usually low and signals are superimposed by noise and artifacts. Therefore, establishing a reliable method to identify which cells are activated by specific stimulus conditions is the first step to identify functional networks...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227230/a-biologically-inspired-image-classifier-adaptive-feature-detection
#11
Jeffrey C Ames, Konstantinos P Michmizos, Jeffrey C Ames, Konstantinos P Michmizos, Jeffrey C Ames, Konstantinos P Michmizos
Today's artificial neural networks use computational models and algorithms inspired by the knowledge of the brain in the '90s. Powerful as they are, artificial networks are impressive but their domain specificity and reliance on vast numbers of labeled examples are obvious limitations. About a decade ago, spiking neural networks (SNNs) emerged as a new formalism that takes advantage of the spike timing and are particularly versatile when depicting spatio-temporal representations. The challenge now is to design rules for SNNs that can help them interact with their environment just like humans do...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227033/advanced-analytics-for-outcome-prediction-in-intensive-care-units
#12
Ali Jalali, Dieter Bender, Mohamed Rehman, Vinay Nadkanri, C Nataraj, Ali Jalali, Dieter Bender, Mohamed Rehman, Vinay Nadkanri, C Nataraj, Mohamed Rehman, Ali Jalali, Vinay Nadkanri, Dieter Bender, C Nataraj
In this paper we present a new expert knowledge based clinical decision support system for prediction of intensive care units outcome based on the physiological measurements collected during the first 48 hours of the patient's admission to the ICU. The developed CDSS algorithm is composed of several stages. First, we categorize the collected data based on the physiological organ that they represent. We then extract clinically relevant features from each data category and then rank these features based on their mutual information with the outcome...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227001/mechanism-for-safe-remote-activation-of-networked-surgical-and-poc-devices-using-dynamic-assignable-controls
#13
Martin Kasparick, Max Rockstroh, Stefan Schlichting, Frank Golatowski, Dirk Timmermann, Martin Kasparick, Max Rockstroh, Stefan Schlichting, Frank Golatowski, Dirk Timmermann, Stefan Schlichting, Martin Kasparick, Max Rockstroh, Frank Golatowski, Dirk Timmermann
The number of devices within an operating room (OR) increases continuously as well as the complexity of the complete system. One key enabler to handle the complexity is an interoperable and vendor independent system of networked medical devices. To build up such an interoperable system we use the proposed IEEE 11073 SDC standards (IEEE P11073-10207, -20701, -20702) for networked point-of-care (PoC) and surgical devices. One of the major problems within the OR is that typically every device has its own control unit...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226853/generalized-binary-noise-stimulation-enables-time-efficient-identification-of-input-output-brain-network-dynamics
#14
Yuxiao Yang, Maryam M Shanechi, Yuxiao Yang, Maryam M Shanechi, Yuxiao Yang, Maryam M Shanechi
Identification of input-output (IO) dynamics of brain networks in response to electrical stimulation is essential for devising closed-loop therapies for neurological disorders such as major depression. A critical component for accurate IO identification is the stimulation input design. The time available for open-loop stimulation to perform system identification is typically limited. While our prior design of a binary noise (BN) modulated input pattern satisfies the requirements for optimal identification and clinical safety, it does not incorporate any prior information about the underlying network...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226841/mentor-s-brain-functional-connectivity-network-during-robotic-assisted-surgery-mentorship
#15
Somayeh B Shafiei, Scott T Doyle, Khurshid A Guru, Somayeh B Shafiei, Scott T Doyle, Khurshid A Guru, Somayeh B Shafiei, Khurshid A Guru, Scott T Doyle
In many complicated cognitive-motor tasks mentoring is inevitable during the learning process. Although mentors are expert in doing the task, trainee's operation might be new for a mentor. This makes mentoring a very difficult task which demands not only the knowledge and experience of a mentor, but also his/her ability to follow trainee's movements and patiently advise him/her during the operation. We hypothesize that information binding throughout the mentor's brain areas, contributed to the task, changes as the expertise level of the trainee improves from novice to intermediate and expert...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226621/encoding-physiological-signals-as-images-for-affective-state-recognition-using-convolutional-neural-networks
#16
Guangliang Yu, Xiang Li, Dawei Song, Xiaozhao Zhao, Peng Zhang, Yuexian Hou, Bin Hu, Guangliang Yu, Xiang Li, Dawei Song, Xiaozhao Zhao, Peng Zhang, Yuexian Hou, Bin Hu, Xiaozhao Zhao, Yuexian Hou, Xiang Li, Bin Hu, Peng Zhang, Dawei Song, Guangliang Yu
Affective state recognition based on multiple modalities of physiological signals has been a hot research topic. Traditional methods require designing hand-crafted features based on domain knowledge, which is time-consuming and has not achieved a satisfactory performance. On the other hand, conducting classification on raw signals directly can also cause some problems, such as the interference of noise and the curse of dimensionality. To address these problems, we propose a novel approach that encodes different modalities of data as images and use convolutional neural networks (CNN) to perform the affective state recognition task...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226447/automatic-tissue-characterization-of-air-trapping-in-chest-radiographs-using-deep-neural-networks
#17
Awais Mansoor, Geovanny Perez, Gustavo Nino, Marius George Linguraru, Awais Mansoor, Geovanny Perez, Gustavo Nino, Marius George Linguraru, Geovanny Perez, Marius George Linguraru, Gustavo Nino, Awais Mansoor
Significant progress has been made in recent years for computer-aided diagnosis of abnormal pulmonary textures from computed tomography (CT) images. Similar initiatives in chest radiographs (CXR), the common modality for pulmonary diagnosis, are much less developed. CXR are fast, cost effective and low-radiation solution to diagnosis over CT. However, the subtlety of textures in CXR makes them hard to discern even by trained eye. We explore the performance of deep learning abnormal tissue characterization from CXR...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28225828/systematic-analysis-of-non-structural-protein-features-for-the-prediction-of-ptm-function-potential-by-artificial-neural-networks
#18
Henry M Dewhurst, Matthew P Torres
Post-translational modifications (PTMs) provide an extensible framework for regulation of protein behavior beyond the diversity represented within the genome alone. While the rate of identification of PTMs has rapidly increased in recent years, our knowledge of PTM functionality encompasses less than 5% of this data. We previously developed SAPH-ire (Structural Analysis of PTM Hotspots) for the prioritization of eukaryotic PTMs based on function potential of discrete modified alignment positions (MAPs) in a set of 8 protein families...
2017: PloS One
https://www.readbyqxmd.com/read/28225791/characterization-of-long-noncoding-rna-and-messenger-rna-signatures-in-melanoma-tumorigenesis-and-metastasis
#19
Siqi Wang, Wenliang Fan, Bing Wan, Mengqi Tu, Feng Jin, Fang Liu, Haibo Xu, Ping Han
The incidence of melanoma, the most aggressive and life-threatening form of skin cancer, has significantly risen over recent decades. Therefore, it is essential to identify the mechanisms that underlie melanoma tumorigenesis and metastasis and to explore novel and effective melanoma treatment strategies. Accumulating evidence s uggests that aberrantly expressed long noncoding RNAs (lncRNAs) have vital functions in multiple cancers. However, lncRNA functions in melanoma tumorigenesis and metastasis remain unclear...
2017: PloS One
https://www.readbyqxmd.com/read/28224079/altered-structural-brain-changes-and-neurocognitive-performance-in-pediatric-hiv
#20
Santosh K Yadav, Rakesh K Gupta, Ravindra K Garg, Vimala Venkatesh, Pradeep K Gupta, Alok K Singh, Sheema Hashem, Asma Al-Sulaiti, Deepak Kaura, Ena Wang, Francesco M Marincola, Mohammad Haris
Pediatric HIV patients often suffer with neurodevelopmental delay and subsequently cognitive impairment. While tissue injury in cortical and subcortical regions in the brain of adult HIV patients has been well reported there is sparse knowledge about these changes in perinatally HIV infected pediatric patients. We analyzed cortical thickness, subcortical volume, structural connectivity, and neurocognitive functions in pediatric HIV patients and compared with those of pediatric healthy controls. With informed consent, 34 perinatally infected pediatric HIV patients and 32 age and gender matched pediatric healthy controls underwent neurocognitive assessment and brain magnetic resonance imaging (MRI) on a 3 T clinical scanner...
2017: NeuroImage: Clinical
keyword
keyword
94793
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"