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Biological machines

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https://www.readbyqxmd.com/read/28339580/the-integration-of-orthodontic-miniscrews-under-mechanical-loading-a-pre-clinical-study-in-rabbit
#1
B Giuliano Maino, Alberto Di Blasio, Davide Spadoni, Francesca Ravanetti, Carlo Galli, Antonio Cacchioli, Christos Katsaros, Mauro Gandolfini
Introduction: Orthodontic miniscrews are an increasingly popular choice to achieve absolute anchorage. The temporary use of miniscrews and their recent introduction have limited the debate over the biological aspect of the materials to that of the surface that permeates the field of dental implants. The aim of the present study was to investigate the integration of grade 5 titanium mini-implants with machined or sand blasted acid etched surface (SAE) under mechanical load in a rabbit tibia model of implant integration...
January 18, 2017: European Journal of Orthodontics
https://www.readbyqxmd.com/read/28328004/red-ml-a-novel-effective-rna-editing-detection-method-based-on-machine-learning
#2
Heng Xiong, Dongbing Liu, Qiye Li, Mengyue Lei, Liqin Xu, Liang Wu, Zongji Wang, Shancheng Ren, Wangsheng Li, Min Xia, Lihua Lu, Haorong Lu, Yong Hou, Shida Zhu, Xin Liu, Yinghao Sun, Jian Wang, Huanming Yang, Kui Wu, Xun Xu, Leo J Lee
Background: With the advancement of second generation sequencing techniques, our ability to detect and quantify RNA editing on a global scale has been vastly improved. As a result, RNA editing is now being studied under a growing number of biological conditions so that its biochemical mechanisms and functional roles can be further understood. However, a major barrier that prevents RNA editing from being a routine RNA-seq analysis, similar to gene expression and splicing analysis for example, is the lack of user-friendly and effective computational tools...
March 2, 2017: GigaScience
https://www.readbyqxmd.com/read/28325017/diffuse-reflectance-spectroscopy-can-differentiate-high-grade-and-low-grade-prostatic-carcinoma
#3
Priya N Werahera, Edward A Jasion, E David Crawford, M Scott Lucia, Adrie van Bokhoven, Holly T Sullivan, Fernando J Kim, Paul D Maroni, J David Port, John W Daily, Francisco G La Rosa
Prostate tumors are graded by the revised Gleason Score (GS) which is the sum of the two predominant Gleason grades present ranging from 6-10. GS 6 cancer exclusively with Gleason grade 3 is designated as low grade (LG) and correlates with better clinical prognosis for patients. GS >7 cancer with at least one of the Gleason grades 4 and 5 is designated as HG indicate worse prognosis for patients. Current transrectal ultrasound guided prostate biopsies often fail to correctly diagnose HG prostate cancer due to sampling errors...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28323285/utilization-of-machine-learning-for-prediction-of-post-traumatic-stress-a-re-examination-of-cortisol-in-the-prediction-and-pathways-to-non-remitting-ptsd
#4
I R Galatzer-Levy, S Ma, A Statnikov, R Yehuda, A Y Shalev
To date, studies of biological risk factors have revealed inconsistent relationships with subsequent post-traumatic stress disorder (PTSD). The inconsistent signal may reflect the use of data analytic tools that are ill equipped for modeling the complex interactions between biological and environmental factors that underlay post-traumatic psychopathology. Further, using symptom-based diagnostic status as the group outcome overlooks the inherent heterogeneity of PTSD, potentially contributing to failures to replicate...
March 21, 2017: Translational Psychiatry
https://www.readbyqxmd.com/read/28322859/decoding-the-encoding-of-functional-brain-networks-an-fmri-classification-comparison-of-non-negative-matrix-factorization-nmf-independent-component-analysis-ica-and-sparse-coding-algorithms
#5
Jianwen Xie, Pamela K Douglas, Ying Nian Wu, Arthur L Brody, Ariana E Anderson
BACKGROUND: Brain networks in fMRI are typically identified using spatial independent component analysis (ICA), yet other mathematical constraints provide alternate biologically-plausible frameworks for generating brain networks. Non-negative Matrix Factorization (NMF) would suppress negative BOLD signal by enforcing positivity. Spatial sparse coding algorithms (L1 Regularized Learning and K-SVD) would impose local specialization and a discouragement of multitasking, where the total observed activity in a single voxel originates from a restricted number of possible brain networks...
March 17, 2017: Journal of Neuroscience Methods
https://www.readbyqxmd.com/read/28319238/behavioral-and-neural-constraints-on-hierarchical-representations
#6
Odelia Schwartz, Luis Gonzalo Sanchez Giraldo
Central to behavior and cognition is the way that sensory stimuli are represented in neural systems. The distributions over such stimuli enjoy rich structure; however, how the brain captures and exploits these regularities is unclear. Here, we consider different sources of perhaps the most prevalent form of structure, namely hierarchies, in one of its most prevalent cases, namely the representation of images. We review experimental approaches across a range of subfields, spanning inference, memory recall, and visual adaptation, to investigate how these constrain hierarchical representations...
March 1, 2017: Journal of Vision
https://www.readbyqxmd.com/read/28316652/a-novel-descriptor-based-on-atom-pair-properties
#7
Masataka Kuroda
BACKGROUND: Molecular descriptors have been widely used to predict biological activities and physicochemical properties or to analyze chemical libraries on the basis of similarity. Although fingerprints and properties are generally used as descriptors, neither is perfect for these purposes. A fingerprint can distinguish between molecules, whereas a property may not do the same in certain cases, and vice versa. When the number of the training set is especially small, the construction of good predictive models is difficult...
2017: Journal of Cheminformatics
https://www.readbyqxmd.com/read/28303936/all-passive-pixel-super-resolution-of-time-stretch-imaging
#8
Antony C S Chan, Ho-Cheung Ng, Sharat C V Bogaraju, Hayden K H So, Edmund Y Lam, Kevin K Tsia
Based on image encoding in a serial-temporal format, optical time-stretch imaging entails a stringent requirement of state-of-the-art fast data acquisition unit in order to preserve high image resolution at an ultrahigh frame rate - hampering the widespread utilities of such technology. Here, we propose a pixel super-resolution (pixel-SR) technique tailored for time-stretch imaging that preserves pixel resolution at a relaxed sampling rate. It harnesses the subpixel shifts between image frames inherently introduced by asynchronous digital sampling of the continuous time-stretch imaging process...
March 17, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28294138/machine-learning-applications-in-cell-image-analysis
#9
REVIEW
Andrey Kan
Machine learning refers to a set of automatic pattern recognition methods that have been successfully applied across various problem domains, including biomedical image analysis. This review focuses on machine learning applications for image analysis in light microscopy experiments with typical tasks of segmenting and tracking individual cells, and modelling of reconstructed lineage trees. After describing a typical image analysis pipeline and highlighting challenges of automatic analysis (e.g., variability in cell morphology, tracking in presence of clutters) this review gives a brief historical outlook of machine learning, followed by basic concepts and definitions required for understanding examples...
March 15, 2017: Immunology and Cell Biology
https://www.readbyqxmd.com/read/28294058/recognizing-and-predicting-thioether-bridges-formed-by-lanthionine-and-%C3%AE-methyllanthionine-in-lantibiotics-using-a-random-forest-approach-with-feature-selection
#10
ShaoPeng Wang, Yu-Hang Zhang, Ning Zhang, Lei Chen, Tao Huang, Yu-Dong Cai
Lantibiotics, which are usually produced from Gram-positive bacteria, are regarded as one type of special bacteriocins. Lantibiotics have unsaturated amino acid residues formed by lanthionine (Lan) and β-methyllanthionine (MeLan) residues as a ring structure in the peptide. They are derived from the serine and threonine residues and are essential to preventing the growth of other similar strains. In this pioneering work, we firstly proposed a machine learning method to recognize and predict the Lan and MeLan residues in the protein sequences of lantibiotics...
March 10, 2017: Combinatorial Chemistry & High Throughput Screening
https://www.readbyqxmd.com/read/28293256/ranking-support-vector-machine-with-kernel-approximation
#11
Kai Chen, Rongchun Li, Yong Dou, Zhengfa Liang, Qi Lv
Learning to rank algorithm has become important in recent years due to its successful application in information retrieval, recommender system, and computational biology, and so forth. Ranking support vector machine (RankSVM) is one of the state-of-art ranking models and has been favorably used. Nonlinear RankSVM (RankSVM with nonlinear kernels) can give higher accuracy than linear RankSVM (RankSVM with a linear kernel) for complex nonlinear ranking problem. However, the learning methods for nonlinear RankSVM are still time-consuming because of the calculation of kernel matrix...
2017: Computational Intelligence and Neuroscience
https://www.readbyqxmd.com/read/28292312/comprehensive-discovery-of-subsample-gene-expression-components-by-information-explanation-therapeutic-implications-in-cancer
#12
Shirley Pepke, Greg Ver Steeg
BACKGROUND: De novo inference of clinically relevant gene function relationships from tumor RNA-seq remains a challenging task. Current methods typically either partition patient samples into a few subtypes or rely upon analysis of pairwise gene correlations that will miss some groups in noisy data. Leveraging higher dimensional information can be expected to increase the power to discern targetable pathways, but this is commonly thought to be an intractable computational problem. METHODS: In this work we adapt a recently developed machine learning algorithm for sensitive detection of complex gene relationships...
March 15, 2017: BMC Medical Genomics
https://www.readbyqxmd.com/read/28288857/a-reductionist-approach-to-extract-robust-molecular-markers-from-microarray-data-series-isolating-markers-to-track-osseointegration
#13
Anwesha Barik, Satarupa Banerjee, Santanu Dhara, Nishant Chakravorty
Complexities in the full genome expression studies hinder the extraction of tracker genes to analyze the course of biological events. In this study, we demonstrate the applications of supervised machine learning methods to reduce the irrelevance in microarray data series and thereby extract robust molecular markers to track biological processes. The methodology has been illustrated by analyzing whole genome expression studies on bone-implant integration (ossointegration). Being a biological process, osseointegration is known to leave a trail of genetic footprint during the course...
March 10, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28287524/a-web-tool-for-generating-high-quality-machine-readable-biological-pathways
#14
Miguel Ramirez-Gaona, Ana Marcu, Allison Pon, Jason Grant, Anthony Wu, David S Wishart
PathWhiz is a web server built to facilitate the creation of colorful, interactive, visually pleasing pathway diagrams that are rich in biological information. The pathways generated by this online application are machine-readable and fully compatible with essentially all web-browsers and computer operating systems. It uses a specially developed, web-enabled pathway drawing interface that permits the selection and placement of different combinations of pre-drawn biological or biochemical entities to depict reactions, interactions, transport processes and binding events...
February 8, 2017: Journal of Visualized Experiments: JoVE
https://www.readbyqxmd.com/read/28286168/predcar-site-carbonylation-sites-prediction-in-proteins-using-support-vector-machine-with-resolving-data-imbalanced-issue
#15
Md Al Mehedi Hasan, Jinyan Li, Shamim Ahmad, Md Khademul Islam Molla
The carbonylation is found as an irreversible post-translational modification and considered a biomarker of oxidative stress. It plays major role not only in orchestrating various biological processes but also associated with some diseases such as Alzheimer's disease, diabetes, and Parkinson's disease. However, since the experimental technologies are costly and time-consuming to detect the carbonylation sites in proteins, an accurate computational method for predicting carbonylation sites is an urgent issue which can be useful for drug development...
March 9, 2017: Analytical Biochemistry
https://www.readbyqxmd.com/read/28283691/-modulation-of-the-intestinal-microbiota-by-nutritional-interventions
#16
S Derer, H Lehnert, C Sina, A E Wagner
Humans live in symbiosis with billions of commensal bacteria. The so-called microbiota live on different biological interfaces such as the skin, the urogenital tract and the gastrointestinal tract. Commensal bacteria replace potentially pathogenic microbes, synthesize vitamins and ferment dietary fibre. An imbalance in the bacterial composition of the intestinal microbiota has been associated with various diseases including gut-associated disorders such as inflammatory bowel diseases, colorectal cancer and nonalcoholic fatty liver disease...
March 10, 2017: Der Internist
https://www.readbyqxmd.com/read/28277504/synthetic-biology-enter-the-living-machine
#17
Herbert Sauro
No abstract text is available yet for this article.
March 8, 2017: Nature
https://www.readbyqxmd.com/read/28275557/a-quantitative-framework-for-the-analysis-of-multimodal-optical-microscopy-images
#18
Andrew J Bower, Benjamin Chidester, Joanne Li, Youbo Zhao, Marina Marjanovic, Eric J Chaney, Minh N Do, Stephen A Boppart
BACKGROUND: Multimodal optical microscopy, a set of imaging techniques based on unique, yet complementary contrast mechanisms and spatially and temporally co-registered data acquisition, has emerged as a powerful biomedical tool. However, the analysis of the dense, high-dimensional datasets acquired by these instruments remains mostly qualitative and restricted to analysis of each modality individually. METHODS: Using a custom-built multimodal nonlinear optical microscope, high dimensional datasets were acquired for automated classification of functional cell states as well as identification of histopathological features in tissues slices...
February 2017: Quantitative Imaging in Medicine and Surgery
https://www.readbyqxmd.com/read/28269154/an-empirical-study-of-parallel-solutions-for-glcm-calculation-of-diffraction-images
#19
John Dixon, Junhua Ding
Feature calculation of large amount of images is time consuming. The GPU based CUDA framework offers an affordable solution for calculating image features in parallel. The research focused on an empirical study of different implementations of a general-purpose GPU-based solution for calculating Gray-Level Co-occurrence Matrices (GLCM) and associated features of diffraction images of biological cells. The GLCM features calculated from the diffraction images are used for rapid cell classification with the machine learning algorithm Support Vector Machine (SVM)...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28269014/learning-approaches-to-improve-prediction-of-drug-sensitivity-in-breast-cancer-patients
#20
Turki Turki, Zhi Wei
Predicting drug response to cancer disease is an important problem in modern clinical oncology that attracted increasing recent attention from various domains such as computational biology, machine learning, and data mining. Cancer patients respond differently to each cancer therapy owing to disease diversity, genetic factors, and environmental causes. Thus, oncologists aim to identify the effective therapies for cancer patients and avoid adverse drug reactions in patients. By predicting the drug response to cancer, oncologists gain full understanding of the effective treatments on each patient, which leads to better personalized treatment...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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