Lipoma with dumb-bell extradural extension through the intervertebral foramen into the spinal canal

Park, Jin-Soo; Shirachi, Isao; Sato, Kengo; Ando, Noriyuki; Nagata, Kensei

doi:10.3171/spi.2005.2.1.0069

Cited by 8 publications

(8 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…This will serve to confirm the diagnosis as well as to plan the surgery, acting as it does to confirm the presence or absence of extradural extension. 5 The high rate of postoperative complications should also be stressed to both clinicians and patients, and the possibility of not returning to rugby subsequently may help to guide the timing of any operation.…”

Section: Discussionmentioning

confidence: 99%

Soft tissue neck lumps in rugby union players

Dearing

2006

Br J Sports Med

View full text Add to dashboard Cite

Dorsal neck masses are well recognised in front row rugby union players. Previously undescribed in the medical literature, they may present in the primary or secondary care setting when they become symptomatic. Often misdiagnosed as lipomata, they may in fact be fibrous and deeply connected, with the consequences of embarking on surgery subsequently underestimated. This paper describes an epidemiological study using the rugby union media and gives key points for healthcare professionals involved in the management of such masses.

show abstract

Section: Discussionmentioning

confidence: 99%

Soft tissue neck lumps in rugby union players

Dearing

2006

Br J Sports Med

View full text Add to dashboard Cite

show abstract

“…cuando son de tamaño pequeño 4 . Dado que este tipo de tumores se pueden extender desde la base del cráneo hasta el mediastino superior, pueden causar una amplia variedad de síntomas dependiendo de la porción de la vía aerodigestiva que afecten.…”

Section: Figuraunclassified

Lipoma retrofaríngeo causante de apnea del sueño y disfagia

López

Ramírez

Ciriaco³

et al. 2015

Gaceta Mexicana de Oncología

View full text Add to dashboard Cite

show abstract

“…It has particularly appeared in papers on dimensionality reduction, clustering or classification for microarray expression time-series data (e.g., [22-24]). More relevantly to the present paper, several works have proposed estimating linear dynamical models from (microarray) expression data [25,26]. As will be explained in greater detail below, this approach to dynamical modeling allows the estimation problem to be reduced to one of regression, which carries both statistical and computational advantages.…”

Section: Introductionmentioning

confidence: 99%

Functional data analysis for identifying nonlinear models of gene regulatory networks

Summer

Perkins

2010

BMC Genomics

View full text Add to dashboard Cite

BackgroundA key problem in systems biology is estimating dynamical models of gene regulatory networks. Traditionally, this has been done using regression or other ad-hoc methods when the model is linear. More detailed, realistic modeling studies usually employ nonlinear dynamical models, which lead to computationally difficult parameter estimation problems. Functional data analysis methods, however, offer a means to simplify fitting by transforming the problem from one of matching modeled and observed dynamics to one of matching modeled and observed time derivatives–a regression problem, albeit a nonlinear one.ResultsWe formulate a functional data analysis approach for estimating the parameters of nonlinear dynamical models and evaluate this approach on data from two real systems, the gap gene system of Drosophila melanogaster and the synthetic IRMA network, which was created expressly as a test case for genetic network inference. We also evaluate the approach on simulated data sets generated by the GeneNetWeaver program, the basis for the annual DREAM reverse engineering challenge. We assess the accuracy with which the correct regulatory relationships within the networks are extracted, and consider alternative methods of regularization for the purpose of overfitting avoidance. We also show that the computational efficiency of the functional data analysis approach, and the decomposability of the resulting regression problem, allow us to explicitly enumerate and evaluate all possible regulator combinations for every gene. This gives deeper insight into the the relevance of different regulators or regulator combinations, and lets one check for alternative regulatory explanations.ConclusionsFunctional data analysis is a powerful approach for estimating detailed nonlinear models of gene expression dynamics, allowing efficient and accurate estimation of regulatory architecture.

show abstract

Lipoma with dumb-bell extradural extension through the intervertebral foramen into the spinal canal

Cited by 8 publications

References 7 publications

Soft tissue neck lumps in rugby union players

Soft tissue neck lumps in rugby union players

Lipoma retrofaríngeo causante de apnea del sueño y disfagia

Functional data analysis for identifying nonlinear models of gene regulatory networks

Contact Info

Product

Resources

About