Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where Maria E. Holmboe is active.

Publication


Featured researches published by Maria E. Holmboe.


IEEE\/ASME Journal of Microelectromechanical Systems | 2009

Fabrication Methods and Performance of Low-Permeability Microfluidic Components for a Miniaturized Wearable Drug Delivery System

Mark J. Mescher; Erin E. Leary Swan; Jason O. Fiering; Maria E. Holmboe; William F. Sewell; Sharon G. Kujawa; Michael J. McKenna; Jeffrey T. Borenstein

In this paper, we describe low-permeability components of a microfluidic drug delivery system fabricated with versatile micromilling and lamination techniques. The fabrication process uses laminate sheets which are machined using XY milling tables commonly used in the printed-circuit industry. This adaptable platform for polymer microfluidics readily accommodates integration with silicon-based sensors, printed-circuit, and surface-mount technologies. We have used these methods to build components used in a wearable liquid-drug delivery system for in vivo studies. The design, fabrication, and performance of membrane-based fluidic capacitors and manual screw valves provide detailed examples of the capability and limitations of the fabrication method. We demonstrate fluidic capacitances ranging from 0.015 to 0.15 muL/kPa, screw valves with on/off flow ratios greater than 38000, and a 45times reduction in the aqueous fluid loss rate to the ambient due to permeation through a silicone diaphragm layer.


Audiology and Neuro-otology | 2009

Development of a Microfluidics-Based Intracochlear Drug Delivery Device

William F. Sewell; Jeffrey T. Borenstein; Zhiqiang Chen; Jason O. Fiering; Ophir Handzel; Maria E. Holmboe; Ernest S. Kim; Sharon G. Kujawa; Michael J. McKenna; Mark M. Mescher; Brian A. Murphy; Erin E. Leary Swan; Marcello Peppi; Sarah Tao

Background: Direct delivery of drugs and other agents into the inner ear will be important for many emerging therapies, including the treatment of degenerative disorders and guiding regeneration. Methods: We have taken a microfluidics/MEMS (MicroElectroMechanical Systems) technology approach to develop a fully implantable reciprocating inner-ear drug-delivery system capable of timed and sequenced delivery of agents directly into perilymph of the cochlea. Iterations of the device were tested in guinea pigs to determine the flow characteristics required for safe and effective delivery. For these tests, we used the glutamate receptor blocker DNQX, which alters auditory nerve responses but not cochlear distortion product otoacoustic emissions. Results: We have demonstrated safe and effective delivery of agents into the scala tympani. Equilibration of the drug in the basal turn occurs rapidly (within tens of minutes) and is dependent on reciprocating flow parameters. Conclusion: We have described a prototype system for the direct delivery of drugs to the inner ear that has the potential to be a fully implantable means for safe and effective treatment of hearing loss and other diseases.


Chemical Senses | 2010

Mouse Urinary Biomarkers Provide Signatures of Maturation, Diet, Stress Level, and Diurnal Rhythm

Michele L. Schaefer; Kanet Wongravee; Maria E. Holmboe; Nina Heinrich; Sarah J. Dixon; Julie E. Zeskind; Heather M. Kulaga; Richard G. Brereton; Randall R. Reed; Jose Trevejo

Body fluids such as urine potentially contain a wealth of information pertaining to age, sex, social and reproductive status, physiologic state, and genotype of the donor. To explore whether urine could encode information regarding environment, physiology, and development, we compared the volatile compositions of mouse urine using solid-phase microextraction and gas chromatography-mass spectrometry (SPME-GC/MS). Specifically, we identified volatile organic compounds (VOCs) in individual urine samples taken from inbred C57BL/6J-H-2(b) mice under several experimental conditions-maturation state, diet, stress, and diurnal rhythms, designed to mimic natural variations. Approximately 1000 peaks (i.e., variables) were identified per comparison and of these many were identified as potential differential biomarkers. Consistent with previous findings, we found groups of compounds that vary significantly and consistently rather than a single unique compound to provide a robust signature. We identified over 49 new predictive compounds, in addition to identifying several published compounds, for maturation state, diet, stress, and time-of-day. We found a considerable degree of overlap in the chemicals identified as (potential) biomarkers for each comparison. Chemometric methods indicate that the strong group-related patterns in VOCs provide sufficient information to identify several parameters of natural variations in this strain of mice including their maturation state, stress level, and diet.


Analytical Chemistry | 2009

Variable Selection Using Iterative Reformulation of Training Set Models for Discrimination of Samples: Application to Gas Chromatography/Mass Spectrometry of Mouse Urinary Metabolites

Kanet Wongravee; Nina Heinrich; Maria E. Holmboe; Michele L. Schaefer; Randall R. Reed; Jose Trevejo; Richard G. Brereton

The paper discusses variable selection as used in large metabolomic studies, exemplified by mouse urinary gas chromatography of 441 mice in three experiments to detect the influence of age, diet, and stress on their chemosignal. Partial least squares discriminant analysis (PLS-DA) was applied to obtain class models, using a procedure of 20,000 iterations including the bootstrap for model optimization and random splits into test and training sets for validation. Variables are selected using PLS regression coefficients on the training set using an optimized number of components obtained from the bootstrap. The variables are ranked in order of significance, and the overall optimal variables are selected as those that appear as highly significant over 100 different test and training set splits. Cost/benefit analysis of performing the model on a reduced number of variables is also illustrated. This paper provides a strategy for properly validated methods for determining which variables are most significant for discriminating between two groups in large metabolomic data sets avoiding the common pitfall of overfitting if variables are selected on a combined training and test set and also taking into account that different variables may be selected each time the samples are split into training and test sets using iterative procedures.


Bioinformatics | 2005

Autoregressive modeling of analytical sensor data can yield classifiers in the predictor coefficient parameter space

Melissa D. Krebs; Robert D. Tingley; Julie E. Zeskind; Joung Mo Kang; Maria E. Holmboe; Cristina E. Davis

SUMMARY The analysis of chromatographic data resulting from complex chemical mixtures is challenging. Components may co-elute, causing their signals to overlap. An algorithm that will increase the signal-to-noise ratio so compounds present in low abundance can be better distinguished from noise is useful in this type of analysis. The autoregressive (AR) filter offers the advantage of smoothing chromatograms to increase this ratio, while also offering data compression and increased resolution. Furthermore, this filter can be useful for classification, as the roots of the predictor coefficient vectors represent features present in the data and can therefore be used for pattern recognition. In this paper, we present a novel method for applying AR filtering to chromatogram data. We show that the AR filter outperforms the Savitzky-Golay filter for smoothing noise while retaining important information within chromatograms, and also that AR correlation coefficients have the potential to be used to classify chromatogram data into groups. CONTACT [email protected].


Audiology and Neuro-otology | 2009

Contents Vol. 14, 2009

Jeffrey P. Harris; Alec N. Salt; Stefan K. Plontke; Kimanh D. Nguyen; Lloyd B. Minor; Charles C. Della Santina; John P. Carey; Amanda Hu; Lorne S. Parnes; Christine T. Dinh; Thomas R. Van De Water; Xiaobo Wang; Luis A. Dellamary; Rayne Fernandez; Anne Harrop; Elizabeth M. Keithley; Qiang Ye; Jay Lichter; Carl Lebel; Fabrice Piu; Sangeeta Maini; Halina Lisnichuk; Hayden Eastwood; Darren Pinder; David E. James; Rachael T. Richardson; Andrew Chang; Tim Connolly; David J. Sly; Gordana Kel

Maurizio Barbara, Rome Olivier Bertrand, Bron F. Owen Black, Portland Th omas Brandt, München Barbara Canlon, Stockholm John P. Carey, Baltimore Douglas A. Cotanche, Boston Cor W.R.J. Cremers, Nijmegen Norbert Dillier, Zürich Robert Dobie, Sacramento Manuel Don, Los Angeles Jill B. Firszt, St. Louis Andrew Forge, London Bernard Fraysse, Toulouse Rick Friedman, Los Angeles Bruce J. Gantz, Iowa City Pablo Gil-Loyzaga, Madrid Anthony W. Gummer, Tübingen James W. Hall III, Gainesville Joseph W. Hall III, Chapel Hill Michael Halmagyi, Camperdown Rudolf Häusler, Bern Vicente Honrubia, Los Angeles Gary D. Housley, Auckland Karl-Bernd Hüttenbrink, Köln Pawel J. Jastreboff , Atlanta Margaret A. Kenna, Boston Philippe P. Lefebvre, Liège Bernd Lütkenhöner, Münster Linda L. Luxon, London Geoff rey A. Manley, Freising Alessandro Martini, Ferrara Jennifer R. Melcher, Boston Saumil N. Merchant, Boston Brian C.J. Moore, Cambridge David R. Moore, Nottingham Cynthia C. Morton, Boston Donata Oertel, Madison Kaoru Ogawa, Tokyo Stephen J. O’Leary, Parkville Alan R. Palmer, Nottingham Lorne S. Parnes, London, Ont. Jean-Luc Puel, Montpellier Ramesh Rajan, Monash Yehoash Raphael, Ann Arbor J. Th omas Roland, New York John J. Rosowski, Boston Rudolf Rübsamen, Leipzig Mario A. Ruggero, Evanston Leonard P. Rybak, Springfi eld Richard J. Salvi, Buff alo Robert V. Shannon, Los Angeles Guido F. Smoorenburg, Besse sur Issole Haim Sohmer, Jerusalem Olivier Sterkers, Clichy Istvan Sziklai, Debrecen Peter R. Th orne, Auckland Shin-ichi Usami, Matsumoto P. Ashley Wackym, Milwaukee Tatsuya Yamasoba, Tokyo Fan-Gang Zeng, Irvine Basic Science and Clinical Research in the Auditory and Vestibular Systems and Diseases of the Ear


Biomedical Microdevices | 2009

Local drug delivery with a self-contained, programmable, microfluidic system.

Jason O. Fiering; Mark J. Mescher; E. E. Leary Swan; Maria E. Holmboe; Brian A. Murphy; Zhiqiang Chen; Marcello Peppi; William F. Sewell; Michael J. McKenna; Sharon G. Kujawa; Jeffrey T. Borenstein


Chemometrics and Intelligent Laboratory Systems | 2006

Alignment of gas chromatography-mass spectrometry data by landmark selection from complex chemical mixtures

Melissa D. Krebs; Robert D. Tingley; Julie E. Zeskind; Maria E. Holmboe; Joung Mo Kang; Cristina E. Davis


Metabolomics | 2009

Monte-Carlo methods for determining optimal number of significant variables. Application to mouse urinary profiles

Kanet Wongravee; John Hall; Maria E. Holmboe; Michele L. Schaefer; Randall R. Reed; Jose Trevejo; Richard G. Brereton


Journal of Chemometrics | 2009

Use of cluster separation indices and the influence of outliers : application of two new separation indices, the modified silhouette index and the overlap coefficient to simulated data and mouse urine metabolomic profiles

Sarah J. Dixon; Nina Heinrich; Maria E. Holmboe; Michele L. Schaefer; Randall R. Reed; Jose Trevejo; Richard G. Brereton

Collaboration


Dive into the Maria E. Holmboe's collaboration.

Top Co-Authors

Avatar
Top Co-Authors

Avatar

Randall R. Reed

Howard Hughes Medical Institute

View shared research outputs
Top Co-Authors

Avatar

Jose Trevejo

Charles Stark Draper Laboratory

View shared research outputs
Top Co-Authors

Avatar

Michele L. Schaefer

Johns Hopkins University School of Medicine

View shared research outputs
Top Co-Authors

Avatar

Nina Heinrich

Charles Stark Draper Laboratory

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Jason O. Fiering

Charles Stark Draper Laboratory

View shared research outputs
Top Co-Authors

Avatar

Jeffrey T. Borenstein

Charles Stark Draper Laboratory

View shared research outputs
Top Co-Authors

Avatar

Julie E. Zeskind

Charles Stark Draper Laboratory

View shared research outputs
Top Co-Authors

Avatar

Sharon G. Kujawa

Massachusetts Eye and Ear Infirmary

View shared research outputs
Researchain Logo
Decentralizing Knowledge