Becton Dickinson and Company Limited

Animas Technologies, LLC

Animas Corporation

Miroslaw Bartkowiak

Dwight Livingston

Mark A Talmer

Janet A Tamada

Robert L Campbell

Thomas D Haubert

Jack H Kessler

Ammon David Lentz

Matthew J Lesho

Wesley S Harper

Eray Kulcu

James A Prescott

Richard L Moore

Michael L Marshall

Gregory S Kramer

Michael Justin Lizzi

Scott Nicholas Danhof

Melody M H Kuroda

M Scott Ulrich

Michael R Walters

Artis R Lockhart

Adam C Curry

Kristin Weidemaier

Alexander W Clark

Andrea Liebmann-Vinson

Eric Fallows

Randy J Somerville

Timothy G Foley, Jr

David S Sebba

Kevin G Dolan

Ernie Ritchey

Donald E Gorelick

Spencer Lovette

Wendy Dale Woodley

Erin Gooch Carruthers

Jeffrey S Ojala

Janet A, Tamada

Eric A Fallows

Melody MH Kuroda

Shawn P Beaty

David A Lentz

Provided herein are methods, systems, and devices for detecting and/or identifying one or more specific microorganisms in a culture sample. Indicator particles, such as surface enhanced Raman spectroscopy (SERS)-active nanoparticles, each having associated therewith one or more specific binding members having an affinity for the one or more microorganisms of interest, can form a complex with specific microorganisms in the culture sample. Further, agitating magnetic capture particles also having associated therewith one or more specific binding members having an affinity for the one or more microorganisms of interest can be used to capture the microorganism-indicator particle complex and concentrate the complex in a localized area of an assay vessel for subsequent detection and identification. The complex can be dispersed, pelleted, and redispersed so that the culture sample can be retested a number of times during incubation so as to allow for real-time monitoring of the culture sample.

Methods, systems, and devices for detecting and identifying microorganisms in microbiological culture samples

Systems and methods for calculating an initial amount of target nucleic acid Nin a sample are provided. A plurality of fluorescent measurements is received. Each respective fluorescent measurement FSis taken in a different cycle n in a PCR amplification experiment of the sample. Then, a model for the PCR amplification experiment is computed. For each respective fluorescent measurement, the model comprises a respective equation for N, where (i) Nis the calculated amount of the target nucleic acid in cycle n of the corresponding PCR amplification experiment, and (ii) the equation for Nis expressed in terms of K and N, where K is the Michaelis-Menton constant. The model can be refined by adjusting K and Nuntil differences between model values Nand corresponding fluorescent measurements are minimized, thereby calculating the initial amount of a target nucleic acid Nas the minimized value for Nfor the model.

Systems and methods for determining an amount of starting reagent using the polymerase chain reaction

The present invention comprises one or more microprocessors programmed to execute methods for improving the performance of an analyte monitoring device including prediction of glucose levels in a subject by utilizing a predicted slower-time constant (1/k). In another aspect of the invention, pre-exponential terms (1/c) can be used to provide a correction for signal decay (e.g., a Gain Factor). In other aspects, the present invention relates to one or more microprocessors comprising programming to control execution of (i) methods for conditional screening of data points to reduce skipped measurements, (ii) methods for qualifying interpolated/extrapolated analyte measurement values, (iii) various integration methods to obtain maximum integrals of analyte-related signals, as well as analyte monitoring devices comprising such microprocessors. Further, the present invention relates to algorithms for improved optimization of parameters for use in prediction models that require optimization of adjustable parameters.

Micropressors, devices and methods for use in analyte monitoring systems

Microprocessors, devices and methods for use in analyte monitoring systems

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San Jose, CA, United States of America

Miroslaw Bartkowiak