Colgate Palmolive Company

Rutgers, the State University of New Jersey

Holerca, Marian N.

Tang, Xiaozhong

Popoff, Christine

Wu, Donghui

Donghui Wu

Iraklis Pappas

Long Pan

Ravi Subramanyam

Chi-Yuan Cheng

Daniel Smith

John J Gatzemeyer

Amjad Farooq

Marija Heibel

Michael Prencipe

Sharon Kennedy

Richard Scott Robinson

Andre Morgan

Matthew Lee Kolb

Rajnish Kohli

Paul Donald Carse

Robert Moskovich

Eduardo J Jimenez

Douglas J Hohlbein

Suman Kumar Chopra

Alan Vincent Sorrentino

Kenneth Gerald Waguespack

James G Masters

Richard J Sullivan

Lynette Anne Zaidel

Christine Boyke

Sarita Vera Mello

Tatiana Brinzari

Ralph Peter Santarpia, Iii

Venda Porter Maloney

Stanislav Jaracz

Michael Stranick

Lisa Manus

Michael Fitzgerald

Hongwei Shen

Guofeng Xu

Harsh Mahendra Trivedi

Laurence Du-Thumm

Zhigang Hao

Marian N Holerca

LaTonya Kilpatrick-Liverman

Jennifer Gronlund

Xiaozhong Tang

Bartosz Luczynski

Dong Hyun Kim

Karen Drehs

John P Rouse

Eric Simon

Jane Ong

Gary Edward Tambs

Virginia Monsul Barnes

Sergio Leite

Diane Cummins

Qin Wang

Wilbens Josias

Zeenat F Nabi

Shujiang Cheng

Xiang Chen

Vyoma Patel

Shamim Alam Ansari

Jeffrey M Miller

Mehdi Javanmard

David Kyung Min Lee

Diana Scala

Qiang Wu

Christine M Popoff

Venda Porter

Halyna Siomyk

Preston T Snee

Karen J DePierro

Kenneth Waguespack

Robin S Cabanas

Zeenat Nabi

Adam Pepperney

Dennis Zhang

Zhichao Hu

Matthew J Eibling

Sheridan Tang

Zhongtian Lin

Armen Shamirian

Jianye Sui

Jairaj Mattai

Minli Shi

Diane Curley

Constantina Christopoulou

Joaquin Bautista Garcia

Andre Michelle Morgan

Ralph Peter Santarpia Iii

Eric A Simon

Andre M Morgan

Laurence D Du-Thumm

Shamim Ansari

Jeffrey Miller

Ralph Peter Iii Santarpia

Ralph Peter Santarpia Lll

Karen Depierro

Daniel W Smith

In one embodiment, a method includes receiving identities of features of a first composition, and receiving a value of a property of the first composition. A learning model is trained using values of predefined characteristics of the features of the first composition, and the value of the property of the first composition. The learning model is then provided identities of second features of a second composition. Using the learning model, a value of a property of the second composition is determined and displayed.

Systems and methods for preparing compositions

Described herein are methods, systems and devices for rapidly detecting biomarkers in a biological sample.

Methods, devices and systems for quantifying biomarkers

A system, apparatus, and/or method is disclosed for determining a value of a property of a considered chemical composition. An identity of a sample chemical composition may be received. A sample chemical composition may comprise ingredients. Each of the ingredients may be associated with a value of a chemoinformatic property of chemoinformatic properties of the sample chemical composition. A value of a property of the sample chemical composition and at least one of (1) the identity of the sample chemical composition or (2) the values of the chemoinformatic properties of the ingredients of the sample chemical composition may be input into a model. The value of the property of the considered chemical composition may be determined, via the model, based on at least one of (1) an identity of the considered chemical composition or (2) values of chemoinformatic properties of ingredients of the considered chemical composition.

Systems and methods for preparing a product

This invention relates to oral care compositions comprising an effective amount of a basic amino acid in free or salt form, together with an antibacterial agent, and to methods of using and of making such compositions.

Oral care product and methods of use and manufacture thereof

A system, apparatus, and/or method is disclosed for producing a personal care product. An identity of a considered chemical composition may be input into a model (e.g., a machine learning model). The identity of the considered chemical composition may include ingredients. Each of the ingredients of the considered chemical composition may be associated with a value of a chemoinformatic property of chemoinformatic properties of the considered chemical composition. A value of the property of the considered chemical composition may be determined via the model. The value may be based on the identity of the considered chemical composition. The property of the considered chemical composition may be affected by an interaction of at least two of the ingredients of the considered chemical composition. A personal care product comprised of the considered chemical composition may be produced.

Systems and methods for producing personal care products

An oral care composition comprising primarily insoluble forms of zinc compounds and stannous compounds, as well as methods of using the same in the treatment or prevention of gingivitis, plaque, and dental caries.

Oral care compositions

Personal care compositions including a naringin:zinc complex and methods for preparing and using the same are provided. The personal care compositions may include a carrier and a naringin:zinc complex having a 2:1 naringin to zinc molar ratio.

Personal care compositions including naringin:zinc complexes and methods for the same

Provided herein are methods of treating one or more symptoms of a gastric disorder in the oral cavity of a subject in need thereof, wherein the method comprises applying to the subject's teeth an oral care composition comprising a basic amino acid in free or salt form, wherein the basic amino acid is arginine (e.g., free form arginine); zinc oxide and zinc citrate; and an orally acceptable carrier.

Methods

Methods of treating gastric disorders

Disclosed herein are amino acid carbamate complexes, methods of synthesis thereof, oral care compositions comprising the same, and methods of making and using thereof.

Amino acid carbamate complexes

A system, apparatus, and/or method is disclosed for producing a personal care product. Values of chemoinformatic properties of ingredients of a sample chemical composition are received. A value of a property of the sample chemical composition is received in which the property is affected by an interaction of at least two of the ingredients. The values of the chemoinformatic properties of the ingredients of the sample chemical composition and the value of the property of the sample chemical composition are input into a model. An identity of the considered chemical composition is determined, via the model, based on at least one of (1) values of chemoinformatic properties of ingredients of the considered chemical composition or (2) a value of a property of the considered chemical composition. The personal care product comprised of the considered chemical composition is produced.

Systems and methods for evaluating compositions

A system, apparatus, and/or method is disclosed for producing a personal care product. An identity of a characteristic of interest and identities of sample chemical compositions are received. For each of the sample chemical compositions, a value of a property is received. For only each of the sample chemical compositions having the characteristic of interest, a value of a property of the sample chemical composition and one of (1) the identity of the sample chemical composition or (2) the values of the chemoinformatic properties of the ingredients of the sample chemical composition are input into a model. The value of the property of the considered chemical composition is determined, via the model, based on an identity of the considered chemical composition or values of chemoinformatic properties of the ingredients of the considered chemical composition. The personal care product having the considered chemical composition is produced.

The present disclosure is directed to a sensing agent. The sensing agent comprises a quantum dot; and a dye moiety coupled to the quantum dot. The sensing agent is capable of sensing at least one analyte chosen from hydrogen sulfide (HS) and bisulfide. Sensors made from the sensing agents are also disclosed.

Ratiometric quantum dot-rhodamine B sensing compound and device made from the compound

Growing community of inventors

Bridgewater, NJ, United States of America

Donghui Wu