Product Images Act Whitening Anticavity Gentle Mint

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Product Label Images

The following 2 images provide visual information about the product associated with Act Whitening Anticavity Gentle Mint NDC 41167-0983 by Chattem, Inc., such as packaging, labeling, and the appearance of the drug itself. This resource could be helpful for medical professionals, pharmacists, and patients seeking to verify medication information and ensure they have the correct product.

PRINCIPAL DISPLAY PANELACTWHITENINGANTICAVITY FLUORIDE MOUTHWASHGENTLE MINT16.9 fl oz (500 mL) - act whitening anticavity fluoride mouthwash gentle 01

PRINCIPAL DISPLAY PANELACTWHITENINGANTICAVITY FLUORIDE MOUTHWASHGENTLE MINT16.9 fl oz (500 mL) - act whitening anticavity fluoride mouthwash gentle 01

ZERQ ALCOHOL #1 DENTIST RECOMMENDED FLUORIDE BRAND Whitening Anticavity Fluoride Mouthwash promotes oral health, strengthens, and protects teeth. It kills bad breath germs and comes in Gentle Mint flavor with 0.02% Sodium Fluoride. The pack contains 500 mL of mouthwash. The directions for proper use should be read before use to ensure optimum performance. It also promises a whiter smile in just four days.*

PRINCIPAL DISPLAY PANELACTWHITENINGANTICAVITY FLUORIDE MOUTHWASHGENTLE MINT16.9 fl oz (500 mL) - act whitening anticavity fluoride mouthwash gentle 02

PRINCIPAL DISPLAY PANELACTWHITENINGANTICAVITY FLUORIDE MOUTHWASHGENTLE MINT16.9 fl oz (500 mL) - act whitening anticavity fluoride mouthwash gentle 02

This is a description of an alcohol-free mouthwash with fluoride that helps prevent dental cavities. The active ingredient is Sodium fluoride 0.02%, and inactive ingredients include water, glycerin, and flavors. The mouthwash is meant for adults and children over 12 years old and should be rinsed for 1 minute before spitting out without swallowing. In case of oral irritation or tooth sensitivity, users should stop using and consult a dentist. If swallowed, users should contact Poison Control Center immediately.*

* The product label images have been analyzed using a combination of traditional computing and machine learning techniques. It should be noted that the descriptions provided may not be entirely accurate as they are experimental in nature. Use the information in this page at your own discretion and risk.