Product Images Alcohol Wipes

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Product Label Images

The following 2 images provide visual information about the product associated with Alcohol Wipes NDC 75163-080 by Zhuji Jianhe Paper Co., Ltd, 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.

80 cloth label - 80 cloth

80 cloth label - 80 cloth

These are sanitizing wipes by Carity USA LLC that are made in China and meant for single use. They contain 75% ethanol alcohol, and their purpose is to clean hands and remove allergens. They comply with GB 15979 and GB/T27728 standards and have a hygiene product license. These are meant for external use only, and caution should be taken to avoid contact with the eyes and to keep away from flames. If redness or irritation develops, use should be stopped, and a healthcare practitioner should be consulted if the condition persists. They should be kept out of reach of children and should not be swallowed. These wipes contain water as an inactive ingredient and have a shelf life of 24 months.*

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acf855f3 ee9f 6446 e053 2a95a90aae3d

This product is a single use wipe that contains 75% ethanol alcohol and is meant for general cleansing purposes. It is distributed by Carity USA LLC and complies with GB 15979 and GB/T27728. It is made in China and has a hygiene product license (CN-ZJ (2020) No. 0082). The wipes come with directions and a shelf life of 24 months. The formula is skin-friendly, non-drip and tear-resistant, and kills 99.9% of germs. The inactive ingredient is water. The product comes with warnings to keep it away from fire or flame and out of the reach of children. If swallowed, medical help or contact with a poison control center should be sought immediately. If irritation or redness occurs, users should stop using the product and consult with a healthcare practitioner if the condition continues.*

* 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.