Product Images Psyllium Husk Fiber Supplement

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Product Label Images

The following 2 images provide visual information about the product associated with Psyllium Husk Fiber Supplement NDC 49483-145 by Time Cap Labs 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.

psyllium-husk-capsules-200-label - psyllium husk capsules 200 label

psyllium-husk-capsules-200-label - psyllium husk capsules 200 label

This is a dietary fiber supplement containing psyllium husk, which supports digestive health, heart health, and healthy blood sugar levels. It provides 2g of soluble fiber per serving and is recommended to be taken up to 4 times daily before meals. The supplement is low in calories and carbohydrates and may help in lowering cholesterol. It is advised to consult a doctor if constipation lasts more than 7 days or if there is rectal bleeding. Bulk-forming fibers like psyllium husk may affect medication absorption. Keep the product in a cool, dry place and avoid use if the inner seal is broken.*

psyllium-husk-capsules-400-label - psyllium husk capsules 400 label

psyllium-husk-capsules-400-label - psyllium husk capsules 400 label

This text provides the supplement facts for adults 12 years and older for a product that contains Psyllium Fiber to support digestive health, heart health, and healthy blood sugar levels. It compares to Metamucil Capsules and includes information on serving sizes, dietary information, and instructions for use. The product is gluten-free and consists of 400 capsules. It is important to gradually increase the daily intake, and users may experience changes in bowel habits as their body adjusts to the increased fiber intake. Additionally, the text warns to take the product with enough liquid to prevent choking and advises against use for individuals with swallowing difficulties.*

* 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.