Publications by authors named "R Roopashree"

Neutrophils are granular and polymorphonuclear cells and one of the main participants of the innate immune system, which have received considerable attention due to the discovery of neutrophil extracellular traps (NETs). Extracellular vesicles (EVs), particularly those released by immune cells such as neutrophils, have been associated with the immunopathogenesis of autoimmune diseases. Besides, studies have reported a fundamental correlation between EVs and NETosis in autoimmune diseases.

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Autoimmune diseases occur when the immune system mistakenly attacks the body's own tissues, affecting millions of people and often requiring long-term treatment. Current therapies, such as immunosuppressants and biologics, help manage symptoms but can cause serious side effects. A promising new approach involves engineered microbiota-a method that modifies gut bacteria to influence immune function and potentially ease autoimmune conditions.

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This study successfully encapsulated palladium nanoparticles within the metal-organic framework material UiO-66 using a straightforward method. Utilizing a microwave-assisted process, the pores of UiO-66 were activated, and the metal precursors were simultaneously reduced in the presence of a reducing agent. The morphological and physicochemical properties of the resulting material were thoroughly analyzed using various techniques, including EDX, SEM, XRD, TGA, BET, and ICP-OES.

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Angiogenesis is critical for effective wound healing, supplying oxygen and nutrients to regenerating tissues. In chronic conditions like diabetes, impaired angiogenesis leads to delayed healing, chronic wounds, and significant healthcare burdens. Exosomes, nano-sized extracellular vesicles derived from cells such as mesenchymal stem cells (MSCs), amniotic epithelial cells, and keratinocytes, have emerged as key mediators in promoting angiogenesis.

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Objective: This study aimed to create a reliable method for preoperative grading of meningiomas by combining radiomic features and deep learning-based features extracted using a 3D autoencoder. The goal was to utilize the strengths of both handcrafted radiomic features and deep learning features to improve accuracy and reproducibility across different MRI protocols.

Materials And Methods: The study included 3,523 patients with histologically confirmed meningiomas, consisting of 1,900 low-grade (Grade I) and 1,623 high-grade (Grades II and III) cases.

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