journal article·2026-05Open access

Freeze-dried larnite-reinforced PVA/PCL/silk fibroin composite scaffolds: Biocompatibility and mechanical assessment for hard tissue repair

Harish parthiban, Yuvaraj Elumalai, Shobana Kothandam, Sherlin Joseph, Dhaya Rani Varkey, Jayanthi Abraham, Sasikumar Swamiappan

Abstract

Bone tissue engineering (BTE) offers an effective strategy for restoring bone defects through biomimetic scaffolds that promote osteogenic differentiation and tissue regeneration. Among silicate-based biomaterials, larnite (Ca 2 SiO 4 ) has emerged as a promising candidate owing to its superior bioactivity, and ability to support apatite formation. However, its intrinsic brittleness limits its application in load-bearing conditions. To overcome this limitation, a larnite-polymer composite scaffolds was fabricated by incorporating biodegradable polymers such as polyvinyl alcohol (PVA), polycaprolactone (PCL), and silk fibroin (SF) to improve flexibility, and mechanical integrity. Porous scaffolds (Lap-1, Lap-2, and Lap-3) were prepared via the freeze-drying technique, achieving a balance between porosity and mechanical strength. Among the three prepared scaffolds Lap-2 exhibited the most favourable characteristics, with a heterogeneous pore structure. After 9 days of immersion, the formation of a hydroxyapatite (HAp) layer confirmed its excellent bioactivity. Moreover, Lap-2 exhibited a compressive strength of 14.13 MPa, a Young’s modulus of 38.26 MPa, 59% antibacterial inhibition, and remarkable hemocompatibility with only 1.3% hemolysis, indicating its safety for biomedical use. The enhanced bioactivity and antibacterial efficiency, combined with improved mechanical integrity of the Lap-2 composite scaffold, highlight its strong potential for bone tissue engineering applications.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Silk-based biomaterials and applications · Bone Tissue Engineering Materials · Hemostasis and retained surgical items

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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