A new strain-sensing structure inspired from insect's (especially the Fly) propricoception sensor is devised. The campaniform sensillum is a strain-sensing microstructure with very high sensitivity despite its small dimension (diameter ~10 m in a relatively stiff material of insect's exocuticle (E = ~10 9 Pa). Previous work shows that the high sensitivity of this structure towards strain is due to its membrane-in-recess-and strainconcentrating-hole-features. Based on this inspiration, we built similar structure using silicon micromachining technology. Then a simple characterisation setup was devised. Here, we present briefly, finite-element modeling and simulation based on this actual sample preparation for the characterisation. As comparison and also to understand mechanical features responsible for the strain-sensitivity, we performed the modeling on different mechanical structures: bulk chunk, blind-hole, thorugh-hole, surface membrane, and membrane-in-recess. The actual experimental characterisation was performed previously using optical technique to membranein-recess micromachined Si structure. The FEM simulation results confirm that the bending stress and strain are concentrated in the hole-vicinity. The membrane inside the hole acts as displacement transducer. The FEM is in conformity with previous analytical results, as well as the optical characterisation result. The end goal is to build a new type MEMS strain sensor.

Osteosarcoma (OS) is the most common primary bone malignancy, but current therapies are far from effective for all patients. A better understanding of the pathological mechanism of OS may help to achieve new treatments for this tumor. Hence, the objective of this study was to investigate ego modules and pathways in OS utilizing EgoNet algorithm and pathway-related analysis, and reveal pathological mechanisms underlying OS. The EgoNet algorithm comprises four steps: constructing background protein-protein interaction (PPI) network (PPIN) based on gene expression data and PPI data; extracting differential expression network (DEN) from the background PPIN; identifying ego genes according to topological features of genes in reweighted DEN; and collecting ego modules using module search by ego gene expansion. Consequently, we obtained 5 ego modules (Modules 2, 3, 4, 5, and 6) in total. After applying the permutation test, all presented statistical significance between OS and normal controls. Finally, pathway enrichment analysis combined with Reactome pathway database was performed to investigate pathways, and Fisher's exact test was conducted to capture ego pathways for OS. The ego pathway for Module 2 was CLEC7A/inflammasome pathway, while for Module 3 a tetrasaccharide linker sequence was required for glycosaminoglycan (GAG) synthesis, and for Module 6 was the Rho GTPase cycle. Interestingly, genes in Modules 4 and 5 were enriched in the same pathway, the 2-LTR circle formation. In conclusion, the ego modules and pathways might be potential biomarkers for OS therapeutic index, and give great insight of the molecular mechanism underlying this tumor.