Development of detailed finite element models for in silico analyses of brain impact dynamics.

BACKGROUND AND OBJECTIVE: In the last few decades, several studies have been performed to investigate traumatic brain injuries (TBIs) and to understand the biomechanical response of brain tissues, by using experimental and computational approaches. As part of computational approaches, human head finite element (FE) models show to be important tools in the analysis of TBIs, making it possible to estimate local mechanical effects on brain tissue for different accident scenarios. The present study aims to contribute to the computational approach by means of the development of three advanced FE head models for accurately describing the head tissue dynamics, the first step to predict TBIs. METHODS: We have developed three detailed FE models of human heads from magnetic resonance images of three volunteers: an adult female (32 yrs), an adult male (35 yrs), and a young male (16 yrs). These models have been validated against experimental data of post mortem human subjects (PMHS) tests available in the literature. Brain tissue displacements relative to the skull, hydrostatic intracranial pressure, and head acceleration have been used as the parameters to compare the model response with the experimental response for validation. The software CORAplus (CORrelation and Analysis) has been adopted to evaluate the bio-fidelity level of FE models. RESULTS: Numerical results from the three models agree with experimental data. FE models presented in this study show a good bio-fidelity for hydrostatic pressure (CORA score of 0.776) and a fair bio-fidelity brain tissue displacements relative to the skull (CORA score of 0.443 and 0.535). The comparison among numerical simulations carried out with the three models shows negligible differences in the mechanical state of brain tissue due to the different morphometry of the heads, when the same acceleration history is considered. CONCLUSIONS: The three FE models, thanks to their accurate description of anatomical morphology and to their bio-fidelity, can be useful tools to investigate brain mechanics due to different impact scenarios. Therefore, they can be used for different purposes, such as the investigation of the correlation between head acceleration and tissue damage, or the effectiveness of helmet designs. This work does not address the issue to define injury thresholds for the proposed models.

RNAi Mediated curcin precursor gene silencing in Jatropha (Jatropha curcas L.).

Curcin, a type I ribosomal inhibiting protein-RIP, encoded by curcin precursor gene, is a phytotoxin present in Jatropha (Jatropha curcas L.). Here, we report designing of RNAi construct for the curcin precursor gene and further its genetic transformation of Jatropha to reduce its transcript expression. Curcin precursor gene was first cloned from Jatropha strain DARL-2 and part of the gene sequence was cloned in sense and antisense orientation separated by an intron sequence in plant expression binary vector pRI101 AN. The construction of the RNAi vector was confirmed by double digestion and nucleotide sequencing. The vector was then mobilized into Agrobacterium tumefaciens strain GV 3101 and used for tissue culture independent in planta transformation protocol optimized for Jatropha. Germinating seeds were injured with a needle before infection with Agrobacterium and then transferred to sterilized sand medium. The seedlings were grown for 90 days and genomic DNA was isolated from leaves for transgenic confirmation based on real time PCR with NPT II specific dual labeled probe. Result of the transgenic confirmation analysis revealed presence of the gene silencing construct in ten out of 30 tested seedlings. Further, quantitative transcript expression analysis of the curcin precursor gene revealed reduction in the transcript abundance by more than 98% to undetectable level. The transgenic plants are being grown in containment for further studies on reduction in curcin protein content in Jatropha seeds.