Identification and Development of Enzymes Associated With the Sperm Inner Acrosomal Membrane and Their Function during Fertilization

In order for mammalian fertilization to transpire, spermatozoa must transit through the female reproductive tract and penetrate the outer investments of the oocyte: the cumulus oophorus and the zona pellucida. In order to penetrate the oocyte, spermatozoa must undergo the acrosome reaction. The acrosome reaction results in the exposure of the inner acrosomal membrane (IAM) and proteins that coat it to the extracellular environment. After the acrosome reaction, the IAM becomes the leading edge of spermatozoa undergoing progressive movement. Thus the enzymes which effect lysis of the oocyte investments ought to be located on the IAM. An objective of this study was to identify and characterize enzymatic activity detected on the IAM and provide evidence that they play a role in fertilization. This study also describes procedures for fractionating spermatozoa and isolating the IAM and proteins on its intra- and extra-vesicular surfaces, and describes their development during male gametogenesis. Since the IAM is exposed to the extracellular environment and oviductal milieu after the acrosome reaction, this study also sought to characterize interactions and relationships between factors in the oviductal environment and the enzymes identified on the IAM. The data presented provide evidence that MMP2 and acrosin are co-localized on the IAM, originate from the Golgi apparatus in gametogenesis, and suggest they cooperate in their function. Their localization and results of in vitro fertilization suggests they have a function in zona pellucida penetration. The data also provide evidence that plasminogen, originating from the oviductal epithelium and/or cumulus-oocyte complex, is present in the immediate environment of sperm-egg initial contact and penetration. Additionally, plasminogen interacts with MMP2 and enhances its enzymatic action on the IAM. The data also provide evidence that MMP2 has an important function in penetration of the cumulus oophorus. Holistically, this thesis provides evidence that enzymes on the IAM, originating from the Golgi apparatus in development, have an important function in penetration of the outer investments of the oocyte, and are aided in penetration by plasminogen in the female reproductive tract.

Linear Hyperspectral Unmixing Using L0-norm Approximations and Nonnegative Matrix Factorization

Spectral unmixing (SU) is a technique to characterize mixed pixels of the hyperspectral images measured by remote sensors. Most of the existing spectral unmixing algorithms are developed using the linear mixing models. Since the number of endmembers/materials present at each mixed pixel is normally scanty compared with the number of total endmembers (the dimension of spectral library), the problem becomes sparse. This thesis introduces sparse hyperspectral unmixing methods for the linear mixing model through two different scenarios. In the first scenario, the library of spectral signatures is assumed to be known and the main problem is to find the minimum number of endmembers under a reasonable small approximation error. Mathematically, the corresponding problem is called the $\ell_0$-norm problem which is NP-hard problem. Our main study for the first part of thesis is to find more accurate and reliable approximations of $\ell_0$-norm term and propose sparse unmixing methods via such approximations. The resulting methods are shown considerable improvements to reconstruct the fractional abundances of endmembers in comparison with state-of-the-art methods such as having lower reconstruction errors. In the second part of the thesis, the first scenario (i.e., dictionary-aided semiblind unmixing scheme) will be generalized as the blind unmixing scenario that the library of spectral signatures is also estimated. We apply the nonnegative matrix factorization (NMF) method for proposing new unmixing methods due to its noticeable supports such as considering the nonnegativity constraints of two decomposed matrices. Furthermore, we introduce new cost functions through some statistical and physical features of spectral signatures of materials (SSoM) and hyperspectral pixels such as the collaborative property of hyperspectral pixels and the mathematical representation of the concentrated energy of SSoM for the first few subbands. Finally, we introduce sparse unmixing methods for the blind scenario and evaluate the efficiency of the proposed methods via simulations over synthetic and real hyperspectral data sets. The results illustrate considerable enhancements to estimate the spectral library of materials and their fractional abundances such as smaller values of spectral angle distance (SAD) and abundance angle distance (AAD) as well.