Parkinson's disease (PD), a neurodegenerative disorder characterized by distinct aging-independent loss of dopaminergic neurons in substantia nigra pars compacta (SNpc) region urging toward neuronal loss. Over the decade, various key findings from clinical perspective to molecular pathogenesis have aided in understanding the genetics with assorted genes related with PD. Subsequently, several pathways have been incriminated in the pathogenesis of PD, involving mitochondrial dysfunction, protein aggregation, and misfolding. On the other hand, the sporadic form of PD cases is found with no genetic linkage, which still remain an unanswered question? The exertion in ascertaining vulnerability factors in PD considering the genetic factors are to be further dissevered in the forthcoming decades with advancement in research studies. One of the major proponents behind the prognosis of PD is the pathogenic transmutation of aberrant alpha-synuclein protein into amyloid fibrillar structures, which actuates neurodegeneration. Alpha-synuclein, transcribed by SNCA gene is a neuroprotein found predominantly in brain. It is implicated in the modulation of synaptic vesicle transport and eventual release of neurotransmitters. Due to genetic mutations and other elusive factors, the alpha-synuclein misfolds into its amyloid form. Therefore, this review aims in briefing the molecular understanding of the alpha-synuclein associated with PD.

Sperm of humans, non-human primates, and other mammalian subjects is considered to be antigenic. The effect of changes in autoimmunity on reproductive cells such as spermatozoa and oocytes play a critical but indistinct role in fertility. Antisperm antibodies (ASAs) are invariably present in both females and males. However, the degree of ASA occurrence may vary according to individual and gender. Although the extent of infertility due to ASAs alone is yet to be determined, it has been found in almost 9–12% of patients who are infertile due to different causes. Postcoital presence of spermatozoa in the reproductive tract of women is not a contributory factor in ASA generation. However, ASA generation may be induced by trauma to the vaginal mucosa, or by anal or oral sex resulting in the deposition of sperm inside the digestive tract. It is strongly believed that, in humans and other species, at least some antibodies may bind to sperm antigens, causing infertility. This form of infertility is termed as immunological infertility, which may be accompanied by impairment of fertility, even in individuals with normozoospermia. Researchers target ASAs for two major reasons: (i) to elucidate the association between ASAs and infertility, the reason ASAs causes infertility, and the mechanism underlying ASA-mediated infertility; and (ii) to assess the potential of ASAs as a contraceptive in humans in case ASAs influences infertility. Therefore, this review explores the potential application of ASAs in the development of anti-spermatozoa vaccines for contraceptive purposes. The usefulness of ASAs for diagnosing obstructive azoospermia, salpingitis, and oligoasthenoteratozoospermia has been reviewed extensively. Important patents pertaining to potential candidates for spermatozoa-derived vaccines that may be utilized as contraceptives are discussed in depth. Antifertility vaccines, as well as treatments for ASA-related infertility, are also highlighted. This review will address many unresolved issues regarding mechanisms involving ASAs in the diagnosis, as well as prognoses, of male infertility. More documented scientific reports are cited to support the mechanisms underlying the potential role of ASA in infertility. The usefulness of sperm antigens or ASAs (recombinant) in human and wild or captive animal contraceptive vaccines has been revealed through research but is yet to be validated via clinical testing.

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An extracellular β-glucosidase was isolated from Proteus mirabilis VIT117 found to be growing on prawn shells. The enzyme production was found to be enhanced (14.58 U/ml) when the culture was maintained at pH 9 and provided with sorbitol as carbon source, yeast extract as nitrogen source and incubated at 37 °C for approximately 72 h. Statistical methods like Plackett–Burman and RSM were also applied here to study the effects of different combinations of growth parameters for the bacteria, where the most significant parameters were found to be inoculum size, pH, yeast extract, incubation time and sorbitol. The optimum concentrations of inoculum size, pH and yeast extract determined by RSM were 2 %, 9 and 2 %, respectively. Partial purification of the protein was done by ammonium sulfate precipitation, followed by dialysis, gel filtration chromatography and SDS-PAGE. The enzyme was found to have a molecular weight of approximately 50 kDa and was observed to be most active at 37 °C in pH 9, with a sharp decline in the enzyme activity when temperature or the pH was increased. Enzyme kinetics study was performed to understand the catalytic behavior of the enzyme and it was found that our β-glucosidase had 5.613 U/ml and 0.082 mM as V max and K m values, respectively.Electronic supplementary materialThe online version of this article (doi:10.1007/s13205-016-0530-7) contains supplementary material, which is available to authorized users.

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Seminal fluid is the secretion from many glands comprised of several organic and inorganic compounds including free amino acids, proteins, fructose, glucosidase, zinc, and other scavenging elements like Mg 2+ , Ca 2+ , K + , and Na + . Therefore, in the view of development of novel approaches and proper diagnosis to male infertility, overall understanding of the biochemical and molecular composition and its role in regulation of sperm quality is highly desirable. Perhaps this can be achieved through artificial intelligence. This study was aimed to elucidate and predict various biochemical markers present in human seminal plasma with three different neural network models. A total of 177 semen samples were collected for this research (both fertile and infertile samples) and immediately processed to prepare a semen analysis report, based on the protocol of the World Health Organization (WHO [2010]). The semen samples were then categorized into oligoasthenospermia (n=35), asthenospermia (n=35), azoospermia (n=22), normospermia (n=34), oligospermia (n=34), and control (n=17). The major biochemical parameters like total protein content, fructose, glucosidase, and zinc content were elucidated by standard protocols. All the biochemical markers were predicted by using three different artificial neural network (ANN) models with semen parameters as inputs. Of the three models, the back propagation neural network model (BPNN) yielded the best results with mean absolute error 0.025, -0.080, 0.166, and -0.057 for protein, fructose, glucosidase, and zinc, respectively. This suggests that BPNN can be used to predict biochemical parameters for the proper diagnosis of male infertility in assisted reproductive technology (ART) centres.

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