Role of Zinc (Zn) in Human Reproduction: A Journey from Initial Spermatogenesis to Childbirth

Zinc (Zn), the second-most necessary trace element, is abundant in the human body. The human body lacks the capacity to store Zn; hence, the dietary intake of Zn is essential for various functions and metabolism. The uptake of Zn during its transport through the body is important for proper development of the three major accessory sex glands: the testis, epididymis, and prostate. It plays key roles in the initial stages of germ cell development and spermatogenesis, sperm cell development and maturation, ejaculation, liquefaction, the binding of spermatozoa and prostasomes, capacitation, and fertilization. The prostate releases more Zn into the seminal plasma during ejaculation, and it plays a significant role in sperm release and motility. During the maternal, labor, perinatal, and neonatal periods, the part of Zn is vital. The average dietary intake of Zn is in the range of 8–12 mg/day in developing countries during the maternal period. Globally, the dietary intake of Zn varies for pregnant and lactating mothers, but the average Zn intake is in the range of 9.6–11.2 mg/day. The absence of Zn and the consequences of this have been discussed using critical evidence. The events and functions of Zn related to successful fertilization have been summarized in detail. Briefly, our current review emphasizes the role of Zn at each stage of human reproduction, from the spermatogenesis process to childbirth. The role of Zn and its supplementation in in vitro fertilization (IVF) opens opportunities for future studies on reproductive biology.     

Nanosponge-based pediatric-controlled release dry suspension of Gabapentin for reconstitution

Abstract

Context: Gabapentin was selected to formulate oral controlled release dry suspension because of short biological half life of 5–7?h and low bioavailability (60%). Gabapentin is a bitter drug so an attempt was made to mask its taste.

Objective: To formulate and evaluate controlled release dry suspension for reconstitution to increase the bioavailability and to control bitter taste of drug.

Materials and methods: Cyclodextrin based nanosponges were synthesized by previously reported melt method. The nanosponge–drug complexes were characterized by FTIR, DSC and PXRD as well as evaluated for taste and saturation solubility. The complexes were coated on Espheres by a suspension layering technique followed by coating with ethyl cellulose and Eudragit RS-100. A dry powder suspension for reconstitution of the microspheres was formulated and evaluated for taste, redispersibility, in vitro dissolution, sedimentation volume, leaching and pharmacokinetics.

Results and discussion: The complexes showed partial entrapment of drug nanocavities. Significant decrease in solubility (25%) was observed in the complexes than pure drug in different media. The microspheres of nanosponge complexes showed desired controlled release profile for 12?h. Insignificant drug leaching was observed in reconstituted suspension during storage for 7 days at 45?°C/75% RH. Nanosponges effectively masked the taste of Gabapentin and the coating polymers provided controlled release of the drug and enhanced taste masking. The results of in vivo studies showed increase in bioavailability of controlled release suspension by 24.09% as compared to pure drug.

Conclusion: The dry powder suspension loaded with microspheres of nanosponges complexes can be proposed as a suitable controlled release drug delivery for Gabapentin.     

Subspace morphing theory for appearance based object identification

Object identification techniques have wide applications ranging from industry, business, military, law enforcement, to people's daily life. This research is motivated to develop a new theory for appearance based object identification with its applications in different areas. Although many successful techniques have been proposed in certain specific applications, object identification, in general, still remains as a difficult and challenging problem. In appearance based approaches, almost all the proposed methods are based on a fundamental assumption, i.e., all the images (both in the model base and to be queried) are in the same dimensions, so that the feature vectors are all in the same feature space; if images are provided with different dimensions, a normalization in scale to a pre-determined image space must be conducted. In this research, a theory for appearance based object identification called subspace morphing is developed, which allows scale-invariant identification of images of objects, and therefore, does not require normalization. Theoretical analysis and experimental evaluation show that in the situation where images are provided in different dimensions, which is common in many applications, subspace morphing theory is superior to the existing, normalization-based techniques in performance.     

Computational models for integrating linguistic and visual information: A survey

This paper surveys research in developing computational models for integrating linguistic and visual information. It begins with a discussion of systems which have been actually implemented and continues with computationally motivated theories of human cognition. Since existing research spans several disciplines (e.g., natural language understanding, computer vision, knowledge representation), as well as several application areas, an important contribution of this paper is to categorize existing research based on inputs and objectives. Finally, some key issues related to integrating information from two such diverse sources are outlined and related to existing research. Throughout, the key issue addressed is the correspondence problem, namely how to associate visual events with words and vice versa.     

An intelligent railway surveillance framework based on recognition of object and railway track using deep learning

Multimedia Tools and Applications - In high speed railways, the intelligent railway safety system is necessary to avoid the accidents due to collision between trains and obstacles on the railway...     

An Efficient Image Analysis Framework for the Classification of Glioma Brain Images Using CNN Approach

The identification of brain tumors is multifarious work for the separation of the similar intensity pixels from their surrounding neighbours. The detection of tumors is performed with the help of automatic computing technique as presented in the proposed work. The non-active cells in brain region are known to be benign and they will never cause the death of the patient. These non-active cells follow a uniform pattern in brain and have lower density than the surrounding pixels. The Magnetic Resonance (MR) image contrast is improved by the cost map construction technique. The deep learning algorithm for differentiating the normal brain MRI images from glioma cases is implemented in the proposed method. This technique permits to extract the linear features from the brain MR image and glioma tumors are detected based on these extracted features. Using k-mean clustering algorithm the tumor regions in glioma are classified. The proposed algorithm provides high sensitivity, specificity and tumor segmentation accuracy.     

Modulating contact angle hysteresis to direct fluid droplets along a homogenous surface

The shape and motion of drops on surfaces is governed by the balance between the driving and the pinning forces. Here we demonstrate control over the motion of droplets on an inclined surface by exerting control over the contact angle hysteresis. The external modulation of contact angle hysteresis is achieved through a voltage-induced local molecular reorganization within the surface film at the solid-liquid interface. We show that tuning contact angle hysteresis alone is sufficient to direct and deform drops when subjected to a constant external driving force, here gravity, in the absence of a pre-defined surface energy gradient or pattern. We also show that the observed stretching and contraction of the drops mimic the motion of an inchworm. Such reversible manipulation of the pinning forces could be an attractive means to direct drops, especially with the dominance of surface forces at micro-/nanoscale.     

Effect of pro‐oxidants on biodegradation of polyethylene (LDPE) by indigenous fungal isolate,Aspergillus oryzae

Proxidant additives represent a promising solution to the problem of the environment contamination with polyethylene film litter. Pro‐oxidants accelerate photo‐ and thermo‐oxidation and consequent polymer chain cleavage rendering the product apparently more susceptible to biodegradation. In the present study, fungal strain, Aspergillus oryzae isolated from HDPE film (buried in soil for 3 months) utilized abiotically treated polyethylene (LDPE) as a sole carbon source and degraded it. Treatment with pro‐oxidant, manganese stearate followed by UV irradiation and incubation with A. oryzae resulted in maximum decrease in percentage of elongation and tensile strength by 62 and 51%, respectively, compared with other pro‐oxidant treated LDPE films which showed 45% (titanium stearate), 40% (iron stearate), and 39% (cobalt stearate) decrease in tensile strength. Fourier transform infrared (FTIR) analysis of proxidant treated LDPE films revealed generation of more number of carbonyl and carboxylic groups (1630–1840 cm⁻¹ and 1220–1340 cm⁻¹) compared with UV treated film. When these films were incubated with A. oryzae for 3 months complete degradation of carbonyl and carboxylic groups was achieved. Scanning electron microscopy of untreated and treated LDPE films also revealed that polymer has undergone degradation after abiotic and biotic treatments. This concludes proxidant treatment before UV irradiation accelerated photo‐oxidation of LDPE, caused functional groups to be generated in the polyethylene film and this resulted in biodegradation due to the consumption of carbonyl and carboxylic groups by A. oryzae which was evident by reduction in carbonyl peaks. Among the pro‐oxidants, manganese stearate treatment caused maximum degradation of polyethylene. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2011