Internet of Things as Intimating for Pregnant Women’s Healthcare: An Impending Privacy Issues

Ingeniously, the innovations are taking place in current medical era, where IoT is a key and its related technology plays a dynamic role in pregnant women care taking inside hospital and outside. IoT ensure the effective and efficient care of pregnant women in any environment because intelligent tiny devices like RF-Tags, sensors are attached with pregnant women, and all the activities of pregnant women can be monitored by professional medical staff from anywhere and anytime. The usage of these advanced technologies in pregnant women care environment, absolutely eradicates the pregnancy complications and harmful incidents, but also raises privacy, religious, ethical, legal and social issues. The purpose of this paper is to discuss the usage of IoT in pregnant women healthcare environments and articulates endorsements to promote research then can guarantee that the pregnant women’s privacy is preserved. DOI : http://dx.doi.org/10.11591/telkomnika.v12i6.422

MicroRNAs: New insight in modulating follicular atresia: A review

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Molecular Genomic Study of Inhibin Molecule Production through Granulosa Cell Gene Expression in Inhibin-Deficient Mice

Inhibin is a molecule that belongs to peptide hormones and is excreted through pituitary gonadotropins stimulation action on the granulosa cells of the ovaries. However, the differential regulation of inhibin and follicle-stimulating hormone (FSH) on granulosa cell tumor growth in mice inhibin-deficient females is not yet well understood. The objective of this study was to evaluate the role of inhibin and FSH on the granulosa cells of ovarian follicles at the premature antral stage. This study stimulated immature wild-type (WT) and Inhibin-α knockout (Inha−/−) female mice with human chorionic gonadotropin (hCG) and examined hCG-induced gene expression changes in granulosa cells. Also, screening of differentially expressed genes (DEGs) was performed in the two groups under study. In addition, related modules to external traits and key gene drivers were determined through Weighted Gene Co-Expression Network Analysis (WGCNA) algorithm. The results identified a number of 1074 and 931 DEGs and 343 overlapping DEGs (ODEGs) were shared in the two groups. Some 341 ODEGs had high relevance and consistent expression direction, with a significant correlation coefficient (r2 = 0.9145). Additionally, the gene co-expression network of selected 153 genes showed 122 nodes enriched to 21 GO biological processes (BP) and reproduction and 3 genes related to genomic pathways. By using principal component analysis (PCA), the 14 genes in the regulatory network were fixed and the cumulative proportion of fitted top three principal components was 94.64%. In conclusion, this study revealed the novelty of using ODEGs for investigating the inhibin and FSH hormone pathways that might open the way toward gene therapy for granulosa cell tumors. Also, these genes could be used as biomarkers for tracking the changes in inhibin and FSH hormone from the changes in the nutrition pattern

Long Non-Coding RNAs:the New Horizon of Gene Regulation in Ovarian Cancer

Long non-coding RNAs (lncRNAs), a class of non-coding transcripts, have recently been emerging with heterogeneous molecular actions, adding a new layer of complexity to gene-regulation networks in tumorigenesis. LncRNAs are considered important factors in several ovarian cancer histotypes, although few have been identified and characterized. Owing to their complexity and the lack of adapted molecular technology, the roles of most lncRNAs remain mysterious. Some lncRNAs have been reported to play functional roles in ovarian cancer and can be used as classifiers for personalized medicine. The intrinsic features of lncRNAs govern their various molecular mechanisms and provide a wide range of platforms to design different therapeutic strategies for treating cancer at a particular stage. Although we are only beginning to understand the functions of lncRNAs and their interactions with microRNAs (miRNAs) and proteins, the expanding literature indicates that lncRNA-miRNA interactions could be useful biomarkers and therapeutic targets for ovarian cancer. In this review, we discuss the genetic variants of lncRNAs, heterogeneous mechanisms of actions of lncRNAs in ovarian cancer tumorigenesis, and drug resistance. We also highlight the recent developments in using lncRNAs as potential prognostic and diagnostic biomarkers. Lastly, we discuss potential approaches for linking lncRNAs to future gene therapies, and highlight future directions in the field of ovarian cancer research

MicroRNAs: New Insight in Modulating Follicular Atresia: A Review

Our understanding of the post-transcriptional mechanisms involved in follicular atresia is limited; however, an important development has been made in understanding the biological regulatory networks responsible for mediating follicular atresia. MicroRNAs have come to be seen as a key regulatory actor in determining cell fate in a wide range of tissues in normal and pathological processes. Profiling studies of miRNAs during follicular atresia and development have identified several putative miRNAs enriched in apoptosis signaling pathways. Subsequent in vitro and/or in vivo studies of granulosa cells have elucidated the functional role of some miRNAs along with their molecular pathways. In particular, the regulatory roles of some miRNAs have been consistently observed during studies of follicular cellular apoptosis. Continued work should gradually lead to better understanding of the role of miRNAs in this field. Ultimately, we expect this understanding will have substantial benefits for fertility management at both the in vivo or/and in vitro levels. The stable nature of miRNA holds remarkable promise in clinical use as a diagnostic tool and in reproductive medicine to solve the ever-increasing fertility problem. In this review, we summarize current knowledge of the involvement of miRNAs in follicular atresia, discuss the challenges for further work and pinpoint areas for future research

Toxicity of Nanoparticles on the Reproductive System in Animal Models: A Review

In the last two decades, nanotechnologies demonstrated various applications in different fields, including detection, sensing, catalysis, electronics, and biomedical sciences. However, public concerns regarding the well-being of human may hinder the wide utilization of this promising innovation. Although, humans are exposed to airborne nanosized particles from an early age, exposure to such particles has risen dramatically within the last century due to anthropogenic sources of nanoparticles. The wide application of nanomaterials in industry, consumer products, and medicine has raised concerns regarding the potential toxicity of nanoparticles in humans. In this review, the effects of nanomaterials on the reproductive system in animal models are discussed. Females are particularly more vulnerable to nanoparticle toxicity, and toxicity in this population may affect reproductivity and fetal development. Moreover, various types of nanoparticles have negative impacts on male germ cells, fetal development, and the female reproductive system. These impacts are associated with nanoparticle modification, composition, concentration, route of administration, and the species of the animal. Therefore, understanding the impacts of nanoparticles on animal growth and reproduction is essential. Many studies have examined the effects of nanoparticles on primary and secondary target organs, with a concentration on the in vivo and in vitro effects of nanoparticles on the male and female reproductive systems at the clinical, cellular, and molecular levels. This review provides important information regarding organism safety and the potential hazards of nanoparticle use and supports the application of nanotechnologies by minimizing the adverse effects of nanoparticles in vulnerable populations

Consequence of birth year, type, sex, season and flock on birth weight trait of Kajli sheep

The liaison of birth weight to neonatal and mature vigor is especially given important if have the acquaintance of factors distressing in birth weight. Unbiased Best linear prediction of breeding values was estimated from pedigree birth weight records of 13715 Kajli sheep of livestock Experiment Station Khizerabad born 1994 to 2010, and Livestock Experimental Station, Khushab. Data records were statistically analyzed by means of using computer programmed Mixed Model Harvey’s Least Squares and Maximum Likelihood. An animal model was used for heritability estimation following Maximum Likelihood procedure. Estimates of birth weight heritability in Kajli sheep were 0.05 ± 0.019. The estimated breeding values of both forms for males, females, and sire were calculated with significant variation. Both farms data were analyzed by using an animal model program. The squares mean slightest for weight at birth (kg), remained 4.13 ± 0.01 kg. In addition, birth of the year, the birth of type, flock and sex significantly affects the (p < 0.001) trait of birth weight. The domino effect of the current study has rational implications not only for sheep husbandry nevertheless as well as for amplified acquaintance of parameters which drastically persuade deviation of weight in birth as weight in birth has become itself noteworthy forecaster of anon fitness outcomes. These results showed the decreasing genetic and static phenotypic at birth weight. It is likely that there are complex interactions between genetics and environmental factors of parental, placental and fetal origin. Birth weight is highly influenced trait by maternal nutrition, genes, care, management, climate, seasonal variation and type of birth

Transcriptomic in silico analysis of bovine Escherichia coli mastitis highlights its immune-related expressed genes as an effective biomarker

Abstract Background Mastitis is one of the major diseases causing economic loss to the dairy industry by reducing the quantity and quality of milk. Thus, the objective of this scientific study was to find new biomarkers based on genes for the early prediction before its severity. Methods In the present study, advanced bioinformatics including hierarchical clustering, enrichment analysis, active site prediction, epigenetic analysis, functional domain identification, and protein docking were used to analyze the important genes that could be utilized as biomarkers and therapeutic targets for mastitis. Results Four differentially expressed genes (DEGs) were identified in different regions of the mammary gland (teat cistern, gland cistern, lobuloalveolar, and Furstenberg’s rosette) that resulted in 453, 597, 577, and 636 DEG, respectively. Also, 101 overlapped genes were found by comparing 27 different expressed genes. These genes were associated with eight immune response pathways including NOD-like receptor signaling pathway (IL8, IL18, IL1B, PYDC1) and chemokine signaling pathway (PTK2, IL8, NCF1, CCR1, HCK). Meanwhile, 241 protein-protein interaction networks were developed among overlapped genes. Fifty-seven regulatory events were found between miRNAs, expressed genes, and the transcription factors (TFs) through micro-RNA and transcription factors (miRNA-DEG-TF) regulatory network. The 3D structure docking model of the expressed genes proteins identified their active sites and the binding ligands that could help in choosing the appropriate feed or treatment for affected animals. Conclusions The novelty of the distinguished DEG and their pathways in this study is that they can precisely improve the detection biomarkers and treatments techniques of cows’ Escherichia coli mastitis disease due to their high affinity with the target site of the mammary gland before appearing the symptoms. Graphical abstrac