Dendritic Cells and the Establishment of Fetomaternal Tolerance for Successful Human Pregnancy.

Pregnancy is a remarkable event where the semi-allogeneic fetus develops in the mother's uterus, despite genetic and immunological differences. The antigen handling and processing at the maternal-fetal interface during pregnancy appear to be crucial for the adaptation of the maternal immune system and for tolerance to the developing fetus and placenta. Maternal antigen-presenting cells (APCs), such as macrophages (Mφs) and dendritic cells (DCs), are present at the maternal-fetal interface throughout pregnancy and are believed to play a crucial role in this process. Despite numerous studies focusing on the significance of Mφs, there is limited knowledge regarding the contribution of DCs in fetomaternal tolerance during pregnancy, making it a relatively new and growing field of research. This review focuses on how the behavior of DCs at the maternal-fetal interface adapts to pregnancy's unique demands. Moreover, it discusses how DCs interact with other cells in the decidual leukocyte network to regulate uterine and placental homeostasis and the local maternal immune responses to the fetus. The review particularly examines the different cell lineages of DCs with specific surface markers, which have not been critically reviewed in previous publications. Additionally, it emphasizes the impact that even minor disruptions in DC functions can have on pregnancy-related complications and proposes further research into the potential therapeutic benefits of targeting DCs to manage these complications.

Proteomic Profiling and Pathway Analysis of Acid Stress-Induced Vasorelaxation of Mesenteric Arteries In Vitro.

Although metabolic acidosis is associated with numerous pathophysiological conditions and its vasorelaxation effects have been well described in different animal and culture models, the molecular mechanisms of acidosis-induced vasorelaxation are not fully understood. Mesenteric artery models have been used extensively to examine the vascular response to various pathophysiological conditions. Our previous studies and several other reports have suggested the vascular responses of goat mesenteric arteries and human arteries to various stimuli, including acidic stress, are highly similar. In this study, to further identify the signaling molecules responsible for altered vasoreactivity in response to acidic pH, we examined the proteomic profile of acid stress-induced vasorelaxation using a goat mesenteric artery model. The vascular proteomes under acidic pH were compared using 2D-GE with 7 cm IPG strips and mini gels, LC-MS/MS, and MALDI TOF MS. The unique proteins identified by mass spectroscopy were actin, transgelin, WD repeat-containing protein 1, desmin, tropomyosin, ATP synthase ß, Hsp27, aldehyde dehydrogenase, pyruvate kinase, and vitamin K epoxide reductase complex subunit 1-like protein. Out of five protein spots identified as actin, three were upregulated > 2-fold. ATP synthase ß was also upregulated (2.14-fold) under acid stress. Other actin-associated proteins upregulated were transgelin, desmin, and WD repeat-containing protein 1. Isometric contraction studies revealed that both receptor-mediated (histamine) and non-receptor-mediated (KCl) vasocontraction were attenuated, whereas acetylcholine-induced vasorelaxation was augmented under acidosis. Overall, the altered vasoreactivity under acidosis observed in the functional studies could possibly be attributed to the increase in expression of actin and ATP synthase ß.

Preserving the Privacy of Healthcare Data over Social Networks Using Machine Learning.

A key challenge in clinical recommendation systems is the problem of aberrant patient profiles in social networks. As a result of a person's abnormal profile, numerous vests might be used to make fake remarks about them, cyber bullying, or cyber-attacks. Many clinical researchers have done extensive study on this topic. The most recent studies on this topic are summarized, and an overarching framework is provided. When it comes to the methods and datasets that make up the data collection, the feature presentation and algorithm selection layers provide an overview of the various types of algorithm selections available. The categorization and evaluation of diseases and disorders has been one of the major advantages of machine learning in medical. Because it was harder to predict, it rendered it more controllable. It might range from difficult-to-find cancers in the early stages to certain other illnesses spread through the bloodstream. In healthcare, we may pick methods in machine learning depending on reliable outcomes. To do so, we must run the findings through each method. The major issue arises during information training and validation. Because the dataset is so large, eliminating mistakes might be difficult. The providers, other characteristics, various algorithms, data labelling techniques, and assessment criteria are all presented and contrasted in depth. Detecting anomalous users in medical social networks, on the other hand, is a work in progress. The result evaluation layer provides an explanation of how to evaluate and mark up the results of the various algorithm selection layers. Finally, it looks forward to more study in this area.

Glutamate Uptake Is Not Impaired by Hypoxia in a Culture Model of Human Fetal Neural Stem Cell-Derived Astrocytes.

Hypoxic ischemic injury to the fetal and neonatal brain is a leading cause of death and disability worldwide. Although animal and culture studies suggest that glutamate excitotoxicity is a primary contributor to neuronal death following hypoxia, the molecular mechanisms, and roles of various neural cells in the development of glutamate excitotoxicity in humans, is not fully understood. In this study, we developed a culture model of human fetal neural stem cell (FNSC)-derived astrocytes and examined their glutamate uptake in response to hypoxia. We isolated, established, and characterized cultures of FNSCs from aborted fetal brains and differentiated them into astrocytes, characterized by increased expression of the astrocyte markers glial fibrillary acidic protein (GFAP), excitatory amino acid transporter 1 (EAAT1) and EAAT2, and decreased expression of neural stem cell marker Nestin. Differentiated astrocytes were exposed to various oxygen concentrations mimicking normoxia (20% and 6%), moderate and severe hypoxia (2% and 0.2%, respectively). Interestingly, no change was observed in the expression of the glutamate transporter EAAT2 or glutamate uptake by astrocytes, even after exposure to severe hypoxia for 48 h. These results together suggest that human FNSC-derived astrocytes can maintain glutamate uptake after hypoxic injury and thus provide evidence for the possible neuroprotective role of astrocytes in hypoxic conditions.

Feature extraction with capsule network for the COVID-19 disease prediction though X-ray images.

Past couple of years, the world is going through one of the biggest pandemic named COVID-19. In the mid of year 2019, it is a very difficult process to predict the COVID-19 just by viewing the images. Later on AI based technology has done a significant role in the prediction of COVID-19 through biomedical images such as CT scan, X ray etc. This study also implemented the deep learning model for the prediction of COVID-19 through X-ray images. The implemented model is termed as XR-CAPS which consist of two models such as U-Net model and the capsule network. The U Net model is used for performing the segmentation of the images and the capsule networks are applied for performing the feature extraction. The XR-CAPS model is applied on the X-ray images for the prediction of COVID-19 and the evaluation of the model is done by three parameters that are accuracy, sensitivity and specificity. The model is compared with other existing models like ResNet50, DenseNet121 and DenseCapsNet, this has achieved an accuracy of 93.2%, sensitivity of 94% and specificity of 97.1% which is better than other states of the art algorithms.

Pathogenesis of Preeclampsia and Therapeutic Approaches Targeting the Placenta.

Preeclampsia (PE) is a serious pregnancy complication, affecting about 5-7% of pregnancies worldwide and is characterized by hypertension and damage to multiple maternal organs, primarily the liver and kidneys. PE usually begins after 20 weeks' gestation and, if left untreated, can lead to serious complications and lifelong disabilities-even death-in both the mother and the infant. As delivery is the only cure for the disease, treatment is primarily focused on the management of blood pressure and other clinical symptoms. The pathogenesis of PE is still not clear. Abnormal spiral artery remodeling, placental ischemia and a resulting increase in the circulating levels of vascular endothelial growth factor receptor-1 (VEGFR-1), also called soluble fms-like tyrosine kinase-1 (sFlt-1), are believed to be among the primary pathologies associated with PE. sFlt-1 is produced mainly in the placenta during pregnancy and acts as a decoy receptor, binding to free VEGF (VEGF-A) and placental growth factor (PlGF), resulting in the decreased bioavailability of each to target cells. Despite the pathogenic effects of increased sFlt-1 on the maternal vasculature, recent studies from our laboratory and others have strongly indicated that the increase in sFlt-1 in PE may fulfill critical protective functions in preeclamptic pregnancies. Thus, further studies on the roles of sFlt-1 in normal and preeclamptic pregnancies are warranted for the development of therapeutic strategies targeting VEGF signaling for the treatment of PE. Another impediment to the treatment of PE is the lack of suitable methods for delivery of cargo to placental cells, as PE is believed to be of placental origin and most available therapies for PE adversely impact both the mother and the fetus. The present review discusses the pathogenesis of PE, the complex role of sFlt-1 in maternal disease and fetal protection, and the recently developed placenta-targeted drug delivery system for the potential treatment of PE with candidate therapeutic agents.

Suitable reference gene for quantitative real-time PCR analysis of gene expression in gonadal tissues of minnow Puntius sophore under high-temperature stress.

BACKGROUND: High ambient temperature is known to affect fish gonadal development and physiology in a variety of ways depending on the severity and duration of exposure; however, the underlying molecular mechanisms are poorly understood. Gonadal gene expression influence the gonadal development, physiology and the quality of egg/sperm produced in teleosts and the mechanistic understanding of spatio-temporal changes in the gonadal gene expression could be instrumental in controlling the fate of egg/sperm and the quality of seed produced. Real time-quantititative polymerase chain reaction (RT-qCR), is a high throughput, sensitive and reproducible methodology used for understanding gene expression patterns by measuring the relative abundance of mRNA transcripts. However, its accuracy relies upon a suitable reference gene whose expression levels remain stable across various experimental conditions. In the present study, we evaluated the suitability of ten potential reference genes to be used as internal controls in RT-qPCR analysis in gonadal tissues (ovary and testis) of minnow Puntius sophore exposed to high temperature stress for different time periods (7 days, 60 days). Expression analysis of ten different constitutively expressed genes viz. 18S ribosomal RNA (18S rRNA), beta actin (ßactin), ß-2 microglobulin (b2mg), eukaryotic elongation factor-1 (eef1), glyceraldehyde-3phosphate dehydrogenase (gapdh), glucose-6-phosphate dehydrogenase (g6pd), ribosomal binding protein L13 (rpl13), tubulin (tub), tata box binding protein (tbp), ubiquitin (ubi) was carried out by using RT-qPCR and the stability in their expressions were evaluated by using four different algorithms; namely, delta Ct, BestKeeper, geNorm and NormFinder. RESULTS: In ovary, eef1 was found to be the most suitable reference gene in all the algorithms used. In testis, b2mg was found to be the most suitable reference gene in delta Ct, BestKeeper, NormFinder analysis while tbp and eef1 were found to be the most suitable reference genes in geNorm analysis. CONCLUSIONS: In conclusion, eef1 and b2mg were found to be the most suitable reference genes in ovary and testis, respectively, of Puntius sophore exposed to high temperature stress, and could be used as internal controls for gene expression analysis in gonadal tissues of Puntius sophore.