Quantitative biophysical metrics for rapid evaluation of ovarian cancer metastatic potential

Ovarian cancer is routinely diagnosed long after the disease has metastasized through the fibrous submesothelium. Despite extensive research in the field linking ovarian cancer progression to increasingly poor prognosis, there are currently no validated cellular markers or hallmarks of ovarian cancer that can predict metastatic potential. To discern disease progression across a syngeneic mouse ovarian cancer progression model, here we fabricated extracellular matrix mimicking suspended fiber networks: cross-hatches of mismatch diameters for studying protrusion dynamics, aligned same diameter networks of varying interfiber spacing for studying migration, and aligned nanonets for measuring cell forces. We found that migration correlated with disease while a force-disease biphasic relationship exhibited F-actin stress fiber network dependence. However, unique to suspended fibers, coiling occurring at the tips of protrusions and not the length or breadth of protrusions displayed the strongest correlation with metastatic potential. To confirm that our findings were more broadly applicable beyond the mouse model, we repeated our studies in human ovarian cancer cell lines and found that the biophysical trends were consistent with our mouse model results. Altogether, we report complementary high throughput and high content biophysical metrics capable of identifying ovarian cancer metastatic potential on a timescale of hours.     

A non-rotational, computer-controlled suspension bioreactor for expansion of umbilical cord blood mononuclear cells

The proliferation and differentiation characteristics of umbilical cord blood mononuclear cells were examined in a non-rotational suspension bioreactor with a fishtail mixer. The system consisted of a glass vessel, a mixer that moved vertically, a data acquisition and control system to continuously monitor pH, temperature and dissolved O₂. The bioreactor provided superior expansion of total HSCs and not total cell number, as well as expression of stemness-related genes which followed with increasing in number of colony-forming cells during 14 days of culture compared to T -lask culture. Vertical agitation thus reduces the total cell number, which may be related to increased shear stress, but has no effect on HSC function.     

Genetic counseling in carriers of reciprocal translocations involving two autosomes

One of the main genetic causes involve in the pathogenesis of recurrent abortion is parental chromosomal abnormalities. The central concept in genetic counseling with such families is to estimate the probability of recurrence of unfavorable pregnancy outcomes. The main questions that consultants usually ask are: Why did this happen? What is the risk to be done again?Our cases were two families with repeated miscarriage. The pedigrees were drawn, the chromosomes of couples were studied, and estimation for recurrent risk was done. We tried to answer those two main questions and clear the results for them.Parental chromosome abnormalities were founded after karyotyping with GTG technique at 450 band resolution, revealing 46 chromosomes with balanced translocation of autosomes in one of the partner in both families. Recurrent risk was estimated as “high” for their future pregnancies in each family.Couples in which one partner is the carrier of such balanced translocation have increased risks of infertility, recurrent abortion, and delivery of chromosomally abnormal offspring. Genetic counseling of such couples, therefore, presents a unique challenge and should be considered in dealing with such families.     

“Bind,cleave and leave”: multiple turnover catalysis of RNA cleavage by bulge–loop inducing supramolecular conjugates

Antisense sequence-specific knockdown of pathogenic RNA offers opportunities to find new solutions for therapeutic treatments. However, to gain a desired therapeutic effect, the multiple turnover catalysis is critical to inactivate many copies of emerging RNA sequences, which is difficult to achieve without sacrificing the sequence-specificity of cleavage. Here, engineering two or three catalytic peptides into the bulge–loop inducing molecular framework of antisense oligonucleotides achieved catalytic turnover of targeted RNA. Different supramolecular configurations revealed that cleavage of the RNA backbone upon sequence-specific hybridization with the catalyst accelerated with increase in the number of catalytic guanidinium groups, with almost complete demolition of target RNA in 24 h. Multiple sequence-specific cuts at different locations within and around the bulge–loop facilitated release of the catalyst for subsequent attacks of at least 10 further RNA substrate copies, such that delivery of only a few catalytic molecules could be sufficient to maintain knockdown of typical RNA copy numbers. We have developed fluorescent assay and kinetic simulation tools to characterise how the limited availability of different targets and catalysts had restrained catalytic reaction progress considerably, and to inform how to accelerate the catalytic destruction of shorter linear and larger RNAs even further.     

The Role of 5-HT1A Receptors and Neuronal Nitric Oxide Synthase in a Seizur Induced Kindling Model in Rats

Neurochemical Research - Dentate gyrus (DG) has a high density of 5-HT1A receptors. It has neural nitric oxide synthase (nNOS), which is involved in neural excitability. The purpose of this study...     

Molecular investigation of association between common IL-6 polymorphism with cytomegalovirus (CMV) infection and recurrent miscarriage in Iranian women

Molecular Biology Reports - Recurrent pregnancy loss (RPL) is described as two or more spontaneous abortions. To date, scientists in various fields of knowledge, such as genetics, endocrinology,...     

Vitamin C counteracts miR-302/367-induced reprogramming of human breast cancer cells and restores their invasive and proliferative capacity

Epigenetic reprogramming by embryonic stem cell-specific miR-302/367 cluster has shown some tumor suppressive effects in cancer cells of different tissues such as skin, colon, and cervix. Vitamin C has been known as a reprogramming enhancer of human and mouse somatic cells. In this study, first we aimed to investigate whether exogenous induction of miR-302/367 in breast cancer cells shows the same tumor suppressive effects previously observed in other cancer cells lines, and whether vitamin C can enhance reprogramming of breast cancer cells and also improve the tumor suppressive function of miR-302/367 cluster. Overexpression of miR-302/367 cluster in MDA-MB-231 and SK-BR-3 breast cancer cells upregulated expression of miR-302/367 members and also some core pluripotency factors including OCT4A, SOX2 and NANOG, induced mesenchymal to epithelial transition, suppressed invasion, proliferation, and induced apoptosis in the both cell lines. However, treatment of the miR-302/367 transfected cells with vitamin C suppressed the expression of pluripotency factors and augmented the tumorigenicity of the breast cancer cells by restoring their proliferative and invasive capacity and compromising the apoptotic effect of miR-302/367. Supplementing the culture medium with vitamin C downregulated expression of TET1 gene which seems to be the reason behind the negative impact of vitamin C on the reprogramming efficiency of miR-302/367 cluster and its anti-tumor effects. Therefore application of vitamin C may not always serve as a reprogramming enhancer depending on its switching function on TET1. This phenomenon should be carefully considered when considering a reprogramming strategy for tumor suppression.     

Machine Learning Based Classification of Microsatellite Variation: An Effective Approach for Phylogeographic Characterization of Olive Populations

Finding efficient analytical techniques is overwhelmingly turning into a bottleneck for the effectiveness of large biological data. Machine learning offers a novel and powerful tool to advance classification and modeling solutions in molecular biology. However, these methods have been less frequently used with empirical population genetics data. In this study, we developed a new combined approach of data analysis using microsatellite marker data from our previous studies of olive populations using machine learning algorithms. Herein, 267 olive accessions of various origins including 21 reference cultivars, 132 local ecotypes, and 37 wild olive specimens from the Iranian plateau, together with 77 of the most represented Mediterranean varieties were investigated using a finely selected panel of 11 microsatellite markers. We organized data in two ‘4-targeted’ and ‘16-targeted’ experiments. A strategy of assaying different machine based analyses (i.e. data cleaning, feature selection, and machine learning classification) was devised to identify the most informative loci and the most diagnostic alleles to represent the population and the geography of each olive accession. These analyses revealed microsatellite markers with the highest differentiating capacity and proved efficiency for our method of clustering olive accessions to reflect upon their regions of origin. A distinguished highlight of this study was the discovery of the best combination of markers for better differentiating of populations via machine learning models, which can be exploited to distinguish among other biological populations.