Human embryonic stem cell-derived neural precursor transplants in collagen scaffolds promote recovery in injured rat spinal cord

Background aimsSeveral studies have reported functional improvement after transplantation of in vivo-derived neural progenitor cells (NPC) into injured spinal cord. However, the potential of human embryonic stem cell-derived NPC (hESC-NPC) as a tool for cell replacement of spinal cord injury (SCI) should be considered.MethodsWe report on the generation of NPC as neural-like tubes in adherent and feeder-free hESC using a defined media supplemented with growth factors, and their transplantation in collagen scaffolds in adult rats subjected to midline lateral hemisection SCI.ResultshESC-NPC were highly expressed molecular features of NPC such as Nestin, Sox1 and Pax6. Furthermore, these cells exhibited the multipotential characteristic of differentiating into neurons and glials in vitro. Implantation of xenografted hESC-NPC into the spinal cord with collagen scaffold improved the recovery of hindlimb locomotor function and sensory responses in an adult rat model of SCI. Analysis of transplanted cells showed migration toward the spinal cord and both neural and glial differentiation in vivo.ConclusionsThese findings show that transplantation of hESC-NPC in collagen scaffolds into an injured spinal cord may provide a new approach to SCI.     

High prevalence of the metabolic syndrome in Iranian adolescents

Objective : No evidence exists regarding the prevalence of the metabolic syndrome in adolescents in Middle Eastern countries. We aimed to evaluate the prevalence of the metabolic syndrome in a representative sample of Iranian adolescents. Research Methods and Procedures : Anthropometry, biochemical measurements, and blood pressure were assessed in a population‐based cross‐sectional study of 3036 Iranian adolescents (1413 boys and 1623 girls) 10 to 19 years of age. Metabolic syndrome was defined according to modified Adult Treatment Panel III definition. Overweight (≥95th percentile) and at risk for overweight (≥85th to <95th percentile) was defined based on the standardized percentile curves of BMI suggested for Iranian adolescents. Results : The prevalence of the metabolic syndrome was 10.1% (95% confidence interval: 9.0 to 11.1) among Iranian adolescents (boys: 10.3%, 8.6 to 11.8; girls: 9.9%, 8.4 to 11.3). Overall, low serum high‐density lipoprotein‐cholesterol and high serum triglycerides were the most common components of the metabolic syndrome (42.8% and 37.5%, respectively). Overweight subjects had the highest proportion of metabolic syndrome compared with those at risk for overweight and those with normal weight (boys: 41.1% vs. 11.4% and 3.0%, respectively, p < 0.01; girls: 43% vs. 15.2% and 5.0%, respectively, p < 0.01). Discussion : This study provides evidence showing a high prevalence of the metabolic syndrome in Iranian adolescents, particularly among overweight adolescents.     

Short-term changes in prostacyclin secretory profile of irradiated rat cervical spinal cord

Prostaglandins changes in radiation myelopathy (RM) have been previously reported. In the present study, we decided to determine the profile of Prostacyclin (PGI2) content in irradiated rat cervical cord. Wistar rats were irradiated with doses of 2,4,6,15,25 and 30 Gy of X-rays. After 24 h, 2 and 13 weeks post-irradiation, samples of spinal cord were prepared for evaluation of PGI2 and histopathologic changes. Prostacyclin content was determined by quantification of 6-keto-prostaglandin-F1alpha (prostacyclin major metabolite). Irradiated segments of spinal cord were stained routinely for histological studies. Results of irradiated were compared to control groups. Average ratio values of 6-keto-PG-F1alpha for doses of 2-30 Gy were between 67.5% and 107%, 65.41% and 100.54%, and 62.20% and 98.89% for 24 h, 2 and 13 weeks post-irradiation, respectively. Histopathological studies showed marked gliosis and vascularities in irradiated specimens. PGI2 bimodal secretory profile was observed along with histopathological changes in this study. Our results can further emphasize on the role of PGI2 in RM.     

An investigation on the expression of miRNAs including miR-144 and miR-34a in plasma samples of RET-positive and RET-negative medullar thyroid carcinoma patients

Medullary thyroid carcinoma (MTC) is a scarce cancerous disease, originating from parafollicular C cells of the thyroid gland. MTC can be manifested as an aggressive carcinoma with metastasis, especially in sporadic forms. Mutations of the rearranged during transfection (RET) proto-oncogene occurs in all hereditary and a few somatic MTCs, so detection of RET mutations is needed for prompt and appropriate treatment. MicroRNAs (miRNAs) are noncoding regulatory RNAs. Extensive studies have done in progress or suppression of several types of cancers such as MTCs with the remarkable application as prognostic markers. Of the effective miRNAs in cancers, miR-144 and miR-34 were evaluated in our study. Blood samples of 25 RET-positive and 25 RET-negative blood samples of patients with MTC were evaluated for these miRNAs, using quantitative real-time polymerase chain reaction (RT-qPCR). Analysis of the results was performed by the 2 ^−ΔΔCt method, showing that miR-144 and miR-34a expression had a relative increase in patients with MTC compared with normal control samples and also in RET positives versus RET negatives. We recruited 50 out of 350 MTC plasma samples (27 female and 23 male) which were selected based on RET mutation in exon 11 (25 RET-positive and 25 RET-negative), with a mean ± SD age of 37.04 ± 1.74 years. Receiver operating characteristic (ROC) curve analysis was done to investigate the prognostic value of these miRNAs; although, they showed no significant prognostic value as MTC biomarkers in plasma samples. In conclusion, miRNAs can be used as biomarkers of cancers such as MTC; however, more studies are needed to find the best candidate miRNAs for the diagnosis of cancers.     

Mixed Mating System Are Regulated by Fecundity in Shorea curtisii (Dipterocarpaceae) as Revealed by Comparison under Different Pollen Limited Conditions

The maintenance of mixed mating was studied in Shorea curtisii, a dominant and widely distributed dipterocarp species in Southeast Asia. Paternity and hierarchical Bayesian analyses were used to estimate the parameters of pollen dispersal kernel, male fecundity and self-pollen affinity. We hypothesized that partial self incompatibility and/or inbreeding depression reduce the number of selfed seeds if the mother trees receive sufficient pollen, whereas reproductive assurance increases the numbers of selfed seeds under low amounts of pollen. Comparison of estimated parameters of self-pollen affinity between high density undisturbed and low density selectively logged forests indicated that self-pollen was selectively excluded from mating in the former, probably due to partial self incompatibility or inbreeding depression until seed maturation. By estimating the self-pollen affinity of each mother tree in both forests, mother trees with higher amount of self-pollen indicated significance of self-pollen affinity with negative estimated value. The exclusion of self-fertilization and/or inbreeding depression during seed maturation occurred in the mother trees with large female fecundity, whereas reproductive assurance increased self-fertilization in the mother trees with lower female fecundity.     

Factors Affecting Gender Differences in the Association between Health-Related Quality of Life and Metabolic Syndrome Components: Tehran Lipid and Glucose Study

Objective

Using structural equation modeling, this study is one of the first efforts aimed at assessing influential factors causing gender differences in the association between health-related quality of life (HRQoL) and metabolic syndrome.

Methods

A sample of 950 adults, from Tehran Lipid and Glucose Study were recruited for this cross sectional study in 2005–2007. Health-related quality of life was assessed using the Iranian version of SF-36. Metabolic syndrome components (MetSCs) and physical and mental HRQoL were considered as continuous latent constructs explaining the variances of their observed components. Structural equation modeling was performed to examine the association between the constructs of MetSCs and the physical and mental HRQoL within the two gender groups.

Results

Based on the primary hypothesis, MetSCs and HRQoL were fitted in a model. The negative effect of MetSCs on HRQoL was found to be significant only in the physical domain and only in women. The proportion of all the cardio-metabolic risk factors as well as subscales of physical HRQoL that have been explained via the two constructs of MetSCs and HRQoL, respectively, were significantly higher in women. Physical activity in both men (β = 3.19, p<0.05) and women (β = 3.94, p<0.05), age (β = -3.28, p<0.05), education (β = 2.63, p<0.05) only in women and smoking (β = 2.28, p<0.05) just in men, directly affected physical HRQoL. Regarding the mental domain, physical activity (β = 3.37, p<0.05) and marital status (β = 3.44, p<0.05) in women and age (β = 2.01, p<0.05) in men were direct effective factors. Age and education in women as well as smoking in men indirectly affected physical HRQoL via MetSCs.

Conclusion

Gender differences in the association between MetSCs and physical HRQoL could mostly be attributed to the different structures of both MetSCs and physical HRQoL constructs in men and women. Age and smoking are the most important socio-behavioral factors which could affect this gender-specific association in the mental domain.     

Identifying Cell Types from Spatially Referenced Single-Cell Expression Datasets

Complex tissues, such as the brain, are composed of multiple different cell types, each of which have distinct and important roles, for example in neural function. Moreover, it has recently been appreciated that the cells that make up these sub-cell types themselves harbour significant cell-to-cell heterogeneity, in particular at the level of gene expression. The ability to study this heterogeneity has been revolutionised by advances in experimental technology, such as Wholemount in Situ Hybridizations (WiSH) and single-cell RNA-sequencing. Consequently, it is now possible to study gene expression levels in thousands of cells from the same tissue type. After generating such data one of the key goals is to cluster the cells into groups that correspond to both known and putatively novel cell types. Whilst many clustering algorithms exist, they are typically unable to incorporate information about the spatial dependence between cells within the tissue under study. When such information exists it provides important insights that should be directly included in the clustering scheme. To this end we have developed a clustering method that uses a Hidden Markov Random Field (HMRF) model to exploit both quantitative measures of expression and spatial information. To accurately reflect the underlying biology, we extend current HMRF approaches by allowing the degree of spatial coherency to differ between clusters. We demonstrate the utility of our method using simulated data before applying it to cluster single cell gene expression data generated by applying WiSH to study expression patterns in the brain of the marine annelid Platynereis dumereilii. Our approach allows known cell types to be identified as well as revealing new, previously unexplored cell types within the brain of this important model system.