Age-specific reference intervals for routine biochemical parameters in healthy neonates,infants, and young children in Iran

Age and sex need to be considered in the establishment of reference intervals (RIs), especially in early life when there are dynamic physiological changes. Since data for important biomarkers in healthy neonates and infants are limited, particularly in Iranian populations, we have determined age-specific RIs for 7 laboratory biochemical parameters. This cross-sectional study comprised a total of 344 paediatric participants (males: 158, females: 186) between the ages of 3 days and 30 months (mean age: 12.91 ± 7.15 months). Serum levels of creatinine, urea, uric acid, calcium, phosphate, vitamin D and high-sensitivity C-reactive protein (hs-CRP) were measured using an Alpha classic-AT plus auto-analyser. We determined age-specific RIs using CLSI Ep28-A3 and C28-A3 guidelines. No sex partitioning was required for any of the biomarkers. Age partitioning was required for kidney function tests and phosphate. The serum concentration of urea and creatinine increased with age, while phosphate and uric acid decreased with age. Age partitioning was not required for serum calcium, vitamin D, and hs-CRP, which remained relatively constant throughout the age range. Age-specific RIs for 7 routine biochemical markers were determined to address critical gaps in RIs in early life to help improve clinical interpretation of blood test results in young children, including neonates. Established age partitions demonstrate the biochemical changes that take place during child growth and development. These novel data will ultimately better disease management in the Iranian paediatric population and can be of value to clinical and hospital laboratories with similar populations.     

Sexual size dimorphism in Darevskia raddei (Sauria: Lacertidae) from northwestern Iran

We examined sexual size dimorphism of the rock-dwelling lizard Darevskia raddei (Boettger, 1892) with the help of 30 specimens that were provided from various sources. Eleven metric and seven meristic features were examined. Seven characters (gulars, length of basal tail, femoral pores, length of head, width of head, length of fore limb and length of hind limb) were identified as dimorphic between the two sexes. Some of these characters have important roles in copulation for males, especially the hind limb and the tail base. The number of femoral pores is important in the release of signal components because females release these components to attract males during the mating season. The length of the hind limb as locomotor performance plays an important role during mating, so that the male can grasp the female and adopt the correct position during copulation.     

Hypermethylation of the CpG Island Near the G4C2 Repeat in ALS with a C9orf72 Expansion

The G₄C₂ repeat expansion in C9orf72 is the most common known cause of amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD). We tested the hypothesis that the repeat expansion causes aberrant CpG methylation near the G₄C₂ repeat, which could be responsible for the downregulation of gene expression. We investigated the CpG methylation profile by two methods using genomic DNA from the blood of individuals with ALS (37 expansion carriers and 64 noncarriers), normal controls (n = 76), and family members of 7 ALS probands with the expansion. We report that hypermethylation of the CpG island 5′ of the G₄C₂ repeat is associated with the presence of the expansion (p < 0.0001). A higher degree of methylation was significantly correlated with a shorter disease duration (p < 0.01), associated with familial ALS (p = 0.009) and segregated with the expansion in 7 investigated families. Notably, we did not detect methylation for either normal or intermediate alleles (up to 43 repeats), bringing to question the current cutoff of 30 repeats for pathological alleles. Our study raises several important questions for the future investigation of large data sets, such as whether the degree of methylation corresponds to clinical presentation (ALS versus FTLD).     

Fractionation of Protein Hydrolysates of Fish Waste Using Membrane Ultrafiltration: Investigation of Antibacterial and Antioxidant Activities

Probiotics and Antimicrobial Proteins - In this study, yellowfin tuna (Thunnus albacores) viscera were hydrolyzed with protamex to obtain hydrolysate that is separated by a membrane ultrafiltration...     

Scalable optimal Bayesian classification of single-cell trajectories under regulatory model uncertainty

Background

Biological networks describes the mechanisms which govern cellular functions. Temporal networks show how these networks evolve over time. Studying the temporal progression of network topologies is of utmost importance since it uncovers how a network evolves and how it resists to external stimuli and internal variations. Two temporal networks have co-evolving subnetworks if the evolving topologies of these subnetworks remain similar to each other as the network topology evolves over a period of time. In this paper, we consider the problem of identifying co-evolving subnetworks given a pair of temporal networks, which aim to capture the evolution of molecules and their interactions over time. Although this problem shares some characteristics of the well-known network alignment problems, it differs from existing network alignment formulations as it seeks a mapping of the two network topologies that is invariant to temporal evolution of the given networks. This is a computationally challenging problem as it requires capturing not only similar topologies between two networks but also their similar evolution patterns.

Results

We present an efficient algorithm, Tempo, for solving identifying co-evolving subnetworks with two given temporal networks. We formally prove the correctness of our method. We experimentally demonstrate that Tempo scales efficiently with the size of network as well as the number of time points, and generates statistically significant alignments—even when evolution rates of given networks are high. Our results on a human aging dataset demonstrate that Tempo identifies novel genes contributing to the progression of Alzheimer’s, Huntington’s and Type II diabetes, while existing methods fail to do so.

Conclusions

Studying temporal networks in general and human aging specifically using Tempo enables us to identify age related genes from non age related genes successfully. More importantly, Tempo takes the network alignment problem one huge step forward by moving beyond the classical static network models.