Biomarkers of metabolic disorders and neurobehavioral diseases in a PCB- exposed population: What we learned and the implications for future research.

Polychlorinated biphenyls (PCBs) are one of the original twelve classes of toxic chemicals covered by the Stockholm Convention on Persistent Organic Pollutants (POP), an international environmental treaty signed in 2001. PCBs are present in the environment as mixtures of multiple isomers at different degree of chlorination. These compounds are manmade and possess useful industrial properties including extreme longevity under harsh conditions, heat absorbance, and the ability to form an oily liquid at room temperature that is useful for electrical utilities and in other industrial applications. They have been widely used for a wide range of industrial purposes over the decades. Despite a ban in production in 1979 in the US and many other countries, they remain persistent and ubiquitous in environment as contaminants due to their improper disposal. Humans, independent of where they live, are therefore exposed to PCBs, which are routinely found in random surveys of human and animal tissues. The prolonged exposures to PCBs have been associated with the development of different diseases and disorders, and they are classified as endocrine disruptors. Due to its ability to interact with thyroid hormone, metabolism and function, they are thought to be implicated in the global rise of obesity diabetes, and their potential toxicity for neurodevelopment and disorders, an example of gene by environmental interaction (GxE). The current review is primarily intended to summarize the evidence for the association of PCB exposures with increased risks for metabolic dysfunctions and neurobehavioral disorders. In particular, we present evidence of gene expression alterations in PCB-exposed populations to construct the underlying pathways that may lead to those diseases and disorders in course of life. We conclude the review with future perspectives on biomarker-based research to identify susceptible individuals and populations.

Transcriptional Profiling and Biological Pathway(s) Analysis of Type 2 Diabetes Mellitus in a Pakistani Population.

The epidemic of type 2 diabetes mellitus (T2DM) is an important global health concern. Our earlier epidemiological investigation in Pakistan prompted us to conduct a molecular investigation to decipher the differential genetic pathways of this health condition in relation to non-diabetic controls. Our microarray studies of global gene expression were conducted on the Affymetrix platform using Human Genome U133 Plus 2.0 Array along with Ingenuity Pathway Analysis (IPA) to associate the affected genes with their canonical pathways. High-throughput qRT-PCR TaqMan Low Density Array (TLDA) was performed to validate the selected differentially expressed genes of our interest, viz., ARNT, LEPR, MYC, RRAD, CYP2D6, TP53, APOC1, APOC2, CYP1B1, SLC2A13, and SLC33A1 using a small population validation sample (n = 15 cases and their corresponding matched controls). Overall, our small pilot study revealed a discrete gene expression profile in cases compared to controls. The disease pathways included: Insulin Receptor Signaling, Type II Diabetes Mellitus Signaling, Apoptosis Signaling, Aryl Hydrocarbon Receptor Signaling, p53 Signaling, Mitochondrial Dysfunction, Chronic Myeloid Leukemia Signaling, Parkinson's Signaling, Molecular Mechanism of Cancer, and Cell Cycle G1/S Checkpoint Regulation, GABA Receptor Signaling, Neuroinflammation Signaling Pathway, Dopamine Receptor Signaling, Sirtuin Signaling Pathway, Oxidative Phosphorylation, LXR/RXR Activation, and Mitochondrial Dysfunction, strongly consistent with the evidence from epidemiological studies. These gene fingerprints could lead to the development of biomarkers for the identification of subgroups at high risk for future disease well ahead of time, before the actual disease becomes visible.

Capturing 3D large-strain Euler-bending filament dynamics in fibrous media simulations; sample case of compression collapse in dendritic actin network.

Cytoskeletal networks to transmission towers are comprised of slender elements. Slender filaments bend and buckle more easily than stretch. Therefore a deforming network is expected to exhaust all possible bending-based modes before engaging filament stretch. While the large-strain bending critically determines fibrous-media response, simulations use small-strain and jointed approximations. At low resolution, these approximations inflate bending resistance and delay buckling onset. The proposed string-of-continuous-beams (SOCB) approach captures 3D nonlinear Euler bending of filaments with high fidelity at low cost. Bending geometry (i.e. angles and its differentials) is solved as primary variables, to fit a 5th order polynomial of the contour angle. Displacement, solved simultaneously as length conservation, is predicted with C3 and C6 smoothness between and within segments, using only 2 nodes. In the chosen analysis frame, in-plane and out-plane moments can be decoupled for arbitrarily-curved segments. Complex crosslink force-transfers can be specified. Simulations show that when a daughter branch is appended, the buckling resistance of a filament changes from linear to nonlinear before reversible collapse. An actin outcrop with 8 generations of mother-daughter branching produced the linear, nonlinear, and collapse regimes observed in compression experiments. 'Collapse' was a redistribution of outcrop forces following the buckling of few strands.